Substitution of dietary monounsaturated fatty acids from olive oil for saturated fatty acids from lard increases low-density lipoprotein apolipoprotein B-100 fractional catabolic rate in subjects with dyslipidemia associated with insulin resistance: a randomized controlled trial.

BACKGROUND: The substitution of monounsaturated acids (MUFAs) for saturated fatty acids (SFAs) is recommended for cardiovascular disease prevention but its impact on lipoprotein metabolism in subjects with dyslipidemia associated with insulin resistance (IR) remains largely unknown. OBJECTIVES: This study aimed to evaluate the impact of substituting MUFAs for SFAs on the in vivo kinetics of apolipoprotein (apo)B-containing lipoproteins and on the plasma lipidomic profile in adults with IR-induced dyslipidemia. METHODS: Males and females with dyslipidemia associated with IR (n = 18) were recruited for this crossover double-blind randomized controlled trial. Subjects consumed, in random order, a diet rich in SFAs (SFAs: 13.4%E; MUFAs: 14.4%E) and a diet rich in MUFAs (SFAs: 7.1%E; MUFAs: 20.7%E) in fully controlled feeding conditions for periods of 4 wk each, separated by a 4-wk washout. At the end of each diet, fasting plasma samples were taken together with measurements of the in vivo kinetics of apoB-containing lipoproteins. RESULTS: Substituting MUFAs for SFAs had no impact on triglyceride-rich lipoprotein apoB-48 fractional catabolic rate (FCR) (Δ = -8.9%, P = 0.4) and production rate (Δ = 0.0%, P = 0.9), although it decreased very low-density lipoprotein apoB-100 pool size (PS) (Δ = -22.5%; P = 0.01). This substitution also reduced low-density lipoprotein cholesterol (LDL-C) (Δ = -7.0%; P = 0.01), non-high-density lipoprotein cholesterol (Δ = -2.5%; P = 0.04), and LDL apoB-100 PS (Δ = -6.0%; P = 0.05). These differences were partially attributed to an increase in LDL apoB-100 FCR (Δ = +1.6%; P = 0.05). The MUFA diet showed reduced sphingolipid concentrations and elevated glycerophospholipid levels compared with the SFA diet. CONCLUSIONS: This study demonstrated that substituting dietary MUFAs for SFAs decreases LDL-C levels and LDL PS by increasing LDL apoB-100 FCR and results in an overall improved plasma lipidomic profile in individuals with IR-induced lipidemia. TRIAL REGISTRATION: This trial was registered as clinicaltrials.gov as NCT03872349.

Learning self-supervised molecular representations for drug-drug interaction prediction.

Drug-drug interactions (DDI) are a critical concern in healthcare due to their potential to cause adverse effects and compromise patient safety. Supervised machine learning models for DDI prediction need to be optimized to learn abstract, transferable features, and generalize to larger chemical spaces, primarily due to the scarcity of high-quality labeled DDI data. Inspired by recent advances in computer vision, we present SMR-DDI, a self-supervised framework that leverages contrastive learning to embed drugs into a scaffold-based feature space. Molecular scaffolds represent the core structural motifs that drive pharmacological activities, making them valuable for learning informative representations. Specifically, we pre-trained SMR-DDI on a large-scale unlabeled molecular dataset. We generated augmented views for each molecule via SMILES enumeration and optimized the embedding process through contrastive loss minimization between views. This enables the model to capture relevant and robust molecular features while reducing noise. We then transfer the learned representations for the downstream prediction of DDI. Experiments show that the new feature space has comparable expressivity to state-of-the-art molecular representations and achieved competitive DDI prediction results while training on less data. Additional investigations also revealed that pre-training on more extensive and diverse unlabeled molecular datasets improved the model's capability to embed molecules more effectively. Our results highlight contrastive learning as a promising approach for DDI prediction that can identify potentially hazardous drug combinations using only structural information.

Timing and Predictors of Loss of Infectivity Among Healthcare Workers With Mild Primary and Recurrent COVID-19: A Prospective Observational Cohort Study.

