Defining the cistrome and quantitative transcriptome of virus-transformed cells using massively parallel sequencing

Lead Research Organisation: University of Edinburgh
Department Name: The Roslin Institute

Abstract

As in humans, many animals including chickens, develop cancer. However, unlike in humans, most of the cancers in chickens are caused by viruses. Marek's disease (MD) is a common disease of chickens involving paralysis and commonly death from the growth of highly malignant T lymphomas (cancers of white blood cells). MD is caused by a transmissible agent, Marek's disease virus (MDV). MDV is very contagious and is a major threat to the poultry industry worldwide. The estimated total loss from this disease worldwide is up to £ 2 billion. Presently, it is controlled by vaccination, and nearly 22 billion vaccine doses a year are used in an attempt to control the disease. Despite widespread vaccination, the threat from this disease is on the increase, and more fundamental studies to understand the mechanisms by which this virus cause cancer is needed to develop more effective control programmes. Another cancer inducing virus of chickens less common in the UK called Reticuloendotheliosis virus (REV) is a very good model for cancer. The advantage of using this virus for studying the mechanisms of cancer is that the experiments to induce cancer can be done on chicken cells collected from birds. We have used this model and examined the molecular changes to the cells while it is transformed into cancer cells. We have identified very important changes in the expression of genes and small 22-nucleotide microRNAs molecules between normal cancer cells, suggesting that these changes contribute to cancer. In this new grant proposal, to be carried out jointly between the Institute for Animal Health (Compton) and ARK-Genomics (Roslin Institute), we want to extend these studies to obtain detailed information on the changes in the expression of genes using the new RNA-Seq technology that will provide a much detailed comprehensive picture on the expression of genes during the transformation process. Similarly, we will also examine the sequences in the genomes where viral oncoproteins can directly bind to the DNA to change the gene expression to cause cancer. We aim to use this excellent model system and Marek's disease cancer model to obtain detailed gene expression data to understand and predict the molecular pathways to cancer. The study is very important to understand the mechanisms by which these viruses induce cancer, some of which are valuable in understanding cancer in other species including humans. Finally, the findings from the project will be very valuable in developing new approaches for the control of cancers caused by oncogenic viruses.

Technical Summary

The objectives of this work are to define the interactions between virus-encoded transcription factors, the host genomic DNA, microRNAs and mRNA expression during transformation by two avian oncogenic viruses, Reticuloendotheliosis virus (REV) and Marek's disease virus (MDV). Our preliminary data show that both MDV and REV encode transcription factors that bind to host DNA and upregulate important mRNA and microRNA genes, and that the miR-155/miR-M4 pathway is incredibly important to both viruses. We will dissect the exact relationship between virus-encoded transcription factors, microRNAs and gene expression using the latest next-generation sequencing technologies. Specifically, in REV we will simultaneously measure the temporal expression of mRNAs and microRNAs using mRNA-Seq and miRNA-Seq. We will combine this data with ChIP-Seq data to define the binding sites of vRel (the oncogenic transcription factor of REV) within the host genome, both at infection and at full transformation. These data will be integrated within a statistical and bioinformatics framework to provide an incredibly rich dataset on how proteins, microRNAs and mRNAs interact in this system. We will repeat the above with Marek's disease virus (MDV); however, we can only assay MDV at uninfected and tumour cells due to a lack of models of in vitro transformation. Finally, we will define the differential targetome of miR-155 and miR-M4 using an RCAS vector system, providing us with fine-grained data on the effects of miR-155 and miR-M4 on gene expression, their similarities and differences. These data combined will allow us to build a model of virus-induced transformation, and to compare and contrast the pathways used by REV and MDV.

Planned Impact

The beneficiaries of this research will include academic scientists, the poultry industry sector including the poultry breeding companies (e.g. Aviagen) and vaccine production companies (Pfizer Animal Health), farmers and the general public. Global demand for food is rising, both as a result of population growth and due to dietary changes in developing countries. A UN FAO report on this issue forecasts that food production will need to increase by over 40% by 2030 and by over 70% by 2050. With close to 55 billion chickens reared annually, poultry meat and eggs dominate animal protein products for human consumption world-wide. In the UK, the poultry sector is thought to contribute around £3.4 billion to the economy. Compared to the other livestock sectors, the modern poultry production methods have the most efficient feed-to-meat conversion ratios with lowest global warming potential. Because of these attributes, the poultry production sector is likely to expand significantly to meet the global demand for food in the coming years. Marek's disease (MD) is also one of the major diseases of poultry which causes serious economic losses and the global estimate of losses from Marek's disease is approximately $2,000 million annually. Detailed understanding of the molecular basis of tumours induced by these viruses, as the current proposal aims to achieve, will benefit development of new strategies for control.
 
