A genome-wide functional investigation into the roles of receptor-like proteins in Arabidopsis

Receptor-like proteins (RLPs) are cell surface receptors that typically consist of an extracellular leucine-rich repeat domain, a transmembrane domain, and a short cytoplasmatic tail. In several plant species, RLPs have been found to play a role in disease resistance, such as the tomato (Solanum lycopersicum) Cf and Ve proteins and the apple (Malus domestica) HcrVf2 protein that mediate resistance against the fungal pathogens Cladosporium fulvum, Verticillium spp., and Venturia inaequalis, respectively. In addition, RLPs play a role in plant development; Arabidopsis (Arabidopsis thaliana) TOO MANY MOUTHS (TMM) regulates stomatal distribution, while Arabidopsis CLAVATA2 (CLV2) and its functional maize (Zea mays) ortholog FASCINATED EAR2 regulate meristem maintenance. In total, 57 RLP genes have been identified in the Arabidopsis genome and a genome-wide collection of T-DNA insertion lines was assembled. This collection was functionally analyzed with respect to plant growth and development and sensitivity to various stress responses, including susceptibility toward pathogens. A number of novel developmental phenotypes were revealed for our CLV2 and TMM insertion mutants. In addition, one AtRLP gene was found to mediate abscisic acid sensitivity and another AtRLP gene was found to influence nonhost resistance toward Pseudomonas syringae pv phaseolicola. This genome-wide collection of Arabidopsis RLP gene T-DNA insertion mutants provides a tool for future investigations into the biological roles of RLPs.     

Neural network strategies for plasma membrane selection in fluorescence microscopy images

In recent years, there has been an explosion of fluorescence microscopy studies of live cells in the literature. The analysis of the images obtained in these studies often requires labor-intensive manual annotation to extract meaningful information. In this study, we explore the utility of a neural network approach to recognize, classify, and select plasma membranes in high-resolution images, thus greatly speeding up data analysis and reducing the need for personnel training for highly repetitive tasks. Two different strategies are tested: 1) a semantic segmentation strategy, and 2) a sequential application of an object detector followed by a semantic segmentation network. Multiple network architectures are evaluated for each strategy, and the best performing solutions are combined and implemented in the Recognition Of Cellular Membranes software. We show that images annotated manually and with the Recognition Of Cellular Membranes software yield identical results by comparing Förster resonance energy transfer binding curves for the membrane protein fibroblast growth factor receptor 3. The approach that we describe in this work can be applied to other image selection tasks in cell biology.     

Conflict and competition between model-based and model-free control

A large literature has accumulated suggesting that human and animal decision making is driven by at least two systems, and that important functions of these systems can be captured by reinforcement learning algorithms. The “model-free” system caches and uses stimulus–value or stimulus–response associations, and the “model-based” system implements more flexible planning using a model of the world. However, it is not clear how the two systems interact during deliberation and how a single decision emerges from this process, especially when they disagree. Most previous work has assumed that while the systems operate in parallel, they do so independently, and they combine linearly to influence decisions. Using an integrated reinforcement learning/drift-diffusion model, we tested the hypothesis that the two systems interact in a non-linear fashion similar to other situations with cognitive conflict. We differentiated two forms of conflict: action conflict, a binary state representing whether the systems disagreed on the best action, and value conflict, a continuous measure of the extent to which the two systems disagreed on the difference in value between the available options. We found that decisions with greater value conflict were characterized by reduced model-based control and increased caution both with and without action conflict. Action conflict itself (the binary state) acted in the opposite direction, although its effects were less prominent. We also found that between-system conflict was highly correlated with within-system conflict, and although it is less clear a priori why the latter might influence the strength of each system above its standard linear contribution, we could not rule it out. Our work highlights the importance of non-linear conflict effects, and provides new constraints for more detailed process models of decision making. It also presents new avenues to explore with relation to disorders of compulsivity, where an imbalance between systems has been implicated.     

OPA1 deficiency promotes secretion of FGF21 from muscle that prevents obesity and insulin resistance

Mitochondrial dynamics is a conserved process by which mitochondria undergo repeated cycles of fusion and fission, leading to exchange of mitochondrial genetic content, ions, metabolites, and proteins. Here, we examine the role of the mitochondrial fusion protein optic atrophy 1 (OPA1) in differentiated skeletal muscle by reducing OPA1 gene expression in an inducible manner. OPA1 deficiency in young mice results in non‐lethal progressive mitochondrial dysfunction and loss of muscle mass. Mutant mice are resistant to age‐ and diet‐induced weight gain and insulin resistance, by mechanisms that involve activation of ER stress and secretion of fibroblast growth factor 21 (FGF21) from skeletal muscle, resulting in increased metabolic rates and improved whole‐body insulin sensitivity. OPA1‐elicited mitochondrial dysfunction activates an integrated stress response that locally induces muscle atrophy, but via secretion of FGF21 acts distally to modulate whole‐body metabolism.     

Stage-specific optimization of activin/nodal and BMP signaling promotes cardiac differentiation of mouse and human pluripotent stem cell lines

Efficient differentiation of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) to a variety of lineages requires step-wise approaches replicating the key commitment stages found during embryonic development. Here we show that expression of PdgfR-α segregates mouse ESC-derived Flk-1 mesoderm into Flk-1(+)PdgfR-α(+) cardiac and Flk-1(+)PdgfR-α(-) hematopoietic subpopulations. By monitoring Flk-1 and PdgfR-α expression, we found that specification of cardiac mesoderm and cardiomyocytes is determined by remarkably small changes in levels of Activin/Nodal and BMP signaling. Translation to human ESCs and iPSCs revealed that the emergence of cardiac mesoderm could also be monitored by coexpression of KDR and PDGFR-α and that this process was similarly dependent on optimal levels of Activin/Nodal and BMP signaling. Importantly, we found that individual mouse and human pluripotent stem cell lines require optimization of these signaling pathways for efficient cardiac differentiation, illustrating a principle that may well apply in other contexts.     

Use of cloned populations of mouse lymphocytes to analyze cellular differentiation

We describe a method for generation of homogeneous cell populations that each arise from clonal expansion of cells at a discrete stage of differentiation within a single lineage. We have used this to produce continuously propagatable lymphocyte clones. Each clone represents a cell at a progressive stage of thymus-dependent cellular differentiation. These cloned cells bear stable surface membrane glycoproteins characteristic of precursor cells and mature progeny; conditions allowing maximal cloning efficiencies for each cell type (10–85%) have been established. Mature lymphocyte clones continue to express specialized function and provide material for biochemical analysis of T lymphocyte functions; one fully differentiated clone from the “inducer” lymphocyte set synthesizes a molecule that activates other lymphocytes to secrete immunoglobulin. This activity is associated with a highly purified molecule having a molecular weight of 45,000 daltons and an isoelectric point of approximately 6.0. This molecule, together with clones of precursor and mature T lymphocytes, may provide a system to further study the mechanisms of gene activation during cellular differentiation.