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Wiedmann, M.

Publications and source records attributed to Wiedmann, M..

At least 19 recordsLinked to original sources

Motile and non-motile Listeria species adopt distinct genomic and ecological strategies to achieve broad geographic ranges in soil

Broad geographic ranges indicate high ecological versatility and are generally associated with low extinction risk. Motility is not only a physiological feature, but also a core ecological trait for bacteria. However, the genomic foundations underlying the broad geographic ranges of motile and non-motile bacteria remain poorly understood. To address this, we analyzed 141 and 90 genomes of Listeria welshimeri and L. booriae, systematically screened from 1,004 soil samples across the United States, representing widespread motile and non-motile species, respectively. We show that L. welshimeri exhibits restricted phylogeographic structure and a weak distance-decay relationship, suggesting minimal geographic barriers to dispersal. Its high dispersal capacity likely stems from enhanced motility and effective host colonization, evidenced by strong positive selection on flagellar genes and the close relatedness to isolates from wild birds. In contrast, L. booriae displays a regionally endemic distribution and limited dispersal. With a large, open pangenome, L. booriae appears strongly adapted to local environments. This is evidenced by pronounced positive selection on genes involved in inorganic ion, amino acid, and coenzyme transport and metabolism, as well as strong associations with abiotic factors, particularly climate, and accompanying bacterial consortia. In summary, to establish widespread distributions, L. welshimeri tends to rely on movement and colonization of wildlife hosts to facilitate long-distance dispersal, while L. booriae leverages genomic plasticity and metabolic versatility that enable adaptation to diverse environmental conditions. These findings highlight the distinct genomic foundations and ecological strategies that motile and non-motile bacteria use to achieve broad geographic ranges in the environment.

ecology↗

Single nucleotide polymorphisms associated with cytotoxicity of Bacillus cereus group strains in Caco-2 cells

Bacillus cereus sensu lato (s.l.) encompasses strains with diverse impacts, ranging from foodborne illness and anthrax to beneficial applications in agriculture and industry. While the risk of anthrax and emetic intoxication can be reliably predicted by the presence of specific virulence genes, predicting diarrheal foodborne illness risk based solely on enterotoxin gene presence has proven unreliable. In this study, we evaluated cytotoxicity against Caco-2 human gut cells using a diverse collection of B. cereus s.l. isolates representing all eight panC phylogenetic groups and conducted genomic analyses to identify predictive markers of cytotoxicity. Isolates from panC groups I, IV, and V exhibited significantly higher cytotoxicity compared to other groups, although individual isolates from other panC groups have also been linked to illness. Logistic and random forest regression models revealed that while the presence of enterotoxin genes was a sensitive indicator of cytotoxicity, it lacked specificity. Logistic regression analysis identified 21 nonsynonymous single nucleotide polymorphisms (SNPs) within enterotoxin (Nhe and Hbl) gene sequences that were more effective predictors of cytotoxicity, providing higher specificity with comparable sensitivity. These SNPs achieved accuracy and precision values exceeding 0.7. Random forest models highlighted the importance of panC group, enterotoxin gene SNPs, and the presence of the full hbl operon as key predictors of cytotoxicity. The strong sensitivity, specificity, and biological relevance of these SNPs position them as promising markers for improving strain-based risk assessment of B. cereus s.l. IMPORTANCEEnterotoxin genes have been associated with B. cereus sensu lato (s.l.) diarrheal foodborne illness; however, their mere presence in a genome is an unreliable predictor of an isolates cytotoxicity towards human gut epithelial cells. To improve food safety risk assessment, more specific markers of cytotoxicity are required. In this study, we identified nonsynonymous SNPs within the coding sequences of the enterotoxins Nhe and Hbl. These SNPs offer potential targets for rapid molecular tests to identify B. cereus s.l. isolates with an elevated food safety risk due to their capacity to inflict cytotoxic damage on human gut epithelial cells. Implementation of such markers upon validation could improve consumer safety while reducing food waste.

microbiology↗

Integration of mathematical modeling and economics approaches to evaluate strategies for control of Salmonella Dublin in a heifer-raising operation

