The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

Microbial community and extracellular polymeric substance dynamics in arid-zone temporary pan ecosystems

Microbial extracellular polymeric substances (EPS) are an important component in sediment ecology. However, most research is highly skewed towards the northern hemisphere and in more permanent systems. This paper investigates EPS (i.e., carbohydrates and proteins) dynamics in arid Austral zone temporary pans sediments. Colorimetric methods and sequence-based metagenomics techniques were employed in a series of small temporary pan ecosystems characterised by alternating wet and dry hydroperiods. Microbial community patterns of distribution were evaluated between seasons (hot-wet and cool-dry) and across depths (and inferred inundation period) based on estimated elevation. Carbohydrates generally occurred in relatively higher proportions than proteins; the carbohydrate:protein ratio was 2.8:1 and 1.6:1 for the dry and wet season respectively, suggesting that EPS found in these systems was largely diatom produced. The wet- hydroperiods (Carbohydrate mean 102 μg g-1; Protein mean 65 μg g-1) supported more EPS production as compared to the dry- hydroperiods (Carbohydrate mean 73 μg g-1; Protein mean 26 μg g-1). A total of 15,042 Unique Amplicon Sequence Variants (ASVs) were allocated to 51 bacterial phyla and 1127 genera. The most abundant genera had commonality in high temperature tolerance, with Firmicutes, Actinobacteria and Proteobacteria in high abundances. Microbial communities were more distinct between seasons compared to within seasons which further suggested that the observed metagenome functions could be seasonally driven. This study's findings implied that there were high levels of denitrification by mostly nitric oxide reductase and nitrite reductase enzymes. EPS production was high in the hot-wet season as compared to relatively lower rates of nitrification in the cool-dry season by ammonia monooxygenases. Both EPS quantities and metagenome functions were highly associated with availability of water, with high rates being mainly associated with wet- hydroperiods compared to dry- hydroperiods. These data suggest that extended dry periods threaten microbially mediated processes in temporary wetlands, with implications to loss of biodiversity by desiccation.

Gut microbiota disturbances in hospitalized older adults with malnutrition and clinical outcomes

OBJECTIVE

Malnutrition is one of the most threatening conditions in geriatric populations. The gut microbiota has an important role in the host's metabolic and muscular health: however, its interplay with disease-related malnutrition is not well understood. We aimed to identify the association of malnutrition with the gut microbiota and predict clinical outcomes in hospitalized acutely ill older adults.

METHODS

We performed a secondary longitudinal analysis in 108 geriatric patients from a prospective cohort evaluated at admission and 72 h of hospitalization. We collected clinical, demographic, nutritional, and 16S rRNA gene-sequenced gut microbiota data. Microbiota diversity, overall composition, and differential abundance were calculated and compared between patients with and without malnutrition. Microbiota features associated with malnutrition were used to predict clinical outcomes.

RESULTS

Patients with malnutrition (51%) had a different microbiota composition compared to those who were well-nourished during hospitalization (ANOSIM R = 0.079, P = 0.003). Patients with severe malnutrition showed poorer α-diversity at admission (Shannon P = 0.012, Simpson P = 0.018) and follow-up (Shannon P = 0.023, Chao1 P = 0.008). Differential abundance of Lachnospiraceae NK4A136 group, Subdoligranulum, and Faecalibacterium prausnitzii were significantly lower and inversely associated with malnutrition, while Corynebacterium, Ruminococcaceae Incertae Sedis, and Fusobacterium were significantly increased and positively associated with malnutrition. Corynebacterium, Ruminococcaceae Incertae Sedis, and the overall composition were important predictors of critical care in patients with malnutrition during hospitalization.

CONCLUSION

Older adults with malnutrition, especially in a severe stage, may be subject to substantial gut microbial disturbances during hospitalization. The gut microbiota profile of patients with malnutrition might help us to predict worse clinical outcomes.

Integrative analysis of systemic lupus erythematosus biomarkers: Role of fecal hsa-mir-223-3p and gut microbiota in transkingdom dynamics

Systemic lupus erythematosus (SLE) involves a florid set of clinical manifestations whose autoreactive origin is characterized by an overactivation of the immune system and the production of a large number of autoantibodies. Because it is a complex pathology with an inflammatory component, its pathogenesis is not yet fully understood, assuming both genetic and environmental predisposing factors. Currently, it is known that the role of the human microbiome is crucial in maintaining the transkingdom balance between commensal microorganisms and the immune system. In the present work we study the intestinal microbiota of Argentine patients with different stages of SLE receiving or not different treatments. Microbiota composition and fecal miRNAs were assessed by 16 S sequencing and qPCR. hsa-miR-223-3p, a miRNA involved in several inflammation regulation pathways, was found underexpressed in SLE patients without immunosuppressive treatment. In terms of microbiota there were clear differences in population structure (Weighted and Unweighted Unifrac distances, p-value <0.05) and core microbiome between cases and controls. In addition, Collinsella, Bifidobacterium, Streptococcus genera and aromatics degradation metabolisms were overrepresented in the SLE group. Medical treatment was also determinant as several microbial metabolic pathways were influenced by immunosuppressive therapy. Particularly, allantoin degradation metabolism was differentially expressed in the group of patients receiving immunosuppressants. Finally, we performed a logistic regression model (LASSO: least absolute shrinkage and selection operator) considering the expression levels of the fecal hsa-miR223-3p; the core microbiota; the differentially abundant bacterial taxa and the differentially abundant metabolic pathways (p<0.05). The model predicted that SLE patients could be associated with greater relative abundance of the formaldehyde oxidation pathway (RUMP_PWY). On the contrary, the preponderance of the ketodeoxyoctonate (Kdo) biosynthesis and activation route (PWY_1269) and the genera Lachnospiraceae_UCG_004, Lachnospira, Victivallis and UCG_003 (genus belonging to the family Oscillospiraceae of the class Clostridia) were associated with a control phenotype. Overall, the present work could contribute to the development of integral diagnostic tools for the comprehensive phenotyping of patients with SLE. In this sense, studying the commensal microbial profile and possible pathobionts associated with SLE in our population proposes more effective and precise strategies to explore possible treatments based on the microbiota of SLE patients.

The intracellular symbiont Wolbachia alters Drosophila development and metabolism to buffer against nutritional stress

The intracellular bacterium Wolbachia is a common symbiont of many arthropods and nematodes, well studied for its impacts on host reproductive biology. However, its broad success as a vertically transmitted infection cannot be attributed to manipulations of host reproduction alone. Using the Drosophila melanogaster model and their natively associated Wolbachia strain " w Mel", we show that Wolbachia infection supports fly development and buffers against nutritional stress. Wolbachia infection across several fly genotypes and a range of nutrient conditions resulted in reduced pupal mortality, increased adult emergence, and larger size. We determined that the exogenous supplementation of pyrimidines partially rescued developmental phenotypes in the Wolbachia -free flies, and that Wolbachia titers were responsive to reduced gene expression of the fly's de novo pyrimidine synthesis pathway. In parallel, transcriptomic and metabolomic analyses indicated that Wolbachia impacts larval biology far beyond pyrimidine metabolism. Wolbachia -infected larvae had strong signatures of shifts in glutathione and mitochondrial metabolism, plus significant changes in the expression of key developmental regulators including Notch , the insulin receptor ( lnR ), and the juvenile hormone receptor Methoprene-tolerant ( Met ). We propose that Wolbachia acts as a beneficial symbiont to support fly development and enhance host fitness, especially during periods of nutrient stress.

SIGNIFICANCE

Wolbachia is a bacterial symbiont of arthropods and nematodes, well described for its manipulations of arthropod reproduction. However, many have theorized there must be more to this symbiosis, even in well-studied Wolbachia- host relationships such as with Drosophila . Reproductive impacts alone cannot explain the success and ubiquity of this bacterium. Here, we use Drosophila melanogaster and their native Wolbachia infections to show that Wolbachia supports fly development and significantly buffers flies against nutritional stress. These developmental advantages might help explain the ubiquity of Wolbachia infections.

