Metagenomic Analysis Reveals the Distribution of Antibiotic Resistance Genes in a Large-Scale Population of Healthy Individuals and Patients With Varied Diseases

Metagenomics reveals the potential transmission risk of resistomes from urban park environment to human

Urban parks play a significant role in urban ecosystems and are strongly associated with human health. Nevertheless, the biological contamination of urban parks - opportunistic pathogens and antibiotic resistance genes (ARGs) - has been poorly reported. Here, metagenomic and 16 S rRNA sequencing methods were used to study the distribution and assembly of opportunistic pathogens and ARGs in soil and water from nine parks in Lanzhou city, and further compared them with local human gut microbiomes to investigate the potential transmission risk. Our results revealed that the most important type of drug resistance in urban parks was multidrug resistance, with various resistance mechanisms. Approximately half of ARGs were shared between human gut and park environment, and it was noteworthy that cross-species transmission might exist among some high-risk ARGs, such as mepA and mdtE, with a significant enrichment in human gut. Metagenomic binning uncovered several bacterial genomes carrying adjacent ARGs, MGEs, and virulence genes, indicating a possibility that these genes may jointly transfer among different environments, particularly from park environment to human. Our results provided a reference point for the management of environmental pollutants in urban parks.

Gut resistome linked to sexual preference and HIV infection

BACKGROUND

People living with HIV (PLWH) are at increased risk of acquisition of multidrug resistant organisms due to higher rates of predisposing factors. The gut microbiome is the main reservoir of the collection of antimicrobial resistance determinants known as the gut resistome. In PLWH, changes in gut microbiome have been linked to immune activation and HIV-1 associated complications. Specifically, gut dysbiosis defined by low microbial gene richness has been linked to low Nadir CD4 + T-cell counts. Additionally, sexual preference has been shown to strongly influence gut microbiome composition in PLWH resulting in different Prevotella or Bacteroides enriched enterotypes, in MSM (men-who-have-sex-with-men) or no-MSM, respectively. To date, little is known about gut resistome composition in PLWH due to the scarcity of studies using shotgun metagenomics. The present study aimed to detect associations between different microbiome features linked to HIV-1 infection and gut resistome composition.

RESULTS

Using shotgun metagenomics we characterized the gut resistome composition of 129 HIV-1 infected subjects showing different HIV clinical profiles and 27 HIV-1 negative controls from a cross-sectional observational study conducted in Barcelona, Spain. Most no-MSM showed a Bacteroides-enriched enterotype and low microbial gene richness microbiomes. We did not identify differences in resistome diversity and composition according to HIV-1 infection or immune status. However, gut resistome was more diverse in MSM group, Prevotella-enriched enterotype and gut micorbiomes with high microbial gene richness compared to no-MSM group, Bacteroides-enriched enterotype and gut microbiomes with low microbial gene richness. Additionally, gut resistome beta-diversity was different according to the defined groups and we identified a set of differentially abundant antimicrobial resistance determinants based on the established categories.

CONCLUSIONS

Our findings reveal a significant correlation between gut resistome composition and various host variables commonly associated with gut microbiome, including microbiome enterotype, microbial gene richness, and sexual preference. These host variables have been previously linked to immune activation and lower Nadir CD4 + T-Cell counts, which are prognostic factors of HIV-related comorbidities. This study provides new insights into the relationship between antibiotic resistance and clinical characteristics of PLWH.

Antibiotic resistance profiles of gut microbiota across various primate species in Guangxi

Introduction

Understanding the gut microbiota and antibiotic resistance gene (ARG) profiles in non-human primates (NHPs) is crucial for evaluating their potential impact on human health and the environment.

Methods

In this study, we performed metagenomic analysis of 203 primate fecal samples, including nine NHP species and humans, to comprehensively characterize their gut microbiota and ARGs.

Results

Our study reveals the prevailing phyla in primates as Firmicutes, Bacteroidetes, Euryarchaeota, and Proteobacteria. The captive NHPs exhibited higher ARG abundance compared to their wild counterparts, with tetracycline and beta-lactam resistance genes prevailing. Notably, ARG subtypes in Trachypithecus leucocephalus (T. leucocephalus) residing in karst limestone habitats displayed a more dispersed distribution compared to other species. Interestingly, ARG profiles of NHPs clustered based on geographic location and captivity status. Co-occurrence network analysis revealed intricate correlations between ARG subtypes and bacterial taxa. Procrustes analysis unveiled a significant correlation between ARGs and microbial phylogenetic community structure. Taxonomic composition analysis further highlighted differences in microbial abundance among NHPs and humans.

