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Background: Nosocomial infections pose a considerable risk to patients who are susceptible, and this is particularly acute in intensive care units when hospital-associated bacteria are endemic. During the first wave of the COVID-19 pandemic, the surge of patients presented a significant obstacle to the effectiveness of infection control measures. We aimed to assess the risks and extent of nosocomial pathogen transmission under a high patient burden by designing a novel bacterial pan-pathogen deep-sequencing approach that could be integrated with standard clinical surveillance and diagnostics workflows., Methods: We did a prospective cohort study in a region of northern Italy that was severely affected by the first wave of the COVID-19 pandemic. Inpatients on both ordinary and intensive care unit (ICU) wards at the San Matteo hospital, Pavia were sampled on multiple occasions to identify bacterial pathogens from respiratory, nasal, and rectal samples. Diagnostic samples collected between April 7 and May 10, 2020 were cultured on six different selective media designed to enrich for Acinetobacter baumannii, Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae, and DNA from each plate with positive growth was deep sequenced en masse. We used mSWEEP and mGEMS to bin sequencing reads by sequence cluster for each species, followed by mapping with snippy to generate high quality alignments. Antimicrobial resistance genes were detected by use of ARIBA and CARD. Estimates of hospital transmission were obtained from pairwise bacterial single nucleotide polymorphism distances, partitioned by within-patient and between-patient samples. Finally, we compared the accuracy of our binned Acinetobacter baumannii genomes with those obtained by single colony whole-genome sequencing of isolates from the same hospital., Findings: We recruited patients from March 1 to May 7, 2020. The pathogen population among the patients was large and diverse, with 2148 species detections overall among the 2418 sequenced samples from the 256 patients. In total, 55 sequence clusters from key pathogen species were detected at least five times. The antimicrobial resistance gene prevalence was correspondingly high, with key carbapenemase and extended spectrum ß-lactamase genes detected in at least 50 (40%) of 125 patients in ICUs. Using high-resolution mapping to infer transmission, we established that hospital transmission was likely to be a significant mode of acquisition for each of the pathogen species. Finally, comparison with single colony Acinetobacter baumannii genomes showed that the resolution offered by deep sequencing was equivalent to single-colony sequencing, with the additional benefit of detection of co-colonisation of highly similar strains., Interpretation: Our study shows that a culture-based deep-sequencing approach is a possible route towards improving future pathogen surveillance and infection control at hospitals. Future studies should be designed to directly compare the accuracy, cost, and feasibility of culture-based deep sequencing with single colony whole-genome sequencing on a range of bacterial species., Funding: Wellcome Trust, European Research Council, Academy of Finland Flagship program, Trond Mohn Foundation, and Research Council of Norway., Competing Interests: Declaration of interests SWL received Robert Austrian Research Award sponsored by Pfizer, outside of the scope of this study. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Cyanobacterial mats are commonly reported as hotspots of microbial diversity across polar environments. These thick, multilayered microbial communities provide a refuge from extreme environmental conditions, with many species able to grow and coexist despite the low allochthonous nutrient inputs. The visibly dominant phototrophic biomass is dependent on internal nutrient recycling by heterotrophic organisms within the mats; however, the specific contribution of heterotrophic protists remains little explored. In this study, mat community diversity was examined along a latitudinal gradient (55-83°N), spanning subarctic taiga, tundra, polar desert, and the High Arctic ice shelves. The prokaryotic and eukaryotic communities were targeted, respectively, by V4 16S ribosomal RNA (rRNA) and V9 18S rRNA gene amplicon high-throughput sequencing. Prokaryotic and eukaryotic richness decreased, in tandem with decreasing temperatures and shorter seasons of light availability, from the subarctic to the High Arctic. Taxonomy-based annotation of the protist community revealed diverse phototrophic, mixotrophic, and heterotrophic genera in all mat communities, with fewer parasitic taxa in High Arctic communities. Co-occurrence network analysis identified greater heterogeneity in eukaryotic than prokaryotic community structure among cyanobacterial mats across the Canadian Arctic. Our findings highlight the sensitivity of microbial eukaryotes to environmental gradients across northern high latitudes., (© The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.)

