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Antimicrobial resistance of Klebsiella pneumoniae stool isolates circulating in Kenya

  • Chris Rowe Taitt ,

    Affiliation Center for Bio/Molecular Science & Engineering, Naval Research Laboratory, Washington, DC United States of America

  • Tomasz A. Leski,

    Affiliation Center for Bio/Molecular Science & Engineering, Naval Research Laboratory, Washington, DC United States of America

  • Daniel P. Erwin,

    Affiliation US Army Medical Research Directorate-Kenya, Walter Reed Army Institute of Research, Kericho, Kenya

  • Elizabeth A. Odundo,

    Affiliation KEMRI/US Army Medical Research Directorate-Kenya, Walter Reed Army Institute of Research, Kericho, Kenya

  • Nancy C. Kipkemoi,

    Affiliation KEMRI/US Army Medical Research Directorate-Kenya, Walter Reed Army Institute of Research, Kericho, Kenya

  • Janet N. Ndonye,

    Affiliation KEMRI/US Army Medical Research Directorate-Kenya, Walter Reed Army Institute of Research, Kericho, Kenya

  • Ronald K. Kirera,

    Affiliation KEMRI/US Army Medical Research Directorate-Kenya, Walter Reed Army Institute of Research, Kericho, Kenya

  • Abigael N. Ombogo,

    Affiliation KEMRI/US Army Medical Research Directorate-Kenya, Walter Reed Army Institute of Research, Kericho, Kenya

  • Judd L. Walson,

    Affiliations Department of Global Health, University of Washington, Seattle, WA, United States of America, Departments of Pediatrics, Medicine, and Epidemiology, University of Washington, Seattle, WA, United States of America

  • Patricia B. Pavlinac,

    Affiliation Department of Global Health, University of Washington, Seattle, WA, United States of America

  • Christine Hulseberg,

    Affiliation US Army Medical Research Directorate-Kenya, Walter Reed Army Institute of Research, Kericho, Kenya

  • Gary J. Vora

    Affiliation Center for Bio/Molecular Science & Engineering, Naval Research Laboratory, Washington, DC United States of America


We sought to determine the genetic and phenotypic antimicrobial resistance (AMR) profiles of commensal Klebsiella spp. circulating in Kenya by testing human stool isolates of 87 K. pneumoniae and three K. oxytoca collected at eight locations. Over one-third of the isolates were resistant to ≥3 categories of antimicrobials and were considered multidrug-resistant (MDR). We then compared the resistance phenotype to the presence/absence of 238 AMR genes determined by a broad-spectrum microarray and PCR. Forty-six genes/gene families were identified conferring resistance to β-lactams (ampC/blaDHA, blaCMY/LAT, blaLEN-1, blaOKP-A/OKP-B1, blaOXA-1-like family, blaOXY-1, blaSHV, blaTEM, blaCTX-M-1 and blaCTX-M-2 families), aminoglycosides (aac(3)-III, aac(6)-Ib, aad(A1/A2), aad(A4), aph(AI), aph3/str(A), aph6/str(B), and rmtB), macrolides (mac(A), mac(B), mph(A)/mph(K)), tetracyclines (tet(A), tet(B), tet(D), tet(G)), ansamycins (arr), phenicols (catA1/cat4, floR, cmlA, cmr), fluoroquinolones (qnrS), quaternary amines (qacEΔ1), streptothricin (sat2), sulfonamides (sul1, sul2, sul3), and diaminopyrimidines (dfrA1, dfrA5, dfrA7, dfrA8, dfrA12, dfrA13/21/22/23 family, dfrA14, dfrA15, dfrA16, dfrA17). This is the first profile of genes conferring resistance to multiple categories of antimicrobial agents in western and central Kenya. The large number and wide variety of resistance genes detected suggest the presence of significant selective pressure. The presence of five or more resistance determinants in almost two-thirds of the isolates points to the need for more effective, targeted public health policies and infection control/prevention measures.


Antimicrobial resistance (AMR) is of significant concern in developing nations due to over-use of antimicrobial agents, widespread availability of counterfeit or substandard drugs, and poor infection control measures [1,2]. The scarcity of reliable and timely information, particularly in sub-Saharan Africa, may further limit epidemiological surveillance and effective stewardship efforts.

