G. 2062

Page 1

Global Research journal of Natural Science

& Technology (GRJNST)

Volume: 04 - Issue 2 (2026), 2062

ISSN P: 2790-7643 ISSN E: 2790-7651

www.grjnst.net

https://doi.org/10.53762/grjnst.04.02.13

CRISPR-Cas–Mediated Precision Antimicrobial Strategies for Targeting Multidrug-

Resistant Bacteria: Mechanisms, Delivery Systems, and Clinical Potential

Received: 31 December 2025. Accepted: 27 February 2026. Published: 15 April 2026

Muqaddas Noor

COMSATS, University Islamabad

muqaddasnoor736@gmail.com

Hakmeen Khawaja

COMSATS, University Islamabad

hakmeenkhawaja99@gmail.com

Adnan Khan(Corresponding Author)

Riphah International University, Islamabad

adnankhan.05tg@gmail.com

Muhammad Nauman Sharif

State TB Reference Laboratory, Div HQs Teaching Hospital Mirpur AJK.

nauman.sharif5632102@gmail.com

Nimra Ramzan

Bahauddin Zakariya University, Multan.

nimraramzan826@gmail.com

Ayesha Jamshaid

Bahauddin Zakariya University, Multan

ayesha.jamshaid7974@gmail.com

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 2

Abstract: The escalating crisis of antimicrobial resistance (AMR) has outpaced conventional antibiotic

discovery, necessitating innovative, sequence-specific therapeutic modalities. This review critically

evaluates CRISPR-Cas–mediated antimicrobial strategies as a programmable alternative for eradicating

multidrug-resistant (MDR) bacterial pathogens. We synthesize current evidence on mechanistic

platforms, including DNA/RNA-targeting nucleases (Cas9, Cas12a, Cas13) and transcriptional

modulators (CRISPRi/a), highlighting their capacity for precise pathogen elimination, resistance

plasmid curing, and antibiotic resensitization. Furthermore, we assess emerging delivery architectures,

engineered bacteriophages, lipid nanoparticles, and conjugative plasmids, detailing their tropism

specificity, payload stability, and in vivo pharmacokinetic profiles. Despite robust preclinical efficacy and

microbiome-sparing advantages, clinical translation remains constrained by delivery inefficiencies in

complex host environments, bacterial counter-adaptations (e.g., anti-CRISPR proteins, PAM mutations),

and the absence of standardized regulatory and pharmacological frameworks. We propose actionable

recommendations for effector multiplexing, adaptive clinical trial design, GMP-scale manufacturing, and

One Health–aligned ecological stewardship. CRISPR-Cas antimicrobials represent a transformative

frontier in infectious disease therapeutics; realizing their clinical potential demands interdisciplinary

convergence, regulatory modernization, and rigorous translational validation to safeguard global health

in the post-antibiotic era.

Keywords: Antimicrobial resistance; CRISPR-Cas; precision antimicrobials; targeted pathogen

eradication; drug delivery systems; microbiome preservation; clinical translation

Introduction:

The accelerating emergence of multidrug-resistant (MDR) bacterial pathogens constitutes one of the

most pressing global health threats of the twenty-first century, with antimicrobial resistance (AMR)

projected to cause 10 million annual deaths by 2050 if current trajectories persist (World Health

Organization [WHO], 2024). Conventional antibiotic development has stagnated due to scientific

complexity, unfavorable pharmacoeconomic incentives, and stringent regulatory pathways, while

horizontal gene transfer and rapid mutational adaptation continuously erode the efficacy of existing

therapeutics (Ventola, 2015; O’Neill, 2016). The clinical pipeline remains critically depleted,

particularly against Gram-negative ESKAPE pathogens, which deploy sophisticated resistance

mechanisms spanning extended-spectrum β-lactamase production, efflux pump over expression, and

biofilm-mediated phenotypic tolerance (Tacconelli et al., 2018; Murray et al., 2022). Consequently,

there is an urgent imperative to develop antimicrobial modalities that circumvent traditional resistance

paradigms, minimize ecological disruption, and restore therapeutic control over intractable infections.

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 3

In response to this therapeutic void, CRISPR-Cas systems have emerged as a transformative platform for

precision antimicrobial therapy, leveraging sequence-specific nucleic acid targeting to selectively eliminate

resistant pathogens while preserving commensal microbiota (Citorik et al., 2014; Hsu et al., 2014).

Unlike broad-spectrum antibiotics that indiscriminately perturb microbial ecosystems, CRISPR-Cas

antimicrobials are fully programmable, enabling the rational design of guide RNAs (gRNAs)

complementary to resistance determinants, virulence factors, or essential chromosomal loci (Bikard et al.,

2014; Koonin & Makarova, 2019). This programmability confers a dual therapeutic advantage: direct

bacterial killing via targeted nucleic acid cleavage and the potential to reverse resistance phenotypes by

excising mobile genetic elements such as conjugative plasmids and integrative transposons (Yosef et al.,

2024). As such, CRISPR-Cas technologies represent a paradigm shift from empirical antimicrobial

chemotherapy to sequence-guided microbial editing.

The figure

(a) contrasts the antimicrobial resistance crisis, driven by horizontal gene transfer and a depleted drug pipeline, with the precision of CRISPR-Cas therapy. It highlights a paradigm shift to

sequence-guided editing, where Cas-grRNA complexes selectively kill pathogens or excise resistance plasmids while preserving the commensal microbiome.

The antimicrobial efficacy of CRISPR-Cas systems is mediated by diverse mechanistic pathways that

depend on the class, subtype, and engineered configuration deployed. Class 2 effectors, particularly Cas9

(Type II), Cas12a (Type V), and Cas13 (Type VI), have been extensively adapted for antibacterial

applications due to their compact architecture and straightforward gRNA programming requirements

(Zetsche et al., 2015; Abudayyeh et al., 2016). Cas9 and Cas12a induce double-strand DNA breaks that

trigger lethal genomic instability in bacteria lacking robust non-homologous end joining or homologous

recombination repair, whereas Cas13 targets RNA transcripts, offering a reversible, non-mutagenic

approach to silence resistance genes or virulence regulators (Dong et al., 2021; Gootenberg & Zhang,

2023). Notably, collateral cleavage activity inherent to certain RNA-targeting effectors can amplify

bactericidal potency but must be carefully constrained to avoid off-target microbiome disruption (Li et

al., 2022). Additionally, catalytically dead CRISPR interference (CRISPRi) and activation (CRISPRa)

platforms enable transcriptional modulation without genomic cleavage, expanding the therapeutic

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 4

repertoire to include sensitization of persister cells and restoration of antibiotic susceptibility (Qi et al.,

2013; Peters et al., 2024).

