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Biology subjects

Poschet, G.

Publications and source records attributed to Poschet, G..

13 recordsLinked to original sources

Rational scaffold design mitigates mitochondrial complex I off-target inhibition in bifunctional degraders

Chemical inducers of proximity have transformed small-molecule pharmacology, but the large, bifunctional architectures they often employ introduce new and poorly understood off-target risks. During a targeted protein degrader synthesis project, we identified a subset of compounds that cause rapid and unexpected ATP depletion in cells. Mechanistic studies traced this effect to inhibition of mitochondrial complex I, a central component of oxidative phosphorylation. This inhibition does not stem from off-target binding by either of the two target ligands, but from the overall long, linear architecture of the bifunctional molecules, which renders them effective ligands of the narrow ubiquinone binding tunnel of complex I. Strikingly, this liability extends to structurally unrelated bifunctional molecules, including six androgen receptor PROTACs including the clinical candidate ARV-110, which inhibits complex I at low nanomolar concentrations. To mitigate complex I inhibition, we established a generalizable design strategy to disrupt linear molecular geometry through the introduction of structural "bumps" or "kinks". In a proof-of-concept study, we successfully apply this strategy to the ARV-110 scaffold, discovering potent AR-degrading ARV-110 analogs that do not inhibit complex I. These findings uncover a previously underappreciated structural determinant of off-target mitochondrial toxicity and establish new design principles for safer proximity-inducing therapeutics.

cancer biology↗

WUSCHEL modulates jasmonate signaling to control the balance between growth and defense in the shoot apical meristem

The growth-defense trade-off is an essential survival strategy for plants under environmental stress. However, how this balance is maintained at the meristematic level remains unclear. Here, we show that wounding of rosette leaves systemically inhibits inflorescence stem growth, associated with reduced cell proliferation in the inner cell layers of the shoot apical meristem (SAM), but not in the apical stem cell domain. Mechanistically, this selective cell behavior is dependent on the interplay between the growth-repressing jasmonate (JA) signaling and the growth-promoting stem cell regulator WUSCHEL (WUS). WUS mitigates wounding-induced growth inhibition by repressing JA-responsive gene expression via promoting the accumulation of JASMONATE-ZIM DOMAIN 3 (JAZ3), which encodes a JA signaling repressor. WUS on the one hand induces JAZ3 mRNA accumulation and on the other hand directly competes with the JA receptor CORONATINE INSENSITIVE1 (COI1) for JAZ3 binding, thereby inhibiting JAZ3 protein degradation. Our findings identify a WUS-JAZ3-COI1 regulatory module that coordinates the growth-defense balance in the SAM upon systemic wounding, revealing a cell-type-specific mechanism for sustaining developmental robustness of the meristem during stress response.

plant biology↗

MetAlyzer to Perform Streamlined, Interactive, and Pathway-Mapping Analysis of Targeted Metabolomics Data from the biocrates Platform

Mass spectrometry (MS)-based metabolomics has emerged as a powerful tool to address multifaceted biological questions. Commercial solutions like the ones developed at biocrates allow reliable and quantitative targeted metabolic profiling, including the conversion of the raw MS spectra into absolute concentrations of metabolites. These results can be exported for further analysis under several formats with varying levels of human-vs. machine-readability. The default output format is an Excel spreadsheet that favours human readability and therefore requires extra preparation steps for downstream bioinformatic analysis and data exploration. To streamline this next step for users of this platform, we developed MetAlyzer, an R package (https://github.com/Lu-Group-UKHD/MetAlyzer) specifically designed to handle the spreadsheets generated by WebIDQ, the biocrates workflow manager software. MetAlyzer converts WebIDQ-generated spreadsheets into flexible SummarizedExperiment objects and provides functions for data preprocessing, statistical testing, and visualization of differential metabolites. To further support data exploration and hypothesis generation by users without coding experience, we also developed an interactive and intuitive Shiny app (https://metalyzer.shinyapps.io/MetAlyzer_ShinyApp/) that interfaces with MetAlyzers core functionality, enabling users to execute the complete analysis workflow without writing code. This combination can help scientists deepen their understanding of metabolomics results, supporting the broader adoption of metabolomics in the life sciences community.

bioinformatics↗

A metabolism-chromatin axis promotes ribosome heterogeneity in the human malaria parasite

