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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]

We isolated and characterized six polymorphic microsatellite loci for the polychaete tubeworm, Hydroides elegans. Two additional loci were not reliably scorable and estimates of heterozygosity were obtained for the other six. In addition, cross-species amplification was successful for two loci using the congener H. hexagonus. Given that few microsatellite loci are available for polychaetes, these markers will be useful in assessing dispersal and gene flow in H. elegans and probably also other polychaetes. [ABSTRACT FROM AUTHOR]

Abstract Background Enriching environmental samples to increase the probability of detection has been standard practice throughout the history of microbiology. However, by its very nature, the process of enrichment creates a biased sample that may have unintended consequences for surveillance or resolving a pathogenic outbreak. With the advent of next-generation sequencing and metagenomic approaches, the possibility now exists to quantify enrichment bias at an unprecedented taxonomic breadth. Findings We investigated differences in taxonomic profiles of three enriched and unenriched tomato phyllosphere samples taken from three different tomato fields (n = 18). 16S rRNA gene meteganomes were created for each of the 18 samples using 454/Roche’s pyrosequencing platform, resulting in a total of 165,259 sequences. Significantly different taxonomic profiles and abundances at a number of taxonomic levels were observed between the two treatments. Although as many as 28 putative Salmonella sequences were detected in enriched samples, there was no significant difference in the abundance of Salmonella between enriched and unenriched treatments. Conclusions Our results illustrate that the process of enriching greatly alters the taxonomic profile of an environmental sample beyond that of the target organism. We also found evidence suggesting that enrichment may not increase the probability of detecting a target. In conclusion, our results further emphasize the need to develop metagenomics as a validated culture independent method for pathogen detection.

Abstract Background North American Agalinis Raf. species represent a taxonomically challenging group and there have been extensive historical revisions at the species, section, and subsection levels of classification. The genus contains many rare species, including the federally listed endangered species Agalinis acuta. In addition to evaluating the degree to which historical classifications at the section and subsection levels are supported by molecular data sampled from 79 individuals representing 29 Agalinis species, we assessed the monophyly of 27 species by sampling multiple individuals representing different populations of those species. Twenty-one of these species are of conservation concern in at least some part of their range. Results Phylogenetic relationships estimated using maximum likelihood analyses of seven chloroplast DNA loci (aligned length = 11 076 base pairs (bp) and the nuclear ribosomal DNA ITS (internal transcribed spacer) locus (733 bp); indicated no support for the historically recognized sections except for Section Erectae. Our results suggest that North American members of the genus comprise six major lineages, however we were not able to resolve branching order among many of these lineages. Monophyly of 24 of the 29 sampled species was supported based on significant branch lengths of and high bootstrap support for subtending branches. However, there was no statistical support for the monophyly of A. acuta with respect to Agalinis tenella and Agalinis decemloba. Although most species were supported, deeper relationships among many species remain ambiguous. Conclusion The North American Agalinis species sampled form a well supported, monophyletic group within the family Orobanchaceae relative to the outgroups sampled. Most hypotheses regarding section- and subsection-level relationships based on morphology were not supported and taxonomic revisions are warranted. Lack of support for monophyly of Agalinis acuta leaves the important question regarding its taxonomic status unanswered. Lack of resolution is potentially due to incomplete lineage sorting of ancestral polymorphisms among recently diverged species; however the gene regions examined did distinguish among almost all other species in the genus. Due to the important policy implications of this finding we are further evaluating the evolutionary distinctiveness of A. acuta using morphological data and loci with higher mutation rates.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Muruvanda, Rand, Pettengill and Pightling.)

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., Importance: This 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., Competing Interests: The authors declare no conflict of interest.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Pightling, Rand and Pettengill.)

