A bistable switch underlying B-cell differentiation and its disruption by the environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin

Unique challenges and best practices for single cell transcriptomic analysis in toxicology

The application and analysis of single-cell transcriptomics in toxicology presents unique challenges. These include identifying cell sub-populations sensitive to perturbation; interpreting dynamic shifts in cell type proportions in response to chemical exposures; and performing differential expression analysis in dose-response studies spanning multiple treatment conditions. This review examines these challenges while presenting best practices for critical single cell analysis tasks. This covers areas such as cell type identification; analysis of differential cell type abundance; differential gene expression; and cellular trajectories. Towards enhancing the use of single-cell transcriptomics in toxicology, this review aims to address key challenges in this field and offer practical analytical solutions. Overall, applying appropriate bioinformatic techniques to single-cell transcriptomic data can yield valuable insights into cellular responses to toxic exposures.

A multiscale spatial modeling framework for the germinal center response

The germinal center response or reaction (GCR) is a hallmark event of adaptive humoral immunity. Unfolding in the B cell follicles of the secondary lymphoid organs, a GC culminates in the production of high-affinity antibody-secreting plasma cells along with memory B cells. By interacting with follicular dendritic cells (FDC) and T follicular helper (Tfh) cells, GC B cells exhibit complex spatiotemporal dynamics. Driving the B cell dynamics are the intracellular signal transduction and gene regulatory network that responds to cell surface signaling molecules, cytokines, and chemokines. As our knowledge of the GC continues to expand in depth and in scope, mathematical modeling has become an important tool to help disentangle the intricacy of the GCR and inform novel mechanistic and clinical insights. While the GC has been modeled at different granularities, a multiscale spatial simulation framework - integrating molecular, cellular, and tissue-level responses - is still rare. Here, we report our recent progress toward this end with a hybrid stochastic GC framework developed on the Cellular Potts Model-based CompuCell3D platform. Tellurium is used to simulate the B cell intracellular molecular network comprising NF-κB, FOXO1, MYC, AP4, CXCR4, and BLIMP1 that responds to B cell receptor (BCR) and CD40-mediated signaling. The molecular outputs of the network drive the spatiotemporal behaviors of B cells, including cyclic migration between the dark zone (DZ) and light zone (LZ) via chemotaxis; clonal proliferative bursts, somatic hypermutation, and DNA damage-induced apoptosis in the DZ; and positive selection, apoptosis via a death timer, and emergence of plasma cells in the LZ. Our simulations are able to recapitulate key molecular, cellular, and morphological GC events, including B cell population growth, affinity maturation, and clonal dominance. This novel modeling framework provides an open-source, customizable, and multiscale virtual GC simulation platform that enables qualitative and quantitative in silico investigations of a range of mechanistic and applied research questions on the adaptive humoral immune response in the future.

A Multiscale Spatial Modeling Framework for the Germinal Center Response

The germinal center response or reaction (GCR) is a hallmark event of adaptive humoral immunity. Unfolding in the B cell follicles of the secondary lymph organs, a GC culminates in the production of high-affinity antibody-secreting plasma cells along with memory B cells. By interacting with follicular dendritic cells (FDC) and T follicular helper (Tfh) cells, GC B cells exhibit complex spatiotemporal dynamics. Driving the B cell dynamics are the intracellular signal transduction and gene regulatory network that responds to cell surface signaling molecules, cytokines, and chemokines. As our knowledge of the GC continues to expand in depth and in scope, mathematical modeling has become an important tool to help disentangle the intricacy of the GCR and inform novel mechanistic and clinical insights. While the GC has been modeled at different granularities, a multiscale spatial simulation framework - integrating molecular, cellular, and tissue-level responses - is still rare. Here, we report our recent progress toward this end with a hybrid stochastic GC framework developed on the Cellular Potts Model-based CompuCell3D platform. Tellurium is used to simulate the B cell intracellular molecular network comprising NF-κB, FOXO1, MYC, AP4, CXCR4, and BLIMP1 that responds to B cell receptor (BCR) and CD40-mediated signaling. The molecular outputs of the network drive the spatiotemporal behaviors of B cells, including cyclic migration between the dark zone (DZ) and light zone (LZ) via chemotaxis; clonal proliferative bursts, somatic hypermutation, and DNA damage-induced apoptosis in the DZ; and positive selection, apoptosis via a death timer, and emergence of plasma cells in the LZ. Our simulations are able to recapitulate key molecular, cellular, and morphological GC events including B cell population growth, affinity maturation, and clonal dominance. This novel modeling framework provides an open-source, customizable, and multiscale virtual GC simulation platform that enables qualitative and quantitative in silico investigations of a range of mechanic and applied research questions in future.

