Artificially designed routes for the conversion of starch to value-added mannosyl compounds through coupling in vitro and in vivo metabolic engineering strategies

Starch/cellulose has become the major feedstock for manufacturing biofuels and biochemicals because of their abundance and sustainability. In this study, we presented an artificially designed “starch-mannose-fermentation” biotransformation process through coupling the advantages of in vivo and in vitro metabolic engineering strategies together. Starch was initially converted into mannose via an in vitro metabolic engineering biosystem, and then mannose was fermented by engineered microorganisms for biomanufacturing valuable mannosyl compounds. The in vitro metabolic engineering biosystem based on phosphorylation/dephosphorylation reactions was thermodynamically favorable and the conversion rate reached 81%. The mannose production using whole-cell biocatalysts reached 75.4 g/L in a 30-L reactor, indicating the potential industrial application. Furthermore, the produced mannose in the reactor was directly served as feedstock for the fermentation process to bottom-up produced 19.2 g/L mannosyl-oligosaccharides (MOS) and 7.2 g/L mannosylglycerate (MG) using recombinant Corynebacterium glutamicum strains. Notably, such a mannose fermentation process facilitated the synthesis of MOS, which has not been achieved under glucose fermentation and improved MG production by 2.6-fold than that using the same C-mole of glucose. This approach also allowed access to produce other kinds of mannosyl derivatives from starch.     

Engineering Escherichia coli for methanol-dependent growth on glucose for metabolite production

Synthetic methylotrophy aims to engineer methane and methanol utilization pathways in platform hosts like Escherichia coli for industrial bioprocessing of natural gas and biogas. While recent attempts to engineer synthetic methanol auxotrophs have proved successful, these studies focused on scarce and expensive co-substrates. Here, we engineered E. coli for methanol-dependent growth on glucose, an abundant and inexpensive co-substrate, via deletion of glucose 6-phosphate isomerase (pgi), phosphogluconate dehydratase (edd), and ribose 5-phosphate isomerases (rpiAB). Since the parental strain did not exhibit methanol-dependent growth on glucose in minimal medium, we first achieved methanol-dependent growth via amino acid supplementation and used this medium to evolve the strain for methanol-dependent growth in glucose minimal medium. The evolved strain exhibited a maximum growth rate of 0.15 h⁻¹ in glucose minimal medium with methanol, which is comparable to that of other synthetic methanol auxotrophs. Whole genome sequencing and ¹³C-metabolic flux analysis revealed the causative mutations in the evolved strain. A mutation in the phosphotransferase system enzyme I gene (ptsI) resulted in a reduced glucose uptake rate to maintain a one-to-one molar ratio of substrate utilization. Deletion of the e14 prophage DNA region resulted in two non-synonymous mutations in the isocitrate dehydrogenase (icd) gene, which reduced TCA cycle carbon flux to maintain the internal redox state. In high cell density glucose fed-batch fermentation, methanol-dependent acetone production resulted in 22% average carbon labeling of acetone from ¹³C-methanol, which far surpasses that of the previous best (2.4%) found with methylotrophic E. coli Δpgi. This study addresses the need to identify appropriate co-substrates for engineering synthetic methanol auxotrophs and provides a basis for the next steps toward industrial one-carbon bioprocessing.     

Total in vitro biosynthesis of the nonribosomal macrolactone peptide valinomycin

Natural products are important because of their significant pharmaceutical properties such as antiviral, antimicrobial, and anticancer activity. Recent breakthroughs in DNA sequencing reveal that a great number of cryptic natural product biosynthetic gene clusters are encoded in microbial genomes, for example, those of Streptomyces species. However, it is still challenging to access compounds from these clusters because many source organisms are uncultivable or the genes are silent during laboratory cultivation. To address this challenge, we develop an efficient cell-free platform for the rapid, in vitro total biosynthesis of the nonribosomal peptide valinomycin as a model. We achieve this goal in two ways. First, we used a cell-free protein synthesis (CFPS) system to express the entire valinomycin biosynthetic gene cluster (>19 kb) in a single-pot reaction, giving rise to approximately 37 μg/L of valinomycin after optimization. Second, we coupled CFPS with cell-free metabolic engineering system by mixing two enzyme-enriched cell lysates to perform a two-stage biosynthesis. This strategy improved valinomycin production ~5000-fold to nearly 30 mg/L. We expect that cell-free biosynthetic systems will provide a new avenue to express, discover, and characterize natural product gene clusters of interest in vitro.     

