Plant diseases caused by bacterial pathogens place major constraints on crop production and cause significant annual losses on a global scale. The attainment of consistent effective management of these diseases can be extremely difficult, and management potential is often affected by grower reliance on highly disease-susceptible cultivars because of consumer preferences, and by environmental conditions favouring pathogen development. New and emerging bacterial disease problems (e.g. zebra chip of potato) and established problems in new geographical regions (e.g. bacterial canker of kiwifruit in New Zealand) grab the headlines, but the list of bacterial disease problems with few effective management options is long. The ever-increasing global human population requires the continued stable production of a safe food supply with greater yields because of the shrinking areas of arable land. One major facet in the maintenance of the sustainability of crop production systems with predictable yields involves the identification and deployment of sustainable disease management solutions for bacterial diseases. In addition, the identification of novel management tactics has also come to the fore because of the increasing evolution of resistance to existing bactericides. A number of central research foci, involving basic research to identify critical pathogen targets for control, novel methodologies and methods of delivery, are emerging that will provide a strong basis for bacterial disease management into the future. Near-term solutions are desperately needed. Are there replacement materials for existing bactericides that can provide effective disease management under field conditions? Experience should inform the future. With prior knowledge of bactericide resistance issues evolving in pathogens, how will this affect the deployment of newer compounds and biological controls? Knowledge is critical. A comprehensive understanding of bacterial pathosystems is required to not only identify optimal targets in the pathogens, but also optimal seasonal timings for deployment. Host resistance to effectors must be exploited, carefully and correctly. Are there other candidate genes that could be targeted in transgenic approaches? How can new technologies (CRISPR, TALEN, etc.) be most effectively used to add sustainable disease resistance to existing commercially desirable plant cultivars? We need an insider's perspective on the management of systemic pathogens. In addition to host resistance or reduced sensitivity, are there other methods that can be used to target these pathogen groups? Biological systems are variable. Can biological control strategies be improved for bacterial disease management and be made more predictable in function? The answers to the research foci outlined above are not all available, as will become apparent in this article, but we are heading in the right direction. In this article, we summarize the contributions from past experiences in bacterial disease management, and also describe how advances in bacterial genetics, genomics and host-pathogen interactions are informing novel strategies in virulence inhibition and in host resistance. We also outline potential innovations that could be exploited as the pressures to maximize a safe and productive food supply continue to become more numerous and more complex.© 2016 BSPP and John Wiley & Sons Ltd.

采用含菌平板抑菌圈测定法,从120株高寒草地牧草内生细菌中分离筛选到一株对番茄细菌性叶斑病拮抗能力较强的菌株264ZY7,其抑菌圈直径为1.22 cm。264ZY7菌体短杆状,大小为1.534 μm×0.571 μm~3.210 μm×0.781 μm,革兰氏阳性菌,根据形态特征,并结合16S rDNA和gyrB基因序列相似性分析,将菌株264ZY7鉴定为解淀粉芽孢杆菌Bacillus amyloliquefaciens。通过室内盆栽防效试验,结果表明该菌株对番茄细菌性叶斑病的防效达69%,此外,该菌株对8种病原真菌具有抑菌能力,说明抑菌谱较宽,且抑菌率均大于30%,对番瓜根腐病菌(Fusarium sp.)效果最明显,抑菌率为52.84%。该研究结果为高寒草地紫花针茅内生细菌264ZY47的进一步开发利用提供了依据。

Identification of dispersed repetitive elements can be difficult, especially when elements share little or no homology with previously described repeats. Consequently, a growing number of computational tools have been designed to identify repetitive elements in an ab initio manner, i.e. without using prior sequence data. Here we present the results of side-by-side evaluations of six of the most widely used ab initio repeat finding programs. Using sequence from rice chromosome 12, tools were compared with regard to time requirements, ability to find known repeats, utility in identifying potential novel repeats, number and types of repeat elements recognized and compactness of family descriptions. The study reveals profound differences in the utility of the tools with some identifying virtually their entire substrate as repetitive, others making reasonable estimates of repetition, and some missing almost all repeats. Of note, even when tools recognized similar numbers of repeats they often showed marked differences in the nature and number of repeat families identified. Within the context of this comparative study, ReAS and RepeatScout showed the most promise in analysis of sequence reads and assembled genomic regions, respectively. Our results should help biologists identify the program(s), if any, that is best suited for their needs.