BACKGROUND: There is a need to understand the duration of infectivity of primary and recurrent coronavirus disease 2019 (COVID-19) and identify predictors of loss of infectivity. METHODS: Prospective observational cohort study with serial viral culture, rapid antigen detection test (RADT) and reverse transcription polymerase chain reaction (RT-PCR) on nasopharyngeal specimens of healthcare workers with COVID-19. The primary outcome was viral culture positivity as indicative of infectivity. Predictors of loss of infectivity were determined using multivariate regression model. The performance of the US Centers for Disease Control and Prevention (CDC) criteria (fever resolution, symptom improvement, and negative RADT) to predict loss of infectivity was also investigated. RESULTS: In total, 121 participants (91 female [79.3%]; average age, 40 years) were enrolled. Most (n = 107, 88.4%) had received ≥3 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine doses, and 20 (16.5%) had COVID-19 previously. Viral culture positivity decreased from 71.9% (87/121) on day 5 of infection to 18.2% (22/121) on day 10. Participants with recurrent COVID-19 had a lower likelihood of infectivity than those with primary COVID-19 at each follow-up (day 5 odds ratio [OR], 0.14; P < .001]; day 7 OR, 0.04; P = .003]) and were all non-infective by day 10 (P = .02). Independent predictors of infectivity included prior COVID-19 (adjusted OR [aOR] on day 5, 0.005; P = .003), an RT-PCR cycle threshold [Ct] value <23 (aOR on day 5, 22.75; P < .001) but not symptom improvement or RADT result.The CDC criteria would identify 36% (24/67) of all non-infectious individuals on day 7. However, 17% (5/29) of those meeting all the criteria had a positive viral culture. CONCLUSIONS: Infectivity of recurrent COVID-19 is shorter than primary infections. Loss of infectivity algorithms could be optimized.

Phylogenomic insights into evolutionary trajectories of multidrug resistant S. pneumoniae CC271 over a period of 14 years in China.

BACKGROUND: Streptococcus pneumoniae is a gram-positive opportunistic pathogen, and infection risks of S. pneumoniae can be profoundly augmented by its acquired multidrug-resistance (MDR). The rapid development of MDR in S. pneumoniae was attributed to the international dissemination of a small number of multidrug-resistant "clones." Clonal complex (CC) 271 is a prevalent MDR CC in the world and the most prevalent CC in China. However, the evolutionary trajectories of multidrug-resistant S. pneumoniae CC271 in China still are largely unknown. METHODS: We investigated a collection of 1312 S. pneumoniae isolates collected from 28 tertiary hospitals in China from 2007 to 2020. Recombination prediction and recombination-masked phylogenetic analysis were combined to determine the population structure and mode of evolution of CC271. Data from the Global Pneumococcal Sequencing program (GPS) were combined to understand the global distribution of clones identified in this study. Bayesian analysis were recruited to analysis the evolutionary dynamics of dominant clones within CC271 in China. RESULTS: The phylogenomic analysis resulted in the discovery of two globally distributed clones, ST271-A and ST271-B. ST271-A was a derivative of ST236 and an ancestor of ST271-B and ST320, refining the internal phylogenetic relationship of CC271. ST271-B was the most dominant clone in China, with higher ß-lactam resistance especially for cephalosporins comparing to other MDR clones. Bayesian skyline plot showed a rapid expansion of 19F ST271-B from 1995 to 2000, which correlates with the widespread use of cephalosporins in the 1990s in China. 19A ST320, a vaccine-escape clone, is the second largest population in China. The Bayesian skyline plot showed that the 19A ST320 began to expand rapidly around 2001, which appeared to coincide with the prevalence of 19A after application of PCV7 in 2000 in the USA. We also observed frequent transmission of 19A ST320 between countries. It suggests that mass vaccination in some countries could affect the prevalence of clones in unvaccinated countries in the context of high-frequency international transmission. CONCLUSIONS: Our results refined the internal phylogenetic relationship of CC271, showing that the 19F ST271-B and 19A ST320 evolved independently from ST271-A, with different histories and driving forces for their evolution and dissemination in China.

Characterization of vancomycin-resistance vanD gene clusters in the human intestinal microbiota by metagenomics and culture-enriched metagenomics.

