Simulated evolution of signal transduction networks

Therapeutic implications of glycogen synthase kinase-3β in Alzheimer's disease: a novel therapeutic target

Alzheimer's disease (AD) is an extremely popular neurodegenerative condition associated with dementia, responsible for around 70% of the cases. There are presently 50 million people living with dementia in the world, but this number is anticipated to increase to 152 million by 2050, posing a substantial socioeconomic encumbrance. Despite extensive research, the precise mechanisms that cause AD remain unidentified, and currently, no therapy is available. Numerous signalling paths related to AD neuropathology, including glycogen synthase kinase 3-β (GSK-3β), have been investigated as potential targets for the treatment of AD in current years.GSK-3β is a proline-directed serine/threonine kinase that is linked to a variety of biological activities, comprising glycogen metabolism to gene transcription. GSK-3β is also involved in the pathophysiology of sporadic as well as familial types of AD, which has led to the development of the GSK3 theory of AD. GSK-3β is a critical performer in the pathology of AD because dysregulation of this kinase affects all the main symbols of the disease such as amyloid formation, tau phosphorylation, neurogenesis and synaptic and memory function. The current review highlights present-day knowledge of GSK-3β-related neurobiology, focusing on its role in AD pathogenesis signalling pathways. It also explores the possibility of targeting GSK-3β for the management of AD and offers an overview of the present research work in preclinical and clinical studies to produce GSK-3β inhibitors.

An Approach for Systems-Level Understanding of Prostate Cancer from High-Throughput Data Integration to Pathway Modeling and Simulation

To understand complex diseases, high-throughput data are generated at large and multiple levels. However, extracting meaningful information from large datasets for comprehensive understanding of cell phenotypes and disease pathophysiology remains a major challenge. Despite tremendous advances in understanding molecular mechanisms of cancer and its progression, current knowledge appears discrete and fragmented. In order to render this wealth of data more integrated and thus informative, we have developed a GECIP toolbox to investigate the crosstalk and the responsible genes'/proteins' connectivity of enriched pathways from gene expression data. To implement this toolbox, we used mainly gene expression datasets of prostate cancer, and the three datasets were GSE17951, GSE8218, and GSE1431. The raw samples were processed for normalization, prediction of differentially expressed genes, and the prediction of enriched pathways for the differentially expressed genes. The enriched pathways have been processed for crosstalk degree calculations for which number connections per gene, the frequency of genes in the pathways, sharing frequency, and the connectivity have been used. For network prediction, protein-protein interaction network database FunCoup2.0 was used, and cytoscape software was used for the network visualization. In our results, we found that there were enriched pathways 27, 45, and 22 for GSE17951, GSE8218, and GSE1431, respectively, and 11 pathways in common between all of them. From the crosstalk results, we observe that focal adhesion and PI3K pathways, both experimentally proven central for cellular output upon perturbation of numerous individual/distinct signaling pathways, displayed highest crosstalk degree. Moreover, we also observe that there were more critical pathways which appear to be highly significant, and these pathways are HIF1a, hippo, AMPK, and Ras. In terms of the pathways' components, GSK3B, YWHAE, HIF1A, ATP1A3, and PRKCA are shared between the aforementioned pathways and have higher connectivity with the pathways and the other pathway components. Finally, we conclude that the focal adhesion and PI3K pathways are the most critical pathways, and since for many other pathways, high-rank enrichment did not translate to high crosstalk degree, the global impact of one pathway on others appears distinct from enrichment.

NF-kB in Signaling Patterns and Its Temporal Dynamics Encode/Decode Human Diseases

