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MUTATIONAL BASIS OF MEROPENEM RESISTANCE IN PSEUDOMONAS AERUGINOSA
Chebotar IV Bocharova YuA, Chaplin AV, Savinova TA, Vasiliadis YuA, Mayansky NA Pirogov Russian National Research Medical University, Moscow, Russia
The carbapenem-resistant strains of Pseudomonas aeruginosa are considered as the dangerous pathogens of critical priority. Deciphering the mechanisms underlying the development of carbopenem resistance is an urgent challenge faced by modern medical science. The study was aimed to describe the diversity and fixation of mutations associated with the development of carbapenem resistance during the P. aeruginosa adaptation to the increasing meropenem concentrations. The objects of the study were P. aeruginosa isolates obtained by growing the ATCC 27853 P. aeruginosa reference strain exposed to increasing concentrations of meropenem. The isolates were tested for meropenem susceptibility using E-tests (Epsilometer tests) and by the agar dilution method. Genomes of the isolates were sequenced in the MGISEQ-2000 whole-genome sequencer. The findings show that in experimental settings P. aeruginosa develops high meropenem resistance very quickly (in 6 days). Evolution of resistance is associated with cloning involving the emergence of multiple clones with various genotypes. Mutagenesis that involves 11 genes, including oprD, pbuE, nalD, nalC, spoT, mlaA, mexD, mexR, oprM, mraY, pbp3, provides the basis for cloning. Regardless of the levels of their meropenem resistance, some of the emerging clones do not progressively develop and are replaced by more successful clones. Keywords: antibiotics, resistance, Pseudomonas aeruginosa, meropenem, mutation Funding: the study was supported by the Russian Science Foundation (project No. 20-15-00235).
Acknowledgements: the authors thank the Center of Precision Genome Editing and Genetic Technologies for Biomedicine of the Pirogov Russian National Research Medical University for their advice on the research methods.
Author contribution: Chebotar IV — concept, manuscript writing; Bocharova YuA — methods, formal analysis; Chaplin AV — formal analysis of sequencing data; Savinova TA — formal analysis of sequencing data; Vasiliadis YuA — methods, sequencing; Mayansky NA — concept, manuscript editing.
Compliance with ethical standards: the study was performed in full compliance with the principles of the Declaration of Helsinki and the standards for handling opportunistic pathogens.
[Я0 Correspondence should be addressed: Igor V Chebotar
Ostrovityanova, 1, Moscow, 117997, Russia: nizarnn@yandex.ru
Received: 25.11.2022 Accepted: 11.12.2022 Published online: 28.12.2022
DOI: 10.24075/brsmu.2022.063
МУТАЦИОННЫЕ ОСНОВЫ ФОРМИРОВАНИЯ УСТОЙЧИВОСТИ К МЕРОПЕНЕМУ У PSEUDOMONAS AERUGINOSA
И. В. Чеботарь Ю. А. Бочарова, А. В. Чаплин, Т. А. Савинова, Ю. А. Василиадис, Н. А. Маянский Российский национальный исследовательский медицинский университет имени Н. И. Пирогова, Москва, Россия
Резистентные к карбапенемам штаммы Pseudomonas aeruginosa расценивают в качестве критически опасных патогенов первого уровня приоритета. Расшифровка механизмов формирования устойчивости к карбапенемам является актуальной задачей современной медицинской науки. Целью работы было описать разнообразие и закрепление мутаций, ассоциированных с формированием карбапенемрезистентности в процессе адаптации P. aeruginosa к повышающимся концентрациям меропенема. Объектами исследования были изоляты P. aeruginosa, полученные при росте референтного штамма P. aeruginosa ATCC 27853 в градиенте возрастающих концентраций меропенема. Оценку чувствительности изолятов к меропенему выполняли при помощи е-тестов (эпсилометрический метод) с меропенемом и при помощи метода дилюции антибиотика в агаре. Геномы изолятов были секвенированы на полногеномном секвенаторе MGISEQ-2000. Полученные результаты показали, что формирование высоких уровней резистентности к меропенему у P. aeruginosa в эксперименте происходит в короткие сроки (6 суток). Эволюция резистентности сопряжена с процессом клонирования, при котором происходит возникновение множества клонов с различными генотипами. Основой клонирования является мутагенез, в который вовлечены 11 генов, включая oprD, pbuE, nalD, nalC, spoT, mlaA, mexD, mexR, oprM, mraY, pbp3. Часть образовавшихся клонов, независимо от уровня их резистентности к меропенему, не получают прогрессивного развития и вытесняются более успешными клонами. Ключевые слова: антибиотики, резистентность, Pseudomonas aeruginosa, меропенем, мутации Финансирование: работа выполнена при поддержке гранта Российского научного фонда (проект № 20-15-00235).
