Role of heterotrophic nitrifiers and aerobic denitrifiers in simultaneous nitrification and denitrification process: a nonconventional nitrogen removal pathway in wastewater treatment

Bacterial species capable of performing both nitrification and denitrification in a single vessel under similar conditions have gained significance in the wastewater treatment scenario considering their unique character of performing the above reactions under heterotrophic and aerobic conditions respectively. Such a novel strategy often referred to as simultaneous nitrification and denitrification (SND) has a tremendous potential in dealing with various wastewaters having low C : N content, considering that the process needs very little or no external carbon source and oxygen supply thus adding to its cost-effective and environmentally friendly nature. Though like other micro-organisms, heterotrophic nitrifiers and aerobic denitrifiers convert inorganic or organic nitrogen-containing substances into harmless dinitrogen gas in the wastewater, their ecophysiological role in the global nitrogen cycle is still not fully understood. Attempts to highlight the role played by the heterotrophic nitrifiers and aerobic denitrifiers in dealing with nitrogen pollution under various environmental operating conditions will help in developing a mechanistic understanding of the SND process to address the issues faced by the traditional methods of aerobic autotrophic nitrification–anaerobic heterotrophic denitrification.     

Seasonal and interannual variations of ecosystem photosynthetic characteristics in a semi-arid grassland of Northern China

北方半干旱草原生态系统光合参数的季节和年际变异 生态系统表观量子效率(α)、最大光合速率(P_max)和暗呼吸速率(R_d)不仅反映了生态系统水平 光合生理特征,同时也是碳循环模型中光合过程模拟的关键参数。气候和植被因子都会影 响光合参数的季节和年际变异,但二者在光合参数调控过程中的相对贡献和作用途径尚不清晰。本研究基于连续12年(2006–2017)的涡度相关观测数据,分析了内蒙古半干旱典型草原光合参数的季节和年际变化规律;利用回归分析和结构方程模型(SEM)方法明晰了环境和生理调控的作用途径及相对贡献。结果发现,光合参数(α、P_max和R_d)均表现出单峰的季节变化趋势,并呈现明显的年际波动。温度(T_a)和土壤含水量(SWC)的变化共同影响光合参数的季节变化,而SWC主导了其年际变异。α和R_d的变化主要由T_a决定,而Pmax的变化主要受SWC的影响。SEM模型分析表明,除了直接作用外,环境因子主要通过影响冠层水平气孔导度(gc)对光合参数和碳同化生理过程进行调控。此外,叶面积指数对光合参数特别是Pmax的季节和年际变异起主要调控作用。以上结果明确了环境和植被共同决定了生态系统水平光合参数的季节和年际变异,并强调了在水分受限的草原生态系统中,植被生理调控在光合碳同化能力和碳汇功能评估中的重要作用。     

Reconstruction of tricarboxylic acid cycle in Corynebacterium glutamicum with a genome-scale metabolic network model for trans-4-hydroxyproline production

trans-4-Hydroxy- l -proline (Hyp) is an abundant component of mammalian collagen and functions as a chiral synthon for the syntheses of anti-inflammatory drugs in the pharmaceutical industry. Proline 4-hydroxylase (P4H) can catalyze the conversion of l -proline to Hyp; however, it is still challenging for the fermentative production of Hyp from glucose using P4H due to the low yield and productivity. Here, we report the metabolic engineering of Corynebacterium glutamicum for the fermentative production of Hyp by reconstructing tricarboxylic acid (TCA) cycle together with heterologously expressing the p4h gene from Dactylosporangium sp. strain RH1. In silico model-based simulation showed that α-ketoglutarate was redirected from the TCA cycle toward Hyp synthetic pathway driven by P4H when the carbon flux from succinyl-CoA to succinate descended to zero. The interruption of the TCA cycle by the deletion of sucCD-encoding the succinyl-CoA synthetase (SUCOAS) led to a 60% increase in Hyp production and had no obvious impact on the growth rate. Fine-tuning of plasmid-borne ProB* and P4H abundances led to a significant increase in the yield of Hyp on glucose. The final engineered Hyp-7 strain produced up to 21.72 g/L Hyp with a yield of 0.27 mol/mol (Hyp/glucose) and a volumetric productivity of 0.36 g·L ⁻¹·hr ⁻¹ in the shake flask fermentation. To our knowledge, this is the highest yield and productivity achieved by microbial fermentation in a glucose-minimal medium for Hyp production. This strategy provides new insights into engineering C. glutamicum by flux coupling for the fermentative production of Hyp and related products.     

