De Novo Mutation Rate Variation and Its Determinants in Chlamydomonas.

De novo mutations are central for evolution, since they provide the raw material for natural selection by regenerating genetic variation. However, studying de novo mutations is challenging and is generally restricted to model species, so we have a limited understanding of the evolution of the mutation rate and spectrum between closely related species. Here, we present a mutation accumulation (MA) experiment to study de novo mutation in the unicellular green alga Chlamydomonas incerta and perform comparative analyses with its closest known relative, Chlamydomonas reinhardtii. Using whole-genome sequencing data, we estimate that the median single nucleotide mutation (SNM) rate in C. incerta is µ = 7.6 × 10-10, and is highly variable between MA lines, ranging from µ = 0.35 × 10-10 to µ = 131.7 × 10-10. The SNM rate is strongly positively correlated with the mutation rate for insertions and deletions between lines (r > 0.97). We infer that the genomic factors associated with variation in the mutation rate are similar to those in C. reinhardtii, allowing for cross-prediction between species. Among these genomic factors, sequence context and complexity are more important than GC content. With the exception of a remarkably high C→T bias, the SNM spectrum differs markedly between the two Chlamydomonas species. Our results suggest that similar genomic and biological characteristics may result in a similar mutation rate in the two species, whereas the SNM spectrum has more freedom to diverge.

Inferring the distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii.

Spontaneous mutations are the source of new genetic variation and are thus central to the evolutionary process. In molecular evolution and quantitative genetics, the nature of genetic variation depends critically on the distribution of effects of mutations on fitness and other quantitative traits. Spontaneous mutation accumulation (MA) experiments have been the principal approach for investigating the overall rate of occurrence and cumulative effect of mutations but have not allowed the phenotypic effects of individual mutations to be studied directly. Here, we crossed MA lines of the green alga Chlamydomonas reinhardtii with its unmutated ancestral strain to create haploid recombinant lines, each carrying an average of 50% of the accumulated mutations in a large number of combinations. With the aid of the genome sequences of the MA lines, we inferred the genotypes of the mutations, assayed their growth rate as a measure of fitness, and inferred the distribution of fitness effects (DFE) using a Bayesian mixture model. We infer that the DFE is highly leptokurtic (L-shaped). Of mutations with absolute fitness effects exceeding 1%, about one-sixth increase fitness in the laboratory environment. The inferred distribution of effects for deleterious mutations is consistent with a strong role for nearly neutral evolution. Specifically, such a distribution predicts that nucleotide variation and genetic variation for quantitative traits will be insensitive to change in the effective population size.

Direct Estimate of the Spontaneous Mutation Rate Uncovers the Effects of Drift and Recombination in the Chlamydomonas reinhardtii Plastid Genome.

Plastids perform crucial cellular functions, including photosynthesis, across a wide variety of eukaryotes. Since endosymbiosis, plastids have maintained independent genomes that now display a wide diversity of gene content, genome structure, gene regulation mechanisms, and transmission modes. The evolution of plastid genomes depends on an input of de novo mutation, but our knowledge of mutation in the plastid is limited to indirect inference from patterns of DNA divergence between species. Here, we use a mutation accumulation experiment, where selection acting on mutations is rendered ineffective, combined with whole-plastid genome sequencing to directly characterize de novo mutation in Chlamydomonas reinhardtii. We show that the mutation rates of the plastid and nuclear genomes are similar, but that the base spectra of mutations differ significantly. We integrate our measure of the mutation rate with a population genomic data set of 20 individuals, and show that the plastid genome is subject to substantially stronger genetic drift than the nuclear genome. We also show that high levels of linkage disequilibrium in the plastid genome are not due to restricted recombination, but are instead a consequence of increased genetic drift. One likely explanation for increased drift in the plastid genome is that there are stronger effects of genetic hitchhiking. The presence of recombination in the plastid is consistent with laboratory studies in C. reinhardtii and demonstrates that although the plastid genome is thought to be uniparentally inherited, it recombines in nature at a rate similar to the nuclear genome.

