Community-based network study of protein-carbohydrate interactions in plant lectins using glycan array data

Comparative transcriptome analysis of two Daphnia galeata genotypes displaying contrasting phenotypic variation induced by fish kairomones in the same environment of the Han River, Korea

BACKGROUND

Phenotypic plasticity is a crucial adaptive mechanism that enables organisms to modify their traits in response to changes in their environment. Predator-induced defenses are an example of phenotypic plasticity observed across a wide range of organisms, from single-celled organisms to vertebrates. In addition to morphology and behavior, these responses also affect life-history traits. The crustacean Daphnia galeata is a suitable model organism for studying predator-induced defenses, as it exhibits life-history traits changes under predation risk. To get a better overview of their phenotypic plasticity under predation stress, we conducted RNA sequencing on the transcriptomes of two Korean Daphnia galeata genotypes, KE1, and KB11, collected in the same environment.

RESULTS

When exposed to fish kairomones, the two genotypes exhibited phenotypic variations related to reproduction and growth, with opposite patterns in growth-related phenotypic variation. From both genotypes, a total of 135,611 unigenes were analyzed, of which 194 differentially expressed transcripts (DETs) were shared among the two genotypes under predation stress, which showed consistent, or inconsistent expression patterns in both genotypes. Prominent DETs were related to digestion and reproduction and consistently up-regulated in both genotypes, thus associated with changes in life-history traits. Among the inconsistent DETs, transcripts encode vinculin (VINC) and protein obstructor-E (OBST-E), which are associated with growth; these may explain the differences in life-history traits between the two genotypes. In addition, genotype-specific DETs could explain the variation in growth-related life-history traits between genotypes, and could be associated with the increased body length of genotype KE1.

CONCLUSIONS

The current study allows for a better understanding of the adaptation mechanisms related to reproduction and growth of two Korean D. galeata genotypes induced by predation stress. However, further research is necessary to better understand the specific mechanisms by which the uncovered DETs are related with the observed phenotypic variation in each genotype. In the future, we aim to unravel the precise adaptive mechanisms underlying predator-induced responses.

Ligand recognition and signal transduction by lectin receptor-like kinases in plant immunity

Lectin receptor-like kinases (LecRKs) locate on the cell membrane and play diverse roles in perceiving environmental factors in higher plants. Studies have demonstrated that LecRKs are involved in plant development and response to abiotic and biotic stresses. In this review, we summarize the identified ligands of LecRKs in Arabidopsis, including extracellular purine (eATP), extracellular pyridine (eNAD⁺), extracellular NAD⁺ phosphate (eNADP⁺) and extracellular fatty acids (such as 3-hydroxydecanoic acid). We also discussed the posttranslational modification of these receptors in plant innate immunity and the perspectives of future research on plant LecRKs.

Comparative Transcriptome Analysis of Eriocheir sinensis from Wild Habitats in Han River, Korea

Eriocheir sinensis is an euryhaline crab found from East Asia to Europe and North America. This species can live in freshwater and seawater due to the unique physiological characteristics of their life cycle, which allows them to adapt and inhabit different habitats in a wide range of environments. Despite the wealth of studies focusing on adaptation mechanism of E. sinensis to specific environmental factors, the adaptation mechanisms to wild habitats with coexisting environmental factors are not well understood. In this study, we conducted a transcriptome analysis to investigate gene expression differences related to habitat adaptation of E. sinensis from two wild habitats with different environmental factors in the Han River, Korea. A total of 138,261 unigenes were analyzed, of which 228 were analyzed as differentially expressed genes (DEGs) between the two wild habitats. Among 228 DEGs, 110 DEGs were annotated against databases; most DEGs were involved in energy metabolism, immunity, and osmoregulation. Moreover, DEG enrichment analysis showed that upregulated genes were related to biosynthesis, metabolism, and immunity in an habitat representing relatively high salinity whereas downregulated genes were related to ion transport and hypoxia response in habitats with relatively low salinity and dissolved oxygen. The present findings can serve as foundation for future E. sinensis culture or conservation approaches in natural conditions.

