Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.

Understanding cell state transitions and their governing regulatory mechanisms remains one of the fundamental questions in biology. We develop a computational method, state transition inference using cross-cell correlations (STICCC), for predicting reversible and irreversible cell state transitions at single-cell resolution by using gene expression data and a set of gene regulatory interactions. The method is inspired by the fact that the gene expression time delays between regulators and targets can be exploited to infer past and future gene expression states. From applications to both simulated and experimental single-cell gene expression data, we show that STICCC-inferred vector fields capture basins of attraction and irreversible fluxes. By connecting regulatory information with systems' dynamical behaviors, STICCC reveals how network interactions influence reversible and irreversible state transitions. Compared to existing methods that infer pseudotime and RNA velocity, STICCC provides complementary insights into the gene regulation of cell state transitions.

Curcumin suppresses colorectal tumorigenesis through restoring the gut microbiota and metabolites.

BACKGROUND: Curcumin has been reported to have activity for prevention and therapy of CRC, yet its underlying mechanisms remain largely unknown. Recently, emerging evidence suggests that the gut microbiota and its metabolites contribute to the causation and progression of Colorectal cancer (CRC). In this study, we aimed to investigate if curcumin affects the tumorigenesis of CRC by modulating gut microbiota and its metabolites. METHODS: Forty male C57BL/6JGpt mice were randomly divided into four groups: negative control (NC), curcumin control, CRC model, and curcumin treatment (CRC-Cur) groups. CRC mouse model was induced by using azoxymethane (AOM) and dextran sodium sulfate (DSS), and the mice in CRC model and curcumin treatment groups received oral PBS or curcumin (150 mg/kg/day), respectively. Additionally, fecal samples were collected. 16 S rRNA sequencing and Liquid Chromatography Mass Spectrometry (LC-MS)-based untargeted metabolomics were used to observe the changes of intestinal flora and intestinal metabolites. RESULTS: Curcumin treatment restored colon length and structural morphology, and significantly inhibited tumor formation in AOM/DSS-induced CRC model mice. The 16S rRNA sequencing analysis indicated that the diversity and richness of core and total species of intestinal microflora in the CRC group were significantly lower than those in the NC group, which were substantially restored in the curcumin treatment group. Curcumin reduced harmful bacteria, including Ileibacterium, Monoglobus and Desulfovibrio, which were elevated in CRC model mice. Moreover, curcumin increased the abundance of Clostridia_UCG-014, Bifidobacterium and Lactobacillus, which were decreased in CRC model mice. In addition, 13 different metabolites were identified. Compared to the NC group, ethosuximide, xanthosine, and 17-beta-estradiol 3-sulfate-17-(beta-D-glucuronide) were elevated in the CRC model group, whereas curcumin treatment significantly reduced their levels. Conversely, glutamylleucine, gamma-Glutamylleucine, liquiritin, ubenimex, 5'-deoxy-5'-fluorouridine, 7,8-Dihydropteroic acid, neobyakangelicol, libenzapril, xenognosin A, and 7,4'-dihydroxy-8-methylflavan were decreased in the CRC group but notably upregulated by curcumin. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis revealed enrichment in seven pathways, including folate biosynthesis (P < 0.05). CONCLUSIONS: The gut microecological balance was disrupted in AOM/DSS-induced CRC mice, accompanied by metabolite dysbiosis. Curcumin restored the equilibrium of the microbiota and regulated metabolites, highly indicating that curcumin may alleviate the development of AOM/DSS induced colorectal cancer in mice by regulating intestinal flora homeostasis and intestinal metabolites.

The toxic effect of 2,6-di-tert-butylphenol on embryonic development in zebrafish (Danio rerio): Decreased survival rate, morphological abnormality, and abnormal vascular development.

