scholarly journals Contributions and Challenges of High Throughput qPCR for Determining Antimicrobial Resistance in the Environment: A Critical Review

Molecules ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 163 ◽  
Author(s):  
Hassan Waseem ◽  
Sana Jameel ◽  
Jafar Ali ◽  
Hamza Saleem Ur Rehman ◽  
Isfahan Tauseef ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
High Throughput ◽  
Point Of Care ◽  
Meta Analysis ◽  
Current Status ◽  
Rrna Gene ◽  
Environmental Matrices ◽  
Subsequent Increase ◽  
Detection Frequency ◽  
Antimicrobial Resistance Genes

Expansion in whole genome sequencing and subsequent increase in antibiotic resistance targets have paved the way of high throughput qPCR (HT-qPCR) for analyzing hundreds of antimicrobial resistance genes (ARGs) in a single run. A meta-analysis of 51 selected studies is performed to evaluate ARGs abundance trends over the last 7 years. WaferGenTM SmartChip is found to be the most widely used HT-qPCR platform among others for evaluating ARGs. Up till now around 1000 environmental samples (excluding biological replicates) from different parts of the world have been analyzed on HT-qPCR. Calculated detection frequency and normalized ARGs abundance (ARGs/16S rRNA gene) reported in gut microbiome studies have shown a trend of low ARGs as compared to other environmental matrices. Disparities in the HT-qPCR data analysis which are causing difficulties to researchers in precise interpretation of results have been highlighted and a possible way forward for resolving them is also suggested. The potential of other amplification technologies and point of care or field deployable devices for analyzing ARGs have also been discussed in the review. Our review has focused on updated information regarding the role, current status and future perspectives of HT-qPCR in the field of antimicrobial resistance.

scholarly journals Diversity and Antimicrobial Resistance in the Streptococcus bovis/Streptococcus equinus Complex (SBSEC) Isolated from Korean Domestic Ruminants

2021 ◽  
Vol 9 (1) ◽  
pp. 98
Author(s):  
Seon Young Park ◽  
Mingyung Lee ◽  
Se Ra Lim ◽  
Hyemin Kwon ◽  
Ye Seul Lee ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Phylogenetic Analyses ◽  
Tetracycline Resistance ◽  
Current Status ◽  
Streptococcus Bovis ◽  
Limited Information ◽  
Phenotypic Resistance ◽  
Domestic Ruminants ◽  
Antimicrobial Resistance Genes ◽  
Acid Producing Bacteria

S. bovis/S. equinus complex (SBSEC) includes lactic acid-producing bacteria considered as the causative agent associated with acute rumen lactic acidosis in intensive ruminants. Considering the limited information on the detailed characteristics and diversity of SBSEC in Korea and the emergence of antimicrobial resistance (AMR), we investigated the diversity of SBSEC from domestic ruminants and verified the presence of antimicrobial resistance genes (ARGs) against several antimicrobials with their phenotypic resistance. Among 51 SBSEC isolates collected, two SBSEC members (S. equinus and S. lutetiensis) were identified; sodA-based phylogenetic analyses and comparisons of overall genome relatedness revealed potential plasticity and diversity. The AMR rates of these SBSEC against erythromycin, clindamycin, and tetracycline were relatively lower than those of other SBSEC isolates of a clinical origin. An investigation of the ARGs against those antimicrobials indicated that tetracycline resistance of SBSECs generally correlated with the presence of tet(M)-possessing Tn916-like transposon. However, no correlation between the presence of ARGs and phenotypic resistance to erythromycin and clindamycin was observed. Although a limited number of animals and their SBSEC isolates were examined, this study provides insights into the potential intraspecies biodiversity of ruminant-origin SBSEC and the current status on antimicrobial resistance of the bacteria in the Korean livestock industry.

scholarly journals Differential overlap in human and animal fecal microbiomes and resistomes in rural versus urban Bangladesh

2021 ◽  
Author(s):  
Jenna M Swarthout ◽  
Erica R Fuhrmeister ◽  
Latifah Hamzah ◽  
Angela Harris ◽  
Mir A. Ahmed ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Urban Communities ◽  
Resistance Genes ◽  
Low Income ◽  
Urban Areas ◽  
Pathogenic Bacteria ◽  
Small Scale ◽  
Rrna Gene ◽  
Antimicrobial Resistance Genes ◽  
Long Read

