Abstract
Acinetobacter baumannii (A. baumannii) attributes 26% of the mortality rate in hospitalized patients, and the percentage can rise to 46 in patients admitted to ICU as it is a major cause of ventilator-associated pneumonia. It has been nominated as the critical priority organism by WHO for which new therapeutic drugs are urgently required. To understand the genomic identification of different strains, antimicrobial resistance patterns, and epidemiological typing of organisms, whole-genome sequencing (WGS) analysis provides insight to explore new epitopes to develop new drugs against the organism. Therefore, the study is aimed at investigating the whole genome sequence of A. baumannii strains to report the new intensifications in its genomic profile. The genome sequences were retrieved from the NCBI database system. Pan-genome BPGA (Bacterial Pan-genome Analysis Tool) was used to analyze the core, pan, and species-specific genome analysis. The pan and core genome curves were extrapolated using the empirical power law equation f(x) = a.xb and the exponential equation f1(x) = c.e (d.x). To identify the resistant genes with resistant mutations against antibiotics, ResFinder and Galaxy Community hub bioinformatics tools were used. According to pan-genome analysis, there were 2227 core genes present in each species of the A. baumannii genome. Furthermore, the number of accessory genes ranged from 1182 to 1460, and the unique genes in the genome were 931. There were 325 exclusively absent genes in the genome of Acinetobacter baumannii. The pan-genome analysis showed that there is a 5-fold increase in the genome of A. baumannii in 5 years, and the genome is still open. There is the addition of multiple unique genes; among them, genes participating in the function of information and processing are increased.
1. Introduction
A nonfermenter Gram-negative coccobacillus known as A. baumannii was thought to be a low category pathogen in past decades but now has arisen as a foremost cause of community and hospital-acquired infections [1]. It can survive in any environment for longer durations, and it is found to be resistant to many classes of antibiotics and disinfectants [2]. A. baumannii has been identified as a responsible factor that causes pneumonia and septicemia in immunocompromised individuals. It confers 26% of mortality rate in hospitalized patients, and the percentage can rise to 46 in patients admitted in ICU as it is a major cause of ventilator-associated pneumonia [3, 4]. It has been categorized among ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) pathogens. WHO has kept carbapenem-resistant A. baumannii (CRAB) as the topmost priority organism for which new therapeutic drugs are urgently required; therefore, rigorous antibiotic stewardship and infection control measures should be taken to control the MDR infections and make it a presenting issue for new therapeutic options [5].
It has been suggested that quorum sensing (QS) is involved in the synthesis of multidrug-resistant biofilm, one of the major virulent factors of A. baumannii. This multidrug-resistant biofilm provides insulation to organisms that help them in surviving the harsh environment. Figure 1 shows the virulent factors of A. baumannii [6, 7]. Furthermore, genomic plasticity provides the ability for A. baumannii to survive on abiotic surfaces. Acquiring genes by horizontal gene transfer and through membrane vesicles has contributed to the development of MDR and XDR strains of these virulent bacteria [8–10].
Figure 1.
Virulence factors of A. baumannii [6].
Figure 1 demonstrates the variety of virulence characteristics that enable A. baumannii to tenaciously resist environment, form biofilms, migrate, interact with host cells, and secrete proteins.
Whole-genome sequencing (WGS) provides deep knowledge regarding species identification, antimicrobial resistance, and epidemiological typing of organisms to researchers. It helps in the identification of new drug targets and the development of new drugs [11]. The ability of WGS to distinguish the strains that differ by even a single nucleotide provides high-resolution information [12]. It has been documented that the A. baumannii possesses a dynamic genome, and it has been postulated that the genomic sequence of this virulent organism may vary in different regions of the globe [13, 14]. The aim of the study was to analyze the genomes of A. baumannii using pan-genomic techniques and to generate significant data on its genomic characteristics on different variants.