Discussion

Our study underscores the impact of lifestyle and geographical location on NHP gut microbiota and ARGs, providing essential insights into the potential risks posed by NHPs to antibiotic resistance dissemination. This comprehensive analysis enhances our understanding of the interplay between NHPs and the gut resistome, offering a critical reference for future research on antibiotic resistance and host-microbe interactions.

MACI: A machine learning-based approach to identify drug classes of antibiotic resistance genes from metagenomic data

Novel methodologies are now essential for identification of antibiotic resistant pathogens in order to resist them. Here, we are presenting a model, MACI (Machine learning-based Antibiotic resistance gene-specific drug Class Identification) that can take metagenomic fragments as input and predict the drug class of antibiotic resistant genes. In our study, we trained a model using the Comprehensive Antibiotic Resistance Database, containing 5138 representative sequences across 134 drug classes. Among these classes, 23 dominated, contributing 85% of the sequence data. The model achieved an average precision of 0.8389 ± 0.0747 and recall of 0.8197 ± 0.0782 for these 23 drug classes. Additionally, it exhibited higher performance (precision and recall: 0.8817 ± 0.0540 and 0.8620 ± 0.0493) for predicting multidrug resistant classes compared to single drug resistant categories (0.7923 ± 0.0669 and 0.7737 ± 0.0794). The model also showed promising results when tested on an independent data. We then analysed these 23 drug classes to identify class-specific overlapping nucleotide patterns. Five significant drug classes, viz. "Carbapenem; cephalosporin; penam", "cephalosporin", "cephamycin", "cephalosporin; monobactam; penam; penem", and "fluoroquinolone" were identified, and their patterns aligned with the functional domains of antibiotic resistance genes. These class-specific patterns play a pivotal role in rapidly identifying drug classes with antibiotic resistance genes. Further analysis revealed that bacterial species containing these five drug classes are associated with well-known multidrug resistance properties.

Metagenomic insight into the prevalence and driving forces of antibiotic resistance genes in the whole process of three full-scale wastewater treatment plants

The spread of antibiotic resistance genes (ARGs) is an emerging global health concern, and wastewater treatment plants (WWTPs), as an essential carrier for the occurrence and transmission of ARGs, deserves more attention. Based on the Illumina NovaSeq high-throughput sequencing platform, this study conducted a metagenomic analysis of 18 samples from three full-scale WWTPs to explore the fate of ARGs in the whole process (influent, biochemical treatment, advanced treatment, and effluent) of wastewater treatment. Total 70 ARG subtypes were detected, among which multidrug, aminoglycoside, tetracycline, and macrolide ARGs were most abundant. The different treatment processes used for three WWTPs were capable of reducing ARG diversity, but did not significantly reduce ARG abundance. Compared to that by denitrification filters, the membrane bioreactor (MBR) process was advantageous in controlling the prevalence of multidrug ARGs in WWTPs. Linear discriminant analysis Effect Size (LEfSe) suggested g_Nitrospira, g_Curvibacter, and g_Mycobacterium as the key bacteria responsible for differential ARG prevalence among different WWTPs. Meanwhile, adeF, sul1, and mtrA were the persistent antibiotic resistance genes (PARGs) and played dominant roles in the prevalence of ARGs. Proteobacteria and Actinobacteria were the host bacteria of majority ARGs in WWTPs, while Pseudomonas and Nitrospira were the most crucial host bacteria influencing the dissemination of critical ARGs (e.g., adeF). In addition, microbial richness was determined to be the decisive factor affecting the diversity and abundance of ARGs in wastewater treatment processes. Overall, regulating the abundance of microorganisms and key host bacteria by selecting processes with microbial interception, such as MBR process, may be beneficial to control the prevalence of ARGs in WWTPs.

Resistome expansion in disease-associated human gut microbiomes

BACKGROUND

The resistome, the collection of antibiotic resistance genes (ARGs) in a microbiome, is increasingly recognised as relevant to the development of clinically relevant antibiotic resistance. Many metagenomic studies have reported resistome differences between groups, often in connection with disease and/or antibiotic treatment. However, the consistency of resistome associations with antibiotic- and non-antibiotic-treated diseases has not been established. In this study, we re-analysed human gut microbiome data from 26 case-control studies to assess the link between disease and the resistome.

