203 research outputs found

    Using exomarkers to assess mitochondrial reactive species in vivo

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    Background: The ability to measure the concentrations of small damaging and signalling molecules such as reactive oxygen species (ROS) in vivo is essential to understanding their biological roles. While a range of methods can be applied to in vitro systems, measuring the levels and relative changes in reactive species in vivo is challenging. Scope of review: One approach towards achieving this goal is the use of exomarkers. In this, exogenous probe compounds are administered to the intact organism and are then transformed by the reactive molecules in vivo to produce a diagnostic exomarker. The exomarker and the precursor probe can be analysed ex vivo to infer the identity and amounts of the reactive species present in vivo. This is akin to the measurement of biomarkers produced by the interaction of reactive species with endogenous biomolecules. Major conclusions and general significance: Our laboratories have developed mitochondria-targeted probes that generate exomarkers that can be analysed ex vivo by mass spectrometry to assess levels of reactive species within mitochondria in vivo. We have used one of these compounds, MitoB, to infer the levels of mitochondrial hydrogen peroxide within flies and mice. Here we describe the development of MitoB and expand on this example to discuss how better probes and exomarkers can be developed. This article is part of a Special Issue entitled Current methods to study reactive oxygen species - pros and cons and biophysics of membrane proteins. Guest Editor: Christine Winterbourn. Abbreviations: EPR, electron paramagnetic resonance; GFP, green fluorescent protein; 4-HNE, 4-hydroxynonenal; MitoB, 3-(dihydroxyboronyl)benzyltriphenylphosphonium bromide; MitoP, (3-hydroxybenzyl)triphenylphosphonium bromide; ROS, reactive oxygen species; SOD, superoxide dismutase; TPMP, methyltriphenylphosphonium; TPP, triphenylphosphonium catio

    A mitochondria-targeted mass spectrometry probe to detect glyoxals: implications for diabetes

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    The glycation of protein and nucleic acids that occurs as a consequence of hyperglycaemia disrupts cell function and contributes to many pathologies, including those associated with diabetes and aging. Intracellular glycation occurs following the generation of the reactive 1,2-dicarbonyls methylglyoxal and glyoxal and disruption to mitochondrial function is associated with hyperglycemia. However, the contribution of these reactive dicarbonyls to mitochondrial damage in pathology is unclear due to uncertainties about their levels within mitochondria in cells and in vivo. To address this we have developed a mitochondria-targeted reagent (MitoG) designed to assess the levels of mitochondrial dicarbonyls within cells. MitoG comprises a lipophilic triphenylphosphonium cationic function, which directs the molecules to mitochondria within cells and an o-phenylenediamine moiety that reacts with dicarbonyls to give distinctive and stable products. The extent of accumulation of these diagnostic heterocyclic products can be readily and sensitively quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS), enabling changes to be determined. Using the MitoG-based analysis we assessed the formation of methylglyoxal and glyoxal in response to hyperglycaemia in cells in culture and in the Akita mouse model of diabetes in vivo. These findings indicated that the levels of methylglyoxal and glyoxal within mitochondria increase during hyperglycaemia in both cells and in vivo, suggesting that they can contribute to the pathological mitochondrial dysfunction that occurs in diabetes and aging

    Itaconate is an anti-inflammatory metabolite that activates Nrf2 via alkylation of KEAP1.

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    The endogenous metabolite itaconate has recently emerged as a regulator of macrophage function, but its precise mechanism of action remains poorly understood. Here we show that itaconate is required for the activation of the anti-inflammatory transcription factor Nrf2 (also known as NFE2L2) by lipopolysaccharide in mouse and human macrophages. We find that itaconate directly modifies proteins via alkylation of cysteine residues. Itaconate alkylates cysteine residues 151, 257, 288, 273 and 297 on the protein KEAP1, enabling Nrf2 to increase the expression of downstream genes with anti-oxidant and anti-inflammatory capacities. The activation of Nrf2 is required for the anti-inflammatory action of itaconate. We describe the use of a new cell-permeable itaconate derivative, 4-octyl itaconate, which is protective against lipopolysaccharide-induced lethality in vivo and decreases cytokine production. We show that type I interferons boost the expression of Irg1 (also known as Acod1) and itaconate production. Furthermore, we find that itaconate production limits the type I interferon response, indicating a negative feedback loop that involves interferons and itaconate. Our findings demonstrate that itaconate is a crucial anti-inflammatory metabolite that acts via Nrf2 to limit inflammation and modulate type I interferons

    Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS.

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    Ischaemia-reperfusion injury occurs when the blood supply to an organ is disrupted and then restored, and underlies many disorders, notably heart attack and stroke. While reperfusion of ischaemic tissue is essential for survival, it also initiates oxidative damage, cell death and aberrant immune responses through the generation of mitochondrial reactive oxygen species (ROS). Although mitochondrial ROS production in ischaemia reperfusion is established, it has generally been considered a nonspecific response to reperfusion. Here we develop a comparative in vivo metabolomic analysis, and unexpectedly identify widely conserved metabolic pathways responsible for mitochondrial ROS production during ischaemia reperfusion. We show that selective accumulation of the citric acid cycle intermediate succinate is a universal metabolic signature of ischaemia in a range of tissues and is responsible for mitochondrial ROS production during reperfusion. Ischaemic succinate accumulation arises from reversal of succinate dehydrogenase, which in turn is driven by fumarate overflow from purine nucleotide breakdown and partial reversal of the malate/aspartate shuttle. After reperfusion, the accumulated succinate is rapidly re-oxidized by succinate dehydrogenase, driving extensive ROS generation by reverse electron transport at mitochondrial complex I. Decreasing ischaemic succinate accumulation by pharmacological inhibition is sufficient to ameliorate in vivo ischaemia-reperfusion injury in murine models of heart attack and stroke. Thus, we have identified a conserved metabolic response of tissues to ischaemia and reperfusion that unifies many hitherto unconnected aspects of ischaemia-reperfusion injury. Furthermore, these findings reveal a new pathway for metabolic control of ROS production in vivo, while demonstrating that inhibition of ischaemic succinate accumulation and its oxidation after subsequent reperfusion is a potential therapeutic target to decrease ischaemia-reperfusion injury in a range of pathologies

    Why Does Exercise “Triggerâ€? Adaptive Protective Responses in the Heart?

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    Numerous epidemiological studies suggest that individuals who exercise have decreased cardiac morbidity and mortality. Pre-clinical studies in animal models also find clear cardioprotective phenotypes in animals that exercise, specifically characterized by lower myocardial infarction and arrhythmia. Despite the clear benefits, the underlying cellular and molecular mechanisms that are responsible for exercise preconditioning are not fully understood. In particular, the adaptive signaling events that occur during exercise to “trigger� cardioprotection represent emerging paradigms. In this review, we discuss recent studies that have identified several different factors that appear to initiate exercise preconditioning. We summarize the evidence for and against specific cellular factors in triggering exercise adaptations and identify areas for future study

    Network Models of TEM β-Lactamase Mutations Coevolving under Antibiotic Selection Show Modular Structure and Anticipate Evolutionary Trajectories

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    Understanding how novel functions evolve (genetic adaptation) is a critical goal of evolutionary biology. Among asexual organisms, genetic adaptation involves multiple mutations that frequently interact in a non-linear fashion (epistasis). Non-linear interactions pose a formidable challenge for the computational prediction of mutation effects. Here we use the recent evolution of β-lactamase under antibiotic selection as a model for genetic adaptation. We build a network of coevolving residues (possible functional interactions), in which nodes are mutant residue positions and links represent two positions found mutated together in the same sequence. Most often these pairs occur in the setting of more complex mutants. Focusing on extended-spectrum resistant sequences, we use network-theoretical tools to identify triple mutant trajectories of likely special significance for adaptation. We extrapolate evolutionary paths (n = 3) that increase resistance and that are longer than the units used to build the network (n = 2). These paths consist of a limited number of residue positions and are enriched for known triple mutant combinations that increase cefotaxime resistance. We find that the pairs of residues used to build the network frequently decrease resistance compared to their corresponding singlets. This is a surprising result, given that their coevolution suggests a selective advantage. Thus, β-lactamase adaptation is highly epistatic. Our method can identify triplets that increase resistance despite the underlying rugged fitness landscape and has the unique ability to make predictions by placing each mutant residue position in its functional context. Our approach requires only sequence information, sufficient genetic diversity, and discrete selective pressures. Thus, it can be used to analyze recent evolutionary events, where coevolution analysis methods that use phylogeny or statistical coupling are not possible. Improving our ability to assess evolutionary trajectories will help predict the evolution of clinically relevant genes and aid in protein design
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