Publications by authors named "Aimee K Zaas"

52 Publications

Does Increased Schedule Flexibility Lead to Change? A National Survey of Program Directors on 2017 Work Hours Requirements.

J Gen Intern Med 2020 11 31;35(11):3205-3209. Epub 2020 Aug 31.

Internal Medicine Residency Program, Duke University School of Medicine, Durham, NC, USA.

Background: The learning and working environment for resident physicians shifted dramatically over the past two decades, with increased focus on work hours, resident wellness, and patient safety. Following two multi-center randomized trials comparing 16-h work limits for PGY-1 trainees to more flexible rules, the ACGME implemented new flexible work hours standards in 2017.

Objective: We sought to determine program directors' (PDs) support for the work hour changes and programmatic response.

Design: In 2017, US Internal Medicine PDs were surveyed about their degree of support for extension of PGY-1 work hour limits, whether they adopted the new maximum continuous work hours permitted, and reasons for their decisions.

Key Results: The response rate was 70% (266/379). Fifty-seven percent of PDs (n = 151) somewhat/strongly support the new work hour rules for PGY-1 residents, while only 25% of programs (N = 66) introduced work periods greater than 16-h on any rotation. Higher rates of adopting change were seen in PDs who strongly/somewhat supported the change (56/151 [37%], P < 0.001), had tenure of 6+ years (33/93 [35%], P = 0.005), were of non-general internal medicine subspecialty (30/80 [38%], P = 0.003), at university-based programs (35/101 [35%], P = 0.009), and with increasing number of approved positions (< 38, 10/63 [16%]; 38-58, 13/69 [19%]; 59-100, 15/64 [23%]; > 100, 28/68 [41%], P = 0.005). Areas with the greatest influence for PDs not extending work hours were the 16-h rule working well (56%) and risk to PGY1 well-being (47%).

Conclusions: Although the majority of PDs support the ACGME 2017 work hours rules, only 25% of programs made immediate changes to extend hours. These data reveal that complex, often competing, forces influence PDs' decisions to change trainee schedules.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11606-020-06109-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7661583PMC
November 2020

A transcriptional signature accurately identifies Aspergillus Infection across healthy and immunosuppressed states.

Transl Res 2020 05 20;219:1-12. Epub 2020 Feb 20.

Center for Applied Genomics and Precision Medicine, Duke University, Durham, North Carolina; Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina; Durham VA Medical Center, Durham, North Carolina.

Invasive aspergillosis (IA) is a major cause of critical illness in immunocompromised (IC) patients. However, current fungal tests are limited. Disease-specific gene expression patterns in circulating host cells show promise as novel diagnostics, however it is unknown whether such a 'signature' exists for IA and the effect of iatrogenic immunosuppression on any such biomarkers. Male BALB/c mice were separated into 6 experimental groups based on Aspergillus fumigatus inhalational exposure and IC status (no immunosuppression, cyclophosphamide, and corticosteroids). Mice were sacrificed 4 days postinfection. Whole blood was assayed for transcriptomic responses in peripheral white blood cells via microarray. An elastic net regularized logistic regression was employed to develop classifiers of IA based on gene expression. Aspergillus infection triggers a powerful response in non-IC hosts with 2718 genes differentially expressed between IA and controls. We generated a 146-gene classifier able to discriminate between non-IC infected and uninfected mice with an AUC of 1. However, immunosuppressive medications exhibited a confounding effect on this transcriptomic classifier. After controlling for the genomic effects of immunosuppression, we were able to generate a 187-gene classifier with an AUC of 0.92 in the absence of immunosuppression, 1 with cyclophosphamide, and 0.9 with steroids. The host transcriptomic response to IA is robust and conserved. Pharmacologic perturbation of the host immune response has powerful effects on classifier performance and must be considered when developing such novel diagnostics. When appropriately designed, host-derived peripheral blood transcriptomic responses demonstrate the ability to accurately diagnose Aspergillus infection, even in the presence of immunosuppression.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.trsl.2020.02.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7170547PMC
May 2020

Misinterpretation of the American Board of Internal Medicine Leave Policies for Resident Physicians Around Parental Leave.

Ann Intern Med 2020 04 24;172(8):570-572. Epub 2019 Dec 24.

University of Alabama at Birmingham, Birmingham, Alabama (L.L.W.).

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.7326/M19-2490DOI Listing
April 2020

Relationship Between Institutional Investment in High-Value Care (HVC) Performance Improvement and Internal Medicine Residents' Perceptions of HVC Training.

