CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.

The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded ß-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts.

Identification of key drivers of antimicrobial resistance in Enterococcus using machine learning.

With antimicrobial resistance (AMR) rapidly evolving in pathogens, quick and accurate identification of genetic determinants of phenotypic resistance is essential for improving surveillance, stewardship, and clinical mitigation. Machine learning (ML) models show promise for AMR prediction in diagnostics but require a deep understanding of internal processes to use effectively. Our study utilised AMR gene, pangenomic, and predicted plasmid features from 647 Enterococcus faecium and Enterococcus faecalis genomes across the One Health continuum, along with corresponding resistance phenotypes, to develop interpretive ML classifiers. Vancomycin resistance could be predicted with 99% accuracy with AMR gene features, 98% with pangenome features, and 96% with plasmid clusters. Top pangenome features overlapped with the resistance genes of the vanA operon, which are often laterally transmitted via plasmids. Doxycycline resistance prediction achieved approximately 92% accuracy with pangenome features, with the top feature being elements of Tn916 conjugative transposon, a tet(M) carrier. Erythromycin resistance prediction models achieved about 90% accuracy, but top features were negatively correlated with resistance due to the confounding effect of population structure. This work demonstrates the importance of reviewing ML models' features to discern biological relevance even when achieving high-performance metrics. Our workflow offers the potential to propose hypotheses for experimental testing, enhancing the understanding of AMR mechanisms, which are crucial for combating the AMR crisis.

Emergent RNA-RNA interactions can promote stability in a facultative phototrophic endosymbiosis.

Eukaryote-eukaryote endosymbiosis was responsible for the spread of chloroplast (plastid) organelles. Stability is required for the metabolic and genetic integration that drives the establishment of new organelles, yet the mechanisms that act to stabilize emergent endosymbioses-between two fundamentally selfish biological organisms-are unclear. Theory suggests that enforcement mechanisms, which punish misbehavior, may act to stabilize such interactions by resolving conflict. However, how such mechanisms can emerge in a facultative endosymbiosis has yet to be explored. Here, we propose that endosymbiont-host RNA-RNA interactions, arising from digestion of the endosymbiont population, can result in a cost to host growth for breakdown of the endosymbiosis. Using the model facultative endosymbiosis between Paramecium bursaria and Chlorella spp., we demonstrate that this mechanism is dependent on the host RNA-interference (RNAi) system. We reveal through small RNA (sRNA) sequencing that endosymbiont-derived messenger RNA (mRNA) released upon endosymbiont digestion can be processed by the host RNAi system into 23-nt sRNA. We predict multiple regions of shared sequence identity between endosymbiont and host mRNA, and demonstrate through delivery of synthetic endosymbiont sRNA that exposure to these regions can knock down expression of complementary host genes, resulting in a cost to host growth. This process of host gene knockdown in response to endosymbiont-derived RNA processing by host RNAi factors, which we term "RNAi collisions," represents a mechanism that can promote stability in a facultative eukaryote-eukaryote endosymbiosis. Specifically, by imposing a cost for breakdown of the endosymbiosis, endosymbiont-host RNA-RNA interactions may drive maintenance of the symbiosis across fluctuating ecological conditions.

Machine Learning for Antimicrobial Resistance Prediction: Current Practice, Limitations, and Clinical Perspective.

Antimicrobial resistance (AMR) is a global health crisis that poses a great threat to modern medicine. Effective prevention strategies are urgently required to slow the emergence and further dissemination of AMR. Given the availability of data sets encompassing hundreds or thousands of pathogen genomes, machine learning (ML) is increasingly being used to predict resistance to different antibiotics in pathogens based on gene content and genome composition. A key objective of this work is to advocate for the incorporation of ML into front-line settings but also highlight the further refinements that are necessary to safely and confidently incorporate these methods. The question of what to predict is not trivial given the existence of different quantitative and qualitative laboratory measures of AMR. ML models typically treat genes as independent predictors, with no consideration of structural and functional linkages; they also may not be accurate when new mutational variants of known AMR genes emerge. Finally, to have the technology trusted by end users in public health settings, ML models need to be transparent and explainable to ensure that the basis for prediction is clear. We strongly advocate that the next set of AMR-ML studies should focus on the refinement of these limitations to be able to bridge the gap to diagnostic implementation.

CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database.

The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD's Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

Environment-dependent fitness gains can be driven by horizontal gene transfer of transporter-encoding genes.

Many microbes acquire metabolites in a "feeding" process where complex polymers are broken down in the environment to their subunits. The subsequent uptake of soluble metabolites by a cell, sometimes called osmotrophy, is facilitated by transporter proteins. As such, the diversification of osmotrophic microorganisms is closely tied to the diversification of transporter functions. Horizontal gene transfer (HGT) has been suggested to produce genetic variation that can lead to adaptation, allowing lineages to acquire traits and expand niche ranges. Transporter genes often encode single-gene phenotypes and tend to have low protein-protein interaction complexity and, as such, are potential candidates for HGT. Here we test the idea that HGT has underpinned the expansion of metabolic potential and substrate utilization via transfer of transporter-encoding genes. Using phylogenomics, we identify seven cases of transporter-gene HGT between fungal phyla, and investigate compatibility, localization, function, and fitness consequences when these genes are expressed in Saccharomyces cerevisiae Using this approach, we demonstrate that the transporters identified can alter how fungi utilize a range of metabolites, including peptides, polyols, and sugars. We then show, for one model gene, that transporter gene acquisition by HGT can significantly alter the fitness landscape of S. cerevisiae We therefore provide evidence that transporter HGT occurs between fungi, alters how fungi can acquire metabolites, and can drive gain in fitness. We propose a "transporter-gene acquisition ratchet," where transporter repertoires are continually augmented by duplication, HGT, and differential loss, collectively acting to overwrite, fine-tune, and diversify the complement of transporters present in a genome.

PSORTm: a bacterial and archaeal protein subcellular localization prediction tool for metagenomics data.

MOTIVATION: Many methods for microbial protein subcellular localization (SCL) prediction exist; however, none is readily available for analysis of metagenomic sequence data, despite growing interest from researchers studying microbial communities in humans, agri-food relevant organisms and in other environments (e.g. for identification of cell-surface biomarkers for rapid protein-based diagnostic tests). We wished to also identify new markers of water quality from freshwater samples collected from pristine versus pollution-impacted watersheds. RESULTS: We report PSORTm, the first bioinformatics tool designed for prediction of diverse bacterial and archaeal protein SCL from metagenomics data. PSORTm incorporates components of PSORTb, one of the most precise and widely used protein SCL predictors, with an automated classification by cell envelope. An evaluation using 5-fold cross-validation with in silico-fragmented sequences with known localization showed that PSORTm maintains PSORTb's high precision, while sensitivity increases proportionately with metagenomic sequence fragment length. PSORTm's read-based analysis was similar to PSORTb-based analysis of metagenome-assembled genomes (MAGs); however, the latter requires non-trivial manual classification of each MAG by cell envelope, and cannot make use of unassembled sequences. Analysis of the watershed samples revealed the importance of normalization and identified potential biomarkers of water quality. This method should be useful for examining a wide range of microbial communities, including human microbiomes, and other microbiomes of medical, environmental or industrial importance. AVAILABILITY AND IMPLEMENTATION: Documentation, source code and docker containers are available for running PSORTm locally at https://www.psort.org/psortm/ (freely available, open-source software under GNU General Public License Version 3). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Black Pill: New Technology and the Male Supremacy of Involuntarily Celibate Men.

Involuntary celibates, or "incels," are people who identify themselves by their inability to establish sexual partnerships. In this article, we use analytic abduction to qualitatively analyze 9,062 comments on a popular incel forum for heterosexual men that is characterized by extensive misogyny. Incels argue that emerging technologies reveal and compound the gender practices that produce involuntarily celibate men. First, incels argue that women's use of dating apps accelerates hypergamy. Second, incels suggest that highly desirable men use dating apps to partner with multiple women. Third, incels assert that subordinate men inflate women's egos and their "sexual marketplace value" through social media platforms. We argue that incels' focus on technology reinforces essentialist views on gender, buttresses male domination, dehumanizes women, and minimizes incels' own misogyny. We discuss findings in relation to theories of masculinity and social scientific research on the impacts of emerging technology.

