Methods for identifying reactive oxygen species

Abstract

The present invention relates to a method for in vitro quantifying the occurrence rate of reactive oxygen species, i.e., ROS, in a biological sample, comprising quantifying the amounts of enzymes in mitochondrial complexes I and III, and calculating the occurrence rate of ROS from the above amounts.

Description

[Technical Field]

[0001] The present invention relates in particular to a method for identifying reactive oxygen species involved in oxidative stress. [Background technology]

[0002] ATP is an organic compound that provides the energy to drive many processes in living cells, such as the propagation of nerve impulses, the dissolution of condensates, and muscle contraction, all thanks to its two phosphate anhydrides. The energy stored in ATP is released by the hydrolysis of the terminal anhydride, which converts ATP to ADP (adenosine diphosphate). Mitochondria are considered a major actor in cellular metabolism because they contain the oxidative phosphorylation system, which enables the generation of most of the ATP used by cells, as well as the Krebs cycle and the beta-oxidation of fatty acids, which regenerates substrates used by the enzymes of oxidative phosphorylation.

[0003] The electron transport chain (ETC) is a series of protein complexes located in mitochondria that transfer electrons from electron donors to electron acceptors via redox reactions (where both reduction and oxidation occur simultaneously). This electron transport is coupled with the transmembrane transport of protons (H+ ions). This proton transport creates an electrochemical proton gradient that drives ATP synthesis.

[0004] Respiratory chain complexes I and III are superoxide anions.

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[0007] ROS that are not regulated by cellular antioxidant defenses can react with cellular components and interfere with their function: this imbalance between ROS and antioxidant defenses is called "oxidative stress." ROS misregulation has been shown to correlate with a variety of diseases, including cancer, diabetes, heart disease, and neurodegenerative diseases.

[0008] Many neurodegenerative diseases are associated with dysfunction of one or more respiratory complexes related to oxidative stress.

[0009] Hydrogen peroxide is a relatively long-lived ROS, making it a focus of research toward understanding ROS in health and disease. Therefore, it can travel through cells, or even across cell membranes, before reacting with target biomolecules.

[0010] Various efforts have been made to detect hydrogen peroxide. For example, peracid in cell systems. For testing hydrogen dioxide, fluorescent scaffolds with boronate detection groups have been synthesized. Chemiluminescent probes based on peroxalate nanoparticles or luminol have been developed.

[0011] However, this known method cannot detect and / or quantify, for example, superoxide anions.

[0012] Therefore, compounds and / or methods for detecting ROS containing superoxide anions are still needed in the field.

[0013] Autosomal dominant optic atrophy 1 (DOA-1) is a neuropathology primarily caused by mutations in the OPA1 gene, which encodes a protein involved in mitochondrial dynamics. The symptoms and age of onset of this disease vary considerably. There is no clear correlation between genotype and phenotype that can explain this variability, and to date, there is no established medical treatment for this disease. The oxidative stress hypothesis has been proposed to explain the variability of symptoms observed in patients. Indeed, mitochondrial energy metabolism is altered in biological models of DOA-1 (cell culture and animal models), and low levels of antioxidant defense have been measured in cells derived from patients with severe pathology. (86)

[0014] Therefore, there is a need in the field to improve the understanding of the physiological and pathological mechanisms involved in this disease. Consequently, compounds and / or methods for detecting ROS, including superoxide anions, remain in demand in the field. [Overview of the project]

[0015] This invention relates to a method for in vitro quantifying the occurrence rate of reactive oxygen species, i.e., ROS, in a biological sample, and this method is a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or mitochondrial respiratory chain complex III, i.e., CIII, or both mitochondrial respiratory chain CI and CIII, wherein the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred, and - Determine the amounts of the seven components that are in the oxidized form of cytochrome C, i.e., cytCox, each concentration value - [NADH], corresponding to the amount of NADH measured in the biological sample, - [NAD+], corresponding to the amount of NAD+ measured in the biological sample, - [Q], corresponding to the amount of quinone measured in the biological sample, - [QH2], corresponding to the amount of quinol measured in the biological sample, - [O2], corresponding to the amount of molecular oxygen measured in the biological sample, - [CytC Red or [CytC red , corresponding to the amount of the reduced form of cytochrome C measured in the biological sample, - [CytC ox , corresponding to the amount of the oxidized form of cytochrome C measured in the biological sample, and b) Calculate the first ROS appearance rate V 1Ros of ROS in the sample,

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[0020] This invention is based on an unexpected observation made by the inventors that an optimized model for measuring the activity of both mitochondrial complex I and complex III allows for the easy assessment of the amount of Ros that can be produced in cells and subsequently in organisms.

[0021] Next, the present invention makes it possible to measure ROS production not by measuring ROS itself, but by measuring the activity of the enzyme and enzyme complex that produce ROS.

[0022] Reactive oxygen species (hereinafter referred to as ROS or Ros) are highly reactive chemical substances formed from diatomic oxygen (O2). Examples of ROS include the following species: hydroxyl radical (HO2). · ), hydroxide ions (HO - ), triplet oxygen (O2 2· ), superoxide anion (O2 ·- ), peroxide ions (O2 -2 ), hydrogen peroxide (H2O2), and nitric oxide (NO2) · ROS is known to be produced by mitochondria, particularly by respiratory chain complexes I and III.

[0023] Mitochondrial complex I is the first enzyme in the respiratory chain. This complex, and the enzymes it contains, oxidizes NADH produced in the mitochondrial matrix via the Krebs cycle, using two electrons to reduce ubiquinone to ubiquinol. Ubiquinol is then reoxidized by the cytochrome bc1 complex in complex IV, transferring electrons to reduce molecular oxygen to water. The redox energy released during this process is used by complexes I, III, and IV to transfer protons from the mitochondrial matrix to the periplasmic space, generating a proton-driven force across the inner mitochondrial membrane. Complex V uses this proton-driven force to produce ATP from ADP and inorganic phosphate. This entire process constitutes OXPHOS. Complex I is the primary electron supplier to the respiratory chain. As it is the entry point and is suggested to be the rate-limiting step in the entire respiration process, it plays a central role in energy metabolism.

[0024] Complex I is the largest and most complex component of the respiratory chain. In previous studies, bovine hearts were used as a model system, and all Complex I subunits were characterized and coding genes were cloned. However, the functions of the individual subunits remain largely unknown. Complex I is the only component of the mammalian respiratory chain, and its three-dimensional structure is only available at low resolution. Mitochondria are also major regulators of calcium signaling, a universal secondary messenger [4,5]. As will be discussed later, Complex I is involved in the regulation of reactive oxygen species (ROS), which are important molecules in various signaling pathways, including apoptosis.

[0025] Mitochondrial complex III generates superoxide during the ubiquinone (Q) cycle. The Q cycle involves the transfer of two electrons from complexes I and II to ubiquinone, resulting in its reduction to ubiquinol (QH2). Subsequent oxidation of ubiquinol in complex III requires the donation of those two electrons to cytochrome c, a single electron carrier. The first electron transfer in complex III is to the Reiske iron-sulfur center protein (RISP). It is then transferred to cytochrome c1, and subsequently to cytochrome c. This transfer of one electron from ubiquinol results in the unstable radical ubisemiquinone (Q ·-This can result in the unpaired electron being donated to oxygen, potentially generating superoxide within the Q cycle. However, in most cases, the unpaired electron from ubiquinol is transferred to the two heme groups of cytochrome b (heme bL and heme bH). The two hemes have different electron affinities because they are located in different polypeptide environments. Heme bL is located closer to the intermembrane space and has a lower affinity for electrons than heme bH, which is located closer to their matrix side. Ubisequinone transfers its electron to bL to form ubiquinone. Heme bL then donates an electron to heme bH, which subsequently reduces another ubiquinone molecule to form ubiquinone. At this stage, only one electron from ubiquinol has been transferred to cytochrome c, so the Q cycle is only half complete. After the second round of the Q cycle, two molecules of ubiquinol are oxidized on the intermembrane side of the inner membrane, two molecules of cytochrome c are reduced, and one molecule of ubiquinone is reduced on the matrix side of the inner membrane.

[0026] Based on literature data, the inventors were able to propose optimized models for both mitochondrial complexes I and III. By simply measuring the concentrations of specific substrates / products of these two complexes and applying the optimized models, the inventors can also easily, rapidly, and efficiently quantify ROS levels in cells, biological samples, and even patients.

[0027] In the method defined above, - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred or cytC Red , and, - The concentration of the oxidized form of cytochrome C, i.e., cytCox. This is measured.

[0028] In this invention, for example, the reduced form of nicotinamide adenine dinucleotide, namely N ADH, the oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+; quinone, i.e., Q; quinol, i.e., QH2; molecular oxide, i.e., O2; the reduced form of cytochrome C, i.e., cytCred or cytC Red The amount or concentration of the oxidized form of cytochrome C, i.e., cytCox, is expressed as moles (M or mol.L). -1 ) is described as follows.

[0029] Intracellular NAD+ and NADH levels can be measured using the NAD+ / NADH assay kit (Abcam) according to the manufacturer's instructions. Other similar tests are also available.

[0030] The reduction and oxidation levels of quinones can be carried out as described in Galinier et al., 2006(58).

[0031] The reduced form of cytochrome C, i.e., cytCred, and the oxidized form of cytochrome C, i.e., cytCox, can be measured as described in Abramczyk, H.; Brozek-Pluska, B.; Kopec, M.; Surmacki, J.; Blazczyk, M.; Radek, M. Redox Imbalance and Biochemical Changes in Cancer by Probing Redox-Sensitive Mitochondrial Cytochromes in Label-Free Visible Resonance Raman Imaging. Cancer 2021, 13, 960 (86), and Abramczyk, H. et al Scientific reports 2022 (87). Other methods known in the art can also be used.

[0032] In this specification, “patient,” “subject,” or “individual” means any individual, e.g., a mammal, e.g., a human of any sex and / or age. For example, a human such as an infant, baby, child, teenager, and adult. For example, a human is between 7 days and 99 years of age. For example, an infant may be between 7 days and 14 months of age, a child between 14 months and 12 years of age, a young adult between 12 and 17 years of age, and an adult between 17 and 99 years of age.

[0033] In this specification, “biological sample” means any biological fluid, which may be, for example, blood, plasma, serum, urine, or synovial fluid sample, any biological tissue, and / or any cells. It may be a serum or blood sample. It may be eukaryotic cells, for example, muscle cells, osteocytes, cancer cells, or epithelial cells. For example, if the biological sample is eukaryotic cells, it may be isolated eukaryotic cells.

[0034] In this specification, the biological sample may be a biological sample previously taken from the patient or subject. It may be a sample taken, for example, 5 minutes to 48 hours before its use in the method according to the present invention, for example, 1 hour to 24 hours before, for example, 1 hour to 6 hours before. According to the present invention, the volume of the biological sample may be 10 μl to 10 ml, for example, 12 μl to 5 ml, for example, 100 to 200 μl, and the volume of the biological sample may be 10 μl to 200 μl, for example, equal to 15 μl.

[0035] Biological samples may be, for example, fresh or frozen. If the sample is frozen, it may be advantageously frozen by, for example, rapid freezing with liquid nitrogen and then stored at, for example, -80°C until analysis.

[0036] In this invention, the reference sample means a biological sample having the same properties as the test sample. It may be, for example, a sample having the same properties as the test sample obtained from a healthy reference "patient," "subject," or "individual."

[0037] The term “healthy reference patient or subject or individual” is used herein to mean any individual, e.g., mammal, e.g., a human of any sex and / or age who is free from any disease and / or “oxidative stress” and / or ROS misregulation. For example, a human such as an infant, baby, child, teenager, and adult. For example, a human may be between 7 days and 99 years of age. For example, an infant may be between 7 days and 14 months of age, a child between 14 months and 12 years of age, a young adult between 12 and 17 years of age, and an adult between 17 and 99 years of age.

[0038] Next, the optimized formula defined above is applied to each of complexes I and III to obtain the respective ROS occurrence rates for each complex. The overall ROS occurrence rate is determined by adding the results for each complex.

[0039] In other words, the present invention relates to a method for quantifying the occurrence rate of reactive oxygen species, i.e., ROS, in a biological sample, preferably in vitro, and this method is a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or mitochondrial respiratory chain complex III, i.e., CIII, or both mitochondrial respiratory chain CI and CIII, wherein the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred, and - The oxidation form of cytochrome C, i.e., cytCox, is determined by determining the amounts of the seven components. Each concentration value - The amount of NADH measured in the biological sample corresponds to [NADH], - The amount of NAD+ measured in the biological sample corresponds to [NAD+], - [Q], corresponding to the amount of quinone measured in the biological sample, -[QH2], corresponding to the amount of quinol measured in the biological sample, - The amount of molecular oxygen measured in the biological sample corresponds to [O2], -[CytC] corresponds to the amount of reduced form of cytochrome C measured in the biological sample. Red ], - The amount of oxidized form of cytochrome C measured in the biological sample corresponds to [CytC ox ], and obtaining, b) The first ROS occurrence rate V in the sample 1Ros This involves calculating,

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[0044] In other words, the present invention relates to a method for quantifying the occurrence rate of reactive oxygen species, i.e., ROS, in a biological sample, preferably in vitro, and this method is a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or mitochondrial respiratory chain complex III, i.e., CIII, or both mitochondrial respiratory chain CI and CIII, wherein the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred, and - The oxidation form of cytochrome C, i.e., cytCox, is determined by determining the amounts of the seven components. Each concentration value - The amount of NADH measured in the biological sample corresponds to [NADH], - The amount of NAD+ measured in the biological sample corresponds to [NAD+], - [Q], corresponding to the amount of quinone measured in the biological sample, -[QH2], corresponding to the amount of quinol measured in the biological sample, - The amount of molecular oxygen measured in the biological sample corresponds to [O2], -[CytC] corresponds to the amount of reduced form of cytochrome C measured in the biological sample. Red ], - The amount of oxidized form of cytochrome C measured in the biological sample corresponds to [CytC ox ], and obtaining, b) The first ROS occurrence rate V in the sample 1Ros This involves calculating,

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[0049] Advantageously, the present invention relates to the method defined above, and this method is b) The first ROS occurrence rate V in the sample 1Ros This involves calculating,

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[0054] In other words, advantageously, the present invention relates to the method defined above, which method a) seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or involved in the activity of mitochondrial respiratory chain complex III, i.e., CIII, or involved in the activity of both mitochondrial respiratory chain CI and CIII, wherein the seven components are - the reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - the oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, - quinone, i.e., Q, - quinol, i.e., QH2, - molecular oxygen, i.e., O2, - the reduced form of cytochrome C, i.e., cytCred, and - the oxidized form of cytochrome C, i.e., cytCox, determining the amounts of the seven components, each concentration value - [NADH], corresponding to the amount of NADH measured in the biological sample, - [NAD+], corresponding to the amount of NAD+ measured in the biological sample, - [Q], corresponding to the amount of quinone measured in the biological sample, - [QH2], corresponding to the amount of quinol measured in the biological sample, - [O2], corresponding to the amount of molecular oxygen measured in the biological sample, - [CytC Red , - [CytC ox , corresponding to the amount of the oxidized form of cytochrome C measured in the biological sample, obtaining, b) calculating a first ROS appearance rate V of ROS in the sample 1Ros by,

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[0059] In this advantageous embodiment, the inventors obtain better results when the formula for obtaining the ROS occurrence rate is improved by using the above-described formula.

[0060] Here, in Model 3 of Complex III, the inventors have an optional input, an antimycin saturation (%).

[0061] More advantageously, the present invention relates to the method defined above, wherein the activity of CI is determined by the following formula.

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[0063] In addition to the emergence of ROS, the method proposed by the inventors makes it possible to evaluate the activity of complex I. By determining the activity of the complex, it is possible to assess the possibility of dysfunction in the complex, and therefore it is possible to propose therapies or treatments to correct the default.

[0064] More advantageously, the present invention relates to the method defined above, wherein the activity of CI is determined by the following formula:

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[0066] Similarly, in addition to the emergence of ROS, the method proposed by the inventors makes it possible to evaluate the activity of complex III. By determining the activity of the complex, it is possible to evaluate potential dysfunction in the complex and, therefore, propose therapies or treatments to correct the default.

[0067] The present invention also relates to a computer program that, when executed by a computer, includes instructions causing the computer to perform steps b) to d) of the method defined above.

[0068] When the computer program according to the present invention is implemented on a computer, by implementing the above formula, the following concentration - The amount of NADH measured in the biological sample corresponds to [NADH], - The amount of NAD+ measured in the biological sample corresponds to [NAD+], - [Q], corresponding to the amount of quinone measured in the biological sample, -[QH2], corresponding to the amount of quinol measured in the biological sample, and - Based on data regarding [O2], which corresponds to the amount of molecular oxygen measured in the biological sample, the appearance rate of ROS and the activity of both complexes can be calculated.

[0069] Any support device available to calculate the data according to the above formula can be used, such as a personal computer, portable computer, tablet smartphone, or any dice.

