Variable contributions of tyrosine residues to the structural and spectroscopic properties of the factor for inversion stimulation

The diverse roles of tyrosine residues in proteins may be attributed to their dual hydrophobic and polar nature, which can result in hydrophobic and ring stacking interactions, as well as hydrogen bonding. The small homodimeric DNA binding protein, factor for inversion stimulation (FIS), contains four tyrosine residues located at positions 38, 51, 69, and 95, each involved in specific intra- or intermolecular interactions. To investigate their contributions to the stability, flexibility, and spectroscopic properties of FIS, each one was independently mutated to phenylalanine. Equilibrium denaturation experiments show that Tyr95 and Tyr51 stabilize FIS by about 2 and 1 kcal/mol, respectively, as a result of their involvement in a hydrogen bond-salt bridge network. In contrast, Tyr38 destabilizes FIS by about 1 kcal/mol due to the placement of a hydroxyl group in a hydrophobic environment. The stability of FIS was not altered when the solvent-exposed Tyr69 was mutated. Limited proteolysis with trypsin and V8 proteases was used to monitor the flexibility of the C-terminus (residues 71-98) and the dimer core (residues 26-70), respectively. The results for Y95F and Y51F FIS revealed a different proteolytic susceptibility of the dimer core compared to the C-terminus, suggesting an increased flexibility of the latter. DNA binding affinity of the various FIS mutants was only modestly affected and correlated inversely with the C-terminal flexibility probed by trypsin proteolysis. Deconvolution of the fluorescence contribution of each mutant revealed that it varies in intensity and direction for each tyrosine in WT FIS, highlighting the role of specific interactions and the local environment in determining the fluorescence of tyrosine residues. The significant changes in stability, flexibility, and signals observed for the Y51F and Y95F mutations are attributed to their coupled participation in the hydrogen bond-salt bridge network. These results highlight the importance of tyrosine hydrogen-bonding and packing interactions for the stability of FIS and demonstrate the varying roles that tyrosine residues can play on the structural and spectroscopic properties of even small proteins.     

SPECIATION DUE TO HYBRID NECROSIS IN PLANT–PATHOGEN MODELS

We develop a model for speciation due to postzygotic incompatibility generated by autoimmune reactions. The model is based on frequency‐dependent interactions between host plants and their pathogens, which can generate disruptive selection and give rise to speciation if distant phenotypes become reproductively isolated. Based on recent experimental evidence from Arabidopsis, we assume that at the molecular level, incompatibility between host strains is caused by epistatic interactions between two proteins in the plant immune system—the guard and the guardee. Within each plant strain, immune reactions occur when the guardee protein is modified by a pathogen effector, and the guard subsequently binds to the guardee, thus precipitating an immune response. When guard and guardee proteins come from phenotypically distant parents, a hybrid's immune system can be triggered by erroneous interactions between these proteins even in the absence of pathogen attack, leading to severe autoimmune reactions in hybrids. This generates a Dobzhnasky–Muller incompatibility due to immune reactions. Our model shows how phenotypic variation generated by frequency‐dependent host–pathogen interactions can lead to such postzygotic incompatibilities between extremal types, and hence to speciation.     

The Role of Exosomes in Pancreatic Cancer Microenvironment

Exosomes are nanovesicles shed by cells as a means of communication with other cells. Exosomes contain mRNAs, microRNAs (miRs) and functional proteins. In the present paper, we develop a mathematical model of tumor–immune interaction by means of exosomes shed by pancreatic cancer cells and dendritic cells. Cancer cells’ exosomes contain miRs that promote their proliferation and that inhibit immune response by dendritic cells, and by CD4+ and CD8+ T cells. Dendritic cells release exosomes with proteins that induce apoptosis of cancer cells and that block regulatory T cells. Simulations of the model show how the size of the pancreatic cancer can be determined by measurement of specific miRs (miR-21 and miR-203 in the case of pancreatic cancer), suggesting these miRs as biomarkers for cancer.     