Cryptic infection of a broad taxonomic and geographic diversity of tadpoles by Perkinsea protists.

The decline of amphibian populations, particularly frogs, is often cited as an example in support of the claim that Earth is undergoing its sixth mass extinction event. Amphibians seem to be particularly sensitive to emerging diseases (e.g., fungal and viral pathogens), yet the diversity and geographic distribution of infectious agents are only starting to be investigated. Recent work has linked a previously undescribed protist with mass-mortality events in the United States, in which infected frog tadpoles have an abnormally enlarged yellowish liver filled with protist cells of a presumed parasite. Phylogenetic analyses revealed that this infectious agent was affiliated with the Perkinsea: a parasitic group within the alveolates exemplified by Perkinsus sp., a "marine" protist responsible for mass-mortality events in commercial shellfish populations. Using small subunit (SSU) ribosomal DNA (rDNA) sequencing, we developed a targeted PCR protocol for preferentially sampling a clade of the Perkinsea. We tested this protocol on freshwater environmental DNA, revealing a wide diversity of Perkinsea lineages in these environments. Then, we used the same protocol to test for Perkinsea-like lineages in livers of 182 tadpoles from multiple families of frogs. We identified a distinct Perkinsea clade, encompassing a low level of SSU rDNA variation different from the lineage previously associated with tadpole mass-mortality events. Members of this clade were present in 38 tadpoles sampled from 14 distinct genera/phylogroups, from five countries across three continents. These data provide, to our knowledge, the first evidence that Perkinsea-like protists infect tadpoles across a wide taxonomic range of frogs in tropical and temperate environments, including oceanic islands.

Molecular diversity and distribution of marine fungi across 130 European environmental samples.

Environmental DNA and culture-based analyses have suggested that fungi are present in low diversity and in low abundance in many marine environments, especially in the upper water column. Here, we use a dual approach involving high-throughput diversity tag sequencing from both DNA and RNA templates and fluorescent cell counts to evaluate the diversity and relative abundance of fungi across marine samples taken from six European near-shore sites. We removed very rare fungal operational taxonomic units (OTUs) selecting only OTUs recovered from multiple samples for a detailed analysis. This approach identified a set of 71 fungal 'OTU clusters' that account for 66% of all the sequences assigned to the Fungi. Phylogenetic analyses demonstrated that this diversity includes a significant number of chytrid-like lineages that had not been previously described, indicating that the marine environment encompasses a number of zoosporic fungi that are new to taxonomic inventories. Using the sequence datasets, we identified cases where fungal OTUs were sampled across multiple geographical sites and between different sampling depths. This was especially clear in one relatively abundant and diverse phylogroup tentatively named Novel Chytrid-Like-Clade 1 (NCLC1). For comparison, a subset of the water column samples was also investigated using fluorescent microscopy to examine the abundance of eukaryotes with chitin cell walls. Comparisons of relative abundance of RNA-derived fungal tag sequences and chitin cell-wall counts demonstrate that fungi constitute a low fraction of the eukaryotic community in these water column samples. Taken together, these results demonstrate the phylogenetic position and environmental distribution of 71 lineages, improving our understanding of the diversity and abundance of fungi in marine environments.

Diverse molecular signatures for ribosomally 'active' Perkinsea in marine sediments.

