Surface-Enhanced Raman Scattering for Label-Free Living Single Cell Analysis

Kuku, Gamze; Altunbek, Mine; Çulha, Mustafa

doi:10.1021/acs.analchem.7b03211

Cited by 50 publications

(54 citation statements)

References 82 publications

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“…Most biological experiments rely on bulk analysis that report on large cell population averages (millions of cells) and mask the presence of subpopulations, rare cells, and individual cellular variations. Measuring the distribution and the magnitude of biological noise is increasingly feasible through single cell analysis techniques, including fluorescence ( Paige et al, 2012 ), microfluidics ( Sibbitts et al, 2018 ), and Raman scattering ( Kuku et al, 2017 ). The limited size and volume of single cells, and the low copy numbers of certain analytes make detection, identification, and quantitation challenging.…”

Section: Introductionmentioning

confidence: 99%

Metabolic Noise and Distinct Subpopulations Observed by Single Cell LAESI Mass Spectrometry of Plant Cells in situ

et al. 2018

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Phenotypic variations and stochastic expression of transcripts, proteins, and metabolites in biological tissues lead to cellular heterogeneity. As a result, distinct cellular subpopulations emerge. They are characterized by different metabolite expression levels and by associated metabolic noise distributions. To capture these biological variations unperturbed, highly sensitive in situ analytical techniques are needed that can sample tissue embedded single cells with minimum sample preparation. Optical fiber-based laser ablation electrospray ionization mass spectrometry (f-LAESI-MS) is a promising tool for metabolic profiling of single cells under ambient conditions. Integration of this MS-based platform with fluorescence and brightfield microscopy provides the ability to target single cells of specific type and allows for the selection of rare cells, e.g., excretory idioblasts. Analysis of individual Egeria densa leaf blade cells (n = 103) by f-LAESI-MS revealed significant differences between the prespecified subpopulations of epidermal cells (n = 97) and excretory idioblasts (n = 6) that otherwise would have been masked by the population average. Primary metabolites, e.g., malate, aspartate, and ascorbate, as well as several glucosides were detected in higher abundance in the epidermal cells. The idioblasts contained lipids, e.g., PG(16:0/18:2), and triterpene saponins, e.g., medicoside I and azukisaponin I, and their isomers. Metabolic noise for the epidermal cells were compared to results for soybean (Glycine max) root nodule cells (n = 60) infected by rhizobia (Bradyrhizobium japonicum). Whereas some primary metabolites showed lower noise in the latter, both cell types exhibited higher noise for secondary metabolites. Post hoc grouping of epidermal and root nodule cells, based on the abundance distributions for certain metabolites (e.g., malate), enabled the discovery of cellular subpopulations characterized by different mean abundance values, and the magnitudes of the corresponding metabolic noise. Comparison of prespecified populations from epidermal cells of the closely related E. densa (n = 20) and Elodea canadensis (n = 20) revealed significant differences, e.g., higher sugar content in the former and higher levels of ascorbate in the latter, and the presence of species-specific metabolites. These results demonstrate that the f-LAESI-MS single cell analysis platform has the potential to explore cellular heterogeneity and metabolic noise for hundreds of tissue-embedded cells.

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Section: Introductionmentioning

confidence: 99%

Metabolic Noise and Distinct Subpopulations Observed by Single Cell LAESI Mass Spectrometry of Plant Cells in situ

et al. 2018

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“…Mustafa Çulha (Oregon Health & Science University, Portland, OR) described his team's effort to utilize surface-enhanced Raman spectroscopy (SERS) for label-free cancer diagnosis from "liquid-biopsy" at The Knight Cancer Institute's Cancer Early Detection Advanced Research Center, or CEDAR, in addition to the use of the technique for tissue differentiation [52][53][54]. SERS, a very sensitive mode of Raman Spectroscopy (RS), can provide label-free fingerprint molecular information from a molecular mixture.…”

Section: Nanodiagnostics and Nanotheranosticsmentioning

confidence: 99%

Advances in Translational Nanotechnology: Challenges and Opportunities

et al. 2020

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The burgeoning field of nanotechnology aims to create and deploy nanoscale structures, devices, and systems with novel, size-dependent properties and functions. The nanotechnology revolution has sparked radically new technologies and strategies across all scientific disciplines, with nanotechnology now applied to virtually every area of research and development in the US and globally. NanoFlorida was founded to create a forum for scientific exchange, promote networking among nanoscientists, encourage collaborative research efforts across institutions, forge strong industry-academia partnerships in nanoscience, and showcase the contributions of students and trainees in nanotechnology fields. The 2019 NanoFlorida International Conference expanded this vision to emphasize national and international participation, with a focus on advances made in translating nanotechnology. This review highlights notable research in the areas of engineering especially in optics, photonics and plasmonics and electronics; biomedical devices, nano-biotechnology, nanotherapeutics including both experimental nanotherapies and nanovaccines; nano-diagnostics and -theranostics; nano-enabled drug discovery platforms; tissue engineering, bioprinting, and environmental nanotechnology, as well as challenges and directions for future research.

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“…SERS is also a great technique for imaging single cells and several reviews have described this topic [310,311,312,313]. Raman microscopes allow for obtaining localised detection of Raman signals with good spatial resolution (currently down to submicrometer) enabling the imaging and mapping of samples.…”

Section: Nanoplasmonicsmentioning

confidence: 99%

Advanced Nanoscale Approaches to Single-(Bio)entity Sensing and Imaging

Neves

Martín‐Yerga

2018

Biosensors

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Individual (bio)chemical entities could show a very heterogeneous behaviour under the same conditions that could be relevant in many biological processes of significance in the life sciences. Conventional detection approaches are only able to detect the average response of an ensemble of entities and assume that all entities are identical. From this perspective, important information about the heterogeneities or rare (stochastic) events happening in individual entities would remain unseen. Some nanoscale tools present interesting physicochemical properties that enable the possibility to detect systems at the single-entity level, acquiring richer information than conventional methods. In this review, we introduce the foundations and the latest advances of several nanoscale approaches to sensing and imaging individual (bio)entities using nanoprobes, nanopores, nanoimpacts, nanoplasmonics and nanomachines. Several (bio)entities such as cells, proteins, nucleic acids, vesicles and viruses are specifically considered. These nanoscale approaches provide a wide and complete toolbox for the study of many biological systems at the single-entity level.

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Surface-Enhanced Raman Scattering for Label-Free Living Single Cell Analysis

Cited by 50 publications

References 82 publications

Metabolic Noise and Distinct Subpopulations Observed by Single Cell LAESI Mass Spectrometry of Plant Cells in situ

Metabolic Noise and Distinct Subpopulations Observed by Single Cell LAESI Mass Spectrometry of Plant Cells in situ

Advances in Translational Nanotechnology: Challenges and Opportunities

Advanced Nanoscale Approaches to Single-(Bio)entity Sensing and Imaging

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