While only infrequently associated with diarrheal disease, Klebsiella pneumoniae and other klebsiellae are common intestinal commensals with significant potential to cause extraintestinal infections in severely ill patients and diarrhea in HIV/AIDS patients [3,4,5,6,7]. Of additional concern, Klebsiella spp. acquire, accumulate, and transfer myriad AMR determinants and therefore may represent a significant reservoir for resistance within the gut [8,9,10] and may increase the risk of resistant infections in hospital environments [5,11]. Indeed, in vivo transfer of AMR genes from intestinal klebsiellae to other bacterial species has been well documented [12,13,14,15,16]. Here, we use intestinal Klebsiella isolates collected at eight medical treatment facilities in western and central Kenya to interrogate the gut resistome and its potential for rapid evolution and spread.

Materials and methods

Sample collection, processing, antimicrobial susceptibility testing

Stool specimens or rectal swabs were collected into sterile, wide-mouth collection cups and aliquoted into thirds (Cary-Blair transport media, 10% formalin for parasitology, and a vial for freezing at -20C for virology) upon enrollment; previous studies showed no differences in frequency of bacterial isolation between stool samples and rectal swabs [17]. Samples were stripped of all identifiers and were assigned accession numbers before transportation to the WRAIR Microbiology Hub laboratory in Kericho (MHK) within 72 hours of collection. Samples were then plated on primary, selective, and differential media. MacConkey, MacConkey-sorbitol, sheep blood agar, Hektoen enteric agar, thiosulfate-citrate-bile-sucrose agar, cefoperazone-vancomycin-amphotericin agar, and cefsulodin-irgasan-novobiocin agar were the primary media; no specific enrichment step was performed as part of the normal workup. At 24 and 48 hours, colonies were subcultured, Gram stained, and subjected to biochemical testing (indole production, Voges-Proskauer reaction, o-nitrophenyl-Δ-D-galactopyrandoside production) before analysis on Microflex MALDI Biotyper (Bruker Daltonics, Millerica, MA, USA) and MicroScan WalkAway40 (Siemens Healthcare, Sacramento, CA, USA) systems for identification and antibiotic susceptibility testing (AST), respectively. MIC 44 and NC 66 panels were used with LabPro software updated for 2015 CLSI breakpoints [18] and automated interpretation of results. Laboratory personnel performing susceptibility testing were enrolled in External Quality Assurance/Proficiency Testing for both College of American Pathologists (three cycles/year) and United Kingdom National External Quality Assessment Service (monthly). Weekly quality control for AST was performed using recommended ATCC strains [18].

Study sites

Samples were collected from eight Kenyan clinical sites participating in the Walter Reed Army Institute of Research (WRAIR), University of Washington/Kenya Institute of Medical Research Institute (KEMRI) collaborative research group enteric surveillance programs. These surveillance sites serve diverse communities: Mbagathi District Hospital serves a highly urban population near the center of Nairobi. The Eldoret-based clinic at Moi Barracks (MBB1) serves military service members and their families in the Kenyan highlands. Kericho District Hospital, also located in the highlands, serves a relatively rural community of tea pluckers and farmers. Kombewa is similarly considered rural. The remaining sites at the district hospitals of Kisumu, Kisii, Migori, and Homa Bay are located in western Kenya near Lake Victoria and serve both urban and rural populations largely subsistent upon agricultural and fishing economies.

Eligibility criteria

Protocol-trained clinical staff at all sites recruited subjects experiencing acute diarrhea (three or more loose stools within a 24 hour period). The cases were recruited only from outpatient populations, and none were admitted to the hospital. Age-matched asymptomatic controls were recruited from the same sites if the subjects had not experienced acute diarrhea within the previous two week period; when possible, controls were healthy siblings close in age to the index case. Participants experiencing (chronic) diarrhea lasting more than 14 days were excluded. Medical histories were captured for a small subset of samples (n = 13). Both cases and controls provided basic clinical, epidemiological (water source and treatment) and demographic (age, gender, residence) information. Enrollment of all subjects required informed consent and custodial assent for subjects under 18 years of age. No diagnostic or therapeutic decisions were based on any phenotypic or genotypic data generated for this study. Work performed on this study was approved by the KEMRI and WRAIR Institutional Review Boards under KEMRI SSC #1549/WRAIR #1549 and KEMRI SSC #2056/WRAIR #1811.