Description 1. Feather and Spleen (RNA-Seq):
The gene expression study in the lymphoid cells and FFE can provide significant insights into the unique virus-host interactions in these two distinct sites of virus replication. Total 12 samples (3 from each - infected spleen, normal spleen, infected FFE and normal FFE cells) are sequenced. The prediction was made that the uniquely expressed/blocked genes in infected feathers and infected spleen might evidence biological processes that are involved in immune evasion or modulation, tumor, shedding of feathers and virus's life cycle. RNASeq data analysis pipeline (Tophat -> HTSeq-counts -> edgeR -> Pathway analysis) was run and differentially expressed genes (FDR < 0.05) were listed for pathway analysis. Viral genes were significantly expressed in infected feathers where the virus is fully productive. Top significantly differentially expressed chicken genes in infected feathers are mainly involved in infectious disease, inflammatory response, feathers growth and regeneration. A significant conclusion from these differential expressions is difficult as the gene functions of all interested genes are not very well recognized.

2. Spontaneous reactivation - Latent and lytic state difference (RNA-Seq):
There were two lymphoblastoid cell lines (NWB from spleen and 3867 from kidney) prepared from tumours induced by MDV virus. The fluorescence-activated cell sorting was used to purify the low-frequency EGFP-positive cells with a spontaneously activating viral genome from the majority EGFP-negative cells and analysed their gene expression profiles by RNA-seq. Global gene expression profiling using RNA-seq was used to examine the transcriptome changes associated with lytic switch. Detailed analysis of the global changes in the host and viral transcriptome of cells undergoing spontaneous lytic switch of MDV from latency in these LCLs was done. Ingenuity pathway analysis on more than 2000 differentially expressed genes between the lytically infected (EGFP-positive) and latently infected (EGFP-negative) cell populations identified the biological pathways involved in the reactivation. Virus-reactivating cells exhibited differential expression of a significant number of viral genes, with hierarchical differences in expression levels. RNASeq data analysis pipeline (Tophat -> HTSeq-counts -> edgeR -> Pathway analysis (IPA)) was run and differentially expressed genes (FDR < 0.05) were listed for pathway analysis.

3. DNA binding sites of Meq (Chip-Seq):
Determination of the DNA-binding sited of the viral Meq oncoprotein to both the latent viral genome and the chicken genome in MDV derived two T-cell-lines. The analysis of ChIP data revealed the genes that the Meq protein bound to nearby the transcriptional start site (TSS). This data indicated that Meq binds to the promoter region of many genes that associated with the development of cancer and correlated with previous studies with the regulation of signalling pathways such as the extracellular signal-regulated kinase/mitogen-activated protein kinase (ERK/MAPK). This study reveals the pathways that Mew utilises in a transformed cell-line for the maintenance of the transformed state.
The analysis steps include - quality trimming -> BWA -> MACS -> Analysis of peaks -> MEME for binding motif analysis in peaks. Analysis of peaks includes checking peaks for its nearest upstream and downstream genes and TSS. The fold change of coverage between input and chip sample were also plotted 10k upstream and downstream of genes. Pathway analysis of these genes was done using IPA for functional importance.

4. Methylation profile in MDV-carrying T-cell lines 265L (Bisulfite sequencing):
The same samples sequenced for Chip-seq were sequenced with bisulfite treatment. The analysis includes - Quality trimming of raw data. The data was then mapped on chicken using Bismark. The CpGs were called by Bismark with the information of methylation level. The methylated/non-methylated CpGs were filtered by selected coverage threshold. The methylation profile around gene - 10k upstream and downstream of genes and genes was plotted to check if there is any pattern of high or low methylation in CpG.. The genes which have peaks (in Chip seq) near promoter regions were selected for detailed methylation profile around genes.

