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# Design, potential and limitations of conjugation-based antibacterial strategies

Elisabeth Derollez, Christian Lesterlin, Sarah Bigot

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Elisabeth Derollez, Christian Lesterlin, Sarah Bigot. Design, potential and limitations of conjugation-based antibacterial strategies. Microbial Biotechnology, 2024, 21, 10.1111/1751-7915.70050. hal-04960628

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MINI REVIEW

MICROBIAL BIOTECHNOLOGY

# Design, potential and limitations of conjugation-based antibacterial strategies

Elisabeth Derollez

Christian Lesterlin

Sarah Bigot

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Microbiologie Moléculaire et Biochimie Structurale (MMSB), Université Lyon 1, CNRS, Inserm, UMR5086, Lyon, France

Correspondence

Christian Lesterlin and Sarah Bigot, Microbiologie Moléculaire et Biochimie Structurale (MMSB), Université Lyon 1, CNRS, Inserm, UMR5086, Lyon 69007, France.

Email: christian.lesterlin@inserm.fr and sarah.bigot@cnrs.fr

Funding information

Joint Programming Initiative on Antimicrobial Resistance, Grant/Award Number: ANR-21-AAMR-0007-01; Fondation pour la Recherche Médicale, Grant/Award Number: EQU202103012587; Agence Nationale de la Recherche, Grant/Award Number: ANR-22-CE35-0017

Abstract

Over the past few decades, the global spread of antimicrobial resistance has underscored the urgent need to develop innovative non-antibiotic antibacterial strategies and to reduce antibiotic use worldwide. In response to this challenge, several methods have been developed that rely on gene transfer by conjugation to deliver toxic compounds or CRISPR systems specifically designed to kill or resensitize target bacterial strains to antibiotics. This review explores the design, potential, and limitations of these conjugation-based antibacterial strategies, focusing on the recent advances in the delivery of CRISPR systems as antibacterial effectors.

IMPACT OF ANTIMICROBIAL RESISTANCE (AMR) ON PUBLIC HEALTH AND ECONOMIC FIELDS

Various studies have evaluated the human and economic cost of antibiotic resistance. As alerted by the Lancet, there were an estimated 4.95 million deaths attributed to infection by AMR bacterial pathogens in 2019, and alarming simulations predict this number could reach 10 million people by 2050 (Murray et al., 2022). In addition to these projections, the COVID-19 pandemic raised concern about the rise of AMR infections in healthcare settings. Most of the hospitalized patients with COVID-19 receive antibiotic therapy when high usage is known to trigger AMR dissemination. In France alone, researchers have calculated that the additional costs related to infections with resistant bacteria reach €1100 per hospital stay, leading to an estimated annual additional cost of nearly €290 million for the entire population (Opatowski et al., 2019; Touat et al., 2019). In addition, AMR is projected to cost from $300 billion to

more than $1 trillion annually by 2050 worldwide (Jonas Olga et al., 2017). This economic burden highlights the critical need for immediate action.

BACTERIAL CONJUGATION: FROM AMR TRANSFER MECHANISM TO SELF-TARGETED ANTIBACTERIAL ARSENAL

The extensive use of antibiotics has led to the emergence of AMR in the clinic as well as in the environment. Antibiotics act on conserved fundamental bacterial processes, resulting in a lack of specificity in their therapeutic effect toward a targeted pathogen. This broad action impacts the entire bacterial community, while promoting the survival and proliferation of pre-existing AMR bacteria. The acquisition of AMR commonly occurs through horizontal gene transfer mechanisms, with bacterial conjugation being considered the most prevalent and important means of spreading AMR genes. Analysis of