Благодарности: авторы благодарят Центр высокоточного редактирования и генетических технологий для биомедицины ФГАОУ ВО РНИМУ им. Н. И. Пирогова Минздрава РФ за консультации по методической части исследования.
Вклад авторов: И. В. Чеботарь — концептуализация, подготовка рукописи; Ю. А. Бочарова — методология, формальный анализ; А. В. Чаплин — формальный анализ данных секвенирования; Т. А. Савинова — формальный анализ данных секвенирования; Ю. А. Василиадис — методология, выполнение секвенирования; Н. А. Маянский — концептуализация, редактирование рукописи.
Соблюдение этических стандартов: исследование выполнено с соблюдением принципов Хельсинкской декларации и норм работ с условно-патогенными организмами.
[><] Для корреспонденции: Игорь Викторович Чеботарь
ул. Островитянова, д. 1, г. Москва, 117997, Россия: nizarnn@yandex.ru
Статья получена: 25.11.2022 Статья принята к печати: 11.12.2022 Опубликована онлайн: 28.12.2022 DOI: 10.24075/vrgmu.2022.063
Pseudomonas aeruginosa is one of the major opportunistic pathogens [1]. The carbapenem-resistant P. aeruginosa strains are especially dangerous for patients, that is why these strains have been included in the WHO priority list for R&D of new antibiotics for antibiotic-resistant bacteria as dangerous
pathogens of critical priority [2]. Carbapenem resistance can be developed in two ways. The first way is implemented by acquiring resistance genes from external sources via horizontal transfer. This resistance mechanism that is often referred to as plasmid-borne resistance provides high levels of resistance.
Studying this mechanism is more popular among scientists. Enzymes, the heterogenous p-lactamases of various Ambler classes combined into a group of carbapenemases based on the function, provide the main molecular basis for the horisontally transferred carbapenem resistance. However, there is one more way of developing carbapenem resistance that is not associated with horizontal gene transfer. It is based on the P. aeruginosa unique adaptive potential and is implemented through mutational variation in the chromosome genes [3]. Among clinical isolates, P. aeruginosa strains isolated from patients with cystic fibrosis are the most vivid examples of mutational antibiotic resistance. Highly resistant strains have been reported, which contain more than 60 genes disrupted by mutations. These genes can be the cause of resistance to various classes of antibiotics [4]. Of those 26 mutant genes can cause carbapenem resistance.
Studying the diversity of mutations that occur during the P. aeruginosa adaptation to carbapenems is of interest for prediction of carbapenem resistance evolution among clinical strains. The mechanisms underlying carbapenem resistance are assessed using two methodological approaches: 1) stydying genetic and phenotypic characteristics of the clinical carbapenem-resistant isolates; 2) targeted in vitro modeling of carbapenem resistance that involves P. aeruginosa exposure to antibiotic.
The study was aimed to describe the diversity and fixation of mutations associated with the development of carbapenem resistance during the P. aeruginosa adaptation to the increasing meropenem concentrations.
The targeted creation of resistant P. aeruginosa strains is more often modelled using a series of consecutive transfers of bacteria in the liquid growth media containing the increasing concentrations of antibiotic (from 0 pg/mL to the concentrations that are tens and hundreds of times greater than the minimum inhibitory concentration (MIC)) [5]. We used the other model [6] that was based on evolution of motile bacteria exposed to the increasing antibiotic concentrations. Such an approach makes it possible to isolate the larger number of clones with various genotypes.
METHODS
The ATCC 27853 P. aeruginosa reference strain used as a standard of carbapenem susceptibility (The European Committee on Antimicrobial Susceptibility Testing (EUCAST). EUCAST Clinical Breakpoint Tables v. 12.0. Available at: www. eucast.org) was the object of the study.