2. Methodology
Pan-genome BPGA (Bacterial Pan-genome Analysis Tool) was used to analyze the core, pan, and species-specific genome analysis. A total of 50 complete genomes were retrieved from the NCBI database, and 2 gbk files were used as input files in the BPGA pipeline. Furthermore, genome assembly and annotation reports were opted to reach the genomic sequences. Then, sequence files were downloaded from the database (GenBank). Usearch tool was applied to develop clusters. The pipeline was used for 99% sequence identity as the cut off value for further analysis. Additionally, cluster of orthologs (COGs) and KEGG pathway detection was carried out by using the BPGA tool. Then, phylogeny based on core and pan proteome was explored using COG distribution, KEGG pathway analyses, and COG distribution. Furthermore, the retrieved data of genomes of A. baumannii were analyzed with and in addition mass screening of antimicrobial resistance, and virulence gene was conducted by ABRicate software [15, 16] to get the information regarding acquired resistant genes and their resistance against specific antibiotic drugs.
Central genome is crucial in each species, and it is responsible for housekeeping of cell, but the axillary genome carries the genes of resistance, stress, and pathogenesis.
3. Results and Discussion
The functional adaptations of Acinetobacter baumannii showed Bpan values of 0.169136 (i.e., <1), suggesting that the pan-genome is still open but may be closed soon. It highlights that to combat the environmental stress, A. baumannii has gone through various evolutionary changes (Table 1). Furthermore, the pan-genome analysis also accentuated that the number of accessory gene families increases as the genome size increases. A total of 2227 core genes were present in all strains; whereas there were 1301 ± 61 number of accessory genes in the genome. There were 325 exclusively absent genes in the genome of A. baumannii; moreover, there were 931 unique genes present in the genome, and the genome no. 1 has acquired the highest number of unique genes, that is, 153 as shown in Table 2.
Table 1.
Pan-genome statistics.
| Pan-genome | Core genome | |
|---|---|---|
| Fit law | Power | Exponential |
| Equation | f(x) = a.x∧b | f1(x) = c.e∧(d.x) |
| Parameters | a = 3625.94 | c = 2994.74 |
| __________ | b = 0.169136 | d = −0.00720414 |
| Expected size | 6846 | 0 |
| Estimated size | 7027.12 | 2088.93 |
Table 2.
Number of unique genes present in different species of A. baumannii.
| Genome number | Gene ID | No. of accessory genes | No. of unique genes | No. of exclusively absent genes |
|---|---|---|---|---|
| 1 | NZ_CP015121 | 1289 | 0 | 2 |
| 2 | NZ_CP045110 | 1289 | 1 | 1 |
| 3 | NZ_CP059040 | 1282 | 0 | 7 |
| 4 | NZ_CP046654 | 1450 | 153 | 8 |
| 5 | NZ_CP059300 | 1372 | 21 | 6 |
| 6 | NZ_CP009257 | 1337 | 28 | 11 |
| 7 | NZ_CP018254 | 1342 | 55 | 5 |
| 8 | NZ_CP027611 | 1460 | 6 | 0 |
| 9 | NZ_CP050385 | 1314 | 22 | 5 |
| 10 | NZ_CP033869 | 1279 | 63 | 9 |
| 11 | NZ_CP048849 | 1281 | 94 | 19 |
| 12 | NZ_CP014528 | 1211 | 56 | 78 |
| 13 | NZ_CP022283 | 1360 | 36 | 4 |
| 14 | CP027528 | 1367 | 13 | 18 |
| 15 | CP040259 | 1223 | 21 | 3 |
| 16 | NZ_CP050403 | 1327 | 24 | 7 |
| 17 | NZ_CP041035 | 1304 | 63 | 30 |
| 18 | NZ_CP023020 | 1344 | 0 | 1 |
| 19 | NZ_CP021326 | 1329 | 0 | 5 |
| 20 | NZ_CP060732 | 1305 | 1 | 0 |
| 21 | NZ_CP051869 | 1350 | 0 | 0 |
| 22 | NZ_CP072280 | 1350 | 0 | 0 |
| 23 | NZ_CP072295 | 1350 | 0 | 0 |
| 24 | CP072275 | 1351 | 0 | 0 |
| 25 | NZ_CP072290 | 1349 | 0 | 0 |
| 26 | NZ_CP072300 | 1260 | 0 | 0 |
| 27 | NZ_CP027178 | 1284 | 14 | 19 |
| 28 | NZ_CP045528 | 1306 | 0 | 0 |
| 29 | NZ_CP051875 | 1349 | 0 | 0 |
| 30 | NZ_CP072270 | 1329 | 5 | 1 |
| 31 | NZ_CP026338 | 1192 | 27 | 28 |
| 32 | NZ_CP060029 | 1345 | 0 | 0 |
| 33 | NZ_CP010779 | 1239 | 1 | 3 |
