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Motivation Wastewater treatment plants (WWTPs) harbor a dense and diverse microbial community. They constantly receive antimicrobial residues and resistant strains, and therefore provide conditions for horizontal gene transfer (HGT) of antimicrobial resistance (AMR) determinants. This facilitates the transmission of clinically important genes between, e.g. enteric and environmental bacteria, and vice versa. Despite the clinical importance, tools for predicting HGT remain underdeveloped. Results In this study, we examined to which extent water cycle microbial community composition, as inferred by partial 16S rRNA gene sequences, can predict plasmid permissiveness, i.e. the ability of cells to receive a plasmid through conjugation, based on data from standardized filter mating assays using fluorescent bio-reporter plasmids. We leveraged a range of machine learning models for predicting the permissiveness for each taxon in the community, representing the range of hosts a plasmid is able to transfer to, for three broad host-range resistance IncP plasmids (pKJK5, pB10, and RP4). Our results indicate that the predicted permissiveness from the best performing model (random forest) showed a moderate-to-strong average correlation of 0.49 for pB10 [95% confidence interval (CI): 0.44–0.55], 0.43 for pKJK5 (0.95% CI: 0.41–0.49), and 0.53 for RP4 (0.95% CI: 0.48–0.57) with the experimental permissiveness in the unseen test dataset. Predictive phylogenetic signals occurred despite the broad host-range nature of these plasmids. Our results provide a framework that contributes to the assessment of the risk of AMR pollution in wastewater systems. Availability and implementation The predictive tool is available as an application at https://github.com/DaneshMoradigaravand/PlasmidPerm. [ABSTRACT FROM AUTHOR]

Background Klebsiella pneumoniae is a human, animal, and environmental commensal and a leading cause of nosocomial infections, which are often caused by multiresistant strains. We evaluate putative sources of K. pneumoniae that are carried by and infect hospital patients. Methods We conducted a 6-month survey on 2 hematology wards at Addenbrooke's Hospital, Cambridge, United Kingdom, in 2015 to isolate K. pneumoniae from stool, blood, and the environment. We conducted cross-sectional surveys of K. pneumoniae from 29 livestock farms, 97 meat products, the hospital sewer, and 20 municipal wastewater treatment plants in the East of England between 2014 and 2015. Isolates were sequenced and their genomes compared. Results Klebsiella pneumoniae was isolated from stool of 17/149 (11%) patients and 18/922 swabs of their environment, together with 1 bloodstream infection during the study and 4 others over a 24-month period. Each patient carried 1 or more lineages that was unique to them, but 2 broad environmental contamination events and patient–environment transmission were identified. Klebsiella pneumoniae was isolated from cattle, poultry, hospital sewage, and 12/20 wastewater treatment plants. There was low genetic relatedness between isolates from patients/their hospital environment vs isolates from elsewhere. Identical genes encoding cephalosporin resistance were carried by isolates from humans/environment and elsewhere but were carried on different plasmids. Conclusion We identified no patient-to-patient transmission and no evidence for livestock as a source of K. pneumoniae infecting humans. However, our findings reaffirm the importance of the hospital environment as a source of K. pneumoniae associated with serious human infection. [ABSTRACT FROM AUTHOR]

The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, the key to controlling spread of resistant strains is accurate and rapid detection. As traditional culture-based methods are time consuming, genetic approaches have recently been developed for this task. The detection of antibiotic resistance is typically made by measuring a few known determinants previously identified from genome sequencing, and thus requires the prior knowledge of its biological mechanisms. To overcome this limitation, we employed machine learning models to predict resistance to 11 compounds across four classes of antibiotics from existing and novel whole genome sequences of 1936 E. coli strains. We considered a range of methods, and examined population structure, isolation year, gene content, and polymorphism information as predictors. Gradient boosted decision trees consistently outperformed alternative models with an average accuracy of 0.91 on held-out data (range 0.81–0.97). While the best models most frequently employed gene content, an average accuracy score of 0.90 could be obtained using population structure information alone. Single nucleotide variation data were less useful, and significantly improved prediction only for two antibiotics, including ciprofloxacin. These results demonstrate that antibiotic resistance in E. coli can be accurately predicted from whole genome sequences without a priori knowledge of mechanisms, and that both genomic and epidemiological data can be informative. This paves way to integrating machine learning approaches into diagnostic tools in the clinic. [ABSTRACT FROM AUTHOR]

