VTechWorks Repository :: Browsing by Author "Behkam, Bahareh"

Browsing by Author "Behkam, Bahareh"

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3D Coiling at the Protrusion Tip: New Perspectives on How Cancer Cells Sense Their Fibrous Surroundings
Mukherjee, Apratim (Virginia Tech, 2021-05-24)
Cancer metastasis, the spread of cancer from the primary site to distant regions in the body, is the major cause of cancer mortality, accounting for almost 90% of cancer related deaths. During metastasis, cancer cells from the primary tumor initially probe the surrounding fibrous tumor microenvironment (TME) prior to detaching and subsequently migrating towards the blood vessels for further dissemination. It has widely been acknowledged that the biophysical cues provided by the fibrous TME greatly facilitate the metastatic cascade. Consequently, there has been a tremendous wealth of work devoted towards elucidating different modes of cancer cell migration. However, our knowledge of how cancer cells at the primary tumor site initially sense their fibrous surroundings prior to making the decision to detach and migrate remains in infancy. In part, this is due to the lack of a fibrous in vitro platform that allows for precise, repeatable manipulation of fiber characteristics. In this study, we use the non-electrospinning, Spinneret based Tunable Engineered Parameters (STEP) technique to manufacture suspended nanofiber networks with exquisite control on fiber dimensions and network architecture and use these networks to investigate how single cancer cells biophysically sense fibers mimicking in vivo dimensions. Using high spatiotemporal resolution imaging (63x magnification/1-second imaging interval), we report for the first time, that cancer cells sense individual fibers by coiling (i.e. wrapping around the fiber axis) at the tip of a cell protrusion. We find that coiling dynamics are mediated by both the fiber curvature and the metastatic capacity of the cancer cells with less aggressive cancer cells showing diminished coiling. Based on these results, we explore the possibility of using coiling in conjunction with other key biophysical metrics such as cell migration dynamics and forces exerted in the development of a genetic marker independent, biophysical predictive tool for disease progression. Finally, we identify the membrane curvature sensing Insulin Receptor tyrosine kinase Substrate protein of 53 kDa (IRSp53) as a key regulator of protrusive activity with IRSp53 knockout (KO) cells exhibiting significantly slower protrusion dynamics and diminished coil width compared to their wild-type (WT) counterparts. We demonstrate that the hindered protrusive activity ultimately translates to impaired contractility, alteration in the nucleus shape and slower migration dynamics, thus highlighting the unique role of IRSp53 as a signal transducer – linking the protrusive activity at the cell membrane to changes in cytoskeletal contractility. Overall, these findings offer novel perspectives to our understanding of how cancer cells biophysically sense their fibrous surroundings. The results from this study could ultimately pave the way for elucidating the precise fiber configurations that either facilitate or hinder cancer cell invasion, allowing for the development of new therapeutics in the long term that could inhibit the metastatic cascade at a relatively nascent stage and yield a more promising prognosis in the perennial fight against cancer.
Actin Filaments Couple the Protrusive Tips to the Nucleus through the I-BAR Domain Protein IRSp53 during the Migration of Cells on 1D Fibers
Mukherjee, Apratim; Ron, Jonathan Emanuel; Hu, Hooi Ting; Nishimura, Tamako; Hanawa-Suetsugu, Kyoko; Behkam, Bahareh; Mimori-Kiyosue, Yuko; Gov, Nir Shachna; Suetsugu, Shiro; Nain, Amrinder Singh (Wiley-VCH, 2023-03)
The cell migration cycle, well-established in 2D, proceeds with forming new protrusive structures at the cell membrane and subsequent redistribution of contractile machinery. Three-dimensional (3D) environments are complex and composed of 1D fibers, and 1D fibers are shown to recapitulate essential features of 3D migration. However, the establishment of protrusive activity at the cell membrane and contractility in 1D fibrous environments remains partially understood. Here the role of membrane curvature regulator IRSp53 is examined as a coupler between actin filaments and plasma membrane during cell migration on single, suspended 1D fibers. IRSp53 depletion reduced cell-length spanning actin stress fibers that originate from the cell periphery, protrusive activity, and contractility, leading to uncoupling of the nucleus from cellular movements. A theoretical model capable of predicting the observed transition of IRSp53-depleted cells from rapid stick-slip migration to smooth and slower migration due to reduced actin polymerization at the cell edges is developed, which is verified by direct measurements of retrograde actin flow using speckle microscopy. Overall, it is found that IRSp53 mediates actin recruitment at the cellular tips leading to the establishment of cell-length spanning fibers, thus demonstrating a unique role of IRSp53 in controlling cell migration in 3D.
