Gut Microbiome and Small RNA Integrative-Omic Perspective of Meconium and Milk-FED Infant Stool Samples.

The human gut microbiome plays an important role in health, and its initial development is conditioned by many factors, such as feeding. It has also been claimed that this colonization is guided by bacterial populations, the dynamic virome, and transkingdom interactions between host and microbial cells, partially mediated by epigenetic signaling. In this article, we characterized the bacteriome, virome, and smallRNome and their interaction in the meconium and stool samples from infants. Bacterial and viral DNA and RNA were extracted from the meconium and stool samples of 2- to 4-month-old milk-fed infants. The bacteriome, DNA and RNA virome, and smallRNome were assessed using 16S rRNA V4 sequencing, viral enrichment sequencing, and small RNA sequencing protocols, respectively. Data pathway analysis and integration were performed using the R package mixOmics. Our findings showed that the bacteriome differed among the three groups, while the virome and smallRNome presented significant differences, mainly between the meconium and stool of milk-fed infants. The gut environment is rapidly acquired after birth, and it is highly adaptable due to the interaction of environmental factors. Additionally, transkingdom interactions between viruses and bacteria can influence host and smallRNome profiles. However, virome characterization has several protocol limitations that must be considered.

Single-Cell Gene Expression Analysis Revealed Immune Cell Signatures of Delta COVID-19.

The coronavirus disease 2019 (COVID-19) is accompanied by a cytokine storm with the release of many proinflammatory factors and development of respiratory syndrome. Several SARS-CoV-2 lineages have been identified, and the Delta variant (B.1.617), linked with high mortality risk, has become dominant in many countries. Understanding the immune responses associated with COVID-19 lineages may therefore aid the development of therapeutic and diagnostic strategies. Multiple single-cell gene expression studies revealed innate and adaptive immunological factors and pathways correlated with COVID-19 severity. Additional investigations covering host-pathogen response characteristics for infection caused by different lineages are required. Here, we performed single-cell transcriptome profiling of blood mononuclear cells from the individuals with different severity of the COVID-19 and virus lineages to uncover variant specific molecular factors associated with immunity. We identified significant changes in lymphoid and myeloid cells. Our study highlights that an abundant population of monocytes with specific gene expression signatures accompanies Delta lineage of SARS-CoV-2 and contributes to COVID-19 pathogenesis inferring immune components for targeted therapy.

Multiomic Approach to Analyze Infant Gut Microbiota: Experimental and Analytical Method Optimization.

BACKGROUND: The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples. METHODS: Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis. RESULTS: The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile. CONCLUSION: A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.