Computational imaging reveals mitochondrial morphology as a biomarker of cancer phenotype and drug response

The link between Mitochondria and Sarcopenia

Sarcopenia, a widespread condition, is characterized by a variety of factors influencing its development. The causes of sarcopenia differ depending on the age of the individual. It is defined as the combination of decreased muscle mass and impaired muscle function, primarily observed in association with ageing. As people age from 20 to 80 years old, there is an approximate 30% reduction in muscle mass and a 20% decline in cross-sectional area. This decline is attributed to a decrease in the size and number of muscle fibres. The regression of muscle mass and strength increases the risk of fractures, frailty, reduced quality of life, and loss of independence. Muscle cells, fibres, and tissues shrink, resulting in diminished muscle power, volume, and strength in major muscle groups. One prominent theory of cellular ageing posits a strong positive relationship between age and oxidative damage. Heightened oxidative stress leads to early-onset sarcopenia, characterized by neuromuscular innervation breakdown, muscle atrophy, and dysfunctional mitochondrial muscles. Ageing muscles generate more reactive oxygen species (ROS), and experience decreased oxygen consumption and ATP synthesis compared to younger muscles. Additionally, changes in mitochondrial protein interactions, cristae structure, and networks may contribute to ADP insensitivity, which ultimately leads to sarcopenia. Within this framework, this review provides a comprehensive summary of our current understanding of the role of mitochondria in sarcopenia and other muscle degenerative diseases, highlighting the crucial need for further research in these areas.

Mitochondrial metabolism: A moving target in hepatocellular carcinoma therapy

Mitochondria are pivotal contributors to cancer mechanisms due to their homeostatic and pathological roles in cellular bioenergetics, biosynthesis, metabolism, signaling, and survival. During transformation and tumor initiation, mitochondrial function is often disrupted by oncogenic mutations, leading to a metabolic profile distinct from precursor cells. In this review, we focus on hepatocellular carcinoma, a cancer arising from metabolically robust and nutrient rich hepatocytes, and discuss the mechanistic impact of altered metabolism in this setting. We provide distinctions between normal mitochondrial activity versus disease-related function which yielded therapeutic opportunities, along with highlighting recent preclinical and clinical efforts focused on targeting mitochondrial metabolism. Finally, several novel strategies for exploiting mitochondrial programs to eliminate hepatocellular carcinoma cells in metabolism-specific contexts are presented to integrate these concepts and gain foresight into the future of mitochondria-focused therapeutics.

A highly efficient, scalable pipeline for fixed feature extraction from large-scale high-content imaging screens

Applying artificial intelligence (AI) to image-based morphological profiling cells offers significant potential for identifying disease states and drug responses in high-content imaging (HCI) screens. When differences between populations (e.g., healthy vs. diseased) are unknown or imperceptible to the human eye, large-scale HCI screens are essential, providing numerous replicates to build reliable models and accounting for confounding factors like donor and intra-experimental variations. As screen sizes grow, so does the challenge of analyzing high-dimensional datasets in an efficient way while preserving interpretable features and predictive power. Here, we introduce ScaleFEx℠, a memory-efficient, open-source Python pipeline that extracts biologically meaningful features from HCI datasets using minimal computational resources or scalable cloud infrastructure. ScaleFEx can be used together with AI models to successfully identify phenotypic shifts in drug-treated cells and rank interpretable features, and is applicable to public datasets, highlighting its potential to accelerate the discovery of disease-associated phenotypes and new therapeutics.

AutoMitoNetwork: Software for analyzing mitochondrial networks in autofluorescence images to enable label-free cell classification

High-resolution mitochondria imaging in combination with image analysis tools have significantly advanced our understanding of cellular function in health and disease. However, most image analysis tools for mitochondrial studies have been designed to work with fluorescently labeled images only. Additionally, efforts to integrate features describing mitochondrial networks with machine learning techniques for the differentiation of cell types have been limited. Herein, we present AutoMitoNetwork software for image-based assessment of mitochondrial networks in label-free autofluorescence images using a range of interpretable morphological, intensity, and textural features. To demonstrate its utility, we characterized unstained mitochondrial networks in healthy retinal cells and in retinal cells exposed to two types of treatments: rotenone, which directly inhibited mitochondrial respiration and ATP production, and iodoacetic acid, which had a milder impact on mitochondrial networks via the inhibition of anaerobic glycolysis. For both cases, our multi-dimensional feature analysis combined with a support vector machine classifier distinguished between healthy cells and those treated with rotenone or iodoacetic acid. Subtle changes in morphological features were measured including increased fragmentation in the treated retinal cells, pointing to an association with metabolic mechanisms. AutoMitoNetwork opens new options for image-based machine learning in label-free imaging, diagnostics, and mitochondrial disease drug development.

Rational design of mitochondria-targeted fluorescent biosensors for in vivo elucidation of the interaction between breast cancer metastasis and mitochondrial autophagy

Breast cancer lung metastases (BCLM) are a major cause of high mortality in patients. The shortage of therapeutic targets and rapid drug screening tools for BCLM is a major challenge at present. Mitochondrial autophagy, which involves the degradation of proteins associated with cancer cell aggressiveness, represents a possible therapeutic approach for the treatment of BCLM. Herein, four fluorescent biosensors with different alkyl chains were designed and synthesized to monitor mitochondrial autophagy. Among them, PMV-12 demonstrated the highest sensitivity to viscosity variance, the least impact on polarity, and the longest imaging time. The introduction of the C12-chain made PMV-12 anchored in the mitochondrial membrane without being disturbed by changes of the mitochondrial membrane potential (MMP), thereby achieving the long-term monitor in situ for mitochondrial autophagy. Mitochondria stained with PMV-12 induced swelling and viscosity increase after treating with apigenin, which indicated that apigenin is a potential mitochondrial autophagy inducer. Apigenin was subsequently verified to inhibit cancer cell invasion by 92%. Furthermore, PMV-12 could monitor the process of BCLM in vivo and evaluate the therapeutic effects of apigenin. This work provides a fluorescent tool for elucidating the role of mitochondrial autophagy in the BCLM process and for anti-metastatic drug development.

