Compartment Proteomics Analysis
of White Perch (<i>Morone americana</i>) Ovary Using Support
Vector Machines
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Abstract
Compartment
proteomics enable broad characterization of target
tissues. We employed a simple fractionation method and filter-aided
sample preparation (FASP) to characterize the cytosolic and membrane
fractions of white perch ovary tissues by semiquantitative tandem
mass spectrometry using label-free quantitation based on normalized
spectral counts. FASP depletes both low-molecular-weight and high-molecular-weight
substances that could interfere with protein digestion and subsequent
peptide separation and detection. Membrane proteins are notoriously
difficult to characterize due to their amphipathic nature and association
with lipids. The simple fractionation we employed effectively revealed
an abundance of proteins from mitochondria and other membrane-bounded
organelles. We further demonstrate that support vector machines (SVMs)
offer categorical classification of proteomics data superior to that
of parametric statistical methods such as analysis of variance (ANOVA).
Specifically, SVMs were able to perfectly (100% correct) classify
samples as either membrane or cytosolic fraction during cross-validation
based on the expression of 242 proteins with the highest ANOVA <i>p</i>-values (i.e., those that were not significant for enrichment
in either fraction). The white perch ovary cytosolic and membrane
proteomes and transcriptome presented in this study can support future
investigations into oogenesis and early embryogenesis of white perch
and other members of the genus <i>Morone</i>