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Monitoring data submitted to the National Center for Biotechnology Information’s Pathogen Detection whole-genome sequence database, which includes the foodborne bacterial pathogens Listeria monocytogenes, Salmonella enterica, and Escherichia coli, has proven effective for detecting emerging outbreaks. As part of the submission process, new sequence data are typed using a whole-genome multi-locus sequence typing scheme and clustered with sequences already in the database. Publicly available text files contain the results of these analyses. However, contextualizing and interpreting this information is complex. We present the Rapid Intuitive Pathogen Surveillance (RIPS) tool, which shows the results of the NCBI Rapid Reports, along with appropriate metadata, in a graphical, interactive dashboard. RIPS makes the information in the Rapid Reports useful for real-time surveillance of genome sequence databases.

ABSTRACT Wastewater surveillance has emerged as a crucial public health tool for population-level pathogen surveillance. Supported by funding from the American Rescue Plan Act of 2021, the FDA‘s genomic epidemiology program, GenomeTrakr, was leveraged to sequence SARS-CoV-2 from wastewater sites across the United States. This initiative required the evaluation, optimization, development, and publication of new methods and analytical tools spanning sample collection through variant analyses. Version-controlled protocols for each step of the process were developed and published on protocols.io. A custom data analysis tool and a publicly accessible dashboard were built to facilitate real-time visualization of the collected data, focusing on the relative abundance of SARS-CoV-2 variants and sub-lineages across different samples and sites throughout the project. From September 2021 through June 2023, a total of 3,389 wastewater samples were collected, with 2,517 undergoing sequencing and submission to NCBI under the umbrella BioProject, PRJNA757291. Sequence data were released with explicit quality control (QC) tags on all sequence records, communicating our confidence in the quality of data. Variant analysis revealed wide circulation of Delta in the fall of 2021 and captured the sweep of Omicron and subsequent diversification of this lineage through the end of the sampling period. This project successfully achieved two important goals for the FDA’s GenomeTrakr program: first, contributing timely genomic data for the SARS-CoV-2 pandemic response, and second, establishing both capacity and best practices for culture-independent, population-level environmental surveillance for other pathogens of interest to the FDA.IMPORTANCEThis paper serves two primary objectives. First, it summarizes the genomic and contextual data collected during a Covid-19 pandemic response project, which utilized the FDA’s laboratory network, traditionally employed for sequencing foodborne pathogens, for sequencing SARS-CoV-2 from wastewater samples. Second, it outlines best practices for gathering and organizing population-level next generation sequencing (NGS) data collected for culture-free, surveillance of pathogens sourced from environmental samples.

Whole-genome sequence databases continue to grow. Collection times between samples are also growing, providing both a challenge for comparing recently collected sequence data to historical samples and an opportunity for evolutionary analyses that can be used to refine match criteria. We measured evolutionary rates for 22 Salmonella enterica serotypes. Based upon these measurements, we propose using an evolutionary rate of 1.97 single-nucleotide polymorphisms (SNPs) per year when determining whether genome sequences match.

Salmonella enterica subsp. enterica serovar Kentucky is frequently isolated from healthy poultry and dairy cows and is occasionally isolated from people with clinical disease. A genomic analysis of 119 isolates collected in the United States from dairy cows, ground beef, poultry and poultry products, and human clinical cases was conducted. Results of the analysis demonstrated that the majority of poultry and bovine-associated S. Kentucky were sequence type (ST) 152. Several bovine-associated (n = 3) and food product isolates (n = 3) collected from the United States and the majority of human clinical isolates were ST198, a sequence type that is frequently isolated from poultry and occasionally from human clinical cases in Northern Africa, Europe and Southeast Asia. A phylogenetic analysis indicated that both STs are more closely related to other Salmonella serovars than they are to each other. Additionally, there was strong evidence of an evolutionary divergence between the poultry-associated and bovine-associated ST152 isolates that was due to polymorphisms in four core genome genes. The ST198 isolates recovered from dairy farms in the United States were phylogenetically distinct from those collected from human clinical cases with 66 core genome SNPs differentiating the two groups, but more isolates are needed to determine the significance of this distinction. Identification of S. Kentucky ST198 from dairy animals in the United States suggests that the presence of this pathogen should be monitored in food-producing animals.

Facile laboratory tools are needed to augment identification in contamination events to trace the contamination back to the source (traceback) of Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis). Understanding the evolution and diversity within and among outbreak strains is the first step towards this goal. To this end, we collected 106 new S. Enteriditis isolates within S. Enteriditis Pulsed-Field Gel Electrophoresis (PFGE) pattern JEGX01.0004 and close relatives, and determined their genome sequences. Sources for these isolates spanned food, clinical and environmental farm sources collected during the 2010 S. Enteritidis shell egg outbreak in the United States along with closely related serovars, S. Dublin, S. Gallinarum biovar Pullorum and S. Gallinarum. Despite the highly homogeneous structure of this population, S. Enteritidis isolates examined in this study revealed thousands of SNP differences and numerous variable genes (n = 366). Twenty-one of these genes from the lineages leading to outbreak-associated samples had nonsynonymous (causing amino acid changes) changes and five genes are putatively involved in known Salmonella virulence pathways. While chromosome synteny and genome organization appeared to be stable among these isolates, genome size differences were observed due to variation in the presence or absence of several phages and plasmids, including phage RE-2010, phage P125109, plasmid pSEEE3072_19 (similar to pSENV), plasmid pOU1114 and two newly observed mobile plasmid elements pSEEE1729_15 and pSEEE0956_35. These differences produced modifications to the assembled bases for these draft genomes in the size range of approximately 4.6 to 4.8 mbp, with S. Dublin being larger (∼4.9 mbp) and S. Gallinarum smaller (4.55 mbp) when compared to S. Enteritidis. Finally, we identified variable S. Enteritidis genes associated with virulence pathways that may be useful markers for the development of rapid surveillance and typing methods, potentially aiding in traceback efforts during future outbreaks involving S. Enteritidis PFGE pattern JEGX01.0004.

