Abstractgene, also known as lymphocyte-specific proto-oncogene, is
Anopheles gambiae Giles sensu stricto (Diptera: Culicidae) is the major Afro-tropical vector of malaria. Novel strategies proposed for the elimination and eradication of this mosquito vector are based on the use of genetic approaches, such as the sterile insect technique (SIT). These approaches rely on the ability of released males to mate with wild females, and depend on the application of effective protocols to assess the swarming and mating behaviours of laboratory-reared insects prior to their release. The present study evaluated whether large semi-field enclosures can be utilized to study the ability of males from a laboratory colony to respond to natural environmental stimuli and initiate normal mating behaviour. Laboratory-reared males exhibited spatiotemporally consistent swarming behaviour within the study enclosures. Swarm initiation, peak and termination time closely tracked sunset. Comparable insemination rates were observed in females captured in copula in the semi-field cages relative to females in small laboratory cages. Oviposition rates after blood feeding were also similar to those observed in laboratory settings. The data suggest that outdoor enclosures are suitable for studying swarming and mating in laboratory-bred males in field-like settings, providing an important reference for future studies aimed at assessing the comparative mating ability of strains for SIT and other vector control strategies.
Background Targeted immunotherapy is mostly associated with cancer treatment wherein designed molecules engage signaling pathways and mutant proteins critical to the survival of the cell. One of several genetic approaches is the use of in silico methods to develop immune epitopes targeting specific antigenic regions on related mutant proteins. In a recent study we showed a functional association between the gamma retrovirus HERV-H Long Terminal Associating (HHLA1, HHLA2 and HHLA3) proteins and melanoma associated antigen of the B class proteins (MAGEB5), with a resultant decrease in expression of HLA class I and II immune variants. HLA-C and HLA-DRB5 were the main HLA class I and II Immune variants, respectively, that showed expression changes across viral samples of interest. Specific immune variants for HLA-C and HLA-DRB5 were filtered for the top ten based on their relative frequency of counts across the samples. Results Protein variants for HHLA1, HHLA2, HHLA3 and MAGEB5 were used to predict antigenic epitope peptides to immune peptide-MHC class I and II binding using artificial neural networks. For IC50 peptide scores (PS) ≥ 0.5 with a transformed binding ability between 0 and 1, the top 5 epitopes identified for all targeted genes HHLA1,2 & 3 and MAGEB5 were qualified as strong or weak binders according to the threshold. Domain analysis using NCBI Conserved Domain Database (CDD) identified HHLA2 with immunoglobulin-like domains (Ig_C1-set) and MAGEB5 with the MAGE Homology Domain (MHD). Linear regression showed a statistical correlation (P < 0.001) for HHLA2 and MAGEB5 predicted epitope peptides to HLA-C but not HLA-DRB5. The prediction model identified HLA-C variant 9 (HLA-C9, BAA08825.1 HLA-B*1511) at 1.1% as the most valuable immune target for clinical considerations. Identification of the 9-mer epitope peptide within the domain showed for HHLA2: YANRTSLFY (PS = 0.5837) and VLAYYLSSSQNTIIN (PS = 0.77) for HLA-C and HLA-DRB5, respectively and for MAGEB5, peptides: FVRLTYLEY (PS = 0.5293) and YPAHYQFLWGPRAYT (PS = 0.62) for HLA-C and HLA-DRB5, respectively. Conclusion Specific immune responses to targeted epitope peptides and their prediction models, suggested co-expression and co-evolution for HHLA2 and MAGEB5 in viral related diseases. HHLA2 and MAGEB5 could be considered markers for virus related tumors and targeted therapy for oncogenic diseases.
Background Viral detection techniques and applications are a critical first step to pathogen detection within a given population, especially during outbreaks. Common viral tests currently used are direct specimen examination, indirect examination and serological tests. Serological tests have gained intense interest because they are rapidly performed with patient blood samples for quick diagnosis and treatment. The diagnostic techniques developed around serology are often expensive, require expertise to use and cannot be afforded by developing countries with recurrent viral outbreaks. Therefore exploiting the huge amount of viral data available in various databases is critical to develop affordable and easy-to-use diagnostic tools. Methods This study obtained viral sample data from Gene Expression Omnibus database with focus on use of viral glycoprotein for host penetration. Gene relative mean across 34 obtained viral samples were extracted into data tables and used with edgeR statistical software in R version 3.3.1. Results Three clusters previously known to be specific (Ebola virus relative viral LCK cluster, EBOVC), specific (Mean differentiation cluster, MDC) and both CD209 and specific (Kurtosis group cluster, KGC), expressed unique LCK CD209 patterns of four proteins of interest (CD209, LCK, IL-2 and MYB). Differential expression analysis showed two cluster patterns on heatmaps, with differentially expressed proteins down-regulated in MDC but up-regulated in KGC and EBOVC for all pairwise cluster comparative analyses performed. Regulatory proteomic variants identified in clusters suggest transcription repression of HLA class I alleles. This study identified viral expression patterns with screening and therapeutic applications. Given that the viral pathogenetic pathway for Ebola has not been clearly identified yet, assembling its components is vital for vaccine development.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.