Technology Development The focus of this renewal application is on the development of technologies that will enable the study of the human genome and the mechanisms underlying human disease at a substantially-reduced cost. Methods to analyze human samples must be extremely sensitive in order to: 1) detect low abundance biomolecules;and 2) be informative using small sample volumes. However, current genomic and proteomic methods vary widely in their suitability for analyzing human samples. For example, genomic methods such as microarrays and next generation sequencing have high sensitivity, but are limited in their quantitative value because ofthe biases of DNA amplification strategies that are required to generate detectable signals. In contrast, current proteomic methods such as ELISA assays simply lack sensitivity altogether, leaving the low abundance proteins that may be informative biomarkers undetected. In this second tier of the proposal. Technology Development, we are focused on developing technologies that can detect nucleic acids and proteins not only with high accuracy and sensitivity, but also with a minimum of time and expense in order to facilitate their translation to clinical medicine. Such technologies will equip biomedical researchers with better tools to investigate the human disease process, and enable the use of less invasive sources of diagnostic material, such as sweat, saliva, or breath. These technologies were in the innovation phase during the previous funding period and met desired milestones. Current development will be directed toward further strengthening the tools and demonstrating their improvement over existing technologies. We will develop a method based on modified atomic force microscopy for the label-free nanomechanical quantitation of nucleic acids, and two methods that integrate microfluidics and electrical impedance sensing for the high-throughput digital detection of proteins from minute samples. Once proof-of-principle has been established, these technologies will be primed for export and application to specific clinical problems.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Program Projects (P01)
Project #
5P01HG000205-25
Application #
8738703
Study Section
Special Emphasis Panel (ZHG1-HGR-N)
Project Start
Project End
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
25
Fiscal Year
2014
Total Cost
$1,532,630
Indirect Cost
$554,970
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Tóth, Eszter N; Lohith, Akshar; Mondal, Manas et al. (2018) Single-cell nanobiopsy reveals compartmentalization of mRNAs within neuronal cells. J Biol Chem 293:4940-4951
Jalili, Roxana; Horecka, Joe; Swartz, James R et al. (2018) Streamlined circular proximity ligation assay provides high stringency and compatibility with low-affinity antibodies. Proc Natl Acad Sci U S A 115:E925-E933
Roy, Kevin R; Smith, Justin D; Vonesch, Sibylle C et al. (2018) Multiplexed precision genome editing with trackable genomic barcodes in yeast. Nat Biotechnol 36:512-520
Emaminejad, Sam; Gao, Wei; Wu, Eric et al. (2017) Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform. Proc Natl Acad Sci U S A 114:4625-4630
Smith, Justin D; Schlecht, Ulrich; Xu, Weihong et al. (2017) A method for high-throughput production of sequence-verified DNA libraries and strain collections. Mol Syst Biol 13:913
Jensen, Michael; Davis, Ronald (2017) RecJ 5' Exonuclease Digestion of Oligonucleotide Failure Strands: A ""Green"" Method of Trityl-On Purification. Biochemistry 56:2417-2424
Lau, Billy T; Ji, Hanlee P (2017) Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes. BMC Genomics 18:745
Shin, GiWon; Grimes, Susan M; Lee, HoJoon et al. (2017) CRISPR-Cas9-targeted fragmentation and selective sequencing enable massively parallel microsatellite analysis. Nat Commun 8:14291
Celaj, Albi; Schlecht, Ulrich; Smith, Justin D et al. (2017) Quantitative analysis of protein interaction network dynamics in yeast. Mol Syst Biol 13:934
Esfandyarpour, Rahim; DiDonato, Matthew J; Yang, Yuxin et al. (2017) Multifunctional, inexpensive, and reusable nanoparticle-printed biochip for cell manipulation and diagnosis. Proc Natl Acad Sci U S A 114:E1306-E1315

Showing the most recent 10 out of 217 publications