The transmission of the most virulent human malaria parasite, Plasmodium falciparum, relies on its survival in the contrasting environments of the human host and mosquito vector. One of the most fascinating adaptations to this lifestyle is the specific silencing of individual rDNA genes in the human host that are de-repressed following host-to-vector transmission. In this study, we defined the epigenetic signatures of rRNA transcription and found that rDNA silencing relies on aerobic glycolysis, the sole energy-generating pathway in the human host. We show that disruption of NAD+ regeneration during lactate fermentation promotes rDNA de-repression and identify the sirtuin histone deacetylase Sir2a as the mediator between fluctuating NAD+ levels and a functional transcriptional outcome. Hence, rDNA activation appears to be coupled to the metabolic state of the parasite as it transitions from aerobic glycolysis to mitochondrial respiration during host-to-vector transmission.

microbiology↗

Interlaboratory comparison of standardised metabolomics and lipidomics analyses in human and rodent blood using the MxP(R) Quant 500 kit

Metabolomics and lipidomics are pivotal in understanding phenotypic variations beyond genomics. However, quantification and comparability of mass spectrometry (MS)-derived data are challenging. Standardised assays can enhance data comparability, enabling applications in multi-center epidemiological and clinical studies. Here we evaluated the performance and reproducibility of the MxP(R) Quant 500 kit across 14 laboratories. The kit allows quantification of 634 different metabolites from 26 compound classes using triple quadrupole MS. Each laboratory analysed twelve samples, including human plasma and serum, lipaemic plasma, NIST SRM 1950, and mouse and rat plasma, in triplicates. 505 out of the 634 metabolites were measurable above the limit of detection in all laboratories, while eight metabolites were undetectable in our study. Out of the 505 metabolites, 412 were observed in both human and rodent samples. Overall, the kit exhibited high reproducibility with a median coefficient of variation (CV) of 14.3 %. CVs in NIST SRM 1950 reference plasma were below 25 % and 10 % for 494 and 138 metabolites, respectively. To facilitate further inspection of reproducibility for any compound, we provide detailed results from the in-depth evaluation of reproducibility across concentration ranges using Deming regression. Interlaboratory reproducibility was similar across sample types, with some species-, matrix-, and phenotype-specific differences due to variations in concentration ranges. Comparisons with previous studies on the performance of MS-based kits (including the AbsoluteIDQ p180 and the Lipidyzer) revealed good concordance of reproducibility results and measured absolute concentrations in NIST SRM 1950 for most metabolites, making the MxP(R) Quant 500 kit a relevant tool to apply metabolomics and lipidomics in multi-center studies.

biochemistry↗

A single-sample workflow for joint metabolomic and proteomic analysis of clinical specimens

Understanding the interplay of the proteome and the metabolome aids in understanding cellular phenotypes. To enable more robust inferences from such multi-omics analyses, combining proteomic and metabolomic datasets from the same sample provides major benefits by reducing technical variation between extracts during the pre-analytical phase, decreasing sample variation due to varying cellular content between aliquots, and limiting the required sample amount. We evaluated the advantages, practicality and feasibility of a single-sample workflow for combined proteome and metabolome analysis. In the workflow, termed MTBE-SP3, we combined a fully automated protein lysis and extraction protocol (autoSP3) with a semi-automated biphasic 75% EtOH/MTBE extraction for quantification of polar/non-polar metabolites. Additionally, we compared the resulting proteome of various biological matrices (FFPE tissue, fresh-frozen tissue, plasma, serum and cells) between autoSP3 and MTBE-SP3. Our analysis revealed that the single-sample workflow provided similar results to those obtained from autoSP3 alone, with an 85-98% overlap of proteins detected across the different biological matrices. Additionally, it provides distinct advantages by decreasing (tissue) heterogeneity by retrieving metabolomics and proteomic data from the identical biological material, and limiting the total amount of required material. Lastly, we applied MTBE-SP3 to a lung adenocarcinoma cohort of 10 patients. Integrating the metabolic and proteomic alterations between tumour and non-tumour adjacent tissue yielded consistent data independent of the method used. This revealed mitochondrial dysfunction in tumor tissue through deregulation of OGDH, SDH family enzymes and PKM. In summary, MTBE-SP3 enables the facile and confident parallel measurement of proteins and metabolites obtained from the same sample. This workflow is particularly applicable for studies with limited sample availability and offers the potential to enhance the integration of metabolomic and proteomic datasets.

cancer biology↗

Altered iron-sulfur cluster transfer in Arabidopsis mitochondria reveals lipoyl synthase as a Janus-faced enzyme that generates toxic sulfide

