Controlled Experimental Infection in Pigs with a Strain of Yersinia enterocolitica Harboring Genetic Markers for Human Pathogenicity: Colonization and Stability.

Yersinia enterocolitica (Ye) is one of the major causes of foodborne zoonosis. The BT4/O:3 bioserotype is most commonly isolated in human infections. Pigs are considered the main reservoir of Ye, and hence, understanding the dynamics of infection by this pathogen at the individual and group levels is crucial. In the present study, an experimental model was validated in Large White pigs infected with a BT4/O:3 strain. This study showed that Ye contamination in pigs may occur via the introduction of the bacteria not only by mouth but also by snout, with a colonization process consisting of three periods corresponding to three contamination statuses of pigs: P1, corresponding to the 24 h following ingestion or inhalation of Ye with the appearance of bacteria in tonsils or in feces; P2, from 2 days postinoculation (dpi), corresponding to expansion of Ye and colonization of the digestive system and extraintestinal organs associated with an IgG serological response; and P3, after 21 dpi, corresponding to regression of colonization with intermittent Ye detection in tonsils and feces. Although the inoculated strain persisted up to 56 dpi in all pigs, genetic variations with the loss of the gene yadA (a gene involved in human infection) and the emergence of two new multilocus variable-number tandem-repeat analysis (MLVA) profiles were observed in 33% of the 30 isolates studied. This experimental infection model of pigs by Ye provides new insights into the colonization steps in pigs in terms of bacterial distribution over time and bacterial genetic stability.

Antimicrobial resistance profiles of Streptococcus suis isolated from pigs, wild boars, and humans in France between 1994 and 2020.

Streptococcus suis, an emerging zoonotic pathogen, causes invasive infections and substantial economic losses in the pig industry worldwide. Antimicrobial resistance against 22 antibiotics was studied for 200 S. suis strains collected in different geographical regions of France. Most of the strains (86%) showed resistance to at least one antibiotic with a low rate of resistance to fluoroquinolones, penicillins, pleuromutilin, and diaminopyrimidine-sulfonamides, and a higher rate to macrolides-lincosamides and tetracycline. Multi-resistance patterns were observed in 138 strains; three of them being resistant to six antibiotic families. Statistical analyses highlighted a decrease in the resistance to trimethoprim-sulfamethoxazole, in our collection, between the two periods studied-before 2010 and after 2015-as well as an impact of the geographical origin with a higher rate of resistance to macrolides-lincosamides and penicillin in Brittany than in the other French regions. Furthermore, macrolides-lincosamides and tetracycline resistance patterns were more likely to be found in pig isolates than in human and wild boar isolates. A difference in resistance was also observed between serotypes. Most of the penicillin-resistant strains belong to serotypes 1, 5, 9, 11, 12, 15, 27, and 29. Finally, penicillin and pleuromutilin resistances were mostly found in "non-clinical" isolates. The empirical treatment of human and porcine infections due to S. suis in France can therefore still be carried out with beta-lactams. However, this study emphasizes the need to monitor antimicrobial resistance in this zoonotic pathogen.

Infectious bursal disease virus: predicting viral pathotype using machine learning models focused on early changes in total blood cell counts.

Infectious bursal disease (IBD) is an avian viral disease caused in chickens by infectious bursal disease virus (IBDV). IBDV strains (Avibirnavirus genus, Birnaviridae family) exhibit different pathotypes, for which no molecular marker is available yet. The different pathotypes, ranging from sub-clinical to inducing immunosuppression and high mortality, are currently determined through a 10-day-long animal experiment designed to compare mortality and clinical score of the uncharacterized strain with references strains. Limits of this protocol lie within standardization and the extensive use of animal experimentation. The aim of this study was to establish a predictive model of viral pathotype based on a minimum number of early parameters measured during infection, allowing faster pathotyping of IBDV strains with improved ethics. We thus measured, at 2 and 4 days post-infection (dpi), the blood concentrations of various immune and coagulation related cells, the uricemia and the infectious viral load in the bursa of Fabricius of chicken infected under standardized conditions with a panel of viruses encompassing the different pathotypes of IBDV. Machine learning algorithms allowed establishing a predictive model of the pathotype based on early changes of the blood cell formula, whose accuracy reached 84.1%. Its accuracy to predict the attenuated and strictly immunosuppressive pathotypes was above 90%. The key parameters for this model were the blood concentrations of B cells, T cells, monocytes, granulocytes, thrombocytes and erythrocytes of infected chickens at 4 dpi. This predictive model could be a second option to traditional IBDV pathotyping that is faster, and more ethical.

