Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data

Abstract

BackgroundTechnological improvements have shifted the focus from data generation to data analysis. The availability of large amounts of data from transcriptomics, protemics and metabolomics experiments raise new questions concerning suitable integrative analysis methods. We compare three integrative analysis techniques (co-inertia analysis, generalized singular value decomposition and integrative biclustering) by applying them to gene and protein abundance data from the six life cycle stages of Plasmodium falciparum. Co-inertia analysis is an analysis method used to visualize and explore gene and protein data. The generalized singular value decomposition has shown its potential in the analysis of two transcriptome data sets. Integrative Biclustering applies biclustering to gene and protein data.ResultsUsing CIA, we visualize the six life cycle stages of Plasmodium falciparum, as well as GO terms in a 2D plane and interpret the spatial configuration. With GSVD, we decompose the transcriptomic and proteomic data sets into matrices with biologically meaningful interpretations and explore the processes captured by the data sets. IBC identifies groups of genes, proteins, GO Terms and life cycle stages of Plasmodium falciparum. We show method-specific results as well as a network view of the life cycle stages based on the results common to all three methods. Additionally, by combining the results of the three methods, we create a three-fold validated network of life cycle stage specific GO terms: Sporozoites are associated with transcription and transport; merozoites with entry into host cell as well as biosynthetic and metabolic processes; rings with oxidation-reduction processes; trophozoites with glycolysis and energy production; schizonts with antigenic variation and immune response; gametocyctes with DNA packaging and mitochondrial transport. Furthermore, the network connectivity underlines the separation of the intraerythrocytic cycle from the gametocyte and sporozoite stages.ConclusionUsing integrative analysis techniques, we can integrate knowledge from different levels and obtain a wider view of the system under study. The overlap between method-specific and common results is considerable, even if the basic mathematical assumptions are very different. The three-fold validated network of life cycle stage characteristics of Plasmodium falciparum could identify a large amount of the known associations from literature in only one study.

Molecular Profiling of Phagocytic Immune Cells in Anopheles gambiae Reveals Integral Roles for Hemocytes in Mosquito Innate Immunity

“…Multiple Coinertia Analysis (MCIA)-MCIA is an integrative analysis method that can be applied to multiple (OMICS) data sets simultaneously (16,17). The data sets are matrices in which the number of features, typically stored in the rows, is much larger than the number of samples, typically stored in the columns.…”

“…Comparisons Between Phagocyte Proteome Profiles and Published Hemocyte Transcriptomes-To compare our granulocyte-enriched proteomes (SF, BF, PF) (supplemental Table S4) with existing hemocyte transcriptional profiles (8), we performed MCIA (16,17) to determine the correlation between protein and transcript data. Granulocyte protein samples were directly compared with transcriptional profiles produced by Pinto et al (8) of nonselected hemocytes from naïve sugar-fed mosquitoes, 24 h after feeding with a noninvasive CTRP mutant Plasmodium berghei (comparable to a noninfectious blood meal), or 24 h post-infection with wild-type P. berghei (8).…”

Platform-Independent Genome-Wide Pattern of DNA Copy-Number Alterations Predicting Astrocytoma Survival and Response to Treatment Revealed by the GSVD Formulated as a Comparative Spectral Decomposition

“…This demonstrated that the GSVD can be used to correctly predict previously unknown cellular mechanisms. Since then, the GSVD has been used to separate the similar from the dissimilar between different species, as well as between different types of molecular biological profiles, mostly large-scale (e.g., mRNA and protein expression in addition to DNA copy-number profiles), and different profiling technologies (e.g., NGS and quantitative real-time PCR in addition to DNA microarray platforms) [18–23] (see also [24–26]).…”

Molecular and biochemical tricks of the research trade: -omics approaches in finfish aquaculture

“…Rezola et al 2014;Tomescu et al 2014). Notwithstanding the expense and complex bioinformatics challenges associated with such integration, its uptake is likely to increase in future.…”