通过对1000个人类腹泻样本进行宏基因组和宏转录组测序,加强传染性肠道疾病的诊断。

IF 10.4 1区 生物学 Q1 GENETICS & HEREDITY
Edward Cunningham-Oakes, Blanca M Perez-Sepulveda, Yan Li, Jay C D Hinton, Charlotte A Nelson, K Marie McIntyre, Maya Wardeh, Sam Haldenby, Richard Gregory, Miren Iturriza-Gómara, Christiane Hertz-Fowler, Sarah J O'Brien, Nigel A Cunliffe, Alistair C Darby
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引用次数: 0

摘要

背景:目前对腹泻病的监测受到传统诊断方法局限性的阻碍,传统诊断方法往往无法确定致病生物体,特别是对于新的或难以培养的细菌病原体。直接从粪便中测序核酸可以克服这些限制,但这种方法需要可靠地检测出传统方法可识别的病原体。方法:作为INTEGRATE研究的一部分,我们使用直接测序分析了1067例胃肠炎症状患者的粪便微生物组,并将结果与英国用于检测细菌和病毒病原体的标准诊断技术(培养、免疫测定、显微镜和单目标PCR)和分子分析(Luminex xTAG GPP)进行了比较。结果:我们发现15种病原体中有6种的超转录组读数与传统诊断之间存在很强的正相关。在14种病原体中,有8种的亚转录组学数据与Luminex检测高度相关。相比之下,宏基因组测序仅在15种病原体中的3种与传统诊断呈正相关,在14种病原体中的4种与Luminex呈正相关。与宏基因组学相比,超转录组学对4种病原体的检测灵敏度更高,而宏基因组学对5种病原体的检测更有效。超转录组学对人乳腺病毒F进行了近乎完整的转录组覆盖,并通过鉴定小隐孢子虫病毒(CSpV1)检测到隐孢子虫。从一名经实验室确认的沙门氏菌感染患者的粪便中提取了肠道沙门氏菌血清型肠炎的综合转录组谱。此外,比较病原体阳性和病原体阴性样本之间的RNA/DNA比率表明,亚转录组学可以区分病原体阳性/阴性样本,并为病原体生物学提供见解。在通过金标准诊断检测呈阳性的样本中观察到更高的RNA/DNA比率。结论:本研究强调了人类样本核酸直接测序增强胃肠道病原体监测和临床诊断的能力。超转录组学在鉴定广泛的病原体方面是最有效的,并表现出优越的敏感性。我们建议将超转录组学应用于胃肠道病原体的诊断和监测。我们收集了丰富的数据资源,包括直接来自患者粪便样本的配对宏基因组和亚转录组数据集,并将这些数据公开,以加强对感染性肠道疾病相关病原体的了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing infectious intestinal disease diagnosis through metagenomic and metatranscriptomic sequencing of 1000 human diarrhoeal samples.

Background: Current surveillance of diarrhoeal disease is hindered by limitations of traditional diagnostic approaches, which often fail to identify the causative organism, particularly for novel or hard-to-culture bacterial pathogens. Sequencing nucleic acids directly from stool can overcome such constraints, but such approaches need to reliably detect pathogens identifiable by conventional methods.

Methods: As part of the INTEGRATE study, we analysed stool microbiomes from 1067 patients with gastroenteritis symptoms using direct sequencing, and compared findings with standard diagnostic techniques (culture, immunoassay, microscopy, and single-target PCR) and molecular assays (Luminex xTAG GPP) for detection of bacterial and viral pathogens in the UK.

Results: We found strong positive correlations between metatranscriptomic reads and traditional diagnostics for six out of 15 pathogens. The metatranscriptomic data were highly correlated with the Luminex assay for eight out of 14 pathogens. In contrast, metagenomic sequencing only showed a strong positive correlation with traditional diagnostics for three of 15 pathogens, and with Luminex for four of 14 pathogens. Compared with metagenomics, metatranscriptomics had increased sensitivity of detection for four pathogens, while metagenomics was more effective for detecting five pathogens. Metatranscriptomics gave near-complete transcriptome coverage for Human mastadenovirus F and detected Cryptosporidium via identification of Cryptosporidium parvum virus (CSpV1). A comprehensive transcriptomic profile of Salmonella enterica serovar Enteritidis was recovered from the stool of a patient with a laboratory-confirmed Salmonella infection. Furthermore, comparison of RNA/DNA ratios between pathogen-positive and pathogen-negative samples demonstrated that metatranscriptomics can distinguish pathogen-positive/negative samples and provide insights into pathogen biology. Higher RNA/DNA ratios were observed in samples that tested positive via gold-standard diagnostics.

Conclusions: This study highlights the power of directly sequencing nucleic acids from human samples to augment gastrointestinal pathogen surveillance and clinical diagnostics. Metatranscriptomics was most effective for identifying a wide range of pathogens and showed superior sensitivity. We propose that metatranscriptomics should be considered for future diagnosis and surveillance of gastrointestinal pathogens. We assembled a rich data resource of paired metagenomic and metatranscriptomic datasets, direct from patient stool samples, and have made these data publicly available to enhance the understanding of pathogens associated with infectious intestinal diseases.

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来源期刊
Genome Medicine
Genome Medicine GENETICS & HEREDITY-
CiteScore
20.80
自引率
0.80%
发文量
128
审稿时长
6-12 weeks
期刊介绍: Genome Medicine is an open access journal that publishes outstanding research applying genetics, genomics, and multi-omics to understand, diagnose, and treat disease. Bridging basic science and clinical research, it covers areas such as cancer genomics, immuno-oncology, immunogenomics, infectious disease, microbiome, neurogenomics, systems medicine, clinical genomics, gene therapies, precision medicine, and clinical trials. The journal publishes original research, methods, software, and reviews to serve authors and promote broad interest and importance in the field.
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