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Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings, detected by our pipeline, provide valuable insights into these diseases.

Importance: Assessing disease similarity is an essential initial step preceding a disease-based approach for drug repositioning. Our study provides a modest first step in underscoring the potential of integrating microbiome insights into the disease similarity assessment. Recent microbiome research has predominantly focused on analyzing individual diseases to understand their unique characteristics, which by design excludes comorbidities in individuals. We analyzed shotgun metagenomic data from existing studies and identified previously unknown similarities between diseases. Our research represents a pioneering effort that utilizes both interpretable machine learning and differential abundance analysis to assess microbial similarity between diseases.

Chicken meat is contaminated with Salmonella from the gut of infected chickens during slaughter. Eradication of Salmonella from broiler chickens through hygiene measures and/or vaccination is not cost-effective; complementary approaches are required. A mature gut microbiota obstructs Salmonella infection in chickens, and deliberate fortification of colonization resistance through prebiotic feed formulations would benefit public health and poultry production. Prebiotic galactooligosaccharides hastens Salmonella clearance from the gut of infected chickens. To better understand the role of galactooligosaccharides in colonization resistance, broiler chickens were raised on a wheat-soybean meal-based feed, with or without galactooligosaccharides for the first 24 days of life. Chickens were orally challenged with Salmonella enterica serovar Enteritidis at 20 days and the effect of supplementary galactooligosaccharides characterized by profiling Salmonella colonization, gut microbiota, innate immune response, and cecal short-chain fatty acid concentrations. Exposure to dietary galactooligosaccharides shortened the time to clear S. Enteritidis from the ceca. Differential abundance analysis of the cecal microbiota associated Salmonella challenge with a bacterial taxon belonging to the Acidaminococcaceae family (P < 0.005). Increased cecal concentrations of the short-chain fatty acids propionate and valerate were measured in Salmonella-challenged chickens sustained on either control or galactooligosaccharide-supplemented feed relative to mock-challenged controls; but far greater concentrations were detected in chickens fed a galactooligosaccharide-supplemented diet in early life. The abundance of the Acidaminococcaceae taxon exhibited a positive correlation with the cecal concentrations of propionate (ρ = 0.724, P = 0.008) and valerate (ρ = 0.71, P = 0.013). The absence of cecal pro-inflammatory transcriptional responses suggest that the rapid Salmonella clearance observed for the galactooligosaccharide-supplemented diet was not linked to innate immune function.

Importance: Work presented here identifies bacterial taxa responsible for colonization resistance to Salmonella in broiler chickens. Deliberate cultivation of these taxa with prebiotic galactooligosaccharide has potential as a straight-forward, safe, and cost-effective intervention against Salmonella. We hypothesize that catabolism of galactooligosaccharide and its breakdown products by indigenous microorganisms colonizing the chicken gut produce excess levels of propionate. In the absence of gross inflammation, propionate is inimical to Salmonella and hastens intestinal clearance.

Medium-chain carboxylates (MCCs) are used in various industrial applications. These chemicals are typically extracted from palm oil, which is deemed not sustainable. Recent research has focused on microbial chain elongation using reactors to produce MCCs, such as n-caproate (C6) and n-caprylate (C8), from organic substrates such as wastes. Even though the production of n-caproate is relatively well-characterized, bacteria and metabolic pathways that are responsible for n-caprylate production are not. Here, three 5 L reactors with continuous membrane-based liquid-liquid extraction (i.e., pertraction) were fed ethanol and acetate and operated for an operating period of 234 days with different operating conditions. Metagenomic and metaproteomic analyses were employed. n-Caprylate production rates and reactor microbiomes differed between reactors even when operated similarly due to differences in H₂ and O₂ between the reactors. The complete reverse β-oxidation (RBOX) pathway was present and expressed by several bacterial species in the Clostridia class. Several Oscillibacter spp., including Oscillibacter valericigenes, were positively correlated with n-caprylate production rates, while Clostridium kluyveri was positively correlated with n-caproate production. Pseudoclavibacter caeni, which is a strictly aerobic bacterium, was abundant across all the operating periods, regardless of n-caprylate production rates. This study provides insight into microbiota that are associated with n-caprylate production in open-culture reactors and provides ideas for further work.IMPORTANCEMicrobial chain elongation pathways in open-culture biotechnology systems can be utilized to convert organic waste and industrial side streams into valuable industrial chemicals. Here, we investigated the microbiota and metabolic pathways that produce medium-chain carboxylates (MCCs), including n-caproate (C6) and n-caprylate (C8), in reactors with in-line product extraction. Although the reactors in this study were operated similarly, different microbial communities dominated and were responsible for chain elongation. We found that different microbiota were responsible for n-caproate or n-caprylate production, and this can inform engineers on how to operate the systems better. We also observed which changes in operating conditions steered the production toward and away from n-caprylate, but more work is necessary to ascertain a mechanistic understanding that could be predictive. This study provides pertinent research questions for future work.