Objectives: To characterize vancomycin-resistance vanD gene clusters and potential vanD-carrying bacteria in the intestinal microbiota of healthy volunteers exposed or not to ß-lactam antibiotics. Methods: Stool samples were collected before and after 7 days of cefprozil ß-lactam antibiotic exposure of 18 participants and six control participants who were not exposed to the antibiotic at the same time points. Metagenomic sequencing and culture-enriched metagenomic sequencing (with and without ß-lactam selection) were used to characterize vanD gene clusters and determine potential vanD-carrying bacteria. Alteration by antimicrobials was also examined. Results: Culture enrichment allowed detection of vanD genes in a large number of participants (11/24; 46%) compared to direct metagenomics (2/24; 8%). vanD genes were detected in stool cultures only following ß-lactam exposure, either after ß-lactam treatment of participants or after culture of stools with ß-lactam selection. Six types of vanD gene clusters were identified. Two types of vanD cluster highly similar to those of enterococci were found in two participants. Other vanD genes or vanD clusters were nearly identical to those identified in commensal anaerobic bacteria of the families Lachnospiraceae and Oscillospiraceae and/or bordered by genomic sequences similar or related to these anaerobes, suggesting that they are the origin or carriers of vanD. Conclusions: This study showed that culture-enriched metagenomics allowed detection of vanD genes not detected by direct metagenomics and revealed collateral enrichment of bacteria containing vancomycin-resistance vanD genes following exposure to ß-lactams, with a higher prevalence of the most likely gut commensal anaerobes carrying vanD. These commensal anaerobes could be the reservoir of vanD genes carried by enterococci.

Gut metagenome profile of the Nunavik Inuit youth is distinct from industrial and non-industrial counterparts.

Comparative metagenomics studies have highlighted differences in microbiome community structure among human populations over diverse lifestyles and environments. With their unique environmental and historical backgrounds, Nunavik Inuit have a distinctive gut microbiome with undocumented health-related implications. Using shotgun metagenomics, we explored the taxonomic and functional structure of the gut microbiome from 275 Nunavik Inuit ranging from 16 to 30-year-old. Whole-metagenome analyses revealed that Nunavik Inuit youths have a more diverse microbiome than their non-industrialized and industrialized counterparts. A comparison of k-mer content illustrated the uniqueness of the Nunavik gut microbiome. Short-chain fatty acids producing species, and carbohydrates degradation pathways dominated Inuit metagenomes. We identified a taxonomic and functional signature unique to the Nunavik gut microbiome contrasting with other populations using a random forest classifier. Here, we show that the Nunavik Inuit gut microbiome exhibits high diversity and a distinct community structure.

Symptomatology during previous SARS-CoV-2 infection and serostatus before vaccination influence the immunogenicity of BNT162b2 COVID-19 mRNA vaccine.

Public health vaccination recommendations for COVID-19 primary series and boosters in previously infected individuals differ worldwide. As infection with SARS-CoV-2 is often asymptomatic, it remains to be determined if vaccine immunogenicity is comparable in all previously infected subjects. This study presents detailed immunological evidence to clarify the requirements for one- or two-dose primary vaccination series for naturally primed individuals. The main objective was to evaluate the immune response to COVID-19 mRNA vaccination to establish the most appropriate vaccination regimen to induce robust immune responses in individuals with prior SARS-CoV-2 infection. The main outcome measure was a functional immunity score (zero to three) before and after vaccination, based on anti-RBD IgG levels, serum capacity to neutralize live virus and IFN-γ secretion capacity in response to SARS-CoV-2 peptide pools. One point was attributed for each of these three functional assays with response above the positivity threshold. The immunity score was compared based on subjects' symptoms at diagnosis and/or serostatus prior to vaccination. None of the naïve participants (n=14) showed a maximal immunity score of three following one dose of vaccine compared to 84% of the previously infected participants (n=55). All recovered individuals who did not have an immunity score of three were seronegative prior to vaccination, and 67% had not reported symptoms resulting from their initial infection. Following one dose of vaccine, their immune responses were comparable to naïve individuals, with significantly weaker responses than individuals who were symptomatic during infection. These results indicate that the absence of symptoms during initial infection and negative serostatus prior to vaccination predict the strength of immune responses to COVID-19 mRNA vaccine. Altogether, these findings highlight the importance of administering the complete two-dose primary regimen and following boosters of mRNA vaccines to individuals who experienced asymptomatic SARS-CoV-2 infection.

