Quantifying bacterial evolution in the wild: A birthday problem for Campylobacter lineages.

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.

Co-evolutionary Signals Identify Burkholderia pseudomallei Survival Strategies in a Hostile Environment.

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.

Integrated chromosomal and plasmid sequence analyses reveal diverse modes of carbapenemase gene spread among Klebsiella pneumoniae.

Molecular and genomic surveillance systems for bacterial pathogens currently rely on tracking clonally evolving lineages. By contrast, plasmids are usually excluded or analyzed with low-resolution techniques, despite being the primary vectors of antibiotic resistance genes across many key pathogens. Here, we used a combination of long- and short-read sequence data of Klebsiella pneumoniae isolates (n = 1,717) from a European survey to perform an integrated, continent-wide study of chromosomal and plasmid diversity. This revealed three contrasting modes of dissemination used by carbapenemase genes, which confer resistance to last-line carbapenems. First, blaOXA-48-like genes have spread primarily via the single epidemic pOXA-48-like plasmid, which emerged recently in clinical settings and spread rapidly to numerous lineages. Second, blaVIM and blaNDM genes have spread via transient associations of many diverse plasmids with numerous lineages. Third, blaKPC genes have transmitted predominantly by stable association with one successful clonal lineage (ST258/512) yet have been mobilized among diverse plasmids within this lineage. We show that these plasmids, which include pKpQIL-like and IncX3 plasmids, have a long association (and are coevolving) with the lineage, although frequent recombination and rearrangement events between them have led to a complex array of mosaic plasmids carrying blaKPC Taken altogether, these results reveal the diverse trajectories of antibiotic resistance genes in clinical settings, summarized as using one plasmid/multiple lineages, multiple plasmids/multiple lineages, and multiple plasmids/one lineage. Our study provides a framework for the much needed incorporation of plasmid data into genomic surveillance systems, an essential step toward a more comprehensive understanding of resistance spread.

Stem Region of tRNA Genes Favors Transition Substitution Towards Keto Bases in Bacteria.

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.

Challenges in realising the potential of wastewater-based epidemiology to quantitatively monitor and predict the spread of disease.

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.

Rapid Genomic Characterization and Global Surveillance of Klebsiella Using Pathogenwatch.

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.

Real time monitoring of Aeromonas salmonicida evolution in response to successive antibiotic therapies in a commercial fish farm.

Our ability to predict evolutionary trajectories of pathogens in response to antibiotic pressure is one of the promising leverage to fight against the present antibiotic resistance worldwide crisis. Yet, few studies tackled this question in situ at the outbreak level, due to the difficulty to link a given pathogenic clone evolution with its precise antibiotic exposure over time. In this study, we monitored the real-time evolution of an Aeromonas salmonicida clone in response to successive antibiotic and vaccine therapies in a commercial fish farm. The clone was responsible for a four-year outbreak of furunculosis within a Recirculating Aquaculture System Salmo salar farm in China, and we reconstructed the precise tempo of mobile genetic elements (MGEs) acquisition events during this period. The resistance profile provided by the acquired MGEs closely mirrored the antibiotics used to treat the outbreak, and we evidenced that two subclonal groups developed similar resistances although unrelated MGE acquisitions. Finally, we also demonstrated the efficiency of vaccination in outbreak management and its positive effect on antibiotic resistance prevalence. Our study provides unprecedented knowledge critical to understand evolutionary trajectories of resistant pathogens outside the laboratory.

Building a genomic framework for prospective MRSA surveillance in the United Kingdom and the Republic of Ireland.

The correct interpretation of microbial sequencing data applied to surveillance and outbreak investigation depends on accessible genomic databases to provide vital genetic context. Our aim was to construct and describe a United Kingdom MRSA database containing over 1000 methicillin-resistant Staphylococcus aureus (MRSA) genomes drawn from England, Northern Ireland, Wales, Scotland, and the Republic of Ireland over a decade. We sequenced 1013 MRSA submitted to the British Society for Antimicrobial Chemotherapy by 46 laboratories between 2001 and 2010. Each isolate was assigned to a regional healthcare referral network in England and was otherwise grouped based on country of origin. Phylogenetic reconstructions were used to contextualize MRSA outbreak investigations and to detect the spread of resistance. The majority of isolates (n = 783, 77%) belonged to CC22, which contains the dominant United Kingdom epidemic clone (EMRSA-15). There was marked geographic structuring of EMRSA-15, consistent with widespread dissemination prior to the sampling decade followed by local diversification. The addition of MRSA genomes from two outbreaks and one pseudo-outbreak demonstrated the certainty with which outbreaks could be confirmed or refuted. We identified local and regional differences in antibiotic resistance profiles, with examples of local expansion, as well as widespread circulation of mobile genetic elements across the bacterial population. We have generated a resource for the future surveillance and outbreak investigation of MRSA in the United Kingdom and Ireland and have shown the value of this during outbreak investigation and tracking of antimicrobial resistance.

