Genomic differences between nasal Staphylococcus aureus from hog slaughterhouse workers and their communities.

New human pathogens can emerge from the livestock-human interface and spread into human populations through many pathways including livestock products. Occupational contact with livestock is a risk factor for exposure to those pathogens and may cause further spreading of those pathogens in the community. The current study used whole genome sequencing to explore nasal Staphylococcus aureus obtained from hog slaughterhouse workers and their community members, all of whom resided in a livestock-dense region in rural North Carolina. Sequence data were analyzed for lineage distribution, pathogenicity-related genomic features, and mobile genetic elements. We observed evidence of nasal S. aureus differences between hog workers and non-workers. Nasal S. aureus from hog workers showed a greater lineage diversity than nasal S. aureus from community residents. Hog worker isolates were less likely to carry the φSa3 prophage and human-specific immune evasion cluster genes than community resident isolates (φSa3 prophage: 54.5% vs. 91.7%, Benjamini-Hochberg (BH) corrected p = 0.035; immune evasion cluster genes: 66.7% vs. 100%, BH p = 0.021). Hog worker isolates had a lower prevalence and diversity of enterotoxins than community resident isolates, particularly lacking the enterotoxin gene cluster (39.4% vs. 70.8%, BH p = 0.125). Moreover, hog worker isolates harbored more diverse antibiotic resistance genes, with a higher prevalence of carriage of multiple resistance genes, than community resident isolates (75.8% vs. 29.2%, BH p = 0.021). Phylogenetic analysis of all ST5 isolates, the most abundant lineage in the collection, further supported separation of isolates from hog workers and non-workers. Together, our observations suggest impact of occupational contact with livestock on nasal S. aureus colonization and highlight the need for further research on the complex epidemiology of S. aureus at the livestock-human interface

Low-Cost HIV-1 Diagnosis and Quantification in Dried Blood Spots by Real Time PCR

BACKGROUND: Rapid and cost-effective methods for HIV-1 diagnosis and viral load monitoring would greatly enhance the clinical management of HIV-1 infected adults and children in limited-resource settings. Recent recommendations to treat perinatally infected infants within the first year of life are feasible only if early diagnosis is routinely available. Dried blood spots (DBS) on filter paper are an easy and convenient way to collect and transport blood samples. A rapid and cost effective method to diagnose and quantify HIV-1 from DBS is urgently needed to facilitate early diagnosis of HIV-1 infection and monitoring of antiretroviral therapy. METHODS AND FINDINGS: We have developed a real-time LightCycler (rtLC) PCR assay to detect and quantify HIV-1 from DBS. HIV-1 RNA extracted from DBS was amplified in a one-step, single-tube system using primers specific for long-terminal repeat sequences that are conserved across all HIV-1 clades. SYBR Green dye was used to quantify PCR amplicons and HIV-1 RNA copy numbers were determined from a standard curve generated using serially diluted known copies of HIV-1 RNA. This assay detected samples across clades, has a dynamic range of 5 log(10), and %CV <8% up to 4 log(10) dilution. Plasma HIV-1 RNA copy numbers obtained using this method correlated well with the Roche Ultrasensitive (r = 0.91) and branched DNA (r = 0.89) assays. The lower limit of detection (95%) was estimated to be 136 copies. The rtLC DBS assay was 2.5 fold rapid as well as 40-fold cheaper when compared to commercial assays. Adaptation of the assay into other real-time systems demonstrated similar performance. CONCLUSIONS: The accuracy, reliability, genotype inclusivity and affordability, along with the small volumes of blood required for the assay suggest that the rtLC DBS assay will be useful for early diagnosis and monitoring of pediatric HIV-1 infection in resource-limited settings

Application of two machine learning algorithms to genetic association studies in the presence of covariates