[0070] The present invention also provides a method for determining ROS detoxification enzyme activity in a sample of an organism, preferably in vitro, and this method is - By performing the method defined above, quantifying the ROS appearance rate in a biological sample to obtain a calculated ratio, - Comparing the calculated ratio with a reference ROS appearance rate, and thus obtaining a ratio R between the ROS appearance rate and the reference ROS appearance rate, wherein the reference ROS appearance rate is obtained from a reference sample, and the reference sample has the same nature as the sample, * If R is lower than 0.85, the sample contains ROS detoxifying enzyme activity that is efficient in detoxifying the sample during oxidative stress, * Otherwise, concluding that the sample does not contain (efficient ROS detoxifying enzyme activity during the process of ROS generation to detoxify the sample).

[0071] It is possible to evaluate the detoxifying activity of an individual using the method defined above, and thus, when subjected to oxidative stress, it is possible to predict whether the individual can efficiently detoxify cells, or whether ROS accumulation is expected, and its drawbacks.

[0072] In other words, the present invention also relates to a method for determining, preferably in vitro, the ROS detoxifying enzyme activity in a sample of an individual, and this method - By performing the method defined above, quantifying the ROS appearance rate in a biological sample to obtain a calculated ratio, that is, a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or in the activity of mitochondrial respiratory chain complex III, i.e., CIII, or in the activities of both mitochondrial respiratory chain CI and CIII, and the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, - Quinone, i.e., Q, - Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred, and - The oxidized form of cytochrome C, i.e., cytCox, determine the amounts of the seven components, each concentration value - [NADH], corresponding to the amount of NADH measured in the biological sample, - [NAD+], corresponding to the amount of NAD+ measured in the biological sample, - [Q], corresponding to the amount of quinone measured in the biological sample, - [QH2], corresponding to the amount of quinol measured in the biological sample, - [O2], corresponding to the amount of molecular oxygen measured in the biological sample, - [CytC Red , corresponding to the amount of the reduced form of cytochrome C measured in the biological sample, - [Cy tC ox [[ID=2�]]], corresponding to the amount of the oxidized form of cytochrome C measured in the biological sample, and obtain b) Calculate the first ROS appearance rate V of ROS in the sample 1Ros by

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[0077] Advantageously, the present invention relates to the above-described method, which - quantifying the ROS occurrence rate in a biological sample by performing the method defined above to obtain a calculated ratio; - obtaining a ratio R between the ROS occurrence rate and a reference ROS occurrence rate by comparing the calculated ratio with the reference ROS occurrence rate, wherein the reference ROS occurrence rate is obtained from a reference sample, and the reference sample has the same nature as the sample; - * if R is lower than 0.85, concluding that the sample contains efficient ROS detoxifying enzyme activity (which detoxifies the sample during the process of ROS generation); * otherwise, concluding that the sample does not contain efficient ROS detoxifying enzyme activity that detoxifies the sample during oxidative stress.

[0078] It is possible to evaluate the detoxifying activity of an individual using the method defined above, and thus, it is possible to predict whether an individual can efficiently detoxify cells or whether ROS accumulation is expected when subjected to oxidative stress, and its drawbacks.

[0079] In other words, the present invention also relates to a method for determining, preferably in vitro, the ROS detoxifying enzyme activity in a sample of an individual, the method comprising - The ROS occurrence rate in biological samples is quantified by performing the method defined above. To convert and obtain the calculated ratio, that is, a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or mitochondrial respiratory chain complex III, i.e., CIII, or both mitochondrial respiratory chain CI and CIII, wherein the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred, and - The oxidation form of cytochrome C, i.e., cytCox, is determined by determining the amounts of the seven components. Each concentration value - The amount of NADH measured in the biological sample corresponds to [NADH], - The amount of NAD+ measured in the biological sample corresponds to [NAD+], - [Q], corresponding to the amount of quinone measured in the biological sample, -[QH2], corresponding to the amount of quinol measured in the biological sample, - The amount of molecular oxygen measured in the biological sample corresponds to [O2], -[CytC] corresponds to the amount of reduced form of cytochrome C measured in the biological sample. Red ], - The amount of oxidized form of cytochrome C measured in the biological sample corresponds to [CytC ox ], and obtaining, b) The first ROS occurrence rate V in the sample 1Ros This involves calculating,

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[0084] More advantageously, the present invention relates to the above method, * If R is lower than 0.8, the sample contains efficient ROS detoxification enzyme activity (which detoxifies the sample during the process of ROS generation). * Otherwise, the sample does not contain efficient ROS detoxification enzyme activity (which detoxifies the sample during the process of ROS generation).

[0085] Advantageously, the present invention also provides a method for determining ROS detoxification enzyme activity in a sample of an organism, preferably in vitro, and the method is -By performing the method defined above, the ROS occurrence rate in a biological sample is quantified, and the calculated ratio is obtained, i.e., a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or mitochondrial respiratory chain complex III, i.e., CIII, or both mitochondrial respiratory chain CI and CIII, wherein the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred, and - The oxidation form of cytochrome C, i.e., cytCox, is determined by determining the amounts of the seven components. Each concentration value - The amount of NADH measured in the biological sample corresponds to [NADH], - The amount of NAD+ measured in the biological sample corresponds to [NAD+], - [Q], corresponding to the amount of quinone measured in the biological sample, -[QH2], corresponding to the amount of quinol measured in the biological sample, - The amount of molecular oxygen measured in the biological sample corresponds to [O2], -[CytC] corresponds to the amount of reduced form of cytochrome C measured in the biological sample. Red ], - The amount of oxidized form of cytochrome C measured in the biological sample corresponds to [CytC ox ], and obtaining, b) The first ROS occurrence rate V in the sample 1Ros This involves calculating,

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[0090] In another embodiment, the present invention relates to a method for in vitro determining a patient's response to a compound that is likely to reduce the amount of ROS in a biological sample, wherein the method is -By performing the method defined above, the ROS appearance rate in the biological sample after administration of the compound to the patient is quantified to obtain the final ROS rate, -Compare the initial ROS rate with the final ROS rate to obtain the ratio R between the final ROS rate and the initial ROS rate. - * If R is lower than 0.85, the compound can reduce the amount of ROS in the sample. * Otherwise, this includes concluding that the sample cannot reduce the amount of ROS in the sample.

[0091] Using the method described above, it is possible to evaluate the effect of compounds on regulating ROS production in cell or organismal samples.

[0092] In the present invention, “compounds that readily reduce ROS levels” refers to any molecule that is desired to be tested. These may be, for example, chemical and / or biological molecules. They may be, for example, therapeutic molecules or drugs that can be used to treat pathologies (e.g., any substance or compound known to those skilled in the art that has therapeutic and / or preventive properties with respect to pathologies, lesions, injuries, or diseases in humans or animals). They may be, for example, pharmaceuticals for human and / or veterinary use.

[0093] By measuring ROS generation by implementing the method according to the present invention at a predetermined time (before any treatment) and after the treatment period, it is possible to evaluate whether the treatment is effective in regulating ROS generation, preferably ROS reduction. A difference of approximately 15% or more compared to the initial value is considered statistically significant and is associated with the effect of the treatment. In contrast, if the difference between the initial ROS amount and the final ROS amount (after treatment) is less than 15%, the treatment is considered not to have an effect on ROS generation.

[0094] Advantageously, the present invention is a method for in vitro determining a patient's response to a compound that is likely to reduce the amount of ROS in a biological sample, and the method is -By performing the method defined above, the method includes quantifying the ROS occurrence rate in a biological sample to obtain an initial ROS rate before administering the compound to the patient, and this method is -By performing the method defined above, the ROS occurrence rate in a biological sample is quantified, and the calculated ratio is obtained, i.e., a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or mitochondrial respiratory chain complex III, i.e., CIII, or both mitochondrial respiratory chain CI and CIII, wherein the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred, and - The oxidation form of cytochrome C, i.e., cytCox, is determined by determining the amounts of the seven components. Each concentration value - The amount of NADH measured in the biological sample corresponds to [NADH], - The amount of NAD+ measured in the biological sample corresponds to [NAD+], - [Q], corresponding to the amount of quinone measured in the biological sample, -[QH2], corresponding to the amount of quinol measured in the biological sample, - The amount of molecular oxygen measured in the biological sample corresponds to [O2], -[CytC] corresponds to the amount of reduced form of cytochrome C measured in the biological sample. Red ], - The amount of oxidized form of cytochrome C measured in the biological sample corresponds to [CytC ox ], and obtaining, b) The first ROS occurrence rate V in the sample 1Ros This involves calculating,

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[0099] More advantageously, the present invention relates to the above method, * If R is less than 0.8, the compound can reduce the amount of ROS in the sample. * Otherwise, the sample cannot reduce the amount of ROS in the sample.

[0100] Advantageously, the present invention is a method for in vitro determining a patient's response to a compound that is likely to reduce the amount of ROS in a biological sample, and the method is -By performing the method defined above, the method includes quantifying the ROS occurrence rate in a biological sample to obtain an initial ROS rate before administering the compound to the patient, and this method is -By performing the method defined above, the ROS occurrence rate in a biological sample is quantified, and the calculated ratio is obtained, i.e., a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or mitochondrial respiratory chain complex III, i.e., CIII, or both mitochondrial respiratory chain CI and CIII, wherein the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, i.e., QH2, - Molecular oxygen, i.e., O2, - The reduced form of cytochrome C, i.e., cytCred, and - The oxidation form of cytochrome C, i.e., cytCox, is determined by determining the amounts of the seven components. Each concentration value - The amount of NADH measured in the biological sample corresponds to [NADH], - The amount of NAD+ measured in the biological sample corresponds to [NAD+], - [Q], corresponding to the amount of quinone measured in the biological sample, -[QH2], corresponding to the amount of quinol measured in the biological sample, - The amount of molecular oxygen measured in the biological sample corresponds to [O2], -[CytC] corresponds to the amount of reduced form of cytochrome C measured in the biological sample. Red ], - The amount of oxidized form of cytochrome C measured in the biological sample corresponds to [CytC ox ], and obtaining, b) The first ROS occurrence rate V in the sample 1Ros This involves calculating,

[0101]

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[0105] In another embodiment, the present invention relates to a method for determining in vitro in a biological sample whether a compound is an oxidation-promoting compound or an antioxidant compound, wherein the method is -By performing the method defined above, the Ros occurrence rate in biological samples is quantified, and the calculated ratio is obtained. - The calculated ratio is compared with the reference Ros occurrence rate to obtain the ratio R between the Ros occurrence rate and the reference Ros occurrence rate, provided that the reference Ros occurrence rate is obtained from a reference sample and the reference sample has the same properties as the sample. - * If R is lower than 0.85, the compound is an antioxidant compound. * If R is greater than 1.15, the compound is an oxidation promoter. *This includes concluding that if R is between 0.85 and 1.15, the compound has neither antioxidant nor pro-oxidative properties.

[0106] Advantageously, the present invention relates to the method defined above, and this method is -By performing the method defined above, the Ros occurrence rate in biological samples is quantified, and the calculated ratio is obtained. - The calculated ratio is compared with the reference Ros occurrence rate to obtain the ratio R between the Ros occurrence rate and the reference Ros occurrence rate, provided that the reference Ros occurrence rate is obtained from a reference sample and the reference sample has the same properties as the sample. - * If R is less than 0.8, the compound is an antioxidant compound. * If R is greater than 1.2, the compound is an oxidation promoter. * This includes concluding that if R is between 0.8 and 1.2, the compound has neither antioxidant nor pro-oxidative properties. [Brief explanation of the drawing]