A graph model for the evolution of specificity in humoral immunity

The immune system protects the body against health-threatening entities, known as antigens, through very complex interactions involving the antigens and the system's own entities. One remarkable feature resulting from such interactions is the immune system's ability to improve its capability to fight antigens commonly found in the individual's environment. This adaptation process is called the evolution of specificity. In this paper, we introduce a new mathematical model for the evolution of specificity in humoral immunity, based on Jerne's functional, or idiotypic, network. The evolution of specificity is modeled as the dynamic updating of connection weights in a dynamic graph whose nodes are related to the network's idiotypes. At the core of this weight-updating mechanism are the increase in specificity caused by clonal selection and the decrease in specificity due to the insertion of uncorrelated idiotypes by the bone marrow. As we demonstrate through numerous computer experiments, for appropriate choices of parameters the new model correctly reproduces, in qualitative terms, several immune functions.     

The SIRP family of receptors and immune regulation

The immune system must be highly regulated to obtain optimal immune responses for the elimination of pathogens without causing undue side effects. This tight regulation involves complex interactions between membrane proteins on leukocytes. Members of the signal-regulatory protein (SIRP) family, which are expressed mainly by myeloid cells, provide one example of these regulatory membrane proteins. There are three SIRP-family genes that encode proteins that have similar extracellular regions but different signalling potentials, and are therefore known as 'paired receptors'. In this Review, we describe recent studies defining the ligands of the SIRP-family members, with particular emphasis on relating the molecular interactions of these proteins to their role in immune-cell regulation.     

Non-local Parabolic and Hyperbolic Models for Cell Polarisation in Heterogeneous Cancer Cell Populations

Tumours consist of heterogeneous populations of cells. The sub-populations can have different features, including cell motility, proliferation and metastatic potential. The interactions between clonal sub-populations are complex, from stable coexistence to dominant behaviours. The cell–cell interactions, i.e. attraction, repulsion and alignment, processes critical in cancer invasion and metastasis, can be influenced by the mutation of cancer cells. In this study, we develop a mathematical model describing cancer cell invasion and movement for two polarised cancer cell populations with different levels of mutation. We consider a system of non-local hyperbolic equations that incorporate cell–cell interactions in the speed and the turning behaviour of cancer cells, and take a formal parabolic limit to transform this model into a non-local parabolic model. We then investigate the possibility of aggregations to form, and perform numerical simulations for both hyperbolic and parabolic models, comparing the patterns obtained for these models.     

Mathematical Model of the Roles of T Cells in Inflammatory Bowel Disease

Gut mucosal homeostasis depends on complex interactions among the microbiota, the intestinal epithelium, and the gut associated immune system. A breakdown in some of these interactions may precipitate inflammation. Inflammatory bowel diseases, Crohn’s disease, and ulcerative colitis are chronic inflammatory disorders of the gastrointestinal tract. The initial stages of disease are marked by an abnormally high level of pro-inflammatory helper T cells, Th1. In later stages, Th2 helper cells may dominate while the Th1 response may dampen. The interaction among the T cells includes the regulatory T cells (Treg). The present paper develops a mathematical model by a system of differential equations with terms nonlocal in the space spanned by the concentrations of cytokines that represents the interaction among T cells through a cytokine signaling network. The model demonstrates how the abnormal levels of T cells observed in inflammatory bowel diseases can arise from abnormal regulation of Th1 and Th2 cells by Treg cells.     

Role of neutrophil extracellular traps in regulation of lung cancer invasion and metastasis: Structural insights from a computational model

Lung cancer is one of the leading causes of cancer-related deaths worldwide and is characterized by hijacking immune system for active growth and aggressive metastasis. Neutrophils, which in their original form should establish immune activities to the tumor as a first line of defense, are undermined by tumor cells to promote tumor invasion in several ways. In this study, we investigate the mutual interactions between the tumor cells and the neutrophils that facilitate tumor invasion by developing a mathematical model that involves taxis-reaction-diffusion equations for the critical components in the interaction. These include the densities of tumor and neutrophils, and the concentrations of signaling molecules and structure such as neutrophil extracellular traps (NETs). We apply the mathematical model to a Boyden invasion assay used in the experiments to demonstrate that the tumor-associated neutrophils can enhance tumor cell invasion by secreting the neutrophil elastase. We show that the model can both reproduce the major experimental observation on NET-mediated cancer invasion and make several important predictions to guide future experiments with the goal of the development of new anti-tumor strategies. Moreover, using this model, we investigate the fundamental mechanism of NET-mediated invasion of cancer cells and the impact of internal and external heterogeneity on the migration patterning of tumour cells and their response to different treatment schedules.     