Mitochondria: A source of potential biomarkers for non-communicable diseases

Mitochondria, as an endosymbiont of eukaryotic cells, controls multiple cellular activities, including respiration, reactive oxygen species production, fatty acid synthesis, and death. Though the majority of functional mitochondrial proteins are translated through a nucleus-controlled process, very few of them (∼10%) are translated within mitochondria through their own machinery. Germline and somatic mutations in mitochondrial and nuclear DNA significantly impact mitochondrial homeostasis and function. Such modifications disturbing mitochondrial biogenesis, metabolism, or mitophagy eventually resulted in cellular pathophysiology. In this chapter, we discussed the impact of mitochondria and its dysfunction on several non-communicable diseases like cancer, diabetes, neurodegenerative, and cardiovascular problems. Mitochondrial dysfunction and its outcome could be screened by currently available omics-based techniques, flow cytometry, and high-resolution imaging. Such characterization could be evaluated as potential biomarkers to assess the disease burden and prognosis.

MMCL-CDR: enhancing cancer drug response prediction with multi-omics and morphology images contrastive representation learning

MOTIVATION

Cancer is a complex disease that results in a significant number of global fatalities. Treatment strategies can vary among patients, even if they have the same type of cancer. The application of precision medicine in cancer shows promise for treating different types of cancer, reducing healthcare expenses, and improving recovery rates. To achieve personalized cancer treatment, machine learning models have been developed to predict drug responses based on tumor and drug characteristics. However, current studies either focus on constructing homogeneous networks from single data source or heterogeneous networks from multiomics data. While multiomics data have shown potential in predicting drug responses in cancer cell lines, there is still a lack of research that effectively utilizes insights from different modalities. Furthermore, effectively utilizing the multimodal knowledge of cancer cell lines poses a challenge due to the heterogeneity inherent in these modalities.

RESULTS

To address these challenges, we introduce MMCL-CDR (Multimodal Contrastive Learning for Cancer Drug Responses), a multimodal approach for cancer drug response prediction that integrates copy number variation, gene expression, morphology images of cell lines, and chemical structure of drugs. The objective of MMCL-CDR is to align cancer cell lines across different data modalities by learning cell line representations from omic and image data, and combined with structural drug representations to enhance the prediction of cancer drug responses (CDR). We have carried out comprehensive experiments and show that our model significantly outperforms other state-of-the-art methods in CDR prediction. The experimental results also prove that the model can learn more accurate cell line representation by integrating multiomics and morphological data from cell lines, thereby improving the accuracy of CDR prediction. In addition, the ablation study and qualitative analysis also confirm the effectiveness of each part of our proposed model. Last but not least, MMCL-CDR opens up a new dimension for cancer drug response prediction through multimodal contrastive learning, pioneering a novel approach that integrates multiomics and multimodal drug and cell line modeling.

AVAILABILITY AND IMPLEMENTATION

MMCL-CDR is available at https://github.com/catly/MMCL-CDR.

Quantitative assessment of mitochondrial morphology relevant for studies on cellular health and environmental toxicity

Mitochondria are essential organelles that play crucial roles in cellular energy metabolism, calcium signaling and apoptosis. Their importance in tissue homeostasis and stress responses, combined to their ability to transition between various structural and functional states, make them excellent organelles for monitoring cellular health. Quantitative assessment of mitochondrial morphology can therefore provide valuable insights into environmentally-induced cell damage. High-content screening (HCS) provides a powerful tool for analyzing organelles and cellular substructures. We developed a fully automated and miniaturized HCS wet-plus-dry pipeline (MITOMATICS) exploiting mitochondrial morphology as a marker for monitoring cellular health or damage. MITOMATICS uses an in-house, proprietary software (MitoRadar) to enable fast, exhaustive and cost-effective analysis of mitochondrial morphology and its inherent diversity in live cells. We applied our pipeline and big data analytics software to assess the mitotoxicity of selected chemicals, using the mitochondrial uncoupler CCCP as an internal control. Six different pesticides (inhibiting complexes I, II and III of the mitochondrial respiratory chain) were tested as individual compounds and five other pesticides present locally in Occitanie (Southern France) were assessed in combination to determine acute mitotoxicity. Our results show that the assayed pesticides exhibit specific signatures when used as single compounds or chemical mixtures and that they function synergistically to impact mitochondrial architecture. Study of environment-induced mitochondrial damage has the potential to open new fields in mechanistic toxicology, currently underexplored by regulatory toxicology and exposome research. Such exploration could inform health policy guidelines and foster pharmacological intervention, water, air and soil pollution control and food safety.

Mitochondrial heterogeneity in diseases

As key organelles involved in cellular metabolism, mitochondria frequently undergo adaptive changes in morphology, components and functions in response to various environmental stresses and cellular demands. Previous studies of mitochondria research have gradually evolved, from focusing on morphological change analysis to systematic multiomics, thereby revealing the mitochondrial variation between cells or within the mitochondrial population within a single cell. The phenomenon of mitochondrial variation features is defined as mitochondrial heterogeneity. Moreover, mitochondrial heterogeneity has been reported to influence a variety of physiological processes, including tissue homeostasis, tissue repair, immunoregulation, and tumor progression. Here, we comprehensively review the mitochondrial heterogeneity in different tissues under pathological states, involving variant features of mitochondrial DNA, RNA, protein and lipid components. Then, the mechanisms that contribute to mitochondrial heterogeneity are also summarized, such as the mutation of the mitochondrial genome and the import of mitochondrial proteins that result in the heterogeneity of mitochondrial DNA and protein components. Additionally, multiple perspectives are investigated to better comprehend the mysteries of mitochondrial heterogeneity between cells. Finally, we summarize the prospective mitochondrial heterogeneity-targeting therapies in terms of alleviating mitochondrial oxidative damage, reducing mitochondrial carbon stress and enhancing mitochondrial biogenesis to relieve various pathological conditions. The possibility of recent technological advances in targeted mitochondrial gene editing is also discussed.

