Effect of Linker Length on Cell Capture by Poly(ethylene glycol)-Immobilized Antimicrobial Peptides

Development of antimicrobial peptide (AMP)-functionalized materials has renewed interest in using poly­(ethylene glycol) (PEG)-mediated linking to minimize unwanted interactions while engendering the peptides with sufficient flexibility and freedom of movement to interact with the targeted cell types. While PEG-based linkers have been used in many AMP-based materials, the role of the tether length has been minimally explored. Here, we assess the impact of varying the length of PEG-based linkers on the binding of bacterial cells by surface-immobilized AMPs. While higher surface densities of immobilized AMPs were observed using shorter PEG linkers, the increased density was insufficient to fully account for the increased binding activity of peptides. Furthermore, effects were specific to both the peptide and cell type tested. These results suggest that simple alterations in linking strategiessuch as changing tether lengthmay result in large differences in the surface properties of the immobilized AMPs that are not easily predictable

Molecular Characterization of Multidrug Resistant Hospital Isolates Using the Antimicrobial Resistance Determinant Microarray

<div><p>Molecular methods that enable the detection of antimicrobial resistance determinants are critical surveillance tools that are necessary to aid in curbing the spread of antibiotic resistance. In this study, we describe the use of the Antimicrobial Resistance Determinant Microarray (ARDM) that targets 239 unique genes that confer resistance to 12 classes of antimicrobial compounds, quaternary amines and streptothricin for the determination of multidrug resistance (MDR) gene profiles. Fourteen reference MDR strains, which either were genome, sequenced or possessed well characterized drug resistance profiles were used to optimize detection algorithms and threshold criteria to ensure the microarray's effectiveness for unbiased characterization of antimicrobial resistance determinants in MDR strains. The subsequent testing of <i>Acinetobacter baumannii</i>, <i>Escherichia coli</i> and <i>Klebsiella pneumoniae</i> hospital isolates revealed the presence of several antibiotic resistance genes [e.g. belonging to TEM, SHV, OXA and CTX-M classes (and OXA and CTX-M subfamilies) of β-lactamases] and their assemblages which were confirmed by PCR and DNA sequence analysis. When combined with results from the reference strains, ∼25% of the ARDM content was confirmed as effective for representing allelic content from both Gram-positive and –negative species. Taken together, the ARDM identified MDR assemblages containing six to 18 unique resistance genes in each strain tested, demonstrating its utility as a powerful tool for molecular epidemiological investigations of antimicrobial resistance in clinically relevant bacterial pathogens.</p></div

ARDM content allocations for genes conferring resistance to different classes of antimicrobial compounds.

<p>Two hundred thirty-nine different resistance determinants are represented by probes on each sub-array.</p

ARDM v.1, PCR and phenotypic β-lactamase/ESBL profiles of the clinical and reference strains used in this study.

<p>N/A – not available. R – resistant, I – intermediate, S – sensitive.</p>a<p>The identified family to which the CTX-M allele belongs is indicated in parentheses.</p>b<p>While no official ATM resistance criteria for <i>A. baumannii</i> are available, all isolates of this species designated as resistant (R) in the above table showed no zone of inhibition around ATM disks.</p>c<p>Weakly positive detection by PCR.</p

ARDM analysis of reference strains.

a<p>ARDM-positive genes that have been validated by sequencing or PCR for strains whose genomes have not been fully sequenced are shown in bold.</p

Electrochemical signals from MDR reference strain, <i>A. baumannii</i> BAA-1710 (A) and antibiotic sensitive reference strain, <i>A. baumannii</i> 17978 (B).