The study was carried out using the spatiotemporal model of antibiotic resistance in motile bacteria in accordance with the earlier reported method [7]. We formed five compartments divided by partitions with the depth of 2.0 cm in the 20.0 x 40.0 cm container and filled these compartments with the solid growth medium containing Luria Bertani broth (LB Miller, Becton Dickinson and Co.; USA). The growth medium in the compartments contained sequential concentrations (0, 0,2, 20, 200, 2000 pg/mL) of meropenem (Supelco® Analytical Products, Merck & Co. Inc.; USA). A single layer (about 0.6 cm high) of solid growth medium containing Luria Bertani broth with no meropenem was formed atop of the compartments. It was covered with the layer of semi-solid agar (0.28% of agar) containing Luria Bertani broth with no meropenem. This layer was about 0.8 cm high. The culture of P. aeruginosa was adapted to semi-solid growth medium by the earlier reported method before starting the experiment [7].
Bacterial suspension with optical density equivalent to 0.5 MacFarland standard was used for inoculation. Inoculation was
performed by injection into the semi-solid agar to a depth of about 1-2 mm in the A sector (Fig. 1).
Every 24 h, samples were collected from the propagating P. aeruginosa growth front and inoculated to Mueller-Hinton agar plates (Becton Dickinson and Co.; USA) in order to gather enough biomaterial for further assessment of phenotypic characteristics (antibiotic resistance profile) and bacterial genome alterations.
Isolates were tested for meropenem susceptibility by determining MICs in two ways: 1) using meropenem E-tests (Epsilometer tests) in accordance with the manufacturer's guidelines (BioMerieux SA; France); 2) using the agar dilution method [8]. The MIC values were not interpreted from a clinical perspective, these were analyzed solely in terms of the MIC dynamics.
Trough meropenem concentrations in the semi-solid agar were assessed 240 h after the start of the experiment by high-performance liquid chromatography (HPLC) using a well-known technique [9].
Bacterial DNA was isolated from the 24-h culture of P. aeruginosa isolates grown on Mueller-Hinton agar (Becton Dickinson and Co.; USA) using the QIAamp DNA Mini Kit (Qiagen; Germany) in accordance with the manufacturer's protocol. DNA samples were stored at -20 °C. Ultrasonic fragmentation (Covaris; USA) of bacterial DNA (400 ng) with subsequent end repair and adapter ligation (MGI Tech; China) were used to prepare genomic DNA libraries. DNA libraries were washed with the Agencourt AMPure XP magnetic beads (Beckman Coulter; USA). The concentrations of bacterial DNA and DNA libraries were measured using the Qubit 4 fluorometer (Thermo Fisher Scientific; USA). Whole-genome sequencing was performed using the MGISEQ-2000 platform (MGI Tech; China). The read length was 250 bp. The quality was tested using the FASTQC (Babraham Institute; UK) and Trimmomatic v.0.38 (Usadel Lab; USA) software. Genomes were assembled de novo using the SPAdes 3.14 software [10]. The Contest16S web server was used to control the assembly completeness and eliminate the possibility of contamination. The quality of assemblies was evaluated in QUAST 5.0 [11]. Genomes were annotated using the RAST server [12] and the Prokka software [13].
To detect single nucleotide polymorphisms (SNPs), the short reads were mapped to the reference genome in Snippy [14]. The genome of "null" isolate, i.e. the isolate obtained after the ATCC 27853 P. aeruginosa strain adaptation to semi-solid agar that was used to launch the experiment, was used as a reference genome. The SnpEff software was used for annotation of the variants identified and prediction of their effects on the genes [15].
BLASTn tools (https://blast.ncbi.nlm.nih.gov/Blast.cgi) were used to analyze genes in the genomes of all the isolates obtained and amino acid sequences of the gene products. The ResFinder service and AMRFinderPlus algorithm included in the NCBI Pathogen Detection pipeline were used for assessment of resistance determinants [16, 17].
RESULTS
The dynamics of the P. aeruginosa propagation across the surface of semi-solid agar towards higher meropenem concentrations is provided in Fig. 1. The edge of the P. aeruginosa growth reached the zone with the maximum meropenem concentration in 168 h (7 days), and growth on the entire area of culture medium was observed within 240 h (10 days). At the end of the experiment meropenem concentration in the E sector of semi-solid agar (Fig. 1) was 56 pg/mL.
