Development of the oral resistome during the first decade of life

Gut resistome of NSCLC patients treated with immunotherapy

Background

The newest method of treatment for patients with NSCLC (non-small cell lung cancer) is immunotherapy directed at the immune checkpoints PD-1 (Programmed Cell Death 1) and PD-L1 (Programmed Cell Death Ligand 1). PD-L1 is the only validated predictor factor for immunotherapy efficacy, but it is imperfect. Some patients do not benefit from immunotherapy and may develop primary or secondary resistance. This study aimed to assess the intestinal resistome composition of non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors in the context of clinical features and potentially new prediction factors for assessing immunotherapy efficacy.

Methods

The study included 30 advanced NSCLC patients, 19 (57%) men and 11 (33%) women treated with first- or second-line immunotherapy (nivolumab, pembrolizumab or atezolizumab). We evaluated the patient's gut resistome composition using the high sensitivity of targeted metagenomics.

Results

Studies have shown that resistome richness is associated with clinical and demographic factors of NSCLC patients treated with immunotherapy. Smoking seems to be associated with an increased abundance of macrolides, lincosamides, streptogramins and vancomycin core resistome. The resistome of patients with progression disease appears to be more abundant and diverse, with significantly higher levels of genomic markers of resistance to lincosamides (lnuC). The resistance genes lnuC, msrD, ermG, aph(6), fosA were correlated with progression-free survival or/and overall survival, thus may be considered as factors potentially impacting the disease.

Conclusion

The results indicate that the intestinal resistome of NSCLC patients with immune checkpoint inhibitors treatment differs depending on the response to immunotherapy, with several distinguished markers. Since it might impact treatment efficacy, it must be examined more deeply.

Mapping the oral resistome: a systematic review

Studying individual ecological niches within the oral cavity is a logical first step to understanding the distribution of antimicrobial resistance genes (ARGs); however, it is not representative of the whole oral resistome. The aim of our systematic review was to provide a map of the oral resistome by reviewing the composition of individual niches. A total of 580 papers were retrieved from a search of all English language publications investigating the presence of oral ARGs in five electronic databases between January 2015 and August 2023. Fifteen studies [10 PCR and 5 next-generation sequencing (NGS)] were included in this review. The heterogeneity of methods precluded meta-analysis. ARGs are present throughout the oral cavity with 158 unique ARGs identified across 6 locations - supra and sub-gingival biofilm, mucosa, oropharynx, root canal system (RCS) and saliva. The supragingival biofilm had the highest resistome richness, while the RCS had the least. Tetracycline was the dominant antimicrobial resistance (AMR) class found. Three core genes were identified - tet(M), tet(O) and ermB.This review highlights the necessity of NGS studies to comprehensively characterize the oral resistome in its entirety. This is the logical foundation for future 'omics studies to truly understand the scope of the resistome and its contribution to AMR.

Impact of cell lysis treatment before saliva metagenomic DNA extraction on the oral microbiome and the associated resistome

OBJECTIVES

The human oral microbiome, a complex ecosystem linked to oral and systemic health, harbors a diverse array of microbial populations, including antimicrobial resistance genes (ARGs). As a critical component of the One Health approach to tackle antibiotic resistance, comprehending the oral resistome's composition and diversity is imperative. The objective of this study was to investigate the impact of chemical cell lysis treatment using MetaPolyzyme on the detectability of the oral microbiome, resistome, and DNA quality and quantity.

MATERIALS AND METHODS

Saliva samples were collected from five healthy individuals, and each of the samples was subjected to DNA extraction with and without the treatment with MetaPolyzyme. Through metagenomic sequencing, we analyzed, assessed, and compared the microbial composition, resistome, and DNA characteristics between both groups of extracted DNA.

RESULTS

Our study revealed that MetaPolyzyme treatment led to significant shifts in the detectability of microbial composition, favoring Gram-positive bacteria, notably Streptococcus, over Gram-negative counterparts. Moreover, the MetaPolyzyme treatment also resulted in a distinct change in ARG distribution. This shift was characterized by an elevated proportion of ARGs linked to fluoroquinolones and efflux pumps, coupled with a reduction in the prevalence of tetracycline and β-lactam resistance genes when compared with the nontreated group. Alpha diversity analysis demonstrated altered species and ARG distribution without affecting overall diversity, while beta diversity analysis confirmed significant differences in the taxonomical composition and oral resistome between treated and nontreated groups.

