Gut microbiome is not associated with mild cognitive impairment in Parkinson's disease.

Gut microbiome differences between people with Parkinson's disease (PD) and control subjects without Parkinsonism are widely reported, but potential alterations related to PD with mild cognitive impairment (MCI) have yet to be comprehensively explored. We compared gut microbial features of PD with MCI (n = 58) to cognitively unimpaired PD (n = 60) and control subjects (n = 90) with normal cognition. Our results did not support a specific microbiome signature related to MCI in PD.

Functional prediction of proteins from the human gut archaeome.

The human gastrointestinal tract contains diverse microbial communities, including archaea. Among them, Methanobrevibacter smithii represents a highly active and clinically relevant methanogenic archaeon, being involved in gastrointestinal disorders, such as inflammatory bowel disease and obesity. Herein, we present an integrated approach using sequence and structure information to improve the annotation of M. smithii proteins using advanced protein structure prediction and annotation tools, such as AlphaFold2, trRosetta, ProFunc, and DeepFri. Of an initial set of 873 481 archaeal proteins, we found 707 754 proteins exclusively present in the human gut. Having analysed archaeal proteins together with 87 282 994 bacterial proteins, we identified unique archaeal proteins and archaeal-bacterial homologs. We then predicted and characterized functional domains and structures of 73 unique and homologous archaeal protein clusters linked the human gut and M. smithii. We refined annotations based on the predicted structures, extending existing sequence similarity-based annotations. We identified gut-specific archaeal proteins that may be involved in defense mechanisms, virulence, adhesion, and the degradation of toxic substances. Interestingly, we identified potential glycosyltransferases that could be associated with N-linked and O-glycosylation. Additionally, we found preliminary evidence for interdomain horizontal gene transfer between Clostridia species and M. smithii, which includes sporulation Stage V proteins AE and AD. Our study broadens the understanding of archaeal biology, particularly M. smithii, and highlights the importance of considering both sequence and structure for the prediction of protein function.

From animal models to gut-on-chip: the challenging journey to capture inter-individual variability in chronic digestive disorders.

Chronic digestive disorders are of increasing incidence worldwide with expensive treatments and no available cure. Available therapeutic schemes mainly rely on symptom relief, with large degrees of variability in patients' response to such treatments, underlining the need for new therapeutic strategies. There are strong indications that the gut microbiota's contribution seems to be a key modulator of disease activity and patients' treatment responses. Hence, efforts have been devoted to understanding host-microbe interactions and the mechanisms underpinning such variability. Animal models, being the gold standard, provide valuable mechanistic insights into host-microbe interactions. However, they are not exempt from limitations prompting the development of alternative methods. Emerging microfluidic technologies and gut-on-chip models were shown to mirror the main features of gut physiology and disease state, reflect microbiota modification, and include functional readouts for studying host responses. In this commentary, we discuss the relevance of animal models in understanding host-microbe interactions and how gut-on-chip technology holds promises for addressing patient variability in responses to chronic digestive disease treatment.

Dispersion of antimicrobial resistant bacteria in pig farms and in the surrounding environment.

BACKGROUND: Antimicrobial resistance has been identified as a major threat to global health. The pig food chain is considered an important source of antimicrobial resistance genes (ARGs). However, there is still a lack of knowledge on the dispersion of ARGs in pig production system, including the external environment. RESULTS: In the present study, we longitudinally followed one swine farm located in Italy from the weaning phase to the slaughterhouse to comprehensively assess the diversity of ARGs, their diffusion, and the bacteria associated with them. We obtained shotgun metagenomic sequences from 294 samples, including pig feces, farm environment, soil around the farm, wastewater, and slaughterhouse environment. We identified a total of 530 species-level genome bins (SGBs), which allowed us to assess the dispersion of microorganisms and their associated ARGs in the farm system. We identified 309 SGBs being shared between the animals gut microbiome, the internal and external farm environments. Specifically, these SGBs were characterized by a diverse and complex resistome, with ARGs active against 18 different classes of antibiotic compounds, well matching antibiotic use in the pig food chain in Europe. CONCLUSIONS: Collectively, our results highlight the urgency to implement more effective countermeasures to limit the dispersion of ARGs in the pig food systems and the relevance of metagenomics-based approaches to monitor the spread of ARGs for the safety of the farm working environment and the surrounding ecosystems.