[0107] The present invention will be better understood in light of the following embodiments and drawings. [Figure 1]Oxygen consumption rate (OCR) was measured in HeLa cells transfected with siOPA1 and siCtrl over time (horizontal axis) (vertical axis). Spontaneous mitochondrial respiration was significantly lower in siOPA-transfected cells (0.33 ± 0.02 pmol / min / mg protein) than in control cells (0.53 ± 0.04 pmol / min / mg protein). After oligomycin (1 μM) injection at 30 minutes, cellular respiration was also significantly lower in siOPA1-transfected cells (0.11 ± 0.01 pmol / min / mg protein) than in control cells (0.17 ± 0.02 pmol / min / mg protein). After FCCP (1 μM) injection at 50 minutes, maximal respiration was significantly lower in siOPA-transfected cells (0.30 ± 0.04 p mol / min / mg protein) than in control cells (0.67 ± 0.10 p mol / min / mg protein). Finally, rotenone (1 μM) + antimycin A (1 μM) injection at 80 minutes inhibited mitochondrial respiration. Results are expressed as mean ± SEM (n > 3). P-values ​​were determined by Student's unpaired t-test (p < 0.05* and p < 0.01**). [Figure 2] Total ATP concentration (vertical axis) was measured in μM / mg protein for siOPA1 Hela cells (gray bars) and siCtrl-treated cells (white bars). ATP concentration did not change in siOPA1 Hela cells (gray bars) compared to siCtrl-treated cells (white bars). Results are expressed as mean ± SEM (n>3). P-values ​​were determined by Student's t-test. [Figure 3]The extracellular acidification rate (ECAR) (vertical axis) was measured in mpH / min / mg protein for siOPA1 Hela cells (gray bars) and siCtrl-treated cells (white bars). The data for the left bars were obtained at the basal level. The data for the right bars were obtained after oligomycin injection. ECAR remained unchanged in OPA1-treated cells (basal: 37.93 ± 1.33 pmol / min / mg protein, oligomycin: 56.42 ± 3.08 pmol / min / mg protein) compared to siCtrl-treated cells (basal: 46.40 ± 3.93 pmol / min / mg protein, oligomycin: 69.14 ± 6.72 pmol / min / mg protein) under basal conditions and after 1 μM oligomycin injection. As expected, ECAR increased in both siCtrl and siOPA1-transfected cells after oligomycin injection. Results are expressed as mean ± SEM (n>3). The p-value was determined by Student's independent t-test (p<0.05 * p<0.001***). [Figure 4] Extracellular lactate (vertical axis) was measured by colorimetric analysis in HeLa cells containing (gray bars) or not containing (white bars) siOPA1 (mean ± SEM, n=2). P-values ​​were determined by Student's paired t-test. [Figure 5-1]This is a representative immunoblot showing the effect of OPA1 downregulation in HeLa cells or control cells on the levels of two subunits of the MRC complex (complexes I-IV) and three subunits of ATP synthase (complex V) compared to actin (vertical axis) (horizontal axis). The histogram shows representative amounts (vertical axis) of NADH:ubiquinone oxidoreductase subunit A9 (NDLIFA9) or NADH:ubiquinone oxidoreductase subunit B4 (NDLIFB4) for complex I, succinate dehydrogenase complex subunit A (SDHA) or succinate dehydrogenase complex subunit B (SDHB) for complex II, core 1 or core 2 for complex III, COX I or COX IV for complex IV, and alpha subunit (F1), gamma subunit (F1), or subunit d (F0) for complex V in HeLa cells containing (gray bars) or not containing (white bars) siOPA1. The amount of NDLIFB4 (n=10) was significantly lower in siOPA1-transfected HeLa cells (0.47±0.07) than in siCtrl-transfected cells (0.85±0.09). The amount of SDHB (n=10) was significantly lower in siOPA1-treated cells (0.68±0.16) than in control cells (0.96±0.16). The level of core 2 (n=10) was significantly lower in siOPA1-treated cells (0.75±0.05) than in control cells (1.238±0.10). The level of COX I (n=10) was lower in siOPA1-treated cells (0.37±0.05) than in control cells (0.69±0.06). The p-values ​​were determined by Student's paired t-test (p<0.05*, p<0.01**, and p<0.001***). [Figure 5-2]This is a representative immunoblot showing the effect of OPA1 downregulation in HeLa cells or control cells on the levels of two subunits of the MRC complex (complexes I-IV) and three subunits of ATP synthase (complex V) compared to actin (vertical axis) (horizontal axis). The histogram shows representative amounts (vertical axis) of NADH:ubiquinone oxidoreductase subunit A9 (NDLIFA9) or NADH:ubiquinone oxidoreductase subunit B4 (NDLIFB4) for complex I, succinate dehydrogenase complex subunit A (SDHA) or succinate dehydrogenase complex subunit B (SDHB) for complex II, core 1 or core 2 for complex III, COX I or COX IV for complex IV, and alpha subunit (F1), gamma subunit (F1), or subunit d (F0) for complex V in HeLa cells containing (gray bars) or not containing (white bars) siOPA1. The amount of NDLIFB4 (n=10) was significantly lower in siOPA1-transfected HeLa cells (0.47±0.07) than in siCtrl-transfected cells (0.85±0.09). The amount of SDHB (n=10) was significantly lower in siOPA1-treated cells (0.68±0.16) than in control cells (0.96±0.16). The level of core 2 (n=10) was significantly lower in siOPA1-treated cells (0.75±0.05) than in control cells (1.238±0.10). The level of COX I (n=10) was lower in siOPA1-treated cells (0.37±0.05) than in control cells (0.69±0.06). The p-values ​​were determined by Student's paired t-test (p<0.05*, p<0.01**, and p<0.001***). [Figure 6]The graph shows the activity of complex I (n=3), complex II (n=16), complex III (n=3), and complex IV (n=16) measured in vitro in both siOPA1-treated (gray bars) and siCtrl-treated (white bars) HeLa cells (vertical axis). Succinate dehydrogenase (complex II) activity was lower in siOPA1-treated cells (6.438±0.701) than in control cells (8.688±0.7229). Results are expressed as mean ± SEM. P-values ​​were determined by Student's paired t-test (p<0.05*, p<0.01**, and p<0.001***). [Figure 7] Total ROS fluorescence (vertical axis) was measured for siOPA1-treated (gray bars) and siCtrl-treated (white bars) HeLa cells. Total ROS measured by the H2-DCFDA probe was lower in siOPA1-transfected HeLa cells (72.63±4.6) than in siCtrl-treated cells (95.48±9.1). [Figure 8] Aconitase activity (vertical axis) was measured in HeLa cells treated with siOPA1 (gray bars) and siCtrl (white bars). Aconitase activity was lower in siOPA1-treated cells (3.185±1.41) than in siCtrl-treated cells (4.811±1.361). [Figure 9] Representative immunoblots showing proteins in siOPA1-treated and siCtrl-treated HeLa cells (horizontal axis) according to their molecular size (vertical axis). The histograms represent the relative levels of aconitase (vertical axis) in siOPA1-treated (gray bars) and siCtrl-treated (white bars) HeLa cells. These results indicate that downregulation of OPA1 in HeLa cells does not affect aconitase expression compared to actin. [Figure 10]Mitochondrial superoxide production was measured using a fluorescence microscope (×40) with MitoSOX Red (mitochondrial-targeted superoxide index). MitoSOX (vertical axis) was measured 72 hours after siCtrl (white) or siOPA1 (gray) transfection. Representative histograms of quantitative fluorescence intensity were analyzed using Imaged software. ROS levels were higher in siOPA1-transfected cells (1,9444±0.2278) than in control cells (1,386±0.08754). Representative micrographs of mitochondrial MitoSOX immunofluorescence and DNA Hoechst staining in siCtrl-treated or siOPA1-treated HeLa cells 72 hours after transfection. Scale bars represent 10 μm. Results are expressed as mean ± SEM for n=8(A), n=6(B), n=8(C), and n=3(D) with over 200 cells. Statistical analysis was performed using a nonparametric test (Mann-Whitney) for A and D, and Student's paired t-test for B (p<0.05*). [Figure 11] Representative micrographs of NRF2 immunofluorescence and DNA Hoechst staining or overlay in siOPA1-treated or siCtrl-treated HeLa cells 72 hours after transfection. [Figure 12] Representative histograms showing the percentage of cells with NRF2 nuclear migration (vertical axis) according to 66, 67, 68, 69, 70, and 72 hours (horizontal axis) after siOPA1 (gray) or siCtrl (white) transfection. NRF2 nuclear immunostaining was observed in 15.18±1.86% of control HeLa cells and 51.68±5.57% of siOPA1-treated cells 72 hours after transfection. Results are expressed as mean ± SEM for n=4~14 (400 cells per condition). P-values ​​were determined by a non-parametric test (Mann-Whitney U test) (p<0.001***). Scale bar: 10 μm. [Figure 13]Representative immunoblots and relative levels of SOD1, SOD2, catalase, NQO1, GSTP1, FHC, and FLC proteins in both siCtrl-treated and siOPA1-treated HeLa cells. SOD1 levels were higher in siOPA1-treated cells (1.05±0.03) than in control cells (0.79±0.05). GSTP1 levels were higher in siOPA1-treated cells (1.07±0.06) than in control cells (0.82±0.11). [Figure 14] Total SOD activity (SOD1 and SOD2) (vertical axis) was measured in HeLa cells treated with siOPA1 (gray bars) and siCtrl (white bars). Total SOD activity was higher in siOPA1-treated cells (1.01±0.12) than in control cells (0.73±0.08). [Figure 15] Catalase activity (vertical axis) was measured in HeLa cells treated with siOPA1 (gray bars) and siCtrl (white bars). Catalase activity was the same in both siOPA1-treated and siCtrl-treated cells. Results are presented as the mean ± SEM for n=8 (A), n=5 (B), n=7 (C), n=5 (D), and n=7. Statistical significance was determined by Student's paired t-test (p<0.01**). [Figure 16] Simulation of Complex I activity using a mathematical model in the context of SiOPA1-treated (gray bars) or SiCtrl-treated (white bars) cells (vertical axis). [Figure 17] Simulation of ROS generation by complex I (vertical axis) using a mathematical model in the context of SiOPA1-treated (gray bars) or SiCtrl-treated (white bars) cells. [Figure 18]Representative immunoblots and histograms showing protein levels of OPA1 (inner membrane), citrate synthase (matrix), HSP60 (matrix), VDAC (outer membrane), and TOM20 (outer membrane) compared to actin (vertical axis) in OPA1-downregulated cells and control cells (horizontal axis). OPA1 protein levels are dramatically reduced (92%) in siOPA1-transfected HeLa cells. In OPA1-downregulated HeLa cells, there is no difference in the amount of any protein compared to control cells. [Figure 19] Citrate synthase activity (vertical axis), a TCA cycle enzyme, in HeLa cells transfected with siOPA1 (gray bars) or siCtrl (white bars). Results are presented as mean + / - SEM for n=8 (A) and n=16 (B). P-values ​​were determined by Student's paired t-test (p<0.001***). [Figure 20] In siOPA1-transfected HeLa cells, the mitochondrial network is punctate, while in siCtr-transfected HeLa cells, it is filamentous (horizontal axis). The nucleus is stained with DAPI, and the mitochondrial network is colored with Mitotracker (vertical axis). The scale bar represents 10 μm. [Figure 21] The NAD+ / NADH,H+ ratio and the total intracellular levels of NAD+ and NADH,H+ (vertical axis) were measured in HeLa cells transfected with siOPA1 (gray bars) or siCtrl (white bars). The NAD+ / NADH,H+ ratio and the total intracellular levels of NAD+ and NADH,H+ did not change in HeLa cells transfected with siOPA1 compared to siCtrl cells. Results are expressed as mean + / - SEM (n=5). The p-value was determined by Student's paired t-test. [Figure 22] Reduced (GSH) and oxidized (GSSG) glutathione levels (vertical axis) are measured in HeLa cells transfected with siOPA1 (gray bars) compared to control cells (white bars). [Figure 23]This study evaluates the oxidized and reduced forms of quinones. The redox state of quinones is the ratio of the oxidized form to the total form (vertical axis). Quinone redox states were measured in HeLa cells transfected with siOPA1 (gray bars) or siCtrl (white bars). Results are presented as the mean ± SEM for n=4 (A) and n=8 (B). P-values ​​were determined by Student's paired t-test. [Figure 24] Representative micrographs of NRF2 immunofluorescence and DNA Hoechst staining (vertical axis) in siOPA1-treated or siCtrl-treated HeLa cells (horizontal axis) 72 hours after transfection. (Scale bar represents 5 μm). [Figure 25] Schematic summary: In OPA1-depleted cells, several subunits of the first four complexes of the mitochondrial respiratory chain are reduced without altering total ATP production. The cells enter a prooxidative state, as highlighted by decreased aconitase activity, translocation of the NRF2 transcription factor to the nucleus, and significantly increased levels of GSTP1 and SOD1 proteins, followed by a decrease in intracellular ROS levels. [Figure 26-1] Activity of Complex I: Simulation of the catalytic rate of NAD+ in several configurations shown in the graph using 1-5 different models with biological data from Heiske et al. (20) (vertical axis) (* indicates biological data from the literature named Heiske et al. (20), and lines of different colors are the results of simulations from models 1-5). A-I: Cases where the concentration of NADH is different and the concentration of quinone Q is constant (1.1-70 μM). J-R: Cases where the concentration of quinone Q is different and the concentration of NADH is constant (1-47.5 μM). S-U: Cases where the concentration of quinol QH2 or the QH2 / Qtot ratio is different and the concentrations of NADH and quinone Q are constant. V-X: Cases where the concentration of NAD+ is different and the concentrations of NADH and quinone Q are constant. [Figure 26-2]Activity of Complex I: Simulation of the catalytic rate of NAD+ in several configurations shown in the graph using 1-5 different models with biological data from Heiske et al. (20) (vertical axis) (* indicates biological data from the literature named Heiske et al. (20), and lines of different colors are the results of simulations from models 1-5). A-I: Cases where the concentration of NADH is different and the concentration of quinone Q is constant (1.1-70 μM). J-R: Cases where the concentration of quinone Q is different and the concentration of NADH is constant (1-47.5 μM). S-U: Cases where the concentration of quinol QH2 or the QH2 / Qtot ratio is different and the concentrations of NADH and quinone Q are constant. V-X: Cases where the concentration of NAD+ is different and the concentrations of NADH and quinone Q are constant. [Figure 26-3] Activity of Complex I: Simulation of the catalytic rate of NAD+ in several configurations shown in the graph using 1-5 different models with biological data from Heiske et al. (20) (vertical axis) (* indicates biological data from the literature named Heiske et al. (20), and lines of different colors are the results of simulations from models 1-5). A-I: Cases where the concentration of NADH is different and the concentration of quinone Q is constant (1.1-70 μM). J-R: Cases where the concentration of quinone Q is different and the concentration of NADH is constant (1-47.5 μM). S-U: Cases where the concentration of quinol QH2 or the QH2 / Qtot ratio is different and the concentrations of NADH and quinone Q are constant. V-X: Cases where the concentration of NAD+ is different and the concentrations of NADH and quinone Q are constant. [Figure 26-4]Activity of Complex I: Simulation of the catalytic rate of NAD+ in several configurations shown in the graph using 1-5 different models with biological data from Heiske et al. (20) (vertical axis) (* indicates biological data from the literature named Heiske et al. (20), and lines of different colors are the results of simulations from models 1-5). A-I: Cases where the concentration of NADH is different and the concentration of quinone Q is constant (1.1-70 μM). J-R: Cases where the concentration of quinone Q is different and the concentration of NADH is constant (1-47.5 μM). S-U: Cases where the concentration of quinol QH2 or the QH2 / Qtot ratio is different and the concentrations of NADH and quinone Q are constant. V-X: Cases where the concentration of NAD+ is different and the concentrations of NADH and quinone Q are constant. [Figure 27-1] ROS production of complex I: Catalytic rate of O2 in several configurations shown in graphs of 1-5 different models using biological data from Kussmaul and Hirst (26) and Grivennikova and Vinogradov (2006) (16) (* indicates biological data from literature named Kussmaul and Hirst (26) and Grivennikova and Vinogradov (16), and solid or dashed lines are the results of simulations from models 1-5). A: Different NADH concentrations. B: Different NAD+ concentrations. C: Concentrations NADH=30μM and Q=100μM. [Figure 27-2]ROS production of complex I: Catalytic rate of O2 in several configurations shown in graphs of 1-5 different models using biological data from Kussmaul and Hirst (26) and Grivennikova and Vinogradov (2006) (16) (* indicates biological data from literature named Kussmaul and Hirst (26) and Grivennikova and Vinogradov (16), and solid or dashed lines are the results of simulations from models 1-5). A: Different NADH concentrations. B: Different NAD+ concentrations. C: Concentrations NADH=30μM and Q=100μM. [Figure 28-1] Activity of Complex III: Simulation of NAD+ catalytic rate in several configurations shown in the graph using 1-3 different models with biological data from Heiske et al. (19) (vertical axis) (* indicates biological data from the literature named Heiske et al. (19), and solid or dashed lines are the results of simulations from models 1-3). A-C: Different concentrations of CytoCox and a constant quinone QH2 concentration (70-210 μM). D-F: Different concentrations of quinone QH2 and a constant CytoCox concentration (20-80 μM). G-J: Different concentrations of quinone Q and a constant concentration of QH2 and CytoCox (20-80 pM). K-N: Different concentrations and proportions of CytoCred and a constant quinol QH2 concentration (210 μM). [Figure 28-2]Activity of Complex III: Simulation of NAD+ catalytic rate in several configurations shown in the graph using 1-3 different models with biological data from Heiske et al. (19) (vertical axis) (* indicates biological data from the literature named Heiske et al. (19), and solid or dashed lines are the results of simulations from models 1-3). A-C: Different concentrations of CytoCox and a constant quinone QH2 concentration (70-210 μM). D-F: Different concentrations of quinone QH2 and a constant CytoCox concentration (20-80 μM). G-J: Different concentrations of quinone Q and a constant concentration of QH2 and CytoCox (20-80 pM). K-N: Different concentrations and proportions of CytoCred and a constant quinol QH2 concentration (210 μM). [Figure 29] ROS production of complex I: Catalytic rates of O2- (vertical axis) for different proportions of quinone Q (horizontal axis) shown in graphs from 1-3 different models using biological data from Drose and Brandt (11) (* represents biological data from the literature named (11), and solid or dashed lines are the results of simulations from models 1-3). [Examples]

[0108] Example 1 Dominant optic atrophy (DOA) is characterized by moderate to severe visual impairment with an insidious onset in early childhood (Amati-Bonneau et al., 2009(45); Lenaers et al.(67), 2012; Yu-Wai-Man et al., 2011(83)). This disease primarily affects retinal ganglion cells (RGCs), the axons that form the optic nerve, which degenerate. The estimated prevalence is 1:10,000 (Denmark) to 1:50,000 (worldwide). There is considerable variation within and between families, and penetrance can be as low as 40%. Different studies have shown that certain OPA1 mutations are associated with severe multiple organ failure (DOA+ syndrome) (Amati-Bonneau et al., 2008 (46); Cohn et al., 2007 (53); Yu-Wai-Man et al., 2010 (82); Zeviani, 2008 (85)). DOA+ patients exhibit further neurological complications such as ataxia, sensorineural hearing loss, sensorimotor neuropathy, progressive extraocular palsy, and parkinsonism, as well as myopathy. In summary, these findings reveal that OPA1 mutations have widespread and detrimental consequences not only for RGCs but also for other cell populations (Barboni et al., 2013 (47); Chao de la Barca et al., 2016 (51); Mackey and Trounce, 2010 (70); Spinazzi et al., 2008 (78); Zeviani, 2008 (85)). Currently, there is no effective treatment for this complex disease.

[0109] Most DOA patients (approximately 75%) have mutations in the OPA1 gene, which encodes mitochondrial GTPase (Delettre et al., 2000(57)). Mitochondrial GTPase is localized in the intermembrane space (IMS) and tethered to the inner mitochondrial membrane (Griparic et al., 2004(62); Ishihara et al., 2006(63); Olichon et al., 2002(73); Satoh et al., 2003(75)). Most OPA1 mutations result in premature termination, and subsequent OPA1 haploinsufficiency is the primary pathogenic mechanism (Amati-Bonneau et al., 2009(45)). The OPA1 protein has been shown to be involved in the fusion of the inner mitochondrial membrane and cristae structure in various cell lines. Mitochondrial fusion and fission control mitochondrial morphology and regulate major mitochondrial functions (Bertholet et al., 2016(48)). These processes also contribute to organelle quality control. Through its role in organizing the structure of cristae, OPA1 sequestrates cytochrome c within the cristae and thus exerts anti-apoptotic function. Data on cutaneous fibroblasts, muscle cells, and lymphoblasts from DOA patients generally show alterations in mitochondrial morphology and energy, as well as increased susceptibility to apoptosis (Alavi et al., 2009 (44); Chevrollier et al., 2008 (52); Olichon et al., 2006 (74); Spinazzi et al., 2008 (78); Yu-Wai-Man et al., 2011 (83); Zanna et al., 2008 (84)). However, there are many conflicting reports regarding the presence and nature of energy deficiency in DOA patients, and therefore the extent to which these processes contribute to the pathogenesis of DOA remains unclear.Furthermore, two invertebrate DOA models, and more recently, mammalian DOA models, have linked significant ROS generation to OPA1 dysfunction (Millet A. et al., 2017(71); Millet et al., 2016(72); Shahrestani et al., 2009(77); Tang et al., 2009(79)).

[0110] The inventors previously developed a deterministic mathematical model that can predict ROS generation of MRC complex I and the catalytic activity of complex I. The method used was the activity of ROS in several operating configurations of complex I (Heiske et al., 2014(20)). The algorithm is based on in vitro data regarding the activity and generation of complex I (Grivennikova and Vinogradov, 2006(16); Kussmaul and Hirst, 2006(26)). These data are introduced into an algorithm with normalization so that future sets of parameters can be scored. The molecular behavior is represented by the Michaelis and Menten equation for the enzyme dynamics of the complex I reaction. Several models with different levels of accuracy are created, and thus the number of parameters to be optimized increases. After randomly generating a set of parameters, each solution is passed to a differential evolution algorithm to generate a set of optimized solutions. The models are connected via a cascade structure and are called sequentially from the simplest model to the most accurate model. According to the algorithm, the selected set of parameters can simultaneously simulate the activity of complex I and the generation of ROS, and the results are qualitatively and quantitatively close to the input data.

