Modelling of helical transmembrane proteins

Im Rahmen der Arbeit wurden computergestütze Methoden zur Untersuchen der Struktur und Funktion helikaler transmembraner Proteine entwickelt und angewandt. Dies führte zu einem erweiterten und verfeinerten Modell der Signaltransduktion von Integrinen. Weiterhin wurde am Beispiel einer Untereinheit des Proteins Cytochrom C Oxidase eine neue Rechenmethode zur Modellierung transmembraner 4-Helix-Bündel vorgestellt und mit gutem Erfolg getestet. Mit dem vorgestellte Verfahren wurde ein strukturelles Modell des transmembranen, Multiresistenz auslösenden Transporter EmrE erstellt, das in Einklang mit allen biochemischen Daten ist. Im Folgenden wurde untersucht, welche Freiheitsgrade einer Helix im polytopen Protein durch Helix-Helix-Wechselwirkungen bestimmt sind. Als Ergebnis wurde gezeigt, dass nur der Kippwinkel der Helices unabhängig von Helix-Helix-Wechselwirkungen ist. Diese Erkenntnis wurde zur Modellierung komplexer Proteine mit Strukturdaten niedriger Auflösung genutzt.In this work the structure and function of helical transmembrane proteins was elucidated based on computational methods. An extended and refined model of transmembrane signal transduction by integrins was developed. Further studies showed the possibility to predict the structure of a four-helix bundle using a newly developed method. The new method was applied to the transmembrane multidrug transporter EmrE. A structural model that is in agreement with all experimental data was developed. Additionally it was examined which degrees of freedom in a helix bundle are determined by helix-helix interactions

Ageing-induced shrinkage of intervessel pit membranes in xylem of Clematis vitalba modifies its mechanical properties as revealed by atomic force microscopy

Bordered pit membranes of angiosperm xylem are anisotropic, mesoporous media between neighbouring conduits, with a key role in long distance water transport. Yet, their mechanical properties are poorly understood. Here, we aim to quantify the stiffness of intervessel pit membranes over various growing seasons. By applying an AFM-based indentation technique “Quantitative Imaging” we measured the effective elastic modulus (Eeffective) of intervessel pit membranes of Clematis vitalba in dependence of size, age, and hydration state. The indentation-deformation behaviour was analysed with a non-linear membrane model, and paired with magnetic resonance imaging to visualise sap-filled and embolised vessels, while geometrical data of bordered pits were obtained using electron microscopy. Eeffective was transformed to the geometrically independent apparent elastic modulus Eapparent and to aspiration pressure Pb. The material stiffness (Eapparent) of fresh pit membranes was with 57 MPa considerably lower than previously suggested. The estimated pressure for pit membrane aspiration was 2.20+28 MPa. Pit membranes from older growth rings were shrunken, had a higher material stiffness and a lower aspiration pressure than current year ones, suggesting an irreversible, mechanical ageing process. This study provides an experimental-stiffness analysis of hydrated intervessel pit membranes in their native state. The estimated aspiration pressure suggests that membranes are not deflected under normal field conditions. Although absolute values should be interpreted carefully, our data suggest that pit membrane shrinkage implies increasing material stiffness, and highlight the dynamic changes of pit membrane mechanics and their complex, functional behaviour for fluid transport

Polyclonal Aptamer Libraries from a FluRoot-SELEX for the Specific Labeling of the Apical and Elongation/Differentiation Zones of Arabidopsis thaliana Roots

In more than 30 years of aptamer research, it has become widely accepted that aptamers are fascinating binding molecules for a vast variety of applications. However, the majority of targets have been proteins, although special variants of the so-called SELEX process for the molecular evolution of specific aptamers have also been developed, allowing for the targeting of small molecules as well as larger structures such as cells and even cellular networks of human (tumor) tissues. Although the provocative thesis is widely accepted in the field, that is, in principle, any level of complexity for SELEX targets is possible, the number of studies on whole organs or at least parts of them is limited. To pioneer this thesis, and based on our FluCell-SELEX process, here, we have developed polyclonal aptamer libraries against apices and the elongation/differentiation zones of plant roots as examples of organs. We show that dedicated libraries can specifically label the respective parts of the root, allowing us to distinguish them in fluorescence microscopy. We consider this achievement to be an initial but important evidence for the robustness of this SELEX variant. These libraries may be valuable tools for plant research and a promising starting point for the isolation of more specific individual aptamers directed against root-specific epitopes

A Polyclonal SELEX Aptamer Library Allows Differentiation of Candida albicans, C. auris and C. parapsilosis Cells from Human Dermal Fibroblasts

