Fitness Cost and Compensation Mechanism of Sulfonamide Resistance Genes (Sul1, Sul2, and Sul3) in Escherichia Coli

Fitness Cost and Compensation Mechanism of Sulfonamide Resistance Genes (Sul1, Sul2, and Sul3) in Escherichia Coli | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Fitness Cost and Compensation Mechanism of Sulfonamide Resistance Genes (Sul1, Sul2, and Sul3) in Escherichia Coli Yuqiao Zhou, Jiehong Fang, Zaeim Davood, Daofeng Qu, Jianzhong Han This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-504582/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Oct, 2021 Read the published version in Environmental Microbiology → Version 1 posted You are reading this latest preprint version Abstract Background: The fitness cost of antibiotic resistance is a crucial factor to determine the evolutionary success of resistant bacteria. Even if the selection pressure in the environment is eliminated, drug-resistant bacteria can still compensate for drug-resistant genes' fitness cost through some compensation mechanisms. The fitness cost and compensatory evolution of antibiotic resistance are an essential part of bacterial evolution. Result: Engineered bacteria with the same genetic background that carry sulfonamide resistance gene were generated to explore the fitness cost of sulfonamide resistance gene in Escherichia coli. There were significant differences in the protein expression of the two-component system pathway (fliZ, fliA, fliC and lrhA), folate biosynthesis pathway (sul1, sul2 and sul3), ABC transporter system (ugpC, rbsA and gsiA), and outer membrane pore protein OmpD through the comparative analysis of differential proteins compared to sensitive bacteria. Thus, we could speculate the possible fitness compensation mechanism. Finally, qRT-PCR was used to verify the functions of some differential proteins at the transcriptional level. Conclusions: The study of fitness cost assessment and compensatory evolution of bacterial resistance will help understand the development track of antibiotic resistance of bacterial pathogens and provide new ideas for solving antibiotic resistance issues. General Microbiology sul genes fitness cost Escherichia coli differentially expressed protein qRT-PCR Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The spread of MDR (multidrug-resistant) amongst Gram-negative bacteria has emerged as one of the most pressing global public health threats [1]. As synthetic broad-spectrum antimicrobial agents, sulfonamides have inhibitory activity against most G + and G - bacteria [2]. While sulfonamides play a substantial role in preventing and treating animal bacterial diseases, bacteria have developed extensive and robust resistance to them [3]. Bacteria usually produce resistance to sulfonamides through two different strategies: (i) gene mutation and (ii) gene substitution. In gene mutation, the gene fol P of dihydrosphenoic acid synthase (DHPS), located on the chromosome, produces drug resistance [4]. In gene substitution, drug resistance is generated by obtaining DHPS replacement genes sul1 , sul2 and sul3. The expression products of the latter mechanism have a lower affinity for sulfonamides [5]. The second mechanism of sulfonamides resistance is more widespread [6] . Several recent reports have shown that sul gene is found and prevalent in Escherichia coli from human and livestock origins, and it may have stable vertical and horizontal transmissions [6].The base sequences of sul1 , sul2 , and sul3 have about 50% homology with each other [7]. The primary mechanism of drug-resistant gene transmission is the horizontal or vertical transfer of mobile genetic elements carrying drug-resistant genes [8]. Gene sul has been identified on both chromosomes and plasmids. At present, plasmids, integrons, transposons and other mobile gene elements (MGEs) have been found to be related to the transmission of sulfonamides resistance [9]. The sul gene originated from animal-associated bacteria. It has been frequently isolated from livestock and is supposedly sustained by sulfonamide's heavy usage in the veterinary sectors [10, 11]. The genes sul1 and sul2 were first published by Swedbery and Radstrom, respectively, in 1983 and 1985. Sul2 was more common and widely distributed in clinical Escherichia coli than the gene sul1 [12]. The sul1 gene is mainly associated with other resistance genes on the integron retention fragment [13]. The sul2 gene is often associated with streptomycin resistance genes found in small, unbound plasmids with a broad host range [14]. In 1990, Martin CT found a gene similar to sul1 in Mycobacterium , but the gene had missed the promoter codon, and the codon had been inserted further upstream, so the gene was named sul3 gene [15] . China has a vast territory with numerous pig farms, making the detection range of sulfonamides in pig faeces samples difficult. Furthermore, the highest detection concentration can reach 50 mg/kg [16-18] . The development of antibiotic resistance often comes with a fitness cost, defined by reduced competitive ability in an antibiotic-free environment. This phenomenon usually allows the fitter, often susceptible strain to outcompete the resistant one [19]. Given the biological basis of transmission and epidemic, the fitness cost and compensation mechanism of sul gene in E. coli have not been reported. The present study aims to investigate the fitness cost of sulfonamide resistance genes in E. coli . bacterial competition in vitro test was used to assess the fitness cost of sul genes in E. coli. The label-free proteomics and real-time fluorescent quantitative PCR were applied to explore adaptive changes of sul gene in E. coli strains at different protein expression levels. This study may help to explain the possible adaptive mechanism of these genes, which provides theoretical support to control their transfer and spread. Methods Bacterial strain and plasmids E. coli DH5α and E. coli BL21 were used as the clone and the expression strains respectively. The sulfonamide resistant genes sul1 , sul2 and sul3 were inserted into polyclonal sites of the constitutive expression plasmid pET23a (Novagen, USA) using BamH I and Sac I enzymes through the gene recombination method. Recombinant plasmids pET23a- sul1 , pET23a- sul2 and pET23a- sul3 carrying sulfonamide resistance genes were transformed into E. coli BL21 cells by heat shock transformation method. Single colonies of the transformed plasmids were selected and inoculated into LB liquid medium and incubated at 37°C and 200 rpm for 5 h. General primers of the vector T7 promoter and terminator were used for colony PCR identification. Antimicrobial susceptibility test MICs were determined by broth dilution method with an inoculum of 10 5 CFU ml −1 in LB medium. Each test was repeated three times at least. Plasmid stability and growth kinetics Transconjugants E. coli BL21: pET23a- sul1 , E. coli BL21: pET23a- sul2 and E. coli BL21, pET23a- sul3 and E. coli BL21: pET23a were propagated by serial transfer for 14 days of passage. The culture broths were serially diluted in 0.9% saline and plated onto LB agar without sulfonamide. Approximately 100 colonies were randomly chosen and replica plated onto sulfonamide-containing and antibiotic-free LB agar plates. The percentage of plasmid retention was calculated by dividing the number of colonies on sulfonamide-containing LB agar by the total number of colonies patched. Three biological replicates were included for each group. The growth kinetics of E. coli BL21 and its transformants carrying the plasmids pET23a- sul1 , pET23a- sul2 , pET23a- sul3 and pET23a were studied by inoculation in 150 mL of fresh LB broth. The initial optical density at 600 nm (OD 600 ) was 0.6, and the bacterial growth was monitored by hourly recording OD 600 for 24 h at 37 ℃. Experiments were performed in triplicate. Motility test Engineered bacteria and control strains were inoculated into MH liquid medium. When the initial OD 600 value was 0.3, 5 μL aliquot of bacterial suspension was taken and inoculated into the center of a 0.4% MH agar medium plate (Ø=9 cm) and incubated at 37℃ for 48 h. In vitro competition experiments To assess the fitness effect of sul1, sul2, sul3 in the bacterial host, E. coli BL21: pET23a- sul1 , E. coli BL21: pET23a- sul2 and E. coli BL21 pET23a- sul3 were used to compete against E. coli BL21: pET23a. E. coli BL21: pET23a was mixed with the control strain in the ratio of 1:1 by volume. The bacterial suspension was transferred to fresh LB medium at a volume ratio of 1:100 every 24 h for 5-6 times. Before each transfer, the mixed bacterial suspension was plated on the non-resistant LB medium to calculate the total number of colonies. 100 single colonies were picked from the non-resistant plate and inoculated on the LB resistant plate (4 mg/ mL sulfamethoxazole concentration). The number of sulfamethoxazole resistant colonies was calculated by Eg. 1. Eq. 1. Selection coefficient = [ln(E/R)t - ln(E/R)0]/T In which, E is experimental group cell number, R is control group cell number, and T is passage number. Preparation and quantitative analysis of proteome samples The engineered and control strains were cultured for 7 h to the logarithmic growth phase. Bacterial suspensions were centrifuged at 5000 × g and 4 °C for 10 min. After decanting the supernatant, cells were thoroughly washed twice by the addition of PBS and subsequent centrifugation under the same condition. Each sample added a moderate amount of SDT lysis buffer (SDS, dithiothreitol, Tris) for 60 s. The sample was then ultrasonized for 10 s at each interval of 15 s for 10 cycles. After 15 min in boiling water bath, the sample was centrifuged at 14000 ×g for 40 min. After centrifugation, the supernatant of each sample was quantified with BCA kit and analysed by SDS–PAGE. Enzymatic hydrolysis of proteins A 30-μL aliquot of protein solution was taken from each sample, DTT was added to the final concentration of 100 mM, boiled in water for 5 min. Two hundred μL UA Buffer was added and mixed well, then transferred into a 10 kD ultrafiltration tube and centrifuged at 14000 × g for 15 min. One hundred μL IAA buffer (100 mM IAA in UA) was added, followed by 600 ×g oscillation for 60 s. The dark reaction was carried out for 30 min followed by centrifugation at 14000 × g for 15 min. Subsequently, 100 μL UA buffer was added and centrifuged at 14000 × g for 15 min, repeated twice. One hundred μL NH 4 HCO 3 solution 25 mM was added and centrifuged at 14000 × g for 15 min, repeated twice. Forty μL Trypsin buffer (4 μg Trypsin in 40 μL 100 mM NH 4 HCO 3 ) was added, mixed well at 600 × g for 60 s, and placed at 37 ℃ for 16-18 h. The collecting tube was replaced and centrifuged at 14000 × g for 15 min. Then, 40 μL 25 mM NH 4 HCO 3 was added and centrifuged at 14000 × g for 15 min, and the filtrate was collected. The peptides were desalted by C 18 cartridge, lyophilized, and redissolved in 40 μL 0.1% formic acid solution. The peptides were quantified by photometry at OD 280 . Mass spectrometry A 5 μg sample of each group was analyzed in triplicate using LC/MS/ MS. The separation was done using an EASY-nLC HPLC (Thermo Scientific, USA). Flowing phases A was 0.1% (v/v) formic acid (Fluka), phases B was acetonitrile solution containing 0.1% (v/v) formic acid. MS/MS was performed using a Q-Exactive Mass Spectrometer (Thermo Scientific, USA). The chromatographic column was balanced with 95% liquid A. The samples were loaded by the automatic sampler to the loading column and fractionated by the analytical column at the liquid A flow rate of 300 nL/min. The mass spectrometer was operated in positive mode using a data-dependent acquisition method. The scanning range of the parent ions was 300–1800 m/z. After each full scan, the 20 most intense precursors were selected for fragmentation. The dynamic exclusion for MS/MS was set as 60 s. The resolution of MS1 was 70,000 for 200 m/z. MS2 had unit mass resolution. Bioinformatics analysis MaxQuant software was used for database identification and quantitative analysis. The relevant parameters and instructions were as follows: the maximum number of permissible leak-cut sites was 2; the mass tolerance of primary ion and secondary ion plasmid were 6 and 20 ppm, respectively. All databases of the library are uniprot_Escherichia_coli_1124415_20180910.fasta. The quantitative strength values of unique peptide and razor peptide were adopted to carry out protein quantification using the LFQ algorithm. After the proteomic data were analyzed and processed, the screened differential proteins were annotated and attributed to protein function. Transcriptional level verification of differentially expressed proteins The total RNA extraction method was carried out according to the total RNA extraction kit for biological bacteria (Baitek). Real-time PCR primers were designed for 16 related genes and 16S DNA using Primer 5.0 software. The primers used in qRT-PCR are presented in supplementary materials. Results Contribution of sul to sulfonamide resistance MIC tests confirmed that the sulfonamide resistance gene was generated successfully. The sulfonamide resistance gene expressed normally and donated sulfisoxazole resistance to the cells. E. coli BL21: pET23a- sul1 , E. coli BL21: pET23a- sul2 and E. coli BL21: pET23a- sul3 had MIC values of 4 mg/mL for sulfisoxazole. The fitness cost of sulfonamide resistance genes in Escherichia coli The plasmid stability of four genetically engineered strains was analyzed under free selection pressure and sulfisoxazole inhibition concentration. The results showed no plasmid loss in strains E. coli BL21: pET23a- sul1 , E. coli BL21: pET23a- sul2 and control strains E. coli BL21: pET23a, but the plasmid loss was 76% ± 4% after 10 days of subculture. No plasmid loss was observed in the control strain E. coli BL21: PET23a at the subinhibitory concentration (5 % MIC, 12.5 μg/ mL). The growth curve of 4 genetically engineered strains was drawn under adequate nutrition and in the absence of drug selection pressure and other influencing factors. E. coli BL21: pET23a- Sul3 showed a reduction in growth ability; however, the other two strains showed no significant difference from the control strain ( P 0.05). In the same way, E. coli BL21: PET23a- sul3 had the lowest microbiota diameter and its motor ability was decreased compared with the other three strains ( P <0.05). E. coli BL21: PET23a- sul1 , E. coli BL21: PET23a- sul2 and the control strain E. coli BL21: PET23a showed no significant difference in colony circle diameter ( P 0.05). E. coli BL21: PET23A was used as the control, and three pairs of competitive tests were carried out using the method of combining resistance plate screening and PCR verification. An inevitable decrease was observed in adaptability by combining the above experimental results and comparing E. coli BL21: PET23a- sul3 with E. coli BL21: PET23a- sul1 and E. coli BL21: PET23a- sul2 . Quality control analysis of proteome A total of 2446 proteins were identified by uniprot_Escherichia_coli_1124415_20180910 database. The number of proteins identified in 12 samples of 4 groups is shown in the table 1. The 2446 proteins identified by LC-MS/MS were compared quantitatively by MaxQuant software LFQ algorithm. Bioinformatics analysis of differentially expressed proteins Gene Ontology (GO) functional annotation analysis In terms of cell composition, the protein changes were mainly located in the cell membrane and cell-matrix among all six groups. These changes are reflected primarily in catalytic activity and binding functions, which involved cells' metabolic process. KEGG pathway analysis In the paired comparison between the engineered strains carrying sul1 , sul2 and control strains, proteins involved in the pathways were relatively concentrated. Apart from the glucose and nucleotide metabolisms, they were also involved in the ABC transporter and the two-component systems. However, in the paired comparison between E. coli BL21: PET23a- sul3 strains in the experimental and control groups, the metabolic pathways were relatively dispersed, mainly focused on glucose and nucleotide metabolism pathways. Analysis of the variation trend of differentially expressed proteins In E. coli BL21: pET23a- sul1 and E. coli BL21: pET23a- sul2 strains, proteins fliA, fliC and their upstream transcriptional activator fliZ in the two-component system were significantly upregulated. However, lrhA , the transcriptional inhibitor expressed by type I pili, was significantly downregulated. The protein SUL1, which is involved in folic acid metabolism, was significantly upregulated in E. coli BL21: pET23a- sul1 strain. Besides, molybtrexate adenosine transferase, molybtrexate synthase catalyzed subunit and cyclopyranxate monophosphate synthase were upregulated by 1.7 and 1.6 times, respectively. 2-amino-4-hydroxy-6-hydroxymethyl dihydroteropterine diphosphate kinase was changed from zero to zero, and 4-amino-4-deoxy branched-acid lythase was altered from existing to non-existing. The protein expression of QueE (7-carboxy-7-deazaguanine synthase), which is involved in the pathway of folic acid metabolism, was downregulated 1.8 times in E. coli BL21: pET23a- sul2 strain. E. coli BL21: pET23a- sul3 strain significantly reduced the number of differential proteins involved in the pathway of folic acid metabolism, and significantly upregulated the expression of dihydrospteric acid synthase SUL3 In this study, obvious differences were observed in the ABC transporter system pathway by KEGG pathway analysis. The expressions of ATP-binding proteins ugpC, rbsA and gsiA , which are closely related to energy supply, were significantly increased in E. coli BL21: pET23a- sul1 or E. coli BL21: pET23a- sul2 , but there was no significant change in E. coli BL21: pET23a- sul3 . Analysis of individual differentially expressed proteins showed that the differential expression ratio of the outer membrane pore protein ompD was the highest among all the proteins. In E. coli BL21: pET23a- sul3 , the quantitative strength of ompD LFQ protein was 1.7 × 10 9 , which was increased by 29.93 times compared with the control strain E. coli BL21: pET23a. Transcriptional level analysis of differentially expressed proteins Genes fliZ , fliA , fliC , lrhA (bacteria movement-related), sul1, sul2, sul3 (folic acid metabolic pathways related), moaB (molybdenum with poison adenosine transferase), moaE (molybdenum with poison synthetase catalytic subunit), moaC (pyran ring poison monosodium phosphate synthetase), APT94_19870 (dihydrogen pteridine diphosphate kinase), C5P43_33360 , ugpC, rbsA, gsiA (ATP binding protein related) and ompD (outer membrane channel proteins), and other 16 genes were chosen for Real-time PCR analysis. Based on 16s rDNA internal genes, 2 -ΔΔCt relative quantitative method was used for comparative quantitative analysis of target genes. The comparative quantitative analysis results showed that the variation trend of target gene mRNA level expression obtained by real-time PCR analysis was the same as that obtained by Label-free proteomic analysis (Figure 6). Discussion Sulfonamide resistance genes sul1 , sul2 , and sul3 can mediate high levels of drug resistance of Escherichia coli to sulfonamides. Several studies have demonstrated these three drug resistance genes are widespread in the pork industry [20-23]. This study was to investigate the biological basis of the prevalence and transmission of sulfonamide-resistant genes sul1 , sul2 and sul3 . The sulfonamide resistance genetic engineering strains with the same genetic background were constructed by gene cloning and recombination techniques. In recent years, the construction of drug-resistant genes in engineered bacteria has been more and more used to research the fitness cost of drug-resistant genes in strains. Nang et al recombined mobile colistin resistance ( mcr-1 ) on a low-copy and broad-spectrum host range vector pBBR1MCS-5 and switched it to Klebsiella pneumonia B5055 to study the fitness cost of mcr-1 gene [24]. As expected, drug-resistant genetically engineered bacteria constructed in this study showed high resistance to sulfonamide in MIC tests. The evolution and persistence of antibiotic resistance in the bacterial population depend on a complex calculus rooted in biological fitness cost associated with the resistance and the impact of the resistance pressure. In the presence of high levels of antibiotics, access to antibiotic resistance mechanisms offers an adaptive advantage over susceptible competitors [25]. However, there are often deleterious effects in the absence of antibiotic resistance mechanisms, typically observed as an increased generation time and reduced survival in a host [19] . These observations suggest that