Mixture design as a potential tool in modeling the effect of light wavelength on Dunaliella salina cultivation: an alternative solution to increase microalgae lipid productivity for biodiesel production

Abstract

For a feasible microalgae biodiesel, increasing lipid productivity is a key parameter. An important cultivation parameter is light wavelength (λ). It can affect microalgal growth, lipid yield, and fatty acid composition. In the current study, the mixture design was used as an alternative to model the influence of the λ on the Dunaliella salina lipid productivity. The illumination was considered to be the mixture of different λ (the light colors blue, red, and green). All experiments were performed with and without sodium acetate (4?g/L), as carbon source, allowing the identification of the impact of the cultivation regimen (autotrophic or mixotrophic). Without sodium acetate, the highest lipid productivity was obtained using blue and red light. The use of mixotrophic cultivations significantly enhanced the results. The optimum obtained result was mixotrophic cultivation under 65% blue and 35% green light, resulting in biomass productivity of 105.06 mgL^?1day^?1, a lipid productivity of 53.47 mgL^?1day^?1, and lipid content of 50.89%. The main fatty acids of the oil obtained in this cultivation were oleic acid (36.52%) and palmitic acid (18.31%).     

One size does not fit all: Customizing MCMC methods for hierarchical models using NIMBLE

Improved efficiency of Markov chain Monte Carlo facilitates all aspects of statistical analysis with Bayesian hierarchical models. Identifying strategies to improve MCMC performance is becoming increasingly crucial as the complexity of models, and the run times to fit them, increases. We evaluate different strategies for improving MCMC efficiency using the open‐source software NIMBLE (R package nimble) using common ecological models of species occurrence and abundance as examples. We ask how MCMC efficiency depends on model formulation, model size, data, and sampling strategy. For multiseason and/or multispecies occupancy models and for N‐mixture models, we compare the efficiency of sampling discrete latent states vs. integrating over them, including more vs. fewer hierarchical model components, and univariate vs. block‐sampling methods. We include the common MCMC tool JAGS in comparisons. For simple models, there is little practical difference between computational approaches. As model complexity increases, there are strong interactions between model formulation and sampling strategy on MCMC efficiency. There is no one‐size‐fits‐all best strategy, but rather problem‐specific best strategies related to model structure and type. In all but the simplest cases, NIMBLE's default or customized performance achieves much higher efficiency than JAGS. In the two most complex examples, NIMBLE was 10–12 times more efficient than JAGS. We find NIMBLE is a valuable tool for many ecologists utilizing Bayesian inference, particularly for complex models where JAGS is prohibitively slow. Our results highlight the need for more guidelines and customizable approaches to fit hierarchical models to ensure practitioners can make the most of occupancy and other hierarchical models. By implementing model‐generic MCMC procedures in open‐source software, including the NIMBLE extensions for integrating over latent states (implemented in the R package nimbleEcology), we have made progress toward this aim.     

Drought conditions alter litter decomposition and nutrient release of litter types in an agroforestry system of China

