Identification of novel dendritic cell subset markers in human blood

Human dendritic cells (DC) are key regulators of innate and adaptive immunity that can be divided in at least three major subpopulations: plasmacytoid DC (pDC), myeloid type 1 DC (mDC1) and myeloid type 2 DC (mDC2) exhibiting different functions. However, research, diagnostic and cell therapeutic studies on human DC subsets are limited because only few DC subset markers have been identified so far. Especially mDC2 representing the rarest blood DC subset are difficult to be separated from mDC1 and pDC due to a paucity of mDC2 markers. We have combined multiparameter flow cytometry analysis of human blood DC subsets with systematic expression analysis of 332 surface antigens in magnetic bead-enriched blood DC samples. The initial analysis revealed eight novel putative DC subset markers CD26, CD85a, CD109, CD172a, CD200, CD200R, CD275 and CD301 that were subsequently tested in bulk peripheral blood mononuclear cell (PBMC) samples from healthy blood donors. Secondary analysis of PBMC samples confirmed three novel DC subset markers CD26 (dipeptidyl peptidase IV), CD85a (Leukocyte immunoglobulin-like receptor B3) and CD275 (inducible costimulator ligand). CD85a is specifically expressed in mDC1 and CD26 and CD275 represent novel mDC2 markers. These markers will facilitate human DC subset discrimination and additionally provide insight into potentially novel DC subset-specific functions.     

Reliable gene signatures for microarray classification: assessment of stability and performance

MOTIVATION: Two important questions for the analysis of gene expression measurements from different sample classes are (1) how to classify samples and (2) how to identify meaningful gene signatures (ranked gene lists) exhibiting the differences between classes and sample subsets. Solutions to both questions have immediate biological and biomedical applications. To achieve optimal classification performance, a suitable combination of classifier and gene selection method needs to be specifically selected for a given dataset. The selected gene signatures can be unstable and the resulting classification accuracy unreliable, particularly when considering different subsets of samples. Both unstable gene signatures and overestimated classification accuracy can impair biological conclusions. METHODS: We address these two issues by repeatedly evaluating the classification performance of all models, i.e. pairwise combinations of various gene selection and classification methods, for random subsets of arrays (sampling). A model score is used to select the most appropriate model for the given dataset. Consensus gene signatures are constructed by extracting those genes frequently selected over many samplings. Sampling additionally permits measurement of the stability of the classification performance for each model, which serves as a measure of model reliability. RESULTS: We analyzed a large gene expression dataset with 78 measurements of four different cartilage sample classes. Classifiers trained on subsets of measurements frequently produce models with highly variable performance. Our approach provides reliable classification performance estimates via sampling. In addition to reliable classification performance, we determined stable consensus signatures (i.e. gene lists) for sample classes. Manual literature screening showed that these genes are highly relevant to our gene expression experiment with osteoarthritic cartilage. We compared our approach to others based on a publicly available dataset on breast cancer. AVAILABILITY: R package at http://www.bio.ifi.lmu.de/~davis/edaprakt     

Nipah virus uses leukocytes for efficient dissemination within a host

Nipah virus (NiV) is a recently emerged zoonotic paramyxovirus whose natural reservoirs are several species of Pteropus fruit bats. NiV provokes a widespread vasculitis often associated with severe encephalitis, with up to 75% mortality in humans. We have analyzed the pathogenesis of NiV infection, using human leukocyte cultures and the hamster animal model, which closely reproduces human NiV infection. We report that human lymphocytes and monocytes are not permissive for NiV and a low level of virus replication is detected only in dendritic cells. Interestingly, despite the absence of infection, lymphocytes could efficiently bind NiV and transfer infection to endothelial and Vero cells. This lymphocyte-mediated transinfection was inhibited after proteolytic digestion and neutralization by NiV-specific antibodies, suggesting that cells could transfer infectious virus to other permissive cells without the requirement for NiV internalization. In NiV-infected hamsters, leukocytes captured and carried NiV after intraperitoneal infection without themselves being productively infected. Such NiV-loaded mononuclear leukocytes transfer lethal NiV infection into naïve animals, demonstrating efficient virus transinfection in vivo. Altogether, these results reveal a remarkable capacity of NiV to hijack leukocytes as vehicles to transinfect host cells and spread the virus throughout the organism. This mode of virus transmission represents a rapid and potent method of NiV dissemination, which may contribute to its high pathogenicity.     

