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Acinetobacter

Acinetobacter is a genus of gram-negative, aerobic, nonfermentative coccobacilli bacteria that are ubiquitous in the environment and can cause opportunistic infections in humans.
These bacteria are known for their ability to survive in harsh conditions and develop antimicrobial resistance, making them a significant concern in healthcare settings.
Acinetobacter species are often associated with nosocomial infections, such as pneumonia, bacteremia, meningitis, and urinary tract infections, particularly in immunocompromised individuals.
Reseearchers can utilize PubCompare.ai's AI-driven platform to enhance the reproducibility and accuracy of their Acinetobacter studies by easily locating the best protocols from literature, pre-prints, and patents through intelligent comparisons.
This cutting-edge tool can help optimize Acinetobacter research and improve the quality of research outputs.

Most cited protocols related to «Acinetobacter»

A single aliquot of the mock community was used throughout the sequencing effort analyzed in this study. This mock community represented 21 strains distributed among members of the Bacteria (n = 20) and Archaea (n = 1). Among the 20 bacterial sequences, there were 6 phyla, 10 classes, 12 orders, and 18 families and genera. The aliquot of mock community DNA was prepared by mixing genomic DNA from Acinetobacter baumanii (NC_009085), Actinomyces odontolyticus (DS264586), Bacillus cereus (AE017194), Bacteroides vulgatus (NC_009614), Clostridium beijerinckii (NC_009617), Deinococcus radiodurans (NC_001263), Enterococcus faecalis (NC_004668), Escherichia coli (NC_000913), Helicobacter pylori (NC_000915), Lactobacillus gasseri (NC_008530), Listeria monocytogenes (NC_003210), Neisseria meningitidis (NC_003112), Propionibacterium acnes (NC_006085), Pseudomonas aeruginosa (NC_002516), Rhodobacter sphaeroides (NC_007493, NC_007494), Staphylococcus aureus (NC_007793), Staphylococcus epidermidis (NC_004461), Streptococcus agalactiae (NC_004116), Streptococcus mutans (NC_004350), Streptococcus pneumoniae (NC_003028), and Methanobrevibacter smithii (NC_009515). Given the low homology between the three PCR primer pairs and the M. smithii 16S rRNA gene sequence, these sequences were rarely observed and have been omitted from the analysis of this study. The proportions of genomic DNAs added were calculated to have an equal number of 16S rRNA genes represented for each species; however, the original investigators did not verify the final relative abundances.
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Publication 2011
Acinetobacter Archaea Bacillus cereus Bacteria Bacteroides vulgatus Clostridium beijerinckii Deinococcus radiodurans DNA Enterococcus faecalis Escherichia coli Genes Genome Helicobacter pylori Lactobacillus gasseri Listeria monocytogenes Methanobrevibacter Neisseria meningitidis Oligonucleotide Primers Propionibacterium acnes Pseudomonas aeruginosa Rhodobacter sphaeroides Ribosomal RNA Genes RNA, Ribosomal, 16S Schaalia odontolytica Staphylococcus aureus Staphylococcus epidermidis Strains Streptococcus agalactiae Streptococcus mutans Streptococcus pneumoniae
We have expanded the Reference Gene Catalog8 (link) to include genetic elements related to stress response and virulence genes; these expansions can be visualized in the Reference Gene Catalog Browser (https://www.ncbi.nlm.nih.gov/pathogens/refgene/). One reason we expanded AMRFinderPlus is to understand the linkages between AMR genes and stress response and virulence genes in food-borne pathogens; thus, the stress response and virulence genes included in the Reference Gene Catalog are composed primarily of E. coli-related genes derived primarily from González-Escalona et al.23 (link) as well as BacMet24 (link), but also have been supplemented by manual curation efforts for other taxa. Stx gene nomenclature adopts the system of Scheutz et al.25 (link) and the intimin (eae) gene nomenclature uses existing designations in the literature26 (link),27 (link). Genes are incorporated only if there is literature supporting the function of that protein or closely related sequences that meet the identification criteria. As a major focus of our work is to improve NCBI’s Pathogen Detection system16 (link), we excluded genes that belonged to organisms not deemed clinically relevant. To remove ‘housekeeping’ proteins that were universally found in one or more taxa in the Pathogen Detection system, sequences were not included if they were found at a frequency of greater than 95% in a survey of 58,531 RefSeq bacterial assemblies belonging to any of the following species: Acinetobacter, Campylobacter, Citrobacter, Enterococcus, Enterobacter, Escherichia/Shigella, Klebsiella, Listeria, Salmonella, Staphylococcus, Pseudomonas, and Vibrio. If genes of particular interest in foodborne pathogens exceeded this threshold, they were excluded in the taxa where they appear to be nearly universal (see “Identifying genomic elements” below). In addition, genes with misidentified functions, such as copper-binding proteins that use copper as a co-factor yet do not confer resistance to copper, also were excluded. As we continue to expand the database, we use similar criteria when adding genes.
