During blastocyst formation, inner cell mass (ICM) cells differentiate into either epiblast (Epi) or primitive endoderm (PrE) cells, labeled by Nanog and Gata6, respectively, and organized in a salt-and-pepper pattern. Previous work in the mouse has shown that, in absence of Nanog, all ICM cells adopt a PrE identity. Moreover, the activation or the blockade of the Fgf/RTK pathway biases cell fate specification towards either PrE or Epi, respectively. We show that, in absence of Gata6, all ICM cells adopt an Epi identity. Furthermore, the analysis of Gata6 +/− embryos reveals a dose-sensitive phenotype, with fewer PrE-specified cells. These results and previous findings have enabled the development of a mathematical model for the dynamics of the regulatory network that controls ICM differentiation into Epi or PrE cells. The model describes the temporal dynamics of Erk signaling and of the concentrations of Nanog, Gata6, secreted Fgf4 and Fgf receptor 2. The model is able to recapitulate most of the cell behaviors observed in different experimental conditions and provides a unifying mechanism for the dynamics of these developmental transitions. The mechanism relies on the co-existence between three stable steady states (tristability), which correspond to ICM, Epi and PrE cells, respectively. Altogether, modeling and experimental results uncover novel features of ICM cell fate specification such as the role of the initial induction of a subset of cells into Epi in the initiation of the salt-and-pepper pattern, or the precocious Epi specification in Gata6 +/− embryos.

During development, interactions between transcription factors control the specification of different cell fates. The regulatory networks of genetic interactions often exhibit multiple stable steady states; such multistability provides a common dynamical basis for differentiation. During early murine embryogenesis, cells from the inner cell mass (ICM) can be specified in epiblast (Epi) or primitive endoderm (PrE). Besides the intracellular gene regulatory network, specification is also controlled by intercellular interactions involving Erk signaling through extracellular Fgf4. We previously proposed a model that describes the gene regulatory network and its interaction with Erk signaling in ICM cells. The model displays tristability in a range of Fgf4 concentrations and accounts for the self-organized specification process observed in vivo. Here, we further investigate the origin of tristability in the model and analyze in more detail the specification process by resorting to a simplified two-cell model. We also carry out simulations of a population of 25 cells under various experimental conditions to compare their outcome with that of mutant embryos or of embryos submitted to exogenous treatments that interfere with Fgf signaling. The results are analyzed by means of bifurcation diagrams. Finally, the model predicts that heterogeneities in extracellular Fgf4 concentration play a primary role in the spatial arrangement of the Epi/PrE cells in a salt-and-pepper pattern. If, instead of heterogeneities in extracellular Fgf4 concentration, internal fluctuations in the levels of expression of the transcription factors are considered as a source of randomness, simulations predict the occurrence of unrealistic switches between the Epi and the PrE cell fates, as well as the evolution of some cells toward one of these states without passing through the previous ICM state, in contrast to what is observed in vivo.

The current routine use of adjuvants in human vaccines provides a strong incentive to increase our understanding of how adjuvants differ in their ability to stimulate innate immunity and consequently enhance vaccine immunogenicity. Here, we evaluated gene expression profiles in cells from whole blood elicited in naive subjects receiving the hepatitis B surface antigen formulated with different adjuvants. We identified a core innate gene signature emerging 1 day after the second vaccination and that was shared by the recipients of vaccines formulated with adjuvant systems AS01B, AS01E, or AS03. This core signature associated with the magnitude of the hepatitis B surface-specific antibody response and was characterized by positive regulation of genes associated with interferon-related responses or the innate cell compartment and by negative regulation of natural killer cell–associated genes. Analysis at the individual subject level revealed that the higher immunogenicity of AS01B-adjuvanted vaccine was linked to its ability to induce this signature in most vaccinees even after the first vaccination. Therefore, our data suggest that adjuvanticity is not strictly defined by the nature of the receptors or signaling pathways it activates but by the ability of the adjuvant to consistently induce a core inflammatory signature across individuals.

Systems biology has the potential to identify gene signatures associated with vaccine immunogenicity and protective efficacy. The main objective of this study was to identify optimal postvaccination time points for evaluating peripheral blood RNA expression profiles in relation to vaccine immunogenicity and potential efficacy in recipients of the candidate tuberculosis vaccine M72/AS01. In this phase II open-label study (NCT01669096; ), healthy Bacillus Calmette–Guérin-primed, HIV-negative adults were administered two doses (30 days apart) of M72/AS01. Twenty subjects completed the study and 18 subjects received two doses. Blood samples were collected pre-dose 1, pre-dose 2, and 1, 7, 10, 14, 17, and 30 days post-dose 2. RNA expression in whole blood (WB) and peripheral blood mononuclear cells (PBMCs) was quantified using microarray technology. Serum interferon-gamma responses and M72-specific CD4+ T cell responses to vaccination, and the observed safety profile were similar to previous trials. Two different approaches were utilized to analyze the RNA expression data. First, a kinetic analysis of RNA expression changes using blood transcription modules revealed early (1 day post-dose 2) activation of several pathways related to innate immune activation, both in WB and PBMC. Second, using a previously identified gene signature as a classifier, optimal postvaccination time points were identified. Since M72/AS01 efficacy remains to be established, a PBMC-derived gene signature associated with the protective efficacy of a similarly adjuvanted candidate malaria vaccine was used as a proxy for this purpose. This approach was based on the assumption that the AS01 adjuvant used in both studies could induce shared innate immune pathways. Subjects were classified as gene signature positive (GS+) or gene signature negative (GS−). Assignments of subjects to GS+ or GS− groups were confirmed by significant differences in RNA expression of the gene signature genes in PBMCs at 14 days post-dose 2 relative to prevaccination and in WB samples at 7, 10, 14, and 17 days post-dose 2 relative to prevaccination. Hence, in comparison with a prevaccination, 7, 10, 14, and 17 days postvaccination appeared to be suitable time points for identifying potentially clinically relevant transcriptome responses to M72/AS01 in WB samples.