Background: Enterococcus faecium is a leading cause of hospital-acquired infection, particularly in the immunocompromised. Here, we use whole genome sequencing of E. faecium to study within-host evolution and the transition from gut carriage to invasive disease. Methods: We isolated and sequenced 180 E. faecium from four immunocompromised patients who developed bloodstream infection during longitudinal surveillance of E. faecium in stool and their immediate environment. Results: A phylogenetic tree based on single nucleotide polymorphisms (SNPs) in the core genome of the 180 isolates demonstrated several distinct clones. This was highly concordant with the population structure inferred by Bayesian methods, which contained four main BAPS (Bayesian Analysis of Population Structure) groups. The majority of isolates from each patient resided in a single group, but all four patients also carried minority populations in stool from multiple phylogenetic groups. Bloodstream isolates from each case belonged to a single BAPS group, which differed in all four patients. Analysis of 87 isolates (56 from blood) belonging to a single BAPS group that were cultured from the same patient over 54 days identified 30 SNPs in the core genome (nine intergenic, 13 non-synonymous, eight synonymous), and 250 accessory genes that were variably present. Comparison of these genetic variants in blood isolates versus those from stool or environment did not identify any variants associated with bloodstream infection. The substitution rate for these isolates was estimated to be 128 (95% confidence interval 79.82 181.77) mutations per genome per year, more than ten times higher than previous estimates for E. faecium. Within-patient variation in vancomycin resistance associated with vanA was common and could be explained by plasmid loss, or less often by transposon loss. Conclusions: These findings demonstrate the diversity of E. faecium carriage by individual patients and significant within-host diversity of E. faecium, but do not provide evidence for adaptive genetic variation associated with invasion. [ABSTRACT FROM AUTHOR]

Klebsiella oxytoca, a member of the Enterobacteriaceae, is a gram-negative pathogenic bacterium of environmental origin, which can cause infection in healthcare settings. Outbreaks of multidrug-resistant K. oxytoca infection have been increasingly reported in hospitalized patients. Despite the growing importance of this pathogen, there is limited knowledge about the population structure and epidemiology of antimicrobial resistant K. oxytoca. We investigated the population structure and genomic basis of antimicrobial resistance of 41 multidrug resistant K. oxytoca isolates recovered from bloodstream infections across the UK and Ireland. Our results show that K. oxytoca has a highly diverse population, which is composed of several distinct clades, and we identified one recent expansion of a clone within our dataset. Although the K. oxytoca genomes are clearly distinct from the genomes of a global collection of Klebsiella pneumoniae complex, pre-dominantly composed of K. pneumoniae, we found evidence for sharing of core genes through recombination, as well as the exchange of accessory antimicrobial resistance and virulence factor genes between the species. Our findings also suggest that the different K. oxytoca clades have acquired antimicrobial resistance and virulence factor genes independently. Thishighlights theclinicalandtherapeutic importanceofgenetic flexibility inK. oxytocaandtherelevance of this in its role as an opportunistic pathogen. [ABSTRACT FROM AUTHOR]

Background: Klebsiella pneumoniae is a gram-negative bacterial species capable of occupying a broad range of environmental and clinical habitats. Known as an opportunistic pathogen, it has recently become a major causative agent of clinical infections worldwide. Despite growing knowledge about the highly diverse population of K. pneumoniae, the evolution and clinical significance of environmental K. pneumoniae, as well as the relationship between clinical and environmental K. pneumoniae, are poorly defined. Methods: We isolated and sequenced K. pneumoniae from in-patients in a single hospital in Thailand, as well as hospital sewage, and surrounding canals and farms within a 20-km radius. Results: Phylogenetic analysis of 77 K. pneumoniae (48 clinical and 29 non-clinical isolates) demonstrated that the two groups were intermixed throughout the tree and in some cases resided in the same clade, suggesting recent divergence from a common ancestor. Phylogenetic comparison of the 77 Thai genomes with 286 K. pneumoniae from a global collection showed that Thai isolates were closely related to the clinical sub-population of the global collection, indicating that Thai clinical isolates belonged to globally circulating lineages. Dating of four Thai K. pneumoniae clades indicated that they emerged between 50 and 150 years ago. Despite their phylogenetic relatedness, virulence factors and β-lactamase resistance genes were more numerous in clinical than in environmental isolates. Our results indicate that clinical and environmental K. pneumoniae are closely related, but that hospitals may select for isolates with a more resistant and virulent genotype. Conclusions: These findings highlight the clinical relevance of environmental K. pneumoniae isolates. [ABSTRACT FROM AUTHOR]

