Evolutionary conservation and diversification of complex synaptic function in human proteome
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Date
02/07/2018Author
Pajak, Maciej
Metadata
Abstract
The evolution of synapses from early proto-synaptic protein complexes in unicellular
eukaryotes to sophisticated machines comprising thousands of proteins parallels the
emergence of finely tuned synaptic plasticity, a molecular correlate for memory and
learning.
Phenotypic change in organisms is ultimately the result of evolution of their genotype
at the molecular level. Selection pressure is a measure of how changes in genome
sequence that arise though naturally occurring processes in populations are fixed or
eliminated in subsequent generations. Inferring phylogenetic information about proteins
such as the variation of selection pressure across coding sequences can provide
valuable information not only about the origin of proteins, but also the contribution
of specific sites within proteins to their current roles within an organism. Recent
evolutionary studies of synaptic proteins have generated attractive hypotheses about
the emergence of finely-tuned regulatory mechanisms in the post-synaptic proteome
related to learning, however, these analyses are relatively superficial.
In this thesis, I establish a scalable molecular phylogenetic modelling framework
based on three new inference methodologies to investigate temporal and spatial aspects
of selection pressure changes for the whole human proteome using protein
orthologs from up to 68 taxa.
Temporal modelling of evolutionary selection pressure reveals informative features
and patterns for the entire human proteome and identifies groups of proteins that
share distinct diversification timelines. Multi-ontology enrichment analysis of these
gene cohorts was used to aid biological interpretation, but these approaches are statistically
under powered and do not capture a clear picture of the emergence of synaptic
plasticity. Subsequent pathway-centric analysis of key synaptic pathways extends the
interpretation of temporal data and allows for revision of previous hypotheses about
the evolution of complex synaptic function. I proceed to integrate inferred selection
pressure timeline information in the context of static protein-protein interaction data.
A network analysis of the full human proteome reveals systematic patterns linking
the temporal profile of proteins’ evolution and their topological role in the interaction
graph. These graphs were used to test a mechanistic hypothesis that proposed a
propagating diversification signal between interactors using the temporal modelling
data and network analysis tools.
Finally, I analyse the data of amino-acid level spatial modelling of selection pressure
events in Arc, one of the master regulators of synaptic plasticity, and its interactors
for which detailed experimental data is available. I use the Arc interactome as
an example to discuss episodic and localised diversifying selection pressure events in
tightly coupled complexes of protein and showcase potential for a similar systematic
analysis of larger complexes of proteins using a pathway-centric approach.
Through my work I revised our understanding of temporal evolutionary patterns
that shaped contemporary synaptic function through profiling of emergence and refinement
of proteins in multiple pathways of the nervous system. I also uncovered
systematic effects linking dependencies between proteins with their active diversification,
and hypothesised about their extension to domain level selection pressure
events.