Biology subjects

Wilkinson, P.

Publications and source records attributed to Wilkinson, P..

5 recordsLinked to original sources

bioRxiv2025

The promise of AlphaFold for gene structure annotation

BackgroundAs sequencing technology improves, more genomes become available. Most lack annotation, automated methods are error prone, and few genomes are ever manually curated due to time and cost. Protein structure prediction software may provide new angles for assessing and improving gene models without requiring experimental data. In this paper, we explore whether scores from protein structure prediction can aid in scoring gene model quality. We chose three species (Fusarium graminearum, Toxoplasma gondii, and Aspergillus fumigatus) from the VEuPathDB database which have collectively undergone more than 1000 manual curation events. We modelled translations of the gene models with AlphaFold 3, before and after curation, collecting various scores. Then we carried out structure searching of the PDB with Foldseek and sequence-based domain identification using InterProScan. We profiled the scores produced by these methods to identify those best for gene model assessment. ResultsAlphaFold 3 scores strongly favoured manually improved over pre-improvement models, supporting 75% of manually-curated changes in F. graminearum, 65% in T. gondii, and 84% in A. fumigatus (the lower percentage in T. gondii attributed to a high level of disorder). Further, combining scores across multiple tools (AlphaFold 3, Foldseek and InterProScan) provided additional improvements in model scoring. ConclusionOverall, the most discriminative scores combined outputs of AlphaFold 3 and Foldseek. Our results therefore highlight the potential of scores derived from deep learning-based protein structure prediction for scoring gene models in the absence of experimental data. Future work should focus on intrinsically disordered regions and developing integrated tools to apply this approach.

bioinformatics↗

bioRxiv2024

A new mRNA structure prediction based approach to identifying improved signal peptides for bone morphogenetic protein 2

BackgroundSignal peptide (SP) engineering has proven able to improve production of many proteins yet is a laborious process that still relies on trial and error. mRNA structure around the translational start site is important in translation initiation and has rarely been considered in this context, with recent improvements in in silico mRNA structure potentially rendering it a useful predictive tool for SP selection. Here we attempt to create a method to systematically screen candidate signal peptide sequences in silico based on both their nucleotide and amino acid sequences. Several recently released computational tools were used to predict signal peptide activity (SignalP), localization target (DeepLoc) and predicted mRNA structure (MXFold2). The method was tested with Bone Morphogenetic Protein 2 (BMP2), an osteogenic growth factor used clinically for bone regeneration. It was hoped more effective BMP2 SPs could improve BMP2-based gene therapies and reduce the cost of recombinant BMP2 production. ResultsAmino acid sequence analysis indicated 2,611 SPs from the TGF-{beta} superfamily were predicted to function when attached to BMP2. mRNA structure prediction indicated structures at the translational start site were likely highly variable. The five sequences with the most accessible translational start sites, a codon optimized BMP2 SP variant and the well-established hIL2 SP sequence were taken forward to in vitro testing. The top five candidates showed non-significant improvements in BMP2 secretion in HEK293T cells. All showed reductions in secretion versus the native sequence in C2C12 cells, with several showing large and significant decreases. None of the tested sequences were able to increase alkaline phosphatase activity above background in C2C12s. The codon optimized control sequence and hIL2 SP showed reasonable activity in HEK293T but very poor activity in C2C12. ConclusionsThese results support the use of peptide sequence based in silico tools for basic predictions around signal peptide activity in a synthetic biology context. However, mRNA structure prediction requires improvement before it can produce reliable predictions for this application. The poor activity of the codon optimized BMP2 SP variant in C2C12 emphasizes the importance of codon choice, mRNA structure, and cellular context for SP activity.

synthetic biology↗

bioRxiv2023

Differential early-life survival underlies the adaptive significance of temperature-dependent sex determination in a long-lived reptile

O_LIMany ectotherms rely on temperature cues experienced during development to determine offspring sex. The first descriptions of temperature-dependent sex determination (TSD) were made over 50 years ago, yet an understanding of its adaptive significance remains elusive, especially in long-lived taxa. C_LIO_LIOne novel hypothesis predicts that TSD should be evolutionarily favored when two criteria are met - (a) incubation temperature influences annual juvenile survival and (b) sexes mature at different ages. Under these conditions, a sex-dependent effect of incubation temperature on offspring fitness arises through differences in age at sexual maturity, with the sex that matures later benefiting disproportionately from temperatures that promote juvenile survival. C_LIO_LIThe American alligator (Alligator mississippiensis) serves as an insightful model in which to test this hypothesis, as males begin reproducing nearly a decade after females. Here, through a combination of artificial incubation experiments and mark-recapture approaches, we test the specific predictions of the survival-to-maturity hypothesis for the adaptive value of TSD by disentangling the effects of incubation temperature and sex on annual survival of alligator hatchlings across two geographically distinct sites. C_LIO_LIHatchlings incubated at male-promoting temperatures consistently exhibited higher survival compared to those incubated at female-promoting temperatures. This pattern appears independent of hatchling sex, as females produced from hormone manipulation at male-promoting temperatures exhibit similar survival to their male counterparts. C_LIO_LIAdditional experiments show that incubation temperature may affect early-life survival primarily by affecting the efficiency with which maternally transferred energy resources are used during development. C_LIO_LIResults from this study provide the first explicit empirical support for the adaptive value of TSD in a crocodilian and point to developmental energetics as a potential unifying mechanism underlying persistent survival consequences of incubation temperature. C_LI

ecology↗

bioRxiv2018

Prioritisation of oncology therapeutic targets using CRISPR-Cas9 screening

Functional genomics approaches can overcome current limitations that hamper oncology drug development such as lack of robust target identification and clinical efficacy. Here we performed genome-scale CRISPR-Cas9 screens in 204 human cancer cell lines from 12 cancer-types and developed a data-driven framework to prioritise cancer therapeutic candidates. We integrated gene cell fitness effects with genomic biomarkers and target tractability for drug development to systematically prioritise new oncology targets in defined tissues and genotypes. Furthermore, we took one of our most promising dependencies, Werner syndrome RecQ helicase, and verified it as a candidate target for tumours with microsatellite instability. Our analysis provides a comprehensive resource of cancer dependencies, a framework to prioritise oncology targets, and nominates specific new candidates. The principles described in this study can transform the initial stages of the drug development process contributing to a new, diverse and more effective portfolio of oncology targets.

cancer biology↗

bioRxiv2017

Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting

Background: Genome editing by CRISPR-Cas9 technology allows large-scale screening of gene essentiality in cancer. A confounding factor when interpreting CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes within copy number amplified regions of the genome. We have developed the computational tool CRISPRcleanR which is capable of identifying and correcting gene-independent responses to CRISPR-Cas9 targeting. CRISPRcleanR uses an unsupervised approach based on the segmentation of single-guide RNA fold change values across the genome, without making any assumption about the copy number status of the targeted genes.\n\nResults Applying our method to existing and newly generated genome-wide essentiality profiles from 15 cancer cell lines, we demonstrate that CRISPRcleanR reduces false positives when calling essential genes, correcting biases within and outside of amplified regions, while maintaining true positive rates. Established cancer dependencies and essentiality signals of amplified cancer driver genes are detectable post-correction. CRISPRcleanR reports sgRNA fold changes and normalised read counts, is therefore compatible with downstream analysis tools, and works with multiple sgRNA libraries.\n\nConclusions CRISPRcleanR is a versatile open-source tool for the analysis of CRISPR-Cas9 knockout screens to identify essential genes.

bioinformatics↗