Dataset Information

Proteogenomic Analysis of Human Colon Carcinoma Cell Lines LIM1215, LIM1899 and LIM2405

ABSTRACT: In this study, we have integrated shotgun proteomics approach to compare the protein expression profiles of 3 human colon cancer cell lines (LIM1215, LIM1899 and LIM2405) representing alternative forms of colorectal cancer. We have performed detailed analysis of our proteomics data (coupled with RNA-Seq data, database identifiers not available), which has identified several cancer-associated proteins with differential expression patterns. We have also identified some protein networks which appear dysregulated in these cell lines. Protein Identification and Data Analysis: Spectra files were converted to mzXML format and processed through the global proteome machine software (GPM) (version 2.1.1), an open source protein identification system that uses the X!Tandem algorithm. For each experiment, 16 fractions were processed sequentially with output files for each individual fraction and a merged, non-redundant output file generated for protein identifications with Log (e) values less than –1. Peptide identification was determined using a parent ion mass error of +3 Da and –0.5 Da and fragment ion tolerance of 0.4 Da.30 Mass spectra were searched based on peptide trypticity with up to three missed cleavages. Carbamidomethyl was considered as a complete modification and partial modifications were also considered, including oxidation of methionine and threonine, and deamidation of asparagine and glutamine. MS/MS spectra were searched against the Homo sapiens database (Database derived from SwissProt, Ensemble, and NCBI) and reverse database searching was used to estimate false discovery rates (calculated at less than 1%).31 Data were analyzed using various bioinformatics tools, including DAVID Functional Annotation Tool (http://david.abcc.ncifcrf.gov/), Pathway Commons (http://www.pathwaycommons.org) and GeneCards (www.genecards.org).

INSTRUMENT(S): LTQ

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Susan Fanayan

PROVIDER: PXD000120 | Pride | 2013-03-13

REPOSITORIES: Pride

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Publications

Proteogenomic analysis of human colon carcinoma cell lines LIM1215, LIM1899, and LIM2405.

Fanayan Susan S Smith Joshua T JT Lee Ling Y LY Yan Fangfei F Snyder Michael M Hancock William S WS Nice Edouard E

Journal of proteome research 20130313 4

As part of the genome-wide and chromosome-centric human proteomic project (C-HPP), we have integrated shotgun proteomics approach and a genome-wide transcriptomic approach (RNA-Seq) of a set of human colon cancer cell lines (LIM1215, LIM1899 and LIM2405) that were selected to represent a wide range of pathological states of colorectal cancer. The combination of a standard proteomics approach (1D-gel electrophoresis coupled to LC/ion trap mass spectrometry) and RNA-Seq allowed us to exploit the g ...[more]

