Important Biological System Research Articles

Exploring Protein Conformational Changes Using a Large-Scale Biophysical Sampling Augmented Deep Learning Strategy.

Inspired by the success of deep learning in predicting static protein structures, researchers are now actively exploring other deep learning algorithms aimed at predicting the conformational changes of proteins. Currently, a major challenge in the development of such models lies in the limited training data characterizing different conformational transitions. To address this issue, molecular dynamics simulations is combined with enhanced sampling methods to create a large-scale database. To this end, the study simulates the conformational changes of 2635 proteins featuring two known stable states, and collects the structural information along each transition pathway. Utilizing this database, a general deep learning model capable of predicting the transition pathway for a given protein is developed. The model exhibits general robustness across proteins with varying sequence lengths (ranging from 44 to 704 amino acids) and accommodates different types of conformational changes. Great agreement is shown between predictions and experimental data in several systems and successfully apply this model to identify a novel allosteric regulation in an important biological system, the human β-cardiac myosin. These results demonstrate the effectiveness of the model in revealing the nature of protein conformational changes.

Mathematical Model for Chemical Reactions in Electrolytes Applied to Cytochrome c Oxidase: An Electro-Osmotic Approach

This study introduces a mathematical model for electrolytic chemical reactions, employing an energy variation approach grounded in classical thermodynamics. Our model combines electrostatics and chemical reactions within well-defined energetic and dissipative functionals. Extending the energy variation method to open systems consisting of charge, mass, and energy inputs, this model explores energy transformation from one form to another. Electronic devices and biological channels and transporters are open systems. By applying this generalized approach, we investigate the conversion of an electrical current to a proton flow by cytochrome c oxidase, a vital mitochondrial enzyme contributing to ATP production, the ‘energetic currency of life’. This model shows how the enzyme’s structure directs currents and mass flows governed by energetic and dissipative functionals. The interplay between electron and proton flows, guided by Kirchhoff’s current law within the mitochondrial membrane and the mitochondria itself, determines the function of the systems, where electron flows are converted into proton flows and gradients. This important biological system serves as a practical example of the use of energy variation methods to deal with electrochemical reactions in open systems. We combine chemical reactions and Kirchhoff’s law in a model that is much simpler to implement than a full accounting of all the charges in a chemical system.

Superparamagnetic behavior of non-interacting antiferromagnetic ferritin nanoparticles

Ferritin is an important biological system and found in blood of living organisms. Inorganic cores of this material are 8 nm in size. The cores are surrounded by protein shells which reduce interparticle interaction. Particle size distribution present in ferritin is determined from transmission electron micrograph. This distribution can be described by a log normal distribution function. The magnetic field (0–70 kG) dependence of the magnetization at different temperatures are analyzed considering the estimated particle size distribution. The resulting mean particle magnetic moment is temperature independent and equal to 310 μB. Saturation magnetization and antiferromagnetic susceptibility of ferritin decrease with increasing temperature.

Recombinant Insulin-Like Growth Factor 1 Dimers: Receptor Binding Affinities and Activation Abilities

Insulin-like growth factor 1 (IGF-1) and its IGF-1 receptor (IGF-1R) belong to an important biological system that is involved in the regulation of normal growth, but that has also been recognized as playing a role in cancer. IGF-1R antagonists could be interesting for the testing of their potential antiproliferative properties as an alternative to IGF-1R tyrosine-kinase inhibitors or anti-IGF-1R monoclonal antibodies. In this study, we were inspired by the successful development of insulin dimers capable of antagonizing insulin effects on the insulin receptor (IR) by simultaneous binding to two separated binding sites and by blocking structural rearrangement of the IR. We designed and produced in Escherichia coli three different IGF-1 dimers in which IGF-1 monomers are interlinked through their N- and C-termini, with linkers having 8, 15 or 25 amino acids. We found that the recombinant products were susceptible to the formation of misfolded or reduced variants, but that some of them were able to bind IGF-1R in low nanomolar affinities and all of them activate IGF-1R proportionally to their binding affinities. Overall, our work can be considered as a pilot study that, although it did not lead to the discovery of new IGF-1R antagonists, explored the possibility of recombinant production of IGF-1 dimers and led to the preparation of active compounds. This work could inspire further studies dealing, for example, with the preparation of IGF-1 conjugates with specific proteins for the study of the hormone and its receptor or for therapeutic applications.Graphical

