Phase-Specific Antibiotic Resistance Mechanisms in anEscherichia coliB Strain

Phase-Specific Antibiotic Resistance Mechanisms in an Escherichia coli B Strain | 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 Phase-Specific Antibiotic Resistance Mechanisms in an Escherichia coli B Strain Manuel Terrazas-López , Vanessa Aitken , Tonya N. Zeczycki , Eda Koculi doi: https://doi.org/10.1101/2025.06.30.662419 Manuel Terrazas-López 1 Department of Chemistry and Biochemistry, The University of Texas at El Paso , El Paso, TX 79968, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Vanessa Aitken 1 Department of Chemistry and Biochemistry, The University of Texas at El Paso , El Paso, TX 79968, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tonya N. Zeczycki 2 Department of Biochemistry and Molecular Biology, The Brody School of Medicine at East Carolina University , Greenville, NC 27858, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: zeczyckit{at}ecu.edu ekoculi{at}utep.edu Eda Koculi 1 Department of Chemistry and Biochemistry, The University of Texas at El Paso , El Paso, TX 79968, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: zeczyckit{at}ecu.edu ekoculi{at}utep.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract The majority of antibiotics developed to date target the fast-growing phase of bacteria, which typically occurs during active infection and resembles the exponential growth phase of laboratory-grown cultures. However, many pathogenic bacteria in the human body occupy environments where nutrients are limited and persist in a low-metabolic state, mirroring the stationary phase observed in laboratory-grown cultures. Bacteria in this latter phase are generally more resistant to antibiotics and are often responsible for recurrent infections. A comprehensive understanding of metabolic processes in both the exponential and stationary phases of bacterial growth could facilitate the development of phase-specific antibiotics. In this study, we adopted an untargeted proteomics approach to establish similarities and differences in the exponential and stationary phase proteome landscapes in BLR (DE3) cells, an Escherichia coli B strain. Our findings are consistent with previous studies, which show that metabolic processes such as translation and ribosome biogenesis decrease during the stationary phase compared to the fast-growing exponential phase, whereas tricarboxylic acid cycle activity increases. Importantly, our data reveal that distinct antibiotic resistance pathways are activated during the exponential and stationary phases, underscoring the potential for developing phase-specific antibiotic therapies. Introduction Pathogenic Escherichia coli ( E. coli ) infections cause about 950,000 deaths worldwide each year 1 . In addition, various nonpathogenic E. coli strains are important components of the human gut microbiome, while others are used in laboratories as model systems to investigate bacterial metabolic pathways, discover and produce novel antimicrobials, and serve as factories for protein production 2 – 5 . Identifying the distinct molecular pathways activated under various stress conditions in different strains of nonpathogenic E. coli could improve our understanding of the microbiome, enhance our ability to use E. coli for protein and antimicrobial production, and guide the design of novel and much-needed antibiotics against pathogenic E. coli and bacterial infections more generally. To elucidate the proteomic differences underlying bacterial growth phases, we compared the relative protein abundances between the exponential and stationary phases of the nonpathogenic E. coli B strain BLR (DE3) using liquid chromatography–tandem mass spectrometry (LC-MS/MS) and a label-free, untargeted proteomics approach. Our data on the E. coli B strain BLR (DE3) reveal that distinct antibiotic resistance pathways are activated during the exponential and stationary phases. This finding is significant, as traditional antibiotics are primarily designed to target fast-growing bacterial cells, which resemble the exponential phase of laboratory-grown cultures and dominate during active infections 6 . However, during chronic infections, bacterial cells often enter the stationary phase, during which their metabolic activity slows and differs markedly from that in active infections 6 , 7 . There is a notable lack of antibiotics effective against bacteria in the stationary phase of growth 6 . Ideally, novel antibiotics should either target both phases of bacterial growth or be tailored to specific stages of infection. This approach would help avoid administering antibiotics when they are least effective and thereby reduce the risk of developing antibiotic-resistant bacteria. The identification of distinct antibiotic resistance pathways activated during the exponential and stationary phases of E. coli BLR (DE3) could inform the design of phase-specific antibiotics for pathogenic E. coli and other bacterial species more broadly. The proteomic changes between the exponential and stationary phases of the E. coli B strain, REL606, have been previously investigated. In that study, two-dimensional (2D) electrophoresis coupled with quadrupole time-of-flight (Q-ToF) MS was used to provide insights into the proteome of the E. coli REL606 strain in the exponential and stationary phases. However, due to the lower protein separation capacity of 2D electrophoresis compared to an offline reversed-phase fractionation system, only about 16% of the proteome could be inferred 8 . In contrast, we implemented a high-resolution, label-free LC-MS/MS workflow using offline reversed-phase fractionation and Orbitrap-based detection to achieve substantially deeper proteome coverage. This approach enabled the confident identification and quantification of low-abundance regulatory proteins and metabolic enzymes not captured in earlier datasets, allowing us to identify approximately 43% of the proteome 8 . This significantly enhanced depth of analysis revealed distinct profiles in antibiotic resistance, metabolic regulation, and translational control that predominate in each phase and were not detected in the previous study 8 . Materials and Methods Materials E. coli BLR (DE3) cells, which are a recA - derivative of BL21 cells, were purchased from Novagen. The iST-Preparation and iST-Fractionation kits used for peptide generation and offline fractionation were purchased from PreOmics. All chemicals and reagents were purchased in the highest grade possible and used without further purification. Nondiet P-40 (NP-40) was originally purchased from Sigma Aldrich. (Note: IGEPAL CA-630 (Sigma--Aldrich) can be used as a direct replacement for NP-40). All remaining chemicals and reagents were obtained from Fisher Bioreagents. Methods Sample preparation Five colonies of E. coli BLR (DE3) ( n = 5 biological replicates ) were separately cultured in 50 mL Luria-Bertani (LB) broth overnight at 37 °C with continuous shaking at 225 revolutions per minute (rpm). Subsequently, the cultures were scaled up to 200 mL and adjusted to an initial optical density at 600 nm (OD 600 ) of 0.03. The cultures were then incubated under the same growth conditions in the same medium for 3 hours, reaching an OD 600 of approximately 0.3, and for 22 hours, reaching an OD 600 of approximately 5. The cells were pelleted by centrifugation at 4 °C at 5000 x g for 15 minutes. The resulting cell pellets were flash-frozen in liquid nitrogen prior to peptide isolation. LC-MS/MS for Label-Free Proteomics Peptide isolation Low protein binding microcentrifuge tubes (Eppendorf Protein LoBind Tubes) were used for peptide isolation and purification steps. Biological replicates (n=5) for each growth condition were initially resuspended in bacterial lysis buffer (500 µL, 50 mM Tris, pH 7.5, 150 mM NaCl, and 0.1% NP-40). It should be noted that IGEPAL CA-630 (Sigma Aldrich) can be directly substituted for NP-40. HALT Protease Inhibitor Cocktail (1X final concentration) was added to the lysis buffer immediately before use. The cells were disrupted via sonication on ice (10 sec burst, 30% amplitude, total of 1 min sonication). After sonication, proteins in the cell lysate were subsequently precipitated using ice-cold methanol (3:1 v/v) at −20° C overnight and pelleted by centrifugation (5000 x g, 10 min). The precipitated protein pellets were washed with ice cold methanol (500 µL, x 2) and allowed to air dry before further use. PreOmics iST and iST-Fractionation Add-on Kits were used according to the provided instructions to prepare mass spectrometry grade peptides. Briefly, the precipitated proteins were resuspended in the provided denaturation/alkylation buffer (150 µL) and heated at 95 °C for 10 min. After cooling to room temperature, freshly prepared digestion solution (50 µL) was added to each sample. Samples were incubated at 37 °C for 2 hours to ensure complete digestion before adding the provided stop solution (100 µL). Samples were cooled to room temperature prior to transferring to the provided solid phase extraction columns. After 2 min of centrifugation (room temperature, 500 x g), the