As high-throughput sequencing platforms produce longer and longer reads, sequences generated from short inserts, such as those obtained from fossil and degraded material, are increasingly expected to contain adapter sequences. Efficient adapter trimming algorithms are also needed to process the growing amount of data generated per sequencing run.We introduce AdapterRemoval v2, a major revision of AdapterRemoval v1, which introduces (i) striking improvements in throughput, through the use of single instruction, multiple data (SIMD; SSE1 and SSE2) instructions and multi-threading support, (ii) the ability to handle datasets containing reads or read-pairs with different adapters or adapter pairs, (iii) simultaneous demultiplexing and adapter trimming, (iv) the ability to reconstruct adapter sequences from paired-end reads for poorly documented data sets, and (v) native gzip and bzip2 support.We show that AdapterRemoval v2 compares favorably with existing tools, while offering superior throughput to most alternatives examined here, both for single and multi-threaded operations.

\n Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. However, given the relatively high error rates of such technologies, efficient and accurate assembly of large repeats and closely related haplotypes remains challenging. We address these issues with Canu, a successor of Celera Assembler that is specifically designed for noisy single-molecule sequences. Canu introduces support for nanopore sequencing, halves depth-of-coverage requirements, and improves assembly continuity while simultaneously reducing runtime by an order of magnitude on large genomes versus Celera Assembler 8.2. These advances result from new overlapping and assembly algorithms, including an adaptive overlapping strategy based on\n tf-idf\n weighted MinHash and a sparse assembly graph construction that avoids collapsing diverged repeats and haplotypes. We demonstrate that Canu can reliably assemble complete microbial genomes and near-complete eukaryotic chromosomes using either Pacific Biosciences (PacBio) or Oxford Nanopore technologies and achieves a contig NG50 of >21 Mbp on both human and\n Drosophila melanogaster\n PacBio data sets. For assembly structures that cannot be linearly represented, Canu provides graph-based assembly outputs in graphical fragment assembly (GFA) format for analysis or integration with complementary phasing and scaffolding techniques. The combination of such highly resolved assembly graphs with long-range scaffolding information promises the complete and automated assembly of complex genomes.\n

Improving the accuracy of prediction of gene starts is one of a few remaining open problems in computer prediction of prokaryotic genes. Its difficulty is caused by the absence of relatively strong sequence patterns identifying true translation initiation sites. In the current paper we show that the accuracy of gene start prediction can be improved by combining models of protein-coding and non-coding regions and models of regulatory sites near gene start within an iterative Hidden Markov model based algorithm. The new gene prediction method, called GeneMarkS, utilizes a non-supervised training procedure and can be used for a newly sequenced prokaryotic genome with no prior knowledge of any protein or rRNA genes. The GeneMarkS implementation uses an improved version of the gene finding program GeneMark.hmm, heuristic Markov models of coding and non-coding regions and the Gibbs sampling multiple alignment program. GeneMarkS predicted precisely 83.2% of the translation starts of GenBank annotated Bacillus subtilis genes and 94.4% of translation starts in an experimentally validated set of Escherichia coli genes. We have also observed that GeneMarkS detects prokaryotic genes, in terms of identifying open reading frames containing real genes, with an accuracy matching the level of the best currently used gene detection methods. Accurate translation start prediction, in addition to the refinement of protein sequence N-terminal data, provides the benefit of precise positioning of the sequence region situated upstream to a gene start. Therefore, sequence motifs related to transcription and translation regulatory sites can be revealed and analyzed with higher precision. These motifs were shown to possess a significant variability, the functional and evolutionary connections of which are discussed.