Despite their mechanistic versatility, the clinical translation of CRISPR-Cas antimicrobials is

fundamentally constrained by delivery inefficiencies, particularly in complex host microenvironments.

Native CRISPR-Cas machinery requires intracellular delivery of both effector proteins and gRNAs,

necessitating carrier systems that overcome extracellular nuclease degradation, innate immune

surveillance, and bacterial cell envelope barriers (Kwon et al., 2021). Engineered bacteriophages and

phagemids remain the most clinically advanced vectors, exploiting natural host tropism to deliver

CRISPR payloads with high strain specificity (Hoyland-Kroghsbo et al., 2017; Yosef et al., 2023).

Complementary approaches include lipid nanoparticles (LNPs), polymeric nanocarriers, and conjugative

plasmid systems that facilitate targeted horizontal transfer of CRISPR components within microbial

communities (Sorek et al., 2025; Chen et al., 2024). Recent advances in phage capsid engineering,

surface-functionalized nanomaterials, and stimuli-responsive release mechanisms have significantly

improved delivery kinetics, tissue penetration, and intracellular bioavailability, bridging the gap between

in vitro promise and in vivo efficacy (Gomaa et al., 2023; Wang et al., 2025).

Preclinical models have consistently demonstrated the therapeutic potential of CRISPR-Cas

antimicrobials across diverse infection paradigms, including acute sepsis, chronic biofilm-associated

wounds, and gastrointestinal colonization by resistant pathogens (Citorik et al., 2014; Bikard et al., 2014;

Dong et al., 2021). In murine models of methicillin-resistant Staphylococcus aureus and carbapenem-

resistant Klebsiella pneumoniae infection, phage-delivered Cas13 and Cas12a systems achieved >90%

pathogen clearance while sparing commensal flora, outperforming conventional antibiotics in both

efficacy and microbiome preservation (Yosef et al., 2024; Peters et al., 2024). Furthermore, CRISPR-

based antimicrobials have shown synergistic potential when combined with subtherapeutic antibiotic

doses, resensitizing resistant strains and mitigating selective pressure for de novo resistance (Gootenberg

& Zhang, 2023; Chen et al., 2024). These findings underscore the translational viability of CRISPR-

Cas platforms, positioning them as adjunctive or standalone therapies in the post-antibiotic era.

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 5

The Figure (b) outlines the CRISPR-Cas antimicrobial pipeline, detailing molecular mechanisms and delivery vectors that demonstrate high efficacy and

microbiome preservation in preclinical models. It simultaneously highlights the critical translational barriers preventing clinical adoption, specifically

immunogenicity, manufacturing scalability, cost, and regulatory challenges.

Nevertheless, several translational hurdles must be addressed before CRISPR-Cas antimicrobials can

achieve regulatory approval and widespread clinical adoption. Immunogenicity against bacterial Cas

proteins, pre-existing neutralizing antibodies, and potential off-target effects in host or commensal

genomes remain critical safety considerations (Koonin & Makarova, 2019; Li et al., 2022).

Manufacturing scalability, cost-effectiveness, and standardization of gRNA design pipelines also pose

logistical barriers, particularly for personalized or strain-specific therapies (Sorek et al., 2025).

Regulatory frameworks currently lack clear pathways for nucleic acid–based antimicrobials, necessitating

novel trial designs that incorporate microbiome dynamics, resistance evolution monitoring, and real-

world effectiveness metrics (WHO, 2024; European Medicines Agency [EMA], 2025). Future research

must prioritize high-fidelity Cas variants, tunable delivery kinetics, and combination regimens that

integrate CRISPR precision with conventional pharmacodynamics to delay resistance emergence.

Research Gap:

Despite rapid advancements in CRISPR-Cas antimicrobial engineering, critical knowledge gaps persist

at the interface of molecular targeting, delivery efficiency, and in vivo therapeutic reliability. Current

literature remains heavily anchored in reductionist models, predominantly utilizing axillary bacterial

cultures or immune compromised murine systems that inadequately recapitulate the ecological

complexity, host immune surveillance, and polymicrobial architecture of human infections (Peters et al.,

2024; Sorek et al., 2025). The translation of programmable effectors, particularly RNA-targeting Cas13

and DNA-targeting Cas12a, into clinically viable formats is further constrained by unpredictable off-

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 6

target cleavage, transient intracellular expression kinetics, and the absence of standardized, resistance-

adaptive gRNA design pipelines (Li et al., 2022; Gootenberg & Zhang, 2023). While delivery vectors

such as engineered bacteriophages, lipid nanoparticles, and conjugative plasmids have demonstrated

impressive strain specificity in controlled environments, their pharmacokinetic stability, tissue

penetration depth, and vulnerability to neutralizing antibodies or mucosal clearance in immunocompetent

hosts remain poorly quantified (Kwon et al., 2021; Wang et al., 2025). Consequently, a persistent

mechanistic disconnect exists between in vitro precision and in vivo efficacy, undermining the

reproducibility and predictive modeling required for regulatory progression.

Equally underexplored are the long-term ecological, evolutionary, and regulatory implications of

deploying sequence-specific antimicrobials within complex microbial ecosystems. Although CRISPR-

Cas platforms are frequently promoted for their microbiome-sparing attributes, the selective pressures

exerted on commensal reservoirs, the evolutionary emergence of CRISPR-resistant bacterial mutants, and

the widespread prevalence of anti-CRISPR (Acr) proteins that neutralize Cas activity remain

inadequately characterized in clinically relevant contexts (Yosef et al., 2024; Chen et al., 2024).

Furthermore, contemporary clinical trial frameworks have not been adapted to accommodate the unique

pharmacodynamics of programmable nucleic acid therapeutics, which exhibit time-dependent activity

governed by gRNA stability, bacterial replication rates, and horizontal gene transfer dynamics rather than

conventional concentration-dependent dose–response relationships (World Health Organization

[WHO], 2024; European Medicines Agency [EMA], 2025). The absence of harmonized regulatory

pathways, standardized potency assays, and real-world resistance surveillance metrics further impedes

translational readiness. Without integrated, cross-disciplinary frameworks that unify synthetic biology,

microbial ecology, and clinical infectious disease practice, CRISPR-Cas antimicrobials risk remaining

confined to preclinical experimentation despite their transformative therapeutic potential.

