Robustness analysis and identification for an enzyme-catalytic complex metabolic network in batch culture.

Bioconversion of glycerol to 1,3-propanediol is a promising way to mitigate the shortage of energy. To maximize the production of 1,3-propanediol, it needs to control precisely microbial fermentation process. However, it might consume lots of human and material resources when conducting experimental tests many times. In this study, a nonlinear enzyme-catalytic dynamical system is developed to describe the bioconversion process of glycerol to 1,3-propanediol, especially continuous piecewise linear functions are used as identification parameters. The existence, uniqueness and continuity of solutions are also discussed. Then, considering the fact that the concentration of intracellular substances is difficult to measure in experiments, a new quantitative definition of biological robustness is introduced as a performance index to determine the identification parameters related to intracellular substances. Meanwhile, a two-phase optimization algorithm is constructed to solve the identification model. By comparison with the experimental data, it can be found that the present nonlinear dynamical system can describe the fermentation process very well. Finally, the present nonlinear dynamical system and the corresponding optimal identification parameters might be useful in future studies on the batch culture of glycerol to 1,3-propanediol.

Sensitivity analysis and parameter identification of nonlinear hybrid systems for glycerol transport mechanisms in continuous culture.

In this paper, we establish a modified fourteen-dimensional nonlinear hybrid dynamic system with genetic regulation to describe the microbial continuous culture, in which we consider that there are three possible ways for glycerol to pass the cell's membrane and one way for 1,3-PD (passive diffusion and active transport). Then we discuss the existence, uniqueness, continuous dependence of solutions and the compactness of the solution set. We construct a global sensitivity analysis approach to reduce the number of kinetic parameters. In order to infer the most reasonable transport mechanism of glycerol, we propose a parameter identification model aiming at identifying the parameter with higher sensitivity and transport of glycerol, which takes the robustness index of the intracellular substance together with the relative error between the experimental data and the computational values of the extracellular substance as a performance index. Finally, a parallel algorithm is applied to find the optimal transport of glycerol and parameters.

Complex metabolic network of 1,3-propanediol transport mechanisms and its system identification via biological robustness.

The bioconversion of glycerol to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae (K. pneumoniae) can be characterized by an intricate metabolic network of interactions among biochemical fluxes, metabolic compounds, key enzymes and genetic regulation. Since there are some uncertain factors in the fermentation, especially the transport mechanisms of 1,3-PD across cell membrane, the metabolic network contains multiple possible metabolic systems. Considering the genetic regulation of dha regulon and inhibition of 3-hydroxypropionaldehyde to the growth of cells, we establish a 14-dimensional nonlinear hybrid dynamical system aiming to determine the most possible metabolic system and the corresponding optimal parameter. The existence, uniqueness and continuity of solutions are discussed. Taking the robustness index of the intracellular substances together as a performance index, a system identification model is proposed, in which 1,395 continuous variables and 90 discrete variables are involved. The identification problem is decomposed into two subproblems and a parallel particle swarm optimization procedure is constructed to solve them. Numerical results show that it is most possible that 1,3-PD passes the cell membrane by active transport coupled with passive diffusion.

µ-Synthesis of dissimilation process of glycerol to 1,3-propanediol in microbial continuous culture.

In this paper, robust control problem using µ-synthesis in microbial continuous culture is studied. The dissimilation process of glycerol to 1,3-propanediol cannot avoid the disturbances caused by uncertain factors. Based on the biodynamical model, a control system with the initial glycerol concentration as input control is proposed to simplify the controller design. µ-synthesis method is applied to find a feedback controller to assure both of robust stability and robust performance of the closed-loop system simultaneously. To solve the corresponding structured singular value optimization problem, a converged result is obtained through D-K iteration method. The µ-synthesis system is also compared with the corresponding H(∞) system. The simulation results indicate that the µ-controller might be more feasible for the continuous bioprocess controlling.

Stability analysis and controller design in microbial continuous culture with discrete time delay.

In this paper, stability analysis and controller design in microbial continuous culture with discrete time delay are studied. The dissimilation process of glycerol to 1,3-propanediol cannot avoid the disturbances caused by time delay. Time delay can limit and degrade the achievable performance of controlled systems, and even induce instability. Based on the biodynamic model, some properties of its solutions are discussed. In addition, we investigate how the time-delay affects the stability of the system. A linear matrix inequalities method is applied to find a feedback controller to ensure the stability of the closed-loop system. The simulation results indicate that this controller might be feasible for continuous bioprocess control.

[Treatment of "hydration therapy" for acute paraquat poisoning].

