Author: ians

Schneider Research Group

Engineering Cell Dynamics

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Iowa State University
Department of Chemical and Biological Engineering
2114 Sweeney Hall
Ames, IA
50011-2230

Office: 3053 Sweeney Hall
Lab: 2140 and 2144 Sweeney Hall
Phone: 515-294-0450
Fax: 515-294-2689
E-mail: ians(at)iastate.edu

Schneider Research Group

Engineering Cell Dynamics

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Engineering Multi-cue
Migrational Environments

Adhesion and Cytoskeleton Dynamics

Research

Lab Members

Publications

How we do it

Teaching

Coincidence Detectors
for Cancer Diagnostics

Cancer Cell-Immune Cell Paracrine Interactions

Schneider Research Group

Engineering Cell Dynamics

Home

Engineering Multi-cue
Migrational Environments

Adhesion and Cytoskeleton Dynamics

Research

Lab Members

Publications

How we do it

Teaching

Coincidence Detectors
for Cancer Diagnostics

Cancer Cell-Immune Cell Paracrine Interactions

Engineering Multi-cue Migrational Environments:

The goal of this project is to use several engineering techniques to create simplified, yet fully tunable in vitro migration platforms. These platforms will be used to assess how cells make migrational decisions when multiple cues are presented. During cancer progression, stromal cells remodel collagen fibers that surround the growing tumor. Cancer cells then migrate out of the tumor along those remodeled fibers, a process called contact guidance. Additionally, immune cells secrete soluble factors, generating concentration gradients. Cancer cells migrate up gradients of soluble proteins such as epidermal growth factor (EGF) towards blood vessels, a process called chemotaxis. Cues for both contact guidance and chemotaxis are presented simultaneously in vivo, however they can be spatially organized such that each gives contradictory information to the cell. While there is a firm understanding of how cells respond to individual contact guiding and chemotactic cues, virtually nothing is known about how cells integrate multiple cues and make migrational decisions based on that integration. I am taking an engineering approach by designing in vitro environments that mimic the in vivo environment with the added ability to independently tune directional cues.

Schneider Research Group

Engineering Cell Dynamics

Home

Engineering Multi-cue
Migrational Environments

Adhesion and Cytoskeleton Dynamics

Research

Lab Members

Publications

How we do it

Teaching

Coincidence Detectors
for Cancer Diagnostics

Cancer Cell-Immune Cell Paracrine Interactions

Adhesion and Cytoskeleton Dynamics:

Cell migration occurs in steps of protrusion, adhesion, contraction, traction generation and retraction. First the cell protrudes via force generated by polymerization of the actin cytoskeleton. The protrusion adheres to the surroundings through specific interactions between integrins and the ECM. This interaction generates macromolecular protein complexes called focal adhesions (FAs). Once adhered, the cell generates contractile forces through the actin cytoskeleton. These contractile forces allow the cell to detach at its trailing edge and move forward. It has long been known that collagen and EGF alter cell migration speed, persistence and directionality when either presented uniformly, in gradients or on aligned fibers. Recently, has there been an interest in pursuing quantitative, high resolution techniques to measure morphology and focal adhesion dynamics . While these papers have at times examined the effect of ECM or growth factors on changes in morphology or FA dynamics, none have attempted to examine their regulation during contact guidance, chemotaxis or when both cues are present.

Schneider Research Group

Engineering Cell Dynamics

Home

Engineering Multi-cue
Migrational Environments

Adhesion and Cytoskeleton Dynamics

Research

Lab Members

Publications

How we do it

Teaching

Coincidence Detectors
for Cancer Diagnostics

Cancer Cell-Immune Cell Paracrine Interactions

Coincidence Detectors for Cancer Diagnostics:

Pancreatic cancer is an aggressive malignancy refractory to surgical excision and available medical treatments resulting in death within 5 years for 94% of diagnosed patients. Two reasons drive the poor prognosis of pancreatic cancer. First, this cancer has not seen decreases in mortality rates like those realized in breast and colon cancer because of a lack of tools to detect pancreatic adenocarcinoma (PDAC) before or during the early stages of invasion. Second, this cancer results in difficult removal of all invasive cancerous tissue during surgery, allowing for redevelopment of the tumor. These challenges require a detection strategy specific to pre-invasive cancerous tissue. Nanoparticles provide an ideal detection platform on which to engineer this required specificity. There has been extensive work done to detect cancer using nanoparticles that merely target cancer cells. These have been largely unsuccessful at generating specific localization because these targeted nanoparticles often bind normal tissue, decreasing the specificity of localization. Coincidence detection, the detection of two inputs simultaneously resulting in one output, provides an opportunity to overcome issues of specificity. I plan to build a coincidence detector by engineering nanoparticles with the ability to target PDAC cells (input 1) and sense enzymatic activity (input 2) that is upregulated directly before invasion. Specifically, I will use quantum dots (QDs), which are luminescent nanoparticles that can report enzymatic activity through changes in their optical properties. These nanoparticles will eventually be used during intravital imaging for early PDAC detection or during surgery as pathology tools to help surgeons properly excise all invasive cancer tissue.