Hybrid physics-based and data-driven modeling for bioprocess online simulation and optimization

Model-based online optimization has not been widely applied to bioprocesses due to the challenges of modeling complex biological behaviors, low-quality industrial measurements, and lack of visualization techniques for ongoing processes. This study proposes an innovative hybrid modeling framework which takes advantages of both physics-based and data-driven modeling for bioprocess online monitoring, prediction, and optimization. The framework initially generates high-quality data by correcting raw process measurements via a physics-based noise filter (a generally available simple kinetic model with high fitting but low predictive performance); then constructs a predictive data-driven model to identify optimal control actions and predict discrete future bioprocess behaviors. Continuous future process trajectories are subsequently visualized by re-fitting the simple kinetic model (soft sensor) using the data-driven model predicted discrete future data points, enabling the accurate monitoring of ongoing processes at any operating time. This framework was tested to maximize fed-batch microalgal lutein production by combining with different online optimization schemes and compared against the conventional open-loop optimization technique. The optimal results using the proposed framework were found to be comparable to the theoretically best production, demonstrating its high predictive and flexible capabilities as well as its potential for industrial application.     

A new generation of predictive models: The added value of hybrid models for manufacturing processes of therapeutic proteins

Due to the lack of complete understanding of metabolic networks and reaction pathways, establishing a universal mechanistic model for mammalian cell culture processes remains a challenge. Contrarily, data-driven approaches for modeling these processes lack extrapolation capabilities. Hybrid modeling is a technique that exploits the synergy between the two modeling methods. Although mammalian cell cultures are among the most relevant processes in biotechnology and indeed looks ideal for hybrid modeling, their application has only been proposed but never developed in the literature. This study provides a quantitative assessment of the improvement brought by hybrid models with respect to the state-of-the-art statistical predictive models in the context of therapeutic protein production. This is illustrated using a dataset obtained from a 3.5 L fed-batch experiment. With the goal to robustly define the process design space, hybrid models reveal a superior capability to predict the time evolution of different process variables using only the initial and process conditions in comparison to the statistical models. Hybrid models not only feature more accurate prediction results but also demonstrate better robustness and extrapolation capabilities. For the future application, this study highlights the added value of hybrid modeling for model-based process optimization and design of experiments.     

Streptomycin-induced ribosome engineering complemented with fermentation optimization for enhanced production of 10-membered enediynes tiancimycin-A and tiancimycin-D

Tiancimycins (TNMs) are a group of 10-membered anthraquinone-fused enediynes, newly discovered from Streptomyces sp. CB03234. Among them, TNM-A and TNM-D have exhibited excellent antitumor performances and could be exploited as very promising warheads for the development of anticancer antibody-drug conjugates (ADCs). However, their low titers, especially TNM-D, have severely limited following progress. Therefore, the streptomycin-induced ribosome engineering was adopted in this work for strain improvement of CB03234, and a TNMs high producer S. sp. CB03234-S with the K43N mutation at 30S ribosomal protein S12 was successfully screened out. Subsequent media optimization revealed the essential effects of iodide and copper ion on the production of TNMs, while the substitution of nitrogen source could evidently promote the accumulation of TNM-D, and the ratio of produced TNM-A and TNM-D was responsive to the change of carbon and nitrogen ratio in the medium. Further amelioration of the pH control in scaled up 25 L fermentation increased the average titers of TNM-A and TNM-D up to 13.7 ± 0.3 and 19.2 ± 0.4 mg/L, respectively. The achieved over 45-fold titer improvement of TNM-A, and 109-fold total titer improvement of TNM-A and TNM-D enabled the efficient purification of over 200 mg of each target molecule from 25 L fermentation. Our efforts have demonstrated a practical strategy for titer improvement of anthraquinone-fused enediynes and set up a solid base for the pilot scale production and preclinical studies of TNMs to expedite the future development of anticancer ADC drugs.     

