Outbreak-associated Salmonella Baildon found in wastewater demonstrates how sewage monitoring can supplement traditional disease surveillance.

Non-typhoidal Salmonella is a common cause of gastroenteritis worldwide, but current non-typhoidal Salmonella surveillance is suboptimal. Here, we evaluated the utility of wastewater monitoring to enhance traditional surveillance for this foodborne pathogen. In June 2022, we tested raw sewage collected twice a week from two treatment plants in central Pennsylvania for non-typhoidal Salmonella and characterized isolates using whole-genome sequencing. We recovered 43 Salmonella isolates from wastewater samples, differentiated by genomic analysis into seven serovars: 16 Panama (37.2%), 9 Senftenberg (20.9%), 8 Baildon (18.6%), and 3 or fewer of four other serovars. We assessed genetic relatedness and epidemiologic links between these wastewater isolates with those from patients with salmonellosis. All S. Baildon isolates from wastewater were genetically similar to those associated with a known contemporaneous salmonellosis outbreak. S. Baildon from wastewater and 42 outbreak-related isolates in the national outbreak detection database had the same core genome multilocus sequence typing, and outbreak code differed by zero or one single polynucleotide polymorphism. One of the 42 outbreak-related isolates was obtained from a patient residing in the wastewater sample collection catchment area, which serves approximately 17000 people. S. Baildon is a rare serovar (reported in <1% cases nationally, over five years). Our study underscores the value of monitoring sewage from a defined population to supplement traditional surveillance methods for the evidence of Salmonella infections and to determine the extent of outbreaks.IMPORTANCEDuring the COVID-19 pandemic, monitoring for SARS-CoV-2 in wastewater was highly effective in identifying the variants of concern earlier than clinical surveillance methods. Here, we show that monitoring domestic sewage can also augment traditional reporting of foodborne illnesses to public health authorities. Our study detected multiple Salmonella enterica serovars in samples from two wastewater treatment plants in central Pennsylvania. Using whole-genome sequencing, we demonstrated that the isolates of variant S. Baildon clustered with those from a foodborne salmonellosis outbreak that occurred in a similar time frame. Cases were primarily from Pennsylvania, and one individual lived within the wastewater treatment catchment area. This study highlights the effectiveness of domestic sewage testing as a proactive public health strategy to track and respond to infectious disease outbreaks.

Sanitizer Resistance and Persistence of Listeria monocytogenes Isolates in Tree Fruit Packing Facilities.

The foodborne pathogen Listeria monocytogenes can persist in produce processing environments, which increases the risk for food contamination. Increased resistance to antimicrobials commonly used in cleaning and sanitizing procedures may contribute to L. monocytogenes' persistence in these environments. This study aimed to evaluate sanitizer resistance in L. monocytogenes isolates collected from three tree fruit packing facilities (F1, F2, and F3) during packing seasons 2020-2021 (Y1) and 2021-2022 (Y2), and to assess evidence of persistence based on the genomic similarity of isolates to historical isolates collected in previous years. L. monocytogenes isolates collected in 2020-2022 (n = 44) were tested for resistance to peroxyacetic acid (PAA) and a proprietary biofilm-removing agent using a broth microdilution assay. Further, L. monocytogenes isolates were whole genome sequenced and screened for the presence of antimicrobial resistance and virulence genes, as well as to assess the genomic similarity of isolates using the CFSAN SNP bioinformatic pipeline. Over half (57%) of the tested isolates had a PAA minimum inhibitory concentration (MIC) of 250 ppm, which was similar to the applied concentration of the PAA sanitizer in the three facilities (230 ppm). In contrast, 80% of tested isolates had a biofilm remover MIC of 0.13 ppm, which was substantially below the concentration applied in the facilities (137 ppm). Genomes of all tested isolates carried antimicrobial resistance (fosX, lin, mdrL, mprF, and norB) and virulence (inlA, inlB, plcA, plcB, prfA, hly, mpl, and iap) genes. L. monocytogenes isolates collected between 2020 and 2022 belonged to three distinct lineages, with 22 multilocus sequence types (MLSTs) belonging to 22 different clonal complexes. Genomic similarity analysis with historical isolates collected from the same facilities in 2016-2017 demonstrated a 5-year persistence of the genotypes ST 1003 and ST 554 in F2, which were no longer detected in 2022. Overall, our results highlight the need to re-evaluate sanitizer concentrations to effectively control persistent L. monocytogenes strains in tree fruit packing facilities.