We describe a program, tRNAscan-SE, which identifies 99-100% of transfer RNA genes in DNA sequence while giving less than one false positive per 15 gigabases. Two previously described tRNA detection programs are used as fast, first-pass prefilters to identify candidate tRNAs, which are then analyzed by a highly selective tRNA covariance model. This work represents a practical application of RNA covariance models, which are general, probabilistic secondary structure profiles based on stochastic context-free grammars. tRNAscan-SE searches at approximately 30 000 bp/s. Additional extensions to tRNAscan-SE detect unusual tRNA homologues such as selenocysteine tRNAs, tRNA-derived repetitive elements and tRNA pseudogenes.

Genomic islands (GIs) are clusters of genes of probable horizontal origin that play a major role in bacterial and archaeal genome evolution and microbial adaptability. They are of high medical and industrial interest, due to their enrichment in virulence factors, some antimicrobial resistance genes and adaptive metabolic pathways. The development of more sensitive but precise prediction tools, using either sequence composition-based methods or comparative genomics, is needed as large-scale analyses of microbial genomes increase.IslandPath-DIMOB, a leading GI prediction tool in the IslandViewer webserver, has now been significantly improved by modifying both the decision algorithm to determine sequence composition biases, and the underlying database of HMM profiles for associated mobility genes. The accuracy of IslandPath-DIMOB and other major software has been assessed using a reference GI dataset predicted by comparative genomics, plus a manually curated dataset from literature review. Compared to the previous version (v0.2.0), this IslandPath-DIMOB v1.0.0 achieves 11.7% and 5.3% increase in recall and precision, respectively. IslandPath-DIMOB has the highest Matthews correlation coefficient among individual prediction methods tested, combining one of the highest recall measures (46.9%) at high precision (87.4%). The only method with higher recall had notably lower precision (55.1%). This new IslandPath-DIMOB v1.0.0 will facilitate more accurate studies of GIs, including their key roles in microbial adaptability of medical, environmental and industrial interest.IslandPath-DIMOB v1.0.0 is freely available through the IslandViewer webserver {{http://www.pathogenomics.sfu.ca/islandviewer/}} and as standalone software {{https://github.com/brinkmanlab/islandpath/}} under the GNU-GPLv3.Supplementary data are available at Bioinformatics online.

We created a visualization tool called Circos to facilitate the identification and analysis of similarities and differences arising from comparisons of genomes. Our tool is effective in displaying variation in genome structure and, generally, any other kind of positional relationships between genomic intervals. Such data are routinely produced by sequence alignments, hybridization arrays, genome mapping, and genotyping studies. Circos uses a circular ideogram layout to facilitate the display of relationships between pairs of positions by the use of ribbons, which encode the position, size, and orientation of related genomic elements. Circos is capable of displaying data as scatter, line, and histogram plots, heat maps, tiles, connectors, and text. Bitmap or vector images can be created from GFF-style data inputs and hierarchical configuration files, which can be easily generated by automated tools, making Circos suitable for rapid deployment in data analysis and reporting pipelines.

The alignment of sequencing reads against a protein reference database is a major computational bottleneck in metagenomics and data-intensive evolutionary projects. Although recent tools offer improved performance over the gold standard BLASTX, they exhibit only a modest speedup or low sensitivity. We introduce DIAMOND, an open-source algorithm based on double indexing that is 20,000 times faster than BLASTX on short reads and has a similar degree of sensitivity.

