A metaproteomic-based gut microbiota profiling in children affected by autism spectrum disorders

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification, and prioritization of microbial proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant [to generate peptide-spectral matches (PSMs) and quantification], PepQuery2 (to verify the quality of PSMs), Unipept (for taxonomic and functional annotation), and MSstatsTMT (for statistical analysis). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

IMPORTANCE

Clinical metaproteomics has immense potential to offer functional insights into the microbiome and its contributions to human disease. However, there are numerous challenges in the metaproteomic analysis of clinical samples, including handling of very large protein sequence databases for sensitive and accurate peptide and protein identification from mass spectrometry data, as well as taxonomic and functional annotation of quantified peptides and proteins to enable interpretation of results. To address these challenges, we have developed a novel clinical metaproteomics workflow that provides customized bioinformatic identification, verification, quantification, and taxonomic and functional annotation. This bioinformatic workflow is implemented in the Galaxy ecosystem and has been used to characterize diverse clinical sample types, such as nasopharyngeal swabs and bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness and availability for use by the research community via analysis of residual fluid from cervical swabs.

Associations between autistic and comorbid somatic problems of gastrointestinal disorders, food allergy, pain, and fatigue in adults

LAY ABSTRACT

What is already known about the topic?Autistic children frequently often have accompanying physical health problems. However, this has been much less studied in autistic men and women during adulthood.What does this article add?This is one of the first studies to investigate the associations between autistic and somatic problems in adults from the general population. Using a continuous measure of autistic symptom scores and a categorical definition of autism (referred to below as probable autism) which considered symptom severity, childhood age of onset, and functional impairment, we found that autistic problems and irritable bowel syndrome, food allergy, pain, and fatigue were associated in adults. Sex differences were present for pain and fatigue, for which the associations with autistic symptom scores were somewhat stronger in females than males. Regarding age differences, the associations with fatigue and having food allergy were more pronounced in younger adults. Conversely, older individuals had a higher risk of developing irritable bowel syndrome or experiencing pain if they met the criteria for probable autism.Implications for practice, research, or policyThere is a need for providing routine programs of screening, assessment, and treatment of autism-related somatic problems and developing evidence-based interventions for autistic individuals. These could be tailored to the needs of specific autistic populations. For example, autistic females could be given extra attention about the potential presence of pain and fatigue, younger adults about the potential presence of food allergy and fatigue, and older adults concerning the potential presence of irritable bowel syndrome and pain.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, which are usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification and prioritization of microbial and host proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant (to generate peptide-spectral matches (PSMs) and quantification), PepQuery2 (to verify the quality of PSMs), and Unipept and MSstatsTMT (for taxonomy and functional annotation). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

From-Toilet-to-Freezer: A Review on Requirements for an Automatic Protocol to Collect and Store Human Fecal Samples for Research Purposes

The composition, viability and metabolic functionality of intestinal microbiota play an important role in human health and disease. Studies on intestinal microbiota are often based on fecal samples, because these can be sampled in a non-invasive way, although procedures for sampling, processing and storage vary. This review presents factors to consider when developing an automated protocol for sampling, processing and storing fecal samples: donor inclusion criteria, urine-feces separation in smart toilets, homogenization, aliquoting, usage or type of buffer to dissolve and store fecal material, temperature and time for processing and storage and quality control. The lack of standardization and low-throughput of state-of-the-art fecal collection procedures promote a more automated protocol. Based on this review, an automated protocol is proposed. Fecal samples should be collected and immediately processed under anaerobic conditions at either room temperature (RT) for a maximum of 4 h or at 4 °C for no more than 24 h. Upon homogenization, preferably in the absence of added solvent to allow addition of a buffer of choice at a later stage, aliquots obtained should be stored at either -20 °C for up to a few months or -80 °C for a longer period-up to 2 years. Protocols for quality control should characterize microbial composition and viability as well as metabolic functionality.

