Neural Upscaling from Residue-Level Protein Structure Networks to Atomistic Structures
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Vy T. Duong↗
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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↗
Structural Basis for the Catalytic Activity of Human SER/THR Protein Phosphatase-5
Serinekhreonine protein phosphatase-5 (PP5) affects many signaling networks that regulate cell growth. Here we report the 1.6 Angstrom resolution crystal structure of PP5 catalytic domain with metal and phosphate ions in the active site. The structure reveals a mechanism for PPS-mediated catalysis that requires the precise positioning of two metal ions within a conserved Asp(sup 271)-M(sub 1),-M(sub 2)-His(sup 427)-W(sup 2)-His(sup 304)-Asp(sup 274) catalytic motif, and provides a structural basis for the exceptional catalytic proficiency of protein phosphatases placing them among the most powerful catalysts. Resolution of the entire C-terminus revealed a novel subdomain, and the structure of PP5 should aid development of specific inhibitors.
Swingle, M. R.↗
Structural Basis for the Catalytic Activity of Human Serine/Threonine Protein Phosphatase-5
Serinehhreonine protein phosphatase-5 (PP5) affects many signaling networks that regulate cell growth and cellular responses to stress. Here we report the crystal structure of the PP5 catalytic domain (PP5c) at a resolution of 1.6 A. From this structure we resolved the mechanism for PP5-mediated hydrolysis of phosphoprotein substrates, which requires the precise positioning of two metal ions within a con served Aspn-271-M(sub 1):M(sub 2)-W(sup 1)-His-427-His-304-Asp-274 catalytic motif. The structure of PPSc provides a structural basis for explaining the exceptional catalytic proficiency of protein phosphatases, which are among the most powerful known catalysts. Resolution of the entire C-terminus revealed a novel subdomain, and the structure of the PP5c should also aid development of type-specific inhibitors.
Swingle, M. R.↗
Mechanical continuity and reversible chromosome disassembly within intact genomes removed from living cells
Chromatin is thought to be structurally discontinuous because it is packaged into morphologically distinct chromosomes that appear physically isolated from one another in metaphase preparations used for cytogenetic studies. However, analysis of chromosome positioning and movement suggest that different chromosomes often behave as if they were physically connected in interphase as well as mitosis. To address this paradox directly, we used a microsurgical technique to physically remove nucleoplasm or chromosomes from living cells under isotonic conditions. Using this approach, we found that pulling a single nucleolus or chromosome out from interphase or mitotic cells resulted in sequential removal of the remaining nucleoli and chromosomes, interconnected by a continuous elastic thread. Enzymatic treatments of interphase nucleoplasm and chromosome chains held under tension revealed that mechanical continuity within the chromatin was mediated by elements sensitive to DNase or micrococcal nuclease, but not RNases, formamide at high temperature, or proteases. In contrast, mechanical coupling between mitotic chromosomes and the surrounding cytoplasm appeared to be mediated by gelsolin-sensitive microfilaments. Furthermore, when ion concentrations were raised and lowered, both the chromosomes and the interconnecting strands underwent multiple rounds of decondensation and recondensation. As a result of these dynamic structural alterations, the mitotic chains also became sensitive to disruption by restriction enzymes. Ion-induced chromosome decondensation could be blocked by treatment with DNA binding dyes, agents that reduce protein disulfide linkages within nuclear matrix, or an antibody directed against histones. Fully decondensed chromatin strands also could be induced to recondense into chromosomes with pre-existing size, shape, number, and position by adding anti-histone antibodies. Conversely, removal of histones by proteolysis or heparin treatment produced chromosome decondensation which could be reversed by addition of histone H1, but not histones H2b or H3. These data suggest that DNA, its associated protein scaffolds, and surrounding cytoskeletal networks function as a structurally-unified system. Mechanical coupling within the nucleoplasm may coordinate dynamic alterations in chromatin structure, guide chromosome movement, and ensure fidelity of mitosis.