Minimum Inhibitory Concentrations (MICs) are the gold standard for quantitatively measuring antibiotic resistance. However, lab-based MIC determination can be time-consuming and suffers from low reproducibility, and interpretation as sensitive or resistant relies on guidelines which change over time. Genome sequencing and machine learning promise to allow in silico MIC prediction as an alternative approach which overcomes some of these difficulties, albeit the interpretation of MIC is still needed. Nevertheless, precisely how we should handle MIC data when dealing with predictive models remains unclear, since they are measured semi-quantitatively, with varying resolution, and are typically also left- and right-censored within varying ranges. We therefore investigated genome-based prediction of MICs in the pathogen Klebsiella pneumoniae using 4367 genomes with both simulated semi-quantitative traits and real MICs. As we were focused on clinical interpretation, we used interpretable rather than black-box machine learning models, namely, Elastic Net, Random Forests, and linear mixed models. Simulated traits were generated accounting for oligogenic, polygenic, and homoplastic genetic effects with different levels of heritability. Then we assessed how model prediction accuracy was affected when MICs were framed as regression and classification. Our results showed that treating the MICs differently depending on the number of concentration levels of antibiotic available was the most promising learning strategy. Specifically, to optimise both prediction accuracy and inference of the correct causal variants, we recommend considering the MICs as continuous and framing the learning problem as a regression when the number of observed antibiotic concentration levels is large, whereas with a smaller number of concentration levels they should be treated as a categorical variable and the learning problem should be framed as a classification. Our findings also underline how predictive models can be improved when prior biological knowledge is taken into account, due to the varying genetic architecture of each antibiotic resistance trait. Finally, we emphasise that incrementing the population database is pivotal for the future clinical implementation of these models to support routine machine-learning based diagnostics.

Background: One Health approaches to address the increasing threat of antimicrobial resistance (AMR) are gaining attention. However, data on the distribution and movement of bacteria and their AMR-associated genes between clinical and non-clinical sources are scarce, especially from low-income and middle-income countries. We aimed to analyse Klebsiella isolates from various sources in Ghana and compare the prevalence of AMR with datasets from two other countries., Methods: We conducted a cross-sectional genomic One Health study. Multiple clinical, environmental, and animal sources were sampled from 78 locations (eg, hospitals, residential areas, and farms) in and around Tamale, Ghana. Clinical samples were collected through routine screening and in cases of suspected infection between March 15 and Sept 15, 2019, and samples from the wider environment were collected during a dedicated sampling effort between the dates of Aug 19, 2018, and Sept 26, 2019. Sampling locations were approximately evenly distributed from the centre of the city and steadily outwards to capture both rural and urban locations. Samples with positive growth for Klebsiella were included. Isolates of Klebsiella were obtained from the samples using Simmons citrate agar medium and characterised by antimicrobial susceptibility testing and whole-genome sequencing. A comparative analysis with Klebsiella population surveys from Pavia, Italy, and Tromsø, Norway, was performed. AMR-associated and virulence genes were detected, and the population distribution of these genes was studied., Findings: Of 957 samples collected around Tamale, Ghana, 620 were positive for Klebsiella spp. 573 Klebsiella isolates were successfully sequenced, of which 370 were Klebsiella pneumoniae. Only two hospital isolates were carbapenem-resistant. Extended-spectrum β-lactamase (ESBL) genes were relatively common among the Ghanaian clinical isolates but rare in the environmental samples. Prevalence of ESBL genes in human-hospital disease samples was 64% (14 of 22 isolates) in Ghana and 44% (four of nine isolates) in Italy, and prevalence in human-hospital carriage samples was 7% (eight of 107) in Ghana and 13% (54 of 428) in Italy; the prevalence was higher in human-hospital disease samples than in human-hospital carriage samples in both countries, and prevalence across both samples in both countries was higher than in Norway. Ghanaian isolates showed evidence of high recombination rates (recombination events compared with point mutations [r/m] 9·455) and a considerable accessory gene overlap with isolates from Italy and Norway., Interpretation: Although several AMR-associated gene classes were observed relatively frequently in non-clinical sources, ESBL, carbapenemase, and virulence genes were predominantly present only in hospital samples. These results suggest that interventions should be focused on clinical settings to have the greatest effect on the prevalence and dissemination of AMR-associated genes., Funding: European Research Council (742158), Academy of Finland EuroHPC grant, Trond Mohn Foundation (BATTALION grant), and Wellcome Trust., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