<footnote>This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
© 2024 The Author(s). *Microbial Biotechnology* published by John Wiley & Sons Ltd.</footnote>
multidrug-resistant (MDR) commensal, environmental, and pathogenic strains has revealed a multitude of conjugative resistance-plasmids carrying genes encoding bacterial enzymes conferring resistance to most if not all classes of antibiotics currently used in clinical treatments. *Enterobacteriaceae* carrying plasmid-encoded extended-spectrum β-lactamase (ESBL) and carbapenemase genes, including *bla*~TEM~, *bla*~SHV~, *bla*~CTX-M~ and *bla*~KPC~, *bla*~NDM~, *bla*~OXA~ respectively, contribute significantly to a multitude of infections (Dunn et al., 2019). Additionally, the presence of plasmid-mediated mobile colistin resistance (*mcr*) genes accelerates the dissemination of clinically significant colistin resistance among *Enterobacteriaceae* (Liu et al., 2023). Although the conjugative plasmids share a common mechanism of conjugation, they differ in their ability to establish stable contact with recipients and to replicate in the new host, which defines their host range. Conjugative pili mediate direct contact from donor to recipient cells and can be classified into two main types. Thick and rigid pili allow efficient contact and transfer only on solid surface, and thin and flexible pili optimizing contact with distant cell and efficient transfer even on liquid environments (Bradley et al., 1980). Additionally, some plasmids also encode type IV pili, which contains PilV adhesins, required only for liquid mating (Komano et al., 1990). Recently, the PilV of the TP114 plasmid has been shown to play a major role in the conjugative host-range specificity (Allard et al., 2022). By producing PilV variants with various adhesin tip domains, the TP114 plasmid modifies the affinity of donor cells for different recipient bacteria. Narrow host-range specificity has been also observed in F-like plasmids, through the plasmid TraN protein which binds to specific outer membrane proteins in recipient cells (Low et al., 2023). In addition to receptor recognition, the ability to replicate within the recipient plays a crucial role in determining host range, as demonstrated by the F plasmid, which cannot to replicate in *Pseudomonas*, limiting its host range to *Enterobacteriaceae* (Zhong et al., 2005). In contrast, broad-host range plasmids, such as RP4 plasmid, can replicate within a wide variety of hosts and do not require specific recipient receptors for successful conjugation.

The natural mechanism of conjugation has been used for many years as a biotechnology tool for microbial engineering, such as genetic modifications of genomes, and as a means of introducing plasmid vectors into bacterial strains unsuitable to natural or artificial transformation. In recent years, the possibility of exploiting this mechanism used by bacteria against themselves has emerged by using conjugation as a mechanism to vehicle antibacterial systems (Table 1 and (Abavisani et al., 2023; Dorado-Morales et al., 2023; Kundar & Gokarn, 2022; Mayorga-Ramos et al., 2023; Wu et al., 2021)). Conjugation-based delivery strategies use conjugative machinery in cis or trans

to deliver antibacterial systems encoded by a large self-transmissible conjugative plasmid or a small mobilizable plasmid, respectively (Table 1 and Figure 1A). In the first strategy, the conjugative machinery is utilized in cis, meaning it is encoded on the same large self-transmissible conjugative plasmid that carries the antibacterial system. This allows the plasmid to independently facilitate its own transfer between bacterial cells. In the second strategy, the conjugative machinery is utilized in trans, where the antibacterial system is encoded on a small mobilizable plasmid. In this case, the mobilizable plasmid relies on a separate helper plasmid or chromosome that provide the necessary conjugative functions for transfer (Figure 1A). The diversity of plasmids, based on their type of pili and host range, provides a wide selection of helper plasmids suited to different experimental design. To date, the RP4 plasmid conjugative system has been the most widely used, likely due to its broad host range (Table 1). Alternative delivery methods have been developed using phages and nanoparticles as vehicles, with their respective advantages and disadvantages reviewed (Mayorga-Ramos et al., 2023). Moreover, the efficacy of mini-cells as delivery agents has been recently explored and validated (Li et al., 2023b).