Active Transport in Chaotic Rayleigh-Bénard Convection
Mehrvarzi, Christopher Omid (Virginia Tech, 2014-01-13)
The transport of a species in complex flow fields is an important phenomenon related to many areas in science and engineering. There has been significant progress theoretically and experimentally in understanding active transport in steady, periodic flows such as a chain of vortices but many open questions remain for transport in complex and chaotic flows. This thesis investigates the active transport in a three-dimensional, time-dependent flow field characterized by a spatiotemporally chaotic state of Rayleigh-Be?nard convection. A nonlinear Fischer-Kolmogorov-Petrovskii-Piskunov reaction is selected to study the transport within these flows. A highly efficient, parallel spectral element approach is employed to solve the Boussinesq and the reaction-advection-diffusion equations in a spatially-extended cylindrical domain with experimentally relevant boundary conditions. The transport is quantified using statistics of spreading and in terms of active transport characteristics like front speed and geometry and are compared with those results for transport in steady flows found in the literature. The results of the simulations indicate an anomalous diffusion process with a power law 2 < ? < 5/2 a result that deviates from other superdiffusive processes in simpler flows, and reveals that the presence of spiral defect chaos induces strongly anomalous transport. Additionally, transport was found to most likely occur in a direction perpendicular to a convection roll in the flow field. The presence of the spiral defect chaos state of the fluid convection is found to enhance the front perimeter by t^3/2 and by a perimeter enhancement ratio r(p) = 2.3.
The AFM Study of Ovarian Cell Structural Mechanics in the Progression of Cancer
Ketene, Alperen Nurullah (Virginia Tech, 2011-05-06)
According to the American Cancer Society, Cancer is the second most common cause of death in the United States, only exceeded by heart disease. Over the past decade, deciphering the complex structure of individual cells and understanding the symptoms of cancer disease has been a highly emphasized research area. The exact cause of Cancer and the genetic heterogeneity that determines the severity of the disease and its response to treatment has been a great challenge. Researchers from the engineering discipline have increasingly made use of recent technological innovations, namely the Atomic Force Microscope (AFM), to better understand cell physics and provide a means for cell biomechanical profiling. The presented work's research objective is to establish a fundamental framework for the development of novel biosensors for cell separation and disease diagnosis. By using AFM nanoindentation, several studies were conducted to identify key distinctions in the trends of cell viscoelasticity between healthy, nontumorigenic cells and their malignant, highly tumorigenic counterparts. The possibility of identifying useful 'biomarkers' was also investigated. Due to the lack of an available human ovarian cell line, experiments were done on a recently developed mouse ovarian surface epithelial (MOSE) cell line, which resembles to human cell characteristics and represents early, intermediate, and late stages of the ovarian cancer. Material properties were extracted via Hertz model contact theory. The experimental results illustrate that the elasticity of late stage MOSE cells were 50% less than that of the early stage. Cell viscosity also decreased by 65% from early to late stage, indicating that the increase in cell deformability directly correlates with increasing levels of malignancy. Various cancer treatment and component-specific drugs were used to identify the causes for the changes in cell biomechanical behavior, depicting that the decrease in the concentration levels of cell structural components, predominantly the actin filament framework, is directly associated with the changes in cell biomechanical property. The investigation of MOSE cells being subject to multiple mechanical loads illustrated that healthy cells react to shear forces by stiffening up to 25% of their original state. On the other hand, cancerous cells are void of such response and at times show signs of decreasing rigidity. Finally, deformation studies on MOSE cancer stem cells have shown that these cells carry a unique elasticity profile among other cell stage phenotypes that could allow for their detection. The results herein carry great potential into contributing to cell separation methods and analysis, furthering the understanding of cell mechanism dynamics. While prior literature emphasizes on the elastic modulus of cells, the study of cell viscosity and other key material properties holds a critical place in the realistic modeling of these complex microstructures. A comprehensive study of individual cells holds a great amount of promise in the development of effective clinical research in the fight against cancer.