PMID: 23458625

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Project description:In this project, we aim to pair-wise analyze the genomes, transcriptomes and proteomes of in-bred rats originating from two different genetic backgrounds. These two strains are Brown Norway (BN-Lx) and Spontaneously Hypertensive Rats (SHR). First, we re-sequenced the genomes for both BN and SHR rats, followed by RNA-seq and proteomics of their liver tissues. We then append novel predicted gene models, non-synonymous SNPs and INDELs (derived from genome re-sequencing), as well as transcript variants such as RNA-editing and alternative splicing (derived from RNA-seq) that can diversify existing protein sequences onto the ENSEMBL rat FASTA (Build 68) to build an enhanced database. For proteomics studies, equal amount of liver lysates were digested with trypsin, LysC, GluC, AspN and chymotrypsin and were individually fractionated with strong cationic exchange chromatography. Doubly- and triply-charged fractions were analyzed with an Triple-TOF 5600 with collision-activated dissociation (CAD); while electron-transfer dissociation (ETD) was applied for fractions containing triple charges and above with a LTQ-Orbitrap Velos. Data analysis: Peak List generation: For Wiff files generated from TripleTOF 5600, tandem MS spectra were de-isotoped, charge- deconvoluted and peak lists converted to Mascot generic format (MGF) files using AB Sciex Data Converter (version 1.1). For data generated from the LTQ-Orbitrap Velos, Raw files were converted to MGF files using Proteome Discoverer (version 1.3). The non-fragment filter was used to simplify ETD spectra and the Top N filter for the HCD spectra. Three MGF files were generated (one for HCD, one for ETD IT and one for ETD FT). The files with an orbitrap readout were deisotoped and charge de-convoluted. Database Searching: All MGF files were queried with Mascot search engine (version 2.3) via Proteome Discoverer version 1.3 (PD 1.3, Thermo Fisher) for submission. The spectra were searched against in-house database (NGS_COMBINED). One of the five different enzymes used (Trypsin/P, LysC/P, Chymotrypsin, GluC-DE and AspN_ambic) were selected for each file and up to 9 missed cleavages were allowed. Cysteine carbamidomethylation was set as fixed modification, and oxidation of methionine and acetylation of the N-term as variable modifications. Peptide tolerance was initially set to 50 ppm and the MS/MS tolerance was set to 0.1 Da (for TOF readout), 0.02 Da (orbitrap readout) and 0.5 Da (ion trap readout). All peptide-spectrum matches (PSMs) were evaluated with Percolator for validation. We classified each PSM based on their q value. For proteins identification, we used set a high stringency filter of q = 0 (0% FDR). For peaks lists that do not yield any peptide matches, we exported them with PD 1.3 for further analysis. De novo search with PEAKS: Unassigned peak lists that are exported were re-analyzed with another software suite i.e. PEAKS Studio (version 6.0). The identification workflows is as follows. Peak lists were first filtered with a quality value of 0.65 as suggested by the manufacturer followed by de novo spectra interpretation. In this step, both peptide tolerance and MS/MS tolerance were set according to MASCOT search. To broaden the search space for these unassigned spectra, we additionally set de-amidation of asparagine and glutamine, and pyro-glu from glutamic acid and glutamine as variable modifications, on top of the other modifications indicated above. Maximum allowed variable PTM per peptide was set to 3. Finally de novo interpreted PSMs were submitted to PEAKS DB database matching, this time allowing semi-enzymatic specificity and a maximum cleavages per peptide of 2. Database used was set to NGS_COMBINED. FDR was estimated using decoy-fusion. The genomics and transcriptomics data are already deposited in the respective EBI repositories. Some of these data are derived from an already published manuscript. For the genomics data (from: Genetic basis of transcriptome differences between the founder strains of the rat HXB/BXH recombinant inbred panel by Simonis et al PMID:22541052) DNA data in Sequence Read Archive (SRA): BN-Lx genome: ERP001355 http://www.ebi.ac.uk/ena/data/view/ERP001355, SHR genome: ERP001371, BN reference genome: ERP000510, http://www.ebi.ac.uk/ena/data/view/ERP000510. RNA data in ArrayExpress: BN-Lx and SHR fragment RNA-seq data: E-MTAB-1029 http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1029, BN-Lx and SHR paired-end RNA-seq data: to be submitted.

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Project description:Detailed information: Rice (*Oryza sativa* L. cv. Nipponbare) is a drought-susceptible species which is well suited for studies of abiotic stress response because of the comprehensive bioinformatics resource available. By withholding water from the entire root system of young rice plants, or half the root system only, it was possible to infer the relative impact of signals arriving from roots growing in wet and dry soil on the shoot proteome. The global proteome of shoots had 685 proteins in common to all three drought treatments but there were major shifts in abundance of individual proteins within 16 functional categories. The dominant changes were analyzed more deeply. First, we investigated transport and cell component organization, where some proteins were up-regulated by drought but many more down-regulated. Proteins involved in protein metabolism were up-regulated in general by drought when they were responsible for protein degradation but those involved in protein synthesis were down-regulated when water was withheld. Stress-related proteins behaved very consistently by increasing in droughted plants but notably some proteins were most abundant when roots of the same plant were growing in both wet and dry soil. This suggests that drought signals are complex interactions and not simply the additive effect of water supply to the roots. Changes in carbohydrate-processing proteins were consistent with the passive accumulation of soluble sugars in shoots under drought, with hydrolysis of sucrose and starch synthesis both enhanced. Data analysis information: The result raw files were converted to mzXML format and processed through the global proteome machine (GPM) software (version 2.1.1) of the X!Tandem algorithm (freely available at http://www.thegpm.org). The 16 gel fractions were processed serially for each experiment and the output files were generated as non-redundant, merged files with protein identifications with log (e) values less than -1, for each individual gel fraction. A protein database compiled from NCBI *O*. *sativa* with 26938 protein sequences (August 2011) was used in GPM to search the tandem mass spectra; the database also included common trypsin and human peptide contaminants. False discovery rates (FDR) were evaluated by searching against a reversed sequence database. Search parameters included MS and MS/MS tolerances of +2 Da and +0.2 Da, carbamidomethylation of cysteine as fixed modifications, oxidation of methionine as variable modifications and tolerance of two missed tryptic cleavages and K/R-P cleavages.

			Action	DRS
	LIM1215_Exp1.xml	Xml
	LIM1215_Exp1_Raw.zip	Other
	LIM1215_Exp1_mzXML.zip	Other
	LIM1215_Exp2.xml	Xml
	LIM1215_Exp2_Raw.zip	Other