175
Chapter 10
Prediction of ProteinProtein Interactions Between
Human Host and Two
Mycobacterial Organisms
Oruganty Krishnadev
Indian Institute of Science, India
Shveta Bisht
Indian Institute of Science, India
Narayanaswamy Srinivasan
Indian Institute of Science, India
ABSTRACT
The genomes of many human pathogens have been sequenced but the protein-protein interactions across
a pathogen and human are still poorly understood. The authors apply a simple homology-based method
to predict protein-protein interactions between human host and two mycobacterial organisms viz.,
M.tuberculosis and M.leprae. They focused on secreted proteins of pathogens and cellular membrane
proteins to restrict to uncovering biologically significant and feasible interactions. Predicted interactions
include five mycobacterial proteins of yet unknown function, thus suggesting a role for these proteins
in pathogenesis. The authors predict interaction partners for secreted mycobacterial antigens such as
MPT70, serine proteases and other proteins interacting with human proteins, such as toll-like receptors,
ras signalling proteins and immune maintenance proteins, that are implicated in pathogenesis. These
results suggest that the list of predicted interactions is suitable for further analysis and forms a useful
step in the understanding of pathogenesis of these mycobacterial organisms.
DOI: 10.4018/978-1-4666-1785-8.ch010
Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Prediction of Protein-Protein Interactions Between Human Host and Two Mycobacterial Organisms
INTRODUCTION
Tuberculosis (TB) has adversely affected human
affairs since biblical times. WHO estimates that
there were 1.7 million cases of death due to tuberculosis in 2007 and around 13 million cases of
Tuberculosis globally, most of them from Africa
and South East Asian regions (www.who.int/tb/
publications/global_report/2009/key_points/en/
index.html). The standard medication for TB
followed worldwide is isoniazid and rifampicin.
However, the emergence of multi drug resistant
strains (LoBue, 2009) has prompted a worldwide
attempt to develop newer and more effective drugs
for the treatment of TB (Kamal, Azeera, Malik,
Shaik, & Rao, 2008; Guy & Mallampalli, 2008).
Further complications in tackling TB are due to
the persistence of M.tuberculosis bacteria inside
the macrophages, which makes drug delivery inefficient. Due to these reasons, there is an increased
need to understand the molecular mechanism of
persistence of M.tuberculosis inside the human
macrophages and to evolve strategies to disrupt
the host-pathogen interplay which leads to this
persistence of the bacteria inside the host (Houben,
Nguyen & Pieters, 2006; Pieters, 2008; Zahrt,
2008). Recent advances in understanding mycobacterium physiology (Young, Stark & Kirschner,
2008; Tailleux et al, 2008) including a computational study of protein-protein interactions in the
pathogen (Cui, Zhang, Wang & He, 2008) may
lead to a better understanding. However the molecular details of host-pathogen interactions for
this organism are still not very well understood.
The host-pathogen interplay in the initial
stages of infection in TB, is mainly due to glycolipids and/or lipoproteins (Józefowski, Sobota, &
Kwiatkowska, 2008) with crucial roles believed
to be mediated by secreted proteins. Thus, there
is a need to understand the molecular details of
protein-protein interactions occurring between
the human host and bacterial pathogen.
Another diseases similar to TB is Leprosy,
it affects mainly the neuronal cells and causes
176
degeneration of the nerves. The organism causing
leprosy is Mycobacterium leprae and is closely
related to M.tuberculosis.
The detection of protein-protein interactions
is not very efficient in such systems and novel
procedures have been proposed for experimental
detection of protein-protein interactions occurring
among the proteins of M.tuberculosis (O’hare,
Juillerat, Dianiskov_, & Johnsson, 2008). Such
approaches and previously proposed methods
(Suter, Kittanakom, & Stagljar, 2008; Lalonde et
al., 2008) can be extended to detect protein -protein interactions occurring between the host and
pathogen also, but to our knowledge has not been
attempted so far on a genome scale. We cannot
understand the pathophysiology of TB without a
comprehensive list of protein-protein interactions
(PPI) across the host and pathogen organisms, and
in order to bridge the gap we applied a method
we developed earlier (Krishnadev & Srinivasan,
2008) for the prediction of PPI across the host
and pathogen organisms.
The prediction of PPI is being extensively
attempted in the recent years at the level of an
organism. Various methods have been proposed
for prediction of PPI within an organism (e.g.,
Wojcik, Boneca & Legrain, 2002; Zhong &
Sternberg, 2006; Persico et al., 2005; Rhodes et
al., 2005; Huang et al., 2004). In the recent years
fewer methods have been proposed to predict PPI
across organisms (Dyer, Murali, & Sobral, 2007;
Dyer, Murali & Sobral, 2008; Davis, Barkan,
Eswar, McKerrow, & Sali, 2008; Krishnadev &
Srinivasan, 2008, Lee et al., 2008). Typically, the
approach used in such predictions is to employ a
set of known PPIs as template and use homology
to infer PPI occurring between target proteins. Our
approach to the problem is to identify proteins of
host and pathogen with high sequence similarity
to interacting proteins in the template dataset. The
high sequence similarity ensures that PPI properties are conserved, and it is especially necessary
since it has been shown earlier that interaction
properties can be different for proteins showing
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