72 research outputs found
Mcr colistin resistance gene : a systematic review of current diagnostics and detection methods
Resistance to colistin, mediated by chromosomal mutations and more recently, by
plasmid-borne
mcr genes, is increasingly being reported in bacterial isolates taken
from humans, animals, farms, foods, and the environment. To easily identify and contain
this quickly spreading menace, efficient diagnostics that are cheaper, faster, simpler,
sensitive, and specific have become indispensable and urgently necessary. A
thorough and systematic review of the literature available at Pubmed, ScienceDirect
and Web of Science was thus undertaken to identify articles describing novel and
efficient colistin resistance-and
mcr gene-detecting
methods. From the final 23
studies included in this review, both phenotypic and molecular tests were found. The
phenotypic tests consisted of novel culture media viz., SuperPolymyxin™, CHROMagar
COL-APSE
and LBJMR media, commercial automated MIC-determining
instruments
such as MICRONAUT-S,
Vitek 2, BD Phoenix, Sensititre and MicroScan, and novel
assays such as Colistin MAC test, Colispot, rapid polymxin NP test (RPNP), alteration
of Zeta potential, modified RPNP test, MICRONAUT-MIC
Strip, MIC Test Strip, UMIC
System, and Sensitest™ Colistin. Molecular diagnostics consisted of the CT103XL
microarray, eazyplex® SuperBug kit, and Taqman®/SYBR Green® real-time
PCR assays,
with 100% sensitivity and specificity plus a shorter turnaround time (<3 hr).
Based on the sensitivity, specificity, cost, required skill and turnaround time, the
RPNP test and/or novel culture media is recommended for under-resourced
laboratories
while the Multiplex PCR or Taqman®/SYBR Green® real-time
PCR assay alongside
the RPNP or novel culture media is suggested for well-resourced
ones.http://www.MicrobiologyOpen.comam2019Medical Microbiolog
Global evolutionary epidemiology and resistome dynamics of Citrobacter species, Enterobacter hormaechei, Klebsiella variicola, and Proteeae clones
Citrobacter spp., Enterobacter hormaechei subsp., Klebsiella variicola and Proteae tribe members are rarely isolated Enterobacterales increasingly implicated in nosocomial infections. Herein, we show that these species contain multiple genes encoding resistance to important antibiotics and are widely and globally distributed, being isolated from human, animal, plant, and environmental sources in 67 countries. Certain clones and clades of these species were internationally disseminated, serving as reservoirs and mediums for the global dissemination of antibiotic resistance genes. As they can easily transmit these genes to more pathogenic species, additional molecular surveillance studies should be undertaken to identify and contain these antibiotic‐resistant species.Supplemental dataset 1. Raw metadata of downloaded genomes from PATRIC containing all the data associated with each genome.Supplemental dataset 2. Species by species tabulation and analyses of the resistomes, specimen sources, country of isolation, MLST, Biosample accession number, and strain name of all the genomes according to their order on the phylogeny trees.Supplemental dataset 3. Colour‐coded species by species tabulation of the resistomes, specimen sources, country of isolation, MLST, Biosample accession number, and strain name of all the genomes according to their order on the phylogeny trees.Supplemental dataset 4 Plasmid replicons and their associated resistomes and bacterial hosts. Selected genomes bearing carbapenemases, mcr, fluoroquinolones, aminoglycosides and other clinically important antibiotic resistance genes, were run through PlasmidFinder, pMLST, and BLASTn to identify their genetic environment. Most antibiotic resistance genes were found on plasmids, making them potentially mobile.Supplementary Figures: Figure S1A‐B Evolutionary epidemiology and resistome of global Citrobacter freundii, brakii, portucalensis, and amalonaticus isolates. S1A shows Citrobacter sp., particularly freundii, portucalensis and brakii clustering into clades A, B1, B2 and B3 whilst S1B shows C. amalonaticus strains clustering into clades A (red highlight), B1 (green highlight), B2 (blue highlight) and C (mauve highlight); clade B2 had very rich resistome repertoire and were all from France, but the other clades had very few resistance genes. Strains from humans (blue labels), animals (red labels), plants (purple/mauve labels) and the environment (green labels) were found in the same clade/cluster. Included in S1A are Pseudomonas, Klebsiella, and Escherichia coli species that were originally classified as C. freundii but later reclassified into their actual species using ANI; their clustering away from the Citrobacter species confirms the ANI results that they were initially misclassified. BlaSED and oqxAB were almost conserved in these genomes. Branches with bootstrap support values of ≥50 were defined as belonging to the same clade. The branch lengths also show the evolutionary distance between the isolates. Blue and red arrows show the direction of evolution as well as local and international dissemination of strains of the same clone/clade through different hosts.