Background Recent studies have demonstrated that natural transformation and the formation of highly structured populations in bacteria are interconnected. In spite of growing evidence about this connection, little is known about the dynamics of natural transformation in spatially structured bacterial populations. Results In this work, we model the interdependency between the dynamics of the bacterial gene pool and those of environmental DNA in space to dissect the effect of transformation on adaptation. Our model reveals that even with only a single locus under consideration, transformation with a free DNA fragment pool results in complex adaptation dynamics that do not emerge in previous models focusing only on the gene shuffling effect of transformation at multiple loci. We demonstrate how spatial restriction on population growth and DNA diffusion in the environment affect the impact of transformation on adaptation. We found that in structured bacterial populations intermediate DNA diffusion rates predominantly cause transformation to impede adaptation by spreading deleterious alleles in the population. Conclusion Overall, our model highlights distinctive evolutionary consequences of bacterial transformation in spatially restricted compared to planktonic bacterial populations. [ABSTRACT FROM AUTHOR]

Recombination has the potential to facilitate adaptation. In spite of the substantial body of theory on the impact of recombination on the evolutionary dynamics of adapting populations, empirical evidence to test these theories is still scarce. We examined the effect of recombination on adaptation on a large-scale empirical fitness landscape in HIV-1 based on in vitro fitness measurements. Our results indicate that recombination substantially increases the rate of adaptation under a wide range of parameter values for population size, mutation rate and recombination rate. The accelerating effect of recombination is stronger for intermediate mutation rates but increases in a monotonic way with the recombination rates and population sizes that we examined. We also found that both fitness effects of individual mutations and epistatic fitness interactions cause recombination to accelerate adaptation. The estimated epistasis in the adapting populations is significantly negative. Our results highlight the importance of recombination in the evolution of HIV-I. [ABSTRACT FROM AUTHOR]

Natural transformation is a process whereby bacteria actively take up DNA from the surrounding environment and incorporate it into their genome. Natural transformation is widespread in bacteria, but its evolutionary significance is still debated. Here, we hypothesize that transformation may confer a fitness advantage in changing environments through a process we term �genetic time travel�: by taking up old genes that were retained in the environment, the bacteria may revert to a past genotypic state that proves advantageous in the present or a future environment. We scrutinize our hypothesis by means of a mathematical model involving two bacterial types (transforming and non-transforming), a single locus under natural selection and a free DNA pool. The two bacterial types were competed in environments with changing selection regimes. We demonstrate that for a wide range of parameter values for the DNA turnover rate, the transformation rate and the frequency of environmental change, the transforming type outcompetes the non-transforming type. We discuss the empirical plausibility of our hypothesis, as well as its relationship to other hypotheses for the evolution of transformation in bacteria and sex more generally, speculating that �genetic time travel� may also be relevant in eukaryotes that undergo horizontal gene transfer. [ABSTRACT FROM AUTHOR]

One of the most challenging questions in evolutionary biology is how sex has evolved in the face of substantial fitness costs. In this study, we focus on the evolution of bacterial sex in the form of natural transformation, where cells take up exogenous DNA and integrate it into the genome. Besides the physiological cost of producing a DNA uptake system, transformation can potentially impose a genetic cost as a result of an overrepresentation of deleterious mutations in the extracellular DNA pool. On the other hand, the uptake of DNA can be beneficial not only because of genetic effects but also because of the immediate nutritional value of the DNA. To disentangle these fitness costs and benefits, we developed a mathematical model and competed three bacterial types during adaptation to a new environment: competent cells capable of DNA import and digestion; competent cells capable of DNA import, digestion, and recombination; and noncompetent cells. Our results indicate a complex interplay between several physiological and ecological factors, including the rate at which DNA is taken up, the rate of DNA decay in the medium, and the nutritional value of DNA. In finite populations, the recombining type is often favored through the Fisher- Muller effect. [ABSTRACT FROM AUTHOR]