Landfill intermediate cover soil microbiomes and their potential for mitigating greenhouse gas emissions revealed through metagenomics

Landfills are a major source of anthropogenic methane emissions and have been found to produce nitrous oxide, an even more potent greenhouse gas than methane. Intermediate cover soil (ICS) plays a key role in reducing methane emissions but may also result in nitrous oxide production. To assess the potential for microbial methane oxidation and nitrous oxide production, long sequencing reads were generated from ICS microbiome DNA and reads were functionally annotated for 24 samples across ICS at a large landfill in New York. Further, incubation experiments were performed to assess methane consumption and nitrous oxide production with varying amounts of ammonia supplemented. Methane was readily consumed by microbes in the composite ICS and all incubations with methane produced small amounts of nitrous oxide even when ammonia was not supplemented. Incubations without methane produced significantly less nitrous oxide than those incubated with methane. In incubations with methane added, the observed specific rate of methane consumption was 0.776 +/- 0.055 μg CH4 g dry weight (DW) soil-1 h-1 and the specific rate of nitrous oxide production was 3.64 × 10-5 +/- 1.30 × 10-5 μg N2O g DW soil-1 h-1. The methanotrophs Methylobacter and an unclassified genus within the family Methlyococcaceae were present in the original ICS samples and the incubation samples, and their abundance increased during incubations with methane. Genes encoding particulate methane monooxygenase/ ammonia monooxygenase (pMMO) were much more abundant than genes encoding soluble methane monooxygenase (sMMO) across the landfill ICS. Genes encoding proteins that convert hydroxylamine to nitrous oxide were not highly abundant in the ICS or incubation metagenomes. In total, these results suggest that although ammonia oxidation via methanotrophs may result in low levels of nitrous oxide production, ICS microbial communities have the potential to greatly reduce the overall global warming potential of landfill emissions.

Nitrosative stress under microaerobic conditions triggers inositol metabolism in Pseudomonas extremaustralis

Bacteria are exposed to reactive oxygen and nitrogen species that provoke oxidative and nitrosative stress which can lead to macromolecule damage. Coping with stress conditions involves the adjustment of cellular responses, which helps to address metabolic challenges. In this study, we performed a global transcriptomic analysis of the response of Pseudomonas extremaustralis to nitrosative stress, induced by S-nitrosoglutathione (GSNO), a nitric oxide donor, under microaerobic conditions. The analysis revealed the upregulation of genes associated with inositol catabolism; a compound widely distributed in nature whose metabolism in bacteria has aroused interest. The RNAseq data also showed heightened expression of genes involved in essential cellular processes like transcription, translation, amino acid transport and biosynthesis, as well as in stress resistance including iron-dependent superoxide dismutase, alkyl hydroperoxide reductase, thioredoxin, and glutathione S-transferase in response to GSNO. Furthermore, GSNO exposure differentially affected the expression of genes encoding nitrosylation target proteins, encompassing metalloproteins and proteins with free cysteine and /or tyrosine residues. Notably, genes associated with iron metabolism, such as pyoverdine synthesis and iron transporter genes, showed activation in the presence of GSNO, likely as response to enhanced protein turnover. Physiological assays demonstrated that P. extremaustralis can utilize inositol proficiently under both aerobic and microaerobic conditions, achieving growth comparable to glucose-supplemented cultures. Moreover, supplementing the culture medium with inositol enhances the stress tolerance of P. extremaustralis against combined oxidative-nitrosative stress. Concordant with the heightened expression of pyoverdine genes under nitrosative stress, elevated pyoverdine production was observed when myo-inositol was added to the culture medium. These findings highlight the influence of nitrosative stress on proteins susceptible to nitrosylation and iron metabolism. Furthermore, the activation of myo-inositol catabolism emerges as a protective mechanism against nitrosative stress, shedding light on this pathway in bacterial systems, and holding significance in the adaptation to unfavorable conditions.

Computational drug repositioning identifies niclosamide and tribromsalan as inhibitors of Mycobacterium tuberculosis and Mycobacterium abscessus

Tuberculosis (TB) is still a major global health challenge, killing over 1.5 million people each year, and hence, there is a need to identify and develop novel treatments for Mycobacterium tuberculosis (M. tuberculosis). The prevalence of infections caused by nontuberculous mycobacteria (NTM) is also increasing and has overtaken TB cases in the United States and much of the developed world. Mycobacterium abscessus (M. abscessus) is one of the most frequently encountered NTM and is difficult to treat. We describe the use of drug-disease association using a semantic knowledge graph approach combined with machine learning models that has enabled the identification of several molecules for testing anti-mycobacterial activity. We established that niclosamide (M. tuberculosis IC90 2.95 μM; M. abscessus IC90 59.1 μM) and tribromsalan (M. tuberculosis IC90 76.92 μM; M. abscessus IC90 147.4 μM) inhibit M. tuberculosis and M. abscessus in vitro. To investigate the mode of action, we determined the transcriptional response of M. tuberculosis and M. abscessus to both compounds in axenic log phase, demonstrating a broad effect on gene expression that differed from known M. tuberculosis inhibitors. Both compounds elicited transcriptional responses indicative of respiratory pathway stress and the dysregulation of fatty acid metabolism.

Genome-scale metabolic network models for industrial microorganisms metabolic engineering: Current advances and future prospects

The construction of high-performance microbial cell factories (MCFs) is the centerpiece of biomanufacturing. However, the complex metabolic regulatory network of microorganisms poses great challenges for the efficient design and construction of MCFs. The genome-scale metabolic network models (GSMs) can systematically simulate the metabolic regulation process of microorganisms in silico, providing effective guidance for the rapid design and construction of MCFs. In this review, we summarized the development status of 16 important industrial microbial GSMs, and further outline the technologies or methods that continuously promote high-quality GSMs construction from five aspects: I) Databases and modeling tools facilitate GSMs reconstruction; II) evolving gap-filling technologies; III) constraint-based model reconstruction; IV) advances in algorithms; and V) developed visualization tools. In addition, we also summarized the applications of GSMs in guiding metabolic engineering from four aspects: I) exploring and explaining metabolic features; II) predicting the effects of genetic perturbations on metabolism; III) predicting the optimal phenotype; IV) guiding cell factories construction in practical experiment. Finally, we discussed the development of GSMs, aiming to provide a reference for efficiently reconstructing GSMs and guiding metabolic engineering.

The Fungal Diversity and Potential Pathogens Associated with Postharvest Fruit Rot of 'Huangguan' Pear (Pyrus bretschneideri) in Hebei Province, China

Postharvest fruit rot caused by pathogens is a serious problem in the pear industry. This study investigated the fungal diversity and main pathogens and identified a new pathogen in the stored 'Huangguan' pear (Pyrus bretschneideri Rehd.), the dominant pear variety in northern China. We sampled 20 refrigeration houses from five main producing regions in Hebei Province and used Illumina sequencing technology to detect the fungal composition. Alternaria (56.3%) was the most abundant fungus, followed by Penicillium (9.2%) and Monilinia (6.2%). We also isolated and identified nine strains of Alternaria and four strains of Penicillium. Moreover, we observed a new postharvest fruit disease in 'Huangguan' pear caused by Stemphylium eturmiunum, which was confirmed by phylogenetic analysis by combining the sequences of three conserved genes, including internal transcribed spacer, gapdh, and calmodulin. This study marks the first documentation of S. eturmiunum causing fruit rot in 'Huangguan' pears, offering valuable insights for identifying and controlling this newly identified postharvest disease.

Gut microbiome composition and metabolic activity in women with diverticulitis

The etiopathogenesis of diverticulitis, among the most common gastrointestinal diagnoses, remains largely unknown. By leveraging stool collected within a large prospective cohort, we performed shotgun metagenomic sequencing and untargeted metabolomics profiling among 121 women diagnosed with diverticulitis requiring antibiotics or hospitalizations (cases), matched to 121 women without diverticulitis (controls) according to age and race. Overall microbial community structure and metabolomic profiles differed in diverticulitis cases compared to controls, including enrichment of pro-inflammatory Ruminococcus gnavus, 1,7-dimethyluric acid, and histidine-related metabolites, and depletion of butyrate-producing bacteria and anti-inflammatory ceramides. Through integrated multi-omic analysis, we detected covarying microbial and metabolic features, such as Bilophila wadsworthia and bile acids, specific to diverticulitis. Additionally, we observed that microbial composition modulated the protective association between a prudent fiber-rich diet and diverticulitis. Our findings offer insights into the perturbations in inflammation-related microbial and metabolic signatures associated with diverticulitis, supporting the potential of microbial-based diagnostics and therapeutic targets.

