Functional analysis of the ocnE gene involved in nicotine-degradation pathways in Ochrobactrum intermedium SCUEC4 and its enzymatic properties.

The SCUEC4 strain of Ochrobactrum intermedium is a newly isolated bacterium that degrades nicotine can use nicotine as the sole carbon source via a series of enzymatic catalytic processes. The mechanisms underlying nicotine degradation in this bacterium and the corresponding functional genes remain unclear. Here, we analyzed the function and biological properties of the ocnE gene involved in the nicotine-degradation pathways in strain SCUEC4. The ocnE gene was cloned by PCR with total DNA of strain SCUEC4 and used to construct the recombinant plasmid pET28a-ocnE. The overexpression of the OcnE protein was detected by SDS-PAGE analysis, and study of the function of this protein was spectrophotometrically carried out by monitoring the changes of 2,5-dihydroxypyridine. Moreover, the effects of temperature, pH, and metal ions on the biological activities of the OcnE protein were analyzed. The optimal conditions for the biological activities of OcnE, a protein of approximately 37.6 kDa, were determined to be 25 °C, pH 7.0, and 25 µmol/L Fe2+, and the suitable storage conditions for the OcnE protein were 0 °C and pH 7.0. In conclusion, the ocnE gene is responsible for the ability of 2,5-dihydroxypyridine dioxygenase. These findings will be beneficial in clarifying the mechanisms of nicotine degradation in O. intermedium SCUEC4.

MegaPath: sensitive and rapid pathogen detection using metagenomic NGS data.

BACKGROUND: Next-generation sequencing (NGS) enables unbiased detection of pathogens by mapping the sequencing reads of a patient sample to the known reference sequence of bacteria and viruses. However, for a new pathogen without a reference sequence of a close relative, or with a high load of mutations compared to its predecessors, read mapping fails due to a low similarity between the pathogen and reference sequence, which in turn leads to insensitive and inaccurate pathogen detection outcomes. RESULTS: We developed MegaPath, which runs fast and provides high sensitivity in detecting new pathogens. In MegaPath, we have implemented and tested a combination of polishing techniques to remove non-informative human reads and spurious alignments. MegaPath applies a global optimization to the read alignments and reassigns the reads incorrectly aligned to multiple species to a unique species. The reassignment not only significantly increased the number of reads aligned to distant pathogens, but also significantly reduced incorrect alignments. MegaPath implements an enhanced maximum-exact-match prefix seeding strategy and a SIMD-accelerated Smith-Waterman algorithm to run fast. CONCLUSIONS: In our benchmarks, MegaPath demonstrated superior sensitivity by detecting eight times more reads from a low-similarity pathogen than other tools. Meanwhile, MegaPath ran much faster than the other state-of-the-art alignment-based pathogen detection tools (and compariable with the less sensitivity profile-based pathogen detection tools). The running time of MegaPath is about 20 min on a typical 1 Gb dataset.

AC-DIAMOND v1: accelerating large-scale DNA-protein alignment.

Summary: AC-DIAMOND (v1) is a DNA-protein alignment tool designed to tackle the efficiency challenge of aligning large amount of reads or contigs to protein databases. When compared with the previously most efficient method DIAMOND, AC-DIAMOND gains a 6- to 7-fold speed-up, while retaining a similar degree of sensitivity. The improvement is rooted at two aspects: first, using a compressed index of seeds with adaptive-length to speed-up the matching between query and reference sequences; second, adopting a compact form of dynamic programing to fully utilize the parallelism of the SIMD capability. Availability and implementation: Software source codes and binaries available at https://github.com/Maihj/AC-DIAMOND/. Supplementary information: Supplementary data are available at Bioinformatics online.

Study on Interaction between Propargyl-Terminated Polybutadiene and Plasticizers Based on Simulation and Experiments.

Molecular dynamics (MD) simulation and experimental methods are used to explore the interaction between the propargyl-terminated polybutadiene (PTPB) binder and plasticizers bis(2,2-dinitropropyl) formal/acetal (BDNPF/A) and dioctyl sebacate (DOS). Flory-Huggins parameters, radial distribution functions, and binding energies between PTPB and plasticizers are calculated using MD simulations. The solubility parameters of PTPB and the plasticizers are calculated by both MD and group contribution method. The mesoscopic dynamics (MesoDyn) is used to simulate the meso-morphology of PTPB and plasticizer blends by converting the results of MD simulation into MesoDyn simulation parameters. The results of simulations and calculations show that PTPB has better compatibility with DOS than with BDNPF/A, and DOS is more suitable as a plasticizer for PTPB. The results of dynamic rheological experiments show that BDNPF/A has little effect on the dynamic viscosity of PTPB, and DOS can significantly reduce the dynamic viscosity of PTPB and has better plasticizing effect on PTPB. Differential scanning calorimetry and dynamic mechanical analysis tests indicate that the DOS and PTPB blend has only one glass transition temperature, while the PTPB and BDNPF/A blend has two glass transition temperatures. Both simulations and experimental results show that the PTPB binder have better compatibility with DOS than with BDNPF/A, and DOS has better plasticization effects on the PTPB binder.

