2016, Davies, Heather S., Singh, Prabha, Deckert-Gaudig, Tanja, Deckert, Volker, Rousseau, Karine, Ridley, Caroline E., Dowd, Sarah E., Doig, Andrew J., Pudney, Paul D. A., Thornton, David J., Blanch, Ewan W.

The major structural components of protective mucus hydrogels on mucosal surfaces are the secreted polymeric gel-forming mucins. The very high molecular weight and extensive O-glycosylation of gel-forming mucins, which are key to their viscoelastic properties, create problems when studying mucins using conventional biochemical/structural techniques. Thus, key structural information, such as the secondary structure of the various mucin subdomains, and glycosylation patterns along individual molecules, remains to be elucidated. Here, we utilized Raman spectroscopy, Raman optical activity (ROA), circular dichroism (CD), and tip-enhanced Raman spectroscopy (TERS) to study the structure of the secreted polymeric gel-forming mucin MUC5B. ROA indicated that the protein backbone of MUC5B is dominated by unordered conformation, which was found to originate from the heavily glycosylated central mucin domain by isolation of MUC5B O-glycan-rich regions. In sharp contrast, recombinant proteins of the N-terminal region of MUC5B (D1-D2-D′-D3 domains, NT5B), C-terminal region of MUC5B (D4-B-C-CK domains, CT5B) and the Cys-domain (within the central mucin domain of MUC5B) were found to be dominated by the β-sheet. Using these findings, we employed TERS, which combines the chemical specificity of Raman spectroscopy with the spatial resolution of atomic force microscopy to study the secondary structure along 90 nm of an individual MUC5B molecule. Interestingly, the molecule was found to contain a large amount of α-helix/unordered structures and many signatures of glycosylation, pointing to a highly O-glycosylated region on the mucin.

2014, Martinez-Cisneros, C.S., Sanchez, S., Xi, W., Schmidt, O.G.

We present ultracompact three-dimensional tubular structures integrating Au-based electrodes as impedimetric microsensors for the in-flow determination of mono- and divalent ionic species and HeLa cells. The microsensors show an improved performance of 2 orders of magnitude (limit of detection = 0.1 nM for KCl) compared to conventional planar conductivity detection systems integrated in microfluidic platforms and the capability to detect single HeLa cells in flowing phosphate buffered saline. These highly integrated conductivity tubular sensors thus open new possibilities for lab-in-a-tube devices for bioapplications such as biosensing and bioelectronics.

2021, Schu, Moritz, Terriac, Emmanuel, Koch, Marcus, Paschke, Stephan, Lautenschläger, Franziska, Flormann, Daniel A.D.

The cellular cortex is an approximately 200-nm-thick actin network that lies just beneath the cell membrane. It is responsible for the mechanical properties of cells, and as such, it is involved in many cellular processes, including cell migration and cellular interactions with the environment. To develop a clear view of this dense structure, high-resolution imaging is essential. As one such technique, electron microscopy, involves complex sample preparation procedures. The final drying of these samples has significant influence on potential artifacts, like cell shrinkage and the formation of artifactual holes in the actin cortex. In this study, we compared the three most used final sample drying procedures: critical-point drying (CPD), CPD with lens tissue (CPD-LT), and hexamethyldisilazane drying. We show that both hexamethyldisilazane and CPD-LT lead to fewer artifactual mesh holes within the actin cortex than CPD. Moreover, CPD-LT leads to significant reduction in cell height compared to hexamethyldisilazane and CPD. We conclude that the final drying procedure should be chosen according to the reduction in cell height, and so CPD-LT, or according to the spatial separation of the single layers of the actin cortex, and so hexamethyldisilazane.

2021, Nittala, Aditya Shekhar, Karrenbauer, Andreas, Khan, Arshad, Kraus, Tobias, Steimle, Jürgen

Electro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.

