Teaching Wildlife Disease Outbreak Response Through a Collaborative One Health Workshop.

Issues in the fields of wildlife disease and One Health are often difficult to address by single research groups because of the many disciplines and areas of expertise required to effectively solve complex problems. Although collaborations are becoming increasingly prevalent in the professional realm, many undergraduate, graduate, and professional students are merely introduced to the idea of collaboration without fully understanding how team-based approaches function. In this report, we describe the framework for a one-day workshop hosted by the Colorado State University student chapter of the Wildlife Disease Association (CSU WDA), where we gathered students and professionals to collectively investigate a simulated wildlife disease outbreak. CSU WDA student members designed the workshop and recruited professionals who are experts in their respective fields to run an outbreak simulation during the event. Based on pre- and post-event evaluation responses, this workshop was effective in increasing participants' knowledge of disease ecology, pathology, genetics, and microbiology, as well as the importance of collaboration among disciplines as it pertains to wildlife disease outbreaks.

Inferring infection hazard in wildlife populations by linking data across individual and population scales.

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.

Novel MEK1 mutation identified by mutational analysis of epidermal growth factor receptor signaling pathway genes in lung adenocarcinoma.

Genetic lesions affecting a number of kinases and other elements within the epidermal growth factor receptor (EGFR) signaling pathway have been implicated in the pathogenesis of human non-small-cell lung cancer (NSCLC). We performed mutational profiling of a large cohort of lung adenocarcinomas to uncover other potential somatic mutations in genes of this pathway that could contribute to lung tumorigenesis. We have identified in 2 of 207 primary lung tumors a somatic activating mutation in exon 2 of MEK1 (i.e., mitogen-activated protein kinase kinase 1 or MAP2K1) that substitutes asparagine for lysine at amino acid 57 (K57N) in the nonkinase portion of the kinase. Neither of these two tumors harbored known mutations in other genes encoding components of the EGFR signaling pathway (i.e., EGFR, HER2, KRAS, PIK3CA, and BRAF). Expression of mutant, but not wild-type, MEK1 leads to constitutive activity of extracellular signal-regulated kinase (ERK)-1/2 in human 293T cells and to growth factor-independent proliferation of murine Ba/F3 cells. A selective MEK inhibitor, AZD6244, inhibits mutant-induced ERK activity in 293T cells and growth of mutant-bearing Ba/F3 cells. We also screened 85 NSCLC cell lines for MEK1 exon 2 mutations; one line (NCI-H1437) harbors a Q56P substitution, a known transformation-competent allele of MEK1 originally identified in rat fibroblasts, and is sensitive to treatment with AZD6244. MEK1 mutants have not previously been reported in lung cancer and may provide a target for effective therapy in a small subset of patients with lung adenocarcinoma.