NASA Discipline Cell Biology↗
Predicting the Functional State of Protein Kinases Using Interpretable Graph Neural Networks
Kinases are a family of proteins that function as molecular switches, regulating several essential cellular activities such as cell proliferation. Dysfunctional kinases are implicated in several types of cancers and hence they are actively pursued as drug targets. Given the vast number of complex kinase structures that are available in the protein data bank (PDB), there is a necessity to develop methodologies that can identify structurally important moieties of the kinases in an automated fashion, for such techniques can be instrumental in identifying novel drug targets. In this work, we develop a graph neural network (GNN) based deep learning framework for classifying the functionally active and inactive states of a large set of eukaryotic protein kinases, making use of their 3D structure from the PDB. We show that GNN based machine learning models can classify protein states with an accuracy greater than 97%. We further use the GNN models to automatically identify regions of the kinases that are important for its function. For this purpose, Gradient-weighted Class Activation Mapping (Grad-CAM) was implemented on the protein graphs. Remarkably, Grad-CAM consistently identifies the highly conserved DFG motif as the most important part of the protein across the entire kinome, without any prior input. Other regions of the hydrophobic core such as the HRD motif were also identified by the interpretable GNN framework, consistent with the literature. We discuss the significance of each of these regions in detail.
Ashwin Ravichandran↗
Modelling protein functional domains in signal transduction using Maude
Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.
Signal Transduction↗
Molecular regulation of plant cell wall extensibility
Gravity responses in plants often involve spatial and temporal changes in cell growth, which is regulated primarily by controlling the ability of the cell wall to extend. The wall is thought to be a cellulose-hemicellulose network embedded in a hydrated matrix of complex polysaccharides and a small amount of structural protein. The wall extends by a form of polymer creep, which is mediated by expansins, a novel group of wall-loosening proteins. Expansins were discovered during a molecular dissection of the "acid growth" behavior of cell walls. Expansin alters the rheology of plant walls in profound ways, yet its molecular mechanism of action is still uncertain. It lacks detectable hydrolytic activity against the major components of the wall, but it is able to disrupt noncovalent adhesion between wall polysaccharides. The discovery of a second family of expansins (beta-expansins) sheds light on the biological role of a major group of pollen allergens and implies that expansins have evolved for diverse developmental functions. Finally, the contribution of other processes to wall extensibility is briefly summarized.
Review↗
Demonstration of prominent actin filaments in the root columella
The distribution of actin filaments within the gravity-sensing columella cells of plant roots remains poorly understood, with studies over numerous years providing inconsistent descriptions of actin organization in these cells. This uncertainty in actin organization, and thus in actin's role in graviperception and gravisignaling, has led us to investigate actin arrangements in the columella cells of Zea mays L., Medicago truncatula Gaertn., Linum usitatissiilium L. and Nicotianla benthamiana Domin. Actin organization was examined using a combination of optimized immunofluorescence techniques, and an improved fluorochrome-conjugated phalloidin labeling method reliant on 3-maleimidobenzoyl-N-hydroxy-succinimide ester (MBS) cross-linking combined with glycerol permeabilization. Confocal microscopy of root sections labeled with anti-actin antibodies revealed patterns suggestive of actin throughout the columella region. These patterns included short and fragmented actin bundles, fluorescent rings around amyloplasts and intense fluorescence originating from the nucleus. Additionally, confocal microscopy of MBS-stabilized and Alexa Fluor-phalloidin-labeled root sections revealed a previously undetected state of actin organization in the columella. Discrete actin structures surrounded the amyloplasts and prominent actin cables radiated from the nuclear surface toward the cell periphery. Furthermore, the cortex of the columella cells contained fine actin bundles (or single filaments) that had a predominant transverse orientation. We also used confocal microscopy of plant roots expressing endoplasmic reticulum (ER)-targeted green fluorescent protein to demonstrate rapid ER movements within the columella cells, suggesting that the imaged actin network is functional. The successful identification of discrete actin structures in the root columella cells forms the perception and signaling.
