Intracellular Regulatory Networks Research Articles

Quantitative omnigenic model discovers interpretable genome-wide associations

As their statistical power grows, genome-wide association studies (GWAS) have identified an increasing number of loci underlying quantitative traits of interest. These loci are scattered throughout the genome and are individually responsible only for small fractions of the total heritable trait variance. The recently proposed omnigenic model provides a conceptual framework to explain these observations by postulating that numerous distant loci contribute to each complex trait via effect propagation through intracellular regulatory networks. We formalize this conceptual framework by proposing the "quantitative omnigenic model" (QOM), a statistical model that combines prior knowledge of the regulatory network topology with genomic data. By applying our model to gene expression traits in yeast, we demonstrate that QOM achieves similar gene expression prediction performance to traditional GWAS with hundreds of times less parameters, while simultaneously extracting candidate causal and quantitative chains of effect propagation through the regulatory network for every individual gene. We estimate the fraction of heritable trait variance in cis- and in trans-, break the latter down by effect propagation order, assess the trans- variance not attributable to transcriptional regulation, and show that QOM correctly accounts for the low-dimensional structure of gene expression covariance. We furthermore demonstrate the relevance of QOM for systems biology, by employing it as a statistical test for the quality of regulatory network reconstructions, and linking it to the propagation of nontranscriptional (including environmental) effects.

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 bimetallic dual-targeting nanoplatform for combinational ferroptosis activation/epigenetic regulation/photothermal therapy against breast cancer and tumor microenvironment remodeling

Restricted by the complex intracellular ferroptosis regulatory networks, single ferroptotic therapy against breast cancer (BC) yields limited therapeutic outcomes. Therefore, novel combination modes are being widely attempted; however, the interactions between different treatments are still less studied. Herein, we propose a combinational pattern by constructing a novel nanoplatform (T-FeCo/P) composed of Panobinostat (histone deacetylase inhibitor)-loaded iron (Fe)/cobalt (Co)-based metal-organic framework with surface modification of telmisartan for dual 4T1 cell/cancer-associated fibroblast (CAF) targeting. T-FeCo/P exhibits good photothermal performance and forcefully triggers cellular ferroptosis, and the dopant of Fe realizes stronger ferroptosis activation than the corresponding single-metal system. Interestingly, for the first time, Panobinostat is elucidated to promote ferroptosis by inhibiting SLC7A11 transcription and regulating thioredoxin binding protein 2 (TBP2)/thioredoxin (Trx) axis. For tumor microenvironment (TME) remodeling, T-FeCo/P specifically kills CAFs, thus destroying extracellular matrix and retarding C-X-C motif chemokine ligand 12 (CXCL12) secretion, which are beneficial to intratumoral drug penetration and cytotoxic T lymphocyte infiltration. Also, this CAF elimination probably sensibilizes ferroptosis by regulating neurofibromatosis type 2 (NF2)-yes associated protein (YAP) pathway and reducing myeloid-derived suppressor cell infiltration. Our experimental data support T-FeCo/P’s tumoricidal activity thanks to the combined ferroptosis activation, epigenetic regulation, photothermal therapy and TME re-education, providing a mighty pattern for BC treatment and constituting a substantial addition to ferroptosis sensitization.

The S2 Subunit of Infectious Bronchitis Virus Affects Abl2-Mediated Syncytium Formation.

The S2 subunit serves a crucial role in infectious bronchitis virus (IBV) infection, particularly in facilitating membrane fusion. Using reverse genetic techniques, mutant strains of the S2 locus exhibited substantially different syncytium-forming abilities in chick embryonic kidney cells. To determine the precise formation mechanism of syncytium, we demonstrated the co-ordinated role of Abl2 and its mediated cytoskeletal regulatory pathway within the S2 subunit. Using a combination of fluorescence quantification, RNA silencing, and protein profiling techniques, the functional role of S2 subunits in IBV-infected cells was exhaustively determined. Our findings imply that Abl2 is not the primary cytoskeletal regulator, the viral S2 component is involved in indirect regulation, and the three different viral strains activate various cytoskeletal regulatory pathways through Abl2. CRK, CRKL, ABI1, NCKAP1, and ENAH also play a role in cytoskeleton regulation. Our research provides a point of reference for the development of an intracellular regulatory network for the S2 subunit and a foundation for the rational design of antiviral drug targets against Abl2.