Salmonella Newport has ranked in the top three Salmonella serotypes associated with foodborne outbreaks from 1995 to 2011 in the United States. In the current study, we selected 26 S. Newport strains isolated from diverse sources and geographic locations and then conducted 454 shotgun pyrosequencing procedures to obtain 16-24 × coverage of high quality draft genomes for each strain. Comparative genomic analysis of 28 S. Newport strains (including 2 reference genomes) and 15 outgroup genomes identified more than 140,000 informative SNPs. A resulting phylogenetic tree consisted of four sublineages and indicated that S. Newport had a clear geographic structure. Strains from Asia were divergent from those from the Americas. Our findings demonstrated that analysis using whole genome sequencing data resulted in a more accurate picture of phylogeny compared to that using single genes or small sets of genes. We selected loci around the mutS gene of S. Newport to differentiate distinct lineages, including those between invH and mutS genes at the 3' end of Salmonella Pathogenicity Island 1 (SPI-1), ste fimbrial operon, and Clustered, Regularly Interspaced, Short Palindromic Repeats (CRISPR) associated-proteins (cas). These genes in the outgroup genomes held high similarity with either S. Newport Lineage II or III at the same loci. S. Newport Lineages II and III have different evolutionary histories in this region and our data demonstrated genetic flow and homologous recombination events around mutS. The findings suggested that S. Newport Lineages II and III diverged early in the serotype evolution and have evolved largely independently. Moreover, we identified genes that could delineate sublineages within the phylogenetic tree and that could be used as potential biomarkers for trace-back investigations during outbreaks. Thus, whole genome sequencing data enabled us to better understand the genetic background of pathogenicity and evolutionary history of S. Newport and also provided additional markers for epidemiological response.

Little is known about the microbial communities found in distribution centers (DCs), especially in those storing and handling food. As many foodborne bacteria are known to establish residence in food facilities, it is reasonable to assume that DCs handling foods are also susceptible to pathogen colonization. To investigate the microbial communities within DCs, 16S amplicon sequencing was completed on 317 environmental surface sponge swabs collected in DCs (n = 18) across the United States. An additional 317 swabs were collected in parallel to determine if any viable Listeria species were also present at each sampling site. There were significant differences in median diversity measures (observed, Shannon, and Chao1) across individual DCs, and top genera across all reads were Carnobacterium_A, Psychrobacter, Pseudomonas_E, Leaf454, and Staphylococcus based on taxonomic classifications using the Genome Taxonomy Database. Of the 39 16S samples containing Listeria ASVs, four of these samples had corresponding Listeria positive microbiological samples. Data indicated a predominance of ASVs identified as coldtolerant bacteria in environmental samples collected in DCs. Differential abundance analysis identified Carnobacterium_A, Psychrobacter, and Pseudomonas_E present at a significantly greater abundance in Listeria positive microbiological compared to those negative for Listeria. Additionally, microbiome composition varied significantly across groupings within variables (e.g., DC, season, general sampling location). [ABSTRACT FROM AUTHOR]

Background. The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). Methods. We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Results. Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). Conclusion. This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions. [ABSTRACT FROM AUTHOR]

Whole-genome sequence databases continue to grow. Collection times between samples are also growing, providing both a challenge for comparing recently collected sequence data to historical samples and an opportunity for evolutionary analyses that can be used to refine match criteria. We measured evolutionary rates for 22 Salmonella enterica serotypes. Based upon these measurements, we propose using an evolutionary rate of 1.97 single-nucleotide polymorphisms (SNPs) per year when determining whether genome sequences match. [ABSTRACT FROM AUTHOR]

Intrapopulation genetic variability in prokaryotes is receiving increasing attention thanks to improving sequencing methods; however, the ability to distinguish intrapopulation variability from species clusters or initial stages of gene flow barrier development remains insufficient. To overcome this limitation, we took advantage of the lifestyle of Ferrovum myxofaciens , a species that may represent 99% of prokaryotic microbiome of biostalactites growing at acid mine drainage springs. We gained four complete and one draft metagenome-assembled F. myxofaciens genomes using Oxford Nanopore and Illumina sequencing and mapped the reads from each sample on the reference genomes to assess the intrapopulation variability. We observed two phenomena associated with intrapopulation variability: hypervariable regions affected by mobilome expansion called "scrapyards," and variability in gene disruptions caused by transposons within each population. Both phenomena were previously described in prokaryotes. However, we present here for the first time scrapyard regression and the development of a new one. Nearly complete loss of intrapopulation short sequence variability in the old scrapyard and high variability in the new one suggest that localized gene flow suppression is necessary for scrapyard formation. Concerning the variable gene disruptions, up to 9 out of 41 occurrences per sample were located in highly conserved diguanylate cyclases/phosphodiesterases. We propose that microdiversification of life strategies may be an adaptive outcome of random diguanylate cyclase elimination. The mine biostalactites thus proved as a unique model system for describing genomic intrapopulation processes, as they offer easily sampleable units enriched in a single microbial species. [ABSTRACT FROM AUTHOR]