OBJECTIVE: To explore the clinical value of "hydration therapy" in the treatment of severe acute paraquat poisoning (APP). METHODS: A prospective historical control observation was conducted. Fifty-eight patients with severe APP admitted to Shouguang People's Hospital Affiliated to Weifang Medical College from February 2014 to June 2019 were enrolled. Twenty-six patients admitted before May 10th, 2016 were enrolled in the standard treatment group. After being admitted to intensive care unit (ICU) from the department of emergency, patients in the standard treatment group were immediately given standard treatment such as repeated gastric lavage, catharsis, adsorption of poison by activated carbon or montmorillonite powder, drug treatment and blood purification. From May 10th, 2016, 32 patients were enrolled in the intensive treatment group. On the basis of standard treatment, "hydration therapy" was carried out, that was, 0.9% NaCl and/or 5% glucose injection were used for continuous intravenous infusion throughout the day, so as to ensure that the total amount of fluid infusion per day reached 200 mL/kg within 48-72 hours after ICU admission. At the same time, furosemide was used to strengthen diuresis to ensure the balance of water and electrolyte. If heart failure or acute pulmonary interstitial edema occurred during the treatment, "hydration therapy" should be stopped immediately. Six months after treatment, all patients were followed up. The patients with normal activity, no complaints of discomfort and no damage of heart, lung, liver, kidney and other organs were regarded as cured. The therapeutic effect of "hydration therapy" was evaluated. RESULTS: There was no significant difference in gender, age, dosage or time from taking poison to ICU between the two groups. In the intensive treatment group, 32 patients did not appear heart failure during continuous rehydration treatment. Follow-up after 6 months showed that the overall cure rate in the intensive treatment group was significantly higher than that in the standard treatment group [59.4% (19/32) vs. 19.2% (5/26), P < 0.05]. In the 6-month follow-up, there was no significant difference in age or time from taking poison to ICU between the two groups, but the dosage in the intensive treatment group was significantly higher than that in the standard treatment group (mL: 54.06±26.03 vs. 23.00±4.47, P < 0.05). After 6 months of follow-up, chest CT showed that the lesions of pulmonary fibrosis of cured patients in both group gradually reduced with time, not completely progressive and irreversible. CONCLUSIONS: "Hydration therapy" with intensive diuresis can significantly improve the rescue success rate of patients with severe APP.

[Effects of hydrocortisone on myocardial function in early stage of sepsis in rabbits].

OBJECTIVE: To study the effects of different dose of hydrocortisone (HC) on myocardial function in early stage of sepsis in rabbits. METHODS: Twenty-four male rabbits were randomly divided into three groups: model group (n=8), HC low dosage group (10 mg/kg, n=8), HC high dosage group (100 mg/kg, n=8). The model was reproduced by cecal ligation and puncture (CLP). The function of the left ventricle was monitored and blood was drawn at 5 time points [before CLP, before treatment (1 hour after CLP) and 2, 4, 6 hours after the treatment] to determine concentrations of cardiac troponin I (cTnI) and nitric oxide (NO). The expression of inducible nitric oxide synthase (iNOS) of myocytes was investigated. RESULTS: Compared to the basic levels, maximal positive and negative change in filling pressure versus time (+/-dp/dt max) decreased significantly, while NO increased significantly before treatment in all groups (all P<0.05). At 6 hours after treatment, +/-dp/dt max in HC low dosage group was significantly higher than that in the other two groups, while cTnI was significantly lower in HC low dosage group than that in the other two groups (all P<0.05). NO content in two HC groups was significantly lower than that in model group (all P<0.05), and the iNOS expressions on myocardial cells was weaker than model group [model group: (81.8+/-15.8)%, HC low dosage group: (56.7+/-21.2)%, HC high dosage group: (54.6+/-16.1)%, all P<0.05]. CONCLUSION: Myocardial function is remarkably damaged in rabbits with sepsis. HC low dosage group exerts protective effect on myocardial cells in early stage of sepsis.

[Experience of continuous fluid therapy in successfully rescuing a patient with acute severe paraquat poisoning].

OBJECTIVE: Paraquat (PQ) poisoning has become one of the common pesticide poisoning in China. PQ is extremely toxic to human beings. The fatality rate of oral PQ poisoning is more than 90%. So far, there is no specific antidote. Seek effective treatment measures for PQ poisoning has become the focus of clinical medical research. In November 2017, a patient with acute severe PQ poisoning was treated in the intensive care unit (ICU) of Shouguang People's Hospital Affiliated to Weifang Medical College. The patient refused blood purification therapy and was rescued successfully only by continuous fluid therapy, diuresis, catharsis and routine treatment. By reviewing the treatment process of this case, new treatment ideas for the clinical treatment of PQ poisoning in primary hospitals were provided. Patients with acute PQ poisoning should be rescued by immediate administration of emetic, gastric lavage, catharsis and oral montmorillonite powder. For those without dysfunction of heart, lung and and kidney, a large amount of fluid treatment and diuresis should be given immediately to promote the excretion of poison. The key to improve the success rate of rescue of acute PQ poisoning is to eliminate PQ from the body as soon as possible.

A clustering algorithm based on two distance functions for MEC model.

Haplotype reconstruction, based on aligned single nucleotide polymorphism (SNP) fragments, is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. This paper first presents two distance functions, which are used to measure the difference degree and similarity degree between SNP fragments. Based on the two distance functions, a clustering algorithm is proposed in order to solve MEC model. The algorithm involves two sections. One is to determine the initial haplotype pair, the other concerns with inferring true haplotype pair by re-clustering. The comparison results prove that our algorithm utilizing two distance functions is effective and feasible.