Spatial topology of organelle is a new breast cancer cell classifier

Genomics and proteomics have been central to identify tumor cell populations, but more accurate approaches to classify cell subtypes are still lacking. We propose a new methodology to accurately classify cancer cells based on their organelle spatial topology. Herein, we developed an organelle topology-based cell classification pipeline (OTCCP), which integrates artificial intelligence (AI) and imaging quantification to analyze organelle spatial distribution and inter-organelle topology. OTCCP was used to classify a panel of human breast cancer cells, grown as 2D monolayer or 3D tumor spheroids using early endosomes, mitochondria, and their inter-organelle contacts. Organelle topology allows for a highly precise differentiation between cell lines of different subtypes and aggressiveness. These findings lay the groundwork for using organelle topological profiling as a fast and efficient method for phenotyping breast cancer function as well as a discovery tool to advance our understanding of cancer cell biology at the subcellular level.

Interaction between PI3K and the VDAC2 channel tethers Ras-PI3K-positive endosomes to mitochondria and promotes endosome maturation

Intracellular organelles of mammalian cells communicate with one another during various cellular processes. The functions and molecular mechanisms of such interorganelle association remain largely unclear, however. We here identify voltage-dependent anion channel 2 (VDAC2), a mitochondrial outer membrane protein, as a binding partner of phosphoinositide 3-kinase (PI3K), a regulator of clathrin-independent endocytosis downstream of the small GTPase Ras. VDAC2 tethers endosomes positive for the Ras-PI3K complex to mitochondria in response to cell stimulation with epidermal growth factor and promotes clathrin-independent endocytosis, as well as endosome maturation at membrane association sites. With an optogenetics system to induce mitochondrion-endosome association, we find that, in addition to its structural role in such association, VDAC2 is functionally implicated in the promotion of endosome maturation. The mitochondrion-endosome association thus plays a role in the regulation of clathrin-independent endocytosis and endosome maturation.

Biomarkers of mitochondrial origin: a futuristic cancer diagnostic

Cancer is a highly fatal disease without effective early-stage diagnosis and proper treatment. Along with the oncoproteins and oncometabolites, several organelles from cancerous cells are also emerging as potential biomarkers. Mitochondria isolated from cancer cells are one such biomarker candidates. Cancerous mitochondria exhibit different profiles compared with normal ones in morphology, genomic, transcriptomic, proteomic and metabolic landscape. Here, the possibilities of exploring such characteristics as potential biomarkers through single-cell omics and Artificial Intelligence (AI) are discussed. Furthermore, the prospects of exploiting the biomarker-based diagnosis and its futuristic utilization through circulatory tumor cell technology are analyzed. A successful alliance of circulatory tumor cell isolation protocols and a single-cell omics platform can emerge as a next-generation diagnosis and personalized treatment procedure.

Exploiting the tumor immune microenvironment and immunometabolism using mitochondria-targeted drugs: Challenges and opportunities in racial disparity and cancer outcome research

Black and Hispanic cancer patients have a higher incidence of cancer mortality. Many factors (e.g., socioeconomic differences, insufficient access to healthcare) contribute to racial disparity. Emerging research implicates biological disparity in cancer outcomes. Studies show distinct differences in the tumor immune microenvironment (TIME) in Black cancer patients. Studies also have linked altered mitochondrial metabolism to changes in immune cell activation in TIME. Recent publications revealed a novel immunomodulatory role for triphenylphosphonium-based mitochondrial-targeted drugs (MTDs). These are synthetically modified, naturally occurring molecules (e.g., honokiol, magnolol, metformin) or FDA-approved small molecule drugs (e.g., atovaquone, hydroxyurea). Modifications involve conjugating the parent molecule via an alkyl linker chain to a triphenylphosphonium moiety. These modified molecules (e.g., Mito-honokiol, Mito-magnolol, Mito-metformin, Mito-atovaquone, Mito-hydroxyurea) accumulate in tumor cell mitochondria more effectively than in normal cells and inhibit mitochondrial respiration, induce reactive oxygen species, activate AMPK and redox transcription factors, and inhibit cancer cell proliferation. Besides these intrinsic effects of MTDs in redox signaling and proliferation in tumors, MTDs induced extrinsic effects in the TIME of mouse xenografts. MTD treatment inhibited tumor-suppressive immune cells, myeloid-derived suppressor cells, and regulatory T cells, and activated T cells and antitumor immune effects. One key biological disparity in Black cancer patients was related to altered mitochondrial oxidative metabolism; MTDs targeting vulnerabilities in tumor cells and the TIME may help us understand this biological disparity. Clinical trials should include an appropriate number of Black and Hispanic cancer patients and should validate the intratumoral, antihypoxic effects of MTDs with imaging.

Mitochondrial Superoxide Dismutase in Cisplatin-Induced Kidney Injury

Cisplatin is a chemotherapy agent commonly used to treat a wide variety of cancers. Despite the potential for both severe acute and chronic side effects, it remains a preferred therapeutic option for many malignancies due to its potent anti-tumor activity. Common cisplatin-associated side-effects include acute kidney injury (AKI) and chronic kidney disease (CKD). These renal injuries may cause delays and potentially cessation of cisplatin therapy and have long-term effects on renal function reserve. Thus, developing mechanism-based interventional strategies that minimize cisplatin-associated kidney injury without reducing efficacy would be of great benefit. In addition to its action of cross-linking DNA, cisplatin has been shown to affect mitochondrial metabolism, resulting in mitochondrially derived reactive oxygen species (ROS). Increased ROS formation in renal proximal convoluted tubule cells is associated with cisplatin-induced AKI and CKD. We review the mechanisms by which cisplatin may induce AKI and CKD and discuss the potential of mitochondrial superoxide dismutase mimetics to prevent platinum-associated nephrotoxicity.

Machine learning-based classification of mitochondrial morphology in primary neurons and brain

The mitochondrial network continually undergoes events of fission and fusion. Under physiologic conditions, the network is in equilibrium and is characterized by the presence of both elongated and punctate mitochondria. However, this balanced, homeostatic mitochondrial profile can change morphologic distribution in response to various stressors. Therefore, it is imperative to develop a method that robustly measures mitochondrial morphology with high accuracy. Here, we developed a semi-automated image analysis pipeline for the quantitation of mitochondrial morphology for both in vitro and in vivo applications. The image analysis pipeline was generated and validated utilizing images of primary cortical neurons from transgenic mice, allowing genetic ablation of key components of mitochondrial dynamics. This analysis pipeline was further extended to evaluate mitochondrial morphology in vivo through immunolabeling of brain sections as well as serial block-face scanning electron microscopy. These data demonstrate a highly specific and sensitive method that accurately classifies distinct physiological and pathological mitochondrial morphologies. Furthermore, this workflow employs the use of readily available, free open-source software designed for high throughput image processing, segmentation, and analysis that is customizable to various biological models.