Defects in signaling pathways are the root cause of many disorders. These malformations come in a wide variety of types, and their causes are also very diverse. Some of these flaws can be brought on by pathogenic organisms and viruses, many of which can obstruct signaling processes. Other illnesses are linked to malfunctions in the way that cell signaling pathways work. When thinking about how errors in signaling pathways might cause disease, the idea of signalosome remodeling is helpful. The signalosome may be conveniently divided into two types of defects: phenotypic remodeling and genotypic remodeling. The majority of significant illnesses that affect people, including high blood pressure, heart disease, diabetes, and many types of mental illness, appear to be caused by minute phenotypic changes in signaling pathways. Such phenotypic remodeling modifies cell behavior and subverts normal cellular processes, resulting in illness. There has not been much progress in creating efficient therapies since it has been challenging to definitively confirm this connection between signalosome remodeling and illness. The considerable redundancy included into cell signaling systems presents several potential for developing novel treatments for various disease conditions. One of the most important pathways, NF-κB, controls several aspects of innate and adaptive immune responses, is a key modulator of inflammatory reactions, and has been widely studied both from experimental and theoretical perspectives. NF-κB contributes to the control of inflammasomes and stimulates the expression of a number of pro-inflammatory genes, including those that produce cytokines and chemokines. Additionally, NF-κB is essential for controlling innate immune cells and inflammatory T cells' survival, activation, and differentiation. As a result, aberrant NF-κB activation plays a role in the pathogenesis of several inflammatory illnesses. The activation and function of NF-κB in relation to inflammatory illnesses was covered here, and the advancement of treatment approaches based on NF-κB inhibition will be highlighted. This review presents the temporal behavior of NF-κB and its potential relevance in different human diseases which will be helpful not only for theoretical but also for experimental perspectives.

Synthesis of Silver Nano Particles Using Myricetin and the In-Vitro Assessment of Anti-Colorectal Cancer Activity: In-Silico Integration

The creation of novel anticancer treatments for a variety of human illnesses, including different malignancies and dangerous microbes, also potentially depends on nanoparticles including silver. Recently, it has been successful to biologically synthesize metal nanoparticles using plant extracts. The natural flavonoid 3,3′, 4′, 5,5′, and 7 hexahydroxyflavon (myricetin) has anticancer properties. There is not much known about the regulatory effects of myricetin on the possible cell fate-determination mechanisms (such as apoptosis/proliferation) in colorectal cancer. Because the majority of investigations related to the anticancer activity of myricetin have dominantly focused on the enhancement of tumor cell uncontrolled growth (i.e., apoptosis). Thus, we have decided to explore the potential myricetin interactors and the associated biological functions by using an in-silico approach. Then, we focused on the main goal of the work which involved the synthesis of silver nanoparticles and the labeling of myricetin with it. The synthesized silver nanoparticles were examined using UV-visible spectroscopy, dynamic light scattering spectroscopy, Fourier transform infrared spectroscopy, and scanning electron microscopy. In this study, we have investigated the effects of myricetin on colorectal cancer where numerous techniques were used to show myricetin’s effect on colon cancer cells. Transmission Electron Microscopy was employed to monitor morphological changes. Furthermore, we have combined the results of the colorectal cancer gene expression dataset with those of the myricetin interactors and pathways. Based on the results, we conclude that myricetin is able to efficiently kill human colorectal cancer cell lines. Since, it shares important biological roles and possible route components and this myricetin may be a promising herbal treatment for colorectal cancer as per an in-silico analysis of the TCGA dataset.

A Network-Guided Approach to Discover Phytochemical-Based Anticancer Therapy: Targeting MARK4 for Hepatocellular Carcinoma

MAP/microtubule affinity-regulating kinase 4 (MARK4) is associated with various biological functions, including neuronal migration, cell polarity, microtubule dynamics, apoptosis, and cell cycle regulation, specifically in the G1/S checkpoint, cell signaling, and differentiation. It plays a critical role in different types of cancers. Hepatocellular carcinoma (HCC) is the one of the most common forms of liver cancer caused due to mutations, epigenetic aberrations, and altered gene expression patterns. Here, we have applied an integrated network biology approach to see the potential links of MARK4 in HCC, and subsequently identified potential herbal drugs. This work focuses on the naturally-derived compounds from medicinal plants and their properties, making them targets for potential anti-hepatocellular treatments. We further analyzed the HCC mutated genes from the TCGA database by using cBioPortal and mapped out the MARK4 targets among the mutated list. MARK4 and Mimosin, Quercetin, and Resveratrol could potentially interact with critical cancer-associated proteins. A set of the hepatocellular carcinoma altered genes is directly the part of infection, inflammation, immune systems, and cancer pathways. Finally, we conclude that among all these drugs, Gingerol and Fisetin appear to be the highly promising drugs against MARK4-based targets, followed by Quercetin, Resveratrol, and Apigenin.