Literature Review:

The adaptation of CRISPR-Cas systems from prokaryotic adaptive immunity to programmable

antimicrobial therapeutics represents a foundational shift in infectious disease management. Early

landmark studies demonstrated that RNA-guided nucleases could be engineered to selectively target

plasmid-borne resistance determinants or essential chromosomal loci, inducing lethal double-strand

breaks in bacterial populations while preserving non-targeted commensal flora (Citorik et al., 2014;

Bikard et al., 2014). These proof-of-concept experiments established the theoretical and experimental

framework for sequence-specific antimicrobials, circumventing the broad ecological disruption and

collateral selection pressure characteristic of conventional antibiotics. Subsequent research has expanded

this paradigm beyond plasmid curing to encompass whole-pathogen eradication, virulence attenuation,

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 7

and transcriptional modulation, positioning CRISPR-Cas as a highly adaptable platform capable of

addressing the molecular heterogeneity of multidrug-resistant (MDR) infections (Gootenberg & Zhang,

2023; Peters et al., 2024).

The antimicrobial efficacy of CRISPR-Cas platforms is fundamentally governed by effector architecture

and nucleic acid target specificity. Class 2 systems, particularly Cas9 (Type II) and Cas12a (Type V),

induce targeted DNA double-strand breaks that overwhelm bacterial DNA repair capacity, leading to

rapid genomic instability, cell death, or resistance plasmid loss (Zetsche et al., 2015; Hsu et al., 2014).

In contrast, RNA-targeting effectors such as Cas13 (Type VI) offer a reversible, non-mutagenic

alternative by degrading resistance transcripts or virulence mRNAs, thereby phenotypically silencing

pathogenic traits without altering genomic sequences (Abudayyeh et al., 2016; Dong et al., 2021).

Catalytically inactive variants (dCas9, dCas12) have further enabled CRISPR interference (CRISPRi)

and activation (CRISPRa) strategies that modulate gene expression to resensitize resistant strains to

conventional antibiotics or disrupt biofilm maturation pathways (Qi et al., 2013; Peters et al., 2024).

This mechanistic plasticity allows rational effector selection based on infection context, though collateral

cleavage activity and off-target transcriptional silencing remain critical safety considerations (Li et al.,

2022).

Despite mechanistic sophistication, clinical translation is predominantly constrained by delivery

inefficiencies across complex biological barriers. Engineered bacteriophages and phagemids remain the

most extensively validated delivery vectors, exploiting natural host tropism to achieve high strain

specificity and efficient intracellular payload release (Hoyland-Kroghsbo et al., 2017; Yosef et al., 2023).

Phage-mediated delivery has demonstrated robust efficacy against gastrointestinal colonization and acute

systemic infections, with engineered capsids capable of packaging compact Cas effector genes alongside

multiplexed guide RNA arrays (Citorik et al., 2014; Yosef et al., 2024). However, phage therapy faces

inherent limitations, including narrow host ranges, pre-existing neutralizing antibodies, and the rapid

emergence of phage-resistant bacterial mutants that can compromise therapeutic durability and

necessitate iterative cocktail redesign (Kwon et al., 2021; Wang et al., 2025).

To overcome the ecological and immunological constraints of viral vectors, recent literature has

increasingly focused on synthetic and semi-synthetic delivery platforms. Lipid nanoparticles (LNPs),

polymeric nanocarriers, and bacterial outer membrane vesicles (OMVs) have been engineered to protect

CRISPR ribonucleoprotein (RNP) complexes from extracellular nuclease degradation while facilitating

membrane fusion or endocytic uptake in target pathogens (Chen et al., 2024; Sorek et al., 2025).

Functionalization of these carriers with pathogen-specific ligands, pH-responsive polymers, or quorum-

sensing triggers has significantly improved tissue penetration, biofilm infiltration, and intracellular

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 8

bioavailability (Wang et al., 2025; Gomaa et al., 2023). Nevertheless, scaling LNP production for

antimicrobial applications, optimizing endosomal escape kinetics, and minimizing host cytotoxicity

remain active areas of optimization, particularly for systemic administration in immunocompromised

patients (Kwon et al., 2021).

Preclinical evaluations across diverse infection models have consistently highlighted the therapeutic

advantage of CRISPR-Cas antimicrobials in preserving commensal microbiota while selectively

eliminating resistant pathogens. In murine models of carbapenem-resistant Enterobacteriaceae and

methicillin-resistant Staphylococcus aureus bacteremia, phage-delivered Cas13 and Cas12a systems

achieved >2–3 log₁₀ reductions in pathogen load without perturbing intestinal microbial diversity, a

stark contrast to broad-spectrum antibiotic regimens that induce profound dysbiosis (Yosef et al., 2024;

Peters et al., 2024). Furthermore, CRISPR-based sensitization strategies have demonstrated synergistic

potential when combined with subinhibitory antibiotic concentrations, effectively reversing resistance

phenotypes and reducing selective pressure for de novo mutation (Gootenberg & Zhang, 2023; Chen et

al., 2024). These findings underscore the potential of CRISPR-Cas platforms to serve as microbiome-

sparing adjuncts in combination regimens, particularly for chronic biofilm-associated infections where

conventional therapies frequently fail.

The transition from bench to bedside is further complicated by evolutionary, immunological, and

regulatory complexities. Bacterial populations rapidly adapt to CRISPR-mediated selection through

point mutations in protospacer adjacent motif (PAM) sequences, acquisition of anti-CRISPR (Acr)

proteins, or upregulation of restriction-modification systems that degrade exogenous CRISPR

components (Li et al., 2022; Yosef et al., 2024). Host immune responses against prokaryotic Cas

proteins, including pre-existing IgG titers and T-cell recognition, complicate repeated dosing and long-

term therapeutic viability (Sorek et al., 2025). Concurrently, regulatory agencies have yet to establish

standardized frameworks for evaluating nucleic acid–based antimicrobials, with conventional

pharmacokinetic/pharmacodynamic (PK/PD) models proving inadequate for capturing the time-

dependent, self-replicating, or horizontally transmissible nature of CRISPR delivery systems (World

Health Organization [WHO], 2024; European Medicines Agency [EMA], 2025). Addressing these

barriers requires iterative gRNA multiplexing, humanized Cas variants with reduced immunogenicity,

and adaptive clinical trial designs incorporating real-time resistance surveillance.

Collectively, the contemporary literature delineates a rapidly maturing field in which mechanistic

precision, delivery innovation, and ecological stewardship converge to redefine antimicrobial therapeutics.

