Metatranscriptomics Reveals Antibiotic-Induced Resistance Gene Expression in the Murine Gut Microbiota

Composting reduces the risks of resistome in beef cattle manure at the transcriptional level

Transcriptomic evidence is needed to determine whether composting is more effective than conventional stockpiling in mitigating the risk of resistome in livestock manure. The objective of this study is to compare composting and stockpiling for their effectiveness in reducing the risk of antibiotic resistance in beef cattle manure. Samples collected from the center and the surface of full-size manure stockpiling and composting piles were subject to metagenomic and metatranscriptomic analyses. While the distinctions in resistome between stockpiled and composted manure were not evident at the DNA level, the advantages of composting over stockpiling were evident at the transcriptomic level in terms of the abundance of antibiotic resistance genes (ARGs), the number of ARG subtypes, and the prevalence of high-risk ARGs (i.e., mobile ARGs associated with zoonotic pathogens). DNA and transcript contigs show that the pathogen hosts of high-risk ARGs included Escherichia coli O157:H7 and O25b:H4, Klebsiella pneumoniae, and Salmonella enterica. Although the average daily temperatures for the entire composting pile exceeded 55°C throughout the field study, more ARG and ARG transcripts were removed at the center of the composting pile than at the surface. This work demonstrates the advantage of composting over stockpiling in reducing ARG risk in active populations in beef cattle manure.IMPORTANCEProper treatment of manure before land application is essential to mitigate the spread of antibiotic resistance in the environment. Stockpiling and composting are two commonly used methods for manure treatment. However, the effectiveness of composting in reducing antibiotic resistance in manure has been debated. This work compared the ability of these two methods to reduce the risk of antibiotic resistance in beef cattle manure. Our results demonstrate that composting reduced more high-risk resistance genes at the transcriptomic level in cattle manure than conventional stockpiling. This finding not only underscores the effectiveness of composting in reducing antibiotic resistance in manure but also highlights the importance of employing RNA analyses alongside DNA analyses.

Antibiotic resistance gene distribution in Shine Muscat grapes and health risk assessment of streptomycin residues in mice

Antibiotic residues and antibiotic resistance genes (ARGs) in fruits and vegetables pose public health risks via the food chain, attracting increased attention. Antibiotics such as streptomycin, used directly on seedless grapes or introduced into vineyard soil through organic fertilizers. However, extensive data supporting the risk assessment of antibiotic residues and resistance in these produce remains lacking. Utilizing metagenomic sequencing, we characterized Shine Muscat grape antibiotic resistome and mobile genetic elements (MGEs). Abundant MGEs and ARGs were found in grapes, with 174 ARGs on the grape surface and 32 in the fruit. Furthermore, our data indicated that soil is not the primary source of these MGEs and ARGs. Escherichia was identified as an essential carrier and potential transmitter of ARGs. In our previous study, streptomycin residue was identified in grapes. Further short-term exposure experiments in mice revealed no severe physiological or histological damage at several environment-related concentrations. However, with increased exposure, some ARGs levels in mouse gut microbes increased, indicating a potential threat to animal health. Overall, this study provides comprehensive insights into the resistance genome and potential hosts in grapes, supporting the risk assessment of antibiotic resistance in fruits and vegetables.

Differential response to prolonged amoxicillin treatment: long-term resilience of the microbiome versus long-lasting perturbations in the gut resistome

The collateral impact of antibiotics on the microbiome has attained increasing attention. However, the ecological consequences of long-term antibiotic exposure on the gut microbiome, including antibiotic resistance, are still limited. Here, we investigated long-term exposure effects to amoxicillin on the human gut microbiome and resistome. Fecal samples were collected from 20 patients receiving 3-months of amoxicillin or placebo treatment as part of a Norwegian multicenter clinical trial on chronic low back pain (AIM study). Samples were collected at baseline, last day of treatment, and 9 months after antibiotic cessation. The abundance and diversity of microbial and resistome composition were characterized using whole shotgun and functional metagenomic sequencing data. While the microbiome profiles of placebo subjects were stable over time, discernible changes in diversity and overall microbiome composition were observed after amoxicillin treatment. In particular, health-associated short-chain fatty acid producing species significantly decreased in proportion. However, these changes were short-lived as the microbiome showed overall recovery 9 months post-treatment. On the other hand, exposure to long-term amoxicillin was associated with an increase in total antimicrobial resistance gene load and diversity of antimicrobial resistance genes, with persistent changes even at 9 months post-treatment. Additionally, beta-lactam resistance was the most affected antibiotic class, suggesting a targeted response to amoxicillin, although changes at the gene level varied across individuals. Overall, our results suggest that the impact of prolonged amoxicillin exposure was more explicit and long-lasting in the fecal resistome than in microbiome composition. Such information is relevant for designing rational administration guidelines for antibiotic therapies.