CONCLUSIONS

These findings underscore the critical role of cell lysis treatment in optimizing oral metagenomic studies and enhance our understanding of the oral resistome's dynamics in the context of antimicrobial resistance.

Prolonged hospitalization signature and early antibiotic effects on the nasopharyngeal resistome in preterm infants

Respiratory pathogens, commonly colonizing nasopharynx, are among the leading causes of death due to antimicrobial resistance. Yet, antibiotic resistance determinants within nasopharyngeal microbial communities remain poorly understood. In this prospective cohort study, we investigate the nasopharynx resistome development in preterm infants, assess early antibiotic impact on its trajectory, and explore its association with clinical covariates using shotgun metagenomics. Our findings reveal widespread nasopharyngeal carriage of antibiotic resistance genes (ARGs) with resistomes undergoing transient changes, including increased ARG diversity, abundance, and composition alterations due to early antibiotic exposure. ARGs associated with the critical nosocomial pathogen Serratia marcescens persist up to 8-10 months of age, representing a long-lasting hospitalization signature. The nasopharyngeal resistome strongly correlates with microbiome composition, with inter-individual differences and postnatal age explaining most of the variation. Our report on the collateral effects of antibiotics and prolonged hospitalization underscores the urgency of further studies focused on this relatively unexplored reservoir of pathogens and ARGs.

Leveraging genomic signatures of oral microbiome-associated antibiotic resistance genes for diagnosing pancreatic cancer

Growing evidence has increasingly suggested a potential linkage between the oral microbiome and various diseases, including pancreatic ductal adenocarcinoma (PDAC). However, the utilization of gene-level information derived from the oral microbiome for diagnosing PDAC remains unexplored. In this study, we sought to investigate the novel potential of leveraging genomic signatures associated with antibiotic resistance genes (ARGs) within the oral microbiome for the diagnosis of PDAC. By conducting an analysis of oral microbiome samples obtained from PDAC patients, we successfully identified specific ARGs that displayed distinct sequence abundance profiles correlated with the presence of PDAC. In the healthy group, three ARGs were found to be enriched, whereas 21 ARGs were enriched in PDAC patients. Remarkably, these ARGs from oral microbiome exhibited promising diagnostic capabilities for PDAC (AUROC = 0.79), providing a non-invasive and early detection method. Our findings not only provide novel modal data for diagnosing PDAC but also shed light on the intricate interplay between the oral microbiome and PDAC.

Lipid Metabolites as Potential Regulators of the Antibiotic Resistome in Tetramorium caespitum

Antibiotic resistance genes (ARGs) are ancient but have become a modern critical threat to health. Gut microbiota, a dynamic reservoir for ARGs, transfer resistance between individuals. Surveillance of the antibiotic resistome in the gut during different host growth phases is critical to understanding the dynamics of the resistome in this ecosystem. Herein, we disentangled the ARG profiles and the dynamic mechanism of ARGs in the egg and adult phases of Tetramorium caespitum. Experimental results showed a remarkable difference in both gut microbiota and gut resistome with the development of T. caespitum. Meta-based metagenomic results of gut microbiota indicated the generalizability of gut antibiotic resistome dynamics during host development. By using Raman spectroscopy and metabolomics, the metabolic phenotype and metabolites indicated that the biotic phase significantly changed lipid metabolism as T. caespitum aged. Lipid metabolites were demonstrated as the main factor driving the enrichment of ARGs in T. caespitum. Cuminaldehyde, the antibacterial lipid metabolite that displayed a remarkable increase in the adult phase, was demonstrated to strongly induce ARG abundance. Our findings show that the gut resistome is host developmental stage-dependent and likely modulated by metabolites, offering novel insights into possible steps to reduce ARG dissemination in the soil food chain.