The co-existence of rats and humans in urban environments has long been a cause for concern regarding human health because of the potential for rats to harbor and transmit disease-causing pathogens. Here, we analyze whole-genome sequence (WGS) data from 41 Escherichia coli isolates collected from rat feces from 12 locations within the city of Chicago, IL, United States to determine the potential for rats to serve as a reservoir for pathogenic E. coli and describe its population structure. We identified 25 different serotypes, none of which were isolated from strains containing significant virulence markers indicating the presence of Shiga toxin-producing and other disease-causing E. coli. Nor did the E. coli isolates harbor any particularly rare stress tolerant or antimicrobial resistance genes. We then compared the isolates against a public database of approximately 100,000 E. coli and Shigella isolates of primarily food, food facility, or clinical origin. We found that only one isolate was genetically similar to genome sequences in the database. Phylogenetic analyses showed that isolates cluster by serotype, and there was little geographic structure (e.g., isolation by distance) among isolates. However, a greater signal of isolation by distance was observed when we compared genetic and geographic distances among isolates of the same serotype. This suggests that E. coli serotypes are independent lineages and recombination between serotypes is rare. [ABSTRACT FROM AUTHOR]

Motivation Microbial gene catalogs are data structures that organize genes found in microbial communities, providing a reference for standardized analysis of the microbes across samples and studies. Although gene catalogs are commonly used, they have not been critically evaluated for their effectiveness as a basis for metagenomic analyses. Results As a case study, we investigate one such catalog, the Integrated Gene Catalog (IGC), however, our observations apply broadly to most gene catalogs constructed to date. We focus on both the approach used to construct this catalog and on its effectiveness when used as a reference for microbiome studies. Our results highlight important limitations of the approach used to construct the IGC and call into question the broad usefulness of gene catalogs more generally. We also recommend best practices for the construction and use of gene catalogs in microbiome studies and highlight opportunities for future research. Availability and implementation All supporting scripts for our analyses can be found on GitHub:  https://github.com/SethCommichaux/IGC.git. The supporting data can be downloaded from:  https://obj.umiacs.umd.edu/igc-analysis/IGC%5fanalysis%5fdata.tar.gz. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

The use of whole genome sequencing (WGS) data generated by the long-read sequencing platform Oxford Nanopore Technologies (ONT) has been shown to provide reliable results for Salmonella serotype prediction in a previous study. To further meet the needs of industry for accurate, rapid, and cost-efficient Salmonella confirmation and serotype classification, we evaluated the serotype prediction accuracy of using WGS data from multiplex ONT sequencing with three, four, five, seven, or ten Salmonella isolates (each isolate represented one Salmonella serotype) pooled in one R9.4.1 flow cell. Each multiplexing strategy was repeated with five flow cells, and the loaded samples were sequenced simultaneously in a GridION sequencer for 48 h. In silico serotype prediction was performed using both SeqSero2 (for raw reads and genome assemblies) and SISTR (for genome assemblies) software suites. An average of 10.63 Gbp of clean sequencing data was obtained per flow cell. We found that the unevenness of data yield among each multiplexed isolate was a major barrier for shortening sequencing time. Using genome assemblies, both SeqSero2 and SISTR accurately predicted all the multiplexed isolates under each multiplexing strategy when depth of genome coverage ≥50× for each isolate. We identified that cross-sample barcode assignment was a major cause of prediction errors when raw sequencing data were used for prediction. This study also demonstrated that, (i) sequence data generated by ONT multiplex sequencing can be used to simultaneously predict serotype for three to ten Salmonella isolates, (ii) with three to ten Salmonella isolates multiplexed, genome coverage at ≥50× per isolate was obtained within an average of 6 h of ONT multiplex sequencing, and (iii) with five isolates multiplexed, the cost per isolate might be reduced to 23% of that incurred with single ONT sequencing. This study is a starting point for future validation of multiplex ONT WGS as a cost-efficient and rapid Salmonella confirmation and serotype classification tool for the food industry. [ABSTRACT FROM AUTHOR]