susceptible, higher fitness populations should generally outcompete resistant bacteria after removing selection pressure. However, several factors can cause the stability of this resistance: 1) co-selection of resistance genes with other functions that confer a fitness advantage [26, 27]; 2) presence of resistances that impose a very low or no cost [28, 29]; 3) compensatory evolution that reduces the fitness cost, often without loss of the resistance [30, 31] Studies have shown that the change of fitness cost will affect normal physiological functions of bacteria to a certain extent, such as growth ability, movement ability, virulence and plasmid stability. In general, there was no significant difference between E. coli BL21: pET23a- sul1 , E. coli BL21: pET23a- sul2 and control E. coli BL21: pET23a ( P >0.05). E. coli BL21: pET23a- sul3 showed a significant ( P <0.05) decrease in growth capacity, locomotion capacity, and loss of plasmid. E. coli BL21: pET23a- sul3 also showed a certain fitness cost in the in vitro competition test. Sul1 and sul2 had lower fitness cost, which illustrated one of the important reasons for the widespread prevalence of these two genes from the biological basis. Theoretically, suppose the adaptability of specific genotypes of drug-resistant bacteria is lower than the average adaptability of the population. In that case, it will be a disadvantage in competition, and these genotypes may be eliminated gradually. However, it is noteworthy that E. coli BL21: pET23a- sul3 adaptability was restored in response to sulfonamides selection pressure. Therefore, if the selective pressure of sulfa drugs persists in nature, the prevalence of sul3 gene will gradually increase. Bacterial proteome changes dynamically with growth environment and growth stage, and there are different protein expression profiles under various conditions. Label-free quantitative proteomics was used to explore the possible fitness mechanisms further. The two-component system (TCS) is the main pathway for bacteria to complete chemotactic movement [32, 33]. It was found that in E. coli BL21: pET23a- sul1 and E. coli BL21: pET23a- sul2 strains, proteins fliA , flic and their upstream transcriptional activator fliZ were significantly upregulated in the TCS. However, lrhA , a transcriptional inhibitor expressed by type I pili, was significantly down-regulated. The increase of FliZ protein expression can promote the expression of FliA and FliC, increase the synthesis of flagellin, and make the cells gain better motility and improve the cells survival [34, 35]. As a transcriptional regulatory inhibitor of the flagellum, motility and chemotactic gene lrhA can promote type I pili and biofilm formation by inhibiting lrhA [36, 37]. However, there was no significant change in these genes in E. coli BL21: pET23a- sul3 , which may be one reason for its lower adaptability than that of sul1 and sul2 . Most prokaryotes must synthesize folate themselves. DHPS is the target enzyme of sulfonamides, which binds to it and inhibits its activity, to reveal antibacterial effects [38]. Sul1 , sul2 and sul3 are dhps substitution genes, and their expression products all act as dihydrosphenoate synthase. The function of dihydrosphenoate synthase substitution enzyme exerted by SUL3 may not be sufficient to balance the influence of 2-amino-4-hydroxy-6-hydroxymethyl dihydrosphenoidine diphosphate kinase overexpression. Silent expression of 4-amino-4-deoxybranch acid cleasthase on the folic acid metabolism pathway may affect the synthesis of folic acid and reducing adaptability. Multidrug efflux transporters are prevalent in the antibiotic resistance mechanisms as they bestow an ability to bacteria to evade most current therapies [39, 40]. ATP-binding cassette transporters are essential biomolecule transport systems in organisms that rely on ATP hydrolysis to obtain energy for transporting various biomolecules [39]. In this study, the energy supply by ATP binding protein UgpC, RbsA, GsiA in E. coli BL21: pET23a- sul1 and E. coli BL21: pET23a - sul2 increased significantly. After obtaining exogenous sul1 and sul2 genes, the strain was subjected to fine regulation by ATP energy supply system in the logarithmic phase. However, there was no noticeable change in E. coli BL21: pET23a - sul3 strains. The changes of the ABC transporter system are closely related to the strain's physiological state and growth conditions. Therefore, the association between the ABC transporter system and bacterial adaptability needs to be further verified. Outer membrane pore protein OmpD is involved in discharging bacterial metabolic poisons, which are mainly caused by metabolic changes and insufficient bacterial carbon sources. OmpD is overexpressed when metabolism is inhibited, or carbon sources are not sufficient [41]. In this study, the expression of OmpD protein in E. coli BL21: pET23a- sul3 was significantly increased. Thus, it was speculated that E. coli BL21: pET23a- sul3 metabolism was inhibited, leading to insufficient carbon source for bacterial metabolism. Accordingly, it was attempted to upregulate OmpD to participate in the excretion of toxin in bacterial metabolism, which consumed energy and affected its fitness cost. Conclusions In this study, the compensation mechanism of sulfonamide resistance genes in E. coli was explored in constructed engineered bacteria carrying sul1 , sul2 and sul3 genes. The results showed that the fitness cost of sul3 was significantly higher than sul1 and sul2 ( P <0.05). The sulfonamide resistant genes obtained by bacteria directly affect the folic acid metabolism pathway of E. coli . sul1 and sul2 genes make more differential proteins involved in folic acid synthesis. Meanwhile, ATP-binding proteins such as UgpC, RbsA and GsiA, which are closely related to energy supply, were upregulated, making folic acid synthesis in bacteria more accurately regulated. In addition, the flagella-related proteins FliA and FliC and their upstream transcriptional activator FliZ in the two-component system were significantly upregulated, while the type I pili transcriptional inhibitor LrhA was downregulated so that the bacteria could obtain better motility and maintain their survival. The fitness compensation mechanism of sul3 was relatively weak. The considerably upregulated OmpD of E. coli BL21: pET23a- sul3 indicated that the bacteria's metabolism was inhibited and energy was insufficient, showing a high adaptive cost, leading lower prevalence of sul3 than sul1 and sul2 . Declarations Acknowledgements Not applicable Authors’ contributions Y.Q.Z constructed the engineering strains. Y.Q.Z. performed MICs, plasmid stability, growth kinetics and motility test. J.H.F. performed competition experiments. Y.Q.Z. and J.H.F. performed bioinformatics analysis and transcriptional level verification. D.F.Q. and J.Z.H. supervised the study. Y.Q.Z., D.F.Q. and Z.D. wrote the manuscript. The authors read and approve the final manuscript. Funding Not applicable Availability of data and materials Not applicable Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. 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Hegedus, Survivability of vancomycin resistant enterococci and fitness cost of vancomycin resistance acquisition. J Clin Pathol, 2005. 58 (7): p. 744-6. Criswell, D., et al., Mutations conferring aminoglycoside and spectinomycin resistance in Borrelia burgdorferi. Antimicrob Agents Chemother, 2006. 50 (2): p. 445-52. Wiesch, P., Compensation of Fitness Costs and Reversibility of Antibiotic Resistance Mutations. . Antimicrobial Agents & Chemotherapy, 2010. 54(2) : p. 2085-92. Andersson, D.I. and D. Hughes, Persistence of antibiotic resistance in bacterial populations. FEMS Microbiol Rev, 2011. 35 (5): p. 901-11. Parkinson, J.S. and E.C. Kofoid, Communication modules in bacterial signaling proteins. annual reviews genetic, 1992(26): p. 71-112. Tierney, A.R. and P.N. Rather, Roles of two-component regulatory systems in antibiotic resistance. Future Microbiology, 2019. 14(6) : p. 533-552. Jubelin, G., et al., FliZ is a global regulatory protein affecting the expression of flagellar and virulence genes in individual Xenorhabdus nematophila bacterial cells. PLoS Genet, 2013. 9 (10): p. e1003915. Xia, Q., et al., Adaptive mechanisms of Campylobacter jejuni to erythromycin treatment. BMC Microbiology 2013. 13 : p. 133-149. D. Lehnen, C.B., et al., LrhA as a new transcriptional key regulator of flagella,motility and chemotaxis. Molecular Microbiology, 2002. 45(2) : p. 521-523. Blumer, C., et al., Regulation of type 1 fimbriae synthesis and biofilm formation by the transcriptional regulator LrhA of Escherichia coli. Microbiology (Reading), 2005. 151 (Pt 10): p. 3287-3298. Moukhlis, R., et al., Linking Pneumocystis jiroveci sulfamethoxazole resistance to the alleles of the DHPS gene using functional complementation in Saccharomyces cerevisiae. Clin Microbiol Infect, 2010. 16 (5): p. 501-7. Orelle, C., K. Mathieu, and J.M. Jault, Multidrug ABC transporters in bacteria. Res Microbiol, 2019. 170 (8): p. 381-391. Wasi, M., et al., ABC Transporter Genes Show Upregulated Expression in Drug-Resistant Clinical Isolates of Candida auris: A Genome-Wide Characterization of ATP-Binding Cassette (ABC) Transporter Genes. Frontiers In Microbiology, 2019. 10 : p. 1445-1456. Santiviago, C.A., et al., Global regulation of the Salmonella enterica serovar typhimurium major porin, OmpD. J Bacteriol, 2003. 185 (19): p. 5901-5. Tables Table 1 The significant differentially expressed proteins in recombinant bacteria Protein Name Pathway or Function. Quantitative results of LFQ protein Differential expression a a S1 s2 s3 S1/a s2/a s3/a SUL1 Folate biosynthesis 8.50E+05 1.01E+11 / / 1.18E+05* / / SUL2 Folate biosynthesis 4.52E+07 / 7.47E+09 / / 165.15 * / SUL3 Folate biosynthesis 1.18E+05 / / 2.85E+10 / / 2.41E+05 FliZ Bacterial motility 1.18E+09 1.74E+09 1.85E+09 1.20E+09 1.47 * 1.56 * 1.02 FliA Bacterial motility 2.52E+07 4.52E+07 4.93E+07 2.44E+07 1.79 * 1.96 * 0.97 FliC Bacterial motility 1.63E+08 6.83E+08 3.47E+08 1.60E+08 4.19 * 2.13 * 0.98 LlrhA Bacterial motility 1.90E+08 1.81E+07 4.81E+07 1.69E+08 0.10 * 0.25 * 0.89 MoaB Folate biosynthesis 1.16E+09 1.96E+09 2.51E+09 / 1.68 * 2.16 * / MoaE Folate biosynthesis 1.77E+08 2.88E+08 3.71E+08 2.70E+08 1.62 * 2.10 * 1.52* MoaC Folate biosynthesis 3.33E+08 5.27E+08 5.54E+08 / 1.58 * 1.66 * / APT94_19870 Folate biosynthesis / 2.16E+07 2.04E+07 / / / / C5P43_33360 Folate biosynthesis 2.42E+07 / / / / / / UgpC ABC transporter system 2.60E+07 5.48E+07 3.92E+07 3.36E+07 2.11 * 1.51 * 1.29 RbsA ABC transporter system 5.10E+06 1.32E+07 1.12E+07 5.14E+06 2.60 * 2.20 * 1.01 GsiA ABC transporter system 4.43E+07 6.83E+07 7.18E+07 4.38E+07 1.54 * 1.62 * 0.99 OmpD Outer membrane pore protein 5.61E+07 1.08E+08 1.02E+08 1.68E+09 1.92 * 1.81 * 29.93* Abbreviation: > 1 represents up-regulation, < 1 represents down-regulation; * represents significant difference. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-504582","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":27941721,"identity":"b9e02027-2bdf-4701-97e7-e3c7da8d682c","order_by":0,"name":"Yuqiao Zhou","email":"","orcid":"","institution":"Zhejiang Gongshang University","correspondingAuthor":false,"prefix":"","firstName":"Yuqiao","middleName":"","lastName":"Zhou","suffix":""},{"id":27941722,"identity":"ea82e12d-2559-44b6-9c7c-53085d8baee7","order_by":1,"name":"Jiehong Fang","email":"","orcid":"","institution":"Zhejiang Gongshang University","correspondingAuthor":false,"prefix":"","firstName":"Jiehong","middleName":"","lastName":"Fang","suffix":""},{"id":27941723,"identity":"2b75e1c5-bced-4ddf-8beb-a4eec9c66e29","order_by":2,"name":"Zaeim Davood","email":"","orcid":"","institution":"Zhejiang Gongshang University","correspondingAuthor":false,"prefix":"","firstName":"Zaeim","middleName":"","lastName":"Davood","suffix":""},{"id":27941724,"identity":"94be14a2-026c-4a01-a59b-bdb4c9045884","order_by":3,"name":"Daofeng Qu","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-6416-603X","institution":"Zhejiang Gongshang University","correspondingAuthor":true,"prefix":"","firstName":"Daofeng","middleName":"","lastName":"Qu","suffix":""},{"id":27941725,"identity":"7954867d-dde5-40ca-bc2b-ec72976319ec","order_by":4,"name":"Jianzhong Han","email":"","orcid":"","institution":"Zhejiang Gongshang University","correspondingAuthor":false,"prefix":"","firstName":"Jianzhong","middleName":"","lastName":"Han","suffix":""}],"badges":[],"createdAt":"2021-05-07 10:36:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-504582/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-504582/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1111/1462-2920.15783","type":"published","date":"2021-10-12T10:07:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":9440062,"identity":"294d8ef3-6a41-421d-b2ae-abc594819e46","added_by":"auto","created_at":"2021-05-21 15:39:55","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45387,"visible":true,"origin":"","legend":"stability of the vector in the gene engineering strains. (A) Results of plasmid stability test without sulfamethoxazole selection pressure; (B)Results of plasmid stability test under the subinhibitory concentration (5% MIC, 12.5 μg/ mL) of control strain E. coli BL21: PET23a.","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-504582/v1/98808e9d6381bd89e154bd77.jpg"},{"id":9440251,"identity":"bbc1d29a-6561-4d29-b491-20fd9f798065","added_by":"auto","created_at":"2021-05-21 15:42:55","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":41915,"visible":true,"origin":"","legend":"The growth curve of 4 strains of genetically engineered bacteria under the condition of adequate nutrition, no drug selection pressure and no other influencing factors\n \n","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-504582/v1/a2fac6d436cb0d75db4db4d2.jpg"},{"id":9440254,"identity":"6e7b894c-1611-4bea-8ef4-8be9ec3e6c00","added_by":"auto","created_at":"2021-05-21 15:42:55","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":36166,"visible":true,"origin":"","legend":"Selection coefficients for the gene engineering strains against the control strain. (A) Selection coefficient without sulfonamide drug selection pressure; (B) Selection coefficient of control strain E. coli BL21: PET23a under subinhibition concentration\n \n","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-504582/v1/32b0f3423e667c2b09c91b92.jpg"},{"id":9440252,"identity":"6eddf025-12db-4414-9b86-f4639607a698","added_by":"auto","created_at":"2021-05-21 15:42:55","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":53271,"visible":true,"origin":"","legend":"SDS-PAGE electrophoresis of total protein. a1, a2 and a3 represent three biologically repeated total proteins of strain E. coli BL21: PET23a. S1-1, S1-2 and S1-3 represented total protein of three biologically repeated strains of E. coli BL21:pET23a-sul1; S2-1, S2-2 and S2-3 represented the total protein of three biologically repeated strains of E. coli BL21: pET23a-Sul2; S3-1, S3-2 and S3-3 represent three biologically repeated total proteins of strain E. coli BL21: pET23a-Sul3.","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-504582/v1/43db136becaf2b255774c6b4.jpg"},{"id":9440253,"identity":"de32f285-01f3-484c-a719-78d4e49966d5","added_by":"auto","created_at":"2021-05-21 15:42:55","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":68573,"visible":true,"origin":"","legend":"Basepeak spectrogram analysis of Q-Exactive mass spectrometry. (A) E. coli BL21: pET23a; (B) E. coli BL21:pET23a-sul1;(C) E. coli BL21: pET23a-sul2; (D) E. coli BL21: pET23a-sul3","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-504582/v1/4d797b0d05bf918a0d7963f6.jpg"},{"id":9440064,"identity":"0b3f47bb-ff7c-400c-b659-17a2e57aa01a","added_by":"auto","created_at":"2021-05-21 15:39:56","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":262097,"visible":true,"origin":"","legend":"Comparison of the differential expression between mRNA level and protein level. A：SUL1；B：SUL2；C：SUL3；D：Fliz；E：FliA；F：FliC；G：LrhA；H：MoaB；I：MoaE；J：MoaC；K：APT94_19870；L：C5P43_33360；M：UgpC；O：RbsA；P：GsiA；Q：OmpD\n\n","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-504582/v1/4559bdee0670fd1f463eacdb.jpg"},{"id":17492549,"identity":"db19c7ae-9dc1-4d6d-8ff1-59112710fa2f","added_by":"auto","created_at":"2022-01-20 10:07:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":751138,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-504582/v1/e0e9d1f4-f8c5-445f-b5b2-a7884dde034d.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eFitness Cost and Compensation Mechanism of Sulfonamide Resistance Genes (Sul1, Sul2, and Sul3) in Escherichia Coli\u003c/p\u003e","fulltext":[{"header":"Introduction ","content":"\u003cp\u003eThe spread of MDR (multidrug-resistant) amongst Gram-negative bacteria has emerged as one of the most pressing global public health threats [1]. As synthetic broad-spectrum antimicrobial agents, sulfonamides have inhibitory activity against most G\u003csup\u003e+\u003c/sup\u003e and G\u003csup\u003e-\u003c/sup\u003e bacteria [2]. While sulfonamides play a substantial role in preventing and treating animal bacterial diseases, bacteria have developed extensive and robust resistance to them [3]. Bacteria usually produce resistance to sulfonamides through two different strategies: (i) gene mutation and (ii) gene substitution. In gene mutation, the gene \u003cem\u003efol\u003c/em\u003eP of dihydrosphenoic acid synthase (DHPS), located on the chromosome, produces drug resistance [4]. In gene substitution, drug resistance is generated by obtaining DHPS replacement genes \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e and \u003cem\u003esul3. \u003c/em\u003eThe expression products of the latter mechanism have a lower affinity for sulfonamides [5]. The second mechanism of sulfonamides resistance is more widespread [6]\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral recent reports have shown that \u003cem\u003esul \u003c/em\u003egene is found and prevalent in \u003cem\u003eEscherichia coli\u003c/em\u003e from human and livestock origins, and it may have stable vertical and horizontal transmissions [6].The base sequences of \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e, and \u003cem\u003esul3\u003c/em\u003e have about 50% homology with each other [7]. The primary mechanism of drug-resistant gene transmission is the horizontal or vertical transfer of mobile genetic elements carrying drug-resistant genes [8]. Gene\u003cem\u003e sul\u003c/em\u003e has been identified on both chromosomes and plasmids. At present, plasmids, integrons, transposons and other mobile gene elements (MGEs) have been found to be related to the transmission of sulfonamides resistance [9].\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003esul\u003c/em\u003e gene originated from animal-associated bacteria. It has been frequently isolated from livestock and is supposedly sustained by sulfonamide's heavy usage in the veterinary sectors [10, 11]. The genes \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e were first published by Swedbery and Radstrom, respectively, in 1983 and 1985. \u003cem\u003eSul2\u003c/em\u003e was more common and widely distributed in clinical \u003cem\u003eEscherichia coli\u003c/em\u003e than the gene \u003cem\u003esul1\u003c/em\u003e [12]. The \u003cem\u003esul1\u003c/em\u003e gene is mainly associated with other resistance genes on the integron retention fragment [13]. The \u003cem\u003esul2\u003c/em\u003e gene is often associated with streptomycin resistance genes found in small, unbound plasmids with a broad host range [14]. In 1990, Martin CT found a gene similar to \u003cem\u003esul1\u003c/em\u003e in \u003cem\u003eMycobacterium\u003c/em\u003e, but the gene had missed the promoter codon, and the codon had been inserted further upstream, so the gene was named \u003cem\u003esul3\u003c/em\u003e gene [15]\u003cstrong\u003e.\u003c/strong\u003e China has a vast territory with numerous pig farms, making the detection range of sulfonamides in pig faeces samples difficult. Furthermore, the highest detection concentration can reach 50 mg/kg [16-18]\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe development of antibiotic resistance often comes with a fitness cost, defined by reduced competitive ability in an antibiotic-free environment. This phenomenon usually allows the fitter, often susceptible strain to outcompete the resistant one [19]. Given the biological basis of transmission and epidemic, the fitness cost and compensation mechanism of \u003cem\u003esul\u003c/em\u003e gene in \u003cem\u003eE. coli\u003c/em\u003e have not been reported.