An Organ-on-Chip Platform for Simulating Drug Metabolism Along the Gut-Liver Axis.

The human microbiome significantly influences drug metabolism through the gut-liver axis, leading to modified drug responses and potential toxicity. Due to the complex nature of the human gut environment, the understanding of microbiome-driven impacts on these processes is limited. To address this, a multiorgan-on-a-chip (MOoC) platform that combines the human microbial-crosstalk (HuMiX) gut-on-chip (GoC) and the Dynamic42 liver-on-chip (LoC), mimicking the bidirectional interconnection between the gut and liver known as the gut-liver axis, is introduced. This platform supports the viability and functionality of intestinal and liver cells. In a proof-of-concept study, the metabolism of irinotecan, a widely used colorectal cancer drug, is imitated within the MOoC. Utilizing liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), irinotecan metabolites are tracked, confirming the platform's ability to represent drug metabolism along the gut-liver axis. Further, using the authors' gut-liver platform, it is shown that the colorectal cancer-associated gut bacterium, Escherichia coli, modifies irinotecan metabolism through the transformation of its inactive metabolite SN-38G into its toxic metabolite SN-38. This platform serves as a robust tool for investigating the intricate interplay between gut microbes and pharmaceuticals, offering a representative alternative to animal models and providing novel drug development strategies.

Integration of multiple flexible electrodes for real-time detection of barrier formation with spatial resolution in a gut-on-chip system.

In healthy individuals, the intestinal epithelium forms a tight barrier to prevent gut bacteria from reaching blood circulation. To study the effect of probiotics, dietary compounds and drugs on gut barrier formation and disruption, human gut epithelial and bacterial cells can be cocultured in an in vitro model called the human microbial crosstalk (HuMiX) gut-on-a-chip system. Here, we present the design, fabrication and integration of thin-film electrodes into the HuMiX platform to measure transepithelial electrical resistance (TEER) as a direct readout on barrier tightness in real-time. As various aspects of the HuMiX platform have already been set in their design, such as multiple compressible layers, uneven surfaces and nontransparent materials, a novel fabrication method was developed whereby thin-film metal electrodes were first deposited on flexible substrates and sequentially integrated with the HuMiX system via a transfer-tape approach. Moreover, to measure localized TEER along the cell culture chamber, we integrated multiple electrodes that were connected to an impedance analyzer via a multiplexer. We further developed a dynamic normalization method because the active measurement area depends on the measured TEER levels. The fabrication process and system setup can be applicable to other barrier-on-chip systems. As a proof-of-concept, we measured the barrier formation of a cancerous Caco-2 cell line in real-time, which was mapped at four spatially separated positions along the HuMiX culture area.

Forecasting the dynamics of a complex microbial community using integrated meta-omics.

Predicting the behaviour of complex microbial communities is challenging. However, this is essential for complex biotechnological processes such as those in biological wastewater treatment plants (BWWTPs), which require sustainable operation. Here we summarize 14 months of longitudinal meta-omics data from a BWWTP anaerobic tank into 17 temporal signals, explaining 91.1% of the temporal variance, and link those signals to ecological events within the community. We forecast the signals over the subsequent five years and use 21 extra samples collected at defined time intervals for testing and validation. Our forecasts are correct for six signals and hint on phenomena such as predation cycles. Using all the 17 forecasts and the environmental variables, we predict gene abundance and expression, with a coefficient of determination ≥0.87 for the subsequent three years. Our study demonstrates the ability to forecast the dynamics of open microbial ecosystems using interactions between community cycles and environmental parameters.

Routes of dispersion of antibiotic resistance genes from the poultry farm system.

