understanding-changes-mitochondrial-morphology-through-dynamic-three

Understanding the Changes in Mitochondrial Morphology through Dynamic and Three-dimensional Fluorescence Micrographs

Mitochondria are highly dynamic organelles that are vital to the survival of any animal, undergoing regular fission and fusion events in response to the ...

Stellenbosch University

Confocal microscopes deliver detailed three-dimensional data and are instrumental in biological analysis and research. Usually, this three-dimensional data is rendered as a projection onto a two-dimensional display. We describe a system for rendering such data using a modern virtual reality (VR) headset. Sample manipulation is possible by fully-immersive hand-tracking and also by means of a conventional gamepad. We apply this system to the specific task of colocalization analysis, an important analysis tool in biological microscopy. We evaluate our system by means of a set of user trials.

Virtual reality assisted microscopy data visualization and colocalization analysis.

Although modern fluorescence microscopy produces detailed three-dimensional (3D) datasets, colocalization analysis and region of interest (ROI) selection is most commonly performed two-dimensionally (2D) using maximum intensity projections (MIP). However, these 2D projections exclude much of the available data. Furthermore, 2D ROI selections cannot adequately select complex 3D structures which may inadvertently lead to either the exclusion of relevant or the inclusion of irrelevant data points, consequently affecting the accuracy of the colocalization analysis. Using a virtual reality (VR) enabled system, we demonstrate that 3D visualization, sample interrogation and analysis can be achieved in a highly controlled and precise manner. We calculate several key colocalization metrics using both 2D and 3D derived super-resolved structured illumination-based data sets. Using a neuronal injury model, we investigate the change in colocalization between Tau and acetylated α-tubulin at control conditions, after 6 hours and again after 24 hours. We demonstrate that performing colocalization analysis in 3D enhances its sensitivity, leading to a greater number of statistically significant differences than could be established when using 2D methods. Moreover, by carefully delimiting the 3D structures under analysis using the 3D VR system, we were able to reveal a time dependent loss in colocalization between the Tau and microtubule network as an early event in neuronal injury. This behavior could not be reliably detected using a 2D based projection. We conclude that, using 3D colocalization analysis, biologically relevant samples can be interrogated and assessed with greater precision, thereby better exploiting the potential of fluorescence-based image analysis in biomedical research.

Improved region of interest selection and colocalization analysis in three-dimensional fluorescence microscopy samples using virtual reality.

Leucine-rich repeat kinase 2 (LRRK2) is important in various cellular processes including mitochondrial homeostasis and mutations in this gene lead to Parkinson's disease (PD). However, the full spectrum of LRRK2's functions remain to be elucidated. The translocase of outer mitochondrial membrane (TOM) complex is essential for the import of almost all nuclear-encoded mitochondrial proteins and is fundamental for cellular survival. Using co-immunoprecipitation, super-resolution structured illumination microscopy (SR-SIM), and 3D virtual reality (VR) assisted co-localization analysis techniques we show that wild-type and mutant (G2019S) LRRK2 associate and co-localize with subunits of the TOM complex, either under basal (dimethyl sulfoxide, DMSO) or stress-induced (carbonyl cyanide m-chlorophenyl hydrazine, CCCP) conditions. Interestingly, LRRK2 interacted with TOM40 under both DMSO and CCCP conditions, and when the PD causing mutation, G2019S was introduced, the association was not altered. Moreover, overexpression of G2019S LRRK2 resulted in the formation of large, perinuclear aggregates that co-localized with the TOM complex. Taken together, this is the first study to show that both WT and mutant LRRK2 associate with the TOM complex subunits. These findings provide additional evidence for LRRK2's role in mitochondrial function which has important implications for its role in PD pathogenesis.

Wild-type and mutant (G2019S) leucine-rich repeat kinase 2 (LRRK2) associate with subunits of the translocase of outer mitochondrial membrane (TOM) complex.

