Automatic Morphological Subtyping Reveals New Roles of Caspases in Mitochondrial Dynamics

Morphological dynamics of mitochondria is associated with key cellular processes related to aging and neuronal degenerative diseases, but the lack of standard quantification of mitochondrial morphology impedes systematic investigation. This paper presents an automated system for the quantification and classification of mitochondrial morphology. We discovered six morphological subtypes of mitochondria for objective quantification of mitochondrial morphology. These six subtypes are small globules, swollen globules, straight tubules, twisted tubules, branched tubules and loops. The subtyping was derived by applying consensus clustering to a huge collection of more than 200 thousand mitochondrial images extracted from 1422 micrographs of Chinese hamster ovary (CHO) cells treated with different drugs, and was validated by evidence of functional similarity reported in the literature. Quantitative statistics of subtype compositions in cells is useful for correlating drug response and mitochondrial dynamics. Combining the quantitative results with our biochemical studies about the effects of squamocin on CHO cells reveals new roles of Caspases in the regulatory mechanisms of mitochondrial dynamics. This system is not only of value to the mitochondrial field, but also applicable to the investigation of other subcellular organelle morphology

MitoLoc: A method for the simultaneous quantification of mitochondrial network morphology and membrane potential in single cells.

Mitochondria assemble into flexible networks. Here we present a simple method for the simultaneous quantification of mitochondrial membrane potential and network morphology that is based on computational co-localisation analysis of differentially imported fluorescent marker proteins. Established in, but not restricted to, Saccharomyces cerevisiae, MitoLoc reproducibly measures changes in membrane potential induced by the uncoupling agent CCCP, by oxidative stress, in respiratory deficient cells, and in ∆fzo1, ∆ref2, and ∆dnm1 mutants that possess fission and fusion defects. In combination with super-resolution images, MitoLoc uses 3D reconstruction to calculate six geometrical classifiers which differentiate network morphologies in ∆fzo1, ∆ref2, and ∆dnm1 mutants, under oxidative stress and in cells lacking mtDNA, even when the network is fragmented to a similar extent. We find that mitochondrial fission and a decline in membrane potential do regularly, but not necessarily, co-occur. MitoLoc hence simplifies the measurement of mitochondrial membrane potential in parallel to detect morphological changes in mitochondrial networks. Marker plasmid open-source software as well as the mathematical procedures are made openly available.This work was supported by funding from the Wellcome Trust (RG 093735/Z/10/Z) and the ERC (Starting grant 260809). M.R. is a Wellcome Trust Research Career Development and Wellcome-Beit prize fellow.This is the final version. It was first published by Elsevier at http://www.sciencedirect.com/science/article/pii/S1567724915300088

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

International audienceThe 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

Ranking of multidimensional drug profiling data by fractional-adjusted bi-partitional scores

Motivation: The recent development of high-throughput drug profiling (high content screening or HCS) provides a large amount of quantitative multidimensional data. Despite its potentials, it poses several challenges for academia and industry analysts alike. This is especially true for ranking the effectiveness of several drugs from many thousands of images directly. This paper introduces, for the first time, a new framework for automatically ordering the performance of drugs, called fractional adjusted bi-partitional score (FABS). This general strategy takes advantage of graph-based formulations and solutions and avoids many shortfalls of traditionally used methods in practice. We experimented with FABS framework by implementing it with a specific algorithm, a variant of normalized cut—normalized cut prime (FABS-NC′), producing a ranking of drugs. This algorithm is known to run in polynomial time and therefore can scale well in high-throughput applications

Regulation and quantification of cellular mitochondrial morphology and content

Mitochondria play a key role in signal transduction, redox homeostasis and cell survival, which extends far beyond their classical functioning in ATP production and energy metabolism. In living cells, mitochondrial content (“mitochondrial mass”) depends on the cell-controlled balance between mitochondrial biogenesis and degradation. These processes are intricately linked to changes in net mitochondrial morphology and spatiotemporal positioning (“mitochondrial dynamics”), which are governed by mitochondrial fusion, fission and motility. It is becoming increasingly clear that mitochondrial mass and dynamics, as well as its ultrastructure and volume, are mechanistically linked to mitochondrial function and the cell. This means that proper quantification of mitochondrial morphology and content is of prime importance in understanding mitochondrial and cellular physiology in health and disease. This review first presents how cellular mitochondrial content is regulated at the level of mitochondrial biogenesis, degradation and dynamics. Next we discuss how mitochondrial dynamics and content can be analyzed with a special emphasis on quantitative live-cell microscopy strategies.acceptedVersio

