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Kaneko S, Hirotaka S, Tsujii M, Maruyama H, Uozumi N, Arai F. Instantaneous extracellular solution exchange for concurrent evaluation of membrane permeability of single cells. LAB ON A CHIP 2024; 24:281-291. [PMID: 38086698 DOI: 10.1039/d3lc00633f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
The osmotic stress imposed on microorganisms by hypotonic conditions is perceived to regulate water and solute flux via cell membranes, which are crucial for survival. Some cells that fail to perceive osmotic stress die because this results in the rupture of the cell membrane. The flux through the membrane is characterized by the membrane permeability, which is measured using a stopped-flow apparatus in response to a millisecond-order osmolarity change. However, the obtained data are an ensemble average of each cell response. Additionally, the measurement of permeability, considering cellular viability, contributes to a more accurate evaluation of osmoadaptation. Here, we present a novel on-chip instantaneous extracellular solution exchange method using an air-liquid interface. The presented method provides a concurrent evaluation at the single-cell level in response to a millisecond-order osmotic shock, considering cellular viability by solution exchange. This method utilizes a liquid bridge with a locally formed droplet on the surface of a micropillar fabricated inside a microchannel. We evaluated a solution exchange time of 3.6 ms and applied this method to Synechocystis PCC 6803 under two different osmolarity conditions. The live/dead ratio of 1 M to 0.5 M osmotic down shock condition was 78.8/21.2% while that of 1 M to 0.25 M osmotic down shock condition was 40.0/60.0%. We evaluated the water permeability of two groups: cells that were still live before and after osmotic shock (hereafter named cell type 1), and cells that were live before but were dead 10 minutes after osmotic shock (hereafter named cell type 2). The results indicated that the water permeability of cell type 2 was higher than that of cell type 1. The results obtained using the presented methods confirmed that the effect of osmotic stress can be accurately evaluated using single-cell analysis.
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Affiliation(s)
- Shingo Kaneko
- Department of Mechanical Engineering, Graduate School of Engineering, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.
| | - Sugiura Hirotaka
- Department of Mechanical Engineering, Graduate School of Engineering, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.
| | - Masaru Tsujii
- Department of Biomolecular Engineering, Graduate School of Engineering, Tohoku University, 6-6-07, Aobayama, Aoba-ku, Sendai 980-8579, Japan
| | - Hisataka Maruyama
- Department of Micro-Nano Mechanical Science and Engineering, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Nobuyuki Uozumi
- Department of Biomolecular Engineering, Graduate School of Engineering, Tohoku University, 6-6-07, Aobayama, Aoba-ku, Sendai 980-8579, Japan
| | - Fumihito Arai
- Department of Mechanical Engineering, Graduate School of Engineering, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.
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2
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Wang D, He M, Zhang M, Yang H, Huang J, Zhou R, Jin Y, Wu C. Food yeasts: occurrence, functions, and stress tolerance in the brewing of fermented foods. Crit Rev Food Sci Nutr 2023; 63:12136-12149. [PMID: 35875880 DOI: 10.1080/10408398.2022.2098688] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
With the rapid development of systems biology technology, there is a deeper understanding of the molecular biological mechanisms and physiological characteristics of microorganisms. Yeasts are widely used in the food industry with their excellent fermentation performances. While due to the complex environments of food production, yeasts have to suffer from various stress factors. Thus, elucidating the stress mechanisms of food yeasts and proposing potential strategies to improve tolerance have been widely concerned. This review summarized the recent signs of progress in the variety, functions, and stress tolerance of food yeasts. Firstly, the main food yeasts occurred in fermented foods, and the taxonomy levels are demonstrated. Then, the main functions of yeasts including aroma enhancer, safety performance enhancer, and fermentation period reducer are discussed. Finally, the stress response mechanisms of yeasts and the strategies to improve the stress tolerance of cells are reviewed. Based on sorting out these related recent researches systematically, we hope that this review can provide help and approaches to further exert the functions of food yeasts and improve food production efficiency.