BACKGROUND: Perkinsea are a parasitic lineage within the eukaryotic superphylum Alveolata. Recent studies making use of environmental small sub-unit ribosomal RNA gene (SSU rDNA) sequencing methodologies have detected a significant diversity and abundance of Perkinsea-like phylotypes in freshwater environments. In contrast only a few Perkinsea environmental sequences have been retrieved from marine samples and only two groups of Perkinsea have been cultured and morphologically described and these are parasites of marine molluscs or marine protists. These two marine groups form separate and distantly related phylogenetic clusters, composed of closely related lineages on SSU rDNA trees. Here, we test the hypothesis that Perkinsea are a hitherto under-sampled group in marine environments. Using 454 diversity 'tag' sequencing we investigate the diversity and distribution of these protists in marine sediments and water column samples taken from the Deep Chlorophyll Maximum (DCM) and sub-surface using both DNA and RNA as the source template and sampling four European offshore locations. RESULTS: We detected the presence of 265 sequences branching with known Perkinsea, the majority of them recovered from marine sediments. Moreover, 27% of these sequences were sampled from RNA derived cDNA libraries. Phylogenetic analyses classify a large proportion of these sequences into 38 cluster groups (including 30 novel marine cluster groups), which share less than 97% sequence similarity suggesting this diversity encompasses a range of biologically and ecologically distinct organisms. CONCLUSIONS: These results demonstrate that the Perkinsea lineage is considerably more diverse than previously detected in marine environments. This wide diversity of Perkinsea-like protists is largely retrieved in marine sediment with a significant proportion detected in RNA derived libraries suggesting this diversity represents ribosomally 'active' and intact cells. Given the phylogenetic range of hosts infected by known Perkinsea parasites, these data suggest that Perkinsea either play a significant but hitherto unrecognized role as parasites in marine sediments and/or members of this group are present in the marine sediment possibly as part of the 'seed bank' microbial community.

Stochastic Gender-Based Violence: How Incels Justify and Encourage Sexualized Violence Against Women.

This study examines how involuntarily celibate ("incels") men justify gender-based and sexualized violence against women. Based on an analysis of 22,060 discussion board comments, we argue that: (1) incel justifications of sexualized violence are tied to their perception of gender relations, (2) incels justify sexual assault as a form of revenge for their incel status, and (3) incels misuse science to argue that women enjoy sexual assault. Adapting the concept of "stochastic terrorism," we argue that incels and similar communities produce stochastic gender-based violence, wherein communities justify and encourage acts of violence. Findings are discussed in relation to gender-based violence, rape culture, masculinities theory, and policy.

A solider and a victim: Masculinity, violence, and incels celebration of December 6th.

In 1989, Marc Lépine murdered 14 women at L'École Polytechnique de Montréal. We demonstrate how involuntarily celibate ("incel") men celebrate Lépine and claim him as a member of their community. Our analysis draws on 637 comments made on incels.is, the main English-language incel forum, that explicitly mentions Marc Lépine. We argue that incels use Lépine to situate themselves in relation to masculinity and to justify violence against women. First, incels orient to both hegemonic and subordinate masculinity by arguing that feminists are waging a gender war against men. Second, incels celebrate Lépine as a methodical and efficient murderer, connecting both themselves and Lépine to hegemonic masculinity. Third, incels describe both themselves and Lépine as victims of feminists and use this perceived subordination to justify violence against women. We discuss findings in relation to theories of masculinity and policies regulating online communities.

En 1989, Marc Lépine a assassiné 14 femmes à l'École Polytechnique de Montréal. Nous montrons comment des hommes involontairement célibataires (« incel ¼) cèlébrent Lépine et le revendiquent comme membre de leur communauté. Notre analyse s'appuie sur 637 commentaires formulés sur incels.is, le principal forum incel anglophone, qui mentionnent explicitement Marc Lépine. Nous soutenons que les incels utilisent Lépine pour se situer par rapport à la masculinité et justifier les violences faites aux femmes. Premiérement, les incels s'orientent vers une masculinité à la fois hégémonique et subordonnée en soutenant que les féministes mènent une guerre de genre contre les hommes. Deuxièmement, les incels célèbrent Lépine comme un meurtrier méthodique et efficace, les liant eux-mêmes et Lépine à la masculinité hégémonique. Troisièmement, les incels se décrivent eux-mêmes et Lépine comme des victimes des féministes et utilisent cette subordination perςue pour justifier la violence contre les femmes. Nous discutons des résultats relatifs aux théories de la masculinité et aux politiques régissant les communautés en ligne.

PHA4GE quality control contextual data tags: standardized annotations for sharing public health sequence datasets with known quality issues to facilitate testing and training.