Salmonella Dublin infections in heifer-raising operations (HROs) cause animal health and economic losses for these operations and represent a pathogen source for dairy farms obtaining replacement heifers from HROs. To improve control of S. Dublin, we (i) developed a mathematical model of S. Dublin transmission on a HRO, (ii) evaluated the vaccine effectiveness and cleaning improvements for controlling the infection, and (iii) evaluated the influence of infection and control strategies on the HROs operating income. We developed a modified Susceptible-Infected-Recovered-Susceptible model of S. Dublin spread in a batch-stocking HRO post-introduction of an index case, with stochasticity introduced through Monte Carlo simulations. Epidemiological outcomes (S. Dublin-induced deaths and abortions during raising and S. Dublin carriers and asymptomatic infections among raised replacement heifers) and operating income per 100-head raised on a HRO over a 2-year simulation were compared between control scenarios. We validated our model against S. Dublin infection data in cattle. Partial rank correlation coefficient and classification trees were used to determine parameter influence on model outcomes. Our model predicts a median of 37 carriers and 92 asymptomatic infections among raised replacement heifers out of 2,330 heifers that departed the operation by the end of the 2-year simulation period, highlighting the critical role of HROs in spreading S. Dublin. Increasing barn floor cleaning frequency (to a maximum of 12x per day) meaningfully reduced the S. Dublin epidemiological outcomes and improved the HROs operating income. Depending on the cost of cleaning, the median operating income increased between 1.2% to 10.6% in the first year when cleaning 12x per day compared to baseline (cleaning 1x per week). In most cost scenarios, predictions do not support the use of vaccination, even when paired with stringent cleaning measures. The developed model is expected to aid efforts to control S. Dublin in HROs.

ecology↗

Lipid A phosphoethanolamine transferase-mediated site-selective modifications show association with colistin resistance phenotypes and fitness

Genes encoding lipid A modifying phosphoethanolamine transferases (PETs) are genetically diverse and can confer resistance to colistin and antimicrobial peptides. To better understand the functional diversity of PETs, we characterized three canonical mobile colistin resistance (mcr) alleles (mcr-1, -3, -9), one intrinsic pet (eptA), and two mcr-like genes (petB, petC). Using an isogenic expression system, we show that mcr-1 and mcr-3 are phenotypically similar by conferring colistin resistance with lower fitness costs. mcr-9, which is phylogenetically closely related to mcr-3, and eptA only provide fitness advantages in the presence of sub-inhibitory concentrations of colistin and significantly reduce fitness in media only. PET-B and PET-C were phenotypically distinct from bonafide PETs; neither conferred colistin resistance or caused considerable fitness cost in Escherichia coli. Strikingly, we found for the first time that different PETs selectively modify different phosphates of lipid A - MCR-1, MCR-3, and PET-C selectively modify the 4-phosphate, while MCR-9 and EptA modify the 1-phosphate. 4-phosphate modifications facilitated by MCR-1 and -3 are associated with high levels of colistin resistance and low toxicity. Our results suggest that PETs have a wide phenotypic diversity and that high level colistin resistance is associated with specific lipid A modification patterns that has been largely unexplored thus far. IMPORTANCERising levels of resistance to increasing numbers of antimicrobials has led to the revival of last resort antibiotic colistin. Unfortunately, resistance to colistin is also spreading in the form of mcr genes, making it essential to (i) improve identification of resistant bacteria to allow clinicians to prescribe effective drug regimens and (ii) develop new combination therapies effective at targeting resistant bacteria. Our results demonstrate that PETs, including MCR variants, are site-selective in E. coli, with site-selectivity correlating with the level of resistance and fitness costs conferred by certain PETs. Site-selectivity associated with a given PET may not only help predict colistin resistance phenotypes, but may also provide an avenue to (i) improved drug regimens and (ii) development of new combination therapies to better combat colistin resistant bacteria.

microbiology↗

A machine learning approach reveals that spore levels in organic bulk tank milk are dependent on farm characteristics and meteorological factors

Bacterial spores in raw milk can lead to quality issues in milk and milk derived products. Since these spores originate from farm environments, it is important to understand contributions of farm-level factors to spore levels in raw milk. Identifying highly influential factors will guide interventions to control the transmission of spores from farm environments into bulk tank raw milk and therefore minimize spoilage in the finished products. The objective of this study was to investigate the impact of farm management practices and meteorological factors on levels of different spore types in organic raw milk by leveraging machine learning models. In this study, raw milk from certified organic dairy farms (n = 102) located across 11 states was collected 6 times over a year and tested for standard plate count, psychrotolerant spore count, mesophilic spore count, thermophilic spore count, and butyric acid bacteria. At each sampling date, a survey was collected from each farm to obtain structured data about farm management practices. Meteorological factors related to temperature, precipitation, solar radiation, and wind were obtained on the date of sampling as well as 1, 2, and 3 days prior to the date of sampling from an open-source website. The dataset was stratified separately based on the use of a parlor for milking, number of years since organic certification, and whether the lactating herd was exposed to pasture time into sub-datasets to address the potential confounders. Using the entire datasets and 6 sub-datasets respectively, we constructed random forest regression models to predict log10 mesophilic spore count, log10 thermophilic spore count, and log10 butyric acid bacteria most probable number as well as a random forest classification model to classify the presence of psychrotolerant spores in each raw milk sample. The summary statistics showed that spore levels vary considerably between certified organic farms but were only slightly higher than spore levels previously reported from conventional dairy farms. The variable importance plots from the random forest models suggest that herd size, certification year, employee-related variables (e.g., number of people milking cows per week), clipping and flaming udders, stocking density, and principal component representing air temperatures are among the top variables influencing the spore levels in organic raw milk, despite the limitation in the model performance (the highest performance for regression and classification is R2 of 0.36 for predicting TSC for farms with a parlor and accuracy of 0.73 for classifying positive PSC for farms without a parlor, respectively). The relatively small effects of top variables as demonstrated by the partial dependence plots suggest that an individualized approach that synergistically considers multiple farm and environmental factors is needed to enable a risk-based approach for managing spore levels. While at the current stage, these models were insufficiently accurate to be used as predictive tools, incorporating novel data streams such as video surveillance and daily farm observations with computer vision and natural language processing, respectively, has the potential to enhance the performance of the model as a real-time monitoring tool for spores as an indicator of milk microbiological quality.