Retinoic acid regulates the ubiquitin–proteasome system in a middle cerebral artery occlusion animal model

BackgroundRetinoic acid is a major metabolite of vitamin A and exerts beneficial effects including anti-oxidant and anti-inflammatory activities in neurons. The ubiquitin–proteasome system is an important biological system that regulates cell survival. Ubiquitination regulates protein degradation and plays an important role in oxidative stress. Deubiquitinating enzymes cleave ubiquitin from proteins and control ubiquitination-induced degradation. We detected decreases in ubiquitin carboxy-terminal hydrolase L1, ubiquitin thioesterase OTUB1, and proteasome subunit alpha types 1 and 3 in cerebral ischemic damage. In this study, we investigated whether retinoic acid regulates the expression of deubiquitinating enzymes ubiquitin carboxy-terminal hydrolase L1, ubiquitin thioesterase OTUB1, and proteasome subunit alpha types 1 and 3 in cerebral ischemic injury. Right middle cerebral artery occlusion (MCAO) was performed to induce cerebral ischemic damage in male rats. Retinoic acid (5 mg/kg) or vehicle was intraperitoneally injected every day from 4 days before surgery. Neurological behavioral tests were performed 24 h after MCAO, and right cerebral cortical tissues were collected.ResultsMCAO damage caused neurological behavioral dysfunction, and retinoic acid alleviated these deficits. The identified proteins decreased in MCAO animals with vehicle, while retinoic acid treatment attenuated these decreases. The results of proteomic study were confirmed by a reverse transcription-PCR technique. Expressions of ubiquitin carboxy-terminal hydrolase L1, ubiquitin thioesterase OTUB1, and proteasome subunit alpha types 1 and 3 were decreased in MCAO animals treated with vehicle. Retinoic acid treatment alleviated these MCAO-induced reductions. The ubiquitin–proteasome system plays an essential role in maintaining cell function and preserving cell shape against ischemic damage.ConclusionsThese findings suggest that retinoic acid regulates ubiquitin- and proteasome-related proteins including ubiquitin carboxy-terminal hydrolase L1, ubiquitin thioesterase OTUB1, and proteasome subunit alpha types 1 and 3 in a brain ischemia model. Changes in these proteins are involved in the neuroprotective effects of retinoic acid.

A mathematical model for cell cycle control: graded response or quantized response

ABSTRACT Cell cycle is an important and complex biological system. A lot of efforts have been put in understanding cell cycle arrest for its vital role in clinical therapies. The cell-cycle-arrest outcomes upon stimulation are complicated. The response could be stringent or relaxed, and graded or quantized. A model fully addressing various cell-cycle-arrest outcomes is to be developed. Here, we developed a mathematical model of cell cycle control incorporating distinct characteristics of various cell-cycle-arrest outcomes. The model can simulate two typical properties of cell cycle arrest, quantized and graded. We also characterized the inheritable quiescence and refractory state, which were crucial in long-term response of the population. Then, we monitored cells respond to multiple stimulations, and the results indicated that cells responded to stimulations with small interval did not induce significantly sustained cell cycle arrest as the existence of refractory state. Our work will benefit fundamental research and make efforts to predicting outcomes of clinical therapeutics.

Mind thenumt: Finding informative mitochondrial markers in a giant grasshopper genome