[0111] Thus, the inventors addressed the issue of OPA1's involvement in oxidative metabolism. Since haploinsufficiency is primarily the cause of DOA, and the effects of OPA1 inactivation are not limited to RGCs, the inventors evaluated the general effects of OPA1 inactivation on oxidative phosphorylation and redox states by downregulating OPA1 in HeLa cells using an RNA interference strategy. The inventors found that cellular respiration decreased when OPA1 levels were reduced. This was accompanied by increased mitochondrial ROS production, which was mitigated by activation of antioxidant defenses, resulting in a prooxidative state. The inventors' algorithm for Complex I can simulate its activity in accordance with the inventors' in vitro data and refine hypotheses about ROS production.

[0112] 2. Results 2.1. Downregulation of OPA1 affects cellular oxygen consumption and the volume and activity of mitochondrial respiratory chain complexes.

[0113] The inventors evaluated the downregulatory effect of OPA1 on respiration and glycolysis in HeLa cells transfected with siRNA against OPA1 (siOPA1), using siRNA against luciferase (siCtrl) as a control. 72 hours after transfection, OPA1 levels were 92% lower in siOPA1-treated cells than in siCtrl cells, but actin levels remained unchanged (Figure 18).

[0114] The inventors used the Seahorse XF24 flux analyzer (Seahorse Bioscience Inc, North Billerica, MA, USA) to measure the oxygen consumption rate (OCR), a direct measure of oxidative phosphorylation activity, and the extracellular acidification rate (ECAR), which accounts for approximately 80% of acidification and is representative of glycolysis (Wu et al.). We evaluated the results of studies by al., 2007 (89); Xie et al., 2009 (90). Basal respiration was 38% lower in siOPA1-transfected HeLa cells than in siCtrl-treated cells (Figure 1). Furthermore, ATP-related respiration, as measured in the presence of oligomycin, which inhibits ATP synthase, decreased by 40%. Maximum OCR, as measured in the presence of the protonophore FCCP, which uncouples oxidation and phosphorylation, decreased by 58%. Maximum OCR in siOPA1-treated cells was not significantly different from basal OCR, in contrast to siCtrl-transfected cells. Rotenone (a complex I inhibitor) and antimycin (a complex III inhibitor) significantly reduced OCR in both siOPA1 and siCtrl-transfected HeLa cells, indicating that over 95% of oxygen consumption was due to mitochondrial respiration (Figure 1). Notably, the decrease in mitochondrial respiration in siOPA1-treated cells did not correlate with a decrease in mitochondrial biomass. In fact, the activity and amount of citrate synthase, as well as the levels of HSP60, VDAC, and TOM20, remained unchanged (Figures 18 and 19). The inventors investigated the mitochondrial network of SiCtrl-treated and SiOPA1-treated HeLa cells. In contrast to the filamentous mitochondrial network observed in physiocytes, SiOPA1-treated cells showed a fragmented mitochondrial network (Figure 20).

[0115] Downregulation of OPA1 induced a decrease in mitochondrial respiration, but total intracellular ATP levels remained unchanged (Figure 2). Furthermore, the reduction in OPA1 levels did not induce glycolysis in HeLa cells, as measured by ECAR (Figure 3) and extracellular lactate levels in the culture medium (Figure 4). Similarly, oligomycin treatment increased the oxidation rate in both siCtrl-treated and siOPA1-treated HeLa cells (Figure 3).

[0116] The downregulation effect of OPA1 on cellular respiration can be explained by a decrease in the levels or activity of mitochondrial respiratory chain (MRC) complexes. The levels of subunits NDUFB4 (complex I), SDHB (complex II), core 2 (complex III), and COX I (complex IV) were 44%, 29%, 39%, and 46% lower, respectively, in siOPA1-treated HeLa cells than in siCtrl-treated cells (Figure 5). However, the levels of other subunits such as NDUFA9 (complex I), SDHA (complex II), core 1 (complex III), and COX IV (complex IV) remained unchanged (Figure 5). The levels of the three ATP synthase subunits (α and γ for the F1 complex, and d for the F0 complex) were not affected by OPA1 silencing in HeLa cells (Figure 5). Next, the inventors evaluated the in vitro activity of complexes I-IV by spectrophotometric measurement. The activity of complexes I, III, and IV was unaffected in HeLa cells with downregulated OPA1, but the activity of complex II was reduced by approximately 25% (Figure 6). Succinate dehydrogenase is also an enzyme in the tricarboxylic acid (TCA) cycle. Therefore, we evaluated the levels of NADH,H+, the major TCA cycle product, in HeLa cells. The total intracellular level of NADH,H+ / NAD+ did not change in siOPA1-treated HeLa cells (Figure 21). Consequently, the activity levels of two other TCA cycle enzymes (fumarase and malate dehydrogenase) also did not change (data not shown).

[0117] 2.2. Downregulation of OPA1 leads to an unbalanced intracellular redox state. Loss of OPA1 leads to impaired mitochondrial respiratory chain function without disrupting the supply of NADH, H+. This can lead to increased electron leakage and, consequently, increased production of reactive oxygen species. Therefore, downregulation of OPA1 can result in an imbalance in intracellular redox homeostasis in HeLa cells.

[0118] The inventors investigated this possibility by first measuring the total ROS content using an H2-DCFDA probe. Surprisingly, ROS levels decreased by 23% in OPA1-downregulated HeLa cells 72 hours after transfection (Figure 7). The inventors then examined aconitase activity. Aconitase activity has been shown to be highly sensitive to oxidation due to a damaged FeS core. Therefore, inhibition of its activity has been widely used as an indicator of increased mitochondrial ROS production (Gardner et al., 1994 (60); Kelly et al., 2010 (65); Vincent et al., 2005 (80)). Aconitase activity was significantly lower in siOPA1-treated HeLa cells than in control cells (34%) (Figure 8). This decrease was not due to differences in protein levels, as protein levels remained unchanged (Figure 9).

[0119] 2.3. Downregulation of OPA1 activates a major antioxidant pathway: NRF2 transcription factor Although total intracellular ROS levels decreased, inhibition of aconitase activity provided evidence of increased mitochondrial ROS production. This suggests that the intracellular antioxidant response was activated upon downregulation of OPA1. Therefore, we first identified two redox reactions. The levels of glutathione and quinone, which are state markers, were analyzed. The ratio of reduced glutathione (GSH) to oxidized glutathione (GSSG) increased by 78% in siOPA1-treated HeLa cells, but this increase was not statistically significant (Figure 22). The redox state of quinones did not change upon loss of OPA1 (Figure 23).

[0120] The inventors then investigated the nuclear factor (erythrocyte-derived 2)-like 2 (NRF2) pathway, which accounts for the majority of the antioxidant response. The inventors evaluated the intracellular localization of NRF2, which shows activation, by immunofluorescence in HeLa cells 66–72 hours post-transfection (Figures 11 and 12). The dynamics of NRF2 immunostaining showed significant NRF2 nuclear relocalization, which began 67 hours after OPA1 downregulation (Figure 12). The inventors already knew that OPA1 protein levels decreased by 50% at 48 hours and 90% at 72 hours post-transfection (data not shown). Therefore, the inventors hypothesized that NRF2 migration occurs 48–72 hours post-transfection. 72 hours after transfection, 51% of siOPA1-treated HeLa cells showed nuclear localization of NRF2, while only 15% of siCtrl-treated cells showed nuclear NRF2 (Figures 11, 12, and 25). Therefore, we evaluated the levels of several NRF2 target proteins, including superoxide dismutase 1 and 2 (SOD1 and SOD2), catalase, NQO1, GSTP1, and ferritin heavy chain (FHC) and light chain (FLC). The amount of SOD1 protein was significantly higher in siOPA1-treated HeLa cells than in control cells (33%) (Figure 13). This increase correlated with a 37% increase in total SOD (SOD1 and SOD2) activity (Figure 14). The amount of GSTP1 protein also increased by 30% in siOPA1-treated HeLa cells (Figure 13). Neither the amount nor the activity of catalase changed with downregulation of OPA1 (Figures 13 and 15). Furthermore, no changes were observed in NQO1, FHC, or FLC protein levels in siOPAI-transfected HeLa cells. The data are summarized in Table 1.

[0121] [Table 1]

[0122] Table 1: Summary table of oxidative metabolism studies performed on OPA1 deficiency in HeLa cells. In summary, these results indicate that downregulation of OPA1 increases mitochondrial ROS levels, activates nuclear translocation of NRF2, which in turn upregulates antioxidant defense and reduces total cellular ROS. This leads to pro-oxidative stress, making cells more susceptible to subsequent stress.

[0123] 2.4. The deterministic mathematical model of complex I can predict the results obtained by down-adjusting OPA1. The data presented in Figure 16 shows that the inventors' algorithm, inputting data from their analysis, found no difference in the activity of complex I, regardless of whether OPA1 was downregulated, similar to the in vitro activity presented by the inventors in Figure 6 (this algorithm does not express results in the same units as the in vitro results in Figure 6 (micromoles / min / milligram protein instead of micromoles / min / million cells)). The inventors verified the stability of protein content in OPA1 downregulated cells and WT cells (SiLuc-treated cells: 99.23+ / -22.56, n=6 and SiOPA1-treated cells: 77.38+ / -16.20; p-value=0.4516, by unpaired t-test). Furthermore, the inventors' algorithm showed no difference in ROS generation by complex I (Figure 17).

[0124] 3. Discussion Mitochondrial respiration was impaired upon OPA1 downregulation in HeLa cells, as previously shown in several cell types (Millet et al., 2016(72)). However, this did not induce a transition to glycolysis. Overall, mitochondrial biomass remained unchanged, as estimated by measurements of both the levels of several mitochondrial proteins and citrate synthase activity. However, levels of certain subunits of the first four complexes of the mitochondrial respiratory chain were reduced. Thus, the reduction in mitochondrial respiration measured in siOPA1-treated cells did not correlate with a decrease in mitochondrial mass, but may be a consequence of impaired activity of the MRC complex. Only the activity of complex II was reduced.

[0125] 3.1. Cellular respiration is impaired in cells with downregulated OPA1 levels. The oxygen consumption rate (OCR) was significantly reduced in cells with downregulated OPA1. This phenomenon was also analyzed in vitro in OPA1-downregulated neurons, but without transition to glycolysis (Millet et al., 2016(72)). Since the levels of citrate synthase, HSP60, VDAC, and TOM20, as well as citrate synthase activity, remained unchanged in both siCtrl-treated and siOPA1-treated cells, the decrease in OCR observed in siOPA1-treated cells could not be attributed to a decrease in mitochondrial biomass. This phenomenon is similar to what was observed in our previous study on OPA1-downregulated rat neurons in primary culture (Millet et al., 2016(72)). Furthermore, the levels of subunits of the first four complexes of the MRC were found to be similar in vitro in both OPA1-downregulated HeLa cells and rat neurons, with the levels of specific subunits being significantly reduced. However, the amount of complex V (ATP synthase) did not change upon OPA1 inactivation in both cell models (Bertholet et al.). al., 2013(49); Millet et al., 2016(72). Such similar mitochondrial metabolic patterns in two very different cell types suggest that downregulation of OPA1 induces mitochondrial dysfunction, likely involved in both neurodegeneration and extraneuronal degeneration, as seen in DOA+ patients.

[0126] 3.2. The redox state is unbalanced in cells with downregulated OPA1. A significant decrease in the amount of MRC subunits and / or dysfunction of the complex's activity leads to increased mitochondrial ROS production while NADH levels remain stable. The fact that NADH, H+, NAD+, and the NAD+ / NADH ratio did not change in siCtrl-treated and siOPA1-treated HeLa cells means that the amount of substrate supplied to the MRC also did not change in both populations. Total intracellular ROS levels decreased, as already demonstrated in siOPA1-treated rat neurons in primary culture. However, aconitase activity also decreased, suggesting an increase in mitochondrial ROS levels. Therefore, the increase in intramitochondrial ROS production leads to an increase in the total intracellular ROS level. This did not correlate with the previous findings, suggesting activation of the antioxidant response during OPA1 downregulation. The inventors first investigated this possibility by analyzing two redox state markers, glutathione and quinone. The ratio of reduced glutathione (GSH) to oxidized glutathione (GSSG) in siOPA1-treated HeLa cells increased by 121% compared to control cells, but without statistical significance (Figure 22), and increased by 78.1% in siOPA1-transfected neurons (p<0.05) as previously described (Millet et al., 2016(72)). The redox state of quinones (oxidized quinone / (oxidized quinone + reduced quinone)) did not change with OPA1 loss (Figure 23). In summary, these results suggest that downregulation of OPA1 activates the antioxidant response by increasing the reduced form of glutathione, the major non-enzymatic antioxidant compound in cells. Quinones do not appear to be involved in mitochondrial ROS detoxification under the inventors' conditions. Again, the similarity between the data obtained in neurons and HeLa cells is remarkable. These data suggest activation of antioxidant signaling pathways to mitigate increased mitochondrial ROS production.

[0127] 3.3. Antioxidant defense is activated in cells with downregulated OPA1 levels. Nuclear levels of NRF2, a major transcription factor involved in antioxidant defense (Ma, 2013(69)), were analyzed over time to assess its activation during OPA1 downregulation. A significant increase in NRF2 nuclear translocation was observed in siOPA1-transfected cells 67–72 hours post-transfection. Notably, OPA1 levels decreased by 50% and 90% at 48 and 72 hours post-siOPA1 transfection, respectively. This correlation between decreased OPA1 content and NRF2 nuclear translocation is particularly interesting as it highlights the relationship between OPA1 and redox states.

[0128] We measured the levels of various NRF2 targets under two conditions; the amounts of SOD1 and GSTP1, which increase during OPA downregulation; and SOD activity. Similarly, both the levels and activity of catalase, another NRF2 target, were elevated in siOPA1-treated neurons (Millet et al., 2016(72)). Superoxide anion detoxification was clearly activated in both cell types, supporting the importance of this phenomenon and the universal involvement of OPA1 in redox signaling.

[0129] This study is clearly consistent with the literature linking OPA1 to redox states in invertebrates (Kanazawa et al., 2008 (64); Yarosh et al., 2008 (81)), and confirms our results in neurons and transgenic mouse cortex (Daloyau et al., 2018 (56); Millet et al., 2016 (72)), allowing for a more precise identification of the activating factors. Furthermore, this paper highlights the ubiquitous effects of OPA1 deficiency on oxidative metabolism in different cell types. Recent studies analyzing OPA1 expression during H2O2 treatment have shown a significant decrease in the long-chain form of OPA1 (Garcia et al., 2018 (59)). Destabilization of the long-chain form of OPA1 then leads to intima-disordering, emphasizing the effect of MRC reorganization and increasing ROS production. In other words, this phenomenon may represent a vicious cycle (Figure 25).

[0130] 3.4. Replicated cells as a biological material for predicting and treating OPA1 gene mutation-related disorders The high convergence of results based on two remarkably different biological models of DOA opens the way to novel ways to analyze, predict, and, in some cases, treat OPA1 dysfunction. Furthermore, the use of mathematical models for complex I activity and ROS generation is also intriguing. In this study, the algorithm fully simulates complex I activity with and without OPA1 expression. Activity is measured both in silico simulation (Figure 16) and in vivo analysis (Figure 6). It is stable in this case. Regarding ROS production, simulations suggest that complex I is not the primary ROS producer. In this context, complex III is the most likely activator of mitochondrial ROS production. In silico simulations using our mathematical model of complex I activity in combination with ROS production are a powerful tool for integrating different biological data and predicting the evolution of the described processes.

[0131] This is a practical demonstration of the concept of translational medicine in the field of neurodegenerative diseases. The inventors plan to analyze the oxidative metabolism of DOA and DOA+ patients using fibroblasts (Millet et al., 2016(72)) and epithelial cells from patient biopsies to predict the evolution of disease that is currently uncontrollable. By combining experimental and mathematical models and considering mitochondrial ROS production and ROS detoxification pathways, the capabilities of wet laboratory investigations will be enhanced, and disease evolution will be predicted more accurately (Merabet et al., 2017(29); Millet A. et al., 2017(71)).

[0132] Mitochondria have long been proposed to play a crucial role in aging (Green et al., 2011(61)). As a result of their central role in ATP formation via MRCs, mitochondria are a major source of ROS and therefore highly involved in oxidative stress processes (Brookes et al., 2004(50)). However, mitochondria are also targets of these molecules (Brookes et al., 2004(50)). Under physiological conditions, approximately 1-3% of molecular oxygen is incompletely reduced during redox reactions in MRCs, producing ROS superoxide anions (O2). -) Byproducts are produced. In this scenario, complex interactions in the antioxidant defense system suppress oxidative stress in mitochondria (Kienhofer et al., 2009(66)). Cell systems that protect against oxidants include antioxidant defense enzymes (superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase) (Kienhofer et al., 2009(66)), oxidant scavengers (vitamin E, vitamin C, carotenoids, uric acid, and polyphenols), and mechanisms that repair oxidant-induced damage to lipids, proteins, or DNA. Despite these protective mechanisms, uncontrolled ROS production can overwhelm the capacity for antioxidant protection and lead to mitochondrial dysfunction (e.g., Parkinson's disease is directly involved in complex I dysfunction). In vivo studies in transgenic mice have shown that overexpression of mitochondrial-targeting catalase reduces age-related diseases and increases their lifespan (Lopez-Armada et al., 2013(68); Schriner et al., 2005(76)). Based on these observations, our overall research clearly suggests that downregulation of OPA1 in cell and animal models induces an imbalance in redox states that can lead to premature cellular senescence.