To date, the arsenal of antibacterial systems delivered through conjugation relies on toxic compounds and CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas (CRISPR associated) systems (Table 1). One mechanism to induce cell death involves toxicity caused by plasmid overreplication (Peng et al., 2006). Specifically, an excessive plasmid copy number beyond what the cell host can tolerate leads to cell death. In the designed system, donor cells transfer a mobilizable plasmid that undergoes overreplication exclusively in recipient cells. This overreplication is triggered by an engineered mutation in the plasmid *pir* gene, which produces a hyperactive form of the replication initiation protein π, thereby increasing the plasmid copy number. Other studies have opted to deliver natural colicins and bacterial toxins from the type II toxin-antitoxin systems of diverse activities (Dmowski & Kern-Zdanowicz, 2020; López-Igual et al., 2019; Shankar et al., 2007; Starčič Erjavec et al., 2015). In these engineered antibacterial systems, donor cells are protected from toxin activity by producing the cognate antitoxin protein. Bacterial cell death is induced through various mechanisms, such as degradation of chromosomal DNA (Colicin E7), inactivation of the DNA gyrase (CcdB toxin), a type II topoisomerase essential for host DNA replication, cleavage of 16S rRNA which halts translation (Colicin E3) or inhibition of cell wall synthesis through specific phosphorylation of peptidoglycan precursor UNAG (Zeta toxin). In 2019, Collins and colleagues designed synthetic antimicrobial aggregation peptides termed OpaL (overexpressed protein aggregate lipophilic), as highly potent antimicrobial agents
<table><caption>TABLE 1 List of antibacterial systems delivered by conjugation.</caption><thead><tr><th>Antibacterial system</th><th>Conjugative system</th><th>Target (host)</th><th>Mode of action</th><th>Ref</th></tr></thead><tbody><tr><td colspan="5"><strong>Toxic compounds</strong></td></tr><tr><td>Plasmid overreplication</td><td>IncP1α RP4<sup>a</sup></td><td>E. coli O157:H7, Serratia marcescens, Enterobacter<br>nimipressuralis, Salmonella enterica, Erwinia caratovora</td><td>Growth inhibition by plasmid<br>overreplication</td><td>(Peng et al., 2006)<sup>c</sup></td></tr><tr><td>Colicin E3</td><td>IncP1α RP4<sup>a</sup></td><td>Acinetobacter baumannii</td><td>16S rRNA Cleavage</td><td>(Shankar et al., 2007)<sup>c</sup></td></tr><tr><td>Colicin E7</td><td>IncF pOX38<sup>a</sup></td><td>E. coli K12, UPEC DL82</td><td>DNA degradation</td><td>(Starčič Erjavec et al., 2015)<sup>c</sup></td></tr><tr><td>Synthetic Aggregating<br>Antimicrobial peptide OpaL</td><td>IncP1α RP4<sup>b</sup></td><td>E. coli BL21</td><td>Disruption of homeostasis</td><td>(Collins et al., 2019)<sup>c</sup></td></tr><tr><td>CcdB toxin</td><td>IncP1α RP4<sup>b</sup></td><td>Pathogenic Vibrio cholerae</td><td>DNA Gyrase inactivation</td><td>(López-Igual et al., 2019)<sup>c,d</sup></td></tr><tr><td>Zeta toxin</td><td>IncM pCTX-M3<sup>b</sup></td><td>E. coli, Bacillus subtilis, lactococcus lactis</td><td>Peptidoglycan synthesis<br>perturbation</td><td>(Dmowski &<br>Kern-Zdanowicz, 2020)<sup>c</sup></td></tr><tr><td colspan="5"><strong>CRISPR systems</strong></td></tr><tr><td colspan="5"><strong>Killing</strong></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>bla<sub>NDM-1</sub>/bla<sub>SHV-18</sub> introduced in E. coli</td><td>Chr. degradation</td><td>(Citorik et al., 2014)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>a</sup></td><td>Chr. loci S. Typhimurium LT2</td><td>Chr. degradation</td><td>(Hamilton et al., 2019)<sup>c</sup></td></tr><tr><td>Cas9</td><td>Incl TP114<sup>a</sup></td><td>cat introduced in E. coli Nissle 1917, Citrobacter rodentium<br>DDBS100</td><td>Chr. degradation</td><td>(Neil et al., 2021)<sup>c,d</sup></td></tr><tr><td>Cas9</td><td>IncF F<sup>b</sup></td><td>Chr. loci E. coli MG1655, C. rodentium ICC168, EPEC<br>E2348/69, Enterobacter cloacae ATCC 13047</td><td>Chr. degradation</td><td>(Reuter et al., 2021)<sup>c</sup></td></tr><tr><td>LwaCas13a</td><td>IncP1α RP4<sup>b</sup></td><td>dnaA, katG, hilA S. Typhimurium</td><td>random RNA degradation</td><td>(Song et al., 2022)<sup>c,d</sup></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>Chr. loci E. coli MG1655, Pseudomonas aeruginosa PAO1,<br>Klebsiella pneumoniae LM21, V. cholerae N16961, S.<br>Typhimurium LT2</td><td>Chr. degradation</td><td>(Djermoun et al., 2023)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup><br>IncF pOX38<sup>b</sup><br>IncN pKM101<sup>b</sup></td><td>ChlR introduced in E. coli MC4100<br>tssJ P. aeruginosa PAO1</td><td>Chr. degradation</td><td>(Li et al., 2023b)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1α pRK24<sup>a</sup><br>IncP1β pBP136<sup>a</sup></td><td>ssaN S. Typhimurium<br>eae EPEC, EHEC</td><td>Chr. degradation</td><td>(Sheng et al., 2023)<sup>c,d</sup></td></tr><tr><td>Cas12a</td><td>IncW R388<sup>b</sup></td><td>lacZ E. coli MG1655</td><td>Chr. degradation</td><td>(Guzmán-Herrador<br>et al., 2024)<sup>c</sup></td></tr><tr><td colspan="5"><strong>Drug resensitization</strong></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>mcr-1 on pHNSHP45 plasmid (E. coli MG1655)</td><td>colistin resensitization</td><td>(Dong et al., 2019)<sup>c</sup></td></tr><tr><td>Cas9</td><td>PRP pPD1<sup>a</sup></td><td>tetM on pCF10 plasmid<br>ermB on pAM771 plasmid (Enterococcus faecalis)</td><td>Tetracycline and<br>Erythromycin resensitization</td><td>(Rodrigues et al., 2019)<sup>c,d</sup></td></tr></tbody></table>