The barcoding of the mitochondrial COX1 gene has been instrumental in cataloguing the tree of life, and in providing insights in the phylogeographic history of species. Yet, this strategy has encountered difficulties in major clades characterized by large genomes, which contain a high frequency of nuclear pseudogenes originating from the mitochondrial genome (numts). Here, we use the meadow grasshopper (Chorthippus parallelus), which possesses a giant genome of ~13 Gb, to identify mitochondrial genes that are underrepresented as numts, and test their use as informative phylogeographic markers. We recover the same full mitochondrial sequence using both whole genome and transcriptome sequencing, including functional protein-coding genes and tRNAs. We show that a region of the mitogenome containing the COX1 gene, typically used in DNA barcoding, has disproportionally higher diversity and coverage than the rest of the mitogenome, consistent with multiple insertions of that region into the nuclear genome. By designing new markers in regions of less elevated diversity and coverage, we identify two mitochondrial genes that are less likely to be duplicated as numts. We show that, while these markers show high levels of incomplete lineage sorting between subspecies, as expected for mitochondrial genes, genetic variation reflects their phylogeographic history accurately. These findings allow us to identify useful mitochondrial markers for future studies in C. parallelus, an important biological system for evolutionary biology. More generally, this study exemplifies how non-PCR-based methods using next-generation sequencing can be used to avoid numts in species characterized by large genomes, which have remained challenging to study in taxonomy and evolution.

Computational aspects towards understanding the photoprocesses in eumelanin

AbstractEumelanin is the active ingredient in skin pigment found in human beings. It is also present in animals, plants, and some bacteria and fungi. However, there are still open questions about its biological activity. The detailed molecular mechanism of its photoprotective property is topic of intense research. While it has been implicated in photo‐damage in certain conditions, the extent of this effect is largely unknown. Furthermore, its involvement in a wide range of metal chelation and radical scavenging properties remain unclear. This rather sparse knowledge about such as important biological system is mainly due to the extreme level of heterogeneity in eumelanin structure, its low solubility, and lack of unique structural features. Due to these difficulties theoretical studies and modeling appear to be a crucial cornerstone towards the understanding of eumelanin system. This review aims to report the current status of the understanding in molecular mechanism of photoprocesses in eumelanin and the theoretical approaches that are used for that. Furthermore, the outstanding open questions and difficulties in understanding the eumelanin system will be dealt with.This article is categorized under: Software > Quantum Chemistry Structure and Mechanism > Computational Biochemistry and Biophysics Structure and Mechanism > Molecular Structures

Self-powered artificial auditory pathway for intelligent neuromorphic computing and sound detection

Human auditory system is one of the most efficient and important biological system for human beings. To reproduce this system with electronic devices would profoundly advance artificial nervous system. However, emulating this system requires a complex architecture to mimic the biological auditory system functions such as listening, analyzing, and integrating instructions, which is still not available. Here, we report a triboelectric nanogenerator (TENG) actuated self-powered artificial auditory pathway to emulate the biological auditory functionalities, demonstrating its application in the intelligent neuromorphic computing and sound detection. The self-powered artificial auditory pathway consists of a femtosecond laser (fs) processed TENG and a field effect synaptic transistor (FEST) which functions as acoustic receptor and acoustic synapse, respectively. Moreover, the fs laser-induced auditory TENG exhibits broader frequency response with high sensitivity (129 mV/dB), and excellent empathy social behavior, and various typical synaptic functions can be well mimicked through TENG actuated FEST. Meanwhile, a self-adaptation artificial neuromorphic circuit with noise-adjustable behavior is demonstrated, which substantially improves the efficiency and accuracy of the instruction recognition process for more human-computer interaction system. This work provides an effective way to well mimic the biological auditory functions, which paves a new way to achieve the instruction recognition in a noise-intensity range ambient, and would profoundly decrease the power-consumption in the field of future neuromorphic systems. • The TENG actuated bioinspired artificial auditory pathway is reported firstly. • Fs-laser induced TENG receptor can effectively improve the quality of acoustic data with a high-sensitivity of 129 mV/dB. • Several intelligent functions such as neuromorphic computing and sound azimuth detection can be achieved. • Noise-adjustable behavior can be well mimicked through a neuromorphic circuit.

