Biology subjects

Dholakia, K.

Publications and source records attributed to Dholakia, K..

11 recordsLinked to original sources

bioRxiv2025

IL-18 metabolically reprograms CAR-expressing natural killer T cells and enhances their antitumor activity against neuroblastoma

Invariant natural killer T cells (NKTs) have intrinsic anti-tumor properties that make them promising candidates for chimeric antigen receptor (CAR)-based immunotherapies. Transgenic cytokine expression has been shown to enhance the potency of cellular immunotherapies, and we hypothesized that co-expressing IL-18 alone or with IL-15 would boost CAR-NKT therapeutic potential. To test this hypothesis, we generated retroviral constructs expressing IL-15 and/or IL-18 with the inducible caspase 9 (iC9) safety switch and co-transduced them with a GD2-specific CAR into human NKTs. Co-expression of IL-18 or IL-15/IL-18 increased GD2.CAR-NKT in vitro cytotoxicity, proliferation, and cytokine secretion compared to IL-15 alone. In a metastatic neuroblastoma model, GD2.CAR-NKTs expressing constructs with IL-18 controlled tumor growth better than cells expressing IL-15 only, but mice in the IL-15/IL-18 group developed severe toxicities not observed in the IL-18-only group. Mechanistically, we found that IL-18 drives a distinct transcriptional profile from IL-15 in CAR-NKTs marked by lower expression of exhaustion gene signatures and enrichment of metabolism-related processes. Finally, targeted metabolomics revealed that IL-18 induces broad metabolic reprogramming in CAR-NKTs including enhancement of oxidative phosphorylation, glycolysis, glutaminolysis and purine metabolism. These results support the use of IL-18 in developing the next generation of cytokine-armed CAR-NKT cancer immunotherapy.

immunology↗

bioRxiv2024

Sidelobe suppressed Bessel beams for one-photon light-sheet microscopy

Bessel beams (BB) have found widespread adoption in various forms of light-sheet microscopy. However, for one-photon fluorescence, the transverse profile of the beam poses challenges due to the detrimental effect of the sidelobes. Here, we mitigate this issue by using a computer generated phase element for generating a sidelobe suppressed Bessel beam (SSBB). We then progress to perform a comparison of biological imaging using SSBB to standard BB in a light-sheet geometry. The SSBB peak intensity is more than an order of magnitude higher than the first sidelobe. In contrast to a standard BB light-sheet, SSBB does not need deconvolution and propagates to depths exceeding 400m in phantom samples maintaining a transverse size of 5 m. Finally, we demonstrate the advantage of using a SSBB light-sheet for biological applications by imaging fixed early-stage zebrafish larvae. In comparison to the standard BB, we observe a two-fold increase in contrast-to-noise ratio (CNR) when imaging the labelled cellular eye structures and the notochords. Our results provide an effective approach to generating and using SSBB light-sheets to enhance contrast for one-photon light-sheet microscopy.

biophysics↗

bioRxiv2023

UVA hyperspectral light-sheet microscopy for volumetric metabolic imaging: application to pre-implantation embryo development

Cellular metabolism is a key regulator of energetics, cell growth, regeneration and homeostasis. Spatially mapping the heterogeneity of cellular metabolic activity is of great importance for unraveling the overall cell and tissue health. In this regard, imaging the endogenous metabolic co-factors NAD(P)H and FAD with sub-cellular resolution and in a non-invasive manner would be useful to determine tissue and cell viability in a clinical environment, but practical use is limited by current imaging techniques. In this article, we demonstrate the use of phasor-based hyperspectral light-sheet (HS-LS) microscopy using a single UVA excitation wavelength as a route to mapping metabolism in three dimensions. We show that excitation solely at a UVA wavelength of 375 nm can simultaneously excite NAD(P)H and FAD autofluorescence, while their relative contributions can be readily quantified using a hardware-based spectral phasor analysis. We demonstrate the potential of our HS-LS system by capturing dynamic changes in metabolic activity during pre-implantation embryo development. To validate our approach, we delineate metabolic changes during pre-implantation embryo development from volumetric maps of metabolic activity. Importantly, our approach overcomes the need for multiple excitation wavelengths, two-photon imaging or significant post-processing of data, paving the way towards clinical translation, such as in situ, non-invasive assessment of embryo viability.