[0133] 4. Materials and Methods 4.1. Cell culture HeLa cells from the American Type Culture Collection (Manassas, VA) were cultured in a 37°C, 5% CO2 incubator in Dulbecco-modified Eagle medium (DMEM, Invitrogen) supplemented with 10% FCS, penicillin (100 units / ml), and streptomycin (100 mg / ml) containing 4.5 g / l glucose. The HeLa cells were cultured in 10 6Using 1.5 μg of control siRNA (D-001210-02, Dharmacon Research) or human OPA1 siRNA (D005273-03, target sequence AAAGAAGGCUGUACCGUUA (Sequence ID 1), Dharmacon Research) per cell. Then, electroporation was performed using the Cell Line Kit R (Amaxa, Lonza).

[0134] 4.2. Measurement of oxygen consumption rate, extracellular acidification rate, and ATP level Oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were measured using an XF24 Extracellular Flux Analyzer (Seahorse Bioscience, North Billerica, MA). HeLa cells (15.103) transfected with siCtrl or siOPA1 were plated into an XF24 microplate three days prior to OCR measurement. The dual analyte sensor cartridge was hydrated overnight at 37°C by immersion in XF Calibrant Solution (Seahorse Biosciences) in a 24-well cell culture microplate. Approximately one hour before the experiment, the injection port on the sensor cartridge was filled with oligomycin (1 μM), carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) (1 μM), and rotenone (1 μM) + antimycin A (1 μM). The plate was then loaded into the XF24 instrument for calibration. To measure oxygen consumption, the DMEM growth medium for HeLa cells was replaced with pH 7.4 DMEM supplemented with NaCl (143 mM), phenol red (3 mg / ml), glucose (10 mM), glutamine (2 mM), and pyruvate (2 mM), and the plates were maintained at 37°C for 1 hour prior to the experiment. The plates were then loaded into a Seahorse XF24 analyzer according to the manufacturer's instructions.

[0135] ATP levels in HeLa cells were determined using an ATP colorimetric / fluorescence assay kit (Abcam). Intracellular ATP levels were determined using a colorimetric assay in 1.106 HeLa cells transfected with control siRNA or OPA1 siRNA, according to the manufacturer's instructions. ATP content was measured in dual (570 nm) and calculated per microgram of protein.

[0136] 4.3 Activity of the in vitro respiratory chain complex The activity of respiratory complexes II and IV and citrate synthase was measured as previously described (Agier et al., 2012(88)). The activity of respiratory complexes I and III was measured as previously described (Spinazzi et al., 2011(78)).

[0137] 4.4. Extracellular lactate levels Extracellular lactate levels were measured using a colorimetric assay (BioMerieux). 72 hours after transfection of HeLa cells with siCtrl or siOPA1, lactate levels in the culture medium supernatant (1 / 10 dilution) were measured at 505 nm according to the manufacturer's instructions.

[0138] 4.5. Immunoblot Analysis Transfected HeLa cells were lysed for 30 minutes in RIPA buffer containing 50 mM Tris-HCl pH 7.5, 250 mM NaCl, 5 mM EDTA, 5 mM EGTA, 1 mM dithiothreitol, 0.1% Triton X-100, 0.1% SDS, 1% deoxycholic acid, 1% NP40, and a protease inhibitor ("Complete" protease inhibitor mixture, Roche Applied Science). The cell lysates were then centrifuged at 14,000 g at 4°C for 10 minutes. The total protein concentration in the supernatant was determined using the Bradford protein assay (Bio-Rad).

[0139] Proteins (100-200 μg) were separated by SDS-PAGE (8-15%). The molecules were then transferred onto a nitrocellulose membrane (Whatman, Protran). The free binding sites were blocked with 5% skim milk powder in 1× Tris-buffered saline (pH 7.6) (blocking buffer) containing 0.2% Tween 20. The membranes were then subjected to various primary antibodies (anti-OPA1 (1 / 300, BD-Biosciences), anti-actin (1 / 25,000, Chemicon), anti-HSP60 (1 / 8,000, Sigma), anti-OXPHOS (1 / 200, Mitosciences), anti-NDUFB4 (1 / 500, Mitosciences), anti-NDUFA9 (1 / 100, Mitosciences), anti-SDHA (1 / 1,000, Abcam), anti-Core1 (1 / 500, Invotrogen), anti-COXIV (1 / 250, Cell Signaling)). The samples were probed with the following antibodies: anti-ATP5C1 (1 / 500, Abgent), anti-ATP5H (1 / 5,000, Abcam), anti-aconitase (1 / 500, Abcam), anti-SOD1 and anti-SOD2 (1 / 2,000, Epitomics), anti-catalase (1 / 3,000, Abcam), anti-NQO1 (1 / 3,000, Abcam), anti-GSTP1 (1 / 8,000, Oxford Biochemical Research), anti-ferritin heavy chain (1 / 500, Abcam), and anti-ferritin light chain (1 / 4,000, Abcam). These were incubated overnight at 4°C in blocking buffer. After chemiluminescence detection of horseradish peroxidase conjugate secondary antibody (1 / 50,000, Abcam), scanned photographic films were analyzed using Imaged software.

[0140] 4.6. Immunocytochemistry or Mitotracker staining HeLa cells were fixed in PBS containing 3.7% formaldehyde for 20 minutes, permeabilized in 1×PBS and 0.25% Triton™ X-100 for 5 minutes, incubated with methanol at -20°C for 10 minutes, and then nuclear NRF2 detection was performed. Nonspecific binding sites were blocked with 3% BSA in 1×PBS at room temperature for 15-30 minutes. Cells were immunostained with rabbit polyclonal anti-NRF2 antibody (1 / 50, Santa Cruz Biotechnology) at 37°C for 1 hour. Subsequently, the HeLa cells were Alexa-enhanced. HeLa cells were incubated with fluor 488 conjugate secondary antibody (1 / 300, Molecular Probes), labeled with 0.25 μg / ml Hoechst in 1×PBS for 5 minutes, and mounted in Mowiol. Immunolabeling of HeLa cells was visualized under a fluorescence microscope (Nikon Eclipse 80i) 66, 67, 68, 69, 70, and 72 hours after siCtrl or siOPA1 transfection, and images were acquired using NIS-Element (Nikon Digital Sight DLIS2 camera). HeLa cells showing accumulation of NRF2 staining in the nucleus were counted by stacking nuclear Hoechst-labeled cells using Imaged software.

[0141] The mitochondrial network was stained with Mitotracker Red (Invitrogen molecular probes FM Invitrogen M22425) in culture medium at 37°C and 5% CO2 for 15 minutes. The cells were then fixed in PBS containing 3.7% formaldehyde for 20 minutes, permeabilized in 1×PBS and 0.25% Triton® X-100 for 5 minutes, and mounted in DAPI mounting medium.

[0142] 4.7. Measurement of reactive oxygen species levels and aconitase activity ROS levels in HeLa cells were measured using the fluorescent dye 2',7'-dichlorodihydrofluorescein diacetate (CM-H2-DCFDA, Molecular Probes) at a concentration of 4 μM for 30 minutes at 37°C. Fluorescence intensity was measured at 493 nm using a WALLAC VICTOR 1480 Multilabel Counter.

[0143] Mitochondrial superoxide production was measured using a fluorescence microscope (×40) with 5 μm MitoSOX Red (mitochondrial-targeted superoxide index) according to the manufacturer's protocol. MitoSOX measurement was performed using siCtrl or siOP The procedure was performed 72 hours after A1 transfection. Fluorescence intensity quantification was analyzed using Imaged software.

[0144] Aconitase activity in HeLa cells was measured at 525 nm using a previously described protocol (Colombani et al., 2009(54)) (UVIKON spectrophotometer 922).

[0145] 4.8. Enzyme Antioxidant Activity Superoxide dismutase (SOD) activity (Mn SOD and Cu / Zn SOD) was assayed by inhibiting pyrogallol autooxidation in HeLa cell extracts, similar to how aconitase activity was assayed. One enzyme unit of SOD activity was defined as the amount of enzyme that inhibits pyrogallol autooxidation by 50% (Galinier et al., 2006(58)). Catalase activity was determined by measuring the decomposition of H2O2 at 240 nm (Galinier et al., 2006(58)).

[0146] 4.9. Statistical analysis Most experiments were statistically analyzed using Student's paired t-test for a systematic comparison between siCtrl-treated HeLa cells and siOPA1-treated HeLa cells. Oxygen consumption rates between siCtrl-treated and siOPA1-treated HeLa cells were examined using a non-parametric test (Mann-Whitney). P-value: p<0.05 * p<0.01 ** , p<0.001 *** .

[0147] 4.10. Immunoblot Analysis The membranes were probed with various primary antibodies (anti-OPA1 (1 / 300, BD-Biosciences), anti-actin (1 / 25000, Chemicon), anti-HSP60 (1 / 8000, Sigma), anti-citrate synthase (1 / 3000, Abcam), anti-VDAC (1 / 1000, Abcam), and anti-TOM20 (1 / 3000, Abcam)) and incubated overnight at 4°C in blocking buffer. After chemiluminescence detection with horseradish peroxidase conjugate secondary antibody (1 / 50000, Abcam), scanned photographic films were analyzed using Imaged software.

[0148] 4.11. Citrate synthase activity Citrate synthase activity was evaluated in lysates of HeLa cells transfected with siCtrl or siOPA1. Citrate synthase activity was determined by measuring TNB, which is produced by the reaction of CoA-SH with 5'5-dithiobis-2nitrobenzoic acid (DTNB). 930 μl of reaction medium (100 μM DTNB, 100 mM TrisHCl (pH 8.0), 300 μM acetyl-CoA, 500 μM oxaloacetate, 0.1% Triton X-100) and 40 μg of protein were measured at 412 nm (37°C). The reaction was initiated by adding 50 μl of 10 mM oxaloacetate diluted in 100 mM Tris HCl (pH 8.1).

[0149] 4.12. NAD + and NADH, H +level Intracellular NAD in HeLa cells + and NADH levels, NAD + The measurement was performed using the / NADH assay kit (Abcam) according to the manufacturer's instructions. In short, 2.10 6 HeLa cells were transfected with either a small interfering RNA control or a small interfering RNA targeting OPA1. Cells were washed with cold PBS and extracted with NADH / NAD extraction buffer by two freeze / thaw cycles (20 minutes on dry ice, followed by 10 minutes at room temperature). Total NAD (NADt) and NADH levels were detected in a 96-well plate, colorimetrically developed, and read at 450 nm. The NAD+ / NADH ratio was calculated as (NADt - NADH) / NADH.

[0150] 4.13. Glutathione and quinone levels HeLa cells were lysed in 200 μl of 5% metaphosphate and then centrifuged at 1,500 g for 10 minutes at 4°C. The final supernatant was prepared as previously described (Galinier et al., 2006(58)), glutathione assay performed by reverse-phase high-performance liquid chromatography (HPLC) It was used for the measurement of protozoan GSH and oxidized GSSG. The reduced and oxidized levels of quinone were determined as described (Galinier et al., 2006(58)).

[0151] Example 2 - Multi-objective optimization of a mitochondrial process model: A novel tool for precision medicine 1. Introduction In the context of precision medicine adapted to different pathologies (neurodegenerative diseases, metabolic diseases, or inflammatory processes), conventional biological approaches remain insufficient. Systems biological methodologies related to engineering techniques are needed. This procedure is used to build knowledge models of biological mechanisms. In cell systems, mitochondria are the primary providers of energy: adenosine triphosphate (A) via oxidative phosphorylation. TP). The oxidative phosphorylation system consists of five enzyme complexes tethered to the inner mitochondrial membrane. Four of these complexes (complexes I-IV) constitute the respiratory chain. By transferring protons (H+), complexes I, VI, and IV establish an electrochemical gradient. This process involves continuous electron transfer from nicotine, reduced nicotinamide adenine dinucleotide (NADH), and succinate. It is driven by the redox energy released during electron transfer to oxygen. The fifth complex uses this electrochemical gradient generated by complexes I, III, and IV to catalyze the phosphorylation of adenosine diphosphate (ADP) to ATP. (Mitchell, 1961 (30); Mitchell, 1966; (31)).

[0152] During normal MRC function, reactive oxygen species (ROS) are essentially produced by complexes I and III. ROS are derivatives of diatomic oxygen with excess electrons. However, dysfunction of complexes I and III caused by different factors (genetic, environmental, or pathological) leads to a dramatic increase in their ROS production. This increase, if not balanced by antioxidant defenses, induces the destruction of lipids, proteins, and DNA. This phenomenon almost always ultimately leads to cell death associated with inflammatory processes. We previously developed a probabilistic mechanical model of complex I that can simulate the activity of complex I and its ROS production (Merabet, 2017(29)). In this embodiment, we focused on deterministic models of complexes I and III.

[0153] 2. Biological mechanisms of the mitochondrial respiratory chain Complex I is the electron gateway in respiratory chain 2. It catalyzes the oxidation of NADH to NAD+ and the reduction of ubiquinone (Q) to ubiquinol (QH2). This reaction allows four protons to move from the matrix into the intermembrane space.

[0154]

number

[0155] "x" refers to the mitochondrial matrix, and "is" refers to the intermembrane space.

[0156] NADH is a non-covalently bonded flavin mononucleotide (F). It is oxidized by MN). The severely reduced flavin, FMNH, and the half-reduced flavin, FMNH, each transfer one electron to a chain of eight iron-sulfur (FrS) clusters that constitute the redox center of complex I. The last cluster in the chain is the electron donor to the Q-binding site. It is widely accepted that biological electron transport is a tunneling process (Moser et al., 1992(32)).

[0157] Complex III oxidizes ubiquinol and reduces cytochrome c. In mammals, complex III is a dimer consisting of 11 subunits per monomer, as described by Iwata et al., 1998 (23). Of these 11 subunits, three are conserved across species from bacteria to mammals and are the four groups involved in the redox function of complex TH: cytochrome b, the bH and bL heme of cytochrome c1, and the [2Fe-2S] center of Rieske protein (ISP). The mechanism of the reaction catalyzed by complex III is called cycle Q. It was first proposed by Mitchell (1975) (91) and subsequently modified (Hunte et al., 2003 (22); Berry et al., 2000 (4)). This mechanism is based on the presence of two binding sites of Q / QH2 redox pairs, called the Qo site and the Qi site. Oxidation of ubiquinol at the Qo site induces the release of two protons and the transfer of two electrons to complex III. The first electron is transferred to the Fb-S group of PSI, then to cytochrome c1, completely reducing cytochrome c (high-potential chain). The other electron enters the low-potential chain with the reduction of heme bL, then to heme bH, and finally to ubiquinone at the Qi site, forming stabilized semiquinone (Hunte et al., 2003(22); Berry et al., 2000(4)). This can be detected and released from the positive side of the membrane, and the second cytochrome c is reduced via the high-potential chain, while the second electron is transferred to the Qi site via the low-potential chain, reducing semiquinone back to ubiquinol. This second step involves the use of two protons (Berry et al., 2000(4)).

[0158] Reactive oxygen species (ROS), more precisely superoxide anions, are primarily produced in mitochondria by MRC complexes I and III. Respiratory chain complexes I and III are considered to be the main producers of superoxide anions and their derivatives within mitochondria (Bleier and Drose, 2013(5); Wong et al., 2017(43); Pryde and Hirst, 2011(36); Murphy, 2009(92)). Superoxide production by Complex I has been demonstrated using isolated complexes (Kussmaul and Hirst, 2006 (26); Esterliazy et al., 2008 (93)), submitochondrial particles (Vinogradov and Grivennikova, 2005 (42); Pryde and Hirst, 2011 (36); Genova et al., 2001 (15); Fato et al., 2009 (13); Grivennikova and Vinogradov, 2013 (17); Maranzana et al., 2013 (28); Kim et al., 2018 (24)), and intact mitochondria from multiple sources. Two modes of superoxide production by Complex I have been identified: a direct production mode in the presence of NADH and a retroproduction mode in the presence of succinate.

