Transcriptomics Meets Proteomics
“It is exciting to perform RNA-seq analysis on the same sample on which proteomics was done,” says Lloyd M. Smith, Ph.D., professor of chemistry at the University of Wisconsin-Madison.
One of the challenges accompanying mass spectrometry-based analyses is that human proteomic databases, despite being frequently updated, do not reflect cell-to-cell variation in the multiple protein forms that are found in various cell and tissue types.
Two major approaches have been implemented and are broadly used in proteomics. Bottom-up proteomics, which involves the enzymatic digestion of proteins into fragments that are subsequently identified by mass spectrometry, is technically more amenable, and the data are easier to interpret than in top-down proteomics, which involves the ionization and mass spectrometry analysis of intact proteins.
While bottom-up proteomics offers higher sensitivity, it is not informative about the context where the peptides originated from, such as alternatively spliced or post-translationally modified protein products.“There are a lot of things that get lost during bottom-up proteomics,” Dr. Smith says.
A new concept that Dr. Smith and colleagues introduced, that of proteoforms, is used to refer to all the molecular forms that the protein product of a single gene can be found in.
This term, capturing a new layer of complexity thus far mostly overlooked, would ensure that protein changes resulting from coding single nucleotide polymorphisms and mutations, post-translational modifications, and RNA splicing are represented when referring to cellular proteins. “It is important to describe all the different forms of a protein that may exist in cells,” he explains.
Recently, Dr. Smith and his colleagues collected proteomics and RNA-seq data from a homogeneous cell population, and developed a bioinformatics pipeline in which novel splice junction sequences were translated into the respective polypeptides, to establish a database that can be used to characterize splice junctions during mass spectrometry.
“Using RNA-seq in conjunction with proteomics is more powerful than performing proteomics alone,” he says. While the strength of this analysis was illustrated in one cell type, efforts in Dr. Smith’s lab are currently directed toward characterizing splice junction peptides and splice site variation in additional cell types. “This is similar to giving glasses to proteomics, and its main advantage is the possibility to unveil splice variants that otherwise one could not see,” Dr. Smith adds.
RNA-seq helped open new research avenues, forge inter- and cross-disciplinary connections, and define new concepts. Areas that historically received relatively little attention, such as RNA methylation, are now expanding into vibrant fields, while more recent disciplines, such as proteomics, are acquiring additional levels of inquiry.
Knowing the extent to which learning about the genome reshaped our perspectives about biology, and considering the even more accentuated complexity of the transcriptome, one can only imagine the wealth and intricacy of the regulatory networks that are waiting to be elucidated.