Niche-specific metabolic phenotypes can be used to identify antimicrobial targets in pathogens.

IF 9.8 1区 生物学 Q1 Agricultural and Biological Sciences PLoS Biology Pub Date : 2024-11-18 DOI:10.1371/journal.pbio.3002907
Emma M Glass, Lillian R Dillard, Glynis L Kolling, Andrew S Warren, Jason A Papin
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Abstract

Bacterial pathogens pose a major risk to human health, leading to tens of millions of deaths annually and significant global economic losses. While bacterial infections are typically treated with antibiotic regimens, there has been a rapid emergence of antimicrobial resistant (AMR) bacterial strains due to antibiotic overuse. Because of this, treatment of infections with traditional antimicrobials has become increasingly difficult, necessitating the development of innovative approaches for deeply understanding pathogen function. To combat issues presented by broad- spectrum antibiotics, the idea of narrow-spectrum antibiotics has been previously proposed and explored. Rather than interrupting universal bacterial cellular processes, narrow-spectrum antibiotics work by targeting specific functions or essential genes in certain species or subgroups of bacteria. Here, we generate a collection of genome-scale metabolic network reconstructions (GENREs) of pathogens through an automated computational pipeline. We used these GENREs to identify subgroups of pathogens that share unique metabolic phenotypes and determined that pathogen physiological niche plays a role in the development of unique metabolic function. For example, we identified several unique metabolic phenotypes specific to stomach pathogens. We identified essential genes unique to stomach pathogens in silico and a corresponding inhibitory compound for a uniquely essential gene. We then validated our in silico predictions with an in vitro microbial growth assay. We demonstrated that the inhibition of a uniquely essential gene, thyX, inhibited growth of stomach-specific pathogens exclusively, indicating possible physiological location-specific targeting. This pioneering computational approach could lead to the identification of unique metabolic signatures to inform future targeted, physiological location-specific, antimicrobial therapies, reducing the need for broad-spectrum antibiotics.

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利基特异性代谢表型可用于确定病原体的抗菌靶标。
细菌病原体对人类健康构成重大威胁,每年导致数千万人死亡,给全球造成重大经济损失。虽然细菌感染通常采用抗生素治疗方案,但由于抗生素的过度使用,耐抗生素(AMR)细菌菌株迅速出现。因此,使用传统抗菌药治疗感染变得越来越困难,这就需要开发创新方法来深入了解病原体的功能。为了解决广谱抗生素带来的问题,以前曾提出并探索过窄谱抗生素的概念。窄谱抗生素不是干扰细菌的普遍细胞过程,而是针对某些物种或亚群细菌的特定功能或重要基因起作用。在这里,我们通过自动计算管道生成了一组病原体基因组规模的代谢网络重建(GENRE)。我们利用这些 GENREs 确定了具有独特代谢表型的病原体亚群,并确定病原体的生理生态位在独特代谢功能的形成过程中发挥了作用。例如,我们发现了几种胃部病原体特有的代谢表型。我们在硅学中确定了胃部病原体特有的重要基因,并为一种独特的重要基因确定了相应的抑制化合物。然后,我们用体外微生物生长试验验证了我们的硅学预测。我们证明,抑制独特的必需基因 thyX 可以完全抑制胃特异性病原体的生长,这表明可能存在生理位置特异性靶向作用。这种开创性的计算方法可以鉴定出独特的代谢特征,为未来有针对性的、生理位置特异性的抗菌疗法提供依据,从而减少对广谱抗生素的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Biology
PLoS Biology BIOCHEMISTRY & MOLECULAR BIOLOGY-BIOLOGY
CiteScore
15.40
自引率
2.00%
发文量
359
审稿时长
3-8 weeks
期刊介绍: PLOS Biology is the flagship journal of the Public Library of Science (PLOS) and focuses on publishing groundbreaking and relevant research in all areas of biological science. The journal features works at various scales, ranging from molecules to ecosystems, and also encourages interdisciplinary studies. PLOS Biology publishes articles that demonstrate exceptional significance, originality, and relevance, with a high standard of scientific rigor in methodology, reporting, and conclusions. The journal aims to advance science and serve the research community by transforming research communication to align with the research process. It offers evolving article types and policies that empower authors to share the complete story behind their scientific findings with a diverse global audience of researchers, educators, policymakers, patient advocacy groups, and the general public. PLOS Biology, along with other PLOS journals, is widely indexed by major services such as Crossref, Dimensions, DOAJ, Google Scholar, PubMed, PubMed Central, Scopus, and Web of Science. Additionally, PLOS Biology is indexed by various other services including AGRICOLA, Biological Abstracts, BIOSYS Previews, CABI CAB Abstracts, CABI Global Health, CAPES, CAS, CNKI, Embase, Journal Guide, MEDLINE, and Zoological Record, ensuring that the research content is easily accessible and discoverable by a wide range of audiences.
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