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation (such as the description of the function of a protein, its domains structure, post-translational modifications, variants, etc.), a minimal level of redundancy and high level of integration with other databases. Recent developments of the database include format and content enhancements, cross-references to additional databases, new documentation files and improvements to TrEMBL, a computer-annotated supplement to SWISS-PROT. TrEMBL consists of entries in SWISS-PROT-like format derived from the translation of all coding sequences (CDSs) in the EMBL Nucleotide Sequence Database, except the CDSs already included in SWISS-PROT. We also describe the Human Proteomics Initiative (HPI), a major project to annotate all known human sequences according to the quality standards of SWISS-PROT. SWISS-PROT is available at: http://www.expasy.ch/sprot/ and http://www.ebi.ac.uk/swissprot/

\n Historically, the incidence of gentamicin resistance in\n Campylobacter\n has been very low, but recent studies reported a high prevalence of gentamicin-resistant\n Campylobacter\n isolated from food-producing animals in China. The reason for the high prevalence was unknown and was addressed in this study. PCR screening identified aminoglycoside resistance genes\n aphA-3\n and\n aphA-7\n and the\n aadE–sat4–aphA-3\n cluster among 41\n Campylobacter\n isolates from broiler chickens. Importantly, a novel genomic island carrying multiple aminoglycoside resistance genes was identified in 26 aminoglycoside resistant\n Campylobacter coli\n strains. Sequence analysis revealed that the genomic island was inserted between\n cadF\n and\n COO1582\n on the\n C. coli\n chromosome and consists of 14 open reading frames (ORFs), including 6 genes (the\n aadE–sat4–aphA-3\n cluster,\n aacA-aphD\n,\n aac\n, and\n aadE\n ) encoding aminoglycoside-modifying enzymes. Analysis by pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing indicated that the\n C. coli\n isolates carrying this unique genomic island were clonal, and the clone of PFGE subtype III and sequence type (ST) 1625 was particularly predominant among the\n C. coli\n isolates examined, suggesting that clonal expansion may be involved in dissemination of this resistance island. Additionally, we were able to transfer this genomic island from\n C. coli\n to a\n Campylobacter jejuni\n strain using natural transformation under laboratory conditions, and the transfer resulted in a drastic increase in aminoglycoside resistance in the recipient strain. These findings identify a previously undescribed genomic island that confers resistance to multiple aminoglycoside antibiotics. Since aminoglycoside antibiotics are used for treating occasional systemic infections caused by\n Campylobacter\n, the emergence and spread of this antibiotic resistance genomic island represent a potential concern for public health.\n

Emerging evidence from genomics gives us a glimpse into the potential contribution of lysogenic bacteriophages (phages) to the environmental adaptability of their hosts. However, it is challenging to quantify this kind of contribution due to the lack of appropriate genetic markers and the associated controllable environmental factors. Here, based on the unique transformable nature of arsenic (the controllable environmental factor), a series of flooding microcosms was established to investigate the contribution of arsM-bearing lysogenic phages to their hosts’ adaptation to trivalent arsenic [As(III)] toxicity, where arsM is the marker gene associated with microbial As(III) detoxification. In the 15-day flooding period, the concentration of As(III) was significantly increased, and this elevated As(III) toxicity visibly inhibited the bacterial population, but the latter quickly adapted to As(III) toxicity. During the flooding period, some lysogenic phages re-infected new hosts after an early burst, while others persistently followed the productive cycle (i.e., lytic cycle). The unique phage-host interplay contributed to the rapid spread of arsM among soil microbiota, enabling the quick recovery of the bacterial community. Moreover, the higher abundance of arsM imparted a greater arsenic methylation capability to soil microbiota. Collectively, this study provides experimental evidence for lysogenic phages assisting their hosts in adapting to an extreme environment, which highlights the ecological perspectives on lysogenic phage-host mutualism.

