2D mxene-graphene heterostructure platform for rapid crispr-based pathogen detection
A next-generation electrochemical biosensing platform combining MXene-graphene heterostructures with CRISPR detection to identify pathogens such as Salmonella in under 15 minutes. The technology offers tunable band gap and capacitance properties for high sensitivity and specificity, with potential expansion to GMO plant detection and other DNA/RNA targets.
Overview
This project develops a rapid, highly sensitive biosensing platform that integrates two-dimensional MXene-graphene heterostructure materials with CRISPR-based detection. The platform targets foodborne and agricultural threats, with Salmonella as the model organism and future expansion to additional DNA/RNA targets including GMO plants. By leveraging the unique tunable electrochemical properties of MXene-graphene composites, the technology aims to deliver results in under 15 minutes, far outperforming conventional detection methods that require 24 to 28 hours. The approach combines the molecular precision of CRISPR with advanced nanomaterials to create a versatile multi-agent sensing platform.
Technical specifications
Core technology components:
- MXene-graphene heterostructure materials with tunable band gap and capacitance properties for enhanced electrochemical signal detection
- CRISPR detection system utilizing dCas9 and Cas12a enzymes for high-specificity target recognition, including single nucleotide polymorphism discrimination
- Custom-designed guide RNAs (gRNAs) tailored to specific pathogens and serotypes, with Salmonella serotype-level detection as the demonstrated model
- Field-effect transistor (FET) sensor architecture enabling real-time, label-free detection of unamplified DNA/RNA targets
- Functional group binding chemistry to attach dCas9 enzymes to MXene surface terminating groups, characterized via XRD, XPS, and FT-IR techniques
- Real-time sensing device capable of providing results comparable to real-time PCR
Key performance advantages:
- Detection time under 15 minutes versus 24-28 hours for traditional methods
- Single nucleotide polymorphism sensitivity without target amplification
- Multi-agent detection capability through CRISPR programmability
- Tunable sensing parameters via MXene material selection and structural optimization
Technology readiness level
The platform is currently at an early-to-mid stage of development. Preliminary validation has demonstrated theoretical support for probe-MXene equilibrium distances within the Debye length, initial capacitance measurements, and DFT-calculated band gaps confirming sensitivity improvements for the MXene-graphene FET. Proof-of-concept testing with ssDNA probes has been completed for SARS-CoV-2 and its Omicron variant, and an initial real-time sensing device has been demonstrated. Ongoing and planned validation efforts include designing and evaluating Salmonella-specific gRNAs, characterizing enzyme-material binding affinity and covalent bonding, and preparing and validating two CRISPR-MXene-graphene sensor configurations. The technology is positioned for continued laboratory validation and refinement before commercial deployment.
About Texas A&M University, College Station
Texas A&M University in College Station is a comprehensive public research university and the flagship of The Texas A&M University System, combining broad academic strengths with a strong applied‑research culture. Industry collaborates on the Texas A&M‑RELLIS campus—an integrated education, research and testing environment that supports large‑scale experimentation and proving grounds—and through the Texas A&M Transportation Institute’s facilities in Bryan‑College Station. A statewide extension network connects university expertise to companies and communities across all Texas counties, enabling rapid piloting and deployment. Research is supported by competitive federal funding from agencies such as NSF, NIH, DOE, USDA and DoD, alongside state and industry sponsorship. Texas A&M Innovation provides IP management, licensing and commercialization pathways across the system.
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