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At least 55 records · Page 3

The histone code of the fungal genus Aspergillus uncovered by evolutionary and proteomic analyses

Chemical modifications of DNA and histone proteins impact the organization of chromatin within the nucleus. Changes in these modifications, catalysed by different chromatin-modifying enzymes, influence chromatin organization, which in turn is thought to impact the spatial and temporal regulation of gene expression. While combinations of different histone modifications, the histone code, have been studied in several model species, we know very little about histone modifications in the fungal genus Aspergillus, whose members are generally well studied due to their importance as models in cell and molecular biology as well as their medical and biotechnological relevance. Here, we used phylogenetic analyses in 94 Aspergilli as well as other fungi to uncover the occurrence and evolutionary trajectories of enzymes and protein complexes with roles in chromatin modifications or regulation. We found that these enzymes and complexes are highly conserved in Aspergilli, pointing towards a complex repertoire of chromatin modifications. Nevertheless, we also observed few recent gene duplications or losses, highlighting Aspergillus species to further study the roles of specific chromatin modifications. SET7 (KMT6) and other components of PRC2 (Polycomb Repressive Complex 2), which is responsible for methylation on histone H3 at lysine 27 in many eukaryotes including fungi, are absent in Aspergilli as well as in closely related Penicillium species, suggesting that these lost the capacity for this histone modification. We corroborated our computational predictions by performing untargeted MS analysis of histone post-translational modifications in Aspergillus nidulans. This systematic analysis will pave the way for future research into the complexity of the histone code and its functional implications on genome architecture and gene regulation in fungi.

59 BASIC BIOLOGICAL SCIENCES↗

Geometric analysis of Arabidopsis root apex reveals a new aspect of the ethylene signal transduction pathway in development

Structurally, ethylene is the simplest phytohormone and regulates multiple aspects of plant growth and development. Its effects are mediated by a signal transduction cascade involving receptors, MAP kinases and transcription factors. Many morphological effects of ethylene in plant development, including root size, have been previously described. In this article a combined geometric and algebraic approach has been used to analyse the shape and the curvature in the root apex of Arabidopsis seedlings. The process requires the fitting of Bezier curves that reproduce the root apex shape, and the calculation of the corresponding curvatures. The application of the method has allowed us to identify significant differences in the root curvatures of ethylene insensitive mutants (ein2-1 and etr1-1) with respect to the wild-type Columbia.

Arabidopsis/genetics/growth & development↗

The effect of hypogravity and hypergravity on cells of the immune system

This article reviews the gravity effects discovered in T lymphocytes and other cells of the immune system. The strong depression of mitogenic activation first observed in an experiment conducted in Spacelab 1 in 1983 triggered several other investigations in space and on the ground in the clinostat and in the centrifuge in the past 10 years. During this period, great progress was made in our knowledge of the complex mechanism of T cell activation as well as the technology to analyze the lymphokines produced during stimulation. Nevertheless, several aspects of the steps leading to activation are not yet clear. Studies in hypogravity and hypergravity may contribute to answering some of the questions. A recent investigation in the U.S. Spacelab SLS-1, based on a new technology in which leukocytes are attached to microcarrier beads, showed that the strong inhibition of activation in microgravity is due to a malfunction of monocytes acting as accessory cells. In fact, interleukin-1 production is nearly nil in resuspended monocytes, whereas T cell activation is doubled in attached cells. In hypergravity, but not at 1g, concanavalin A bound to erythrocytes activates B lymphocytes in addition to T cells. The activation of Jurkat cells is also severely impaired in space. These recent results have raised new questions that have to be answered in experiments to be conducted in space and on Earth in this decade. The experimental system, based on the mitogenic activation of T lymphocytes and accessory cells attached to microcarriers, offers an optimum model for studying basic biological mechanisms of the cell to assess the immunological fitness of humans in space and to test the feasibility of bioprocesses in space as well as on Earth.

