Characterisation of in vitro resistance selection against second-/last-line antibiotics in methicillin-resistant Staphylococcus aureus

Characterisation of in vitro resistance selection against second-/last-line antibiotics in methicillin-resistant Staphylococcus aureus | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Characterisation of in vitro resistance selection against second-/last-line antibiotics in methicillin-resistant Staphylococcus aureus View ORCID Profile Anggia Prasetyoputri , View ORCID Profile Miranda E. Pitt , View ORCID Profile Minh Duc Cao , View ORCID Profile Soumya Ramu , Angela Kavanagh , View ORCID Profile Alysha G. Elliott , View ORCID Profile Devika Ganesamoorthy , View ORCID Profile Ian Monk , View ORCID Profile Timothy P. Stinear , View ORCID Profile Matthew A. Cooper , View ORCID Profile Lachlan J.M. Coin , View ORCID Profile Mark A. T. Blaskovich doi: https://doi.org/10.1101/2024.12.22.630013 Anggia Prasetyoputri 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia 2 Research Centre for Applied Microbiology, National Research and Innovation Agency , Cibinong, Indonesia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anggia Prasetyoputri Miranda E. Pitt 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia 3 Australian Institute for Microbiology and Infection, University of Technology Sydney , Ultimo, New South Wales, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Miranda E. Pitt Minh Duc Cao 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Minh Duc Cao Soumya Ramu 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Soumya Ramu Angela Kavanagh 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alysha G. Elliott 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alysha G. Elliott Devika Ganesamoorthy 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Devika Ganesamoorthy Ian Monk 4 The Peter Doherty Institute for Infection and Immunity, University of Melbourne , Melbourne, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ian Monk Timothy P. Stinear 4 The Peter Doherty Institute for Infection and Immunity, University of Melbourne , Melbourne, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Timothy P. Stinear Matthew A. Cooper 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia 5 Trinity College Dublin , Dublin, Ireland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Matthew A. Cooper Lachlan J.M. Coin 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia 4 The Peter Doherty Institute for Infection and Immunity, University of Melbourne , Melbourne, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lachlan J.M. Coin For correspondence: m.blaskovich{at}imb.uq.edu.au lachlan.coin{at}unimelb.edu.au Mark A. T. Blaskovich 1 Centre for Superbug Solutions, Institute for Molecular Bioscience, The University of Queensland , Brisbane, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mark A. T. Blaskovich For correspondence: m.blaskovich{at}imb.uq.edu.au lachlan.coin{at}unimelb.edu.au Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Background The increasing occurrence of MRSA clinical isolates harbouring reduced susceptibility to mainstay antibiotics has escalated the use of second and last line antibiotics. Hence, it is critical to evaluate the likelihood of MRSA developing clinical resistance to these antibiotics. Objectives Our study sought to identify the rate in which MRSA develop resistance to vancomycin, daptomycin and linezolid in vitro and further determine the mechanisms underpinning resistance. Methods MRSA was exposed to increasing concentrations of vancomycin, daptomycin, and linezolid for 20 days, with eight replicates for each antibiotic conducted in parallel. The resulting day 20 (D20) isolates were subjected to antimicrobial susceptibility testing, whole genome sequencing, autolysis assays, and growth curves to determine bacterial fitness. Results Exposure to vancomycin or linezolid for 20 days resulted in a subtle two-fold increase in the MIC, whereas daptomycin exposure yielded daptomycin-nonsusceptible isolates with up to 16-fold MIC increase. The MIC increase was accompanied by variable changes in relative fitness and reduced resistance to autolysis in some isolates. D20 isolates harboured mutations in