4 research outputs found
Comprehensive Metabolomic and Lipidomic Profiling of Human Kidney Tissue: A Platform Comparison
Metabolite profiling
of tissue samples is a promising approach
for the characterization of cancer pathways and tumor classification
based on metabolic features. Here, we present an analytical method
for nontargeted metabolomics of kidney tissue. Capitalizing on different
chemical properties of metabolites allowed us to extract a broad range
of molecules covering small polar molecules and less polar lipid classes
that were analyzed by LC-QTOF-MS after HILIC and RP chromatographic
separation, respectively. More than 1000 features could be reproducibly
extracted and analyzed (CV < 30%) in porcine and human kidney tissue,
which were used as surrogate matrices for method development. To further
assess assay performance, cross-validation of the nontargeted metabolomics
platform to a targeted metabolomics approach was carried out. Strikingly,
from 102 metabolites that could be detected on both platforms, the
majority (>90%) revealed Spearmanâs correlation coefficients
â„0.3, indicating that quantitative results from the nontargeted
assay are largely comparable to data derived from classical targeted
assays. Finally, as proof of concept, the method was applied to human
kidney tissue where a clear differentiation between kidney cancer
and nontumorous material could be demonstrated on the basis of unsupervised
statistical analysis
Additional file 3: of Systems-level organization of yeast methylotrophic lifestyle
Enrichment of the peroxisomal marker protein Pex3p in the peroxisomal fraction. (PDF 271 kb
Additional file 1: of Systems-level organization of yeast methylotrophic lifestyle
Transcriptomic, proteomic, and metabolomic regulation of P. pastoris during methylotrophic growth. Containing the following eight sheets: Summary Omics Data: number of significantly regulated genes, proteins or metabolites (e.g. âupâ refers to up-regulation in methanol/glycerol compared to glucose). Transcriptomics and proteomics: Average fold changes and P values of transcriptomics and proteomics comparing P. pastoris cultivated with methanol/glycerol or glucose as carbon source in chemostat. Average values derive from three biological replicates per condition. Metabolomics: Average fold changes and P values of metabolomics measurements comparing P. pastoris cultivated with methanol/glycerol or glucose as carbon source in chemostat cultivations. Average values derive from three biological replicates per condition. Co-regulation (related to Fig. 1 in the text): Regulation of the 575 gene-protein pairs with transcriptomics and proteomics data available and assignment to regulatory groups. Central carbon metabolism (related to Fig. 4 in the text): Average fold changes and P values of transcriptomics, proteomics, and metabolomics measurement depicted in Fig. 4. Amino acid metabolism (related to Fig. 6 in the text): Average fold changes and P values of transcriptomics, proteomics, and metabolomics measurement depicted in Fig. 6. Vitamin biosynthesis (related to Fig. 7 in the text): Average fold changes and P values of transcriptomics, proteomics, and metabolomics measurement depicted in Fig. 7. Peroxisomal gene regulation: Average fold changes and P values of transcriptomics and proteomics for all mentioned peroxisomal genes. Average values derive from three biological replicates per condition. (XLSX 2348 kb
Additional file 4: of Systems-level organization of yeast methylotrophic lifestyle
Proteomic identification and quantification of methanol metabolic enzymes and control proteins in peroxisomal fractions and homogenates of P. pastoris cells grown on methanol. Containing the following three sheets: Protein hits: contains all identified proteins that met the threshold in at least one sample, with their respective MASCOT scores, number of peptides, and percent sequence coverage. Peptide hits: list of all identified peptides, their MASCOT scores, mass and charge values, and intensities. Peptides used for quantâ+âareas: lists all peptides of the proteins in Table 3 that were used for quantification, and their respective peak areas in the different samples. (XLSX 879 kb