Profiles of symbiotic microbial communities ("microbiomes") can provide insight into the natural history and ecology of their hosts. Using high throughput DNA sequencing of the 16S rRNA V4 region, microbiomes of five shark species in South Florida (nurse, lemon, sandbar, Caribbean reef, and tiger) have been characterized for the first time. The microbiomes show species specific microbiome composition, distinct from surrounding seawater. Shark anatomical location (gills, teeth, skin, cloaca) affected the diversity of microbiomes. An in-depth analysis of teeth communities revealed species specific microbial communities. For example, the genus Haemophilus , explained 7.0% of the differences of the teeth microbiomes of lemon and Caribbean reef sharks. Lemon shark teeth communities (n = 11) contained a high abundance of both Vibrio (10.8 ± 26.0%) and Corynebacterium (1.6 ± 5.1%), genera that can include human pathogenic taxa. The Vibrio (2.8 ± 6.34%) and Kordia (3.1 ± 6.0%) genera and Salmonella enterica (2.6 ± 6.4%) were the most abundant members of nurse shark teeth microbial communities. The Vibrio genus was highly represented in the sandbar shark (54.0 ± 46.0%) and tiger shark (5.8 ± 12.3%) teeth microbiomes. The prevalence of genera containing potential human pathogens could be informative in shark bite treatment protocols and future research to confirm or deny human pathogenicity. We conclude that South Florida sharks host species specific microbiomes that are distinct from their surrounding environment and vary due to differences in microbial community composition among shark species and diversity and composition among anatomical locations. Additionally, when considering the confounding effects of both species and location, microbial community diversity and composition varies. [ABSTRACT FROM AUTHOR]

Whole genome sequencing (WGS) enables high resolution typing of bacteria up to the single nucleotide polymorphism (SNP) level. WGS is used in clinical microbiology laboratories for infection control, molecular surveillance and outbreak analyses. Given the large palette of WGS reagents and bioinformatics tools, the Swiss clinical bacteriology community decided to conduct a ring trial (RT) to foster harmonization of NGS-based bacterial typing. The RT aimed at assessing methicillin-susceptible Staphylococcus aureus strain relatedness from WGS and epidemiological data. The RT was designed to disentangle the variability arising from differences in sample preparation, SNP calling and phylogenetic methods. Nine laboratories participated. The resulting phylogenetic tree and cluster identification were highly reproducible across the laboratories. Cluster interpretation was, however, more laboratory dependent, suggesting that an increased sharing of expertise across laboratories would contribute to further harmonization of practices. More detailed bioinformatic analyses unveiled that while similar clusters were found across laboratories, these were actually based on different sets of SNPs, differentially retained after sample preparation and SNP calling procedures. Despite this, the observed number of SNP differences between pairs of strains, an important criterion to determine strain relatedness given epidemiological information, was similar across pipelines for closely related strains when restricting SNP calls to a common core genome defined by S. aureus cgMLST schema. The lessons learned from this pilot study will serve the implementation of larger-scale RT, as a mean to have regular external quality assessments for laboratories performing WGS analyses in a clinical setting. [ABSTRACT FROM AUTHOR]

This study investigated the prevalence, serovar distribution, antimicrobial resistance, and pulsed field gel electrophoresis (PFGE) typing of Salmonella enterica isolated from Lake Zapotlán, Jalisco, Mexico. Additionally, the association of the presence of Salmonella with physicochemical and environmental parameters was analyzed using Pearson correlation analysis and principal component analysis (PCA). Salmonella spp. were identified in 19 of 63 (30.15%) samples. The prevalence of Salmonella was positively correlated with air temperature, electrical conductivity, pH, and dissolved oxygen and negatively correlated with relative humidity, water temperature, turbidity, and precipitation. The predominant serotype identified was Agona (68.48%), followed by Weltevreden (5.26%), Typhimurium (5.26%), and serogroup B (21.05%). Overall, the highest detected antimicrobial resistance was toward colistin (73.68%), followed by sulfamethoxazole (63.15%), tetracycline (57.89%), nalidixic acid (52.63%), and trimethoprim (52.63%). All Salmonella strains were genetically diverse, with a total of 11 Xba I and four Bln I profiles on PFGE. The use of these two enzymes allowed differentiate strains of Salmonella of the same serotype. The results obtained in this study contribute to a better understanding of the Salmonella spp. ecology in an endorheic subtropical lake and provide information for decision makers to propose and implement effective strategies to control point and non-point sources of pathogen contamination. [ABSTRACT FROM AUTHOR]

Open-source DNA sequence databases have long been touted as beneficial to public health, including the facilitation of earlier detection and response to infectious disease outbreaks. Of critical importance to harnessing these benefits is the metadata that describe general and other domain-specific attributes (eg, collection location, isolate type) of a sample. Unlike the sequence data, metadata are often incomplete and lack adherence to an international standard. Here, we describe the problem posed by such variable and incomplete metadata in terms of interpretative labor costs (the time and energy necessary to make sense of the signal in the genetic data) and the impact such metadata have on foodborne outbreak detection and response. Improving the quality of sequence-associated metadata would allow for earlier detection of emerging food safety hazards and allow faster response to foodborne outbreaks. [ABSTRACT FROM AUTHOR]

