Anna Lyubimova
Royal Netherlands Academy of Arts and Sciences
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Publication
Featured researches published by Anna Lyubimova.
Nature Cell Biology | 2012
Johan H. van Es; Toshiro Sato; Marc van de Wetering; Anna Lyubimova; Annie Ng Yee Nee; Alex Gregorieff; Nobuo Sasaki; Laura Zeinstra; Maaike van den Born; Jeroen Korving; Anton Martens; Nick Barker; Alexander van Oudenaarden; Hans Clevers
Lgr5+ intestinal stem cells generate enterocytes and secretory cells. Secretory lineage commitment requires Notch silencing. The Notch ligand Dll1 is expressed by a subset of immediate stem cell daughters. Lineage tracing in Dll1GFP–ires–CreERT2 knock-in mice reveals that single Dll1high cells generate small, short-lived clones containing all four secretory cell types. Lineage specification thus occurs in immediate stem cell daughters through Notch lateral inhibition. Cultured Dll1high cells form long-lived organoids (mini-guts) on brief Wnt3A exposure. When Dll1high cells are genetically marked before tissue damage, stem cell tracing events occur. Thus, secretory progenitors exhibit plasticity by regaining stemness on damage.
Nature | 2015
Dominic Grün; Anna Lyubimova; Lennart Kester; Kay Wiebrands; Onur Basak; Nobuo Sasaki; Hans Clevers; Alexander van Oudenaarden
Understanding the development and function of an organ requires the characterization of all of its cell types. Traditional methods for visualizing and isolating subpopulations of cells are based on messenger RNA or protein expression of only a few known marker genes. The unequivocal identification of a specific marker gene, however, poses a major challenge, particularly if this cell type is rare. Identifying rare cell types, such as stem cells, short-lived progenitors, cancer stem cells, or circulating tumour cells, is crucial to acquire a better understanding of normal or diseased tissue biology. To address this challenge we first sequenced the transcriptome of hundreds of randomly selected cells from mouse intestinal organoids, cultured self-organizing epithelial structures that contain all cell lineages of the mammalian intestine. Organoid buds, like intestinal crypts, harbour stem cells that continuously differentiate into a variety of cell types, occurring at widely different abundances. Since available computational methods can only resolve more abundant cell types, we developed RaceID, an algorithm for rare cell type identification in complex populations of single cells. We demonstrate that this algorithm can resolve cell types represented by only a single cell in a population of randomly sampled organoid cells. We use this algorithm to identify Reg4 as a novel marker for enteroendocrine cells, a rare population of hormone-producing intestinal cells. Next, we use Reg4 expression to enrich for these rare cells and investigate the heterogeneity within this population. RaceID confirmed the existence of known enteroendocrine lineages, and moreover discovered novel subtypes, which we subsequently validated in vivo. Having validated RaceID we then applied the algorithm to ex vivo-isolated Lgr5-positive stem cells and their direct progeny. We find that Lgr5-positive cells represent a homogenous abundant population of stem cells mixed with a rare population of Lgr5-positive secretory cells. We envision broad applicability of our method for discovering rare cell types and the corresponding marker genes in healthy and diseased organs.
Cell Stem Cell | 2016
Dominic Grün; Mauro J. Muraro; Jean Charles Boisset; Kay Wiebrands; Anna Lyubimova; Gitanjali Dharmadhikari; Maaike van den Born; Johan H. van Es; Erik W.L. Jansen; Hans Clevers; Eelco J.P. de Koning; Alexander van Oudenaarden
Summary Adult mitotic tissues like the intestine, skin, and blood undergo constant turnover throughout the life of an organism. Knowing the identity of the stem cell is crucial to understanding tissue homeostasis and its aberrations upon disease. Here we present a computational method for the derivation of a lineage tree from single-cell transcriptome data. By exploiting the tree topology and the transcriptome composition, we establish StemID, an algorithm for identifying stem cells among all detectable cell types within a population. We demonstrate that StemID recovers two known adult stem cell populations, Lgr5+ cells in the small intestine and hematopoietic stem cells in the bone marrow. We apply StemID to predict candidate multipotent cell populations in the human pancreas, a tissue with largely uncharacterized turnover dynamics. We hope that StemID will accelerate the search for novel stem cells by providing concrete markers for biological follow-up and validation.