The qualitative analysis of colocalisation in fluorescence microscopy is of critical importance to the understanding of biological processes and cellular function. However, the degree of accuracy achieved may differ substantially when executing different yet commonly utilized colocalisation analyses. We propose a novel biological visual analysis method that determines the correlation within the fluorescence intensities and subsequently uses this correlation to assign a colourmap value to each voxel in a three-dimensional sample while also highlighting volumes with greater combined fluorescence intensity. This addresses the ambiguity and variability which can be introduced into the visualisation of the spatial distribution of correlation between two fluorescence channels when the colocalisation between these channels is not considered. Most currently employed and generally accepted methods of visualising colocalisation using a colourmap can be negatively affected by this ambiguity, for example by incorrectly indicating non-colocalised voxels as positively correlated. In this paper we evaluate the proposed method by applying it to both synthetic data and biological fluorescence micrographs and demonstrate how it can enhance the visualisation in a robust way by visualising only truly colocalised regions using a colourmap to indicate the qualitative measure of the correlation between the fluorescence intensities. This approach may substantially support fluorescence microscopy applications in which precise colocalisation analysis is of particular relevance.

Regression adjusted colocalisation colour mapping (RACC): A novel biological visual analysis method for qualitative colocalisation analysis of 3D fluorescence micrographs.

Mitochondrial fission and fusion play an important role not only in maintaining mitochondrial homeostasis but also in preserving overall cellular viability. However, quantitative analysis based on the three-dimensional localisation of these highly dynamic mitochondrial events in the cellular context has not yet been accomplished. Moreover, it remains largely uncertain where in the mitochondrial network depolarisation is most likely to occur. We present the mitochondrial event localiser (MEL), a method that allows high-throughput, automated and deterministic localisation and quantification of mitochondrial fission, fusion and depolarisation events in large three-dimensional microscopy time-lapse sequences. In addition, MEL calculates the number of mitochondrial structures as well as their combined and average volume for each image frame in the time-lapse sequence. The mitochondrial event locations can subsequently be visualised by superposition over the fluorescence micrograph z-stack. We apply MEL to both control samples as well as to cells before and after treatment with hydrogen peroxide (H2O2). An average of 9.3/7.2/2.3 fusion/fission/depolarisation events per cell were observed respectively for every 10 sec in the control cells. With peroxide treatment, the rate initially shifted toward fusion with and average of 15/6/3 events per cell, before returning to a new equilibrium not far from that of the control cells, with an average of 6.2/6.4/3.4 events per cell. These MEL results indicate that both pre-treatment and control cells maintain a fission/fusion equilibrium, and that depolarisation is higher in the post-treatment cells. When individually validating mitochondrial events detected with MEL, for a representative cell for the control and treated samples, the true-positive events were 47%/49%/14% respectively for fusion/fission/depolarisation events. We conclude that MEL is a viable method of quantitative mitochondrial event analysis.

Mitochondrial event localiser (MEL) to quantitativelydescribe fission, fusion and depolarisation in the three-dimensional space.

Mitochondria and peroxisomes are dynamic signaling organelles that constantly undergo fission, driven by the large GTPase dynamin-related protein 1 (DRP1; encoded by DNM1L). Patients with de novo heterozygous missense mutations in DNM1L present with encephalopathy due to defective mitochondrial and peroxisomal fission (EMPF1) - a devastating neurodevelopmental disease with no effective treatment. To interrogate the mechanisms by which DRP1 mutations cause cellular dysfunction, we used human-derived fibroblasts from patients who present with EMPF1. In addition to elongated mitochondrial morphology and lack of fission, patient cells display lower coupling efficiency, increased proton leak and upregulation of glycolysis. Mitochondrial hyperfusion also results in aberrant cristae structure and hyperpolarized mitochondrial membrane potential. Peroxisomes show a severely elongated morphology in patient cells, which is associated with reduced respiration when cells are reliant on fatty acid oxidation. Metabolomic analyses revealed impaired methionine cycle and synthesis of pyrimidine nucleotides. Our study provides insight into the role of mitochondrial dynamics in cristae maintenance and the metabolic capacity of the cell, as well as the disease mechanism underlying EMPF1.

DRP1 mutations associated with EMPF1 encephalopathy alter mitochondrial membrane potential and metabolic programs.