A septin GTPase scaffold of dynein-dynactin motors triggers retrograde lysosome transport

The metabolic and signaling functions of lysosomes depend on their intracellular positioning and trafficking, but the underlying mechanisms are little understood. Here, we have discovered a novel septin GTPase-based mechanism for retrograde lysosome transport. We found that septin 9 (SEPT9) associates with lysosomes, promoting the perinuclear localization of lysosomes in a Rab7-independent manner. SEPT9 targeting to mitochondria and peroxisomes is sufficient to recruit dynein and cause perinuclear clustering. We show that SEPT9 interacts with both dynein and dynactin through its GTPase domain and N-terminal extension, respectively. Strikingly, SEPT9 associates preferentially with the dynein intermediate chain (DIC) in its GDP-bound state, which favors dimerization and assembly into septin multimers. In response to oxidative cell stress induced by arsenite, SEPT9 localization to lysosomes is enhanced, promoting the perinuclear clustering of lysosomes. We posit that septins function as GDP-activated scaffolds for the cooperative assembly of dynein-dynactin, providing an alternative mechanism of retrograde lysosome transport at steady state and during cellular adaptation to stress.

Mito Hacker: a set of tools to enable high-throughput analysis of mitochondrial network morphology

Mitochondria are highly dynamic organelles that can exhibit a wide range of morphologies. Mitochondrial morphology can differ significantly across cell types, reflecting different physiological needs, but can also change rapidly in response to stress or the activation of signaling pathways. Understanding both the cause and consequences of these morphological changes is critical to fully understanding how mitochondrial function contributes to both normal and pathological physiology. However, while robust and quantitative analysis of mitochondrial morphology has become increasingly accessible, there is a need for new tools to generate and analyze large data sets of mitochondrial images in high throughput. The generation of such datasets is critical to fully benefit from rapidly evolving methods in data science, such as neural networks, that have shown tremendous value in extracting novel biological insights and generating new hypotheses. Here we describe a set of three computational tools, Cell Catcher, Mito Catcher and MiA, that we have developed to extract extensive mitochondrial network data on a single-cell level from multi-cell fluorescence images. Cell Catcher automatically separates and isolates individual cells from multi-cell images; Mito Catcher uses the statistical distribution of pixel intensities across the mitochondrial network to detect and remove background noise from the cell and segment the mitochondrial network; MiA uses the binarized mitochondrial network to perform more than 100 mitochondria-level and cell-level morphometric measurements. To validate the utility of this set of tools, we generated a database of morphological features for 630 individual cells that encode 0, 1 or 2 alleles of the mitochondrial fission GTPase Drp1 and demonstrate that these mitochondrial data could be used to predict Drp1 genotype with 87% accuracy. Together, this suite of tools enables the high-throughput and automated collection of detailed and quantitative mitochondrial structural information at a single-cell level. Furthermore, the data generated with these tools, when combined with advanced data science approaches, can be used to generate novel biological insights.

Caveolin-1-mediated sphingolipid oncometabolism underlies a metabolic vulnerability of prostate cancer

Plasma and tumor caveolin-1 (Cav-1) are linked with disease progression in prostate cancer. Here we report that metabolomic profiling of longitudinal plasmas from a prospective cohort of 491 active surveillance (AS) participants indicates prominent elevations in plasma sphingolipids in AS progressors that, together with plasma Cav-1, yield a prognostic signature for disease progression. Mechanistic studies of the underlying tumor supportive onco-metabolism reveal coordinated activities through which Cav-1 enables rewiring of cancer cell lipid metabolism towards a program of 1) exogenous sphingolipid scavenging independent of cholesterol, 2) increased cancer cell catabolism of sphingomyelins to ceramide derivatives and 3) altered ceramide metabolism that results in increased glycosphingolipid synthesis and efflux of Cav-1-sphingolipid particles containing mitochondrial proteins and lipids. We also demonstrate, using a prostate cancer syngeneic RM-9 mouse model and established cell lines, that this Cav-1-sphingolipid program evidences a metabolic vulnerability that is targetable to induce lethal mitophagy as an anti-tumor therapy.

Intracellular localization of polymyxins in human alveolar epithelial cells

Background

Current inhaled polymyxin therapy is empirical and often large doses are administered, which can lead to pulmonary adverse effects. There is a dearth of information on the mechanisms of polymyxin-induced lung toxicity and their intracellular localization in lung epithelial cells.

Objectives

To investigate the intracellular localization of polymyxins in human lung epithelial A549 cells.

Methods

A549 cells were treated with polymyxin B and intracellular organelles (early and late endosomes, endoplasmic reticulum, mitochondria, lysosomes and autophagosomes), ubiquitin protein and polymyxin B were visualized using immunostaining and confocal microscopy. Fluorescence intensities of the organelles and polymyxin B were quantified and correlated for co-localization using ImageJ and Imaris platforms.

Results

Polymyxin B co-localized with early endosomes, lysosomes and ubiquitin at 24 h. Significantly increased lysosomal activity and the autophagic protein LC3A were observed after 0.5 and 1.0 mM polymyxin B treatment at 24 h. Polymyxin B also significantly co-localized with mitochondria (Pearson's R = 0.45) and led to the alteration of mitochondrial morphology from filamentous to fragmented form (n = 3, P < 0.001). These results are in line with the polymyxin-induced activation of the mitochondrial apoptotic pathway observed in A549 cells.

Conclusions

Accumulation of polymyxins on mitochondria probably caused mitochondrial toxicity, resulting in increased oxidative stress and cell death. The formation of autophagosomes and lysosomes was likely a cellular response to the polymyxin-induced stress and played a defensive role by disassembling dysfunctional organelles and proteins. Our study provides new mechanistic information on polymyxin-induced lung toxicity, which is vital for optimizing inhaled polymyxins in the clinic.

