Our work focuses on the implementation of microfluidic network (μFN) platforms for the development of new bioassays and diagnositics in micro total analytical systems (μTAS). Several examples of ongoing research are highlighted below:

Multiplexed biomolecule and virus detection
A local, evanescent, array-coupled (LEAC) sensor based on a compact, single-mode optical waveguide (IOW) is being developed by the Dandy, Lear, and Henry groups for multianalyte sensing of targets ranging from small biomolecules to virus particles. The LEAC sensor is a promising platform for point-of-care diagnostics. The sensor fabrication is compatible with trailing-edge complementary metal oxide semiconductor CMOS technology, which both lowers its cost and makes it possible to build a portable lab-on-a-chip system with silicon integrated circuits. As a label-free optical biosensor, it does not require reagents during operation. Furthermore, the LEAC approach is less sensitive to temperature or wavelength variations than resonance-based label-free optical biosensors, such as surface plasmon resonance biosensors or ring resonator biosensors. Molecular specificity is provided by probe molecules, e.g., monoclonal- or monospecific polyclonal antibodies, aptamers, or antibody fragments immobilized on the sensor during the manufacturing process.

Passive and active micromixing strategies
It is recognized that mixing plays an important role in the growing use of microfluidic devices for lab-on-a-chip applications. For applications ranging from DNA separation and amplification to protein crystallization and kinetics studies, the performance of a lab-on-a-chip device is directly related to the rate at which two or more fluids can be mixed. Due to the small dimensions of microchannels as well as the limited range of obtainable linear flow rates, flow in microchannels is confined to the laminar regime and mixing is dominated by molecular diffusion.

With the goal of further simplifying fabrication of a micromixer, we are developing a new method for achieving chaotic advection through application of a localized electric field perpendicular to the mean flow direction driven by a pressure gradient in a planar rectangular microchannel. The electric field, created by a potential drop across an integrated electrode gap, drives electro-osmotic flow (EOF) perpendicular to the main flow direction, thereby creating a secondary recirculation flow profile.

Passive pumping
Controlled pumping of fluids through microfluidic networks is a critical unit operation ubiquitous to lab-on-a-chip applications. Although there have been a number of studies involving the creation of passive flows within lab-on-a-chip devices, none have shown the ability to create temporally stable flows for periods longer than several minutes. We have developed passive pumping approach in which a large pressure differential arising from a small, curved meniscus situated along the bottom corners of an outlet reservoir serves to drive fluid through a microfluidic network. The system quickly reaches steady state and is able to provide precise volumetric flow rates for periods lasting many hours.

Spatially resolved sampling
The spatial and temporal distributions of diffusible molecules play an important role in a wide variety of biological and chemical processes. The formation and maintenance of these distributions is a complex function of the local fluid convection profiles, the diffusivities of the chemicals in question, and chemical reactions that take place. There are many applications in which these chemical distributions possess characteristic length scales on the order of 1 to 1000 μm. A microfluidic device capable of sampling multiple chemical messengers with a spatial resolution dictated by the extent and overall architecture of the tissue has been developed. Due to the precise fabrication methods of the underlying microfluidic architecture, the position of each sampling port can easily be modified to sample fluid from specific regions of interest within the sample reservoir. The device is readily fabricated using soft lithographic processes, where the degree of fluid sampling from each port is controlled via passive pumping techniques. The system is compatible with most transduction mechanisms that are easily incorporated into planar microfluidic systems, leading to a cost-effective solution for high-resolution, multi-analyte chemical analysis.

Bioparticle  concentration and separation
The ability to continuously and reliably concentrate and separate small diameter bioparticle (≤ 2 µm) suspensions, such as bacteria, subcellular organelles and even virus that are flowing through microchannels, offers significant potential for biomedical, environmental, food, and biofuel production applications. Typically, bioparticle concentration and separation are accomplished through industrial or laboratory centrifugation, but when the particle size is very small and its density is comparable to the mixture medium, as with bacteria, virus and subcellular organelles, this approach can be problematic. A simple but robust platform able to provide significant improvements over current concentration techniques is needed.

The use of microfluidics has streamlined many traditional laboratory techniques, due to the advantages of ease to operation, low-cost, and miniaturized size. In the specific application to bioparticle concentration and separation, inertial focusing is a very promising approach that relies solely on channel geometry and intrinsic hydrodynamic forces exerted on particles in a dilute suspension as they are transported in laminar flow with a non-uniform velocity profile. We are investigating the use of this inertial microfluidics technique to separate micron and sub-micron bioparticles based on their size, and to incorporate the approach with digital microfluidics and cytometry.