Taxonomic and metabolic development of the human gut microbiome across life stages: a worldwide metagenomic investigation

The human gut microbiota is a dynamic community of microorganisms that undergo variable changes over the entire life span. To thoroughly investigate the possible fluctuations of the microbiota throughout human life, we performed a pooled analysis of healthy fecal samples across different age groups covering the entire human life span. Our study integrated data from 79 publicly available studies and new stool samples from an Italian cohort, i.e., the Parma Microbiota project, resulting in 6,653 samples processed through the shotgun metagenomic approach. This approach has allowed species-level taxonomic reconstruction of the gut microbiota and investigation of its metabolic potential across the human life span. From a taxonomic point of view, our findings confirmed and detailed at species-level accuracy that the microbial richness of the gut microbiota gradually increases in the first stage of life, becoming relatively stable during adolescence. Moreover, the analysis identified the potential core microbiota representative of distinct age groups, revealing age-related bacterial patterns and the continuous rearrangement of the microbiota in terms of relative abundances across the life span rather than the acquisition and loss of taxa. Furthermore, the shotgun approach provided insights into the functional contribution of the human gut microbiome. The metagenomic analysis revealed functional age-related differences, particularly in carbohydrate and fiber metabolism, suggesting a co-evolution of the microbiome assembly with diet. Additionally, we identified correlations between vitamin synthesis, such as thiamine and niacin, and early life, suggesting a potential role of the microbiome in human physiology, in particular in the functions of the host's nervous and immune systems.

IMPORTANCE

In this study, we provided comprehensive insights into the dynamic nature of the human gut microbiota across the human life span. In detail, we analyzed a large data set based on a shotgun metagenomic approach, combining public data sets and new samples from the Parma Microbiota project and obtaining a detailed overview of the possible relationship between gut microbiota development and aging. Our findings confirmed the main stages in microbial richness development and revealed specific core microbiota associated with different age stages. Moreover, the shotgun metagenomic approach allowed the disentangling of the functional changes in the microbiome across the human life span, particularly in diet-related metabolism, which is probably correlated to bacterial co-evolution with dietary habits. Notably, our study also uncovered positive correlations with vitamin synthesis in early life, suggesting a possible impact of the microbiota on human physiology.

Mapping multi-omics characteristics related to short-term PM2.5 trajectory and their impact on type 2 diabetes in middle-aged and elderly adults in Southern China

The relationship between PM2.5 and metabolic diseases, including type 2 diabetes (T2D), has become increasingly prominent, but the molecular mechanism needs to be further clarified. To help understand the mechanistic association between PM2.5 exposure and human health, we investigated short-term PM2.5 exposure trajectory-related multi-omics characteristics from stool metagenome and metabolome and serum proteome and metabolome in a cohort of 3267 participants (age: 64.4 ± 5.8 years) living in Southern China. And then integrate these features to examine their relationship with T2D. We observed significant differences in overall structure in each omics and 193 individual biomarkers between the high- and low-PM2.5 groups. PM2.5-related features included the disturbance of microbes (carbohydrate metabolism-associated Bacteroides thetaiotaomicron), gut metabolites of amino acids and carbohydrates, serum biomarkers related to lipid metabolism and reducing n-3 fatty acids. The patterns of overall network relationships among the biomarkers differed between T2D and normal participants. The subnetwork membership centered on the hub nodes (fecal rhamnose and glycylproline, serum hippuric acid, and protein TB182) related to high-PM2.5, which well predicted higher T2D prevalence and incidence and a higher level of fasting blood glucose, HbA1C, insulin, and HOMA-IR. Our findings underline crucial PM2.5-related multi-omics biomarkers linking PM2.5 exposure and T2D in humans.

Stress Knowledge Map: A knowledge graph resource for systems biology analysis of plant stress responses

Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical, signaling, and regulatory molecular interactions in plants: a highly curated model of plant stress signaling (PSS; 543 reactions) and a large comprehensive knowledge network (488 390 interactions). Both were constructed by domain experts through systematic curation of diverse literature and database resources. SKM provides a single entry point for investigations of plant stress response and related growth trade-offs, as well as interactive explorations of current knowledge. PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin. Here, we describe the features of SKM and show, through two case studies, how it can be used for complex analyses, including systematic hypothesis generation and design of validation experiments, or to gain new insights into experimental observations in plant biology.

Naturalization of treated wastewater by a constructed wetland in a water-scarce Mediterranean region

The effluents from conventional wastewater treatment plants (WWTP), even if accomplishing quality regulations, substantially differ in their characteristics with those of waters in natural environments. Constructed wetlands (CWs) serve as transitional ecosystems within WWTPs, mitigating these differences and restoring natural features before water is poured into the natural environment. Our study focused on an experimental surface-flow CW naturalizing the WWTP effluent in a semiarid area in Eastern Spain. Despite relatively low pollutant concentrations entering the CW, it effectively further reduced settled organic matter and nitrogen. Dissolved organic matter (DOM) reaching the CW was mainly protein-like, yet optical property changes in the DOM indicated increased humification, aromaticity, and stabilization as it flowed through the CW. Flow cytometry analysis revealed that the CW released less abundant but more active bacterial populations than those received. MiSeq Illumina sequencing highlighted changes in the prokaryotic community composition, with phyla Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria dominating the CW outflow. Functional prediction tools (FaproTax and PICRUSt2) demonstrated a shift towards microbial guilds aligned with those of the natural aquatic environments, increased aerobic chemoheterotrophs, photoautotrophs, and metabolic reactions at higher redox potentials. Enhanced capabilities for degrading plant material correlated well with changes in the DOM pool. Our findings emphasize the role of CWs in releasing biochemically stable DOM and functionally suited microbial populations for natural receiving environments. Consequently, we propose CWs as a naturalization nature-based solution (NBS) in water-scarce regions like the Mediterranean, where reclaimed discharged water can significantly contribute to ecosystem's water resources compared to natural flows.

EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology

The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies.

Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease

Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.

Gender-affirming hormone therapy preserves skeletal maturation in young mice via the gut microbiome

Gender-affirming hormone therapy (GAHT) is often prescribed to transgender (TG) adolescents to alleviate gender dysphoria, but the effect of GAHT on the growing skeleton is unclear. We found GAHT to improve trabecular bone structure via increased bone formation in young male mice and not to affect trabecular structure in female mice. GAHT modified gut microbiome composition in both male and female mice. However, fecal microbiota transfers (FMTs) revealed that GAHT-shaped gut microbiome was a communicable regulator of bone structure and turnover in male, but not in female mice. Mediation analysis identified 2 species of Bacteroides as significant contributors to the skeletal effects of GAHT in male mice, with Bacteroides supplementation phenocopying the effects of GAHT on bone. Bacteroides have the capacity to expand Treg populations in the gut. Accordingly, GAHT expanded intestinal Tregs and stimulated their migration to the bone marrow (BM) in male but not in female mice. Attesting to the functional relevance of Tregs, pharmacological blockade of Treg expansion prevented GAHT-induced bone anabolism. In summary, in male mice GAHT stimulated bone formation and improved trabecular structure by promoting Treg expansion via a microbiome-mediated effect, while in female mice, GAHT neither improved nor impaired trabecular structure.

Elucidation of bacterial trehalose-degrading trehalase and trehalose phosphorylase: physiological significance and its potential applications

Bacteria possess diverse metabolic and genetic processes, resulting in the inability of certain bacteria to degrade trehalose. However, some bacteria do have the capability to degrade trehalose, utilizing it as a carbon source, and for defense against environmental stress. Trehalose, a disaccharide, serves as a carbon source for many bacteria, including some that are vital for pathogens. The degradation of trehalose is carried out by enzymes like trehalase (EC 3.2.1.28) and trehalose phosphorylase (EC 2.4.1.64/2.4.1.231), which are classified under the glycoside hydrolase families GH37, GH15, and GH65. Numerous studies and reports have explored the physiological functions, recombinant expression, enzymatic characteristics, and potential applications of these enzymes. However, further research is still being conducted to understand their roles in bacteria. This review aims to provide a comprehensive summary of the current understanding of trehalose degradation pathways in various bacteria, focusing on three key areas: (i) identifying different trehalose-degrading enzymes in Gram-positive and Gram-negative bacteria, (ii) elucidating the mechanisms employed by trehalose-degrading enzymes belonging to the glycoside hydrolases GH37, GH15, and GH65, and (iii) discussing the potential applications of these enzymes in different sectors. Notably, this review emphasizes the bacterial trehalose-degrading enzymes, specifically trehalases (GH37, GH15, and GH65) and trehalose phosphorylases (GH65), in both Gram-positive and Gram-negative bacteria, an aspect that has not been highlighted before.

