Targeted metagenomic sequencing is an emerging strategy to survey disease-specific microbiome biomarkers for clinical diagnosis and prognosis. However, this approach often yields inconsistent or conflicting results owing to inadequate study power and sequencing bias. We introduce Taxa4Meta, a bioinformatics pipeline explicitly designed to compensate for technical and demographic bias. We designed and validated Taxa4Meta for accurate taxonomic profiling of 16S rRNA amplicon data acquired from different sequencing strategies. Taxa4Meta offers significant potential in identifying clinical dysbiotic features that can reliably predict human disease, validated comprehensively via reanalysis of individual patient 16S data sets. We leveraged the power of Taxa4Meta’s pan-microbiome profiling to generate 16S-based classifiers that exhibited excellent utility for stratification of diarrheal patients with Clostridioides difficile infection, irritable bowel syndrome, or inflammatory bowel diseases, which represent common misdiagnoses and pose significant challenges for clinical management. We believe that Taxa4Meta represents a new “best practices” approach to individual microbiome surveys that can be used to define gut dysbiosis at a population-scale level.

中文翻译：

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泛微生物组分析系统 Taxa4Meta 可识别临床生态失调特征并对腹泻病进行分类

靶向宏基因组测序是一种新兴策略，用于调查疾病特异性微生物组生物标志物以进行临床诊断和预后。然而，由于研究能力不足和测序偏差，这种方法常常会产生不一致或相互矛盾的结果。我们推出了 Taxa4Meta，这是一个专门为弥补技术和人口统计学偏差而设计的生物信息学管道。我们设计并验证了 Taxa4Meta，用于对从不同测序策略获取的 16S rRNA 扩增子数据进行准确的分类分析。Taxa4Meta 在识别临床失调特征方面具有巨大潜力，这些特征可以可靠地预测人类疾病，并通过对个体患者 16S 数据集的重新分析进行全面验证。我们利用 Taxa4Meta 的泛微生物组分析功能生成基于 16S 的分类器，该分类器在对患有艰难梭菌 感染、肠易激综合征或炎症性肠病的腹泻患者进行分层方面表现出出色的实用性，这些疾病是常见的误诊并对临床管理提出了重大挑战。我们相信，Taxa4Meta 代表了一种新的个体微生物组调查“最佳实践”方法，可用于定义人群规模水平的肠道菌群失调。