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Background: Enterococci are clinically significant because of their increasing antibiotic resistance and their ability to cause severe infections due to an arsenal of virulence genes. Few studies in the developing world have examined virulence factors that may significantly impact patient outcomes. This study describes the antimicrobial resistance profiles and prevalence of five key Enterococcal virulence genes gelE, asa, cylA, esp, and hyl in forty-four clinical Enterococcus faecalis and E. faecium isolates in Kenya and their association with patients' demographic and clinical characteristics. Results: All E. faecium isolates were obtained from hospital-acquired skin and soft tissue infections. While E. faecalis was associated with community-acquired urinary tract infections. All isolates were resistant to erythromycin, whereas 11/44 (27.5%), 25/44 (56.8%), 28/44 (63.6%), 37/44 (84.1%), 40/44 (90.0%), and 43/44 (97.5%) were susceptible to tetracycline, levofloxacin, gentamicin, ampicillin, nitrofurantoin, and teicoplanin, respectively. All isolates were susceptible to tigecycline, vancomycin, and linezolid. There was little difference in the antibiotic resistance profiles between E. faecalis and E. faecium. The prevalence of the virulence genes among the 44 isolates were 27 (61.4%) for gelE, 26 (59.1%) for asa1, 16 (36.3%) for esp, 11 (25.0%) for cylA, and 1 (2.3%) for hyl. 72.9% of E. faecalis isolates had multiple virulence genes compared to 57% of E. faecium isolates with no virulence genes. The hyl gene was only detected in E. faecium, while cylA and asa1 were only detected in E. faecalis. A significant correlation was observed between the presence of asa1 and esp virulence genes and tetracycline resistance (P=0.0305 and 0.0363, respectively). A significant correlation was also observed between the presence of virulence genes gelE and asa1 and nitrofurantoin resistance (P=0.0175 and 0.0225, respectively) and ampicillin resistance (P=0.0005 and 0.0008, respectively). Conclusion: The study highlights the high levels of erythromycin resistance in E. faecalis and E. faecium, the demographic factors influencing the species distribution among patients, and the accumulation of multiple virulence genes in E. faecalis. The significant association of gelE, asa1, and esp virulence genes with drug resistance could explain the pathogenic success of E. faecalis and provides a guide for future studies.
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Klebsiella pneumoniae is a globally significant opportunistic pathogen causing healthcare-associated and community-acquired infections. This study examined the epidemiology and the distribution of resistance and virulence genes in clinical K. pneumoniae strains in Kenya. A total of 89 K. pneumoniae isolates were collected over six years from five counties in Kenya and were analyzed using whole-genome sequencing and bioinformatics. These isolates were obtained from community-acquired (62/89) and healthcare-associated infections (21/89), and from the hospital environment (6/89). Genetic analysis revealed the presence of blaNDM-1 and blaOXA-181 carbapenemase genes and the armA and rmtF genes known to confer pan-aminoglycoside resistance. The most abundant extended-spectrum beta-lactamase genes identified were blaCTX-M-15 (36/89), blaTEM (35/89), and blaOXA (18/89). In addition, one isolate had a mobile colistin resistance gene (mcr-8). Fluoroquinolone resistance-conferring mutations in gyrA and parC genes were also observed. The most notable virulence factors were those associated with hyper-virulence (rmpA/A2 and magA), yersiniabactin (ybt), salmochelin (iro), and aerobactin (iuc and iutA). A total of 38 distinct sequence types were identified, including known global lineages ST14, ST15, ST147, and ST307, and a regional clone ST17 implicated in regional outbreaks. In addition, this study genetically characterized two potential hypervirulent isolates and two community-acquired ST147 high-risk clones that contained carbapenemase genes, yersiniabactin, and other multidrug resistance genes. These results demonstrate that the resistome and virulome of Kenyan clinical and hospital environmental K. pneumoniae isolates are diverse. The reservoir of high-risk clones capable of spreading resistance, and virulence factors have the potential to cause unmanageable infection outbreaks with high morbidity and mortality.