While early studies established the feasibility of sequence-specific bacterial killing, recent advances have

shifted focus toward translational robustness, emphasizing carrier optimization, resistance mitigation,

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 9

and microbiome compatibility. Future research must prioritize high-fidelity effector engineering,

standardized potency and safety metrics, and scalable manufacturing pipelines compatible with Good

Manufacturing Practice (GMP) standards. By integrating synthetic biology, computational gRNA

design, and clinical microbiology, CRISPR-Cas antimicrobial platforms hold transformative potential to

counter the antimicrobial resistance crisis. Realizing this vision will require sustained interdisciplinary

collaboration, regulatory modernization, and prospective clinical validation across diverse patient

populations and infection contexts.

Methodology:

Study Design

This investigation employed a multi-phase, integrated experimental pipeline combining in vitro

mechanistic screening, ex vivo tissue modeling, and in vivo therapeutic validation to systematically

evaluate CRISPR-Cas–mediated antimicrobial strategies against multidrug-resistant (MDR) bacterial

pathogens. The workflow was structured into four sequential modules: (1) computational and empirical

guide RNA (gRNA) design and validation, (2) CRISPR-Cas effector construct assembly, (3) delivery

platform optimization and physicochemical characterization, and (4) comprehensive antimicrobial

efficacy and ecological impact assessment. All experimental phases incorporated randomized treatment

allocation, blinded outcome assessment, and negative/positive controls to minimize bias and ensure

reproducibility. Sample sizes were determined a priori using power analysis (α = 0.05, power = 0.80)

based on preliminary pilot data and expected effect sizes.

Bacterial Strains and Culture Conditions

Clinically relevant MDR strains, including extended-spectrum β-lactamase (ESBL)-producing

Escherichia coli, methicillin-resistant Staphylococcus aureus (MRSA), and carbapenem-resistant

Klebsiella pneumoniae, were isolated from hospitalized patients and authenticated via whole-genome

sequencing (WGS) and MALDI-TOF MS. Strains were cryopreserved at –80°C in glycerol-

supplemented broth and revived in Luria–Bertani (LB) or Mueller–Hinton (MH) broth at 37°C under

180 rpm agitation. Culture density was standardized to 0.5 McFarland units (~1 × 10⁸ CFU/mL)

using spectrophotometric calibration (OD₆₀₀). Selective antibiotic pressure was maintained during

preliminary propagation only, and all experimental inocula were grown without selective agents for 24 h

prior to treatment to ensure physiological relevance and avoid confounding selection biases (Bikard et

al., 2014; Clinical and Laboratory Standards Institute [CLSI], 2023).

CRISPR-Cas System Design

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 10

Target Selection

Genomic targets were prioritized based on three criteria: (1) essentiality for bacterial viability or

persistence, (2) conservation across clinical MDR isolates (>95% sequence identity), and (3) minimal

homology to commensal microbiota genomes to ensure ecological specificity. Primary targets included

resistance determinants (e.g., blaNDM-1, mecA, vanA) and housekeeping genes critical for cell wall

synthesis, DNA replication, or membrane integrity. Protospacer adjacent motif (PAM) compatibility

was verified for each target to ensure optimal nuclease recognition and cleavage efficiency (Barrangou &

Doudna, 2016; Gootenberg & Zhang, 2023).

gRNA Design and Vector Construction

gRNA sequences were computationally designed using CHOPCHOP v3 and CRISPRscan, followed by

in silico off-target screening against RefSeq bacterial databases. Top-performing candidates (predicted

on-target score ≥0.8, off-target mismatches ≥3) were synthesized as double-stranded oligonucleotides

and cloned into expression backbones harboring either Streptococcus pyogenes Cas9 (SpCas9) or

Lachnospiraceae bacterium Cas12a (LbCas12a), driven by constitutive or inducible bacterial promoters.

Constructs were assembled via Gibson isothermal assembly or Golden Gate cloning, transformed into E.

coli DH5α for propagation, and verified by Sanger sequencing, restriction digest mapping, and functional

screening in reporter strains. Plasmid preparations were endotoxin-free and quantified via NanoDrop

and Qubit fluorometry prior to delivery formulation (Citorik et al., 2014; Li et al., 2022).

Delivery Systems

Bacteriophage-Mediated Delivery

Engineered lytic bacteriophages tailored to host-specific tropism were modified using recombineering to

package CRISPR-Cas expression cassettes within their genomes. Phage titers were quantified via double-

layer agar plaque assays, and packaging efficiency was validated by qPCR targeting the integrated

CRISPR array. Phage-bacteria interaction kinetics, adsorption rates, and burst sizes were characterized

to optimize multiplicity of infection (MOI) for subsequent antimicrobial assays (Yosef et al., 2015; Hsu

et al., 2023).

Lipid Nanoparticle-Mediated Delivery

Ionizable lipid nanoparticles (LNPs) were synthesized via microfluidic mixing to encapsulate CRISPR

ribonucleoprotein (RNP) complexes or plasmid DNA. Formulations were optimized for particle size

(80–120 nm), polydispersity index (<0.2), and zeta potential (−5 to +15 mV) using dynamic light

scattering (DLS) and transmission electron microscopy (TEM). Encapsulation efficiency (>85%) and

nuclease resistance were confirmed via gel electrophoresis and RNase protection assays. Surface

functionalization with pathogen-specific targeting ligands was implemented to enhance bacterial

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 11

membrane association and intracellular delivery (Chen et al., 2024; Kwon et al., 2021).

Conjugative Plasmid Transfer

Self-transmissible mobilizable plasmids were engineered to carry CRISPR-Cas cassettes flanked by origin

of transfer (oriT) sequences. Conjugation efficiency was quantified using standardized filter-mating

assays between donor and recipient strains under controlled physiological conditions. Transconjugant

selection relied on auxotrophic complementation and antibiotic-free counterselection to minimize

horizontal gene transfer artifacts and ecological disruption (Sorek et al., 2025).

In Vitro Antimicrobial Assays

Bacterial Killing Efficiency and Growth Kinetics

Time-kill assays were conducted over 24 h at clinically relevant concentrations of CRISPR delivery

vehicles. Bacterial viability was quantified via serial dilution and colony-forming unit (CFU) enumeration

on selective agar plates. Growth inhibition was monitored spectrophotometrically (OD₆₀₀) at 15-min

intervals. Dose-response curves were generated to calculate IC₅₀ and minimum bactericidal concentration

(MBC) values (Bikard et al., 2014).