GlyNet: a multi-task neural network for predicting protein-glycan interactions

Advances in diagnostics, therapeutics, vaccines, transfusion, and organ transplantation build on a fundamental understanding of glycan–protein interactions. To aid this, we developed GlyNet, a model that accurately predicts interactions (relative binding strengths) between mammalian glycans and 352 glycan-binding proteins, many at multiple concentrations. For each glycan input, our model produces 1257 outputs, each representing the relative interaction strength between the input glycan and a particular protein sample. GlyNet learns these continuous values using relative fluorescence units (RFUs) measured on 599 glycans in the Consortium for Functional Glycomics glycan arrays and extrapolates these to RFUs from additional, untested glycans. GlyNet's output of continuous values provides more detailed results than the standard binary classification models. After incorporating a simple threshold to transform such continuous outputs the resulting GlyNet classifier outperforms those standard classifiers. GlyNet is the first multi-output regression model for predicting protein–glycan interactions and serves as an important benchmark, facilitating development of quantitative computational glycobiology.

GlyNet, a neural net model of glycan-protein binding strengths. Given a glycan it outputs binding to each of several protein samples. Reproducing glycan array data, it extrapolates the binding of untested glycans against the protein samples.

Glyco-nanotechnology: A biomedical perspective

Glycans govern cellular signaling through glycan-protein and glycan-glycan crosstalk. Disruption in the crosstalk initiates 'rogue' signaling and pathology. Nanomaterials supply platforms for multivalent displays of glycans, mediate 'rogue' signal correction, and provide disease treatment modalities (therapeutics). The decorated glycans also target overexpressed lectins on unhealthy cells and direct metal nanoparticles such as gold, iron oxide, and quantum dots to the site of infection. The nanoparticles inform us about the state of the disease (diagnosis) through their distinct optical, magnetic, and electronic properties. Glyco-nanoparticles can sense disease biomarkers, report changes in protein-glycan interactions, and safeguard quality control (analysis). Here we review the current state of glyco-nanotechnology focusing on diagnosis, therapeutics, and analysis of human diseases. We highlight how glyco-nanotechnology could aid in improving diagnostic methods for the detection of disease biomarkers with magnetic resonance imaging (MRI) and fluorescence imaging (FLI), enhance therapeutics such as anti-adhesive treatment of cancer and vaccines against pneumonia, and advance analysis such as the rapid detection of pharmaceutical heparin contaminant and recombinant SARS-COV-2 spike protein. We illustrate these progressions and outline future potentials of glyco-nanotechnology in advancing human health.

Role of Transportome in the Gills of Chinese Mitten Crabs in Response to Salinity Change: A Meta-Analysis of RNA-Seq Datasets

Chinese mitten crab (CMC) or Eriocheir sinensis is a strong osmoregulator that can keep rigorous cellular homeostasis. CMC can flourish in freshwater, as well as seawater, habitats and represents the most important species for freshwater aquaculture. Salt stress can have direct effects on several stages (e.g., reproduction, molting, growth, etc.) of the CMC life cycle. To get a better overview of the genes involved in the gills of CMC under different salinity conditions, we conducted an RNA-Seq meta-analysis on the transcriptomes of four publicly available datasets. The meta-analysis identified 405 differentially expressed transcripts (DETs), of which 40% were classified into various transporter classes, including accessory factors and primary active transporters as the major transport classes. A network analysis of the DETs revealed that adaptation to salinity is a highly regulated mechanism in which different functional modules play essential roles. To the best of our knowledge, this study is the first to conduct a transcriptome meta-analysis of gills from crab RNA-Seq datasets under salinity. Additionally, this study is also the first to focus on the differential expression of diverse transporters and channels (transportome) in CMC. Our meta-analysis opens new avenues for a better understanding of the osmoregulation mechanism and the selection of potential transporters associated with salinity change.

CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates

Characterizing glycans and glycoconjugates in the context of three-dimensional structures is important in understanding their biological roles and developing efficient therapeutic agents. Computational modeling and molecular simulation have become an essential tool complementary to experimental methods. Here, we present a computational tool, Glycan Modeler for in silico N-/O-glycosylation of the target protein and generation of carbohydrate-only systems. In our previous study, we developed Glycan Reader, a web-based tool for detecting carbohydrate molecules from a PDB structure and generation of simulation system and input files. As integrated into Glycan Reader in CHARMM-GUI, Glycan Modeler (Glycan Reader & Modeler) enables to generate the structures of glycans and glycoconjugates for given glycan sequences and glycosylation sites using PDB glycan template structures from Glycan Fragment Database (http://glycanstructure.org/fragment-db). Our benchmark tests demonstrate the universal applicability of Glycan Reader & Modeler to various glycan sequences and target proteins. We also investigated the structural properties of modeled glycan structures by running 2-μs molecular dynamics simulations of HIV envelope protein. The simulations show that the modeled glycan structures built by Glycan Reader & Modeler have the similar structural features compared to the ones solved by X-ray crystallography. We also describe the representative examples of glycoconjugate modeling with video demos to illustrate the practical applications of Glycan Reader & Modeler. Glycan Reader & Modeler is freely available at http://charmm-gui.org/input/glycan.

In silico identification of genes involved in chronic metabolic acidosis

AIMS

Chronic metabolic acidosis (CMA) refers to increased plasma acidity due to disturbed acid-base equilibrium in human body. CMA leads to many dysfunctions including disorders of intestinal metabolism and barrier functions. The human body responds to these intestinal dysfunctions by creating a compensatory mechanism at genomic level in intestinal epithelial cells. This study was to identify the molecular pathways involved in metabolic dysfunction and compensatory adaptations in intestinal epithelium during CMA.

MAIN METHODS

In silico approaches were utilized to characterize a set of 88 differentially expressed genes (DEGs) from intestinal cells of rat CMA model. Interaction networks were constructed for DEGs by GeneMANIA and hub genes as well as enriched clusters in the network were screened using GLay. Gene Ontology (GO) was used for enriching functions in each cluster.

KEY FINDINGS

Four gene hubs, i.e., trefoil factor 1, 5-hydroxytryptamine (serotonin) receptor 5a, solute carrier family 6 (neurotransmitter transporter), member 11, and glutamate receptor, ionotropic, n-methyl d-aspartate 2b, exhibiting the highest node degree were predicted. Six biologically related gene clusters were also predicted. Functional enrichment of GO terms predicted neurological processes such as neurological system process regulation and nerve impulse transmission which are related to negative and positive regulation of digestive system processes., intestinal motility and absorption and maintenance of gastrointestinal epithelium.

SIGNIFICANCE

The study predicted several important genomic pathways that potentially play significant roles in metabolic disruptions or compensatory adaptations of intestinal epithelium induced by CMA. The results provide a further insight into underlying molecular mechanisms associated with CMA.

Inverse Resolution Limit of Partition Density and Detecting Overlapping Communities by Link-Surprise

Finding overlapping communities of complex networks remains a challenge in network science. To address this challenge, one of the widely used approaches is finding the communities of links by optimizing the objective function, partition density. In this study, we show that partition density suffers from inverse resolution limit; it has a strong preference to triangles. This resolution limit makes partition density an improper objective function for global optimization. The conditions where partition density prefers triangles to larger link community structures are analytically derived and confirmed with global optimization calculations using synthetic and real-world networks. To overcome this limitation of partition density, we suggest an alternative measure, Link Surprise, to find link communities, which is suitable for global optimization. Benchmark studies demonstrate that global optimization of Link Surprise yields meaningful and more accurate link community structures than partition density optimization.

