Computational synchronization of microarray data with application to Plasmodium falciparum

Proteome Science

Proceedings

Jacquin C Niles¹  Jianshu Cao²  Wei Zhao³  Justin Dauwels³ 

[1] Singapore-MIT Alliance for Research and Technology, Centre for Life Sciences, 28 Medical Drive, 117456, Singapore;Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 56-341, 02139, Cambridge, MA, USA;Singapore-MIT Alliance for Research and Technology, Centre for Life Sciences, 28 Medical Drive, 117456, Singapore;Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 6-237A, 02139, Cambridge, MA, USA;Singapore-MIT Alliance for Research and Technology, Centre for Life Sciences, 28 Medical Drive, 117456, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore;

关键词: Microarray Data;    Microarray Experiment;    Stage Parasite;    Normalize Life Span;    Infection Period;   

DOI  :  10.1186/1477-5956-10-S1-S10

来源: Springer

【 摘 要 】

BackgroundMicroarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data.MethodsWe develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC.ResultsBy analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions.ConclusionsThis study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved in this process. Overall, these results indicate that further functional analysis of these additional putative protein kinases may reveal new insights into how the P. falciparum IDC is regulated.

【 授权许可】

Unknown   
© Zhao et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.