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Cui X, Dong X, Hu M, Zhou W, Shi W. Large field of view and spatial region of interest transcriptomics in fixed tissue. Commun Biol 2024; 7:1020. [PMID: 39164496 PMCID: PMC11335973 DOI: 10.1038/s42003-024-06694-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 08/07/2024] [Indexed: 08/22/2024] Open
Abstract
Expression profiling in spatially defined regions is crucial for systematically understanding tissue complexity. Here, we report a method of photo-irradiation for in-situ barcoding hybridization and ligation sequencing, named PBHL-seq, which allows targeted expression profiling from the photo-irradiated region of interest in intact fresh frozen and formalin fixation and paraffin embedding (FFPE) tissue samples. PBHL-seq uses photo-caged oligodeoxynucleotides for in situ reverse transcription followed by spatially targeted barcoding of cDNAs to create spatially indexed transcriptomes of photo-illuminated regions. We recover thousands of differentially enriched transcripts from different regions by applying PBHL-seq to OCT-embedded tissue (E14.5 mouse embryo and mouse brain) and FFPE mouse embryo (E15.5). We also apply PBHL-seq to the subcellular microstructures (cytoplasm and nucleus, respectively) and detect thousands of differential expression genes. Thus, PBHL-seq provides an accessible workflow for expression profiles from the region of interest in frozen and FFPE tissue at subcellular resolution with areas expandable to centimeter scale, while preserving the sample intact for downstream analysis to promote the development of transcriptomics.
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Affiliation(s)
- Xiaonan Cui
- Single Cell Systems Biology Laboratory, College of Marine Life Sciences, Ocean University of China, Qingdao, Shandong, 266100, China
| | - Xue Dong
- Single Cell Systems Biology Laboratory, College of Marine Life Sciences, Ocean University of China, Qingdao, Shandong, 266100, China
| | - Mengzhu Hu
- Single Cell Systems Biology Laboratory, College of Marine Life Sciences, Ocean University of China, Qingdao, Shandong, 266100, China
| | - Wenjian Zhou
- Single Cell Systems Biology Laboratory, College of Marine Life Sciences, Ocean University of China, Qingdao, Shandong, 266100, China
| | - Weiyang Shi
- Department of Orthopedics, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
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Yue L, Liu F, Hu J, Yang P, Wang Y, Dong J, Shu W, Huang X, Wang S. A guidebook of spatial transcriptomic technologies, data resources and analysis approaches. Comput Struct Biotechnol J 2023; 21:940-955. [PMID: 38213887 PMCID: PMC10781722 DOI: 10.1016/j.csbj.2023.01.016] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 01/13/2023] [Accepted: 01/14/2023] [Indexed: 01/18/2023] Open
Abstract
Advances in transcriptomic technologies have deepened our understanding of the cellular gene expression programs of multicellular organisms and provided a theoretical basis for disease diagnosis and therapy. However, both bulk and single-cell RNA sequencing approaches lose the spatial context of cells within the tissue microenvironment, and the development of spatial transcriptomics has made overall bias-free access to both transcriptional information and spatial information possible. Here, we elaborate development of spatial transcriptomic technologies to help researchers select the best-suited technology for their goals and integrate the vast amounts of data to facilitate data accessibility and availability. Then, we marshal various computational approaches to analyze spatial transcriptomic data for various purposes and describe the spatial multimodal omics and its potential for application in tumor tissue. Finally, we provide a detailed discussion and outlook of the spatial transcriptomic technologies, data resources and analysis approaches to guide current and future research on spatial transcriptomics.
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Affiliation(s)
- Liangchen Yue
- Beijing Institute of Microbiology and Epidemiology, Beijing 100850, China
| | - Feng Liu
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China
| | - Jiongsong Hu
- University of South China, Hengyang, Hunan 421001, China
| | - Pin Yang
- Anhui Medical University, Hefei 230022, Anhui, China
| | - Yuxiang Wang
- Beijing Institute of Microbiology and Epidemiology, Beijing 100850, China
| | - Junguo Dong
- Beijing Institute of Microbiology and Epidemiology, Beijing 100850, China
| | - Wenjie Shu
- Beijing Institute of Microbiology and Epidemiology, Beijing 100850, China
| | - Xingxu Huang
- Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, and Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310029, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Shengqi Wang
- Beijing Institute of Microbiology and Epidemiology, Beijing 100850, China
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3
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Abstract
The function of many biological systems, such as embryos, liver lobules, intestinal villi, and tumors, depends on the spatial organization of their cells. In the past decade, high-throughput technologies have been developed to quantify gene expression in space, and computational methods have been developed that leverage spatial gene expression data to identify genes with spatial patterns and to delineate neighborhoods within tissues. To comprehensively document spatial gene expression technologies and data-analysis methods, we present a curated review of literature on spatial transcriptomics dating back to 1987, along with a thorough analysis of trends in the field, such as usage of experimental techniques, species, tissues studied, and computational approaches used. Our Review places current methods in a historical context, and we derive insights about the field that can guide current research strategies. A companion supplement offers a more detailed look at the technologies and methods analyzed: https://pachterlab.github.io/LP_2021/ .
