Siva A. Vanapalli - US grants

0932796/0933090
Vanapalli/Wong

The notion of using tiny nanoliter-scale water droplets in an oil phase as reaction vessels for applications in chemical and life sciences is turning into a reality due to rapid progress in the science and engineering of microfluidics. Despite such progress, fundamental challenges remain to transform current droplet-based devices to next generation fluidic processors capable of characterizing large-scale biological complexity. Two scientific challenges exist in the realization of such an integrated two-phase fluidic processor. First, the transport of a large number of confined droplets in microchannels leads to prohibitively excess pressure drop. Second, due to collective hydrodynamic resistive effects, it is difficult to control the position and timing of droplets for reactions on a device. To address these challenges requires a thorough understanding of hydrodynamic resistance introduced by the motion of confined droplets. The PIs will combine experiments and modeling to quantify the hydrodynamic resistance due to a confined droplet and its dependence on system parameters. Novel aspects of the work include the use of a sensitive microfluidic comparator technique to measure hydrodynamic resistance at the level of individual droplets. Experimental methods and models will be developed to quantify the currently unknown contribution of end-cap, thin film and corner flows to the hydrodynamic resistance of a droplet in rectangular microchannels, with the ultimate goal of achieving predictive capability of pressure drop for enhanced device performance. This study will enable rational design of two-phase fluidic processors that could be potentially autonomous and passively driven. This work will also impact other engineering areas that rely on fundamental understanding of multiphase flows in confined media such as tertiary oil recovery and fuel cells. Educational component of the project includes drawing minority graduate and undergraduate students to the visually striking research on microfluidics and providing state-of-the-art training in microfluidics, microfabrication, microscopy and numerical modeling. The PIs will pursue outreach activities at their respective institutions such as developing a weeklong hands-on-activities and lectures on the theme "Bubbles on Chips".

0967172
Vanapalli

In applications such as foods and consumer products, emulsions are often employed because of their remarkable ability to form a wide variety of materials ranging from low-viscosity fluids, to gels to highly elastic pastes. In some of these applications emulsions containing crystallizable oils are tempered and sheared to form bicontinuous gels by exploiting a phenomenon known as partial coalescence. Unlike coalescence in liquid droplets, partial coalescence occurs when the interfacial crystals of semi-crystalline droplets penetrate neighboring droplets. The mechanical strength of the crystalline network linking the droplets is capable of overcoming the Laplace pressure and maintains the integrity of the non-spherical aggregates. Despite prior investigations, partial coalescence remains a poorly understood convolution of two non-equilibrium and stochastic phenomena - nucleation and aggregation in emulsions. Emerging technologies such as topical drugs and phase change materials also rely on partial coalescence. Thus, fundamental understanding of partial coalescence in oil-in-water emulsions would broadly impact the technological development in these applications. Currently partial coalescence has confounded scientific understanding because of polydispersity in emulsions, shear and additives such as surfactants - all of which affect both the nucleation rates and the probability of partial coalescence. In addition, current methods such as X-ray diffraction and differential scanning calorimetry are top-down approaches and are inadequate to probe the stochastic nature of nucleation and partial coalescence at the level of individual droplets. To address these scientific challenges, the investigators deploy microfluidic technology and direct visualization methods to (1) Quantify nucleation kinetics in exceptionally monodisperse droplets and test the validity of current nucleation theories (2) Directly measure the kinetics of partial coalescence and test the applicability of kinetic theories of aggregation and (3) Directly quantify the probability of shear-induced coalescence in crystalline droplets.

The intellectual merit of this work is an integrated experimental effort combining microfluidics and microscopy to address a technological need to fundamentally understand nucleation and partial coalescence in emulsions. Novel aspects of the work include routing droplet traffic in a microfluidic network to control individual droplet parking in well-defined spots on a microfluidic device. Generating such large-scale single droplet arrays enables repeated crystallization-melting cycles to be performed to quantify the heterogeneity in the dynamics of nucleation. In addition, by manipulating the parking space available for droplets, the investigators will generate microfluidic doublets and hexagonally-packed monodisperse droplet arrays for direct visualization of the microscopic dynamics of partial coalescence. To probe shear-induced coalescence, we will generate two microfluidic trains of droplets and induce repeated head-on collisions between individual droplets. The ability to create such large statistical ensembles and perform measurements at the level of individual droplets is essential to discriminate the various mechanisms causing nucleation and will yield a never-before-available picture of the stochastic nature of nucleation and partial coalescence. Thus, this potentially transformative research moves beyond current top-down methods by introducing bottom-up approaches to investigate the non-equilibrium thermodynamics of nucleation and partial coalescence in emulsions.

