Research of wet string grid dust removal vehicle and creation of dust control area on tunnel working face.

The spread of blast dust throughout the tunnel becomes a common problem in drill and blast tunneling,the key to breaking through the problem is the creation of a dust control area on the working face.In view of this key problem, a wet string grid dust removal crawler vehicle was developed, the power of the vehicle came from the diesel generator, and further, the air cooler of the diesel generator was used to generate airflow, and the suction process formed by the on-board axial flow fan was coupled to create a dust control area of the working face after blasting.The results show that when the frequency of the axial flow fan is adjusted to 30 Hz, the airflow speed of the wet chord grid section reaches 3.34 m/s, and the dust removal efficiency is the highest, with a value of 94.3%.Compared with the non-use of the dust removal vehicle, when the air outlet of the air cooler is front, horizontal front, horizontal rear, the dust concentration is reduced by 74.37, 92.39 and 50.53%.Finally, the optimized wet grid dust removal crawler was installed in the Dading tunnel, and the actual dust reduction efficiency was about 78.49%. The results obtained provide an important technical way to improve the working environment of the drilling and blasting construction tunnel.

A Novel Tiled Amplicon Sequencing Assay Targeting the Tomato Brown Rugose Fruit Virus (ToBRFV) Genome Reveals Widespread Distribution in Municipal Wastewater Treatment Systems in the Province of Ontario, Canada.

Tomato Brown Rugose Fruit Virus (ToBRFV) is a plant pathogen that infects important Solanaceae crop species and can dramatically reduce tomato crop yields. The ToBRFV has rapidly spread around the globe due to its ability to escape detection by antiviral host genes which confer resistance to other tobamoviruses in tomato plants. The development of robust and reproducible methods for detecting viruses in the environment aids in the tracking and reduction of pathogen transmission. We detected ToBRFV in municipal wastewater influent (WWI) samples, likely due to its presence in human waste, demonstrating a widespread distribution of ToBRFV in WWI throughout Ontario, Canada. To aid in global ToBRFV surveillance efforts, we developed a tiled amplicon approach to sequence and track the evolution of ToBRFV genomes in municipal WWI. Our assay recovers 95.7% of the 6393 bp ToBRFV RefSeq genome, omitting the terminal 5' and 3' ends. We demonstrate that our sequencing assay is a robust, sensitive, and highly specific method for recovering ToBRFV genomes. Our ToBRFV assay was developed using existing ARTIC Network resources, including primer design, sequencing library prep, and read analysis. Additionally, we adapted our lineage abundance estimation tool, Alcov, to estimate the abundance of ToBRFV clades in samples.

Pareto Dominance Archive and Coordinated Selection Strategy-Based Many-Objective Optimizer for Protein Structure Prediction.

Protein structure prediction (PSP) is predicting the three-dimensional of protein from its amino acid sequence only based on the information hidden in the protein sequence. One of the efficient tools to describe this information is protein energy functions. Despite the advancements in biology and computer science, PSP is still a challenging problem due to its large protein conformation space and inaccurate energy functions. In this study, PSP is treated as a many-objective optimization problem and four conflicting energy functions are used as different objectives to be optimized. A novel Pareto-dominance-archive and Coordinated-selection-strategy-based Many-objective-optimizer (PCM) is proposed to perform the conformation search. In it, convergence and diversity-based selection metrics are used to enable PCM to find near-native proteins with well-distributed energy values, while a Pareto-dominance-based archive is proposed to save more potential conformations that can guide the search to more promising conformation areas. The experimental results on thirty-four benchmark proteins demonstrate the significant superiority of PCM in comparison with other single, multiple, and many-objective evolutionary algorithms. Additionally, the inherent characteristics of iterative search of PCM can also give more insights into the dynamic progress of protein folding besides the final predicted static tertiary structure. All these confirm that PCM is a fast, easy-to-use, and fruitful solution generation method for PSP.

Fully Complex-Valued Dendritic Neuron Model.

A single dendritic neuron model (DNM) that owns the nonlinear information processing ability of dendrites has been widely used for classification and prediction. Complex-valued neural networks that consist of a number of multiple/deep-layer McCulloch-Pitts neurons have achieved great successes so far since neural computing was utilized for signal processing. Yet no complex value representations appear in single neuron architectures. In this article, we first extend DNM from a real-value domain to a complex-valued one. Performance of complex-valued DNM (CDNM) is evaluated through a complex XOR problem, a non-minimum phase equalization problem, and a real-world wind prediction task. Also, a comparative analysis on a set of elementary transcendental functions as an activation function is implemented and preparatory experiments are carried out for determining hyperparameters. The experimental results indicate that the proposed CDNM significantly outperforms real-valued DNM, complex-valued multi-layer perceptron, and other complex-valued neuron models.