This longitudinal study tests correlations between antimicrobial agents (AA) and corresponding antimicrobial resistance genes (ARGs) generated by a community of >100 k people inhabiting one city (Bath) over a 13 month randomised monitoring programme of community wastewater. Several AAs experienced seasonal fluctuations, such as the macrolides erythromycin and clarithromycin that were found in higher loads in winter, whilst other AA levels, including sulfamethoxazole and sulfapyridine, stayed consistent over the study period. Interestingly, and as opposed to AAs, ARGs prevalence was found to be less variable, which indicates that fluctuations in AA usage might either not directly affect ARG levels or this process spans beyond the 13-month monitoring period. However, it is important to note that weekly positive correlations between individual associated AAs and ARGs were observed where seasonal variability in AA use was reported: ermB and macrolides CLR-clarithromycin and dmCLR-N-desmethyl clarithromycin, aSPY- N-acetyl sulfapyridine and sul1, and OFX-ofloxacin and qnrS. Furthermore, ARG loads normalised to 16S rRNA (gene load per microorganism) were positively correlated to the ARG loads normalised to the human population (gene load per capita), which indicates that the abundance of microorganisms is proportional to the size of human population and that the community size, and not AA levels, is a major driver of ARG levels in wastewater. Comparison of hospital and community wastewater showed higher number of AAs and their metabolites, their frequency of occurrence and concentrations in hospital wastewater. Examples include: LZD-linezolid (used only in severe bacterial infections) and AMX-amoxicillin (widely used, also in community but with very low wastewater stability) that were found only in hospital wastewater. CIP-ciprofloxacin, SMX-sulfamethoxazole, TMP-trimethoprim, MTZ-metronidazole and macrolides were found at much higher concentrations in hospital wastewater while TET-tetracycline and OTC-oxytetracycline, as well as antiretrovirals, had an opposite trend. In contrast, comparable concentrations of resistant genes were observed in both community and hospital wastewater. This supports the hypothesis that AMR levels are more of an endemic nature, developing over time in individual communities. Both hospital and community wastewater had AAs that exceeded PNEC values (e.g. CLR-clarithromycin, CIP-ciprofloxacin). In general, though, hospital effluents had a greater number of quantifiable AAs exceeding PNECs (e.g. SMX-sulfamethoxazole, ERY-erythromycin, TMP-trimethoprim). Hospitals are therefore an important consideration in AMR surveillance as could be high risk areas for AMR., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Staphylococcus aureus is an opportunistic pathogen and a leading cause of morbidity and mortality worldwide. Genomic-based surveillance has greatly improved our ability to track the emergence and spread of high-risk clones, but the full potential of genomic data is only reached when used in conjunction with detailed metadata. Here, we demonstrate the utility of an integrated approach by leveraging a curated collection of clinical and epidemiological metadata of S. aureus in the San Matteo Hospital (Italy) through a semisupervised clustering strategy. We sequenced 226 sepsis S. aureus samples, recovered over a period of 9 years. By using existing antibiotic profiling data, we selected strains that capture the full diversity of the population. Genome analysis revealed 49 sequence types, 16 of which are novel. Comparative genomic analyses of hospital- and community-acquired infection ruled out the existence of genomic features differentiating them, while evolutionary analyses of genes and traits of interest highlighted different dynamics of acquisition and loss between antibiotic resistance and virulence genes. Finally, highly resistant clones belonging to clonal complexes (CC) 8 and 22 were found to be responsible for abundant infections and deaths, while the highly virulent CC30 was responsible for rare but deadly episodes of infections. IMPORTANCE Genome sequencing is an important tool in clinical microbiology, as it allows in-depth characterization of isolates of interest and can propel genome-based surveillance studies. Such studies can benefit from ad hoc methods of sample selection to capture the genomic diversity present in a data set. Here, we present an approach based on clustering of antibiotic resistance profiles that allows optimal sample selection for bacterial genomic surveillance. We apply the method to a 9-year collection of Staphylococcus aureus from a large hospital in northern Italy. Our method allows us to sequence the genomes of a large variety of strains of this important pathogen, which we then leverage to characterize the epidemiology in the hospital and to perform evolutionary analyses on genes and traits of interest. These analyses highlight different dynamics of acquisition and loss between antibiotic resistance and virulence genes., Competing Interests: The authors declare no conflict of interest.