Aligned fibers direct collective cell migration to engineer closing and nonclosing wound gaps
Sharma, Puja; Ng, Colin; Jana, Aniket; Padhi, Abinash; Szymanski, Paige; Lee, Jerry S. H.; Behkam, Bahareh; Nain, Amrinder S. (2017-09-15)
Cell emergence onto damaged or organized fibrous extracellular matrix (ECM) is a crucial precursor to collective cell migration in wound closure and cancer metastasis, respectively. However, there is a fundamental gap in our quantitative understanding of the role of local ECM size and arrangement in cell emergence-based migration and local gap closure. Here, using ECM-mimicking nanofibers bridging cell monolayers, we describe a method to recapitulate and quantitatively describe these in vivo behaviors over multispatial (single cell to cell sheets) and temporal (minutes to weeks) scales. On fiber arrays with large interfiber spacing, cells emerge (invade) either singularly by breaking cell-cell junctions analogous to release of a stretched rubber band (recoil), or in groups of few cells (chains), whereas on closely spaced fibers, multiple chains emerge collectively. Advancing cells on fibers form cell streams, which support suspended cell sheets (SCS) of various sizes and curvatures. SCS converge to form local gaps that close based on both the gap size and shape. We document that cell stream spacing of 375 mu m and larger hinders SCS advancement, thus providing abilities to engineer closing and nonclosing gaps. Altogether we highlight the importance of studying cell-fiber interactions and matrix structural remodeling in fundamental and translational cell biology.
The Application of the Solar Chimney for Ventilating Buildings
Park, David (Virginia Tech, 2016-11-09)
This study sought to demonstrate the potential applications of the solar chimney for the naturally ventilating a building. Computational fluid dynamics (CFD) was used to model various room configurations to assess ventilation strategies. A parametric study of the solar chimney system was executed, and three-dimensional simulations were compared and validated with experiments. A new definition for the hydraulic diameter that incorporated the chimney geometry was developed to predict the flow regime in the solar chimney system. To mitigate the cost and effort to use experiments to analyze building energy, a mathematical approach was considered. A relationship between small- and full-scale models was investigated using non-dimensional analysis. Multiple parameters were involved in the mathematical model to predict the air velocity, where the predictions were in good agreement with experimental data as well as the numerical simulations from the present study. The second part of the study considered building design optimization to improve ventilation using air changes per hour (ACH) as a metric, and air circulation patterns within the building. An upper vent was introduced near the ceiling of the chimney system, which induced better air circulation by removing the warm air in the building. The study pursued to model a realistic scenario for the solar chimney system, where it investigated the effect of the vent sizes, insulation, and a reasonable solar chimney size. It was shown that it is critical to insulate the backside of the absorber and that the ratio of the conditioned area to chimney volume should be at least 10. Lastly, the application of the solar chimney system for basement ventilation was discussed. Appropriate vent locations in the basement were determined, where the best ventilation was achieved when the duct inlet was located near the ceiling and the exhaust vent was located near the floor of the chimney. Sufficient ventilation was also achieved even for scenarios of a congested building when modeling the presence of multiple people.
Automatic Detection and Characterization of Parasite Eggs by Image Processing
Ostergaard, Lindsey Eubank (Virginia Tech, 2013-08-26)
The accurate identification of parasites allows for the quick diagnosis and treatment of infections. Current state-of-the-art identification techniques require a trained technician to examine prepared specimens by microscope or other molecular methods. In an effort to automate the process and better facilitate the field identification of parasites, approaches are developed to utilize LabVIEW and MATLAB, which are commercially available image processing software packages, for parasite egg identification. The goal of this project is to investigate different image processing techniques and descriptors for the detection and characterization of the following parasite eggs: Ascaris lumbricoides, Taenia sp., and Paragonimus westermani. One manual approach and four automated approaches are used to locate the parasite eggs and gather parasite characterization data. The manual approach uses manual measurements of the parasite eggs within the digital images. The four automated approaches are LabVIEW Vision Assistant scripts, MATLAB separation code, MATLAB cross-section grayscale analysis, and MATLAB edge signature analysis. Forty-four separate measurements were analyzed through the four different approaches. Two types of statistical tests, single factor global Analysis of Variance (ANOVA) test and Multiple Comparison tests, are used to demonstrate that parasite eggs can be differentiated. Thirty-six of the measurements proved to be statistically significant in the differentiation of at least two of the parasite egg types. Of the thirty-six measurements, seven proved to be statistically significant in the differentiation of all three parasite egg types. These results have shown that it is feasible to develop an automated parasite egg detection and identification algorithm through image processing. The automated image processing techniques have proven successful at differentiating parasite eggs from background material. This initial research will be the foundation for future software structure, image processing techniques, and measurements that should be used for automated parasite egg detection.