Acad Med 2018 10;93(10):1517-1523

K.L. Ryskina is assistant professor of medicine, Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; ORCID: https://orcid.org/0000-0003-3379-6394. C.D. Smith is vice president, Clinical Programs, American College of Physicians, and adjunct associate professor of medicine, Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; ORCID: https://orcid.org/0000-0002-1910-9546. V.M. Arora is associate professor and director, Graduate Medical Education Clinical Learning Environment Innovation, Section of General Internal Medicine, Department of Medicine, University of Chicago, Chicago, Illinois; ORCID: https://orcid.org/0000-0002-4745-7599. A.K. Zaas is associate professor, Division of Infectious Diseases and International Health, and program director, Duke Internal Medicine Residency, Duke University School of Medicine, Duke University, Durham, North Carolina. A.J. Halvorsen is assistant professor of medicine, Office of Educational Innovations, Internal Medicine Residency Program, Mayo Clinic, Rochester, Minnesota; ORCID: https://orcid.org/0000-0003-1272-616X. A. Weissman is director, Research Center, American College of Physicians, Philadelphia, Pennsylvania. S. Wahi-Gururaj is associate professor of medicine, Section of General Internal Medicine, and program director, Internal Medicine Residency, Department of Internal Medicine, University of Nevada, Las Vegas School of Medicine, Las Vegas, Nevada.

Purpose: To measure the association between institutional investment in high-value care (HVC) performance improvement and resident HVC experiences.

Method: The authors analyzed data from two 2014 surveys assessing institutions' investments in HVC performance improvement as reported by program directors (PDs) and residents' perceptions of the frequency of HVC teaching, participation in HVC-focused quality improvement (QI), and views on HVC topics. The authors measured the association between institutional investment and resident-reported experiences using logistic regression, controlling for program and resident characteristics.

Results: The sample included 214 programs and 9,854 residents (59.3% of 361 programs, 55.2% of 17,851 residents surveyed). Most PDs (158/209; 75.6%) reported some support. Residents were more likely to report HVC discussions with faculty at least a few times weekly if they trained in programs that offered HVC-focused faculty development (odds ratio [OR] = 1.19; 95% confidence interval [CI] 1.04-1.37; P = .01), that supported such faculty development (OR = 1.21; 95% CI 1.04-1.41; P = .02), or that provided physician cost-of-care performance data (OR = 1.19; 95% CI 1.03-1.39; P = .02). Residents were more likely to report participation in HVC QI if they trained in programs with a formal HVC curriculum (OR = 1.83; 95% CI 1.48-2.27; P < .001) or with HVC-focused faculty development (OR = 1.46; 95% CI 1.15-1.85; P = .002).

Conclusions: Institutional investment in HVC-related faculty development and physician feedback on costs of care may increase the frequency of HVC teaching and resident participation in HVC-related QI.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/ACM.0000000000002257DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442932PMC
October 2018

Hot in the Tropics.

J Hosp Med 2017 06;12(6):462-466

Department of Medicine, Duke University School of Medicine, Durham, North Carolina.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.12788/jhm.2753DOI Listing
June 2017

Improving Timely Resident Follow-Up and Communication of Results in Ambulatory Clinics Utilizing a Web-Based Audit and Feedback Module.

J Grad Med Educ 2017 Apr;9(2):195-200

Background: Failure to follow up and communicate test results to patients in outpatient settings may lead to diagnostic and therapeutic delays. Residents are less likely than attending physicians to report results to patients, and may face additional barriers to reporting, given competing clinical responsibilities.

Objective: This study aimed to improve the rates of communicating test results to patients in resident ambulatory clinics.

Methods: We performed an internal medicine, residency-wide, pre- and postintervention, quality improvement project using audit and feedback. Residents performed audits of ambulatory patients requiring laboratory or radiologic testing by means of a shared online interface. The intervention consisted of an educational module viewed with initial audits, development of a personalized improvement plan after Phase 1, and repeated real-time feedback of individual relative performance compared at clinic and program levels. Outcomes included results communicated within 14 days and prespecified "significant" results communicated within 72 hours.

Results: A total of 76 of 86 eligible residents (88%) reviewed 1713 individual ambulatory patients' charts in Phase 1, and 73 residents (85%) reviewed 1509 charts in Phase 2. Follow-up rates were higher in Phase 2 than Phase 1 for communicating results within 14 days and significant results within 72 hours (85% versus 78%,  < .001; and 82% versus 70%,  = .002, respectively). Communication of "significant" results was more likely to occur via telephone, compared with communication of nonsignificant results.

Conclusions: Participation in a shared audit and feedback quality improvement project can improve rates of resident follow-up and communication of results, although communication gaps remained.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.4300/JGME-D-16-00460.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5398151PMC
April 2017

What motivates residents to teach? The Attitudes in Clinical Teaching study.

Med Educ 2016 Jul;50(7):768-77

Division of Rheumatology and Immunology, Duke University Medical Center, Durham, North Carolina, USA.

Context: Graduate medical trainees have a critical role in the teaching of other trainees. Improving their teaching requires an understanding of their attitudes towards teaching and their motivation to teach. Both have been incompletely explored in this population. We aimed to better understand graduate medical trainees' attitudes towards teaching and motivation to teach in the clinical setting in order to inform modifications to resident-as-teacher (RAT) programmes and enhance teaching practices.

Methods: We applied Q methodology, an established sorting method, to identify and quantify the factors that have an impact on trainees' engagement in teaching. We invited house officers at our institution to rank-order 47 statements regarding their attitudes to and motivation for teaching. Respondents explained their Q-sort rankings in writing and completed a demographic questionnaire. By-person factor analysis yielded groups of individuals with similar attitudes.