genes commonly associated with resistance to the respective antibiotics (e.g. walK for vancomycin, mprF and rpoB for daptomycin, rplC for linezolid), along with several previously unreported variants. Introduction of key mutations to these identified genes in the parental strain via allelic exchange confirmed their role in the development of resistance. Conclusions In vitro selection against vancomycin, daptomycin, or linezolid resulted in the acquisition of mutations similar to those correlated with clinical resistance, including the associated phenotypic alterations. INTRODUCTION MRSA has retained its ranking as a ‘High’ priority pathogen on the revised 2024 WHO Bacterial Priority Pathogens List 1 and has been identified as one of the leading causes of global infections 2 , 3 and economic burden. 4 The glycopeptide antibiotic vancomycin has been a mainstay treatment for MRSA-related infections. 5 Although complete resistance against vancomycin in MRSA is currently rare, 6 its efficacy is compromised by the increasing incidence of vancomycin-intermediate S. aureus (VISA) and heterogeneous VISA (hVISA). 7 Treatment failures and poor clinical outcomes in glycopeptide-treated patients have been associated with reduced vancomycin susceptibility 6 , 8 , 9 and vancomycin tolerance. 10 Furthermore, emerging resistance to alternative MRSA antibiotics, such as linezolid 11 and daptomycin 12 also adds to the current burden, and highlights the importance for discovery of new MRSA antibiotics. Clinical resistance in MRSA and its underlying genetic basis has been extensively investigated 6 , 13 – 15 Elucidation of the genomic basis of resistance has been conducted in clinical isolates 16 , 17 as well as laboratory-derived strains. 18 , 19 Collectively, these have revealed pathways more prone to mutations selected for by clinically-used antibiotics and have been applied to help design new antibiotics that overcome existing resistance mechanisms. New MRSA antibiotics ideally would have a low propensity to select for clinical resistance. To enable development of such antibiotics, a comprehensive understanding of the nature of resistance mechanisms that might impair their efficacy, and the rate at which that resistance arises, is essential. Availability of in vitro resistance selection that could reveal genomic and phenotypic changes similar to those found in clinical settings. This would be a valuable tool for predicting mutations and monitoring the progression of resistance before a candidate antibiotic progressed to the clinic. As an example, laboratory-derived MRSA with reduced susceptibility to daptomycin were generated via resistance selection 20 – 22 and certain genomic variants potentially associated with resistance development were identified. Resistance selection could also provide clues to potential cross-resistance between antibiotics having the same cellular target 23 or give insights into antibiotic resistance mechanisms. 24 This study aimed to investigate the feasibility of using in vitro selection of resistance against vancomycin, daptomycin or linezolid in MRSA to predict mutations similarly identified in clinical isolates. We selected an MRSA strain (ATCC 43300) which is susceptible to vancomycin, daptomycin, and linezolid. ATCC 43300 was serially passaged in the presence of increasing concentrations of each antibiotic and the development of resistance was monitored over 20 days. Genomic and phenotypic alterations were elucidated along with propensities for cross-resistance These investigations are expected to provide further insight into resistance development in MRSA and tools for predicting potential clinical resistance in the context of novel antibiotic discovery. MATERIALS & METHODS Bacterial strains and growth conditions MRSA ATCC 43300 isolates were sourced from the American Type Culture Collection (ATCC; Manassas, USA). ATCC 43300 (housed at the University of Queensland - MIC: vancomycin = 1mg/L; daptomycin = 0.5mg/L; linezolid = 2mg/L) was used for in vitro resistance selection, subsequent phenotypic assays and genome sequencing. Another ATCC 43300 (University of Melbourne – MIC: vancomycin = 1mg/L; daptomycin = 0.125mg/L) was used in allelic exchange assays. Bacterial isolates were stored in 20% v/v glycerol at -80 °C. ATCC 43300 was grown in cation-adjusted Muller Hinton Broth (Ca-MHB, Oxoid) at 37°C, 220rpm, unless otherwise indicated. Resistance selection In vitro resistance selection was conducted 25 for vancomycin, daptomycin, or linezolid, with detailed procedure in Supplementary data. Corning® non-binding surface (NBS) 96-well plates (Sigma- Aldrich) were used to minimise binding of antibiotics to test plate. 