A high throughput microfluidic platform for size-selective enrichment of cell populations in tissue and blood samples.

Numerous applications in biology and medicine require the efficient and reliable separation of cells for disease diagnosis, genetic analysis, drug screening, and therapeutics. In this work, we demonstrate a novel technology that integrates a passive and an active device to separate, enrich and release cells on-demand from a complex blood sample, or cancer cells derived from a tissue biopsy. We exploit the high throughput (>1 mL min-1), size-based sorting capability of the passive spiral inertial microfluidic (iMF) device to focus particles/cells towards an active lateral cavity acoustic transducer (LCAT) device for size-selective enrichment. We demonstrate that this platform is capable of efficiently (>90%) removing smaller cells, such as RBCs in a blood sample or smaller cancer cells in a heterogeneous cell line, and providing 44 000× enrichment from the remaining sample within 5 min of device operation. Finally, we use this platform for two applications: selective enrichment of the side-population of DU-145 cells from tissue biopsy and isolation of larger monocytes from blood. Our platform integrates the high throughput (processing rate) capacity of spiral iMF with the high selectivity of LCAT, thereby offering a unique route for highly-selective, label-free particle/cell sorting, with potential application in lab-on-chip platforms for liquid biopsy and diagnostics applications.

Multiscale Modeling of Bistability in the Yeast Polarity Circuit.

Cell polarity refers to the asymmetric distribution of proteins and other molecules along a specified axis within a cell. Polarity establishment is the first step in many cellular processes. For example, directed growth or migration requires the formation of a cell front and back. In many cases, polarity occurs in the absence of spatial cues. That is, the cell undergoes symmetry breaking. Understanding the molecular mechanisms that allow cells to break symmetry and polarize requires computational models that span multiple spatial and temporal scales. Here, we apply a multiscale modeling approach to examine the polarity circuit of yeast. In addition to symmetry breaking, experiments revealed two key features of the yeast polarity circuit: bistability and rapid dismantling of the polarity site following a loss of signal. We used modeling based on ordinary differential equations (ODEs) to investigate mechanisms that generate these behaviors. Our analysis revealed that a model involving positive and negative feedback acting on different time scales captured both features. We then extend our ODE model into a coarse-grained reaction-diffusion equation (RDE) model to capture the spatial profiles of polarity factors. After establishing that the coarse-grained RDE model qualitatively captures key features of the polarity circuit, we expand it to more accurately capture the biochemical reactions involved in the system. We convert the expanded model to a particle-based model that resolves individual molecules and captures fluctuations that arise from the stochastic nature of biochemical reactions. Our models assume that negative regulation results from negative feedback. However, experimental observations do not rule out the possibility that negative regulation occurs through an incoherent feedforward loop. Therefore, we conclude by using our RDE model to suggest how negative feedback might be distinguished from incoherent feedforward regulation.

Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories.

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.

Sustaining yield and nutritional quality of peanuts in harsh environments: Physiological and molecular basis of drought and heat stress tolerance.

Climate change is significantly impacting agricultural production worldwide. Peanuts provide food and nutritional security to millions of people across the globe because of its high nutritive values. Drought and heat stress alone or in combination cause substantial yield losses to peanut production. The stress, in addition, adversely impact nutritional quality. Peanuts exposed to drought stress at reproductive stage are prone to aflatoxin contamination, which imposes a restriction on use of peanuts as health food and also adversely impact peanut trade. A comprehensive understanding of the impact of drought and heat stress at physiological and molecular levels may accelerate the development of stress tolerant productive peanut cultivars adapted to a given production system. Significant progress has been achieved towards the characterization of germplasm for drought and heat stress tolerance, unlocking the physiological and molecular basis of stress tolerance, identifying significant marker-trait associations as well major QTLs and candidate genes associated with drought tolerance, which after validation may be deployed to initiate marker-assisted breeding for abiotic stress adaptation in peanut. The proof of concept about the use of transgenic technology to add value to peanuts has been demonstrated. Advances in phenomics and artificial intelligence to accelerate the timely and cost-effective collection of phenotyping data in large germplasm/breeding populations have also been discussed. Greater focus is needed to accelerate research on heat stress tolerance in peanut. A suits of technological innovations are now available in the breeders toolbox to enhance productivity and nutritional quality of peanuts in harsh environments. A holistic breeding approach that considers drought and heat-tolerant traits to simultaneously address both stresses could be a successful strategy to produce climate-resilient peanut genotypes with improved nutritional quality.

