Toxoplasma gondii is an Apicomplexan parasite that
chronically infects at least a quarter of the global human population,
with potentially fatal consequences during pregnancies and among the
immunocompromised. Characterized by an extraordinarily diverse host
range and increasing incidences of drug resistance, the organism's
metabolism and factors affecting its virulence have been studied by the
Parkinson lab through the use of modeling and comparative genomics.
The Plasmodium group of Apicomplexan parasites is
responsible for the continued transmission of malaria, a disease that
continues to impact millions of lives across the globe. The Parkinson
lab has extensively studied the metabolic network of the most prominent
and deadly member of the genus, Plasmodium falciparum. We have
also sought to characterize the organism's inner membrane complex (IMC),
an essential part of the parasite's infection machinery.
The Apicomplexa branch of single-celled eukaryotic parasites
represents a significant portion of known human pathogens, preying
especially on the immunocompromised and inhabitants of the Third World.
Many of these parasites are gaining new prominence in human healthcare
with the emergence of infections resistant to traditional modes of
treatment. The Parkinson lab has made several comparative analyses of
Apicomplexan genomes, and has also worked toward characterizing proteins
responsible for virulence and protein palmitoylation in these
Worms, particularly those belonging to the nematode and cestode
division of the clade, represent an important branch of eukaryotes to
study as vectors of human disease and as model organisms. The Parkinson
lab has investigated patterns of evolution in tapeworms, and further
investigated the development and regulatory pathways of worms at a
genomic and transcriptomic level. It has also been active in the
curation of sequencing information of nematode worms.
Metagenomics seeks to understand entire systems of organisms, as
found in samples of fresh earth, the bottom of the sea, or even within
human bodies, at a genomic level. This novel approach to biology is
expected to significantly improve understanding of ecosystems at a
microscopic scale. The Parkinson lab has been active in the emerging
field of metagenomics, with a particular interest in understanding the
dynamics of microbiotic locales associated with human disease.
Metatranscriptomic surveys seeks to push our understanding of
biology from studies of individual genomes toward investigations of the
patterns of genomic expression across entire communities of species
existing at the microscopic scale. The Parkinson lab has already
investigated the contents of a mammalian intestine at the
metatranscriptomic level, and is working toward producing a fully
functional pipeline to aid future investigations of this type of
The production of high-quality software tools meant for
microbiome study has been an important priority for the Parkinson lab.
Next generation sequencing (NGS)-based approaches to the study of
microbial communities present a number of unique challenges in data
analysis, necessitating the development of special tools and pipelines
to effectively process the raw information.
Understanding the components of an organism's metabolism allows
for clear descriptions of the systems of regulation and utilization of
the chemical components of a cell's environment as well as providing
clues to its internal state. In the case of the Parkinson lab's analyses
of Apicomplexan parasites, these investigations may play an essential
role in the identification of drug targets and novel modes of treatment.
The lab has also investigated the development of metabolism from an
Biological systems are composed of myriad constituent parts,
interacting with proteins, nucleic acids, and metabolites to create
order out of constantly changing environments. The mapping of the
networks of interaction by which this fundamental biological process is
done has been an important focus of biologists, particularly in the last
decade, and is an important area of research for the Parkinson lab,
particularly in the model organism, Escherichia coli.
The advent of next-generation sequencing has resulted in an
unprecedented quantity of biological data in the form of genomic
information. The Parkinson lab is currently studying this information
with the intent of providing important insights into the patterns of
evolution across entire swathes of microbiotic life forms. These sorts
of investigations promise to clarify the selective pressures and
environmental cues that compel bacterial evolution.
Bacterial life has undergone billions of years of evolution,
resulting in some of the most diverse biological functions on the
planet. The evolution of these life forms poses challenges to medicine
in the form of emerging drug resistance. The Parkinson Lab's research in
bacterial evolution seeks to use the hundreds of bacterial genomes
currently available, as well as computational tools and gene orthology
predictors, to determine patterns in evolution across the entire
spectrum of bacterial life.
Metabolomics seeks to analyse and identify those metabolic patterns that render a bacterium "unique".
Extracellular matrix fibres, produced as monomers, self-assemble
into polymeric structures that impart their unique properties. For
example, changes in the number and arrangement of the elastomeric and
cross-linking regions in elastic fibres have been shown to significantly
impact their assembly and mechanical properties. The use of computer
simulations allows us to explore the evolution of polymeric ECM proteins
and may prove valuable for the tuneable design of new molecules that
may be exploited as useful biomaterials.
Sequence / Function Relationships
Elastic fibres provide flexibility to cardiac, dermal, and
arterial tissues. Abnormalities can adversely affect the integrity of
fibres leading to disease. We are studying genetic variations e.g.
single nucleotide polymorphisms (SNPs) at sites within elastin and other
elastic fibre genes using bioinformatic and wet lab approaches to
discover variants leading to adverse changes in the physical and
functional properties of the resulting proteins.
The extracellular matrix (ECM) is a 3D meshwork of proteins
imparting structure and mechanical stability to tissues. With major
roles in cell adhesion, proliferation and morphogenesis, defects in the
ECM are implicated in e.g. cancer, fibrosis and arthritis. We defined
an initial set of ECM components and constructed an ECM-interactome.
This network is used to identify functional modules and as a framework
to organize and interpret expression data, disease associations and
Although it is well known that some ECM proteins are ancient,
the relative contributions of ancient and novel domains to ECM evolution
have not been previously quantified. Using a systems approach, we
identify domains of eukaryotic and metazoan origin recruited into new
roles in vertebrate-specific combinations coinciding with the
acquisition of novel proteins accounting for approximately 2/3 of the
ECM proteins in humans.
The study of entire genomes has become an important component of
biological inquiry. The Parkinson lab has been involved in the analysis
of a wide variety of genomes, including those of bacteria, tapeworms,
and Apicomplexan parasites. Our analyses of these data sources continue
to move forward through the analysis of entire systems of genomes,
through our work in metagenomics.
Biological complexity arises from the many connections between parts of
cells. Members of the Parkinson lab have been involved in determining
the structural components that mediate these connections in complex,
multi-segment protein complexes. Other members have sought to predict
novel connections in emerging genomes.
The Parkinson lab has developed several tools associated with the
prediction and mapping of metabolic networks, especially in parasitic
organisms. These metabolic networks may in the future present important
targets for pharmaceutical intervention.
Models represent an important part of computational biology. The
Parkinson lab has been involved in the creation of models representing
the flow of metabolites through metabolic networks in parasitic
organisms, as well as models defining the extracellular matrix in