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During the last decade, the evidences on the relationship between neurodevelopmental disorders and the microbial communities of the intestinal tract have considerably grown. Particularly, the role of gut microbiota (GM) ecology and predicted functions in Autism Spectrum Disorders (ASD) has been especially investigated by 16S rRNA targeted and shotgun metagenomics, trying to assess disease signature and their correlation with cognitive impairment or gastrointestinal (GI) manifestations of the disease. Herein we present a metaproteomic approach to point out the microbial gene expression profiles, their functional annotations, and the taxonomic distribution of gut microbial communities in ASD children. We pursued a LC-MS/MS based investigation, to compare the GM profiles of patients with those of their respective relatives and aged-matched controls, providing a quantitative evaluation of bacterial metaproteins by SWATH analysis. All data were managed by a multiple step bioinformatic pipeline, including network analysis. In particular, comparing ASD subjects with CTRLs, up-regulation was found for some metaproteins associated with Clostridia and with carbohydrate metabolism (glyceraldehyde-3-phosphate and glutamate dehydrogenases), while down-regulation was observed for others associated with Bacteroidia (SusC and SusD family together with the TonB dependent receptor). Moreover, network analysis highlighted specific microbial correlations among ASD subgroups characterized by different functioning levels and GI symptoms. To the best of our knowledge, this study represents the first metaproteomic investigation on the gut microbiota of ASD children compared with relatives and age-matched CTRLs. Remarkably, the applied SWATH methodology allowed the attribution of differentially regulated functions to specific microbial taxa, offering a novel and complementary point of view with respect to previous studies. [Display omitted] • SWATH analysis supported the metaproteomic outcome when comparing ASD and controls. • The gut microbiota of controls differs from both that of ASD and their relatives. • The enhanced functions in the gut microbiota of ASD are ascribed to Clostridia. [ABSTRACT FROM AUTHOR]

Gingival Crevicular Fluid (GCF), a plasma-derived exudate present in the gingival crevice was collected from deciduous, exfoliating and permanent teeth from 20 children (60 samples) with the aim to characterize and quantify by a mass spectrometry based top-down proteomic approach, the peptide/proteins in the fluid and verify possible variations occurring during the exfoliating process. The results obtained confirmed the presence in GCF of α-Defensins 1–4, Thymosin β4 and Thymosin β10, as described in previous works and revealed the presence of other interesting peptides never described before in GCF such as specific fragments of α-1-antitrypsin, α-1-antichymotrypsin; fragments of Thymosin β4 and Thymosin β10; Fibrinopeptide A and its fragments and Fibrinopeptide B; S100A8 and S100A9, LVV Hemorphin-7 (hemoglobin chain β fragment), as well as some other peptides deriving from α and β subunits of hemoglobin. Statistical analysis evidenced different levels in 5 proteins/peptides in the three groups. Our study demonstrate that an in-depth analysis of a biological fluid like GCF, present in small amount, can provide useful information for the understanding of different biological processes like teeth eruption. Data are available via ProteomeXchange with identifier PXD016010 and PXD016049. GCF due to his site-specific nature has a great potential in containing factors that are specific for action at a given site and might have diagnostic value to detect qualitative and quantitative variations of proteins/peptides composition linked to physiological or pathological conditions. • GCF was collected from deciduous, exfoliating and permanent teeth from 20 children. • Peptide/proteins content was characterized by a Top-Down MS proteomic approach. • The data help to understand complex biological processes like teeth eruption. • Data are available via ProteomeXcharge with identifier PXD016010 and PXD016049. Unlabelled Image [ABSTRACT FROM AUTHOR]

Food allergy is the disease where the immune system is elicited by antigens in food. Although innocuous for immune-tolerant individuals, an ever-growing number of food allergenic people are being registered worldwide. To date, no treatment to cure food allergy is available and the disease management relies on the careful exclusion of the allergenic food from the diet of the allergic individuals. Great efforts are ongoing to clarify the allergenic mechanisms of the diverse allergenic proteins of food origin, aimed to both designing suitable therapies and for a timely and precise diagnosis of the allergic condition. Among the other omics sciences, mass spectrometry (MS)-based proteomics is gaining a steadily increasing interest by the whole scientific community acknowledged its high versatility. In the present work, the latest proteomics based-studies on allergenic proteins are reviewed to provide guidance on the different MS-based methodologies adopted in the research on food allergens. Our review points to highlight the strengths of the MS-based proteomics and how these have been exploited to address specific research questions. Also, the most common drawbacks encountered in a proteomic study are discussed, providing an overview that helps novel researchers in choosing the more suitable experimental workflow. Wide wealth of knowledge arising from the various MS-based proteomic investigations is improving our understanding of food allergy through molecular characterization of food allergens. The present work reviews the key aspects to be evaluated while investigating food allergens by means of MS-based proteomics and provide guidance to the novel research groups approaching to the fascinating world of MS-based food allergens detection. Unlabelled Image • Food allergy represents a steadily increasing public health threat. • MS-based proteomics enables deep characterization of food allergens. • MS-proteomics unequivocally identifies multiple allergens per run. • Harmonization between allergen quantitation methods is needed. • Exploring sensibility is the next challenge of MS-based food allergen analysis. [ABSTRACT FROM AUTHOR]

Breastfeeding is nowadays known to be one of the most critical factors contributing to the development of an efficient immune system. In the last decade, a consistent number of pieces of evidence demonstrated the relationship between a healthy organism and its gut microbiota. However, this link is still not fully understood and requires further investigation. We recently adopted a murine model to describe the impact of either maternal milk or parental genetic background, on the composition of the gut microbial population in the first weeks of life. A metaproteomic approach to such complex environments is a big challenge that requires a strong effort in both data production and analysis, including the set-up of dedicated multitasking bioinformatics pipelines. Herein we present an LC-MS/MS based investigation to monitor mouse gut microbiota in the early life, aiming at characterizing its functions and metabolic activities together with a taxonomic description in terms of operational taxonomic units. We provided a quantitative evaluation of bacterial metaproteins, taking into account differential expression results in relation to the functional and taxonomic classification, particularly with proteins from orthologues groups. This allowed the reduction of the bias arising from the presence of a high number of shared peptides, and proteins, among different bacterial species. We also focused on host mucosal proteome and its modulation, according to different microbiota composition. This paper would represent a reference work for investigations on gut microbiota in early life, from both a microbiological and a functional proteomic point of view. We focused on the shaping of the mouse gut microbiota in dependence on the feeding modality, defining a reliable taxonomic description, highlighting some functional characteristics of the microbial community, and performing a first quantitative evaluation by data independent analysis in metaproteomics. Unlabelled Image • Lack of IgA in breast milk favors Escherichia predominance. • Gut microbiota shaping is not driven by breastfeeding only. • The two cross-feeding conditions led to more similar gut microbial populations. • An altered microbiota composition could reflect in different host mucosal proteomes. [ABSTRACT FROM AUTHOR]