26 (Supplementary material). Following 20 days of antibiotic passaging, isolates were further grown for 5 days (Day 25 (D25)) without antibiotic to assess stability of resistance. Antimicrobial susceptibility testing The MIC was determined by the broth microdilution (BMD) method according to CLSI guidelines 27 using Ca-MHB (Supplementary data). Susceptibility of all D20 isolates were assessed against their respective selecting antibiotic after the resistance selection experiment was completed, as well as against all antibiotics (vancomycin, daptomycin and linezolid) to assess potential cross-resistance. MIC breakpoints were determined using standards from EUCAST version 14.0, 28 where resistance was defined as MIC ˃ 2 mg/L for vancomycin, MIC ˃ 1 mg/L for daptomycin, and MIC ˃ 4 mg/L for linezolid. DNA extractions and library preparation Aliquots (10 µL) of glycerol stocks of initial day (day 0/D0) and day 5, 10, 15 and 20 isolates were grown overnight in Ca-MHB supplemented with antibiotics (up to half MIC recorded) (Table S1). Cells from 4 mL of culture were centrifuged (14,000 rpm, 2 mins) and DNA extracted using DNeasy Blood and Tissue Kit (QIAGEN) according to manufacturer’s instructions. Following quantification with Qubit®3.0 (Thermo Fisher Scientific), a library preparation with 1 ng DNA input was conducted using Nextera XT Kit (Illumina). Library preparation of the D0 isolate was performed with the SQK- LSK109 kit (Oxford Nanopore Technologies, ONT) and sequenced on an R9 flow cell. DNA fragmentation was determined with a TapeStation 4200 (Agilent). Sequencing and analysis All DNA libraries were run on Illumina HiSeq2500 with 150 bp paired-end reads and ≥ 100X coverage. The reference D0 isolate was sequenced on a MinION (ONT), base-called using Guppy 2.3.7 and a complete hybrid assembly (Illumina, ONT reads) generated via Unicycler v0.3.7. 29 Illumina reads were trimmed using Trimmomatic v0.27, 30 assembled using SPAdes v3.10.1 31 and annotated using Prokka v1.12. 32 Trimmed reads were mapped to D0 using BWA-MEM 33 with default settings. GATK Unified Genotyper 34 was used to call single-nucleotide polymorphisms (SNPs) and small insertion and deletions (indels) from high-quality reads and impact of non-synonymous variants was annotated using snpEff v4.1, 35 followed by further quality filtering with SnpSift. 36 Autolysis Selected D20 isolates with increased vancomycin MIC were subjected to Triton X-induced autolysi. 37 Briefly, overnight cultures were prepared in Brain Heart Infusion (BHI) broth (Oxoid) by inoculating 10µL of glycerol stock into 4mL BHI at 37°C, 200 rpm for 16-20 hours. Subcultures were prepared in 50mL BHI (1:40) and mid log-phase cultures (OD600 = 0.4-0.6) were pelleted (13,000 rpm, 15 mins, 4°C). Cells were washed twice with ice-cold sterile water before resuspension in freshly prepared 0.05 M Tris-HCl (pH 7.2) containing 0.05% (v/v) Triton X-100 (Sigma Chemical Co., St. Louis, Mo.) and incubated at 37 °C, 200 rpm. Absorbance was monitored every 30 min for 5 hours. Results are presented as percentage of OD600 decrease after 5 hours relative to the initial OD600. Controls include D0, MRSA VISA (NRS1; Mu50) ATCC 700699 and MSSA ATCC 29213. Bacterial fitness Relative bacterial fitness was determined by generating growth curves to obtain the average doubling time (DT) following a previous method, 38 with some modifications (Supplementary data). Allelic exchange To validate if mutations confer resistance, selected genes from vancomycin- and daptomycin D20 isolates were incorporated into WT MRSA ATCC 43300 via allelic exchange as previously described 39 (Supplementary data, Table S2). All WT and resulting mutant strains underwent antibiotic susceptibility testing as described above. Data availability Nucleotide sequences including genome