There is ample empirical evidence revealing that fitness landscapes are often complex: the fitness effect of a newly arisen mutation can depend strongly on the allelic state at other loci. However, little is known about the effects of recombination on adaptation on such fitness landscapes. Here, we investigate how recombination influences the rate of adaptation on a special type of complex fitness landscapes. On these landscapes, the mutational trajectories from the least to the most fit genotype are interrupted by genotypes with low relative fitness. We study the dynamics of adapting populations on landscapes with different compositions and numbers of low fitness genotypes, with and without recombination. Our results of the deterministic model (assuming an infinite population size) show that recombination generally decelerates adaptation on these landscapes. However, in finite populations, this deceleration is outweighed by the accelerating Fisher-Muller effect under certain conditions. We conclude that recombination has complex effects on adaptation that are highly dependent on the particular fitness landscape, population size and recombination rate. [ABSTRACT FROM AUTHOR]

The TBX1 gene plays a critical role in the development of 22q11.2 deletion syndrome (22q11.2DS), a complex genetic disorder associated with various phenotypic manifestations. In this study, we performed in-silico analysis to identify potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) within the TBX1 gene and evaluate their functional and structural impact on 22q11.2DS. A comprehensive analysis pipeline involving multiple computational tools was employed to predict the pathogenicity of nsSNPs. This study assessed protein stability and explored potential alterations in protein-protein interactions. The results revealed the rs751339103(C>A), rs780800634(G>A), rs1936727304(T>C), rs1223320618(G>A), rs1248532217(T>C), rs1294927055 (C>T), rs1331240435 (A>G, rs1601289406 (A>C), rs1936726164 (G>A), and rs911796187(G>A) with a high-risk potential for affecting protein function and stability. These nsSNPs were further analyzed for their impact on post-translational modifications and structural characteristics, indicating their potential disruption of molecular pathways associated with TBX1 and its interacting partners. These findings provide a foundation for further experimental studies and elucidation of potential therapeutic targets and personalized treatment approaches for individuals affected by 22q11.2DS. [ABSTRACT FROM AUTHOR]

Motivation: High-throughput chemical genomic screens produce informative datasets, providing valuable insights into unknown gene function on a genome-wide level. However, there is currently no comprehensive analytic package publicly available. We developed ChemGAPP to bridge this gap. ChemGAPP integrates various steps in a streamlined and user-friendly format, including rigorous quality control measures to curate screening data. Results: ChemGAPP provides three sub-packages for different chemical-genomic screens: ChemGAPP Big for large-scale screens; ChemGAPP Small for small-scale screens; and ChemGAPP GI for genetic interaction screens. ChemGAPP Big, tested against the Escherichiacoli KEIO collection, revealed reliable fitness scores which displayed biologically relevant phenotypes. ChemGAPP Small demonstrated significant changes in phenotype in a small-scale screen. ChemGAPP GI was benchmarked against three sets of genes with known epistasis types and successfully reproduced each interaction type. Availability and implementation: ChemGAPP is available at https://github.com/HannahMDoherty/ChemGAPP, as a standalone Python package as well as Streamlit applications. [ABSTRACT FROM AUTHOR]

Background: A comprehensive understanding of the pre-existing genetic variation in genes associated with antibiotic resistance in the Mycobacterium tuberculosis complex (MTBC) is needed to accurately interpret whole-genome sequencing data for genotypic drug susceptibility testing (DST). Methods: We investigated mutations in 92 genes implicated in resistance to 21 anti-tuberculosis drugs using the genomes of 405 phylogenetically diverse MTBC strains. The role of phylogenetically informative mutations was assessed by routine phenotypic DST data for the first-line drugs isoniazid, rifampicin, ethambutol, and pyrazinamide from a separate collection of over 7000 clinical strains. Selected mutations/strains were further investigated by minimum inhibitory concentration (MIC) testing. Results: Out of 547 phylogenetically informative mutations identified, 138 were classified as not correlating with resistance to first-line drugs. MIC testing did not reveal a discernible impact of a Rv1979c deletion shared by M. africanum lineage 5 strains on resistance to clofazimine. Finally, we found molecular evidence that some MTBC subgroups may be hyper-susceptible to bedaquiline and clofazimine by different loss-of-function mutations affecting a drug efflux pump subunit (MmpL5). Conclusions: Our findings underline that the genetic diversity in MTBC has to be studied more systematically to inform the design of clinical trials and to define sound epidemiologic cut-off values (ECOFFs) for new and repurposed anti-tuberculosis drugs. In that regard, our comprehensive variant catalogue provides a solid basis for the interpretation of mutations in genotypic as well as in phenotypic DST assays. [ABSTRACT FROM AUTHOR]