Biology subjects

Richter, S.

Publications and source records attributed to Richter, S..

30 records · Page 2Linked to original sources

bioRxiv2022

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. Single sentence summaryWe performed the largest proteogenomic analysis of CLL, linked proteomic profiles to clinical outcomes, and discovered a new poor outcome subgroup (ASB-CLL).

cancer biology↗

bioRxiv2021

Heterodimers of functionally divergent ARF-GEF paralogues prevented by self-interacting dimerisation domain

Functionally divergent paralogs of homomeric proteins do not form potentially deleterious heteromers, which requires distinction between self and non-self (Hochberg et al., 2018; Marchant et al, 2019; Marsh and Teichmann, 2015). In Arabidopsis, two ARF guanine-nucleotide exchange factors (ARF-GEFs) related to mammalian GBF1, named GNOM and GNL1, can mediate coatomer complex (COPI)-coated vesicle formation in retrograde Golgi-endoplasmic reticulum (ER) traffic (Geldner et al., 2003; Richter et al., 2007; Teh and Moore, 2007). Unlike GNL1, however, GNOM is also required for polar recycling of endocytosed auxin efflux regulator PIN1 from endosomes to the plasma membrane. Here we show that these paralogues form homodimers constitutively but no heterodimers. We also address why and how GNOM and GNL1 might be kept separate. These paralogues share a common domain organisation and each N-terminal dimerisation (DCB) domain can interact with the complementary fragment ({Delta}DCB) of its own and the other protein. However, unlike self-interacting DCBGNOM (Grebe et al., 2000; Anders et al., 2008), DCBGNL1 did not interact with itself nor DCBGNOM. DCBGNOM removal or replacement with DCBGNL1, but not disruption of cysteine bridges that stabilise DCB-DCB interaction, resulted in GNOM-GNL1 heterodimers which impaired developmental processes such as lateral root formation. We propose precocious self-interaction of the DCBGNOM domain as a mechanism to preclude formation of fitness-reducing GNOM-GNL1 heterodimers.

plant biology↗

bioRxiv2021

Biologging of emperor penguins - attachment techniques and associated deployment performance

An increasing number of marine animals are equipped with biologgers, to study their physiology, behaviour and ecology, often for conservation purposes. To minimise the impacts of biologgers on the animals welfare, the Refinement principle from the Three Rs framework (Replacement, Reduction, Refinement) urges to continuously test and evaluate new and updated biologging protocols. Here, we propose alternative and promising techniques for emperor penguin (Aptenodytes forsteri) capture and on-site logger deployment that aim to mitigate the potential negative impacts of logger deployment on these birds. We equipped adult emperor penguins for short-term (GPS, Time-Depth Recorder (TDR)) and long-term (i.e. planned for one year) deployments (ARGOS platforms, TDR), as well as juvenile emperor penguins for long-term deployments (ARGOS platforms) in the Weddell Sea area where they had not yet been studied. We describe and qualitatively evaluate our protocols for the attachment of biologgers on-site at the colony, the capture of the animals and the recovery of the devices after deployment. We report unprecedented recaptures of long-term equipped adult emperor penguins (50% of equipped individuals recaptured after 290 days). Our data demonstrate that the traditional technique of long-term attachment by gluing the biologgers directly to the back feathers is detrimental to the birds. It causes excessive feather breakage and the loss of the devices at an early stage. We therefore propose an alternative method of attachment for back-mounted devices. This technique led to successful year-round deployments on 37.5% of the equipped juveniles. Finally, we also disclose the first deployments of leg-bracelet mounted TDRs on emperor penguins. Our findings highlight the importance of monitoring potential impacts of biologger deployments on the animals and the need to remain critical towards established and new protocols.

ecology↗

bioRxiv2021

Squidpy: a scalable framework for spatial single cell analysis

Spatial omics data are advancing the study of tissue organization and cellular communication at an unprecedented scale. Here, we present Squidpy, a Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or multivariate proteins. Squidpy provides both infrastructure and numerous analysis methods that allow to efficiently store, manipulate and interactively visualize spatial omics data.

bioinformatics↗

bioRxiv2021

GLS-driven glutamine catabolism contributes to prostate cancer radiosensitivity by regulating the redox state, stemness and ATG5-mediated autophagy

