Compartment Proteomics Analysis of White Perch (Morone americana) Ovary Using Support Vector Machines

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 p-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 Morone.