| 34 | NZ_CP013924 | 1301 | 0 | 0 |
| 35 | NZ_CP040050 | 1302 | 0 | 0 |
| 36 | NZ_CP040050 | 1338 | 0 | 0 |
| 37 | NZ_CP072398 | 1339 | 0 | 0 |
| 38 | NZ_CP072398 | 1246 | 0 | 3 |
| 39 | NZ_CP027183 | 1334 | 0 | 6 |
| 40 | NZ_CP020597 | 1279 | 4 | 2 |
| 41 | NZ_CP014215 | 1332 | 1 | 5 |
| 42 | NZ_CP059354 | 1182 | 0 | 0 |
| 43 | NZ_CP059729 | 1182 | 0 | 0 |
| 44 | NZ_CP059729 | 1273 | 64 | 7 |
| 45 | NZ_CP012952 | 1199 | 108 | 4 |
| 46 | CP044519 | 1237 | 18 | 11 |
| 47 | NZ_CP024576 | 1259 | 7 | 5 |
| 48 | NZ_CP050523 | 1194 | 11 | 5 |
| 49 | NZ_CP039341 | 1285 | 14 | 7 |
| 50 | NZ_LS483472 | 1288 | 0 | 0 |
The plateau formation on the pan-genome indicated that the genome is still open and will be closed soon. The pan-genome of bacteria including A. baumannii should be kept open permanently due to its evolution and horizontal gene transfer as highlighted in core pan plot (Figure 2). The new genes that contribute to the highest number in pan-genome of A. baumannii were 931 (Figure 3). COG analysis showed that the core and accessory genes were involved in the function of metabolism prominently; however, unique genes were found to be involved in the function of information storage and processing (Figures 4(a) and 4(b)).
Figure 2.
The pan and core genome plot of A. baumannii genomes.
Figure 3.
Number of new genes contributing to pan-genome of Acinetobacter baumannii.
Figure 4.
(a) COG distribution of the genes making up the core, accessory, and unique portion of 164 the A. baumannii genome. (b) Functional distribution of core, accessory, and unique genes.
Moreover, comparative KEGG analysis functionally distributed the core, accessory, and unique genes and highlighted that these genes were mostly responsible for the human diseases, genetic information, and environmental adaptations as shown in Figures 5(a) and 5(b).
Figure 5.
(a) KEGG distribution of core, accessory, and unique genes. (b) KEGG analysis, functional distribution of core, accessory, and unique genes in A. baumannii genome.
The A. baumannii definitely be categorized as an emerging pathogen of clinical significance. It has gained the attention of scientists in recent years; increase in the size of its genome and resistance to multiple drugs are making this organism more virulent, particularly in hospital settings [17]. The increase in the occurrence of infections due to the vulnerability of this organism is disturbing healthcare settings as well as stroking a high economic burden [18]. In order to understand its metabolic processes and resistance profile, study of its genome and study of variations in reported genetic patterns from different countries is required. The data from these studies will facilitate the researchers to target the A. baumannii according to its genetic identification and will be beneficial to overcome the resistance [19, 20]. In this manuscript, we have highlighted the current pan-genomics of Acinetobacter baumannii. Furthermore, we also accentuate the distribution of its genes according to the metabolic processes (i.e., COG and KEGG analyses) involved in its genome. Since 2011 studies have been done on the pan-genome analysis of A. baumannii initially six and seven, and in 2016, thirty genomes were studied; however, now in 2022, the number of genomes has been increased at the NCBI website that we have analyzed in the current study [21, 22]. The information of the genome of an organism provides the details of its genetic evolution; it highlights the increase in pan-genome size which eventually indicates that the genome is still open and increasing. According to pan-genome analysis, its genome has been found open which is indicating that the genome can still acquire more genes and environmental adaptations and can lose certain genes, that is, further strengthening its genomic evaluation and vulnerability [23, 24].