Immunochemical and mass spectrometric methods were used to examine the gluten composition of a gluten-reduced beer produced by brewing with barley malt in the presence of prolyl endopeptidase (PEP) and a final filtration treatment with diatomaceous earth and perlite. The competitive ELISA is generally considered appropriate for the analysis of hydrolysed gluten, but it is not considered a scientifically valid method for the quantification of gluten in fermented or hydrolysed foods due to the lack of an appropriate reference standard. As no single analytical method can capture the spectrum of gluten-derived products in beer, a comprehensive approach was employed to analyse the intact and hydrolysed fractions of gluten with complementary methods. The combination of PEP addition and diatomaceous earth/perlite filtration was more effective at reducing the concentration of detectable gluten than each of the treatments alone. However, gluten proteins and/or polypeptides were observed in filtered, PEP-treated beers using sandwich ELISA methods, western blot, and bottom-up mass spectrometry. In addition, mass spectrometry results showed that the number of hydrolysed gluten peptides was almost unaffected by the filtration process. Gluten peptides that contained potentially immunopathogenic sequences were identified in the filtered PEP-containing beers by MS. Variability in gluten composition was observed between three replicate pilot-scale productions, suggesting that the gluten profile in beer could differ from batch to batch. As there is uncertainty in the detection and quantification of gluten in hydrolysed and fermented foods, characterisation of hydrolysed gluten by complementary analytical methodologies is recommended. [ABSTRACT FROM AUTHOR]

Salmonella enterica subspecies enterica is a highly diverse subspecies with more than 1500 serovars and the ability to distinguish serovars within this group is vital for surveillance. With the development of whole-genome sequencing technology, serovar prediction by traditional serotyping is being replaced by molecular serotyping. Existing in silico serovar prediction approaches utilize surface antigen encoding genes, core genome MLST and serovar-specific gene markers or DNA fragments for serotyping. However, these serovar-specific gene markers or DNA fragments only distinguished a small number of serovars. In this study, we compared 2258 Salmonella accessory genomes to identify 414 candidate serovar-specific or lineage-specific gene markers for 106 serovars which includes 24 polyphyletic serovars and the paraphyletic serovar Enteritidis. A combination of several lineage-specific gene markers can be used for the clear identification of the polyphyletic serovars and the paraphyletic serovar. We designed and evaluated an in silico serovar prediction approach by screening 1089 genomes representing 106 serovars against a set of 131 serovar-specific gene markers. The presence or absence of one or more serovar-specific gene markers was used to predict the serovar of an isolate from genomic data. We show that serovar-specific gene markers have comparable accuracy to other in silico serotyping methods with 84.8% of isolates assigned to the correct serovar with no false positives (FP) and false negatives (FN) and 10.5% of isolates assigned to a small subset of serovars containing the correct serovar with varied FP. Combined, 95.3% of genomes were correctly assigned to a serovar. This approach would be useful as diagnosis moves to culture-independent and metagenomic methods as well as providing a third alternative to confirm other genome-based analyses. The identification of a set of gene markers may also be useful in the development of more cost-effective molecular assays designed to detect specific gene markers of the all major serovars in a region. These assays would be useful in serotyping isolates where cultures are no longer obtained and traditional serotyping is therefore impossible. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including ancestral polymorphisms, population genetic data sets and gene tree independence in phylogenomics, as well as lists individuals who have contributed in reviewing journal manuscripts.

We introduce the R package openEBGM, an implementation of the Gamma-Poisson Shrinker (GPS) model for identifying unexpected counts in large contingency tables using an empirical Bayes approach. The Empirical Bayes Geometric Mean (EBGM) and quantile scores are obtained from the GPS model estimates. openEBGM provides for the evaluation of counts using a number of different methods, including the model-based disproportionality scores, the relative reporting ratio (RR), and the proportional reporting ratio (PRR). Data squashing for computational efficiency and stratification for confounding variable adjustment are included. Application to adverse event detection is discussed. [ABSTRACT FROM AUTHOR]

Salmonella enterica subsp. enterica serovar Kentucky is frequently isolated from healthy poultry and dairy cows and is occasionally isolated from people with clinical disease. A genomic analysis of 119 isolates collected in the United States from dairy cows, ground beef, poultry and poultry products, and human clinical cases was conducted. Results of the analysis demonstrated that the majority of poultry and bovine-associated S. Kentucky were sequence type (ST) 152. Several bovine-associated (n = 3) and food product isolates (n = 3) collected from the United States and the majority of human clinical isolates were ST198, a sequence type that is frequently isolated from poultry and occasionally from human clinical cases in Northern Africa, Europe and Southeast Asia. A phylogenetic analysis indicated that both STs are more closely related to other Salmonella serovars than they are to each other. Additionally, there was strong evidence of an evolutionary divergence between the poultry-associated and bovine-associated ST152 isolates that was due to polymorphisms in four core genome genes. The ST198 isolates recovered from dairy farms in the United States were phylogenetically distinct from those collected from human clinical cases with 66 core genome SNPs differentiating the two groups, but more isolates are needed to determine the significance of this distinction. Identification of S. Kentucky ST198 from dairy animals in the United States suggests that the presence of this pathogen should be monitored in food-producing animals. [ABSTRACT FROM AUTHOR]

