Simultaneous Identification and Susceptibility Determination to Multiple Antibiotics of <i>Staphylococcus aureus</i> by Bacteriophage Amplification Detection Combined with Mass Spectrometry

The continued advance of antibiotic resistance in clinically relevant bacterial strains necessitates the development and refinement of assays that can rapidly and cost-effectively identify bacteria and determine their susceptibility to a panel of antibiotics. A methodology is described herein that exploits the specificity and physiology of the Staphylococci bacteriophage K to identify <i>Staphylococcus aureus</i> (<i>S. aureus</i>) and determine its susceptibility to clindamycin and cefoxitin. The method uses liquid chromatography–mass spectrometry to monitor the replication of bacteriophage after it is used to infect samples thought to contain <i>S. aureus</i>. Amplification of bacteriophage K indicates the sample contains <i>S. aureus</i>, for it is only in the presence of a suitable host that bacteriophage K can amplify. If bacteriophage amplification is detected in samples containing the antibiotics clindamycin or cefoxitin, the sample is deemed to be resistant to these antibiotics, respectively, for bacteriophage can only amplify in a viable host. Thus, with a single work flow, <i>S. aureus</i> can be detected in an unknown sample and susceptibility to clindamycin and cefoxitin can be ascertained. This Article discusses implications for the use of bacteriophage amplification in the clinical laboratory

Comparative analysis of NSPs from <i>E</i>. <i>granulosus</i> PSCs after the induction of strobilar development.

<p>(A) Functional categories of total identified NSPs. Percentages of identified proteins in each functional category are indicated. (O) Post-translational modification, protein turnover, and chaperones; (C) Energy production and conversion; (Z) Cytoskeleton; (U) Intracellular trafficking, secretion, and vesicular transport; (S) Function unknown; (K) Transcription; (J) Translation, ribosomal structure and biogenesis; (A) RNA processing and modification; (F) Nucleotide transport and metabolism; (E) Amino acid transport and metabolism; (T) Signal transduction mechanisms; (D) Cell cycle control, cell division, chromosome partitioning; (G) Carbohydrate transport and metabolism; (Q) Secondary metabolites biosynthesis, transport, and catabolism; (L) Replication, recombination and repair; (P) Inorganic ion transport and metabolism; (M) Cell wall/membrane/envelope biogenesis. The distribution of level 3 biological processes for SSD and NSD-exclusive and up-regulated proteins. (B) A heat map from NSPs with high (red) or low (green) expression levels between the SSD and NSD groups.</p

<i>In toto</i> visualization of proteins synthesized by <i>E</i>. <i>granulosus</i> PSCs induced to strobilar development.

<p>(A) NSPs were specifically visualized in the presence of AHA and Alexa Fluor 488 Alkyne. The other images represent the DAPI nuclei staining, the bright field merges of DAPI and Alexa Fluor 488 antibody staining and the bright field images. (B) AHA+/Alexa-, (C) AHA-/Alexa+ and (D) AHA-/Alexa- did not show significant fluorescence or autofluorescence (400x). (E) The quantification of NSP (Alexa Fluor 488) and nucleic acid regions (DAPI) fluorescence. a.u., arbitrary units.</p

Proteins identified in <i>E</i>. <i>granulosus</i> PSCs after the induction of strobilar development.

<p>Venn diagram showing the identified proteins in the AHA and control samples. (A) Exclusive proteins identified in SSD and CSD. (B) Differentially expressed proteins.</p

Optimization of the linear quantification range of an online trypsin digestion coupled liquid chromatography–tandem mass spectrometry (LC–MS/MS) platform

<p>Tandem mass spectrometry (MS/MS)-based proteomic workflows with a bottom-up approach require enzymatic digestion of proteins to peptide analytes, usually by trypsin. Online coupling of trypsin digestion of proteins, using an immobilized enzyme reactor (IMER), with liquid chromatography (LC) and MS/MS is becoming a frequently used approach. However, finding IMER digestion conditions that allow quantitative analysis of multiple proteins with wide range of endogenous concentration requires optimization of multiple interactive parameters: digestion buffer flow rate, injection volume, sample dilution, and surfactant type/concentration. In this report, we present a design of experiment approach for the optimization of an integrated IMER-LC–MS/MS platform. With bovine serum albumin as a model protein, the digestion efficacy and digestion rate were monitored based on LC–MS/MS peak area count versus protein concentration regression. The optimal parameters were determined through multivariate surface response modeling and consideration of diffusion controlled immobilized enzyme kinetics. The results may provide guidance to other users for the development of quantitative IMER-LC–MS/MS methods for other proteins.</p

Differentially expressed proteins.

<p>The proteins that were identified as exclusive in at least two replicates or the proteins that were differentially expressed with significant T-Test values (<i>p</i>≤0.05) are presented.</p><p>^aFunctional classification determined by eggNOG.</p><p>^<i>b</i>Protein accession numbers according to GeneDB (<a href="http://www.genedb.org/" target="_blank">www.genedb.org/</a>).</p><p>^<i>c</i>Protein accession numbers according to NCBI (<a href="http://www.ncbi.nlm.nih.gov/" target="_blank">www.ncbi.nlm.nih.gov/</a>).</p><p>^dAverage NSAF for SSD replicates.</p><p>^eAverage NSAF for NSD replicates.</p><p>Differentially expressed proteins.</p

Detection of NSPs from <i>in vitro</i> cultured <i>E</i>. <i>granulosus</i> PSCs.