Genomic diversity of Campylobacter jejuni and Campylobacter coli isolated from the Ethiopian dairy supply chain.

Campylobacteriosis outbreaks have previously been linked to dairy foods. While the genetic diversity of Campylobacter is well understood in high-income countries, it is largely unknown in low-income countries, such as Ethiopia. This study therefore aimed to conduct the first genomic characterization of Campylobacter isolates from the Ethiopian dairy supply chain to aid in future epidemiological studies. Fourteen C. jejuni and four C. coli isolates were whole genome sequenced using an Illumina platform. Sequences were analyzed using the bioinformatics tools in the GalaxyTrakr platform to identify MLST types, and single nucleotide polymorphisms, and infer phylogenetic relationships among the studied isolates. Assembled genomes were further screened to detect antimicrobial resistance and virulence gene sequences. Among 14 C. jejuni, ST 2084 and ST 51, which belong to the clonal complexes ST-353 and ST-443, respectively, were identified. Among the 4 sequenced C. coli isolates, two isolates belonged to ST 1628 and two to ST 830 from the clonal complex ST-828. The isolates of C. jejuni ST 2084 and ST 51 carried ß-lactam resistance gene blaOXA-605, a fluoroquinolone resistance-associated mutation T86I in the gryA gene, and a macrolide resistance-associated mutation A103V in 50S L22. Only ST 2084 isolates carried the tetracycline resistance gene tetO. Conversely, all four C. coli ST 830 and ST 1628 isolates carried tetO, but only ST 1628 isolates also carried blaOXA-605. Lastly, C. jejuni ST 2084 isolates carried a total of 89 virulence genes, and ST 51 isolates carried up to 88 virulence genes. Among C. coli, ST 830 isolates carried 71 genes involved in virulence, whereas two ST 1628 isolates carried up to 82 genes involved in virulence. Isolates from all identified STs have previously been isolated from human clinical cases, demonstrating a potential food safety concern. This finding warrants further monitoring of Campylobacter in dairy foods in Ethiopia to better understand and manage the risks associated with Campylobacter contamination and transmission.

Draft genome sequence of Ruoffia tabacinasalis isolated from a bovine nasal swab: a novel member of the bovine nasal microbiota.

We report the isolation and draft genome sequence of Ruoffia tabacinasalis, a novel member of the bovine nasal microbiota. The genome, which is estimated to be 90.5% complete, is composed of one contig comprising 2,363,349 bp with a GC content of 36.66%.

Assessment of the exposure to cytotoxic Bacillus cereus group genotypes through high-temperature, short-time milk consumption.

This study addresses the limited tools available for assessing food safety risks from cytotoxic Bacillus cereus group strains in contaminated food. We quantified the growth, in skim milk broth, of 17 cytotoxic B. cereus strains across 6 phylogenetic groups with various virulence gene profiles. The strains did not grow in HTST milk at 4 or 6°C. At 10°C, 15 strains exhibited growth; at 8°C, one strain grew; and all strains grew at temperatures ≥14°C. Using growth data from 16 strains, we developed linear secondary growth models and an exposure assessment model. This model, simulating a 5-stage HTST milk supply chain and up to 35 d of consumer storage with an initial contamination of 100 cfu/mL, estimated that 2.81 ± 0.66% and 4.13 ± 2.53% of milk containers would surpass 105 cfu/mL of B. cereus by d 21 and 35, respectively. A sensitivity analysis identified the initial physiological state of cells as the most influential variable affecting predictions for specific isolates. What-if scenarios indicated that increases in mean and variability of consumer storage temperatures significantly affected the predicted B. cereus concentrations in milk. This model serves as an initial tool for risk-based food safety decision-making regarding low-level B. cereus contamination.

