Dispersion of antimicrobial resistant bacteria in pig farms and in the surrounding environment.

BACKGROUND: Antimicrobial resistance has been identified as a major threat to global health. The pig food chain is considered an important source of antimicrobial resistance genes (ARGs). However, there is still a lack of knowledge on the dispersion of ARGs in pig production system, including the external environment. RESULTS: In the present study, we longitudinally followed one swine farm located in Italy from the weaning phase to the slaughterhouse to comprehensively assess the diversity of ARGs, their diffusion, and the bacteria associated with them. We obtained shotgun metagenomic sequences from 294 samples, including pig feces, farm environment, soil around the farm, wastewater, and slaughterhouse environment. We identified a total of 530 species-level genome bins (SGBs), which allowed us to assess the dispersion of microorganisms and their associated ARGs in the farm system. We identified 309 SGBs being shared between the animals gut microbiome, the internal and external farm environments. Specifically, these SGBs were characterized by a diverse and complex resistome, with ARGs active against 18 different classes of antibiotic compounds, well matching antibiotic use in the pig food chain in Europe. CONCLUSIONS: Collectively, our results highlight the urgency to implement more effective countermeasures to limit the dispersion of ARGs in the pig food systems and the relevance of metagenomics-based approaches to monitor the spread of ARGs for the safety of the farm working environment and the surrounding ecosystems.

Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses.

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

Routes of dispersion of antibiotic resistance genes from the poultry farm system.

Poultry farms are hotspots for the development and spread of antibiotic resistance genes (ARGs), due to high stocking densities and extensive use of antibiotics, posing a threat of spread and contagion to workers and the external environment. Here, we applied shotgun metagenome sequencing to characterize the gut microbiome and resistome of poultry, workers and their households - also including microbiomes from the internal and external farm environment - in three different farms in Italy during a complete rearing cycle. Our results highlighted a relevant overlap among the microbiomes of poultry, workers, and their families (gut and skin), with clinically relevant ARGs and associated mobile elements shared in both poultry and human samples. On a finer scale, the reconstruction of species-level genome bins (SGBs) allowed us to delineate the dynamics of microorganism and ARGs dispersion from farm systems. We found the associations with worker microbiomes representing the main route of ARGs dispersion from poultry to human populations. Collectively, our findings clearly demonstrate the urgent need to implement more effective procedures to counteract ARGs dispersion from poultry food systems and the relevance of metagenomics-based metacommunity approaches to monitor the ARGs dispersion process for the safety of the working environment on farms.

Quantitative PCR versus metagenomics for monitoring antibiotic resistance genes: balancing high sensitivity and broad coverage.

The widespread occurrence of clinically relevant antibiotic resistance within humans, animals, and environment motivates the development of sensitive and accurate detection and quantification methods. Metagenomics and quantitative PCR (qPCR) are amongst the most used approaches. In this study, we aimed to evaluate and compare the performance of these methods to screen antibiotic resistance genes in animal faecal, wastewater, and water samples. Water and wastewater samples were from hospital effluent, different treatment stages of two treatment plants, and of the receiving river at the discharge point. The animal samples were from pig and chicken faeces. Antibiotic resistance gene coverage, sensitivity, and usefulness of the quantitative information were analyzed and discussed. While both methods were able to distinguish the resistome profiles and detect gradient stepwise mixtures of pig and chicken faeces, qPCR presented higher sensitivity for the detection of a few antibiotic resistance genes in water/wastewater. In addition, the comparison of predicted and observed antibiotic resistance gene quantifications unveiled the higher accuracy of qPCR. Metagenomics analyses, while less sensitive, provided a markedly higher coverage of antibiotic resistance genes compared to qPCR. The complementarity of both methods and the importance of selecting the best method according to the study purpose are discussed.

Predicting ß-lactam susceptibility from the genome of Streptococcus pneumoniae and other mitis group streptococci.