biophysics↗

bioRxiv2023

Investigation of refractive index dynamics during embryo development using digital holographic microscopy

Embryo quality is a crucial factor affecting live birth outcomes. However, an accurate diagnostic for embryo quality remains elusive in the in vitro fertilization clinic. Determining physical parameters of the embryo may offer key information for this purpose. Here, we demonstrate that digital holographic microscopy (DHM) can rapidly and non-invasively assess the refractive index of mouse embryos. We showed that DHM can detect spatio-temporal changes in refractive index during embryo development that are reflective of its lipid content. As accumulation of intracellular lipid is known to compromise embryo health, DHM may prove beneficial in developing an accurate, non-invasive, multimodal diagnostic.

biophysics↗

bioRxiv2021

High throughput hemogram of T cells using digital holographic microscopy and deep learning

T cells of the adaptive immune system provide effective protection to the human body against numerous pathogenic challenges. Current labelling methods of detecting these cells, such as flow cytometry or magnetic bead labelling, are time consuming and expensive. To overcome these limitations, the label-free method of digital holographic microscopy (DHM) combined with deep learning has recently been introduced which is both time and cost effective. In this study, we demonstrate the application of digital holographic microscopy with deep learning to classify the key CD4+ and CD8+ T cell subsets. We show that combining DHM of varying fields of view, with deep learning, can potentially achieve a classification throughput rate of 78,000 cells per second with an accuracy of 76.2% for these morphologically similar cells. This throughput rate is 100 times faster than the previous studies and proves to be an effective replacement for labelling methods.

immunology↗

bioRxiv2021

Learned deconvolution using physics priors for structured light-sheet microscopy

Deconvolution is a challenging inverse problem, particularly in techniques that employ complex engineered point-spread functions, such as microscopy with propagation-invariant beams. Here, we present a deep learning method for deconvolution that, in lieu of end-to-end training with ground truths, is trained using known physics of the imaging system. Specifically, we train a generative adversarial network with images generated with the known point-spread function of the system, and combine this with unpaired experimental data that preserves perceptual content. Our method rapidly and robustly deconvolves and superresolves microscopy images, demonstrating a two-fold improvement in image contrast to conventional deconvolution methods. In contrast to common end-to-end networks that often require 1,000-10,000s paired images, our method is experimentally unsupervised and can be trained solely on a few hundred regions of interest. We demonstrate its performance on light-sheet microscopy with propagation-invariant Airy beams, including in calibration beads, oocytes, preimplantation embryos, and excised brain tissue, as well as illustrate its utility for Bessel-beam LSM. This method aims to democratise learned methods for deconvolution, as it does not require data acquisition outwith the conventional imaging protocol.

biophysics↗

bioRxiv2020

Label-free imaging of immune cell dynamics in the living retina using adaptive optics

Our recent work characterized the movement of single blood cells within the retinal vasculature of healthy mice (Joseph et al. 2019) using adaptive optics ophthalmoscopy. Here we apply this technique to the context of acute inflammation and discover both infiltrating and tissue-resident immune cells to be visible without any labelling in the living retina using near - infrared light alone. Intravital imaging of immune cells can be negatively impacted by surgical manipulation, exogenous dyes, transgenic manipulation and phototoxicity. These confounds are now overcome, using phase contrast and time-lapse videography to reveal the dynamic behavior of myeloid cells as they interact, extravasate and survey the retina. Cellular motility and differential vascular responses can be measured noninvasively and in vivo across hours to months at the same retinal location, from initiation to the resolution of inflammation. As comparable systems are already available for clinical research, this approach could be readily translated to human application. Impact statementImmune cell motility and vascular response are imaged in vivo and label-free in the CNS for the first time, using high-resolution phase-contrast adaptive optics retinal imaging.

