Biology subjects

Bohndiek, S. E.

Publications and source records attributed to Bohndiek, S. E..

12 recordsLinked to original sources

bioRxiv2026

Spectral characterisation of short-wave infrared (SWIR) tissue chromophores and tissue-mimicking phantom optical properties

Significance Short-wave infrared (SWIR) sensors promise to expand the capabilities of optical sensing technologies, but the lack of robust data characterising tissue-constituent optical properties in the SWIR makes instrument design challenging. Aim We characterise and evaluate the optical properties of the dominant chromophores in tissue and tissue- mimicking phantoms, from visible to SWIR wavelengths. Approach Using single-integrating sphere systems, we measured the optical properties of single-component chromophores (H2O, haemoglobin, corn oil, synthetic melanin) and multi-component tissues (whole blood, lard), to decouple contributions from optical scattering, H2O absorption and other contributing chromophores; we also characterised commonly-used phantom materials and investigated their potential to mimic soft tissues in the SWIR range using simulations. Results We provide a consistent dataset of absorption and reduced scattering coefficients ({micro}a and {micro}'s) that characterise the dominant tissue chromophores from 450 nm out to 1600 nm. These results were shown to be consistent with literature data, where available. We integrate these data into an open-source Python toolkit, SIMPA, for optical modelling and demonstrate soft tissue simulations that can be probed continuously from visible to SWIR wavelengths. Our findings are compared with tissue-mimicking phantoms, highlighting a need for additives for polymer-based phantoms that mimic SWIR water absorption. Conclusions By providing this open-source dataset, we aim to enable future studies exploring SWIR light-tissue interactions that facilitate rapid assessment and prototyping of next-generation spectroscopy and imaging techniques.

bioengineering↗

bioRxiv2026

SPEND-hSRS imaging of fumarate uncovers mitochondrial metabolic heterogeneity

Mitochondria, acting as the energy powerhouse, biosynthetic center, and reductive equivalent hub of the cell, participate in cellular metabolic activities. However directly imaging mitochondrial chemical content and quantifying metabolic activity in living cells remain challenging. Here, by Self-PErmutation Noise2noise Denoiser enhanced Hyperspectral Stimulated Raman Scattering (SPEND-hSRS) microscopy, we demonstrate fingerprint-region metabolic imaging of fumarate, a key intermediate in the tricarboxylic acid (TCA) cycle, with sub-millimolar sensitivity. In chemotherapy-stressed bladder cancer cells, fumarate imaging revealed two mitochondrial subpopulations with divergent TCA metabolic preferences quantified by ratio metric analysis. Pixel-wise least absolute shrinkage and selection operator (LASSO) spectral unmixing further reconstructs fumarate and lipid maps, uncovering localized fumarate enrichment in protrusions. Extending to CH-window hyperspectral SRS imaging, we uncover the interplay between mitochondria and lipid droplets (LDs) in protrusions, where fatty acid is found to be released from LDs, to fuel the TCA cycle. Together, our work establishes SPEND-hSRS as high-resolution platform for linking fumarate to mitochondrial heterogeneity. Our results provide new insights into how mitochondrial heterogeneity and interaction with LDs drive cancer cell adaptation to stress.

cancer biology↗

bioRxiv2025

Unravelling the in vivo traits of vasculogenic mimicry

Vasculogenic mimicry (VM) describes the ability of cancer cells to acquire endothelial properties and form vessel-like channels that facilitate tumour blood supply. While the molecular drivers of VM have been well-explored in cell cultures and biopsies, an in vivo description remains elusive. Here, we used graph theory to define VM biomarkers and elucidate the spatiotemporal dynamics of VM using in vitro and in vivo breast cancer models with and without anti-angiogenic treatment. Optical microscopy was used to assess pseudo-vascular networks in vitro while photoacoustic imaging across scales was applied in vivo to identify and locate haemoglobin contrast-derived blood vessel morphology and functionality. VM was associated with greater oxygenation heterogeneity and poorer anti-angiogenic response, reflected as stable meshed networks in vitro and blood-containing circular structures in vivo. We demonstrate for the first time a multi-scale approach bridging the in vitro-in vivo translational gap to assess anti-vascular treatment resistance and the therapeutic potential in vasculogenic mimicry-rich tumours, exploring novel avenues in preclinical drug screening and systemic drug delivery.