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Publication 2021
Acinetobacter Bacteria Bears Campylobacter Citrobacter Copper copper-binding protein Enterobacter Enterococcus Escherichia Escherichia coli factor A Food Gene Components Genome Components Klebsiella Linkage, Genetic Listeria Operator, Genetic Pathogenicity Proteins Pseudomonas Salmonella Shigella Staphylococcus Vibrio Virulence
A total of 173 Acinetobacter strains were characterized (Table 3). Most isolates were from clinical origin and were, with few exceptions, collected between 1987 and 2005, mainly in European countries. First, 123 genotypically distinct and epidemiologically unrelated A. baumannii strains (‘diversity set’) were included. These isolates were selected from ∼600 isolates (excluding outbreak replicates) from the Leiden University Medical Center AFLP database, such that the selection displayed the maximal diversity at the 90% AFLP similarity cut-off level, and was also diverse in time-space origin. Previous studies have used the ∼80% AFLP similarity level as a cut-off for defining major clones [43] . Thus, the diversity set included 25 strains of the international (previously named ‘European’) clone I, 30 of clone II, and 15 of clone III (Table 3). Second, 24 additional A. baumannii isolates from 7 outbreaks for which one representative was included in the diversity set, were investigated for reproducibility and epidemiological concordance. Isolates of each of the seven outbreaks had an AFLP similarity ≥90% and were from the same time-space origin. Apart from these, there were 48 additional A. baumannii isolates of the diversity set that were from known outbreaks (Table 3). These isolates were considered to represent an outbreak if they shared with other isolates a common time-space origin and a common genotype and/or a common antibiotic susceptibility profile. Isolates were not considered to be part of an outbreak (Table 3) if local data (typing and epidemiology) showed no evidence for this. If there was no indication that a strain belonged to an outbreak or not, they were labeled as ‘outbreak unknown’. Third, we included the seven A. baumannii strains (ATCC 17978, AYE, SDF, ACICU, AB0057, AB307-0294 and AB900) for which a complete genome sequence was published; the sequences of the gene portions corresponding to the MLST templates were extracted from the genome sequences [38] (link)–[42] (link). Finally, we included 15 isolates of the species that are closely related to A. baumannii (A. calcoaceticus, A. gen. sp. 3 and 13TU), and four isolates of Acinetobacter gen. sp. 13BJ and 15BJ (used as outgroups for the phylogenetic analysis).
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Publication 2010
Acinetobacter Antibiotics Clone Cells Europeans Genes Genetic Diversity Genome Genotype Reproduction Strains Susceptibility, Disease

Acinetobacter genome assemblies from our collection for which the KL and OCL types had been previously determined via manual or automated sequence inspection ([2, 41 (link)]; and unpublished data) were used to assess the level of typing accuracy that could be achieved through the use of our novel databases with Kaptive. Paired-end Illumina read data (described in [2, 41 (link)] and available under BioProject accession PRJEB2801) were de novo assembled using SPAdes v. 3.13.1 [46 (link)] and optimized with Unicycler v. 0.4.7 [47 (link)]. High-quality genome assemblies (n=719) with a maximum contig number of 300 and minimum assembly length of 3.6 Mbp were included in the analysis (cut-offs determined empirically by manual inspection of the contig number and assembly length distributions, respectively). These assemblies were assessed for oxaAb presence using blastn (>95 % nucleotide sequence similarity and >90 % combined coverage) to confirm the A. baumannii species assignment. Confirmed A. baumannii sequences (n=642) were analysed using both KL and OCL reference databases with command-line Kaptive v. 0.7 [44 (link)] with default parameters.
