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Development of a Genotype-linked Antibiotic Resistance Platform for Real Time Pathogen Risk Classification and Epidemiology

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41AI122740-01A1
Agency Tracking Number: R41AI122740
Amount: $219,655.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: NIAID
Solicitation Number: PA15-270
Solicitation Year: 2016
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-08-01
Award End Date (Contract End Date): 2017-07-31
Small Business Information
San Mateo, CA 94402-7023
United States
DUNS: 079203445
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (510) 703-6386
Business Contact
Phone: (650) 388-9277
Research Institution

Project Summary
Antibiotic resistance has become a pressing public health concern due to the rise of pathogenic bacterial
strains with mutations that reduce or eliminate the effectiveness of drugs to treat infections Beta lactamases
produced by some bacteria provide resistance by degrading beta lactams one of most widely used class of
antibiotics Originally restricted to penicillins mutant beta lactamases that confer resistance to antibiotics
including monobactams and most cephalosporins known as extended spectrum beta lactamases or ESBLs
are widespread Clinical isolates are currently characterized for ESBL resistance using inhibition zone tests
against a panel of lactam antibiotics but the results produced by these tests are difficult to standardize and do
not translate consistently into clinical practice In addition these tests typically produce no information about
the genetic basis for the observed resistance nor the relatedness to other potentially characterized strains
Here we propose the development of a sequence based analysis platform and knowledgebase for
analyzing molecular signatures of extended spectrum beta lactamase resistance that can initially market to
health institutions and companies monitoring the spread of EBSL resistance The platform will consist of an
analysis kit that extracts positively selected variants beta lactamase sequences and other genomic
information relevant to the ESBL phenotype from whole genome sequences of clinical samples A total of
samples will be analyzed of which ESBL resistant samples provided by the Mercy Center at UC Merced
will be newly sequenced and the rest will be obtained from a published study from the University of
Washington A cloud based searchable database with interactive visualization will be served as the repository
of the ESBL resistant features identified in the clinical samples By leveraging the metadata exchange
standards being developed for broad sharing of human genomic data the rapidly expanding Global Alliance for
Genomics and Health application program interface our work will represent the initial extension of this API for
sharing microbial centric data The ultimate goal of this project is to create an accurate predictive resistance
classifier using beta lactamase gene sequences and other genomic markers that are linked to known treatment
outcomes and strain phenotypes We will develop this new classifier based on published methods found to be
effective with HIV genotype phenotype prediction ESBL resistant features obtained from the clinical samples
in this study will be used for training and testing of the classifier The powerful combination of sharable
database and analytic tools in a single platform will significantly advance knowledge of antibiotic resistant
bacteria facilitate epidemiological monitoring of the spread of ESBL resistance and represents a key first step
to develop a diagnostic tool to counter ESBL resistance using whole genome sequences !Project Narrative
Infectious diseases caused by antibiotic resistant bacteria are difficult to treat and represent a serious threat to
human health world wide This project will develop a platform of pathogen search tools with simple interfaces
for clinical researchers to rapidly match and analyze molecular signatures of extended spectrum beta
lactamase resistance Broad application of this cloud based database and search technology should
significantly advance knowledge of antibiotic resistant bacteria enable more effective targeted treatment and
limit future outbreaks by establishing real time pathogen signature data sharing

* Information listed above is at the time of submission. *

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