Isolation of Genes Encoding Carbon Metabolism Pathways from Complex Microbial Communities.

The ability to produce high-value products using bacteria will increasingly rely on continued research to make large-scale bacterial fermentation cost-efficient. Engineering bacteria to use alternate carbon sources as feedstock provides an opportunity to reduce production costs. Using inexpensive carbon sources from various forms of waste provides an opportunity to substantially reduce feedstock costs. Functional carbon metabolism pathways can be identified by the introduction of metagenomic libraries into the organism of interest followed by screening for the desired phenotype. We present here a method to transfer metagenomic libraries from E. coli to Pseudomonas alloputida, followed by screening for use of galactose as a sole carbon source.

Information-Theory-based Nondominated Sorting Ant Colony Optimization for Multiobjective Feature Selection in Classification.

Feature selection (FS) has received significant attention since the use of a well-selected subset of features may achieve better classification performance than that of full features in many real-world applications. It can be considered as a multiobjective optimization consisting of two objectives: 1) minimizing the number of selected features and 2) maximizing classification performance. Ant colony optimization (ACO) has shown its effectiveness in FS due to its problem-guided search operator and flexible graph representation. However, there lacks an effective ACO-based approach for multiobjective FS to handle the problematic characteristics originated from the feature interactions and highly discontinuous Pareto fronts. This article presents an Information-theory-based Nondominated Sorting ACO (called INSA) to solve the aforementioned difficulties. First, the probabilistic function in ACO is modified based on the information theory to identify the importance of features; second, a new ACO strategy is designed to construct solutions; and third, a novel pheromone updating strategy is devised to ensure the high diversity of tradeoff solutions. INSA's performance is compared with four machine-learning-based methods, four representative single-objective evolutionary algorithms, and six state-of-the-art multiobjective ones on 13 benchmark classification datasets, which consist of both low and high-dimensional samples. The empirical results verify that INSA is able to obtain solutions with better classification performance using features whose count is similar to or less than those obtained by its peers.

Dynamics of microbial populations and diversity in NAPL contaminated peat soil under varying water table conditions.

Despite the risks that hydrocarbon contamination from pipeline leaks or train derailments impose on the health of peatlands in hydrocarbon production areas and transportation corridors, assessing the effect of such contaminations on the health and sustainability of peatlands has received little attention. This study investigates the impacts of hydrocarbons on peat microbial communities. Column experiments were conducted on non-aqueous phase liquid (NAPL) contaminated undisturbed peat core (0-35 cm) under static and fluctuating water table conditions. Water table fluctuations reduced residual NAPL saturation from 8.1-11.3% to 7.7-9.5%. Biodegradation of n-C8 and n-C12 along with oxidation of CH4 together produced high CO2 concentrations in the headspace. Clear patterns in dynamics in the microbial community structure were observed, with a more pronounced population growth. However, a significant loss of microbial richness was observed in contaminated columns. The result indicates that the phylum Proteobacteria benefited most from NAPL; however, their families differed between static and fluctuating water table conditions. This study established strong evidence that peat microbes and water table fluctuation can be an excellent tool for hydrocarbon removal and its control in peatlands.

Slr4, a newly identified S-layer protein from marine Gammaproteobacteria, is a major biofilm matrix component.

S-layers are paracrystalline proteinaceous lattices that surround prokaryotic cells, forming a critical interface between the cells and their extracellular environment. Here, we report the discovery of a novel S-layer protein present in the Gram-negative marine organism, Pseudoalteromonas tunicata D2. An uncharacterized protein (EAR28894) was identified as the most abundant protein in planktonic cultures and biofilms. Bioinformatic methods predicted a beta-helical structure for EAR28894 similar to the Caulobacter S-layer protein, RsaA, despite sharing less than 20% sequence identity. Transmission electron microscopy revealed that purified EAR28894 protein assembled into paracrystalline sheets with a unique square lattice symmetry and a unit cell spacing of ~9.1 nm. An S-layer was found surrounding the outer membrane in wild-type cells and completely removed from cells in an EAR28894 deletion mutant. S-layer material also appeared to be "shed" from wild-type cells and was highly abundant in the extracellular matrix where it is associated with outer membrane vesicles and other matrix components. EAR28894 and its homologs form a new family of S-layer proteins that are widely distributed in Gammaproteobacteria including species of Pseudoalteromonas and Vibrio, and found exclusively in marine metagenomes. We propose the name Slr4 for this novel protein family.