RESULTS

The human gut resistome is highly variable between individuals both within and between studies, but may also vary significantly between case and control groups even in the absence of large taxonomic differences. We found that for diseases commonly treated with antibiotics, namely cystic fibrosis and diarrhoea, patient microbiomes had significantly elevated ARG abundances compared to controls. Disease-associated resistome expansion was found even when ARG abundance was high in controls, suggesting ongoing and additive ARG acquisition in disease-associated strains. We also found a trend for increased ARG abundance in cases from some studies on diseases that are not treated with antibiotics, such as colorectal cancer.

CONCLUSIONS

Diseases commonly treated with antibiotics are associated with expanded gut resistomes, suggesting that historical exposure to antibiotics has exerted considerable selective pressure for ARG acquisition in disease-associated strains. Video Abstract.

Captivity and geography influence the antibiotic resistome of non-human primates

INTRODUCTION

Antibiotic resistance poses a serious threat for animals and humans health worldwide. Yet a comprehensive exploration of the influence of captivity and geography on non-human primate (NPH) gut antibiotic resistance remains incomplete.

METHODS

In this study, 131 metagenomic sequencing datasets of five species of NHPs included different regions and lifestyles were selected to perform the antibiotic resistance analysis.

RESULTS

Nineteen related resistance antibiotics and 325 antibiotic resistance genes (ARGs) were obtained. A significantly higher abundance and diversity index of ARGs in the captive NHPs than in the wild was found but not for all of the samples. The biomarker-tracking of ARGs analysis identified key ARGs related to aminoglycoside resistance genes and tetracycline resistance genes.

DISCUSSION

These results suggest that captivity and geography changes associated with human activities can lead to marked changes in the ecology of the NHP gut flora ARGs.

A novel therapeutic concern: Antibiotic resistance genes in common chronic diseases

Infections caused by multidrug-resistant bacteria carrying antibiotic resistance genes pose a severe threat to global public health and human health. In clinical practice, it has been found that human gut microbiota act as a “reservoir” of antibiotic resistance genes (ARGs) since gut microbiota contain a wide variety of ARGs, and that the structure of the gut microbiome is influenced by the profile of the drug resistance genes present. In addition, ARGs can spread within and between species of the gut microbiome in multiple ways. To better understand gut microbiota ARGs and their effects on patients with chronic diseases, this article reviews the generation of ARGs, common vectors that transmit ARGs, the characteristics of gut microbiota ARGs in common chronic diseases, their impact on prognosis, the current state of treatment for ARGs, and what should be addressed in future research.

Occurrence of antibiotics and bacterial resistance genes in wastewater: resistance mechanisms and antimicrobial resistance control approaches

Antimicrobial pharmaceuticals are classified as emergent micropollutants of concern, implying that even at low concentrations, long-term exposure to the environment can have significant eco-toxicological effects. There is a lack of a standardized regulatory framework governing the permissible antibiotic content for monitoring environmental water quality standards. Therefore, indiscriminate discharge of antimicrobials at potentially active concentrations into urban wastewater treatment facilities is rampant. Antimicrobials may exert selective pressure on bacteria, leading to resistance development and eventual health consequences. The emergence of clinically important multiple antibiotic-resistant bacteria in untreated hospital effluents and wastewater treatment plants (WWTPs) has been linked to the continuous exposure of bacteria to antimicrobials. The levels of environmental exposure to antibiotics and their correlation to the evolution and spread of resistant bacteria need to be elucidated to help in the formulation of mitigation measures. This review explores frequently detected antimicrobials in wastewater and gives a comprehensive coverage of bacterial resistance mechanisms to different antibiotic classes through the expression of a wide variety of antibiotic resistance genes either inherent and/or exchanged among bacteria or acquired from the reservoir of antibiotic resistance genes (ARGs) in wastewater systems. To complement the removal of antibiotics and ARGs from WWTPs, upscaling the implementation of prospective interventions such as vaccines, phage therapy, and natural compounds as alternatives to widespread antibiotic use provides a multifaceted approach to minimize the spread of antimicrobial resistance.

Analysis of Gut Microbiota Signature and Microbe-Disease Progression Associations in Locally Advanced Non-Small Cell Lung Cancer Patients Treated With Concurrent Chemoradiotherapy

Purpose

To evaluate the association of gut microbiome signature and disease progression in locally advanced non-small cell lung cancer (LA-NSCLC) patients treated with concurrent chemoradiotherapy (CCRT) by fecal metagenome analysis.