The same method was used to test databases against 3412 genome sequences available in the NCBI non-redundant and WGS databases as of February 2019. These genome assemblies were bulk downloaded from NCBI as a compressed .tar file for local analysis. Genomes lacking oxaAb were removed prior to typing but quality control (QC) analysis as described above was applied to this data set only after typing was complete.
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Publication 2020
Acinetobacter Base Sequence Dietary Fiber Genome
For validation of the CIM, a selection of 30 Gram-negative isolates was used. This selection included isolates obtained from different institutes across the world carrying known carbapenemase encoding genes and carbapenem susceptible isolates, according to the submitter (Table 1). In addition, 694 isolates submitted to the National Institute for Public Health and the Environment for the national surveillance of carbapenemase-producing Enterobacteriaceae (CPE) by Dutch medical microbiology laboratories (MMLs) during the first six months of 2012 and the first six months of 2013 were used. For the national surveillance of CPE in the Netherlands, Dutch MMLs are requested to submit Enterobacteriaceae isolates with an MIC for meropenem > 0.25 μg/ml. However, more than half of the isolates (411/694, 59%) sent in for CPE surveillance were non-fermenting Gram-negatives belonging to the genera Pseudomonas and Acinetobacter. Furthermore, 35% of the isolates had MICs below 0.25 μg/ml. Nevertheless, all isolates were included in this study.
The species identification, as performed by the MMLs, was confirmed using MALDI-TOF (Bruker Daltonics GmbH, Bremen, Germany) and the MIC for all isolates was confirmed by E-test (BioMerieux Inc., Marcy L’Etoile, France). Culturing of isolates was done on Columbia Sheep Blood (bioTRADING Benelux BV, Mijdrecht, The Netherlands) and Mueller-Hinton agarplates (Oxoid Ltd, Hampshire, United Kingdom). An overview of all CPE surveillance isolates and their characteristics is displayed in Tables 2 and 3.
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Publication 2015
Acinetobacter Blood Carbapenem-Resistant Enterobacteriaceae carbapenemase Carbapenems Domestic Sheep Enterobacteriaceae Genes Meropenem Pseudomonas Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

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Publication 2023
Acinetobacter Agar Bacteria Escherichia coli Methicillin-Resistant Staphylococcus aureus Microbicides Nutrients Pneumonia Pseudomonas aeruginosa Staphylococcus aureus Staphylococcus haemolyticus
Toxin_43 domain-containing proteins were identified using the Pfam database, and multiple sequence alignments (MSAs) of the toxin_43 domain-containing proteins (Atu4350, N643_13510, VPUCM_729, and NM96_04490) from different species were performed using Jalview (63 (link)). TafE homologs were identified with tBLASTn using the TafE protein (ACX60_15365) from strain ATCC 17978 as the query sequence. The TafE homologs obtained from Alphaproteobacteria (genera Methylobacterium, Vannielia, Tritonibacter, Paracoccus, Jannaschia, Loktanella, and Rhodovulum), Betaproteobacteria (genera Paraburkholderia and Burkholderia), and Gammaproteobacteria (genera Vibrio, Pseudoalteromonas, Acinetobacter, and Pseudomonas) were aligned by using ClustalX 2.1, and phylogenies were constructed using MEGA 7.0 (64 (link)) with 1,000 replicates using the neighbor-joining (NJ) method. The Interactive Tree of Life (iTOL) was used for visualization of the phylogenetic tree (65 (link)).
