High-resolution Gene Expression Profiling Research Articles

Spatial Transcriptomics of Tissue-Based Immune Response to Acute Graft-Versus-Host Disease of the Lower Gastrointestinal Tract

Background: Corticosteroid resistant acute graft-versus-host disease (GVHD) of the lower gastrointestinal (GI) tract is a leading cause of morbidity and mortality after allogeneic hematopoietic cell transplantation. We hypothesized that distinct gene expression profiles exist within affected GI tissue at GVHD diagnosis and may be associated with treatment outcomes. Methods: Unstained tissue sections from 33 patients with biopsy-confirmed acute lower GI GVHD were used for spatial transcriptomics using the NanoString GeoMxTM Digital Spatial Profiler (DSP) platform. Fluorescent morphology markers (PanCK, CD45 and CD31) were used to visualize the epithelial, immune and endothelial compartments and guide capture of RNA expression profiles using the GeoMxTM Human Whole Transcriptome Atlas (18,676 genes). A total of 739 areas of interest (AOIs) were sampled across the 33 patients with a total of 57,960 immune, 37,610 epithelial, and 2298 vascular endothelial cells analyzed (average of 1756.4 immune, 1139.7 epithelial and 69.6 endothelial cells per case). The gene specific oligos were quantified using Illumina's i5 x i7 dual-indexing system and sequenced on the Illumina NextSeq 500 using a 2 x 75 MidOutput v2.5 flow cell. The FASTQ files were processed to generate target probe-specific count files and saved in DCC format. Gene expression files were normalized per NanoString protocol. All unsupervised clustering and differential expression were done in Bioconductor in the R statistical computing space. Results: The gene expression data for each AOI of immune, epithelial, and endothelial cells were normalized and the top 500 most variable genes were used for unsupervised hierarchical clustering to obtain an unbiased classification of different subtypes. There were two clear major AOI clusters for each of the cellular compartments with immune clustering shown in Figure 1A. The left immune cluster (IC1) and the right immune cluster (IC2) were then evaluated for association with clinical GVHD outcomes. IC1 had an over-representation of patients with steroid sensitive GVHD (Fisher exact p value = <0.0001) and AOIs with low grade pathology (Fisher exact p value = 0.031). To obtain gene level differences between IC1 and IC2, differential expression was performed using a Wilcoxon Rank Sum test and volcano plots were generated to illustrate the most differentially expressed genes across the visual AOI-based clusters (Figure 1B). Genes with an adjusted p-value of 0.05 for association with the particular arm of the volcano plot and at least a 2-fold change over the other cluster were considered significant. Gene set enrichment analysis (GSEA) using curated datasets from MSigDB was performed and identified that IC1 genes were enriched for IFNγ response (q value = 2.99e-5), TNFα signaling (q value = 2.99e-5) and inflammatory response (q value = 0.0063). These IC1 differentially expressed genes included CD74 (835 vs. 361.6 mean normalized gene transcripts), LYZ, β2-microglobulin, C1QB and CD68. IC2, on the other hand, had a prominent exhausted/immunosuppressive signature significantly enriched for Th17 cell genes (q value = 0.027) by GSEA. Notable genes that were statistically significant were FCF1 (152.3 vs. 74 mean normalized transcripts) and USP17L11 (78.3 vs. 36.4 mean normalized transcripts). Extension of this analysis to the epithelial (EC) and vascular endothelial (VC) cell compartments also identified distinct clustering with both having an inflamed (EC1 and VC1) and a basal-like state (EC2 and VC2). Interestingly, the inflamed epithelial cells (EC2) associated with immunosuppressive IC2 immune cells (Fisher exact p-value = 0.006), but inflamed vascular endothelium (VC1) associated with the pro-inflammatory IC1 immune cells (Fisher exact p-value = 0.0005). Conclusion: Spatial transcriptomics provides high resolution gene expression profiles in distinct cellular compartments in human acute GI GVHD samples and provides a better understanding of the relationship of the immune response with epithelial and vascular endothelial cell phenotypes. Initial analysis demonstrates that an inflammatory immune signature is associated with steroid responsive acute GI GVHD and an exhausted phenotype with steroid resistance. Future studies are needed to confirm the predictive value of specific gene expression profiles as biomarkers of corticosteroid response at diagnostic biopsy. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Zooming in on liver zonation.