Abstract: In 2017 and 2019, five outbreaks of infections from multiple strains of Salmonella linked to the consumption of whole, fresh Maradol papayas were reported in the United States, resulting in 325 ill persons. Traceback, laboratory, and epidemiologic evidence indicated papayas as the likely vehicle for each of these outbreaks and identified the source of papayas. State and U.S. Food and Drug Administration (FDA) laboratories recovered Salmonella from papaya samples from various points of distribution, including at import entry, and conducted serotyping, pulsed-field gel electrophoresis, and phylogenetic analyses of whole genome sequencing data. Federal and state partners led traceback investigations to determine the source of papayas. Four different suppliers of papayas were linked by traceback and laboratory results to five separate outbreaks of Salmonella infections associated with papayas. In 2017, multiple states tested papaya samples collected at retail, and Maryland and Virginia investigators recovered strains of Salmonella associated with one outbreak. FDA collected 183 papaya samples in 2017, and 11 samples yielded 62 isolates of Salmonella. Eleven serotypes of Salmonella were recovered from FDA papaya samples, and nine serotypes were closely related genetically by pulsed-field gel electrophoresis and whole genome sequencing to clinical isolates of four outbreaks, including the outbreak associated with positive state sample results. Four farms in Mexico were identified, and their names were released to the general public, retailers, and foreign authorities. In 2019, FDA collected 119 papaya samples, three of which yielded Salmonella; none yielded the 2019 outbreak strain. Investigators determined that papayas of interest had been sourced from a single farm in Campeche, Mexico, through traceback. This information was used to protect public health through public guidance, recalls, and import alerts and helped FDA collaborate with Mexican regulatory partners to enhance the food safety requirements for papayas imported from Mexico., (Published 2021 by the International Association for Food Protection Not subject to U.S. Copyright. This is an open access article.)

Staphylococcus aureus bacteria are ranked among the top five foodborne pathogens in the United States. Here, we report the draft genome sequences of 62 S. aureus isolates that originated from the manufacturing environment of an Illinois bakery and were associated with outbreaks between 2010 and 2011 in the United States.

In 2017, the US Food and Drug Administration investigated the sources of multiple outbreaks of salmonellosis. Epidemiologic and traceback investigations identified Maradol papayas as the suspect vehicles. During the investigations, the genomes of 55 Salmonella enterica that were isolated from papaya samples were sequenced. Serovar assignments and phylogenetic analysis placed the 55 isolates into ten distinct groups, each representing a different serovar. Within-serovar SNP differences are generally between 0 and 20 SNPs, while the median between-serovar distance is 51 812 SNPs. We observed two groups with SNP distances between 21 and 100 SNPs. These relatively large within-serovar SNP distances may indicate that the isolates represent either diverse populations or multiple, genetically distinct subpopulations. Further inspection of these cases with traceback evidence allowed us to identify an 11th population. We observed that high levels of genomic diversity from individual firms is possible, with one firm yielding five of the ten serovars. Also, high levels of diversity are possible within small geographic regions, as five of the serovars were isolated from papayas that originated from farms located in Armería and Tecomán, Colima. In addition, we identified AMR genes that are present in three of the serovars studied here ( aph(3')-lb, aph(6)-ld, tet(C), fosA7, and qnrB19 ) and we detected the presence of the plasmid IncHI2A among S . Urbana isolates.

Abstract: Antimicrobial-resistant bacteria are a major public health problem. Of particular importance in the context of food safety is the prevalence of antimicrobial resistance (AMR) genes within nontyphoidal Salmonella, which is a leading bacterial cause of foodborne disease. We determined the prevalence of AMR genes across a very large number of Salmonella genomes (n = 25,647) collected from isolates from 16 common food sources. The average percentage of isolates from nonanimal foods, such as fruit, nuts and seeds, and vegetables, harboring at least one AMR gene was only marginally lower (72%) than that observed in isolates from animal foods such as beef, chicken, turkey, and pork (74%). This high prevalence of AMR genes was primarily driven by the high prevalence of aminoglycoside resistance genes in nearly all food isolates; genes for resistance to tetracycline and sulfonamide also were highly prevalent. However, evaluation of the number of genes per isolate revealed that the prevalence of AMR genes was higher in animal food isolates than in nonanimal food isolates (P = 0.018). A random forest analysis provided evidence that within a given serovar, resistance gene profiles differed according to isolate food source. AMR gene profiles could be used to correctly predict the food of origin for 71% of the isolates, but success differed according to serovar. This information can help inform AMR risk assessments of food commodities and refine processes for targeting interventions to limit the spread of AMR through the food supply., (Published 2020 by the International Association for Food Protection Not subject to U.S. Copyright. This is an open access.)