The pan-genome of A. baumannii seemed to be composed of 37254 genes; out of which, 36323 genes were formulating the core genome, 931 were unique genes, and 301 genes were found to be absent in the current analysis. Compared to the analysis of Hassan et al., the current genome has increased 5-folds in five years [21]. The increase in the size of genome among prokaryotes including A. baumannii is attributed to horizontal gene transfer; it has been identified that due to the absence of sexual reproduction, bacteria evolve through conjugation that facilitates gene transfer among different strains of organisms [25]. This gene transfer increases the size of the genome and resistance profile in the organisms that have not encountered the particular antibiotic before, but the gene of resistance was transferred to it from the bacterial strain which was exposed to that antibiotic earlier [26]. The COG distribution analysis (Figure 4(a)) revealed that among core genes in the new genome of fifty plasmids, the higher percentage observed was of genes involved in performing the function of metabolism; however, in unique genes, the major proportion was obtained by genes which attribute function of information and processing in the genome. This is highlighting that the evolution in the genome particularly the addition of unique genes is increasing the information that is thought to be a major factor contributing an increase in resistance against multiple antimicrobial drugs [27].
The KEGG analysis of the A. baumannii highlighted the functional distribution of core, assessor, and unique genes of its genome. As depicted in Figure 5(b), it was identified that there was more adaptation of accessory and unique genes that were used for the metabolic processes including metabolism of amino acids, carbohydrates, vitamins, and nucleotides. Additionally, this analysis also revealed that among the drug resistance, there was highest acquisition of unique genes highlighting the potential of this organism to become one of the most resistant bacteria. Similar to the data reported by Xiong et. al., the KEGG analysis of the current study also emphasized that there was more functional adaptation in the genes of amino acid metabolism; however, in their study, they knocked out the abal to evaluate the resistant profile considering it as the most important virulence factor; however, they could not found any change as there was no difference in virulence as well as resistance profile of the organism that in perspective of the current study may be due to acquisition of unique genes which are responsible for drug resistance [28].
The phylogenic trees were formulated to compare the evolution of the pan and core genomes of A. baumannii. Figures 6(a) and 6(b) depict the phylogenic trees of the pan and core genomes.
Figure 6.
(a) Pan-genome phylogenic tree. (b) Core genome phylogenic tree.
The resistance acquisition was analyzed by ResFinder software, and mass screening of resistant genes was evaluated by ABRicat tool. According to the findings of ResFinder, the genome of A. baumannii seemed to be resistant against all antibiotic drug classes including beta lactams, aminoglycosides, fluoroquinolones, and sulfonamides. However, the ABRicat analysis revealed that all the antibiotic drugs belonging to different classes can come out to be ineffective, as the genome of A. baumannii has acquired mutant genes possessing resistance against conventionally used antibiotic drugs. Table 3 shows resistant genes against available therapeutic options.
Table 3.
Resistant genes against available therapeutic options for A. baumannii (ResFinder and ABRicat analyses).