At present, three distinct project areas exist within the Henry group. i) Development of low-cost methods for the analysis of environmental pollutants, with a primary focus on air pollution. Paper-based microfluidic analytical devices are employed to understand occupational and environmental exposure to pollutants in atmospheric aerosols such as particulate matter and heavy metals. ii) Development of biosensors for bacteria, viruses and biomarkers. This involves the coupling of microfluidic devices with electrochemistry, colorimetry or electrophoresis, for the low cost and sensitive analysis of relevant biological targets. iii) Design of new lab-on-a-chip systems, such as composite electrode materials, 3D printed microfluidic devices and colorimetric chemometers. These are employed for a range targets and systems from environmental monitoring to global health.

The Kipper research lab develops new functional biomaterials by advancing technology along several research themes that are inspired by biological materials.

One of the research themes consists of exploiting ‘hyperfunctionality’ of biologically derived materials. More specifically, the Kipper research lab develops techniques for exploiting inherent compatibility and functionality amongst biocompatible materials, functional biomaterials, and biologically derived materials, by designing new biomaterials from biologically-derived materials.

A class of biologically derived polymers called polysaccharides, pose unique challenges and offer tremendous opportunity for development of function into biomaterials. They are challenging, because a lack in sequencing and synthesis technology has hindered the progress in this area. However, this offers an opportunity. By introducing polysaccharides into biomaterials we can simultaneously introduce many functions into a biomaterial, including cell adhesion ligands, guidance of cell migration, stabilization and delivery of biochemical signals, anti-microbial activity, and moieties that spatially organize other biomolecules.

Another research theme explored in the Kipper research lab are techniques for engineering assemblies of biomolecules across length scales. A distinguishing feature of biology is that function is intimately dependent upon structure. Particularly, at the molecular, nanoscopic, and microscopic length scales, specific functions are organized inside organelles in cells, at interfaces and membranes, and in the pericellular and extracellular spaces. This organization and compartmentalization of function gives rise to emergent biological properties. We develop new processing methods for organizing biological macromolecule, like polysaccharides, into new nanomaterials with prescribed two-dimensional, and three-dimensional organization. This enables us to derive structure-property-function relationships that can be used to develop design principles for biologically inspired materials.

The third research theme explored by the Kipper research lab is tissue engineering, orthopedics, and cardiovascular materials. These themes converge when we develop new materials for biomedical applications. Currently we are developing materials that stabilize and deliver otherwise very unstable biochemical signals (cytokines), materials that guide adult stem cell differentiation, and materials that have multiple specialized functions for orthopedics and cardiovascular applications. These materials have are being used to develop new technologies that could improve outcomes treatments for cardiovascular disease (the number one cause of death worldwide) and arthritis (which affects more than 20 % of the adult US population). We are also contributing to the development of new materials for biosensors, for stem cell cultivation and expansion, and materials with advanced optical and photonic properties.

Dr. Munsky’s research lab works to integrate models and experiments to better understand, predict, and control complex biological behaviors.

Even genetically identical cells in identical environments exhibit wildly different phenotypical behaviors due to cellular fluctuations known as gene expression “noise”. Previously, such noise was considered a nuisance that compromised cellular responses, complicated modeling, and made predictive understanding all but impossible. Many studies focused on how cellular processes remove or exploit noise to a cell’s advantage. However, different cellular mechanisms affect these cellular fluctuations in different ways, and it is now clear that these fluctuations contain valuable information about underlying cellular mechanisms. Finding and exploiting this information requires a strong integration of single-cell/single-molecule measurements with discrete stochastic analyses. The Munsky Group focuses on utilizing this information to gain predictive understanding of new biological phenomena. Along these lines, we have studied natural and synthetic transcriptional regulation pathways in bacteria, yeast and mammalian cells. Notably, the Munsky Group is heavily involved in q-bio, or Quantitative biology, an emerging interdisciplinary field that encompasses many different approaches to modeling, understanding, predicting, and manipulating biological processes.

The Peccoud lab is a synthetic biology lab focused on the application of software and computer languages to the study of biological systems. This includes the development of software for designing gene sequences and optimizing DNA manufacturing workflows and the use of computational tools to model biological functions. The Peccoud lab is also exploring the security implications of the increasing use of computers in the life sciences. The overarching goal of the lab is to better understand DNA as a language and to use computer grammars and software to improve our ability to speak that language well.