5. Overexpression of miR-155, miR-M4 and miR-XSR cell-lines (RNAseq):
Fibroblast and macrophages of different cell lines are transfected with mimic microRNAs - miR-155, miR-M4 and miR-XSR. Target genes - UP/DOWN regulated genes in the cell-lines transfected with three different microRNAs, miR-155, miR-M4 and miR-XSR are listed. The 3' UTR region of these target genes are analysed for seed sequence. The differentially expressed genes between control and transfected samples were identified. The 3'UTR of down regulated genes were analysed to find the microRNA binding sites.
Exploitation Route Avian oncogenic viruses: we have continued our studies of a range of avian oncogenic viruses, including the characterisation of a number of important avian cell types and lines (many transcformed by oncogenic virused). We have discovered and published microRNAs associated with duck-enteritis virus (DEV: 10.1099/vir.0.040634-0); we have sequenced and published the small RNA profiles of a range of avian haemopoietic cells (10.3389/fgene.2013.00153); we published one of the first examples of a retrovirus using canonical processing mechanisms to generate a novel viral microRNA, with possible roles in myeloid leucosis (10.1128/JVI.02921-13); we have demonstrated that the oncoprotein encoded by REV-T, v-Rel (an NF-kappa-B orthologue) binds upstream of gga-miR-155 during infection and promotes massive expression of this microRNA, manipulating both the host immune system and the cell cycle (10.1099/jgv.0.000718); finally, we have discovered and published genes differentially expressed during spontaneous reactivation of Marek's disease virus (accepted for publication). More generally, we have produced additional datasets that enable us to study gene regulation during transformation of avian cells by oncogenic viruses, including transcription factor binding, methylation patterns and gene expression/RNA-Seq

These papers and data will be hugely important for researchers and vaccine developers wishing to know the mechanism by which Marek's, and other oncogenic viruses, infect and cause disease in chickens and other birds.
Sectors Agriculture, Food and Drink,Healthcare

 
Description By understanding how important viral diseases interact with their hosts, we can better design intervention strategies such as novel vaccines, drugs and targeted gene drives. This may result in better farm animal production and increased human health via the reduction of the impact of animal and human diseases.
First Year Of Impact 2016
Sector Agriculture, Food and Drink
Impact Types Economic

 
Description Dissecting the molecular pathways of MDV oncoprotein Meq for understanding pathogenesis and aid vaccine development
Amount £312,917 (GBP)
Funding ID BB/R007632/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 06/2018 
End 05/2021
 
Description Dissecting the molecular pathways of MDV oncoprotein Meq for understanding pathogenesis and aid vaccine development
Amount £384,966 (GBP)
Funding ID BB/R007632/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 04/2018 
End 03/2021
 
Title PRJEB14979 
Description Marek's Disease Virus (MDV) is a widespread alphaherpesvirus of poultry that causes Marek's disease (MD) characterised by fatal visceral CD4+ TCRaß+ T cell tumours at high incidence in susceptible hosts. As is the case with many virus-induced tumours, immortal cell lines harbouring viral genome have been generated from ex vivo cultures of MD tumours. As readily-available sources of large numbers of cells of a uniform type, MDV-transformed lymphoblastoid cell lines (LCL) have proved extremely valuable in studying virus-host interaction. While the viral genome is held in a latent state in most of the cells, a minor population of cells display spontaneous reactivation identifiable by the expression of lytic viral genes such as pp38. The process of spontaneous reactivation in these cell populations offers the opportunity for investigating the biological processes involved in the reactivation events. For this, we used two lymphoblastoid cell lines derived from lymphomas induced by pRB1B-UL47eGFP, a recombinant MDV engineered to express EGFP fused with the UL47. We used Fluorescence-activated cell sorting (FACS) to purify the rare EGFP-positive cell population with spontaneously activating viral genome from the majority EGFP-negative cells and analysed their gene expression profiles by RNA-sequencing using Illumina HiSeq2500. The reads generated were mapped using TopHat and gene expression levels were analysed by edgeR. Ingenuity pathway analysis software on more than 2000 differentially-expressed genes between the lytically infected (EGFP-positive) and latently infected (EGFP-negative) cell populations was used identify major biological pathways involved in the reactivation. These studies revealed that amongst others, transcripts directly involved in T activation such as CD3 complex, CD28, ICOS, phospholipase C, CD3 complex were down-regulated following reactivation of the virus in the LCL. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
Impact These data detail the gene expression changes during spontaneous activation of MDV and will be useful to researchers investigating the mechanism of action of this important virus, as well as in vaccine design 
URL https://www.ebi.ac.uk/ena/data/view/PRJEB14979
 
Description Venu Nair, The Pirbright Institute 
Organisation The Pirbright Institute
Country United Kingdom 
Sector Academic/University 
PI Contribution We have been working with Venu Nair at The Pirbright Institute for over 10 years, broadly in the area of avian oncogenic viruses such as Marek's disease and ALV.
Collaborator Contribution Venu's group are expert in virology and virus research whereas my group is expert in genomics and bioinformatics. Together we use genomics to explore virus-host interactions.
Impact 28113043 24155381 23967013 22492913 19403687 19297609 18256158
Start Year 2006