The inflammasome adapter ASC assembles into filaments with integral participation of its two Death Domains, PYD and CARD

The inflammasome is a multiprotein complex necessary for the onset of inflammation. The adapter protein ASC assembles inflammasome components by acting as a molecular glue between danger-signal sensors and procaspase-1. The assembly is mediated by ASC self-association and protein interactions via its two Death Domains, PYD and CARD. Truncated versions of ASC have been shown to form filaments, but information on the filaments formed by full-length ASC is needed to construct a meaningful model of inflammasome assembly. To gain insights into this system, we used a combination of transmission EM, NMR, and computational analysis to investigate intact ASC structures. We show that ASC forms ∼6-7-nm-wide filaments that stack laterally to form bundles. The structural characteristics and dimensions of the bundles indicate that both PYD and CARD are integral parts of the filament. A truncated version of ASC with only the CARD domain (ASCCARD) forms different filaments (∼3-4-nm width), providing further evidence that both domains work in concert in filament assembly. Ring-shaped protein particles bound to pre-existing filaments match the size of ASC dimer structures generated by NMR-based protein docking, suggesting that the ASC dimer could be a basic building block for filament formation. Solution NMR binding studies identified the protein surfaces involved in the ASCCARD-ASCCARD interaction. These data provide new insights into the structural underpinnings of the inflammasome and should inform future efforts to interrogate this important biological system.

Food and the gut: relevance to some of the autisms.

Complex, diverse and rarely appearing without comorbidity, the autism spectrum disorders continue to be a source of research interest. With core symptoms variably impacting on social communication skills, the traditional focus of many research efforts has centred on the brain and how genetic and environmental processes impact on brain structure, function and/or connectivity to account for various behavioural presentations. Alongside emerging ideas on autistic traits being present in various clinical states, the autisms, and the overrepresentation of several comorbid conditions impacting on quality of life, other research avenues have opened up. The central role of the brain in relation to autism may be at least partially influenced by the functions of other organs. The gastrointestinal (GI) tract represents an important biological system pertinent to at least some autism. The notion of a gut-brain-behaviour axis has garnered support from various findings: an overrepresentation of functional and pathological bowel states, bowel and behavioural findings showing bidirectional associations, a possible relationship between diet, GI function and autism and recently, greater focus on aspects of the GI tract such as the collected gut microbiota in relation to autism. Gaps remain in our knowledge of the functions of the GI tract linked to autism, specifically regarding mechanisms of action onward to behavioural presentation. Set however within the context of diversity in the presentation of autism, science appears to be moving towards defining important GI-related autism phenotypes with the possibility of promising dietary and other related intervention options onward to improving quality of life.

Construction of an integrated gene regulatory network link to stress-related immune system in cattle.

The immune system is an important biological system that is negatively impacted by stress. This study constructed an integrated regulatory network to enhance our understanding of the regulatory gene network used in the stress-related immune system. Module inference was used to construct modules of co-expressed genes with bovine leukocyte RNA-Seq data. Transcription factors (TFs) were then assigned to these modules using Lemon-Tree algorithms. In addition, the TFs assigned to each module were confirmed using the promoter analysis and protein-protein interactions data. Therefore, our integrated method identified three TFs which include one TF that is previously known to be involved in immune response (MYBL2) and two TFs (E2F8 and FOXS1) that had not been recognized previously and were identified for the first time in this study as novel regulatory candidates in immune response. This study provides valuable insights on the regulatory programs of genes involved in the stress-related immune system.

Fundamental principles of vascular network topology.

The vascular system is arguably the most important biological system in many organisms. Although the general principles of its architecture are simple, the growth of blood vessels occurs under extreme physical conditions. Optimization is an important aspect of the development of computational models of the vascular branching structures. This review surveys the approaches used to optimize the topology and estimate different geometrical parameters of the vascular system. The review is focused on optimizations using complex cost functions based on the minimum total energy principle and the relationship between the laws of growth and precise vascular network topology. Experimental studies of vascular networks in different species are also discussed.

Actomyosin stress fiber mechanosensing in 2D and 3D.

