Induction and measurement of the early stage of a host‐parasite interaction using a combined optical trapping and Raman microspectroscopy system

Sinjab, Faris; Elsheikha, Hany M.; Dooley, Max; Notingher, Ioan

doi:10.1002/jbio.201960065

Cited by 8 publications

(5 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They successfully demonstrated that OT-RS is capable of monitoring the chemical reaction of single particles [39]. Very recently, Sinjab et al applied OT Raman micro-spectroscopy to detect and monitor the molecular trafficking of a specific molecular species in the single cell [40]. This study demonstrated that OT-RS could be an effective method of detecting and monitoring biological processes.…”

Section: Introductionmentioning

confidence: 87%

Single-particle optical-trapping Raman spectroscopy for the detection and identification of aerosolized airborne biological particles

Alali

Pan

et al. 2021

Meas. Sci. Technol.

View full text Add to dashboard Cite

The detection and identification of bioaerosol particles, especially a potential threat from aerosolized biowarfare agents (BWAs), has become increasingly important. Here, we report on single-particle optical-trapping Raman spectroscopy (OT-RS) for the detection and identification of airborne biological particles. OT enables the capture of single particles in air for several minutes or longer, more than sufficient to capture the Raman spectra and minimize the interference from background aerosol particles. Simultaneously, the embedded imaging system can provide real-time information on the shape and size of the trapped particles. Several kinds of bioaerosol particles were analyzed using OT-RS including four BWA surrogates: Bacillus globigii, Yersinia rhodei, MS2, and Bacillus subtilis, along with some interfering bioaerosol particles commonly presented in the atmosphere. Similarities and differences of the Raman spectra of these biological particles are discussed. In addition, the BWA surrogates are well classified by using the principal component analysis. The results demonstrate that single-particle OT-RS can be used not only for the potential detection of BWAs but also for the identification of BWAs.

show abstract

Section: Introductionmentioning

confidence: 87%

Single-particle optical-trapping Raman spectroscopy for the detection and identification of aerosolized airborne biological particles

Alali

Pan

et al. 2021

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Another promising direction for label-free single-cell analysis is via measuring the inherent optical properties of cells. This has been shown in recent work such as the single-cell identification of parasites through their Raman spectra [125], the quantification of single-cell viral infection titer through Laser Force Cytology [126], and single bacteria detection via refractive index measurements [127]. Lastly, the mechanical and size properties of cells have also been exploited for identifying infected single cells.…”

Section: Label-free Analysismentioning

confidence: 98%

The Role of Single-Cell Technology in the Study and Control of Infectious Diseases

Lin

Tay

Lu³

et al. 2020

Cells

View full text Add to dashboard Cite

The advent of single-cell research in the recent decade has allowed biological studies at an unprecedented resolution and scale. In particular, single-cell analysis techniques such as Next-Generation Sequencing (NGS) and Fluorescence-Activated Cell Sorting (FACS) have helped show substantial links between cellular heterogeneity and infectious disease progression. The extensive characterization of genomic and phenotypic biomarkers, in addition to host–pathogen interactions at the single-cell level, has resulted in the discovery of previously unknown infection mechanisms as well as potential treatment options. In this article, we review the various single-cell technologies and their applications in the ongoing fight against infectious diseases, as well as discuss the potential opportunities for future development.

show abstract

“…76 More broadly in biology, it is fundamentally crucial to understand the temporal interactions of host and pathogens, where Raman spectroscopy can be employed to monitor the molecular trafficking at the single cell level in real-time. 142,143 Examples include tracking temporal changes in tissue composition upon bacterial infection, determining the outcome of infections. 144 Spatial Tissue Profiling.…”

Section: Single-cell Identification Using Sers and Ml: Bacterial Iden...mentioning

confidence: 99%

“…Supervised classification analysis revealed variations in lipid, nucleic acid, and collagen content resulting from each therapy, consistent with their distinct mechanisms of action . More broadly in biology, it is fundamentally crucial to understand the temporal interactions of host and pathogens, where Raman spectroscopy can be employed to monitor the molecular trafficking at the single cell level in real-time. , Examples include tracking temporal changes in tissue composition upon bacterial infection, determining the outcome of infections …”

Section: Single-cell Identification Using Sers and Ml: Bacterial Iden...mentioning

confidence: 99%

From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis

Zhang,

Chang,

Ogunlade

et al. 2024

ACS Nano

View full text Add to dashboard Cite

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surfaceenhanced Raman spectroscopy (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, and metabolome at the single-cell level. We first review how advances in nanophotonics− including plasmonics, metamaterials, and metasurfaces−enhance Raman scattering for rapid, strong label-free spectroscopy. We then discuss ML approaches for precise and interpretable spectral analysis, including neural networks, perturbation and gradient algorithms, and transfer learning. We provide illustrative examples of single-cell Raman phenotyping using nanophotonics and ML, including bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, and immunotherapy efficacy and toxicity predictions. Lastly, we discuss exciting prospects for the future of single-cell Raman spectroscopy, including Raman instrumentation, self-driving laboratories, Raman data banks, and machine learning for uncovering biological insights.

show abstract

Induction and measurement of the early stage of a host‐parasite interaction using a combined optical trapping and Raman microspectroscopy system

Abstract: Understanding and quantifying the temporal acquisition of host cell molecules by intracellular pathogens is fundamentally important in biology. In this study, a recently developed holographic optical trapping (HOT)-based Raman microspectroscopy (RMS) instrument is applied

Cited by 8 publications

References 25 publications

Single-particle optical-trapping Raman spectroscopy for the detection and identification of aerosolized airborne biological particles

Single-particle optical-trapping Raman spectroscopy for the detection and identification of aerosolized airborne biological particles

The Role of Single-Cell Technology in the Study and Control of Infectious Diseases

From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis

Contact Info

Product

Resources

About