assemblies (.fasta) and base-called (.fastq) data for both Illumina and ONT are deposited under NCBI BioProject: PRJNA986267 ( www.ncbi.nlm.nih.gov/bioproject/986267 ). RESULTS Acquisition and retention of in vitro resistance differed between antibiotic treatments The susceptibility profiles of D20 isolates varied greatly between vancomycin, daptomycin, and linezolid following resistance selection ( Figure 1a-c ). Few vancomycin isolates surpassed the clinical breakpoint ( Figure 1a ), whereas all of the daptomycin isolates reached the clinical breakpoint of 1 mg/L ( Figure 1b ). While vancomycin and linezolid isolates experienced less than four-fold increases in MIC after 20 days, daptomycin isolates acquired up to 16-fold increases ( Figure 1d ). Five days of passaging without antibiotics to discern resistance stability was conducted ( Figure 1a-c ). Over half of the vancomycin D20 resistant isolates regained susceptibility and all daptomycin isolates retained resistance. Whilst all linezolid D20 isolates were identified as susceptible, re-culturing glycerol stocks revealed three (LZD-2, LZD-3, LZD-4) exhibited resistance (8 mg/L) which was stable for the five antibiotic-free passages. Download figure Open in new tab Figure 1. ATCC 43300 acquisition and stability of resistance towards vancomycin, daptomycin, and linezolid. Average MIC values were plotted for (a) vancomycin (VAN)- (b) daptomycin (DAP)- and (c) linezolid (LZD)-treated isolates. Horizontal dotted line represents clinical breakpoints for respective antibiotics based on EUCAST v14.0. Vertical line at D21 includes re-cultured D20 glycerol stocks and subsequent passaging for 5 days with no antibiotics. D25 value indicates highest MIC detected for replicates (n=4). (d) Fold change in MIC values of day 20 isolates compared to day 0 (mean±SD; n=8). Statistical significance was determined by one-way ANOVA with Tukey’s multiple comparisons test ( p < 0.05 was considered as significant; ** p = 0.0080; *** p = 0.0003). Genomic alterations reflect pathways associated with the antibiotics’ target Vancomycin isolates exhibited chromosomal mutations in genes associated with cell wall synthesis and metabolism, such as walK, atl_3 and korB ( Table 1 ). Genes involved in DNA repair ( recX ), protein synthesis ( pheS ), and virulence regulation ( tlyC and rny ) were also affected. Different mutations occurred across the eight replicates, such as amino acid M246R change in recX gene shared by VAN-1 and VAN-7 ( Table 2 ), as well as a deletion in bifunctional autolysin-encoding atl_3 gene in VAN-5 and VAN-6. No non-synonymous variants were detected in VAN-8; however, resistance was only briefly present in the D20 re-culture and quickly reverted to susceptible ( Figure 1a ). The frequency these mutations appeared over the time course were monitored (Table S3). The majority of mutations appeared as early as day 5 and established well before D20. Interestingly, the mutations affecting the protein synthesis pathway ( rny and pheS ) appeared at a later time and subpopulations having no mutations still existed by D20. View this table: View inline View popup Table 1. Non-synonymous variants detected in D20 isolates and the resulting phenotype View this table: View inline View popup Download powerpoint Table 2. MIC of mutants generated by allelic exchange Daptomycin D20 isolates exhibited more mutations compared to vancomycin, and a greater diversity of pathways were affected ( Table 1 ). Genomic variants were found in genes having a role in cell wall synthesis ( ltaS and epsJ ), membrane phospholipid production ( mprF ), protein synthesis pathway ( ychF , rpoB , proS and rsmG ), as well as glucose ( lacC_2 ) and carbohydrate ( ptsI ) metabolism pathways. Similar to vancomycin, recX (M246R) was also detected in DAP-3 and DAP-4. All isolates became resistant to daptomycin (4-32 mg/L). Development of daptomycin-non-susceptibility (Daptomycin-NS) was likely brought about by an accumulation of mutations, half of which appeared after day 10 (Table S3). The appearance of certain mutations did correspond with increases in MIC. For example, the mprF mutation was initially detected at day 10 in the DAP-7 and the MIC increased significantly from day 10 onward ( Figure 