MegaGTA: a sensitive and accurate metagenomic gene-targeted assembler using iterative de Bruijn graphs.

BACKGROUND: The recent release of the gene-targeted metagenomics assembler Xander has demonstrated that using the trained Hidden Markov Model (HMM) to guide the traversal of de Bruijn graph gives obvious advantage over other assembly methods. Xander, as a pilot study, indeed has a lot of room for improvement. Apart from its slow speed, Xander uses only 1 k-mer size for graph construction and whatever choice of k will compromise either sensitivity or accuracy. Xander uses a Bloom-filter representation of de Bruijn graph to achieve a lower memory footprint. Bloom filters bring in false positives, and it is not clear how this would impact the quality of assembly. Xander does not keep track of the multiplicity of k-mers, which would have been an effective way to differentiate between erroneous k-mers and correct k-mers. RESULTS: In this paper, we present a new gene-targeted assembler MegaGTA, which attempts to improve Xander in different aspects. Quality-wise, it utilizes iterative de Bruijn graphs to take full advantage of multiple k-mer sizes to make the best of both sensitivity and accuracy. Computation-wise, it employs succinct de Bruijn graphs (SdBG) to achieve low memory footprint and high speed (the latter is benefited from a highly efficient parallel algorithm for constructing SdBG). Unlike Bloom filters, an SdBG is an exact representation of a de Bruijn graph. It enables MegaGTA to avoid false-positive contigs and to easily incorporate the multiplicity of k-mers for building better HMM model. We have compared MegaGTA and Xander on an HMP-defined mock metagenomic dataset, and showed that MegaGTA excelled in both sensitivity and accuracy. On a large rhizosphere soil metagenomic sample (327Gbp), MegaGTA produced 9.7-19.3% more contigs than Xander, and these contigs were assigned to 10-25% more gene references. In our experiments, MegaGTA, depending on the number of k-mers used, is two to ten times faster than Xander. CONCLUSION: MegaGTA improves on the algorithm of Xander and achieves higher sensitivity, accuracy and speed. Moreover, it is capable of assembling gene sequences from ultra-large metagenomic datasets. Its source code is freely available at https://github.com/HKU-BAL/megagta .

MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices.

The study of metagenomics has been much benefited from low-cost and high-throughput sequencing technologies, yet the tremendous amount of data generated make analysis like de novo assembly to consume too much computational resources. In late 2014 we released MEGAHIT v0.1 (together with a brief note of Li et al. (2015) [1]), which is the first NGS metagenome assembler that can assemble genome sequences from metagenomic datasets of hundreds of Giga base-pairs (bp) in a time- and memory-efficient manner on a single server. The core of MEGAHIT is an efficient parallel algorithm for constructing succinct de Bruijn Graphs (SdBG), implemented on a graphical processing unit (GPU). The software has been well received by the assembly community, and there is interest in how to adapt the algorithms to integrate popular assembly practices so as to improve the assembly quality, as well as how to speed up the software using better CPU-based algorithms (instead of GPU). In this paper we first describe the details of the core algorithms in MEGAHIT v0.1, and then we show the new modules to upgrade MEGAHIT to version v1.0, which gives better assembly quality, runs faster and uses less memory. For the Iowa Prairie Soil dataset (252Gbp after quality trimming), the assembly quality of MEGAHIT v1.0, when compared with v0.1, has a significant improvement, namely, 36% increase in assembly size and 23% in N50. More interestingly, MEGAHIT v1.0 is no slower than before (even running with the extra modules). This is primarily due to a new CPU-based algorithm for SdBG construction that is faster and requires less memory. Using CPU only, MEGAHIT v1.0 can assemble the Iowa Prairie Soil sample in about 43h, reducing the running time of v0.1 by at least 25% and memory usage by up to 50%. MEGAHIT v1.0, exhibiting a smaller memory footprint, can process even larger datasets. The Kansas Prairie Soil sample (484Gbp), the largest publicly available dataset, can now be assembled using no more than 500GB of memory in 7.5days. The assemblies of these datasets (and other large metgenomic datasets), as well as the software, are available at the website https://hku-bal.github.io/megabox.

