Towards Kinetic Modeling of Global Metabolic Networks： Methylobacterium extorquens AM1 Growth as Validation

Here we report a systematic method for constructing a large scale kinetic metabolic model and its initial application to the modeling of central metabolism of Methylobacterium extorquens AM1, a methylotrophic and environmental important bacterium. Its central metabolic network includes formaldehyde metabolism, serine cycle, citric acid cycle, pentose phosphate pathway, gluconeogensis, PHB synthesis and acetyl-CoA conversion pathway, respiration and energy metabolism. Through a systematic and consistent procedure of finding a set of parameters in the physiological range we overcome an outstanding difficulty in large scale kinetic modeling: the requirement for a massive number of enzymatic reaction parameters. We are able to construct the kinetic model based on general biological considerations and incomplete experimental kinetic parameters. Our method consists of the following major steps: 1) using a generic enzymatic rate equation to reduce the number of enzymatic parameters to a minimum set while still preserving their characteristics; 2) using a set of steady state fluxes and metabolite concentrations in the physiological range as the expected output steady state fluxes and metabolite concentrations for the kinetic model to restrict the parametric space of enzymatic reactions; 3) choosing enzyme constants K's and K'eqs optimized for reactions under physiological concentrations, if their experimental values are unknown; 4) for models which do not cover the entire metabolic network of the organisms, designing a dynamical exchange for the coupling between the metabolism represented in the model and the rest not included.

Study on Extraction and Properties of Gelatin from Squid Skin

A kind of aquatic gelatin was prepared from squid skin. The technological parameters for extracting gelatin were optimized by the method of orthogonal design. The fundamental properties of the raw material and gelatin were analyzed. The results showed that the optimal extraction conditions were as follows： pH val- ue of 8, temperature at 70 ℃, material-to-liquid ratio at 1：4, and extraction time of 1.5 h. under such conditions, the highest yield of gelatin and the purity were 5.94% and 96.73%, respectively. The physicoehemical properties of squid skin gelatin were coincided with standards of edible gelatin. In addition, the contents of amino acids were similar to many kinds of aquatic gelatin.

Mapping QTLs for Salt Tolerance at Seeding Stage of Landrace Rice (Oryza sativa L.)

[Objectives] The identification of salt tolerant genetic loci in rice can provide a research basis for the molecular mechanism of salt tolerance and gene resources for improving salt tolerant cultivars. [Methods] Recombinant inbred lines(RILs) derived from Zhaxima, an indica landrace variety from Yunnan Province and Nanjing 46, an elite japonica variety with superior grain quality from Jiangsu Province were used. The salt tolerance at seeding stage in the RIL population was investigated as the phenotypic value. [Results] Combined with the linkage map, a total of 4 QTLs were detected: qSST-1, qSST-3, qSST-5 and qSST-11, located in rice chromosomes 1, 3, 5 and 11, respectively. All positive alleles were from the parent Nanjing 46. Three QTLs among them were not included in chromosome intervals the same as cloned rice salt tolerance genes, and thus were described as new candidate gene loci associated with seeding-stage salt tolerance. [Conclusions] This study provides important information for further exploration and utilization of new salt tolerant QTLs in rice. It is of great significance for improving the utilization of saline land in China and ensuring the stable rice production.

A PARALLELIZATION METHOD FOR DO-LOOP BASED ON EQUIVALENCE CLASSIFICIATION

In this paper, a new method for DO-loop parallelization based on the new collcept allocation-dependence and equivalence classification of iteration space is proposed. This method has many advantages: It is a general,ullified method for DO-loop parallelization. It is used in coarse grain parallel partitioning on MINID and SPMD. While partitioning iteration space, it also does the does the partition and computation partition such that these partitions are independent each other. It can extract the potential parallelism of program accurately. Combining with task-level parallelization vectorization and pipeline,it can extract parallelism thoroughly.

金砖国家对发达国家投资空间格局与动机研究

一般认为发展中国家对外直接投资是为了获取市场、自然资源和战略资产,尤其是战略资产寻求,没有效率寻求动机。本文基于2010—2017年金砖国家对发达国家逆向投资数据对此进行检验,并有不同发现:金砖国家对发达国家逆向投资具有市场寻求动机、自然资源寻求动机和效率寻求动机,但没有显著的战略资产寻求动机。从时间维度看,市场寻求动机有增强趋势;而其他三类投资动机有随时间减弱的趋势,但减弱趋势并不显著。从国别维度看,中国、俄罗斯和南非逆向投资具有自然资源寻求动机;中国和印度逆向投资具有战略寻求动机;中国、印度和南非具有效率寻求动机,更偏好劳动力成本低的发达国家。机制分析表明造成投资动机差异的根源在于各国不同的战略意图。