1b , Table S3). Similarly, the rpoB mutation in the DAP-8 started to appear from D15 and by D20 its MIC increased by two-fold ( Figure 1b , Table S3). Variants detected in linezolid isolates were minimal and only impacted rplC (G155R) which affects the 50S subunit ribosomal protein L3. Only 3 isolates harboured this mutation and had a resistant phenotype (MIC: 8 mg/L) after re-culturing D20. This mutation appeared between D10-15 in these isolates (Table S3). Potential cross-resistance between vancomycin and daptomycin isolates Nearly all vancomycin D20 isolates exhibited reduced susceptibility to vancomycin, with the exception of VAN-7 ( Figure 2a,b ) (Table S4). All vancomycin isolates had up to four-fold increase in daptomycin MICs that resulted in daptomycin-NS phenotypes ( Figure 2c ), suggesting cross- resistance between vancomycin and daptomycin. Conversely, these D20 isolates exhibited a two-fold MIC decrease against linezolid, with all isolates remaining well below the breakpoint ( Figure 2d ). Download figure Open in new tab Figure 2. Cross resistance between D20 isolates. (a) Vancomycin D20 isolate fold change for all three antibiotics. MICs of vancomycin D20 isolates against (b) vancomycin, (c) daptomycin, and (d) linezolid. (e) Daptomycin D20 isolate fold change. MICs of daptomycin D20 isolates against (f) vancomycin, (g) daptomycin, and (h) linezolid. (i) Linezolid D20 isolate fold change for all three antibiotics. MICs of linezolid D20 isolates against (j) vancomycin, (k) daptomycin, and (l) linezolid. Fold change represented as average(n=8)±SEM and MICs performed for n ≥ 4. Dotted line indicates breakpoints (EUCAST) and all experiments used re-cultured -80°C D20 glycerol stocks. Daptomycin D20 isolates exhibited greater than ten-fold increases in MIC against daptomycin ( Figure 2e , g). Half of the isolates also had elevated vancomycin MICs over its breakpoint, while the other half exhibited less than two-fold MIC changes ( Figure 2e , f). However, the daptomycin D20 isolates remained susceptible to linezolid ( Figure 2e , h). Linezolid D20 isolates demonstrated a slight elevation in MIC against the three antibiotics tested, only by less than two-fold overall ( Figure 2i ). All D20 isolates remained susceptible to vancomycin ( Figure 2j ), while three out of eight isolates (LZD-2, LZD-3 and LZD-4) exhibited a daptomycin-NS phenotype, reaching a daptomycin MIC of 2 mg/L ( Figure 2k ). Although this result suggested potential cross-resistance between linezolid and daptomycin, the linezolid MIC increase was only within a two-fold dilution. The same three isolates also had elevated MICs against linezolid ( Figure 2l ). Variable bacterial fitness costs evident for differing antibiotic exposure Average doubling time (DT) for each D20 isolate was calculated to assess whether mutations had any impact on the relative bacterial fitness. Vancomycin D20 isolates had a large variability of DT within the biological replicates ( Figure 3a ) with no significant difference. Daptomycin D20 isolates were found to exhibit DTs longer than that of D0 isolate, though only DAP-2 was significantly different (DT = 69.6±6.1 mins, a 96% increase) ( Figure 3b , Table S5). Meanwhile, no significant variation in DTs were found in linezolid isolates ( Figure 3c , Table S5). Download figure Open in new tab Figure 3. Relative bacterial fitness of D20 isolates. Doubling time (in minutes) of vancomycin (a), daptomycin (b) and linezolid (c) D20 isolates were calculated to measure the relative fitness compared to the initial D0 isolate. Fitness determined using three biological replicates (mean±SD). Significant difference as measured by two-tailed Welch’s t-test ( p <0.05) between D20 versus D0 is shown with asterisks (** p = 0.0020). Differing degrees of autolysis were observed for vancomycin and daptomycin D20 isolates D20 isolates were selected based on resistance profile and detected mutations associated with autolysis pathways. The rate of Triton-X-induced autolysis was compared to D0, MSSA and a VISA Mu50 isolate known to exhibit reduced autolysis. VAN-1 and VAN-3 exhibited a slower rate of OD600 decrease compared to D0 with rates similar to the VISA Mu50 ( Figure 4a ). VAN-8 also had a slower rate of autolysis