The Cell Tracking Challenge: 10 years of objective benchmarking.

The Cell Tracking Challenge is an ongoing benchmarking initiative that has become a reference in cell segmentation and tracking algorithm development. Here, we present a significant number of improvements introduced in the challenge since our 2017 report. These include the creation of a new segmentation-only benchmark, the enrichment of the dataset repository with new datasets that increase its diversity and complexity, and the creation of a silver standard reference corpus based on the most competitive results, which will be of particular interest for data-hungry deep learning-based strategies. Furthermore, we present the up-to-date cell segmentation and tracking leaderboards, an in-depth analysis of the relationship between the performance of the state-of-the-art methods and the properties of the datasets and annotations, and two novel, insightful studies about the generalizability and the reusability of top-performing methods. These studies provide critical practical conclusions for both developers and users of traditional and machine learning-based cell segmentation and tracking algorithms.

Engineered DNA plasmid reduces immunity to dystrophin while improving muscle force in a model of gene therapy of Duchenne dystrophy.

In gene therapy for Duchenne muscular dystrophy there are two potential immunological obstacles. An individual with Duchenne muscular dystrophy has a genetic mutation in dystrophin, and therefore the wild-type protein is "foreign," and thus potentially immunogenic. The adeno-associated virus serotype-6 (AAV6) vector for delivery of dystrophin is a viral-derived vector with its own inherent immunogenicity. We have developed a technology where an engineered plasmid DNA is delivered to reduce autoimmunity. We have taken this approach into humans, tolerizing to myelin proteins in multiple sclerosis and to proinsulin in type 1 diabetes. Here, we extend this technology to a model of gene therapy to reduce the immunogenicity of the AAV vector and of the wild-type protein product that is missing in the genetic disease. Following gene therapy with systemic administration of recombinant AAV6-microdystrophin to mdx/mTRG2 mice, we demonstrated the development of antibodies targeting dystrophin and AAV6 capsid in control mice. Treatment with the engineered DNA construct encoding microdystrophin markedly reduced antibody responses to dystrophin and to AAV6. Muscle force in the treated mice was also improved compared with control mice. These data highlight the potential benefits of administration of an engineered DNA plasmid encoding the delivered protein to overcome critical barriers in gene therapy to achieve optimal functional gene expression.

An objective comparison of cell-tracking algorithms.

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

Prostaglandin E2 is essential for efficacious skeletal muscle stem-cell function, augmenting regeneration and strength.

Skeletal muscles harbor quiescent muscle-specific stem cells (MuSCs) capable of tissue regeneration throughout life. Muscle injury precipitates a complex inflammatory response in which a multiplicity of cell types, cytokines, and growth factors participate. Here we show that Prostaglandin E2 (PGE2) is an inflammatory cytokine that directly targets MuSCs via the EP4 receptor, leading to MuSC expansion. An acute treatment with PGE2 suffices to robustly augment muscle regeneration by either endogenous or transplanted MuSCs. Loss of PGE2 signaling by specific genetic ablation of the EP4 receptor in MuSCs impairs regeneration, leading to decreased muscle force. Inhibition of PGE2 production through nonsteroidal anti-inflammatory drug (NSAID) administration just after injury similarly hinders regeneration and compromises muscle strength. Mechanistically, the PGE2 EP4 interaction causes MuSC expansion by triggering a cAMP/phosphoCREB pathway that activates the proliferation-inducing transcription factor, Nurr1 Our findings reveal that loss of PGE2 signaling to MuSCs during recovery from injury impedes muscle repair and strength. Through such gain- or loss-of-function experiments, we found that PGE2 signaling acts as a rheostat for muscle stem-cell function. Decreased PGE2 signaling due to NSAIDs or increased PGE2 due to exogenous delivery dictates MuSC function, which determines the outcome of regeneration. The markedly enhanced and accelerated repair of damaged muscles following intramuscular delivery of PGE2 suggests a previously unrecognized indication for this therapeutic agent.

Objective comparison of particle tracking methods.

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.

A benchmark for comparison of cell tracking algorithms.

MOTIVATION: Automatic tracking of cells in multidimensional time-lapse fluorescence microscopy is an important task in many biomedical applications. A novel framework for objective evaluation of cell tracking algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2013 Cell Tracking Challenge. In this article, we present the logistics, datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. RESULTS: The main contributions of the challenge include the creation of a comprehensive video dataset repository and the definition of objective measures for comparison and ranking of the algorithms. With this benchmark, six algorithms covering a variety of segmentation and tracking paradigms have been compared and ranked based on their performance on both synthetic and real datasets. Given the diversity of the datasets, we do not declare a single winner of the challenge. Instead, we present and discuss the results for each individual dataset separately. AVAILABILITY AND IMPLEMENTATION: The challenge Web site (http://www.codesolorzano.com/celltrackingchallenge) provides access to the training and competition datasets, along with the ground truth of the training videos. It also provides access to Windows and Linux executable files of the evaluation software and most of the algorithms that competed in the challenge.