<p>The coomassie-stained proteins and UV detected TAMRA-labeled NSPs from the PSCs incubated for 72 h in the presence (A and B) or absence (C and D) of AHA, respectively.</p

Debridement significantly increases mouse survival from subcutaneous <i>B. anthracis</i> infection.

<p>(A) Black and white photos of a single A/J mouse infected with 1×10⁵ BIG23 spores in the left ear overlaid with false-color representation of photon emission intensity as indicated by the scale on the right in p/s/cm-2/sr. At 12 hours post injection luminescent infected tissue (left photo- before) was removed (debrided) to eliminate all bacterial luminescence (right photo- after). (B to D) BIG23 spores were injected subcutaneously into the left ear of 4–12 week old A/J mice. Control mice either had their left ear unperturbed (control) or non infected tissue on the same ear was removed (cut control). Mice were then monitored for infection and dissemination using in vivo bioluminescent imaging. Mice were monitored for a total of ten days post-infection (p.i.), until luminescence was detected in a major organ, or mouse appeared moribund (indicating imminent death). (B) Mice were inoculated with 1×10⁵ spores of BIG23. Luminescent tissue was debrided at 12 hours p.i. Survival data from a total of seven mice from three independent experiments were analyzed with the log rank test to determine significant differences in survival between debrided and control mice (*, p = 0.0108), and debrided and cut control mice (**, p = 0.0021). There was no statistical difference between control and cut control mice. (C) Mice were inoculated with 1×10⁶ spores of BIG23. Luminescent tissue was debrided at 12 hours p.i. Survival data was analyzed with the log rank test on a total of ten debrided mice and seven mice each for the control groups from three independent experiments to determine significant differences in survival between debrided and control mice (*, p = 0.0109) and debrided and cut control mice (**, p = 0.0026). There was no statistical difference between control and cut control mice. (D) Mice were infected with BIG23 as described above, but debridement of luminescent tissue was performed at 24, 48, or 78 hour p.i. Survival data was analyzed with the log rank test on a total of seven mice from each experimental group, with the exception of the control mice that totaled six, from three independent experiments to determine significant differences from control mice. The survival of mice debrided at 24 hours (*, p = 0.0110) and 48 hours (*, p = 0.0477) p.i. was significantly increased. The survival of mice debrided at 72 hours p.i. was not significantly different than control mice (p = 0.1734).</p

Quantification of Botulinum Neurotoxin Serotypes A and B from Serum Using Mass Spectrometry

Botulinum neurotoxins (BoNT) are the deadliest agents known. Previously, we reported an endopeptidase activity based method (Endopep-MS) that detects and differentiates BoNT serotypes A–G. This method uses serotype specific monoclonal antibodies and the specific enzymatic activity of BoNT against peptide substrates which mimic the toxin’s natural target. Cleavage products from the reaction are detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. We have now developed a multiple reaction monitoring method to quantify the biological activity of BoNT serotypes A (BoNT/A) and B (BoNT/B) present in 0.5 mL of serum using electrospray mass spectrometry. The limit of quantification for each serotype is 1 mouse intraperitoneal lethal dose (MIPLD₅₀) corresponding to 31 pg of BoNT/A and 15 pg of BoNT/B in this study. This method was applied to serum from rhesus macaques with inhalational botulism following exposure to BoNT/B, showing a maximum activity of 6.0 MIPLD₅₀/mL in surviving animals and 653.6 MIPLD₅₀/mL in animals that died in the study. The method detects BoNT/B in serum 2–5 h after exposure and up to 14 days. This is the first report of a quantitative method with sufficient sensitivity, selectivity, and low sample size requirements to measure circulating BoNT activity at multiple times during the course of botulism

Presence of lethal factor in cervical draining lymph node does not alter cellular activation.

<p>Mice were infected with 1×10⁶ Sterne strain or TKO spores subcutaneously in the left ear. At 24 hours cLN were taken from mice including: Sterne infected mice (solid line non-shaded) along with control non-infected contralateral lymph nodes from Sterne infected mice (solid line shaded), and TKO infected (dashed line non-shaded) and control non-infected contralateral lymph nodes from TKO infected mice (dashed line shaded). cLN were homogenized and cells were stained for flow cytometry. Flow plots were gated for single event live CD45 positive cells. (A) Left- a representative histogram comparing expression of CD69 in draining cLN. Right- The mean fluorescence intensity of lymph nodes draining either Sterne (*, p = 0.0464) or TKO (*, p = 0.0256) infections from seven mice was significantly higher than contralateral control lymph nodes as determined using Student's T test. (B) Left- a representative histogram comparing expression of CD86 in draining cLN. Right- The mean fluorescence intensity of lymph nodes draining either Sterne (*, p = 0.0119) or TKO (**, p = 0.0063) infections from seven mice was significantly higher than contralateral control lymph nodes as determined using Student's T test. (C) A representative comparison of CD80 expression in draining cLN. The mean fluorescence intensity of lymph nodes draining either Sterne or TKO infections from seven mice was not significantly higher than lymph nodes that were not.</p