A systematic review on omics data (metagenomics, metatranscriptomics, and metabolomics) in the role of microbiome in gallbladder disease

Microbiotas are the range of microorganisms (mainly bacteria and fungi) colonizing multicellular, macroscopic organisms. They are crucial for several metabolic functions affecting the health of the host. However, difficulties hamper the investigation of microbiota composition in cultivating microorganisms in standard growth media. For this reason, our knowledge of microbiota can benefit from the analysis of microbial macromolecules (DNA, transcripts, proteins, or by-products) present in various samples collected from the host. Various omics technologies are used to obtain different data. Metagenomics provides a taxonomical profile of the sample. It can also be used to obtain potential functional information. At the same time, metatranscriptomics can characterize members of a microbiome responsible for specific functions and elucidate genes that drive the microbiotas relationship with its host. Thus, while microbiota refers to microorganisms living in a determined environment (taxonomy of microorganisms identified), microbiome refers to the microorganisms and their genes living in a determined environment and, of course, metagenomics focuses on the genes and collective functions of identified microorganisms. Metabolomics completes this framework by determining the metabolite fluxes and the products released into the environment. The gallbladder is a sac localized under the liver in the human body and is difficult to access for bile and tissue sampling. It concentrates the bile produced in the hepatocytes, which drains into bile canaliculi. Bile promotes fat digestion and is released from the gallbladder into the upper small intestine in response to food. Considered sterile originally, recent data indicate that bile microbiota is associated with the biliary tract’s inflammation and carcinogenesis. The sample size is relevant for omic studies of rare diseases, such as gallbladder carcinoma. Although in its infancy, the study of the biliary microbiota has begun taking advantage of several omics strategies, mainly based on metagenomics, metabolomics, and mouse models. Here, we show that omics analyses from the literature may provide a more comprehensive image of the biliary microbiota. We review studies performed in this environmental niche and focus on network-based approaches for integrative studies.

The Spread of Antibiotic Resistance Genes In Vivo Model

Infections caused by antibiotic-resistant bacteria are a major public health threat. The emergence and spread of antibiotic resistance genes (ARGs) in the environment or clinical setting pose a serious threat to human and animal health worldwide. Horizontal gene transfer (HGT) of ARGs is one of the main reasons for the dissemination of antibiotic resistance in vitro and in vivo environments. There is a consensus on the role of mobile genetic elements (MGEs) in the spread of bacterial resistance. Most drug resistance genes are located on plasmids, and the spread of drug resistance genes among microorganisms through plasmid-mediated conjugation transfer is the most common and effective way for the spread of multidrug resistance. Experimental studies of the processes driving the spread of antibiotic resistance have focused on simple in vitro model systems, but the current in vitro protocols might not correctly reflect the HGT of antibiotic resistance genes in realistic conditions. This calls for better models of how resistance genes transfer and disseminate in vivo. The in vivo model can better mimic the situation that occurs in patients, helping study the situation in more detail. This is crucial to develop innovative strategies to curtail the spread of antibiotic resistance genes in the future. This review aims to give an overview of the mechanisms of the spread of antibiotic resistance genes and then demonstrate the spread of antibiotic resistance genes in the in vivo model. Finally, we discuss the challenges in controlling the spread of antibiotic resistance genes and their potential solutions.

Antimicrobial Resistance Profile by Metagenomic and Metatranscriptomic Approach in Clinical Practice: Opportunity and Challenge

The burden of bacterial resistance to antibiotics affects several key sectors in the world, including healthcare, the government, and the economic sector. Resistant bacterial infection is associated with prolonged hospital stays, direct costs, and costs due to loss of productivity, which will cause policy makers to adjust their policies. Current widely performed procedures for the identification of antibiotic-resistant bacteria rely on culture-based methodology. However, some resistance determinants, such as free-floating DNA of resistance genes, are outside the bacterial genome, which could be potentially transferred under antibiotic exposure. Metagenomic and metatranscriptomic approaches to profiling antibiotic resistance offer several advantages to overcome the limitations of the culture-based approach. These methodologies enhance the probability of detecting resistance determinant genes inside and outside the bacterial genome and novel resistance genes yet pose inherent challenges in availability, validity, expert usability, and cost. Despite these challenges, such molecular-based and bioinformatics technologies offer an exquisite advantage in improving clinicians’ diagnoses and the management of resistant infectious diseases in humans. This review provides a comprehensive overview of next-generation sequencing technologies, metagenomics, and metatranscriptomics in assessing antimicrobial resistance profiles.

