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Tronolone JJ, Mohamed N, Jain A. Engineering Lymphangiogenesis-On-Chip: The Independent and Cooperative Regulation by Biochemical Factors, Gradients, and Interstitial Fluid Flow. Adv Biol (Weinh) 2024; 8:e2400031. [PMID: 38400704 DOI: 10.1002/adbi.202400031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Indexed: 02/25/2024]
Abstract
Despite the crucial role of lymphangiogenesis during development and in several diseases with implications for tissue regeneration, immunity, and cancer, there are significantly fewer tools to understand this process relative to angiogenesis. While there has been a major surge in modeling angiogenesis with microphysiological systems, they have not been rigorously optimized or standardized to enable the recreation of the dynamics of lymphangiogenesis. Here, a Lymphangiogenesis-Chip (L-Chip) is engineered, within which new sprouts form and mature depending upon the imposition of interstitial flow, growth factor gradients, and pre-conditioning of endothelial cells with growth factors. The L-Chip reveals the independent and combinatorial effects of these mechanical and biochemical determinants of lymphangiogenesis, thus ultimately resulting in sprouts emerging from a parent vessel and maturing into tubular structures up to 1 mm in length within 4 days, exceeding prior art. Further, when the constitution of the pre-conditioning cocktail and the growth factor cocktail used to initiate and promote lymphangiogenesis are dissected, it is found that endocan (ESM-1) results in more dominant lymphangiogenesis relative to angiogenesis. Therefore, The L-Chip provides a foundation for standardizing the microfluidics assays specific to lymphangiogenesis and for accelerating its basic and translational science at par with angiogenesis.
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Affiliation(s)
- James J Tronolone
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Nadin Mohamed
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Abhishek Jain
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA
- Department of Medical Physiology, School of Medicine, Texas A&M Health Science Center, Bryan, TX, 77807, USA
- Department of Cardiovascular Sciences, Houston Methodist Academic Institute, Houston, TX, 77030, USA
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2
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Ghosh LD, Mathur T, Tronolone JJ, Chuong A, Rangel K, Corvigno S, Sood AK, Jain A. Angiogenesis-Enabled Human Ovarian Tumor Microenvironment-Chip Evaluates Pathophysiology of Platelets in Microcirculation. Adv Healthc Mater 2024:e2304263. [PMID: 38553940 DOI: 10.1002/adhm.202304263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/25/2024] [Indexed: 04/09/2024]
Abstract
The tumor microenvironment (TME) promotes angiogenesis for its growth through the recruitment of multiple cells and signaling mechanisms. For example, TME actively recruits and activates platelets from the microcirculation to facilitate metastasis, but platelets may simultaneously also support tumor angiogenesis. Here, to model this complex pathophysiology within the TME that involves a signaling triad of cancer cells, sprouting endothelial cells, and platelets, an angiogenesis-enabled tumor microenvironment chip (aTME-Chip) is presented. This platform recapitulates the convergence of physiology of angiogenesis and platelet function within the ovarian TME and describes the contribution of platelets in promoting angiogenesis within an ovarian TME. By including three distinct human ovarian cancer cell-types, the aTME-Chip quantitatively reveals the following outcomes-first, introduction of platelets significantly increases angiogenesis; second, the temporal dynamics of angiogenic signaling is dependent on cancer cell type; and finally, tumor-educated platelets either activated exogenously by cancer cells or derived clinically from a cancer patient accelerate tumor angiogenesis. Further, analysis of effluents available from aTME-Chip validate functional outcomes by revealing changes in cytokine expression and several angiogenic and metastatic signaling pathways due to platelets. Collectively, this tumor microphysiological system may be deployed to derive antiangiogenic targets combined with antiplatelet treatments to arrest cancer metastasis.