Differential Effects of Two Common Antiparasitics on Microbiota Resilience

BACKGROUND

Parasitic infections challenge vertebrate health worldwide, and off-target effects of antiparasitic treatments may be an additional obstacle to recovery. However, there have been few investigations of the effects of antiparasitics on the gut microbiome in the absence of parasites.

METHODS

We investigated whether two common antiparasitics-albendazole (ALB) and metronidazole (MTZ)-significantly alter the gut microbiome of parasite-free mice. We treated mice with ALB or MTZ daily for 7 days and sampled the fecal microbiota immediately before and after treatment and again after a two-week recovery period.

RESULTS

ALB did not immediately change the gut microbiota, while MTZ decreased microbial richness by 8.5% and significantly changed community structure during treatment. The structural changes caused by MTZ included depletion of the beneficial family Lachnospiraceae, and predictive metagenomic analysis revealed that these losses likely depressed microbiome metabolic function. Separately, we compared the fecal microbiotas of treatment groups after recovery, and there were minor differences in community structure between the ALB, MTZ, and sham-treated control groups.

CONCLUSIONS

These results suggest that a healthy microbiome is resilient after MTZ-induced depletions of beneficial gut microbes, and ALB may cause slight, latent shifts in the microbiota but does not deplete healthy gut microbiota diversity.

Multi-modal molecular determinants of clinically relevant osteoporosis subtypes

Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is not sufficient to accurately identify all patients at risk of osteoporotic fractures and to guide therapy. Here, we constructed the first prospective multi-omics atlas of the largest osteoporosis cohort to date (longitudinal data from 366 participants at three time points), and also implemented an explainable data-intensive analysis framework (DLSF: Deep Latent Space Fusion) for an omnigenic model based on a multi-modal approach that can capture the multi-modal molecular signatures (M3S) as explicit functional representations of hidden genotypes. Accordingly, through DLSF, we identified two subtypes of the osteoporosis population in Chinese individuals with corresponding molecular phenotypes, i.e., clinical intervention relevant subtypes (CISs), in which bone mineral density benefits response to calcium supplements in 2-year follow-up samples. Many snpGenes associated with these molecular phenotypes reveal diverse candidate biological mechanisms underlying osteoporosis, with xQTL preferences of osteoporosis and its subtypes indicating an omnigenic effect on different biological domains. Finally, these two subtypes were found to have different relevance to prior fracture and different fracture risk according to 4-year follow-up data. Thus, in clinical application, M3S could help us further develop improved diagnostic and treatment strategies for osteoporosis and identify a new composite index for fracture prediction, which were remarkably validated in an independent cohort (166 participants).

Sociobiome - Individual and neighborhood socioeconomic status influence the gut microbiome in a multi-ethnic population in the US

Lower socioeconomic status (SES) is related to increased incidence and mortality due to chronic diseases in adults. Association between SES variables and gut microbiome variation has been observed in adults at the population level, suggesting that biological mechanisms may underlie the SES associations; however, there is a need for larger studies that consider individual- and neighborhood-level measures of SES in racially diverse populations. In 825 participants from a multi-ethnic cohort, we investigated how SES shapes the gut microbiome. We determined the relationship of a range of individual- and neighborhood-level SES indicators with the gut microbiome. Individual education level and occupation were self-reported by questionnaire. Geocoding was applied to link participants' addresses with neighborhood census tract socioeconomic indicators, including average income and social deprivation in the census tract. Gut microbiome was measured using 16SV4 region rRNA gene sequencing of stool samples. We compared α-diversity, β-diversity, and taxonomic and functional pathway abundance by SES. Lower SES was significantly associated with greater α-diversity and compositional differences among groups, as measured by β-diversity. Several taxa related to low SES were identified, especially an increasing abundance of Prevotella copri and Catenibacterium sp000437715, and decreasing abundance of Dysosmobacter welbionis in terms of their high log-fold change differences. In addition, nativity and race/ethnicity have emerged as ecosocial factors that also influence the gut microbiota. Together, these results showed that lower SES was strongly associated with compositional and taxonomic measures of the gut microbiome, and may contribute to shaping the gut microbiota.

Mitochondrial ATP generation is more proteome efficient than glycolysis

Metabolic efficiency profoundly influences organismal fitness. Nonphotosynthetic organisms, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. Although respiration is more energy efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (that is, faster). Through quantitative flux analysis and proteomics, we find, however, that mitochondrial respiration is actually more proteome efficient than aerobic glycolysis. This is shown across yeast strains, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which promotes hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth but outgrow respiratory cells during oxygen limitation. We accordingly propose that aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.

The Mla system and its role in maintaining outer membrane barrier function in Stenotrophomonas maltophilia

Stenotrophomonas maltophilia are ubiquitous Gram-negative bacteria found in both natural and clinical environments. It is a remarkably adaptable species capable of thriving in various environments, thanks to the plasticity of its genome and a diverse array of genes that encode a wide range of functions. Among these functions, one notable trait is its remarkable ability to resist various antimicrobial agents, primarily through mechanisms that regulate the diffusion across cell membranes. We have investigated the Mla ABC transport system of S. maltophilia, which in other Gram-negative bacteria is known to transport phospholipids across the periplasm and is involved in maintaining outer membrane homeostasis. First, we structurally and functionally characterized the periplasmic substrate-binding protein MlaC, which determines the specificity of this system. The predicted structure of the S. maltophilia MlaC protein revealed a hydrophobic cavity of sufficient size to accommodate the phospholipids commonly found in this species. Moreover, recombinant MlaC produced heterologously demonstrated the ability to bind phospholipids. Gene knockout experiments in S. maltophilia K279a revealed that the Mla system is involved in baseline resistance to antimicrobial and antibiofilm agents, especially those with divalent-cation chelating activity. Co-culture experiments with Pseudomonas aeruginosa also showed a significant contribution of this system to the cooperation between both species in the formation of polymicrobial biofilms. As suggested for other Gram-negative pathogenic microorganisms, this system emerges as an appealing target for potential combined antimicrobial therapies.

Azetidines Kill Multidrug-Resistant Mycobacterium tuberculosis without Detectable Resistance by Blocking Mycolate Assembly

Tuberculosis (TB) is the leading cause of global morbidity and mortality resulting from infectious disease, with over 10.6 million new cases and 1.4 million deaths in 2021. This global emergency is exacerbated by the emergence of multidrug-resistant MDR-TB and extensively drug-resistant XDR-TB; therefore, new drugs and new drug targets are urgently required. From a whole cell phenotypic screen, a series of azetidines derivatives termed BGAz, which elicit potent bactericidal activity with MIC99 values <10 μM against drug-sensitive Mycobacterium tuberculosis and MDR-TB, were identified. These compounds demonstrate no detectable drug resistance. The mode of action and target deconvolution studies suggest that these compounds inhibit mycobacterial growth by interfering with cell envelope biogenesis, specifically late-stage mycolic acid biosynthesis. Transcriptomic analysis demonstrates that the BGAz compounds tested display a mode of action distinct from the existing mycobacterial cell wall inhibitors. In addition, the compounds tested exhibit toxicological and PK/PD profiles that pave the way for their development as antitubercular chemotherapies.

Fever-like temperature impacts on Staphylococcus aureus and Pseudomonas aeruginosa interaction, physiology, and virulence both in vitro and in vivo

BACKGROUND

Staphylococcus aureus (SA) and Pseudomonas aeruginosa (PA) cause a wide variety of bacterial infections and coinfections, showing a complex interaction that involves the production of different metabolites and metabolic changes. Temperature is a key factor for bacterial survival and virulence and within the host, bacteria could be exposed to an increment in temperature during fever development. We analyzed the previously unexplored effect of fever-like temperatures (39 °C) on S. aureus USA300 and P. aeruginosa PAO1 microaerobic mono- and co-cultures compared with 37 °C, by using RNAseq and physiological assays including in vivo experiments.

