A.Title OF PROPOSED Undertaking:

Transcriptomic profiling of the Human Jurkat Cell Line

C1.RESEARCH AREA

Genomicss and Transcriptomics

D.Undertaking DIGEST.

To understand the assorted cellular and molecular procedures traveling on in life beings, we need exemplary systems that can mime the physiological conditions of the being under survey. However, surveies have shown that no theoretical account system can stand for the natural environment of populating beings to the full extent. Variations exist and the demand is to find the extent and significance of these fluctuations so that appropriate theoretical accounts can be selected while planing experiments and the consequences can be interpreted and generalized consequently. We propose to measure one such theoretical account system, the Jurkat Cell line, which is derived from White blood cells, and so compare the degrees of expressed cistrons to the normal tissue. Such a survey will find the significance of the consequences of surveies conducted on these theoretical account systems.

Undertaking Detailss

1. Undertaking SUMMARY

Describe the proposed research. ( soap. 100 words )

The Jurkat cell line was derived from the blood of a patient with T-cell leukaemia. Old ages of research on Jurkat cells have shed a great trade of visible radiation on the T-cell receptor signaling. Assorted surveies, nevertheless, have shown that the look profiles of cell lines differ significantly from the tissues of their beginning, raising a inquiry on the practicality of utilizing these theoretical accounts for miming the physiological conditions and the significance of the consequences. We propose to profile transcriptomes of the Jurkat cell line and the tissue of its beginning utilizing to measure the differences in look forms.

2.PROPOSED GOALS/OBJECTIVES

HYPOTHESIS/BASIS OF RESEARCH

Based on old surveies we hypothesize that important differences exist in the transcriptomes of cell lines and the tissues from which they are derived and the demand is to find the significance of these fluctuations in context of construing the consequences.

Research OBJECTIVES

  1. To sequence the transcriptomes of human Jurkat cell line and the tissue of its beginning ( white blood cells )
  2. To clarify fluctuations in their look profiles.
  3. To re-evaluate the antecedently generated informations and design future experiments consequently.

3.INTRODUCTION

Human Jurkat cell line, derived from blood of a Leukemic patient, was foremost discovered in 1970s. Over the old ages, it has turned into an of import theoretical account system for clarifying the T-cell signaling tracts. Expression of Interleukin-2 has besides been established in it ( Gillis and Watson 1980 ) . Despite the fact that cell lines are extensively used as theoretical account systems for analyzing biological procedures, the fluctuation observed between them and their beginning are rather important ( Shaw, Morse et Al. 2002 ; Boess, Kamber et Al. 2003 ; Landry, Pyl et Al. 2013 ) .

We are suggesting a genomics and transcriptomics study affecting making a transcriptomic resource for the human Jurkat cell line utilizing deep RNA sequencing. Jurkat transcriptome will be profiled along with the normal tissue of beginning ( white blood cells ) and compared to the RNA-Seq informations available from Illumina Human BodyMap 2.0.

We aim to place the differences in form and degree of look between thein vitroandin vivosystem so that while planing experiments and construing their consequences, these differences can be considered.

4A.BACKGROUND OF THE RESEARCH PROBLEMS TO BE ADDRESSED ( Not to transcend two pages )

The Jurkat cell line was foremost established in 1970s. It was derived from the blood of a patient with T-cell leukaemia ( Schneider, Schwenk et Al. 1977 ) . Since so it has gained importance for clarifying the signalling pathways affecting T-cells, T-cell Leukemia, malignant neoplastic diseases and their response to radiation therapy, etc.

Soon after this cell line was derived, look of interleukin 2 was established in it ( Gillis and Watson 1980 ) , helping the word picture of this immunoregulatory molecule. Old ages of research on Jurkat cells have shed a great trade of visible radiation on the T-cell receptor signalling ( Spinozzi, Pagliacci et Al. 1994 ; Meisner, Conway et Al. 1995 ; Abraham and Weiss 2004 ) . In another survey cholecystokininbinding sites were identified in the Jurkat cells ( Lignon, Bernad et Al. 1991 ) . cholecystokininis a peptide involved in the digestion of fats and proteins ( Gibbs, Young et Al. 1973 ) , and this find helped in farther clarifying the ordinance of CCK receptors. Surveies were carried out, trying to explicate mechanisms of T-cells activation and programmed cell death, under emphasis conditions ( Katika, Hendriksen et Al. 2012 ) . In other surveies, constituents of the apoptotic tract including several Heat Shock proteins and caspases were identified in Jurkat cells ( Samali, Cai et Al. 1999 ) . Jurkat cells have been extensively used to analyze immune responses by bring oning programmed cell death of T-cells ( Dhein, Walczak et Al. 1995 ; Martinez-Lorenzo, Alava et Al. 1998 ) .

These surveies although have led to a figure of of import finds, it needs to be kept it mind that they were conducted on immortalized cell lines and it needs to be seen how much divergency have they gone through in footings of cistron look to accomplish this province so that the consequences can be generalized to the in vivo conditions. Transcriptomic profiling of the Jurkat cell line and the tissue of its beginning can uncover the possible differences in look degrees.

