Figures
Abstract
Propelled by global climate changes, the shrimp industry has been facing tremendous losses in production due to various disease outbreaks, particularly early mortality syndrome (EMS), a disease caused by Vibrio parahaemolyticus AHPND. Not only is the use of antibiotics as EMS control agents not yet been proven successful, but the overuse and misuse of antibiotics could also worsen one of the most challenging global health issues—antimicrobial resistance. To circumvent antibiotic usage, anti-lipopolysaccharide factor isoform 3 (ALFPm3), an antimicrobial peptide (AMP) derived from the shrimp innate immune system, was proposed as an antibiotic alternative for EMS control. However, prolonged use of AMPs could also lead to bacterial cross resistance with life-saving antibiotics used in human diseases. Here, we showed that ALFPm3-resistant strains of E. coli could be induced in vitro. Genome analysis of the resistant mutants revealed multiple mutations, with the most interesting being a qseC(L299R). A study of antibiotic susceptibility profile showed that the resistant strains harboring the qseC(L299R) not only exhibited higher degree of resistance towards polymyxin antibiotics, but also produced higher biofilm under ALFPm3 stress. Lastly, a single cell death analysis revealed that, at early-log phase when biofilm is scarce, the resistant strains were less affected by ALFPm3 treatment, suggesting additional mechanisms by which qseC orchestrates to protect the bacteria from ALFPm3. Altogether, this study uncovers involvement of qseC mutation in mechanism of resistance of the bacteria against ALFPm3 paving a way for future studies on sustainable use of ALFPm3 as an EMS control agent.
Citation: Khunsri I, Prombutara P, Htoo HH, Wanvimonsuk S, Samernate T, Pornsing C, et al. (2023) Roles of qseC mutation in bacterial resistance against anti-lipopolysaccharide factor isoform 3 (ALFPm3). PLoS ONE 18(6): e0286764. https://doi.org/10.1371/journal.pone.0286764
Editor: Tzong-Yueh Chen, National Cheng Kung University, TAIWAN
Received: March 21, 2023; Accepted: May 23, 2023; Published: June 2, 2023
Copyright: © 2023 Khunsri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This research project is supported by Agricultural Research Development Agency (ARDA) (ID: CRP6105021050) and the Japan Science and Technology Agency (JST)/Japan International Cooperation Agency (JICA), Science and Technology Research Partnership for Sustainable Development, SATREPS JPMJSA1806 (K.S., P.N.). This research project is also supported by National Research Council of Thailand (NRCT) and Mahidol University: N42A650368 and Mahidol University under the New Discovery and Frontier Research Grant (P.N.). C.P. is supported by the National Science and Technology Development Agency (NSTDA) under the Junior Science Talent Project (JSTP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
In recent years, the situation of the world food security and starvation are rapidly worsening in every region across the globe [1–3]. Many factors such as social inequality, political conflicts, and climate changes, are accountable for the sharp drop in food production yield [3–5]. Particularly, negative impacts caused by climate abnormality were seen in all sectors of agricultural value chains from feed, farm and food [3]. Not only does the change in climate directly affect the production yield, as seen in the effects on certain crops around the world [5, 6], but unpredictable weather patterns also increase the likelihood of major disease outbreaks that severely decrease the production output of many agricultural products including farm animals [7].
Thailand is a littoral country situated between the Andaman Sea and the Gulf of Thailand with total coastal length of about 2,815 km. Thus, a vast area along the coastline is suitable for aquaculture—an essential player in Thai economy. Among all others, shrimp was listed as the top fishery product exported in terms of value, in the early 2020s [8]. However, in the past years, the shrimp industry has been facing increasing problems of disease outbreaks such as white spot syndrome virus (WSSV) disease [9, 10], yellow head virus (YHV) disease [11], and acute hepatopancreatic necrosis disease (AHPND) [12], causing a sharp drop in shrimp production. One of the forerunners, AHPND, also known as early mortality syndrome (EMS), a disease caused by a halophilic Gram-negative bacterium—Vibrio parahaemolyticus AHPND (VP-AHPND)—causes long-lasting and devasting wounds to the shrimp industry [12–14]. Since shrimp farming has become vital for Thai economy, protecting the shrimp from the perils of AHPND at all costs is essential. Commonly, shrimp farmers would use chemicals and antibiotics to control AHPND but, to date, there has been no confirmation that antibiotics can sustainably eliminate the disease [15]. Worryingly though, long-term use of antibiotics may induce antibiotic resistance in bacteria not only in the targeted pathogens but also in other bacteria in the environment [16, 17]. Furthermore, antibiotic resistant genes could also be transferred to other bacterial species including human pathogens, thereby uncontrollably spreading to the environment and ultimately leading to severe adverse effects on human health [17, 18].
In 2021, the World Health Organization declared antimicrobial resistance (AMR) as among the top 10 public health issues [19]. Since AMR is ubiquitous along the animal-human-environment interface [20, 21], unsurprisingly, the overuse of antibiotics in animals and livestock, as preventive measures of illnesses, and the misuse as growth promoters, has been identified as the major cause of AMR [15, 17, 22]. In order to find alternative ways to reduce the use of antibiotics, some have focused on exploiting the innate immune system of the organisms [23]. In particular, previous studies have identified antimicrobial peptides (AMPs) in the immune system of the shrimp that can inhibit the growth of VP-AHPND. ALFPm3—the anti-lipopolysaccharide factor isoform 3, isolated from black tiger shrimp Penaeus monodon—is a member of the anti-liposaccharide factors (ALFs) family with a broad range of antimicrobial activities against both Gram-positive and Gram-negative bacteria, including VP-AHPND and Vibrio harveyi, a species that causes vibriosis [24–26]. In terms of mechanism of action, ALFPm3 binds to the lipopolysaccharide (LPS) of the bacterial cell wall causing cell envelop damage followed by cell death [25, 26]. With its broad antibacterial activity, ALFPm3 was proposed as a good candidate for replacing the use of antibiotics in shrimp farms [27]. However, the long-term use of ALFPm3 against bacteria also raises concerns about the development of bacterial resistance. Studies on other AMPs have revealed that the use of cationic AMPs could induce resistance in a wide range of bacterial species including human pathogens [23, 28]. Therefore, it is reasonable to speculate that the ALFPm3-resistant mechanisms might overlap with those of other antibiotics, leading to resistance development towards life-saving antibiotics.