RESULTS

In general terms both temperature and co-culturing had a strong impact on both PA and SA with the exception of the temperature response of monocultured PA. We studied metabolic and virulence changes in both species. Altered metabolic features at 39 °C included arginine biosynthesis and the periplasmic glucose oxidation in S. aureus and P. aeruginosa monocultures respectively. When PA co-cultures were exposed at 39 °C, they upregulated ethanol oxidation-related genes along with an increment in organic acid accumulation. Regarding virulence factors, monocultured SA showed an increase in the mRNA expression of the agr operon and hld, pmsα, and pmsβ genes at 39 °C. Supported by mRNA data, we performed physiological experiments and detected and increment in hemolysis, staphyloxantin production, and a decrease in biofilm formation at 39 °C. On the side of PA monocultures, we observed an increase in extracellular lipase and protease and biofilm formation at 39 °C along with a decrease in the motility in correlation with changes observed at mRNA abundance. Additionally, we assessed host-pathogen interaction both in vitro and in vivo. S. aureus monocultured at 39οC showed a decrease in cellular invasion and an increase in IL-8-but not in IL-6-production by A549 cell line. PA also decreased its cellular invasion when monocultured at 39 °C and did not induce any change in IL-8 or IL-6 production. PA strongly increased cellular invasion when co-cultured at 37 and 39 °C. Finally, we observed increased lethality in mice intranasally inoculated with S. aureus monocultures pre-incubated at 39 °C and even higher levels when inoculated with co-cultures. The bacterial burden for P. aeruginosa was higher in liver when the mice were infected with co-cultures previously incubated at 39 °C comparing with 37 °C.

CONCLUSIONS

Our results highlight a relevant change in the virulence of bacterial opportunistic pathogens exposed to fever-like temperatures in presence of competitors, opening new questions related to bacteria-bacteria and host-pathogen interactions and coevolution.

16S rRNA metagenomic dataset on endophytic bacterial community of the cashew plant (Anacardium occidentale L.) grown in Dak Lak Province of Vietnam

Vietnam is currently one of the largest producers and exporters of cashew nuts in the world. Cashew (Anacardium occidentale L.) is one of the main industrial crops cultivated in Dak Lak Province of Vietnam. Comprehending the endophytic bacteria of this plant, a new biofertilizer for sustainable cashew nut production can be progressed. In this report, the cashew root sample was collected from cashew fields in 2021 in Dak Lak. The DNeasy Powersoil kit was used to extract the genomic DNA of endophytic bacteria from the root sample. The 16S rRNA genes (V1-V9 regions) were amplified by PCR, and libraries of amplicons were prepared using the Swift amplicon 16S plus ITS panel kit. The Illumina MiSeq platform was applied to sequence amplicon libraries using 16S rRNA metagenomics. Taxonomic analyses showed that Gammaproteobacteria (38.77 %) and Alphaproteobacteria (37.76 %) were the predominant classes among the endophytic bacteria. Functional analyses revealed that biosynthesis (72.78 %) was the primary function of the endophytic bacterial community. Raw sequences (Fastq files) have been deposited in Mendeley Data [1]. The obtained data provide insight into the endophytic bacterial community of cashews cultivated in Dak Lak Province of Vietnam. The data are valuable for further developing a new biofertilizer for cashew nut production using endophytic bacteria. Ours is the first report about endophytic bacterial communities of cashews cultivated in this province as well as the Central Highlands of Vietnam.

Metabolic Connectome and Its Role in the Prediction, Diagnosis, and Treatment of Complex Diseases

The interconnectivity of advanced biological systems is essential for their proper functioning. In modern connectomics, biological entities such as proteins, genes, RNA, DNA, and metabolites are often represented as nodes, while the physical, biochemical, or functional interactions between them are represented as edges. Among these entities, metabolites are particularly significant as they exhibit a closer relationship to an organism's phenotype compared to genes or proteins. Moreover, the metabolome has the ability to amplify small proteomic and transcriptomic changes, even those from minor genomic changes. Metabolic networks, which consist of complex systems comprising hundreds of metabolites and their interactions, play a critical role in biological research by mediating energy conversion and chemical reactions within cells. This review provides an introduction to common metabolic network models and their construction methods. It also explores the diverse applications of metabolic networks in elucidating disease mechanisms, predicting and diagnosing diseases, and facilitating drug development. Additionally, it discusses potential future directions for research in metabolic networks. Ultimately, this review serves as a valuable reference for researchers interested in metabolic network modeling, analysis, and their applications.

Classifying patients with psoriatic arthritis according to their disease activity status using serum metabolites and machine learning

INTRODUCTION

Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management.

OBJECTIVES

To identify metabolites capable of classifying patients with PsA according to their disease activity.

METHODS

An in-house solid-phase microextraction (SPME)-liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based on psoriatic arthritis disease activity scores (PASDAS). Metabolite data were analyzed using eight machine learning methods to predict disease activity levels. Top performing methods were selected based on area under the curve (AUC) and significance.

RESULTS

The best model for predicting high disease activity from low disease activity achieved AUC 0.818. The best model for predicting high disease activity from moderate disease activity achieved AUC 0.74. The best model for classifying low disease activity from moderate and high disease activity achieved AUC 0.765. Compounds confirmed by MS/MS validation included metabolites from diverse compound classes such as sphingolipids, phosphatidylcholines and carboxylic acids.

CONCLUSION

Several lipids and other metabolites when combined in classifying models predict high disease activity from both low and moderate disease activity. Lipids of key interest included lysophosphatidylcholine and sphingomyelin. Quantitative MS assays based on selected reaction monitoring, are required to quantify the candidate biomarkers identified.

Genome-scale metabolic network model and phenome of solvent-tolerant Pseudomonas putida S12

BACKGROUND

Pseudomonas putida S12 is a gram-negative bacterium renowned for its high tolerance to organic solvents and metabolic versatility, making it attractive for various applications, including bioremediation and the production of aromatic compounds, bioplastics, biofuels, and value-added compounds. However, a metabolic model of S12 has yet to be developed.

RESULTS

In this study, we present a comprehensive and highly curated genome-scale metabolic network model of S12 (iSH1474), containing 1,474 genes, 1,436 unique metabolites, and 2,938 metabolic reactions. The model was constructed by leveraging existing metabolic models and conducting comparative analyses of genomes and phenomes. Approximately 2,000 different phenotypes were measured for S12 and its closely related KT2440 strain under various nutritional and environmental conditions. These phenotypic data, combined with the reported experimental data, were used to refine and validate the reconstruction. Model predictions quantitatively agreed well with in vivo flux measurements and the batch cultivation of S12, which demonstrated that iSH1474 accurately represents the metabolic capabilities of S12. Furthermore, the model was simulated to investigate the maximum theoretical metabolic capacity of S12 growing on toxic organic solvents.

CONCLUSIONS

iSH1474 represents a significant advancement in our understanding of the cellular metabolism of P. putida S12. The combined results of metabolic simulation and comparative genome and phenome analyses identified the genetic and metabolic determinants of the characteristic phenotypes of S12. This study could accelerate the development of this versatile organism as an efficient cell factory for various biotechnological applications.

PathBank 2.0-the pathway database for model organism metabolomics

PathBank (https://pathbank.org) and its predecessor database, the Small Molecule Pathway Database (SMPDB), have been providing comprehensive metabolite pathway information for the metabolomics community since 2010. Over the past 14 years, these pathway databases have grown and evolved significantly to meet the needs of the metabolomics community and respond to continuing changes in computing technology. This year's update, PathBank 2.0, brings a number of important improvements and upgrades that should make the database more useful and more appealing to a larger cross-section of users. In particular, these improvements include: (i) a significant increase in the number of primary or canonical pathways (from 1720 to 6951); (ii) a massive increase in the total number of pathways (from 110 234 to 605 359); (iii) significant improvements to the quality of pathway diagrams and pathway descriptions; (iv) a strong emphasis on drug metabolism and drug mechanism pathways; (v) making most pathway images more slide-compatible and manuscript-compatible; (vi) adding tools to support better pathway filtering and selecting through a more complete pathway taxonomy; (vii) adding pathway analysis tools for visualizing and calculating pathway enrichment. Many other minor improvements and updates to the content, the interface and general performance of the PathBank website have also been made. Overall, we believe these upgrades and updates should greatly enhance PathBank's ease of use and its potential applications for interpreting metabolomics data.

Early microbial intervention reshapes phenotypes of newborn Bos taurus through metabolic regulations

BACKGROUND

The rumen of neonatal calves has limited functionality, and establishing intestinal microbiota may play a crucial role in their health and performance. Thus, we aim to explore the temporal colonization of the gut microbiome and the benefits of early microbial transplantation (MT) in newborn calves.

RESULTS

We followed 36 newborn calves for 2 months and found that the composition and ecological interactions of their gut microbiomes likely reached maturity 1 month after birth. Temporal changes in the gut microbiome of newborn calves are widely associated with changes in their physiological statuses, such as growth and fiber digestion. Importantly, we observed that MT reshapes the gut microbiome of newborns by altering the abundance and interaction of Bacteroides species, as well as amino acid pathways, such as arginine biosynthesis. Two-year follow-up of those calves further showed that MT improves their later milk production. Notably, MT improves fiber digestion and antioxidant capacity of newborns while reducing diarrhea. MT also contributes to significant changes in the metabolomic landscape, and with putative causal mediation analysis, we suggest that altered gut microbial composition in newborns may influence physiological status through microbial-derived metabolites.

