Comparative analysis of DNA extraction and PCR product purification methods for cervicovaginal microbiome analysis using cpn60 microbial profiling

Background The microbiota of the lower female genital tract plays an important role in women’s health. Microbial profiling using the chaperonin60 (cpn60) universal target (UT) improves resolution of vaginal species associated with negative health outcomes compared to the more commonly used 16S ribosomal DNA target. However, the choice of DNA extraction and PCR product purification methods may bias sequencing-based microbial studies and should be optimized for the sample type and molecular target used. In this study, we compared two commercial DNA extraction kits and two commercial PCR product purification kits for the microbial profiling of cervicovaginal samples using the cpn60 UT. Methods DNA from cervicovaginal secretions and vaginal lavage samples as well as mock community standards were extracted using either the specialized QIAamp DNA Microbiome Kit, or the standard DNeasy Blood & Tissue kit with enzymatic pre-treatment for enhanced lysis of gram-positive bacteria. Extracts were PCR amplified using well-established cpn60 primer sets and conditions. Products were then purified using a column-based method (QIAquick PCR Purification Kit) or a gel-based PCR clean-up method using the QIAEX II Gel Extraction Kit. Purified amplicons were sequenced with the MiSeq platform using standard procedures. The overall quality of each method was evaluated by measuring DNA yield, alpha diversity, and microbial composition. Results DNA extracted from cervicovaginal samples using the DNeasy Blood and Tissue kit, pre-treated with lysozyme and mutanolysin, resulted in increased DNA yield, bacterial diversity, and species representation compared to the QIAamp DNA Microbiome kit. The column-based PCR product purification approach also resulted in greater average DNA yield and wider species representation compared to a gel-based clean-up method. In conclusion, this study presents a fast, effective sample preparation method for high resolution cpn60 based microbial profiling of cervicovaginal samples.

Gut Microbiota Exceeds Cervical Microbiota for Early Diagnosis of Endometriosis

The diagnosis of endometriosis is typically delayed by years for the unexclusive symptom and the traumatic diagnostic method. Several studies have demonstrated that gut microbiota and cervical mucus potentially can be used as auxiliary diagnostic biomarkers. However, none of the previous studies has compared the robustness of endometriosis classifiers based on microbiota of different body sites or demonstrated the correlation among microbiota of gut, cervical mucus, and peritoneal fluid of endometriosis, searching for alternative diagnostic approaches. Herein, we enrolled 41 women (control, n = 20; endometriosis, n = 21) and collected 122 well-matched samples, derived from feces, cervical mucus, and peritoneal fluid, to explore the nature of microbiome of endometriosis patients. Our results indicated that microbial composition is remarkably distinguished between three body sites, with 19 overlapped taxa. Moreover, endometriosis patients harbor distinct microbial communities versus control group especially in feces and peritoneal fluid, with increased abundance of pathogens in peritoneal fluid and depletion of protective microbes in feces. Particularly, genera of Ruminococcus and Pseudomonas were identified as potential biomarkers in gut and peritoneal fluid, respectively. Furthermore, novel endometriosis classifiers were constructed based on taxa selected by a robust machine learning method. These results demonstrated that gut microbiota exceeds cervical microbiota in diagnosing endometriosis. Collectively, this study reveals important insights into the microbial profiling in different body sites of endometriosis, which warrant future exploration into the role of microbiota in endometriosis and highlighted values on gut microbiota in early diagnosis of endometriosis.

Gut Microbiota Interplay With COVID-19 Reveals Links to Host Lipid Metabolism Among Middle Eastern Populations

The interplay between the compositional changes in the gastrointestinal microbiome, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) susceptibility and severity, and host functions is complex and yet to be fully understood. This study performed 16S rRNA gene-based microbial profiling of 143 subjects. We observed structural and compositional alterations in the gut microbiota of the SARS-CoV-2-infected group in comparison to non-infected controls. The gut microbiota composition of the SARS-CoV-2-infected individuals showed an increase in anti-inflammatory bacteria such as Faecalibacterium (p-value = 1.72 × 10–6) and Bacteroides (p-value = 5.67 × 10–8). We also revealed a higher relative abundance of the highly beneficial butyrate producers such as Anaerostipes (p-value = 1.75 × 10–230), Lachnospiraceae (p-value = 7.14 × 10–65), and Blautia (p-value = 9.22 × 10–18) in the SARS-CoV-2-infected group in comparison to the control group. Moreover, phylogenetic investigation of communities by reconstructing unobserved state (PICRUSt) functional prediction analysis of the 16S rRNA gene abundance data showed substantial differences in the enrichment of metabolic pathways such as lipid, amino acid, carbohydrate, and xenobiotic metabolism, in comparison between both groups. We discovered an enrichment of linoleic acid, ether lipid, glycerolipid, and glycerophospholipid metabolism in the SARS-CoV-2-infected group, suggesting a link to SARS-CoV-2 entry and replication in host cells. We estimate the major contributing genera to the four pathways to be Parabacteroides, Streptococcus, Dorea, and Blautia, respectively. The identified differences provide a new insight to enrich our understanding of SARS-CoV-2-related changes in gut microbiota, their metabolic capabilities, and potential screening biomarkers linked to COVID-19 disease severity.

