Mitra Lab Research Interests:

We are developing experimental and computational tools that will allow biologists to collect high volumes of quantitative data on nucleic acids and proteins.

Some specific areas that we are focused on are listed below:

Single Molecule Proteomics

Our ability to detect and quantify proteins has lagged behind our ability to analyze nucleic acids. Closing this gap by developing more sensitive and quantitative protein analysis methods would greatly aid efforts to understand cellular processes and the search for protein biomarkers that reveal disease state. We are developing methods to unite the field of protein detection with single molecule counting, with the long-term goal of sequencing single peptide molecules. In collaboration with the Elbert lab, we have characterized two low background surfaces that are highly resistant to protein adsorption.  Using these surfaces, we have demonstrated accurate and sensitive quantification of proteins in serum by single molecule counting on a solid surface. In these experiments, we were able to detect 80% of immobilized molecules by binding fluorescently labeled antibodies and single molecule counting.

Relevant Publications:

1. Tessler LA, Reifenberger J, Mitra RD. Protein quantification in complex mixtures by solid phase single-molecule counting. Analytical Chemistry, 2009, Sep 1;81(17):7141-8.
2. Tessler LA, Donahoe CD, Garcia DJ, Jun YS, Elbert DL, Mitra RD, Nanogel coatings for improved single-molecule detection substrates. Journal of the Royal Society, Interface, 2011 Epub Feb 16. PMID: 21325313
3. Tessler, L. A. and Mitra, R. D. (2011), Sensitive single-molecule protein quantification and protein complex detection in a microarray format. PROTEOMICS, 11: 4731–4735.

Testing the Common Disease-Rare Variant Hypothesis

The genetic factors that underlie common diseases are largely unknown.  The search for these genetic factors has been predicated on the common disease -common variant hypothesis.  While this approach has identified genetic variants associated with disease, these only account for a small proportion of the heritability for most complex diseases.  In contrast, there is increasing evidence that private or rare variants, not shared between individuals, cumulatively account for a major fraction of the heritability of complex diseases.  We are using second generation sequencing to test the common disease-rare variant hypothesis, and developing novel genomic tools to dissect the mechanisms by which rare variants operate.

Identification of disease associated rare variants by targeted and pooled-sample sequencing.  We developed SPLINTER, an algorithm rooted in large deviation theory to analyze sequencing data from pooled samples. We are applying this methodology in combination with targeted exon capture to find disease-associated rare variants in diseases such as respiratory distress syndrome, pediatric cancer, Crohn’s disease and nicotine addiction.  We are working with 13 laboratories at Washington University to investigate the relative contributions of rare and common variants to common diseases.

Multiplexed amplification and sequencing for clinical diagnoses.  The rare variant hypothesis suggests that common diseases are not caused by single ancestral alleles, but by a spectrum of rare variants.  Therefore, to make a clinical diagnosis, one must sequence the complete coding sequencing of a gene, and this is not cost-effective by current methods.  We are developing cost-effective methods for the multiplexed clinical sequencing.

Relevant Publications:

1. Druley TE, Vallania FML, Wegner DJ, Varley KE, Knowles OL, Bonds JA, Robison SW, Doniger SW, Hamvas A, Cole FS, Fay JC, Mitra RD. Accurate quantification of rare allelic variants from the pooled genomic DNA of 1111 individuals. Nature Methods, 2009, 6: 263-265.
2. Vallania FLM, Druley TE, Ramos E, Wang J, Borecki I, Province M, Mitra RD. High-throughput discovery of rare insertions and deletions in large cohorts. (Genome Research, in revision)
3. Matkovich SJ, Van Booven DJ, Hindes A, Kang MY, Druley TE, Vallania FL, Mitra RD, Reilly MP, Cappola TP, Dorn GW 2nd. Cardiac signaling genes exhibit unexpected sequence diversity in sporadic cardiomyopathy, revealing HSPB7 polymorphisms associated with disease. J Clin Invest. 2010 Jan;120(1):280-9.
4. Varley, KE, and Mitra, RD. Nested Patch PCR Enables Highly Multiplex Mutation Discovery in Candidate Genes. Genome Research, 2008; 18(11):1844-50.
5. Varley KE, Mitra RD. Highly multiplexed bisulfite sequencing reveals tumor specific promoter methylation in breast and colon cancer. (Genome Research, in press)

Identifying the Genomic Targets of Transcription Factors

Transcription factors orchestrate the transcriptional networks that control cellular processes such as cell growth, division, and differentiation. As a result, there is much interest in identifying the target genes of transcription factors, and the primary methods for doing so are chromatin immunoprecipitation coupled with microarrays (ChIP-chip) or high-throughput sequencing (ChIP-Seq). These methods are powerful, but they cannot address some important problems in development because they require pure cell populations and cannot record transcription factor binding through cellular differentiation.

We have developed, in collaboration with the Johnston lab, transposon “Calling Cards”, a method that employs the yeast retrotransposon Ty5 as a “Calling Card” to mark the visits of TFs to their targets in the genome. By coupling this method to next-generation sequencing, it is possible to multiplex transcription factor analysis. We have successfully analyze 8 TF in a single experiment and identified novel binding motifs and gene targets. We are working to enable higher levels of multiplexing.

We are also working to port the Calling Card method to work in mammalian cells and aim to use this method to trace transcription factor binding along different cell lineages during development. An important future direction is to implement this methodology in a developing organism, such as the zebrafish.

Relevant Publications:

1. Wang, H, Johnston, M, Mitra, RD. Calling Cards for DNA-binding Proteins. Genome Research 2007; 17: 1202-1209.
2. Wang, H, Heinz, ME, Crosby, SD, Johnston, HM, Mitra, RD. Calling cards: a method for the high-throughput identification of targets of yeast DNA-binding proteins. Nature Protocols, 2008; 3:1569-1577.
3. Wang H, Mayhew D, Chen X, Johnston M*,Mitra RD*. Multiplexed identification of the genomic targets of DNA binding proteins. (submitted)