Increase, Reactive oxygen species

60-35-5

DLFVBJFMPXGRIB-UHFFFAOYSA-N

Acetamide

Acetamid acetamida Acetic acid amide Acetimidic acid Ethanamide Ethanimidic acid Methanecarboxamide NSC 25945

DTXSID7020005

103-90-2

RZVAJINKPMORJF-UHFFFAOYSA-N

Acetaminophen

4-Acetamidophenol APAP Paracetamol 4-hydroxyacetanilide Acetamide, N-(4-hydroxyphenyl)- 4-(Acetylamino)phenol 4-(N-Acetylamino)phenol 4-Acetaminophenol 4'-Hydroxyacetanilide Abensanil Acetagesic Acetalgin ACETAMIDE, N-(4-HYDROXYPHENYL) Acetaminofen Acetanilide, 4'-hydroxy- ACETANILIDE, 4-HYDROXY- Algotropyl Alvedon Anaflon Apamide Banesin Ben-u-ron Bickie-mol Biocetamol Cetadol Citramon P Claratal Clixodyne Dafalgan Daphalgan Dial-a-gesic Disprol Doliprane Dolprone Dymadon Efferalgan Endophy Febrilex Febrilix Febro-Gesic Febrolin Fepanil Finimal Gattaphen T Gelocatil Gutte Enteric Homoolan Jin Gang Lestemp Liquagesic Lonarid Lyteca Syrup Minoset Momentum N-(4-Hydroxyphenyl)acetamide N-Acetyl-4-aminophenol N-Acetyl-4-hydroxyaniline N-Acetyl-p-aminophenol Napafen Naprinol Nobedon NSC 109028 NSC 3991 Ortensan p-(Acetylamino)phenol p-Aceaminophenol Pacemol p-Acetamidophenol p-Acetoaminophen P-ACETYLAMINOPHENOL Paldesic panadeine Panadol Panadol Actifast Panadol Extend Panaleve Panasorb Panodil Paracetamol DC Paracetamole Parageniol Paramol Paraspen Parelan Pasolind N Perfalgan Phenaphen Phendon p-Hydroxyacetanilide Prodafalgan Puerxitong Pyrinazine Resfenol Resprin Rhodapop NCR Salzone Tabalgin Tachipirina Tempanal Tralgon Tylenol TylolHot Valadol Valgesic Vermidon Vick Pyrena

DTXSID2020006

968-81-0

VGZSUPCWNCWDAN-UHFFFAOYSA-N

Acetohexamide

Benzenesulfonamide, 4-acetyl-N-[(cyclohexylamino)carbonyl]- 1-(p-Acetylbenzenesulfonyl)-3-cyclohexylurea 1-[(p-Acetylphenyl)sulfonyl]-3-cyclohexylurea Acetohexamid acetohexamida Dimelin Dimelor Dymelor Gamadiabet Hypoglicil Metaglucina Minoral N-(p-Acetylphenylsulfonyl)-N'-cyclohexylurea Ordimel Tsiklamid Urea, 1-[(p-acetylphenyl)sulfonyl]-3-cyclohexyl-

DTXSID7020007

67-66-3

HEDRZPFGACZZDS-UHFFFAOYSA-N

Chloroform

Trichloromethane Methane, trichloro- CARBON TRICHLORIDE Chloroforme cloroformo Formyl trichloride Methane trichloride Methane,trichloro- NSC 77361 Trichloroform UN 1888

DTXSID1020306

110-00-9

YLQBMQCUIZJEEH-UHFFFAOYSA-N

Furan

Divinylene oxide furanne Furfuran Oxacyclopentadiene Tetrole UN 2389

DTXSID6020646

7429-90-5

XAGFODPZIPBFFR-UHFFFAOYSA-N

AZDRQVAHHNSJOQ-UHFFFAOYSA-N

Aluminum

Aisin Metal Fiber Al 050P-H24 ALC Fine Alcan XI 1391 Almi-Paste SSP 303AR Aloxal 3010 Alpaste 00-0506 Alpaste 0100M Alpaste 0100MA Alpaste 0100M-C Alpaste 0200M Alpaste 0200T Alpaste 0230M Alpaste 0230T Alpaste 0241M Alpaste 0300M Alpaste 0500M Alpaste 0539X Alpaste 0620MS Alpaste 0625TS Alpaste 0638-70C Alpaste 0700M Alpaste 0780M Alpaste 0900M Alpaste 100M Alpaste 100MS Alpaste 100MSR Alpaste 1100M Alpaste 1100MA Alpaste 1100N Alpaste 1100NA Alpaste 1109MA Alpaste 1109MC Alpaste 1200M Alpaste 1200T Alpaste 1260MS Alpaste 1500MA Alpaste 1700NL Alpaste 1810YL Alpaste 1830YL Alpaste 1900M Alpaste 1900XS Alpaste 1950M Alpaste 1950N Alpaste 210N Alpaste 2172EA Alpaste 2173 Alpaste 240T Alpaste 241M Alpaste 417 Alpaste 46-046 Alpaste 4-621 Alpaste 4919 Alpaste 50-63 Alpaste 50-635 Alpaste 51-148B Alpaste 51-231 Alpaste 5205N Alpaste 5207N Alpaste 52-509 Alpaste 52-568 Alpaste 5301N Alpaste 5302N Alpaste 53-119 Alpaste 5422NS Alpaste 54-452 Alpaste 54-497 Alpaste 54-542 Alpaste 55-516 Alpaste 55-519 Alpaste 55-574 Alpaste 5620NS Alpaste 5630NS Alpaste 5640NS Alpaste 56-501 Alpaste 5650NS Alpaste 5653NS Alpaste 5654NS Alpaste 5680N Alpaste 5680NS Alpaste 60-600 Alpaste 60-760 Alpaste 60-768 Alpaste 62-356 Alpaste 6340NS Alpaste 6370NS Alpaste 6390NS Alpaste 640NS Alpaste 65-388 Alpaste 66NLB Alpaste 710N Alpaste 7130N Alpaste 7160N Alpaste 7160NS Alpaste 725N Alpaste 740NS Alpaste 7430NS Alpaste 7580NS Alpaste 7620NS Alpaste 7640NS Alpaste 7670M Alpaste 7670NS Alpaste 7675NS Alpaste 7679NS Alpaste 7680N Alpaste 7680NS Alpaste 76840NS Alpaste 7730N Alpaste 7770N Alpaste 7830N Alpaste 8004 Alpaste 8080N Alpaste 8260NAR Alpaste 891K Alpaste 91-0562 Alpaste 92-0592 Alpaste 93-0595 Alpaste 93-0647 Alpaste 94-2315 Alpaste 95-0570 Alpaste 96-0635 Alpaste 96-2104 Alpaste 97-0510 Alpaste 97-0534 Alpaste AW 520B Alpaste AW 612 Alpaste AW 9800 Alpaste F 795 Alpaste FM 7680K Alpaste FX 440 Alpaste FX 910 Alpaste FZ 0534 Alpaste FZU 40C Alpaste G Alpaste HR 8801 Alpaste HS 2 Alpaste J Alpaste K 9800 Alpaste MC 666 Alpaste MC 707 Alpaste MF 20 Alpaste MG 01 Alpaste MG 1000 Alpaste MG 1300 Alpaste MG 500 Alpaste MG 600 Alpaste MH 6601 Alpaste MH 8801 Alpaste MH 9901 Alpaste MR 7000 Alpaste MR 9000 Alpaste MS 630 Alpaste N 1700NL Alpaste NS 7670 Alpaste O 100N Alpaste O 2130 Alpaste O 300M Alpaste P 0100 Alpaste P 1950 Alpaste S Alpaste SAP 110 Alpaste SAP 414P Alpaste SAP 550N Alpaste SCR 5070 Alpaste TCR 2020 Alpaste TCR 2060 Alpaste TCR 2070 Alpaste TCR 3010 Alpaste TCR 3030 Alpaste TCR 3040 Alpaste TCR 3130 Alpaste TD 200T Alpaste UF 500 Alpaste WB 0230 Alpaste WD 500 Alpaste WJP-U 75C Alpaste WX 0630 Alpaste WX 7830 Alpaste WXA 7640 Alpaste WXM 0630 Alpaste WXM 0650 Alpaste WXM 0660 Alpaste WXM 1415 Alpaste WXM 1440 Alpaste WXM 5422 Alpaste WXM 760b Alpaste WXM 7640 Alpaste WXM 7675 Alpaste WXM-T 60B Alpaste WXM-U 75 Alpaste WXM-U 75C Altop X Aluchrome Ultrafin Super Alumat 1600 Alumet H 30 aluminio Aluminium Aluminium Flake Aluminum 27 Aluminum atom Aluminum element Aluminum Flake PCF 7620 Aluminum granules ALUMINUM METAL/GRANULE ALUMINUM PASTE ALUMINUM PIGMENT ALUMINUM TURNINGS Alumi-paste 640NS Alumipaste 91-0562 Alumipaste 98-1822T Alumipaste AW 620 Alumipaste CR 300 Alumipaste GX 180A Alumipaste GX 201A Alumipaste HR 7000 Alumipaste HR 850 Alumipaste MG 11 Alumipaste MH 8801 Aquamet NPW 2900 Aquapaste 205-5 Aquasilver LPW Astroflake 40 Astroflake Black N 020 Astroflake Black N 070 Astroflake LG 40 Astroflake LG 70 Astroflake Silver N 040 Astroshine NJ 1600 Astroshine T 8990 Atomizalumi VA 200 C.I. PIGMENT METAL 1 Chromal IV Chromal X Decomet 1001/10 Decomet 2018/10 Decomet High Gloss Al 1002/10 Ecka AS 081 Eckart 9155 Eterna Brite 301-1 Eterna Brite 601-1 Eterna Brite 651-1 Eterna Brite EBP 251PA Eterna Brite Primier 251PA Ferro FX 53-038 Friend Color F 500GR-W Friend Color F 500WT Friend Color F 700RE-W Friend Color F 701RE-W Hi Print 60T High Print 60T Hisparkle HS 2 Hydro Paste 8726 Hydrolac WHH 2153 Hydrolan 3560 Hydrolux Reflexal 100 Hydroshine WS 1001 JISA 51010P Kryal Z Lansford 243 LE Sheet 800 Leafing Alpaste LG-H Silver 25 Lunar Al-V 95 Metallux 161 Metallux 2154 Metallux 2192 Metalure Metalure 55350 Metalure L 55350 Metalure L 59510 Metalure W 2001 Metapor Metasheen 1800 Metasheen HR 0800 Metasheen KM 100 Metasheen KM 1000 Metasheen Slurry 1807 Metasheen Slurry 1811 Metasheen Slurry KM 100 Metax G Metax S Mirror Glow 1000 Mirror Glow 600 Mirrorsheen Noral Aluminium Noral Ink Grade Aluminium Obron 10890 Offset FM 4500 Puratronic Reflexal 145 Reynolds 400 Reynolds 4-301 Reynolds 4-591 Reynolds 667 SAP 260PW-HS SAP-FM 4010 SBC 516-20Z Scotchcal 7755SE Serumekku Setanium 50MIS-H8 Siberline ET 2025 Siberline ST 21030E1 Silvar A Silver VT 522 Silverline SSP 353 Silvex 793-20C Sparkle Silver 3141ST Sparkle Silver 3500 Sparkle Silver 3641 Sparkle Silver 5000AR Sparkle Silver 516AR Sparkle Silver 5242AR Sparkle Silver 5245AR Sparkle Silver 5271AR Sparkle Silver 5500 Sparkle Silver 5745 Sparkle Silver 7000AR Sparkle Silver 7005AR Sparkle Silver 7500 Sparkle Silver 960-25E1 Sparkle Silver E 1745AR Sparkle Silver L 1526AR Sparkle Silver Premier 751 Sparkle Silver SS 3130 Sparkle Silver SS 5242AR Sparkle Silver SS 5588 Sparkle Silver SSP 132AR Special PCR 507 Splendal 6001BG Spota Mobil 801 SSP 760-20C Stapa Aloxal PM 2010 Stapa Aloxal PM 3010 Stapa Aloxal PM 4010 Stapa Hydrolac BG 8n.1 Stapa Hydrolac BGH Chromal X Stapa Hydrolac PM Chromal VIII Stapa Hydrolac W 60NL Stapa Hydrolac WH 16 Stapa Hydrolac WH 66NL Stapa Hydrolux 2192 Stapa Hydrolux 8154 Stapa IL Hydrolan 2192-55900G Stapa Metallic R 607 Stapa Metallux 1050 Stapa Metallux 211 Stapa Metallux 212 Stapa Metallux 2196 Stapa Metallux 274 Stapa Mobilux 181 Stapa Offset 3000 Stapa PV 10 Stapa VP 46432G Starbrite 2100 Super Fine 18000 Super Fine 22000 Supramex 2022 Toyo Aluminum 02-0005 Toyo Aluminum 93-3040 Transmet K 102HE Tufflake 3645 Tufflake 5843 UN 1396 US Aluminum 809 Valimet H 2 Valimet H 3 White Silver 7080N White Silver 7130N

DTXSID3040273

7440-43-9

BDOSMKKIYDKNTQ-UHFFFAOYSA-N

Cadmium

Cadimium CADMIUM BLUE CADMIUM, IN PLATTEN, STANGEN, BROCKEN,KOERNER

DTXSID1023940

7439-97-6

QSHDDOUJBYECFT-UHFFFAOYSA-N

Mercury

Liquid silver Mercure MERCURIC METAL TRIPLE DISTILLED mercurio Mercury element Quecksilber Quicksilver UN 2024 UN 2809

DTXSID1024172

7440-61-1

JFALSRSLKYAFGM-UHFFFAOYSA-N

Uranium

Uranium, isotope of mass 238 238U Element UN 2979 (DOT) Uranium I

DTXSID1042522

7440-38-2

RQNWIZPPADIBDY-UHFFFAOYSA-N

Arsenic

As Arsenic black ARSENIC METAL arsenico Grey arsenic UN 1558

DTXSID4023886

7440-22-4

BQCADISMDOOEFD-UHFFFAOYSA-N

Silver

Ag Nanopaste NPS-J 90 Ag Sphere 2 Ag-C-GS Algaedyn Arctic Silver 3 Argentum Astroflake 5 Carey Lea silver Colloidal silver Dotite XA 208 Du Pont 4943 ECM 100AF4810 Enlight 600 Enlight silver plate 600 Epinall Finesphere SVND 102 Fordel DC FP 5369-502 Jelcon SH 1 Jungindai Takasago 300 KS (metal) LCP 1-19SFS Metz 3000-1 Nanomelt AGC-A Nanomelt Ag-XA 301 Nanomelt Ag-XF 301 Nanomelt Ag-XF 301H Nanopaste NPS-J 90 Perfect Silver Puff Silver X 1200 RT 1710S-C1 SD (metal) Shell Silver Silbest E 20 Silbest F 20 Silbest J 18 Silbest TC 12 Silbest TC 20E Silbest TC 25A Silbest TCG 1 Silbest TCG 7 Silcoat AgC 103 Silcoat AgC 2011 Silcoat AgC 209 Silcoat AgC 2190 Silcoat AgC 222 Silcoat AgC 2411 Silcoat AgC 74T Silcoat AgC-A Silcoat AgC-AO Silcoat AgC-B Silcoat AgC-BO Silcoat AgC-D Silcoat AgC-G Silcoat AgC-GS Silcoat AgC-L Silcoat AgC-O Silcoat GS Silcoat RF 200 Silflake 135 Silsphere 514 Silver atom Silver element Silver Flake 1 Silver Flake 25 Silver Flake 52 Silver Flake 7A SILVER FLAKES Silver metal Silvest TCG 11N Technic 299 Technic 450 Techno Alpha 175

DTXSID4024305

7439-96-5

PWHULOQIROXLJO-UHFFFAOYSA-N

Manganese

Colloidal manganese Cutaval Manganese element Manganese fulleride Manganese metal alloy Manganese-55 manganeso

DTXSID2024169

7440-02-0

PXHVJJICTQNCMI-UHFFFAOYSA-N

Nickel

Carbonyl 255 Carbonyl Ni 123 Carbonyl Ni 283 Carbonyl Nickel 123 Carbonyl Nickel 283 Carbonyl Nickel 287 Cerac N 2003 CNS 10 Micron Exmet 4 Ni X-4/0 Fibrex P Incofoam Nickel element NICKEL ROUND ANODES Nicrobraz LM:BNi 2 Ni-Flake 95 Novamet 123 Novamet 4SP Novamet 4SP10 Novamet 525 Novamet CNS 400 Novamet HCA 1 Novamet NI 255 Raney nickel Raney nickel 2800 UN 1325 UN 2881

DTXSID2020925

7440-66-6

HCHKCACWOHOZIP-UHFFFAOYSA-N

Zinc

Zn Asarco L 15 C.I. Pigment Black 16 Merrillite NC-Zinc Rheinzink Stapa TE Zinc AT UF (metal) UN 1436 Zinc dust Zinc Dust 3 Zinc Dust 500 mesh Zinc Dust LS 2 Zinc Dust MCS Zinc Flakes GTT ZINC METAL ZINC MOSSY ZINC STRIP ZINC, MOSSY Zincsalt GTT

DTXSID7035012

51-28-5

UFBJCMHMOXMLKC-UHFFFAOYSA-N

2,4-Dinitrophenol

DNP 1,3-Dinitro-4-hydroxybenzene 1-Hydroxy-2,4-dinitrobenzene 2,4-dinitrofenol Aldifen Dinitrophenol DINITROPHENOL, 2,4- Dinofan Fenoxyl Carbon N NSC 1532 Phenol, α-dinitro- UN 1320 UN 1599 α-Dinitrophenol Phenol, 2,4-dinitro-

DTXSID0020523

10537-47-0

MZOPWQKISXCCTP-UHFFFAOYSA-N

Malonoben

DTXSID1042106

87-86-5

IZUPBVBPLAPZRR-UHFFFAOYSA-N

Pentachlorophenol

PCP Phenol, pentachloro- 1-Hydroxy-2,3,4,5,6-pentachlorobenzene 1-Hydroxypentachlorobenzene Chlorophenasic acid CHLOROPHENATE Dowicide EC 7 Dura Treet II Fungifen Grundier Arbezol Lauxtol Liroprem NSC 263497 Penchlorol Pentachlorphenol Perchlorophenol Permasan Phenol, 2,3,4,5,6-pentachloro- Pole topper Pole topper fluid Preventol P Santophen 20 Satophen UN 3155 Witophen P Woodtreat A 2,3,4,5,6-Pentachlorophenol