(Continues)
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th>Antibacterial system</th><th>Conjugative system</th><th>Target (host)</th><th>Mode of action</th><th>Ref</th></tr></thead><tbody><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>bla<sub>TEM-52b</sub> on pEC15 plasmid<br>bla<sub>CTX-M-14</sub> on pEC13 plasmid (E. coli HB101)</td><td>β-lactam resensitization</td><td>(Ruotsalainen et al., 2019)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>nikA, hicB, vagC, sopA, mcr-1 on plasmids p14EC033a,b,d,f and p14ECC007a,b (E. coli clinical isolates)</td><td>colistin resensitization</td><td>(Wang et al., 2019)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>bla<sub>NDM-1</sub> on cloning vector pBBR1 (E. coli SAR08)</td><td>β-lactam resensitization</td><td>(Wongpayak et al., 2021)<sup>c</sup></td></tr><tr><td>Cas9/dCas9</td><td>IncF F<sup>b</sup></td><td>bla<sub>OXA48</sub> on pOXA-48a plasmid (E. coli MG1655)</td><td>Carbapenem resensitization</td><td>(Reuter et al., 2021)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>bla<sub>NDM-5</sub> on pNDM-5 plasmid (E. coli J53)</td><td>Carbapenem resensitization</td><td>(Li et al., 2022)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>tetA on vectors pBR322, p15A, pUC (E. coli MG1655)<br>bla on RP4 plasmid (P. aeruginosa PAO1)</td><td>Tetracycline and β-lactam resensitization</td><td>(Li et al., 2023a)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1ε pKJK5<sup>a</sup></td><td>aacC1 on vector pHERD30T (E. coli K12)</td><td>Chloramphenicol resensitization</td><td>(Walker-Sünderhauf et al., 2023)<sup>c</sup></td></tr><tr><td>Cas3</td><td>IncP1α RP4<sup>b</sup></td><td>bla<sub>KPC</sub> on IncFII plasmid (K. pneumoniae)</td><td>Meropenem resensitization</td><td>(Zhou et al., 2023)<sup>c,d</sup></td></tr><tr><td>Cas9</td><td>IncP1α pRK24<sup>a</sup><br>IncP1β pBP136<sup>a</sup></td><td>bla<sub>CMY-2</sub> on pAR06302 plasmid (E. coli C3b)</td><td>β-lactam resensitization</td><td>(Sheng et al., 2023)<sup>c,d</sup></td></tr><tr><td>Cas9</td><td>PRP pPD1<sup>a</sup></td><td>ermB on pAM714 plasmid (E. faecalis)</td><td>Erythromycin resensitization</td><td>(Upreti et al., 2024)<sup>c</sup></td></tr><tr><td>Cas9</td><td>IncP1α RP4<sup>b</sup></td><td>tet(X4), mcr-1 on clinical plasmids (E. coli EC600)<sup>c</sup> (E. coli B2 and B3-1 clinical isolates)<sup>d</sup></td><td>Tigecycline and colistin resensitization</td><td>(Zhang et al., 2024)<sup>c,d</sup></td></tr></tbody></table>

Abbreviation: Chr., chromosome.

