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基于基因组尺度代谢模型揭示生物膜形成过程中的代谢变化。

Revealing the Metabolic Alterations during Biofilm Development of Based on Genome-Scale Metabolic Modeling.

作者信息

Altay Ozlem, Zhang Cheng, Turkez Hasan, Nielsen Jens, Uhlén Mathias, Mardinoglu Adil

机构信息

Science for Life Laboratory, KTH-Royal Institute of Technology, 171 65 Solna, Sweden.

Department of Clinical Microbiology, Sami Ulus Training and Research Hospital, University of Health Sciences, Ankara 06080, Turkey.

出版信息

Metabolites. 2021 Apr 5;11(4):221. doi: 10.3390/metabo11040221.

Abstract

is among the important pathogens isolated from cystic fibrosis (CF) patients. It has attracted considerable attention because of its capacity to evade host immune defenses during chronic infection. Advances in systems biology methodologies have led to the emergence of methods that integrate experimental transcriptomics data and genome-scale metabolic models (GEMs). Here, we integrated transcriptomics data of bacterial cells grown on exponential and biofilm conditions into a manually curated GEM of . We observed substantial differences in pathway response to different growth conditions and alternative pathway susceptibility to extracellular nutrient availability. For instance, we found that blockage of the reactions was vital through the lipid biosynthesis pathways in the exponential phase and the absence of microenvironmental lysine and tryptophan are essential for survival. During biofilm development, bacteria mostly had conserved lipid metabolism but altered pathway activities associated with several amino acids and pentose phosphate pathways. Furthermore, conversion of serine to pyruvate and 2,5-dioxopentanoate synthesis are also identified as potential targets for metabolic remodeling during biofilm development. Altogether, our integrative systems biology analysis revealed the interactions between the bacteria and its microenvironment and enabled the discovery of antimicrobial targets for biofilm-related diseases.

摘要

是从囊性纤维化(CF)患者中分离出的重要病原体之一。由于其在慢性感染期间逃避宿主免疫防御的能力,它引起了相当大的关注。系统生物学方法的进展导致了将实验转录组学数据与基因组规模代谢模型(GEMs)相结合的方法的出现。在这里,我们将在指数生长和生物膜条件下生长的细菌细胞的转录组学数据整合到一个人工策划的的GEM中。我们观察到不同生长条件下途径反应的显著差异以及替代途径对细胞外营养可用性的敏感性。例如,我们发现阻断指数生长期脂质生物合成途径中的反应至关重要,并且微环境中赖氨酸和色氨酸的缺乏对生存至关重要。在生物膜形成过程中,细菌的脂质代谢大多保守,但与几种氨基酸和磷酸戊糖途径相关的途径活性发生了改变。此外,丝氨酸向丙酮酸的转化和2,5-二氧代戊酸的合成也被确定为生物膜形成过程中代谢重塑的潜在靶点。总之,我们的综合系统生物学分析揭示了细菌与其微环境之间的相互作用,并能够发现与生物膜相关疾病的抗菌靶点。

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