Non-NASA Center↗
Quantifying Structural Relationships of Metal-Binding Sites Suggests Origins of Biological Electron Transfer
Biological redox reactions drive planetary biogeochemical cycles. Using a novel, structure-guided sequence analysis of proteins, we explored the patterns of evolution of enzymes responsible for these reactions. Our analysis reveals that the folds that bind transition metal–containing ligands have similar structural geometry and amino acid sequences across the full diversity of proteins. Similarity across folds reflects the availability of key transition metals over geological time and strongly suggests that transition metal–ligand binding had a small number of common peptide origins. We observe that structures central to our similarity network come primarily from oxidoreductases, suggesting that ancestral peptides may have also facilitated electron transfer reactions. Last, our results reveal that the earliest biologically functional peptides were likely available before the assembly of fully functional protein domains over 3.8 billion years ago. Thus, life is a special, very complex form of motion of matter, but this form did not always exist, and it is not separated from inorganic nature by an impassable abyss; rather, it arose from inorganic nature as a new property in the process of evolution of the world. We must study the history of this evolution if we want to solve the problem of the origin of life.
Yana Bromberg↗
Structural Basis for the Catalytic Activity of Human Serine/Threonine Protein Phosphatase type 5 (PP5)
Serine/threonine protein phosphatase-5 (PP5) is a member of the PPP-gene family of protein phosphatases that is widely expressed in mammalian tissues and is highly conserved among eukaryotes. PP5 associates with several proteins that affect signal transduction networks, including the glucocorticoid receptor (GR)-heat shock protein-90 (Hsp90)-heterocomplex, the CDC16 and CDC27 subunits of the anaphase-promoting complex, elF2alpha kinase, the A subunit of PP2A, the G12-alpha / G13-alpha subunits of heterotrimeric G proteins and DNA-PK. The catalytic domain of PP5 (PP5c) shares 35-45% sequence identity with the catalytic domains of other PPP-phosphatases, including protein phosphatase-1 (PP1), -2A (PP2A), -2B / calcineurin (PP2B), -4 (PP4), -6 (PP6), and -7 (PP7). Like PP1, PP2A and PP4, PP5 is also sensitive to inhibition by okadaic acid, microcystin, cantharidin, tautomycin, and calyculin A. Here we report the crystal structure of the PP5 catalytic domain (PP5c) at a resolution of 1.6 angstroms. From this structure we propose a mechanism for PP5-mediated hydrolysis of phosphoprotein substrates, which requires the precise positioning of two metal ions within a conserved Asp(sup 271)-M(sub 1):M(sub 2)-W(sup 1)-His(sup 304)-Asp(sup 274) catalytic motif. The structure of PP5c provides a possible structural basis for explaining the exceptional catalytic proficiency of protein phosphatases, which are among the most powerful known catalysts. Resolution of the entire C-terminus revealed a novel subdomain, and the structure of the PP5c should also aid development of type-specific inhibitors.
Swingle, Mark R.↗
Assembly and enlargement of the primary cell wall in plants
Growing plant cells are shaped by an extensible wall that is a complex amalgam of cellulose microfibrils bonded noncovalently to a matrix of hemicelluloses, pectins, and structural proteins. Cellulose is synthesized by complexes in the plasma membrane and is extruded as a self-assembling microfibril, whereas the matrix polymers are secreted by the Golgi apparatus and become integrated into the wall network by poorly understood mechanisms. The growing wall is under high tensile stress from cell turgor and is able to enlarge by a combination of stress relaxation and polymer creep. A pH-dependent mechanism of wall loosening, known as acid growth, is characteristic of growing walls and is mediated by a group of unusual wall proteins called expansins. Expansins appear to disrupt the noncovalent bonding of matrix hemicelluloses to the microfibril, thereby allowing the wall to yield to the mechanical forces generated by cell turgor. Other wall enzymes, such as (1-->4) beta-glucanases and pectinases, may make the wall more responsive to expansin-mediated wall creep whereas pectin methylesterases and peroxidases may alter the wall so as to make it resistant to expansin-mediated creep.