Monitoring and Determining Mitochondrial Network Parameters in Live Lung Cancer Cells

Mitochondria are dynamic organelles that constantly fuse and divide, forming dynamic tubular networks. Abnormalities in mitochondrial dynamics and morphology are linked to diverse pathological states, including cancer. Thus, alterations in mitochondrial parameters could indicate early events of disease manifestation or progression. However, finding reliable and quantitative tools for monitoring mitochondria and determining the network parameters, particularly in live cells, has proven challenging. Here, we present a 2D confocal imaging-based approach that combines automatic mitochondrial morphology and dynamics analysis with fractal analysis in live small cell lung cancer (SCLC) cells. We chose SCLC cells as a test case since they typically have very little cytoplasm, but an abundance of smaller mitochondria compared to many of the commonly used cell types. The 2D confocal images provide a robust approach to quantitatively measure mitochondrial dynamics and morphology in live cells. Furthermore, we performed 3D reconstruction of electron microscopic images and show that the 3D reconstruction of the electron microscopic images complements this approach to yield better resolution. The data also suggest that the parameters of mitochondrial dynamics and fractal dimensions are sensitive indicators of cellular response to subtle perturbations, and hence, may serve as potential markers of drug response in lung cancer.

Synthesis of a dihalogenated pyridinyl silicon rhodamine for mitochondrial imaging by a halogen dance rearrangement

Background: Since their first synthesis, silicon xanthenes and the subsequently developed silicon rhodamines (SiR) gained a lot of attention as attractive fluorescence dyes offering a broad field of application. We aimed for the synthesis of a fluorinable pyridinyl silicon rhodamine for the use in multimodal (PET/OI) medical imaging of mitochondria in cancerous cells.

Results: A dihalogenated fluorinatable pyridinyl rhodamine could be successfully synthesized with the high yield of 85% by application of a halogen dance (HD) rearrangement. The near-infrared dye shows a quantum yield of 0.34, comparable to other organelle targeting SiR derivatives and absorbs at 665 nm (ε_max = 34 000 M⁻¹cm⁻¹) and emits at 681 nm (τ = 1.9 ns). Using colocalization experiments with MitoTracker^® Green FM, we could prove the intrinsic targeting ability to mitochondria in two human cell lines (Pearson coefficient >0.8). The dye is suitable for live cell STED nanoscopy imaging and shows a nontoxic profile which makes it an appropriate candidate for medical imaging.

Conclusions: We present a biocompatible, nontoxic, small molecule near-infrared dye with the option of subsequent radiolabelling and excellent optical properties for medical and bioimaging. As a compound with intrinsic mitochondria targeting ability, the radiolabelled analogue can be applied in multimodal (PET/OI) imaging of mitochondria for diagnostic and therapeutic use in, e.g., cancer patients.

Force Spectrum Microscopy Using Mitochondrial Fluctuations of Control and ATP-Depleted Cells

A single-cell assay of active and passive intracellular mechanical properties of mammalian cells could give significant insight into cellular processes. Force spectrum microscopy (FSM) is one such technique, which combines the spontaneous motion of probe particles and the mechanical properties of the cytoskeleton measured by active microrheology using optical tweezers to determine the force spectrum of the cytoskeleton. A simpler and noninvasive method to perform FSM would be very useful, enabling its widespread adoption. Here, we develop an alternative method of FSM using measurement of the fluctuating motion of mitochondria. Mitochondria of the C3H-10T1/2 cell line were labeled and tracked using confocal microscopy. Mitochondrial probes were selected based on morphological characteristics, and their mean-square displacement, creep compliance, and distributions of directional change were measured. We found that the creep compliance of mitochondria resembles that of particles in viscoelastic media. However, comparisons of creep compliance between controls and cells treated with pharmacological agents showed that perturbations to the actomysoin network had surprisingly small effects on mitochondrial fluctuations, whereas microtubule disruption and ATP depletion led to a significantly decreased creep compliance. We used properties of the distribution of directional change to identify a regime of thermally dominated fluctuations in ATP-depleted cells, allowing us to estimate the viscoelastic parameters for a range of timescales. We then determined the force spectrum by combining these viscoelastic properties with measurements of spontaneous fluctuations tracked in control cells. Comparisons with previous measurements made using FSM revealed an excellent match.

Mitochondria in the signaling pathways that control longevity and health span

Genetic and pharmacological intervention studies have identified evolutionarily conserved and functionally interconnected networks of cellular energy homeostasis, nutrient-sensing, and genome damage response signaling pathways, as prominent regulators of longevity and health span in various species. Mitochondria are the primary sites of ATP production and are key players in several other important cellular processes. Mitochondrial dysfunction diminishes tissue and organ functional performance and is a commonly considered feature of the aging process. Here we review the evidence that through reciprocal and multilevel functional interactions, mitochondria are implicated in the lifespan modulation function of these pathways, which altogether constitute a highly dynamic and complex system that controls the aging process. An important characteristic of these pathways is their extensive crosstalk and apparent malleability to modification by non-invasive pharmacological, dietary, and lifestyle interventions, with promising effects on lifespan and health span in animal models and potentially also in humans.

Morphology-based prediction of cancer cell migration using an artificial neural network and a random decision forest

Metastasis is the cause of death in most patients of breast cancer and other solid malignancies. Identification of cancer cells with highly migratory capability to metastasize relies on markers for epithelial-to-mesenchymal transition (EMT), a process increasing cell migration and metastasis. Marker-based approaches are limited by inconsistences among patients, types of cancer, and partial EMT states. Alternatively, we analyzed cancer cell migration behavior using computer vision. Using a microfluidic single-cell migration chip and high-content imaging, we extracted morphological features and recorded migratory direction and speed of breast cancer cells. By applying a Random Decision Forest (RDF) and an Artificial Neural Network (ANN), we achieved over 99% accuracy for cell movement direction prediction and 91% for speed prediction. Unprecedentedly, we identified highly motile cells and non-motile cells based on microscope images and a machine learning model, and pinpointed and validated morphological features determining cell migration, including not only known features related to cell polarization but also novel ones that can drive future mechanistic studies. Predicting cell movement by computer vision and machine learning establishes a ground-breaking approach to analyze cell migration and metastasis.

