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Marine algae have attracted a great deal of interest as excellent sources of nutrients. Polysaccharides are the main components in marine algae, hence a great deal of attention has been directed at isolation and characterization of marine algae polysaccharides because of their numerous health benefits. In this review, extraction and purification approaches and chemico-physical properties of marine algae polysaccharides (MAPs) are summarized. The biological activities, which include immunomodulatory, antitumor, antiviral, antioxidant, and hypolipidemic, are also discussed. Additionally, structure-function relationships are analyzed and summarized. MAPs’ biological activities are closely correlated with their monosaccharide composition, molecular weights, linkage types, and chain conformation. In order to promote further exploitation and utilization of polysaccharides from marine algae for functional food and pharmaceutical areas, high efficiency, and low-cost polysaccharide extraction and purification methods, quality control, structure-function activity relationships, and specific mechanisms of MAPs activation need to be extensively investigated.

β-Glucans are a heterogeneous group of glucose polymers with a common structure comprising a main chain of β-(1,3) and/or β-(1,4)-glucopyranosyl units, along with side chains with various branches and lengths. β-Glucans initiate immune responses via immune cells, which become activated by the binding of the polymer to specific receptors. However, β-glucans from different sources also differ in their structure, conformation, physical properties, binding affinity to receptors, and thus biological functions. The mechanisms behind this are not fully understood. This mini-review provides a comprehensive and up-to-date commentary on the relationship between β-glucans' structure and function in relation to their use for immunomodulation.

Microbial physiological processes are intimately involved in nutrient cycling. However, it remains unclear to what extent microbial diversity or community composition is important for determining the rates of ecosystem-scale functions. There are many examples of positive correlations between microbial diversity and ecosystem function, but how microbial communities ‘map' onto ecosystem functions remain unresolved. This uncertainty limits our ability to predict and manage crucial microbially mediated processes such as nutrient losses and greenhouse gas emissions. To overcome this challenge, we propose integrating traditional biodiversity–ecosystem function research with ideas from genotype–phenotype mapping in organisms. We identify two insights from genotype–phenotype mapping that could be useful for microbial biodiversity–ecosystem function studies: the concept of searching ‘agnostically' for markers of ecosystem function and controlling for population stratification to identify microorganisms uniquely associated with ecosystem function. We illustrate the potential for these approaches to elucidate microbial biodiversity–ecosystem function relationships by analysing a subset of published data measuring methane oxidation rates from tropical soils. We assert that combining the approaches of traditional biodiversity–ecosystem function research with ideas from genotype–phenotype mapping will generate novel hypotheses about how complex microbial communities drive ecosystem function and help scientists predict and manage changes to ecosystem functions resulting from human activities. This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.

Phospholipases A2 (PLA2s) belong to a superfamily of enzymes responsible for hydrolysis of the sn-2 fatty acids of membrane phospholipids to release arachidonic acid. PLA2s are the rate limiting enzyme for the downstream synthesis of prostaglandins and leukotrienes that are the main mediators of inflammation. The extracellular forms of this enzyme are also called the secretary phospholipase A2 (sPLA2) and are distributed extensively in most of the tissues in the human body. Their integral role in inflammatory pathways has been the primary reason for the extensive research on this molecule. The catalytic mechanism of sPLA2 is initiated by a histidine/aspartic acid/calcium complex within the active site. Though they are known to have certain housekeeping functions, certain mutations of sPLA2 are known to be implicated in causation of certain pathologies leading to diseases such as atherosclerosis, cardiovascular diseases, benign fleck retina, neurodegeneration, and asthma. We present an overview of human sPLA2 and a comprehensive compilation of the mutations that result in various disease phenotypes. The study not only helps to have a holistic understanding of human sPLA2 mutations and their clinical implications, but is also a useful platform to initiate research pertaining to structure–function relationship of the mutations to develop effective therapies for management of these diseases.

Mucociliary clearance (MCC) is one of the most important defence mechanisms of the human respiratory system. Its failure is implicated in many chronic and debilitating airway diseases. However, due to the complexity of lung organization, we currently lack full understanding on the relationship between these regional differences in anatomy and biology and MCC functioning. For example, it is unknown whether the regional variability of airway geometry, cell biology and ciliary mechanics play a functional role in MCC. It therefore remains unclear whether the regional preference seen in some airway diseases could originate from local MCC dysfunction. Though great insights have been gained into the genetic basis of cilia ultrastructural defects in airway ciliopathies, the scaling to regional MCC function and subsequent clinical phenotype remains unpredictable. Understanding the multiscale mechanics of MCC would help elucidate genotype–phenotype relationships and enable better diagnostic tools and treatment options. Here, we review the hierarchical and variable organization of ciliated airway epithelium in human lungs and discuss how this organization relates to MCC function. We then discuss the relevancy of these structure–function relationships to current topics in lung disease research. Finally, we examine how state-of-the-art computational approaches can help address existing open questions. This article is part of the Theo Murphy meeting issue ‘Unity and diversity of cilia in locomotion and transport’.