| Resistant gene | Accession no. | ResFinder | ABRicat | Coverage |
|---|---|---|---|---|
| aac(3)-Ia | X15852 | Aminoglycoside resistance | Gentamicin | 87.07865169 |
| aac(3)-IIa | CP023555 | Aminoglycoside resistance | Gentamicin; tobramycin | 100 |
| aac(6′)-Ian | AP014611 | Warning: gene is missing from note files. Please inform curator. | Amikacin; tobramycin | 100 |
| aac(6′)-Ibcr | EF636461 | Fluoroquinolone and aminoglycoside resistance | Streptomycin | 100 |
| aac(6′)-Ib-Hangzhou | FJ503047 | Warning: gene is missing from note files. Please inform curator. | Streptomycin | 100 |
| aadA1 | JQ480156 | Aminoglycoside resistance | Streptomycin | 100 |
| aadA24 | DQ677333 | Aminoglycoside resistance | Gentamicin; tobramycin | 98.97435897 |
| aadA2b | D43625 | Aminoglycoside resistance | Streptomycin | 100 |
| ant(3″)-Ia | X02340 | Warning: gene is missing from note files. Please inform curator. | 81.48148148 | |
| aph(3′)-Ia | X62115 | Aminoglycoside resistance | Streptomycin | 100 |
| aph(3″)-Ib | AF321550 | Aminoglycoside resistance alternate name; aph(3″)-Ib | Streptomycin | 100 |
| aph(3′)VIa | X07753 | Aminoglycoside resistance | Amikacin | 100 |
| aph(6)-Id | M28829 | Aminoglycoside resistance alternate name; aph(6)-Id | Streptomycin | 100 |
| armA | AY220558 | Aminoglycoside resistance | Streptomycin | 100 |
| ARR-2 | HQ141279 | Rifampicin resistance | Streptomycin | 100 |
| blaADC-25 | EF016355 | Beta-lactam resistance | Amikacin; gentamicin; tobramycin | 100 |
| blaCARB-14 | JQ364968 | Warning: gene is missing from note files. Please inform curator. | 100 | |
| blaCTXM-124 | JQ429324 | Beta-lactam resistance | 100 | |
| blaCTXM-15 | AY044436 | Beta-lactam resistance alternate name; UOE-1 | Ampicillin; amoxicillin; piperacillin | 100 |
| blaNDM-1 | FN396876 | Beta-lactam resistance | Amoxicillin; ampicillin; aztreonam; cefepime; cefotaxime; ceftazidime; ceftriaxone; piperacillin; ticarcillin | 100 |
| blaOXA-235 | JQ820240 | Beta-lactam resistance | Amoxicillin; amoxicillin+clavulanic acid; ampicillin; ampicillin+clavulanic acid; cefepime; cefixime; cefotaxime; cefoxitin; ceftazidime; ertapenem; imipenem; Meropenem; piperacillin; piperacillin+tazobactam | 100 |
| blaOXA-239 | JQ837239 | Beta-lactam resistance | 100 | |
| blaOXA-371 | AB871653 | Beta-lactam resistance | Amoxicillin; +clavulanic acid; ampicillin; +clavulanic_; ceftazidime; piperacillin | 100 |
| blaOXA-402 | JX865391 | Warning: gene is missing from note files. Please inform curator. | 100 | |
| blaOXA-64 | AY750907 | Beta-lactam resistance | Imipenem; meropenem | 100 |
| blaOXA-65 | AY750908 | Beta-lactam resistance | Amoxicillin; ampicillin; cefoxitin; imipenem; meropenem; piperacillin; piperacillin+tazobactam | 100 |
| blaPER-1 | GU944725 | Beta-lactam resistance | 100 | |
| blaPER-7 | HQ713678 | Beta-lactam resistance | Amoxicillin; ampicillin | 100 |
| blaTEM1A | HM749966 | Beta-lactam resistance alternate name; RblaTEM-1 | 100 | |
| catA1 | V00622 | Phenicol resistance | Amoxicillin; ampicillin; cephalothin; piperacillin; ticarcillin | 100 |
| catB8 | AF227506 | Phenicol resistance | Chloramphenicol | 100 |
| cmlA1 | M64556 | Phenicol resistance | Trimethoprim | 99.91769547 |
| dfrA1 | X00926 | Trimethoprim resistance | Chloramphenicol; florfenicol | 100 |
| floR | AF118107 | Phenicol resistance | Erythromycin | 100 |
| Mph(E) | DQ839391 | Macrolide resistance | 100 | |
| Msr(E) | FR751518 | Macrolide, lincosamide, and streptogramin B resistance | Sulfamethoxazole | 100 |
| qacE | X68232 | Disinfectant resistance | Doxycycline; tetracycline | 100 |
| sul1 | U12338 | Sulphonamide resistance | Doxycycline; tetracycline; minocycline | 100 |
| Tet(A) | AJ517790 | Tetracycline resistance | Doxycycline; tetracycline | 100 |