The Mitochondrion as an Emerging Therapeutic Target in Cancer

Mitochondria have emerged as important pharmacological targets because of their key role in cellular proliferation and death. In tumor tissues, mitochondria can switch metabolic phenotypes to meet the challenges of high energy demand and macromolecular synthesis. Furthermore, mitochondria can engage in crosstalk with the tumor microenvironment, and signals from cancer-associated fibroblasts can impinge on mitochondria. Cancer cells can also acquire a hybrid phenotype in which both glycolysis and oxidative phosphorylation (OXPHOS) can be utilized. This hybrid phenotype can facilitate metabolic plasticity of cancer cells more specifically in metastasis and therapy-resistance. In light of the metabolic heterogeneity and plasticity of cancer cells that had until recently remained unappreciated, strategies targeting cancer metabolic dependency appear to be promising in the development of novel and effective cancer therapeutics.

Two-Dimensional Light Scattering Anisotropy Cytometry for Label-Free Classification of Ovarian Cancer Cells via Machine Learning

We develop a single-mode fiber-based cytometer for the obtaining of two-dimensional (2D) light scattering patterns from static single cells. Anisotropy of the 2D light scattering patterns of single cells from ovarian cancer and normal cell lines is investigated by histograms of oriented gradients (HOG) method. By analyzing the HOG descriptors with support vector machine, an accuracy rate of 92.84% is achieved for the automatic classification of these two kinds of label-free cells. The 2D light scattering anisotropy cytometry combined with machine learning may provide a label-free, automatic method for screening of ovarian cancer cells, and other types of cells. © 2019 International Society for Advancement of Cytometry.

Breast Cancer Subtypes Present a Differential Production of Reactive Oxygen Species (ROS) and Susceptibility to Antioxidant Treatment

Due to their crucial role in cell metabolism and homeostasis, alterations in mitochondrial biology and function have been related to the progression of diverse diseases including cancer. One of the consequences associated to mitochondrial dysfunction is the production of reactive oxygen species (ROS). ROS are known to have a controversial role during cancer initiation and progression and although several studies have tried to manipulate intracellular ROS levels using antioxidants or pro-oxidation conditions, it is not yet clear how to target oxidation for cancer therapy. In this study, we found differences in mitochondrial morphology in breast cancer cells when compared to a non-tumorigenic cell line and differences in mitochondrial function among breast cancer subtypes when exploring gene-expression data from the TCGA tumor dataset. Interestingly, we found increased ROS levels in triple negative breast cancer (TNBC) cell lines and a dependency on ROS for survival since antioxidant treatment induced cell death in TNBC cells but not in an estrogen receptor positive (ER+) cell line. Moreover, we identified the mitochondria as the main source of ROS in TNBC cell lines. Our results indicate a potential use for ROS as a target for therapy in the TNBC subtype which currently has the worst prognosis among all breast cancers and remains as the only breast cancer subtype which lacks a targeted therapy.

Incomplete Healing as a Cause of Aging: The Role of Mitochondria and the Cell Danger Response

The rate of biological aging varies cyclically and episodically in response to changing environmental conditions and the developmentally-controlled biological systems that sense and respond to those changes. Mitochondria and metabolism are fundamental regulators, and the cell is the fundamental unit of aging. However, aging occurs at all anatomical levels. At levels above the cell, aging in different tissues is qualitatively, quantitatively, and chronologically distinct. For example, the heart can age faster and differently than the kidney and vice versa. Two multicellular features of aging that are universal are: (1) a decrease in physiologic reserve capacity, and (2) a decline in the functional communication between cells and organ systems, leading to death. Decreases in reserve capacity and communication impose kinetic limits on the rate of healing after new injuries, resulting in dyssynchronous and incomplete healing. Exercise mitigates against these losses, but recovery times continue to increase with age. Reinjury before complete healing results in the stacking of incomplete cycles of healing. Developmentally delayed and arrested cells accumulate in the three stages of the cell danger response (CDR1, 2, and 3) that make up the healing cycle. Cells stuck in the CDR create physical and metabolic separation—buffer zones of reduced communication—between previously adjoining, synergistic, and metabolically interdependent cells. Mis-repairs and senescent cells accumulate, and repeated iterations of incomplete cycles of healing lead to progressively dysfunctional cellular mosaics in aging tissues. Metabolic cross-talk between mitochondria and the nucleus, and between neighboring and distant cells via signaling molecules called metabokines regulates the completeness of healing. Purinergic signaling and sphingolipids play key roles in this process. When viewed against the backdrop of the molecular features of the healing cycle, the incomplete healing model provides a new framework for understanding the hallmarks of aging and generates a number of testable hypotheses for new treatments.

Live cell super resolution imaging by radial fluctuations using fluorogen binding tags

Fluorescence-Activating and absorption-Shifting Tag (FAST) is a novel genetically encoded optical highlighter probe. Since the fluorescence of FAST originates from the stochastic and reversible diffusive association of a fluorogenic ligand, we investigate the application of FAST using Super-Resolution Radial Fluctuations (SRRF) to achieve routine imaging below the diffraction limit in a widefield epifluorescence microscope. We show that intensity fluctuation analysis like SRRF allows the imaging of FAST-tagged proteins with sub - 100 nm resolution in live cells. FAST co-labeled with conventional fluorophores enables real time multicolour 2D and 3D super-resolution imaging, indicating that FAST can be used for the observation of sub-diffraction limited structures in both living and fixed samples.

A New Infrared Probe Targeting Mitochondria via Regulation of Molecular Hydrophobicity

Herein, we developed a near-infrared (NIR) fluorescent probe for mitochondrial staining based on the NIR fluorochrome, silicon-rhodamine. The hydrophobicity of the fluorescent core was systematically modified by conjugation with 10 different commercial amines. The resulting fluorescent compounds exhibited similar photophysical properties but diverse hydrophobicity. We identified the optimal level of hydrophobicity associated with high mitochondrial targeting efficiency. In particular, the SiR-Mito 8 probe provided excellent mitochondrial staining and successfully differentiated the live Hep3B cancer cells from normal L02 cells in vitro.

Automated Quantitative Analysis of Mitochondrial Morphology

Mitochondria are dynamic organelles that in most cells behave as a dynamic network and can change their biogenesis and structure depending on the cell needs or as a response to different conditions. Analyzing the architecture of mitochondria is determinant to describe their state and function. In this chapter, image processing techniques are applied in a workflow manner to segment the mitochondrial network and extract the most relevant parameters that enable an accurate morphology analysis. This workflow is programmed with ImageJ macro language and can be applied to automatically analyze multiple cells from multiple images or tiles. When combined with multiwell plates and automated microscopy, this method may allow to perform high content image analysis of hundreds of cells under different conditions.