This fundamental investigation of crystallization and partial coalescence in emulsions will broadly impact the technology and engineering in areas as diverse as foods, cosmetics, drug delivery and phase change materials. Furthermore, this study may catalyze the development of an entirely new class of droplet-based fluidic devices for rapid assessment of crystallization and emulsion stability. This work will also impact other engineering areas that rely on fundamental understanding of emulsion crystallization and stability such as oil recovery. The educational component of the project includes drawing graduate and undergraduate students to the visually striking microfluidics research and providing state-of-the-art training in microfluidics, emulsion science, non-equilibrium thermodynamics and microscopy. The PI will pursue outreach activities to high school students by developing a weeklong hands-on-activities and lectures on the theme "Bubbles on Chips"

Currently, microfluidic devices can produce millions of nanoliter-scale droplets allowing high throughput biological analysis. Given the multi-step nature of biological analysis, these droplets often need to be shuttled through a network of fluidic channels so that they can be merged with other reagent-loaded droplets, then sorted and eventually analyzed. Realizing this vision of an ultrafast fluidic bioprocessor in the laboratory is quite a daunting task because non-linearity in the motion of droplets through interconnected networks precludes full control over the position and timing of each and every droplet. The principal hypothesis of this work is that computational thinking approaches can lead to a paradigm shift in precision engineering of error-free fluidic processors by narrowing down the design space and yielding optimized solutions of network architecture. Preliminary data supports this hypothesis, motivating us to implement computational strategies to address this design challenge. First, predictive models of the basic fluidic components of a processor will be built. Second, predictive control strategies will be used to address the relative significance of passive approaches vis-à-vis active methods to regulate droplet trajectories in fluidic networks. Finally, specialized genetic algorithms (GAs) will be developed to optimize network architecture for desired processor functionality. Additional cyber aspects of the proposal include generation and analysis of tremendous amount of digital microscopy data capturing the non-linear dynamics of droplets in networks and efficient knowledge generation from this abundant data using the best available computational infrastructure. Thus, the proposed work cuts across several disciplines including control theory, systems engineering, computational science, non-linear dynamics, fluid mechanics, microfabrication and image processing.

The results from this study will not only advance scientific and engineering frontiers in a variety of disciplines but will also lead to transformative impact in applications related to biological analysis, material synthesis, biosensing and disease diagnostics. The computational tools being developed in this work can be adapted to analyze complex networks in natural systems including microcirculation and transportation systems. Educational component of the project includes drawing graduate and undergraduate students to the visually striking microfluidics research and providing state-of-the-art training in interdisciplinary areas - yielding a workforce that is uniquely trained. In addition to disseminating the results through conference presentations and publications, the digital movies generated during the project will be stored on dedicated network servers for access to other users to eventually build a digital library of fluidic processor architectures.

1150836
PI: Vanapalli

Current high-throughput screening (HTS) methods use robotic actuators for dispensing and diluting fluids in microliter-scale multi-well plates. This approach requires significant investment and imposes constraints on reducing the fluid volumes due to evaporation. Microfluidic arrays of immobilized drops could emerge as an inexpensive and powerful alternative to multi-well plate screening. However, the technical challenge in generating these static drop arrays (SDAs) is to develop a means to (i) array drops of tunable volume and (ii) vary the reagent concentration from drop to drop in the array. Despite recent progress, current microfluidic devices are incapable of manipulating individual drop concentration and varying the volume in the static array. The field is ripe for breakthroughs and if the challenge is met the benefits are enormous ? low cost; reduced fluid volumes; capability to monitor many reactions in drops simultaneously; and ability to further manipulate drops as the position is indexed in the array.

