A compendium of molecules involved in vector-pathogen interactions pertaining to malaria

Malaria is a vector-borne disease causing extensive morbidity, debility and mortality. Development of resistance to drugs among parasites and to conventional insecticides among vector-mosquitoes necessitates innovative measures to combat this disease. Identification of molecules involved in the maintenance of complex developmental cycles of the parasites within the vector and the host can provide attractive targets to intervene in the disease transmission. In the last decade, several efforts have been made in identifying such molecules involved in mosquito-parasite interactions and, subsequently, validating their role in the development of parasites within the vector. In this study, a list of mosquito proteins, which facilitate or inhibit the development of malaria parasites in the midgut, haemolymph and salivary glands of mosquitoes, is compiled. A total of 94 molecules have been reported and validated for their role in the development of malaria parasites inside the vector. This compendium of molecules will serve as a centralized resource to biomedical researchers investigating vector-pathogen interactions and malaria transmission. © 2013 Sreenivasamurthy et al.; licensee BioMed Central Ltd

Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

© 2017 Wong et al.; Published by Cold Spring Harbor Laboratory Press. Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions, 192 novel protein start sites, 19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted noncoding RNAs to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes

Dataset on fat body proteome of Anopheles stephensi Liston

Fat body from Anopheles stephensi female mosquitoes were dissected and processed for proteomic analysis. Both SDS-PAGE and basic Reverse Phase Liquid Chromatography-based fractionation strategies were used to achieve a broad coverage of protein identification. The fractionated peptides were then analyzed on a high-resolution mass spectrometer. Searching the raw data against the protein database of An. stephensi resulted in identification of 4535 proteins, which is, to our knowledge, the largest catalog of fat body proteome in any mosquito vector species reported so far. Bioinformatics analysis on these fat body proteins suggested the enrichment of biological processes including carbon and lipid metabolism, amino acid metabolism, signal peptide processing and oxidation-reduction. In addition, using proteogenomic approaches, 43 novel proteins were identified, which were not listed in the annotated gene annotations of An. stephensi. The data used in the analysis are related to the article ‘Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes’ (Prasad et al., 2017)

Proteome data of Anopheles stephensi hemolymph using high resolution mass spectrometry

The article provides insights into the protein expression in Anopheles stephensi hemolymph. We carried out data acquisition using a high-resolution LTQ-Orbitrap Velos mass spectrometer to identify the hemolymph proteins of An. stephensi. Experimentally derived mass spectrometry data was analyzed using Proteome Discoverer 2.1 software using two different search algorithms SEQUEST and MASCOT. A total of 1091 proteins were identified from the hemolymph. The identified proteins were categorized for their role in biological processes and molecular functions. The interactions between these proteins were predicted using STRING online tool. Relation can be drawn between the data provided in this study to the already published article “Integrating transcriptomics and proteomics data for accurate assembly and annotation of genomes” (Prasad et al., 2017) [1]

Proteome data of Anopheles stephensi ovary using high-resolution mass spectrometry

This article contains data on the proteins expressed in the ovaries of Anopheles stephensi, a major vector of malaria in India. Data acquisition was performed using a high-resolution Orbitrap-Velos mass spectrometer. The acquired MS/MS data was searched against An. stephensi protein database comprising of 11,789 sequences. Overall, 4407 proteins were identified, functional analysis was performed for the identified proteins and a protein-protein interaction map predicted. The data provided here is also related to a published article - “Integrating transcriptomics and proteomics data for accurate assembly and annotation of genomes” (Prasad et al., 2017) [1]

Mapping Anopheles stephensi midgut proteome using high-resolution mass spectrometry

Anopheles stephensi Liston is one of the major vectors of malaria in urban areas of India. Midgut plays a central role in the vector life cycle and transmission of malaria. Because gene expression of An. stephensi midgut has not been investigated at protein level, an unbiased mass spectrometry-based proteomic analysis of midgut tissue was carried out. Midgut tissue proteins from female An. stephensi mosquitoes were extracted using 0.5% SDS and digested with trypsin using two complementary approaches, in-gel and in-solution digestion. Fractions were analysed on high-resolution mass spectrometer, which resulted in acquisition of 494,960 MS/MS spectra. The MS/MS spectra were searched against protein database comprising of known and predicted proteins reported in An. stephensi using Sequest and Mascot software. In all, 47,438 peptides were identified corresponding to 5,709 An. stephensi proteins. The identified proteins were functionally categorized based on their cellular localization, biological processes and molecular functions using Gene Ontology (GO) annotation. Several proteins identified in this data are known to mediate the interaction of the Plasmodium with vector midgut and also regulate parasite maturation inside the vector host. This study provides information about the protein composition in midgut tissue of female An. stephensi, which would be useful in understanding vector parasite interaction at molecular level and besides being useful in devising malaria transmission blocking strategies. The data of this study is related to the research article “Integrating transcriptomics and proteomics data for accurate assembly and annotation of genomes”

Integrated genomic analysis reveals mutated ELF3 as a potential gallbladder cancer vaccine candidate

Gallbladder cancer incidence shows characteristic geographic patterns. Here the authors perform a genomic analysis of gallbladder cancers in patients from countries with high incidence (South Korea, India and Chile) and identify ELF3 and other significantly mutated genes not previously associated with gallbladder cancer

A draft map of the human proteome

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease. © 2014 Macmillan Publishers Limited