Introduction: For Streptococcus pneumoniae, ß-lactam susceptibility can be predicted from the amino acid sequence of the penicillin-binding proteins PBP1a, PBP2b, and PBP2x. The combination of PBP-subtypes provides a PBP-profile, which correlates to a phenotypic minimal inhibitory concentration (MIC). The non-S. pneumoniae Mitis-group streptococci (MGS) have similar PBPs and exchange pbp-alleles with S. pneumoniae. We studied whether a simple BLAST analysis could be used to predict phenotypic susceptibility in Danish S. pneumoniae isolates and in internationally collected MGS. Method: Isolates with available WGS and phenotypic susceptibility data were included. For each isolate, the best matching PBP-profile was identified by BLAST analysis. The corresponding MICs for penicillin and ceftriaxone was retrieved. Category agreement (CA), minor-, major-, and very major discrepancy was calculated. Genotypic-phenotypic accuracy was examined with Deming regression. Results: Among 88 S. pneumoniae isolates, 55 isolates had a recognized PBP-profile, and CA was 100% for penicillin and 98.2% for ceftriaxone. In 33 S. pneumoniae isolates with a new PBP-profile, CA was 90.9% (penicillin) and 93.8% (ceftriaxone) using the nearest recognized PBP-profile. Applying the S. pneumoniae database to non-S. pneumoniae MGS revealed that none had a recognized PBP-profile. For Streptococcus pseudopneumoniae, CA was 100% for penicillin and ceftriaxone in 19 susceptible isolates. In 33 Streptococcus mitis isolates, CA was 75.8% (penicillin) and 86.2% (ceftriaxone) and in 25 Streptococcus oralis isolates CA was 8% (penicillin) and 100% (ceftriaxone). Conclusion: Using a simple BLAST analysis, genotypic susceptibility prediction was accurate in Danish S. pneumoniae isolates, particularly in isolates with recognized PBP-profiles. Susceptibility was poorly predicted in other MGS using the current database.

One Day in Denmark: Nationwide point-prevalence survey of human bacterial isolates and comparison of classical and whole-genome sequence-based species identification methods.

OBJECTIVES: Implementing whole-genome sequencing (WGS) technologies in clinical microbiology laboratories can increase the amount and quality of information available for healthcare practitioners. In this study, we analysed the applicability of this method and determined the distribution of bacterial species processed in clinical settings in Denmark. METHODS: We performed a point-prevalence study of all bacterial isolates (n = 2,009) processed and reported in the Clinical Microbiology Laboratories in Denmark in one day in January 2018. We compared species identification as performed by classical methods (MALDI-TOF) and by bioinformatics analysis (KmerFinder and rMLST) of WGS (Illumina NextSeq) data. We compared the national point-prevalence of bacterial isolates observed in clinical settings with the research attention given to those same genera in scientific literature. RESULTS: The most prevalent bacterium was Escherichia coli isolated from urine (n = 646), followed by Staphylococcus spp. from skin or soft tissues (n = 197). The distribution of bacterial species throughout the country was not homogeneous. We observed concordance of species identification for all methods in 95.7% (n = 1,919) of isolates, furthermore obtaining concordance for 99.7% (n = 1,999) at genus level. The number of scientific publications in the country did not correlate with the number of bacterial isolates of each genera analysed in this study. CONCLUSIONS: WGS technologies have the potential to be applied in clinical settings for routine diagnostics purposes. This study also showed that bioinformatics databases should be continuously improved and results from local point-prevalence surveys should not be applied at national levels without previously determining possible regional variations.

FI: The Fecobiome Initiative.

Animal husbandry has been key to the sustainability of human societies for millennia. Livestock animals, such as cattle, convert plants to protein biomass due to a compartmentalized gastrointestinal tract (GIT) and the complementary contributions of a diverse GIT microbiota, thereby providing humans with meat and dairy products. Research on cattle gut microbial symbionts has mainly focused on the rumen (which is the primary fermentation compartment) and there is a paucity of functional insight on the intestinal (distal end) microbiota, where most foodborne zoonotic bacteria reside. Here, we present the Fecobiome Initiative (or FI), an international effort that aims at facilitating collaboration on research projects related to the intestinal microbiota, disseminating research results, and increasing public availability of resources. By doing so, the FI can help mitigate foodborne and animal pathogens that threaten livestock and human health, reduce the emergence and spread of antimicrobial resistance in cattle and their proximate environment, and potentially improve the welfare and nutrition of animals. We invite all researchers interested in this type of research to join the FI through our website: www.fecobiome.com.

Danish Whole-Genome-Sequenced Candida albicans and Candida glabrata Samples Fit into Globally Prevalent Clades.

Candida albicans and Candida glabrata are opportunistic fungal pathogens with increasing incidence worldwide and higher-than-expected prevalence in Denmark. We whole-genome sequenced yeast isolates collected from Danish Clinical Microbiology Laboratories to obtain an overview of the Candida population in the country. The majority of the 30 C. albicans isolates were found to belong to three globally prevalent clades, and, with one exception, the remaining isolates were also predicted to cluster with samples from other geographical locations. Similarly, most of the eight C. glabrata isolates were predicted to be prevalent subtypes. Antifungal susceptibility testing proved all C. albicans isolates to be susceptible to both azoles and echinocandins. Two C. glabrata isolates presented azole-resistant phenotypes, yet all were susceptible to echinocandins. There is no indication of causality between population structure and resistance phenotypes for either species.