BACKGROUND: Population-based investigations aimed at uncovering genotype-trait associations often involve high-dimensional genetic polymorphism data as well as information on multiple environmental and clinical parameters. Machine learning (ML) algorithms offer a straightforward analytic approach for selecting subsets of these inputs that are most predictive of a pre-defined trait. The performance of these algorithms, however, in the presence of covariates is not well characterized. METHODS AND RESULTS: In this manuscript, we investigate two approaches: Random Forests (RFs) and Multivariate Adaptive Regression Splines (MARS). Through multiple simulation studies, the performance under several underlying models is evaluated. An application to a cohort of HIV-1 infected individuals receiving anti-retroviral therapies is also provided. CONCLUSION: Consistent with more traditional regression modeling theory, our findings highlight the importance of considering the nature of underlying gene-covariate-trait relationships before applying ML algorithms, particularly when there is potential confounding or effect mediation

Genomic differences between nasal <i>Staphylococcus aureus</i> from hog slaughterhouse workers and their communities - Fig 3

<p>Numbers of (A) staphylococcal enterotoxins and (B) antibiotic resistance genes in the genomes of the nasal <i>S</i>. <i>aureus</i> of hog workers, their household members, and community residents, respectively.</p

Maximum likelihood phylogeny of the 19 ST5 <i>S</i>. <i>aureus</i> isolates sequenced in this study.

<p>Published genome sequences of 6 ST5 strains (502A, ECT-R2, ED98, Mu3, Mu50, N315) and 2 ST105 strains (JH1 and JH9) were included for comparison, with the country of report and host (H, human; C, chicken) for each reference strain shown in parenthesis (details in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193820#pone.0193820.s006" target="_blank">S1 Table</a>). Color dots represent host groups in this study (red, community residents; green, household members; blue, hog workers). <i>spa</i> types and MGE types are listed on the right of the phylogeny. Subgroups a and b include isolates of certain relatedness, with subgroup b coming from the same household. Asterisk denotes a ST5 MRSA (SCC<i>mec</i> IV) isolate.</p

Genomic differences between nasal <i>Staphylococcus aureus</i> from hog slaughterhouse workers and their communities

<div><p>New human pathogens can emerge from the livestock-human interface and spread into human populations through many pathways including livestock products. Occupational contact with livestock is a risk factor for exposure to those pathogens and may cause further spreading of those pathogens in the community. The current study used whole genome sequencing to explore nasal <i>Staphylococcus aureus</i> obtained from hog slaughterhouse workers and their community members, all of whom resided in a livestock-dense region in rural North Carolina. Sequence data were analyzed for lineage distribution, pathogenicity-related genomic features, and mobile genetic elements. We observed evidence of nasal <i>S</i>. <i>aureus</i> differences between hog workers and non-workers. Nasal <i>S</i>. <i>aureus</i> from hog workers showed a greater lineage diversity than nasal <i>S</i>. <i>aureus</i> from community residents. Hog worker isolates were less likely to carry the φSa3 prophage and human-specific immune evasion cluster genes than community resident isolates (φSa3 prophage: 54.5% vs. 91.7%, Benjamini-Hochberg (BH) corrected <i>p</i> = 0.035; immune evasion cluster genes: 66.7% vs. 100%, BH <i>p</i> = 0.021). Hog worker isolates had a lower prevalence and diversity of enterotoxins than community resident isolates, particularly lacking the enterotoxin gene cluster (39.4% vs. 70.8%, BH <i>p</i> = 0.125). Moreover, hog worker isolates harbored more diverse antibiotic resistance genes, with a higher prevalence of carriage of multiple resistance genes, than community resident isolates (75.8% vs. 29.2%, BH <i>p</i> = 0.021). Phylogenetic analysis of all ST5 isolates, the most abundant lineage in the collection, further supported separation of isolates from hog workers and non-workers. Together, our observations suggest impact of occupational contact with livestock on nasal <i>S</i>. <i>aureus</i> colonization and highlight the need for further research on the complex epidemiology of <i>S</i>. <i>aureus</i> at the livestock-human interface.</p></div

Genomic differences between nasal <i>Staphylococcus aureus</i> from hog slaughterhouse workers and their communities - Fig 1

<p><b>Profiles of (A) virulence factors and (B) antimicrobial resistance genes for the 76 sequenced nasal <i>S</i>. <i>aureus</i> isolates.</b> Each row represents one isolate from an individual, with the color bar on the left side indicating host groups (red, community residents; green, household members; blue, hog workers) and the texts on the right side indicating lineages.</p