\u003c/p\u003e\n\u003cp\u003eThe present study aims to investigate the fitness cost of sulfonamide resistance genes in \u003cem\u003eE. coli\u003c/em\u003e. bacterial competition \u003cem\u003ein vitro\u003c/em\u003e test was used to assess the fitness cost of \u003cem\u003esul\u003c/em\u003e genes in \u003cem\u003eE. coli. \u003c/em\u003eThe label-free proteomics and real-time fluorescent quantitative PCR were applied to explore adaptive changes of \u003cem\u003esul\u003c/em\u003e gene in\u003cem\u003e E. coli \u003c/em\u003estrains at different protein expression levels. This study may help to explain the possible adaptive mechanism of these genes, which provides theoretical support to control their transfer and spread.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eBacterial strain and plasmids\u003c/h3\u003e\n\u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e DH5\u0026alpha; and \u003cem\u003eE. coli\u003c/em\u003e BL21 were used as the clone and the expression strains respectively. The sulfonamide resistant genes \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e and \u003cem\u003esul3\u003c/em\u003e were inserted into polyclonal sites of the constitutive expression plasmid pET23a (Novagen, USA) using BamH I and Sac I enzymes through the gene recombination method. Recombinant plasmids pET23a-\u003cem\u003esul1\u003c/em\u003e, pET23a-\u003cem\u003esul2\u003c/em\u003e and pET23a-\u003cem\u003esul3\u003c/em\u003e carrying sulfonamide resistance genes were transformed into \u003cem\u003eE. coli\u003c/em\u003e BL21 cells by heat shock transformation method. Single colonies of the transformed plasmids were selected and inoculated into LB liquid medium and incubated at 37\u0026deg;C and 200 rpm for 5 h. General primers of the vector T7 promoter and terminator were used for colony PCR identification.\u003c/p\u003e\n\u003ch3\u003eAntimicrobial susceptibility test\u003c/h3\u003e\n\u003cp\u003eMICs were determined by broth dilution method with an inoculum of 10\u003csup\u003e5 \u003c/sup\u003eCFU ml\u003csup\u003e\u0026minus;1 \u003c/sup\u003ein LB medium. Each test was repeated three times at least.\u003c/p\u003e\n\u003ch3\u003ePlasmid stability and growth kinetics\u003c/h3\u003e\n\u003cp\u003eTransconjugants \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e, \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e BL21, pET23a-\u003cem\u003esul3\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a were propagated by serial transfer for 14 days of passage. The culture broths were serially diluted in 0.9% saline and plated onto LB agar without sulfonamide. Approximately 100 colonies were randomly chosen and replica plated onto sulfonamide-containing and antibiotic-free LB agar plates. The percentage of plasmid retention was calculated by dividing the number of colonies on sulfonamide-containing LB agar by the total number of colonies patched. Three biological replicates were included for each group. The growth kinetics of \u003cem\u003eE. coli\u003c/em\u003e BL21 and its transformants carrying the plasmids pET23a-\u003cem\u003esul1\u003c/em\u003e, pET23a-\u003cem\u003esul2\u003c/em\u003e, pET23a-\u003cem\u003esul3\u003c/em\u003e and pET23a were studied by inoculation in 150 mL of fresh LB broth. The initial optical density at 600 nm (OD\u003csub\u003e600\u003c/sub\u003e) was 0.6, and the bacterial growth was monitored by hourly recording OD\u003csub\u003e600 \u003c/sub\u003efor 24 h at 37 ℃. Experiments were performed in triplicate.\u003c/p\u003e\n\u003ch3\u003eMotility test\u003c/h3\u003e\n\u003cp\u003eEngineered bacteria and control strains were inoculated into MH liquid medium. When the initial OD\u003csub\u003e600\u003c/sub\u003e value was 0.3, 5 \u0026mu;L aliquot of bacterial suspension was taken and inoculated into the center of a 0.4% MH agar medium plate (\u0026Oslash;=9 cm) and incubated at 37℃ for 48 h.\u003c/p\u003e\n\u003ch3\u003e\u003cem\u003eIn vitro\u003c/em\u003e competition experiments\u003c/h3\u003e\n\u003cp\u003eTo assess the fitness effect of \u003cem\u003esul1, sul2, sul3\u003c/em\u003e in the bacterial host, \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e, \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e BL21 pET23a-\u003cem\u003esul3\u003c/em\u003e were used to compete against \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a. \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a was mixed with the control strain in the ratio of 1:1 by volume. The bacterial suspension was transferred to fresh LB medium at a volume ratio of 1:100 every 24 h for 5-6 times. Before each transfer, the mixed bacterial suspension was plated on the non-resistant LB medium to calculate the total number of colonies. 100 single colonies were picked from the non-resistant plate and inoculated on the LB resistant plate (4 mg/ mL sulfamethoxazole concentration). The number of sulfamethoxazole resistant colonies was calculated by Eg. 1.\u003c/p\u003e\n\u003cp\u003eEq. 1.\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Selection coefficient = [ln(E/R)t - ln(E/R)0]/T\u003c/p\u003e\n\u003cp\u003eIn which, E is experimental group cell number, R is control group cell number, and T is passage number.\u003c/p\u003e\n\u003ch3\u003ePreparation and quantitative analysis of proteome samples\u003c/h3\u003e\n\u003cp\u003eThe engineered and control strains were cultured for 7 h to the logarithmic growth phase. Bacterial suspensions were centrifuged at 5000 \u0026times;\u003cem\u003eg\u003c/em\u003e and 4 \u0026deg;C for 10 min. After decanting the supernatant, cells were thoroughly washed twice by the addition of PBS and subsequent centrifugation under the same condition. Each sample added a moderate amount of SDT lysis buffer (SDS, dithiothreitol, Tris) for 60 s. The sample was then ultrasonized for 10 s at each interval of 15 s for 10 cycles. After 15 min in boiling water bath, the sample was centrifuged at 14000 \u003cem\u003e\u0026times;g \u003c/em\u003efor 40 min. After centrifugation, the supernatant of each sample was quantified with BCA kit and analysed by SDS\u0026ndash;PAGE.\u003c/p\u003e\n\u003ch3\u003eEnzymatic hydrolysis of proteins\u003c/h3\u003e\n\u003cp\u003eA 30-\u0026mu;L aliquot of protein solution was taken from each sample, DTT was added to the final concentration of 100 mM, boiled in water for 5 min. Two hundred \u0026mu;L UA Buffer was added and mixed well, then transferred into a 10 kD ultrafiltration tube and centrifuged at 14000 \u0026times;\u003cem\u003eg\u003c/em\u003e for 15 min. One hundred \u0026mu;L IAA buffer (100 mM IAA in UA) was added, followed by 600 \u003cem\u003e\u0026times;g \u003c/em\u003eoscillation for 60 s. The dark reaction was carried out for 30 min followed by centrifugation at 14000 \u0026times;\u003cem\u003eg\u003c/em\u003e for 15 min. Subsequently, 100 \u0026mu;L UA buffer was added and centrifuged at 14000 \u0026times;\u003cem\u003eg\u003c/em\u003e for 15 min, repeated twice. One hundred \u0026mu;L NH\u003csub\u003e4\u003c/sub\u003eHCO\u003csub\u003e3\u003c/sub\u003e solution 25 mM was added and centrifuged at 14000 \u0026times;\u003cem\u003eg \u003c/em\u003efor 15 min, repeated twice. Forty \u0026mu;L Trypsin buffer (4 \u0026mu;g Trypsin in 40 \u0026mu;L 100 mM NH\u003csub\u003e4\u003c/sub\u003eHCO\u003csub\u003e3\u003c/sub\u003e) was added, mixed well at 600 \u0026times;\u003cem\u003eg\u003c/em\u003e for 60 s, and placed at 37 ℃ for 16-18 h. The collecting tube was replaced and centrifuged at 14000 \u0026times;\u003cem\u003eg\u003c/em\u003e for 15 min. Then, 40 \u0026mu;L 25 mM NH\u003csub\u003e4\u003c/sub\u003eHCO\u003csub\u003e3\u003c/sub\u003e was added and centrifuged at 14000 \u0026times;\u003cem\u003eg\u003c/em\u003e for 15 min, and the filtrate was collected. The peptides were desalted by C\u003csub\u003e18\u003c/sub\u003e cartridge, lyophilized, and redissolved in 40 \u0026mu;L 0.1% formic acid solution. The peptides were quantified by photometry at OD\u003csub\u003e280\u003c/sub\u003e.\u003c/p\u003e\n\u003ch3\u003eMass spectrometry\u003c/h3\u003e\n\u003cp\u003eA 5 \u0026mu;g sample of each group was analyzed in triplicate using LC/MS/ MS. The separation was done using an EASY-nLC HPLC (Thermo Scientific, USA). Flowing phases A was 0.1% (v/v) formic acid (Fluka), phases B was acetonitrile solution containing 0.1% (v/v) formic acid. MS/MS was performed using a Q-Exactive Mass Spectrometer (Thermo Scientific, USA). The chromatographic column was balanced with 95% liquid A. The samples were loaded by the automatic sampler to the loading column and fractionated by the analytical column at the liquid A flow rate of 300 nL/min. The mass spectrometer was operated in positive mode using a data-dependent acquisition method. The scanning range of the parent ions was 300\u0026ndash;1800 m/z. After each full scan, the 20 most intense precursors were selected for fragmentation. The dynamic exclusion for MS/MS was set as 60 s. The resolution of MS1 was 70,000 for 200 m/z. MS2 had unit mass resolution.\u003c/p\u003e\n\u003ch3\u003eBioinformatics analysis\u003c/h3\u003e\n\u003cp\u003eMaxQuant software was used for database identification and quantitative analysis. The relevant parameters and instructions were as follows: the maximum number of permissible leak-cut sites was 2; the mass tolerance of primary ion and secondary ion plasmid were 6 and 20 ppm, respectively. All databases of the library are uniprot_Escherichia_coli_1124415_20180910.fasta. The quantitative strength values of unique peptide and razor peptide were adopted to carry out protein quantification using the LFQ algorithm. After the proteomic data were analyzed and processed, the screened differential proteins were annotated and attributed to protein function.\u003c/p\u003e\n\u003ch3\u003eTranscriptional level verification of differentially expressed proteins\u003c/h3\u003e\n\u003cp\u003eThe total RNA extraction method was carried out according to the total RNA extraction kit for biological bacteria (Baitek). Real-time PCR primers were designed for 16 related genes and 16S DNA using Primer 5.0 software. The primers used in qRT-PCR are presented in supplementary materials.\u003c/p\u003e"},{"header":"Results","content":"\u003ch3\u003eContribution of\u003cem\u003e sul\u003c/em\u003e to sulfonamide resistance\u003c/h3\u003e\n\u003cp\u003eMIC tests confirmed that the sulfonamide resistance gene was generated successfully. The sulfonamide resistance gene expressed normally and donated sulfisoxazole resistance to the cells. \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e, \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e had MIC values of 4 mg/mL for sulfisoxazole.