Charting the landscape of the environmental exposome

Toxicogenomics of glutathione S-transferase (GST) gene family members: Chemical-gene interactions and potential implications of gene deletions

A toxicogenomic analysis of GSTT1 and GSTM1 genes was performed in this study. Diseases, gene-chemical interactions, expression profiles, and biological processes associated with both genes were analyzed using data and tools from STRING and The Comparative Toxicogenomics Database. Protein interaction networks detailed the participation of Gstt1 (Mus musculus) and GSTM1 (Homo sapiens) in the detoxification of xenobiotics. Metabolism of long-chain fatty acids, glutathione and multiple xenobiotics were observed among the top-10 biological processes in GST protein networks. Different types of cancer, chromosomal aberrations, and liver damage were among the top-10 diseases/conditions associated with the genes. A diversity of environmental pollutants was listed among the top-10 chemicals acting on GSTT1 or GSTM1. In total, 167 chemicals interact with both genes. However, out of the 270 chemical agents acting on GSTT1, 103 (38.15 %) interact exclusively with this gene. Out of the 472 chemicals acting on GSTM1, 305 (64.62 %) interact exclusively with this gene. These results indicate that the GST enzyme system is not completely redundant, helping to explain why GSTT1 and GSTM1 deletions are phenotypically relevant. Most chemicals affect the expression of GSTT1 and GSTM1 in a complex manner, especially in the GSTT1 case (p = 0.013). A significantly higher percentage of chemicals increased GSTM1 expression (29.81 %) compared to GSTT1 (20.96 %, p < 0.001). In brief, GSTT1 and/or GSTM1 deletions can affect the metabolism of hundreds of xenobiotics, helping to explain why these genes influence the risk of a wide diversity of cell phenotypes and pathological conditions.

Global Geographic Patterns of Soil Microbial Degradation Potential for Polycyclic Aromatic Hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) are toxic and persistent pollutants that are widely distributed in the environment. PAHs are toxic to microorganisms and pose ecological risks. Bacteria encode enzymes for PAH degradation through specific genes, thereby mitigating PAH pollution. However, due to PAHs' complexity, information on the global degradation potential, diversity, and associated risks of PAH-degrading microbes in soils is lacking. In this study, we analyzed 121 PAH-degrading genes and selected 33 as marker genes to predict the degradation potential within the soil microbiome. By constructing a Hidden Markov Model, we identified 4990 species carrying PAH-degrading genes in 40,039 soil metagenomic assembly genomes, with Burkholderiaceae and Stellaceae emerging as high-potential degraders. We demonstrated that the candidate PAH degraders predominantly emerged in artificial soil and farmland, with significantly fewer present in extreme environments, driven by factors such as average annual rainfall, organic carbon, and human modification of terrestrial systems. Furthermore, we comprehensively quantified the potential risks of each potential host in future practical applications using three indicators (antibiotic resistance genes, virulence factors, and pathogenic bacteria). We found that the degrader Stellaceae has significant application prospects. Our research will help determine the biosynthetic potential of PAH-degrading enzymes globally and further identify potential PAH-degrading bacteria at lower risk.

Chemical Pollutant Exposure in Neurodevelopmental Disorders: Integrating Toxicogenomic and Transcriptomic Evidence to Elucidate Shared Biological Mechanisms and Developmental Signatures

Rapid industrialization has introduced a range of chemicals into the environment, posing significant risks to fetal and child brain development. Using the Comparative Toxicogenomics Database (CTD), we constructed chemical exposome frameworks for seven neurodevelopmental disorders (NDDs) and identified chemical pollutants of epidemiological concern, including air pollutants (n = 8), toxic elements (n = 14), pesticides and related compounds (n = 18), synthetic organic chemicals (n = 16), and solvents (n = 5). Gene set enrichment analysis validated and revealed significant toxicogenomic associations between these chemical pollutants and NDDs, including autism spectrum disorder (ASD) (12 pollutants, proportional reporting ratio (PRR) 3.56-7.21) and intellectual disability (ID) (9 pollutants, PRR 3.13-5.59). Functional annotation of pollutant-specific gene sets highlighted shared biological processes, such as metabolic processes (e.g., xenobiotic metabolic process, xenobiotic catabolic process, and cytochrome P450 pathway) for ASD and cognitive processes (e.g., cognition, social behavior, and synapse assembly) for ID (Bonferroni-corrected p-values < 0.05). Time trajectory analysis of developmental transcriptomic data from the BrainSpan database for ASD (275 genes) and ID (93 genes) revealed three distinct expression patterns of chemical-pollutant-associated genes-higher prenatal, postnatal, and perinatal expression-indicating common and divergent underlying mechanisms across critical windows of chemical pollutant exposure.

