Scripps Research, La Jolla, California 92037, United States.
University of Minnesota, Minneapolis, Minnesota 55455, United States.
J Proteome Res. 2021 Feb 5;20(2):1451-1454. doi: 10.1021/acs.jproteome.0c00822. Epub 2021 Jan 4.
In this Letter, we reanalyze published mass spectrometry data sets of clinical samples with a focus on determining the coinfection status of individuals infected with SARS-CoV-2 coronavirus. We demonstrate the use of ComPIL 2.0 software along with a metaproteomics workflow within the Galaxy platform to detect cohabitating potential pathogens in COVID-19 patients using mass spectrometry-based analysis. From a sample collected from gargling solutions, we detected (opportunistic and multidrug-resistant pathogen) and (a probiotic component) along with SARS-Cov-2. We could also detect . Bc-h from COVID-19 positive samples and and from COVID-19 negative samples collected from oro- and nasopharyngeal samples. We believe that the early detection and characterization of coinfections by using metaproteomics from COVID-19 patients will potentially impact the diagnosis and treatment of patients affected by SARS-CoV-2 infection.
在这封信件中，我们重新分析了已发表的临床样本质谱数据集，重点是确定感染 SARS-CoV-2 冠状病毒的个体的合并感染状态。我们展示了使用 ComPIL 2.0 软件以及 Galaxy 平台中的代谢组学工作流程，使用基于质谱的分析来检测 COVID-19 患者中同时存在的潜在病原体。从漱口液中采集的样本中，我们检测到 （机会性和多药耐药病原体）和 （益生菌成分）以及 SARS-Cov-2。我们还可以检测到来自 COVID-19 阳性样本的 ，以及来自口咽和鼻咽样本的 COVID-19 阴性样本中的 和 。我们相信，通过对 COVID-19 患者进行代谢组学分析，早期检测和鉴定合并感染，将有可能影响到受 SARS-CoV-2 感染影响的患者的诊断和治疗。
