How Modifications of Corneal Cross-Linking Protocols Influence Corneal Resistance to Enzymatic Digestion and Treatment Depth.

Purpose: The purpose of this study was to determine the effects of the Photoactivated Chromophore for Keratitis Corneal Cross-Linking (PACK-CXL) protocol modifications on corneal resistance to enzymatic digestion and treatment depth. Methods: Eight hundred one ex vivo porcine eyes were randomly divided into groups of 12 to 86 corneas, treated with various epi-off PACK-CXL modifications, including acceleration (30 > 2 minutes, 5.4 J/cm2), increased fluence (5.4 > 32.4 J/cm2), deuterium oxide (D2O) supplementation, different carrier types (dextran versus hydroxypropyl methylcellulose [HPMC]), increased riboflavin concentration (0.1 > 0.4%), and riboflavin replenishment during irradiation (yes/no). Control group eyes did not receive PACK-CXL. A pepsin digestion assay was used to determine corneal resistance to enzymatic digestion. A phalloidin fluorescent imaging assay was used to determine the PACK-CXL treatment effect depth. Differences between groups were evaluated using a linear model and a derivative method, respectively. Results: PACK-CXL significantly increased corneal resistance to enzymatic digestion compared to no treatment (P < 0.03). When compared to a 10 minute, 5.4 J/cm2 PACK-CXL protocol, fluences of 16.2 J/cm2 and higher increased corneal resistance to enzymatic digestion by 1.5- to 2-fold (P < 0.001). Other protocol modifications did not significantly change corneal resistance. A 16.2 J/cm2 fluence also increased collagen compaction in the anterior stroma, whereas omitting riboflavin replenishment during irradiation increased PACK-CXL treatment depth. Conclusions: Increasing fluence will likely optimize PACK-CXL treatment effectiveness. Treatment acceleration reduces treatment duration without compromising effectiveness. Translational Relevance: The generated data help to optimize clinical PACK-CXL settings and direct future research efforts.

Detecting variation in starch granule size and morphology by high-throughput microscopy and flow cytometry.

Starch forms semi-crystalline, water-insoluble granules, the size and morphology of which vary according to biological origin. These traits, together with polymer composition and structure, determine the physicochemical properties of starch. However, screening methods to identify differences in starch granule size and shape are lacking. Here, we present two approaches for high-throughput starch granule extraction and size determination using flow cytometry and automated, high-throughput light microscopy. We evaluated the practicality of both methods using starch from different species and tissues and demonstrated their effectiveness by screening for induced variation in starch extracted from over 10,000 barley lines, yielding four with heritable changes in the ratio of large A-granules to small B-granules. Analysis of Arabidopsis lines altered in starch biosynthesis further demonstrates the applicability of these approaches. Identifying variation in starch granule size and shape will enable identification of trait-controlling genes for developing crops with desired properties, and could help optimise starch processing.

Posttranscriptional Regulation of the Human LDL Receptor by the U2-Spliceosome.

BACKGROUND: The LDLR (low-density lipoprotein receptor) in the liver is the major determinant of LDL-cholesterol levels in human plasma. The discovery of genes that regulate the activity of LDLR helps to identify pathomechanisms of hypercholesterolemia and novel therapeutic targets against atherosclerotic cardiovascular disease. METHODS: We performed a genome-wide RNA interference screen for genes limiting the uptake of fluorescent LDL into Huh-7 hepatocarcinoma cells. Top hit genes were validated by in vitro experiments as well as analyses of data sets on gene expression and variants in human populations. RESULTS: The knockdown of 54 genes significantly inhibited LDL uptake. Fifteen of them encode for components or interactors of the U2-spliceosome. Knocking down any one of 11 out of 15 genes resulted in the selective retention of intron 3 of LDLR. The translated LDLR fragment lacks 88% of the full length LDLR and is detectable neither in nontransfected cells nor in human plasma. The hepatic expression of the intron 3 retention transcript is increased in nonalcoholic fatty liver disease as well as after bariatric surgery. Its expression in blood cells correlates with LDL-cholesterol and age. Single nucleotide polymorphisms and 3 rare variants of one spliceosome gene, RBM25, are associated with LDL-cholesterol in the population and familial hypercholesterolemia, respectively. Compared with overexpression of wild-type RBM25, overexpression of the 3 rare RBM25 mutants in Huh-7 cells led to lower LDL uptake. CONCLUSIONS: We identified a novel mechanism of posttranscriptional regulation of LDLR activity in humans and associations of genetic variants of RBM25 with LDL-cholesterol levels.