Impact of helminth-microbiome interactions on childhood health and development-A clinical perspective

Humans have co-existed with parasites for virtually the entirety of our existence as a species. Today, nearly one third of the human population is infected with at least one helminthic species, most of which reside in the intestinal tract, where they have co-evolved alongside the human gut microbiota (GM). Appreciation for the interconnected relationship between helminths and GM has increased in recent years. Here, we review the evidence of how helminths and GM can influence various aspects of childhood development and the onset of paediatric diseases. We discuss the emerging evidence of how many of the changes that parasitic worms inflict on their host is enacted through gut microbes. In this light, we argue that helminth-induced microbiota modifications are of great importance in both facing the global challenge of overcoming parasitic infections, and in replicating helminthic protective effects against inflammatory diseases. We propose that deepening our knowledge of helminth-microbiota interactions will uncover novel, safer and more effective therapeutic strategies in combatting an array of childhood disorders.

Xylan Prebiotics and the Gut Microbiome Promote Health and Wellbeing: Potential Novel Roles for Pentosan Polysulfate

This narrative review highlights the complexities of the gut microbiome and health-promoting properties of prebiotic xylans metabolized by the gut microbiome. In animal husbandry, prebiotic xylans aid in the maintenance of a healthy gut microbiome. This prevents the colonization of the gut by pathogenic organisms obviating the need for dietary antibiotic supplementation, a practice which has been used to maintain animal productivity but which has led to the emergence of antibiotic resistant bacteria that are passed up the food chain to humans. Seaweed xylan-based animal foodstuffs have been developed to eliminate ruminant green-house gas emissions by gut methanogens in ruminant animals, contributing to atmospheric pollution. Biotransformation of pentosan polysulfate by the gut microbiome converts this semi-synthetic sulfated disease-modifying anti-osteoarthritic heparinoid drug to a prebiotic metabolite that promotes gut health, further extending the therapeutic profile and utility of this therapeutic molecule. Xylans are prominent dietary cereal components of the human diet which travel through the gastrointestinal tract as non-digested dietary fibre since the human genome does not contain xylanolytic enzymes. The gut microbiota however digest xylans as a food source. Xylo-oligosaccharides generated in this digestive process have prebiotic health-promoting properties. Engineered commensal probiotic bacteria also have been developed which have been engineered to produce growth factors and other bioactive factors. A xylan protein induction system controls the secretion of these compounds by the commensal bacteria which can promote gut health or, if these prebiotic compounds are transported by the vagal nervous system, may also regulate the health of linked organ systems via the gut–brain, gut–lung and gut–stomach axes. Dietary xylans are thus emerging therapeutic compounds warranting further study in novel disease prevention protocols.

Machine Learning Data Analysis Highlights the Role of Parasutterella and Alloprevotella in Autism Spectrum Disorders

In recent years, the involvement of the gut microbiota in disease and health has been investigated by sequencing the 16S gene from fecal samples. Dysbiotic gut microbiota was also observed in Autism Spectrum Disorder (ASD), a neurodevelopmental disorder characterized by gastrointestinal symptoms. However, despite the relevant number of studies, it is still difficult to identify a typical dysbiotic profile in ASD patients. The discrepancies among these studies are due to technical factors (i.e., experimental procedures) and external parameters (i.e., dietary habits). In this paper, we collected 959 samples from eight available projects (540 ASD and 419 Healthy Controls, HC) and reduced the observed bias among studies. Then, we applied a Machine Learning (ML) approach to create a predictor able to discriminate between ASD and HC. We tested and optimized three algorithms: Random Forest, Support Vector Machine and Gradient Boosting Machine. All three algorithms confirmed the importance of five different genera, including Parasutterella and Alloprevotella. Furthermore, our results show that ML algorithms could identify common taxonomic features by comparing datasets obtained from countries characterized by latent confounding variables.

