scholarly journals Blood Identification at the Single-Cell Level Based on a Combination of Laser Tweezers Raman Spectroscopy and Machine Learning

2021 ◽  
Author(s):  
ziqi wang ◽  
Yiming Liu ◽  
Weilai Lu ◽  
Yu Vincent Fu ◽  
Zhou Zhehai
Keyword(s):  
Machine Learning ◽  
Raman Spectroscopy ◽  
Single Cell ◽  
Laser Tweezers ◽  
Single Cell Level ◽  
Cell Level

Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level

Talanta ◽  
2021 ◽  
Vol 226 ◽  
pp. 122195
Author(s):  
Shuaishuai Yan ◽  
Shuying Wang ◽  
Jingxuan Qiu ◽  
Menghua Li ◽  
Dezhi Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Raman Spectroscopy ◽  
Single Cell ◽  
Rapid Detection ◽  
Single Cell Level ◽  
Cell Level ◽  
Food Borne Pathogens ◽  
Food Borne

Monitoring human leukocyte antigen class I molecules by micro-Raman spectroscopy at single-cell level

2010 ◽  
Vol 15 (2) ◽  
pp. 027007 ◽  
Author(s):  
Gobind Das ◽  
Rosanna La Rocca ◽  
Tadepally Lakshmikanth ◽  
Francesco Gentile ◽  
Rossana Tallerico ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Human Leukocyte Antigen ◽  
Single Cell ◽  
Human Leukocyte Antigen Class ◽  
Human Leukocyte ◽  
Class I ◽  
Single Cell Level ◽  
Cell Level ◽  
Leukocyte Antigen ◽  
Micro Raman Spectroscopy

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.

Alterations of Raman profiles of nasopharyngeal carcinoma cells after treated with chemodrugs detected by laser tweezer Raman spectroscopy.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15513-e15513
Author(s):  
Miaomiao Li ◽  
Xiaochuan Chen ◽  
Ting Lin ◽  
Zongwei Huang ◽  
Shihong Wu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Nasopharyngeal Carcinoma ◽  
Single Cell ◽  
Control Group ◽  
Single Cell Level ◽  
Label Free ◽  
Cell Level ◽  
Analytical Strategy ◽  
Linear Discriminant ◽  
Laser Tweezer

e15513 Background: To explore the metabolic alterations of nasopharyngeal carcinoma (NPC) cells after treated with chemodrugs, the Raman profiles were characterized with laser tweezer Raman spectroscopy. Methods: Two NPC cell lines (CNE2 and C666-1) were treated with gemcitabine, cisplatin, and paclitaxel, respectively. The high-quality Raman spectra of cells without or with treatments were recorded at the single-cell level with label-free laser tweezers Raman spectroscopy (LTRS) and analyzed for the differences of alterations of Raman profiles. Results: Tentative assignments of Raman peaks indicated that the cellular specific biomolecular changes associated with drug treatment, including changes in protein structure (e.g. 1655 cm−1), changes in DNA content and structure (e.g. 830 cm−1), destruction of DNA base pairs (e.g. 785 cm−1), and reduction in lipids (e.g. 970 cm−1). Besides, both principal components analysis (PCA) combined with linear discriminant analysis (LDA) and the classification and regression trees (CRT) algorithms were employed to further analyze and classify the spectral data between control group and treated group, with the best discriminant accuracy of 96.7% and 90.0% for CNE2 and C666-1 group treated with paclitaxel, respectively. Conclusions: This exploratory work demonstrated that LTRS technology combined with multivariate statistical analysis has promising potential to be a novel analytical strategy at the single-cell level for the evaluation of NPC-related chemotherapeutic drugs.

Identification Of Pathogenic Bacteria Extracted From Milk On Single-Cell-Level By Means Of Micro-Raman Spectroscopy

2010 ◽  
Author(s):  
Susann Meisel ◽  
Stephan Stöckel ◽  
Mandy Elschner ◽  
Falk Melzer ◽  
Petra Rösch ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Single Cell ◽  
Pathogenic Bacteria ◽  
Single Cell Level ◽  
Cell Level ◽  
Micro Raman Spectroscopy

scholarly journals Discriminating Bacterial Phenotypes at the Population and Single‐Cell Level: A Comparison of Flow Cytometry and Raman Spectroscopy Fingerprinting

2019 ◽  
Vol 97 (7) ◽  
pp. 713-726 ◽  
Author(s):  
Cristina García‐Timermans ◽  
Peter Rubbens ◽  
Jasmine Heyse ◽  
Frederiek‐Maarten Kerckhof ◽  
Ruben Props ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Raman Spectroscopy ◽  
Single Cell ◽  
Single Cell Level ◽  
Cell Level

Apoptosis Process under High Concentrations of Ethanol Stress at a Single Cell Level with Raman Spectroscopy

2014 ◽  
Vol 43 (6) ◽  
pp. 630005
Author(s):  
WANG Qiaozhen LU Mingqian ◽  
LI Bing ◽  
LIAO Wei ◽  
SHI Guiyu ◽  
HUANG Shushi
Keyword(s):  
Raman Spectroscopy ◽  
Single Cell ◽  
Ethanol Stress ◽  
Single Cell Level ◽  
Cell Level ◽  
High Concentrations ◽  
Apoptosis Process

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.

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