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Article: Cell-TIMP: Cellular Trajectory Inference based on Morphological Parameter.

Raj, Piyush / Gupta, Himanshu / Anantha, Pooja / Barman, Ishan

bioRxiv : the preprint server for biology

2024

Abstract: Cellular morphology, shaped by various genetic and environmental influences, is pivotal to studying experimental cell biology, necessitating precise measurement and analysis techniques. Traditional approaches, which rely on geometric metrics derived from ...

Abstract	Cellular morphology, shaped by various genetic and environmental influences, is pivotal to studying experimental cell biology, necessitating precise measurement and analysis techniques. Traditional approaches, which rely on geometric metrics derived from stained images, encounter obstacles stemming from both the imaging and analytical domains. Staining processes can disrupt the cell's natural state and diminish accuracy due to photobleaching, while conventional analysis techniques, which categorize cells based on shape to discern pathophysiological conditions, often fail to capture the continuous and asynchronous nature of biological processes such as cell differentiation, immune responses, and cancer progression. In this work, we propose the use of quantitative phase imaging for morphological assessment due to its label-free nature. For analysis, we repurposed the genomic analysis toolbox to perform trajectory inference analysis purely based on morphology information. We applied the developed framework to study the progression of leukemia and breast cancer metastasis. Our approach revealed a clear pattern of morphological evolution tied to the diseases' advancement, highlighting the efficacy of our method in identifying functionally significant shape changes where conventional techniques falter. This advancement offers a fresh perspective on analyzing cellular morphology and holds significant potential for the broader research community, enabling a deeper understanding of complex biological dynamics.
Language	English
Publishing date	2024-04-22
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.04.18.590109
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Article ; Online: Optical diffraction tomography and Raman spectroscopy reveal distinct cellular phenotypes during white and brown adipocyte differentiation

Anantha, Pooja / Liu, Zhenhui / Raj, Piyush / Barman, Ishan

Biosensors and Bioelectronics. 2023 Sept., v. 235 p.115388-

2023

Abstract: White adipose tissue (WAT) and brown adipose tissue (BAT) are the primary types of fats in humans, and they play prominent roles in energy storage and thermogenesis, respectively. While the mechanisms of terminal adipogenesis are well understood, much ... ...

Abstract	White adipose tissue (WAT) and brown adipose tissue (BAT) are the primary types of fats in humans, and they play prominent roles in energy storage and thermogenesis, respectively. While the mechanisms of terminal adipogenesis are well understood, much remains unknown about the early stages of adipogenic differentiation. Label-free approaches, such as optical diffraction tomography (ODT) and Raman spectroscopy, offer the ability to retrieve morphological and molecular information at the single cell level without the negative effects of photobleaching and system perturbation due to introduction of fluorophores. In this study, we employed 3D ODT and Raman spectroscopy to gain deeper insights into the early stages of differentiation of human white preadipocytes (HWPs) and human brown preadipocytes (HBPs). We utilized ODT to retrieve morphological information, including cell dry mass and lipid mass, and Raman spectroscopy to obtain molecular information about lipids. Our findings reveal that HWPs and HBPs undergo dynamic and differential changes during the differentiation process. Notably, we found that HBPs accumulated lipids more rapidly and had a higher lipid mass than HWPs. Additionally, both cell types experienced an increase and subsequent decrease in cell dry mass during the first seven days, followed by an increase after day 7, which we attribute to the transformation of adipogenic precursors in the early stages. Finally, HBPs had higher lipid unsaturation levels than HWPs for the same differentiation timepoints. The insights gained from our study provide crucial contributions towards the advancement of new therapies for obesity and related diseases.
Keywords	Raman spectroscopy ; adipogenesis ; biosensors ; brown adipocytes ; brown adipose tissue ; energy ; fluorescent dyes ; heat production ; humans ; lipids ; obesity ; photobleaching ; tomography ; white adipose tissue ; Optical diffraction tomography ; Human white preadipocyte ; Human brown preadipocyte ; Adipocyte differentiation
Language	English
Dates of publication	2023-09
Publishing place	Elsevier B.V.
Document type	Article ; Online
ZDB-ID	1011023-9
ISSN	1873-4235 ; 0956-5663
ISSN (online)	1873-4235
ISSN	0956-5663
DOI	10.1016/j.bios.2023.115388
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Article ; Online: Quantum Plexcitonic Sensing.