Exploring the reprogramming potential of B cells and comprehending its clinical and therapeutic perspective

Initiating from multipotent progenitors, the lineages extrapolated from hematopoietic stem cells are determined by transcription factors specific to each of them. The commitment factors assist in the differentiation of progenitor cells into terminally differentiated cells. B lymphocytes constitute a population of cells that expresses clonally diverse cell surface immunoglobulin (Ig) receptors specific to antigenic epitopes. B cells are a significant facet of the adaptive immune system. The secreted antibodies corresponding to the B cell recognize the antigens via the B cell receptor (BCR). Following antigen recognition, the B cell is activated and thereafter undergoes clonal expansion and proliferation to become memory B cells. The essence of 'cellular reprogramming' has aided in reliably altering the cells to desired tissue type. The potential of reprogramming has been harnessed to decipher and find solutions for various genetically inherited diseases and degenerative disorders. B lymphocytes can be reprogrammed to their initial naive state from where they get differentiated into any lineage or cell type similar to a pluripotent stem cell which can be accomplished by the deletion of master regulators of the B cell lineage. B cells can be reprogrammed into pluripotent stem cells and also can undergo transdifferentiation at the midway of cell differentiation to other cell types. Mandated expression of C/EBP in specialized B cells corresponds to their fast and effective reprogramming into macrophages, reversing the cell fate of these lymphocytes and allowing them to differentiate freshly into other types of cells. The co-expression of C/EBPα and OKSM (Oct4, Sox2, Klf4, c-Myc) amplified the reprogramming efficiency of B lymphocytes. Various human somatic cells including the immune cells are compliant to reprogramming which paves a path for opportunities like autologous tissue grafts, blood transfusion, and cancer immunotherapy. The ability to reprogram B cells offers an unprecedented opportunity for developing a therapeutic approach for several human diseases. Here, we will focus on all the proteins and transcription factors responsible for the developmental commitment of B lymphocytes and how it is harnessed in various applications.

Coupled mutual inhibition and mutual activation motifs as tools for cell-fate control

Multistability is central to biological systems as it plays a crucial role in adaptation, evolvability, and differentiation. The presence of positive feedback loops can enable multistability. The simplest of such feedback loops are a) a mutual inhibition loop (MI), b) a mutual activation loop (MA), and c) self-activation, all three of them known to give rise to bistability. However, the characteristic differences in the bistability exhibited by these motifs are relatively less understood. Here, we use dynamical simulations across a large ensemble of parameter sets and initial conditions to study the bistability characteristics of these motifs. Furthermore, we investigate the utility of these motifs for achieving coordinated expression through cyclic and parallel coupling amongst them. Our analysis revealed that MI-based architectures offer discrete and robust control over gene expression, multistability, and coordinated expression among multiple genes, as compared to MA-based architectures. We then devised a combination of MI and MA architectures to improve coordination and multistability. Such designs help improve our understanding of the control structures involved in robust cell-fate decisions and provide a way to achieve controlled decision-making in synthetic systems.

A New Bistable Switch Model of Alzheimer’s Disease Pathogenesis

We propose a model to explain the pathogenesis of Alzheimer’s disease (AD) based on the theory that any disease affecting a healthy organism originates from a bistable feedback loop that shifts the system from a physiological to a pathological condition. We focused on the known double inhibitory loop involving the cellular prion protein (PrPC) and the enzyme BACE1 that produces amyloid-beta (Aβ) peptides. BACE1 is inhibited by PrPC, but its inhibitory activity is lost when PrPC binds to Aβ oligomers (Aβo). Excessive Aβo formation would switch the loop to a pathogenic condition involving the Aβo-PrPC-mGluR5 complex, Fyn kinase activation, tau, and NMDAR phosphorylation, ultimately leading to neurodegeneration. Based on the emerging role of cyclic nucleotides in Aβ production, and thereby in synaptic plasticity and cognitive processes, cAMP and cGMP can be considered as modulatory factors capable of inducing the transition from a physiological steady state to a pathogenic one. This would imply that critical pharmacological targets for AD treatment lie within pathways that lead to an imbalance of cyclic nucleotides in neurons. If this hypothesis is confirmed, it will provide precise indications for the development of preventive or therapeutic treatments for the disease.

The transcriptional regulator HDP1 controls expansion of the inner membrane complex during early sexual differentiation of malaria parasites

Transmission of Plasmodium falciparum and other malaria parasites requires their differentiation from asexual blood stages into gametocytes, the non-replicative sexual stage necessary to infect the mosquito vector. This transition involves changes in gene expression and chromatin reorganization that result in the activation and silencing of stage-specific genes. However, the genomes of malaria parasites have been noted for their limited number of transcriptional and chromatin regulators, and the molecular mediators of these changes remain largely unknown. We recently identified homeodomain protein 1 (HDP1) as a DNA-binding protein, first expressed in gametocytes, that enhances the expression of key genes critical for early sexual differentiation. The discovery of HDP1 marks a new class of transcriptional regulator in malaria parasites outside of the better-characterized ApiAP2 family. Here, using molecular biology, biochemistry and microscopy techniques, we show that HDP1 is essential for gametocyte maturation, facilitating the necessary upregulation of inner membrane complex components during early gametocytogenesis that gives P. falciparum gametocytes their characteristic shape.