Poultry farms are hotspots for the development and spread of antibiotic resistance genes (ARGs), due to high stocking densities and extensive use of antibiotics, posing a threat of spread and contagion to workers and the external environment. Here, we applied shotgun metagenome sequencing to characterize the gut microbiome and resistome of poultry, workers and their households - also including microbiomes from the internal and external farm environment - in three different farms in Italy during a complete rearing cycle. Our results highlighted a relevant overlap among the microbiomes of poultry, workers, and their families (gut and skin), with clinically relevant ARGs and associated mobile elements shared in both poultry and human samples. On a finer scale, the reconstruction of species-level genome bins (SGBs) allowed us to delineate the dynamics of microorganism and ARGs dispersion from farm systems. We found the associations with worker microbiomes representing the main route of ARGs dispersion from poultry to human populations. Collectively, our findings clearly demonstrate the urgent need to implement more effective procedures to counteract ARGs dispersion from poultry food systems and the relevance of metagenomics-based metacommunity approaches to monitor the ARGs dispersion process for the safety of the working environment on farms.

A toolbox of machine learning software to support microbiome analysis.

The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learning (ML) algorithms can process vast amounts of data to uncover informative patterns and relationships within the data, even with limited prior knowledge. Therefore, there has been a rapid growth in the development of software specifically designed for the analysis and interpretation of microbiome data using ML techniques. These software incorporate a wide range of ML algorithms for clustering, classification, regression, or feature selection, to identify microbial patterns and relationships within the data and generate predictive models. This rapid development with a constant need for new developments and integration of new features require efforts into compile, catalog and classify these tools to create infrastructures and services with easy, transparent, and trustable standards. Here we review the state-of-the-art for ML tools applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on ML based software and framework resources currently available for the analysis of microbiome data in humans. The aim is to support microbiologists and biomedical scientists to go deeper into specialized resources that integrate ML techniques and facilitate future benchmarking to create standards for the analysis of microbiome data. The software resources are organized based on the type of analysis they were developed for and the ML techniques they implement. A description of each software with examples of usage is provided including comments about pitfalls and lacks in the usage of software based on ML methods in relation to microbiome data that need to be considered by developers and users. This review represents an extensive compilation to date, offering valuable insights and guidance for researchers interested in leveraging ML approaches for microbiome analysis.

Validation of a SARS-CoV-2 Surrogate Neutralization Test Detecting Neutralizing Antibodies against the Major Variants of Concern.

SARS-CoV-2 infection and/or vaccination elicit a broad range of neutralizing antibody responses against the different variants of concern (VOC). We established a new variant-adapted surrogate virus neutralization test (sVNT) and assessed the neutralization activity against the ancestral B.1 (WT) and VOC Delta, Omicron BA.1, BA.2, and BA.5. Analytical performances were compared against the respective VOC to the reference virus neutralization test (VNT) and two CE-IVD labeled kits using three different cohorts collected during the COVID-19 waves. Correlation analyses showed moderate to strong correlation for Omicron sub-variants (Spearman's r = 0.7081 for BA.1, r = 0.7205 for BA.2, and r = 0.6042 for BA.5), and for WT (r = 0.8458) and Delta-sVNT (r = 0.8158), respectively. Comparison of the WT-sVNT performance with two CE-IVD kits, the "Icosagen SARS-CoV-2 Neutralizing Antibody ELISA kit" and the "Genscript cPass, kit" revealed an overall good correlation ranging from 0.8673 to -0.8773 and a midway profile between both commercial kits with 87.76% sensitivity and 90.48% clinical specificity. The BA.2-sVNT performance was similar to the BA.2 Genscript test. Finally, a correlation analysis revealed a strong association (r = 0.8583) between BA.5-sVNT and VNT sVNT using a double-vaccinated cohort (n = 100) and an Omicron-breakthrough infection cohort (n = 91). In conclusion, the sVNT allows for the efficient prediction of immune protection against the various VOCs.

Fiber deprivation and microbiome-borne curli shift gut bacterial populations and accelerate disease in a mouse model of Parkinson's disease.

