TY - JOUR A1 - Huber, Florian A1 - Strehle, Dan A1 - Schnauß, Jörg A1 - Käs, Josef T1 - Formation of regularly spaced networks as a general feature of actin bundle condensation by entropic forces JF - New Journal of Physics KW - DOAJ Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34833 SN - 1367-2630 VL - 17 IS - 4 PB - IOP Publishing ER - TY - JOUR A1 - Huber, Florian A1 - Verhoeven, Stefan A1 - Meijer, Christiaan A1 - Spreeuw, Hanno A1 - Castilla, Efraín A1 - Geng, Cunliang A1 - van der Hooft, Justin J. J. A1 - Rogers, Simon A1 - Belloum, Adam A1 - Diblen, Faruk A1 - Spaaks, Jurriaan H. T1 - matchms - processing and similarity evaluation of mass spectrometry data JF - Journal of Open Source Software KW - DOAJ Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34856 SN - 2475-9066 VL - 5 IS - 52 PB - Cold Spring Harbor Laboratory ER - TY - JOUR A1 - Stuhrmann, Björn A1 - Huber, Florian A1 - Käs, Josef T1 - Robust organizational principles of protrusive biopolymer networks in migrating living cells JF - Plos One N2 - Cell migration is associated with the dynamic protrusion of a thin actin-based cytoskeletal extension at the cell front, which has been shown to consist of two different substructures, the leading lamellipodium and the subsequent lamellum. While the formation of the lamellipodium is increasingly well understood, organizational principles underlying the emergence of the lamellum are just beginning to be unraveled. We report here on a 1D mathematical model which describes the reaction-diffusion processes of a polarized actin network in steady state, and reproduces essential characteristics of the lamellipodium-lamellum system. We observe a steep gradient in filament lengths at the protruding edge, a local depolymerization maximum a few microns behind the edge, as well as a differential dominance of the network destabilizer ADF/cofilin and the stabilizer tropomyosin. We identify simple and robust organizational principles giving rise to the derived network characteristics, uncoupled from the specifics of any molecular implementation, and thus plausibly valid across cell types. An analysis of network length dependence on physico-chemical system parameters implies that to limit array treadmilling to cellular dimensions, network growth has to be truncated by mechanisms other than aging-induced depolymerization, e.g., by myosin-associated network dissociation at the transition to the cell body. Our work contributes to the analytical understanding of the cytoskeletal extension's bisection into lamellipodium and lamellum and sheds light on how cells organize their molecular machinery to achieve motility. KW - DOAJ Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34901 SN - 1932-6203 N1 - Funding: This work has been supported by the Leipzig Graduate College ‘‘GK 1097 InterNeuro - Interdisciplinary Approaches in Cellular Neuroscience’’ (http:// www.uni-leipzig.de/˜ineuro/) and the Graduate School ‘‘Leipzig School of Natural Sciences - Building with Molecules and Nano-objects (BuildMoNa)’’ (http://www. buildmona.de/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. VL - 6 IS - 1 PB - Public Library of Science (PLoS) ER - TY - JOUR A1 - Preciado López, Magdalena A1 - Huber, Florian A1 - Grigoriev, Ilya A1 - Steinmetz, Michel O. A1 - Akhmanova, Anna A1 - Koenderink, Gijsje H. A1 - Dogterom, Marileen T1 - Actin-microtubule coordination at growing microtubule ends JF - Nature Communications N2 - To power dynamic processes in cells, the actin and microtubule cytoskeletons organize into complex structures. Although it is known that cytoskeletal coordination is vital for cell function, the mechanisms by which cross-linking proteins coordinate actin and microtubule activities remain poorly understood. In particular, it is unknown how the distinct mechanical properties of different actin architectures modulate the outcome of actin-microtubule interactions. To address this question, we engineered the protein TipAct, which links growing microtubule ends via end-binding proteins to actin filaments. We show that growing microtubules can be captured and guided by stiff actin bundles, leading to global actin-microtubule alignment. Conversely, growing microtubule ends can transport, stretch and bundle individual actin filaments, thereby globally defining actin filament organization. Our results provide a physical basis to understand actin-microtubule cross-talk, and reveal that a simple cross-linker can enable a mechanical feedback between actin and microtubule organization that is relevant to diverse biological contexts. KW - DOAJ Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34878 SN - 2041-1723 VL - 5 PB - Springer Nature ER - TY - JOUR A1 - Huber, Florian A1 - van der Burg, Sven A1 - van der Hooft, Justin J. J. A1 - Ridder, Lars T1 - MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra JF - Journal of Cheminformatics N2 - Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are generally considered to be characteristic signatures of the chemical compound they originate from, yet the chemical structure itself usually cannot be easily deduced from the spectrum. Often, spectral similarity measures are used as a proxy for structural similarity but this approach is strongly limited by a generally poor correlation between both metrics. Here, we propose MS2DeepScore: a novel Siamese neural network to predict the structural similarity between two chemical structures solely based on their MS/MS fragmentation spectra. Using a cleaned dataset of > 100,000 mass spectra of about 15,000 unique known compounds, we trained MS2DeepScore to predict structural similarity scores for spectrum pairs with high accuracy. In addition, sampling different model varieties through Monte-Carlo Dropout is used to further improve the predictions and assess the model's prediction uncertainty. On 3600 spectra of 500 unseen compounds, MS2DeepScore is able to identify highly-reliable structural matches and to predict Tanimoto scores for pairs of molecules based on their fragment spectra with a root mean squared error of about 0.15. Furthermore, the prediction uncertainty estimate can be used to select a subset of predictions with a root mean squared error of about 0.1. Furthermore, we demonstrate that MS2DeepScore outperforms classical spectral similarity measures in retrieving chemically related compound pairs from large mass spectral datasets, thereby illustrating its potential for spectral library matching. Finally, MS2DeepScore can also be used to create chemically meaningful mass spectral embeddings that could be used to cluster large numbers of spectra. Added to the recently introduced unsupervised Spec2Vec metric, we believe that machine learning-supported mass spectral similarity measures have great potential for a range of metabolomics data processing pipelines. KW - DOAJ Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-34847 UR - http://www.ncbi.nlm.nih.gov/pubmed/34715914 SN - 1758-2946 N1 - J.J.J.v.d.H. acknowledges funding from an ASDI eScience grant, ASDI.2017.030, from the Netherlands eScience Center. VL - 13 IS - 1 PB - Cold Spring Harbor Laboratory ER -