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4
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Khan AH, Lee LK, Smith DJ. Single-cell analysis of gene expression in the substantia nigra pars compacta of a pesticide-induced mouse model of Parkinson's disease. Transl Neurosci 2022; 13:255-269. [PMID: 36117858 PMCID: PMC9438968 DOI: 10.1515/tnsci-2022-0237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 07/18/2022] [Accepted: 07/25/2022] [Indexed: 12/02/2022] Open
Abstract
Exposure to pesticides in humans increases the risk of Parkinson’s disease (PD), but the mechanisms remain poorly understood. To elucidate these pathways, we dosed C57BL/6J mice with a combination of the pesticides maneb and paraquat. Behavioral analysis revealed motor deficits consistent with PD. Single-cell RNA sequencing of substantia nigra pars compacta revealed both cell-type-specific genes and genes expressed differentially between pesticide and control, including Fam241b, Emx2os, Bivm, Gm1439, Prdm15, and Rai2. Neurons had the largest number of significant differentially expressed genes, but comparable numbers were found in astrocytes and less so in oligodendrocytes. In addition, network analysis revealed enrichment in functions related to the extracellular matrix. These findings emphasize the importance of support cells in pesticide-induced PD and refocus our attention away from neurons as the sole agent of this disorder.
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Affiliation(s)
- Arshad H. Khan
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, UCLA, Box 951735, 23-151 A CHS, Los Angeles, CA 90095-1735, United States of America
| | - Lydia K. Lee
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, UCLA, Los Angeles, CA 90095-6928, United States of America
| | - Desmond J. Smith
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, UCLA, Box 951735, 23-151 A CHS, Los Angeles, CA 90095-1735, United States of America
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5
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Hermosilla VE, Hepp MI, Escobar D, Farkas C, Riffo EN, Castro AF, Pincheira R. Developmental SALL2 transcription factor: a new player in cancer. Carcinogenesis 2017; 38:680-690. [DOI: 10.1093/carcin/bgx036] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2016] [Accepted: 04/11/2017] [Indexed: 11/12/2022] Open
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6
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Valor LM, Barco A. Hippocampal gene profiling: toward a systems biology of the hippocampus. Hippocampus 2010; 22:929-41. [PMID: 21080408 DOI: 10.1002/hipo.20888] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/24/2010] [Indexed: 01/17/2023]
Abstract
Transcriptomics and proteomics approaches give a unique perspective for understanding brain and hippocampal functions but also pose unique challenges because of the singular complexity of the nervous system. The proliferation of genome-wide expression studies during the last decade has provided important insight into the molecular underpinnings of brain anatomy, neural plasticity, and neurological diseases. Microarray technology has dominated transcriptomics research, but this situation is rapidly changing with the recent technological advances in high-throughput sequencing. The full potential of transcriptomics in the neurosciences will be achieved as a result of its integration with other "-omics" disciplines as well as the development of novel analytical bioinformatics and systems biology tools for meta-analysis. Here, we review some of the most relevant advances in the gene profiling of the hippocampus, its relationship with proteomics approaches, and the promising perspectives for the future.
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Affiliation(s)
- Luis M Valor
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas, Campus de Sant Joan, Apt. 18, Sant Joan d'Alacant, 03550, Alicante, Spain
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7
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Tabakoff B, Saba L, Printz M, Flodman P, Hodgkinson C, Goldman D, Koob G, Richardson HN, Kechris K, Bell RL, Hübner N, Heinig M, Pravenec M, Mangion J, Legault L, Dongier M, Conigrave KM, Whitfield JB, Saunders J, Grant B, Hoffman PL. Genetical genomic determinants of alcohol consumption in rats and humans. BMC Biol 2009; 7:70. [PMID: 19874574 PMCID: PMC2777866 DOI: 10.1186/1741-7007-7-70] [Citation(s) in RCA: 127] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2009] [Accepted: 10/27/2009] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND We have used a genetical genomic approach, in conjunction with phenotypic analysis of alcohol consumption, to identify candidate genes that predispose to varying levels of alcohol intake by HXB/BXH recombinant inbred rat strains. In addition, in two populations of humans, we assessed genetic polymorphisms associated with alcohol consumption using a custom genotyping array for 1,350 single nucleotide polymorphisms (SNPs). Our goal was to ascertain whether our approach, which relies on statistical and informatics techniques, and non-human animal models of alcohol drinking behavior, could inform interpretation of genetic association studies with human populations. RESULTS In the HXB/BXH recombinant inbred (RI) rats, correlation analysis of brain gene expression levels with alcohol consumption in a two-bottle choice paradigm, and filtering based on behavioral and gene expression quantitative trait locus (QTL) analyses, generated a list of candidate genes. A literature-based, functional analysis of the interactions of the products of these candidate genes defined pathways linked to presynaptic GABA release, activation of dopamine neurons, and postsynaptic GABA receptor trafficking, in brain regions including the hypothalamus, ventral tegmentum and amygdala. The analysis also implicated energy metabolism and caloric intake control as potential influences on alcohol consumption by the recombinant inbred rats. In the human populations, polymorphisms in genes associated with GABA synthesis and GABA receptors, as well as genes related to dopaminergic transmission, were associated with alcohol consumption. CONCLUSION Our results emphasize the importance of the signaling pathways identified using the non-human animal models, rather than single gene products, in identifying factors responsible for complex traits such as alcohol consumption. The results suggest cross-species similarities in pathways that influence predisposition to consume alcohol by rats and humans. The importance of a well-defined phenotype is also illustrated. Our results also suggest that different genetic factors predispose alcohol dependence versus the phenotype of alcohol consumption.