The FIS protein fails to block the binding of DnaA protein to oriC, the Escherichia coli chromosomal origin.

The Escherichia coli chromosomal origin contains several bindings sites for factor for inversion stimulation (FIS), a protein originally identified to be required for DNA inversion by the Hin and Gin recombinases. The primary FIS binding site is close to two central DnaA boxes that are bound by DnaA protein to initiate chromosomal replication. Because of the close proximity of this FIS site to the two DnaA boxes, we performed in situ footprinting with 1, 10-phenanthroline-copper of complexes formed with FIS and DnaA protein that were separated by native gel electrophoresis. These studies show that the binding of FIS to the primary FIS site did not block the binding of DnaA protein to DnaA boxes R2 and R3. Also, FIS appeared to be bound more stably to oriC than DnaA protein, as deduced by its reduced rate of dissociation from a restriction fragment containing oriC . Under conditions in which FIS was stably bound to the primary FIS site, it did not inhibit oriC plasmid replication in reconstituted replication systems. Inhibition, observed only at high levels of FIS, was due to absorption by FIS binding of the negative superhelicity of the oriC plasmid that is essential for the initiation process.     

Two-dimensional kinetics of beta 2-integrin and ICAM-1 bindings between neutrophils and melanoma cells in a shear flow

Cell adhesion, mediated by specific receptor-ligand interactions, plays an important role in biological processes such as tumor metastasis and inflammatory cascade. For example, interactions between beta 2-integrin (lymphocyte function-associated antigen-1 and/or Mac-1) on polymorphonuclear neutrophils (PMNs) and ICAM-1 on melanoma cells initiate the bindings of melanoma cells to PMNs within the tumor microenvironment in blood flow, which in turn activate PMN-melanoma cell aggregation in a near-wall region of the vascular endothelium, therefore enhancing subsequent extravasation of melanoma cells in the microcirculations. Kinetics of integrin-ligand bindings in a shear flow is the determinant of such a process, which has not been well understood. In the present study, interactions of PMNs with WM9 melanoma cells were investigated to quantify the kinetics of beta 2-integrin and ICAM-1 bindings using a cone-plate viscometer that generates a linear shear flow combined with a two-color flow cytometry technique. Aggregation fractions exhibited a transition phase where it first increased before 60 s and then decreased with shear durations. Melanoma-PMN aggregation was also found to be inversely correlated with the shear rate. A previously developed probabilistic model was modified to predict the time dependence of aggregation fractions at different shear rates and medium viscosities. Kinetic parameters of beta 2-integrin and ICAM-1 bindings were obtained by individual or global fittings, which were comparable to respectively published values. These findings provide new quantitative understanding of the biophysical basis of leukocyte-tumor cell interactions mediated by specific receptor-ligand interactions under shear flow conditions.     

DeepCKI:一个基于变分图自编码器预测细胞-细胞因子相互作用的生物信息学模型

细胞因子(cytokine)是一类由免疫细胞和某些非免疫细胞合成和分泌的信号分子,在免疫系统中通过结合相应受体调节细胞生长、分化和调控免疫应答。目前研究多侧重于通过实验方法检测细胞因子和受体的相互作用来研究细胞间的通讯网络,但存在实验周期长、设备要求高和成本高等不足。因此,有必要通过计算方法来加快对细胞-细胞因子相互作用(cell-cytokine interactions, CKI)的系统研究。本文提出一种基于变分图自编码器(variational graph auto-encoder, VGAE)预测细胞-细胞因子相互作用的深度学习模型——DeepCKI。该模型可有效融合蛋白质相互作用网络和不同类型的蛋白质特征,充分挖掘网络拓扑结构和节点属性中的有效信息,实现对细胞-细胞因子相互作用的高效预测。与变分自编码和深度神经网络方法相比,采用图结构设计的DeepCKI表现出了最优的预测性能。DeepCKI模型对4种不同类型细胞-细胞因子相互作用的ROC曲线下面积均高于0.8,模型具有一定的鲁棒性和有效性。预测打分排名前100的细胞-细胞因子相互作用中,有36对已被最新发表文献验证,表明该模...     