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Affiliation(s)
- Dingkang Wang
- College of Biomass Science and Engineering, Sichuan University, Chengdu, China
- Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu, China
| | - Muwen He
- College of Biomass Science and Engineering, Sichuan University, Chengdu, China
- Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu, China
| | - Min Zhang
- College of Biomass Science and Engineering, Sichuan University, Chengdu, China
- Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu, China
| | - Huan Yang
- College of Biomass Science and Engineering, Sichuan University, Chengdu, China
- Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu, China
| | - Jun Huang
- College of Biomass Science and Engineering, Sichuan University, Chengdu, China
- Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu, China
| | - Rongqing Zhou
- College of Biomass Science and Engineering, Sichuan University, Chengdu, China
- Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu, China
| | - Yao Jin
- College of Biomass Science and Engineering, Sichuan University, Chengdu, China
- Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu, China
| | - Chongde Wu
- College of Biomass Science and Engineering, Sichuan University, Chengdu, China
- Key Laboratory of Leather Chemistry and Engineering, Ministry of Education, Sichuan University, Chengdu, China
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3
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Sun Y, Zhang F, Li L, Chen K, Wang S, Ouyang Q, Luo C. Two-Layered Microfluidic Devices for High-Throughput Dynamic Analysis of Synthetic Gene Circuits in E. coli. ACS Synth Biol 2022; 11:3954-3965. [PMID: 36283074 DOI: 10.1021/acssynbio.2c00307] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Escherichia coli is a common chassis for synthetic gene circuit studies. In addition to the dose-response of synthetic gene circuits, the analysis of dynamic responses is also an important part of the future design of more complicated synthetic systems. Recently, microfluidic-based methods have been widely used for the analysis of gene expression dynamics. Here, we established a two-layered microfluidic platform for the systematic characterization of synthetic gene circuits (eight strains in eight different culture environments could be observed simultaneously with a 5 min time resolution). With this platform, both dose responses and dynamic responses with a high temporal resolution could be easily derived for further analysis. A controlled environment ensures the stability of the bacterial growth rate, excluding changes in gene expression dynamics caused by changes of the growth dilution rate. The precise environmental switch and automatic micrograph shooting ensured that there was nearly no time lag between the inducer addition and the data recording. We studied four four-node incoherent-feedforward-loop (IFFL) networks with different operators using this device. The experimental results showed that as the effect of inhibition increased, two of the IFFL networks generated pulselike dynamic gene expressions in the range of the inducer concentrations, which was different from the dynamics of the two other circuits with only a simple pattern of rising to the platform. Through fitting the dose-response curves and the dynamic response curves, corresponding parameters were derived and introduced to a simple model that could qualitatively explain the generation of pulse dynamics.
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Affiliation(s)
- Yanhong Sun
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of Physics, Peking University, Beijing100871, China
| | - Fengyu Zhang
- School of Life Sciences and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing100871, China
| | - Lusi Li
- Academy of Advanced Interdisciplinary Studies, Peking University, Beijing100871, China
| | - Kaiyue Chen
- Wenzhou Institute University of Chinese Academy of Sciences, Wenzhou, Zhejiang325001, China
| | - Shujing Wang
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of Physics, Peking University, Beijing100871, China
| | - Qi Ouyang
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of Physics, Peking University, Beijing100871, China.,Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China
| | - Chunxiong Luo
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of Physics, Peking University, Beijing100871, China.,Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China.,Wenzhou Institute University of Chinese Academy of Sciences, Wenzhou, Zhejiang325001, China
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4
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The regulatory mechanism of the yeast osmoresponse under different glucose concentrations. iScience 2022; 26:105809. [PMID: 36636353 PMCID: PMC9830198 DOI: 10.1016/j.isci.2022.105809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 07/20/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022] Open
Abstract
Cells constantly respond to environmental changes by modulating gene expression programs. These responses may demand substantial costs and, thus, affect cell growth. Understanding the regulation of these processes represents a key question in biology and biotechnology. Here, we studied the responses to osmotic stress in glucose-limited environments. By analyzing seventeen osmotic stress-induced genes and stress-activated protein kinase Hog1, we found that cells exhibited stronger osmotic gene expression response and larger integral of Hog1 nuclear localization during adaptation to osmotic stress under glucose-limited conditions than under glucose-rich conditions. We proposed and verified that in glucose-limited environment, glycolysis intermediates (representing "reserve flux") were limited, which required cells to express more glycerol-production enzymes for stress adaptation. Consequently, the regulatory mechanism of osmoresponse was derived in the presence and absence of such reserve flux. Further experiments suggested that this reserve flux-dependent stress-defense strategy may be a general principle under nutrient-limited environments.
