巴斯德毕赤酵母甲醇诱导表达磷脂酶A2的转录组学分析

【目的】基于转录组学技术研究表达磷脂酶A_2的毕赤酵母重组菌在甲醇诱导表达外源蛋白时的基因表达差异,从而解析外源蛋白高效诱导表达机制,为进一步工程菌株的改造提供理论支撑。【方法】以一株产磷脂酶(PLA_2)的毕赤酵母为出发菌株,采用RNA-Seq二代测序方法,研究在甘油培养和甲醇诱导两种条件下,重组毕赤酵母转录组基因表达差异情况。【结果】重组毕赤酵母中共鉴定到5225个转录本。甘油培养与甲醇诱导相比,共有857个基因发生显著变化。依据代谢途径分类,差异基因集中在核糖体成分、甲醇代谢、磷酸戊糖途径、糖酵解途径、柠檬酸循环、乙醛酸循环以及蛋白质加工过程。【结论】通过分析甲醇诱导前后的差异表达基因,结果表明碳源改变对胞内代谢会产生全局影响。本研究结果为进一步研究毕赤酵母表达外源蛋白的机制提供了基础。     

Genome‐derived minimal metabolic models for Escherichia coli MG1655 with estimated in vivo respiratory ATP stoichiometry

Metabolic network models describing growth of Escherichia coli on glucose, glycerol and acetate were derived from a genome scale model of E. coli. One of the uncertainties in the metabolic networks is the exact stoichiometry of energy generating and consuming processes. Accurate estimation of biomass and product yields requires correct information on the ATP stoichiometry. The unknown ATP stoichiometry parameters of the constructed E. coli network were estimated from experimental data of eight different aerobic chemostat experiments carried out with E. coli MG1655, grown at different dilution rates (0.025, 0.05, 0.1, and 0.3 h^?1) and on different carbon substrates (glucose, glycerol, and acetate). Proper estimation of the ATP stoichiometry requires proper information on the biomass composition of the organism as well as accurate assessment of net conversion rates under well‐defined conditions. For this purpose a growth rate dependent biomass composition was derived, based on measurements and literature data. After incorporation of the growth rate dependent biomass composition in a metabolic network model, an effective P/O ratio of 1.49 ± 0.26 mol of ATP/mol of O, K_X (growth dependent maintenance) of 0.46 ± 0.27 mol of ATP/C‐mol of biomass and m_ATP (growth independent maintenance) of 0.075 ± 0.015 mol of ATP/C‐mol of biomass/h were estimated using a newly developed Comprehensive Data Reconciliation (CDR) method, assuming that the three energetic parameters were independent of the growth rate and the used substrate. The resulting metabolic network model only requires the specific rate of growth, µ, as an input in order to accurately predict all other fluxes and yields. Biotechnol. Bioeng. 2010;107: 369–381. © 2010 Wiley Periodicals, Inc.     

The metabolic flux phenotype of heterotrophic Arabidopsis cells reveals a complex response to changes in nitrogen supply

The extent to which individual plants utilise nitrate and ammonium, the two principal nitrogen sources in the rhizosphere, is variable and many species require a balance between the two forms for optimal growth. The effects of nitrate and ammonium on gene expression, enzyme activity and metabolite composition have been documented extensively with the aim of understanding the way in which plant cells respond to the different forms of nitrogen, but ultimately the impact of these changes on the organisation and operation of the central metabolic network can only be addressed by analysing the fluxes supported by the network. Accordingly steady‐state metabolic flux analysis was used to define the metabolic phenotype of a heterotrophic Arabidopsis thaliana cell culture grown in Murashige and Skoog and ammonium‐free media, treatments that influenced growth and biomass composition. Fluxes through the central metabolic network were deduced from the redistribution of label into metabolic intermediates and end products observed when cells were labelled with [1‐¹³C]‐, [2‐¹³C]‐ or [¹³C₆]glucose, in tandem with ¹⁴C‐measurements of the net accumulation of biomass. Analysis of the flux maps showed that: (i) flux through the oxidative pentose phosphate pathway varied independently of the reductant demand for biosynthesis, (ii) non‐plastidic processes made a significant and variable contribution to the provision of reducing power for the plastid, and (iii) the inclusion of ammonium in the growth medium increased cell maintenance costs, in agreement with the futile cycling model of ammonium toxicity. These conclusions highlight the complexity of the metabolic response to a change in nitrogen nutrition.     

