scholarly journals Cell-type diversity and regionalized gene expression in the planarian intestine revealed by laser-capture microdissection transcriptome profiling

2019 ◽  
Author(s):  
David J. Forsthoefel ◽  
Nicholas I. Cejda ◽  
Umair W. Khan ◽  
Phillip A. Newmark
Keyword(s):  
Gene Expression ◽  
Laser Capture Microdissection ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Cell Types ◽  
Goblet Cells ◽  
Intestinal Cell ◽  
Specific Gene ◽  
Cell Type ◽  
Laser Capture

AbstractOrgan regeneration requires precise coordination of new cell differentiation and remodeling of uninjured tissue to faithfully re-establish organ morphology and function. An atlas of gene expression and cell types in the uninjured state is therefore an essential pre-requisite for understanding how damage is repaired. Here, we use laser-capture microdissection (LCM) and RNA-Seq to define the transcriptome of the intestine of Schmidtea mediterranea, a planarian flatworm with exceptional regenerative capacity. Bioinformatic analysis of 1,844 intestine-enriched transcripts suggests extensive conservation of digestive physiology with other animals, including humans. Comparison of the intestinal transcriptome to purified absorptive intestinal cell (phagocyte) and published single-cell expression profiles confirms the identities of known intestinal cell types, and also identifies hundreds of additional transcripts with previously undetected intestinal enrichment. Furthermore, by assessing the expression patterns of 143 transcripts in situ, we discover unappreciated mediolateral regionalization of gene expression and cell-type diversity, especially among goblet cells. Demonstrating the utility of the intestinal transcriptome, we identify 22 intestine-enriched transcription factors, and find that several have distinct functional roles in the regeneration and maintenance of goblet cells. Furthermore, depletion of goblet cells inhibits planarian feeding and reduces viability. Altogether, our results show that LCM is a viable approach for assessing tissue-specific gene expression in planarians, and provide a new resource for further investigation of digestive tract regeneration, the physiological roles of intestinal cell types, and axial polarity.

410. Gene expression analysis in endometriotic lesions using laser capture microdissection

2008 ◽  
Vol 20 (9) ◽  
pp. 90
Author(s):  
L. Fu ◽  
J. E. Girling ◽  
P. A. W. Rogers
Keyword(s):  
Gene Expression ◽  
Real Time ◽  
Laser Capture Microdissection ◽  
Stromal Cells ◽  
Expression Profiles ◽  
Specific Gene ◽  
Rt Pcr ◽  
Normal Endometrium ◽  
Rna Quality ◽  
Laser Capture

Previous studies examining gene expression profiles in normal endometrium and endometriotic lesions have used RNA extracted from whole tissue samples. Results from these studies can be difficult to interpret as they reflect expression averaged across several different cell types that may be functionally quite different. The aim of this study was to establish laser capture microdissection (LCM) as a technique to examine gene expression in stromal and epithelial cells from normal and ectopic endometrium. We hypothesised that genes associated with inflammation would be elevated in cells from endometriotic lesions. Full thickness uterine samples were collected during abdominal hysterectomy from normal cycling premenopausal women. Endometriotic lesions were collected during abdominal laparoscopy. Samples were either frozen in OCT or stored in RNAlater for 12 h before freezing. Tissues were immunostained with an antibody against CD10 to identify ectopic endometrial stromal cells before LCM. Endometrial epithelial and stromal cells were collected using the PALM MicroLaser System. RNA quality was accessed using Experion. TGFβ1, MMP1, αSMA, SMAD2 and NFκB mRNA was analysed using real-time RT–PCR. Of the endometriotic samples stored in OCT (n = 58), only 14% (n = 8) had visible endometrial glands. Of these, only 37% (n = 3) had RNA of an acceptable quality for further analysis. However, RNA quality and quantity were dramatically improved in 3 of 5 samples collected in RNAlater. In preliminary studies, expression of TGFβ1 and αSMA mRNA was elevated in endometriotic lesions in comparison to the normal endometrium, whereas NFκB expression did not change. We have shown that RNAlater solution is useful to preserve RNA quality for small clinical endometriotic samples and that immuno-guided LCM-generated homogenous cell populations coupled with real-time RT–PCR can provide valuable insights into cell and disease-specific gene expression in endometriotic lesions.

scholarly journals CT-FOCS: a novel method for inferring cell type-specific enhancer-promoter maps

2019 ◽  
Author(s):  
Tom Aharon Hait ◽  
Ran Elkon ◽  
Ron Shamir
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Patterns ◽  
Cell Types ◽  
Specific Gene ◽  
Cell Type ◽  
Chromatin Interactions ◽  
Cell Type Specific ◽  
Novel Method ◽  
Validation Scheme

AbstractSpatiotemporal gene expression patterns are governed to a large extent by enhancer elements, typically located distally from their target genes. Identification of enhancer-promoter (EP) links that are specific and functional in individual cell types is a key challenge in understanding gene regulation. We introduce CT-FOCS, a new statistical inference method that utilizes multiple replicates per cell type to infer cell type-specific EP links. Computationally predicted EP links are usually benchmarked against experimentally determined chromatin interactions measured by ChIA-PET and promoter-capture HiC techniques. We expand this validation scheme by using also loops that overlap in their anchor sites. In analyzing 1,366 samples from ENCODE, Roadmap epigenomics and FANTOM5, CT-FOCS inferred highly cell type-specific EP links more accurately than state-of-the-art methods. We illustrate how our inferred EP links drive cell type-specific gene expression and regulation.