Genome-wide identification of potential odontogenic genes involved in the dental epithelium-mesenchymal interaction during early odontogenesis

BackgroundEpithelium-mesenchymal interactions are involved in odontogenic processes. Previous studies have focused on the intracellular signalling regulatory network in tooth development, but the functions of extracellular regulatory molecules have remained unclear. This study aims to explore the gene profile of extracellular proteoglycans and their glycosaminoglycan chains potentially involved in dental epithelium-mesenchymal interactions using high-throughput sequencing to provide new understanding of early odontogenesis.ResultsWhole transcriptome profiles of the mouse dental epithelium and mesenchyme were investigated by RNA sequencing (RNA-seq). A total of 1,281 and 1,582 differentially expressed genes were identified between the dental epithelium and mesenchyme at E11.5 and E13.5, respectively. Enrichment analysis showed that extracellular regions and ECM-receptor interactions were significantly enriched at both E11.5 and E13.5. Polymerase chain reaction analysis confirmed that the extracellular proteoglycan family exhibited distinct changes during epithelium-mesenchymal interactions. Most proteoglycans showed higher transcript levels in the dental mesenchyme, whereas only a few were upregulated in the epithelium at both stages. In addition, 9 proteoglycans showed dynamic expression changes between these two tissue compartments. Gpc4, Sdc2, Spock2, Dcn and Lum were expressed at higher levels in the dental epithelium at E11.5, whereas their expression was significantly higher in the dental mesenchyme at E13.5, which coincides with the odontogenic potential shift. Moreover, the glycosaminoglycan biosynthetic enzymes Ext1, Hs3st1/5, Hs6st2/3, Ndst3 and Sulf1 also exhibited early upregulation in the epithelium but showed markedly higher expression in the mesenchyme after the odontogenic potential shift.ConclusionThis study reveals the dynamic expression profile of extracellular proteoglycans and their biosynthetic enzymes during the dental epithelium–mesenchymal interaction. This study offers new insight into the roles of extracellular proteoglycans and their distinct sulfation underlying early odontogenesis.

Emergent activity, heterogeneity, and robustness in a calcium feedback model of the sinoatrial node

The sinoatrial node (SAN) is the primary pacemaker of the heart. SAN activity emerges at an early point in life and maintains a steady rhythm for the lifetime of the organism. The ion channel composition and currents of SAN cells can be influenced by a variety of factors. Therefore, the emergent activity and long-term stability imply some form of dynamical feedback control of SAN activity. We adapt a recent feedback model—previously utilized to describe control of ion conductances in neurons—to a model of SAN cells and tissue. The model describes a minimal regulatory mechanism of ion channel conductances via feedback between intracellular calcium and an intrinsic target calcium level. By coupling a SAN cell to the calcium feedback model, we show that spontaneous electrical activity emerges from quiescence and is maintained at steady state. In a 2D SAN tissue model, spatial variability in intracellular calcium targets lead to significant, self-organized heterogeneous ion channel expression and calcium transients throughout the tissue. Furthermore, multiple pacemaking regions appear, which interact and lead to time-varying cycle length, demonstrating that variability in heart rate is an emergent property of the feedback model. Finally, we demonstrate that the SAN tissue is robust to the silencing of leading cells or ion channel knockouts. Thus, the calcium feedback model can reproduce and explain many fundamental emergent properties of activity in the SAN that have been observed experimentally based on a minimal description of intracellular calcium and ion channel regulatory networks.

Emergent pacemaking and tissue heterogeneity in a calcium feedback regulatory model of the sinoatrial node.