The haplotype assembly model with genotype information and iterative local-exhaustive search algorithm.

The minimum error correction (MEC) model for haplotype reconstruction is efficient only when the error rate in SNP fragments is low. In order to improve reconstruction rate, additional genotype information is added into MEC model as an extension to MEC model. In this paper, we first establish a new mathematical model for haplotype assembly problem with genotype information. Several properties of the mathematical model are proved. Then an iterative local-exhaustive search algorithm is proposed based on the model and its properties. The main idea is to find the optimal pair among 2(l-1) (l denotes the number of heterozygous sites of a genotype) haplotype pairs by performing local exhaustive search for the promising haplotype pair step by step. By experiments and comparison, extensive numerical results on real data and simulated data indicate that our algorithm outperforms the other algorithms in terms of efficiency and robustness.

Discrimination of outer membrane proteins by a new measure of information discrepancy.

Discriminating outer membrane proteins for globular proteins (GPs) and other types of membrane proteins from genomic sequences is an important and hot topic. In this paper, a measure based on information discrepancy is proposed and applied to the discrimination of outer membrane proteins. It differs from previous methods which are based on amino acid composition. Our approach focuses on the comparison of subsequence distributions and takes into account the effect of residue order in protein primary structures. As a result, the new approach outperforms all previous methods on the same benchmark datasets. In particular, we show that the proposed approach has correctly identified the outer membrane proteins at an accuracy of 99% for the training set of 337 proteins and has correctly excluded the GPs at an accuracy of 86% in a non-redundant dataset of 668 proteins. Furthermore, this method is able to correctly exclude alpha-helical membrane proteins at an accuracy of 100%.

Optimal HP configurations of proteins by combining local search with elastic net algorithm.

The prediction of protein conformation from its amino-acid sequence is one of the most prominent problems in computational biology. But it is NP-hard. Here, we focus on an abstraction widely studied of this problem, the two-dimensional hydrophobic-polar protein folding problem (2D HP PFP). Mathematical optimal model of free energy of protein is established. Native conformations are often sought using stochastic sampling methods, but which are slow. The elastic net (EN) algorithm is one of fast deterministic methods as travelling salesman problem (TSP) strategies. However, it cannot be applied directly to protein folding problem, because of fundamental differences in the two types of problems. In this paper, how the 2D HP protein folding problem can be framed in terms of TSP is shown. Combination of the modified elastic net algorithm and novel local search method is adopted to solve this problem. To our knowledge, this is the first application of EN algorithm to 2D HP model. The results indicate that our approach can find more optimal conformations and is simple to implement, computationally efficient and fast.

Computational method for inferring objective function of glycerol metabolism in Klebsiella pneumoniae.

Flux balance analysis (FBA) is an effective tool in the analysis of metabolic network. It can predict the flux distribution of engineered cells, whereas the accurate prediction depends on the reasonable objective function. In this work, we propose two nonlinear bilevel programming models on anaerobic glycerol metabolism in Klebsiella pneumoniae (K. pneumoniae) for 1,3-propanediol (1,3-PD) production. One intends to infer the metabolic objective function, and the other is to analyze the robustness of the objective function. In view of the models' characteristic an improved genetic algorithm is constructed to solve them, where some techniques are adopted to guarantee all chromosomes are feasible and move quickly towards the global optimal solution. Numerical results reveal some interesting conclusions, e.g., biomass production is the main force to drive K. pneumoniae metabolism, and the objective functions, which are obtained in term of several different groups of flux distributions, are similar.

The simulation of the three-dimensional lattice hydrophobic-polar protein folding.

One of the most prominent problems in computational biology is to predict the natural conformation of a protein from its amino acid sequence. This paper focuses on the three-dimensional hydrophobic-polar (HP) lattice model of this problem. The modified elastic net (EN) algorithm is applied to solve this nonlinear programming hard problem. The lattice partition strategy and two local search methods (LS(1) and LS(2)) are proposed to improve the performance of the modified EN algorithm. The computation and analysis of 12 HP standard benchmark instances are also involved in this paper. The results indicate that the hybrid of modified EN algorithm, lattice partition strategy, and local search methods has a greater tendency to form a globular state than genetic algorithm does. The results of noncompact model are more natural in comparison with that of compact model.

Exploration of two-dimensional hydrophobic-polar lattice model by combining local search with elastic net algorithm.

Determining the functional conformation of a protein from its amino acid sequence remains a central problem in computational biology. In this paper, we establish the mathematical optimal model of protein folding problem (PFP) on two-dimensional space based on the minimal energy principle. A novel hybrid of elastic net algorithm and local search method (ENLS) is applied successfully to simulations of protein folding on two-dimensional hydrophobic-polar (HP) lattice model. Eight HP benchmark instances with up to 64 amino acids are tested to verify the effectiveness of proposed approach and model. In several cases, the ENLS method finds new lower energy states. The numerical results show that it is drastically superior to other methods in finding the ground state of a protein.