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Pseudomonas aeruginosa is a leading cause of nosocomial infections worldwide. It can produce a range of debilitating infections, have a propensity for developing antimicrobial resistance, and present with a variety of potent virulence factors. This study investigated the sequence types (ST), phenotypic antimicrobial susceptibility profiles, and resistance and virulence genes among clinical isolates from urinary tract and skin and soft tissue infections. Fifty-six P. aeruginosa clinical isolates were obtained from six medical centers across five counties in Kenya between 2015 and 2020. Whole-genome sequencing (WGS) was performed to conduct genomic characterization, sequence typing, and phylogenetic analysis of the isolates. Results showed the presence of globally distributed high-risk clones (ST244 and ST357), local high-risk clones (ST2025, ST455, and ST233), and a novel multidrug-resistant (MDR) clone carrying virulence genes (ST3674). Furthermore, 31% of the study isolates were found to be MDR with phenotypic resistance to a variety of antibiotics, including piperacillin (79%), ticarcillin-clavulanic acid (57%), meropenem (34%), levofloxacin (70%), and cefepime (32%). Several resistance genes were identified, including carbapenemases VIM-6 (ST1203) and NDM-1 (ST357), fluoroquinolone genes, crpP, and qnrVCi, while 14 and 22 different chromosomal mutations were detected in the gyrA and parC genes, respectively. All isolates contained at least three virulence genes. Among the virulence genes identified, phzB1 was the most abundant (50/56, 89%). About 21% (12/56) of the isolates had the exoU+/exoS- genotype, while 73% (41/56) of the isolates had the exoS+/exoU- genotype. This study also discovered 12 novel lineages of P. aeruginosa, of which one (ST3674) demonstrated both extensive antimicrobial resistance and the highest number of virulence genes (236/242, 98%). Although most high-risk clones were detected in Nairobi County, high-risk and clones of interest were found throughout the country, indicating the local spread of global epidemic clones and the emergence of new strains. Thus, this study illustrates the urgent need for coordinated local, regional, and international antimicrobial resistance surveillance efforts.
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INTRODUCTION: Clostridioides difficile is primarily associated with hospital-acquired diarrhoea. The disease burden is aggravated in patients with comorbidities due to increased likelihood of polypharmacy, extended hospital stays and compromised immunity. The study aimed to investigate comorbidity predictors of healthcare facility-onset C. difficile infection (HO-CDI) in hospitalized patients. METHODOLOGY: We performed a cross sectional study of 333 patients who developed diarrhoea during hospitalization. The patients were tested for CDI. Data on demographics, admission information, medication exposure and comorbidities were collected. The comorbidities were also categorised according to Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). Comorbidity predictors of HO-CDI were identified using multiple logistic regression analysis. RESULTS: Overall, 230/333 (69%) patients had comorbidities, with the highest proportion being in patients aged over 60 years. Among the patients diagnosed with HO-CDI, 63/71(88.7%) reported comorbidities. Pairwise comparison between HO-CDI patients and comparison group revealed significant differences in hypertension, anemia, tuberculosis, diabetes, chronic kidney disease and chronic obstructive pulmonary disease. In the multiple logistic regression model significant predictors were chronic obstructive pulmonary disease (odds ratio [OR], 9.51; 95% confidence interval [CI], 1.8-50.1), diabetes (OR, 3.56; 95% CI, 1.11-11.38), chronic kidney disease (OR, 3.88; 95% CI, 1.57-9.62), anemia (OR, 3.67; 95% CI, 1.61-8.34) and hypertension (OR, 2.47; 95% CI, 1.-6.07). Among the comorbidity scores, CCI score of 2 (OR 6.67; 95% CI, 2.07-21.48), and ECI scores of 1 (OR, 4.07; 95% CI, 1.72-9.65), 2 (OR 2.86; 95% CI, 1.03-7.89), and ≥ 3 (OR, 4.87; 95% CI, 1.40-16.92) were significantly associated with higher odds of developing HO-CDI. CONCLUSION: Chronic obstructive pulmonary disease, chronic kidney disease, anemia, diabetes, and hypertension were associated with an increased risk of developing HO-CDI. Besides, ECI proved to be a better predictor for HO-CDI. Therefore, it is imperative that hospitals should capitalize on targeted preventive approaches in patients with these underlying conditions to reduce the risk of developing HO-CDI and limit potential exposure to other patients.
