Lactobacillus Intestinalis Primes Epithelial Cells to Suppress Colitis-Related Th17 Response by Host-Microbe Retinoic Acid Biosynthesis.

Gut microbiome is integral to the pathogenesis of ulcerative colitis. A novel probiotic Lactobacillus intestinalis (L. intestinalis) exerts a protective effect against dextran sodium sulfate-induced colitis in mice. Based on flow cytometry, colitis-associated Th17 cells are the target of L. intestinalis, which is supported by the lack of protective effects of L. intestinalis in T cell-null Rag1-/- mice or upon anti-IL-17-A antibody-treated mice. Although L. intestinalis exerts no direct effect on T cell differentiation, it decreases C/EBPA-driven gut epithelial SAA1 and SAA2 production, which in turn impairs Th17 cell differentiation. Cometabolism of L. intestinalis ALDH and host ALDH1A2 contributed to elevated biosynthesis of retinoic acid (RA), which accounts for the anti-colitis effect in RAR-α -mediated way. In a cohort of ulcerative colitis patients, it is observed that fecal abundance of L. intestinalis is negatively associated with the C/EBPA-SAA1/2-Th17 axis. Finally, L. intestinalis has a synergistic effect with mesalazine in alleviating murine colitis. In conclusion, L. intestinalis and associated metabolites, RA, have potential therapeutic effects for suppressing colonic inflammation by modulating the crosstalk between intestinal epithelia and immunity.

Lactobacillus johnsonii alleviates colitis by TLR1/2-STAT3 mediated CD206+ macrophagesIL-10 activation.

Imbalance of gut microbiota homeostasis is related to the occurrence of ulcerative colitis (UC), and probiotics are thought to modulate immune microenvironment and repair barrier function. Here, in order to reveal the interaction between UC and gut microbiota, we screened a new probiotic strain by 16S rRNA sequencing from Dextran Sulfate Sodium (DSS)-induced colitis mice, and explored the mechanism and clinical relevance. Lactobacillus johnsonii (L. johnsonii), as a potential anti-inflammatory bacterium was decreased colonization in colitis mice. Gavage L. johnsonii could alleviate colitis by specifically increasing the proportion of intestinal macrophages and the secretion of Il-10 with macrophages depleted model and in Il10-/- mice. We identified this subset of immune cells activated by L. johnsonii as CD206+ macrophagesIL-10. Mechanistically, L. johnsonii supplementation enhanced the mobilization of CD206+ macrophagesIL-10 through the activation of STAT3 in vivo and in vitro. In addition, we revealed that TLR1/2 was essential for the activation of STAT3 and the recognition of L. johnsonii by macrophages. Clinically, there was positive correlation between the abundance of L. johnsonii and the expression level of MRC1, IL10 and TLR1/2 in UC tissues. L. johnsonii could activate native macrophages into CD206+ macrophages and release IL-10 through TLR1/2-STAT3 pathway to relieve experimental colitis. L. johnsonii may serve as an immunomodulator and anti-inflammatory therapeutic target for UC.

On determining firing delay time of transitions for petri net based signaling pathways by introducing stochastic decision rules.

Parameter determination is important in modeling and simulating biological pathways including signaling pathways. Parameters are determined according to biological facts obtained from biological experiments and scientific publications. However, such reliable data describing detailed reactions are not reported in most cases. This prompted us to develop a general methodology of determining the parameters of a model in the case of that no information of the underlying biological facts is provided. In this study, we use the Petri net approach for modeling signaling pathways, and propose a method to determine firing delay times of transitions for Petri net models of signaling pathways by introducing stochastic decision rules. Petri net technology provides a powerful approach to modeling and simulating various concurrent systems, and recently have been widely accepted as a description method for biological pathways. Our method enables to determine the range of firing delay time which realizes smooth token flows in the Petri net model of a signaling pathway. The availability of this method has been confirmed by the results of an application to the interleukin-1 induced signaling pathway.

Construction of a human body model for acupuncture and moxibustion treatment by colored Petri nets.