Mesenchymal Stem Cells Shift Mitochondrial Dynamics and Enhance Oxidative Phosphorylation in Recipient Cells

Mesenchymal stem cells (MSCs) are the most commonly used cells in tissue engineering and regenerative medicine. MSCs can promote host tissue repair through several different mechanisms including donor cell engraftment, release of cell signaling factors, and the transfer of healthy organelles to the host. In the present study, we examine the specific impacts of MSCs on mitochondrial morphology and function in host tissues. Employing in vitro cell culture of inherited mitochondrial disease and an in vivo animal experimental model of low-grade inflammation (high fat feeding), we show human-derived MSCs to alter mitochondrial function. MSC co-culture with skin fibroblasts from mitochondrial disease patients rescued aberrant mitochondrial morphology from a fission state to a more fused appearance indicating an effect of MSC co-culture on host cell mitochondrial network formation. In vivo experiments confirmed mitochondrial abundance and mitochondrial oxygen consumption rates were elevated in host tissues following MSC treatment. Furthermore, microarray profiling identified 226 genes with differential expression in the liver of animals treated with MSC, with cellular signaling, and actin cytoskeleton regulation as key upregulated processes. Collectively, our data indicate that MSC therapy rescues impaired mitochondrial morphology, enhances host metabolic capacity, and induces widespread host gene shifting. These results highlight the potential of MSCs to modulate mitochondria in both inherited and pathological disease states.

Deep Analysis of Mitochondria and Cell Health Using Machine Learning

There is a critical need for better analytical methods to study mitochondria in normal and diseased states. Mitochondrial image analysis is typically done on still images using slow manual methods or automated methods of limited types of features. MitoMo integrated software overcomes these bottlenecks by automating rapid unbiased quantitative analysis of mitochondrial morphology, texture, motion, and morphogenesis and advances machine-learning classification to predict cell health by combining features. Our pixel-based approach for motion analysis evaluates the magnitude and direction of motion of: (1) molecules within mitochondria, (2) individual mitochondria, and (3) distinct morphological classes of mitochondria. MitoMo allows analysis of mitochondrial morphogenesis in time-lapse videos to study early progression of cellular stress. Biological applications are presented including: (1) establishing normal phenotypes of mitochondria in different cell types; (2) quantifying stress-induced mitochondrial hyperfusion in cells treated with an environmental toxicant, (3) tracking morphogenesis in mitochondria undergoing swelling, and (4) evaluating early changes in cell health when morphological abnormalities are not apparent. MitoMo unlocks new information on mitochondrial phenotypes and dynamics by enabling deep analysis of mitochondrial features in any cell type and can be applied to a broad spectrum of research problems in cell biology, drug testing, toxicology, and medicine.

Essential roles of mitochondrial and heme function in lung cancer bioenergetics and tumorigenesis

Contrary to Warburg’s hypothesis, mitochondrial oxidative phosphorylation (OXPHOS) contributes significantly to fueling cancer cells. Several recent studies have demonstrated that radiotherapy-resistant and chemotherapy-resistant cancer cells depend on OXPHOS for survival and progression. Several cancers exhibit an increased risk in association with heme intake. Mitochondria are widely known to carry out oxidative phosphorylation. In addition, mitochondria are also involved in heme synthesis. Heme serves as a prosthetic group for several proteins that constitute the complexes of mitochondrial electron transport chain. Therefore, heme plays a pivotal role in OXPHOS and oxygen consumption. Further, lung cancer cells exhibit heme accumulation and require heme for proliferation and invasion in vitro. Abnormalities in mitochondrial biogenesis and mutations are implicated in cancer. This review delves into mitochondrial OXPHOS and lesser explored area of heme metabolism in lung cancer.

Single-cell barcode analysis provides a rapid readout of cellular signaling pathways in clinical specimens

Serial tissue sampling has become essential in guiding modern targeted and personalized cancer treatments. An alternative to image guided core biopsies are fine needle aspirates (FNA) that yield cells rather than tissues but are much better tolerated and have lower complication rates. The efficient pathway analysis of such cells in the clinic has been difficult, time consuming and costly. Here we develop an antibody-DNA barcoding approach where harvested cells can be rapidly re-stained through the use of custom designed oligonucleotide-fluorophore conjugates. We show that this approach can be used to interrogate drug-relevant pathways in scant clinical samples. Using the PI3K/PTEN/CDK4/6 pathways in breast cancer as an example, we demonstrate how analysis can be performed in tandem with trial enrollment and can evaluate downstream signaling following therapeutic inhibition. This approach should allow more widespread use of scant single cell material in clinical samples.

Methods for imaging mammalian mitochondrial morphology: A prospective on MitoGraph

Mitochondria are found in a variety of shapes, from small round punctate structures to a highly interconnected web. This morphological diversity is important for function, but complicates quantification. Consequently, early quantification efforts relied on various qualitative descriptors that understandably reduce the complexity of the network leading to challenges in consistency across the field. Recent application of state-of-the-art computational tools have resulted in more quantitative approaches. This prospective highlights the implementation of MitoGraph, an open-source image analysis platform for measuring mitochondrial morphology initially optimized for use with Saccharomyces cerevisiae. Here Mitograph was assessed on five different mammalian cells types, all of which were accurately segmented by MitoGraph analysis. MitoGraph also successfully differentiated between distinct mitochondrial morphologies that ranged from entirely fragmented to hyper-elongated. General recommendations are also provided for confocal imaging of labeled mitochondria (using mito-YFP, MitoTracker dyes and immunostaining parameters). Widespread adoption of MitoGraph will help achieve a long-sought goal of consistent and reproducible quantification of mitochondrial morphology.