<footnote><sup>a</sup>Conjugative machinery in cis/self-transmissible plasmid.</footnote>

<footnote><sup>b</sup>Conjugative machinery in trans/mobilizable plasmid.</footnote>

<footnote><sup>c</sup>Tested in vitro.</footnote>

<footnote><sup>d</sup>Tested in vivo.</footnote>
<figure><img src="image_5.png" /><figcaption>**FIGURE 1** Overview of conjugation-based antibacterial strategies. (A) The panel illustrates *cis* and *trans* conjugation-based delivery methods through a conjugative Type IV secretion system (T4SS). The expression on the surface of donor and recipient cells of specific nanobodies (Nb) and their cognate antigen (Ag) as synthetic cell-to-cell adhesion systems is depicted. (B) The cumulative number of publications since 2006 reporting the use of conjugation for delivering toxic compounds or CRISPR systems. (C) The panel presents the mechanisms of bacterial killing and drug resensitization by CRISPR-Cas systems.</figcaption></figure>

(Collins et al., 2019). Due to their extreme hydrophobicity, OpaL peptides form co-aggregates with endogenous macromolecules, disrupting bacterial homeostasis.

Delivery of toxins by conjugation has proven effective in killing bacteria. However, similar to antibiotics, their impact is broad, affecting all populations capable

of acquiring the plasmid that produces the antibacterial system. To solve this lack of specificity, López-Igual et al. devised an ingenious strategy to confine the production and activation of toxins to MDR pathogenic *Vibrio cholerae* (López-Igual et al., 2019). In this system, the expression of the toxin gene is triggered
by a transcriptional regulator controlling *V. cholerae*'s virulence factors. Toxin activation occurs by repressing the antitoxin gene through a regulator associated with a genetic element involved in MDR *V. cholerae* strains (López-Igual et al., 2019). A major limitation of this system remains its restriction to *V. cholerae* species and its challenging adaptation for targeting other species. In contrast, CRISPR-Cas systems offer broader applicability due to their specificity, which relies on a ~20-nucleotide targeted sequence, enabling them to target a wide range of bacterial species. The specific targeting and binding of all CRISPR-Cas systems rely on a CRISPR RNA (crRNA) or spacer that recognizes the target sequence adjacent to a Protospacer Adjacent Motif (PAM) to load the CRISPR-Cas complex. Figure 1B illustrates the cumulative number of publications over the years that report the use of conjugation for delivering antibacterial systems. Since 2020, there have been no reports on the use of toxic compounds as antibacterial agents. However, CRISPR-based strategies continue to be developed, with at least one publication on this topic each year.

## CRISPR SYSTEMS: A HIGHLY SPECIFIC TARGETING THERAPEUTIC OPTION

CRISPR-Cas systems are natural mechanisms of adaptive immunity against exogenous DNA in bacteria and archaea. By their ability to target nucleic acids with high precision and reliability, these systems revolutionized genetic engineering and have been rapidly deployed for their potential as antimicrobial agents. The specificity of the CRISPR-Cas system is so precise that the complex can distinguish between a susceptible and a resistant strain that differ by a single mutation in the target, such as the *gyrA* gene, where a spontaneous mutation confers resistance to quinolones (Citorik et al., 2014).

### Diversity of CRISPR systems as antibacterial

The CRISPR-Cas9 system from *Streptococcus pyogenes* was initially engineered to achieve specific antimicrobial activity by inducing double-strand breaks (DSBs) in DNA or through CRISPR interference (CRISPRi) for specific silencing of gene transcription using catalytically dead Cas9 (dCas9) (Bikard & Barrangou, 2017). However, recent studies have expanded this antimicrobial strategy by including other CRISPR-Cas systems (Table 1). Efficient killing can be achieved using the Cas12a protein, which introduces DSBs in the target DNA but, unlike the Cas9 protein, does not require a transactivating CRISPR RNA (tracrRNA) to form the Cas complex (Guzmán-Herrador et al., 2024).

Elimination of pathogen species using the Cas13a system has also been developed (Song et al., 2022). The CRISPR-Cas13a system, characterized by RNA-guided single-stranded (ssRNA) cleavage activity results in specific gene inhibition and bactericidal effect. Recently, Zhou et al. engineered a CRISPR-Cas3 system, which cleaves and degrades DNA through exonuclease activity rather than cleaving as the CRISPR-Cas9 system does (Zhou et al., 2023). The ongoing progress of CRISPR technologies, coupled with improved computational methods for mining metagenomic data, will further expand the CRISPR antimicrobial toolkit (Shah et al., 2019; Zhang et al., 2014). Additionally, sequencing DNA directly from natural microbial communities offers the key advantage of discovering CRISPR systems from uncultivated microorganisms (Burstein et al., 2017; Esquerra-Ruvira et al., 2023). However, regardless of the extent of the CRISPR system choice and experimental design, targeting can result in cell death of the target or sensitization of drug-resistant bacteria by loss of AMR (Figure 1C).

