Advancements in CRISPR Technology for Studying Antibiotic

Resistance Mechanisms in Bacteria

Ziyi Xu

Collage of Biological Sciences, University of Guelph, Ontario, Canada

Keywords: CRISPR‑Cas Systems, Antibiotic Resistance, Gene Editing.

Abstract: Antibiotic resistance (AR) is a global threat in terms of public health that lowers the efficacy of antibiotics as

well as raises disease loads. While traditional genomics-based strategies have worked in detecting resistance

genes in bacteria, these strategies are not reliable in functional validation of genes. The emergence of CRISPR

(Clustered Regularly Interspaced Short Palindromic Repeats) technologies has ushered in a very potent gene-

editing tool in understanding resistance in bacteria. This paper is a discussion on recent advancements in

CRISPR-Cas9, CRISPRi, and CRISPRa application in resistance gene research, in designing antibacterial

strategies, as well as in modulating metabolic pathways in bacteria. Furthermore, it explores CRISPR

application in phage therapy, novel antibiotic development, as well as resistance gene modification. Future

research will involve improving CRISPR delivery methods, increasing specificity in CRISPR editing, as well

as incorporating synthetic biology strategies toward more potent anti-resistance therapies.

1 INTRODUCTION

Antibiotic resistance (AR) poses a global threat to

human health. The World Health Organization

(WHO) projects that in 2050, over 10 million will be

annually killed by antibiotic-resistant infections

(WHO, 2020). Over recent years, multidrug-resistant

(MDR) and extensive drug-resistant (XDR) bacteria

have escalated the frequency at which antibiotics are

becoming ineffective, with bacterial antimicrobial

resistance (AMR) having 1.27 million reported deaths

in 2019 alone. Resistance in bacteria is achieved in a

variety of ways, including through enzymes that

break down (degrade) antibiotics (e.g., β-lactamases);

through efflux pumps (e.g., AcrAB-TolC), which

pump out (actively remove from a bacterium)

antibiotics (Du et al., 2018); and through target

modification (e.g., 23S rRNA methylation), which

lowers binding affinity between antibiotics and target

(Wilson, 2014). The bacteria also lower membrane

permeability, which lowers entrance into bacteria, as

well as transfer resistance genes via horizontal gene

transfer (HGT) pathways, which involve plasmid, as

well as bacteriophage, mediated gene transfer.

Genomesequence-based approaches as well as

transcriptome wide sequencing have identified a vast

array of resistance-coding genes; these approaches

are correlation-based alone and lack a direct means of

ascertaining gene functionality. Over recent years,

CRISPR-Cas technologies have evolved as a highly

targeted gene-editing platform that holds a new

approach toward understanding antibiotic resistance.

The advent of CRISPR started with the discovery

of short, repeated units in the genome of Escherichia

coli by Ishino et al. subsequently established that

these repeats can be utilized in order to store virus-

derived DNA segments that facilitate bacteria in

forming immunological memories that can be utilized

in defense against bacteriophage infections.

Barangou et al. proceeded with establishing that

CRISPR-Cas is a defense mechanism that can

specifically target as well as cleave invasive DNA. In

2012, CRISPR-Cas9 as a gene-editing platform was

established by Doudna as well as Charpentier,

followed by its utilization in mammalian cells by

Zhang et al. (2013), which paved its way towards

extensive utilization in genetic modification. CRISPR

over a time developed into a range of forms, which

are CRISPR-Cas9 (for gene modification as well as

knocking out), CRISPRi (for inhibition in gene

expression by binding with dCas9), as well as

CRISPRa (for activation in gene expression with

transcriptional activation factors) (Zhang et al.,

2013). All these developments have immensely

124

Xu, Z.

Advancements in CRISPR Technology for Studying Antibiotic Resistance Mechanisms in Bacteria.

DOI: 10.5220/0014431700004933

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Biomedical Engineering and Food Science (BEFS 2025), pages 124-127

ISBN: 978-989-758-789-4

improved specificity as well as efficacy in research on

antibiotic resistance.

Over recent years, CRISPR has experienced

extensive application in research on resistance to

antibiotics, in functional validation of resistance

genes, research on antibacterial targets, as well as

phage therapy. In functional validation, CRISPR-

Cas9 is used in targeted deletion of resistance genes,

making bacteria more susceptible towards antibiotics

(Mascellino, 2024). CRISPRi can also be utilized in

knocking down efflux pump genes (for instance,

acrAB), which allows investigators to investigate its

role in MDR strains. In research on antibacterial

targets, CRISPR is applied in probing 23S rRNA

mutations' impact on resistance in macrolide, as well

as probing β-lactam antibacterial target impacts on

bacteria survival, as in the case of penicillin-binding

protein (PBP) mutations. CRISPR-phage is also a

new strategy in combating resistant bacteria.