Results: One hundred and seven trainees completed the Q-sort. We found three primary groups of attitudes towards teaching in the clinical setting: enthusiasm, reluctance and rewarded. Enthusiastic teachers are committed and make time to teach. Teaching increases their job satisfaction. Reluctant teachers have enthusiasm but are earlier in training and feel limited by clinical workload and unprepared. Rewarded teachers feel teaching is worthwhile and derive satisfaction from the rewards and recognition they receive for teaching.

Conclusions: This improved understanding of common attitudes shared by groups of residents will help curriculum designers create RAT programmes to further reinforce and encourage attitudes that promote teaching as well as improve trainees' motivation to teach. Designing RAT programmes that acknowledge the attitudes to and motivations for teaching should help develop effective teachers to improve educational outcomes. Directed efforts to enhance motivation for reluctant teachers and encourage more positive attitudes in rewarded teachers may lead to improved teaching behaviours among residents.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/medu.13075DOI Listing
July 2016

Patients, Nurses, and Physicians Working Together to Develop a Discharge Entrustable Professional Activity Assessment Tool.

Acad Med 2016 Oct;91(10):1388-1391

L.B. Meade is Macy Faculty Scholar, Baystate Medical Center, Springfield, and associate professor of medicine, Tufts University School of Medicine, Boston, Massachusetts.K.H. Suddarth is associate program director for internal medicine and assistant professor of medicine, University of Colorado Denver School of Medicine, Denver, Colorado.R.R. Jones is associate program director in internal medicine, Summa Health Systems, Akron, and associate professor of medicine, Department of Medicine, Northeast Ohio Medical University, Rootstown, Ohio.A.K. Zaas is program director for internal medicine and associate professor, Duke University School of Medicine, Durham, North Carolina.T. Albanese is formerly manager of medical education, Summa Health System, Akron, Ohio.K. Yamazaki is outcome assessment research associate, Accreditation Council for Graduate Medical Education, Chicago, Illinois.C.W. O'Malley is program director in internal medicine and assistant professor of medicine, University of Arizona College of Medicine, Phoenix, Arizona.

Problem: The Accreditation Council for Graduate Medical Education milestones were written by physicians and thus may not reflect all the behaviors necessary for physicians to optimize their performance as a key member of an interprofessional team.

Approach: From April to May 2013, the authors, Educational Research Outcomes Collaborative leaders, assembled interprofessional team discussion groups, including patients or family members, nurses, physician trainees, physician educators, and other staff (optional), at 11 internal medicine (IM) programs. Led by the site's principal investigator, the groups generated a list of physician behaviors related to the entrustable professional activity (EPA) of a safe and effective discharge of a patient from the hospital, and prioritized those behaviors.

Outcomes: A total of 182 behaviors were listed, with lists consisting of between 10 and 29 behaviors. Overall, the site principal investigators described all participants as emerging from the activity with a new understanding of the complexity of training physicians for the discharge EPA. The authors batched behaviors into six components of a safe and effective discharge: medication reconciliation, discharge summary, patient/caregiver communication, team communication, active collaboration, and anticipation of posthospital needs. Specific, high-priority behavior examples for each component were identified, and an assessment tool for direct observation was developed for the discharge EPA.

Next Steps: The authors are currently evaluating trainee and educator perceptions of the assessment tool after implementation in 15 IM programs. Additional next steps include developing tools for other EPAs, as well as a broader evaluation of patient outcomes in the era of milestone-based assessment.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/ACM.0000000000001189DOI Listing
October 2016

A Genomic Signature of Influenza Infection Shows Potential for Presymptomatic Detection, Guiding Early Therapy, and Monitoring Clinical Responses.

Open Forum Infect Dis 2016 Jan 19;3(1):ofw007. Epub 2016 Jan 19.

Center for Applied Genomics and Precision Medicine, Duke University; Durham Veterans Affairs Medical Center; Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina.

Early, presymptomatic intervention with oseltamivir (corresponding to the onset of a published host-based genomic signature of influenza infection) resulted in decreased overall influenza symptoms (aggregate symptom scores of 23.5 vs 46.3), more rapid resolution of clinical disease (20 hours earlier), reduced viral shedding (total median tissue culture infectious dose [TCID50] 7.4 vs 9.7), and significantly reduced expression of several inflammatory cytokines (interferon-γ, tumor necrosis factor-α, interleukin-6, and others). The host genomic response to influenza infection is robust and may provide the means for early detection, more timely therapeutic interventions, a meaningful reduction in clinical disease, and an effective molecular means to track response to therapy.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/ofid/ofw007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4771939PMC
January 2016

Implementation of Milestones-Based Assessment for a Safe and Effective Discharge.

Am J Med 2016 Jun 19;129(6):640-6. Epub 2016 Feb 19.

