Cajanus cajan- a source of PPARγ activators leading to anti-inflammatory and cytotoxic effects.

Cajanus cajan is an important legume crop in the human diet in many parts of the world. Due to its pharmacological properties, C. cajan is, moreover, used in traditional medicine for treating skin diseases, diabetes, inflammatory disorders and various other dysfunctions. In this study, we focused on the role of peroxisome proliferator-activated receptor gamma (PPARγ) as a potential therapeutic target of Cajanus cajan and its main compounds for the treatment of cancer, inflammation and inflammation-related disorders. The anti-inflammatory potential of C. cajan and its bioactive compounds and their cytotoxicity on the human cervical adenocarcinoma cell line HeLa, the human colorectal adenocarcinoma cell line CaCo-2 and the human breast adenocarcinoma cell line MCF-7 were elucidated. C. cajan and its compounds exerted significant anti-inflammatory activity on lipopolysaccharide-stimulated macrophages, showed good cytotoxic effects on the 3 different cancer cell lines and proved PPARγ activity in vitro. The main active compounds were orientin, pinostrobin and vitexin. Cajaninstilbene acid and pinosylvin monomethylether were identified as novel PPARγ activators. Based on these data, C. cajan provides excellent beneficial medicinal attributes and may be used as a potential food or a pharmaceutical supplement.

Heat-Treatment-Responsive Proteins in Different Developmental Stages of Tomato Pollen Detected by Targeted Mass Accuracy Precursor Alignment (tMAPA).

Recently, we have developed a quantitative shotgun proteomics strategy called mass accuracy precursor alignment (MAPA). The MAPA algorithm uses high mass accuracy to bin mass-to-charge (m/z) ratios of precursor ions from LC-MS analyses, determines their intensities, and extracts a quantitative sample versus m/z ratio data alignment matrix from a multitude of samples. Here, we introduce a novel feature of this algorithm that allows the extraction and alignment of proteotypic peptide precursor ions or any other target peptide from complex shotgun proteomics data for accurate quantification of unique proteins. This strategy circumvents the problem of confusing the quantification of proteins due to indistinguishable protein isoforms by a typical shotgun proteomics approach. We applied this strategy to a comparison of control and heat-treated tomato pollen grains at two developmental stages, post-meiotic and mature. Pollen is a temperature-sensitive tissue involved in the reproductive cycle of plants and plays a major role in fruit setting and yield. By LC-MS-based shotgun proteomics, we identified more than 2000 proteins in total for all different tissues. By applying the targeted MAPA data-processing strategy, 51 unique proteins were identified as heat-treatment-responsive protein candidates. The potential function of the identified candidates in a specific developmental stage is discussed.