Department of Pathology and Immunology, Baylor College of Medicine, Houston, Texas, USA.
Texas Children's Microbiome Center, Department of Pathology, Texas Children's Hospital, Houston, Texas, USA.
J Clin Invest. 2024 Jan 16;134(2):e170859. doi: 10.1172/JCI170859.
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.
靶向宏基因组测序是一种新兴的策略，用于检测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，由于研究力度不足和测序偏差，这种方法经常产生不一致或相互矛盾的结果。我们引入了 Taxa4Meta，这是一个专门设计的生物信息学管道，用于补偿技术和人口统计学偏差。我们设计并验证了 Taxa4Meta，用于对从不同测序策略获得的 16S rRNA 扩增子数据进行准确的分类群分析。Taxa4Meta 具有很大的潜力，可以识别出能够可靠预测人类疾病的临床失调特征，通过对个体患者 16S 数据集的重新分析进行了全面验证。我们利用 Taxa4Meta 的泛微生物组分析功能，生成了基于 16S 的分类器，这些分类器在区分艰难梭菌感染、肠易激综合征或炎症性肠病（这些都是常见的误诊，对临床管理构成重大挑战）的腹泻患者方面表现出了优异的效用。我们相信，Taxa4Meta 代表了一种新的“最佳实践”方法，可以用于在人群水平上定义肠道菌群失调。
