Integrated proteomic and transcriptomic profiling of mouse lung development and Nmyc target genes
Brian Cox1,2,8,9, Thomas Kislinger3,8,10, Dennis A Wigle2,11, Anitha Kannan4, Kevin Brown5,6, Tadashi Okubo7,12, Brigid Hogan7, Igor Jurisica5,6, Brendan Frey1,4, Janet Rossant1,2,9 & Andrew Emili1,3
- Department of Medical Genetics and Microbiology, University of Toronto, Toronto, Ontario, Canada
- Samuel Lunenfeld Research Institute, Mt Sinai Hospital, Toronto, Ontario, Canada
- Program in Proteomics and Bioinformatics, University of Toronto, Toronto, Ontario, Canada
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Division of Signaling Biology, Princess Margaret Hospital, Toronto, Ontario, Canada
- Department of Cell Biology, Duke University Medical Center, NC, USA
- These authors contributed equally to this work
- Present address: Department of Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
- Present address: Ontario Cancer Institute, Toronto, Canada
- Present address: Division of Thoracic Surgery, Mayo Clinic Cancer Center, Mayo Clinic, MN, USA
- Present address: Center For Integrative Bioscience, National Institutes of Natural Sciences, Okazaki, Japan
Correspondence to: Andrew Emili1,3 Donnelly Centre for Cellular and Biomolecular Research (CCBR), University of Toronto, 160 College Street, Room 914, Toronto, Ontario, Canada M5S 3E1. Tel.: +416 946 7281; Fax: +416 978 8528; Email: andrew.emili@utoronto.ca
Correspondence to: Janet Rossant1,2,9 The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, Canada M5G 1X8. Tel.: +416 813 6577; Fax: +416 813 5085; Email: janet.rossant@sickkids.ca
Received 6 November 2006; Accepted 18 March 2007; Published online 8 May 2007
Article highlights
- Survey of expression of over 3300 proteins during lung development over six time points, E13.5 to adult
- Prediction of subcellular localization of 1000 proteins
- Correlation of microarray expression data with protein data to identify a set of over 600 gene products with correlated expression profiles
- Identification of 90 putative direct targets of the transcription factor Nmyc in the lung using loss and gain of function mutants
Synopsis
The lung is a complex and highly organized tissue consisting of an epithelium in contact with the air, a mesenchyme layer allowing for the expansion and contraction of the lung during breathing and a complex vasculature to bring blood close to the site of gas exchange. The development of the lung is well defined morphologically and many genes have been shown to the critical for correct development using mouse genetic models such as gene knockout and misexpression (Kimura et al, 1996; Sekine et al, 1999). Several global microarray expression studies have investigated the profile of gene expression during normal lung development (Mariani et al, 2002; Bonner et al, 2003; Lu et al, 2004a). However, the expression levels and subcellular localization of the cognate proteins are largely unknown.
Here, we report the profiling of proteins in the lung by gel-free two-dimensional liquid chromatography coupled to shotgun tandem mass spectrometry (MudPIT) over six developmental time points covering most of the significant stages of lung development. A prefractionation into organellar compartments (cytosol, nucleus and mitochondria) was performed to assay both tissue and subcellular specificity from the same sample preparation (Kislinger et al, 2003, 2006). Comparison of the proteomic data with mRNA expression profiles revealed a large number of gene products (protein and mRNA) that are coordinately regulated during development (Figure 5A). We were also able to identify a smaller group of 
30 genes whose levels of mRNA and protein expression are uncorrelated (Figure 5D), suggesting regulation via post-transcriptional or post-translational control mechanisms.
Figure 5
Correlation analysis of protein and microarray data for lung developmental time course. Math modeling identified four subsets in the data sets: (A) significant inliers, (B) insignificant inliers, (C) insignificant outliers and (D) significant outliers. Whereas inlier denotes a positive correlation score, outliers denote a negative correlation score and significant indicates that the correlation is statistically different from the background (noise) model, whereas insignificant is not. Each subset was then either clustered by K-means (A, B) or simply visualized due to the lower information content. Note that the significant inliers contains many clear patterns of dynamic gene expression and those with static expression throughout development. The significant outliers shows several genes with off set protein and mRNA expression, where the mRNA increases before the protein.
Full figure and legend (237K)Figures & Tables indexHaving established a baseline of normal lung development, we next characterized the molecular changes that take place in mutant genetic backgrounds. One of the most powerful tools in understanding gene function is the combination of loss-of-function (nulls or hypomorophs) and gain-of-function (misexpression or overexpression) mutants. We used loss- and gain-of-function mutants of the gene Nmyc, a transcription factor that has previously been shown to be critical for lung development (Moens et al, 1992, 1993; Okubo et al, 2005), to molecularly characterize its function in lung development by proteomics and microarray profiling. By combining these data sets, we identified several potential direct targets of Nmyc regulation (Figure 6). Furthermore, as Nmyc can function as both a transcriptional activator and repressor, we were able to classify these target genes as being activated or repressed by Nmyc. Along with several known targets of Nmyc, we also identified many genes involved in mRNA processing, splicing and export that appeared positively regulated by Nmyc. We identified four genes that appeared to be repressed by Nmyc including Igf2r an imprinted gene.
Figure 6
mRNA and protein regulation in Nmyc loss- and gain-of-function mutant E18.5 lungs. Combined protein and microarray that tested as being significantly regulated was separated into direct and indirect classes based on the expected profiles of positive, where both transcript and protein are reduced in the loss of function mutant and the transcript is increased in the gain of function mutant and negative, with the opposite profile to positive. Based on these profiles, 90 protein microarray pairs were extracted and are organized with the potential positive targets followed by the four negative targets at the bottom of the figure.
Full figure and legend (160K)Figures & Tables indexIn summary, we have shown that the technique of gel-free two-dimensional liquid chromatography coupled to shotgun tandem mass spectrometry (MudPIT) can be used to profile embryonic tissues during development. Mining of protein profiles and protein–protein interaction networks was used to identify proteins with potential developmental importance. Finally, integrative analysis of protein and mRNA levels in Nmyc hypomorph and overexpressing mutant mice identified a list of possible direct Nmyc target genes.
Acknowledgements
We thank Eric Sat for assistance in genenotyping and breeding the Nmyc9a mice and Owen Tamplin for assistance with confocal microscopy. This work was supported by grants from the Canadian Institutes of Health Research to JR and grants from Canadian Institutes of Health Research, the McLaughlin Centre for Molecular Medicine, Genome Canada and the Ontario Genomics Institute (OGI) and the Natural Science and Engineering Council of Canada (NSERC) to AE. DAW was supported by a Canadian Institutes of Health Research postdoctoral fellowship, TK was supported in part by the Josef Schormüller Gedächtnisstiftung, BC by a Canadian Institutes of Health Research Doctoral fellowship and JR a distinguished investigator award from the CIHR. OPHID is supported by funding from Genome Canada through the Ontario Genomics Institute, the Younger and Firemen Foundations and IBM.
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