产肌醇毕赤酵母细胞工厂的优化

【背景】肌醇是一种B族维生素,广泛应用于食品、医药、饲料等领域。微生物发酵法是最具前景的肌醇生产方法,但使用大肠杆菌生产的肌醇在食品及医药领域中的使用受到限制。毕赤酵母作为生物安全菌株是工业上生产异源蛋白的良好宿主,其本身含有天然的肌醇合成途径,具有被改造成为高效生产肌醇细胞工厂的潜力。【目的】通过代谢工程改造毕赤酵母工程菌株,降低副产物的生成并提高肌醇的产量。【方法】以实验室前期构建的产肌醇毕赤酵母工程菌株为出发菌株,确定副产物阿拉伯糖醇、核糖醇和甘露糖合成相关基因。通过关键基因敲除、发酵液中葡萄糖浓度控制降低副产物的产量。通过过表达甘油转运蛋白、甘油激酶和甘油-3-磷酸脱氢酶基因实现产肌醇毕赤酵母对甘油和葡萄糖的共利用,得到重组菌Z10。经过发酵条件优化,进一步提高Z10的肌醇产量。【结果】在最优条件下,重组菌Z10的肌醇产量达到36.7 g/L,是目前酵母类细胞工厂生产肌醇的最高值,副产物总产量与出发菌株相比降低了63.1%。【结论】在毕赤酵母中建立了降低阿拉伯糖醇、核糖醇和甘露糖合成的有效策略,并通过甘油、葡萄糖共利用及相对应的发酵条件优化提高了肌醇产量,为肌醇及其他高价值生物...     

毕赤酵母细胞工厂工程化改造与应用

毕赤酵母作为细胞工厂在小分子代谢产物发酵和蛋白制品生物合成中扮演着重要角色，具有极其重要的工业应用价值。随着CRISPR/Cas9等新型编辑工具的开发和应用，对毕赤酵母细胞工厂进行多基因高效率的工程化改造已成为可能。本文首先对毕赤酵母工程化改造的遗传操作技术和目标方向进行了归纳总结，其次介绍了毕赤酵母作为细胞工厂的应用现状，同时探讨了毕赤酵母细胞工厂的优点及缺陷，并对其发展方向作出展望；以期为未来的毕赤酵母工程化改造研究提供参考和启示，推动毕赤酵母细胞工厂在生物产业中的创新应用。     

Genome‐scale gene/reaction essentiality and synthetic lethality analysis

Synthetic lethals are to pairs of non‐essential genes whose simultaneous deletion prohibits growth. One can extend the concept of synthetic lethality by considering gene groups of increasing size where only the simultaneous elimination of all genes is lethal, whereas individual gene deletions are not. We developed optimization‐based procedures for the exhaustive and targeted enumeration of multi‐gene (and by extension multi‐reaction) lethals for genome‐scale metabolic models. Specifically, these approaches are applied to iAF1260, the latest model of Escherichia coli, leading to the complete identification of all double and triple gene and reaction synthetic lethals as well as the targeted identification of quadruples and some higher‐order ones. Graph representations of these synthetic lethals reveal a variety of motifs ranging from hub‐like to highly connected subgraphs providing a birds‐eye view of the avenues available for redirecting metabolism and uncovering complex patterns of gene utilization and interdependence. The procedure also enables the use of falsely predicted synthetic lethals for metabolic model curation. By analyzing the functional classifications of the genes involved in synthetic lethals, we reveal surprising connections within and across clusters of orthologous group functional classifications.     

Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate

Mycoplasma hyopneumoniae is cultured on large‐scale to produce antigen for inactivated whole‐cell vaccines against respiratory disease in pigs. However, the fastidious nutrient requirements of this minimal bacterium and the low growth rate make it challenging to reach sufficient biomass yield for antigen production. In this study, we sequenced the genome of M. hyopneumoniae strain 11 and constructed a high quality constraint‐based genome‐scale metabolic model of 284 chemical reactions and 298 metabolites. We validated the model with time‐series data of duplicate fermentation cultures to aim for an integrated model describing the dynamic profiles measured in fermentations. The model predicted that 84% of cellular energy in a standard M. hyopneumoniae cultivation was used for non‐growth associated maintenance and only 16% of cellular energy was used for growth and growth associated maintenance. Following a cycle of model‐driven experimentation in dedicated fermentation experiments, we were able to increase the fraction of cellular energy used for growth through pyruvate addition to the medium. This increase in turn led to an increase in growth rate and a 2.3 times increase in the total biomass concentration reached after 3–4 days of fermentation, enhancing the productivity of the overall process. The model presented provides a solid basis to understand and further improve M. hyopneumoniae fermentation processes. Biotechnol. Bioeng. 2017;114: 2339–2347. © 2017 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals, Inc.     