DTXSID7021106

3380-34-5

XEFQLINVKFYRCS-UHFFFAOYSA-N

Triclosan

5-Chloro-2-(2,4-dichlorophenoxy)phenol Phenol, 5-chloro-2-(2,4-dichlorophenoxy)- 2, 4, 4'-Trichloro-2'-hydroxydiphenylether 2,2'-Oxybis(1',5'-dichlorophenyl-5-chlorophenol) 2,4,4'-TRICHLORO-2'-HYDROXY DIPHENYLETHER 2',4',4-Trichloro-2-hydroxydiphenyl ether 2',4,4'-Trichloro-2-hydroxydiphenyl ether 2,4,4'-Trichloro-2'-hydroxydiphenyl ether 2'-Hydroxy-2,4,4'-trichlorodiphenyl ether 2-Hydroxy-2',4,4'-trichlorodiphenyl ether 3-Chloro-6-(2,4-dichlorophenoxy)phenol 4-Chloro-2-hydroxyphenyl 2,4-dichlorophenyl ether 5-Chloro-2-(2', 4'-dichlorophenoxy) phenol Aquasept Bacti-Stat soap Cansan TCH DIPHENYL ETHER, 2,4,4'-TRICHLORO-2'-HYDROXY- Irgacare MP Irgacide LP 10 Irgaguard B 1000 Irgaguard B 1325 Irgasan Irgasan CH 3565 Irgasan DP 30 Irgasan DP 300 Irgasan DP 3000 Irgasan DP 400 Irgasan PE 30 Irgasan PG 60 Microban Additive B Microban B Oletron Phenol, 5-chloro-2-(2,4-dichlorophenoxy) Phenol, 5-chloro-2-(2,4-dichlorophenoxy)-, dihydrogen phosphate Sanitized XTX Sapoderm SterZac Tinosan AM 100 Tinosan AM 110 TRICLOSAM Ultra Fresh NM 100 Ultrafresh NM-V 2 Vinyzene DP 7000 Yujiexin Zilesan UW

DTXSID5032498

518-82-1

RHMXXJGYXNZAPX-UHFFFAOYSA-N

Emodin

9,10-Anthracenedione, 1,3,8-trihydroxy-6-methyl- 1,3,8-trihidroxi-6-metilantraquinona 1,3,8-Trihydroxy-6-methyl-9,10-anthraquinone 1,3,8-Trihydroxy-6-methylanthrachinon 1,3,8-trihydroxy-6-methylanthraquinone 1,6,8-Trihydroxy-3-methylanthraquinone 3-Methyl-1,6,8-trihydroxyanthraquinone 4,5,7-Trihydroxy-2-methylanthraquinone Anthraquinone, 1,3,8-trihydroxy-6-methyl- Frangula emodin Frangulic acid NSC 408120 NSC 622947 Rheum emodin Schuttgelb

DTXSID5025231

CHEBI:26523

CHEBI reactive oxygen species

CHEBI:35366

CHEBI fatty acid

CHEBI:15422

CHEBI ATP

UBERON:0000468

UBERON multicellular organism

GO:1903409

GO reactive oxygen species biosynthetic process

MP:0003674

MP oxidative stress

GO:0018158

GO protein oxidation

GO:0006635

GO fatty acid beta-oxidation

GO:0006754

GO ATP biosynthetic process

GO:0008219

GO cell death

GO:0040007

GO growth

WIKI increased

WIKI decreased

Acetaminophen

2016-11-29T18:42:26

Chloroform

2016-11-29T18:42:27

furan

2020-05-01T14:35:22

Platinum

2022-02-04T14:36:54

Aluminum

2022-02-04T14:42:11

Cadmium

2017-10-25T08:33:12

Mercury

2016-11-29T18:42:19

Uranium

2021-08-05T14:28:50

Arsenic

2021-04-27T00:15:21

Silver

2022-02-03T11:20:11

Manganese

2022-02-04T14:47:23

Nickel

2022-02-04T14:47:59

Zinc

2022-02-04T15:05:00

nanoparticles

2016-12-21T09:40:06

Carbonyl cyanide-p-trifluoromethoxyphenylhydrazone

2020-11-12T17:59:28

Carbonyl cyanide m-chlorophenyl hydrazone

2020-11-12T17:59:47

2,4-Dinitrophenol

2016-11-29T18:42:27

Malonoben

2020-11-27T14:43:47

Pentachlorophenol

2020-11-12T17:59:12

Triclosan

2020-11-12T18:00:07

Emodin

2020-11-20T13:48:58

WikiUser_28

Vertebrates

WCS_9606

common toxicological species human

WikiUser_25

Wikiuser: Cyauk human and other cells in culture

10090

NCBI mouse

WCS_35525

common ecological species crustaceans

WCS_4472

common ecological species Lemna minor

WCS_7955

common ecological species zebrafish

WikiUser_26

ApacheUser rodents

9606

NCBI Homo sapiens

WCS_9606

common toxicological species humans

WikiUser_17

mammals

WikiUser_6

ApacheUser fish

WCS_63659

common ecological species green algae

10116

NCBI rat

10116

NCBI Rattus norvegicus

WCS_90988

common ecological species fathead minnow

WCS_35525

common ecological species Daphnia magna

Increase, Reactive oxygen species

Increase, ROS

Cellular

Biological State: increased reactive oxygen species (ROS) Biological compartment: an entire cell -- may be cytosolic, may also enter organelles. Reactive oxygen species (ROS) are O2- derived molecules that can be both free radicals (e.g. superoxide, hydroxyl, peroxyl, alcoxyl) and non-radicals (hypochlorous acid, ozone and singlet oxygen) (Bedard and Krause 2007; Ozcan and Ogun 2015). ROS production occurs naturally in all kinds of tissues inside various cellular compartments, such as mitochondria and peroxisomes (Drew and Leeuwenburgh 2002; Ozcan and Ogun 2015). Furthermore, these molecules have an important function in the regulation of several biological processes – they might act as antimicrobial agents or triggers of animal gamete activation and capacitation (Goud et al. 2008; Parrish 2010; Bisht et al. 2017).  However, in environmental stress situations (exposure to radiation, chemicals, high temperatures) these molecules have its levels drastically increased, and overly interact with macromolecules, namely nucleic acids, proteins, carbohydrates and lipids, causing cell and tissue damage (Brieger et al. 2012; Ozcan and Ogun 2015).  <div> Reactive oxygen species (ROS) refers to the chemical species superoxide, hydrogen peroxide, and their secondary reactive products. In the biological context, ROS are signaling molecules with important roles in cell energy metabolism, cell proliferation, and fate. Therefore, balancing ROS levels at the cellular and tissue level is an important part of many biological processes. Disbalance, mainly an increase in ROS levels, can cause cell dysfunction and irreversible cell damage. ROS are produced from both exogenous stressors and normal endogenous cellular processes, such as the mitochondrial electron transport chain (ETC). Inhibition of the ETC can result in the accumulation of ROS. Exposure to chemicals, heavy metal ions, or ionizing radiation can also result in increased production of ROS. Chemicals and heavy metal ions can deplete cellular antioxidants reducing the cell’s ability to control cellular ROS and resulting in the accumulation of ROS. Cellular antioxidants include glutathione (GSH), protein sulfhydryl groups, superoxide dismutase (SOD). ROS are radicals, ions, or molecules that have a single unpaired electron in their outermost shell of electrons, which can be categorized into two groups: free oxygen radicals and non-radical ROS [Liou et al., 2010]. <Free oxygen radicals> <div> <table cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <tbody> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:2px solid black; vertical-align:top; width:290px"> superoxide </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:2px solid black; vertical-align:top; width:290px"> O2·- </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> hydroxyl radical </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> ·OH </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> nitric oxide </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> NO· </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> organic radicals </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> R· </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> peroxyl radicals </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> ROO· </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> alkoxyl radicals </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> RO· </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> thiyl radicals </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> RS· </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> sulfonyl radicals </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> ROS· </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> thiyl peroxyl radicals </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> RSOO· </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> disulfides </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> RSSR </td> </tr> </tbody> </table> </div> <Non-radical ROS> <div> <table cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <tbody> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:2px solid black; vertical-align:top; width:290px"> hydrogen peroxide </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:2px solid black; vertical-align:top; width:290px"> H2O2 </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> singlet oxygen </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> 1O2 </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> ozone/trioxygen </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> O3 </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> organic hydroperoxides </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> ROOH </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> hypochlorite </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> ClO- </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> peroxynitrite </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> ONOO- </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> nitrosoperoxycarbonate anion </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> O=NOOCO2- </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> nitrocarbonate anion </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> O2NOCO2- </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> dinitrogen dioxide </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> N2O2 </td> </tr> <tr> <td style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> nitronium </td> <td style="border-bottom:2px solid black; border-left:none; border-right:2px solid black; border-top:none; vertical-align:top; width:290px"> NO2+ </td> </tr> <tr> <td colspan="2" style="border-bottom:2px solid black; border-left:2px solid black; border-right:2px solid black; border-top:none; vertical-align:top; width:580px"> highly reactive lipid- or carbohydrate-derived carbonyl compounds </td> </tr> </tbody> </table> </div> Potential sources of ROS include NADPH oxidase, xanthine oxidase, mitochondria, nitric oxide synthase, cytochrome P450, lipoxygenase/cyclooxygenase, and monoamine oxidase [Granger et al., 2015]. ROS are generated through NADPH oxidases consisting of p47phox and p67phox. ROS are generated through xanthine oxidase activation in sepsis [Ramos et al., 2018]. Arsenic produces ROS [Zhang et al., 2011]. Mitochondria-targeted paraquat and metformin mediate ROS production [Chowdhury et al., 2020]. ROS are generated by bleomycin [Lu et al., 2010]. Radiation induces dose-dependent ROS production [Ji et al., 2019]. ROS are generated in the course of cellular respiration, metabolism, cell signaling, and inflammation [Dickinson and Chang 2011; Egea et al. 2017]. Hydrogen peroxide is also made by the endoplasmic reticulum in the course of protein folding. Nitric oxide (NO) is produced at the highest levels by nitric oxide synthase in endothelial cells and phagocytes. NO production is one of the main mechanisms by which phagocytes kill bacteria [Wang et al., 2017]. The other species are produced by reactions with superoxide or peroxide, or by other free radicals or enzymes. ROS activity is principally local. Most ROS have short half-lives, ranging from nano- to milliseconds, so diffusion is limited, while reactive nitrogen species (RNS) nitric oxide or peroxynitrite can survive long enough to diffuse across membranes [Calcerrada et al. 2011]. Consequently, local concentrations of ROS are much higher than average cellular concentrations, and signaling is typically controlled by colocalization with redox buffers [Dickinson and Chang 2011; Egea et al. 2017]. Although their existence is limited temporally and spatially, ROS interact with other ROS or with other nearby molecules to produce more ROS and participate in a feedback loop to amplify the ROS signal, which can increase RNS. Both ROS and RNS also move into neighboring cells, and ROS can increase intracellular ROS signaling in neighboring cells [Egea et al. 2017]. In the primary event, photoreactive chemicals are excited by the absorption of photon energy.  The energy of the photoactivated chemicals transfer to oxygen and then generates the reactive oxygen species (ROS), including superoxide (O2−) via type I reaction and singlet oxygen (1O2) via type II reaction, as principal intermediate species in phototoxic reaction (Foote, 1991, Onoue et al. , 2009). </div>

Photocolorimetric assays (Sharma et al. 2017; Griendling et al. 2016) or through commercial kits purchased from specialized companies. Yuan, Yan, et al., (2013) described ROS monitoring by using H2-DCF-DA, a redox-sensitive fluorescent dye. Briefly, the harvested cells were incubated with H2-DCF-DA (50 µmol/L final concentration) for 30 min in the dark at 37°C. After treatment, cells were immediately washed twice, re-suspended in PBS, and analyzed on a BD-FACS Aria flow cytometry. ROS generation was based on fluorescent intensity which was recorded by excitation at 504 nm and emission at 529 nm. Lipid peroxidation (LPO) can be measured as an indicator of oxidative stress damage Yen, Cheng Chien, et al., (2013). Chattopadhyay, Sukumar, et al. (2002) assayed the generation of free radicals within the cells and their extracellular release in the medium by addition of yellow NBT salt solution (Park et al., 1968). Extracellular release of ROS converted NBT to a purple colored formazan. The cells were incubated with 100 ml of 1 mg/ml NBT solution for 1 h at 37 °C and the product formed was assayed at 550 nm in an Anthos 2001 plate reader. The observations of the ‘cell-free system’ were confirmed by cytological examination of parallel set of explants stained with chromogenic reactions for NO and ROS. On the basis of the pathogenesis of drug-induced phototoxicity, a reactive oxygen species (ROS) assay was proposed to evaluate the phototoxic risk of chemicals. The ROS assay can monitor generation of ROS, such as singlet oxygen and superoxide, from photoirradiated chemicals, and the ROS data can be used to evaluate the photoreactivity of chemicals (Onoue et al. , 2014, Onoue et al. , 2013, Onoue and Tsuda, 2006).  The ROS assay is a recommended approach by guidelines to evaluate the phototoxic risk of chemicals (ICH, 2014, PCPC, 2014). <div> <Direct detection> Many fluorescent compounds can be used to detect ROS, some of which are specific, and others are less specific. ・ROS can be detected by fluorescent probes such as p-methoxy-phenol derivative [Ashoka et al., 2020]. ・Chemiluminescence analysis can detect the superoxide, where some probes have a wider range for detecting hydroxyl radical, hydrogen peroxide, and peroxynitrite [Fuloria et al., 2021]. ・ROS in the blood can be detected using superparamagnetic iron oxide nanoparticles (SPION)-based biosensor [Lee et al., 2020]. ・Hydrogen peroxide (H2O2) can be detected with a colorimetric probe, which reacts with H2O2 in a 1:1 stoichiometry to produce a bright pink colored product, followed by the detection with a standard colorimetric microplate reader with a filter in the 540-570 nm range. ・The levels of ROS can be quantified using multiple-step amperometry using a stainless steel counter electrode and non-leak Ag|AgCl reference node [Flaherty et al., 2017]. ・Singlet oxygen can be measured by monitoring the bleaching of p-nitrosodimethylaniline at 440 nm using a spectrophotometer with imidazole as a selective acceptor of singlet oxygen [Onoue et al., 2014]. <Indirect Detection> Alternative methods involve the detection of redox-dependent changes to cellular constituents such as proteins, DNA, lipids, or glutathione [Dickinson and Chang 2011; Wang et al. 2013; Griendling et al. 2016]. However, these methods cannot generally distinguish between the oxidative species behind the changes and cannot provide good resolution for the kinetics of oxidative activity. </div>

ROS is a normal constituent found in all organisms, lifestages, and sexes.

UBERON:0000062

UBERON organ

CL:0000000

CL cell

High Unspecific High Mixed

High

All life stages

High Moderate Moderate Moderate High High High

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2025-06-12T01:27:08

Increase, Oxidative Stress

Molecular

Oxidative stress is defined as an imbalance in the production of reactive oxygen species (ROS) and antioxidant defenses. High levels of oxidizing free radicals can be very damaging to cells and molecules within the cell.  As a result, the cell has important defense mechanisms to protect itself from ROS. For example, Nrf2 is a transcription factor and master regulator of the oxidative stress response. During periods of oxidative stress, Nrf2-dependent changes in gene expression are important in regaining cellular homeostasis (Nguyen, et al., 2009) and can be used as indicators of the presence of oxidative stress in the cell.  In addition to the directly damaging actions of ROS, cellular oxidative stress also changes cellular activities on a molecular level. Redox sensitive proteins have altered physiology in the presence and absence of ROS, which is caused by the oxidation of sulfhydryls to disulfides on neighboring amino acids (Antelmann & Helmann 2011). Importantly Keap1, the negative regulator of Nrf2, is regulated in this manner (Itoh, et al. 2010).  ROS also undermine the mitochondrial defense system from oxidative damage. The antioxidant systems consist of superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase, as well as antioxidants such as α-tocopherol and ubiquinol, or antioxidant vitamins and minerals including vitamin E, C, carotene, lutein, zeaxanthin, selenium, and zinc (Fletcher, 2010). The enzymes, vitamins and minerals catalyze the conversion of ROS to non-toxic molecules such as water and O2. However, these antioxidant systems are not perfect and endogenous metabolic processes and/or exogenous oxidative influences can trigger cumulative oxidative injuries to the mitochondria, causing a decline in their functionality and efficiency, which further promotes cellular oxidative stress (Balasubramanian, 2000; Ganea & Harding, 2006; Guo et al., 2013; Karimi et al., 2017).   However, an emerging viewpoint suggests that ROS-induced modifications may not be as detrimental as previously thought, but rather contribute to signaling processes (Foyer et al., 2017).    Sources of ROS Production  Direct Sources: Direct sources involve the deposition of energy onto water molecules, breaking them into active radical species. When ionizing radiation hits water, it breaks it into hydrogen (H*) and hydroxyl (OH*) radicals by destroying its bonds. The hydrogen will create hydroxyperoxyl free radicals (HO2*) if oxygen is available, which can then react with another of itself to form hydrogen peroxide (H2O2) and more O2 (Elgazzar and Kazem, 2015). Antioxidant mechanisms are also affected by radiation, with catalase (CAT) and peroxidase (POD) levels rising as a result of exposure (Seen et al. 2018; Ahmad et al. 2021).   Indirect Sources: An indirect source of ROS is the mitochondria, which is one of the primary producers in eukaryotic cells (Powers et al., 2008).  As much as 2% of the electrons that should be going through the electron transport chain in the mitochondria escape, allowing them an opportunity to interact with surrounding structures. Electron-oxygen reactions result in free radical production, including the formation of hydrogen peroxide (H2O2) (Zhao et al., 2019). The electron transport chain, which also creates ROS, is activated by free adenosine diphosphate (ADP), O2, and inorganic phosphate (Pi) (Hargreaves et al. 2020; Raimondi et al. 2020; Vargas-Mendoza et al. 2021). The first and third complexes of the transport chain are the most relevant to mammalian ROS production (Raimondi et al., 2020). The mitochondria has its own set of DNA and it is a prime target of oxidative damage (Guo et al., 2013). ROS is also produced through nicotinamide adenine dinucleotide phosphate oxidase (Nox) stimulation, an event commenced by angiotensin II, a product/effector of the renin-angiotensin system (Nguyen Dinh Cat et al. 2013; Forrester et al. 2018). Other ROS producers include xanthine oxidase, immune cells (macrophage, neutrophils, monocytes, and eosinophils), phospholipase A2 (PLA2), monoamine oxidase (MAO), and carbon-based nanomaterials (Powers et al. 2008; Jacobsen et al. 2008; Vargas-Mendoza et al. 2021).