Fig. 1. The dynamics of P. aeruginosa propagation across the surface of semi-solid agar towards the higher concentrations of meropenem. The images were acquired after incubation for 48, 72, 96, 120, 144, 168, 192, 216, 240 h from the start of the experiment. The dashed lines refer to the boundaries which divide sectors A, B, C, D, E with various meropenem concentrations (0, 0,2, 20, 200, 2000 pg/mL, respectively) in the lower layer of solid growth medium (see Methods). Asterisk refers to the starting point (inoculation of the culture of P. aeruginosa ATCC 27853)
A total of 92 isolates were collected from the propagating P. aeruginosa growth front. Meropenem resistance of the isolates increased as the bacteria propagated towards higher meropenem concentrations (Fig. 2). The increase in MICs from 0.5 pg/mL to 2, 4, and 8 pg/mL was observed within 72 h after the start of the experiment. Isolates with MIC = 16 pg/mL and MIC = 32 pg/mL emerged after 144 h, while isolates with MIC = 64 pg/mL emerged after 216 h. The meropenem MICs > 8 pg/mL were reported in 61 isolates, and MICs > 32 were reported in 45 isolates.
Nonsynonymous mutations were found in 11 genes, including oprD, pbuE, nalD, nalC, spoTм mlaA, mexD, mexR, oprM, mraY, pbp3. Mutations of these genes were not detected in four genomes out of 92 (4.3%), these were genomes of isolates obtained in the first 48 h of growth. In other 88 genomes out of 92 (95.7%), various combinations of genes disrupted by mutations were detected (Table 1). The most frequent disrupted genes were oprD, pbuE, nalD (Table 2). Mutations of genes nalD, spoT, mlaA, mexR, mraY, pbp3 were associated with high levels of resistance in the isolates carrying these mutations, the meropenem MICs of which exceeded 8 pg/mL (Table 2). In contrast, the oprM gene mutations were found only in four strains out of 92 (4.3%) with meropenem MICs exceeding 8 pg/mL. Among 84 strains carrying oprD mutations four highly susceptible isolates with meropenem MICs of 0.5-2 pg/mL were found. In these isolates oprD mutations resulted in L292Q, L252P, G307D substitutions in three cases and in premature termination of protein synthesis (W138stop) in one case. The genotype carrying a combination of mutations in oprD, pbuE, nalD was the most common (Table 1).
The dynamics of mutation emergence at various stages of biomaterial collection is provided in Table 2. The first stable mutations emerged in the oprD and pbuE genes within 72 h after the start of the experiment. The pbuE mutation resulting in the A261D substitution was represented by only one variant and was combined with different variants of other mutations evenly in 77 isolates out of 92 (83.7%). The oprD mutations were represented by nine variants. However, only two variants of mutations resulting in the G307D (oprD-G307D) and L238P (oprD-L238P) substitutions were found in the majority of isolates carrying oprD mutations (73 out of 84; 86.9%). The other seven variants of oprD mutations were relatively rare, these were found in 11 isolates with mutant oprD genes out of 84 (13.1%). Thus, the original strain produced two clones, oprD-G307D and oprD-L238P (Fig. 2). The strain that was a direct ancestor of the clone oprD-G307D emerged within 96 h of the experiment and its meropenem MIC was 2 pg/mL. The strain that was a direct ancestor of the clone oprD-L238P was not isolated during the experiment. Hypothetically, it could
emerge within 120 h after the start of the experiment. Evolution of the main clones, oprD-G307D and oprD-L238P, was associated with reduction of their meropenem susceptibility (Fig. 2) and accumulation of mutations in other genes important for development of carbapenem resistance.
Starting from hour 144 of the experiment, isolates carrying nalD mutation resulting in the G172D substitution emerged among strains of the oprD-G307D clone. By the end of the experiment, 14 strains of the oprD-G307D clone out of 34 were carriers of this mutation.
The oprD-L238P clone was related to the other nalD mutations resulting in the T11N (24 isolates of the clone out of 39) and H56P (4 isolates of the clone out of 39) substitutions. The deletion in the mlaA gene (5 bp del (nucleotides 423-427)) resulting in the open reading frame shift was also found only in isolates (11 out of 39) of the clone oprD-L238P. The mlaA deletion was combined with the T11N mutation of the nalD gene in all cases.
Mutations of genes mexR, oprM, mraY, pbp3, nalC were found only in few isolates.
