A Shared Gene-Expression Signature in Innate-Like Lymphocytes.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3903-3903
Author(s):  
Tetsuya Yamagata ◽  
Christophe Benoist ◽  
Diane Mathis
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Signature ◽  
Cell Types ◽  
Self Recognition ◽  
Distinct Cell ◽  
Invariant Structures ◽  
Small Set ◽  
High Degree

Abstract Innate and adaptive immunity are the two major arms of the immune system. They rely on very distinct cell-types, primarily distinguished by the source of diversity for non-self recognition, of germline or somatic origin. There exists, however, a subset of lymphocytes whose receptors require rearrangement but result in semi-invariant structures with a high degree of self-specificity. We hypothesized that these innate-like lymphocytes might share a common gene transcription signature. To test this notion, we made pair-wise comparisons of the gene-expression profiles of innate-like lymphocytes and closely paired adaptive system counterparts (NKT vs. CD4T, CD8ααT vs. CD8αβT, B1 vs. B2), and bioinformatically extracted common features and common genes distinguishing innate from adaptive cell-types. A statistically significant “innate signature” was indeed distilled, composed of a small set of genes over- and under-expressed in innate vs. adaptive lymphocytes. Particularly intriguing was the high representation of interferon-inducible GTPases crucial for resistance against intracellular pathogens, and of small G proteins involved in intracellular vacuole maturation and trafficking. Overall, this combined expression pattern can thus be designated as an “innate signature” among lymphocytes.

scholarly journals Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bing He ◽  
Ping Chen ◽  
Sonia Zambrano ◽  
Dina Dabaghie ◽  
Yizhou Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Human Kidney ◽  
Cell Types ◽  
Model Organisms ◽  
Mural Cell ◽  
Glomerular Cell ◽  
Individual Gene ◽  
The Individual

AbstractMolecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), are missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we use Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis reveals genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells. Importantly, we detect heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observe remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

Gene Expression Regulation underlying Osteo-, Adipo-, and Chondro-Genic Lineage Commitment of Human Mesenchymal Stem Cells

2013 ◽  
pp. 76-94 ◽  
Author(s):  
Ana M. Sotoca ◽  
Michael Weber ◽  
Everardus J. J. van Zoelen
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Gene Expression Regulation ◽  
Expression Profiles ◽  
Human Mesenchymal Stem Cells ◽  
Gene Expression Profiles ◽  
Stem Cell Differentiation ◽  
Cell Types ◽  
Lineage Commitment

Human mesenchymal stem cells have a high potential in regenerative medicine. They can be isolated from a variety of adult tissues, including bone marrow, and can be differentiated into multiple cell types of the mesodermal lineage, including adipocytes, osteocytes, and chondrocytes. Stem cell differentiation is controlled by a process of interacting lineage-specific and multipotent genes. In this chapter, the authors use full genome microarrays to explore gene expression profiles in the process of Osteo-, Adipo-, and Chondro-Genic lineage commitment of human mesenchymal stem cells.

scholarly journals Aortic heterogeneity across segments and under high fat/salt/glucose conditions at the single-cell level

2020 ◽  
Vol 7 (5) ◽  
pp. 881-896 ◽  
Author(s):  
Dongxu He ◽  
Aiqin Mao ◽  
Chang-Bo Zheng ◽  
Hao Kan ◽  
Ka Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
The Body ◽  
Dietary Salt ◽  
High Fat ◽  
High Blood Glucose ◽  
Thoracic And Abdominal

Abstract The aorta, with ascending, arch, thoracic and abdominal segments, responds to the heartbeat, senses metabolites and distributes blood to all parts of the body. However, the heterogeneity across aortic segments and how metabolic pathologies change it are not known. Here, a total of 216 612 individual cells from the ascending aorta, aortic arch, and thoracic and abdominal segments of mouse aortas under normal conditions or with high blood glucose levels, high dietary salt, or high fat intake were profiled using single-cell RNA sequencing. We generated a compendium of 10 distinct cell types, mainly endothelial (EC), smooth muscle (SMC), stromal and immune cells. The distributions of the different cells and their intercommunication were influenced by the hemodynamic microenvironment across anatomical segments, and the spatial heterogeneity of ECs and SMCs may contribute to differential vascular dilation and constriction that were measured by wire myography. Importantly, the composition of aortic cells, their gene expression profiles and their regulatory intercellular networks broadly changed in response to high fat/salt/glucose conditions. Notably, the abdominal aorta showed the most dramatic changes in cellular composition, particularly involving ECs, fibroblasts and myeloid cells with cardiovascular risk factor-related regulons and gene expression networks. Our study elucidates the nature and range of aortic cell diversity, with implications for the treatment of metabolic pathologies.