Metatranscriptomics for the Human Microbiome and Microbial Community Functional Profiling

Shotgun metatranscriptomics (MTX) is an increasingly practical way to survey microbial community gene function and regulation at scale. This review begins by summarizing the motivations for community transcriptomics and the history of the field. We then explore the principles, best practices, and challenges of contemporary MTX workflows: beginning with laboratory methods for isolation and sequencing of community RNA, followed by informatics methods for quantifying RNA features, and finally statistical methods for detecting differential expression in a community context. In thesecond half of the review, we survey important biological findings from the MTX literature, drawing examples from the human microbiome, other (nonhuman) host-associated microbiomes, and the environment. Across these examples, MTX methods prove invaluable for probing microbe-microbe and host-microbe interactions, the dynamics of energy harvest and chemical cycling, and responses to environmental stresses. We conclude with a review of open challenges in the MTX field, including making assays and analyses more robust, accessible, and adaptable to new technologies; deciphering roles for millions of uncharacterized microbial transcripts; and solving applied problems such as biomarker discovery and development of microbial therapeutics.

Deciphering of antibiotic resistance genes (ARGs) and potential abiotic indicators for the emergence of ARGs in an interconnected lake-river-reservoir system

This study aimed to decipher the patterns of antibiotic resistance genes (ARGs) and linkages of key abiotic indicators with ARGs in an interconnected lake-river-reservoir system. The results showed that seasonal variations in the relative abundance of ARGs and mobile gene elements (MGEs) were significant (KW, p < 0.05). ARGs representative of fecal pollution and natural environment were primarily distributed in the river and reservoir, respectively. The lake, river, and reservoir shared 54.5% of ARGs subtypes, most of which are multidrug resistance genes encoding for efflux pumps. Network results showed that ARGs conferring resistance to aminoglycoside frequently co-occurred with class 1 integrons and Limnohabitans. The resistance risks were low and associated with non-corresponding ARGs, and the highest resistance risk was caused by enrofloxacin in the Dianshan Lake. Fluorescence indices derived from two methods exhibited consistent positive correlations with abundance of individual genes (i.e. aada1 and aadA2-03) as well as total aminoglycoside resistance genes (Pearson, p < 0.05). Moreover, ARGs indicators of human and animal fecal pollution showed linkages with humic-like and fulvic-like indices (Pearson, p < 0.05). The results provide novel insights into the roles of abiotic factors on indicating dynamics of ARGs in aquatic environment impacted by anthropogenic activities.

Current Trends in Experimental and Computational Approaches to Combat Antimicrobial Resistance

A multitude of factors, such as drug misuse, lack of strong regulatory measures, improper sewage disposal, and low-quality medicine and medications, have been attributed to the emergence of drug resistant microbes. The emergence and outbreaks of multidrug resistance to last-line antibiotics has become quite common. This is further fueled by the slow rate of drug development and the lack of effective resistome surveillance systems. In this review, we provide insights into the recent advances made in computational approaches for the surveillance of antibiotic resistomes, as well as experimental formulation of combinatorial drugs. We explore the multiple roles of antibiotics in nature and the current status of combinatorial and adjuvant-based antibiotic treatments with nanoparticles, phytochemical, and other non-antibiotics based on synergetic effects. Furthermore, advancements in machine learning algorithms could also be applied to combat the spread of antibiotic resistance. Development of resistance to new antibiotics is quite rapid. Hence, we review the recent literature on discoveries of novel antibiotic resistant genes though shotgun and expression-based metagenomics. To decelerate the spread of antibiotic resistant genes, surveillance of the resistome is of utmost importance. Therefore, we discuss integrative applications of whole-genome sequencing and metagenomics together with machine learning models as a means for state-of-the-art surveillance of the antibiotic resistome. We further explore the interactions and negative effects between antibiotics and microbiomes upon drug administration.

Colonization of Mice With Amoxicillin-Associated Klebsiella variicola Drives Inflammation via Th1 Induction and Treg Inhibition

β-Lactam antibiotics can increase the resistance and virulence of individual intestinal microorganisms, which may affect host physiology and health. Klebsiella, a crucial gut inhabitant, has been confirmed to be resistant to most β-lactam antibiotics and contributes to the etiology of inflammatory bowel disease (IBD). In this study, the influence of amoxicillin (AMO) on Klebsiella and its role in colitis was investigated in an antibiotic cocktail (ABx) murine model. The results suggested that a 7-day AMO treatment significantly enriched the abundance of Klebsiella and enhanced serum resistance, antibiotic resistance, and biofilm formation ability of Klebsiella variicola (K. variicola) compared to the wild-type strain in the control group mice. Colonization of mice with the AMO-associated K. variicola could induce Th1 cells and inhibit Treg differentiation to promote inflammation in ABx murine model. In addition, inoculation of AMO-associated K. variicola in dextran sodium sulfate (DSS)-induced colitis murine model mice also confirmed that K. variicola colonization exacerbated inflammation as assessed by increased TNF-α, IFN-γ, IL-17a, and disease activity (DAI) levels; decreased colon length and bodyweight; and a disrupted Th1/Treg balance. The results of our study demonstrate that AMO enhances Klebsiella virulence in mice by disrupting the T cell equilibrium to exacerbate colitis, thereby providing a reference for proper antibiotic prescription.