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1.  A Host-Based RT-PCR Gene Expression Signature to Identify Acute Respiratory Viral Infection 
Science translational medicine  2013;5(203):203ra126.
Improved ways to diagnose acute respiratory viral infections could decrease inappropriate antibacterial use and serve as a vital triage mechanism in the event of a potential viral pandemic. Measurement of the host response to infection is an alternative to pathogen-based diagnostic testing and may improve diagnostic accuracy. We have developed a host-based assay with a reverse transcription polymerase chain reaction (RT-PCR) TaqMan low-density array (TLDA) platform for classifying respiratory viral infection. We developed the assay using two cohorts experimentally infected with influenza A H3N2/Wisconsin or influenza A H1N1/Brisbane, and validated the assay in a sample of adults presenting to the emergency department with fever (n = 102) and in healthy volunteers (n = 41). Peripheral blood RNA samples were obtained from individuals who underwent experimental viral challenge or who presented to the emergency department and had microbiologically proven viral respiratory infection or systemic bacterial infection. The selected gene set on the RT-PCR TLDA assay classified participants with experimentally induced influenza H3N2 and H1N1 infection with 100 and 87% accuracy, respectively. We validated this host gene expression signature in a cohort of 102 individuals arriving at the emergency department. The sensitivity of the RT-PCR test was 89% [95% confidence interval (CI), 72 to 98%], and the specificity was 94% (95% CI, 86 to 99%). These results show that RT-PCR–based detection of a host gene expression signature can classify individuals with respiratory viral infection and sets the stage for prospective evaluation of this diagnostic approach in a clinical setting.
doi:10.1126/scitranslmed.3006280
PMCID: PMC4286889  PMID: 24048524
2.  A Host Transcriptional Signature for Presymptomatic Detection of Infection in Humans Exposed to Influenza H1N1 or H3N2 
PLoS ONE  2013;8(1):e52198.
There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent.
doi:10.1371/journal.pone.0052198
PMCID: PMC3541408  PMID: 23326326
3.  Multicenter Evaluation of the LightCycler Methicillin-Resistant Staphylococcus aureus (MRSA) Advanced Test as a Rapid Method for Detection of MRSA in Nasal Surveillance Swabs ▿  
Journal of Clinical Microbiology  2010;48(5):1661-1666.
The rate of methicillin-resistant Staphylococcus aureus (MRSA) infection continues to rise in many health care settings. Rapid detection of MRSA colonization followed by appropriate isolation can reduce transmission and infection. We compared the performance of the new Roche LightCycler MRSA advanced test to that of the BD GeneOhm MRSA test and culture. Double-headed swabs were used to collect anterior nasal specimens from each subject. For both tests, DNA was extracted and real-time PCR was performed according to manufacturer's instructions. For culture, one swab of the pair was plated directly to CHROMagar MRSA. The swab paired with the BD GeneOhm MRSA test was also placed into an enrichment broth and then plated to CHROMagar MRSA. Colonies resembling staphylococci were confirmed as S. aureus by standard methods. Discrepant specimens had further testing with additional attempts to grow MRSA as well as sample amplicon sequencing. Agreement between results for the two swabs was 99.3% for those with valid results. A total of 1,402 specimens were tested using direct culture detection of MRSA as the gold standard; 187 were culture positive for MRSA. The LightCycler MRSA advanced test had relative sensitivity and specificity of 95.2% (95% confidence interval [CI]: 91.1% to 97.8%) and 96.4% (95% CI: 95.2% to 97.4%), respectively. The BD GeneOhm assay had relative sensitivity and specificity of 95.7% (95% CI: 91.7% to 98.1%) and 91.7% (95% CI: 90.0% to 93.2%), respectively. Following discrepancy analysis, the relative sensitivities of the LightCycler MRSA advanced test and the BD GeneOhm MRSA assay were 92.2 and 93.2%, respectively; relative specificities were 98.9 and 94.2%, respectively. Specificity was significantly better (P < 0.001) with the LightCycler MRSA advanced test. The sensitivity of direct culture was 80.4%. The LightCycler MRSA advanced test is a useful tool for sensitive and rapid detection of MRSA nasal colonization.