Background: Using phylogenomic analysis tools for tracking pathogens has become standard practice in academia, public health agencies, and large industries. Using the same raw read genomic data as input, there are several different approaches being used to infer phylogenetic tree. These include many different SNP pipelines, wgMLST approaches, k-mer algorithms, whole genome alignment and others; each of these has advantages and disadvantages, some have been extensively validated, some are faster, some have higher resolution. A few of these analysis approaches are well-integrated into the regulatory process of US Federal agencies (e.g. the FDA's SNP pipeline for tracking foodborne pathogens). However, despite extensive validation on benchmark datasets and comparison with other pipelines, we lack methods for fully exploring the effects of multiple parameter values in each pipeline that can potentially have an effect on whether the correct phylogenetic tree is recovered., Results: To resolve this problem, we offer a program, TreeToReads, which can generate raw read data from mutated genomes simulated under a known phylogeny. This simulation pipeline allows direct comparisons of simulated and observed data in a controlled environment. At each step of these simulations, researchers can vary parameters of interest (e.g., input tree topology, amount of sequence divergence, rate of indels, read coverage, distance of reference genome, etc) to assess the effects of various parameter values on correctly calling SNPs and reconstructing an accurate tree., Conclusions: Such critical assessments of the accuracy and robustness of analytical pipelines are essential to progress in both research and applied settings.

Three multistate outbreaks between 2014 and 2016, involving case patients in and outside the United States, were linked to stone fruit, caramel apples, and packaged leafy green salad contaminated with Listeria monocytogenes singleton sequence type 382 (ST382), a serotype IVb-v1 clone with limited genomic divergence. Isolates from these outbreaks and other ST382 isolates not associated with these outbreaks were analyzed by whole-genome sequencing (WGS) analysis. The primary differences among ST382 strains were single nucleotide polymorphisms (SNPs). WGS analysis differentiated ST382 from a clonal complex 1 outbreak strain co-contaminating the caramel apples. WGS clustered food, environmental, and clinical isolates within each outbreak, and also differentiated among the three outbreak strains and epidemiologically unrelated ST382 isolates, which were indistinguishable by pulsed-field gel electrophoresis. ST382 appeared to be an emerging clone that began to diverge from its ancestor approximately 32 years before 2016. We estimated that there was 1.29 nucleotide substitution per genome (2.94 Mbp) per year for this clone., (Copyright © 2017 Chen et al.)

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., Competing Interests: The authors have declared that no competing interests exist.

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.

The advent of next-generation sequencing (NGS) has revolutionised public health microbiology. Given the potential impact of NGS, it is paramount to ensure standardisation of 'wet' laboratory and bioinformatic protocols and promote comparability of methods employed by different laboratories and their outputs. Therefore, one of the ambitious goals of the Global Microbial Identifier (GMI) initiative (http://www.globalmicrobialidentifier.org/) has been to establish a mechanism for inter-laboratory NGS proficiency testing (PT). This report presents findings from the survey recently conducted by Working Group 4 among GMI members in order to ascertain NGS end-use requirements and attitudes towards NGS PT. The survey identified the high professional diversity of laboratories engaged in NGS-based public health projects and the wide range of capabilities within institutions, at a notable range of costs. The priority pathogens reported by respondents reflected the key drivers for NGS use (high burden disease and 'high profile' pathogens). The performance of and participation in PT was perceived as important by most respondents. The wide range of sequencing and bioinformatics practices reported by end-users highlights the importance of standardisation and harmonisation of NGS in public health and underpins the use of PT as a means to assuring quality. The findings of this survey will guide the design of the GMI PT program in relation to the spectrum of pathogens included, testing frequency and volume as well as technical requirements. The PT program for external quality assurance will evolve and inform the introduction of NGS into clinical and public health microbiology practice in the post-genomic era.