The phylogenic analysis of this bacteria showed that the strains belonging to the same clonal lineages have strong similarities in their proteome [29]. The phylogenic analysis has also shown that numerous similar proteins are expressed by various strains of Acinetobacter baumannii. Therefore, in addition to studying the genome of this pathogen, the paradigm has shifted to examining the structure of similar proteins expressed by the genes of various strains of A. baumannii to discover new epitopes that could aid in the creation of vaccines against this vulnerable organism [30, 31]. Growth in the new genome of different organisms is increasing the lethality of bacterial diseases; the lethality is attributed to resistance against therapeutic drugs. Resistance against multiple antibacterial drugs is increasing day by day; previously, it was thought that irrational prescription, suboptimal doses, and patient incompliance are the factors involved in the development of resistance among microorganisms, but in the current era, genomic evolution and characterization are adding more information in it which is highlighting that the increase in resistance is not only accredited with prescription of drugs, but the genetic growth, acquisition of different genes from other organisms, and strains via horizontal gene transfer are some of the major contributing factors in the development of the multidrug-resistant organisms [32–34]. The ResFinder and Galaxy Community hub bioinformatics tools highlighted that the genome of A. baumannii has developed resistant to all available antibiotics, and the gene acquisition is in process as the genome is still open. That is an alarming signal which is suggesting the creation of superbug that cannot be killed by any available antibiotic [35]. The current need to deal with the persistent scenario of increase in the antibacterial resistance is identification of mechanisms by which the bacteria are protecting themselves; along with this, identification of mode of acquisition of genes is also required so that further expansion of genome in terms of acquiring resistant genes from other bacteria can be inhibited.
4. Conclusion
The pan-genome analysis showed that there is a 5-fold increase in the genome of A. baumannii in 5 years, and the genome is still open. There is the addition of multiple unique genes; among them, genes participating in the function of information and processing are more increased. The phylogenic analysis is revealing homology among different strains of this organism. Furthermore, the ResFinder and Galaxy Community hub bioinformatics tools revealed that the genome of A. baumannii has been resistant to almost all available antibiotics, so there is a critical requirement for the development of novel therapeutic agents against this organism.
Contributor Information
Akhtar Ali, Email: akhtar.ali@zu.edu.pk.
Ambrina Khatoon, Email: ambrina.khatoon@zu.edu.pk.
Data Availability
The data were collected from the NCBI GenBank, as it was a study based on the use of bioinformatics tools.
Ethical Approval
To access the tools via the university portal, official permission was taken from university authorities.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
References
- 1.Asif M., Alvi I. A., Rehman S. U. Insight into Acinetobacter baumannii: pathogenesis, global resistance, mechanisms of resistance, treatment options, and alternative modalities. Infection and Drug Resistance . 2018;Volume 11:1249–1260. doi: 10.2147/IDR.S166750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Lee C. R., Lee J. H., Park M., et al. Biology of Acinetobacter baumannii: pathogenesis, antibiotic resistance mechanisms, and prospective treatment options. Frontiers in Cellular and Infection Microbiology . 2017;7(7):p. 55. doi: 10.3389/fcimb.2017.00055. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Almasaudi S. B. Acinetobacter spp. as nosocomial pathogens: epidemiology and resistance features. Saudi Journal of Biological Sciences . 2018;25(3):586–596. doi: 10.1016/j.sjbs.2016.02.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Demirdal T., Sari U. S., Nemli S. A. Is inhaled colistin beneficial in ventilator associated pneumonia or nosocomial pneumonia caused by Acinetobacter baumannii? Annals of Clinical Microbiology and Antimicrobials . 2016;15(1):1–6. doi: 10.1186/s12941-016-0123-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Shlaes D. M., Bradford P. A. Antibiotics—from there to where?: how the antibiotic miracle is threatened by resistance and a broken market and what we can do about it. Pathogens & Immunity . 2018;3(1):19–43. doi: 10.20411/pai.v3i1.231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Saipriya K., Swathi C. H., Ratnakar K. S., Sritharan V. Quorum-sensing system in Acinetobacter baumannii: a potential target for new drug development. Journal of Applied Microbiology . 2020;128(1):15–27. doi: 10.1111/jam.14330. [DOI] [PubMed] [Google Scholar]
