Microproteomics: Quantitative proteomic profiling of small numbers of laser-captured cells

INTRODUCTIONDuring the last decade, significant progress in the analysis of whole genomes and transcriptomes has triggered efforts to analyze the proteome. Advancements in protein extraction, purification, and identification have been driven by the development of mass spectrometers with greater sensitivity and resolution. Nevertheless, comparative and quantitative proteomic technologies have not progressed to the extent of genomic and transcriptomic technologies for accessing gene expression differences. Unlike the genome, which is similar throughout all cells in a given organism, the proteome varies in different cells. Also, there is no self-replicating amplification mechanism for proteins such as the polymerase chain reaction (PCR) for DNA. Therefore, developing methods that extract, separate, detect, and identify proteins from extremely small samples are needed. The advent of laser capture microdissection (LCM) has expanded the analytical capabilities of proteomics. LCM has proven an effective technique to harvest pure cell populations from tissue sections. This protocol describes a microproteomic platform that uses nanoscale liquid chromatography/tandem mass spectrometry (nano-LC-MS/MS) to simultaneously identify and quantify hundreds of proteins from LCMs of tissue sections from small tissue samples containing as few as 1000 cells. The LCM-dissected tissues are subjected to protein extraction, reduction, alkylation, and digestion, followed by injection into a nano-LC-MS/MS system for chromatographic separation and protein identification. The approach can be validated by secondary screening using immunological techniques such as immunohistochemistry or immunoblots.</jats:p

Convergent differential regulation of SLIT-ROBO axon guidance genes in the brains of vocal learners.

Only a few distantly related mammals and birds have the trait of complex vocal learning, which is the ability to imitate novel sounds. This ability is critical for speech acquisition and production in humans, and is attributed to specialized forebrain vocal control circuits that have several unique connections relative to adjacent brain circuits. As a result, it has been hypothesized that there could exist convergent changes in genes involved in neural connectivity of vocal learning circuits. In support of this hypothesis, expanding on our related study (Pfenning et al. [2014] Science 346: 1256846), here we show that the forebrain part of this circuit that makes a relatively rare direct connection to brainstem vocal motor neurons in independent lineages of vocal learning birds (songbird, parrot, and hummingbird) has specialized regulation of axon guidance genes from the SLIT-ROBO molecular pathway. The SLIT1 ligand was differentially downregulated in the motor song output nucleus that makes the direct projection, whereas its receptor ROBO1 was developmentally upregulated during critical periods for vocal learning. Vocal nonlearning bird species and male mice, which have much more limited vocal plasticity and associated circuits, did not show comparable specialized regulation of SLIT-ROBO genes in their nonvocal motor cortical regions. These findings are consistent with SLIT and ROBO gene dysfunctions associated with autism, dyslexia, and speech sound language disorders and suggest that convergent evolution of vocal learning was associated with convergent changes in the SLIT-ROBO axon guidance pathway