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.

Phage typing has been used for the epidemiological surveillance of Salmonella enterica serovar Enteritidis for over 2 decades. However, knowledge of the genetic and evolutionary relationships between phage types is very limited, making differences difficult to interpret. Here, single nucleotide polymorphisms (SNPs) identified from whole-genome comparisons were used to determine the relationships between some S. Enteritidis phage types (PTs) commonly associated with food-borne outbreaks in the United States. Emphasis was placed on the predominant phage types PT8, PT13a, and PT13 in North America. With >89,400 bp surveyed across 98 S. Enteritidis isolates representing 14 distinct phage types, 55 informative SNPs were discovered within 23 chromosomally anchored loci. To maximize the discriminatory and evolutionary partitioning of these highly homogeneous strains, sequences comprising informative SNPs were concatenated into a single combined data matrix and subjected to phylogenetic analysis. The resultant phylogeny allocated most S. Enteritidis isolates into two distinct clades (clades I and II) and four subclades. Synapomorphic (shared and derived) sets of SNPs capable of distinguishing individual clades/subclades were identified. However, individual phage types appeared to be evolutionarily disjunct when mapped to this phylogeny, suggesting that phage typing may not be valid for making phylogenetic inferences. Furthermore, the set of SNPs identified here represents useful genetic markers for strain differentiation of more clonal S. Enteritidis strains and provides core genotypic markers for future development of a SNP typing scheme with S. Enteritidis.

Here, we report draft genome sequences of 26 isolates of Salmonella enterica subsp. enterica, representing eight serotypes, which were isolated from cows in a Pennsylvania dairy herd, the farm on which they were reared, and the associated off-site heifer-raising facility over an 8-year sampling period.

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.

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&#95;19 (similar to pSENV), plasmid pOU1114 and two newly observed mobile plasmid elements pSEEE1729&#95;15 and pSEEE0956&#95;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 enterica subsp. enterica serovar Enteritidis is a common food-borne pathogen, often associated with shell eggs and poultry. Here, we report draft genomes of 21 S. Enteritidis strains associated with or related to the U.S.-wide 2010 shell egg recall. Eleven of these genomes were from environmental isolates associated with the egg outbreak, and 10 were reference isolates from previous years, unrelated to the outbreak. The whole-genome sequence data for these 21 human pathogen strains are being released in conjunction with the newly formed 100K Genome Project.

This article documents the addition of 283 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Agalinis acuta; Ambrosia artemisiifolia; Berula erecta; Casuarius casuarius; Cercospora zeae-maydis; Chorthippus parallelus; Conyza canadensis; Cotesia sesamiae; Epinephelus acanthistius; Ficedula hypoleuca; Grindelia hirsutula; Guadua angustifolia; Leucadendron rubrum; Maritrema novaezealandensis; Meretrix meretrix; Nilaparvata lugens; Oxyeleotris marmoratus; Phoxinus neogaeus; Pristomyrmex punctatus; Pseudobagrus brevicorpus; Seiridium cardinale; Stenopsyche marmorata; Tetranychus evansi and Xerus inauris. These loci were cross-tested on the following species: Agalinis decemloba; Agalinis tenella; Agalinis obtusifolia; Agalinis setacea; Agalinis skinneriana; Cercospora zeina; Cercospora kikuchii; Cercospora sorghi; Mycosphaerella graminicola; Setosphaeria turcica; Magnaporthe oryzae; Cotesia flavipes; Cotesia marginiventris; Grindelia Xpaludosa; Grindelia chiloensis; Grindelia fastigiata; Grindelia lanceolata; Grindelia squarrosa; Leucadendron coniferum; Leucadendron salicifolium; Leucadendron tinctum; Leucadendron meridianum; Laodelphax striatellus; Sogatella furcifera; Phoxinus eos; Phoxinus rigidus; Phoxinus brevispinosus; Phoxinus bicolor; Tetranychus urticae; Tetranychus turkestani; Tetranychus ludeni; Tetranychus neocaledonicus; Tetranychus amicus; Amphitetranychus viennensis; Eotetranychus rubiphilus; Eotetranychus tiliarium; Oligonychus perseae; Panonychus citri; Bryobia rubrioculus; Schizonobia bundi; Petrobia harti; Xerus princeps; Spermophilus tridecemlineatus and Sciurus carolinensis., (© 2009 Blackwell Publishing Ltd.)