WGS of 1058 Enterococcus faecium from Copenhagen, Denmark, reveals rapid clonal expansion of vancomycin-resistant clone ST80 combined with widespread dissemination of a vanA-containing plasmid and acquisition of a heterogeneous accessory genome.

OBJECTIVES: From 2012 to 2015, a sudden significant increase in vancomycin-resistant (vanA) Enterococcus faecium (VREfm) was observed in the Capital Region of Denmark. Clonal relatedness of VREfm and vancomycin-susceptible E. faecium (VSEfm) was investigated, transmission events between hospitals were identified and the pan-genome and plasmids from the largest VREfm clonal group were characterized. METHODS: WGS of 1058 E. faecium isolates was carried out on the Illumina platform to perform SNP analysis and to identify the pan-genome. One isolate was also sequenced on the PacBio platform to close the genome. Epidemiological data were collected from laboratory information systems. RESULTS: Phylogeny of 892 VREfm and 166 VSEfm revealed a polyclonal structure, with a single clonal group (ST80) accounting for 40% of the VREfm isolates. VREfm and VSEfm co-occurred within many clonal groups; however, no VSEfm were related to the dominant VREfm group. A similar vanA plasmid was identified in ≥99% of isolates belonging to the dominant group and 69% of the remaining VREfm. Ten plasmids were identified in the completed genome, and ∼29% of this genome consisted of dispensable accessory genes. The size of the pan-genome among isolates in the dominant group was 5905 genes. CONCLUSIONS: Most probably, VREfm emerged owing to importation of a successful VREfm clone which rapidly transmitted to the majority of hospitals in the region whilst simultaneously disseminating a vanA plasmid to pre-existing VSEfm. Acquisition of a heterogeneous accessory genome may account for the success of this clone by facilitating adaptation to new environmental challenges.

Closed genome sequences of Staphylococcus lloydii sp. nov. and Staphylococcus durrellii sp. nov. isolated from captive fruit bats (Pteropus livingstonii).

The increasing availability of whole genome sequencing of bacteria has accelerated the discovery of novel species which may not have been easy to discriminate using standard phenotypic or single gene methods. Phylogenomic analysis of genome sequences from a collection of coagulase-negative staphylococcal species isolated from captive fruit bats revealed two clusters which were close to Staphylococcus kloosii. To assess the relatedness of the strains we used digital DNA-DNA hybridization (dDDH) and two methods for average nucleotide identity (ANI) computation which predicted two novel species having dDDH less than 70 % and ANI less than 95%. We propose these species as Staphylococcus lloydii sp. nov. (type strain 23_2_7_LYT=NCTC 14453T=DSM 111639T) and Staphylococcus durrellii sp. nov (type strain 27_4_6_LYT=NCTC 14454T=DSM 111640T).

Predicting the virulence of MRSA from its genome sequence.

Microbial virulence is a complex and often multifactorial phenotype, intricately linked to a pathogen's evolutionary trajectory. Toxicity, the ability to destroy host cell membranes, and adhesion, the ability to adhere to human tissues, are the major virulence factors of many bacterial pathogens, including Staphylococcus aureus. Here, we assayed the toxicity and adhesiveness of 90 MRSA (methicillin resistant S. aureus) isolates and found that while there was remarkably little variation in adhesion, toxicity varied by over an order of magnitude between isolates, suggesting different evolutionary selection pressures acting on these two traits. We performed a genome-wide association study (GWAS) and identified a large number of loci, as well as a putative network of epistatically interacting loci, that significantly associated with toxicity. Despite this apparent complexity in toxicity regulation, a predictive model based on a set of significant single nucleotide polymorphisms (SNPs) and insertion and deletions events (indels) showed a high degree of accuracy in predicting an isolate's toxicity solely from the genetic signature at these sites. Our results thus highlight the potential of using sequence data to determine clinically relevant parameters and have further implications for understanding the microbial virulence of this opportunistic pathogen.

Alternative Splice in Alternative Lice.

