A frameshift mutation in the methyltransferase rlmN is associated with increased linezolid resistance in Mycobacterium tuberculosis

A frameshift mutation in the methyltransferase rlmN is associated with increased linezolid resistance in Mycobacterium tuberculosis | 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 A frameshift mutation in the methyltransferase rlmN is associated with increased linezolid resistance in Mycobacterium tuberculosis View ORCID Profile Bryn Marie Reimer , View ORCID Profile Anna G. Green doi: https://doi.org/10.1101/2025.11.20.689544 Bryn Marie Reimer 1 University of Massachusetts Amherst, Manning College of Information & Computer Sciences , 140 Governors Drive, Amherst, MA 01003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Bryn Marie Reimer For correspondence: breimer{at}umass.edu annagreen{at}umass.edu Anna G. Green 1 University of Massachusetts Amherst, Manning College of Information & Computer Sciences , 140 Governors Drive, Amherst, MA 01003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anna G. Green For correspondence: breimer{at}umass.edu annagreen{at}umass.edu Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Linezolid is a key component of treatment regimens for multidrug-resistant and extensively drug-resistant tuberculosis, which is caused by the pathogen Mycobacterium tuberculosis (MTB). Resistance to linezolid in MTB has traditionally been attributed to mutations in the 23S rRNA ( rrl ) and ribosomal protein L3 ( rplC ), but only a fraction of clinically observed linezolid resistance is explained by mutations in these two genes. We report that an analysis of strains with paired whole-genome sequencing and linezolid minimum inhibitory concentration (MIC) phenotyping from the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) reveals that a relatively common frameshift mutation in MTB methyltransferase rlmN (5.3% of assessed isolates) is significantly associated with increased linezolid MIC. In additional to statistical associations, we provide evolutionary evidence of homology to an established linezolid resistance mechanism in Staphylococcus aureus , and structural evidence that the frameshift mutation likely ablates rlmN methyltransferase functionality. Introduction Tuberculosis (TB) remains the world’s most deadly infectious disease, causing an estimated 1.25 million deaths in 2023 alone. 1 TB is caused by the bacillus Mycobacterium tuberculosis (MTB), which is uniquely difficult to treat with antimicrobial agents, due in part to its waxy mycolic acid coating. 2 Further complicating treatment is the high rate of drug-resistant infections: in 2023, an estimated 400,000 individuals developed multidrug-resistant or rifampicin-resistant TB, which requires treatment with second-line drugs. 1 Linezolid, a first-generation oxazolidinone, is a commonly used drug in multidrug- and extensively drug-resistant TB, 3 and resistance to linezolid is present in an estimated 4.2% of patients with multi-drug resistant TB. 4 The World Health Organization (WHO) maintains a catalogue of mutations known to cause resistance to antitubercular drugs, including linezolid, based on stringent statistical criteria applied to mutations in candidate genes. 5 While mutations in rrl , the 23S rRNA, and rplC , ribosomal protein L3, have been observed in linezolid-resistant strains of MTB, 6 , 7 it is unclear what proportion of resistance is explained by these mutations. Estimates vary, but between 20% and 54% of linezolid-resistant isolates appear to have wild-type rrl and rplC . 8 , 9 Because a large proportion of linezolid resistance cannot be easily tied to mutations in these two major candidate genes, it is reasonable to presume other genetic mechanisms of resistance may be present. In this work, we demonstrate that the presence of a frameshift mutation in the ribosomal methyltransferase rlmN is associated with increased quantitative linezolid resistance in MTB as measured by MIC (referred to as “linezolid resistance” hereafter). We analyze MTB isolates with paired genotype and phenotype data to show that the presence of this frameshift mutation is significantly predictive of linezolid resistance, explaining an additional 32.1% of resistant isolates compared to using only known resistance-associated mutations from the WHO. 5 Additionally, we contribute a brief analysis of RNA methyltransferases in MTB to justify our focus on rlmN , which is known to cause antibiotic resistance in the pathogen Staphylococcus aureus . 10 Finally, we contribute a structural analysis of rlmN that provides evidence that the observed frameshift mutation would have a deleterious effect. Results A protein similarity analysis uncovers MTB’s sole rlmN homolog Multiple previous studies have implicated RNA methyltransferase genes in linezolid resistance in other bacterial species. Prior work has proposed a role for the Staphylococcus aureus methyltransferase rlmN in creating the correct methylation state of the rRNA to facilitate linezolid binding. 