Exposomics: a review of methodologies, applications, and future directions in molecular medicine

The exposome is the measure of all the exposures of an individual in a lifetime and how those exposures relate to health. Exposomics is the emerging field of research to measure and study the totality of the exposome. Exposomics can assist with molecular medicine by furthering our understanding of how the exposome influences cellular and molecular processes such as gene expression, epigenetic modifications, metabolic pathways, and immune responses. These molecular alterations can aid as biomarkers for the diagnosis, disease prediction, early detection, and treatment and offering new avenues for personalized medicine. Advances in high throughput omics and other technologies as well as increased computational analytics is enabling comprehensive measurement and sophisticated analysis of the exposome to elucidate their cumulative and combined impacts on health, which can enable individuals, communities, and policymakers to create programs, policies, and protections that promote healthier environments and people. This review provides an overview of the potential role of exposomics in molecular medicine, covering its history, methodologies, current research and applications, and future directions.

Network-Based Identification of Key Toxic Compounds in Airborne Chemical Exposome

Air pollution is a leading contributor to the global disease burden. However, the complex nature of the chemicals to which humans are exposed through inhalation has obscured the identification of the key compounds responsible for diseases. Here, we develop a network topology-based framework to identify key toxic compounds in the airborne chemical exposome. Using cardiovascular diseases (CVDs) as a model disease, we found that toxic network modules of various compounds are closely linked to the modules of CVDs. The proximity of compound target modules to disease modules can indicate the extent of toxicity induced by the compounds. By integrating mass spectrometry-based external exposure concentrations and machine learning-predicted internal exposure concentrations, we established a comprehensive linkage connecting exposure to disease-related risk for the identification of toxic compounds. These findings were subsequently validated using exposure and disease data on the regional scale. This work provides an effective strategy for identifying key compounds within environmental exposomes and establishes a new paradigm for understanding the pathogenicity of air pollution.

Mycotoxin toxicity and its alleviation strategy on female mammalian reproduction and fertility

BACKGROUND

Mycotoxin, a secondary metabolite of fungus, found worldwide and concerning in crops and food, causes multiple acute and chronic toxicities. Its toxic profile includes hepatotoxicity, carcinogenicity, teratogenicity, estrogenicity, immunotoxicity, and neurotoxicity, leading to deleterious impact on human and animal health. Emerging evidence suggests that it adversely affects perinatal health and progeny by its ability to cross placental barriers.

AIM OF REVIEW

Due to its wide occurrence and potential toxicity on reproductive health, it is essential to understand the mechanisms of mycotoxin-related reproductive toxicity. This review summarizes the toxicities and mechanisms of mycotoxin on maternal and offspring reproduction among mammalian species. Approaches for effective mycotoxin alleviation are also discussed, providing strategies against mycotoxin contamination.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The profound mycotoxin toxicities in female mammalian reproduction affect follicle assembly, embryo development, and fetus growth, thereby decreasing offspring fertility. Factors from endocrine system such as hypothalamic-pituitary-gonadal axis and gut-ovarian axis, placenta ABC transporters, organelle and cytoskeleton dynamics, cell cycle control, genomic stability, and redox homeostasis are found to be closely related to mycotoxin toxicities. Approaches from physical, chemical, biological, and supplementation of natural antioxidants are discussed for the mycotoxin elimination, while their applications are not widespread. Available ways for mycotoxin and its toxicities alleviation need further study. Since a species-, time-, and dose-specific response might exist in mycotoxin toxicities, more consideration should be given to the protocols for mycotoxin toxicity studies, such as experimental animal models, exposure duration, and dosage. Specific mechanism for mycotoxin, especially form a molecular biology perspective, could be investigated with multi-omics technologies and advanced imaging techniques. Mass spectrometry with algorithms may provide more accurate exposure assessments, and it may be further helpful to identify the high-risk individuals in the future.

Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024)

BACKGROUND

Although agricultural health has gained importance, to date, much of the existing research relies on traditional epidemiological approaches that often face limitations related to sample size, geographic scope, temporal coverage, and the range of health events examined. To address these challenges, a complementary approach involves leveraging and reusing data beyond its original purpose. Administrative health databases (AHDs) are increasingly reused in population-based research and digital public health, especially for populations such as farmers, who face distinct environmental risks.

OBJECTIVE

We aimed to explore the reuse of AHDs in addressing health issues within farming populations by summarizing the current landscape of AHD-based research and identifying key areas of interest, research gaps, and unmet needs.

METHODS

We conducted a scoping review and bibliometric analysis using PubMed and Web of Science. Building upon previous reviews of AHD-based public health research, we conducted a comprehensive literature search using 72 terms related to the farming population and AHDs. To identify research hot spots, directions, and gaps, we used keyword frequency, co-occurrence, and thematic mapping. We also explored the bibliometric profile of the farming exposome by mapping keyword co-occurrences between environmental factors and health outcomes.

RESULTS

Between 1975 and April 2024, 296 publications across 118 journals, predominantly from high-income countries, were identified. Nearly one-third of these publications were associated with well-established cohorts, such as Agriculture and Cancer and Agricultural Health Study. The most frequently used AHDs included disease registers (158/296, 53.4%), electronic health records (124/296, 41.9%), insurance claims (106/296, 35.8%), population registers (95/296, 32.1%), and hospital discharge databases (41/296, 13.9%). Fifty (16.9%) of 296 studies involved >1 million participants. Although a broad range of exposure proxies were used, most studies (254/296, 85.8%) relied on broad proxies, which failed to capture the specifics of farming tasks. Research on the farming exposome remains underexplored, with a predominant focus on the specific external exposome, particularly pesticide exposure. A limited range of health events have been examined, primarily cancer, mortality, and injuries.

CONCLUSIONS

The increasing use of AHDs holds major potential to advance public health research within farming populations. However, substantial research gaps persist, particularly in low-income regions and among underrepresented farming subgroups, such as women, children, and contingent workers. Emerging issues, including exposure to per- and polyfluoroalkyl substances, biological agents, microbiome, microplastics, and climate change, warrant further research. Major gaps also persist in understanding various health conditions, including cardiovascular, reproductive, ocular, sleep-related, age-related, and autoimmune diseases. Addressing these overlooked areas is essential for comprehending the health risks faced by farming communities and guiding public health policies. Within this context, promoting AHD-based research, in conjunction with other digital data sources (eg, mobile health, social health data, and wearables) and artificial intelligence approaches, represents a promising avenue for future exploration.

Airborne antibiotics, antimicrobial resistance, and bacterial pathogens in a commercial composting facility: Transmission and exposure risk

Multiple elements associated with antimicrobial resistance in compost may escape into the air during the composting process, including antibiotic resistance genes (ARGs), human pathogenic bacteria (HPBs), and even antibiotics. Although antibiotics play a critical role in the evolution of resistance in HPBs, no information is available on airborne antibiotics in composting facilities. In this study, we systematically quantified airborne antibiotics, ARGs, and HPBs in comparison with those in compost. The burden of antibiotics in the air reached 4.17 ± 2.71 × 102 ng/g, significantly higher than that in compost. The concentration of ARGs (102 copies/g) in air also increased compared with that in compost. Concentrations of target contaminants in air were affected by temperature, organic matter, and heavy metals. Co-occurrence network analysis revealed the connectivity and complexity of antibiotics, ARGs, and HPBs were greater in air than in compost. The maximum daily antibiotic intake dose was up to 1.18 × 10-1ng/d/kg, accompanied by considerable inhalation levels of ARGs and HPBs. Our results reveal the severity of airborne antimicrobial resistance (AMR) elements in composting facilities, highlight the non-negligible amount of antibiotics and their co-existence with ARGs and HPBs, and shed light on the potential role of airborne antibiotics in the evolution of environmental AMR.