[0159] ROS generation in direct mode is maximal when the NADH / NAD+ ratio is high (the NAD pool is strongly reduced) and when complex I is inhibited by a Q-site inhibitor (e.g., rotenone) in mitochondria and submitochondrial particles (Kussmaul and Hirst, 2006(26); Lambert and Brand, 2004(27)). The second generation mode involves coupled submitochondrial particles and This was observed in contact mitochondria. This production mode depends on the reverse transfer of electrons in complex I, which requires the presence of a highly reduced quinone pool and a sufficiently high electrochemical gradient. The production rate measured in reverse mode can be up to three times that of the direct mode, measured under optimal conditions for KOS production in direct mode (presentation of a completely reduced NAD pool and Q site, and presence of a complex I Q site inhibitor such as rotenone). The reverse production mode of complex I has been known since the 1960s, as described by Hinkle et al., 1967(21), but has long been considered a phenomenon of no physiological relevance. However, several studies have suggested that this process, which does not require inhibition or dysfunction of complex I, may have physiological validity. In fact, this process may play an important role in the redox signaling mechanism at the basal position and in pathological oxidation mechanisms (especially in pathological mechanisms) (Chouchani et al., 2016(8); Pell et al., 2018(35); Robb et al, 2018(38)).

[0160] Complex III can produce large amounts of superoxide when inhibited by antimycin A at the Qi site. This production occurs at the Qo site, and the generated superoxide is released to both sides of the inner mitochondrial membrane. In the absence of antimycin A, complex III can produce O2 - The generation of (T) is low or undetectable. ^ irrens et al., 1985 (41); Muller et al, 2002 (33); Muller et al., 2003 (34); Drose and Brandt, 2008 (11); Borek et al., 2008 (6); Chen et al., 2003 (7); Ksenzenko et al., 1983 (25)). However, in the presence of physiological membrane potential, purified yeast complex III reconstituted iii phospholipid vesicles also produce a non-negligible amount of ROS (Rottenberg et al., 2009 (39)). The rate of ROS production increases exponentially as a function of membrane potential and can reach values ​​similar to the underlying antimycin A obtained. Furthermore, the absence of production by complex 111 under basal conditions does not mean that this production cannot be increased under pathological conditions (Bleier and Drose, 2013(5)). This oxygen electron donor is the semiquinone produced at the Qo site (Drose and Brandt, 2008(11); Fisher et al., 2016(14)).

[0161] 3. Modeling of enzyme dynamics 3.1 Complex I Complex I is considered a system capable of transferring electrons from a donor (NADH) to several receptors (Q, O2) depending on the situation. The inventors relate their observations to the formulas of Michaelis and Menten. At the two active sites, substrates must bind to Complex I to enable electron transfer (donor or receptor). Furthermore, once products are formed, they access the active sites and block subsequent substrates. These products constitute competitive inhibition of their own substrates. The function of the active sites takes the following forms:

[0162]

number

[0163] f NADH About

[0164]

number

[0165]

number

[0166] There is also the phenomenon of inhibition by the substrate. These can physically prevent the product from leaving the active site, reducing the resulting activity. Complex I has the ability to accumulate a limited number of electrons within itself. Therefore, the more electrons the complex stores, the slower the reaction rate of electron donation from NADH to the complex becomes, and the bottleneck effect is felt more strongly. Thus, if quinone Q has a low ability to accept electrons, the complex will slowly become empty, resulting in a bottleneck, and NADH will not be able to donate its electrons very quickly, and therefore,

[0167]

number

[0168] Superoxide anion (O2) ·- The generation of [the substance] is proportional to the amount of oxygen, but it is also inhibited by the following two phenomena: NAD + It blocks access to oxygen when donating electrons to the complex. This effect is modeled by competitive inhibition. • The complex functions properly when the availability of quinone Q is sufficiently high. The inventors add an empirical parameter α to control this phenomenon.

[0169] Since the two types of inhibition do not act at the same site, they are multiplied by the following formula:

[0170]

number

[0171] By using the mechanism of complex I in direct mode, the inventors can transfer its activity for each electron pathway. When all substrates are present at their sites, the NADH molecule donates two electrons, both of which are donated to the quinone site or directly to oxygen reduction.

[0172]

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[0173] The inventors of this invention have identified a constant V + The ability of complex I to accept electron transport is modeled using this method. The inventors have separated the different pathways so that a normal pathway involving quinone reduction can be obtained.

[0174]

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[0175]

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[0176] A second operating mode can be added to the direct mode: inverse mode. In inverse mode, quinol QH2 becomes the electron donor, and NAD + Alternatively, O2 acts as a receptor. NAD + and f QH2 The function is then used in conjunction with the mirror configuration of its direct mode equivalents. O2 ·- Regarding generation, the inventors assume that the electron donor is flavin as described above, but in direct mode O2 ·-The presence or absence of quinones that inhibit generation does not affect the reverse mode, so we remove them from Equation 4.

[0177] After all these equations are established, constant

[0178]

number

[0179] The inventors use a total of five direct models of Complex I. The first model (number 1) is the simplest of all and uses the formulas presented earlier in 2, 3, 4, 6, and 7. Model N * 2 represents one of the Michaelis constants using the sigmoid function. Models 3 and 4 are f Q and NAD + f by O2 Consider inhibition of 2. The fifth and final models implement steric inhibition of NADH.

[0180] Each model improves upon the previous one, and therefore, Model 5, taking into account all the additions mentioned, is the most complete.

[0181] 3.2 Complex III Complex III, depending on the situation, receives several receptors (Q, Cyt) from the donor (QH2). c It is thought to be a system capable of transferring electrons to O2. • If quinone is not present at the Qi site, cytochrome C acts as the receptor. • If antimycin is present, cytochrome C and oxygen accept electrons.

[0182] The inventors use the formulas of Michaelis and Menten to relate their observations to the formulas. At the three active sites, substrates must bind to complex III to enable electron transfer (donor or acceptor), and furthermore, once products are formed, they access the active site and block subsequent substrates. These products constitute competitive inhibition of their own substrates. The function of the active sites takes the following forms:

[0183]

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[0184]

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[0185]

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[0186] The effect of antimycin on complex III and the QH2 oxidation rate allows the inventors to hypothesize that there is a dependence between the QH2 oxidation rate and the ability of cytochrome C to accept electrons. When cytochrome C has a high electron-accepting ability, QH2 can donate electrons more quickly, (n) therefore,

[0187]

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[0188]

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[0189]

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[0190] The electrons generated in complex III are preferentially accepted by the two substrates Q and cytochrome C, and therefore

[0191]

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[0192] The inventors have developed a method that includes the inhibition of antimycin,

[0193]

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[0194]

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[0195] By using the mechanism of Complex III, the inventors can transfer the activity of each component. When all substrates are present at their sites, the quinol molecule donates two electrons, one to each site. Cytochrome C is reduced, and the quinone is partially reduced to obtain the following:

[0196]

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[0197] The inventors of this invention have identified a constant V + We use this to model the ability of complex III to accept electron transfer. In the absence of the quinone, the two electrons of the quinone reduce the two cytochromes. The presence of the quinone is considered to be an inhibitor here.

[0198]

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[0199] In the presence of antimycin, the electrons of quinol are distributed between cytochrome and heme bL. Q o The quinone molecule in this region collects electrons from heme bL via reverse transfer and donates them to oxygen.

[0200]

number

[0201] QH2, Q, cytc ox cytc red The concentrations of O2 and antimycin are input data from the literature.

[0202] The inventors used the model of complex III, and other constants

[0203]

number

[0204] The inventors use a total of three models for complex III. The first model (number 1) is the simplest and uses the presented formula. The second model uses a sigmoid function to represent one of the Michaelis constants. The third and last models implement the inhibition of complex III by antimycin.

[0205] Each model improves upon the previous one, and therefore, Model 3, taking into account all the additions mentioned, is the most complete.

[0206] 4. Multi-objective optimization Optimization function The inventors use experimental data from the following paper: Regarding Complex I, there are three; regarding activity, one (Heiske et al., 2014(20)); and regarding ROS generation, another (Kussmaul and Hirst, 2006(26); Grivennikova and Vinogradov, 20 06(16)). There are two studies on Complex III, one on its activity (Heiske et al., 2017(19)), and another on ROS generation (Drose et Brandt, 2008(11)).

[0207] The inventors explore ways to minimize the maximum difference between model evaluation and experimental data: optimization is guaranteed through constant values.

[0208]

number

[0209] fi is the i-th objective function, and V exp,i V is the catalytic rate vector in the i-th target experiment. mod i This is the catalytic rate vector evaluated by the model. Because the order of magnitude between the catalytic rate and the ROS generation rate is too large, the inventors use the method of Grodzevich et Romanko, 2006(18).

[0210]

number

[0211] To optimize the parameters, the inventors establish an objective function from experimental data from the literature and from modeling of this data using their own model. Therefore, the inventors seek to minimize the difference between the experimental data and their model. The optimization domain is limited by two points. • Ideal point: This is the ideal objective vector that minimizes each objective function individually. • Worst-case scenario: This is a vector that refers to the worst-case optimization of each objective function, which has a solution found for the ideal point.

[0212] Normalization allows us to assign a score between 0 and 1 to each objective function. A score close to 0 means that the solution is close to the ideal and therefore represents a good multi-objective solution. Conversely, a score close to 1 yields a solution that should be excluded.

[0213] Superiority These scores allow us to sort the most interesting solutions according to their superiority. Solution a is superior to solution b if each of its scores is less than or equal to each of b's scores, and there is at least one score lower than each of b's scores.

[0214]

number

[0215] k is the number of optimization objective functions. These solutions are arranged by front, with front 1 containing all non-dominant solutions, and front 2 containing solutions that are dominant only once. The sequence continues similarly until all fronts are present.

[0216] The congestion distance (Deb, 2002(10)) allows solutions to be ranked within the same dominance front. For each objective, the solutions with the highest and lowest scores have an infinite distance. Intermediate solutions have a congestion distance calculated by the normalized absolute difference of the objective function solutions (i+1 and i-1) adjacent to solution i. In other words, for each objective function fj, if j ∈ {1, ..., k}, the solutions are sorted in ascending order of score, and intermediate solutions Xi, i ∈ {2, ..., NP-1} are calculated as follows:

[0217]

number

[0218] The total clutter distance can be calculated by adding the distances of each target for a given solution Xi. Therefore, the set of solutions is first prioritized by its superiority rank, and then, within that rank, the solution with the largest clutter distance is considered the best solution.

[0219] Initial Population The initial candidate population is usually randomly generated to cover a broader field of the research area. However, experimental data and the objective function allow for prior knowledge of relevant intervals for different parameters. Nevertheless, this method can converge towards a local minimum, distorting the continuation of the procedure. Therefore, Afi's method is used to generate a population of size NP following a uniform random distribution, while being constrained by the user, and a population of opposing candidates is constructed in parallel to reinforce the total population. Dimension n candidate X=(x 1; x2,...,x n ) is true for all i∈[1,2,...,n] Xi ∈[l l ,u l Constructed to have ] and x i =l i +(u i -l i ) * U(0,1). The opposite candidate X'=(x'1,x'2,...,x' n ) is x' i =l i +u i -x i These candidates are defined by ~, and all of them constitute a set of 2NP candidates. The inventors use the superiority sorting method described above for the set of NP best candidates.

[0220] Evolutionary algorithm: When a population is formed, each X pG The candidate (the p-th candidate of population generation G) undergoes a differential evolution algorithm with three operators: mutation, crossover, and selection.

[0221] Mutation: This operator creates a new candidate from three candidates in the current population. Candidate X p,G Three random candidates

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number

[0223]

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[0224]

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[0225] F is a control parameter between 0 and 1.

[0226] Crossover: Mutation candidate M p,G =(m p,G,1 ,...,m p,G,n ) to initial candidate X p,G =(x p,G,1 ,...,x p,G,n ) intersects with provisional candidate C p,G =(c p,G,1 ,...,c p,G,n )

[0227]

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[0228] Selection: Typically, selection occurs between initial candidates and crossover candidates, with the best candidate being selected to incorporate into the next generation's initial population, while the others are simply discarded. The unselected candidates are then placed in a pool, and as the entire population runs through the evolutionary algorithm, this pool is challenged with previously selected candidates, retaining only the best NP for the next generation's population.

[0229] The evolutionary algorithm can be stopped early once a certain population convergence is reached. This convergence is measured using the stability of the density of non-dominant solutions. In other words, the stopping criterion is based on the evolution of solution congestion, and when the congestion distance no longer evolves significantly over several generations, convergence is observed, and therefore the search for solutions stops. The inventors have found that the generation

[0230]

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[0234] At this stage, even after convergence

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[0239] 5. Results and Discussion The inventors constructed models of the catalytic activity of complex I and its superoxide anion generation in both direct and reverse modes. To construct these models, they modified classical enzyme rate equations to suit the specificity of complex I. The inventors optimized the parameters of the direct model using a multi-objective algorithm.

[0240] The model of complex I can simulate catalytic activity (Figure 26) and ROS generation (Figure 27) in direct mode for different substrate and product configurations and concentrations.

[0241] When the NADH concentration varies but the quinone Q concentration (1.1–70 μM) remains constant, our Model No. 5 is the most accurate when compared to experimental data. The results from Models 1–5 are shown in Figures 26A–I.

[0242] When the quinone Q concentration varies and the NADH concentration (1-47.5 μM) remains constant, our Model No. 5 performs better than experimental data in most cases. The results from Models 1-5 are shown in Figures 26J-R.

[0243] Quinol QH2 concentration or QH2 / Q tot When the ratios differ and the concentrations of NADH and quinone Q are constant, our Model No. 5 is the most accurate when compared to experimental data. The results from Models 1-5 are shown in Figures 26S-U.

[0244] Finally, NAD + When the concentrations of different substances differ, but the concentrations of NADH and quinone Q are constant, our Model No. 5 is the most accurate when compared to experimental data. The results from Models 1 to 5 are shown in Figures 26V to X.

[0245] NAD + When the concentrations differ, Model No. 5 performs best for low concentrations of NADH, but diverges for high concentrations of NADH. The results from Models 1-5 are shown in Figure 27A.

[0246] NAD + Model No. 5 performs best when the concentrations differ. The results from Models 1-5 are shown in Figure 27B.

[0247] For concentrations of NADH = 30 μM and Q = 100 μM, all models are acceptable. The results from models 1 to 5 are shown in Figure 27C.

[0248] The inventors can observe actual improvements in the simulation through the iterative process from Model 1 to Model 5.

[0249] CytoC ox When the concentrations of different substances differ, but the concentration of quinol QH2 (70-210 μM) remains constant, our Model No. 3 is the most accurate when compared to experimental data. The results from Models 1-3 are shown in Figures 28A-C.

[0250] The concentration of quinol QH2 differs, and CytoC ox When the concentration (20-80 μM) is constant, Model No. 3 is the most accurate when compared to experimental data. The results from Models 1-3 are shown in Figures 28D-F.

[0251] The concentrations of quinone Q differ, resulting in quinol QH2 and CytoC ox When the concentration (20-80 μM) is constant, our Model No. 3 is the most accurate when compared with experimental data. The results from Models 1-3 are shown in Figures 28G-J.

[0252] CytoC red When the concentrations and proportions of the other substances differ, but the concentration of quinol QH2 (210 μM) remains constant, Model No. 3 is the most accurate when compared to the experimental data. The results from Models 1-3 are shown in Figures 28K-N.

[0253] When the proportion of quinone Q differs, Model No. 3 is the best. The results from Models 1-3 are shown in Figure 29.

[0254] The inventors applied the modeling method used for Complex I to Complex III. They created a model capable of simulating ROS generation and the catalytic activity of Complex III. They also performed sensitivity analysis using the same method as for Complex I.

[0255] Gauthier et al. (2013a) constructed a mathematical model of ROS generation by complexes I and III to study ROS generation in cardiomyocytes under different metabolic conditions. However, this model focuses only on ROS generation and does not examine the respiratory chain, which lacks catalytic activity. Another model of ROS generation by complexes I and III has been proposed by Bazil et al. (2). This model includes the respiratory chain model developed by Beard et al. (3). The Beard et al. (3) model models the activity of the respiratory complexes by the law of mass action. In the Bazil et al. (2) model, the model for complex I is the same as that previously proposed by Bazil et al. (1). Furthermore, the Bazil et al. (1) model assumes ROS generation by a semiquinone donor, which is inconsistent with the experimental data obtained for complex I. Other models of complex III have been proposed, but they focus only on the mechanisms of ROS generation or quinol oxidation by complex III (Quinlan et al., 2011(37); Crofts et al., 2006(9)). Therefore, these models do not meet the criteria set by the inventors for the creation of the model of the present invention, and the criteria important for use in a global model of a more comprehensive model of mitochondrial metabolism for different applications such as neurodegenerative pathology, metabolic diseases, inflammatory diseases, or aging.