This paper documents the development of a novel method to predict the occurrence and exact locations of mitochondrial fission, fusion and depolarisation events in three dimensions. This novel implementation of neural networks to predict these events using information encoded only in the morphology of the mitochondria eliminate the need for time-lapse sequences of cells. The ability to predict these morphological mitochondrial events using a single image can not only democratise research but also revolutionise drug trials. The occurrence and location of these events were successfully predicted with a three-dimensional version of the Pix2Pix generative adversarial network (GAN) as well as a three-dimensional adversarial segmentation network called the Vox2Vox GAN. The Pix2Pix GAN predicted the locations of mitochondrial fission, fusion and depolarisation events with accuracies of 35.9%, 33.2% and 4.90%, respectively. Similarly, the Vox2Vox GAN achieved accuracies of 37.1%, 37.3% and 7.43%. The accuracies achieved by the networks in this paper are too low for the immediate implementation of these tools in life science research. They do however indicate that the networks have modelled the mitochondrial dynamics to some degree of accuracy and may therefore still be helpful as an indication of where events might occur if time lapse sequences are not available. The prediction of these morphological mitochondrial events have, to our knowledge, never been achieved before in literature. The results from this paper can be used as a baseline for the results obtained by future work.

Predicting mitochondrial fission, fusion and depolarisation event locations from a single z-stack.

Face recognition is widely used for security and access control. Its performance is limited when working with highly pigmented skin tones due to training bias caused by the under-representation of darker-skinned individuals in existing datasets and the fact that darker skin absorbs more light and therefore reflects less discernible detail in the visible spectrum. To improve performance, this work incorporated the infrared (IR) spectrum, which is perceived by electronic sensors. We augmented existing datasets with images of highly pigmented individuals captured using the visible, IR, and full spectra and fine-tuned existing face recognition systems to compare the performance of these three. We found a marked improvement in accuracy and AUC values of the receiver operating characteristic (ROC) curves when including the IR spectrum, increasing performance from 97.5% to 99.0% for highly pigmented faces. Different facial orientations and narrow cropping also improved performance, and the nose region was the most important feature for recognition.

Using infrared to improve face recognition of individuals with highly pigmented skin.

Memantine is an FDA-approved, non-competitive NMDA-receptor antagonist that has been shown to have mitochondrial protective effects, improve cell viability and enhance clearance of Aβ peptide. Currently, there are uncertainties regarding the precise molecular targets as well as the most favourable treatment concentrations of memantine. Here, we made use of an imaging-based approach to investigate the concentration-dependent effects of memantine on mitochondrial fission and fusion dynamics, autophagy and mitochondrial quality control using a neuronal model of CCCP-induced mitochondrial injury so as to better unpack how memantine aids in promoting neuronal health. GT1-7 murine hypothalamic cells were cultured under standard conditions, treated with a relatively high and low concentration (100 µM and 50 µM) of memantine for 48 h. Images were acquired using a Zeiss 780 PS1 platform. Utilising the mitochondrial event localiser (MEL), we demonstrated clear concentration-dependent effects of memantine causing a protective response to mitochondrial injury. Both concentrations maintained the mitochondrial network volume whilst the low concentration caused an increase in mitochondrial number as well as increased fission and fusion events following CCCP-induced injury. Additionally, we made use of a customised Python-based image processing and analysis pipeline to quantitatively assess memantine-dependent changes in the autophagosomal and lysosomal compartments. Our results revealed that memantine elicits a differential, concentration-dependent effect on autophagy pathway intermediates. Intriguingly, low but not high concentrations of memantine lead to the induction of mitophagy. Taken together, our findings have shown that memantine is able to protect the mitochondrial network by preserving its volume upon mitochondrial injury with high concentrations of memantine inducing macroautophagy, whereas low concentrations lead to the induction of mitophagy.

The Highs and Lows of Memantine-An Autophagy and Mitophagy Inducing Agent That Protects Mitochondria.

