CRISPR-Cas9-based electrochemical biosensor for the detection of katG gene mutations in isoniazid-resistant tuberculosis: Original scientific article

Dika Apriliana Wulandari; Muhammad Ihda Hamlu Liwaissunati Zein; Salma Nur Zakiyyah; Safri Ishmayana; Mehmet Ozsoz; Yeni Wahyuni Hartati; Irkham

doi:10.5599/admet.2766

Authors

Dika Apriliana Wulandari Department of Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Sumedang 45363, Indonesia https://orcid.org/0009-0003-8361-2116
Muhammad Ihda Hamlu Liwaissunati Zein Department of Chemistry “Giacomo Ciamician”, Alma Mater Studiorum – University of Bologna, Bologna 40126, Italy https://orcid.org/0000-0001-6656-7315
Salma Nur Zakiyyah Department of Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Sumedang 45363, Indonesia https://orcid.org/0000-0003-0985-5980
Safri Ishmayana Departmeent of Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Sumedang 45363, Indonesia https://orcid.org/0000-0002-9825-4425
Mehmet Ozsoz Department of Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Sumedang 45363, Indonesia and Department of Biomedical Engineering, Near East University, Mersin 99138, Turkey https://orcid.org/0000-0003-4037-3445
Yeni Wahyuni Hartati Department of Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Sumedang 45363, Indonesia and Study Center of Sensor and Green Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Bandung 40132, Indonesia https://orcid.org/0000-0003-1463-6352
Irkham Department of Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Sumedang 45363, Indonesia and Study Center of Sensor and Green Chemistry, Faculty of Mathematics and Natural Science, Universitas Padjadjaran, Bandung 40132, Indonesia https://orcid.org/0000-0001-9938-2931

DOI:

https://doi.org/10.5599/admet.2766

Keywords:

Electrochemistry, guide RNA, ferrocene signal, drug-resistant tuberculosis

Abstract

Background and purpose: Multidrug-resistant tuberculosis (MDR-TB) remains a significant challenge in tuberculosis (TB) treatment, driven by simultaneous mutations in the rpoB and katG genes that confer resistance to rifampicin and isoniazid. While many molecular diagnostic tools focus on rpoB, the katG gene is often overlooked despite its critical role in confirming MDR-TB. This study aims to develop a CRISPR/Cas9-based electrochemical biosensor for the rapid and selective detection of katG mutation. Experimental approach: A guide RNA (gRNA) specific to the mutation site on katG gene was designed using the Benchling CRISPR tool, considering on-target and off-target scores, specificity, and cleavage sites within the Mycobacterium tuberculosis genome. The selected gRNA achieved the highest on-target score of 61.2 and an off-target score of 49.0 at cut position 2928, with a PAM sequence of AGG. Its cleavage efficiency was validated experimentally using an electrochemical biosensing platform incorporating a gold-modified screen-printed carbon electrode (SPCE/Au). Redox response enhancement by [Fe(CN₆)]^3-/4- confirmed the improved performance of the electrode. Key results: The biosensor system detects the target DNA through hybridization with DNA probe-Fc, forming double-stranded DNA (dsDNA) that is recognized and cleaved by the Cas9/gRNA complex. This cleavage significantly reduces the ferrocene oxidation signal, indicating the presence of a katG mutation. Non-mutated target DNA produces a nondetectable ferrocene signal, suggesting that the Cas9 enzyme may remain bound to the electrode without cleavage. The CRISPR/Cas9 electrochemical biosensor demonstrated a low detection limit of 7.5530 aM and a detection range of 10¹ to 10⁶ aM. Conclusion: The CRISPR/Cas9-based electrochemical biosensor exhibits high sensitivity and specificity for the detection katG mutation, offering a promising platform for rapid MDR-TB diagnostics.

Downloads

Download data is not yet available.