NASA Discipline Plant Biology↗
Evolutionary Cell Computing: From Protocells to Self-Organized Computing
On the path from inanimate to animate matter, a key step was the self-organization of molecules into protocells - the earliest ancestors of contemporary cells. Studies of the properties of protocells and the mechanisms by which they maintained themselves and reproduced are an important part of astrobiology. These studies also have the potential to greatly impact research in nanotechnology and computer science. Previous studies of protocells have focussed on self-replication. In these systems, Darwinian evolution occurs through a series of small alterations to functional molecules whose identities are stored. Protocells, however, may have been incapable of such storage. We hypothesize that under such conditions, the replication of functions and their interrelationships, rather than the precise identities of the functional molecules, is sufficient for survival and evolution. This process is called non-genomic evolution. Recent breakthroughs in experimental protein chemistry have opened the gates for experimental tests of non-genomic evolution. On the basis of these achievements, we have developed a stochastic model for examining the evolutionary potential of non-genomic systems. In this model, the formation and destruction (hydrolysis) of bonds joining amino acids in proteins occur through catalyzed, albeit possibly inefficient, pathways. Each protein can act as a substrate for polymerization or hydrolysis, or as a catalyst of these chemical reactions. When a protein is hydrolyzed to form two new proteins, or two proteins are joined into a single protein, the catalytic abilities of the product proteins are related to the catalytic abilities of the reactants. We will demonstrate that the catalytic capabilities of such a system can increase. Its evolutionary potential is dependent upon the competition between the formation of bond-forming and bond-cutting catalysts. The degree to which hydrolysis preferentially affects bonds in less efficient, and therefore less well-ordered, peptides is also critical to evolution of a non-genomic system. Based on these results, a new computational object called a "molnet" is defined. Like a neural network, it is formed of interconnected units that send "signals" to each other. Like molecules, neural networks have a specific function once their structure is defined. The difference between a molnet and traditional neural networks, is that input to molnets is not simply passed along and processed from input to output units, but rather it is utilized to form and break connections(bonds), and thus to form new structures. Molnets represent a powerful tool that can be used to understand the conditions under which chemical systems can form large molecules, such as proteins, and display ever more complex functions. This has direct applications, for example to the design of smart,synthetic fabrics. Additional information is contained in the original.
Colombano, Silvano↗
The M2 Proton Channel of Influenza Virus: How Does It Work?
The transport of protons across membranes is an essential process for both bioenergetics of modem cells and the origins of cellular life. All living systems make use of proton gradients across cell walls to convert environmental energy into a high-energy chemical compound, adenosine triphosphate (ATR), synthesized from adenosine diphosphate. ATR, in turn, is used as a source of energy to drive many cellular reactions. The ubiquity of this process in biology suggests that even the earliest cellular systems were relying on proton gradient for harvesting environmental energy needed to support their survival and growth. In contemporary cells, proton transfer is assisted by large, complex proteins embedded in membranes. The issue addressed in this study was: how the same process can be accomplished with the aid of similar, but much simpler molecules that could have existed in the protobiological milieu? The model system used in the study contained a bilayer membrane made of phospholipid, dimyristoylphosphatidylcholine (DMPC), which is a good model of the biological membranes focusing cellular boundaries. Both sides of the bilayer were surrounded by water which simulated the environment inside and outside the cell. Embedded in the membrane was a fragment of the Influenza-A M2 protein and enough sodium counterions to maintain system neutrality. This protein has been shown to exhibit remarkably high rates of proton transport and, therefore, is an excellent model to study the formation of proton gradients across membranes. The Influenza M2 protein is 97 amino acids in length, but a fragment 25 amino acids long, which contains a transmembrane domain of 19 amino acids flanked by 3 amino acids on each side, is sufficient to transport protons. Four identical protein