Prof. Piotr Garstecki Profile

Prof. Piotr Garstecki

at Institute of Physical Chemistry PAS

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Publications (2)

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Proceedings Article | 5 October 2023 Poster + Paper

Opto-hydrodynamic fiber tweezers for stimulated Raman imaging cytometry of leukemic cells

Shreyas Vasantham, Piotr Garstecki, Ladislav Derzsi, Abhay Kotnala

Proceedings Volume 12649, 126490Q (2023) https://doi.org/10.1117/12.2677250

KEYWORDS: Raman spectroscopy, Leukemia, Microfluidics, Biological imaging, Proteins, Optofluidics, Optical fibers, Signal processing, Raman scattering, Microscopes

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Raman fingerprinting of leukemic cells has potential applications in diagnosis and in vitro chemosensitivity assessment. A biochemical map of the contents of leukemic cells can not only help distinguish cancer patients from healthy ones but also shed light on different subtypes of leukemia such as ALL, AML, etc. Certain important requirements need to be fulfilled to effectively measure the Raman map of a single leukemic cell. Firstly, since the leukemia cells are suspension cells, it is preferred to keep them in a free solution rather than attached to a fixed surface during signal acquisition. Secondly, the cells need to be immobilized for several seconds, for the acquisition of the weak Raman signal even when using stimulated Raman Spectroscopy (SRS) which provides relatively stronger Raman signal. Thus, a device capable of sequentially flowing, holding, and releasing individual leukemia cells in a robust, efficient and high-throughput manner is required. We present an optofluidic fiber tweezers device comprised of a novel combination of 3D hydrodynamic flow focusing and optical fiber in a microfluidic chip. By exploiting the interplay between the optical and hydrodynamic forces acting on the cell, we demonstrate rapid, efficient, sequential delivery and trapping of single leukemic cells in a flow cytometer format followed by SRS imaging of the trapped cell. The specific Raman vibration bands corresponding to the lipids, nucleic acids, and proteins in the trapped cells were analyzed to distinguish cancerous cells from healthy cells. Our device is also capable of isolating cells with unique Raman signatures for further processing using techniques like gene sequencing etc.

Proceedings Article | 6 March 2023 Presentation + Paper

Speckle imaging offers sensitive detection of bacterial growth in microdroplet antibiotic susceptibility testing assays

Shreyas Vasantham, Shakeel Ahmad, Piotr Garstecki, Abhay Kotnala

Proceedings Volume 12374, 1237407 (2023) https://doi.org/10.1117/12.2649807

KEYWORDS: Signal detection, Bacteria, Speckle, Light scattering, Speckle imaging, Signal intensity, Laser scattering, Microfluidics

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Detection and quantification of bacterial populations in droplets is a fundamental prerequisite for the application of droplet microfluidic technology in antibiotic susceptibility assays, paving the way for single-cell profiling and quantifying hetero-resistance. While several label-free detection approaches have been proposed, limited detection sensitivity and the ability to quantify bacterial populations in droplets accurately remain challenging. Furthermore, these approaches are prone to a high number of false positives resulting in low accuracy and requiring highly monodisperse droplets. This study presents a speckle image-based detection technique for the quantification of the bacterial population in droplets. Speckles are generated by scattering laser light from bacteria-loaded droplets in a flow cytometric approach. Spatial segregation of the scattering signal from the droplet surface as well as its contents allows the detection of encapsulated bacteria with a high signal-to-noise ratio. This results in a detection sensitivity of ⁓100 CFU/droplet, the highest achieved by any label-free detection technique in a flow format thus far. It also allows the identification of false-positive signals, thereby increasing the accuracy of detection and enabling operation with polydisperse droplets (diameter: 10–500 µm). The properties of the speckle image generated from droplets, such as speckle grain size and density, can be used to quantify the population of bacteria in droplets. This detection approach applies to a wide range of bacteria species of clinical and industrial importance, creating avenues for innovation in bacteria analysis using droplet microfluidics.

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