Targeted mass spectrometry for the analysis of nutritive modulation of catalase and heme oxygenase-1 expression

Targeted mass spectrometry to monitor nuclear accumulation of endogenous Nrf2 and its application to SH-SY5Y cells stimulated with food components

The Nrf2 signaling pathway is highly significant for redox homeostasis. Hence, nutrients and drugs activating Nrf2 can prevent oxidative stress-mediated medical conditions. After activation, Nrf2 accumulates in the cell nucleus; therefore, stimulation of Nrf2 by food components and drugs is usually monitored by measuring nuclear Nrf2 levels. The present study developed a targeted mass spectrometry method for the highly reliable quantification of nuclear Nrf2 levels. Three Nrf2-specific peptides were detected after enzymatic digestion of the nuclear fraction by the developed protocol for micro-liquid chromatography-tandem mass spectrometry in scheduled multiple reaction monitoring mode (microLC-MS/MS-sMRM). The method also identified nuclear Nrf2 unequivocally and specifically in the SDS-PAGE fraction of 100-150 kDa. Moreover, highly precise and linear relative quantification was achieved (mean relative standard deviation 8.3%; coefficient of determination 0.998). Incubation experiments in SH-SY5Y neuroblastoma cells revealed significantly up to 6-fold elevated nuclear Nrf2 levels after stimulation with 10 μM carnosol (rosemary), 10 μM sulforaphane (broccoli), or 20 μM cinnamaldehyde (cinnamon). Our results were in very good accordance with conventional Nrf2 western blotting and were highly correlated with the food components' effect on the expression levels of NAD(P)H dehydrogenase [quinone] 1 and thioredoxin reductase 1, two major Nrf2-regulated cytoprotective enzymes. The newly developed microLC-MS/MS-sMRM method shows broad applicability and can serve as a highly selective and reliable method to analyze Nrf2 activation. Graphical abstract ᅟ.

Targeted label-free quantification of interleukin-8 in PMA-activated U937 cell secretome by nanoLC-ESI-MS/MS-sSRM

Monocytes are a part of the innate immune system. Their differentiation into macrophages changes their cellular proteome and secretome. Particularly secretome components such as cytokines are crucial for immune response and inflammation in many diseases. Differentiation of human lymphoma cell line U937 can be triggered by phorbol 12-myristate 13-acetate (PMA). Screening of the cytokine release in U937 upon PMA stimulation by cytometric bead array almost exclusively showed interleukin-8 (IL-8). Next, a label-free nanoLC-ESI-MS/MS-sSRM method for quantification of IL-8 in the cell secretome was established and applied to monitor the time kinetics of PMA treatment in different concentrations. Targeted secretome analysis was achieved by scheduled SRM-MS using one proteotypic peptide as precursor ion and four mass transitions. Label-free quantification was performed by external calibration using IL-8 standard. Validation results indicated that the method was suited for the quantification of IL-8 in the secretome. The maximal IL-8 release of 62.4 ng/mL was observed after incubating cells treated by 50 ng/mL PMA for 48 h. The method can now be used for quantification of IL-8 release from different cells under various conditions. Furthermore, it can be easily expanded to other secreted proteins detected by untargeted screening methods.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.