The iPhylo suite: an interactive platform for building and annotating biological and chemical taxonomic trees

Accurate and rapid taxonomic classifications are essential for systematically exploring organisms and metabolites in diverse environments. Many tools have been developed for biological taxonomic trees, but limitations apply, and a streamlined method for constructing chemical taxonomic trees is notably absent. We present the iPhylo suite (https://www.iphylo.net/), a comprehensive, automated, and interactive platform for biological and chemical taxonomic analysis. The iPhylo suite features web-based modules for the interactive construction and annotation of taxonomic trees and a stand-alone command-line interface (CLI) for local operation or deployment on high-performance computing (HPC) clusters. iPhylo supports National Center for Biotechnology Information (NCBI) taxonomy for biologicals and ChemOnt and NPClassifier for chemical classifications. The iPhylo visualization module, fully implemented in R, allows users to save progress locally and customize the underlying R code. Finally, the CLI module facilitates analysis across all hierarchical relational databases. We showcase the iPhylo suite's capabilities for visualizing environmental microbiomes, analyzing gut microbial metabolite synthesis preferences, and discovering novel correlations between microbiome and metabolome in humans and environment. Overall, the iPhylo suite is distinguished by its unified and interactive framework for in-depth taxonomic and integrative analyses of biological and chemical features and beyond.

Deep longitudinal lower respiratory tract microbiome profiling reveals genome-resolved functional and evolutionary dynamics in critical illness

The lower respiratory tract (LRT) microbiome impacts human health, especially among critically ill patients. However, comprehensive characterizations of the LRT microbiome remain challenging due to low microbial mass and host contamination. We develop a chelex100-based low-biomass microbial-enrichment method (CMEM) that enables deep metagenomic profiling of LRT samples to recover near-complete microbial genomes. We apply the method to 453 longitudinal LRT samples from 157 intensive care unit (ICU) patients in three geographically distant hospitals. We recover 120 high-quality metagenome-assembled genomes (MAGs) and associated plasmids without culturing. We detect divergent longitudinal microbiome dynamics and hospital-specific dominant opportunistic pathogens and resistomes in pneumonia patients. Diagnosed pneumonia and the ICU stay duration were associated with the abundance of specific antibiotic-resistance genes (ARGs). Moreover, CMEM can serve as a robust tool for genome-resolved analyses. MAG-based analyses reveal strain-specific resistome and virulome among opportunistic pathogen strains. Evolutionary analyses discover increased mobilome in prevailing opportunistic pathogens, highly conserved plasmids, and new recombination hotspots associated with conjugative elements and prophages. Integrative analysis with epidemiological data reveals frequent putative inter-patient strain transmissions in ICUs. In summary, we present a genome-resolved functional, transmission, and evolutionary landscape of the LRT microbiota in critically ill patients.

DNA Adductomics: A Narrative Review of Its Development, Applications, and Future

DNA adductomics is the global study of all DNA adducts and was first proposed in 2006 by the Matsuda group. Its development has been greatly credited to the advances in mass spectrometric techniques, particularly tandem and multiple-stage mass spectrometry. In fact, liquid chromatography-mass spectrometry (LC-MS)-based methods are virtually the sole technique with practicality for DNA adductomic studies to date. At present, DNA adductomics is primarily used as a tool to search for DNA adducts, known and unknown, providing evidence for exposure to exogenous genotoxins and/or for the molecular mechanisms of their genotoxicity. Some DNA adducts discovered in this way have the potential to predict cancer risks and/or to be associated with adverse health outcomes. DNA adductomics has been successfully used to identify and determine exogenous carcinogens that may contribute to the etiology of certain cancers, including bacterial genotoxins and an N-nitrosamine. Also using the DNA adductomic approach, multiple DNA adducts have been observed to show age dependence and may serve as aging biomarkers. These achievements highlight the capability and power of DNA adductomics in the studies of medicine, biological science, and environmental science. Nonetheless, DNA adductomics is still in its infancy, and great advances are expected in the future.