Efficacy of passive immunization in broiler chicks via an inactivated Escherichia coli autogenous vaccine administered to broiler breeder hens.

Avian pathogenic Escherichia coli (APEC) cause extra-intestinal infections called colibacillosis, which is the dominant bacterial disease in broilers. To date, given the diversity of APEC strains and the need for an acceptable level of protection in day-old chicks, no satisfactory commercial vaccine is available. As part of a French nationwide project, we selected three representative strains among several hundred APEC that cause colibacillosis disease. We first performed experiments to develop colibacillosis in vivo models, using an inoculum of 3 × 107 CFU of each E. coli strain per chick. Two APEC strains (19-381 and 19-383-M1) were found to be highly virulent for day-old chicks, whereas the third strain (19-385-M1) induced no mortality nor morbidity.We then produced an autogenous vaccine using the (Llyod, 1982; MaCQueen, 1967) 19-381 and 19-383-M1 APEC strains and a passive immunization trial was undertaken. Specific-pathogen-free Leghorn hens were vaccinated twice 2 weeks apart, the control group receiving a saline solution. The vaccinated and control hens exhibited no clinical signs, and egg production and fertility of both groups were similar. Fertile eggs were collected for 2 weeks after the second vaccination and chicks were obtained. After challenge with each APEC (19-381 and 19-383-M1), chicks appeared to be partially protected from infection with the 19-383-M1 strain, with 40% mortality compared with 80% for the non-vaccinated chicks. No protection was found when the chicks were challenged with the 19-381 strain. Now, further work is needed to consider some aspects: severity of the pathogen challenge model, persistence of the protection, number of APEC strains in the autogenous vaccine, choice of adjuvants, and heterologous protection by the vaccine made from strain 19-383-M1.RESEARCH HIGHLIGHTS Three APEC strains were characterized and selected to develop in vivo models of colibacillosis.A bivalent autogenous vaccine was produced and a passive immunization trial was carried out.Protection of chicks was demonstrated when challenged with the 19-383-M1 APEC strain (homologous challenge).Further work is needed in particular to evaluate the protection against heterologous challenge.

DUGMO: tool for the detection of unknown genetically modified organisms with high-throughput sequencing data for pure bacterial samples.

BACKGROUND: The European Community has adopted very restrictive policies regarding the dissemination and use of genetically modified organisms (GMOs). In fact, a maximum threshold of 0.9% of contaminating GMOs is tolerated for a "GMO-free" label. In recent years, imports of undescribed GMOs have been detected. Their sequences are not described and therefore not detectable by conventional approaches, such as PCR. RESULTS: We developed DUGMO, a bioinformatics pipeline for the detection of genetically modified (GM) bacteria, including unknown GM bacteria, based on Illumina paired-end sequencing data. The method is currently focused on the detection of GM bacteria with - possibly partial - transgenes in pure bacterial samples. In the preliminary steps, coding sequences (CDSs) are aligned through two successive BLASTN against the host pangenome with relevant tuned parameters to discriminate CDSs belonging to the wild type genome (wgCDS) from potential GM coding sequences (pgmCDSs). Then, Bray-Curtis distances are calculated between the wgCDS and each pgmCDS, based on the difference of genomic vocabulary. Finally, two machine learning methods, namely the Random Forest and Generalized Linear Model, are carried out to target true GM CDS(s), based on six variables including Bray-Curtis distances and GC content. Tests carried out on a GM Bacillus subtilis showed 25 positive CDSs corresponding to the chloramphenicol resistance gene and CDSs of the inserted plasmids. On a wild type B. subtilis, no false positive sequences were detected. CONCLUSION: DUGMO detects exogenous CDS, truncated, fused or highly mutated wild CDSs in high-throughput sequencing data, and was shown to be efficient at detecting GM sequences, but it might also be employed for the identification of recent horizontal gene transfers.

Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data.

INTRODUCTION: Metabolomics is a powerful phenotyping tool in nutrition and health research, generating complex data that need dedicated treatments to enrich knowledge of biological systems. In particular, to investigate relations between environmental factors, phenotypes and metabolism, discriminant statistical analyses are generally performed separately on metabolomic datasets, complemented by associations with metadata. Another relevant strategy is to simultaneously analyse thematic data blocks by a multi-block partial least squares discriminant analysis (MBPLSDA) allowing determining the importance of variables and blocks in discriminating groups of subjects, taking into account data structure. OBJECTIVE: The present objective was to develop a full open-source standalone tool, allowing all steps of MBPLSDA for the joint analysis of metabolomic and epidemiological data. METHODS: This tool was based on the mbpls function of the ade4 R package, enriched with functionalities, including some dedicated to discriminant analysis. Provided indicators help to determine the optimal number of components, to check the MBPLSDA model validity, and to evaluate the variability of its parameters and predictions. RESULTS: To illustrate the potential of this tool, MBPLSDA was applied to a real case study involving metabolomics, nutritional and clinical data from a human cohort. The availability of different functionalities in a single R package allowed optimizing parameters for an efficient joint analysis of metabolomics and epidemiological data to obtain new insights into multidimensional phenotypes. CONCLUSION: In particular, we highlighted the impact of filtering the metabolomic variables beforehand, and the relevance of a MBPLSDA approach in comparison to a standard PLS discriminant analysis method.

MINT: a multivariate integrative method to identify reproducible molecular signatures across independent experiments and platforms.

BACKGROUND: Molecular signatures identified from high-throughput transcriptomic studies often have poor reliability and fail to reproduce across studies. One solution is to combine independent studies into a single integrative analysis, additionally increasing sample size. However, the different protocols and technological platforms across transcriptomic studies produce unwanted systematic variation that strongly confounds the integrative analysis results. When studies aim to discriminate an outcome of interest, the common approach is a sequential two-step procedure; unwanted systematic variation removal techniques are applied prior to classification methods. RESULTS: To limit the risk of overfitting and over-optimistic results of a two-step procedure, we developed a novel multivariate integration method, MINT, that simultaneously accounts for unwanted systematic variation and identifies predictive gene signatures with greater reproducibility and accuracy. In two biological examples on the classification of three human cell types and four subtypes of breast cancer, we combined high-dimensional microarray and RNA-seq data sets and MINT identified highly reproducible and relevant gene signatures predictive of a given phenotype. MINT led to superior classification and prediction accuracy compared to the existing sequential two-step procedures. CONCLUSIONS: MINT is a powerful approach and the first of its kind to solve the integrative classification framework in a single step by combining multiple independent studies. MINT is computationally fast as part of the mixOmics R CRAN package, available at http://www.mixOmics.org/mixMINT/ and http://cran.r-project.org/web/packages/mixOmics/ .

Impact of third-generation-cephalosporin administration in hatcheries on fecal Escherichia coli antimicrobial resistance in broilers and layers.