Microbial communities offer considerable potential for tackling environmental challenges by improving the functioning of ecosystems. Top-down community engineering is a promising strategy that could be used to obtain communities of desired function. However, the ecological factors that control the balance between community shaping and propagation are not well understood. Dairy backslopping, which consists of using part of the previous production to inoculate a new one, can be used as a model engineering approach to investigate community dynamics during serial propagations. In this study, 26 raw milk samples were serially propagated 6 times each, giving rise to 26 community lineages. Bacterial community structures were analyzed by metabarcoding, and acidification was recorded by pH monitoring. The results revealed that different types of community lineages could be obtained in terms of taxonomic composition and dynamics. Five lineages reached a repeatable community structure in a few propagation steps, with little variation between the final generations, giving rise to stable acidification kinetics. Moreover, these stabilized communities presented a high variability of structure and diverse acidification properties between community lineages. Besides, the other lineages were characterized by different levels of dynamics leading to parallel or divergent trajectories. The functional properties and dynamics of the communities were mainly related to the relative abundance and the taxonomic composition of lactic acid bacteria within the communities. These findings highlight that short-term schemes of serial fermentation can produce communities with a wide range of dynamics and that the balance between community shaping and propagation is intimately linked to community structure.

Importance: Microbiome applications require approaches for shaping and propagating microbial communities. Shaping allows the selection of communities with desired taxonomic and functional properties, while propagation allows the production of the biomass required to inoculate the engineered communities in the target ecosystem. In top-down community engineering, where communities are obtained from a pool of mixed microorganisms by acting on environmental variables, a major challenge is to master the balance between shaping and propagation. However, the ecological factors that favor high dynamics of community structure and, conversely, those that favor stability during propagation are not well understood. In this work, short-term dairy backslopping was used to investigate the key role of the taxonomic composition and structure of bacterial communities on their dynamics. The results obtained open up interesting prospects for the biotechnological use of microbiomes, particularly in the field of dairy fermentation, to diversify approaches for injecting microbial biodiversity into cheesemaking processes.

Infection with Mycobacterium bovis precipitates a spectrum of pathologies in bovines, notably necrotic pneumonia, mastitis, and arthritis, impinging upon the health and nutritional assimilation of these animals. A pivotal factor, lipocalin 2 (Lcn2), is responsive to microbial invasion, inflammatory processes, and tissue damage, the extent of which Lcn2 modulates the gut environment, however, remains unclear in response to M. bovis-induced alterations. To explore the role of Lcn2 in shaping the gut milieu of mice during a 5-week period post-M. bovis infection, Lcn2 knockout Lcn2^-/- mice were scrutinized for changes in the gut microbiota and metabolomic profiles. Results showed that Lcn2^-/- mice infected with M. bovis exhibited notable shifts in the operational taxonomic units (OTUs) of gut microbiota, alongside significant disparities in α and β diversity. Concomitantly, a marked increase was observed during the 5-week period in the abundance of Akkermansia, Oscillospira, and Bacteroides, coupled with a substantial decrease in Ruminococcus within the microbiome of Lcn2 knockout mice. Notably, Akkermansia muciniphila was significantly enriched in the gut flora of Lcn2^-/- mice. Furthermore, the absence of Lcn2 significantly altered the gut metabolomic landscape, evidenced by elevated levels of metabolites such as taurodeoxycholic acid, 10-undecenoic acid, azelaic acid, and dodecanedioic acid in Lcn2^-/- mice. Our findings demonstrated that the lack of Lcn2 in the context of M. bovis infection profoundly affected the regulation of gut microbiota and metabolomic components, culminating in a transformed gut environment. Our results revealed that Lcn2 may regulate gut microbiota and metabolome components, changing the intestinal environment, thereby affecting the infection status of M. bovis.