Fig. S1C. Evolutionary epidemiology and resistome of global Citrobacter koseri isolates. C. koseri strains clustered into clades A (grey highlight), B1 (light blue highlight), B2 (orange highlight) and B3 (mauve highlight). Strains from humans (blue labels) and animals (red labels) were found in the same clade/cluster. BlaCKO and blaMAL were almost conserved in these genomes. Included in S1C are Serratia marcescens, Klebsiella, Enterobacter and Escherichia coli species that were originally classified as C. koseri but later reclassified into their actual species using ANI; their clustering away from Citrobacter koseri confirms the ANI results that they were initially misclassified. Branches with bootstrap support values of ≥50 were defined as belonging to the same clade. The branch lengths also show the evolutionary distance between the isolates. Blue and red arrows show the direction of evolution as well as local and international dissemination of strains of the same clone/clade through different hosts.
Fig. S1D. Evolutionary epidemiology and resistome of global Citrobacter spp, isolates, A and B. This tree shows information for additional Citrobacter freundii and Citrobacter sp. that were not featured figures 1, and S1A–C above. Included in S1D are Serratia marcescens, Klebsiella, Enterobacter and Escherichia coli species that were originally classified as C. freundii, but later reclassified into their actual species using ANI; their clustering away from C. freundii confirms the ANI results that they were initially misclassified. C. freundii clustered into four main clades (A, B1, B2 and B3), highlighted with distinct colours. Clade B3 had the most resistome abundance and diversity. Strains from humans (blue labels), animals (red labels), plants (purple/mauve labels) and the environment (green labels) were found in the same clade/cluster. BlaCMY was conserved in these genomes. Branches with bootstrap support values of ≥50 were defined as belonging to the same clade. The branch lengths also show the evolutionary distance between the isolates. Blue and red arrows show the direction of evolution as well as local and international dissemination of strains of the same clone/clade through different hosts.
Figs S2A‐B. Evolutionary epidemiology and resistome of global Enterobacter hormaechei subsp. Hormaechei, Xiangfangensis, Oharae, and Steigerwaltii, isolates. S2A is strictly E. hormaechei subsp. Hormaechei and is an addition to Figure 4 whilst S2B is an addition to Figures 3‐4 above as additional genomes of E. hormaechei subsp. Xiangfangensis, Oharae, and Steigerwaltii; these could not be added to Figures 3‐4 and are shown here in Fig. S2B. The E. hormaechei isolates in S2A clustered into three main clades A, B and C (with distinct highlights) that contained strains distributed globally from humans (blue labels), and animals (red labels), plants (purple/mauve labels) and the environment (green labels). Clades B and C contained diverse and rich resistome repertoire. blaACT was conserved in these genomes. S2B contains E. hormaechei subsp.Xiangfangensis, Oharae, and Steigerwaltii isolates clustering into 6 branches (I‐VI); genomes of the same subsp. clustered closely together. Branches with bootstrap support values of ≥50 were defined as belonging to the same clade. The branch lengths also show the evolutionary distance between the isolates. Blue and red arrows show the direction of evolution as well as local and international dissemination of strains of the same clone/clade through different hosts.
Fig. S3A‐B. Evolutionary epidemiology and resistome of global Klebsiella variicola isolates. S3A‐B are additional trees to Figure 5 and show additional K. variicola genomes that could not be added to Figure 5; in all, Figures 5 and S3A‐B show 600 K. variicola genomes. S3A and S3B trees are composed of different K. variicola genomes, which is reflected in the differences in the resistomes and tree topologies. Included in S3A and S3B are K. pneumoniae and K. pneumoniae and quasipneumoniae species respectively, that were originally classified as K. variicola, but later reclassified into their actual species using ANI; their clustering away from K. variicola confirms the ANI results that they were initially misclassified. The K. variicola strains clustered into eight (S3A) and seven (S3B) clades I‐VIII and I‐VII respectively, which were highlighted with distinct colours and were isolated from countries around the globe. The clades contained strains distributed globally from humans (blue labels), animals (red labels), plants (purple/mauve labels) and the environment (green labels). Besides a few strains in clade B2, the other strains contained very few resistance genes. blaLEN was conserved in these genomes. Branches with bootstrap support values of ≥50 were defined as belonging to the same clade. The branch lengths also show the evolutionary distance between the isolates. Blue and red arrows show the direction of evolution as well as local and international dissemination of strains of the same clone/clade through different hosts.
