Bacterial but Not Fungal Gut Microbiota Alterations Are Associated With Common Variable Immunodeficiency (CVID) Phenotype.

Common Variable Immunodeficiency (CVID) is the most frequent symptomatic immune disorder characterized by reduced serum immunoglobulins. Patients often suffer from infectious and serious non-infectious complications which impact their life tremendously. The monogenic cause has been revealed in a minority of patients so far, indicating the role of multiple genes and environmental factors in CVID etiology. Using 16S and ITS rRNA amplicon sequencing, we analyzed the bacterial and fungal gut microbiota, respectively, in a group of 55 participants constituting of CVID patients and matched healthy controls including 16 case-control pairs living in the same household, to explore possible associations between gut microbiota composition and disease phenotype. We revealed less diverse and significantly altered bacterial but not fungal gut microbiota in CVID patients, which additionally appeared to be associated with a more severe disease phenotype. The factor of sharing the same household impacted both bacterial and fungal microbiome data significantly, although not as strongly as CVID diagnosis in bacterial assessment. Overall, our results suggest that gut bacterial microbiota is altered in CVID patients and may be one of the missing environmental drivers contributing to some of the symptoms and disease severity. Paired samples serving as controls will provide a better resolution between disease-related dysbiosis and other environmental confounders in future studies.

The Impact of DNA Extraction Methods on Stool Bacterial and Fungal Microbiota Community Recovery.

Our understanding of human gut microbiota in health and disease depends on accurate and reproducible microbial data acquisition. The critical step in this process is to apply an appropriate methodology to extract microbial DNA, since biases introduced during the DNA extraction process may result in inaccurate microbial representation. In this study, we attempted to find a DNA extraction protocol which could be effectively used to analyze both the bacterial and fungal community. We evaluated the effect of five DNA extraction methods (QIAamp DNA Stool Mini Kit, PureLinkTM Microbiome DNA Purification Kit, ZR Fecal DNA MiniPrepTM Kit, NucleoSpin® DNA Stool Kit, and IHMS protocol Q) on bacterial and fungal gut microbiome recovery using (i) a defined system of germ-free mice feces spiked with bacterial or fungal strains, and (ii) non-spiked human feces. In our experimental setup, we confirmed that the examined methods significantly differed in efficiency and quality, which affected the identified stool microbiome composition. In addition, our results indicated that fungal DNA extraction might be prone to be affected by reagent/kit contamination, and thus an appropriate blank control should be included in mycobiome research. Overall, standardized IHMS protocol Q, recommended by the International Human Microbiome Consortium, performed the best when considering all the parameters analyzed, and thus could be applied not only in bacterial, but also in fungal microbiome research.

Rapid identification of medically important Candida isolates using high resolution melting analysis.

An increasing trend in non albicans infections and various susceptibility patterns to antifungal agents implies a requirement for the quick and reliable identification of a number of medically important Candida species. Real-time PCR followed by high resolution melting analysis (HRMA) was developed, tested on 25 reference Candida collection strains and validated on an additional 143 clinical isolates in this study. All reference strains and clinical isolates inconclusive when using phenotypic methods and/or HRMA were analysed using ITS2 sequencing. Considering reference and clinical strains together, 23 out of 27 Candida species could be clearly distinguished by HRMA, while the remaining 4 species were grouped in 2 pairs, when applying the mean Tm ± 3 SD values, the shape of the derivative melting curve (dMelt curve) and, in some cases, the normalized and temperature-shifted difference plot against C. krusei. HRMA as a simple, rapid and inexpensive tool was shown to be useful in identifying a wide spectrum of clinically important Candida species. It may complement the current clinical diagnostic approach based on commercially available biochemical kits.