2,6-di-tert-butylphenol (2,6-DTBP) has been used extensively in plastics, rubber and polymer phenolic antioxidants. It is discharged into the aquatic environment through industrial waste. However, the toxicity assessment of 2,6-DTBP is insufficient. Here, zebrafish embryos were used as an animal model to investigate the toxicological effects of 2,6-DTBP. The results showed that 2,6-DTBP induced mitochondrial dysfunction and reactive oxygen species accumulation, which caused apoptosis, and further led to developmental toxicity of zebrafish embryos, such as delayed incubation, reduced survival rate, and increased malformation rate and heart rate. 2,6-DTBP can also cause morphological changes in the zebrafish endothelial cell (zEC) nucleus, inhibit zEC migration, trigger abnormal angiogenesis and zEC sprouting angiogenesis, and ultimately affect vascular development. In addition, 2,6-DTBP interfered with the endogenous antioxidant system, causing changes in activities of superoxide dismutase, catalase, and glutathione S-transferase and contents of malondialdehyde and glutathione. Transcriptome sequencing showed that 2,6-DTBP altered the mRNA levels of genes associated with vascular development, oxidative stress, apoptosis, extracellular matrix components and receptors. Integrative biomarker response assessment found that 12 µM 2,6-DTBP had the highest toxicity. These results indicated that 2,6-DTBP induced apoptosis through oxidative stress, leading to toxicity of zebrafish embryo development. This study contributes to understanding the effects of environmental 2,6-DTBP exposure on early development of aquatic organisms and draws public attention to the health risks posed by chemicals in aquatic organisms.

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML.

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a new optimization procedure to identify the top network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression.

EuTGA1, a bZIP transcription factor, positively regulates EuFPS1 expression in Eucommia ulmoides.

Eucommia ulmoides (E. ulmoides) is widely cultivated and exhibits remarkable adaptability in China. It is the most promising rubber source plant in the temperate zone. E. ulmoides gum (EUG) is a trans-polyisoprene with a unique "rubber-plastic duality", and is widely used in advanced materials and biomedical fields. The transcription of Farnesyl pyrophosphate synthase (FPS), the rate-limiting enzyme of EUG biosynthesis, is controlled by regulatory mechanisms that remain poorly elucidated. In this research, 12 TGA transcription factors (TFs) in E. ulmoides were identified. Promoter prediction results revealed that the EuFPS1 promoter had binding sites for EuTGAs. Subsequently, the EuTGA1 was obtained by screening the E. ulmoides cDNA library using the EuFPS1 promoter as a bait. The individual yeast one­hybrid and dual-luciferase assays confirmed that in the tobacco plant, EuTGA1 interacted with the EuFPS1 promoter, resulting in a more than threefold increase in the activity of the EuFPS1. Subcellular localization study further revealed that EuTGA1 is localized in the nucleus and acts as a TF to regulate EuFPS1 expression. In addition, qRT-PCR analysis demonstrated that the expression trend of EuFPS1 and EuTGA1 was the same at different time of the year. Notably, low temperature and MeJA treatments down-regulated EuTGA1 expression. Additionally, the transient transformation of EuTGA1 enhanced NtFPS1 expression in tobacco plants. Overall, this study identified a TF that interacted with EuFPS1 promoter to positively regulate EuFPS1 expression. The findings of this study provide a theoretical basis for further research on the expression regulation of EuFPS1.

Wearable Sensors for Breath Monitoring Based on Water-Based Hexagonal Boron Nitride Inks Made with Supramolecular Functionalization.

Wearable humidity sensors are attracting strong attention as they allow for real-time and continuous monitoring of important physiological information by enabling activity tracking as well as air quality assessment. Amongst 2Dimensional (2D) materials, graphene oxide (GO) is very attractive for humidity sensing due to its tuneable surface chemistry, high surface area, processability in water, and easy integration onto flexible substrates. However, strong hysteresis, low sensitivity, and cross-sensitivity issues limit the use of GO in practical applications, where continuous monitoring is preferred. Herein, a wearable and wireless impedance-based humidity sensor made with pyrene-functionalized hexagonal boron nitride (h-BN) nanosheets is demonstrated. The device shows enhanced sensitivity towards relative humidity (RH) (>1010 Ohms/%RH in the range from 5% to 100% RH), fast response (0.1 ms), no appreciable hysteresis, and no cross-sensitivity with temperature in the range of 25-60 °C. The h-BN-based sensor is able to monitor the whole breathing cycle process of exhaling and inhaling, hence enabling to record in real-time the subtlest changes of respiratory signals associated with different daily activities as well as various symptoms of flu, without requiring any direct contact with the individual.