Fig. S4. Evolutionary epidemiology and resistome of global Proteus mirabilis isolates. The P. mirabilis isolates clustered into 10 clades, A‐A3, B1‐B3, and C1‐C3 (shown with different highlights), which contained diverse and abundant resistomes with conserved catA and tet genes. The clades contained strains distributed globally from humans (blue labels), animals (red labels), plants (purple/mauve labels) and the environment (green labels). Branches with bootstrap support values of ≥50 were defined as belonging to the same clade. The branch lengths also show the evolutionary distance between the isolates. Blue and red arrows show the direction of evolution as well as local and international dissemination of strains of the same clone/clade through different hosts.
Fig. S5 (A‐C). Count of antibiotic resistance genes (ARGs) in Citrobacter freundii (A), and Citrobacter species (B and C). The sum of each unique ARG and its variants are computed and shown as a bar chart to depict the most abundant ARGs.
Fig. S6 (A‐B). Count of antibiotic resistance genes (ARGs) in Citrobacter amalonaticus (A), and Citrobacter koseri (B). The sum of each unique ARG and its variants are computed and shown as a bar chart to depict the most abundant ARGs.
Fig. S7 (A‐B). Count of antibiotic resistance genes (ARGs) in Enterobacter steigerwaltii and oharae (A), and Enterobacter xiangfangensis (B). The sum of each unique ARG and its variants are computed and shown as a bar chart to depict the most abundant ARGs.
Fig. S8 (A‐C). Count of antibiotic resistance genes (ARGs) in Enterobacter hormaechei (A, B and C). The sum of each unique ARG and its variants are computed and shown as a bar chart to depict the most abundant ARGs.
Fig. S9 (A‐C). Count of antibiotic resistance genes (ARGs) in Klebsiella variicola (A, B and C). The sum of each unique ARG and its variants are computed and shown as a bar chart to depict the most abundant ARGs.
Fig. S10 (A‐C). Count of antibiotic resistance genes (ARGs) in Morganella morganii (A), Proteus mirabilis (B) and Providencia species (C). The sum of each unique ARG and its variants are computed and shown as a bar chart to depict the most abundant ARGs.Table S4. Statistical analyses of resistome diversity, abundance, and relative richnesshttps://sfamjournals.onlinelibrary.wiley.com/journal/146229202022-01-07hj2021Medical Microbiolog
Genomic and resistance epidemiology of gram-negative bacteria in Africa : a systematic review and phylogenomic analyses from a one health perspective
Antibiotic resistance (AR) remains a major threat to public and animal
health globally. However, AR ramifications in developing countries are worsened by
limited molecular diagnostics, expensive therapeutics, inadequate numbers of skilled
clinicians and scientists, and unsanitary environments. The epidemiology of Gramnegative
bacteria, their AR genes, and geographical distribution in Africa are described
here. Data were extracted and analyzed from English-language articles published
between 2015 and December 2019. The genomes and AR genes of the
various species, obtained from the Pathosystems Resource Integration Center
(PATRIC) and NCBI were analyzed phylogenetically using Randomized Axelerated
Maximum Likelihood (RAxML) and annotated with Figtree. The geographic location
of resistant clones/clades was mapped manually. Thirty species from 31 countries
and 24 genera from 41 countries were analyzed from 146 articles and 3,028 genomes,
respectively. Genes mediating resistance to -lactams (including blaTEM-1,
blaCTX-M, blaNDM, blaIMP, blaVIM, and blaOXA-48/181), fluoroquinolones (oqxAB, qnrA/B/
D/S, gyrA/B, and parCE mutations, etc.), aminoglycosides (including armA and rmtC/
F), sulfonamides (sul1/2/3), trimethoprim (dfrA), tetracycline [tet(A/B/C/D/G/O/M/39)],
colistin (mcr-1), phenicols (catA/B, cmlA), and fosfomycin (fosA) were mostly found in
Enterobacter spp. and Klebsiella pneumoniae, and also in Serratia marcescens, Escherichia
coli, Salmonella enterica, Pseudomonas, Acinetobacter baumannii, etc., on mostly
IncF-type, IncX3/4, ColRNAI, and IncR plasmids, within IntI1 gene cassettes, insertion
sequences, and transposons. Clonal and multiclonal outbreaks and dissemination
of resistance genes across species and countries and between humans,
animals, plants, and the environment were observed; Escherichia coli ST103, K.
pneumoniae ST101, S. enterica ST1/2, and Vibrio cholerae ST69/515 were common
strains. Most pathogens were of human origin, and zoonotic transmissions were relatively limited.
