Signal integration and integral feedback control with biochemical reaction networks.

Biochemical reaction networks perform a variety of signal processing functions, one of which is computing the integrals of signal values. This is often used in integral feedback control, where it enables a system's output to respond to changing inputs, but to then return exactly back to some pre-determined setpoint value afterward. To gain a deeper understanding of how biochemical networks are able to both integrate signals and perform integral feedback control, we investigated these abilities for several simple reaction networks. We found imperfect overlap between these categories, with some networks able to perform both tasks, some able to perform integration but not integral feedback control, and some the other way around. Nevertheless, networks that could either integrate or perform integral feedback control shared key elements. In particular, they included a chemical species that was neutrally stable in the open loop system (no feedback), meaning that this species does not have a unique stable steady-state concentration. Neutral stability could arise from zeroth order decay reactions, binding to a partner that was produced at a constant rate (which occurs in antithetic control), or through a long chain of covalent cycles. Mathematically, it arose from rate equations for the reaction network that were underdetermined when evaluated at steady-state.

Design patterns of biological cells.

Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.

Design Patterns of Biological Cells.

Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology in order to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.

Landscape of MicroRNA Regulatory Network Architecture and Functional Rerouting in Cancer.

Somatic mutations are a major source of cancer development, and many driver mutations have been identified in protein coding regions. However, the function of mutations located in miRNA and their target binding sites throughout the human genome remains largely unknown. Here, we built detailed cancer-specific miRNA regulatory networks across 30 cancer types to systematically analyze the effect of mutations in miRNAs and their target sites in 3' untranslated region (3' UTR), coding sequence (CDS), and 5' UTR regions. A total of 3,518,261 mutations from 9,819 samples were mapped to miRNA-gene interactions (mGI). Mutations in miRNAs showed a mutually exclusive pattern with mutations in their target genes in almost all cancer types. A linear regression method identified 148 candidate driver mutations that can significantly perturb miRNA regulatory networks. Driver mutations in 3'UTRs played their roles by altering RNA binding energy and the expression of target genes. Finally, mutated driver gene targets in 3' UTRs were significantly downregulated in cancer and functioned as tumor suppressors during cancer progression, suggesting potential miRNA candidates with significant clinical implications. A user-friendly, open-access web portal (mGI-map) was developed to facilitate further use of this data resource. Together, these results will facilitate novel noncoding biomarker identification and therapeutic drug design targeting the miRNA regulatory networks. SIGNIFICANCE: A detailed miRNA-gene interaction map reveals extensive miRNA-mediated gene regulatory networks with mutation-induced perturbations across multiple cancers, serving as a resource for noncoding biomarker discovery and drug development.

BioSimulators: a central registry of simulation engines and services for recommending specific tools.

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations.

Nutri: A Behavioral Science-Based Clinical Decision Support for Chronic Disease Management.

Clinical decision support systems (CDSS) for the ongoing decision making required to support health behavior change for chronic disease management should incorporate behavioral science (e.g., a collaborative goal setting workflow) with more common CDSS components (i.e., an evidence-based knowledge base that processes patient data). Given known challenges with CDSS usability and adoption, engaging clinician end-users in designing new CDSS is vital. Therefore, we tested Nutri, a CDSS for collaborative diet goal setting, with 10 clinicians in a simulated primary care appointment with a patient actor. Simulation recordings, usability surveys, and debriefing interviews provided a multi-method view of clinicians' perceptions of Nutri's value and usability. 100% of participating clinicians achieved Nutri's main objective: selecting a high impact diet goal during a collaborative goal setting discussion with the patient; participants found Nutri usable, potentially timesaving, and increased their diet counseling self-efficacy. Insights will improve Nutri's usability and clinical workflow integration.

Dynamics and Sensitivity of Signaling Pathways.