10 In addition, the presence of the plasmid-borne RNA methyltransferase cfr in several species such as S. aureus and Escherichia coli has been associated with linezolid resistance. 11 The importance of these two methyltransferase genes in linezolid resistance indicates that the correct methylation state of the ribosomal RNA is critical for linezolid function. Therefore, we hypothesize that methyltransferases provide a promising reservoir of genes that may be implicated in linezolid resistance in MTB. The only prior catalogue of all MTB methyltransferases, published in 2016, does not capture some important members of the MTB RNA methyltransferases (see Discussion). 12 We therefore contribute a systematic catalogue of RNA methyltransferases with two goals: (1) to provide a candidate gene list for further exploration of drug targets in MTB and (2) to clarify the identity of rlmN in MTB, as there has been some confusion in the literature about the identity of rlmN in MTB; some have proposed that tsnR is its homolog in MTB. 13 Because a loss of function mutation in the S. aureus rlmN leads to increased linezolid resistance, 10 we hypothesized that if MTB has an rlmN homolog, its function may also affect linezolid’s activity. Thus, we proceeded to catalogue the RNA methyltransferases in MTB and to align the sequences of these methyltransferases with the S. aureus rlmN to find its homolog(s) in MTB. First, we performed a search for all annotated genes that are known or suspected RNA methyltransferases in MTB using a combination of UniProt 14 and several reference genome annotations (see Methods). 15 , 16 We identified 19 putative or confirmed RNA methyltransferases in MTB, representing 20 genes in the H37Rv reference genome (see Table 1 ). All 19 genes were found in UniProt, though not all were reviewed entries. The rlmN gene as annotated by UniProt is a fusion of Rv2879c and Rv2880c, which are annotated as separate, overlapping genes in the H37Rv reference genome. We confirmed with a BLAST 17 search that there were no additional homologs to S. aureus rlmN in the MTB genome (see Methods) that were not recovered by our prior searches through genome annotations. View this table: View inline View popup Table 1. A catalogue of known and suspected RNA methyltransferases in MTB. We aligned all putative and confirmed RNA methyltransferase protein sequences in MTB to the S. aureus rlmN protein sequence (UniProt ID: Q2FZ66) to find potential MTB homolog(s) (see Figure 1 ). Of all putative and confirmed RNA methyltransferases in MTB, the S. aureus rlmN is most similar by percent identity (32.73%) to the MTB rlmN , whereas it is only 9.43% identical to MTB tsnR . It is a common, if conservative, heuristic to assume homology between two proteins that have at least 30% sequence identity. 18 Applying this threshold, and noting that BLAST did not find any other potential hits for rlmN in the MTB genome, we can confirm that MTB rlmN is the sole MTB ortholog to S. aureus rlmN . We therefore assert that tsnR is not the MTB rlmN , nor is it a close homolog of the MTB or S. aureus rlmN , despite its similar putative methyltransferase activity, and despite the in vitro evidence of tsnR association with MTB linezolid resistance. 19 Download figure Open in new tab Figure 1: Each putative and confirmed MTB methyltransferase is shown with its associated percent identity to the S. aureus rlmN . Highlighted in dark blue are the MTB rlmN as well as tsnR , which prior literature suggests may be an rlmN homolog in MTB. Only the MTB rlmN passes the 30% homology threshold to be considered a true homolog. Genotypic analysis recovers known resistance mechanisms and reveals that an rlmN frameshift mutation is associated with linezolid resistance We evaluated the association between genomic variants and linezolid resistance by finding genomic variants in sequenced isolates and assessing their association with a change in the observed minimum inhibitory concentration (MIC) for linezolid. By assessing resistance association using MIC values rather than resistance breakpoints, we may be able to find low-level determinants of resistance. Using the BV-BRC as a resource, 20 we accessed isolates that had (1) lab-determined linezolid resistance phenotypes and (2) a whole-genome sequencing accession number. The genome assemblies associated with the accession numbers for the resulting 8454 MTB isolates were downloaded from AllTheBacteria, 21 where possible. After pre-processing to remove low-quality genome assemblies or isolates with missing data (see Methods), 7436 isolates remained for analysis. We used a candidate gene approach for our genotypic analysis, following approach used to generate a WHO-endorsed catalogue of MTB mutations and whether they cause antibiotic resistance (the “WHO mutation catalogue”). 