Massively parallel spectroscopy of sources in Galactic globular clusters

Globular clusters (GCs) consist of hundreds of thousands of stars, densely packed into a spherical shape. Not only do GC contain ordinary main sequence and red giant stars, but also the products of frequent stellar encounters, stellar remnants, and potentially intermediate-mass black holes (IMBH). But how can we find these objects hidden between thousands of other stars? With the progress in observation techniques used in astronomy, it is possible to observe individual stars in the cores of GCs, the most crowded regions. In particular, the development of large integral-field spectrographs, such as Multi-Unit Spectroscopic Explorer (MUSE) at the Very Large Telescope, and adaptive optics to correct for atmospheric distortions, enable high-resolution observations from the ground. Using these techniques, we can efficiently observe GCs and measure individual spectra of thousands of stars simultaneously. During an automated search for emission-line objects in these spectra, we detected a previously unknown nebula in M22. The spectrum of this nebula shows emission lines of hydrogen, nitrogen, and sulphur, but it does not look like a typical spectrum of a planetary nebula (PN). Not only are its spectral lines unusual, but with its small size and a low luminosity, the nebula also does not resemble any of the four known PNe in Galactic GCs, including the one in M22. The literature contains many attempts to detect a central IMBH in a Galactic GC. So far, there is no unambiguous discovery. We use data taken with the MUSE narrow-field mode with a spatial resolution comparable to the Hubble Space Telescope to analyse the motion of stars in M80. To overcome the usual problems of previous attempts, we employ both a model based on the Jeans equations and an independent $N$-body model of M80. We find two equally probable solutions with different dynamical cluster centres: One solution has its centre close to the photometric centre from the literature, and it does not need an IMBH to explain the observed stellar motions. Another solution has a centre with a small offset from the first one. Here, a central IMBH with a mass of several thousand solar masses is needed. The $N$-body models exclude the existence of many stellar-mass black holes, which could mimic the effect of an IMBH on the stellar motions.2021-10-1

Discovery of an old nova remnant in the Galactic globular cluster M 22

A nova is a cataclysmic event on the surface of a white dwarf in a binary system that increases the overall brightness by several orders of magnitude. Although binary systems with a white dwarf are expected to be overabundant in globular clusters (GCs) compared to the Galaxy, only two novae from Galactic globular clusters have been observed. We present the discovery of an emission nebula in the Galactic globular cluster M 22 (NGC 6656) in observations made with the integral-field spectrograph MUSE. We extract the spectrum of the nebula and use the radial velocity determined from the emission lines to confirm that the nebula is part of NGC 6656. Emission-line ratios are used to determine the electron temperature and density. It is estimated to have a mass of 1 to $17 \times 10^{-5}$ solar masses. This mass and the emission-line ratios indicate that the nebula is a nova remnant. Its position coincides with the reported location of a 'guest star', an ancient Chinese term for transients, observed in May 48 BCE. With this discovery, this nova may be one of the oldest confirmed extrasolar events recorded in human history.Comment: 7 pages, 3 figures; accepted for publication in Astronomy & Astrophysic

Lgr5+ stem and progenitor cells reside at the apex of a heterogeneous embryonic hepatoblast pool.

During mouse embryogenesis, progenitors within the liver known as hepatoblasts give rise to adult hepatocytes and cholangiocytes. Hepatoblasts, which are specified at E8.5-E9.0, have been regarded as a homogeneous progenitor population that initiate differentiation from E13.5. Recently, scRNA-seq analysis has identified sub-populations of transcriptionally distinct hepatoblasts at E11.5. Here, we show that hepatoblasts are not only transcriptionally but also functionally heterogeneous, and that a subpopulation of E9.5-E10.0 hepatoblasts exhibit a previously unidentified early commitment to cholangiocyte fate. Importantly, we also identify a subpopulation constituting 2% of E9.5-E10.0 hepatoblasts that express the adult stem cell marker Lgr5, and generate both hepatocyte and cholangiocyte progeny that persist for the lifespan of the mouse. Combining lineage tracing and scRNA-seq, we show that Lgr5 marks E9.5-E10.0 bipotent liver progenitors residing at the apex of a hepatoblast hierarchy. Furthermore, isolated Lgr5+ hepatoblasts can be clonally expanded in vitro into embryonic liver organoids, which can commit to either hepatocyte or cholangiocyte fates. Our study demonstrates functional heterogeneity within E9.5 hepatoblasts and identifies Lgr5 as a marker for a subpopulation of bipotent liver progenitors.M.H. is a Wellcome Trust Sir Henry Dale Fellow and is jointly funded by the Wellcome Trust and the Royal Society (104151/Z/14/Z); M.H. and N.P. are funded by a Horizon 2020 grant (LSFM4LIFE). C.H. was funded by a Cambridge Stem Cell Institute Seed funding for interdisciplinary research awarded to M.H. and B.D.S., B.D.S acknowledges funding from the Royal Society E.P. Abraham Research Professorship (RP\R1\180165) and Wellcome Trust (098357/Z/12/Z). W.L. and B.G. were supported by programmatic funding from the Wellcome Trust, CRUK and Bloodwise, core infrastructure support from the Wellcome and MRC to the Wellcome & MRC Cambridge Stem Cell Institute, and an MRC Clinical Research Infrastructure grant supporting single cell molecular analysis. S.R. was funded on a Herchel-Smith Fellowship. The authors acknowledge core funding to the Gurdon Institute from the Wellcome Trust (092096) and CRUK (C6946/A14492)