Propagating P. aeruginosa growth front (hours from the start of the experiment):
- 240
- 216
192
168
- 144
- 120
_ 96
_ 72
- 48
- 24
•j Starting point
(J) Hypothetical ancestor of the clone
Fig. 2. Topology of P. aeruginosa clones on the surface of semi-solid agar with the increasing meropenem concentrations after 240 h of incubation. The numbers refer to meropenem MICs (pg/mL) of isolates collected from the sites designated with the numbers. White arrows demonstrate the oprD-L238P clone propagation, black arrows demonstrate the oprD-G307D clone propagation
Table 1. Genes and gene combinations where nonsynonymous mutations were found
№ Combinations of genes carrying mutations Number of strains (% of all strains, n = 92)
1 oprD, pbuE, nalD 20 (22.2)
2 oprD, pbuE 11 (12.0)
3 oprD, pbuE, nalD, spoT 10 (10.9)
4 oprD, pbuE, nalD, mlaA 11 (12.0)
5 oprD, pbuE, mexD 9 (10)
6 oprD 6 (7)
7 oprD, pbuE, spoT 4 (4)
8 oprD, pbuE, mexR 3 (3)
9 pbuE 3 (3)
10 oprD, nalD 2 (2)
11 oprD, pbuE, mexR, mraY 2 (2)
12 oprD, oprM 2 (2)
13 oprM 1 (1)
14 oprD, nalC, pbuE 1 (1)
15 oprD, pbuE, oprM 1 (1)
16 oprD, pbuE, spoT, mexD 1 (1)
17 oprD, pbuE, pbp3 1 (1)
18 No mutations 4 (4)
DISCUSSION
When discussing phenotypic traits of the P. aeruginosa adaptation to meropenem, the focus should be placed on the rate of developing resistance. The resistance levels of certain isolates obtained at this stage reached meropenem MICs of 32 |jg/ml_ within 6 days. The maximum meropenem MICs were 64 jg/m_, these were 128 times higher than the MIC values registered in isolates obtained within the first 48 h of the experiment. The fact of finding isolates with MIC values of 32 jg/m_ in the zone with the actual meropenem content of 56 jg/m_ can be explained by the differences between the conditions of determining MICs by reference methods (Epsilometer test and agar dilution method) and the experimental conditions (growth medium, incubation time).
Gene mutation was revealed along with the meropenem MIC increase in distinct strains on the term of 72 h. A total of 11 mutated genes were found during the experiment. Among those the association with carbapenem resistance was proven only for oprD, nalC, nalD, mexD, mexR, and pbp3 [18-21]. The
role of oprM, pbuE, spoT, mraY, mlaA genes in the development of antibiotic resistance has not been reported before, however, this does not eliminate their indirect effects on adaptation to carbapenems.
When considering the mutation pattern as a whole, attention should be paid to the phenomenon of cloning. Two major clonal lines emerged within 72-96 h. All the members of the first clonal line carried the oprD mutation resulting in the G307D substitution. The oprD mutation resulted in the L238P substitution in all representatives of the other clonal line. New mutations, that resulted in the increased phenotypic resistance to meropenem, emerged and were partially fixed in the clones produced. Along with these lines, single clones carrying other oprD mutations emerged. These clones showed no progressive spread, while some of the clones had higher meropenem MICs than the surrounding representatives of the clones oprD-G307D and oprD-_238P (Fig. 2). Perhaps, mutations in the non-successful but highly resistant clones were the factor adversely affecting the outcome of intraspecific competition. It is worth mentioning that oprD disruption in the
Table 2. Meropenem resistant phenotypes of P. aeruginosa and genes that can possibly determine carbapenem resistance
№ Gene Time of mutation emergence (hours since the start) Number of strains (% of the group) carrying mutations in the groups with various meropenem MICs (Mg/mL) Number of strains carrying mutations (% of all strains, n = 92)
< 8, n = 31 > 8 < 32, n = 16 > 32, n = 45
1 oprD 72 23 (74,2) 16 (100) 45 (100) 84 (91,3)
2 pbuE 72 16 (51,6) 16 (100) 45 (100) 77 (83,7)
3 nalD 120 1 (3) 12 (75) 30 (66,7) 43 (46,7)
4 spoT 192 0 (0) 1 (6) 14 (31,1) 15 (16,3)
5 mlaA 144 0 (0) 1 (6) 10 (22,2) 11 (12,0)
6 mexD 120 3 (10) 3 (29) 4 (9) 10 (10,9)
7 mexR 144 0 (0) 2 (13) 3 (7) 5 (5)
8 oprM 72 4 (13) 0 (0) 0 (0) 4 (4)
9 mraY 168 0 (0) 0 (0) 2 (4) 2 (2)
10 pbp3 144 0 (0) 0 (0) 1 (2) 1 (1)
11 nalC 72 1 (3) 0 (0) 0 (0) 0 (0)
P. aeruginosa meropenem resistant isolates is observed not only in experimental settings. Thus, five highly meropenem resistant (MIC > 32 jg/m_) P. aeruginosa strains out of six, which were found in individuals with cystic fibrosis and produced no carbapenemases, carried mutations in the oprD genes [4]. At the same time, disruption of one gene (oprD) is insufficient for development of meropenem resistance. Even the strain carrying the oprD nonsense mutation (W138stop termination codon) remained higly susceptible to meropenem. Accumulation of chromosomal mutations in multiple chromosome genes directly or indirectly affecting antibiotic susceptibility is essential for resistance.