Autophagy as a Mechanism for Adaptive Prediction-Mediated Emergence of Drug Resistance.

Drug resistance is a major problem in treatment of microbial infections and cancers. There is growing evidence that a transient drug tolerant state may precede and potentiate the emergence of drug resistance. Therefore, understanding the mechanisms leading to tolerance is critical for combating drug resistance and for the development of effective therapeutic strategy. Through laboratory evolution of yeast, we recently demonstrated that adaptive prediction (AP), a strategy employed by organisms to anticipate and prepare for a future stressful environment, can emerge within 100 generations by linking the response triggered by a neutral cue (caffeine) to a mechanism of protection against a lethal agent (5-fluoroorotic acid, 5-FOA). Here, we demonstrate that mutations selected across multiple laboratory-evolved lines had linked the neutral cue response to core genes of autophagy. Across these evolved lines, conditional activation of autophagy through AP conferred tolerance, and potentiated subsequent selection of mutations in genes specific to overcoming the toxicity of 5-FOA. These results offer a new perspective on how extensive genome-wide genetic interactions of autophagy could have facilitated the emergence of AP over short evolutionary timescales to potentiate selection of 5-FOA resistance-conferring mutations.

Bistability in the polarity circuit of yeast.

Cells polarize their growth or movement in many different physiological contexts. A key driver of polarity is the Rho GTPase Cdc42, which when activated becomes clustered or concentrated at polar sites. Multiple models for polarity establishment have been proposed. All of them rely on positive feedback to reinforce regions of high Cdc42 activity. Positive feedback can lead to bistability, a scenario in which cells can exist in either a polarized or unpolarized state under identical external conditions. Determining if the signaling circuit that drives Cdc42 polarity is bistable would provide important information about the mechanism that underlies polarity establishment and insights into the design features required for proper cellular function. We studied polarity establishment during the mating response of yeast. Using microfluidics to precisely control the temporal profile of mating pheromone and live-cell imaging to monitor the polarity process in single living cells, we found that the polarity circuit of yeast shows hysteresis, a characteristic feature of bistable systems. Our analysis also revealed that cells exposed to high pheromone concentrations rapidly lose polarity following a precipitous removal of pheromone. We used a reaction-diffusion model for polarity establishment to demonstrate that delayed negative regulation is sufficient to explain our experimental results. [Media: see text] [Media: see text] [Media: see text] [Media: see text].

Dean Flow Dynamics in Low-Aspect Ratio Spiral Microchannels.

A wide range of microfluidic cell-sorting devices has emerged in recent years, based on both passive and active methods of separation. Curvilinear channel geometries are often used in these systems due to presence of secondary flows, which can provide high throughput and sorting efficiency. Most of these devices are designed on the assumption of two counter rotating Dean vortices present in the curved rectangular channels and existing in the state of steady rotation and amplitude. In this work, we investigate these secondary flows in low aspect ratio spiral rectangular microchannels and define their development with respect to the channel aspect ratio and Dean number. This work is the first to experimentally and numerically investigate Dean flows in microchannels for Re > 100, and show presence of secondary Dean vortices beyond a critical Dean number. We further demonstrate the impact of these multiple vortices on particle and cell focusing. Ultimately, this work offers new insights into secondary flow instabilities for low-aspect ratio, spiral microchannels, with improved flow models for design of more precise and efficient microfluidic devices for applications such as cell sorting and micromixing.

Continuous separation of blood cells in spiral microfluidic devices.

Blood cell sorting is critical to sample preparation for both clinical diagnosis and therapeutic research. The spiral inertial microfluidic devices can achieve label-free, continuous separation of cell mixtures with high throughput and efficiency. The devices utilize hydrodynamic forces acting on cells within laminar flow, coupled with rotational Dean drag due to curvilinear microchannel geometry. Here, we report on optimized Archimedean spiral devices to achieve cell separation in less than 8 cm of downstream focusing length. These improved devices are small in size (<1 in.(2)), exhibit high separation efficiency (∼95%), and high throughput with rates up to 1 × 10(6) cells per minute. These device concepts offer a path towards possible development of a lab-on-chip for point-of-care blood analysis with high efficiency, low cost, and reduced analysis time.