Nature Protocols | 2013
Anna Lyubimova; Shalev Itzkovitz; Jan Philipp Junker; Zi Peng Fan; Xuebing Wu; Alexander van Oudenaarden
We present a protocol for visualizing and quantifying single mRNA molecules in mammalian (mouse and human) tissues. In the approach described here, sets of about 50 short oligonucleotides, each labeled with a single fluorophore, are hybridized to target mRNAs in tissue sections. Each set binds to a single mRNA molecule and can be detected by fluorescence microscopy as a diffraction-limited spot. Tissue architecture is then assessed by counterstaining the sections with DNA dye (DAPI), and cell borders can be visualized with a dye-coupled antibody. Spots are detected automatically with custom-made software, which we make freely available. The mRNA molecules thus detected are assigned to single cells within a tissue semiautomatically by using a graphical user interface developed in our laboratory. In this protocol, we describe an example of quantitative analysis of mRNA levels and localization in mouse small intestine. The procedure (from tissue dissection to obtaining data sets) takes 3 d. Data analysis will require an additional 3–7 d, depending on the type of analysis.
Proceedings of the National Academy of Sciences of the United States of America | 2016
Nobuo Sasaki; Norman Sachs; Kay Wiebrands; Saskia I. J. Ellenbroek; Arianna Fumagalli; Anna Lyubimova; Harry Begthel; Maaike van den Born; Johan H. van Es; Wouter R. Karthaus; Vivian Li; Peter J. Peters; Jacco van Rheenen; Alexander van Oudenaarden; Hans Clevers
Significance Stem cells crucially depend on their complex microenvironment, also called niche. The niche is defined as an anatomic site, consisting of specialized niche cells. These niche cells anchor stem cells and provide the stem cells with physical protection and essential growth and maintenance signals. In the murine small intestinal crypts, Paneth cells constitute an important part of cellular niche for Lgr5+ stem cells with which they are intermingled. Paneth cells provide molecules such as Wnt3, EGF, and Notch ligands to maintain intestinal stem cell. There exists no typical Paneth cell in the colon. Here, we show that Reg4-expressing deep crypt secretory cells function as the colon equivalent of Paneth cells. Leucine-rich repeat-containing G-protein coupled receptor 5-positive (Lgr5+) stem cells reside at crypt bottoms of the small and large intestine. Small intestinal Paneth cells supply Wnt3, EGF, and Notch signals to neighboring Lgr5+ stem cells. Whereas the colon lacks Paneth cells, deep crypt secretory (DCS) cells are intermingled with Lgr5+ stem cells at crypt bottoms. Here, we report regenerating islet-derived family member 4 (Reg4) as a marker of DCS cells. To investigate a niche function, we eliminated DCS cells by using the diphtheria-toxin receptor gene knocked into the murine Reg4 locus. Ablation of DCS cells results in loss of stem cells from colonic crypts and disrupts gut homeostasis and colon organoid growth. In agreement, sorted Reg4+ DCS cells promote organoid formation of single Lgr5+ colon stem cells. DCS cells can be massively produced from Lgr5+ colon stem cells in vitro by combined Notch inhibition and Wnt activation. We conclude that Reg4+ DCS cells serve as Paneth cell equivalents in the colon crypt niche.