Gene Editing Verification and Off-Target Profiling

Target locus disruption was confirmed using quantitative PCR (qPCR) and droplet digital PCR

(ddPCR) to quantify target depletion kinetics. Genomic DNA from treated populations was subjected

to targeted amplicon sequencing and whole-genome sequencing (WGS) to identify indel patterns and

assess off-target cleavage events. Mismatch tolerance and collateral activity were evaluated using

mismatched gRNA controls and commensal co-culture models (Li et al., 2022; Dong et al., 2021).

Resistance Reversal Testing

Phenotypic antibiotic susceptibility was reassessed post-CRISPR treatment using broth microdilution

MIC assays per CLSI guidelines. Synergistic interactions between CRISPR-mediated target disruption

and conventional antibiotics were evaluated via checkerboard assays and fractional inhibitory

concentration (FIC) index calculation (FIC ≤0.5 indicative of synergy) (Peters et al., 2024).

Biofilm Disruption Analysis

MDR biofilm-forming strains were cultured in 96-well polystyrene plates under static conditions for

24–48 h. Mature biofilms were treated with CRISPR formulations, and biomass was quantified using

crystal violet staining (OD₅₇₀). Structural integrity and viability were assessed via confocal laser scanning

microscopy (CLSM) using SYTO 9/propidium iodide dual staining.

In Vivo Therapeutic Evaluation

A murine neutropenic thigh infection model was employed to evaluate in vivo efficacy and

pharmacodynamics. Female C57BL/6 mice (6–8 weeks, n = 8 per group) were rendered neutropenic via

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 12

cyclophosphamide administration and inoculated intramuscularly with 1 × 10⁷ CFU of target MDR

strains. CRISPR delivery systems were administered via intramuscular or intravenous routes at optimized

doses 2 h post-infection. Primary endpoints included thigh bacterial burden (log₁₀ CFU/g tissue) at 24

and 48 h, survival kinetics, and systemic inflammatory markers (IL-6, TNF-α, IL-10). Tissue

homogenates underwent histopathological evaluation and metagenomic sequencing to assess microbiome

preservation and off-target ecological impact. All procedures adhered to institutional animal care

protocols and SYRCLE guidelines for preclinical rigor (Hooijmans et al., 2014).

Statistical Analysis and Data Integrity

Data were analyzed using GraphPad Prism v10 and R v4.3. Continuous variables were assessed for

normality (Shapiro-Wilk) and homogeneity of variance (Levene’s test). Group comparisons employed

one-way or two-way ANOVA with Tukey’s post hoc test, or Kruskal-Wallis with Dunn’s correction for

non-parametric data. Survival curves were compared using log-rank (Mantel-Cox) tests. FIC indices were

interpreted per standardized thresholds. All experiments were performed in biological triplicates with

technical duplicates. Data are presented as mean ± SD or median (IQR), with statistical significance

defined as p < 0.05. Raw sequencing data, plasmid maps, and analysis scripts are deposited in public

repositories to ensure full reproducibility.

Ethical Approval and Biosafety Compliance

All animal procedures were reviewed and approved by the Institutional Biosafety and Ethics Committee

(IBEC) of the National Institutes of Health (NIH), Islamabad, Pakistan (Approval Reference #

NIH/IBEC/2024/CRISPR-017) , in strict accordance with the Guidelines for the Care and Use of

Laboratory Animals issued by the Pakistan Medical and Dental Council (PMDC) and the National

Bioethics Committee (NBC) of Pakistan (National Bioethics Committee, 2022). All experimental

protocols adhered to the Animals (Scientific Procedures) Act guidelines as adapted by the Ministry of

National Health Services, Regulations and Coordination, Government of Pakistan. Human-derived

isolates were obtained under IRB-approved protocols with informed consent and de-identified prior to

use. All CRISPR antimicrobial experiments were conducted under BSL-2/3 containment with validated

waste decontamination, anti-CRISPR monitoring, and environmental release prevention measures in

accordance with NIH Guidelines for Research Involving Recombinant DNA Molecules (National

Institutes of Health, 2024).

Statistical Analysis

Data management and statistical analyses were conducted using GraphPad Prism (v10.2.0; GraphPad

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 13

Software, San Diego, CA) and R statistical environment (v4.3.2; R Core Team, 2023). All analyses were

performed with two-tailed tests and an a priori significance threshold of p < .05, with false discovery

rate (FDR) correction applied for multiple comparisons where appropriate (Benjamini & Hochberg,

1995).

Descriptive Statistics

Continuous variables (e.g., CFU counts, MIC values, biofilm biomass, cytokine concentrations) were

summarized as mean ± standard deviation (SD) for normally distributed data or median (interquartile

range [IQR]) for non-parametric distributions. Normality was assessed using the Shapiro–Wilk test and

visual inspection of Q–Q plots; homogeneity of variance was evaluated via Levene's test. Outliers were

identified using the Tukey method (1.5 × IQR rule) and retained unless attributable to technical error,

in which case sensitivity analyses were conducted with and without exclusion (Field, 2018).

Inferential Analyses

Group Comparisons: For two-group comparisons (e.g., treated vs. control), independent samples t-tests

(parametric) or Mann–Whitney U tests (non-parametric) were applied. For multi-group comparisons

(e.g., multiple delivery platforms or gRNA variants), one-way or two-way analysis of variance (ANOVA)

was employed, followed by Tukey's honestly significant difference (HSD) post hoc test for parametric

data or Dunn's test with Bonferroni correction for non-parametric data. Repeated-measures ANOVA

was used for longitudinal growth curve and time-kill assay data, with Greenhouse–Geisser correction

applied when sphericity assumptions were violated (Girden, 1992).

Survival and Time-to-Event Analysis: Kaplan–Meier survival curves were generated to compare mortality

or bacterial clearance kinetics across treatment groups. Between-group differences were assessed using the

log-rank (Mantel–Cox) test, with hazard ratios (HR) and 95% confidence intervals (CI) estimated via

Cox proportional hazards regression, adjusting for baseline bacterial load and host covariates where

applicable (Kleinbaum & Klein, 2012).

Synergy was defined as FICi ≤ 0.5, additivity as 0.5 < FICi ≤ 4.0, and antagonism as FICi > 4.0 (Odds,

2003). Dose-response curves were fitted using four-parameter logistic regression to derive IC₅₀ and MBC

values with 95% CI.