The Peebles Group works in the areas of metabolic engineering, secondary metabolism, regulatory networks, and systems biology in plants, bacteria and yeast for the production of bio-based chemicals and fuels. More specifically these areas can be divided into 2 main applications: the first is the use of plant metabolic engineering to produce important pharmaceuticals and nutraceuticals, and he second is the engineering of photoautotrophs for the production of bio-based chemicals and fuels. One area focuses on the metabolic engineering of cyanobacteria for fuels and chemical while the second area focuses on plant metabolic engineering to produce pharmaceuticals.

Today, that work, funded in part by seed money from the Colorado Center for Biorefining and Biofuels, involves manipulating the genetic structure of a microorganism called cyanobacteria, which is believed to have been a building block to the development of life on Earth two to three billion years ago. Using newly developed metabolic engineering tools and methods for controlling gene expression, Peebles and her research team at CSU are exploring whether some genetically engineered form of a microorganism such as cyanobacteria can someday emerge as a building block for biomass-derived fuels and chemicals. Cyanobacteria are believed to be the first organisms capable of oxygenic photosynthesis. According to Peebles, while still largely unexplored as a production source for commercial biofuels and biochemicals, they possess several qualities that make them especially promising in those pathways.

Peebles and her CSU team are also investigating two pathways involving cyanobacteria, one designed to yield free fatty acids for producing biodiesel and chemicals (mainly for human health applications), and the other designed to yield terpenoids, also to produce biofuels and chemicals that may prove valuable in the human health arena, such as in the development of drugs for treating cancer

Cyano-bacteria can double their biomass in four to eight hours, as compared to several days for popular biomass feedstocks such as corn, notes Peebles. They are capable of growing in areas considered inhospitable to other agricultural species (marginal, nonarable lands), and they can do so with “gray” (non-potable) water, so they won’t compete for resources with agricultural products.

Such a bioreactor — a “cell factory” in Peebles’ terms — could produce a range of products, from fatty acid-based biodiesel for transportation applications to high-value chemicals such as carotenoids and terpenoids.

The Prasad Group works on several projects at the interface of the physical sciences and engineering with biology, using mathematical and computational methods as well as experiments.

Research areas of interest to the group include cellular biomechanics and the determination of cell shape, the theoretical properties of signaling and gene transcription networks, synthetic biology, especially in plants, identification of network aberrations in cancer using machine learning, and genome scale metabolic modeling. The group has developed methods for quantitative image analysis to distinguish between some types of cancer cells, and is currently working to extend these methods more generally.

In biomechanics, Dr. Prasad is interested in developing techniques for measuring the physical parameters of the cellular cytoskeleton using microrheology, and relating them to cellular phenotype, motility and cytoskeletal properties. In synthetic biology the group works on developing synthetic circuits in plants, in collaboration with plant synthetic biologists at CSU.

In cancer network analysis, Dr. Prasad collaborates with researchers in the College of Veterinary Sciences to help uncover the signatures of drug sensitivity of cancers. The group also works on understanding p53 dynamics and mitochondrial dynamics in cancer cells. In metabolic modeling, Dr. Prasad’s group recently built a genome-scale metabolic model of the photosynthetic cyanobacterium, Synechocystis, and is interested in using metabolic models to understand dynamic changes, such as the day and night cycle of photosynthetic microorganisms. The research group also collaborates closely with many experimental groups across campus.

The Reisfeld Group investigates the disposition of foreign chemicals (environmental toxicants and drugs) in humans and their effects on human health. Specific topics include:

• chemical pharmacokinetics and ADME (absorption, distribution, metabolism, and excretion)
• chemical pharmacodynamics/toxicodynamics
• metabolizing enzymes and their microenvironments
• host, drug, pathogen interactions, including the immune response
• drug transport and partitioning in tissues
• OneHealth

The Reisfeld Group uses modeling approaches to study pharmacokinetics and pharmacodynamics. In other words, models are developed to better understand and predict how drug molecules are distributed throughout bodies, as well as how they affect the organs and tissues, as well as how the body processes the small molecules. Additional efforts are made to study the role of the immune system in responding to foreign molecules (xenobiotics). Ultimately, such models can guide targeted experiments to analyze and predict how human beings will react to and process xenobiotics. At the most detailed molecular level this includes modeling specific cytochrome P450 isozyme reaction rates and ligand binding.

