<b>Department of bioinformatics in infection research ([BRICS] BIFO)</b>http://hdl.handle.net/10033/6205972024-03-29T09:21:31Z2024-03-29T09:21:31ZMIAMI--a tool for non-targeted detection of metabolic flux changes for mode of action identification.Dudek, Christian-AlexanderReuse, CarstenFuchs, RegineHendriks, JannekeStarck, VeroniqueHiller, Karstenhttp://hdl.handle.net/10033/6231882022-05-07T01:56:59ZMIAMI--a tool for non-targeted detection of metabolic flux changes for mode of action identification.
Dudek, Christian-Alexander; Reuse, Carsten; Fuchs, Regine; Hendriks, Janneke; Starck, Veronique; Hiller, Karsten
In vitro interaction network of a synthetic gut bacterial community.Weiss, Anna SBurrichter, Anna GDurai Raj, Abilash Chakravarthyvon Strempel, AlexandraMeng, ChenKleigrewe, KarinMünch, Philipp CRössler, LuisHuber, ClaudiaEisenreich, WolfgangJochum, Lara MGöing, StephanieJung, KirstenLincetto, ChiaraHübner, JohannesMarinos, GeorgiosZimmermann, JohannesKaleta, ChristophSanchez, AlvaroStecher, Bärbelhttp://hdl.handle.net/10033/6231452022-01-18T03:43:27Z2021-12-02T00:00:00ZIn vitro interaction network of a synthetic gut bacterial community.
Weiss, Anna S; Burrichter, Anna G; Durai Raj, Abilash Chakravarthy; von Strempel, Alexandra; Meng, Chen; Kleigrewe, Karin; Münch, Philipp C; Rössler, Luis; Huber, Claudia; Eisenreich, Wolfgang; Jochum, Lara M; Göing, Stephanie; Jung, Kirsten; Lincetto, Chiara; Hübner, Johannes; Marinos, Georgios; Zimmermann, Johannes; Kaleta, Christoph; Sanchez, Alvaro; Stecher, Bärbel
A key challenge in microbiome research is to predict the functionality of microbial communities based on community membership and (meta)-genomic data. As central microbiota functions are determined by bacterial community networks, it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on the growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM12) synthetic bacterial community, which is increasingly used as a model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments as well as in community batch culture. Metabolic network reconstruction in combination with metabolomics analysis of bacterial culture supernatants provided insights into the metabolic potential and activity of the individual community members. Thereby, we could show that the OMM12 interaction network is shaped by both exploitative and interference competition in vitro in nutrient-rich culture media and demonstrate how community structure can be shifted by changing the nutritional environment. In particular, Enterococcus faecalis KB1 was identified as an important driver of community composition by affecting the abundance of several other consortium members in vitro. As a result, this study gives fundamental insight into key drivers and mechanistic basis of the OMM12 interaction network in vitro, which serves as a knowledge base for future mechanistic in vivo studies.
2021-12-02T00:00:00ZAccurate and scalable variant calling from single cell DNA sequencing data with ProSolo.Lähnemann, DavidKöster, JohannesFischer, UteBorkhardt, ArndtMcHardy, Alice CSchönhuth, Alexanderhttp://hdl.handle.net/10033/6231422022-01-14T03:20:07Z2021-11-18T00:00:00ZAccurate and scalable variant calling from single cell DNA sequencing data with ProSolo.
Lähnemann, David; Köster, Johannes; Fischer, Ute; Borkhardt, Arndt; McHardy, Alice C; Schönhuth, Alexander
Accurate single cell mutational profiles can reveal genomic cell-to-cell heterogeneity. However, sequencing libraries suitable for genotyping require whole genome amplification, which introduces allelic bias and copy errors. The resulting data violates assumptions of variant callers developed for bulk sequencing. Thus, only dedicated models accounting for amplification bias and errors can provide accurate calls. We present ProSolo for calling single nucleotide variants from multiple displacement amplified (MDA) single cell DNA sequencing data. ProSolo probabilistically models a single cell jointly with a bulk sequencing sample and integrates all relevant MDA biases in a site-specific and scalable-because computationally efficient-manner. This achieves a higher accuracy in calling and genotyping single nucleotide variants in single cells in comparison to state-of-the-art tools and supports imputation of insufficiently covered genotypes, when downstream tools cannot handle missing data. Moreover, ProSolo implements the first approach to control the false discovery rate reliably and flexibly. ProSolo is implemented in an extendable framework, with code and usage at: https://github.com/prosolo/prosolo.
2021-11-18T00:00:00ZA bipartite element with allele-specific functions safeguards DNA methylation imprints at the Dlk1-Dio3 locus.Aronson, Boaz EScourzic, LaurianneShah, VeevekSwanzey, EmilyKloetgen, AndreasPolyzos, AlexanderSinha, AbhishekAzziz, AnnabelCaspi, InbalLi, JiexiPelham-Webb, BobbieGlenn, Rachel AVierbuchen, ThomasWichterle, HynekTsirigos, AristotelisDawlaty, Meelad MStadtfeld, MatthiasApostolou, Effiehttp://hdl.handle.net/10033/6231132021-12-08T01:53:08Z2021-10-27T00:00:00ZA bipartite element with allele-specific functions safeguards DNA methylation imprints at the Dlk1-Dio3 locus.
Aronson, Boaz E; Scourzic, Laurianne; Shah, Veevek; Swanzey, Emily; Kloetgen, Andreas; Polyzos, Alexander; Sinha, Abhishek; Azziz, Annabel; Caspi, Inbal; Li, Jiexi; Pelham-Webb, Bobbie; Glenn, Rachel A; Vierbuchen, Thomas; Wichterle, Hynek; Tsirigos, Aristotelis; Dawlaty, Meelad M; Stadtfeld, Matthias; Apostolou, Effie
Loss of imprinting (LOI) results in severe developmental defects, but the mechanisms preventing LOI remain incompletely understood. Here, we dissect the functional components of the imprinting control region of the essential Dlk1-Dio3 locus (called IG-DMR) in pluripotent stem cells. We demonstrate that the IG-DMR consists of two antagonistic elements: a paternally methylated CpG island that prevents recruitment of TET dioxygenases and a maternally unmethylated non-canonical enhancer that ensures expression of the Gtl2 lncRNA by counteracting de novo DNA methyltransferases. Genetic or epigenetic editing of these elements leads to distinct LOI phenotypes with characteristic alternations of allele-specific gene expression, DNA methylation, and 3D chromatin topology. Although repression of the Gtl2 promoter results in dysregulated imprinting, the stability of LOI phenotypes depends on the IG-DMR, suggesting a functional hierarchy. These findings establish the IG-DMR as a bipartite control element that maintains imprinting by allele-specific restriction of the DNA (de)methylation machinery.
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