The Intratumor Microbiota Signatures Associate With Subtype, Tumor Stage, and Survival Status of Esophageal Carcinoma

Altered human microbiome characteristic has been linked with esophageal carcinoma (ESCA), analysis of microbial profiling directly derived from ESCA tumor tissue is beneficial for studying the microbial functions in tumorigenesis and development of ESCA. In this study, we identified the intratumor microbiome signature and investigated the correlation between microbes and clinical characteristics of patients with ESCA, on the basis of data and information obtained from The Cancer Microbiome Atlas (TCMA) and The Cancer Genome Atlas (TCGA) databases. A total of 82 samples were analyzed for microbial composition at various taxonomic levels, including 40 tumor samples of esophageal squamous cell carcinoma (ESCC), 20 tumor samples of esophageal adenocarcinoma (EAD), and 22 adjacent normal samples. The results showed that the relative abundance of several microbes changed in tumors compared to their paired normal tissues, such as Firmicutes increased significantly while Proteobacteria decreased in tumor samples. We also identified a microbial signature composed of ten microbes that may help in the classification of ESCC and EAD, the two subtypes of ESCA. Correlation analysis demonstrated that compositions of microbes Fusobacteria/Fusobacteriia/Fusobacteriales, Lactobacillales/Lactobacillaceae/Lactobacillus, Clostridia/Clostridiales, Proteobacteria, and Negativicutes were correlated with the clinical characteristics of ESCA patients. In summary, this study supports the feasibility of detecting intratumor microbial composition derived from tumor sequencing data, and it provides novel insights into the roles of microbiota in tumors. Ultimately, as the second genome of human body, microbiome signature analysis may help to add more information to the blueprint of human biology.

Microbiome Forensic Biobanking: A Step toward Microbial Profiling for Forensic Human Identification

In recent years many studies have highlighted the great potential of microbial analysis in human identification for forensic purposes, with important differences in microbial community composition and function across different people and locations, showing a certain degree of uncertainty. Therefore, further studies are necessary to enable forensic scientists to evaluate the risk of microbial transfer and recovery from various items and to further critically evaluate the suitability of current human DNA recovery protocols for human microbial profiling for identification purposes. While the establishment and development of microbiome research biobanks for clinical applications is already very structured, the development of studies on the applicability of microbiome biobanks for forensic purposes is still in its infancy. The creation of large population microbiome biobanks, specifically dedicated to forensic human identification, could be worthwhile. This could also be useful to increase the practical applications of forensic microbiology for identification purposes, given that this type of evidence is currently absent from most real casework investigations and judicial proceedings in courts.

PSIII-18 Identification of microbial interactions and markers associated with Shiga toxin-producing bacteria colonization in the rectum of beef steers

This study aimed to identify whether microbial interactions in the rectum contribute to Shiga toxin producing bacteria colonization. In total, 12 rectal digesta samples based on the previously identified Shiga toxin 2 gene (stx2) abundance (DNA) and expression (RNA) in Shiga toxin-producing bacteria (Stx2- group: detectable DNA, n=6; Stx2+ group: detectable DNA and RNA, n = 6) were subjected to microbial profiling using amplicon sequencing. Firmicutes (72.7 ± 2.0 %) and Bacteroidetes (24.6 ± 1.9 %) are the most predominant phyla of rectal microbiota, and no compositional differences were identified between two groups at the phylum level. The Shannon and Chao1 indices weren’t different in rectal digesta microbial communities between two groups. Twenty-four and thirteen taxa were identified to be group-specific genera in microbial communities from Stx2- and Stx2+ group, respectively (2 out of 6, average relative abundance >0.1%). The network analysis indicated 12 and 14 keystone taxa (Generalists, densely connected with other taxa) in microbial communities between Stx2- and Stx2+ groups, respectively. Eight out of 12 and six out of 14 generalists in the Stx2- and Stx2+ group are belonging to group-specific genera, respectively. Generalists belonging to group-specific genera were broadly distributed in Stx2- network while centralized distributed in the Stx2+ network, suggesting the higher stability of the Stx2- network structure in comparison of Stx2+ network computed by the natural connectivity measurement. However, 66 core genera shared by microbial communities between two groups were not classified into network generalists. Overall, our results indicate microbial crosstalks and keystone taxa in microbial communities between two groups differed, suggesting that the microbial interactions rather than the shifts in taxa abundance may be more important affecting host. Moreover, group-specific genera play a vital ecological role in the microbial interactions, indicating the potential for being microbial markers to differentiate Shiga toxin-producing bacteria colonization in beef cattle.