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML.

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a novel optimization procedure to identify the optimal network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression.

A quantitative evaluation of topological motifs and their coupling in gene circuit state distributions.

One of the major challenges in biology is to understand how gene interactions collaborate to determine overall functions of biological systems. Here, we present a new computational framework that enables systematic, high-throughput, and quantitative evaluation of how small transcriptional regulatory circuit motifs, and their coupling, contribute to functions of a dynamical biological system. We illustrate how this approach can be applied to identify four-node gene circuits, circuit motifs, and motif coupling responsible for various gene expression state distributions, including those derived from single-cell RNA sequencing data. We also identify seven major classes of four-node circuits from clustering analysis of state distributions. The method is applied to establish phenomenological models of gene circuits driving human neuron differentiation, revealing important biologically relevant regulatory interactions. Our study will shed light on a better understanding of gene regulatory mechanisms in creating and maintaining cellular states.

Novel Seed Size: A Novel Seed-Developing Gene in Glycine max.

Soybean-seed development is controlled in multiple ways, as in many known regulating genes. Here, we identify a novel gene, Novel Seed Size (NSS), involved in seed development, by analyzing a T-DNA mutant (S006). The S006 mutant is a random mutant of the GmFTL4pro:GUS transgenic line, with phenotypes with small and brown seed coats. An analysis of the metabolomics and transcriptome combined with RT-qPCR in the S006 seeds revealed that the brown coat may result from the increased expression of chalcone synthase 7/8 genes, while the down-regulated expression of NSS leads to small seed size. The seed phenotypes and a microscopic observation of the seed-coat integument cells in a CRISPR/Cas9-edited mutant nss1 confirmed that the NSS gene conferred small phenotypes of the S006 seeds. As mentioned in an annotation on the Phytozome website, NSS encodes a potential DNA helicase RuvA subunit, and no such genes were previously reported to be involved in seed development. Therefore, we identify a novel gene in a new pathway controlling seed development in soybeans.

A data-driven optimization method for coarse-graining gene regulatory networks.

One major challenge in systems biology is to understand how various genes in a gene regulatory network (GRN) collectively perform their functions and control network dynamics. This task becomes extremely hard to tackle in the case of large networks with hundreds of genes and edges, many of which have redundant regulatory roles and functions. The existing methods for model reduction usually require the detailed mathematical description of dynamical systems and their corresponding kinetic parameters, which are often not available. Here, we present a data-driven method for coarse-graining large GRNs, named SacoGraci, using ensemble-based mathematical modeling, dimensionality reduction, and gene circuit optimization by Markov Chain Monte Carlo methods. SacoGraci requires network topology as the only input and is robust against errors in GRNs. We benchmark and demonstrate its usage with synthetic, literature-based, and bioinformatics-derived GRNs. We hope SacoGraci will enhance our ability to model the gene regulation of complex biological systems.

NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity.

A major question in systems biology is how to identify the core gene regulatory circuit that governs the decision-making of a biological process. Here, we develop a computational platform, named NetAct, for constructing core transcription factor regulatory networks using both transcriptomics data and literature-based transcription factor-target databases. NetAct robustly infers regulators' activity using target expression, constructs networks based on transcriptional activity, and integrates mathematical modeling for validation. Our in silico benchmark test shows that NetAct outperforms existing algorithms in inferring transcriptional activity and gene networks. We illustrate the application of NetAct to model networks driving TGF-ß-induced epithelial-mesenchymal transition and macrophage polarization.

What Makes a Functional Gene Regulatory Network? A Circuit Motif Analysis.

