Occurrence of antibiotic resistance genes and bacterial pathogens in water and sediment in urban recreational water

2019 ◽  
Vol 77 ◽  
pp. 65-74 ◽  
Author(s):  
Peiyan Dong ◽  
Qijia Cui ◽  
Tingting Fang ◽  
Yong Huang ◽  
Hui Wang
2017 ◽  
Author(s):  
Christian Munck ◽  
Mostafa M. Hashim Ellabaan ◽  
Michael Schantz Klausen ◽  
Morten O.A. Sommer

AbstractGenes capable of conferring resistance to clinically used antibiotics have been found in many different natural environments. However, a concise overview of the resistance genes found in common human bacterial pathogens is lacking, which complicates risk ranking of environmental reservoirs. Here, we present an analysis of potential antibiotic resistance genes in the 17 most common bacterial pathogens isolated from humans. We analyzed more than 20,000 bacterial genomes and defined a clinical resistome as the set of resistance genes found across these genomes. Using this database, we uncovered the co-occurrence frequencies of the resistance gene clusters within each species enabling identification of co-dissemination and co-selection patterns. The resistance genes identified in this study represent the subset of the environmental resistome that is clinically relevant and the dataset and approach provides a baseline for further investigations into the abundance of clinically relevant resistance genes across different environments. To facilitate an easy overview the data is presented at the species level at www.resistome.biosustain.dtu.dk.


mSphere ◽  
2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Craig Stephens ◽  
Tyler Arismendi ◽  
Megan Wright ◽  
Austin Hartman ◽  
Andres Gonzalez ◽  
...  

ABSTRACT The evolution and propagation of antibiotic resistance by bacterial pathogens are significant threats to global public health. Contemporary DNA sequencing tools were applied here to gain insight into carriage of antibiotic resistance genes in Escherichia coli, a ubiquitous commensal bacterium in the gut microbiome in humans and many animals, and a common pathogen. Draft genome sequences generated for a collection of 101 E. coli strains isolated from healthy undergraduate students showed that horizontally acquired antibiotic resistance genes accounted for most resistance phenotypes, the primary exception being resistance to quinolones due to chromosomal mutations. A subset of 29 diverse isolates carrying acquired resistance genes and 21 control isolates lacking such genes were further subjected to long-read DNA sequencing to enable complete or nearly complete genome assembly. Acquired resistance genes primarily resided on F plasmids (101/153 [67%]), with smaller numbers on chromosomes (30/153 [20%]), IncI complex plasmids (15/153 [10%]), and small mobilizable plasmids (5/153 [3%]). Nearly all resistance genes were found in the context of known transposable elements. Very few structurally conserved plasmids with antibiotic resistance genes were identified, with the exception of an ∼90-kb F plasmid in sequence type 1193 (ST1193) isolates that appears to serve as a platform for resistance genes and may have virulence-related functions as well. Carriage of antibiotic resistance genes on transposable elements and mobile plasmids in commensal E. coli renders the resistome highly dynamic. IMPORTANCE Rising antibiotic resistance in human-associated bacterial pathogens is a serious threat to our ability to treat many infectious diseases. It is critical to understand how acquired resistance genes move in and through bacteria associated with humans, particularly for species such as Escherichia coli that are very common in the human gut but can also be dangerous pathogens. This work combined two distinct DNA sequencing approaches to allow us to explore the genomes of E. coli from college students to show that the antibiotic resistance genes these bacteria have acquired are usually carried on a specific type of plasmid that is naturally transferrable to other E. coli, and likely to other related bacteria.


2020 ◽  
Author(s):  
Jorge Agramont ◽  
Sergio Gutierrez-Cortez ◽  
Enrique Joffré ◽  
Åsa Sjöling ◽  
Carla Calderon Toledo

AbstractWater and sediment samples affected by mining activities were collected from three lakes in Bolivia, the pristine Andean lake Pata Khota, the Milluni Chico lake directly impacted by acid mine drainage, and the Uru-Uru lake located close to Oruro city and highly polluted by mining activities and human wastewater discharges. Physicochemical parameters, including metal compositions, were analyzed in water and sediment samples. Antibiotic resistance genes (ARGs), were screened for, and verified by quantitative PCR together with the mobile element class 1 integron (intl1) as well as crAssphage, a marker of human fecal pollution. The gene intl1 showed a positive correlation with sul1, sul2, tetA and blaOXA-2. CrAssphage was only detected in Uru-Uru lake and its tributaries and significantly higher abundance of ARGs were found in these sites. Multivariate analysis showed that crAssphage abundance, electrical conductivity and pH were positively correlated with higher levels of intl1 and ARGs. Taken together our results suggest that fecal pollution is the major driver of higher ARGs and intl1 in wastewater and mining contaminated environments.


2018 ◽  
Vol 85 (4) ◽  
Author(s):  
Richard C. Allen ◽  
Daniel C. Angst ◽  
Alex R. Hall

ABSTRACTBacterial pathogens that carry antibiotic resistance alleles sometimes pay a cost in the form of impaired growth in antibiotic-free conditions. This cost of resistance is expected to be a key parameter for understanding how resistance spreads and persists in pathogen populations. Analysis of individual resistance alleles from laboratory evolution and natural isolates has shown they are typically costly, but these costs are highly variable and influenced by genetic variation at other loci. It therefore remains unclear how strongly resistance is linked to impaired antibiotic-free growth in bacteria from natural and clinical scenarios, where resistance alleles are likely to coincide with other types of genetic variation. To investigate this, we measured the growth of 92 natural and clinicalEscherichia coliisolates across three antibiotic-free environments. We then tested whether variation of antibiotic-free growth among isolates was predicted by their resistance to 10 antibiotics, while accounting for the phylogenetic structure of the data. We found that isolates with similar resistance profiles had similar antibiotic-free growth profiles, but it was not simply that higher average resistance was associated with impaired growth. Next, we used whole-genome sequences to identify antibiotic resistance genes and found that isolates carrying a greater number of resistance gene types grew relatively poorly in antibiotic-free conditions, even when the resistance genes they carried were different. This suggests that the resistance of bacterial pathogens is linked to growth costs in nature, but it is the total genetic burden and multivariate resistance phenotype that predict these costs, rather than individual alleles or mean resistance across antibiotics.IMPORTANCEManaging the spread of antibiotic resistance in bacterial pathogens is a major challenge for global public health. Central to this challenge is understanding whether resistance is linked to impaired bacterial growth in the absence of antibiotics, because this determines whether resistance declines when bacteria are no longer exposed to antibiotics. We studied 92 isolates of the key bacterial pathogenEscherichia coli; these isolates varied in both their antibiotic resistance genes and other parts of the genome. Taking this approach, rather than focusing on individual genetic changes associated with resistance as in much previous work, revealed that growth without antibiotics was linked to the number of specialized resistance genes carried and the combination of antibiotics to which isolates were resistant but was not linked to average antibiotic resistance. This approach provides new insights into the genetic factors driving the long-term persistence of antibiotic-resistant bacteria, which is important for future efforts to predict and manage resistance.


2021 ◽  
Vol 408 ◽  
pp. 124985
Author(s):  
Cheng Wang ◽  
Ruiwen Hu ◽  
P.J. Strong ◽  
Wei Zhuang ◽  
Weiming Huang ◽  
...  

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