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Affiliation(s)
- Lopamudra D Ghosh
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Tanmay Mathur
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - James J Tronolone
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Ashley Chuong
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Kelly Rangel
- Department of Gynecologic Oncology and Reproductive Medicine, UT MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Sara Corvigno
- Department of Gynecologic Oncology and Reproductive Medicine, UT MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Anil K Sood
- Department of Gynecologic Oncology and Reproductive Medicine, UT MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Abhishek Jain
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, 77843, USA
- Department of Medical Physiology, College of Medicine, Texas A&M Health Science Center, Bryan, TX, 77807, USA
- Department of Cardiovascular Sciences, Houston Methodist Academic Institute, Houston, TX, 77030, USA
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Tronolone JJ, Mathur T, Chaftari CP, Sun Y, Jain A. Machine learning chained neural network analysis of oxygen transport amplifies the physiological relevance of vascularized microphysiological systems. Bioeng Transl Med 2023; 8:e10582. [PMID: 38023704 PMCID: PMC10658488 DOI: 10.1002/btm2.10582] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 07/04/2023] [Accepted: 07/14/2023] [Indexed: 12/01/2023] Open
Abstract
Since every biological system requires capillaries to support its oxygenation, design of engineered preclinical models of such systems, for example, vascularized microphysiological systems (vMPS) have gained attention enhancing the physiological relevance of human biology and therapies. But the physiology and function of formed vessels in the vMPS is currently assessed by non-standardized, user-dependent, and simple morphological metrics that poorly relate to the fundamental function of oxygenation of organs. Here, a chained neural network is engineered and trained using morphological metrics derived from a diverse set of vMPS representing random combinations of factors that influence the vascular network architecture of a tissue. This machine-learned algorithm outputs a singular measure, termed as vascular network quality index (VNQI). Cross-correlation of morphological metrics and VNQI against measured oxygen levels within vMPS revealed that VNQI correlated the most with oxygen measurements. VNQI is sensitive to the determinants of vascular networks and it consistently correlates better to the measured oxygen than morphological metrics alone. Finally, the VNQI is positively associated with the functional outcomes of cell transplantation therapies, shown in the vascularized islet-chip challenged with hypoxia. Therefore, adoption of this tool will amplify the predictions and enable standardization of organ-chips, transplant models, and other cell biosystems.
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Affiliation(s)
- James J. Tronolone
- Department of Biomedical Engineering, College of EngineeringTexas A&M UniversityCollege StationTexasUSA
| | - Tanmay Mathur
- Department of Biomedical Engineering, College of EngineeringTexas A&M UniversityCollege StationTexasUSA
| | - Christopher P. Chaftari
- Department of Biomedical Engineering, College of EngineeringTexas A&M UniversityCollege StationTexasUSA
| | - Yuxiang Sun
- Department of Nutrition, College of Agriculture and Life SciencesTexas A&M UniversityCollege StationTexasUSA
| | - Abhishek Jain
- Department of Biomedical Engineering, College of EngineeringTexas A&M UniversityCollege StationTexasUSA
- Department of Medical Physiology, School of MedicineTexas A&M Health Science CenterBryanTexasUSA
- Department of Cardiovascular ScienceHouston Methodist Academic InstituteHoustonTexasUSA
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Tronolone JJ, Mathur T, Chaftari CP, Jain A. Evaluation of the Morphological and Biological Functions of Vascularized Microphysiological Systems with Supervised Machine Learning. Ann Biomed Eng 2023:10.1007/s10439-023-03177-2. [PMID: 36913087 DOI: 10.1007/s10439-023-03177-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 02/22/2023] [Indexed: 03/14/2023]
Abstract
Vascularized microphysiological systems and organoids are contemporary preclinical experimental platforms representing human tissue or organ function in health and disease. While vascularization is emerging as a necessary physiological organ-level feature required in most such systems, there is no standard tool or morphological metric to measure the performance or biological function of vascularized networks within these models. Further, the commonly reported morphological metrics may not correlate to the network's biological function-oxygen transport. Here, a large library of vascular network images was analyzed by the measure of each sample's morphology and oxygen transport potential. The oxygen transport quantification is computationally expensive and user-dependent, so machine learning techniques were examined to generate regression models relating morphology to function. Principal component and factor analyses were applied to reduce dimensionality of the multivariate dataset, followed by multiple linear regression and tree-based regression analyses. These examinations reveal that while several morphological data relate poorly to the biological function, some machine learning models possess a relatively improved, but still moderate predictive potential. Overall, random forest regression model correlates to the biological function of vascular networks with relatively higher accuracy than other regression models.
