# A rapid, automated system for bacteria profiling of intra-abdominal infections

> **NIH NIH R01** · UNIV OF MARYLAND, COLLEGE PARK · 2022 · $517,373

## Abstract

Project Summary
 New diagnostic tools capable of rapidly identifying and quantifying bacteria within intra-abdominal
infections are needed to help clinicians select appropriate antibiotics during the critical early stages of
treatment. Current molecular diagnostics remain costly and require access to significant laboratory
infrastructure, making them inappropriate for use in small satellite laboratories within the hospital
environment. Here we seek to address this urgent need by developing a simple, inexpensive, and
automated microfluidic platform capable of evaluating bacteria directly from intra-abdominal abscess
fluids to guide initial treatment of infection. The technology will combine on-chip nucleic acid extraction,
rapid quantitative PCR (qPCR), and high resolution melt analysis (HRMA) for multiplexed pathogen
identification and quantification in under 10 min. The platform will consist of disposable thermoplastic
microwell chips and a compact USB-powered reader containing all components for assay operation.
Significantly, the entire assay will require only two pipette strokes to discretize sample within a dense
array of microliter reaction wells containing all primers and other reagents needed for assay execution.
The integration of multiplexed PCR primers into the thermoplastic microwell array during chip
manufacture will enable automated thermally-controlled release during PCR, while passive sample
discretization within the disposable microwell arrays will further simplify assay operation. Assay times
below 10 min will be enabled by integrated thin film electrodes and a unique thermoplastic fabrication
technique supporting optimal thermal transport. A disposable piezoelectric element integrated into the
chip inlet tube will enable efficient release of nucleic acids prior to sample discretization, and the assay
will be operated through an embedded mixed-signal processor supporting all functions, with power
and communication provided through a single USB connection to a laptop computer. Using this
system, multiplexed qPCR for bacteria identification plus HRMA for product validation will be
demonstrated, followed by an investigation of qPCR-HRMA based pathogen identification using
unique signatures in the 16S rRNA gene, with a theoretical detection limit of 50 CFU/mL. The
technology will be validated within a hospital environment through a clinical study with 50 patients for
the simultaneous quantification of 8 bacteria commonly found in intra-abdominal infections, conditions
where treatment currently relies on subjective visual assessment and empiric treatment, and where
rapid near-patient bacterial identification would transform clinical practice.

## Key facts

- **NIH application ID:** 10335980
- **Project number:** 5R01AI153564-02
- **Recipient organization:** UNIV OF MARYLAND, COLLEGE PARK
- **Principal Investigator:** Don L DeVoe
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $517,373
- **Award type:** 5
- **Project period:** 2021-01-28 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10335980

## Citation

> US National Institutes of Health, RePORTER application 10335980, A rapid, automated system for bacteria profiling of intra-abdominal infections (5R01AI153564-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10335980. Licensed CC0.

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