Faced with the eminent risk of cross resistance between ALFPm3 and antibiotics used for bacterial infection treatment in humans, we were compelled to investigate the possible mechanisms underlying ALFPm3 resistance. First, we isolated three ALFPm3-resistant strains of E. coli that are eight times more resistant to ALFPm3 when compared to their sensitive counterpart. Genome analysis of these resistant mutants revealed that mutations were present in multiple genes, with the most interesting being that in the qseC gene, a gene involved in antibiotic stress response, among others. Next, the study of antibiotic susceptibility profile showed that the resistant strain harboring the mutation in the qseC gene showed higher degree of resistance towards cationic lipopeptide antibiotics; polymyxins. Accordingly, biofilm production assay revealed that the qseC mutation is also responsible for higher biofilm production in the presence of ALFPm3. Lastly, single cell death analysis by microscopy revealed that the resistant strains at early-log phase were also less affected by the ALFPm3 treatment, hinting on additional mechanisms by which QseC orchestrates to protect the bacteria from ALFPm3.
Results
ALFPm3-resistant E. coli isolation and their susceptibility against ALFPm3
In order to examine if a long-term use of ALFPm3 as an antibacterial agent could induce resistance, we first attempted to isolate ALFPm3-resistant E. coli. Since the antibacterial activity of ALFPm3 against the wildtype E. coli MC4100 used in this study (Table 1) had not been previously tested, we first determined the minimum inhibitory concentration (MIC) of ALFPm3 against the bacteria and found that ALFPm3 could inhibit the growth of E. coli MC4100 at 1 μM (Table 2). Then, we isolated ALFPm3-resistant strains of E. coli by passaging the E. coli MC4100 in culture media supplemented with gradually-increasing concentrations of ALFPm3, and successfully obtained three strains of ALFPm3-resistant E. coli; PN1001, PN1002 and PN1004, the identities of which were confirmed by 16S rRNA analysis. Susceptibility test showed that the MIC of these strains are 8 times higher than that of the wildtype (Table 2).
Genome analysis of ALFPm3-resistant E. coli
In order to examine the genes responsible for ALFPm3 resistance, once the resistant strains were obtained, whole genome sequencing of all three strains were carried out in comparison with the MC4100 strain. In total, six mutations were detected—two in the intergenic region and four in the coding region (Table 2). In particular, PN1001 harbors one mutation in an intergenic region (A2323955T) and two mutations in a coding region including c.C3995906T encoding for hypothetical protein and c.C103024T that causes silent mutation in ddlB gene. One intergenic mutation (C921168A) and, one silent mutation c.T4320752C in cpdB gene, were found in PN1002. The genome of PN1004 contains only one mutation at c.A3611241C which the gene is annotated as qseC gene.
Among the mutations in the coding regions, ddlB and qseC genes are of interest due to their involvement in bacterial resistance against other antibiotics from previous studies. For example, the mutation in ddlB, a gene encoding for D-alanine-D-alanine ligase (VanA) that is involved in the peptidoglycan biosynthesis of bacteria, was reported to be involved in vancomycin resistance, by altering the substrate of the VanA, thereby preventing vancomycin from attaching to the substrate on the bacterial cell wall [29–31]. However, the fact that the mutation in ddlB found in this study is a silent mutation makes it less desirable for further study. In contrast, a missense mutation found in the qseC gene (L299R) of PN1004 is particularly interesting. QseC is part of the two-component regulatory system quorum sensing in bacteria, including E. coli [32]. The quorum sensing plays an important role in cell-cell signaling in bacteria that regulates pmrB gene that has been reported to be involved in bacterial resistance against the cationic antimicrobial peptide antibiotic, polymyxin [28, 33]. Altogether, the whole genome analysis of all resistant mutants revealed multiple mutated genes, some of which were previously shown to affect susceptibility of the bacteria to antibiotics.
ALFPm3-resistant strains harboring qseC mutations showed higher resistance to lipopeptide antibiotics, polymyxin and colistin
The presence of an antibiotic resistance-related mutation in the resistant strains urged us to further investigate if the antibiotic susceptibility profiles of these mutant strains were altered. We examined the MIC of all mutants against 11 different antibiotics from five major classes of antibiotics including DNA replication inhibitors, RNA transcription inhibitors, protein translation inhibitors, cell wall synthesis inhibitors, and membrane disrupting agents. The result showed that the strains PN1001 and PN1002 did not exhibit drastic changes in their antibiotic susceptibility profile when compared to that of wildtype MC4100 (Table 3). Only slight, two-fold changes were seen in some antibiotics such as kanamycin and nalidixic acid, suggesting that mutations found in PN1001 and PN1002 do not contribute to the significant changes in their susceptibility profiles against all 11 antibiotics tested in this study.