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Publication 2023
Acinetobacter Alphaproteobacteria Amino Acid Sequence Betaproteobacteria Burkholderia Gammaproteobacteria Methylobacterium Paracoccus Proteins Pseudoalteromonas Pseudomonas Rhodovulum Strains Toxins, Biological Trees Vibrio
We also tested the sensitivity of the result that accessory gene contents differed by environment to sampling biases of the plasmid database by repeating our main analyses on subsets of the data. To do this, we first calculated the taxonomic distribution of bacterial hosts in the data set using the R package ggsankey (https://github.com/davidsjoberg/ggsankey). Next, we investigated patterns within the most abundant phyla, as explained above. We then examined trends within E. coli, the most abundant species represented. Finally, we removed the three most abundant genera from Proteobacteria (Acinetobacter, Escherichia, and Klebsiella) and the most abundant genus from Firmicutes (Staphylococcus). We then retested that the results held within these two dominant phyla.
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Publication 2023
Acinetobacter ARID1A protein, human Bacteria Escherichia Escherichia coli Firmicutes Genes Hypersensitivity Klebsiella Plasmids Proteobacteria Staphylococcus
Clinical samples from various illnesses in the ICU (n = 79) were prepared for culture using traditional techniques (cultures on routine media such as blood agar or MacConkey agar and selective media with specific biochemical tests when necessary) where all the clinical isolates have proceeded for culture on blood and MacConkey agars and then Gram staining was performed to identify bacterial morphology and Gram reaction. The studies were cultured several times to ensure that all isolates were pure. Several biochemical tests were performed to confirm that all isolates belonged to A. baumannii, including oxidase, catalase, and indole tests. Standard phenotypic assays were used for the initial identification [25 (link)].
Vitek 2 system (BioMerieux, Marcy-l’Étoile, France) was used in the microbiology laboratory to confirm the identification of the isolates, following the manufacturer’s instructions. All isolates were investigated for antibiotic susceptibility, using this automated Vitek 2 Compact system. The included samples were cultured on blood agars, and then the suspension was made for every single isolate. A liquid suspension of the studied isolates was loaded on the Vitek system, and left overnight to obtain the result. The next day, results illustrated the samples’ identification and antibiotic susceptibility.
VITEK 2 system was approved for authenticating the names of Acinetobacter spp. as described by the manufacturer (BioMerieux). The Vitek2 card contains 64 wells holding different fluorescent biochemical assays. Twenty out of the sixty-four wells were carbohydrate assimilation; four are phosphatase, nitrate, urea, and actidione tests. The machine controlled this card automatically, including filling, sealing, and finally transferring such cards into the linked incubator at a temperature of 35 °C. Each output report is usually decoded according to a specific algorithmic system. The acquired results were recognized and recorded. Most known Acinetobacter spp. have clear-cut profiles, and the system led to the correction of the unknown organism.
The susceptibility of the most commonly used antibiotics (n = 13) for the prevalent ICU infections has been recorded.