microbiology↗

Risk assessment predicts most of the salmonellosis risk in raw chicken parts is concentrated in those few products with high-levels of high-virulent serotypes of Salmonella

Salmonella prevalence has reduced in U.S. raw poultry products since adopting prevalence-based Salmonella performance standards, but human illnesses did not reduce proportionally. We used Quantitative Microbial Risk Assessment to evaluate public health risks of raw chicken parts contaminated with different levels of all Salmonella and specific high- and low-virulent serotypes. Lognormal Salmonella level distributions were fitted using data from 2012 USDA-FSIS Baseline Survey and 2023 USDA-FSIS HACCP verification sampling data. Three different dose-response (DR) models were used: Single DR for all serotypes, reduced virulence for Kentucky, multiple serotype- specific DR models. All scenarios found risk concentrated in the few products with high Salmonella levels. Using a single DR model with Baseline data (=-3.19, {sigma}=1.29), 68% and 37% of illnesses were attributed to the 0.7% and 0.06% of products > 1 and 10 CFU/g Salmonella, respectively. More recent HACCP data (=-4.85, {sigma}=2.44) showed that 99.9% and 99.6% of illnesses were attributed to the 2.3% and 0.8% of products > 1 and 10 CFU/g Salmonella, respectively. Scenarios with serotype-specific DR models showed more concentrated risk at higher levels. Baseline data showed 91.5% and 63.7% and HACCP data showed >99.9% and 99.9% of illnesses were attributed to products > 1 and 10 CFU/g Salmonella, respectively. Regarding serotypes, 0.003% and 0.3% of illnesses were attributed to the 0.2% and 0.7% of products with > 1 CFU/g of Kentucky, respectively, while 69% and 78.7% of illnesses were attributed to the 0.3% and 1.2% of products > 1 CFU/g containing either Enteritidis, Infantis, or Typhimurium using Baseline or HACCP input data, respectively. These results suggest public health risk in chicken parts is concentrated in the few finished products with high-levels and specifically high- levels of high-virulent serotypes. Low-virulent serotypes, such as Kentucky, are predicted to contribute to extremely few human cases.

microbiology↗

Exposure assessment suggests some cytotoxic Bacillus cereus group genotypes can grow over 3 logs in HTST milk throughout the shelf life at temperature abuse conditions

Cytotoxic Bacillus cereus group strains are common causes of foodborne illness including diarrhea. However, our ability to assess food safety risks associated with the exposure to cytotoxic B. cereus group strains via contaminated food is limited due to the lack of predictive tools. In this study, we experimentally quantified the growth of 17 cytotoxic B. cereus group strains, representing six phylogenetic groups, in skim milk broth and used the growth data to develop an exposure assessment model. While none of the tested strains showed detectable growth in HTST milk at 4 or 6{degrees}C, 15 of the 17 strains showed growth at 10{degrees}C, 1 of the 17 strains showed growth at 8{degrees}C, and all strains grew at [≥]14{degrees}C. Growth data for 16 strains allowed us to generate linear secondary growth models, which were then used to develop the exposure assessment model. We simulated a five-stage supply chain with up to 35 consumer storage days, as that was the timing when distinguishable variations in percent milk containers over 105 CFU/m with different B. cereus genotypes were observed. When the initial contamination level of the HTST milk is set at an average of 100 CFU/mL, the model predicts that, on consumer home storage day 21 and 35, 2.81{+/-}0.66 and 4.13{+/-}2.53 % (mean {+/-} standard deviation) of the milk containers would exceed B. cereus group concentrations of 105 CFU/mL; these data represent the average across all strains. Sensitivity analysis showed that variation in the input parameter Q0, the initial physiological state of cells, has the largest effect on models prediction for 1 of 4 group II isolates, 1 of 6 group IV isolates and both group V isolates, suggesting the need to better characterize the growth parameters of these isolates. What-if scenario analysis showed that increased mean and variability in storage temperature at the consumers home both have substantial influence on final predicted B. cereus group concentration in milk containers. This model introduces an initial tool designed to facilitate risk-based food safety decision making for products that are contaminated with low B. cereus group levels.