We investigated the impact of the hatchery practice of administering third-generation cephalosporin (3GC) on the selection and persistence of 3GC-resistant Escherichia coli in poultry. We studied 15 3GC-treated (TB) and 15 non-3GC-treated (NTB) broiler flocks and 12 3GC-treated (TL) and 10 non-3GC-treated (NTL) future layer flocks. Fecal samples from each flock were sampled before arrival on the farm (day 0), on day 2, on day 7, and then twice more. E. coli isolates were isolated on MacConkey agar without antibiotics and screened for 3GC resistance, and any 3GC-resistant E. coli isolates were further analyzed. 3GC-resistant E. coli isolates were found in all 3GC-treated flocks on at least one sampling date. The percentages of 3GC-resistant E. coli isolates were significantly higher in TB (41.5%) than in NTB (19.5%) flocks and in TL (49.5%) than in NTL (24.5%) flocks. In the day 2 samples, more than 80% of the E. coli strains isolated were 3GC resistant. 3GC-resistant E. coli strains were still detected at the end of the follow-up period in 6 out of 27 3GC-treated and 5 out of 25 non-3GC-treated flocks. Many 3GC-resistant E. coli strains were resistant to tetracycline, and there were significant differences in the percentages of resistance to sulfamethoxazole-trimethoprim, streptomycin, or gentamicin between treated and nontreated flocks. blaCTX-M and blaCMY-2 were the most frequently detected genes. These results clearly demonstrated that 3GC-resistant strains are introduced early in flocks and that the use of 3GC in hatcheries promotes the selection of 3GC-resistant E. coli. Measures must be implemented to avoid the spread and selection of 3GC-resistant strains.

H5-based DNA constructs derived from selected highly pathogenic H5N1 avian influenza virus induce high levels of humoral antibodies in Muscovy ducks against low pathogenic viruses.

BACKGROUND: H5 low pathogenic avian influenza virus (LPAIV) infection in domestic ducks is a major problem in duck producing countries. Their silent circulation is an ongoing source of potential highly pathogenic or zoonotic emerging strains. To prevent such events, vaccination of domestic ducks might be attempted but remains challenging. Currently licensed vector vaccines derived from H5N1 HPAIV possess clade 0, clade 2.2 or clade 2.3.4 HA sequences: selection of the best HA candidate inducing the largest cross protection is a key issue. For this purpose, DNA immunization of specific pathogen free Muscovy ducks was performed using different synthetic codon optimized (opt) or native HA genes from H5N2 LPAIV and several H5N1 HPAIV clade 2.1, 2.2.1 and 2.3.4. Humoral cross-immunity was assessed 3 weeks after boost by hemagglutination inhibition (HI) and virus neutralization (VN) against three French H5 LPAIV antigens. FINDINGS: Vaccination with LP H5N2 HA induced the highest VN antibody titre against the homologous antigen; however, the corresponding HI titre was lower and comparable to HI titres obtained after immunization with opt HA derived from clades 2.3.4 or 2.1. Compared to the other HPAIV-derived constructs, vaccination with clade 2.3.4 opt HA consistently induced the highest antibody titres in HI and VN, when tested against all three H5 LPAIV antigens and H5N2 LPAIV, respectively: differences in titres against this last strain were statistically significant. CONCLUSION: The present study provides a standardized method to assess cross-immunity based on HA immunogenicity alone, and suggests that clade 2.3.4-derived recombinant vaccines might be the optimal candidates for further challenge testing to vaccinate domestic Muscovy ducks against H5 LPAIV.

Application of multiblock analysis to identify key areas and risk factors for dairy cow persistence.