Although susceptibility profile of PN1004 harboring the qseC(L299R) mutation did not drastically alter DNA replication, RNA transcription, protein translation, and cell wall synthesis inhibitors tested, it showed 32 times higher resistance to a group of membrane disrupting agents; polymyxin B and colistin, when compared to that of MC4100. This result highlights the importance of qseC mutation in bacterial resistance against both ALFPm3 and cationic peptide polymyxin antibiotics. Spurred by this result, we further investigated if the qseC gene was indeed responsible for the resistance to ALFPm3 and colistin. Through genome engineering, the qseC gene in E. coli MC4100 was replaced by chloramphenicol resistant gene camR, to generate a new strain of E. coli harboring qseC::camR designated as IC1001 (Fig 1A and 1B). Notably, the MICs of ALFPm3 and colistin in IC1001 are also higher when compared to MC4100 (Tables 2 and 3), indicating that qseC deletion is also responsible for higher degree of bacterial resistance against ALFPm3 and colistin. However, its resistant level is yet lower than that of the original PN1004 strain: 2- and 16-fold lower in ALFPm3 and colistin, respectively (Tables 2 and 3), suggesting that qseC::camR is not equivalent to qseC(L299R) in terms of promoting the resistant level of the bacteria against ALFPm3 and colistin.
(A) Construction of IC1001 strain via CRISPR-Cas two-plasmid system. (B) Confirmation of the presence of qseC::camR in IC1001 strain. Neg ctrl is a representative of unsuccessful CRISPR-engineered clone containing wild type qseC gene. (C) A representative result of biofilm formation of tested bacterial strains with or without ALFPm3 (half MIC). (D) Quantification of biofilm formation after 24 hours incubation with or without ALFPm3 supplement. The error bars illustrate the standard deviations of three separate experiments. The statistical significance using two-tail student t-test (*P < 0.05).
qseC mutation resulted in higher biofilm production of the bacteria under ALFPm3 stress
Next, we examined what possible phenotypic responses the bacteria harboring qseC mutations might employ to protect themselves against ALFPm3. Previous studies have shed light onto the relationship between two-component signaling system QseBC and PmrAB, showing the involvement of the system in biofilm formation [32, 34]. We, thus, tested if the qseC mutations are affecting biofilm formation, and eventually leading to antibiotic resistance. The result showed that, in an absence of ALFPm3, no significant difference in biofilm production was detected in all strains tested. However, when supplemented with sub-MIC level of ALFPm3, the amount of biofilm generated from PN1004 was significantly higher than that of MC4100 (Fig 1C and 1D). Notably, the deletion of qseC gene (qseC::camR) did not significantly alter biofilm production of the bacteria (IC1001) either with or without ALFPm3 supplement, suggesting that qseC(L299R), and not the qseC::camR, is responsible for the higher production of the biofilm of the bacteria under ALFPm3 stress.
Single cell death analysis by microscopy showed that qseC(L299R) and qseC::camR strains are less sensitive to ALFPm3 at early timepoint
It is well known that, under the limited nutrient environment or stress, biofilm production of the bacteria occurs as a means of survival response [35–37]. The fact that IC1001, which is four times more resistant to ALFPm3 than MC4100, showed no significant increase in biofilm production urged us to investigate whether or not, at the early stage of bacterial growth where biofilm production is limited, bacteria with qseC mutations are protected from ALFPm3. Thus, we performed fluorescence microscopy to investigate the levels of single cell death in MC4100, PN1004 and IC1001 strains upon 1 μM ALFPm3 treatment. When treated with ALFPm3, 77.84% of wildtype MC4100 cells were stained with SYTOX Green, a fluorescent dye that indicates cell death since it is unable to enter cells with intact membranes [38], whereas only a 1.59% and 9.58% of PN1004 and IC1001 cells, respectively, were stained (Fig 2). This suggests that both resistant strains were protected from ALFPm3 at the early stage of the growth when biofilm is still absent. Notably, in accordance with the difference in MIC levels of the resistant strains, PN1004 which possess higher MIC of ALFPm3, was significantly less affected by ALFPm3 treatment in the single cell death analysis when compared to IC1001.
(A) Representative images of MC4100, PN1004 and IC1001 strains of E. coli that were incubated with and without 1 μM ALFPm3 for 1 hour then stained with 1 μg/ml FM4-64 (red) and 0.5 μM SYTOX Green (green) fluorescent dyes. Scale bar represents 1 μm. (B) A graph showing the difference in the % of nucleoids that are stained with SYTOX Green between treatment conditions with and without ALFPm3, in MC4100, PN1004 and IC1001 strains. The % of nucleoids stained are indicated. The error bars indicate standard deviations from 3 independent experiments as detailed in the materials and methods. ** P < 0.001.
Discussion
In an era of antibiotic resistance, novel antibiotics are urgently needed in order to combat antibiotic resistant pathogens. However, searching for new antibiotics is notoriously difficult [39, 40]. Thus, in recent years, antibiotic alternatives, whose potential have not yet been fully exploited, have been in the spotlight, due to their diversity and abundance [41]. One of the most promising antibiotic alternatives are antimicrobial peptides (AMPs) since they were previously prioritized in Tier 2 approaches, where breakthrough insights in systemic therapy are emerging [40, 42]. Albeit their vast diversity and broad antibacterial activity, using AMPs as therapeutic agents also raised concerns about the impact on the innate immune system of higher eukaryotic organisms, due to the similarity between the therapeutic AMPs and those of the eukaryotes [43]. Also, many studies worryingly revealed that resistance against AMPs shared some similarity with the resistance to certain antibiotics [43]. An interesting example would be that in clinical isolates of Acinetobacter baumannii that were exposed to colistin, cross-resistance to AMPs, including a human-derived peptide LL-37, was observed [44]. Thus, understanding the mechanism of resistance of the bacteria against AMPs is vital for the sustainable use of AMPs as antibiotic alternatives; thereby truly alleviating the worsening situation of AMR.