Radiotherapy is one of the curative treatment options for localized prostate cancer (PCa). The curative potential of radiotherapy is mediated by irradiation-induced oxidative stress and DNA damage in tumor cells. However, PCa radiocurability can be impeded by tumor resistance mechanisms and normal tissue toxicity. Metabolic reprogramming is one of the major hallmarks of tumor progression and therapy resistance. Here, we found that radioresistant PCa cells and prostate cancer stem cells (CSCs) have a high glutamine demand. Glutaminase (GLS)-driven catabolism of glutamine serves not only for energy production but also for the maintenance of the redox state. Consequently, glutamine depletion or inhibition of critical regulators of glutamine utilization, such as glutaminase (GLS) and the transcription factor MYC results in PCa radiosensitization. On the contrary, we found that a combination of glutamine metabolism inhibitors with irradiation does not cause toxic effects on nonmalignant prostate cells. Glutamine catabolism contributes to the maintenance of CSCs through regulation of the alpha-ketoglutarate (-KG)-dependent chromatin-modifying dioxygenase. The lack of glutamine results in the inhibition of CSCs with a high aldehyde dehydrogenase (ALDH) activity, decreases the frequency of the CSC populations in vivo and reduces tumor formation in xenograft mouse models. Moreover, this study shows that activation of the ATG5-mediated autophagy in response to a lack of glutamine is a tumor survival strategy to withstand radiation-mediated cell damage. In combination with autophagy inhibition, the blockade of glutamine metabolism might be a promising strategy for PCa radiosensitization. High blood levels of glutamine in PCa patients significantly correlate with a shorter prostate-specific antigen (PSA) doubling time. Furthermore, high expression of critical regulators of glutamine metabolism, GLS1 and MYC, is significantly associated with a decreased progression-free survival in PCa patients treated with radiotherapy. Our findings demonstrate that GLS-driven glutaminolysis is a prognostic biomarker and therapeutic target for PCa radiosensitization.

cancer biology↗

bioRxiv2020

Ultra-high sensitivity mass spectrometry quantifies single-cell proteome changes upon perturbation

Single-cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing1-3. However, proteins are the main drivers of cellular function and in-depth characterization of individual cells by mass spectrometry (MS)-based proteomics would thus be highly valuable and complementary4,5. Chemical labeling-based single-cell approaches introduce hundreds of cells into the MS, but direct analysis of single cells has not yet reached the necessary sensitivity, robustness and quantitative accuracy to answer biological questions6,7. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow-rate chromatography and a novel trapped ion mobility mass spectrometer, resulting in a more than ten-fold improved sensitivity. We accurately and robustly quantify proteomes and their changes in single, FACS-isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators such as CDK2NA, the E2 ubiquitin ligase UBE2S, DNA topoisomerases TOP2A/B and the chromatin regulator HMGA1. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single-cell proteomes to transcriptome data revealed a stable core proteome despite perturbation, while the transcriptome appears volatile. This emphasizes substantial regulation of translation and sets the stage for its elucidation at the single cell level. Our technology can readily be applied to ultra-high sensitivity analyses of tissue material8, posttranslational modifications and small molecule studies to gain unprecedented insights into cellular heterogeneity in health and disease.

systems biology↗

bioRxiv2020

ARF1 dimerization is essential for vesicle trafficking and dependent on activation by ARF-GEF dimers in Arabidopsis

Membrane traffic maintains the organization of the eukaryotic cell and delivers cargo proteins to their subcellular destinations such as sites of action or degradation. Membrane vesicle formation requires ARF GTPase activation by the SEC7 domain of ARF guanine-nucleotide exchange factors (ARF-GEFs), resulting in the recruitment of coat proteins by GTP-bound ARFs. In vitro exchange assays were done with monomeric proteins, although ARF-GEFs have been shown to form dimers in vivo. This feature is conserved across the eukaryotes, however its biological significance is unknown. Here we demonstrate ARF1 dimerization in vivo and we show that ARF-GEF dimers mediate ARF1 dimer formation. Mutational disruption of ARF1 dimers interfered with ARF1-dependent trafficking but not coat protein recruitment in Arabidopsis. Mutations disrupting simultaneous binding of two ARF1*GDPs by the two SEC7 domains of GNOM ARF-GEF dimer prevented stable interaction of ARF1 with ARF-GEF and thus, efficient ARF1 activation. Our results suggest a model of activation-dependent dimerization of membrane-inserted ARF1*GTP molecules required for coated membrane vesicle formation. Considering the evolutionary conservation of ARFs and ARF-GEFs, this initial regulatory step of membrane trafficking might well occur in eukaryotes in general.

plant biology↗

bioRxiv2019

Efficient data management infrastructure for the integration of imaging and omics data in life science research

As technical developments in omics and biomedical imaging drive the increase in quality, modality, and throughput of data generation in life sciences, the need for information systems capable of integrative, long-term storage and management of these heterogeneous digital assets is also increasing. Here, we propose an approach based on principles of Service Oriented Architecture design, to allow the integrated management and analysis of multi-omics and biomedical imaging data. The proposed architecture introduces an interoperable image management system, the OMERO server, into the backend of qPortal, a FAIR-compliant web-based platform for omics data management. The implementation of an integrated metadata model, the development of software components to enable the communication with the OMERO server, and an extension to the data management operations of established software, allows for FAIR management of heterogeneous omics and biomedical imaging data within an integrated system, which facilitates metadata queries from web-based scientific applications. The applicability of the proposed architecture is demonstrated in two prototypical use cases, a plant biology study using confocal scanning microscopy, and a clinical study on hepatocellular carcinoma, with data from a variety of medical imaging and omics modalities. We anticipate that FAIR data management systems for multi-modal data repositories will play a pivotal role in data-driven research, as the joint analysis of omics and imaging data becomes not only desirable but necessary to derive novel insights into biological processes. In particular for powerful machine learning applications where the availability of large datasets with high quality phenotypic annotations is a requirement.