The present study analysed the importance of individual variables and different thematic blocks of production areas, management, and herd infectious disease status on cow persistence, characterised by herd on-farm mortality rate (MR), culling rate (CR), and mean age of culled cows (MAofCC) applying multiblock partial least squares (mbPLS) analysis. This study included 120 free-stall dairy herds with ≥ 100 cows. Data on the previous year's predominant cow housing system and management practices were collected, and on-farm measurements and cow scoring were performed. Bulk tank milk (BTM) and heifer blood samples (10 samples per herd) were collected and analysed for antibodies against the selected pathogens. In total, 172 variables were aggregated into 14 thematic blocks. The annual CR, MR, and MAofCC values were calculated for each herd. Thematic blocks with significant impact on cow persistence (included herd MR, CR and MAofCC) were 'infectious diseases' (block importance index out of all blocks = 13.6%, 95% CI 10.3; 20.5), 'fertility management' (16.3%, 95% CI 6.8; 26.9), 'lactating cow management' (11.5%, 95% CI 6.4; 17.8), 'milking' (11.3%, 95% CI 3.2; 17.1), 'herd characteristics' (10.1%, 95% CI 6.3; 14.2), 'close-up period management' (9.7%, 95% CI 2.7; 15.7), 'calving management' (7.9%, 95% CI 3.1; 11.4) and 'disease management' (7.3%, 95% CI 0.2; 12.0). Variable categories with the highest importance in explaining composite outcome including herd MR, CR and MAofCC were rear-end and udder lesions in ≥ 20% of the cows, BTM and heifers seropositive to bovine respiratory syncytial virus, vaccination against bovine herpesvirus 1, twice daily milking and herd location in Northwest region. Larger herd size, higher levels of milk yield, and rearing predominantly Holstein breed cattle were herd factors associated with poorer cow persistency. Grazing cows and having semi-insulated barns were associated with lower CR and MR, respectively. Heat detection and farm pregnancy testing strategies were significant factors in the fertility block. Using disposable dry papers for teat cleaning and not using any wet teat-cleaning tools were risk factors for high MR. A robotic milking system was protective for increased herd MR and CR. A high pre-calving body condition score and poor rear body cleanliness of ≥ 30% of cows were associated with inferior herd persistency outcomes. Calving in group pens with deep litter bedding was associated with a lower CR. Multiblock PLS model is innovative tool that helped to identify most influential farming areas but also single risk factors associated with cow persistency described by multiple parameters.

Virulence genes, resistome and mobilome of Streptococcus suis strains isolated in France.

Streptococcus suis is a leading cause of infection in pigs, causing extensive economic losses. In addition, it can also infect wild fauna, and can be responsible for severe infections in humans. Increasing antimicrobial resistance (AMR) has been described in S. suis worldwide and most of the AMR genes are carried by mobile genetic elements (MGEs). This contributes to their dissemination by horizontal gene transfer. A collection of 102 strains isolated from humans, pigs and wild boars in France was subjected to whole genome sequencing in order to: (i) study their genetic diversity, (ii) evaluate their content in virulence-associated genes, (iii) decipher the mechanisms responsible for their AMR and their association with MGEs, and (iv) study their ability to acquire extracellular DNA by natural transformation. Analysis by hierarchical clustering on principal components identified a few virulence-associated factors that distinguish invasive CC1 strains from the other strains. A plethora of AMR genes (n=217) was found in the genomes. Apart from the frequently reported erm(B) and tet(O) genes, more recently described AMR genes were identified [vga(F)/sprA, vat(D)]. Modifications in PBPs/MraY and GyrA/ParC were detected in the penicillin- and fluoroquinolone-resistant isolates respectively. New AMR gene-MGE associations were detected. The majority of the strains have the full set of genes required for competence, i.e for the acquisition of extracellular DNA (that could carry AMR genes) by natural transformation. Hence the risk of dissemination of these AMR genes should not be neglected.

Polygenic inheritance and its interplay with smoking history in predicting lung cancer diagnosis: a French-Canadian case-control cohort.