Seasonal variation of Salmonella enterica prevalence in milk and cottage cheese along the dairy value chain in three regions of Ethiopia.

Seasonal fluctuations influence foodborne illness transmission and affect patterns of microbial contamination of food. Previous investigations on the seasonality of Salmonella enterica prevalence in dairy products in Ethiopia have been minimal. However, such data are needed to inform strategic development of effective interventions to improve food safety, as seasonal differences may affect intervention strategies. This study was conducted to identify differences in the prevalence of Salmonella in milk and cheese samples between wet and dry seasons. A longitudinal study design was utilized with a random sampling occurring during both dry and wet seasons. A total of 448 milk and cottage cheese samples were collected from Oromia, Sidama, and Amhara regions. Samples were tested for Salmonella using the ISO 6579-1: 2008 method, followed by PCR confirmation. A chi-square test was conducted to assess the significance of differences in the prevalence of Salmonella in the samples between the two seasons. Results from this study showed a higher prevalence of Salmonella in all sample types during the dry season (P < 0.05). Moreover, when comparing raw milk, pasteurized milk, and cottage cheese samples, a significant difference was observed in Salmonella prevalence from raw milk samples (27.08%) collected in the Oromia region. Additionally, data showed a significantly higher prevalence of Salmonella in samples collected from raw milk producers (29.17%) during the wet season (P < 0.05). This study indicates that in order to enhance the safety of dairy products in Ethiopia, comprehensive, long-term awareness building on hygienic milk production and handling that consider seasonal influence is warranted. Supplementary Information: The online version contains supplementary material available at 10.1186/s40550-024-00108-4.

kmerDB: A database encompassing the set of genomic and proteomic sequence information for each species.

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

Comparison of the performance of multiple whole-genome sequence-based tools for the identification of Bacillus cereus sensu stricto biovar Thuringiensis.

The Bacillus cereus sensu stricto (s.s.) species comprises strains of biovar Thuringiensis (Bt) known for their bioinsecticidal activity, as well as strains with foodborne pathogenic potential. Bt strains are identified (i) based on the production of insecticidal crystal proteins, also known as Bt toxins, or (ii) based on the presence of cry, cyt, and vip genes, which encode Bt toxins. Multiple bioinformatics tools have been developed for the detection of crystal protein-encoding genes based on whole-genome sequencing (WGS) data. However, the performance of these tools is yet to be evaluated using phenotypic data. Thus, the goal of this study was to assess the performance of four bioinformatics tools for the detection of crystal protein-encoding genes. The accuracy of sequence-based identification of Bt was determined in reference to phenotypic microscope-based screening for the production of crystal proteins. A total of 58 diverse B. cereus sensu lato strains isolated from clinical, food, environmental, and commercial biopesticide products underwent WGS. Isolates were examined for crystal protein production using phase contrast microscopy. Crystal protein-encoding genes were detected using BtToxin_Digger, BTyper3, IDOPS (identification of pesticidal sequences), and Cry_processor. Out of 58 isolates, the phenotypic production of crystal proteins was confirmed for 18 isolates. Specificity and sensitivity of Bt identification based on sequences were 0.85 and 0.94 for BtToxin_Digger, 0.97 and 0.89 for BTyper3, 0.95 and 0.94 for IDOPS, and 0.88 and 1.00 for Cry_processor, respectively. Cry_processor predicted crystal protein production with the highest specificity, and BtToxin_Digger and IDOPS predicted crystal protein production with the highest sensitivity. Three out of four tested bioinformatics tools performed well overall, with IDOPS achieving high sensitivity and specificity (>0.90).IMPORTANCEStrains of Bacillus cereus sensu stricto (s.s.) biovar Thuringiensis (Bt) are used as organic biopesticides. Bt is differentiated from the foodborne pathogen Bacillus cereus s.s. by the production of insecticidal crystal proteins. Thus, reliable genomic identification of biovar Thuringiensis is necessary to ensure food safety and facilitate risk assessment. This study assessed the accuracy of whole-genome sequencing (WGS)-based identification of Bt compared to phenotypic microscopy-based screening for crystal protein production. Multiple bioinformatics tools were compared to assess their performance in predicting crystal protein production. Among them, identification of pesticidal sequences performed best overall at WGS-based Bt identification.