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Affiliation(s)
- Boris Tabakoff
- Department of Pharmacology, University of Colorado, Denver, Aurora, CO, USA
| | - Laura Saba
- Department of Pharmacology, University of Colorado, Denver, Aurora, CO, USA
| | - Morton Printz
- Department of Pharmacology, University of California San Diego, La Jolla, CA, USA
| | - Pam Flodman
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
| | - Colin Hodgkinson
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - David Goldman
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - George Koob
- Committee on the Neurobiology of Addictive Disorders, The Scripps Research Institute, La Jolla, CA, USA
| | - Heather N Richardson
- Committee on the Neurobiology of Addictive Disorders, The Scripps Research Institute, La Jolla, CA, USA
- Department Psychology-Neuroscience, University of Massachusetts Amherst, Amherst, MA, USA
| | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA
| | - Richard L Bell
- Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Norbert Hübner
- Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | | | - Michal Pravenec
- Institute of Physiology, Czech Academy of Sciences, Prague, Czech Republic
| | - Jonathan Mangion
- MRC Clinical Sciences Centre, London, UK
- Applied Biosystems, Lingley House, 120 Birchwood Blvd., Warrington, Cheshire, WA3 7QH, UK
| | - Lucie Legault
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Maurice Dongier
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Katherine M Conigrave
- Drug Health Services, Royal Prince Alfred Hospital, Sydney Medical School, University of Sydney, New South Wales, Australia
| | | | - John Saunders
- School of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Bridget Grant
- Division of Epidemiology, National Institute on Alcohol Abuse and Alcoholism, Rockville, MD, USA
| | - Paula L Hoffman
- Department of Pharmacology, University of Colorado, Denver, Aurora, CO, USA
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Hourani M, Berretta R, Mendes A, Moscato P. Genetic signatures for a rodent model of Parkinson's disease using combinatorial optimization methods. Methods Mol Biol 2008; 453:379-392. [PMID: 18712315 DOI: 10.1007/978-1-60327-429-6_20] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
This chapter illustrates the use of the combinatorial optimization models presented in Chapter 19 for the Feature Set selection and Gene Ordering problems to find genetic signatures for diseases using micro-array data. We demonstrate the quality of this approach by using a microarray dataset from a mouse model of Parkinson's disease. The results are accompanied by a description of the currently known molecular functions and biological processes of the genes in the signatures.
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Affiliation(s)
- Mou'ath Hourani
- Newcastle Bioinformatics Initiative, School of Electrical Engineering and Computer Science, The University of Newcastle, Callaghan, New South Wales, Australia
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9
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Zhao X, Li Q, Zhao L, Pu X. Proteome analysis of substantia nigra and striatal tissue in the mouse MPTP model of Parkinson's disease. Proteomics Clin Appl 2007; 1:1559-69. [PMID: 21136655 DOI: 10.1002/prca.200700077] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2007] [Indexed: 12/21/2022]
Abstract
The dopaminergic neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) replicates many of the pathological hallmarks of Parkinson's disease (PD) in mice via selective destruction of dopamine neurons of the substantia nigra and striatum. Although MPTP has been widely used to study downstream effects following the degeneration of dopaminergic neurons, the underlying mechanisms of MPTP action remain poorly understood. To determine the underlying mechanisms of MPTP action at the protein level, a 2-DE-based proteomics approach was used to evaluate the changes in protein expression in substantia nigra and striatal tissue in C57BL/6 mice after MPTP administration. We identified nine proteins that were markedly altered and are likely to be involved in mitochondrial function, heat shock protein activity, and which contribute enzyme activities for energy metabolism and protein degradation.