Prevalence and genomic analysis of ESBL-producing Escherichia coli in retail raw meats in Singapore.

OBJECTIVES: To determine the prevalence and genetic characteristics of ESBL-producing Escherichia coli in retail raw meats from Singapore markets. METHODS: A total of 634 raw meat (chicken, pork and beef) samples were collected from markets in Singapore during June 2017-October 2018. The samples were enriched overnight and then incubated on Brilliance™ ESBL Agar. Presumptive ESBL isolates were confirmed using the double-disc synergy test. Confirmed ESBL-producing E. coli were sent for WGS and bioinformatic analysis was performed. RESULTS: The prevalence of ESBL-producing E. coli in chicken, pork and beef meats was 51.2% (109/213), 26.9% (58/216) and 7.3% (15/205), respectively. A total of 225 ESBL-producing E. coli were isolated from 184 samples. ß-Lactam resistance genes were detected in all isolates. After ß-lactam resistance genes, the most common antimicrobial resistance genes detected were aminoglycoside resistance genes (92.4%). One hundred and seventy-two (76.4%), 102 (45.3%) and 52 (23.1%) isolates carried blaCTX-M genes, blaTEM genes and blaSHV genes, respectively. blaCTX-M-55 (57/225, 25.3%) and blaCTX-M-65 (40/225, 17.8%) were the most frequent ESBL genes. Colistin resistance genes (including mcr-1, mcr-3 and mcr-5) were found in 15.6% of all isolates. CONCLUSIONS: This study indicates that ESBL-producing E. coli are widely found in retail raw meats, especially chicken, in Singapore. Occurrence of MDR (resistance to at least three classes of antimicrobial) and colistin resistance genes in retail raw meat suggests potential food safety and public health risks.

Dissection of the antimicrobial and hemolytic activity of Cap18: Generation of Cap18 derivatives with enhanced specificity.

Due to the rapid emergence of resistance to classical antibiotics, novel antimicrobial compounds are needed. It is desirable to selectively kill pathogenic bacteria without targeting other beneficial bacteria in order to prevent the negative clinical consequences caused by many broad-spectrum antibiotics as well as reducing the development of antibiotic resistance. Antimicrobial peptides (AMPs) represent an alternative to classical antibiotics and it has been previously demonstrated that Cap18 has high antimicrobial activity against a broad range of bacterial species. In this study we report the design of a positional scanning library consisting of 696 Cap18 derivatives and the subsequent screening for antimicrobial activity against Y. ruckeri, A. salmonicida, S. Typhimurium and L. lactis as well as for hemolytic activity measuring the hemoglobin release of horse erythrocytes. We show that the hydrophobic face of Cap18, in particular I13, L17 and I24, is essential for its antimicrobial activity against S. Typhimurium, Y. ruckeri, A. salmonicida, E. coli, P. aeruginosa, L. lactis, L. monocytogenes and E. faecalis. In particular, Cap18 derivatives harboring a I13D, L17D, L17P, I24D or I24N substitution lost their antimicrobial activity against any of the tested bacterial strains. In addition, we were able to generate species-specific Cap18 derivatives by particular amino acid substitutions either in the hydrophobic face at positions L6, L17, I20, and I27, or in the hydrophilic face at positions K16 and K18. Finally, our data showed the proline residue at position 29 to be essential for the inherent low hemolytic activity of Cap18 and that substitution of the residues K16, K23, or G21 by any hydrophobic residues enhances the hemolytic activity. This study demonstrates the potential of generating species-specific AMPs for the selective elimination of bacterial pathogens.

SCCmecFinder, a Web-Based Tool for Typing of Staphylococcal Cassette Chromosome mec in Staphylococcus aureus Using Whole-Genome Sequence Data.

