EAGER: Tool development for proteomics and environmental metaproteomics

这个EAGER项目的布赖恩Palenik，加州大学圣地亚哥分校，是为工具开发，以确定以前未知的，推定的基因在宏基因组序列数据。宏基因组序列代表了群落中微生物基因组的完整组成，由于其复杂性而难以分析。即使是培养生物的基因组也很难注释，因为通常50%的基因组序列可能包含未知或新的基因。蛋白质组学使用质谱法来分析来自样品的蛋白质水解的肽。该分析允许确定原始样品中是否存在特定蛋白质。在某些形式中，蛋白质组学可以使用基因组数据库作为肽和蛋白质鉴定的起点。最近，正在测试一种形式的“反向蛋白质组学”，其中使用质谱数据通过证明初始基因组注释中未预测的蛋白质的存在来改进全基因组注释。这项技术现在开始在复杂环境样品的分析中显示出希望，例如元蛋白质组学样品。这种社区一级的分析不仅可以带来关于生物多样性的新信息，而且可以带来关于生态系统功能的新信息。然而，质谱和基因组和宏基因组数据的耦合来分析环境样品仍然需要工具开发。当宏基因组和元蛋白质组采样可以协调以优化和测试工具时，这种开发是最好的。该PI正在开发几种工具，用于使用从同一站点获得的宏基因组学数据分析元蛋白质组。这些工具包括发现新的开放阅读框架和基因的计算程序，在没有DNA测序的情况下识别哪些物种存在的方法，以及分析聚球藻宏基因组中翻译后修饰的方法。这方面的工作比其他目标的风险更高，但很重要，因为这将使他们能够评估宏基因组中哪些基因是活跃的。该项目代表了海洋微生物学家和质谱学家之间的一种新的跨学科合作，它是及时的，因为它利用了另一个NSF提案资助的正在进行的宏基因组测序。如果成功，这些工具将允许识别社区内的激活基因。此外，将在宏基因组中鉴定新的或新颖的基因，并且将鉴定这些新颖基因的产物。该研究团队将专注于海洋蓝藻群落作为测试宏基因组。PI已经对两种聚球藻（海洋蓝细菌）的基因组进行了测序，他将使用这些基因组作为宏基因组/元蛋白组分析的参考基因组。 海洋中的聚球藻组合不是很多样化，因此聚球藻宏基因组是这些测试的最佳宏基因组，因为这些群体可以从海水中富集以产生用于蛋白质组学分析的几乎纯的样品。由于这一奖项，PI正在监督两名博士后的培训。

This EAGER project to Brian Palenik, UC San Diego, is for tools development to identify previously unknown, putative genes in metagenomic sequence data. Metagenomic sequences represent the full complement of microbial genomes in a community and are difficult to analyse because of their complexity. Even the genomes of cultured organisms are difficult to annotate as typically 50% of the genome sequence can contain unknown or novel genes. Proteomics uses mass spectrometry to analyze peptides derived from the proteolysis of samples. This analysis allows for the determination of the presence or absence of specific proteins in the original sample. In some forms, proteomics can use genomic databases as a starting point for peptide and protein identification. More recently, a form of "reverse proteomics" is being tested where mass spectrometry data are used to improve whole genome annotation by demonstrating the presence of proteins not predicted in the initial genome annotation. This technology is now beginning to show promise in the analysis of complex environmental samples, such as metaproteomic samples. This type of community-level analysis can lead to new information about not only the biodiversity but the functioning of ecosystems. However, the coupling of mass spectrometry and genome and metagenome data to analyze environmental samples still requires tool development. This development is best done when the metagenome and metaproteome sampling can be coordinated to optimize and test the tools. This PI is developing several tools for analyzing metaproteomes using metagenomics data obtained from the same site. The tools include computational procedures to discover new open reading frames and genes, methods to identify which species are present without DNA sequencing and an approach for analysing post-translational modifications in Synechococcus metagenomes. This aspect of the work is higher risk than the other aims but is important because this will allow them to evaluate which genes in the metagenome are active. This project represents a novel interdisciplinary collaboration between a marine microbiologist and a mass spectroscopist, and it is timely as it takes advantage of ongoing metagenome sequencing funded by another NSF proposal. If successful, these tools will allow for the identification of activated genes within communities. Further, new or novel genes will be identified in the metagenomes and the products of these novel genes will be identified. This research team will focus on marine cyanobacterial communities as the test metagenome. The PI has already sequenced the genomes of two Synechococcus (marine cyanobacteria) and he will use these as reference genomes for the metagenomic/metaproteomic analyses. Synechococcus assemblages in the ocean are not very diverse, therefore Synechococcus metagenomes are some of the best metagenomes for these tests because these populations can be enriched from seawater to produce a nearly pure samples for proteomic analysis. The PI is overseeing training of two post-docs as a result of this award.