The spread of fecally transmitted parasites in socially-structured populations

Mammals are infected by a wide array of gastrointestinal parasites, including parasites that also infect humans and domesticated animals. Many of these parasites are acquired through contact with infectious stages present in soil, feces or vegetation, suggesting that ranging behavior will have a major impact on their spread. We developed an individual-based spatial simulation model to investigate how range use intensity, home range overlap, and defecation rate impact the spread of fecally transmitted parasites in a population composed of social groups (i.e., a socially structured population). We also investigated the effects of epidemiological parameters involving host and parasite mortality rates, transmissibility, disease-related mortality, and group size. The model was spatially explicit and involved the spillover of a gastrointestinal parasite from a reservoir population along the edge of a simulated reserve, which was designed to mimic the introduction pathogens into protected areas. Animals ranged randomly within a "core" area, with biased movement toward the range center when outside the core. We systematically varied model parameters using a Latin hypercube sampling design. Analyses of simulation output revealed a strong positive association between range use intensity and the prevalence of infection. Moreover, the effects of range use intensity were similar in magnitude to effects of group size, mortality rates, and the per-contact probability of transmission. Defecation rate covaried positively with gastrointestinal parasite prevalence. Greater home range overlap had no positive effects on prevalence, with a smaller core resulting in less range overlap yet more intensive use of the home range and higher prevalence. Collectively, our results reveal that parasites with fecal-oral transmission spread effectively in socially structured populations. Future application should focus on parameterizing the model with empirically derived ranging behavior for different species or populations and data on transmission characteristics of different infectious organisms.     

Tumor-infiltrating dendritic cell precursors recruited by a beta-defensin contribute to vasculogenesis under the influence of Vegf-A

The involvement of immune mechanisms in tumor angiogenesis is unclear. Here we describe a new mechanism of tumor vasculogenesis mediated by dendritic cell (DC) precursors through the cooperation of beta-defensins and vascular endothelial growth factor-A (Vegf-A). Expression of mouse beta-defensin-29 recruited DC precursors to tumors and enhanced tumor vascularization and growth in the presence of increased Vegf-A expression. A new leukocyte population expressing DC and endothelial markers was uncovered in mouse and human ovarian carcinomas coexpressing Vegf-A and beta-defensins. Tumor-infiltrating DCs migrated to tumor vessels and independently assembled neovasculature in vivo. Bone marrow-derived DCs underwent endothelial-like differentiation ex vivo, migrated to blood vessels and promoted the growth of tumors expressing high levels of Vegf-A. We show that beta-defensins and Vegf-A cooperate to promote tumor vasculogenesis by carrying out distinct tasks: beta-defensins chemoattract DC precursors through CCR6, whereas Vegf-A primarily induces their endothelial-like specialization and migration to vessels, which is mediated by Vegf receptor-2.     

Genetic changes in a novel breeding population of Brassica napus synthesized from hundreds of crosses between B. rapa and B. carinata

Introgression of genomic variation between and within related crop species is a significant evolutionary approach for population differentiation, genome reorganization and trait improvement. Using the Illumina Infinium Brassica 60K SNP array, we investigated genomic changes in a panel of advanced generation new‐type Brassica napus breeding lines developed from hundreds of interspecific crosses between 122 Brassica rapa and 74 Brassica carinata accessions, and compared them with representative accessions of their three parental species. The new‐type B. napus population presented rich genetic diversity and abundant novel genomic alterations, consisting of introgressions from B. rapa and B. carinata, novel allelic combinations, reconstructed linkage disequilibrium patterns and haplotype blocks, and frequent deletions and duplications (nonrandomly distributed), particularly in the C subgenome. After a much shorter, but very intensive, selection history compared to traditional B. napus, a total of 15 genomic regions with strong selective sweeps and 112 genomic regions with putative signals of selective sweeps were identified. Some of these regions were associated with important agronomic traits that were selected for during the breeding process, while others were potentially associated with restoration of genome stability and fertility after interspecific hybridization. Our results demonstrate how a novel method for population‐based crop genetic improvement can lead to rapid adaptation, restoration of genome stability and positive responses to artificial selection.     

Modulation of habit formation by levodopa in Parkinson's disease

Dopamine promotes the execution of positively reinforced actions, but its role for the formation of behaviour when feedback is unavailable remains open. To study this issue, the performance of treated/untreated patients with Parkinson's disease and controls was analysed in an implicit learning task, hypothesising dopamine-dependent adherence to hidden task rules. Sixteen patients on/off levodopa and fourteen healthy subjects engaged in a Go/NoGo paradigm comprising four equiprobable stimuli. One of the stimuli was defined as target which was first consistently preceded by one of the three non-target stimuli (conditioning), whereas this coupling was dissolved thereafter (deconditioning). Two task versions were presented: in a 'Go version', only the target cue required the execution of a button press, whereas non-target stimuli were not instructive of a response; in a 'NoGo version', only the target cue demanded the inhibition of the button press which was demanded upon any non-target stimulus. Levodopa influenced in which task version errors grew from conditioning to deconditioning: in unmedicated patients just as controls errors only rose in the NoGo version with an increase of incorrect responses to target cues. Contrarily, in medicated patients errors went up only in the Go version with an increase of response omissions to target cues. The error increases during deconditioning can be understood as a perpetuation of reaction tendencies acquired during conditioning. The levodopa-mediated modulation of this carry-over effect suggests that dopamine supports habit conditioning under the task demand of response execution, but dampens it when inhibition is required. However, other than in reinforcement learning, supporting dopaminergic actions referred to the most frequent, i. e., non-target behaviour. Since this is passive whenever selective actions are executed against an inactive background, dopaminergic treatment could in according scenarios contribute to passive behaviour in patients with Parkinson's disease.