Systemic Regulation of Host Energy and Oogenesis by Microbiome-Derived Mitochondrial Coenzymes

Gnainsky, Yulia; Zfanya, Nofar; Elgart, Michael; Omri, Eman; Brandis, Alexander; Mehlman, Tevie; Itkin, Maxim; Malitsky, Sergey; Adamski, Jerzy; Soen, Yoav

doi:10.1016/j.celrep.2020.108583

Cited by 33 publications

(35 citation statements)

References 78 publications

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“…FAD participates in the execution of many functions. 15 FAD is the strongest free radical scavenger, and glutathione (GSH) constitutes the most important antioxidant barrier for cells. FAD can also convert homocysteine into S- adenosyl methionine (SAM), thereby avoiding the accumulation of homocysteine.…”

Section: Resultsmentioning

confidence: 99%

Application of Artificial Intelligence Modeling Technology Based on Multi-Omics in Noninvasive Diagnosis of Inflammatory Bowel Disease

Huang¹,

Zhang²,

Hu³

2021

JIR

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Purpose: Inflammatory bowel disease (IBD) is difficult to diagnose and classify. The purpose of this study is to establish an artificial intelligence model based on fecal multiomics data for multi-classification diagnosis of IBD and its subtypes. Materials and Methods: A total of 299 clinical cohort studies were included in this study, including 86 healthy people, 140 CD patients and 73 UC patients. Based on the idea of hierarchical modeling for different groups, we model the total population and the groups with self-evaluation of "very well" and "slightly below par", respectively. The original total features were fecal multi-omics data, including metagenomics, metatranscriptomics, proteomics, metabolomics, viromics, faecal calprotectin. The importance, collinearity and other feature engineering methods were used to evaluate the features. Finally, three individualized diagnosis models with less features and high accuracy were obtained. Results: First, we screened 111 features to form the optimal feature set for the total population and established a three-classification individual diagnosis model with AUC of 0.83, which can simultaneously diagnose health, CD and UC. Secondly, according to the hierarchical modeling of the total population, we established two models for population with different self-evaluation. For "very well" population, we screened 59 features and established a three-classification diagnostic model with AUC of 0.85. For the self-evaluation population with "slightly below par", we finally included 22 features and established a threeclassification diagnostic model with AUC of 0.84. Only metabolomics and metatranscriptomics features were included in the optimal feature sets. Conclusion:This study provides a valuable method for high accuracy, noninvasive diagnosis and subtype identification of IBD patients. Researchers can choose biomarkers in different models according to different self-evaluation of patients. Simple noninvasive fecal sampling can be used to detect metabolomics and metatranscriptomics data, thus replacing the tedious and painful clinical colonoscopy and biopsy procedures.

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Section: Resultsmentioning

confidence: 99%

Application of Artificial Intelligence Modeling Technology Based on Multi-Omics in Noninvasive Diagnosis of Inflammatory Bowel Disease

Huang¹,

Zhang²,

Hu³

2021

JIR

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“…Beta oxidation is prone to congestion because of competition between longer and shorter acyl-CoA molecules for the same dehydrogenase enzymes, also leading to moderate accumulation of acylcarnitines. Such congestion can result from increased supply of long-chain fatty acids to mitochondria, insufficient capacity of the TCA cycle, or deficiency of oxidized forms of the key electron carriers FAD and NAD + (van Eunen, et al 2016; Gnainsky, et al 2021). The latter may in turn result from a backlog of the reduced forms FADH 2 and NADH at the electron transport chain or from general deficiency of those cofactors.…”

Section: Discussionmentioning

confidence: 99%

Evolutionary adaptation to juvenile malnutrition impacts adult metabolism and impairs adult fitness inDrosophila