Schneider Research Group

Engineering Cell Dynamics

Home

Engineering Multi-cue
Migrational Environments

Adhesion and Cytoskeleton Dynamics

Research

Lab Members

Publications

How we do it

Teaching

Coincidence Detectors
for Cancer Diagnostics

Cancer Cell-Immune Cell Paracrine Interactions

Cancer Cell-Immune Cell Paracrine Interactions:

Cell-cell communication regulates the physiological process of wound healing as well as the pathological process of cancer metastasis. Recently, it was discovered that there is a paracrine loop linking carcinoma cells and macrophages during the early stages of metastasis. Carcinoma cells secrete colony stimulating factor-1 (CSF-1). CSF-1 induces macrophages to secrete epidermal growth factor (EGF). EGF induces carcinoma cells to leave the tumor and to secrete more CSF-1, which in turn activates more macrophages. We are interested in examining the signaling dynamics of this paracrine interaction as well as how this paracrin interaction operates spatially in mixed-cultures with varying densities and spacing of cells.

Schneider Research Group

Engineering Cell Dynamics

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Principal Investigator:

Research

Lab Members

Publications

How we do it

Teaching

Ian Schneider

Post-docs:

Graduate Students:

Protease Biosensors

Adhesion Dynamics

Multi-cue
Environments

Yanjie Zhang

Yue (Ariel) Hou

Laura Lara Rodriquez

Protease Biosensors

Contact Guidance

Amanda Haage

Nick Romsey

Undergraduate Students:

Caged RGD

Multi-cue
Environments

3D Collagen
Fiber Alignment

Andy Ford

Tim Ouverson

Kianna Elahi

2D Collagen
Fiber Alignment

Carin Lightner

Alumni:
Greg Harris, Graduate student in ChE, ISU (2009-2010) [Graduate Student, University of South Carolina]
Latrisha Peterson, Independent Study Graduate student in ChE, ISU (Spring 2010) [Post-doc, Iowa State University]
Amanda Machacek. Undergraduate student in ChE, ISU (2009-2010) [ChE, Lionel]
Samantha Chalfant. Undergraduate student in ChE, ISU (Spring 2010) [Graduate Student, Iowa State University]
Abdulrahman Ahmadi. Undergraduate student in ChE, University College London (2010-2011)
Sara Hedberg. Undergraduate student in ChE, University College London (2010-2011)
Vania Romay. Undergraduate student in ChE, ISU (Spring 2011)
Nick Wetzel. Undergraduate student in ChE, ISU (Spring 2011)
Carolyn Zahler. BioMaP NSF REU student in Chemistry, University of Florida (Summer 2009) [Medical Student, University of Miami]
Daniel Flores. BioMaP NSF REU student in Biotechnology, Tecnológico de Monterrey, Mexico (Summer 2010) [Graduate Student, Iowa State University]
Alex Cochrane. BioMaP NSF REU student in Applied Biology, Rose Hullman (Summer 2011)
Dorothea Craigen. Undergraduate SPEED student in ChE and Agronomy, ISU (Summer 2010)
Zach Benedict. Undergraduate SPEED student in AeroE, ISU (Summer 2011)
Tanea Hibler. Academies Creating Teacher Scientists teacher, (Summer 2010 , Summer 2011) [High School Teacher, Concordia International School, Shanghai, China]
Victor Wang. Ames High School Student (Summer 2011)

