Ian M. Overton

A Comprehensive Collection of Chicken cDNAs

Birds have played a central role in many biological disciplines, particularly ecology, evolution, and behavior. The chicken, as a model vertebrate, also represents an important experimental system for developmental biologists, immunologists, cell biologists, and geneticists. However, genomic resources for the chicken have lagged behind those for other model organisms, with only 1845 nonredundant full-length chicken cDNA sequences currently deposited in the EMBL databank. We describe a large-scale expressed-sequence-tag (EST) project aimed at gene discovery in chickens (http://www.chick.umist.ac.uk). In total, 339,314 ESTs have been sequenced from 64 cDNA libraries generated from 21 different embryonic and adult tissues. These were clustered and assembled into 85,486 contiguous sequences (contigs). We find that a minimum of 38% of the contigs have orthologs in other organisms and define an upper limit of 13,000 new chicken genes. The remaining contigs may include novel avian specific or rapidly evolving genes. Comparison of the contigs with known chicken genes and orthologs indicates that 30% include cDNAs that contain the start codon and 20% of the contigs represent full-length cDNA sequences. Using this dataset, we estimate that chickens have approximately 35,000 genes in total, suggesting that this number may be a characteristic feature of vertebrates.

TarO: a target optimisation system for structural biology

TarO (http://www.compbio.dundee.ac.uk/taro) offers a single point of reference for key bioinformatics analyses relevant to selecting proteins or domains for study by structural biology techniques. The protein sequence is analysed by 17 algorithms and compared to 8 databases. TarO gathers putative homologues, including orthologues, and then obtains predictions of properties for these sequences including crystallisation propensity, protein disorder and post-translational modifications. Analyses are run on a high-performance computing cluster, the results integrated, stored in a database and accessed through a web-based user interface. Output is in tabulated format and in the form of an annotated multiple sequence alignment (MSA) that may be edited interactively in the program Jalview. TarO also simplifies the gathering of additional annotations via the Distributed Annotation System, both from the MSA in Jalview and through links to Dasty2. Routes to other information gateways are included, for example to relevant pages from UniProt, COG and the Conserved Domains Database. Open access to TarO is available from a guest account with private accounts for academic use available on request. Future development of TarO will include further analysis steps and integration with the Protein Information Management System (PIMS), a sister project in the BBSRC ‘Structural Proteomics of Rational Targets’ initiative

The Scottish Structural Proteomics Facility: Targets, Methods and Outputs.

The Scottish Structural Proteomics Facility was funded to develop a laboratory scale approach to high throughput structure determination. The effort was successful in that over 40 structures were determined. These structures and the methods harnessed to obtain them are reported here. This report reflects on the value of automation but also on the continued requirement for a high degree of scientific and technical expertise. The efficiency of the process poses challenges to the current paradigm of structural analysis and publication. In the 5xa0year period we published ten peer-reviewed papers reporting structural data arising from the pipeline. Nevertheless, the number of structures solved exceeded our ability to analyse and publish each new finding. By reporting the experimental details and depositing the structures we hope to maximize the impact of the project by allowing others to follow up the relevant biology.

Translocation portals for the substrates and products of a viral transcription complex: the bluetongue virus core

The bluetongue virus core is a molecular machine that simultaneously and repeatedly transcribes mRNA from 10 segments of viral double‐stranded RNA, packaged in a liquid crystalline array. To determine how the logistical problems of transcription within a sealed shell are solved, core crystals were soaked with various ligands and analysed by X‐ray crystallography. Mg2+ ions produce a slight expansion of the capsid around the 5‐fold axes. Oligonucleotide soaks demonstrate that the 5‐fold pore, opened up by this expansion, is the exit site for mRNA, whilst nucleotide soaks pinpoint a separate binding site that appears to be a selective channel for the entry and exit of substrates and by‐products. Finally, nucleotides also bind to the outer core layer, providing a substrate sink.