Methods

Metagenome-wide association studies on baseline fecal samples from 18 LA-NSCLC patients before CCRT and 13 controls from healthy first-degree relatives were performed. Among the 18 LA-NSCLC patients, six patients were defined as the long progression-free survival (long-PFS) group (PFS≥11 months) while another 12 were in the short-PFS group (PFS<11 months). Alpha diversity, taxonomic composition, and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional pathways were compared between groups.

Results

The Firmicutes/Bacteroidetes value of long-PFS group was higher than those of short-PFS (p=0.073) and healthy individual groups (p=0.009). Meanwhile, long-PFS group had significantly higher diversities in Fungi, Archaea, and Viruses than short-PFS group. The KEGG pathways overrepresented in short-PFS group included fructose and mannose metabolism (p=0.028), streptomycin biosynthesis (p=0.028), acarbose and validamycin biosynthesis (p=0.013), ribosome biogenesis in eukaryotes (p=0.035), biosynthesis of vancomycin group antibiotics (p=0.004), apoptosis-fly (p=0.044), and tetracycline biosynthesis (p=0.044), while those overrepresented in long-PFS group included fatty acid biosynthesis (p=0.035), fatty acid metabolism (p=0.008), vancomycin resistance (p=0.008), longevity regulating pathway-worm (p=0.028), type II diabetes mellitus (p=0.004), and viral carcinogenesis (p=0.003). Further analysis of antibiotic resistome demonstrated that the short-PFS group had a trend with more antibiotic resistance genes than healthy control (p=0.070) and long-PFS groups (p=0.218). The vancomycin resistance sequences were significantly enriched in the long-PFS group compared to the short-PFS group (p=0.006).

Conclusions

The baseline gut microbiome composition and functionality might be associated with PFS in LA-NSCLC treated with CCRT. The outcome of CCRT might be modulated through bacterial metabolic pathways. The antibiotic resistance genes might play a role in disease progression and provide potential information on the relationship between the use of antibiotics and treatment efficacy of CCRT in LA-NSCLC.

Good microbes, bad genes? The dissemination of antimicrobial resistance in the human microbiome

A global rise in antimicrobial resistance among pathogenic bacteria has proved to be a major public health threat, with the rate of multidrug-resistant bacterial infections increasing over time. The gut microbiome has been studied as a reservoir of antibiotic resistance genes (ARGs) that can be transferred to bacterial pathogens via horizontal gene transfer (HGT) of conjugative plasmids and mobile genetic elements (the gut resistome). Advances in metagenomic sequencing have facilitated the identification of resistome modulators, including live microbial therapeutics such as probiotics and fecal microbiome transplantation that can either expand or reduce the abundances of ARG-carrying bacteria in the gut. While many different gut microbes encode for ARGs, they are not uniformly distributed across, or transmitted by, various members of the microbiome, and not all are of equal clinical relevance. Both experimental and theoretical approaches in microbial ecology have been applied to understand differing frequencies of ARG horizontal transfer between commensal microbes as well as between commensals and pathogens. In this commentary, we assess the evidence for the role of commensal gut microbes in encoding antimicrobial resistance genes, the degree to which they are shared both with other commensals and with pathogens, and the host and environmental factors that can impact resistome dynamics. We further discuss novel sequencing-based approaches for identifying ARGs and predicting future transfer events of clinically relevant ARGs from commensals to pathogens.