Here we demonstrated that ALFPm3-resistant E. coli, isolated in this study, harbors various mutations in the coding regions that might be associated with antibiotic resistance. One of the limitations worth mentioning is that this study focused only on the role of qseC gene mutation found in PN1004. Thus, the characteristics of ALFPm3 resistance of PN1001 and PN1002 were not fully investigated. Particularly, the possible role of missense mutation at c.C3995906T which was annotated as a hypothetical protein in ALFPm3 resistance was not included in this study. Many studies have identified myriad of mutated hypothetical proteins that are involved in antibiotic resistant mechanism of bacteria [45, 46]. Thus, it is interesting to further explore the role of the hypothetical protein in ALFPm3 resistance that might lead to a better understanding of how bacteria become resistant to ALFPm3.
Apart from mutations in the coding regions, mutations in the intergenic regions of both PN1001 (A2323955T) and PN1002 (C921168A) found in this study are also intriguing. It is possible that mutations in intergenic areas may affect neighboring genes by altering regulatory components that govern the target gene, despite the intergenic region’s distance from the target gene. A previous study found that, A2323955T mutation, located near the fabB gene, which encodes for 3-oxoacyl-ACP synthase in fatty acid synthesis in lipid metabolism, contributed to the overexpression of the fabB gene resulting in the upregulation of the efflux pump and hence, bacterial resistance against tialactomycin [47]. In this study, intergenic region mutation at C921168A in PN1002 is also a promising candidate for further studies since it is located near ompA gene that encodes for outer membrane protein A. OmpA is a well-known protein that is involved in various antibiotic resistance pathways of the bacteria. For example, a previous study showed that E. coli resistant to tetracycline displayed an increase in the expression of ompA [48]. Thus, whether or not these intergenic mutations are responsible for ALFPm3 resistance needs further investigations.
Biofilm production has been linked to bacterial resistance against various antibiotics in many studies [49, 50]. It has been shown that biofilm formation also contributed to AMP resistance by electrostatic repulsion from biofilm capsule polymers [51], and sequestration of negatively charged AMPs by the positively charged biofilm polysaccharides and proteolytic breakdown of AMPs [52]. Thus, it is not unexpected that the ALFPm3-resistant bacteria with higher biofilm production confer resistance to other peptide-based antibiotics that share similar MOA such as the lipopeptide polymyxin. Regarding qseC mutation, we showed that not only is the bacteria harboring qseC(L299R) mutation more resistant to ALFPm3 and colistin, but it also produces higher amount of biofilm in the presence of ALFPm3. In support of these findings, many previous studies have demonstrated that the qseC gene, which belongs to the PhoPQ family, was involved in virulence and biofilm formation of bacteria [49, 53]. It is interesting to note that even though the strain harboring qseC::camR mutation is also resistant to ALFPm3, it did not show significant changes in biofilm production, either in the absence or the presence of ALFPm3. The finding is slightly in contrast with a previous study where deletion of qseC gene resulted in impaired biofilm formation, among other stresses, in Haemophilus parasuis [49].
It is also worth noting that, even though we showed that qseC(L299R) mutation in PN1004 resulted in higher biofilm production upon ALFPm3 treatment at 24 hours, there is no direct evidence showing that biofilm formation is the sole protective mechanism of the resistant bacteria from ALFPm3. It is possible that the higher production of biofilm at 24 hours, contributed to higher MIC data which was also collected at 24 hours timepoint. However, the higher biofilm formation at this time point cannot fully explain the resistance characteristics of the bacteria at the early stage of growth as seen in our single cell death analysis. At this early stage of cell growth (early-log phase), where biofilm production is limited, we found that the bacteria harboring qseC(L299R) or qseC::camR mutations were also protected from ALFPm3, which resulted in significantly lower number of dead cells. This finding suggests that qseC might exert its resistant mechanism toward ALFPm3 via different cellular pathways, that have yet to be determined in future studies. It is possible that qseC mutation might alter the membrane envelop properties of the bacteria making the resistant bacteria less susceptible to the cationic peptide as seen in other resistance mechanisms against various peptide-based antibiotics [54, 55]. Further studies regarding mechanism of resistance via qseC could provide an insight into how the gene might be involved in antimicrobial peptide resistance of the bacteria.
Materials and methods
Bacterial strains and plasmids
Complete details on the bacterial strains and plasmids used in this study, along with its characteristics and sources are listed in Table 1.
Production and purification of the recombinant ALFPm3 protein
The recombinant ALFPm3 (rALFPm3) protein was produced in the yeast Pichia pastoris according to a previous study [56]. Briefly, a single colony of P. pastoris containing ALFPm3 was grown overnight in YPD broth medium at 30°C. Later, the overnight culture was inoculated into BMGY medium and grown at 30°C until an OD600 of 4–6. The cell was induced for protein production by being transferred to culture in BMMY medium. Furthermore, methanol (100%) was added every 24 hours to a final concentration of 0.5% (v/v). At day 2 post methanol induction, the supernatant, which is crude rALFPm3, was collected. To purify rALFPm3 protein, the crude supernatant was diluted 1:1 with the starter buffer (20 mM Tris–HCl, 200 mM NaCl, pH 7.0), and then purified by a strong cation exchange chromatography, SP Sepharose High-Performance column, (GE Healthcare). Elution was then performed with the elution buffer (20 mM Tris–HCl, 1 M NaCl, pH 7.0) and dialyzed overnight against sterile deionized water at 4°C to reduce the salt. The purified rALFPm3 was analyzed by SDS-PAGE using Coomassie blue staining and by western blot analysis using a specific antibody. The purified protein was kept at -20°C until used.
MIC determination
MIC is the lowest concentration that can successfully inhibit the growth of the bacteria, and was determined by broth microdilution method [57]. Briefly, overnight cultures of single colonies of bacteria were grown in fresh Luria-Bertani (LB) broth on a roller at 50 rpm, at 30°C. Early log phase cultures were further diluted in LB broth and added to wells of a 96-well plate that contained 2-fold serial dilutions of ALFPm3 or antibiotics in LB broth, to obtain 100,000 CFU/ml. The plate was then incubated at 30°C while shaking at 250 rpm for 24 hours. The MIC was interpreted by visual observation as the lowest concentration of the drug that can inhibit the growth of the bacteria.
