From Poverty to Economic Independence: An Examination of Factors Contributing to Success and Self-Sufficiency among Black Male Family Self-Sufficiency Program Participants

The purpose of this study was to acquire accurate information concerning the motivations and methods utilized by Black males who have successfully achieved economic independence, as well as the ways in which they maintain their economic independence. The scope of this study was to examine adult Black males who had successfully completed a Family Self-Sufficiency program and are currently economically independent. Using a phenomenological methodology, their experiences and a description of the relationship connecting the problem statement, research question, theory and study design was completed. This study revealed perceptions that were contrary to popular mainstream beliefs about impoverished Black males. Family and an intrinsic motivation to succeed were echoed by the participants as the driver that leads them to economic independence. This study found three major implications; the first implication was participants expressed a belief that discrimination is a legitimate problem which can hinder one’s opportunities for employment and upward mobility. The second implication was that participants believe they are viewed as threatening and dangerous, especially to law enforcement. The last implication of this study was that the participants were conservative in their ideological perspective. Though their political affiliation was Democrat, ideologically their views were fundamentally conservative. Most importantly, these participants did not allow societal hindrance to deter them from their ultimate goal of economic independence for themselves as well as their families

Metagenomics: The Next Culture-Independent Game Changer

A trend towards the abandonment of obtaining pure culture isolates in frontline laboratories is at a crossroads with the ability of public health agencies to perform their basic mandate of foodborne disease surveillance and response. The implementation of culture-independent diagnostic tests (CIDTs) including nucleic acid and antigen-based assays for acute gastroenteritis is leaving public health agencies without laboratory evidence to link clinical cases to each other and to food or environmental substances. This limits the efficacy of public health epidemiology and surveillance as well as outbreak detection and investigation. Foodborne outbreaks have the potential to remain undetected or have insufficient evidence to support source attribution and may inadvertently increase the incidence of foodborne diseases. Next-generation sequencing of pure culture isolates in clinical microbiology laboratories has the potential to revolutionize the fields of food safety and public health. Metagenomics and other ‘omics’ disciplines could provide the solution to a cultureless future in clinical microbiology, food safety and public health. Data mining of information obtained from metagenomics assays can be particularly useful for the identification of clinical causative agents or foodborne contamination, detection of AMR and/or virulence factors, in addition to providing high-resolution subtyping data. Thus, metagenomics assays may provide a universal test for clinical diagnostics, foodborne pathogen detection, subtyping and investigation. This information has the potential to reform the field of enteric disease diagnostics and surveillance and also infectious diseases as a whole. The aim of this review will be to present the current state of CIDTs in diagnostic and public health laboratories as they relate to foodborne illness and food safety. Moreover, we will also discuss the diagnostic and subtyping utility and concomitant bias limitations of metagenomics and comparable detection techniques in clinical microbiology, food and public health laboratories. Early advances in the discipline of metagenomics, however, have indicated noteworthy challenges. Through forthcoming improvements in sequencing technology and analytical pipelines among others, we anticipate that within the next decade, detection and characterization of pathogens via metagenomics-based workflows will be implemented in routine usage in diagnostic and public health laboratories

Cronobacter sakazakii clinical isolates overcome host barriers and evade the immune response

Cronobacter sakazakii is the most frequently clinically isolated species of the Cronobacter genus. However the virulence factors of C. sakazakii including their ability to overcome host barriers remains poorly studied. In this study, ten clinical isolates of C. sakazakii were assessed for their ability to invade and translocate through human microvascular endothelial cells (HBMEC). Their ability to avoid phagocytosis in human macrophages U937 and human brain microglial cells was investigated. Additionally, they were tested for serum sensitivity and the presence of the Cronobacter plasminogen activation gene (cpa) gene, which is reported to confer serum resistance. Our data showed that the clinical C. sakazakii strains invaded and translocated through Caco-2 and HBMEC cell lines and some strains showed significantly higher levels of invasion and translocation. Moreover, C. sakazakii was able to persist and even multiply in phagocytic macrophage and microglial cells. All strains, except one, were able to withstand human serum exposure, the single serum sensitive strain was also the only one which did not encode for the cpa gene. These results demonstrate that C. sakazakii clinical host immune response indicating their capacity to cause diseases such as necrotizing enterocolitis (NEC) and meningitis. Our data showed for the first time the ability of C. sakazakii clinical isolates to survive and multiply within human microglial cells. Additionally, it was shown that C. sakazakii clinical strains have the capacity to translocate through the Caco-2 and HBMEC cell lines paracellularly