Time Series Resolution of the Fish Necrobiome Reveals a Decomposer Succession Involving Toxigenic Bacterial Pathogens.

Despite progress understanding microbial communities involved in terrestrial vertebrate decomposition, little is known about the microbial decomposition of aquatic vertebrates from a functional and environmental context. Here, we analyzed temporal changes in the "necrobiome" of rainbow darters, which are common North American fish that are sensitive indicators of water quality. By combining 16S rRNA gene and shotgun metagenomic sequence data from four time points, we studied the progression of decomposers from both taxonomic and functional perspectives. The 16S rRNA gene profiles revealed strong community succession, with early decomposition stages associated with Aeromonas and Clostridium taxa and later stages dominated by members of the Rikenellaceae (i.e., Alistipes/Acetobacteroides genera). These results were reproducible and independent of environmental perturbation, given that exposure to wastewater treatment plant effluent did not substantially influence the necrobiome composition of fish or the associated water sample microbiota. Metagenomic analysis revealed significant changes throughout decomposition in degradation pathways for amino acids, carbohydrates/glycans, and other compounds, in addition to putrefaction pathways for production of putrescine, cadaverine, and indole. Binning of contigs confirmed a predominance of Aeromonas genome assemblies, including those from novel strains related to the pathogen Aeromonas veronii These bins of Aeromonas genes also encoded known hemolysin toxins (e.g., aerolysin) that were particularly abundant early in the process, potentially contributing to host cell lysis during decomposition. Overall, our results demonstrate that wild-caught fish have a reproducible decomposer succession and that the fish necrobiome serves as a potential source of putative pathogens and toxigenic bacteria.IMPORTANCE The microbial decomposition of animal tissues is an important ecological process that impacts nutrient cycling in natural environments. We studied the microbial decomposition of a common North American fish (rainbow darters) over four time points, combining 16S rRNA gene and shotgun metagenomic sequence data to obtain both taxonomic and functional perspectives. Our data revealed a strong community succession that was reproduced across different fish and environments. Decomposition time point was the main driver of community composition and functional potential; fish environmental origin (upstream or downstream of a wastewater treatment plant) had a secondary effect. We also identified strains related to the putative pathogen Aeromonas veronii as dominant members of the decomposition community. These bacteria peaked early in decomposition and coincided with the metagenomic abundance of hemolytic toxin genes. Our work reveals a strong decomposer succession in wild-caught fish, providing functional and taxonomic insights into the vertebrate necrobiome.

Bi-objective Elite Differential Evolution Algorithm for Multivalued Logic Networks.

In this paper, a novel algorithm called bi-objective elite differential evolution (BOEDE) is proposed to optimize multivalued logic (MVL) networks. It is a multiobjective algorithm completely different from all previous single-objective optimization ones. The two objective functions, error and optimality, are put into evaluating the fitness of individuals in evolution simultaneously. BOEDE innovatively uses an archive population with different ranks to store elite individuals and offsprings. Moreover, a characteristic updating method based on this archive structure is designed to produce the parent population. Because of the particularity of MVL network problems, the performance of BOEDE to solve them is further improved by strictly distinguishing elite solutions and Pareto optimal solutions, and by modifying the method of dealing with illegal variables. The simulations show that BOEDE can collect a great number of solutions to provide decision support for a variety of applications. The comparison results also indicate that BOEDE is significantly better than the existing algorithms.

Dendritic Neuron Model With Effective Learning Algorithms for Classification, Approximation, and Prediction.

An artificial neural network (ANN) that mimics the information processing mechanisms and procedures of neurons in human brains has achieved a great success in many fields, e.g., classification, prediction, and control. However, traditional ANNs suffer from many problems, such as the hard understanding problem, the slow and difficult training problems, and the difficulty to scale them up. These problems motivate us to develop a new dendritic neuron model (DNM) by considering the nonlinearity of synapses, not only for a better understanding of a biological neuronal system, but also for providing a more useful method for solving practical problems. To achieve its better performance for solving problems, six learning algorithms including biogeography-based optimization, particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, and population-based incremental learning are for the first time used to train it. The best combination of its user-defined parameters has been systemically investigated by using the Taguchi's experimental design method. The experiments on 14 different problems involving classification, approximation, and prediction are conducted by using a multilayer perceptron and the proposed DNM. The results suggest that the proposed learning algorithms are effective and promising for training DNM and thus make DNM more powerful in solving classification, approximation, and prediction problems.