Importance: Our study addresses the critical knowledge gap regarding the specific influence of lipocalin 2 (LCN2) in the context of Mycobacterium bovis infection, particularly focusing on its role in the gut environment. Utilizing LCN2 knockout (Lcn2^-/-) mice, we meticulously assessed changes in the gut microbiota and metabolic components following M. bovis infection. Our findings reveal alterations in the gut microbial community, emphasizing the potentially crucial role of LCN2 in maintaining stability. Furthermore, we observed significant shifts in specific microbial communities, including the enrichment of Akkermansia muciniphila, known for its positive impact on intestinal health and immune regulation. The implications of our study extend beyond understanding the dynamics of the gut microbiome, offering insights into the potential therapeutic strategies for gut-related health conditions and microbial dysbiosis.

Modeling microbial metabolic dynamics is important for the rational optimization of both biosynthetic systems and industrial processes to facilitate green and efficient biomanufacturing. Classical approaches utilize explicit equation systems to represent metabolic networks, enabling the quantification of pathway fluxes to identify metabolic bottlenecks. However, these white-box models, despite their diverse applications, have limitations in simulating metabolic dynamics and are intrinsically inaccurate for industrial strains that lack information on network structures and kinetic parameters. On the other hand, black-box models do not rely on prior mechanistic knowledge of strains but are built upon observed time-series trajectories of biosynthetic systems in action. In practice, these observations are typically irregular, with discontinuously observed time points across multiple independent batches, each time point potentially containing missing measurements. Learning from such irregular data remains challenging for existing approaches. To address this issue, we present the Bidirectional Time-Series State Transfer Network (BTSTN) for modeling metabolic dynamics directly from irregular observations. Using evaluation data sets derived from both ideal dynamic systems and a real-world fermentation process, we demonstrate that BTSTN accurately reconstructs dynamic behaviors and predicts future trajectories. This approach exhibits enhanced robustness against missing measurements and noise, as compared to the state-of-the-art methods.IMPORTANCEIndustrial biosynthetic systems often involve strains with unclear genetic backgrounds, posing challenges in modeling their distinct metabolic dynamics. In such scenarios, white-box models, which commonly rely on inferred networks, are thereby of limited applicability and accuracy. In contrast, black-box models, such as statistical models and neural networks, are directly fitted or learned from observed time-series trajectories of biosynthetic systems in action. These methods typically assume regular observations without missing time points or measurements. If the observations are irregular, a pre-processing step becomes necessary to obtain a fully filled data set for subsequent model training, which, at the same time, inevitably introduces errors into the resulting models. BTSTN is a novel approach that natively learns from irregular observations. This distinctive feature makes it a unique addition to the current arsenal of technologies modeling metabolic dynamics.

