Inferring developmental stage composition from gene expression in human malaria

PLoS Computational Biology
Regina JoiceMatthias Marti

Abstract

In the current era of malaria eradication, reducing transmission is critical. Assessment of transmissibility requires tools that can accurately identify the various developmental stages of the malaria parasite, particularly those required for transmission (sexual stages). Here, we present a method for estimating relative amounts of Plasmodium falciparum asexual and sexual stages from gene expression measurements. These are modeled using constrained linear regression to characterize stage-specific expression profiles within mixed-stage populations. The resulting profiles were analyzed functionally by gene set enrichment analysis (GSEA), confirming differentially active pathways such as increased mitochondrial activity and lipid metabolism during sexual development. We validated model predictions both from microarrays and from quantitative RT-PCR (qRT-PCR) measurements, based on the expression of a small set of key transcriptional markers. This sufficient marker set was identified by backward selection from the whole genome as available from expression arrays, targeting one sentinel marker per stage. The model as learned can be applied to any new microarray or qRT-PCR transcriptional measurement. We illustrate its use in vitro in...Continue Reading

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Citations

Aug 27, 2015·Wiley Interdisciplinary Reviews. Systems Biology and Medicine·Justine SwannElizabeth A Winzeler
Jun 19, 2015·PLoS Pathogens·Sandra K NilssonMatthias Marti
Jul 7, 2017·PLoS Pathogens·Robert E Sinden
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May 10, 2018·MBio·Nicanor ObaldiaMatthias Marti
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Methods Mentioned

BETA
dissection
PCR
transgenic
fluorescence microscopy
light microscopy
electrophoresis

Software Mentioned

Sleipnir library
PlasmoDB Blast
GSEA
GraphPad Prism
GenePattern
R function quadprog
Gene Set Enrichment Analysis ( GSEA
RMA
PlasmoDB
Nanostring

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