Biology subjects

Nightingale, D. J. H.

Publications and source records attributed to Nightingale, D. J. H..

4 recordsLinked to original sources

bioRxiv2020

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

The cell is compartmentalised into complex micro-environments allowing an array of specialised biological processes to be carried out in synchrony. Determining a proteins sub-cellular localisation to one or more of these compartments can therefore be a first step in determining its function. High-throughput and high-accuracy mass spectrometry-based sub-cellular proteomic methods can now shed light on the localisation of thousands of proteins at once. Machine learning algorithms are then typically employed to make protein-organelle assignments. However, these algorithms are limited by insufficient and incomplete annotation. We propose a semi-supervised Bayesian approach to novelty detection, allowing the discovery of additional, previously unannotated sub-cellular niches. Inference in our model is performed in a Bayesian framework, allowing us to quantify uncertainty in the allocation of proteins to new sub-cellular niches, as well as in the number of newly discovered compartments. We apply our approach across 10 mass spectrometry based spatial proteomic datasets, representing a diverse range of experimental protocols. Application of our approach to hyper LOPIT datasets validates its utility by recovering enrichment with chromatin-associated proteins without annotation and uncovers sub-nuclear compartmentalisation which was not identified in the original analysis. Moreover, using sub-cellular proteomics data from Saccharomyces cerevisiae, we uncover a novel group of proteins trafficking from the ER to the early Golgi apparatus. Overall, we demonstrate the potential for novelty detection to yield biologically relevant niches that are missed by current approaches.

systems biology↗

bioRxiv2019

Characterisation of protein isoforms encoded by the Drosophila Glycogen Synthase Kinase 3 gene shaggy

The Drosophila shaggy gene (sgg, GSK-3) encodes multiple protein isoforms with serine/threonine kinase activity and is a key player in diverse developmental signalling pathways. Currently it is unclear whether different Sgg proteoforms are similarly involved in signalling or if different proteoforms have distinct functions. We used CRISPR/Cas9 genome engineering to tag eight different Sgg proteoform classes and determined their localization during embryonic development. We performed proteomic analysis of the two major proteoform classes and generated mutant lines for both of these for transcriptomic and phenotypic analysis. We uncovered distinct tissue-specific localization patterns for all of the tagged proteoforms we examined, most of which have not previously been characterised directly at the protein level, including one proteoform initiating with a non-standard codon. Collectively this suggests complex developmentally regulated splicing of the sgg primary transcript. Further, affinity purification followed by mass spectrometric analyses indicate a different repertoire of interacting proteins for the two major proteoform classes we examined, one with ubiquitous expression (Sgg-PB) and one with nervous system specific expression (Sgg-PA). Specific mutation of these proteoforms shows that Sgg-PB performs the well characterised maternal and zygotic segmentations functions of the sgg locus, while Sgg-PA mutants show adult lifespan and locomotor defects consistent with its nervous system localisation. Our findings provide new insights into the role of GSK-3 proteoforms and intriguing links with the GSK-3 and GSK-3{beta} encoded by independent vertebrate genes. Our analysis suggests that different protein isoforms generated by alternative splicing perform distinct functions.

genetics↗

bioRxiv2019

A multi-omic analysis of optineurin proteinopathy in a yeast model suggests the involvement of lipid metabolism in Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is an incurable fatal neurodegenerative disease for which the precise mechanisms of toxicity remain unclear despite some significant advances in our understanding of the underlying genetic basis. A holistic, integrated view of cellular changes will be critical to understanding the processes of neurodegeneration and the development of effective treatments. Mutant forms of optineurin (a ubiquitin-binding protein involved in autophagy, membrane trafficking, and NF-{kappa}B activation) are found associated with cytoplasmic inclusions containing TDP43 or SOD1 in some ALS patients. We have taken a multi-omics approach to understand the cellular response to OPTN overexpression in a yeast model of ALS. We found that genetic interaction screens and metabolomics provided parallel, highly complementary data on OPTN toxicity. Genetic enhancers of OPTN toxicity in yeast relate directly to the native function of OPTN in vesicular trafficking and intracellular transport, suggesting the human OPTN protein is functional when expressed in yeast even though there is no yeast ortholog. Crucially, we find that the genetic modifiers and the metabolic response are distinct for different ALS-linked genes expressed in yeast. This lends strong support to the use of yeast as a model system and omics platform to study ALS.

systems biology↗

bioRxiv2017

Organisation of the transcriptional regulation of genes involved in protein transactions in yeast

The topological analyses of many large-scale molecular interaction networks often provide only limited insights into network function or evolution. In this paper, we argue that the functional heterogeneity of network components, rather than network size, is the main factor limiting the utility of topological analysis of large cellular networks. We have analysed large epistatic, functional, and transcriptional regulatory networks of genes that were attributed to the following biological process groupings: protein transactions, gene expression, cell cycle, and small molecule metabolism. Control analyses were performed on networks of randomly selected genes. We identified novel biological features emerging from the analysis of functionally homogenous biological networks irrespective of their size. In particular, direct regulation by transcription as an underrepresented feature of protein transactions. The analysis also demonstrated that the regulation of the genes involved in protein transactions at the transcriptional level was orchestrated by only a small number of regulators. Quantitative proteomic analysis of nuclear- and chromatin-enriched sub-cellular fractions of yeast provided supportive evidence for the conclusions generated by network analyses.

systems biology↗