fragments, each folded into a helix, aggregate to form small channels spanning the membrane. Protons are conducted through a narrow pore in the middle of the channel in response to applied voltage. This channel is large enough to contain water molecules, and is normally filled with water. In analogy to the mechanism of proton transfer in some other channels, it has been postulated that protons are translocated along the network of water molecules filling the pore of the channel. This mechanism, however, must involve an additional, important step because the channel contains four histidine amino acid residues, one from each of the helices, which are sufficiently large to occlude the pore and interrupt the water network. The histidine residues ensure channel selectivity by blocking transport of small such as sodium or potassium. They have been also implicated in gating protons due to the ability of each histidine to become positively charged by accepting an additional proton. Two mechanisms of gating have been proposed. In one mechanism, all four histidines acquire an additional proton and, due to repulsion between their positive charges, move away from one another, thus opening the channel. The alternative mechanism relies of the ability of protons to move between different atoms in a molecule (tautomerization). Thus, a proton is captured on one side of the gate while another proton is released from the opposite side, and the molecule returns to the initial state through tautomerization. The simulations were designed to test these two mechanisms. Large-scale, atomic-level molecular dynamics simulations of the channel, in which the histidine residues were in different protonation states revealed that all intermediate states of the system involved in the tautomerization mechanism are structurally stable and the arrangement of water molecules in the channel is conducive to the proton transport. In contrast, in the four-protonated state, postulated to exist in the gate-opening mechanism, the electrostatic repulsion between the histidine residues appears to be so large that the channel looses its structural integrity and one helix moves away from the remaining three. This result indicates that such a mechanism of proton transport is unlikely. The simulations revealed that translocation along a network of water molecules in the channel and tautomerization of the histidine residues in the M2 proteins in the most likely mechanism of proton transport. The results not only explain how a remarkably simple protein system can efficiently aid in the formation of proton gradients across cell walls, but also suggest how this system can be genetically re-engineered to become a directional, reversible proton pump. Such a pump can provide energy to laboratory-built models of simple cellular systems. If they were successfully constructed it would greatly advance our understanding of the beginnings of life and find important applications in medicine and pharmacology.
Pohorille, Andrew↗
Neurosymbolic Hybrid Approach to Driver Collision Warning
There are two main algorithmic approaches to autonomous driving systems: (1) An end-to-end system in which a single deep neural network learns to map sensory input directly into appropriate warning and driving responses. (2) A mediated hybrid recognition system in which a system is created by combining independent modules that detect each semantic feature. While some researchers believe that deep learning can solve any problem, others believe that a more engineered and symbolic approach is needed to cope with complex environments with less data. Deep learning alone has achieved state-of-the-art results in many areas, from complex gameplay to predicting protein structures. In particular, in image classification and recognition, deep learning models have achieved accuracies as high as humans. But sometimes it can be very difficult to debug if the deep learning model doesn't work. Deep learning models can be vulnerable and are very sensitive to changes in data distribution. Generalization can be problematic. It's usually hard to prove why it works or doesn't. Deep learning models can also be vulnerable to adversarial attacks. Here, we combine deep learning-based object recognition and tracking with an adaptive neurosymbolic network agent, called the Non-Axiomatic Reasoning System (NARS), that can adapt to its environment by building concepts based on perceptual sequences. We achieved an improved intersection-over-union (IOU) object recognition performance of 0.65 in the adaptive retraining model compared to IOU 0.31 in the COCO data pre-trained model. We improved the object detection limits using RADAR sensors in a simulated environment, and demonstrated the weaving car detection capability by combining deep learning-based object detection and tracking with a neurosymbolic model.