Resilience function uncovers the critical transitions in cancer initiation

Considerable evidence suggests that during the progression of cancer initiation, the state transition from wellness to disease is not necessarily smooth but manifests switch-like nonlinear behaviors, preventing the cancer prediction and early interventional therapy for patients. Understanding the mechanism of such wellness-to-disease transitions is a fundamental and challenging task. Despite the advances in flux theory of nonequilibrium dynamics and 'critical slowing down'-based system resilience theory, a system-level approach still lacks to fully describe this state transition. Here, we present a novel framework (called bioRFR) to quantify such wellness-to-disease transition during cancer initiation through uncovering the biological system's resilience function from gene expression data. We used bioRFR to reconstruct the biologically and dynamically significant resilience functions for cancer initiation processes (e.g. BRCA, LUSC and LUAD). The resilience functions display the similar resilience pattern with hysteresis feature but different numbers of tipping points, which implies that once the cell become cancerous, it is very difficult or even impossible to reverse to the normal state. More importantly, bioRFR can measure the severe degree of cancer patients and identify the personalized key genes that are associated with the individual system's state transition from normal to tumor in resilience perspective, indicating that bioRFR can contribute to personalized medicine and targeted cancer therapy.

Evaluation of Cr(VI) Reducing Capability of Shewanella putrefaciens (MTTC8410) and Optimization of Operational Parameters

Bioremediation is an important technology to remediate the chromium (Cr) contaminated soil and water. In this study, Shewanella putrefaciens (MTTC8410) was used to investigate the influence of carbon concentration, pH, and temperature on reduction of hexavalent chromium [Cr(VI)] into trivalent chromium [Cr(III)]. The increased bacterial growth rate was significantly reduced the Cr(VI) concentration. In batch mode experiments, 1% starch recorded the highest reduction of Cr(VI) (90%) followed by 1% glucose (88% reduction) and a reduction of 77% was by 1% cellulose. By using various pH conditions the maximum Cr(VI) reduction was achieved at pH 7.0. In this experiment the maximum Cr(VI) reduction (75%) was observed at 35°C, followed by 30°C with 62% of Cr(VI) reduction. Bioreactor analysis revealed the highest reduction of Cr(VI) (88%) in unsterile tannery effluent. The significant levels of physico- chemical parameters were reduced in unsterile tannery effluent, as compared to the sterile tannery effluent. The experimental results revealed that the S. putrefaciens (MTTC8410) could be used as a potential bacterial strain for reduction of Cr(VI) from contaminated groundwater.

From Genes to Transcripts, a Tightly Regulated Journey in Plasmodium

Over the past decade, we have witnessed significant progresses in understanding gene regulation in Apicomplexa including the human malaria parasite, Plasmodium falciparum. This parasite possesses the ability to convert in multiple stages in various hosts, cell types, and environments. Recent findings indicate that P. falciparum is talented at using efficient and complementary molecular mechanisms to ensure a tight control of gene expression at each stage of its life cycle. Here, we review the current understanding on the contribution of the epigenome, atypical transcription factors, and chromatin organization to regulate stage conversion in P. falciparum. The adjustment of these regulatory mechanisms occurring during the progression of the life cycle will be extensively discussed.

A multistationary loop model of ALS unveils critical molecular interactions involving mitochondria and glucose metabolism

Amyotrophic lateral sclerosis (ALS) is a poor-prognosis disease with puzzling pathogenesis and inconclusive treatments. We develop a mathematical model of ALS based on a system of interactive feedback loops, focusing on the mutant SOD1G93A mouse. Misfolded mutant SOD1 aggregates in motor neuron (MN) mitochondria and triggers a first loop characterized by oxidative phosphorylation impairment, AMP kinase over-activation, 6-phosphofructo-2-kinase (PFK3) rise, glucose metabolism shift from pentose phosphate pathway (PPP) to glycolysis, cell redox unbalance, and further worsening of mitochondrial dysfunction. Oxidative stress then triggers a second loop, involving the excitotoxic glutamatergic cascade, with cytosolic Ca2+ overload, increase of PFK3 expression, and further metabolic shift from PPP to glycolysis. Finally, cytosolic Ca2+ rise is also detrimental to mitochondria and oxidative phosphorylation, thus closing a third loop. These three loops are overlapped and positive (including an even number of inhibitory steps), hence they form a candidate multistationary (bistable) system. To describe the system dynamics, we model the interactions among the functional agents with differential equations. The system turns out to admit two stable equilibria: the healthy state, with high oxidative phosphorylation and preferential PPP, and the pathological state, with AMP kinase activation, PFK3 over expression, oxidative stress, excitotoxicity and MN degeneration. We demonstrate that the loop system is monotone: all functional agents consistently act toward the healthy or pathological condition, depending on low or high mutant SOD1 input. We also highlight that molecular interactions involving PFK3 are crucial, as their deletion disrupts the system's bistability leading to a single healthy equilibrium point. Hence, our mathematical model unveils that promising ALS management strategies should be targeted to mechanisms that keep low PFK3 expression and activity within MNs.