microbiology↗

Intensive environmental sampling and whole genome sequence-based characterization of Listeria in small and medium sized dairy plants reveal opportunities for simplified and size-appropriate environmental monitoring strategies

Small and medium sized dairy processing plants (SMDPs) may face unique challenges with respect to controlling Listeria in their processing environments, e.g., due to limited resources. The aim of this study was to implement and evaluate environmental monitoring programs (EMPs) for Listeria control in eight SMDPs in a [~]1-year longitudinal study; this included a comparison of pre-operation (i.e., after cleaning and sanitation and prior to production) and mid-operation (i.e., at least 4 h into production) sampling strategies. Among 2,072 environmental sponge samples collected across all plants, 272 (13%) were positive for Listeria. Listeria prevalence among pre- and mid-operation samples (15 and 17%, respectively), was not significantly different. Whole genome sequencing (WGS) performed on select isolates to characterize Listeria persistence patterns revealed repeated isolation of closely related Listeria isolates (i.e., [≤]20 high quality single nucleotide polymorphism [hqSNP] differences) in 5/8 plants over >6 months, suggesting Listeria persistence and/or re-introduction was relatively common among the SMDPs evaluated here. WGS furthermore showed that for 41 sites where samples collected pre- and mid- operation were positive for Listeria, Listeria isolates obtained were highly related (i.e., [≤]10 hqSNP differences), suggesting that pre-operation sampling alone may be sufficient and more effective for detecting sites of Listeria persistence. Importantly, our data also showed that only 1/8 plants showed a significant decrease in Listeria prevalence over 1 year, indicating continued challenges with Listeria control in at least some SMDPs. We conclude that options for simplified Listeria EMP programs (e.g., with a focus on pre-operation sampling, which allows for more rapid identification of likely persistence sites) may be valuable for improved Listeria control in SMDPs.

microbiology↗

Escherichia coli B-strains are intrinsically resistant to colistin and not suitable for characterization and identification of mcr genes

Antimicrobial resistance is an increasing threat to human and animal health. Due to the rise of multi- and extreme drug resistance, last resort antibiotics, such as colistin, are extremely important in human medicine. While the distribution of colistin resistance genes can be tracked through sequencing methods, phenotypic characterization of putative antimicrobial resistance (AMR) genes is still important to confirm the phenotype conferred by different genes. While heterologous expression of AMR genes (e.g., in E. coli) is a common approach, so far, no standard method for heterologous expression and characterization of mcr genes exists. E. coli B-strains, designed for optimum protein expression, are frequently utilized. Here we report that four E. coli B-strains are intrinsically resistant to colistin (MIC 8 - 16 g/mL). Additionally, the three tested B-strains that encode T7 RNA show growth defects when transformed with empty or gene-expressing pET17b plasmids and grown in the presence of IPTG; K-12 or B-strains without T7 RNA polymerase do not show these growth defects. The E. coli Shuffle T7 express strain carrying empty pET17b also showed a heteroresistance phenotype when exposed to colistin in the presence of IPTG. These phenotypes could explain why B-strains were erroneously reported as colistin susceptible. Analysis of existing genome data identified one nonsynonymous change in each pmrA and pmrB in all four E. coli B-strains; the E121K change in PmrB has previously been linked to intrinsic colistin resistance. We conclude that E. coli B-strains are not appropriate heterologous expression hosts for identification and characterization of mcr genes.

microbiology↗

More than mcr: Canonical Plasmid- and Transposon-Encoded Mobilized Colistin Resistance (mcr) Genes Represent a Subset of Phosphoethanolamine Transferases