Bacteria from the family Vibrionaceae have been implicated in mass mortalities of farmed Pacific oysters ( Magallana gigas ) in multiple countries, leading to substantial impairment of growth in the sector. In Ireland there has been concern that Vibrio have been involved in serious summer outbreaks. There is evidence that Vibrio aestuarianus is increasingly becoming the main pathogen of concern for the Pacific oyster industry in Ireland. While bacteria belonging to the Vibrio splendidus clade are also detected frequently in mortality episodes, their role in the outbreaks of summer mortality is not well understood. To identify and characterize strains involved in these outbreaks, 43 Vibrio isolates were recovered from Pacific oyster summer mass mortality episodes in Ireland from 2008 to 2015 and these were whole-genome sequenced. Among these, 25 were found to be V. aestuarianus (implicated in disease) and 18 were members of the V. splendidus species complex (role in disease undetermined). Two distinct clades of V. aestuarianus - clade A and clade B - were found that had previously been described as circulating within French oyster culture. The high degree of similarity between the Irish and French V. aestuarianus isolates points to translocation of the pathogen between Europe's two major oyster-producing countries, probably via trade in spat and other age classes. V. splendidus isolates were more diverse, but the data reveal a single clone of this species that has spread across oyster farms in Ireland. This underscores that Vibrio could be transmitted readily across oyster farms. The presence of V. aestuarianus clades A and B in not only France but also Ireland adds weight to growing concern that this pathogen is spreading and impacting Pacific oyster production within Europe.

The rise of antimicrobial resistance (AMR) in bacterial pathogens such as Klebsiella pneumoniae (Kp) is a pressing public health and economic concern. The 'One-Health' framework recognizes that effective management of AMR requires surveillance in agricultural as well as clinical settings, particularly in low-resource regions such as Pakistan. Here, we use whole-genome sequencing to characterise 49 isolates of Klebisella spp. (including 43 Kp) and 2 presumptive Providencia rettgeri isolates recovered from dairy farms located near 3 cities in Pakistan-Quetta ( n = 29), Faisalabad ( n = 19), and Sargodha ( n = 3). The 43 Kp isolates corresponded to 38 sequence types (STs), and 35 of these STs were only observed once. This high diversity indicates frequent admixture and limited clonal spread on local scales. Of the 49 Klebsiella spp. isolates, 41 (84%) did not contain any clinically relevant antimicrobial resistance genes (ARGs), and we did not detect any ARGs predicted to encode resistance to carbapenems or colistin. However, four Kp lineages contained multiple ARGs: ST11 ( n = 2), ST1391-1LV ( n = 1), ST995 ( n = 1) and ST985 ( n = 1). STs 11, 1391-1LV and 995 shared a core set of five ARGs, including bla CTX-M-15 , harboured on different AMR plasmids. ST985 carried a different set of 16 resistance genes, including bla CTX-M-55 . The two presumptive P. rettgeri isolates also contained multiple ARGs. Finally, the four most common plasmids which did not harbour ARGs in our dataset were non-randomly distributed between regions, suggesting that local expansion of the plasmids occurs independently of the host bacterial lineage. Evidence regarding how dairy farms contribute to the emergence and spread of AMR in Pakistan is valuable for public authorities and organizations responsible for health, agriculture and the environment, as well as for industrial development.