Evidence for microbial local adaptation in nature.

Local adaptation is an outcome of divergent selection on microbial populations and has been linked to the immense genetic diversity of microbes observed in nature. Because it is difficult to study microbes in their natural habitats, most tests of microbial local adaptation have been performed in model laboratory systems; as a result, microbiologists have limited understanding of local adaptation among natural microbial populations. In this review, we summarize the evidence for microbial local adaptation in nature. Local adaptation has been most frequently studied, and most frequently found, in host-pathogen systems. We argue that more research is needed to understand the prevalence of local adaptation in free-living microbial populations. However, researchers will need to overcome a variety of logistical and conceptual challenges when studying natural microbial local adaptation, including a lack of solid understanding of many microbes' natural histories. We propose strategies to facilitate future natural history research on divergent selection. We also summarize laboratory experimental work investigating the ecological and evolutionary processes leading to local adaptation. Microbiologists' ongoing challenge is to integrate the valuable knowledge gained from laboratory experiments into well-designed field experiments. Such integration will help us understand the prevalence of, and circumstances leading to, local adaptation among microorganisms.

Temporal patterns of local adaptation in soil pseudomonads.

Strong divergent selection leading to local adaptation is often invoked to explain the staggering diversity of bacteria in microbial ecosystems. However, examples of specialization by bacterial clones to alternative niches in nature are rare. Here, we investigate the extent of local adaptation in natural isolates of pseudomonads and their relatives to their soil environments across both space and time. Though most isolates grew well in most environments, patchily distributed low-quality environments were found to drive specialization. In contrast to experimental evolution work on microbial adaptation, temporal adaptation was stronger than spatial adaptation among the isolates and environments we sampled. Time-shift analysis of fitness across two seasons of growth revealed an unexpectedly strong effect of preadaptation. This pattern of apparent future adaptation may be caused by unknown abiotic properties of these environments, phages, bacterial competitors or general mechanisms of ecological niche release, and warrants future study.

The biogeography of kin discrimination across microbial neighbourhoods.

The spatial distribution of potential interactants is critical to social evolution in all cooperative organisms. Yet the biogeography of microbial kin discrimination at the scales most relevant to social interactions is poorly understood. Here we resolve the microbiogeography of social identity and genetic relatedness in local populations of the model cooperative bacterium Myxococcus xanthus at small spatial scales, across which the potential for dispersal is high. Using two criteria of relatedness-colony-merger compatibility during cooperative motility and DNA-sequence similarity at highly polymorphic loci-we find that relatedness decreases greatly with spatial distance even across the smallest scale transition. Both social relatedness and genetic relatedness are maximal within individual fruiting bodies at the micrometre scale but are much lower already across adjacent fruiting bodies at the millimetre scale. Genetic relatedness was found to be yet lower among centimetre-scale samples, whereas social allotype relatedness decreased further only at the metre scale, at and beyond which the probability of social or genetic identity among randomly sampled isolates is effectively zero. Thus, in M. xanthus, high-relatedness patches form a rich mosaic of diverse social allotypes across fruiting body neighbourhoods at the millimetre scale and beyond. Individuals that migrate even short distances across adjacent groups will frequently encounter allotypic conspecifics and territorial kin discrimination may profoundly influence the spatial dynamics of local migration. Finally, we also found that the phylogenetic scope of intraspecific biogeographic analysis can affect the detection of spatial structure, as some patterns evident in clade-specific analysis were masked by simultaneous analysis of all strains.

Patterns of local adaptation in space and time among soil bacteria.

