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The evolution and the development of the symptoms of Coronavirus disease 19 (COVID-19) are due to different factors, where the microbiome plays a relevant role. The possible relationships between the gut, lung, nasopharyngeal, and oral microbiome with COVID-19 have been investigated. We analyzed the nasal microbiome of both positive and negative SARS-CoV-2 individuals, showing differences in terms of bacterial composition in this niche of respiratory tract. The microbiota solution A (Arrow Diagnostics) was used to cover the hypervariable V1–V3 regions of the bacterial 16S rRNA gene. MicrobAT Suite and MicrobiomeAnalyst program were used to identify the operational taxonomic units (OTUs) and to perform the statistical analysis, respectively. The main taxa identified in nasal microbiome of COVID-19 patients and in Healthy Control subjects belonged to three distinct phyla: Proteobacteria (HC = 14%, Cov19 = 35.8%), Firmicutes (HC = 28.8%, Cov19 = 30.6%), and Actinobacteria (HC = 56.7%, Cov19 = 14.4%) with a relative abundance > 1% in all groups. A significant reduction of Actinobacteria in Cov19 group compared to controls (P P Corynebacterium was found in the patients compared to healthy controls (P = 0.001). Reduced abundance of Corynebacterium has been widely associated with anosmia, a common symptom of COVID-19 as suffered from our patients. Contrastingly, the Corynebacterium genus was highly represented in the nasal mucosa of healthy subjects. Further investigations on larger cohorts are necessary to establish functional relationships between nasal microbiota content and clinical features of COVID-19.

Colorectal cancer (CRC) is one of the most common malignancies in the Western world and intestinal dysbiosis might contribute to its pathogenesis. The mucosal colon microbiome and C-C motif chemokine 2 (CCL2) were investigated in 20 healthy controls (HC) and 20 CRC patients using 16S rRNA sequencing and immunoluminescent assay, respectively. A total of 10 HC subjects were classified as overweight/obese (OW/OB_HC) and 10 subjects were normal weight (NW_HC), 15 CRC patients were classified as OW/OB_CRC and 5 patients were NW_CRC. Results: Fusobacterium nucleatum and Escherichia coli were more abundant in OW/OB_HC than in NW_HC microbiomes. Globally, Streptococcus intermedius, Gemella haemolysans, Fusobacterium nucleatum, Bacteroides fragilis and Escherichia coli were significantly increased in CRC patient tumor/lesioned tissue (CRC_LT) and CRC patient unlesioned tissue (CRC_ULT) microbiomes compared to HC microbiomes. CCL2 circulating levels were associated with tumor presence and with the abundance of Fusobacterium nucleatum, Bacteroides fragilis and Gemella haemolysans. Our data suggest that mucosal colon dysbiosis might contribute to CRC pathogenesis by inducing inflammation. Notably, Fusobacterium nucleatum, which was more abundant in the OW/OB_HC than in the NW_HC microbiomes, might represent a putative link between obesity and increased CRC risk.

Purpose. Fat mass and obesity-related (FTO) rs9939609 polymorphism has a role in body mass index (BMI) increase and in predisposing to metabolic syndrome (MetS). Our aim was to investigate if a very light physical activity could counteract weight gain and MetS in obese subjects bearing the rs9939609 FTO polymorphism from Southern Italy. Methods. Data of fitness components, anthropometry, clinical-biochemical parameters and FTO polymorphism in 78 unrelated morbid obese subjects from Southern Italy (15-30 years) were examined. Physical activity energy expenditure was monitored by a SenseWear Pro 3 Armband for 24 h/day for two consecutive weekdays in all enrolled individuals. Results. Sedentary obese subjects had higher waist circumference (124.8 vs 117.9 cm, P