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Affiliation(s)
- James J Tronolone
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, 101 Bizzell Street, College Station, TX, 77843, USA
| | - Tanmay Mathur
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, 101 Bizzell Street, College Station, TX, 77843, USA
| | - Christopher P Chaftari
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, 101 Bizzell Street, College Station, TX, 77843, USA
| | - Abhishek Jain
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, 101 Bizzell Street, College Station, TX, 77843, USA.
- Department of Medical Physiology, School of Medicine, Texas A&M University, Bryan, TX, USA.
- Department of Cardiovascular Sciences, Houston Methodist Academic Institute, Houston, USA.
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Tronolone JJ, Mathur T, Chaftari CP, Jain A. Evaluation of the morphological and biological functions of vascularized microphysiological systems with supervised machine learning. bioRxiv 2023:2023.01.12.523755. [PMID: 36711458 PMCID: PMC9882172 DOI: 10.1101/2023.01.12.523755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Vascularized microphysiological systems and organoids are contemporary preclinical experimental platforms representing human tissue or organ function in health and disease. While vascularization is emerging as a necessary physiological organ-level feature required in most such systems, there is no standard tool or morphological metric to measure the performance or biological function of vascularized networks within these models. Further, the commonly reported morphological metrics may not correlate to the network's biological function - oxygen transport. Here, a large library of vascular network images was analyzed by the measure of each sample's morphology and oxygen transport potential. The oxygen transport quantification is computationally expensive and user-dependent, so machine learning techniques were examined to generate regression models relating morphology to function. Principal component and factor analyses were applied to reduce dimensionality of the multivariate dataset, followed by multiple linear regression and tree-based regression analyses. These examinations reveal that while several morphological data relate poorly to the biological function, some machine learning models possess a relatively improved, but still moderate predictive potential. Overall, random forest regression model correlates to the biological function of vascular networks with relatively higher accuracy than other regression models.
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Mathur T, Tronolone JJ, Jain A. AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks. bioRxiv 2023:2023.01.09.523275. [PMID: 36711826 PMCID: PMC9881947 DOI: 10.1101/2023.01.09.523275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Measuring the capacity of microvascular networks in delivering soluble oxygen and nutrients to its organs is essential in health, disease, and surgical interventions. Here, a finite element method-based oxygen transport program, AngioMT, is designed and validated to predict spatial oxygen distribution and other physiologically relevant transport metrics within both the vascular network and the surrounding tissue. The software processes acquired images of microvascular networks and produces a digital mesh which is used to predict vessel and tissue oxygenation. The image-to-physics translation by AngioMT correlated with results from commercial software, however only AngioMT could provide predictions within the solid tissue in addition to vessel oxygenation. AngioMT predictions were sensitive and positively correlated to spatial heterogeneity and extent of vascularization of 500 different vascular networks formed with variable vasculogenic conditions. The predictions of AngioMT cross-correlate with experimentally-measured oxygen distributions in vivo. The computational power of the software is increased by including calculations of higher order reaction mechanisms, and the program includes defining additional organ and tissue structures for a more physiologically relevant analysis of tissue oxygenation in complex co-cultured systems, or in vivo. AngioMT may serve as a digital performance measuring tool of vascular networks in microcirculation, experimental models of vascularized tissues and organs, and in clinical applications, such as organ transplants.