Bacteria - Hydrogel Interactions: Mechanistic Insights via Microelastography and Deep Learning
Karmarkar, Bhas Niteen (Virginia Tech, 2024-01-05)
Bacteria-based cancer therapy (BBCT) holds immense promise in addressing the limitations in treatment of solid tumors. Bacterial strains used for BBCT are engineered to express therapeutics, facilitate precise navigation within the tumor microenvironment by enhancing bacteria's motility, chemotaxis (movement toward or away from specific chemicals), or other mechanisms that aid in reaching and infiltrating the tumor tissue effectively, and complementing traditional chemotherapy and immunotherapies while minimizing side effects. Bacterial motility not only influences the ability of bacteria to navigate within the tumor but also plays a pivotal role in optimizing drug delivery, treatment efficacy, and minimizing potential obstacles associated with the complex microenvironment of human tissues. However, the current understanding of bacterial motility remains limited. In this thesis, we use a reductionist approach and study bacteria motile behavior within human tissue phantoms (collagen and agar) and the bacteria-hydrogel interactions. Apart from motility, it is important to analyze the mechanical properties of the hydrogels the bacteria interact with as they play a vital role in overall behavior and physics of bacteria movement. To that extent, there exists a gap in our understanding of the viscoelastic properties of hydrogels. Lastly, systematic and comprehensive investigation of bacteria behavior in hydrogels requires tracking of thousands of individual cells. Thus, there is an unmet need to develop new automated techniques to reduce the labor-intensive manual tracking of bacteria in low-contrast hydrogel environments, with feature sizes comparable to that of bacteria. To address these gaps, this thesis proposes a trident approach towards mechanistic understanding of bacteria motility in time-invariant agar and temporally evolving collagen hydrogels to bridge critical gaps in understanding bacterial motile behavior in these media, non-destructive microelastography-based mechanical characterization of hydrogels with less than 4.7% error compared with rheology, and the development of deep learning-enabled automated bacteria tracking tools with 77% precision.
Bacteria-Enabled Autonomous Drug Delivery Systems: Design, Modeling, and Characterization of Transport and Sensing
Traore, Mahama Aziz (Virginia Tech, 2014-06-25)
The lack of efficacy of existing chemotherapeutic treatments of solid tumors is partially attributed to the limited diffusion distance of therapeutics and the low selectivity of anti-cancer drugs with respect to cancerous tissue, which also leads to high levels of systemic toxicity in patients. Thus, chemotherapy can be enhanced through improving anti-cancer drug carrier selectivity and transport properties. Several strains of gram positive (e.g. Clostridium and Bifidobacterium) and gram-negative (e.g. Salmonella Typhimurium and Escherichia coli) bacteria have been shown to possess the innate ability to preferentially colonize tumor tissues. The overall goal of this dissertation is to characterize the transport and sensing of Bacteria-Enabled Drug Delivery Systems (BEADS) in select relevant environments and to investigate the associated underlying principles. BEADS consist of an engineered abiotic load (i.e. drug-laden micro or nano-particles) and a living component (i.e. bacteria) for sensing and actuation purposes. Findings of this dissertation work are culminated in experimental demonstration of deeper penetration of the NanoBEADS within tumor tissue when compared to passively diffusing chemotherapeutic nanoparticles. Lastly, the transport mechanisms that Salmonella Typhimurium VNP20009 utilize to preferentially colonize solid tumors are also examined with the ultimate goal of engineering intelligent and more efficacious drug delivery vehicles for cancer therapy.
