ABI Development: A Novel Protein Fragment Assembler for Metagenomic Data Analysis

这个奖项授予J·克雷格·文特尔研究所(JCVI)，是为了开发分析元基因组序列数据的新方法。元基因组学是利用独立于培养的技术来研究微生物群落的基因组含量。这一模式彻底改变了微生物学领域，特别是考虑到我们无法培养出存在于许多环境中的大多数微生物。下一代测序技术通常用于从元基因组样本中产生大量的核苷酸序列读取数据。从这些数据中识别全长蛋白质序列可以全面和准确地分析组成微生物的代谢潜力。这通常是通过组装核苷酸序列读数，然后使用产生的一组重叠群作为底物进行蛋白质鉴定来实现的。然而，元基因组组装通常是非常零散的，产生较短的重叠群，也留下了很大一部分未组装的读物，从而限制了这种方法的实用性。该项目将开发一种序列组装框架，用于直接从核苷酸读数中识别的短肽片段重建全长蛋白质序列。这种方法的动机是两个观察结果？(A)原核生物基因组中观察到的高编码密度--这意味着大多数核苷酸读数将至少包含蛋白质的一部分；和(B)遗传密码中的冗余--这减轻了核苷酸水平多态的影响，这种多态极大地混淆了核苷酸组装，并允许即使在基本组成核苷酸序列不相同的情况下也能重建蛋白质序列。多肽组装器的输出将被用来开发一个框架，根据蛋白质和途径的丰度来分析和比较元基因组样本。该项目将创建用于汇编和分析的开放源码文件软件包，并提供给研究界使用。该项目将创建基础设施和工具，用于在元基因组信息学的广泛领域进行培训，使更广泛的生物科学研究以及数学和科学教育社区能够获得数据分析概念。此外，博士后研究人员和实习生将接受元基因组学和计算生物学方面的培训。还将创建一个教育单元，通过讲习班向高中教师介绍基因组学和元基因组学中的生物信息学方法。参加工作坊的教师随后将在自己的课堂上教授课程。这种方法将促进年轻科学家对发现和研究的兴奋。

This award to the J. Craig Venter Institute (JCVI) is to develop novel methods for analyzing metagenomic sequence data. Metagenomics pertains to the study of the genomic content of microbial communities using cultivation independent techniques. This paradigm has revolutionized the field of microbiology, especially given our inability to cultivate a majority of microbes that exist in many environments. Next-generation sequencing technologies are used routinely for generating large volumes of nucleotide sequence read data from metagenomic samples. The identification of full-length protein sequences from these data allows for a comprehensive and accurate analysis of the metabolic potential of the constituent microbes. This is often implemented by assembling the nucleotide sequence reads, and then using the set of generated contigs as substrate for protein identification. However, metagenomic assemblies are typically very fragmented, producing short contigs and also leaving a large fraction of reads unassembled, thereby limiting the utility of this approach. This project will develop a sequence assembly framework for reconstructing full-length protein sequences directly from short peptide fragments identified on nucleotide reads. This approach is motivated by two observations ? (a) the high coding density observed in prokaryotic genomes - which implies that most of the nucleotide reads will contain at least part of a protein; and (b) the redundancy in the genetic code - which alleviates the effect of nucleotide-level polymorphisms that greatly confound nucleotide assembly, and allows for the reconstruction of protein sequences even when the underlying constituent nucleotide sequences are not identical. The peptide assembler output will be used to develop a framework for analyzing and comparing metagenomic samples based on their protein and pathway abundances. Open-source documented software packages for assembly and analysis will be created by this project, and made available for use by the research community.This project will create infrastructure and tools for training in the broad area of metagenomic informatics to make data analysis concepts accessible to the wider community doing research in the biological sciences, and for mathematics and science education. Additionally, postdoctoral researchers and interns will be trained in metagenomics and computational biology. An educational module will also be created to introduce high school teachers, via workshops, to bioinformatic methods in genomics and metagenomics. The teachers participating in the workshops will subsequently teach the curriculum in their classrooms. This approach will promote the excitement of discovery and research in young scientists.