Association of Diet and Antimicrobial Resistance in Healthy U.S. Adults

Antimicrobial resistance (AMR) represents a significant source of morbidity and mortality worldwide, with expectations that AMR-associated consequences will continue to worsen throughout the coming decades. Since resistance to antibiotics is encoded in the microbiome, interventions aimed at altering the taxonomic composition of the gut might allow us to prophylactically engineer microbiomes that harbor fewer antibiotic resistant genes (ARGs). Diet is one method of intervention, and yet little is known about the association between diet and antimicrobial resistance. To address this knowledge gap, we examined diet using the food frequency questionnaire (FFQ; habitual diet) and 24-h dietary recalls (Automated Self-Administered 24-h [ASA24^®] tool) coupled with an analysis of the microbiome using shotgun metagenome sequencing in 290 healthy adult participants of the United States Department of Agriculture (USDA) Nutritional Phenotyping Study. We found that aminoglycosides were the most abundant and prevalent mechanism of AMR in these healthy adults and that aminoglycoside-O-phosphotransferases (aph3-dprime) correlated negatively with total calories and soluble fiber intake. Individuals in the lowest quartile of ARGs (low-ARG) consumed significantly more fiber in their diets than medium- and high-ARG individuals, which was concomitant with increased abundances of obligate anaerobes, especially from the family Clostridiaceae, in their gut microbiota. Finally, we applied machine learning to examine 387 dietary, physiological, and lifestyle features for associations with antimicrobial resistance, finding that increased phylogenetic diversity of diet was associated with low-ARG individuals. These data suggest diet may be a potential method for reducing the burden of AMR. IMPORTANCE Antimicrobial resistance (AMR) represents a considerable burden to health care systems, with the public health community largely in consensus that AMR will be a major cause of death worldwide in the coming decades. Humans carry antibiotic resistance in the microbes that live in and on us, collectively known as the human microbiome. Diet is a powerful method for shaping the human gut microbiome and may be a tractable method for lessening antibiotic resistance, and yet little is known about the relationship between diet and AMR. We examined this relationship in healthy individuals who contained various abundances of antibiotic resistance genes and found that individuals who consumed diverse diets that were high in fiber and low in animal protein had fewer antibiotic resistance genes. Dietary interventions may be useful for lessening the burden of antimicrobial resistance and might ultimately motivate dietary guidelines which will consider how nutrition can reduce the impact of infectious disease.

Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes

Type 2 diabetes (T2D) is a deficiency in how the body regulates glucose. Uncontrolled T2D will result in chronic high blood sugar levels, eventually resulting in T2D complications. These complications, such as kidney, eye, and nerve damage, are even harder to treat. Identifying individuals at high risk of developing T2D and its complications is essential for early prevention and treatment. Numerous studies have been done to identify biomarkers for T2D diagnosis and prognosis. This review focuses on recent T2D biomarker studies based on circulating nucleic acids using different omics technologies: genomics, transcriptomics, and epigenomics. Omics studies have profiled biomarker candidates from blood, urine, and other non-invasive samples. Despite methodological differences, several candidate biomarkers were reported for the risk and diagnosis of T2D, the prognosis of T2D complications, and pharmacodynamics of T2D treatments. Future studies should be done to validate the findings in larger samples and blood-based biomarkers in non-invasive samples to support the realization of precision medicine for T2D.

Microbiomes and Resistomes in Biopsy Tissue and Intestinal Lavage Fluid of Colorectal Cancer

Aim: The gut microbiome plays a crucial role in colorectal cancer (CRC) tumorigenesis, but compositions of microorganisms have been inconsistent in previous studies due to the different types of specimens. We investigated the microbiomes and resistomes of CRC patients with colonic biopsy tissue and intestinal lavage fluid (IVF). Methods: Paired samples (biopsy tissue and IVF) were collected from 20 patients with CRC, and their gut microbiomes and resistomes were measured by shotgun metagenomics. Clinical and laboratory data were recorded. Bioinformatics (KneadData, Kraken2, and FMAP) and statistical analysis were done using the R (v4.0.2) software. Results: Bacterial diversity in IVF was higher than in tissue samples, and bacterial operational taxonomic units (OTUs) were 2,757 in IVF vs. 197 in tissue. β-diversity showed distinct clusters in paired samples. The predominant bacteria in IVF were phylum Proteobacteria, while the predominant bacteria of tissue were phylum Actinobacteria. Twenty-seven representative bacteria were selected to form six bacterial clusters, which showed only Firmicutes Cluster 1, and the Bacteroidetes Cluster 1 were significantly more abundant in the IVF group than those in the tissue group (p < 0.05). The Firmicutes Cluster 2, Bacteroidetes Cluster 2, Pathogen Cluster, and Prevotella Cluster were not significantly different between IVF and tissue (p > 0.05). Correlation analysis revealed that some bacteria could have effects on metabolic and inflammatory parameters of CRC patients. A total of 1,295 antibiotic resistance genes (ARGs) were detected in the gut microbiomes, which conferred multidrug resistance, as well as resistance to tetracycline, aminoglycoside, and more. Co-occurrence patterns revealed by the network showed mainly ARG-carrying bacteria to be similar between IVF and tissue, but leading bacteria located in the hub differed between IVF and tissue. Conclusion: Heterogeneity of microbiota is particularly evident when studied with IVF and tissue samples, but bacterial clusters that have close relationships with CRC carcinogenesis are not significantly different, using IVF as an alternative to tissue for gut microbiome, and resistome assessment may be a feasible method.