Background: The opportunistic pathogen Staphylococcus aureus is an asymptomatically carried member of the microbiome of about one third of the human population at any given point in time. Body sites known to harbor S. aureus are the skin, nasopharynx, and gut. In particular, the mechanisms allowing S. aureus to pass the gut epithelial barrier and to invade the bloodstream were so far poorly understood. Therefore, the objective of our present study was to investigate the extent to which genetic differences between enteric S. aureus isolates and isolates that caused serious bloodstream infections contribute to the likelihood of invasive disease., Results: Here, we present genome-wide association studies (GWAS) that compare the genome sequences of 69 S. aureus isolates from enteric carriage by healthy volunteers and 95 isolates from bloodstream infections. We complement our GWAS results with a detailed characterization of the cellular and extracellular proteomes of the representative gut and bloodstream isolates, and by assaying the virulence of these isolates with infection models based on human gut epithelial cells, human blood cells, and a small animal infection model. Intriguingly, our results show that enteric and bloodstream isolates with the same sequence type (ST1 or ST5) are very similar to each other at the genomic and proteomic levels. Nonetheless, bloodstream isolates are not necessarily associated with an invasive profile. Furthermore, we show that the main decisive factor preventing infection of gut epithelial cells in vitro is the presence of a tight barrier., Conclusions: Our data show that virulence is a highly variable trait, even within a single clone. Importantly, however, there is no evidence that blood stream isolates possess a higher virulence potential than those from the enteric carriage. In fact, some gut isolates from healthy carriers were more virulent than bloodstream isolates. Based on our present observations, we propose that the integrity of the gut epithelial layer, rather than the pathogenic potential of the investigated enteric S. aureus isolates, determines whether staphylococci from the gut microbiome will become invasive pathogens. Video Abstract., (© 2022. The Author(s).)

The Klebsiella group, found in humans, livestock, plants, soil, water and wild animals, is genetically and ecologically diverse. Many species are opportunistic pathogens and can harbour diverse classes of antimicrobial resistance genes. Healthcare-associated Klebsiella pneumoniae clones that are non-susceptible to carbapenems can spread rapidly, representing a high public health burden. Here we report an analysis of 3,482 genome sequences representing 15 Klebsiella species sampled over a 17-month period from a wide range of clinical, community, animal and environmental settings in and around the Italian city of Pavia. Northern Italy is a hotspot for hospital-acquired carbapenem non-susceptible Klebsiella and thus a pertinent setting to examine the overlap between isolates in clinical and non-clinical settings. We found no genotypic or phenotypic evidence for non-susceptibility to carbapenems outside the clinical environment. Although we noted occasional transmission between clinical and non-clinical settings, our data point to a limited role of animal and environmental reservoirs in the human acquisition of Klebsiella spp. We also provide a detailed genus-wide view of genomic diversity and population structure, including the identification of new groups., (© 2022. The Author(s).)

With increasing emergence of antimicrobial resistant bacteria (ARB) and the risk this poses to public health, there are growing concerns regarding water pollution contributing to the spread of antimicrobial resistance (AMR) through inadequate amenities and the rapid rate of urbanization. In this study, the impact of different anthropogenic factors on the prevalence of AMR in the urban water cycle in Stellenbosch, South Africa (SA) was examined. Carbapenem, colistin, gentamicin and sulfamethoxazole resistant Gram-negative bacteria were recovered by selectively culturing aqueous, biofilm and sediment samples from sites impacted to varying degrees by informal settlements, residential, industrial, and agricultural activities, as well as a municipal wastewater treatment works (WWTW). A metagenomic approach determined community profiles and dominant AMR genes at various sites, while carbapenem resistant colonies were characterized using whole genome sequencing (WGS). Isolates recovered from agricultural sites exhibited relatively high levels of resistance to carbapenems and colistin, whereas sites impacted by domestic run-off had a higher prevalence of resistance to gentamicin and sulfamethoxazole, corresponding to usage data in SA. Similar microbial taxa were identified in raw sewage, sites downstream of informal settlements, and industrial areas that have limited waste removal infrastructure while WWTW were seen to reduce the prevalence of ARB in treated wastewater when operating efficiently. The results indicate the multiple complex drivers underpinning environmental dissemination of AMR and suggest that WWTW assist in removing AMR from the environment, reinforcing the necessity of adequate waste removal infrastructure and antibiotic stewardship measures to mitigate AMR transmission. IMPORTANCE The results from this study are of importance as they fill a gap in the data available on environmental AMR in South Africa to date. This study was done in parallel with co-investigators focusing on the prevalence of various antimicrobials at the same sites selected in our study, verifying that the sites that are influenced by informal settlements and WWTW influent had higher concentrations of antimicrobials and antimicrobial metabolites. The various locations of the sample sites selected, the frequency of the samples collected over a year, and the different types of samples collected at each site all contribute to informing how AMR in the environment might be affected by anthropogenic activity.