5 When assessing genotypic variants associated with linezolid resistance, the WHO assess three genes: rrl , rplC , and tsnR , finding mutations significantly associated with resistance in only rplC and rrl ( rplC C154R; various in rrl , including G2270T). We include these three genes and add rlmN . We restricted our search to missense and nonsense mutations for proteins rplC , rlmN, and tsnR and to single nucleotide polymorphisms for the ribosomal genes rrl . Indels and frameshifts were included only if they were present in greater than 1% of resistant or sensitive isolates, to minimize possible erroneous mutation calls (see Methods). For each mutation found in these genes in our dataset, we used the Mann-Whitney U-test to test the null hypothesis that isolates with and without a given mutation are selected from populations with the same MIC distribution (see Methods). We find that six mutations are significantly associated with an increase in linezolid MIC in our dataset (see Table 2 ). No mutations in tsnR attained significant association with resistance in our dataset. Of the six significantly-associated mutations, rrl G2270T and rplC C154R are also associated with resistance in the WHO mutation catalogue, which uses binarized phenotypes based on the WHO linezolid breakpoint rather than correlations with an increase in MIC. 5 In addition to these two known variants, we also describe two other rrl variants (C344T, C637G) that are significantly associated with resistance in our dataset, but which did not meet criteria for association with resistance in the dataset used by the WHO. View this table: View inline View popup Download powerpoint Table 2: Observed mutations significantly associated with increased linezolid resistance The final two observed mutations that are associated with resistance in our dataset are both in rlmN . The first is an aspartic acid to asparagine missense mutation at amino acid position 244 in the rlmN gene (D244N). The second is a frameshift mutation starting at amino acid position 176. This frameshift mutation is relatively common in our dataset (394/7436, or approximately 5.3%). When examining raw MIC values, we find that the presence of this frameshift mutation in any isolate is significantly associated with a raw difference of 0.18 mg/L in MIC ( Table 2 ). If we binarize the phenotypes using the WHO breakpoint of 1.0 mg/L 22 (isolates with MIC > 1.0 mg/L are resistant), we observe that this mutation is more common in linezolid-resistant isolates (11/128, or approximately 8.6%) than in linezolid-susceptible isolates (383/7308, or approximately 5.2%). The rlmN D244N mutation appears to be significantly associated with resistance in our dataset, but further analysis shows that this mutation is only present on the background of the frameshift mutation. Because D244N mutation appears only downstream of the frameshift mutation at position 176, it is difficult to assess its importance in this dataset. D244N seems likely to be acting as a marker of the frameshift mutation being present. We also examined how many resistant isolates harbor the mutations that we identify as having significant associations with linezolid resistance (see Table 2 ). Of the 128 resistant isolates in our dataset (as calculated using the WHO breakpoint), only 28 (21.88%) were found to have at least one mutation from the WHO catalogue of resistance-associated mutations. When we added just the rlmN frameshift mutation to this analysis, 37 (28.91%) isolates harbored the frameshift mutation or at least one mutation from the WHO catalogue. Therefore, the frameshift mutation in rlmN provides increased explanatory power (32.1%) when assessing the known genetic causes of linezolid resistance, although our baseline ability to ascribe resistance to genetic loci is still limited. The frameshift mutation will likely cause loss of function of MTB rlmN To evaluate a possible mechanistic explanation for the observed association, we performed in silico protein structure analyses to assess the likely effect of the frameshift mutation on protein function. While there are no experimentally-derived protein structures available for either MTB RlmN or S. aureus RlmN, there are several X-ray structures available for E. coli RlmN. We aligned the MTB rlmN protein sequence with the E. coli rlmN protein sequence and found 37% sequence identity across the sequence match, supporting the homology of these two proteins (see Figure 2A ). We then generated a protein-ligand interaction fingerprint (PLIF; see Methods) to assess which amino acids were likely important for binding S -adenosyl methionine (SAM), the critical cofactor for RlmN protein methyltransferase activity (see Figure 2B ). The PLIF shows 5 residues with critical binding interactions with SAM, four of which are ablated when the frameshift mutation is present. Although the frameshift mutation only occurs about halfway through the protein, it clearly impacts important residues for cofactor binding and therefore activity (see Figure 2C ), leading us to hypothesize that the frameshift mutation will likely cause loss of function of the MTB RlmN. This loss of function, and consequent loss of rRNA methylation, may be the mechanism of the observed associated linezolid resistance, and it is consistent with the mechanism of resistance observed in S. aureus , where abolishment of RlmN activity leads to resistance due to a lack of A2503 methylation. 