Targeting Aryl hydrocarbon receptor for next-generation immunotherapies: Selective modulators (SAhRMs) versus rapidly metabolized ligands (RMAhRLs)

Aryl Hydrocarbon Receptor (AhR) constitutes a major network hub of genomic and non-genomic signaling pathways, connecting host's immune cells to environmental factors. It shapes innate and adaptive immune processes to environmental stimuli with species-, cell- and tissue-type dependent specificity. Although an ever increasing number of studies has thrust AhR into the limelight as attractive target for the development of next-generation immunotherapies, concerns exist on potential safety issues associated with small molecule modulation of the receptor. Selective AhR modulators (SAhRMs) and rapidly metabolized AhR ligands (RMAhRLs) are two classes of receptor agonists that are emerging as interesting lead compounds to bypass AhR-related toxicity in favor of therapeutic effects. In this article, we discuss SAhRMs and RMAhRLs reported in literature, covering concepts underlying their definitions, specific binding modes, structure-activity relationships and AhR-mediated functions.

From Discrete to Continuous Modeling of Lymphocyte Development and Plasticity in Chronic Diseases

The molecular events leading to differentiation, development, and plasticity of lymphoid cells have been subject of intense research due to their key roles in multiple pathologies, such as lymphoproliferative disorders, tumor growth maintenance and chronic diseases. The emergent roles of lymphoid cells and the use of high-throughput technologies have led to an extensive accumulation of experimental data allowing the reconstruction of gene regulatory networks (GRN) by integrating biochemical signals provided by the microenvironment with transcriptional modules of lineage-specific genes. Computational modeling of GRN has been useful for the identification of molecular switches involved in lymphoid specification, prediction of microenvironment-dependent cell plasticity, and analyses of signaling events occurring downstream the activation of antigen recognition receptors. Among most common modeling strategies to analyze the dynamical behavior of GRN, discrete dynamic models are widely used for their capacity to capture molecular interactions when a limited knowledge of kinetic parameters is present. However, they are less powerful when modeling complex systems sensitive to biochemical gradients. To compensate it, discrete models may be transformed into regulatory networks that includes state variables and parameters varying within a continuous range. This approach is based on a system of differential equations dynamics with regulatory interactions described by fuzzy logic propositions. Here, we discuss the applicability of this method on modeling of development and plasticity processes of adaptive lymphocytes, and its potential implications in the study of pathological landscapes associated to chronic diseases.

Dynamical systems approaches to personalized medicine

The complexity of the human body is a major roadblock to diagnosis and treatment of disease. Individuals may be diagnosed with the same disease but exhibit different biomarker profiles or physiological changes and, importantly, they may respond differently to the same risk factors and the same treatment. There is no doubt that computational methods of data analysis and interpretation must be developed for medicine to evolve from the traditional population-based approaches to personalized treatment strategies. We discuss how computational systems biology is contributing to this current evolution.

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

Single-cell RNA sequencing reveals a signature of sexual commitment in malaria parasites

Pathogens have to balance transmission with persistence. For Plasmodium falciparum, the most widespread and virulent malaria parasite, persistence within its human host requires continuous asexual replication within red blood cells, while its mosquito-borne transmission depends on intra-erythrocytic differentiation into non-replicating sexual stages called gametocytes. Commitment to either fate is determined during the preceding cell cycle that begins with invasion by a single, asexually committed merozoite and ends, 48 hours later, with a schizont releasing newly formed merozoites, all committed to either continued asexual replication or differentiation into gametocytes. Sexual commitment requires the transcriptional activation of ap2-g (PF3D7_1222600), the master regulator of sexual development, from an epigenetically silenced state during asexual replication. AP2-G expression during this 'commitment cycle' prepares gene expression in nascent merozoites to initiate sexual development through a hitherto unknown mechanism. To maintain a persistent infection, the expression of ap2-g is limited to a sub-population of parasites (1-30%, depending on genetic background and growth conditions). As sexually committed schizonts comprise only a sub-population and are morphologically indistinguishable from their asexually committed counterparts, defining their characteristic gene expression has been difficult using traditional, bulk transcriptome profiling. Here we use highly parallel, single-cell RNA sequencing of malaria cultures undergoing sexual commitment to determine the transcriptional changes induced by AP2-G within this sub-population. By analysing more than 18,000 single parasite transcriptomes from a conditional AP2-G knockdown line and NF54 wild-type parasites at multiple stages of development, we show that sexually committed, AP2-G⁺ mature schizonts specifically upregulate additional regulators of gene expression, including other AP2 transcription factors, histone-modifying enzymes, and regulators of nucleosome positioning. These epigenetic regulators may act to facilitate the expression and/or repression of genes that are necessary for the initiation of gametocyte development in the subsequent cell cycle.