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5
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Microfluidic-Enabled Multi-Cell-Densities-Patterning and Culture Device for Characterization of Yeast Strains’ Growth Rates under Mating Pheromone. CHEMOSENSORS 2022. [DOI: 10.3390/chemosensors10040141] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Yeast studies usually focus on exploring diversity in terms of a specific trait (such as growth rate, antibiotic resistance, or fertility) among extensive strains. Microfluidic chips improve these biological studies in a manner of high throughput and high efficiency. For a population study of yeast, it is of great significance to set a proper initial cell density for every strain under specific circumstances. Herein, we introduced a novel design of chip, which enables users to load cells in a gradient order (six alternatives) of initial cell density within one channel. We discussed several guidelines to choose the appropriate chamber to ensure successful data recording. With this chip, we successfully studied the growth rate of yeast strains under a mating response, which is crucial for yeasts to control growth behaviors for prosperous mating. We investigated the growth rate of eight different yeast strains under three different mating pheromone levels (0.3 μM, 1 μM, and 10 μM). Strains with, even, a six-fold in growth rate can be recorded, with the available data produced simultaneously. This work has provided an efficient and time-saving microfluidic platform, which enables loading cells in a pattern of multi-cell densities for a yeast population experiment, especially for a high-throughput study. Besides, a quantitatively analyzed growth rate of different yeast strains shall reveal inspiring perspectives for studies concerning yeast population behavior with a stimulated mating pheromone.
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6
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Wu Y, Wu J, Deng M, Lin Y. Yeast cell fate control by temporal redundancy modulation of transcription factor paralogs. Nat Commun 2021; 12:3145. [PMID: 34035307 PMCID: PMC8149833 DOI: 10.1038/s41467-021-23425-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 04/28/2021] [Indexed: 11/19/2022] Open
Abstract
Recent single-cell studies have revealed that yeast stress response involves transcription factors that are activated in pulses. However, it remains unclear whether and how these dynamic transcription factors temporally interact to regulate stress survival. Here we show that budding yeast cells can exploit the temporal relationship between paralogous general stress regulators, Msn2 and Msn4, during stress response. We find that individual pulses of Msn2 and Msn4 are largely redundant, and cells can enhance the expression of their shared targets by increasing their temporal divergence. Thus, functional redundancy between these two paralogs is modulated in a dynamic manner to confer fitness advantages for yeast cells, which might feed back to promote the preservation of their redundancy. This evolutionary implication is supported by evidence from Msn2/Msn4 orthologs and analyses of other transcription factor paralogs. Together, we show a cell fate control mechanism through temporal redundancy modulation in yeast, which may represent an evolutionarily important strategy for maintaining functional redundancy between gene duplicates.