The sinoatrial node (SAN) is the primary pacemaker of the heart. SAN activity emerges at an early point in life, and maintains a steady rhythm for the lifetime of the organism. The ion channel composition and currents of the cells can be influenced by a variety of factors. Therefore, the emergent activity and long-term stability imply some form of dynamical feedback control of the SAN cell activity. Here, we adapt a recent neuronal model to the SAN rabbit cell. The model describes a minimal regulatory mechanism of neuronal ion channel conductance based on a feedback loop defined by an intracellular [Ca2+] level as its target. Briefly, the cell upregulates or downregulates its channel mRNA and membrane expression levels based on the difference between the intercellular Ca2+ level in the cell and a set intercellular Ca2+ target. Based on this feedback model, spontaneous electrical activity emerges in the SAN cell from a quiescent state with low initial conductances. As conductances increase, the intracellular [Ca2+] level reaches the target, and ion channel conductance reach a steady state consistent with sustained spontaneous activity. In a 2D tissue, variability in [Ca2+] target leads to heterogeneous ion channel expression and Ca2+ transients throughout the tissue. Further, dominant focal clusters appear, which interact with one another leading to a heterogeneous tissue cycle length, implying that variability in heart rate is an emergent property of the feedback model. Finally, the 2D tissue is robust to the silencing of leading cells or ion channel knock-outs. Thus, the calcium feedback regulatory model explains a number of experimental data using a minimal description of intracellular calcium and ion channel regulatory networks.

Molecular foundations of the etiology and pathogenesis of Legg-Calve-Perthes disease and prospects for targeted therapy: A literature review

BACKGROUND: The etiology and pathogenesis of the development of LeggCalvePerthes disease, despite intensive research, remains not fully understood. Most studies have concluded about the multifactorial genesis of the development of hip osteochondropathy. Moreover, a complete understanding of all elements of pathogenesis leading to the manifestation and the progressive development of aseptic necrosis make it possible to develop targeted antiresorptive therapy. At present, several studies have investigated impaired functioning of signaling pathways that influence bone homeostasis during the development of LeggCalvePerthes disease. In addition, impaired metabolism in avascular necrosis is characterized by significant complexity and heterogeneity, which is based on aseptic inflammation associated with ischemic stress. Concepts of antiresorptive therapy were developed based on the results of studies on the pathogenesis of LeggCalvePerthes disease. Nevertheless, these treatment algorithms have not achieved wide practical application and require further investigation.
 AIM: This study aimed to conduct a literary analysis of the molecular basis of the etiology and pathogenesis of LeggCalvePerthes disease and assess the prospects of therapy aimed at correcting bone homeostasis disorders.
 MATERIALS AND METHODS: Data sources were PubMed, Medline, Scopus, Web of Science, and RSCI databases, without language restrictions.
 RESULTS: The relationship between ischemic stress and the induction of a cytokine cascade with a predominance of the biological actions of proinflammatory cytokines, with parallel activation of intracellular regulatory networks that determine osteoresorptive processes, including due to pyroptosis, is shown. Data on the possibility of various variants of targeted antiresorptive therapy with the use of genetically engineered drugs are presented.
 CONCLUSIONS: The pathogenesis of LeggCalvePerthes disease is characterized by significant genetic heterogeneity with the induction of various mediators of inflammation, angiogenesis, and osteogenesis, depending on the disease stage. Investigating features of impaired bone homeostasis regulation in the case of LeggCalvePerthes disease at the molecular and cellular level opens up opportunities for the development and clinical application of personalized therapy.

In silico discovery of blood cell macromolecular associations

BackgroundPhysical molecular interactions are the basis of intracellular signalling and gene regulatory networks, and comprehensive, accessible databases are needed for their discovery. Highly correlated transcripts may reflect important functional associations, but identification of such associations from primary data are cumbersome. We have constructed and adapted a user-friendly web application to discover and identify putative macromolecular associations in human peripheral blood based on significant correlations at the transcriptional level.MethodsThe blood transcriptome was characterized by quantification of 17,328 RNA species, including 341 mature microRNAs in 105 clinically well-characterized postmenopausal women. Intercorrelation of detected transcripts signal levels generated a matrix with > 150 million correlations recognizing the human blood RNA interactome. The correlations with calculated adjusted p-values were made easily accessible by a novel web application.ResultsWe found that significant transcript correlations within the giant matrix reflect experimentally documented interactions involving select ubiquitous blood relevant transcription factors (CREB1, GATA1, and the glucocorticoid receptor (GR, NR3C1)). Their responsive genes recapitulated up to 91% of these as significant correlations, and were replicated in an independent cohort of 1204 individual blood samples from the Framingham Heart Study. Furthermore, experimentally documented mRNAs/miRNA associations were also reproduced in the matrix, and their predicted functional co-expression described. The blood transcript web application is available at http://app.uio.no/med/klinmed/correlation-browser/blood/index.php and works on all commonly used internet browsers.ConclusionsUsing in silico analyses and a novel web application, we found that correlated blood transcripts across 105 postmenopausal women reflected experimentally proven molecular associations. Furthermore, the associations were reproduced in a much larger and more heterogeneous cohort and should therefore be generally representative. The web application lends itself to be a useful hypothesis generating tool for identification of regulatory mechanisms in complex biological data sets.

