Publications by authors named "Robert H Austin"

We use a microfluidic ecology which generates non-uniform phage concentration gradients and micro-ecological niches to reveal the importance of time, spatial population structure and collective population dynamics in the de evolution of T4r bacteriophage resistant motile . An insensitive bacterial population against T4r phage occurs within 20 hours in small interconnected population niches created by a gradient of phage virions, driven by evolution in transient biofilm patches. Sequencing of the resistant bacteria reveals mutations at the receptor site of bacteriophage T4r as expected but also in genes associated with biofilm formation and surface adhesion, supporting the hypothesis that evolution within transient biofilms drives phage resistance.

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  • Cancer cell survival and growth are influenced by somatic evolution, which selects specific cell traits in response to changing environments.
  • Researchers analyzed lung adenocarcinomas with varied genetic mutations (n=313) and discovered a limited number (376) of mutations under positive selection linked to significant changes in gene expression.
  • Key pathways important for cancer cell fitness involve loss of normal tissue functions, with specific genes related to cell cycle, DNA repair, and metabolism showing significant conservation and increased expression in tumors.
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Chemoresistance is a major cause of treatment failure in many cancers. However, the life cycle of cancer cells as they respond to and survive environmental and therapeutic stress is understudied. In this study, we utilized a microfluidic device to induce the development of doxorubicin-resistant (DOXR) cells from triple negative breast cancer (TNBC) cells within 11 days by generating gradients of DOX and medium.

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  • Evolvability refers to a population's ability to generate heritable variations that are relevant for natural selection, influencing individual adaptations and overall fitness.
  • The study models how different species with varying evolvability compete under different environmental conditions, revealing that faster-evolving species do better far from equilibrium, while slower-evolving species succeed when near equilibrium.
  • Environmental changes impact species survival, with frequent minor changes leading to the extinction of smaller populations, yet allowing for coexistence in diverse ecological niches, particularly favoring slower-evolving species.
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  • The polyaneuploid cancer cell (PACC) state helps cancer cells survive extreme conditions and spread more effectively, leading to increased lethality.
  • Recent findings indicate that cancer cells that recover from treatment show resistance to various therapies, which may result from a phenomenon called PACC memory, where cells quickly return to a resistant state.
  • This paper builds on mathematical models to explore the effects of innate resistance and PACC memory on cancer cell dynamics, suggesting that both factors play significant roles in resistance and survival in cancer populations.
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The evolution of antibiotic resistance is a fundamental problem in disease management but is rarely quantified on a single-cell level owing to challenges associated with capturing the spatial and temporal variation across a population. To evaluate cell biological phenotypic responses, we tracked the single-cell dynamics of filamentous bacteria through time in response to ciprofloxacin antibiotic stress. We measured the degree of phenotypic variation in nucleoid length and the accumulation of protein damage under ciprofloxacin antibiotic and quantified the impact on bacterial survival.

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Most definitions of cancer broadly conform to the current NCI definition: "Cancer is a disease in which some of the body's cells grow uncontrollably and spread to other parts of the body." These definitions tend to describe what cancer "looks like" or "does" but do not describe what cancer "is" or "has become." While reflecting past insights, current definitions have not kept pace with the understanding that the cancer cell is itself transformed and evolving.

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The emergence of chemotherapy resistance drives cancer lethality in cancer patients, with treatment initially reducing overall tumor burden followed by resistant recurrent disease. While molecular mechanisms underlying resistance phenotypes have been explored, less is known about the cell biological characteristics of cancer cells that survive to eventually seed the recurrence. To identify the unique phenotypic characteristics associated with survival upon chemotherapy exposure, we characterized nuclear morphology and function as prostate cancer cells recovered following cisplatin treatment.

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In this didactic paper, we present a theoretical modeling framework, called the G-function, that integrates both the ecology and evolution of cancer to understand oncogenesis. The G-function has been used in evolutionary ecology, but has not been widely applied to problems in cancer. Here, we build the G-function framework from fundamental Darwinian principles and discuss how cancer can be seen through the lens of ecology, evolution, and game theory.

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Time-reversal symmetry breaking and entropy production are universal features of nonequilibrium phenomena. Despite its importance in the physics of active and living systems, the entropy production of systems with many degrees of freedom has remained of little practical significance because the high dimensionality of their state space makes it difficult to measure. Here we introduce a local measure of entropy production and a numerical protocol to estimate it.