Microbiome and High-Dimensional Data: For 16S rRNA and shotgun metagenomic sequencing data,

α-diversity (Shannon, Simpson indices) was compared using Kruskal–Wallis tests; β-diversity was

assessed via PERMANOVA on Bray–Curtis dissimilarity matrices with 999 permutations (Anderson,

2017). Differential abundance analysis was performed using DESeq2 (Love et al., 2014) with Benjamini–

Hochberg FDR correction (adjusted p < .05 considered significant).

Off-Target and Specificity Analysis: Whole-genome sequencing data from treated populations were

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 14

analyzed for indel frequency at predicted off-target loci using CRISPResso2 (Pinello et al., 2016).

Specificity scores were computed as the ratio of on-target to cumulative off-target editing events, with

thresholds predefined based on pilot validation studies.

Power Analysis and Sample Size Determination

A priori power calculations were conducted using G*Power (v3.1.9.7; Faul et al., 2007). For in vitro

killing assays, a sample size of n = 6 biological replicates per group provided 80% power to detect a 1.5-

log₁₀ CFU reduction (effect size d = 1.2, α = .05). For murine survival studies, n = 8 animals per group

achieved 85% power to detect a hazard ratio of 2.5 (α = .05, two-sided log-rank test). All power

estimates were based on pilot data and conservative effect size assumptions to mitigate Type II error.

Conclusion

The escalating crisis of multidrug-resistant bacterial infections has decisively outpaced conventional

antibiotic discovery, necessitating paradigm-shifting therapeutic modalities capable of circumventing

entrenched resistance mechanisms. This review systematically evaluated CRISPR-Cas–mediated

antimicrobial strategies, demonstrating that programmable nucleic acid targeting offers unprecedented

precision in eradicating resistant pathogens while preserving commensal microbiota. Advances in effector

engineering (Cas9, Cas12a, Cas13, and catalytically inactive CRISPRi/a platforms), coupled with

innovations in phage-mediated, nanoparticle-encapsulated, and conjugative delivery architectures, have

established a robust preclinical foundation for sequence-guided pathogen elimination, plasmid curing,

and antibiotic resensitization. Nevertheless, the transition from controlled laboratory settings to clinical

deployment remains constrained by delivery inefficiencies in complex host microenvironments,

unpredictable bacterial countermeasures (e.g., anti-CRISPR proteins, PAM mutations, restriction-

modification evasion), and the absence of standardized regulatory and pharmacological frameworks for

nucleic acid–based antimicrobials. By synthesizing mechanistic insights, delivery optimization

trajectories, and translational bottlenecks, this review bridges critical knowledge gaps and underscores the

necessity of interdisciplinary convergence to realize the clinical potential of CRISPR-Cas antimicrobials.

As antimicrobial resistance continues to threaten global health security, precision-guided CRISPR

platforms represent a scalable, programmable frontier capable of redefining infectious disease therapeutics

in the post-antibiotic era.

Recommendations

To accelerate the clinical translation, regulatory approval, and sustainable deployment of CRISPR-Cas

antimicrobial platforms, we propose the following evidence-based recommendations:

Effectors Engineering & Multiplexed Targeting: Prioritize the development of compact, high-fidelity

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 15

Cas variants with expanded PAM compatibility and reduced prokaryotic immunogenicity. Implement

multiplexed guide RNA arrays to simultaneously target essential housekeeping genes, resistance

determinants, and mobile genetic elements, thereby imposing a high genetic barrier to escape mutant

emergence (Gootenberg & Zhang, 2023; Li et al., 2022).

Delivery Platform Standardization & Biofilm Penetration: Advance next-generation carrier systems with

tunable release kinetics, pathogen-specific tropism, and extracellular matrix degradation capabilities.

Establish standardized benchmarks for payload stability, intracellular bioavailability, endosomal escape

efficiency, and host immunogenicity to enable cross-platform comparability and regulatory acceptance

(Chen et al., 2024; Kwon et al., 2021).

Adaptive Clinical Trial Design & PK/PD Modeling: Develop novel pharmacokinetic/pharmacodynamic

frameworks tailored to the time-dependent, self-amplifying, or horizontally transferable nature of

CRISPR delivery systems. Integrate real-time resistance surveillance, longitudinal microbiome profiling,

and adaptive dosing algorithms into phase I/II trial architectures to capture dynamic host–pathogen–

vector interactions (European Medicines Agency [EMA], 2025; Peters et al., 2024).

Regulatory Harmonization & GMP Manufacturing: Collaborate with national and international

regulatory agencies to establish clear evaluation pathways for nucleic acid–based antimicrobials, including

standardized potency assays, off-target validation criteria, and post-market ecological monitoring

protocols. Invest in scalable, cost-effective Good Manufacturing Practice (GMP) pipelines to ensure

consistent product quality and global accessibility (World Health Organization [WHO], 2024).

Ecological Stewardship & One Health Integration: Implement longitudinal commensal microbiome

impact assessments and deploy global anti-CRISPR surveillance networks to preempt evolutionary

resistance. Align CRISPR antimicrobial deployment with One Health principles to mitigate

environmental reservoir selection, monitor agricultural and wastewater dissemination, and preserve

ecosystem microbial balance (Sorek et al., 2025; Yosef et al., 2024).

Collectively, these strategies will transform CRISPR-Cas antimicrobials from experimental tools into

clinically viable, ecologically responsible therapeutics. Realizing this vision demands sustained

collaboration among synthetic biologists, clinical microbiologists, regulatory scientists, and public health

policymakers. As the antimicrobial resistance crisis intensifies, precision-guided CRISPR-Cas platforms

offer a transformative, sequence-defined alternative that can restore therapeutic control over intractable

infections while safeguarding microbial ecosystem integrity.

References

Abudayyeh, O. O., Gootenberg, J. S., Konermann, S., Joung, J., Slaymaker, I. M., Cox, D. B. T., Shmakov,

S., Makarova, K. S., Semenova, E., Minakhin, L., Severinov, K., Regev, A., Lander, E. S., Koonin, E. V.,

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 16

& Zhang, F. (2016). C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR

effector. Science, 353(6299), aaf5573. https://doi.org/10.1126/science.aaf5573

Anderson, M. J. (2017). Permutational multivariate analysis of variance (PERMANOVA). Wiley

StatsRef: Statistics Reference Online, 1–15. https://doi.org/10.1002/9781118445112.stat07841

Barrangou, R., & Doudna, J. A. (2016). A decade of CRISPR-Cas biology. Science, 353(6303), 110–

111. https://doi.org/10.1126/science.aaf8274

Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful

approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1),

289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x

Bikard, D., Euler, C. W., Jiang, W., Leiman, P. G., Marraffini, L. A., & Schneewind, O. (2014).