Propionic acid (PPA) is used to study the role of mitochondrial dysfunction in neurodevelopmental conditions like autism spectrum disorders. PPA is known to disrupt mitochondrial biogenesis, metabolism, and turnover. However, the effect of PPA on mitochondrial dynamics, fission, and fusion remains challenging to study due to the complex temporal nature of these mechanisms. Here, we use complementary quantitative visualization techniques to examine how PPA influences mitochondrial ultrastructure, morphology, and dynamics in neuronal-like SH-SY5Y cells. PPA (5 mM) induced a significant decrease in mitochondrial area (p < 0.01), Feret's diameter and perimeter (p < 0.05), and in area (p < 0.01). Mitochondrial event localiser analysis demonstrated a significant increase in fission and fusion events (p < 0.05) that preserved mitochondrial network integrity under stress. Moreover, mRNA expression of cMYC (p < 0.0001), NRF1 (p < 0.01), TFAM (p < 0.05), STOML2 (p < 0.0001), and OPA1 (p < 0.01) was significantly decreased. This illustrates a remodeling of mitochondrial morphology, biogenesis, and dynamics to preserve function under stress. Our data provide new insights into the influence of PPA on mitochondrial dynamics and highlight the utility of visualization techniques to study the complex regulatory mechanisms involved in the mitochondrial stress response.

Propionic acid induces alterations in mitochondrial morphology and dynamics in SH-SY5Y cells.

Neurodegenerative diseases are often characterized by hydrophobic inclusion bodies, and it may be the case that the aggregate-prone proteins that comprise these inclusion bodies are in fact the cause of neurotoxicity. Indeed, the appearance of protein aggregates leads to a proteostatic imbalance that causes various interruptions in physiological cellular processes, including lysosomal and mitochondrial dysfunction, as well as break down in calcium homeostasis. Oftentimes the approach to counteract proteotoxicity is taken to merely upregulate autophagy, measured by an increase in autophagosomes, without a deeper assessment of contributors toward effective turnover through autophagy. There are various ways in which autophagy is regulated ranging from the mammalian target of rapamycin (mTOR) to acetylation status of proteins. Healthy mitochondria and the intracellular energetic charge they preserve are key for the acidification status of lysosomes and thus ensuring effective clearance of components through the autophagy pathway. Both mitochondria and lysosomes have been shown to bear functional protein complexes that aid in the regulation of autophagy. Indeed, it may be the case that minimizing the proteins associated with the respective neurodegenerative pathology may be of greater importance than addressing molecularly their resulting inclusion bodies. It is in this context that this review will dissect the autophagy signaling pathway, its control and the manner in which it is molecularly and functionally connected with the mitochondrial and lysosomal system, as well as provide a summary of the role of autophagy dysfunction in driving neurodegenerative disease as a means to better position the potential of rapamycin-mediated bioactivities to control autophagy favorably.

Cogs in the autophagic machine-equipped to combat dementia-prone neurodegenerative diseases.

Knowledge of a person's level of skin pigmentation, or so-called "skin tone", has proven to be an important building block in improving the performance and fairness of various applications that rely on computer vision. These include medical diagnosis of skin conditions, cosmetic and skincare support, and face recognition, especially for darker skin tones. However, the perception of skin tone, whether by the human eye or by an optoelectronic sensor, uses the reflection of light from the skin. The source of this light, or illumination, affects the skin tone that is perceived. This study aims to refine and assess a convolutional neural network-based skin tone estimation model that provides consistent accuracy across different skin tones under various lighting conditions. The 10-point Monk Skin Tone Scale was used to represent the skin tone spectrum. A dataset of 21,375 images was captured from volunteers across the pigmentation spectrum. Experimental results show that a regression model outperforms other models, with an estimated-to-target distance of 0.5. Using a threshold estimated-to-target skin tone distance of 2 for all lights results in average accuracy values of 85.45% and 97.16%. With the Monk Skin Tone Scale segmented into three groups, the lighter exhibits strong accuracy, the middle displays lower accuracy, and the dark falls between the two. The overall skin tone estimation achieves average error distances in the LAB space of 16.40±20.62.

Skin Tone Estimation under Diverse Lighting Conditions.

There exists a distinct lack of publicly available literature addressing the most effective hardware design for photoplethysmography (PPG) devices for clinical and domestic applications. In this article, this problem was addressed by investigating the hardware design configuration of a PPG device, with particular emphasis on the light source wavelength, light source brightness, number of light sources, photodetector lens shape, and sensor-to-skin contact pressure. A participant study was conducted to collect cardiovascular metric data from 110 participants with varying skin tones, which was used to determine the most promising hardware configuration of the PPG device. It was concluded that the device had little bias to skin tone, with only a 3.82 dB variance over all the skin tones tested.

Investigating the Design of a Photoplethysmography Device for Vital Sign Monitoring.