Tufts University Medical School, Baystate Medical Center, Springfield, Mass.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.amjmed.2016.02.005DOI Listing
June 2016

An individualized predictor of health and disease using paired reference and target samples.

BMC Bioinformatics 2016 Jan 22;17:47. Epub 2016 Jan 22.

Electrical Engineering and Computer Science Department, University of Michigan, Ann Arbor MI, USA.

Background: Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This paper develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels.

Results: The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large scale serially sampled respiratory virus challenge study we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample. The full study consists of 2886 microarray chips assaying 12,023 genes of 151 human volunteer subjects under 4 different inoculation regimes (HRV, RSV, H1N1, H3N2). We train (with cross-validation) reference-aided sparse multi-class classifier algorithms on this data to show that inclusion of a subject's reference sample can improve prediction accuracy by as much as 14 %, for the H3N2 cohort, and by at least 6 %, for the H1N1 cohort. Remarkably, these gains in accuracy are achieved by using smaller panels of genes, e.g., 39 % fewer for H3N2 and 31 % fewer for H1N1. The biomarkers selected by the predictors fall into two categories: 1) contrasting genes that tend to differentially express between target and reference samples over the population; 2) reinforcement genes that remain constant over the two samples, which function as housekeeping normalization genes. Many of these genes are common to all 4 viruses and their roles in the predictor elucidate the function that they play in differentiating the different states of host immune response.

Conclusions: If one uses a suitable mathematical prediction algorithm, inclusion of a healthy reference in biomarker diagnostic testing can potentially improve accuracy of disease prediction with fewer biomarkers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12859-016-0889-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722633PMC
January 2016

Host gene expression classifiers diagnose acute respiratory illness etiology.

Sci Transl Med 2016 Jan;8(322):322ra11

Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708.

Acute respiratory infections caused by bacterial or viral pathogens are among the most common reasons for seeking medical care. Despite improvements in pathogen-based diagnostics, most patients receive inappropriate antibiotics. Host response biomarkers offer an alternative diagnostic approach to direct antimicrobial use. This observational cohort study determined whether host gene expression patterns discriminate noninfectious from infectious illness and bacterial from viral causes of acute respiratory infection in the acute care setting. Peripheral whole blood gene expression from 273 subjects with community-onset acute respiratory infection (ARI) or noninfectious illness, as well as 44 healthy controls, was measured using microarrays. Sparse logistic regression was used to develop classifiers for bacterial ARI (71 probes), viral ARI (33 probes), or a noninfectious cause of illness (26 probes). Overall accuracy was 87% (238 of 273 concordant with clinical adjudication), which was more accurate than procalcitonin (78%, P < 0.03) and three published classifiers of bacterial versus viral infection (78 to 83%). The classifiers developed here externally validated in five publicly available data sets (AUC, 0.90 to 0.99). A sixth publicly available data set included 25 patients with co-identification of bacterial and viral pathogens. Applying the ARI classifiers defined four distinct groups: a host response to bacterial ARI, viral ARI, coinfection, and neither a bacterial nor a viral response. These findings create an opportunity to develop and use host gene expression classifiers as diagnostic platforms to combat inappropriate antibiotic use and emerging antibiotic resistance.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/scitranslmed.aad6873DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4905578PMC
January 2016

Diabetes Quality of Care Before and After Implementation of a Resident Clinic Practice Partnership System.

Am J Med Qual 2017 Jan/Feb;32(1):66-72. Epub 2016 Jul 10.

1 Duke University, Durham, NC.

Deficiencies in resident diabetes care quality may relate to continuity clinic design. This retrospective analysis compared diabetes care processes and outcomes within a traditional resident continuity clinic structure (2005) and after the implementation of a practice partnership system (PPS; 2009). Under PPS, patients were more likely to receive annual foot examinations (odds ratio [OR] = 11.6; 95% confidence interval [CI] = 7.2, 18.5), microalbumin screening (OR = 2.4; 95% CI = 1.6, 3.4), and aspirin use counseling (OR = 3.8; 95% CI = 2.5, 6.0) and were less likely to receive eye examinations (OR = 0.54; 95% CI = 0.36, 0.82). Hemoglobin A1c and lipid testing were similar between periods, and there was no difference in achievement of diabetes and blood pressure goals. Patients were less likely to achieve cholesterol goals under PPS (OR = 0.62; 95% CI = 0.39, 0.98). Resident practice partnerships may improve processes of diabetes care but may not affect intermediate outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1177/1062860615615210DOI Listing
February 2018

Gene Expression Profiles Link Respiratory Viral Infection, Platelet Response to Aspirin, and Acute Myocardial Infarction.

PLoS One 2015 20;10(7):e0132259. Epub 2015 Jul 20.

Center for Applied Genomics and Precision Medicine, Duke University Medical Center, Durham, North Carolina, United States of America; Department of Medicine, Duke University Medical Center, Durham, North Carolina, United States of America.