We do not exclude the possibility that some isolates with unique genotypes have not been selected during the experiment, and information about these isolates has been lost. The example of this is uncertainty about the progenitor of the oprD-_238P clone being an intermediate between the highly susceptible and highly resistant strains. However, in contrast
to evolution in liquid medium, spatiotemporal resistance model makes it possible to isolate a larger number of clones and avoid the loss of information about possible mutations leading to resistance.
CONCLUSIONS
In experimental settings P. aeruginosa develops high meropenem resistance very quickly (in 6 days). Evolution of resistance is associated with cloning involving the emergence of multiple clones with various genotypes. Mutagenesis that involves 11 genes, including oprD, pbuE, nalD, nalC, spoT, mlaA, mexD, mexR, oprM, mraY, pbp3, provides the basis for cloning. Regardless of the levels of their meropenem resistance, some of the emerging clones do not progressively develop and are replaced by the more successful clones. The model used during the experiment is a convenient tool to obtain the set of variants with various resistant genotypes.
References
1. Lazareva AV, Chebotar IV, Kryzhanovskaya OA, Chebotar VI, Mayanskiy NA. Pseudomonas aeruginosa: patogennost', patogenez i patologiya. Klin Mikrobiol Antimikrob Ximioter. 2015; 17 (3): 17086. Russian.
2. WHO priority list for research and development of new antibiotics for antibiotic-resistant bacteria. Geneva: World Health Organization, 2017. Available from: https://www.who.int/news/ item/27-02-2017-who-publishes-list-of-bacteria-for-which-new-antibiotics-are-urgently-needed (accessed September 1, 2012).
3. Oliver A, Mulet X, Lopez-Causape C, Juan C. The increasing threat of Pseudomonas aeruginosa high-risk clones. Drug Resistance Updates. 2015; 21: 41-59. Available from: https:// doi.org/10.1016/j.drup.2015.08.002.
4. Lopez-Causape C, Sommer LM, Cabot G, Rubio R, Ocampo-Sosa AA, Johansen H et al. Evolution of the Pseudomonas aeruginosa mutational resistome in an international cystic fibrosis clone. Sci Rep. 2017; 7: 5555. Available from: https://doi. org/10.1038/s41598-017-05621-5.
5. Barbosa C, Trebosc V, Kemmer C, Rosenstiel P, Beardmore R, Schulenburg H, et al. Alternative evolutionary paths to bacterial antibiotic resistance cause distinct collateral effects. Mol Biol Evol. 2017; 34 (9): 2229-44. Available from: https://doi.org/10.1093/ molbev/msx158.
6. Baym M, Lieberman TD, Kelsic ED, Chait R, Gross R, Yelin I, et al. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 2016; 353 (6304): 1147-51. Available from: https://doi. org/10.1126/science.aag0822.
7. Savinova TA, Bocharova YA, Chaplin AV, Korostin DO, Shamina OV, Mayanskiy NA, et al. Meropenem-induced reduction in colistin susceptibility in Pseudomonas aeruginosa strain ATCC 27853. Bulletin of RSMU. 2022; 1: 30-4. Available from: https://doi. org/10.24075/brsmu.2022.001.
