Biology subjects

Kwiatkowski, M.

Publications and source records attributed to Kwiatkowski, M..

12 recordsLinked to original sources

bioRxiv2026

Predicting Pain Using a Data-Driven Agent-Based Model of the Bilateral Central Amygdala

Sensory processing in the amygdala is a complex, dynamic process. Decades of surgical, electrical, pharmacological, optogenetic, and chemogenetic in vivo manipulations have revealed the nociceptive functions of anatomically- and genetically-restricted neuronal populations. In parallel, molecular and electrophysiological approaches have allowed for high-resolution, temporal examination of nociceptive-induced alterations in amygdala plasticity. Computational integration of this data is critical for future therapeutic development; in practice, these models would allow for in silico prediction of amygdala activity following injury, and in a reciprocal fashion, changes in pain-like behaviors following manipulation of discrete amygdala neuronal populations. To this end, we developed a three-dimensional computer model of the bilateral central nucleus of the amygdala (CeA). We employed agent-based modelling to integrate wet-lab data from two CeA cell populations: Calcitonin Gene-Related Peptide Receptor (CGRPR; Calcrl) expressing cells and Protein Kinase C delta (PKC{delta}; Prkcd) expressing cells. We integrated the spatial location, connectivity, neuronal activity, and electrophysiological properties of these neurons in our realistic bilateral model architecture. Our model captures properties of the amygdala that drive pain modulation, including hemisphere-specific physiological differences, and generates predictions of nociception related to bladder injury. Predictions from the model were compared retrospectively to pain outcomes during manipulation of CGRPR-expressing neurons in whole mice. These comparisons show strong alignment between our model and in vivo outcomes. Significance StatementNociceptive processing in the amygdala emerges from interactions among cell types. No framework has been developed that recapitulates this complexity. Here, we generated a 3-D agent-based computational model of the bilateral central amygdala (CeA) using data that accounts for pain-associated changes in neuronal physiology, cellular identity, anatomical positioning, and temporal specificity. The model revealed that hemispheric differences in intrinsic CeA neuronal excitability are dominant drivers of nociceptive output. Furthermore, when manipulated to mimic injury-associated plasticity, the model accurately predicted behavioral outcomes. This model is a publicly available computational tool that predicts hemisphere-targeted pain therapy efficacy. Moreover, the flexibility of this framework will allow future adaptations to other brain areas and disease contexts.

neuroscience↗

bioRxiv2026

Abscisic acid binds to an Arabidopsis thaliana phosphodiesterase and tunes its activity

Growing evidence suggests that plant proteomes contain numerous proteins that specifically bind abscisic acid (ABA). Many of them are complex multidomain proteins where specific ABA-binding can cause biochemical and physiological changes. Here we show that the Arabidopsis thaliana K+ transporter AtKUP5 contains both a functional cytoplasmic N-terminal adenylate cyclase (AC) enabling the synthesis of 3,5-cAMP from ATP and a C-terminal phosphodiesterase (PDE) that hydrolyses 3,5-cAMP to 5-AMP. We found that ABA binds in a ligand-specific manner to the catalytic center of the PDE thereby causing a reduction of 3,5-cAMP hydrolysis in vitro. The hydrolytic activity of the PDE is ABA concentration-dependent, biphasic and requires the presence of an intact ABA-binding site similar to the one in the canonical Pyrabactin resistance 1/PYR-like/Abscisic acid receptors, with Vmax of 1.19 pmole min{square}1 g{square}1 in the absence of ABA, increasing to 1.58 pmole min{square}1 g{square}1 at 2 nM ABA, and decreasing to 0.75 pmole min{square}1 g{square}1 at 50 nM ABA. These findings are therefore consistent with a direct role of ABA in PDE activity modulations and form a functional link between 3,5-cAMP signaling and K+ flux. Furthermore, we predict that a growing number of such receptor-like proteins that specifically and directly interact with ABA will be discovered thereby uncovering complex and ancient layers of signaling and metabolic regulation.

plant biology↗

bioRxiv2024

TXNIP mediates LAT1/SLC7A5 endocytosis to reduce amino acid uptake in cells entering quiescence