Conservation of endangered species has become increasingly complex, and costly interventions to protect wildlife require a robust scientific evidence base. This includes consideration of the role of the microbiome in preserving animal health. Captivity introduces stressors not encountered in the wild including environmental factors and exposure to exotic species, humans and antimicrobial drugs. These stressors may perturb the microbiomes of wild animals, with negative consequences for their health and welfare and hence the success of the conservation project, and ultimately the risk of release of non-native organisms into native ecosystems. We compared the genomes of Staphylococcus aureus colonising critically endangered Livingstone's fruit bats (Pteropus livingstonii) which have been in a captive breeding programme for 25 years, with those from bats in the endemic founder population free ranging in the Comoros Republic. Using whole genome sequencing, we compared 47 isolates from captive bats with 37 isolates from those free ranging in the Comoros Republic. Our findings demonstrate unexpected resilience in the bacteria carried, with the captive bats largely retaining the same two distinctive lineages carried at the time of capture. In addition, we found evidence of genomic changes which suggest specific adaptations to the bat host., (© 2022. The Author(s).)

Researchers around the world have demonstrated correlations between measurements of SARS-CoV-2 RNA in wastewater (WW) and case rates of COVID-19 derived from direct testing of individuals. This has raised concerns that wastewater-based epidemiology (WBE) methods might be used to quantify the spread of this and other diseases, perhaps faster than direct testing, and with less expense and intrusion. We illustrate, using data from Scotland and the USA, the issues regarding the construction of effective predictive models for disease case rates. We discuss the effects of variation in, and the problem of aligning, public health (PH) reporting and WW measurements. We investigate time-varying effects in PH-reported case rates and their relationship to WW measurements. We show the lack of proportionality of WW measurements to case rates with associated spatial heterogeneity. We illustrate how the precision of predictions is affected by the level of aggregation chosen. We determine whether PH or WW measurements are the leading indicators of disease and how they may be used in conjunction to produce predictive models. The prospects of using WW-based predictive models with or without ongoing PH data are discussed.

A common approach to estimate the strength and direction of selection acting on protein coding sequences is to calculate the dN/dS ratio. The method to calculate dN/dS has been widely used by many researchers and many critical reviews have been made on its application after the proposition by Nei and Gojobori in 1986. However, the method is still evolving considering the non-uniform substitution rates and pretermination codons. In our study of SNPs in 586 genes across 156 Escherichia coli strains, synonymous polymorphism in 2-fold degenerate codons were higher in comparison to that in 4-fold degenerate codons, which could be attributed to the difference between transition (Ti) and transversion (Tv) substitution rates where the average rate of a transition is four times more than that of a transversion in general. We considered both the Ti/Tv ratio, and nonsense mutation in pretermination codons, to improve estimates of synonymous (S) and non-synonymous (NS) sites. The accuracy of estimating dN/dS has been improved by considering the Ti/Tv ratio and nonsense substitutions in pretermination codons. We showed that applying the modified approach based on Ti/Tv ratio and pretermination codons results in higher values of dN/dS in 29 common genes of equal reading-frames between E. coli and Salmonella enterica. This study emphasizes the robustness of amino acid composition with varying codon degeneracy, as well as the pretermination codons when calculating dN/dS values., (© The Author(s) 2022. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.)

Wastewater treatment plants have been highlighted as a potential hotspot for the development and spread of antibiotic resistance. Although antibiotic resistant bacteria in wastewater present a public health threat, it is also possible that these bacteria play an important role in the bioremediation through the metabolism of antibiotics before they reach the wider environment. Here we address this possibility with a particular emphasis on stereochemistry using a combination of microbiology and analytical chemistry tools including the use of supercritical-fluid chromatography coupled with mass spectrometry for chiral analysis and high-resolution mass spectrometry to investigate metabolites. Due to the complexities around chiral analysis the antibiotic chloramphenicol was used as a proof of concept to demonstrate stereoselective metabolism due to its relatively simple chemical structure and availability over the counter in the U.K. The results presented here demonstrate the chloramphenicol can be stereoselectively transformed by the chloramphenicol acetyltransferase enzyme with the orientation around the first stereocentre being key for this process, meaning that accumulation of two isomers may occur within the environment with potential impacts on ecotoxicity and emergence of bacterial antibiotic resistance within the environment., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

