Biology subjects

Ball, S.

Publications and source records attributed to Ball, S..

6 recordsLinked to original sources

bioRxiv2026

Characterization of starch metabolism pathways in dinoflagellates, chromerids and apicomplexans highlights the presence of a starch accumulating symbiont in their common ancestor

Unlike most other heterotrophic protist lineages which synthesize glycogen, alveolates accumulate -glucan storage polysaccharides in the form of starch. Within Alveolata, ciliates do so by using a simple pathway analogous to that used for glycogen metabolism in eukaryotes. However, Myzozoa have evolved five additional enzymatic steps which are common to Dinoflagellata, Chromerids and Apicomplexa. Moreover, dinoflagellates have acquired seven additional enzymes that distinguish them from the Chromerids-Apicompexa lineages, while chromerids possess only a single enzyme not found in dinoflagellates. Such modifications are not found in other eukaryotic lineages save for those resulting directly from primary or secondary plastid endosymbiosis. The many differences affecting the starch pathway of Myzozoa can be explained by a single secondary or tertiary plastid endosymbiosis of a starch-containing alga followed by distinct compartmentalisation outcomes of starch metabolism in Dinoflagellata relative to chromerids and Apicomplexa.

evolutionary biology↗

bioRxiv2021

Klarigi: Explanations for Semantic Groupings

BackgroundAnnotation of biomedical entities with ontology classes provides for formal semantic analysis and mobilisation of background knowledge in determining their relationships. To date enrichment analysis has been routinely employed to identify classes that are over-represented in annotations across sets of groups, such as biosample gene expression profiles or patient phenotypes. These approaches, however, usually consider only univariate relationships, make limited use of the semantic features of ontologies, and provide limited information and evaluation of the explanatory power of both singular and grouped candidate classes. Moreover, they do not solve the problem of deriving cohesive, characteristic, and discriminatory sets of classes for entity groups. ResultsWe have developed a new method, Klarigi, which introduces multiple scoring heuristics for identification of classes that are both compositional and discriminatory for groups of entities annotated with ontology classes. The tool includes a novel algorithm for derivation of multivariable semantic explanations for entity groups, makes use of semantic inference through live use of an ontology reasoner, and includes a classification method for identifying the discriminatory power of candidate sets. We describe the design and implementation of Klarigi, and evaluate its use in two test cases, comparing and contrasting methods and results with literature and enrichment analysis methods. ConclusionsWe demonstrate that Klarigi produces characteristic and discriminatory explanations for groups of biomedical entities in two settings. We also show that these explanations recapitulate and extend the knowledge held in existing biomedical databases and literature for several diseases. We conclude that Klarigi provides a distinct and valuable perspective on biomedical datasets when compared with traditional enrichment methods, and therefore constitutes a new method by which biomedical datasets can be explored, contributing to improved insight into semantic data.

bioinformatics↗

bioRxiv2020

Komenti: A semantic text mining framework

SummaryKomenti is a reasoner-enabled semantic query and information extraction framework. It is the only text mining tool that enables querying inferred knowledge from biomedical ontologies. It also contains multiple novel components for vocabulary construction and context disambiguation, which can improve the power of text mining and ontology-based analysis tasks, with a view towards making full use of the semantic provision of biomedical ontologies for text characterisation and analysis. Here, we describe Komenti and its features, and present a use case wherein we automate a clinical audit, extracting medications for hypertrophic cardiomyopathy patients from text, revealing a high precision, and identifying a sub-cohort of patients with atrial fibrillation who are not anti-coagulated, and are therefore at a higher risk of stroke. Availability and ImplementationKomenti is freely available under an open source licence at http://github.com/reality/komenti. More information concerning the use-case is available in supplementary data.

bioinformatics↗

bioRxiv2020

A fast, accurate, and generalisable heuristic-based negation detection algorithm for clinical text