MODL-21. Multi-omics investigation of medulloblastoma resistant models reveals functional association between intracellular regulatory networks and drug susceptibility

Abstract Medulloblastoma (MB) is the most common malignant brain tumor of childhood. Despite high-dose radio/chemotherapy treatment, 15-30% of patients still display a high risk of tumor recurrence. In this context, the characterization of innovative cellular models resembling therapy-induced drug resistance represents an unprecedented opportunity for selecting relevant therapies for chemotherapy-refractory patients. In order to unveil the molecular mechanisms sustaining chemotherapy resistance in MB, we setup in vitro models of MB drug resistance by exposing Patient-Derived MB (PD-MB) cells to a combination of the commonly used chemotherapeutics for pediatric MB treatment. Integration of multi-omics data, including transcriptional, proteomic and kinase activation profiling, disclosed that drug resistant PD-MB cells are characterized by a significant deregulation of several cancer-related pathways converging to metabolism of xenobiotics, adaptation of the biochemical processes sustaining energetic metabolic demand, cell proliferation and survival, protein homeostasis, RNA processing and modification, and immune response. Moreover, this intriguing regulatory network was functionally associated to the response of drug-resistant MB cells to a large library of compounds through a semi-automated High-Throughput drug Screening (HTS) workflow, suggesting the antimetabolite class of drugs as relevant therapeutics displaying high selectivity and efficacy against resistant MB models, together with a significant synergistic action when combined with standard chemotherapeutic agents. Collectively, our results suggest that drug-resistant MB cells are subjected to a peculiar adaptation of multiple intracellular processes during adaptation to chemotherapy, which protects them from the toxic environment but, at the same time, provides targetable vulnerabilities for therapeutic purposes.

The people behind the papers – Megan Rommelfanger and Adam MacLean

Cell fate decisions are dependent on both internal and external factors, but mathematical models of this process have often neglected the external signals. A new paper in Development describes a multiscale model that integrates intracellular gene regulatory networks with a cell-cell communication network at single-cell resolution. We caught up with the authors, PhD student Megan Rommelfanger and Adam MacLean, Assistant Professor at the University of Southern California, to find out more about their research.

Roles of Noncoding RNA in Reproduction.

The World Health Organization predicts that infertility will be the third major health threat after cancer and cardiovascular disease, and will become a hot topic in medical research. Studies have shown that epigenetic changes are an important component of gametogenesis and related reproductive diseases. Epigenetic regulation of noncoding RNA (ncRNA) is appropriate and is a research hotspot in the biomedical field; these include long noncoding RNA (lncRNA), microRNA (miRNA), and PIWI-interacting RNA (piRNA). As vital members of the intracellular gene regulatory network, they affect various life activities of cells. LncRNA functions as a molecular bait, molecular signal and molecular scaffold in the body through molecular guidance. miRNAs are critical regulators of gene expression; they mainly control the stability or translation of their target mRNA after transcription. piRNA functions mainly through silencing genomic transposable elements and the post-transcriptional regulation of mRNAs in animal germ cells. Current studies have shown that these ncRNAs also play significant roles in the reproductive system and are involved in the regulation of essential cellular events in spermatogenesis and follicular development. The abnormal expression of ncRNA is closely linked to testicular germ cell tumors, poly cystic ovary syndrome and other diseases. This paper briefly presents the research on the reproductive process and reproductive diseases involving ncRNAs.