cartridges were washed with wash 1 and 2 solutions (200 µL each, 2 min centrifugation, 500 x g) to remove hydrophobic and hydrophilic contaminations. For reverse-phase, pH-dependent fractionation, peptides were eluted from the cartridges using elution buffers 1-3 (150 µL, 2 min centrifugation, room temperature, 500 x g). Each elution was collected in separate low protein binding tube and dried under a stream of N 2 to dryness. Purified, alkylated peptides were reconstituted in 30 µL of loading buffer (98:2, v/v water/acetonitrile with 0.1% formic acid). Peptide concentrations in each sample were determined fluorometrically (Pierce Quantitative Peptide Assay) and adjusted to 0.25 mg/mL with loading buffer. nLC-MS/MS for label-free proteomics Peptides were analyzed were subjected to nano–liquid chromatography–mass spectrometry (nanoLC-MS/MS) analysis using an UltiMate 3000 RSLCnano system (Thermo Fisher Scientific) coupled to a Q Exactive Plus Hybrid Quadrupole-Orbitrap mass spectrometer (Thermo Fisher Scientific) via a nanoelectrospray ionization source. For each fraction, 1 μg (4 µL) of sample was first trapped on an Acclaim PepMap 100 (20 mm x 0.075 mm) trapping column (Thermo Fisher Scientific) at 98:2 v/v water/acetonitrile with 0.1% formic acid (5 µL/min, 6 min trapping). Analytical separation was performed over 120 min with an effective linear gradient of 4-35% acetonitrile plus 0.1% formic acid (300 nL/min) using an EASY-Spray PepMap RSLC C18 column (75 μm x2 50 mm Thermo Fisher Scientific) with a column temperature of 50 °C. MS1 was performed at 70,000 resolution, with an automatic gain control (AGC) target of 1 × 10 5 ions and a maximum injection time (IT) of 100 ms. MS2 spectra were collected by data-dependent acquisition on the top 20 most abundant precursor ions with a charge > 1 per MS1 scan. Precursor ion isolation window was 1.5 mass/charge ratio (m/z), dynamic exclusion was 20 s, and the normalized collision energy was 32. MS2 scans were performed at 17,500 resolution, maximum IT of 60 ms, and AGC target of 5 × 10 4 ions. Database searching and analysis FragPipe (v 19.1) was used to for raw data analysis with default search parameters for LFQ-MBR workflows 9 . Fractions for each biological sample were searched together as a single experiment. An initial open search against the canonical Uniprot E. coli BLR(DE3) reference proteome (UP000475070, accessed 6/2024) was used to identify potential post-translational modifications for inclusion in the LFQ-MBR workflow 10 . Precursor m/z tolerance was set to −150 to 500 Da and fragment tolerance was ±20 ppm with 3 missed cleavages for Trp and Lys-C allowed. Peptide spectrum matches (PSMs) were validated using PeptideProphet and results were filtered at the ion, peptide, and protein level with a 1% false discovery rate (FDR). Based on these initial searches, the following variable modifications were included in the LFQ-MBR analysis: oxidation (+15.5995 Da on Met), deamidation (+0.98401 Da on Gln and Asn), and fixed modification carbamodiomethyl (+57.025 Da on Cys). For LFQ-MBR analysis, data were search again searched against the canonical Uniprot E. coli BLR(DE3) reference proteome (UP000475070, accessed 6/2024). Precursor ion m/z tolerance was ±20 ppm with 3 missed cleavages for Trypsin/LysC allowed. The search results were filtered by a 1% FDR at the ion, peptide, and protein-level. PSMs were validated using Percolator and label free quantification was carried out using IonQuant Match between runs FDR rate at the ion level was set to 10% for the top 300 runs. Proteins with >95% probability of ID, >2 unique peptides, and in more than 80% of a sample group (i.e. 4/5 injections) were considered high confidence IDs and retained for analysis. Intensities were log 2 transformed, quantile normalized within the entire sample run and relative abundances for low sampling proteins were determined via knn methods (15 neighbors) in Perseus 11 . Thresholds and biological process identification GO enrichment analysis (statistical overrepresentation test) using Panther GO was used to identify over- and under-represented GO terms. A log 2 fold change threshold of ± 0.585 (fold changes of 1.5 and 1/1.5) in protein abundances during the exponential and stationary growth phases was used to identify biologically significant differences in protein abundances and was included in the GO enrichment analysis 12 , 13 . Fisher’s exact test ( p < 0.05) was used to establish statistically significant over-or under-representation. Protein–protein interactions and additional biological processes, molecular functions, and cellular locations of proteins were identified using STRING analysis with E. coli K-12 as the reference organism 14 . A subset of protein functions was further investigated using UniProt and EcoCyc 15 , 16 . Results and Discussion 493 proteins showed altered abundance between the exponential and stationary phases of E. coli BLR (DE3), while 1,326 proteins remained unchanged From approximately 4,200 predicted protein-coding genes in E. coli , we identified 1,819 proteins with high confidence ( Figure 1 ) 8 . By comparison, only 651 proteins were identified in the E. coli B strain REL606 study 8 . Our findings therefore provide novel insights into alterations in metabolic pathways and cellular processes between the exponential and stationary growth phases—insights that were not attainable in the previous study due to the limited number of detected proteins 8 . Download figure Open in new tab Figure 1. Differential protein abundance in BLR (DE3) E. coli cells across growth phases. Of the 1,819 proteins identified, 230 exhibited increased abundance in the exponential phase, while 263 exhibited increased abundance in the stationary phase. The remaining 1,326 proteins displayed no significant change in abundance between the two phases. In the present study, 230 proteins exhibited biologically and statistically significant increases in abundance during the exponential phase compared to the stationary phase, while 263 showed significant decreases ( Figure 1 ). Protein levels associated with translation, ribosome biogenesis, and gene expression rose during exponential growth to support rapid cell division ( Figure 2 , Table S1). Conversely, in the nutrient-limited stationary phase, proteins involved in the tricarboxylic acid (TCA) cycle—which enables energy production from alternative carbon sources and provides biosynthetic precursors—were more abundant (Table S2) 17 – 19 . Likewise, enzymes involved in small-molecule synthesis that feed into the TCA cycle also increased relative to the exponential phase (Table S2). Download figure Open in new tab Figure 2. Growth phase-dependent regulation of translation, ribosome biogenesis and antibiotic resistance. Proteins associated with ribosome biogenesis and translation are reduced during the stationary phase, while distinct proteins linked to antibiotic resistance are elevated in both phases. Fold change was calculated as the ratio of protein abundance in the exponential phase to that in the stationary phase. Dotted lines indicate thresholds for biological and statistically significance: a p-value of 0.05 and log₂ (fold change) of ± 0.585. Legend: Proteins involved in antibiotic resistance are shown in red, ribosome biogenesis in blue, and translation in orange. Ribosomal maturation factors DeaD, DbpA, RlhE, and RimP are more abundant during the exponential phase than during the stationary phase The ribosome (70S) in E. coli consists of the small (30S) and large (50S) subunits. The small subunit possesses one ribosomal RNA (rRNA) molecule, 16S, and 21 ribosomal proteins, while the large subunit possesses two rRNA molecules, 5S and 23S, and 33 ribosomal proteins 20 . In bacteria, dozens of proteins transiently interact with ribosomal intermediates and facilitate their maturation 21 – 23 . One class of maturation factors that facilitates ribosome assembly in most known organisms is the DEAD-box RNA helicases 24 – 28 . In E. coli , there are five DEAD-box RNA helicases—DeaD, DbpA, RlhB, RlhE, and SrmB—of which four (DeaD, DbpA, RlhE, and SrmB) are involved in large subunit ribosome assembly; DeaD is also implicated in small subunit assembly 29 – 33 . Our data reveal that during the exponential growth phase, the abundance of the DEAD-box RNA helicases DeaD, DbpA, and RlhE increases relative to the stationary phase ( Figure 3A ). Download figure Open in new tab Figure 3. Ribosomal proteins from both the small and large subunits, DEAD-box RNA helicases, and proteins involved in translation modulation are elevated during the exponential phase relative to the stationary phase. A) Ribosomal proteins, DEAD-box RNA helicases, and enzymes involved in rRNA and tRNA modification are elevated during the exponential phase relative to the stationary phase. B) Proteins involved in translation initiation and elongation, along with arginyl-tRNA synthetase (ArgRS), are also elevated during the exponential phase relative to the stationary phase. For both panels A and B, bar graphs represent the log 2 (fold change), and error bars indicate the standard error of the log 2 (fold change). Log 2 (fold change) was calculated as the base-2 logarithm of the ratio of protein abundance in the exponential phase to that in the stationary phase. Proteins were considered differentially abundant if they had a p-value < 0.05 and an absolute log 2 (fold change) ≥ 0.585. Previous studies have shown that the number of mature ribosomes increases during the fast-growing exponential phase compared to the stationary phase 34 , 35 . Therefore, the increased abundance of DeaD, DbpA, and RlhE likely supports the elevated rate of ribosome production during the exponential growth phase in E. coli BLR (DE3) 35 – 39 . In the BW25113 E. coli strain, a K-12 strain grown in LB medium, the abundance of the DEAD-box RNA helicases DeaD, RlhE, and SrmB increases during the exponential phase compared to the 24-hour stationary phase 40 . The DbpA protein was not detected in the BW25113 study 40 . In our study, similar to the BW25113 strain, the abundance of the DeaD and RlhE proteins increases during the exponential phase ( Figure 3A ) 40 . However, unlike the BW25113 study, we observed no change in SrmB abundance between the exponential and stationary phases (Table S3) 40 . Our analysis shows that RimP, another protein that facilitates ribosome assembly, is more abundant during the exponential phase compared to the stationary phase ( Figure 3A ) 41 . RimP promotes faster binding of small subunit proteins uS9 and uS19 to 30S intermediates, while inhibiting the binding of uS12 and uS13 42 . In E. coli , deletion of the rimP gene results in a high-temperature, slow-growth phenotype and the accumulation of small subunit intermediates 41 . Our findings regarding RimP protein abundance are consistent with observations in BW25113 cells, where RimP levels also increase during the exponential phase compared to the stationary phase 40 . Exponential phase enrichment of specific ribosomal and translational machinery components Thirteen large and small ribosomal subunit proteins show increased abundance in the exponential phase compared to the stationary phase ( Figure 3A , Table S4). In E. coli , several large and small subunit proteins possess RNA and/or protein chaperone activity in addition to their structural roles. Of the thirteen ribosomal proteins more abundant during the exponential phase, uL1 and uL24 exhibit RNA chaperone activity, while uL15, uL18, and bL19 exhibit both RNA and protein chaperone activities 43 , 44 . Therefore, similar to the ribosome maturation factors DeaD, DbpA, RlhE, and RimP, the large subunit proteins uL1, uL15, uL18, bL19, and uL24 likely also facilitate the extensive folding of rRNA and ribosomal proteins necessary for ribosome assembly and protein synthesis during the exponential phase—processes essential for supporting the rapid cell growth and division characteristic of this phase 35 – 39 . Lastly, to support the elevated translational activity characteristic of the exponential phase, initiation factors IF-1 and IF-3, elongation factor EF-P, and ArgRS are more abundant during the exponential phase than in the stationary phase ( Figure 3B ) 38 , 39 . Similarly, in BW25113 cells, levels of IF-1 and ArgRS also increased during the exponential phase compared to the stationary phase 40 . In contrast, IF-3 levels remained unchanged between the two phases in BW25113 cells, and EF-P was not detected in that study 40 . RlmN, RsmI, RluB, RlmG, and TsaC—RNA post-transcriptional modifying enzymes—are enriched during the exponential phase Five enzymes—RlmN, RsmI, RluB, RlmG, and TsaC—implicated in the incorporation of rRNA and tRNA modifications are more abundant in the exponential phase relative to the stationary phase in E. coli BLR (DE3) cells ( Figure 4 ) 45 – 52 . Three of these RNA-modifying enzymes—RlmN, RluB, and RlmG—act on the 23S rRNA of the large ribosomal subunit 45 , 46 , 48 , 50 , 51 . The RNA-modifying enzyme RsmI acts on the 16S rRNA of the small ribosomal subunit, while TsaC is an essential E. coli protein involved in both tRNA modification and small ribosomal subunit assembly 47 , 49 , 53 , 54 . Download figure Open in new tab Figure 4. Five RNA post-transcriptional modifying enzymes are enriched during the exponential phase compared to the stationary phase. These enzymes catalyze nucleotide modifications within small and large subunit rRNAs and tRNAs. Bar graphs represent the log 2 (fold change) for each enzyme, and the lines indicate the standard error of the log 2 (fold change). Log 2 (fold change) was calculated as the base-2 logarithm of the ratio of protein abundance in the exponential phase to that in the stationary phase. Proteins were considered differentially abundant if they had a p-value < 0.05 and an absolute log 2 (fold change) ≥ 0.585. RlmN catalyzes the incorporation of the m 2 A modification at position 2507 of the 23S rRNA 46 , 50 , 51 . This m 2 A2507 modification—along with the 7-methylguanosine at position 2073 and 2-methylguanosine at position 2447 introduced by RlmKL, the 2′-O-methylcytidine (C m ) at position 2505 introduced by RlmM, and the pseudouridine at position 2461 introduced by RluE, all located within the peptidyl transferase center (PTC) of 23S rRNA—facilitate maturation of the 50S large ribosomal subunit and increase the translation elongation rate 45 , 46 , 55 – 57 . In DH5α cells, a K-12 strain of E.coli , the level of m 2 A2507 is elevated during the exponential growth phase in cells cultured in LB medium, relative to those subjected to metabolic or cold stress 58 . Similarly, in BW25113 cells, the abundance of RlmN increases during the exponential phase compared to the stationary phase. Thus, during the exponential phase—characterized by enhanced ribosome biogenesis and elevated translation rates—the m 2 A2507 modification, which supports these processes, also increases across multiple E. coli strains 35 – 39 , 56 . RluB catalyzes the isomerization of U 2609 in 23S rRNA to pseudouridine (Ψ), a modification located within PTC 52 . The role of RluB in large subunit maturation, as well as the function or significance of the Ψ 2609 modification in ribosome maturation, stability, or translation, remains unclear 56 , 59 . Interestingly, both our data and previous results from BW25113 cells show that RluB is enriched during the exponential phase ( Figure 4 ) 40 . Although the biological functions of RluB and the Ψ 2609 modification remain unknown, RluB’s selective enrichment during the exponential phase suggests that RluB and/or Ψ 2609 plays a role in optimizing ribosome structure and/or function during rapid cellular proliferation—alternatively, may confer a disadvantage during the stationary phase. Future studies are needed to elucidate how RluB-mediated pseudouridylation modulates ribosome function and structure across different physiological states. The m²G1837 modification, catalyzed by the RlmG enzyme, has been shown to influence the stability of the E. coli 70S ribosome by strengthening interactions between the 50S and 30S subunits 60 , 61 . Similar to the results shown here, the abundance of RlmG is reduced during the stationary phase of BW25113 cells compared to the exponential phase ( Figure 4 ) 40 . Furthermore, the extent of m²G1837 modification decreases in DH5α cells under cold and metabolic stress conditions 58 . Collectively, our data and previous studies indicate that under various stress conditions, 70S ribosomes may be less stable and tend to dissociate into 30S and 50S subunits. These free subunits are more vulnerable to degradation, a process that may contribute to energy production during the stationary phase—a growth stage characterized by nutrient limitation 62 . Additionally, during the stationary phase, a smaller fraction of ribosomes is engaged in active translation 38 , 39 . Thus, the reduced stability of 70S ribosomes during this phase may further increases the pool of inactive 30S and 50S subunits. RsmI is an enzyme that catalyzes the 2′-O-methylation of the C1402 residue in 16S rRNA 49 . Another enzyme, RsmH, modifies the same nucleotide by methylating the N4 position of C1402 (m⁴C) 49 . In BLR (DE3) cells, we observed that RsmI abundance increases during the exponential phase relative to the stationary phase, whereas RsmH levels remain largely unchanged based on our biological and statistical thresholds ( Figure 4 ). These findings suggest that during the exponential phase, a greater proportion of C1402 residues in BLR (DE3) cells are modified by both 2′-O-methylation and N4-methylation. In contrast, during the stationary phase, many C1402 residues likely carry only the N4-methylation. In BW25113 cells, however, the expression levels of both RsmI and RsmH remain constant between the exponential and stationary phases 40 . Consequently, the proportion of dimethylated C1402 residues in these cells likely remains stable across growth phases. The C1402 nucleotide makes direct contact with the mRNA positioned in the ribosomal A site of the ribosome 49 . Both N4-methylation and 2′-O-methylation at this site contribute to maintaining translation fidelity 49 . Here, we report that the abundance of the RsmI enzyme— which catalyzes 2′-O-methylation