Metaproteomic analysis of Chesapeake Bay microbial communities.

Jinjun Kan, Thomas E Hanson, Joy M Ginter, Kui Wang, Feng Chen
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引用次数: 108

Abstract

Background: Natural microbial communities are extremely complex and dynamic systems in terms of their population structure and functions. However, little is known about the in situ functions of the microbial communities.

Results: This study describes the application of proteomic approaches (metaproteomics) to observe expressed protein profiles of natural microbial communities (metaproteomes). The technique was validated using a constructed community and subsequently used to analyze Chesapeake Bay microbial community (0.2 to 3.0 microm) metaproteomes. Chesapeake Bay metaproteomes contained proteins from pI 4-8 with apparent molecular masses between 10-80 kDa. Replicated middle Bay metaproteomes shared approximately 92% of all detected spots, but only shared 30% and 70% of common protein spots with upper and lower Bay metaproteomes. MALDI-TOF analysis of highly expressed proteins produced no significant matches to known proteins. Three Chesapeake Bay proteins were tentatively identified by LC-MS/MS sequencing coupled with MS-BLAST searching. The proteins identified were of marine microbial origin and correlated with abundant Chesapeake Bay microbial lineages, Bacteroides and alpha-proteobacteria.

Conclusion: Our results represent the first metaproteomic study of aquatic microbial assemblages and demonstrate the potential of metaproteomic approaches to link metagenomic data, taxonomic diversity, functional diversity and biological processes in natural environments.

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切萨皮克湾微生物群落的元蛋白质组学分析。
背景:天然微生物群落在种群结构和功能方面是极其复杂和动态的系统。然而,人们对微生物群落的原位功能知之甚少。结果:本研究描述了应用蛋白质组学方法(元蛋白质组学)观察天然微生物群落(元蛋白质组学)表达的蛋白质谱。该技术通过构建的群落进行验证,随后用于分析切萨皮克湾微生物群落(0.2至3.0微米)的元蛋白质组。切萨皮克湾元蛋白质组包含pI 4-8蛋白,表观分子质量在10-80 kDa之间。复制的中湾元蛋白质组在所有检测到的斑点中共享约92%,但与上湾和下湾元蛋白质组只共享30%和70%的共同蛋白质斑点。高表达蛋白的MALDI-TOF分析与已知蛋白无显著匹配。通过LC-MS/MS测序结合MS- blast搜索,初步鉴定了3种切萨皮克湾蛋白。所鉴定的蛋白质来源于海洋微生物,与丰富的切萨皮克湾微生物谱系、拟杆菌和α -变形菌相关。结论:我们的研究结果首次代表了水生微生物组合的元蛋白质组学研究,并证明了元蛋白质组学方法在将元基因组数据、分类多样性、功能多样性和自然环境中的生物过程联系起来方面的潜力。
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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