JCJC SVSE 6 - JCJC : Sciences de la vie, de la santé et des écosystèmes : Génomique, génomique fonctionnelle, bioinformatique, biologie systémique

Computational methods for the analysis of transcriptional regulation in Plasmodium falciparum – PlasmoExpress

Computational methods for the analysis of transcriptomic regulation in Plasmodium falciparum

This project aims to develop new bioinformatic methods to understand <br />how the parasite responsible for malaria regulates the activity of its <br />genes, in response to a stress or a treatment. Ultimately, one aim is <br />to understand how the parasite reacts to an anti-malarial treatment, <br />to improve existing treatments and find new ones. <br />

Understand the biology of one of the deadliest parasites

Malaria is one of the deadliest infectious diseases, threatening half <br />a billion humans worldwide with a yearly death toll of 1 to 2 million <br />people, mainly in developing countries. Malaria is due to infections <br />by protozoan parasites of the Plasmodium genus, transmitted by bites <br />of female Anopheles mosquitoes. <br /> <br />Despite sustained efforts to combat the disease, safe and affordable <br />new drugs, and new drug targets, are still required to circumvent drug <br />resistance outbreaks. To this end, a fundamental understanding of how <br />parasite genes are regulated is critical to developing novel <br />therapeutic strategies against this organism. New insights into the <br />complex processes that regulate genes involved in key functions such <br />as transmission success, immune evasion, and drug resistance are <br />expected to provide promising new drug targets. In addition, this can <br />also shed light on the mode of action of known drugs, and help <br />understanding the Plasmodium resistance mechanisms. <br /> <br /> <br />The aim of this project is to develop new bioinformatic methods to <br />unravel the mechanisms regulating gene activity in <br />Plasmodium. Ultimately, the goals are identifying new therapeutic <br />targets, and identifying targets of known anti-malarial. <br />

In addition to its genome sequenced in 2002, numerous high-throughput
studies have screened the activity of the Plasmodium genes under
various conditions, normal or following an antimalarial
treatment. These data, often referred to as post-genomic data, have
shown a tightly controlled and intricate gene expression
program. However, apart from a few specific genes, we remain largely
ignorant of the mechanisms underlying gene control. The objective of
this project is to develop new computational methods for analyzing the
genomic and post-genomic data of Plasmodium in order to identify 1)
the mechanisms underlying gene control; 2) the key targets of known
antimalarial drugs. An essential component of post-genomic data is,
besides to their large size, the fact they are often noisy. This makes
the identification of the few genes involved in a particular mechanism
particularly difficult. Therefore, it is necessary to use specially
designed probabilistic and statistical methods in order to
differentiate what is a specific biological response, what is only
noise, and what is a biological co-occurring response with no direct
link with the observed phenomenon.

A major outcome of the project is a method which identifies in the
genome of a given organism (Plasmodium, but the method was also
successfully applied to other organisms) regulatory signals related to
the activity of its genes. More specifically, the method identifies
«words« of length around ten nucleotides (A, T, G, C) whose presence
in the immediate vicinity of a gene is correlated with the expression
profile of this gene, i.e. its activity level at different time points
of the cell cycle. In other word, it is these words in the genome
which code when a gene should be activated or inactivated. In
Plasmodium, this method allowed to identify about thirty words
correlated to specific profiles: words whose presence near a gene
induced a high activity-level early in the cycle cell, words inducing
reverse expression-profiles, etc..

This method has been implemented in a software called RED2, which is
freely available on the bioinformatics platform of the LIRMM. Users
upload a set of expression profiles and select an organism, and the
platform sends them by email all regulatory signals identified by the
program, along with the list of genes they control.
www.atgc-montpellier.fr/RED2/

One perspective of this work is to realize a comprehensive inventory
of all regulatory signals present in the Plasmodium genome, using the
RED2 method on all post-genomic data produced for this organism.


The RED2 method has been accepted for publication in the journal
Genome Biology:
Computational Discovery of Regulatory Elements in a term continuous
space. Lajoie M., Gascuel O., V. Lefort, Brehelin L. Genome Biology,
in pr

Malaria is one of the deadliest infectious diseases, threatening half
a billion humans worldwide with a yearly death toll of 1 to 2 million
people, mainly in developing countries. Malaria is due to infections
by protozoan parasites of the Plasmodium genus, transmitted by bites
of female Anopheles mosquitoes. Of the four species that infect
humans, P.falciparum causes the greatest incidence of illness and
death.

The genome of P.falciparum has been published in 2002. It is an
atypical genome with a large proportion of A/T (80%) and the presence
of long low-complexity insertions of unknown function. Around 60% of
the ~5500 predicted genes do not have sufficient similarity to
characterized genes in other species to justify provision of
functional assignments and have no annotation in the Gene Ontology
(http://www.geneontology.org). Although this situation may be
explained by the existence of genes that are unique to the Plasmodium
genus, it is further exacerbated by the high evolutionary distance
between P.falciparum and other sequenced organisms, which makes
homology detection particularly difficult.

Despite sustained efforts to combat the disease, safe and affordable
new drugs, and new drug targets, are still required to circumvent drug
resistance outbreaks. To this end, a fundamental understanding of how
parasite genes are regulated is critical to developing novel
therapeutic strategies against this organism. New insights into the
complex processes that regulate genes involved in key functions such
as transmission success, immune evasion, and drug resistance are
expected to provide promising new drug targets. In addition, this can
also shed light on the mode of action of known drugs, and help
understanding the P.falciparum resistance mechanisms.

Numerous high-throughput studies have screened P.falciparum gene
expression under various conditions, showing a tightly controlled and
intricate gene expression program. However, apart from a few specific
genes, we remain largely ignorant of the mechanisms underlying gene
control, and, more specifically, on the relative role of
transcriptional and post-transcriptional regulation in the parasite.

This project aims at developing new computational methods to decipher
the mechanisms of gene expression regulation in P.falciparum. The
objectives are to identify both new drug targets and targets of
already known drugs. Three tasks compose the core of the project: 1)
Searching for new transcription factors into the P.falciparum
proteome; 2) Investigating to what extent chromatin modification and
post-transcriptional processes control steady-state mRNA; 3)
Characterizing the transcriptomic response of P.falciparum to known
drugs. From a computational perspective, this involves the development
of new approaches for homology detection, high-throughput data
modeling, and feature selection. We will use machine learning
approaches involving HMMs, mixture models, time series analysis,
clustering, and various learning algorithms able to cope with the
inherent nature of most post-genomic data.

This project is a collaboration between the bioinformatic team of the
LIRMM (Montpellier) and three biology laboratories involved in the
study of P.falciparum: the Eric Maréchal's team in the LPCV
(Grenoble), the Henri Vial's team in the laboratory DIMNP
(Montpellier), and the Karine Le Roch's laboratory in the University
of California (Riverside). These three laboratories have a long
experience in the study of P.falciparum and in drug discovery, and
they have collaborated several times.

Project coordinator

Monsieur Laurent BRÉHÉLIN (CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE - DELEGATION REGIONALE LANGUEDOC-ROUSSILLON) – brehelin@lirmm.fr

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

LIRMM CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE - DELEGATION REGIONALE LANGUEDOC-ROUSSILLON

Help of the ANR 190,000 euros
Beginning and duration of the scientific project: - 36 Months

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