Detection of resistance determinants

The presence/absence of 238 different AMR genes was determined using the Antimicrobial Resistance Determinant Microarray (ARDM) v.2 as previously described [19,20]. Briefly, this microarray was designed for detection of >200 determinants derived from both Gram-positive and–negative bacteria. Chip content covers genes conferring resistance to 15 categories of antimicrobials (β-lactams, aminoglycosides, macrolides, lincosamides, streptogramins, quaternary amines, ansamycins, diaminopyrimidines, antimicrobial peptides, tetracyclines, phenicols, glycopeptides, platensemycin, fluoroquinolones, sulfonamides); several plasmid-borne multidrug efflux pumps are also represented on the chip. Full chip content information is given in [19]. Following sample processing, hybridization, and washing, the signal associated with each probe was determined electrochemically. An AMR gene was identified as detected when > 50% of its representative probes had signals above the mean signal from the lowest 2,128 probes + 3 standard deviations or when >70% of its probes had signals above either of two less stringent thresholds [20,21]. A limited set of detected AMR and integrase genes were confirmed by PCR and DNA amplicon sequencing (S1 Table).

Statistical analysis

Statistical comparisons between populations were performed using two-tailed student's t-tests (assuming unequal variance). Chi-square tests were used to compare binomial proportions in independent samples (2 × n contingency tables). Linear regression was used to compare the number of genes/isolate with age (Ho: slope = 0, tested by student's t-test).


Sample set characteristics

A total of 90 Klebsiella spp. strains were isolated from participants ranging in age from 4 months to 54 years (median age 57 months). Half of the subjects presented with acute diarrheal illness and half were healthy controls. The majority of isolates came from the Kisii and Kisumu sites (37 [41.1%] and 16 [17.8%] isolates, respectively) (Table 1). Thirty-three of the isolates (36.7%) were non-susceptible to at least three categories of antimicrobials and were considered multidrug resistant (MDR) per Magiorakos [22]. One isolate, MHK02590, was considered extensively drug-resistant (non-susceptible to at least one agent in all but two or fewer antimicrobial categories; Table 2) [22]. As a whole, there were no differences between overall MDR phenotypes (P = 0.940) in the strains isolated from subjects with ADI and asymptomatic controls, nor between genders (P = 0.463). Between 80 and 90% of the tested isolates were susceptible to all β-lactams except ampicillin, to one or more aminoglycosides, and to both of the fluoroquinolones tested. Over half were susceptible to tetracycline, but more than 60% were resistant to sulfamethoxazole-trimethoprim (SXT).

Table 1. Summary of antimicrobial phenotypic susceptibility for diarrheal and control isolates.

Table 2. Metadata and phenotypic antimicrobial susceptibility for individual isolates.

A total of 46 AMR genes or gene families covering 11 categories of antimicrobials were identified amongst the 90 isolates using a broad-range microarray (Table 3). PCR was used to verify the presence of a select group of genes detected by microarray, as well as ancillary genes associated with specific combinations of AMR determinants (S1 Table). All but six isolates harbored multiple resistance determinants (Table 4). While there were no differences in MDR phenotype between age quartiles (P = 0.336), a small but significant inverse relationship was observed between the total number of genes per isolate and age (P = 0.029; t-test of linear regression), with isolates from younger subjects harboring a larger number of genes. No significant differences in genes/isolate were observed between diarrheal and control isolates (P = 0.458) or between genders (P = 0.184). The disparate numbers of isolates collected at the various sites (n = 4 to n = 37) precluded any statistically valid site-to-site comparisons. However, sites with highest percentages of MDR phenotype, Mbagathi (3 of 4 isolates) and Kisii (17 of 37 isolates), also harbored the widest overall varieties of resistance determinants (28 and 41 determinants, respectively).

Table 4. AMR genes present in individual Kenyan Klebsiella spp. isolates.