Genomic and transcriptomics analyses have revealed human head and body lice to be almost genetically identical; although con-specific, they nevertheless occupy distinct ecological niches and have differing feeding patterns. Most importantly, while head lice are not known to be vector competent, body lice can transmit three serious bacterial diseases; epidemictyphus, trench fever, and relapsing fever. In order to gain insights into the molecular bases for these differences, we analyzed alternative splicing (AS) using next-generation sequencing data for one strain of head lice and one strain of body lice. We identified a total of 3,598 AS events which were head or body lice specific. Exon skipping AS events were overrepresented among both head and body lice, whereas intron retention events were underrepresented in both. However, both the enrichment of exon skipping and the underrepresentation of intron retention are significantly stronger in body lice compared with head lice. Genes containing body louse-specific AS events were found to be significantly enriched for functions associated with development of the nervous system, salivary gland, trachea, and ovarian follicle cells, as well as regulation of transcription. In contrast, no functional categories were overrepresented among genes with head louse-specific AS events. Together, our results constitute the first evidence for transcript pool differences in head and body lice, providing insights into molecular adaptations that enabled human lice to adapt to clothing, and representing a powerful illustration of the pivotal role AS can play in functional adaptation.

A genomic portrait of the emergence, evolution, and global spread of a methicillin-resistant Staphylococcus aureus pandemic.

The widespread use of antibiotics in association with high-density clinical care has driven the emergence of drug-resistant bacteria that are adapted to thrive in hospitalized patients. Of particular concern are globally disseminated methicillin-resistant Staphylococcus aureus (MRSA) clones that cause outbreaks and epidemics associated with health care. The most rapidly spreading and tenacious health-care-associated clone in Europe currently is EMRSA-15, which was first detected in the UK in the early 1990s and subsequently spread throughout Europe and beyond. Using phylogenomic methods to analyze the genome sequences for 193 S. aureus isolates, we were able to show that the current pandemic population of EMRSA-15 descends from a health-care-associated MRSA epidemic that spread throughout England in the 1980s, which had itself previously emerged from a primarily community-associated methicillin-sensitive population. The emergence of fluoroquinolone resistance in this EMRSA-15 subclone in the English Midlands during the mid-1980s appears to have played a key role in triggering pandemic spread, and occurred shortly after the first clinical trials of this drug. Genome-based coalescence analysis estimated that the population of this subclone over the last 20 yr has grown four times faster than its progenitor. Using comparative genomic analysis we identified the molecular genetic basis of 99.8% of the antimicrobial resistance phenotypes of the isolates, highlighting the potential of pathogen genome sequencing as a diagnostic tool. We document the genetic changes associated with adaptation to the hospital environment and with increasing drug resistance over time, and how MRSA evolution likely has been influenced by country-specific drug use regimens.

Transmission of Staphylococcus aureus from Humans to Green Monkeys in The Gambia as Revealed by Whole-Genome Sequencing.

UNLABELLED: Staphylococcus aureus is an important pathogen of humans and animals. We genome sequenced 90 S. aureus isolates from The Gambia: 46 isolates from invasive disease in humans, 13 human carriage isolates, and 31 monkey carriage isolates. We inferred multiple anthroponotic transmissions of S. aureus from humans to green monkeys (Chlorocebus sabaeus) in The Gambia over different time scales. We report a novel monkey-associated clade of S. aureus that emerged from a human-to-monkey switch estimated to have occurred 2,700 years ago. Adaptation of this lineage to the monkey host is accompanied by the loss of phage-carrying genes that are known to play an important role in human colonization. We also report recent anthroponotic transmission of the well-characterized human lineages sequence type 6 (ST6) and ST15 to monkeys, probably because of steadily increasing encroachment of humans into the monkeys' habitat. Although we have found no evidence of transmission of S. aureus from monkeys to humans, as the two species come into ever-closer contact, there might be an increased risk of additional interspecies exchanges of potential pathogens. IMPORTANCE: The population structures of Staphylococcus aureus in humans and monkeys in sub-Saharan Africa have been previously described using multilocus sequence typing (MLST). However, these data lack the power to accurately infer details regarding the origin and maintenance of new adaptive lineages. Here, we describe the use of whole-genome sequencing to detect transmission of S. aureus between humans and nonhuman primates and to document the genetic changes accompanying host adaptation. We note that human-to-monkey switches tend to be more common than the reverse and that a novel monkey-associated clade is likely to have emerged from such a switch approximately 2,700 years ago. Moreover, analysis of the accessory genome provides important clues as to the genetic changes underpinning host adaptation and, in particular, shows that human-to-monkey switches tend to be associated with the loss of genes known to confer adaptation to the human host.

