美国纽约市立大学公共卫生学院Levi Waldron小组近日取得一项新成果。经过不懈努力，他们利用BugSigD揭示了各种宿主相关微生物特征的差异丰度模式。2023年9月11日出版的《自然-生物技术》发表了这项成果。

研究人员研发了BugSigDB，这是一个可编辑的数据库，其中包含已发表的微生物特征差异化丰度研究，并附有有关研究地理、健康结果、宿主体部位以及使用受控实验、流行病学和统计方法等信息。该数据库的初始版本包含了与三个宿主物种有关600多项已发表研究揭示的2500多个手工辅助特征，能够对特征相似性、分类单元富集、共生和共排除以及共有特征进行高通量分析。

这些数据可以评估实验条件、环境或身体部位内和之间的微生物组差异丰度。跨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，包括口腔微生物频繁渗入肠道。

据介绍，越来越多的研究倾向于人类和其他宿主相关微生物组领域，但对已发表的不同丰度的宿主相关微生物组特征结果进行系统比较仍具有挑战。

附：英文原文

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

Author: Geistlinger, Ludwig, Mirzayi, Chloe, Zohra, Fatima, Azhar, Rimsha, Elsafoury, Shaimaa, Grieve, Clare, Wokaty, Jennifer, Gamboa-Tuz, Samuel David, Sengupta, Pratyay, Hecht, Issac, Ravikrishnan, Aarthi, Gonalves, Rafael S., Franzosa, Eric, Raman, Karthik, Carey, Vincent, Dowd, Jennifer B., Jones, Heidi E., Davis, Sean, Segata, Nicola, Huttenhower, Curtis, Waldron, Levi

Issue&Volume: 2023-09-11

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.

DOI: 10.1038/s41587-023-01872-y

Source: https://www.nature.com/articles/s41587-023-01872-y