Our understanding of microbial biogeography has been governed by the dictum "Everything is everywhere, but the environment selects." In other words, the distribution of microbes is thought to occur in a regime of extensive dispersal and strong selection, generating local adaptation. However, direct tests of these assumptions are rare. Here, we investigate the extent of local adaptation in space and time of a collection of soil-derived microbial isolates, most belonging to the genus Pseudomonas, across a growing season from a deciduous forest in western Quebec, Canada, using a reciprocal transplant design. Average performance of all clones varied substantially in both space and time, in line with the expectation of strong selection in both dimensions. The behavior of genotype-by-environment variance in fitness and its components, responsiveness and inconsistency, in space and through time suggests that the strength of divergent selection increases as sites become more distant from each other in both dimensions. However, divergent selection was not strong enough to maintain different specialized types across the environments studied, which suggests that Pseudomonas and their close relatives are not locally adapted to the prevailing conditions of growth.

Relationship of insight with medication adherence and the impact on outcomes in patients with schizophrenia and bipolar disorder: results from a 1-year European outpatient observational study.

BACKGROUND: Many patients with schizophrenia and bipolar disorder have impaired insight and low medication adherence. The aim of this post hoc analysis was to explore the relationship between insight and medication adherence. METHODS: We included 903 patients with schizophrenia or bipolar disorder who participated in an observational study conducted in Europe on the outcomes of patients treated with two oral formulations of olanzapine over a 1-year period. Evaluations included Clinical Global Impression (CGI), Global Assessment of Functioning (GAF), insight (Scale to Assess Unawareness of Mental Disorder, SUMD) medication adherence (Medication Adherence Rating Scale, MARS), and therapeutic alliance (Working Alliance Inventory, WAI). RESULTS: Medication adherence was higher in bipolar patients (mean MARS score (SD) 6.5 (2.8) versus 5.8 (2.7) in schizophrenia; p < 0.001). Patients with schizophrenia had lower insight (i.e., SUMD item 1, unawareness of mental disorder, mean (SD) of 2.5 (1.3) in schizophrenia versus 1.9 (1.2) in bipolar, p < 0.001). Better insight was associated with higher adherence (Spearman Correlation Coefficient, SCC, ranging from 0.39 to 0.49 for the three SUMD general items, p < 0.0001 in all cases). Higher insight was related to a stronger therapeutic alliance (SCC ranging from 0.38 to 0.48, p < 0.0001). A path analysis revealed a positive impact of insight on adherence and alliance and that stronger alliance was related to lower clinical severity (lower CGI score). CONCLUSION: Insight and adherence were found to be closely related. Insight impacts on the therapeutic alliance with mental health professionals. These factors are associated to treatment outcomes.

Prevalence of ADHD in nonpsychotic adult psychiatric care (ADPSYC): A multinational cross-sectional study in Europe.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) often persists into adulthood. This study was designed to estimate the prevalence of ADHD in adult psychiatric outpatients in several European countries. METHOD: ADHD diagnosis was made using the Diagnostic Interview for ADHD in Adults, version 2.0 (DIVA), according to criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR) and 5th Edition (DSM-5). RESULTS: Of 5662 patients present/approached, 2284 (40.3 %) consented, of whom 1986 patients (87.0 %) completed the study. Based on the DIVA, and applying DSM-IV-TR or DSM-5 criteria, 15.8 % (95 % confidence interval [CI] 14.2 %-17.4 %) or 17.4 % (95 % CI 15.7 %-19.0 %) of patients were diagnosed with ADHD, respectively. The prevalence of ADHD was 15.3 % when counting as non-ADHD those patients who screened positive but did not complete the DIVA (DSM-5). CONCLUSIONS: Estimates from this study indicate that a relevant part of the psychiatric outpatient care population suffers from ADHD.

Social complementation and growth advantages promote socially defective bacterial isolates.