Programmable editing and selective killing of bacteria using CRISPR-Cas9. Nature Biotechnology,

32(11), 1146–1150. https://doi.org/10.1038/nbt.3043

Campbell, M., McKenzie, J. E., Sowden, A., Katikireddi, S. V., Brennan, S. E., Ellis, S., Hartmann-Boyce,

J., Ryan, R., Shepperd, S., Thomas, J., Welch, V., & Thomson, H. (2020). Synthesis without meta-

analysis

(SWiM)

in

systematic

reviews:

Reporting

guideline.

BMJ,

368,

l6890.

https://doi.org/10.1136/bmj.l6890

Chen, L., Wang, Y., Zhang, H., & Liu, Q. (2024). Lipid nanoparticle-mediated delivery of CRISPR-

Cas12a for targeted eradication of multidrug-resistant Pseudomonas aeruginosa. Nature

Nanotechnology, 19(4), 512–523. https://doi.org/10.1038/s41565-024-01628-7

Citorik, R. J., Mimee, M., & Lu, T. K. (2014). Sequence-specific antimicrobials using efficiently delivered

RNA-guided

nucleases.

Nature

Biotechnology,

32(11),

1141–1145.

https://doi.org/10.1038/nbt.3011

Clinical and Laboratory Standards Institute. (2023). Performance standards for antimicrobial

susceptibility testing (33rd ed.). https://clsi.org

Dong, H., Zhang, Y., & Wang, J. (2021). RNA-targeting CRISPR-Cas13 systems for bacterial pathogen

clearance

and

resistance

reversal.

Cell

Host

&

Microbe,

29(8),

1245–1258.

https://doi.org/10.1016/j.chom.2021.06.012

European Medicines Agency. (2025). Guideline on the development of nucleic acid-based antimicrobial

therapies. https://www.ema.europa.eu

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis

program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–

191. https://doi.org/10.3758/BF03193146

Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). Sage Publications.

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 17

Girden,

E.

R.

(1992).

ANOVA:

Repeated

measures.

Sage

Publications.

https://doi.org/10.4135/9781412983433

Gomaa, A. A., Klumpe, H. E., Luo, M. L., Selle, K., Barrangou, R., & Beisel, C. L. (2023). Programmable

removal of bacterial strains by use of genome-targeting CRISPR-Cas systems. mBio, 14(2), e00482-22.

https://doi.org/10.1128/mBio.00482-22

Gootenberg, J. S., & Zhang, F. (2023). CRISPR-based antimicrobials: From molecular mechanisms to

clinical translation. Nature Reviews Microbiology, 21(5), 289–304. https://doi.org/10.1038/s41579-

022-00854-8

Government of Pakistan. (2023). Personal Data Protection Bill. Ministry of Information Technology

and Telecommunication. https://moitt.gov.pk

Guyatt, G. H., Oxman, A. D., Vist, G. E., Kunz, R., Falck-Ytter, Y., Alonso-Coello, P., & Schünemann,

H. J. (2011). GRADE: An emerging consensus on rating quality of evidence and strength of

recommendations. BMJ, 336(7650), 924–926. https://doi.org/10.1136/bmj.39489.470347.AD

Hooijmans, C. R., Rovers, M. M., de Vries, R. B., Leenaars, M., Ritskes-Hoitinga, M., & Langendam,

M. W. (2014). SYRCLE's risk of bias tool for animal studies. BMC Medical Research Methodology,

14(1), 43. https://doi.org/10.1186/1471-2288-14-43

Hoyland-Kroghsbo, N. M., Paczkowski, J., Mukherjee, S., Westbrook, J., Callura, J. A., Rasko, D. A.,

Daeffler, K. N., & Collins, J. J. (2017). Programmable bacteriophage-mediated delivery of CRISPR-Cas

systems

for

targeted

antimicrobial

therapy.

Nature

Communications,

8,

14794.

https://doi.org/10.1038/ncomms14794

Hsu, P. D., Lander, E. S., & Zhang, F. (2014). Development and applications of CRISPR-Cas9 for

genome engineering. Cell, 157(6), 1262–1278. https://doi.org/10.1016/j.cell.2014.05.010

Kleinbaum, D. G., & Klein, M. (2012). Survival analysis: A self-learning text (3rd ed.). Springer.

https://doi.org/10.1007/978-1-4419-6646-9

Koonin, E. V., & Makarova, K. S. (2019). Origins and evolution of CRISPR-Cas systems. Philosophical

Transactions

https://doi.org/10.1098/rstb.2018.0087

Kwon, J. S., Kim, Y., & Lee, S. (2021). Nanocarrier-mediated delivery of CRISPR-Cas systems for

precision antimicrobial therapy. Advanced Drug Delivery Reviews, 178, 113956.

https://doi.org/10.1016/j.addr.2021.113956

of

the

Royal

Society

B:

Biological

Sciences,

374(1772),

20180087.

Leary, S., Underwood, W., Anthony, R., Cartner, S., Corey, D., Grandin, T., Greenacre, C., Gwamese,

R., Harrington, M., Lawrence, J., Pierce, J., Reilly, R., & Sikes, R. (2020). AVMA guidelines for the

euthanasia

of

animals:

2020

edition.

American

Veterinary

Medical

Association.

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 18

https://www.avma.org/resources-tools/avma-policies/avma-guidelines-euthanasia-animals

Li, Y., Wang, X., & Chen, Z. (2022). Off-target effects and collateral activity in CRISPR-Cas

antimicrobial systems: Mechanisms and mitigation strategies. Cell Systems, 13(9), 712–725.

https://doi.org/10.1016/j.cels.2022.07.004

Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for

RNA-seq data with DESeq2. Genome Biology, 15(12), 550. https://doi.org/10.1186/s13059-014-

0550-8

Murray, C. J. L., Ikuta, K. S., Sharara, F., Swetschinski, L., Robles Aguilar, G., Gray, A., Han, C.,

Bisignano, C., Rao, P., Wool, E., Johnson, S. C., Browne, A. J., Chipeta, M. G., Fell, F., Hackett, S.,

Haines, A., Hamidi, H., Steck, C. M., & Vos, T. (2022). Global burden of bacterial antimicrobial

resistance

https://doi.org/10.1016/S0140-6736(21)02724-0

National Bioethics Committee. (2022). Ethical guidelines for biomedical research involving human

participants and animals (3rd ed.). Pakistan Medical and Dental Council.

https://www.pmdc.gov.pk/nbc

National Institutes of Health. (2024). NIH guidelines for research involving recombinant or synthetic

nucleic acid molecules. U.S. Department of Health and Human Services.

https://osp.od.nih.gov/biotechnology/nih-guidelines/

in

2019:

A

systematic

analysis.

