Search

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 β-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.

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.

This case report describes a 68-year-old male with recurrent multidrug-resistant Salmonella enterica serovar Typhimurium bacteremia acquired during travel abroad. He experienced a recurrence of bacteremia without a clear source and was successfully treated with 10 weeks of intravenous ertapenem. Post hoc genome sequencing revealed an isolate bearing class A, C, and D extended-spectrum β-lactamases (ESBLs). A review of English- and French-language literature since 2000 revealed eight publications that discussed recurrent S. enterica serovar Typhimurium bacteremia. Patients with multidrug-resistant S. enterica serovar Typhimurium should be monitored frequently for recrudescence, even in the absence of risk factors.

The growing challenge of microbial resistance emphasizes the importance of new antibiotics or reviving strategies for the use of old ones. Macrolide antibiotics are potent bacterial protein synthesis inhibitors with a formidable capacity to treat life-threatening bacterial infections; however, acquired and intrinsic resistance limits their clinical application. In the work presented here, we reveal that bicarbonate is a potent enhancer of the activity of macrolide antibiotics that overcomes both acquired and intrinsic resistance mechanisms. With a focus on azithromycin, a highly prescribed macrolide antibiotic, and using clinically relevant pathogens, we show that physiological concentrations of bicarbonate overcome drug resistance by increasing the intracellular concentration of azithromycin. We demonstrate the potential of bicarbonate as a formulation additive for topical use of azithromycin in treating a murine wound infection caused by

Outbreaks of virulent and/or drug-resistant bacteria have a significant impact on human health and major economic consequences. Genomic islands (GIs; defined as clusters of genes of probable horizontal origin) are of high interest because they disproportionately encode virulence factors, some antimicrobial-resistance (AMR) genes, and other adaptations of medical or environmental interest. While microbial genome sequencing has become rapid and inexpensive, current computational methods for GI analysis are not amenable for rapid, accurate, user-friendly and scalable comparative analysis of sets of related genomes. To help fill this gap, we have developed IslandCompare, an open-source computational pipeline for GI prediction and comparison across several to hundreds of bacterial genomes. A dynamic and interactive visualization strategy displays a bacterial core-genome phylogeny, with bacterial genomes linearly displayed at the phylogenetic tree leaves. Genomes are overlaid with GI predictions and AMR determinants from the Comprehensive Antibiotic Resistance Database (CARD), and regions of similarity between the genomes are also displayed. GI predictions are performed using Sigi-HMM and IslandPath-DIMOB, the two most precise GI prediction tools based on nucleotide composition biases, as well as a novel blast-based consistency step to improve cross-genome prediction consistency. GIs across genomes sharing sequence similarity are grouped into clusters, further aiding comparative analysis and visualization of acquisition and loss of mobile GIs in specific sub-clades. IslandCompare is an open-source software that is containerized for local use, plus available via a user-friendly, web-based interface to allow direct use by bioinformaticians, biologists and clinicians (at https://islandcompare.ca).

Enterococcus faecium is a ubiquitous opportunistic pathogen that is exhibiting increasing levels of antimicrobial resistance (AMR). Many of the genes that confer resistance and pathogenic functions are localized on mobile genetic elements (MGEs), which facilitate their transfer between lineages. Here, features including resistance determinants, virulence factors and MGEs were profiled in a set of 1273 E. faecium genomes from two disparate geographic locations (in the UK and Canada) from a range of agricultural, clinical and associated habitats. Neither lineages of E. faecium , type A and B, nor MGEs are constrained by geographic proximity, but our results show evidence of a strong association of many profiled genes and MGEs with habitat. Many features were associated with a group of clinical and municipal wastewater genomes that are likely forming a new human-associated ecotype within type A. The evolutionary dynamics of E. faecium make it a highly versatile emerging pathogen, and its ability to acquire, transmit and lose features presents a high risk for the emergence of new pathogenic variants and novel resistance combinations. This study provides a workflow for MGE-centric surveillance of AMR in Enterococcus that can be adapted to other pathogens.

