Fernández Busnadiego, Rubén

[["dc.bibliographiccitation.firstpage","e1007962"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","PLoS Computational Biology"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Salfer, Maria"],["dc.contributor.author","Collado, Javier F."],["dc.contributor.author","Baumeister, Wolfgang"],["dc.contributor.author","Fernández Busnadiego, Rubén"],["dc.contributor.author","Martínez-Sánchez, Antonio"],["dc.date.accessioned","2021-04-14T08:23:54Z"],["dc.date.available","2021-04-14T08:23:54Z"],["dc.date.issued","2020"],["dc.description.abstract","Curvature is a fundamental morphological descriptor of cellular membranes. Cryo-electron tomography (cryo-ET) is particularly well-suited to visualize and analyze membrane morphology in a close-to-native state and molecular resolution. However, current curvature estimation methods cannot be applied directly to membrane segmentations in cryo-ET, as these methods cannot cope with some of the artifacts introduced during image acquisition and membrane segmentation, such as quantization noise and open borders. Here, we developed and implemented a Python package for membrane curvature estimation from tomogram segmentations, which we named PyCurv. From a membrane segmentation, a signed surface (triangle mesh) is first extracted. The triangle mesh is then represented by a graph, which facilitates finding neighboring triangles and the calculation of geodesic distances necessary for local curvature estimation. PyCurv estimates curvature based on tensor voting. Beside curvatures, this algorithm also provides robust estimations of surface normals and principal directions. We tested PyCurv and three well-established methods on benchmark surfaces and biological data. This revealed the superior performance of PyCurv not only for cryo-ET, but also for data generated by other techniques such as light microscopy and magnetic resonance imaging. Altogether, PyCurv is a versatile open-source software to reliably estimate curvature of membranes and other surfaces in a wide variety of applications."],["dc.identifier.doi","10.1371/journal.pcbi.1007962"],["dc.identifier.pmid","32776920"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/81095"],["dc.identifier.url","https://mbexc.uni-goettingen.de/literature/publications/59"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation","EXC 2067: Multiscale Bioimaging"],["dc.relation.eissn","1553-7358"],["dc.relation.workinggroup","RG Fernández-Busnadiego (Structural Cell Biology)"],["dc.rights","CC BY 4.0"],["dc.title","Reliable estimation of membrane curvature for cryo-electron tomography"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","179"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Cell"],["dc.bibliographiccitation.lastpage","187.e10"],["dc.bibliographiccitation.volume","171"],["dc.contributor.author","Bäuerlein, Felix J.B."],["dc.contributor.author","Saha, Itika"],["dc.contributor.author","Mishra, Archana"],["dc.contributor.author","Kalemanov, Maria"],["dc.contributor.author","Martínez-Sánchez, Antonio"],["dc.contributor.author","Klein, Rüdiger"],["dc.contributor.author","Dudanova, Irina"],["dc.contributor.author","Hipp, Mark S."],["dc.contributor.author","Hartl, F. Ulrich"],["dc.contributor.author","Baumeister, Wolfgang"],["dc.contributor.author","Fernández Busnadiego, Rubén"],["dc.date.accessioned","2022-03-01T11:45:03Z"],["dc.date.available","2022-03-01T11:45:03Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1016/j.cell.2017.08.009"],["dc.identifier.pii","S0092867417309340"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/103197"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-531"],["dc.relation.issn","0092-8674"],["dc.rights.uri","https://www.elsevier.com/tdm/userlicense/1.0/"],["dc.title","In Situ Architecture and Cellular Interactions of PolyQ Inclusions"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Nature Communications"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Trinkaus, Victoria A."],["dc.contributor.author","Riera-Tur, Irene"],["dc.contributor.author","Martínez-Sánchez, Antonio"],["dc.contributor.author","Bäuerlein, Felix J. B."],["dc.contributor.author","Guo, Qiang"],["dc.contributor.author","Arzberger, Thomas"],["dc.contributor.author","Baumeister, Wolfgang"],["dc.contributor.author","Dudanova, Irina"],["dc.contributor.author","Hipp, Mark S."],["dc.contributor.author","Fernández