Enhanced endoxylanase production by Myceliophthora thermophila using rice straw and its synergism with phytase in improving nutrition

The goal of the present investigation was to attain the enhanced production of endoxylanase in submerged fermentation using different approaches followed by its utility in improving nutrition of wheat and rice flours along with phytase. Myceliophthora thermophila BJTLRMDU3 produced 51.70 U/mL of xylanase using rice straw as a substrate after optimization with ‘one variable at a time’ approach. After Plackett-Burman design study, sodium nitrate, K₂HPO₄ and Tween 20 were selected as critical factors and further optimized by response surface methodology. Increased xylanase production (80.15 U/mL) was attained with 2.5 % (w/v) sodium nitrate, 1.25 % (w/v) K₂HPO₄, and 2 % (v/v) Tween 20 at 40 °C. An overall 1.5-fold increase in xylanase production was achieved after statistical optimization. Applicability of M. thermophila xylanase (200 U/g flour) alone and in combination with phytase (15 U/g flour) from Aspergillus oryzae SBS50 in wheat and rice flours showed enhancement in nutritional qualities of both flours. About 45.67 %, 29.73 %, and 107.91 % increase in reducing sugars, soluble proteins and inorganic phosphate, respectively in wheat flour, while 94.16 %, 134.52 %, and 473.33 % increase in reducing sugars, soluble proteins and inorganic phosphate, respectively in rice flour was achieved at 60 °C and pH 5.0 by synergistic action of xylanase and phytase as compared to control having only xylanase.     

Design,synthesis and anti-influenza A virus activity of novel 2,4-disubstituted quinazoline derivatives

Four 2,4-disubstituted quinazoline series containing various amide moieties were designed and synthesized as new anti-influenza A virus agents using the strategies of bio-isosterism and scaffold hopping. Many of them exhibit potent in vitro anti-influenza A virus activity and low cytotoxicity (CC₅₀: >100 μM). Particularly, compounds 10a5 and 17a show better activity (IC₅₀: 3.70–4.19 μM) and higher selective index (SI: >27.03, >23.87, respectively) against influenza A/WSN/33 virus (H1N1), opening a new direction for quinazoline derivatives in anti-influenza A virus field.     

Integration of high-throughput analytics and cell imaging enables direct early productivity and product quality assessment during Chinese Hamster ovary cell line development for a complex multi-subunit vaccine antigen

Mammalian cell line generation typically includes stable pool generation, single cell cloning and several rounds of clone selection based on cell growth, productivity and product quality criteria. Individual clone expansion and phenotype-based ranking is performed initially for hundreds or thousands of mini-scale cultures, representing the major operational challenge during cell line development. Automated cell culture and analytics systems have been developed to enable high complexity clone selection workflows; while ensuring traceability, safety, and quality of cell lines intended for biopharmaceutical applications. Here we show that comprehensive and quantitative assessment of cell growth, productivity, and product quality attributes are feasible at the 200–1,200 cell colony stage, within 14 days of the single cell cloning in static 96-well plate culture. The early cell line characterization performed prior to the clone expansion in suspension culture can be used for a single-step, direct selection of high quality clones. Such clones were comparable, both in terms of productivity and critical quality attributes (CQAs), to the top-ranked clones identified using an established iterative clone screening approach. Using a complex, multi-subunit antigen as a model protein, we observed stable CQA profiles independently of the cell culture format during the clonal expansion as well as in the batch and fed-batch processes. In conclusion, we propose an accelerated clone selection approach that can be readily incorporated into various cell line development workstreams, leading to significant reduction of the project timelines and resource requirements.     

Active and machine learning-based approaches to rapidly enhance microbial chemical production

In order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic models (e.g., kinetic/stoichiometric models of metabolism)—requiring many experimental datasets for their parameterization—while experimental methods may require screening large mutant libraries to explore the design space for the few mutants with desired behaviors. To address these limitations, we developed an active and machine learning approach (ActiveOpt) to intelligently guide experiments to arrive at an optimal phenotype with minimal measured datasets. ActiveOpt was applied to two separate case studies to evaluate its potential to increase valine yields and neurosporene productivity in Escherichia coli. In both the cases, ActiveOpt identified the best performing strain in fewer experiments than the case studies used. This work demonstrates that machine and active learning approaches have the potential to greatly facilitate metabolic engineering efforts to rapidly achieve its objectives.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

Structural and Biochemical Characterization of Compounds Inhibiting Mycobacterium tuberculosis Pantothenate Kinase

