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Article ; Online: Generating therapeutic monoclonal antibodies to complex multi-spanning membrane targets: Overcoming the antigen challenge and enabling discovery strategies.

Dodd, Roger / Schofield, Darren J / Wilkinson, Trevor / Britton, Zachary T

2020 Volume 180, Page(s) 111–126

Abstract: Complex integral membrane proteins, which are embedded in the cell surface lipid bilayer by multiple transmembrane spanning helices, encompass families of proteins which are important target classes for drug discovery. These protein families include G ... ...

Abstract	Complex integral membrane proteins, which are embedded in the cell surface lipid bilayer by multiple transmembrane spanning helices, encompass families of proteins which are important target classes for drug discovery. These protein families include G protein-coupled receptors, ion channels and transporters. Although these proteins have typically been targeted by small molecule drugs and peptides, the high specificity of monoclonal antibodies offers a significant opportunity to selectively modulate these target proteins. However, it remains the case that isolation of antibodies with desired pharmacological function(s) has proven difficult due to technical challenges in preparing membrane protein antigens suitable to support antibody drug discovery. In this review recent progress in defining strategies for generation of membrane protein antigens is outlined. We also highlight antibody isolation strategies which have generated antibodies which bind the membrane protein and modulate the protein function.
MeSH term(s)	Animals ; Antibodies, Monoclonal/immunology ; Antibodies, Monoclonal/isolation & purification ; Bacteria/metabolism ; Drug Discovery/methods ; Gene Expression/genetics ; Gene Expression/immunology ; HEK293 Cells ; Humans ; Insecta/metabolism ; Ion Channels/immunology ; Membrane Proteins/chemistry ; Membrane Proteins/immunology ; Membrane Proteins/isolation & purification ; Receptors, G-Protein-Coupled/chemistry ; Receptors, G-Protein-Coupled/immunology ; Recombinant Proteins ; Yeasts/metabolism
Chemical Substances	Antibodies, Monoclonal ; Ion Channels ; Membrane Proteins ; Receptors, G-Protein-Coupled ; Recombinant Proteins
Language	English
Publishing date	2020-05-15
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	1066584-5
ISSN	1095-9130 ; 1046-2023
ISSN (online)	1095-9130
ISSN	1046-2023
DOI	10.1016/j.ymeth.2020.05.006
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Book ; Online: A Review of Stochastic Block Models and Extensions for Graph Clustering

Lee, Clement / Wilkinson, Darren J

2019

Abstract: There have been rapid developments in model-based clustering of graphs, also known as block modelling, over the last ten years or so. We review different approaches and extensions proposed for different aspects in this area, such as the type of the graph, ...

Abstract	There have been rapid developments in model-based clustering of graphs, also known as block modelling, over the last ten years or so. We review different approaches and extensions proposed for different aspects in this area, such as the type of the graph, the clustering approach, the inference approach, and whether the number of groups is selected or estimated. We also review models that combine block modelling with topic modelling and/or longitudinal modelling, regarding how these models deal with multiple types of data. How different approaches cope with various issues will be summarised and compared, to facilitate the demand of practitioners for a concise overview of the current status of these areas of literature. Comment: 93 pages, 3 figures, 4 tables
Keywords	Statistics - Machine Learning ; Computer Science - Machine Learning
Publishing date	2019-02-28
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Empirical food webs of 12 tropical reservoirs in Singapore.

Wilkinson, Clare / Lim, Rayson B H / Liew, Jia Huan / Kwik, Jeffrey T B / Tan, Claudia L Y / Heok Hui, Tan / Yeo, Darren C J

Biodiversity data journal

2022 Volume 10, Page(s) e86192

Abstract: Background: Food webs summarise trophic interactions of the biotic components within an ecosystem, which can influence nutrient dynamics and energy flows, ultimately affecting ecosystem functions and services. Food webs represent the hypothesised ... ...

Abstract	Background: Food webs summarise trophic interactions of the biotic components within an ecosystem, which can influence nutrient dynamics and energy flows, ultimately affecting ecosystem functions and services. Food webs represent the hypothesised trophic links between predators and prey and can be presented as empirical food webs, in which the relative strength/importance of the respective links are quantified. Some common methods used in food web research include gut content analysis (GCA) and stable isotope analysis (SIA). We combine both methods to construct empirical food web models as a basis for monitoring and studying ecosystem-level outcomes of natural (e.g. species turnover in fish assemblage) and intentional environmental change (e.g. biomanipulation). New information: We present 12 food webs from tropical reservoir communities in Singapore and summarise the topology of each with widely-used network indices (e.g. connectance, link density). Each reservoir was surveyed over 4-6 sampling occasions, during which, representative animal groups (i.e. fish species and taxonomic/functional groups of zooplankton and benthic macroinvertebrates) and all likely sources of primary production (i.e. macrophytes, periphyton, phytoplankton and riparian terrestrial plants) were collected. We analysed gut content in fishes and bulk isotope (d
Language	English
Publishing date	2022-09-14
Publishing country	Bulgaria
Document type	Journal Article
ZDB-ID	2736709-5
ISSN	1314-2828
ISSN	1314-2828
DOI	10.3897/BDJ.10.e86192
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Article ; Online: Therapeutic Monoclonal Antibodies to Complex Membrane Protein Targets: Antigen Generation and Antibody Discovery Strategies.