10 Download figure Open in new tab Figure 2. (A) This panel shows the BLAST alignment of the protein sequences for rlmN in both E. coli and MTB, with grey highlights showing the parts of the sequence that would be downstream of the frameshift mutation. Purple highlights indicate important residues in the protein-ligand interaction fingerprint (PLIF). (B) The PLIF, as calculated by the Cresset software (see Methods), is shown for E. coli RlmN (PDBID: 3RFA). The green and blue dotted lines indicate hydrogen bonds and weak hydrogen bonds, respectively. The purple lines indicate aromatic interactions. Amino acids are numbered by their index in E. coli . Image initially generated using Flare™ from Cresset®, then modified by the authors. (C) The E. coli RlmN protein structure is shown, with the area downstream of the frameshift in grey, the SAM co-factor in green, and residues important in the PLIF in purple. Discussion In this study we report the existence of a significant association between a frameshift mutation in an MTB methyltransferase, rlmN , and phenotypic resistance to linezolid as quantified by MIC. To support our addition of rlmN to a small list of candidate genes, we contribute a catalogue of all known and putative MTB RNA methyltransferases ( Table 1 ). We demonstrate the homology of MTB rlmN to S. aureus rlmN , dispelling prior suggestions that tsnR may be functioning as an rlmN homolog. Upon finding a significant association between a frameshift mutation in rlmN and an increase in linezolid MIC, we provide structural evidence for a hypothesized mechanism of resistance. Despite our survey of all known associated genetic loci for linezolid resistance, using our six reported significantly-associated mutations as well as all WHO-reported mutations that were also observed in our dataset, we were only able to assign a putative genetic cause of resistance to 37/128 (28.91%) of resistant isolates in our dataset. In contrast, Kadura et al report that, across eight studies with sequencing results for rrl and rplC , 85/106 (80.19%) of resistant isolates harbored at least one mutation in those genes. 9 If we were to use these same criteria and assess isolates with any mutation in rrl or rplC in our dataset, we would nonetheless only mechanistically explain 42/128 (32.81%) of resistant isolates in our dataset. Notably, in our study, 977/7308 (13.37%) of susceptible isolates still had at least one mutation in rrl or rplC , but that number drops to 396/7308 (5.42%) when only considering significantly-resistance-associated rrl or rplC mutations, further justifying our choice to restrict analysis to mutations that are significantly associated with resistance. Regardless, there is a substantial portion of linezolid-resistant MTB isolates where resistance cannot be ascribed to one of the known genetic loci, including our newly-discovered rlmN frameshift mutation. This phenomenon of unexplained resistance has also been noted in Mycobacteroides abscessus , a closely related mycobacterial species that also only harbors one copy of ribosomal DNA, 23 where it has been reported that only 8.2% of linezolid-resistant strains contained ribosomal mutations. 24 A recent review proposes that that mechanisms involving efflux pumps 24 and the fatty acyl-AMP ligase fadD32 25 may contribute to part of the remaining unexplained resistance. 13 Future work assessing the importance of mutations in the MTB homologues of these genes could aid in our understanding of currently-unexplained linezolid resistance. Additionally, while the present work focused on a single methyltransferase, rlmN , that has compelling evidence for conferring linezolid resistance in S. aureus , many other MTB RNA methyltransferases may also be involved in creating the correct methylation state for linezolid and other ribosome-targeted therapeutics. There has been growing interest in the plausibility of methyltransferases as drug targets for MTB, 26 in no small part due to the importance of MTB methyltransferases such as tlyA in capreomycin resistance 27 and gidB in streptomycin resistance. 28 We recommend that relevant ribosomal methyltransferase genes be added to candidate gene lists for assessing genotype-phenotype correlations in drug-resistant TB, especially for drugs which target the ribosome. However, we recognize that because the precise mechanism of action is only known for a few of these methyltransferases, picking a targeted candidate gene list based on the proclivity of a gene to methylate near a drug binding site remains difficult. It is plausible that other RNA modifications, such as formylation, acetylation, or sulfation may also be important for drug resistance. Knowledge of the precise RNA modifications required for drug activity can help shape structure-activity studies as we continue to develop ribosome-targeted drugs in the future. To this end, one of our contributions is a systematic catalogue of all known or putative MTB RNA methyltransferases. We note that a 2016 review of MTB methyltransferases by Grover et al . suggests the presence of only 16 RNA methyltransferases, in contrast to our 19 identified RNA methyltransferases. 