Big Data for a Small World: A Review on Databases and Resources for Studying Microbiomes

IF 1.8 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Journal of the Indian Institute of Science Pub Date : 2023-04-05 DOI:10.1007/s41745-023-00370-z
Pratyay Sengupta, Shobhan Karthick Muthamilselvi Sivabalan, Amrita Mahesh, Indumathi Palanikumar, Dinesh Kumar Kuppa Baskaran, Karthik Raman
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引用次数: 1

Abstract

Microorganisms are ubiquitous in nature and form complex community networks to survive in various environments. This community structure depends on numerous factors like nutrient availability, abiotic factors like temperature and pH as well as microbial composition. Categorising accessible biomes according to their habitats would help in understanding the complexity of the environment-specific communities. Owing to the recent improvements in sequencing facilities, researchers have started to explore diverse microbiomes rapidly and attempts have been made to study microbial crosstalk. However, different metagenomics sampling, preprocessing, and annotation methods make it difficult to compare multiple studies and hinder the recycling of data. Huge datasets originating from these experiments demand systematic computational methods to extract biological information beyond microbial compositions. Further exploration of microbial co-occurring patterns across the biomes could help us in designing cross-biome experiments. In this review, we catalogue databases with system-specific microbiomes, discussing publicly available common databases as well as specialised databases for a range of microbiomes. If the new datasets generated in the future could maintain at least biome-specific annotation, then researchers could use those contemporary tools for relevant and bias-free analysis of complex metagenomics data.

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小世界的大数据:微生物研究数据库和资源综述
微生物在自然界中无处不在,并形成复杂的群落网络,在各种环境中生存。这种群落结构取决于许多因素,如营养物质的可用性、温度和pH等非生物因素以及微生物组成。根据栖息地对可进入的生物群落进行分类将有助于了解特定环境群落的复杂性。由于测序设施的最近改进,研究人员已经开始快速探索不同的微生物组,并试图研究微生物串扰。然而,不同的宏基因组学采样、预处理和注释方法使多项研究难以进行比较,并阻碍了数据的回收。源自这些实验的庞大数据集需要系统的计算方法来提取微生物组成之外的生物信息。对生物群落中微生物共存模式的进一步探索可以帮助我们设计跨生物群落实验。在这篇综述中,我们对具有系统特定微生物组的数据库进行了编目,讨论了公开可用的常见数据库以及一系列微生物组的专业数据库。如果未来生成的新数据集能够至少保持生物群落特定的注释,那么研究人员可以使用这些当代工具对复杂的宏基因组学数据进行相关和无偏见的分析。
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来源期刊
Journal of the Indian Institute of Science
Journal of the Indian Institute of Science MULTIDISCIPLINARY SCIENCES-
CiteScore
4.30
自引率
0.00%
发文量
75
期刊介绍: Started in 1914 as the second scientific journal to be published from India, the Journal of the Indian Institute of Science became a multidisciplinary reviews journal covering all disciplines of science, engineering and technology in 2007. Since then each issue is devoted to a specific topic of contemporary research interest and guest-edited by eminent researchers. Authors selected by the Guest Editor(s) and/or the Editorial Board are invited to submit their review articles; each issue is expected to serve as a state-of-the-art review of a topic from multiple viewpoints.
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