Dodd, Roger B / Wilkinson, Trevor / Schofield, Darren J

BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy

2018 Volume 32, Issue 4, Page(s) 339–355

Abstract: Cell surface membrane proteins comprise a wide array of structurally and functionally diverse proteins involved in a variety of important physiological and homeostatic processes. Complex integral membrane proteins, which are embedded in the lipid bilayer ...

Abstract	Cell surface membrane proteins comprise a wide array of structurally and functionally diverse proteins involved in a variety of important physiological and homeostatic processes. Complex integral membrane proteins, which are embedded in the lipid bilayer by multiple transmembrane-spanning helices, are represented by families of proteins that are important target classes for drug discovery. Such protein families include G-protein-coupled receptors, ion channels and transporters. Although these targets have typically been the domain of small-molecule drugs, the exquisite specificity of monoclonal antibodies offers a significant opportunity to selectively modulate these target proteins. Nevertheless, the isolation of antibodies with desired pharmacological functions has proved difficult because of technical challenges in preparing membrane protein antigens for antibody drug discovery. In this review, we describe recent progress in defining strategies for the generation of membrane protein antigens. We also describe antibody-isolation strategies that identify antibodies that bind the membrane protein and modulate protein function.
MeSH term(s)	Animals ; Antibodies, Monoclonal/isolation & purification ; Antigens/immunology ; Drug Discovery/methods ; Humans ; Membrane Proteins/immunology
Chemical Substances	Antibodies, Monoclonal ; Antigens ; Membrane Proteins
Language	English
Publishing date	2018-06-20
Publishing country	New Zealand
Document type	Journal Article ; Review
ZDB-ID	1364202-9
ISSN	1179-190X ; 1173-8804
ISSN (online)	1179-190X
ISSN	1173-8804
DOI	10.1007/s40259-018-0289-y
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Article: An Oxford Nanopore Technology-Based Hepatitis B Virus Sequencing Protocol Suitable For Genomic Surveillance Within Clinical Diagnostic Settings.

Tshiabuila, Derek / Choga, Wonderful / James, San E / Maponga, Tongai / Preiser, Wolfgang / van Zyl, Gert / Moir, Monika / van Wyk, Stephanie / Giandhari, Jennifer / Pillay, Sureshnee / Anyaneji, Ugochukwu J / Lessells, Richard J / Naidoo, Yeshnee / Sanko, Tomasz Janusz / Wilkinson, Eduan / Tegally, Houriiyah / Baxter, Cheryl / Martin, Darren P / de Oliveira, Tulio

medRxiv : the preprint server for health sciences

2024

Abstract: ... into ten phylogenetically distinct genotypes (A - J) determined based on full-genome sequence data or ...

Abstract	Chronic hepatitis B virus (HBV) infection remains a significant public health concern, particularly in Africa, where there is a substantial burden. HBV is an enveloped virus, with isolates being classified into ten phylogenetically distinct genotypes (A - J) determined based on full-genome sequence data or reverse hybridization-based diagnostic tests. In practice, limitations are noted in that diagnostic sequencing, generally using Sanger sequencing, tends to focus only on the S-gene, yielding little or no information on intra-patient HBV genetic diversity with very low-frequency variants and reverse hybridization detects only known genotype-specific mutations. To resolve these limitations, we developed an Oxford Nanopore Technology (ONT)-based HBV genotyping protocol suitable for clinical virology, yielding complete HBV genome sequences and extensive data on intra-patient HBV diversity. Specifically, the protocol involves tiling-based PCR amplification of HBV sequences, library preparation using the ONT Rapid Barcoding Kit, ONT GridION sequencing, genotyping using Genome Detective software, recombination analysis using jpHMM and RDP5 software, and drug resistance profiling using Geno2pheno software. We prove the utility of our protocol by efficiently generating and characterizing high-quality near full-length HBV genomes from 148 left-over diagnostic Hepatitis B patient samples obtained in the Western Cape province of South Africa, providing valuable insights into the genetic diversity and epidemiology of HBV in this region of the world.
Language	English
Publishing date	2024-01-25
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.01.19.24301519
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Book ; Online: A hierarchical model of non-homogeneous Poisson processes for Twitter retweets

Lee, Clement / Wilkinson, Darren J

2018

Abstract: We present a hierarchical model of non-homogeneous Poisson processes (NHPP) for information diffusion on online social media, in particular Twitter retweets. The retweets of each original tweet are modelled by a NHPP, for which the intensity function is ... ...