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Affiliation(s)
- Xin Zhao
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University, Beijing, P. R. China
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10
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Chin MH, Geng AB, Khan AH, Qian WJ, Petyuk VA, Boline J, Levy S, Toga AW, Smith RD, Leahy RM, Smith DJ. A genome-scale map of expression for a mouse brain section obtained using voxelation. Physiol Genomics 2007; 30:313-21. [PMID: 17504947 PMCID: PMC3299369 DOI: 10.1152/physiolgenomics.00287.2006] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological diseases. We have reconstructed two-dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 mm3. Good reliability of the microarray results were confirmed using multiple replicates, subsequent quantitative RT-PCR voxelation, mass spectrometry voxelation, and publicly available in situ hybridization data. Known and novel genes were identified with expression patterns localized to defined substructures within the brain. In addition, genes with unexpected patterns were identified, and cluster analysis identified a set of genes with a gradient of dorsal/ventral expression not restricted to known anatomical boundaries. The genome-scale maps of gene expression obtained using voxelation will be a valuable tool for the neuroscience community.
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Affiliation(s)
- Mark H Chin
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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11
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Petyuk VA, Qian WJ, Chin MH, Wang H, Livesay EA, Monroe ME, Adkins JN, Jaitly N, Anderson DJ, Camp DG, Smith DJ, Smith RD. Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography-mass spectrometry. Genome Res 2007; 17:328-36. [PMID: 17255552 PMCID: PMC1800924 DOI: 10.1101/gr.5799207] [Citation(s) in RCA: 56] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
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.
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Affiliation(s)
- Vladislav A. Petyuk
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Wei-Jun Qian
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Mark H. Chin
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
| | - Haixing Wang
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Eric A. Livesay
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Matthew E. Monroe
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Joshua N. Adkins
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Navdeep Jaitly
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - David J. Anderson
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - David G. Camp
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Desmond J. Smith
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
| | - Richard D. Smith
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
- Corresponding author.E-mail ; fax (509) 376-7722
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12
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Petritis K, Kangas LJ, Yan B, Monroe ME, Strittmatter EF, Qian WJ, Adkins JN, Moore RJ, Xu Y, Lipton MS, Camp DG, Smith RD. Improved peptide elution time prediction for reversed-phase liquid chromatography-MS by incorporating peptide sequence information. Anal Chem 2006; 78:5026-39. [PMID: 16841926 PMCID: PMC1924966 DOI: 10.1021/ac060143p] [Citation(s) in RCA: 152] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We describe an improved artificial neural network (ANN)-based method for predicting peptide retention times in reversed-phase liquid chromatography. In addition to the peptide amino acid composition, this study investigated several other peptide descriptors to improve the predictive capability, such as peptide length, sequence, hydrophobicity and hydrophobic moment, and nearest-neighbor amino acid, as well as peptide predicted structural configurations (i.e., helix, sheet, coil). An ANN architecture that consisted of 1052 input nodes, 24 hidden nodes, and 1 output node was used to fully consider the amino acid residue sequence in each peptide. The network was trained using approximately 345,000 nonredundant peptides identified from a total of 12,059 LC-MS/MS analyses of more than 20 different organisms, and the predictive capability of the model was tested using 1303 confidently identified peptides that were not included in the training set. The model demonstrated an average elution time precision of approximately 1.5% and was able to distinguish among isomeric peptides based upon the inclusion of peptide sequence information. The prediction power represents a significant improvement over our earlier report (Petritis, K.; Kangas, L. J.; Ferguson, P. L.; Anderson, G. A.; Pasa-Tolic, L.; Lipton, M. S.; Auberry, K. J.; Strittmatter, E. F.; Shen, Y.; Zhao, R.; Smith, R. D. Anal. Chem. 2003, 75, 1039-1048) and other previously reported models.
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Affiliation(s)
- Konstantinos Petritis
- Biological Sciences Division, Environmental and Molecular Sciences Laboratory, P. O. Box 999, Richland, Washington 99352, USA
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Abstract
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.
