Effects of Metarhizium anisopliae on searching,feeding and predation by Orius albidipennis (Hem., Anthocoridae) on Thrips tabaci (Thy., Thripidae) larvae

The generalist predator Orius albidipennis Reut. (Hem., Anthocoridae) and entomopathogenic fungus Metarhizium anisopliae (Metchnikoff) Sorokin (Ascomycota: Clavicipitaceae) are important biocontrol agents of Thrips tabaci Lindeman (Thys., Thripidae) in most greenhouses. In this study, we estimated searching time, feeding time and predation rate in O. albidipennis feeding on untreated and treated thrips larvae which had been inoculated with three concentrations of M. anisopliae V275 at four time intervals; 0, 24, 48 and 72 h after infestation. Applied concentrations were 1×10³, 2×10⁴ and 2×10⁵ conidia/mL which roughly correspond to the LC₂₅, LC₅₀ and LC₇₅ for second instar-larvae. O. albidipennis responded to the presence of the M. anisopliae on the treated hosts by increasing the searching time and decreasing feeding time and predation rate levels. It was also able to detect and avoid treated patches.     

Identification and engineering of the cytochalasin gene cluster from Aspergillus clavatus NRRL 1

Cytochalasins are a group of fungal secondary metabolites with diverse structures and bioactivities, including cytochalasin E produced by Aspergillus clavatus, which is a potent anti-angiogenic agent. Here, we report the identification and characterization of the cytochalasin gene cluster from A. clavatus NRRL 1. As a producer of cytochalasin E and K, the genome of A. clavatus was analyzed and the ∼30 kb ccs gene cluster was identified based on the presence of a polyketide synthase–nonribosomal peptide synthetases (PKS–NRPS) and a putative Baeyer–Villiger monooxygenase (BVMO). Deletion of the central PKS–NRPS gene, ccsA, abolished the production of cytochalasin E and K, confirming the association between the natural products and the gene cluster. Based on bioinformatic analysis, a putative biosynthetic pathway is proposed. Furthermore, overexpression of the pathway specific regulator ccsR elevated the titer of cytochalasin E from 25 mg/L to 175 mg/L. Our results not only shed light on the biosynthesis of cytochalasins, but also provided genetic tools for increasing and engineering the production.     

Shift in chicken intestinal gene association networks after infection with Salmonella

A primary infection of Salmonella enteritidis causes a spatial-temporal dependent change in the gene expression patterns in the intestine of chickens (Gallus gallus). This is the result of a dynamic intestinal response to adapt to the altered environment and to optimize its ‘health’ and functionality under the new circumstances. By inferring gene association networks (GANs), the complexities of and changes in biological networks can be uncovered. Within such GANs highly interacting (hub) genes can be identified, which are supposed to be high-level regulators connected to multiple processes. By exploring the intestinal expression of genes differing between control and Salmonella infected chicken in a time-dependent manner differences in GANs were found. In control chickens more developmental processes were observed, whereas in infected chickens relatively more processes were associated to ‘defense/pathogen response’. Moreover the conserved protein domains of the identified hub genes in controls were nuclear-associated, whereas hub genes in infected chickens were involved in ‘cellular communication’. The shift in topology and functionality of the intestinal GANs in control and Salmonella infected animals and the identification of GAN-specific hubs is a first step to understand the complexity of biological networks and processes regulating intestinal health and functionality under normal and disturbed conditions.     

Determination of partial amino acid composition from tandem mass spectra for use in peptide identification strategies

We demonstrate a new approach to the determination of amino acid composition from tandem mass spectrometrically fragmented peptides using both experimental and simulated data. The approach has been developed to be used as a search-space filter in a protein identification pipeline with the aim of increased performance above that which could be attained by using immonium ion information. Three automated methods have been developed and tested: one based upon a simple peak traversal, in which all intense ion peaks are treated as being either a b- or y-ion using a wide mass tolerance; a second which uses a much narrower tolerance and does not perform transformations of ion peaks to the complementary type; and the unique fragments method which allows for b- or y-ion type to be inferred and corroborated using a scan of the other ions present in each peptide spectrum. The combination of these methods is shown to provide a high-accuracy set of amino acid predictions using both experimental and simulated data sets. These high quality predictions, with an accuracy of over 85%, may be used to identify peptide fragments that are hard to identify using other methods. The data simulation algorithm is also shown post priori to be a good model of noiseless tandem mass spectrometric peptide data.     

Protein and peptide identification algorithms using MS for use in high-throughput, automated pipelines

Current proteomics experiments can generate vast quantities of data very quickly, but this has not been matched by data analysis capabilities. Although there have been a number of recent reviews covering various aspects of peptide and protein identification methods using MS, comparisons of which methods are either the most appropriate for, or the most effective at, their proposed tasks are not readily available. As the need for high-throughput, automated peptide and protein identification systems increases, the creators of such pipelines need to be able to choose algorithms that are going to perform well both in terms of accuracy and computational efficiency. This article therefore provides a review of the currently available core algorithms for PMF, database searching using MS/MS, sequence tag searches and de novo sequencing. We also assess the relative performances of a number of these algorithms. As there is limited reporting of such information in the literature, we conclude that there is a need for the adoption of a system of standardised reporting on the performance of new peptide and protein identification algorithms, based upon freely available datasets. We go on to present our initial suggestions for the format and content of these datasets.     