The Influence of Human Interindividual Variability on the Low-Dose Region of Dose-Response Curve Induced by 2,3,7,8-Tetrachlorodibenzo-p-Dioxin in Primary B Cells

The influence of interindividual variability is not typically assessed in traditional toxicological studies. Given that chemical exposures occur in heterogeneous populations, this knowledge gap has the potential to cause undue harm within the realms of public health and industrial and municipal finances. A recent report from the National Research Council (NRC) suggests that when accounting for interindividual variation in responses, traditionally assumed nonlinear dose-response relationships (DRRs) for noncancer-causing endpoints would better be explained with a linear relationship within the low-dose region. To address this knowledge gap and directly test the NRC's assumption, this study focused on assessing the DRR between 2,3,7,8-tetracholorodibenzo-p-dioxin (TCDD) exposure and immune suppression in a cohort of unique human donors. Human B cells were isolated from 51 individual donors and treated with logarithmically increasing concentrations of TCDD (0-30 nM TCDD). Two endpoints sensitive to TCDD were assessed: (1) number of IgM-secreting B cells and (2) quantity of IgM secreted. The results show that TCDD significantly suppressed both the number of IgM-secreting B cells and the quantity of IgM secreted (P < .05). Statistical model comparisons indicate that the low-dose region of the two DRRs is best explained with a nonlinear relationship. Rather than assuming low-dose linearity for all noncancer-causing DRRs, our study suggests the need to consider the specific mode of action of toxicants and pharmaceuticals during risk-management decision making.

A Network Model to Describe the Terminal Differentiation of B Cells

Terminal differentiation of B cells is an essential process for the humoral immune response in vertebrates and is achieved by the concerted action of several transcription factors in response to antigen recognition and extracellular signals provided by T-helper cells. While there is a wealth of experimental data regarding the molecular and cellular signals involved in this process, there is no general consensus regarding the structure and dynamical properties of the underlying regulatory network controlling this process. We developed a dynamical model of the regulatory network controlling terminal differentiation of B cells. The structure of the network was inferred from experimental data available in the literature, and its dynamical behavior was analyzed by modeling the network both as a discrete and a continuous dynamical systems. The steady states of these models are consistent with the patterns of activation reported for the Naive, GC, Mem, and PC cell types. Moreover, the models are able to describe the patterns of differentiation from the precursor Naive to any of the GC, Mem, or PC cell types in response to a specific set of extracellular signals. We simulated all possible single loss- and gain-of-function mutants, corroborating the importance of Pax5, Bcl6, Bach2, Irf4, and Blimp1 as key regulators of B cell differentiation process. The model is able to represent the directional nature of terminal B cell differentiation and qualitatively describes key differentiation events from a precursor cell to terminally differentiated B cells.

Generation of antibody-producing cells through terminal B cell differentiation represents a good model to study the formation of multiple effector cells from a progenitor cell type. This process is controlled by the action of several molecules that maintain cell type specific programs in response to cytokines, antigen recognition and the direct contact with T helper cells, forming a complex regulatory network. While there is a large body of experimental data regarding some of the key molecules involved in this process and there have been several efforts to reconstruct the underlying regulatory network, a general consensus about the structure and dynamical behavior of this network is lacking. Moreover, it is not well understood how this network controls the establishment of specific B cell expression patterns and how it responds to specific external signals. We present a model of the regulatory network controlling terminal B cell differentiation and analyze its dynamical behavior under normal and mutant conditions. The model recovers the patterns of differentiation of B cells and describes a large set of gain- and loss-of-function mutants. This model provides an unified framework to generate qualitative descriptions to interpret the role of intra- and extracellular regulators of B cell differentiation.