Bacteria-Enabled Autonomous Drug Delivery Systems: Development, Characterization of Intratumoral Transport and Modeling
Suh, SeungBeum (Virginia Tech, 2017-08-17)
Systemic chemotherapy is a major therapeutic approach for nearly all types and stages of cancer. Success of this treatment depends not only on the efficacy of the therapeutics but also on the transport of the drug to all tumor cells in sufficient concentrations. Intratumoral drug transport is limited by characteristics of the tumor microenvironment such as elevated interstitial pressure and sparse, irregular vascularization. Moreover, poor tumor selectivity, leads to systemic toxicity. Bacteria possess a host of characteristics that address the aforementioned challenges in conventional drug delivery approaches including tumor selectivity, preferential tumor colonization, effective tumor penetration, which can be augmented via genetic engineering. However, in clinical trials conducted to date, bacteria have rarely been able to inhibit tumor growth solely by their presence in the tumor. The overall goal of this doctoral dissertation is to develop a novel tumor treatment system based on Salmonella Typhimurium VNP20009 (genetically modified for preferential tumor colonization and attenuation) coupled with biodegradable copolymer, poly(lactic-co-glycolic acid) nanoparticles, hereafter referred to as NanoBEADS (Nanoscale Bacteria Enabled Autonomous Drug Delivery System). To this end, a NanoBEADS fabrication procedure that is robust and repeatable was established and a microfluidic chemotaxis-based sorting platform for the separation NanoBEADS from unattached nanoparticles was developed. The transport efficacy of NanoBEADS compared to the commonly used passively-diffusing nanoparticle was investigated in vitro and in vivo and the intratumoral penetration of the therapeutic vectors was quantified using a custom image processing algorithm. The mechanism of intratumoral penetration was elucidated through 2D and 3D invasion assays. Lastly, we developed a biophysical model of intratumoral transport of NanoBEADS based on the intratumoral penetration experimental results towards the theoretical evaluation of the drug transport profile following the administration of NanoBEADS.
Bacterial chemotaxis-enabled autonomous sorting of nanoparticles of comparable sizes
Suh, SeungBeum; Traore, Mahama Aziz; Behkam, Bahareh (Royal Society of Chemistry, 2016-02-18)
High throughput sorting of micro/nanoparticles of similar sizes is of significant interest in many biological and chemical applications. In this work, we report a simple and cost-effective sorting technique for separation of similarly-sized particles of dissimilar surface properties within a diffusion-based microfluidic platform using chemotaxis in Escherichia coli bacteria. Differences in surface chemistry of two groups of similarly-sized nanoparticles in a mixture were exploited to selectively assemble one particle group onto motile E. coli, through either specific or non-specific adhesion, and separate them from the remaining particle group via chemotaxis of the attached bacteria. To enable optimal operation of the sorting platform, the chemotaxis behavior of E. coli bacteria in response to casamino acids, the chemoeffector of choice was first characterized. The chemical concentration gradient range within which the bacteria exhibit a positive chemotactic response was found to be within 0.25 × 10−7–1.0 × 10−3 g ml−1 mm−1. We demonstrate that at the optimum concentration gradient of 5.0 × 10−4 g ml−1 mm−1, a sorting efficiency of up to 81% at a throughput of 2.4 × 105 particles per min can be achieved. Sensitivity of the sorting efficiency to the adhesion mechanism and particle size in the range of 320–1040 nm was investigated.
Biomanufacturing of Bacteria-Mediated Drug Delivery Systems and Investigation of Their Interaction with the Tumor Microenvironment
Zhan, Ying (Virginia Tech, 2024-05-14)
The limited transport of conventional chemotherapy within the tumor microenvironment (TME) is due to irregular vascularization, increased tumor interstitial pressure, and a dense extracellular matrix (ECM). The lack of selectivity of anticancer drugs often leads to systemic toxicity and damage to healthy tissues. Bacteria-based cancer therapy (BBCT) is a promising alternative, as tumor-targeting bacteria have been shown to preferentially colonize primary and metastatic tumors and induce anti-tumor effects. In this dissertation, we focus on several aspects of bacteria-nanoparticle conjugates, wherein BBCT is synergistically combined with nanomedicine to augment the efficacy of both treatment modalities. We explore biofabrication of our bacteria-nanoparticle conjugates called NanoBEADS (Nanoscale Bacteria Enabled Autonomous Drug Delivery Systems) and their interaction with the TME. Specifically, (1) we investigate the effects of two bacteria-NP conjugation chemistry and assembly process parameters of mixing method, volume, and duration, on NP attachment density and repeatability. We evaluate the influence of linkage chemistry and NP size on NP attachment density, viability, growth rate, and motility of NanoBEADS. (2) We investigate the effect of dense stroma and ECM production on the intratumoral penetration of bacteria with a mathematical model of bacterial intratumoral transport and growth. (3) We develop a microfluidic device with multicellular tumor spheroids to study the transport of tumor-targeting bacteria and support real-time imaging and long-term experiments. (4) We develop a new type of bacteria-based bio-hybrid drug delivery system using engineered cell surface display for enhancing the attachment of nanoparticles.
