GCAT-SEEKquence
The Genome Consortium for Active Teaching
NextGen Sequencing Group
NextGen Sequencing Request Form
Complete fields below, save file with your last name at the beginning of
the filename (e.g. newman-GCAT-SEEK Sequence request form.pdf) and
email to Vincent Buonaccorsi <BUONACCORSI@juniata.edu>
A. Contact Information
1. Name:
Dennis Revie
2. Department: Biology
3. Institution: California Lutheran University
4. Phone Number: 805-493-3380
5. Email Address: revie@clunet.edu
B. Project Information
1. Title: Analysis of the response of monocytes to Hepatitis C Virus (HCV)
2. Category: RNA-seq/transcriptomes
3. Total amount of sequence requested: 1 to 3 lanes
4. Preferred technology: Illumina
5. Do you have funds for a partial run next Spring? No
C. Describe the background, hypotheses and specific aims (500 words max)
HCV is a positive strand RNA virus that infects humans. We previously developed a system for the
isolation of HCV and its replication in vitro (Revie et al, 2005). The system uses serum from infected patients
to infect macrophages. Recently, we have extended the system to the use of monocytic cell lines for
culturing HCV. Macrophages derive from monocytes and they can differentiate into macrophages by the
addition of PMA (phorbal myristate acetate). These cell lines have the advantage of being available to all
researchers. We found that HCV can infect a U-937 monocytic cell line while it does not infect a monocytic
THP-1 DC cell line. We are interested in examining the response of the monocytes to infection by HCV.
First, we want to compare the two monocytic cell lines to determine the differences in gene expression
between the two cell lines. In particular, we are interested in differences between cell surface proteins that
might affect virus binding and entry or in genes involved in the cellular response to viral infections. Second,
we will compare gene expression in cells that are infected by HCV with those that are not. This will let us
determine which genes are up or down regulated in response to the infection. These studies may help
explain why some cell types can be infected by HCV while others cannot.
D. Describe the methods [sample prep, calculation of amount of sequence required, analysis plan]
We will analyze uninfected U-937, HCV-infected U-937 at five time points post-infection (0, 1, 4, 16 and
64 hours), uninfected THP-1, and infected THP-1 at three time points post-infection (0, 1, and 4 hours). This
will give us 10 samples. At the specified times, RNA will be isolated for the analysis. We also plan to
perform the experiments in triplicate to provide better statistical comparisons between the samples as well
as to check for reproducibility.
As one lane of Illumina can give 37 GBp or more of 75 bp sequence, we can barcode the samples to
reduce the number of lanes needed for the analyses. If we put 10 barcoded samples/lane, 1 lane would
provide one full set of data, while 3 lanes would give us triplicate results (Wang et al., 2011).
Comparisons of genes expressed in the two uninfected cell lines will provide candidate genes that may
be important for infection by HCV. Comparisons of infected and uninfected cell lines will provide gene
candidates that may be involved in combating the virus. As the genes expressed will change with the time
of infection, a time course should show differences for genes expressed early and later in infection. For
example, the virus must enter the cell, disassemble, replicate, reassemble, and then exit the cell. Each step
in the process may activate cellular genes that either help or hinder the process. Gene candidates can then
be compared to ones identified by other researchers for hepatoma cells (e.g., Woodhouse et al., 2010).
E. Describe the role and number of undergraduates involved in the project, and how they would benefit.
All aspects of the project will be performed by undergraduates. The cell culturing and RNA purification
will be performed by undergraduate research students. The data analysis will be done by undergraduate
researcher students and also by students in a Genomics course (Biology 427). Different students or groups
of students will test different hypotheses, such as which membrane receptors differ between U-937 cells
and THP-1 cells, which antiviral pathways are activated by the infection process in the two cell types, etc. I
typically have around 6 undergraduates per year work on research projects, and the Genomics course has
about 10 students per year.
F. I agree to administer the GCAT-SEEK pre- and post-activity assessment test for students and to complete
the faculty post-utilization survey. __x__ yes, ____ no
G. Describe any other broader impact or intellectual merit considerations.
HCV is estimated to infect 170 million individuals in the world, and it is estimated that about 3 million
are infected in the US. HCV can cause liver diseases as well as extrahepatic diseases such as B cell
lymphomas. The major site of HCV production in individuals is the liver, but extrahepatic replication of HCV
also occurs (Revie and Salahuddin, 2011). To date, only one RNA-seq study has been published that has
investigated the response of cells to HCV in vitro (Woodhouse et al., 2010), and it used a synthetic virus to
infect hepatoma cells. Therefore, this study will provide the first RNA-seq data for infection of non-liver
cells, the first to analyze cellular response over time, and the first to use HCV from patient serum instead of
a synthetic virus.
H. References
Revie D, Braich RS, Bayles D, Chelyapov N, Khan R, Geer C, Reisman R, Kelley AS, Prichard JG, Salahuddin SZ
(2005). Transmission of human hepatitis C virus from patients in secondary cells for long term culture. Virol
Journal 2005, 2:37.
Revie D, Salahuddin SZ (2011). Human cell types important for Hepatitis C Virus replication in vivo and in
vitro. Old assertions and current evidence. Virology Journal 8:346
Wang Y, Ghaffari N, Johnson CD, Braga-Neto UM, Wang H, Chen R, Zhou H. Evaluation of the coverage and
depth of transcriptome by RNA-Seq in chickens. BMC Bioinformatics. 2011 Oct 18;12 Suppl 10:S5.
Woodhouse SD, Narayan R, Latham S, Lee S, Antrobus R, Gangadharan B, Luo S, Schroth GP, Klenerman P,
Zitzmann N. (2010). Transcriptome Sequencing, Microarray, and Proteomic Analyses Reveal Cellular and
Metabolic Impact of Hepatitis C Virus Infection In Vitro. Hepatology 52, 443-453.