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Background: We investigated the feasibility of rapid disc diffusion antibiotic susceptibility testing (rAST) with reading of inhibition zones after 6 and/or 8 h of incubation for Enterococcus faecalis, Enterococcus faecium, Pseudomonas aeruginosa and Acinetobacter baumannii. In addition, we evaluated discrimination of resistant populations from the WT populations at early timepoints and the requirement for clinical breakpoint adaptations for proper interpretation of rAST data.Methods: In total, 815 clinical strains [E. faecalis (n = 135), E. faecium (n = 227), P. aeruginosa (n = 295) and A. baumannii (n = 158)] were included in this study. Disc diffusion plates were streaked, incubated and imaged using the WASPLabTM automation system. WT populations and non-WT populations were defined using epidemiological cut-offs.Results and conclusions: rAST at 6 and 8 h was possible for A. baumannii and enterococci with readability of inhibition zones >90%. Overall categorical agreement of rAST at 6 h with AST at 18 h was 97.2%, 97.4% and 95.3% for E. faecalis, E. faecium and A. baumannii, respectively. With few exceptions, major categorization error rates were <1% for A. baumannii, and vancomycin-resistant E. faecium were clearly separated from the WT at 6 h. For P. aeruginosa the average readability of inhibition zones was 68.9% at 8 h and we found an overall categorical agreement of 94.8%. Adaptations of clinical breakpoints and/or introduction of technical buffer zones, preferably based on aggregated population data from various epidemiological settings, are required for proper interpretation of rAST. [ABSTRACT FROM AUTHOR]

Background: Antibiotic resistance poses a significant threat to patients suffering from infectious diseases. Early readings of antibiotic susceptibility test (AST) results could be of critical importance to ensure adequate treatment. Disc diffusion is a well-standardized, established and cost-efficient AST procedure; however, its use in the clinical laboratory is hampered by the many manual steps involved, and an incubation time of 16-18 h, which is required to achieve reliable test results.Methods: We have evaluated a fully automated system for its potential for early reading of disc diffusion diameters after 6-12 h of incubation. We assessed availability of results, methodological precision, categorical agreement and interpretation errors as compared with an 18 h standard. In total, 1028 clinical strains (291 Escherichia coli , 272 Klebsiella pneumoniae , 176 Staphylococcus aureus and 289 Staphylococcus epidermidis ) were included in this study. Disc diffusion plates were streaked, incubated and imaged using the WASPLab TM automation system.Results and conclusions: Our results demonstrate that: (i) early AST reading is possible for important pathogens; (ii) methodological precision is not hampered at early timepoints; and (iii) species-specific reading times must be selected. As inhibition zone diameters change over time and are phenotype/drug combination dependent, specific cut-offs and expert rules will be essential to ensure reliable interpretation and reporting of early susceptibility testing results. [ABSTRACT FROM AUTHOR]

We have recently developed a scalable algorithm for ordering the instantaneous observations of a dynamical system evolving continuously in time. Here, we apply the method to long molecular dynamics trajectories. The procedure requires only a pairwise, geometrical distance as input. Suitable annotations of both structural and kinetic nature reveal the free energy basins visited by biomolecules. The profile is supplemented by a trace of the temporal evolution of the system highlighting the sequence of events. We demonstrate that the resultant SAPPHIRE (States And Pathways Projected with HIgh REsolution) plots provide a comprehensive picture of the thermodynamics and kinetics of complex, molecular systems exhibiting dynamics covering a range of time and length scales. Information on pathways connecting states and the level of recurrence are quickly inferred from the visualisation. The considerable advantages of our approach are speed and resolution: the SAPPHIRE plot is scalable to very large data sets and represents every single snapshot. This minimizes the risk of missing states because of overlap or prior coarse-graining of the data. [ABSTRACT FROM AUTHOR]

Whole-genome sequencing allows rapid detection of drug-resistant Mycobacterium tuberculosis isolates. However, the availability of high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been limited. We determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from the Democratic Republic of the Congo, Ivory Coast, Peru, Thailand, and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD Bactec MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared DST results with predicted drug resistance profiles inferred by whole-genome sequencing. Classification of strains by the two phenotypic DST methods into resistotype/wild-type populations was concordant in 73 to 99% of cases, depending on the drug. Our data suggest that the established critical concentration (5 mg/liter) for ethambutol resistance (MGIT 960 system) is too high and misclassifies strains as susceptible, unlike 7H10 agar dilution. Increased minimal inhibitory concentrations were explained by mutations identified by whole-genome sequencing. Using whole-genome sequences, we were able to predict quantitative drug resistance levels for the majority of drug resistance mutations. Predicting quantitative levels of drug resistance by whole-genome sequencing was partially limited due to incompletely understood drug resistance mechanisms. The overall sensitivity and specificity of whole-genome-based DST were 86.8% and 94.5%, respectively. Despite some limitations, whole-genome sequencing has the potential to infer resistance profiles without the need for time-consuming phenotypic methods., (Copyright © 2019 Gygli et al.)

Data mining techniques depend strongly on how the data are represented and how distance between samples is measured. High-dimensional data often contain a large number of irrelevant dimensions (features) for a given query. These features act as noise and obfuscate relevant information. Unsupervised approaches to mine such data require distance measures that can account for feature relevance. Molecular dynamics simulations produce high-dimensional data sets describing molecules observed in time. Here, we propose to globally or locally weight simulation features based on effective rates. This emphasizes, in a data-driven manner, slow degrees of freedom that often report on the metastable states sampled by the molecular system. We couple this idea to several unsupervised learning protocols. Our approach unmasks slow side chain dynamics within the native state of a miniprotein and reveals additional metastable conformations of a protein. The approach can be combined with most algorithms for clustering or dimensionality reduction.

We have captured the binding of a peptide to a PDZ domain by unbiased molecular dynamics simulations. Analysis of the trajectories reveals on-pathway encounter complex formation, which is driven by electrostatic interactions between negatively charged carboxylate groups in the peptide and positively charged side chains surrounding the binding site. In contrast, the final stereospecific complex, which matches the crystal structure, features completely different interactions, namely the burial of the hydrophobic side chain of the peptide C-terminal residue and backbone hydrogen bonds. The simulations show that nonnative salt bridges stabilize kinetically the encounter complex during binding. Unbinding follows the inverse sequence of events with the same nonnative salt bridges in the encounter complex. Thus, in contrast to protein folding, which is driven by native interactions, the binding of charged peptides can be steered by nonnative interactions, which might be a general mechanism, e.g., in the recognition of histone tails by bromodomains., (Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.)