Typing of methicillin-resistant Staphylococcus aureus (MRSA) is important in infection control and surveillance. The current nomenclature of MRSA includes the genetic background of the S. aureus strain determined by multilocus sequence typing (MLST) or equivalent methods like spa typing and typing of the mobile genetic element staphylococcal cassette chromosome mec (SCCmec), which carries the mecA or mecC gene. Whereas MLST and spa typing are relatively simple, typing of SCCmec is less trivial because of its heterogeneity. Whole-genome sequencing (WGS) provides the essential data for typing of the genetic background and SCCmec, but so far, no bioinformatic tools for SCCmec typing have been available. Here, we report the development and evaluation of SCCmecFinder for characterization of the SCCmec element from S. aureus WGS data. SCCmecFinder is able to identify all SCCmec element types, designated I to XIII, with subtyping of SCCmec types IV (2B) and V (5C2). SCCmec elements are characterized by two different gene prediction approaches to achieve correct annotation, a Basic Local Alignment Search Tool (BLAST)-based approach and a k-mer-based approach. Evaluation of SCCmecFinder by using a diverse collection of clinical isolates (n = 93) showed a high typeability level of 96.7%, which increased to 98.9% upon modification of the default settings. In conclusion, SCCmecFinder can be an alternative to more laborious SCCmec typing methods and is freely available at https://cge.cbs.dtu.dk/services/SCCmecFinder. IMPORTANCE SCCmec in MRSA is acknowledged to be of importance not only because it contains the mecA or mecC gene but also for staphylococcal adaptation to different environments, e.g., in hospitals, the community, and livestock. Typing of SCCmec by PCR techniques has, because of its heterogeneity, been challenging, and whole-genome sequencing has only partially solved this since no good bioinformatic tools have been available. In this article, we describe the development of a new bioinformatic tool, SCCmecFinder, that includes most of the needs for infection control professionals and researchers regarding the interpretation of SCCmec elements. The software detects all of the SCCmec elements accepted by the International Working Group on the Classification of Staphylococcal Cassette Chromosome Elements, and users will be prompted if diverging and potential new elements are uploaded. Furthermore, SCCmecFinder will be curated and updated as new elements are found and it is easy to use and freely accessible.

High throughput resistance profiling of Plasmodium falciparum infections based on custom dual indexing and Illumina next generation sequencing-technology.

Genetic polymorphisms in P. falciparum can be used to indicate the parasite's susceptibility to antimalarial drugs as well as its geographical origin. Both of these factors are key to monitoring development and spread of antimalarial drug resistance. In this study, we combine multiplex PCR, custom designed dual indexing and Miseq sequencing for high throughput SNP-profiling of 457 malaria infections from Guinea-Bissau, at the cost of 10 USD per sample. By amplifying and sequencing 15 genetic fragments, we cover 20 resistance-conferring SNPs occurring in pfcrt, pfmdr1, pfdhfr, pfdhps, as well as the entire length of pfK13, and the mitochondrial barcode for parasite origin. SNPs of interest were sequenced with an average depth of 2,043 reads, and bases were called for the various SNP-positions with a p-value below 0.05, for 89.8-100% of samples. The SNP data indicates that artemisinin resistance-conferring SNPs in pfK13 are absent from the studied area of Guinea-Bissau, while the pfmdr1 86 N allele is found at a high prevalence. The mitochondrial barcodes are unanimous and accommodate a West African origin of the parasites. With this method, very reliable high throughput surveillance of antimalarial drug resistance becomes more affordable than ever before.

A sampling and metagenomic sequencing-based methodology for monitoring antimicrobial resistance in swine herds.

OBJECTIVES: Reliable methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs are essential to understand the trends, transmission and importance of agricultural resistance. Quantification of AMR is mostly done using culture-based techniques, but metagenomic read mapping shows promise for quantitative resistance monitoring. METHODS: We evaluated the ability of: (i) MIC determination for Escherichia coli; (ii) cfu counting of E. coli; (iii) cfu counting of aerobic bacteria; and (iv) metagenomic shotgun sequencing to predict expected tetracycline resistance based on known antimicrobial consumption in 10 Danish integrated slaughter pig herds. In addition, we evaluated whether fresh or manure floor samples constitute suitable proxies for intestinal sampling, using cfu counting, qPCR and metagenomic shotgun sequencing. RESULTS: Metagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on antimicrobial consumption. Our metagenomic approach had sufficient resolution to detect antimicrobial-induced changes to individual resistance gene abundances. Pen floor manure samples were found to represent rectal samples well when analysed using metagenomics, as they contain the same DNA with the exception of a few contaminating taxa that proliferate in the extraintestinal environment. CONCLUSIONS: We present a workflow, from sampling to interpretation, showing how resistance monitoring can be carried out in swine herds using a metagenomic approach. We propose metagenomic sequencing should be part of routine livestock resistance monitoring programmes and potentially of integrated One Health monitoring in all reservoirs.