Multi-species biofilms of environmental microbiota isolated from fruit packing facilities promoted tolerance of Listeria monocytogenes to benzalkonium chloride.

Listeria monocytogenes may survive and persist in food processing environments due to formation of complex multi-species biofilms of environmental microbiota that co-exists in these environments. This study aimed to determine the effect of selected environmental microbiota on biofilm formation and tolerance of L. monocytogenes to benzalkonium chloride in formed biofilms. The studied microbiota included bacterial families previously shown to co-occur with L. monocytogenes in tree fruit packing facilities, including Pseudomonadaceae, Xanthomonadaceae, Microbacteriaceae, and Flavobacteriaceae. Biofilm formation ability and the effect of formed biofilms on the tolerance of L. monocytogenes to benzalkonium chloride was measured in single- and multi-family assemblages. Biofilms were grown statically on polystyrene pegs submerged in a R2A broth. Biofilm formation was quantified using a crystal violet assay, spread-plating, confocal laser scanning microscopy, and its composition was assessed using amplicon sequencing. The concentration of L. monocytogenes in biofilms was determined using the most probable number method. Biofilms were exposed to the sanitizer benzalkonium chloride, and the death kinetics of L. monocytogenes were quantified using a most probable number method. A total of 8, 8, 6, and 3 strains of Pseudomonadaceae, Xanthomonadaceae, Microbacteriaceae, and Flavobacteriaceae, respectively, were isolated from the environmental microbiota of tree fruit packing facilities and were used in this study. Biofilms formed by Pseudomonadaceae, Xanthomonadaceae, and all multi-family assemblages had significantly higher concentration of bacteria, as well as L. monocytogenes, compared to biofilms formed by L. monocytogenes alone. Furthermore, multi-family assemblage biofilms increased the tolerance of L. monocytogenes to benzalkonium chloride compared to L. monocytogenes mono-species biofilms and planktonic multi-family assemblages. These findings suggest that L. monocytogenes control strategies should focus not only on assessing the efficacy of sanitizers against L. monocytogenes, but also against biofilm-forming microorganisms that reside in the food processing built environment, such as Pseudomonadaceae or Xanthomonadaceae.

Genomic characterization of Listeria monocytogenes and Listeria innocua isolated from milk and dairy samples in Ethiopia.

Listeriosis caused by Listeria monocytogenes often poses a significant threat to vulnerable populations. Dairy products have been implicated in outbreaks of listeriosis worldwide. In Ethiopia, studies have identified Listeria spp. and L. monocytogenes in various dairy products, but the genetic diversity and phylogenetic relationships of these bacteria remain largely unknown in the low- and middle-income countries. Therefore, we conducted whole-genome sequencing on 15 L. monocytogenes and 55 L. innocua isolates obtained from different levels of the dairy supply chains across three regions in Ethiopia. Genomes were assembled and used for MLST genotyping and single nucleotide polymorphism (SNP) analysis to infer phylogenetic relationships. We identified a total of 3 L. monocytogenes (i.e., 2, 145, and 18) and 12 L. innocua (i.e., 1489, 1619, 603, 537, 1010, 3186, 492, 3007, 1087, 474, 1008, and 637) MLST sequence types among the studied isolates. Some of these sequence types showed region-specific occurrence, while others were broadly distributed across regions. Through high-quality SNP analysis, we found that among 13 L. monocytogenes identified as ST 2, 11 of them were highly similar with low genetic variation, differing by only 1 to 10 SNPs, suggesting potential selection in the dairy food supply chain. The L. innocua isolates also exhibited low intra-ST genetic variation with only 0-10 SNP differences, except for the ST 1619, which displayed a greater diversity.