Iron-sulfur (Fe-S) cluster are vital cofactors in all domains of life. Mitochondrial Fe-S cluster assembly occurs in two major steps to first build [2Fe-2S] clusters and subsequently assemble these into [4Fe-4S] clusters. The two assembly machineries are interconnected by glutaredoxin S15 (GRXS15) that transfers [2Fe-2S] clusters to the second machinery. Diminished cluster transfer activity of GRXS15 in Arabidopsis mitochondria causes specific defects associated with lipoyl synthase (LIP1) activity. Conversely, overexpression of LIP1 in wild-type plants causes the release of toxic amounts of sulfide that can be detoxified by increasing the capacity for sulfide fixation through overexpression of O-acetylserine-(thiol)-lyase. The release of sulfide by lipoyl synthase causes a disturbance of mitochondrial sulfide homeostasis resulting in distinct and readily observable macroscopic phenotypes. These phenotypes enable a direct readout of consequences resulting from defects in Fe-S cluster assembly or targeted modulation of Fe-S cluster flux in mitochondria.

plant biology↗

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis

Metabolomic and proteomic analyses of human plasma and serum samples harbour the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implement a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4{degrees}C) are imperative for metabolic profiling, the analysed proteome showed variability when exposed to temperatures of 4{degrees}C for more than 2 hours, highlighting the need for compromises in a combined analysis. We formalised a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonised standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies we suggest to keep blood samples up to 2 hours on ice (4{degrees}C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open source R package allowing the systematic scoring of proteomics and metabolomics datasets to assess the stability of plasma and serum samples.

biochemistry↗

Deep metabolic profiling assessment of tissue extraction protocols for three model organisms

Metabolic profiling harbors the potential to better understand various disease entities such as cancer, diabetes, Alzheimers, Parkinsons disease or COVID-19. Deciphering these intricate pathways in human studies requires large sample sizes as a means of reducing variability. While such broad human studies have discovered new associations between a given disease and certain affected metabolites, i.e. biomarkers, they often provide limited functional insights. To design more standardized experiments, reduce variability in the measurements and better resolve the functional component of such dynamic metabolic profiles, model organisms are frequently used. Standardized rearing conditions and uniform sampling strategies are prerequisites towards a successful metabolomic study. However, further aspects such as the choice of extraction protocol and analytical technique can influence the outcome drastically. Here, we employed a highly standardized metabolic profiling assay analyzing 630 metabolites across three commonly used model organisms (Drosophila, mouse and Zebrafish) to find the optimal extraction protocols for various matrices. Focusing on parameters such as metabolite coverage, metabolite yield and variance between replicates we compared seven extraction protocols. We found that the application of a combination of 75% ethanol and methyl tertiary-butyl ether (MTBE), while not producing the broadest coverage and highest yields, was the most reproducible extraction protocol. We were able to determine up to 530 metabolites in mouse kidney samples, 509 in mouse liver, 422 in Zebrafish and 388 in Drosophila and discovered a core overlap of 261 metabolites in these four matrices. To enable other scientists to search for the most suitable extraction protocol in their experimental context and interact with this comprehensive data, we have integrated our data set in the open-source shiny app "MetaboExtract". This will enable scientists to search for their metabolite or metabolite class of interest, compare it across the different tested extraction protocols and sample types as well as find reference concentrations.

biochemistry↗

Comparison of extraction methods for intracellular metabolomics

Measurements of metabolic compounds inside cells or tissues are of high informative potential since they represent the endpoint of biological information flow and a snapshot of the integration of many regulatory processes. However, it requires careful extraction to quantify their abundance. Here we present a comprehensive study using ten extraction protocols on four human sample types (liver tissue, bone marrow, HL60 and HEK cells) targeting 630 metabolites of different chemical classes. We show that the extraction efficiency and stability is highly variable across protocols and tissues by using different quality metrics including the limit of detection and variability between replicates as well as the sum of concentration as a global estimate of extraction stability. The profile of extracted metabolites depends on the used solvents - an observation which has implications for measurements of different sample types and metabolic compounds of interest. To identify the optimal extraction method for future metabolomics studies, the benchmark dataset was implemented in an easy-to-use, interactive and flexible online resource (R/shiny app MetaboExtract).