BASE: a practical de novo assembler for large genomes using long NGS reads.

BACKGROUND: De novo genome assembly using NGS data remains a computation-intensive task especially for large genomes. In practice, efficiency is often a primary concern and favors using a more efficient assembler like SOAPdenovo2. Yet SOAPdenovo2, based on de Bruijn graph, fails to take full advantage of longer NGS reads (say, 150 bp to 250 bp from Illumina HiSeq and MiSeq). Assemblers that are based on string graphs (e.g., SGA), though less popular and also very slow, are more favorable for longer reads. METHODS: This paper shows a new de novo assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs. RESULTS: Experiments on two bacteria and four human datasets shows the advantage of BASE in both contig quality and speed in dealing with longer reads. In the experiment on bacteria, two datasets with read length of 100 bp and 250 bp were used.. Especially for the 250 bp dataset, BASE gives much better quality than SOAPdenovo2 and SGA and is simlilar to SPAdes. Regarding speed, BASE is consistently a few times faster than SPAdes and SGA, but still slower than SOAPdenovo2. BASE and Soapdenov2 are further compared using human datasets with read length 100 bp, 150 bp and 250 bp. BASE shows a higher N50 for all datasets, while the improvement becomes more significant when read length reaches 250 bp. Besides, BASE is more-meory efficent than SOAPdenovo2 when sequencing data with error rate. CONCLUSIONS: BASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.

MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph.

MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement.

Base-assisted transmetalation enables gold-catalyzed oxidative Sonogashira coupling reaction.

The traditional transition metal catalyzed neutral C(sp)-C(sp2) cross-coupling reaction between a nucleophile and an electrophile is a key technique for the formation of carbon-carbon bonds. Herein, we present a general gold-catalyzed oxidative Sonogashira cross-coupling of arylboronic acids and terminal arylalkynes at room temperature with excellent functional-group tolerance and good chemoselectivity. Moreover, our mechanistic studies suggested a third pathway involving a base-assisted transmetalation between the gold(I) catalyst and aryl boronic acid might predominate in our reaction conditions, rather than the previously assumed oxidation of the gold(I) complex or deprotonation of alkynes.

Flame Retardancy of Nylon 6 Fibers: A Review.

As synthetic fibers with superior performances, nylon 6 fibers are widely used in many fields. Due to the potential fire hazard caused by flammability, the study of the flame retardancy of nylon 6 fibers has been attracting more and more attention. The review has summarized the present research status of flame-retarded nylon 6 fibers from three aspects: intrinsic flame-retarded nylon 6, nylon 6 composites, and surface strategies of nylon 6 fibers/fabrics. The current main focus is still how to balance the application performances, flame retardancy, and production cost. Moreover, melt dripping during combustion remains a key challenge for nylon 6 fibers, and the further developing trend is to study novel flame retardants and new flame-retardancy technologies for nylon 6 fibers.

Enhancing Char Formation and Flame Retardancy of Ethylene-Vinyl Acetate Copolymer (EVA)/Aluminum Hydroxide (ATH) Composites by Grafting Ladder Phenyl/Vinyl Polysilsesquioxane (PhVPOSS).

The ladder phenyl/vinyl polysilsesquioxane (PhVPOSS) was used to improve the flame-retardancy performances of ethylene-vinyl acetate copolymer (EVA)/aluminum hydroxide (ATH) composites due to the reactivity of its vinyl groups. FTIR, XPS, 1H NMR, and SEM-EDS data demonstrated the PhVPOSS grafting onto EVA molecular chains. The PhVPOSS improved the thermal stability of EVA/ATH composites, as shown by the thermogravimetric analysis (TGA). Furthermore, with the cone calorimeter (CONE) experiments, EVA/ATH/PhVPOSS showed better fire safety than the EVA/ATH composites, with the PHRR, PSPR, and PCOP reduced by 7.89%, 57.4%, and 90.9%, respectively. The mechanism investigations of flame retardancy revealed that the charring behaviors of the EVA/ATH/PhVPOSS composites were improved by the formation of Si-C bonds and Si-O bonds, and a more compact and denser char layer can contribute more to the barrier effect.

Fabrication of an Eco-Friendly Clay-Based Coating for Enhancing Flame Retardant and Mechanical Properties of Cotton Fabrics via LbL Assembly.