immunology↗

bioRxiv2020

Widefield light sheet microscopy using an Airy beam combined with deep-learning super-resolution

Imaging across length scales and in depth has been an important pursuit of widefield optical imaging. This promises to reveal fine cellular detail within a widefield snapshot of a tissue sample. Current advances often sacrifice resolution through selective sub-sampling to provide a wide field of view in a reasonable time scale. We demonstrate a new avenue for recovering high-resolution images from sub-sampled data in light-sheet microscopy using deep-learning super-resolution. We combine this with the use of a widefield Airy beam to achieve high-resolution imaging over extended fields of view and depths. We characterise our method on fluorescent beads as test targets. We then demonstrate improvements in imaging amyloid plaques in a cleared brain from a mouse model of Alzheimers disease, and in excised healthy and cancerous colon and breast tissues. This development can be widely applied in all forms of light sheet microscopy to provide a two-fold increase in the dynamic range of the imaged length scale. It has the potential to provide further insight into neuroscience, developmental biology and histopathology.

biophysics↗

bioRxiv2019

Multi-photon attenuation-compensated light-sheet fluorescence microscopy

Attenuation of optical fields owing to scattering and absorption limits the penetration depth for imaging. Whilst aberration correction may be used, this is difficult to implement over a large field-of-view in heterogeneous tissue. Attenuation-compensation allows tailoring of the maximum lobe of a propagation-invariant light field and promises an increase in depth penetration for imaging. Here we show this promising approach may be implemented in multi-photon (two-photon) light-sheet fluorescence microscopy and, furthermore, be achieved in a facile manner utilizing a graded neutral density filter, circumventing the need for complex beam shaping apparatus. A "gold standard" system utilizing a spatial light modulator for beam shaping is used to benchmark our implementation. The approach will open up enhanced depth penetration in light-sheet imaging to a wide range of end users.

cell biology↗

bioRxiv2018

Three-photon light-sheet fluorescence microscopy

We present the first demonstration of three-photon excitation light-sheet fluorescence microscopy. Light-sheet fluorescence microscopy in single- and two-photon modes has emerged as a powerful wide-field, low photo-damage technique for fast volumetric imaging of biological samples. We extend this imaging modality to the three-photon regime enhancing its penetration depth. Our present study uses a standard conventional femtosecond pulsed laser at 1000 nm wavelength for the imaging of 450 {micro}m diameter cellular spheroids. In addition, we show, experimentally and through numerical simulations, the potential advantages in three-photon light-sheet microscopy of using propagation-invariant Bessel beams in preference to Gaussian beams.

cell biology↗

bioRxiv2018

The dyslexia susceptibility KIAA0319 gene shows a highly specific expression pattern during zebrafish development supporting a role beyond neuronal migration.

Dyslexia is a common neurodevelopmental disorder that affects reading abilities and is predicted to be caused by a significant genetic component. Very few genetic susceptibility factors have been identified so far and amongst those, KIAA0319 is a key candidate. KIAA0319 is highly expressed during brain development but its function remains poorly understood. Initial RNA-interference studies in rats suggested a role in neuronal migration whereas subsequent work with double knock-out mouse models for both Kiaa0319 and its paralogue Kiaa0319-like reported effects in the auditory system but not in neuronal migration. To further understand the role of KIAA0319 during neurodevelopment, we carried out an expression study of the zebrafish orthologue at different embryonic stages. We report particularly high gene expression during the first few hours of development. At later stages, expression becomes localised in well-defined structures such as the eyes, the telencephalon and the notochord, supporting a role for kiaa0319 that is not restricted to brain development. Surprisingly, kiaa0319-like, which generally shows a similar expression pattern, was not expressed in the notochord suggesting a role specific to kiaa0319 in this structure. This study contributes to our understanding of KIAA0319 function during embryonic development which might involve additional roles in the visual system and in the notochord. Such a specific spatiotemporal expression pattern is likely to be under the controlled of tightly regulated sequences. Therefore, these data provide a framework to interpret the effects of the dyslexia-associated genetic variants that reside in KIAA0319 non-coding regulatory regions.

neuroscience↗