Flicker-assisted localization microscopy reveals altered mitochondrial architecture in hypertension

Mitochondrial morphology is central to normal physiology and disease development. However, in many live cells and tissues, complex mitochondrial structures exist and morphology has been difficult to quantify. We have measured the shape of electrically-discrete mitochondria, imaging them individually to restore detail hidden in clusters and demarcate functional boundaries. Stochastic “flickers” of mitochondrial membrane potential were visualized with a rapidly-partitioning fluorophore and the pixel-by-pixel covariance of spatio-temporal fluorescence changes analyzed. This Flicker-assisted Localization Microscopy (FaLM) requires only an epifluorescence microscope and sensitive camera. In vascular myocytes, the apparent variation in mitochondrial size was partly explained by densely-packed small mitochondria. In normotensive animals, mitochondria were small spheres or rods. In hypertension, mitochondria were larger, occupied more of the cell volume and were more densely clustered. FaLM provides a convenient tool for increased discrimination of mitochondrial architecture and has revealed mitochondrial alterations that may contribute to hypertension

Selective targeting of non-centrosomal AURKA functions through use of a targeted protein degradation tool.

Targeted protein degradation tools are becoming a new therapeutic modality, allowing small molecule ligands to be reformulated as heterobifunctional molecules (PROteolysis Targeting Chimeras, PROTACs) that recruit ubiquitin ligases to targets of interest, leading to ubiquitination and destruction of the targets. Several PROTACs against targets of clinical interest have been described, but detailed descriptions of the cell biology modulated by PROTACs are missing from the literature. Here we describe the functional characterization of a PROTAC derived from AURKA inhibitor MLN8237 (alisertib). We demonstrate efficient and specific destruction of both endogenous and overexpressed AURKA by Cereblon-directed PROTACs. At the subcellular level, we find differential targeting of AURKA on the mitotic spindle compared to centrosomes. The phenotypic consequences of PROTAC treatment are therefore distinct from those mediated by alisertib, and in mitotic cells differentially regulate centrosome- and chromatin- based microtubule spindle assembly pathways. In interphase cells PROTAC-mediated clearance of non-centrosomal AURKA modulates the cytoplasmic role played by AURKA in mitochondrial dynamics, whilst the centrosomal pool is refractory to PROTAC-mediated clearance. Our results point to differential sensitivity of subcellular pools of substrate, governed by substrate conformation or localization-dependent accessibility to PROTAC action, a phenomenon not previously described for this new class of degrader compounds

High-content high-throughput imaging reveals distinct connections between mitochondrial morphology and functionality for oxphos complex I, III, and V inhibitors

Cells can adjust their mitochondrial morphology by altering the balance between mitochondrial fission and fusion to adapt to stressful conditions. The connection between a chemical perturbation, changes in mitochondrial function, and altered mitochondrial morphology is not well understood. Here, we made use of high-throughput high-content confocal microscopy to assess the effects of distinct classes of oxidative phosphorylation (OXPHOS) complex inhibitors on mitochondrial parameters in a concentration and time resolved manner. Mitochondrial morphology phenotypes were clustered based on machine learning algorithms and mitochondrial integrity patterns were mapped. In parallel, changes in mitochondrial membrane potential (MMP), mitochondrial and cellular ATP levels, and viability were microscopically assessed. We found that inhibition of MMP, mitochondrial ATP production, and oxygen consumption rate (OCR) using sublethal concentrations of complex I and III inhibitors did not trigger mitochondrial fragmentation. Instead, complex V inhibitors that suppressed ATP and OCR but increased MMP provoked a more fragmented mitochondrial morphology. In agreement, complex V but not complex I or III inhibitors triggered proteolytic cleavage of the mitochondrial fusion protein, OPA1. The relation between increased MMP and fragmentation did not extend beyond OXPHOS complex inhibitors: increasing MMP by blocking the mPTP pore did not lead to OPA1 cleavage or mitochondrial fragmentation and the OXPHOS uncoupler FCCP was associated with OPA1 cleavage and MMP reduction. Altogether, our findings connect vital mitochondrial functions and phenotypes in a high-throughput high-content confocal microscopy approach that help understanding of chemical-induced toxicity caused by OXPHOS complex perturbing chemicals.Toxicolog