References

[1] World Health Organization. Global Tuberculosis Report 2024, Available at https://doi.org/https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2024, accessed Agustus 2024

[2] D.A. Wulandari, Y.W. Hartati, A.U. Ibrahim, D.A.E Pitaloka, and Irkham. Multidrug-resistant tuberculosis. Clinica Chimica Acta 559 (2024) 119701. https://doi.org/10.1016/j.cca.2024.119701

[3] M. De Rycker, B. Baragaña, S.L. Duce, and I.H. Gilbert. Challenges and recent progress in drug discovery for tropical diseases. Nature 559 (2018) 498-506. https://doi.org/10.1038/s41586-018-0327-4

[4] V. Singh, K. Chibale. Strategies to combat multi-drug resistance in tuberculosis. Accounts of Chemical Research 54 (2021) 2361-2376. https://doi.org/10.1021/acs.accounts.0c00878

[5] L. Muthukrishnan. Multidrug resistant tuberculosis - Diagnostic challenges and its conquering by nanotechnology approach - An overview. Chemico-Biological Interactions 337 (2021) 109397. https://doi.org/10.1016/j.cbi.2021.109397

[6] A. Jain, P Dixit. Multidrug resistant to extensively drug resistant tuberculosis: What is next? Journal of Biosciences 33 (2008) 605-616. https://doi.org/10.1007/s12038-008-0078-8

[7] J.L. Khawbung, D. Nath, and S. Chakraborty, Drug resistant tuberculosis: A review. Comparative Immunology, Microbiology and Infectious Diseases 74 (2021) 101574. https://doi.org/10.1016/j.cimid.2020.101574

[8] J.G. Jang , J.H. Chung. Diagnosis and treatment of multidrug-resistant tuberculosis. Yeungnam University Journal of Medicine 34 (2020) 277-285. https://doi.org/10.12701/yujm.2020.00626

[9] E. Rivière, M.G. Whitfield, J. Nelen, T.H. Heupink, A.V. Rie. Identifying isoniazid resistance makers to guide inclusion of high-dose isoniazid in tuberculosis treatment regimens. Clinical Microbiology and Infection 26 (2020) 1332-1337. https://doi.org/10.1016/j.cmi.2020.07.004

[10] C. Metcalfe, I.K. Macdonald, E.J. Murphy, K.A. Brown, E.L. Raven, P.C.E. Moody. The tuberculosis prodrug isoniazid bound to activating peroxidases. Journal of Biological Chemistry 283 (2008) 6193-6200. https://doi.org/10.1074/jbc.M707412200

[11] P. Purkan, I. Ihsanawati, D. Natalia, Y.M. Syah, D.S. Retnoningrum, I. Siswanto. Molecular analysis of katG encoding catalase-peroxidase from clinical isolate of isoniazid-resistant mycobacterium tuberculosis. Journal of Medicine and Life 11 (2018) 160-167. https://pmc.ncbi.nlm.nih.gov/articles/PMC6101688/

[12] W.J. Koh, Y. Ko, C.K. Kim, K.S. Park, N.Y. Lee. Rapid Diagnosis of tuberculosis and multidrug resistantce using a MGIT 960 system. Annals of Laboratory Medicine 32 (2012) 264-269. http://dx.doi.org/10.3343/alm.2012.32.4.264

[13] A.H. Salim, K.J.M Aung, M.A Hossain, A.V. Deun. Early and rapid microscopy-based diagnosis of true treatment failure and MDR-TB. The International Journal of Tuberculosis and Lung Disease 10 (2006) 1248-1254. https://pubmed.ncbi.nlm.nih.gov/17131784/

[14] C.C. Boehme, P. Nabeta, D. Hillemann, M.P. Nicol, S. Shenai, F, Krapp, J. Allen, R. Tahirli, R. Blakemore, R. Rustomjee, A. Milovic, M. Jones, S. M. O’brien, D.H. Persing, S. Ruesch-Gerdes, E. Gotuzzo, C. Rodrigues, D. Alland, M.D. Perkins. Rapid Molecular Detection of tuberculosis and rifampicin resistant. The New England Journal of Medicine 363 (2010) 1005-1015. https://doi.org/10.1056/nejmoa0907847