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Affiliation(s)
- Yan Wu
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Mathematical Sciences, Peking University, Beijing, China
| | - Jiaqi Wu
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Minghua Deng
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- School of Mathematical Sciences, Peking University, Beijing, China
- Center for Statistical Science, Peking University, Beijing, China
| | - Yihan Lin
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
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7
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Chen K, Shen W, Zhang Z, Xiong F, Ouyang Q, Luo C. Age-dependent decline in stress response capacity revealed by proteins dynamics analysis. Sci Rep 2020; 10:15211. [PMID: 32939000 PMCID: PMC7494919 DOI: 10.1038/s41598-020-72167-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 08/21/2020] [Indexed: 02/06/2023] Open
Abstract
The aging process is regarded as the progressive loss of physiological integrity, leading to impaired biological functions and the increased vulnerability to death. Among various biological functions, stress response capacity enables cells to alter gene expression patterns and survive when facing internal and external stresses. Here, we explored changes in stress response capacity during the replicative aging of Saccharomyces cerevisiae. To this end, we used a high-throughput microfluidic device to deliver intermittent pulses of osmotic stress and tracked the dynamic changes in the production of downstream stress-responsive proteins, in a large number of individual aging cells. Cells showed a gradual decline in stress response capacity of these osmotic-related downstream proteins during the aging process after the first 5 generations. Among the downstream stress-responsive genes and unrelated genes tested, the residual level of response capacity of Trehalose-6-Phosphate Synthase (TPS2) showed the best correlation with the cell remaining lifespan. By monitor dynamics of the upstream transcription factors and mRNA of Tps2, it was suggested that the decline in downstream stress response capacity was caused by the decline of translational rate of these proteins during aging.
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Affiliation(s)
- Kaiyue Chen
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, China.,Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Wenting Shen
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Zhiwen Zhang
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, China
| | - Fangzheng Xiong
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, China
| | - Qi Ouyang
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, China.,Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Chunxiong Luo
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, China. .,Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
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8
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Abstract
Cells can rapidly adapt to changing environments through nongenetic processes; however, the metabolic cost of such adaptation has never been considered. Here we demonstrate metabolic coupling in a remarkable, rapid adaptation process (1 in 1,000 cells adapt per hour) by simultaneously measuring metabolism and division of thousands of individual Saccharomyces cerevisiae cells using a droplet microfluidic system: droplets containing single cells are immobilized in a two-dimensional (2D) array, with osmotically induced changes in droplet volume being used to measure cell metabolism, while simultaneously imaging the cells to measure division. Following a severe challenge, most cells, while not dividing, continue to metabolize, displaying a remarkably wide diversity of metabolic trajectories from which adaptation events can be anticipated. Adaptation requires a characteristic amount of energy, indicating that it is an active process. The demonstration that metabolic trajectories predict a priori adaptation events provides evidence of tight energetic coupling between metabolism and regulatory reorganization in adaptation. This process allows S. cerevisiae to adapt on a physiological timescale, but related phenomena may also be important in other processes, such as cellular differentiation, cellular reprogramming, and the emergence of drug resistance in cancer.
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9
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Abstract
Living cell microarrays in microfluidic chips allow the non-invasive multiplexed molecular analysis of single cells. Here, we developed a simple and affordable perfusion microfluidic chip containing a living yeast cell array composed of a population of cell variants (green fluorescent protein (GFP)-tagged Saccharomyces cerevisiae clones). We combined mechanical patterning in 102 microwells and robotic piezoelectric cell dispensing in the microwells to construct the cell arrays. Robotic yeast cell dispensing of a yeast collection from a multiwell plate to the microfluidic chip microwells was optimized. The developed microfluidic chip and procedure were validated by observing the growth of GFP-tagged yeast clones that are linked to the cell cycle by time-lapse fluorescence microscopy over a few generations. The developed microfluidic technology has the potential to be easily upscaled to a high-density cell array allowing us to perform dynamic proteomics and localizomics experiments.