Potential and Therapeutic Roles of Diosmin in Human Diseases

Because of their medicinal characteristics, effectiveness, and importance, plant-derived flavonoids have been a possible subject of research for many years, particularly in the last decade. Plants contain a huge number of flavonoids, and Diosmin, a flavone glycoside, is one of them. Numerous in-vitro and in-vivo studies have validated Diosmin’s extensive range of biological capabilities which present antioxidative, antihyperglycemic, anti-inflammatory, antimutagenic, and antiulcer properties. We have presented this review work because of the greater biological properties and influences of Diosmin. We have provided a brief overview of Diosmin, its pharmacology, major biological properties, such as anti-cancer, anti-diabetic, antibacterial, anticardiovascular, liver protection, and neuroprotection, therapeutic approach, potential Diosmin targets, and pathways that are known to be associated with it.

Multi-staged gene expression profiling reveals potential genes and the critical pathways in kidney cancer

Cancer is among the highly complex disease and renal cell carcinoma is the sixth-leading cause of cancer death. In order to understand complex diseases such as cancer, diabetes and kidney diseases, high-throughput data are generated at large scale and it has helped in the research and diagnostic advancement. However, to unravel the meaningful information from such large datasets for comprehensive and minute understanding of cell phenotypes and disease pathophysiology remains a trivial challenge and also the molecular events leading to disease onset and progression are not well understood. With this goal, we have collected gene expression datasets from publicly available dataset which are for two different stages (I and II) for renal cell carcinoma and furthermore, the TCGA and cBioPortal database have been utilized for clinical relevance understanding. In this work, we have applied computational approach to unravel the differentially expressed genes, their networks for the enriched pathways. Based on our results, we conclude that among the most dominantly altered pathways for renal cell carcinoma, are PI3K-Akt, Foxo, endocytosis, MAPK, Tight junction, cytokine-cytokine receptor interaction pathways and the major source of alteration for these pathways are MAP3K13, CHAF1A, FDX1, ARHGAP26, ITGBL1, C10orf118, MTO1, LAMP2, STAMBP, DLC1, NSMAF, YY1, TPGS2, SCARB2, PRSS23, SYNJ1, CNPPD1, PPP2R5E. In terms of clinical significance, there are large number of differentially expressed genes which appears to be playing critical roles in survival.

Global Gene Expression and Docking Profiling of COVID-19 Infection

Coronavirus is an enclosed positive-sense RNA virus with club-like spikes protruding from its surface that causes acute respiratory infections in humans. Because it is considered a member of the complex pathogen group, it has been found to infect different host species and cause a variety of diseases. So far, it has been discovered that it may affect the immune, infection, and inflammatory systems, leading to the hypothesis that the immune and inflammatory systems (signaling pathways and components) fail to control infection, opening the door to look for potential targets primarily in these systems. The study’s main purpose is to identify highly overexpressed genes and their functional implications as a result of COVID-19 infection, as well as to investigate probable infections, inflammation, and immune systems to better understand the impact of coronavirus infection. We explored the genes and pathways mostly linked with infection, inflammation, and the immune systems using the datasets available for COVID-19 infection gene expression compendium. NFKBIA, FN1, FAP, KANK4, COMP, FAM101B, COL1A2, ANKRD1, TAGLN, SPARC, ADAM19, OLFM4, CXCL10/11, OASL, FOS, APOBEC3A, IFI44L, IFI27, IFIT1, RSAD2, NDUFS1, SRSF6, HECTD1, CBX3, and DDX17 are among the genes that may be impacted by infection, according to our findings. The functional changes are mainly associated with these pathways TNF, cytokine, NF—kB, TLR, TCR, BCR, Foxo, and TGF signaling pathways are among them and there are additional pathways such as hippo signaling, apoptosis, estrogen signaling, regulating pluropotency of stem cells, ErbB, Wnt, p53, cAMP, MAPK, PI3K—AKT, oxidative phosphorylation, protein processing in endoplasmic reticulum, prolactin signaling, adipocytokine, neurotrophine signaling, and longevity regulating pathways. Moreover, we have also explored the potential herbal drug (apigenin, quercetin, and resveratrol) targets for the top-rated genes based on the overall analysis where we observe that quercetin and resveratrol as most effective.

