Chemistry: molecular biology and microbiology – Measuring or testing process involving enzymes or... – Involving nucleic acid
Reexamination Certificate
2000-12-28
2003-10-21
Guzo, David (Department: 1636)
Chemistry: molecular biology and microbiology
Measuring or testing process involving enzymes or...
Involving nucleic acid
C435S007100, C435S007210, C435S069100, C435S320100, C536S023100, C536S024300, C536S024320, C530S350000, C530S324000
Reexamination Certificate
active
06635422
ABSTRACT:
FIELD OF THE INVENTION
This invention relates generally to post-transcriptional regulation and methods of profiling gene expression.
BACKGROUND OF THE INVENTION
Many diseases are genetically based, and the genetic background of each individual can have a profound effect on his or her susceptibility to disease. The relatively new field of functional genomics has provided researchers with the ability to determine the functions of proteins based upon knowledge of the genes that encode the proteins. A major goal of functional genomics is to identify gene products that are suitable targets for drug discovery. Such knowledge can lead to a basis for target validation if it is demonstrated that the target of interest has an essential function in a disease. Accordingly, a need exists to develop methods that allow profiling of the gene expression state of cells and tissues in order to understand the consequences of genetics on growth and development.
Understanding global gene expression at the level of the whole cell requires detailed knowledge of the contributions of transcription, pre-mRNA processing, mRNA turnover and translation. Although the sum total of these regulatory processes in each cell accounts for its unique expression profile, few methods are available to independently assess each process en masse.
The expression state of genes in a complex tissue or tumor is generally determined by extracting messenger RNAs from samples (e.g., whole tissues) and analyzing the expressed genes using cDNA libraries, microarrays or serial analysis of gene expression (SAGE) methodologies. See, e.g., Duggan, et al., (1999)
Nature Genetics
21, 10-14.; Gerhold, et al., (1999)
Trends in Biochemical Sciences
24, 168-173; Brown, et al., (1999)
Nature Genetics
21, 38-41; Velculescu, et al., (1995)
Science
270, 484-487 Velculescu, et al. (1997)
Cell
88, 243-251. In order to determine the gene expression profile of any single cell type within a tissue or tumor or to recover those messenger RNAs, the tissue must first be subjected to microdissection. This is very laborious, as only a small amount of cellular material is recovered and the purity as well as the quality of the cellular material is compromised.
Post-transcriptional events influence the outcome of protein expression as significantly as transcriptional events. The regulation of transcription and post-transcription are generally linked. Altering the expression of transcriptional activators or repressors has important consequences for the development of a cell. Therefore, feedback loops following translational activation of specific mRNAs may change the program of transcription in response to growth or differentiation signals. DNA arrays are well-suited for profiling the steady-state levels of mRNA globally (i.e., total mRNA or the “transcriptome”). However, because of post-transcriptional events affecting mRNA stability and translation, the expression levels of many cellular proteins do not directly correlate with steady-state levels of mRNAs (Gygi et al. (1999)
Mol. Cell Biol.
19, 1720-1730; Futcher et al. (1999)
Mol. Cell Biol.
19, 7357-7368).
Many mRNAs contain sequences that regulate their post-transcriptional expression and localization (Richter (1996) in
Translational Control,
eds. J. W. B Hershey, et al., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, pp. 481-504). These regulatory elements reside in both introns and exons of pre-mRNAs, as well as in both coding and noncoding regions of mature transcripts (Jacobson and Peltz (1996)
Annu. Rev. Biochem.
65, 693-739; Wickens et al. (1997)
Curr. Opin. Genet. Dev.
7, 220-232). One example of a sequence-specific regulatory motif is the AU-rich instability element (ARE) present in the 3′-untranslated regions (UTRs) of early-response gene (ERG) mRNAs, many of which encode proteins essential for growth and differentiation (Caput et al. (1986)
Proc. Natl. Acad. Sci. USA
83, 1670-1674; Shaw and Kamen (1986)
Cell
46, 659-667; Schiavi et al. (1992)
Biochim. Biophys. Acta
1114, 95-106; Chen and Shyu (1995)
Trends Biochem. Sci.