2015, Beer, Meike V., Hahn, Kathrin, Diederichs, Sylvia, Fabry, Marlies, Singh, Smriti, Spencer, Steve J., Salber, Jochen, Möller, Martin, Shard, Alexander G., Groll, Jürgen

Hydrogels are extensively studied for biomaterials application as they provide water swollen noninteracting matrices in which specific binding motifs and enzyme-sensitive degradation sites can be incorporated to tailor cell adhesion, proliferation, and migration. Hydrogels also serve as excellent basis for surface modification of biomaterials where interfacial characteristics are decisive for implant success or failure. However, the three-dimensional nature of hydrogels makes it hard to distinguish between the bioactive ligand density at the hydrogel-cell interface that is able to interact with cells and the ligands that are immobilized inside the hydrogel and not accessible for cells. Here, the authors compare x-ray photoelectron spectrometry (XPS), time-of-flight secondary ion mass spectroscopy (ToF-SIMS), enzyme linked immunosorbent assay (ELISA), and the correlation with quantitative cell adhesion using primary human dermal fibroblasts (HDF) to gain insight into ligand distribution. The authors show that although XPS provides the most useful quantitative analysis, it lacks the sensitivity to measure biologically meaningful concentrations of ligands. However, ToF-SIMS is able to access this range provided that there are clearly distinguishable secondary ions and a calibration method is found. Detection by ELISA appears to be sensitive to the ligand density on the surface that is necessary to mediate cell adhesion, but the upper limit of detection coincides closely with the minimal ligand spacing required to support cell proliferation. Radioactive measurements and ELISAs were performed on amine reactive well plates as true 2D surfaces to estimate the ligand density necessary to allow cell adhesion onto hydrogel films. Optimal ligand spacing for HDF adhesion and proliferation on ultrathin hydrogel films was determined as 6.5 ± 1.5 nm.

2014, Jahangiri, E., Reichelt, S., Thomas, I., Hausmann, K., Schlosser, D., Schulze, A.

The versatile oxidase enzyme laccase was immobilized on porous supports such as polymer membranes and cryogels with a view of using such biocatalysts in bioreactors aiming at the degradation of environmental pollutants in wastewater. Besides a large surface area for supporting the biocatalyst, the aforementioned porous systems also offer the possibility for simultaneous filtration applications in wastewater treatment. Herein a "green" water-based, initiator-free, and straightforward route to highly reactive membrane and cryogel-based bioreactors is presented, where laccase was immobilized onto the porous polymer supports using a water-based electron beam-initiated grafting reaction. In a second approach, the laccase redox mediators 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) and syringaldehyde were cross-linked instead of the enzyme via electron irradiation in a frozen aqueous poly(acrylate) mixture in a one pot set-up, yielding a mechanical stable macroporous cryogel with interconnected pores ranging from 10 to 50 μm in size. The membranes as well as the cryogels were characterized regarding their morphology, chemical composition, and catalytic activity. The reactivity towards waste-water pollutants was demonstrated by the degradation of the model compound bisphenol A (BPA). Both membrane- and cryogel-immobilized laccase remained highly active after electron beam irradiation. Apparent specific BPA removal rates were higher for cryogel-than for membrane-immobilized and free laccase, whereas membrane-immobilized laccase was more stable with respect to maintenance of enzymatic activity and prevention of enzyme leakage from the carrier than cryogel-immobilized laccase. Cryogel-immobilized redox mediators remained functional in accelerating the laccase-catalyzed BPA degradation, and especially ABTS was found to act more efficiently in immobilized than in freely dissolved state.

2014, Raz, Y., Adler, J., Vogel, A., Scheidt, H.A., Häupl, T., Abel, B., Huster, D., Miller, Y.