Cancer Cells Sense Fibers by Coiling on them in a Curvature-Dependent Manner
Mukherjee, Apratim; Behkam, Bahareh; Nain, Amrinder S. (2019-09-27)
Metastatic cancer cells sense the complex and heterogeneous fibrous extracellular matrix (ECM) by formation of protrusions, and our knowledge of how cells physically recognize these fibers remains in its infancy. Here, using suspended ECM-mimicking isodiameter fibers ranging from 135 to 1,000 nm, we show that metastatic breast cancer cells sense fiber diameters differentially by coiling (wrapping-around) on them in a curvature-dependent manner, whereas non-tumorigenic cells exhibit diminished coiling. We report that coiling occurs at the tip of growing protrusions and the coil width and coiling rate increase in a curvature-dependent manner, but time to maximum coil width occurs biphasically. Interestingly, bundles of 135-nm diameter fibers recover coiling width and rate on 1,000-nm-diameter fibers. Coiling also coincides with curvature-dependent persistent and ballistic transport of endogenous granules inside the protrusions. Altogether, our results lay the groundwork to link biophysical sensing with biological signaling to quantitate pro- and anti-invasive fibrous environments.
Cancer Protrusions on a Tightrope - Suspended Fiber Platform Reveals Protrusion Dynamics Independent of Cell Migration
Koons, Brian Joseph (Virginia Tech, 2015-06-04)
Indispensable to all modes of migration used during single cell metastasis, cytoplasmic protrusions are pivotal in surveying cells local surroundings which ultimately initiates migration of the cell body. Cancer cell migration is fairly well studied with the traditional focus on protrusion driven cell body displacement, while less is known on the role of protrusions in sensing cellular microenvironments. Here, we present a suspended and aligned fiber platform capable of high spatio-temporal imaging of protrusions capable of sensing fiber curvature contrasts independent of cell migration. By varying the diameter of suspended fibers, we are able to maintain cell migration along low curvature-large diameter (2μm) fibers, while solely allowing cells to sense, initiate, and mature protrusions on orthogonally deposited high curvature-low diameter (~100, 200 and 600 nm) fibers. Using highly aggressive breast MDA-MB-231 and brain glioblastoma DBTRG-05MG model systems, we find that MDA-MB-231 protrusion maturation dynamics are more sensitive to changes in fiber curvature and fibronectin ligand coating concentration compared to DBTRG-05MG. Furthermore, we find that vimentin intermediate filaments localize within 70% of mature protrusions, which normally form on larger diameter fibers. Additionally, protrusion lengths fluctuate continuously until the protrusion is either terminated or stabilized, and occasionally protrusions are observed to shed cytoplasmic fragments. Through manipulation of curvature contrasts, we demonstrate single protrusive hierarchical decomposition and coordination in zeroth (main), first and second order branches. The fiber curvature platform presented here uniquely allows cancer cells to sense nanofiber curvature contrasts, thus providing new mechanistic insights in protrusion initiation, maturation, and hierarchical coordination.