[15] J.E. van Dongen, J.T.W. Berendsen, R.D.M. Steenbergen, R.M.F. Wolthuis, J.C.T. Eijkel, L.I. Segerink. Point-of-care CRISPR/Cas nucleic acid detection: recent advances, challenges and opportunities. Biosensors and Bioelectronics 166 (2020) 112445. https://doi.org/10.1016/j.bios.2020.112445

[16] M. Wang, R. Zhang, J. Li. CRISPR/Cas system redefine nucleic acid detection: principles and methods. Biosensors and Bioelectronics 165 (2020) 112430. https://doi.org/10.1016/j.bios.2020.112430

[17] M.I.H.L. Zein, A. Hardianto, Irkham, Y.W. Hartati, Identification of CRISPR/Cas12a (Cpf1) guideRNA Sequence Targeting the Mitochondrial DNA D-loop Region in Wild Pig (Sus scrofa) Through Homology Difference and Mismatch Analysis. Trends in Sciences 21 (2024) 7603. https://doi.org/10.48048/tis.2024.7603

[18] V. Konstantakos, A. Nentidis, A. Krithara, G. Paliouras, CRISPR-Cas9 gRNA efficiency prediction: an overview of predictive tools and the role of deep learning, Nucleic Acids Research 50 (2022) 3616-3637. https://doi.org/10.1093/nar/gkac192

[19] S.N. Zakiyyah, A.U. Ibrahim, M.S. Babiker, S. Gaffer, M. Ozsoz, M.I.H.L. Zein, Y.W. Hartati. Detection of Tropical Diseases Caused by Mosquitoes Using CRISPR-Based Biosensors. Tropical Medicine and Infectious Disease 7 (2022) 309. https://doi.org/10.3390/tropicalmed7100309

[20] Irkham, A.U. Ibrahim, P.C. Pwavodi, C.W. Nwekwo, Y.W. Hartati. CRISPR-based biosensor for the detection of Marburg and Ebola virus. Sensing and Bio-Sensing Research 43 (2024) 100641. https://doi.org/10.1016/j.sbsr.2023.100601

[21] Irkham, A.U. Ibrahim, C.W. Nwekwo, P.C. Pwavodi, S.N. Zakiyyah, M. Ozsoz, Y.W. Hartati. From nanotechnology to AI: The next generation of CRISPR-based smart biosensors for infectious disease detection. Microchemical Journal 208 (2025) 112577. https://doi.org/10.1016/j.microc.2024.112577

[22] G.I. Corsi, K. Qu, F. Alkan, X. Pan, Y. Luo, J. Gorodkin. CRISPR/Cas9 gRNA activity depends on free energy changes and on the target PAM context. Nature Communication 13 (2022) 3006. https://doi.org/10.1038/s41467-022-30515-0

[23] F.J.M. Mojica, C. Díez-Villaseñor, J. García-Martínez, C. Almendros. Short motif sequences determine the targets of the prokaryotic CRISPR defence system. Microbiology 155 (2009) 733-740. https://doi.org/10.1099/mic.0.023960-0

[24] N. Wong, W. Liu, X. Wang. WU-CRISPR: Characteristics of functional guide RNAs for the CRISPR/Cas9 system. Genome Biology 16 (2015) 218. https://doi.org/10.1186/s13059-015-0784-0

[25] L. Augustin, N. Agarwal. Designing a Cas9/gRNA-assisted quantitative real-time PCR (CARP) assay for identification of point mutations leading to rifampicin resistance in the human pathogen mycobacterium tuberculosis. Gene 857 (2023) 147173. https://doi.org/10.1016/j.gene.2023.147173

[26] E. Kivrak, T. Pauzaite, M.A. Copeland, J.G. hardy, P. Kara, M. Firlak, A.I. Yardimci, S. Yilmaz, F. Palaz, M. Ozsoz. Detection of CRISPR-Cas9-Mediated Mutations Using a Carbon Nanotube-Modified Electrochemical Genosensor. Biosensors 11/1) (2021) 17. https://doi.org/10.3390/bios11010017.

