Type 2 diabetes mellitus (T2DM) accounts for 90% of diabetes cases worldwide. The majority of T2DM patients are obese. Dysbiosis in the gut microflora is strongly associated with the pathogenesis of obesity and T2DM; however, the microbiome of obese-T2DM individuals in the Pakistani population remains unexplored. The gut microbiota signature of 60 Pakistani adults was studied using 16S rRNA sequencing targeting V3–V4 hypervariable regions. The sequence analysis revealed that bacteria from Firmicutes were predominant along with those from Clostridia and Negativicutes, whereas bacteria from Verrucomicrobia, Bacteroidetes, Proteobacteria, and Elusimicrobia were less abundant among the obese T2DM patients. These data distinctively vary from those in reports on the Indian population. The difference in gut microbiota could presumably be related to the distinct lifestyle and eastern dietary habits (high carbohydrate and fat intake, low fiber intake) and unregulated antibiotic consumption. This is the first study carried out to understand the gut microbiome and its correlation with individual life style of obese T2DM patients in the Pakistani population.

Microbial diversity in unique environmental settings enables abrupt responses catalysed by altering the gene regulation and formation of gene clusters called operons. Operons increases bacterial adaptability, which in turn increases their survival. This review article presents the emergence of computational operon prediction methods for whole microbial genomes and metagenomes, and discusses their strengths and limitations. Most of the whole-genome operon prediction methods struggle to generalize on unrelated genomes. The applicability of universal whole-genome operon prediction methods to metagenomic data is an interesting yet less investigated question. We have evaluated the potential of various operon prediction features for genomic and metagenomic data. Most of operon prediction methods with high accuracy have been compiled into databases. Despite of the high predictive performance, the data among many databases are not completely consistent for similar species. We performed a correlation analysis between the computationally predicted operon databases and experimentally validated data for Escherichia coli, Bacillus subtilis and Mycobacterium tuberculosis. Operon prediction for most of the less characterized microbes cannot be verified due to absence of experimentally validated operons. The generation of validated information for other microbes would test the authenticity of operon databases for other less annotated microbes as well. Advances in sequencing technologies and development of better analysis methods will help researchers to overcome the technological hurdles (such as long sequencing reads and improved contig size) and further improve operon predictions and better utilize operonic information.

Zebrafish have been used as a model organism for more than 50 years and are considered an excellent model for studying host-microbiome interactions. However, this largely depends on our understanding of the zebrafish gut microbiome itself. Despite advances in sequencing and data analysis methods, the zebrafish gut microbiome remains highly understudied. This study performed the de novo metagenome assembly and recovery of the metagenome-assembled genomes (MAGs) through genome binning (and refinement) of the contigs assembled from the zebrafish stool. The results indicate that majority of the MAGs had excellent quality i.e. high completeness (≥90%) and low contamination levels (≤5%). MAGs mainly belong to the taxa that are known to be members of the core zebrafish stool microbiome, including the phylum Proteobacteria, Fusobacteriota, and Actinobacteriota. However, most of the MAGs remained unclassified at the species level and reflected previously unexplored microbial taxa and their potential novelty. These MAGs also contained genes with predicted functions associated with diverse metabolic pathways that included carbohydrate, amino acid, and lipid metabolism pathways. Lastly, we performed a comparative analysis of Paucibacter MAGs and reference genomes that highlighted the presence of novel Paucibacter species and enriched metabolic potential in the recovered MAGs.

No abstract

The human microbiota is recognized as a vital “virtual” organ of the human body that influences human health, metabolism, and physiology. While the microbiomes of the gut, oral cavity, and skin have been extensively studied in the literature, relatively little work has been done on characterizing the microbiota of the human reproductive tract organs, and specifically on investigating its association to fertility. Here, we implemented a 16S ribosomal RNA (rRNA) amplicon sequencing approach to sequence and characterize the gut and genital tract microbiomes from several married Pakistani couples. The recruited individuals included 31 fertile and 35 infertile individuals, with ages ranging from 19–45 years. We identified several fluctuations in the diversity and composition of the gut and genital microbiota among fertile and infertile samples. For example, measures of α-diversity varied significantly between the genital samples donated by fertile and infertile men and there was overall greater between-sample variability in genital samples regardless of gender. In terms of taxonomic composition, Actinobacteria, Bacteroidetes, and Firmicutes fluctuated significantly between the gut microbiomes of fertile and infertile samples. Finally, biomarker analyses identified features (genera and molecular functions and pathways) that differed significantly between the fertile and infertile samples and in the past have been associated with bacterial vaginosis. However, we emphasize that 16S amplicon data alone has no bearing on individual health and is merely representative of microbial taxonomic differences that could also arise due to multiple other factors. Our findings, however, represent the first effort to characterize the microbiome associated with fertile and infertile couples in Pakistan and will hopefully pave the way for more comprehensive and broad-scale investigations in the future.