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Publication 2023
Acinetobacter Actidione Agar Antibiotics Antibiotics, Antitubercular Bacteria Biological Assay Blood Blood Culture Carbohydrates Catalase Culture Media indole Infection Nitrates Oxidases Phenotype Phosphoric Monoester Hydrolases Susceptibility, Disease Urea
Susceptibility testing was performed by the Kirby–Bauer disk diffusion method. Overnight cultures were suspended in physiological saline to 0.5 McFarland units (McFarland Densitometer DEN-1, Biosan, Latvia). The suspension was inoculated on Mueller–Hinton agar (Oxid, UK). Selected antibiotics were placed on the inoculated plates. For S. aureus strains, cefoxitin 30 µg, ceftriaxone 30 µg, benzylpenicillin 1iu, ampicillin 2 µg, ampicillin–sulbactam 10/10 µg, amoxicillin–clavulanic acid 20/10 µg, norfloxacin 10 µg, amikacin 30 µg, erythromycin 15 µg, clindamycin 2 µg, and chloramphenicol 30 µg were applied (Liofilchem, Italy). For K. pneumoniae and Serratia liquefaciens strains, amoxicillin–clavulanic acid 20/10 µg, piperacillin–tazobactam 30/6 µg, cefotaxime 5 µg, ceftazidime 10 µg, ertapenem 10 µg, imipenem 10 µg, meropenem 10 µg, ciprofloxacin 5 µg, gentamicin 10 µg, and trimethoprim/sulfamethoxazole 1.25/23.75 µg were applied (Liofilchem, Italy). For Acinetobacter spp., piperacillin–tazobactam 30/6 µg, ceftazidime 10 µg, imipenem 10 µg, meropenem 10 µg, ciprofloxacin 5 µg, and amikacin 30 µg were applied (Liofilchem, Italy). For Acinetobacter spp., imipenem 10 µg, amikacin 30 µg, gentamicin 10 µg, trimethoprim/sulfamethoxazole 1.25/23.75 µg, ciprofloxacin 5 µg, and levofloxacin 5 µg were applied (Liofilchem, Italy). The size of the zone of inhibition around the disk was measured after 16–20 h of incubation. The evaluation of the results was carried out according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) standard, actual EUCAST version [17 ].
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Publication 2023
Acinetobacter Agar Amikacin Amox clav Ampicillin ampicillin-sulbactam Antibiotics Biosan Cefotaxime Cefoxitin Ceftazidime Ceftriaxone Chloramphenicol Ciprofloxacin Clindamycin Ertapenem Erythromycin Europeans Gentamicin Imipenem Kirby-Bauer Disk-Diffusion Method Klebsiella pneumoniae Levofloxacin Meropenem Microbicides Norfloxacin Penicillin G physiology Piperacillin-Tazobactam Combination Product Psychological Inhibition Saline Solution Serratia liquefaciens Staphylococcus aureus Strains Susceptibility, Disease Trimethoprim-Sulfamethoxazole Combination

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CHROMagar Acinetobacter is a chromogenic culture medium designed for the detection and enumeration of Acinetobacter species. The product provides a simple and efficient way to identify Acinetobacter directly from clinical samples or environmental sources.
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The API 20E is a standardized identification system for Enterobacteriaceae and other non-fastidious Gram-negative rods. It consists of 20 miniaturized biochemical tests, which allow the identification of the most frequently encountered members of the Enterobacteriaceae family as well as certain other Gram-negative bacteria.
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MacConkey agar is a selective and differential culture medium used for the isolation and identification of Gram-negative enteric bacteria, particularly members of the Enterobacteriaceae family. It inhibits the growth of Gram-positive bacteria while allowing the growth of Gram-negative bacteria.

More about "Acinetobacter"

Acinetobacter is a genus of Gram-negative, aerobic, and non-fermenting coccobacilli bacteria that are ubiquitous in the environment.
These opportunistic pathogens are known for their ability to survive in harsh conditions and develop antimicrobial resistance, making them a significant concern in healthcare settings.
Acinetobacter species are often associated with nosocomial (hospital-acquired) infections, such as pneumonia, bacteremia, meningitis, and urinary tract infections, particularly in immunocompromised individuals.
Identification and characterization of Acinetobacter can be done using various laboratory techniques, including the Vitek 2 system, Etest, CHROMagar Acinetobacter, API 20E, and MALDI-TOF MS (Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry).
The Vitek 2 automated system is a widely used method for rapid and accurate identification of Acinetobacter species. β-glucosidase activity is commonly used as a marker for the identification of certain Acinetobacter species.
Researchers can utilize PubCompare.ai's AI-driven platform to enhance the reproducibility and accuracy of their Acinetobacter studies.
This cutting-edge tool can help optimize Acinetobacter research by easily locating the best protocols from literature, pre-prints, and patents through intelligent comparisons, ultimately improving the quality of research outputs.
By incorporating synonyms, related terms, abbreviations, and key subtopics, researchers can gain a comprehensive understanding of Acinetobacter and its clinical relevance, as well as the latest advancements in its detection and characterization.