Parkinson's disease (PD) is a neurological disorder characterized by motor dysfunction, dopaminergic neuron loss, and alpha-synuclein (αSyn) inclusions. Many PD risk factors are known, but those affecting disease progression are not. Lifestyle and microbial dysbiosis are candidates in this context. Diet-driven gut dysbiosis and reduced barrier function may increase exposure of enteric neurons to toxins. Here, we study whether fiber deprivation and exposure to bacterial curli, a protein cross-seeding with αSyn, individually or together, exacerbate disease in the enteric and central nervous systems of a transgenic PD mouse model. We analyze the gut microbiome, motor behavior, and gastrointestinal and brain pathologies. We find that diet and bacterial curli alter the microbiome and exacerbate motor performance, as well as intestinal and brain pathologies, but to different extents. Our results shed important insights on how diet and microbiome-borne insults modulate PD progression via the gut-brain axis and have implications for lifestyle management of PD.

Protocol for a multicentre cross-sectional, longitudinal ambulatory clinical trial in rheumatoid arthritis and Parkinson's disease patients analysing the relation between the gut microbiome, fasting and immune status in Germany (ExpoBiome).

INTRODUCTION: Chronic inflammatory diseases like rheumatoid arthritis (RA) and neurodegenerative disorders like Parkinson's disease (PD) have recently been associated with a decreased diversity in the gut microbiome, emerging as key driver of various diseases. The specific interactions between gut-borne microorganisms and host pathophysiology remain largely unclear. The microbiome can be modulated by interventions comprising nutrition.The aim of our clinical study is to (1) examine effects of prolonged fasting (PF) and time-restricted eating (TRE) on the outcome parameters and the immunophenotypes of RA and PD with (2) special consideration of microbial taxa and molecules associated with changes expected in (1), and (3) identify factors impacting the disease course and treatment by in-depth screening of microorganisms and molecules in personalised HuMiX gut-on-chip models, to identify novel targets for anti-inflammatory therapy. METHODS AND ANALYSIS: This trial is an open-label, multicentre, controlled clinical trial consisting of a cross-sectional and a longitudinal study. A total of 180 patients is recruited. For the cross-sectional study, 60 patients with PD, 60 patients with RA and 60 healthy controls are recruited at two different, specialised clinical sites. For the longitudinal part, 30 patients with PD and 30 patients with RA undergo 5-7 days of PF followed by TRE (16:8) for a period of 12 months. One baseline visit takes place before the PF intervention and 10 follow-up visits will follow over a period of 12 months (April 2021 to November 2023). ETHICS AND DISSEMINATION: Ethical approval was obtained to plan and conduct the trial from the institutional review board of the Charité-Universitätsmedizin Berlin (EA1/204/19), the ethics committee of the state medical association (Landesärztekammer) of Hessen (2021-2230-zvBO) and the Ethics Review Panel (ERP) of the University of Luxembourg (ERP 21-001 A ExpoBiome). The results of this study will be disseminated through peer-reviewed publications, scientific presentations and social media. TRIAL REGISTRATION NUMBER: NCT04847011.

A Gut-on-a-Chip Model to Study the Gut Microbiome-Nervous System Axis.

The human body is colonized by at least the same number of microbial cells as it is composed of human cells, and most of these microorganisms are located in the gut. Though the interplay between the gut microbiome and the host has been extensively studied, how the gut microbiome interacts with the enteric nervous system remains largely unknown. To date, a physiologically representative in vitro model to study gut microbiome-nervous system interactions does not exist. To fill this gap, we further developed the human-microbial crosstalk (HuMiX) gut-on-chip model by introducing induced pluripotent stem cell-derived enteric neurons into the device. The resulting model, 'neuroHuMiX', allows for the co-culture of bacterial, epithelial, and neuronal cells across microfluidic channels, separated by semi-permeable membranes. Despite separation of the different cell types, the cells can communicate with each other through soluble factors, simultaneously providing an opportunity to study each cell type separately. This setup allows for first insights into how the gut microbiome affects the enteric neuronal cells. This is a critical first step in studying and understanding the human gut microbiome-nervous system axis.

Lower gastric sensitivity in quiescent inflammatory bowel disease than in irritable bowel syndrome.

