枯草芽孢杆菌菌素合成过程中差异表达蛋白的比较生物学网络分析。

IF 1.5 4区 生物学 Q4 CELL BIOLOGY Integrative Biology Pub Date : 2022-08-03 DOI:10.1093/intbio/zyac010
Meltem Kutnu, Elif Tekin İşlerel, Nurcan Tunçbağ, Gülay Özcengiz
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引用次数: 0

摘要

革兰氏阳性杆菌枯草芽孢杆菌产生多种具有不同结构和活性的次级代谢物。其中,杆菌素是由l -丙氨酸和l -抗cap蛋白组成的酶促合成的二肽。我们小组先前的研究表明,在其生产者枯草芽孢杆菌PY79中,杆菌素是一种多效性分子。然而,在没有菌素的情况下,蛋白质相互作用的性质尚未确定。在目前的工作中,我们基于最近从杆菌素沉默菌株OGU1中获得的比较蛋白质组学数据,使用组学整合器构建了蛋白质-蛋白质相互作用子网络。对所得到的网络的功能富集分析指出了某些假定的干扰途径,如柠檬酸循环、群体感应和次生代谢物生物合成。实验数据中没有的各种分子被包括在最终的网络中。我们相信本研究对进一步鉴定和确认枯草芽孢杆菌蛋白-蛋白相互作用具有指导意义。
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Comparative biological network analysis for differentially expressed proteins as a function of bacilysin biosynthesis in Bacillus subtilis.

The Gram-positive bacterium Bacillus subtilis produces a diverse range of secondary metabolites with different structures and activities. Among them, bacilysin is an enzymatically synthesized dipeptide that consists of L-alanine and L-anticapsin. Previous research by our group has suggested bacilysin's role as a pleiotropic molecule in its producer, B. subtilis PY79. However, the nature of protein interactions in the absence of bacilysin has not been defined. In the present work, we constructed a protein-protein interaction subnetwork by using Omics Integrator based on our recent comparative proteomics data obtained from a bacilysin-silenced strain, OGU1. Functional enrichment analyses on the resulting networks pointed to certain putatively perturbed pathways such as citrate cycle, quorum sensing and secondary metabolite biosynthesis. Various molecules, which were absent from the experimental data, were included in the final network. We believe that this study can guide further experiments in the identification and confirmation of protein-protein interactions in B. subtilis.

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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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