MASS cohort: Multicenter, longitudinal, and prospective study of the role of microbiome in severe pneumonia and host susceptibility

The MASS cohort comprises 2000 ICU patients with severe pneumonia, covering community-acquired pneumonia, hospital-acquired pneumonia, and ventilator-associated pneumonia, sourced from 19 hospitals across 10 cities in three provinces. A wide array of samples including bronchoalveolar lavage fluid, sputum, feces, and whole blood are longitudinally collected throughout patients' ICU stays. The cohort study seeks to uncover the dynamics of lung and gut microbiomes and their associations with severe pneumonia and host susceptibility, integrating deep metagenomics and transcriptomics with detailed clinical data.

Characterization of airborne endotoxin in personal exposure to fine particulate matter (PM2.5) and bioreactivity for elderly residents in Hong Kong

The heavy metals and bioreactivity properties of endotoxin in personal exposure to fine particulate matter (PM2.5) were characterized in the analysis. The average personal exposure concentrations to PM2.5 were ranged from 6.8 to 96.6 μg/m3. The mean personal PM2.5 concentrations in spring, summer, autumn, and winter were 32.1±15.8, 22.4±11.8, 35.3±11.9, and 50.2±19.9 μg/m3, respectively. There were 85 % of study targets exceeded the World Health Organization (WHO) PM2.5 threshold (24 hours). The mean endotoxin concentrations ranged from 1.086 ± 0.384-1.912 ± 0.419 EU/m3, with a geometric mean (GM) varied from 1.034 to 1.869. The concentration of iron (Fe) (0.008-1.16 μg/m3) was one of the most abundant transition metals in the samples that could affect endotoxin toxicity under Toll-Like Receptor 4 (TLR4) stimulation. In summer, the interleukin 6 (IL-6) levels showed statistically significant differences compared to other seasons. Spearman correlation analysis showed endotoxin concentrations were positively correlated with chromium (Cr) and nickel (Ni), implying possible roles as nutrients and further transport via adhering to the surface of fine inorganic particles. Mixed-effects model analysis demonstrated that Tumor necrosis factor-α (TNF-α) production was positively associated with endotoxin concentration and Cr as a combined exposure factor. The Cr contained the highest combined effect (0.205-0.262), suggesting that Cr can potentially exacerbate the effect of endotoxin on inflammation and oxidative stress. The findings will be useful for practical policies for mitigating air pollution to protect the public health of the citizens.

Selection versus transmission: Quantitative and organismic biology in antibiotic resistance

We aimed to determine the importance of selection (mostly dependent on the anthropogenic use of antimicrobials) and transmission (mostly dependent on hygiene and sanitation) as drivers of the spread of antibiotic-resistant bacterial populations. The first obstacle to estimating the relative weight of both independent variables is the lack of detailed quantitative data concerning the number of bacterial cells, potentially either pathogenic or harmless, and bacterial species exposed to antimicrobial action in the microbiotas of specific environments. The second obstacle is the difficulty of considering the relative importance of the transmission and selection exerting their combined effects on antibiotic resistance across eco-biological levels. As a consequence, advances are urgently required in quantitative biology and organismic biology of antimicrobial resistance. The absolute number of humans exposed to antibiotics and the absolute number of potentially pathogenic and commensal bacteria in their microbiomes should influence both the selection and transmission of resistant bacterial populations. The "whole Earth" microbiome, with astonishingly high numbers of bacterial cells and species, which are also exposed to anthropogenic antimicrobials in various biogeographical spaces, shapes the antibiotic resistance landscape. These biogeographical spaces influence various intensities of selection and transmission of potentially pathogenic bacteria. While waiting for more precise data, biostatistics analysis and mathematical or computational modeling can provide proxies to compare the influence of selection and transmission in resistant bacteria. In European countries with lower sanitation levels, antibiotic consumption plays a major role in increasing antibiotic resistance; however, this is not the case in countries with high sanitation levels. Although both independent variables are linked, their relative influence on the level of antibiotic resistance varies according to the particular location. Therefore, interventions directed to decrease antibiotic resistance should be designed "a la carte" for specific locations with particular ecological conditions, including sanitation facilities.