Two small protein families, DYNAMIN-RELATED PROTEIN3 and FISSION1, are required for peroxisome fission in Arabidopsis

Peroxisomes are multi-functional organelles that differ in size and abundance depending on the species, cell type, developmental stage, and metabolic and environmental conditions. The PEROXIN11 protein family and the DYNAMIN-RELATED PROTEIN3A (DRP3A) protein have been shown previously to play key roles in peroxisome division in Arabidopsis. To establish a mechanistic model of peroxisome division in plants, we employed forward and reverse genetic approaches to identify more proteins involved in this process. In this study, we identified three new components of the Arabidopsis peroxisome division apparatus: DRP3B, a homolog of DRP3A, and FISSION1A and 1B (FIS1A and 1B), two homologs of the yeast and mammalian FIS1 proteins that mediate the fission of peroxisomes and mitochondria by tethering the DRP proteins to the membrane. DRP3B is partially targeted to peroxisomes and causes defects in peroxisome fission when the gene function is disrupted. drp3A drp3B double mutants display stronger deficiencies than each single mutant parent with respect to peroxisome abundance, seedling establishment and plant growth, suggesting partial functional redundancy between DRP3A and DRP3B. In addition, FIS1A and FIS1B are each dual-targeted to peroxisomes and mitochondria; their mutants show growth inhibition and contain peroxisomes and mitochondria with incomplete fission, enlarged size and reduced number. Our results demonstrate that both DRP3 and FIS1 protein families contribute to peroxisome fission in Arabidopsis, and support the view that DRP and FIS1 orthologs are common components of the peroxisomal and mitochondrial division machineries in diverse eukaryotic species.     

Mathematical modeling of cancer cell invasion of tissue: biological insight from mathematical analysis and computational simulation

The ability of cancer cells to break out of tissue compartments and invade locally gives solid tumours a defining deadly characteristic. One of the first steps of invasion is the remodelling of the surrounding tissue or extracellular matrix (ECM) and a major part of this process is the over-expression of proteolytic enzymes, such as the urokinase-type plasminogen activator (uPA) and matrix metalloproteinases (MMPs), by the cancer cells to break down ECM proteins. Degradation of the matrix enables the cancer cells to migrate through the tissue and subsequently to spread to secondary sites in the body, a process known as metastasis. In this paper we undertake an analysis of a mathematical model of cancer cell invasion of tissue, or ECM, which focuses on the role of the urokinase plasminogen activation system. The model consists of a system of five reaction-diffusion-taxis partial differential equations describing the interactions between cancer cells, uPA, uPA inhibitors, plasmin and the host tissue. Cancer cells react chemotactically and haptotactically to the spatio-temporal effects of the uPA system. The results obtained from computational simulations carried out on the model equations produce dynamic heterogeneous spatio-temporal solutions and using linear stability analysis we show that this is caused by a taxis-driven instability of a spatially homogeneous steady-state. Finally we consider the biological implications of the model results, draw parallels with clinical samples and laboratory based models of cancer cell invasion using three-dimensional invasion assay, and go on to discuss future development of the model.     

A model for simulating cognate recognition and response in the immune system.

We have constructed a model of the immune system that focuses on the clonotypic cell types and their interactions with other cells, and with antigens and antibodies. We carry out simulations of the humoral immune system based on a generalized cellular automaton implementation of the model. We propose using computer simulation as a tool for doing experiments in machine, in the computer, as an adjunct to the usual in vivo and in vitro techniques. These experiments would not be intended to replace the usual biological experiments since, in the foreseeable future, a complete enough computer model capable of reliably simulating the whole immune would not be possible. However a model simulating areas of interest could be used for extensively testing ideas to help in the design of the critical biological experiments. Our present model concentrates on the cellular interactions and is quite adept at testing the importance and effects of cellular interactions with other cells, antigens and antibodies. The implementation is quite general and unrestricted allowing most other immune system components to be added with relative ease when desired.     