### CRISPR strategy for bacterial killing

The majority of CRISPR cell-killing strategies are based on the introduction of DSBs into target chromosomal sites. Bacteria cannot initiate repair mechanisms of this type of cleavage at any chromosomal location resulting in chromosome degradation and lethality (Cui & Bikard, 2016). Using chromosomal cleavage antimicrobial strategy, numerous studies demonstrated efficient killing of pathogens S. Typhimurium (Djermoun et al., 2023; Hamilton et al., 2019; Sheng et al., 2023), *C. rodentium* (Neil et al., 2020; Reuter et al., 2021), *P. aeruginosa* (Djermoun et al., 2023; Liu et al., 2023), *K. pneumoniae* (Djermoun et al., 2023), and *E. cloacae*, EPEC and EHEC (Reuter et al., 2021; Sheng et al., 2023) (Table 1). Alternatively, cell death can be triggered by CRISPRi through transcriptional repression of essential genes (Figure 1C). However, this strategy has not been tested to date by conjugation-based delivery strategies.

### CRISPR strategy for resensitizing antibiotic-resistant bacteria

Acquired resistance is mainly driven by the horizontal transfer of AMR conjugative plasmids making them a promising target for resensitizing antibiotic-resistant bacteria. Antibiotic sensitization is achieved by triggering plasmid loss following its degradation by CRISPR system activity (Figure 1C). To date, delivering spacer targeting plasmid AMR genes has been the primary strategy for inducing plasmid degradation (Table 1). Using this approach, numerous studies have
demonstrated the elimination of clinical AMR conjuga-
tive plasmids in bacteria, resulting in resensitization
to carbapenems (Li et al., 2022; Reuter et al., 2021),
β-lactams (Ruotsalainen et al., 2019), colistin (Dong
et al., 2019; Sheng et al., 2023; Wang et al., 2019;
Zhang et al., 2024) and tigecycline (Zhang et al., 2024).
While this strategy is designed to avoid killing bacteria
and instead focuses on the loss of AMR plasmids, the
presence of plasmid toxin-antitoxin addiction systems
can result in cell death after plasmid curing (Citorik
et al., 2014; Reuter et al., 2021). An alternative ap-
proach to resensitize antibiotic-resistant bacteria in-
volves gene interference by repressing the expression
of AMR genes, either located on the chromosome or
conjugative plasmids, and blocking the production of
bacterial enzymes conferring antibiotic resistance in-
stead of plasmid degradation (Figure 1C). So far, one
study has successfully applied this strategy to resen-
sitize carbapenem-resistant bacteria by inhibiting the
expression of the *bla*<sub>OXA48</sub> gene, which encodes a
carbapenemase on the clinical pOXA-48a plasmid
(Reuter et al., 2021). In addition, CRISPR systems
designed against conjugative plasmids act as a bar-
rier to AMR spreading. Delivered in AMR plasmid-free
bacteria within a bacterial community, they can block
the acquisition of targeted AMR conjugative plasmids
by preventing their establishment in bacteria (Reuter
et al., 2021; Walker-Sünderhauf et al., 2023).

CRISPR strategy, the challenge of
designing spacers

The efficacy of CRISPR-Cas antimicrobial strategy re-
lies on the precise design of spacer sequences spe-
cific to the targeted genome. This can be efficiently
determined using basic BLAST alignment. However,
the growing number of computational CRISPR tools
available online further facilitates this design process
(Torres-Perez et al., 2019). Most CRISPR tools oper-
ate on the principle of first identifying a candidate tar-
get region as input, which is then used to generate and
display spacer sequences relative to the genomic fea-
tures within the browser. While traditional algorithms
typically discard spacers that target multiple sites,
CRISPR Associated Software for Pathway Engineering
and Research (CASPER) was developed to design
a single spacer capable of targeting multiple sites
across a genome (Mendoza & Trinh, 2018). In addition,
CASPER's algorithm enables the design of spacers
that can target multiple populations by simultaneously
analysing multiple genomes. One challenge of alter-
native antibacterial strategies is the precise targeting
of specific bacterial species within a given microbiota,
without impacting other bacterial strains. This signifi-
cantly restricts the number of suitable spacers, making
their identification and design particularly challenging.