AutoTube: a novel software for the automated morphometric analysis of vascular networks in tissues.

Due to their involvement in many physiologic and pathologic processes, there is a great interest in identifying new molecular pathways that mediate the formation and function of blood and lymphatic vessels. Vascular research increasingly involves the image-based analysis and quantification of vessel networks in tissue whole-mounts or of tube-like structures formed by cultured endothelial cells in vitro. While both types of experiments deliver important mechanistic insights into (lymph)angiogenic processes, the manual analysis and quantification of such experiments are typically labour-intensive and affected by inter-experimenter variability. To bypass these problems, we developed AutoTube, a new software that quantifies parameters like the area covered by vessels, vessel width, skeleton length and branching or crossing points of vascular networks in tissues and in in vitro assays. AutoTube is freely downloadable, comprises an intuitive graphical user interface and helps to perform otherwise highly time-consuming image analyses in a rapid, automated and reproducible manner. By analysing lymphatic and blood vascular networks in whole-mounts prepared from different tissues or from gene-targeted mice with known vascular abnormalities, we demonstrate the ability of AutoTube to determine vascular parameters in close agreement to the manual analyses and to identify statistically significant differences in vascular morphology in tissues and in vascular networks formed in in vitro assays.

Quantitative spatial analysis of haematopoiesis-regulating stromal cells in the bone marrow microenvironment by 3D microscopy.

Sinusoidal endothelial cells and mesenchymal CXCL12-abundant reticular cells are principal bone marrow stromal components, which critically modulate haematopoiesis at various levels, including haematopoietic stem cell maintenance. These stromal subsets are thought to be scarce and function via highly specific interactions in anatomically confined niches. Yet, knowledge on their abundance, global distribution and spatial associations remains limited. Using three-dimensional quantitative microscopy we show that sinusoidal endothelial and mesenchymal reticular subsets are remarkably more abundant than estimated by conventional flow cytometry. Moreover, both cell types assemble in topologically complex networks, associate to extracellular matrix and pervade marrow tissues. Through spatial statistical methods we challenge previous models and demonstrate that even in the absence of major specific interaction forces, virtually all tissue-resident cells are invariably in physical contact with, or close proximity to, mesenchymal reticular and sinusoidal endothelial cells. We further show that basic structural features of these stromal components are preserved during ageing.

VEGF-A Regulates Cellular Localization of SR-BI as Well as Transendothelial Transport of HDL but Not LDL.