Felmlee, Daniel J. Ph.D.1; Grün, Dominic Ph.D.2; Baumert, Thomas F. M.D3,4 Author Information

High-Resolution Gene Expression Profiling of RNA Synthesis, Processing, and Decay by Metabolic Labeling of Newly Transcribed RNA Using 4-Thiouridine.

Cellular RNA levels are orchestrated by highly regulated processes involving RNA synthesis (transcription), processing (e.g., splicing, polyadenylation, transport), and degradation. Profiling these changes provides valuable information on the regulation of gene expression. Total cellular RNA is a poor template for revealing short-term changes in gene expression, alterations in RNA decay rates, and the kinetics of RNA processing as well as the differentiation thereof. Here, we describe the metabolic labeling and purification of newly transcribed RNA with 4-thiouridine, by which these limitations are overcome.

Abstract 160: Identification of the carcinoma and immune cells in the breast cancer by single-cell RNA sequencing

Abstract Summary: Breast cancer is a heterogeneous type of cancer accompanying extensive immune cell infiltration. Although its mortality rate has been decreasing with early diagnosis and introduction of molecular targeted therapies, it is still one of the world leading cause of cancer death in women. In breast cancer, molecular subtyping is used for the patient stratification and treatment decisions, emphasizing the importance of inter-patient tumoral heterogeneity in the tumor cell behavior. Tumor cells within a patient may also manifest intra-tumoral heterogeneity, which may cause treatment resistance. Single cell gene expression profiling would reveal both inter- and intra-tumoral heterogeneity in breast cancer encompassing tumor cells and associated stromal and immune cells. Experimental Process: From 4 different subtype primary breast cancer and 2 lymph node metastases, single cells were captured and amplified through C1™Single-cell Auto Prep System (Fluidigm) with the SMARTer Ultra Low RNA Kit. Sequencing libraries were constructed with the Nextera XT DNA sample Prep Kit and sequenced through a Hiseq2500 (Illumina) as 100-bp paired end mode of the TruSeq Rapid PE Cluster kit and Truseq Rapid SBS kit. Computational Process: RNA sequencing reads were aligned to the modified human genome reference using 2-pass mode of STAR_2.4.0b, and transcript per million (TPM) values were obtained as the relative gene expression levels of single cells through RSEM v1.2.17. Results: As most breast cancers originate from the mammary epithelium, we distinguished carcinoma cells from associated non-tumor cells by epithelial cell adhesion molecule (EPCAM) signature genes. We validated the distinction with chromosomal gene expression patterns and gene set enrichment analyses using tumor, stromal, or immune genesets. With or without removal of non-tumor cells, TNBC tumor cells showed the highest gene expression heterogeneity, recapitulating the known inter-patient heterogeneity. TNBC tumor cells from a single patient were categorized into 6 different TNBC-subtypes, further demonstrating intra-tumoral heterogeneity. In addition, immune cells identified in the TNBC tumor were naïve B cells and regulatory T cells, suggesting non-activated status of the immune system. Conclusions: The high resolution gene expression profiling revealed features of breast cancer transcriptome which may provide clues for molecular directed therapies targeting the tumor or the immune compartment. Citation Format: Woosung Chung, Hye Hyeon Eum, Kyu-Tae Kim, Kyung-Min Lee, Arum Jo, WonShik Han, Hae-Ock Lee, Woong-Yang Park. Identification of the carcinoma and immune cells in the breast cancer by single-cell RNA sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 160.

High-resolution gene expression profiling using RNA sequencing in patients with inflammatory bowel disease and in mouse models of colitis.

Proper interpretation of data from preclinical animal studies requires thorough knowledge of the pathophysiology of both the human disease and animal models. In this study, the expression of inflammatory bowel disease [IBD]-associated genes was characterised in mouse models of colitis to examine the underlying molecular pathways and assess the similarity between the experimental models and human disease. RNA sequencing was performed on colon biopsies from Crohn's disease [CD] patients, ulcerative colitis [UC] patients and non-IBD controls. Genes shown to be significantly dysregulated in human IBD were used to study gene expression in colons from a piroxicam-accelerated colitis interleukin-10 knockout [PAC IL-10 k.o.], an adoptive transfer [AdTr] and a dextran sulfate sodium [DSS] colitis mouse model. Of 115 literature-defined genes linked to IBD, 92 were significantly differentially expressed in inflamed mucosa of CD and/or UC patients compared with non-IBD controls. The most upregulated genes were shared by both diseases, including REG1A, LCN2, NOS2, CXCL1-2, and S100A9. Of those 92 IBD-associated genes, 71 [77%] were significantly dysregulated in PAC IL-10 k.o. mice, whereas 59 [64%] were significantly dysregulated in AdTr mice compared with wild-type controls. Some of the most upregulated genes, including S100a8-9, Nos2, and Lcn2, were shared by the colitis models and correlated with disease activity. IBD and experimental murine colitis have a high degree of similarity in the colonic transcriptional profile, probably secondary to non-specific inflammatory processes. However, differences do exist between models, emphasising the need for careful selection and interpretation of qualified animal models in preclinical research.