Signalling pathways in autism spectrum disorder: mechanisms and therapeutic implications

Autism spectrum disorder (ASD) is a prevalent and complex neurodevelopmental disorder which has strong genetic basis. Despite the rapidly rising incidence of autism, little is known about its aetiology, risk factors, and disease progression. There are currently neither validated biomarkers for diagnostic screening nor specific medication for autism. Over the last two decades, there have been remarkable advances in genetics, with hundreds of genes identified and validated as being associated with a high risk for autism. The convergence of neuroscience methods is becoming more widely recognized for its significance in elucidating the pathological mechanisms of autism. Efforts have been devoted to exploring the behavioural functions, key pathological mechanisms and potential treatments of autism. Here, as we highlight in this review, emerging evidence shows that signal transduction molecular events are involved in pathological processes such as transcription, translation, synaptic transmission, epigenetics and immunoinflammatory responses. This involvement has important implications for the discovery of precise molecular targets for autism. Moreover, we review recent insights into the mechanisms and clinical implications of signal transduction in autism from molecular, cellular, neural circuit, and neurobehavioural aspects. Finally, the challenges and future perspectives are discussed with regard to novel strategies predicated on the biological features of autism.

Gut Microbiota Ecology and Inferred Functions in Children With ASD Compared to Neurotypical Subjects

Autism spectrum disorders (ASDs) is a multifactorial neurodevelopmental disorder. The communication between the gastrointestinal (GI) tract and the central nervous system seems driven by gut microbiota (GM). Herein, we provide GM profiling, considering GI functional symptoms, neurological impairment, and dietary habits. Forty-one and 35 fecal samples collected from ASD and neurotypical children (CTRLs), respectively, (age range, 3–15 years) were analyzed by 16S targeted-metagenomics (the V3–V4 region) and inflammation and permeability markers (i.e., sIgA, zonulin lysozyme), and then correlated with subjects’ metadata. Our ASD cohort was characterized as follows: 30/41 (73%) with GI functional symptoms; 24/41 (58%) picky eaters (PEs), with one or more dietary needs, including 10/41 (24%) with food selectivity (FS); 36/41 (88%) presenting high and medium autism severity symptoms (HMASSs). Among the cohort with GI symptoms, 28/30 (93%) showed HMASSs, 17/30 (57%) were picky eaters and only 8/30 (27%) with food selectivity. The remaining 11/41 (27%) ASDs without GI symptoms that were characterized by HMASS for 8/11 (72%) and 7/11 (63%) were picky eaters. GM ecology was investigated for the overall ASD cohort versus CTRLs; ASDs with GI and without GI, respectively, versus CTRLs; ASD with GI versus ASD without GI; ASDs with HMASS versus low ASSs; PEs versus no-PEs; and FS versus absence of FS. In particular, the GM of ASDs, compared to CTRLs, was characterized by the increase of Proteobacteria, Bacteroidetes, Rikenellaceae, Pasteurellaceae, Klebsiella, Bacteroides, Roseburia, Lactobacillus, Prevotella, Sutterella, Staphylococcus, and Haemophilus. Moreover, Sutterella, Roseburia and Fusobacterium were associated to ASD with GI symptoms compared to CTRLs. Interestingly, ASD with GI symptoms showed higher value of zonulin and lower levels of lysozyme, which were also characterized by differentially expressed predicted functional pathways. Multiple machine learning models classified correctly 80% overall ASDs, compared with CTRLs, based on Bacteroides, Lactobacillus, Prevotella, Staphylococcus, Sutterella, and Haemophilus features. In conclusion, in our patient cohort, regardless of the evaluation of many factors potentially modulating the GM profile, the major phenotypic determinant affecting the GM was represented by GI hallmarks and patients’ age.