Mitochondrial autophagosomes as a mechanism of drug resistance in breast carcinoma

We have previously described the process by which mitochondria donate their membranes for the formation of autophagosomes, and in this study we show that the same process could be involved in drug sequestration and exocytosis resulting in multidrug-resistant cancerous cells. We examine the implications of mitochondrial vesicle formation of mitoautophagosomes (MAPS) in response to the cytotoxic drug MKT-077, which targets mortalin, in a drug-resistant breast carcinoma cell line overexpressing P-glycoprotein (P-gp). The breast cancer cell line MCF-7Adr is derived from MCF-7, but differs from its ancestral line in tolerance of MKT-077-induced mitochondrial toxicity. Our ultrastructural observations suggest that autophagy in the MCF-7Adr cells entails regional sequestration of MKT077 in multilamellar LC3-labeled MAPS, which then separate from their mitochondria, and fuse with or engulf each other. MAPS appeared to be migrating through the cytoplasm and fusing with the plasma membrane, thus carrying out exocytotic secretion. This mechanism, which seems ineffective in the ancestral cell line, provides a resistance mechanism for MKT-077 by enhancing the efflux process of the cells. After 8 hr of MKT-077 exposure, a fraction of the resistant cells appeared viable and contained larger number of smaller sized mitochondria. Mitoautophagosomes, therefore, provide a potentially novel model for multidrug resistance in cancerous cells and may contribute to the P-gp efflux process.

The Concerted Action of Mitochondrial Dynamics and Positioning: New Characters in Cancer Onset and Progression

Mitochondria are dynamic organelles whose morphology and activity are extremely variable, depending on the metabolic state of the cell. In particular, their shape and movements within the cell are finely regulated by an increasing number of proteins, which take part in the process of mitochondrial fission/fusion and connect the organelles to the cytoskeleton. As to their activities, mitochondria are considered to be at the crossroad between cell life and death since, on the one hand, they are essential in ATP production and in multiple metabolic pathways but, on the other, they are involved in the intrinsic apoptotic cascade, triggered by different stress conditions. Importantly, the process of mitochondrial Ca²⁺ uptake, as well as the morphology and the dynamics of these organelles, is known to deeply impact on both pro-survival and pro-death mitochondrial activities. Recently, increasing evidence has accrued on a central role of deregulated mitochondrial functionalities in the onset and progression of different pathologies, ranging from neurodegenerative diseases to cancer. In this contribution, we will present the latest findings connecting alterations in the machineries that control mitochondrial dynamics and localization to specific cancer hallmarks, highlighting the importance of mitochondria for the viability of cancer cells and discussing their role as promising targets for the development of novel anticancer therapies.

Understanding tumor anabolism and patient catabolism in cancer-associated cachexia

Cachexia is a multifactorial paraneoplastic syndrome commonly associated with advanced stages of cancer. Cachexia is responsible for poor responses to antitumoral treatment and death in close to one-third of affected patients. There is still an incomplete understanding of the metabolic dysregulation induced by a tumor that leads to the appearance and persistence of cachexia. Furthermore, cachexia is irreversible, and there are currently no guidelines for its diagnosis or treatments for it. In this review, we aim to discuss the current knowledge about cancer-associated cachexia, starting with generalities about cancer as the generator of this syndrome, then analyzing the characteristics of cachexia at the biochemical and metabolic levels in both the tumor and the patient, and finally discussing current therapeutic approaches to treating cancer-associated cachexia.

Connecting mitochondrial dynamics and life-or-death events via Bcl-2 family proteins

The morphology of a population of mitochondria is the result of several interacting dynamical phenomena, including fission, fusion, movement, elimination and biogenesis. Each of these phenomena is controlled by underlying molecular machinery, and when defective can cause disease. New understanding of the relationships between form and function of mitochondria in health and disease is beginning to be unraveled on several fronts. Studies in mammals and model organisms have revealed that mitochondrial morphology, dynamics and function appear to be subject to regulation by the same proteins that regulate apoptotic cell death. One protein family that influences mitochondrial dynamics in both healthy and dying cells is the Bcl-2 protein family. Connecting mitochondrial dynamics with life-death pathway forks may arise from the intersection of Bcl-2 family proteins with the proteins and lipids that determine mitochondrial shape and function. Bcl-2 family proteins also have multifaceted influences on cells and mitochondria, including calcium handling, autophagy and energetics, as well as the subcellular localization of mitochondrial organelles to neuronal synapses. The remarkable range of physical or functional interactions by Bcl-2 family proteins is challenging to assimilate into a cohesive understanding. Most of their effects may be distinct from their direct roles in apoptotic cell death and are particularly apparent in the nervous system. Dual roles in mitochondrial dynamics and cell death extend beyond BCL-2 family proteins. In this review, we discuss many processes that govern mitochondrial structure and function in health and disease, and how Bcl-2 family proteins integrate into some of these processes.

CHCHD4 Regulates Intracellular Oxygenation and Perinuclear Distribution of Mitochondria

Hypoxia is a characteristic of the tumor microenvironment and is known to contribute to tumor progression and treatment resistance. Hypoxia-inducible factor (HIF) dimeric transcription factors control the cellular response to reduced oxygenation by regulating the expression of genes involved in metabolic adaptation, cell motility, and survival. Alterations in mitochondrial metabolism are not only a downstream consequence of HIF-signaling but mitochondria reciprocally regulate HIF signaling through multiple means, including oxygen consumption, metabolic intermediates, and reactive oxygen species generation. CHCHD4 is a redox-sensitive mitochondrial protein, which we previously identified and showed to be a novel regulator of HIF and hypoxia responses in tumors. Elevated expression of CHCHD4 in human tumors correlates with the hypoxia gene signature, disease progression, and poor patient survival. Here, we show that either long-term (72 h) exposure to hypoxia (1% O2) or elevated expression of CHCHD4 in tumor cells in normoxia leads to perinuclear accumulation of mitochondria, which is dependent on the expression of HIF-1α. Furthermore, we show that CHCHD4 is required for perinuclear localization of mitochondria and HIF activation in response to long-term hypoxia. Mutation of the functionally important highly conserved cysteines within the Cys-Pro-Cys motif of CHCHD4 or inhibition of complex IV activity (by sodium azide) redistributes mitochondria from the perinuclear region toward the periphery of the cell and blocks HIF activation. Finally, we show that CHCHD4-mediated perinuclear localization of mitochondria is associated with increased intracellular hypoxia within the perinuclear region and constitutive basal HIF activation in normoxia. Our study demonstrates that the intracellular distribution of the mitochondrial network is an important feature of the cellular response to hypoxia, contributing to hypoxic signaling via HIF activation and regulated by way of the cross talk between CHCHD4 and HIF-1α.