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Affiliation(s)
- Giovanni Coppola
- Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA 90095, USA
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14
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Wang H, Qian WJ, Mottaz HM, Clauss TRW, Anderson DJ, Moore RJ, Camp DG, Khan AH, Sforza DM, Pallavicini M, Smith DJ, Smith RD. Development and evaluation of a micro- and nanoscale proteomic sample preparation method. J Proteome Res 2005; 4:2397-403. [PMID: 16335993 PMCID: PMC1781925 DOI: 10.1021/pr050160f] [Citation(s) in RCA: 137] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Challenges associated with the efficient and effective preparation of micro- and nanoscale (micro- and nanogram) clinical specimens for proteomic applications include the unmitigated sample losses that occur during the processing steps. Herein, we describe a simple "single-tube" preparation protocol appropriate for small proteomic samples using the organic cosolvent, trifluoroethanol (TFE) that circumvents the loss of sample by facilitating both protein extraction and protein denaturation without requiring a separate cleanup step. The performance of the TFE-based method was initially evaluated by comparisons to traditional detergent-based methods on relatively large scale sample processing using human breast cancer cells and mouse brain tissue. The results demonstrated that the TFE-based protocol provided comparable results to the traditional detergent-based protocols for larger, conventionally sized proteomic samples (>100 microg protein content), based on both sample recovery and numbers of peptide/protein identifications. The effectiveness of this protocol for micro- and nanoscale sample processing was then evaluated for the extraction of proteins/peptides and shown effective for small mouse brain tissue samples (approximately 30 microg total protein content) and also for samples of approximately 5000 MCF-7 human breast cancer cells (approximately 500 ng total protein content), where the detergent-based methods were ineffective due to losses during cleanup and transfer steps.
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Affiliation(s)
- Haixing Wang
- Biological Sciences Division, Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
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15
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Zapala MA, Hovatta I, Ellison JA, Wodicka L, Del Rio JA, Tennant R, Tynan W, Broide RS, Helton R, Stoveken BS, Winrow C, Lockhart DJ, Reilly JF, Young WG, Bloom FE, Lockhart DJ, Barlow C. Adult mouse brain gene expression patterns bear an embryologic imprint. Proc Natl Acad Sci U S A 2005; 102:10357-62. [PMID: 16002470 PMCID: PMC1173363 DOI: 10.1073/pnas.0503357102] [Citation(s) in RCA: 147] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The current model to explain the organization of the mammalian nervous system is based on studies of anatomy, embryology, and evolution. To further investigate the molecular organization of the adult mammalian brain, we have built a gene expression-based brain map. We measured gene expression patterns for 24 neural tissues covering the mouse central nervous system and found, surprisingly, that the adult brain bears a transcriptional "imprint" consistent with both embryological origins and classic evolutionary relationships. Embryonic cellular position along the anterior-posterior axis of the neural tube was shown to be closely associated with, and possibly a determinant of, the gene expression patterns in adult structures. We also observed a significant number of embryonic patterning and homeobox genes with region-specific expression in the adult nervous system. The relationships between global expression patterns for different anatomical regions and the nature of the observed region-specific genes suggest that the adult brain retains a degree of overall gene expression established during embryogenesis that is important for regional specificity and the functional relationships between regions in the adult. The complete collection of extensively annotated gene expression data along with data mining and visualization tools have been made available on a publicly accessible web site (www.barlow-lockhart-brainmapnimhgrant.org).
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Affiliation(s)
- Matthew A Zapala
- Laboratory of Genetics, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA 92037, USA
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16
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Stichel CC, Schoenebeck B, Foguet M, Siebertz B, Bader V, Zhu XR, Lübbert H. sgk1, a member of an RNA cluster associated with cell death in a model of Parkinson's disease. Eur J Neurosci 2005; 21:301-16. [PMID: 15673431 DOI: 10.1111/j.1460-9568.2005.03859.x] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
In an effort to gain deeper insight into the molecular processes underlying neurodegeneration in Parkinson's disease, we performed gene expression profiling at several early time points after MPTP-injection into old (1-year) mice. We used a PCR-based gene expression profiling method, digital expression pattern display (DEPD), a method of very high sensitivity and reproducibility, which displays almost all transcripts of a tissue. To identify cell death-associated genes, we defined clusters of differentially expressed transcripts with expression behaviour that correlated with the temporal profile of cell death progression and characterized one of these cell death clusters further. We selected one of the strongest regulated genes, the serum and glucocorticoid-regulated kinase 1 (sgk1), and validated its differential expression by Northern blot analysis, semiquantitative PCR and in situ hybridization. Up-regulation of sgk1 (i) coincides with the onset of dopaminergic cell death in both the 8-week acute and 1-year subacute MPTP models, (ii) spans the entire brain, (iii) is attenuated by the l-deprenyl-mediated inhibition of the MPTP conversion to its active metabolite MPP+ and (iv) is not induced by dehydration. This study demonstrated that the combination of the DEPD technology, clustering analysis and a detailed histopathology is a useful tool for elucidating molecular pathways in neurodegenerative diseases.