Background: Influenza infection is associated with myocardial infarction (MI), suggesting that respiratory viral infection may induce biologic pathways that contribute to MI. We tested the hypotheses that 1) a validated blood gene expression signature of respiratory viral infection (viral GES) was associated with MI and 2) respiratory viral exposure changes levels of a validated platelet gene expression signature (platelet GES) of platelet function in response to aspirin that is associated with MI.

Methods: A previously defined viral GES was projected into blood RNA data from 594 patients undergoing elective cardiac catheterization and used to classify patients as having evidence of viral infection or not and tested for association with acute MI using logistic regression. A previously defined platelet GES was projected into blood RNA data from 81 healthy subjects before and after exposure to four respiratory viruses: Respiratory Syncytial Virus (RSV) (n=20), Human Rhinovirus (HRV) (n=20), Influenza A virus subtype H1N1 (H1N1) (n=24), Influenza A Virus subtype H3N2 (H3N2) (n=17). We tested for the change in platelet GES with viral exposure using linear mixed-effects regression and by symptom status.

Results: In the catheterization cohort, 32 patients had evidence of viral infection based upon the viral GES, of which 25% (8/32) had MI versus 12.2% (69/567) among those without evidence of viral infection (OR 2.3; CI [1.03-5.5], p=0.04). In the infection cohorts, only H1N1 exposure increased platelet GES over time (time course p-value = 1e-04).

Conclusions: A viral GES of non-specific, respiratory viral infection was associated with acute MI; 18% of the top 49 genes in the viral GES are involved with hemostasis and/or platelet aggregation. Separately, H1N1 exposure, but not exposure to other respiratory viruses, increased a platelet GES previously shown to be associated with MI. Together, these results highlight specific genes and pathways that link viral infection, platelet activation, and MI especially in the case of H1N1 influenza infection.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132259PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4507878PMC
April 2016

Moving toward prime time: host signatures for diagnosis of respiratory infections.

J Infect Dis 2015 Jul 29;212(2):173-5. Epub 2015 Jan 29.

Institute for Genome Sciences and Precision Medicine, Division of Infectious Diseases and International Health, Department of Medicine, Duke University Medical Center, Durham, North Carolina.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/infdis/jiv032DOI Listing
July 2015

The current epidemiology and clinical decisions surrounding acute respiratory infections.

Trends Mol Med 2014 Oct 5;20(10):579-88. Epub 2014 Sep 5.

Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA.

Acute respiratory infection (ARI) is a common diagnosis in outpatient and emergent care settings. Currently available diagnostics are limited, creating uncertainty in the use of antibacterial, antiviral, or supportive care. Up to 72% of ambulatory care patients with ARI are treated with an antibacterial, despite only a small fraction actually needing one. Antibiotic overuse is not restricted to ambulatory care: ARI accounts for approximately 5 million emergency department (ED) visits annually in the USA, where 52-61% of such patients receive antibiotics. Thus, an accurate test for the presence or absence of viral or bacterial infection is needed. In this review, we focus on recent research showing that the host-response (genomic, proteomic, or miRNA) can accomplish this task.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.molmed.2014.08.001DOI Listing
October 2014

Development of a novel preclinical model of pneumococcal pneumonia in nonhuman primates.

Am J Respir Cell Mol Biol 2014 May;50(5):995-1004

1 Departments of Medicine and.

Pneumococcal pneumonia is a leading cause of bacterial infection and death worldwide. Current diagnostic tests for detecting Streptococcus pneumoniae can be unreliable and can mislead clinical decision-making and treatment. To address this concern, we developed a preclinical model of pneumococcal pneumonia in nonhuman primates useful for identifying novel biomarkers, diagnostic tests, and therapies for human S. pneumoniae infection. Adult colony-bred baboons (n = 15) were infected with escalating doses of S. pneumoniae (Serotype 19A-7). We characterized the pathophysiological and serological profiles of healthy and infected animals over 7 days. Pneumonia was prospectively defined by the presence of three criteria: (1) change in white blood cell count, (2) isolation of S. pneumoniae from bronchoalveolar lavage fluid (BALF) or blood, and (3) concurrent signs/symptoms of infection. Animals given 10(9) CFU consistently met our definition and developed a phenotype of tachypnea, tachycardia, fever, hypoxemia, and radiographic lobar infiltrates at 48 hours. BALF and plasma cytokines, including granulocyte colony-stimulating factor, IL-6, IL-10, and IL-1ra, peaked at 24 to 48 hours. At necropsy, there was lobar consolidation with frequent pleural involvement. Lung histopathology showed alveolar edema and macrophage influx in areas of organizing pneumonia. Hierarchical clustering of peripheral blood RNA data at 48 hours correctly identified animals with and without pneumonia. Dose-dependent inoculation of baboons with S. pneumoniae produces a host response ranging from spontaneous clearance (10(6) CFU) to severe pneumonia (10(9) CFU). Selected BALF and plasma cytokine levels and RNA profiles were associated with severe pneumonia and may provide clinically useful parameters after validation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1165/rcmb.2013-0340OCDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4068947PMC
May 2014

Longitudinal analysis of leukocyte differentials in peripheral blood of patients with acute respiratory viral infections.