Mobilized colistin resistance genes (mcr) may confer resistance to colistin, a last-resort, critically important antimicrobial for human health. mcr can often be transmitted horizontally (e.g., via mobile genetic elements); however, mcr encode phosphoethanolamine transferases (PET) closely related to chromosomally encoded, intrinsic lipid modification enzymes (e.g., EptA, EptB, CptA). To explore the genetic diversity of mcr within the context of intrinsic lipid modification PET, we identified 9,836 non-redundant protein accession numbers associated with mcr-like genes, representing a total of 69,814 mcr-like genes present across 256 bacterial genera. We subsequently identified 125 unique, putative novel mcr-like genes encoded on the same contig as a plasmid replicon and other antimicrobial resistance genes. Sequence similarity and a maximum likelihood phylogeny of mcr, putative novel mcr-like genes, and intrinsic lipid modification PET-encoding genes indicated that sequence similarity is insufficient to discriminate between genes involved in colistin resistance and genes encoding intrinsic lipid modification PET. A mixed-effect model of evolution (MEME) indicated that site- and branch-specific diversifying positive selection might have played a role in the evolution of subvariants within the mcr-2 and mcr-9 families. MEME suggested that positive selection played a role in the diversification of several residues in structurally important regions, including (i) a bridging region that connects the membrane-bound and catalytic periplasmic domains, and (ii) a periplasmic loop juxtaposing the substrate entry tunnel. These residues were found to be differentially conserved in different mcr families and thus may play a role in mcr subvariant phenotypic diversity. Moreover, we found that eptA and mcr are localized within different genomic contexts. Canonical eptA are typically chromosomally encoded in an operon with a two-component regulatory system or adjacent to a TetR-type regulator. In contrast, mcr are encoded as single-gene operons or adjacent to pap2 and dgkA, which encode a PAP2 family lipid A phosphatase and diacylglycerol kinase, respectively. Our data suggest that eptA can give rise to "colistin resistance genes" through various mechanisms, including selection and diversification of the genomic context, regulatory pathways, and mobilization. These mechanisms likely altered gene expression levels and enzyme activity, allowing bona fide eptA to evolve to function in colistin resistance.

microbiology↗

Structural equation models suggest that on-farm non-crop vegetation removal is not associated with improved food safety outcomes but is linked to impaired water quality

While growers have reported pressures to minimize wildlife intrusion into produce fields through non-crop vegetation (NCV) removal, NCV provides key ecosystem services. To model food safety and environmental tradeoffs associated with NCV removal, published and publicly available food safety and water quality data from the Northeastern USA were obtained. Because data on NCV removal are not widely available, forest-wetland cover was used as a proxy, consistent with previous studies. Structural equation models (SEMs) were used to quantify the effect of forest-wetland cover on (i) food safety outcomes (e.g., detecting pathogens in soil) and (ii) water quality (e.g., nutrient levels). Based on the SEMs, NCV was not associated with or had a protective effect on food safety outcomes (more NCV was associated with a reduced likelihood of pathogen detection). The probabilities of detecting Listeria spp. in soil (Effect Estimate [EE]=-0.17; P=0.005) and enterohemorrhagic Escherichia coli in stream samples (EE=-0.27; P<0.001) were negatively associated with the amount of NCV surrounding the sampling site. Higher amounts of NCV were also associated with lower nutrient, salinity, and sediment levels and higher dissolved oxygen levels. Total phosphorous levels were negatively associated with the amount of NCV in the upstream watershed (EE=-0.27; P<0.001). Similar negative associations (P<0.05) were observed for other physicochemical parameters, such as nitrate (EE=-0.38). Our findings suggest that NCV should not be considered an inherent produce safety risk or result in farm audit demerits. This study also provides a framework for evaluating environmental trade-offs associated with using specific preharvest food safety strategies. ImportanceCurrently, on-farm food safety decisions are typically made independently of conservation considerations, often with detrimental impacts on agroecosystems. Co-managing agricultural environments to simultaneously meet conservation and food safety aims is complicated because farms are closely linked to surrounding environments, and management decisions can have unexpected environmental, economic, and food safety consequences. Thus, there is a need for research on the conservation and food safety trade-offs associated with implementing specific preharvest food safety practices. Understanding these trade-offs is critical for developing adaptive co-management strategies and ensuring the short and long-term safety, sustainability, and profitability of agricultural systems. This study quantifies tradeoffs and synergies between food safety and environmental aims, and outlines a framework for modeling trade-offs and synergies between management aims that can be used to support future co-management research.

ecology↗

Detecting anomalous content in dairy with whole metagenome sequencing

The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. These methods could be used to identify ingredients that deviate from their typical microbial composition, which could indicate food fraud or safety issues. The objective of this study was to assess the feasibility of using shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. Contrastive PCA, cluster-based methods, and explainable AI were evaluated for the detection of two anomalous sample classes using longitudinal metagenomic profiling of fluid milk compared to baseline samples collected under comparable circumstances. Traditional methods (alpha and beta diversity, clustering-based contrastive PCA, MDS, and dendrograms) failed to differentiate anomalous sample classes; however, explainable AI was able to classify anomalous vs. baseline samples and indicate microbial drivers in association with antibiotic use. We validated the potential for explainable AI to classify different milk sources using larger publicly available fluid milk 16s rDNA sequencing datasets and demonstrated that explainable AI is able to differentiate between milk storage methods, processing stage, and season. Our results indicate the application of artificial intelligence continues to hold promise in the realm of microbiome data analysis and could present further opportunities for downstream analytic automation to aid in food safety and quality. IMPORTANCEWe evaluated the feasibility of using untargeted metagenomic se-quencing of raw milk for detecting anomalous food ingredient content with artificial intelligence methods in a study specifically designed to test this hypothesis. We also show through analysis of publicly available fluid milk microbial data that our artificial intelligence approach is able to successfully predict milk in different stages of process-ing. The approach could potentially be applied in the food industry for safety and quality control.