Mycobacterium tuberculosis, the bacterial causative agent of tuberculosis, currently affects millions of people. The emergence of drug-resistant strains makes development of new antibiotics targeting the bacterium a global health priority. Pantothenate kinase, a key enzyme in the universal biosynthesis of the essential cofactor CoA, was targeted in this study to find new tuberculosis drugs. The biochemical characterizations of two new classes of compounds that inhibit pantothenate kinase from M. tuberculosis are described, along with crystal structures of their enzyme-inhibitor complexes. These represent the first crystal structures of this enzyme with engineered inhibitors. Both classes of compounds bind in the active site of the enzyme, overlapping with the binding sites of the natural substrate and product, pantothenate and phosphopantothenate, respectively. One class of compounds also interferes with binding of the cofactor ATP. The complexes were crystallized in two crystal forms, one of which is in a new space group for this enzyme and diffracts to the highest resolution reported for any pantothenate kinase structure. These two crystal forms allowed, for the first time, modeling of the cofactor-binding loop in both open and closed conformations. The structures also show a binding mode of ATP different from that previously reported for the M. tuberculosis enzyme but similar to that in the pantothenate kinases of other organisms.     

Engineering the Pattern of Protein Glycosylation Modulates the Thermostability of a GH11 Xylanase

Protein glycosylation is a common post-translational modification, the effect of which on protein conformational and stability is incompletely understood. Here we have investigated the effects of glycosylation on the thermostability of Bacillus subtilis xylanase A (XynA) expressed in Pichia pastoris. Intact mass analysis of the heterologous wild-type XynA revealed two, three, or four Hex_8–16GlcNAc₂ modifications involving asparagine residues at positions 20, 25, 141, and 181. Molecular dynamics (MD) simulations of the XynA modified with various combinations of branched Hex₉GlcNAc₂ at these positions indicated a significant contribution from protein-glycan interactions to the overall energy of the glycoproteins. The effect of glycan content and glycosylation position on protein stability was evaluated by combinatorial mutagenesis of all six potential N-glycosylation sites. The majority of glycosylated enzymes expressed in P. pastoris presented increased thermostability in comparison with their unglycosylated counterparts expressed in Escherichia coli. Steric effects of multiple glycosylation events were apparent, and glycosylation position rather than the number of glycosylation events determined increases in thermostability. The MD simulations also indicated that clustered glycan chains tended to favor less stabilizing glycan-glycan interactions, whereas more dispersed glycosylation patterns favored stabilizing protein-glycan interactions.     

Design,synthesis and biological evaluation of novel aminothiazoles as antiviral compounds acting against human rhinovirus

We describe here the design, synthesis and biological evaluation of antiviral compounds acting against human rhinovirus (HRV). A series of aminothiazoles demonstrated pan-activity against the HRV genotypes screened and productive structure–activity relationships. A comprehensive investigational library was designed and performed allowing the identification of potent compounds with lower molecular weight and improved ADME profile. 31d-1, 31d-2, 31f showed good exposures in CD-1 mice. The mechanism of action was discovered to be a host target: the lipid kinase phosphatidylinositol 4-kinase III beta (PI4KIIIß). The identification of the pan-HRV active compound 31f combined with a structurally distinct literature compound T-00127-HEV1 allowed the assessment of target related tolerability of inhibiting this kinase for a short period of time in order to prevent HRV replication.     

New strigolactone mimics: Structure–activity relationship and mode of action as germinating stimulants for parasitic weeds

Strigolactones (SLs) are new plant hormones with varies important bio-functions. This Letter deals with germination of seeds of parasitic weeds. Natural SLs have a too complex structure for synthesis. Therefore, there is an active search for SL analogues and mimics with a simpler structure with retention of activity. SL analogues all contain the D-ring connected with an enone moiety through an enol ether unit. A new mechanism for the hydrolysis SL analogues involving bidentate bound water and an α,β-hydrolase with a Ser-His-Asp catalytic triad has been proposed. Newly discovered SL mimics only have the D-ring with an appropriate leaving group at C-5. A mode of action for SL mimics was proposed for which now supporting evidence is provided. As predicted an extra methyl group at C-4 of the D-ring blocks the germination of seeds of parasitic weeds.     

苦丁茶防晒组分萃取工艺的可视化分析

对采用超声辅助法萃取苦丁茶防晒组分进行了较为系统的研究。选择萃取时间、萃取剂体积分数、萃取温度、样品细度4个主要影响因素,运用多因素多水平可视化设计法安排实验。以防晒光区的紫外吸收面积值作为防晒组分萃取含量的实验评定指标。用自主提出的多因素多水平实验结果可视化分析方法对多维空间实验数据进行分析。得出当ρ(苦丁茶)=0.20 g/L时,最佳工艺范围为萃取时间30～60 min、萃取剂体积分数φ(C2H5OH)为50%～70%、萃取温度50～65℃、萃取样品细度140～160目。