12 Their list of methyltransferases with RNA-binding activity does not recognize the RNA binding potential of Rv1407, Rv2689c, Rv3919c, and Rv2966c, which our list does due to their homology to known methyltransferases in other species. Rv2966c, in particular, is now an experimentally-verified MTB rRNA methyltransferase. 29 Additionally, Grover et al consider Rv3024c a methyltransferase; however, more recent evidence from 2023 supports the role of Rv3024c as an enzyme that sulfurates (rather than methylates) tRNA isoacceptors. 30 In our study we include two methyltransferases as candidate genes for association with linezolid resistance: rlmN , our gene of interest, and tsnR , which is on the current candidate gene list for linezolid resistance in the WHO mutation catalogue. 5 Loss of function of tsnR has been observed in vivo to correlate to linezolid resistance. 19 Despite this observation in vitro , no observed tsnR mutations met our stringent thresholds for significant association with resistance. This result was also seen in the WHO mutation catalogue, which reports no tsnR mutations as being associated with resistance. The association of rlmN mutation with linezolid resistance in MTB has not been reported previously. While Li et al performed a genome-wide CRISPRi screen that covered 98% of the MTB genome, neither rlmN nor its two constituent annotated genes in the H37Rv reference genome (Rv2879c and Rv2880c) were targeted by their guide RNAs. 19 Further, the fact that the frameshift mutation appears to be present in the H37Rv reference genome obscures the presence of rlmN in MTB by causing difficulty with annotation software; the current Mycobrowser reference genome does not list rlmN and the putative methyltransferase function of the gene is not listed under either Rv2879c nor Rv2880c. 15 Recently, however, a comprehensive update to the H37Rv reference genome was released. 16 While the reference genome still contains the rlmN frameshift mutation, improved annotation software has now recognized the homology of the gene fragment to rlmN . We propose that the community consider adopting this updated 2022 H37Rv reference genome in preference to the 1998 H37Rv reference genome with annotations from 2011 that is currently in use. In conclusion, we report the novel association between a frameshift mutation in the methyltransferase rlmN and linezolid resistance in MTB, as measured by quantitative MIC. This statistical association is observed in a set of 7426 linezolid MIC phenotyped isolates. Further, we use protein structural studies to hypothesize a plausible causal mechanism of resistance from loss of function due to the ablation of the majority of the critical SAM cofactor binding sites. As a part of this study, we provide three other items of broad usefulness to the scientific community: one, a catalogue of all known MTB methyltransferases, to be used as candidate genes for future drug resistance work for ribosomally-targeted drugs; two, a proposal that rlmN be considered as a candidate gene in future WHO mutation catalogues; and three, an evidence-based recommendation for use of the new, 2022 H37Rv MTB reference genome which benefits from updated annotations. Our findings, which unveil a novel genetic mechanism underlying linezolid resistance in MTB, have future implications for improved resistance diagnostics and better-targeted therapeutic strategies. Online Methods Building a catalogue of confirmed and putative RNA methyltransferases in MTB To find all confirmed and putative methyltransferases in MTB, we combined several strategies. First, we searched the standard 2011 H37Rv annotation furnished by Mycobrowser 15 as well as a newly-released re-annotation of H37Rv 16 for “methyltransferase” and “RNA”. We noted all genes and pseudogenes that were found in this manner (see Supplemental Information), whether or not they were included in the final list, and if not, why. Additionally, we searched UniProt 14 for methyltransferases thought to have RNA binding ability. Because some methyltransferases have dual specificity for tRNA and rRNA, we searched for any RNA methyltransferase that was either in the methyltransferase class (Enzyme Commission (EC) number 2.1.1.*), 31 or that was annotated with the gene ontology (GO) term for RNA methyltransferase activity (GO: 0008173). 32 , 33 Specifically, we used the following search terms: Search 1: “ec:2.1.1.