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Sensors for Cell Analysis
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Sensors for Cell Analysis

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (30 July 2018) | Viewed by 34839

Special Issue Editor

Prof. Dr. Kosuke Ino

E-Mail Website
Guest Editor
Graduate School of Engineering, Tohoku University, 6-6-11 Aramaki-aza Aoba, Aoba-ku, Sendai 980-8579, Japan
Interests: cell analysis; electrochemical devices; bioMEMS/NEMS; organs on a chip; cell culture platforms; micro/nanochemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cell analysis has received considerable interest for drug discovery, cancer cell research, stem cell research, environmental monitoring, healthcare, and tissue engineering. For cell analysis, several kinds of sensors have been developed. Especially, MEMS/NEMS-based sensors and micro/nanochemistry-based sensors are progressing rapidly. These sensors are utilized for high-throughput cell screening and highly-sensitive assays. In addition, paper-based devices and small chip devices have been developed for low-cost assays and the simple process of cell analysis. This Special Issue focuses on research and development in the field of sensors and methods for cell analysis. The Special Issue will cover research topics from single cell analysis to evaluation of three-dimensional cultured cells resembling organs. I will also welcome microfluidics, electrochemical devices, optical sensors, organs on a chip containing sensing systems, and more.

I would like to invite you to submit both original research papers and review articles on sensors for cell analysis.

Dr. Kosuke Ino
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cell analysis
  • MEMS/NEMS
  • electrochemical sensors
  • microfludic devices
  • micro/nanochemistry
  • chip devices
  • organs on a chip
  • cell culture platforms

Published Papers (7 papers)

