A novel hyper-cube shrink algorithm to predict metabolic fluxes based on enzyme activity only

OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs such role to calculate the sensitivity of flux change upon that of enzymes under the framework of ordinary differential equation(ODE)models,which are restricted in small-scale networks and require explicit kinetic parameters.The constraint-based models,like flux balance analysis(FBA),lack of the room of performing MCA because they are parameters-free.In this study,we developed a hyper-cube shrink algorithm(HCSA)to incorporate the enzymatic properties to the FBA model by introducing a pair of parameters for each reaction.Our algorithm was able to handle not only prediction of knockout strains but also strains with an adjustment of expression level of certain enzymes.RESULTS We first showed the concept by applying HCSA to a simplest three-nodes network.Then we show the HCSA possesses Michaelis-Menten like behaviors characterized by steady state of ODE.We obtained good prediction of a synthetic network in Saccharomyces cerevisiae producing voilacein and analogues.Finally we showed its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast.CONCLUSION We have developed an algorithm the impact on fluxes when certain enzymes were inhibited or activated.It provides us a powerful tool to evaluate the consequences of enzyme inhibitor or activator.

Cryo-EM Data Statistics and Theoretical Analysis of KaiC Hexamer

Cryo-electron microscopy(cryo-EM) provides a powerful tool to resolve the structure of biological macromolecules in natural state. One advantage of cryo-EM technology is that different conformation states of a protein complex structure can be simultaneously built, and the distribution of different states can be measured. This provides a tool to push cryo-EM technology beyond just to resolve protein structures, but to obtain the thermodynamic properties of protein machines. Here, we used a deep manifold learning framework to get the conformational landscape of Kai C proteins, and further obtained the thermodynamic properties of this central oscillator component in the circadian clock by means of statistical physics.

Cellbow:a robust customizable cell segmentation program

Backgrounds Time-lapse live cell imaging of a growing cell population is routine in many biological investigations.A major challenge in imaging analysis is accurate segmentation,a process to define the boundaries of cells based on raw image data.Current segmentation methods relying on single boundary features have problems in robustness when dealing with inhomogeneous foci which invariably happens in cell population imaging.Methods:Combined with a multi-layer training set strategy,we developed a neural-network-based algorithm—Cellbow.Results'Cellbow can achieve accurate and robust segmentation of cells in broad and general settings.It can also facilitate long-term tracking of cell growth and division.To facilitate the application of Cellbow,we provide a website on which one can online test the software,as well as an I mage J plugin for the user to visualize the performance before software installation.Conclusions Cellbow is customizable and generalizable.It is broadly applicable to segmenting fluorescent images of diverse cell types with no further training needed.For bright-field images,only a small set of sample images of the specific cell type from the user may be needed for training.

Synthetic immunology:T-cell engineering and adoptive immunotherapy

During the past decades,the rapidly-evolving cancer is hard to be thoroughly eliminated even though the radiotherapy and chemotherapy do exhibit efficacy in some degree.However,a breakthrough appeared when the adoptive cancer therapy[1]was developed,especially T cells armed with chimeric antigen receptors(CARs)showed great potential in tumor clinical trials recently.CAR-T cells successfully elevated the efficiency and specificity of cytotoxicity.In this review,we will talk about the design of CAR and CAR-included combinatory therapeutic applications in the principles of systems and synthetic immunology.