of the C1402 residue in the 16S rRNA—decreases during the stationary phase relative to the exponential phase ( Figure 4 ). This finding suggests that, in BLR (DE3) cells, translational accuracy is reduced under stationary-phase conditions. Accordingly, during this growth phase, BLR (DE3) cells may prioritize survival over fidelity in protein synthesis. A decline in translational accuracy under stress conditions has also been observed in other E. coli and other bacteria 63 . TsaC catalyzes the formation of L-threonylcarbamoyladenylate (t 6 A) 47 . Subsequently, the TsaB, TsaD, and TsaE enzymes collaboratively incorporate t 6 A at position 37 in tRNA 47 , 64 . This tRNA modification enhances translation fidelity by stabilizing codon–anticodon interactions 47 , 65 . In addition to its role in tRNA modification, the TsaC protein is involved in the maturation of the E. coli small ribosomal subunit 53 . Our data show an increased abundance of the TsaC enzyme in the exponential phase compared to the stationary phase. However, no change was observed in the abundance of TsaB and TsaD, and the TsaE protein was not detected in either growth phase (Table S3). The elevated abundance of TsaC in the exponential phase, without a corresponding increase in TsaD and TsaB, suggests that TsaC may play a role in 30S small subunit assembly or in other, yet-uncharacterized, cellular functions that do not require the activity of the TsaD and TsaB proteins 53 . In E. coli BLR (DE3) cells, fourteen proteins associated with antibiotic resistance are more abundant in the exponential phase, while a different set of thirteen proteins is elevated in the stationary phase The abundances of 27 proteins associated with antibiotic resistance differ between the exponential and stationary phases of E. coli BLR (DE3) growth ( Figure 5 , Table 1 ). These proteins are involved in wide rage antibiotic resistance mechanisms and cellular metabolic pathways (Table S5-S8). Notably, several proteins exhibit similar abundance patterns between the two growth phases in both BLR (DE3) and BW25113 strains, whereas others either remain unchanged in BW25113 or display opposite trends in relative abundance 40 . Download figure Open in new tab Figure 5. Protein expression profiles reveal growth phase–specific antibiotic resistance mechanisms. Fourteen proteins, indicated in red, are upregulated in the exponential phase relative to the stationary phase. Thirteen proteins, indicated in purple, are upregulated in the stationary phase relative to the exponential phase. Bar graphs represent the log 2 (fold change) for each enzyme and the lines indicate the standard error of the log 2 (fold change). Log 2 (fold change) was calculated as the base-2 logarithm of the ratio of protein abundance in the exponential phase to that in the stationary phase. Proteins were considered differentially abundant if they had a p-value < 0.05 and an absolute log 2 (fold change) ≥ 0.585. View this table: View inline View popup Table 1. Unique proteins associated with single- and multidrug resistance are enriched during the exponential or stationary growth phase in E. coli BLR (DE3). The abundance of seven proteins — CBAP, FeoB, ArnA, EmrA, IscR, PstB, and DapE — is higher in the exponential phase of both BLR (DE3) and BW25113 cells relative to the stationary phase ( Figure 5 , Table 1 ) 40 . On the other hand, the abundance of six proteins — E_SOD, CusC, Lpp, BamE, FabA, and PNPase — increases in the exponential phase of BLR (DE3) cells relative to the stationary phase, but the abundance of these proteins exhibits the opposite trend in the BW25113 cells, or remains unchanged between the two phases ( Figure 5 , Table 1 ) 40 . The abundance of the EptA protein increases in the exponential phase of BLR (DE3) cells, while this protein is not detected in the BW25113 cells ( Figure 5 , Table 1 ) 40 . In the stationary phase, the abundance of three proteins, EntB, EntC, and EntF, increases relative to the exponential phase for both BLR (DE3) and BW25113 cells ( Figure 5 , Table 1 ) 40 . In contrast, the abundance of nine proteins, HflC, Mfd, AcrA, NsfA, DegP, ClpP, KatG, DacB and CysE increases in the stationary phase of BLR (DE3) cells relative to the exponential phase while these abundances remain unchanged or show the opposite trend in the BW25113 cells. Finally, the abundance of the NsfB protein increases in the stationary phase in of the BLR (DE3) cells whereas its abundance remains undetermined in BW25113 cells 40 . In summary, the data collected in this study, combined with previous results, demonstrate that the two different E. coli strains—BLR (DE3), a B strain, and BW25113, a K-12 strain — possess a number of shared and many unique, antibiotic resistance mechanisms during the exponential and stationary growth phases 40 . Conclusion Our results are consistent with previous findings in E. coli , which show that processes essential for rapid cell growth—such as gene expression, ribosome assembly, and translation—are elevated in the exponential phase relative to the stationary phase ( Figure 1 , Table S1) 35 – 39 . In contrast, the TCA cycle, which is required for energy production and biosynthesis processes when glucose is limited, is more active in the stationary phase than in the exponential phase (Table S2) 17 – 19 . Importantly, we conducted a systematic and comprehensive analysis of differences in antibiotic resistance mechanisms between the exponential and stationary phases. Our results demonstrate that distinct resistance pathways are activated in each phase of BLR (DE3), a nonpathogenic E. coli B strain. This insight may inform the development of phase-specific antibiotics targeting pathogenic E. coli and other bacteria ( Figure 5 , Table 1 ). Lastly, we observed distinct differences in the proteomic profiles associated with antibiotic resistance between the nonpathogenic E. coli B strain characterized in this study and a previously investigated nonpathogenic E. coli K-12 strain 40 . Future large-scale, quantitative proteomic analyses comparing pathogenic E. coli strains with nonpathogenic E. coli from the human microbiome could uncover both conserved and strain-specific resistance pathways. This knowledge may inform the development of narrow-spectrum antibiotic treatments that selectively target pathogenic E. coli while preserving commensal strains, thereby minimizing microbiome disruption and reducing the potential for resistance development. Data Availability The mass spectrometry proteomics data and associated metadata, experimental details, and sample-to-data files have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier XXXXXX 132 , 133 . Associated Content Supporting Information Biological pathways elevated in the exponential phase of E. coli BLR (DE3) cells relative to the stationary phase. Biological pathways elevated in the stationary phase of E. coli BLR (DE3) cells relative to the exponential phase. Log₂ fold change, p-values, and the phase-specific abundance of TsaB, TsaD, RsmH, and SrmB proteins in the exponential and stationary growth phases of E. coli . Relative abundance and p-values of ribosomal structural proteins. Cellular functions of proteins whose abundance uniquely increases during the exponential phase of E. coli growth and that are involved in antibiotic resistance. Cellular functions of proteins whose abundance uniquely increases during the stationary phase of E. coli growth and that are involved in antibiotic resistance. Biological processes associated with proteins involved in antibiotic resistance that increase in abundance during the exponential phase. Biological processes associated with proteins involved in antibiotic resistance that increase in abundance during the stationary phase. Funding This work was supported in part by the National Institute of General Medical Sciences grant R01-GM131062, the University of Texas System Rising STARs Program, and the start-up from the Chemistry and Biochemistry Department at the University of Texas at El Paso (to EK). Brody School of Medicine at ECU’s MS Core has received support from the Golden Leaf Foundation and federal COVID-19 relief funds appropriated to ECU in North Carolina SL 2020-4. Download figure Open in new tab FOR TABLE OF CONTENT USE ONLY. Acknowledgment EK is grateful to Luis Gracia Mazuca for the discussions concerning the RNA modifying enzymes. Funder Information Declared National Institute of General Medical Sciences , R01-GM131062 University of Texas System Rising STARs Program Start-up from the Chemistry and Biochemistry Department at the University of Texas at El Paso Golden Leaf Foundation COVID-19 relief funds appropriated to ECU in North Carolina SL 2020-4 References [1]. ↵ Collaborators , G. B. D. A. R . ( 2022 ) Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019 , Lancet 400 , 2221 – 2248 . OpenUrl CrossRef PubMed 2. ↵ Gao , Y.