20, 465-470). Regulation via the ARE is poorly understood, but the mammalian ELAV/Hu proteins have been shown to bind to ARE sequence elements in vitro and to affect post-transcriptional mRNA stability and translation in vivo (Jain et al. (1997)
Mol. Cell Biol.
17, 954-962; Levy et al. (1998)
J. Biol. Chem.
273, 6417-6423; Fan and Steitz (1998)
EMBO J.
17, 3448-3460; Peng et al. (1998)
EMBO J.
17, 3461-3470; Keene (1999)
Proc. Natl. Acad. Sci. USA
96, 5-7).
In vitro RNA selection methods based upon cellular sequences are reported in Gao et al.,
Proc. Natl. Acad. Sci USA
90, 11207-11211 (1994) and U.S. Pat. Nos. 5,773,246, 5,525,495 and 5,444,149, all to Keene et al., the disclosures of which are incorporated herein in their entirety. Generally, these methods were intended to identify large numbers of mRNAs present in messenger RNP (mRNP) complexes, and utilized in vitro binding and amplification of mRNA sequences from large pools of naturally-occurring mRNAs. These studies used proteins (referred to as ELAV or Hu proteins) known to bind to AU-rich sequence elements present in the untranslated regions of cellular mRNAs. These experiments led to the discovery that mRNAs which are structurally or functionally related may be revealed using multi-targeted RNA binding proteins (i.e., RNA binding proteins that specifically bind more than one target). See Levine, et al., (1994) et al.,
Molecular and Cellular Biology
13, 3494-3504; and King, et al., (1993)
Journal of Neuroscience
14, 1943-1952; reviewed in Antic and Keene (1997)
American Journal of Human Genetics
61, 273-278 and Keene (1999)
Proceedings of the National Academy of Sciences
(
USA
) 96, 5-7. However, these reports are limited to in vitro applications, and do not describe in vivo methods for partitioning RNA into structural or functional subsets using RNA binding proteins. Although in vitro methods have been used to determine protein-RNA interactions, their use has certain limitations. Biochemical methods are generally reliable when carefully controlled, but RNA-binding can be problematic because many interactions may be of low affinity, low specificity or even artifactual. In order to understand RNA-protein interactions and their functional implications on a global systems level it is necessary to find reliable methods to monitor messenger RNP complexes in vivo.
The successful immunoprecipitation of epitope-tagged ELAV/Hu protein which has been transfected into pre-neuronal cells has been reported. See Antic et al.,
Genes and Development
13, 449-461 (1999). This immunoprecipitation was followed by nucleic acid amplification that allowed for the identification of a messenger RNA encoding neurofilament M protein (NF-M).
SUMMARY OF THE INVENTION
The present invention relates to a new, in vivo approach for the determination of gene expression that utilizes the flow of genetic information through messenger RNA clusters or subsets. Recently, the practice of examining multiple macromolecular events simultaneously and in parallel with the goal of organizing such information computationally has taken the designation “-ome.” Thus, the genome identifies all of the genes of a cell, while the transcriptome is defined as the messenger RNA complement of the genome and the proteome is defined as the protein complement of the genome (see FIG.
1
). The present inventors have defined several physically organized subsets of the transcriptome and defined them as dynamic units of the “ribonome”. As described herein, the ribonome consists of a plurality of distinct subsets of messenger RNAs (mRNAs) that are clustered in the cell due to their association with RNA-binding proteins (e.g., regulatory RNA-binding proteins). By identifying the mRNA components of a cellular ribonome, the cellular transcriptome can be broken down into a series of subprofiles that together can be used to define the gene expression state of a cell or tissue (see FIG.
2
). In combination with, for exampl
Carson Craig C.
Keene Jack D.
Tenenbaum Scott A.
Guzo David
Marvich Maria
Ribonomics, Inc.
Testa Hurwitz & Thibeault LLP
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