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Microbial monitoring of hospital surfaces can help identify target areas for improved infection prevention and control (IPCs). This study aimed to determine the levels and variations in the bacterial contamination of high-touch surfaces in five Kenyan hospitals and identify the contributing modifiable risk factors. A total of 559 high-touch surfaces in four departments identified as high risk of hospital-acquired infections were sampled and examined for bacterial levels of contamination using standard bacteriological culture methods. Bacteria were detected in 536/559 (95.9%) surfaces. The median bacterial load on all sampled surfaces was 6.0 × 104 CFU/cm2 (interquartile range (IQR); 8.0 × 103-1.0 × 106). Only 55/559 (9.8%) of the sampled surfaces had acceptable bacterial loads, <5 CFU/cm². Cleaning practices, such as daily washing of patient sheets, incident rate ratio (IRR) = 0.10 [95% CI: 0.04-0.24], providing hand wash stations, IRR = 0.25 [95% CI: 0.02-0.30], having running water, IRR = 0.19 [95% CI: 0.08-0.47] and soap for handwashing IRR = 0.21 [95% CI: 0.12-0.39] each significantly lowered bacterial loads. Transporting dirty linen in a designated container, IRR = 72.11 [95% CI: 20.22-257.14], increased bacterial loads. The study hospitals can best reduce the bacterial loads by improving waste-handling protocols, cleaning high-touch surfaces five times a day and providing soap at the handwash stations.
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Cross Infection , Hospitals , Bacterial Load , Hand Disinfection , Humans , KenyaABSTRACT
Carbapenem-resistant gram-negative bacteria are an increasingly significant clinical threat globally. This risk may be underestimated in Kenya as only four carbapenemase genes in three bacterial species have been described. The study aimed to understand the antibiotic resistance profiles, genes, sequence types, and distribution of carbapenem-resistant gram-negative bacteria from patients in six hospitals across five Kenyan counties by bacterial culture, antibiotic susceptibility testing, and whole-genome sequence analysis. Forty-eight, non-duplicate, carbapenem non-susceptible, clinical isolates were identified across the five counties (predominantly in Nairobi and Kisii): twenty-seven Acinetobacter baumannii, fourteen Pseudomonas aeruginosa, three Escherichia coli, two Enterobacter cloacae, and two Klebsiella pneumoniae. All isolates were non-susceptible to ß-lactam drugs with variable susceptibility to tigecycline (66%), minocycline (52.9%), tetracycline (29.4%), and levofloxacin (22.9%). Thirteen P. aeruginosa isolates were resistant to all antibiotics tested. Eleven carbapenemase genes were identified: blaNDM-1, blaOXA-23, -58, -66, -69, and -91 in A. baumannii (STs 1, 2, 164 and a novel ST1475), blaNDM-1 in E. cloacae (STs 25,182), blaNDM-1, blaVIM-1and -6, blaOXA-50 in P. aeruginosa (STs 316, 357, 654, and1203), blaOXA-181, blaNDM-1 in K. pneumoniae (STs 147 and 219), and blaNDM-5 in E. coli (ST164). Five A. baumannii isolates had two carbapenemases, blaNDM-1, and either blaOXA-23 (4) or blaOXA-58 (1). AmpC genes were detected in A. baumannii (blaADC-25), E. cloacae (blaDHA-1 and blaACT-6, 16), and K. pneumoniae (blaCMY). Significant multiple-drug resistant genes were the pan-aminoglycoside resistance16srRNA methyltransferase armA, rmtB, rmtC, and rmtF genes. This study is the first to report blaOXA-420, -58, -181, VIM-6, and blaNDM-5 in Kenyan isolates. High-risk STs of A. baumannii (ST1475, ST2), E. cloacae ST182, K. pneumoniae ST147, P. aeruginosa (ST357, 654), and E. coli ST167, ST648 were identified which present considerable therapeutic danger. The study recommends urgent carbapenem use regulation and containment of high-risk carbapenem-resistant bacteria.