In the United States Salmonella enterica subsp. enterica serotypes Kentucky and Cerro are frequently isolated from asymptomatic dairy cows. However, factors that contribute to colonization of the bovine gut by these two serotypes have not been identified. To investigate associations between Salmonella status and bacterial diversity, as well as the diversity of the microbial community in the dairy cow hindgut, the bacterial and archaeal communities of fecal samples from cows on a single dairy farm were determined by high-throughput sequencing of 16S rRNA gene amplicons. Fecal grab samples were collected from two Salmonella-positive cows and two Salmonella-negative cows on five sampling dates (n = 20 cows), and 16S rRNA gene amplicons from these samples were sequenced on the Illumina MiSeq platform. A high level of alpha (within) and beta diversity (between) samples demonstrated that microbial profiles of dairy cow hindguts are quite diverse. To determine whether Salmonella presence, sampling year, or sampling date explained a significant amount of the variation in microbial diversity, we performed constrained ordination analyses (distance based RDA) on the unifrac distance matrix produced with QIIME. Results indicated that there was not a significant difference in the microbial diversity associated with Salmonella presence (P > 0.05), but there were significant differences between sampling dates and years (Pseudo-F = 2.157 to 4.385, P < 0.05). Based on these data, it appears that commensal Salmonella infections with serotypes Cerro and Kentucky in dairy cows have little or no association with changes in the abundance of major bacterial groups in the hindgut. Rather, our results indicated that temporal dynamics and other undescribed parameters associated with them were the most influential drivers of the differences in microbial diversity and community structure in the dairy cow hindgut. [ABSTRACT FROM AUTHOR]

With the advent of more sophisticated models and increase in computational power, an ever-growing amount of information can be extracted from DNA sequence data. In particular, recent advances have allowed researchers to estimate the date of historical events for a group of interest including time to most recent common ancestor (TMRCA), dates of specific nodes in a phylogeny, and the date of divergence or speciation date. Here I use coalescent simulations and re-analyze an empirical dataset to illustrate the importance of taxon sampling, in particular, on correctly estimating such dates. I show that TMRCA of representatives of a single taxon is often not the same as divergence date due to issues such as incomplete lineage sorting. Of critical importance is when estimating divergence or speciation dates a representative from a different taxonomic lineage must be included in the analysis. Without considering these issues, studies may incorrectly estimate the times at which historical events occurred, which has profound impacts within both research and applied (e.g., those related to public health) settings. [ABSTRACT FROM AUTHOR]

Shiga toxins (Stx) are cytotoxins involved in severe human intestinal disease. These toxins are commonly found in Shigella dysenteriae serotype 1 and Shiga-toxin-producing Escherichia coli; however, the toxin genes have been found in other Shigella species. We identified 26 Shigella flexneri serotype 2 strains isolated by public health laboratories in the United States during 2001-2013, which encode the Shiga toxin 1a gene (stx[sub 1a]). These strains produced and released Stx1a as measured by cytotoxicity and neutralization assays using anti-Stx/Stx1a antiserum. The release of Stx1a into culture supernatants increased ≈100-fold after treatment with mitomycin C, suggesting that stx[sub 1a] is carried by a bacteriophage. Infectious phage were found in culture supernatants and increased ≈1,000-fold with mitomycin C. Whole-genome sequencing of several isolates and PCR analyses of all strains confirmed that stx[sub 1a] was carried by a lambdoid bacteriophage. Furthermore, all patients who reported foreign travel had recently been to Hispañiola, suggesting that emergence of these novel strains is associated with that region. [ABSTRACT FROM AUTHOR]

Salmonella enterica subsp. enterica serovar Heidelberg (S. Heidelberg) is one of the top serovars causing human salmonellosis. Recently, an antibiotic-resistant strain of this serovar was implicated in a large 2011 multistate outbreak resulting from consumption of contaminated ground turkey that involved 136 confirmed cases, with one death. In this study, we assessed the evolutionary diversity of 44 S. Heidelberg isolates using whole-genome sequencing (WGS) generated by the 454 GS FLX (Roche) platform. The isolates, including 30 with nearly indistinguishable (one band difference) Xbal pulsed-field gel electrophoresis patterns (JF6X01.0032, JF6X01.0058), were collected from various sources between 1982 and 2011 and included nine isolates associated with the 2011 outbreak. Additionally, we determined the complete sequence for the chromosome and three plasmids from a clinical isolate associated with the 2011 outbreak using the Pacific Biosciences (PacBio) system. Using single-nucleotide polymorphism (SNP) analyses, we were able to distinguish highly clonal isolates, including strains isolated at different times in the same year. The isolates from the recent 2011 outbreak clustered together with a mean SNP variation of only 17 SNPs. The S. Heidelberg isolates carried a variety of phages, such as prophage P22, P4, lambda-like prophage Gifsy-2, and the P2-like phage which carries the sopE1 gene, virulence genes including 62 pathogenicity, and 13 fimbrial markers and resistance plasmids of the incompatibility (Inc)I1, IncA/C, and IncHI2 groups. Twenty-one strains contained an IncX plasmid carrying a type IV secretion system. On the basis of the recent and historical isolates used in this study, our results demonstrated that, in addition to providing detailed genetic information for the isolates, WGS can identify SNP targets that can be utilized for differentiating highly clonal S. Heidelberg isolates. [ABSTRACT FROM PUBLISHER]

