Year: 2022
Type: article
Abstract: Nanopore sensors have shown great utility in nucleic acid detection and sequencing approaches. Recent studies also indicate that current signatures produced by peptide-nanopore interactions can distinguish high purity peptide mixtures, but the utility of nanopore sensors in clinical applications still needs to be explored due to the inherent complexity of clinical specimens. To fill this gap between research and clinical nanopore applications, we describe a methodology to select peptide biomarkers suitable for use in an immunoprecipitation-coupled nanopore (IP-NP) assay, based on their pathogen specificity, antigenicity, charge, water solubility and ability to produce a characteristic nanopore interaction signature. Using tuberculosis as a proof-of-principle example in a disease that can be challenging to diagnose, we demonstrate that a peptide identified by this approach produced high-affinity antibodies and yielded a characteristic peptide signature that was detectable over a broad linear range, to detect and quantify a pathogen-derived peptide from digested human serum samples with high sensitivity and specificity. This nanopore signal distinguished serum from a TB case, non-disease controls, and from a TB-case after extended anti-TB treatment. We believe this assay approach should be readily adaptable to other infectious and chronic diseases that can be diagnosed by peptide biomarkers.
Source: Nano Today
Institutions: Tulane University, University of South Carolina
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,690
Awards: Quantification of brain-derived extracellular vesicle microRNAs in blood by a liposome-mediated CRISPR assay for traumatic brain injury detection, G1403152943, G2224762734, G2292002165, G3004649480, G3765401515, G4241728406, G4705169589, Digital Nanoplasmonic Quantification of Tumor-derived Extracellular Vesicles in Plasma Microsamples, G9000126022, G9000209726, G9000286477, G9000322685, G9000328141, Detecting pathogen and host factors on extracellular vesicles for pediatric TB diagnosis and management
OpenAlex ID: W4281759147
