Endocrinology Endocrine Society
Total Page：16
File Type：pdf, Size：1020Kb
Gene Signature of Proliferating Human Pancreatic ααα-Cells Giselle Dominguez Gutierrez, Yurong Xin, Haruka Okamoto, Jinrang Kim, Ann-Hwee Lee, Min Ni, Christina Adler, George D. Yancopoulos, Andrew J. Murphy, and Jesper Gromada Endocrinology Endocrine Society Submitted: May 15, 2018 Accepted: July 04, 2018 First Online: July 11, 2018 Advance Articles are PDF versions of manuscripts that have been peer reviewed and accepted but Endocrinology not yet copyedited. The manuscripts are published online as soon as possible after acceptance and before the copyedited, typeset articles are published. They are posted "as is" (i.e., as submitted by the authors at the modification stage), and do not reflect editorial changes. No corrections/changes to the PDF manuscripts are accepted. Accordingly, there likely will be differences between the Advance Article manuscripts and the final, typeset articles. The manuscripts remain listed on the Advance Article page until the final, typeset articles are posted. At that point, the manuscripts are removed from the Advance Article page. DISCLAIMER: These manuscripts are provided "as is" without warranty of any kind, either express or particular purpose, or non-infringement. Changes will be made to these manuscripts before publication. Review and/or use or reliance on these materials is at the discretion and risk of the reader/user. In no event shall the Endocrine Society be liable for damages of any kind arising references to, products or publications do not imply endorsement of that product or publication. ADVANCE ARTICLE: Downloaded from https://academic.oup.com/endo/advance-article-abstract/doi/10.1210/en.2018-00469/5051604 by [email protected] user on 17 July 2018 Endocrinology; Copyright 2018 DOI: 10.1210/en.2018-00469 Human α-cell proliferation gene signature Gene Signature of Proliferating Human Pancreatic ααα-Cells Giselle Dominguez Gutierrez*1, Yurong Xin*1, Haruka Okamoto1, Jinrang Kim1, Ann-Hwee Lee1, Min Ni1, Christina Adler1, George D. Yancopoulos1, Andrew J. Murphy1, and Jesper Gromada1 1Regeneron Pharmaceuticals, Inc., 777 Old Saw Mill River Road, Tarrytown, New York, 10591, USA Received 15 May 2018. Accepted 04 July 2018. *GDG and YX are co-first authors. Pancreatic α-cells proliferate with low rate and little is known about the control of this process. Here we report the characterization of human α-cells by large-scale single cell RNA sequencing coupled with pseudotime ordering. We identified two large subpopulations and a smaller cluster of proliferating α-cells with increased expression of genes involved in cell cycle regulation. The proliferating α-cells were differentiated, had normal levels of GCG expression and showed no signs of cellular stress. Proliferating α-cells were detected in both the G1S and G2M phases of the cell cycle. Human α-cells proliferate with 5-fold higher rate than human β-cells and express lower levels of the cell cycle inhibitors CDKN1A and CDKN1C. Collectively, this study provides the gene signatures of human α-cells and the genes involved in their cell division. The lower expression of two cell cycle inhibitors in human α-cells could account for their higher rate of proliferation compared to their insulin producing counterparts. RNA sequencing of single human α-cells and pseudotime ordering of their transcriptomes revealed proliferating cells in different stages of the cell cycle and the genes regulating this process. Endocrinology 1. Introduction The initiation and progression of the cell cycle requires a tightly regulated transcriptional program and results in cell division. Cyclins and cyclin dependent kinases (CDKs) form heterodimer complexes and are key regulators of this transcriptional network. Their activation and subsequent inactivation help drive the different phases of the cell cycle 1. Transcription factors also play a key role in the regulation of the cell cycle machinery 1. It is well established that the early postnatal stages in mice (days or weeks) and humans (few years) are associated with expansion of the endocrine islet mass 2,3. After this initial expansion, the proliferation rate decreases to very low levels 4. While it has been a focus to understand the mechanisms governing the α-cell expansion during develoment, insights into the factors and pathways orchestrating the proliferation of adult α-cells has only started to emerge. A recent study using transcriptomics analysis of islet cells from fetal and adult mice was able to capture cells undergoing proliferation 5. Not surprisingly, the majority of the proliferating cells pertained to the embryonicADVANCE and juvenile stages and they observed ARTICLEa higher ratio of proliferating α-cells compared to β-cells. While their findings shed light on the genes regulating division of α- and β- ADVANCE ARTICLE: cells in mice, comparable knowledge in humans is limited to detection of few proliferating α- cells with distinct gene signatures 6,7. In the present study, we