CRISPR-phages have also been successfully

engineered by investigators with specificity in lysing

resistant species as well as eliminating MDR bacteria

(Khan et al., 2021), whereas CRISPR-mediated

targeting of resistance plasmids is used in halting

resistance gene dissemination. Amidst these

advancements, CRISPR is bedeviled with a series of

challenges that include off-targeting that erodes

specificity, bacteria-evoked development of anti-

CRISPR (Acr) strategies that suppress CRISPR

activity (Pawluk et al., 2016), as well as a need for

refinement in delivery system in order to boost

efficiency, particularly in bacteriophage as well as in

nanoscale-based CRISPR delivery.

The objectives in this paper are to provide a

comprehensive report on new advancements in

CRISPR in research on antibiotic resistance with a

focus on validation of gene functions, target profiling

of antibiotics, as well as phage therapy. In addition,

we discuss challenges that are attributed with

CRISPR-based resistance management strategies as

well as directions towards overcoming these

challenges. In providing a theoretical understanding

on mechanisms in antibiotic resistance, in turn, this

research aims at fostering new strategies in

antimicrobials as well as incorporating CRISPR into

research on antibiotic resistance.

2 APPLICATION OF CRISPR IN

BACTERIAL ANTIBIOTIC

RESISTANCE RESEARCH

2.1 Functional Validation of Resistance

Genes

CRISPR-Cas9 is a precise gene-editing tool that has

been used to target and disrupt antibiotic resistance

genes, making bacteria more susceptible to

antibiotics. For example, Mascellino demonstrated

that deleting blaTEM and blaCTX-M, which encode

β-lactamases, using CRISPR-Cas9 significantly

reduced bacterial resistance to penicillins and

cephalosporins. Additionally, CRISPRi, by using

dCas9 to bind specific promoter regions, can suppress

the transcription of resistance genes, such as efflux

pump genes (acrAB, mexAB-oprM), thereby

increasing bacterial sensitivity to tetracyclines and

fluoroquinolones (Qi et al., 2013).

2.2 Antibiotic Target Research

CRISPR has also been employed to investigate the

mechanisms of antibiotic targets. For instance,

researchers have used CRISPR-Cas9 to edit genes

related to 23S rRNA methylation to examine how

such modifications contribute to resistance against

macrolide antibiotics, such as erythromycin and

clarithromycin (Wilson, 2014). Furthermore, site-

directed mutagenesis via CRISPR has been utilized to

explore resistance mechanisms in β-lactam

antibiotics, particularly by studying mutations in

penicillin-binding proteins (PBPs). Studies have

shown that certain pbp2a mutations can increase

bacterial resistance to methicillin (Pandey et al.,

2020).

2.3 CRISPR-Based Phage Therapy

CRISPR-based phage therapy is an emerging

approach to combating antibiotic-resistant bacteria.

Researchers have engineered bacteriophages to carry

CRISPR-Cas components, allowing them to

selectively target and degrade resistance genes in

bacterial populations. This restores bacterial

susceptibility to antibiotics (Khan et al., 2021). For

example, a study on Klebsiella pneumoniae resistant

to carbapenems demonstrated that CRISPR-phage

therapy successfully eliminated resistance plasmids,

reducing bacterial tolerance to these antibiotics.

Furthermore, CRISPR-mediated plasmid degradation

Advancements in CRISPR Technology for Studying Antibiotic Resistance Mechanisms in Bacteria

125

has been used to decrease the spread of multidrug-

resistant Escherichia coli, enhancing antibiotic

efficacy (Mascellino, 2024).

2.4 CRISPR-Mediated Metabolic

Regulation

CRISPR can also regulate bacterial metabolic

pathways to enhance antibiotic effectiveness.

CRISPRi can be used to silence key metabolic

regulators, such as soxR and marA, thereby

weakening bacterial resistance and increasing

susceptibility to antibiotics. Additionally, CRISPR

has been applied in metabolic pathway

reprogramming to disrupt biofilm formation, which is

a major contributor to antibiotic resistance. By

modifying metabolic networks, researchers have

improved antibiotic efficacy in treating chronic

infections (Pawluk et al., 2016).