OBJECTIVE: Low- and high-density lipoproteins (LDL and HDL) must pass the endothelial layer to exert pro- and antiatherogenic activities, respectively, within the vascular wall. However, the rate-limiting factors that mediate transendothelial transport of lipoproteins are yet little known. Therefore, we performed a high-throughput screen with kinase drug inhibitors to identify modulators of transendothelial LDL and HDL transport. APPROACH AND RESULTS: Microscopy-based high-content screening was performed by incubating human aortic endothelial cells with 141 kinase-inhibiting drugs and fluorescent-labeled LDL or HDL. Inhibitors of vascular endothelial growth factor (VEGF) receptors (VEGFR) significantly decreased the uptake of HDL but not LDL. Silencing of VEGF receptor 2 significantly decreased cellular binding, association, and transendothelial transport of 125I-HDL but not 125I-LDL. RNA interference with VEGF receptor 1 or VEGF receptor 3 had no effect. Binding, uptake, and transport of HDL but not LDL were strongly reduced in the absence of VEGF-A from the cell culture medium and were restored by the addition of VEGF-A. The restoring effect of VEGF-A on endothelial binding, uptake, and transport of HDL was abrogated by pharmacological inhibition of phosphatidyl-inositol 3 kinase/protein kinase B or p38 mitogen-activated protein kinase, as well as silencing of scavenger receptor BI. Moreover, the presence of VEGF-A was found to be a prerequisite for the localization of scavenger receptor BI in the plasma membrane of endothelial cells. CONCLUSIONS: The identification of VEGF as a regulatory factor of transendothelial transport of HDL but not LDL supports the concept that the endothelium is a specific and, hence, druggable barrier for the entry of lipoproteins into the vascular wall.

Long-term tracking of budding yeast cells in brightfield microscopy: CellStar and the Evaluation Platform.

With the continuous expansion of single cell biology, the observation of the behaviour of individual cells over extended durations and with high accuracy has become a problem of central importance. Surprisingly, even for yeast cells that have relatively regular shapes, no solution has been proposed that reaches the high quality required for long-term experiments for segmentation and tracking (S&T) based on brightfield images. Here, we present CellStar, a tool chain designed to achieve good performance in long-term experiments. The key features are the use of a new variant of parametrized active rays for segmentation, a neighbourhood-preserving criterion for tracking, and the use of an iterative approach that incrementally improves S&T quality. A graphical user interface enables manual corrections of S&T errors and their use for the automated correction of other, related errors and for parameter learning. We created a benchmark dataset with manually analysed images and compared CellStar with six other tools, showing its high performance, notably in long-term tracking. As a community effort, we set up a website, the Yeast Image Toolkit, with the benchmark and the Evaluation Platform to gather this and additional information provided by others.

Hypoxia Induces a HIF-1-Dependent Transition from Collective-to-Amoeboid Dissemination in Epithelial Cancer Cells.

Cancer metastases arise from a multi-step process that requires metastasizing tumor cells to adapt to signaling input from varying tissue environments [1]. As an early metastatic event, cancer cell dissemination occurs through different migration programs, including multicellular, collective, and single-cell mesenchymal or amoeboid migration [2-4]. Migration modes can interconvert based on changes in cell adhesion, cytoskeletal mechanotransduction [5], and/or proteolysis [6], most likely under the control of transcriptional programs such as the epithelial-to-mesenchymal transition (EMT) [7, 8]. However, how plasticity of tumor cell migration and EMT is spatiotemporally controlled and connected upon challenge by the tumor microenvironment remains unclear. Using 3D cultures of collectively invading breast and head and neck cancer spheroids, here we identify hypoxia, a hallmark of solid tumors [9], as an inducer of the collective-to-amoeboid transition (CAT), promoting the dissemination of amoeboid-moving single cells from collective invasion strands. Hypoxia-induced amoeboid detachment was driven by hypoxia-inducible factor 1 (HIF-1), followed the downregulation of E-cadherin, and produced heterogeneous cell subsets whose phenotype and migration were dependent (∼30%) or independent (∼70%) of Twist-mediated EMT. EMT-like and EMT-independent amoeboid cell subsets showed stable amoeboid movement over hours as well as leukocyte-like traits, including rounded morphology, matrix metalloproteinase (MMP)-independent migration, and nuclear deformation. Cancer cells undergoing pharmacological stabilization of HIFs retained their constitutive ability for early metastatic seeding in an experimental model of lung metastasis, indicating that hypoxia-induced CAT enhances cell release rather than early organ colonization. Induced by metabolic challenge, amoeboid movement may thus constitute a common endpoint of both EMT-dependent and EMT-independent cancer dissemination programs.

