Reactive Oxygen Species Generation by Reverse Electron Transfer at Mitochondrial Complex I Under Simulated Early Reperfusion Conditions.
Caio Tabata FukushimaIan-Shika DancilHannah ClaryNidhi ShahSergiy M NadtochiyPaul S BrookesPublished in: bioRxiv : the preprint server for biology (2023)
Ischemic tissues accumulate succinate, which is rapidly oxidized upon reperfusion, driving a burst of mitochondrial reactive oxygen species (ROS) generation that triggers cell death. In isolated mitochondria with succinate as the sole metabolic substrate under non-phosphorylating conditions, 90% of ROS generation is from reverse electron transfer (RET) at the Q site of respiratory complex I (Cx-I). Together, these observations suggest Cx-I RET is the source of pathologic ROS in reperfusion injury. However, numerous factors present in early reperfusion may impact Cx-I RET, including: (i) High [NADH]; (ii) High [lactate]; (iii) Mildly acidic pH; (iv) Defined ATP/ADP ratios; (v) Presence of the nucleosides adenosine and inosine; and (vi) Defined free [Ca 2+ ]. Herein, experiments with mouse cardiac mitochondria revealed that under simulated early reperfusion conditions including these factors, overall mitochondrial ROS generation was only 56% of that seen with succinate alone, and only 52% of this ROS was assignable to Cx-I RET. The residual non-RET ROS could be partially assigned to complex III (Cx-III) with the remainder likely originating from other ROS sources upstream of the Cx-I Q site. Together, these data suggest the relative contribution of Cx-I RET ROS to reperfusion injury may be overestimated, and other ROS sources may contribute a significant fraction of ROS in early reperfusion.
Keyphrases
- reactive oxygen species
- cell death
- cerebral ischemia
- acute myocardial infarction
- dna damage
- acute ischemic stroke
- oxidative stress
- electron transfer
- cell cycle arrest
- gene expression
- squamous cell carcinoma
- blood brain barrier
- electronic health record
- neoadjuvant chemotherapy
- cell proliferation
- single cell
- machine learning
- locally advanced
- artificial intelligence
- protein kinase
- ionic liquid
- big data
- pi k akt