Dehydration Tolerance in Epidemic versus Nonepidemic MRSA Demonstrated by Isothermal Microcalorimetry

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) clusters are considered epidemic or nonepidemic based on their ability to spread effectively. Successful transmission could be influenced by dehydration tolerance. Current methods for determination of dehydration tolerance lack accuracy. Here, a climate-controlled in vitro dehydration assay using isothermal microcalorimetry (IMC) was developed and linked with mathematical modeling to determine survival of 44 epidemic versus 54 nonepidemic MRSA strains from France, the United Kingdom, and the Netherlands after 1 week of dehydration. For each MRSA strain, the growth parameters time to end of first growth phase (tmax [h]) and maximal exponential growth rate (μ_m) were deduced from IMC data for 3 experimental replicates, 3 different starting inocula, and before and after dehydration. If the maximal exponential growth rate was within predefined margins (±36% of the mean), a linear relationship between tmax and starting inoculum could be utilized to predict log reduction after dehydration for individual strains. With these criteria, 1,330 of 1,764 heat flow curves (data sets) (75%) could be analyzed to calculate the post-dehydration inoculum size, and thus the log reduction due to dehydration, for 90 of 98 strains (92%). Overall reduction was ~1 log after 1 week. No difference in dehydration tolerance was found between the epidemic and nonepidemic strains. Log reduction was negatively correlated with starting inoculum, indicating better survival of higher inocula. This study presents a framework to quantify bacterial survival. MRSA strains showed great capacity to persist in the environment, irrespective of epidemiological success. This finding strengthens the need for effective surface cleaning to contain MRSA transmission. IMPORTANCE Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of infections globally. While some MRSA clusters have spread worldwide, others are not able to disseminate successfully beyond certain regions despite frequent introduction. Dehydration tolerance facilitates transmission in hospital environments through enhanced survival on surfaces and fomites, potentially explaining differences in transmission success between MRSA clusters. Unfortunately, the currently available techniques to determine dehydration tolerance of cluster-forming bacteria like S. aureus are labor-intensive and unreliable due to their dependence on quantitative culturing. In this study, bacterial survival was assessed in a newly developed assay using isothermal microcalorimetry. With this technique, the effect of drying can be determined without the disadvantages of quantitative culturing. In combination with a newly developed mathematical algorithm, we determined dehydration tolerance of a large number of MRSA strains in a systematic, unbiased, and robust manner.

Keywords: Staphylococcus aureus; desiccation; environmental survival; epidemiological success; transmission.

FIG 1

Validation of IMC for Staphylococcus aureus growth characterization. Growth curves were deduced from heat flow data (panel A: raw data; panel B: cumulated over time) and optical density data (panel C: differentiated between time steps; panel D: raw data) (example strain SA2704). The correlation between tmax from heat flow or optical density (OD) and inoculum size for strains SA2704, SAMUP15a, M116, and SAC042W was 0.97, 0.96, 0.96 and 0.95, respectively (based on 3 independent experiments, P < 0.001). Panel E: Linear relationship between inoculum and tmax for different starting inocula for 8 pilot methicillin-susceptible (MSSA) and methicillin-resistant S. aureus (MRSA) strains (see Supplemental data analysis section A for underlying data). Data are from 3 independent experiments.

FIG 2

Heat flow profiles. Typically, S. aureus heat flow curves are characterized by a bell-like shape (examples in panels A and B). In 31 strains, multiple data sets with multiple heat flow peaks were observed (examples in panel C and D).

FIG 3

Mean log reduction results. Mean log reduction by (A) inoculum; (B) inoculum and success (color); (C) inoculum, success (color), and lineage (panel); and (D) inoculum, country (color), and lineage (panel). Bars indicate means with standard deviation error bars.

FIG 4

Schematic overview of all steps in data analysis. In the first step, smoothed cubic splines were fitted to the data and key growth parameters were extracted from the first growth phase of all data sets (e.g., tmax and maximal exponential growth rate, shown here in red). For step 2, data sets with ≤36% variability in maximal exponential growth rate were included for further analysis. In step 3, a linear model was fitted to tmax data prior to dehydration and the inoculum surviving dehydration was predicted based on the tmax after dehydration.