Laser Capture Microdissection, Amplified Antisense Rna, and Highdensity Microarrays: The New Frontier for Gene Expression Profiling From Limited Amounts of Tissue

2000 ◽  
Vol 6 (S2) ◽  
pp. 840-841
Author(s):  
Roger D. Madison, Ph.D.
Keyword(s):  
Gene Expression ◽  
Laser Capture Microdissection ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Mrna Levels ◽  
Functional Protein ◽  
Protein Levels ◽  
Degradation Rates ◽  
A Cell ◽  
Laser Capture

Because the genes in all somatic cells of an individual are identical, it is the differential expression of the proteins encoded by particular genes that determines a cell's phenotype. There is now increasing interest in relating the simultaneous expression patterns of multiple proteins to complex biological processes. The goal is to develop ‘expression profiles’ of the proteins that are active within a cell or tissue during a particular condition. The ultimate control of functional protein expression is quite complex and may involve transcriptional, combinatorial, and postranslational mechanisms, as well as differences in protein degradation rates that vary under different conditions. Although mRNA levels do not always predict functional protein levels, they are a useful first step in determining the expression profile.The evolution of three key technologies offers the promise of obtaining quantitative analysis of gene expression from restricted amounts of nervous system tissue. Laser capture microdissection can accomplish harvesting of identified cell populations from histologically processed tissue.

Automated Sorting of Monocytes from Whole Blood for Reproducible Gene Expression Profiling.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3840-3840
Author(s):  
Carsten Poggel ◽  
Timo Adams ◽  
Sabine Martin ◽  
Carola Pickel ◽  
Nicole Prahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Gene Expression Profiling ◽  
Whole Blood ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Specific Gene

Abstract Microarray-based gene expression profiling has been used to develop clinically relevant molecular classifiers for many different diseases. Furthermore, it has been shown for various chronic diseases that specific gene expression patterns are reflected at the level of blood cells. However, blood is a complex tissue comprising numerous cell types. Therefore, the contribution of rare cell types to a whole blood expression profile might not be detected and a substantial proportion of what is usually reported as “up-regulation” or “down-regulation” might actually be the result of a shift in cell populations and not of a true regulatory process. In order to circumvent these problems, several techniques have been established to analyze purified subpopulations rather than whole blood samples. Previously, it has been shown, for example, that reproducible gene expression profiles can be generated by positive selection of blood cell subsets from PBMCs1. As the preparation of PBMCs by, for example, Ficoll is time-consuming, inconvenient, and not amenable to automation, we have set up a combined direct whole blood cell separation and gene expression profiling protocol. By using Whole Blood CD14 MicroBeads in combination with the autoMACS Pro™ Separator, the separation protocol generally allowed enrichment of monocytes from whole blood within 30 min with purities higher than 90%. In combination with the depletion of neutrophils, the major source of contaminating RNA, purities increased to over 95% for all tested blood donors. Monocytes included the CD14bright/CD16− as well as the CD14dim/CD16+ populations. To assess the reproducibility of gene expression profiles and the influence of several experimental parameters, monocytes were sorted from 5 ml whole blood. RNA was extracted and hybridized to microarrays and the Pearson correlation coefficients of pairwise comparisons were calculated. Technical repeats of monocyte analysis from blood donated at different days showed a higher correlation coefficient than whole blood RNA. Blood storage at room temperature resulted in a strong deregulation of many genes, whereas blood stored at 4°C showed minimal changes, which is in agreement with previous studies. Skipping the centrifugation step, which is used to remove unbound MicroBeads did not alter the gene expression profiles. Incubation of sorted cells in PrepProtect™ Stabilization Buffer showed no alteration of gene expression thus enabling the shipping of cells without liquid nitrogen. Monocytes play a crucial role in diseases like atherosclerosis. Our rapid and simple protocol for combined direct cell sorting from whole blood and gene expression profiling of monocytes might help to ease the discovery of new biomarkers and to screen and monitor patients. 1 Lyons et al., BMC Genomics (2007), 8:64.

scholarly journals CellMeSH: Probabilistic Cell-Type Identification Using Indexed Literature

2020 ◽  
Author(s):  
Shunfu Mao ◽  
Yue Zhang ◽  
Georg Seelig ◽  
Sreeram Kannan
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Probabilistic Method ◽  
Expression Patterns ◽  
Cell Types ◽  
Cellular Systems ◽  
Biological Knowledge ◽  
Specific Gene ◽  
Cell Type ◽  
Link Type