Mycobacterium tuberculosis (Mtb) exposure leads to a range of outcomes including clearance, latent TB infection (LTBI), and pulmonary tuberculosis (TB). Some heavily exposed individuals resist tuberculin skin test (TST) and interferon-gamma (IFNγ) release assay (IGRA) conversion (RSTR), which suggests that they employ IFNγ-independent mechanisms of Mtb control. Here, we compare monocyte epigenetic profiles of RSTR and LTBI from a Ugandan household contact cohort. Chromatin accessibility did not differ between uninfected RSTR and LTBI monocytes. By contrast, methylation significantly differed at 174 CpG sites and across 63 genomic regions. Consistent with previous transcriptional findings in this cohort, differential methylation was enriched in lipid- and cholesterol-associated pathways including the genes APOC3, KCNQ1, and PLA2G3. In addition, methylation was enriched in Hippo signaling, which is associated with cholesterol homeostasis and includes CIT and SHANK2. Lipid export and Hippo signaling pathways were also associated with gene expression in response to Mtb in RSTR as well as IFN stimulation in monocyte-derived macrophages (MDMs) from an independent healthy donor cohort. Moreover, serum-derived high-density lipoprotein from RSTR had elevated ABCA1-mediated cholesterol efflux capacity (CEC) compared to LTBI. Our findings suggest that resistance to TST/IGRA conversion is linked to regulation of lipid accumulation in monocytes, which could facilitate early Mtb clearance among RSTR subjects through IFNγ-independent mechanisms.IMPORTANCETuberculosis (TB) remains an enduring global health challenge with millions of deaths and new cases each year. Despite recent advances in TB treatment, we lack an effective vaccine or a durable cure. While heavy exposure to Mycobacterium tuberculosis often results in latent TB latent infection (LTBI), subpopulations exist that are either resistant to infection or contain Mtb with interferon-gamma (IFNγ)-independent mechanisms not indicative of LTBI. These resisters provide an opportunity to investigate the mechanisms of TB disease and discover novel therapeutic targets. Here, we compare monocyte epigenetic profiles of RSTR and LTBI from a Ugandan household contact cohort. We identify methylation signatures in host lipid and cholesterol pathways with potential relevance to early TB clearance before the sustained IFN responses indicative of LTBI. This adds to a growing body of literature linking TB disease outcomes to host lipids.

Gastrointestinal diseases are the most frequently reported clinical problems in captive common marmosets (Callithrix jacchus), often affecting the health and welfare of the animal and ultimately their use as a research subject. The microbiome has been shown to be intimately connected to diet and gastrointestinal health. Here, we use shotgun metagenomics and untargeted metabolomics in fecal samples of common marmosets collected before, during, and after a dietary transition from a biscuit to a gel diet. The overall health of marmosets, measured as weight recovery and reproductive outcome, improved after the diet transition. Moreover, each marmoset pair had significant shifts in the microbiome and metabolome after the diet transition. In general, we saw a decrease in Escherichia coli and Prevotella species and an increase in Bifidobacterium species. Untargeted metabolic profiles indicated that polyamine levels, specifically cadaverine and putrescine, were high after diet transition, suggesting either an increase in excretion or a decrease in intestinal reabsorption at the intestinal level. In conclusion, our data suggest that Bifidobacterium species could potentially be useful as probiotic supplements to the laboratory marmoset diet. Future studies with a larger sample size will be beneficial to show that this is consistent with the diet change.

Importance: Appropriate diet and health of the common marmoset in captivity are essential both for the welfare of the animal and to improve experimental outcomes. Our study shows that a gel diet compared to a biscuit diet improves the health of a marmoset colony, is linked to increases in Bifidobacterium species, and increases the removal of molecules associated with disease. The diet transition had an influence on the molecular changes at both the pair and time point group levels, but only at the pair level for the microbial changes. It appears to be more important which genes and functions present changed rather than specific microbes. Further studies are needed to identify specific components that should be considered when choosing an appropriate diet and additional supplementary foods, as well as to validate the benefits of providing probiotics. Probiotics containing Bifidobacterium species appear to be useful as probiotic supplements to the laboratory marmoset diet, but additional work is needed to validate these findings.