链霉菌Streptomyces sp. FXP04是健康马铃薯根际土壤中分离的一株对致病疫霉（Phytophthora infestans）有显著拮抗作用的革兰氏阳性放线菌。解析菌株FXP04的全部基因组序列信息，深入探索该菌株拮抗作用机制，并挖掘其次级代谢产物基因资源。利用Illumina和PacBio平台相结合测序技术对FXP04进行全基因组测序，并进行了基因预测、功能注释、比较基因组学分析以及次级代谢产物合成基因簇预测。FXP04基因组大小为4 535 201 bp，共编码5 037个基因，GC含量为72.95%，其中含有3个5S rRNA、3个16S rRNA、3个23S rRNA，33个tRNA以及23个sRNA；含有1 699个串联重复序列，含1 284个小卫星 DNA，188个微卫星 DNA；在 GO、COG、KEGG、CAZy、VFDB和ARDB数据库分别注释到2 088、2 319、1 530、73、139和14个基因；同时预测到菌株FXP04中有10个次级代谢产物合成基因簇，分别编码杀粉蝶菌素、Youssoufene等抑菌物质。通过基因组测序初步揭示了菌株FXP04的内在作用机制，对后续开发利用菌株FXP04提供理论依据。

Aromatic polyketides have attractive biological activities and pharmacological properties. Different from other polyketides, aromatic polyketides are characterized by their polycyclic aromatic structure. The biosynthesis of aromatic polyketides is usually accomplished by the type II polyketide synthases (PKSs), which produce highly diverse polyketide chains by sequential condensation of the starter units with extender units, followed by reduction, cyclization, aromatization and tailoring reactions. Recently, significant progress has been made in characterization and engineering of type II PKSs to produce novel products and improve product titers. In this review, we briefly summarize the architectural organizations and genetic contributions of PKS genes to provide insight into the biosynthetic process. We then review the most recent progress in engineered biosynthesis of aromatic polyketides, with emphasis on generating novel molecular structures. We also discuss the current challenges and future perspectives in the rational engineering of type II PKSs for large scale production of aromatic polyketides.

ε-poly-L-lysine (ε-PL) is a naturally occurring poly(amino acid) of varying polymerization degree, which possesses excellent antimicrobial activity and has been widely used in food and pharmaceutical industries. To provide new perspectives from recent advances, this review compares several conventional and advanced strategies for the discovery of wild strains and development of high-producing strains, including isolation and culture-based traditional methods as well as genome mining and directed evolution. We also summarize process engineering approaches for improving production, including optimization of environmental conditions and utilization of industrial waste. Then, efficient downstream purification methods are described, including their drawbacks, followed by the brief introductions of proposed antimicrobial mechanisms of ε-PL and its recent applications. Finally, we discuss persistent challenges and future perspectives for the commercialization of ε-PL.

A novel antibiotic alpha,beta-unsaturated sesquiterpene ketone, albaflavenone with a zizaene skeleton was isolated from a morphologically novel, highly odorous Streptomyces species which was identified with the species group S. albidoflavus, cluster 1. The new compound, partly responsible for the odour, was assigned the structure of 2R',6,7,7-tetramethyl-1S',8R'- tricyclo-[6.2.1.0(1,5)]undec-5-en-4-one based on spectroscopic studies including 2D NMR (COSY, HETCOR, ROESY, NOE-difference) experiments.

Plant diseases caused by pathogenic microorganisms in agriculture present a considerable obstacle, resulting in approximately 30–40% crop damage. The use of conventional techniques to manage these microorganisms, i.e., applying chemical pesticides and antimicrobials, has been discovered to have adverse effects on human health and the environment. Furthermore, these methods have contributed to the emergence of resistance among phytopathogens. Consequently, it has become imperative to investigate natural alternatives to address this issue. The Streptomyces genus of gram-positive bacteria is a potentially viable natural alternative that has been extensively researched due to its capacity to generate diverse antimicrobial compounds, such as metabolites and organic compounds. Scientists globally use diverse approaches and methodologies to extract new bioactive compounds from these bacteria. The efficacy of bioactive compounds in mitigating various phytopathogens that pose a significant threat to crops and plants has been demonstrated. Hence, the Streptomyces genus exhibits potential as a biological control agent for combating plant pathogens. This review article aims to provide further insight into the Streptomyces genus as a source of antimicrobial compounds that can potentially be a biological control against plant pathogens. The investigation of various bioactive compounds synthesized by this genus can enhance our comprehension of their prospective utilization in agriculture.