Kinematic differences between multiple populations in Galactic globular clusters

The formation process of multiple populations in globular clusters is still up for debate. Kinematic differences between the populations are particularly interesting in this respect, because they allow us to distinguish between single-epoch formation scenarios and multi-epoch formation scenarios. We analyze the kinematics of 25 globular clusters and aim to find kinematic differences between multiple populations to constrain their formation process. We split red-giant branch (RGB) stars in each cluster into three populations (P1, P2, P3) for the type-II clusters and two populations (P1 and P2) otherwise using Hubble photometry. We derive the rotation and dispersion profiles for each cluster and its populations by using all stars with radial velocity measurements obtained from MUSE spectroscopy. Based on these profiles, we calculate the rotation strength in terms of ordered-over-random motion $\left(v/\sigma\right)_\mathrm{HL}$ evaluated at the half-light radius of the cluster. We detect rotation in all but four clusters. For NGC~104, NGC~1851, NGC~2808, NGC~5286, NGC~5904, NGC~6093, NGC~6388, NGC~6541, NGC~7078 and NGC~7089 we also detect rotation for P1 and/or P2 stars. For NGC~2808, NGC~6093 and NGC~7078 we find differences in $\left(v/\sigma\right)_\mathrm{HL}$ between P1 and P2 that are larger than $1\sigma$. Whereas we find that P2 rotates faster than P1 for NGC~6093 and NGC~7078, the opposite is true for NGC~2808. However, even for these three clusters, the differences are still of low significance. We find that the strength of rotation of a cluster generally scales with its median relaxation time. For P1 and P2, the corresponding relation is very weak at best. We observe no correlation between the difference in rotation strength between P1 and P2 and cluster relaxation time. The MUSE stellar radial velocities that this analysis is based on are made publicly available

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells.

Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions ( https://github.com/theislab/paga ). PAGA maps preserve the global topology of data, allow analyzing data at different resolutions, and result in much higher computational efficiency of the typical exploratory data analysis workflow. We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, adult planaria and the zebrafish embryo and benchmark computational performance on one million neurons.Wellcome Trust, MRC, CRUK, Bloodwise, Swedish Research Council, Helmholtz Association, German Center for Cardiovascular Research, German Research Foundatio

A stellar census in globular clusters with MUSE: Binaries in NGC 3201

We utilize multi-epoch MUSE spectroscopy to study binaries in the core of NGC 3201. Our sample consists of 3553 stars with 54883 spectra in total comprising 3200 main-sequence stars up to 4 magnitudes below the turn-off. Each star in our sample has between 3 and 63 (with a median of 14) reliable radial velocity (RV) measurements within five years of observations. We introduce a statistical method to determine the probability of a star showing RV variations based on the whole inhomogeneous RV sample. Using HST photometry and an advanced dynamical MOCCA simulation of this specific GC we overcome observational biases that previous spectroscopic studies had to deal with. This allows us to infer a binary frequency in the MUSE FoV and enables us to deduce the underlying true binary frequency of (6.75+-0.72) % in NGC 3201. The comparison of the MUSE observations with the MOCCA simulation suggests a significant fraction of primordial binaries. We can also confirm a radial increase of the binary fraction towards the GC centre due to mass segregation. We discovered that in our sample at least (57.5+-7.9) % of blue straggler stars (BSS) are in a binary system. For the first time in a study of GCs, we were able to fit Keplerian orbits to a significant sample of 95 binaries. We present the binary system properties of eleven BSS and show evidence that two BSS formation scenarios, the mass transfer in binary (or triple) star systems and the coalescence due to binary-binary interactions, are present in our data. We also describe the binary and spectroscopic properties of four sub-subgiant (or red straggler) stars. Furthermore, we discovered two new black hole (BH) candidates with minimum masses (Msini) of (7.68+-0.50) M_sun, (4.4+-2.8) M_sun, and refine the minimum mass estimate on the already published BH to (4.53+-0.21) M_sun. These BHs are consistent with an extensive BH subsystem hosted by NGC 3201

Combined Single-Cell Functional and Gene Expression Analysis Resolves Heterogeneity within Stem Cell Populations.

