- WBPaper00042548:miRISC_enriched
Testable genes were defined as having reliable signals in two different biological replicates using the Agilent microarray chip. Multiple probes for the same gene were removed, keeping the probe with the lowest p-value as defined by a one-tailed t-test comparing all testable probes versus probes towards a designated gene. The testable data was then supplemented with the enrichment values (as percent ranks) of a fifth replicate, from another microarray platform GPL5883 (which had a single probe for each gene), and statistical significance was re-calculate. p < 0.001 was the final cutoff.
Genes enriched in neuronal miRNA-induced silencing complexes (miRISC) as detected by immunoprecipitations and microarray analysis.
- WBPaper00045140:aging_dynamic_regulation
The approaches of Gene Set Enrichment Analysis (GSEA) were performed using Category package in version 2.6.0 of Bioconductor to identify the significantly enriched pathways and genes in both above two subsets. In this analysis, the gene sets with less than 10 genes were excluded. The t-statistic mean of the genes was computed in each KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway. Using a permutation test with 1000 times, the cutoff of significance level p value was set as 0.01 for the most significant pathways related to aging. Accordingly, the significant pathways and genes were then identified under the comparison between different time points, including from L4 to D6 and from D6 to D15.
Genes with dynamic regulation pattern in signaling pathways during aging, based on re-analysis of microarray datasets.
- WBPaper00038213:E.coli(LF82)_24h_downregulated
Raw data were converted into a single peak list file using the in-house-developed software DTASupercharge and searched against the C. elegans NCBI nonredundant database using MASCOT 2.0 (Matrix Science, London, UK) with the following parameters: carbamidomethylcysteine was set as fixed modification and methionine oxidation, deamidation of asparagine and glutamine, and protein amino-terminal acetylation were set as variable modifications. 15N Metabolic was chosen as quantification mode. Two miss cleavages were allowed; enzyme specificity was trypsin D/DP, precursor mass accuracy had to be within 30 ppm, and the fragment spectra mass accuracy was set at 0.8 Da. The identified peptides were recalibrated using MSQuant (version 1.4.3a89), results were combined using MGF combiner (version 1.05) and re-searched using MASCOT 2.0 with the above mentioned parameters except that the precursor mass tolerance was set to 5 ppm. MSQuant and in-house-developed script N15-patch was used to quantify peptides and all spectra were manually verified. The represented protein ratio is calculated by averaging all peptide ratios for that protein. To correct for mixing errors, protein ratios were normalized by adjusting the median ratio to 1. To determine the number of false-positive peptide hits the data were searched against a decoy database and the MASCOT peptide score was adjusted to yield a number of false-positive peptide identifications of less than 1%. Only proteins identified by two or more unique peptides were considered. Two biological replicates were analyzed.
Proteins whose abundance decreased more than 1.5-fold, after 24 h of infection with bacteria LF82.
- WBPaper00038213:E.coli(LF82)_72h_upregulated
Raw data were converted into a single peak list file using the in-house-developed software DTASupercharge and searched against the C. elegans NCBI nonredundant database using MASCOT 2.0 (Matrix Science, London, UK) with the following parameters: carbamidomethylcysteine was set as fixed modification and methionine oxidation, deamidation of asparagine and glutamine, and protein amino-terminal acetylation were set as variable modifications. 15N Metabolic was chosen as quantification mode. Two miss cleavages were allowed; enzyme specificity was trypsin D/DP, precursor mass accuracy had to be within 30 ppm, and the fragment spectra mass accuracy was set at 0.8 Da. The identified peptides were recalibrated using MSQuant (version 1.4.3a89), results were combined using MGF combiner (version 1.05) and re-searched using MASCOT 2.0 with the above mentioned parameters except that the precursor mass tolerance was set to 5 ppm. MSQuant and in-house-developed script N15-patch was used to quantify peptides and all spectra were manually verified. The represented protein ratio is calculated by averaging all peptide ratios for that protein. To correct for mixing errors, protein ratios were normalized by adjusting the median ratio to 1. To determine the number of false-positive peptide hits the data were searched against a decoy database and the MASCOT peptide score was adjusted to yield a number of false-positive peptide identifications of less than 1%. Only proteins identified by two or more unique peptides were considered. Two biological replicates were analyzed.
Proteins whose abundance increased more than 1.5-fold, after 72 h of infection with bacteria LF82.
- WBPaper00038213:E.coli(LF82)_72h_downregulated
Raw data were converted into a single peak list file using the in-house-developed software DTASupercharge and searched against the C. elegans NCBI nonredundant database using MASCOT 2.0 (Matrix Science, London, UK) with the following parameters: carbamidomethylcysteine was set as fixed modification and methionine oxidation, deamidation of asparagine and glutamine, and protein amino-terminal acetylation were set as variable modifications. 15N Metabolic was chosen as quantification mode. Two miss cleavages were allowed; enzyme specificity was trypsin D/DP, precursor mass accuracy had to be within 30 ppm, and the fragment spectra mass accuracy was set at 0.8 Da. The identified peptides were recalibrated using MSQuant (version 1.4.3a89), results were combined using MGF combiner (version 1.05) and re-searched using MASCOT 2.0 with the above mentioned parameters except that the precursor mass tolerance was set to 5 ppm. MSQuant and in-house-developed script N15-patch was used to quantify peptides and all spectra were manually verified. The represented protein ratio is calculated by averaging all peptide ratios for that protein. To correct for mixing errors, protein ratios were normalized by adjusting the median ratio to 1. To determine the number of false-positive peptide hits the data were searched against a decoy database and the MASCOT peptide score was adjusted to yield a number of false-positive peptide identifications of less than 1%. Only proteins identified by two or more unique peptides were considered. Two biological replicates were analyzed.
Proteins whose abundance decreased more than 1.5-fold, after 72 h of infection with bacteria LF82.
- WBPaper00038213:E.coli(LF82)_24h_upregulated
Raw data were converted into a single peak list file using the in-house-developed software DTASupercharge and searched against the C. elegans NCBI nonredundant database using MASCOT 2.0 (Matrix Science, London, UK) with the following parameters: carbamidomethylcysteine was set as fixed modification and methionine oxidation, deamidation of asparagine and glutamine, and protein amino-terminal acetylation were set as variable modifications. 15N Metabolic was chosen as quantification mode. Two miss cleavages were allowed; enzyme specificity was trypsin D/DP, precursor mass accuracy had to be within 30 ppm, and the fragment spectra mass accuracy was set at 0.8 Da. The identified peptides were recalibrated using MSQuant (version 1.4.3a89), results were combined using MGF combiner (version 1.05) and re-searched using MASCOT 2.0 with the above mentioned parameters except that the precursor mass tolerance was set to 5 ppm. MSQuant and in-house-developed script N15-patch was used to quantify peptides and all spectra were manually verified. The represented protein ratio is calculated by averaging all peptide ratios for that protein. To correct for mixing errors, protein ratios were normalized by adjusting the median ratio to 1. To determine the number of false-positive peptide hits the data were searched against a decoy database and the MASCOT peptide score was adjusted to yield a number of false-positive peptide identifications of less than 1%. Only proteins identified by two or more unique peptides were considered. Two biological replicates were analyzed.
Proteins whose abundance increased more than 1.5-fold, after 24 h of infection with bacteria LF82.