Background Low- and middle-income countries (LMICs) bear the largest mortality burden due to antimicrobial-resistant infections. Small-scale animal production and free-roaming domestic animals are common in many LMICs, yet data on zoonotic exchange of gut bacteria and antimicrobial resistance genes (ARGs) in low-income communities are sparse. Differences between rural and urban communities in population density, antibiotic use, and cohabitation with animals likely influence the frequency of transmission of gut bacterial communities and ARGs between humans and animals. Here, we determined the similarity in gut microbiomes, using 16S rRNA gene amplicon sequencing, and resistomes, using long-read metagenomics, between humans, chickens, and goats in rural compared to urban Bangladesh. Results Gut microbiomes were more similar between humans and chickens in rural (where cohabitation is more common) compared to urban areas, but there was no difference for humans and goats. Urbanicity did not impact the similarity of human and animal resistomes; however, ARG abundance was higher in urban animals compared to rural animals. We identified substantial overlap of ARG alleles in humans and animals in both settings. Humans and chickens had more overlapping ARG alleles than humans and goats. All fecal hosts carried ARGs on contigs classified as potentially pathogenic bacteria, including Escherichia coli, Campylobacter jejuni, Clostridiodes difficile, and Klebsiella pneumoniae. Conclusions While the development of antimicrobial resistance in animal gut microbiomes and subsequent transmission to humans has been demonstrated in intensive farming environments and high-income countries, evidence of zoonotic exchange of antimicrobial resistance in LMIC communities is lacking. This research provides genomic evidence of overlap of antimicrobial resistance genes between humans and animals, especially in urban communities, and highlights chickens as important reservoirs of antimicrobial resistance. Chicken and human gut microbiomes were more similar in rural Bangladesh, where cohabitation is more common. Incorporation of long-read metagenomics enabled characterization of bacterial hosts of resistance genes, which has not been possible in previous culture-independent studies using only short-read sequencing. These findings highlight the importance of developing strategies for combatting antimicrobial resistance that account for chickens being reservoirs of ARGs in community environments, especially in urban areas.

scholarly journals Antimicrobial resistance gene surveillance in the receiving waters of an upgraded wastewater treatment plant

FACETS ◽  
2018 ◽  
Vol 3 (1) ◽  
pp. 128-138 ◽  
Author(s):  
Claire N. Freeman ◽  
Lena Scriver ◽  
Kara D. Neudorf ◽  
Lisbeth Truelstrup Hansen ◽  
Rob C. Jamieson ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Antimicrobial Resistance ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Nutrient Content ◽  
Rrna Gene ◽  
Treated Effluent ◽  
Antimicrobial Resistance Genes ◽  
Antimicrobial Resistance Gene ◽  
The Impact

Wastewater treatment plants (WWTPs) have been identified as hotspots for antimicrobial resistance genes (ARGs) and thus represent a critical point where patterns in ARG abundances can be monitored prior to their release into the environment. The aim of the current study was to measure the impact of the release of the final treated effluent (FE) on the abundance of ARGs in the receiving water of a recently upgraded WWTP in the Canadian prairies. Sample nutrient content (phosphorous and nitrogen species) was measured as a proxy for WWTP functional performance, and quantitative PCR (qPCR) was used to measure the abundance of eight ARGs, the intI1 gene associated with class I integrons, and the 16S rRNA gene. The genes ermB, sul1, intI1, blaCTX-M, qnrS, and tetO all had higher abundances downstream of the WWTP, consistent with the genes with highest abundance in the FE. These findings are consistent with the increasing evidence suggesting that human activity affects the abundances of ARGs in the environment. Although the degree of risk associated with releasing ARGs into the environment is still unclear, understanding the environmental dimension of this threat will help develop informed management policies to reduce the spread of antibiotic resistance and protect public health.

scholarly journals Investigation of Stress Response Genes in Antimicrobial Resistant Pathogens Sampled from Five Countries

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 927
Author(s):  
Rachael Pei ◽  
Liz Zhang ◽  
Catherine Duan ◽  
Michael Gao ◽  
Rachel Feng ◽  
...  
Keyword(s):  
Stress Response ◽  
Antimicrobial Resistance ◽  
Hierarchical Clustering ◽  
Resistance Genes ◽  
Historical Data ◽  
Dimensional Space ◽  
Stress Response Genes ◽  
Detection Frequency ◽  
Antimicrobial Resistance Genes ◽  
The World