\u003c/p\u003e\n\u003ch3\u003eThe fitness cost of sulfonamide resistance genes in \u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/h3\u003e\n\u003cp\u003eThe plasmid stability of four genetically engineered strains was analyzed under free selection pressure and sulfisoxazole inhibition concentration. The results showed no plasmid loss in strains \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e, \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e and control strains \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a, but the plasmid loss was 76% \u0026plusmn; 4% after 10 days of subculture. No plasmid loss was observed in the control strain \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a at the subinhibitory concentration (5 % MIC, 12.5 \u0026mu;g/ mL).\u003c/p\u003e\n\u003cp\u003eThe growth curve of 4 genetically engineered strains was drawn under adequate nutrition and in the absence of drug selection pressure and other influencing factors. \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003eSul3\u003c/em\u003e showed a reduction in growth ability; however, the other two strains showed no significant difference from the control strain (\u003cem\u003eP\u003c/em\u003e 0.05). In the same way, \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a-\u003cem\u003esul3\u003c/em\u003e had the lowest microbiota diameter and its motor ability was decreased compared with the other three strains (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a-\u003cem\u003esul1\u003c/em\u003e, \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a-\u003cem\u003esul2\u003c/em\u003e and the control strain \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a showed no significant difference in colony circle diameter (\u003cem\u003eP\u003c/em\u003e 0.05). \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23A was used as the control, and three pairs of competitive tests were carried out using the method of combining resistance plate screening and PCR verification. An inevitable decrease was observed in adaptability by combining the above experimental results and comparing \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a-\u003cem\u003esul3\u003c/em\u003e with \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a-\u003cem\u003esul1\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a-\u003cem\u003esul2\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003eQuality control analysis of proteome\u003c/h3\u003e\n\u003cp\u003eA total of 2446 proteins were identified by uniprot_Escherichia_coli_1124415_20180910 database. The number of proteins identified in 12 samples of 4 groups is shown in the table 1. The 2446 proteins identified by LC-MS/MS were compared quantitatively by MaxQuant software LFQ algorithm.\u003c/p\u003e\n\u003ch3\u003eBioinformatics analysis of differentially expressed proteins\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eGene Ontology (GO) functional annotation analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn terms of cell composition, the protein changes were mainly located in the cell membrane and cell-matrix among all six groups. These changes are reflected primarily in catalytic activity and binding functions, which involved cells' metabolic process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKEGG pathway analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the paired comparison between the engineered strains carrying \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e and control strains, proteins involved in the pathways were relatively concentrated. Apart from the glucose and nucleotide metabolisms, they were also involved in the ABC transporter and the two-component systems. However, in the paired comparison between \u003cem\u003eE. coli\u003c/em\u003e BL21: PET23a-\u003cem\u003esul3\u003c/em\u003e strains in the experimental and control groups, the metabolic pathways were relatively dispersed, mainly focused on glucose and nucleotide metabolism pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of the variation trend of differentially expressed proteins\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e strains, proteins\u003cem\u003e fliA, fliC \u003c/em\u003eand their upstream transcriptional activator \u003cem\u003efliZ\u003c/em\u003e in the two-component system were significantly upregulated. However, \u003cem\u003elrhA\u003c/em\u003e, the transcriptional inhibitor expressed by type I pili, was significantly downregulated.\u003c/p\u003e\n\u003cp\u003eThe protein SUL1, which is involved in folic acid metabolism, was significantly upregulated in \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e strain. Besides, molybtrexate adenosine transferase, molybtrexate synthase catalyzed subunit and cyclopyranxate monophosphate synthase were upregulated by 1.7 and 1.6 times, respectively. 2-amino-4-hydroxy-6-hydroxymethyl dihydroteropterine diphosphate kinase was changed from zero to zero, and 4-amino-4-deoxy branched-acid lythase was altered from existing to non-existing. The protein expression of QueE (7-carboxy-7-deazaguanine synthase), which is involved in the pathway of folic acid metabolism, was downregulated 1.8 times in \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e strain. \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e strain significantly reduced the number of differential proteins involved in the pathway of folic acid metabolism, and significantly upregulated the expression of dihydrospteric acid synthase SUL3\u003c/p\u003e\n\u003cp\u003eIn this study, obvious differences were observed in the ABC transporter system pathway by KEGG pathway analysis. The expressions of ATP-binding proteins \u003cem\u003eugpC, rbsA\u003c/em\u003e and \u003cem\u003egsiA\u003c/em\u003e, which are closely related to energy supply, were significantly increased in \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e or \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e, but there was no significant change in \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eAnalysis of individual differentially expressed proteins showed that the differential expression ratio of the outer membrane pore protein \u003cem\u003eompD\u003c/em\u003e was the highest among all the proteins. In \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e, the quantitative strength of \u003cem\u003eompD\u003c/em\u003e LFQ protein was 1.7 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e, which was increased by 29.93 times compared with the control strain \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a.\u003c/p\u003e\n\u003ch3\u003eTranscriptional level analysis of differentially expressed proteins\u003c/h3\u003e\n\u003cp\u003eGenes \u003cem\u003efliZ\u003c/em\u003e, \u003cem\u003efliA\u003c/em\u003e, \u003cem\u003efliC\u003c/em\u003e, \u003cem\u003elrhA\u003c/em\u003e (bacteria movement-related), \u003cem\u003esul1, sul2, sul3\u003c/em\u003e (folic acid metabolic pathways related), \u003cem\u003emoaB\u003c/em\u003e (molybdenum with poison adenosine transferase), \u003cem\u003emoaE\u003c/em\u003e (molybdenum with poison synthetase catalytic subunit), \u003cem\u003emoaC\u003c/em\u003e (pyran ring poison monosodium phosphate synthetase), \u003cem\u003eAPT94_19870 \u003c/em\u003e(dihydrogen pteridine diphosphate kinase), \u003cem\u003eC5P43_33360\u003c/em\u003e, \u003cem\u003eugpC, rbsA, gsiA \u003c/em\u003e(ATP binding protein related) and \u003cem\u003eompD\u003c/em\u003e (outer membrane channel proteins), and other 16 genes were chosen for Real-time PCR analysis. Based on 16s rDNA internal genes, 2\u003csup\u003e-\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e relative quantitative method was used for comparative quantitative analysis of target genes.\u003c/p\u003e\n\u003cp\u003eThe comparative quantitative analysis results showed that the variation trend of target gene mRNA level expression obtained by real-time PCR analysis was the same as that obtained by Label-free proteomic analysis (Figure 6).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSulfonamide resistance genes \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e, and \u003cem\u003esul3\u003c/em\u003e can mediate high levels of drug resistance of \u003cem\u003eEscherichia coli\u003c/em\u003e to sulfonamides. Several studies have demonstrated these three drug resistance genes are widespread in the pork industry [20-23]. This study was to investigate the biological basis of the prevalence and transmission of sulfonamide-resistant genes \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e and \u003cem\u003esul3\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eThe sulfonamide resistance genetic engineering strains with the same genetic background were constructed by gene cloning and recombination techniques. In recent years, the construction of drug-resistant genes in engineered bacteria has been more and more used to research the fitness cost of drug-resistant genes in strains. Nang et al recombined mobile colistin resistance (\u003cem\u003emcr-1\u003c/em\u003e) on a low-copy and broad-spectrum host range vector pBBR1MCS-5 and switched it to \u003cem\u003eKlebsiella pneumonia \u003c/em\u003eB5055 to study the fitness cost of \u003cem\u003emcr-1\u003c/em\u003e gene [24]. As expected, drug-resistant genetically engineered bacteria constructed in this study showed high resistance to sulfonamide in MIC tests.\u003c/p\u003e\n\u003cp\u003eThe evolution and persistence of antibiotic resistance in the bacterial population depend on a complex calculus rooted in biological fitness cost associated with the resistance and the impact of the resistance pressure. In the presence of high levels of antibiotics, access to antibiotic resistance mechanisms offers an adaptive advantage over susceptible competitors [25]. However, there are often deleterious effects in the absence of antibiotic resistance mechanisms, typically observed as an increased generation time and reduced survival in a host [19]\u003cstrong\u003e.