Vaginal microbiomes show ethnic evolutionary dynamics and positive selection of Lactobacillus adhesins driven by a long-term niche-specific process

The vaginal microbiome's composition varies among ethnicities. However, the evolutionary landscape of the vaginal microbiome in the multi-ethnic context remains understudied. We perform a systematic evolutionary analysis of 351 vaginal microbiome samples from 35 multi-ethnic pregnant women, in addition to two validation cohorts, totaling 462 samples from 90 women. Microbiome alpha diversity and community state dynamics show strong ethnic signatures. Lactobacillaceae have a higher ratio of non-synonymous to synonymous polymorphism and lower nucleotide diversity than non-Lactobacillaceae in all ethnicities, with a large repertoire of positively selected genes, including the mucin-binding and cell wall anchor genes. These evolutionary dynamics are driven by the long-term evolutionary process unique to the human vaginal niche. Finally, we propose an evolutionary model reflecting the environmental niches of microbes. Our study reveals the extensive ethnic signatures in vaginal microbial ecology and evolution, highlighting the importance of studying the host-microbiome ecosystem from an evolutionary perspective.

Generalized reporter score-based enrichment analysis for omics data

Enrichment analysis contextualizes biological features in pathways to facilitate a systematic understanding of high-dimensional data and is widely used in biomedical research. The emerging reporter score-based analysis (RSA) method shows more promising sensitivity, as it relies on P-values instead of raw values of features. However, RSA cannot be directly applied to multi-group and longitudinal experimental designs and is often misused due to the lack of a proper tool. Here, we propose the Generalized Reporter Score-based Analysis (GRSA) method for multi-group and longitudinal omics data. A comparison with other popular enrichment analysis methods demonstrated that GRSA had increased sensitivity across multiple benchmark datasets. We applied GRSA to microbiome, transcriptome and metabolome data and discovered new biological insights in omics studies. Finally, we demonstrated the application of GRSA beyond functional enrichment using a taxonomy database. We implemented GRSA in an R package, ReporterScore, integrating with a powerful visualization module and updatable pathway databases, which is available on the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/ReporterScore). We believe that the ReporterScore package will be a valuable asset for broad biomedical research fields.

Longitudinal Mapping of Personal Biotic and Abiotic Exposomes and Transcriptome in Underwater Confined Space Using Wearable Passive Samplers

Silicone-based passive samplers, commonly paired with gas chromatography-mass spectrometry (GC-MS) analysis, are increasingly utilized for personal exposure assessments. However, its compatibility with the biotic exposome remains underexplored. In this study, we introduce the wearable silicone-based AirPie passive sampler, coupled with nontargeted liquid chromatography with high-resolution tandem mass spectrometry (LC-HRMS/MS), GC-HRMS, and metagenomic shotgun sequencing methods, offering a comprehensive view of personalized airborne biotic and abiotic exposomes. We applied the AirPie samplers to 19 participants in a unique deep underwater confined environment, annotating 4,390 chemical and 2,955 microbial exposures, integrated with corresponding transcriptomic data. We observed significant shifts in environmental exposure and gene expression upon entering this unique environment. We noted increased exposure to pollutants, such as benzenoids, polycyclic aromatic hydrocarbons (PAHs), opportunistic pathogens, and associated antibiotic-resistance genes (ARGs). Transcriptomic analyses revealed the activation of neurodegenerative disease-related pathways, mostly related to chemical exposure, and the repression of immune-related pathways, linked to both biological and chemical exposures. In summary, we provided a comprehensive, longitudinal exposome map of the unique environment and underscored the intricate linkages between external exposures and human health. We believe that the AirPie sampler and associated analytical methods will have broad applications in exposome and precision medicine.