Subject(s)
Anti-Bacterial Agents/pharmacology , Carbapenems/pharmacology , Genes, Bacterial , Genes, MDR , Gram-Negative Bacteria/genetics , Gram-Negative Bacterial Infections/microbiology , Drug Resistance, Bacterial , Gram-Negative Bacteria/drug effects , Gram-Negative Bacteria/isolation & purification , Gram-Negative Bacterial Infections/drug therapy , Gram-Negative Bacterial Infections/epidemiology , Humans , Kenya/epidemiologyABSTRACT
The emergence and rise of mobile colistin resistance genes are of great global concern due to the ease of transfer of resistance to other bacteria. This report describes the genome of a colistin- and multidrug-resistant Klebsiella pneumoniae isolate bearing mcr-8, obtained from a hospitalized patient in Kenya.
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Introduction: Clostridioides difficile is a neglected pathogen in many African countries as it is generally not regarded as one of the major contributors toward the diarrheal disease burden in the continent. However, several studies have suggested that C. difficile infection (CDI) may be underreported in many African settings. The aim of this study was to determine the prevalence of CDI in hospitalized patients, evaluate antimicrobial exposure, and detect toxin and antimicrobial resistance profiles of the isolated C. difficile strains. Methods: In this cross-sectional study, 333 hospitalized patients with hospital-onset diarrhoea were selected. The stool samples were collected and cultured on cycloserine-cefoxitin egg yolk agar (CCEY). Isolates were presumptively identified by phenotypic characteristics and Gram stain and confirmed by singleplex real-time PCR (qPCR) assays detecting the species-specific tpi gene, toxin A (tcdA) gene, toxin B (tcdB) gene, and the binary toxin (cdtA/cdtB) genes. Confirmed C. difficile isolates were tested against a panel of eight antimicrobials (vancomycin, metronidazole, rifampicin, ciprofloxacin, tetracycline, clindamycin, erythromycin, and ceftriaxone) using E-test strips. Results: C. difficile was detected in 57 (25%) of diarrheal patients over the age of two, 56 (98.2%) of whom received antimicrobials before the diarrheal episode. Amongst the 71 confirmed isolates, 69 (97.1%) harbored at least one toxin gene. More than half of the toxigenic isolates harbored a truncated tcdA gene. All isolates were sensitive to vancomycin, while three isolates (2.1%) were resistant to metronidazole (MIC >32 mg/L). High levels of resistance were observed to rifampicin (65/71, 91.5%), erythromycin (63/71, 88.7%), ciprofloxacin (59/71, 83.1%), clindamycin (57/71, 80.3%), and ceftriaxone (36/71, 50.7.8%). Among the resistant isolates, 61 (85.9%) were multidrug-resistant. Conclusion: Multidrug-resistant C. difficile strains were a significant cause of healthcare facility-onset C. difficile infections in patients with prior antimicrobial exposure in this Kenyan hospital.