IMPORTANCE Antibiotic resistance (AR) is one of the major public health threats
and challenges to effective containment and treatment of infectious bacterial diseases
worldwide. Here, we used different methods to map out the geographical hot
spots, sources, and evolutionary epidemiology of AR. Escherichia coli, Klebsiella pneumoniae,
Salmonella enterica, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter
spp., Neisseria meningitis/gonorrhoeae, Vibrio cholerae, Campylobacter jejuni,
etc., were common pathogens shuttling AR genes in Africa. Transmission of the
same clones/strains across countries and between animals, humans, plants, and the
environment was observed. We recommend Enterobacter spp. or K. pneumoniae as
better sentinel species for AR surveillance.https://msystems.asm.orgam2021Medical Microbiolog
Global epidemiology, genetic environment, risk factors and therapeutic prospects of MCR genes : a current and emerging update
BACKGROUND : Mobile colistin resistance (mcr) genes modify Lipid A molecules
of the lipopolysaccharide, changing the overall charge of the outer membrane.
RESULTS AND DISCUSSION: Ten mcr genes have been described to date within
eleven Enterobacteriaceae species, with Escherichia coli, Klebsiella
pneumoniae, and Salmonella species being the most predominant. They are
present worldwide in 72 countries, with animal specimens currently having the
highest incidence, due to the use of colistin in poultry for promoting growth
and treating intestinal infections. The wide dissemination of mcr from food
animals to meat, manure, the environment, and wastewater samples has
increased the risk of transmission to humans via foodborne and vectorborne routes. The stability and spread of mcr genes were mediated by
mobile genetic elements such as the IncHI2 conjugative plasmid, which is
associated with multiple mcr genes and other antibiotic resistance genes. The
cost of acquiring mcr is reduced by compensatory adaptation mechanisms.
MCR proteins are well conserved structurally and via enzymatic action. Thus,
therapeutics found effective against MCR-1 should be tested against the
remaining MCR proteins.
CONCLUSION: The dissemination of mcr genes into the clinical setting, is
threatening public health by limiting therapeutics options available.
Combination therapies are a promising option for managing and treating
colistin-resistant Enterobacteriaceae infections whilst reducing the toxic
effects of colistin.The National Health Laboratory Service (NHLS) and the National Research Foundation.https://www.frontiersin.org/journals/cellular-and-infection-microbiologydm2022Medical Microbiolog
Plasmid evolution in carbapenemase‐producing Enterobacteriaceae : a review
Please read abstract in the article.Table S1. Metadata of plasmids deposited at GenBank and included in this study.Supplementary dataset. Nucleotide sequences of plasmids included in this study and obtained from Genbank.https://nyaspubs.onlinelibrary.wiley.com/journal/174966322020-12-01hj2019Medical Microbiolog
Editorial : Community series - characterization of mobile genetic elements associated with acquired resistance mechanisms, volume II
Antibiotic resistance in bacteria remains a great challenge to clinical medicine as resistant
bacterial infections are very difficult to manage. It is estimated that antibiotic-resistant
infections resulted in 1.27 million deaths in 2019, which is expected to increase to 10 million
deaths annually by 2050 (Antimicrobial Resistance Collaborators, 2022). In the US alone,
at least 2 million people got an antimicrobial-resistant infection, of which at least 23,000
people died in 2019 (CDC, 2019). In the EU, 541,000 deaths were associated with antibiotic
resistance while 133,000 deaths were attributable to this menace (European Antimicrobial
Resistance Collaborators, 2022). Moreover, the costs associated with antibiotic resistance
have been estimated by Nelson et al. (2022) to be 4.6 billion in health care costs accrued annually from treating antibiotic
resistance in six pathogens in the US (CDC, 2021). These statistics evince why the WHO has
categorized antibiotic resistance among the top 10 threats for global health (Antimicrobial
Resistance Collaborators, 2022).http://www.frontiersin.org/Microbiologyam2024DermatologySDG-03:Good heatlh and well-bein
Current and emerging polymyxin resistance diagnostics : a systematic review of established and novel detection methods
The emergence of polymyxin resistance, due to transferable mcr genes, threatens public
and animal health as there are limited therapeutic options. As polymyxin is one of the
last-line
antibiotics, there is a need to contain the spread of its resistance to conserve its
efficacy. Herein, we describe current and emerging polymyxin resistance diagnostics to
inform faster clinical diagnostic choices. A literature search in diverse databases for studies
published between 2016 and 2020 was performed. English articles evaluating colistin
resistance methods/diagnostics were included. Screening resulted in the inclusion of 93
journal articles. Current colistin resistance diagnostics are either phenotypic or molecular.