Zheng, Peng / Semancik, Steve / Barman, Ishan

Nano letters

2023 Volume 23, Issue 20, Page(s) 9529–9537

Abstract: While fundamental to quantum sensing, quantum state control has been traditionally limited to extreme conditions. This restricts the impact of the practical implementation of quantum sensing on a broad range of physical measurements. Plexcitons, however, ...

Abstract	While fundamental to quantum sensing, quantum state control has been traditionally limited to extreme conditions. This restricts the impact of the practical implementation of quantum sensing on a broad range of physical measurements. Plexcitons, however, provide a promising path under ambient conditions toward quantum state control and thus quantum sensing, owing to their origin from strong plasmon-exciton coupling. Herein, we harness plexcitons to demonstrate quantum plexcitonic sensing by strongly coupling excitonic particles to a plasmonic hyperbolic metasurface. As compared to classical sensing in the weak-coupling regime, our model of quantum plexcitonic sensing performs at a level that is ∼40 times more sensitive. Noise-modulated sensitivity studies reinforce the quantum advantage over classical sensing, featuring better sensitivity, smaller sensitivity uncertainty, and higher resilience against optical noise. The successful demonstration of quantum plexcitonic sensing opens the door for a variety of physical, chemical, and biological measurements by leveraging strongly coupled plasmon-exciton systems.
Language	English
Publishing date	2023-10-11
Publishing country	United States
Document type	Journal Article
ISSN	1530-6992
ISSN (online)	1530-6992
DOI	10.1021/acs.nanolett.3c03095
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Article ; Online: Optical diffraction tomography and Raman spectroscopy reveal distinct cellular phenotypes during white and brown adipocyte differentiation.

Anantha, Pooja / Liu, Zhenhui / Raj, Piyush / Barman, Ishan

Biosensors & bioelectronics

2023 Volume 235, Page(s) 115388

Abstract	White adipose tissue (WAT) and brown adipose tissue (BAT) are the primary types of fats in humans, and they play prominent roles in energy storage and thermogenesis, respectively. While the mechanisms of terminal adipogenesis are well understood, much remains unknown about the early stages of adipogenic differentiation. Label-free approaches, such as optical diffraction tomography (ODT) and Raman spectroscopy, offer the ability to retrieve morphological and molecular information at the single cell level without the negative effects of photobleaching and system perturbation due to introduction of fluorophores. In this study, we employed 3D ODT and Raman spectroscopy to gain deeper insights into the early stages of differentiation of human white preadipocytes (HWPs) and human brown preadipocytes (HBPs). We utilized ODT to retrieve morphological information, including cell dry mass and lipid mass, and Raman spectroscopy to obtain molecular information about lipids. Our findings reveal that HWPs and HBPs undergo dynamic and differential changes during the differentiation process. Notably, we found that HBPs accumulated lipids more rapidly and had a higher lipid mass than HWPs. Additionally, both cell types experienced an increase and subsequent decrease in cell dry mass during the first seven days, followed by an increase after day 7, which we attribute to the transformation of adipogenic precursors in the early stages. Finally, HBPs had higher lipid unsaturation levels than HWPs for the same differentiation timepoints. The insights gained from our study provide crucial contributions towards the advancement of new therapies for obesity and related diseases.
MeSH term(s)	Humans ; Adipocytes, Brown/metabolism ; Spectrum Analysis, Raman ; Biosensing Techniques ; Cell Differentiation/genetics ; Lipids ; Phenotype ; Tomography
Chemical Substances	Lipids
Language	English
Publishing date	2023-05-12
Publishing country	England
Document type	Journal Article
ZDB-ID	1011023-9
ISSN	1873-4235 ; 0956-5663
ISSN (online)	1873-4235
ISSN	0956-5663
DOI	10.1016/j.bios.2023.115388
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Jg. 1995 - 2021: Lesesall (2.OG)
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Article ; Online: CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Raj, Piyush / Paidi, Santosh Kumar / Conway, Lauren / Chatterjee, Arnab / Barman, Ishan

Journal of biomedical optics

2024 Volume 29, Issue Suppl 2, Page(s) S22706

Abstract: Significance: Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has ...

