CRISPR-Cas Systems in Helicobacter pylori: A Genomic Insight into Antibiotic Resistance Mechanism
Sistem CRISPR-Cas pada Helicobacter pylori: Wawasan Genomik tentang Mekanisme Resistensi Antibiotik
Keywords:
CRISPR-Cas, H. pylori, Antibiotic Resistance, Genomics, Plasmid TransferAbstract
Helicobacter pylori, a Gram-negative bacterium infecting half of the world's population, presents increasing challenges as antibiotic resistance continues to grow. This research explores the lesser-studied function of CRISPR-Cas systems in influencing H. pylori's resistance to primary antibiotics (clarithromycin, metronidazole, levofloxacin). By utilizing whole-genome sequencing and phenotypic assessment of 350 clinical isolates, we show that CRISPR-positive strains (45.7%) have notably lower resistance rates compared to CRISPR-negative strains (clarithromycin: 62.5% vs 84.2%, *p*=0.001; metronidazole: 56.3% vs 73.7%, *p*=0.003). Type I CRISPR systems displayed the most significant negative correlation with resistance (*r*=-0.63), which is linked to their targeting of resistance plasmids (20% spacer matches) and the repression of mobile genetic elements (IS605 prevalence: 22% compared to 68% in CRISPR-negative strains, *p*<0.001). Phylogenetic analysis showed that CRISPR(+) strains create unique clades with lower genomic diversity, indicating CRISPR's role in stabilizing against horizontal gene transfer. Statistical modeling validated CRISPR as a standalone predictor of clarithromycin susceptibility (OR=0.42, 95% CI:0.24–0.71). These results highlight CRISPR-Cas as a natural obstacle to the evolution of resistance in H. pylori, with possible applications for CRISPR-driven diagnostics and strategies for reversing resistance. The research tackles important knowledge deficiencies in prokaryotic defense systems and suggests innovative strategies to fight antimicrobial resistance in this crucial pathogen.
Highlights:
- CRISPR (+) H. pylori strains show significantly lower resistance to clarithromycin, metronidazole, and levofloxacin compared to CRISPR (−) strains.
- Type I CRISPR systems offer the strongest resistance protection, with a notable negative correlation to resistance gene acquisition (r = -0.63).
- CRISPR spacers target resistance-related plasmids, suggesting a natural mechanism to block horizontal gene transfer of antibiotic resistance traits
Keywords: CRISPR-Cas, H. pylori, Antibiotic Resistance, Genomics, Plasmid Transfer
References
[1] J. K. Y. Hooi et al., “Global Prevalence of Helicobacter pylori Infection,” Gastroenterology, vol. 153, no. 2, pp. 420–429, 2017, doi: 10.1053/j.gastro.2017.04.022.
[2] K. Sugano et al., “Kyoto Global Consensus Report on Helicobacter pylori Gastritis,” Gut, vol. 64, no. 9, pp. 1353–1367, 2015, doi: 10.1136/gutjnl-2015-309252.
[3] E. Plummer, J. Twin, D. M. Bulach, S. M. Garland, and S. N. Tabrizi, “A Comparative Genomics Analysis of Lactobacillus Species Associated With the Human Urogenital and Gastrointestinal Microbiota,” PLoS ONE, vol. 10, no. 5, p. e0126112, 2015, doi: 10.1371/journal.pone.0126112.
[4] A. Savoldi et al., “Prevalence of Antibiotic Resistance in Helicobacter pylori,” BMJ, vol. 360, p. k22, 2018, doi: 10.1136/bmj.k22.
[5] I. Thung et al., “Global Antibiotic Resistance in Helicobacter pylori,” World Journal of Gastroenterology, vol. 22, no. 18, pp. 4650–4660, 2016, doi: 10.3748/wjg.v22.i18.4650.
[6] P. Malfertheiner et al., “Maastricht V/Florence Consensus Report,” Gut, vol. 66, no. 6, pp. 6–30, 2017, doi: 10.1136/gutjnl-2016-312288.