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Affiliation(s)
- Tanmay Mathur
- Department of Biomedical Engineering, Texas A&M University, 101 Bizzell St, College Station, TX 77843, USA
| | - James J. Tronolone
- Department of Biomedical Engineering, Texas A&M University, 101 Bizzell St, College Station, TX 77843, USA
| | - Abhishek Jain
- Department of Biomedical Engineering, Texas A&M University, 101 Bizzell St, College Station, TX 77843, USA
- Department of Medical Physiology, College of Medicine, Texas A&M Health Science Center, Bryan, TX, USA
- Department of Cardiovascular Sciences, Houston Methodist Research Institute, Houston, TX 77030, USA
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Tronolone JJ, Mathur T, Chaftari CP, Jain A. A machine‐learned microvasculature optimizes physiological insulin secretion in a vascularized pancreas‐chip. FASEB J 2022. [DOI: 10.1096/fasebj.2022.36.s1.r6103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | - Tanmay Mathur
- Biomedical EngineeringTexas A&M UniversityCollege StationTX
| | | | - Abhishek Jain
- Biomedical EngineeringTexas A&M UniversityCollege StationTX
- Medical PhysiologyTexas A&M UniversityCollege StationTX
- Cardiovascular SciencesTexas A&M UniversityCollege StationTX
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Abstract
Background Organ‐on‐chip technology has accelerated in vitro preclinical research of the vascular system, and a key strength of this platform is its promise to impact personalized medicine by providing a primary human cell–culture environment where endothelial cells are directly biopsied from individual tissue or differentiated through stem cell biotechniques. However, these methods are difficult to adopt in laboratories, and often result in impurity and heterogeneity of cells. This limits the power of organ‐chips in making accurate physiological predictions. In this study, we report the use of blood‐derived endothelial cells as alternatives to primary and induced pluripotent stem cell–derived endothelial cells. Methods and Results Here, the genotype, phenotype, and organ‐chip functional characteristics of blood‐derived outgrowth endothelial cells were compared against commercially available and most used primary endothelial cells and induced pluripotent stem cell–derived endothelial cells. The methods include RNA‐sequencing, as well as criterion standard assays of cell marker expression, growth kinetics, migration potential, and vasculogenesis. Finally, thromboinflammatory responses under shear using vessel‐chips engineered with blood‐derived endothelial cells were assessed. Blood‐derived endothelial cells exhibit the criterion standard hallmarks of typical endothelial cells. There are differences in gene expression profiles between different sources of endothelial cells, but blood‐derived cells are relatively closer to primary cells than induced pluripotent stem cell–derived. Furthermore, blood‐derived endothelial cells are much easier to obtain from individuals and yet, they serve as an equally effective cell source for functional studies and organ‐chips compared with primary cells or induced pluripotent stem cell–derived cells. Conclusions Blood‐derived endothelial cells may be used in preclinical research for developing more robust and personalized next‐generation disease models using organ‐on‐chips.
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Affiliation(s)
- Tanmay Mathur
- Department of Biomedical Engineering, College of Engineering Texas A&M University College Station TX
| | - James J Tronolone
- Department of Biomedical Engineering, College of Engineering Texas A&M University College Station TX
| | - Abhishek Jain
- Department of Biomedical Engineering, College of Engineering Texas A&M University College Station TX.,Department of Medical Physiology College of MedicineTexas A&M Health Science Center Bryan TX.,Department of Cardiovascular Sciences Houston Methodist Research Institute Houston TX
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Saha B, Mathur T, Tronolone JJ, Chokshi M, Lokhande GK, Selahi A, Gaharwar AK, Afshar-Kharghan V, Sood AK, Bao G, Jain A. Human tumor microenvironment chip evaluates the consequences of platelet extravasation and combinatorial antitumor-antiplatelet therapy in ovarian cancer. Sci Adv 2021; 7:eabg5283. [PMID: 34290095 PMCID: PMC8294767 DOI: 10.1126/sciadv.abg5283] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 06/04/2021] [Indexed: 05/13/2023]
Abstract
Platelets extravasate from the circulation into tumor microenvironment, enable metastasis, and confer resistance to chemotherapy in several cancers. Therefore, arresting tumor-platelet cross-talk with effective and atoxic antiplatelet agents in combination with anticancer drugs may serve as an effective cancer treatment strategy. To test this concept, we create an ovarian tumor microenvironment chip (OTME-Chip) that consists of a platelet-perfused tumor microenvironment and which recapitulates platelet extravasation and its consequences. By including gene-edited tumors and RNA sequencing, this organ-on-chip revealed that platelets and tumors interact through glycoprotein VI (GPVI) and tumor galectin-3 under shear. Last, as proof of principle of a clinical trial, we showed that a GPVI inhibitor, Revacept, impairs metastatic potential and improves chemotherapy. Since GPVI is an antithrombotic target that does not impair hemostasis, it represents a safe cancer therapeutic. We propose that OTME-Chip could be deployed to study other vascular and hematological targets in cancer.
