RESUMEN
Phenotypic switching plays a crucial role in cell fate determination across various organisms. Recent experimental findings highlight the significance of protein compartmentalization via liquid-liquid phase separation in influencing such decisions. However, the precise mechanism through which phase separation regulates phenotypic switching remains elusive. To investigate this, we established a mathematical model that couples a phase separation process and a gene expression process with feedback. We used the chemical master equation theory and mean-field approximation to study the effects of phase separation on the gene expression products. We found that phase separation can cause bistability and bimodality. Furthermore, phase separation can control the bistable properties of the system, such as bifurcation points and bistable ranges. On the other hand, in stochastic dynamics, the droplet phase exhibits double peaks within a more extensive phase separation threshold range than the dilute phase, indicating the pivotal role of the droplet phase in cell fate decisions. These findings propose an alternative mechanism that influences cell fate decisions through the phase separation process. As phase separation is increasingly discovered in gene regulatory networks, related modeling research can help build biomolecular systems with desired properties and offer insights into explaining cell fate decisions.
Asunto(s)
Modelos Biológicos , Fenotipo , Procesos Estocásticos , Redes Reguladoras de Genes , Transición de Fase , Separación de FasesRESUMEN
Gene expression is a stochastic and noisy process often occurring in "bursts". Experiments have shown that the compartmentalization of proteins by liquid-liquid phase separation is conducive to reducing the noise of gene expression. Therefore, an important goal is to explore the role of bursts in phase separation noise reduction processes. We propose a coupled model that includes phase separation and a two-state gene expression process. Using the timescale separation method, we obtain approximate solutions for the expectation, variance, and noise strength of the dilute phase. We find that a higher burst frequency weakens the ability of noise reduction by phase separation, but as the burst size increases, this ability first increases and then decreases. This study provides a deeper understanding of phase separation to reduce noise in the stochastic gene expression with burst kinetics.
Asunto(s)
Separación de Fases , Proteínas , Procesos EstocásticosRESUMEN
Thirteen kinds of common drug precursor chemicals were detected on the spot by transportable Raman spectrometer independently researched and developed. Changing analysis methods, such as the focal position of the instrument, analysis time, external light source, sample containers and the concentration of the analyte, the high quality Raman spectrums were obtained. The study shows that analysis method can be optimized to improve the detection efficiency, LOD (limit of detection) of 1-phenyl-2-acetone, toluene and chloroform was recorded for lower concentrations and the component contents of the mixture have a significant impact on the test results. Selecting the appropriate instrument conditions can be more effective and fast screening of precursor chemicals on site to provide help for those who are engaged in the anti-drug work.
Asunto(s)
Profármacos/química , Espectrometría Raman/métodos , Acetona/química , Cloroformo/química , Espectrometría Raman/instrumentación , Tolueno/químicaRESUMEN
OBJECTIVE: To determine the content of flavonoids and rutin in the different parts of Saussurea involucrata, and to establish their HPLC fingerprint chromatogram for the further development and utilization of the leaf. METHODS: The content of flavonoids was determined with UV. The similarity evaluation system for chromatographic fingerprint of TCM was used to calculate similar degree of the HPLC chromatogram of different parts. RESULTS: The content of flavonoids and rutin is relatively high in the leaf. The similarity between leaf and the whole grass is 0. 812.