Intracellular and Intercellular Gene Regulatory Network Inference From Time-Course Individual RNA-Seq.

Gene regulatory network (GRN) inference is an effective approach to understand the molecular mechanisms underlying biological events. Generally, GRN inference mainly targets intracellular regulatory relationships such as transcription factors and their associated targets. In multicellular organisms, there are both intracellular and intercellular regulatory mechanisms. Thus, we hypothesize that GRNs inferred from time-course individual (whole embryo) RNA-Seq during development can reveal intercellular regulatory relationships (signaling pathways) underlying the development. Here, we conducted time-course bulk RNA-Seq of individual mouse embryos during early development, followed by pseudo-time analysis and GRN inference. The results demonstrated that GRN inference from RNA-Seq with pseudo-time can be applied for individual bulk RNA-Seq similar to scRNA-Seq. Validation using an experimental-source-based database showed that our approach could significantly infer GRN for all transcription factors in the database. Furthermore, the inferred ligand-related and receptor-related downstream genes were significantly overlapped. Thus, the inferred GRN based on whole organism could include intercellular regulatory relationships, which cannot be inferred from scRNA-Seq based only on gene expression data. Overall, inferring GRN from time-course bulk RNA-Seq is an effective approach to understand the regulatory relationships underlying biological events in multicellular organisms.

The E3 Ligase Itch Is a Regulator of Bone Marrow Mesenchymal Stem Cells and the Hematopoietic Stem Cell Niche

Hematopoietic stem cells (HSCs) reside in a complex cellular microenvironment within the bone marrow. Bone marrow mesenchymal stromal/stem cells (BM-MSCs) have emerged as an important cellular component of this hematopoietic stem cell niche. BM-MSCs have been implicated in physiological hematopoiesis as well as in hematological malignancies. The intracellular regulatory network that governs BM-MSC homeostasis and their function within the HSC niche remains poorly understood. Posttranslational modification of proteins through ubiquitylation has been proven an integrative component in the regulation of quiescence, proliferation, self-renewal and differentiation of stem cells. We have previously demonstrated that the E3 ubiquitin ligase Itch is a negative regulator of HSC homeostasis and function (Rathinam et al., Nat.Immunol., 2011). Notably, patients suffering from a rare ITCH deficiency syndrome display morphologic abnormalities with dysmorphic features, suggesting a role for this E3 ligase within the skeletal tissue and mesenchymal lineage cells (Lohr et al., Am.J.Hum.Genet., 2010).In the present study, we identify Itch as a critical regulator of BM-MSCs. Itch-/- mice exhibit an at least two-fold reduction of MSCs (immunophenotypically identified as CD45-TER119-CD31-PDGFRα+Sca-1+CD90+) in the BM. Consistently, Colony Forming Unit-Fibroblasts (CFU-F) assays revealed a remarkable reduction of MSCs in the BM (p=0.0392). Moreover, in-vitro culture studies identified a hyperproliferative phenotype of Itch mutant MSCs. However, further studies revealed that Itch deficiency leads to reduced differentiation of MSCs into osteoblasts, both in-vivo and in-vitro, and therefore resulting in osteopenic bone phenotype. Reciprocal and Serial Bone marrow transplantation studies suggested an alteration of the niche for HSCs in Itch deficient BM. Interestingly, Itch-/- recipients exhibited a five-fold increase in their donor (wild-type) hematopoietic stem and progenitor cell compartment. Molecular and biochemical studies documented an increase of signals mediated by Notch in Itch deficient MSCs and co-localization of Itch and Notch-1 intracellular domain. Of note these findings gain importance, as Notch signaling has been previously implicated in the regulation of MSC differentiation into osteoblasts, as well as in the regulation of the HSC niche.In summary, our studies identified Itch as a positive regulator of BM-MSC homeostasis. Our results suggest that the Itch-Notch axis within the HSC niche may serve as a potential pharmaceutical target, especially in the setting of bone marrow transplantation in humans. Treatment of the transplant recipient with an Itch inhibitor may avoid graft failure or rescue poor hematopoietic recovery. DisclosuresSchünemann:German Academic Exchange Service: Other: scholarship; Boehringer Ingelheim Fonds: Other: travel grant.