8. European Committee for Antimicrobial Susceptibility Testing (EUCAST) of the European Society of Clinical Microbiology and Infectious Diseases (ESCMID). Determination of minimum inhibitory concentrations (MICs) of antibacterial agents by agar dilution. Clin Microbiol Infect. 2000; 6 (9): 509-15. Available from: https://doi.org/10.1046/j.1469-0691.2000.00142.x.
9. Kazanova AM, Stepanova ES, Makarenkova LM, Chistyakov VV, Zyryanov SK, Senchenko SP. Razrabotka i validaciya metodiki kolichestvennogo opredeleniya meropenema v plazme krovi dlya terapevticheskogo lekarstvennogo monitoringa. Ximiko-farmacevticheskij zhurnal. 2020; 54 (4): 56-60. Available from: https://doi.org/10.30906/0023-1134-2020-54-4-56-60. Russian.
10. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012; 19:
455-77. Available from: https://doi.org/10.1089/cmb.2012.0021.
11. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013; 29 (8): 1072-5. Available from: https://doi.org/10.1093/ bioinformatics/btt086.
12. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014; 42: D206-14. Available from: https://doi.org/10.1093/nar/gkt1226.
13. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014; 30 (14): 2068-9. Available from: https://doi. org/10.1093/bioinformatics/btu153.
14. Seemann T. 2015. Snippy: fast bacterial variant calling from NGS reads. GitHub. Available at: https://github.com/tseemann/snippy (accessed November 2022).
15. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012; 6 (2): 80-92. Available from: https://doi.org/10.4161/fly.19695.
16. Afgan E, Baker D, Batut B, van den Beek M, Bouvier D, Cech M, et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res. 2018; 46 (W1): W537-44. Available from: https://doi.org/10.1093/nar/gky379 .
17. Bortolaia V, Kaas RS, Ruppe E, Roberts MC, Schwarz S, Cattoir V, et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother. 2020; 75 (12): 3491-500. Available from: https://doi.org/10.1093/jac/dkaa345.
18. Li H, Luo YF, Williams BJ, Blackwell TS, Xie CM. Structure and function of OprD protein in Pseudomonas aeruginosa: from antibiotic resistance to novel therapies. Int J Med Microbiol. 2012; 302 (2): 63-8. Available from: https://doi.org/10.1016/j. ijmm.2011.10.001.
19. Lister PD, Wolter DJ, Hanson ND. Antibacterial-resistant Pseudomonas aeruginosa: clinical impact and complex regulation of chromosomally encoded resistance mechanisms. Clin Microbiol Rev. 2009; 22 (4): 582-610. Available from: https://doi. org/10.1128/CMR.00040-09.
20. Srikumar R, Kon T, Gotoh N, Poole K. Expression of Pseudomonas aeruginosa multidrug efflux pumps MexA-MexB-OprM and MexC-MexD-OprJ in a multidrug-sensitive Escherichia coli strain. Antimicrob Agents Chemother. 1998; 42 (1): 65-71. Available from: https://doi.org/10.1128/AAC.42.1.65.
21. Glen KA, Lamont IL. ß-lactam Resistance in Pseudomonas aeruginosa: Current Status, Future Prospects. Pathogens. 2021; 10 (12): 1638. Available from: https://doi.org/10.3390/ pathogens10121638.
Литература
1. Лазарева А. В., Чеботарь И. В., Крыжановская О. А., Чеботарь В. И., Маянский Н. А. Pseudomonas aeruginosa: патогенность, патогенез и патология. Клин Микробиол Антимикроб Химиотер. 2015; 17 (3): 170-86.
2. WHO priority list for research and development of new antibiotics for antibiotic-resistant bacteria. Geneva: World Health Organization, 2017. Available from: https://www.who.int/news/ item/27-02-2017-who-publishes-list-of-bacteria-for-which-new-antibiotics-are-urgently-needed (accessed September 1, 2012).
3. Oliver A, Mulet X, Lopez-Causape C, Juan C. The increasing threat of Pseudomonas aeruginosa high-risk clones. Drug Resistance Updates. 2015; 21: 41-59. Available from: https:// doi.org/10.1016/j.drup.2015.08.002.
4. Lopez-Causape C, Sommer LM, Cabot G, Rubio R, Ocampo-Sosa AA, Johansen H et al. Evolution of the Pseudomonas aeruginosa mutational resistome in an international cystic fibrosis clone. Sci Rep. 2017; 7: 5555. Available from: https://doi. org/10.1038/s41598-017-05621-5.