microbiology↗

Phage genome cleavage enables resuscitation from Cas13-induced bacterial dormancy

CRISPR-Cas systems provide their prokaryotic hosts with sequence-specific immunity to foreign genetic elements, including bacteriophages and plasmids. While most interfere with phage infection though cleavage of viral DNA, type VI CRISPR systems use the RNA-guided nuclease Cas13 to recognize mRNA targets. Upon engaging with target RNA, Cas13 cleaves both phage and host transcripts nonspecifically, leading to a state of cell dormancy that is incompatible with phage propagation. However, whether and how infected cells recover from dormancy is not clear. Here we show that type VI CRISPR systems frequently co-occur with DNA-cleaving restriction modification (RM) systems. Using genetics and microscopy, we show that Cas13 and RM systems synergize in anti-phage defense in the natural type VI CRISPR host Listeria seeligeri. Cleavage of the phage genome by RM removes the source of phage transcripts, enabling cells to recover from Cas13-induced cellular dormancy. We find that Cas13 and RM systems operating simultaneously eliminate phage DNA and neutralize infection more effectively than either defense alone. Thus, cells harboring both defense systems exhibit robust anti-phage immunity and survive infection. Our work therefore reveals that type VI CRISPR immunity is cell-autonomous and non-abortive, if paired with RM or similar DNA-targeting defenses. The ability of an abortive response to be resolved by the actions of another anti-phage defense has implications for the roles of diverse host-directed immune systems in bacteria.

microbiology↗

A multidrug-resistant Salmonella enterica serotype Typhimurium DT104 lineage circulating among humans and cattle in the United States lost the ability to produce pertussis-like toxin ArtAB in close temporal proximity to the global DT104 epidemic

Salmonella enterica subspecies enterica serotype Typhimurium definitive type 104 (DT104) can infect both humans and animals and is often multidrug-resistant (MDR). Previous studies have indicated that, unlike most S. Typhimurium, the overwhelming majority of DT104 strains produce pertussis-like toxin ArtAB via prophage-encoded genes artAB. However, DT104 that lack artAB have been described on occasion. Here, we identify a MDR DT104 complex lineage circulating among humans and cattle in the United States, which lacks artAB (i.e., the "U.S. artAB-negative major clade"; n = 42 genomes). Unlike most other bovine- and human-associated DT104 complex strains from the U.S. (n = 230 total genomes), which harbor artAB on prophage Gifsy-1 (n = 177), members of the U.S. artAB-negative major clade lack Gifsy-1, as well as anti-inflammatory effector gogB. The U.S. artAB-negative major clade encompasses human- and cattle-associated strains isolated from [&ge;]11 U.S. states over a twenty-year period. The clade was predicted to have lost artAB, Gifsy-1, and gogB circa 1985-1987 (95% highest posterior density interval 1979.0-1992.1). When compared to DT104 genomes from other world regions (n = 752 total genomes), several additional, sporadic artAB, Gifsy-1, and/or gogB loss events among clades encompassing [&le;]5 genomes were observed. Using phenotypic assays that simulate conditions encountered during human and/or bovine digestion, members of the U.S. artAB-negative major clade did not differ from closely related Gifsy-1/artAB/gogB-harboring U.S. DT104 complex strains (ANOVA raw P-value > 0.05); thus, future research is needed to elucidate the roles that artAB, gogB, and Gifsy-1 play in DT104 virulence in humans and animals. Impact StatementMulti-drug resistant (MDR) Salmonella enterica serotype Typhimurium definitive type 104 (DT104) was responsible for a global epidemic among humans and animals throughout the 1990s and continues to circulate worldwide. Previous studies have indicated that the vast majority of DT104 produce pertussis-like toxin ArtAB via prophage-encoded artAB. Here, we identify a DT104 complex lineage that has been circulating among cattle and humans across [&ge;]11 U.S. states for over twenty years, which lacks the ability to produce ArtAB (i.e., the "U.S. artAB-negative major clade"). The common ancestor of all U.S. artAB-negative major clade members lost the ability to produce ArtAB in the 1980s; however, the reason for this loss-of-function event within this well-established pathogen remains unclear. The role that ArtAB plays in DT104 virulence remains elusive, and phenotypic assays conducted here indicate that members of the U.S. artAB-negative major clade do not have a significant advantage or disadvantage relative to closely related, Gifsy-1/artAB/gogB-harboring U.S. DT104 complex strains when exposed to stressors encountered during human and/or bovine digestion in vitro. However, ArtAB heterogeneity within the DT104 complex suggests clade-specific selection for or against maintenance of ArtAB. Thus, future studies querying the virulence characteristics of the U.S. artAB-negative major clade are needed. Data SummarySupplementary Data is available under DOI 10.5281/zenodo.7688792, with URL https://doi.org/10.5281/zenodo.7688792.

microbiology↗

Nonsynonymous mutations in fepR are associated with Listeria adaptation to low concentrations of benzalkonium chloride, but not increased survival in use level concentrations of benzalkonium chloride.