obtained the transcriptomes of >6,000 α-cells by RNA sequencing of single islet cells isolated from 12 non-diabetic donors. The cells divided into three 1 Downloaded from https://academic.oup.com/endo/advance-article-abstract/doi/10.1210/en.2018-00469/5051604 by [email protected] user on 17 July 2018 Endocrinology; Copyright 2018 DOI: 10.1210/en.2018-00469 subpopulations, two large and homogeneous subpopulations and a distinct cluster of proliferating α-cells. We used pseudotime analysis to investigate the progression of gene expression changes in the proliferating α-cells. This was obtained by projecting each cell onto a trajectory. The ordered sequence of the cells provides a higher resolution view of the genes important for the control of the various stages of the cell cycle. We also interrogated how these genes provide α- cells with greater proliferation capacity than their insulin producing counterparts obtained during the same sequencing effort. 2. Material and Methods Human islet processing Human cadaveric islets were procured from Prodo Labs. Information regarding the 12 non- diabetic donors analyzed in this study, along with their diabetes status and when available their hemoglobin A1c is provided in Supplemental Table 1. We received the islets 4-6 days after the isolation. Islets were plated in complete Prodo Islet Media (PIM-S) supplemented with glutamine/glutathione (PIM-G) and human AB serum (PIM-ABS) and incubated overnight in a tissue culture incubator at 37 ºC with a 5% CO2 in air atmosphere before dissociating into single cells. Handpicked islets were enzymatically digested at 37 ºC for 10 min using TrypLE Express (Life Technologies). Subsequently, the cells were filtered (30-µm strainer) and centrifuged. Afterwards, cells were re-suspended in 1X PBS containing 0.04% BSA. This process was immediately followed by loading and sequencing of the cells. Viability of the cells was measured using Trypan blue staining (91.2±3.3% cell viability; n=12). RNA fluorescence in situ hybridization of whole islets and dissociated islet cells Cytospin was used to place dissociated islet cells on microcope slides. Whole islets and dissociated cells were fixed in 10% neutral formalin for 35 min. Islets were embedded in paraffin Endocrinology and cut in 6 µm sections. Disociated cells underwent a process of permeabilization followed by hybridization with mRNA probes for GCG and CDK1, MKI67, RRM2 and TOP2A. The hybridization process was performed as per the manufacture’s instructions (Advanced Cell Diagnostics). Fluorescein and Cy3 fluorescent signals were amplified using a fluorescent kit. Images were captured using a microscope slide scanner (Zeiss Axio Scan.Z1). To quantify the fluorescence intensity signal, the RNA FISH analysis module from HALO image software ( Indica Labs) was utilized. Single cell RNA sequencing and read mapping Single cells suspended in PBS with 0.04% BSA were loaded on a Chromium Single Cell Instrument (10X Genomics). RNAseq libraries were prepared using Chromium Single Cell 3’ Library, Gel Beads & Mutiplex Kit (10X Genomics). Paried-end sequencing was performed on Illumina NextSeq500 with Read 1 for 59-bp transcript read, and Read 2 for 14-bp I7 index for cell barcode, 8-bp I5 index for sample index, and 10-bp unique molecular identifier (UMI). The Cell Ranger Single-Cell Software Suite (10X Genomics, v1.1.0) was used to perform sample de- multiplexing,ADVANCE alignment, filtering, and UMI counting. TheARTICLE Human B37.3 Genome assembly and UCSC gene model were used for the alignment. ADVANCE ARTICLE: Single cell data analysis As part of the quality control process, cells were removed if the number of detected genes was <500, total number of UMI was <3000, or viability score >0.2 8. Viability score was defined by the ratio of the sum of UMIs for MT-RNR2, MT-ND1, MT-CO1, MT-CO2, MT-ATP8, MT- ATP6, MT-CO3, MT-CYB expression to total UMI. Low viability was indicated by a higher 2 Downloaded from https://academic.oup.com/endo/advance-article-abstract/doi/10.1210/en.2018-00469/5051604 by [email protected] user on 17 July 2018 Endocrinology; Copyright 2018 DOI: 10.1210/en.2018-00469 score. In order to identify islet endocrine cell types, densityMclust (mclust package) was used to define two expression groups (high and low) of GCG, INS, SST and PPY. Cells with more than one hormone in the high-expression group were excluded. Single-hormone cells were identified as α (GCG-high only), β (INS-high only), δ (SST-high only), PP (PPY-high only), and ε (GHRL- high only) cells. Clustering of retained endocrine and non-endocrine cells was identified by Seurat using 1,166 variable genes. Enriched genes among the α-cell subpopulations were found by FindMarkers in Seurat with p-value <0.05 and log-scale fold change >0.25. Enriched endocrine genes were obtained by comparing endocrine cells (α-, β-, δ-, PP-, and ε-cells) with the non- endocrine cells. Pseudotime trajectory reconstruction Monocle was used to reconstruct pseudotime ordering of α-cells with the default setting.