Entry and exit from cellular quiescence require dynamic adjustments in nutrient acquisition, yet the mechanisms by which quiescent cells downregulate amino acid (AA) transport remain poorly understood. Here, we demonstrate that cells entering quiescence select plasma membrane-resident AA transporters for endocytosis and lysosomal degradation, to match AA uptake with reduced translation. We identify the -arrestin TXNIP as a key regulator of AA uptake during quiescence, since it mediates the endocytosis of the SLC7A5-SLC3A2 (LAT1-4F2hc) transporter complex in response to reduced AKT signaling. Mechanistically, TXNIP interacts with HECT-type ubiquitin ligases to facilitate transporter ubiquitination. Loss of TXNIP disrupts this regulation, resulting in dysregulated AA uptake, sustained mTORC1 signaling, and accelerated quiescence exit. A novel TXNIP loss-of-function mutation in a patient with severe metabolic disease further supports its role in nutrient homeostasis and human health. These findings highlight TXNIPs role in controlling SLC7A5-SLC3A2 mediated AA acquisition with implications for quiescence biology and disease.

cell biology↗

bioRxiv2024

GEMCAT - A new algorithm for gene expression-based prediction of metabolic alterations

The conclusive interpretation of multi-omics datasets obtained from high throughput approaches is an important prerequisite to understand disease-related physiological changes and to predict biomarkers in body fluids. We here present a Gene Expression-based Metabolite Centrality Analysis Tool, GEMCAT, a new genome scale metabolic modelling algorithm. GEMCAT enables integration of transcriptomics or proteomics data to predict changes in metabolite concentrations which can be verified by targeted metabolomics. In addition, GEMCAT allows to trace measured and predicted metabolic changes back to the underlying alterations in gene expression or proteomics and thus enables functional interpretation and integration of multi-omics data. We demonstrate the predictive capacity of GEMCAT on two datasets, one using RNA sequencing data and metabolomics from an engineered human cell line with a functional deletion of the mitochondrial NAD-transporter and another using proteomics and metabolomics measurements from patients with inflammatory bowel disease.

bioinformatics↗

bioRxiv2024

Automated liquid handling extraction and rapid quantification of underivatized amino acids and tryptophan metabolites from human serum and plasma using dual-column U(H)PLC-MRM-MS and its application to prostate cancer study.

Free amino acids (AAs) and their metabolites are important building blocks, energy sources and signaling molecules associated with various pathological phenotypes. The quantification of AA and tryptophan (TRP) metabolites in human serum and plasma is therefore of great diagnostic interest. Robust and reproducible sample extraction and processing workflows as well as rapid, sensitive absolute quantification of AA and TRP metabolites are required to identify candidate biomarkers and to improve current screening methods. We developed a validated semi-automated extraction and sample processing workflow using a robotic liquid handling platform and a rapid method for the absolute quantification of 20 free, underivatized AAs and 6 TRP metabolites using dual-column U(H)PLC-MRM-MS. The automated extraction and sample preparation workflow is designed for use in a 96-well plate format, allowing robust and reproducible high sample throughput without the need for further SPE, evaporation and/or buffer exchange. Samples extracted from serum and/or plasma in 96-well plates can be transferred directly to the U(H)PLC autosampler. The dual-column U(H)PLC-MRM-MS method, using a mixed- mode reversed-phase anion exchange column with formic acid as mobile phase modifier and a high- strength silica reversed-phase column with difluoroacetic acid as mobile phase additive, provided absolute quantification with nanomolar lower limits of quantification (LLOQ) for all metabolites except glycine (LLOQ: 2.46 {micro}M) in only 7.9 minutes. The semi-automated extraction workflow and dual-column U(H)PLC-MRM-MS method was applied to a human prostate cancer study and was shown to discriminate between treatment regimens and to identify amino acids responsible for the statistical separation between healthy controls and prostate cancer patients on active surveillance.