As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability, and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies - community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The tags can also be applied to synthetic (lab created) data. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA's GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.

Prevalence and Risk Factors for Urinary Incontinence in Nulliparous Women: A Contemporary, Population-Based Cohort Study.

IMPORTANCE AND OBJECTIVES: Epidemiologic studies of incontinence largely focus on parous women, and there are limited data regarding nulliparous women. Our objectives were to evaluate risk factors for urinary incontinence among a nationally representative, contemporary sample of nulliparous women of all ages in the United States and to describe the prevalence and subtypes of urinary incontinence and nocturia in this population. STUDY DESIGN: This cross-sectional, population-based study used the National Health and Nutrition Examination Survey cycles 2011-2018 to assemble a sample of nulliparous women 20-80 years old. Crude and adjusted odds ratios were estimated using multivariable logistic regression for the exposures of interest: body mass index (BMI), age, physical activity, prior hysterectomy, and current smoking. Prevalence of urinary incontinence and nocturia were estimated. RESULTS: Among 1,603 nulliparous women, prevalence of any urinary incontinence was 29.38%. Prevalence of stress, urgency, and mixed urinary incontinence and nocturia, respectively, were 27.68%, 19.64%, 10.57%, and 58.95%. Women with a BMI ≥25 (calculated as weight in kilograms divided by height in meters squared; adjusted odds ratio [aOR], 1.57; 95% confidence interval [CI], 1.11-2.23), at least 45 years (aOR, 3.75; 95% CI, 2.31-5.83), and current smoking (aOR, 1.63; 95% CI, 1.07-2.49) had increased the odds of incontinence compared with women without these risk factors. When stress urinary incontinence (SUI) was considered alone, only women with a BMI ≥25 (aOR, 1.66; 95% CI, 1.20-2.31) and age at least 45 years (aOR, 3.17; 95% CI, 2.01-5.00) had increased odds of SUI compared with women without these risk factors. CONCLUSIONS: Urinary incontinence and nocturia are prevalent in nulliparous women, and age, elevated BMI, and current smoking may represent risk factors for incontinence in this population.

Lachnoanaerobaculum orale bacteremia in a patient with acute myeloid leukemia and stomatitis: An emerging pathogen.

Background: Lachnoanaerobaculum orale is a newly described, obligately anaerobic gram-positive bacillus. The first report of invasive disease caused by L. orale was described in a patient with acute lymphocytic leukemia following systematic chemotherapy. Here we describe another case of L. orale bacteremia in a patient with a hematologic malignancy following chemotherapy-induced neutropenia. Methods: We present a case of a 46-year-old woman with a recent diagnosis of AML who presented to Sunnybrook Health Sciences Center with febrile neutropenia following induction chemotherapy with daunorubicin-cytarabine (3 +7 regimen) with Gemtuzumab and Ozogamycin. Despite being on intravenous pipercillin-tazobactam she remained febrile. Following our clinical assessment and investigations, potential sources of infection included a swollen digit and severe mucositis. Results: One blood culture from admission grew Lachnoanaerobaculum orale in the anaerobic bottle, identified by Matrix-Assisted Laser Desorption Ionization-Time of Flight (MALDI-TOF). The isolate also underwent whole-genome sequencing using methods that have been described previously. Results demonstrated the organism was susceptible to cefoxitin, clindamycin, meropenem, metronidazole, penicillin, and piperacillin-tazobactam. We concluded that the source of this patient's bloodstream infection to be chemotherapy-induced stomatitis. Conclusion: With the increasing use of intensive immunosuppressive regimens and hematopoietic stem cell transplantation for patients with hematologic malignancies, there has been an increase in the incidence and detection of bloodstream infections due to anaerobic organisms. This is only the second case report of L. orale bacteremia, highlighting its emerging role as an opportunistic pathogen in immunocompromised patients.

Use of whole genome sequencing to identify low-frequency mutations in SARS-CoV-2 patients treated with remdesivir.