Purpose of Review: Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently associated with cancer and can result in cells acquiring an ability to divide and grow uncontrollably. Because signaling pathways play such a significant role in cancer initiation and advancement, their constituent proteins are attractive therapeutic targets. In this review, we discuss how signaling pathway modeling can assist with identifying effective drugs for treating diseases, such as cancer. An achievement that would facilitate the use of such models is their ability to identify controlling biochemical parameters in signaling pathways, such as molecular abundances and chemical reaction rates, because this would help determine effective points of attack by therapeutics. Recent Findings: We summarize the current state of understanding the sensitivity of phosphorylation cycles with and without sequestration. We also describe some basic properties of regulatory motifs including feedback and feedforward regulation. Summary: Although much recent work has focused on understanding the dynamics and particularly the sensitivity of signaling networks in eukaryotic systems, there is still an urgent need to build more scalable models of signaling networks that can appropriately represent their complexity across different cell types and tumors.

Python interfaces for the Smoldyn simulator.

MOTIVATION: Smoldyn is a particle-based biochemical simulator that is frequently used for systems biology and biophysics research. Previously, users could only define models using text-based input or a C/C++ application programming interface (API), which were convenient, but limited extensibility. RESULTS: We added a Python API to Smoldyn to improve integration with other software tools, such as Jupyter notebooks, other Python code libraries and other simulators. It includes low-level functions that closely mimic the existing C/C++ API and higher-level functions that are more convenient to use. These latter functions follow modern object-oriented Python conventions. AVAILABILITY AND IMPLEMENTATION: Smoldyn is open source and free, available at http://www.smoldyn.org and can be installed with the Python package manager pip. It runs on Mac, Windows and Linux.Documentation is available at http://www.smoldyn.org/SmoldynManual.pdf and https://smoldyn.readthedocs.io/en/latest/python/api.html.

Developing a real-time EHR-integrated SDoH clinical tool.

We describe an implementation of a pilot integration to embed SDoH-based data visualizations into the EHR in real time for clinical staff treating children with asthma.

Using Blockchain Technology to Mitigate Challenges in Service Access for the Homeless and Data Exchange Between Providers: Qualitative Study.

BACKGROUND: In the homeless population, barriers to housing and supportive services include a lack of control or access to data. Disparate data formats and storage across multiple organizations hinder up-to-date intersystem access to records and a unified view of an individual's health and documentation history. The utility of blockchain to solve interoperability in health care is supported in recent literature, but the technology has yet to be tested in real-life conditions encompassing the complex regulatory standards in the health sector. OBJECTIVE: This study aimed to test the feasibility and performance of a blockchain system in a homeless community to securely store and share data across a system of providers in the health care ecosystem. METHODS: We performed a series of platform demonstrations and open-ended qualitative feedback interviews to determine the key needs and barriers to user and stakeholder adoption. Account creation and data transactions promoting organizational efficiency and improved health outcomes in this population were tested with homeless users and service providers. RESULTS: Persons experiencing homelessness and care organizations could successfully create accounts, grant and revoke data sharing permissions, and transmit documents across a distributed network of providers. However, there were issues regarding the security of shared data, user experience and adoption, and organizational preparedness for service providers as end users. We tested a set of assumptions related to these problems within the project time frame and contractual obligations with an existing blockchain-based platform. CONCLUSIONS: Blockchain technology provides decentralized data sharing, validation, immutability, traceability, and integration. These core features enable a secure system for the management and distribution of sensitive information. This study presents a concrete evaluation of the effectiveness of blockchain through an existing platform while revealing limitations from the perspectives of user adoption, cost-effectiveness, scalability, and regulatory frameworks.

Effects of surfaces and macromolecular crowding on bimolecular reaction rates.