Antimicrobial Resistance in the Environment: Towards Elucidating the Roles of Bioaerosols in Transmission and Detection of Antibacterial Resistance Genes.

Antimicrobial resistance (AMR) is continuing to grow across the world. Though often thought of as a mostly public health issue, AMR is also a major agricultural and environmental problem. As such, many researchers refer to it as the preeminent One Health issue. Aerial transport of antimicrobial-resistant bacteria via bioaerosols is still poorly understood. Recent work has highlighted the presence of antibiotic resistance genes in bioaerosols. Emissions of AMR bacteria and genes have been detected from various sources, including wastewater treatment plants, hospitals, and agricultural practices; however, their impacts on the broader environment are poorly understood. Contextualizing the roles of bioaerosols in the dissemination of AMR necessitates a multidisciplinary approach. Environmental factors, industrial and medical practices, as well as ecological principles influence the aerial dissemination of resistant bacteria. This article introduces an ongoing project assessing the presence and fate of AMR in bioaerosols across Canada. Its various sub-studies include the assessment of the emissions of antibiotic resistance genes from many agricultural practices, their long-distance transport, new integrative methods of assessment, and the creation of dissemination models over short and long distances. Results from sub-studies are beginning to be published. Consequently, this paper explains the background behind the development of the various sub-studies and highlight their shared aspects.

Large-scale analysis of circulating glutamate and adipose gene expression in relation to abdominal obesity.

Circulating levels of the amino acid glutamate are associated with central fat accumulation, yet the pathophysiology of this relationship remains unknown. We aimed to (i) refine and validate the association between circulating glutamate and abdominal obesity in a large twin cohort, and (ii) investigate whether transcriptomic profiles in adipose tissue could provide insight into the biological mechanisms underlying the association. First, in a cohort of 4665 individuals from the TwinsUK resource, we identified individuals with abdominal obesity and compared prevalence of the latter across circulating glutamate quintiles. Second, we used transcriptomic signatures generated from adipose tissue, both subcutaneous and visceral, to investigate associations with circulating glutamate levels. Individuals in the top circulating glutamate quintile had a sevenfold higher prevalence of abdominal obesity compared to those in the bottom quintile. The adipose tissue transcriptomic analyses identified GLUL, encoding Glutamate-Ammonia Ligase, as being associated with circulating glutamate and abdominal obesity, with pronounced signatures in the visceral depot. In conclusion, circulating glutamate is positively associated with the prevalence of abdominal obesity which relates to dysregulated GLUL expression specifically in visceral adipose tissue.

Flexible protein database based on amino acid k-mers.

Identification of proteins is one of the most computationally intensive steps in genomics studies. It usually relies on aligners that do not accommodate rich information on proteins and require additional pipelining steps for protein identification. We introduce kAAmer, a protein database engine based on amino-acid k-mers that provides efficient identification of proteins while supporting the incorporation of flexible annotations on these proteins. Moreover, the database is built to be used as a microservice, to be hosted and queried remotely.

The REinfection in COVID-19 Estimation of Risk (RECOVER) study: Reinfection and serology dynamics in a cohort of Canadian healthcare workers.

BACKGROUND: Understanding the immune response to natural infection by SARS-CoV-2 is key to pandemic management, especially in the current context of emerging variants. Uncertainty remains regarding the efficacy and duration of natural immunity against reinfection. METHODS: We conducted an observational prospective cohort study in Canadian healthcare workers (HCWs) with a history of PCR-confirmed SARS-CoV-2 infection to (i) measure the average incidence rate of reinfection and (ii) describe the serological immune response to the primary infection. RESULTS: Our cohort comprised 569 HCWs; median duration of individual follow-up was 371 days. We detected six cases of reinfection in absence of vaccination between August 21, 2020, and March 1, 2022, for a reinfection incidence rate of 4.0 per 100 person-years. Median duration of seropositivity was 415 days in symptomatics at primary infection compared with 213 days in asymptomatics (p < 0.0001). Other characteristics associated with prolonged seropositivity for IgG against the spike protein included age over 55 years, obesity, and non-Caucasian ethnicity. CONCLUSIONS: Among unvaccinated healthcare workers, reinfection with SARS-CoV-2 following a primary infection remained rare.