Context matters: environmental microbiota from ice cream processing facilities affected the inhibitory performance of two lactic acid bacteria strains against Listeria monocytogenes.

IMPORTANCE: Antilisterial LAB strains have been proposed as biological control agents for application in food processing environments. However, the effect of resident food processing environment microbiota on the performance on antilisterial LAB strains is poorly understood. Our study shows that the presence of microbiota collected from ice cream processing facilities' environmental surfaces can affect the attachment and inhibitory effect of LAB strains against L. monocytogenes. Further studies are therefore needed to assess whether individual microbial taxa affect antilisterial properties of LAB strains and to characterize the underlying mechanisms.

Prevalence of ciprofloxacin resistance and associated genetic determinants differed among Campylobacter isolated from human and poultry meat sources in Pennsylvania.

Poultry is the primary source of Campylobacter infections and severe campylobacteriosis cases are treated with macrolides and fluoroquinolones. However, these drugs are less effective against antimicrobial-resistant strains. Here, we investigated the prevalence of phenotypic antimicrobial resistance and associated resistance genetic determinants in Campylobacter isolates collected from human clinical (N = 123) and meat (N = 80) sources in Pennsylvania in 2017 and 2018. Our goal was to assess potential differences in the prevalence of antimicrobial resistance in Campylobacter isolated from human and poultry meat sources in Pennsylvania and to assess the accuracy of predicting antimicrobial resistance phenotypes based on resistance genotypes. We whole genome sequenced isolates and identified genetic resistance determinants using the National Antimicrobial Resistance Monitoring System Campylobacter AMR workflow v2.0 in GalaxyTrakr. Phenotypic antimicrobial susceptibility testing was carried out using the E-Test and Sensititre CAMPYCMV methods for human clinical and poultry meat isolates, respectively, and the results were interpreted using the EUCAST epidemiological cutoff values. The 193 isolates were represented by 85 MLST sequence types and 23 clonal complexes, suggesting high genetic diversity. Resistance to erythromycin was confirmed in 6% human and 4% meat isolates. Prevalence of ciprofloxacin resistance was significantly higher in human isolates as compared to meat isolates. A good concordance was observed between phenotypic resistance and the presence of the corresponding known resistance genetic determinants.

The composition of environmental microbiota in three tree fruit packing facilities changed over seasons and contained taxa indicative of L. monocytogenes contamination.

BACKGROUND: Listeria monocytogenes can survive in cold and wet environments, such as tree fruit packing facilities and it has been implicated in outbreaks and recalls of tree fruit products. However, little is known about microbiota that co-occurs with L. monocytogenes and its stability over seasons in tree fruit packing environments. In this 2-year longitudinal study, we aimed to characterize spatial and seasonal changes in microbiota composition and identify taxa indicative of L. monocytogenes contamination in wet processing areas of three tree fruit packing facilities (F1, F2, F3). METHODS: A total of 189 samples were collected during two apple packing seasons from floors under the washing, drying, and waxing areas. The presence of L. monocytogenes was determined using a standard culturing method, and environmental microbiota was characterized using amplicon sequencing. PERMANOVA was used to compare microbiota composition among facilities over two seasons, and abundance-occupancy analysis was used to identify shared and temporal core microbiota. Differential abundance analysis and random forest were applied to detect taxa indicative of L. monocytogenes contamination. Lastly, three L. monocytogenes-positive samples were sequenced using shotgun metagenomics with Nanopore MinION, as a proof-of-concept for direct detection of L. monocytogenes' DNA in environmental samples. RESULTS: The occurrence of L. monocytogenes significantly increased from 28% in year 1 to 46% in year 2 in F1, and from 41% in year 1 to 92% in year 2 in F3, while all samples collected from F2 were L. monocytogenes-positive in both years. Samples collected from three facilities had a significantly different microbiota composition in both years, but the composition of each facility changed over years. A subset of bacterial taxa including Pseudomonas, Stenotrophomonas, and Microbacterium, and fungal taxa, including Yarrowia, Kurtzmaniella, Cystobasidium, Paraphoma, and Cutaneotrichosporon, were identified as potential indicators of L. monocytogenes within the monitored environments. Lastly, the DNA of L. monocytogenes was detected through direct Nanopore sequencing of metagenomic DNA extracted from environmental samples. CONCLUSIONS: This study demonstrated that a cross-sectional sampling strategy may not accurately reflect the representative microbiota of food processing facilities. Our findings also suggest that specific microorganisms are indicative of L. monocytogenes, warranting further investigation of their role in the survival and persistence of L. monocytogenes. Video Abstract.