CONCLUSIONS

Our study provides a metagenomic and metabolomic atlas of the temporal development of the gut microbiome in newborn calves. MT can alter the gut microbiome of newborns, leading to improved physiological status and later milk production. The data may help develop strategies to manipulate the gut microbiota during early life, which may be relevant to the health and production of newborn calves.

Maternal smoking during pregnancy increases the risk of gut microbiome-associated childhood overweight and obesity

Childhood obesity is linked to maternal smoking during pregnancy. Gut microbiota may partially mediate this association and could be potential targets for intervention; however, its role is understudied. We included 1,592 infants from the Canadian Healthy Infants Longitudinal Development Cohort. Data on environmental exposure and lifestyle factors were collected prenatally and throughout the first three years. Weight outcomes were measured at one and three years of age. Stool samples collected at 3 and 12 months were analyzed by sequencing the V4 region of 16S rRNA to profile microbial compositions and magnetic resonance spectroscopy to quantify the metabolites. We showed that quitting smoking during pregnancy did not lower the risk of offspring being overweight. However, exclusive breastfeeding until the third month of age may alleviate these risks. We also reported that maternal smoking during pregnancy significantly increased Firmicutes abundance and diversity. We further revealed that Firmicutes diversity mediates the elevated risk of childhood overweight and obesity linked to maternal prenatal smoking. This effect possibly occurs through excessive microbial butyrate production. These findings add to the evidence that women should quit smoking before their pregnancies to prevent microbiome-mediated childhood overweight and obesity risk, and indicate the potential obesogenic role of excessive butyrate production in early life.

Impact of propiconazole fungicide on soil microbiome (bacterial and fungal) diversity, functional profile, and associated dehydrogenase activity

Pesticides, protect crops but can harm the environment and human health when used without caution. This study evaluated the impact of propiconazole, a fungicide that acts on fungal cell membranes, on soil microbiome abundance, diversity, and functional profile, as well as soil dehydrogenase activity (DHA). The study conducted microcosm experiments using soil samples treated with propiconazole and employed next-generation sequencing (MiSeq) and chromatographic approaches (GC-MS/MS) to analyze the shift in microbial communities and propiconazole level, respectively. The results showed that propiconazole significantly altered the distribution of microbial communities, with notable changes in the abundance of various bacterial and fungal taxa. Among soil bacterial communities, the relative abundance of Proteobacteria and Planctomycetota increased, while that of Acidobacteria decreased after propiconazole treatment. In the fungal communities, propiconazole increased the abundance of Ascomycota and Basidiomycota in the treated soil, while that of Mortierellomycota was reduced. Fungicide application further triggered a significant decrease in DHA over time. Analysis of the functional profile of bacterial communities showed that propiconazole significantly affected bacterial cellular and metabolic pathways. The carbon degradation pathway was upregulated, indicating the microbial detoxification of the contaminant in the treated soil. Our findings suggest that propiconazole application has a discernible impact on soil microbial communities, which could have long-term consequences for soil health, quality, and function.

Comparative genomics of a vertically transmitted thiotrophic bacterial ectosymbiont and its close free-living relative

Thiotrophic symbioses between sulphur-oxidizing bacteria and various unicellular and metazoan eukaryotes are widespread in reducing marine environments. The giant colonial ciliate Zoothamnium niveum, however, is the only host of thioautotrophic symbionts that has been cultivated along with its symbiont, the vertically transmitted ectosymbiont Candidatus Thiobius zoothamnicola (short Thiobius). Because theoretical predictions posit a smaller genome in vertically transmitted endosymbionts compared to free-living relatives, we investigated whether this is true also for an ectosymbiont. We used metagenomics to recover the high-quality draft genome of this bacterial symbiont. For comparison we have also sequenced a closely related free-living cultured but not formally described strain Milos ODIII6 (short ODIII6). We then performed comparative genomics to assess the functional capabilities at gene, metabolic pathway and trait level. 16S rRNA gene trees and average amino acid identity confirmed the close phylogenetic relationship of both bacteria. Indeed, Thiobius has about a third smaller genome than its free-living relative ODIII6, with reduced metabolic capabilities and fewer functional traits. The functional capabilities of Thiobius were a subset of those of the more versatile ODIII6, which possessed additional genes for oxygen, sulphur and hydrogen utilization and for the acquisition of phosphorus illustrating features that may be adaptive for the unstable environmental conditions at hydrothermal vents. In contrast, Thiobius possesses genes potentially enabling it to utilize lactate and acetate heterotrophically, compounds that may be provided as byproducts by the host. The present study illustrates the effect of strict host-dependence of a bacterial ectosymbiont on genome evolution and host adaptation.

Meta-analysis reveals obesity associated gut microbial alteration patterns and reproducible contributors of functional shift

The majority of cohort-specific studies associating gut microbiota with obesity are often contradictory; thus, the replicability of the signature remains questionable. Moreover, the species that drive obesity-associated functional shifts and their replicability remain unexplored. Thus, we aimed to address these questions by analyzing gut microbial metagenome sequencing data to develop an in-depth understanding of obese host-gut microbiota interactions using 3329 samples (Obese, n = 1494; Control, n = 1835) from 17 different countries, including both 16S rRNA gene and metagenomic sequence data. Fecal metagenomic data from diverse geographical locations were curated, profiled, and pooled using a machine learning-based approach to identify robust global signatures of obesity. Furthermore, gut microbial species and pathways were systematically integrated through the genomic content of the species to identify contributors to obesity-associated functional shifts. The community structure of the obese gut microbiome was evaluated, and a reproducible depletion of diversity was observed in the obese compared to the lean gut. From this, we infer that the loss of diversity in the obese gut is responsible for perturbations in the healthy microbial functional repertoire. We identified 25 highly predictive species and 37 pathway associations as signatures of obesity, which were validated with remarkably high accuracy (AUC, Species: 0.85, and pathway: 0.80) with an independent validation dataset. We observed a reduction in short-chain fatty acid (SCFA) producers (several Alistipes species, Odoribacter splanchnicus, etc.) and depletion of promoters of gut barrier integrity (Akkermansia muciniphila and Bifidobacterium longum) in obese guts. Our analysis underlines SCFAs and purine/pyrimidine biosynthesis, carbohydrate metabolism pathways in control individuals, and amino acid, enzyme cofactor, and peptidoglycan biosynthesis pathway enrichment in obese individuals. We also mapped the contributors to important obesity-associated functional shifts and observed that these are both dataset-specific and shared across the datasets. In summary, a comprehensive analysis of diverse datasets unveils species specifically contributing to functional shifts and consistent gut microbial patterns associated to obesity.

Metabolomics: An Emerging "Omics" Platform for Systems Biology and Its Implications for Huntington Disease Research

Huntington's disease (HD) is a progressive, fatal neurodegenerative disease characterized by motor, cognitive, and psychiatric symptoms. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Important new strategies are of paramount importance to identify early biomarkers with predictive value for intervening in disease progression at a stage when cellular dysfunction has not progressed irreversibly. Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under certain conditions and is becoming an essential tool for the systemic characterization of metabolites to provide a snapshot of the functional and pathophysiological states of an organism and support disease diagnosis and biomarker discovery. This review briefly highlights the historical progress of metabolomic methodologies, followed by a more detailed review of the use of metabolomics in HD research to enable a greater understanding of the pathogenesis, its early prediction, and finally the main technical platforms in the field of metabolomics.

The Integral Role of Magnesium in Muscle Integrity and Aging: A Comprehensive Review

Aging is characterized by significant physiological changes, with the degree of decline varying significantly among individuals. The preservation of intrinsic capacity over the course of an individual's lifespan is fundamental for healthy aging. Locomotion, which entails the capacity for independent movement, is intricately connected with various dimensions of human life, including cognition, vitality, sensory perception, and psychological well-being. Notably, skeletal muscle functions as a pivotal nexus within this intricate framework. Any perturbation in its functionality can manifest as compromised physical performance and an elevated susceptibility to frailty. Magnesium is an essential mineral that plays a central role in approximately 800 biochemical reactions within the human body. Its distinctive physical and chemical attributes render it an indispensable stabilizing factor in the orchestration of diverse cellular reactions and organelle functions, thereby rendering it irreplaceable in processes directly impacting muscle health. This narrative review offers a comprehensive exploration of the pivotal role played by magnesium in maintaining skeletal muscle integrity, emphasizing the critical importance of maintaining optimal magnesium levels for promoting healthy aging.