A similar survey was conducted on HeLa cell line, one of the most normally used theoretical account for analyzing cellular and molecular biological science. Consequences showed that the cell line showed markedly variable forms of look when compared to normal tissues of same beginning ( Landry, Pyl et Al. 2013 ) . In another survey the transcriptome of HEK293 cells was profiled to place the kidney cell type from which the cell line originated ( Shaw, Morse et Al. 2002 ) .

Hepatic cell lines were used to transport out a similar survey, uncovering major differences between the look degrees of the liver cells and the cell lines ( Boess, Kamber et Al. 2003 )

As mentioned above, the importance of Jurkat cells in clarifying of import signaling tracts such as programmed cell death and T-cell signaling which are an indispensable constituent of the immune ordinance procedure calls for analysing its transcriptome in order to determine that the consequences obtained do so match to the normal physiological conditions. These findings highlight the practicality of utilizing of suchin vitrosystems for mimingin vivoconditions, and extrapolation of the consequences.

4B.RESEARCH PLAN/ METHODOLOGY: SCHEDULE/PHASING

  • RNASeq library readying
  • RNASeq utilizing Illumina Genome Analyzer II
  • Read alliance against Human BodyMap 2.0 by Illumina
  • RNA-Seq Analysis: Reads per cistron calculated by HTSeq to find look degree

4C.REFERENCES

Abraham, R. T. and A. Weiss ( 2004 ) . “ Jurkat T cells and development of the T-cell receptor signalling paradigm. ”Nat Rev Immunol4( 4 ) : 301-308.

Boess, F. , M. Kamber, et Al. ( 2003 ) . “ Gene look in two hepatic cell lines, cultured primary hepatocytes, and liver pieces compared to the in vivo liver cistron look in rats: possible deductions for toxicogenomics usage of in vitro systems. ”Toxicological Sciences73( 2 ) : 386-402.

Dhein, J. , H. Walczak, et Al. ( 1995 ) . “ Autocrine T-cell self-destruction mediated by APO-1/ ( Fas/CD95 ) . ”Nature373( 6513 ) : 438-441.

Gibbs, J. , R. C. Young, et Al. ( 1973 ) . “ Cholecystokinin decreases nutrient consumption in rats. ”Journal of comparative and physiological psychological science84( 3 ) : 488.

Gillis, S. and J. Watson ( 1980 ) . “ Biochemical and biological word picture of lymphocyte regulative molecules. V. Identification of an interleukin 2-producing human leukaemia T cell line. ”J Exp Med152( 6 ) : 1709-1719.

Katika, M. R. , P. J. Hendriksen, et Al. ( 2012 ) . “ Transcriptome analysis of the human T lymph cell cell line Jurkat and human peripheral blood mononuclear cells exposed to deoxynivalenol ( DON ) : New mechanistic penetrations. ”Toxicol Appl Pharmacol264( 1 ) : 51-64.

Landry, J. J. , P. T. Pyl, et Al. ( 2013 ) . “ The genomic and transcriptomic landscape of a HeLa cell line. ”G3 ( Bethesda )3( 8 ) : 1213-1224.

Lignon, M. F. , N. Bernad, et Al. ( 1991 ) . “ Pharmacological word picture of type B cholecystokinin adhering sites on the human JURKAT T lymph cell cell line. ”Mol Pharmacol39( 5 ) : 615-620.

Martinez-Lorenzo, M. J. , M. A. Alava, et Al. ( 1998 ) . “ Involvement of APO2 ligand/TRAIL in activation-induced decease of Jurkat and human peripheral blood T cells. ”Eur J Immunol28( 9 ) : 2714-2725.

Meisner, H. , B. R. Conway, et Al. ( 1995 ) . “ Interactions of Cbl with Grb2 and phosphatidylinositol 3′-kinase in activated Jurkat cells. ”Mol Cell Biol15( 7 ) : 3571-3578.

Samali, A. , J. Cai, et Al. ( 1999 ) . “ Presence of a pre-apoptotic composite of pro-caspase-3, Hsp60 and Hsp10 in the mitochondrial fraction of jurkat cells. ”EMBO J18( 8 ) : 2040-2048.

Schneider, U. , H. U. Schwenk, et Al. ( 1977 ) . “ Characterization of EBVaˆ?genome negative “null” and “T” cell lines derived from kids with acute lymphoblastic leukaemia and leukemic transformed nonaˆ?Hodgkin lymphoma. ”International diary of malignant neoplastic disease19( 5 ) : 621-626.

Shaw, G. , S. Morse, et Al. ( 2002 ) . “ Discriminatory transmutation of human neural cells by human adenoviruses and the beginning of HEK 293 cells. ”FASEB J16( 8 ) : 869-871.

Spinozzi, F. , M. C. Pagliacci, et Al. ( 1994 ) . “ The natural tyrosine kinase inhibitor genistein produces cell rhythm apprehension and programmed cell death in Jurkat T-leukemia cells. ”Leuk Res18( 6 ) : 431-439.

5. IMPACT ( of proposed research on teaching/training of work force, institutional capableness edifice and on local industry )

This survey, along with old researches will let research workers to plan and construe experiments in the visible radiation of the fact that the theoretical account systems we use do non mime the normal physiological conditions 100 % so we need to maintain these differences in head when we extrapolate the findings to in vivo systems.

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