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10
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Graham G, Csicsery N, Stasiowski E, Thouvenin G, Mather WH, Ferry M, Cookson S, Hasty J. Genome-scale transcriptional dynamics and environmental biosensing. Proc Natl Acad Sci U S A 2020; 117:3301-3306. [PMID: 31974311 PMCID: PMC7022183 DOI: 10.1073/pnas.1913003117] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Genome-scale technologies have enabled mapping of the complex molecular networks that govern cellular behavior. An emerging theme in the analyses of these networks is that cells use many layers of regulatory feedback to constantly assess and precisely react to their environment. The importance of complex feedback in controlling the real-time response to external stimuli has led to a need for the next generation of cell-based technologies that enable both the collection and analysis of high-throughput temporal data. Toward this end, we have developed a microfluidic platform capable of monitoring temporal gene expression from over 2,000 promoters. By coupling the "Dynomics" platform with deep neural network (DNN) and associated explainable artificial intelligence (XAI) algorithms, we show how machine learning can be harnessed to assess patterns in transcriptional data on a genome scale and identify which genes contribute to these patterns. Furthermore, we demonstrate the utility of the Dynomics platform as a field-deployable real-time biosensor through prediction of the presence of heavy metals in urban water and mine spill samples, based on the the dynamic transcription profiles of 1,807 unique Escherichia coli promoters.
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Affiliation(s)
- Garrett Graham
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093
| | - Nicholas Csicsery
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093
| | - Elizabeth Stasiowski
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093
| | - Gregoire Thouvenin
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093
| | | | | | | | - Jeff Hasty
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093;
- Quantitative BioSciences, Inc., San Diego, CA 92121
- Molecular Biology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093
- BioCircuits Institute, University of California San Diego, La Jolla, CA 92093
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11
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Affiliation(s)
- Iulia M. Lazar
- Department of Biological Sciences, Academy of Integrated Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States
- Carilion School of Medicine, Academy of Integrated Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Nicholas S. Gulakowski
- Systems Biology, Academy of Integrated Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States
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12
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Kasai Y, Sakuma S, Arai F. High-Speed On-Chip Mixing by Microvortex Generated by Controlling Local Jet Flow Using Dual Membrane Pumps. IEEE Robot Autom Lett 2019. [DOI: 10.1109/lra.2019.2921696] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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13
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Zhao X, Luo C, Wang H. Protein dynamic analysis of the budding yeast sporulation process at the single-cell level in an air-enriched microfluidic device. Integr Biol (Camb) 2019. [DOI: 10.1093/intbio/zyz007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Xiang Zhao
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, China
| | - Chunxiong Luo
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, China
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, China
| | - Hongli Wang
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, China
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, China
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14
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Bai Y, Gao M, Wen L, He C, Chen Y, Liu C, Fu X, Huang S. Applications of Microfluidics in Quantitative Biology. Biotechnol J 2017; 13:e1700170. [PMID: 28976637 DOI: 10.1002/biot.201700170] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Revised: 09/03/2017] [Indexed: 01/15/2023]
Abstract
Quantitative biology is dedicated to taking advantage of quantitative reasoning and advanced engineering technologies to make biology more predictable. Microfluidics, as an emerging technique, provides new approaches to precisely control fluidic conditions on small scales and collect data in high-throughput and quantitative manners. In this review, the authors present the relevant applications of microfluidics to quantitative biology based on two major categories (channel-based microfluidics and droplet-based microfluidics), and their typical features. We also envision some other microfluidic techniques that may not be employed in quantitative biology right now, but have great potential in the near future.
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Affiliation(s)
- Yang Bai
- Center for Synthetic Biology Engineering Research, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Meng Gao
- Center for Synthetic Biology Engineering Research, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Lingling Wen
- Center for Synthetic Biology Engineering Research, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Caiyun He
- Center for Synthetic Biology Engineering Research, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Yuan Chen
- Center for Synthetic Biology Engineering Research, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Chenli Liu
- Center for Synthetic Biology Engineering Research, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Xiongfei Fu
- Center for Synthetic Biology Engineering Research, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Shuqiang Huang
- Center for Synthetic Biology Engineering Research, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
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