Profiling Yeast Deletion Strains Using Sample Multiplexing and Network-Based Analyses

The
yeast, Saccharomyces cerevisiae, is
a widely used model system for investigating conserved biological
functions and pathways. Advancements in sample multiplexing have facilitated
the study of the yeast proteome, yet many yeast proteins remain uncharacterized
or only partially characterized. Yeast deletion strain collections
are powerful resources for yeast proteome studies, uncovering the
effects of gene function, genetic interactions, and cellular stresses.
As complex biological systems cannot be understood by simply analyzing
the individual components, a systems approach is often required in
which a protein is represented as a component of large, interacting
networks. Here, we evaluate the current state of yeast proteome analysis
using isobaric tag-based sample multiplexing (TMTpro16) to profile
the proteomes of 75 yeast deletion strains for which we measured the
abundance of nearly 5000 proteins. Using statistical approaches, we
highlighted covariance and regulation subnetworks and the enrichment
of gene ontology classifications for covarying and coregulated proteins.
This dataset presents a resource that is amenable to further data
mining to study individual deletion strains, pathways, proteins, and/or
interactions thereof while serving as a template for future network-based
investigations using yeast deletion strain collections.