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Biology subjects

Mohr, T.

Publications and source records attributed to Mohr, T..

3 recordsLinked to original sources

Integrated tissue proteomics and lipidomics from ovine organs suggests novel functional implications for fatty acids and lipid mediators.

Lipid mediators are potent biomolecules that may help to gain specific information about biological processes. However, due to incomplete functional annotations and hence interpretive challenges these molecules are hardly considered in molecular profiling experiments. We hypothesized that correlating lipid mediators extracted from tissues with corresponding proteomics data and the corresponding Gene Ontology terms characteristic of specific tissue types could enable functional annotation of these lipids. Thirteen organs and tissues from sheep (Ovis aries) were analyzed using mass spectrometry-based untargeted proteomics and lipidomics. In total, 4717 proteins and 166 free fatty acids, oxylipins, lysolipids, endocannabinoids, and bile acids were catalogued. This included the previously uncharacterized oxylipin 4-hydroxy-eicosatetraenoic acid (4-HETE), whose identity was confirmed by chemical synthesis. Co-expression and clustering analyses validated our hypothesis, successfully reproducing known and suggesting novel lipid mediator functions. Tissue levels of polyunsaturated fatty acids (PUFAs) correlated with pro-resolving mediators and, unexpectedly, with the cellular protein synthesis and folding machinery. These findings suggest that PUFAs and their derivatives support protein synthesis fidelity and efferocytosis, both essential contributors for the effective resolution of inflammation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/685055v2_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@126b41org.highwire.dtl.DTLVardef@13fa9adorg.highwire.dtl.DTLVardef@9ccaa1org.highwire.dtl.DTLVardef@1bb429b_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO The Figure was partly generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 Unported license. C_FIG

systems biology↗

Multilevel Omics-Readouts of in vitro Perturbation Studies are Determined by Memory Effects from Subculture

Mass spectrometry-based omics technologies are increasingly used to map drug effects to biological pathways by identifying significant molecular events. Significance is influenced by the effect size and the variation of each molecular parameter. While the former is largely determined by the biological system, the latter can be tuned by the experimental workflow. Here, we unequivocally show that memory effects originating from subculture of colon carcinoma cells before treating with arsenic trioxide exacerbate the variation of multiple omics levels, including eicosadomics, proteomics and phosphoproteomics, without necessarily impacting on effect size. Real-time monitoring of individual samples enables control over subculture homogeneity and improves the median variation >2-fold across omics levels. This considerably facilitated mode of action deconvolution and resulted in a bilevel perturbation network of 321 causal conjectures. Controlling memory effects from subculture revealed key signaling cascades and transcriptional regulatory events that extend the molecular understanding of arsenic trioxide in solid tumors.

systems biology↗

STAT3-dependent systems-level analysis reveals PDK4 as an independent predictor of biochemical recurrence in prostate cancer

Prostate cancer (PCa) has a broad spectrum of clinical behaviour, hence biomarkers are urgently needed for risk stratification. We previously described the protective effect of STAT3 in a prostate cancer mouse model. By utilizing a gene co-expression network in addition to laser microdissected proteomics from human and murine prostate FFPE samples, we describe STAT3-induced downregulation of the TCA cycle/OXPHOS in PCa on transcriptomic and proteomic level. We identify pyruvate dehydrogenase kinase 4 (PDK4), a key regulator of the TCA cycle, as a promising independent prognostic marker in PCa. PDK4 predicts disease recurrence independent of diagnostic risk factors such as grading, staging and PSA level. Furthermore, PDK4 expression is causally linked to type 2 diabetes mellitus, which is known to have a protective effect on PCa. We conclude that this effect is related to PDK4 expression and that PDK4 loss could serve as a biomarker for PCa with dismal prognosis.

cancer biology↗