[27] M.I.H.L. Zein, C.Y. Kharismasari, A. Hardianto, S.N. Zakiyyah, R. Amalia, M. Ozsoz, M. Mirasoli, Irkham, Y.W. Hartati. A CRISPR/Cas12a electrochemical biosensing to detect pig mtDNA D-loop for ensuring food authenticity. Sensing and Bio-Sensing Research 47 (2025) 100755. https://doi.org/10.1016/j.sbsr.2025.100755

[28] H.N. Nguyen,, S. Hwang, S.W. Lee, E. Jin, M. Lee. Detection of HPV 16 and 18 L1 genes by a nucleic acid amplification-free electrochemical biosensor powered by CRISPR/Cas9. Bioelectrochemistry 162 (2025) 108861. https://doi.org/10.1016/j.bioelechem.2024.108861

[29] National Center for Biotechnology Information (NCBI). NCBI Nucleotide: AL123456.3 Mycobacterium tuberculosis H37Rv complete genome. https://www.ncbi.nlm.nih.gov/nuccore/AL123456.3 (accessed November 2, 2023)

[30] National Center for Biotechnology Information (NCBI). NCBI Nucleotide: AL123456.3 Mycobacterium tuberculosis H37Rv complete genome (rpoB gene). https://www.ncbi.nlm.nih.gov/nuccore/AL123456.3?from=759807&to=76332%205 (accessed November 2, 2023)

[31] National Center for Biotechnology Information (NCBI). NCBI Nucleotide: X68081.1 Mycobacterium tuberculosis gene for catalase-peroxidase (katG). https://www.ncbi.nlm.nih.gov/nuccore/X68081.1 (accessed November 2, 2023).

[32] M. Haeussler, K. Schönig, H. Eckert, A. Eschstruth, J. Mianné, J.B. Renaud, S. Schneider-Maunoury, A. Shkumatava, L. Teboul, J. Kent, J.S. Joly, J.P. Concordet. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biology 17 (2016) 148. https://doi.org/10.1186/s13059-016-1012-2

[33] J.G. Doench, N. Fusi, M. Sullender, M. Hedge, E.W. Vaimberg, K.F. Donovan, I. Smith, Z. Tothova, C. Wilen, R. Orchard, H.W. Virgin, J. Listgarten, D.E. Root. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nature Biotechnology 34 (2016) 184-191. https://doi.org/10.1038/nbt.3437

[34] P.D. Hsu, D.A. Scott, J.A. Weinstein, F.A. Ran, S. Konermann, V. Agarwala, Y. Li, E.J. Fine, X. Wu, O. Shalem, T.J. Cradick, L.A. Marraffini, G. Bao, F. Zhang. DNA targeting specificity of RNA-guided Cas9 nucleases. Nature Biotechnology 31 (2013) 827-832. https://doi.org/10.1038/nbt.2647

[35] T. Zheng, Y. Hou, P. Zhang, Z. Zhang, Y. Xu, L. Zhang, L. Niu, Y. Yang, D. Liang, F. Yi, W. Peng, W. Feng, Y. Yang, J. Chen, Y.Y. Zhu, L.H. Zhang, Q. Du. Profiling single-guide RNA specificity reveals a mismatch sensitive core sequence. Scientific Reports 8 (2017) 40638. https://doi.org/10.1038/srep40638

[36] S.C. Strutt, R.M. Torrez, E. Kaya, O.A. Negrete, Doudna. Jennifer A. RNA-dependent RNA targeting by CRISPR-Cas9. eLife 7 (2018) e32724. https://doi.org/10.7554/eLife.32724

[37] M. Zhou, X. Li, H. Wen, B. Huang, J. Ren, J. Zhang. The construction of CRISPR/Cas9-mediated FRET 16S rDNA sensor for detection of Mycobacterium tuberculosis. Analyst 148 (2023) 2308-2315. https://doi.org/10.1039/d3an00462g