ALFPm3-resistant bacteria selection and confirmation
ALFPm3 resistance induction in E. coli was done by serial passage method [58]. Overnight cultures of single colonies of E. coli MC4100 were diluted in fresh LB broth and grown on a roller at 50 rpm, at 30°C. Early log phase cultures were further diluted in LB broth and cultured in a 96-well plate in the presence of sub-MIC levels of ALFPm3 and incubated at 30°C for 24 hours. The cultures were then passaged in higher concentrations of ALFPm3 and further incubated for 24 to 48 hours until the bacteria can successfully grow in this higher concentration of ALFPm3.
All of resistant isolates were confirmed by 16S rRNA analysis. Briefly, E. coli were cultured in LB broth at 30°C overnight prior to cell collection and genomic DNA extraction using FavorPrepTM Tissue Genomic DNA Extraction Mini Kit. The 16S rRNA was amplified with primers BSF8/20 (5’ AGAGTTTGATCCTGGCTCAG 3’) and REVB (5’ GGTTACCTTGTTACGACTT 3’) and purified with GenepHlowTM Gel/PCR Kit. 16S rRNA’s DNA sequence were assessed on https://blast.ncbi.nlm.nih.gov/Blast.cgi.
Whole genome sequencing and mutated gene analysis
Whole genome sequencing (WGS) and analysis of both wild type and resistant strains were carried out by the Omics Science & Bioinformatics Center at Chulalongkorn University. Briefly, the raw data sequence performance was assessed using FASTQC (v0.11.9), and irrelevant data was removed using Trim Galore (v0.6.2). The trimmed pieces were then assembled via SPAdes (v3.14.1). SNIPPY software (v4.3.6) was utilized to assess the mutations in resistant clones and to compare them with the reference E. coli K-12 sub-strain—MC4100 (NCBI txid:1403831). Prokka (v1.13.4) annotated the genomic DNA sequences with mutations in order to determine characteristics of the altered genes. Finally, putative mutant genes of resistant clones were identified by comparing with those of the wild type. All mutations shown in Table 1 were confirmed by Sanger sequencing.
Bacterial genome engineering
To replace wildtype qseC with chloramphenicol resistant gene (camR), we performed CRISPR-based bacterial genome engineering using a two-plasmid system; pCas and pTargetF, according to previous studies [59, 60]. Briefly, gibson assembly was used to insert the N20 sequence, which includes the PAM sequence for the target locus of qseC gene, into pTargetF to generate pTargetF-qseC. Also, the homologous DNA template consisting of camR flanked by qseC homology was generated. E. coli JP313 harboring pCas was then transformed with 400 ng of homologous DNA template and 100 ng of pTargetF-qseC by electroporation. Transformants were selected on LB agar supplemented with 50 μg/ml each of spectinomycin and kanamycin, and 5 μg/ml chloramphenicol.
Biofilm formation assay
The biofilm forming capability of bacteria was evaluated based on previous studies [61, 62]. Briefly, overnight cultures of bacteria were diluted 1:100 into fresh LB broth and grown until the OD600 reached 0.4. The cells were aspirated into a 96-well plate and then treated with or without half MIC of ALFPm3 at 37°C for 24 hours. The biofilms were rinsed with water and PBS before being dyed with 150 ml of 0.1% crystal violet for 30 minutes. One hundred microliters of 30%(v/v) acetic acid were added to each well, which was subsequently transferred to be analyzed by a spectrophotometer at a wavelength of 595 nm (S1 Table).
Fluorescence microscopy
Well separated single colonies of E. coli MC4100, PN1004 and IC1001 were inoculated in LB and grown overnight on a roller at 30°C. Overnight cultures were diluted in fresh media and grown until early log phase, until OD600 of 0.2 was reached. All strains were then treated for 1 hour with 1 μM of ALFPm3 and accompanied by untreated controls. The cells were then stained with fluorescent dyes—1 μg/ml FM4-64, 2 μg/ml DAPI and 0.5 μM SYTOX Green. The cells were then harvested by centrifugation and concentrated by resuspending in LB at 1/10 of the original volume, after which 3 μl was loaded onto an agarose pad containing 1.2% agarose in 10% LB, the cover slip applied and then subjected to fluorescent microscopy on DeltaVisionTM microscope, with consistent parameters throughout all experiments. Excitation/emission wavelengths of the fluorescent dyes are 575/679 nm, 390/435 nm and 475/525 nm for FM 4–64, DAPI and SYTOX Green, respectively.
Image analysis
Images obtained from the microscope were first preprocessed on Fiji software [63] and then subjected to analysis on CellProfiler software [64] version 4.3.1. The nucleoid outline, stained by the fluorescent dye DAPI, was used to define the area at which to measure the SYTOX Green intensity, after which the background intensity was subtracted to obtain the actual SYTOX intensity of individual cells. SYTOX Green intensity was measured in the unadjusted image obtained from fluorescence microscopy.
Statistical analysis of single cell death calculations
Statistical analysis for single cell death calculations was performed on Microsoft Excel version 16.59. Statistical analysis was carried out on 3 independent experiments, each experiment comprising of; 5 images per strain, each having 40 to 300 nucleoids, for–ALFPm3 conditions; and 7 to 11 images per strain, each with 30 to 400 nucleoid outlines, for + ALFPm3 conditions. The percent of SYTOX Green is the percent of cells, per strain of bacteria, that are higher than 3 times the mean of SYTOX intensity of the corresponding untreated controls. Statistical significance was from two-tailed Student’s t-test, comparing between–ALFPm3 and + ALFPm3 conditions (** P < 0.001), error bars represent standard deviation (Fig 2, S2 Table).