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Affiliation(s)
- Biswajit Saha
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77840, USA
| | - Tanmay Mathur
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77840, USA
| | - James J Tronolone
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77840, USA
| | - Mithil Chokshi
- Department of Bioengineering, George R. Brown School of Engineering, Rice University, Houston, TX 77005, USA
| | - Giriraj K Lokhande
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77840, USA
| | - Amirali Selahi
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77840, USA
| | - Akhilesh K Gaharwar
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77840, USA
- Materials Science and Engineering, College of Engineering, Texas A&M University, College Station, TX 77840, USA
- Center for Remote Health Technologies and Systems, Texas A&M University, College Station TX 77840, USA
| | - Vahid Afshar-Kharghan
- Department of Benign Hematology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Anil K Sood
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Gang Bao
- Department of Bioengineering, George R. Brown School of Engineering, Rice University, Houston, TX 77005, USA
| | - Abhishek Jain
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77840, USA.
- Department of Medical Physiology, College of Medicine, Texas A&M Health Science Center, Bryan, TX 77807, USA
- Department of Cardiovascular Sciences, Houston Methodist Academic Institute, Houston, TX 77030, USA
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Tronolone JJ, Lam J, Agrawal A, Sung K. Pumpless, modular, microphysiological systems enabling tunable perfusion for long-term cultivation of endothelialized lumens. Biomed Microdevices 2021; 23:25. [PMID: 33855605 DOI: 10.1007/s10544-021-00562-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/03/2021] [Indexed: 12/28/2022]
Abstract
Given the increased recognition of the importance of physiologically relevant microenvironments when designing in vitro assays, microphysiological systems (MPS) that mimic the critical function and structure of tissues and organs have gained considerable attention as alternatives to traditional experimental models. Accordingly, the field is growing rapidly, and some promising MPS are being tested for use in pharmaceutical development and toxicological testing. However, most MPS are complex and require additional infrastructure, which limits their successful translation. Here, we present a pumpless, modular MPS consisting of 1) a resistance module that controls flow rate and 2) a physiologically relevant, three-dimensional blood vessel module. Flow is provided by an attached reservoir tank that feeds fluid into the resistance channel via hydrostatic pressure. The flow rate is controlled by the height of the media in the tank and the resistance channel's dimensions. The flow from the resistance module is streamed into the blood vessel module using a liquid bridge. We utilize optical coherence tomography (OCT) to measure fluid velocity at regions of interest. The endothelial cells cultured in the MPS remain viable for up to 14 days and demonstrate the functional characteristics of the human blood vessels verified by tight junction expression and diffusion assay. Our results show that a modular MPS can simulate a functional endothelium in vitro while simplifying the operation of the MPS. The simplicity of the system allows for modifications to incorporate other microenvironmental components and to build other organ-modeling systems easily.