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17
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Azuaje F, Wang H, Chesneau A. Non-linear mapping for exploratory data analysis in functional genomics. BMC Bioinformatics 2005; 6:13. [PMID: 15661072 PMCID: PMC548129 DOI: 10.1186/1471-2105-6-13] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2004] [Accepted: 01/20/2005] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory, visualisation-driven approaches. Such approaches should satisfy the following factors: Support for intuitive cluster visualisation, user-friendly and robust application, computational efficiency and generation of biologically meaningful outcomes. This research assesses a relaxation method for non-linear mapping that addresses these concerns. Its applications to gene expression and protein-protein interaction data analyses are investigated. RESULTS Publicly available expression data originating from leukaemia, round blue-cell tumours and Parkinson disease studies were analysed. The method distinguished relevant clusters and critical analysis areas. The system does not require assumptions about the inherent class structure of the data, its mapping process is controlled by only one parameter and the resulting transformations offer intuitive, meaningful visual displays. Comparisons with traditional mapping models are presented. As a way of promoting potential, alternative applications of the methodology presented, an example of exploratory data analysis of interactome networks is illustrated. Data from the C. elegans interactome were analysed. Results suggest that this method might represent an effective solution for detecting key network hubs and for clustering biologically meaningful groups of proteins. CONCLUSION A relaxation method for non-linear mapping provided the basis for visualisation-driven analyses using different types of data. This study indicates that such a system may represent a user-friendly and robust approach to exploratory data analysis. It may allow users to gain better insights into the underlying data structure, detect potential outliers and assess assumptions about the cluster composition of the data.
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Affiliation(s)
- Francisco Azuaje
- School of Computing and Mathematics, University of Ulster, BT37 0QB, UK
| | - Haiying Wang
- School of Computing and Mathematics, University of Ulster, BT37 0QB, UK
| | - Alban Chesneau
- Molecular Genetics Institute, CNRS UMR5535, 1919, route de Mende, 34293 Montpellier, France
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18
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Singh RP, Liu D, Chaudhari A, Cherry SR, Leahy RM, Smith DJ. Investigation of different transcript quantitation tools for high-throughput mapping of brain gene expression using voxelation. J Mol Histol 2004; 35:397-402. [PMID: 15503813 DOI: 10.1023/b:hijo.0000039878.01844.c6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
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.
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Affiliation(s)
- Ram P Singh
- Department of Molecular and Medical Pharmacology, UCLA School of Medicine, Los Angeles, CA 90095, USA
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19
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Sforza DM, Annese J, Liu D, Levy S, Toga AW, Smith DJ. Anatomical methods for voxelation of the mammalian brain. Neurochem Res 2004; 29:1299-306. [PMID: 15176486 DOI: 10.1023/b:nere.0000023616.67996.00] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
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.
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Affiliation(s)
- Daniel M Sforza
- Department of Molecular and Medical Pharmacology, School of Medicine, University of California, Los Angeles, California 90095-1735, USA
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20
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Smith RD, Shen Y, Tang K. Ultrasensitive and quantitative analyses from combined separations-mass spectrometry for the characterization of proteomes. Acc Chem Res 2004; 37:269-78. [PMID: 15096064 DOI: 10.1021/ar0301330] [Citation(s) in RCA: 110] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
This article describes developments in fundamental and applied aspects of separations, electrospray ionization phenomena, and mass spectrometric instrumentation that are interrelated and important for making more effective and quantitative measurements, particularly for proteomics applications. The basis for better quantitation and ultrahigh sensitivity is highlighted for high-resolution capillary liquid chromatography separations that provide low nanoliter per minute flow rates to an electrospray ionization interface. The increased dynamic range of measurements and low zeptomole regime detection limits obtainable open new avenues for biological research.
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Affiliation(s)
- Richard D Smith
- Pacific Northwest National Laboratory, P.O. Box 999, Richland, WA 99352, USA
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21
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Sforza DM, Smith DJ. Voxelation Methods for Genome Scale Imaging of Brain Gene Expression. Methods Enzymol 2004; 386:314-23. [PMID: 15120259 DOI: 10.1016/s0076-6879(04)86015-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Daniel M Sforza
- Department of Molecular and Medical Pharmacology, UCLA School of Medicine, Los Angeles, California 90095, USA
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22
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Liu D, Smith DJ. Voxelation and gene expression tomography for the acquisition of 3-D gene expression maps in the brain. Methods 2003; 31:317-25. [PMID: 14597316 DOI: 10.1016/s1046-2023(03)00162-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022] Open
Abstract
Voxelation and gene expression tomography or GET are novel methods for the high-throughput acquisition of gene expression patterns in the mammalian brain. Voxelation employs analysis of spatially registered voxels (cubes), while GET employs analysis of sets of parallel slices rotated about multiple independent axes of rotation. Both methods employ reconstruction of the data to result in multiple volumetric maps of gene expression analogous to those obtained from biomedical imaging techniques. Here, we describe the methodologies underlying voxelation and GET and briefly outline the insights that can be obtained from these approaches.
