Probabilistic movement model with emigration simulates movements of deer in Nebraska, 1990–2006

Movements of deer can affect population dynamics, spatial redistribution, and transmission and spread of diseases. Our goal was to model the movement of deer in Nebraska in an attempt to predict the potential for spread of chronic wasting disease (CWD) into eastern Nebraska. We collared and radio-tracked \u3e600 white-tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) in Nebraska during 1990–2006.We observed large displacements (\u3e10 km) for both species and sexes of deer, including migrations up to 100 km and dispersals up to 50 km. Average distance traveled between successive daily locations was 166m for male and 173 for female deer in eastern Nebraska, and 427m for male and 459 for female deer in western Nebraska. Average daily displacement from initial capture point was 10m for male and 14m for female deer in eastern Nebraska, and 27m for male and 28m for female deer in western Nebraska.We used these data on naturally occurring movements to create and test 6 individual-based models of movement for white-tailed deer and mule deer in Nebraska, including models that incorporated sampling from empirical distributions of movement lengths and turn angles (DIST), correlated random walks (CRW), home point fidelity (FOCUS), shifting home point (SHIFT), probabilistic movement acceptance (MOVE), and probabilistic movement with emigration (MOVEwEMI). We created models in sequence in an attempt to account for the shortcomings of the previous model(s). We used the Kolmogrov–Smirnov goodness-of-fit test to verify improvement of simulated annual displacement distributions to empirical displacement distributions. The best-fit model (D = 0.07 and 0.08 for eastern and western Nebraska, respectively) included a probabilistic-movement chance with emigration (MOVEwEMI) and resulted in an optimal daily movement length of 350m (maximum daily movement length of 2800m for emigrators) for eastern Nebraska and 370m (maximum of 2960m) for western Nebraska. The proportion of deer that moved as emigrators was 0.10 and 0.13 for eastern and western Nebraska, respectively. We propose that the observed spread of CWD may be driven by large movements of a small proportion of deer that help to establish a low prevalence of the disease in areas east of the current endemic area. Our movement models will be used in a larger individual-based simulation of movement, survival, and transmission of CWD to help determine future surveillance and management actions

CD94-NKG2A recognition of human leukocyte antigen (HLA)-E bound to an HLA class I leader sequence

The recognition of human leukocyte antigen (HLA)-E by the heterodimeric CD94-NKG2 natural killer (NK) receptor family is a central innate mechanism by which NK cells monitor the expression of other HLA molecules, yet the structural basis of this highly specific interaction is unclear. Here, we describe the crystal structure of CD94-NKG2A in complex with HLA-E bound to a peptide derived from the leader sequence of HLA-G. The CD94 subunit dominated the interaction with HLA-E, whereas the NKG2A subunit was more peripheral to the interface. Moreover, the invariant CD94 subunit dominated the peptide-mediated contacts, albeit with poor surface and chemical complementarity. This unusual binding mode was consistent with mutagenesis data at the CD94-NKG2A–HLA-E interface. There were few conformational changes in either CD94-NKG2A or HLA-E upon ligation, and such a “lock and key” interaction is typical of innate receptor–ligand interactions. Nevertheless, the structure also provided insight into how this interaction can be modulated by subtle changes in the peptide ligand or by the pairing of CD94 with other members of the NKG2 family. Differences in the docking strategies used by the NKG2D and CD94-NKG2A receptors provided a basis for understanding the promiscuous nature of ligand recognition by NKG2D compared with the fidelity of the CD94-NKG2 receptors

A structural basis for selection and cross-species reactivity of the semi-invariant NKT cell receptor in CD1d/glycolipid recognition

Little is known regarding the basis for selection of the semi-invariant αβ T cell receptor (TCR) expressed by natural killer T (NKT) cells or how this mediates recognition of CD1d–glycolipid complexes. We have determined the structures of two human NKT TCRs that differ in their CDR3β composition and length. Both TCRs contain a conserved, positively charged pocket at the ligand interface that is lined by residues from the invariant TCR α- and semi-invariant β-chains. The cavity is centrally located and ideally suited to interact with the exposed glycosyl head group of glycolipid antigens. Sequences common to mouse and human invariant NKT TCRs reveal a contiguous conserved “hot spot” that provides a basis for the reactivity of NKT cells across species. Structural and functional data suggest that the CDR3β loop provides a plasticity mechanism that accommodates recognition of a variety of glycolipid antigens presented by CD1d. We propose a model of NKT TCR–CD1d–glycolipid interaction in which the invariant CDR3α loop is predicted to play a major role in determining the inherent bias toward CD1d. The findings define a structural basis for the selection of the semi-invariant αβ TCR and the unique antigen specificity of NKT cells

Natural micropolymorphism in human leukocyte antigens provides a basis for genetic control of antigen recognition

Human leukocyte antigen (HLA) gene polymorphism plays a critical role in protective immunity, disease susceptibility, autoimmunity, and drug hypersensitivity, yet the basis of how HLA polymorphism influences T cell receptor (TCR) recognition is unclear. We examined how a natural micropolymorphism in HLA-B44, an important and large HLA allelic family, affected antigen recognition. T cell–mediated immunity to an Epstein-Barr virus determinant (EENLLDFVRF) is enhanced when HLA-B*4405 was the presenting allotype compared with HLA-B*4402 or HLA-B*4403, each of which differ by just one amino acid. The micropolymorphism in these HLA-B44 allotypes altered the mode of binding and dynamics of the bound viral epitope. The structure of the TCR–HLA-B*4405EENLLDFVRF complex revealed that peptide flexibility was a critical parameter in enabling preferential engagement with HLA-B*4405 in comparison to HLA-B*4402/03. Accordingly, major histocompatibility complex (MHC) polymorphism can alter the dynamics of the peptide-MHC landscape, resulting in fine-tuning of T cell responses between closely related allotypes

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease

HIV Drug-resistant Strains as Epidemiologic Sentinels

The decrease in the proportion of drug resistance among newly infected HIV-1 patients may signal a worsening of the epidemic

KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness.

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP-SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10-9) and 3145 (P < 1 × 10-5) SNP-SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene-gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP-SNP interactions were supported by gene expression and protein-protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness