BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures

IF 33.1 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Ludwig Geistlinger, Chloe Mirzayi, Fatima Zohra, Rimsha Azhar, Shaimaa Elsafoury, Clare Grieve, Jennifer Wokaty, Samuel David Gamboa-Tuz, Pratyay Sengupta, Issac Hecht, Aarthi Ravikrishnan, Rafael S. Gonçalves, Eric Franzosa, Karthik Raman, Vincent Carey, Jennifer B. Dowd, Heidi E. Jones, Sean Davis, Nicola Segata, Curtis Huttenhower, Levi Waldron
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引用次数: 0

Abstract

The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated microbial signatures from published differential abundance studies accompanied by information on study geography, health outcomes, host body site and experimental, epidemiological and statistical methods using controlled vocabulary. The initial release of the database contains >2,500 manually curated signatures from >600 published studies on three host species, enabling high-throughput analysis of signature similarity, taxon enrichment, co-occurrence and coexclusion and consensus signatures. These data allow assessment of microbiome differential abundance within and across experimental conditions, environments or body sites. Database-wide analysis reveals experimental conditions with the highest level of consistency in signatures reported by independent studies and identifies commonalities among disease-associated signatures, including frequent introgression of oral pathobionts into the gut. A database of microbial signatures is used for systematic comparison of differential abundance patterns.

Abstract Image

BugSigDB 能够捕捉与宿主相关的各种微生物特征的丰度差异模式。
有关人类和其他宿主相关微生物组研究的文献正在迅速增加,但系统地比较已发表的宿主相关微生物组丰度差异特征的结果仍然很困难。我们介绍的 BugSigDB 是一个社区可编辑的数据库,其中包含从已发表的丰度差异研究中人工编辑的微生物特征,并附有研究地理、健康结果、宿主身体部位以及使用受控词汇的实验、流行病学和统计方法等信息。该数据库的初始版本包含来自已发表的关于三种宿主物种的 600 多项研究的 2500 个人工特征,可对特征相似性、分类群富集、共现、共排和共识特征进行高通量分析。通过这些数据,可以评估实验条件、环境或身体部位内部和之间的微生物组丰度差异。全数据库分析揭示了独立研究报告中特征一致性最高的实验条件,并确定了疾病相关特征之间的共性,包括口腔致病菌频繁引入肠道。
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
Nature biotechnology
Nature biotechnology 工程技术-生物工程与应用微生物
CiteScore
63.00
自引率
1.70%
发文量
382
审稿时长
3 months
期刊介绍: Nature Biotechnology is a monthly journal that focuses on the science and business of biotechnology. It covers a wide range of topics including technology/methodology advancements in the biological, biomedical, agricultural, and environmental sciences. The journal also explores the commercial, political, ethical, legal, and societal aspects of this research. The journal serves researchers by providing peer-reviewed research papers in the field of biotechnology. It also serves the business community by delivering news about research developments. This approach ensures that both the scientific and business communities are well-informed and able to stay up-to-date on the latest advancements and opportunities in the field. Some key areas of interest in which the journal actively seeks research papers include molecular engineering of nucleic acids and proteins, molecular therapy, large-scale biology, computational biology, regenerative medicine, imaging technology, analytical biotechnology, applied immunology, food and agricultural biotechnology, and environmental biotechnology. In summary, Nature Biotechnology is a comprehensive journal that covers both the scientific and business aspects of biotechnology. It strives to provide researchers with valuable research papers and news while also delivering important scientific advancements to the business community.
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