BACKGROUND: Remdesivir (RDV) has been shown to reduce hospitalization and mortality in COVID-19 patients. Resistance mutations caused by RDV are rare and have been predominantly reported in patients who are on prolonged therapy and immunocompromised. We investigate the effects of RDV treatment on intra-host SARS-CoV-2 diversity and low-frequency mutations in moderately ill hospitalized COVID-19 patients and compare them to patients without RDV treatment. METHODS: From March 2020 to April 2022, sequential collections of nasopharyngeal and mid-turbinate swabs were obtained from 14 patients with and 30 patients without RDV treatment. Demographic and clinical data on all patients were reviewed. A total of 109 samples were sequenced and mutation analyses were performed. RESULTS: Previously reported drug resistant mutations in nsp12 were not identified during short courses of RDV therapy. In genes encoding and surrounding the replication complex (nsp6-nsp14), low-frequency minority variants were detected in 7/14 (50%) and 18/30 (60%) patients with and without RDV treatment, respectively. We did not detect significant differences in within-host diversity and positive selection between the RDV-treated and untreated groups. CONCLUSIONS: Minimal intra-host variability and stochastic low-frequency variants detected in moderately ill patients suggests little selective pressure in patients receiving short courses of RDV. The barrier to RDV resistance is high in patients with moderate disease. Patients undergoing short regimens of RDV therapy should continue to be monitored.

Prevalence of Low-Frequency, Antiviral Resistance Variants in SARS-CoV-2 Isolates in Ontario, Canada, 2020-2023.

Importance: Nirmatrelvir-ritonavir is an oral antiviral medication that improves outcomes in SARS-CoV-2 infections. However, there is concern that antiviral resistance will develop and that these viruses could be selected for after treatment. Objective: To determine the prevalence of low-frequency SARS-CoV-2 variants in patient samples that could be selected for by nirmatrelvir-ritonavir. Design, Setting, and Participants: This retrospective cohort study was conducted at 4 laboratories that serve community hospitals, academic tertiary care centers, and COVID-19 assessment centers in Ontario, Canada. Participants included symptomatic or asymptomatic patients who tested positive for SARS-CoV-2 virus and submitted virus samples for diagnostic testing between March 2020 and January 2023. Exposure: SARS-CoV-2 infection. Main Outcomes and Measures: Samples with sufficient viral load underwent next-generation genome sequencing to identify low-frequency antiviral resistance variants that could not be identified through conventional sequencing. Results: This study included 78 866 clinical samples with next-generation whole-genome sequencing data for SARS-CoV-2. Low-frequency variants in the viral nsp5 gene were identified in 128 isolates (0.16%), and no single variant associated with antiviral resistance was predominate. Conclusions and Relevance: This cohort study of low-frequency variants resistant to nirmatrelvir-ritonavir found that these variants were very rare in samples from patients with SARS-CoV-2, suggesting that selection of these variants by nirmatrelvir-ritonavir following the initiation of treatment may also be rare. Surveillance efforts that involve sequencing of viral isolates should continue to monitor for novel resistance variants as nirmatrelvir-ritonavir is used more broadly.

Genomic and transcriptomic characterization of delta SARS-CoV-2 infection in free-ranging white-tailed deer (Odocoileus virginianus).

White-tailed deer (WTD) are susceptible to SARS-CoV-2 and represent an important species for surveillance. Samples from WTD (n = 258) collected in November 2021 from Québec, Canada were analyzed for SARS-CoV-2 RNA. We employed viral genomics and host transcriptomics to further characterize infection and investigate host response. We detected Delta SARS-CoV-2 (B.1.617.2) in WTD from the Estrie region; sequences clustered with human sequences from October 2021 from Vermont, USA, which borders this region. Mutations in the S-gene and a deletion in ORF8 were detected. Host expression patterns in SARS-CoV-2 infected WTD were associated with the innate immune response, including signaling pathways related to anti-viral, pro- and anti-inflammatory signaling, and host damage. We found limited correlation between genes associated with innate immune response from human and WTD nasal samples, suggesting differences in responses to SARS-CoV-2 infection. Our findings provide preliminary insights into host response to SARS-CoV-2 infection in naturally infected WTD.