NASA Discipline Regulatory Physiology↗

Modular cell-free expression plasmids to accelerate biological design in cells

Industrial biotechnology aims to produce high-value products from renewable resources. This can be challenging because model microorganisms—organisms that are easy to use like Escherichia coli—often lack the machinery required to utilize desired feedstocks like lignocellulosic biomass or syngas. Non-model organisms, such as Clostridium, are industrially proven and have desirable metabolic features but have several hurdles to mainstream use. Namely, these species grow more slowly than conventional laboratory microbes, and genetic tools for engineering them are far less prevalent. To address these hurdles for accelerating cellular design, cell-free synthetic biology has matured as an approach for characterizing non-model organisms and rapidly testing metabolic pathways in vitro. Unfortunately, cell-free systems can require specialized DNA architectures with minimal regulation that are not compatible with cellular expression. In this work, we develop a modular vector system that allows for T7 expression of desired enzymes for cell-free expression and direct Golden Gate assembly into Clostridium expression vectors. Utilizing the Joint Genome Institute’s DNA Synthesis Community Science Program, we designed and synthesized these plasmids and genes required for our projects allowing us to shuttle DNA easily between our in vitro and in vivo experiments. We next validated that these vectors were sufficient for cell-free expression of functional enzymes, performing on par with the previous state-of-the-art. Lastly, we demonstrated automated six-part DNA assemblies for Clostridium autoethanogenum expression with efficiencies ranging from 68% to 90%. We anticipate this system of plasmids will enable a framework for facile testing of biosynthetic pathways in vitro and in vivo by shortening development cycles.

59 BASIC BIOLOGICAL SCIENCES↗

Study of impacts of two types of cellular aging on the yeast bud morphogenesis

Understanding the mechanisms of the cellular aging processes is crucial for attempting to extend organismal lifespan and for studying age-related degenerative diseases. Yeast cells divide through budding, providing a classical biological model for studying cellular aging. With their powerful genetics, relatively short cell cycle, and well-established signaling pathways also found in animals, yeast cells offer valuable insights into the aging process. Recent experiments suggested the existence of two aging modes in yeast characterized by nucleolar and mitochondrial declines, respectively. By analyzing experimental data, this study shows that cells evolving into those two aging modes behave differently when they are young. While buds grow linearly in both modes, cells that consistently generate spherical buds throughout their lifespan demonstrate greater efficacy in controlling bud size and growth rate at young ages. A three-dimensional multiscale chemical-mechanical model was developed and used to suggest and test hypothesized impacts of aging on bud morphogenesis. Experimentally calibrated model simulations showed that during the early stage of budding, tubular bud shape in one aging mode could be generated by locally inserting new materials at the bud tip, a process guided by the polarized Cdc42 signal. Furthermore, the aspect ratio of the tubular bud could be stabilized during the late stage as observed in experiments in this work. The model simulation results suggest that the localization of new cell surface material insertion, regulated by chemical signal polarization, could be weakened due to cellular aging in yeast and other cell types, leading to the change and stabilization of the bud aspect ratio.

Tsai, Kevin↗

MicroRNA expression in animal models of amyotrophic lateral sclerosis and potential therapeutic approaches

A review of recent animal models of amyotrophic lateral sclerosis showed a large number of miRNAs had altered levels of expression in the brain and spinal cord, motor neurons of spinal cord and brainstem, and hypoglossal, facial, and red motor nuclei and were mostly upregulated. Among the miRNAs found to be upregulated in two of the studies were miR-21, miR-155, miR-125b, miR-146a, miR-124, miR-9, and miR-19b, while those downregulated in two of the studies included miR-146a, miR-29, miR-9, and miR-125b. A change of direction in miRNA expression occurred in some tissues when compared (e.g., miR-29b-3p in cerebellum and spinal cord of wobbler mice at 40 days), or at different disease stages (e.g., miR-200a in spinal cord of SOD1(G93A) mice at 95 days vs. 108 and 112 days). In the animal models, suppression of miR-129-5p resulted in increased lifespan, improved muscle strength, reduced neuromuscular junction degeneration, and tended to improve motor neuron survival in the SOD1(G93A) mouse model. Suppression of miR-155 was also associated with increased lifespan, while lowering of miR-29a tended to improve lifespan in males and increase muscle strength in SOD1(G93A) mice. Overexpression of members of miR-17~92 cluster improved motor neuron survival in SOD1(G93A) mice. Treatment with an artificial miRNA designed to target hSOD1 increased lifespan and improved muscle strength in SOD1(G93A) animals. Further studies with animal models of amyotrophic lateral sclerosis are warranted to validate these findings and identify specific miRNAs whose suppression or directed against hSOD1 results in increased lifespan, improved muscle strength, reduced neuromuscular junction degeneration, and improved motor neuron survival in SOD1(G93A) animals.