Metformin is the most commonly prescribed medication for type 2 diabetes, owing to its glucose-lowering effects, which are mediated through the suppression of hepatic glucose production (reviewed in refs. 1-3). However, in addition to its effects on the liver, metformin reduces appetite and in preclinical models exerts beneficial effects on ageing and a number of diverse diseases (for example, cognitive disorders, cancer, cardiovascular disease) through mechanisms that are not fully understood1-3. Given the high concentration of metformin in the liver and its many beneficial effects beyond glycemic control, we reasoned that metformin may increase the secretion of a hepatocyte-derived endocrine factor that communicates with the central nervous system4. Here we show, using unbiased transcriptomics of mouse hepatocytes and analysis of proteins in human serum, that metformin induces expression and secretion of growth differentiating factor 15 (GDF15). In primary mouse hepatocytes, metformin stimulates the secretion of GDF15 by increasing the expression of activating transcription factor 4 (ATF4) and C/EBP homologous protein (CHOP; also known as DDIT3). In wild-type mice fed a high-fat diet, oral administration of metformin increases serum GDF15 and reduces food intake, body mass, fasting insulin and glucose intolerance; these effects are eliminated in GDF15 null mice. An increase in serum GDF15 is also associated with weight loss in patients with type 2 diabetes who take metformin. Although further studies will be required to determine the tissue source(s) of GDF15 produced in response to metformin in vivo, our data indicate that the therapeutic benefits of metformin on appetite, body mass and serum insulin depend on GDF15.

Bacteria have evolved sophisticated mechanisms to inhibit the growth of competitors1. One such mechanism involves type VI secretion systems, which bacteria can use to directly inject antibacterial toxins into neighboring cells. Many of these toxins target cell envelope integrity, but the full range of growth inhibitory mechanisms remains to be determined2. Here, we discover a novel type VI secretion effector, Tas1, in the opportunistic pathogen Pseudomonas aeruginosa. A crystal structure of Tas1 reveals similarity to enzymes that synthesize (p)ppGpp, a broadly conserved signaling molecule in bacteria that modulates cell growth rate, particularly in response to nutritional stress3. Strikingly, however, we find that Tas1 does not synthesize (p)ppGpp, and instead pyrophosphorylates adenosine nucleotides to produce (p)ppApp at rates of nearly 180,000 per min. Consequently, delivery of Tas1 into competitor cells drives the rapid accumulation of (p)ppApp, depletion of ATP, and widespread dysregulation of essential metabolic pathways, resulting in target cell death. Collectively, our findings reveal a new mechanism for interbacterial antagonism and demonstrate, for the first time, a physiological role for the metabolite (p)ppApp in bacteria.

Novel gene targets are needed in accurate diagnosis of malaria. Previous studies show that the dynein light chains (dlc) in Plasmodium are uniquely conserved within the species, possibly due to their role as the cargo adptor moiety. This study aimed at the development of PCR assay for the detection of Plasmodium based on the (dlc-Tctex) as a genus and species-specific tool in malaria diagnosis. Multiple primers were designed based on Plasmodium spp dlc(Tctex) genes. The primers were applied on PCR to detect malaria on clinical samples and on laboratory maintained isolates of P. falciparum and P. vivax for human infecting species and P. knowlesi and P. cynomolgi for zoonoses infection involving primates. The amplified PCR fragments were gene cleaned and sequenced. BLASTn e-values output from the raw nucleotide queries supports that the genes are uniquely conserved. Species-specific primers amplified P. falciparum infections with no cross-reactivity to P. vivax, P. knowlesi or P. cynomolgi species. In this assay only 11 out of the 30 microscope positive malaria positive clinical blood samples were positive for PCR detection of P. falciparum infection. Primers designed for Plasmodium genus amplified the target band in all clinical malaria samples but also had another specific band amplification. This preliminary data demonstrate that a species-specific dlc(Tctex) PCR assay can be used for detection of P. falciparum and optimized genus primers can be applied to differentiate mixed malaria infections.

Obesity results from a caloric imbalance between energy intake, absorption and expenditure. In both rodents and humans, diet-induced thermogenesis contributes to energy expenditure and involves the activation of brown adipose tissue (BAT). We hypothesize that environmental toxicants commonly used as food additives or pesticides might reduce BAT thermogenesis through suppression of uncoupling protein 1 (UCP1) and this may contribute to the development of obesity. Using a step-wise screening approach, we discover that the organophosphate insecticide chlorpyrifos suppresses UCP1 and mitochondrial respiration in BAT at concentrations as low as 1 pM. In mice housed at thermoneutrality and fed a high-fat diet, chlorpyrifos impairs BAT mitochondrial function and diet-induced thermogenesis, promoting greater obesity, non-alcoholic fatty liver disease (NAFLD) and insulin resistance. This is associated with reductions in cAMP; activation of p38MAPK and AMPK; protein kinases critical for maintaining UCP1 and mitophagy, respectively in BAT. These data indicate that the commonly used pesticide chlorpyrifos, suppresses diet-induced thermogenesis and the activation of BAT, suggesting its use may contribute to the obesity epidemic., Chlorpyrifos is a widely-used pesticide and a common residue on vegetables and fruits. Here the authors show that at non-neurotoxic doses, chlorpyrifos reduces energy expenditure, by inhibiting diet induced thermogenesis, and promotes obesity and insulin resistance.

The emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and more recently, the independent evolution of multiple SARS-CoV-2 variants has generated renewed interest in virus evolution and cross-species transmission. While all known human coronaviruses (HCoVs) are speculated to have originated in animals, very little is known about their evolutionary history and factors that enable some CoVs to co-exist with humans as low pathogenic and endemic infections (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1), while others, such as SARS-CoV, MERS-CoV and SARS-CoV-2 have evolved to cause severe disease. In this review, we highlight the origins of all known HCoVs and map positively selected for mutations within HCoV proteins to discuss the evolutionary trajectory of SARS-CoV-2. Furthermore, we discuss emerging mutations within SARS-CoV-2 and variants of concern (VOC), along with highlighting the demonstrated or speculated impact of these mutations on virus transmission, pathogenicity, and neutralization by natural or vaccine-mediated immunity.

SummaryBackgroundThe aim of this prospective cohort study was to determine the burden of SARS-CoV-2 in air and on surfaces in rooms of patients hospitalized with COVID-19, and to identify patient characteristics associated with SARS-CoV-2 environmental contamination.MethodsNasopharyngeal swabs, surface, and air samples were collected from the rooms of 78 inpatients with COVID-19 at six acute care hospitals in Toronto from March to May 2020. Samples were tested for SARS-CoV-2 viral RNA and cultured to determine potential infectivity. Whole viral genomes were sequenced from nasopharyngeal and surface samples. Association between patient factors and detection of SARS-CoV-2 RNA in surface samples were investigated using a mixed-effects logistic regression model.FindingsSARS-CoV-2 RNA was detected from surfaces (125/474 samples; 42/78 patients) and air (3/146 samples; 3/45 patients) in COVID-19 patient rooms; 17% (6/36) of surface samples from three patients yielded viable virus. Viral sequences from nasopharyngeal and surface samples clustered by patient.Multivariable analysis indicated hypoxia at admission, a PCR-positive nasopharyngeal swab with a cycle threshold of ≤30 on or after surface sampling date, higher Charlson co-morbidity score, and shorter time from onset of illness to sample date were significantly associated with detection of SARS-CoV-2 RNA in surface samples.InterpretationThe infrequent recovery of infectious SARS-CoV-2 virus from the environment suggests that the risk to healthcare workers from air and near-patient surfaces in acute care hospital wards is likely limited. Surface contamination was greater when patients were earlier in their course of illness and in those with hypoxia, multiple co-morbidities, and higher SARS-CoV-2 RNA concentration in NP swabs. Our results suggest that air and surfaces may pose limited risk a few days after admission to acute care hospitals.

Genome-wide variation in SARS-CoV-2 reveals evolution and transmission dynamics which are critical considerations for disease control and prevention decisions. Here, we review estimates of the genome-wide viral mutation rates, summarize current COVID-19 case load in the province of Ontario, Canada (5 January 2021), and analyze published SARS-CoV-2 genomes from Ontario (collected prior to 24 November 2020) to test for more infectious genetic variants or lineages., Genome-wide variation in SARS-CoV-2 reveals evolution and transmission dynamics which are critical considerations for disease control and prevention decisions. Here, we review estimates of the genome-wide viral mutation rates, summarize current COVID-19 case load in the province of Ontario, Canada (5 January 2021), and analyze published SARS-CoV-2 genomes from Ontario (collected prior to 24 November 2020) to test for more infectious genetic variants or lineages. The reported mutation rate (∼10−6 nucleotide [nt]−1 cycle−1) for SARS-CoV-2 is typical for coronaviruses. Analysis of published SARS-CoV-2 genomes revealed that the G614 spike protein mutation has dominated infections in Ontario and that SARS-CoV-2 lineages present in Ontario have not differed significantly in their rate of spread. These results suggest that the SARS-CoV-2 population circulating in Ontario has not changed significantly to date. However, ongoing genome monitoring is essential for identification of new variants and lineages that may contribute to increased viral transmission.