Wang, Pei↗
Genes encoding calmodulin-binding proteins in the Arabidopsis genome
Analysis of the recently completed Arabidopsis genome sequence indicates that approximately 31% of the predicted genes could not be assigned to functional categories, as they do not show any sequence similarity with proteins of known function from other organisms. Calmodulin (CaM), a ubiquitous and multifunctional Ca(2+) sensor, interacts with a wide variety of cellular proteins and modulates their activity/function in regulating diverse cellular processes. However, the primary amino acid sequence of the CaM-binding domain in different CaM-binding proteins (CBPs) is not conserved. One way to identify most of the CBPs in the Arabidopsis genome is by protein-protein interaction-based screening of expression libraries with CaM. Here, using a mixture of radiolabeled CaM isoforms from Arabidopsis, we screened several expression libraries prepared from flower meristem, seedlings, or tissues treated with hormones, an elicitor, or a pathogen. Sequence analysis of 77 positive clones that interact with CaM in a Ca(2+)-dependent manner revealed 20 CBPs, including 14 previously unknown CBPs. In addition, by searching the Arabidopsis genome sequence with the newly identified and known plant or animal CBPs, we identified a total of 27 CBPs. Among these, 16 CBPs are represented by families with 2-20 members in each family. Gene expression analysis revealed that CBPs and CBP paralogs are expressed differentially. Our data suggest that Arabidopsis has a large number of CBPs including several plant-specific ones. Although CaM is highly conserved between plants and animals, only a few CBPs are common to both plants and animals. Analysis of Arabidopsis CBPs revealed the presence of a variety of interesting domains. Our analyses identified several hypothetical proteins in the Arabidopsis genome as CaM targets, suggesting their involvement in Ca(2+)-mediated signaling networks.
NASA Discipline Plant Biology↗
Bioreactor perfusion system for the long-term maintenance of tissue-engineered skeletal muscle organoids
Three-dimensional skeletal muscle organ-like structures (organoids) formed in tissue culture by fusion of proliferating myoblasts into parallel networks of long, unbranched myofibers provide an in vivo-like model for examining the effects of growth factors, tension, and space flight on muscle cell growth and metabolism. To determine the feasibility of maintaining either avian or mammalian muscle organoids in a commercial perfusion bioreactor system, we measured metabolism, protein turnover. and autocrine/paracrine growth factor release rates. Medium glucose was metabolized at a constant rate in both low-serum- and serum-free media for up to 30 d. Total organoid noncollagenous protein and DNA content decreased approximately 22-28% (P < 0.05) over a 13-d period. Total protein synthesis rates could be determined accurately in the bioreactors for up to 30 h and total protein degradation rates could be measured for up to 3 wk. Special fixation and storage conditions necessary for space flight studies were validated as part of the studies. For example, the anabolic autocrine/paracrine skeletal muscle growth factors prostaglandin F2alpha (PGF2alpha) and insulin-like growth factor-1 (IGF-1) could be measured accurately in collected media fractions, even after storage at 37 degrees C for up to 10 d. In contrast, creatine kinase activity (a marker of cell damage) in collected media fractions was unreliable. These results provide initial benchmarks for long-term ex vivo studies of tissue-engineered skeletal muscle.
NASA Discipline Musculoskeletal↗
How actin crosslinking and bundling proteins cooperate to generate an enhanced cell mechanical response
Actin-crosslinking proteins organize actin filaments into dynamic and complex subcellular scaffolds that orchestrate important mechanical functions, including cell motility and adhesion. Recent mutation studies have shown that individual crosslinking proteins often play seemingly non-essential roles, leading to the hypothesis that they have considerable redundancy in function. We report live-cell, in vitro, and theoretical studies testing the mechanical role of the two ubiquitous actin-crosslinking proteins, alpha-actinin and fascin, which co-localize to stress fibers and the basis of filopodia. Using live-cell particle tracking microrheology, we show that the addition of alpha-actinin and fascin elicits a cell mechanical response that is significantly greater than that originated by alpha-actinin or fascin alone. These live-cell measurements are supported by quantitative rheological measurements with reconstituted actin filament networks containing pure proteins that show that alpha-actinin and fascin can work in concert to generate enhanced cell stiffness. Computational simulations using finite element modeling qualitatively reproduce and explain the functional synergy of alpha-actinin and fascin. These findings highlight the cooperative activity of fascin and alpha-actinin and provide a strong rationale that an evolutionary advantage might be conferred by the cooperative action of multiple actin-crosslinking proteins with overlapping but non-identical biochemical properties. Thus the combination of structural proteins with similar function can provide the cell with unique properties that are required for biologically optimal responses.
Non-NASA Center↗