In Vivo Fluorescence Imaging of the Activity of CEA TCB, a Novel T-Cell Bispecific Antibody, Reveals Highly Specific Tumor Targeting and Fast Induction of T-Cell-Mediated Tumor Killing.

PURPOSE: CEA TCB (RG7802, RO6958688) is a novel T-cell bispecific antibody, engaging CD3ε upon binding to carcinoembryonic antigen (CEA) on tumor cells. Containing an engineered Fc region, conferring an extended blood half-life while preventing side effects due to activation of innate effector cells, CEA TCB potently induces tumor lysis in mouse tumors. Here we aimed to characterize the pharmacokinetic profile, the biodistribution, and the mode of action of CEA TCB by combining in vitro and in vivo fluorescence imaging readouts. EXPERIMENTAL DESIGN: CEA-expressing tumor cells (LS174T) and human peripheral blood mononuclear cells (PBMC) were cocultured in vitro or cografted into immunocompromised mice. Fluorescence reflectance imaging and intravital 2-photon (2P) microscopy were employed to analyze in vivo tumor targeting while in vitro confocal and intravital time-lapse imaging were used to assess the mode of action of CEA TCB. RESULTS: Fluorescence reflectance imaging revealed increased ratios of extravascular to vascular fluorescence signals in tumors after treatment with CEA TCB compared with control antibody, suggesting specific targeting, which was confirmed by intravital microscopy. Confocal and intravital 2P microscopy showed CEA TCB to accelerate T-cell-dependent tumor cell lysis by inducing a local increase of effector to tumor cell ratios and stable crosslinking of multiple T cells to individual tumor cells. CONCLUSIONS: Using optical imaging, we demonstrate specific tumor targeting and characterize the mode of CEA TCB-mediated target cell lysis in a mouse tumor model, which supports further clinical evaluation of CEA TCB. Clin Cancer Res; 22(17); 4417-27. ©2016 AACRSee related commentary by Teijeira et al., p. 4277.

Modeling dynamics of cell-to-cell variability in TRAIL-induced apoptosis explains fractional killing and predicts reversible resistance.

Isogenic cells sensing identical external signals can take markedly different decisions. Such decisions often correlate with pre-existing cell-to-cell differences in protein levels. When not neglected in signal transduction models, these differences are accounted for in a static manner, by assuming randomly distributed initial protein levels. However, this approach ignores the a priori non-trivial interplay between signal transduction and the source of this cell-to-cell variability: temporal fluctuations of protein levels in individual cells, driven by noisy synthesis and degradation. Thus, modeling protein fluctuations, rather than their consequences on the initial population heterogeneity, would set the quantitative analysis of signal transduction on firmer grounds. Adopting this dynamical view on cell-to-cell differences amounts to recast extrinsic variability into intrinsic noise. Here, we propose a generic approach to merge, in a systematic and principled manner, signal transduction models with stochastic protein turnover models. When applied to an established kinetic model of TRAIL-induced apoptosis, our approach markedly increased model prediction capabilities. One obtains a mechanistic explanation of yet-unexplained observations on fractional killing and non-trivial robust predictions of the temporal evolution of cell resistance to TRAIL in HeLa cells. Our results provide an alternative explanation to survival via induction of survival pathways since no TRAIL-induced regulations are needed and suggest that short-lived anti-apoptotic protein Mcl1 exhibit large and rare fluctuations. More generally, our results highlight the importance of accounting for stochastic protein turnover to quantitatively understand signal transduction over extended durations, and imply that fluctuations of short-lived proteins deserve particular attention.

Bridging the gaps in systems biology.

Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding-the elucidation of the basic and presumably conserved "design" and "engineering" principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.

STL-based analysis of TRAIL-induced apoptosis challenges the notion of type I/type II cell line classification.