Heterogeneity within the self-renewal durability of adult hematopoietic stem cells (HSCs) challenges our understanding of the molecular framework underlying HSC function. Gene expression studies have been hampered by the presence of multiple HSC subtypes and contaminating non-HSCs in bulk HSC populations. To gain deeper insight into the gene expression program of murine HSCs, we combined single-cell functional assays with flow cytometric index sorting and single-cell gene expression assays. Through bioinformatic integration of these datasets, we designed an unbiased sorting strategy that separates non-HSCs away from HSCs, and single-cell transplantation experiments using the enriched population were combined with RNA-seq data to identify key molecules that associate with long-term durable self-renewal, producing a single-cell molecular dataset that is linked to functional stem cell activity. Finally, we demonstrated the broader applicability of this approach for linking key molecules with defined cellular functions in another stem cell system.Work in the author’s laboratory is supported by grants from the Leukaemia and Lymphoma Research, the Medical Research Council, Cancer Research UK, Biotechnology and Biological Sciences Research Council, Leukemia Lymphoma Society, and the National Institute for Health Research Cambridge Biomedical Research Centre and core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research and Wellcome Trust-MRC Cambridge Stem Cell Institute. D.G.K. is the recipient of a Canadian Institutes of Health Research Postdoctoral Fellowship. F.B. and F.J.T. are funded by the European Research Council (starting grant “LatentCauses”). For funding for the open access charge, the core support grant was provided by the Wellcome Trust-MRC Cambridge Stem Cell Institute. We acknowledge the support of the University of Cambridge, Cancer Research UK Institute (core grant C14303/A17197), and Hutchison Whampoa Limited.This is the final published version. It first appeared at http://www.cell.com/cell-stem-cell/abstract/S1934-5909%2815%2900162-9

The Human Cell Atlas.

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community

Identification of novel regulators of developmental hematopoiesis using Endoglin regulatory elements as molecular probes.

Enhancers are the primary determinants of cell identity, and specific promoter/enhancer combinations of Endoglin (ENG) have been shown to target blood and endothelium in the embryo. Here, we generated a series of embryonic stem cell lines, each targeted with reporter constructs driven by specific promoter/enhancer combinations of ENG, to evaluate their discriminative potential and value as molecular probes of the corresponding transcriptome. The Eng promoter (P) in combination with the -8/+7/+9-kb enhancers, targeted cells in FLK1 mesoderm that were enriched for blast colony forming potential, whereas the P/-8-kb enhancer targeted TIE2+/c-KIT+/CD41- endothelial cells that were enriched for hematopoietic potential. These fractions were isolated using reporter expression and their transcriptomes profiled by RNA-seq. There was high concordance between our signatures and those from embryos with defects at corresponding stages of hematopoiesis. Of the 6 genes that were upregulated in both hemogenic mesoderm and hemogenic endothelial fractions targeted by the reporters, LRP2, a multiligand receptor, was the only gene that had not previously been associated with hematopoiesis. We show that LRP2 is indeed involved in definitive hematopoiesis and by doing so validate the use of reporter gene-coupled enhancers as probes to gain insights into transcriptional changes that facilitate cell fate transitions.National Health and Medical Research Council of Australia, Australian Research Council, Dr Tom Bee Stem Cell Research Fund, Cancer Research UK, Biotechnology and Biological Sciences Research Council, Leukaemia and Lymphoma Research, The Leukaemia and Lymphoma Society, core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research and Wellcome Trust - MRC Cambridge Stem Cell Institute (Grant IDs: R01 HL04880, P015PO1HL32262-32, 5P30 DK49216, 5R01 DK53298, 5U01 HL10001-05, R24 DK092760)This is the author accepted manuscript. The final version is available from the American Society of Hematology via http://dx.doi.org/10.1182/blood-2016-02-69787

Decoding the regulatory network of early blood development from single-cell gene expression measurements.

Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.We thank J. Downing (St. Jude Children's Research Hospital, Memphis, TN, USA) for the Runx1-ires-GFP mouse. Research in the authors' laboratory is supported by the Medical Research Council, Biotechnology and Biological Sciences Research Council, Leukaemia and Lymphoma Research, the Leukemia and Lymphoma Society, Microsoft Research and core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research and Wellcome Trust - MRC Cambridge Stem Cell Institute. V.M. is supported by a Medical Research Council Studentship and Centenary Award and S.W. by a Microsoft Research PhD Scholarship.This is the accepted manuscript for a paper published in Nature Biotechnology 33, 269–276 (2015) doi:10.1038/nbt.315