Abstract	Significance: Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. Aim: We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. Approach: The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the Results: The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2 s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Conclusion: Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.
MeSH term(s)	Humans ; Image Processing, Computer-Assisted/methods ; Imaging, Three-Dimensional/methods ; Quantitative Phase Imaging ; Algorithms ; Optical Imaging
Language	English
Publishing date	2024-04-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	1309154-2
ISSN	1560-2281 ; 1083-3668
ISSN (online)	1560-2281
ISSN	1083-3668
DOI	10.1117/1.JBO.29.S2.S22706
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Article ; Online: Label-Free Visualization and Morphological Profiling of Neuronal Differentiation and Axonal Degeneration through Quantitative Phase Imaging.

Kim, Jeong Hee / Cetinkaya-Fisgin, Aysel / Zahn, Noah / Sari, Mehmet Can / Hoke, Ahmet / Barman, Ishan

Advanced biology

2024 Volume 8, Issue 5, Page(s) e2400020

Abstract: Understanding the intricate processes of neuronal growth, degeneration, and neurotoxicity is paramount for unraveling nervous system function and holds significant promise in improving patient outcomes, especially in the context of chemotherapy-induced ... ...

Abstract	Understanding the intricate processes of neuronal growth, degeneration, and neurotoxicity is paramount for unraveling nervous system function and holds significant promise in improving patient outcomes, especially in the context of chemotherapy-induced peripheral neuropathy (CIPN). These processes are influenced by a broad range of entwined events facilitated by chemical, electrical, and mechanical signals. The progress of each process is inherently linked to phenotypic changes in cells. Currently, the primary means of demonstrating morphological changes rely on measurements of neurite outgrowth and axon length. However, conventional techniques for monitoring these processes often require extensive preparation to enable manual or semi-automated measurements. Here, a label-free and non-invasive approach is employed for monitoring neuronal differentiation and degeneration using quantitative phase imaging (QPI). Operating on unlabeled specimens and offering little to no phototoxicity and photobleaching, QPI delivers quantitative maps of optical path length delays that provide an objective measure of cellular morphology and dynamics. This approach enables the visualization and quantification of axon length and other physical properties of dorsal root ganglion (DRG) neuronal cells, allowing greater understanding of neuronal responses to stimuli simulating CIPN conditions. This research paves new avenues for the development of more effective strategies in the clinical management of neurotoxicity.
MeSH term(s)	Animals ; Ganglia, Spinal/pathology ; Ganglia, Spinal/cytology ; Axons/pathology ; Cell Differentiation ; Neurons/pathology ; Humans ; Mice ; Peripheral Nervous System Diseases/pathology ; Peripheral Nervous System Diseases/chemically induced ; Peripheral Nervous System Diseases/physiopathology ; Quantitative Phase Imaging
Language	English
Publishing date	2024-03-28
Publishing country	Germany
Document type	Journal Article
ISSN	2701-0198
ISSN (online)	2701-0198
DOI	10.1002/adbi.202400020
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Article: DNA-POINT: DNA Patterning of Optical Imprint for Nanomaterials Topography

Liang, Le / Jia, Sisi / Barman, Ishan

ACS applied materials & interfaces. 2022 Aug. 15, v. 14, no. 33

2022

Abstract: Engineering well-defined scale-spanning structures through transfer of diverse biomolecules and materials to a surface is of tremendous interest in life sciences research yet remains profoundly challenging. Here, we report a novel method, termed as DNA ... ...

Abstract	Engineering well-defined scale-spanning structures through transfer of diverse biomolecules and materials to a surface is of tremendous interest in life sciences research yet remains profoundly challenging. Here, we report a novel method, termed as DNA patterning of optical imprint for nanomaterials topography (DNA-POINT), for rapid photopatterning of large area, geometrically complex surfaces via light-responsive DNA. Our method employs top-down multiphoton-driven patterning of azobenzene-modified DNA strands, offering precise position control of molecules and nanoparticles along the axial plane and a template for bottom-up self-assembly of multiple layers of different chemical composition along the vertical plane. We demonstrate the surface patterning of plasmonic gold nanoparticles, fluorophore-labeled oligonucleotides, and multiple layers consisting of molecule–nanoparticle hybrid patterns into preconceived shapes without compromising on the functionality of the biomolecules. Furthermore, we exhibit scanning mode operation of DNA-POINT, thereby paving the way for maskless and cleanroom-free fast fabrication of biochips for high-throughput diagnostics and biosensing applications.
Keywords	DNA ; chemical composition ; diagnostic techniques ; nanogold ; nanoparticles ; oligonucleotides ; topography
Language	English
Dates of publication	2022-0815
Size	p. 38388-38397.
Publishing place	American Chemical Society
Document type	Article
ISSN	1944-8252
DOI	10.1021/acsami.2c10908
Database	NAL-Catalogue (AGRICOLA)

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Article: CellSNAP: A fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Raj, Piyush / Paidi, Santosh / Conway, Lauren / Chatterjee, Arnab / Barman, Ishan

bioRxiv : the preprint server for biology

2023

Abstract: Quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. In particular, three-dimensional (3D) ... ...