* H37Rv -H37Ra RNA”. We then looked for evidence of ribosomal methylation in the protein annotation. Search 2: “GO:0008173 H37Rv -H37Ra” Any protein that was found by these methods and that seemed likely to have RNA methyltransferase activity based on experimental evidence or homology was included in our catalogue. Confirmation that no additional rlmN homologs are present in MTB To show that we did not miss any potential rlmN homolog(s) in MTB, we performed a tblastn search with the S. aureus rlmN protein sequence (UniProt ID: Q2FZ66) against the H37Rv reference genome and confirmed that the known MTB rlmN was the only hit produced. Default BLAST parameters were used. 17 Protein similarity analysis of RNA methyltransferases in MTB Protein similarity analysis of the catalogue of confirmed and putative RNA methyltransferases in MTB (against the S. aureus rlmN ) was performed using T-Coffee and the EMBL-EBI job dispatcher with the default parameters. 34 , 35 Protein sequences were sourced from UniProt, using the accessions noted in the full text. 14 The percent identity matrix was calculated with T-Coffee, 34 and visualized using R version 4.4.2 and the pheatmap library. 36 , 37 Acquiring MTB isolate phenotype data from the BV-BRC Information on MTB isolates with lab-based linezolid phenotypes was accessed from the BV-BRC on 31 July 2025. 20 For analyses using binarized phenotypes, isolates were labeled resistant if their linezolid MIC was > 1.0 mg/L and sensitive otherwise, following the WHO recommended breakpoint. 22 For all isolates with a lab-based phenotype value for linezolid, their BioSample Accession values were also accessed from the BV-BRC (n=8454). Processing uniformly-assembled genomes from AllTheBacteria We used the BioSample Accession values from the BV-BRC 20 to query AllTheBacteria, 21 a resource supplying uniformly-assembled bacterial genomes. All genomes that were available were downloaded (n=8364). It was noted that a small number of genomes had unusual genome sizes (very large or almost empty) or otherwise poor assemblies. We proceeded to include for analysis only genomes with a size within 5% of the 4411532 bp size of the H37Rv reference genome (n=7775). We confirmed that genomes with aberrant sizes that were excluded were not enriched for resistant isolates (Before filtering: 1.71% resistance; after filtering, 1.79% resistance) We then used BLAST to find our 4 genes of interest in each genome assembly. 17 We used tblastn for the protein sequences ( rplC, tsnR, rlmN ) and blastn for the ribosomal DNA sequence ( rrl ). We only extracted the top hit for each search, with an E-value cutoff of 1e-10. After finding all sequences for each genome assembly, we only included for downstream analysis those isolates that had missense, nonsense, or frameshift/indel mutations (n=7436; 128 resistant, 7308 susceptible = 1.72% resistance), excluding those isolates with small, rare indels (present in <1% of either resistant or susceptible isolates). Again, the proportion of resistant isolates remained similar after filtering. For each mutation detected in each gene, its presence or absence was noted in each isolate. We were then able to calculate the two-sided Mann Whitney U-test statistic for each mutation’s association with MIC in order to test the null hypothesis that isolates with and without a given mutation are selected from populations with the same MIC distribution. Resultant p -values were corrected using the Bonferroni procedure. Only mutations significantly associated with an increase in quantitative resistance (MIC) were reported in Table 2 . Structural insights from E. coli RlmN Protein sequence similarity between rlmN in MTB (UniProt ID: P9WH15) and in E. coli (UniProt ID: P36979) was performed with BLAST, using default parameters. 17 The protein structure of RlmN was downloaded from the PDB (PDB ID: 3RFA). 39 – 41 The protein-ligand interaction fingerprint was generated using Flare™ from Cresset®, and then modified for clarity and color-complementarity. 42 Structural modelling was done in PyMOL version 3.1.3. 43 Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials Data supporting the conclusions of this article are available in the GitHub repository, https://github.com/BrynMarieR/rlmN_frameshift . Some data are also included within the article and its supplemental file. The other datasets mentioned in, but not created for, this study are available from their respective, publicly available repositories as mentioned in the main text. Competing interests The authors declare that they have no competing interests. Funding B.M.R. is supported by the Spaulding-Smith Fellowship at University of Massachusetts Amherst. Authors’ contributions B.M.R conceived and designed the study; acquired, analyzed, and interpreted the data; and drafted the manuscript. A.G.G. made substantial contributions to the conception and design of the study, aided in data interpretation, and contributed to the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors would like to acknowledge valuable discussions had with Professors Maha R. Farhat and M. Sloan Siegrist. The authors also thank members of the UMass SAGE lab for useful input. This work utilized resources from Unity, a collaborative, multi-institutional high-performance computing cluster managed by UMass Amherst Research Computing and Data. Funder Information Declared University of Massachusetts Amherst Spaulding-Smith Fellowship Footnotes https://github.com/BrynMarieR/rlmN_frameshift References 1. ↵ WHO Global tuberculosis report 2024. ( 2024 ). 