compared to D0 (50% OD600 decrease after 90 mins) but not as slow as the VISA Mu50 (50% OD600 decrease after 150 mins). In contrast, VAN-5 and VAN-6 had a slightly delayed rate of autolysis compared to D0, though not as slow as the VISA strain, having a 50% OD600 decrease between 60-90 mins. DAP-6 and DAP-7 exhibited similar trends in their resistance to autolysis, having similar rates of OD600 decrease to D0 ( Figure 4b ). Conversely, DAP-8 showed a higher resistance to autolysis compared to D0, exhibiting similar, if not higher, rate of OD600 decrease to the VISA Mu50. No linezolid isolates were tested for reduced autolysis due to the lack of mutations associated with autolytic activity. Download figure Open in new tab Figure 4. Triton-X-induced autolysis assay on selected vancomycin and daptomycin D20 isolates. Individual plotted percentage of optical density decrease for D20 isolates exhibiting reduced susceptibility. Isolates selected exhibited an elevated MIC as well as mutations in pathways associated with changes in autolysis. (a) Vancomycin isolates VAN-1, VAN-3, VAN-5, VAN-6 and VAN-8 (MIC 4 mg/L); (b) Daptomycin isolates DAP-6, DAP-7, and DAP-8 (MIC 16, 32, and 8 mg/L, respectively). Autolysis measured over five hours. Presented as the percentage decrease in optical density relative to initial D0 (mean±SD). Controls include VISA Mu50 (known tolerance to autolysis) and MSSA (sensitive to autolysis). Data was obtained from three independent experiments. Certain variants contribute to the development of resistance To ascertain whether variants contribute to resistance, we generated mutants of genes harbouring both known and novel mutations via allelic exchange. Four mutants were successfully generated: walK (Asp365Glu), mprF (Ser337Leu), rsmG (Ala80Ser), and ptsI (Arg476Cys) ( Table 2 ). Although rsmG and ptsI have not been reported to be associated with drug resistance in MRSA, rsmG (Ala80Ser) was the only change detected in DAP-6 (MIC: 16 mg/L) and present in DAP-7 (MIC: 32 mg/L) ( Table 1 ). The ptsI (Arg476Cys) variant was found in DAP-2 exhibiting severely reduced growth rate ( Figure 3 ). The generation of rpoB (Gly716Cys) and rplC (Gly155Arg) mutants were unsuccessful. As the linezolid mutation in rplC was known to cause resistance, this was excluded. The walK (Asp365Glu) mutant had a two-fold increase in vancomycin MIC, which is consistent to our observations in VAN-3 ( Table 2 ). The two-fold increase in daptomycin MIC suggested potential cross-resistance between vancomycin and daptomycin, despite it being less than observed in VAN-3 (four-fold increase in daptomycin MIC compared to D0) ( Table 2 ). Similarly, the mprF (Ser337Leu) mutant exhibited a 16-fold increase in daptomycin MIC and a two-fold increase in vancomycin MIC, suggesting cross-resistance and providing evidence of the role of mprF (Ser337Leu) in daptomycin- NS phenotype observed in DAP-6. rsmG (Ala80Ser) and ptsI (Arg476Cys) had a two-fold increase in daptomycin MIC compared to the parental MRSA, but had no change in their vancomycin MIC. This is different from the MIC determination of the D20 resistance selection isolates, where DAP-2 and DAP-6 had 8-/16-fold increase in daptomycin MIC compared to D0, respectively. The rsmG (Ala80Ser) mutation may partially contribute to daptomycin resistance in DAP-7, but further studies are required to unravel the 16-fold increase in DAP-6. Similarly, it is possible that mutations other than the ptsI (Arg476Cys) also contributed to the daptomycin-NS phenotype in DAP-2. DISCUSSION In vitro resistance selection assays provide key insights into the mechanisms bacteria can employ to develop resistance and can mimic genomic changes detected in a clinical setting. This was evident in our study which exposed MRSA to 20 days of vancomycin, daptomycin or linezolid. Subsequent phenotypes associated with pathways impacted such as fitness and autolysis correlated with clinical isolates. The WalKR two-component regulator, crucial for cell wall synthesis and metabolism, is strongly associated with vancomycin resistance. 