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Research

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11 pages, 1095 KiB  
Article
Extracellular Electrophysiology in the Prostate Cancer Cell Model PC-3
by Miguel Cabello, Haobo Ge, Carmen Aracil, Despina Moschou, Pedro Estrela, Jose Manuel Quero, Sofia I. Pascu and Paulo R. F. Rocha
Sensors 2019, 19(1), 139; https://doi.org/10.3390/s19010139 - 03 Jan 2019
Cited by 18 | Viewed by 5313
Abstract
Although prostate cancer is one of the most common cancers in the male population, its basic biological function at a cellular level remains to be fully understood. This lack of in depth understanding of its physiology significantly hinders the development of new, targeted [...] Read more.
Although prostate cancer is one of the most common cancers in the male population, its basic biological function at a cellular level remains to be fully understood. This lack of in depth understanding of its physiology significantly hinders the development of new, targeted and more effective treatment strategies. Whilst electrophysiological studies can provide in depth analysis, the possibility of recording electrical activity in large populations of non-neuronal cells remains a significant challenge, even harder to address in the picoAmpere-range, which is typical of cellular level electrical activities. In this paper, we present the measurement and characterization of electrical activity of populations of prostate cancer cells PC-3, demonstrating for the first time a meaningful electrical pattern. The low noise system used comprises a multi-electrode array (MEA) with circular gold electrodes on silicon oxide substrates. The extracellular capacitive currents present two standard patterns: an asynchronous sporadic pattern and a synchronous quasi-periodic biphasic spike pattern. An amplitude of ±150 pA, a width between 50–300 ms and an inter-spike interval around 0.5 Hz characterize the quasi-periodic spikes. Our experiments using treatment of cells with Gd3⁺, known as an inhibitor for the Ca2⁺ exchanges, suggest that the quasi-periodic signals originate from Ca2⁺ channels. After adding the Gd3⁺ to a population of living PC-3 cells, their electrical activity considerably decreased; once the culture was washed, thus eliminating the Gd3⁺ containing medium and addition of fresh cellular growth medium, the PC-3 cells recovered their normal electrical activity. Cellular viability plots have been carried out, demonstrating that the PC-3 cells remain viable after the use of Gd3⁺, on the timescale of this experiment. Hence, this experimental work suggests that Ca2⁺ is significantly affecting the electrophysiological communication pattern among PC-3 cell populations. Our measuring platform opens up new avenues for real time and highly sensitive investigations of prostate cancer signalling pathways. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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8 pages, 1369 KiB  
Communication
Label-Free Rapid Separation and Enrichment of Bone Marrow-Derived Mesenchymal Stem Cells from a Heterogeneous Cell Mixture Using a Dielectrophoresis Device
by Junya Yoshioka, Yu Ohsugi, Toru Yoshitomi, Tomoyuki Yasukawa, Naoki Sasaki and Keitaro Yoshimoto
Sensors 2018, 18(9), 3007; https://doi.org/10.3390/s18093007 - 08 Sep 2018
Cited by 17 | Viewed by 3734
Abstract
Bone marrow-derived mesenchymal stem cells (BMSCs) are an important cell resource for stem cell-based therapy, which are generally isolated and enriched by the density-gradient method based on cell size and density after collection of tissue samples. Since this method has limitations with regards [...] Read more.
Bone marrow-derived mesenchymal stem cells (BMSCs) are an important cell resource for stem cell-based therapy, which are generally isolated and enriched by the density-gradient method based on cell size and density after collection of tissue samples. Since this method has limitations with regards to purity and repeatability, development of alternative label-free methods for BMSC separation is desired. In the present study, rapid label-free separation and enrichment of BMSCs from a heterogeneous cell mixture with bone marrow-derived promyelocytes was successfully achieved using a dielectrophoresis (DEP) device comprising saw-shaped electrodes. Upon application of an electric field, HL-60 cells as models of promyelocytes aggregated and floated between the saw-shaped electrodes, while UE7T-13 cells as models of BMSCs were effectively captured on the tips of the saw-shaped electrodes. After washing out the HL-60 cells from the device selectively, the purity of the UE7T-13 cells was increased from 33% to 83.5% within 5 min. Although further experiments and optimization are required, these results show the potential of the DEP device as a label-free rapid cell isolation system yielding high purity for rare and precious cells such as BMSCs. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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12 pages, 1695 KiB  
Article
Colony Fingerprint-Based Discrimination of Staphylococcus species with Machine Learning Approaches
by Yoshiaki Maeda, Yui Sugiyama, Atsushi Kogiso, Tae-Kyu Lim, Manabu Harada, Tomoko Yoshino, Tadashi Matsunaga and Tsuyoshi Tanaka
Sensors 2018, 18(9), 2789; https://doi.org/10.3390/s18092789 - 24 Aug 2018
Cited by 10 | Viewed by 4107
Abstract
Detection and discrimination of bacteria are crucial in a wide range of industries, including clinical testing, and food and beverage production. Staphylococcus species cause various diseases, and are frequently detected in clinical specimens and food products. In particular, S. aureus is well known [...] Read more.
Detection and discrimination of bacteria are crucial in a wide range of industries, including clinical testing, and food and beverage production. Staphylococcus species cause various diseases, and are frequently detected in clinical specimens and food products. In particular, S. aureus is well known to be the most pathogenic species. Conventional phenotypic and genotypic methods for discrimination of Staphylococcus spp. are time-consuming and labor-intensive. To address this issue, in the present study, we applied a novel discrimination methodology called colony fingerprinting. Colony fingerprinting discriminates bacterial species based on the multivariate analysis of the images of microcolonies (referred to as colony fingerprints) with a size of up to 250 μm in diameter. The colony fingerprints were obtained via a lens-less imaging system. Profiling of the colony fingerprints of five Staphylococcus spp. (S. aureus, S. epidermidis, S. haemolyticus, S. saprophyticus, and S. simulans) revealed that the central regions of the colony fingerprints showed species-specific patterns. We developed 14 discriminative parameters, some of which highlight the features of the central regions, and analyzed them by several machine learning approaches. As a result, artificial neural network (ANN), support vector machine (SVM), and random forest (RF) showed high performance for discrimination of theses bacteria. Bacterial discrimination by colony fingerprinting can be performed within 11 h, on average, and therefore can cut discrimination time in half compared to conventional methods. Moreover, we also successfully demonstrated discrimination of S. aureus in a mixed culture with Pseudomonas aeruginosa. These results suggest that colony fingerprinting is useful for discrimination of Staphylococcus spp. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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16 pages, 4134 KiB  
