Biology subjects

Boppart, S. A.

Publications and source records attributed to Boppart, S. A..

8 recordsLinked to original sources

bioRxiv2026

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy

Label-free optical redox imaging utilizes endogenous NAD(P)H and FAD autofluorescence to evaluate metabolism in living specimens. The conventional optical redox ratio collapses these two channels into a single value; however, it does not indicate whether a pixel has sufficient photon support or the cellular context necessary for quantitative aggregation. To address this limitation, we introduce FPhaS, a fixed-calibration phase- autofluorescence framework that integrates quantitative phase imaging (QPI) with simultaneous label-free autofluorescence multi-harmonic microscopy (SLAM), using fluorescence lifetime imaging (FLIM) solely for validation. Because QPI and SLAM are acquired with the same objective, a unified non-biological calibration aligns phase-derived structural data with the autofluorescence frame, yielding a residual error of 0.39 pixels. This calibration is maintained across all biological specimens. This shared geometric reference enables local evaluation of structural and metabolic information, rather than comparing approximately aligned images. FPhaS decomposes the data into cell presence, ratio credibility, and confidence-supported pooling. We validated FPhaS on A549 cells under high and low-photon conditions; the framework is designed to generalize to other cell and tissue types. Confidence-weighted intensity redox estimates were compared with lifetime-derived measurements within mask-locked cellular regions. Concordance improved exclusively when both the denominator photon support and an independent structural criterion were satisfied. The same reference layer generated cell-level descriptors of metabolic content, metabolic-structural organization, and measurement reliability, while also constraining the CombinedWLS reconstruction under diminished fluorescence acquisition. FPhaS redefines label-free metabolic imaging from producing comprehensive ratio maps to identifying regions where optical evidence substantiates quantitative inference.

bioengineering↗

bioRxiv2025

Two-photon activation, deactivation, and coherent control of melanopsin in live cells

Intrinsically photosensitive retinal ganglion cells are photoreceptors discovered in the last 20 years. These cells project to the suprachiasmatic nucleus of the brain to drive circadian rhythms, regulated by ambient light levels. The photopigment responsible for photoactivation in these cells, melanopsin, has been shown to exhibit many unique activation features among opsins. Notably, the photopigment can exist in three states dependent on the intensity and spectrum of ambient light, which affects its function. Despite increasing knowledge about these cells and melanopsin, tools that can manipulate their three states, and do so with single-cell precision, are limited. This reduces the extent to which circuit-level phenomena, and studying the implications of melanopsin tri-stability in living systems, can be pursued. In this report, we evoke and modulate calcium transients in live cells and intrinsically photosensitive retinal ganglion cells from isolated retinal tissues following two-photon excitation using near-infrared light pulses. We demonstrate that two-photon activation of melanopsin can successfully stimulate melanopsin-expressing cells with high spatio-temporal precision. Moreover, we demonstrate that the functional tri-stability of the photopigment can be interrogated by multiphoton excitation using spectral-temporal modulation of a broadband, ultrafast laser source.

bioengineering↗

bioRxiv2024

Cholesterol Metabolite 27-Hydroxycholesterol Enhances the Secretion of Cancer Promoting Extracellular Vesicles by a Mitochondrial ROS-Induced Impairment of Lysosomal Function

Extracellular vesicles (EVs) serve as crucial mediators of cell-to-cell communication in normal physiology as well as in diseased states, and have been largely studied in regard to their role in cancer progression. However, the mechanisms by which their biogenesis and secretion are regulated by metabolic or endocrine factors remain unknown. Here, we delineate a mechanism by which EV secretion is regulated by a cholesterol metabolite, 27-Hydroxycholesterol (27HC), where treatment of myeloid immune cells (RAW 264.7 and J774A.1) with 27HC impairs lysosomal homeostasis, leading to shunting of multivesicular bodies (MVBs) away from lysosomal degradation, towards secretion as EVs. This impairment of lysosomal function is caused by mitochondrial dysfunction and subsequent increase in reactive oxygen species (ROS). Interestingly, cotreatment with a mitochondria-targeted antioxidant rescued the lysosomal impairment and attenuated the 27HC-mediated increase in EV secretion. Overall, our findings establish how a cholesterol metabolite regulates EV secretion and paves the way for the development of strategies to regulate cancer progression by controlling EV secretion.

cell biology↗

bioRxiv2022

Tunable image-mapping optical coherence tomography

We present tunable image-mapping optical coherence tomography (TIM-OCT), which can provide optimized imaging performance for a given application by using a programmable phase-only spatial light modulator in a low-coherence full-field spectral-domain interferometer. The resultant system can provide either a high lateral resolution or a high axial resolution in a snapshot without moving parts. Alternatively, the system can achieve a high resolution along all dimensions through a multiple-shot acquisition. We evaluated TIM-OCT in imaging both standard targets and biological samples. Additionally, we demonstrated the integration of TIM-OCT with computational adaptive optics in correcting sample-induced optical aberrations.