[0256] References 1. Bazil,JN,Beard,DA,and Vinnakota,KC(2016).Catalytic coupling of oxidative phosphorylation,atp demand,and reactive oxygen species generation.Biophysical journal, 110(4), 962-971. 2. Bazil,J.N.,Pannala,V.R.,Dash,R.K.,and Beard,D.A.(2014).Determining the origins of superoxide and hydrogen peroxide in the mammalian nadh:ubiquinone oxidoreductase.Free radical biology & medicine,77,121-129. 3. Beard,D.A.(2005).A biophysical model of the mitochondrial respiratory system and oxidative phosphorylation.PLoS computational biology,1(4),e36. 4. Berry,E.,Guergova-Kuras,M.,Huang,L.,and Crofts,A.(2000).Structure and function of cytochrome be complexes.Annual review of biochemistry,69,1005-1075. 5. Bleier,L.and Drose,S.(2013).Superoxide generation by complex iii:from mechanistic rationales to functional * This work is supported by European Union FEDER and INSPIRE,consequences.Biochimica etbiophysica acta,1827(1112),1320-1331. 6. Borek,A.,Sarewicz,M.,and Osyczka,A.( 2008).Movement of the ironsulfur head domain of cytochrome bc1 transiently opens the catalytic qo site for reaction with oxygen.Biochemistry,47(47),12365-12370. 7. Chen,H.,Detmer,S.A.,Ewald,A.J.,Griffin,E.E.,Fraser,S.E.,and Chan,D.C.(2003).Mitofusins mfn1 and mfn2 coordinately regulate mitochondrial fusion and are essential for embryonic development.The Journal of cell biology,160(2),189-200. 8. Chouchani,E.T.,Pell,V.R.,James,A.M.,Work,L.M.,Saeb-Parsy,K.,Frezza,C.,Krieg,T.,and Murphy,M.P.(2016).A unifying mechanism for mitochondrial superoxide production during ischemia-reperfusion injury.Cell Metabolism,23(2),254-263. 9. Crofts,A.R.,Lhee,S.,Crofts,S.B.,Cheng,J.,and Rose,S.(2006).Proton pumping in the bc1 complex:a new gating mechanism that prevents short circuits.Biochimica et biophysica acta,1757(8),1019-1034. 10. Deb,K.,Pratap,A.,Agarwal,S.,and Meyarivan,T.(2002).A fast and elitist multiobjective genetic algorithm:Nsga-ii.IEEE Transactions on Evolutionary Computation,6(2),182-197. 11. Drose,S.and Brandt,U.(2008).The mechanism of mitochondrial superoxide production by the cytochrome bc1 complex.The Journal of biological chemistry,283(31),21649-21654. 12. Esterhazy,D.,King,M.S.,Yakovlev,G.,and Hirst,J.(2008).Production of reactive oxygen species by complex i (nadh:ubiquinone oxidoreductase)from escherichia coli and comparison to the enzyme from mitochondria.Biochemistry,47(12),3964-3971. 13. Fato,R.,Bergamini,C.,Bortolus,M.,Maniero,A.L.,Leoni,S.,Ohnishi,T.,and Lenaz,G.(2009).Differential effects of mitochondrial complex i inhibitors on production of reactive oxygen species.Biochimica et biophysica acta,1787(5),384-392. 14. Fisher,N.,Bowman,M.K.,and Kramer,D.M.(2016).Electron Transfer Reactions at the Qo Site of the Cytochrome bc1 Complex:The Good,the Bad,and the Ugly,419- 434.Springer Netherlands,Dordrecht. 15. Genova,M.,Ventura,B.,Giuliano,G.,Bo vina,C.,Formiggini,G.,Parenti Castelli,G.,and Lenaz,G.(2001).The site of production of superoxide radical in mitochondrial complex i is not a bound ubisemiquinone but presumably iron-sulfur cluster n2.FEBS letters,505(3),364-368. 16. Grivennikova,V.G.and Vinogradov,A.D.(2006).Generation of superoxide by the mitochondrial complex i.Biochimica et Biophysica Acta (BBA)- Bioenergetics,1757(5),553 - 561.14th European Bioenergetics Conference. 17. Grivennikova,V.G.and Vinogradov,A.D.(2013).Partitioning of superoxide and hydrogen peroxide production by mitochondrial respiratory complex i.Biochimica et Biophysica Acta (BBA)- Bioenergetics,1827(3),446 - 454. 18. Grodzevich,O.and Romanko,O.(2006).Normalization and other topics in multi-objective optimization.In Fields-MITACS Industrial Problems Workshop. 19. Heiske,M.,Letellier,T.,and Klipp,E.(2017).Comprehensive mathematical model of oxidative phosphorylation valid for physiological and pathological conditions.The FEBS journal,284(17),2802-2828. 20. Heiske,M.,Nazaret,C.,and Mazat,J.P.(2014).Modeling the respiratory chain complexes with biothermokinetic equations - the case of complex i.Biochimica et Biophysica Acta (BBA)- Bioenergetics,1837(10),1707 - 1716. 21. Hinkle,P.,Butow,R.,Racker,E.,and Chance,B.(1967).Partial resolution of the enzymes catalyzing oxidative phosphorylation,xv.reverse electron transfer in the flavin-cytochrome beta region of the respiratory chain of beef heart submitochondrial particles.The Journal of biological chemistry,242(22),5169-5173. 22. Hunte,C.,Palsdottir,H.,and Trumpower,B.L.(2003).Protonmotive pathways and mechanisms in the cytochrome bc1 complex.FEBS letters,545(1),39-46. 23. Iwata,S.,Lee,J.,Okada,K.,Lee,J.,Iwata,M.,Rasmussen,B.,Link,T.,Ramaswamy,S.,and Jap,B.(1998).Complete structure of the 11-subunit bovine mitochondrial cytochrome bc1 complex.Science (New York,N.Y. ),281(5373),64-71. 24. Kim,M.,Stepanova,A.,Niatsetskaya,Z.,Sosunov,S.,Arndt,S.,Murphy,M.P.,Galkin,A.,and Ten,V.S.(2018).Attenuation of oxidative damage by targeting mitochondrial complex i in neonatal hypoxic-ischemic brain injury.Free Radical Biology and Medicine,124,517-524. 25. Ksenzenko,M.,Konstantinov,A.,Khomutov,G.,Tikhonov,A.,and Ruuge,E.(1983).Effect of electron transfer inhibitors on superoxide generation in the cytochrome bc1 site of the mitochondrial respiratory chain.FEBS letters,155(1),19-24. 26. Kussmaul,L.and Hirst,J.(2006).The mechanism of superoxide production by nadh:ubiquinone oxidoreductase (complex i)from bovine heart mitochondria.Proceedings of the National Academy of Sciences of the United States of America,103(20),7607-7612. 27. Lambert,A.J.and Brand,M.D.(2004).Superoxide production by nadh:ubiquinone oxidoreductase (complex i)depends on the ph gradient across the mitochondrial inner membrane.The Biochemical journal,382(Pt 2),511-517. 28. Maranzana,E.,Barbero,G.,Falasca,A.I.,Lenaz,G.,and Genova,M.L.(2013).Mitochondrial respiratory supercomplex association limits production of reactive oxygen species from complex i.Antioxidants & redox signaling,19(13),1469-1480. 29. Merabet,N.,Bordeneuve,J.,and Davezac,N.(2017).Modelling the redox imbalance in dominant optic atrophy:the case of respiratory complex i.IFAC,50,862-867. 30. Mitchell,P.(1961)。Coupling of phosphorylation to electron and hydrogen transfer by a chemi-osmotic type of mechanism.Nature,191,144-148. 31. Mitchell,P.(1966)。Chemiosmotic coupling in oxidative and photosynthetic phosphorylation.Biological Reviews,41(3),445-501. 32. Moser,C.,M.Keske,J.,Warncke,K.,Farid,R.,and Leslie Dutton,P.(1992).Nature of biological electron transfer.Nature,355,796-802. 33. Muller,F.,Crofts,A.R.,and Kramer,D. M.(2002).Multiple q-cycle bypass reactions at the qo site of the cytochrome bc1 complex.Biochemistry,41(25),7866-7874. 34. Muller,F.L.,Roberts,A.G.,Bowman,M.K.,and Kramer,D.M.(2003).Architecture of the qo site of the cytochrome bc1 complex probed by superoxide production.Biochemistry,42(21),6493-6499.Murphy,M.P.(2009).How mitochondria produce reactive oxygen species.The Biochemical journal,417(1),1-13. 35. Pell,V.R.,Spiroski,A.M.,Mulvey,J.,Burger,N.,Costa,A.S.,Logan,A.,Gruszczyk,A.V.,Rosa,T.,James,A.M.,Frezza,C.,Murphy,M.P.,and Krieg,T.(2018).Ischemic preconditioning protects against cardiac ischemia reperfusion injury without affecting succinate accumulation or oxidation.Journal of Molecular and Cellular Cardiology,123,88-91. 36. Pryde,K.R.and Hirst,J.(2011).Superoxide is produced by the reduced flavin in mitochondrial complex i:A single,unified mechanism that applies during both forward and reverse electron transfer.Journal of Biological Chemistry,286(20),18056-18065. 37. Quinlan,C.L.,Gerencser,A.A.,Treberg,J.R.,and Brand,M.D.(2011).The mechanism of superoxide production by the antimycin-inhibited mitochondrial q-cycle.The Journal of biological chemistry,286(36),31361-31372. 38. Robb,E.L.,Hall,A.R.,Prime,T.A.,Eaton,S.,Szibor,M.,Viscomi,C.,James,A.M.,and Murphy,M.P.(2018).Control of mitochondrial superoxide production by reverse electron transport at complex i.The Journal of biological chemistry,293(25),9869- 9879. 39. Rottenberg,H.,Covian,R.,and Trumpower,B.L.(2009).Membrane potential greatly enhances superoxide generation by the cytochrome bc1 complex reconstituted into phospholipid vesicles.The Journal of biological chemistry,284(29),19203-19210. 40. Roudenko,O.and Schoenauer,M.(2004).A steady performance stopping criterion for pareto-based evolutionary algorithms.In Proceedings of the 6th international multi-objective programming and goal programming conference. 41. Turrens,J.,Alexandre,A.,and Lehninger,A.(1985).Ubisemiquinone is the electron donor for superoxide formation by complex iii of heart mitochondria.Archives of biochemistry and biophysics,237(2),408-414P. 42. Vinogradov,A.and Grivennikova,V.(2005).Generation of superoxide-radical by the nadh:ubiquinone oxidoreductase of heart mitochondria.Biochemistry.Biokhimiia,70(2),120-127. 43. Wong,H.S.,Dighe,P.A.,Mezera,V.,Monternier,P.A.,and Brand,M.D.(2017).Production of superoxide and hydrogen peroxide from specific mitochondrial sites under different bioenergetic conditions.Journal of Biological Chemistry,292(41),16804-16809 44. Alavi, M.V., Fuhrmann, N., Nguyen, H.P., Yu-Wai-Man, P., Heiduschka, P., Chinnery, P.F., and Wissinger, B. (2009).Subtle neurological and metabolic abnormalities in an Opal mouse model of autosomal dominant optic atrophy.Experimental neurology 220,404-409.10.1016 / j.expneurol.2009.09.026. 45. Amati-Bonneau,P.,Milea,D.,Bonneau,D.,Chevrollier,A.,Ferre,M.,Guillet,V.,Gueguen,N.,Loiseau,D.,de Crescenzo,MA,Verny,C.,et al.(2009).OPA1- associated disorders: phenotypes and pathophysiology.The international journal of biochemistry & cell biology 41,1855-1865.10.1016 / j.biocel.2009.04.012. 46. ​​Amati-Bonneau,P.,Valentino,ML,Reynier,P.,Gallardo,ME,Bornstein,B.,Boissiere,A.,Campos,Y.,Rivera,H.,de la Aleja,JG,Carroccia,R.,et al.(2008).OPA1 mutations induce mitochondrial DNA instability and optic atrophy'plus' phenotypes.Brain:a journal of neurology 131,338-351. 47. Barboni, P., Valentino, M.L., La Morgia, C., Carbonelli, M., Savini, G., De Negri, A., Simonelli, F., Sadun, F., Caporali, L., Maresca, A., et al. (2013). Idebenone treatment in patients with OPA1-mutant dominant optic atrophy.Brain:a journal of neurology 136,e231.10.1093 / brain / aws280. 48. Bertholet, A.M., Delerue, T., Millet, A. M.,Moulis,MF,David,C.,Daloyau,M.,Arnaune-Pelloquin,L.,Davezac,N.,Mils,V.,Miquel,MC,etal.(2016).Mitochondrial fusion / fission dynamics in neurodegeneration and neuronal plasticity.Neurobiology of disease 90.3-19.10.1016 / j.nbd.2015.10.011. 49. Bertholet, AM, Millet, AM, Guillermin, O., Daloyau, M., Davezac, N., Miquel, MC, and Belenguer, P. (2013). OPA1 loss of function affects in vitro neuronal maturation. Brain: a journal of neurology 136,1518-1533.10.1093 / brain / awt060. 50. Brookes,P.S.,Yoon,Y.,Robotham,J.L.,Anders,M.W.,and Sheu,S.S.(2004).Calcium,ATP,and ROS:a mitochondrial love-hate triangle.American journal of physiology.Cell physiology 287,C817-833.10.1152 / ajpcell.00139.2004. 51. Chao de la Barca,J.M.,Prunier-Mirebeau,D.,Amati-Bonneau,P.,Ferre,M.,Sarzi,E.,Bris,C.,Leruez,S.,Chevrollier,A.,Desquiret-Dumas,V.,Gueguen,N.,etal.(2016).OPA1-related disorders:Diversity of clinical expression,modes of inheritance and pathophysiology.Neurobiology of disease 90,20-26.10.1016 / j.nbd.2015.08.015. 52. Chevrollier,A.,Guillet,V.,Loiseau,D.,Gueguen,N.,de Crescenzo,M.A.,Verny,C.,Ferre,M.,Dollfus,H.,Odent,S.,Milea,D.,et al.(2008).Hereditary optic neuropathies share a common mitochondrial coupling defect.Annals of neurology 63,794-798. 53. Cohn,A.C.,Toomes,C.,Potter,C.,Towns,K.V.,Hewitt,A.W.,Inglehearn,C.F.,Craig,J.E.,and Mackey,D.A.(2007).Autosomal dominant optic atrophy:penetrance and expressivity in patients with OPA1 mutations.American journal of ophthalmology 143,656-662. 54. Colombani,A.L.,Carneiro,L.,Benani,A.,Galinier,A.,Jaillard,T.,Duparc,T.,Offer,G.,Lorsignol,A.,Magnan,C.,Casteilla,L.,et al.(2009).Enhanced hypothalamic glucose sensing in obesity:alteration of redox signaling.Diabetes 58,2189-2197.10.2337 / db09-0110. 55. Coustham,C.,Merabet,N.,Bordeneuve-guibe,J.,and Davezac,N.(2021).Modeling of Complex I catalytic activity and ROS production:a multi-objective optimization for personalized medicine.GFB 21-24th September 2021. 56. Daloyau,M.,Millet,A.,Miquel,M.C.,Mils,V.,Wissinger,B.,Belenguer,P.,and Davezac,N.(2018).Brains from aged opa1+ / -(B6;C3-Opa1 329-355del)Mouse Strain Are in a Pro-Oxidative State.ROS 6,1-10. 57. Delettre,C.,Lenaers,G.,Griffoin,J.M.,Gigarel,N.,Lorenzo,C.,Belenguer,P.,Pelloquin,L.,Grosgeorge,J.,Turc-Carel,C.,Perret,E.,et al.(2000).Nuclear gene OPA1,encoding a mitochondrial dynamin-related protein,is mutated in dominant optic atrophy [In Process Citation],Nat Genet 26,207-210. 58. Galinier,A.,Carriere,A.,Fernandez,Y.,Carpene,C.,Andre,M.,Caspar-Bauguil,S.,Thouvenot,J.P.,Periquet,B.,Penicaud,L.,and Casteilla,L.(2006).Adipose tissue proadipogenic redox changes in obesity.The Journal of biological chemistry 281,12682-12687.10.1074 / jbc.M506949200. 59. Garcia,I.,Innis-Whitehouse,W.,Lopez,A.,Keniry,M.,and Gilkerson,R.(2018).Oxidative insults disrupt OPA1-mediated mitochondrial dynamics in cultured mammalian cells.Redox Rep 23,160-167.10.1080 / 13510002.2018.1492766. 60. Gardner,P.R.,Nguyen,D.D.,and White,C.W.(1994).Aconitase is a sensitive and critical target of oxygen poisoning in cultured mammalian cells and in rat lungs.Proceedings of the National Academy of Sciences of the United States of America 91,12248-12252. 61. Green,D.R.,Galluzzi,L.,and Kroemer,G.(2011).Mitochondria and the autophagy- inflammation-cell death axis in organismal aging.Science 333,1109-1112.10.1126 / science.1201940. 62. Griparic,L.,van der Wei,N.N.,Orozco,I.J.,Peters,P.J.,and van der Bliek,A.M.(2004).Loss of the intermembrane space protein Mgm1 / OPA1 induces swelling and localized constrictions along the lengths of mitochondria.The Journal of biological chemistry 279,18792-18798.10.1074 / jbc.M400920200. 63. Ishihara,N.,Fujita,Y.,Oka,T.,and Mihara,K.(2006).Regulation of mitochondria l morphology through proteolytic cleavage of OPA1.The EM BO journal 25,2966-2977.10.1038 / sj.emboj.7601184. 64. Kanazawa,T.,Zappaterra,M.D.,Hasegawa,A.,Wright,A.P.,Newman-Smith,E.D.,Buttle,K.F.,McDonald,K.,Mannella,C.A.,and van der Bliek,A.M.(2008).The C.elegans Opal homologue EAT-3 is essential for resistance to free radicals.PLoS genetics 4,e1000022. 65. Kelly,M.,Trudel,S.,Brouillard,F.,Bouillaud,F.,Colas,J.,Nguyen-Khoa,T.,Ollero,M.,Edelman,A.,and Fritsch,J.(2010).Cystic fibrosis transmembrane regulator inhibitors CFTR(inh)-172 and GlyH-101 target mitochondrial functions,independently of chloride channel inhibition.The Journal of pharmacology and experimental therapeutics 333,60-69。10.1124 / jpet.109.162032. 66. Kienhofer,J.,Haussler,D.J.,Ruckelshausen,F.,Muessig,E.,Weber,K.,Pimentel,D.,Ullrich,V.,Burkle,A.,and Bachschmid,M.M.(2009).Association of mitochondrial antioxidant enzymes with mitochondrial DNA as integral nucleoid constituents.FASEB journal:official publication of the Federation of American Societies for Experimental Biology 23,2034-2044.10.1096 / fj.08-113571. 67. Lenaers,G.,Hamel,C.,Delettre,C.,Amati-Bonneau,P.,Procaccio,V.,Bonneau,D.,Reynier,P.,and Milea,D.(2012).Dominant optic atrophy.Orphanet journal of rare diseases 7,46.10.1186 / 1750-1172-7-46. 68. Lopez-Armada,M.J.,Riveiro-Naveira,R.R.,Vaamonde-Garcia,C.,and Valcarcel- Ares,M.N.(2013).Mitochondrial dysfunction and the inflammatory response.Mitochondrion 13,106-118.10.1016 / j.mito.2013.01.003. 69. Ma,Q.(2013).Role of nrf2 in oxidative stress and toxicity.Annual review of pharmacology and toxicology 53,401-426.10.1146 / annurev-pharmtox-011112- 140320. 70. Mackey,D.A.,and Trounce,I.(2010).Genetics:Optic nerve genetics--more than meets the eye.Nature reviews.Neurology 6,357-358.10.1038 / nrneurol.2010.77. 71. Millet A.,M.N.,Bertholet A.,Daloyau M.,Reynier P.,G.A.,Devin A.,Wissinger B.,and Bordeneuve-guibe J.,B.P.,Davezac N.(2017).Imbalance of the REDOX state in dominant Optic Atrophy:the way of mathematical modeling.Archives of the International Society of Antioxidants in Nutrition and Health 5,21-24. 72. Millet,A.M.,Bertholet,A.M.,Daloyau,M.,Reynier,P.,Galinier,A.,Devin,A.,Wissinguer,B.,Belenguer,P.,and Davezac,N.(2016).Loss of functional OPA1 unbalances redox state:implications in dominant optic atrophy pathogenesis.Annals of clinical and translational neurology 3,408-421.10.1002 / acn3.305. 73. Olichon,A.,Emorine,L.J.,Descoins,E.,Pelloquin,L.,Brichese,L.,Gas,N.,Guillou,E.,Delettre,C.,Valette,A.,Hamel,C.P.,et The human dynamin-related protein OPA1 is anchored to the mitochondrial inner membrane facing the inter-membrane space.FEBS Letters 523,171-176. [ PubMed ] 74. Olichon, A., Guillou, E., Delettre, C., Landes, T., Arnaune-Pelloquin, L., Emorine, LJ, Mils, V., Daloyau, M., Hamel, C., Amati-Bonneau, P., et al minutes 1763,500-509. [ PMC free article ] [ PubMed ] 75. M. Satoh, T. Hamamoto, N. Seo, Y. Kagawa, and H. Endo OPA1 isoforms in mitochondria.Biochemical and Biophysical Research Communications 300,482-493. 76. Schriner , SE , Linford , NJ , Martin , GM , Treuting , P , Ogburn , CE , Emond , M , Coskun , PE , Ladiges , W , Wolf , N , Van Remmen , H , et al 308,1909–1911.10.1126 / science.1106653. 77. Shahrestani,P.,Leung,H.T.,Le,P.K.,Pak,W.L.,Tse,S.,Ocorr,K.,and Huang,T.(2009).Heterozygous mutation of Drosophila Opal causes the development of multiple organ abnormalities in an age-dependent and organ-specific manner.PloS one 4,e6867.10.1371 / journal.pone.0006867. 78. Spinazzi,M.,Cazzola,S.,Bortolozzi,M.,Baracca,A.,Loro,E.,Casarin,A.,Solaini, G.,Sgarbi,G.,Casalena,G.,Cenacchi,G.,et al.(2008).A novel deletion in the GTPase domain of OPA1 causes defects in mitochondrial morphology and distribution,but not in function.Human molecular genetics 17,3291-3302. 79. Tang,S.,Le,P.K.,Tse,S.,Wallace,D.C.,and Huang,T.(2009).Heterozygous mutation of Opal in Drosophila shortens lifespan mediated through increased reactive oxygen species production.PloS one 4,e4492. 80. Vincent,A.M.,McLean,L.L.,Backus,C.,and Feldman,E.L.(2005).Short-term hyperglycemia produces oxidative damage and apoptosis in neurons.FASEB journal:official publication of the Federation of American Societies for Experimental Biology 19,638-640.10.1096 / fj.04-2513fje. 81. Yarosh,W.,Monserrate,J.,Tong,J.J.,Tse,S.,Le,P.K.,Nguyen,K.,Brachmann,C.B.,Wallace,D.C.,and Huang,T.(2008).The molecular mechanisms of OPA1-mediated optic atrophy in Drosophila model and prospects for antioxidant treatment.PLoS genetics 4,e6. 82. Yu-Wai-Man,P.,Griffiths,P.G.,Gorman,G.S.,Lourenco,C.M.,Wright,A.F.,Auer- Grumbach,M.,Toscano,A.,Musumeci,O.,Valentino,M.L.,Caporali,L.,etal.(2010).Multi-system neurological disease is common in patients with OPA1 mutations.Brain:a journal of neurology 133,771-786.10.1093 / brain / awq007. 83. Yu-Wai-Man,P.,Trenell,M.I.,Hollingsworth,K.G.,Griffiths,P.G.,and Chinnery,P.F.(2011).OPA1 mutations impair mitochondrial function in both pure and complicated dominant optic atrophy.Brain a journal of neurology 134,e164.10.1093 / brain / awq288. 84. Zanna,C.,Ghelli,A.,Porcelli,A.M.,Karbowski,M.,Youle,R.J.,Schimpf,S.,Wissinger,B.,Pinti,M.,Cossarizza,A.,Vidoni,S.,et al.(2008).OPA1 mutations associated with dominant optic atrophy impair oxidative phosphorylation and mitochondrial fusion.Brain:a journal of neurology 131,352-367. 85. Zeviani,M.(2008).OPA1 mutations and mitochondrial DNA damage:keeping the magic circle in shape.Brain:a journal of neurology 131,314-317.10.1093 / brain / awm339. 86. Abramczyk,H.;Brozek-Pluska,B.;Kopec,M.;Surmacki,J.;Blaszczyk,M.;Radek,M.Redox Imbalance and Biochemical Changes in Cancer by Probing Redox-Sensitive Mitochondrial Cytochromes in Label-Free Visible Resonance Raman Imaging.Cancers 2021,13,960. 87. H.Abramczyk,B.Brozek-Pluska & M.Kopec Scientific reports 2022,08 February 2022 Double face of cytochrome c in cancers by Raman imaging Scientific Reports volume 12,Article number:2120 (2022). 88. V.Agier,P.Oliviero,J.Laine,C.L’Hermitte-Stead,S.Girard,S.Fillaut,et al.Defective mitochondrial fusion,altered respiratory function,and distorted cristae structure in skin fibroblasts with heterozygous OPA1 mutations Biochim Biophys Acta 2012 Vol.1822 Issue 10 Pages 1570-80 Accession Number:22800932 DOI:10.1016 / j.bbadis.2012.07.002 http: / / www.ncbi.nlm.nih.gov / pubmed / 22800932 89. Wu,A.Neilson,A.L.Swift,R.Moran,J.Tamagnine,D.Parslow,et al.Multiparameter metabolic analysis reveals a close link between attenuated mitochondrial bioenergetic function and enhanced glycolysis dependency in human tumor cells Am J Physiol Cell Physiol 2007 Vol.292 Issue 1 Pages C125-36 Accession Number:16971499 DOI:10.1152 / ajpcell.00247.2006 https: / / www.ncbi.nlm.nih.gov / pubmed / 16971499 90. Mitchell,P,The protonmotive Q cycle:a general formulation Febs Lett,1975,vol.59,no 2,p.137-139 DOI:10.1016 / 0014-5793(75)80359-0 https: / / doi.org / 10.1016 / 0014- 5793(75)80359-0Murphy,2009 91. Esterhazy,Daria and King,Martin S.and Yakovlev,Gregory and Hirst,Judy,Production of reactive oxygen species by complex I (NADH:ubiquinone oxidoreductase)from Escherichia coli and comparison to the enzyme from mitochondria.Biochemistry,2008,vol.47,no 12,p.3964-3971.DOI 10.1021 / bi702243b https: / / doi.org / 10.1021 / bi702243b.