An eco-friendly clay-based synergistic flame-retardant coating was established on cotton fabrics via facile layer-by-layer assembly derived from polyethyleneimine (PEI), attapulgite clay (ATP), and phytic acid (PA). The fabricated flame-retardant (FR) cotton fabrics demonstrated improved thermal stability. Compared to untreated cotton fabrics, the limiting oxygen index of Cotton-8TL was improved to 27.0%. The peak heat release rates of the prepared FR cotton fabrics were lower than that of the pristine cotton fabrics, showing a maximum reduction of 41%. The deposition coating system improved the amount of char residue effectively. The intumescent flame-retardant mechanism was proposed through the analysis of char residue and the suppression properties of volatile gases. Furthermore, compared with those of the untreated cotton fabrics, the tensile strength and elongation at break of the FR cotton fabrics in the warp direction were improved by 20% and 47% remarkably, respectively. A feasible surface modification strategy was provided for the flame-retardant treatment of cotton fabrics with the improvement of mechanical properties.

A cross-linked charring strategy for mitigating the hazards of smoke and heat of aluminum diethylphosphonate/polyamide 6 by caged octaphenyl polyhedral oligomeric silsesquioxanes.

Aluminum diethylphosphonate (ADP) is a highly efficient phosphorus-based flame retardant, widely used in polyamide 6 (PA6). However, ADP/PA6 releases large amounts of heat and smoke under high heat flux, which commonly means serious hazards to life and property. Octaphenyl polyhedral oligomeric silsesquioxanes (OPS) is an organic-inorganic hybrid silicon compound, playing flame retardant role in condensed phase. In this work, combustion behaviors of OPS/ADP/PA6 were investigated by limited oxygen index (LOI), UL94 and cone calorimeter (CONE) tests. The LOI and UL94 rating results did not change obviously, while the CONE data and smoke density data showed the synergistic effect of OPS and ADP in PA6. For 2.5%OPS/7.5%ADP/PA6, the peak values of heat, smoke and CO release rate (pk-HRR, pk-RSR, Ds, max with/without pilot flame and pk-COP) decreased by 60.2%, 82.1%, 45.9%/38.3% and 80.4% respectively, compared with 10%ADP/PA6. Moreover, 2.5%OPS/7.5%ADP/PA6 produced 337.5% more residue than 10%ADP/PA6. TGA, TG-IR, SEM-EDS, XPS and py-GC/MS were used to further explore the synergistic mechanism of OPS and ADP. It was verified that the cross-linked charring strategy apparently has weakened the hazards of smoke and heat of PA6. This work proposed a possible technical approach to solve both fire risk and heat/smoke hazards of PA6.

Preparation and Characterization of TCPP-CaMMT Nanocompound and Its Composite with Polypropylene.

Based on the molecular dynamics method, the tris-(1-chloropropan-2yl) phosphate (TCPP)/montmorillonite (MMT) molecular model was established to study the binding energy and microstructure changes in TCPP and MMT. The theoretical simulation results showed that TCPP can enter the MMT layer and increase the layer spacing. From this, an organic intercalated Ca-montmorillonite TCPP-CaMMT was prepared by a very simple direct mixing method using flame retardant TCPP as a modifier. Polypropylene (PP) composites were prepared by TCPP, CaMMT, and TCPP-CaMMT. The microstructures of TCPP-CaMMT nanocompounds and PP composites were studied by X-ray diffraction (XRD), scanning electron microscope (SEM), and transmission electron microscope (TEM). The results showed that TCPP-CaMMT nanocompounds could be exfoliated into nanosheets in PP. The flame retardancy and mechanical properties of PP/TCPP-CaMMT samples were studied by limited oxygen index (LOI) measurements and tensile tests. The PP/TCPP-CaMMT composites showed better LOI, tensile strength, and elongation at break than the machine-mixed PP/TCPP + CaMMT.

Micro-Nanometer Particle Composition and Functional Design of Surface Nano-Structured Ammonium Polyphosphate and Its Application in Intumescent Flame-Retardant Polypropylene.

A novel composite and functional micro-nanometer particle is designed by the hydrolysis of aluminium isopropoxide on the surface of ammonium polyphosphate (APP) to prepare surface nanostructured ammonium polyphosphate (NSAPP). NSAPP is characterised by XPS, XRF, SEM, water solubility tests, and TGA. Results indicate that nanosized aluminium hydroxide is deposited on the surface of NSAPP, which enhanced its water resistance and thermostability. Then, APP and NSAPP coupled with dipentaerythritol (DPER) is used for the flame retardant of polypropylene (PP). The limiting oxygen index (LOI) value of the PP/DPER/NSAPP composite is higher than that of PP/DPER/APP. Besides, the UL 94 vertical burning test of PP/DPER/NSAPP composites can reach the V-0 rating easily. According to the study of the combustion behaviour of FR-PP composites, NSAPP contributes to form a dense and multi-layered char in the combustion process. Thus, such an intumescent char with a ceramic-like, continuous, and dense structure over the PP matrix protects the underlying matrix and enhances the thermal stability of the condensed phase, thereby improving the flame retardant performance of FR-PP.