Oxidative Stress: Direct measurement of ROS is difficult because ROS are unstable. The presence of ROS can be assayed indirectly by measurement of cellular antioxidants, or by ROS-dependent cellular damage. Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed  <ul> <li>Detection of ROS by chemiluminescence (https://www.sciencedirect.com/science/article/abs/pii/S0165993606001683) </li> <li>Detection of ROS by chemiluminescence is also described in OECD TG 495 to assess phototoxic potential. </li> <li>Glutathione (GSH) depletion. GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green- ab138881.html). </li> <li>TBARS. Oxidative damage to lipids can be measured by assaying for lipid peroxidation using TBARS (thiobarbituric acid reactive substances) using a commercially available kit. </li> <li>8-oxo-dG. Oxidative damage to nucleic acids can be assayed by measuring 8-oxo-dG adducts (for which there are a number of ELISA based commercially available kits),or HPLC, described in Chepelev et al. (Chepelev, et al. 2015). </li> </ul>    Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assay for Nrf2 activity include:  <ul> <li>Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus Western blot for increased Nrf2 protein levels </li> <li>Western blot of cytoplasmic and nuclear fractions to observe translocation of Nrf2 protein from the cytoplasm to the nucleus qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences) </li> <li>Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway (e.g., Jackson et al. 2014) </li> <li>OECD TG422D describes an ARE-Nrf2 Luciferase test method </li> </ul> In general, there are a variety of commercially available colorimetric or fluorescent kits for detecting Nrf2 activation. <table border="1"> <tbody> <tr> <td> Assay Type & Measured Content  </td> <td> Description  </td> <td> Dose Range Studied  </td> <td> Assay Characteristics (Length/Ease of use/Accuracy)  </td> </tr> <tr> <td> ROS  Formation in the Mitochondria assay (Shaki et al., 2012)  </td> <td> “The mitochondrial ROS measurement was performed flow cytometry using DCFH-DA. Briefly, isolated kidney mitochondria were incubated with UA (0, 50, 100 and 200 µM) in respiration buffer containing (0.32 mM sucrose, 10mM Tris, 20 mM Mops, 50 µM EGTA, 0.5 mM MgCl2, 0.1 mM KH2PO4 and 5 mM sodium succinate) [32]. In the interval times of 5, 30 and 60 min following the UA addition, a sample was taken and DCFH-DA was added (final concentration, 10 µM) to mitochondria and was then incubated for 10 min.Uranyl acetate-induced ROS generation in isolated kidney mitochondria were determined through the flow cytometry (Partec, Deutschland) equipped with a 488-nm argon ion laser and supplied with the Flomax software and the signals were obtained using a 530-nm bandpass filter (FL-1 channel). Each determination is based on the mean fluorescence intensity of 15,000 counts.”    </td> <td> 0, 50,100 and 200 µM of Uranyl Acetate    </td> <td>  Long/ Easy High accuracy    </td> </tr> <tr> <td> Mitochondrial Antioxidant Content Assay Measuring GSH content (Shaki et al., 2012)    </td> <td> “GSH content was determined using DTNB as the indicator and spectrophotometer method for the isolated mitochondria. The mitochondrial fractions (0.5 mg protein/ml) were incubated with various concentrations of uranyl acetate for 1 h at 30 °C and then 0.1 ml of mitochondrial fractions was added into 0.1 mol/l of phosphate buffers and 0.04% DTNB in a total volume of 3.0 ml (pH 7.4). The developed yellow color was read at 412 nm on a spectrophotometer (UV-1601 PC, Shimadzu, Japan). GSH content was expressed as µg/mg protein.”  </td> <td> 0, 50,  100, or  200 µM  Uranyl Acetate  </td> <td>   </td> </tr> <tr> <td> H2O2 Production Assay Measuring H2O2 Production in isolated mitochondria (Heyno et al., 2008)    </td> <td> “Effect of CdCl2 and antimycin A (AA) on H2O2 production in isolated mitochondria from potato. H2O2 production was measured as scopoletin oxidation. Mitochondria were incubated for 30 min in the measuring buffer  (see the Materials and Methods) containing 0.5 mM succinate as an electron donor and 0.2 µM mesoxalonitrile 3‐chlorophenylhydrazone (CCCP) as an uncoupler, 10 U horseradish peroxidase and 5 µM scopoletin.”   </td> <td> 0, 10, 30  µM Cd2+     2 µM antimycin A  </td> <td>   </td> </tr> <tr> <td> Flow Cytometry ROS & Cell Viability (Kruiderig et al., 1997)    </td> <td> “For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”“For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”  </td> <td>   </td> <td>           Strong/easy medium  </td> </tr> <tr> <td> DCFH-DA  Assay Detection of hydrogen peroxide production (Yuan et al.,  2016)  </td> <td> Intracellular ROS production was measured using DCFH-DA as a probe. Hydrogen peroxide oxidizes DCFH to DCF. The probe is hydrolyzed intracellularly to DCFH carboxylate anion. No direct reaction with H2O2 to form fluorescent production.    </td> <td> 0-400  µM  </td> <td> Long/ Easy High accuracy  </td> </tr> <tr> <td> H2-DCF-DAAssay Detection of superoxide production (Thiebault etal., 2007)    </td> <td> This dye is a stable nonpolar compound which diffuses readily into the cells and yields H2-DCF. Intracellular OH or ONOO- react with H2-DCF when cells contain peroxides, to form the highly fluorescent compound DCF, which effluxes the cell. Fluorescence intensity of DCF is measured using a fluorescence spectrophotometer.  </td> <td> 0–600  µM  </td> <td> Long/ Easy High accuracy  </td> </tr> <tr> <td> CM-H2DCFDA  Assay (Eruslanov  & Kusmartsev, 2009)  </td> <td> The dye (CM-H2DCFDA) diffuses into the cell and is cleaved by esterases, the thiol reactive chlormethyl group reacts with intracellular glutathione which can be detected using flow cytometry.  </td> <td>   </td> <td> Long/Easy/ High Accuracy  </td> </tr> </tbody> </table>   <table border="1"> <tbody> <tr> <td> Method of Measurement   </td> <td> References   </td> <td> Description   </td> <td colspan="2"> OECD-Approved Assay  </td> </tr> <tr> <td> Chemiluminescence   </td> <td> (Lu, C. et al., 2006;   Griendling, K. K., et al., 2016)  </td> <td> ROS can induce electron transitions in molecules, leading to electronically excited products. When the electrons transition back to ground state, chemiluminescence is emitted and can be measured. Reagents such as luminol and lucigenin are commonly used to amplify the signal.   </td> <td colspan="2"> No    </td> </tr> <tr> <td> Spectrophotometry   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> NO has a short half-life. However, if it has been reduced to nitrite (NO2-), stable azocompounds can be formed via the Griess Reaction, and further measured by spectrophotometry.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Direct or Spin Trapping-Based electron paramagnetic resonance (EPR) Spectroscopy   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> The unpaired electrons (free radicals) found in ROS can be detected with EPR and is known as electron paramagnetic resonance. A variety of spin traps can be used.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Nitroblue Tetrazolium Assay   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> The Nitroblue Tetrazolium assay is used to measure O2.− levels. O2.− reduces nitroblue tetrazolium (a yellow dye) to formazan (a blue dye), and can be measured at 620 nm.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Fluorescence analysis of dihydroethidium (DHE) or Hydrocyans   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> Fluorescence analysis of DHE is used to measure O2.− levels.  O2.− is reduced to O2 as DHE is oxidized to 2-hydroxyethidium, and this reaction can be measured by fluorescence. Similarly, hydrocyans can be oxidized by any ROS, and measured via fluorescence.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Amplex Red Assay   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> Fluorescence analysis to measure extramitochondrial or extracellular H2O2 levels. In the presence of horseradish peroxidase and H2O2, Amplex Red is oxidized to resorufin, a fluorescent molecule measurable by plate reader.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Dichlorodihydrofluorescein Diacetate (DCFH-DA)   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> An indirect fluorescence analysis to measure intracellular H2O2 levels.  H2O2 interacts with peroxidase or heme proteins, which further react with DCFH, oxidizing it to dichlorofluorescein (DCF), a fluorescent product.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> HyPer Probe   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> Fluorescent measurement of intracellular H2O2 levels. HyPer is a genetically encoded fluorescent sensor that can be used for in vivo and in situ imaging.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Cytochrome c Reduction Assay   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> The cytochrome c reduction assay is used to measure O2.− levels. O O2.− is reduced to O2 as ferricytochrome c is oxidized to ferrocytochrome c, and this reaction can be measured by an absorbance increase at 550 nm.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Proton-electron double-resonance imaging (PEDRI)   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> The redox state of tissue is detected through nuclear magnetic resonance/magnetic resonance imaging, with the use of a nitroxide spin probe or biradical molecule.   </td> <td colspan="2"> No              </td> </tr> <tr> <td> Glutathione (GSH) depletion   </td> <td> (Biesemann, N. et al., 2018)   </td> <td> A downstream target of the Nrf2 pathway is involved in GSH synthesis. As an indication of oxidation status, GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., <a href="http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green-ab138881.html" rel="noreferrer noopener" target="_blank">http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green-ab138881.html</a>).    </td> <td colspan="2"> No  </td> </tr> <tr> <td> Thiobarbituric acid reactive substances (TBARS)   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> Oxidative damage to lipids can be measured by assaying for lipid peroxidation with TBARS using a commercially available kit.    </td> <td colspan="2"> No  </td> </tr> <tr> <td> Protein oxidation (carbonylation)  </td> <td> (Azimzadeh et al., 2017; Azimzadeh et al., 2015; Ping et al., 2020)  </td> <td> Can be determined with ELISA or a commercial assay kit. Protein oxidation can indicate the level of oxidative stress.  </td> <td colspan="2"> No  </td> </tr> <tr> <td> Seahorse XFp Analyzer  </td> <td> Leung et al. 2018  </td> <td> The Seahorse XFp Analyzer provides information on mitochondrial function, oxidative stress, and metabolic dysfunction of viable cells by measuring respiration (oxygen consumption rate; OCR) and extracellular pH (extracellular acidification rate; ECAR).  </td> <td> No  </td> </tr> </tbody> </table>   Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assays for Nrf2 activity include:   <table border="1"> <tbody> <tr> <td> Method of Measurement   </td> <td> References   </td> <td> Description   </td> <td> OECD-Approved Assay  </td> </tr> <tr> <td> Immunohistochemistry   </td> <td> (Amsen, D., de Visser, K. E., and Town, T., 2009)  </td> <td> Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus    </td> <td> No  </td> </tr> <tr> <td> qPCR   </td> <td> (Forlenza et al., 2012)  </td> <td> qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences)   </td> <td> No  </td> </tr> <tr> <td> Whole transcriptome profiling via microarray or via RNA-seq followed by a pathway analysis  </td> <td> (Jackson, A. F. et al., 2014)  </td> <td> Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway  </td> <td> No  </td> </tr> </tbody> </table> Update - non-endorsed (by You Song, 02/09/2026) ToxCast/Tox21 assays (invitrodb v4.3): ATG_NRF2_ARE_CIS; Tox21_ARE_BLA_Agonist_ratio; TOX21_ARE_KS_LUC_Agonist; LTEA_HepaRG_NFE2L2; LTEA_HepaRG_GCLC; LTEA_HepaRG_CAT

Taxonomic applicability: Occurrence of oxidative stress is not species specific.   Life stage applicability: Occurrence of oxidative stress is not life stage specific.  Sex applicability: Occurrence of oxidative stress is not sex specific.  Evidence for perturbation by prototypic stressor: There is evidence of the increase of oxidative stress following perturbation from a variety of stressors including exposure to ionizing radiation and altered gravity (Bai et al., 2020; Ungvari et al., 2013; Zhang et al., 2009).

High Mixed

High

All life stages

High High

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2026-09-02T04:19:05

Increase, Protein oxidation

Molecular

Protein oxidation refers to an increase in oxidative modification of proteins relative to an appropriate control state. Proteins are abundant and chemically diverse macromolecules that contain amino-acid side chains and peptide backbones susceptible to attack by ROS and related oxidants. Oxidation can lead to formation of protein carbonyls, oxidation of sulfur-containing amino acids such as cysteine and methionine, nitration or hydroxylation of aromatic residues, disulfide formation, S-glutathionylation, fragmentation, cross-linking, aggregation, altered folding and changes in enzymatic or structural function (Stadtman and Levine, 2003; Dalle-Donne et al., 2006; Fedorova et al., 2014).     The KE is defined by the observed or measured increase in oxidatively modified proteins rather than by a particular upstream stressor or downstream consequence. Protein oxidation can be reversible or irreversible depending on the chemical modification. Reversible thiol oxidation, disulfide formation, S-glutathionylation and methionine oxidation may participate in redox signaling and adaptive regulation, whereas irreversible carbonylation, backbone cleavage and protein aggregation are more commonly associated with protein dysfunction, proteostatic burden and cellular injury (Stadtman and Levine, 2003; Dalle-Donne et al., 2006; Reichmann et al., 2018).     Within oxidative stress AOPs, protein oxidation is an important molecular damage KE because it links redox imbalance to functional impairment of enzymes, structural proteins, signaling proteins and organelle proteins. In the ROS-growth AOP network, oxidation of mitochondrial respiratory proteins, cytoskeletal proteins or metabolic enzymes may contribute to decreased coupling of oxidative phosphorylation, impaired ATP production, altered cell cycle regulation, increased cell injury/death and reduced growth. However, these downstream consequences should be described on separate KER and AOP pages so that KE 1767 remains modular and reusable.

Protein oxidation can be measured using biochemical, immunochemical, fluorescence-based and proteomic approaches. No single method captures all forms of protein oxidation. Protein carbonylation is one of the most widely used and relatively stable indicators of oxidative protein damage, but other modifications such as methionine sulfoxide, cysteine oxidation, nitrotyrosine, S-glutathionylation and protein cross-linking may be more appropriate in particular biological contexts. Confidence is highest when the method directly detects a defined oxidized protein modification or oxidized peptide, and lower when broad assays are used without complementary specificity checks.   <table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <thead> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:130px"> Measurement approach </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:139px"> Endpoint measured </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:158px"> Representative method names </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:302px"> Scientific confidence and limitations </td> </tr> </thead> <tbody> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Protein carbonyl assays </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Protein carbonyl groups formed by direct oxidation or by adduction of reactive carbonyl species </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> DNPH derivatization with spectrophotometry, ELISA, immunoblotting or OxyBlot; hydrazide-based probes </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:302px"> Widely used, relatively stable and broadly accepted as a marker of protein oxidation. DNPH methods are sensitive but do not identify individual proteins unless combined with immunoblotting or proteomics. Carbonyls may arise from direct oxidation or from secondary reactions with lipid peroxidation products (Levine et al., 1990; Dalle-Donne et al., 2006; Fedorova et al., 2014). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Redox proteomics </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Oxidized proteins or oxidized amino-acid residues at protein or peptide level </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> 2D gel electrophoresis plus anti-DNP immunoblotting; LC-MS/MS redox proteomics; carbonyl-reactive enrichment workflows </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:302px"> High mechanistic value because it can identify protein targets and modification sites. Requires careful sample handling, derivatization or enrichment, and appropriate bioinformatic analysis (McDonagh et al., 2005; Fedorova et al., 2014; Butterfield and Dalle-Donne, 2014). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Thiol oxidation assays </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Oxidation state of protein thiols and disulfides </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Biotin-switch methods; maleimide labeling; redox Western blot; differential alkylation; thiol redox proteomics </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:302px"> Useful for reversible cysteine oxidation and redox signaling. Interpretation depends on preservation of redox state during sampling and on whether reversible signaling events or irreversible damage are being assessed (Dalle-Donne et al., 2006; Reichmann et al., 2018). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> S-glutathionylation assays </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Protein S-glutathionylation as a reversible thiol redox modification </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Anti-glutathione immunoblotting; redox proteomics; mass spectrometry </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:302px"> Mechanistically informative for redox regulation and oxidative stress responses. It may represent adaptive regulation rather than irreversible damage and should be interpreted in biological context (Dailianis et al., 2009; Zaffagnini et al., 2012). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Nitrotyrosine and other specific oxidized residue assays </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Specific oxidized or nitrated amino-acid residues </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Anti-nitrotyrosine immunoassays; LC-MS/MS; targeted proteomics </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:302px"> Provides higher chemical specificity for particular oxidant pathways, such as peroxynitrite-associated nitration, but does not capture all protein oxidation. Best used when the expected chemistry is known. </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Advanced oxidation protein products and aggregate assays </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Bulk oxidized protein products, cross-linked proteins or protein aggregates </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> AOPP assays; aggregate detection; protein insolubility assays </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:302px"> Useful for broad screening of oxidative protein burden but less specific than defined chemical or proteomic measurements. Should be interpreted as supportive evidence, especially when combined with carbonyl or mass-spectrometric endpoints. </td> </tr> </tbody> </table>

The biological domain of applicability for this KE is broad because proteins are universal biological macromolecules and many amino-acid residues are susceptible to oxidative modification. The KE is applicable wherever proteins are exposed to oxidants and where oxidative modification can be measured. It is therefore relevant across unicellular algae, invertebrates, fish, mammals, plants and human-derived cell systems. The evidence base is strongest in mammalian toxicology and biomedical studies, but ecotoxicological evidence supports relevance in algae, fish, mollusks and crustaceans.     The KE is not intrinsically limited by life stage or sex. However, the magnitude and toxicological importance of protein oxidation may be modified by antioxidant capacity, proteasomal and lysosomal degradation capacity, protein turnover, metal ion availability, oxygen availability, temperature, inflammatory status, nutritional status, mitochondrial activity, and exposure duration. Tissues or cells with high metabolic demand, high mitochondrial density, high inflammatory activity, or low proteostatic reserve may be especially susceptible.     Within the ROS-growth AOP network, this KE functions as a molecular damage event linking oxidative stress to downstream impairment of mitochondrial function and cellular injury. Nevertheless, the KE should remain modular. It may be reused in any AOP in which increased oxidative modification of proteins is measured or inferred as a discrete biological state, regardless of whether the downstream effect is impaired oxidative phosphorylation, cell death, altered signaling, immune dysfunction, neurotoxicity, growth inhibition or another adverse outcome.