Saccharomyces cerevisiae transcriptional reprograming due to bacterial contamination during industrial scale bioethanol production.

BackgroundThe bioethanol production system used in Brazil is based on the fermentation of sucrose from sugarcane feedstock by highly adapted strains of the yeast Saccharomyces cerevisiae. Bacterial contaminants present in the distillery environment often produce yeast-bacteria cellular co-aggregation particles that resemble yeast-yeast cell adhesion (flocculation). The formation of such particles is undesirable because it slows the fermentation kinetics and reduces the overall bioethanol yield.ResultsIn this study, we investigated the molecular physiology of one of the main S. cerevisiae strains used in Brazilian bioethanol production, PE-2, under two contrasting conditions: typical fermentation, when most yeast cells are in suspension, and co-aggregated fermentation. The transcriptional profile of PE-2 was assessed by RNA-seq during industrial scale fed-batch fermentation. Comparative analysis between the two conditions revealed transcriptional profiles that were differentiated primarily by a deep gene repression in the co-aggregated samples. The data also indicated that Lactobacillus fermentum was likely the main bacterial species responsible for cellular co-aggregation and for the high levels of organic acids detected in the samples.ConclusionsHere, we report the high-resolution gene expression profiling of strain PE-2 during industrial-scale fermentations and the transcriptional reprograming observed under co-aggregation conditions. This dataset constitutes an important resource that can provide support for further development of this key yeast biocatalyst.Electronic supplementary materialThe online version of this article (doi:10.1186/s12934-015-0196-6) contains supplementary material, which is available to authorized users.

De novo transcriptome analysis and highly sensitive digital gene expression profiling of Calliphora vicina (Diptera: Calliphoridae) pupae using MACE (Massive Analysis of cDNA Ends)

Determining a post-mortem interval using the weight or length of blow fly larvae to calculate the insect's age is well established. However, to date, there are only a handful studies dealing with age estimation of blow fly pupae, in which weight or length cannot be used as a relevant parameter. The analysis of genetic markers, which indicate a certain developmental stage, can extend the period for a successful post-mortem interval determination. In order to break new ground in the field of age determination of forensic relevant blow flies, we performed a de novo transcriptome analysis of Calliphora vicina pupae at 15 different developmental stages. Obtained data serve as base to establish molecular age determination techniques. We used a new, deeper, and more cost-effective digital gene expression profiling method called MACE (Massive Analysis of cDNA Ends). We generated 15 libraries out of 15 developmental stages, with 3–8 million reads per library. In total, 53,539 distinct transcripts were detected, and 7548 were annotated to known insect genes. The analysis provides high-resolution gene expression profiles of all covered transcripts, which were used to identify differentially expressed genetic markers as candidates for a molecular age estimation of C. vicina pupae. Moreover, the analysis allows insights into gene activity of pupal development and the relationship between different genes interesting for insect development in general.

Abstract C230: A platform for discovery of novel stem cell modulators and subsequent development of therapeutic targets.

