Metatranscriptomic analysis to define the Secrebiome, and 16S rRNA profiling of the gut microbiome in obesity and metabolic syndrome of Mexican children.

BACKGROUND: In the last decade, increasing evidence has shown that changes in human gut microbiota are associated with diseases, such as obesity. The excreted/secreted proteins (secretome) of the gut microbiota affect the microbial composition, altering its colonization and persistence. Furthermore, it influences microbiota-host interactions by triggering inflammatory reactions and modulating the host's immune response. The metatranscriptome is essential to elucidate which genes are expressed under diseases. In this regard, little is known about the expressed secretome in the microbiome. Here, we use a metatranscriptomic approach to delineate the secretome of the gut microbiome of Mexican children with normal weight (NW) obesity (O) and obesity with metabolic syndrome (OMS). Additionally, we performed the 16S rRNA profiling of the gut microbiota. RESULTS: Out of the 115,712 metatranscriptome genes that codified for proteins, 30,024 (26%) were predicted to be secreted, constituting the Secrebiome of the gut microbiome. The 16S profiling confirmed an increased abundance in Firmicutes and decreased in Bacteroidetes in the obesity groups, and a significantly higher richness and diversity than the normal weight group. We found novel biomarkers for obesity with metabolic syndrome such as increased Coriobacteraceae, Collinsela, and Collinsella aerofaciens; Erysipelotrichaceae, Catenibacterium and Catenibacterium sp., and decreased Parabacteroides distasonis, which correlated with clinical and anthropometric parameters associated to obesity and metabolic syndrome. Related to the Secrebiome, 16 genes, homologous to F. prausniitzi, were overexpressed for the obese and 15 genes homologous to Bacteroides, were overexpressed in the obesity with metabolic syndrome. Furthermore, a significant enrichment of CAZy enzymes was found in the Secrebiome. Additionally, significant differences in the antigenic density of the Secrebiome were found between normal weight and obesity groups. CONCLUSIONS: These findings show, for the first time, the role of the Secrebiome in the functional human-microbiota interaction. Our results highlight the importance of metatranscriptomics to provide novel information about the gut microbiome's functions that could help us understand the impact of the Secrebiome on the homeostasis of its human host. Furthermore, the metatranscriptome and 16S profiling confirmed the importance of treating obesity and obesity with metabolic syndrome as separate conditions to better understand the interplay between microbiome and disease.

Biophysical investigation of liposome systems decorated with bioconjugated copolymers in the presence of amantadine.

Liposome-based technologies derived from lipids and polymers (e.g., PEGylated liposomes) have been recognized because of their applications in nanomedicine. However, since such systems represent myriad challenges and may promote immune responses, investigation of new biomaterials is mandatory. Here, we report on a biophysical investigation of liposomes decorated with bioconjugated copolymers in the presence (or absence) of amantadine (an antiviral medication). First, copolymers of poly(N,N-dimethylacrylamide-co-fluoresceinacrylate-co-acrylic acid-N-succinimide ester)-block-poly(N-isopropylacrylamide) (PDMA-b-PNIPAM) containing a fluorescence label were biofunctionalized with short peptides that resemble the sequence of the loops 220 and 130 of the binding receptor of the hemagglutinin (HA) protein of the influenza A virus. Then, the bioconjugated copolymers were self-assembled along with liposomes composed of 1,2 dimyristoyl-sn-glycero-3-phosphocholine, sphingomyelin, and cholesterol (MSC). These biohybrid systems, with and without amantadine, were systematically characterized using differential scanning calorimetry (DSC), dynamic light scattering (DLS), and cryogenic transmission electron microscopy (cryoTEM). Finally, the systems were tested in an in vitro study to evaluate cytotoxicity and direct immunofluorescence in Madin Darbin Canine Kidney (MDCK) cells. The biohybrid systems displayed long-term stability, thermo-responsiveness, hydrophilic-hydrophobic features, and fluorescence properties and were presumable endowed with cell targeting properties intrinsically integrated into the amino acid sequences of the utilized peptides, which indeed turn them into promising nanodevices for biomedical applications.

Combining metagenomics, metatranscriptomics and viromics to explore novel microbial interactions: towards a systems-level understanding of human microbiome.

The advances in experimental methods and the development of high performance bioinformatic tools have substantially improved our understanding of microbial communities associated with human niches. Many studies have documented that changes in microbial abundance and composition of the human microbiome is associated with human health and diseased state. The majority of research on human microbiome is typically focused in the analysis of one level of biological information, i.e., metagenomics or metatranscriptomics. In this review, we describe some of the different experimental and bioinformatic strategies applied to analyze the 16S rRNA gene profiling and shotgun sequencing data of the human microbiome. We also discuss how some of the recent insights in the combination of metagenomics, metatranscriptomics and viromics can provide more detailed description on the interactions between microorganisms and viruses in oral and gut microbiomes. Recent studies on viromics have begun to gain importance due to the potential involvement of viruses in microbial dysbiosis. In addition, metatranscriptomic combined with metagenomic analysis have shown that a substantial fraction of microbial transcripts can be differentially regulated relative to their microbial genomic abundances. Thus, understanding the molecular interactions in the microbiome using the combination of metagenomics, metatranscriptomics and viromics is one of the main challenges towards a system level understanding of human microbiome.