Shotgun metagenomics reveals interkingdom association between intestinal bacteria and fungi involving competition for nutrients

BACKGROUND

The accuracy of internal-transcribed-spacer (ITS) and shotgun metagenomics has not been robustly evaluated, and the effect of diet on the composition and function of the bacterial and fungal gut microbiome in a longitudinal setting has been poorly investigated. Here we compared two approaches to study the fungal community (ITS and shotgun metagenomics), proposed an enrichment protocol to perform a reliable mycobiome analysis using a comprehensive in-house fungal database, and correlated dietary data with both bacterial and fungal communities.

RESULTS

We found that shotgun DNA sequencing after a new enrichment protocol combined with the most comprehensive and novel fungal databases provided a cost-effective approach to perform gut mycobiome profiling at the species level and to integrate bacterial and fungal community analyses in fecal samples. The mycobiome was significantly more variable than the bacterial community at the compositional and functional levels. Notably, we showed that microbial diversity, composition, and functions were associated with habitual diet composition instead of driven by global dietary changes. Our study indicates a potential competitive inter-kingdom interaction between bacteria and fungi for food foraging.

CONCLUSION

Together, our present work proposes an efficient workflow to study the human gut microbiome integrating robustly fungal, bacterial, and dietary data. These findings will further advance our knowledge of the interaction between gut bacteria and fungi and pave the way for future investigations in human mycobiome. Video Abstract.

Automating methods for estimating metabolite volatility

The volatility of metabolites can influence their biological roles and inform optimal methods for their detection. Yet, volatility information is not readily available for the large number of described metabolites, limiting the exploration of volatility as a fundamental trait of metabolites. Here, we adapted methods to estimate vapor pressure from the functional group composition of individual molecules (SIMPOL.1) to predict the gas-phase partitioning of compounds in different environments. We implemented these methods in a new open pipeline called volcalc that uses chemoinformatic tools to automate these volatility estimates for all metabolites in an extensive and continuously updated pathway database: the Kyoto Encyclopedia of Genes and Genomes (KEGG) that connects metabolites, organisms, and reactions. We first benchmark the automated pipeline against a manually curated data set and show that the same category of volatility (e.g., nonvolatile, low, moderate, high) is predicted for 93% of compounds. We then demonstrate how volcalc might be used to generate and test hypotheses about the role of volatility in biological systems and organisms. Specifically, we estimate that 3.4 and 26.6% of compounds in KEGG have high volatility depending on the environment (soil vs. clean atmosphere, respectively) and that a core set of volatiles is shared among all domains of life (30%) with the largest proportion of kingdom-specific volatiles identified in bacteria. With volcalc, we lay a foundation for uncovering the role of the volatilome using an approach that is easily integrated with other bioinformatic pipelines and can be continually refined to consider additional dimensions to volatility. The volcalc package is an accessible tool to help design and test hypotheses on volatile metabolites and their unique roles in biological systems.

Maternal transmission of bacterial microbiota during embryonic development in a viviparous lizard

IMPORTANCE

We investigated the presence and diversity of bacteria in the embryos of the viviparous lizard Sceloporus grammicus and their amniotic environment. We compared this diversity to that found in the maternal intestine, mouth, and cloaca. We detected bacterial DNA in the embryos, albeit with a lower bacterial species diversity than found in maternal tissues. Most of the bacterial species detected in the embryos were also found in the mother, although not all of them. Interestingly, we detected a high similarity in the composition of bacterial species among embryos from different mothers. These findings suggest that there may be a mechanism controlling the transmission of bacteria from the mother to the embryo. Our results highlight the possibility that the interaction between maternal bacteria and the embryo may affect the development of the lizards.

Review: Towards the next-generation models of the rumen microbiome for enhancing predictive power and guiding sustainable production strategies

The rumen ecosystem harbours a galaxy of microbes working in syntrophy to carry out a metabolic cascade of hydrolytic and fermentative reactions. This fermentation process allows ruminants to harvest nutrients from a wide range of feedstuff otherwise inaccessible to the host. The interconnection between the ruminant and its rumen microbiota shapes key animal phenotypes such as feed efficiency and methane emissions and suggests the potential of reducing methane emissions and enhancing feed conversion into animal products by manipulating the rumen microbiota. Whilst significant technological progress in omics techniques has increased our knowledge of the rumen microbiota and its genome (microbiome), translating omics knowledge into effective microbial manipulation strategies remains a great challenge. This challenge can be addressed by modelling approaches integrating causality principles and thus going beyond current correlation-based approaches applied to analyse rumen microbial genomic data. However, existing rumen models are not yet adapted to capitalise on microbial genomic information. This gap between the rumen microbiota available omics data and the way microbial metabolism is represented in the existing rumen models needs to be filled to enhance rumen understanding and produce better predictive models with capabilities for guiding nutritional strategies. To fill this gap, the integration of computational biology tools and mathematical modelling frameworks is needed to translate the information of the metabolic potential of the rumen microbes (inferred from their genomes) into a mathematical object. In this paper, we aim to discuss the potential use of two modelling approaches for the integration of microbial genomic information into dynamic models. The first modelling approach explores the theory of state observers to integrate microbial time series data into rumen fermentation models. The second approach is based on the genome-scale network reconstructions of rumen microbes. For a given microorganism, the network reconstruction produces a stoichiometry matrix of the metabolism. This matrix is the core of the so-called genome-scale metabolic models which can be exploited by a plethora of methods comprised within the constraint-based reconstruction and analysis approaches. We will discuss how these methods can be used to produce the next-generation models of the rumen microbiome.

DBP-FP change of biofilm in drinking water distribution system induced by sequential UV and chlorine disinfection: Effect of UV dose and influencing mechanism

The issue of biofilm-related disinfection byproducts (DBPs) in drinking water distribution system (DWDS) has garnered significant attention. This study sought to examine the changes in biofilm-originated halogenated DBP formation potential (biofilm DBP-FP) in simulated continuous-flow DWDSs subjected to sequential UV and chlorine disinfection (UV-Cl2) treatments with varying UV doses and to propose the underlying mechanism. The formation potential of trihalomethanes (THMs), haloacetic acids (HAAs), and the total organic halogen (TOX, X = Cl and Br) produced by biofilm were measured. Results showed that the biofilm TOCl-FP was at a minimum with a UV dose of 80 mJ/cm2, corresponding to the lowest amounts of protein and polysaccharides in the extracellular polymeric substances (EPS). Sphingobium, Methylobacterium, and Sphingomonas played a crucial role in protein and polysaccharide biosynthesis. Bacterial community composition characterization together with metabolic function analysis indicated that dominant bacteria varied and metabolic function shifted due to UV-Cl2 disinfection, with Alphaproteobacteria increasing in relative abundance and Bacteroidia showing the opposite trend with increasing UV doses. Correlation analysis suggested that the UV-Cl2 disinfection process led to changes in the water matrix, including organics, inorganics, bacteria, and components that provide environmental pressure for the biofilm. These changes ultimately influenced the properties of the biofilm EPS, which had a direct impact on biofilm DBP-FP.

Saposhnikovia divaricata root and its major components ameliorate inflammation and altered gut microbial diversity and compositions in DSS-induced colitis

Background

The root of Saposhnikovia divaricata (Turcz.) Schischk is a well-known traditional medicinal plant, containing various bioactive compounds with anti-inflammatory, antioxidant, and analgesic properties. However, no scientific studies have validated its clinical use as an anti-inflammatory agent against inflammatory bowel disease (IBD). This study aimed to investigate whether the root extract of S. divaricata ameliorates IBD and induces gut microbial alteration, using a RAW 264.7 cell line and a DSS-induced colitis mouse model.

Methods

To investigate the anti-inflammatory effects and alleviation of IBD, using a methanol extract of Saposhnikovia divaricata (Turcz.) Schischk. root (MESD), RAW 264.7, murine macrophages and a dextran sodium sulfate (DSS)-induced colitis mouse model were employed. 16S rRNA gene sequencing was conducted to determine the alterations in the gut microbiota of mice with DSS-induced colitis.