With the advent of the SARS-CoV-2 pandemic, Wastewater-Based Epidemiology (WBE) has been applied to track community infection in cities worldwide and has proven succesful as an early warning system for identification of hotspots and changingprevalence of infections (both symptomatic and asymptomatic) at a city or sub-city level. Wastewater is only one of environmental compartments that requires consideration. In this manuscript, we have critically evaluated the knowledge-base and preparedness for building early warning systems in a rapidly urbanising world, with particular attention to Africa, which experiences rapid population growth and urbanisation. We have proposed a Digital Urban Environment Fingerprinting Platform (DUEF) - a new approach in hazard forecasting and early-warning systems for global health risks and an extension to the existing concept of smart cities. The urban environment (especially wastewater) contains a complex mixture of substances including toxic chemicals, infectious biological agents and human excretion products. DUEF assumes that these specific endo- and exogenous residues, anonymously pooled by communities' wastewater, are indicative of community-wide exposure and the resulting effects. DUEF postulates that the measurement of the substances continuously and anonymously pooled by the receiving environment (sewage, surface water, soils and air), can provide near real-time dynamic information about the quantity and type of physical, biological or chemical stressors to which the surveyed systems are exposed, and can create a risk profile on the potential effects of these exposures. Successful development and utilisation of a DUEF globally requires a tiered approach including: Stage I: network building, capacity building, stakeholder engagement as well as a conceptual model, followed by Stage II: DUEF development, Stage III: implementation, and Stage IV: management and utilization. We have identified four key pillars required for the establishment of a DUEF framework: (1) Environmental fingerprints, (2) Socioeconomic fingerprints, (3) Statistics and modelling and (4) Information systems. This manuscript critically evaluates the current knowledge base within each pillar and provides recommendations for further developments with an aim of laying grounds for successful development of global DUEF platforms., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Transversion and transition mutations have variable effects on the stability of RNA secondary structure considering that the former destabilizes the double helix geometry to a greater extent by introducing purine:purine (R:R) or pyrimidine:pyrimidine (Y:Y) base pairs. Therefore, transversion frequency is likely to be lower than that of transition in the secondary structure regions of RNA genes. Here, we performed an analysis of transition and transversion frequencies in tRNA genes defined well with secondary structure and compared with the intergenic regions in five bacterial species namely Escherichia coli, Klebsiella pneumoniae, Salmonella enterica, Staphylococcus aureus and Streptococcus pneumoniae using a large genome sequence data set. In general, the transversion frequency was observed to be lower than that of transition in both tRNA genes and intergenic regions. The transition to transversion ratio was observed to be greater in tRNA genes than that in the intergenic regions in all the five bacteria that we studied. Interestingly, the intraspecies base substitution analysis in tRNA genes revealed that non-compensatory substitutions were more frequent than compensatory substitutions in the stem region. Further, transition to transversion ratio in the loop region was observed to be significantly lesser than that among the non-compensatory substitutions in the stem region. This indicated that the transversion is more deleterious than transition in the stem regions. In addition, substitutions from amino bases (A/C) to keto bases (G/T) were also observed to be more than the reverse substitutions in the stem region. Substitution from amino bases to keto bases are likely to facilitate the stable G:U pairing unlike the reverse substitution that facilitates the unstable A:C pairing in the stem region of tRNA. This work provides additional support that the secondary structure of tRNA molecule is what drives the different substitutions in its gene sequence., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The soil bacterium Burkholderia pseudomallei is the causative agent of melioidosis and a significant cause of human morbidity and mortality in many tropical and subtropical countries. The species notoriously survives harsh environmental conditions but the genetic architecture for these adaptations remains unclear. Here we employed a powerful combination of genome-wide epistasis and co-selection studies (2,011 genomes), condition-wide transcriptome analyses (82 diverse conditions), and a gene knockout assay to uncover signals of "co-selection"-that is a combination of genetic markers that have been repeatedly selected together through B. pseudomallei evolution. These enabled us to identify 13,061 mutation pairs under co-selection in distinct genes and noncoding RNA. Genes under co-selection displayed marked expression correlation when B. pseudomallei was subjected to physical stress conditions, highlighting the conditions as one of the major evolutionary driving forces for this bacterium. We identified a putative adhesin (BPSL1661) as a hub of co-selection signals, experimentally confirmed a BPSL1661 role under nutrient deprivation, and explored the functional basis of co-selection gene network surrounding BPSL1661 in facilitating the bacterial survival under nutrient depletion. Our findings suggest that nutrient-limited conditions have been the common selection pressure acting on this species, and allelic variation of BPSL1661 may have promoted B. pseudomallei survival during harsh environmental conditions by facilitating bacterial adherence to different surfaces, cells, or living hosts., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Background: Klebsiella species, including the notable pathogen K. pneumoniae, are increasingly associated with antimicrobial resistance (AMR). Genome-based surveillance can inform interventions aimed at controlling AMR. However, its widespread implementation requires tools to streamline bioinformatic analyses and public health reporting., Methods: We developed the web application Pathogenwatch, which implements analytics tailored to Klebsiella species for integration and visualization of genomic and epidemiological data. We populated Pathogenwatch with 16 537 public Klebsiella genomes to enable contextualization of user genomes. We demonstrated its features with 1636 genomes from 4 low- and middle-income countries (LMICs) participating in the NIHR Global Health Research Unit (GHRU) on AMR., Results: Using Pathogenwatch, we found that GHRU genomes were dominated by a small number of epidemic drug-resistant clones of K. pneumoniae. However, differences in their distribution were observed (eg, ST258/512 dominated in Colombia, ST231 in India, ST307 in Nigeria, ST147 in the Philippines). Phylogenetic analyses including public genomes for contextualization enabled retrospective monitoring of their spread. In particular, we identified hospital outbreaks, detected introductions from abroad, and uncovered clonal expansions associated with resistance and virulence genes. Assessment of loci encoding O-antigens and capsule in K. pneumoniae, which represent possible vaccine candidates, showed that 3 O-types (O1-O3) represented 88.9% of all genomes, whereas capsule types were much more diverse., Conclusions: Pathogenwatch provides a free, accessible platform for real-time analysis of Klebsiella genomes to aid surveillance at local, national, and global levels. We have improved representation of genomes from GHRU participant countries, further facilitating ongoing surveillance., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.)