Busnadiego, Rubén"],["dc.date.accessioned","2021-06-01T09:41:39Z"],["dc.date.available","2021-06-01T09:41:39Z"],["dc.date.issued","2021"],["dc.description.abstract","Abstract The molecular architecture of α-Synuclein (α-Syn) inclusions, pathognomonic of various neurodegenerative disorders, remains unclear. α-Syn inclusions were long thought to consist mainly of α-Syn fibrils, but recent reports pointed to intracellular membranes as the major inclusion component. Here, we use cryo-electron tomography (cryo-ET) to image neuronal α-Syn inclusions in situ at molecular resolution. We show that inclusions seeded by α-Syn aggregates produced recombinantly or purified from patient brain consist of α-Syn fibrils crisscrossing a variety of cellular organelles. Using gold-labeled seeds, we find that aggregate seeding is predominantly mediated by small α-Syn fibrils, from which cytoplasmic fibrils grow unidirectionally. Detailed analysis of membrane interactions revealed that α-Syn fibrils do not contact membranes directly, and that α-Syn does not drive membrane clustering. Altogether, we conclusively demonstrate that neuronal α-Syn inclusions consist of α-Syn fibrils intermixed with membranous organelles, and illuminate the mechanism of aggregate seeding and cellular interaction."],["dc.identifier.doi","10.1038/s41467-021-22108-0"],["dc.identifier.pmid","33854052"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/84996"],["dc.identifier.url","https://mbexc.uni-goettingen.de/literature/publications/276"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-425"],["dc.relation","EXC 2067: Multiscale Bioimaging"],["dc.relation.eissn","2041-1723"],["dc.relation.workinggroup","RG Fernández-Busnadiego (Structural Cell Biology)"],["dc.rights","CC BY 4.0"],["dc.title","In situ architecture of neuronal α-Synuclein inclusions"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","476"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Developmental Cell"],["dc.bibliographiccitation.lastpage","487.e7"],["dc.bibliographiccitation.volume","51"],["dc.contributor.author","Collado, Javier"],["dc.contributor.author","Kalemanov, Maria"],["dc.contributor.author","Campelo, Felix"],["dc.contributor.author","Bourgoint, Clélia"],["dc.contributor.author","Thomas, Ffion"],["dc.contributor.author","Loewith, Robbie"],["dc.contributor.author","Martínez-Sánchez, Antonio"],["dc.contributor.author","Baumeister, Wolfgang"],["dc.contributor.author","Stefan, Christopher J."],["dc.contributor.author","Fernández Busnadiego, Rubén"],["dc.date.accessioned","2020-12-10T14:23:24Z"],["dc.date.available","2020-12-10T14:23:24Z"],["dc.date.issued","2019"],["dc.description.abstract","Membrane contact sites (MCS) between the endoplasmic reticulum (ER) and the plasma membrane (PM) play fundamental roles in all eukaryotic cells. ER-PM MCS are particularly abundant in Saccharomyces cerevisiae, where approximately half of the PM surface is covered by cortical ER (cER). Several proteins, including Ist2, Scs2/22, and Tcb1/2/3 are implicated in cER formation, but the specific roles of these molecules are poorly understood. Here, we use cryo-electron tomography to show that ER-PM tethers are key determinants of cER morphology. Notably, Tcb proteins (tricalbins) form peaks of extreme curvature on the cER membrane facing the PM. Combined modeling and functional assays suggest that Tcb-mediated cER peaks facilitate the transport of lipids between the cER and the PM, which is necessary to maintain PM integrity under heat stress. ER peaks were also present at other MCS, implying that membrane curvature enforcement may be a widespread mechanism to regulate MCS function."],["dc.identifier.doi","10.1016/j.devcel.2019.10.018"],["dc.identifier.pmid","31743662"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/71922"],["dc.identifier.url","https://mbexc.uni-goettingen.de/literature/publications/33"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation","EXC 2067: Multiscale Bioimaging"],["dc.relation.workinggroup","RG Fernández-Busnadiego (Structural Cell Biology)"],["dc.rights","CC BY-NC-ND 4.0"],["dc.title","Tricalbin-Mediated Contact Sites Control ER Curvature to Maintain Plasma Membrane Integrity"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3200"],["dc.bibliographiccitation.issue","10"],["dc.bibliographiccitation.journal","Journal of Cell