BackgroundNegation detection is an important task in biomedical text mining. Particularly in clinical settings, it is of critical importance to determine whether findings mentioned in text are present or absent. Rule-based negation detection algorithms are a common approach to the task, and more recent investigations have resulted in the development of rule-based systems utilising the rich grammatical information afforded by typed dependency graphs. However, interacting with these complex representations inevitably necessitates complex rules, which are time-consuming to develop and do not generalise well. We hypothesise that a heuristic approach to determining negation via dependency graphs could offer a powerful alternative. ResultsWe describe and implement an algorithm for negation detection based on grammatical distance from a negatory construct in a typed dependency graph. To evaluate the algorithm, we develop two testing corpora comprised of sentences of clinical text extracted from the MIMIC-III database and documents related to hypertrophic cardiomyopathy patients routinely collected at University Hospitals Birmingham NHS trust. Gold-standard validation datasets were built by a combination of human annotation and examination of algorithm error. Finally, we compare the performance of our approach with four other rule-based algorithms on both gold-standard corpora. ConclusionsThe presented algorithm exhibits the best performance by f-measure over the MIMIC-III dataset, and a similar performance to the syntactic negation detection systems over the HCM dataset. It is also the fastest of the dependency-based negation systems explored in this study. Our results show that while a single heuristic approach to dependency-based negation detection is ignorant to certain advanced cases, it nevertheless forms a powerful and stable method, requiring minimal training and adaptation between datasets. As such, it could present a drop-in replacement or augmentation for many-rule negation approaches in clinical text-mining pipelines, particularly for cases where adaptation and rule development is not required or possible.

bioinformatics↗

bioRxiv2020

Substitution of nucleotide-sugar by trehalose-dependent glycogen synthesis pathways in Chlamydiales underlines an unusual requirement for storage polysaccharides within obligate intracellular bacteria

All obligate intracellular pathogens or symbionts of eukaryotes lack glycogen metabolism. Most members of the Chlamydiales order are exceptions to this rule as they contain the classical GlgA-GlgC-dependent pathway of glycogen metabolism that relies on the ADP-Glucose substrate. We surveyed the diversity of Chlamydiales and found glycogen metabolism to be universally present with the important exception of Criblamydiaceae and Waddliaceae families that had been previously reported to lack an active pathway. However, we now find elements of the more recently described GlgE maltose-1-P-dependent pathway in several protist-infecting Chlamydiales. In the case of Waddliaceae and Criblamydiaceae, the substitution of the classical pathway by this recently proposed GlgE pathway was essentially complete as evidenced by the loss of both GlgA and GlgC. Biochemical analysis of recombinant proteins expressed from Waddlia chondrophila and Estrella lausannensis established that both enzymes do polymerize glycogen from trehalose through the production of maltose-1-P by TreS-Mak and its incorporation into glycogens outer chains by GlgE. Unlike Mycobacteriaceae where GlgE-dependent polymerization is produced from both bacterial ADP-Glc and trehalose, glycogen synthesis seems to be entirely dependent on host supplied UDP-Glc and Glucose-6-P or on host supplied trehalose and maltooligosaccharides. These results are discussed in the light of a possible effector nature of these enzymes, of the chlamydial host specificity and of a possible function of glycogen in extracellular survival and infectivity of the chlamydial elementary bodies. They underline that contrarily to all other obligate intracellular bacteria, glycogen metabolism is indeed central to chlamydial replication and maintenance.

microbiology↗

bioRxiv2019

A novel antibody targeting ICOS increases intratumoural cytotoxic to regulatory T cell ratio and induces tumour regression.

The immunosuppressive tumour microenvironment constitutes a significant hurdle to the response to immune checkpoint inhibitors. Both soluble factors and specialised immune cells such as regulatory T cells (TReg) are key components of active intratumoural immunosuppression. Previous studies have shown that Inducible Co-Stimulatory receptor (ICOS) is highly expressed in the tumour microenvironment, especially on TReg, suggesting that it represents a relevant target for preferential depletion of these cells. Here, we used immune profiling of samples from tumour bearing mice and cancer patients to characterise the expression of ICOS in different tissues and solid tumours. By immunizing an Icos knockout transgenic mouse line expressing antibodies with human variable domains, we selected a fully human IgG1 antibody called KY1044 that binds ICOS from different species. Using KY1044, we demonstrated that we can exploit the differential expression of ICOS on T cell subtypes to modify the tumour microenvironment and thereby improve the anti-tumour immune response. We showed that KY1044 induces sustained depletion of ICOShigh TReg cells in mouse tumours and depletion of ICOShigh T cells in the blood of non-human primates, but was also associated with secretion of pro-inflammatory cytokines from ICOSlow TEFF cells. Altogether, KY1044 improved the intratumoural TEFF:TReg ratio and increased activation of TEFF cells, resulting in monotherapy efficacy or in synergistic combinatorial efficacy when administered with the immune checkpoint blocker anti-PD-L1. In summary, our data demonstrate that targeting ICOS with KY1044 can favourably alter the intratumoural immune contexture, promoting an anti-tumour response.

cancer biology↗