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Mäklin T et al.)

Measuring molecular evolution in bacteria typically requires estimation of the rate at which nucleotide changes accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the 'birthday problem'. Using large genomic datasets and comparative genomic approaches, we use isolate pairs that share recent common ancestry to estimate the rate of nucleotide change for the population. Identifying synonymous and non-synonymous nucleotide changes, both within and outside of recombined regions of the genome, we quantify clock-like diversification to estimate synonymous rates of nucleotide change for the common pathogenic bacteria Campylobacter coli (2.4 x 10-6 s/s/y) and Campylobacter jejuni (3.4 x 10-6 s/s/y). Finally, using estimated total rates of nucleotide change, we infer the number of effective lineages within the sample time frame-analogous to a shared birthday-and assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalizable approach to calibrating rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species., Competing Interests: The authors have declared that no competing interests exist.

Studies to understand the role wastewater treatment plants (WWTPs) play in the dissemination of antibiotics (ABs), and in the emergence of antibiotic resistance (ABR), play an important role in tackling this global crisis. Here we describe the abundance and distribution of 16 ABs, and 4 corresponding antibiotic resistance genes (ARGs), sampled from the influent to five WWTPs within a single river catchment. We consider four classes of antibiotics: fluroquinolones, macrolides, sulfamethoxazole and chloramphenicol, as well the corresponding antibiotic resistance genes qnrS, ermB, sul1 and catA. All antibiotics, apart from four fluroquinolones (besifloxacin, lomefloxacin, ulifloxacin, prulifloxacin), were detected within all influent wastewater from the 5 cities (1 city = 1 WWTP), as were the corresponding antibiotic resistance genes (ARGs). Strong correlations were observed between the daily loads of ABs and ARGs versus the size of the population served by each WWTP, as well as between AB and ARG loads at a single site. The efficiency of ABs and ARGs removal by the WWTPs varied according to site (and treatment process utilized) and target, although strong correlations were maintained between the population size served by WWTPs and daily loads of discharged ABs and ARGs into the environment. We therefore conclude that population size is the main determinant of the magnitude of AB and ARG burden in the environment., (Copyright © 2021 Elsevier Ltd. All rights reserved.)