BACKGROUND: The most near-term clinical application of genome-wide association studies in lung cancer is a polygenic risk score (PRS). METHODS: A case-control dataset was generated consisting of 4002 lung cancer cases from the LORD project and 20,010 ethnically matched controls from CARTaGENE. A genome-wide PRS including >1.1 million genetic variants was derived and validated in UK Biobank (n = 5419 lung cancer cases). The predictive ability and diagnostic discrimination performance of the PRS was tested in LORD/CARTaGENE and benchmarked against previous PRSs from the literature. Stratified analyses were performed by smoking status and genetic risk groups defined as low (<20th percentile), intermediate (20-80th percentile) and high (>80th percentile) PRS. FINDINGS: The phenotypic variance explained and the effect size of the genome-wide PRS numerically outperformed previous PRSs. Individuals with high genetic risk had a 2-fold odds of lung cancer compared to low genetic risk. The PRS was an independent predictor of lung cancer beyond conventional clinical risk factors, but its diagnostic discrimination performance was incremental in an integrated risk model. Smoking increased the odds of lung cancer by 7.7-fold in low genetic risk and by 11.3-fold in high genetic risk. Smoking with high genetic risk was associated with a 17-fold increase in the odds of lung cancer compared to individuals who never smoked and with low genetic risk. INTERPRETATION: Individuals at low genetic risk are not protected against the smoking-related risk of lung cancer. The joint multiplicative effect of PRS and smoking increases the odds of lung cancer by nearly 20-fold. FUNDING: This work was supported by the CQDM and the IUCPQ Foundation owing to a generous donation from Mr. Normand Lord.

Distribution of infectious and parasitic agents among three sentinel bee species across European agricultural landscapes.

Infectious and parasitic agents (IPAs) and their associated diseases are major environmental stressors that jeopardize bee health, both alone and in interaction with other stressors. Their impact on pollinator communities can be assessed by studying multiple sentinel bee species. Here, we analysed the field exposure of three sentinel managed bee species (Apis mellifera, Bombus terrestris and Osmia bicornis) to 11 IPAs (six RNA viruses, two bacteria, three microsporidia). The sentinel bees were deployed at 128 sites in eight European countries adjacent to either oilseed rape fields or apple orchards during crop bloom. Adult bees of each species were sampled before their placement and after crop bloom. The IPAs were detected and quantified using a harmonised, high-throughput and semi-automatized qPCR workflow. We describe differences among bee species in IPA profiles (richness, diversity, detection frequencies, loads and their change upon field exposure, and exposure risk), with no clear patterns related to the country or focal crop. Our results suggest that the most frequent IPAs in adult bees are more appropriate for assessing the bees' IPA exposure risk. We also report positive correlations of IPA loads supporting the potential IPA transmission among sentinels, suggesting careful consideration should be taken when introducing managed pollinators in ecologically sensitive environments.

Novel indices reveal that pollinator exposure to pesticides varies across biological compartments and crop surroundings.

Declines in insect pollinators have been linked to a range of causative factors such as disease, loss of habitats, the quality and availability of food, and exposure to pesticides. Here, we analysed an extensive dataset generated from pesticide screening of foraging insects, pollen-nectar stores/beebread, pollen and ingested nectar across three species of bees collected at 128 European sites set in two types of crop. In this paper, we aimed to (i) derive a new index to summarise key aspects of complex pesticide exposure data and (ii) understand the links between pesticide exposures depicted by the different matrices, bee species and apple orchards versus oilseed rape crops. We found that summary indices were highly correlated with the number of pesticides detected in the related matrix but not with which pesticides were present. Matrices collected from apple orchards generally contained a higher number of pesticides (7.6 pesticides per site) than matrices from sites collected from oilseed rape crops (3.5 pesticides), with fungicides being highly represented in apple crops. A greater number of pesticides were found in pollen-nectar stores/beebread and pollen matrices compared with nectar and bee body matrices. Our results show that for a complete assessment of pollinator pesticide exposure, it is necessary to consider several different exposure routes and multiple species of bees across different agricultural systems.

MBPCA-OS: an exploratory multiblock method for variables of different measurement levels. Application to study the immune response to SARS-CoV-2 infection and vaccination.