- 7.Li Y. H., Tian X. Quorum sensing and bacterial social interactions in biofilms. Sensors . 2012;12(3):2519–2538. doi: 10.3390/s120302519. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Traglia G. M., Place K., Dotto C., et al. Interspecies DNA acquisition by a naturally competent Acinetobacter baumannii strain. International Journal of Antimicrobial Agents . 2019;53(4):483–490. doi: 10.1016/j.ijantimicag.2018.12.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Wyres K. L., Cahill S. M., Holt K. E., Hall R. M., Kenyon J. J. Identification of Acinetobacter baumannii loci for capsular polysaccharide (KL) and lipooligosaccharide outer core (OCL) synthesis in genome assemblies using curated reference databases compatible with Kaptive. Microbial Genomics . 2020;6(3) doi: 10.1099/mgen.0.000339. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Yakkala H., Samantarrai D., Gribskov M., Siddavattam D. Comparative genome analysis reveals niche-specific genome expansion in Acinetobacter baumannii strains. PLoS One . 2019;14(6, article e0218204) doi: 10.1371/journal.pone.0218204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Bruzek S., Vestal G., Lasher A., Lima A., Silbert S. Bacterial whole genome sequencing on the illumina iSeq 100 for clinical and public health laboratories. The Journal of Molecular Diagnostics . 2020;22(12):1419–1429. doi: 10.1016/j.jmoldx.2020.09.003. [DOI] [PubMed] [Google Scholar]
- 12.Bogaty C., Mataseje L., Gray A., et al. Investigation of a carbapenemase-producing Acinetobacter baumannii outbreak using whole genome sequencing versus a standard epidemiologic investigation. Antimicrobial Resistance and Infection Control . 2018;7(1):1–7. doi: 10.1186/s13756-018-0437-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Hua X., Zhang L., He J., Leptihn S., Yu Y. Population biology and epidemiological studies of Acinetobacter baumannii in the era of whole genome sequencing: is the Oxford scheme still appropriate? Frontiers in Microbiology . 2020;11:p. 775. doi: 10.3389/fmicb.2020.00775. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Jia H., Chen Y., Wang J., Xie X., Ruan Z. Emerging challenges of whole-genome-sequencing-powered epidemiological surveillance of globally distributed clonal groups of bacterial infections, giving Acinetobacter baumannii ST195 as an example. International Journal of Medical Microbiology . 2019;309(7, article 151339) doi: 10.1016/j.ijmm.2019.151339. [DOI] [PubMed] [Google Scholar]
- 15.ABRicate software 2022. https://github.com/tseemann/abricate .
- 16.Res-finder 2022. Cited 2021. https://pubmed.ncbi.nlm.nih.gov/22782487/
- 17.Vázquez-López R., Solano-Gálvez S. G., Juárez Vignon-Whaley J. J., et al. Acinetobacter baumannii resistance: a real challenge for clinicians. Antibiotics . 2020;9(4):p. 205. doi: 10.3390/antibiotics9040205. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Zhen X., Stålsby Lundborg C., Sun X., Zhu N., Gu S., Dong H. Economic burden of antibiotic resistance in China: a national level estimate for inpatients. Antimicrobial Resistance and Infection Control . 2021;10(1):1–9. doi: 10.1186/s13756-020-00872-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Galac M. R., Snesrud E., Lebreton F., et al. A diverse panel of clinical Acinetobacter baumannii for research and development. Antimicrobial Agents and Chemotherapy . 2020;64(10, article e00840) doi: 10.1128/AAC.00840-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Vrancianu C. O., Pelcaru C. F., Alistar A., et al. Biocides role in the selection and dissemination of resistant Acinetobacter baumannii clones. Romanian Biotechnological Letters . 2020;25(4):1823–1831. [Google Scholar]
