CellProfiler has enabled the scientific research community to create flexible, modular image analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new version of the ...software supporting both whole-volume and plane-wise analysis of three-dimensional (3D) image stacks, increasingly common in biomedical research. CellProfiler's infrastructure is greatly improved, and we provide a protocol for cloud-based, large-scale image processing. New plugins enable running pretrained deep learning models on images. Designed by and for biologists, CellProfiler equips researchers with powerful computational tools via a well-documented user interface, empowering biologists in all fields to create quantitative, reproducible image analysis workflows.
The appearance-based approach to face detection has seen great advances in the last several years. In this approach, we learn the image statistics describing the texture pattern (appearance) of the ...object class we want to detect, e.g., the face. However, this approach has had limited success in providing an accurate and detailed description of the internal facial features, i.e., eyes, brows, nose, and mouth. In general, this is due to the limited information carried by the learned statistical model. While the face template is relatively rich in texture, facial features (e.g., eyes, nose, and mouth) do not carry enough discriminative information to tell them apart from all possible background images. We resolve this problem by adding the context information of each facial feature in the design of the statistical model. In the proposed approach, the context information defines the image statistics most correlated with the surroundings of each facial component. This means that when we search for a face or facial feature, we look for those locations which most resemble the feature yet are most dissimilar to its context. This dissimilarity with the context features forces the detector to gravitate toward an accurate estimate of the position of the facial feature. Learning to discriminate between feature and context templates is difficult, however, because the context and the texture of the facial features vary widely under changing expression, pose, and illumination, and may even resemble one another. We address this problem with the use of subclass divisions. We derive two algorithms to automatically divide the training samples of each facial feature into a set of subclasses, each representing a distinct construction of the same facial component (e.g., closed versus open eyes) or its context (e.g., different hairstyles). The first algorithm is based on a discriminant analysis formulation. The second algorithm is an extension of the AdaBoost approach. We provide extensive experimental results using still images and video sequences for a total of 3,930 images. We show that the results are almost as good as those obtained with manual detection.
PARP inhibitors have shown promising clinical activities for patients with BRCA mutations and are changing the landscape of ovarian cancer treatment. However, the therapeutic mechanisms of action for ...PARP inhibition in the interaction of tumors with the tumor microenvironment and the host immune system remain unclear. We find that PARP inhibition by olaparib triggers robust local and systemic antitumor immunity involving both adaptive and innate immune responses through a STING-dependent antitumor immune response in mice bearing Brca1-deficient ovarian tumors. This effect is further augmented when olaparib is combined with PD-1 blockade. Our findings thus provide a molecular mechanism underlying antitumor activity by PARP inhibition and lay a foundation to improve therapeutic outcome for cancer patients.
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•T cell-mediated cytotoxicity is important for therapeutic activity of PARP inhibition•Olaparib-treated Brca1-deficient tumor cells activate the STING pathway in APCs•STING pathway activation is required for the antitumor efficacy of PARP inhibition•PD-1 blockade enhances the antitumor efficacy of olaparib in Brca1-deficient tumors
Ding et al. show that PARP inhibition in Brca1-deficient tumors elicits strong antitumor immunity involving activation of both innate and adaptive immune responses, a process that is dependent on STING pathway activation. In addition, they show that addition of PD-1 blockade augments the therapeutic efficacy of PARP inhibitor treatment.