Biological cells are complex environments that are densely packed with macromolecules and subdivided by membranes, both of which affect the rates of chemical reactions. It is well known that crowding reduces the volume available to reactants, which increases reaction rates, and also inhibits reactant diffusion, which decreases reaction rates. This work investigates these effects quantitatively using analytical theory and particle-based simulations. A reaction rate equation based on only these two processes turned out to be inconsistent with simulation results. However, accounting for diffusion inhibition by the surfaces of nearby obstacles, which affects access to reactants, it led to perfect agreement for reactions near impermeable planar membranes and improved agreement for reactions in crowded spaces. A separate model that quantified reactant occlusion by crowders, and extensions to a thermodynamic 'cavity' model proposed by Berezhkovskii and Szabo [25], were comparably successful. These results help elucidate reaction dynamics in confined spaces and improve prediction of in vivo reaction rates from in vitro ones.

Rule-Based Modeling Using Wildcards in the Smoldyn Simulator.

Many biological molecules exist in multiple variants, such as proteins with different posttranslational modifications, DNAs with different sequences, and phospholipids with different chain lengths. Representing these variants as distinct species, as most biochemical simulators do, leads to the problem that the number of species, and chemical reactions that interconvert them, typically increase combinatorially with the number of ways that the molecules can vary. This can be alleviated by "rule-based modeling methods," in which software generates the chemical reaction network from relatively simple "rules." This chapter presents a new approach to rule-based modeling. It is based on wildcards that match to species names, much as wildcards can match to file names in computer operating systems. It is much simpler to use than the formal rule-based modeling approaches developed previously but can lead to unintended consequences if not used carefully. This chapter demonstrates rule-based modeling with wildcards through examples for signaling systems, protein complexation, polymerization, nucleic acid sequence copying and mutation, the "SMILES" chemical notation, and others. The method is implemented in Smoldyn, a spatial and stochastic biochemical simulator, for both generate-first and on-the-fly expansion, meaning whether the reaction network is generated before or during the simulation.

Transferring information without distortion.

Despite employing diverse molecular mechanisms, many different cell signaling systems avoid losing information by transmitting it in a linear manner.

Smoldyn: particle-based simulation with rule-based modeling, improved molecular interaction and a library interface.

Motivation: Smoldyn is a spatial and stochastic biochemical simulator. It treats each molecule of interest as an individual particle in continuous space, simulating molecular diffusion, molecule-membrane interactions and chemical reactions, all with good accuracy. This article presents several new features. Results: Smoldyn now supports two types of rule-based modeling. These are a wildcard method, which is very convenient, and the BioNetGen package with extensions for spatial simulation, which is better for complicated models. Smoldyn also includes new algorithms for simulating the diffusion of surface-bound molecules and molecules with excluded volume. Both are exact in the limit of short time steps and reasonably good with longer steps. In addition, Smoldyn supports single-molecule tracking simulations. Finally, the Smoldyn source code can be accessed through a C/C ++ language library interface. Availability and Implementation: Smoldyn software, documentation, code, and examples are at http://www.smoldyn.org . Contact: steven.s.andrews@gmail.com.

Push-Pull and Feedback Mechanisms Can Align Signaling System Outputs with Inputs.

Many cell signaling systems, including the yeast pheromone response system, exhibit "dose-response alignment" (DoRA), in which output of one or more downstream steps closely matches the fraction of occupied receptors. DoRA can improve the fidelity of transmitted dose information. Here, we searched systematically for biochemical network topologies that produced DoRA. Most networks, including many containing feedback and feedforward loops, could not produce DoRA. However, networks including "push-pull" mechanisms, in which the active form of a signaling species stimulates downstream activity and the nominally inactive form reduces downstream activity, enabled perfect DoRA. Networks containing feedbacks enabled DoRA, but only if they also compared feedback to input and adjusted output to match. Our results establish push-pull as a non-feedback mechanism to align output with variable input and maximize information transfer in signaling systems. They also suggest genetic approaches to determine whether particular signaling systems use feedback or push-pull control.

Selective inhibition of tropomyosin-receptor-kinase A (TrkA) reduces pain and joint damage in two rat models of inflammatory arthritis.

