Additivity of inhibitory effects in multidrug combinations

December 1, 2018

In each of these experiments, an inoculum of 104 cells was inoculated into 150 μl of media in a Nunc 96-well flat-bottom microplate. Antibiotics were added into the wells as indicated using a D300e digital dispenser (Tecan), which dispenses a nanolitre-scale volume of each antibiotic. Each concentration combination was performed in duplicate wells. Multiple untreated control wells (no antibiotics) were designated on each plate (2–6% of the wells in each experiment). To avoid systematic positional effects across the plates, the wells chosen for each drug combination on the plates were randomized. The plates were incubated at 30 °C with shaking (Liconic orbital shaker STX44), and OD600 nm was measured at least every 25 min using a Tecan robotic system and the Infinite M200 Pro reader. To enhance uniformity, the plate orientations in the shaker were rotated 180° following every measurement

From natural ecology1-4 to clinical therapy5-8, cells are often exposed to mixtures of multiple drugs. Two competing null models are used to predict the combined effect of drugs: response additivity (Bliss) and dosage additivity (Loewe)9-11. Here, noting that these models diverge with increased number of drugs, we contrast their predictions with growth measurements of four phylogenetically distant microorganisms including Escherichia coli, Staphylococcus aureus, Enterococcus faecalis and Saccharomyces cerevisiae, under combinations of up to ten different drugs. In all species, as the number of drugs increases, Bliss maintains accuracy while Loewe systematically loses its predictive power. The total dosage required for growth inhibition, which Loewe predicts should be fixed, steadily increases with the number of drugs, following a square-root scaling. This scaling is explained by an approximation to Bliss where, inspired by R. A. Fisher's classical geometric model12, dosages of independent drugs add up as orthogonal vectors rather than linearly. This dose-orthogonality approximation provides results similar to Bliss, yet uses the dosage language as in Loewe and is hence easier to implement and intuit. The rejection of dosage additivity in favour of effect additivity and dosage orthogonality provides a framework for understanding how multiple drugs and stressors add up in nature and the clinic.

Russ, D; Kishony, R;

Journal: Nat Microbiol Pages: 1339-1345

Original article (30323252)