Mood Disorders: The Gut Bacteriome and Beyond

Knowledge of the microbiome-gut-brain axis has revolutionized the field of psychiatry. It is now well recognized that the gut bacteriome is associated with, and likely influences, the pathogenesis of mental disorders, including major depressive disorder and bipolar disorder. However, while substantial advances in the field of microbiome science have been made, we have likely only scratched the surface in our understanding of how these ecosystems might contribute to mental disorder pathophysiology. Beyond the gut bacteriome, research into lesser explored components of the gut microbiome, including the gut virome, mycobiome, archaeome, and parasitome, is increasingly suggesting relevance in psychiatry. The contribution of microbiomes beyond the gut, including the oral, lung, and small intestinal microbiomes, to human health and pathology should not be overlooked. Increasing both our awareness and understanding of these less traversed fields of research are critical to improving the therapeutic benefits of treatments targeting the gut microbiome, including fecal microbiome transplantation, postbiotics and biogenics, and dietary intervention. Interdisciplinary collaborations integrating systems biology approaches are required to fully elucidate how these different microbial components and distinct microbial niches interact with each other and their human hosts. Excitingly, we may be at the start of the next microbiome revolution and thus one step closer to informing the field of precision psychiatry to improve outcomes for those living with mental illness.

From mechanism to application: Decrypting light-regulated denitrifying microbiome through geometric deep learning

Regulation on denitrifying microbiomes is crucial for sustainable industrial biotechnology and ecological nitrogen cycling. The holistic genetic profiles of microbiomes can be provided by meta-omics. However, precise decryption and further applications of highly complex microbiomes and corresponding meta-omics data sets remain great challenges. Here, we combined optogenetics and geometric deep learning to form a discover-model-learn-advance (DMLA) cycle for denitrification microbiome encryption and regulation. Graph neural networks (GNNs) exhibited superior performance in integrating biological knowledge and identifying coexpression gene panels, which could be utilized to predict unknown phenotypes, elucidate molecular biology mechanisms, and advance biotechnologies. Through the DMLA cycle, we discovered the wavelength-divergent secretion system and nitrate-superoxide coregulation, realizing increasing extracellular protein production by 83.8% and facilitating nitrate removal with 99.9% enhancement. Our study showcased the potential of GNNs-empowered optogenetic approaches for regulating denitrification and accelerating the mechanistic discovery of microbiomes for in-depth research and versatile applications.

Probiotics and Fecal Microbiota Transplantation in Major Depression: Doxa or Episteme?

In the human body, eukaryotic somatic cells and prokaryotic microorganisms live together. In this state, the body can be viewed as a "superorganism." Symbiotic life with commensal microorganisms can be observed in almost every part of the body. Intestinal microbiota plays an important role in health and disease, and in shaping and regulating neuronal functions from the intrauterine period to the end of life. Microbiota-based treatment opportunities are becoming more evident in both understanding the etiopathogenesis and treatment of neuropsychiatric disorders, especially depression. Antidepressant drugs, which are the first choice in the treatment of depression, also have antimicrobial and immunomodulatory mechanisms of action. From these perspectives, direct probiotics and fecal microbiota transplantation are treatment options to modulate microbiota composition. There are few preclinical and clinical studies on the effectiveness and safety of these applications in depression. The information obtained from these studies may still be at a doxa level. However, the probability that this information will become episteme in the future seems to be increasing.

Dynamic human exposure to airborne bacteria-associated antibiotic resistomes revealed by longitudinal personal monitoring data

Airborne antibiotic-resistant bacteria (ARB) can critically impact human health. We performed resistome profiling of 283 personal airborne exposure samples from 15 participants spanning 890 days and 66 locations. We found a greater diversity and abundance of airborne bacteria community and antibiotic resistomes in spring than in winter, and temperature contributed largely to the difference. A total of 1123 bacterial genera were detected, with 16 genera dominating. Of which, 7/16 were annotated as major antibiotic resistance gene (ARG) hosts. The participants were exposed to a highly dynamic collection of ARGs, including 322 subtypes conferring resistance to 18 antibiotic classes dominated by multidrug, macrolide-lincosamide-streptogramin, β-lactam, and fosfomycin. Unlike the overall community-level bacteria exposure, an extremely high abundance of specific ARG subtypes, including lunA and qacG, were found in some samples. Staphylococcus was the predominant genus in the bacterial community, serving as a primary bacterial host for the ARGs. The annotation of ARG-carrying contigs indicated that humans and companion animals were major reservoirs for ARG-carrying Staphylococcus. This study contextualized airborne antibiotic resistomes in the precision medicine framework through longitudinal personal monitoring, which can have broad implications for human health.