Bacterial whole genome-based phylogeny: construction of a new benchmarking dataset and assessment of some existing methods.

BACKGROUND: Whole genome sequencing (WGS) is increasingly used in diagnostics and surveillance of infectious diseases. A major application for WGS is to use the data for identifying outbreak clusters, and there is therefore a need for methods that can accurately and efficiently infer phylogenies from sequencing reads. In the present study we describe a new dataset that we have created for the purpose of benchmarking such WGS-based methods for epidemiological data, and also present an analysis where we use the data to compare the performance of some current methods. RESULTS: Our aim was to create a benchmark data set that mimics sequencing data of the sort that might be collected during an outbreak of an infectious disease. This was achieved by letting an E. coli hypermutator strain grow in the lab for 8 consecutive days, each day splitting the culture in two while also collecting samples for sequencing. The result is a data set consisting of 101 whole genome sequences with known phylogenetic relationship. Among the sequenced samples 51 correspond to internal nodes in the phylogeny because they are ancestral, while the remaining 50 correspond to leaves. We also used the newly created data set to compare three different online available methods that infer phylogenies from whole-genome sequencing reads: NDtree, CSI Phylogeny and REALPHY. One complication when comparing the output of these methods with the known phylogeny is that phylogenetic methods typically build trees where all observed sequences are placed as leafs, even though some of them are in fact ancestral. We therefore devised a method for post processing the inferred trees by collapsing short branches (thus relocating some leafs to internal nodes), and also present two new measures of tree similarity that takes into account the identity of both internal and leaf nodes. CONCLUSIONS: Based on this analysis we find that, among the investigated methods, CSI Phylogeny had the best performance, correctly identifying 73% of all branches in the tree and 71% of all clades. We have made all data from this experiment (raw sequencing reads, consensus whole-genome sequences, as well as descriptions of the known phylogeny in a variety of formats) publicly available, with the hope that other groups may find this data useful for benchmarking and exploring the performance of epidemiological methods. All data is freely available at: https://cge.cbs.dtu.dk/services/evolution_data.php .

A Bacterial Analysis Platform: An Integrated System for Analysing Bacterial Whole Genome Sequencing Data for Clinical Diagnostics and Surveillance.

Recent advances in whole genome sequencing have made the technology available for routine use in microbiological laboratories. However, a major obstacle for using this technology is the availability of simple and automatic bioinformatics tools. Based on previously published and already available web-based tools we developed a single pipeline for batch uploading of whole genome sequencing data from multiple bacterial isolates. The pipeline will automatically identify the bacterial species and, if applicable, assemble the genome, identify the multilocus sequence type, plasmids, virulence genes and antimicrobial resistance genes. A short printable report for each sample will be provided and an Excel spreadsheet containing all the metadata and a summary of the results for all submitted samples can be downloaded. The pipeline was benchmarked using datasets previously used to test the individual services. The reported results enable a rapid overview of the major results, and comparing that to the previously found results showed that the platform is reliable and able to correctly predict the species and find most of the expected genes automatically. In conclusion, a combined bioinformatics platform was developed and made publicly available, providing easy-to-use automated analysis of bacterial whole genome sequencing data. The platform may be of immediate relevance as a guide for investigators using whole genome sequencing for clinical diagnostics and surveillance. The platform is freely available at: https://cge.cbs.dtu.dk/services/CGEpipeline-1.1 and it is the intention that it will continue to be expanded with new features as these become available.

Fatal Septicemia Linked to Transmission of MRSA Clonal Complex 398 in Hospital and Nursing Home, Denmark.

We describe 2 fatal cases of methicillin-resistant Staphylococcus aureus (MRSA) clonal complex 398 septicemia in persons who had no contact with livestock. Whole-genome sequencing of the isolated MRSA strains strongly suggest that both were of animal origin and that the patients had been infected through 2 independent person-to-person transmission chains.

Consolidating and Exploring Antibiotic Resistance Gene Data Resources.

The unrestricted use of antibiotics has resulted in rapid acquisition of antibiotic resistance (AR) and spread of multidrug-resistant (MDR) bacterial pathogens. With the advent of next-generation sequencing technologies and their application in understanding MDR pathogen dynamics, it has become imperative to unify AR gene data resources for easy accessibility for researchers. However, due to the absence of a centralized platform for AR gene resources, availability, consistency, and accuracy of information vary considerably across different databases. In this article, we explore existing AR gene data resources in order to make them more visible to the clinical microbiology community, to identify their limitations, and to propose potential solutions.