Microbial trend analysis for common dynamic trend, group comparison, and classification in longitudinal microbiome study

Background The human microbiome is inherently dynamic and its dynamic nature plays a critical role in maintaining health and driving disease. With an increasing number of longitudinal microbiome studies, scientists are eager to learn the comprehensive characterization of microbial dynamics and their implications to the health and disease-related phenotypes. However, due to the challenging structure of longitudinal microbiome data, few analytic methods are available to characterize the microbial dynamics over time. Results We propose a microbial trend analysis (MTA) framework for the high-dimensional and phylogenetically-based longitudinal microbiome data. In particular, MTA can perform three tasks: 1) capture the common microbial dynamic trends for a group of subjects at the community level and identify the dominant taxa; 2) examine whether or not the microbial overall dynamic trends are significantly different between groups; 3) classify an individual subject based on its longitudinal microbial profiling. Our extensive simulations demonstrate that the proposed MTA framework is robust and powerful in hypothesis testing, taxon identification, and subject classification. Our real data analyses further illustrate the utility of MTA through a longitudinal study in mice. Conclusions The proposed MTA framework is an attractive and effective tool in investigating dynamic microbial pattern from longitudinal microbiome studies.

Biochemical and microbial profiling establish “Eu” (a traditional fermented beverage of Toto people) as a probiotic health drink

Abstract“Eu,” is a traditional millet-based mild alcoholic beverage consumed by the Toto tribe of West Bengal. Eu is prepared through the fermentation of millet with locally groomed starter culture “Moaa.” The study highlighted the overview of the traditional process of Eu preparation along with its molecular and biochemical characterization. Semi-structured interviews were conducted for collecting the ethnobotanical data and the samples. We have also included qualitative assays like acute toxicity, antioxidant, gas chromatography-mass spectrometry (GC-MS), molecular docking, and physiochemical characteristics such as pH and alcohol content. Moreover, metagenomics of the starter culture has been reported. This type of study on Eu has not been done previously. Therefore, it seems to be a pioneer report especially on the metagenomic analysis of Eu. Results revealed that Eu has a very low alcohol content (approximately 1-3%) and a high antioxidant capacity. GC-MS analysis identified thirteen different bioactive compounds. Metagenomics analysis revealed that the Eu has a high source of various beneficial gut microflora. Overall Lactobacillus, Lactococcus, Enterococcus, Leuconostoc, and Pediococcus are dominant genera identified in the starter culture. The present study revealed that the consumption of Eu is safe and has the potential to scavenge reactive oxygen species (ROS). Hence, the commercialization of Eu can be an alternative source of income for the poor endangered Toto tribe.

Fecal Microbiota Analysis Exploring Taxonomic Diversity of Hindgut Microbial Communities in Kasaragod Dwarf and Holstein Friesian Cattle

The indigenous cattle are efficient in converting low quality feeds and forage into animal products. Kasaragod Dwarf (K-Dwarf) cattle, a non-descriptive native cattle variety of Kerala, are noted for their unique qualities, like short stature, low feed intake, thermotolerance, greater resistance to diseases and A2 allelic variant milk. This study hypothesizes that K-Dwarf cow relies on their unique hindgut microbes to ferment the low quality feeds into the efficient animal product. To compare and contrast this unique microbiota and their relationship between the host, we performed microbial profiling of the two genetically distinct cattle-type viz., K-Dwarf, and Holstein utilizing 16S rRNA high-throughput sequencing. Principle Coordinate Analysis using weighted and unweighted UniFrac distance matrices showed significantly distinct clustering of K-Dwarf microbial community compared to Holstein, implying the distinct microbial architecture that K-Dwarf harbors. The dissimilarities observed between the two cattle types were further revealed from the signature taxa identified in each cattle type following Random Forest analysis. In addition, the study observed the predominance of feed efficiency associated genera viz., Anaerovibrio, Succinivibrio, Roseburia, Coprococcus, Anaerostipes, Paludibacter, Elusimicrobium, Sutterella, Oribacterium, Coprobacillus, and Ruminobacter in K-Dwarf cattle. The study highlights the abundance of unique and beneficial hindgut microflora found in K-Dwarf, which may attest its importance over exotic cattle breeds viz., Holstein. To our knowledge, this is the first report of K-Dwarf cattle gut microbiome profiling. Further molecular characterization is solicited to better understand the microbial role in the conversion of low-quality feeds into more efficient animal products, a well-defined characteristic of indigenous cattle.