Phylogenomic Analysis of Salmonella enterica subsp. enterica Serovar Bovismorbificans from Clinical and Food Samples Using Whole Genome Wide Core Genes and kmer Binning Methods to Identify Two Distinct Polyphyletic Genome Pathotypes

Salmonella enterica subsp. enterica serovar Bovismorbificans has caused multiple outbreaks involving the consumption of produce, hummus, and processed meat products worldwide. To elucidate the intra-serovar genomic structure of S. Bovismorbificans, a core-genome analysis with 2690 loci (based on 150 complete genomes representing Salmonella enterica serovars developed as part of this study) and a k-mer-binning based strategy were carried out on 95 whole genome sequencing (WGS) assemblies from Swiss, Canadian, and USA collections of S. Bovismorbificans strains from foodborne infections. Data mining of a digital DNA tiling array of legacy SARA and SARB strains was conducted to identify near-neighbors of S. Bovismorbificans. The core genome analysis and the k-mer-binning methods identified two polyphyletic clusters, each with emerging evolutionary properties. Four STs (2640, 142, 1499, and 377), which constituted the majority of the publicly available WGS datasets from >260 strains analyzed by k-mer-binning based strategy, contained a conserved core genome backbone with a different evolutionary lineage as compared to strains comprising the other cluster (ST150). In addition, the assortment of genotypic features contributing to pathogenesis and persistence, such as antimicrobial resistance, prophage, plasmid, and virulence factor genes, were assessed to understand the emerging characteristics of this serovar that are relevant clinically and for food safety concerns. The phylogenomic profiling of polyphyletic S. Bovismorbificans in this study corresponds to intra-serovar variations observed in S. Napoli and S. Newport serovars using similar high-resolution genomic profiling approaches and contributes to the understanding of the evolution and sequence divergence of foodborne Salmonellae. These intra-serovar differences may have to be thoroughly understood for the accurate classification of foodborne Salmonella strains needed for the uniform development of future food safety mitigation strategies

Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria

The persuasiveness of genomic evidence has pressured scientific agencies to supplement or replace well-established methodologies to inform public health and food safety decision-making. This study of 52 epidemiologically defined Listeria monocytogenes isolates, collected between 1981 and 2011, including nine outbreaks, was undertaken (1) to characterize their phylogenetic relationship at finished genome-level resolution, (2) to elucidate the underlying genetic diversity within an endemic subtype, CC8, and (3) to re-evaluate the genetic relationship and epidemiology of a CC8-delimited outbreak in Canada in 2008. Genomes representing Canadian Listeria outbreaks between 1981 and 2010 were closed and manually annotated. Single nucleotide variants (SNVs) and horizontally acquired traits were used to generate phylogenomic models. Phylogenomic relationships were congruent with classical subtyping and epidemiology, except for CC8 outbreaks, wherein the distribution of SNV and prophages revealed multiple co-evolving lineages. Chronophyletic reconstruction of CC8 evolution indicates that prophage-related genetic changes among CC8 strains manifest as PFGE subtype reversions, obscuring the relationship between CC8 isolates, and complicating the public health interpretation of subtyping data, even at maximum genome resolution. The size of the shared genome interrogated did not change the genetic relationship measured between highly related isolates near the tips of the phylogenetic tree, illustrating the robustness of these approaches for routine public health applications where the focus is recent ancestry. The possibility exists for temporally and epidemiologically distinct events to appear related even at maximum genome resolution, highlighting the continued importance of epidemiological evidence

Occurrence, characterization, and potential predictors of verotoxigenic Escherichia coli, Listeria monocytogenes, and Salmonella in surface water used for produce irrigation in the Lower Mainland of British Columbia, Canada.