cancer biology↗

bioRxiv2025

Early Radiation Therapy Response Assessment using Multi-scale Photoacoustic Imaging

There is a critical unmet clinical need to identify biomarkers that predict and detect radiotherapy response in cancer. Using the unique capabilities of multi-scale photoacoustic imaging (PAI) for depicting tumour oxygenation and vasculature in vivo, we identified surrogate biomarkers of radiation response in two human breast cancer models (MCF7 and MDA-MB-231), comparing hypofractionated delivery with an ablative single dose scheme. Ex vivo immunohistochemistry results underpinned findings from mesoscopic and multispectral tomographic PAI, performed 24h pre-RT, 24h post-RT, and at endpoint. A denser and more mature vasculature of the MCF7 xenografts afforded an improved response to both RT schemes compared to MDA-MB-231, in terms of overall tumour oxygenation, tumour volume and proliferation. Increased intratumoural blood oxygen saturation and oxygen diffusion pre-RT were associated with improved outcomes and decreased proliferation, expected given the oxygen-enhancement effect in RT. In vivo PAI revealed the differential effect between ablative courses of RT in both models, with the ablative scheme altering the tumour vasculature as early as 24h post-RT, and pruning the looping vessels and total blood volume at endpoint in the more radiosensitive MCF-7 xenografts. An increase in blood oxygen saturation at endpoint was observed only in the MCF7 xenografts treated with hypofractionated RT, confirming the reduced oxygen consumption of damaged tumour cells, indicative of response. Thus, we showed that PAI could capture early RT response and inform on radioresistance, thus demonstrating promise of PAI as an in vivo and future clinical tool to monitor the tumour vascular response to RT.

cancer biology↗

bioRxiv2023

The in vitro dynamics of pseudo-vascular network formation.

Pseudo-vascular network formation capacity in vitro is considered a key characteristic of vasculogenic mimicry. While many cancer cell lines are known to form pseudo-vascular networks, little is known about the spatiotemporal dynamics of these formations. Here, we present a framework for monitoring and characterising the dynamic formation and dissolution of pseudo-vascular networks in vitro. The framework combines time-resolved optical microscopy with open-source image analysis for network feature extraction and statistical modelling. The framework is demonstrated by comparing diverse cancer cell lines associated with vasculogenic mimicry, then in detecting response to drug compounds proposed to affect formation of vasculogenic mimics. Dynamic datasets collected were analysed morphometrically and a descriptive statistical analysis model was developed in order to measure stability and dissimilarity characteristics of the pseudo-vascular networks formed. Melanoma cells formed the most stable pseudo-vascular networks and were selected to evaluate the response of their pseudo-vascular networks to treatment with axitinib, brucine and tivantinib. Our framework is shown to enable quantitative analysis of both the capacity for network formation, linked vasculogenic mimicry, as well as dynamic responses to treatment.

cancer biology↗

bioRxiv2023

In Vivo Monitoring of Cellular Senescence by Photoacoustic and Fluorescence Imaging Utilizing a Nanostructured Organic Probe

Senescent cells accumulate in multiple age-related disorders, including cancer, exacerbating the pathological manifestations, and the eradication of these cells has emerged as a promising therapeutic strategy. Despite the impact of senescence in diseases, the development of tools to monitor the senescent burden in vivo remains a challenge due to their suboptimal specificity, translatability, and tissue penetrance. Here, we have designed a nanostructured organic probe (NanoJaggs) based on biocompatible indocyanine green dye (ICG) building blocks forming J-aggregates, which possess distinct spectral properties allowing both fluorescence and photoacoustic tomography (PAT) detection. We show that NanoJaggs are taken up by an active process of endocytosis and exhibit selective accumulation at the lysosomal compartment in several in vitro models for senescence. Finally, NanoJagg probe is validated in two in vivo studies including live PAT imaging and shows remarkable specificity to tumours with chemotherapy-induced senescence compared to untreated proliferative tumors. In vitro, ex vivo and in vivo all indicate that NanoJaggs are a clinically translatable tool for detection of senescence and their robust PAT signal makes them suitable for longitudinal monitoring of the senescent burden in solid tumors after chemo or radiotherapy.