Machine learning-based classification of dual fluorescence signals reveals muscle stem cell fate transitions in response to regenerative niche factors.

The proper regulation of muscle stem cell (MuSC) fate by cues from the niche is essential for regeneration of skeletal muscle. How pro-regenerative niche factors control the dynamics of MuSC fate decisions remains unknown due to limitations of population-level endpoint assays. To address this knowledge gap, we developed a dual fluorescence imaging time lapse (Dual-FLIT) microscopy approach that leverages machine learning classification strategies to track single cell fate decisions with high temporal resolution. Using two fluorescent reporters that read out maintenance of stemness and myogenic commitment, we constructed detailed lineage trees for individual MuSCs and their progeny, classifying each division event as symmetric self-renewing, asymmetric, or symmetric committed. Our analysis reveals that treatment with the lipid metabolite, prostaglandin E2 (PGE2), accelerates the rate of MuSC proliferation over time, while biasing division events toward symmetric self-renewal. In contrast, the IL6 family member, Oncostatin M (OSM), decreases the proliferation rate after the first generation, while blocking myogenic commitment. These insights into the dynamics of MuSC regulation by niche cues were uniquely enabled by our Dual-FLIT approach. We anticipate that similar binary live cell readouts derived from Dual-FLIT will markedly expand our understanding of how niche factors control tissue regeneration in real time.

A collagen-based microwell migration assay to study NK-target cell interactions.

Natural killer (NK) cell cytotoxicity in tissue is dependent on the ability of NK cells to migrate through the extracellular matrix (ECM) microenvironment. Traditional imaging studies of NK cell migration and cytotoxicity have utilized 2D surfaces, which do not properly reproduce the structural and mechanical cues that shape the migratory response of NK cells in vivo. Here, we have combined a microwell assay that allows long-term imaging and tracking of small, well-defined populations of NK cells with an interstitial ECM-like matrix. The assay allows for long-term imaging of NK-target cell interactions within a confined 3D volume. We found marked differences in motility between individual cells with a small fraction of the cells moving slowly and being confined to a small volume within the matrix, while other cells moved more freely. A majority of NK cells also exhibited transient variation in their motility, alternating between periods of migration arrest and movement. The assay could be used as a complement to in vivo imaging to study human NK cell heterogeneity in migration and cytotoxicity.

Global linking of cell tracks using the Viterbi algorithm.

Automated tracking of living cells in microscopy image sequences is an important and challenging problem. With this application in mind, we propose a global track linking algorithm, which links cell outlines generated by a segmentation algorithm into tracks. The algorithm adds tracks to the image sequence one at a time, in a way which uses information from the complete image sequence in every linking decision. This is achieved by finding the tracks which give the largest possible increases to a probabilistically motivated scoring function, using the Viterbi algorithm. We also present a novel way to alter previously created tracks when new tracks are created, thus mitigating the effects of error propagation. The algorithm can handle mitosis, apoptosis, and migration in and out of the imaged area, and can also deal with false positives, missed detections, and clusters of jointly segmented cells. The algorithm performance is demonstrated on two challenging datasets acquired using bright-field microscopy, but in principle, the algorithm can be used with any cell type and any imaging technique, presuming there is a suitable segmentation algorithm.

A single cell bioengineering approach to elucidate mechanisms of adult stem cell self-renewal.

The goal of regenerative medicine is to restore form and function to damaged and aging tissues. Adult stem cells, present in tissues such as skeletal muscle, comprise a reservoir of cells with a remarkable capacity to proliferate and repair tissue damage. Muscle stem cells, known as satellite cells, reside in a quiescent state in an anatomically distinct compartment, or niche, ensheathed between the membrane of the myofiber and the basal lamina. Recently, procedures for isolating satellite cells were developed and experiments testing their function upon transplantation into muscles revealed an extraordinary potential to contribute to muscle fibers and access and replenish the satellite cell compartment. However, these properties are rapidly lost once satellite cells are plated in culture. Accordingly, elucidating the role of extrinsic factors in controlling muscle stem cell fate, in particular self-renewal, is critical. Through careful design of bioengineered culture platforms, analysis of specific proteins presented to stem cells is possible. Critical to the success of the approach is single cell analysis, as more rapidly proliferating progenitors may mask the behavior of stem cells that proliferate slowly. Bioengineering approaches provide a potent means of gaining insight into the role of extrinsic factors in the stem cell microenvironment on stem cell function and the mechanisms that control their diverse fates. Ultimately, the multidisciplinary approach presented here will lead to novel therapeutic strategies for degenerative diseases.