Network Analysis for the Identification of Differentially Expressed Hub Genes Using Myogenin Knock-down Muscle Satellite Cells

Muscle, a multinucleate syncytium formed by the fusion of mononuclear myoblasts, arises from quiescent progenitors (satellite cells) via activation of muscle-specific transcription factors (MyoD, Myf5, myogenin: MYOG, and MRF4). Subsequent to a decline in Pax7, induction in the expression of MYOG is a hallmark of myoblasts that have entered the differentiation phase following cell cycle withdrawal. It is evident that MYOG function cannot be compensated by any other myogenic regulatory factors (MRFs). Despite a plethora of information available regarding MYOG, the mechanism by which MYOG regulates muscle cell differentiation has not yet been identified. Using an RNA-Seq approach, analysis of MYOG knock-down muscle satellite cells (MSCs) have shown that genes associated with cell cycle and division, DNA replication, and phosphate metabolism are differentially expressed. By constructing an interaction network of differentially expressed genes (DEGs) using GeneMANIA, cadherin-associated protein (CTNNA2) was identified as the main hub gene in the network with highest node degree. Four functional clusters (modules or communities) were identified in the network and the functional enrichment analysis revealed that genes included in these clusters significantly contribute to skeletal muscle development. To confirm this finding, in vitro studies revealed increased expression of CTNNA2 in MSCs on day 12 compared to day 10. Expression of CTNNA2 was decreased in MYOG knock-down cells. However, knocking down CTNNA2, which leads to increased expression of extracellular matrix (ECM) genes (type I collagen α1 and type I collagen α2) along with myostatin (MSTN), was not found significantly affecting the expression of MYOG in C2C12 cells. We therefore propose that MYOG exerts its regulatory effects by acting upstream of CTNNA2, which in turn regulates the differentiation of C2C12 cells via interaction with ECM genes. Taken together, these findings highlight a new mechanism by which MYOG interacts with CTNNA2 in order to promote myoblast differentiation.

Protein-carbohydrate interactions as part of plant defense and animal immunity

The immune system consists of a complex network of cells and molecules that interact with each other to initiate the host defense system. Many of these interactions involve specific carbohydrate structures and proteins that specifically recognize and bind them, in particular lectins. It is well established that lectin-carbohydrate interactions play a major role in the immune system, in that they mediate and regulate several interactions that are part of the immune response. Despite obvious differences between the immune system in animals and plants, there are also striking similarities. In both cases, lectins can play a role as pattern recognition receptors, recognizing the pathogens and initiating the stress response. Although plants do not possess an adaptive immune system, they are able to imprint a stress memory, a mechanism in which lectins can be involved. This review will focus on the role of lectins in the immune system of animals and plants.

Effect of algae and plant lectins on planktonic growth and biofilm formation in clinically relevant bacteria and yeasts

This study aimed to evaluate the abilities of plant and algae lectins to inhibit planktonic growth and biofilm formation in bacteria and yeasts. Initially, ten lectins were tested on Staphylococcus epidermidis, Staphylococcus aureus, Klebsiella oxytoca, Pseudomonas aeruginosa, Candida albicans, and C. tropicalis at concentrations of 31.25 to 250 μg/mL. The lectins from Cratylia floribunda (CFL), Vatairea macrocarpa (VML), Bauhinia bauhinioides (BBL), Bryothamnion seaforthii (BSL), and Hypnea musciformis (HML) showed activities against at least one microorganism. Biofilm formation in the presence of the lectins was also evaluated; after 24 h of incubation with the lectins, the biofilms were analyzed by quantifying the biomass (by crystal violet staining) and by enumerating the viable cells (colony-forming units). The lectins reduced the biofilm biomass and/or the number of viable cells to differing degrees depending on the microorganism tested, demonstrating the different characteristics of the lectins. These findings indicate that the lectins tested in this study may be natural alternative antimicrobial agents; however, further studies are required to better elucidate the functional use of these proteins.