One of the key questions in systems biology is to understand the roles of gene regulatory circuits in determining cellular states and their functions. In previous studies, some researchers have inferred large gene networks from genome wide genomics/transcriptomics data using the top-down approach, while others have modeled core gene circuits of small sizes using the bottom-up approach. Despite many existing systems biology studies, there is still no general rule on what sizes of gene networks and what types of circuit motifs a system would need to achieve robust biological functions. Here, we adopt a gene circuit motif analysis to discover four-node circuits responsible for multiplicity (rich in dynamical behavior), flexibility (versatile to alter gene expression), or both. We identify the most reoccurring two-node circuit motifs and the co-occurring motif pairs. Furthermore, we investigate the contributing factors of multiplicity and flexibility for large gene networks of different types and sizes. We find that gene networks of intermediate sizes tend to have combined high levels of multiplicity and flexibility. Our study will contribute to a better understanding of the dynamical mechanisms of gene regulatory circuits and provide insights into rational designs of robust gene circuits in synthetic and systems biology.

An Efficient Agrobacterium rhizogenes-Mediated Hairy Root Transformation Method in a Soybean Root Biology Study.

The stable genetic transformation of soybean is time-consuming and inefficient. As a simple and practical alternative method, hairy root transformation mediated by Agrobacterium rhizogenes is widely applied in studying root-specific processes, nodulation, biochemical and molecular functions of genes of interest, gene editing efficiency of CRISPR/Cas9, and biological reactors and producers. Therefore, many laboratories have developed unique protocols to obtain hairy roots in composite plants composed of transgenic roots and wild-type shoots. However, these protocols still suffer from the shortcomings of low efficiency and time, space, and cost consumption. To address this issue, we developed a new protocol efficient regeneration and transformation of hairy roots (eR&T) in soybean, by integrating and optimizing the main current methods to achieve high efficiency in both hairy root regeneration and transformation within a shorter period and using less space. By this eR&T method, we obtained 100% regeneration of hairy roots for all explants, with an average 63.7% of transformation frequency, which promoted the simultaneous and comparative analysis of the function of several genes. The eR&T was experimentally verified Promoter:GUS reporters, protein subcellular localization, and CRISPR/Cas9 gene editing experiments. Employing this approach, we identified several novel potential regulators of nodulation, and nucleoporins of the Nup107-160 sub-complex, which showed development-dependent and tissue-dependent expression patterns, indicating their important roles in nodulation in soybean. Thus, the new eR&T method is an efficient and economical approach for investigating not only root and nodule biology, but also gene function.

Automatic Rate and Rate-Integrating Mode-Switchable Axisymmetric Gyroscope.

This paper describes a novel rate and rate-integrating mode-switchable axisymmetric gyroscope. A precession angle tracking algorithm is developed to enable the gyro to switch automatically between rate and rate-integrating modes at preset rate points through a digital control system within the gyro. We also propose a vibrating amplitude control method for the rate-integrating mode that directly extracts the angular rate output to ensure switching stability. In rate mode, the bias instability and angle random walk of the gyro reach 0.106°/h and 0.011°/√h, respectively. Additionally, an input range of over ±5000°/s is measured in rate-integrating mode. The scale factor nonlinearity reaches approximately 116 ppm over the full-scale range. The control system implements effective steering control of the gyroscope, with a switching delay of 10 ms from rate mode to rate-integrating mode and 100 ms from rate-integrating to rate mode. The proposed system actualizes a new type of gyroscope with high accuracy and a wide input range, which combines the benefits of rate and rate-integrating modes.

Preparation of Nereid oligopeptide and investigation of the mechanism underlying the induction of apoptosis in human lung cancer H1299 cells.