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Affiliation(s)
- Dahai Liu
- Department of Molecular and Medical Pharmacology, UCLA School of Medicine, University of California, 23-120 CHS, Box 951735, Los Angeles, CA 90095-1735, USA
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23
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Abstract
Two new approaches, voxelation and gene expression tomography (GET), permit multiplex acquisition of gene expression patterns in the brain. Both methods result in volumetric images of gene expression analogous to those produced in biomedical imaging systems. Voxelation employs analysis of spatially registered cubes from the brain, whereas GET entails analysis of parallel slices obtained by rotation about multiple axes. These methods have been used to investigate neurologic diseases and their models in both humans and mice. The results of these studies are discussed, as is the future of high-throughput gene expression mapping in the brain.
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Affiliation(s)
- Ram P Singh
- Department of Molecular and Medical Pharmacology, Crump Institute for Molecular Imaging, UCLA School of Medicine, Los Angeles, California 90095, USA
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24
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Singh RP, Brown VM, Chaudhari A, Khan AH, Ossadtchi A, Sforza DM, Meadors AK, Cherry SR, Leahy RM, Smith DJ. High-resolution voxelation mapping of human and rodent brain gene expression. J Neurosci Methods 2003; 125:93-101. [PMID: 12763235 DOI: 10.1016/s0165-0270(03)00045-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Voxelation allows high-throughput acquisition of multiple volumetric images of brain gene expression, similar to those obtained from biomedical imaging systems. To obtain these images, the method employs analysis of spatially registered voxels (cubes). For creation of high-resolution maps using voxelation, relatively small voxel sizes are necessary and instruments will be required for semiautomated harvesting of such voxels. Here, we describe two devices that allow spatially registered harvesting of voxels from the human and rodent brain, giving linear resolutions of 3.3 and 1 mm, respectively. Gene expression patterns obtained using these devices showed good agreement with known expression patterns. The voxelation instruments and their future iterations represent a valuable approach to the genome scale acquisition of gene expression patterns in the human and rodent brain.
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Affiliation(s)
- Ram P Singh
- Department of Molecular and Medical Pharmacology, UCLA School of Medicine, 23-120 CHS, 90095-1735, Los Angeles, CA, USA
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25
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Mandel S, Weinreb O, Youdim MBH. Using cDNA microarray to assess Parkinson's disease models and the effects of neuroprotective drugs. Trends Pharmacol Sci 2003; 24:184-91. [PMID: 12707005 DOI: 10.1016/s0165-6147(03)00067-1] [Citation(s) in RCA: 56] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The remarkable progress made by molecular biology and molecular genetics during the past decade, and the advent of the novel tools of genomics and proteomics, are expected to reveal differential expression profiles of thousands of genes and proteins involved in the degeneration of dopamine-containing cells in Parkinson's disease and allow more focused treatments according to individual genotypes. Of particular interest is the application of microarrays in drug discovery and design to identify 'fingerprints' as potential candidate targets for drug intervention. The major microarray findings relevant to Parkinson's disease and its neurotoxin-induced animal and cell models will be discussed, with particular reference to the neuroprotective therapeutic potential that could arise from the development of drugs 'a la carte'.
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Affiliation(s)
- Silvia Mandel
- Eve Topf and US National Parkinson Foundation Centers of Excellence for Neurodegenerative Diseases Research and Department of Pharmacology, Technion-Rappaport Faculty of Medicine, PO Box 9697, Haifa 31096, Israel
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26
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Leil TA, Ossadtchi A, Nichols TE, Leahy RM, Smith DJ. Genes regulated by learning in the hippocampus. J Neurosci Res 2003; 71:763-8. [PMID: 12605401 DOI: 10.1002/jnr.10541] [Citation(s) in RCA: 34] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The enduring changes in long-term memory probably depend on regulation of gene expression in the hippocampus. To seek genes regulated by learning, we used microarray technology to compare hippocampal gene expression in mice undergoing training in the Morris water maze and control mice forced to swim for the same period in the absence of a hidden platform. ANOVA was employed to prioritize genes for further study, and three genes were confirmed by real-time PCR as being regulated during learning. One of the genes was the alpha subunit of the platelet-derived growth factor receptor (Pdgfra); another showed homology to DnaJ and cAMP response element-binding protein 2 (CREB2); and a third was novel. These genes may provide useful insights into the molecular mechanisms of hippocampal learning.
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Affiliation(s)
- Tarek A Leil
- Department of Molecular and Medical Pharmacology, Crump Institute for Molecular Imaging, UCLA School of Medicine, Los Angeles, California, USA
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27
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Abstract
We describe a microarray design based on the concept of error-correcting codes from digital communication theory. Currently, microarrays are unable to efficiently deal with "drop-outs," when one or more spots on the array are corrupted. The resulting information loss may lead to decoding errors in which no quantitation of expression can be extracted for the corresponding genes. This issue is expected to become increasingly problematic as the number of spots on microarrays expands to accommodate the entire genome. The error-correcting approach employs multiplexing (encoding) of more than one gene onto each spot to efficiently provide robustness to drop-outs in the array. Decoding then allows fault-tolerant recovery of the expression information from individual genes. The error-correcting method is general and may have important implications for future array designs in research and diagnostics.