40 , 41 Our study also confirmed (VAN-3, walK (Asp365Glu), MIC 4 mg/L) and validated this with allelic exchange. The Asp365Glu mutant has yet to be reported and impacts the PAS domain. This variant is within one residue of a lab-derived VISA strain harbouring a walK mutation (His364Arg) exhibiting decreased autolytic activity and longer doubling times. 42 Daptomycin clinical resistance can be associated with genes mprF and rpoB 43 – 48 and in vitro assays 20 , 22 , 49 , consistent with our findings. mprF plays a role in lysinylation of cell membrane phosphatidylglycerol, generating lysyl-PG and its translocation to the outer cell membrane. Mutations impacting the mprF gene result in a gain-in-function phenotype that includes increased cell membrane charge, leading to repulsion of the calcium-daptomycin complex. 50 Interestingly, this particular Ser337Leu mutation in DAP-7 has been reported in several studies associated with the Daptomycin- NS phenotype in clinical and laboratory-derived strains. 43 , 45 , 49 , 51 – 63 DAP-7 was found to have the highest increase in daptomycin MIC (32 mg/L), but remained susceptible to vancomycin (MIC: 2 mg/L) as well as a longer doubling time, similar to previous studies. 45 , 64 DAP-8 harboured the rpoB (Arg716Cys) variant and resulted in reduced susceptibility to both daptomycin (MIC: 8 mg/L) and vancomycin (MIC: 4 mg/L), suggesting cross-resistance. Although the exact mutation has not been reported, the concurrent reduced susceptibility to daptomycin and vancomycin has been reported in other rpoB perturbations. 44 , 65 rpoB mutations can exhibit a VISA phenotype, 66 which was evident in our study as DAP-8 had an autolysis trend similar to VISA Mu50. Mutations in rplC have been detected in clinical linezolid-resistant isolates 67 , 68 Linezolid selection yielded a G463C mutation in rplC encoding the 50S ribosomal protein L3. This exact amino acid change has previously been found in an in vitro assay using MSSA. 69 This mutation is located within the peptidyl transferase center (PTC) of the 50S ribosomal subunit, and based on structural studies, can interfere with a conserved part of the PTC and cause reduced binding affinity. 69 Resistance against linezolid has been largely attributed to mutations in the domain V of 23S rRNA, 12 , 70 but mutations in ribosomal protein L3 encoded by rplC (as well as ribosomal protein L4 encoded by rplD ), are also known to be associated with resistance. 70 Doubling times for all D20 isolates revealed DAP-2 exhibiting a severely impaired growth, in which an Arg476Cys mutation was identified in ptsI . ptsI is part of the phosphotransferase system (PTS), and mutations in the PTS system have been implicated in heightened daptomycin resistance in Enterococcus faecium . 71 Mutation in ptsI is also associated with fosfomycin resistance in E. coli that confers a fitness cost. 72 Further experimentation is needed to confirm whether this ptsI mutation is responsible for impaired fitness. Our allelic exchange assay revealed a two-fold increase in daptomycin MIC, suggesting a role in MRSA resistance. Cross-resistance between vancomycin and daptomycin have often been documented with genes, such as walK and mprF , which confer both VISA and daptomycin-NS phenotypes. 49 , 73 – 75 For example, mutations affecting walK have been shown to cause cross-resistance, 76 similar to our observations with VAN-3 with daptomycin MIC of 4 mg/L. This is consistent with reports on daptomycin-NS accompanied by reduced susceptibility to vancomycin in the clinic, 77 – 79 and daptomycin-NS phenotypes emerging from vancomycin treatment. 79 This study found that 50% of vancomycin D20 isolates became daptomycin-NS. Similarly, some of daptomycin D20 had elevated vancomycin MIC, as exemplified by DAP-6 harbouring mprF (Ser337Leu) causing a two-fold elevation in vancomycin MIC. The concurrent evolution of resistance to both vancomycin and daptomycin may be due to common pathway/s or mechanism/s. 80 All vancomycin D20 isolates became daptomycin-NS, but daptomycin isolates exhibited variable vancomycin susceptibility profiles. Hence, cross-resistance is likely dependent on the genes and their mutations. Notably, the DAP-7 S337L mprF mutation that remained vancomycin susceptible. Ruzin et al . demonstrated that mprF impairment could lead to increased vancomycin susceptibility. 81 Additionally, vancomycin reduced susceptibility could be independent to mprF alterations. 