Presence of and selection for Listeria spp. and Listeria monocytogenes that are less effectively inactivated by quaternary ammonium compounds (such as benzalkonium chloride [BC]) is a food safety concern, including in fresh produce environments. An initial MIC assay on 67 produce-associated Listeria strains showed that strains carrying BC resistance genes bcrABC (n=10) and qacH (n=1) showed higher MIC (4-6 mg/L BC) compared to strains lacking these genes (MIC of 1-2 mg/L BC). Serial passaging experiments that exposed the 67 strains to increasing BC concentrations revealed that 62/67 strains showed growth in BC concentrations above their parent MIC (range of 4-20 mg/L). Two serially passaged isolates were obtained for each parent strain and substreaked onto BHI agar in the absence of BC for seven rounds; 105/134 substreaked isolates showed higher substreaked MIC (range of 4 - 6 mg/L) compared to parent MIC. These results suggested isolates acquired genetic adaptations that confer BC resistance. Substreaked isolates were characterized by a combination of whole genome sequencing and Sanger sequencing of fepR, a local repressor of the MATE family efflux pump FepA. These data identified nonsynonymous fepR mutations in 48/67 isolates including 24 missense, 16 nonsense, and 8 frameshift mutations. The mean inactivation of substreaked isolates after exposure to use level concentrations of BC (300 mg/L) was 4.48 log, which was not significantly different from inactivation observed in parent strains. Serial passage experiments performed on cocultures of Listeria strains containing bcrABC or qacH did not yield growth at higher BC concentrations than monoculture experiments. IMPORTANCEListeria resistance to quaternary ammonium compounds has been raised as a concern with regards to Listeria persistence in food environments, which can increase risk of product contamination, food recalls and foodborne illness outbreaks. Findings from our study show that individual Listeria strains can acquire genetic adaptations that confer resistance to low concentrations of benzalkonium chloride, but these genetic adaptations dont increase Listeria survival when exposed to concentrations of benzalkonium chloride used for food contact surface sanitation (300 mg/L). Our study also suggests that there is limited risk of benzalkonium chloride resistance genes bcrABC and qacH spreading through horizontal gene transfer and conferring enhanced resistance of L. monocytogenes to benzalkonium chloride. Overall, our study suggests that emergence of benzalkonium chloride resistant Listeria strains in food processing environments is of limited concern, as even strains adapted to gain higher MIC in vitro maintain full sensitivity to use level concentrations of benzalkonium chloride.

microbiology↗

Soil collected in the Great Smoky Mountains National Park yielded a novel Listeria species, L. swaminathanii, effectively expanding the sensu stricto clade to ten species

Soil samples collected in the Great Smoky Mountains National Park yielded a Listeria isolate that could not be classified to the species level. Whole-genome sequence-based average nucleotide identity BLAST and in silico DNA-DNA Hybridization analyses confirmed this isolate to be a novel Listeria sensu stricto species with the highest similarity to L. marthii (ANI=93.9%, isDDH=55.9%). Additional whole-genome-based analysis using the Genome Taxonomy Database Toolkit, an automated program for classifying bacterial genomes, further supported delineation as a novel Listeria sensu stricto species, as this tool failed to assign a species identification but identified L. marthii as the closest match. Phenotypic and genotypic characterization results indicate that this species is nonpathogenic. Specifically, the novel Listeria species described here is phenotypically (i) non-hemolytic and (ii) negative for phosphatidylinositol-specific phospholipase C activity; the draft genome lacks all virulence genes found in the Listeria pathogenicity island 1 (LIPI-1), as well as the internalin genes inlA and inlB. While the type strain for the new species is phenotypically catalase-negative (an unusual characteristic for Listeria sensu stricto species), its genome contained an apparently intact catalase gene (kat); hence assessment of this phenotype with future isolates will be important. Rapid species identification systems (Listeria API, VITEK 2, VITEK MS) misidentified this novel species as either L. monocytogenes, L. innocua, or L. marthii. We propose the name L. swaminathanii, and the type strain is FSL L7-0020T (=ATCC TSD-239T). IMPORTANCEL. swaminathanii is a novel sensu stricto species that originated from a US National Park, and its place of origin is ultimately preventing this species from achieving valid status. The US National Park Service restricts strain accessibility and open access is currently a prerequisite for species validation. Essentially the only criteria that was not met for L. swaminathanii validation is accessibility of the type strain, therefore nomenclature status should not negate the significance of this discovery. As a novel sensu stricto species, L. swaminathanii expands the group of species whose presence is associated with an increased risk of an L. monocytogenes contamination, and therefore could play an important role in public health. While developers of Listeria spp. detection methods historically only included validly publish species in their validation studies, L. swaminathanii is unequivocally a sensu stricto species and should be included as well.

