Label-free electronic detection of peptide post-translational modification with functional enzyme-driven assay at the physical limit

  • Eleonora Macchia
  • , Kim Björkström
  • , Amit Tewari
  • , Ville Eskonen
  • , Axel Luukkonen
  • , Amir Mohammad Ghafari
  • , Lucia Sarcina
  • , Mariapia Caputo
  • , Natalia Tong-Ochoa
  • , Kari Kopra
  • , Fredrik Pettersson
  • , Zahra Gounani
  • , Luisa Torsi
  • , Harri Härmä*
  • , Ronald Österbacka*
  • *Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
33 Downloads (Pure)

Abstract

High-performance, ultra-sensitive, and universal protein post-translational modification (PTM) and protein-protein interaction (PPI) technologies are eagerly pursued in the pharmaceutical industry and bioanalytical research. Novel PTM and PPI detection methods outperform traditional assays in scope and scalability, enabling the collection of information on multiple biochemical targets. Detecting peptides and proteins at the single-molecule level is done by utilizing nanosized transducing elements and assaying solutions at very high analyte concentrations, in the nanomolar range or higher. Here, a proof of principle of a biosensing platform for single-molecule PTM detection is demonstrated. This platform is based on the single molecule with a large transistor (SiMoT) technology, encompassing a millimeter-sized electrolyte-gated organic field-effect transistor, for label-free PTM detection with a zeptomolar limit of detection. Sensitivity is improved 106- to 1012-fold compared with mass-spectrometry and luminescence-based assay methods. A functional assay for detecting enzyme-driven peptide PTMs in the zeptomolar concentration range is demonstrated using multivariate data processing, opening the way for future applications to monitor PTMs.

Original languageEnglish
Article number101874
JournalCell Reports Physical Science
Volume5
Issue number8
DOIs
Publication statusPublished - 21 Aug 2024
MoE publication typeA1 Journal article-refereed

Funding

The authors acknowledge Prof. Carl-Eric Wil\u00E9n and Ms. Pernilla Sund for useful discussions in this work's early stages. The following are all acknowledged for partial financial support: Academy of Finland projects 296225, 323433, 269973, 316881, 316883, 332106, 296093, and 270010; PON SISTEMA (MIUR); H2020, Electronic Smart Systems, SiMBiT (single-molecule bioelectronic smart system array for clinical testing) (grant agreement ID: 824946); Doctoral Network of Materials Research at \u00C5bo Akademi University; NoOne (a binary sensor with a single-molecule digit to discriminate biofluids enclosing zero or at least one biomarker), ERC Stg2021, GA:101040383; I primi mille clinical trial con il Centro DIGITAL ASSAY, Centro di Innovazione Regionale Digital Assay, Presidente Prof. L. Torsi; Responsabile Scientifico UNIBA E. Macchia Regione PUGLIA Delibera Regionale n 702 del 08/11/2022 (CUP B93C22000840001); PMGB \u2013 Sviluppo di piattaforme meccatroniche, genomiche e bioinformatiche per l'oncologia di precisione and ARS01_01195 \u2013 PON RICERCA E INNOVAZIONE 2014\u20132020 projects; Italian network of excellence for advanced diagnosis (INNOVA), Ministero della Salute -code PNC-E3-2022-23683266 PNC-HLS-DA, CUP: C43C22001630001; Complementary National Plan PNC-I.1 research initiatives for innovative technologies and pathways in the health and welfare sector D.D. 931 of 06/06/2022; DARE (DigitAl lifelong pRevEntion initiative), code PNC0000002, CUP: B53C22006420001; \u00C5bo Akademi University CoE bioelectronic activation of cell functions; CSGI - Center for Colloid and Surface Science; Vilho, Yrj\u00F6, and Kalle V\u00E4is\u00E4l\u00E4 Foundation; and the Drug Research Doctoral Programme (University of Turku Graduate School). Conceptualization, L.T. H.H. and R.\u00D6.; methodology, V.E. N.T.-O. K.K. L.T. H.H. and R.\u00D6.; validation, E.M. K.B. A.T. and F.P.; formal analysis, E.M. K.B. A.T. V.E. A.L. and F.P.; investigation, E.M. K.B. A.T. V.E. A.M.G. L.S. M.C. F.P. and Z.G.; resources, V.E. A.M.G. L.S. M.C. N.T.-O. K.K. and Z.G.; data curation, E.M. and A.T.; writing \u2013 original draft and review & editing, E.M. K.B. L.T. H.H. and R.\u00D6.; visualization, E.M. K.B. and A.T.; supervision, L.T. H.H. and R.\u00D6.; project administration, L.T. H.H. and R.\u00D6. The authors declare no competing interests. The authors acknowledge Prof. Carl-Eric Wil\u00E9n and Ms. Pernilla Sund for useful discussions in this work\u2019s early stages. The following are all acknowledged for partial financial support: Academy of Finland projects 296225, 323433, 269973, 316881, 316883, 332106, 296093, and 270010; PON SISTEMA ( MIUR ), H2020, Electronic Smart Systems, SiMBiT (single-molecule bioelectronic smart system array for clinical testing) (grant agreement ID: 824946 ); Doctoral Network of Materials Research at \u00C5bo Akademi University , NoOne (a binary sensor with a single-molecule digit to discriminate biofluids enclosing zero or at least one biomarker), ERC Stg2021 , GA: 101040383 ; I primi mille clinical trial con il Centro DIGITAL ASSAY, Centro di Innovazione Regionale Digital Assay ; Presidente Prof. L. Torsi; Responsabile Scientifico UNIBA E. Macchia Regione PUGLIA Delibera Regionale n 702 del 08/11/2022 ( CUP B93C22000840001 ); PMGB \u2013 Sviluppo di piattaforme meccatroniche , genomiche e bioinformatiche per l\u2019oncologia di precisione and ARS01_01195 \u2013 PON RICERCA E INNOVAZIONE 2014\u20132020 projects; Italian network of excellence for advanced diagnosis ( INNOVA ), Ministero della Salute -code PNC-E3-2022-23683266 PNC-HLS-DA , CUP: C43C22001630001 ; Complementary National Plan PNC-I.1 research initiatives for innovative technologies and pathways in the health and welfare sector D.D. 931 of 06/06/2022; DARE ( DigitAl lifelong pRevEntion initiative ), code PNC0000002 , CUP: B53C22006420001 ; \u00C5bo Akademi University CoE bioelectronic activation of cell functions , CSGI ; Vilho , Yrj\u00F6 , and Kalle V\u00E4is\u00E4l\u00E4 Foundation ; and the Drug Research Doctoral Programme (University of Turku Graduate School).

Keywords

  • multivariate data processing
  • organic bioelectronics
  • peptide detection
  • SiMoT
  • single-molecule assay with large transistors
  • single-molecule detection

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