Exploring microbial functional biodiversity at the protein family level-From metagenomic sequence reads to annotated protein clusters.

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Frontiers in bioinformatics Pub Date : 2023-03-03 eCollection Date: 2023-01-01 DOI:10.3389/fbinf.2023.1157956

Fotis A Baltoumas, Evangelos Karatzas, David Paez-Espino, Nefeli K Venetsianou, Eleni Aplakidou, Anastasis Oulas, Robert D Finn, Sergey Ovchinnikov, Evangelos Pafilis, Nikos C Kyrpides, Georgios A Pavlopoulos

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Abstract

Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.

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从蛋白质家族水平探索微生物功能生物多样性--从元基因组序列读数到注释蛋白质群。

元基因组学使人们能够获得自然微生物群落的基因库。元基因组枪式测序已成为研究和分类各种环境中微生物的首选方法。为此，人们开发了多种方法来处理和分析从原始读数到最终产品（如预测的蛋白质序列或家族）的序列数据。在本文中，我们将对这些方法进行全面回顾，以简化处理过程，并讨论可供选择的方法，以便在蛋白质家族水平上探索生物多样性。我们提供了分析工具的详细信息，并对其可扩展性及其优缺点进行了评论。最后，我们报告了可用的数据存储库，并推荐了与系统发育分布、结构预测和元数据富集有关的蛋白质家族注释的各种方法。

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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来源期刊

Frontiers in bioinformatics

CiteScore

2.60

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0.00%

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