bioinformatics↗

bioRxiv2019

Druggability Assessment in TRAPP using Machine Learning Approaches

Accurate protein druggability predictions are important for the selection of drug targets in the early stages of drug discovery. Due to the flexible nature of proteins, the druggability of a binding pocket may vary due to conformational changes. We have therefore developed two statistical models, a logistic regression model (TRAPP-LR) and a convolutional neural network model (TRAPP-CNN), for predicting druggability and how it varies with changes in the spatial and physicochemical properties of a binding pocket. These models are integrated into TRAPP (TRAnsient Pockets in Proteins), a tool for the analysis of binding pocket variations along a protein motion trajectory. The models, which were trained on publicly available and self-augmented data sets, show equivalent or superior performance to existing methods on test sets of protein crystal structures, and have sufficient sensitivity to identify potentially druggable protein conformations in trajectories from molecular dynamics simulations. Visualization of the evidence for the decisions of the models in TRAPP facilitates identification of the factors affecting the druggability of protein binding pockets.

bioinformatics↗

bioRxiv2019

Cryopreservation impairs cytotoxicity and migration of NK cells in 3-D tissue: Implications for cancer immunotherapy

Natural killer (NK) cells are important effector cells in the immune response to cancer. Clinical trials on adoptively transferred NK cells in patients with solid tumors, however, have thus far been unsuccessful. As NK cells need to pass stringent safety evaluation for clinical use, the cells are cryopreserved to bridge the necessary evaluation time. While a degranulation assay confirms the ability of cryopreserved NK cells to kill target cells, we find a significant decrease of cytotoxicity after cryopreservation in a chromium release assay. We complement these standard assays with measurements of NK cell motility and cytotoxicity in 3-dimensional (3-D) collagen gels that serve as a substitute for connective tissue. We find a 5.6 fold decrease of cytotoxicity after cryopreservation and establish that this is mainly caused by a 6-fold decrease in the fraction of motile NK cells. These findings may explain the persistent failure of NK cell therapy in patients with solid tumors and highlight the crucial role of a 3-D environment for testing NK cell function.\n\nSynopsisCryopreservation of natural killer (NK) cells dramatically impairs their motility and cytotoxicity in tissue. This finding may explain the persistent failure of clinical trials in which NK cell therapy is used for treating solid tumors.

immunology↗

bioRxiv2018

G-quadruplex forming sequences in the genome of all known human viruses: a comprehensive guide

G-quadruplexes are non-canonical nucleic acid structures that control transcription, replication, and recombination in organisms. G-quadruplexes are present in eukaryotes, prokaryotes, and viruses. In the latter, mounting evidence indicates their key biological activity. Since data on viruses are scattered, we here present a comprehensive analysis of putative G-quadruplexes in the genome of all known viruses that can infect humans. We show that the presence, distribution, and location of G-quadruplexes are features characteristic of each virus class and family. Our statistical analysis proves that their presence within the viral genome is orderly arranged, as indicated by the possibility to correctly assign up to two-thirds of viruses to their exact class based on the G-quadruplex classification. For each virus we provide: i) the list of all G-quadruplexes formed by GG-, GGG- and GGGG-islands present in the genome (positive and negative strands), ii) their position in the viral genome along with the known function of that region, iii) the degree of conservation among strains of each G-quadruplex in its genome context, iv) the statistical significance of G-quadruplex formation. This information is accessible from a database (http://www.medcomp.medicina.unipd.it/main_site/doku.php?id=g4virus) to allow the easy and interactive navigation of the results. The availability of these data will greatly expedite research on G-quadruplex in viruses, with the possibility to accelerate finding therapeutic opportunities to numerous and some fearsome human diseases.

bioinformatics↗

bioRxiv2018

Infections patterns and fitness effects of Rickettsia and Sodalis symbionts in the green lacewing Chrysoperla carnea

Endosymbionts are wide-spread among insects and can play an essential role in host ecology. The common green lacewing (Chrysoperla carnea s. str.) is a neuropteran insect species which is widely used as a biological pest control. We screened for endosymbionts in natural and laboratory populations of the green lacewing using diagnostic PCR amplicons. We found the endosymbiont Rickettsia to be very common in all screened populations, whereas a so far uncharacterized Sodalis strain was solely found in laboratory populations. The new Sodalis strain was characterized using a whole genome shotgun approach. Its draft genome revealed an approximate genome size of 4.3 Mbp and the presence of 5213 coding sequences. Phylogenomic analyses indicated that this bacterium is the sister taxon of S. praecaptivus. In an experimental approach, we found a negative impact of Sodalis on the reproduction success of the green lacewing. Co-infections with Rickettsia and Sodalis caused an even higher decrease of reproductive success than single Sodalis infections. In contrast, no significant fitness differences were found in Rickettsia infected green lacewings compared to uninfected lacewings. The Rickettsia/Sodalis/Ch. carnea system presents a promising model to study evolutionary endosymbiont-host interactions in Neuroptera and endosymbiont-endosymbiont interactions in general. The economic and ecological importance of green lacewings in biological pest control warrants a more profound understanding of its biology, which might be strongly influenced by symbionts.

evolutionary biology↗