Studying a large number of variables measured on the same observations and organized in blocks - denoted multiblock data - is becoming standard in several domains especially in biology. To explore the relationships between all these variables - at the block- and the variable-level - several exploratory multiblock methods were proposed. However, most of them are only designed for numeric variables. In reality, some data sets contain variables of different measurement levels (i.e., numeric, nominal, ordinal). In this article, we focus on exploratory multiblock methods that handle variables at their appropriate measurement level. Multi-Block Principal Component Analysis with Optimal Scaling (MBPCA-OS) is proposed and applied to multiblock data from the CURIE-O-SA French cohort. In this study, variables are of different measurement levels and organized in four blocks. The objective is to study the immune responses according to the SARS-CoV-2 infection and vaccination statuses, the symptoms and the participant's characteristics.

Monophasic Variant of Salmonella Typhimurium Infection Affects the Serum Metabolome in Swine.

Salmonella is the most relevant foodborne zoonotic agent found in swine, and its presence in French herds is significant. Its carriage is asymptomatic, which makes it difficult to detect during rearing, thus increasing the risk of its presence on pork meat. Studies have shown that enteric infection in animals could be associated with changes in the serum metabolome composition, through the immune response or changes in the digestive microbiota composition. We hypothesized that these changes in the serum metabolome composition could be used as markers for the detection of asymptomatic animals infected by Salmonella. Using untargeted analysis by liquid chromatography coupled with mass spectrometry, we showed that significant differences in the composition of the serum metabolome could be detected between infected or noninfected animals both 1 and 21 days after experimental infection. This serum metabolome composition significantly changed during the 21 days postinfection in the infected animal groups, suggesting an evolution of the impact of infection with time. Despite this evolution, differences in the serum metabolome composition persisted between infected and noninfected animals 21 days after the initial infection. We also showed a possible difference between high-shedding and low-shedding animals 21 days postinfection. Finally, some of the variations in the metabolome were found to be significantly associated with variations of specific members of the fecal microbiota. Thus, excreting and asymptomatic animals, but also high-shedding animals, could be identified on the basis of their serum metabolome composition.

Study of the effect of administration of narasin or antibiotics on in vivo selection of a narasin- and multidrug-resistant Enterococcus cecorum strain.

Enterococcus cecorum is a member of the normal poultry gut microbiota and an emerging poultry pathogen. Some strains are resistant to key antibiotics and coccidiostats. We evaluated the impact on chicken excretion and persistence of a multidrug-resistant E. cecorum of administering narasin or antibiotics. E. cecorum CIRMBP-1294 (Ec1294) is non-wild-type to many antimicrobials, including narasin, levofloxacin, oxytetracycline and glycopeptides, it has a low susceptibility to amoxicillin, and carries a chromosomal vanA operon. Six groups of 15 chicks each were orally inoculated with Ec1294 and two groups were left untreated. Amoxicillin, oxytetracycline or narasin were administered orally to one group each, either at the recommended dose for five days (amoxicillin, oxytetracycline) or continuously (narasin). Faecal samples were collected weekly and caecal samples were obtained from sacrificed birds on day 28. Ec1294 titres were evaluated by culture on vancomycin- and levofloxacin-supplemented media in 5 % CO2. For inoculated birds given narasin, oxytetracycline or no antimicrobials, vancomycin-resistant enterococci were searched by culture on vancomycin-supplemented media incubated in air, and a PCR was used to detect the vanA gene. Ec1294 persisted in inoculated chicks up to day 28. Compared to the control group, the Ec1294 titre was significantly lower in the amoxicillin- and narasin-receiving groups on days 21 and 28, but was unexpectedly higher in the oxytetracycline-receiving group before and after oxytetracycline administration, preventing a conclusion for this group. No transfer of the vanA gene to other enterococci was detected. Other trials in various experimental conditions should now be conducted to confirm this apparent absence of co-selection of the multi-drug-resistant E. cecorum by narasin or amoxicillin administration.

High antigenic diversity of serotype 1 infectious bursal disease virus revealed by antigenic cartography.