Role of the gut microbiome in multiple sclerosis: From etiology to therapeutics

Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS that affects around one million people in the United States. Predisposition or protection from this disease is linked with both genetic and environmental factors. In recent years, gut microbiome has emerged as an important environmental factor in the pathobiology of MS. The gut microbiome supports various physiologic functions, including the development and maintenance of the host immune system, the perturbation of which is known as dysbiosis and has been linked with multiple diseases including MS. We and others have shown that people with MS (PwMS) have gut dysbiosis that is characterized by specific gut bacteria being enriched or depleted. Consequently, there is an emphasis on determining the mechanism(s) through which gut bacteria and/or their metabolites alter the course of MS through their ability to provide protection, predispose individuals, or promote disease progression. Improving our understanding of these mechanisms will allow us to harness the enormous potential of the gut microbiome as a diagnostic and/or therapeutic agent. In this chapter, we will discuss current advances in microbiome research in the context of MS, including a review of specific bacteria that are currently linked with this disease, potential mechanisms of disease pathogenesis, and the utility of microbiome-based therapy for PwMS.

An overview of technologies for MS-based proteomics-centric multi-omics

INTRODUCTION

Mass spectrometry-based proteomics reveals dynamic molecular signatures underlying phenotypes reflecting normal and perturbed conditions in living systems. Although valuable on its own, the proteome has only one level of moleclar information, with the genome, epigenome, transcriptome, and metabolome, all providing complementary information. Multi-omic analysis integrating information from one or more of these other domains with proteomic information provides a more complete picture of molecular contributors to dynamic biological systems.

AREAS COVERED

Here, we discuss the improvements to mass spectrometry-based technologies, focused on peptide-based, bottom-up approaches that have enabled deep, quantitative characterization of complex proteomes. These advances are facilitating the integration of proteomics data with other 'omic information, providing a more complete picture of living systems. We also describe the current state of bioinformatics software and approaches for integrating proteomics and other 'omics data, critical for enabling new discoveries driven by multi-omics.

EXPERT COMMENTARY

Multi-omics, centered on the integration of proteomics information with other 'omic information, has tremendous promise for biological and biomedical studies. Continued advances in approaches for generating deep, reliable proteomic data and bioinformatics tools aimed at integrating data across 'omic domains will ensure the discoveries offered by these multi-omic studies continue to increase.

The Brain-Gut-Microbiome System: Pathways and Implications for Autism Spectrum Disorder

Gastrointestinal dysfunction is one of the most prevalent physiological symptoms of autism spectrum disorder (ASD). A growing body of largely preclinical research suggests that dysbiotic gut microbiota may modulate brain function and social behavior, yet little is known about the mechanisms that underlie these relationships and how they may influence the pathogenesis or severity of ASD. While various genetic and environmental risk factors have been implicated in ASD, this review aims to provide an overview of studies elucidating the mechanisms by which gut microbiota, associated metabolites, and the brain interact to influence behavior and ASD development, in at least a subgroup of individuals with gastrointestinal problems. Specifically, we review the brain-gut-microbiome system and discuss findings from current animal and human studies as they relate to social-behavioral and neurological impairments in ASD, microbiota-targeted therapies (i.e., probiotics, fecal microbiota transplantation) in ASD, and how microbiota may influence the brain at molecular, structural, and functional levels, with a particular interest in social and emotion-related brain networks. A deeper understanding of microbiome-brain-behavior interactions has the potential to inform new therapies aimed at modulating this system and alleviating both behavioral and physiological symptomatology in individuals with ASD.

Clinical Parasitology and Parasitome Maps as Old and New Tools to Improve Clinical Microbiomics

A growing body of evidence shows that dysbiotic gut microbiota may correlate with a wide range of disorders; hence, the clinical use of microbiota maps and fecal microbiota transplantation (FMT) can be exploited in the clinic of some infectious diseases. Through direct or indirect ecological and functional competition, FMT may stimulate decolonization of pathogens or opportunistic pathogens, modulating immune response and colonic inflammation, and restoring intestinal homeostasis, which reduces host damage. Herein, we discuss how diagnostic parasitology may contribute to designing clinical metagenomic pipelines and FMT programs, especially in pediatric subjects. The consequences of more specialized diagnostics in the context of gut microbiota communities may improve the clinical parasitology and extend its applications to the prevention and treatment of several communicable and even noncommunicable disorders.