scholarly journals Purity and Enrichment of Laser-Microdissected Midbrain Dopamine Neurons

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Amanda L. Brown ◽  
Trevor A. Day ◽  
Christopher V. Dayas ◽  
Doug W. Smith
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Dopamine Neuron ◽  
Dopamine Neurons ◽  
Acid Decarboxylase ◽  
Cell Groups ◽  
Midbrain Dopamine ◽  
High Degree ◽  
Midbrain Dopamine Neurons

The ability to microdissect individual cells from the nervous system has enormous potential, as it can allow for the study of gene expression in phenotypically identified cells. However, if the resultant gene expression profiles are to be accurately ascribed, it is necessary to determine the extent of contamination by nontarget cells in the microdissected sample. Here, we show that midbrain dopamine neurons can be laser-microdissected to a high degree of enrichment and purity. The average enrichment for tyrosine hydroxylase (TH) gene expression in the microdissected sample relative to midbrain sections was approximately 200-fold. For the dopamine transporter (DAT) and the vesicular monoamine transporter type 2 (Vmat2), average enrichments were approximately 100- and 60-fold, respectively. Glutamic acid decarboxylase (Gad65) expression, a marker for GABAergic neurons, was several hundredfold lower than dopamine neuron-specific genes. Glial cell and glutamatergic neuron gene expression were not detected in microdissected samples. Additionally, SN and VTA dopamine neurons had significantly different expression levels of dopamine neuron-specific genes, which likely reflects functional differences between the two cell groups. This study demonstrates that it is possible to laser-microdissect dopamine neurons to a high degree of cell purity. Therefore gene expression profiles can be precisely attributed to the targeted microdissected cells.

Genomics and Systems Biology.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. sci-51-sci-51
Author(s):  
Todd R. Golub
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Biological Networks ◽  
High Throughput Screening ◽  
Expression Profiles ◽  
Low Cost ◽  
Gene Expression Profiles ◽  
Gene Expression Signature ◽  
Small Molecule Libraries ◽  
Approved Drugs

Genomics holds particular potential for the elucidation of biological networks that underlie disease. For example, gene expression profiles have been used to classify human cancers, and have more recently been used to predict graft rejection following organ transplantation. Such signatures thus hold promise both as diagnostic approaches and as tools with which to dissect biological mechanism. Such systems-based approaches are also beginning to impact the drug discovery process. For example, it is now feasible to measure gene expression signatures at low cost and high throughput, thereby allowing for the screening libraries of small molecule libraries in order to identify compounds capable of perturbing a signature of interest (even if the critical drivers of that signature are not yet known). This approach, known as Gene Expression-Based High Throughput Screening (GE-HTS), has been shown to identify candidate therapeutic approaches in AML, Ewing sarcoma, and neuroblastoma, and has identified tool compounds capable of inhibiting PDGF receptor signaling. A related approach, known as the Connectivity Map (www.broad.mit.edu/cmap) attempts to use gene expression profiles as a universal language with which to connect cellular states, gene product function, and drug action. In this manner, a gene expression signature of interest is used to computationally query a database of gene expression profiles of cells systematically treated with a large number of compounds (e.g., all off-patent FDA-approved drugs), thereby identifying potential new applications for existing drugs. Such systems level approaches thus seek chemical modulators of cellular states, even when the molecular basis of such altered states is unknown.

Identification of synthetic lethal interactions with the BRAF oncogene in colorectal cancer.