J Clin Virol 2013 Dec 28;58(4):689-95. Epub 2013 Sep 28.

Durham VA Medical Center, Durham, NC, United States; Division of Infectious Diseases, Duke University Medical Center, Durham, NC, United States. Electronic address:

Background: Leukocyte counts and differentials are commonly acquired in patients with suspected respiratory viral infections and may contribute diagnostic information. However, most published work is limited to a single timepoint at initial presentation to a medical provider, which may correspond to widely varying points in the course of disease.

Objectives: To examine the temporal development and time-dependent utility of routine leukocyte differentials in the diagnosis of respiratory viral infections.

Study Design: We analyzed data from recent experimental human challenges with influenza A/H3N2, human rhinovirus (HRV), and respiratory syncytial virus (RSV). Routine clinical lab cell counts and differentials were measured daily from the time period immediately prior to inoculation through the eventual resolution of symptomatic disease.

Results: Approximately 50% of challenged individuals developed symptoms and viral shedding consistent with clinical disease. Subpopulations of WBC showed marked differences between symptomatic and asymptomatic individuals over time, but these changes were much more profound and consistent in influenza infection. Influenza-infected subjects develop both relative lymphopenia and relative monocytosis, both of which closely mirror symptom development in time. A lymphocyte:monocyte ratio of <2 correctly classifies 100% of influenza (but not RSV or HRV) infected subjects at the time of maximal symptoms.

Conclusions: Leukocyte differentials may suggest a viral etiology in patients with upper respiratory infection, but are not sufficient to allow differentiation between common viruses. Timing of data acquisition relative to the disease course is a key component in determining the utility of these tests.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jcv.2013.09.015DOI Listing
December 2013

A host-based RT-PCR gene expression signature to identify acute respiratory viral infection.

Sci Transl Med 2013 Sep;5(203):203ra126

Institute for Genome Sciences and Policy, Duke University School of Medicine, Durham, NC 27710, USA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/scitranslmed.3006280DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4286889PMC
September 2013

Playing with curricular milestones in the educational sandbox: Q-sort results from an internal medicine educational collaborative.

Acad Med 2013 Aug;88(8):1142-8

Department of Medicine, Tufts University School of Medicine, Springfield, MA 01199, USA.

Purpose: In competency-based medical education, the focus of assessment is on learner demonstration of predefined outcomes or competencies. One strategy being used in internal medicine (IM) is applying curricular milestones to assessment and reporting milestones to competence determination. The authors report a practical method for identifying sets of curricular milestones for assessment of a landmark, or a point where a resident can be entrusted with increased responsibility.

Method: Thirteen IM residency programs joined in an educational collaborative to apply curricular milestones to training. The authors developed a game using Q-sort methodology to identify high-priority milestones for the landmark "Ready for indirect supervision in essential ambulatory care" (EsAMB). During May to December 2010, the programs'ambulatory faculty participated in the Q-sort game to prioritize 22 milestones for EsAMB. The authors analyzed the data to identify the top 8 milestones.

Results: In total, 149 faculty units (1-4 faculty each) participated. There was strong agreement on the top eight milestones; six had more than 92% agreement across programs, and five had 75% agreement across all faculty units. During the Q-sort game, faculty engaged in dynamic discussion about milestones and expressed interest in applying the game to other milestones and educational settings.

Conclusions: The Q-sort game enabled diverse programs to prioritize curricular milestones with interprogram and interparticipant consistency. A Q-sort exercise is an engaging and playful way to address milestones in medical education and may provide a practical first step toward using milestones in the real-world educational setting.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/ACM.0b013e31829a3967DOI Listing
August 2013

Surface-enhanced Raman scattering molecular sentinel nanoprobes for viral infection diagnostics.

Anal Chim Acta 2013 Jul 20;786:153-8. Epub 2013 May 20.

Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.

In this paper, we describe a surface-enhanced Raman scattering (SERS)-based detection approach, referred to as "molecular sentinel" (MS) plasmonic nanoprobes, to detect an RNA target related to viral infection. The MS method is essentially a label-free technique incorporating the SERS effect modulation scheme associated with silver nanoparticles and Raman dye-labeled DNA hairpin probes. Hybridization with target sequences opens the hairpin and spatially separates the Raman label from the silver surface thus reducing the SERS signal of the label. Herein, we have developed a MS nanoprobe to detect the human radical S-adenosyl methionine domain containing 2 (RSAD2) RNA target as a model system for method demonstration. The human RSAD2 gene has recently emerged as a novel host-response biomarker for diagnosis of respiratory infections. Our results showed that the RSAD2 MS nanoprobes exhibits high specificity and can detect as low as 1 nM target sequences. With the use of a portable Raman spectrometer and total RNA samples, we have also demonstrated for the first time the potential of the MS nanoprobe technology for detection of host-response RNA biomarkers for infectious disease diagnostics.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.aca.2013.05.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4022285PMC
July 2013

Unsupervised Bayesian linear unmixing of gene expression microarrays.