Mechanotransduction is the process through which cells survey the mechanical properties of their environment, convert these mechanical inputs into biochemical signals, and modulate their phenotype in response. These mechanical inputs, which may be encoded in the form of extracellular matrix stiffness, dimensionality, and adhesion, all strongly influence cell morphology, migration, and fate decisions. One mechanism through which cells on planar or pseudo-planar matrices exert tensile forces and interrogate microenvironmental mechanics is through stress fibers, which are bundles composed of actin filaments and, in most cases, non-muscle myosin II filaments. Stress fibers form a continuous structural network that is mechanically coupled to the extracellular matrix through focal adhesions. Furthermore, myosin-driven contractility plays a central role in the ability of stress fibers to sense matrix mechanics and generate tension. Here, we review the distinct roles that non-muscle myosin II plays in driving mechanosensing and focus specifically on motility. In a closely related discussion, we also describe stress fiber classification schemes and the differing roles of various myosin isoforms in each category. Finally, we briefly highlight recent studies exploring mechanosensing in three-dimensional environments, in which matrix content, structure, and mechanics are often tightly interrelated. Stress fibers and the myosin motors therein represent an intriguing and functionally important biological system in which mechanics, biochemistry, and architecture all converge.

The effect of using the plant functional type paradigm on a data-constrained global phenology model

Abstract. Leaf seasonality impacts a variety of important biological, chemical, and physical Earth system processes, which makes it essential to represent leaf phenology in ecosystem and climate models. However, we are still lacking a general, robust parametrisation of phenology at global scales. In this study, we use a simple process-based model, which describes phenology as a strategy for carbon optimality, to test the effects of the common simplification in global modelling studies that plant species within the same plant functional type (PFT) have the same parameter values, implying they are assumed to have the same species traits. In a previous study this model was shown to predict spatial and temporal dynamics of leaf area index (LAI) well across the entire global land surface provided local grid cell parameters were used, and is able to explain 96 % of the spatial variation in average LAI and 87 % of the variation in amplitude. In contrast, we find here that a PFT level parametrisation is unable to capture the spatial variability in seasonal cycles, explaining on average only 28 % of the spatial variation in mean leaf area index and 12 % of the variation in seasonal amplitude. However, we also show that allowing only two parameters, light compensation point and leaf age, to be spatially variable dramatically improves the model predictions, increasing the model's capability of explaining spatial variations in leaf seasonality to 70 and 57 % of the variation in LAI average and amplitude, respectively. This highlights the importance of identifying the spatial scale of variation of plant traits and the necessity to critically analyse the use of the plant functional type assumption in Earth system models.

Prefractionation methods for individual adult fruit fly hemolymph proteomic analysis.

The analysis of blood provides in depth chemical information of physiological states of organisms. Hemolymph (blood) is the fluid in the open circulatory system of Drosophila melanogaster that is the medium for molecules regulating a wide variety of physiological activities and signaling between tissues. Adult Drosophila is typically less than 3mm in length and, as a consequence, the available volume of hemolymph is usually less than 50 nL from individual flies. Proteomic analysis of volume-limited hemolymph is a great challenge for both sample handling and subsequent mass spectrometry characterization of this chemically diverse biological fluid with a wide dynamic range of proteins in concentrations. Less abundant proteins, in particular, could be easily lost during sample preparation or missed by current mass spectrometry methods. This article describes simple and customized RPLC column and IEX columns to prefractionate volume-limited hemolymph without excessive dilution. Step-gradient elution methods were developed and optimized to enhance the identification of novel proteins from an individual fruit fly hemolymph sample. Fractions from each step gradient was analyzed by an Agilent nano-RPLC chip column and then characterized by high mass resolution and high mass accuracy orbitrap mass spectrometry. As a result, both RPLC (11 proteins) and IEX fractionation approaches (9 proteins) identified more proteins than an unfractionated control approach with higher protein scores, emPAI values and coverage. Furthermore, a significant number of novel proteins were revealed by both RPLC and IEX fractionation methods, which were missed by unfractionated controls. The demonstration of this method establishes a means to deepen proteomic analysis to this commonly used, important biological model system.

Study of plasma coagulation induced by contact with calcium chloride solution.