UBERON:0000062

UBERON organ

CL:0000000

CL cell

Moderate Unspecific

Moderate

All life stages

High High High Moderate Moderate

AOP-Wiki. 2026. Key Event 1767: Increase, Protein oxidation. AOP-Wiki. Available at: https://aopwiki.org/events/1767. Accessed 14 May 2026. Almaida-Pagán PF, Lucas-Sánchez A, Tocher DR. 2014. Changes in mitochondrial membrane composition and oxidative status during rapid growth, maturation and aging in zebrafish, Danio rerio. Biochimica et Biophysica Acta - Molecular and Cell Biology of Lipids 1841(7):1003-1011. https://doi.org/10.1016/j.bbalip.2014.04.004. Butterfield DA, Dalle-Donne I. 2014. Redox proteomics: from protein modifications to cellular dysfunction and diseases. Mass Spectrometry Reviews 33(1):1-6. https://doi.org/10.1002/mas.21382. Dailianis S, Patetsini E, Kaloyianni M. 2009. The role of signaling molecules on actin glutathionylation and protein carbonylation induced by cadmium in hemocytes of mussel Mytilus galloprovincialis. Journal of Experimental Biology 212(22):3612-3620. https://doi.org/10.1242/jeb.031211. Dalle-Donne I, Aldini G, Carini M, Colombo R, Rossi R, Milzani A. 2006. Protein carbonylation, cellular dysfunction, and disease progression. Journal of Cellular and Molecular Medicine 10(2):389-406. https://doi.org/10.1111/j.1582-4934.2006.tb00407.x. Fedorova M, Bollineni RC, Hoffmann R. 2014. Protein carbonylation as a major hallmark of oxidative damage: update of analytical strategies. Mass Spectrometry Reviews 33(2):79-97. https://doi.org/10.1002/mas.21381. Levine RL, Garland D, Oliver CN, Amici A, Climent I, Lenz AG, Ahn BW, Shaltiel S, Stadtman ER. 1990. Determination of carbonyl content in oxidatively modified proteins. Methods in Enzymology 186:464-478. https://doi.org/10.1016/0076-6879(90)86141-H. Martínez M, Rodríguez-Graña L, Santos L, Denicola A, Calliari D. 2020. Long-term exposure to salinity variations induces protein carbonylation in the copepod Acartia tonsa. Journal of Experimental Marine Biology and Ecology 526:151337. https://doi.org/10.1016/j.jembe.2020.151337. McDonagh B, Tyther R, Sheehan D. 2005. Carbonylation and glutathionylation of proteins in the blue mussel Mytilus edulis detected by proteomic analysis and Western blotting: actin as a target for oxidative stress. Aquatic Toxicology 73(3):315-326. https://doi.org/10.1016/j.aquatox.2005.03.020. Mukherjee K, Chio TI, Sackett DL, Bane SL. 2015. Detection of oxidative stress-induced carbonylation in live mammalian cells using a hydrazine-based fluorescent probe. Free Radical Biology and Medicine 84:11-21. https://doi.org/10.1016/j.freeradbiomed.2015.03.011. Parvez S, Raisuddin S. 2005. Protein carbonyls: novel biomarkers of exposure to oxidative stress-inducing pesticides in freshwater fish Channa punctata (Bloch). Environmental Toxicology and Pharmacology 20(1):112-117. https://doi.org/10.1016/j.etap.2004.11.002. Reichmann D, Voth W, Jakob U. 2018. Maintaining a healthy proteome during oxidative stress. Molecular Cell 69(2):203-213. https://doi.org/10.1016/j.molcel.2017.12.021. Sokolov EP, Markert S, Hinzke T, Hirschfeld C, Becher D, Ponsuksili S, Sokolova IM. 2019. Effects of hypoxia-reoxygenation stress on mitochondrial proteome and bioenergetics of the hypoxia-tolerant marine bivalve Crassostrea gigas. Journal of Proteomics 194:99-111. https://doi.org/10.1016/j.jprot.2018.12.009. Stadtman ER, Levine RL. 2003. Free radical-mediated oxidation of free amino acids and amino acid residues in proteins. Amino Acids 25(3-4):207-218. https://doi.org/10.1007/s00726-003-0011-2. Tseng YC, Chen RD, Lucassen M, Schmidt MM, Dringen R, Abele D, Hwang PP. 2011. Exploring uncoupling proteins and antioxidant mechanisms under acute cold exposure in brains of fish. PLoS ONE 6(3):e18180. https://doi.org/10.1371/journal.pone.0018180. Zaffagnini M, Bedhomme M, Groni H, Marchand CH, Puppo C, Gontero B, Cassier-Chauvat C, Decottignies P, Lemaire SD. 2012. Glutathionylation in the photosynthetic model organism Chlamydomonas reinhardtii: a proteomic survey. Molecular & Cellular Proteomics 11(2):M111.014142. https://doi.org/10.1074/mcp.M111.014142. AOPWiki 2020-04-30T12:37:00

2026-06-23T06:29:10

Decrease, Fatty acid beta-oxidation

Decrease, Fatty acid β-oxidation

Cellular

Fatty acid oxidation in liver tissue is controlled by PPARalpha signaling networks (Evans et al 2004). The PPARalpha signaling network controls expression of the genes within metabolic pathways that catalyze fatty acid oxidation reactions (Desvergne and Wahli 1999).

A variety of approaches establishing the effects of PPARalpha signaling on fatty acid oxidation are reviewed in Evans et al (2004).

See review for Human PPARalpha signaling in (Evans et al 2004).

High

Desvergne B, Wahli W (1999) Peroxisome proliferator-activated receptors: nuclear control of metabolism. Endocrine Reviews 20(5): 649-688. Evans RM, Barish GD, Wang YX: PPARs and the complex journey to obesity. Nat Med 2004, 10(4):355-361. AOPWiki 2016-11-29T18:41:23

2025-05-23T06:50:10

Decrease, Adenosine triphosphate pool

Decrease, ATP pool

Cellular

Decreased adenosine triphosphate (ATP) pool describes the loss of balance between ATP synthesis and ATP consumption, leading to reduced total ATP. As a primary form of biological energy, ATP is used by many biological processes (Bonora 2012). Decrease in ATP level normally attributes to metabolic disorders in major ATP synthetic pathways, such as mitochondrial oxidative phosphorylation, fatty acid β-oxidation, glycolysis and plant photophosphorylation.

-The ATP pool in cells or tissue can be quantified using a well-established ATP bioluminescent assay (Lemasters 1978; Wibom 1990). Assay principles: ATP can react with luciferase and luciferin from firefly and the luminescence emitted from the reaction is proportional to the ATP concentration:   ATP + D-Luciferin + O2 è Oxyluciferin + AMP + PPi + CO2 + Light -ToxCast high-throughput screening bioassays, such as “NCCT_HEK293T_CellTiterGLO” and “NIS_HEK293T_CTG_Cytotoxicity” can be used to measure this KE.

Taxonomic applicability domain This key event is in general considered applicable to all eukaryotes utilizing ATP as a direct source of energy and signaling molecule.   Life stage applicability domain This key event is considered applicable to all life stages, as all developmental stages require energy supply to maintain necessary physiological processes.   Sex applicability domain This key event is considered sex-unspecific, as both males and females use ATP as an essential energy molecule.

CL:0000000

CL cell

High Unspecific

High

Embryo

High

Juvenile

Moderate

Adult, reproductively mature

High High High High High

Bonora M, Patergnani S, Rimessi A, De Marchi E, Suski JM, Bononi A, Giorgi C, Marchi S, Missiroli S, Poletti F, Wieckowski MR, Pinton P. 2012. ATP synthesis and storage. Purinergic Signalling 8:343-357. DOI: 10.1007/s11302-012-9305-8. Lemasters JJ, Hackenbrock CR. 1978. [4] Firefly luciferase assay for ATP production by mitochondria. Methods in Enzymology. Vol 57. Academic Press, pp 36-50. Wibom R, Lundin A, Hultman E. 1990. A sensitive method for measuring ATP-formation in rat muscle mitochondria. Scandinavian Journal of Clinical and Laboratory Investigation 50:143-152. DOI: 10.1080/00365519009089146.  AOPWiki 2020-04-30T12:42:35

2021-06-14T13:40:17

Increase, Cell injury/death

Cell injury/death

Cellular

Two types of cell death can be distinguished by morphological features, although it is likely that these are two ends of a spectrum with possible intermediate forms. Apoptosis involves shrinkage, nuclear disassembly, and fragmentation of the cell into discrete bodies with intact plasma membranes. These are rapidly phagocytosed by neighbouring cells. An important feature of apoptosis is the requirement for adenosine triphosphate (ATP) to initiate the execution phase. In contrast, necrotic cell death is characterized by cell swelling and lysis. This is usually a consequence of profound loss of mitochondrial function and resultant ATP depletion, leading to loss of ion homeostasis, including volume regulation, and increased intracellular Ca2+. The latter activates a number of nonspecific hydrolases (i.e., proteases, nucleases, and phospholipases) as well as calcium dependent kinases. Activation of calpain I, the Ca2+-dependent cysteine protease cleaves the death-promoting Bcl-2 family members Bid and Bax which translocate to mitochondrial membranes, resulting in release of truncated apoptosis-inducing factor (tAIF), cytochrome c and endonuclease in the case of Bid and cytocrome c in the case of Bax. tAIF translocates to cell nuclei, and together with cyclophilin A and phosphorylated histone H2AX (γH2AX) is responsible for DNA cleavage, a feature of programmed necrosis. Activated calpain I has also been shown to cleave the plasma membrane Na+–Ca2+ exchanger, which leads to build-up of intracellular Ca2+, which is the source of additional increased intracellular Ca2+. Cytochrome c in cellular apoptosis is a component of the apoptosome. DNA damage activates nuclear poly(ADP-ribose) polymerase-1(PARP-1), a DNA repair enzyme. PARP-1 forms poly(ADP-ribose) polymers, to repair DNA, but when DNA damage is extensive, PAR accumulates, exits cell nuclei and travels to mitochondrial membranes, where it, like calpain I, is involved in AIF release from mitochondria. A fundamental distinction between necrosis and apoptosis is the loss of plasma membrane integrity; this is integral to the former but not the latter. As a consequence, lytic release of cellular constituents promotes a local inflammatory reaction, whereas the rapid removal of apoptotic bodies minimizes such a reaction. The distinction between the two modes of death is easily accomplished in vitro but not in vivo. Thus, although claims that certain drugs induce apoptosis have been made, these are relatively unconvincing. DNA fragmentation can occur in necrosis, leading to positive TUNEL staining (see explanation below). Conversely, when apoptosis is massive, it can exceed the capacity for rapid phagocytosis, resulting in the eventual appearance of secondary necrosis. Two alternative pathways - either extrinsic (receptor-mediated) or intrinsic (mitochondria-mediated) - lead to apoptotic cell death. The initiation of cell death begins either at the plasma membrane with the binding of TNF or FasL to their cognate receptors or within the cell. The latter is due to the occurrence of intracellular stress in the form of biochemical events such as oxidative stress, redox changes, covalent binding, lipid peroxidation, and consequent functional effects on mitochondria, endoplasmic reticulum, microtubules, cytoskeleton, or DNA. The intrinsic mitochondrial pathway involves the initiator, caspase-9, which, when activated, forms an “apoptosome” in the cytosol, together with cytochrome c, which translocates from mitochondria, Apaf-1 and dATP. The apoptosome activates caspase-3, the central effector caspase, which in turn activates downstream factors that are responsible for the apoptotic death of a cell (Fujikawa, 2015). Intracellular stress either directly affects mitochondria or can lead to effects on other organelles, which then send signals to the mitochondria to recruit participation in the death process (Fujikawa, 2015; Malhi et al., 2010). Constitutively expressed nitric oxide synthase (nNOS) is a Ca2+-dependent cytosolic enzyme that forms nitric oxide (NO) from L-arginine, and NO reacts with the free radical such as superoxide (O2−) to form the very toxic free radical peroxynitrite (ONOO−). Free radicals such as ONOO−, O2 − and hydroxyl radical (OH−) damage cellular membranes and intracellular proteins, enzymes and DNA (Fujikawa, 2015; Malhi et al., 2010; Kaplowitz, 2002; Kroemer et al., 2009).

Necrosis: Lactate dehydrogenase (LDH) is a soluble cytoplasmic enzyme that is present in almost all cells and is released into extracellular space when the plasma membrane is damaged. To detect the leakage of LDH into cell culture medium, a tetrazolium salt is used in this assay. In the first step, LDH produces reduced nicotinamide adenine dinucleotide (NADH) when it catalyzes the oxidation of lactate to pyruvate. In the second step, a tetrazolium salt is converted to a colored formazan product using newly synthesized NADH in the presence of an electron acceptor. The amount of formazan product can be colorimetrically quantified by standard spectroscopy. Because of the linearity of the assay, it can be used to enumerate the percentage of necrotic cells in a sample (Chan et al., 2013).  The MTT assay is a colorimetric assay for assessing cell viability. NAD(P)H-dependent cellular oxidoreductase enzymes may reflect the number of viable cells present. These enzymes are capable of reducing the tetrazolium dye MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide to its insoluble formazan, which has a purple color. Other closely related tetrazolium dyes include XTT, MTS and the WSTs. Tetrazolium dye assays can also be used to measure cytotoxicity (loss of viable cells) or cytostatic activity (shift from proliferation to quiescence) of potential medicinal agents and toxic materials. MTT assays are usually done in the dark since the MTT reagent is sensitive to light (Berridgeet al.,2005). Propidium iodide (PI) is an intercalating agent and a fluorescent molecule used to stain necrotic cells. It is cell membrane impermeant so it stains only those cells where the cell membrane is destroyed. When PI is bound to nucleic acids, the fluorescence excitation maximum is 535 nm and the emission maximum is 617 nm (Moore et al.,1998) Alamar Blue (resazurin) is a fluorescent dye. The oxidized blue non fluorescent Alamar blue is reduced to a pink fluorescent dye in the medium by cell activity (O'Brien et al., 2000) (12). Neutral red uptake, which is based on the ability of viable cells to incorporate and bind the supravital dye neutral red in lysosomes (Repetto et al., 2008)(13). Moreover, quantification of ATP, signaling the presence of metabolically active cells, can be performed (CellTiter-Glo; Promega). ATP assay: Quantification of ATP, signaling the presence of metabolically active cells (CellTiter-Glo; Promega). Apoptosis: TUNEL is a common method for detecting DNA fragmentation that results from apoptotic signalling cascades. The assay relies on the presence of nicks in the DNA which can be identified by terminal deoxynucleotidyl transferase or TdT, an enzyme that will catalyze the addition of dUTPs that are secondarily labeled with a marker. It may also label cells that have suffered severe DNA damage. Caspase activity assays measured by fluorescence. During apoptosis, mainly caspase-3 and -7 cleave PARP to yield an 85 kDa and a 25 kDa fragment. PARP cleavage is considered to be one of the classical characteristics of apoptosis. Antibodies to the 85 kDa fragment of cleaved PARP or to caspase-3 both serve as markers for apoptotic cells that can be monitored using immunofluorescence (Li, Peng et al., 2004). Hoechst 33342 staining: Hoechst dyes are cell-permeable and bind to DNA in live or fixed cells. Therefore, these stains are often called supravital, which means that cells survive a treatment with these compounds. The stained, condensed or fragmented DNA is a marker of apoptosis (Loo, 2002; Kubbies and Rabinovitch, 1983).  Acridine Orange/Ethidium Bromide staining is used to visualize nuclear changes and apoptotic body formation that are characteristic of apoptosis. Cells are viewed under a fluorescence microscope and counted to quantify apoptosis.   Update - non-endorsed (by You Song, 02/09/2026) ToxCast/Tox21 assays (invitrodb v4.3): APR_HepG2_CellLoss_*; ATG_XTT_Cytotoxicity; LTEA_HepaRG_LDH_cytotoxicity

Cell death is an universal event occurring in cells of any species (Fink and Cookson,2005).

CL:0000255

CL eukaryotic cell

Not Specified Unspecific

Not Specified

All life stages

High High High High

<ul> <li>Fujikawa, D.G. (2015), The role of excitotoxic programmed necrosis in acute brain injury, Comput Struct Biotechnol J, vol. 13, pp. 212-221.</li> <li>Malhi, H. et al. (2010), Hepatocyte death: a clear and present danger, Physiol Rev, vol. 90, no. 3, pp. 1165-1194.</li> <li>Kaplowitz, N. (2002), Biochemical and Cellular Mechanisms of Toxic Liver Injury, Semin Liver Dis, vol. 22, no. 2, <a class="external free" href="http://www.medscape.com/viewarticle/433631" rel="nofollow" target="_blank">http://www.medscape.com/viewarticle/433631</a> (accessed on 20 January 2016).</li> <li>Kroemer, G. et al., (2009), Classification of cell death: recommendations of the Nomenclature Committee on Cell Death, Cell Death Differ, vol. 16, no. 1, pp. 3-11.</li> <li>Chan, F.K., K. Moriwaki and M.J. De Rosa (2013), Detection of necrosis by release of lactate dehydrogenase (LDH) activity, Methods Mol Biol, vol. 979, pp. 65–70.</li> <li>Berridge, M.V., P.M. Herst and A.S. Tan (2005), Tetrazolium dyes as tools in cell biology: new insights into their cellular reduction. Biotechnology Annual Review, vol. 11, pp 127-152.</li> <li>Moore, A, et al.(1998), Simultaneous measurement of cell cycle and apoptotic cell death,Methods Cell Biol, vol. 57, pp. 265–278.</li> <li>Li, Peng et al. (2004), Mitochondrial activation of apoptosis, Cell, vol. 116, no. 2 Suppl,pp. S57-59, 2 p following S59.</li> <li>Loo, D.T. (2002), TUNEL Assay an overview of techniques, Methods in Molecular Biology, vol. 203: In Situ Detection of DNA Damage, chapter 2, Didenko VV (ed.), Humana Press Inc.</li> <li>Kubbies, M. and P.S. Rabinovitch (1983), Flow cytometric analysis of factors which influence the BrdUrd-Hoechst quenching effect in cultivated human fibroblasts and lymphocytes, Cytometry, vol. 3, no. 4, pp. 276–281.</li> <li>Fink, S.L. and B.T. Cookson (2005), Apoptosis, pyroptosis, and necrosis: mechanistic description of dead and dying eukaryotic cells, Infect Immun, vol. 73, no. 4, pp.1907-1916.</li> <li>O'Brien J, Wilson I, Orton T, Pognan F. 2000. Investigation of the Alamar Blue (resazurin) fluorescent dye for the assessment of mammalian cell cytotoxicity. European journal of biochemistry / FEBS 267(17): 5421-5426.</li> <li>Repetto G, del Peso A, Zurita JL. 2008. Neutral red uptake assay for the estimation of cell viability/cytotoxicity. Nature protocols 3(7): 1125-1131.</li> </ul> AOPWiki 2016-11-29T18:41:22

2026-09-02T04:23:51

Decrease, Growth

Individual

Decreased growth refers to a reduction in size and/or weight of a tissue, organ or individual organism. Growth is normally controlled by growth factors and mainly achieved through cell proliferation (Conlon 1999).