59 BASIC BIOLOGICAL SCIENCES↗

Solving the puzzle of Fe homeostasis by integrating molecular, mathematical, and societal models

To ensure optimal utilization and bioavailability, iron uptake, transport, subcellular localization, and assimilation are tightly regulated in plants. In this work, we examine recent advances in our understanding of cellular responses to Fe deficiency. We then use intracellular mechanisms of Fe homeostasis to discuss how formalizing cell biology knowledge via a mathematical model can advance discovery even when quantitative data is limited. Using simulation-based inference to identify plausible systems mechanisms that conform to known emergent phenotypes can yield novel, testable hypotheses to guide targeted experiments. However, this approach relies on the accurate encoding of domain-expert knowledge in exploratory mathematical models. We argue that this would be facilitated by fostering more “systems thinking” life scientists and that diversifying your research team may be a practical path to achieve that goal.

59 BASIC BIOLOGICAL SCIENCES↗

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

59 BASIC BIOLOGICAL SCIENCES↗

Use of microgravity bioreactors for development of an in vitro rat salivary gland cell culture model

During development, salivary gland (SG) cells both secrete factors which modulate cellular behavior and express specific hormone receptors. Whether SG cell growth is modulated by an autocrine epidermal growth factor (EGF) receptor-mediated signal transduction pathway is not clearly understood. SG tissue is the synthesis site for functionally distinct products including growth factors, digestive enzymes, and homeostasis maintaining factors. Historically, SG cells have proven difficult to grow and may be only maintained as limited three-dimensional ductal-type structures in collagen gels or on reconstituted basement membrane gels. A novel approach to establishing primary rat SG cultures is use of microgravity bioreactors originally designed by NASA as low-shear culture systems for predicting cell growth and differentiation in the microgravity environment of space. These completely fluid-filled bioreactors, which are oriented horizontally and rotate, have proven advantageous for Earth-based culture of three-dimensional cell assemblies, tissue-like aggregates, and glandular structures. Use of microgravity bioreactors for establishing in vitro models to investigate steroid-mediated secretion of EGF by normal SG cells may also prove useful for the investigation of cancer and other salivary gland disorders. These microgravity bioreactors promise challenging opportunities for future applications in basic and applied cell research.

NASA Program Space Biology↗

Tensegrity II. How structural networks influence cellular information processing networks

The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

Review↗

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic insights explain the transforming potential of the T507K substitution in the protein-tyrosine phosphatase SHP2

The protein-tyrosine phosphatase SHP2 is an allosteric enzyme critical for cellular events downstream of growth factor receptors. Mutations in the SHP2 gene have been linked to many different types of human diseases, including developmental disorders, leukemia, and solid tumors. Unlike most SHP2-activating mutations, the T507K substitution in SHP2 is unique in that it exhibits oncogenic Ras-like transforming activity. However, the biochemical basis of how the SHP2/T507K variant elicits transformation remains unclear. By combining kinetic and biophysical methods, X-ray crystallography, and molecular modeling, as well as using cell biology approaches, in this work we uncovered that the T507K substitution alters both SHP2 substrate specificity and its allosteric regulatory mechanism. We found that although SHP2/T507K exists in the closed, autoinhibited conformation similar to the WT enzyme, the interactions between its N-SH2 and protein-tyrosine phosphatase domains are weakened such that SHP2/T507K possesses a higher affinity for the scaffolding protein Grb2-associated binding protein 1 (Gab1). We also discovered that the T507K substitution alters the structure of the SHP2 active site, resulting in a change in SHP2 substrate preference for Sprouty1, a known negative regulator of Ras signaling and a potential tumor suppressor. Our results suggest that SHP2/T507K's shift in substrate specificity coupled with its preferential association of SHP2/T507K with Gab1 enable the mutant SHP2 to more efficiently dephosphorylate Sprouty1 at pTyr-53. This dephosphorylation hyperactivates Ras signaling, which is likely responsible for SHP2/T507K's Ras-like transforming activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