Coordinated action of human papillomavirus type 16 E6 and E7 oncoproteins on competitive endogenous RNA (ceRNA) network members in primary human keratinocytes

BackgroundmiRNAs and lncRNAs can regulate cellular biological processes both under physiological and pathological conditions including tumour initiation and progression. Interactions between differentially expressed diverse RNA species, as a part of a complex intracellular regulatory network (ceRNA network), may contribute also to the pathogenesis of HPV-associated cancer. The purpose of this study was to investigate the global expression changes of miRNAs, lncRNAs and mRNAs driven by the E6 and E7 oncoproteins of HPV16, and construct a corresponding ceRNA regulatory network of coding and non-coding genes to suggest a regulatory network associated with high-risk HPV16 infections. Furthermore, additional GO and KEGG analyses were performed to understand the consequences of mRNA expression alterations on biological processes.MethodsSmall and large RNA deep sequencing were performed to detect expression changes of miRNAs, lncRNAs and mRNAs in primary human keratinocytes expressing HPV16 E6, E7 or both oncoproteins. The relationships between lncRNAs, miRNAs and mRNAs were predicted by using StarBase v2.0, DianaTools-LncBase v.2 and miRTarBase. The lncRNA-miRNA-mRNA regulatory network was visualized with Cytoscape v3.4.0. GO and KEEG pathway enrichment analysis was performed using DAVID v6.8.ResultsWe revealed that 85 miRNAs in 21 genomic clusters and 41 lncRNAs were abnormally expressed in HPV E6/E7 expressing cells compared with controls. We constructed a ceRNA network with members of 15 lncRNAs – 43 miRNAs – 358 mRNAs with significantly altered expressions. GO and KEGG functional enrichment analyses identified numerous cancer related genes, furthermore we recognized common miRNAs as key regulatory elements in biological pathways associated with tumorigenesis driven by HPV16.ConclusionsThe multiple molecular changes driven by E6 and E7 oncoproteins resulting in the malignant transformation of HPV16 host cells occur, at least in part, due to the abnormal alteration in expression and function of non-coding RNA molecules through their intracellular competing network.

A multiscale compartment-based model of stochastic gene regulatory networks using hitting-time analysis.

Spatial stochastic models of single cell kinetics are capable of capturing both fluctuations in molecular numbers and the spatial dependencies of the key steps of intracellular regulatory networks. The spatial stochastic model can be simulated both on a detailed microscopic level using particle tracking and on a mesoscopic level using the reaction–diffusion master equation. However, despite substantial progress on simulation efficiency for spatial models in the last years, the computational cost quickly becomes prohibitively expensive for tasks that require repeated simulation of thousands or millions of realizations of the model. This limits the use of spatial models in applications such as multicellular simulations, likelihood-free parameter inference, and robustness analysis. Further approximation of the spatial dynamics is needed to accelerate such computational engineering tasks. We here propose a multiscale model where a compartment-based model approximates a detailed spatial stochastic model. The compartment model is constructed via a first-exit time analysis on the spatial model, thus capturing critical spatial aspects of the fine-grained simulations, at a cost close to the simple well-mixed model. We apply the multiscale model to a canonical model of negative-feedback gene regulation, assess its accuracy over a range of parameters, and demonstrate that the approximation can yield substantial speedups for likelihood-free parameter inference.