biochemistry↗

MYCN mediates cysteine addiction and sensitizes to ferroptosis

Aberrant expression of MYC family members predicts poor clinical outcome in many human cancers. Oncogenic MYC profoundly alters metabolism and mediates an antioxidant response to maintain redox balance. Here we show that MYC induces massive lipid peroxidation upon depletion of cysteine, the rate-limiting amino acid for glutathione biosynthesis and sensitizes cells to ferroptosis, an oxidative, non-apoptotic and irondependent type of cell death. In MYCN-amplified childhood neuroblastoma, MYCN mediates resistance to ferroptosis by activating transsulfuration of methionine to cysteine. MYCN may contribute to spontaneous tumor regression in low-risk neuroblastomas by promoting ferroptosis in cells with epigenetically silenced cystathionine-beta-synthase, the rate-limiting enzyme for transsulfuration. We identified enzymes and antiporter proteins crucial to ferroptotic escape, providing multiple previously unknown sites that may be acted on therapeutically.

cancer biology↗

Branched-chain amino acid catabolism depends on GRXS15 through mitochondrial lipoyl cofactor homeostasis

Iron-sulfur (Fe-S) clusters are ubiquitous cofactors in all life and are used in a wide array of diverse biological processes, including electron transfer chains and several metabolic pathways. Biosynthesis machineries for Fe-S clusters exist in plastids, the cytosol and mitochondria. A single monothiol glutaredoxin (GRX) has been shown to be involved in Fe-S cluster assembly in mitochondria of yeast and mammals. In plants, the role of the mitochondrial homologue GRXS15 has only partially been characterized. Arabidopsis grxs15 null mutants are not viable, but mutants complemented with the variant GRXS15 K83A develop with a dwarf phenotype. In an in-depth metabolic analysis, we show that most Fe-S cluster-dependent processes are not affected, including biotin biosynthesis, molybdenum cofactor biosynthesis and the electron transport chain. Instead, we observed an increase in most TCA cycle intermediates and amino acids, especially pyruvate, 2-oxoglutarate, glycine and branched-chain amino acids (BCAAs). The most pronounced accumulation occurred in branched-chain -keto acids (BCKAs), the first degradation products resulting from deamination of BCAAs. In wild-type plants, pyruvate, 2-oxoglutarate, glycine and BCKAs are all metabolized through decarboxylation by four mitochondrial lipoyl cofactor-dependent dehydrogenase complexes. Because these enzyme complexes are very abundant and the biosynthesis of the lipoyl cofactor depends on continuous Fe-S cluster supply to lipoyl synthase, this could explain why lipoyl cofactor-dependent processes are most sensitive to restricted Fe-S supply in GRXS15 K83A mutants. One-sentence summaryDeficiency in GRXS15 restricts protein lipoylation and causes metabolic defects in lipoyl cofactor-dependent dehydrogenase complexes, with branched-chain amino acid catabolism as dominant bottleneck.

plant biology↗

Redox-mediated Kick-Start of Mitochondrial Energy Metabolism drives Resource-efficient Seed Germination

Seeds preserve a far developed plant embryo in a quiescent state. Seed metabolism relies on stored resources and is re-activated to drive germination when the external conditions are favorable. Since the switchover from quiescence to re-activation provides a remarkable case of a cell physiological transition we investigated the earliest events in energy and redox metabolism of Arabidopsis seeds at imbibition. By developing fluorescent protein biosensing in intact seeds, we observed ATP accumulation and oxygen uptake within minutes, indicating rapid activation of mitochondrial respiration, which coincided with a sharp transition from an oxidizing to a more reducing thiol redox environment in the mitochondrial matrix. To identify individual operational protein thiol switches, we captured the fast release of metabolic quiescence in organello and devised quantitative iodoacetyl tandem mass tag-based (iodoTMT) thiol redox proteomics. The redox state across all Cys-peptides was shifted towards reduction from 27.1 % to 13.0 %. A large number of Cys-peptides (412) were redox-switched, representing central pathways of mitochondrial energy metabolism, including the respiratory chain and each enzymatic step of the tricarboxylic acid cycle (TCA). Active site Cys-peptides of glutathione reductase 2, NADPH-thioredoxin reductase a/b and thioredoxin-o1 showed the strongest responses. Germination of seeds lacking those redox proteins was associated with markedly enhanced respiration and deregulated TCA cycle dynamics suggesting decreased resource efficiency of energy metabolism. Germination in aged seeds was strongly impaired. We identify a global operation of thiol redox switches that is required for optimal usage of energy stores by the mitochondria to drive efficient germination.

plant biology↗