Conditional Forest Models Built Using Metagenomic Data Accurately Predicted Salmonella Contamination in Northeastern Streams.

The use of water contaminated with Salmonella for produce production contributes to foodborne disease burden. To reduce human health risks, there is a need for novel, targeted approaches for assessing the pathogen status of agricultural water. We investigated the utility of water microbiome data for predicting Salmonella contamination of streams used to source water for produce production. Grab samples were collected from 60 New York streams in 2018 and tested for Salmonella. Separately, DNA was extracted from the samples and used for Illumina shotgun metagenomic sequencing. Reads were trimmed and used to assign taxonomy with Kraken2. Conditional forest (CF), regularized random forest (RRF), and support vector machine (SVM) models were implemented to predict Salmonella contamination. Model performance was assessed using 10-fold cross-validation repeated 10 times to quantify area under the curve (AUC) and Kappa score. CF models outperformed the other two algorithms based on AUC (0.86, CF; 0.81, RRF; 0.65, SVM) and Kappa score (0.53, CF; 0.41, RRF; 0.12, SVM). The taxa that were most informative for accurately predicting Salmonella contamination based on CF were compared to taxa identified by ALDEx2 as being differentially abundant between Salmonella-positive and -negative samples. CF and differential abundance tests both identified Aeromonas salmonicida (variable importance [VI] = 0.012) and Aeromonas sp. strain CA23 (VI = 0.025) as the two most informative taxa for predicting Salmonella contamination. Our findings suggest that microbiome-based models may provide an alternative to or complement existing water monitoring strategies. Similarly, the informative taxa identified in this study warrant further investigation as potential indicators of Salmonella contamination of agricultural water. IMPORTANCE Understanding the associations between surface water microbiome composition and the presence of foodborne pathogens, such as Salmonella, can facilitate the identification of novel indicators of Salmonella contamination. This study assessed the utility of microbiome data and three machine learning algorithms for predicting Salmonella contamination of Northeastern streams. The research reported here both expanded the knowledge on the microbiome composition of surface waters and identified putative novel indicators (i.e., Aeromonas species) for Salmonella in Northeastern streams. These putative indicators warrant further research to assess whether they are consistent indicators of Salmonella contamination across regions, waterways, and years not represented in the data set used in this study. Validated indicators identified using microbiome data may be used as targets in the development of rapid (e.g., PCR-based) detection assays for the assessment of microbial safety of agricultural surface waters.

Prevalence and associated risk factors for Salmonella enterica contamination of cow milk and cottage cheese in Ethiopia.