Isometries of the hypercube: A tool for Boolean regulatory networks analysis

Boolean finite dynamical systems (FDS) are commonly used in systems biology to model the dynamics of intracellular regulatory networks and interpret the emergence of cellular behaviors. Given a Boolean FDS, we can compute the corresponding regulatory network, that is a directed signed graph representing all the interactions between components (genes), endowed with logical rules specifying the dynamical behavior of the system. We consider the asynchronous trajectories generated by this Boolean FDS, supported by the hypercube. The exploration and analysis of this dynamics is a challenging task because of the combinatorial explosion that we face. A way to approach this problem is to exploit the links between the regulatory graph and the dynamics.We use the isometries of the hypercube to define classes gathering all the isometric Boolean FDS. Thus, we classify the set of Boolean FDS on the basis of those isometries, and emphasize their common features through regulatory graphs and logical rules. We can then restrict the dynamical analysis of all the Boolean FDS to one representative per class, and thereby considerably improve the efficiency of analysis of all the Boolean FDS. Relying on invariants properties, we propose a constructive method to provide, given a FDS, a representative regulatory graph of its class.We illustrate the efficiency of the method in concrete situations. For instance, the motif analysis (Remy et al., 2003; Remy et al., 2016; Didier and Remy, 2012) is strongly improved thanks to this classification. We also revisit the negative Thomas’ rule (Remy and Ruet, 2008; Richard, 2010) by establishing a new demonstration.

Dynamics of calcium signals and the intracellular regulatory signaling network

<p indent="0mm">The calcium ion (Ca²⁺) acts as a ubiquitous cellular messenger, regulating a wide variety of cellular processes. The intracellular signaling network precisely controls the normal and pathophysiological functions of cells to conduct various physiological activities. This article reviews our research progress on the dynamics of intracellular Ca²⁺ signaling and cellular signaling network models in recent years, including the release of local Ca²⁺ signals from clustered Ca²⁺ channels, global Ca²⁺ waves in cells, Ca²⁺ regulation with microdomains between the endoplasmic reticulum and mitochondria, dynamics of cell apoptosis regulated by Ca²⁺ signaling, and dynamics of cellular signaling regulation networks. These simulation studies provide directions and ideas for future research on how Ca²⁺ signals and cellular signaling networks regulate the complicated life functions in cells.

Inferring microenvironmental regulation of gene expression from single-cell RNA sequencing data using scMLnet with an application to COVID-19.

Inferring how gene expression in a cell is influenced by cellular microenvironment is of great importance yet challenging. In this study, we present a single-cell RNA-sequencing data based multilayer network method (scMLnet) that models not only functional intercellular communications but also intracellular gene regulatory networks (https://github.com/SunXQlab/scMLnet). scMLnet was applied to a scRNA-seq dataset of COVID-19 patients to decipher the microenvironmental regulation of expression of SARS-CoV-2 receptor ACE2 that has been reported to be correlated with inflammatory cytokines and COVID-19 severity. The predicted elevation of ACE2 by extracellular cytokines EGF, IFN-γ or TNF-α were experimentally validated in human lung cells and the related signaling pathway were verified to be significantly activated during SARS-COV-2 infection. Our study provided a new approach to uncover inter-/intra-cellular signaling mechanisms of gene expression and revealed microenvironmental regulators of ACE2 expression, which may facilitate designing anti-cytokine therapies or targeted therapies for controlling COVID-19 infection. In addition, we summarized and compared different methods of scRNA-seq based inter-/intra-cellular signaling network inference for facilitating new methodology development and applications.

A system-level mechanistic explanation for asymmetric stem cell fates: Arabidopsis thaliana root niche as a study system

Asymmetric divisions maintain long-term stem cell populations while producing new cells that proliferate and then differentiate. Recent reports in animal systems show that divisions of stem cells can be uncoupled from their progeny differentiation, and the outcome of a division could be influenced by microenvironmental signals. But the underlying system-level mechanisms, and whether this dynamics also occur in plant stem cell niches (SCN), remain elusive. This article presents a cell fate regulatory network model that contributes to understanding such mechanism and identify critical cues for cell fate transitions in the root SCN. Novel computational and experimental results show that the transcriptional regulator SHR is critical for the most frequent asymmetric division previously described for quiescent centre stem cells. A multi-scale model of the root tip that simulated each cell’s intracellular regulatory network, and the dynamics of SHR intercellular transport as a cell-cell coupling mechanism, was developed. It revealed that quiescent centre cell divisions produce two identical cells, that may acquire different fates depending on the feedback between SHR’s availability and the state of the regulatory network. Novel experimental data presented here validates our model, which in turn, constitutes the first proposed systemic mechanism for uncoupled SCN cell division and differentiation.