Gene or Size: Metabolic Rate and Body Temperature in Obese Growth Hormone‐Deficient Dwarf Mice

Objective: SMA1 mice carry a missense mutation in the growth hormone gene that leads to semidominant dwarfism and obesity. In this study, the basic thermal and metabolic properties of SMA1 mice were examined to detect metabolic alterations that can support the accretion of excess fat. Research Methods and Procedures: Basal and resting metabolic rates (RMRs) in wild‐type and SMA1 (sma1/+ and sma1/sma1) mice were determined by indirect calorimetry. Body temperature (T_b) was recorded using intraperitoneally implanted temperature‐sensitive transmitters, and body composition was determined by DXA. Results: SMA1 mice have proportionally lower basal and resting metabolic rates, higher body mass (BM)‐specific RMRs, and a higher lower critical temperature, and display a decrease in T_b by 0.4 °C in sma1/+ and 0.9 °C in sma1/sma1. Discussion: The analysis of gene effects on BM and energy expenditure in mouse mutants must consider the appropriate allometric relationship between BM and metabolic rate. With the exception of T_b, all metabolic alterations observed in SMA1 reflect reduced size.     

High-fat diets: modeling the metabolic disorders of human obesity in rodents

Research Methods and Procedures: High‐fat (HF) diet feeding can induce obesity and metabolic disorders in rodents that resemble the human metabolic syndrome. However, this dietary intervention is not standardized, and the HF‐induced phenotype varies distinctly among different studies. The question which HF diet type is best to model the metabolic deterioration seen in human obesity remains unclear. Therefore, in this review, metabolic data obtained with different HF diet approaches are compiled. Both whole‐body and organ‐specific diet effects are analyzed. Results: On the basis of these results, we conclude that animal fats and ω‐6/ω‐9‐containing plant oils can be used to generate an obese and insulin‐resistant phenotype in rodents, whereas fish oil‐fed animals do not develop these disorders. Discussion: Looking at the present data, it does not seem possible to define an ideal HF diet, and an exact definition of diet composition and a thorough metabolic characterization of the HF diet effects in a researcher's specific laboratory setting remains essential for metabolic studies with this model.     

Metabolic engineering of Escherichia coli for the production of polylactic acid and its copolymers

Polylactic acid (PLA) is a promising biomass‐derived polymer, but is currently synthesized by a two‐step process: fermentative production of lactic acid followed by chemical polymerization. Here we report production of PLA homopolymer and its copolymer, poly(3‐hydroxybutyrate‐co‐lactate), P(3HB‐co‐LA), by direct fermentation of metabolically engineered Escherichia coli. As shown in an accompanying paper, introduction of the heterologous metabolic pathways involving engineered propionate CoA‐transferase and polyhydroxyalkanoate (PHA) synthase for the efficient generation of lactyl‐CoA and incorporation of lactyl‐CoA into the polymer, respectively, allowed synthesis of PLA and P(3HB‐co‐LA) in E. coli, but at relatively low efficiency. In this study, the metabolic pathways of E. coli were further engineered by knocking out the ackA, ppc, and adhE genes and by replacing the promoters of the ldhA and acs genes with the trc promoter based on in silico genome‐scale metabolic flux analysis in addition to rational approach. Using this engineered strain, PLA homopolymer could be produced up to 11 wt% from glucose. Also, P(3HB‐co‐LA) copolymers containing 55–86 mol% lactate could be produced up to 56 wt% from glucose and 3HB. P(3HB‐co‐LA) copolymers containing up to 70 mol% lactate could be produced to 46 wt% from glucose alone by introducing the Cupriavidus necator β‐ketothiolase and acetoacetyl‐CoA reductase genes. Thus, the strategy of combined metabolic engineering and enzyme engineering allowed efficient bio‐based one‐step production of PLA and its copolymers. This strategy should be generally useful for developing other engineered organisms capable of producing various unnatural polymers by direct fermentation from renewable resources. Biotechnol. Bioeng. 2010; 105: 161–171. © 2009 Wiley Periodicals, Inc.     