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Affiliation(s)
- Arshad H Khan
- Department of Molecular and Medical Pharmacology, Crump Institute for Biomedical Imaging, University of California at Los Angeles School of Medicine, 90095, USA
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28
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Pollock JD. Gene expression profiling: methodological challenges, results, and prospects for addiction research. Chem Phys Lipids 2002; 121:241-56. [PMID: 12505704 DOI: 10.1016/s0009-3084(02)00160-3] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
This review describes the current methods used to profile gene expression. These methods include microarrays, spotted arrays, serial analysis of gene expression (SAGE), and massive parallel signature sequencing (MPSS). Methodological and statistical problems in interpreting microarray and spotted array experiments are also discussed. Methods and formats such as minimum information about microarray experiments (MIAME) needed to share gene expression data are described. The last part of the review provides an overview of the application of gene-expression profiling technology to substance abuse research and discusses future directions.
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Affiliation(s)
- Jonathan D Pollock
- Genetics and Molecular Neurobiology Research Branch, National Institute on Drug Abuse, 6001 Executive Blvd, Rockville, MD 20850, USA.
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29
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Robinson GE, Ben-Shahar Y. Social behavior and comparative genomics: new genes or new gene regulation? GENES, BRAIN, AND BEHAVIOR 2002; 1:197-203. [PMID: 12882364 DOI: 10.1034/j.1601-183x.2002.10401.x] [Citation(s) in RCA: 79] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Molecular analyses of social behavior are distinguished by the use of an unusually broad array of animal models. This is advantageous for a number of reasons, including the opportunity for comparative genomic analyses that address fundamental issues in the molecular biology of social behavior. One issue relates to the kinds of changes in genome structure and function that occur to give rise to social behavior. This paper considers one aspect of this issue, whether social evolution involves new genes, new gene regulation, or both. This is accomplished by briefly reviewing findings from studies of the fish Haplochromis burtoni, the vole Microtus ochrogaster, and the honey bee Apis mellifera, with a more detailed and prospective consideration of the honey bee.
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Affiliation(s)
- G E Robinson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana 61801, USA.
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30
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Ossadtchi A, Brown VM, Khan AH, Cherry SR, Nichols TE, Leahy RM, Smith DJ. Statistical analysis of multiplex brain gene expression images. Neurochem Res 2002; 27:1113-21. [PMID: 12462409 DOI: 10.1023/a:1020965107124] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Analysis of variance (ANOVA) was employed to investigate 9,000 gene expression patterns from brains of both normal mice and mice with a pharmacological model of Parkinson's disease (PD). The data set was obtained using voxelation, a method that allows high-throughput acquisition of 3D gene expression patterns through analysis of spatially registered voxels (cubes). This method produces multiple volumetric maps of gene expression analogous to the images reconstructed in biomedical imaging systems. The ANOVA model was compared to the results from singular value decomposition (SVD) by using the first 42 singular vectors of the data matrix, a number equal to the rank of the ANOVA model. The ANOVA was also compared to the results from non-parametric statistics. Lastly, images were obtained for a subset of genes that emerged from the ANOVA as significant. The results suggest that ANOVA will be a valuable framework for insights into the large number of gene expression patterns obtained from voxelation.
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Affiliation(s)
- Alex Ossadtchi
- Department of Electrical Engineering, Signal and Image Processing Institute, School of Engineering, University of Southern California, Los Angeles 90089, USA
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31
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Carson JP, Thaller C, Eichele G. A transcriptome atlas of the mouse brain at cellular resolution. Curr Opin Neurobiol 2002; 12:562-5. [PMID: 12367636 DOI: 10.1016/s0959-4388(02)00356-2] [Citation(s) in RCA: 70] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A genome-wide expression atlas of the nervous system at cellular resolution would be a valuable resource for neurobiology, genetics, developmental biology and medicine. Progress in automation of in situ hybridization makes such an atlas possible. Standardized and computerized annotation of expression patterns will be critical for producing a searchable atlas database that can be accessed through the internet.
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Affiliation(s)
- James P Carson
- Program in Structural and Computational Biology and Molecular Biophysics and National Center for Macromolecular Imaging, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA
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32
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Brown M, Clough J, Ramster B, Stapley L. News in brief. Drug Discov Today 2002. [DOI: 10.1016/s1359-6446(02)02397-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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33
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Affiliation(s)
- Andrew S Peterson
- Department of Neurology and the Ernest Gallo Clinic and Research Center, University of California at San Francisco, Emeryville, California 94608, USA.
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