Abstract In recent years, there has been a significant and growing interest in specific pathways the human body utilizes in response to damage and their exploitation to induce cell proliferation, differentiation and apoptosis. Epistem's Novel Therapies division has created a discovery platform to allow identification of novel soluble regulators for development of therapeutic targets in oncology, regenerative medicine, and gastrointestinal diseases. Target discovery and identification starts with a known stem cell model and the creation of a disease system in vivo to identify potential stem cell markers. A damage response model of the gastrointestinal tract for stem cell proliferation and apoptosis post-irradiation describes the different phases of the cell recovery process. Post-irradiation, the stem cells, which are located at the base of the intestinal crypt, undergo apoptosis, followed by a rapid phase of regeneration, resulting in an ‘overshoot’ in crypt cell numbers, with homeostasis finally achieved by a ‘shut off’ phase with a decrease in proliferation to basal levels. Using high resolution gene expression profiling of dissected crypts (upper and lower), from small intestine and colon, isolated at various key time points post irradiation, we have identified many candidate novel stem cell regulators involved in damage response. Recombinant proteins have been produced; purified; and characterized, then tested using our proprietary in vitro model assays, looking for efficacy in cell proliferation, apoptosis and differentiation. Proteins that demonstrated robust and reproducible activities were then further evaluated using our industry standard in vivo intestinal stem cell function assays. Pharmocodynamic gene expression profiling was then applied to establish mechanism of action (MOA) linkages between in vitro and in vivo data. Having identified novel protein therapeutics, we are currently focused on pharmacotherapeutics that can modulate the identified pathways. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C230. Citation Format: Shaun Ainsworth, Sarah Hoyle, Aude-Marine Bonavita, Laura Kemp, Jo Read, Alan Murdoch, Lorna Woolford, Gino Miele, Cath Booth. A platform for discovery of novel stem cell modulators and subsequent development of therapeutic targets. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C230.

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene expression. Along with a better understanding of the involved molecular mechanisms, precise measurements of the underlying kinetics have become increasingly important. Here, these powerful methodologies face major limitations due to intrinsic properties of the template samples they study, i.e. total cellular RNA. In many cases changes in total cellular RNA occur either too slowly or too quickly to represent the underlying molecular events and their kinetics with sufficient resolution. In addition, the contribution of alterations in RNA synthesis, processing, and decay are not readily differentiated. We recently developed high-resolution gene expression profiling to overcome these limitations. Our approach is based on metabolic labeling of newly transcribed RNA with 4-thiouridine (thus also referred to as 4sU-tagging) followed by rigorous purification of newly transcribed RNA using thiol-specific biotinylation and streptavidin-coated magnetic beads. It is applicable to a broad range of organisms including vertebrates, Drosophila, and yeast. We successfully applied 4sU-tagging to study real-time kinetics of transcription factor activities, provide precise measurements of RNA half-lives, and obtain novel insights into the kinetics of RNA processing. Finally, computational modeling can be employed to generate an integrated, comprehensive analysis of the underlying molecular mechanisms.

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene expression. Along with a better understanding of the involved molecular mechanisms, precise measurements of the underlying kinetics have become increasingly important. Here, these powerful methodologies face major limitations due to intrinsic properties of the template samples they study, i.e. total cellular RNA. In many cases changes in total cellular RNA occur either too slowly or too quickly to represent the underlying molecular events and their kinetics with sufficient resolution. In addition, the contribution of alterations in RNA synthesis, processing, and decay are not readily differentiated. We recently developed high-resolution gene expression profiling to overcome these limitations. Our approach is based on metabolic labeling of newly transcribed RNA with 4-thiouridine (thus also referred to as 4sU-tagging) followed by rigorous purification of newly transcribed RNA using thiol-specific biotinylation and streptavidin-coated magnetic beads. It is applicable to a broad range of organisms including vertebrates, Drosophila, and yeast. We successfully applied 4sU-tagging to study real-time kinetics of transcription factor activities, provide precise measurements of RNA half-lives, and obtain novel insights into the kinetics of RNA processing. Finally, computational modeling can be employed to generate an integrated, comprehensive analysis of the underlying molecular mechanisms.

Deciphering the modulation of gene expression by type I and II interferons combining 4sU-tagging, translational arrest and in silico promoter analysis.

Interferons (IFN) play a pivotal role in innate immunity, orchestrating a cell-intrinsic anti-pathogenic state and stimulating adaptive immune responses. The complex interplay between the primary response to IFNs and its modulation by positive and negative feedback loops is incompletely understood. Here, we implement the combination of high-resolution gene-expression profiling of nascent RNA with translational inhibition of secondary feedback by cycloheximide. Unexpectedly, this approach revealed a prominent role of negative feedback mechanisms during the immediate (≤60 min) IFNα response. In contrast, a more complex picture involving both negative and positive feedback loops was observed on IFNγ treatment. IFNγ-induced repression of genes associated with regulation of gene expression, cellular development, apoptosis and cell growth resulted from cycloheximide-resistant primary IFNγ signalling. In silico promoter analysis revealed significant overrepresentation of SP1/SP3-binding sites and/or GC-rich stretches. Although signal transducer and activator of transcription 1 (STAT1)-binding sites were not overrepresented, repression was lost in absence of STAT1. Interestingly, basal expression of the majority of these IFNγ-repressed genes was dependent on STAT1 in IFN-naïve fibroblasts. Finally, IFNγ-mediated repression was also found to be evident in primary murine macrophages. IFN-repressed genes include negative regulators of innate and stress response, and their decrease may thus aid the establishment of a signalling perceptive milieu.