BMC Bioinformatics 2013 Mar 19;14:99. Epub 2013 Mar 19.

University of Toulouse, IRIT/INP-ENSEEIHT, 2 rue Camichel, BP 7122, 31071 Toulouse cedex 7, France.

Background: This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters.

Results: Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here.

Conclusions: The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/1471-2105-14-99DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3681645PMC
March 2013

A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.

PLoS One 2013 9;8(1):e52198. Epub 2013 Jan 9.

Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, USA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0052198PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3541408PMC
July 2013

Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.

PLoS One 2013 9;8(1):e48979. Epub 2013 Jan 9.

Division of Infectious Diseases and International Health, Department of Medicine, Duke University, Durham, North Carolina, USA.

Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host's inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.84). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0048979PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3541361PMC
July 2013

The Hsp90 co-chaperone Sgt1 governs Candida albicans morphogenesis and drug resistance.

PLoS One 2012 6;7(9):e44734. Epub 2012 Sep 6.

Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.

The molecular chaperone Hsp90 orchestrates regulatory circuitry governing fungal morphogenesis, biofilm development, drug resistance, and virulence. Hsp90 functions in concert with co-chaperones to regulate stability and activation of client proteins, many of which are signal transducers. Here, we characterize the first Hsp90 co-chaperone in the leading human fungal pathogen, Candida albicans. We demonstrate that Sgt1 physically interacts with Hsp90, and that it governs C. albicans morphogenesis and drug resistance. Genetic depletion of Sgt1 phenocopies depletion of Hsp90, inducing yeast to filament morphogenesis and invasive growth. Sgt1 governs these traits by bridging two morphogenetic regulators: Hsp90 and the adenylyl cyclase of the cAMP-PKA signaling cascade, Cyr1. Sgt1 physically interacts with Cyr1, and depletion of either Sgt1 or Hsp90 activates cAMP-PKA signaling, revealing the elusive link between Hsp90 and the PKA signaling cascade. Sgt1 also mediates tolerance and resistance to the two most widely deployed classes of antifungal drugs, azoles and echinocandins. Depletion of Sgt1 abrogates basal tolerance and acquired resistance to azoles, which target the cell membrane. Depletion of Sgt1 also abrogates tolerance and resistance to echinocandins, which target the cell wall, and renders echinocandins fungicidal. Though Sgt1 and Hsp90 have a conserved impact on drug resistance, the underlying mechanisms are distinct. Depletion of Hsp90 destabilizes the client protein calcineurin, thereby blocking crucial responses to drug-induced stress; in contrast, depletion of Sgt1 does not destabilize calcineurin, but blocks calcineurin activation in response to drug-induced stress. Sgt1 influences not only morphogenesis and drug resistance, but also virulence, as genetic depletion of C. albicans Sgt1 leads to reduced kidney fungal burden in a murine model of systemic infection. Thus, our characterization of the first Hsp90 co-chaperone in a fungal pathogen establishes C. albicans Sgt1 as a global regulator of morphogenesis and drug resistance, providing a new target for treatment of life-threatening fungal infections.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0044734PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3435277PMC
March 2013

β-D-glucan surveillance with preemptive anidulafungin for invasive candidiasis in intensive care unit patients: a randomized pilot study.

PLoS One 2012 6;7(8):e42282. Epub 2012 Aug 6.

Department of Medicine and Pathology, University of Utah, Salt Lake City, Utah, United States of America.

Background: Invasive candidiasis (IC) is a devastating disease. While prompt antifungal therapy improves outcomes, empiric treatment based on the presence of fever has little clinical impact. Β-D-Glucan (BDG) is a fungal cell wall component detectable in the serum of patients with early invasive fungal infection (IFI). We evaluated the utility of BDG surveillance as a guide for preemptive antifungal therapy in at-risk intensive care unit (ICU) patients.

Methods: Patients admitted to the ICU for ≥ 3 days and expected to require at least 2 additional days of intensive care were enrolled. Subjects were randomized in 3:1 fashion to receive twice weekly BDG surveillance with preemptive anidulafungin in response to a positive test or empiric antifungal treatment based on physician preference.

Results: Sixty-four subjects were enrolled, with 1 proven and 5 probable cases of IC identified over a 2.5 year period. BDG levels were higher in subjects with proven/probable IC as compared to those without an IFI (117 pg/ml vs. 28 pg/ml; p<0.001). Optimal assay performance required 2 sequential BDG determinations of ≥ 80 pg/ml to define a positive test (sensitivity 100%, specificity 75%, positive predictive value 30%, negative predictive value 100%). In all, 21 preemptive and 5 empiric subjects received systemic antifungal therapy. Receipt of preemptive antifungal treatment had a significant effect on BDG concentrations (p< 0.001). Preemptive anidulafungin was safe and generally well tolerated with excellent outcome.

Conclusions: BDG monitoring may be useful for identifying ICU patients at highest risk to develop an IFI as well as for monitoring treatment response. Preemptive strategies based on fungal biomarkers warrant further study.

Trial Registration: Clinical Trials.gov NCT00672841.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0042282PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3412848PMC
January 2013

Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.

