Detection and enumeration of Legionella in water samples is of great importance for risk assessment analysis. The plate culture method is the gold standard, but has received several well-known criticisms, which have induced researchers to develop alternative methods. The purpose of this study was to compare Legionella counts obtained by the analysis of potable water samples through the plate culture method and through the IDEXX liquid culture Legiolert method. Legionella plate culture, according to ISO 11731:1998, was performed using 1 L of water. Legiolert was performed using both the 10 mL and 100 mL Legiolert protocols. Overall, 123 potable water samples were analyzed. Thirty-seven (30%) of them, positive for L. pneumophila, serogroups 1 or 2–14 by plate culture, were used for comparison with the Legiolert results. The Legiolert 10 mL test detected 34 positive samples (27.6%) and the Legiolert 100 mL test detected 37 positive samples, 27.6% and 30% respectively, out of the total samples analyzed. No significant difference was found between either the Legiolert 10 mL and Legiolert 100 mL vs. the plate culture (p = 0.9 and p = 0.3, respectively) or between the Legiolert 10 mL and Legiolert 100 mL tests (p = 0.83). This study confirms the reliability of the IDEXX Legiolert test for Legionella pneumophila detection and enumeration, as already shown in similar studies. Like the plate culture method, the Legiolert assay is also suitable for obtaining isolates for typing purposes, relevant for epidemiological investigations.

Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity towards other antibiotics, offers novel treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here we address this issue in the Gram-positive pathogen S. pneumoniae by quantifying collateral and fitness effects of a series of clinically relevant first-step (gyrA or parC) mutations, and their combinations, that confer resistance to fluoroquinolones. We integrated these results in a mathematical model which allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC mutations; however, the spectrum of collateral effects was unique for each mutation or mutation pair. This indicated that mutation identity, even different mutations to the same amino acid, can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. In addition, we observed that epistatic effects between gyrA and parC mutations strongly alter the strength of collateral effects against different antibiotics. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic specific pharmacodynamics, revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that the gene, mutational identity, and interactions between resistance mutations can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies.

Significance A promising strategy to overcome the evolution of antibiotic-resistant bacteria is to use collateral sensitivity-informed antibiotic treatments that rely on cycling or mixing of antibiotics, such that that resistance toward one antibiotic confers increased sensitivity to the other. Here, focusing on multistep fluoroquinolone resistance in Streptococcus pneumoniae , we show that antibiotic resistance induces diverse collateral responses whose magnitude and direction are determined by allelic identity. Using mathematical simulations, we show that these effects can be exploited via combination treatment regimens to suppress the de novo emergence of resistance during treatment.