scholarly journals Non-Linear Cellular Dielectrophoretic Behavior Characterization Using Dielectrophoretic Tweezers-Based Force Spectroscopy inside a Microfluidic Device

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3543 ◽  
Author(s):  
Seungyeop Choi ◽  
Kwanhwi Ko ◽  
Jongwon Lim ◽  
Sung Kim ◽  
Sung-Hun Woo ◽  
...  
Keyword(s):  
Force Spectroscopy ◽  
Living Cells ◽  
Nonlinear Property ◽  
Single Cell Level ◽  
Cell Level ◽  
Ac Electric Field ◽  
Non Linear ◽  
Cellular Behaviors ◽  
Frequency Modulations

Characterization of cellular dielectrophoretic (DEP) behaviors, when cells are exposed to an alternating current (AC) electric field of varying frequency, is fundamentally important to many applications using dielectrophoresis. However, to date, that characterization has been performed with monotonically increasing or decreasing frequency, not with successive increases and decreases, even though cells might behave differently with those frequency modulations due to the nonlinear cellular electrodynamic responses reported in previous works. In this report, we present a method to trace the behaviors of numerous cells simultaneously at the single-cell level in a simple, robust manner using dielectrophoretic tweezers-based force spectroscopy. Using this method, the behaviors of more than 150 cells were traced in a single environment at the same time, while a modulated DEP force acted upon them, resulting in characterization of nonlinear DEP cellular behaviors and generation of different cross-over frequencies in living cells by modulating the DEP force. This study demonstrated that living cells can have non-linear di-polarized responses depending on the modulation direction of the applied frequency as well as providing a simple and reliable platform from which to measure a cellular cross-over frequency and characterize its nonlinear property.

scholarly journals Effect of Laser Irradiation on Cell Function and Its Implications in Raman Spectroscopy

2018 ◽  
Vol 84 (8) ◽  
pp. e02508-17 ◽  
Author(s):  
Xiaofei Yuan ◽  
Yanqing Song ◽  
Yizhi Song ◽  
Jiabao Xu ◽  
Yinhu Wu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Cell Growth ◽  
Single Cell ◽  
Laser Irradiation ◽  
Living Cells ◽  
Growth Characteristics ◽  
Single Cell Level ◽  
Bacterial Cells ◽  
Cell Level ◽  
Gram Negative

ABSTRACTLasers are instrumental in advanced bioimaging and Raman spectroscopy. However, they are also well known for their destructive effects on living organisms, leading to concerns about the adverse effects of laser technologies. To implement Raman spectroscopy for cell analysis and manipulation, such as Raman-activated cell sorting, it is crucial to identify nondestructive conditions for living cells. Here, we evaluated quantitatively the effect of 532-nm laser irradiation on bacterial cell fate and growth at the single-cell level. Using a purpose-built microfluidic platform, we were able to quantify the growth characteristics, i.e., specific growth rates and lag times of individual cells, as well as the survival rate of a population in conjunction with Raman spectroscopy. Representative Gram-negative and Gram-positive species show similar trends in response to a laser irradiation dose. Laser irradiation could compromise the physiological function of cells, and the degree of destruction is both dose and strain dependent, ranging from reduced cell growth to a complete loss of cell metabolic activity and finally to physical disintegration. Gram-positive bacterial cells are more susceptible than Gram-negative bacterial strains to irradiation-induced damage. By directly correlating Raman acquisition with single-cell growth characteristics, we provide evidence of nondestructive characteristics of Raman spectroscopy on individual bacterial cells. However, while strong Raman signals can be obtained without causing cell death, the variety of responses from different strains and from individual cells justifies careful evaluation of Raman acquisition conditions if cell viability is critical.IMPORTANCEIn Raman spectroscopy, the use of powerful monochromatic light in laser-based systems facilitates the detection of inherently weak signals. This allows environmentally and clinically relevant microorganisms to be measured at the single-cell level. The significance of being able to perform Raman measurement is that, unlike label-based fluorescence techniques, it provides a “fingerprint” that is specific to the identity and state of any (unlabeled) sample. Thus, it has emerged as a powerful method for studying living cells under physiological and environmental conditions. However, the laser's high power also has the potential to kill bacteria, which leads to concerns. The research presented here is a quantitative evaluation that provides a generic platform and methodology to evaluate the effects of laser irradiation on individual bacterial cells. Furthermore, it illustrates this by determining the conditions required to nondestructively measure the spectra of representative bacteria from several different groups.

scholarly journals Characterization of the development of the mouse cochlear epithelium at the single cell level

