Metabolic modeling of sex-specific liver tissue suggests mechanism of differences in toxicological responses.

IF 4.3 2区 生物学
PLoS Computational Biology Pub Date : 2023-08-21 eCollection Date: 2023-08-01 DOI:10.1371/journal.pcbi.1010927
Connor J Moore, Christopher P Holstege, Jason A Papin
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引用次数: 0

Abstract

Male subjects in animal and human studies are disproportionately used for toxicological testing. This discrepancy is evidenced in clinical medicine where females are more likely than males to experience liver-related adverse events in response to xenobiotics. While previous work has shown gene expression differences between the sexes, there is a lack of systems-level approaches to understand the direct clinical impact of these differences. Here, we integrate gene expression data with metabolic network models to characterize the impact of transcriptional changes of metabolic genes in the context of sex differences and drug treatment. We used Tasks Inferred from Differential Expression (TIDEs), a reaction-centric approach to analyzing differences in gene expression, to discover that several metabolic pathways exhibit sex differences including glycolysis, fatty acid metabolism, nucleotide metabolism, and xenobiotics metabolism. When TIDEs is used to compare expression differences in treated and untreated hepatocytes, we find several subsystems with differential expression overlap with the sex-altered pathways such as fatty acid metabolism, purine and pyrimidine metabolism, and xenobiotics metabolism. Finally, using sex-specific transcriptomic data, we create individual and averaged male and female liver models and find differences in the pentose phosphate pathway and other metabolic pathways. These results suggest potential sex differences in the contribution of the pentose phosphate pathway to oxidative stress, and we recommend further research into how these reactions respond to hepatotoxic pharmaceuticals.

性别特异性肝组织的代谢模型提示了毒理学反应差异的机制。
动物和人类研究中的男性受试者被不成比例地用于毒理学测试。这种差异在临床医学中得到了证明,女性比男性更有可能在对外源性药物的反应中出现与肝脏相关的不良事件。虽然先前的研究表明性别之间的基因表达存在差异,但缺乏系统层面的方法来理解这些差异的直接临床影响。在这里,我们将基因表达数据与代谢网络模型相结合,以表征性别差异和药物治疗背景下代谢基因转录变化的影响。我们使用从差异表达推断的任务(TIDE),这是一种以反应为中心的分析基因表达差异的方法,发现几种代谢途径表现出性别差异,包括糖酵解、脂肪酸代谢、核苷酸代谢和外源性代谢。当使用TIDE来比较处理和未处理肝细胞的表达差异时,我们发现几个具有差异表达的子系统与性别改变的途径重叠,如脂肪酸代谢、嘌呤和嘧啶代谢以及外源性代谢。最后,使用性别特异性转录组数据,我们创建了个体和平均的男性和女性肝脏模型,并发现了磷酸戊糖途径和其他代谢途径的差异。这些结果表明,磷酸戊糖途径对氧化应激的贡献存在潜在的性别差异,我们建议进一步研究这些反应对肝毒性药物的反应。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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