Social interactions among diverse individuals that encounter one another in nature have often been studied among animals but rarely among microbes. For example, the evolutionary forces that determine natural frequencies of bacteria that express cooperative behaviours at low levels remain poorly understood. Natural isolates of the soil bacterium Myxococcus xanthus sampled from the same fruiting body often vary in social phenotypes, such as group swarming and multicellular development. Here, we tested whether genotypes highly proficient at swarming or development might promote the persistence of less socially proficient genotypes from the same fruiting body. Fast-swarming strains complemented slower isolates, allowing the latter to keep pace with faster strains in mixed groups. During development, one low-sporulating strain was antagonized by high sporulators, whereas others with severe developmental defects had those defects partially complemented by high-sporulating strains. Despite declining in frequency overall during competition experiments spanning multiple cycles of development, developmentally defective strains exhibited advantages during the growth phases of competitions. These results suggest that microbes with low-sociality phenotypes often benefit from interacting with more socially proficient strains. Such complementation may combine with advantages at other traits to increase equilibrium frequencies of low-sociality genotypes in natural populations.

Endemic social diversity within natural kin groups of a cooperative bacterium.

The spatial structure of genetic diversity underlying social variation is a critical determinant of how cooperation and conflict evolve. Here we investigated whether natural social groups of the cooperative soil bacterium Myxococcus xanthus harbor internal genetic and phenotypic variation and thus the potential for social conflict between interacting cells. Ten M. xanthus fruiting bodies isolated from soil were surveyed for variation in multiple social phenotypes and genetic loci, and patterns of diversity within and across fruiting body groups were examined. Eight of the 10 fruiting bodies were found to be internally diverse, with four exhibiting significant variation in social swarming phenotypes and five harboring large variation in the number of spores produced by member clones in pure culture. However, genetic variation within fruiting bodies was much lower than across fruiting bodies, suggesting that migration across even spatially proximate groups is limited relative to mutational generation of persisting endemic diversity. Our results simultaneously highlight the potential for social conflict within Myxococcus social groups and the possibility of social coevolution among diverse related lineages that are clustered in space and cotransmitted across generations.

A multiyear time series (2004-2012) of bacterial and archaeal community dynamics in a changing Arctic Ocean.

Climate change is profoundly impacting the Arctic, leading to a loss of multiyear sea ice and a warmer, fresher upper Arctic Ocean. The response of microbial communities to these climate-mediated changes is largely unknown. Here, we document the interannual variation in bacterial and archaeal communities across a 9-year time series of the Canada Basin that includes two historic sea ice minima (2007 and 2012). We report an overall loss of bacterial and archaeal community richness and significant shifts in community composition. The magnitude and period of most rapid change differed between the stratified water layers. The most pronounced changes in the upper water layers (surface mixed layer and upper Arctic water) occurred earlier in the time series, while changes in the lower layer (Pacific-origin water) occurred later. Shifts in taxonomic composition across time were subtle, but a decrease in Bacteroidota taxa and increase in Thaumarchaeota and Euryarchaeota taxa were the clearest signatures of change. This time series provides a rare glimpse into the potential influence of climate change on Arctic microbial communities; extension to the present day should contribute to deeper insights into the trajectory of Arctic marine ecosystems in response to warming and freshening.

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data.

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.

The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology.

The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). In addition, the Portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. From inception to execution, the portal was developed with a conscientious focus on strong data governance principles and practices. Extensive efforts ensured a commitment to Canadian privacy laws, data security standards, and organizational processes. This Portal has been coupled with other resources like Viral AI and was further leveraged by the Coronavirus Variants Rapid Response Network (CoVaRR-Net) to produce a suite of continually updated analytical tools and notebooks. Here we highlight this Portal, including its contextual data not available elsewhere, and the 'Duotang', a web platform that presents key genomic epidemiology and modeling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the Portal (COVID-MVP, CoVizu), are all open-source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.

The Canadian VirusSeq Data Portal and Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology.

The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform the public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). In addition, the portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. From inception to execution, the portal was developed with a conscientious focus on strong data governance principles and practices. Extensive efforts ensured a commitment to Canadian privacy laws, data security standards, and organizational processes. This portal has been coupled with other resources, such as Viral AI, and was further leveraged by the Coronavirus Variants Rapid Response Network (CoVaRR-Net) to produce a suite of continually updated analytical tools and notebooks. Here we highlight this portal (https://virusseq-dataportal.ca/), including its contextual data not available elsewhere, and the Duotang (https://covarr-net.github.io/duotang/duotang.html), a web platform that presents key genomic epidemiology and modelling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the portal (COVID-MVP, CoVizu), are all open source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.