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 403-403
Author(s):  
Loredana Vecchione ◽  
Valentina Gambino ◽  
Giovanni d'Ario ◽  
Sun Tian ◽  
Iris Simon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Signature ◽  
Gene Signature ◽  
Braf V600e ◽  
P Value ◽  
Synthetic Lethal ◽  
Braf Mutant

403 Background: Approximately 8-15% of colorectal (CRC) patients carry an activating mutation in BRAF. This CRC subtype is associated with poor outcome and with resistance, both to chemotherapeutic treatments and to tailored drugs. We recently showed that BRAF (V600E) colon cancers (CCs) have a characteristic gene expression signature (1, 2) which is found also in subsets of KRAS mutant and KRAS-BRAF wild type (WT2) tumors. Tumors having this gene signature, referred as “BRAF-like”, have a similar poor prognosis irrespective of the presence of the BRAF (V600E) mutation. By using a shRNA-based genetic screen in BRAF mutant CC cell lines we aimed to identify genes and pathways necessary for survival and growth of BRAFmutant CC. Such studies may reveal additional targets for therapy and potentially provide new biomarkers for patient stratification Methods: We identified 363 genes that are selectively overexpressed in BRAF mutant tumors as compared to WT2 type tumors, based on gene expression profiles of the PETACC3 (1) and Agendia (2) datasets. The TRC human genome-wide shRNA collection (TRC-Hs1.0) was used to generate a 1815 hairpins sub-library targeting those identified genes (BRAF library). BRAF(V600E) CC cell lines were infected with the BRAF library and screened for shRNAs that cause lethality. LIM1215 CC cell line (WT2) was used as a control. Cells stably expressing the shRNA library were cultured for 13 days, after which shRNAs were recovered by PCR. Deep sequencing was applied to determine the specific depletion of shRNA in BRAF(V600E) cells as compared to LIM1215 cells Results: Candidate genes were identified by using following filtering criteria: depletion in BRAF(V600E) cells by at least 50% and depletion in BRAF(V600E) cells 1, 5-fold higher than in control cells with the corresponding p-value to be ≤ 0.1. A total of 34 genes met our criteria of which 6 genes were presented with more than one hairpin and were concordant across the cell lines selected for validation. Conclusions: We identified candidate synthetic lethal genes in BRAF mutant CC cell lines. Functional analysis is ongoing. Data will be presented. References 1. J Clin Oncol 2012 Apr 20;30(12):1288-9 2. Gut (2012). doi:10.1136/gutjnl-2012-302423

scholarly journals Gene Expression in Porphyromonas gingivalis after Contact with Human Epithelial Cells

2005 ◽  
Vol 73 (4) ◽  
pp. 2327-2335 ◽  
Author(s):  
Yumiko Hosogi ◽  
Margaret J. Duncan
Keyword(s):  
Gene Expression ◽  
Epithelial Cells ◽  
Porphyromonas Gingivalis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Adverse Conditions ◽  
Human Epithelial Cells ◽  
Host Epithelium ◽  
Shock Proteins

ABSTRACT Porphyromonas gingivalis, a gram-negative oral anaerobe, is strongly associated with adult periodontitis. The adherence of the organism to host epithelium signals changes in both cell types as bacteria initiate infection and colonization and epithelial cells rally their defenses. We hypothesized that the expression of a defined set of P. gingivalis genes would be consistently up-regulated during infection of HEp-2 human epithelial cells. P. gingivalis genome microarrays were used to compare the gene expression profiles of bacteria that adhered to HEp-2 cells and bacteria that were incubated alone. Genes whose expression was temporally up-regulated included those involved in the oxidative stress response and those encoding heat shock proteins that are essential to maintaining cell viability under adverse conditions. The results suggest that contact with epithelial cells induces in P. gingivalis stress-responsive pathways that promote the survival of the bacterium.

scholarly journals Self-reporting transposons enable simultaneous readout of gene expression and transcription factor binding in single cells

2019 ◽  
Author(s):  
Arnav Moudgil ◽  
Michael N. Wilkinson ◽  
Xuhua Chen ◽  
June He ◽  
Alex J. Cammack ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Single Cell ◽  
Binding Sites ◽  
Expression Profiles ◽  
Single Cells ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Specific Cell

