Buchmann Institut für Molekulare Lebenswissenschaften (BMLS)
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In bioengineering, scaffold proteins have been increasingly used to recruit molecules to parts of a cell, or to enhance the efficacy of biosynthetic or signalling pathways. For example, scaffolds can be used to make weak or non-immunogenic small molecules immunogenic by attaching them to the scaffold, in this role called carrier. Here, we present the dodecin from Mycobacterium tuberculosis (mtDod) as a new scaffold protein. MtDod is a homododecameric complex of spherical shape, high stability and robust assembly, which allows the attachment of cargo at its surface. We show that mtDod, either directly loaded with cargo or equipped with domains for non-covalent and covalent loading of cargo, can be produced recombinantly in high quantity and quality in Escherichia coli. Fusions of mtDod with proteins of up to four times the size of mtDod, e.g. with monomeric superfolder green fluorescent protein creating a 437 kDa large dodecamer, were successfully purified, showing mtDod’s ability to function as recruitment hub. Further, mtDod equipped with SYNZIP and SpyCatcher domains for post-translational recruitment of cargo was prepared of which the mtDod/SpyCatcher system proved to be particularly useful. In a case study, we finally show that mtDod-peptide fusions allow producing antibodies against human heat shock proteins and the C-terminus of heat shock cognate 70 interacting protein (CHIP).
The Corona pandemic has painfully taught us the threat of new pathogens in a globalized world and how vital modern vaccines are. Platform technologies play an important role in the discovery of new vaccines as reducing the time for the development dramatically — time that saves lives. Here, we present the protein Dodecin and how it may be utilized as a versatile platform technology to produce cheap and robust new vaccines for everyone in all parts of the world.
DIE ARCHITEKTUR DER ZELLE : Wie sehen die Bausteine des Lebens genau aus, wie interagieren die zellulären Akteure miteinander? Im Rahmen der Exzellenzcluster-Initiative SCALE (Subcellular Architecture of Life) wollen Frankfurter Wissenschaftlerinnen und Wissenschaftler diesen wichtigen Fragen nachgehen. Das Projekt ist interdisziplinär: Mehrere Forschungsgruppen, deren Schwerpunkt Biophysik ist, arbeiten zusammen. Der Biophysiker Achilleas Frangakis und die Bioinformatikerin Kathi Zarnack sind auch dabei. Sie verfolgen im Rahmen des Projekts große Ziele.
Background: The technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language—quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data.
Results: QuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data.
Conclusions: The presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.
The FUBP1-FUSE complex is an essential component of a transcription molecular machinery that is necessary for tight regulation of expression of many key genes including c-Myc and p21. FUBP1 utilizes its four articulated KH modules, which function cooperatively, for FUSE nucleotide binding. To understand molecular mechanisms fundamental to the intermolecular interaction, we present a set of crystal structures, as well ssDNA-binding characterization of FUBP1 KH domains. All KH1-4 motifs were highly topologically conserved, and were able to interact with FUSE individually and independently. Nevertheless, differences in nucleotide binding properties among the four KH domains were evident, including higher nucleotide-binding potency for KH3 as well as diverse nucleotide sequence preferences. Variations in amino acid compositions at one side of the binding cleft responsible for nucleobase resulted in diverse shapes and electrostatic charge interaction, which might feasibly be a contributing factor for different nucleotide-binding propensities among KH1-4. Nonetheless, conservation of structure and nucleotide-binding property in all four KH motifs is essential for the cooperativity of multi KH modules present in FUBP1 towards nanomolar affinity for FUSE interaction. Comprehensive structural comparison and ssDNA binding characteristics of all four KH domains presented here provide molecular insights at a fundamental level that might be beneficial for elucidating the mechanisms of the FUBP1-FUSE interaction.
Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still pose a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.
Publicly available compound and bioactivity databases provide an essential basis for data-driven applications in life-science research and drug design. By analyzing several bioactivity repositories, we discovered differences in compound and target coverage advocating the combined use of data from multiple sources. Using data from ChEMBL, PubChem, IUPHAR/BPS, BindingDB, and Probes & Drugs, we assembled a consensus dataset focusing on small molecules with bioactivity on human macromolecular targets. This allowed an improved coverage of compound space and targets, and an automated comparison and curation of structural and bioactivity data to reveal potentially erroneous entries and increase confidence. The consensus dataset comprised of more than 1.1 million compounds with over 10.9 million bioactivity data points with annotations on assay type and bioactivity confidence, providing a useful ensemble for computational applications in drug design and chemogenomics.
Of the 16 non-structural proteins (Nsps) encoded by SARS CoV-2, Nsp3 is the largest and plays important roles in the viral life cycle. Being a large, multidomain, transmembrane protein, Nsp3 has been the most challenging Nsp to characterize. Encoded within Nsp3 is the papain-like protease PLpro domain that cleaves not only the viral protein but also polyubiquitin and the ubiquitin-like modifier ISG15 from host cells. We here compare the interactors of PLpro and Nsp3 and find a largely overlapping interactome. Intriguingly, we find that near full length Nsp3 is a more active protease compared to the minimal catalytic domain of PLpro. Using a MALDI-TOF based assay, we screen 1971 approved clinical compounds and identify five compounds that inhibit PLpro with IC50s in the low micromolar range but showed cross reactivity with other human deubiquitinases and had no significant antiviral activity in cellular SARS-CoV-2 infection assays. We therefore looked for alternative methods to block PLpro activity and engineered competitive nanobodies that bind to PLpro at the substrate binding site with nanomolar affinity thus inhibiting the enzyme. Our work highlights the importance of studying Nsp3 and provides tools and valuable insights to investigate Nsp3 biology during the viral infection cycle.
The impact of the appropriate and inappropriately applied statistical metrics to verify the State of Control of pharmaceutical manufacturing has been reviewed from an auditor’s perspective. Good and bad statistical practices have been presented in an attempt for manufactures to appreciate the risks of using these metrics. Conclusions concerning (1) control charts to be used instead of line/run charts for trend analysis, (2) Ppk as the preferred capability index (but still with an ambition to get processes into statistical control), (3) show process capability indices along with their respective control charts (4) determine which Manufacturing State of Control the product/process lies in (5) an effective Control Strategy can only be implemented if the Manufacturing State of Control is understood, (6) when presenting data consider what is truly representative of the product/process and not the average (7) Management should align with ICH Q10 more effectively to provide statistical resources for their personnel.
Cryo-electron tomography is the only technique that can provide sub-nanometer resolved images of cell regions or even whole cells, without the need of labeling or staining methods. Technological advances over the past decade in electron microscope stability, cameras, stage precision and software have resulted in faster acquisition speeds and considerably improved resolution. In pursuit of even better image resolution, researchers seek to reduce noise – a crucial factor affecting the reliability of the tomogram interpretation and ultimately limiting the achieved resolution. Sub-tomogram averaging is the method of choice for reducing noise in repetitive objects. However, when averaging is not applicable, a trade-off between reducing noise and conserving genuine image details must be achieved. Thus, denoising is an important process that improves the interpretability of the tomogram not only directly but also by facilitating other downstream tasks, such as segmentation and 3D visualization. Here, I review contemporary denoising techniques for cryo-electron tomography by taking into account noise-specific properties of both reconstruction and detector noise. The outcomes of different techniques are compared, in order to help researchers select the most appropriate for each dataset and to achieve better and more reliable interpretation of the tomograms.