OBJECTIVE: Visceral hypersensitivity is considered a key symptom in inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), both of which seriously affect health-related quality of life (HrQoL). Previous findings are mostly based on invasive procedures that may interfere with the assessment of visceral perception. The current study, therefore, investigates whether IBD and IBS are characterized by altered perception of 'natural' gastric distensions ('interoception'). METHODS: Twenty IBD patients in remission (13 Crohn's disease, 7 ulcerative colitis), 12 IBS patients, and 20/12 matched healthy control (HC) individuals, respectively, underwent the water load test, in which they could drink ad libitum until the subjective thresholds of satiation (stage 1) and fullness (stage 2) were reached. Gastric motility was assessed using electrogastrography. RESULTS: IBD patients drank significantly more water until satiation than IBS patients, whereas no differences between patients and HC groups were observed. Electrogastrographic patterns were comparable between groups, suggesting no pathologies in gastric motility in IBD or IBS. The amount of water consumed until satiation negatively correlated with HrQoL related to bowel symptoms in IBD patients, but was positively associated with emotional well-being in IBS patients. CONCLUSION: Our findings implicate relative gastric hypersensitivity in IBS, and relative hyposensitivity in IBD patients, which are both related to specific HrQoL aspects.

Spatio-functional organization in virocells of small uncultivated archaea from the deep biosphere.

Despite important ecological roles posited for virocells (i.e., cells infected with viruses), studying individual cells in situ is technically challenging. We introduce here a novel correlative microscopic approach to study the ecophysiology of virocells. By conducting concerted virusFISH, 16S rRNA FISH, and scanning electron microscopy interrogations of uncultivated archaea, we linked morphologies of various altiarchaeal cells to corresponding phylogenetic signals and indigenous virus infections. While uninfected cells exhibited moderate separation between fluorescence signals of ribosomes and DNA, virocells displayed complete cellular segregation of chromosomal DNA from viral DNA, the latter co-localizing with host ribosome signals. A similar spatial separation was observed in dividing cells, with viral signals congregating near ribosomes at the septum. These observations suggest that replication of these uncultivated viruses occurs alongside host ribosomes, which are used to generate the required proteins for virion assembly. Heavily infected cells sometimes displayed virus-like particles attached to their surface, which agree with virus structures in cells observed via transmission electron microscopy. Consequently, this approach is the first to link genomes of uncultivated viruses to their respective structures and host cells. Our findings shed new light on the complex ecophysiology of archaeal virocells in deep subsurface biofilms and provide a solid framework for future in situ studies of virocells.

Altered infective competence of the human gut microbiome in COVID-19.

BACKGROUND: Infections with SARS-CoV-2 have a pronounced impact on the gastrointestinal tract and its resident microbiome. Clear differences between severe cases of infection and healthy individuals have been reported, including the loss of commensal taxa. We aimed to understand if microbiome alterations including functional shifts are unique to severe cases or a common effect of COVID-19. We used high-resolution systematic multi-omic analyses to profile the gut microbiome in asymptomatic-to-moderate COVID-19 individuals compared to a control group. RESULTS: We found a striking increase in the overall abundance and expression of both virulence factors and antimicrobial resistance genes in COVID-19. Importantly, these genes are encoded and expressed by commensal taxa from families such as Acidaminococcaceae and Erysipelatoclostridiaceae, which we found to be enriched in COVID-19-positive individuals. We also found an enrichment in the expression of a betaherpesvirus and rotavirus C genes in COVID-19-positive individuals compared to healthy controls. CONCLUSIONS: Our analyses identified an altered and increased infective competence of the gut microbiome in COVID-19 patients. Video Abstract.

Reservoirs of antimicrobial resistance in the context of One Health.