-D. , Zhao , Y. , and Huang , J. ( 2014 ) Metabolic Modeling of Common Escherichia coliStrains in Human Gut Microbiome , BioMed Research International 2014 , 1 – 11 . OpenUrl [3]. Martinson , J. N. V. , and Walk , S. T . ( 2020 Sep 25 ) Escherichia coli Residency in the Gut of Healthy Human Adults , EcoSal Plus 9 . [4]. Iacovelli , R. , Sokolova , N. , and Haslinger , K . ( 2022 ) Striving for sustainable biosynthesis: discovery, diversification, and production of antimicrobial drugs in Escherichia coli , Biochem Soc Trans 50 , 1315 – 1328 . OpenUrl CrossRef PubMed [5]. ↵ Ferrer-Miralles , N. , and Villaverde , A . ( 2013 ) Bacterial cell factories for recombinant protein production; expanding the catalogue , Microb Cell Fact 12 , 113 . OpenUrl CrossRef PubMed [6]. ↵ Zheng , E. J. , Valeri , J. A. , Andrews , I. W. , Krishnan , A. , Bandyopadhyay , P. , Anahtar , M. N. , Herneisen , A. , Schulte , F. , Linnehan , B. , Wong , F. , Stokes , J. M. , Renner , L. D. , Lourido , S. , and Collins , J. J . ( 2024 ) Discovery of antibiotics that selectively kill metabolically dormant bacteria , Cell Chem Biol 31 , 712 – 728 e719 . OpenUrl CrossRef PubMed [7]. ↵ Forsyth , V. S. , Armbruster , C. E. , Smith , S. N. , Pirani , A. , Springman , A. C. , Walters , M. S. , Nielubowicz , G. R. , Himpsl , S. D. , Snitkin , E. S. , and Mobley , H. L. T . ( 2018 ) Rapid Growth of Uropathogenic Escherichia coli during Human Urinary Tract Infection , mBio 9 . [8]. ↵ Han , M. J. , Yun , H. , Lee , J. W. , Lee , Y. H. , Lee , S. Y. , Yoo , J. S. , Kim , J. Y. , Kim , J. F. , and Hur , C. G . ( 2011 ) Genome-wide identification of the subcellular localization of the Escherichia coli B proteome using experimental and computational methods , Proteomics 11 , 1213 – 1227 . OpenUrl CrossRef PubMed Web of Science [9]. ↵ Kong , A. T. , Leprevost , F. V. , Avtonomov , D. M. , Mellacheruvu , D. , and Nesvizhskii , A. I . ( 2017 ) MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics , Nat Methods 14 , 513 – 520 . OpenUrl CrossRef PubMed [10]. ↵ Yu , F. , Haynes , S. E. , and Nesvizhskii , A. I . ( 2021 ) IonQuant Enables Accurate and Sensitive Label-Free Quantification With FDR-Controlled Match-Between-Runs , Mol Cell Proteomics 20 , 100077 . OpenUrl CrossRef PubMed [11]. ↵ Tyanova , S. , Temu , T. , Sinitcyn , P. , Carlson , A. , Hein , M. Y. , Geiger , T. , Mann , M. , and Cox , J . ( 2016 ) The Perseus computational platform for comprehensive analysis of (prote)omics data , Nat Methods 13 , 731 – 740 . OpenUrl CrossRef PubMed [12]. ↵ Mi , H. , Muruganujan , A. , Huang , X. , Ebert , D. , Mills , C. , Guo , X. , and Thomas , P. D. ( 2019 ) Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0) , Nat Protoc 14 , 703 – 721 . OpenUrl CrossRef PubMed [13]. ↵ Mi , H. , Muruganujan , A. , Ebert , D. , Huang , X. , and Thomas , P. D . ( 2019 ) PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools , Nucleic Acids Res 47 , D419 – D426 . OpenUrl CrossRef PubMed 14. ↵ Szklarczyk , D. , Kirsch , R. , Koutrouli , M. , Nastou , K ., Mehryary , F. , Hachilif , R. , Gable , A. L. , Fang , T. , Doncheva , N. T. , Pyysalo , S. , Bork , P. , Jensen , L. J. , and von Mering , C. ( 2023 ) The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest , Nucleic Acids Res 51 , D638 – D646 . OpenUrl CrossRef PubMed [15]. ↵ UniProt , C . ( 2025 ) UniProt: the Universal Protein Knowledgebase in 2025 , Nucleic Acids Res 53 , D609 – D617 . OpenUrl CrossRef PubMed [16]. ↵ Moore , L. R. , Caspi , R. , Boyd , D. , Berkmen , M. , Mackie , A. , Paley , S. , and Karp , P. D . ( 2024 ) Revisiting the y-ome of Escherichia coli , Nucleic Acids Res 52 , 12201 – 12207 . OpenUrl CrossRef PubMed [17]. ↵ Zalis , E. A. , Nuxoll , A. S. , Manuse , S. , Clair , G. , Radlinski , L. C. , Conlon , B. P. , Adkins , J. , and Lewis , K . ( 2019 ) Stochastic Variation in Expression of the Tricarboxylic Acid Cycle Produces Persister Cells , mBio 10 . [18]. Vemuri , G. N. , Altman , E. , Sangurdekar , D. P. , Khodursky , A. B. , and Eiteman , M. A . ( 2006 ) Overflow metabolism in Escherichia coli during steady-state growth: transcriptional regulation and effect of the redox ratio , Appl Environ Microbiol 72 , 3653 – 3661 . OpenUrl Abstract / FREE Full Text [19]. ↵ Kao , K. C. , Tran , L. M. , and Liao , J. C . ( 2005 ) A global regulatory role of gluconeogenic genes in Escherichia coli revealed by transcriptome network analysis , J Biol Chem 280 , 36079 – 36087 . OpenUrl Abstract / FREE Full Text [20]. ↵ Noeske , J. , Wasserman , M. R. , Terry , D. S. , Altman , R. B. , Blanchard , S. C. , and Cate , J. H . ( 2015 ) High-resolution structure of the Escherichia coli ribosome , Nat Struct Mol Biol 22 , 336 – 341 . OpenUrl CrossRef PubMed [21]. ↵ Shajani , Z. , Sykes , M. T. , and Williamson , J. R . ( 2011 ) Assembly of bacterial ribosomes , Annu Rev Biochem 80 , 501 – 526 . OpenUrl CrossRef PubMed Web of Science [22]. Connolly , K. , and Culver , G . ( 2009 ) Deconstructing ribosome construction , Trends Biochem Sci 34 , 256 – 263 . OpenUrl CrossRef PubMed Web of Science [23]. ↵ Klinge , S. , and Woolford , J. L. , Jr . . ( 2019 ) Ribosome assembly coming into focus , Nat Rev Mol Cell Biol 20 , 116 – 131 . OpenUrl CrossRef PubMed [24]. ↵ Linder , P. , and Fuller-Pace , F . ( 2015 ) Happy birthday: 25 years of DEAD-box proteins , Methods Mol Biol 1259 , 17 – 33 . OpenUrl CrossRef PubMed [25]. Bohnsack , K. E. , Yi , S. , Venus , S. , Jankowsky , E. , and Bohnsack , M. T . ( 2023 ) Cellular functions of eukaryotic RNA helicases and their links to human diseases , Nat Rev Mol Cell Biol 24 , 749 – 769 . OpenUrl CrossRef PubMed [26]. Cordin , O. , Banroques , J. , Tanner , N. K. , and Linder , P . ( 2006 ) The DEAD-box protein family of RNA helicases , Gene 367 , 17 – 37 . OpenUrl CrossRef PubMed Web of Science 27. Moore , A. F. T. , de Victoria , A. L. , and Koculi , E. ( 2021 ) Interactions of the C-Terminal Truncated DEAD-Box Protein DDX3X With RNA and Nucleotide Substrates , ACS Omega 6 , 12640 – 12646 . OpenUrl CrossRef PubMed [28]. ↵ Moore , A. F. T. , Berhie , Y. , Weislow S. I. and Koculi , E . ( 2025 ) Substrate Specificities of DDX1: A Human DEAD-Box Protein , ACS Omega . [29]. ↵ Iost , I. , and Dreyfus , M . ( 2006 ) DEAD-box RNA helicases in Escherichia coli , Nucleic Acids Res 34 , 4189 – 4197 . OpenUrl CrossRef PubMed Web of Science [30]. Jain , C . ( 2008 ) The E. coli RhlE RNA helicase regulates the function of related RNA helicases during ribosome assembly , Rna 14 , 381 – 389 . OpenUrl Abstract / FREE Full Text [31]. Gentry , R. C. , Childs , J. J. , Gevorkyan , J. , Gerasimova , Y. V. , and Koculi , E . ( 2016 ) Time course of large ribosomal subunit assembly in E. coli cells overexpressing a helicase inactive DbpA protein , RNA 22 , 1055 – 1064 . OpenUrl Abstract / FREE Full Text 32. Lopez de Victoria , A. , Moore , A. F. T. , Gittis , A. G. , and Koculi , E. ( 2017 ) Kinetics and Thermodynamics of DbpA Protein’s C-Terminal Domain Interaction with RNA , ACS Omega 2 , 8033 – 8038 . OpenUrl CrossRef PubMed [33]. ↵ Moore , A. F. , Gentry , R. C. , and Koculi , E . ( 2017 ) DbpA is a region-specific RNA helicase , Biopolymers 107 . [34]. ↵ Deutscher , M. P . ( 2003 ) Degradation of stable RNA in bacteria , J Biol Chem 278 , 45041 – 45044 . OpenUrl FREE Full Text [35]. ↵ Reier , K. , Lahtvee , P. J. , Liiv , A. , and Remme , J . ( 2022 ) A Conundrum of r-Protein Stability: Unbalanced Stoichiometry of r-Proteins during Stationary Phase in Escherichia coli , mBio 13 , e0187322 . OpenUrl CrossRef PubMed [36]. Scott , M. , Gunderson , C. W. , Mateescu , E. M. , Zhang , Z. , and Hwa , T . ( 2010 ) Interdependence of cell growth and gene expression: origins and consequences , Science 330 , 1099 – 1102 . OpenUrl Abstract / FREE Full Text [37]. Bremer , H. , and Dennis , P. P . ( 2008 ) Modulation of Chemical Composition and Other Parameters of the Cell at Different Exponential Growth Rates , EcoSal Plus 3 . [38]. ↵ Reier , K. , Liiv , A. , and Remme , J . ( 2023 ) Ribosome Protein Composition Mediates Translation during the Escherichia coli Stationary Phase , Int J Mol Sci 24 . [39]. ↵ Dai , X. , Zhu , M. , Warren , M. , Balakrishnan , R. , Patsalo , V. , Okano , H. , Williamson , J. R. , Fredrick , K. , Wang , Y. P. , and Hwa , T . ( 2016 ) Reduction of translating ribosomes enables Escherichia coli to maintain elongation rates during slow growth , Nat Microbiol 2 , 16231 . OpenUrl CrossRef PubMed [40]. ↵ Schmidt , A. , Kochanowski , K. , Vedelaar , S. , Ahrne , E. , Volkmer , B. , Callipo , L. , Knoops , K. , Bauer , M. , Aebersold , R. , and Heinemann , M . ( 2016 ) The quantitative and condition-dependent Escherichia coli proteome , Nat Biotechnol 34 , 104 – 110 . OpenUrl CrossRef PubMed [41]. ↵ Nord , S. , Bhatt , M. J. , Tukenmez , H. , Farabaugh , P. J. , and Wikstrom , P. M . ( 2015 ) Mutations of ribosomal protein S5 suppress a defect in late-30S ribosomal subunit biogenesis caused by lack of the RbfA biogenesis factor , RNA 21 , 1454 – 1468 . OpenUrl Abstract / FREE Full Text [42]. ↵ Bunner , A. E. , Nord , S. , Wikstrom , P. M. , and Williamson , J. R . ( 2010 ) The effect of ribosome assembly cofactors on in vitro 30S subunit reconstitution , J Mol Biol 398 , 1 – 7 . OpenUrl CrossRef PubMed Web of Science [43]. ↵ Semrad , K. , Green , R. , and Schroeder , R . ( 2004 ) RNA chaperone activity of large ribosomal subunit proteins from Escherichia coli , RNA 10 , 1855 – 1860 . OpenUrl Abstract / FREE Full Text [44]. ↵ Kovacs , D. , Rakacs , M. , Agoston , B. , Lenkey , K. , Semrad , K. , Schroeder , R. , and Tompa , P . ( 2009 ) Janus chaperones: assistance of both RNA- and protein-folding by ribosomal proteins , FEBS Lett 583 , 88 – 92 . OpenUrl CrossRef PubMed Web of Science [45]. ↵ Ofengand , J. , and Del Campo , M . ( 2004 ) Modified Nucleosides of Escherichia coli Ribosomal RNA , EcoSal Plus 1 . [46]. ↵ Toh , S.