cancer biology↗

bioRxiv2023

Segmentation of 3D blood vessel networks using unsupervised deep learning

Mesoscopic photoacoustic imaging (PAI) enables label-free visualisation of vascular networks in tissue at high contrast and resolution. The segmentation of vascular networks from 3D PAI data and interpretation of their meaning in the context of physiological and pathological processes is a crucial but time consuming and error-prone task. Deep learning holds potential to solve these problems, but current supervised analysis frameworks require human-annotated ground-truth labels. Here, we overcome the need for ground-truth labels by introducing an unsupervised image-to-image translation deep learning model called the vessel segmentation generative adversarial network (VAN-GAN). VAN-GAN integrates synthetic blood vessel networks that closely resemble real-life anatomy into its training process and learns to replicate the underlying physics of the PAI system in order to learn how to segment vasculature from 3D biomedical images. With a variety of in silico, in vitro and in vivo data, including patient-derived breast cancer xenograft models, we show that VAN-GAN facilitates accurate and unbiased segmentation of 3D vascular networks from PAI data volumes. By leveraging synthetic data to reduce the reliance on manual labelling, VAN-GAN lowers the barrier to entry for high-quality blood vessel segmentation to benefit users in the life sciences applying PAI to studies of vascular structure and function.

biophysics↗

bioRxiv2022

Performance evaluation of mesoscopic photoacoustic imaging

Photoacoustic mesoscopy visualises vascular architecture and associated tissue structures at high resolution at up to 3 mm depth. The technique has shown promise in both preclinical and clinical imaging studies, with possible applications in oncology and dermatology, however, the accuracy and precision of photoacoustic mesoscopy has not been well established. Here, we present a performance evaluation of a commercial photoacoustic mesoscopy system for imaging vascular structures. Typical artefact types are first highlighted and limitations due to non-isotropic illumination and detection are evaluated with respect to rotation, angularity, and depth of the target. Then, using tailored phantoms and mouse models we demonstrate high system precision, with acceptable coefficients of variation (COV) between repeated scans (short term (1h): COV=1.2%; long term (25 days): COV=9.6%), from target repositioning (without: COV=1.2%, with: COV=4.1%), or from varying in vivo user experience (experienced: COV=15.9%, unexperienced: COV=20.2%). While our findings support the robustness of the technique, they also underscore the general challenges of limited field-of-view photoacoustic systems in accurately imaging vessel-like structures, thereby guiding users to correctly interpret biologically-relevant information.

bioengineering↗

bioRxiv2021

Quantification of vascular networks in photoacoustic mesoscopy

Mesoscopic photoacoustic imaging (PAI) enables non-invasive visualisation of tumour vasculature and has the potential to assess prognosis and therapeutic response. Currently, evaluating vasculature using mesoscopic PAI involves visual or semi-quantitative 2D measurements, which fail to capture 3D vessel network complexity, and lack robust ground truths for assessment of segmentation accuracy. Here, we developed an in silico, phantom, in vivo, and ex vivo-validated end-to-end framework to quantify 3D vascular networks captured using mesoscopic PAI. We applied our framework to evaluate the capacity of rule-based and machine learning-based segmentation methods, with or without vesselness image filtering, to preserve blood volume and network structure by employing topological data analysis. We first assessed segmentation performance against ground truth data of in silico synthetic vasculatures and a photoacoustic string phantom. Our results indicate that learning-based segmentation best preserves vessel diameter and blood volume at depth, while rule-based segmentation with vesselness image filtering accurately preserved network structure in superficial vessels. Next, we applied our framework to breast cancer patient-derived xenografts (PDXs), with corresponding ex vivo immunohistochemistry. We demonstrated that the above segmentation methods can reliably delineate the vasculature of 2 breast PDX models from mesoscopic PA images. Our results underscore the importance of evaluating the choice of segmentation method when applying mesoscopic PAI as a tool to evaluate vascular networks in vivo.