Pathogens, which survive from stressed environmental conditions and evolve with antimicrobial resistance, cause millions of human diseases every year in the world. Fortunately, the NCBI Pathogen Detection Isolates Browser (NPDIB) collects the detected stress response genes and antimicrobial resistance genes in pathogen isolates sampled around the world. While several studies have been conducted to identify important antimicrobial resistance genes, little work has been done to analyze the stress response genes in the NPDIB database. In order to address this, this work conducted the first comprehensive statistical analysis of the stress response genes from five countries of the major residential continents, including the US, the UK, China, Australia, and South Africa. Principal component analysis was first conducted to project the stress response genes onto a two-dimensional space, and hierarchical clustering was then implemented to identify the outlier (i.e., important) genes that show high occurrences in the historical data from 2010 to 2020. Stress response genes and AMR genes were finally analyzed together to investigate the co-occurring relationship between these two types of genes. It turned out that seven genes were commonly found in all five countries (i.e., arsR, asr, merC, merP, merR, merT, and qacdelta1). Pathogens E. coli and Shigella, Salmonella enterica, and Klebsiella pneumoniae were the major pathogens carrying the stress response genes. The hierarchical clustering result showed that certain stress response genes and AMR genes were grouped together, including golT~golS and mdsB~mdsC, ymgB and mdtM, and qacEdelta1 and sul1. The occurrence analysis showed that the samples containing three stress response genes and three AMR genes had the highest detection frequency in the historical data. The findings of this work on the important stress response genes, along with their connection with AMR genes, could inform future drug development that targets stress response genes to weaken antimicrobial resistance pathogens.

scholarly journals Quantification and Characterization of Antimicrobial Resistance in Greywater Discharged to the Environment

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1460 ◽  
Author(s):  
Seema Porob ◽  
Hillary A. Craddock ◽  
Yair Motro ◽  
Orly Sagi ◽  
Michael Gdalevich ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
16S Rrna ◽  
Fecal Coliforms ◽  
Resistant Bacteria ◽  
Rrna Gene ◽  
Wastewater Management ◽  
Class 1 Integron ◽  
Gene Copies ◽  
Antimicrobial Resistance Genes ◽  
Esbl Producers

In disenfranchised communities, untreated greywater (wastewater without sewage) is often environmentally discharged, resulting in potential human exposure to antimicrobial-resistant bacteria (ARB), including extended-spectrum beta-lactamase (ESBL) producers. We sought to examine the abundance of ARB, specifically ESBLs, and antimicrobial resistance genes (ARGs) in greywater from off-grid, pastoral Bedouin villages in Southern Israel. Greywater samples (n = 21) collected from five villages were analyzed to enumerate fecal coliforms and Escherichia coli. ESBL producers were recovered on CHROMagar ESBL and confirmed by VITEK®2 (bioMerieux, Marcy l’Etoile, France) for identification and antimicrobial susceptibility testing. Total genomic DNA was extracted from greywater samples and quantitative PCR (qPCR) was used to determine relative abundance (gene copies/16S rRNA gene) of class 1 integron-integrase intI1, blaTEM, blaCTX-M-32, sul1, and qnrS. The mean count of presumptive ESBL-producing isolates was 4.5 × 106 CFU/100 mL. Of 81 presumptive isolates, 15 ESBL producers were recovered. Phenotypically, 86.7% of ESBL producers were multi-drug resistant. Results from qPCR revealed a high abundance of intI1 (1.4 × 10−1 gene copies/16S rRNA), sul1 (5.2 × 10−2 gene copies/16S rRNA), and qnrS (1.7 × 10−2 gene copies/16S rRNA) followed by blaTEM (3.5 × 10−3 gene copies/16S rRNA) and blaCTX-M-32 (2.2 × 10−5 gene copies/16S rRNA). Results from our study indicate that greywater can be a source of ARB, including ESBL producers, in settings characterized by low sanitary conditions and inadequate wastewater management.

Prevalence of antimicrobial resistance genes and its association with restricted antimicrobial use in food-producing animals: a systematic review and meta-analysis

2020 ◽  
Author(s):  
Diego B Nobrega ◽  
Karen L Tang ◽  
Niamh P Caffrey ◽  
Jeroen De Buck ◽  
Susan C Cork ◽  
...  
Keyword(s):  
Systematic Review ◽  
Antimicrobial Resistance ◽  
Meta Analysis ◽  
Scientific Evidence ◽  
Meca Gene ◽  
Antimicrobial Use ◽  
Vana Gene ◽  
Antimicrobial Resistance Genes ◽  
Restricted Use ◽  
Positive Effect