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  • Therapeutic resistance in cancer is largely due to a specific state called the polyaneuploid cancer cell (PACC) state, which helps cancer cells evade treatment and adapt to stress.
  • The PACC state arises from aneuploid cancer cells that undergo processes like whole genome doubling, allowing them to survive harsh conditions and develop adaptability by increasing their genomic content.
  • By using a mathematical model and simulations, the research suggests that targeting the PACC state with timed therapies could potentially eliminate these resilient cancer cells and prevent the development of resistance, improving treatment outcomes.
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  • Recent research indicates that the polyaneuploid cancer cell (PACC) state helps cancer cells adapt to stress and resist treatment by pausing division and avoiding damage.
  • Transitioning to this state enhances the cells' ability to evolve over time, allowing them to develop resistance through mutations or self-modification.
  • A simulation model was created to explore how treatment dosage affects these evolutionary paths, finding that lower doses favor evolutionary triage while higher doses promote self-genetic modification.
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Experimental robobiological physics can bring insights into biological evolution. We present a development of hybrid analog/digital autonomous robots with mutable diploid dominant/recessive 6-byte genomes. The robots are capable of death, rebirth, and breeding.

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Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors.

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We reinvestigate a simple model used in the literature concerning the thermodynamic analysis of protein cold denaturation. We derive an exact thermodynamic expression for cold denaturation and give a better approximation than exists in the literature for predicting cold denaturation temperatures in the two-state model. We discuss the "dark-side" implications of this work for previous temperature-dependent protein dynamics experiments and discuss microfluidic experimental technologies, which could explore the thermal stability range of proteins below the bulk freezing point of water.

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We present an ecology-inspired form of active matter consisting of a robot swarm. Each robot moves over a planar dynamic resource environment represented by a large light-emitting diode array in search of maximum light intensity; the robots deplete (dim) locally by their presence the local light intensity and seek maximum light intensity. Their movement is directed along the steepest local light intensity gradient; we call this emergent symmetry breaking motion "field drive.

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We describe a deterministic lateral displacement (DLD) for particle separation with only a single column of bumping features. The bifurcation of fluid streams at obstacles is not set by the "tilt" of columns with respect to macroscopic current flow, but rather by the fluidic resistances for lateral flow at each obstacle. With one column of 14 bumping features and corresponding inlet/outlet channels, the single-column DLD can separate particles with diameters of 4.

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The advent of microfluidics in the 1990s promised a revolution in multiple industries from healthcare to chemical processing. Deterministic lateral displacement (DLD) is a continuous-flow microfluidic particle separation method discovered in 2004 that has been applied successfully and widely to the separation of blood cells, yeast, spores, bacteria, viruses, DNA, droplets, and more. Deterministic lateral displacement is conceptually simple and can deliver consistent performance over a wide range of flow rates and particle concentrations.

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The heterogenous, highly metabolic stressed, poorly irrigated, solid tumor microenvironment - the tumor swamp - is widely recognized to play an important role in cancer progression as well as the development of therapeutic resistance. It is thus important to create realistic in vitro models within the therapeutic pipeline that can recapitulate the fundamental stress features of the tumor swamp. Here we describe a microfluidic system which generates a chemical gradient within connected microenvironments achieved through a static diffusion mechanism rather than active pumping.

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Conventional cell culture remains the most frequently used preclinical model, despite its proven limited ability to predict clinical results in cancer. Microfluidic cancer-on-chip models have been proposed to bridge the gap between the oversimplified conventional 2D cultures and more complicated animal models, which have limited ability to produce reliable and reproducible quantitative results. Here, we present a microfluidic cancer-on-chip model that reproduces key components of a complex tumor microenvironment in a comprehensive manner, yet is simple enough to provide robust quantitative descriptions of cancer dynamics.

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Cancer led to the deaths of more than 9 million people worldwide in 2018, and most of these deaths were due to metastatic tumor burden. While in most cases, we still do not know why cancer is lethal, we know that a total tumor burden of 1 kg-equivalent to one trillion cells-is not compatible with life. While localized disease is curable through surgical removal or radiation, once cancer has spread, it is largely incurable.

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Antibiotics can induce mutations that cause antibiotic resistance. Yet, despite their importance, mechanisms of antibiotic-promoted mutagenesis remain elusive. We report that the fluoroquinolone antibiotic ciprofloxacin (cipro) induces mutations by triggering transient differentiation of a mutant-generating cell subpopulation, using reactive oxygen species (ROS).

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The ability of a population of PC3 prostate epithelial cancer cells to become resistant to docetaxel therapy and progress to a mesenchymal state remains a fundamental problem. The progression towards resistance is difficult to directly study in heterogeneous ecological environments such as tumors. In this work, we use a micro-fabricated "evolution accelerator" environment to create a complex heterogeneous yet controllable in-vitro environment with a spatially-varying drug concentration.

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Bacteria under external stress can reveal unexpected emergent phenotypes. We show that the intensely studied bacterium can transform into long, highly motile helical filaments poized at a torsional buckling criticality when exposed to minimum inhibitory concentrations of several antibiotics. While the highly motile helices are physically either right- or left-handed, the motile helices always rotate with a right-handed angular velocity [Formula: see text], which points in the same direction as the translational velocity [Formula: see text] of the helix.

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