Animal sourced foods, such as dairy products, are common sources of Salmonella enterica, a foodborne pathogen of increasing global concern, particularly in developing countries. In Ethiopia, most data on the prevalence of Salmonella in dairy products is highly varied and limited to a specific region or district. Furthermore, there is no data available on the risk factors for Salmonella contamination of cow milk and cottage cheese in Ethiopia. This study was therefore conducted to determine the presence of Salmonella throughout the Ethiopian dairy value chain and to identify risk factors for contamination with Salmonella. The study was carried out in three regions of Ethiopia, including Oromia, Southern Nations, Nationalities and Peoples, and Amhara during a dry season. A total 912 samples were collected from milk producers, collectors, processors, and retailers. Samples were tested for Salmonella using the ISO 6579-1: 2008 method, followed by PCR confirmation. Concurrent with sample collection, a survey was administered to study participants to identify risk factors associated with Salmonella contamination. Salmonella contamination was highest in raw milk samples at the production (19.7%) and at milk collection (21.3%) levels. No significant difference in the prevalence of Salmonella contamination among regions was detected (p > 0.05). Regional differences were apparent for cottage cheese, with the highest prevalence being in Oromia (6.3%). Identified risk factors included the temperature of water used for cow udder washing, the practice of mixing milk lots, the type of milk container, use of refrigeration, and milk filtration. These identified factors can be leveraged to develop targeted intervention strategies aimed at reducing the prevalence of Salmonella in milk and cottage cheese in Ethiopia.

Prevalence of Campylobacter species and associated risk factors for contamination of dairy products collected in a dry season from major milk sheds in Ethiopia.

A cross-sectional study was conducted to investigate the prevalence and risk factors for contamination of Ethiopian dairy products with Campylobacter. A total of 912 dairy food samples were collected from establishments of 682 study participants that were interviewed. Samples were tested for Campylobacter by following the ISO 10272-1:2017 standard and PCR confirmation. Campylobacter was detected in 11% of tested food samples and all detected Campylobacter were C. jejuni. The highest prevalence of C. jejuni was found in raw milk (16%), followed by pasteurized milk (9%) and cottage cheese (2%) (P < 0.001). Using warm water and soap for cleaning cow udders and teats on farms reduced the likelihood of detecting Campylobacter in milk (AOR = 0.3, P = 0.023). Filtering milk with a cloth, using a plastic filter (AOR = 0.065, P = 0.005), and storing milk in an aluminum container (AOR = 0.23, P = 0.027) reduced the likelihood of detecting Campylobacter in milk at the collection facilities. In contrast, Campylobacter detection was significantly more likely in milk collected at collection centers with concrete floors (AOR = 5.2, P = 0.004). The odds of detecting Campylobacter in milk were 17 times greater (AOR = 17, P = 0.007) in milk processing facilities that did not calibrate a pasteurizer on an annual basis. Finally, having a separate refrigerator for milk storage reduced the odds of detecting Campylobacter in retail (AOR = 0.29, P = 0.021).

Short-Term Tomato Consumption Alters the Pig Gut Microbiome toward a More Favorable Profile.

Diets rich in fruits and vegetables have been shown to exert positive effects on the gut microbiome. However, little is known about the specific effect of individual fruits or vegetables on gut microbe profiles. This study aims to elucidate the effects of tomato consumption on the gut microbiome, as tomatoes account for 22% of vegetable consumption in Western diets, and their consumption has been associated with positive health outcomes. Using piglets as a physiologically relevant model of human metabolism, 20 animals were assigned to either a control or a tomato powder-supplemented diet (both macronutrient matched and isocaloric) for 14 days. The microbiome was sampled rectally at three time points: day 0 (baseline), day 7 (midpoint), and day 14 (end of study). DNA was sequenced using shotgun metagenomics, and reads were annotated using MG-RAST. There were no differences in body weight or feed intake between our two treatment groups. There was a microbial shift which included a higher ratio of Bacteroidota to Bacillota (formerly known as Bacteroidetes and Firmicutes, respectively) and higher alpha-diversity in tomato-fed animals, indicating a shift to a more desirable phenotype. Analyses at both the phylum and genus levels showed global microbiome profile changes (permutational multivariate analysis of variance [PERMANOVA], P ≤ 0.05) over time but not with tomato consumption. These data suggest that short-term tomato consumption can beneficially influence the gut microbial profile, warranting further investigation in humans. IMPORTANCE The composition of the microorganisms in the gut is a contributor to overall health, prompting the development of strategies to alter the microbiome composition. Studies have investigated the role of the diet on the microbiome, as it is a major modifiable risk factor contributing to health; however, little is known about the causal effects of consumption of specific foods on the gut microbiota. A more complete understanding of how individual foods impact the microbiome will enable more evidence-based dietary recommendations for long-term health. Tomatoes are of interest as the most consumed nonstarchy vegetable and a common source of nutrients and phytochemicals across the world. This study aimed to elucidate the effect of short-term tomato consumption on the microbiome, using piglets as a physiologically relevant model to humans. We found that tomato consumption can positively affect the gut microbial profile, which warrants further investigation in humans.