The only algorithm that overcomes this challenge is the CSTB (Crispr Search Tool for Bacteria) algorithm (https://cstb.ibcp.fr.), which enables comparative analysis of spacer sequence across approximately 3000 bacterial genomes and plasmids (Reuter et al., 2021). Similar to CASPER's algorithm, CSTB allows the design of spacers targeting multiple sites and organisms. However, it is unique in that it allows users to exclude specific organisms during the design process, ensuring the targeting of particular strains without affecting others (Reuter et al., 2021). As an example of CSTB's effectiveness, we searched for a spacer that specifically targets the *P. aeruginosa* group-*P. aeruginosa*, *P. oleovorans*, *P. alcaligenes*, *P. citronellolis*, *P. resinovorans*, and *P. mendocina*, while sparing all other bacteria in the database. The algorithm's comparative analysis identified a single spacer sequence that would have been extremely difficult to discover without the help of CSTB. However, an inconvenience associated with CSTB is its limitation to Cas9, necessitating further development to accommodate spacer design for other nucleases such as Cas13a. This limitation poses challenges for researchers seeking to utilize alternative nucleases in CRISPR-based antibacterial strategies. Therefore, future enhancements to CSTB should prioritize expanding its capabilities to support a broader range of nucleases, thereby enhancing its utility and versatility in the design of antimicrobial systems.

LIMITATION OF GENETIC
ENGINEERING-BASED
CONJUGATION STRATEGIES

The practical implementation and effectiveness of
conjugation-based antibacterial approaches are sub-
jected to several constraints and potential limitations.
One primary challenge lies in achieving optimal ef-
ficiency in the transfer of plasmids from donors to
targeted strains. Some plasmids have a narrow host
range, transferring only between closely related bac-
terial species, while others possess a broad host
range, capable of moving across different genera
and even between Gram-positive and Gram-negative
bacteria. This first requires choosing a conjuga-
tion system with an appropriate host range depend-
ing on the bacterial species or strain to be targeted.
Strategies based on mobilizable plasmids offer great
versatility in this regard, as their host range can be
easily and rapidly modulated by changing the helper
plasmid. Strategy based on Targeted Antibacterial
Plasmids (TAPs) demonstrated a modulable mobi-
lization from narrow to broad host range depending
on the conjugative systems provided by the helper
system (Djermoun et al., 2023; Reuter et al., 2021).
Due to its broad host range, the IncP RP4 plasmid
has been used in a large part of delivery systems
developed to date (Table 1). However, other conjugation systems also attract substantial attention, such as the Incl TP114 plasmid which exhibits high transfer efficiency within the mouse gut (Allard et al., 2022; Neil et al., 2020), or the IncM pCTX-M3 plasmid capable of transferring even to Gram-positive recipients (Dmowski & Kern-Zdanowicz, 2020). Besides these specific examples, new conjugative plasmids are continuously being discovered through metagenomic analysis of genetic material from environmental samples. These studies dramatically increase our understanding of the remarkable diversity of conjugative plasmids in nature, with the gut environment serving as a particularly rich reservoir for these mobile genetic elements. This diverse array of conjugative plasmids serves as a valuable reservoir of conjugation systems that could function as effective gene delivery vehicles. Understanding the host range and the ecosystems from which these plasmids originate can aid in selecting conjugation systems with the greatest potential for successful transfer. However, experimental research is required to evaluate the biological properties of these plasmids, including their host range and transfer efficiency in various ecosystems, and identify plasmids with desirable specificities for targeted applications.

Various strategies have been explored to enhance the transfer efficiency of natural conjugation systems. One approach involves plasmid mutagenesis, using techniques such as Adaptive Laboratory Evolution (ALE) (Neil et al., 2020) or transposon mutagenesis, followed by the selection of plasmid variants exhibiting enhanced transfer rates, commonly referred to as the hyperspreader phenotype (Yamaichi et al., 2015). Another strategy focuses on optimizing adhesion between donor and recipient cells by using beads (Hamilton et al., 2019) or synthetic cell-to-cell adhesion systems involving nanobodies (Figure 1A and (Li et al., 2023b; Robledo et al., 2022)). However, while these strategies exhibit promise, they may not be directly translatable to natural environments, which would require engineering the targeted bacteria. Despite these promising engineering possibilities, it remains uncertain whether the modified conjugation systems can effectively deliver genetic material to all target cells within natural microbial consortia, which consist of a complex mix of diverse bacterial strains with varying susceptibilities to plasmid uptake. Factors such as physical barriers, microbial community structure, and the physiological state of recipient cells can significantly influence the transfer rate of plasmid transfer. Therefore, the actual percentage of target cells that will acquire the plasmid remains unclear. To address this concern, it is crucial to conduct experimental studies that evaluate conjugation efficiency across different environmental conditions and microbial communities. Acknowledging and

investigating these limitations will be essential for optimizing conjugation-based approaches and ensuring their effectiveness in natural settings.