Produce has become a major source of foodborne illness, and may become contaminated through surface water irrigation. The objectives of this study were to (i) determine the frequency of verotoxigenic E. coli (VTEC), Listeria monocytogenes, and Salmonella in surface waters used for irrigation in the Lower Mainland of British Columbia, (ii) assess the suitability of fecal coliforms and generic E. coli as hygiene indicators, and (iii) investigate the correlations of environmental factors with pathogen occurrence. Water samples were collected semi-monthly for 18 months from seven irrigation ditches across the Serpentine and Sumas watersheds. VTEC colonies on water filters were detected using a verotoxin colony immunoblot, and the presence of virulence genes vt1 and vt2 was ascertained via multiplex PCR. Detection of L. monocytogenes and Salmonella was completed using standard, Health Canada Compendium of Analytical Methods. Fecal coliforms and generic E. coli were enumerated by 3M™ Petrifilm™ and filtration methods, and meteorological and geographic data were collected from government records. VTEC, L. monocytogenes, and Salmonella were detected in 4.93%, 10.3%, and 2.69% of 223 samples, respectively. L. monocytogenes occurrence was greatest in the Serpentine watershed (χ2; p < 0.05), and was most common during the winter and fall (Fisher exact test; p < 0.05). Site dependence of VTEC and Salmonella occurrence was observed within watersheds (Fisher's exact test; p < 0.10). Pathogen occurrence correlated with fecal coliform counts (r = 0.448), while VTEC occurrence also correlated with precipitation over the five days before sampling (r = 0.239). The density of upstream livestock correlated with VTEC (rs = 0.812), and L. monocytogenes (rs = 0.841) detection. These data show that foodborne pathogens are present in the waters used for irrigation in the Lower Mainland of British Columbia, but their frequency may depend on spatial and temporal factors

Choice of Reference Sequence and Assembler for Alignment of <i>Listeria monocytogenes</i> Short-Read Sequence Data Greatly Influences Rates of Error in SNP Analyses

<div><p>The wide availability of whole-genome sequencing (WGS) and an abundance of open-source software have made detection of single-nucleotide polymorphisms (SNPs) in bacterial genomes an increasingly accessible and effective tool for comparative analyses. Thus, ensuring that real nucleotide differences between genomes (<i>i.e.</i>, true SNPs) are detected at high rates and that the influences of errors (such as false positive SNPs, ambiguously called sites, and gaps) are mitigated is of utmost importance. The choices researchers make regarding the generation and analysis of WGS data can greatly influence the accuracy of short-read sequence alignments and, therefore, the efficacy of such experiments. We studied the effects of some of these choices, including: i) depth of sequencing coverage, ii) choice of reference-guided short-read sequence assembler, iii) choice of reference genome, and iv) whether to perform read-quality filtering and trimming, on our ability to detect true SNPs and on the frequencies of errors. We performed benchmarking experiments, during which we assembled simulated and real <i>Listeria monocytogenes</i> strain 08-5578 short-read sequence datasets of varying quality with four commonly used assemblers (BWA, MOSAIK, Novoalign, and SMALT), using reference genomes of varying genetic distances, and with or without read pre-processing (<i>i.e.</i>, quality filtering and trimming). We found that assemblies of at least 50-fold coverage provided the most accurate results. In addition, MOSAIK yielded the fewest errors when reads were aligned to a nearly identical reference genome, while using SMALT to align reads against a reference sequence that is ∼0.82% distant from 08-5578 at the nucleotide level resulted in the detection of the greatest numbers of true SNPs and the fewest errors. Finally, we show that whether read pre-processing improves SNP detection depends upon the choice of reference sequence and assembler. In total, this study demonstrates that researchers should test a variety of conditions to achieve optimal results.</p></div