Tau is a microtubule-associated protein and is involved in microtubule assembly and stabilization. It consists of four repeats that bind to the microtubule. The ΔK280 deletion mutation in the tau R2 repeat region is directly associated with the development of the frontotemporal dementia parkinsonism linked to chromosome 17 (FTDP-17). This deletion mutation is known to accelerate tau R2 repeat aggregation. However, the secondary and the tertiary structures of the self-assembled ΔK280 tau R2 repeat mutant aggregates are still controversial. Moreover, it is unclear whether extensions by one residue in the N- or the C-terminus of this mutant can influence the secondary or the tertiary structure. Herein, we combine solid-state NMR, atomic force microscopy, electron microscopy and all-atom explicit molecular dynamics simulations to investigate the effects of the deletion mutation and the N- and the C-terminal extension of this mutant on the structure. Our main findings show that the deletion mutation induces the formation of small aggregates, such as oligomers, and reduces the formation of fibrils. However, the extensions in the N- or the C-terminus revealed more fibril formation than small aggregates. Further, in the deletion mutation only one structure is preferred, while the N- and the C-terminal extensions strongly lead to polymorphic states. Finally, our broad and combined experimental and computational techniques provide direct structural information regarding ΔK280 tau R2 repeat mutant aggregates and their extensions in the N- and C-terminii by one residue.

2014, Appelhans, Dietmar, Klajnert-Maculewicz, Barbara, Janaszewska, Anna, Lazniewska, Joanna, Voit, Brigitte

In this review we highlight the potential for biomedical applications of dendritic glycopolymers based on polyamine scaffolds. The complex interplay of the molecular characteristics of the dendritic architectures and their specific interactions with various (bio)molecules are elucidated with various examples. A special role of the individual sugar units attached to the dendritic scaffolds and their density is identified, which govern ionic and H-bond interactions, and biological targeting, but to a large extent are also responsible for the significantly reduced toxicity of the dendritic glycopolymers compared to their polyamine scaffolds. Thus, the application of dendritic glycopolymers in drug delivery systems for gene transfection but also as therapeutics in neurodegenerative diseases has great promise.

2016, Thamm, Kristina, Graupner, Sylvi, Werner, Carsten, Huttner, Wieland B., Corbeil, Denis, Nabi, Ivan R

The pentaspan membrane glycoprotein prominin-1 (CD133) is widely used in medicine as a cell surface marker of stem and cancer stem cells. It has opened new avenues in stem cell-based regenerative therapy and oncology. This molecule is largely used with human samples or the mouse model, and consequently most biological tools including antibodies are directed against human and murine prominin-1. Although the general structure of prominin-1 including its membrane topology is conserved throughout the animal kingdom, its primary sequence is poorly conserved. Thus, it is unclear if anti-human and -mouse prominin-1 antibodies cross-react with their orthologs in other species, especially dog. Answering this issue is imperative in light of the growing number of studies using canine prominin-1 as an antigenic marker. Here, we address this issue by cloning the canine prominin-1 and use its overexpression as a green fluorescent protein fusion protein in Madin-Darby canine kidney cells to determine its immunoreactivity with antibodies against human or mouse prominin-1. We used immunocytochemistry, flow cytometry and immunoblotting techniques and surprisingly found no cross-species immunoreactivity. These results raise some caution in data interpretation when anti-prominin-1 antibodies are used in interspecies studies.

2023, Cortacero, Kévin, McKenzie, Brienne, Müller, Sabina, Khazen, Roxana, Lafouresse, Fanny, Corsaut, Gaëlle, Van Acker, Nathalie, Frenois, François-Xavier, Lamant, Laurence, Meyer, Nicolas, Vergier, Béatrice, Wilson, Dennis G., Luga, Hervé, Staufer, Oskar, Dustin, Michael L., Valitutti, Salvatore, Cussat-Blanc, Sylvain

An unresolved issue in contemporary biomedicine is the overwhelming number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. However, these frameworks require large human-annotated datasets for training and the resulting “black box” models are difficult to interpret. In this study, we introduce Kartezio, a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets. This Few-Shot Learning method confers tremendous flexibility, speed, and functionality to this approach. We then deploy Kartezio to solve a series of semantic and instance segmentation problems, and demonstrate its utility across diverse images ranging from multiplexed tissue histopathology images to high resolution microscopy images. While the flexibility, robustness and practical utility of Kartezio make this fully explicable evolutionary designer a potential game-changer in the field of biomedical image processing, Kartezio remains complementary and potentially auxiliary to mainstream Deep Learning approaches.