2. ↵ Jarlier , V. & Nikaido , H . Mycobacterial cell wall: Structure and role in natural resistance to antibiotics . FEMS Microbiol. Lett . 123 , 11 – 18 ( 1994 ). OpenUrl CrossRef PubMed Web of Science 3. ↵ Hashemian , S. M. R. , Farhadi , T. & Ganjparvar , M . Linezolid: a review of its properties, function, and use in critical care . Drug Des. Devel. Ther . 12 , 1759 – 1767 ( 2018 ). OpenUrl CrossRef PubMed 4. ↵ Azimi , T. et al. Linezolid resistance in multidrug-resistant mycobacterium tuberculosis: A systematic review and meta-analysis . Front. Pharmacol . 13 , 955050 ( 2022 ). OpenUrl PubMed 5. ↵ Walker , T. M. et al. The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: A genotypic analysis . Lancet Microbe 3 , e265 – e273 ( 2022 ). OpenUrl 6. ↵ Long , K. S. & Vester , B . Resistance to linezolid caused by modifications at its binding site on the ribosome . Antimicrob. Agents Chemother . 56 , 603 – 612 ( 2012 ). OpenUrl Abstract / FREE Full Text 7. ↵ Beckert , P. et al. rplC T460C identified as a dominant mutation in linezolid-resistant Mycobacterium tuberculosis strains . Antimicrob. Agents Chemother . 56 , 2743 – 2745 ( 2012 ). OpenUrl Abstract / FREE Full Text 8. ↵ Zong , Z. et al. Comparison of In Vitro Activity and MIC Distributions between the Novel Oxazolidinone Delpazolid and Linezolid against Multidrug-Resistant and Extensively Drug-Resistant Mycobacterium tuberculosis in China . Antimicrob. Agents Chemother. 62 , e00165 – 18 ( 2018 ). OpenUrl PubMed 9. ↵ Kadura , S. et al. Systematic review of mutations associated with resistance to the new and repurposed Mycobacterium tuberculosis drugs bedaquiline, clofazimine, linezolid, delamanid and pretomanid . J. Antimicrob. Chemother . 75 , 2031 – 2043 ( 2020 ). OpenUrl CrossRef PubMed 10. ↵ LaMarre , J. M. , Howden , B. P. & Mankin , A. S . Inactivation of the indigenous methyltransferase RlmN in Staphylococcus aureus increases linezolid resistance . Antimicrob. Agents Chemother . 55 , 2989 – 2991 ( 2011 ). OpenUrl Abstract / FREE Full Text 11. ↵ Long , K. S. , Poehlsgaard , J. , Kehrenberg , C. , Schwarz , S. & Vester , B . The Cfr rRNA methyltransferase confers resistance to Phenicols, Lincosamides, Oxazolidinones, Pleuromutilins, and Streptogramin A antibiotics . Antimicrob. Agents Chemother . 50 , 2500 – 2505 ( 2006 ). OpenUrl Abstract / FREE Full Text 12. ↵ Grover , S. et al. Analyses of methyltransferases across the pathogenicity spectrum of different mycobacterial species point to an extremophile connection . Mol. Biosyst . 12 , 1615 – 1625 ( 2016 ). OpenUrl PubMed 13. ↵ Gan , W. C. , Ng , H. F. & Ngeow , Y. F . Mechanisms of Linezolid Resistance in Mycobacteria . Pharm. Basel Switz . 16 , 784 ( 2023 ). OpenUrl 14. ↵ The UniProt Consortium et al. UniProt: the Universal Protein Knowledgebase in 2025 . Nucleic Acids Res . 53 , D609 – D617 ( 2025 ). OpenUrl CrossRef PubMed 15. ↵ Kapopoulou , A. , Lew , J. M. & Cole , S. T . The MycoBrowser portal: a comprehensive and manually annotated resource for mycobacterial genomes . Tuberc. Edinb. Scotl . 91 , 8 – 13 ( 2011 ). OpenUrl 16. ↵ Chitale , P. et al. A comprehensive update to the Mycobacterium tuberculosis H37Rv reference genome . Nat. Commun . 13 , 7068 ( 2022 ). OpenUrl CrossRef PubMed 17. ↵ Camacho , C. et al. BLAST+: architecture and applications . BMC Bioinformatics 10 , 421 ( 2009 ). OpenUrl CrossRef PubMed 18. ↵ Pearson , W. R . An introduction to sequence similarity (‘homology’) searching . Curr. Protoc. Bioinforma. Chapter 3, 3.1.1-3.1.8 ( 2013 ). 19. ↵ Li , S. et al. CRISPRi chemical genetics and comparative genomics identify genes mediating drug potency in Mycobacterium tuberculosis . Nat. Microbiol . 7 , 766 – 779 ( 2022 ). OpenUrl PubMed 20. ↵ Olson , R. D. et al. Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR . Nucleic Acids Res . 51 , D678 – D689 ( 2023 ). OpenUrl CrossRef PubMed 21. ↵ Hunt , M. et al. AllTheBacteria – all bacterial genomes assembled, available, and searchable . Preprint at doi: 10.1101/2024.03.08.584059 ( 2024 ). OpenUrl Abstract / FREE Full Text 22. ↵ WHO . Technical Report on critical concentrations for drug susceptibility testing of medicines used in the treatment of drug-resistant tuberculosis. ( 2018 ). 23. ↵ Ripoll , F. et al. Non Mycobacterial Virulence Genes in the Genome of the Emerging Pathogen Mycobacterium abscessus . PLoS ONE 4 , e5660 ( 2009 ). OpenUrl CrossRef PubMed 24. ↵ Ye , M. et al. Molecular Analysis of Linezolid-Resistant Clinical Isolates of Mycobacterium abscessus . Antimicrob. Agents Chemother . 