3 DISCUSSION

The fast development of CRISPR has provided a

powerful tool for studying antibiotic resistance. Its

high specificity, programmability, and broad

applicability allow researchers to directly manipulate

bacterial genomes to explore the gene functions,

optimize antibiotic targets, and develop new anti-

bacteria methods. However, CRISPR still faces

several challenges. Which include off-target effects,

bacterial anti-CRISPR mechanisms, and the need for

improved delivery systems. To make CRISPR a

viable tool against antibiotic-resistant bacteria,

researchers must keeping refine its editing accuracy,

enhance its efficiency in complex microbial

communities, and surmount the bacterial defense

mechanisms against CRISPR-Cas systems.

The precision of CRISPR largely depends on

single-guide RNA (sgRNA) recognition of target

sequences. However, the researchers have shown that

Cas9 may introduce unintended cuts at non-target

sites, leading to off-target effects (Slaymaker et al.,

2016). This issue limits CRISPR’s application in

studying resistance genes and developing

antibacterial strategies, as an unintended mutations

could alter experimental outcomes or pose safety

risks. To minimize off-target effects, researchers have

developed several optimization strategies, including

high-fidelity Cas9 variants such as eSpCas9 and HiFi-

Cas9, which will improve DNA binding specificity

(Kim et al., 2018). Additionally, using dual sgRNA

strategies—where two sgRNAs target the same gene

for precise editing—has been shown to reduce

unintended modifications (Qi et al., 2013). With

advancements in artificial intelligence (AI) and deep

learning, computational models have been employed

to predict potential off-target sites. For example, the

“DeepCRISPR”, is an AI-based tool, improves

sgRNA design accuracy by analyzing large amount of

CRISPR datasets, reducing the likelihood of off-

target effects (Bengio et al., 2022).

Despite CRISPR-Cas9’s high gene-editing

efficiency, many bacteria have evolved anti-CRISPR

(Acr) mechanisms to resist CRISPR-mediated

genome modifications. These Acr proteins, often

encoded by bacteriophages, inhibit CRISPR function

by blocking Cas9 binding to DNA or degrading Cas

protein complexes (Pawluk et al., 2016). Studies have

shown that Acr systems significantly reduce

CRISPR-Cas9 editing efficiency in certain

multidrug-resistant bacteria, such as carbapenem-

resistant Klebsiella pneumoniae and methicillin-

resistant Staphylococcus aureus (Khan et al., 2021).

To overcome this issue, researchers are developing

novel CRISPR variants, such as Cas12 and Cas13,

which function differently from Cas9 and may evade

Acr-mediated inhibition. Additionally, AI-driven

AcrFinder algorithms are being used to identify new

anti-CRISPR proteins, helping scientists engineer

improved CRISPR tools (Stanley et al., 2019).

Another critical challenge is CRISPR delivery

systems, which play a crucial role in determining its

effectiveness in real-world applications. Unlike

laboratory experiments, clinical applications require

CRISPR to be efficiently and precisely delivered to

target bacterial populations. Existing delivery

methods, such as electroporation, transformation, or

plasmid transfection, are effective in controlled

settings but have limitations in in vivo applications

(Kim et al., 2018). To address this, researchers have

developed bacteriophage-based CRISPR delivery

systems, where engineered phages act as natural

carriers to transport CRISPR components into

resistant bacteria. This method has shown success in

targeting carbapenem-resistant Klebsiella

pneumoniae and multidrug-resistant Escherichia coli,

effectively eliminating resistance plasmids

(Mascellino, 2024). Additionally, nanoparticle-based

delivery systems, such as lipid nanoparticles (LNPs)

and polymer nanoparticles (PNPs), are being

explored as non-viral alternatives to improve

CRISPR stability and enhance its targeting efficiency

in bacterial populations (Kim et al., 2018). Further

optimization of these delivery systems, along with the

integration of synthetic biology approaches to design

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intelligent CRISPR carriers, will be essential for

advancing CRISPR-based antibacterial therapies.

Despite these challenges, CRISPR has vast

potential in antibiotic resistance treatment, gene

regulation, and personalized medicine. Future

research should focus on AI-driven sgRNA

optimization to improve editing specificity and

efficiency (Bengio et al., 2022). Additionally, further

exploration of alternative Cas proteins, such as Cas12

and Cas13, could help bypass Acr-mediated CRISPR

inhibition (Pawluk et al., 2016). Moreover, the

development of more efficient delivery systems,

including bacteriophages, nanoparticles, and

synthetic biology carriers, will further enhance

CRISPR’s clinical applicability (Kim et al., 2018).

