Biology subjects

Pocock, M.

Publications and source records attributed to Pocock, M..

3 recordsLinked to original sources

bioRxiv2024

Maturation of human cardiac organoids are required for disease modelling and drug discovery

Cardiac maturation is an important developmental phase culminating in profound biological and functional changes to adapt to the high demand environment after birth1,2. Maturation of human pluripotent stem cell-derived human cardiac organoids (hCO) to more closely resemble human heart tissue is critical for understanding disease pathology. Herein, we profile human heart maturation in vivo3 to identify key signalling pathways that drive maturation in hCOs4,5. Transient activation of both the 5 AMP-activated kinase (AMPK) and estrogen-related receptor (ERR) promoted hCO maturation by mimicking the increased functional demands of post-natal development. hCOs cultured under these directed maturation (DM) conditions (DM-hCOs) display robust transcriptional maturation including increased expression of mature sarcomeric and oxidative phosphorylation genes resulting in enhanced metabolic capacity. DM-hCOs have functionally mature properties such as sarcoplasmic reticulum-dependent calcium handling, accurate responses to drug treatments perturbing the excitation-coupling process and ability to detect ectopy CASQ2 and RYR2 mutants. Importantly, DM- hCOs permit modelling of complex human disease processes such as desmoplakin (DSP) cardiomyopathy, which is driven by multiple cell types. Subsequently, we deploy DM-hCOs to demonstrate that bromodomain extra-terminal inhibitor INCB054329 rescues the DSP phenotype. Together, this study demonstrates that recapitulating in vivo development promotes advanced maturation enabling disease modelling and the identification of a therapeutic strategy for DSP- cardiomyopathy.

bioengineering↗

bioRxiv2021

Integration of probabilistic functional networks without an external Gold Standard

BackgroundProbabilistic functional integrated networks (PFINs) are designed to aid our understanding of cellular biology and can be used to generate testable hypotheses about protein function. PFINs are generally created by scoring the quality of interaction datasets against a Gold Standard dataset, usually chosen from a separate high-quality data source, prior to their integration. Use of an external Gold Standard has several drawbacks, including data redundancy, data loss and the need for identifier mapping, which can complicate the network build and impact on PFIN performance. ResultsWe describe the development of an integration technique, ssNet, that scores and integrates both high-throughput and low-throughout data from a single source database in a consistent manner without the need for an external Gold Standard dataset. Using data from Saccharomyces cerevisiae we show that ssNet is easier and faster, overcoming the challenges of data redundancy, Gold Standard bias and ID mapping, while producing comparable performance. In addition ssNet results in less loss of data and produces a more complete network. ConclusionsThe ssNet method allows PFINs to be built successfully from a single database, while producing comparable network performance to networks scored using an external Gold Standard source.

bioinformatics↗

bioRxiv2020

Inferring species interactions from ecological survey data: a mechanistic approach to predict quantitative food webs of seed-feeding by carabid beetles

O_LIEcological networks are valuable for ecosystem analysis but their use is often limited by a lack of data because many types of ecological interaction, e.g. predation, are short-lived and difficult to observe or detect. There are different methods for inferring the presence of interactions, which we lack methods to predict interaction strengths and so use weighted network analysis. C_LIO_LIHere, we develop a trait-based approach suitable for creating quantitative networks, i.e. with varying interaction strengths. We developed the method for seed-feeding carabid ground beetles (Coleoptera: Carabidae) although the principles can be applied to other interactions. C_LIO_LIWe used existing literature data from experimental seed-feeding trials to predict a per-individual interaction cost index based on carabid and seed size with frequency-dependent prey selection and assuming bottom up control. This was scaled up to the population level to create predicted inferred weighted networks using the abundance of carabids and seeds in samples from arable fields and energetic intake rates of carabids from the literature. From these weighted networks, we also calculated a novel measure of predation pressure. C_LIO_LIWe applied it to existing ecological survey data from 255 arable fields with carabid data from pitfall traps and plant seeds from seed rain traps. Analysis of these inferred networks led to testable hypotheses about how networks and predation pressure varied amongst fields. C_LIO_LIInferred networks are valuable because (i) they provide null models for the structuring of food webs to test against empirical species interaction data, e.g. DNA analysis of carabid gut regurgitates, and (ii) they allow weighted inferred networks to be constructed whenever we can estimate interactions between species and have ecological census data available. This would permit network analysis even at times and in places when interactions were not directly assessed. C_LI

ecology↗