Genome scale mapping of brain gene expression

Quantifying mRNA levels across tissue sections with 2D-RT-qPCR

Measurement of mRNA levels across tissue samples facilitates an understanding of how genes function and what their roles are in disease. Quantifying low-abundance mRNA requires a workflow that preserves spatial information, isolates RNA, and performs reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR). This is complex because these steps are typically performed in three separate platforms. In the present study, we describe two-dimensional RT-qPCR (2D-RT-qPCR), a method that quantifies RNA across tissues sections in a single integrated platform. The method uses the grid format of a multi-well plate to macrodissect tissue sections and preserve the spatial location of the RNA; this also eliminates the need for physical homogenization of the tissue. A new lysis and nucleic acid purification protocol is performed in the same multi-well plate, followed by RT-qPCR. The feasibility 2D-RT-qPCR was demonstrated on a variety of tissue types. Potential applications of the technology as a high-throughput tissue analysis platform are discussed.

Mapping protein abundance patterns in the brain using voxelation combined with liquid chromatography and mass spectrometry

Voxelation creates expression atlases by high-throughput analysis of spatially registered cubes or voxels harvested from the brain. The modality independence of voxelation allows a variety of bioanalytical techniques to be used to map abundance. Protein expression patterns in the brain can be obtained using liquid chromatography (LC) combined with mass spectrometry (MS). Here we describe the methodology of voxelation as it pertains particularly to LC-MS proteomic analysis: sample preparation, instrumental set up and analysis, peptide identification and protein relative abundance quantitation. We also briefly describe some of the advantages, limitations and insights into the brain that can be obtained using combined proteomic and transcriptomic maps.

Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography-mass spectrometry

Temporally and spatially resolved mapping of protein abundance patterns within the mammalian brain is of significant interest for understanding brain function and molecular etiologies of neurodegenerative diseases; however, such imaging efforts have been greatly challenged by complexity of the proteome, throughput and sensitivity of applied analytical methodologies, and accurate quantitation of protein abundances across the brain. Here, we describe a methodology for comprehensive spatial proteome mapping that addresses these challenges by employing voxelation integrated with automated microscale sample processing, high-throughput liquid chromatography (LC) system coupled with high-resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrometer, and a "universal" stable isotope labeled reference sample approach for robust quantitation. We applied this methodology as a proof-of-concept trial for the analysis of protein distribution within a single coronal slice of a C57BL/6J mouse brain. For relative quantitation of the protein abundances across the slice, an 18O-isotopically labeled reference sample, derived from a whole control coronal slice from another mouse, was spiked into each voxel sample, and stable isotopic intensity ratios were used to obtain measures of relative protein abundances. In total, we generated maps of protein abundance patterns for 1028 proteins. The significant agreement of the protein distributions with previously reported data supports the validity of this methodology, which opens new opportunities for studying the spatial brain proteome and its dynamics during the course of disease progression and other important biological and associated health aspects in a discovery-driven fashion.

Microarrays and the microscope: balancing throughput with resolution

The cellular complexity of the brain is a major issue in the planning, execution and interpretation of microarray studies. Recent technical advances allow for high-throughput study of specific cell populations and circuits. Here we review representative examples of currently available methods that allow high resolution and specificity in brain microarray studies, while maintaining the goal of comprehensive, high-throughput analysis.

Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide enrichment

We report a global proteomic approach for analyzing brain tissue and for the first time a comprehensive characterization of the whole mouse brain proteome. Preparation of the whole brain sample incorporated a highly efficient cysteinyl-peptide enrichment (CPE) technique to complement a global enzymatic digestion method. Both the global and the cysteinyl-enriched peptide samples were analyzed by SCX fractionation coupled with reversed phase LC-MS/MS analysis. A total of 48,328 different peptides were confidently identified (>98% confidence level), covering 7792 nonredundant proteins ( approximately 34% of the predicted mouse proteome). A total of 1564 and 1859 proteins were identified exclusively from the cysteinyl-peptide and the global peptide samples, respectively, corresponding to 25% and 31% improvements in proteome coverage compared to analysis of only the global peptide or cysteinyl-peptide samples. The identified proteins provide a broad representation of the mouse proteome with little bias evident due to protein pI, molecular weight, and/or cellular localization. Approximately 26% of the identified proteins with gene ontology (GO) annotations were membrane proteins, with 1447 proteins predicted to have transmembrane domains, and many of the membrane proteins were found to be involved in transport and cell signaling. The MS/MS spectrum count information for the identified proteins was used to provide a measure of relative protein abundances. The mouse brain peptide/protein database generated from this study represents the most comprehensive proteome coverage for the mammalian brain to date, and the basis for future quantitative brain proteomic studies using mouse models. The proteomic approach presented here may have broad applications for rapid proteomic analyses of various mouse models of human brain diseases.

Investigation of different transcript quantitation tools for high-throughput mapping of brain gene expression using voxelation

Voxelation is a new approach for genome scale acquisition of brain gene expression patterns. The method employs high-throughput analysis of spatially registered voxels (cubes) to create multiple volumetric images of brain gene expression, similar to those obtained from biomedical imaging systems. The spatial resolution of voxelation depends on voxel size, with smaller voxels giving higher resolution. An important question is the applicability of different transcript profiling tools for the various levels of resolution that can be employed. Here, we describe the use of three methods to analyze voxel transcript abundance: real-time PCR, microarray analysis and linear amplification coupled with microarrays. We show statistically significant concordance between real-time PCR and microarray analysis for the myelin basic protein gene in human brain specimens at differing levels of spatial resolution. In addition, we also demonstrate the feasibility of using linear amplification coupled with microarray analysis to create voxelation maps from the mouse brain at high resolution, 1 microl. These data indicate the suitability of a number of transcript profiling tools for various levels of spatial resolution in voxelation.

Anatomical methods for voxelation of the mammalian brain

Voxelation allows high-throughput acquisition of three-dimensional gene expression patterns in the brain through analysis of spatially registered voxels (cubes). The method results in multiple volumetric maps of gene expression analogous to the images reconstructed in biomedical imaging techniques. An important issue for voxelation is the development of approaches to anchor correctly harvested voxels to the underlying anatomy. Here, we describe experiments to identify fixation and cryopreservation protocols for improved registration of harvested voxels with neuroanatomical structures. Paraformaldehyde fixation greatly reduced RNA recovery as judged by ribosomal RNA abundance. However, gene expression signals from paraformaldehyde-fixed samples were not appreciably diminished as judged by average signal-noise ratios from microarrays, highlighting the difficulties of accurate quantitation of cross-linked RNA. Additional use of cryoprotection helped to improve further RNA recovery and signal from fixed tissue. It appears that the best protocol to provide the necessary resolution of neuroanatomical information in voxelation entails a controlled dose of fixation and thorough cryoprotection, complemented by histological staining.