Resistance to β-lactams

The ARDM v.2 content comprises probes for 52 β-lactamase genes, including 12 families of extended-spectrum β-lactamases (ESBLs) and 15 carbapenemases. The ARDM detected blaSHV, a chromosomal gene presumptively carried in all K. pneumoniae [23], in 63 isolates (70%), while PCR detected blaSHV in an additional fourteen (S2 Table); 13 of the 90 isolates were negative for blaSHV by both methods, but this may be due to point mutations within the primer regions (PCR) or regions used for hybridization on the microarray. β-lactamase inhibitors such as clavulanate and sulbactam are typically active against Klebsiella SHV-1 and TEM-1 lactamases, but one-third of the isolates tested here showed resistance to at least one of these inhibitors. While such resistance may arise from hyperproduction of β-SHV lactamases [24], this resistance was highly correlated to the presence of blaTEM (P<0.0001), suggesting either TEM hyperproduction [25,26] or the possible presence of inhibitor-resistant TEM enzymes. The presence of blaOXA-1-like genes–most often conferring resistance to clavulanate and sulbactam–can also potentially explain phenotypic inhibitor resistance in two strains (MHK01590, MHK05068), although blaTEM genes are also present in both. However, strain MHK01305—positive for blaOXA-1-like, blaTEM, and blaCTX-M-1 family genes–is broadly susceptible to almost all tested β-lactams and lactam-inhibitor combinations, suggesting that either none of these genes are expressed or that the encoded gene products are non-functional.

Nine strains were resistant to at least one third or fourth generation cephalosporin (Table 1), with six classified as ESBL producers by the MicroScan. Five of the ESBL-producing isolates were positive for blaCTX-M-1-group genes (confirmed by PCR, see S1 and S2 Tables). An additional three isolates also carried blaCTX-M-1-family genes, two of which were resistant to the third and fourth generation cephalosporins tested but negative for ESBL production by Microscan; one of these (MHK04922) also carried ampC/blaDHA, which can mask the ESBL phenotype [27]. One isolate (NTS01708) was positive for the blaCTX-M-2-family, which was also confirmed by PCR. The blaCTX-M-2 amplicon sequence (NCBI Accession no. KX377894) identified this gene as encoding a protein most similar to CTX-M-2 (Toho 1), CTX-M-20, CTX-M-56, CTX-M-75, CTX-M-95, CTX-M-165, and KLUA-9. To our knowledge, this is the first time that a gene from the blaCTX-M-2-family has been identified within Enterobacteriaceae from East Africa. Interestingly, this blaCTX-M-2-positive isolate were susceptible to both of the lactam/inhibitor combinations tested and all other tested β-lactams except ampicillin, suggesting that this gene was not transcribed or that the encoded proteins was non-functional. None of the 90 isolates were positive for genes encoding the CTX-M-8 and CTX-M-9 families of ESBLs. The preferential carriage of CTX-M-1-type enzymes over other ESBLs agrees with other studies of this region [28,29].

Only three isolates were phenotypically resistant to either imipenem (one isolate) or meropenem (two isolates). However, none of the 15 carbapenemase genes represented on the ARDM v.2 were detected.

Resistance to aminoglycosides

Isolates were tested for the presence of 44 different aminoglycoside resistance determinants. While only nine of the isolates were resistant to the three aminoglycosides tested, a relatively large number harbored genes commonly associated with aminoglycoside resistance: aac(3)-III (five isolates); aac(6)-Ib family (four isolates); aadA1/A2 family (18 isolates); aad(A4) (one isolate); aphA1 (seven isolates); aph3/str(A) (44 isolates); aph6/str(B) (47 isolates), and rmtB (one isolate). As the microarray cannot detect point mutations, we PCR-amplified and sequenced the aac(6)-Ib genes detected in four isolates to confirm that these alleles were not the aac(6)-Ib-cr variant conferring resistance to quinolones. The presence of aac(3)-III was correlated to phenotypic resistance to gentamicin and tobramycin (P < 0.0001) and aac(6)-Ib family genes to amikacin and tobramycin (P < 0.0001). Not surprisingly, the isolate harboring rmtB, which confers pan-resistance to aminoglycosides, was resistant to all three aminoglycosides.