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the pandemic Coronavirus Disease 2019 (COVID-19). This virus is highly transmissible among individuals through both droplets and aerosol leading to determine severe pneumonia. Among the various factors that can influence both the onset of disease and the severity of its complications, the microbiome composition has also been investigated. Recent evidence showed the possible relationship between gut, lung, nasopharyngeal, or oral microbiome and COVID-19, but very little is known about it. Therefore, we aimed to verify the relationships between nasopharyngeal microbiome and the development of either COVID-19 or the severity of symptoms. To this purpose, we analyzed, by next generation sequencing, the hypervariable V1-V2-V3 regions of the bacterial 16S rRNA in nasopharyngeal swabs from SARS-CoV-2 infected patients (n=18) and control (CO) individuals (n=12) using Microbiota solution A (Arrow Diagnostics). We found a significant lower abundance of Proteobacteria and Fusobacteria in COVID-19 patients in respect to CO (p=0.003 and p

Our body is inhabited by a variety of microbes (microbiota), mainly bacteria, that outnumber our own cells. Until recently, most of what we knew about the human microbiota was based on culture methods, whereas a large part of the microbiota is uncultivable, and consequently previous information was limited. The advent of culture-independent methods and, particularly, of next-generation sequencing (NGS) methodology, marked a turning point in studies of the microbiota in terms of its composition and of the genes encoded by these microbes (microbiome). The microbiome is influenced predominantly by environmental factors that cause a large inter-individual variability (~20%) being its heritability only 1.9%. The gut microbiome plays a relevant role in human physiology, and its alteration (“dysbiosis”) has been linked to a variety of inflammatory gut diseases, including celiac disease (CD). CD is a chronic, immune-mediated disorder that is triggered by both genetic (mainly HLA-DQ2/DQ8 haplotypes) and environmental factors (gluten), but, in recent years, a large body of experimental evidence suggested that the gut microbiome is an additional contributing factor to the pathogenesis of CD. In this review, we summarize the literature that has investigated the gut microbiome associated with CD, the methods and biological samples usually employed in CD microbiome investigations and the putative pathogenetic role of specific microbial alterations in CD. In conclusion, both gluten-microbe and host-microbe interactions drive the gluten-mediated immune response. However, it remains to be established whether the CD-associated dysbiosis is the consequence of the disease, a simple concomitant association or a concurring causative factor.

Coeliac disease (CD) is a multifactorial autoimmune disorder and gut dysbiosis contributes to its pathogenesis. We previously profiled by 16S rRNA sequencing duodenal and oropharyngeal microbiomes in active CD (a-CD), gluten-free diet (GFD) patients, and controls (CO) and found significantly higher levels of Neisseria spp., with pro-inflammatory activities, in a-CD patients than in the other two groups. In this study, we developed a fast and simple qPCR-based method to evaluate the abundance of the oral Neisseria spp. and the diagnostic performances of the test in CD diagnosis. The Neisseria spp. abundances detected by quantitative PCR (qPCR) were: CO = 0.14, GFD = 0.15, a-CD = 2.08, showing a similar trend to those previously measured by next generation sequencing (NGS). In particular, Neisseria spp. values obtained by both methods were significantly higher (p < 0.001) in a-CD than in the other two groups GFD and CO—the latter almost overlapping. We calculated by ROC curve analysis the threshold of 1.12 ng/μL of Neisseria spp. to discriminate between CO+GFD and a-CD patients with 100% and 96.7% of diagnostic sensitivity and specificity, respectively. In conclusion, our data, if confirmed in other cohorts, suggest the q-PCR evaluation of oral Neisseria spp. could be a fast and simple method to assess CD-associated dysbiosis for diagnostic purposes.