-M. , Xiong , L. , Bae , T. , and Mankin , A. S . ( 2008 ) The methyltransferase YfgB/RlmN is responsible for modification of adenosine 2503 in 23S rRNA , RNA 14 , 98 – 106 . OpenUrl Abstract / FREE Full Text 47. ↵ Deutsch , C. , El Yacoubi , B. , de Crecy-Lagard , V. , and Iwata-Reuyl , D. ( 2012 ) Biosynthesis of threonylcarbamoyl adenosine (t6A), a universal tRNA nucleoside , J Biol Chem 287 , 13666 – 13673 . OpenUrl Abstract / FREE Full Text [48]. ↵ Sergiev , P. V. , Lesnyak , D. V. , Bogdanov , A. A. , and Dontsova , O. A . ( 2006 ) Identification of Escherichia coli m2G methyltransferases: II. The ygjO Gene Encodes a Methyltransferase Specific for G1835 of the 23 S rRNA , Journal of Molecular Biology 364 , 26 – 31 . OpenUrl CrossRef PubMed Web of Science [49]. ↵ Kimura , S. , and Suzuki , T . ( 2010 ) Fine-tuning of the ribosomal decoding center by conserved methyl-modifications in the Escherichia coli 16S rRNA , Nucleic Acids Res 38 , 1341 – 1352 . OpenUrl CrossRef PubMed Web of Science [50]. ↵ Koculi , E. , and Cho , S. S . ( 2022 ) RNA Post-Transcriptional Modifications in Two Large Subunit Intermediates Populated in E. coli Cells Expressing Helicase Inactive R331A DbpA , Biochemistry 61 , 833 – 842 . OpenUrl CrossRef PubMed [51]. ↵ Narayan , G. , Gracia Mazuca , L. A. , Cho , S. S. , Mohl , J. E. , and Koculi , E . ( 2023 ) RNA Post-transcriptional Modifications of an Early-Stage Large-Subunit Ribosomal Intermediate , Biochemistry 62 , 2908 – 2915 . OpenUrl CrossRef PubMed [52]. ↵ Del Campo , M. , Kaya , Y. , and Ofengand , J . ( 2001 ) Identification and site of action of the remaining four putative pseudouridine synthases in Escherichia coli , RNA 7 , 1603 – 1615 . OpenUrl Abstract [53]. ↵ Kaczanowska , M. , and Ryden-Aulin , M . ( 2005 ) The YrdC protein--a putative ribosome maturation factor , Biochim Biophys Acta 1727 , 87 – 96 . OpenUrl PubMed 54. ↵ Thiaville , P. C. , El Yacoubi, B., Kohrer, C., Thiaville, J. J., Deutsch, C., Iwata-Reuyl, D., Bacusmo, J. M., Armengaud, J., Bessho, Y., Wetzel, C., Cao, X., Limbach, P. A., RajBhandary, U. L., and de Crecy-Lagard, V . ( 2015 ) Essentiality of threonylcarbamoyladenosine (t(6)A), a universal tRNA modification, in bacteria , Mol Microbiol 98 , 1199 – 1221 . OpenUrl CrossRef PubMed [55]. ↵ Wang , K.-T. , Desmolaize , B. , Nan , J. , Zhang , X.-W. , Li , L.-F. , Douthwaite , S. , and Su , X.-D . ( 2012 ) Structure of the bifunctional methyltransferase YcbY (RlmKL) that adds the m 7 G2069 and m 2 G2445 modifications in Escherichia coli 23S rRNA , Nucleic Acids Research 40 , 5138 – 5148 . OpenUrl CrossRef PubMed Web of Science [56]. ↵ Bao , L. , Liljeruhm , J. , Crespo Blanco , R. , Brandis , G. , Remme , J. , and Forster , A. C . ( 2024 ) Translational impacts of enzymes that modify ribosomal RNA around the peptidyl transferase centre , RNA Biol 21 , 31 – 41 . OpenUrl CrossRef [57]. ↵ Purta , E. , O’Connor , M. , Bujnicki , J. M. , and Douthwaite , S . ( 2009 ) YgdE is the 2′- O -ribose methyltransferase RlmM specific for nucleotide C2498 in bacterial 23S rRNA , Molecular Microbiology 72 , 1147 – 1158 . OpenUrl CrossRef PubMed Web of Science [58]. ↵ Fleming , A. M. , Bommisetti , P. , Xiao , S. , Bandarian , V. , and Burrows , C. J . ( 2023 ) Direct Nanopore Sequencing for the 17 RNA Modification Types in 36 Locations in the E. coli Ribosome Enables Monitoring of Stress-Dependent Changes , ACS Chem Biol 18 , 2211 – 2223 . OpenUrl CrossRef PubMed [59]. ↵ Ero , R. , Leppik , M. , Reier , K. , Liiv , A. , and Remme , J . ( 2024 ) Ribosomal RNA modification enzymes stimulate large ribosome subunit assembly in E. coli , Nucleic Acids Res 52 , 6614 – 6628 . OpenUrl CrossRef PubMed [60]. ↵ Sergiev , P. V. , Lesnyak , D. V. , Bogdanov , A. A. , and Dontsova , O. A . ( 2006 ) Identification of Escherichia coli m2G methyltransferases: II. The ygjO gene encodes a methyltransferase specific for G1835 of the 23 S rRNA , J Mol Biol 364 , 26 – 31 . OpenUrl CrossRef PubMed Web of Science [61]. ↵ Osterman , I. A. , Sergiev , P. V. , Tsvetkov , P. O. , Makarov , A. A. , Bogdanov , A. A. , and Dontsova , O. A . ( 2011 ) Methylated 23S rRNA nucleotide m2G1835 of Escherichia coli ribosome facilitates subunit association , Biochimie 93 , 725 – 729 . OpenUrl CrossRef PubMed Web of Science [62]. ↵ Zundel , M. A. , Basturea , G. N. , and Deutscher , M. P . ( 2009 ) Initiation of ribosome degradation during starvation in Escherichia coli , RNA 15 , 977 – 983 . OpenUrl Abstract / FREE Full Text [63]. ↵ Lyu , Z. , Wilson , C. , and Ling , J . ( 2023 ) Translational Fidelity during Bacterial Stresses and Host Interactions , Pathogens 12 . 64. ↵ Missoury , S. , Plancqueel , S. , Li de la Sierra-Gallay , I. , Zhang , W. , Liger , D. , Durand , D. , Dammak , R. , Collinet , B. , and van Tilbeurgh , H. ( 2019 ) The structure of the TsaB/TsaD/TsaE complex reveals an unexpected mechanism for the bacterial t6A tRNA-modification , Nucleic Acids Res 47 , 9464 – 9465 . OpenUrl CrossRef PubMed [65]. ↵ Murphy , F. V. t. , Ramakrishnan , V. , Malkiewicz , A. , and Agris , P. F. ( 2004 ) The role of modifications in codon discrimination by tRNA(Lys)UUU , Nat Struct Mol Biol 11 , 1186 – 1191 . OpenUrl CrossRef PubMed Web of Science [66]. Qin , S. , Wang , Y. , Zhang , Q. , Chen , X. , Shen , Z. , Deng , F. , Wu , C. , and Shen , J . ( 2012 ) Identification of a Novel Genomic Island Conferring Resistance to Multiple Aminoglycoside Antibiotics in Campylobacter coli , Antimicrobial Agents and Chemotherapy 56 , 5332 – 5339 . OpenUrl Abstract / FREE Full Text [67]. Efimochkina , N. R. , Stetsenko , V. V. , Bykova , I. V. , Markova , Y. M. , Polyanina , A. S. , Aleshkina , A. I. , and Sheveleva , S. A . ( 2018 ) Studying the Phenotypic and Genotypic Expression of Antibiotic Resistance in Campylobacter jejuni under Stress Conditions , Bulletin of Experimental Biology and Medicine 164 , 466 – 472 . OpenUrl CrossRef PubMed [68]. Qian , Y. , Lai , L. , Cheng , M. , Fang , H. , Fan , D. , Zylstra , G. J. , and Huang , X . ( 2024 ) Identification, characterization, and distribution of novel amidase gene aphA in sphingomonads conferring resistance to amphenicol antibiotics , Appl Environ Microbiol 90 , e0151224 . OpenUrl CrossRef PubMed [69]. Gibreel , A. , Skold , O. , and Taylor , D. E . ( 2004 ) Characterization of plasmid-mediated aphA-3 kanamycin resistance in Campylobacter jejuni , Microb Drug Resist 10 , 98 – 105 . OpenUrl CrossRef PubMed [70]. Veeranagouda , Y. , Husain , F. , Boente , R. , Moore , J. , Smith , C. J. , Rocha , E. R. , Patrick , S. , and Wexler , H. M . ( 2014 ) Deficiency of the ferrous iron transporter FeoAB is linked with metronidazole resistance in Bacteroides fragilis , Journal of Antimicrobial Chemotherapy 69 , 2634 – 2643 . OpenUrl CrossRef PubMed [71]. Trebosc , V. , Gartenmann , S. , Tötzl , M. , Lucchini , V. , Schellhorn , B. , Pieren , M. , Lociuro , S. , Gitzinger , M. , Tigges , M. , Bumann , D. , and Kemmer , C . ( 2019 ) Dissecting Colistin Resistance Mechanisms in Extensively Drug-Resistant Acinetobacter baumannii Clinical Isolates , mBio 10 . [72]. Potron , A. , Vuillemenot , J.-B. , Puja , H. , Triponney , P. , Bour , M. , Valot , B. , Amara , M. , Cavalié , L. , Bernard , C. , Parmeland , L. , Reibel , F. , Larrouy-Maumus , G. , Dortet , L. , Bonnin , R. A. , and Plésiat , P . ( 2019 ) ISAba1-dependent overexpression of eptA in clinical strains of Acinetobacter baumannii resistant to colistin , Journal of Antimicrobial Chemotherapy 74 , 2544 – 2550 . OpenUrl CrossRef PubMed [73]. Cervoni , M. , Sposato , D. , Lo Sciuto , A. , and Imperi , F . ( 2023 ) Regulatory Landscape of the Pseudomonas aeruginosa Phosphoethanolamine Transferase Gene eptA in the Context of Colistin Resistance , Antibiotics 12 , 200 . OpenUrl CrossRef PubMed [74]. Mettert , E. L. , and Kiley , P. J . ( 2024 /08/01) Fe-S cluster homeostasis and beyond: The multifaceted roles of IscR , Biochimica et Biophysica Acta (BBA) - Molecular Cell Research 1871 . [75]. Yi , X. , Xu , X. , Qi , X. , Chen , Y. , Zhu , Z. , Xu , G. , Li , H. , Kraco , E.