Growth can be indicated by measuring weight, length, total volume, and/or total area of a tissue, organ or individual organism.   Revised version (non-endorsed, added by You Song, 02/09/2026) Growth can be measured as a change in size, mass, biomass, length, area, volume, or growth rate of a tissue, organ, or whole organism over a defined exposure period. The appropriate measurement depends on the biological system, life stage, and test species. At the organism level, growth is commonly assessed by measuring body weight, wet weight, dry weight, body length, standard length, total length, shell length, shoot height, root length, frond number, frond area, cell density, biomass, or relative growth rate. Growth inhibition is typically expressed as a statistically significant reduction relative to the control, or as an effect concentration causing a defined percentage reduction in growth, such as ECx, ErCx, EyCx, LOEC, NOEC, or benchmark concentration/dose values. For unicellular algae and cyanobacteria, growth is commonly quantified from changes in biomass over time. Biomass may be estimated using direct cell counts, electronic particle counters, microscopy, optical density, fluorescence, chlorophyll-related measurements, or other validated biomass proxies. Growth inhibition is commonly calculated from average specific growth rate and yield. For aquatic macrophytes such as Lemna spp., growth is typically quantified using frond number and at least one additional growth-related variable, such as total frond area, dry weight, fresh weight, or image-based area measurements. Digital imaging, flatbed scanning, stereomicroscopy, or automated image-analysis tools can be used to quantify frond area and related morphological endpoints. For terrestrial plants, growth can be measured using seedling emergence, survival, shoot height, root length, fresh or dry biomass, leaf area, and visual signs of phytotoxicity such as chlorosis, necrosis, deformation, or delayed development. Measurements may be made using rulers or calipers, analytical balances, scanners, digital imaging, or plant image-analysis software. For aquatic invertebrates, growth may be assessed using body length, body area, wet weight, dry weight, developmental stage, or size at defined time points. In small organisms such as Daphnia, body length is often measured from microscope or stereomicroscope images using calibrated image-analysis software. For fish and amphibians, growth is commonly assessed using wet weight, dry weight, standard length, total length, snout–vent length, condition factor, developmental stage, and specific growth rate. Measurements may be obtained using balances, calipers, digital imaging, or stereomicroscopy, depending on organism size and life stage. For mammals and other vertebrates in repeated-dose or reproductive/developmental toxicity studies, growth-related endpoints are typically evaluated using body weight, body-weight gain, food and water consumption, pup or offspring weight, litter growth, organ weight, and developmental landmarks. These endpoints are usually interpreted together with clinical observations, survival, pathology, and reproductive or developmental parameters. Because growth is an integrative apical endpoint, measurement should be performed over a biologically appropriate time window and interpreted in relation to survival, developmental delay, nutritional status, reproductive output, and general toxicity. Direct measurements of organismal size, biomass, or growth rate provide the strongest evidence for this key event, whereas indirect indicators such as altered morphology, reduced condition factor, or reduced organ weight may provide supporting evidence depending on biological context. Relevant OECD Test Guidelines include, but are not limited to: <ul> <li> OECD TG 201: Freshwater Alga and Cyanobacteria, Growth Inhibition Test. This guideline directly assesses inhibition of algal or cyanobacterial growth, typically using average specific growth rate and yield as response variables. </li> <li> OECD TG 208: Terrestrial Plant Test: Seedling Emergence and Seedling Growth Test. This guideline assesses effects on seedling emergence and early growth of terrestrial plants, including biomass, shoot height, and visible phytotoxic effects. </li> <li> OECD TG 211: Daphnia magna Reproduction Test. Although the primary endpoint is reproductive output, the test can provide chronic organism-level information relevant to population performance, and growth-related observations such as body size may be reported as supporting endpoints when included in the study design. </li> <li> OECD TG 212: Fish, Short-term Toxicity Test on Embryo and Sac-Fry Stages. This guideline assesses toxicity during early fish development from fertilized egg to the end of the sac-fry stage. Growth-related developmental observations may support interpretation of early-life-stage impairment. </li> <li> OECD TG 215: Fish, Juvenile Growth Test. This guideline directly evaluates effects on juvenile fish growth. Effects are expressed using growth rate, and concentration-response analysis can be used to estimate concentrations causing a defined percentage change in growth rate. </li> <li> OECD TG 221: Lemna sp. Growth Inhibition Test. This guideline directly assesses effects on vegetative growth of Lemna spp. using average specific growth rate and yield, commonly based on frond number and additional variables such as frond area or biomass. </li> <li> OECD TG 228: Determination of Developmental Toxicity to Dipteran Dung Flies. This guideline is relevant where chemical exposure affects development and growth-related performance in terrestrial invertebrates. </li> <li> OECD TG 241: Larval Amphibian Growth and Development Assay. This guideline evaluates growth and development in amphibians from fertilization through the early juvenile period. </li> <li> OECD TG 407: Repeated Dose 28-day Oral Toxicity Study in Rodents. This guideline includes body weight and food/water consumption measurements as part of the assessment of repeated-dose systemic toxicity. </li> <li> OECD TG 408: Repeated Dose 90-day Oral Toxicity Study in Rodents. This guideline includes body weight and related clinical observations as part of subchronic systemic toxicity assessment. </li> <li> OECD TG 416: Two-Generation Reproduction Toxicity. This guideline evaluates effects on reproduction as well as growth and development of offspring across generations. </li> <li> OECD TG 422: Combined Repeated Dose Toxicity Study with the Reproduction/Developmental Toxicity Screening Test. This guideline includes body weight, food/water consumption, offspring observations and measurements, and developmental parameters. </li> <li> OECD TG 443: Extended One-Generation Reproductive Toxicity Study. This guideline evaluates reproductive and developmental effects, including health, growth, development, and function of offspring following pre- and postnatal exposure. </li> <li> OECD TG 453: Combined Chronic Toxicity/Carcinogenicity Studies. This guideline includes body weight and body-weight gain as part of the evaluation of chronic systemic toxicity and carcinogenicity. </li> </ul>

Taxonomic applicability domain This key event is in general applicable to all eukaryotes.   Life stage applicability domain This key event is applicable to early life stages such as embryo and juvenile.   Sex applicability domain This key event is sex-unspecific.

High Unspecific

High

Embryo

High

Juvenile

Moderate Moderate Moderate High High High Moderate

Conlon I, Raff M. 1999. Size control in animal development. Cell 96:235-244. DOI: 10.1016/s0092-8674(00)80563-2.  AOPWiki 2018-05-24T15:24:11

2026-09-02T03:23:17

<upstream-id>32f38065-e41d-4339-943c-cbabd1252995</upstream-id> <downstream-id>962b5ff3-d0f6-44d9-ad6a-840b859708e4</downstream-id> This KER describes the causal and predictive relationship by which an increase in reactive oxygen species leads to oxidative stress. ROS include superoxide, hydrogen peroxide, hydroxyl radical and secondary oxygen-derived reactive products. At low or transient levels, ROS can participate in normal cell signaling. However, when ROS production, flux or local concentration exceeds the capacity of enzymatic and non-enzymatic antioxidant defenses, the redox balance of the biological system shifts toward an oxidizing state, producing oxidative stress (Schieber and Chandel, 2014; Sies et al., 2017).     The downstream KE, oxidative stress, is not identical to increased ROS. Rather, it represents a systems-level imbalance between pro-oxidant pressure and antioxidant or repair capacity. The KER therefore depends not only on the magnitude of ROS increase, but also on the duration, localization and chemical identity of the ROS, the capacity of scavenging systems such as glutathione, superoxide dismutase, catalase and glutathione peroxidases, and the ability of the cell or organism to activate adaptive redox responses such as NRF2 signaling (Halliwell and Gutteridge, 2015; Griendling et al., 2016; Sies et al., 2017). Within the ROS-growth AOP network, Relationship 2009 functions as a shared upstream KER. It connects the early measurable perturbation of increased ROS to the central hub event of oxidative stress, from which downstream AOP branches proceed through oxidative DNA damage, lipid peroxidation, protein oxidation, mitochondrial dysfunction, ATP depletion, altered cell proliferation, cell injury/death and decreased growth. This KER should remain modular and stressor-agnostic; stressor-specific mechanisms of ROS generation should be described in MIE or stressor sections where appropriate.

Evidence for this KER was assembled from three complementary sources. First, existing AOP-Wiki content was reviewed, including the current Relationship 2009 page and the corresponding KE pages for Event 1115 and Event 1392. These pages define the upstream and downstream events and document existing applicability and evidence summaries (AOP-Wiki, 2026a, 2026b, 2026c). Second, the ROS-growth literature review and data-mining exercise was used to identify studies in which ROS and oxidative stress or antioxidant-response endpoints were measured in the same biological system following exposure to relevant stressors. Third, targeted searches of mechanistic reviews and primary studies were used to support biological plausibility, empirical concordance and domain-of-applicability statements.     The evidence search strategy followed the AI-human hybrid workflow used for the ROS-growth AOPN. Search terms were developed for the upstream and downstream KEs, including “reactive oxygen species”, “ROS”, “oxidative stress”, “antioxidant enzyme”, “superoxide dismutase”, “catalase”, “glutathione peroxidase”, “glutathione”, “Nrf2”, “redox imbalance”, and representative stressor terms such as paraquat, hydrogen peroxide, copper, cadmium, chlorothalonil, radiation, hypoxia/reoxygenation and pathogen infection. AOP-helpFinder and targeted database searches were used to identify candidate studies, and ChatGPT (OpenAI, San Francisco, CA, USA)-assisted screening was used only for preliminary prioritization and metadata extraction. Final inclusion, interpretation and weight-of-evidence calls were made by expert review of the original sources. Studies were prioritized when they measured both upstream and downstream events, reported dose or concentration and exposure duration, used biologically interpretable oxidative stress endpoints, and provided information relevant to dose-response, temporal or incidence concordance. Endpoints considered supportive of the downstream KE included antioxidant enzyme induction or depletion, GSH/GSSG changes, NRF2/ARE pathway activation, lipid peroxidation, and broader redox imbalance. Direct ROS measurements were given greater weight than studies in which ROS production was inferred solely from the stressor mode of action.

Biological plausibility of Relationship 2009 is high. ROS are produced endogenously by mitochondrial electron transport, oxidase enzymes, peroxisomal reactions, photosynthetic electron transport and immune-cell oxidant systems, and they may also be generated by redox-cycling chemicals, metals, radiation and other stressors (Bedard and Krause, 2007; Murphy, 2009; Halliwell and Gutteridge, 2015). Oxidative stress is defined as a disturbance in the balance between oxidants and antioxidants in favor of oxidants, leading to disruption of redox signaling and/or molecular damage (Sies et al., 2017). Therefore, a sufficient increase in ROS has a direct mechanistic basis for causing oxidative stress when antioxidant and repair capacity are exceeded. This relationship is also strongly supported by the known biology of antioxidant defenses. Superoxide dismutases convert superoxide to hydrogen peroxide; catalase, glutathione peroxidases and peroxiredoxins reduce hydrogen peroxide and organic peroxides; and glutathione and thioredoxin systems maintain protein thiol redox balance. Increased ROS can consume these defenses, oxidize redox-sensitive proteins, activate NRF2-dependent antioxidant response pathways, and produce oxidative modification of lipids, proteins and nucleic acids (Schieber and Chandel, 2014; Griendling et al., 2016; Sies et al., 2017).

Empirical support for this KER is high. Numerous studies across taxa and stressor classes demonstrate concordant increases in ROS or ROS-generating conditions and oxidative stress endpoints. The strongest evidence comes from studies measuring both ROS and antioxidant-response or oxidative-stress biomarkers in the same biological system. Several examples from the ROS-growth concordance table are summarized below.   <table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <thead> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:106px"> Biological system </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:86px"> Stressor </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:96px"> Exposure </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:130px"> Evidence for KE1115 (ROS increase) </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:139px"> Evidence for KE1392 (oxidative stress increase) </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:130px"> Concordance interpretation </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:91px"> Reference </td> </tr> </thead> <tbody> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:106px"> Chlorella vulgaris </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:86px"> Paraquat </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:96px"> 24 h; 0-1.0 uM </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> DCFH-DA fluorescence increased; LOEC for ROS approximately 0.5 uM paraquat. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> SOD, POD and CAT activities increased at similar concentrations; antioxidant enzymes were approximately 3-5-fold above control at 0.5 uM. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Dose concordance supports ROS increase leading to oxidative stress in a photosynthetic eukaryote. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:91px"> Qian et al. (2009) </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:106px"> Daphnia magna </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:86px"> Paraquat </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:96px"> 48 h; 0.01-10 uM </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> ROS induction threshold reported around 0.1 uM paraquat. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> SOD, CAT and GPx induction observed around 0.5 uM; TBARS increased around 1 uM. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> ROS occurs at lower or similar concentrations than antioxidant and damage markers, supporting dose concordance. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:91px"> Barata et al. (2005) </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:106px"> Trachinotus ovatus </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:86px"> Streptococcus agalactiae infection </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:96px"> 0-120 h; 2 x 10^7 CFU/fish </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> ROS increased early, with maximum response around 6 h. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Antioxidant enzyme activities and antioxidant gene expression changed following the ROS response. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Temporal concordance supports ROS preceding redox-response activation during pathogen-induced oxidative stress. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:91px"> Gao et al. (2022) </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:106px"> Mus musculus </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:86px"> Copper sulfate </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:96px"> 42 days; 0-40 mg/kg bw </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> ROS increased at the lowest tested dose by day 42. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Antioxidant markers including SOD, GSH-related responses and oxidative stress/inflammatory indicators changed with exposure. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Concordant ROS and antioxidant-response changes support the relationship in mammals. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:91px"> Jian et al. (2020) </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:106px"> Marine bivalves </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:86px"> Chlorothalonil </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:96px"> 96 h; 0.1-10 ug/L </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Stressor is thiol-reactive and associated with oxidative challenge; direct ROS was not the primary endpoint. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> SOD, CAT and GPx activity changes and MDA/TBARS increases occurred in gill tissues. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Supports downstream oxidative stress following a stressor known to disturb redox balance; direct ROS evidence is weaker than in rows with ROS measurement. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:91px"> Haque et al. (2019) </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:106px"> Mya arenaria </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:86px"> Cyclic hypoxia/reoxygenation </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:96px"> 3 weeks; repeated low oxygen exposure </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Hypoxia/reoxygenation is a recognized ROS-generating condition in mitochondria. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:139px"> Mitochondrial proton leak and oxidative stress-related bioenergetic changes were elevated under cyclic hypoxia. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:130px"> Supports environmental modulation of ROS-associated oxidative stress and mitochondrial response. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:91px"> Ouillon et al. (2021) </td> </tr> </tbody> </table>

The main uncertainties relate to measurement specificity and context dependence. ROS are chemically diverse and often short-lived, so different assays may detect different ROS species or generalized oxidant-dependent probe oxidation rather than a single ROS concentration. DCFH-DA and related probes are useful screening tools but can be influenced by peroxidases, metals, light, probe loading and cellular esterase activity (Wardman, 2007; Kalyanaraman et al., 2012). Consequently, apparent ROS increases must be interpreted with assay limitations in mind. A second uncertainty is that ROS increases are not always adverse. Transient or localized ROS signals may activate adaptive stress responses and restore redox homeostasis without producing sustained oxidative stress. Conversely, oxidative stress may be inferred from antioxidant enzyme induction or oxidative damage biomarkers in studies where ROS were not directly measured. These cases support the KER less strongly than studies with direct, temporally resolved ROS measurements. Differences among taxa, life stages, tissues, exposure durations and antioxidant capacities may alter the threshold at which increased ROS becomes oxidative stress.

<table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <thead> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:120px"> Modulating factor </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:158px"> Details </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:235px"> Effect on the KER </td> <td style="background-color:#d9eaf7; border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:1px solid #bfbfbf; vertical-align:top; width:216px"> Supporting evidence </td> </tr> </thead> <tbody> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:120px"> Antioxidant capacity </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Levels and activities of GSH, SOD, CAT, GPx, peroxiredoxins, thioredoxin systems and antioxidant vitamins. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:235px"> Higher antioxidant capacity buffers ROS and raises the threshold for oxidative stress; depleted or impaired antioxidant systems lower the threshold. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:216px"> Halliwell and Gutteridge (2015); Sies et al. (2017). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:120px"> NRF2/ARE pathway activation </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Induction of antioxidant and detoxification genes through NRF2-dependent signaling. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:235px"> Adaptive NRF2 activation may reduce progression from increased ROS to sustained oxidative stress, but strong NRF2 activation can also serve as evidence that ROS has perturbed redox homeostasis. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:216px"> Schieber and Chandel (2014); Sies et al. (2017); AOP-Wiki (2026c). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:120px"> Subcellular localization of ROS </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Mitochondria, chloroplasts, peroxisomes, membranes, nuclei and phagosomes differ in ROS production and local antioxidant buffering. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:235px"> Localized ROS production can cause oxidative stress in a specific compartment even when whole-cell ROS measurements are modest. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:216px"> Murphy (2009); Griendling et al. (2016). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:120px"> Exposure duration and recovery time </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Acute pulses, chronic low-level exposure and repeated stress can produce different redox outcomes. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:235px"> Short pulses may be buffered or adaptive; sustained or repeated ROS elevations increase the probability of oxidative stress. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:216px"> Sies et al. (2017); Ouillon et al. (2021). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:120px"> Oxygen availability and hypoxia/reoxygenation </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Oxygen tension affects mitochondrial electron transport and ROS formation. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:235px"> Reoxygenation after hypoxia can increase mitochondrial ROS and enhance oxidative stress. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:216px"> Ouillon et al. (2021). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:120px"> Temperature and metabolic rate </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Temperature and metabolic demand alter oxygen flux, mitochondrial activity and antioxidant capacity. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:235px"> Higher metabolic activity or thermal stress can increase ROS formation and shift the balance toward oxidative stress. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:216px"> Tseng et al. (2011). </td> </tr> <tr> <td style="border-bottom:1px solid #bfbfbf; border-left:1px solid #bfbfbf; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:120px"> Stressor chemistry </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:158px"> Redox cycling, metal-catalyzed reactions, radiation and mitochondrial inhibition generate ROS by different mechanisms. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:235px"> Stressor type influences the ROS species, localization, time course and threshold for oxidative stress. </td> <td style="border-bottom:1px solid #bfbfbf; border-left:none; border-right:1px solid #bfbfbf; border-top:none; vertical-align:top; width:216px"> Bedard and Krause (2007); Murphy (2009); Qian et al. (2009); Gao et al. (2022). </td> </tr> </tbody> </table>

Quantitative understanding of this KER is low to moderate. The qualitative relationship is well established: oxidative stress occurs when ROS production or flux exceeds antioxidant and repair capacity. However, a universal quantitative threshold for ROS leading to oxidative stress cannot be defined because the relationship depends strongly on ROS species, subcellular localization, measurement method, antioxidant capacity, exposure duration, organism, cell type and co-stressors (Kalyanaraman et al., 2012; Griendling et al., 2016; Sies et al., 2017).