bioengineering↗

bioRxiv2022

Weakly supervised deep learning for human breast cancer-related optical biomarker discovery in label-free virtual histopathology

With the latest advancements in optical bioimaging, rich structural and functional information has been generated from biological samples, which calls for capable computational tools to identify patterns and uncover relationships between optical characteristics and various biomedical conditions. Constrained by the existing knowledge of the novel signals obtained by those bioimaging techniques, precise and accurate ground truth annotations can be difficult to obtain. Here we present a weakly supervised Deep Learning framework for optical signature discovery based on inexact and incomplete supervision. The framework consists of a Multiple Instance Learning-based classifier for the identification of regions of interest in coarsely labeled images, and model interpretation techniques for optical signature discovery. We applied this framework to investigate human breast cancer-related optical signatures based on virtual histopathology enabled by simultaneous label-free autofluorescence multiharmonic microscopy (SLAM), with the goal to explore unconventional cancer-related optical signatures from normal-appearing breast tissues. The framework has achieved an average area under the curve (AUC) of 0.975 on the cancer diagnosis task. In addition to well-known cancer biomarkers, non-obvious cancer-related patterns were revealed by the framework, including NAD(P)H-rich extracellular vesicles observed in normal-appearing breast cancer tissue, which facilitate new insights into the tumor microenvironment and field cancerization. This framework can be further extended to diverse imaging modalities and optical signature discovery tasks.

bioinformatics↗

bioRxiv2021

Wound-like tumor periphery in human breast cancer predicts a convergent drug nonresponse

A significant portion of breast cancer patients are nonresponsive to well-established drugs and destined for a poor outcome regardless of molecular subtype. Although several (multiparameter) molecular markers have predicted their resistance to some of these drugs, profound uniparameter markers predictive of a convergent nonresponse to all these drugs remain elusive. We employ co-registered standard-multiphoton histology to representatively sample a few peripheral niches of the primary tumor, so that hundreds of patients can be stratified with either a wound-like or non-wound tumor periphery. With no fitting variable, this simple uniparameter morphological marker is: (a) highly sensitive and specific to predict a multidrug-nonresponsive phenotype that accounts for the majority of recurrence or death, independent of the molecular subtype or related adjuvant drug selection, clinical endpoint (disease-free versus overall survival), and hosting medical center; (b) robust against intratumor heterogeneity and valid at the earliest clinicopathological stage; and (c) dominant in predicting prognosis in the context of routine clinicopathological markers. Considering the mechanistic link between a wound-like extracellular matrix and a microenvironment supporting migratory or mesenchymal tumor cells, we attribute these unusual capabilities to an epithelial-mesenchymal transition nature of the morphological marker long sought after by pathologists.

pathology↗

bioRxiv2020

Bile acid excess impairs thermogenic function in brown adipose tissue

Bile acids (BAs) not only facilitate fat digestion but also protect against obesity. Here, we show that a genetic mouse model for BA overload (Farnesoid X receptor; Small heterodimer double knockout (DKO)) exhibits mitochondrial dysfunction resulting in a thermogenic defect. By housing DKO mice at thermoneutrality, the poor mitochondrial function in brown fat protects them from diet-induced obesity. Compared to control, we find higher adipose BA levels with excess accumulation of taurocholic acid in the DKO mice. We report that the expression of genes responsible for BA de novo synthesis, conjugation and transporters and accumulation of BAs are present in both brown and white adipocytes. We determine that BA overload is sufficient to cause adipocyte mitochondrial dysfunction and induce the expression of cellular senescence genes in vitro. Taken together, we uncover that BA levels within the adipose tissue may modulate its overall function. HighlightsO_LIMouse model of BA overload exhibits adipose defects, which is partially restored by housing at thermoneutrality. C_LIO_LIBAs are present in detectable concentrations in both BAT and WAT. C_LIO_LIAdipocytes express genes responsible for de novo synthesis, conjugation and transport of BAs, and accumulate BAs. C_LIO_LIPathological accumulation of BAs impairs mitochondrial function leading to thermogenic defect. C_LI

physiology↗

bioRxiv2020

Dynamic signatures of lipid droplets as new markers to quantify cellular metabolic changes

The metabolic properties of live cells are very susceptible to intra- or extra-cellular perturbations, making their measurements challenging tasks. We show that the dynamics of lipid droplets (LDs) carry information to measure the lipid metabolism of live cells. Coherent anti-Stokes Raman scattering microscopy was used to statistically quantify LD dynamics in living cells in a label-free manner. We introduce dynamic signatures of cells derived from the LD displacement, speed, travel length, and directionality, which allows for the detection of cellular changes induced by stimuli such as fluorescent labeling, temperature change, starvation, and chemical treatment. Histogram fittings of the dynamic signatures using lognormal distribution functions provide quantification of changes in cellular metabolic states. The LD dynamics also enable separation of subpopulations of LDs correlated with different functions. We demonstrate that LD dynamics are new markers to quantify the metabolic changes in live cells.

biophysics↗