In the present study, oligopeptides from Nereid (Perinereis aibuhitensis) were prepared via enzymatic hydrolysis, and the mechanism underlying the induction of apoptosis in H1299 cells was investigated. According to the analysis of the inhibition rate on proliferation, alkaline protease demonstrated the best enzymatic efficiency. The optimal conditions for hydrolysis were as follows: 50˚C and pH 10 for 6 h; a material­to­liquid ratio of 1:1 (g/ml); and addition of 400 U/g enzyme. The hydrolysates were purified using ultrafiltration, anion chromatography, gel filtration chromatography, and high­performance liquid chromatography. The Nereid oligopeptide (NOP), with a molecular weight of 841 kDa and an amino acid sequence of glutamine­isoleucine­asparagine­glutamine­histidine­leucine, was obtained. NOP inhibited the proliferation of H1299 cells in a time­ and dose­dependent manner. Morphological changes and apoptosis were also induced by NOP in H1299 cells. The western blot analysis revealed that the B­cell lymphoma 2/Bcl­2 associated X (Bcl­2/Bax) ratio was reduced by 24.7% in the NOP treatment group compared with the control group. The relative expression levels of cleaved caspase­9 (cleaved­CASP9) and cleaved caspase­3 (cleaved­CASP3) in the NOP treatment group were 2.55­ and 1.71­fold higher than those measured in the control group, respectively. These results suggested that NOP exerts antitumor effects by influencing the proliferation and apoptosis of H1299 cells.

Bronchial epithelium epithelial-mesenchymal plasticity forms aberrant basaloid-like cells in vitro.

Although epithelial-mesenchymal transition (EMT) is a common feature of fibrotic lung disease, its role in fibrogenesis is controversial. Recently, aberrant basaloid cells were identified in fibrotic lung tissue as a novel epithelial cell type displaying a partial EMT phenotype. The developmental origin of these cells remains unknown. To elucidate the role of EMT in the development of aberrant basaloid cells from the bronchial epithelium, we mapped EMT-induced transcriptional changes at the population and single-cell levels. Human bronchial epithelial cells grown as submerged or air-liquid interface (ALI) cultures with or without EMT induction were analyzed by bulk and single-cell RNA-Sequencing. Comparison of submerged and ALI cultures revealed differential expression of 8,247 protein coding (PC) and 1,621 long noncoding RNA (lncRNA) genes and revealed epithelial cell-type-specific lncRNAs. Similarly, EMT induction in ALI cultures resulted in robust transcriptional reprogramming of 6,020 PC and 907 lncRNA genes. Although there was no evidence for fibroblast/myofibroblast conversion following EMT induction, cells displayed a partial EMT gene signature and an aberrant basaloid-like cell phenotype. The substantial transcriptional differences between submerged and ALI cultures highlight that care must be taken when interpreting data from submerged cultures. This work supports that lung epithelial EMT does not generate fibroblasts/myofibroblasts and confirms ALI cultures provide a physiologically relevant system to study aberrant basaloid-like cells and mechanisms of EMT. We provide a catalog of PC and lncRNA genes and an interactive browser (https://bronc-epi-in-vitro.cells.ucsc.edu/) of single-cell RNA-Seq data for further exploration of potential roles in the lung epithelium in health and lung disease.

Combined application of H2S and a plant growth promoting strain JIL321 regulates photosynthetic efficacy, soil enzyme activity and growth-promotion in rice under salt stress.

Salinity stress is one of the most harmful abiotic stresses that inhibit crop growth and grain yield. In this study, a salt-tolerant bacterium was isolated from the soil of the rice rhizosphere and named Myroides sp. JIL321, based on the results of the phylogenetic tree analysis. The strain JIL321 tolerated up to 1, 283.37 mM of NaCl and exhibited positive plant growth-promoting traits, such as the production of indole acetic acid (IAA) and 1-aminocyclopropane-1-carboxylate (ACC) deaminase. Therefore, the effects of JIL321 on rice (Oryza sativa L.) under salinity stress were determined. The inoculation of strain JIL321 significantly increased the chlorophyll content and the accumulation of osmotic adjustment substances, such as proline and soluble sugars, in rice expose to salt stress. Additionally, strain JIL321 inoculation significantly enhanced the activities of some enzymes commonly found in soil, such as urease, invertase and catalase. Moreover, the production of hydrogen sulfide (H2S), a pivotal signaling molecule, was also induced in rice by salt stress. Treatment with sodium hydrogen sulfide (NaHS, H2S donor) improved salt stress tolerance of the rice, while treatment with hypotaurine (HT, H2S scavenger) significantly suppressed it. Interestingly, NaHS treatment also improved the production of IAA and ACC deaminase in strain JIL321 under 0 mM and 150 mM salt concentrations. The combined treatment of JIL321 and NaHS could further improve the growth of salt-stressed rice seedlings, most likely due to the interaction effect between H2S and strain JIL321. To our knowledge, this study is the first to demonstrate that the combined use of H2S and plant growth-promoting bacteria could alleviate the adverse effects of salt stress on rice plants, and further verifies the novel role of H2S as a signaling molecule that enhance the tolerance of plant to abiotic stresses.