Indole and Tryptophan Metabolism: Endogenous and Dietary Routes to Ah Receptor Activation

The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor recognized for its role in xenobiotic metabolism. The physiologic function of AHR has expanded to include roles in immune regulation, organogenesis, mucosal barrier function, and the cell cycle. These functions are likely dependent upon ligand-mediated activation of the receptor. High-affinity ligands of AHR have been classically defined as xenobiotics, such as polychlorinated biphenyls and dioxins. Identification of endogenous AHR ligands is key to understanding the physiologic functions of this enigmatic receptor. Metabolic pathways targeting the amino acid tryptophan and indole can lead to a myriad of metabolites, some of which are AHR ligands. Many of these ligands exhibit species selective preferential binding to AHR. The discovery of specific tryptophan metabolites as AHR ligands may provide insight concerning where AHR is activated in an organism, such as at the site of inflammation and within the intestinal tract.

Inhibition of cathepsin B activity by 2,3,7,8-tetrachlorodibenzo-p-dioxin

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is the most potent toxic isomer in the dioxin-like family. Due to its resistance to metabolic degradation, this ubiquitous environmental pollutant readily accumulates in multiple organs. Cathepsin B is a lysosomal cysteine protease playing an essential role in the intracellular protein turnover. Alterations in its expression, activity, and localization may facilitate the development of many pathologies, including cancer. TCDD, due to its extremely lipophilic nature, may diffuse through biological membranes and affect lysosomal enzymes, including cathepsins. Therefore, in this study we performed two enzymatic assays, spectrofluorimetry and gelatin zymography, in order to evaluate the effect of TCDD on purified bovine cathepsin B. We showed that the dioxin decreases the enzyme's activity in a dose-dependent manner. The reversibility of TCDD-induced inhibition of the protease was also examined, suggesting that TCDD does not bind covalently to the enzyme's active site, acting rather as a reversible inhibitor.

Molecular signaling network motifs provide a mechanistic basis for cellular threshold responses

BACKGROUND

Increasingly, there is a move toward using in vitro toxicity testing to assess human health risk due to chemical exposure. As with in vivo toxicity testing, an important question for in vitro results is whether there are thresholds for adverse cellular responses. Empirical evaluations may show consistency with thresholds, but the main evidence has to come from mechanistic considerations.

OBJECTIVES

Cellular response behaviors depend on the molecular pathway and circuitry in the cell and the manner in which chemicals perturb these circuits. Understanding circuit structures that are inherently capable of resisting small perturbations and producing threshold responses is an important step towards mechanistically interpreting in vitro testing data.

METHODS

Here we have examined dose-response characteristics for several biochemical network motifs. These network motifs are basic building blocks of molecular circuits underpinning a variety of cellular functions, including adaptation, homeostasis, proliferation, differentiation, and apoptosis. For each motif, we present biological examples and models to illustrate how thresholds arise from specific network structures.

DISCUSSION AND CONCLUSION

Integral feedback, feedforward, and transcritical bifurcation motifs can generate thresholds. Other motifs (e.g., proportional feedback and ultrasensitivity)produce responses where the slope in the low-dose region is small and stays close to the baseline. Feedforward control may lead to nonmonotonic or hormetic responses. We conclude that network motifs provide a basis for understanding thresholds for cellular responses. Computational pathway modeling of these motifs and their combinations occurring in molecular signaling networks will be a key element in new risk assessment approaches based on in vitro cellular assays.

Antagonism of cannabinoid receptor 2 pathway suppresses IL-6-induced immunoglobulin IgM secretion

Background

Cannabinoid receptor 2 (CB2) is expressed predominantly in the immune system, particularly in plasma cells, raising the possibility that targeting the CB2 pathway could yield an immunomodulatory effect. Although the role of CB2 in mediating immunoglobulin class switching has been reported, the effects of targeting the CB2 pathway on immunoglobulin secretion per se remain unclear.

Methods

Human B cell line SKW 6.4, which is capable of differentiating into IgM-secreting cells once treated with human IL-6, was employed as the cell model. SKW 6.4 cells were incubated for 4 days with CB2 ligands plus IL-6 (100 U/ml). The amount of secreted IgM was determined by an ELISA. Cell proliferation was determined by the ³H-Thymidine incorporation assay. Signal molecules involved in the modulation of IgM secretion were examined by real-time RT-PCR and Western blot analyses or by using their specific inhibitors.

Results

We demonstrated that CB2 inverse agonists SR144528 and AM630, but not CB2 agonist HU308 or CB1 antagonist SR141716, effectively inhibited IL-6-induced secretion of soluble IgM without affecting cell proliferation as measured by thymidine uptake. SR144528 alone had no effects on the basal levels of IgM in the resting cells. These effects were receptor mediated, as pretreatment with CB2 agonist abrogated SR144528-mediated inhibition of IL-6 stimulated IgM secretion. Transcription factors relevant to B cell differentiation, Bcl-6 and PAX5, as well as the protein kinase STAT3 pathway were involved in the inhibition of IL-6-induced IgM by SR144528.

Conclusions

These results uncover a novel function of CB2 antagonists and suggest that CB2 ligands may be potential modulators of immunoglobulin secretion.