The cytochrome P450 (CYP) superfamily is a diverse and important enzyme family, playing a central role in chemical defense and in synthesis and metabolism of major biological signaling molecules. The CYPomes of four cnidarian genomes (Hydra vulgaris, Acropora digitifera, Aurelia aurita, Nematostella vectensis) were annotated; phylogenetic analyses determined the evolutionary relationships amongst the sequences and with existing metazoan CYPs. 155 functional CYPs were identified and 90 fragments. Genes were from 24 new CYP families and several new subfamilies; genes were in 9 of the 12 established metazoan CYP clans. All species had large expansions of clan 2 diversity, with H. vulgaris having reduced diversity for both clan 3 and mitochondrial clan. We identified potential candidates for xenobiotic metabolism and steroidogenesis. That each genome contained multiple, novel CYP families may reflect the large evolutionary distance within the cnidarians, unique physiology in the cnidarian classes, and/or different ecology of the individual species.

Diagnosing antimicrobial resistance (AMR) in the clinic is based on empirical evidence and current gold standard laboratory phenotypic methods. Genotypic methods have the potential advantages of being faster and cheaper, and having improved mechanistic resolution over phenotypic methods. We generated and applied rule-based and logistic regression models to predict the AMR phenotype from Escherichia coli and Pseudomonas aeruginosa multidrug-resistant clinical isolate genomes. By inspecting and evaluating these models, we identified previously unknown β-lactamase substrate activities. In total, 22 unknown β-lactamase substrate activities were experimentally validated using targeted gene expression studies. Our results demonstrate that generating and analysing predictive models can help guide researchers to the mechanisms driving resistance and improve annotation of AMR genes and phenotypic prediction, and suggest that we cannot solely rely on curated knowledge to predict resistance phenotypes.

Cancer immunotherapies using monoclonal antibodies to block inhibitory checkpoints are showing durable remissions in many types of cancer patients, although the majority of breast cancer patients acquire little benefit. Human melanoma and lung cancer patient studies suggest that immune checkpoint inhibitors are often potent in patients that already have intratumoral T cell infiltrate; although it remains unknown what types of interventions can result in an intratumoral T cell infiltrate in breast cancer. Using non-T cell-inflamed mammary tumors, we assessed what biological processes and downstream inflammation can overcome the barriers to spontaneous T cell priming. Here we show a specific type of combination therapy, consisting of oncolytic virus and chemotherapy, activates necroptosis and limits tumor growth in autochthonous tumors. Combination therapy activates proinflammatory cytokines; intratumoral influx of myeloid cells and cytotoxic T cell infiltrate in locally treated and distant autochthonous tumors to render them susceptible to immune checkpoint inhibitors., Workenhe et al. show in mice that a combination of oncolytic HSV-1 virus and Mitomycin-C activates an inflammatory response, through necroptosis induction, that renders tumours susceptible to immune checkpoint inhibitors. These findings informs on the potential role of necroptosis in immunotherapy approaches.

Type I interferons (IFNs) are our first line of defence against virus infection. Recent studies have suggested the ability of SARS-CoV-2 proteins to inhibit IFN responses. Emerging data also suggest that timing and extent of IFN production is associated with manifestation of COVID-19 severity. In spite of progress in understanding how SARS-CoV-2 activates antiviral responses, mechanistic studies into wildtype SARS-CoV-2-mediated induction and inhibition of human type I IFN responses are scarce. Here we demonstrate that SARS-CoV-2 infection induces a type I IFN response in vitro and in moderate cases of COVID-19. In vitro stimulation of type I IFN expression and signaling in human airway epithelial cells is associated with activation of canonical transcriptions factors, and SARS-CoV-2 is unable to inhibit exogenous induction of these responses. Furthermore, we show that physiological levels of IFNα detected in patients with moderate COVID-19 is sufficient to suppress SARS-CoV-2 replication in human airway cells., Graphical Abstract

Type VI secretion systems facilitate the delivery of antibacterial effector proteins between neighbouring Gram-negative bacteria. A subset of these effectors harbor N-terminal transmembrane domains (TMDs) implicated in effector translocation across the target cell membrane. However, the abundance and distribution of these TMD-containing effectors has remained unknown. Here we report the discovery of prePAAR, a conserved motif found in over 6,000 putative TMD-containing effectors. Based on their differing sizes and number of TMDs these effectors fall into two distinct classes that are unified by their requirement for a member of the Eag family of T6SS chaperones for export. Co-crystal structures of class I and class II effector TMD-chaperone complexes from Salmonella Typhimurium and Pseudomonas aeruginosa, respectively, reveals that Eag chaperones mimic transmembrane helical packing to stabilize effector TMDs. In addition to participating in the chaperone-TMD interface, we find that prePAAR functions to facilitate proper folding of the downstream PAAR domain, which is required for effector interaction with the T6SS spike. Taken together, our findings define the mechanism of chaperone-assisted secretion of a widespread family of T6SS membrane protein effectors.