AbstractIn situ measurements of transcription factor (TF) binding are confounded by cellular heterogeneity and represent averaged profiles in complex tissues. Single cell RNA-seq (scRNA-seq) is capable of resolving different cell types based on gene expression profiles, but no technology exists to directly link specific cell types to the binding pattern of TFs in those cell types. Here, we present self-reporting transposons (SRTs) and their use in single cell calling cards (scCC), a novel assay for simultaneously capturing gene expression profiles and mapping TF binding sites in single cells. First, we show how the genomic locations of SRTs can be recovered from mRNA. Next, we demonstrate that SRTs deposited by the piggyBac transposase can be used to map the genome-wide localization of the TFs SP1, through a direct fusion of the two proteins, and BRD4, through its native affinity for piggyBac. We then present the scCC method, which maps SRTs from scRNA-seq libraries, thus enabling concomitant identification of cell types and TF binding sites in those same cells. As a proof-of-concept, we show recovery of cell type-specific BRD4 and SP1 binding sites from cultured cells. Finally, we map Brd4 binding sites in the mouse cortex at single cell resolution, thus establishing a new technique for studying TF biology in situ.

scholarly journals Information topology of gene expression profile in dopaminergic neurons

2017 ◽  
Author(s):  
Mónica Tapia Pacheco ◽  
Pierre Baudot ◽  
Martial A. Dufour ◽  
Christine Formisano-Tréziny ◽  
Simone Temporal ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dopaminergic Neurons ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Combinatorial Structure ◽  
Maximum Information ◽  
Midbrain Neurons ◽  
High Degree ◽  
Multivariate Mutual Information ◽  
Gene Expression Levels

SUMMARY PARAGRAPHExtracting high-degree interactions and dependences between variables (pairs, triplets, … k-tuples) is a challenge posed by all omics approaches1, 2. Here we used multivariate mutual information (Ik) analysis3 on single-cell retro-transcription quantitative PCR (sc-RTqPCR) data obtained from midbrain neurons to estimate the k-dimensional topology of their gene expression profiles. 41 mRNAs were quantified and statistical dependences in gene expression levels could be fully described for 21 genes: Ik analysis revealed a complex combinatorial structure including modules of pairs, triplets (up to 6-tuples) sharing strong positive, negative or zero Ik, corresponding to co-varying, clustering and independent sets of genes, respectively. Therefore, Ik analysis simultaneously identified heterogeneity (negative Ik) of the cell population under study and regulatory principles conserved across the population (homogeneity, positive Ik). Moreover, maximum information paths enabled to determine the size and stability of such transcriptional modules. Ik analysis represents a new topological and statistical method of data analysis.

scholarly journals Bayesian log-normal deconvolution for enhanced in silico microdissection of bulk gene expression data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bárbara Andrade Barbosa ◽  
Saskia D. van Asten ◽  
Ji Won Oh ◽  
Arantza Farina-Sarasqueta ◽  
Joanne Verheij ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Expression Data ◽  
Cell Type ◽  
Expression Variability ◽  
Variable Nature ◽  
Log Normal

AbstractDeconvolution of bulk gene expression profiles into the cellular components is pivotal to portraying tissue’s complex cellular make-up, such as the tumor microenvironment. However, the inherently variable nature of gene expression requires a comprehensive statistical model and reliable prior knowledge of individual cell types that can be obtained from single-cell RNA sequencing. We introduce BLADE (Bayesian Log-normAl Deconvolution), a unified Bayesian framework to estimate both cellular composition and gene expression profiles for each cell type. Unlike previous comprehensive statistical approaches, BLADE can handle > 20 types of cells due to the efficient variational inference. Throughout an intensive evaluation with > 700 simulated and real datasets, BLADE demonstrated enhanced robustness against gene expression variability and better completeness than conventional methods, in particular, to reconstruct gene expression profiles of each cell type. In summary, BLADE is a powerful tool to unravel heterogeneous cellular activity in complex biological systems from standard bulk gene expression data.

Sign in / Sign up

Export Citation Format

Share Document