Fungal and bacterial gut microbiota differ between Clostridioides difficile colonization and infection

J. Henderickx, M. Crobach, E. M. Terveer, WK Smits, E. Kuijper, R. Zwittink
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Abstract

Aim: The bacterial microbiota is well-recognized for its role in Clostridioides difficile colonization and infection, while fungi and yeasts remain understudied. The aim of this study was to analyze the predictive value of the mycobiota and its interactions with the bacterial microbiota in light of C. difficile colonization and infection. Methods: The mycobiota was profiled by ITS2 sequencing of fecal DNA from C. difficile infection (CDI) patients (n = 29), asymptomatically C. difficile colonization (CDC) patients (n = 38), and hospitalized controls with C. difficile negative stool culture (controls; n = 38). Previously published 16S rRNA gene sequencing data of the same cohort were used additionally for machine learning and fungal-bacterial network analysis. Results: CDI patients were characterized by a significantly higher abundance of Candida spp. (MD 0.270 ± 0.089, P = 0.002) and Candida albicans (MD 0.165 ± 0.082, P = 0.023) compared to controls. Additionally, they were deprived of Aspergillus spp. (MD -0.067 ± 0.026, P = 0.000) and Penicillium spp. (MD -0.118 ± 0.043, P = 0.000) compared to CDC patients. Network analysis revealed a positive association between several fungi and bacteria in CDI and CDC, although the analysis did not reveal a direct association between Clostridioides spp. and fungi. Furthermore, the microbiota machine learning model outperformed the models based on the mycobiota and the joint microbiota-mycobiota model. The microbiota classifier successfully distinguished CDI from CDC [Area Under the Receiver Operating Characteristic (AUROC) = 0.884] and CDI from controls (AUROC = 0.905). Blautia and Bifidobacterium were marker genera associated with CDC patients and controls. Conclusion: The gut mycobiota differs between CDI, CDC, and controls and may affect Clostridioides spp. through indirect interactions. The mycobiota data alone could not successfully discriminate CDC from controls or CDI patients and did not have additional predictive value to the bacterial microbiota data. The identification of bacterial marker genera associated with CDC and controls warrants further investigation.
难辨梭状芽孢杆菌定植和感染时,真菌和细菌肠道微生物群有所不同
目的:细菌微生物群因其在艰难梭菌定植和感染中的作用而得到广泛认可,而真菌和酵母仍未得到充分研究。本研究的目的是分析真菌菌群及其与细菌微生物群的相互作用在艰难梭菌定植和感染方面的预测价值。方法:通过对艰难梭菌感染(CDI)患者(n = 29)、无症状艰难梭菌定植(CDC)患者(n = 38)和艰难梭菌阴性粪便培养住院对照(对照组;N = 38)。先前发表的同一队列的16S rRNA基因测序数据被额外用于机器学习和真菌-细菌网络分析。结果:CDI患者的念珠菌(md0.270±0.089,P = 0.002)和白色念珠菌(md0.165±0.082,P = 0.023)丰度显著高于对照组。此外,与CDC患者相比,他们被剥夺了曲霉菌(MD -0.067±0.026,P = 0.000)和青霉菌(MD -0.118±0.043,P = 0.000)。网络分析显示,CDI和CDC中几种真菌和细菌之间存在正相关关系,但分析未发现梭状芽孢杆菌与真菌之间存在直接关联。此外,微生物群机器学习模型优于基于真菌群和联合微生物群-真菌群模型的模型。微生物群分类器成功区分了CDI与CDC[受者工作特征下面积(AUROC) = 0.884]和CDI与对照(AUROC = 0.905)。蓝杆菌和双歧杆菌是与CDC患者和对照组相关的标记属。结论:CDI、CDC和对照组肠道菌群存在差异,可能通过间接相互作用影响梭状芽孢杆菌。单独的真菌菌群数据不能成功区分CDC与对照组或CDI患者,并且对细菌微生物群数据没有额外的预测价值。与CDC和对照相关的细菌标记属的鉴定值得进一步调查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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