Resistance to tetracyclines, chloramphenicol

Almost half of the isolates were non-susceptible to tetracycline. Phenotypic resistance was positively correlated to the presence of a tetracycline resistance determinant (P < 0.0005), although 10 isolates harboring resistance genes were phenotypically sensitive. Of the 38 tetracycline resistance genes on the ARDM v.2, only four were detected: tet(A) (18%), tet(D) (12%), tet(B) (10%), and tet(G) (1%).

The ARDM v.2 chip also contains probes directed against 20 chloramphenicol resistance determinants. However, only four were detected in the tested population: cmr (32 isolates); two variants of floR originating from different species (one isolate); cmlA (one isolate); and catA1/cat4 (seven isolates). Phenotypic resistance to chloramphenicol was not assessed.

Resistance to quinolones

A single isolate (MHK02590) was resistant to both ciprofloxacin and levofloxacin, while the remainder were susceptible to one (three isolates) or both quinolones tested (86 isolates). The plasmid-mediated quinolone resistance gene, qnrS, was observed in two isolates, of which one displayed intermediate susceptibility for ciprofloxacin. None of the other plasmid-mediated quinolone resistance genes were detected (norA, qnrA, qepA, aac(6)-Ib-cr). The ARDM is unable to identify mutations in gyrase or helicase genes that confer high-level resistance to quinolones.

Genes conferring resistance to macrolides, lincosamides, streptogramins, and ansamycins

Ansamycins and macrolides, lincosamide, and streptogramin (MLS) antibiotics are not typically considered clinically relevant for treatment of Gram-negative infections. However, some researchers have suggested that commensal Gram-negative organisms may serve as a reservoir of AMR genes that can be transferred to other pathogens and organisms responsible for severe intestinal infections [30,31,32,33]. For this reason, the ARDM v.2 chip content includes ten MLS resistance genes derived from Gram-negative species, in addition to 31 MLS resistance genes derived from Gram-positive species. As expected, none of the isolates tested were positive for any of the Gram-positive-derived MLS resistance determinants, but Escherichia coli-derived genes, mph(A)/mph(K), mac(A), and mac(B), were detected in six, 29, and 25 isolates, respectively. All isolates positive for mac(B) also harbored mac(A). PCR amplification and amplicon sequencing confirmed that the microarray-detected mac(A) and mac(B) sequences are analogous to those derived from E. coli (NCBI accession nos. KX377891 through KX377893), although Klebsiella-derived analogs were also detected. Analogous mac(A) and mac(B) genes derived from Klebsiella spp. are only 70% identical to the E. coli genes and can be discriminated from the E. coli-derived genes by hybridization to the ARDM and amplicon sequencing (S2 Table).

Two isolates were positive for the presence of the rifampicin resistance determinant, arr. The presence of arr and mphA/mphK within stool isolates of K. pneumoniae–while not clinically relevant in itself—may portend the spread of azithromycin or rifaximin resistance, respectively, to other intestinal pathogens, potentially limiting the effectiveness of these drugs for treatment of travelers' diarrhea [34,35].

Resistance to sulfonamides, quaternary amines, streptothricin, and trimethoprim

Sixty percent of the tested isolates were resistant to SXT, a first line agent for treatment of enteric infections in many parts of Africa [33,36]. Phenotypic resistance to SXT was highly correlated to the presence of a sulfonamide or trimethoprim resistance determinant (P << 0.0001). Approximately half of the tested isolates harbored at least one of the 28 trimethoprim resistance genes present on the ARDM: dfrA14 (18 isolates), dfrA1 (nine isolates), dfrA5 (seven isolates), dfrA7 or dfrA8 (5 isolates each), and dfrA12, dfrA13/21/22/23 family, dfrA15, dfrA16, and dfrA17 (three or fewer isolates each). The high rate of dfrA14-positive samples observed here contrasts with other studies showing a much higher proportion of dfrA1 and dfrA7 amongst African intestinal isolates [37,38]. Seven isolates harbored multiple dfrA genes.

Present in 52.2% of the tested isolates, sul2 was the most frequently encountered sulfonamide resistance determinant. Sul1 was detected in 28 isolates, 21 of which also harbored sul2. In agreement with other studies of the region [37,39], sul3 was infrequently encountered (1 isolate).