Estuarine and coastal ecosystems are of high economic and ecological importance, owing to their diverse communities and the disproportionate role they play in carbon cycling, particularly in carbon sequestration. Organisms inhabiting these environments must overcome strong natural fluctuations in salinity, nutrients, and turbidity, as well as numerous climate change-induced disturbances such as land loss, sea level rise, and, in some locations, increasingly severe tropical cyclones that threaten to disrupt future ecosystem health. The northern Gulf of Mexico (nGoM) along the Louisiana coast contains dozens of estuaries, including the Mississippi-Atchafalaya River outflow, which dramatically influence the region due to their vast upstream watershed. Nevertheless, the microbiology of these estuaries and surrounding coastal environments has received little attention. To improve our understanding of microbial ecology in the understudied coastal nGoM, we conducted a 16S rRNA gene amplicon survey at eight sites and multiple time points along the Louisiana coast and one inland swamp spanning freshwater to high brackish salinities, totaling 47 duplicated Sterivex (0.2-2.7 µm) and prefilter (>2.7 µm) samples. We cataloged over 13,000 Amplicon Sequence ariants (ASVs) from common freshwater and marine clades such as SAR11 (Alphaproteobacteria), Synechococcus (Cyanobacteria), and acI and Candidatus Actinomarina (Actinobacteria). We observed correlations with freshwater or marine habitats in many organisms and characterized a group of taxa with specialized distributions across brackish water sites, supporting the hypothesis of an endogenous brackish-water community. Additionally, we observed brackish-water associations for several aquatic clades typically considered marine or freshwater taxa, such as SAR11 subclade II, SAR324, and the acI Actinobacteria. The data presented here expand the geographic coverage of microbial ecology in estuarine communities, help delineate the native and transitory members of these environments, and provide critical aquatic microbiological baseline data for coastal and estuarine sites in the nGoM.IMPORTANCEEstuarine and coastal waters are diverse ecosystems influenced by tidal fluxes, interconnected wetlands, and river outflows, which are of high economic and ecological importance. Microorganisms play a pivotal role in estuaries as "first responders" and ecosystem architects, yet despite their ecological importance, they remain underrepresented in microbial studies compared to open ocean environments. This leads to substantial knowledge gaps that are important for understanding global biogeochemical cycling and making decisions about conservation and management strategies in these environments. Our study makes key contributions to the microbial ecology of estuarine and coastal habitats in the northern Gulf of Mexico. Our microbial community data support the concept of a globally distributed, core brackish micr

Campylobacter jejuni and Arcobacter butzleri are microaerobic food-borne human gastrointestinal pathogens that mainly cause diarrheal disease. These related species of the Campylobacteria class face variable atmospheric environments during infection and transmission, ranging from nearly anaerobic to aerobic conditions. Consequently, their lifestyles require that both pathogens need to adjust their metabolism and respiration to the changing oxygen concentrations of the colonization sites. Our transcriptomic and proteomic studies revealed that C. jejuni and A. butzleri, lacking a Campylobacteria-specific regulatory protein, C. jejuni Cj1608, or a homolog, A. butzleri Abu0127, are unable to reprogram tricarboxylic acid cycle or respiration pathways, respectively, to produce ATP efficiently and, in consequence, adjust growth to changing oxygen supply. We propose that these Campylobacteria energy and metabolism regulators (CemRs) are long-sought transcription factors controlling the metabolic shift related to oxygen availability, essential for these bacteria's survival and adaptation to the niches they inhabit. Besides their significant universal role in Campylobacteria, CemRs, as pleiotropic regulators, control the transcription of many genes, often specific to the species, under microaerophilic conditions and in response to oxidative stress.

Importance: C. jejuni and A. butzleri are closely related pathogens that infect the human gastrointestinal tract. In order to infect humans successfully, they need to change their metabolism as nutrient and respiratory conditions change. A regulator called CemR has been identified, which helps them adapt their metabolism to changing conditions, particularly oxygen availability in the gastrointestinal tract so that they can produce enough energy for survival and spread. Without CemR, these bacteria, as well as a related species, Helicobacter pylori, produce less energy, grow more slowly, or, in the case of C. jejuni, do not grow at all. Furthermore, CemR is a global regulator that controls the synthesis of many genes in each species, potentially allowing them to adapt to their ecological niches as well as establish infection. Therefore, the identification of CemR opens new possibilities for studying the pathogenicity of C. jejuni and A. butzleri.