Cancer Drug Screening Scale-up: Combining Biomimetic Microfluidic Platforms and Deep Learning Image Analysis

The development of cancer drugs is usually costly and time-consuming, mainly due to growing complexity in screening large number of candidate compounds and high failure rates in translation from preclinical trials to clinical approval. Despite the great efforts, the preclinical screening platforms combing good clinical relevance and high throughput for large-scale drug testing is still lacking. In addition, accumulating evidence suggests that cancer drug response can be altered by tumor microenvironment (TME), which includes not only cancer cells but also physical, and biochemical cues in niches. To improve the current cancer drug screening assays, it is important to mimic local TME to achieve better physiological relevance. In the first part of this dissertation, three TME-mimicking microfluidic platforms were introduced for three different in-vitro TME-mimicking tumor sphere models: spheres in matrix, self-aggregated spheres, and single-cell clonal spheres. First, a 3D gel-island chip investigated the heterogeneity of single-cell drug responses in biomimetic extracellular matrix (ECM). With 1,500 isolated single cell chambers containing ECM, it was demonstrated that ECM support was favorable for some population of cancer cells to maintain stemness and develop drug resistance. This result suggested the importance of drug screening at single-cell resolution in TME-mimicking platforms. Secondly, a drug combination screening chip enabling high-throughput and scalable combinatorial drug screening was demonstrated for the aggregated sphere model. Instead of screening a single drug on each of the tumors, this chip allows the screening of all pairwise drug combinations from eight different cancer drugs, in total 172 different treatment conditions, and 1,032 tested samples in a single microfluidic chip. The presented design approach was easily scalable to incorporate arbitrary number of drugs for large-scale drug screening. Finally, single-cell Hi-Sphere chip enabled high-throughput clonal sphere culture and selective retrieval. Combining fluorescent dye on-situ staining techniques, we identified rare cancer stem-like cell population and confirms its location at the leading edge of spheres. Advance in experimental throughput generates massive data, which demands the corresponding automatic analysis and intelligent interpretation capabilities. The second part of this dissertation focuses on the applications of computer vision and machine learning algorithms to automated biomedical data processing. Image analysis with convolutional neural network was applied for drug efficacy evaluation in a fast and label-free manner. The estimated drug efficacy is highly correlated with the experimental ground truth (R-value > 0.93), while the predicted half-maximal inhibitory concentration is within 8% error range. In addition, metastatic fast-moving cells could be identified after extracting morphological features from the microscope images and applying deep learning algorithm for image analysis, achieving over 99% accuracy for cell movement direction prediction and 91% for speed prediction. In summary, this dissertation presents high-throughput TME-mimicking microfluidics and deep learning image analysis for large-scale drug screening solutions.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163039/1/zhangzx_1.pd

Mitochondrial Transfer by Human Mesenchymal Stromal Cells Ameliorates Hepatocyte Lipid Load in a Mouse Model of NASH

Mesenchymal stromal cell (MSC) transplantation ameliorated hepatic lipid load; tissue inflammation; and fibrosis in rodent animal models of non-alcoholic steatohepatitis (NASH) by as yet largely unknown mechanism(s). In a mouse model of NASH; we transplanted bone marrow-derived MSCs into the livers; which were analyzed one week thereafter. Combined metabolomic and proteomic data were applied to weighted gene correlation network analysis (WGCNA) and subsequent identification of key drivers. Livers were analyzed histologically and biochemically. The mechanisms of MSC action on hepatocyte lipid accumulation were studied in co-cultures of hepatocytes and MSCs by quantitative image analysis and immunocytochemistry. WGCNA and key driver analysis revealed that NASH caused the impairment of central carbon; amino acid; and lipid metabolism associated with mitochondrial and peroxisomal dysfunction; which was reversed by MSC treatment. MSC improved hepatic lipid metabolism and tissue homeostasis. In co-cultures of hepatocytes and MSCs; the decrease of lipid load was associated with the transfer of mitochondria from the MSCs to the hepatocytes via tunneling nanotubes (TNTs). Hence; MSCs may ameliorate lipid load and tissue perturbance by the donation of mitochondria to the hepatocytes. Thereby; they may provide oxidative capacity for lipid breakdown and thus promote recovery from NASH-induced metabolic impairment and tissue injury