Mendelian Randomization Analysis Identifies Blood Tyrosine Levels as a Biomarker of Non-Alcoholic Fatty Liver Disease.

Non-alcoholic fatty liver disease (NAFLD) is a complex disease associated with premature mortality. Its diagnosis is challenging, and the identification of biomarkers causally influenced by NAFLD may be clinically useful. We aimed at identifying blood metabolites causally impacted by NAFLD using two-sample Mendelian randomization (MR) with validation in a population-based biobank. Our instrument for genetically predicted NAFLD included all independent genetic variants from a recent genome-wide association study. The outcomes included 123 blood metabolites from 24,925 individuals. After correction for multiple testing, a positive effect of NAFLD on plasma tyrosine levels but not on other metabolites was identified. This association was consistent across MR methods and was robust to outliers and pleiotropy. In observational analyses performed in the Estonian Biobank (10,809 individuals including 359 patients with NAFLD), after multivariable adjustment, tyrosine levels were positively associated with the presence of NAFLD (odds ratio per 1 SD increment = 1.23 [95% confidence interval = 1.12-1.36], p = 2.19 × 10-5). In a small proof-of-concept study on bariatric surgery patients, blood tyrosine levels were higher in patients with NAFLD than without. This study revealed a potentially causal effect of NAFLD on blood tyrosine levels, suggesting it may represent a new biomarker of NAFLD.

Single-cell transcriptomics of the ventral posterolateral nucleus-enriched thalamic regions from HSV-1-infected mice reveal a novel microglia/microglia-like transcriptional response.

BACKGROUND: Microglia participate in the immune response upon central nervous system (CNS) infections. However, the role of these cells during herpes simplex encephalitis (HSE) has not been fully characterized. We sought to identify different microglia/microglia-like cells and describe the potential mechanisms and signaling pathways involved during HSE. METHODS: The transcriptional response of CD11b+ immune cells, including microglia/microglia-like cells, was investigated using single-cell RNA sequencing (scRNA-seq) on cells isolated from the ventral posterolateral nucleus (VPL)-enriched thalamic regions of C57BL/6 N mice intranasally infected with herpes simplex virus-1 (HSV-1) (6 × 105 PFUs/20 µl). We further performed scanning electronic microscopy (SEM) analysis in VPL regions on day 6 post-infection (p.i.) to provide insight into microglial functions. RESULTS: We describe a novel microglia-like transcriptional response associated with a rare cell population (7% of all analyzed cells), named "in transition" microglia/microglia-like cells in HSE. This new microglia-like transcriptional signature, found in the highly infected thalamic regions, was enriched in specific genes (Retnlg, Cxcr2, Il1f9) usually associated with neutrophils. Pathway analysis of this cell-type transcriptome showed increased NLRP3-inflammasome-mediated interleukin IL-1ß production, promoting a pro-inflammatory response. These cells' increased expression of viral transcripts suggests that the distinct "in transition" transcriptome corresponds to the intrinsic antiviral immune signaling of HSV-1-infected microglia/microglia-like cells in the thalamus. In accordance with this phenotype, we observed several TMEM119+/IBA-I+ microglia/microglia-like cells immunostained for HSV-1 in highly infected regions. CONCLUSIONS: A new microglia/microglia-like state may potentially shed light on how microglia could react to HSV-1 infection. Our observations suggest that infected microglia/microglia-like cells contribute to an exacerbated CNS inflammation. Further characterization of this transitory state of the microglia/microglia-like cell transcriptome may allow the development of novel immunomodulatory approaches to improve HSE outcomes by regulating the microglial immune response.

Complete Genome Sequences of Klebsiella michiganensis and Citrobacter farmeri, KPC-2-Producers Serially Isolated from a Single Patient.