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Likhitha Kolla ◽  
Michael C. Kelly ◽  
Zoe F. Mann ◽  
Alejandro Anaya-Rocha ◽  
Kathryn Ellis ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Level ◽  
Cell Level

scholarly journals Cross-Tissue Characterization of Heterogeneities of Mesenchymal Stem Cells and Their Differentiation Potentials

2021 ◽  
Vol 9 ◽  
Author(s):  
Wenhong Hou ◽  
Li Duan ◽  
Changyuan Huang ◽  
Xingfu Li ◽  
Xiao Xu ◽  
...  
Keyword(s):  
Single Cell ◽  
Umbilical Cord ◽  
Stromal Cells ◽  
Tissue Characterization ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Cell Sources ◽  
Cell Subpopulations

Mesenchymal stem/stromal cells (MSCs) are promising cell sources for regenerative medicine and the treatment of autoimmune disorders. Comparing MSCs from different tissues at the single-cell level is fundamental for optimizing clinical applications. Here we analyzed single-cell RNA-seq data of MSCs from four tissues, namely umbilical cord, bone marrow, synovial tissue, and adipose tissue. We identified three major cell subpopulations, namely osteo-MSCs, chondro-MSCs, and adipo/myo-MSCs, across all MSC samples. MSCs from the umbilical cord exhibited the highest immunosuppression, potentially indicating it is the best immune modulator for autoimmune diseases. MSC subpopulations, with different subtypes and tissue sources, showed pronounced differences in differentiation potentials. After we compared the cell subpopulations and cell status pre-and-post chondrogenesis induction, osteogenesis induction, and adipogenesis induction, respectively, we found MSC subpopulations expanded and differentiated when their subtypes consist with induction directions, while the other subpopulations shrank. We identified the genes and transcription factors underlying each induction at the single-cell level and subpopulation level, providing better targets for improving induction efficiency.

scholarly journals Application of Imaging Flow Cytometry for the Characterization of Intracellular Attributes in Chinese Hamster Ovary Cell Lines at the Single‐Cell Level

2019 ◽  
Vol 14 (7) ◽  
pp. 1800675 ◽  
Author(s):  
Eva Pekle ◽  
Andrew Smith ◽  
Guglielmo Rosignoli ◽  
Christopher Sellick ◽  
C. M. Smales ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Single Cell ◽  
Cell Lines ◽  
Chinese Hamster Ovary ◽  
Chinese Hamster ◽  
Ovary Cell ◽  
Single Cell Level ◽  
Cell Level ◽  
Imaging Flow Cytometry

Surface-enhanced Raman spectroscopy of microorganisms: limitations and applicability on the single-cell level

The Analyst ◽  
2019 ◽  
Vol 144 (3) ◽  
pp. 943-953 ◽  
Author(s):  
Ruben Weiss ◽  
Márton Palatinszky ◽  
Michael Wagner ◽  
Reinhard Niessner ◽  
Martin Elsner ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Single Cell ◽  
Environmental Studies ◽  
Surface Enhanced Raman Spectroscopy ◽  
Clinical Diagnostics ◽  
Single Cell Level ◽  
Cell Level ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Detection and characterization of microorganisms is essential for both clinical diagnostics and environmental studies.

scholarly journals Identifying tumor cells at the single cell level

2021 ◽  
Author(s):  
Jan Dohmen ◽  
Artem Baranovskii ◽  
Bora Uyar ◽  
Jonathan Ronen ◽  
Vedran Franke ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Biomarker Discovery ◽  
Single Cell Analysis ◽  
High Sensitivity ◽  
Simple Problem ◽  
Cancer Therapies ◽  
Single Cell Level ◽  
Cell Level

Tumors are highly complex tissues composed of cancerous cells, surrounded by a heterogeneous cellular microenvironment. Tumor response to treatments is governed by an interaction of cancer cell intrinsic factors with external influences of the tumor microenvironment. Disentangling the heterogeneity within a tumor is a crucial step in developing and utilization of effective cancer therapies. Single cell sequencing has the potential to revolutionize personalized medicine. In cancer therapy it enables an effective characterization of the complete heterogeneity within the tumor. A governing challenge in cancer single cell analysis is cell annotation, the assignment of a particular cell type or a cell state to each sequenced cell. We propose Ikarus, a machine learning pipeline aimed at solving a perceived simple problem, distinguishing tumor cells from normal cells at the single cell level. Automatic characterization of tumor cells is a critical limiting step for a multitude of research, clinical, and commercial applications. Automatic characterization of tumor cells would expedite neoantigen prediction, automatic characterization of tumor cell states, it would greatly facilitate cancer biomarker discovery. Such a tool can be used for automatic annotation of histopathological data, profiled using multichannel immunofluorescence or spatial sequencing. We have tested ikarus on multiple single cell datasets to ascertain that it achieves high sensitivity and specificity in multiple experimental contexts.

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