Another constraint is to ensure the appropriate expression of antibacterial systems within recipient cells, as overproduction of Cas proteins can lead to toxicity and off-target effects (Cui et al., 2018). While inducible systems commonly employed in vitro may not be suitable for in vivo applications, achieving optimal Cas and guide RNA production can be facilitated through the utilization of synthetic constitutive promoters that function across a wide range of bacterial hosts (Djermoun et al., 2023; Reuter et al., 2021). Even with the use of synthetic constitutive promoters designed to function across a wide range of bacterial hosts, introduced promoters may not always perform as expected in the target bacterial strain. Differences in promoter recognition, transcriptional machinery, and regulatory networks can lead to suboptimal expression levels or complete inactivity of the antibacterial systems. This limitation highlights the importance of experimental validation to confirm the functionality of promoters within the specific target strain. Alternative strategies include subverting conjugative machinery to deliver Cas-nucleoprotein complexes covalently attached to transferred DNA (Guzmán-Herrador et al., 2024).

Finally and foremost, specific barrier mechanisms present in the targeted recipient strain may inherently jeopardize the efficiency of conjugation-based antibacterial approaches. Defence systems, such as CRISPR-Cas and restriction-modification systems, restrict the entry of incoming DNA. Specific phages hijacking the conjugative pili, entry exclusion systems produced by resident plasmids closely related to the antibacterial conjugation system (Garcillán-Barcia & de la Cruz, 2008), or capsules (Haudiquet et al., 2024) are other physical barriers that may impact the antibacterial delivery process. In addition, escaping mechanisms can also emerge within the targeted strain characterized by spontaneous mutations or rearrangements of the targeted locus, or inactivation of the CRISPR system by insertion sequences or transposons (Citorik et al., 2014; Cui & Bikard, 2016; Djermoun et al., 2023; Hamilton et al., 2019; Li et al., 2023a; Neil et al., 2021; Reuter et al., 2021; Ruotsalainen et al., 2019; Zhang et al., 2024). Understanding and circumventing these mechanisms are essential for enhancing the efficacy of CRISPR-based strategies.

## CONCLUDING REMARKS

In conclusion, various limitations and constraints associated with conjugation-based antibacterial strategies can be identified, which complicate the prediction
of their applicability and efficacy across defined environments and among specific donor and recipient strains. Therefore, a systematic experimental approach employing model systems may be indispensable for comprehensively addressing and resolving these complexities. There is a pressing need to evaluate these antimicrobial systems in environments that better mimic natural conditions and are tailored toward clinical applications. Encouragingly, several studies have already demonstrated the effectiveness of CRISPR-based approaches in vivo, employing models such gut colonization in mice (Neil et al., 2021; Rodrigues et al., 2019; Selle et al., 2020; Song et al., 2022; Zhang et al., 2024) and murine skin infection (Bikard et al., 2014; Cobb et al., 2019; Park et al., 2017), which hold promise for future applications.

## AUTHOR CONTRIBUTIONS

**Elisabeth Derollez:** Writing – review and editing.

**Christian Lesterlin:** Funding acquisition; writing – review and editing.
**Sarah Bigot:** Funding acquisition; writing – original draft; writing – review and editing.

## ACKNOWLEDGEMENTS

This work was supported by the JPI AMR STARS-TAP [grant number ANR-21-AAMR-0007-01], the FRM (Foundation for Medical Research) [grant number EQU202103012587], the ANR through DeCa-P [grant number ANR-22-CE35-0017].

## CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

## ORCID

Sarah Bigot ID https://orcid.org/0000-0002-9340-6303

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**How to cite this article:** Derollez, E., Lesterlin, C. & Bigot, S. (2024) Design, potential and limitations of conjugation-based antibacterial strategies. *Microbial Biotechnology*, **17**, e70050. Available from: https://doi.org/10.1111/1751-7915.70050