Acupuncture and moxibustion treatment has been widely spread all over the world because it has few side effects and is effective for ahead sick and incurable disease. However, the treatment is often performed empirically and clinically, and the mechanism and process of the treatment are not yet scientifically elucidated. Therefore, it is required to establish objective and unified research methods and evaluation criteria that incorporate modern Western medicine and scientific and technological viewpoints. In this paper, a human body model is constructed, which includes the internal organs and the meridians for acupuncture and moxibustion treatment based on traditional Chinese medicine using colored Petri nets. This model aims at expressing the relationship between acupoints and internal organs realistically and accurately in acupuncture and moxibustion treatment, and leading to realization of an objective analysis method of the mechanism and process of acupuncture and moxibustion treatment. Firstly, the calculation of the acupoints' efficacy on internal organs is discussed, and measurement equations and model construction methods are proposed. Next, an interface is established as a bridge to connect the internal organs and the meridians with acupoints. By Java language, a simulation system is developed based on the proposed Petri net model. Finally, simulations of acupuncture and moxibustion treatment are performed to verify the validity of model.

A phosphatidic acid-binding lncRNA SNHG9 facilitates LATS1 liquid-liquid phase separation to promote oncogenic YAP signaling.

Long noncoding RNAs (lncRNAs) are emerging as a new class of important regulators of signal transduction in tissue homeostasis and cancer development. Liquid-liquid phase separation (LLPS) occurs in a wide range of biological processes, while its role in signal transduction remains largely undeciphered. In this study, we uncovered a lipid-associated lncRNA, small nucleolar RNA host gene 9 (SNHG9) as a tumor-promoting lncRNA driving liquid droplet formation of Large Tumor Suppressor Kinase 1 (LATS1) and inhibiting the Hippo pathway. Mechanistically, SNHG9 and its associated phosphatidic acids (PA) interact with the C-terminal domain of LATS1, promoting LATS1 phase separation and inhibiting LATS1-mediated YAP phosphorylation. Loss of SNHG9 suppresses xenograft breast tumor growth. Clinically, expression of SNHG9 positively correlates with YAP activity and breast cancer progression. Taken together, our results uncover a novel regulatory role of a tumor-promoting lncRNA (i.e., SNHG9) in signal transduction and cancer development by facilitating the LLPS of a signaling kinase (i.e., LATS1).

On determining firing delay time of transitions for Petri net based signaling pathways by introducing stochastic decision rules.

Parameter determination is important in modeling and simulating biological pathways including signaling pathways. Parameters are determined according to biological facts obtained from biological experiments and scientific publications. However, such reliable data describing detailed reactions are not reported in most cases. This prompted us to develop a general methodology of determining the parameters of a model in the case of that no information of the underlying biological facts is provided. In this study, we use the Petri net approach for modeling signaling pathways, and propose a method to determine firing delay times of transitions for Petri net models of signaling pathways by introducing stochastic decision rules. Petri net technology provides a powerful approach to modeling and simulating various concurrent systems, and recently have been widely accepted as a description method for biological pathways. Our method enables to determine the range of firing delay time which realizes smooth token flows in the Petri net model of a signaling pathway. The availability of this method has been confirmed by the results of an application to the interleukin-1 induced signaling pathway.

Modelling and simulation of signal transductions in an apoptosis pathway by using timed Petri nets.

This paper first presents basic Petri net components representing molecular interactions and mechanisms of signalling pathways, and introduces a method to construct a Petri net model of a signalling pathway with these components. Then a simulation method of determining the delay time of transitions, by using timed Petri nets - i.e. the time taken in fi ring of each transition - is proposed based on some simple principles that the number of tokens flowed into a place is equivalent to the number of tokens fl owed out. Finally, the availability of proposed method is confirmed by observing signalling transductions in biological pathways through simulation experiments of the apoptosis signalling pathways as an example.

Structural modeling and analysis of signaling pathways based on Petri nets.

The purpose of this paper is to discuss how to model and analyze signaling pathways by using Petri net. Firstly, we propose a modeling method based on Petri net by paying attention to the molecular interactions and mechanisms. Then, we introduce a new notion "activation transduction component" in order to describe an enzymic activation process of reactions in signaling pathways and shows its correspondence to a so-called elementary T-invariant in the Petri net models. Further, we design an algorithm to effectively find basic enzymic activation processes by obtaining a series of elementary T-invariants in the Petri net models. Finally, we demonstrate how our method is practically used in modeling and analyzing signaling pathway mediated by thrombopoietin as an example.