Structures of Three HIV-1 HLA-B*5703-Peptide Complexes and Identification of Related HLAs Potentially Associated with Long-Term Nonprogression

Long-term nonprogression during acute HIV infection has been strongly associated with HLA-B*5701 or HLA-B*5703. In this study, we present the high resolution crystal structures of HLA-B*5703 complexes with three HIV-1 epitopes: ISPRTLNAW (ISP), KAFSPEVIPMF (KAF-11), and KAFSPEVI (KAF-8). These reveal peptide anchoring at position 2 and their C termini. The different peptide lengths and primary sequences are accommodated by variation in the specific contacts made to the HLA-B*5703, flexibility in water structure, and conformational adjustment of side chains within the peptide-binding groove. The peptides adopt markedly different conformations, and trap variable numbers of water molecules, near a cluster of tyrosine side chains located in the central region of the peptide-binding groove. The KAF-11 epitope completely encompasses the shorter KAF-8 epitope but the peptides are presented in different conformations; the KAF-11 peptide arches out of the peptide-binding groove, exposing a significant main chain surface area. Bioinformatic analysis of the MHC side chains observed to contribute to the peptide anchor specificity, and other specific peptide contacts, reveals HLA alleles associated with long-term nonprogression and a number of related HLA alleles that may share overlapping peptide repertoires with HLA-B*5703 and thus may display a similar capacity for efficient immune control of HIV-1 infection.

Addressing Statistical Biases in Nucleotide-Derived Protein Databases for Proteogenomic Search Strategies

Proteogenomics has the potential to advance genome annotation through high quality peptide identifications derived from mass spectrometry experiments, which demonstrate a given gene or isoform is expressed and translated at the protein level. This can advance our understanding of genome function, discovering novel genes and gene structure that have not yet been identified or validated. Because of the high-throughput shotgun nature of most proteomics experiments, it is essential to carefully control for false positives and prevent any potential misannotation. A number of statistical procedures to deal with this are in wide use in proteomics, calculating false discovery rate (FDR) and posterior error probability (PEP) values for groups and individual peptide spectrum matches (PSMs). These methods control for multiple testing and exploit decoy databases to estimate statistical significance. Here, we show that database choice has a major effect on these confidence estimates leading to significant differences in the number of PSMs reported. We note that standard target:decoy approaches using six-frame translations of nucleotide sequences, such as assembled transcriptome data, apparently underestimate the confidence assigned to the PSMs. The source of this error stems from the inflated and unusual nature of the six-frame database, where for every target sequence there exists five incorrect targets that are unlikely to code for protein. The attendant FDR and PEP estimates lead to fewer accepted PSMs at fixed thresholds, and we show that this effect is a product of the database and statistical modeling and not the search engine. A variety of approaches to limit database size and remove noncoding target sequences are examined and discussed in terms of the altered statistical estimates generated and PSMs reported. These results are of importance to groups carrying out proteogenomics, aiming to maximize the validation and discovery of gene structure in sequenced genomes, while still controlling for false positives.

ParCrys: a Parzen window density estimation approach to protein crystallization propensity prediction.

The ability to rank proteins by their likely success in crystallization is useful in current Structural Biology efforts and in particular in high-throughput Structural Genomics initiatives. We present ParCrys, a Parzen Window approach to estimate a proteins propensity to produce diffraction-quality crystals. The Protein Data Bank (PDB) provided training data whilst the databases TargetDB and PepcDB were used to define feature selection data as well as test data independent of feature selection and training. ParCrys outperforms the OB-Score, SECRET and CRYSTALP on the data examined, with accuracy and Matthews correlation coefficient values of 79.1% and 0.582, respectively (74.0% and 0.227, respectively, on data with a real-world ratio of positive:negative examples). ParCrys predictions and associated data are available from www.compbio.dundee.ac.uk/parcrys.

A normalised scale for structural genomics target ranking: the OB-Score.

Target selection and ranking is fundamental to structural genomics. We present a Z‐score scale, the “OB‐Score”, to rank potential targets by their predicted propensity to produce diffraction‐quality crystals. The OB‐Score is derived from a matrix of predicted isoelectric point and hydrophobicity values for nonredundant PDB entries solved to ⩽3.0 Å against a background of UniRef50. A highly significant difference was found between the OB‐Scores for TargetDB test datasets. A wide range of OB‐Scores was observed across 241 proteomes and within 7868 PfamA families; 73.4% of PfamA families contain ⩾1 member with a high OB‐Score, presenting favourable candidates for structural studies.