pattern recognition↗

Generative diffusion model surrogates for mechanistic agent-based biological models

Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution. The Cellular-Potts Model (CPM) is a powerful and popular framework for developing and interrogating these models. CPMs become computationally expensive at large space- and time- scales making application and investigation of developed models difficult. Surrogate models may allow for the accelerated evaluation of CPMs of complex biological systems. However, the stochastic nature of these models means each set of parameters may give rise to different model configurations, complicating surrogate model development. In this work, we leverage denoising diffusion probabilistic models (DDPMs) to train a generative AI surrogate of a CPM used to investigate in vitro vasculogenesis. We describe the use of an image classifier to learn the characteristics that define unique areas of a 2-dimensional parameter space. We then apply this classifier to aid in surrogate model selection and verification. Our CPM model surrogate generates model configurations 20,000 timesteps ahead of a reference configuration and demonstrates approximately a 22x reduction in computational time as compared to native code execution. Our work represents a step towards the implementation of DDPMs to develop digital twins of stochastic biological systems.

97 MATHEMATICS AND COMPUTING↗

The calculation of radial dose from heavy ions: predictions of biological action cross sections

The track structure model of heavy ion cross sections was developed by Katz and co-workers in the 1960s. In this model the action cross section is evaluated by mapping the dose-response of a detector to gamma rays (modeled from biological target theory) onto the radial dose distribution from delta rays about the path of the ion. This is taken to yield the radial distribution of probability for a "hit" (an interaction leading to an observable end-point). Radial integration of the probability yields the cross section. When different response from ions of different Z having the same stopping power is observed this model may be indicated. Since the 1960s there have been several developments in the computation of the radial dose distribution, in the measurement of these distributions, and in new radiobiological data against which to test the model. The earliest model, by Butts and Katz made use of simplified delta ray distribution functions, of simplified electron range-energy relations, and neglected angular distributions. Nevertheless it made possible the calculation of cross sections for the inactivation of enzymes and viruses, and allowed extension to tracks in nuclear emulsions and other detectors and to biological cells. It set the pattern for models of observable effects in the matter through which the ion passed. Here we outline subsequent calculations of radial dose which make use of improved knowledge of the electron emission spectrum, the electron range-energy relation, the angular distribution, and some considerations of molecular excitation, of particular interest both close to the path of the ion and the outer limits of electron penetration. These are applied to the modeling of action cross sections for the inactivation of several strains of E-coli and B. subtilis spores where extensive measurements in the "thin-down" region have been made with heavy ion beams. Such calculations serve to test the radial dose calculations at the outer limit of electron penetration. We lack data from which to test these calculations in regions close to the path of the ion aside from our earliest work on latent tracks in plastics, though it appears that the criterion then suggested for the threshold of track formation, of a minimal dose at a minimal distance (of about 20 angstroms, in plastics), remains valid.

