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      Diabetes Relief in Mice by Glucose-Sensing Insulin-Secreting Human α-Cells

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          Abstract

          Cell identity switches, where terminally-differentiated cells convert into different cell-types when stressed, represent a widespread regenerative strategy in animals, yet they are poorly documented in mammals. In mice, some glucagon-producing pancreatic α-cells and somatostatin-producing δ-cells become insulin expressers upon ablation of insulin-secreting β-cells, promoting diabetes recovery. Whether human islets also display this plasticity, especially in diabetic conditions, remains unknown. Here we show that islet non-β-cells, namely α-cells and PPY-producing γ–cells, obtained from deceased non-diabetic or diabetic human donors, can be lineage-traced and reprogrammed by the transcription factors Pdx1 and MafA to produce and secrete insulin in response to glucose. When transplanted into diabetic mice, converted human α-cells reverse diabetes and remain producing insulin even after 6 months. Surprisingly, insulin-producing α-cells maintain α-cell markers, as seen by deep transcriptomic and proteomic characterization. These observations provide conceptual evidence and a molecular framework for a mechanistic understanding of in situ cell plasticity as a treatment for diabetes and other degenerative diseases.

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          Most cited references52

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          Reversal of diabetes with insulin-producing cells derived in vitro from human pluripotent stem cells.

          Transplantation of pancreatic progenitors or insulin-secreting cells derived from human embryonic stem cells (hESCs) has been proposed as a therapy for diabetes. We describe a seven-stage protocol that efficiently converts hESCs into insulin-producing cells. Stage (S) 7 cells expressed key markers of mature pancreatic beta cells, including MAFA, and displayed glucose-stimulated insulin secretion similar to that of human islets during static incubations in vitro. Additional characterization using single-cell imaging and dynamic glucose stimulation assays revealed similarities but also notable differences between S7 insulin-secreting cells and primary human beta cells. Nevertheless, S7 cells rapidly reversed diabetes in mice within 40 days, roughly four times faster than pancreatic progenitors. Therefore, although S7 cells are not fully equivalent to mature beta cells, their capacity for glucose-responsive insulin secretion and rapid reversal of diabetes in vivo makes them a promising alternative to pancreatic progenitor cells or cadaveric islets for the treatment of diabetes.
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            MultiNotch MS3 Enables Accurate, Sensitive, and Multiplexed Detection of Differential Expression across Cancer Cell Line Proteomes

            Multiplexed quantitation via isobaric chemical tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantitation (iTRAQ)) has the potential to revolutionize quantitative proteomics. However, until recently the utility of these tags was questionable due to reporter ion ratio distortion resulting from fragmentation of coisolated interfering species. These interfering signals can be negated through additional gas-phase manipulations (e.g., MS/MS/MS (MS3) and proton-transfer reactions (PTR)). These methods, however, have a significant sensitivity penalty. Using isolation waveforms with multiple frequency notches (i.e., synchronous precursor selection, SPS), we coisolated and cofragmented multiple MS2 fragment ions, thereby increasing the number of reporter ions in the MS3 spectrum 10-fold over the standard MS3 method (i.e., MultiNotch MS3). By increasing the reporter ion signals, this method improves the dynamic range of reporter ion quantitation, reduces reporter ion signal variance, and ultimately produces more high-quality quantitative measurements. To demonstrate utility, we analyzed biological triplicates of eight colon cancer cell lines using the MultiNotch MS3 method. Across all the replicates we quantified 8 378 proteins in union and 6 168 proteins in common. Taking into account that each of these quantified proteins contains eight distinct cell-line measurements, this data set encompasses 174 704 quantitative ratios each measured in triplicate across the biological replicates. Herein, we demonstrate that the MultiNotch MS3 method uniquely combines multiplexing capacity with quantitative sensitivity and accuracy, drastically increasing the informational value obtainable from proteomic experiments.
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              In vivo reprogramming of adult pancreatic exocrine cells to beta-cells.

              One goal of regenerative medicine is to instructively convert adult cells into other cell types for tissue repair and regeneration. Although isolated examples of adult cell reprogramming are known, there is no general understanding of how to turn one cell type into another in a controlled manner. Here, using a strategy of re-expressing key developmental regulators in vivo, we identify a specific combination of three transcription factors (Ngn3 (also known as Neurog3) Pdx1 and Mafa) that reprograms differentiated pancreatic exocrine cells in adult mice into cells that closely resemble beta-cells. The induced beta-cells are indistinguishable from endogenous islet beta-cells in size, shape and ultrastructure. They express genes essential for beta-cell function and can ameliorate hyperglycaemia by remodelling local vasculature and secreting insulin. This study provides an example of cellular reprogramming using defined factors in an adult organ and suggests a general paradigm for directing cell reprogramming without reversion to a pluripotent stem cell state.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                12 April 2019
                13 February 2019
                March 2019
                13 August 2019
                : 567
                : 7746
                : 43-48
                Affiliations
                [1 ]Department of Genetic Medicine and Development, iGE3 and Centre facultaire du diabète, Faculty of Medicine, University of Geneva, Switzerland;
                [2 ]Department of Clinical Science, University of Bergen, Bergen, Norway;
                [3 ]Department of Cell Biology, Harvard Medical School, Boston, MA, USA;
                [4 ]Departments of Immunohematology & Blood Transfusion, Leiden University Medical Center, Leiden, Netherlands;
                [5 ]Cell Isolation and Transplantation Center, Department of Surgery, University of Geneva and University Hospitals of Geneva, Switzerland;
                [6 ]Oregon Stem Cell Center, Oregon Health & Science University, Portland, OR, USA;
                [7 ]Department of Pediatrics, Haukeland University Hospital, Norway;
                [8 ]Department of Diabetes Immunology, Diabetes & Metabolism Research Institute, City of Hope, Duarte, CA, USA.
                Author notes

                Author contributions K.F. conceived and performed the experiments and analyses, and wrote the manuscript; S.C. analyzed the omics data and wrote the manuscript; L.vG. and L.G. analyzed the omics data, and edited the manuscript; N.D. conceived and performed some experiments and analyses, and edited the manuscript; D.O. analyzed data and wrote the manuscript; A.M.J., K.F. and B.O.R. performed and analyzed immunogenicity tests; H.V. and H.R. prepared samples and contributed to the mass spectrometry study; J.A.P. performed the TMT-labeling experiment and mass spectrometry analysis; T.B. and D.B. generated some human islet preparations and contributed to discussion; C.D. and M.G. generated antibodies, established cell-sorting strategies and contributed to discussion; F.T. and P.L.H. conceived the experiments, interpreted the observations and wrote the manuscript.

                Corresponding author: Pedro L. Herrera, pedro.herrera@ 123456unige.ch
                Article
                NIHMS1518742
                10.1038/s41586-019-0942-8
                6624841
                30760930
                6bf115c0-500f-466a-aeb5-977d4b6e671e

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