Subject(s)
Anti-Infective Agents , Bacterial Toxins , Clostridioides difficile , Anti-Bacterial Agents/pharmacology , Bacterial Toxins/genetics , Clostridioides , Clostridioides difficile/genetics , Cross-Sectional Studies , Humans , Kenya/epidemiology , Microbial Sensitivity Tests , PrevalenceABSTRACT
BACKGROUND: The increase and spread of virulent-outbreak associated, methicillin and vancomycin resistant (MRSA/VRSA) Staphylococcus aureus require a better understanding of the resistance and virulence patterns of circulating and emerging strains globally. This study sought to establish the resistance phenotype, and strains of 32 non-duplicate clinical MRSA and MSSA S. aureus isolates from four Kenyan hospitals, identify their resistance and virulence genes and determine the genetic relationships of MRSA with global strains. METHODS: Antimicrobial susceptibility profiles were determined on a Vitek 2, genomic DNA sequenced on an Illumina Miseq and isolates typed in-silico. Resistance and virulence genes were identified using ARIBA and phylogenies generated using RAxML. RESULTS: The MRSA isolates were 100% susceptible to vancomycin, teicoplanin, linezolid, and tigecycline. Nine distinct CC, 12 ST and 15 spa types including the novel t17826 and STs (4705, 4707) were identified with CC8 and CC152 predominating. MRSA isolates distributed across 3 CCs; CC5-ST39 (1), CC8 - ST241 (4), a novel CC8-ST4705 (1), ST8 (1) and CC152 (1). There was > 90% phenotype-genotype concordance with key resistance genes identified only among MRSA isolates: gyrA, rpoB, and parC mutations, mecA, ant (4')-lb, aph (3')-IIIa, ermA, sat-4, fusA, mphC and msrA. Kenyan MRSA isolates were genetically diverse and most closely related to Tanzanian and UK isolates. There was a significant correlation between map, hlgA, selk, selq and cap8d virulence genes and severe infections. CONCLUSION: The findings showed a heterogeneous S. aureus population with novel strain types. Though limited by the low number of isolates, this study begins to fill gaps and expand our knowledge of S. aureus epidemiology while uncovering interesting patterns of distribution of strain types which should be further explored. Although last-line treatments are still effective, the potential for outbreaks of both virulent and resistant strains remain, requiring sustained surveillance of S. aureus populations.
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Anti-Bacterial Agents/pharmacology , Sequence Analysis, DNA/methods , Staphylococcal Infections/microbiology , Staphylococcus aureus/classification , Virulence Factors/genetics , Drug Resistance, Multiple, Bacterial , Genotype , Humans , Kenya , Methicillin-Resistant Staphylococcus aureus/isolation & purification , Microbial Sensitivity Tests , Phenotype , Phylogeny , Staphylococcus aureus/drug effects , Staphylococcus aureus/pathogenicityABSTRACT
Entamoeba moshkovskii is a member of the Entamoeba complex and a colonizer of the human gut. We used nested polymerase chain reaction (PCR) to differentiate Entamoeba species in stool samples that had previously been screened by microscopy. Forty-six samples were tested, 23 of which had previously been identified as Entamoeba complex positive by microscopy. Of the 46 specimens tested, we identified nine (19.5%) as E. moshkovskii-positive. In seven of these nine E. moshkovskii-positive samples, either E. dispar or E. histolytica (or both) were also identified, suggesting that co-infections may be common. E. moshkovskii was also detected in both symptomatic and asymptomatic participants. To the best of our knowledge, this is the first report of E. moshkovskii in Kenya.
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PURPOSE: Data on the clonal distribution of Staphylococcus aureus in Africa are scanty, partly due to the high costs and long turnaround times imposed by conventional genotyping methods such as spa and multilocus sequence typing (MLST), which means there is a need for alternative typing approaches. This study evaluated the discriminatory power, cost of and time required for genotyping Kenyan staphylococcal isolates using iPlex MassARRAY compared to conventional methods. METHODOLOGY: Fifty-four clinical S. aureus isolates from three counties were characterized using iPlex MassARRAY, spa and MLST typing methods. Ten single-nucleotide polymorphisms (SNPs) from the S. aureus MLST loci were assessed by MassARRAY. >RESULTS: The MassARRAY assay identified 14 unique SNP genotypes, while spa typing and MLST revealed 22 spa types and 21 sequence types (STs) that displayed unique regional distribution. spa type t355 (ST152) was the dominant type overall while t037/t2029 (ST 241) dominated among the methicillin-resistant S. aureus (MRSA) isolates. MassARRAY showed 83 % and 82 % accuracy against spa typing and MLST, respectively, in isolate classification. Moreover, MassARRAY identified all MRSA strains and a novel spa type. MassARRAY had a reduced turnaround time (<12 h) compared to spa typing (4 days) and MLST (20 days). The MassARRAY reagent and consumable costs per isolate were approximately $18 USD compared to spa typing ($30 USD) and MLST ($126 USD). CONCLUSION: This study demonstrated that iPlex MassARRAY can be adapted as a useful surveillance tool to provide a faster, more affordable and fairly accurate method for genotyping African S. aureus isolates to identify clinically significant genotypes, MRSA strains and emerging strain types.