One of the major challenges in multiple particle tracking is the capture of extremely heterogeneous movements of objects in crowded scenes. The presence of numerous assignment candidates in the ...expected range of particle motion makes the tracking ambiguous and induces false positives. Lowering the ambiguity by reducing the search range, on the other hand, is not an option, as this would increase the rate of false negatives. We propose here a piecewise-stationary motion model (PMM) for the particle transport along an iterative smoother that exploits recursive tracking in multiple rounds in forward and backward temporal directions. By fusing past and future information, our method, termed PMMS, can recover fast transitions from freely or confined diffusive to directed motions with linear time complexity. To avoid false positives, we complemented recursive tracking with a robust inline estimator of the search radius for assignment (a.k.a. gating), where past and future information are exploited using only two frames at each optimization step. We demonstrate the improvement of our technique on simulated data especially the impact of density, variation in frame to frame displacements, and motion switching probability. We evaluated our technique on the 2D particle tracking challenge dataset published by Chenouard et al. in 2014. Using high SNR to focus on motion modeling challenges, we show superior performance at high particle density. On biological applications, our algorithm allows us to quantify the extremely small percentage of motor-driven movements of fluorescent particles along microtubules in a dense field of unbound, diffusing particles. We also show with virus imaging that our algorithm can cope with a strong reduction in recording frame rate while keeping the same performance relative to methods relying on fast sampling.
PARP inhibitors (PARPi) have drastically changed the treatment landscape of advanced ovarian tumors with BRCA mutations. However, the impact of this class of inhibitors in patients with advanced ...BRCA-mutant breast cancer is relatively modest. Using a syngeneic genetically-engineered mouse model of breast tumor driven by Brca1 deficiency, we show that tumor-associated macrophages (TAMs) blunt PARPi efficacy both in vivo and in vitro. Mechanistically, BRCA1-deficient breast tumor cells induce pro-tumor polarization of TAMs, which in turn suppress PARPi-elicited DNA damage in tumor cells, leading to reduced production of dsDNA fragments and synthetic lethality, hence impairing STING-dependent anti-tumor immunity. STING agonists reprogram M2-like pro-tumor macrophages into an M1-like anti-tumor state in a macrophage STING-dependent manner. Systemic administration of a STING agonist breaches multiple layers of tumor cell-mediated suppression of immune cells, and synergizes with PARPi to suppress tumor growth. The therapeutic benefits of this combination require host STING and are mediated by a type I IFN response and CD8
T cells, but do not rely on tumor cell-intrinsic STING. Our data illustrate the importance of targeting innate immune suppression to facilitate PARPi-mediated engagement of anti-tumor immunity in breast cancer.
Vimentin fibers orient traction stress Costigliola, Nancy; Ding, Liya; Burckhardt, Christoph J. ...
Proceedings of the National Academy of Sciences - PNAS,
05/2017, Letnik:
114, Številka:
20
Journal Article
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The intermediate filament vimentin is required for cells to transition from the epithelial state to the mesenchymal state and migrate as single cells; however, little is known about the specific role ...of vimentin in the regulation of mesenchymal migration. Vimentin is known to have a significantly greater ability to resist stress without breaking in vitro compared with actin or microtubules, and also to increase cell elasticity in vivo. Therefore, we hypothesized that the presence of vimentin could support the anisotropic mechanical strain of single-cell migration. To study this, we fluorescently labeled vimentin with an mEmerald tag using TALEN genome editing. We observed vimentin architecture in migrating human foreskin fibroblasts and found that network organization varied from long, linear bundles, or “fibers,” to shorter fragments with a mesh-like organization. We developed image analysis tools employing steerable filtering and iterative graph matching to characterize the fibers embedded in the surrounding mesh. Vimentin fibers were aligned with fibroblast branching and migration direction. The presence of the vimentin network was correlated with 10-fold slower local actin retrograde flow rates, as well as spatial homogenization of actin-based forces transmitted to the substrate. Vimentin fibers coaligned with and were required for the anisotropic orientation of traction stresses. These results indicate that the vimentin network acts as a load-bearing superstructure capable of integrating and reorienting actin-based forces. We propose that vimentin’s role in cell motility is to govern the alignment of traction stresses that permit single-cell migration.
A deep generative model of 3D single-cell organization Donovan-Maiye, Rory M; Brown, Jackson M; Chan, Caleb K ...