Biomechanical movement analysis is crucial in medical and sports contexts, yet the technology remains expensive and inaccessible to many. Recent advancements in machine learning and computer vision, particularly in Pose Estimation (PE), offer promising alternatives. PE models detect key points on the human body to estimate its pose in either 2D or 3D space, enabling markerless motion capture. This approach facilitates more natural and flexible movement tracking without the need for physical markers. However, markerless systems generally lack the accuracy of marker-based methods and require extensive annotated data for training, which is often anatomically inaccurate. Additionally, current 3D pose estimation techniques face practical challenges, including complex hardware setups, intricate camera calibrations, and a shortage of reliable ground truth 2D-3D datasets. To address these challenges, we introduce a multimodal dataset comprising 3,444 recordings, 2,896,943 image frames, and 3,804,413 corresponding 3D and 2D marker-based motion capture keypoint coordinates. The dataset includes 28 participants performing eight strength and conditioning actions at three different speeds, with full image and keypoint data available for 26 participants, while two participants have only keypoint data without accompanying image data. Video and image data were captured using a custom-developed multi-RGB-camera system, while the marker-based 3D data was acquired using the Vicon system and subsequently projected into each camera's internal coordinate system, represented in both 3D space and 2D image space. The multi-RGB-camera system consists of six cameras arranged in a circular formation around the subject, offering a full 360° view of the scene from the same height and resulting in a diverse set of viewing angles. The recording setup was designed to allow both capture systems to record participants' movements simultaneously, synchronizing the data to provide ground truth 3D data, which was then back-projected to generate 2D-pixel keypoint data for each corresponding image frame. This design enables the dataset to support both 2D and 3D pose estimation tasks. To ensure anatomical accuracy, a professional placed an extensive array of markers on each participant, adhering to industry standards. The dataset also includes all intrinsic and extrinsic camera parameters, as well as origin axis data, necessary for performing any 3D or 2D projections. This allows the dataset to be adjusted and tailored to meet specific research or application needs.

Article	Year
Virtual reality assisted microscopy data visualization and colocalization analysis. BMC bioinformatics\| PubMed ID: 28251867	2017
Improved region of interest selection and colocalization analysis in three-dimensional fluorescence microscopy samples using virtual reality. PloS one\| PubMed ID: 30157239	2018
Wild-type and mutant (G2019S) leucine-rich repeat kinase 2 (LRRK2) associate with subunits of the translocase of outer mitochondrial membrane (TOM) complex. Experimental cell research\| PubMed ID: 30597143	2019
Regression adjusted colocalisation colour mapping (RACC): A novel biological visual analysis method for qualitative colocalisation analysis of 3D fluorescence micrographs. PloS one\| PubMed ID: 31710634	2019
Mitochondrial event localiser (MEL) to quantitativelydescribe fission, fusion and depolarisation in the three-dimensional space. PloS one\| PubMed ID: 33378337	2020
DRP1 mutations associated with EMPF1 encephalopathy alter mitochondrial membrane potential and metabolic programs. Journal of cell science\| PubMed ID: 36763487	2023
Predicting mitochondrial fission, fusion and depolarisation event locations from a single z-stack. PloS one\| PubMed ID: 36888628	2023
Using infrared to improve face recognition of individuals with highly pigmented skin. iScience\| PubMed ID: 37416460	2023
The Highs and Lows of Memantine-An Autophagy and Mitophagy Inducing Agent That Protects Mitochondria. Cells\| PubMed ID: 37443760	2023
Propionic acid induces alterations in mitochondrial morphology and dynamics in SH-SY5Y cells. Scientific reports\| PubMed ID: 37582965	2023
Cogs in the autophagic machine-equipped to combat dementia-prone neurodegenerative diseases. Frontiers in molecular neuroscience\| PubMed ID: 37720551	2023
Skin Tone Estimation under Diverse Lighting Conditions. Journal of imaging\| PubMed ID: 38786563	2024
Investigating the Design of a Photoplethysmography Device for Vital Sign Monitoring. Sensors (Basel, Switzerland)\| PubMed ID: 40293003	2025
SUMediPose: A 2D-3D pose estimation dataset. Data in brief\| PubMed ID: 40391133	2025

Rensu Theart

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