A dynamic metabolic flux balance based model of fed‐batch fermentation of bordetella pertussis

A mathematical model based on a dynamic metabolic flux balance (DMFB) is developed for a process of fed‐batch fermentation of Bordetella pertussis. The model is based on the maximization of growth rate at each time interval subject to stoichiometric constraints. The model is calibrated and verified with experimental data obtained in two different bioreactor experimental systems. It was found that the model calibration was mostly sensitive to the consumption or production rates of tyrosine and, for high supplementation rates, to the consumption rate of glutamate. Following this calibration the model correctly predicts biomass and by‐products concentrations for different supplementation rates. Comparisons of model predictions to oxygen uptake and carbon emission rates measurements indicate that the TCA cycle is fully functional. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 520–531, 2013     

Thiolase engineering for enhanced butanol production in Clostridium acetobutylicum

Biosynthetic thiolases catalyze the condensation of two molecules acetyl‐CoA to acetoacetyl‐CoA and represent key enzymes for carbon–carbon bond forming metabolic pathways. An important biotechnological example of such a pathway is the clostridial n‐butanol production, comprising various natural constraints that limit titer, yield, and productivity. In this study, the thiolase of Clostridium acetobutylicum, the model organism for solventogenic clostridia, was specifically engineered for reduced sensitivity towards its physiological inhibitor coenzyme A (CoA‐SH). A high‐throughput screening assay in 96‐well microtiter plates was developed employing Escherichia coli as host cells for expression of a mutant thiolase gene library. Screening of this library resulted in the identification of a thiolase derivative with significantly increased activity in the presence of free CoA‐SH. This optimized thiolase comprised three amino acid substitutions (R133G, H156N, G222V) and its gene was expressed in C. acetobutylicum ATCC 824 to assess the effect of reduced CoA‐SH sensitivity on solvent production. In addition to a clearly delayed ethanol and acetone formation, the ethanol and butanol titers were increased by 46% and 18%, respectively, while the final acetone concentrations were similar to the vector control strain. These results demonstrate that thiolase engineering constitutes a suitable methodology applicable to improve clostridial butanol production, but other biosynthetic pathways involving thiolase‐mediated carbon flux limitations might also be subjected to this new metabolic engineering approach. Biotechnol. Bioeng. 2013; 110: 887–897. © 2012 Wiley Periodicals, Inc.     

Metabolic modeling of endosymbiont genome reduction on a temporal scale

A fundamental challenge in Systems Biology is whether a cell‐scale metabolic model can predict patterns of genome evolution by realistically accounting for associated biochemical constraints. Here, we study the order in which genes are lost in an in silico evolutionary process, leading from the metabolic network of Eschericia coli to that of the endosymbiont Buchnera aphidicola. We examine how this order correlates with the order by which the genes were actually lost, as estimated from a phylogenetic reconstruction. By optimizing this correlation across the space of potential growth and biomass conditions, we compute an upper bound estimate on the model's prediction accuracy (R=0.54). The model's network‐based predictive ability outperforms predictions obtained using genomic features of individual genes, reflecting the effect of selection imposed by metabolic stoichiometric constraints. Thus, while the timing of gene loss might be expected to be a completely stochastic evolutionary process, remarkably, we find that metabolic considerations, on their own, make a marked 40% contribution to determining when such losses occur.     

Model‐assisted identification of metabolic engineering strategies for Jatropha curcas lipid pathways

Efficient approaches to increase plant lipid production are necessary to meet current industrial demands for this important resource. While Jatropha curcas cell culture can be used for in vitro lipid production, scaling up the system for industrial applications requires an understanding of how growth conditions affect lipid metabolism and yield. Here we present a bottom‐up metabolic reconstruction of J. curcas supported with labeling experiments and biomass characterization under three growth conditions. We show that the metabolic model can accurately predict growth and distribution of fluxes in cell cultures and use these findings to pinpoint energy expenditures that affect lipid biosynthesis and metabolism. In addition, by using constraint‐based modeling approaches we identify network reactions whose joint manipulation optimizes lipid production. The proposed model and computational analyses provide a stepping stone for future rational optimization of other agronomically relevant traits in J. curcas.     

A comprehensive genome‐scale reconstruction of Escherichia coli metabolism—2011

The initial genome‐scale reconstruction of the metabolic network of Escherichia coli K‐12 MG1655 was assembled in 2000. It has been updated and periodically released since then based on new and curated genomic and biochemical knowledge. An update has now been built, named iJO1366, which accounts for 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites. iJO1366 was (1) updated in part using a new experimental screen of 1075 gene knockout strains, illuminating cases where alternative pathways and isozymes are yet to be discovered, (2) compared with its predecessor and to experimental data sets to confirm that it continues to make accurate phenotypic predictions of growth on different substrates and for gene knockout strains, and (3) mapped to the genomes of all available sequenced E. coli strains, including pathogens, leading to the identification of hundreds of unannotated genes in these organisms. Like its predecessors, the iJO1366 reconstruction is expected to be widely deployed for studying the systems biology of E. coli and for metabolic engineering applications.     