Evaluating how decomposition rates and litter nutrient release of different litter types respond to changes in water conditions is crucial for understanding global carbon and nutrient cycling. However, it is unclear how decreasing water affects litter mixture interactions for the maize–poplar system in arid regions. Here, the responses of the litter decomposition process and litter mixture interactions in the agroforestry system to changes in water conditions (control, light drought, and moderate drought) were tested. Moderate drought significantly decreased the decomposition rate for poplar leaf and mixed litters, and decomposition rate was significantly reduced for maize straw litter in light and moderate drought stress. The mass loss rates of maize straw and mixed litters were significantly higher than that of the poplar leaf litter under drought conditions, but there was no significant difference among the three litter types in the control. There was no interaction between mass loss of the mixed litter in the control and light drought conditions, and the litter mixture interaction showed nonadditive synergistic interactions under moderate drought. In terms of nutrient release, there was also no interaction between litter mixture with nitrogen and carbon, but there was antagonistic interaction with potassium release under the light drought condition. Our results demonstrate that drought conditions can lead to decreasing decomposition rate and strong changes in the litter mixture interactions from additive effects to nonadditive synergistic effects in moderate drought. Moreover, light drought changed the mixture interaction from an additive effect to an antagonistic interaction for potassium release.     

鼻饲中药抗休克合剂治疗重症烧伤休克期患者的疗效及对胃肠道复苏的影响

摘要 目的：探讨中药抗休克合剂经鼻饲给药法治疗重症烧伤休克期患者的疗效及对胃肠道复苏的影响。方法：选取上海中医药大学附属第七人民医院2017年10月至2020年9月期间收治的重症烧伤休克患者共计60例,将其按照随机数字表法分为对照组和实验组,每组各30例。对照组患者进行常规抗休克治疗,实验组在常规抗休克的基础上经鼻饲法给予中药抗休克合剂治疗。观察并记录两组患者复苏前、复苏后1 d、2 d、3 d的动脉血乳酸、内毒素水平,心率、尿量及补液量,腹胀缓解肠鸣音恢复时间、肛门排气时间,消化道不良反应、消化道出血发生率及有无继发全身性感染情况。结果：两组患者经治疗后血清内毒素和动脉血乳酸水平均呈不同趋势下降,复苏后1 d、2 d两组患者实验室指标虽有降低,但两组组间比较差异不显著（P＞0.05）,实验组患者复苏后3 d血清内毒素和动脉血乳酸值下降显著,且明显优于对照组,差异有统计学意义（P＜0.05）。实验组复苏后1 d、2 d补液量均较对照组更低（P<0.05）;实验组复苏后1 d、2 d尿量与对照组比较无统计学差异（P>0.05）,而复苏后3 d尿量较对照组更多（P<0.05）;实验组复苏后1 d、2 d、3 d心率均优于对照组（P<0.05）。实验组腹胀缓解肠鸣音恢复时间、肛门排气时间和消化不良反应、消化道出血、继发全身性感染发生率均低于对照组(P＜0.05)。结论：经鼻饲法给予中药抗休克合剂配合西医常规抗休克治疗,可发挥中医药特色,治疗重症烧伤休克期患者临床疗效明确,有助于胃肠道复苏,降低并发症及感染机率,具有一定的临床价值。     

北京市珍珠泉乡不同昆虫采集方法采集效果对比分析

为了探究科研调查中不同昆虫采集方法的采集效率差异,在北京珍珠泉乡不同的生境类型中,采用样线法、马氏网法、灯诱法、陷阱法(糖醋液)4种采集方法进行昆虫采集,按生境类型对不同采集方法采集的昆虫进行统计分析.在实验中共采集昆虫3996头,隶属12目87科,其中在昆虫种类数量上,鳞翅目最多,其次是半翅目和鞘翅目;在数量上,半翅目昆虫数量最多,依次是双翅目和鳞翅目.样线法共采集到昆虫61科72种、灯诱法共采集到45科95种、马氏网法共采集到39科41种、陷阱法共采集到14科25种.在调查中,不同方法在不同生境采集昆虫种类数多存在显著差异(P<0.05).不同的采集方式间除马氏网和样线法采集昆虫的种类相似度为中等不相似(q=0.436),其他方法间均为极不相似.采用不同的采集方式可以采集到更多的昆虫种类.马氏网法是最优选的采集方式,马氏网采集昆虫最方便,节省人力;样线法采集的效果最稳定;灯诱法的采集效果好,但是应用较为复杂;糖醋液陷阱法采集昆虫效率对比其他三种方法,既不能采集到大量昆虫也没有采集到特定种昆虫,如无特别需求可以考虑减少或者放弃使用.