Twenty-seven of the 28 isolates positive for sul1 also harbored qacEΔ1. Although association of qac genes with phenotypic antiseptic resistance is currently under debate, co-carriage of qacEΔ1 with sul1 within the 3'-conserved sequences of many class 1 integrons is often linked to the presence of other resistance genes, presumptively as gene cassettes within the integrons [40]. The presence of intI1 –indicative of a class 1 integron—was confirmed in all qacEΔ1+/sul1+ isolates. IntI1 was detected in 20 additional strains by PCR, indicating the absence of a full 3'-conserved sequence amongst almost half of the integrons detected here (S2 Table). Carriage of class 1 integrons with alternative structures has previously been documented within Kenya, albeit at lower rates [39]. Similarly, co-carriage of dfrA1, aadA1/A2, and sat2 is often associated with the presence of class 2 integrons. PCR amplification of intI2 confirmed the presence of class 2 integrons in the three isolates harboring all three genes.


With improvements in metagenomic sequencing and other methods to characterize intestinal microbiota, a number of recent studies have documented intestinal colonization with klebsiellae as a source of extra-intestinal infections [4] and an initial stage in many nosocomial infections [6,41]. Pertinent to the current study, intestinal klebsiellae and other Enterobacteriaceae may serve as reservoirs of AMR determinants, increasing the potential for highly resistant disease [10,12,42]. Here we have assessed a collection of 90 Klebsiella spp. intestinal isolates as a model for the accumulation and evolution of resistance assemblages within the gut of Kenyan individuals.

Our data suggest that there is some selective pressure for the establishment and maintenance of bacterial populations resistant to multiple antimicrobial compounds within this region. The high proportion of isolates that were classified as MDR (36.7%), in a sample population not selected for resistance underscores this point, although some bias may have resulted from recent antibiotic use by the participants (no participant medical histories were available for most samples). Specific to Kenya, widespread use of tetracycline in livestock production [43], use of SXT and chloramphenicol as first line therapeutics for typhoid [2,44], and prophylactic use of SXT in persons exposed to or infected with HIV [45] may have contributed to the high prevalence of resistance to these compounds. These results are in line with other studies in East Africa showing similar rates of resistance and carriage of AMR genes [46,47,48]. On the other hand, while ciprofloxacin and third generation cephalosporins are widely distributed in Kenya [49,50,51,52], their high costs limit their use [53,54,55,56]. Thus, it was not surprising that only a small percentage of the tested population was resistant to fluoroquinolones or third/fourth generation cephalosporins, with a correspondingly low number of isolates positive for genes conferring resistance to these compounds. Similarly, carbapenem resistance was observed in only three isolates, and none of the 15 carbapenemase genes on the ARDM v.2 were identified here, including those detected in previous studies of the region where higher carbapenem resistance was observed (e.g., blaOXA-48, blaVIM, blaNDM, blaIMP, blaKPC) [57,58,59]. Differences in the current dataset and those of other studies in East Africa may simply reflect the particular species studied (e.g., E. coli, Klebsiella spp.), age and medical histories of participants, or the sample sources (e.g., urine, blood, stool). Alternatively, our results may suggest that availability and use of carbapenems are lower in Kenya than elsewhere in the region [60].

A large number of K. pneumoniae strains hybridized to the mac(A) and mac(B) probes derived from E. coli genes, although isolates carrying variants from both species were also identified (S2 Table). Interestingly, the presence of E. coli-derived mac(A)/mac(B) genes was also correlated with the presence of sequences hybridizing to an E. coli-derived cmr gene (P <0.0001), which is only ~80% identical to the Klebsiella spp. homolog. BLAST searches of the E. coli-derived mac(AB) sequences indicated that these sequences have not previously been documented in any klebsiellae.

