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

The role of the two splice variants and extranuclear pathway on Ki-67 regulation in non-cancer and cancer cells

Ki-67 is a nuclear protein that has been used in cancer diagnostic because of its specific cell-cycle dependent expression profile. After quantifying and characterising the expression level of Ki-67, as a function of the cell cycle, we found out that the two main splice variants of the protein (i.e. α and β) are differently regulated in non-cancerous and cancerous cells both at mRNA and protein level. We were able to correlate the presence of the α variant of the protein with the progression through the interphase of cell cycle. We also observed that the different expression profiles correspond to different degradation pathways for non-cancerous and cancerous cells. Furthermore, Ki-67 is continuously regulated and degraded via proteasome system in both cell types, suggesting an active control of the protein. However we also observed a putative extranuclear elimination pathway of Ki-67 where it is transported to the Golgi apparatus. Our evidence in the different expression of the splice variants may represent a milestone for the development of new targets for cancer diagnostic and prognostic. Additionally, the unexpected extranuclear elimination of Ki-67 strongly suggests that this protein must be looked at also outside of the "nuclear box", as thought to date

The pediatric gut bacteriome and virome in response to SARS-CoV-2 infection

Introduction since the beginning of the SARS-CoV-2 pandemic in early 2020, it has been apparent that children were partially protected from both infection and the more severe forms of the disease. many different mechanisms have been proposed to explain this phenomenon, including children's frequent exposure to other upper respiratory infections and vaccines, and which inflammatory cytokines they are more likely to produce in response to infection. furthermore, given the presence of SARS-CoV-2 in the intestine and its ability to infect enterocytes, combined with the well described immunomodulatory capabilities of the microbiome, another potential contributing factor may be the presence of certain protective microbial members of the gut microbiota (GM). methods we performed shotgun metagenomic sequencing and profiled both the bacteriome and virome of the GM of pediatric SARS-CoV-2 patients compared to healthy, age-matched subjects. results we found that, while pediatric patients do share some pro-inflammatory microbial signatures with adult patients, they also possess a distinct microbial signature of protective bacteria previously found to be negatively correlated with SARS-CoV-2 infectivity and COVID-19 severity. COVID-19 was also associated with higher fecal cytomegalovirus load, and with shifts in the relative abundances of bacteriophages in the GM. furthermore, we address how the preventative treatment of COVID-19 patients with antibiotics, a common practice especially in the early days of the pandemic, affected the bacteriome and virome, as well as the abundances of antimicrobial resistance and virulence genes in these patients. discussion to our knowledge, this is the first study to address the bacteriome, virome, and resistome of pediatric patients in response to COVID-19 and to preventative antibiotics use

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

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

The metaproteome of the gut microbiota in pediatric patients affected by COVID-19

IntroductionThe gut microbiota (GM) play a significant role in the infectivity and severity of COVID-19 infection. However, the available literature primarily focuses on adult patients and it is known that the microbiota undergoes changes throughout the lifespan, with significant alterations occurring during infancy and subsequently stabilizing during adulthood. Moreover, children have exhibited milder symptoms of COVID-19 disease, which has been associated with the abundance of certain protective bacteria. Here, we examine the metaproteome of pediatric patients to uncover the biological mechanisms that underlie this protective effect of the GM.MethodsWe performed nanoliquid chromatography coupled with tandem mass spectrometry on a high resolution analytical platform, resulting in label free quantification of bacterial protein groups (PGs), along with functional annotations via COG and KEGG databases by MetaLab-MAG. Additionally, taxonomic assignment was possible through the use of the lowest common ancestor algorithm provided by Unipept software.ResultsA COVID-19 GM functional dissimilarity respect to healthy subjects was identified by univariate analysis. The alteration in COVID-19 GM function is primarily based on bacterial pathways that predominantly involve metabolic processes, such as those related to tryptophan, butanoate, fatty acid, and bile acid biosynthesis, as well as antibiotic resistance and virulence.DiscussionThese findings highlight the mechanisms by which the pediatric GM could contribute to protection against the more severe manifestations of the disease in children. Uncovering these mechanisms can, therefore, have important implications in the discovery of novel adjuvant therapies for severe COVID-19

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

Exploring nasopharyngeal microbiota profile in children affected by SARS-CoV-2 infection

The relationship between COVID-19 and nasopharyngeal (NP) microbiota has been investigated mainly in the adult population. We explored the NP profile of children affected by COVID-19, compared to healthy controls (CTRLs). NP swabs of children with COVID-19, collected between March and September 2020, were investigated at the admission (T-0), 72 h to 7 days (T-1), and at the discharge (T-2) of the patients. NP microbiota was analyzed by 16S rRNA targeted-metagenomics. Data from sequencing were investigated by QIIME 2.0 and PICRUSt 2. Multiple machine learning (ML) models were exploited to classify patients compared to CTRLs. The NP microbiota of COVID-19 patients (N = 71) was characterized by reduction of alpha-diversity compared to CTRLs (N = 59). The NP microbiota of COVID-19 cohort appeared significantly enriched in Streptococcus, Haemophilus, Staphylococcus, Veillonella, Enterococcus, Neisseria, Moraxella, Enterobacteriaceae, Gemella, Bacillus, and reduced in Faecalibacterium, Akkermansia, Blautia, Bifidobacterium, Ruminococcus, and Bacteroides, compared to CTRLs (FDR < 0.001). Exploiting ML models, Enterococcus, Pseudomonas, Streptococcus, Capnocytopagha, Tepidiphilus, Porphyromonas, Staphylococcus, and Veillonella resulted as NP microbiota biomarkers, in COVID-19 patients. No statistically significant differences were found comparing the NP microbiota profile of COVID-19 patients during the time-points or grouping patients on the basis of high, medium, and low viral load (VL). This evidence provides specific pathobiont signatures of the NP microbiota in pediatric COVID-19 patients, and the reduction of anaerobic protective commensals. Our data suggest that the NP microbiota may have a specific disease-related signature since infection onset without changes during disease progression, regardless of the SARS-CoV-2 VL. IMPORTANCE Since the beginning of pandemic, we know that children are less susceptible to severe COVID-19 disease. A potential role of the nasopharyngeal (NP) microbiota has been hypothesized but to date, most of the studies have been focused on adults. We studied the NP microbiota modifications in children affected by SARS-CoV-2 infection showing a specific NP microbiome profile, mainly composed by pathobionts and almost missing protective anaerobic commensals. Moreover, in our study, specific microbial signatures appear since the first days of infection independently from SARS-CoV-2 viral load