PLOS computational biology/PLoS computational biology,
01/2022, Letnik:
18, Številka:
1
Journal Article
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We introduce a framework for end-to-end integrative modeling of 3D single-cell multi-channel fluorescent image data of diverse subcellular structures. We employ stacked conditional β-variational ...autoencoders to first learn a latent representation of cell morphology, and then learn a latent representation of subcellular structure localization which is conditioned on the learned cell morphology. Our model is flexible and can be trained on images of arbitrary subcellular structures and at varying degrees of sparsity and reconstruction fidelity. We train our full model on 3D cell image data and explore design trade-offs in the 2D setting. Once trained, our model can be used to predict plausible locations of structures in cells where these structures were not imaged. The trained model can also be used to quantify the variation in the location of subcellular structures by generating plausible instantiations of each structure in arbitrary cell geometries. We apply our trained model to a small drug perturbation screen to demonstrate its applicability to new data. We show how the latent representations of drugged cells differ from unperturbed cells as expected by on-target effects of the drugs.
We studied two aspects of vimentin intermediate filament dynamics-transport of filaments and subunit exchange. We observed transport of long filaments in the periphery of cells using live-cell ...structured illumination microscopy. We studied filament transport elsewhere in cells using a photoconvertible-vimentin probe and total internal reflection microscopy. We found that filaments were rapidly transported along linear tracks in both anterograde and retrograde directions. Filament transport was microtubule dependent but independent of microtubule polymerization and/or an interaction with the plus end-binding protein APC. We also studied subunit exchange in filaments by long-term imaging after photoconversion. We found that converted vimentin remained in small clusters along the length of filaments rather than redistributing uniformly throughout the network, even in cells that divided after photoconversion. These data show that vimentin filaments do not depolymerize into individual subunits; they recompose by severing and reannealing. Together these results show that vimentin filaments are very dynamic and that their transport is required for network maintenance.
Overexpression of the histone acetyltransferase p300 is implicated in the proliferation and progression of prostate cancer, but evidence of a causal role is lacking. In this study, we provide genetic ...evidence that this generic transcriptional coactivator functions as a positive modifier of prostate tumorigenesis. In a mouse model of PTEN deletion-induced prostate cancer, genetic ablation of p300 attenuated expression of the androgen receptor (AR). This finding was confirmed in human prostate cancer cells in which PTEN expression was abolished by RNA interference-mediated attenuation. These results were consistent with clinical evidence that the expression of p300 and AR correlates positively in human prostate cancer specimens. Mechanistically, PTEN inactivation increased AR phosphorylation at serine 81 (Ser81) to promote p300 binding and acetylation of AR, thereby precluding its polyubiquitination and degradation. In support of these findings, in PTEN-deficient prostate cancer in the mouse, we found that p300 was crucial for AR target gene expression. Taken together, our work identifies p300 as a molecular determinant of AR degradation and highlights p300 as a candidate target to manage prostate cancer, especially in cases marked by PTEN loss.
Neuron morphology analysis is an essential component of neuron cell-type definition. Morphology reconstruction represents a bottleneck in high-throughput morphology analysis workflow, and erroneous ...extra reconstruction owing to noise and entanglements in dense neuron regions restricts the usability of automated reconstruction results. We propose SNAP, a structure-based neuron morphology reconstruction pruning pipeline, to improve the usability of results by reducing erroneous extra reconstruction and splitting entangled neurons.
For the four different types of erroneous extra segments in reconstruction (caused by noise in the background, entanglement with dendrites of close-by neurons, entanglement with axons of other neurons, and entanglement within the same neuron), SNAP incorporates specific statistical structure information into rules for erroneous extra segment detection and achieves pruning and multiple dendrite splitting.
Experimental results show that this pipeline accomplishes pruning with satisfactory precision and recall. It also demonstrates good multiple neuron-splitting performance. As an effective tool for post-processing reconstruction, SNAP can facilitate neuron morphology analysis.
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