Background and Aims Reproductive character displacement (RCD) is often an important signature of reinforcement when partially cross-compatible taxa meet in secondary sympatry. In this study, floral evolution is examined during the Holocene range expansion of Clarkia xantiana subsp. parviflora from eastern Pleistocene refugia to a western zone of sympatry with its sister taxon, subsp. xantiana. Floral divergence between the two taxa is greater in sympatry than allopatry. The goal was to test an alternative hypothesis to reinforcement – that floral divergence of sympatric genotypes is simply a by-product of adaptation to pollination environments that differ between the allopatric and sympatric portions of the subspecies' range. Methods Floral trait data from two common garden studies were used to examine floral divergence between sympatric and allopatric regions and among phylogeographically defined lineages. In natural populations of C. x. parviflora, the magnitude of pollen limitation and reproductive assurance were quantified across its west-to-east range. Potted sympatric and allopatric genotypes were also reciprocally translocated between geographical regions to distinguish between the effects of floral phenotype versus contrasting pollinator environments on reproductive ecology. Key Results Sympatric populations are considerably smaller flowered with reduced herkogamy. Pollen limitation and the reproductive assurance value of selfing are greater in sympatric than in allopatric populations. Most significantly, reciprocal translocation experiments showed these differences in reproductive ecology cannot be attributed to contrasting pollinator environments between the sympatric and allopatric regions, but instead reflect the effects of flower size on pollinator attraction. Conclusions Floral evolution occurred during the westward range expansion of parviflora, particularly in the zone of sympatry with xantiana. No evidence was found that strongly reduced flower size in sympatric parviflora (and RCD between parviflora and xantiana) is due to adaptation to limited pollinator availability. Rather, floral divergence appears to have been driven by other factors, such as interactions with congenerics in secondary sympatry. [ABSTRACT FROM PUBLISHER]

Salmonella Newport has ranked in the top three Salmonella serotypes associated with foodborne outbreaks from 1995 to 2011 in the United States. In the current study, we selected 26 S. Newport strains isolated from diverse sources and geographic locations and then conducted 454 shotgun pyrosequencing procedures to obtain 16–24 × coverage of high quality draft genomes for each strain. Comparative genomic analysis of 28 S. Newport strains (including 2 reference genomes) and 15 outgroup genomes identified more than 140,000 informative SNPs. A resulting phylogenetic tree consisted of four sublineages and indicated that S. Newport had a clear geographic structure. Strains from Asia were divergent from those from the Americas. Our findings demonstrated that analysis using whole genome sequencing data resulted in a more accurate picture of phylogeny compared to that using single genes or small sets of genes. We selected loci around the mutS gene of S. Newport to differentiate distinct lineages, including those between invH and mutS genes at the 3′ end of Salmonella Pathogenicity Island 1 (SPI-1), ste fimbrial operon, and Clustered, Regularly Interspaced, Short Palindromic Repeats (CRISPR) associated-proteins (cas). These genes in the outgroup genomes held high similarity with either S. Newport Lineage II or III at the same loci. S. Newport Lineages II and III have different evolutionary histories in this region and our data demonstrated genetic flow and homologous recombination events around mutS. The findings suggested that S. Newport Lineages II and III diverged early in the serotype evolution and have evolved largely independently. Moreover, we identified genes that could delineate sublineages within the phylogenetic tree and that could be used as potential biomarkers for trace-back investigations during outbreaks. Thus, whole genome sequencing data enabled us to better understand the genetic background of pathogenicity and evolutionary history of S. Newport and also provided additional markers for epidemiological response. [ABSTRACT FROM AUTHOR]

The article lists the members of the editorial board of the periodical including Frank Davis, John Eimes and Kathleen Ferris.

Facile laboratory tools are needed to augment identification in contamination events to trace the contamination back to the source (traceback) of Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis). Understanding the evolution and diversity within and among outbreak strains is the first step towards this goal. To this end, we collected 106 new S. Enteriditis isolates within S. Enteriditis Pulsed-Field Gel Electrophoresis (PFGE) pattern JEGX01.0004 and close relatives, and determined their genome sequences. Sources for these isolates spanned food, clinical and environmental farm sources collected during the 2010 S. Enteritidis shell egg outbreak in the United States along with closely related serovars, S. Dublin, S. Gallinarum biovar Pullorum and S. Gallinarum. Despite the highly homogeneous structure of this population, S. Enteritidis isolates examined in this study revealed thousands of SNP differences and numerous variable genes (n = 366). Twenty-one of these genes from the lineages leading to outbreak-associated samples had nonsynonymous (causing amino acid changes) changes and five genes are putatively involved in known Salmonella virulence pathways. While chromosome synteny and genome organization appeared to be stable among these isolates, genome size differences were observed due to variation in the presence or absence of several phages and plasmids, including phage RE-2010, phage P125109, plasmid pSEEE3072_19 (similar to pSENV), plasmid pOU1114 and two newly observed mobile plasmid elements pSEEE1729_15 and pSEEE0956_35. These differences produced modifications to the assembled bases for these draft genomes in the size range of approximately 4.6 to 4.8 mbp, with S. Dublin being larger (~4.9 mbp) and S. Gallinarum smaller (4.55 mbp) when compared to S. Enteritidis. Finally, we identified variable S. Enteritidis genes associated with virulence pathways that may be useful markers for the development of rapid surveillance and typing methods, potentially aiding in traceback efforts during future outbreaks involving S. Enteritidis PFGE pattern JEGX01.0004. [ABSTRACT FROM AUTHOR]

The article offers an introduction to the issue's reprinted recollection of a mob's altercation with the Shaker community in Enfield, New Hampshire in May 1818, which was caused by the efforts mothers Eunice Hawley Chapman and Mary Marshall Dyer to retrieve their children from the Shakers.