The impact of host metapopulation structure on the population genetics of colonizing bacteria.

Many key bacterial pathogens are frequently carried asymptomatically, and the emergence and spread of these opportunistic pathogens can be driven, or mitigated, via demographic changes within the host population. These inter-host transmission dynamics combine with basic evolutionary parameters such as rates of mutation and recombination, population size and selection, to shape the genetic diversity within bacterial populations. Whilst many studies have focused on how molecular processes underpin bacterial population structure, the impact of host migration and the connectivity of the local populations has received far less attention. A stochastic neutral model incorporating heightened local transmission has been previously shown to fit closely with genetic data for several bacterial species. However, this model did not incorporate transmission limiting population stratification, nor the possibility of migration of strains between subpopulations, which we address here by presenting an extended model. We study the consequences of migration in terms of shared genetic variation and show by simulation that the previously used summary statistic, the allelic mismatch distribution, can be insensitive to even large changes in microepidemic and migration rates. Using likelihood-free inference with genotype network topological summaries we fit a simpler model to commensal and hospital samples from the common nosocomial pathogens Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis and Enterococcus faecium. Only the hospital data for E. faecium display clearly marked deviations from the model predictions which may be attributable to its adaptation to the hospital environment.

Molecular tracing of the emergence, adaptation, and transmission of hospital-associated methicillin-resistant Staphylococcus aureus.

Hospital-associated infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are a global health burden dominated by a small number of bacterial clones. The pandemic EMRSA-16 clone (ST36-II) has been widespread in UK hospitals for 20 y, but its evolutionary origin and the molecular basis for its hospital association are unclear. We carried out a Bayesian phylogenetic reconstruction on the basis of the genome sequences of 87 S. aureus isolates including 60 EMRSA-16 and 27 additional clonal complex 30 (CC30) isolates, collected from patients in three continents over a 53-y period. The three major pandemic clones to originate from the CC30 lineage, including phage type 80/81, Southwest Pacific, and EMRSA-16, shared a most recent common ancestor that existed over 100 y ago, whereas the hospital-associated EMRSA-16 clone is estimated to have emerged about 35 y ago. Our CC30 genome-wide analysis revealed striking molecular correlates of hospital- or community-associated pandemics represented by mobile genetic elements and nonsynonymous mutations affecting antibiotic resistance and virulence. Importantly, phylogeographic analysis indicates that EMRSA-16 spread within the United Kingdom by transmission from hospitals in large population centers in London and Glasgow to regional health-care settings, implicating patient referrals as an important cause of nationwide transmission. Taken together, the high-resolution phylogenomic approach used resulted in a unique understanding of the emergence and transmission of a major MRSA clone and provided molecular correlates of its hospital adaptation. Similar approaches for hospital-associated clones of other bacterial pathogens may inform appropriate measures for controlling their intra- and interhospital spread.

Atypical at skew in Firmicute genomes results from selection and not from mutation.

The second parity rule states that, if there is no bias in mutation or selection, then within each strand of DNA complementary bases are present at approximately equal frequencies. In bacteria, however, there is commonly an excess of G (over C) and, to a lesser extent, T (over A) in the replicatory leading strand. The low G+C Firmicutes, such as Staphylococcus aureus, are unusual in displaying an excess of A over T on the leading strand. As mutation has been established as a major force in the generation of such skews across various bacterial taxa, this anomaly has been assumed to reflect unusual mutation biases in Firmicute genomes. Here we show that this is not the case and that mutation bias does not explain the atypical AT skew seen in S. aureus. First, recently arisen intergenic SNPs predict the classical replication-derived equilibrium enrichment of T relative to A, contrary to what is observed. Second, sites predicted to be under weak purifying selection display only weak AT skew. Third, AT skew is primarily associated with largely non-synonymous first and second codon sites and is seen with respect to their sense direction, not which replicating strand they lie on. The atypical AT skew we show to be a consequence of the strong bias for genes to be co-oriented with the replicating fork, coupled with the selective avoidance of both stop codons and costly amino acids, which tend to have T-rich codons. That intergenic sequence has more A than T, while at mutational equilibrium a preponderance of T is expected, points to a possible further unresolved selective source of skew.

Optimising machine learning prediction of minimum inhibitory concentrations in Klebsiella pneumoniae.

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.

Arctic cyanobacterial mat community diversity decreases with latitude across the Canadian Arctic.

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.