PRISM: a data management system for high-throughput proteomics

Advanced proteomic research efforts involving areas such as systems biology or biomarker discovery are enabled by the use of high level informatics tools that allow the effective analysis of large quantities of differing types of data originating from various studies. Performing such analyses on a large scale is not feasible without a computational platform that performs data processing and management tasks. Such a platform must be able to provide high-throughput operation while having sufficient flexibility to accommodate evolving data analysis tools and methodologies. The Proteomics Research Information Storage and Management system (PRISM) provides a platform that serves the needs of the accurate mass and time tag approach developed at Pacific Northwest National Laboratory. PRISM incorporates a diverse set of analysis tools and allows a wide range of operations to be incorporated by using a state machine that is accessible to independent, distributed computational nodes. The system has scaled well as data volume has increased over several years, while allowing adaptability for incorporating new and improved data analysis tools for more effective proteomics research.     

3DSDSCAR—a three dimensional structural database for sialic acid-containing carbohydrates through molecular dynamics simulation

The inherent flexibility and lack of strong intramolecular interactions of oligosaccharides demand the use of theoretical methods for their structural elucidation. In spite of the developments of theoretical methods, not much research on glycoinformatics is done so far when compared to bioinformatics research on proteins and nucleic acids. We have developed three dimensional structural database for a sialic acid-containing carbohydrates (3DSDSCAR). This is an open-access database that provides 3D structural models of a given sialic acid-containing carbohydrate. At present, 3DSDSCAR contains 60 conformational models, belonging to 14 different sialic acid-containing carbohydrates, deduced through 10 ns molecular dynamics (MD) simulations. The database is available at the URL: http://www.3dsdscar.org.     

Detection and avoidance of an entomopathogenic fungus by a generalist insect predator

Abstract.  1. Increasing evidence suggests that insects can assess their environment based on cues related to mortality risks to themselves or their offspring. Limited knowledge is available on such abilities in relation to entomopathogenic fungi, which can cause significant mortality in insect populations. In laboratory bioassays, the ability of the generalist predator Anthocoris nemorum L. (Heteroptera: Anthocoridae) to detect the presence of its natural enemy, the fungal pathogen Beauveria bassiana (Balsamo) Vuillemin (Ascomycota: Hypocreales) was investigated.
2. Behavioural observations were conducted on adults of A. nemorum foraging in choice and non-choice arenas treated with conidia suspensions of B. bassiana or just the carrier (control). The arenas consisted either of nettle leaves or soil. Additionally, behaviours in response to sporulating nettle aphid cadavers compared with uninfected aphids or paper balls were evaluated on nettle leaves. An oviposition experiment was also conducted in choice arenas on conidia-treated and untreated nettle leaves.
3. Males and females detected and avoided contact with leaf surfaces inoculated with B. bassiana . Females that were forced to enter fungus-treated leaf surfaces were very reluctant to do so. When females encountered cadavers sporulating with B. bassiana they rapidly withdrew compared with harmless paper ball dummies. Soil inoculated with B. bassiana did not affect A. nemorum behaviour or residence time compared with control soil. Females inserted significantly more eggs in control leaf areas compared with areas treated with B. bassiana conidia.
4. All results suggest that A. nemorum detects and avoids the pathogen B. bassiana when it forages on host plants with which it is adapted but not on soil surfaces. The adaptive significance of detection of entomopathogenic fungi is discussed.     

Mapping QTLs and candidate genes for iron and zinc concentrations in unpolished rice of Madhukar×Swarna RILs

Identifying QTLs/genes for iron and zinc in rice grains can help in biofortification programs. 168 F(7) RILs derived from Madhukar×Swarna were used to map QTLs for iron and zinc concentrations in unpolished rice grains. Iron ranged from 0.2 to 224ppm and zinc ranged from 0.4 to 104ppm. Genome wide mapping using 101 SSRs and 9 gene specific markers showed 5 QTLs on chromosomes 1, 3, 5, 7 and 12 significantly linked to iron, zinc or both. In all, 14 QTLs were identified for these two traits. QTLs for iron were co-located with QTLs for zinc on chromosomes 7 and 12. In all, ten candidate genes known for iron and zinc homeostasis underlie 12 of the 14 QTLs. Another 6 candidate genes were close to QTLs on chromosomes 3, 5 and 7. Thus the high priority candidate genes for high Fe and Zn in seeds are OsYSL1 and OsMTP1 for iron, OsARD2, OsIRT1, OsNAS1, OsNAS2 for zinc and OsNAS3, OsNRAMP1, Heavy metal ion transport and APRT for both iron and zinc together based on our genetic mapping studies as these genes strictly underlie QTLs. Several elite lines with high Fe, high Zn and both were identified.