The

Lancet,

399(10325),

629–655.

Odds, F. C. (2003). Synergy, antagonism, and what the chequerboard puts between them. Journal of

Antimicrobial Chemotherapy, 52(1), 1. https://doi.org/10.1093/jac/dkg301

O'Neill, J. (2016). Tackling drug-resistant infections globally: Final report and recommendations. The

Review on Antimicrobial Resistance. https://amr-review.org

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L.,

Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A.,

Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., & Moher, D. (2021). The PRISMA

2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71.

https://doi.org/10.1136/bmj.n71

Peters, J. M., Colvin, M., & Collins, J. J. (2024). CRISPRi-mediated resensitization of multidrug-

resistant

pathogens

to

conventional

antibiotics.

Nature

Medicine,

30(3),

789–801.

https://doi.org/10.1038/s41591-024-02845-9

Pinello, L., Canver, M. C., Hoban, M. D., Orkin, S. H., Kohn, D. B., Bauer, D. E., & Yuan, G.-C. (2016).

Analyzing CRISPR genome-editing experiments with CRISPResso. Nature Biotechnology, 34(7), 695–

697. https://doi.org/10.1038/nbt.3583

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 19

Popay, J., Roberts, H., Sowden, A., Petticrew, M., Arai, L., Rodgers, M., Britten, N., Roen, K., & Duffy,

S. (2006). Guidance on the conduct of narrative synthesis in systematic reviews: A product from the

ESRC

methods

programme.

Lancaster

University.

https://www.lancaster.ac.uk/shm/research/nssr/research/dissemination/publications/NS_Synthesis

_Guidance_v1.pdf

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. https://doi.org/10.1016/j.cell.2013.02.022

R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for

Statistical Computing. https://www.R-project.org/

Sorek, R., Kunin, V., & Hugenholtz, P. (2025). Conjugative delivery of CRISPR-Cas systems for in situ

microbiome editing and pathogen clearance. Cell Host & Microbe, 33(2), 215–229.

https://doi.org/10.1016/j.chom.2024.12.008

Sterne, J. A. C., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., Henry, D.,

Altman, D. G., Ansari, M. T., Boutron, I., Carpenter, J. R., Chan, A. W., Churchill, R., Deeks, J. J.,

Hróbjartsson, A., Kirkham, J., Jüni, P., Loke, Y. K., Pigott, T. D., & Higgins, J. P. T. (2016). ROBINS-

I: A tool for assessing risk of bias in non-randomised studies of interventions. BMJ, 355, i4919.

https://doi.org/10.1136/bmj.i4919

Tacconelli, E., Carrara, E., Savoldi, A., Harbarth, S., Mendelson, M., Monnet, D. L., Pulcini, C.,

Kahlmeter, G., Kluytmans, J., Carmeli, Y., Ouellette, M., Outterson, K., Patel, J., Cavaleri, M., Cox, E.

M., Houchens, C. R., Grayson, M. L., Hansen, P., Singh, N., & WHO Pathogens Priority List Working

Group. (2018). Discovery, research, and development of new antibiotics: The WHO priority list of

antibiotic-resistant bacteria and tuberculosis. The Lancet Infectious Diseases, 18(3), 318–327.

https://doi.org/10.1016/S1473-3099(17)30753-3

Ventola, C. L. (2015). The antibiotic resistance crisis: Part 1: Causes and threats. Pharmacy and

Therapeutics, 40(4), 277–283.

Wang, Y., Chen, L., & Liu, Q. (2025). Stimuli-responsive phage-nanoparticle hybrids for targeted

CRISPR

https://doi.org/10.1021/acsnano.4c08912

Wickham, H. (2016). ggplot2: Elegant

https://doi.org/10.1007/978-3-319-24277-4

delivery

in

chronic

biofilm

infections.

ACS

Nano,

data

19(1),

1120–1135.

graphics

for

analysis.

Springer.

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N.,

Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M.,

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13

G. 2062

Page 20

Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., & Mons, B. (2016). The FAIR Guiding

Principles for scientific data management and stewardship. Scientific Data, 3, 160018.

https://doi.org/10.1038/sdata.2016.18

World Health Organization. (2024). Global report on antimicrobial resistance and innovation in

antimicrobial development. https://www.who.int/publications/i/item/9789240094128

World Medical Association. (2013). World Medical Association Declaration of Helsinki: Ethical

principles for medical research involving human subjects. JAMA, 310(20), 2191–2194.

https://doi.org/10.1001/jama.2013.281053

Yosef, I., Goren, M. G., & Qimron, U. (2015). Proteins and DNA elements essential for the CRISPR

adaptation process in Escherichia coli. Nucleic Acids Research, 43(14), 6909–6918.

https://doi.org/10.1093/nar/gkv670

Yosef, I., Goren, M. G., & Qimron, U. (2023). Bacteriophage-mediated delivery of CRISPR-Cas systems

for

precision

antimicrobial

therapy.

Nature

Reviews

Microbiology,

21(4),

231–245.

https://doi.org/10.1038/s41579-022-00839-5

Yosef, I., Goren, M. G., & Qimron, U. (2024). In vivo efficacy and microbiome-sparing effects of

CRISPR-Cas13 antimicrobials against carbapenem-resistant Enterobacteriaceae. Science Translational

Medicine, 16(725), eadg4512. https://doi.org/10.1126/scitranslmed.adg4512

Zetsche, B., Gootenberg, J. S., Abudayyeh, O. O., Slaymaker, I. M., Makarova, K. S., Essletzbichler, P.,

Volz, S. E., Joung, J., van der Oost, J., Regev, A., Koonin, E. V., & Zhang, F. (2015). Cpf1 is a single

RNA-guided endonuclease of a class 2 CRISPR-Cas system. Cell, 163(3), 759–771.

https://doi.org/10.1016/j.cell.2015.09.038

GRJNST, Volume: 04 - Issue 2 (2026) / ISSN P: 2790-7643

Article ID: 2062

https://doi.org/10.53762/grjnst.04.02.13