Comparative Evaluation of the Antimicrobial Activity of Different Antimicrobial Peptides against a Range of Pathogenic Bacteria.

ANALYSIS OF A SELECTED SET OF ANTIMICROBIAL PEPTIDES: The rapid emergence of resistance to classical antibiotics has increased the interest in novel antimicrobial compounds. Antimicrobial peptides (AMPs) represent an attractive alternative to classical antibiotics and a number of different studies have reported antimicrobial activity data of various AMPs, but there is only limited comparative data available. The mode of action for many AMPs is largely unknown even though several models have suggested that the lipopolysaccharides (LPS) play a crucial role in the attraction and attachment of the AMP to the bacterial membrane in Gram-negative bacteria. We compared the potency of Cap18, Cap11, Cap11-1-18m2, Cecropin P1, Cecropin B, Bac2A, Bac2A-NH2, Sub5-NH2, Indolicidin, Melittin, Myxinidin, Myxinidin-NH2, Pyrrhocoricin, Apidaecin and Metalnikowin I towards Staphylococcus aureus, Enterococcus faecalis, Pseudomonas aeruginosa, Escherichia coli, Aeromonas salmonicida, Listeria monocytogenes, Campylobacter jejuni, Flavobacterium psychrophilum, Salmonella typhimurium and Yersinia ruckeri by minimal inhibitory concentration (MIC) determinations. Additional characteristics such as cytotoxicity, thermo and protease stability were measured and compared among the different peptides. Further, the antimicrobial activity of a selection of cationic AMPs was investigated in various E. coli LPS mutants. CAP18 SHOWS A HIGH BROAD SPECTRUM ANTIMICROBIAL ACTIVITY: Of all the tested AMPs, Cap18 showed the most efficient antimicrobial activity, in particular against Gram-negative bacteria. In addition, Cap18 is highly thermostable and showed no cytotoxic effect in a hemolytic assay, measured at the concentration used. However, Cap18 is, as most of the tested AMPs, sensitive to proteolytic digestion in vitro. Thus, Cap18 is an excellent candidate for further development into practical use; however, modifications that should reduce the protease sensitivity would be needed. In addition, our findings from analyzing LPS mutant strains suggest that the core oligosaccharide of the LPS molecule is not essential for the antimicrobial activity of cationic AMPs, but in fact has a protective role against AMPs.

Biocide Susceptibility of Staphylococcus aureus CC398 and CC30 Isolates from Pigs and Identification of the Biocide Resistance Genes, qacG and qacC.

OBJECTIVES: Methicillin-resistant Staphylococcus aureus (MRSA), in particular clonal complex (CC) 398, is increasingly found in livestock. Recently, MRSA CC30 was identified in Danish pigs. We determined the susceptibility of porcine S. aureus isolates of CC398 and CC30 to disinfectants used in pig farming (benzalkonium chloride, hydrogen peroxide, formaldehyde, sodium hypochlorite, and caustic soda). Furthermore, efflux pump activity, antimicrobial resistance profiles, hemolysis properties, and the presence of toxic shock syndrome toxin-1 (TSST-1) and Panton-Valentine Leukocidin (PVL)-encoding virulence factors were investigated. METHODS: Susceptibilities to biocides and antimicrobial agents of 79 porcine S. aureus isolates were determined by the microdilution method. Isolates comprised 21 methicillin-sensitive S. aureus (MSSA) and 40 MRSA isolates belonging to CC398 and 13 MSSA and 5 MRSA isolates belonging to CC30. The presence of quaternary ammonium compound (QAC) resistance efflux pumps was analyzed using an ethidium bromide accumulation assay. The presence of qac resistance genes in active efflux pump positive isolates was determined by whole-genome sequencing data. All isolates were screened for lukPV and tst genes with PCR, and hemolytic activities were determined using an agar plate assay. RESULTS: S. aureus isolates did not show reduced susceptibility to the biocides tested. However, the QAC resistance gene, qacG, was detected in three MRSA CC30 isolates and the qacC in one MRSA CC30 isolate. CC30 isolates were generally more susceptible to non-beta-lactam antibiotics than CC398. Isolates generally had low hemolytic activity and none encoded PVL or TSST-1. CONCLUSION: The presence of qac genes in European porcine S. aureus isolates and in livestock-associated MRSA CC30 is for the first time described in this study. This finding is concerning as it ultimately may compromise disinfection with QACs and thereby contribute to the selection and spread of MRSA CC30.