Comparably high retention and low relapse rates in different subpopulations of bipolar patients in a German non-interventional study.

BACKGROUND: Although a range of pharmacotherapeutical options are available for the treatment of bipolar disorder, patient non-adherence to prescribed treatment regimens and early treatment discontinuation remain among the primary obstacles to effective treatment. Therefore, this observational study assessed time on mood stabilizing medication and retention rates in patients with bipolar disorder (BD). METHODS: In an 18-month, prospective, multicenter, non-interventional study conducted in Germany 761 outpatients (≥18 years) with BD and on maintenance therapy were documented. For analysis, patients were stratified by baseline medication: monotherapy olanzapine (OM, N = 186), lithium (LM, N = 152), anticonvulsants (N = 216), other mood stabilizing medication (OMS, N = 44); combination therapy olanzapine/lithium (N = 47), olanzapine/anticonvulsant (N = 68), other combinations (OC, N = 48). Continuation on medication was assessed as retention rates with 95% confidence intervals. Time to discontinuation and relapse-free time were calculated by Kaplan-Meier analysis. A relapse was defined as increase to CGI-BP >3, worsening of CGI-BP by ≥2 points, hospitalization or death related to BD. A Cox regression was calculated for the discontinuation of mood stabilizing therapy (reference: OM). Logistic regression models with stepwise forward selection were used to explore possible predictors of maintenance of treatment and relapse. RESULTS: After 540 days (18 months), the overall retention rate of baseline medication was 87.7%, without notable differences between the cohorts. The overall mean time on mood stabilizing treatment was 444.7 days, with a range of 377.5 (OMS) to 481 (LM) by cohort. 74.0% of all patients were without relapse, with rates between the cohorts ranging from 58.4% (OC) to 80.2% (LM). CONCLUSIONS: Retention rates exceeded controlled trial results in all treatment cohorts, in addition to other explanations possibly reflecting that the physicians were expertly adapting treatment regimens to the individual patient's disease characteristics and special needs.

Antibiotic resistance gene sequencing is necessary to reveal the complex dynamics of immigration from sewers to activated sludge.

Microbial community composition has increasingly emerged as a key determinant of antibiotic resistance gene (ARG) content. However, in activated sludge wastewater treatment plants (AS-WWTPs), a comprehensive understanding of the microbial community assembly process and its impact on the persistence of antimicrobial resistance (AMR) remains elusive. An important part of this process is the immigration dynamics (or community coalescence) between the influent and activated sludge. While the influent wastewater contains a plethora of ARGs, the persistence of a given ARG depends initially on the immigration success of the carrying population, and the possible horizontal transfer to indigenously resident populations of the WWTP. The current study utilized controlled manipulative experiments that decoupled the influent wastewater composition from the influent microbial populations to reveal the fundamental mechanisms involved in ARG immigration between sewers and AS-WWTP. A novel multiplexed amplicon sequencing approach was used to track different ARG sequence variants across the immigration interface, and droplet digital PCR was used to quantify the impact of immigration on the abundance of the targeted ARGs. Immigration caused an increase in the abundance of over 70 % of the quantified ARGs. However, monitoring of ARG amplicon sequence variants (ARG-ASVs) at the immigration interface revealed various immigration patterns such as (i) suppression of the indigenous mixed liquor ARG-ASV by the immigrant, or conversely (ii) complete immigration failure of the influent ARG-ASV. These immigration profiles are reported for the first time here and highlight the crucial information that can be gained using our novel multiplex amplicon sequencing techniques. Future studies aiming to reduce AMR in WWTPs should consider the impact of influent immigration in process optimisation and design.

A genome catalogue of lake bacterial diversity and its drivers at continental scale.