The polychaete tubeworm Hydroides elegans (Haswell) is a biofouling species with relatively limited larval dispersal. Four highly polymorphic microsatellite loci were used to make inferences about the migration and global population structure of 137 individuals from seven sub-populations located in the Atlantic, Pacific, and Indian Oceans and in the Mediterranean Sea. The results of the genetic analyses suggest minimal population sub-structure (Fst = 0.09). Estimates of pairwise Fst and migration rates using the coalescent-based method of MIGRATE suggest that there is little genetic differentiation between certain populations. Variation in relatedness among pairs of populations is consistent with a suite of local and global factors. The most likely explanation for close genetic relatedness among certain populations over such vast distances is the regular and consistent transport of adults and larvae on the hulls and in the ballast water of ships, respectively. [ABSTRACT FROM AUTHOR]

Background: A variety of diseases are caused by chromosomal abnormalities such as aneuploidies (having an abnormal number of chromosomes), microdeletions, microduplications, and uniparental disomy. High density single nucleotide polymorphism (SNP) microarrays provide information on chromosomal copy number changes, as well as genotype (heterozygosity and homozygosity). SNP array studies generate multiple types of data for each SNP site, some with more than 100,000 SNPs represented on each array. The identification of different classes of anomalies within SNP data has been challenging. Results: We have developed SNPscan, a web-accessible tool to analyze and visualize high density SNP data. It enables researchers (1) to visually and quantitatively assess the quality of user-generated SNP data relative to a benchmark data set derived from a control population, (2) to display SNP intensity and allelic call data in order to detect chromosomal copy number anomalies (duplications and deletions), (3) to display uniparental isodisomy based on loss of heterozygosity (LOH) across genomic regions, (4) to compare paired samples (e.g. tumor and normal), and (5) to generate a file type for viewing SNP data in the University of California, Santa Cruz (UCSC) Human Genome Browser. SNPscan accepts data exported from Affymetrix Copy Number Analysis Tool as its input. We validated SNPscan using data generated from patients with known deletions, duplications, and uniparental disomy. We also inspected previously generated SNP data from 90 apparently normal individuals from the Centre d'Étude du Polymorphisme Humain (CEPH) collection, and identified three cases of uniparental isodisomy, four females having an apparently mosaic X chromosome, two mislabelled SNP data sets, and one microdeletion on chromosome 2 with mosaicism from an apparently normal female. These previously unrecognized abnormalities were all detected using SNPscan. The microdeletion was independently confirmed by fluorescence in situ hybridization, and a region of homozygosity in a UPD case was confirmed by sequencing of genomic DNA. Conclusion: SNPscan is useful to identify chromosomal abnormalities based on SNP intensity (such as chromosomal copy number changes) and heterozygosity data (including regions of LOH and some cases of UPD). The program and source code are available at the SNPscan website http://pevsnerlab.kennedykrieger.org/snpscan.htm. [ABSTRACT FROM AUTHOR]

The article offers information on the Genetic Analysis Workshop 14 (GAW14), held from September 7-10, 2004, in Noordwijkerhout, the Netherlands. The theme of the workshop was comparison of microsatellite and single-nucleotide polymorphism (SNP) markers for genome-wide scans and statistical methods that can exploit the information provided in such scans for linkage and association studies.

The ENGAGE project (http://www.engage-europe.eu/) was a collaboration between eight institutions across Europe. The aim was to boost the scientific cooperation to use whole genome sequencing (WGS) analysis in food safety and public health protection. ENGAGE focused on Escherichia coli (commensal E. coli) and different Salmonella spp. serotypes. A total of 3,360 genomes, 778 and 2,582 of E. coli and Salmonella, respectively, were produced. These genomes were stored and shared among partners in a temporary repository to be submitted to the European Nucleotide Archive by the end of the project. Generated genomes were used for benchmarking exercises to assess the possibility of replacing conventional typing with WGS for outbreak investigation. For the analysed strains, the benchmarking exercises showed that SPAdes assembly performed better than Velvet and that, by using different bioinformatics tools, WGS Salmonella serotyping and antimicrobial resistance genes detection, were largely in concordance with phenotypic data. Discrepancies were related to sequence quality and phenotype misclassification rather than to limitations of the bioinformatics tools. All partners were able to infer the expected phylogeny for the Salmonella and Campylobacter isolates in benchmarking exercises. Two WGS proficiency tests (assessing different genomic quality markers) were conducted among partners with satisfactory results. Guidelines including available bioinformatics tools and standard operating procedures (wet and dry lab) were prepared and posted online. Workshops, training courses and twinning programmes were conducted. The training focused on online, Galaxy‐based, and command line bioinformatics tools. To reach out beyond ENGAGE, an e‐learning course (17 videos) was developed and made available online. Several proof of concept projects were run and some outcomes published, e.g. the discovery of colistin resistance gene, mcr‐5. Overall, the project showed that laboratories without previous WGS experience need a period of time to implement and perform WGS for foodborne pathogens routine analysis. All developed material will remain available on the ENGAGE website. [ABSTRACT FROM AUTHOR]