Oral microbiota, co-evolution, and implications for health and disease: The case of indigenous peoples

Evidence indicates that oral microbiota plays a crucial role in human health and disease. For instance, diseases with multifactorial etiology, such as periodontitis and caries, which cause a detrimental impact on human well-being and health, can be caused by alterations in the host-microbiota interactions, where non-pathogenic bacteria give way to pathogenic orange/red-complex bacterial species (a change from a eubiotic to dysbiotic state). In this scenario, where thousands of oral microorganisms, including fungi, archaea, and phage species, and their host are co-evolving, a set of phenomena, such as the arms race and Red or Black Queen dynamics, are expected to operate. We review concepts on the subject and revisit the nature of bacterial complexes linked to oral health and diseases, as well as the problem of the bacterial resistome in the face of the use of antibiotics and what is the impact of this on the evolutionary trajectory of the members of this symbiotic ecosystem. We constructed a 16SrRNA tree to show that adaptive consortia of oral bacterial complexes do not necessarily rescue phylogenetic relationships. Finally, we remember that oral health is not exempt from health disparity trends in some populations, such as Native Americans, when compared with non-Indigenous people.

The antibiotic resistance reservoir of the lung microbiome expands with age in a population of critically ill patients

Antimicrobial resistant lower respiratory tract infections are an increasing public health threat and an important cause of global mortality. The lung microbiome can influence susceptibility of respiratory tract infections and represents an important reservoir for exchange of antimicrobial resistance genes. Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene burden, however, corollary studies in the lung microbiome remain absent. We performed an observational study of children and adults with acute respiratory failure admitted to the intensive care unit. From tracheal aspirate RNA sequencing data, we evaluated age-related differences in detectable antimicrobial resistance gene expression in the lung microbiome. Using a multivariable logistic regression model, we find that detection of antimicrobial resistance gene expression was significantly higher in adults compared with children after adjusting for demographic and clinical characteristics. This association remained significant after additionally adjusting for lung bacterial microbiome characteristics, and when modeling age as a continuous variable. The proportion of adults expressing beta-lactam, aminoglycoside, and tetracycline antimicrobial resistance genes was higher compared to children. Together, these findings shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

Rapid Detection of Antimicrobial Resistance Genes in Critically Ill Children Using a Custom TaqMan Array Card

Bacteria are identified in only 22% of critically ill children with respiratory infections treated with antimicrobial therapy. Once an organism is isolated, antimicrobial susceptibility results (phenotypic testing) can take another day. A rapid diagnostic test identifying antimicrobial resistance (AMR) genes could help clinicians make earlier, informed antimicrobial decisions. Here we aimed to validate a custom AMR gene TaqMan Array Card (AMR-TAC) for the first time and assess its feasibility as a screening tool in critically ill children. An AMR-TAC was developed using a combination of commercial and bespoke targets capable of detecting 23 AMR genes. This was validated using isolates with known phenotypic resistance. The card was then tested on lower respiratory tract and faecal samples obtained from mechanically ventilated children in a single-centre observational study of respiratory infection. There were 82 children with samples available, with a median age of 1.2 years. Major comorbidity was present in 29 (35%) children. A bacterial respiratory pathogen was identified in 13/82 (16%) of children, of which 4/13 (31%) had phenotypic AMR. One AMR gene was detected in 49/82 (60%), and multiple AMR genes were detected in 14/82 (17%) children. Most AMR gene detections were not associated with the identification of phenotypic AMR. AMR genes are commonly detected in samples collected from mechanically ventilated children with suspected respiratory infections. AMR-TAC may have a role as an adjunct test in selected children in whom there is a high suspicion of antimicrobial treatment failure.