64 Yet, other mprF mutations can confer reduced susceptibility to both vancomycin and daptomycin. 73 Alterations in other genes such as rpoB could also yield a similar outcome. 65 Importantly, there could also be implications of the mprF -mediated cross-resistance, such as cross-resistance with lipoglycopeptide dalbavancin. 75 Exposure to sub-inhibitory cell-wall targeting antibiotic concentrations could lead to the development of a VISA phenotype, 82 which includes autolysis tolerance. The VAN-3 isolate showed reduced autolytic activity similar to a VISA Mu50 strain known to have increased autolysis resistance. 66 This is consistent with previous reports of mutations affecting the WalKR regulon resulting in a VISA phenotype, 6 typically characterized by thickened cell wall and reduced autolysis. 66 , 83 Suppression of the autolytic system could result from exposure to sub-inhibitory concentrations of cell wall inhibitors, likely to minimise damage to the cell wall. 84 No significant difference was observed in the VAN-3 isolate doubling time, as noted for other walK mutants. 66 This study has provided evidence that in vitro resistance selection emulated both the genomic and phenotypic changes acquired in the clinic. Although we have confirmed the role of certain genomic variants in contributing to resistance, further studies are needed to validate the role of novel mutations not previously reported, and the effects of multiple mutations in one isolate. Furthermore, this study has provided additional insight into cross-resistance between vancomycin and daptomycin mediated by certain mutations. Identifying variants at the genetic level can provide clues to the underlying mechanisms of these shifts in resistance profiles and provide information for alternative antibiotic treatment in the clinic. Additional experiments providing information on fitness, such as competitive growth assays, would be useful to generate more accurate predictions regarding the likelihood of that mutation being maintained within the population. 85 This study has demonstrated the feasibility of using in vitro resistance selection to predict pathways impacted and in turn, potentially forecast the viability of new antibiotics entering the clinic. FUNDING This work was supported by National Health and Medical Research Council (NHMRC) Project Grants (APP631632 and APP1026922), Wellcome Trust Seeding Drug Discovery Award 094977/Z/10/Z, and AID sequencing grant (2015). A. P. was an Australia Awards Scholarship scholar and was supported by APEC-Australia Women in Research Fellowship 2022. M.E.P. is supported by an AIMI Pathway Fellowship (UTS). TRANSPARENCY DECLARATIONS M. A. C. currently holds a fractional Professorial Research Fellow appointment at the University of Queensland with his remaining time as CEO of Inflazome Ltd, a company with headquarters in Dublin, Ireland that is developing drugs to address clinical unmet needs in inflammatory disease by targeting the inflammasome. All other authors: none to declare. AUTHOR CONTRIBUTIONS A.P., M.E.P., A.G.E., M.A.C., L.J.M.C. and M.A.T.B. conceived this study. S.R., and A.K. performed the resistance selection experiments. M.E.P. and D.G. performed the library preparation for WGS. A.P., M.E.P., S.R., A.K., D.G., A.E., and I.M. performed all other microbiological assays, including antibiotic susceptibility testing. A.P., M.E.P. and M.D.C. performed the sequencing analysis. A.P. and I.M. performed the allelic exchange. A.P. wrote the original draft. M.A.C., T.S., L.J.M.C. and M.A.T.B. provided supervision, project administration and funding acquisition. All authors reviewed the data, wrote and revised the manuscript, and approved the final version. ACKNOWLEDGEMENTS The authors would like to thank Dr Arnold Bainomugisa for his guidance on the variant detection pipeline and Ali Hinton for her help with optimising the resistance selection experiments. Footnotes ↵ # These authors contributed equally REFERENCES 1. ↵ WHO Bacterial Priority Pathogens List, 2024 : bacterial pathogens of public health importance to guide research, development and strategies to prevent and control antimicrobial resistance . 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