Gene Expression Profiling of Early Acute Febrile Stage of Dengue Infection and Its Comparative Analysis With Streptococcus pneumoniae Infection

Infectious diseases are the disorders caused by organisms such as bacteria, viruses, fungi, or parasites. Although many of them are permentantly hazardous, a number of them live in and on our bodies and they are normally harmless or even helpful. Under certain circumstances, some organisms may cause diseases and these infectious diseases may be passed directly from person to person or via intermediate vectors including insects and other animals. Dengue virus and Streptococcus pneumoniae are the critical and common sources of infectious diseases. So, it is critical to understand the gene expression profiling and their inferred functions in comparison to the normal and virus infected conditions. Here, we have analyzed the gene expression profiling for dengue hemorrhagic fever, dengue fever, and normal human dataset. Similar to it, streptococcus pneumoniae infectious data were analyzed and both the outcomes were compared. Our study leads to the conclusion that the dengue hemorrhagic fever arises in result to potential change in the gene expression pattern, and the inferred functions obviously belong to the immune system, but also there are some additional potential pathways which are critical signaling pathways. In the case of pneumoniae infection, 19 pathways were enriched, almost all these pathways are associated with the immune system and 17 of the enriched pathways were common with dengue infection except platelet activation and antigen processing and presentation. In terms of the comparative study between dengue virus and Streptococcus pneumoniae infection, we conclude that cell adhesion molecules (CAMs), MAPK signaling pathway, natural killer cell mediated cytotoxicity, regulation of actin cytoskeleton, and cytokine-cytokine receptor interaction are commonly enriched in all the three cases of dengue infection and Streptococcus pneumoniae infection, focal adhesion was enriched between classical dengue fever — dengue hemorrhagic fever, dengue hemorrhagic fever—normal samples, and SP, and antigen processing and presentation and Leukocyte transendothelial migration were enriched in classical dengue fever —normal samples, dengue hemorrhagic fever—normal samples, and Streptococcus pneumoniae infection.

In-Silico Study of Immune System Associated Genes in Case of Type-2 Diabetes With Insulin Action and Resistance, and/or Obesity

Type-2 diabetes and obesity are among the leading human diseases and highly complex in terms of diagnostic and therapeutic approaches and are among the most frequent and highly complex and heterogeneous in nature. Based on epidemiological evidence, it is known that the patients suffering from obesity are considered to be at a significantly higher risk of type-2 diabetes. There are several pieces of evidence that support the hypothesis that these diseases interlinked and obesity may aggravate the risk(s) of type-2 diabetes. Multi-level unwanted alterations such as (epi-) genetic alterations, changes at the transcriptional level, and altered signaling pathways (receptor, cytoplasmic, and nuclear level) are the major sources that promote several complex diseases, and such a heterogeneous level of complexity is considered as a major barrier in the development of therapeutics. With so many known challenges, it is critical to understand the relationships and the shared causes between type-2 diabetes and obesity, and these are difficult to unravel and understand. For this purpose, we have selected publicly available datasets of gene expression for obesity and type-2 diabetes, have unraveled the genes and the pathways associated with the immune system, and have also focused on the T-cell signaling pathway and its components. We have applied a simplified computational approach to understanding differential gene expression and patterns and the enriched pathways for obesity and type-2 diabetes. Furthermore, we have also analyzed genes by using network-level understanding. In the analysis, we observe that there are fewer genes that are commonly differentially expressed while a comparatively higher number of pathways are shared between them. There are only 4 pathways that are associated with the immune system in case of obesity and 10 immune-associated pathways in case of type-2 diabetes, and, among them, only 2 pathways are commonly altered. Furthermore, we have presented SPNS1, PTPN6, CD247, FOS, and PIK3R5 as the overexpressed genes, which are the direct components of TCR signaling.