Abstract Background There is ongoing debate regarding potential associations between restrictions of antimicrobial use and prevalence of antimicrobial resistance (AMR) in bacteria. Objectives To summarize the effects of interventions reducing antimicrobial use in food-producing animals on the prevalence of AMR genes (ARGs) in bacteria from animals and humans. Methods We published a full systematic review of restrictions of antimicrobials in food-producing animals and their associations with AMR in bacteria. Herein, we focus on studies reporting on the association between restricted antimicrobial use and prevalence of ARGs. We used multilevel mixed-effects models and a semi-quantitative approach based on forest plots to summarize findings from studies. Results A positive effect of intervention [reduction in prevalence or number of ARGs in group(s) with restricted antimicrobial use] was reported from 29 studies for at least one ARG. We detected significant associations between a ban on avoparcin and diminished presence of the vanA gene in samples from animals and humans, whereas for the mecA gene, studies agreed on a positive effect of intervention in samples only from animals. Comparisons involving mcr-1, blaCTX-M, aadA2, vat(E), sul2, dfrA5, dfrA13, tet(E) and tet(P) indicated a reduced prevalence of genes in intervention groups. Conversely, no effects were detected for β-lactamases other than blaCTX-M and the remaining tet genes. Conclusions The available body of scientific evidence supported that restricted use of antimicrobials in food animals was associated with an either lower or equal presence of ARGs in bacteria, with effects dependent on ARG, host species and restricted drug.

scholarly journals ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Achal Dhariwal ◽  
Roger Junges ◽  
Tsute Chen ◽  
Fernanda C Petersen
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Gene ◽  
High Throughput ◽  
Resistance Genes ◽  
Visual Analytics ◽  
Gene List ◽  
Metagenomic Sequencing ◽  
High Throughput Analysis ◽  
Antimicrobial Resistance Genes ◽  
Antimicrobial Resistance Gene

Abstract The study of resistomes using whole metagenomic sequencing enables high-throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies. ResistoXplorer contains three modules—the ‘Antimicrobial Resistance Gene Table’ module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the ‘Integration’ module supports integrative exploratory analysis of resistome and microbiome abundance profiles derived from metagenomic samples; finally, the ‘Antimicrobial Resistance Gene List’ module enables users to intuitively explore the associations between antimicrobial resistance genes and the microbial hosts using network visual analytics to gain biological insights. ResistoXplorer is publicly available at http://www.resistoxplorer.no.

scholarly journals Towards routine employment of computational tools for antimicrobial resistance determination via high-throughput sequencing

2021 ◽  
Author(s):  
Simone Marini ◽  
Rodrigo Mora ◽  
Christina Boucher ◽  
Noelle Noyes ◽  
Mattia Prosperi
Keyword(s):  
Antimicrobial Resistance ◽  
High Throughput ◽  
Bacterial Infections ◽  
High Throughput Sequencing ◽  
Markov Models ◽  
Point Of Care ◽  
Economic Loss ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Data Repositories

Antimicrobial resistance (AMR) is a growing threat to public health and farming at large. Without appropriate interventions, it can lead to millions of deaths per year and substantial economic loss worldwide. In clinical and veterinary practice, a timely characterization of the antibiotic susceptibility profile of bacterial infections is a crucial step in optimizing treatment. Fast turnaround of AMR testing is also needed in food safety and infection control surveillance (e.g., contamination of healthcare or long-term nursing facilities). High-throughput sequencing is a promising option for clinical point-of-care and ecological surveillance, opening the opportunity to develop genotyping-based AMR determination as a possibly faster alternative to phenotypic testing. In the present work, we compare the performance of state-of-the-art methods for detection of AMR from high-throughput sequencing data in healthcare settings. We consider five complementary computational approaches --alignment (AMRPlusPlus), deep learning (DeepARG), k-mer genomic signatures (KARGA, ResFinder), and hidden Markov models (Meta-MARC). We use an extensive collection of clinical studies never employed for model training. To do so, we assemble data from multiple, independent AMR high-throughput sequencing experiments collected in a variety of hospital settings, comprising of 585 isolates with a available AMR resistance profiles determined by phenotypic tests across nine antibiotic classes. We show how the prediction landscape of AMR classifiers is highly heterogeneous, with balanced accuracy varying from 0.4 to 0.92. Although some algorithms---ResFinder, KARGA, and AMRPlusPlus-- exhibit overall better balanced accuracy than others, the high per-AMR-class variance and related findings suggest that: (1) all algorithms might be subject to sampling bias present both in data repositories used for training and experimental/clinical settings; and (2) a portion of clinical samples might contain uncharacterized AMR genes that the algorithms---mostly trained on known AMR genes---fail to generalize upon. These results lead us to formulate practical advice for software configuration and application, as well as give suggestions for future study design to further develop AMR prediction tools from proof-of-concept to bedside.

Sign in / Sign up

Export Citation Format

Share Document