Ultrasensitive response motifs: basic amplifiers in molecular signalling networks

Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input–output relationship that is steeper than the Michaelis–Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm.

All-or-none suppression of B cell terminal differentiation by environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin

Many environmental contaminants can disrupt the adaptive immune response. Exposure to the ubiquitous aryl hydrocarbon receptor (AhR) ligand 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other agonists suppresses the antibody response. The underlying pathway mechanism by which TCDD alters B cell function is not well understood. The present study investigated the mechanism of AhR-mediated pathways and mode of suppression by which TCDD perturbs terminal differentiation of B cells to plasma cells and thereby impairs antibody production. An integrated approach combining computational pathway modeling and in vitro assays with primary mouse B cells activated by lipopolysaccharide was employed. We demonstrated that suppression of the IgM response by TCDD occurs in an all-or-none (binary) rather than graded mode: i.e., it reduces the number of IgM-secreting cells in a concentration-dependent manner without affecting the IgM content in individual plasma cells. The mathematical model of the gene regulatory circuit underpinning B cell differentiation revealed that two previously identified AhR-regulated pathways, inhibition of signaling protein AP-1 and activation of transcription factor Bach2, could account for the all-or-none mode of suppression. Both pathways disrupt the operation of a bistable-switch circuit that contains transcription factors Bcl6, Prdm1, Pax5, and Bach2 and regulates B cell fate. The model further predicted that by transcriptionally activating Bach2, TCDD might delay B cell differentiation and increase the likelihood of isotype switching, thereby altering the antibody repertoire. In conclusion, the present study revealed the mode and specific pathway mechanisms by which the environmental immunosuppressant TCDD suppresses B cell differentiation.

Modeling drug- and chemical-induced hepatotoxicity with systems biology approaches

We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of “toxicity pathways” is described in the context of the 2007 US National Academies of Science report, “Toxicity testing in the 21st Century: A Vision and A Strategy.” Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity) – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular “virtual tissue” model of the liver lobule that combines molecular circuits in individual hepatocytes with cell–cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the aryl hydrocarbon receptor toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsym™) to understand drug-induced liver injury (DILI), the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

B cell activation triggered by the formation of the small receptor cluster: a computational study

We proposed a spatially extended model of early events of B cell receptors (BCR) activation, which is based on mutual kinase-receptor interactions that are characteristic for the immune receptors and the Src family kinases. These interactions lead to the positive feedback which, together with two nonlinearities resulting from the double phosphorylation of receptors and Michaelis-Menten dephosphorylation kinetics, are responsible for the system bistability. We demonstrated that B cell can be activated by a formation of a tiny cluster of receptors or displacement of the nucleus. The receptors and Src kinases are activated, first locally, in the locus of the receptor cluster or the region where the cytoplasm is the thinnest. Then the traveling wave of activation propagates until activity spreads over the whole cell membrane. In the models in which we assume that the kinases are free to diffuse in the cytoplasm, we found that the fraction of aggregated receptors, capable to initiate B cell activation decreases with the decreasing thickness of cytoplasm and decreasing kinase diffusion. When kinases are restricted to the cell membrane - which is the case for most of the Src family kinases - even a cluster consisting of a tiny fraction of total receptors becomes activatory. Interestingly, the system remains insensitive to the modest changes of total receptor level. The model provides a plausible mechanism of B cells activation due to the formation of small receptors clusters collocalized by binding of polyvalent antigens or arising during the immune synapse formation.

B cells are activated in response to binding of appropriate ligands, which induces the aggregation of B cell receptors. The formation of even small clusters containing less than 1% of all the receptors is sufficient for activation. This observation led us to a model in which the receptor cluster serves only as a switch that turns on the activation process involving also the remaining receptors. The idea of the model exploits the fact the Src kinase - BCR system is bistable, and thus its local activation may start the propagation of a traveling wave, which spreads activation over the entire membrane. We found that the minimal size of the activatory cluster decreases with the thickness of the cytoplasm and kinase diffusion coefficient. It is particularly small when kinases are restricted to the membrane. These findings are consistent with the properties of B cells, which prior to activation have extremely thin cytoplasmic layer and in which Src family kinases (interacting with the receptors) are tethered to the membrane.