Cell-Fiber Interactions: A New Route to Mechano-Biological Investigations in Developmental and Disease Biology
Sheets, Kevin Tyler (Virginia Tech, 2014-11-03)
Cells in the body interact with a predominantly fibrous microenvironment and constantly adapt to changes in their neighboring physiochemical environment, which has implications in developmental and disease biology. A myriad of in vitro platforms including 2D flat and 3D gel substrates with and without anisotropy have demonstrated cellular alterations to subtle changes in topography. Recently, our work using suspended fibers as a new in vitro biological assay has revealed that cells are able to sense and respond to changes in fiber curvature and structural stiffness as evidenced by alterations to cytoskeleton arrangement, including focal adhesion cluster lengths and nucleus shape indices, leading to altered migration speeds. It is hypothesized that these behaviors occur due to modulation of cellular inside-out forces in response to changes in the external fibrous environment (outside-in). Thus, in this study, we investigate the role of fiber curvature and structural stiffness in force modulation of single cells attached to suspended fibers. Using our previously reported non-electrospinning Spinneret based Tunable Engineered Parameters (STEP) fiber manufacturing platform, we present our findings on single cell inside-out and outside-in forces using fibers of three diameters (250 nm, 400 nm and 800 nm) representing a wide range of structural stiffness (3-45 nN/μm). To investigate cellular adaptability to external perturbation, we present the development of a first-of-its-kind force measurement 'nanonet' platform capable of investigating cell adhesion forces in response to symmetric and non-symmetric (injury model) loading. Our combined findings are multi-fold: (i) Cells on suspended fibers are able to form focal adhesion clusters approximately four times longer than those on flat substrates, which gives them potential to double their migration speeds, (ii) Nanonets as force probes show that the contractility-based inside-out forces are nearly equally distributed on both sides of the cell body, and that overall force magnitudes are dependent on fiber structural stiffness, and (iii) External perturbation can evenly (symmetric) or unevenly (non-symmetric) distribute forces within the cell, and the resulting bias causes diameter-dependent outside-in adhesion force response. Finally, we demonstrate the power of the developed force measurement platform by extending our studies to cell-cell junctional forces as well as single-cell disease models including cancer and aortic aneurysm.
Computational and experimental study of chemotaxis of an ensemble of bacteria attached to a microbead
Traore, Mahama Aziz; Sahari, A.; Behkam, Bahareh (American Physical Society, 2011-12-12)
Micro-objects propelled by whole cell actuators, such as flagellated bacteria, are being increasingly studied and considered for a wide variety of applications. In this work we present theoretical and experimental investigations of chemotactic motility of a 10 mu m diameter microbead propelled by an ensemble of attached flagellated bacteria. The stochastic model presented here encompasses the behavior of each individual bacterium attached to the microbead in a spatiotemporally varying chemoattractant field. The computational model shows that in a chemotactic environment, the ensemble of bacteria, although constrained, propel the bead in a chemotactic manner with a 67% enhancement in displacement to distance ratio (defined as directionality) compared to nonchemotactic propulsion. The simulation results are validated experimentally. Close agreement between theory and experiments demonstrates the possibility of using the presented model as a predictive tool for other similar biohybrid systems.
Computational Modeling of Intracapillary Bacteria Transport in Tumor Microvasculature
Windes, Peter (Virginia Tech, 2016-09-23)
The delivery of drugs into solid tumors is not trivial due to obstructions in the tumor microenvironment. Innovative drug delivery vehicles are currently being designed to overcome this challenge. In this research, computational fluid dynamics (CFD) simulations were used to evaluate the behavior of several drug delivery vectors in tumor capillaries—specifically motile bacteria, non-motile bacteria, and nanoparticles. Red blood cells, bacteria, and nanoparticles were imposed in the flow using the immersed boundary method. A human capillary model was developed using a novel method of handling deformable red blood cells (RBC). The capillary model was validated with experimental data from the literature. A stochastic model of bacteria motility was defined based on experimentally observed run and tumble behavior. The capillary and bacteria models were combined to simulate the intracapillary transport of bacteria. Non-motile bacteria and nanoparticles of 200 nm, 300 nm, and 405 nm were also simulated in capillary flow for comparison to motile bacteria. Motile bacteria tended to swim into the plasma layer near the capillary wall, while non-motile bacteria tended to get caught in the bolus flow between the RBCs. The nanoparticles were more impacted by Brownian motion and small scale fluid fluctuations, so they did not trend toward a single region of the flow. Motile bacteria were found to have the longest residence time in a 1 mm long capillary as well as the highest average radial velocity. This suggests motile bacteria may enter the interstitium at a higher rate than non-motile bacteria or nanoparticles of diameters between 200–405 nm.
Controlling Microbial Adhesion to the Surfaces Using Topographical Cues
Kargar, Mehdi (Virginia Tech, 2013-05-08)
The state of adhesion of bacteria to nanofiber-textured model surfaces is analyzed at single-cell level. The results reveal similarities between the effect of topography on bacteria-surface interactions and vesicle-surface interactions. The results are discussed in the context of controlling bacterial adhesion to surfaces using nanofibrous topographical features.