biochemistry↗

bioRxiv2023

Guanylate cyclase activity of TIR1/AFB auxin receptorsin rapid auxin responses

The plant hormone auxin is perceived by TIR1/AFB receptors, which mediate transcriptional reprogramming via a ubiquitination- and cAMP-dependent mechanism. Same receptors mediate also rapid, non-transcriptional growth responses that are mechanistically less well understood. Here, we demonstrate that TIR1/AFB receptors possess not only adenylate cyclase but also guanylate cyclase activity. Auxin perception independently activates cAMP and cGMP production by TIR1/AFBs in vitro and elevates both cAMP and cGMP levels in planta. Genetic and synthetic biology approaches revealed that AFB1 guanylate cyclase activity is required for the rapid cytosolic Ca2+ transients and root growth inhibition. This unprecedented combination of adenylate and guanylate cyclase activities within a single hormone receptor establishes a new paradigm for how one perception mechanism can mediate distinct downstream responses. One-Sentence SummaryTIR1/AFB auxin receptors possess both, adenylate and guanylate cyclase activities, mediating transcriptional reprogramming and rapid Ca2+-dependent growth responses, respectively.

plant biology↗

bioRxiv2023

Tryptophan stress activates EGFR-RAS-signaling to MTORC1 and p38/MAPK to sustain translation and AHR-dependent autophagy

Tumours face tryptophan (Trp) depletion, but the mechanisms sustaining protein biosynthesis under Trp stress remain unclear. We report that Trp stress increases the levels of the translation repressor EIF4EBP1. Yet, at the same time, EIF4EBP1 is selectively phosphorylated by the metabolic master regulator MTORC1 kinase, preventing EIF4EBP1 from inhibiting translation. MTORC1 activity under Trp stress is unexpected because the absence of amino acids is typically linked with MTORC1 inhibition. EIF4EBP1-sensitive translation in Trp starved cells is sustained by EGFR and RAS signalling to MTORC1. Via this mechanism, Trp stress enhances the synthesis and activity of the aryl hydrocarbon receptor (AHR). This is noteworthy as Trp catabolites are known to activate AHR, and therefore Trp stress was previously considered to inhibit AHR. Trp stress-induced AHR enhances the expression of key regulators of autophagy, which sustains intracellular Trp levels and Trp-charged tRNAs for translation. Hence, Trp stress switches MTORC1 from its established inhibitory function into an enhancer of autophagy, acting through AHR. The clinical potential of this fundamental mechanism is highlighted by the activity of the mTORC1-AHR pathway and an autophagy signature in 20% of glioblastoma patients, opening up new avenues for cancer therapy.

biochemistry↗

bioRxiv2022

Proteome coverage after simultaneous proteo-metabolome liquid-liquid extraction

Proteo-metabolomics is essential in systems biology and simultaneous proteo-metabolome extraction by liquid-liquid extraction (SPM-LLE) allows extraction of the metabolome and proteome from the same sample. Since the proteome is present as a pellet in SPM-LLE it must be solubilized for quantitative proteomics. Solubilization and proteome extraction is a critical factor in the information that can be obtained at the proteome level. In this study, we investigated the performance of two surfactants (sodium deoxycholate (SDC), sodium dodecyl sulfate (SDS)) and urea with respect to proteome coverage and extraction efficiency of an interphase proteome pellet generated by methanol-chloroform based SPM-LLE. We also investigated the extent to which the performance differs when the proteome is extracted from the interphase pellet or by direct cell lysis. Our study reveals that the proteome coverages between the two surfactants and urea for the SPM-LLE interphase pellet were very similar, but the extraction efficiencies differed significantly. While SDS led to enrichment of basic proteins, which were mainly ribosomal and ribonuclear proteins, urea was the most efficient extraction agent for simultaneous proteo-metabolome analysis. The results of our study also show that the performance of surfactants (SDC, SDS) for quantitative proteomics is better when the proteome was extracted by direct cell lysis and not from an interphase pellet. In contrast, the performance of urea for quantitative proteomics was significantly better when the proteome was extracted from an interphase pellet and by direct cell lysis.

systems biology↗

bioRxiv2022

Comparative assessment of quantification methods for tumor tissue phosphoproteomics

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture) and TMT isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. TMT offered the lowest accuracy and the highest precision and robustness towards different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites, and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics.

biochemistry↗

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↗