Broth microdilution is currently the only gold standard for determining colistin MICs
(minimum inhibitory concentration). Phenotypic methods comprise of agar-based
methods
such as CHROMagar™ Col-APSE,
SuperPolymyxin, ChromID® Colistin R, LBJMR
and LB medium; manual MIC-determiners
viz., UMIC, MICRONAUT MIC-Strip
and
ComASP Colistin; automated antimicrobial susceptibility testing systems such as BD
Phoenix, MICRONAUT-S,
MicroScan, Sensititre and Vitek 2; MCR-detectors
such as
lateral flow immunoassay (LFI) and chelator-based
assays including EDTA-and
DPA-based
tests, that is, combined disk test, modified colistin broth-disk
elution (CBDE),
Colispot, and Colistin MAC test as well as biochemical colorimetric tests, that is, Rapid
Polymyxin NP test and Rapid ResaPolymyxin NP test. Molecular methods only characterize
mobile colistin resistance; they include PCR, LAMP and whole-genome
sequencing.
Due to the faster turnaround time (≤3 h), improved sensitivity (84%–100%)
and specificity (93.3%–100%)
of the Rapid ResaPolymyxin NP test and Fastinov®, we recommend
this test for initial screening of colistin-resistant
isolates. This can be followed
by CBDE with EDTA or the LFI as they both have 100% sensitivity and a specificity of
≥94.3% for the rapid screening of mcr genes. However, molecular assays such as LAMP
and PCR may be considered in well-equipped
clinical laboratories.We hereby regretfully report the death of our colleague
Professor Nontombi Marylucy Mbelle, who died during
the submission of this article. This work is dedicated to her
memory.The National Health Laboratory Service (NHLS)http://wileyonlinelibrary.com/journal/jamam2022Medical Microbiolog
Antibiotic resistance of Mycobacterium tuberculosis complex in Africa : a systematic review of current reports of molecular epidemiology, mechanisms and diagnostics
BACKGROUND : Tuberculosis (TB) remains a main global public health problem. However, a systematic review of TB resistance epidemiology in Africa is wanting.
METHODS : A comprehensive systematic search of PubMed, Web of Science and ScienceDirect for English research articles reporting on the molecular epidemiology of Mycobacterium tuberculosis complex resistance in Africa from January 2007 to December 2018 was undertaken.
RESULTS AND CONCLUSION : Qualitative and quantitative synthesis were, respectively, undertaken with 232 and 186 included articles, representing 32 countries. TB monoresistance rate was highest for isoniazid (59%) and rifampicin (27%), particularly in Zimbabwe (100%), Swaziland (100%), and Sudan (67.9%) whilst multidrug resistance (MDR) rate was substantial in Zimbabwe (100%), Sudan (34.6%), Ivory Coast (24.5%) and Ethiopia (23.9%). Resistance-conferring mutations were commonly found in katG (n = 3694), rpoB (n = 3591), rrs (n = 1272), inhA (n = 1065), pncA (n = 1063) and embB (n = 705) in almost all included countries: S315G/I/N/R/T, V473D/F/G/I, Q471H/Q/R/Y, S303C/L etc. in katG; S531A/F/S/G, H526A/C/D/G, D516A/E/G etc. in rpoB; A1401G, A513C etc. in rrs; -15C→T, -17G→A/T, -16A→G etc. in inhA; Ins456C, Ins 172 G, L172P, C14R, Ins515G etc. in pncA. Commonest lineages and families such as T (n = 8139), LAM (n = 5243), Beijing (n = 5471), Cameroon (n = 3315), CAS (n = 2021), H (n = 1773) etc., with the exception of T, were not fairly distributed; Beijing, Cameroon and CAS were prevalent in South Africa (n = 4964), Ghana (n = 2306), and Ethiopia/Tanzania (n = 799/635), respectively. Resistance mutations were not lineage-specific and sputum (96.2%) were mainly used for diagnosing TB resistance using the LPA (38.5%), GeneXpert (17.2%), whole-genome sequencing (12.3%) and PCR/amplicon sequencing (9%/23%). Intercountry spread of strains was limited while intra-country dissemination was common. TB resistance and its diagnosis remain a major threat in Africa, necessitating urgent action to contain this global menace.Figure S1: Frequency of M. tuberculosis Lineages/sub-lineages in Africa, January 2007-December 2018: Frequency of Indo-oceanic lineage/sub-lineages (A); Beijing sublineage (B); CAS-sublineage (C), Euro-American lineage/sub-lineages (D); M. africanum West Africa I & II (E); M. tuberculosis Eth lineage 7 and sub-lineages (F); and proportion of each M. tuberculosis lineage in Africa (G).Table S1: Distribution of M. tuberculosis complex strains, specimen source/s, genotyping method/s, molecular anti-TB drug resistance rate and resistance mechanisms in M. tb across African countries, January 2007 to December 2018Table S2: Resistance mechanisms, molecular diagnosis method/s used, frequency and proportion of gene mutation per total resistant M. tuberculosis complex isolates across African countries, January 2007- December 2018Table S3: Molecular antibiotics resistance rates and resistance mechanisms in M. tuberculosis complex across African countries, January 2007-December 2018.Table S4: Frequency of gene mutation(s) and specific amino acid/nucleotide changes conferring antitubercular drug resistances across African countries January 2007- December 2018Table S5: Distribution of specimen source/s, phenotypic DST method/s used, total number of isolates, and phenotypic antibiotics monoresistance rate, MDR and XDR rate of M. tb complex across African countries, January 2007- December 2018Table S6: Distribution of genotypes/lineages/sub-lineages, frequency and patterns of antibiotics resistance-conferring mutations across African countries, January 2007- December 2018Supplementary dataset 1: Metadata of M. tuberculosis isolates included in phylogenomic analyses.Supplementary dataset 2: Country-by-country frequency of lineage and sub-lineage of M. tuberculosis in Africa: January 2007-December 2018http://www.elsevierhealth.com/journals/jinf2020-12-01hj2020Medical Microbiolog
A comparative evaluation of the new Genexpert MTB/RIF ultra and other rapid diagnostic assays for detecting tuberculosis in pulmonary and extra pulmonary specimens
Studies evaluating the new GeneXpert Ultra with other rapid diagnostic assays are limited, particularly
in diferent geographical settings. The performance of the GeneXpert Ultra, the GeneXpert G4, the
Line probe assays (LPA) and auramine smear microscopy in detecting TB in pulmonary and extrapulmonary samples were thus evaluated. Remnants (n=205 samples) of pulmonary (n=125 samples)
and extra-pulmonary (n=80 samples) specimens from TB suspects were prospectively collected. Each
sample was divided for diagnosis using microscopy, GeneXpert MTB/RIF assays, and LPA; these were all
comparatively evaluated, using the MGIT 960 culture as a gold standard. The sensitivity and specifcity
of microscopy, Xpert Ultra, Xpert G4 and MTBDRplus (ver 2) in pulmonary samples were respectively:
82.00% and 90.28%; 88.00% and 58.57%; 79.59% and 90.28%; 80.00% and 11.11%. For extrapulmonary specimen, the sensitivity and specifcity were respectively: 53.85% and 98.51%; 69.23% and
49.25%; 50.00% and 97.01%; 69.23% and 25.37%. The new and improved GeneXpert Ultra assay was
more sensitive than GeneXpert G4 and LPA in both pulmonary and extra pulmonary samples, albeit
with lower specifcity than the GeneXpert G4. The auramine and LPA tests were also highly sensitive,
although the LPA was less specifc.University of Pretoria; National Research Foundation; Medical Research Council of South Africahttps://www.nature.com/sreppm2020Medical Microbiolog
Molecular screening of clinical multidrug-resistant gram-negative bacteria shows endemicity of carbapenemases, coexistence of multiple carbapenemases, and rarity of mcr in South Africa
Please read abstract in the article.The NHLS and the National Research Foundation of South Africa.https://home.liebertpub.com/publications/microbial-drug-resistance/44hj2023Medical Microbiolog
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