Supporting information
S1 Table. Minimal dataset for biofilm assay showing absorbance at 595 nm for all strains with and without ALFPm3 treatment (Minimal data for Fig 1D).
https://doi.org/10.1371/journal.pone.0286764.s001
(XLSX)
S2 Table. The percent of nucleoids stained with SYTOX Green that are more than 3 times the mean SYTOX intensity of the untreated (- ALFPm3) condition per strain of bacteria, together with P-values (Minimal dataset for Fig 2B).
https://doi.org/10.1371/journal.pone.0286764.s002
(XLSX)
S1 Raw image. Raw image (agarose gel) for Fig 1B.
https://doi.org/10.1371/journal.pone.0286764.s003
(PDF)
Acknowledgments
We would like to thank Mahidol University Frontier Research Facility (MU-FRF) for instrumentation support for DeltaVisionTM Ultra and the Advanced Cell Imaging Center, Institute of Molecular Biosciences, Mahidol University for the fluorescent microscopy imaging, operated by Ms Naraporn Sirinonthanawech.
References
- 1. Collet D. Storage and starvation: public granaries as agents of “food security” in early modern Europe. Historical Social Research. 2010;35: 234–252.
- 2. Kannan K, Dev S, Alakh Narin S. Concerns on Food Security. 2000;35: 3919–3922.
- 3. Natalini D, Bravo G, Jones AW. Global food security and food riots–an agent-based modelling approach. Food Security: The Science, Sociology and Economics of Food Production and Access to Food. 2019;11: 1153–1173.
- 4. Parry M, Rosenzweig C, Iglesias A, Fischer G, Livermore M. Climate change and world food security: a new assessment. Global Environmental Change. 1999;9: S51–S67.
- 5. Butt TA, McCarl BA, Angerer J, Dyke PT, Stuth JW. The economic and food security implications of climate change in mali. Climatic Change. 2005;68: 355–378.
- 6. Wheeler T, von Braun J. Climate change impacts on global food security. Science. 2013;341: 508–513. pmid:23908229
- 7. Gitz V, Meybeck A, Lipper L, Young CD, Braatz S. Climate change and food security: risks and responses. 2016; 122.
- 8. Suwannapoom S. County Fisheries Trade: Thailand. In: SEAFDEC [Internet]. 2019 [cited 10 Nov 2022]. Available: http://www.seafdec.org/county-fisheries-trade-thailand/
- 9. Patil PK, Geetha R, Ravisankar T, Avunje S, Solanki HG, Abraham TJ, et al. Economic loss due to diseases in Indian shrimp farming with special reference to Enterocytozoon hepatopenaei (EHP) and white spot syndrome virus (WSSV). Aquaculture. 2021;533: 736231.
- 10. Yi G, Wang Z, Qi Y, Yao L, Qian J, Hu L. Vp28 of shrimp white spot syndrome virus is involved in the attachment and penetration into shrimp cells. J Biochem Mol Biol. 2004;37: 726–734. pmid:15607033
- 11. Tirasophon W, Yodmuang S, Chinnirunvong W, Plongthongkum N, Panyim S. Therapeutic inhibition of yellow head virus multiplication in infected shrimps by YHV-protease dsRNA. Antiviral Res. 2007;74: 150–155. pmid:17166601
- 12. Theethakaew C, Nakamura S, Motooka D, Matsuda S, Kodama T, Chonsin K, et al. Plasmid dynamics in Vibrio parahaemolyticus strains related to shrimp Acute Hepatopancreatic Necrosis Syndrome (AHPNS). Infect Genet Evol. 2017;51: 211–218. pmid:28404482
- 13. Ahmmed S, Khan MdA A-K, Eshik MdME, Punom NJ, Islam ABMMdK, Rahman MS. Genomic and evolutionary features of two AHPND positive Vibrio parahaemolyticus strains isolated from shrimp (Penaeus monodon) of south-west Bangladesh. BMC Microbiology. 2019;19: 270. pmid:31796006
- 14. Zorriehzahra MJ. Early Mortality Syndrome (EMS) as new Emerging Threat in Shrimp Industry. Adv Anim Vet Sci. 2015;3: 64–72.
- 15. Kewcharoen W, Srisapoome P. Probiotic effects of Bacillus spp. from Pacific white shrimp (Litopenaeus vannamei) on water quality and shrimp growth, immune responses, and resistance to Vibrio parahaemolyticus (AHPND strains). Fish Shellfish Immunol. 2019;94: 175–189. pmid:31499198
- 16. Bérdy J. Thoughts and facts about antibiotics: Where we are now and where we are heading. J Antibiot. 2012;65: 385–395. pmid:22511224
- 17. Holmström K, Gräslund S, Wahlström A, Poungshompoo S, Bengtsson B-E, Kautsky N. Antibiotic use in shrimp farming and implications for environmental impacts and human health. International Journal of Food Science & Technology. 2003;38: 255–266.
- 18. Phillips I, Casewell M, Cox T, De Groot B, Friis C, Jones R, et al. Does the use of antibiotics in food animals pose a risk to human health? A critical review of published data. J Antimicrob Chemother. 2004;53: 28–52. pmid:14657094
- 19.
Global action plan on antimicrobial resistance. [cited 10 Nov 2022]. Available: https://fctc.who.int/publications/i/item/global-action-plan-on-antimicrobial-resistance
- 20. Alhaji N, abubakar Hassan, Adamu A, Odetokun , Lawan M, Fasina FO. Practices of antimicrobial usage and associated resistance emergence in smallholder beef cattle production systems in Northern Nigeria: Drivers and One Health challenge. Preprints; 2022 Mar.