Response-response information is available in specific systems. For example, in Chlorella vulgaris exposed to paraquat, ROS and antioxidant enzyme responses were observed at approximately 0.5 uM after 24 h, indicating local dose concordance between the upstream and downstream events (Qian et al., 2009). In Daphnia magna exposed to paraquat, ROS induction was reported at lower concentrations than antioxidant enzyme and TBARS responses, supporting an expected dose sequence in which ROS increases precede oxidative stress endpoints (Barata et al., 2005). These examples provide semi-quantitative support, but they cannot be generalized across all taxa or stressors.

The time scale of the KER can range from minutes to hours for ROS-sensitive signaling and antioxidant pathway activation, and from hours to days for measurable changes in antioxidant enzyme activities, glutathione status or oxidative damage biomarkers. In pathogen-exposed golden pompano, ROS increased early, followed by antioxidant enzyme and gene expression responses over subsequent hours to days, supporting temporal concordance (Gao et al., 2022).

Known feedback and feedforward mechanisms influence the linkage. NRF2-dependent antioxidant responses can reduce ROS and restore homeostasis, whereas mitochondrial dysfunction, lipid peroxidation, inflammation and redox-sensitive signaling can amplify ROS generation and sustain oxidative stress. These feedbacks make the KER dynamic and nonlinear, particularly under chronic exposure or repeated stress.

High Unspecific

High

All life stages

High High High High High High

This KER is broadly applicable to aerobic eukaryotic systems in which ROS production and antioxidant buffering can be measured. The current AOP-Wiki relationship page identifies human, mouse and rat with high evidence, but the ROS-growth evidence base supports extension to algae, fish, crustaceans, mollusks and other organisms relevant to environmental toxicology (AOP-Wiki, 2026a). The relationship is expected to be conserved because it is based on redox chemistry and conserved antioxidant-defense systems rather than on a taxon-specific receptor or signaling pathway. The applicability domain should nevertheless be bounded by biological context and measurement feasibility. This KER is most relevant when the upstream KE is a measurable increase in ROS and the downstream KE is a measurable redox imbalance or antioxidant-response state rather than a distal oxidative damage endpoint alone. In organisms or compartments where ROS cannot be measured directly, evidence may rely on antioxidant-response or oxidative damage biomarkers, but these should be interpreted as indirect support. Applicability is strongest when ROS and oxidative stress endpoints are measured in the same system under the same exposure conditions.

AOP-Wiki. 2026a. Relationship 2009: Increase, ROS leads to Increase, Oxidative stress. AOP-Wiki. Available at: https://aopwiki.org/relationships/2009. Accessed 14 May 2026. AOP-Wiki. 2026b. Event 1115: Increase, Reactive oxygen species. AOP-Wiki. Available at: https://aopwiki.org/events/1115. Accessed 14 May 2026. AOP-Wiki. 2026c. Event 1392: Increase, Oxidative stress. AOP-Wiki. Available at: https://aopwiki.org/events/1392. Accessed 14 May 2026. Barata C, Varo I, Navarro JC, Arun S, Porte C. 2005. Antioxidant enzyme activities and lipid peroxidation in the freshwater cladoceran Daphnia magna exposed to redox cycling compounds. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology 140(2):175-186. https://doi.org/10.1016/j.cca.2005.01.013. Bedard K, Krause KH. 2007. The NOX family of ROS-generating NADPH oxidases: physiology and pathophysiology. Physiological Reviews 87(1):245-313. https://doi.org/10.1152/physrev.00044.2005. Dickinson BC, Chang CJ. 2011. Chemistry and biology of reactive oxygen species in signaling or stress responses. Nature Chemical Biology 7(8):504-511. https://doi.org/10.1038/nchembio.607. Esperanza M, Cid A, Herrero C, Rioboo C. 2015. Acute effects of a prooxidant herbicide on the microalga Chlamydomonas reinhardtii: screening cytotoxicity and genotoxicity endpoints. Aquatic Toxicology 165:210-221. https://doi.org/10.1016/j.aquatox.2015.06.004. Gao J, Liu M, Guo H, Zhu K, Liu B, Liu B, Zhang N, Sun X, Jiang S, Zhang D. 2022. ROS induced by Streptococcus agalactiae activate inflammatory responses via the TNF-alpha/NF-kappaB signaling pathway in golden pompano Trachinotus ovatus (Linnaeus, 1758). Antioxidants 11(9):1809. https://doi.org/10.3390/antiox11091809. Griendling KK, Touyz RM, Zweier JL, Dikalov S, Chilian W, Chen YR, Harrison DG, Bhatnagar A. 2016. Measurement of reactive oxygen species, reactive nitrogen species, and redox-dependent signaling in the cardiovascular system: a scientific statement from the American Heart Association. Circulation Research 119(5):e39-e75. https://doi.org/10.1161/RES.0000000000000110. Halliwell B, Gutteridge JMC. 2015. Free Radicals in Biology and Medicine. 5th ed. Oxford: Oxford University Press. Haque MN, Eom HJ, Nam SE, Shin YK, Rhee JS. 2019. Chlorothalonil induces oxidative stress and reduces enzymatic activities of Na+/K+-ATPase and acetylcholinesterase in gill tissues of marine bivalves. PLoS ONE 14(4):e0214236. https://doi.org/10.1371/journal.pone.0214236. Jian Z, Guo H, Liu H, Cui H, Fang J, Zuo Z, Deng J, Li Y, Wang X, Zhao L. 2020. Oxidative stress, apoptosis and inflammatory responses involved in copper-induced pulmonary toxicity in mice. Aging 12(17):16867-16886. https://doi.org/10.18632/aging.103585. Kalyanaraman B, Darley-Usmar V, Davies KJA, Dennery PA, Forman HJ, Grisham MB, Mann GE, Moore K, Roberts LJ II, Ischiropoulos H. 2012. Measuring reactive oxygen and nitrogen species with fluorescent probes: challenges and limitations. Free Radical Biology and Medicine 52(1):1-6. https://doi.org/10.1016/j.freeradbiomed.2011.09.030. Murphy MP. 2009. How mitochondria produce reactive oxygen species. Biochemical Journal 417(1):1-13. https://doi.org/10.1042/BJ20081386. Ouillon N, Sokolov EP, Otto S, Rehder G, Sokolova IM. 2021. Effects of variable oxygen regimes on mitochondrial bioenergetics and reactive oxygen species production in a marine bivalve, Mya arenaria. Journal of Experimental Biology 224(4):jeb237156. https://doi.org/10.1242/jeb.237156. Pan YX, Luo Z, Zhuo MQ, Wei CC, Chen GH, Song YF. 2018. Oxidative stress and mitochondrial dysfunction mediated Cd-induced hepatic lipid accumulation in zebrafish Danio rerio. Aquatic Toxicology 199:12-20. https://doi.org/10.1016/j.aquatox.2018.03.017. Qian H, Chen W, Sun L, Jin Y, Liu W, Fu Z. 2009. Inhibitory effects of paraquat on photosynthesis and the response to oxidative stress in Chlorella vulgaris. Ecotoxicology 18(5):537-543. https://doi.org/10.1007/s10646-009-0311-8. Schieber M, Chandel NS. 2014. ROS function in redox signaling and oxidative stress. Current Biology 24(10):R453-R462. https://doi.org/10.1016/j.cub.2014.03.034. Sies H, Berndt C, Jones DP. 2017. Oxidative stress. Annual Review of Biochemistry 86:715-748. https://doi.org/10.1146/annurev-biochem-061516-045037. Tseng YC, Chen RD, Lucassen M, Schmidt MM, Dringen R, Abele D, Hwang PP. 2011. Exploring uncoupling proteins and antioxidant mechanisms under acute cold exposure in brains of fish. PLoS ONE 6(3):e18180. https://doi.org/10.1371/journal.pone.0018180. Wardman P. 2007. Fluorescent and luminescent probes for measurement of oxidative and nitrosative species in cells and tissues: progress, pitfalls, and prospects. Free Radical Biology and Medicine 43(7):995-1022. https://doi.org/10.1016/j.freeradbiomed.2007.06.026. AOPWiki 2019-12-03T20:49:51

2026-06-23T06:57:32

<upstream-id>962b5ff3-d0f6-44d9-ad6a-840b859708e4</upstream-id> <downstream-id>09a12f9d-7c68-43a0-8723-f6594a18aadf</downstream-id> This KER describes the relationship by which an increase in oxidative stress leads to increased protein oxidation. Oxidative stress represents a state in which oxidant generation or antioxidant depletion shifts the biological system toward a pro-oxidant condition. Under these conditions, reactive oxygen and nitrogen species, lipid-derived reactive aldehydes, metal-catalyzed oxidants and oxidized thiol/disulfide systems can modify proteins directly or indirectly. Protein oxidation includes irreversible modifications such as protein carbonyl formation, oxidation of aromatic and sulfur-containing amino acids, backbone fragmentation, crosslinking and aggregation, as well as reversible or regulatory modifications such as disulfide formation, S-glutathionylation, S-nitrosylation and other redox post-translational modifications (Stadtman and Levine, 2003; Dalle-Donne et al., 2006; Davies, 2016). The relationship is biologically plausible because proteins are abundant cellular targets and many amino acid side chains react with oxidants or with secondary products of oxidative stress. Increased oxidative stress raises the probability that susceptible proteins will undergo oxidation, particularly when antioxidant defenses, reductive repair systems, proteasomal degradation or protein turnover cannot maintain proteostasis. The downstream KE therefore reflects a measurable biochemical consequence of the upstream oxidative-stress state.

Evidence for this KER was assembled from the ROS-growth AOP network literature review and data-mining workflow, targeted searches of the primary literature, AOP-Wiki records, and mechanistic reviews of protein oxidation chemistry. The evidence-collection process followed the AOP-Wiki KER page template, including structured consideration of biological applicability, KER description, evidence collection strategy, evidence supporting the KER, modulating factors, quantitative understanding, domain of applicability and references.     The search strategy focused on studies that measured oxidative stress and protein oxidation in the same biological system, or that provided strong mechanistic support for the transition from oxidative stress to protein oxidation. Search concepts included "oxidative stress", "reactive oxygen species", "protein oxidation", "protein carbonyl", "carbonylation", "oxidized proteins", "protein glutathionylation", "thiol oxidation", "redox proteomics", "AOPP", "hydrogen peroxide", "cadmium", "copper", "paraquat", "temperature stress", "salinity stress", "bivalve", "fish", "Chlamydomonas", "human cells", and "mammalian cells". PubMed, Web of Science, Google Scholar, AOP-Wiki, and the curated ROS-growth concordance table were consulted. AOP-helpFinder and preliminary text-mining were used to identify co-occurrence of event-related terms, followed by overlap analysis to remove redundant records and exclude taxa-irrelevant or low-priority literature. Large language model-assisted screening was used only to extract candidate metadata and prioritize abstracts and full-text records. Final inclusion, interpretation and weight-of-evidence calls were made manually by expert review. Mechanistic reviews were used to support biological plausibility, while primary experimental studies were prioritized for empirical support, especially when oxidative stress and protein oxidation endpoints were measured in the same exposure context.

Biological plausibility of this KER is high. Oxidative stress produces or reflects oxidizing conditions that can modify proteins through multiple well-established chemical mechanisms. Hydroxyl radicals, peroxyl radicals, singlet oxygen, hypochlorous acid, peroxynitrite and metal-catalyzed oxidants can oxidize amino acid side chains, while secondary products of lipid peroxidation, such as reactive aldehydes, can form protein adducts and carbonyl derivatives. These processes produce measurable protein carbonyls, oxidized methionine, oxidized cysteine residues, disulfides, protein hydroperoxides, crosslinks and fragmented or aggregated proteins (Stadtman and Levine, 2003; Dalle-Donne et al., 2006; Davies, 2016). The structural and functional relationship between the two KEs is direct. The upstream KE increases the oxidizing chemical environment, and the downstream KE is the covalent modification of protein targets under that oxidizing environment. Because proteins are abundant and essential for enzyme activity, signaling, structural integrity and energy metabolism, protein oxidation is a broadly expected consequence of oxidative stress when protective and repair mechanisms are insufficient.

Empirical support for this KER is moderate to high. Multiple studies in diverse systems show that oxidative-stress conditions coincide with or precede increases in protein oxidation markers, especially protein carbonylation, oxidized thiols or glutathionylated proteins. The strongest evidence comes from experiments in which oxidative stress biomarkers and protein oxidation endpoints were measured in the same biological system and exposure context. However, the empirical evidence is not uniformly high because many studies measure protein oxidation alone as an oxidative damage endpoint, without direct upstream ROS or redox measurements in the same time course.   <table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <tbody> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:154px"> Biological system </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; width:163px"> Stressor or condition </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; width:307px"> Evidence relevant to KER </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; width:182px"> Interpretation </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Chlamydomonas reinhardtii </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Cadmium or hydrogen peroxide / oxidative stress conditions </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:307px"> Proteomic analyses identified protein carbonylation and redox modifications including glutathionylation of photosynthetic and metabolic proteins under oxidative stress conditions (Zaffagnini et al., 2012). </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:182px"> Supports occurrence of protein oxidation under oxidative-stress conditions in photosynthetic eukaryotes. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Zebrafish brain </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Acute cold exposure </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:307px"> Protein carbonyls increased by 38% within 1 h after cold exposure, with increased antioxidant response markers over the same early time frame (Tseng et al., 2011). </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:182px"> Supports temporal association between oxidative stress response and protein oxidation in fish. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Freshwater fish Channa punctata </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Deltamethrin, endosulfan and paraquat </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:307px"> Protein carbonyls were proposed and measured as biomarkers of exposure to oxidative-stress-inducing pesticides (Parvez and Raisuddin, 2005). </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:182px"> Supports stressor-induced protein oxidation in fish exposed to pro-oxidant pesticides. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Mytilus galloprovincialis hemocytes </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Cadmium or 17 beta-estradiol </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:307px"> Redox parameters were altered by micromolar concentrations of stressors, consistent with oxidative stress and linked signaling processes in mussel hemocytes (Koutsogiannaki et al., 2014). </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:182px"> Supports relevance of oxidative stress/protein-oxidation processes in molluscan immune cells. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Mammalian / human cell systems </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Hydrogen peroxide and related oxidants </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:307px"> Live-cell fluorescent detection approaches demonstrate oxidative stress-induced carbonylation of biomolecules, including proteins (Mukherjee et al., 2015). </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:182px"> Supports direct oxidative stress-induced carbonylation in mammalian cell systems. </td> </tr> </tbody> </table> <h2> </h2>

A major uncertainty is that protein oxidation comprises many different chemical modifications with different reversibility, biological consequences and measurement approaches. Protein carbonyls are widely used as relatively stable markers, but they represent only one subset of oxidative protein damage. Thiol oxidation, methionine oxidation and glutathionylation may be reversible or regulatory, while carbonylation and aggregation are often associated with irreversible damage. Therefore, different studies may use different operational definitions of protein oxidation, making quantitative comparison difficult (Dalle-Donne et al., 2006; Davies, 2016). A second uncertainty is that oxidative stress is often inferred from antioxidant enzyme activity, glutathione status or damage endpoints rather than directly measured ROS flux. As a result, some empirical studies demonstrate co-occurrence of oxidative-stress markers and protein oxidation but cannot establish the exact sequence of events. Conversely, protein oxidation may arise secondarily from lipid peroxidation products, inflammation, metal-catalyzed reactions or impaired protein turnover, so the upstream oxidative-stress KE should be interpreted as a redox-state driver rather than a single chemical species. No strong contradictory evidence was identified for the general relationship that oxidative stress can increase protein oxidation.

<table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <tbody> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; width:163px"> Modulating factor </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; width:211px"> Details </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; width:230px"> Influence on KER </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; width:163px"> Supporting evidence </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Antioxidant and reductive capacity </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Glutathione, thioredoxin, glutaredoxin, peroxiredoxins, catalase, superoxide dismutase and related systems. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:230px"> Higher antioxidant/reductive capacity decreases the probability or magnitude of protein oxidation for a given oxidative challenge; depletion increases sensitivity. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Sies et al., 2017; Rouhier et al., 2015; Zaffagnini et al., 2012. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Metal availability </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Iron, copper, cadmium and other redox-active or thiol-reactive metals. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:230px"> Transition metals and thiol-reactive metals can promote site-specific oxidation, protein carbonylation or altered thiol redox state. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Stadtman and Levine, 2003; Parvez and Raisuddin, 2005; Koutsogiannaki et al., 2014. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Protein composition and localization </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Proteins rich in cysteine, methionine, aromatic residues or metal-binding sites; mitochondrial, chloroplast and membrane-associated proteins. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:230px"> Susceptible proteins and proteins located near ROS sources are more likely to undergo oxidation. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Davies, 2016; Dalle-Donne et al., 2006. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Proteostasis and repair capacity </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Proteasome activity, autophagy, methionine sulfoxide reductases, thiol-disulfide exchange systems and protein turnover. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:230px"> Efficient repair and degradation can reduce accumulation of oxidized proteins even when oxidative stress occurs. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Dalle-Donne et al., 2006; Davies, 2016. </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Exposure duration and intensity </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Acute versus chronic oxidative stress; pulse versus sustained oxidant generation. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:230px"> Longer or more intense oxidative stress increases accumulation of stable oxidative protein damage, especially carbonyls and aggregates. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Mukherjee et al., 2015; Tseng et al., 2011. </td> </tr> </tbody> </table>

Quantitative understanding of this KER is moderate. The qualitative biochemical relationship between oxidative stress and protein oxidation is well established, and response-response relationships exist in some experimental systems.

However, a general quantitative function predicting the magnitude of protein oxidation from a given oxidative-stress measurement has not been established across taxa, tissues, protein classes, stressors and assay methods. Quantitative prediction is complicated because the upstream KE can be measured by multiple endpoints, including ROS probes, glutathione status, antioxidant enzyme responses or pathway activation, while the downstream KE can be measured by protein carbonyls, oxidized thiols, methionine oxidation, glutathionylation, AOPP or redox proteomics.

The time scale of the linkage can range from minutes to days. Oxidation of susceptible amino acid residues may occur rapidly during an acute oxidant pulse, whereas accumulation of stable carbonylated proteins, protein aggregates or proteomic changes may require longer exposure or exceed the capacity of repair and degradation systems. In zebrafish exposed to acute cold stress, protein carbonylation increased within 1 h, showing that the downstream KE can occur rapidly in vivo under oxidative-stress conditions (Tseng et al., 2011). In Chlamydomonas and mammalian cell systems, protein oxidation and carbonylation are also detectable under defined pro-oxidant exposure conditions (Zaffagnini et al., 2012; Mukherjee et al., 2015).