<p>Each data point represents one probe; data are sorted according to alleles represented by each probe. In each panel, the horizontal dotted line indicates the “probe threshold” used to determine whether probes were considered positive (mean of lowest 95% probes+3 SD). For panel A, peaks correspond to the following alleles: <b><i>a</i></b>: <i>tet(G)</i> [9/9 probes positive]; <b><i>b</i></b>: <i>cat4</i> [5/7 probes positive]; <b><i>c</i></b>: <i>dfrA1</i> [9/9 probes positive]; <b><i>d</i></b>: <i>catA1</i> [6/8 probes positive]; <b><i>e</i></b>: <i>arr-3</i> [8/8 probes positive]; <b><i>f</i></b><i>: aph6/str(B)</i> [8/10 probes positive], <i>aph3″/str(A)</i> [10/10 probes positive], <i>aadA1b</i> [10/10 probes positive], <i>aadB</i> [10/10 probes positive]; <b><i>g</i></b>: <i>qacEΔ1</i> [10/10 probes positive]; <b><i>h</i></b>: <i>aadA2</i> [2/9 probes positive - allele deemed negative], <i>aadA1</i> [7/7 probes positive]; <b><i>i</i></b>: <i>bla</i>_VEB [9/9 probes positive]; <b><i>j</i></b>: <i>bla</i>_OXA-10 [7/7 probes positive]; <b><i>k</i></b>: <i>dfrA10</i> [8/10 probes positive]; <b><i>l</i></b>: <i>bla</i>_PSE-1/CARB [2/10 probes positive – allele deemed negative]; <b><i>m</i></b>: <i>aacC1</i> [9/9 probes positive], <i>aphA1</i> [10/10 probes positive]; <b><i>n</i></b>: <i>ant(2′)-Ia</i> [10/10 probes positive]; <b><i>o</i></b>: <i>sulI</i> [10/10 probes positive]; <b><i>p</i></b>: <i>tet(A)</i> [9/9 probes positive]. For panel B, the <i>sulII</i> allele (peak indicated) was deemed positive with 7/7 probes positive; other alleles had one or two positive probes, but were deemed negative.</p

Clinical isolates from Egyptian hospitals.

a<p>Clinical sites from which the isolates were obtained. CUH – Cairo University Hospital, Cairo, Egypt; AFH – Abbasia Fever Hospital, Cairo, Egypt; ASU – Assiut Fever Hospital, Assiut, Egypt; SAH – Shebeen Al Kom Hospital, Shebeen Al Kom, Egypt; ALX – Alexandria Fever Hospital, Alexandria, Egypt; TBRI – Theodor Bilharz Research Institute, Cairo, Egypt.</p>b<p>This ESBL strain containing <i>bla</i>_CTX-M-15 has been previously described under the designation of E450 (35).</p

Genetic MDR profiles from clinical isolates, excluding ESBLs.

a<p>Abbreviations: TET – tetracyclines; CHLOR – chloramphenicol; QAC – quaternary ammonium compounds; SUL – sulfonamides; TRI – trimethoprim; FQ - fluoroquinolones.</p>b<p>Genes responsible for resistance to β-lactams, which are not included in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0069507#pone-0069507-t003" target="_blank">Table 3</a>.</p>c<p>Based on results obtained with the reference strains and PCR validation (data not shown) and may reflect false positives and/or truncated genes.</p

Summary of AMR genes in the tested population.

<p>Summary of AMR genes in the tested population.</p

Antimicrobial resistance of <i>Klebsiella pneumoniae</i> stool isolates circulating in Kenya

<div><p>We sought to determine the genetic and phenotypic antimicrobial resistance (AMR) profiles of commensal <i>Klebsiella</i> spp. circulating in Kenya by testing human stool isolates of 87 <i>K</i>. <i>pneumoniae</i> and three <i>K</i>. <i>oxytoca</i> 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 (<i>ampC</i>/<i>bla</i>_DHA, <i>bla</i>_CMY/LAT, <i>bla</i>_LEN-1, <i>bla</i>_OKP-A/OKP-B1, <i>bla</i>_OXA-1-like family, <i>bla</i>_OXY-1, <i>bla</i>_SHV, <i>bla</i>_TEM, <i>bla</i>_CTX-M-1 and <i>bla</i>_CTX-M-2 families), aminoglycosides (<i>aac(3)-III</i>, <i>aac(6)-Ib</i>, <i>aad</i>(A1/A2), <i>aad</i>(A4), <i>aph</i>(AI), <i>aph3/str</i>(A), <i>aph6/str</i>(B), and <i>rmtB</i>), macrolides (<i>mac</i>(A), <i>mac</i>(B), <i>mph</i>(A)<i>/mph</i>(K)), tetracyclines (<i>tet</i>(A), <i>tet</i>(B), <i>tet</i>(D), <i>tet</i>(G)), ansamycins (<i>arr</i>), phenicols (<i>catA1/cat4</i>, <i>floR</i>, <i>cmlA</i>, <i>cmr</i>), fluoroquinolones (<i>qnrS</i>), quaternary amines (<i>qacE</i>Δ<i>1</i>), streptothricin (<i>sat2</i>), sulfonamides (<i>sul1</i>, <i>sul2</i>, <i>sul3</i>), and diaminopyrimidines (<i>dfrA1</i>, <i>dfrA5</i>, <i>dfrA7</i>, <i>dfrA8</i>, <i>dfrA12</i>, <i>dfrA13/21/22/23</i> family, <i>dfrA14</i>, <i>dfrA15</i>, <i>dfrA16</i>, <i>dfrA17</i>). 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.</p></div