63 , e01842 – 18 ( 2019 ). OpenUrl PubMed 25. ↵ Ng , H. F. & Ngeow , Y. F . Mutations in Genes Encoding 23S rRNA and FadD32 May be Associated with Linezolid Resistance in Mycobacteroides abscessus . Microb. Drug Resist. Larchmt. N 29 , 41 – 46 ( 2023 ). OpenUrl 26. ↵ Salaikumaran , M. R. , Badiger , V. P. & Burra , V. L. S. P . 16S rRNA Methyltransferases as Novel Drug Targets Against Tuberculosis . Protein J . 41 , 97 – 130 ( 2022 ). OpenUrl PubMed 27. ↵ Maus , C. E. , Plikaytis , B. B. & Shinnick , T. M . Mutation of tlyA confers capreomycin resistance in Mycobacterium tuberculosis . Antimicrob. Agents Chemother . 49 , 571 – 577 ( 2005 ). OpenUrl Abstract / FREE Full Text 28. ↵ Wong , S. Y. et al. Mutations in gidB confer low-level streptomycin resistance in Mycobacterium tuberculosis . Antimicrob. Agents Chemother . 55 , 2515 – 2522 ( 2011 ). OpenUrl Abstract / FREE Full Text 29. ↵ Kumar , A. , Saigal , K. , Malhotra , K. , Sinha , K. M. & Taneja , B . Structural and functional characterization of Rv2966c protein reveals an RsmD-like methyltransferase from Mycobacterium tuberculosis and the role of its N-terminal domain in target recognition . J. Biol. Chem . 286 , 19652 – 19661 ( 2011 ). OpenUrl Abstract / FREE Full Text 30. ↵ Tomasi , F. G. , Kimura , S. , Rubin , E. J. & Waldor , M. K . A tRNA modification in Mycobacterium tuberculosis facilitates optimal intracellular growth . eLife 12 , RP87146 ( 2023 ). OpenUrl PubMed 31. ↵ Webb , E. C . Enzyme Nomenclature 1992: Recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the Nomenclature and Classification of Enzymes. (Published for the International Union of Biochemistry and Molecular Biology by Academic Press , San Diego , 1992 ). 32. ↵ Ashburner , M. et al. Gene Ontology: tool for the unification of biology . Nat. Genet . 25 , 25 – 29 ( 2000 ). OpenUrl CrossRef PubMed Web of Science 33. ↵ The Gene Ontology Consortium et al. The Gene Ontology knowledgebase in 2023 . GENETICS 224 , iyad031 ( 2023 ). OpenUrl CrossRef PubMed 34. ↵ Notredame , C. , Higgins , D. G. & Heringa , J . T-Coffee: A novel method for fast and accurate multiple sequence alignment . J. Mol. Biol . 302 , 205 – 217 ( 2000 ). OpenUrl CrossRef PubMed Web of Science 35. ↵ Madeira , F. et al. The EMBL-EBI Job Dispatcher sequence analysis tools framework in 2024 . Nucleic Acids Res . 52 , W521 – W525 ( 2024 ). OpenUrl CrossRef PubMed 36. ↵ R Core Team . R: A Language and Environment for Statistical Computing . R Foundation for Statistical Computing ( 2024 ). 37. ↵ Kolde , R . pheatmap: Pretty Heatmaps. ( 2019 ). 38. Virtanen , P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python . Nat. Methods 17 , 261 – 272 ( 2020 ). OpenUrl CrossRef PubMed 39. ↵ Boal , A. K. et al. Structural Basis for Methyl Transfer by a Radical SAM Enzyme . Science 332 , 1089 – 1092 ( 2011 ). OpenUrl Abstract / FREE Full Text 40. Boal , A. K. et al. X-ray structure of RlmN from Escherichia coli in complex with S-adenosylmethionine: 3rfa . doi: 10.2210/pdb3rfa/pdb ( 2011 ). OpenUrl CrossRef 41. ↵ Berman , H. M . The Protein Data Bank . Nucleic Acids Res . 28 , 235 – 242 ( 2000 ). OpenUrl CrossRef PubMed Web of Science 42. ↵ Bauer , M. R. & Mackey , M. D . Electrostatic Complementarity as a Fast and Effective Tool to Optimize Binding and Selectivity of Protein–Ligand Complexes . J. Med. Chem . 62 , 3036 – 3050 ( 2019 ). OpenUrl CrossRef PubMed 43. ↵ The PyMOL Molecular Graphics System . PyMOL. Schrodinger, LLC. View the discussion thread. Back to top Previous Next Posted November 20, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following A frameshift mutation in the methyltransferase rlmN is associated with increased linezolid resistance in Mycobacterium tuberculosis Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share A frameshift mutation in the methyltransferase rlmN is associated with increased linezolid resistance in Mycobacterium tuberculosis Bryn Marie Reimer , Anna G. Green bioRxiv 2025.11.20.689544; doi: https://doi.org/10.1101/2025.11.20.689544 Share This Article: Copy Citation Tools A frameshift mutation in the methyltransferase rlmN is associated with increased linezolid resistance in Mycobacterium tuberculosis Bryn Marie Reimer , Anna G. Green bioRxiv 2025.11.20.689544; doi: https://doi.org/10.1101/2025.11.20.689544 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Bioinformatics Subject Areas All Articles Animal Behavior and Cognition (7618) Biochemistry (17633) Bioengineering (13856) Bioinformatics (41841) Biophysics (21399) Cancer Biology (18529) Cell Biology (25422) Clinical Trials (138) Developmental Biology (13352) Ecology (19860) Epidemiology (2067) Evolutionary Biology (24282) Genetics (15582) Genomics (22462) Immunology (17700) Microbiology (40295) Molecular Biology (17140) Neuroscience (88419) Paleontology (666) Pathology (2823) Pharmacology and Toxicology (4813) Physiology (7632) Plant Biology (15107) Scientific Communication and Education (2042) Synthetic Biology (4284) Systems Biology (9808) Zoology (2267)