Ludewig, Fabian

[["dc.bibliographiccitation.artnumber","4091"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Shomroni, Orr"],["dc.contributor.author","Sitte, Maren"],["dc.contributor.author","Schmidt, Julia"],["dc.contributor.author","Parbin, Sabnam"],["dc.contributor.author","Ludewig, Fabian"],["dc.contributor.author","Yigit, Gökhan"],["dc.contributor.author","Zelarayan, Laura Cecilia"],["dc.contributor.author","Streckfuss-Bömeke, Katrin"],["dc.contributor.author","Wollnik, Bernd"],["dc.contributor.author","Salinas, Gabriella"],["dc.date.accessioned","2022-04-01T10:01:43Z"],["dc.date.available","2022-04-01T10:01:43Z"],["dc.date.issued","2022"],["dc.description.abstract","Single cell multi-omics analysis has the potential to yield a comprehensive understanding of the cellular events that underlie the basis of human diseases. The cardinal feature to access this information is the technology used for single-cell isolation, barcoding, and sequencing. Most currently used single-cell RNA-sequencing platforms have limitations in several areas including cell selection, documentation and library chemistry. In this study, we describe a novel high-throughput, full-length, single-cell RNA-sequencing approach that combines the CellenONE isolation and sorting system with the ICELL8 processing instrument. This method offers substantial improvements in single cell selection, documentation and capturing rate. Moreover, it allows the use of flexible chemistry for library preparations and the analysis of living or fixed cells, whole cells independent of sizing and morphology, as well as of nuclei. We applied this method to dermal fibroblasts derived from six patients with different segmental progeria syndromes and defined phenotype associated pathway signatures with variant associated expression modifiers. These results validate the applicability of our method to highlight genotype-expression relationships for molecular phenotyping of individual cells derived from human patients."],["dc.description.sponsorship","Georg-August-Universität Göttingen"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.doi","10.1038/s41598-022-07874-1"],["dc.identifier.pii","7874"],["dc.identifier.pmid","35260714"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/105735"],["dc.identifier.url","https://mbexc.uni-goettingen.de/literature/publications/460"],["dc.identifier.url","https://sfb1002.med.uni-goettingen.de/production/literature/publications/424"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-530"],["dc.relation","EXC 2067: Multiscale Bioimaging"],["dc.relation","SFB 1002: Modulatorische Einheiten bei Herzinsuffizienz"],["dc.relation.eissn","2045-2322"],["dc.relation.workinggroup","RG Wollnik"],["dc.relation.workinggroup","RG Zelarayán-Behrend (Developmental Pharmacology)"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","A novel single-cell RNA-sequencing approach and its applicability connecting genotype to phenotype in ageing disease"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","247"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Molecular Biology of the Cell"],["dc.bibliographiccitation.lastpage","257"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Alkhaja, Alwaleed K."],["dc.contributor.author","Jans, Daniel C."],["dc.contributor.author","Nikolov, Miroslav"],["dc.contributor.author","Vukotic, Milena"],["dc.contributor.author","Lytovchenko, Oleksandr"],["dc.contributor.author","Ludewig, Fabian"],["dc.contributor.author","Schliebs, Wolfgang"],["dc.contributor.author","Riedel, Dietmar"],["dc.contributor.author","Urlaub, Henning"],["dc.contributor.author","Jakobs, Stefan"],["dc.contributor.author","Deckers, Markus"],["dc.date.accessioned","2017-09-07T11:49:01Z"],["dc.date.available","2017-09-07T11:49:01Z"],["dc.date.issued","2012"],["dc.description.abstract","The inner membrane of mitochondria is especially protein rich and displays a unique morphology characterized by large invaginations, the mitochondrial cristae, and the inner boundary membrane, which is in proximity to the outer membrane. Mitochondrial inner membrane proteins appear to be not evenly distributed in the inner membrane, but instead organize into functionally distinct subcompartments. It is unknown how the organization of the inner membrane is achieved. We identified MINOS1/MIO10 (C1orf151/YCL057C-A), a conserved mitochondrial inner membrane protein. mio10-mutant yeast cells are affected in growth on nonfermentable carbon sources and exhibit altered mitochondrial morphology. At the ultrastructural level, mutant mitochondria display loss of inner membrane organization. Proteomic analyses reveal MINOS1/Mio10 as a novel constituent of Mitofilin/Fcj1 complexes in human and yeast mitochondria. Thus our analyses reveal new insight into the composition of the mitochondrial inner membrane organizing machinery."],["dc.identifier.doi","10.1091/mbc.E11-09-0774"],["dc.identifier.gro","3142588"],["dc.identifier.isi","000299108000002"],["dc.identifier.pmid","22114354"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/7823"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8955"],["dc.language.iso","en"],["dc.notes.intern","WoS Import 2017-03-10"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.relation.issn","1059-1524"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","MINOS1 is a conserved component of mitofilin complexes and required for mitochondrial function and cristae organization"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","UNSP e0117818"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Heyde, Silvia von der"],["dc.contributor.author","Wagner, Steve"],["dc.contributor.author","Czerny, Alexander"],["dc.contributor.author","Nietert, Manuel M."],["dc.contributor.author","Ludewig, Fabian"],["dc.contributor.author","Salinas-Riester, Gabriela"],["dc.contributor.author","Arlt, Dorit"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2018-11-07T10:00:48Z"],["dc.date.available","2018-11-07T10:00:48Z"],["dc.date.issued","2015"],["dc.description.abstract","Intrinsic and acquired resistance to the monoclonal antibody drug trastuzumab is a major problem in the treatment of HER2-positive breast cancer. A deeper understanding of the underlying mechanisms could help to develop new agents. Our intention was to detect genes and single nucleotide polymorphisms (SNPs) affecting trastuzumab efficiency in cell culture. Three HER2-positive breast cancer cell lines with different resistance phenotypes were analyzed. We chose BT474 as model of trastuzumab sensitivity, HCC1954 as model of intrinsic resistance, and BTR50, derived from BT474, as model of acquired resistance. Based on RNA-Seq data, we performed differential expression analyses on these cell lines with and without trastuzumab treatment. Differentially expressed genes between the resistant cell lines and BT474 are expected to contribute to resistance. Differentially expressed genes between untreated and trastuzumab treated BT474 are expected to contribute to drug efficacy. To exclude false positives from the candidate gene set, we removed genes that were also differentially expressed between untreated and trastuzumab treated BTR50. We further searched for SNPs in the untreated cell lines which could contribute to trastuzumab resistance. The analysis resulted in 54 differentially expressed candidate genes that might be connected to trastuzumab efficiency. 90% of 40 selected candidates were validated by RT-qPCR. ALPP, CALCOCO1, CAV1, CYP1A2 and IGFBP3 were significantly higher expressed in the trastuzumab treated than in the untreated BT474 cell line. GDF15, IL8, LCN2, PTGS2 and 20 other genes were significantly higher expressed in HCC1954 than in BT474, while NCAM2, COLEC12, AFF3, TFF3, NRCAM, GREB1 and TFF1 were significantly lower expressed. Additionally, we inferred SNPs in HCC1954 for CAV1, PTGS2, IL8 and IGFBP3. The latter also had a variation in BTR50. 20% of the validated subset have already been mentioned in literature. For half of them we called and analyzed SNPs. These results contribute to a better understanding of trastuzumab action and resistance mechanisms."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2015"],["dc.identifier.doi","10.1371/journal.pone.0117818"],["dc.identifier.isi","000350683900039"],["dc.identifier.pmid","25710561"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11652"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37888"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","mRNA Profiling Reveals Determinants of Trastuzumab Efficiency in HER2-Positive Breast Cancer"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]