Erkoşar

Dupuis

Cavigliasso

et al. 2022

Preprint

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Juveniles are often first to suffer from nutrient shortage, and juvenile undernutrition is likely an important force of natural selection shaping animal physiology, with consequences potentially extending into adulthood. We combined RNAseq, targeted metabolomics and genomics to study the consequences of experimental evolution under juvenile undernutrition for metabolism of reproductively active adult females of Drosophila melanogaster. Compared to six Control populations maintained on standard diet, six Selected populations evolved for over 230 generations on a nutrient-poor larval diet showed major changes in adult gene expression and metabolite abundance. In particular, Selected flies were relatively deficient in essential amino acids and purine nucleotides, but showed overabundance of several non-essential amino-acids involved in purine synthesis and overexpression of multiple enzymes catalyzing this pathway. Selected flies also accumulated medium-chain acylcarnitines suggestive of congestion in beta-oxidation, possibly linked to deficiency of electron transporters. Some aspects of the metabolic profile of Selected flies resembled that of flies subject to starvation. Furthermore, differences between Selected and Control populations in adult gene expression were in general positively correlated with differences in larval expression, consistent with pleiotropy in gene regulation between the life stages. Finally, Selected flies were less fit in terms of fecundity than Controls even when both were raised under the conditions under which the Selected populations evolved. These results suggest that evolutionary adaptation to juvenile undernutrition has large pleiotropic consequences for adult metabolism, and that they are costly rather than adaptive for adult fitness.

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“…Aldh expression and the normal oogenesis phenotype could be restored by re-introduction of a specific Acetobacter gut bacterium to the flies. Gnainsky et al (2021) suggested that specific gut bacteria provision an essential B vitamin (riboflavin) and mitochondrial co-enzymes to the host to support oogenesis. While further research is needed to elucidate the involvement of these molecular pathways in microbiome-dependent egg production in D. suzukii , our study is the first to discover that the microbiome-dependent effects on egg production could have an effect on the foraging behavior of the host insects.…”

Section: Discussionmentioning

confidence: 99%

Sex-Dependent Effects of the Microbiome on Foraging and Locomotion in Drosophila suzukii

et al. 2021

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There is growing evidence that symbiotic microbes can influence multiple nutrition-related behaviors of their hosts, including locomotion, feeding, and foraging. However, how the microbiome affects nutrition-related behavior is largely unknown. Here, we demonstrate clear sexual dimorphism in how the microbiome affects foraging behavior of a frugivorous fruit fly, Drosophila suzukii. Female flies deprived of their microbiome (axenic) were consistently less active in foraging on fruits than their conventional counterparts, even though they were more susceptible to starvation and starvation-induced locomotion was notably more elevated in axenic than conventional females. Such behavioral change was not observed in male flies. The lag of axenic female flies but not male flies to forage on fruits is associated with lower oviposition by axenic flies, and mirrored by reduced food seeking observed in virgin females when compared to mated, gravid females. In contrast to foraging intensity being highly dependent on the microbiome, conventional and axenic flies of both sexes showed relatively consistent and similar fruit preferences in foraging and oviposition, with raspberries being preferred among the fruits tested. Collectively, this work highlights a clear sex-specific effect of the microbiome on foraging and locomotion behaviors in flies, an important first step toward identifying specific mechanisms that may drive the modulation of insect behavior by interactions between the host, the microbiome, and food.

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Systemic Regulation of Host Energy and Oogenesis by Microbiome-Derived Mitochondrial Coenzymes

Cited by 33 publications

References 78 publications

Application of Artificial Intelligence Modeling Technology Based on Multi-Omics in Noninvasive Diagnosis of Inflammatory Bowel Disease

Application of Artificial Intelligence Modeling Technology Based on Multi-Omics in Noninvasive Diagnosis of Inflammatory Bowel Disease

Evolutionary adaptation to juvenile malnutrition impacts adult metabolism and impairs adult fitness inDrosophila

Sex-Dependent Effects of the Microbiome on Foraging and Locomotion in Drosophila suzukii

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