Carbapenemase-producing Enterobacterales, including KPC-2 producers, have become a major clinical problem. During an outbreak in Quebec City, Canada, KPC-2-producing Klebsiella michiganensis and Citrobacter farmeri were isolated from a patient six weeks apart. We determined their complete genome sequences. Both isolates carried nearly identical IncN2 plasmids with blaKPC-2 on a Tn4401b element. Both strains also carried IncP1 plasmids, but that of C. farmeri did not carry a Beta-lactamase gene, whereas that of K. michiganensis carried a second copy of blaKPC-2 on Tn4401b. These results suggest recent plasmid transfer between the two species and a recent transposition event.

On the robustness of generalization of drug-drug interaction models.

BACKGROUND: Deep learning methods are a proven commodity in many fields and endeavors. One of these endeavors is predicting the presence of adverse drug-drug interactions (DDIs). The models generated can predict, with reasonable accuracy, the phenotypes arising from the drug interactions using their molecular structures. Nevertheless, this task requires improvement to be truly useful. Given the complexity of the predictive task, an extensive benchmarking on structure-based models for DDIs prediction was performed to evaluate their drawbacks and advantages. RESULTS: We rigorously tested various structure-based models that predict drug interactions using different splitting strategies to simulate different real-world scenarios. In addition to the effects of different training and testing setups on the robustness and generalizability of the models, we then explore the contribution of traditional approaches such as multitask learning and data augmentation. CONCLUSION: Structure-based models tend to generalize poorly to unseen drugs despite their ability to identify new DDIs among drugs seen during training accurately. Indeed, they efficiently propagate information between known drugs and could be valuable for discovering new DDIs in a database. However, these models will most probably fail when exposed to unknown drugs. While multitask learning does not help in our case to solve the problem, the use of data augmentation does at least mitigate it. Therefore, researchers must be cautious of the bias of the random evaluation scheme, especially if their goal is to discover new DDIs.

A novel bioluminescent herpes simplex virus 1 for in vivo monitoring of herpes simplex encephalitis.

Herpes simplex virus 1 (HSV-1) is responsible for herpes simplex virus encephalitis (HSE), associated with a 70% mortality rate in the absence of treatment. Despite intravenous treatment with acyclovir, mortality remains significant, highlighting the need for new anti-herpetic agents. Herein, we describe a novel neurovirulent recombinant HSV-1 (rHSV-1), expressing the fluorescent tdTomato and Gaussia luciferase (Gluc) enzyme, generated by the Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) (CRISPR-Cas9) system. The Gluc activity measured in the cell culture supernatant was correlated (P = 0.0001) with infectious particles, allowing in vitro monitoring of viral replication kinetics. A significant correlation was also found between brain viral titers and Gluc activity in plasma (R2 = 0.8510, P < 0.0001) collected from BALB/c mice infected intranasally with rHSV-1. Furthermore, evaluation of valacyclovir (VACV) treatment of HSE could also be performed by analyzing Gluc activity in mouse plasma samples. Finally, it was also possible to study rHSV-1 dissemination and additionally to estimate brain viral titers by in vivo imaging system (IVIS). The new rHSV-1 with reporter proteins is not only as a powerful tool for in vitro and in vivo antiviral screening, but can also be used for studying different aspects of HSE pathogenesis.

Exploring polypharmacy with artificial intelligence: data analysis protocol.

BACKGROUND: Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication combinations and sequences of use makes it complicated for traditional statistical methods to predict which therapy is genuinely associated with health outcomes. The project aims to use artificial intelligence (AI) to determine the quality of polypharmacy among older adults with chronic diseases in the province of Québec, Canada. METHODS: We will use data from the Quebec Integrated Chronic Disease Surveillance System (QICDSS). QICDSS contains information about prescribed medications in older adults in Quebec collected over 20 years. It also includes diagnostic codes and procedures, and sociodemographic data linked through a unique identification number for each individual. Our research will be structured around three interconnected research axes: AI, Health, and Law&Ethics. The AI research axis will develop algorithms for finding frequent patterns of medication use that correlate with health events, considering data locality and temporality (explainable AI or XAI). The Health research axis will translate these patterns into polypharmacy indicators relevant to public health surveillance and clinicians. The Law&Ethics axis will assess the social acceptability of the algorithms developed using AI tools and the indicators developed by the Heath axis and will ensure that the developed indicators neither discriminate against any population group nor increase the disparities already present in the use of medications. DISCUSSION: The multi-disciplinary research team consists of specialists in AI, health data, statistics, pharmacy, public health, law, and ethics, which will allow investigation of polypharmacy from different points of view and will contribute to a deeper understanding of the clinical, social, and ethical issues surrounding polypharmacy and its surveillance, as well as the use of AI for health record data. The project results will be disseminated to the scientific community, healthcare professionals, and public health decision-makers in peer-reviewed publications, scientific meetings, and reports. The diffusion of the results will ensure the confidentiality of individual data.