Incorporation of Solvent Effect into Multi-Objective Evolutionary Algorithm for Improved Protein Structure Prediction.

The problem of predicting the three-dimensional (3-D) structure of a protein from its one-dimensional sequence has been called the "holy grail of molecular biology", and it has become an important part of structural genomics projects. Despite the rapid developments in computer technology and computational intelligence, it remains challenging and fascinating. In this paper, to solve it we propose a multi-objective evolutionary algorithm. We decompose the protein energy function Chemistry at HARvard Macromolecular Mechanics force fields into bond and non-bond energies as the first and second objectives. Considering the effect of solvent, we innovatively adopt a solvent-accessible surface area as the third objective. We use 66 benchmark proteins to verify the proposed method and obtain better or competitive results in comparison with the existing methods. The results suggest the necessity to incorporate the effect of solvent into a multi-objective evolutionary algorithm to improve protein structure prediction in terms of accuracy and efficiency.

The Completed PacBio Single-Molecule Real-Time Sequence of Methylosinus trichosporium Strain OB3b Reveals the Presence of a Third Large Plasmid.

Presented here is the complete genome sequence of the well-studied Rhizobiales methanotroph Methylosinus trichosporium strain OB3b. The assembly contains 5,183,433 bp, corresponding to a chromosome of 4,508,832 bp and three circular plasmids of 285,280 bp, 209,102 bp, and 180,219 bp.

Discovery of a proteolytic flagellin family in diverse bacterial phyla that assembles enzymatically active flagella.

Bacterial flagella are cell locomotion and occasional adhesion organelles composed primarily of the polymeric protein flagellin, but to date have not been associated with any enzymatic function. Here, we report the bioinformatics-driven discovery of a class of enzymatic flagellins that assemble to form proteolytically active flagella. Originating by a metallopeptidase insertion into the central flagellin hypervariable region, this flagellin family has expanded to at least 74 bacterial species. In the pathogen, Clostridium haemolyticum, metallopeptidase-containing flagellin (which we termed flagellinolysin) is the second most abundant protein in the flagella and is localized to the extracellular flagellar surface. Purified flagellar filaments and recombinant flagellin exhibit proteolytic activity, cleaving nearly 1000 different peptides. With ~ 20,000 flagellin copies per ~ 10-µm flagella this assembles the largest proteolytic complex known. Flagellum-mediated extracellular proteolysis expands our understanding of the functional plasticity of bacterial flagella, revealing this family as enzymatic biopolymers that mediate interactions with diverse peptide substrates.So far no enzymatic activity has been attributed to flagellin, the major component of bacterial flagella. Here the authors use bioinformatic analysis and identify a metallopeptidase insertion in flagellins from 74 bacterial species and show that recombinant flagellin and flagellar filaments have proteolytic activity.

Functional metagenomics reveals novel ß-galactosidases not predictable from gene sequences.

The techniques of metagenomics have allowed researchers to access the genomic potential of uncultivated microbes, but there remain significant barriers to determination of gene function based on DNA sequence alone. Functional metagenomics, in which DNA is cloned and expressed in surrogate hosts, can overcome these barriers, and make important contributions to the discovery of novel enzymes. In this study, a soil metagenomic library carried in an IncP cosmid was used for functional complementation for ß-galactosidase activity in both Sinorhizobium meliloti (α-Proteobacteria) and Escherichia coli (γ-Proteobacteria) backgrounds. One ß-galactosidase, encoded by six overlapping clones that were selected in both hosts, was identified as a member of glycoside hydrolase family 2. We could not identify ORFs obviously encoding possible ß-galactosidases in 19 other sequenced clones that were only able to complement S. meliloti. Based on low sequence identity to other known glycoside hydrolases, yet not ß-galactosidases, three of these ORFs were examined further. Biochemical analysis confirmed that all three encoded ß-galactosidase activity. Lac36W_ORF11 and Lac161_ORF7 had conserved domains, but lacked similarities to known glycoside hydrolases. Lac161_ORF10 had neither conserved domains nor similarity to known glycoside hydrolases. Bioinformatic and structural modeling implied that Lac161_ORF10 protein represented a novel enzyme family with a five-bladed propeller glycoside hydrolase domain. By discovering founding members of three novel ß-galactosidase families, we have reinforced the value of functional metagenomics for isolating novel genes that could not have been predicted from DNA sequence analysis alone.

Methods for the Isolation of Genes Encoding Novel PHA Metabolism Enzymes from Complex Microbial Communities.