bioengineering↗

bioRxiv2020

DNA-based nanocarriers to enhance the optoacoustic contrast of tumors in vivo

Optoacoustic tomography (OT) enables non-invasive deep tissue imaging of optical contrast at high spatio-temporal resolution. The applications of OT in cancer imaging often rely on the use of molecular imaging contrast agents based on near infrared dyes to enhance contrast at the tumor site. While these agents afford excellent biocompatibility and minimal toxicity, they present limited optoacoustic signal generation capability and rapid renal clearance, which can impede their tumor imaging efficacy. In this work, a synthetic strategy to overcome these limitations utilizing biodegradable DNA-based nanocarrier (DNA-NC) platforms is introduced. DNA-NCs enable the incorporation of near infrared dyes (in this case, IRDye 800CW) at precise positions to enable fluorescence quenching and maximize optoacoustic signal generation. Furthermore, these DNA-NCs show a prolonged blood circulation compared to the native fluorophores, facilitating tumor accumulation by the Enhanced Permeability and Retention (EPR) effect. In vivo imaging of tumor xenografts in mice following intravenous administration of DNA-NCs revealed enhanced OT signals at 24h when compared to free fluorophores, indicating promise for this method to enhance the optoacoustic signal generation capability and tumor uptake of clinically relevant near infrared dyes.

bioengineering↗

bioRxiv2019

ThX - A next-generation probe for the early detection of amyloid aggregates

Neurodegenerative diseases such as Alzheimers and Parkinsons are associated with protein misfolding and aggregation. Recent studies suggest that the small, rare and heterogeneous oligomeric species, formed early on in the aggregation process, may be a source of cytotoxicity. Thioflavin T (ThT) is currently the gold-standard fluorescent probe for the study of amyloid proteins and aggregation processes. However, the poor photophysical and binding properties of ThT impairs the study of oligomers. To overcome this challenge, we have designed Thioflavin X, (ThX), a next-generation fluorescent probe which displays superior properties; including a 5-fold increase in brightness and 7-fold increase in binding affinity to amyloidogenic proteins. As an extrinsic dye, this can be used to study unique structural amyloid features both in bulk and on a single-aggregate level. Furthermore, ThX can be used as a super-resolution imaging probe in single-molecule localisation microscopy. Finally, we demonstrate that ThX can be used to detect a distinct oligomeric species, not observed via traditional ThT imaging.

biophysics↗

bioRxiv2017

Photoacoustic molecular rulers based on DNA nanostructures

Molecular rulers that rely on the Forster resonance energy transfer (FRET) mechanism are widely used to investigate dynamic molecular processes that occur on the nanometer scale. However, the capabilities of these fluorescence molecular rulers are fundamentally limited to shallow imaging depths by light scattering in biological samples. Photoacoustic tomography (PAT) has recently emerged as a high resolution modality for in vivo imaging, coupling optical excitation with ultrasound detection. In this paper, we report the capability of PAT to probe distance-dependent FRET at centimeter depths. Using DNA nanotechnology we created several nanostructures with precisely positioned fluorophore-quencher pairs over a range of nanoscale separation distances. PAT of the DNA nanostructures showed distance-dependent photoacoustic signal generation and experimentally demonstrated the ability of PAT to reveal the FRET process deep within tissue mimicking phantoms. Further, we experimentally validated these DNA nanostructures as providing a novel and biocompatible strategy to augment the intrinsic photoacoustic signal generation capabilities of small molecule fluorescent dyes.

bioengineering↗