Metformin is the most commonly prescribed medication for type 2 diabetes, owing to its glucose-lowering effects, which are mediated through the suppression of hepatic glucose production (reviewed in refs. 1-3). However, in addition to its effects on the liver, metformin reduces appetite and in preclinical models exerts beneficial effects on ageing and a number of diverse diseases (for example, cognitive disorders, cancer, cardiovascular disease) through mechanisms that are not fully understood1-3. Given the high concentration of metformin in the liver and its many beneficial effects beyond glycemic control, we reasoned that metformin may increase the secretion of a hepatocyte-derived endocrine factor that communicates with the central nervous system4. Here we show, using unbiased transcriptomics of mouse hepatocytes and analysis of proteins in human serum, that metformin induces expression and secretion of growth differentiating factor 15 (GDF15). In primary mouse hepatocytes, metformin stimulates the secretion of GDF15 by increasing the expression of activating transcription factor 4 (ATF4) and C/EBP homologous protein (CHOP; also known as DDIT3). In wild-type mice fed a high-fat diet, oral administration of metformin increases serum GDF15 and reduces food intake, body mass, fasting insulin and glucose intolerance; these effects are eliminated in GDF15 null mice. An increase in serum GDF15 is also associated with weight loss in patients with type 2 diabetes who take metformin. Although further studies will be required to determine the tissue source(s) of GDF15 produced in response to metformin in vivo, our data indicate that the therapeutic benefits of metformin on appetite, body mass and serum insulin depend on GDF15.

Genome sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is increasingly important to monitor the transmission and adaptive evolution of the virus. The accessibility of high-throughput methods and polymerase chain reaction (PCR) has facilitated a growing ecosystem of protocols. Two differing protocols are tiling multiplex PCR and bait capture enrichment. Each method has advantages and disadvantages but a direct comparison with different viral RNA concentrations has not been performed to assess the performance of these approaches. Here we compare Liverpool amplification, ARTIC amplification, and bait capture using clinical diagnostics samples. All libraries were sequenced using an Illumina MiniSeq with data analyzed using a standardized bioinformatics workflow (SARS-CoV-2 Illumina GeNome Assembly Line; SIGNAL). One sample showed poor SARS-CoV-2 genome coverage and consensus, reflective of low viral RNA concentration. In contrast, the second sample had a higher viral RNA concentration, which yielded good genome coverage and consensus. ARTIC amplification showed the highest depth of coverage results for both samples, suggesting this protocol is effective for low concentrations. Liverpool amplification provided a more even read coverage of the SARS-CoV-2 genome, but at a lower depth of coverage. Bait capture enrichment of SARS-CoV-2 cDNA provided results on par with amplification. While only two clinical samples were examined in this comparative analysis, both the Liverpool and ARTIC amplification methods showed differing efficacy for high and low concentration samples. In addition, amplification-free bait capture enriched sequencing of cDNA is a viable method for generating a SARS-CoV-2 genome sequence and for identification of amplification artifacts.

Vaccination has transformed public health, most notably including the eradication of smallpox. Despite its profound historical importance, little is known of the origins and diversity of the viruses used in smallpox vaccination. Prior to the twentieth century, the method, source and origin of smallpox vaccinations remained unstandardised and opaque. We reconstruct and analyse viral vaccine genomes associated with smallpox vaccination from historical artefacts. Significantly, we recover viral molecules through non-destructive sampling of historical materials lacking signs of biological residues. We use the authenticated ancient genomes to reveal the evolutionary relationships of smallpox vaccination viruses within the poxviruses as a whole.

SARS-CoV-2 emerged in December 2019 in Wuhan, China and has since infected over 1.5 million people, of which over 107,000 have died. As SARS-CoV-2 spreads across the planet, speculations remain about the range of human cells that can be infected by SARS-CoV-2. In this study, we report the isolation of SARS-CoV-2 from two COVID-19 patients in Toronto, Canada. We determined the genomic sequences of the two isolates and identified single nucleotide changes in representative populations of our virus stocks. More importantly, we tested a wide range of human immune cells for productive infection with SARS-CoV-2. Here we confirm that human primary peripheral blood mononuclear cells (PBMCs) are not permissive to SARS-CoV-2. As SARS-CoV-2 continues to spread globally, it is essential to monitor small nucleotide polymorphisms in the virus and to continue to isolate circulating viruses to determine cell susceptibility and pathogenicity using in vitro and in vivo infection models.