Pet cats may shape the antibiotic resistome of their owner's gut and living environment

BACKGROUND

Companion animals can contribute to the physical and mental health of people and often live in very close association with their owners. However, the antibiotic resistome carried by companion animals and the impact they have on their owners and living environment remain unclear. In this study, we compared the ARG profiles of cats, humans, and their living environments using metagenomic analysis to identify the core ARGs in the cat and human gut and explore the potential impact of cats on ARGs in the human gut through the environment.

RESULTS

Results showed that the abundance of ARGs in the cat gut was significantly higher than that in the human gut (P < 0.0001), with aminoglycoside and tetracycline resistance genes being the dominant ARGs in the cat gut. There was no significant difference in the abundance of total ARGs in the guts of cat owners and non-owners (P > 0.05). However, the abundance of aminoglycoside resistance genes including APH(2'')-IIa and AAC(6')-Im was significantly higher in cat owners than that in non-cat owners (P < 0.001). Also, ARG abundance was positively correlated with the frequency of cat activity in the living environment. Enterobacteriaceae was the dominant ARG host co-occurring in the cat gut, human gut, and living environment.

CONCLUSIONS

Our results show that cats may shape the living environment resistome and thus the composition of some ARGs in the human gut, highlighting the importance of companion animal environment health. Video Abstract.

High-sensitivity profiling of SARS-CoV-2 noncoding region-host protein interactome reveals the potential regulatory role of negative-sense viral RNA

A deep understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-host interactions is crucial to developing effective therapeutics and addressing the threat of emerging coronaviruses. The role of noncoding regions of viral RNA (ncrRNAs) has yet to be systematically scrutinized. We developed a method using MS2 affinity purification coupled with liquid chromatography-mass spectrometry and designed a diverse set of bait ncrRNAs to systematically map the interactome of SARS-CoV-2 ncrRNA in Calu-3, Huh7, and HEK293T cells. Integration of the results defined the core ncrRNA-host protein interactomes among cell lines. The 5' UTR interactome is enriched with proteins in the small nuclear ribonucleoproteins family and is a target for the regulation of viral replication and transcription. The 3' UTR interactome is enriched with proteins involved in the stress granules and heterogeneous nuclear ribonucleoproteins family. Intriguingly, compared with the positive-sense ncrRNAs, the negative-sense ncrRNAs, especially the negative-sense of 3' UTR, interacted with a large array of host proteins across all cell lines. These proteins are involved in the regulation of the viral production process, host cell apoptosis, and immune response. Taken together, our study depicts the comprehensive landscape of the SARS-CoV-2 ncrRNA-host protein interactome and unveils the potential regulatory role of the negative-sense ncrRNAs, providing a new perspective on virus-host interactions and the design of future therapeutics. Given the highly conserved nature of UTRs in positive-strand viruses, the regulatory role of negative-sense ncrRNAs should not be exclusive to SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic affecting millions of lives. During replication and transcription, noncoding regions of the viral RNA (ncrRNAs) may play an important role in the virus-host interactions. Understanding which and how these ncrRNAs interact with host proteins is crucial for understanding the mechanism of SARS-CoV-2 pathogenesis. We developed the MS2 affinity purification coupled with liquid chromatography-mass spectrometry method and designed a diverse set of ncrRNAs to identify the SARS-CoV-2 ncrRNA interactome comprehensively in different cell lines and found that the 5' UTR binds to proteins involved in U1 small nuclear ribonucleoprotein, while the 3' UTR interacts with proteins involved in stress granules and the heterogeneous nuclear ribonucleoprotein family. Interestingly, negative-sense ncrRNAs showed interactions with a large number of diverse host proteins, indicating a crucial role in infection. The results demonstrate that ncrRNAs could serve diverse regulatory functions.