-K. , Shen , H. , Lin , M. , Zheng , J. , Qin , Y. , and Jiang , X . ( 2022 ) Mechanisms Underlying the Virulence Regulation of Vibrio alginolyticus ND-01 pstS and pstB with a Transcriptomic Analysis , Microorganisms 10 , 2093 . OpenUrl CrossRef PubMed [76]. Engel , H. , Mika , M. , Denapaite , D. , Hakenbeck , R. , Mühlemann , K. , Heller , M. , Hathaway , L. J. , and Hilty , M . ( 2014 ) A Low-Affinity Penicillin-Binding Protein 2x Variant Is Required for Heteroresistance in Streptococcus pneumoniae , Antimicrobial Agents and Chemotherapy 58 , 3934 – 3941 . OpenUrl Abstract / FREE Full Text [77]. Bhardwaj , P. , Islam , M. Z. , Kim , C. , Nguyen , U. T. , and Palmer , K. L . ( 2021 ) ddcP, pstB, and excess D-lactate impact synergism between vancomycin and chlorhexidine against Enterococcus faecium 1,231,410 , PLOS ONE 16 , e0249631 . OpenUrl CrossRef PubMed [78]. Zhang , H. , Ma , Y. , Liu , P. , and Li , X . ( 2016 ) Multidrug resistance operon emrAB contributes for chromate and ampicillin co-resistance in a Staphylococcus strain isolated from refinery polluted river bank , SpringerPlus 5 . [79]. Furukawa , H. , Tsay , J. T. , Jackowski , S. , Takamura , Y. , and Rock , C. O . ( 1993 ) Thiolactomycin resistance in Escherichia coli is associated with the multidrug resistance efflux pump encoded by emrAB , Journal of Bacteriology 175 , 3723 – 3729 . OpenUrl Abstract / FREE Full Text [80]. Lomovskaya , O. , and Lewis , K . ( 1992 ) Emr, an Escherichia coli locus for multidrug resistance ., Proceedings of the National Academy of Sciences 89 , 8938 – 8942 . OpenUrl Abstract / FREE Full Text [81]. Heindorf , M. , Kadari , M. , Heider , C. , Skiebe , E. , and Wilharm , G . ( 2014 ) Impact of Acinetobacter baumannii Superoxide Dismutase on Motility, Virulence, Oxidative Stress Resistance and Susceptibility to Antibiotics , PLoS ONE 9 , e101033 . OpenUrl CrossRef PubMed [82]. Chen , D. , Zhao , Y. , Qiu , Y. , Xiao , L. , He , H. , Zheng , D. , Li , X. , Yu , X. , Xu , N. , Hu , X. , Chen , F. , Li , H. , and Chen , Y . ( 2020 ) CusS-CusR Two-Component System Mediates Tigecycline Resistance in Carbapenem-Resistant Klebsiella pneumoniae , Frontiers in Microbiology 10 . [83]. Chang , T.-W. , Lin , Y.-M. , Wang , C.-F. , and Liao , Y.-D . ( 2012 ) Outer Membrane Lipoprotein Lpp Is Gram-negative Bacterial Cell Surface Receptor for Cationic Antimicrobial Peptides , Journal of Biological Chemistry 287 , 418 – 428 . OpenUrl Abstract / FREE Full Text [84]. Ebbensgaard , A. , Mordhorst , H. , Aarestrup , F. M. , and Hansen , E. B . ( 2018 ) The Role of Outer Membrane Proteins and Lipopolysaccharides for the Sensitivity of Escherichia coli to Antimicrobial Peptides , Frontiers in Microbiology 9 . [85]. Mathelié-Guinlet , M. , Asmar , A. T. , Collet , J.-F. , and Dufrêne , Y. F . ( 2020 ) Lipoprotein Lpp regulates the mechanical properties of the E. coli cell envelope , Nature Communications 11 . [86]. Wykes , H. , Le , V. V. H. , Olivera , C. , and Rakonjac , J . ( 2023 ) When less is more: shortening the Lpp protein leads to increased vancomycin resistance in Escherichia coli , The Journal of Antibiotics 76 , 746 – 750 . OpenUrl CrossRef PubMed [87]. Nocek , B. , Starus , A. , Makowska-Grzyska , M. , Gutierrez , B. , Sanchez , S. , Jedrzejczak , R. , Mack , J. C. , Olsen , K. W. , Joachimiak , A. , and Holz , R. C . ( 2014 ) The Dimerization Domain in DapE Enzymes Is required for Catalysis , PLoS ONE 9 , e93593 . OpenUrl CrossRef PubMed [88]. Terrazas-López , M. , González-Segura , L. , Díaz-Vilchis , A. , Aguirre-Mendez , K. A. , Lobo-Galo , N. , Martínez-Martínez , A. , and Díaz-Sánchez , Á. G . ( 2024 /06/01) The three-dimensional structure of DapE from Enterococcus faecium reveals new insights into DapE/ArgE subfamily ligand specificity , International Journal of Biological Macromolecules 270 . [89]. Fan , Z. , Pan , X. , Wang , D. , Chen , R. , Fu , T. , Yang , B. , Jin , Y. , Bai , F. , Cheng , Z. , and Wu , W . ( 2021 ) Pseudomonas aeruginosa Polynucleotide Phosphorylase Controls Tolerance to Aminoglycoside Antibiotics by Regulating the MexXY Multidrug Efflux Pump , Antimicrobial Agents and Chemotherapy 65 . [90]. Fan , Z. , Chen , H. , Li , M. , Pan , X. , Fu , W. , Ren , H. , Chen , R. , Bai , F. , Jin , Y. , Cheng , Z. , Jin , S. , and Wu , W . ( 2019 ) Pseudomonas aeruginosa Polynucleotide Phosphorylase Contributes to Ciprofloxacin Resistance by Regulating PrtR , Frontiers in Microbiology 10 . [91]. Mcmurry , L. M. , and Levy , S. B . ( 1987 ) Tn5 insertion in the polynucleotide phosphorylase (pnp) gene in Escherichia coli increases susceptibility to antibiotics , Journal of Bacteriology 169 , 1321 – 1324 . OpenUrl Abstract / FREE Full Text [92]. Wu , N. , Zhang , Y. , Zhang , S. , Yuan , Y. , Liu , S. , Xu , T. , Cui , P. , Zhang , W. , and Zhang , Y . ( 2023 ) Polynucleotide Phosphorylase Mediates a New Mechanism of Persister Formation in Escherichia coli , Microbiology Spectrum 11 . [93]. Ross , J. I. , Eady , E. A. , Cove , J. H. , and Baumberg , S . ( 1995 /02/03) Identification of a chromosomally encoded ABC-transport system with which the staphylococcal erythromycin exporter MsrA may interact , Gene 153 . [94]. Moynié , L. , Leckie , S. M. , McMahon , S. A. , Duthie , F. G. , Koehnke , A. , Taylor , J. W. , Alphey , M. S. , Brenk , R. , Smith , A. D. , and Naismith , J. H . ( 2013 /01/23) Structural Insights into the Mechanism and Inhibition of the β-Hydroxydecanoyl-Acyl Carrier Protein Dehydratase from Pseudomonas aeruginosa , Journal of Molecular Biology 425 . [95]. Moynié , L. , Hope , A. G. , Finzel , K. , Schmidberger , J. , Leckie , S. M. , Schneider , G. , Burkart , M. D. , Smith , A. D. , Gray , D. W. , and Naismith , J. H . ( 2016 / 1 / 16 ) A Substrate Mimic Allows High-Throughput Assay of the FabA Protein and Consequently the Identification of a Novel Inhibitor of Pseudomonas aeruginosa FabA , Journal of Molecular Biology 428 . [96]. Petia Z. Gatzeva-Topalova , Andrew P. May , A. , and Marcelo C. Sousa *. ( September 30 , 2004 ) Crystal Structure of Escherichia coli ArnA (PmrI) Decarboxylase Domain. A Key Enzyme for Lipid A Modification with 4-Amino-4-deoxy-l-arabinose and Polymyxin Resistance†,‡ . [97]. Sonawane , K. D. , Parulekar , R. S. , Malkar , R. S. , Nimbalkar , P. R. , Barage , S. H. , Jadhav , D. B. , Sonawane , K. D. , Parulekar , R. S. , Malkar , R. S. , Nimbalkar , P. R. , Barage , S. H. , and Jadhav , D. B . ( 2014 - 11 -, 20 ) Homology modeling and molecular docking studies of ArnA protein from Erwinia amylovora: role in polymyxin antibiotic resistance , Journal of Plant Biochemistry and Biotechnology 2014 24 : 4 24 . OpenUrl [98]. Mitchell , M. E. , Gatzeva-Topalova , P. Z. , Bargmann , A. D. , Sammakia , T. , and Sousa , M. C. ( July 6 , 2023 ) Targeting the Conformational Change in ArnA Dehydrogenase for Selective Inhibition of Polymyxin Resistance , Biochemistry 62 . [99]. Hinz , A. , Lee , S. , Jacoby , K. , and Manoil , C . ( 2011 ) Membrane Proteases and Aminoglycoside Antibiotic Resistance , Journal of Bacteriology 193 , 4790 – 4797 . OpenUrl Abstract / FREE Full Text [100]. Wessel , A. K. , Yoshii , Y. , Reder , A. , Boudjemaa , R. , Szczesna , M. , Betton , J.-M. , Bernal-Bayard , J. , Beloin , C. , Lopez , D. , Völker , U. , and Ghigo , J.-M . ( 2023 ) Escherichia coli SPFH Membrane Microdomain Proteins HflKC Contribute to Aminoglycoside and Oxidative Stress Tolerance , Microbiology Spectrum 11 . [101]. Mullowney , M. W. , Maltseva , N. I. , Endres , M. , Kim , Y. , Joachimiak , A. , and Crofts , T. S . ( 2022 ) Functional and Structural Characterization of Diverse NfsB Chloramphenicol Reductase Enzymes from Human Pathogens , Microbiology Spectrum 10 . [102]. Crofts , T. S. , Sontha , P. , King , A. O. , Wang , B. , Biddy , B. A. , Zanolli , N. , Gaumnitz , J. , and Dantas , G . ( 2019 ) Discovery and Characterization of a Nitroreductase Capable of Conferring Bacterial Resistance to Chloramphenicol , Cell Chemical Biology 26 , 559 – 570.e556 . OpenUrl CrossRef PubMed [103]. Wan , Y. , Mills , E. , Leung , R. C. Y. , Vieira , A. , Zhi , X. , Croucher , N. J. , Woodford , N. , Jauneikaite , E. , Ellington , M. J. , and Sriskandan , S . ( 2021 ) Alterations in chromosomal genes nfsA, nfsB, and ribE are associated with nitrofurantoin resistance in Escherichia coli from the United Kingdom , Microb Genom 7 . [104]. Zhang , X. , Zhang , Y. , Wang , F. , Wang , C. , Chen , L. , Liu , H. , Lu , H. , Wen , H. , and Zhou , T . ( 2018 /08/01) Unravelling mechanisms of nitrofurantoin resistance and epidemiological characteristics among Escherichia coli clinical isolates , International Journal of Antimicrobial Agents 52 . [105]. Han , J. , Sahin , O. , Barton , Y.-W. , and Zhang , Q . ( 2008 ) Key Role of Mfd in the Development of Fluoroquinolone Resistance in Campylobacter jejuni , PLoS Pathogens 4 , e1000083 . OpenUrl CrossRef PubMed [106]. Lee , G. H. , Jeong , J. Y. , Chung , J. W. , Nam , W. H. , Lee , S. M. , Pak , J. H. , Choi , K. D. , Song , H. J. , Jung , H. Y. , and Kim , J. H . ( 2009 ) The Helicobacter pylori Mfd protein is important for antibiotic resistance and DNA repair , Diagn Microbiol Infect Dis 65 , 454 – 456 . OpenUrl CrossRef PubMed [107]. Ragheb , M. N. , Thomason , M. K. , Hsu , C. , Nugent , P. , Gage , J. , Samadpour , A. N. , Kariisa , A. , Merrikh , C. N. , Miller , S. I. , Sherman , D. R. , and Merrikh , H . ( 2019 ) Inhibiting the Evolution of Antibiotic Resistance , Mol Cell 73 , 157 – 165 e155 . OpenUrl CrossRef PubMed [108]. Potrykus , J. , Baranska , S. , and Wegrzyn , G . ( 2002 ) Inactivation of the acrA gene is partially responsible for chloramphenicol sensitivity of Escherichia coli CM2555 strain expressing the chloramphenicol acetyltransferase gene , Microb Drug Resist 8 , 179 – 185 . OpenUrl CrossRef PubMed Web of Science [109]. Xu , L. , Henriksen , C. , Mebus , V. , Guérillot , R. , Petersen , A. , Jacques , N. , Jiang , J.