Cytoskeletal Remodeling in Fibrous Environments to Study Pathophysiology
Jana, Aniket (Virginia Tech, 2021-09-28)
Mechanical interactions of cells with their immediately surrounding extracellular matrix (ECM) is now known to be critical in pathophysiology. For example, during cancer progression, while uncontrollable cell division leads to tumor formation, the subsequent metastatic migration of cells from the primary tumor site to distant parts of the body causes most cancer-related deaths. The metastatic journey requires cells to be able to adopt different shapes and move persistently through the highly fibrous native ECM, thereby requiring significant spatiotemporal reorganization of the cell cytoskeleton. While numerous studies performed on flat 2-dimensional culture platforms and physiological 3D gels have elucidated cytoskeletal reorganization, our understanding on how cells adapt to natural fibrous microenvironments and regulate their behavior in response to specific ECM biophysical cues including fiber size, spacing, alignment and stiffness remains in infancy. Here, we utilize the non -electrospinning Spinneret tunable engineered parameters (STEP) technique to manufacture ECM mimicking suspended fibrous matrices with precisely controlled fiber diameters, network architecture, inter-fiber spacing and structural stiffness to advance our fundamental understanding of how external cues affect cytoskeleton-based cellular forces in 3-distinct morphological processes of the cell cycle starting from division to spreading and migration. Mechanobiological insights from these studies are implemented to deliver intracellular cargo inside cells using electrical fields. Holistically, we conclude that fibrous environments elicit multiple new cell behaviors never before reported. Specifically, our new findings include (i) design of fiber networks regulates actin networks and cell forces to sculpt nuclei in varying shapes: compressed ovals, tear drop, and invaginations, and drive the nuclear translocation of transcription factors like YAP/TAZ. In all these shapes, nuclei remain rupture-free, thus demonstrating the unique adaptability of cells to fibers, (ii) dense crosshatch networks are fertile environments for persistent 1D migration in 3D shapes of rounded nuclei and low density of actin networks, while sparse fiber networks induce 2D random migration in flattened shapes and well-defined actin stress fibers, (iii) actin retraction fiber-based stability regulates mitotic errors. Cells undergoing mitosis on single fibers exhibit significant 3D movement, and those attached to two fibers can have rotated mitotic machinery, both conditions contributing to erroneous division, and (iv) a bi-phasic force response to electroporation that coincides with actin cytoskeleton remodeling. Cells on suspended fibers can withstand higher electric field abuse, which opens opportunities to deliver cargo of varying sizes inside the cell. Taken altogether, our findings provide new mechanobiological understanding of cell-fiber interactions at high spatiotemporal resolution impacting cell migration, division and nuclear mechanics-key behaviors in the study of pathophysiology.
Data-driven statistical modeling of the emergent behavior of biohybrid microrobots
Leaman, Eric J.; Sahari, Ali; Traore, Mahama Aziz; Geuther, Brian Q.; Morrow, Carmen M.; Behkam, Bahareh (2020-03-01)
Multi-agent biohybrid microrobotic systems, owing to their small size and distributed nature, offer powerful solutions to challenges in biomedicine, bioremediation, and biosensing. Synthetic biology enables programmed emergent behaviors in the biotic component of biohybrid machines, expounding vast potential benefits for building biohybrid swarms with sophisticated control schemes. The design of synthetic genetic circuits tailored toward specific performance characteristics is an iterative process that relies on experimental characterization of spatially homogeneous engineered cell suspensions. However, biohybrid systems often distribute heterogeneously in complex environments, which will alter circuit performance. Thus, there is a critically unmet need for simple predictive models that describe emergent behaviors of biohybrid systems to inform synthetic gene circuit design. Here, we report a data-driven statistical model for computationally efficient recapitulation of the motility dynamics of two types of Escherichia coli bacteria-based biohybrid swarms-NanoBEADS and BacteriaBots. The statistical model was coupled with a computational model of cooperative gene expression, known as quorum sensing (QS). We determined differences in timescales for programmed emergent behavior in BacteriaBots and NanoBEADS swarms, using bacteria as a comparative baseline. We show that agent localization and genetic circuit sensitivity strongly influence the timeframe and the robustness of the emergent behavior in both systems. Finally, we use our model to design a QS-based decentralized control scheme wherein agents make independent decisions based on their interaction with other agents and the local environment. We show that synergistic integration of synthetic biology and predictive modeling is requisite for the efficient development of biohybrid systems with robust emergent behaviors.

Browsing by Author "Behkam, Bahareh"

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