bioRxiv | 2018
Norman Sachs; Domenique D. Zomer-van Ommen; Angelos Papaspyropoulos; Inha Heo; Lena Bottinger; Dymph Klay; Fleur Weeber; Guizela Huelsz-Prince; Nino Iakobachvili; Marco C. Viveen; Anna Lyubimova; Luc Teeven; Sepideh Derakhshan; Jeroen Korving; Harry Begthel; Kuldeep Kumawat; Emilio Ramos; Matthijs F.M. van Oosterhout; Eduardo P. Olimpio; Joep de Ligt; Krijn K. Dijkstra; Egbert F. Smit; Maarten van der Linden; Emile E. Voest; Coline H.M. van Moorsel; Cornelis K. van der Ent; Edwin Cuppen; Alexander van Oudenaarden; Frank E. J. Coenjaerts; Linde Meyaard
Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term-expanding human airway organoids from broncho-alveolar biopsies or lavage material. The pseudostratified airway organoid epithelium consists of basal cells, functional multi-ciliated cells, mucus-producing goblet cells, and CC10-secreting club cells. Airway organoids derived from cystic fibrosis (CF) patients allow assessment of CFTR function in an organoid swelling assay. Organoid culture conditions also allow gene editing as well as the derivation of various types of lung cancer organoids. Respiratory syncytial virus (RSV) infection recapitulated central disease features and dramatically increases organoid cell motility, found to be driven by the non-structural viral NS2 protein. We conclude that human airway organoids represent versatile models for the in vitro study of hereditary, malignant, and infectious pulmonary disease.
Journal of Investigative Dermatology | 2017
Christelle Adolphe; Jan Phillipp Junker; Anna Lyubimova; Alexander van Oudenaarden; Brandon J. Wainwright
By using the sensitivity of single-molecule fluorescent in situ hybridization, we have precisely quantified the levels and defined the temporal and spatial distribution of Hedgehog signaling activity during embryonic skin development and discovered that there is a Hedgehog signaling gradient along the proximal-distal axis of developing hair follicles. To explore the contribution of Hedgehog receptors Ptch1 and Ptch2 in establishing the epidermal signaling gradient, we quantitated the level of pathway activity generated in Ptch1- and Ptch1;Ptch2-deficient skin and defined the contribution of each receptor to regulation of the levels of Hedgehog signaling identified in wild-type skin. Moreover, we show that both the cellular phenotype and level of pathway activity featured in Ptch1;Ptch2-deficient cells faithfully recapitulates the Peak level of endogenous Hedgehog signaling detected at the base of developing follicles, where the concentration of endogenous Shh is predicted to be highest. Taken together, these data show that both Ptch1 and Ptch2 play a crucial role in sensing the concentration of Hedgehog ligand and regulating the appropriate dose-dependent response.
Nature Methods | 2018
Jean Charles Boisset; Judith Vivié; Dominic Grün; Mauro J. Muraro; Anna Lyubimova; Alexander van Oudenaarden
A cell’s function is influenced by the environment, or niche, in which it resides. Studies of niches usually require assumptions about the cell types present, which impedes the discovery of new cell types or interactions. Here we describe ProximID, an approach for building a cellular network based on physical cell interaction and single-cell mRNA sequencing, and show that it can be used to discover new preferential cellular interactions without prior knowledge of component cell types. ProximID found specific interactions between megakaryocytes and mature neutrophils and between plasma cells and myeloblasts and/or promyelocytes (precursors of neutrophils) in mouse bone marrow, and it identified a Tac1+ enteroendocrine cell–Lgr5+ stem cell interaction in small intestine crypts. This strategy can be used to discover new niches or preferential interactions in a variety of organs.The ProximID approach generates single-cell expression profiles and a network of enriched physical cellular interactions within a tissue.
Cell | 2013
Daniel E. Stange; Bon-Kyoung Koo; Meritxell Huch; Greg Sibbel; Onur Basak; Anna Lyubimova; Pekka Kujala; Sina Bartfeld; Jan Koster; Jessica H. Geahlen; Peter J. Peters; Johan H. van Es; Marc van de Wetering; Jason C. Mills; Hans Clevers
Scientific Reports | 2013
David B. Agus; Jenolyn F. Alexander; Wadih Arap; Shashanka Ashili; Joseph E. Aslan; Robert H. Austin; Vadim Backman; Kelly Bethel; Richard Bonneau; Wei Chiang Chen; Chira Chen-Tanyolac; Nathan C. Choi; Steven A. Curley; Matthew R. Dallas; Dhwanil Damania; Paul Davies; Paolo Decuzzi; Laura E. Dickinson; Luis Estévez-Salmerón; Veronica Estrella; Mauro Ferrari; Claudia Fischbach; Jasmine Foo; Stephanie I. Fraley; Christian Frantz; Alexander Fuhrmann; Philippe Gascard; Robert A. Gatenby; Yue Geng; Sharon Gerecht