Biology subjects

Kwiatkowski, M.

Publications and source records attributed to Kwiatkowski, M..

3 recordsLinked to original sources

bioRxiv2021

Moonlighting adenylyl cyclases in plants: an Arabidopsis thaliana 9-cis-epoxycarotenoid dioxygenase as point in case

Adenylyl cyclases (ACs) and their catalytic product cAMP are regulatory components of plant responses. AC domains are intrinsic components of complex molecules with multiple functions, some of which are co-regulated by cAMP. Here we used an amino acid search motif based on annotated ACs in organisms across species to identify 12 unique Arabidopsis thaliana candidate ACs, four of which have a role in the biosynthesis of the stress hormone abscisic acid (ABA). One of these, the 9-cis-epoxycarotenoid dioxygenase (NCED3, At3g14440), was identified by sequence and structural analysis as a putative AC and then tested experimentally for activity. We show that an NCED3 AC fragment can complement an AC deficient E. coli mutant and this rescue is nullified when key amino acids in the AC motif are mutated. AC activity was also confirmed by tandem liquid chromatography mass spectrometry (LC-MS/MS). Our results are consistent with a moonlighting role for mononucleotide cyclases in multi-domain proteins that have at least one other distinct molecular function such as catalysis or ion channel activation and promise to yield new insights into tuning mechanisms of ABA dependent plant responses. Finally, our search method can also be applied to discover ACs in other species including Homo sapiens. HighlightsO_LIAn adenylyl cyclase (AC) catalytic center motif identifies novel ACs in plants C_LIO_LIACs can moonlight in complex proteins with other enzymatic domains C_LIO_LIA 9-cis-epoxycarotenoid dioxygenase essential for abscisic acid synthesis contains an AC C_LIO_LIThis finding implicates cAMP in abscisic acid synthesis and signaling C_LI

plant biology↗

bioRxiv2020

Natural isotope correction improves analysis of protein modification dynamics

Stable isotope labelling in combination with high resolution mass spectrometry approaches are increasingly used to analyse both metabolite and protein modification dynamics. To enable correct estimation of the resulting dynamics it is critical to correct the measured values for naturally occurring stable isotopes, a process commonly called isotopologue correction or deconvolution. While the importance of isotopologue correction is well recognized in metabolomics, it has received far less attention in proteomics approaches. Although several tools exist that enable isotopologue correction of mass spectrometry data, the majority is tailored for the analysis of low molecular weight metabolites. We here present PICor which has been developed for isotopologue correction of complex isotope labelling experiments in proteomics or metabolomics and demonstrate the importance of appropriate correction for accurate determination of protein modifications dynamics, using histone acetylation as an example.

bioinformatics↗

bioRxiv2019

Fibroblast-specific genome-scale modelling predicts an imbalance in amino acid metabolism in Refsum disease

Refsum disease is an inborn error of metabolism that is characterised by a defect in peroxisomal -oxidation of the branched-chain fatty acid phytanic acid. The disorder presents with late-onset progressive retinitis pigmentosa and polyneuropathy and can be diagnosed biochemically by elevated levels of phytanic acid in plasma and tissues of patients. To date, no cure exists for Refsum disease, but phytanic acid levels in patients can be reduced by plasmapheresis and a strict diet.\n\nIn this study, we reconstructed a fibroblast-specific genome-scale model based on the recently published, FAD-curated model, based on Recon3D reconstruction. We used transcriptomics (available via GEO database with identifier GSE138379), metabolomics, and proteomics data (available via ProteomeXchange with identifier PXD015518), which we obtained from healthy controls and Refsum disease patient fibroblasts incubated with phytol, a precursor of phytanic acid.\n\nOur model correctly represents the metabolism of phytanic acid and displays fibroblast-specific metabolic functions. Using this model, we investigated the metabolic phenotype of Refsum disease at the genome-scale, and we studied the effect of phytanic acid on cell metabolism. We identified 53 metabolites that were predicted to discriminate between Healthy and Refsum disease patients, several of which with a link to amino acid metabolism. Ultimately, these insights in metabolic changes may provide leads for pathophysiology and therapy.

systems biology↗