PLoS Genet 2011 Aug 25;7(8):e1002234. Epub 2011 Aug 25.

Center for Computational Biology and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.

Exposure to influenza viruses is necessary, but not sufficient, for healthy human hosts to develop symptomatic illness. The host response is an important determinant of disease progression. In order to delineate host molecular responses that differentiate symptomatic and asymptomatic Influenza A infection, we inoculated 17 healthy adults with live influenza (H3N2/Wisconsin) and examined changes in host peripheral blood gene expression at 16 timepoints over 132 hours. Here we present distinct transcriptional dynamics of host responses unique to asymptomatic and symptomatic infections. We show that symptomatic hosts invoke, simultaneously, multiple pattern recognition receptors-mediated antiviral and inflammatory responses that may relate to virus-induced oxidative stress. In contrast, asymptomatic subjects tightly regulate these responses and exhibit elevated expression of genes that function in antioxidant responses and cell-mediated responses. We reveal an ab initio molecular signature that strongly correlates to symptomatic clinical disease and biomarkers whose expression patterns best discriminate early from late phases of infection. Our results establish a temporal pattern of host molecular responses that differentiates symptomatic from asymptomatic infections and reveals an asymptomatic host-unique non-passive response signature, suggesting novel putative molecular targets for both prognostic assessment and ameliorative therapeutic intervention in seasonal and pandemic influenza.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pgen.1002234DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3161909PMC
August 2011

Next-generation computational genetic analysis: multiple complement alleles control survival after Candida albicans infection.

Infect Immun 2011 Nov 29;79(11):4472-9. Epub 2011 Aug 29.

Department of Anesthesia, Stanford University School of Medicine, 300 Pasteur Dr., Stanford, CA 94305, USA.

Candida albicans is a fungal pathogen that causes severe disseminated infections that can be lethal in immunocompromised patients. Genetic factors are known to alter the initial susceptibility to and severity of C. albicans infection. We developed a next-generation computational genetic mapping program with advanced features to identify genetic factors affecting survival in a murine genetic model of hematogenous C. albicans infection. This computational tool was used to analyze the median survival data after inbred mouse strains were infected with C. albicans, which provides a useful experimental model for identification of host susceptibility factors. The computational analysis indicated that genetic variation within early classical complement pathway components (C1q, C1r, and C1s) could affect survival. Consistent with the computational results, serum C1 binding to this pathogen was strongly affected by C1rs alleles, as was survival of chromosome substitution strains. These results led to a combinatorial, conditional genetic model, involving an interaction between C5 and C1r/s alleles, which accurately predicted survival after infection. Beyond applicability to infectious disease, this information could increase our understanding of the genetic factors affecting susceptibility to autoimmune and neurodegenerative diseases.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1128/IAI.05666-11DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3257944PMC
November 2011

PKC signaling regulates drug resistance of the fungal pathogen Candida albicans via circuitry comprised of Mkc1, calcineurin, and Hsp90.

PLoS Pathog 2010 Aug 26;6(8):e1001069. Epub 2010 Aug 26.

Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.

Fungal pathogens exploit diverse mechanisms to survive exposure to antifungal drugs. This poses concern given the limited number of clinically useful antifungals and the growing population of immunocompromised individuals vulnerable to life-threatening fungal infection. To identify molecules that abrogate resistance to the most widely deployed class of antifungals, the azoles, we conducted a screen of 1,280 pharmacologically active compounds. Three out of seven hits that abolished azole resistance of a resistant mutant of the model yeast Saccharomyces cerevisiae and a clinical isolate of the leading human fungal pathogen Candida albicans were inhibitors of protein kinase C (PKC), which regulates cell wall integrity during growth, morphogenesis, and response to cell wall stress. Pharmacological or genetic impairment of Pkc1 conferred hypersensitivity to multiple drugs that target synthesis of the key cell membrane sterol ergosterol, including azoles, allylamines, and morpholines. Pkc1 enabled survival of cell membrane stress at least in part via the mitogen activated protein kinase (MAPK) cascade in both species, though through distinct downstream effectors. Strikingly, inhibition of Pkc1 phenocopied inhibition of the molecular chaperone Hsp90 or its client protein calcineurin. PKC signaling was required for calcineurin activation in response to drug exposure in S. cerevisiae. In contrast, Pkc1 and calcineurin independently regulate drug resistance via a common target in C. albicans. We identified an additional level of regulatory control in the C. albicans circuitry linking PKC signaling, Hsp90, and calcineurin as genetic reduction of Hsp90 led to depletion of the terminal MAPK, Mkc1. Deletion of C. albicans PKC1 rendered fungistatic ergosterol biosynthesis inhibitors fungicidal and attenuated virulence in a murine model of systemic candidiasis. This work establishes a new role for PKC signaling in drug resistance, novel circuitry through which Hsp90 regulates drug resistance, and that targeting stress response signaling provides a promising strategy for treating life-threatening fungal infections.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.ppat.1001069DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2928802PMC
August 2010