Colony Stimulating Factor 1 Receptor (CSF1R) is a potential target for anti-epileptic drugs. However, inhibition of CSF1R is not well tolerated by patients, thereby prompting the need for alternative targets. To develop a framework for identification of such alternatives, we here develop a mathematical model of a pro-inflammatory gene regulatory network (GRN) involved in epilepsy and centered around CSF1R. This GRN comprises validated transcriptional and post-transcriptional regulations involving STAT1, STAT3, NFκB, IL6R, CSF3R, IRF8, PU1, C/EBPα, TNFR1, CSF1 and CSF1R. The model was calibrated on mRNA levels of all GRN components in lipopolysaccharide (LPS)-treated mouse microglial BV-2 cells, and allowed to predict that STAT1 and STAT3 have the strongest impact on the expression of the other GRN components. Microglial BV-2 cells were selected because, the modules from which the GRN was deduced are enriched for microglial marker genes. The function of STAT1 and STAT3 in the GRN was experimentally validated in BV-2 cells. Further, in silico analysis of the GRN dynamics predicted that a pro-inflammatory stimulus can induce irreversible bistability whereby the expression level of GRN components occurs as two distinct states. The irreversibility of the switch may enforce the need for chronic inhibition of the CSF1R GRN in order to achieve therapeutic benefit. The cell-to-cell heterogeneity driven by the bistability may cause variable therapeutic response. In conclusion, our modeling approach uncovered a GRN controlling CSF1R that is predominantly regulated by STAT1 and STAT3. Irreversible inflammation-induced bistability and cell-to-cell heterogeneity of the GRN provide a theoretical foundation to the need for chronic GRN control and the limited potential for disease modification via inhibition of CSF1R.

Coronavirus (Covid-19) has to date (March 29th 2020) infected over 81,000 Chinese citizens, mostly in Hubei Province, since it was first identified in December 2019. It has so far spread to more than 202 countries. On the 31th of March 2020, the total number of laboratory-confirmed COVID-19 cases reported by Ministry of Public Health (MoPH) in Thailand is 1524, of which 127 have recovered, 1388 are receiving treatment (17 cases are severe) in healthcare settings and nine have died. Recently Geographic Information System (GIS) provide epidemiologists and public health officers in the surveillance, monitoring and controlling of many infected diseases such as vector-borne diseases or human-to-human transmission diseases in many countries. Particularly it can provide the functions of collecting, updating and managing disease surveillance and related data, such as geographical factor and socio-economic. They are also pertinent to suit the needs of understanding the spatial spread or diffusion of disease outbreak and response for designing the prevention and control strategies. The major objective of this research is to apply the spatial epidemiology approaches for studying COVID-19 patterns and hotspots in Bangkok Metropolitan Region (BMR), Thailand. The specific objectives are to analyze the COVID-19 patterns in the terms of population and geographic distribution patterns; to detect the COVID-19 incidence rate under different months by using the spatial analysis. This research provides maps to view the pandemic situation of BMR and the provincial level of COVID-19 in particular heat maps and ring maps.

Gene expression data is commonly used in vaccine studies to characterize differences between treatment groups or sampling time points. Group-wise comparisons of the transcriptional perturbations induced by vaccination have been applied extensively for investigating the mechanisms of action of vaccines. Such approaches, however, may not be sensitive enough for detecting changes occurring within a minority of the population under investigation or in single individuals. In this study, we developed a data analysis framework to characterize individual subject response profiles in the context of repeated measure experiments, which are typical of vaccine mode of action studies. Following the definition of the methodology, this was applied to the analysis of human transcriptome responses induced by vaccination with a subunit influenza vaccine. Results highlighted a substantial heterogeneity in how different subjects respond to vaccination. Moreover, the extent of transcriptional modulation experienced by each individual subject was found to be associated with the magnitude of vaccine-specific functional antibody response, pointing to a mechanistic link between genes involved in protein production and innate antiviral response. Overall, we propose that the improved characterization of the intersubject heterogeneity, enabled by our approach, can help driving the improvement and optimization of current and next-generation vaccines.

Despite significant progress in prevention, diagnosis and treatment, Malaria and Tuberculosis (TB) remain major health challenges. In 2014 WHO estimated that ≈438000 people died from Malaria and ≈1.5 million from TB, mainly in resource-poor countries. Vaccines represent a cost-effective and efficient method of preventing infectious diseases. The development of vaccines for TB and Malaria would significantly contribute to reducing disease burden, particularly with the emergence of drug-resistant pathogens. GSK’s Malaria vaccine, Mosquirix™ (RTS,S/AS01), received a positive opinion from European regulators for the prevention of Malaria in young children in sub-Saharan Africa. GSK’s candidate vaccine for TB (M72/AS01) induces robust TB-specific CD4 T-cell responses in humans, and it is undergoing phase IIb clinical trials. System biology approaches can support vaccines at different stages of development by identifying molecular signatures that drive responses to vaccination. Here, we describe the application of systems vaccinology to the analysis of gene expression data from clinical trials for Malaria and TB candidate vaccines. Our analysis aimed to identify early predictors of vaccine efficacy in Malaria clinical trials and to detect signatures associated with reactogenicity in the early development of a TB vaccine. To better capture the multidimensional nature of the data, we used multivariate analysis approaches such as Partial Least Squares regression. Additionally, biological interpretation of our results allowed us to pinpoint biological processes linked with response to vaccination, advancing our understanding of vaccine mode of action.