doi:10.1128/JCM.00003-10
PMCID: PMC2863939  PMID: 20335423
4.  Multiplex PCR To Diagnose Bloodstream Infections in Patients Admitted from the Emergency Department with Sepsis ▿  
Sepsis is caused by a heterogeneous group of infectious etiologies. Early diagnosis and the provision of appropriate antimicrobial therapy correlate with positive clinical outcomes. Current microbiological techniques are limited in their diagnostic capacities and timeliness. Multiplex PCR has the potential to rapidly identify bloodstream infections and fill this diagnostic gap. We identified patients from two large academic hospital emergency departments with suspected sepsis. The results of a multiplex PCR that could detect 25 bacterial and fungal pathogens were compared to those of blood culture. The results were analyzed with respect to the likelihood of infection, sepsis severity, the site of infection, and the effect of prior antibiotic therapy. We enrolled 306 subjects with suspected sepsis. Of these, 43 were later determined not to have infectious etiologies. Of the remaining 263 subjects, 70% had sepsis, 16% had severe sepsis, and 14% had septic shock. The majority had a definite infection (41.5%) or a probable infection (30.7%). Blood culture and PCR performed similarly with samples from patients with clinically defined infections (areas under the receiver operating characteristic curves, 0.64 and 0.60, respectively). However, blood culture identified more cases of septicemia than PCR among patients with an identified infectious etiology (66 and 46, respectively; P = 0.0004). The two tests performed similarly when the results were stratified by sepsis severity or infection site. Blood culture tended to detect infections more frequently among patients who had previously received antibiotics (P = 0.06). Conversely, PCR identified an additional 24 organisms that blood culture failed to detect. Real-time multiplex PCR has the potential to serve as an adjunct to conventional blood culture, adding diagnostic yield and shortening the time to pathogen identification.
doi:10.1128/JCM.01447-09
PMCID: PMC2812289  PMID: 19846634
5.  Gene Expression Signatures Diagnose Influenza and Other Symptomatic Respiratory Viral Infection in Humans 
Cell host & microbe  2009;6(3):207-217.
Summary
Acute respiratory infections (ARI) are a common reason for seeking medical attention and the threat of pandemic influenza will likely add to these numbers. Using human viral challenge studies with live rhinovirus, respiratory syncytial virus, and influenza A, we developed peripheral blood gene expression signatures that distinguish individuals with symptomatic ARI from uninfected individuals with > 95% accuracy. We validated this “acute respiratory viral” signature - encompassing genes with a known role in host defense against viral infections - across each viral challenge. We also validated the signature in an independently acquired dataset for influenza A and classified infected individuals from healthy controls with 100% accuracy. In the same dataset, we could also distinguish viral from bacterial ARIs (93% accuracy). These results demonstrate that ARIs induce changes in human peripheral blood gene expression that can be used to diagnose a viral etiology of respiratory infection and triage symptomatic individuals.
doi:10.1016/j.chom.2009.07.006
PMCID: PMC2852511  PMID: 19664979
6.  Complex Genetic Interactions in a Quantitative Trait Locus 
PLoS Genetics  2006;2(2):e13.
Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs), characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg) QTGs (MKT1, END3, and RHO2). We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3′UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.
Synopsis
Most of the differences in phenotype between unrelated members of a species are polygenic in nature. Because of their ubiquity and importance, these polygenic (or quantitative) traits have been intensively studied, and a variety of techniques have been proposed to identify and characterize quantitative trait genes (QTGs). Indeed, the main application of the recently published human HapMap project is to identify the genes responsible for diseases that are quantitative in nature. Using a well-defined Saccharomyces cerevisiae quantitative trait locus containing three QTGs (MKT1, END3, and RHO2), the authors used deletions to analyze the contributions of each gene to phenotype, singly and in combination, and found a variety of interactions. Expression analysis showed no difference in steady-state mRNA levels between alleles of the three genes. Homologous allele replacement identified the phenotypically relevant differences between alleles of each gene, which were single coding polymorphisms for two genes (MKT1 and END3) and the 3′ untranslated region of one gene (RHO2). Finally, analysis of multiple genetic backgrounds showed that the phenotypes conferred by these genetic variants were not conserved. The results show that the techniques proposed to identify QTGs, such as expression analysis and marker-trait association, have profound limitations, and that unbiased genome-wide approaches are needed to dissect quantitative traits. The results also demonstrate the complexity of the genetic interactions that affect quantitative traits and the value of the S. cerevisiae system in studying these traits.
doi:10.1371/journal.pgen.0020013
PMCID: PMC1359075  PMID: 16462944

Results 1-6 (6)