(1) Background. Snake venom phosphodiesterases (SVPDEs) are among the least studied venom enzymes. In envenomation, they display various pathological effects, including induction of hypotension, inhibition of platelet aggregation, edema, and paralysis. Until now, there have been no 3D structural studies of these enzymes, thereby preventing structure–function analysis. To enable such investigations, the present work describes the model-based structural and functional characterization of a phosphodiesterase from Crotalus adamanteus venom, named PDE_Ca. (2) Methods. The PDE_Ca structure model was produced and validated using various software (model building: I-TESSER, MODELLER 9v19, Swiss-Model, and validation tools: PROCHECK, ERRAT, Molecular Dynamic Simulation, and Verif3D). (3) Results. The proposed model of the enzyme indicates that the 3D structure of PDE_Ca comprises four domains, a somatomedin B domain, a somatomedin B-like domain, an ectonucleotide pyrophosphatase domain, and a DNA/RNA non-specific domain. Sequence and structural analyses suggest that differences in length and composition among homologous snake venom sequences may account for their differences in substrate specificity. Other properties that may influence substrate specificity are the average volume and depth of the active site cavity. (4) Conclusion. Sequence comparisons indicate that SVPDEs exhibit high sequence identity but comparatively low identity with mammalian and bacterial PDEs.

Network models describe the brain as sets of nodes and edges that represent its distributed organization. So far, most discoveries in network neuroscience have prioritized insights that highlight distinct groupings and specialized functional contributions of network nodes. Importantly, these functional contributions are determined and expressed by the web of their interrelationships, formed by network edges. Here, we underscore the important contributions made by brain network edges for understanding distributed brain organization. Different types of edges represent different types of relationships, including connectivity and similarity among nodes. Adopting a specific definition of edges can fundamentally alter how we analyze and interpret a brain network. Furthermore, edges can associate into collectives and higher order arrangements, describe time series, and form edge communities that provide insights into brain network topology complementary to the traditional node-centric perspective. Focusing on the edges, and the higher order or dynamic information they can provide, discloses previously underappreciated aspects of structural and functional network organization.

The study of the structure–function relationship of ion channels has been one of the most challenging goals in contemporary physiology. Revelation of the three-dimensional (3D) structure of ion channels has facilitated our understanding of many of the submolecular mechanisms inside ion channels, such as selective permeability, voltage dependency, agonist binding, and inter-subunit multimerization. Identifying the structure–function relationship of the ion channels is clinically important as well since only such knowledge can imbue potential therapeutics with practical possibilities. In a sense, recent advances in the understanding of the structure–relationship of transient receptor potential canonical (TRPC) channels look promising since human TRPC channels are calcium-permeable, non-selective cation channels expressed in many tissues such as the gastrointestinal (GI) tract, kidney, heart, vasculature, and brain. TRPC channels are known to regulate GI contractility and motility, pulmonary hypertension, right ventricular hypertrophy, podocyte injury, seizure, fear, anxiety-like behavior, and many others. In this article, we tried to elaborate recent findings of Cryo-EM (cryogenic-electron microscopy) based structural information of TRPC 4 and 5 channels and domain-specific functions of the channel, such as G-protein mediated activation mechanism, extracellular modification of the channel, homo/hetero-tetramerization, and pharmacological gating mechanisms.

An emerging field of human brain imaging deals with the characterization of the connectome, a comprehensive global description of structural and functional connectivity within the human brain. However, the question of how functional and structural connectivity are related has not been fully answered yet. Here, we used different methods to estimate the connectivity between each voxel of the cerebral cortex based on functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data in order to obtain observer-independent functional–structural connectomes of the human brain. Probabilistic fiber-tracking and a novel global fiber-tracking technique were used to measure structural connectivity whereas for functional connectivity, full and partial correlations between each voxel pair's fMRI-timecourses were calculated. For every voxel, two vectors consisting of functional and structural connectivity estimates to all other voxels in the cortex were correlated with each other. In this way, voxels structurally and functionally connected to similar regions within the rest of the brain could be identified. Areas forming parts of the ‘default mode network’ (DMN) showed the highest agreement of structure–function connectivity. Bilateral precuneal and inferior parietal regions were found using all applied techniques, whereas the global tracking algorithm additionally revealed bilateral medial prefrontal cortices and early visual areas. There were no significant differences between the results obtained from full and partial correlations. Our data suggests that the DMN is the functional brain network, which uses the most direct structural connections. Thus, the anatomical profile of the brain seems to shape its functional repertoire and the computation of the whole-brain functional–structural connectome appears to be a valuable method to characterize global brain connectivity within and between populations. •Structure–function connectivity relationship•Multi-modal data fusion•Voxel-wise connectivity analysis•Default mode network•Global fiber-tracking

Human cognition and behaviors depend upon the brain's functional connectomes, which vary remarkably across individuals. However, whether and how the functional connectome individual variability architecture is structurally constrained remains largely unknown. Using tractography- and morphometry-based network models, we observed the spatial convergence of structural and functional connectome individual variability, with higher variability in heteromodal association regions and lower variability in primary regions. We demonstrated that functional variability is significantly predicted by a unifying structural variability pattern and that this prediction follows a primary-to-heteromodal hierarchical axis, with higher accuracy in primary regions and lower accuracy in heteromodal regions. We further decomposed group-level connectome variability patterns into individual unique contributions and uncovered the structural-functional correspondence that is associated with individual cognitive traits. These results advance our understanding of the structural basis of individual functional variability and suggest the importance of integrating multimodal connectome signatures for individual differences in cognition and behaviors.