- 21. Moore RE, Millar BC, Moore JE. Antimicrobial resistance (AMR) and marine plastics: Can food packaging litter act as a dispersal mechanism for AMR in oceanic environments? Mar Pollut Bull. 2020;150: 110702. pmid:31740179
- 22. Zhang YB, Li Y, Sun XL. Antibiotic resistance of bacteria isolated from shrimp hatcheries and cultural ponds on Donghai Island, China. Mar Pollut Bull. 2011;62: 2299–2307. pmid:21945557
- 23. Guilhelmelli F, Vilela N, Albuquerque P, Derengowski L da S, Silva-Pereira I, Kyaw CM. Antibiotic development challenges: the various mechanisms of action of antimicrobial peptides and of bacterial resistance. Frontiers in Microbiology. 2013;4. pmid:24367355
- 24. Tassanakajon A, Somboonwiwat K. Antimicrobial peptides from the black tiger shrimp Penaeus monodon—A review. Selangor, Malaysia; 2011. pp. 229–240.
- 25. Jaree P, Tassanakajon A, Somboonwiwat K. Effect of the anti-lipopolysaccharide factor isoform 3 (ALFPm3) from Penaeus monodon on Vibrio harveyi cells. Dev Comp Immunol. 2012;38: 554–560. pmid:23000267
- 26. Tassanakajon A, Amparyup P, Somboonwiwat K, Supungul P. Cationic antimicrobial peptides in penaeid shrimp. Mar Biotechnol (NY). 2011;13: 639–657. pmid:21533916
- 27. Supungul P, Jaree P, Somboonwiwat K, Junprung W, Proespraiwong P, Mavichak R, et al. A potential application of shrimp antilipopolysaccharide factor in disease control in aquaculture. Aquaculture Research. 2017;48: 809–821.
- 28. Gruenheid S, Le Moual H. Resistance to antimicrobial peptides in Gram-negative bacteria. FEMS Microbiol Lett. 2012;330: 81–89. pmid:22339775
- 29. Kapoor G, Saigal S, Elongavan A. Action and resistance mechanisms of antibiotics: A guide for clinicians. J Anaesthesiol Clin Pharmacol. 2017;33: 300–305. pmid:29109626
- 30. Dutka-Malen S, Evers S, Courvalin P. Detection of glycopeptide resistance genotypes and identification to the species level of clinically relevant enterococci by PCR. J Clin Microbiol. 1995;33: 24–27. pmid:7699051
- 31. Healy VL, Park IS, Walsh CT. Active-site mutants of the VanC2 D-alanyl-D-serine ligase, characteristic of one vancomycin-resistant bacterial phenotype, revert towards wild-type D-alanyl-D-alanine ligases. Chem Biol. 1998;5: 197–207. pmid:9545431
- 32. Guckes KR, Kostakioti M, Breland EJ, Gu AP, Shaffer CL, Martinez CR, et al. Strong cross-system interactions drive the activation of the QseB response regulator in the absence of its cognate sensor. Proceedings of the National Academy of Sciences. 2013;110: 16592–16597. pmid:24062463
- 33. Jochumsen N, Marvig RL, Damkiær S, Jensen RL, Paulander W, Molin S, et al. The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is shaped by strong epistatic interactions. Nat Commun. 2016;7: 13002. pmid:27694971
- 34. Breland EJ, Zhang EW, Bermudez T, Martinez CR, Hadjifrangiskou M. The Histidine Residue of QseC Is Required for Canonical Signaling between QseB and PmrB in Uropathogenic Escherichia coli. Silhavy TJ, editor. J Bacteriol. 2017;199. pmid:28396353
- 35. Jefferson KK. What drives bacteria to produce a biofilm? FEMS Microbiology Letters. 2004;236: 163–173. pmid:15251193
- 36. Oliveira M, Nunes SF, Carneiro C, Bexiga R, Bernardo F, Vilela CL. Time course of biofilm formation by Staphylococcus aureus and Staphylococcus epidermidis mastitis isolates. Vet Microbiol. 2007;124: 187–191. pmid:17509779
- 37. Uruén C, Chopo-Escuin G, Tommassen J, Mainar-Jaime RC, Arenas J. Biofilms as Promoters of Bacterial Antibiotic Resistance and Tolerance. Antibiotics. 2021;10: 3. pmid:33374551
- 38. Lebaron P, Catala P, Parthuisot N. Effectiveness of SYTOX Green Stain for Bacterial Viability Assessment. Appl Environ Microbiol. 1998;64: 2697–2700. pmid:9647851
- 39. Cook MA, Wright GD. The past, present, and future of antibiotics. Sci Transl Med. 2022;14: eabo7793. pmid:35947678
- 40. Lei J, Sun L, Huang S, Zhu C, Li P, He J, et al. The antimicrobial peptides and their potential clinical applications. Am J Transl Res. 2019;11: 3919–3931. pmid:31396309
- 41. Wang S, Zeng X, Yang Q, Qiao S. Antimicrobial Peptides as Potential Alternatives to Antibiotics in Food Animal Industry. Int J Mol Sci. 2016;17: 603. pmid:27153059
- 42. Czaplewski L, Bax R, Clokie M, Dawson M, Fairhead H, Fischetti VA, et al. Alternatives to antibiotics—a pipeline portfolio review. The Lancet Infectious Diseases. 2016;16: 239–251. pmid:26795692
- 43. Fleitas O, Franco OL. Induced Bacterial Cross-Resistance toward Host Antimicrobial Peptides: A Worrying Phenomenon. Front Microbiol. 2016;7: 381. pmid:27047486
- 44. Napier BA, Burd EM, Satola SW, Cagle SM, Ray SM, McGann P, et al. Clinical Use of Colistin Induces Cross-Resistance to Host Antimicrobials in Acinetobacter baumannii. mBio. 2013;4: e00021–13. pmid:23695834
- 45. Reem A, Zhong Z-H, Al-Shehari WA, Al-Shaebi F, Amran GA, Moeed YAG, et al. Functional Annotation of Hypothetical Proteins related to Antibiotic Resistance in Pseudomonas Aeruginosa PA01. Clin Lab. 2021;67. pmid:34383409
- 46. Zhang F, Gao J, Wang B, Huo D, Wang Z, Zhang J, et al. Whole-genome sequencing reveals the mechanisms for evolution of streptomycin resistance in Lactobacillus plantarum. Journal of Dairy Science. 2018;101: 2867–2874. pmid:29397163
- 47. Jackowski S, Zhang Y-M, Price AC, White SW, Rock CO. A Missense Mutation in the fabB (β-Ketoacyl-Acyl Carrier Protein Synthase I) Gene Confers Thiolactomycin Resistance to Escherichia coli. Antimicrob Agents Chemother. 2002;46: 1246–1252.
