The secondary metabolite bioinformatics portal:Computational tools to facilitate synthetic biology of secondary metabolite production

AbstractNatural products are among the most important sources of lead molecules for drug discovery. With the development of affordable whole-genome sequencing technologies and other ‘omics tools, the field of natural products research is currently undergoing a shift in paradigms. While, for decades, mainly analytical and chemical methods gave access to this group of compounds, nowadays genomics-based methods offer complementary approaches to find, identify and characterize such molecules. This paradigm shift also resulted in a high demand for computational tools to assist researchers in their daily work. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http://www.secondarymetabolites.org) is introduced to provide a one-stop catalog and links to these bioinformatics resources. In addition, an outlook is presented how the existing tools and those to be developed will influence synthetic biology approaches in the natural products field

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

Background: Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology.Results: We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model.Conclusions: After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis

Conventional Vickers and true instrumented indentation hardness determined by instrumented indentation tests

We evaluate Vickers hardness and true instrumented indentation test (IIT) hardness of 24 metals over a wide range of mechanical properties using just IIT parameters by taking into account the real contact morphology beneath the Vickers indenter. Correlating the conventional Vickers hardness, indentation contact morphology, and IIT parameters for the 24 metals reveals relationships between contact depths and apparent material properties. We report the conventional Vickers and true IIT hardnesses measured only from IIT contact depths; these agree well with directly measured hardnesses within ±6% for Vickers hardness and ±10% for true IIT hardness

Metabolic engineering with systems biology tools to optimize production of prokaryotic secondary metabolites

This Highlight examines current status of metabolic engineering and systems biology tools deployed for the optimal production of prokaryotic secondary metabolites.</p

Effects of Distilled Cervi Pantotrichum Cornu and Rehmannia glutinosa Pharmacopuncture at GB21 (Jianjing) on Heart Rate Variability: A Randomized and Double-blind Clinical Trial

AbstractBackground/PurposeThe purpose of this study was to use heart rate variability (HRV) to investigate the effects of distilled Cervi Pantotrichum Cornu pharmacopuncture and Rehmannia glutinosa pharmacopuncture on the autonomic nervous system.Materials and methodsForty healthy male participants were divided into two groups: the participants of the C-group received distilled Cervi Pantotrichum Cornu pharmacopuncture and those of the R-group received Rehmannia glutinosa pharmacopuncture. The study design was a randomized, double-blind clinical trial. Each participant received one of the two solutions injected at GB21 (Jianjing). The changes in HRV were measured seven times using the QECG-3: LXC3203 system (LAXTHA Inc. Korea). Time-dependent changes in HRV for each group were analyzed using the paired t test (significance level: p < 0.05), and the difference in the HRV fluctuations between the two experimental groups was evaluated using the independent sample test (significance level: p < 0.05).Results and conclusionThe results showed that Cervi Pantotrichum Cornu pharmacopuncture and Rehmannia glutinosa pharmacopuncture tended to activate the autonomic nervous system within the normal range. Cervi Pantotrichum Cornu pharmacopuncture tended to activate the sympathetic nervous system, whereas Rehmannia glutinosa pharmacopuncture tended to activate both the sympathetic and parasympathetic nervous systems

Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters

Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats such as rule-based BGC detection, sequence and annotation quality and cluster boundary prediction, which all have to be considered while planning for, performing and analyzing the results of genome mining studies

Current evidence and the potential role of proton beam therapy for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death, and external beam radiation therapy has emerged as a promising approach for managing HCC. Proton beam therapy (PBT) offers dosimetric advantages over X-ray therapy, with superior physical properties known as the Bragg peak. PBT holds promise for reducing hepatotoxicity and allowing safe dose-escalation to the tumor. It has been tried in various clinical conditions and has shown promising local tumor control and survival outcomes. A recent phase III trial demonstrated the non-inferiority of PBT in local tumor control compared to current standard radiofrequency ablation in early-stage HCC. PBT also tended to show more favorable outcomes compared to transarterial chemoembolization in the intermediate stage, and has proven effective in-field disease control and safe toxicity profiles in advanced HCC. In this review, we discuss the rationale, clinical studies, optimal indication, and future directions of PBT in HCC treatment

Two-gap and paramagnetic pair-breaking effects on upper critical field of SmFeAsO0.85_{0.85} and SmFeAsO0.8_{0.8}F0.2_{0.2} single crystals

We investigated the temperature dependence of the upper critical field [$H_{c2}(T)$] of fluorine-free SmFeAsO$_{0.85}$ and fluorine-doped SmFeAsO$_{0.8}$F$_{0.2}$ single crystals by measuring the resistive transition in low static magnetic fields and in pulsed fields up to 60 T. Both crystals show that $H_{c2}(T)$'s along the c axis [$H_{c2}^c(T)$] and in an $ab$-planar direction [$H_{c2}^{ab}(T)$] exhibit a linear and a sublinear increase, respectively, with decreasing temperature below the superconducting transition. $H_{c2}(T)$'s in both directions deviate from the conventional one-gap Werthamer-Helfand-Hohenberg theoretical prediction at low temperatures. A two-gap nature and the paramagnetic pair-breaking effect are shown to be responsible for the temperature-dependent behavior of $H_{c2}^c$ and $H_{c2}^{ab}$, respectively.Comment: 21 pages, 8 figure

Perspective and Potential of Smart Optical Materials

The increasing requirements of hyperspectral imaging optics, electro/photo-chromic materials, negative refractive index metamaterial optics, and miniaturized optical components from microscale to quantum-scale optics have all contributed to new features and advancements in optics technology. Development of multifunctional capable optics has pushed the boundaries of optics into new fields that require new disciplines and materials to maximize the potential benefits. The purpose of this study is to understand and show the fundamental materials and fabrication technology for field-controlled spectrally active optics (referred to as smart optics) that are essential for future industrial, scientific, military, and space applications, such as membrane optics, light detection and ranging (LIDAR) filters, windows for sensors and probes, telescopes, spectroscopes, cameras, light valves, light switches, and flat-panel displays. The proposed smart optics are based on the Stark and Zeeman effects in materials tailored with quantum dot arrays and thin films made from readily polarizable materials via ferroelectricity or ferromagnetism. Bound excitonic states of organic crystals are also capable of optical adaptability, tunability, and reconfigurability. To show the benefits of smart optics, this paper reviews spectral characteristics of smart optical materials and device technology. Experiments testing the quantum-confined Stark effect, arising from rare earth element doping effects in semiconductors, and applied electric field effects on spectral and refractive index are discussed. Other bulk and dopant materials were also discovered to have the same aspect of shifts in spectrum and refractive index. Other efforts focus on materials for creating field-controlled spectrally smart active optics (FCSAO) on a selected spectral range. Surface plasmon polariton transmission of light through apertures is also discussed, along with potential applications. New breakthroughs in micro scale multiple zone plate optics as a micro convex lens are reviewed, along with the newly discovered pseudo-focal point not predicted with conventional optics modeling. Micron-sized solid state beam scanner chips for laser waveguides are reviewed as well