The miR‐379/miR‐410 cluster at the imprinted Dlk1‐Dio3 domain controls neonatal metabolic adaptation

In mammals, birth entails complex metabolic adjustments essential for neonatal survival. Using a mouse knockout model, we identify crucial biological roles for the miR‐379/miR‐410 cluster within the imprinted Dlk1‐Dio3 region during this metabolic transition. The miR‐379/miR‐410 locus, also named C14MC in humans, is the largest known placental mammal‐specific miRNA cluster, whose 39 miRNA genes are expressed only from the maternal allele. We found that heterozygote pups with a maternal—but not paternal—deletion of the miRNA cluster display partially penetrant neonatal lethality with defects in the maintenance of energy homeostasis. This maladaptive metabolic response is caused, at least in part, by profound changes in the activation of the neonatal hepatic gene expression program, pointing to as yet unidentified regulatory pathways that govern this crucial metabolic transition in the newborn's liver. Not only does our study highlight the physiological importance of miRNA genes that recently evolved in placental mammal lineages but it also unveils additional layers of RNA‐mediated gene regulation at the Dlk1‐Dio3 domain that impose parent‐of‐origin effects on metabolic control at birth and have likely contributed to mammal evolution.     

Coping strategies in a strongly schooling fish,the common carp Cyprinus carpio

Individual common carp Cyprinus carpio were screened repeatedly for risk taking (rate of exploration of a novel, potentially dangerous environment) and for competitive ability (success in gaining access to a spatially restricted food source). Marked differences in behaviour were evident, and significant consistency in individual responses across trials was found for both risk taking and competitive ability. In addition, there was a significant positive relationship between individual performance in these two contexts, with fish that explored more quickly in the novel environment tending to be among the first to gain access to restricted food. In two follow‐up studies, resting metabolic rate, blood lactate and glucose and the expression of the cortisol receptor gene in the head kidney and brain were compared in fish from the two extremes of the risk‐taking spectrum. Mass‐specific metabolic rate was significantly higher in risk‐taking than in risk‐avoiding fish, while plasma lactate and glucose concentrations and expression of the cortisol receptor gene were lower. It was concluded that a behavioural syndrome based on boldness and aggression exists in C. carpio, as it does in many other animals, and that this is associated with differences in metabolic and stress physiology (down to the genomic level) similar to those described in animals with different coping strategies.     

Meta‐analysis on the G‐308A Tumor Necrosis Factor α Gene Variant and Phenotypes Associated with the Metabolic Syndrome

Objective: The G‐308A tumor necrosis factor (TNF) α gene variant has been associated with obesity, insulin resistance, and hypertension. We performed a systematical review of the literature by means of a meta‐analysis to assess the association of the G‐308A TNFα polymorphism with the components of the metabolic syndrome. Research Methods and Procedures: Studies were identified by searches of the literature for reports using the terms: diabetes, insulin resistance, hypertension, obesity or metabolic syndrome and TNF, variants or polymorphism or alleles, and Nco or ?308. From 824 reports, we included 31 observational studies, case control and cohort at baseline, which analyzed the association between the TNFα polymorphism and one or more components of the metabolic syndrome. A fixed effect model was used to pool data from individual studies. Results: Obesity [odds ratio, 1.23; 95% confidence interval (CI), 1.045 to 1.45; p = 0.013] in a total of 3562 individuals from eight homogeneous studies, systolic arterial blood pressure (standardized difference, 0.132; 95% CI, 0.016 to 0.25; p < 0.03) in a total of 1624 individuals from four homogeneous studies and plasma insulin levels (standardized difference, 0.095; 95% CI, 0.020 to 0.17; p = 0.013) in a total of 3720 subjects from 16 homogeneous studies were positively associated with the ?308A variant. Discussion: These results indicate that individuals who carried the ?308A TNFα gene variant are at 23% risk of developing obesity compared with controls and showed significantly higher systolic arterial blood pressure and plasma insulin levels, supporting the hypothesis that the TNFα gene is involved in the pathogenesis of the metabolic syndrome.