AbstractSingle-cell RNA sequencing (scRNA-seq) is widely used for analyzing gene expression in multi-cellular systems and provides unprecedented access to cellular heterogeneity. scRNA-seq experiments aim to identify and quantify all cell types present in a sample. Measured single-cell transcriptomes are grouped by similarity and the resulting clusters are mapped to cell types based on cluster-specific gene expression patterns. While the process of generating clusters has become largely automated, annotation remains a laborious ad-hoc effort that requires expert biological knowledge. Here, we introduce CellMeSH - a new automated approach to identifying cell types based on prior literature. CellMeSH combines a database of gene-cell type associations with a probabilistic method for database querying. The database is constructed by automatically linking gene and cell type information from millions of publications using existing indexed literature resources. Compared to manually constructed databases, CellMeSH is more comprehensive and scales automatically. The probabilistic query method enables reliable information retrieval even though the gene-cell type associations extracted from the literature are necessarily noisy. CellMeSH achieves up to 60% top-1 accuracy and 90% top-3 accuracy in annotating the cell types on a human dataset, and up to 58.8% top-1 accuracy and 88.2% top-3 accuracy on three mouse datasets, which is consistently better than existing approaches.AvailabilityWeb server: https://uncurl.cs.washington.edu/db_query and API: https://github.com/shunfumao/cellmesh

scholarly journals Analysis of the transcriptome of bovine endometrial cells isolated by laser micro-dissection (1): specific signatures of stromal, glandular and luminal epithelial cells

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Wiruntita Chankeaw ◽  
Sandra Lignier ◽  
Christophe Richard ◽  
Theodoros Ntallaris ◽  
Mariam Raliou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Localization ◽  
Expression Profiles ◽  
Cell Types ◽  
Molecular Signature ◽  
Receptor Protein ◽  
Specific Gene ◽  
Specific Cell ◽  
Biological Processes ◽  
Endometrial Cells

Abstract Background A number of studies have examined mRNA expression profiles of bovine endometrium at estrus and around the peri-implantation period of pregnancy. However, to date, these studies have been performed on the whole endometrium which is a complex tissue. Consequently, the knowledge of cell-specific gene expression, when analysis performed with whole endometrium, is still weak and obviously limits the relevance of the results of gene expression studies. Thus, the aim of this study was to characterize specific transcriptome of the three main cell-types of the bovine endometrium at day-15 of the estrus cycle. Results In the RNA-Seq analysis, the number of expressed genes detected over 10 transcripts per million was 6622, 7814 and 8242 for LE, GE and ST respectively. ST expressed exclusively 1236 genes while only 551 transcripts were specific to the GE and 330 specific to LE. For ST, over-represented biological processes included many regulation processes and response to stimulus, cell communication and cell adhesion, extracellular matrix organization as well as developmental process. For GE, cilium organization, cilium movement, protein localization to cilium and microtubule-based process were the only four main biological processes enriched. For LE, over-represented biological processes were enzyme linked receptor protein signaling pathway, cell-substrate adhesion and circulatory system process. Conclusion The data show that each endometrial cell-type has a distinct molecular signature and provide a significantly improved overview on the biological process supported by specific cell-types. The most interesting result is that stromal cells express more genes than the two epithelial types and are associated with a greater number of pathways and ontology terms.

scholarly journals Histone modifications form a cell-type-specific chromosomal bar code that persists through the cell cycle

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
John A. Halsall ◽  
Simon Andrews ◽  
Felix Krueger ◽  
Charlotte E. Rutledge ◽  
Gabriella Ficz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Histone Modifications ◽  
Expression Patterns ◽  
Cell Types ◽  
Cell Type ◽  
Bar Code ◽  
Genes Encoding ◽  
Cell Type Specific ◽  
Rolling Windows

AbstractChromatin configuration influences gene expression in eukaryotes at multiple levels, from individual nucleosomes to chromatin domains several Mb long. Post-translational modifications (PTM) of core histones seem to be involved in chromatin structural transitions, but how remains unclear. To explore this, we used ChIP-seq and two cell types, HeLa and lymphoblastoid (LCL), to define how changes in chromatin packaging through the cell cycle influence the distributions of three transcription-associated histone modifications, H3K9ac, H3K4me3 and H3K27me3. We show that chromosome regions (bands) of 10–50 Mb, detectable by immunofluorescence microscopy of metaphase (M) chromosomes, are also present in G1 and G2. They comprise 1–5 Mb sub-bands that differ between HeLa and LCL but remain consistent through the cell cycle. The same sub-bands are defined by H3K9ac and H3K4me3, while H3K27me3 spreads more widely. We found little change between cell cycle phases, whether compared by 5 Kb rolling windows or when analysis was restricted to functional elements such as transcription start sites and topologically associating domains. Only a small number of genes showed cell-cycle related changes: at genes encoding proteins involved in mitosis, H3K9 became highly acetylated in G2M, possibly because of ongoing transcription. In conclusion, modified histone isoforms H3K9ac, H3K4me3 and H3K27me3 exhibit a characteristic genomic distribution at resolutions of 1 Mb and below that differs between HeLa and lymphoblastoid cells but remains remarkably consistent through the cell cycle. We suggest that this cell-type-specific chromosomal bar-code is part of a homeostatic mechanism by which cells retain their characteristic gene expression patterns, and hence their identity, through multiple mitoses.

Sign in / Sign up

Export Citation Format

Share Document