Bionanotechnology:

The Snow Laboratory is engaged in Biological Engineering. The focus in these cases is engineering at the level of biological macromolecules and assemblies thereof rather than engineering at the cellular level.

One strength of the department is the ability to engineer functional nanostructures by taking advantage of biomolecular engineering approaches. Specifically, the Snow Lab engineers proteins that serve as building blocks within larger assemblies, respectively protein crystals and viral phage capsids. Both groups use protein engineering and chemical biology methods to optimize the resulting protein assemblies.

The Snow Lab is engineering porous protein crystals as scaffolds in which the position of guest macromolecules can be programmed. Applications include advanced catalytic materials (by loading enzymes and enzyme mixtures), advanced biodegradable biosensors (by conditionally confining fluorescent proteins), oxygen carrying materials (by loading hemoglobin), deep tissue in vivo imaging (by loading infrared fluorescent proteins), high surface area conductive materials (via in crystallo synthesis of conductive polymers), anchored DNA nanotechnology (via installation of guest oligonucleotides), and new approaches to crystallographic structure determination (by loading guest molecules of unknown structure).

Mathematic Modeling:

Modeling is a strong branch of the department; multiple research groups specialize in diverse mathematical or computational modeling strategies.

The Snow Lab develops software to model and design proteins (www.sharp-n.org), and uses other software to simulate proteins and protein assemblies. These simulations range from atomic detail (molecular dynamics simulations including explicit water molecules) to coarse grained simulations (simulating the assembly of multiple nucleic acid strands). One of the key applications for these molecular simulations is to validate designed proteins prior to experimental testing. To simulate events that occur on longer time scales or length scales Snow group researchers use implicit solvent, Brownian dynamics, and Markov State models. To accelerate the expensive computations, the Snow group uses graphics cards (GPUs). Another specialty is using continuum electrostatics calculations (Poisson Boltzmann) to understand subtle energetic effects involving screening of charge-charge interactions.

The Snow Lab also has a long standing interest in explicitly modeling cytochrome P450 structure and reaction specificity. Example applications for the methods described above are to assess the risk associated with exposure to environmental pollutants, or to optimize drug regimens.

Polymer Science:

The Snow Lab also engineers polymers. First, the expressed polypeptides (proteins) that are the building blocks for their [Bionanotechnology] efforts are themselves polymers. More important, however, are the efforts in both groups to synthesize highly controlled polymers by covalently linking together proteins as templated by non-covalent assembly.

Transport Phenomena:

The Snow Lab is also interesting in modeling transport in the particular context of understanding and controlling the diffusion of guest molecules within porous crystals. Confocal microscopy provides the experimental data to allow tracking the transport of fluorescent guest particles within crystals. On the computational site, a range of computational models are being used to build predictive models for transport. In order of increasing complexity and detail, these include simple finite difference models, Markov State models, Brownian dynamics simulations, and Molecular dynamics simulations.

The Wang Group’s research interests combine advanced theories and computer simulation techniques to study at nano-to-meso-scales (i.e., from sub-nanometers to micrometers) the behavior of nanostructured polymeric materials. The Wang Group uses a suite of computational tools to investigate the thermodynamic and dynamic behavior of these systems and to establish the interconnections between these results at different levels, thus enabling hierarchical modeling bridging various time and length scales. The group also focuses on collaborating with experimentalists to provide insights into experimental results, to validate simulation and theoretical results, and to further help experimental design.

Transport Phenomena:

The Watson Group has a particularly strong focus on quantifying and understanding transport phenomena using magnetic resonance imaging. The ability of nuclear magnetic resonance (NMR) methods to perform measurements noninvasively and to reconcile them spatially, provide enormous potential for significant growth of NMR within many diverse fields in science and engineering. Exciting applications have been reported within a number of industries, including chemical, food processing, building and construction, medicine, and petroleum production. Applications include on-line monitoring of processes, food quality inspections, and characterization of underground petroleum resources.

The Watson Group takes advantage of the sensitivity of NMR to different molecular environments and motions to design experiments that provide for determination of properties, resolved as three-dimensional spatial data, useful for describing various physical phenomena of interest. The primary target of the ongoing work is to better understand flow in permeable media, and to better characterize the porosity and morphology of the host media. Research in this area can lead to methods for characterizing various tissues, including bone, skin, and cartilage, and mathematical models that describe physical processes within those tissues, such as flow and diffusion; design and control of in-situ bioremediation of groundwater resources; methods for microbially-enhanced oil recovery; and characterization and evaluation of scaffolds for tissue engineering.