The antibiotic resistance reservoir of the lung microbiome expands with age

Antimicrobial resistant lower respiratory tract infections (LRTI) are an increasing public health threat, and an important cause of global mortality. The lung microbiome influences LRTI susceptibility and represents an important reservoir for exchange of antimicrobial resistance genes (ARGs). Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene (ARG) burden, however corollary studies in the lung microbiome remain absent, despite the respiratory tract representing one of the most clinically significant sites for drug resistant infections. We performed a prospective, multicenter observational study of 261 children and 88 adults with acute respiratory failure, ranging in age from 31 days to ≥ 89 years, admitted to intensive care units in the United States. We performed RNA sequencing on tracheal aspirates collected within 72 hours of intubation, and evaluated age-related differences in detectable ARG expression in the lung microbiome as a primary outcome. Secondary outcomes included number and classes of ARGs detected, proportion of patients with an ARG class, and composition of the lung microbiome. Multivariable logistic regression models (adults vs children) or continuous age (years) were adjusted for sex, race/ethnicity, LRTI status, and days from intubation to specimen collection. Detection of ARGs was significantly higher in adults compared with children after adjusting for sex, race/ethnicity, LRTI diagnosis, and days from intubation to specimen collection (adjusted odds ratio (aOR): 2.16, 95% confidence interval (CI): 1.10-4.22). A greater proportion of adults compared with children had beta-lactam ARGs (31% (CI: 21-41%) vs 13% (CI: 10-18%)), aminoglycoside ARGs (20% (CI: 13-30%) vs 2% (CI: 0.6-4%)), and tetracycline ARGs (14% (CI: 7-23%) vs 3% (CI: 1-5%)). Adults ≥70 years old had the highest proportion of these three ARG classes. The total bacterial abundance of the lung microbiome increased with age, and microbiome alpha diversity varied with age. Taxonomic composition of the lung microbiome, measured by Bray Curtis dissimilarity index, differed between adults and children (p = 0.003). The association between age and increased ARG detection remained significant after additionally including lung microbiome total bacterial abundance and alpha diversity in the multivariable logistic regression model (aOR: 2.38, (CI: 1.25-4.54)). Furthermore, this association remained robust when modeling age as a continuous variable (aOR: 1.02, (CI: 1.01-1.03) per year of age). Taken together, our results demonstrate that age is an independent risk factor for ARG detection in the lower respiratory tract microbiome. These data shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

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.

Feature selection with a genetic algorithm can help improve the distinguishing power of microbiota information in monozygotic twins' identification

INTRODUCTION

Personal identification of monozygotic twins (MZT) has been challenging in forensic genetics. Previous research has demonstrated that microbial markers have potential value due to their specificity and long-term stability. However, those studies would use the complete information of detected microbial communities, and low-value species would limit the performance of previous models.

METHODS

To address this issue, we collected 80 saliva samples from 10 pairs of MZTs at four different time points and used 16s rRNA V3-V4 region sequencing to obtain microbiota information. The data formed 280 inner-individual (Self) or MZT sample pairs, divided into four groups based on the individual relationship and time interval, and then randomly divided into training and testing sets with an 8:2 ratio. We built 12 identification models based on the time interval ( ≤ 1 year or ≥ 2 months), data basis (Amplicon sequence variants, ASVs or Operational taxonomic unit, OTUs), and distance parameter selection (Jaccard distance, Bray-Curist distance, or Hellinger distance) and then improved their identification power through genetic algorithm processes. The best combination of databases with distance parameters was selected as the final model for the two types of time intervals. Bayes theory was introduced to provide a numerical indicator of the evidence's effectiveness in practical cases.

RESULTS

From the 80 saliva samples, 369 OTUs and 1130 ASVs were detected. After the feature selection process, ASV-Jaccard distance models were selected as the final models for the two types of time intervals. For short interval samples, the final model can completely distinguish MZT pairs from Self ones in both training and test sets.

DISCUSSION

Our findings support the microbiota solution to the challenging MZT identification problem and highlight the importance of feature selection in improving model performance.

Deciphering the dynamics of metal and antibiotic resistome profiles under different metal(loid) contamination levels

Metal(loid) contaminations pose considerable threats to ecological security and public health, yet little is known about the dynamics of metal resistance genes (MRGs) and antibiotic resistance genes (ARGs) under different metal(loid) contamination levels. Here, we provided a systematic investigation of MRGs and ARGs in three zones (Zones I, II, and III) with different metal(loid) contamination levels across an abandoned sewage reservoir. More diverse MRGs and ARGs were detected from the high-contaminated Zone I and the moderate-contaminated Zone II, while the abundant MGEs (mobile genetic elements) potentially enhanced the horizontal gene transfer potential and the resistome diversity in Zone I. Particularly, resistome hosts represented by Thiobacillus, Ramlibacter, and Dyella were prevalent in Zone II, promoting the vertical gene transfer of MRGs and ARGs. The highest health risk of ARGs was predicted for Zone I (about 7.58% and 0.48% of ARGs classified into Rank I and Rank II, respectively), followed by Zone II (2.11% and 0%) and Zone III (0% and 0%). However, the ARGs co-occurring with MRGs might exhibit low proportions and low health risks (all were Rank IV) in the three zones. Overall, these findings uncovered the dynamic responses of resistomes and their hosts to different metal(loid) contamination levels, contributing to formulating accurate management and bioremediation countermeasures for various metal(loid) contaminated environments.