Article
An Empirical-Mathematical Approach for Calibration and Fitting Cell-Electrode Electrical Models in Bioimpedance Tests
by Juan A. Serrano, Gloria Huertas, Andrés Maldonado-Jacobi, Alberto Olmo, Pablo Pérez, María E. Martín, Paula Daza and Alberto Yúfera
Sensors 2018, 18(7), 2354; https://doi.org/10.3390/s18072354 - 20 Jul 2018
Cited by 12 | Viewed by 3434
Abstract
This paper proposes a new yet efficient method allowing a significant improvement in the on-line analysis of biological cell growing and evolution. The procedure is based on an empirical-mathematical approach for calibration and fitting of any cell-electrode electrical model. It is valid and [...] Read more.
This paper proposes a new yet efficient method allowing a significant improvement in the on-line analysis of biological cell growing and evolution. The procedure is based on an empirical-mathematical approach for calibration and fitting of any cell-electrode electrical model. It is valid and can be extrapolated for any type of cellular line used in electrical cell-substrate impedance spectroscopy (ECIS) tests. Parameters of the bioimpedance model, acquired from ECIS experiments, vary for each cell line, which makes obtaining results difficult and—to some extent-renders them inaccurate. We propose a fitting method based on the cell line initial characterization, and carry out subsequent experiments with the same line to approach the percentage of well filling and the cell density (or cell number in the well). To perform our calibration technique, the so-called oscillation-based test (OBT) approach is employed for each cell density. Calibration results are validated by performing other experiments with different concentrations on the same cell line with the same measurement technique. Accordingly, a bioimpedance electrical model of each cell line is determined, which is valid for any further experiment and leading to a more precise electrical model of the electrode-cell system. Furthermore, the model parameters calculated can be also used by any other measurement techniques. Promising experimental outcomes for three different cell-lines have been achieved, supporting the usefulness of this technique. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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10 pages, 2952 KiB  
Article
Near Real-Time Detection of E. coli in Reclaimed Water
by Samendra Sherchan, Syreeta Miles, Luisa Ikner, Hye-Weon Yu, Shane A. Snyder and Ian L. Pepper
Sensors 2018, 18(7), 2303; https://doi.org/10.3390/s18072303 - 16 Jul 2018
Cited by 17 | Viewed by 3681
Abstract
Advanced treatment of reclaimed water prior to potable reuse normally results in the inactivation of bacterial populations, however, incremental treatment failure can result in bacteria, including pathogens, remaining viable. Therefore, potential microorganisms need to be detected in real-time to preclude potential adverse human [...] Read more.
Advanced treatment of reclaimed water prior to potable reuse normally results in the inactivation of bacterial populations, however, incremental treatment failure can result in bacteria, including pathogens, remaining viable. Therefore, potential microorganisms need to be detected in real-time to preclude potential adverse human health effects. Real-time detection of microbes presents unique problems which are dependent on the water quality of the test water, including parameters such as particulate content and turbidity, and natural organic matter content. In addition, microbes are unusual in that: (i) viability and culturability are not always synonymous; (ii) viability in water can be reduced by osmotic stress; and (iii) bacteria can invoke repair mechanisms in response to UV disinfection resulting in regrowth of bacterial populations. All these issues related to bacteria affect the efficacy of real-time detection for bacteria. Here we evaluate three different sensors suitable for specific water qualities. The sensor A is an on-line, real-time sensor that allows for the continuous monitoring of particulates (including microbial contaminants) using multi-angle-light scattering (MALS) technology. The sensor B is a microbial detection system that uses optical technique, Mie light scattering, for particle sizing and fluorescence emission for viable bacteria detection. The last sensor C was based on adenosine triphosphate (ATP) production. E. coli was used a model organism and out of all tested sensors, we found the sensor C to be the most accurate. It has a great potential as a surrogate parameter for microbial loads in test waters and be useful for process control in treatment trains. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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26 pages, 8583 KiB  
Article
Dielectric Spectroscopy and Optical Density Measurement for the Online Monitoring and Control of Recombinant Protein Production in Stably Transformed Drosophila melanogaster S2 Cells
by Jan Zitzmann, Tobias Weidner, Gerrit Eichner, Denise Salzig and Peter Czermak
Sensors 2018, 18(3), 900; https://doi.org/10.3390/s18030900 - 18 Mar 2018
Cited by 22 | Viewed by 8611
Abstract
The production of recombinant proteins in bioreactors requires real-time process monitoring and control to increase process efficiency and to meet the requirements for a comprehensive audit trail. The combination of optical near-infrared turbidity sensors and dielectric spectroscopy provides diverse system information because different [...] Read more.
The production of recombinant proteins in bioreactors requires real-time process monitoring and control to increase process efficiency and to meet the requirements for a comprehensive audit trail. The combination of optical near-infrared turbidity sensors and dielectric spectroscopy provides diverse system information because different measurement principles are exploited. We used this combination of techniques to monitor and control the growth and protein production of stably transformed Drosophila melanogaster S2 cells expressing antimicrobial proteins. The in situ monitoring system was suitable in batch, fed-batch and perfusion modes, and was particularly useful for the online determination of cell concentration, specific growth rate (µ) and cell viability. These data were used to pinpoint the optimal timing of the key transitional events (induction and harvest) during batch and fed-batch cultivation, achieving a total protein yield of ~25 mg at the 1-L scale. During cultivation in perfusion mode, the OD880 signal was used to control the bleed line in order to maintain a constant cell concentration of 5 × 107 cells/mL, thus establishing a turbidostat/permittistat culture. With this setup, a five-fold increase in productivity was achieved and 130 mg of protein was recovered after 2 days of induced perfusion. Our results demonstrate that both sensors are suitable for advanced monitoring and integration into online control strategies. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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Review