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Affiliation(s)
- James J Tronolone
- Division of Cellular and Gene Therapies, Center for Biologics Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, Maryland, 20993-0002, USA
| | - Johnny Lam
- Division of Cellular and Gene Therapies, Center for Biologics Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, Maryland, 20993-0002, USA
| | - Anant Agrawal
- Divison of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Kyung Sung
- Division of Cellular and Gene Therapies, Center for Biologics Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, Maryland, 20993-0002, USA.
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Tronolone JJ, Jain A. Engineering new microvascular networks on-chip: ingredients, assembly, and best practices. Adv Funct Mater 2021; 31:2007199. [PMID: 33994903 PMCID: PMC8114943 DOI: 10.1002/adfm.202007199] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Indexed: 05/23/2023]
Abstract
Tissue engineered grafts show great potential as regenerative implants for diseased or injured tissues within the human body. However, these grafts suffer from poor nutrient perfusion and waste transport, thus decreasing their viability post-transplantation. Graft vascularization is therefore a major area of focus within tissue engineering because biologically relevant conduits for nutrient and oxygen perfusion can improve viability post-implantation. Many researchers utilize microphysiological systems as testing platforms for potential grafts due to an ability to integrate vascular networks as well as biological characteristics such as fluid perfusion, 3D architecture, compartmentalization of tissue-specific materials, and biophysical and biochemical cues. While many methods of vascularizing these systems exist, microvascular self-assembly has great potential for bench-to-clinic translation as it relies on naturally occurring physiological events. In this review, we highlight the past decade of literature and critically discuss the most important and tunable components yielding a self-assembled vascular network on chip: endothelial cell source, tissue-specific supporting cells, biomaterial scaffolds, biochemical cues, and biophysical forces. This article discusses the bioengineered systems of angiogenesis, vasculogenesis, and lymphangiogenesis, and includes a brief overview of multicellular systems. We conclude with future avenues of research to guide the next generation of vascularized microfluidic models and future tissue engineered grafts.
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Affiliation(s)
- James J Tronolone
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Abhishek Jain
- Department of Medical Physiology, College of Medicine, Texas A&M Health Science Center, Bryan, TX 77808, USA
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Tronolone JJ, Orrill M, Song W, Kim HS, Lee BY, LeBlanc S. Electric Field Assisted Self-Assembly of Viruses into Colored Thin Films. Nanomaterials (Basel) 2019; 9:nano9091310. [PMID: 31540252 PMCID: PMC6781059 DOI: 10.3390/nano9091310] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 08/28/2019] [Accepted: 09/10/2019] [Indexed: 02/07/2023]
Abstract
Filamentous viruses called M13 bacteriophages are promising materials for devices with thin film coatings because phages are functionalizable, and they can self-assemble into smectic helicoidal nanofilament structures. However, the existing “pulling” approach to align the nanofilaments is slow and limits potential commercialization of this technology. This study uses an applied electric field to rapidly align the nanostructures in a fixed droplet. The electric field reduces pinning of the three-phase contact line, allowing it to recede at a constant rate. Atomic force microscopy reveals that the resulting aligned structures resemble those produced via the pulling method. The field-assisted alignment results in concentric color bands quantified with image analysis of red, green, and blue line profiles. The alignment technique shown here could reduce self-assembly time from hours to minutes and lend itself to scalable manufacturing techniques such as inkjet printing.
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Affiliation(s)
- James J Tronolone
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA.
| | - Michael Orrill
- Department of Mechanical and Aerospace Engineering, The George Washington University, Washington, DC 20052, USA.
| | - Wonbin Song
- Department of Mechanical Engineering, Korea University, Seoul 02841, Korea.
| | - Hyun Soo Kim
- Department of Mechanical Engineering, Korea University, Seoul 02841, Korea.
| | - Byung Yang Lee
- Department of Mechanical Engineering, Korea University, Seoul 02841, Korea.
| | - Saniya LeBlanc
- Department of Mechanical and Aerospace Engineering, The George Washington University, Washington, DC 20052, USA.
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