David Liao

Acceleration of Emergence of Bacterial Antibiotic Resistance in Connected Microenvironments

Gradients of antibiotics generated in a microfluidic device provoke selection of ciprofloxacin resistance in Escherichia coli. The emergence of bacterial antibiotic resistance is a growing problem, yet the variables that influence the rate of emergence of resistance are not well understood. In a microfluidic device designed to mimic naturally occurring bacterial niches, resistance of Escherichia coli to the antibiotic ciprofloxacin developed within 10 hours. Resistance emerged with as few as 100 bacteria in the initial inoculation. Whole-genome sequencing of the resistant organisms revealed that four functional single-nucleotide polymorphisms attained fixation. Knowledge about the rapid emergence of antibiotic resistance in the heterogeneous conditions within the mammalian body may be helpful in understanding the emergence of drug resistance during cancer chemotherapy.

An analogy between the evolution of drug resistance in bacterial communities and malignant tissues.

Cancer cells rapidly evolve drug resistance through somatic evolution and, in order to continue growth in the metastatic phase, violate the organism-wide consensus of regulated growth and beneficial communal interactions. We suggest that there is a fundamental mechanistic connection between the rapid evolution of resistance to chemotherapy in cellular communities within malignant tissues and the rapid evolution of antibiotic resistance in bacterial communities. We propose that this evolution is the result of a programmed and collective stress response performed by interacting cells, and that, given this fundamental connection, studying bacterial communities can provide deeper insights into the dynamics of adaptation and the evolution of cells within tumours.

Computation of mutual fitness by competing bacteria

Competing populations in shared spaces with nonrenewable resources do not necessarily wage a battle for dominance at the cost of extinction of the less-fit strain if there are fitness advantages to the presence of the other strain. We report on the use of nanofabricated habitat landscapes to study the population dynamics of competing wild type and a growth advantage in stationary phase (GASP) mutant strains of Escherichia coli in a sealed and heterogeneous nutrient environment. Although GASP mutants are competitors with wild-type bacteria, we find that the 2 strains cooperate to maximize fitness (long-term total productivity) via spatial segregation: despite their very close genomic kinship, wild-type populations associate with wild-type populations and GASP populations with GASP populations. Thus, wild-type and GASP strains avoid each other locally, yet fitness is enhanced for both strains globally. This computation of fitness enhancement emerges from the local interaction among cells but maximizes global densities. At present we do not understand how fluctuations in both spatial and temporal dimensions lead to the emergent computation and how multilevel aggregates produce this collective adaptation.

A microfluidic device for continuous cancer cell culture and passage with hydrodynamic forces

We demonstrate a novel and robust microfluidic chip with combined functions of continuous culture and output of PC-3 prostate cancer cells. With digital controls, polydimethylsiloxane (PDMS) flexible diaphragms are able to apply hydrodynamic shear forces on cultures, detaching a fraction of attached cancer cells from the surface for output while leaving others for reuse in subsequent cultures. The fractions of detached cells and remaining cells can be precisely controlled. The system has not only the advantages of small size, high cell culture efficiency, and digital control, but also of simple fabrication at low cost, easy operation and robust performance. The chip performs 9 passages during 30 days of continuous culture and shows promise as a durable design suitable for long-term cell output.

Game theory in the death galaxy: interaction of cancer and stromal cells in tumour microenvironment.

Preventing relapse is the major challenge to effective therapy in cancer. Within the tumour, stromal (ST) cells play an important role in cancer progression and the emergence of drug resistance. During cancer treatment, the fitness of cancer cells can be enhanced by ST cells because their molecular signalling interaction delays the drug-induced apoptosis of cancer cells. On the other hand, competition among cancer and ST cells for space or resources should not be ignored. We explore the population dynamics of multiple myeloma (MM) versus bone marrow ST cells by using an experimental microecology that we call the death galaxy, with a stable drug gradient and connected microhabitats. Evolutionary game theory is a quantitative way to capture the frequency-dependent nature of interactive populations. Therefore, we use evolutionary game theory to model the populations in the death galaxy with the gradients of pay-offs and successfully predict the future densities of MM and ST cells. We discuss the possible clinical use of such analysis for predicting cancer progression.

Single molecule correlation spectroscopy in continuous flow mixers with zero-mode waveguides

Zero-Mode Waveguides were first introduced for Fluorescence Correlation Spectroscopy at micromolar dye concentrations. We show that combining zero-mode waveguides with fluorescence correlation spectroscopy in a continuous flow mixer avoids the compression of the FCS signal due to fluid transport at channel velocities up to approximately 17 mm/s. We derive an analytic scaling relationship [equation: see text] converting this flow velocity insensitivity to improved kinetic rate certainty in time-resolved mixing experiments. Thus zero-mode waveguides make FCS suitable for direct kinetics measurements in rapid continuous flow.

Physics of cancer propagation: A game theory perspective

This is a theoretical paper which examines at a game theoretical perspective the dynamics of cooperators and cheater cells under metabolic stress conditions and high spatial heterogeneity. Although the ultimate aim of this work is to understand the dynamics of cancer tumor evolution under stress, we use a simple bacterial model to gain fundamental insights into the progression of resistance to drugs under high competition and stress conditions.

The Goldilocks Principle and Antibiotic Resistance in Bacteria

We have designed and fabricated a microecology to mimic a naturally occurring bacterial culture, which includes the stress gradient, metapopulation, and cellular motility. In this microecology, we show that it is possible to fix the resistance to the mutagenic antibiotic Ciprofloxacin in wild-type Escherichia coli within 10 h. We found the evolution of resistance is further accelerated in microecology if bacteria have already acquired the phenotype of growth advantage at the stationary phase (GASP).

Anomalous Spatial Redistribution of Competing Bacteria under Starvation Conditions

Bacterial cells evolved under prolonged stress often have a growth advantage in stationary phase (GASP); we expect GASP cells to maintain a proliferative state and dominate wild-type cells during starvation, especially when nutrients are limited and the medium has been conditioned. However, when we compete GASP mutants against wild-type cells in a chain of microfluidic microhabitat patches (MHPs) with alternating nutrient-rich and nutrient-limited regions, we observe the reverse effect: wild-type cells achieve maximum relative density under nutrient-limited conditions, while GASP cells dominate nutrient-rich regions. We explain this surprising observation in terms of ideal free distributions, where we show that wild-type cells maximize their fitness at high cell density by redistributing themselves to sparsely populated MHPs. At the microscopic level, we describe how biofilm formation also contributes to the population redistribution. We conclude by discussing the implications of these results for social interactions of more complex organisms.

Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.