Generalized Radon transform approach to target motion parameter estimation using a stationary underwater vector hydrophone.

Underwater platforms provide long-term detection of undersea targets. In this paper, we propose a method for the estimation of target motion parameters by submerged static acoustic detection equipment. The proposed method is based on the Radon transform of modeling the target moving in a uniform straight line. The heading angle, the time to the closest point of approach (CPA), and the ratio of velocity to the horizontal range of the target at the CPA to the sensor are obtained by applying the generalized Radon transform (GRT) to bearing-time records. The velocity of the target is determined by applying the GRT to the line-spectrum-time records. Furthermore, the motion trajectory of the target with respect to the detection equipment can be calculated from the above parameters. To validate the feasibility and performance of the proposed method, computer simulations and sea trials based on a fixed single vector measurement system were analyzed in this paper. The results suggest that the proposed method can accurately estimate the motion parameters and can calculate the trajectory of the moving vessel along a straight line at constant velocity.

Analysis of Tilt Effect on Notch Depth Profiling Using Thin-Skin Regime of Driver-Pickup Eddy-Current Sensor.

Electromagnetic eddy current sensors are commonly used to identify and quantify the surface notches of metals. However, the unintentional tilt of eddy current sensors affects results of size profiling, particularly for the depth profiling. In this paper, based on the eddy current thin-skin regime, a revised algorithm has been proposed for the analytical voltage or impedance of a tilted driver-pickup eddy current sensor scanning across a long ideal notch. Considering the resolution of the measurement, the bespoke driver-pickup, also termed as transmitter-receiver (T-R) sensor is designed with a small mean radius of 1 mm. In addition, the T-R sensor is connected to the electromagnetic instrument and controlled by a scanning stage with high spatial travel resolution, with a limit of 0.2 µm and selected as 0.25 mm. Experiments were conducted for imaging of an aluminium sheet with seven machined long notches of different depths using T-R sensor under different tilt angles. By fitting the measured voltage (both real and imaginary part) with proposed analytical algorithms, the depth profiling of notches is less affected by the tilt angle of sensors. From the results, the depth of notches can be retrieved within a deviation of 10% for tilt angles up to 60 degrees.

Computational systems-biology approaches for modeling gene networks driving epithelial-mesenchymal transitions.

Epithelial-mesenchymal transition (EMT) is an important biological process through which epithelial cells undergo phenotypic transitions to mesenchymal cells by losing cell-cell adhesion and gaining migratory properties that cells use in embryogenesis, wound healing, and cancer metastasis. An important research topic is to identify the underlying gene regulatory networks (GRNs) governing the decision making of EMT and develop predictive models based on the GRNs. The advent of recent genomic technology, such as single-cell RNA sequencing, has opened new opportunities to improve our understanding about the dynamical controls of EMT. In this article, we review three major types of computational and mathematical approaches and methods for inferring and modeling GRNs driving EMT. We emphasize (1) the bottom-up approaches, where GRNs are constructed through literature search; (2) the top-down approaches, where GRNs are derived from genome-wide sequencing data; (3) the combined top-down and bottom-up approaches, where EMT GRNs are constructed and simulated by integrating bioinformatics and mathematical modeling. We discuss the methodologies and applications of each approach and the available resources for these studies.