Positive selection at sites of chemosensory genes is associated with the recent divergence and local ecological adaptation in cactophilic Drosophila

Background

Adaptation to new hosts in phytophagous insects often involves mechanisms of host recognition by genes of sensory pathways. Most often the molecular evolution of sensory genes has been explained in the context of the birth-and-death model. The role of positive selection is less understood, especially associated with host adaptation and specialization. Here we aim to contribute evidence for this latter hypothesis by considering the case of Drosophila mojavensis, a species with an evolutionary history shaped by multiple host shifts in a relatively short time scale, and its generalist sister species, D. arizonae.

Results

We used a phylogenetic and population genetic analysis framework to test for positive selection in a subset of four chemoreceptor genes, one gustatory receptor (Gr) and three odorant receptors (Or), for which their expression has been previously associated with host shifts. We found strong evidence of positive selection at several amino acid sites in all genes investigated, most of which exhibited changes predicted to cause functional effects in these transmembrane proteins. A significant portion of the sites identified as evolving positively were largely found in the cytoplasmic region, although a few were also present in the extracellular domains.

Conclusions

The pattern of substitution observed suggests that some of these changes likely had an effect on signal transduction as well as odorant recognition and protein-protein interactions. These findings support the role of positive selection in shaping the pattern of variation at chemosensory receptors, both during the specialization onto one or a few related hosts, but as well as during the evolution and adaptation of generalist species into utilizing several hosts.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1250-x) contains supplementary material, which is available to authorized users.

Insights into the Temporal Gene Expression Pattern in Lymantria dispar Larvae During the Baculovirus Induced Hyperactive Stage

Baculoviruses are effective biological control agents for many insect pests. They not only efficiently challenge the host immune system but also make them hyperactive for better virus dispersal. Some investigations have focused on the viral mechanisms for induction of such altered response from the host. However, there are no current studies monitoring changes in gene expression during this altered phenotype in infected larvae. The L. dispar multiple nucleopolyhedrovirus (LdMNPV) induces hyperactivity in third instar L. dispar larvae at 3-days post infection (dpi), to continued till 6 dpi. The transcriptome profiles of the infected and uninfected larvae at these time points were analyzed to provide new clues on the response of the larvae towards infection during hyperactivity. Gene ontology enrichment analysis revealed, most of the differentially expressed genes (DEGs) were involved in proteolysis, extracellular region, and serine-type endopeptidase activity. Similarly, Kyoto Encyclopedia of Genes and Genome enrichment analysis showed maximum enrichment of 487 genes of the signal transduction category and neuroactive ligand-receptor interaction sub-category with 85 annotated genes. In addition, enrichment map visualization of gene set enrichment analysis showed the coordinated response of neuroactive ligand-receptor interaction genes with other functional gene sets, as an important signal transduction mechanism during the hyperactive stage. Interestingly all the DEGs in neuroactive ligand-receptor interactions were serine proteases, their differential expression during the hyperactive stage correlated with their conceivable involvement in disease progression and the resulting altered phenotype during this period. The outcome provides a basic understanding of L. dispar larval responses to LdMNPV infection during the hyperactive stage and helps to determine the important host factors involved in this process.

Modeling evolution of crosstalk in noisy signal transduction networks

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

A Link Between Alzheimer's and Type II Diabetes Mellitus? Ca+2 -Mediated Signal Control and Protein Localization

We propose protein localization dependent signal activation (PLDSA) as a model to describe pre-existing protein partitioning between the cytosol, and membrane surface, as a means to modulate signal activation, specificity, and robustness. We apply PLDSA to explain possible molecular links between type II diabetes mellitus (T2DM) and Alzheimer's disease (AD) by describing Ca+2 -mediated interactions between the Src non-receptor tyrosine kinase and p52Shc adaptor protein. We suggest that these interactions may serve as a contributing factor to disease development and progression. In particular, we propose that signaling response is regulated, in part, by Ca+2 -mediated partitioning of lipid-bound and soluble forms of Src and p52shc. Thus, protein-protein interactions that drive signaling in response to extracellular ligand binding are also mediated by partitioning of signaling proteins between membrane-bound and soluble populations. We propose that PLDSA effects may explain, in part, the evolutionary basis of promiscuous protein interaction domains and their importance in cellular function.