To address this challenge, the PI proposes to investigate the dynamics of trains of confined drops and/or long plugs in a special class of fluidic networks called microfluidic parking networks (MPNs). MPNs typically consist of a repeated sequence of loops, with each loop containing a fluidic trap to park (i.e. immobilize) drops. Preliminary exploration in just a small region of the control parameter space yielded a series of unanticipated and astonishing behaviors driven by collective hydrodynamic resistive interactions in the network. Sub-classes of collective behavior involving drop parking, break-up, and coalescence led to the generation of SDAs with tuneable volumes as well as with variation in reagent concentration from drop-to-drop. To harness the full potential and autonomous control offered by the preliminary observations, the PI proposes a comprehensive investigation of the collective hydrodynamics of drops in MPNs, than is currently available. The investigation will focus on (i) coordinated experimental and modeling efforts to predict the spatiotemporal dynamics of drops in MPNs that drive many of the collective behaviors we observed. New tools involving drop-on-demand generators will be integrated into MPNs, to vary the control parameters to map the full phase space of collective dynamics (ii) providing a complete picture of drop/plug break-up in MPNs, by characterizing the fragmentation dynamics to control the size of drop relative to trap. This data when combined with a novel strategy to measure pressure variations during break-up will enable rigorous confrontation of existing models of drop break-up at bifurcations; and (iii) controlling the coalescence and material exchange between parked and moving drops, by probing the factors that regulate film drainage, and passive tracer transport and mixing when drops fuse.

The proposed fundamental investigations will enable the development of inexpensive SDAs with sophisticated capabilities. This work is poised to deliver a true nanoliter-scale analog of the multi-well plate with the enormous simplification that dilutions and mixing are carried out passively, thus solving a long-standing challenge. Replacing a room full of robots with these penny-sized devices will tremendously benefit HTS methods in biology and material science. The CAREER project will also provide interdisciplinary training for students in the cutting-edge areas of microfluidics, multiphase flows, microfabrication and nonlinear dynamics. Graphic modules of droplet traffic and parking will be developed for active learning, where students will design their own network topologies and conduct original analysis. These modules will be integrated into an elective course on microfluidics and the core courses. Outreach activities will be developed for middle school girls on the theme "Bubbles on Chips" in which students will mold devices containing a street map of Lubbock and study bubble traffic to identify the exits that bubbles choose.

The proposed innovation uses microfluidic technology to rapidly generate fluid mixtures of drugs with fine increments in their proportions to assist with combination drug development. Although automated pipetting systems and well plates have been the workhorse for primary drug screening where thousands of individual compounds are tested, few, if any, are flexible for screening combination drugs because of the complexity involved in scanning a large number of drug-and-dose combinations. This technology involves injecting plugs of drug solutions into a uniquely designed microfluidic device that allows autonomous mixing and dilution. This approach allows mixing drugs in very fine increments with significantly less consumption of drug samples and reagents.

Development of a microfluidic drop technology for combination drug discovery may accelerate the process of drug screening and discovery of new or combination drugs. It would help to reduce the drug development time cycle and cost as it facilitates fluid mixtures of drugs in very small increments. Outside of the pharmaceutical industry, this technology could also play a role in combinational mixing of consumer products and biomaterials.

This PFI: AIR Technology Translation project focuses on translating a discovery, which involves storing hundreds of nanoliter-scale droplets in a microfluidic device with unprecedented capabilities to control the chemical composition of individual drops. This microfluidic dose response analyzer will deliver significant societal benefit by transforming the way preclinical drug discovery is conducted in the pharmaceutical industry. It will guide decision-making early on in the drug discovery process helping to reduce drug development cycle time and cost. The project will result in a prototype with defined design criteria and performance parameters, as well as validation data on cell-based assays. This technology uses significantly less sample and reagent volumes, eliminates pipetting errors and allows automated reagent delivery and washing. These features will lead to significant cost savings, high-resolution data and simpler workflows compared to multiwell plates and pipetting systems that occupy the current market space.

This project addresses the technical obstacles as it translates from research discovery toward commercial application. Current microfluidic drop methods lack the ability to store cells at precise coordinates on a substrate, followed by addition or removal of media or drugs. As a result, such approaches have difficulty culturing cells and screening for drug efficacy, while retaining the benefits of nanoliter reagent volumes. In this project, this bottleneck will be resolved by coalescing stored and moving drops in a uniquely designed microfluidic network. A working prototype and validation data will be produced by optimizing device design, cell density and flow conditions. In addition, personnel involved in this project (graduate and undergraduate students) will receive training in innovation and entrepreneurship. The PI and co-PI have been involved in the University Accelerator Program which will form a natural channel for students working on this project to learn about entrepreneurship.