Extrinsic apoptosis is a programmed cell death triggered by external ligands, such as the TNF-related apoptosis inducing ligand (TRAIL). Depending on the cell line, the specific molecular mechanisms leading to cell death may significantly differ. Precise characterization of these differences is crucial for understanding and exploiting extrinsic apoptosis. Cells show distinct behaviors on several aspects of apoptosis, including (i) the relative order of caspases activation, (ii) the necessity of mitochondria outer membrane permeabilization (MOMP) for effector caspase activation, and (iii) the survival of cell lines overexpressing Bcl2. These differences are attributed to the activation of one of two pathways, leading to classification of cell lines into two groups: type I and type II. In this work we challenge this type I/type II cell line classification. We encode the three aforementioned distinguishing behaviors in a formal language, called signal temporal logic (STL), and use it to extensively test the validity of a previously-proposed model of TRAIL-induced apoptosis with respect to experimental observations made on different cell lines. After having solved a few inconsistencies using STL-guided parameter search, we show that these three criteria do not define consistent cell line classifications in type I or type II, and suggest mutants that are predicted to exhibit ambivalent behaviors. In particular, this finding sheds light on the role of a feedback loop between caspases, and reconciliates two apparently-conflicting views regarding the importance of either upstream or downstream processes for cell-type determination. More generally, our work suggests that these three distinguishing behaviors should be merely considered as type I/II features rather than cell-type defining criteria. On the methodological side, this work illustrates the biological relevance of STL-diagrams, STL population data, and STL-guided parameter search implemented in the tool Breach. Such tools are well-adapted to the ever-increasing availability of heterogeneous knowledge on complex signal transduction pathways.

STSE: Spatio-Temporal Simulation Environment Dedicated to Biology.

BACKGROUND: Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. RESULTS: The Spatio-Temporal Simulation Environment (STSE) is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS) and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and workflow. We demonstrate it's usefulness using the example of a signaling cascade leading to formation of a morphological gradient of Fus3 within the cytoplasm of the mating yeast cell Saccharomyces cerevisiae. CONCLUSIONS: STSE is an efficient and powerful novel platform, designed for computational handling and evaluation of microscopic images. It allows for an uninterrupted workflow including digitization, representation, analysis, and mathematical modeling. By providing the means to relate the simulation to the image data it allows for systematic, image driven model validation or rejection. STSE can be scripted and extended using the Python language. STSE should be considered rather as an API together with workflow guidelines and a collection of GUI tools than a stand alone application. The priority of the project is to provide an easy and intuitive way of extending and customizing software using the Python language.

Flux-based transport enhancement as a plausible unifying mechanism for auxin transport in meristem development.

Plants continuously generate new organs through the activity of populations of stem cells called meristems. The shoot apical meristem initiates leaves, flowers, and lateral meristems in highly ordered, spiralled, or whorled patterns via a process called phyllotaxis. It is commonly accepted that the active transport of the plant hormone auxin plays a major role in this process. Current hypotheses propose that cellular hormone transporters of the PIN family would create local auxin maxima at precise positions, which in turn would lead to organ initiation. To explain how auxin transporters could create hormone fluxes to distinct regions within the plant, different concepts have been proposed. A major hypothesis, canalization, proposes that the auxin transporters act by amplifying and stabilizing existing fluxes, which could be initiated, for example, by local diffusion. This convincingly explains the organised auxin fluxes during vein formation, but for the shoot apical meristem a second hypothesis was proposed, where the hormone would be systematically transported towards the areas with the highest concentrations. This implies the coexistence of two radically different mechanisms for PIN allocation in the membrane, one based on flux sensing and the other on local concentration sensing. Because these patterning processes require the interaction of hundreds of cells, it is impossible to estimate on a purely intuitive basis if a particular scenario is plausible or not. Therefore, computational modelling provides a powerful means to test this type of complex hypothesis. Here, using a dedicated computer simulation tool, we show that a flux-based polarization hypothesis is able to explain auxin transport at the shoot meristem as well, thus providing a unifying concept for the control of auxin distribution in the plant. Further experiments are now required to distinguish between flux-based polarization and other hypotheses.