Molecular mechanisms creating bistable switches at cell cycle transitions

Progression through the eukaryotic cell cycle is characterized by specific transitions, where cells move irreversibly from stage i−1 of the cycle into stage i. These irreversible cell cycle transitions are regulated by underlying bistable switches, which share some common features. An inhibitory protein stalls progression, and an activatory protein promotes progression. The inhibitor and activator are locked in a double-negative feedback loop, creating a one-way toggle switch that guarantees an irreversible commitment to move forward through the cell cycle, and it opposes regression from stage i to stage i−1. In many cases, the activator is an enzyme that modifies the inhibitor in multiple steps, whereas the hypo-modified inhibitor binds strongly to the activator and resists its enzymatic activity. These interactions are the basis of a reaction motif that provides a simple and generic account of many characteristic properties of cell cycle transitions. To demonstrate this assertion, we apply the motif in detail to the G1/S transition in budding yeast and to the mitotic checkpoint in mammalian cells. Variations of the motif might support irreversible cellular decision-making in other contexts.     

Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information

Abstract

The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type filter for inferring the structure of the gene regulatory network. In this paper, an inference framework based on point-based Gaussian approximation filters that can exploit the prior information is developed to solve the gene regulatory network inference problem. Different point-based Gaussian approximation filters, including the unscented Kalman filter (UKF), the third-degree cubature Kalman filter (CKF₃), and the fifth-degree cubature Kalman filter (CKF₅) are employed. Several types of network prior information, including the existing network structure information, sparsity assumption, and the range constraint of parameters, are considered, and the corresponding filters incorporating the prior information are developed. Experiments on a synthetic network of eight genes and the yeast protein synthesis network of five genes are carried out to demonstrate the performance of the proposed framework. The results show that the proposed methods provide more accurate inference results than existing methods, such as the EKF and the traditional UKF.

     

Skin aging caused by intrinsic or extrinsic processes characterized with functional proteomics

The skin provides protection against environmental stress. However, intrinsic and extrinsic aging causes significant alteration to skin structure and components, which subsequently impairs molecular characteristics and biochemical processes. Here, we have conducted an immunohistological investigation and established the proteome profiles on nude mice skin to verify the specific responses during aging caused by different factors. Our results showed that UVB‐elicited aging results in upregulation of proliferating cell nuclear antigen and strong oxidative damage in DNA, whereas chronological aging abolished epidermal cell growth and increased the expression of caspase‐14, as well as protein carbonylation. Network analysis indicated that the programmed skin aging activated the ubiquitin system and triggered obvious downregulation of 14‐3‐3 sigma, which might accelerate the loss of cell growth capacity. On the other hand, UVB stimulation enhanced inflammation and the risk of skin carcinogenesis. Collectively, functional proteomics could provide large‐scale investigation of the potent proteins and molecules that play important roles in skin subjected to both intrinsic and extrinsic aging.     

Focus: The Aging Brain: The Significance of the Default Mode Network (DMN) in Neurological and Neuropsychiatric Disorders: A Review

The relationship of cortical structure and specific neuronal circuitry to global brain function, particularly its perturbations related to the development and progression of neuropathology, is an area of great interest in neurobehavioral science. Disruption of these neural networks can be associated with a wide range of neurological and neuropsychiatric disorders. Herein we review activity of the Default Mode Network (DMN) in neurological and neuropsychiatric disorders, including Alzheimer’s disease, Parkinson’s disease, Epilepsy (Temporal Lobe Epilepsy - TLE), attention deficit hyperactivity disorder (ADHD), and mood disorders. We discuss the implications of DMN disruptions and their relationship to the neurocognitive model of each disease entity, the utility of DMN assessment in clinical evaluation, and the changes of the DMN following treatment.     

Simple assumptions predicts prey selection by piscivorous fishes

Studies on trophic interactions permits the use of community-wide network analyses to evaluate the consequences of human interventions in natural communities. In this paper, we aimed to get insights into the underlying mechanism of prey selection for four piscivorous species, and evaluate behavioral responses to prey selection after an impoundment. We assemble six food web models to search for the hypothesis that best predict observed prey selection pattern of piscivorous fishes combining the following assumptions: (i) predation window, defined as the size range of prey species consumed by a piscivorous fish; (ii) prey strategies to avoid predation (iii) and prey abundance. We tested the probability of each hypothesis to reproduce two empirical data, one before and one after an impoundment with minimum assumptions. Before impoundment, we found that predators presented switching behavior, preying preferably on abundant prey; while after impoundment, predators consumed prey within its predation window. Those results explained better than the null hypotesis and all other assumptions; and corroborate with both theoretical and empirical studies. We conclude that different assumptions drives piscivorous fish behavior in different environments; and modelling procedures can be used to assess gaps in trophic interactions of fish communities.     