Global network analysis of drug tolerance, mode of action and virulence in methicillin-resistant S. aureus

BackgroundStaphylococcus aureus is a major human pathogen and strains resistant to existing treatments continue to emerge. Development of novel treatments is therefore important. Antimicrobial peptides represent a source of potential novel antibiotics to combat resistant bacteria such as Methicillin-Resistant Staphylococcus aureus (MRSA). A promising antimicrobial peptide is ranalexin, which has potent activity against Gram-positive bacteria, and particularly S. aureus. Understanding mode of action is a key component of drug discovery and network biology approaches enable a global, integrated view of microbial physiology, including mechanisms of antibiotic killing. We developed a systems-wide functional association network approach to integrate proteome and transcriptome profiles, enabling study of drug resistance and mode of action.ResultsThe functional association network was constructed by Bayesian logistic regression, providing a framework for identification of antimicrobial peptide (ranalexin) response modules from S. aureus MRSA-252 transcriptome and proteome profiling. These signatures of ranalexin treatment revealed multiple killing mechanisms, including cell wall activity. Cell wall effects were supported by gene disruption and osmotic fragility experiments. Furthermore, twenty-two novel virulence factors were inferred, while the VraRS two-component system and PhoU-mediated persister formation were implicated in MRSA tolerance to cationic antimicrobial peptides.ConclusionsThis work demonstrates a powerful integrative approach to study drug resistance and mode of action. Our findings are informative to the development of novel therapeutic strategies against Staphylococcus aureus and particularly MRSA.

Carbonic Anhydrase 9 Expression Increases with Vascular Endothelial Growth Factor–Targeted Therapy and Is Predictive of Outcome in Metastatic Clear Cell Renal Cancer

Background There is a lack of biomarkers to predict outcome with targeted therapy in metastatic clear cell renal cancer (mccRCC). This may be because dynamic molecular changes occur with therapy. Objective To explore if dynamic, targeted-therapy-driven molecular changes correlate with mccRCC outcome. Design, setting, and participants Multiple frozen samples from primary tumours were taken from sunitinib-naïve (n = 22) and sunitinib-treated mccRCC patients (n = 23) for protein analysis. A cohort (n = 86) of paired, untreated and sunitinib/pazopanib-treated mccRCC samples was used for validation. Array comparative genomic hybridisation (CGH) analysis and RNA interference (RNAi) was used to support the findings. Intervention Three cycles of sunitinib 50 mg (4 wk on, 2 wk off). Outcome measurements and statistical analysis Reverse phase protein arrays (training set) and immunofluorescence automated quantitative analysis (validation set) assessed protein expression. Results and limitations Differential expression between sunitinib-naïve and treated samples was seen in 30 of 55 proteins (p < 0.05 for each). The proteins B-cell CLL/lymphoma 2 (BCL2), mutL homolog 1 (MLH1), carbonic anhydrase 9 (CA9), and mechanistic target of rapamycin (mTOR) (serine/threonine kinase) had both increased intratumoural variance and significant differential expression with therapy. The validation cohort confirmed increased CA9 expression with therapy. Multivariate analysis showed high CA9 expression after treatment was associated with longer survival (hazard ratio: 0.48; 95% confidence interval, 0.26–0.87; p = 0.02). Array CGH profiles revealed sunitinib was associated with significant CA9 region loss. RNAi CA9 silencing in two cell lines inhibited the antiproliferative effects of sunitinib. Shortcomings of the study include selection of a specific protein for analysis, and the specific time points at which the treated tissue was analysed. Conclusions CA9 levels increase with targeted therapy in mccRCC. Lower CA9 levels are associated with a poor prognosis and possible resistance, as indicated by the validation cohort. Patient summary Drug treatment of advanced kidney cancer alters molecular markers of treatment resistance. Measuring carbonic anhydrase 9 levels may be helpful in determining which patients benefit from therapy.