干细胞处于所有癌症的中心吗？

干细胞和癌细胞是细胞众多状态中的一部分,这个事实说明干细胞不会处于所有癌症的中心,但会是癌症发生发展的一个重要因素.近年来更多的生物实验研究和医学临床观察也充分支持这个结论.干细胞与癌症的关系是关于细胞形态维持与转化——生物的中心问题之一.通过分析干细胞和癌症在3种层次-现象、分子生物标志、系统生物机理-中的关系,21世纪内发展起来的内源性网络理论可以作为一个全新的、综合性的思考平台.它能定量地刻画细胞状态的稳定性和相互转化的动态路径,把遗传和表观遗传现象的描述统一在同一个理论中,能更好地理解目前对这个问题研究的热潮下的生物学意义并能在理论和计算上帮助它向前推进.所有这些进展都指向一个可能:革命性的突破就在我们眼前.

Decoding early myelopoiesis from dynamics of core endogenous network

A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network perspective. Indeed, there are numerical difficulties even for those who were determined to explore along this direction. Undeterred, seven years ago a group of Chinese scientists started a program aiming to obtain quantitative connections between tumors and network dynamics. Many interesting results have been obtained. In this paper we wish to test such idea from a different angle: the connection between a normal biological process and the network dynamics. We have taken early myelopoiesis as our biological model. A standard roadmap for the cell-fate diversification during hematopoiesis has already been well established experimentally, yet little was known for its underpinning dynamical mechanisms. Compounding this difficulty there were additional experimental challenges, such as the seemingly conflicting hematopoietic roadmaps and the cell-fate inter-conversion events. With early myeloid cell-fate determination in mind, we constructed a core molecular endogenous network from well-documented gene regulation and signal transduction knowledge. Turning the network into a set of dynamical equations, we found computationally several structurally robust states. Those states nicely correspond to known cell phenotypes. We also found the states connecting those stable states.They reveal the developmental routes—how one stable state would most likely turn into another stable state. Such interconnected network among stable states enabled a natural organization of cell-fates into a multi-stable state landscape. Accordingly, both the myeloid cell phenotypes and the standard roadmap were explained mechanistically in a straightforward manner. Furthermore,recent challenging observations were also explained naturally. Moreover, the landscape visually enables a prediction of a pool of additional cell states and developmental routes, including the non-sequential and cross-branch transitions, which are testable by future experiments. In summary, the endogenous network dynamics provide an integrated quantitative framework to understand the heterogeneity and lineage commitment in myeloid progenitors.

From Phage lambda to human cancer： endogenous molecular-cellular network hypothesis

Experimental evidences and theoretical analyses have amply suggested that in cancer genesis and progression genetic information is very important but not the whole. Nevertheless, ＂cancer as a disease of the genome＂ is still currently the dominant doctrine. With such a background and based on the fundamental properties of biological systems, a new endogenous molecular-cellular network theory for cancer was recently proposed by us. Similar proposals were also made by others. The new theory attempts to incorporate both genetic and environmental effects into one single framework, with the possibility to give a quantitative and dynamical description. It is asserted that the complex regulatory machinery behind biological processes may be modeled by a nonlinear stochastic dynamical system similar to a noise perturbed Morse-Smale system. Both qualitative and quantitative descriptions may be obtained. The dynamical variables are specified by a set of endogenous molecular-cellular agents and the structure of the dynamical system by the interactions among those biological agents. Here we review this theory from a pedagogical angle which emphasizes the role of modularization, hierarchy and autonomous regulation. We discuss how the core set of assumptions is exemplified in detail in one of the simple, important and well studied model organisms, Phage lambda. With this concrete and quantitative example in hand, we show that the application of the hypothesized theory in human cancer, such as hepatocellular carcinoma （HCC）, is plausible, and that it may provide a set of new insights on understanding cancer genesis and progression, and on strategies for cancer prevention, cure, and care.

New discovery of high-affinity SARS-CoV-2 spike S2 protein binding peptide selected by PhIP-Seq

Dear Editor,Theworld had suffered pandemics of COVID-19 caused by SARS-CoV-2.At the time ofwriting,COVID-19 is still widely spreading inmany countries and regions,and by June 14,2022,totally 532,887,351 cases,including 6,307,021 deaths,were reported globally(WHO,https://covid19.who.int/table).Powerful measures,such as prophylactic and therapeutic interventions against the virus,are in urgent need for COVID-19 control and prevention.The spike protein,which is expressed on the virus surface,is the key determinant of viral-host interaction(Ng et al.,2021)and mediates the virus entry.