The carboxy-terminus,a key regulator of protein function

All proteins end with a carboxyl terminus that has unique biophysical properties and is often disordered. Although there are examples of important C-termini functions, a more global role for the C-terminus is not yet established. In this review, we summarize research on C-termini, a unique region in proteins that cells exploit. Alternative splicing and proteolysis increase the diversity of proteins and peptides in cells with unique C-termini. The C-termini of proteins contain minimotifs, short peptides with an encoded function generally characterized as binding, posttranslational modifications, and trafficking. Many of these activities are specific to minimotifs on the C-terminus. Approximately 13% of C-termini in the human proteome have a known minimotif, and the majority, if not all of the remaining termini have conserved motifs inferring a function that remains to be discovered. C-termini, their predictions, and their functions are collated in the C-terminome, Proteus, and Terminus Oriented Protein Function INferred Database (TopFIND) database/web systems. Many C-termini are well conserved, and some have a known role in health and disease. We envision that this summary of C-termini will guide future investigation of their biochemical and physiological significance.     

Characterization of Changes and Driver Microbes in Gut Microbiota During Healthy Aging Using A Captive Monkey Model

Recent population studies have significantly advanced our understanding of how age shapes the gut microbiota. However, the actual role of age could be inevitably confounded due to the complex and variable environmental factors in human populations. A well-controlled environment is thus necessary to reduce undesirable confounding effects, and recapitulate age-dependent changes in the gut microbiota of healthy primates. Herein we performed 16S rRNA gene sequencing, characterized the age-associated gut microbial profiles from infant to elderly crab-eating macaques reared in captivity, and systemically revealed the lifelong dynamic changes of the primate gut microbiota. While the most significant age-associated taxa were mainly found as commensals such as Faecalibacterium, the abundance of a group of suspicious pathogens such as Helicobacter was exclusively increased in infants, underlining their potential role in host development. Importantly, topology analysis indicated that the network connectivity of gut microbiota was even more age-dependent than taxonomic diversity, and its tremendous decline with age could probably be linked to healthy aging. Moreover, we identified key driver microbes responsible for such age-dependent network changes, which were further linked to altered metabolic functions of lipids, carbohydrates, and amino acids, as well as phenotypes in the microbial community. The current study thus demonstrates the lifelong age-dependent changes and their driver microbes in the primate gut microbiota, and provides new insights into their roles in the development and healthy aging of their hosts.     

Identifying ‘firebreaks’ to fragment dispersal networks of a marine parasite

Marine ecosystems are beset by disease outbreaks, and efficient strategies to control dispersal of pathogens are scarce. We tested whether introducing no-farming areas or ‘firebreaks’ could disconnect dispersal networks of a parasitic disease affecting the world’s largest marine fish farming industry (～1000 farms). Larval salmon lice (Lepeophtheirus salmonis) are released from and transported among salmon farms by ocean currents, creating inter-farm networks of louse dispersal. We used a state-of-the-art biophysical model to predict louse movement along the Norwegian coastline and network analysis to identify firebreaks to dispersal. At least one firebreak that fragmented the network into two large unconnected groups of farms was identified for all seasons. During spring, when wild salmon migrate out into the ocean, and louse levels per fish at farms must be minimised, two effective firebreaks were created by removing 13 and 21 farms (1.3% and 2.2% of all farms in the system) at ～61°N and 67°N, respectively. We have demonstrated that dispersal models coupled with network analysis can identify no-farming zones that fragment dispersal networks. Reduced dispersal pathways should lower infection pressure at farms, slow the evolution of resistance to parasite control measures, and alleviate infection pressure on wild salmon populations.     

Virtual screening of active compounds from Artemisia argyi and potential targets against gastric ulcer based on Network pharmacology

Artemisia argyi (AA) is one of the renowned herbs in China often used in the treatment of gastric ulcer (GU). Aiming to predict the active compounds and systematically investigate the mechanisms of Artemisia argyi for GU treatment, the approach of network pharmacology, molecular docking, gene ontology (GO) analysis, and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were adopted, respectively, in present study. A total of 13 predicted targets of the 103 compounds in Artemisia argyi were obtained. Sorted by pathogenic mechanisms of targets and structure types of compounds, it was revealed that flavonoids and sesquiterpenes had better performance than monoterpenes. The network analysis showed that Phospholipase a2 (PA21B), Sulfotransferase family cytosolic 2b member 1 (ST2B1), Nitric-oxide synthase, endothelial (NOS3), Gastrin (GAST), neutrophil collagenase (MMP-8), Leukotriene A-4 hydrolase (LKHA4), Urease maturation factor HypB (HYPB), and Periplasmic serine endoprotease DegP (HtrA) were the key targets with intensely interaction. The functional enrichment analysis indicated that AA probably produced the gastric mucosa protection effects by synergistically regulating many biological pathways, such as NF-κB signaling pathway, HIF-1 signaling pathway, TNF signaling pathway, VEGF signaling pathway, and Toll-like receptor signaling pathway, etc. In addition, C73 and C15 might be promising leading compounds with good molecular docking score. As a consequence, this study holistically illuminates the active constituents and mechanisms based on data analysis, which contributes to searching for leading compounds and the development of new drugs for gastric ulcer.