The gut microbiota may have an impact on obesity. To date, the majority of studies in obese patients reported microbiota composition in stool samples. The aim of this study was to investigate the duodenal mucosa dysbiosis in adult obese individuals from Campania, a region in Italy with a very high percentage of obese people, to highlight microbial taxa likely associated with obesity. Duodenum biopsies were taken during upper gastrointestinal endoscopy in 19 obese (OB) and 16 lean control subjects (CO) and microbiome studied by 16S rRNA gene sequencing. Duodenal microbiome in our groups consisted of six phyla: Proteobacteria, Firmicutes, Actinobacteria, Fusobacteria, Bacteroidetes and Acidobacteria. Proteobacteria (51.1% vs. 40.1%) and Firmicutes (33.6% vs. 44.9%) were significantly (p < 0.05) more and less abundant in OB compared with CO, respectively. Oribacterium asaccharolyticum, Atopobium parvulum and Fusobacterium nucleatum were reduced (p < 0.01) and Pseudomonadales were increased (p < 0.05) in OB compared with CO. Receiver operating characteristic curve analysis showed Atopobium and Oribacterium genera able to discriminate with accuracy (power = 75% and 78%, respectively) OB from CO. In conclusion, increased Proteobacteria and decreased Firmicutes (Lachnospiraceae) characterized the duodenal microbiome of obese subjects. These data direct to further studies to evaluate the functional role of the dysbiotic-obese-associated signature.

Nutritional imbalance and metabolic alterations associated with maternal obesity during pregnancy predispose offspring to obesity and/or to type 2 diabetes, but the mechanisms underlying these effects are still obscure. In this context, we evaluated whether the two main energy-producing pathways (glycolysis and mitochondrial oxidative phosphorylation) are impaired in obesity during pregnancy thus contributing to metabolic intrauterine alterations. Specifically, we studied metabolic abnormalities in the intrauterine life of newborns using stem cells isolated from amnion and umbilical cord (hA- and hUC-MSCs). We isolated, at delivery, neonatal hUC-MSCs from 13 obese (Ob) and 10 normal weight control (Co) women (prepregnancy body mass index >30 and

Background. Laparoscopic adjustable gastric banding (LAGB) results in significant lasting weight loss and improved metabolism in obese patients. To evaluate whether epigenetic factors could concur to these benefits, we investigated the subcutaneous adipose tissue (SAT) microRNA (miRNA) profile before (T0) and three years (T1) after LAGB in three morbidly obese women. Case Reports. SAT miRNA profiling, evaluated by TaqMan Array, showed four downexpressed (miR-519d, miR-299-5p, miR-212, and miR-671-3p) and two upexpressed (miR-370 and miR-487a) miRNAs at T1 versus T0. Bioinformatics predicted that these miRNAs regulate genes belonging to pathways associated with the cytoskeleton, inflammation, and metabolism. Western blot analysis showed that PPAR-alpha, which is the target gene of miR-519d, increased after LAGB, thereby suggesting an improvement in SAT lipid metabolism. Accordingly, the number and diameter of adipocytes were significantly higher and lower, respectively, at T1 versus T0. Bioinformatics predicted that the decreased levels of miR-212, miR-299-5p, and miR-671-3p at T1 concur in reducing SAT inflammation. Conclusion. We show that the miRNA profile changes after LAGB. This finding, although obtained in only three cases, suggests that this epigenetic mechanism, by regulating the expression of genes involved in inflammation and lipid metabolism, could concur to improve SAT functionality in postoperative obese patients.

Maternal obesity increases the risk of obesity and/or obesity-related diseases in the offspring of animal models. The aim of this study was to identify metabolic dysfunctions that could represent an enhanced risk for human obesity or obesity-related diseases in newborn or in adult life, similar to what occurs in animal models. To this aim, we studied the proteome of 12 obese (Ob-) and 6 non-obese (Co-) human amniotic mesenchymal stem cells (hA-MSCs) obtained from women at delivery by cesarean section (pre-pregnancy body mass index [mean ± SD]: 42.7 ± 7.7 and 21.3 ± 3.3 kg/m2, respectively). The proteome, investigated by two-dimensional fluorescence difference gel electrophoresis/mass spectrometry, revealed 62 differently expressed proteins in Ob- vs Co-hA-MSCs (P