? DESCRIPTION (provided by applicant): Exercise is arguably the most potent approach we can take to defer physical decline associated with aging and to protect against late onset diseases such as diabetes, cancer, and Alzheimer's disease. Molecular understanding of how exercise benefits translate into healthy aging is thus of definitive medical interest. We study fundamental processes relevant to healthy aging in the 959-celled nematode C. elegans. Recently we made a fascinating discovery-C. elegans can exercise (swim) to exhibit training benefits, and appear to gain benefits by molecular pathways conserved in humans. Our initial model development opens up a new research area for understanding how tissue-specific and organism-wide health benefits are induced by exercise, and creates a novel paradigm for identifying exercise mimetic drugs that might promote healthy aging. To really harvest the potential of this model, we need to measure the strength of the tiny C. elegans. We collaborated to develop a strength test in which trained animals thread through a matrix of deformable pillars, and the extent of pillar deflection is used to calculate force. Our NemaFlex force detection device is the quantitative foundation with which we expect to break new ground in understanding exercise impact on healthy aging. Here we propose required development to enhance assay throughput and pursue applications that will not only anchor this technology as an essential component of C. elegans exercise evaluation but also accelerate studies on exercise biology and healthy aging in this powerful model. Aim 1 is to develop a novel high throughput tool for direct strength evaluation in C. elegans. This aim will generate an essential tool for analysis of C. elegans strength at multiple life stages, define the exercise regimen that will become the anchor protocol in the field, and reveal features of training in this model. Aim 2 is to use NemaFlex to evaluate exercise mimetic drugs & to facilitate focused pilot genetic screens. This aim will establish critical proof-of-principle for genetic and drug discovery using the NemaFlex. Aim 3 is to initiate dissection of the functional and molecular relationship between exercise and healthy aging, grounded in NemaFlex force measures of training benefits. To begin, we will test how optimized strength training tracks with a broad spectrum of healthspan indicators that decline with age, we will investigate impact of cessation of training on aging quality, and we will ask if exercise mimetic drugs extend healthspan in the absence of training. Our goals will create novel technology that for the first time permits facile quantitativ analysis of exercise adaptations in the powerful C. elegans genetic model. Accomplishment of our tractable aims will anchor a new subfield of genetic investigation of exercise and healthy aging that may influence design of interventions that broadly promote health and defer aging.

The broad impact/commercial potential of this I-Corps project is an innovative high throughput technology for screening drugs in small animals including the popular model organism C. elegans, a millimeter-sized nematode. Age is a significant risk factor for a variety of diseases including cancer, cardiovascular ailments and neurodegenerative disorders. It is projected that by 2030, 20% of the US population will be 65 years or older indicating that with the growing aging population the incidence of these diseases is expected to rise. Likewise, soil-transmitted helminthic infections are prevalent worldwide and there is increasing evidence that parasitic nematodes are becoming resistant to available drugs. C. elegans is a low-cost and high throughput animal model for identifying drug candidates for age-related diseases and parasitic infections. The I-Corps project has the potential to address current bottlenecks in conducting high throughput drug assays in the C. elegans model, thereby paving the path for a drug discovery pipeline. The impact of this project is on alleviating the socio-economic burden associated with age-associated diseases and parasitic infections.

This I-Corps project seeks to develop a microfluidics-based technology for automated drug testing on small nematodes. Current approaches to drug testing on C. elegans involve tedious steps of manual picking and transferring animals cultured on agar plates and moreover do not allow flexible control of culture environment. The proposed technology builds on basic principles of microscale flows, locomotion of active swimmers and crawlers, and low-cost wide-field imaging. Novel features of the technology for drug testing include an optimized microfluidic pillar arena that forms a habitat for growing animals, with unprecedented control over reagent delivery and culture environment. The low-cost wide-field imaging allows facile video recording of animal response to different drugs. The proposed innovation will markedly advance the throughput of in vivo drug and toxicity assays in an established, high throughput and low-cost animal model.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.