Photoinduced inverse Sonogashira coupling reaction.

Alkynes are widely used in chemistry, medicine and materials science. Here we demonstrate a transition-metal and photocatalyst-free inverse Sonogashira coupling reaction between iodoalkynes and (hetero)arenes or alkenes under visible-light irradiation. Mechanistic and computational studies suggest that iodoalkynes can be directly activated by visible light irradiation, and an excited state iodoalkyne acted as an "alkynyl radical synthetic equivalent", reacting with a series of C(sp2)-H bonds for coupling products. This work should open new windows in radical chemistry and alkynylation method.

The Role of Intestinal Bacteria and Gut-Brain Axis in Hepatic Encephalopathy.

Hepatic encephalopathy (HE) is a neurological disorder that occurs in patients with liver insufficiency. However, its pathogenesis has not been fully elucidated. Pharmacotherapy is the main therapeutic option for HE. It targets the pathogenesis of HE by reducing ammonia levels, improving neurotransmitter signal transduction, and modulating intestinal microbiota. Compared to healthy individuals, the intestinal microbiota of patients with liver disease is significantly different and is associated with the occurrence of HE. Moreover, intestinal microbiota is closely associated with multiple links in the pathogenesis of HE, including the theory of ammonia intoxication, bile acid circulation, GABA-ergic tone hypothesis, and neuroinflammation, which contribute to cognitive and motor disorders in patients. Restoring the homeostasis of intestinal bacteria or providing specific probiotics has significant effects on neurological disorders in HE. Therefore, this review aims at elucidating the potential microbial mechanisms and metabolic effects in the progression of HE through the gut-brain axis and its potential role as a therapeutic target in HE.

Functional analysis of the agnH gene involved in nicotine-degradation pathways in Agrobacterium tumefaciens strain SCUEC1.

Agrobacterium tumefaciens strain SCUEC1 is a nicotine-degrading bacterium, which has been recently isolated from the tobacco waste-contaminated field soil. However, the mechanism for nicotine degradation in this strain remains unclear. Here, we analyze the function and biological properties of the agnH gene in the strain SCUEC1. The overexpression of the AgnH protein was detected by SDS-PAGE analysis, and functional insight of the AgnH protein was carried out with monitoring the changes of maleic acid into fumaric acid by high performance liquid chromatography (HPLC). Moreover, the effects of temperature, pH and metal ions on the enzymatic activities of the AgnH protein were also analyzed. The results demonstrated that the agnH gene was successfully ligated to the plasmid pET28a. The optimal condition for the enzymatic activities for the AgnH, approximately 28.0 kDa, was determined as 37 °C, pH 8.0 and 25 µM Mg2+. Conclusively, the agnH gene fulfils an important role in the conversion of maleic acid into fumaric acid involved in nicotine-degradation pathways in Agrobacterium tumefaciens strain SCUEC1.

Potential utility of metagenomic sequencing for improving etiologic diagnosis of infective endocarditis.

Aim: To explore potential utility of metagenomic sequencing for improving etiologic diagnosis of infective endocarditis (IE) caused by fastidious bacteria. Materials & methods: Plasma and heart valves of two patients, who were diagnosed with IE caused by Bartonella quintana and Propionibacterium species, were sequenced by using Illumina MiSeq and Nanopore MinION. Results: For patient 1, B. quintana was detected in the plasma pool collected 4 days before valvular replacement surgery. For patient 2, Propionibacterium sp. oral taxon 193 was detected in the plasma sample collected on hospital day 1. Nearly complete bacterial genomes (>98%) were retrieved from resected heart valves of both patients, enabling detection of antibiotic resistance-associated features. Real-time sequencing of heart valves identified both pathogens within the first 16 min of sequencing runs. Conclusion: Metagenomic sequencing may be a helpful supplement to IE diagnostic workflow, especially when conventional tests fail to yield a diagnosis.

Evaluation of meat as a first complementary food for breastfed infants: impact on iron intake.

The rationale for promoting the availability of local, affordable, non-fortified food sources of bioavailable iron in developing countries is considered in this review. Intake of iron from the regular consumption of meat from the age of 6 months is evaluated with respect to physiological requirements. Two major randomized controlled trials evaluating meat as a first and regular complementary food are described in this article. These trials are presently in progress in poor communities in Guatemala, Pakistan, Zambia, Democratic Republic of the Congo, and China.