Biology"],["dc.bibliographiccitation.lastpage","3211"],["dc.bibliographiccitation.volume","218"],["dc.contributor.author","Chen, Yan"],["dc.contributor.author","Yong, Jeffery"],["dc.contributor.author","Martínez-Sánchez, Antonio"],["dc.contributor.author","Yang, Yang"],["dc.contributor.author","Wu, Yumei"],["dc.contributor.author","De Camilli, Pietro"],["dc.contributor.author","Fernández Busnadiego, Rubén"],["dc.contributor.author","Wu, Min"],["dc.date.accessioned","2020-12-10T18:15:36Z"],["dc.date.available","2020-12-10T18:15:36Z"],["dc.date.issued","2019"],["dc.description.abstract","Clathrin-mediated endocytosis depends on the formation of functional clathrin-coated pits that recruit cargos and mediate the uptake of those cargos into the cell. However, it remains unclear whether the cargos in the growing clathrin-coated pits are actively monitored by the coat assembly machinery. Using a cell-free reconstitution system, we report that clathrin coat formation and cargo sorting can be uncoupled, indicating that a checkpoint is required for functional cargo incorporation. We demonstrate that the ATPase Hsc70 and a dynamic exchange of clathrin during assembly are required for this checkpoint. In the absence of Hsc70 function, clathrin assembles into pits but fails to enrich cargo. Using single-molecule imaging, we further show that uncoating takes place throughout the lifetime of the growing clathrin-coated pits. Our results suggest that the dynamic exchange of clathrin, at the cost of the reduced overall assembly rates, primarily serves as a proofreading mechanism for quality control of endocytosis."],["dc.identifier.doi","10.1083/jcb.201804136"],["dc.identifier.pmid","31451612"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/74897"],["dc.identifier.url","https://mbexc.uni-goettingen.de/literature/publications/200"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation","EXC 2067: Multiscale Bioimaging"],["dc.relation.workinggroup","RG Fernández-Busnadiego (Structural Cell Biology)"],["dc.rights","CC BY 4.0"],["dc.title","Dynamic instability of clathrin assembly provides proofreading control for endocytosis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Trinkaus, Victoria A."],["dc.contributor.author","Riera-Tur, Irene"],["dc.contributor.author","Martínez-Sánchez, Antonio"],["dc.contributor.author","Bäuerlein, Felix J. B."],["dc.contributor.author","Guo, Qiang"],["dc.contributor.author","Arzberger, Thomas"],["dc.contributor.author","Baumeister, Wolfgang"],["dc.contributor.author","Dudanova, Irina"],["dc.contributor.author","Hipp, Mark S."],["dc.contributor.author","Hartl, F. Ulrich"],["dc.contributor.author","Fernández Busnadiego, Rubén"],["dc.date.accessioned","2022-02-23T13:16:14Z"],["dc.date.available","2022-02-23T13:16:14Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1101/2020.08.07.234138"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/100363"],["dc.identifier.url","https://mbexc.uni-goettingen.de/literature/publications/164"],["dc.relation","EXC 2067: Multiscale Bioimaging"],["dc.relation.workinggroup","RG Fernández-Busnadiego (Structural Cell Biology)"],["dc.title","In situ architecture of neuronal α-Synuclein inclusions"],["dc.type","preprint"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","696"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Cell"],["dc.bibliographiccitation.lastpage","705.e12"],["dc.bibliographiccitation.volume","172"],["dc.contributor.author","Guo, Qiang"],["dc.contributor.author","Lehmer, Carina"],["dc.contributor.author","Martínez-Sánchez, Antonio"],["dc.contributor.author","Rudack, Till"],["dc.contributor.author","Beck, Florian"],["dc.contributor.author","Hartmann, Hannelore"],["dc.contributor.author","Pérez-Berlanga, Manuela"],["dc.contributor.author","Frottin, Frédéric"],["dc.contributor.author","Hipp, Mark S."],["dc.contributor.author","Hartl, F. Ulrich"],["dc.contributor.author","Fernández Busnadiego, Rubén"],["dc.date.accessioned","2022-03-01T11:45:04Z"],["dc.date.available","2022-03-01T11:45:04Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1016/j.cell.2017.12.030"],["dc.identifier.pii","S0092867417315106"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/103198"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-531"],["dc.relation.issn","0092-8674"],["dc.rights.uri","https://www.elsevier.com/tdm/userlicense/1.0/"],["dc.title","In Situ Structure of Neuronal C9orf72 Poly-GA Aggregates Reveals Proteasome Recruitment"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]