Pivotal role of glycogen synthase kinase-3: A therapeutic target for Alzheimer's disease

Neurodegenerative diseases are among the most challenging diseases with poorly known mechanism of cause and paucity of complete cure. Out of all the neurodegenerative diseases, Alzheimer's disease is the most devastating and loosening of thinking and judging ability disease that occurs in the old age people. Many hypotheses came forth in order to explain its causes. In this review, we have enlightened Glycogen Synthase Kinase-3 which has been considered as a concrete cause for Alzheimer's disease. Plaques and Tangles (abnormal structures) are the basic suspects in damaging and killing of nerve cells wherein Glycogen Synthase Kinase-3 has a key role in the formation of these fatal accumulations. Various Glycogen Synthase Kinase-3 inhibitors have been reported to reduce the amount of amyloid-beta as well as the tau hyperphosphorylation in both neuronal and nonneuronal cells. Additionally, Glycogen Synthase Kinase-3 inhibitors have been reported to enhance the adult hippocampal neurogenesis in vivo as well as in vitro. Keeping the chemotype of the reported Glycogen Synthase Kinase-3 inhibitors in consideration, they may be grouped into natural inhibitors, inorganic metal ions, organo-synthetic, and peptide like inhibitors. On the basis of their mode of binding to the constituent enzyme, they may also be grouped as ATP, nonATP, and allosteric binding sites competitive inhibitors. ATP competitive inhibitors were known earlier inhibitors but they lack efficient selectivity. This led to find the new ways for the enzyme inhibition.

Identifying Driver Nodes in the Human Signaling Network Using Structural Controllability Analysis

Cell signaling governs the basic cellular activities and coordinates the actions in cell. Abnormal regulations in cell signaling processing are responsible for many human diseases, such as diabetes and cancers. With the accumulation of massive data related to human cell signaling, it is feasible to obtain a human signaling network. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis to biological networks. In this work, we apply structural controllability to a human signaling network and detect driver nodes, providing a systematic analysis of the role of different proteins in controlling the human signaling network. We find that the proteins in the upstream of the signaling information flow and the low in-degree proteins play a crucial role in controlling the human signaling network. Interestingly, inputting different control signals on the regulators of the cancer-associated genes could cost less than controlling the cancer-associated genes directly in order to control the whole human signaling network in the sense that less drive nodes are needed. This research provides a fresh perspective for controlling the human cell signaling system.

Negative interactions and feedback regulations are required for transient cellular response

Signal transduction is a process required to conduct information from a receptor to the nucleus. This process is vital for the control of cellular function and fate. The dynamics of signaling activation and inhibition determine processes such as apoptosis, proliferation, and differentiation. Thus, it is important to understand the factors modulating transient and sustained response. To address this question, by applying mathematical approach we have studied the factors which can alter the activation nature of downstream signaling molecules. The factors which we have investigated are loops (feed forward and feedback loops), cross-talk of signal transduction pathways, and the change in the concentration of the signaling molecules. Based on our results we conclude that among these factors feedback loop and the cross-talks which directly inhibit the target protein dominantly controls the transient cellular response.

Systems approaches for synthetic biology: a pathway toward mammalian design

We review methods of understanding cellular interactions through computation in order to guide the synthetic design of mammalian cells for translational applications, such as regenerative medicine and cancer therapies. In doing so, we argue that the challenges of engineering mammalian cells provide a prime opportunity to leverage advances in computational systems biology. We support this claim systematically, by addressing each of the principal challenges to existing synthetic bioengineering approaches—stochasticity, complexity, and scale—with specific methods and paradigms in systems biology. Moreover, we characterize a key set of diverse computational techniques, including agent-based modeling, Bayesian network analysis, graph theory, and Gillespie simulations, with specific utility toward synthetic biology. Lastly, we examine the mammalian applications of synthetic biology for medicine and health, and how computational systems biology can aid in the continued development of these applications.