Simulation of evolution implemented in the mutualistic symbioses towards enhancing their ecological efficiency,functional integrity and genotypic specificity

We created the mathematical model for the evolution of the Efficiency of Mutualistic Symbioses (EMS) which was estimated as the microsymbiont impacts on the host’s reproductive potential. Using the example of rhizobia–legume interaction, the relationships were studied between EMS and Functional Integrity of Symbiosis (FIS) which is represented as a measure for concordance of changes in the partners’ genotypic frequencies under the environmental fluctuations represented by the minor deviations of the systemic model parameters. The FIS indices correlate positively with EMS values suggesting an enhancement of FIS via the natural selection operating in the partners’ populations in favor of high EMS. Due to this selection, nodular habitats may be closed for colonization by the non-beneficial bacterial strains and the Genotypic Specificity of Mutualism (GSM) in partners’ interactions is enhanced: the selective advantage of host-specific vs non-host-specific mutualists is increasing. The novelty of our model is to suggest a selective background for macroevolutionary events reorganizing the structure and functions of symbiotic systems and to present its evolution as a result of shifting the equilibrium between different types of mutualists under the impacts of the symbiosis-stipulated modes of natural selection.     

Qualitative dynamics of a network model of regulation of the immune system: A rationale for the IgM to IgG switch

A mathematical model has been developed that simulates some of the main features of a network theory of regulation of the immune system. According to the network viewpoint, the V regions (idiotypes) on antibodies and lymphocytes are self-antigens, to which other lymphocytes of the system can respond specifically, just as they respond to foreign antigens. The resultant couplings between the lymphocytes are considered to be basic for the regulation of the system.The present mathematical model simulates the interactions between cells that recognize the antigen (“positive cells”), and “negative cells” that have receptors that specifically recognize the V regions of the positive cells. The mathematical model incorporates only the interactions that are postulated to be important in the four steady states of the theory, and includes neither the antigen nor any accessory (“A”) cells. The effects of both antigen-specific and anti-idiotypic T and B cells are included, as well as antigen-specific and anti-idiotypic T cell factors, and the two main classes of antibodies. The model is a first order autonomous ordinary differential equation in two variables. We describe a geometric technique that gives strong information on the model, without explicitly solving the ordinary differential equation. This technique proves to be powerful in permitting us to systematically scan the parameter space of the model. The detailed analysis leads to support for the idea that the model provides a rationale for the switch observed in the immune system from the production of one major class of antibody (IgM) to the other major class (IgG). The analysis also leads to a new, previously unsuspected possibility for the nature of the suppressed state within the context of the postulates of the symmetrical network theory.     

Yersinia outer protein P inhibits CD8 T cell priming in the mouse infection model

Pathogenic yersiniae translocate a mixture of effector proteins called Yersinia outer proteins (Yops) into the cytosol of eukaryotic cells by their type III secretion system. YopP is one of the best characterized of these effector proteins and known to inhibit the proinflammatory response of the host by interfering with NF-kappaB signal transduction and inducing apoptosis of macrophages. The effects of YopP on the immune response were studied by a Yersinia Ag-independent approach using bacteria that translocate the well-characterized model Ag listeriolysin O of Listeria monocytogenes via their type III secretion system. In this study we demonstrate a novel function for YopP in vivo. It is shown for the first time that YopP not only counteracts the innate immune defense but also inhibits the adaptive immune system by suppressing the development of an effective CD8 T cell response in a mouse model. A possible mechanism for this could be the inhibition of Ag presentation by dendritic cells (DC). In vitro this is shown to be due to the rapid induction of programmed DC death and to inhibition of DC maturation. Using this approach we could further show that the listeriolysin O-specific CD8 T cells generated in vivo by the yopP mutant are functional and are able to protect mice against a lethal challenge with wild type Listeria.     

Latently Infected Cell Activation: A Way to Reduce the Size of the HIV Reservoir?

While antiretroviral drugs can drive HIV to undetectably low levels in the blood, eradication is hindered by the persistence of long-lived, latently infected memory CD4 T cells. Immune activation therapy aims to eliminate this latent reservoir by reactivating these memory cells, exposing them to removal by the immune system and the cytotoxic effects of active infection. In this paper, we develop a mathematical model that investigates the use of immune activation strategies while limiting virus and latent class rebound. Our model considers infection of two memory classes, central and transitional CD4 T cells and the role that general immune activation therapy has on their elimination. Further, we incorporate ways to control viral rebound by blocking activated cell proliferation through anti proliferation therapy. Using the model, we provide insight into the control of latent infection and subsequently into the long term control of HIV infection.