\u003c/strong\u003e These observations suggest that susceptible, higher fitness populations should generally outcompete resistant bacteria after removing selection pressure. However, several factors can cause the stability of this resistance: 1) co-selection of resistance genes with other functions that confer a fitness advantage [26, 27]; 2) presence of resistances that impose a very low or no cost [28, 29]; 3) compensatory evolution that reduces the fitness cost, often without loss of the resistance [30, 31]\u003c/p\u003e\n\u003cp\u003eStudies have shown that the change of fitness cost will affect normal physiological functions of bacteria to a certain extent, such as growth ability, movement ability, virulence and plasmid stability. In general, there was no significant difference between \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e, \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e and control \u003cem\u003eE. coli \u003c/em\u003eBL21: pET23a (\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05). \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e showed a significant (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) decrease in growth capacity, locomotion capacity, and loss of plasmid. \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e also showed a certain fitness cost in the \u003cem\u003ein vitro\u003c/em\u003e competition test. \u003cem\u003eSul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e had lower fitness cost, which illustrated one of the important reasons for the widespread prevalence of these two genes from the biological basis. Theoretically, suppose the adaptability of specific genotypes of drug-resistant bacteria is lower than the average adaptability of the population. In that case, it will be a disadvantage in competition, and these genotypes may be eliminated gradually. However, it is noteworthy that \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e adaptability was restored in response to sulfonamides selection pressure. Therefore, if the selective pressure of sulfa drugs persists in nature, the prevalence of \u003cem\u003esul3\u003c/em\u003e gene will gradually increase.\u003c/p\u003e\n\u003cp\u003eBacterial proteome changes dynamically with growth environment and growth stage, and there are different protein expression profiles under various conditions. Label-free quantitative proteomics was used to explore the possible fitness mechanisms further.\u003c/p\u003e\n\u003cp\u003eThe two-component system (TCS) is the main pathway for bacteria to complete chemotactic movement [32, 33]. It was found that in \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul2\u003c/em\u003e strains, proteins \u003cem\u003efliA\u003c/em\u003e, \u003cem\u003eflic\u003c/em\u003e and their upstream transcriptional activator \u003cem\u003efliZ\u003c/em\u003e were significantly upregulated in the TCS. However,\u003cem\u003e lrhA\u003c/em\u003e, a transcriptional inhibitor expressed by type I pili, was significantly down-regulated. The increase of FliZ protein expression can promote the expression of FliA and FliC, increase the synthesis of flagellin, and make the cells gain better motility and improve the cells survival [34, 35]. As a transcriptional regulatory inhibitor of the flagellum, motility and chemotactic gene \u003cem\u003elrhA\u003c/em\u003e can promote type I pili and biofilm formation by inhibiting \u003cem\u003elrhA\u003c/em\u003e [36, 37]. However, there was no significant change in these genes in \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e, which may be one reason for its lower adaptability than that of \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eMost prokaryotes must synthesize folate themselves. DHPS is the target enzyme of sulfonamides, which binds to it and inhibits its activity, to reveal antibacterial effects [38]. \u003cem\u003eSul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e and \u003cem\u003esul3\u003c/em\u003e are \u003cem\u003edhps\u003c/em\u003e substitution genes, and their expression products all act as dihydrosphenoate synthase. The function of dihydrosphenoate synthase substitution enzyme exerted by SUL3 may not be sufficient to balance the influence of 2-amino-4-hydroxy-6-hydroxymethyl dihydrosphenoidine diphosphate kinase overexpression. Silent expression of 4-amino-4-deoxybranch acid cleasthase on the folic acid metabolism pathway may affect the synthesis of folic acid and reducing adaptability.\u003c/p\u003e\n\u003cp\u003eMultidrug efflux transporters are prevalent in the antibiotic resistance mechanisms as they bestow an ability to bacteria to evade most current therapies [39, 40]. ATP-binding cassette transporters are essential biomolecule transport systems in organisms that rely on ATP hydrolysis to obtain energy for transporting various biomolecules [39]. In this study, the energy supply by ATP binding protein UgpC, RbsA, GsiA in \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul1\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a - \u003cem\u003esul2\u003c/em\u003e increased significantly. After obtaining exogenous \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e genes, the strain was subjected to fine regulation by ATP energy supply system in the logarithmic phase. However, there was no noticeable change in\u003cem\u003e E. coli \u003c/em\u003eBL21: pET23a -\u003cem\u003esul3\u003c/em\u003e strains. The changes of the ABC transporter system are closely related to the strain's physiological state and growth conditions. Therefore, the association between the ABC transporter system and bacterial adaptability needs to be further verified.\u003c/p\u003e\n\u003cp\u003eOuter membrane pore protein OmpD is involved in discharging bacterial metabolic poisons, which are mainly caused by metabolic changes and insufficient bacterial carbon sources. OmpD is overexpressed when metabolism is inhibited, or carbon sources are not sufficient [41]. In this study, the expression of OmpD protein in \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e was significantly increased. Thus, it was speculated that \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e metabolism was inhibited, leading to insufficient carbon source for bacterial metabolism. Accordingly, it was attempted to upregulate OmpD to participate in the excretion of toxin in bacterial metabolism, which consumed energy and affected its fitness cost.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, the compensation mechanism of sulfonamide resistance genes in \u003cem\u003eE. coli\u003c/em\u003e was explored in constructed engineered bacteria carrying \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e and \u003cem\u003esul3\u003c/em\u003e genes. The results showed that the fitness cost of \u003cem\u003esul3\u003c/em\u003e was significantly higher than \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). The sulfonamide resistant genes obtained by bacteria directly affect the folic acid metabolism pathway of \u003cem\u003eE. coli\u003c/em\u003e. \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e genes make more differential proteins involved in folic acid synthesis. Meanwhile, ATP-binding proteins such as UgpC, RbsA and GsiA, which are closely related to energy supply, were upregulated, making folic acid synthesis in bacteria more accurately regulated. In addition, the flagella-related proteins FliA and FliC and their upstream transcriptional activator FliZ in the two-component system were significantly upregulated, while the type I pili transcriptional inhibitor LrhA was downregulated so that the bacteria could obtain better motility and maintain their survival. The fitness compensation mechanism of \u003cem\u003esul3\u003c/em\u003e was relatively weak. The considerably upregulated OmpD of \u003cem\u003eE. coli\u003c/em\u003e BL21: pET23a-\u003cem\u003esul3\u003c/em\u003e indicated that the bacteria's metabolism was inhibited and energy was insufficient, showing a high adaptive cost, leading lower prevalence of \u003cem\u003esul3\u003c/em\u003e than \u003cem\u003esul1\u003c/em\u003e and \u003cem\u003esul2\u003c/em\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.Q.Z constructed the engineering strains. Y.Q.Z. performed MICs, plasmid stability, growth kinetics and motility test. J.H.F. performed competition experiments. Y.Q.Z. and J.H.F. performed bioinformatics analysis and transcriptional level verification. D.F.Q. and J.Z.H. supervised the study. Y.Q.Z., D.F.Q. and Z.D. wrote the manuscript. The authors read and approve the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eZhejiang Gongshang University, Hangzhou 310035, PR China, [email protected]\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Zhejiang Gongshang University, Hangzhou 310035, PR China, [email protected]\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eZhejiang Gongshang University, Hangzhou 310035, PR China, [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eShrivastava., S. 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Jault, \u003cem\u003eMultidrug ABC transporters in bacteria.\u003c/em\u003e Res Microbiol, 2019. \u003cstrong\u003e170\u003c/strong\u003e(8): p. 381-391.\u003c/li\u003e\n\u003cli\u003eWasi, M., et al., \u003cem\u003eABC Transporter Genes Show Upregulated Expression in Drug-Resistant Clinical Isolates of Candida auris: A Genome-Wide Characterization of ATP-Binding Cassette (ABC) Transporter Genes.\u003c/em\u003e Frontiers In Microbiology, 2019. \u003cstrong\u003e10\u003c/strong\u003e: p. 1445-1456.\u003c/li\u003e\n\u003cli\u003eSantiviago, C.A., et al., \u003cem\u003eGlobal regulation of the Salmonella enterica serovar typhimurium major porin, OmpD.\u003c/em\u003e J Bacteriol, 2003. \u003cstrong\u003e185\u003c/strong\u003e(19): p. 5901-5.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 The significant differentially expressed proteins in recombinant bacteria\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" width=\"98\"\u003e\n\u003cp\u003eProtein Name\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"96\"\u003e\n\u003cp\u003ePathway or Function.