BACKGROUND: Inflammation is an essential component of arthritis pain. Nerve growth factor (NGF) plays a key role in acute and chronic pain states especially those associated with inflammation. NGF acts through tropomyosin-receptor-kinase A (TrkA). NGF blockade has reduced arthritis pain in clinical trials. We explored the mechanisms within the joint which may contribute to the analgesic effects of NGF by selectively inhibiting TrkA in carrageenan-induced or collagen-induced joint pain behaviour. The goal of the current study was to elucidate whether inflammation is central to the efficacy for NGF blockade. METHODS: Rats were injected in their left knees with 2 % carrageenan or saline. Collagen-induced arthritis (CIA) was induced by intradermal injections of a mixture of bovine type II collagen (0.2 mg) and incomplete Freund's adjuvant (0.2 mg). Oral doses (30 mg/kg) of AR786 or vehicle control were given twice daily after arthritis induction. Ibuprofen-treated (35 mg/kg, orally, once daily) rats with CIA were used as positive analgesic controls. Pain behaviour was measured as hind-limb weight-bearing asymmetry and hind-paw withdrawal thresholds to von Frey hair stimulation (carrageenan synovitis), or withdrawal to joint compression using a Randall Selitto device (CIA). Inflammation was measured as increased knee joint diameter and by histopathological analysis. RESULTS: Intra-articular injections of carrageenan or induction of CIA was each associated with pain behaviour and synovial inflammation. Systemic administration of the TrkA inhibitor AR786 reduced carrageenan-induced or CIA-induced pain behaviour to control values, and inhibited joint swelling and histological evidence of synovial inflammation and joint damage. CONCLUSIONS: By using two models of varying inflammation we demonstrate for the first time that selective inhibition of TrkA may reduce carrageenan-induced or CIA-induced pain behaviour in rats, in part through potentially inhibiting synovial inflammation, although direct effects on sensory nerves are also likely. Our observations suggest that inflammatory arthritis causes pain and the presence of inflammation is fundamental to the beneficial effects (reduction in pain and pathology) of NGF blockade. Further research should determine whether TrkA inhibition may ameliorate human inflammatory arthritis.

Crosstalk between the lipopolysaccharide and phospholipid pathways during outer membrane biogenesis in Escherichia coli.

The outer membrane of gram-negative bacteria is composed of phospholipids in the inner leaflet and lipopolysaccharides (LPS) in the outer leaflet. LPS is an endotoxin that elicits a strong immune response from humans, and its biosynthesis is in part regulated via degradation of LpxC (EC 3.5.1.108) and WaaA (EC 2.4.99.12/13) enzymes by the protease FtsH (EC 3.4.24.-). Because the synthetic pathways for both molecules are complex, in addition to being produced in strict ratios, we developed a computational model to interrogate the regulatory mechanisms involved. Our model findings indicate that the catalytic activity of LpxK (EC 2.7.1.130) appears to be dependent on the concentration of unsaturated fatty acids. This is biologically important because it assists in maintaining LPS/phospholipids homeostasis. Further crosstalk between the phospholipid and LPS biosynthetic pathways was revealed by experimental observations that LpxC is additionally regulated by an unidentified protease whose activity is independent of lipid A disaccharide concentration (the feedback source for FtsH-mediated LpxC regulation) but could be induced in vitro by palmitic acid. Further experimental analysis provided evidence on the rationale for WaaA regulation. Overexpression of waaA resulted in increased levels of 3-deoxy-d-manno-oct-2-ulosonic acid (Kdo) sugar in membrane extracts, whereas Kdo and heptose levels were not elevated in LPS. This implies that uncontrolled production of WaaA does not increase the LPS production rate but rather reglycosylates lipid A precursors. Overall, the findings of this work provide previously unidentified insights into the complex biogenesis of the Escherichia coli outer membrane.

A Method and On-Line Tool for Maximum Likelihood Calibration of Immunoblots and Other Measurements That Are Quantified in Batches.