Molecular Aspects of Breast Cancer Metastasis to the Brain

Our knowledge of the biology underlying the development of brain metastases (BM) from breast cancer has improved over the last decade due to large clinical epidemiological studies, animal models of metastasis, and the use of high-resolution gene expression profiling technologies. However, there are still major gaps in our understanding of the mechanisms utilized by breast cancer cells to colonize the brain microenvironment, thus our arsenal of therapies remains relatively nonspecific, and the prognosis for breast cancer patients with BM remains poor. Additional insights into these mechanisms are necessary to facilitate the development of new preventive and curative therapeutic regimens to block this fatal disease. This paper aims to provide a general overview for the readers of what has been achieved in this field of research and its translation into clinical practice to date and to highlight exciting new areas of research that promise to inform the development of new targeted therapies for BM.

Gene expression in early and progression phases of autosomal dominant polycystic kidney disease

BackgroundLittle is known about the genes involved in the initial cyst formation and disease progression in autosomal dominant polycystic kidney disease (ADPKD); however, such knowledge is necessary to explore therapeutic avenues for this common inherited kidney disease.FindingsTo uncover the genetic determinants and molecular mechanisms of ADPKD, we analyzed 4-point time-series DNA microarrays from Pkd1L3/L3 mice to generate high resolution gene expression profiles at different stages of disease progression. We found different characteristic gene expression signatures in the kidneys of Pkd1L3/L3 mice compared to age-matched controls during the initial phase of the disease. By postnatal week 1, the Pkd1L3/L3 kidney already had a distinctive gene expression pattern different from the corresponding normal controls.ConclusionThe genes differentially expressed, either induced or repressed, in ADPKD are important in immune defense, cell structure and motility, cellular proliferation, apoptosis and metabolic processes, and include members of three pathways (Wnt, Notch, and BMP) involved in morphogenetic signaling. Further analysis of the gene expression profiles from the early stage of cystogenesis to end stage disease identified a possible gene network involved in the pathogenesis of ADPKD.

High-Throughput RNA Isolation Technologies. New Tools for High-Resolution Gene Expression Profiling in Plant Systems

The complete genome sequences of two representative species of flowering plants, the monocot rice ( Oryza sativa ) and the eudicot Arabidopsis ( Arabidopsis thaliana ), provide us with a new opportunity to understand developmental and physiological events at the genome level ([Arabidopsis Genome

Candidate tumor-suppressor genes on chromosome arm 8p in early-onset and high-grade breast cancers.

Loss of genetic material from chromosome arm 8p occurs commonly in breast carcinomas, suggesting that this region is the site of one or more tumor-suppressor genes (TSGs). Comparative genomic hybridization analysis showed that 8p loss is more common in breast cancers from pre-menopausal compared with post-menopausal patients, as well as in high-grade breast cancers, regardless of the menopausal status. Subsequent high-resolution gene expression profiling of genes mapped to chromosome arm 8p, on an extended cohort of clinical tumor samples, indicated a similar dichotomy of breast cancer clinicopathologic types. Some of these genes showed differential downregulation in early-onset and later-onset, high-grade cancers compared with lower-grade, later-onset cancers. Three such genes were analysed further by in situ technologies, performed on tissue microarrays representing breast tumor and normal tissue samples. PCM1, which encodes a centrosomal protein, and DUSP4/MKP-2, which encodes a MAP kinase phosphatase, both showed frequent gene and protein loss in carcinomas. In contrast, there was an excess of cases showing loss of expression in the absence of reduced gene copy number of SFRP1, which encodes a dominant-negative receptor for Wnt-family ligands. These candidate TSGs may constitute some of the molecular drivers of chromosome arm 8p loss in breast carcinogenesis.