Gastrointestinal neuromuscular apparatus: An underestimated target of gut microbiota

Over the last few years, the importance of the resident intestinal microbiota in the pathogenesis of several gastro- intestinal diseases has been largely investigated. Growing evidence suggest that microbiota can influence gastro- intestinal motility. The current working hypothesis is that dysbiosis-driven mucosal alterations induce the production of several inflammatory/immune mediators which affect gut neuro-muscular functions. Besides these indirect mucosal-mediated effects, the present review highlights that recent evidence suggests that microbiota can directly affect enteric nerves and smooth muscle cells functions through its metabolic products or bacterial molecular components translocated from the intestinal lumen. Toll- like receptors, the bacterial recognition receptors, are expressed both on enteric nerves and smooth muscle and are emerging as potential mediators between microbiota and the enteric neuromuscular apparatus. Furthermore, the ongoing studies on probiotics support the hypothesis that the neuromuscular apparatus may represent a target of intervention, thus opening new physiopathological and therapeutic scenarios

Bifidobacteria and lactobacilli in the gut microbiome of children with non-alcoholic fatty liver disease: which strains act as health players?

Introduction: Non-alcoholic fatty liver disease (NAFLD), considered the leading cause of chronic liver disease in children, can often progress from non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH). It is clear that obesity is one of the main risk factors involved in NAFLD pathogenesis, even if specific mechanisms have yet to be elucidated. We investigated the distribution of intestinal bifidobacteria and lactobacilli in the stools of four groups of children: obese, obese with NAFL, obese with NASH, and healthy, age-matched controls (CTRLs). Material and methods: Sixty-one obese, NAFL and NASH children and 54 CTRLs were enrolled in the study. Anthropometric and metabolic parameters were measured for all subjects. All children with suspected NASH underwent liver biopsy. Bifidobacteria and lactobacilli were analysed in children’s faecal samples, during a broader, 16S rRNA-based pyrosequencing analysis of the gut microbiome. Results: Three Bifidobacterium spp. (Bifidobacterium longum, Bifidobacterium bifidum, and Bifidobacterium adolescentis) and five Lactobacillus spp. (L. zeae, L. vaginalis, L. brevis, L. ruminis, and L. mucosae) frequently recurred in metagenomic analyses. Lactobacillus spp. increased in NAFL, NASH, or obese children compared to CTRLs. Particularly, L. mucosae was significantly higher in obese (p = 0.02426), NAFLD (p = 0.01313) and NASH (p = 0.01079) than in CTRLs. In contrast, Bifidobacterium spp. were more abundant in CTRLs, suggesting a protective and beneficial role of these microorganisms against the aforementioned diseases. Conclusions: Bifidobacteria seem to have a protective role against the development of NAFLD and obesity, highlighting their possible use in developing novel, targeted and effective probiotics

Accidental Nasal Myiasis Caused by Megaselia rufipes (Diptera: Phoridae) in a Child

A case of a nasal myiasis in a 3-yr-old Italian girl who was referred to Bambino Gesù Hospital in Rome, Italy, is reported. Larvae discharged with the nasal mucus were microscopically identified as Megaselia spp.; DNA barcoding analysis showed that they belonged to the 'scuttle fly' species Megaselia rufipes (Meigen). Based on the patient's history, she became infected when she played outside. This is the first report of myiasis in humans due to M. rufipes (Diptera: Phoridae)

Proteomics boosts translational and clinical microbiology

The application of proteomics to translational and clinical microbiology is one of the most advanced frontiers in the management and control of infectious diseases and in the understanding of complex microbial systems within human fluids and districts. This new approach aims at providing, by dedicated bioinformatic pipelines, a thorough description of pathogen proteomes and their interactions within the context of human host ecosystems, revolutionizing the vision of infectious diseases in biomedicine and approaching new viewpoints in both diagnostic and clinical management of the patient.Indeed, in the last few years, many laboratories have matured a series of advanced proteomic applications, aiming at providing individual proteome charts of pathogens, with respect to their morph and/or cell life stages, antimicrobial or antimycotic resistance profiling, epidemiological dispersion. Herein, we aim at reviewing the current state-of-the-art on proteomic protocols designed and set-up for translational and diagnostic microbiological purposes, from axenic pathogens' characterization to microbiota ecosystems' full description. The final goal is to describe applications of the most common MALDI-TOF MS platforms to advanced diagnostic issues related to emerging infections, increasing of fastidious bacteria, and generation of patient-tailored phylotypes. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. © 2013 The Authors

Cases of cryptosporidiosis co-infections in AIDS patients: a correlation between clinical presentation and GP60 subgenotype lineages from aged formalin-fixed stool samples

Nine cases of cryptosporidiosis co-infections in AIDS patients were clinically categorised into severe (patients 1, 3, 8 and 9), moderate (patients 4 and 5) and mild (patients 2, 6 and 7). Formalin-fixed faecal specimens from these patients were treated to obtain high quality DNA competent for amplification and sequencing of the 60-kDa glycoprotein (GP60) gene. Sequence analysis revealed that one patient was infected with Cryptosporidium hominis whereas the remaining eight patients were infected with C. parvum. Interestingly, the patients showing severe cryptosporidiosis harboured two subtypes within the C. parvum allelic family IIc (IIcA5G3 and IIcA5G3R2), whereas patients with moderate or mild infections showed various subtypes of the C. parvum allelic family IIa (IIaA14G2R1, IIaA15G2R1, IIaA17G3R1 and IIaA18G3R1)

Network analysis of gut microbiome and metabolome to discover microbiota-linked biomarkers in patients affected by non-small cell lung cancer

Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients

Network analysis of gut microbiome and metabolome to discover microbiota-linked biomarkers in patients affected by non-small cell lung cancer

Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients

Longitudinal Multi-Omics Study of a Mother-Infant Dyad from Breastfeeding to Weaning: An Individualized Approach to Understand the Interactions Among Diet, Fecal Metabolome and Microbiota Composition

The development of the human gut microbiota is characterized by a dynamic sequence of events from birth to adulthood, which make the gut microbiota unique for everyone. Its composition and metabolism may play a critical role in the intestinal homeostasis and health. We propose a study on a single mother-infant dyad to follow the dynamics of an infant fecal microbiota and metabolome changes in relation to breast milk composition during the lactation period and evaluate the changes induced by introduction of complementary food during the weaning period. Nuclear Magnetic Resonance (NMR)-based metabolomics was performed on breast milk and, together with 16S RNA targeted-metagenomics analysis, also on infant stool samples of a mother-infant dyad collected over a period running from the exclusive breastfeeding diet to weaning. Breast milk samples and neonatal stool samples were collected from the 4th to the 10th month of life. Both specimens were collected from day 103 to day 175, while from day 219–268 only stool samples were examined. An exploratory and a predictive analysis were carried out by means of Common component and specific weight analysis and multi-block partial least squares discriminant analysis, respectively. Stools collected during breastfeeding and during a mixed fruit/breastfeeding diet were characterized by high levels of fucosyl-oligosaccharides and glycolysis intermediates, including succinate and formate. The transition to a semi-solid food diet was characterized by several changes in fecal parameters: increase in short-chain fatty acids (SCFAs) levels, including acetate, propionate and butyrate, dissapearance of HMOs and the shift in the community composition, mainly occurring within the Firmicutes phylum. The variations in the fecal metabolome reflected the infant’s diet transition, while the composition of the microbiota followed a more complex and still unstable behavior