The antigenic characterization of IBDV, a virus that causes an immunosuppressive disease in young chickens, has been historically addressed using cross virus neutralization (VN) assay and antigen-capture enzyme-linked immunosorbent (AC-ELISA). However, VN assay has been usually carried out either in specific antibody negative embryonated eggs, for non-cell culture adapted strains, which is tedious, or on chicken embryo fibroblasts (CEF), which requires virus adaptation to cell culture. AC-ELISA has provided crucial information about IBDV antigenicity, but this information is limited to the epitopes included in the tested panel with a lack of information of overall antigenic view. The present work aimed at overcoming those technical limitations and providing an extensive antigenic landscape based on original cross VN assays employing primary chicken B cells, where no previous IBDV adaptation is required. Sixteen serotype 1 IBDV viruses, comprising both reference strains and documented antigenic variants were tested against eleven chicken post-infectious sera. The VN data were analysed by antigenic cartography, a method which enables reliable high-resolution quantitative and visual interpretation of large binding assay datasets. The resulting antigenic cartography revealed i) the existence of several antigenic clusters of IBDV, ii) high antigenic relatedness between some genetically unrelated viruses, iii) a highly variable contribution to global antigenicity of previously identified individual epitopes and iv) broad reactivity of chicken sera raised against antigenic variants. This study provides an overall view of IBDV antigenic diversity. Implementing this approach will be instrumental to follow the evolution of IBDV antigenicity and control the disease.

Application of Machine Learning Prediction of Individual SARS-CoV-2 Vaccination and Infection Status to the French Serosurveillance Survey From March 2020 to 2022: Cross-Sectional Study.

BACKGROUND: The seroprevalence of SARS-CoV-2 infection in the French population was estimated with a representative, repeated cross-sectional survey based on residual sera from routine blood testing. These data contained no information on infection or vaccination status, thus limiting the ability to detail changes observed in the immunity level of the population over time. OBJECTIVE: Our aim is to predict the infected or vaccinated status of individuals in the French serosurveillance survey based only on the results of serological assays. Reference data on longitudinal serological profiles of seronegative, infected, and vaccinated individuals from another French cohort were used to build the predictive model. METHODS: A model of individual vaccination or infection status with respect to SARS-CoV-2 obtained from a machine learning procedure was proposed based on 3 complementary serological assays. This model was applied to the French nationwide serosurveillance survey from March 2020 to March 2022 to estimate the proportions of the population that were negative, infected, vaccinated, or infected and vaccinated. RESULTS: From February 2021 to March 2022, the estimated percentage of infected and unvaccinated individuals in France increased from 7.5% to 16.8%. During this period, the estimated percentage increased from 3.6% to 45.2% for vaccinated and uninfected individuals and from 2.1% to 29.1% for vaccinated and infected individuals. The decrease in the seronegative population can be largely attributed to vaccination. CONCLUSIONS: Combining results from the serosurveillance survey with more complete data from another longitudinal cohort completes the information retrieved from serosurveillance while keeping its protocol simple and easy to implement.

Avian metapneumovirus: A five-plex digital droplet RT-PCR method for identification of subgroups A, B, C, and D.

End-point and real-time avian metapneumovirus (AMPV) RT-PCRs have been developed to detect one or two of the four recognized subgroups (A,B,C, and D) simultaneously or for broad range AMPV detection. Current subgroup specific tests target variable areas of the genome which makes these PCRs sensitive to specificity defects as recently documented. In the current study, a single five-plex digital droplet RT-PCR targeting the conserved viral polymerase gene of AMPV, which is less prone to genetic drift, has been designed. This digital droplet RT-PCR was capable of identifying each of the four AMPV subgroups. Each subgroup was identified according to a specifically assigned fluorescent amplitude. Specificity, which was tested including 31 AMPV strains, non-AMPV avian viruses and closely related human respiratory viruses, was 100%. The specific limit of detection for extracted viral RNA was estimated between 1 and 3 copies/µl. This tool simplifies the number of tests required for AMPV genotype diagnostics and should be theoretically less effected by viral genome evolution due to its target region. Ultimately, application of this test will contribute to an improved understanding of the global geographic distribution and subgroup host range of field strains.