NASA Discipline Radiation Health↗

Interactions involving the Rad51 paralogs Rad51C and XRCC3 in human cells

Homologous recombinational repair of DNA double-strand breaks and crosslinks in human cells is likely to require Rad51 and the five Rad51 paralogs (XRCC2, XRCC3, Rad51B/Rad51L1, Rad51C/Rad51L2 and Rad51D/Rad51L3), as has been shown in chicken and rodent cells. Previously, we reported on the interactions among these proteins using baculovirus and two- and three-hybrid yeast systems. To test for interactions involving XRCC3 and Rad51C, stable human cell lines have been isolated that express (His)6-tagged versions of XRCC3 or Rad51C. Ni2+-binding experiments demonstrate that XRCC3 and Rad51C interact in human cells. In addition, we find that Rad51C, but not XRCC3, interacts directly or indirectly with Rad51B, Rad51D and XRCC2. These results argue that there are at least two complexes of Rad51 paralogs in human cells (Rad51C-XRCC3 and Rad51B-Rad51C-Rad51D-XRCC2), both containing Rad51C. Moreover, Rad51 is not found in these complexes. X-ray treatment did not alter either the level of any Rad51 paralog or the observed interactions between paralogs. However, the endogenous level of Rad51C is moderately elevated in the XRCC3-overexpressing cell line, suggesting that dimerization between these proteins might help stabilize Rad51C.

Non-NASA Center↗

Kullback–Leibler Divergence of an Open-Queuing Network of a Cell-Signal-Transduction Cascade

Queuing networks (QNs) are essential models in operations research, with applications in cloud computing and healthcare systems. However, few studies have analyzed the cell’s biological signal transduction using QN theory. This study entailed the modeling of signal transduction as an open Jackson’s QN (JQN) to theoretically determine cell signal transduction, under the assumption that the signal mediator queues in the cytoplasm, and the mediator is exchanged from one signaling molecule to another through interactions between the signaling molecules. Each signaling molecule was regarded as a network node in the JQN. The JQN Kullback–Leibler divergence (KLD) was defined using the ratio of the queuing time (λ) to the exchange time (μ), λ/μ. The mitogen-activated protein kinase (MAPK) signal-cascade model was applied, and the KLD rate per signal-transduction-period was shown to be conserved when the KLD was maximized. Our experimental study on MAPK cascade supported this conclusion. This result is similar to the entropy-rate conservation of chemical kinetics and entropy coding reported in our previous studies. Thus, JQN can be used as a novel framework to analyze signal transduction.

97 MATHEMATICS AND COMPUTING↗

Pattern formation in a coupled membrane-bulk reaction-diffusion model for intracellular polarization and oscillations

Reaction-diffusion systems have been widely used to study spatio-temporal phenomena in cell biology, such as cell polarization. Coupled bulk-surface models naturally include compartmentalization of cytosolic and membrane-bound polarity molecules. Here we study the distribution of the polarity protein Cdc42 in a mass-conserved membrane-bulk model, and explore the effects of diffusion and spatial dimensionality on spatio-temporal pattern formation. We first analyze a one-dimensional (1-D) model for Cdc42 oscillations in fission yeast, consisting of two diffusion equations in the bulk domain coupled to nonlinear ODEs for binding kinetics at each end of the cell. In 1-D, our analysis reveals the existence of symmetric and asymmetric steady states, as well as anti-phase relaxation oscillations typical of slow-fast systems. We then extend our analysis to a two-dimensional (2-D) model with circular bulk geometry, for which species can either diffuse inside the cell or become bound to the membrane and undergo a nonlinear reaction-diffusion process. We also consider a nonlocal system of PDEs approximating the dynamics of the 2-D membrane-bulk model in the limit of fast bulk diffusion. In all three model variants we find that mass conservation selects perturbations of spatial modes that simply redistribute mass. In 1-D, only anti-phase oscillations between the two ends of the cell can occur, and in-phase oscillations are excluded. In higher dimensions, no radially symmetric oscillations are observed. Instead, the only instabilities are symmetry-breaking, either corresponding to stationary Turing instabilities, leading to the formation of stationary patterns, or to oscillatory Turing instabilities, leading to traveling and standing waves. Codimension-two Bogdanov—Takens bifurcations occur when the two distinct instabilities coincide, causing traveling waves to slow down and to eventually become stationary patterns. Our work clarifies the effect of geometry and dimensionality on behaviors observed in ma.ss-conserved cell polarity models.

97 MATHEMATICS AND COMPUTING↗