Claims

1. A method for in vitro quantifying the occurrence rate of reactive oxygen species, i.e., ROS, in a biological sample, wherein the method is a) Seven components involved in the activity of mitochondrial respiratory chain complex I, i.e., CI, or mitochondrial respiratory chain complex III, i.e., CIII, or both mitochondrial respiratory chain CI and CIII, wherein the seven components are - The reduced form of nicotinamide adenine dinucleotide, i.e., NADH, - The oxidized form of nicotinamide adenine dinucleotide, i.e., NAD+, -Quinon, that is, Q, -Quinol, or QH ２ , - Molecular oxygen, i.e., O ２ , - The reduced form of cytochrome C, i.e., cytCred, and - Determine the amounts of the seven components, which are the oxidation forms of cytochrome C, i.e., cytCox. Each concentration value - [NADH], corresponding to the amount of NADH measured in the biological sample, - [NAD+], corresponding to the amount of NAD+ measured in the biological sample, - [Q], corresponding to the amount of quinone measured in the biological sample, - The amount of quinol measured in the biological sample corresponds to [QH ２ ], - Corresponding to the amount of molecular oxygen measured in the biological sample, [O ２ ], - Corresponding to the amount of the reduced form of cytochrome C measured in the biological sample, [CytC Ｒｅｄ ], - Corresponding to the amount of oxidized form of cytochrome C measured in the biological sample, [CytC ｏｘ ], and obtaining, b) The first ROS occurrence rate V of ROS in the sample １Ｒｏｓ This involves calculating, [Math 1] During the ceremony, [Math 2] During the ceremony, V ＋ =1727.2 mmol / min / mg K Ｍ，０ ＮＡＤＨ =10.6、 K １ =174.1、K ２ =681.2、 K Ｍ ＮＡＤ＋ =1028.6μM、 K Ｍ Ｑ =11.6μM、K ｉｓ Ｑ =719128.5μM、 K Ｍ ＱＨ２ =16.3μM、K ｉｓ ＱＨ２ =36.2μM、 K ｉ ＮＡＤ＋ =26.4、 K Ｏ２ = 4871.0, and α = 5, and to calculate this, c) The second Ros occurrence rate V of ROS in the sample. ２Ｒｏｓ This involves calculating, [Math 3] During the ceremony, [Math 4] During the ceremony, V2 ＋ = 3579.29 mmol / min / mg; K １ =23.05、K ２ =472.12、 K Ｍ，０ ＱＨ２０ =184.77μM、K Ｍ ＱＨ２ｉ =397.14、 K Ｍ Ｑｏ =43.08μM、K Ｍ Ｑｉ =225.21μM、 K Ｍ ｃｙｔＣｏｘ =8.11μM、K Ｍ ｃｙｔＣｒｅｄ =419.16μM、 K’ Ｏ２ =914.51、 α' = 22.02 and β = 173.54, to be calculated, d) VRos = V １Ｒｏｓ +V ２Ｒｏｓ A method comprising obtaining the aforementioned Ros occurrence rate.

2. The method described above is b) The first ROS occurrence rate V of ROS in the sample １Ｒｏｓ This involves calculating, [Math 5] During the ceremony, [Math 6] In the formula, V ＋ =2121.1 mmol / min / mg, K Ｍ，０ ＮＡＤＨ = 8.1 μM, K １ = 185.2, K ２ = 1021.2, K Ｍ ＮＡＤ＋ = 625.8 μM, K Ｍ Ｑ = 15.7 μM, K Ｍ ＱＨ２ = 26 μM, K ｉｓ Ｑ =1066907.0μM, K ｉｓ ＱＨ２ = 48.6 μM, K ｉｓ ＮＡＤＨ =165076.9μM, K ｉ ＮＡＤ＋ = 34.3, K Ｏ２ = 9551.4 et α = 3.3, to be calculated, c) The second ROS occurrence rate V of ROS in the sample. ２Ｒｏｓ This involves calculating, [Number 7] During the ceremony, [Number 8] During the ceremony, V2 ＋ =399.06mmol / minute / mg, K １ =19.96、K ２ =341.15、 K Ｍ，０ ＱＨ２０ =157.61μM、K Ｍ ＱＨ２ｉ =478.63、 K Ｍ Ｑｏ =50.49μM、K Ｍ Ｑｉ =280.26μM、 K Ｍ ｃｙｔＣｏｘ =10.98μM、K Ｍ ｃｙｔＣｒｅｄ =248.18μM、 K’ Ｏ２ =760.78、 α' = 38.66 and β = 212.03, to be calculated, d) VRos = V １Ｒｏｓ +V ２Ｒｏｓ The method according to claim 1, comprising obtaining the ROS occurrence rate such that

3. The method according to claim 1 or 2, wherein the activity of the CI is determined by the following formula. [Number 9]

4. The method according to claim 1 or 2, wherein the activity of CIII is determined by the following formula. [Number 10]

5. A computer program including instructions, wherein when the program is executed by a computer, the instructions cause the computer to execute steps b) to d) of the method according to any one of claims 1 to 4.

6. A method for determining the Ros detoxification enzyme activity in an individual sample in vitro, wherein the method is -By performing the method according to any one of claims 1 to 4, the Ros appearance rate in the biological sample is quantified and the calculated ratio is obtained, - The method involves comparing the calculated ratio with the reference Ros occurrence rate to obtain the ratio R between the Ros occurrence rate and the reference Ros occurrence rate, wherein the reference Ros occurrence rate is obtained from a reference sample, and the reference sample has the same properties as the sample. － ＊ If R is lower than 0.85, the sample contains Ros detoxification enzyme activity that is efficient for detoxifying the sample during oxidative stress. ＊ A method comprising, otherwise, concluding that the sample does not contain efficient Ros detoxification enzyme activity (for detoxifying the sample during oxidative stress).

7. ＊ If R is less than 0.8, the sample contains Ros detoxification enzyme activity that is efficient for detoxifying the sample during oxidative stress. ＊ Otherwise, the method according to claim 6, wherein the sample does not contain Ros detoxification enzyme activity that is efficient for detoxifying the sample during oxidative stress.

8. A method for in vitro determining a patient's response to a compound that is likely to reduce the amount of Ros in a biological sample, wherein the method is -By performing the method according to any one of claims 1 to 4, the Ros appearance rate in the biological sample is quantified before administering the compound to the patient, and an initial Ros rate is obtained. - By performing the method described in any one of claims 1 to 4, the patient After administering the compound, the rate of Ros appearance in the biological sample is quantified to obtain the final Ros rate. - Comparing the initial Ros rate with the final Ros rate, obtain the ratio R between the final Ros rate and the initial Ros rate. － ＊ If R is less than 0.85, the compound can reduce the amount of Ros in the sample. ＊ A method comprising: otherwise, concluding that the sample cannot reduce the amount of Ros in the sample.

9. ＊ If R is less than 0.8, the compound can reduce the amount of Ros in the sample. ＊ Otherwise, the sample cannot reduce the amount of Ros in the sample, according to claim 8.

10. A method for determining in vitro in a biological sample whether a compound is an antioxidant or a pro-oxidant compound, wherein the method is -By performing the method according to any one of claims 1 to 4, the Ros appearance rate in the biological sample is quantified and the calculated ratio is obtained, - The method involves comparing the calculated ratio with the reference Ros occurrence rate to obtain the ratio R between the Ros occurrence rate and the reference Ros occurrence rate, wherein the reference Ros occurrence rate is obtained from a reference sample, and the reference sample has the same properties as the sample. － ＊ If R is lower than 0.85, the compound is an antioxidant compound. ＊ If R is greater than 1.15, the compound is an oxidation-promoting compound. ＊ A method comprising concluding that, when R is between 0.85 and 1.15, the compound has neither antioxidant properties nor pro-oxidative properties.

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