Easy and reliable identification of pathogenic species such as yeasts, emerging as problematic microbes originating from the genus Candida, is a task in the management and treatment of infections, especially in hospitals and other healthcare environments. Aptamers are seizing an already indispensable role in different sensing applications as binding entities with almost arbitrarily tunable specificities and optimizable affinities. Here, we describe a polyclonal SELEX library that not only can specifically recognize and fluorescently label Candida cells, but is also capable to differentiate C. albicans, C. auris and C. parapsilosis cells in flow-cytometry, fluorometric microtiter plate assays and fluorescence microscopy from human cells, exemplified here by human dermal fibroblasts. This offers the opportunity to develop diagnostic tools based on this library. Moreover, these specific and robust affinity molecules could also serve in the future as potent binding entities on biomaterials and as constituents of technical devices and will thus open avenues for the development of cost-effective and easily accessible next generations of electronic biosensors in clinical diagnostics and novel materials for the specific removal of pathogenic cells from human bio-samples

Albumin Microspheres as “Trans-ferry-beads” for Easy Cell Passaging in Cell Culture Technology

Protein hydrogels represent ideal materials for advanced cell culture applications, including 3D-cultivation of even fastidious cells. Key properties of fully functional and, at the same time, economically successful cell culture materials are excellent biocompatibility and advanced fabrication processes allowing their easy production even on a large scale based on affordable compounds. Chemical crosslinking of bovine serum albumin (BSA) with N-(3-dimethylaminopropyl)-N’-ethylcarbodiimide hydrochloride (EDC) in a water-in-oil emulsion with isoparaffinic oil as the continuous phase and sorbitan monooleate as surfactant generates micro-meter-scale spherical particles. They allow a significant simplification of an indispensable and laborious step in traditional cell culture workflows. This cell passaging (or splitting) to fresh culture vessels/flasks conventionally requires harsh trypsinization, which can be omitted by using the “trans-ferry-beads” presented here. When added to different pre-cultivated adherent cell lines, the beads are efficiently boarded by cells as passengers and can be easily transferred afterward for the embarkment of novel flasks. After this procedure, cells are perfectly viable and show normal growth behavior. Thus, the trans-ferry-beads not only may become extremely affordable as a final product but also may generally replace trypsinization in conventional cell culture, thereby opening new routes for the establishment of optimized and resource-efficient workflows in biological and medical cell culture laboratories

Interaction of β-Sheet Folds with a Gold Surface

The adsorption of proteins on inorganic surfaces is of fundamental biological importance. Further, biomedical and nanotechnological applications increasingly use interfaces between inorganic material and polypeptides. Yet, the underlying adsorption mechanism of polypeptides on surfaces is not well understood and experimentally difficult to analyze. Therefore, we investigate here the interactions of polypeptides with a gold(111) surface using computational molecular dynamics (MD) simulations with a polarizable gold model in explicit water. Our focus in this paper is the investigation of the interaction of polypeptides with β-sheet folds. First, we concentrate on a β-sheet forming model peptide. Second, we investigate the interactions of two domains with high β-sheet content of the biologically important extracellular matrix protein fibronectin (FN). We find that adsorption occurs in a stepwise mechanism both for the model peptide and the protein. The positively charged amino acid Arg facilitates the initial contact formation between protein and gold surface. Our results suggest that an effective gold-binding surface patch is overall uncharged, but contains Arg for contact initiation. The polypeptides do not unfold on the gold surface within the simulation time. However, for the two FN domains, the relative domain-domain orientation changes. The observation of a very fast and strong adsorption indicates that in a biological matrix, no bare gold surfaces will be present. Hence, the bioactivity of gold surfaces (like bare gold nanoparticles) will critically depend on the history of particle administration and the proteins present during initial contact between gold and biological material. Further, gold particles may act as seeds for protein aggregation. Structural re-organization and protein aggregation are potentially of immunological importance

Identifying Discrete States of a Biological System Using a Novel Step Detection Algorithm

<div><p>Identification of discrete states is a common task when studying biological systems on microscopic scales. Here, we present a novel step detection algorithm that is ideally suited to locate steplike features separating adjacent plateaus, even if they are smooth and hidden by noise. It can be adjusted to detect very low or narrow steps that cannot be recognized by conventional methods. We demonstrate the applicability of the technique on various experimental data and show strong evidence of sub-10-pN steps in atomic force spectroscopy measurements performed with living lymphocytes.</p> </div

Detection rates vs. noise amplitudes of the MSF and the method applied to synthetic test signals.

<p>Every marker represents the average rate over 100 curves with distinct random noise, with error bars indicating the standard errors. a: Two steps of height one separated by a variable distance (data set A, see example in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0045896#pone-0045896-g001" target="_blank">fig. 1c</a>). The last plot shows the average detection rates over 33 step distances between 40 and 1000 data points. Detection parameters were optimized for the constant SNRs and distances of the steps. b: Artificial force curves generated by Monte Carlo simulations with varied number of steps (data set B, see example in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0045896#pone-0045896-g001" target="_blank">fig. 1d</a>). Parameter optimization was performed for each noise level and number of steps. The last plot shows the average detection rates over the range of 2, 3, …, 50 steps.</p

Total average detection rates for the data shown in fig. 2.

<p>Filter settings were individually optimized for every noise amplitude and step width (data set A)/number of steps (data set B). Relative rates are related to the results obtained by the method combined with the windowed mean filter.</p

Test signals used for the evaluation of the step detection algorithms.

<p>Test signals used for the evaluation of the step detection algorithms.</p