Serratia marcescens SCH909 as reservoir and source of genetic elements related to wide dissemination of antimicrobial resistance mechanisms.

Serratia marcescens SCH909 is a multidrug resistant strain isolated in 1988 harboring three class 1 integrons. We wondered if these integrons were retained over time and if there were other antimicrobial resistant determinants contributing to its multidrug resistant profile. Genomic analysis showed a fourth multidrug resistance integron, a Tn7 transposon with dfrA1-sat2-ybeA-ybfA-ybfB-ybgA gene cassettes in the variable region. Insertion sequences were involved in the genesis of novel composite transposons in the L4 subtype plasmid pSCH909, such as Tn6824 carrying an arsenic regulon and two head to head class 1 integrons surrounded by two complete IS1. Remarkably, a novel chromosomal genomic island, SmaR, was identified, closely related to Multiple Antimicrobial Resistance Regions (MARR), usually found in AbaR0-type and AbGRI2-0 from global clones of Acinetobacter baumannii, and in M-type plasmids circulating in Enterobacteriaceae. Maintenance studies showed that the three class 1 integrons were maintained over 1 month without antimicrobial pressure. Since S. marcescens is considered a relevant nosocomial pathogen that can have a wide range of niches - human, plant, animal, soil and inanimate surfaces, our findings support the ability of this species to capture, maintain and spread a broad variety of antimicrobial resistance elements.

Genomic diversity and CRISPR-Cas systems in the cyanobacterium Nostoc in the High Arctic.

Nostoc (Nostocales, Cyanobacteria) has a global distribution in the Polar Regions. However, the genomic diversity of Nostoc is little known and there are no genomes available for polar Nostoc. Here we carried out the first genomic analysis of the Nostoc commune morphotype with a recent sample from the High Arctic and a herbarium specimen collected during the British Arctic Expedition (1875-76). Comparisons of the polar genomes with 26 present-day non-polar members of the Nostocales family highlighted that there are pronounced genetic variations among Nostoc strains and species. Osmoprotection and other stress genes were found in all Nostoc strains, but the two Arctic strains had markedly higher numbers of biosynthetic gene clusters for uncharacterised non-ribosomal peptide synthetases, suggesting a high diversity of secondary metabolites. Since viral-host interactions contribute to microbial diversity, we analysed the CRISPR-Cas systems in the Arctic and two temperate Nostoc species. There were a large number of unique repeat-spacer arrays in each genome, indicating diverse histories of viral attack. All Nostoc strains had a subtype I-D system, but the polar specimens also showed evidence of a subtype I-B system that has not been previously reported in cyanobacteria, suggesting diverse cyanobacteria-virus interactions in the Arctic.

Streamlining CRISPR spacer-based bacterial host predictions to decipher the viral dark matter.

Thousands of new phages have recently been discovered thanks to viral metagenomics. These phages are extremely diverse and their genome sequences often do not resemble any known phages. To appreciate their ecological impact, it is important to determine their bacterial hosts. CRISPR spacers can be used to predict hosts of unknown phages, as spacers represent biological records of past phage-bacteria interactions. However, no guidelines have been established to standardize host prediction based on CRISPR spacers. Additionally, there are no tools that use spacers to perform host predictions on large viral datasets. Here, we developed a set of tools that includes all the necessary steps for predicting the hosts of uncharacterized phages. We created a database of >11 million spacers and a program to execute host predictions on large viral datasets. Our host prediction approach uses biological criteria inspired by how CRISPR-Cas naturally work as adaptive immune systems, which make the results easy to interpret. We evaluated the performance using 9484 phages with known hosts and obtained a recall of 49% and a precision of 69%. We also found that this host prediction method yielded higher performance for phages that infect gut-associated bacteria, suggesting it is well suited for gut-virome characterization.