[38] J. Huang, Z. Liang, Y. Liu, J. Zhou, F. He. Development of an MSPQC Nucleic Acid Sensor Based on CRISPR/Cas9 for the Detection of Mycobacterium tuberculosis. Analytical Chemistry 94 (2022) 11409-11415. https://doi.org/10.1021/acs.analchem.2c02538

[39] S.N. Zakiyyah, N.P. Satriana, N. Fransisca, S. Gaffar, N. Syakir, Irkham, Y.W. Hartati. Gold nanoparticle-modified screen-printed carbon electrodes for label-free detection of SARS-CoV-2 RNA using drop casting and spray coating methods. ADMET & DMPK 13 (2025) 2577. https://doi.org/10.5599/admet.2577

[40] C.J. Weber, N.E. Strom, O. Simoska. Electrochemical deposition of gold nanoparticles on carbon ultramicroelectrode arrays. Nanoscale 16 (2024) 16204-16217. https://doi.org/10.1039/D4NR02326A

[41] S. Zuliska, Irkham, S.N. Zakiyyah, Y.W. Hartati, Y.Einaga, I.P.Maksum. Electrochemical aptasensor for ultrasensitive detection of glycated hemoglobin (HbA1c) using gold-modified SPCE. Sensing and Bio-Sensing Research 47 (2025) 100765. https://doi.org/10.1016/j.sbsr.2025.100765

[42] C.M. Dundas, D. Demonte, S. Park. Streptavidin-biotin technology: improvements and innovations in chemical and biological applications. Applied Microbiology and Biotechnology 97 (2013). 9343-9353. https://doi.org/10.1007/s00253-013-5232-z

[43] M. Drozd, S. Karoń, E. Malinowska. Recent Advancements in Receptor Layer Engineering for Applications in SPR-Based Immunodiagnostics. Sensors 21(11) (2021) 3781. https://doi.org/10.3390/s21113781

[44] F. Gao, G. Liu, Y. Qiao, X. Dong, L. Liu. Streptavidin-Conjugated DNA for the Boronate Affinity-Based Detection of Poly(ADP-Ribose) Polymerase-1 with Improved Sensitivity. Biosensors 13 (2023) 723. https://doi.org/10.3390/bios13070723

[45] F.V. Oberhaus, D. Frense, D. Beckmann. Immobilization Techniques for Aptamers on Gold Electrodes for the Electrochemical Detection of Proteins: A Review. Biosensors 10 (2020) 45. http://dx.doi.org/10.3390/bios10050045

[46] G. Ströhle, H. Li. Comparison of blocking reagents for antibody microarray‑based immunoassays on glass and paper membrane substrates. Analytical and Bioanalytical Chemistry 415 (2023). 1967-1977. https://doi.org/10.1007/s00216-023-04614-w

[47] N. Chen, Z.J. Wu, H.C. Xu. Ferrocene as a Redox Catalyst for Organic Electrosynthesis. Israel Journal of Chemistry 64 (2023). https://doi.org/10.1002/ijch.202300097

[48] V. Mekler, L. Minakhin, K. Severinov. Mechanism of duplex DNA destabilization by RNA-guided Cas9 nuclease during target interrogation. The Proceedings of the National Academy of Sciences (PNAS) 114 (2017) 5443-5448. https://doi.org/10.1073/pnas.1619926114

[49] S. H. Sternberg, B. LaFrance, M. Kaplan, J. A. Doudna. Conformational control of DNA target cleavage by CRISPR-Cas9. Nature 527(2015) 110 - 113. https://doi.org/10.1038/nature15544

[50] F. Jiang, D. W. Taylor, J. S. Chen, J. E. Kornfeld, K. Zhou, A. J. Thompson, E. Nogales, J. A. Doudna. Structures of a CRISPR-Cas9 R-loop complex primed for DNA cleavage. Science 351 (2016) 867-871. https://doi.org/10.1126/science.aad8282