Abstract	Quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. In particular, three-dimensional (3D) tomographic imaging of live cells has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw 3D tomograms is not well-developed. This work focuses on a critical, yet often underappreciated, step of the analysis pipeline, that of 3D cell segmentation from the acquired tomograms. The current method employed for such tasks is the Otsu-based 3D watershed algorithm, which works well for isolated cells; however, it is very challenging to draw boundaries when the cells are clumped. This process is also memory intensive since the processing requires computation on a 3D stack of images. We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the segmentation of QPI images, which outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2 seconds per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused segmentation tools. We envision our work will lead to the broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.
Language	English
Publishing date	2023-08-13
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.07.24.550376
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Article ; Online: DNA-POINT: DNA Patterning of Optical Imprint for Nanomaterials Topography.

Liang, Le / Jia, Sisi / Barman, Ishan

ACS applied materials & interfaces

2022 Volume 14, Issue 33, Page(s) 38388–38397

Abstract	Engineering well-defined scale-spanning structures through transfer of diverse biomolecules and materials to a surface is of tremendous interest in life sciences research yet remains profoundly challenging. Here, we report a novel method, termed as DNA patterning of optical imprint for nanomaterials topography (DNA-POINT), for rapid photopatterning of large area, geometrically complex surfaces via light-responsive DNA. Our method employs top-down multiphoton-driven patterning of azobenzene-modified DNA strands, offering precise position control of molecules and nanoparticles along the axial plane and a template for bottom-up self-assembly of multiple layers of different chemical composition along the vertical plane. We demonstrate the surface patterning of plasmonic gold nanoparticles, fluorophore-labeled oligonucleotides, and multiple layers consisting of molecule-nanoparticle hybrid patterns into preconceived shapes without compromising on the functionality of the biomolecules. Furthermore, we exhibit scanning mode operation of DNA-POINT, thereby paving the way for maskless and cleanroom-free fast fabrication of biochips for high-throughput diagnostics and biosensing applications.
MeSH term(s)	DNA/chemistry ; Gold/chemistry ; Metal Nanoparticles/chemistry ; Nanostructures
Chemical Substances	Gold (7440-57-5) ; DNA (9007-49-2)
Language	English
Publishing date	2022-08-15
Publishing country	United States
Document type	Journal Article
ISSN	1944-8252
ISSN (online)	1944-8252
DOI	10.1021/acsami.2c10908
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Shining Light on Osteoarthritis: Spatially Offset Raman Spectroscopy as a Window into Cartilage Health.

Raj, Piyush / Wu, Lintong / Almeida, Craig / Conway, Lauren / Tanwar, Swati / Middendorf, Jill / Barman, Ishan

bioRxiv : the preprint server for biology

2023

Abstract: Articular cartilage is a complex tissue, and early detection of osteoarthritis (OA) is crucial for effective treatment. However, current imaging modalities lack molecular specificity and primarily detect late-stage changes. In this study, we propose the ... ...

Abstract	Articular cartilage is a complex tissue, and early detection of osteoarthritis (OA) is crucial for effective treatment. However, current imaging modalities lack molecular specificity and primarily detect late-stage changes. In this study, we propose the use of Spatially Offset Raman Spectroscopy (SORS) for non-invasive, depth-dependent, and molecular-specific diagnostics of articular cartilage. We demonstrate the potential of SORS to penetrate deep layers of cartilage, providing a comprehensive understanding of disease progression. Our SORS measurements were characterized and validated through mechanical and histological techniques, revealing strong correlations between spectroscopic measurements and both Young's modulus and depth of cartilage damage. By longitudinally monitoring enzymatically degraded condyles, we further developed a depth-dependent damage-tracking method. Our analysis revealed distinct components related to sample depth and glycosaminoglycan (GAG) changes, offering a comprehensive picture of cartilage health. Collectively, these findings highlight the potential of SORS as a valuable tool for enhancing OA management and improving patient outcomes.
Language	English
Publishing date	2023-08-16
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.08.14.553328
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