Schneider Research Group

Engineering Cell Dynamics

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Publications:
Gardel, M.L., Schneider, I.C., Aratyn-Schaus, Y. and Waterman, C. 2010. Mechanical Integration of Actin and Adhesion Dynamics in Cell Migration. Ann. Rev. of Cell and Dev. Biol. 26:315-333.
Pasapera, A.M., Schneider, I.C., Rericha, E., Schlaepfer, D.D. and Waterman, C. 2010. Myosin II Activity Regulates Vinculin Recuritment to Focal Adhesions Through FAK-mediated Paxillin-phosphorylation. J. Cell Biol. 188: 877-890.
Schneider, I.C., Hays, C.K. and Waterman, C.M. 2009. EGF-induced Contraction Regulates Paxillin Phosphorylation to Temporally Separate Traction Generation from De-adhesion. Mol. Biol. Cell. 20: 3155-3167.
Haugh, J.M. and Schneider, I.C. 2006. Effectiveness Factor for Spatial Gradient Sensing in Living Cells. Chem. Eng. Sci. 61: 5603-5611.
Schneider, I.C. and Haugh, J.M. 2006. Mechanisms of Gradient Sensing and Chemotaxis: Conserved Pathways, Diverse Regulation. Cell Cycle. 5: 1130-1134.
Schneider, I.C. and Haugh, J.M. 2005. Quantitative Elucidation of a Distinct Spatial Gradient Sensing Mechanism in Fibroblasts. J. Cell Biol. 171:883-892.
Schneider, I.C., Parrish, E., and Haugh, J.M. 2005. Spatial Analysis of 3’ Phosphoinositide Signaling in Living Fibroblasts: III. Influence of Cell Morphology and Morphological Polarity. Biophys. J. 89:1420-1430.
Haugh, J.M., Schneider, I.C., and Lewis, J.M. 2004. On the Cross-regulation of Protein Tyrosine Phosphatases and Receptor Tyrosine Kinases in Intracellular Signaling. J. Theor. Biol. 230:119-132.
Schneider, I.C. and Haugh, J.M. 2004. Spatial Analysis of 3’ Phosphoinositide Signaling in Living Fibroblasts: II. Parameter Estimates for Individual Cells from Experiments. Biophys. J. 86:599-608.
Haugh, J.M. and Schneider, I.C. 2004. Spatial Analysis of 3’ Phosphoinositide Signaling in Living Fibroblasts: I. Uniform Stimulation Model and Bounds on Dimensionless Groups. Biophys. J. 86:589-598.
Park, C.S., Schneider, I.C., and Haugh, J.M. 2003. Kinetic Analysis of Platelet-derived Growth Factor Receptor/Phosphoinositide 3-Kinase/Akt Signaling in Fibroblasts. J. Biol. Chem. 278:37064-37072.
Schneider, I.C., Ames, M.L., Rasmussen, M.A., and Reilly, P.J. 2002. Fermentation of Cottonseed and Other Feedstuffs in Cattle Ruminal Contents. J. Agric. Food Chem. 50:2267-2273.
Schneider, I.C., Rhamy, P.J., Fink-Winter, R.J., and Reilly, P.J. 1999. High-performance Anion-exchange Chromatography of Sugar and Glycerol Phosphates on Quaternary Ammonium Resins. Carbohydrate Research. 322:128-134.

Schneider Research Group

Engineering Cell Dynamics

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Equipment:

High resolution light microscope. The high resolution light microscope is a multi-mode Nikon TiE microscope that includes widefield fluorescence (10x, 20x,40x and 60x), through-the-objective total internal reflection fluorescence (TIRF) (60x and 100x), differential interference contrast (40x, 60x and 100x) and phase contrast (10x and 20x) microscopy. The stage is heated with an air curtain, but chambers have additional heating for precise temperature control (see below). TIRF illumination includes an argon ion laser with 514/488/457nm lines (150 mW/130 mW/30 mW) and a solid state laser with a 442nm line (45 mW) and shutters to control each laser line separately. Both lines are home-coupled into a single mode fiber that is fed into the TIRF illuminator. Our widefield fluorescence is built around a Prior ProscanII and has excitation/emission/dichroics for 6 different fluorophores. The TiE includes the Perfect Focus System, automated TIRF angle adjustment, and automated Prior shutters and filter wheels for complete control through a computer interface. The two detectors are a low-noise Photometrics CoolSnap HQ2 CCD and Andor iXon EMCCD for high-quality, high-resolution microscopy. The latter is ideal for low signal fluorophores or those prone to photobleaching like GFP and its variants. The microscope and peripherals are driven by mManager, freeware built on ImageJ.
Long timelapse microscope. This microscope is a Nikon TiE microsope that includes widefield fluorescence (10x, 20x,40x and 60x), differential interference contrast (40x, 60x and 100x) and phase contrast (10x and 20x) microscopy. The widefield fluorescence is built around a Prior ProscanII and has excitation/emission/dichroics for 2 different fluorophores. The TiE includes the Perfect Focus System and automated Sutter shutters for control through a computer interface. The detector is a CCD from the ImagingSource. The microscope and peripherals are driven by mManager, freeware built on ImageJ.

Links:

MicroManager
ImageJ
Web of Science
Nikon Microscopy U
Invitrogen SpectraViewer

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