Lakes are heterogeneous ecosystems inhabited by a rich microbiome whose genomic diversity is poorly defined. We present a continental-scale study of metagenomes representing 6.5 million km2 of the most lake-rich landscape on Earth. Analysis of 308 Canadian lakes resulted in a metagenome-assembled genome (MAG) catalogue of 1,008 mostly novel bacterial genomospecies. Lake trophic state was a leading driver of taxonomic and functional diversity among MAG assemblages, reflecting the responses of communities profiled by 16S rRNA amplicons and gene-centric metagenomics. Coupling the MAG catalogue with watershed geomatics revealed terrestrial influences of soils and land use on assemblages. Agriculture and human population density were drivers of turnover, indicating detectable anthropogenic imprints on lake bacteria at the continental scale. The sensitivity of bacterial assemblages to human impact reinforces lakes as sentinels of environmental change. Overall, the LakePulse MAG catalogue greatly expands the freshwater genomic landscape, advancing an integrative view of diversity across Earth's microbiomes.

Geospatial analysis reveals a hotspot of fecal bacteria in Canadian prairie lakes linked to agricultural non-point sources.

Lakes are sentinels of environmental changes within their watersheds including those induced by a changing climate and anthropogenic activities. In particular, contamination originating from point or non-point sources (NPS) within watersheds might be reflected in changes in the bacterial composition of lake water. We assessed the abundance of potentially pathogenic bacteria (PPB) sampled in 413 lakes within 8 southern Canadian ecozones that represent a wide diversity of lakes and watershed land use. The study objectives were (1) to explore the diversity of PPB; (2) to build a fecal multi-indicator from a cluster of co-occurring PPB; and (3) to predict the fecal multi-indicator over thousands of lakes. We identified bacterial taxa based on 16S rRNA amplicon sequencing and clustered 33 PPB matching taxa in the Canadian ePATHogen database using a Sørensen dissimilarity index on binary data across the sampled lakes. One cluster contained Erysipelothrix, Desulfovibrio, Bacteroides, Vibrio and Acholeplasma and was related to the NPS fraction of agriculture and pasture within the watershed as its main driver and thus it was determined as the fecal multi-indicator. We subsequently developed a fecal multi-indicator predictive model across 200 212 southern Canadian lakes which explained 55.1% of the deviance. Mapping the predictions showed higher fecal multi-indicator abundances in the Prairies and Boreal Plains compared to the other ecozones. These results represent the first attempt to map a potential fecal multi-indicator at the continental scale, which may be further improved in the future. Lastly, the study demonstrates the capacity of a multi-disciplinary approach leveraging both datasets derived from remote sensing and DNA sequencing to provide mapping information for public health governmental policies.

Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a generalist virus, infecting and evolving in numerous mammals, including captive and companion animals, free-ranging wildlife, and humans. Transmission among non-human species poses a risk for the establishment of SARS-CoV-2 reservoirs, makes eradication difficult, and provides the virus with opportunities for new evolutionary trajectories, including the selection of adaptive mutations and the emergence of new variant lineages. Here, we use publicly available viral genome sequences and phylogenetic analysis to systematically investigate the transmission of SARS-CoV-2 between human and non-human species and to identify mutations associated with each species. We found the highest frequency of animal-to-human transmission from mink, compared with lower transmission from other sampled species (cat, dog, and deer). Although inferred transmission events could be limited by sampling biases, our results provide a useful baseline for further studies. Using genome-wide association studies, no single nucleotide variants (SNVs) were significantly associated with cats and dogs, potentially due to small sample sizes. However, we identified three SNVs statistically associated with mink and 26 with deer. Of these SNVs, ~⅔ were plausibly introduced into these animal species from local human populations, while the remaining ~⅓ were more likely derived in animal populations and are thus top candidates for experimental studies of species-specific adaptation. Together, our results highlight the importance of studying animal-associated SARS-CoV-2 mutations to assess their potential impact on human and animal health.