The linkage is expected to be nonlinear and threshold-dependent. Low or transient oxidative stress may lead to reversible redox signaling or repairable thiol modifications, whereas stronger or persistent oxidative stress is more likely to cause irreversible carbonylation, aggregation or loss of protein function. Quantitative evaluation is therefore strongest when upstream oxidative stress and downstream protein oxidation are measured in the same biological system across multiple exposure concentrations and time points.

Moderate Unspecific

Moderate

All life stages

High High High High Moderate

This KER is broadly applicable to aerobic biological systems in which oxidative stress and protein oxidation can be measured. It is particularly relevant to tissues and cellular compartments exposed to high oxidant flux, including mitochondria, chloroplasts, peroxisomes, inflammatory cells, gill and digestive tissues, nervous tissues and rapidly metabolizing cells. The relationship is expected to be conserved because it is based on fundamental redox chemistry and protein chemistry rather than on a taxon-specific receptor or signaling pathway. The KER should be applied with greatest confidence when upstream oxidative stress is assessed using direct or mechanistically interpretable redox endpoints and downstream protein oxidation is measured using specific markers such as protein carbonyls, oxidized thiols, methionine oxidation, AOPP, or redox proteomics. Applicability is weaker when protein oxidation is inferred only from broad stress responses or when oxidative stress and protein oxidation are not measured in the same biological context. Species, life stage and sex should be considered mainly as modifiers of sensitivity rather than determinants of whether the relationship can occur.

AOP-Wiki. Relationship 3632: Increase, Oxidative Stress leads to Increase, Protein oxidation. https://aopwiki.org/relationships/3632. Accessed 14 May 2026. Dalle-Donne I, Aldini G, Carini M, Colombo R, Rossi R, Milzani A. 2006. Protein carbonylation, cellular dysfunction, and disease progression. Journal of Cellular and Molecular Medicine 10(2):389-406. https://doi.org/10.1111/j.1582-4934.2006.tb00407.x. Davies MJ. 2016. Protein oxidation and peroxidation. Biochemical Journal 473(7):805-825. https://doi.org/10.1042/BJ20151227. Halliwell B, Gutteridge JMC. 2015. Free Radicals in Biology and Medicine. 5th ed. Oxford: Oxford University Press. Koutsogiannaki S, Franzellitti S, Fabbri E, Kaloyianni M. 2014. Oxidative stress parameters induced by exposure to either cadmium or 17 beta-estradiol on Mytilus galloprovincialis hemocytes: the role of signaling molecules. Aquatic Toxicology 146:186-195. https://doi.org/10.1016/j.aquatox.2013.11.005. Mukherjee K, Chio TI, Sackett DL, Bane SL. 2015. Detection of oxidative stress-induced carbonylation in live mammalian cells using a hydrazine-based fluorescent probe. Free Radical Biology and Medicine 84:11-21. https://doi.org/10.1016/j.freeradbiomed.2015.03.011. Parvez S, Raisuddin S. 2005. Protein carbonyls: novel biomarkers of exposure to oxidative stress-inducing pesticides in freshwater fish Channa punctata (Bloch). Environmental Toxicology and Pharmacology 20(1):112-117. https://doi.org/10.1016/j.etap.2004.11.002. Rouhier N, Cerveau D, Couturier J, Reichheld JP, Rey P. 2015. Involvement of thiol-based mechanisms in plant development. FEBS Letters 589(1):37-44. https://doi.org/10.1016/j.febslet.2014.11.021. Schieber M, Chandel NS. 2014. ROS function in redox signaling and oxidative stress. Current Biology 24(10):R453-R462. https://doi.org/10.1016/j.cub.2014.03.034. Sies H, Berndt C, Jones DP. 2017. Oxidative stress. Annual Review of Biochemistry 86:715-748. https://doi.org/10.1146/annurev-biochem-061516-045037. Stadtman ER, Levine RL. 2003. Free radical-mediated oxidation of free amino acids and amino acid residues in proteins. Amino Acids 25(3-4):207-218. https://doi.org/10.1007/s00726-003-0011-2. Tseng YC, Chen RD, Lucassen M, Schmidt MM, Dringen R, Abele D, Hwang PP. 2011. Exploring uncoupling proteins and antioxidant mechanisms under acute cold exposure in brains of fish. PLoS ONE 6(3):e18180. https://doi.org/10.1371/journal.pone.0018180. Zaffagnini M, Bedhomme M, Groni H, Marchand CH, Puppo C, Gontero B, Cassier-Chauvat C, Decottignies P, Lemaire SD. 2012. Glutathionylation in the photosynthetic model organism Chlamydomonas reinhardtii: a proteomic survey. Molecular & Cellular Proteomics 11(2):M111.014142. https://doi.org/10.1074/mcp.M111.014142. AOPWiki 2025-09-08T04:06:22

2026-06-23T07:04:47

<upstream-id>09a12f9d-7c68-43a0-8723-f6594a18aadf</upstream-id> <downstream-id>51152dd0-641f-4b5a-b8ed-bc9cb7de47d5</downstream-id>

AOPWiki 2025-09-08T04:37:55

2025-09-08T04:37:55

<upstream-id>51152dd0-641f-4b5a-b8ed-bc9cb7de47d5</upstream-id> <downstream-id>67451db7-2085-4c64-8106-9bac6970c68d</downstream-id>

AOPWiki 2025-09-08T04:38:03

2025-09-08T04:38:03

<upstream-id>67451db7-2085-4c64-8106-9bac6970c68d</upstream-id> <downstream-id>101ddfa7-61da-4d1d-913a-0228c6bb03d9</downstream-id> This key event relationship describes the causal and predictive link by which a decrease in the cellular adenosine triphosphate (ATP) pool leads to increased cell injury and/or cell death. ATP is required to maintain ion gradients, plasma membrane integrity, mitochondrial homeostasis, macromolecular repair, vesicular trafficking, and regulated cell death programs. When ATP depletion is sufficiently severe or prolonged, energy-dependent adaptive and repair processes fail, calcium and sodium homeostasis are disrupted, mitochondrial permeability transition may be promoted, and cells may undergo apoptosis, necrosis, necroptosis-like injury or mixed forms of cell death depending on cellular context and residual ATP availability (Nieminen et al., 1994; Leist et al., 1997; Bonora et al., 2012). The direction of this KER is from reduced ATP availability to increased cell injury/death. The KER is not intended to specify a single mode of cell death. Rather, it captures the general biological principle that loss of cellular energy supply increases the probability of irreversible cellular injury and death, with the exact death phenotype depending on cell type, severity of ATP depletion, duration of exposure, and availability of death-execution pathways.

The evidence base was assembled using the same structured strategy applied across the ROS-growth AOP network. Existing AOP-Wiki pages and OECD AOP reports were reviewed first to identify reusable KEs and related KERs. Particular attention was given to the mitochondrial energetic AOP series, including AOP 263 and AOP 264, because these AOPs contain the upstream event decreased ATP pool and downstream cellular or organismal outcomes relevant to growth inhibition and cell injury/death. Targeted literature searches were then conducted using combinations of terms related to ATP depletion, cellular ATP, energetic failure, mitochondrial dysfunction, metabolic inhibition, apoptosis, necrosis, cytotoxicity, cell viability, cell injury, mitochondrial permeability transition, calcium electroporation, rotenone, FCCP, CCCP, paraquat, cadmium, algae, bivalves, fish, mammalian cells and human cells. Primary studies were prioritized when they measured ATP levels and cell viability, cytotoxicity, apoptosis or necrosis in the same biological system and reported dose/concentration or time-course information. Mechanistic reviews were used to support biological plausibility, while primary experimental studies were used for empirical concordance and quantitative understanding. The evidence was curated for weight-of-evidence indicators including biological plausibility, temporal concordance, dose-response concordance, incidence concordance, evidence of threshold behavior, and intervention or rescue information. Studies were considered most informative when ATP depletion preceded or occurred at lower or similar exposure levels than cytotoxicity or cell death, or when restoration of energy metabolism reduced the downstream injury response.

The overall evidence supporting this KER is considered moderate to high. Biological plausibility is high because ATP is indispensable for cellular homeostasis and because severe ATP depletion is a well-established trigger of irreversible cell injury and death. Empirical support is moderate to high because multiple studies in mammalian cells, algae, aquatic organisms and cancer cell systems demonstrate concordance between ATP depletion and cell injury/death; however, the exact quantitative threshold varies substantially across biological systems and exposure conditions.

Biological plausibility is high. ATP depletion compromises core cellular maintenance processes including ion pumping, membrane integrity, cytoskeletal dynamics, protein turnover, DNA repair, and mitochondrial function. When ATP supply falls below the level required for homeostasis, cells lose the ability to maintain electrochemical gradients and to execute energy-dependent adaptive responses. Severe energetic collapse promotes necrotic injury, while partial ATP depletion may permit regulated apoptotic execution depending on residual ATP availability and caspase competence (Nieminen et al., 1994; Leist et al., 1997; Nicotera et al., 1998; Zong and Thompson, 2006). The mechanistic relationship is also supported by mitochondrial cell-death biology. ATP depletion often accompanies mitochondrial membrane depolarization, permeability transition, impaired oxidative phosphorylation, calcium dysregulation, and increased reactive oxygen species generation. These processes can amplify cellular injury and increase the probability of cell death (Kroemer et al., 1998; Green and Kroemer, 2004; Halestrap, 2009; Bonora et al., 2012).

Empirical support is moderate to high. In mammalian systems, ATP depletion has been directly linked to cell killing after metabolic inhibition, and experimental work has shown that ATP depletion rather than mitochondrial depolarization can mediate hepatocyte death under some conditions (Nieminen et al., 1994). A widely cited study demonstrated that intracellular ATP concentration influences whether cells die by apoptosis or necrosis, supporting both causality and phenotype dependence (Leist et al., 1997). Calcium electroporation studies provide dose-dependent evidence that ATP depletion is associated with reduced cancer cell survival and increased cell death (Hansen et al., 2015). Evidence from environmental and ecotoxicological systems is consistent with this relationship. In   Chlamydomonas reinhardtii, herbicide exposure produced ATP depletion and cell injury/death in a multiple-endpoint assay, demonstrating concordance between energetic disruption and cellular toxicity in an algal model (Nestler et al., 2012). In eastern oysters, cadmium exposure affected mitochondrial bioenergetics and was associated with cellular damage endpoints, supporting applicability of energetic failure to cell injury in aquatic invertebrates (Sokolova et al., 2005). In ROS-growth concordance data, mitochondrial toxicants and oxidative stressors including paraquat, rotenone, cadmium and hydrogen peroxide frequently produce decreased ATP or mitochondrial dysfunction together with cytotoxicity or tissue injury, although direct measurement of both KEs in the same study is not always available. <table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <thead> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:144px"> Evidence type </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:384px"> Summary </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:192px"> Representative references </td> </tr> </thead> <tbody> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:144px"> Biological plausibility </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:384px"> ATP is required for ion homeostasis, membrane maintenance, repair, and regulated cell death execution; severe ATP depletion promotes irreversible cell injury/death. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:192px"> Nieminen et al. 1994; Leist et al. 1997; Bonora et al. 2012 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:144px"> Temporal concordance </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:384px"> ATP depletion can occur rapidly after metabolic inhibition or mitochondrial impairment and precedes detectable loss of viability or death execution in several cell systems. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:192px"> Nieminen et al. 1994; Hansen et al. 2015 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:144px"> Dose-response concordance </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:384px"> Increasing intensity of energetic perturbation or calcium electroporation increases ATP depletion and cell killing. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:192px"> Hansen et al. 2015 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:144px"> Incidence concordance </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:384px"> Systems showing marked ATP depletion commonly show increased cytotoxicity, cell injury or cell death, although moderate ATP depletion may be compensated in some contexts. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:192px"> Leist et al. 1997; Nestler et al. 2012; Sokolova et al. 2005 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:144px"> Essentiality / intervention </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:384px"> Experimental data indicate that ATP availability influences the form and occurrence of cell death; restoration or maintenance of energy status can reduce injury in some systems, but direct rescue evidence across taxa remains limited. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:192px"> Leist et al. 1997; Nicotera et al. 1998 </td> </tr> </tbody> </table>

The main uncertainty is that ATP depletion is not the only cause of cell injury/death. Cell death may also be initiated by DNA damage, receptor-mediated apoptosis, oxidative damage, calcium overload, lysosomal injury, proteotoxic stress or inflammatory signaling. Consequently, the presence of cell injury/death does not uniquely imply ATP depletion. The KER is strongest when ATP decline occurs before or at lower concentrations than cell death and when the upstream energetic perturbation is mechanistically established.     Another uncertainty concerns severity thresholds. Moderate ATP depletion may be reversible or may shift cells into cell-cycle arrest, reduced proliferation, or adaptive metabolic compensation rather than death. Conversely, very severe ATP depletion may prevent the energy-requiring execution of apoptosis and produce necrotic injury instead. Therefore, the downstream phenotype depends on the magnitude and duration of ATP depletion and on cellular metabolic reserve (Leist et al., 1997; Nicotera et al., 1998). Empirical evidence across environmental species remains less dense than evidence from mammalian cell systems. Many ecotoxicological studies measure ATP, mitochondrial dysfunction, or cytotoxicity separately rather than measuring both KEs in the same time- and dose-resolved experiment. This limits the strength of concordance assessment across the full taxonomic applicability domain.

<table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <thead> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:154px"> Modulating factor </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:211px"> Details </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:259px"> Effect on this KER </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:163px"> References </td> </tr> </thead> <tbody> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Magnitude and duration of ATP depletion </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Transient or moderate ATP depletion versus severe, sustained ATP depletion. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:259px"> Severe and sustained ATP depletion increases probability of irreversible injury/death. Partial depletion may cause reversible stress or cell-cycle arrest. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Nieminen et al. 1994; Leist et al. 1997 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Metabolic flexibility / glycolytic capacity </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Ability to compensate for mitochondrial ATP loss by glycolysis or alternative ATP-generating pathways. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:259px"> Higher metabolic flexibility may reduce sensitivity of the downstream cell death response. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Bonora et al. 2012; Zong and Thompson 2006 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Cell type and proliferative/metabolic demand </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Highly energy-demanding or poorly glycolytic cells may have lower tolerance to ATP depletion. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:259px"> Alters threshold and time-scale for transition from ATP depletion to injury/death. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Bonora et al. 2012; Green and Kroemer 2004 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Mitochondrial permeability transition and calcium homeostasis </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Calcium overload and permeability transition can amplify ATP depletion and membrane failure. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:259px"> Can accelerate progression to necrotic or mixed cell injury phenotypes. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Halestrap 2009; Nieminen et al. 1994 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:154px"> Apoptotic execution machinery </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:211px"> Caspase competence and residual ATP availability influence whether death is apoptotic or necrotic. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:259px"> Determines cell death mode rather than the existence of injury/death per se. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:163px"> Leist et al. 1997; Nicotera et al. 1998 </td> </tr> </tbody> </table>

The quantitative understanding of this KER is considered moderate. Quantitative evidence supports a general response-response relationship in which larger or longer decreases in ATP increase the probability and severity of cell injury/death. However, a single universal threshold cannot be defined because ATP demand, ATP reserve, glycolytic capacity, cell type, death pathway, and exposure duration vary substantially among biological systems. Several studies support threshold-like behavior. In hepatocytes, ATP depletion mediated killing after metabolic inhibition, supporting a causal threshold relationship between energetic collapse and cell death (Nieminen et al., 1994). Experiments in human T cells showed that intracellular ATP concentration can act as a switch influencing apoptotic versus necrotic death phenotypes (Leist et al., 1997). Calcium electroporation studies showed dose-dependent ATP depletion and reduced survival, supporting a quantitative relationship between the upstream energetic disturbance and the downstream cell death outcome (Hansen et al., 2015).

The expected response-response relationship is generally monotonic but non-linear. Small or transient ATP reductions may be tolerated or compensated. Larger reductions increase the probability of cell stress, impaired repair, loss of membrane integrity, and cell death. At extreme ATP depletion, necrotic injury is favored, whereas intermediate depletion may permit energy-dependent apoptosis depending on cell type and execution machinery (Leist et al., 1997; Nicotera et al., 1998).

The time scale of ATP depletion can range from minutes to hours following direct mitochondrial inhibition, uncoupling, metabolic inhibition, or membrane-disrupting interventions. Observable downstream cell injury/death may occur within hours to days depending on cell type, severity of ATP loss, and endpoint measured. In whole organisms, cell death may contribute to tissue injury or growth impairment over longer time frames.

Feedback and feedforward processes may influence this linkage. ATP depletion can impair ion pumps, causing calcium dysregulation and mitochondrial permeability transition, which further suppresses ATP production and amplifies injury. Loss of mitochondrial function may also increase ROS generation, further damaging mitochondrial and cellular components. Conversely, glycolytic compensation and stress-response activation may temporarily buffer ATP depletion and delay cell death.

Moderate Unspecific

Moderate

All life stages

High High High High High

The biological domain of applicability is broad because ATP-dependent homeostasis is a conserved property of living cells. The KER is most directly applicable to eukaryotic cells and tissues in which mitochondrial and/or glycolytic ATP supply maintains cellular viability. It is particularly relevant to metabolically active tissues and developing organisms where energy demand is high. It is applicable to both sexes and to multiple life stages, although sensitivity may differ with developmental status, tissue type, temperature, oxygen availability, and metabolic reserve. The chemical and stressor applicability domain includes stressors that reduce cellular ATP through mitochondrial inhibition, OXPHOS uncoupling, oxidative stress, membrane disruption, calcium overload, metabolic poisons, hypoxia or other mechanisms that impair ATP synthesis or increase ATP demand beyond compensatory capacity. In the ROS-growth AOP network, this KER is most relevant downstream of OXPHOS impairment caused by lipid peroxidation or protein oxidation, where energetic failure contributes to increased cell injury/death.