Experimental measurements require calibration to transform measured signals into physically meaningful values. The conventional approach has two steps: the experimenter deduces a conversion function using measurements on standards and then calibrates (or normalizes) measurements on unknown samples with this function. The deduction of the conversion function from only the standard measurements causes the results to be quite sensitive to experimental noise. It also implies that any data collected without reliable standards must be discarded. Here we show that a "1-step calibration method" reduces these problems for the common situation in which samples are measured in batches, where a batch could be an immunoblot (Western blot), an enzyme-linked immunosorbent assay (ELISA), a sequence of spectra, or a microarray, provided that some sample measurements are replicated across multiple batches. The 1-step method computes all calibration results iteratively from all measurements. It returns the most probable values for the sample compositions under the assumptions of a statistical model, making them the maximum likelihood predictors. It is less sensitive to measurement error on standards and enables use of some batches that do not include standards. In direct comparison of both real and simulated immunoblot data, the 1-step method consistently exhibited smaller errors than the conventional "2-step" method. These results suggest that the 1-step method is likely to be most useful for cases where experimenters want to analyze existing data that are missing some standard measurements and where experimenters want to extract the best results possible from their data. Open source software for both methods is available for download or on-line use.

High Molybdenum availability for evolution in a Mesoproterozoic lacustrine environment.

Trace metal data for Proterozoic marine euxinic sediments imply that the expansion of nitrogen-fixing cyanobacteria and diversification of eukaryotes were delayed while the availability of bioessential metals such as molybdenum in the ocean was limited. However, there is increasing recognition that the Mesoproterozoic evolution of nitrogen fixation and eukaryotic life may have been promoted in marginal marine and terrestrial environments, including lakes, rather than in the deep ocean. Molybdenum availability is critical to life in lakes, just as it is in the oceans. It is, therefore, important to assess molybdenum availability to the lacustrine environment in the Mesoproterozoic. Here we show that the flux of molybdenum to a Mesoproterozoic lake was 1 to 2 orders of magnitude greater than typical fluxes in the modern and ancient marine environment. Thus, there was no barrier to availability to prevent evolution in the terrestrial environment, in contrast to the nutrient-limited Mesoproterozoic oceans.

Development of an Experimental Animal Model for Lower Back Pain by Percutaneous Injury-Induced Lumbar Facet Joint Osteoarthritis.

We report generation and characterization of pain-related behavior in a minimally invasive facet joint degeneration (FJD) animal model in rats. FJD was produced by a non-open percutaneous puncture-induced injury on the right lumbar FJs at three consecutive levels. Pressure hyperalgesia in the lower back was assessed by measuring the vocalization response to pressure from a force transducer. After hyperalgesia was established, pathological changes in lumbar FJs and alterations of intervertebral foramen size were assessed by histological and imaging analyses. To investigate treatment options for lumber FJ osteoarthritis-induced pain, animals with established hyperalgesia were administered with analgesic drugs, such as morphine, a selective COX-2 inhibitor, a non-steroidal anti-inflammatory drug (NSAID) (ketorolac), or pregabalin. Effects were assessed by behavioral pain responses. One week after percutaneous puncture-induced injury of the lumbar FJs, ipsilateral primary pressure hyperalgesia developed and was maintained for at least 12 weeks without foraminal stenosis. Animals showed decreased spontaneous activity, but no secondary hyperalgesia in the hind paws. Histopathological and microfocus X-ray computed tomography analyses demonstrated that the percutaneous puncture injury resulted in osteoarthritis-like structural changes in the FJs cartilage and subchondral bone. Pressure hyperalgesia was completely reversed by morphine. The administration of celecoxib produced moderate pain reduction with no statistical significance while the administration of ketorolac and pregabalin produced no analgesic effect on FJ osteoarthritis-induced back pain. Our animal model of non-open percutanous puncture-induced injury of the lumbar FJs in rats shows similar characteristics of low back pain produced by human facet arthropathy.