Single-cell transcriptome analysis of endometrial tissue
| Autor: | Triin Laisk-Podar, D. Lubenets, M. Vera-Rodriguez, Shintaro Katayama, Kaarel Krjutškov, Andres Salumets, Merly Saare, Külli Samuel, Elisabet Einarsdottir, Juha Kere, Hindrek Teder |
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| Přispěvatelé: | Research Programs Unit, Päivi Marjaana Saavalainen / Principal Investigator, Research Programme for Molecular Neurology, Juha Kere / Principal Investigator |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Pathology endometrial receptivity Cell Separation Endometrium Transcriptome NORMALIZATION 0302 clinical medicine Single-cell analysis HETEROGENEITY Cells Cultured POPULATION education.field_of_study Reproductive Biology 030219 obstetrics & reproductive medicine medicine.diagnostic_test Rehabilitation food and beverages Obstetrics and Gynecology Cell cycle biopsy cryopreservation medicine.anatomical_structure DIFFERENTIATION Female Stem cell Single-Cell Analysis STEM-CELLS Adult Estonia EXPRESSION medicine.medical_specialty CORTEX Stromal cell Population endometrial biopsy Biology CD13 Antigens Luteal Phase Tetraspanin 29 03 medical and health sciences medicine Humans RNA Messenger education Gene Library Cryopreservation Sequence Analysis RNA Gene Expression Profiling MESSENGER-RNA-SEQ fungi Epithelial Cells Original Articles GENE 030104 developmental biology Gene Ontology Reproductive Medicine Gene Expression Regulation STROMAL CELLS Cancer research 3111 Biomedicine clinical sampling Biomarkers Endometrial biopsy single-cell FACS |
| Zdroj: | Europe PubMed Central Human Reproduction (Oxford, England) |
| Popis: | STUDY QUESTION: How can we study the full transcriptome of endometrial stromal and epithelial cells at the single-cell level? SUMMARY ANSWER: By compiling and developing novel analytical tools for biopsy, tissue cryopreservation and disaggregation, single-cell sorting, library preparation, RNA sequencing (RNA-seq) and statistical data analysis. WHAT IS KNOWN ALREADY: Although single-cell transcriptome analyses from various biopsied tissues have been published recently, corresponding protocols for human endometrium have not been described. STUDY DESIGN, SIZE, DURATION: The frozen-thawed endometrial biopsies were fluorescence-activated cell sorted (FACS) to distinguish CD13-positive stromal and CD9-positive epithelial cells and single-cell transcriptome analysis performed from biopsied tissues without culturing the cells. We studied gene transcription, applying a modern and efficient RNA-seq protocol. In parallel, endometrial stromal cells were cultured and global expression profiles were compared with uncultured cells. PARTICIPANTS/MATERIALS, SETTING, METHODS: For method validation, we used two endometrial biopsies, one from mid-secretory phase (Day 21, LH+8) and another from late-secretory phase (Day 25). The samples underwent single-cell FACS sorting, single-cell RNA-seq library preparation and Illumina sequencing. MAIN RESULTS AND THE ROLE OF CHANCE: Here we present a complete pipeline for single-cell gene-expression studies, from clinical sampling to statistical data analysis. Tissue manipulation, starting from disaggregation and cell-type-specific labelling and ending with single-cell automated sorting, is managed within 90 min at low temperature to minimize changes in the gene expression profile. The single living stromal and epithelial cells were sorted using CD13- and CD9-specific antibodies, respectively. Of the 8622 detected genes, 2661 were more active in cultured stromal cells than in biopsy cells. In the comparison of biopsy versus cultured cells, 5603 commonly expressed genes were detected, with 241 significantly differentially expressed genes. Of these, 231 genes were up- and 10 down-regulated in cultured cells, respectively. In addition, we performed a gene ontology analysis of the differentially expressed genes and found that these genes are mainly related to cell cycle, translational processes and metabolism. LIMITATIONS, REASONS FOR CAUTION: Although CD9-positive single epithelial cells sorting was successfully established in our laboratory, the amount of transcriptome data per individual epithelial cell was low, complicating further analysis. This step most likely failed due to the high dose of RNases that are released by the cells' natural processes, or due to rapid turnaround time or the apoptotic conditions in freezing- or single-cell solutions. Since only the cells from the late-secretory phase were subject to more focused analysis, further studies including larger sample size from the different time-points of the natural menstrual cycle are needed. The methodology also needs further optimization to examine different cell types at high quality. WIDER IMPLICATIONS OF THE FINDINGS: The symbiosis between clinical biopsy and the sophisticated laboratory and bioinformatic protocols described here brings together clinical diagnostic needs and modern laboratory and bioinformatic solutions, enabling us to implement a precise analytical toolbox for studying the endometrial tissue even at the single-cell level. |
| Databáze: | OpenAIRE |
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