Bonora M, Patergnani S, Rimessi A, De Marchi E, Suski JM, Bononi A, Giorgi C, Marchi S, Missiroli S, Poletti F, Wieckowski MR, Pinton P. 2012. ATP synthesis and storage. Purinergic Signaling 8:343-357. https://doi.org/10.1007/s11302-012-9305-8. Green DR, Kroemer G. 2004. The pathophysiology of mitochondrial cell death. Science 305:626-629. https://doi.org/10.1126/science.1099320. Halestrap AP. 2009. What is the mitochondrial permeability transition pore? Journal of Molecular and Cellular Cardiology 46:821-831. https://doi.org/10.1016/j.yjmcc.2009.02.021. Hansen EL, Sozer EB, Romeo S, Frandsen SK, Vernier PT, Gehl J. 2015. Dose-dependent ATP depletion and cancer cell death following calcium electroporation, relative effect of calcium concentration and electric field strength. PLoS ONE 10:e0122973. https://doi.org/10.1371/journal.pone.0122973. Kroemer G, Dallaporta B, Resche-Rigon M. 1998. The mitochondrial death/life regulator in apoptosis and necrosis. Annual Review of Physiology 60:619-642. https://doi.org/10.1146/annurev.physiol.60.1.619. Leist M, Single B, Castoldi AF, Kuhnle S, Nicotera P. 1997. Intracellular adenosine triphosphate (ATP) concentration: a switch in the decision between apoptosis and necrosis. Journal of Experimental Medicine 185:1481-1486. https://doi.org/10.1084/jem.185.8.1481. Lemasters JJ, Qian T, Bradham CA, Brenner DA, Cascio WE, Trost LC, Nishimura Y, Nieminen AL, Herman B. 1999. Mitochondrial dysfunction in the pathogenesis of necrotic and apoptotic cell death. Journal of Bioenergetics and Biomembranes 31:305-319. https://doi.org/10.1023/A:1005419617371. Nestler H, Groh KJ, Schonenberger R, Behra R, Schirmer K, Eggen RIL, Suter MJF. 2012. Multiple-endpoint assay provides a detailed mechanistic view of responses to herbicide exposure in Chlamydomonas reinhardtii. Aquatic Toxicology 110-111:214-224. https://doi.org/10.1016/j.aquatox.2012.01.014. Nicotera P, Leist M, Ferrando-May E. 1998. Intracellular ATP, a switch in the decision between apoptosis and necrosis. Toxicology Letters 102-103:139-142. https://doi.org/10.1016/S0378-4274(98)00298-7. Nieminen AL, Saylor AK, Herman B, Lemasters JJ. 1994. ATP depletion rather than mitochondrial depolarization mediates hepatocyte killing after metabolic inhibition. American Journal of Physiology - Cell Physiology 267:C67-C74. https://doi.org/10.1152/ajpcell.1994.267.1.C67. OECD. 2022. Uncoupling of oxidative phosphorylation leading to growth inhibition via decreased cell proliferation. OECD Series on Adverse Outcome Pathways No. 28. Paris: OECD Publishing. Sokolova IM, Sokolov EP, Ponnappa KM. 2005. Cadmium exposure affects mitochondrial bioenergetics and gene expression of key mitochondrial proteins in the eastern oyster Crassostrea virginica Gmelin (Bivalvia: Ostreidae). Aquatic Toxicology 73:242-255. https://doi.org/10.1016/j.aquatox.2005.03.016. Zong WX, Thompson CB. 2006. Necrotic death as a cell fate. Genes & Development 20:1-15. https://doi.org/10.1101/gad.1376506. AOPWiki 2022-09-27T13:24:52

2026-06-23T07:40:42

<upstream-id>101ddfa7-61da-4d1d-913a-0228c6bb03d9</upstream-id> <downstream-id>4aea0ec0-1761-4718-9185-284d857a8a97</downstream-id> This KER describes the causal and predictive relationship whereby an increase in cell injury and/or cell death leads to a decrease in growth. The upstream KE, cell injury/death, represents loss of cellular viability or severe cellular damage resulting in apoptosis, necrosis, or other forms of lethal cellular injury. The downstream KE, decreased growth, represents reduced accumulation of biomass, body size, length, cell density, tissue mass, or other growth-related endpoints at organ, organism, or population levels. The biological logic of the KER is that growth requires a positive balance between production of new cellular material and loss of existing cells. When cell injury/death is sufficiently frequent, persistent, or spatially distributed across growth-relevant tissues, net cell accumulation is reduced and tissue or organismal growth is impaired. In unicellular systems, increased cell death directly reduces viable cell density and biomass accumulation. In multicellular organisms, the relationship depends on the affected tissue, the ability to compensate through proliferation or regeneration, and the timing of injury relative to developmental or growth windows. This relationship is not intended to imply that all decreases in growth are caused by cell death. Growth can also decrease through reduced cell proliferation, altered energy allocation, endocrine disruption, nutrient limitation, or developmental delay without overt lethality. Rather, the KER applies when increased cell injury/death is of sufficient magnitude or duration to reduce the viable cellular pool needed for growth or to damage growth-relevant tissues. Within the ROS-growth AOP network, this KER provides a terminal convergence relationship for pathways in which oxidative stress, DNA strand breaks, or ATP depletion produce cytotoxicity that contributes to reduced growth.

Evidence for this KER was assembled using the same AI-human hybrid strategy applied across the ROS-growth AOP network. Initial evidence identification used AOP-Wiki relationship and key event mapping, prior ROS-growth concordance tables, and targeted literature searches. Search terms combined upstream and downstream concepts such as “cell death”, “cell injury”, “cytotoxicity”, “apoptosis”, “necrosis”, “viability”, “growth inhibition”, “growth retardation”, “developmental delay”, “biomass”, “cell density”, “condition index”, and “organism growth”, together with taxa and stressor terms including algae, Daphnia, copepod, bivalve, fish embryo, mammalian embryo, paraquat, cadmium, methanol, rotenone, gamma radiation, and oxidative stress. AOP-Wiki was consulted to confirm that Relationship 2767 links Event 55 to Event 1521 and to identify related AOP reuse contexts. Candidate studies were prioritized when they measured both cell injury/death and a growth-related outcome in the same biological system, reported dose or concentration and exposure duration, or provided information relevant to temporal, dose-response, or incidence concordance. Large language model assistance was used only as an auxiliary screening and structuring tool to extract study metadata, identify potentially relevant endpoints, and prioritize records for expert review. Final inclusion decisions, interpretation of endpoints, and weight-of-evidence judgments were made by manual expert curation against the original article text. Mechanistic reviews were used to support biological plausibility, while primary experimental studies were used preferentially to support empirical concordance.

Overall call: High. Growth at the level of a tissue, organ, organism, or cell population depends on net accumulation of cells and cellular biomass. Increased cell death directly lowers the number of viable cells and can reduce tissue mass, disrupt morphogenesis, or impair the capacity for biomass accumulation. This relationship is strongly supported by developmental and cell-size control principles showing that final tissue and organism size depend on the balance among cell growth, cell division, and cell death (Conlon and Raff, 1999). In embryos and developing organisms, excessive cell death can reduce cell number available for organ formation and growth, whereas in unicellular populations and cell cultures, cytotoxicity directly reduces viable cell density. The KER is therefore mechanistically plausible across taxa, although the magnitude of growth impairment depends on the tissue affected, compensatory proliferation, regeneration, and exposure duration.

Overall call: Moderate. Empirical support is moderate because multiple studies report concordance between cell injury/death and growth-related effects, but the evidence is heterogeneous and not always designed specifically to test this KER. In several systems, cell injury/death and growth inhibition are measured at different time points, and growth can be affected by mechanisms other than cell death. Nevertheless, the available data support the expected direction of effect across algae, fish embryos, mollusks, and mammalian embryo models.   <table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <thead> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:112px"> Biological system </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:112px"> Stressor / context </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:112px"> Upstream evidence: cell injury/death </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:112px"> Downstream evidence: decreased growth </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:112px"> Concordance interpretation </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:112px"> Reference </td> </tr> </thead> <tbody> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Chlamydomonas reinhardtii </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Paraquat </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Loss of membrane integrity measured by SYTOX Green; cell death observed at approximately 0.5 uM after 24 h. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Reduced cell density/growth after 72 h; growth LOEC approximately 0.1 uM and EC50 approximately 0.26 uM. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Partial temporal and endpoint concordance. Growth effects occurred at or below cytotoxicity thresholds, indicating that cell death contributes but is not the only driver of growth inhibition. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Jamers and De Coen, 2010 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Chlamydomonas reinhardtii </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Paraquat and herbicides </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> SYTOX Green cell death observed with paraquat; cell injury occurred alongside ATP depletion and other stress endpoints. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Assay system reported reduced growth/cell density and multiple mechanistic endpoints following herbicide exposure. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Supports association between cytotoxicity and reduced population growth, but includes multiple parallel mechanisms. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Nestler et al., 2012 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Mouse and rat whole-embryo culture </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Methanol </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Cell death markedly elevated in embryos at growth-relevant concentrations. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Mouse and rat embryo growth reduction observed in exposed cultures. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Supports developmental concordance between increased embryonic cell death and growth impairment, with species differences in sensitivity. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Abbott et al., 1995 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Eastern oyster, Crassostrea virginica </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Cadmium and temperature interaction </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Hemocyte mortality, lysosomal destabilization, and cellular energy disruption observed under cadmium stress. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Reduced condition index and increased mortality under combined cadmium and elevated temperature. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Supports linkage between cellular injury and reduced growth/condition, although growth is modified by temperature and energy budget effects. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Sokolova et al., 2005; Cherkasov et al., 2006 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Fish embryos and juveniles </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Rotenone </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Histological lesions and tissue injury observed at low concentrations. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Developmental delay and growth-related impairment reported after short-term exposure. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Supports association between cellular/tissue injury and developmental growth impairment; direct measurement of cell death was limited. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Melo et al., 2015 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Marine copepod, Paracyclopina nana </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Gamma radiation </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Radiation induced oxidative stress and impaired survival/development. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Growth retardation and failure of nauplii to develop to adults observed. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Supports an adverse sequence from stress-induced cellular injury to growth retardation, although cell death was not always measured directly. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:112px"> Won and Lee, 2014 </td> </tr> </tbody> </table> <h2> </h2>

The main uncertainty is that decreased growth is an integrative endpoint and can arise through several mechanisms that do not require overt cell death. Reduced proliferation, ATP depletion, endocrine disruption, altered energy allocation, nutrient limitation, delayed development, or behavioral effects can all reduce growth. For this reason, cell injury/death should be interpreted as a sufficient but not always necessary contributor to decreased growth. A second uncertainty is that many studies measure cytotoxicity and growth at different times or in different tissues, which limits direct evaluation of temporal concordance. In some algal studies, growth inhibition occurs at lower concentrations than overt cell death, suggesting that non-lethal impairment of proliferation, photosynthesis, or energy metabolism may precede cell death. Conversely, mild or localized cell injury may be compensated by repair or proliferation and may not lead to measurable growth reduction. These uncertainties support a moderate, rather than high, empirical call for this KER.

<table align="center" cellspacing="0" class="MsoTableGrid" style="border-collapse:collapse; border:none"> <thead> <tr> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:168px"> Modulating factor </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:168px"> Relevant details </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:168px"> Effect on the KER </td> <td style="background-color:#d9eaf7; border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:1px solid black; vertical-align:top; width:168px"> Supporting references </td> </tr> </thead> <tbody> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Developmental stage </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Embryonic and larval stages, rapid growth phases </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Increases sensitivity because rapid tissue growth requires high net cell accumulation; cell death during development can disproportionately impair growth. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Abbott et al., 1995; Conlon and Raff, 1999 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Tissue regenerative capacity </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Capacity for compensatory proliferation or tissue repair </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Reduces probability that cell death will translate into growth impairment when surviving cells can replace lost cells. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Conlon and Raff, 1999 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Exposure duration and timing </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Acute versus chronic exposures; timing relative to growth window </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Longer or developmentally timed exposures increase probability of growth effects from cell loss. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Jamers and De Coen, 2010; Melo et al., 2015 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Energy and nutritional status </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Energy budget, food availability, metabolic reserve </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Can increase or decrease impact of cell death on growth by altering compensatory capacity and resource allocation. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Sokolova, 2013; Cherkasov et al., 2006 </td> </tr> <tr> <td style="border-bottom:1px solid black; border-left:1px solid black; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Environmental stressors </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Temperature, oxygen availability, salinity, co-exposures </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Can amplify cytotoxicity or reduce compensatory growth responses, modifying downstream growth effects. </td> <td style="border-bottom:1px solid black; border-left:none; border-right:1px solid black; border-top:none; vertical-align:top; width:168px"> Cherkasov et al., 2006; Won and Lee, 2014 </td> </tr> </tbody> </table>

Overall call: Low to moderate. Quantitative understanding is limited because the relationship between cell injury/death and growth depends on the proportion of cells affected, tissue location, developmental timing, compensatory proliferation, regenerative capacity, and organismal energy allocation. At a conceptual level, the linkage is quantitative: growth rate reflects the balance between biomass accumulation and biomass or cell loss, so increasing the frequency or magnitude of cell death should reduce net growth if cell replacement or compensatory growth is insufficient. However, few studies provide response-response models that predict growth reduction from a measured degree of cell injury/death across taxa or stressors.

In cell populations and unicellular organisms, the quantitative relationship can be relatively direct because viable cell density is part of the growth measurement. In multicellular organisms, the relationship is less direct because growth can continue despite localized cell death if compensatory proliferation or tissue repair occurs. Some data show concordance between cytotoxicity and growth inhibition, but these data are generally insufficient to define universal thresholds. Therefore, quantitative understanding should be considered low to moderate for broad AOP-Wiki application, with higher confidence possible for specific model systems where cell viability and growth rate are measured in the same assay and time course.

Moderate Unspecific

Moderate

All life stages

Moderate Moderate Moderate Moderate Moderate

The KER is applicable to biological systems in which growth depends on maintenance or expansion of viable cell number or biomass. This includes unicellular populations, developing embryos, juvenile organisms, growing tissues, and adult organisms in which tissue condition or somatic growth is assessed. Taxonomic applicability is broad across eukaryotes, but empirical support is strongest for algae, aquatic invertebrates, mollusks, fish, and mammalian embryo or cell models. The KER is not sex-specific, but sex, endocrine status, life stage, and environmental context may modulate sensitivity. The relationship is most relevant when cell injury/death is sufficiently extensive, sustained, or located in growth-relevant tissues. It is less predictive when growth is reduced by upstream mechanisms that suppress proliferation or metabolism without substantial cell death.

Abbott, B. D., Harris, M. W., & Birnbaum, L. S. (1995). Cell death in rat and mouse embryos exposed to methanol in whole embryo culture: Evaluation of the role of the p53 tumor suppressor gene. Teratogenesis, Carcinogenesis, and Mutagenesis, 15(3), 147–169. Cherkasov, A. S., Biswas, P. K., Ridings, D. M., Ringwood, A. H., & Sokolova, I. M. (2006). Effects of acclimation temperature and cadmium exposure on cellular energy budgets in the marine mollusk Crassostrea virginica: Linking cellular and mitochondrial responses. Journal of Experimental Biology, 209(7), 1274–1284. Conlon, I., & Raff, M. (1999). Size control in animal development. Cell, 96(2), 235–244. Jamers, A., & De Coen, W. (2010). Effect assessment of the herbicide paraquat on a green alga using differential gene expression and biochemical biomarkers. Environmental Toxicology and Chemistry, 29(4), 893–901. Knops, M., Altenburger, R., & Segner, H. (2001). Alterations of physiological energetics, growth and reproduction of Daphnia magna under toxicant stress. Aquatic Toxicology, 53(2), 79–90. Melo, K. M., Oliveira, R., Grisolia, C. K., Domingues, I., Pieczarka, J. C., de Souza Filho, J., & Nagamachi, C. Y. (2015). Short-term exposure to low doses of rotenone induces developmental, biochemical, behavioral, and histological changes in fish. Environmental Science and Pollution Research, 22(18), 13926–13938. Nestler, H., Groh, K. J., Schönenberger, R., Eggen, R. I. L., & Suter, M. J.-F. (2012). Multiple-endpoint assay provides a detailed mechanistic view of responses to herbicide exposure in Chlamydomonas reinhardtii. Aquatic Toxicology, 110–111, 214–224. Organisation for Economic Co-operation and Development (OECD). (2018). Users’ handbook supplement to the guidance document for developing and assessing adverse outcome pathways. OECD Series on Adverse Outcome Pathways No. 1. OECD Publishing, Paris. Organisation for Economic Co-operation and Development (OECD). (2021). Guidance document for the scientific review of adverse outcome pathways. OECD Series on Testing and Assessment No. 344. OECD Publishing, Paris. Sokolova, I. M. (2013). Energy-limited tolerance to stress as a conceptual framework to integrate the effects of multiple stressors. Integrative and Comparative Biology, 53(4), 597–608. Sokolova, I. M., Sokolov, E. P., & Ponnappa, K. M. (2005). Cadmium exposure affects mitochondrial bioenergetics and gene expression of key mitochondrial proteins in the eastern oyster Crassostrea virginica Gmelin (Bivalvia: Ostreidae). Aquatic Toxicology, 73(3), 242–255. Won, E. J., & Lee, J. S. (2014). Gamma radiation induces growth retardation, impaired egg production, and oxidative stress in the marine copepod Paracyclopina nana. Aquatic Toxicology, 150, 17–26. AOPWiki 2022-09-27T13:22:59

2026-06-23T07:54:07

Excessive reactive oxygen species leading to growth inhibition via fatty acid oxidation and cell injury/death

ROS leading to growth inhibition via fatty acid oxidation and cell injury/death

You Song

Shihori Tanabe

BY-SA

2.7

Growth is a regulatory relevant chronic toxicity endpoint for almost all organisms. Multiple OECD test guidelines have included growth either as a main endpoint of concern, or as an additional endpoint to be considered in the toxicity assessments. Relevant test guidelines include, but not only limited to:   -Test No. 201: Freshwater Alga and Cyanobacteria, Growth Inhibition Test -Test No. 208: Terrestrial Plant Test: Seedling Emergence and Seedling Growth Test -Test No. 211: Daphnia magna Reproduction Test -Test No. 212: Fish, Short-term Toxicity Test on Embryo and Sac-Fry Stages -Test No. 215: Fish, Juvenile Growth Test -Test No. 221: Lemna sp. Growth Inhibition Test -Test No. 228: Determination of Developmental Toxicity to Dipteran Dung Flies (Scathophaga stercoraria L. (Scathophagidae), Musca autumnalis De Geer (Muscidae)) -Test No. 241: The Larval Amphibian Growth and Development Assay (LAGDA) -Test No. 407: Repeated Dose 28-day Oral Toxicity Study in Rodents -Test No. 408: Repeated Dose 90-Day Oral Toxicity Study in Rodents -Test No. 416: Two-Generation Reproduction Toxicity -Test No. 422: Combined Repeated Dose Toxicity Study with the Reproduction/Developmental Toxicity Screening Test -Test No. 443: Extended One-Generation Reproductive Toxicity Study -Test No. 453: Combined Chronic Toxicity/Carcinogenicity Studies

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<div> <table class="table table-bordered table-fullwidth"> <thead> <tr> <th>Modulating Factor (MF)</th> <th>Influence or Outcome</th> <th>KER(s) involved</th> </tr> </thead> <tbody> <tr> <td> </td> <td> </td> <td> </td> </tr> </tbody> </table> </div>

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