Specialized, physician-owned cardiac hospitals have grown rapidly. Physicians have also expanded their capability to provide cardiovascular diagnostic services in their offices. In this paper we consider evidence of errors in Medicare's prices for hospital care and physician services and discuss ways to improve the accuracy of those prices. We find that recent proposals to change the inpatient prospective payment system would help dampen hospitals' financial incentives to favor some kinds of patients and related investments. For the physician fee schedule, we suggest that the Centers for Medicare and Medicaid Services (CMS) review the accuracy of prices for high-growth diagnostic services.

The data provided to the Genetic Analysis Workshop 14 (GAW 14) was the result of a collaboration among several different groups, catalyzed by Elizabeth Pugh from The Center for Inherited Disease Research (CIDR) and the organizers of GAW 14, Jean MacCluer and Laura Almasy. The DNA, phenotypic characterization, and microsatellite genomic survey were provided by the Collaborative Study on the Genetics of Alcoholism (COGA), a nine-site national collaboration funded by the National Institute of Alcohol and Alcoholism (NIAAA) and the National Institute of Drug Abuse (NIDA) with the overarching goal of identifying and characterizing genes that affect the susceptibility to develop alcohol dependence and related phenotypes. CIDR, Affymetrix, and Illumina provided single-nucleotide polymorphism genotyping of a large subset of the COGA subjects. This article briefly describes the dataset that was provided.

The Medicare program initiated prospective payment for inpatient hospital services in 1983. Although the payment system has achieved many of its goals, changes in the health care market and the public nature of the program will continue to present both challenges and opportunities for improvement. Looking forward, policymakers must consider how to balance paying accurately for services with using Medicare to achieve broader policy objectives. Paying for new technologies, responding to market segmentation and specialization, and encouraging quality improvement must also be addressed. To successfully navigate these issues, policymakers and program administrators need accurate and timely information.

The number of hospital closures increased substantially after the implementation of Medicare's Prospective Payment System (PPS). This acceleration in closures raised a number of concerns over current payment policies and their impact on access. This paper investigates hospital closures that occurred in 1985 through 1988. A hospital's financial status and mission or community standing were found to be determinants of hospital closure. Closed hospitals are much less likely to be publicly owned but more likely to offer fewer facilities and services, and have fewer cases. This may suggest that the patients directly affected by the closure can be absorbed by other hospitals or other nonhospital providers. Profitability is associated with the Medicare case-mix index and the share of Medicare patients. The findings also suggest that the case mix index may be rewarding some small hospitals in excess of the costs attributable to case-mix. For both urban and rural hospitals, a low share of Medicare patients increased the risk of hospital closure, independently of the relationship between Medicare share and profit. The share of Medicare patients also affected closure indirectly, through its effects on profit. Competition appears to affect the odds of closure through its effects on the number of cases. In addition, hospitals in areas with small or declining population are more at risk than other hospitals in both urban and rural areas.

There is widespread interest in the development of a measure of hospital output. This paper describes the problem of measuring the expected cost of the mix of inpatient cases treated in a hospital (hospital case-mix) and a general approach to its solution. The solution is based on a set of homogeneous groups of patients, defined by a patient classification system, and a set of estimated relative cost weights corresponding to the patient categories. This approach is applied to develop a summary measure of the expected relative costliness of the mix of Medicare patients treated in 5,576 participating hospitals. The Medicare case-mix index is evaluated by estimating a hospital average cost function. This provides a direct test of the hypothesis that the relationship between Medicare case-mix and Medicare cost per case is proportional. The cost function analysis also provides a means of simulating the effects of classification error on our estimate of this relationship. Our results indicate that this general approach to measuring hospital case-mix provides a valid and robust measure of the expected cost of a hospital's case-mix.