-H. , Derks , R. J. E. , Sánchez-López , E. , Giera , M. , Leeten , K. , Stinear , T. P. , Oury , C. , Howden , B. P. , Peleg , A. Y. , and Frees, D. ( 2023 ) Novel determinant of antibiotic resistance: a clinically selected Staphylococcus aureus clpP mutant survives daptomycin treatment by reducing binding of the antibiotic and adapting a rod-shaped morphology , Cold Spring Harbor Laboratory . [110]. Avila-Sakar , A. J. , Misaghi , S. , Wilson-Kubalek , E. M. , Downing , K. H. , Zgurskaya , H. , Nikaido , H. , and Nogales , E . ( 2001 /10/01) Lipid-Layer Crystallization and Preliminary Three-Dimensional Structural Analysis of AcrA, the Periplasmic Component of a Bacterial Multidrug Efflux Pump , Journal of Structural Biology 136 . [111]. Ip , H. , Stratton , K. , Zgurskaya , H. , and Liu , J . ( 2003 ) pH-induced Conformational Changes of AcrA, the Membrane Fusion Protein of Escherichia coli Multidrug Efflux System , Journal of Biological Chemistry 278 , 50474 – 50482 . OpenUrl Abstract / FREE Full Text [112]. Mikolosko , J. , Bobyk , K. , Zgurskaya , H. I. , and Ghosh , P . ( 2006 ) Conformational Flexibility in the Multidrug Efflux System Protein AcrA , Structure 14 , 577 – 587 . OpenUrl CrossRef PubMed [113]. Whiteway , J. , Koziarz , P. , Veall , J. , Sandhu , N. , Kumar , P. , Hoecher , B. , and Lambert , I. B . ( 1998 ) Oxygen-insensitive nitroreductases: analysis of the roles of nfsA and nfsB in development of resistance to 5-nitrofuran derivatives in Escherichia coli , J Bacteriol 180 , 5529 – 5539 . OpenUrl Abstract / FREE Full Text [114]. Day , M. A. , Jarrom , D. , Christofferson , A. J. , Graziano , A. E. , Anderson , J. L. R. , Searle , P. F. , Hyde , E. I. , and White , S. A . ( 2021 ) The structures of E. coli NfsA bound to the antibiotic nitrofurantoin; to 1,4-benzoquinone and to FMN , Biochem J 478 , 2601 – 2617 . OpenUrl CrossRef PubMed [115]. Dulyayangkul , P. , Sealey , J. E. , Lee , W. W. Y. , Satapoomin , N. , Reding , C. , Heesom , K. J. , Williams , P. B. , and Avison , M. B . ( 2024 ) Improving nitrofurantoin resistance prediction in Escherichia coli from whole-genome sequence by integrating NfsA/B enzyme assays , Antimicrobial Agents and Chemotherapy 68 . [116]. Cho , H. , Choi , Y. , Min , K. , Son , J. B. , Park , H. , Lee , H. H. , and Kim , S . ( 2020 ) Over-activation of a nonessential bacterial protease DegP as an antibiotic strategy , Communications Biology 3 . [117]. Frees , D. , Gerth , U. , and Ingmer , H . ( 2014 / 03 / 01 ) Clp chaperones and proteases are central in stress survival, virulence and antibiotic resistance of Staphylococcus aureus , International Journal of Medical Microbiology 304 . [118]. Zheng , J. , Wu , Y. , Lin , Z. , Wang , G. , Jiang , S. , Sun , X. , Tu , H. , Yu , Z. , and Qu , D . ( 2020 ) ClpP participates in stress tolerance, biofilm formation, antimicrobial tolerance, and virulence of Enterococcus faecalis , BMC Microbiology 20 . [119]. Brossier , F. , Boudinet , M. , Jarlier , V. , Petrella , S. , and Sougakoff , W . ( 2016 ) Comparative study of enzymatic activities of new KatG mutants from low-and high-level isoniazid-resistant clinical isolates of Mycobacterium tuberculosis , Tuberculosis 100 , 15 – 24 . OpenUrl CrossRef PubMed [120]. Munir , A. , Wilson , M. T. , Hardwick , S. W. , Chirgadze , D. Y. , Worrall , J. A. R. , Blundell , T. L. , and Chaplin , A. K . ( 2021 ) Using cryo-EM to understand antimycobacterial resistance in the catalase-peroxidase (KatG) from Mycobacterium tuberculosis , Structure 29 , 899 – 912.e894 . OpenUrl CrossRef [121]. Escalante , P. , McKean-Cowdin , R. , Ramaswamy , S. V. , Williams-Bouyer , N. , Teeter , L. D. , Jones , B. E. , and Graviss , E. A . ( 2013 ) Can mycobacterial katG genetic changes in isoniazid-resistant tuberculosis influence human disease features? , The International Journal of Tuberculosis and Lung Disease 17 . [122]. Toğay , S. Ö. , Ay , M. , Güneşer , O. , Yüceer , Y. K. , Toğay , S. Ö. , Ay , M. , Güneşer , O. , and Yüceer , Y. K . ( 2016 - 12 - 31 ) Investigation of antimicrobial activity and entA and entB genes in Enterococcus faecium and Enterococcus faecalis strains isolated from naturally fermented Turkish white cheeses , Food Science and Biotechnology 2016 25 : 6 25 . OpenUrl [123]. Amaretti , A. , Righini , L. , Candeliere , F. , Musmeci , E. , Bonvicini , F. , Gentilomi , G. A. , Rossi , M. , and Raimondi , S . ( 2020 ) Antibiotic Resistance, Virulence Factors, Phenotyping, and Genotyping of Non-Escherichia coli Enterobacterales from the Gut Microbiota of Healthy Subjects , International Journal of Molecular Sciences 21 , 1847 . OpenUrl CrossRef PubMed [124]. Iwaya , M. , and Strominger , J. L . ( 1977 ) Simultaneous deletion of D-alanine carboxypeptidase IB-C and penicillin-binding component IV in a mutant of Escherichia coli K12 ., Proceedings of the National Academy of Sciences 74 , 2980 – 2984 . OpenUrl Abstract / FREE Full Text [125]. Barbosa , C. , Gregg , K. S. , and Woods , R. J . ( 2020 ) Variants in ampD and dacB lead to in vivo resistance evolution of Pseudomonas aeruginosa within the central nervous system , Journal of Antimicrobial Chemotherapy 75 , 3405 – 3408 . OpenUrl CrossRef PubMed [126]. Oppezzo , O. J. , and Antón , D. N . ( 1995 ) Involvement of cysB and cysE genes in the sensitivity of Salmonella typhimurium to mecillinam , Journal of Bacteriology 177 , 4524 – 4527 . OpenUrl Abstract / FREE Full Text [127]. Chen , C. , Yan , Q. , Tao , M. , Shi , H. , Han , X. , Jia , L. , Huang , Y. , Zhao , L. , Wang , C. , Ma , X. , and Ma , Y . ( 2019 /06/01) Characterization of serine acetyltransferase (CysE) from methicillin-resistant Staphylococcus aureus and inhibitory effect of two natural products on CysE , Microbial Pathogenesis 131 . [128]. Rakonjac , J. , Milic , M. , and Savic , D. J . ( 1991 ) cysB and cysE mutants of Escherichia coli K12 show increased resistance to novobiocin , Molecular and General Genetics MGG 228 , 307 – 311 . OpenUrl CrossRef [129]. Turnbull , A. L. , Surette , M. G. , Turnbull , A. L. , and Surette , M. G . ( 2008 /11/01) l-Cysteine is required for induced antibiotic resistance in actively swarming Salmonella enterica serovar Typhimurium , Microbiology 154 . [130]. Jain , N. , Rodriguez , A. C. , Kimsawatde , G. , Seleem , M. N. , Boyle , S. M. , and Sriranganathan , N . ( 2011 ) Effect of entF deletion on iron acquisition and erythritol metabolism by Brucella abortus 2308 , FEMS Microbiology Letters 316 , 1 – 6 . OpenUrl CrossRef PubMed [131]. Nas , M. Y. , Cianciotto , N. P. , Nas , M. Y. , and Cianciotto , N. P . ( 2017 /11/01) Stenotrophomonas maltophilia produces an EntC-dependent catecholate siderophore that is distinct from enterobactin , Microbiology 163 . [132]. ↵ Perez-Riverol , Y. , Bandla , C. , Kundu , D. J. , Kamatchinathan , S. , Bai , J. , Hewapathirana , S. , John , N. S. , Prakash , A. , Walzer , M. , Wang , S. , and Vizcaino , J. A . ( 2025 ) The PRIDE database at 20 years: 2025 update , Nucleic Acids Res 53 , D543 – D553 . OpenUrl CrossRef PubMed [133]. ↵ Deutsch , E. W. , Bandeira , N. , Perez-Riverol , Y. , Sharma , V. , Carver , J. J. , Mendoza , L. , Kundu , D. J. , Wang , S. , Bandla , C. , Kamatchinathan , S. , Hewapathirana , S. , Pullman , B. S. , Wertz , J. , Sun , Z. , Kawano , S. , Okuda , S. , Watanabe , Y. , MacLean , B. , MacCoss , M. J. , Zhu , Y. , Ishihama , Y. , and Vizcaino , J. A . ( 2023 ) The ProteomeXchange consortium at 10 years: 2023 update , Nucleic Acids Res 51 , D1539 – D1548 . OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted July 01, 2025. Download PDF Supplementary Material 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 Phase-Specific Antibiotic Resistance Mechanisms in an Escherichia coli B Strain 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 Phase-Specific Antibiotic Resistance Mechanisms in an Escherichia coli B Strain Manuel Terrazas-López , Vanessa Aitken , Tonya N. Zeczycki , Eda Koculi bioRxiv 2025.06.30.662419; doi: https://doi.org/10.1101/2025.06.30.662419 Share This Article: Copy Citation Tools Phase-Specific Antibiotic Resistance Mechanisms in an Escherichia coli B Strain Manuel Terrazas-López , Vanessa Aitken , Tonya N. Zeczycki , Eda Koculi bioRxiv 2025.06.30.662419; doi: https://doi.org/10.1101/2025.06.30.662419 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 Biochemistry Subject Areas All Articles Animal Behavior and Cognition (7635) Biochemistry (17691) Bioengineering (13892) Bioinformatics (41936) Biophysics (21452) Cancer Biology (18588) Cell Biology (25504) Clinical Trials (138) Developmental Biology (13378) Ecology (19899) Epidemiology (2067) Evolutionary Biology (24320) Genetics (15609) Genomics (22506) Immunology (17736) Microbiology (40394) Molecular Biology (17181) Neuroscience (88605) Paleontology (666) Pathology (2832) Pharmacology and Toxicology (4824) Physiology (7641) Plant Biology (15153) Scientific Communication and Education (2045) Synthetic Biology (4294) Systems Biology (9825) Zoology (2271)