- 48. Viveiros M, Dupont M, Rodrigues L, Couto I, Davin-Regli A, Martins M, et al. Antibiotic Stress, Genetic Response and Altered Permeability of E. coli. PLoS One. 2007;2: e365. pmid:17426813
- 49. He L, Dai K, Wen X, Ding L, Cao S, Huang X, et al. QseC Mediates Osmotic Stress Resistance and Biofilm Formation in Haemophilus parasuis. Frontiers in Microbiology. 2018;9. Available: https://www.frontiersin.org/articles/10.3389/fmicb.2018.00212 pmid:29487590
- 50. Stewart PS, Costerton JW. Antibiotic resistance of bacteria in biofilms. Lancet. 2001;358: 135–138. pmid:11463434
- 51. Otto M. Bacterial Evasion of Antimicrobial Peptides by Biofilm Formation. In: Shafer WM, editor. Antimicrobial Peptides and Human Disease. Berlin, Heidelberg: Springer; 2006. pp. 251–258. pmid:16909925
- 52. Galdiero E, Lombardi L, Falanga A, Libralato G, Guida M, Carotenuto R. Biofilms: Novel Strategies Based on Antimicrobial Peptides. Pharmaceutics. 2019;11: 322. pmid:31295834
- 53. Guckes KR, Breland EJ, Zhang EW, Hanks SC, Gill NK, Algood HMS, et al. Signaling by two-component system noncognate partners promotes intrinsic tolerance to polymyxin B in uropathogenic Escherichia coli. Sci Signal. 2017;10: eaag1775. pmid:28074004
- 54. Chen X, Tian J, Luo C, Wang X, Li X, Wang M. Cell Membrane Remodeling Mediates Polymyxin B Resistance in Klebsiella pneumoniae: An Integrated Proteomics and Metabolomics Study. Frontiers in Microbiology. 2022;13. Available: https://www.frontiersin.org/articles/10.3389/fmicb.2022.810403 pmid:35222333
- 55. da Silva KE, Thi Nguyen TN, Boinett CJ, Baker S, Simionatto S. Molecular and epidemiological surveillance of polymyxin-resistant Klebsiella pneumoniae strains isolated from Brazil with multiple mgrB gene mutations. International Journal of Medical Microbiology. 2020;310: 151448. pmid:33092694
- 56. Somboonwiwat K, Marcos M, Tassanakajon A, Klinbunga S, Aumelas A, Romestand B, et al. Recombinant expression and anti-microbial activity of anti-lipopolysaccharide factor (ALF) from the black tiger shrimp Penaeus monodon. Dev Comp Immunol. 2005;29: 841–851. pmid:15978281
- 57. Htoo HH, Brumage L, Chaikeeratisak V, Tsunemoto H, Sugie J, Tribuddharat C, et al. Bacterial Cytological Profiling as a Tool To Study Mechanisms of Action of Antibiotics That Are Active against Acinetobacter baumannii. Antimicrobial Agents and Chemotherapy. 2019;63: e02310–18. pmid:30745382
- 58. Andersson DI, Hughes D, Kubicek-Sutherland JZ. Mechanisms and consequences of bacterial resistance to antimicrobial peptides. Drug Resist Updat. 2016;26: 43–57. pmid:27180309
- 59. Jiang Y, Chen B, Duan C, Sun B, Yang J, Yang S. Multigene Editing in the Escherichia coli Genome via the CRISPR-Cas9 System. Kelly RM, editor. Appl Environ Microbiol. 2015;81: 2506–2514. pmid:25636838
- 60. Wang X, He J, Le K. Making point mutations in Escherichia coli BL21 genome using the CRISPR-Cas9 system. FEMS Microbiology Letters. 2018;365. pmid:29596631
- 61. Merritt JH, Kadouri DE, O’Toole GA. Growing and Analyzing Static Biofilms. Current Protocols in Microbiology. 2006;00: 1B.1.1-1B.1.17. pmid:18770545
- 62. Wannasrichan W, Htoo HH, Suwansaeng R, Pogliano J, Nonejuie P, Chaikeeratisak V. Phage-resistant Pseudomonas aeruginosa against a novel lytic phage JJ01 exhibits hypersensitivity to colistin and reduces biofilm production. Frontiers in Microbiology. 2022;13. Available: https://www.frontiersin.org/articles/10.3389/fmicb.2022.1004733 pmid:36274728
- 63. Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, et al. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012;9: 676–682. pmid:22743772
- 64. Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, et al. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biology. 2006;7: R100. pmid:17076895
- 65. Pogliano J, Lynch AS, Belin D, Lin EC, Beckwith J. Regulation of Escherichia coli cell envelope proteins involved in protein folding and degradation by the Cpx two-component system. Genes Dev. 1997;11: 1169–1182. pmid:9159398