5. Barbosa C, Trebosc V, Kemmer C, Rosenstiel P, Beardmore R, Schulenburg H, et al. Alternative evolutionary paths to bacterial antibiotic resistance cause distinct collateral effects. Mol Biol Evol. 2017; 34 (9): 2229-44. Available from: https://doi.org/10.1093/ molbev/msx158.
6. Baym M, Lieberman TD, Kelsic ED, Chait R, Gross R, Yelin I, et al. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 2016; 353 (6304): 1147-51. Available from: https://doi. org/10.1126/science.aag0822.
7. Savinova TA, Bocharova YA, Chaplin AV, Korostin DO, Shamina OV, Mayanskiy NA, et al. Meropenem-induced reduction in colistin susceptibility in Pseudomonas aeruginosa strain ATCC 27853. Bulletin of RSMU. 2022; 1: 30-4. Available from: https://doi. org/10.24075/brsmu.2022.001.
8. European Committee for Antimicrobial Susceptibility Testing (EUCAST) of the European Society of Clinical Microbiology and Infectious Diseases (ESCMID). Determination of minimum inhibitory concentrations (MICs) of antibacterial agents by agar dilution. Clin Microbiol Infect. 2000; 6 (9): 509-15. Available from: https://doi.org/10.1046/j.1469-0691.2000.00142.x.
9. Казанова А. М., Степанова Е. С., Макаренкова Л. М., Чистяков В. В., Зырянов С. К., Сенченко С. П.. Разработка и валидация методики количественного определения меропенема в плазме крови для терапевтического лекарственного мониторинга. Химико-фармацевтический журнал. 2020; 54 (4): 56-60. Available from: https://doi.org/10.30906/0023-1134-2020-54-4-56-60.
10. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012; 19:
455-77. Available from: https://doi.org/10.1089/cmb.2012.0021.
11. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013; 29 (8): 1072-5. Available from: https://doi.org/10.1093/ bioinformatics/btt086.
12. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014; 42: D206-14. Available from: https://doi.org/10.1093/nar/gkt1226.
13. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014; 30 (14): 2068-9. Available from: https://doi. org/10.1093/bioinformatics/btu153.
14. Seemann T. 2015. Snippy: fast bacterial variant calling from NGS reads. GitHub. Available at: https://github.com/tseemann/snippy (accessed November 2022).
15. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012; 6 (2): 80-92. Available from: https://doi.org/10.4161/fly.19695.
16. Afgan E, Baker D, Batut B, van den Beek M, Bouvier D, Cech M, et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res. 2018; 46 (W1): W537-44. Available from: https://doi.org/10.1093/nar/ gky379 .
17. Bortolaia V, Kaas RS, Ruppe E, Roberts MC, Schwarz S, Cattoir V, et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother. 2020; 75 (12): 3491-500. Available from: https://doi.org/10.1093/jac/dkaa345.
18. Li H, Luo YF, Williams BJ, Blackwell TS, Xie CM. Structure and function of OprD protein in Pseudomonas aeruginosa: from antibiotic resistance to novel therapies. Int J Med Microbiol. 2012; 302 (2): 63-8. Available from: https://doi.org/10.1016/j. ijmm.2011.10.001.
19. Lister PD, Wolter DJ, Hanson ND. Antibacterial-resistant Pseudomonas aeruginosa: clinical impact and complex regulation of chromosomally encoded resistance mechanisms. Clin Microbiol Rev. 2009; 22 (4): 582-610. Available from: https://doi. org/10.1128/CMR.00040-09.
20. Srikumar R, Kon T, Gotoh N, Poole K. Expression of Pseudomonas aeruginosa multidrug efflux pumps MexA-MexB-OprM and MexC-MexD-OprJ in a multidrug-sensitive Escherichia coli strain. Antimicrob Agents Chemother. 1998; 42 (1): 65-71. Available from: https://doi.org/10.1128/AAC.42.1.65.
21. Glen KA, Lamont IL. ß-lactam Resistance in Pseudomonas aeruginosa: Current Status, Future Prospects. Pathogens. 2021; 10 (12): 1638. Available from: https://doi.org/10.3390/ pathogens10121638.