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" width=\"308\"\u003e\n\u003cp\u003eQuantitative results of LFQ protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"206\"\u003e\n\u003cp\u003eDifferential expression\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003ea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003eS1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003es2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003es3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003eS1/a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003es2/a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003es3/a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u003cem\u003eSUL1\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eFolate biosynthesis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e8.50E+05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e\u0026nbsp;1.01E+11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.18E+05*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"71\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u003cem\u003eSUL2\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eFolate biosynthesis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e4.52E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e7.47E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e165.15 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u003cem\u003eSUL3\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eFolate biosynthesis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e1.18E+05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e2.85E+10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e2.41E+05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eFliZ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eBacterial motility\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e1.18E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.74E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e1.85E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.20E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.47 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e1.56 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e1.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eFliA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eBacterial motility\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e2.52E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e4.52E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e4.93E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e2.44E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.79 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e1.96 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e0.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eFliC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eBacterial motility\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e1.63E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e6.83E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e3.47E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.60E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e4.19 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e2.13 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e0.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eLlrhA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eBacterial motility\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e1.90E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.81E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e4.81E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.69E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.10 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e0.25 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e0.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eMoaB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eFolate biosynthesis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e1.16E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.96E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e2.51E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.68 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e2.16 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eMoaE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eFolate biosynthesis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e1.77E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.88E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e3.71E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e2.70E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.62 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e2.10 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e1.52*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eMoaC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eFolate biosynthesis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e3.33E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e5.27E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e5.54E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.58 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e1.66 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eAPT94_19870\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eFolate biosynthesis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.16E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e2.04E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eC5P43_33360\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eFolate biosynthesis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e2.42E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eUgpC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eABC transporter system\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e2.60E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e5.48E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e3.92E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e3.36E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e2.11 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e1.51 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e1.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eRbsA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eABC transporter system\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e5.10E+06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.32E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e1.12E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e5.14E+06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e2.60 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e2.20 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eGsiA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eABC transporter system\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e4.43E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e6.83E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e7.18E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e4.38E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.54 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e1.62 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e0.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eOmpD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eOuter membrane pore protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e5.61E+07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.08E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e1.02E+08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.68E+09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e1.92 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e1.81 *\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e29.93*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"0\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: \u0026gt; 1 represents up-regulation, \u0026lt; 1 represents down-regulation; * represents significant difference.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sul genes, fitness cost, Escherichia coli, differentially expressed protein, qRT-PCR","lastPublishedDoi":"10.21203/rs.3.rs-504582/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-504582/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The fitness cost of antibiotic resistance is a crucial factor to determine the evolutionary success of resistant bacteria. Even if the selection pressure in the environment is eliminated, drug-resistant bacteria can still compensate for drug-resistant genes' fitness cost through some compensation mechanisms. The fitness cost and compensatory evolution of antibiotic resistance are an essential part of bacterial evolution.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResult: \u003c/strong\u003eEngineered bacteria with the same genetic background that carry sulfonamide resistance gene were generated to explore the fitness cost of sulfonamide resistance gene in Escherichia coli. There were significant differences in the protein expression of the two-component system pathway (fliZ, fliA, fliC and lrhA), folate biosynthesis pathway (sul1, sul2 and sul3), ABC transporter system (ugpC, rbsA and gsiA), and outer membrane pore protein OmpD through the comparative analysis of differential proteins compared to sensitive bacteria. Thus, we could speculate the possible fitness compensation mechanism. Finally, qRT-PCR was used to verify the functions of some differential proteins at the transcriptional level.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e The study of fitness cost assessment and compensatory evolution of bacterial resistance will help understand the development track of antibiotic resistance of bacterial pathogens and provide new ideas for solving antibiotic resistance issues.\u003c/p\u003e","manuscriptTitle":"Fitness Cost and Compensation Mechanism of Sulfonamide Resistance Genes (Sul1, Sul2, and Sul3) in Escherichia Coli","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-05-21 15:39:53","doi":"10.21203/rs.3.rs-504582/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"57131718-1122-403f-b76e-15c4fefbdb3b","owner":[],"postedDate":"May 21st, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":4488158,"name":"General Microbiology"}],"tags":[],"updatedAt":"2022-01-20T10:07:24+00:00","versionOfRecord":{"articleIdentity":"rs-504582","link":"https://doi.org/10.1111/1462-2920.15783","journal":{"identity":"environmental-microbiology","isVorOnly":true,"title":"Environmental Microbiology"},"publishedOn":"2021-10-12 10:07:24","publishedOnDateReadable":"October 12th, 2021"},"versionCreatedAt":"2021-05-21 15:39:53","video":"","vorDoi":"10.1111/1462-2920.15783","vorDoiUrl":"https://doi.org/10.1111/1462-2920.15783","workflowStages":[]},"version":"v1","identity":"rs-504582","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-504582","identity":"rs-504582","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}