Results

MESD significantly decreased nitric oxide (NO) and inflammatory cytokine levels in lipopolysaccharide (LPS)-induced RAW 264.7 cells in vitro. Oral administration of MESD reduced the expression of inflammatory cytokines in the colons of mice with DSS-induced colitis. Additionally, MESD inhibited the abundance of Clostridium sensu stricto 1 and enhanced the predicted functional pathways, including l-glutamate degradation VIII (to propanoic acid). Seven compounds with anti-inflammatory properties were isolated from the MESD. Among them, 3'-O-acetylhamaudol and 3'-O-angeloylhamaudol exhibited strong anti-inflammatory effects in vitro.

Conclusion

Overall, MESD may be a potential natural product for the treatment of IBD by lowering inflammatory cytokine levels and altering gut microbiota composition.

Construction of a synthetic microbial community based on multiomics linkage technology and analysis of the mechanism of lignocellulose degradation

The efficient degradation of lignocellulose is a bottleneck for its integrated utilization. This research performed species analysis and made functional predictions in various ecosystems using multiomics coupling to construct a core synthetic microbial community with efficient lignocellulose degradation function. The synthetic microbial community was employed to degrade corn straw via solid-state fermentation. The degradation mechanisms were resolved using proteomics. The optimum culture conditions included 10% inoculum level (w/v), 4% nitrogen source ratio and a fermentation time of 23 d. Under these conditions, the degradation rates of cellulose, hemicellulose, and lignin were 34.91%, 45.94%, and 23.34%, respectively. Proteomic analysis revealed that lignin 1,4-β-xylanase, β-xylosidase and endo-1,4-β-xylanase were closely related to lignocellulose degradation. The metabolic pathways involved in lignocellulose degradation and the functional roles of eight strains were obtained. The synthesis of a microbial community via multiomics linkage technology can effectively decompose lignocellulose, which is useful for their further utilization.

Genome-scale metabolic models reveal determinants of phenotypic differences in non-Saccharomyces yeasts

BACKGROUND

Use of alternative non-Saccharomyces yeasts in wine and beer brewing has gained more attention the recent years. This is both due to the desire to obtain a wider variety of flavours in the product and to reduce the final alcohol content. Given the metabolic differences between the yeast species, we wanted to account for some of the differences by using in silico models.

RESULTS

We created and studied genome-scale metabolic models of five different non-Saccharomyces species using an automated processes. These were: Metschnikowia pulcherrima, Lachancea thermotolerans, Hanseniaspora osmophila, Torulaspora delbrueckii and Kluyveromyces lactis. Using the models, we predicted that M. pulcherrima, when compared to the other species, conducts more respiration and thus produces less fermentation products, a finding which agrees with experimental data. Complex I of the electron transport chain was to be present in M. pulcherrima, but absent in the others. The predicted importance of Complex I was diminished when we incorporated constraints on the amount of enzymatic protein, as this shifts the metabolism towards fermentation.

CONCLUSIONS

Our results suggest that Complex I in the electron transport chain is a key differentiator between Metschnikowia pulcherrima and the other yeasts considered. Yet, more annotations and experimental data have the potential to improve model quality in order to increase fidelity and confidence in these results. Further experiments should be conducted to confirm the in vivo effect of Complex I in M. pulcherrima and its respiratory metabolism.

Unraveling Connective Tissue Growth Factor as a Therapeutic Target and Assessing Kahweol as a Potential Drug Candidate in Triple-Negative Breast Cancer Treatment

Triple-negative breast cancer (TNBC) is characterized by aggressive behavior and limited treatment options, necessitating the identification of novel therapeutic targets. In this study, we investigated the clinical significance of connective tissue growth factor (CTGF) as a prognostic marker and explored the potential therapeutic effects of kahweol, a coffee diterpene molecule, in TNBC treatment. Initially, through a survival analysis on breast cancer patients from The Cancer Genome Atlas (TCGA) database, we found that CTGF exhibited significant prognostic effects exclusively in TNBC patients. To gain mechanistic insights, we performed the functional annotation and gene set enrichment analyses, revealing the involvement of CTGF in migratory pathways relevant to TNBC treatment. Subsequently, in vitro experiments using MDA-MB 231 cells, a representative TNBC cell line, demonstrated that recombinant CTGF (rCTGF) administration enhanced cell motility, whereas CTGF knockdown using CTGF siRNA resulted in reduced motility. Notably, rCTGF restored kahweol-reduced cell motility, providing compelling evidence for the role of CTGF in mediating kahweol's effects. At the molecular level, kahweol downregulated the protein expression of CTGF as well as critical signaling molecules, such as p-ERK, p-P38, p-PI3K/AKT, and p-FAK, associated with cell motility. In summary, our findings propose CTGF as a potential prognostic marker for guiding TNBC treatment and suggest kahweol as a promising antitumor compound capable of regulating CTGF expression to suppress cell motility in TNBC. These insights hold promise for the development of targeted therapies and improved clinical outcomes for TNBC patients.

Microbial community dynamics and cycling of plutonium and iron in a seasonally stratified and radiologically contaminated pond

Plutonium (Pu) cycling and mobility in the environment can be impacted by the iron cycle and microbial community dynamics. We investigated the spatial and temporal changes of the microbiome in an iron (Fe)-rich, plutonium-contaminated, monomictic reservoir (Pond B, Savannah River Site, South Carolina, USA). The microbial community composition varied with depth during seasonal thermal stratification and was strongly correlated with redox. During stratification, Fe(II) oxidizers (e.g., Ferrovum, Rhodoferax, Chlorobium) were most abundant in the hypoxic/anoxic zones, while Fe(III) reducers (e.g., Geothrix, Geobacter) dominated the deep, anoxic zone. Sulfate reducers and methanogens were present in the anoxic layer, likely contributing to iron and plutonium cycling. Multinomial regression of predicted functions/pathways identified metabolisms highly associated with stratification (within the top 5%), including iron reduction, methanogenesis, C1 compound utilization, fermentation, and aromatic compound degradation. Two sediment cores collected at the Inlet and Outlet of the pond were dominated by putative fermenters and organic matter (OM) degraders. Overall, microbiome analyses revealed the potential for three microbial impacts on the plutonium and iron biogeochemical cycles: (1) plutonium bioaccumulation throughout the water column, (2) Pu-Fe-OM-aggregate formation by Fe(II) oxidizers under microaerophilic/aerobic conditions, and (3) Pu-Fe-OM-aggregate or sediment reductive dissolution and organic matter degradation in the deep, anoxic waters.

Prebiotic potential of green banana flour: impact on gut microbiota modulation and microbial metabolic activity in a murine model

Introduction

Green banana flour can be used as a prebiotic due to its ability to promote gut health and provide several health benefits. In this study, we investigated whether feeding mice green banana flour at different doses would alter intestinal microbiota composition.

Methods

We fed C57BL/6N mice either a Low-dose (500 mg/kg/day) or High-dose (2000 mg/kg/day) of green banana flour daily for 3 weeks, and fecal samples were collected on days 0, 14, and 21 for microbiota analysis.

Results

Our results showed that the composition of intestinal microbiota was significantly altered by day 21, regardless of the dose. Notably, the consumption of green banana flour increased the presence of beneficial bacteria, including Coriobacteriaceae_UCG-002, Turicibacter, Parasutterella, Gastranaerophilales_ge, and RF39_ge. These changes in the intestinal microorganisms were accompanied by increased biological processes such as amino acid biosynthesis and secondary metabolite biosynthesis. Conversely, the consumption of green banana flour resulted in a decrease in biological processes related to carbohydrate degradation, glycerol degradation, and similar functions.

Discussion

These results emphasize the potential of green banana flour as a prebiotic that can benefit the gut microbiome.

Design and Construction of Artificial Biological Systems for One-Carbon Utilization

The third-generation (3G) biorefinery aims to use microbial cell factories or enzymatic systems to synthesize value-added chemicals from one-carbon (C1) sources, such as CO2, formate, and methanol, fueled by renewable energies like light and electricity. This promising technology represents an important step toward sustainable development, which can help address some of the most pressing environmental challenges faced by modern society. However, to establish processes competitive with the petroleum industry, it is crucial to determine the most viable pathways for C1 utilization and productivity and yield of the target products. In this review, we discuss the progresses that have been made in constructing artificial biological systems for 3G biorefineries in the last 10 years. Specifically, we highlight the representative works on the engineering of artificial autotrophic microorganisms, tandem enzymatic systems, and chemo-bio hybrid systems for C1 utilization. We also prospect the revolutionary impact of these developments on biotechnology. By harnessing the power of 3G biorefinery, scientists are establishing a new frontier that could potentially revolutionize our approach to industrial production and pave the way for a more sustainable future.