The breadth of genes on the microarray allowed us to detect multiple classes of resistance determinants, which may suggest the presence of integrons and/or plasmids associated with AMR. Strain MHK02590, isolated at Mbagathi District Hospital in Nairobi, was resistant to all tested antimicrobials except carbapenems and harbored 21 resistance determinants. Interestingly, Kariuki and colleagues [61] recently isolated an IncHI2 plasmid, pKST313, from a Kenyan Salmonella typhimurium carrying 11 of these determinants. While we did not attempt to confirm the presence of pKST313 in strain MHK02590, isolation of this strain within the Nairobi metropolitan area where pKST313 was first identified suggests that this plasmid may be circulating within this urban setting.

This study had several limitations. As with any molecular method, genotype is not always fully predictive of phenotype. Though statistically valid genotypic/phenotypic correlations could be made for many genes in this study, a disconnect was observed between the presence of several β-lactamase and dihydrofolate reductase genes and the predicted resistance profiles. These discrepancies could be due to poor gene expression, non-functionality of the expressed gene products, or the presence of other genes or mechanisms not addressed. On the other hand, we were unable to identify the molecular mechanisms for carbapenem or fluoroquinolone non-susceptibility observed in a number of samples. While carbapenem resistance was likely due to the presence of a carbapenemase gene not currently included in the ARDM chip content, fluoroquinolone resistance is likely due to mutations in DNA gyrase and topoisomerase genes, gyrA and parC [62,63]. The ARDM cannot detect these mutations. In such an instance, a more comprehensive technique such as whole genome sequencing (WGS) might provide the needed information. An additional advantage of WGS is the ability to discriminate closely related alleles and identification of changes in regulatory sequences affecting gene expression. However, WGS may also miss the presence of important genes or point mutations if coverage is insufficient or error rates are too high [64]. Nonetheless, molecular approaches such as microarray hybridization and WGS can assist in tracking the epidemiological development and spread of AMR, a benefit not realized through phenotypic testing.

Despite these limitations, we identified a high prevalence of MDR amongst a collection of Kenyan Klebsiella spp. stool isolates not specifically selected for their resistance characteristics. In most cases, phenotypic resistance was highly correlated to the presence of appropriate AMR determinants. While our results suggest that selective pressure exists for carriage of genes conferring resistance to tetracyclines, phenicols, trimethoprim, and sulfonamides, resistance to fluoroquinolones, third- and fourth-generation cephalosporins, and carbapenems was observed in only a small number of isolates, likely commensurate with regional usage. The wide variety of resistance determinants detected, the large number of isolates harboring five or more of these genes (65.5%) and the high prevalence of MDR phenotype (36.7%) underscore the need for more effective, targeted public health policies and infection control/prevention measures than those likely implemented in the population tested. Timely public health intervention to new and emerging sources of resistance are always important–and unfortunately often not available—in developing countries where access to second- and third-line antimicrobials may be limited.

Supporting information

S1 Table. PCR primers used for confirmation of specific AMR and integrase genes.


S2 Table. Comparison of resistance genes detected thru microarray hybridization and by PCR.



Some authors are employed by the US Government and this work was prepared as part of their official duties. Title 17, US code, section 105 provides that ‘Copyright protection under this title is not available for any work of the US Government’ as defined as ‘prepared by a military service member or employee of the US Government as part of that person’s official duties.’

“This work is presented with the permission of the Director, KEMRI. The work presented here represents the opinions of the authors and should not be seen to represent the policy of the Kenya Medical Research Institute, US Army Medical Research Directorate–Kenya, Walter Reed Army Institute of Research, US Department of the Army, US Navy, or the US Department of Defense.”

Author Contributions

  1. Conceptualization: CRT TAL CH GJV.
  2. Data curation: CRT TAL DPE EAO JLW PBP CH GJV.
  3. Formal analysis: CRT TAL PBP CH.
  4. Funding acquisition: DPE JLW PBP GJV.
  5. Investigation: CRT TAL DPE EAO NCK JNN RKK ANO CH.
  6. Methodology: CRT TAL DPE CH GJV.
  7. Project administration: CRT TAL DPE EAO JLW PBP CH GJV.
  9. Supervision: CRT DPE JLW PBP CH GJV.
  10. Validation: CRT TAL DPE CH.
  11. Visualization: CRT.
  12. Writing – original draft: CRT TAL PBP CH GJV.
  13. Writing – review & editing: CRT TAL DPE EAO NCK JNN RKK ANO JLW PBP CH GJV.


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