4 CONCLUSION

This study evaluated CRISPR-Cas application in

research on antibiotic resistance genes, antibiotic

targets, CRISPR-phage therapy, as well as in

metabolic pathways in bacteria. CRISPR is a very

potent tool in resistance research as well as in new

therapies design, although challenges do still lie in its

way. Such challenges are off-targeting, CRISPR

defenses in bacteria, as well as effective CRISPR

delivery. Upcoming research will entail improving

CRISPR delivery (for instance, bacteriophages,

nanoparticles), making gene editing more targeted, as

well as synergistically coupling CRISPR with

synthetic biology in order to design new antibacterial

therapies. CRISPR can be a key remedy in tackling

antibiotic resistance, designing customized

antibacterial therapies, as well as in phasing out

classical antibiotics as CRISPR technologies mature.

REFERENCES

Bengio, Y., Bertin, P., Bauer, S., Aliee, H., &

Krishnakumar, R. 2022. Causal machine learning for

single-cell genomics. arXiv preprint arXiv:2310.14935.

Du, D., Wang, Z., James, C. E., & Venter, H. 2018.

Structure of the AcrAB-TolC multidrug efflux pump.

Nature, 558(7704), 60-64.

Khan, M., Abbas, A., Ahmad, T., & Nadeem, M. 2021.

CRISPR-Cas System: Biological Role in Bacterial

Virulence, Genome Editing, and Antimicrobial

Resistance. Punjab University Journal of Zoology,

36(1), 85-96.

Kim, S., Kim, D., Cho, S. W., Kim, J., & Kim, J. S. 2018.

A highly efficient and biocompatible delivery system

for CRISPR-Cas9 ribonucleoproteins. Genome

Research, 28(8), 1175-1184.

Mascellino, M. T., Oliva, A., & Biswas, S. 2024. New

therapeutic strategies against carbapenem-resistant

gram-negative bacteria. Frontiers in Microbiology.

https://www.frontiersin.org/journals/microbiology/arti

cles/10.3389/fmicb.2024.1513900/full

Pandey, S. D., Jain, D., Kumar, N., & Adhikary, A. 2020.

MSMEG_2432 of Mycobacterium smegmatis mc²155

is a dual-function enzyme that exhibits DD-

carboxypeptidase and β-lactamase activities.

Microbiology Research, 166(6), 412-421.

Pawluk, A., Staals, R. H. J., Taylor, C., Watson, B. N. J.,

Saha, S., Fineran, P. C., Maxwell, K. L., & Davidson,

A. R. 2016. Inactivation of CRISPR-Cas systems by

anti-CRISPR proteins in diverse bacterial species.

Nature Microbiology, 1, 16085. h

Qi, L. S., Larson, M. H., Gilbert, L. A., Doudna, J. A.,

Weissman, J. S., Arkin, A. P., & Lim, W. A. 2013.

Repurposing CRISPR as an RNA-guided platform for

sequence-specific control of gene expression. Cell,

152(5), 1173-1183.

Slaymaker, I. M., Gao, L., Zetsche, B., Scott, D. A., Yan,

W. X., & Zhang, F. 2016. Rationally engineered Cas9

nucleases with improved specificity. Science,

351(6268), 84-88.

Stanley, S. Y., Borges, A. L., Chen, K. H., Swaney, D. L.,

Krogan, N. J., & Bondy-Denomy, J. 2019. Anti-

CRISPR-associated proteins are crucial modulators of

phage biology. Nature Microbiology, 4(4), 556-566.

Wilson, D. N. 2014. Ribosome-targeting antibiotics and

mechanisms of bacterial resistance. Nature Reviews

Microbiology, 12(1), 35-48.

World Health Organization (WHO). 2020. Antibiotic

resistance: A global threat. Retrieved from

https://www.who.int/news-room/fact-

sheets/detail/antibiotic-resistance

Zhang, G., Xie, H., & Dai, X. 2024. DeepIndel: An

Interpretable Deep Learning Approach for Predicting

CRISPR/Cas9-Mediated Editing Outcomes.

International Journal of Molecular Sciences, 25(20),

10928.

Advancements in CRISPR Technology for Studying Antibiotic Resistance Mechanisms in Bacteria

127