microbiology↗

Monitoring the Antimicrobial Resistance Dynamics of Salmonella enterica in Healthy Dairy Cattle Populations at the Individual Farm Level Using Whole-Genome Sequencing

Livestock represent a possible reservoir for facilitating the transmission of the zoonotic foodborne pathogen Salmonella enterica to humans; there is also concern that strains can acquire resistance to antimicrobials in the farm environment. Here, we use whole-genome sequencing (WGS) to characterize Salmonella strains (n = 128) isolated from healthy dairy cattle and their associated environments on 13 New York State farms to assess the diversity and microevolution of this important pathogen at the level of the individual herd. Additionally, the accuracy and concordance of multiple in silico tools are assessed, including: (i) two in silico serotyping tools, (ii) combinations of five antimicrobial resistance (AMR) determinant detection tools and one to five AMR determinant databases, and (iii) one antimicrobial minimum inhibitory concentration (MIC) prediction tool. For the isolates sequenced here, in silico serotyping methods outperformed traditional serotyping and resolved all un-typable and/or ambiguous serotype assignments. Serotypes assigned in silico showed greater congruency with the Salmonella whole-genome phylogeny than traditional serotype assignments, and in silico methods showed high concordance (99% agreement). In silico AMR determinant detection methods additionally showed a high degree of concordance, regardless of the pipeline or database used ([&ge;]98% agreement between susceptible/resistant assignments for all pipeline/database combinations). For AMR detection methods that relied exclusively on nucleotide BLAST, accuracy could be maximized by using a range of minimum nucleotide identity and coverage thresholds, with thresholds of 75% nucleotide identity and 50-60% coverage adequate for most pipeline/database combinations. In silico characterization of the microevolution and AMR dynamics of each of six serotype groups (S. Anatum, Cerro, Kentucky, Meleagridis, Newport, Typhimurium/Typhimurium variant Copenhagen) revealed that some lineages were strongly associated with individual farms, while others were distributed across multiple farms. Numerous AMR determinant acquisition and loss events were identified, including the recent acquisition of cephalosporin resistance-conferring blaCMY- and blaCTX-M-type beta-lactamases. The results presented here provide high-resolution insight into the temporal dynamics of AMR Salmonella at the scale of the individual farm and highlight both the strengths and limitations of WGS in tracking zoonotic pathogens and their associated AMR determinants at the livestock-human interface.

microbiology↗

DNA extraction and host depletion methods significantly impact and potentially bias bacterial detection in a biological fluid

Untargeted sequencing of nucleic acids present in food can inform the detection of food safety and origin, as well as product tampering and mislabeling issues. The application of such technologies to food analysis could reveal valuable insights that are simply unobtainable by targeted testing, leading to the efforts of applying such technologies in the food industry. However, before these approaches can be applied, it is imperative to verify that the most appropriate methods are used at every step of the process: gathering primary material, laboratory methods, data analysis, and interpretation. The focus of this study is in gathering the primary material, in this case, DNA. We used bovine milk as a model to 1) evaluate commercially available kits for their ability to extract nucleic acids from inoculated bovine milk; 2) evaluate host DNA depletion methods for use with milk, and 3) develop and evaluate a selective lysis-PMA based protocol for host DNA depletion in milk. Our results suggest that magnetic-based nucleic acid extraction methods are best for nucleic acid isolation of bovine milk. Removal of host DNA remains a challenge for untargeted sequencing of milk, highlighting that the individual matrix characteristics should always be considered in food testing. Some reported methods introduce bias against specific types of microbes, which may be particularly problematic in food safety where the detection of Gram-negative pathogens and indicators is essential. Continuous efforts are needed to develop and validate new approaches for untargeted metagenomics in samples with large amounts of DNA from a single host. ImportanceTracking the bacterial communities present in our food has the potential to inform food safety and product origin. To do so, the entire genetic material present in a sample is extracted using chemical methods or commercially available kits and sequenced using next-generation platforms to provide a snapshot of what the relative composition looks like. Because the genetic material of higher organisms present in food (e.g., cow in milk or beef, wheat in flour) is around one thousand times larger than the bacterial content, challenges exist in gathering the information of interest. Additionally, specific bacterial characteristics can make them easier or harder to detect, adding another layer of complexity to this issue. In this study, we demonstrate the impact of using different methods in the ability of detecting specific bacteria and highlight the need to ensure that the most appropriate methods are being used for each particular sample.

molecular biology↗