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17 pages, 3964 KiB  
Review
Nanobiosensing Platforms for Real-Time and Non-Invasive Monitoring of Stem Cell Pluripotency and Differentiation
by Intan Rosalina Suhito, Novi Angeline, Sung-Sik Choo, Ho Young Woo, Taejong Paik, Taek Lee and Tae-Hyung Kim
Sensors 2018, 18(9), 2755; https://doi.org/10.3390/s18092755 - 21 Aug 2018
Cited by 20 | Viewed by 5288
Abstract
Breakthroughs in the biomedical and regenerative therapy fields have led to the influential ability of stem cells to differentiate into specific types of cells that enable the replacement of injured tissues/organs in the human body. Non-destructive identification of stem cell differentiation is highly [...] Read more.
Breakthroughs in the biomedical and regenerative therapy fields have led to the influential ability of stem cells to differentiate into specific types of cells that enable the replacement of injured tissues/organs in the human body. Non-destructive identification of stem cell differentiation is highly necessary to avoid losses of differentiated cells, because most of the techniques generally used as confirmation tools for the successful differentiation of stem cells can result in valuable cells becoming irrecoverable. Regarding this issue, recent studies reported that both Raman spectroscopy and electrochemical sensing possess excellent characteristics for monitoring the behavior of stem cells, including differentiation. In this review, we focus on numerous studies that have investigated the detection of stem cell pluripotency and differentiation in non-invasive and non-destructive manner, mainly by using the Raman and electrochemical methods. Through this review, we present information that could provide scientific or technical motivation to employ or further develop these two techniques for stem cell research and its application. Full article
(This article belongs to the Special Issue Sensors for Cell Analysis)
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