- 21.Hassan A., Naz A., Obaid A., et al. Pangenome and immuno-proteomics analysis of Acinetobacter baumannii strains revealed the core peptide vaccine targets. BMC Genomics . 2016;17(1):1–25. doi: 10.1186/s12864-016-2951-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.NCBI. Acinetobacter baumannii genome . NCBI; 2021. http://www.ncbi.nlm.nih.gov/genome/?term=Acinetobacter+baumannii . [Google Scholar]
- 23.Khan A. W., Garg V., Roorkiwal M., Golicz A. A., Edwards D., Varshney R. K. Super-pangenome by integrating the wild side of a species for accelerated crop improvement. Trends in Plant Science . 2020;25(2):148–158. doi: 10.1016/j.tplants.2019.10.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Costa A. R., Monteiro R., Azeredo J. Genomic analysis of Acinetobacter baumannii prophages reveals remarkable diversity and suggests profound impact on bacterial virulence and fitness. Scientific Reports . 2018;8(1):1–1. doi: 10.1038/s41598-018-33800-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Oliveira P. H., Touchon M., Cury J., Rocha E. P. The chromosomal organization of horizontal gene transfer in bacteria. Nature Communications . 2017;8(1):1–1. doi: 10.1038/s41467-017-00808-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Redondo-Salvo S., Fernández-López R., Ruiz R., et al. Pathways for horizontal gene transfer in bacteria revealed by a global map of their plasmids. Nature Communications . 2020;11:3602–3603. doi: 10.1038/s41467-020-17278-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Geisinger E., Huo W., Hernandez-Bird J., Isberg R. R. Acinetobacter baumannii: envelope determinants that control drug resistance, virulence, and surface variability. Annual Review of Microbiology . 2019;73(1):481–506. doi: 10.1146/annurev-micro-020518-115714. [DOI] [PubMed] [Google Scholar]
- 28.Xiong L., Yi F., Yu Q., et al. Transcriptomic analysis reveals the regulatory role of quorum sensing in the Acinetobacter baumannii ATCC 19606 via RNA-seq. BMC Microbiology . 2022;22(1):1–2. doi: 10.1186/s12866-022-02612-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Salto I. P., Torres Tejerizo G., Wibberg D., Pühler A., Schlüter A., Pistorio M. Comparative genomic analysis of Acinetobacter spp. plasmids originating from clinical settings and environmental habitats. Scientific Reports . 2018;8(1):1–2. doi: 10.1038/s41598-018-26180-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Solanki V., Tiwari V. Subtractive proteomics to identify novel drug targets and reverse vaccinology for the development of chimeric vaccine against Acinetobacter baumannii. Scientific Reports . 2018;8(1):1–9. doi: 10.1038/s41598-018-26689-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Ren S., Guan L., Dong Y., Wang C., Feng L., Xie Y. Design and evaluation of a multi-epitope assembly peptide vaccine against Acinetobacter baumannii infection in mice. Swiss Medical Weekly . 2019;149(2324) doi: 10.4414/smw.2019.20052. [DOI] [PubMed] [Google Scholar]
- 32.Tafreshi N., Babaeekhou L., Ghane M. Antibiotic resistance pattern of Acinetobacter baumannii from burns patients: increase in prevalence of bla (OXA-24-like) and bla (OXA-58-like) genes. Iranian Journal of Microbiology . 2019;11(6):502–509. [PMC free article] [PubMed] [Google Scholar]
- 33.Machowska A., Stålsby L. C. Drivers of irrational use of antibiotics in Europe. International Journal of Environmental Research and Public Health . 2019;16(1):p. 27. doi: 10.3390/ijerph16010027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Leungtongkam U., Thummeepak R., Tasanapak K., Sitthisak S. Acquisition and transfer of antibiotic resistance genes in association with conjugative plasmid or class 1 integrons of Acinetobacter baumannii. PLoS One . 2018;13(12, article e0208468) doi: 10.1371/journal.pone.0208468. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Jalali Y., Jalali M., Payer J. Acinetobacter baumannii: emergence of a superbug, past, present, and future. 2022. https://www.intechopen.com/online-first/81001 .
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data were collected from the NCBI GenBank, as it was a study based on the use of bioinformatics tools.