The emergence and spread of antimicrobial resistance (AMR) and resistant bacteria, are a global public health challenge. Through horizontal gene transfer, potential pathogens can acquire antimicrobial resistance genes (ARGs) that can subsequently be spread between human, animal, and environmental reservoirs. To understand the dissemination of ARGs and linked microbial taxa, it is necessary to map the resistome within different microbial reservoirs. By integrating knowledge on ARGs in the different reservoirs, the One Health approach is crucial to our understanding of the complex mechanisms and epidemiology of AMR. Here, we highlight the latest insights into the emergence and spread of AMR from the One Health perspective, providing a baseline of understanding for future scientific investigations into this constantly growing global health threat.

Glacier-Fed Stream Biofilms Harbor Diverse Resistomes and Biosynthetic Gene Clusters.

Antimicrobial resistance (AMR) is a universal phenomenon the origins of which lay in natural ecological interactions such as competition within niches, within and between micro- to higher-order organisms. To study these phenomena, it is crucial to examine the origins of AMR in pristine environments, i.e., limited anthropogenic influences. In this context, epilithic biofilms residing in glacier-fed streams (GFSs) are an excellent model system to study diverse, intra- and inter-domain, ecological crosstalk. We assessed the resistomes of epilithic biofilms from GFSs across the Southern Alps (New Zealand) and the Caucasus (Russia) and observed that both bacteria and eukaryotes encoded twenty-nine distinct AMR categories. Of these, beta-lactam, aminoglycoside, and multidrug resistance were both abundant and taxonomically distributed in most of the bacterial and eukaryotic phyla. AMR-encoding phyla included Bacteroidota and Proteobacteria among the bacteria, alongside Ochrophyta (algae) among the eukaryotes. Additionally, biosynthetic gene clusters (BGCs) involved in the production of antibacterial compounds were identified across all phyla in the epilithic biofilms. Furthermore, we found that several bacterial genera (Flavobacterium, Polaromonas, Superphylum Patescibacteria) encode both atimicrobial resistance genes (ARGs) and BGCs within close proximity of each other, demonstrating their capacity to simultaneously influence and compete within the microbial community. Our findings help unravel how naturally occurring BGCs and AMR contribute to the epilithic biofilms mode of life in GFSs. Additionally, we report that eukaryotes may serve as AMR reservoirs owing to their potential for encoding ARGs. Importantly, these observations may be generalizable and potentially extended to other environments that may be more or less impacted by human activity. IMPORTANCE Antimicrobial resistance is an omnipresent phenomenon in the anthropogenically influenced ecosystems. However, its role in shaping microbial community dynamics in pristine environments is relatively unknown. Using metagenomics, we report the presence of antimicrobial resistance genes and their associated pathways in epilithic biofilms within glacier-fed streams. Importantly, we observe biosynthetic gene clusters associated with antimicrobial resistance in both pro- and eukaryotes in these biofilms. Understanding the role of resistance in the context of this pristine environment and complex biodiversity may shed light on previously uncharacterized mechanisms of cross-domain interactions.

Long COVID Classification: Findings from a Clustering Analysis in the Predi-COVID Cohort Study.

The increasing number of people living with Long COVID requires the development of more personalized care; currently, limited treatment options and rehabilitation programs adapted to the variety of Long COVID presentations are available. Our objective was to design an easy-to-use Long COVID classification to help stratify people with Long COVID. Individual characteristics and a detailed set of 62 self-reported persisting symptoms together with quality of life indexes 12 months after initial COVID-19 infection were collected in a cohort of SARS-CoV-2 infected people in Luxembourg. A hierarchical ascendant classification (HAC) was used to identify clusters of people. We identified three patterns of Long COVID symptoms with a gradient in disease severity. Cluster-Mild encompassed almost 50% of the study population and was composed of participants with less severe initial infection, fewer comorbidities, and fewer persisting symptoms (mean = 2.9). Cluster-Moderate was characterized by a mean of 11 persisting symptoms and poor sleep and respiratory quality of life. Compared to the other clusters, Cluster-Severe was characterized by a higher proportion of women and smokers with a higher number of Long COVID symptoms, in particular vascular, urinary, and skin symptoms. Our study evidenced that Long COVID can be stratified into three subcategories in terms of severity. If replicated in other populations, this simple classification will help clinicians improve the care of people with Long COVID.