Development of different PHAs as alternatives to petrochemically derived plastics can be facilitated by mining metagenomic libraries for diverse PHA cycle genes that might be useful for synthesis of bio-plastics. The specific phenotypes associated with mutations of the PHA synthesis pathway genes in Sinorhizobium meliloti and Pseudomonas putida, allows the use of powerful selection and screening tools to identify complementing novel PHA synthesis genes. Identification of novel genes through their function rather than sequence facilitates the functional proteins that may otherwise have been excluded through sequence-only screening methodology. We present here methods that we have developed for the isolation of clones expressing novel PHA metabolism genes from metagenomic libraries.

Novel polyhydroxyalkanoate copolymers produced in Pseudomonas putida by metagenomic polyhydroxyalkanoate synthases.

Bacterially produced biodegradable polyhydroxyalkanoates (PHAs) with versatile properties can be achieved using different PHA synthases (PhaCs). This work aims to expand the diversity of known PhaCs via functional metagenomics and demonstrates the use of these novel enzymes in PHA production. Complementation of a PHA synthesis-deficient Pseudomonas putida strain with a soil metagenomic cosmid library retrieved 27 clones expressing either class I, class II, or unclassified PHA synthases, and many did not have close sequence matches to known PhaCs. The composition of PHA produced by these clones was dependent on both the supplied growth substrates and the nature of the PHA synthase, with various combinations of short-chain-length (SCL) and medium-chain-length (MCL) PHA. These data demonstrate the ability to isolate diverse genes for PHA synthesis by functional metagenomics and their use for the production of a variety of PHA polymer and copolymer mixtures.

Current and future resources for functional metagenomics.

Functional metagenomics is a powerful experimental approach for studying gene function, starting from the extracted DNA of mixed microbial populations. A functional approach relies on the construction and screening of metagenomic libraries-physical libraries that contain DNA cloned from environmental metagenomes. The information obtained from functional metagenomics can help in future annotations of gene function and serve as a complement to sequence-based metagenomics. In this Perspective, we begin by summarizing the technical challenges of constructing metagenomic libraries and emphasize their value as resources. We then discuss libraries constructed using the popular cloning vector, pCC1FOS, and highlight the strengths and shortcomings of this system, alongside possible strategies to maximize existing pCC1FOS-based libraries by screening in diverse hosts. Finally, we discuss the known bias of libraries constructed from human gut and marine water samples, present results that suggest bias may also occur for soil libraries, and consider factors that bias metagenomic libraries in general. We anticipate that discussion of current resources and limitations will advance tools and technologies for functional metagenomics research.

Evaluation of a pooled strategy for high-throughput sequencing of cosmid clones from metagenomic libraries.

High-throughput sequencing methods have been instrumental in the growing field of metagenomics, with technological improvements enabling greater throughput at decreased costs. Nonetheless, the economy of high-throughput sequencing cannot be fully leveraged in the subdiscipline of functional metagenomics. In this area of research, environmental DNA is typically cloned to generate large-insert libraries from which individual clones are isolated, based on specific activities of interest. Sequence data are required for complete characterization of such clones, but the sequencing of a large set of clones requires individual barcode-based sample preparation; this can become costly, as the cost of clone barcoding scales linearly with the number of clones processed, and thus sequencing a large number of metagenomic clones often remains cost-prohibitive. We investigated a hybrid Sanger/Illumina pooled sequencing strategy that omits barcoding altogether, and we evaluated this strategy by comparing the pooled sequencing results to reference sequence data obtained from traditional barcode-based sequencing of the same set of clones. Using identity and coverage metrics in our evaluation, we show that pooled sequencing can generate high-quality sequence data, without producing problematic chimeras. Though caveats of a pooled strategy exist and further optimization of the method is required to improve recovery of complete clone sequences and to avoid circumstances that generate unrecoverable clone sequences, our results demonstrate that pooled sequencing represents an effective and low-cost alternative for sequencing large sets of metagenomic clones.

Versatile broad-host-range cosmids for construction of high quality metagenomic libraries.

We constructed IncP broad-host-range Gateway® entry cosmids pJC8 and pJC24, which replicate in diverse Proteobacteria. We demonstrate the functionality of these vectors by extracting, purifying, and size-selecting metagenomic DNA from agricultural corn and wheat soils, followed by cloning into pJC8. Metagenomic DNA libraries of 8×10(4) (corn soil) and 9×10(6) (wheat soil) clones were generated for functional screening. The DNA cloned in these libraries can be transferred from these recombinant cosmids to Gateway® destination vectors for specialized screening purposes. Those library clones are available from the Canadian MetaMicroBiome Library project (http://www.cm2bl.org/).