Changes in DNA methylation and gene expression during 2,3,7,8-tetrachlorodibenzo-p-dioxin-induced suppression of the lipopolysaccharide-stimulated IgM response in splenocytes

Lipopolysaccharide (LPS) is a bacterial endotoxin and a potent B-cell activator capable of inducing a humoral immune response. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a well-established immunotoxicant that can suppress humoral immune responses, including those initiated by LPS stimulation. In murine models, TCDD-induced suppression of the LPS-activated primary immunoglobulin M (IgM) response is observed both in vivo and in vitro and is typically evaluated as a decrease in the number of IgM antibody-forming cells. The TCDD-induced suppression of the primary humoral immune response occurs, at least in part, upstream of IgM production. The current study was designed as an initial test of our hypothesis that altered DNA methylation, an epigenetic event, is involved in the LPS-induced IgM response by splenocytes as is the suppression of this response by TCDD. Splenocyte-derived DNA from mice treated in vivo with sesame oil + PBS, LPS, TCDD, or LPS + TCDD was used for the current investigation. DNA methylation was evaluated using a technique that permits assessment of the methylation status of multiple genomic regions simultaneously in an unbiased fashion (no specific genes or genomic regions are preselected). Additionally, the expression of selected genes was determined. Our results indicate that treatment with LPS or TCDD can alter DNA methylation and, importantly, combined TCDD + LPS results in altered DNA methylation that was not simply the addition of the changes discerned in the individual treatment groups. Thus, we have identified cross talk between LPS and TCDD at the level of DNA methylation and gene expression.

The long winding road toward understanding the molecular mechanisms for B-cell suppression by 2,3,7,8-tetrachlorodibenzo-p-dioxin

Suppression of humoral immune responses by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) was first reported in the mid-1970s. Since this initial observation, much effort has been devoted by many laboratories toward elucidation of the cellular and molecular mechanisms responsible for the profound impairment of humoral immune responses by TCDD, which is characterized by decreased B cell to plasma cell differentiation and suppression of immunoglobulin production. These efforts have led to a significant body of research demonstrating a direct effect of TCDD on B-cell maturation and function as well as a requisite but as yet undefined role of the aryl hydrocarbon receptor (AhR) in these effects. Likewise, a number of molecular targets putatively involved in mediating B-cell dysfunction by TCDD, and other AhR ligands, have been identified. However, our current understanding has primarily relied on findings from mouse models, and the translation of this knowledge to effects on human B cells and humoral immunity in humans is less clear. Therefore, a current challenge is to determine how TCDD and the AhR affect human B cells. Efforts have been made in this direction but continued progress in developing adequate human models is needed. An in-depth discussion of these advances and limitations in elucidating the cellular and molecular mechanisms putatively involved in the suppression of B-cell function by TCDD as well as the implications on human diseases associated in epidemiological studies with exposure to TCDD and dioxin-like compounds is the primary focus of this review.

Stochastic modeling of B lymphocyte terminal differentiation and its suppression by dioxin

Background

Upon antigen encounter, naïve B lymphocytes differentiate into antibody-secreting plasma cells. This humoral immune response is suppressed by the environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other dioxin-like compounds, which belong to the family of aryl hydrocarbon receptor (AhR) agonists.

Results

To achieve a better understanding of the immunotoxicity of AhR agonists and their associated health risks, we have used computer simulations to study the behavior of the gene regulatory network underlying B cell terminal differentiation. The core of this network consists of two coupled double-negative feedback loops involving transcriptional repressors Bcl-6, Blimp-1, and Pax5. Bifurcation analysis indicates that the feedback network can constitute a bistable system with two mutually exclusive transcriptional profiles corresponding to naïve B cells and plasma cells. Although individual B cells switch to the plasma cell state in an all-or-none fashion when stimulated by the polyclonal activator lipopolysaccharide (LPS), stochastic fluctuations in gene expression make the switching event probabilistic, leading to heterogeneous differentiation response among individual B cells. Moreover, stochastic gene expression renders the dose-response behavior of a population of B cells substantially graded, a result that is consistent with experimental observations. The steepness of the dose response curve for the number of plasma cells formed vs. LPS dose, as evaluated by the apparent Hill coefficient, is found to be inversely correlated to the noise level in Blimp-1 gene expression. Simulations illustrate how, through AhR-mediated repression of the AP-1 protein, TCDD reduces the probability of LPS-stimulated B cell differentiation. Interestingly, stochastic simulations predict that TCDD may destabilize the plasma cell state, possibly leading to a reversal to the B cell phenotype.

Conclusion

Our results suggest that stochasticity in gene expression, which renders a graded response at the cell population level, may have been exploited by the immune system to launch humoral immune response of a magnitude appropriately tuned to the antigen dose. In addition to suppressing the initiation of the humoral immune response, dioxin-like compounds may also disrupt the maintenance of the acquired immunity.

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell biology has advanced rapidly with increasing availability of new data and powerful simulation techniques, a quantitative orientation is still lacking in life sciences education to make efficient use of these new tools to implement the new toxicity testing paradigm. A revamped undergraduate curriculum in the biological sciences including compulsory courses in mathematics and analysis of dynamical systems is required to address this gap. In parallel, dissemination of computational systems biology techniques and other analytical tools among practicing toxicologists and risk assessment professionals will help accelerate implementation of the new toxicity testing vision.