检测pT_(1-4a)N_(1-3)M_0期胃癌淋巴结微转移检测的临床意义

目的:探讨胃癌淋巴结微转移及临床病理因素对p T1-4aN1-3M0期胃癌患者术后5年无瘤生存率的影响。方法:选取我院2009年1月至12月期间胃肠外科单一手术组行D2胃癌根治术p T1-4aN1-3M0期患者63例1427枚HE染色阴性淋巴结,应用免疫组化法检测这些淋巴结中CK19表达,观察微转移的情况并分析发生微转移的胃癌患者临床病理特征及对患者5年无瘤生存率的影响。结果:临床病理分期p T1-4aN1-3M0胃癌患者中,经免疫组化染色,1427枚HE常规染色阴性淋巴结中CK19阳性表达率为15.49%(221/1427);63例胃癌患者中CK19表达阳性率39.68%(25/63);术后随访时间5.6~68.5月(平均时间43.88月),淋巴结中CK19阴性表达、阳性表达患者的总5年生存率分别为52.63%、28.00%;两者无瘤生存率差异有统计学意义(x2=8.677,P=0.003)。淋巴结CK19阳性表达与胃癌患者的肿瘤直径(P0.05)、浸润胃壁深度(P0.05)有关。COX生存回归分析显示淋巴结微转移为独立预后因素。25例患者发现淋巴结微转移并推荐再分期,再分期率39.68%(25/63)。结论:p T1-4aN1-3M0期胃癌病人,CK-19免疫组化法染色能检出常规HE染色阴性淋巴结中的微转移,有助于细化分期、判断预后及指导治疗。     

纳豆激酶基因的优化设计、合成及其在烟草叶片中的瞬时表达

根据植物偏爱密码子优化设计、合成纳豆激酶基因sNK,利用重叠延伸PCR法在其中插入番茄果实特异性表达基因E8的第一内含子构成sNKi基因,通过农杆菌渗透法将这两种基因渗入到烟草NC89叶片中并实现瞬时表达。通过RT-qPCR法将两种基因在烟草叶片中转录水平的表达量进行比较,结果表明两种基因在烟草叶片中均表达,且sNKi基因的表达量显著高于sNK基因;通过纤维蛋白平板法在两种基因的瞬时表达样品中均能检测到纤溶酶活性,表明目的基因在烟草叶片中可正常翻译并表现出溶栓活性,且sNKi基因在翻译水平的表达量显著高于sNK基因。表明内含子对人工合成的纳豆激酶基因的瞬时表达具有显著的促进作用。     

Characterization of a model cyanobacterium Synechocystis sp. PCC 6803 autotrophic growth in a flat‐panel photobioreactor

We characterized the photoautotrophic growth of glucose‐tolerant Synechocystis sp. PCC 6803 in a flat‐panel photobioreactor running on a semicontinuous regime under various lights, temperatures, and influx carbon dioxide concentrations. The maximum reached growth rate was 0.135 h^?1, which corresponds to a doubling time of 5.13 h—a growth speed never reported for Synechocystis before. Saturating red light intensity for the strain was 220–360 μmol(photons) m^?2 s^?1, and we did not observe any photoinhibition up to 660 μmol(photons) m^?2 s^?1. Synechocystis was able to grow under red light only; however, photons of wavelengths 405–585 and 670–700 nm further improved its growth. Optimal growth temperature was 35°C. Below 32°C, the growth rates decreased linearly with temperature coefficient (Q₁₀) 1.70. Semicontinuous cultivation is known to be efficient for growth characterization and optimization. However, the assumption of correct growth rates calculation—culture exponential growth—is often not fulfilled. The semicontinuous setup in this study was operated as a turbidostat. Accurate online OD measurements with high time‐resolution allowed fast and reliable growth rates determination. Repeating diluting frequencies (up to 18 dilutions per day) were essential for rapid growth stability evaluation. The presented setup provides improvement to previously published semicontinuous characterization strategies by decreasing experimental time requirements and maintaining the culture in exponential growth phase throughout the entire characterization procedure.     

垃圾微生物除臭剂的筛选、复配及其培养条件的优化

为了获取作为除臭微生物制剂的候选菌株,从垃圾渗滤液中分离筛选了4株具有对硫化氢和氨气高效降解菌株,分别标记为CC3、CC7、CC13和CC16。通过形态、生理生化和16S rDNA序列分析,分别鉴定为乳酸片球菌（Pediococcus acidilactici）、巨大芽胞杆菌（Bacillus megaterium）、嗜酸乳杆菌（Lactobacillus acidophilus）、粪产碱杆菌（Alcaligenes faecalis）,并确定复配菌剂的除臭能力。实验结果表明：菌株CC7、CC13和CC16组成的复配组合除臭效率最优,其最佳复配比例为1:1.5:0.5,接种量为5%,培养温度为30 ℃,初始培养基pH值为6.5,培养时间为60 h时,对氨气和硫化氢的去除率为最大值,可达到83.56%和70.25%。