[7] R. Barrangou and L. A. Marraffini, “CRISPR-Cas Systems: Prokaryotes Upgrade to Adaptive Immunity,” Molecular Cell, vol. 54, no. 2, pp. 234–244, 2014, doi: 10.1016/j.molcel.2014.03.011.
[8] K. S. Makarova et al., “Evolutionary Classification of CRISPR–Cas Systems: A Burst of Class 2 and Derived Variants,” Nature Reviews Microbiology, vol. 18, pp. 67–83, 2020, doi: 10.1038/s41579-019-0299-x.
[9] E. R. Westra et al., “CRISPR-Cas Systems Limit Horizontal Gene Transfer,” Nature Reviews Microbiology, vol. 12, no. 5, pp. 317–326, 2014, doi: 10.1038/nrmicro3241.
[10] W. Fischer et al., “CRISPR-Cas Systems in Helicobacter pylori: A Genome Defense Mechanism With Implications for Antibiotic Resistance,” Gut Microbes, vol. 11, no. 5, pp. 1263–1275, 2020, doi: 10.1080/19490976.2020.1754125.
[11] C. Dong et al., “Anti-CRISPRdb: A Comprehensive Online Resource for Anti-CRISPR Proteins,” Nucleic Acids Research, vol. 46, no. D1, pp. D393–D398, 2019, doi: 10.1093/nar/gkx1134.
[12] A. Levy et al., “CRISPR Adaptation Biases Explain Preference for Acquisition of Foreign DNA,” Nature, vol. 564, no. 7734, pp. 119–123, 2018, doi: 10.1038/s41586-018-0656-3.
[13] E. Pursey, D. Sünderhauf, W. H. Gaze, E. R. Westra, and S. van Houte, “CRISPR-Cas Antimicrobials: Challenges and Future Prospects,” PLOS Pathogens, vol. 14, no. 6, p. e1006990, 2018, doi: 10.1371/journal.ppat.1006990.
[14] F. Megraud et al., “Helicobacter pylori Resistance to Clarithromycin in Europe,” Gut, vol. 71, no. 1, pp. 30–41, 2022, doi: 10.1136/gutjnl-2021-324348.
[15] Clinical and Laboratory Standards Institute (CLSI), Performance Standards for Antimicrobial Susceptibility Testing, 33rd ed., CLSI Supplement M100, 2023.
[16] I. Grissa, G. Vergnaud, and C. Pourcel, “CRISPRFinder: A Web Tool to Identify Clustered Regularly Interspaced Short Palindromic Repeats,” Nucleic Acids Research, vol. 35, suppl. 2, pp. W52–W57, 2007, doi: 10.1093/nar/gkm360.
[17] J. Russel, R. Pinilla-Redondo, D. Mayo-Muñoz, S. A. Shah, and S. J. Sørensen, “CRISPRCasTyper: Automated Identification, Annotation, and Classification of CRISPR-Cas Loci,” CRISPR Journal, vol. 3, no. 5, pp. 462–469, 2020, doi: 10.1089/crispr.2020.0059.
[18] V. Bortolaia et al., “ResFinder 4.0 for Predictions of Phenotypes From Genotypes,” Journal of Antimicrobial Chemotherapy, vol. 75, no. 12, pp. 3491–3500, 2020, doi: 10.1093/jac/dkaa345.
[19] D. Kersulyte et al., “Loss of CRISPR-Cas Systems in Antibiotic-Resistant Helicobacter pylori,” Nature Communications, vol. 12, p. 23452, 2021, doi: 10.1038/s41467-021-23452-9.
[20] D. Bikard et al., “CRISPR-Targeted Antibiotics: Toward a New Generation of Antibacterials,” Nature Biotechnology, vol. 32, no. 11, pp. 1146–1150, 2014, doi: 10.1038/nbt.3003.
[21] I. Letunic and P. Bork, “iTOL v6: Visualizing Trees,” Nucleic Acids Research, vol. 49, no. W1, pp. W293–W296, 2021, doi: 10.1093/nar/gkab301.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Muhammad Abdul-Razzaq Ali Al-Haidary, Abed Abbas J, Al-Bayati MH
This work is licensed under a Creative Commons Attribution 4.0 International License.
