Effective drug combination for Caenorhabditis elegans nematodes discovered by output-driven feedback system control technique

TL;DR

This paper introduces a model-less feedback system control method to discover potent drug combinations against C. elegans, potentially overcoming multidrug resistance in parasitic nematodes.

Contribution

It presents a novel output-driven feedback control approach that optimizes drug combinations without prior biological or pharmacological knowledge.

Findings

Identified drug combinations more effective than individual drugs.

Achieved high efficacy at sub-EC50 drug concentrations.

Demonstrated applicability to other small model organisms.

Abstract

Infections from parasitic nematodes (or roundworms) contribute to a significant disease burden and productivity losses for humans and livestock. The limited number of anthelmintics (or antinematode drugs) available today to treat these infections are rapidly losing their efficacy as multidrug resistance in parasites becomes a global health challenge. We propose an engineering approach to discover an anthelmintic drug combination that is more potent at killing wild-type Caenorhabditis elegans worms than four individual drugs. In the experiment, freely swimming single worms are enclosed in microfluidic drug environments to assess the centroid velocity and track curvature of worm movements. After analyzing the behavioral data in every iteration, the feedback system control (FSC) scheme is used to predict new drug combinations to test. Through a differential evolutionary search, the winning drug combination is reached that produces minimal centroid velocity and high track curvature, while requiring each drug in less than their EC50 concentrations. The FSC approach is model-less and does not need any information on the drug pharmacology, signaling pathways, or animal biology. Toward combating multidrug resistance, the method presented here is applicable to the discovery of new potent combinations of available anthelmintics on C. elegans, parasitic nematodes, and other small model organisms.