Blood coagulation capability is one of the most important factors for the diagnosis of patients with thrombosis. Regarding the blood coagulation as an example of gelation of soft matter, we can apply an analytical method to this phenomenon and pick up some relevant parameters. In various systems, gelation dynamics induced by contact between a polymer solution and a crosslinker solution are well explained by the "moving boundary picture" (Yamamoto et al., J. Phys. Chem. B, 2010, 114, 10002-10009). The aim of this paper is to clarify whether this picture can be applied to a clinically important biological system used for blood coagulation tests. We have measured the time course of the thickness of a plasma gel layer formed when plasma comes in contact with calcium chloride solution in a rectangular cell and analyzed theoretically on the basis of the moving boundary picture. The entire process was well expressed using a scaled equation involving three parameters characterizing the plasma, k, Kin, and β, where k is the time required to reach the incipient stage of three-dimensional network formation, the parameter Kin is proportional to calcium chloride concentration and β is a constant. These results indicate the direct applicability of the general theory of gelation dynamics induced by contact between two solutions to the in vitro coagulation (gelation) of plasma, and the fitting parameters may be used for diagnosis.

Obesity: Liraglutide--another weapon in the war against obesity?

Liraglutide is an agonist of glucagon-like receptor-1, which is a component of an important biological system that inhibits food intake and enhances insulin secretion from the pancreas in the presence of glucose. This drug can therefore facilitate weight loss and glucose control at the same time.

The B Cell Receptor Dictates its Local Lipid Environment

The B cell receptor (BCR) is responsible for sensing and responding to intact antigen during the immune response and is hypothesized to nucleate a unique composition of lipids surrounding receptor clusters during antigen binding and signaling. This unique lipid composition, sometimes referred to as a “lipid raft,” is predicted to be enriched in glycosphingolipids and cholesterol. An altered lipid composition surrounding the BCR could influence the partitioning and activity of regulatory proteins and lipids, acting as a mechanism for the B cell to regulate signal transduction following stimulus by antigen. However, without direct observations of this phenomenon, theories surrounding lipid compositional heterogeneity in B cells remain controversial. In this work, we utilize two-color super-resolution localization microscopy (STORM and PALM) to directly observe the lipid composition proximal to B cell receptors, using the photoactivatable fluorescent protein mEos3.2 anchored to the plasma membrane through posttranslational lipid modifications. These probes mimic important regulatory proteins involved in BCR signaling by their membrane anchor but lack the protein interaction domains or biological activity found in the native protein. By analyzing the co-distributions of the B cell receptor and lipid probes using correlation functions, we find that the membrane surrounding B cell receptor clusters is depleted of probes bearing unsaturated and branched geranylgeranyl modifications and is enriched in probes bearing saturated palmitoyl modifications. Quantification of lipid probe distributions reveals that B cell compositional heterogeneity influences the partitioning of these lipid modifications with order 1kBT of effective potential, as expected from predications of composition fluctuations in critical systems. These findings provide definitive evidence of membrane compositional heterogeneity in an important biological signaling system. Our results suggest that compositional fluctuations contribute to cellular responses by influencing the spatial distribution of specific components in the plasma membrane.

Drug inhibition and proton conduction mechanisms of the influenza a M2 proton channel.

The influenza A virus matrix protein 2 (M2 protein) is a pH-regulated proton channel embedded in the viral membrane. Inhibition of the M2 proton channel has been used to treat influenza infections for decades due to the crucial role of this protein in viral infection and replication. However, the widely-used M2 inhibitors, amantadine and rimantadine, have gradually lost their efficiencies because of naturally-occurring drug resistant mutations. Therefore, investigation of the structure and function of the M2 proton channel will not only increase our understanding of this important biological system, but also lead to the design of novel and effective anti-influenza drugs. Despite the simplicity of the M2 molecular structure, the M2 channel is highly flexible and there have been controversies and arguments regarding the channel inhibition mechanism and the proton conduction mechanism. In this book chapter, we will first carefully review the experimental and computational studies of the two possible drug binding sites on the M2 protein and explain the mechanisms regarding how inhibitors prevent proton conduction. Then, we will summarize our recent molecular dynamics simulations of the drug-resistant mutant channels and propose mechanisms for drug resistance. Finally, we will discuss two existing proton conduction mechanisms and talk about the remaining questions regarding the proton-relay process through the channel. The studies reviewed here demonstrate how molecular modeling and simulations have complemented experimental work and helped us understand the M2 channel structure and function.