Effect of processing on the anti-inflammatory efficacy of cocoa in a high fat diet-induced mouse model of obesity.

Obesity causes inflammation which may lead to development of co-morbidities like cardiovascular diseases. Cocoa is a popular food ingredient that has been shown to mitigate obesity and inflammation in preclinical models. Cocoa typically undergoes fermentation and roasting prior to consumption, which can affect the polyphenol content in cocoa. The aim of this study was to compare the effect of fermentation and roasting protocols on the ability of cocoa to mitigate obesity, gut barrier dysfunction, and chronic inflammation in high fat (HF)-fed, obese C57BL/6J mice. We found that treatment of mice with 80 mg/g dietary cocoa powder for 8 weeks reduced rate of body weight gain in both male and female mice (46-57%), regardless of fermentation and roasting protocol. Colonic length was increased (11-24%) and gut permeability was reduced (48-79%) by cocoa supplementation. Analysis of the cecal microbiome showed that cocoa, regardless of fermentation and roasting protocol, reduced the ratio of Firmicutes to Bacteroidetes. Multivariate statistical analysis of markers of inflammation and body weight data showed sex differences in the effect of both the HF diet as well as cocoa supplementation. Based on this data there was strong protective efficacy from cocoa supplementation especially for the more processed cocoa samples. Overall, this study shows that anti-obesity and anti-inflammatory efficacy of cocoa is resilient to changes in polyphenol content and composition induced by fermentation or roasting. Further, this study shows that although cocoa has beneficial effects in both males and females, there are significant sex differences.

Strains Associated with Two 2020 Welder Anthrax Cases in the United States Belong to Separate Lineages within Bacillus cereus sensu lato.

Anthrax-causing members of Bacillus cereus sensu lato (s.l.) pose a serious threat to public health. While most anthrax-causing strains resemble B. anthracis phenotypically, rare cases of anthrax-like illness caused by strains resembling "B. cereus" have been reported. Here, whole-genome sequencing was used to characterize three B. cereus s.l. isolates associated with two 2020 welder anthrax cases in the United States, which resembled "B. cereus" phenotypically. Comparison of the three genomes sequenced here to all publicly available, high-quality B. cereus s.l. genomes (n = 2890 total genomes) demonstrated that genomes associated with each case effectively belonged to separate species at the conventional 95% average nucleotide identity prokaryotic species threshold. Two PubMLST sequence type 78 (ST78) genomes affiliated with a case in Louisiana were most closely related to B. tropicus and possessed genes encoding the Bps exopolysaccharide capsule, as well as hemolysin BL (Hbl) and cytotoxin K (CytK). Comparatively, a ST108 genome associated with a case in Texas was most closely related to B. anthracis; however, like other anthrax-causing strains most closely related to B. anthracis, this genome did not possess Bps-, Hbl-, or CytK-encoding genes. Overall, results presented here provide insights into the evolution of anthrax-causing B. cereus s.l.

Laboratory Misidentifications Resulting from Taxonomic Changes to Bacillus cereus Group Species, 2018-2022.

Whole-genome sequencing (WGS) is being applied increasingly to Bacillus cereus group species; however, misinterpretation of WGS results may have severe consequences. We report 3 cases, 1 of which was an outbreak, in which misinterpretation of B. cereus group WGS results hindered communication within public health and industrial laboratories.