Abstract	We present a hierarchical model of non-homogeneous Poisson processes (NHPP) for information diffusion on online social media, in particular Twitter retweets. The retweets of each original tweet are modelled by a NHPP, for which the intensity function is a product of time-decaying components and another component that depends on the follower count of the original tweet author. The latter allows us to explain or predict the ultimate retweet count by a network centrality-related covariate. The inference algorithm enables the Bayes factor to be computed, in order to facilitate model selection. Finally, the model is applied to the retweet data sets of two hashtags. Comment: 48 pages, 13 figures, 2 tables
Keywords	Statistics - Applications ; Computer Science - Social and Information Networks ; Statistics - Computation
Publishing date	2018-02-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Empirical food webs of 12 tropical reservoirs in Singapore

Wilkinson, Clare / Lim, Rayson B H / Liew, Jia Huan / Kwik, Jeffrey T B / Tan, Claudia L Y / Heok Hui, Tan / Yeo, Darren C J

Biodiversity Data Journal. 2022 Sept. 14, v. 10 p.e86192-

2022

Abstract: Food webs summarise trophic interactions of the biotic components within an ecosystem, which can influence nutrient dynamics and energy flows, ultimately affecting ecosystem functions and services. Food webs represent the hypothesised trophic links ... ...

Abstract	Food webs summarise trophic interactions of the biotic components within an ecosystem, which can influence nutrient dynamics and energy flows, ultimately affecting ecosystem functions and services. Food webs represent the hypothesised trophic links between predators and prey and can be presented as empirical food webs, in which the relative strength/importance of the respective links are quantified. Some common methods used in food web research include gut content analysis (GCA) and stable isotope analysis (SIA). We combine both methods to construct empirical food web models as a basis for monitoring and studying ecosystem-level outcomes of natural (e.g. species turnover in fish assemblage) and intentional environmental change (e.g. biomanipulation). We present 12 food webs from tropical reservoir communities in Singapore and summarise the topology of each with widely-used network indices (e.g. connectance, link density). Each reservoir was surveyed over 4–6 sampling occasions, during which, representative animal groups (i.e. fish species and taxonomic/functional groups of zooplankton and benthic macroinvertebrates) and all likely sources of primary production (i.e. macrophytes, periphyton, phytoplankton and riparian terrestrial plants) were collected. We analysed gut content in fishes and bulk isotope (d¹³C and d¹⁵N) profiles of all animals (i.e. fishes and invertebrates) and plants collected. Both sets of information were used to estimate the relative strength of trophic relationships using Bayesian mixing models. We document our protocol here, alongside a script in the R programming language for executing data management/analyses/visualisation procedures used in our study. These data can be used to glean insights into trends in inter- and intra-specific or guild interactions in analogous freshwater lake habitats.
Keywords	Bayesian theory ; Singapore ; biodiversity ; digestive system ; ecosystems ; energy ; fish ; food webs ; freshwater lakes ; information management ; macroinvertebrates ; macrophytes ; periphyton ; phytoplankton ; primary productivity ; stable isotopes ; topology ; zooplankton ; gut content ; stable isotope analysis ; freshwater communities ; reservoirs ; trophic interactions
Language	English
Dates of publication	2022-0914
Publishing place	Pensoft Publishers
Document type	Article ; Online
ZDB-ID	2736709-5
ISSN	1314-2828
ISSN	1314-2828
DOI	10.3897/BDJ.10.e86192
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Bayesian inference for Markov jump processes with informative observations.

Golightly, Andrew / Wilkinson, Darren J

Statistical applications in genetics and molecular biology

2015 Volume 14, Issue 2, Page(s) 169–188

Abstract: In this paper we consider the problem of parameter inference for Markov jump process (MJP) representations of stochastic kinetic models. Since transition probabilities are intractable for most processes of interest yet forward simulation is ... ...

Abstract	In this paper we consider the problem of parameter inference for Markov jump process (MJP) representations of stochastic kinetic models. Since transition probabilities are intractable for most processes of interest yet forward simulation is straightforward, Bayesian inference typically proceeds through computationally intensive methods such as (particle) MCMC. Such methods ostensibly require the ability to simulate trajectories from the conditioned jump process. When observations are highly informative, use of the forward simulator is likely to be inefficient and may even preclude an exact (simulation based) analysis. We therefore propose three methods for improving the efficiency of simulating conditioned jump processes. A conditioned hazard is derived based on an approximation to the jump process, and used to generate end-point conditioned trajectories for use inside an importance sampling algorithm. We also adapt a recently proposed sequential Monte Carlo scheme to our problem. Essentially, trajectories are reweighted at a set of intermediate time points, with more weight assigned to trajectories that are consistent with the next observation. We consider two implementations of this approach, based on two continuous approximations of the MJP. We compare these constructs for a simple tractable jump process before using them to perform inference for a Lotka-Volterra system. The best performing construct is used to infer the parameters governing a simple model of motility regulation in Bacillus subtilis.
MeSH term(s)	Algorithms ; Bayes Theorem ; Computer Simulation ; Kinetics ; Markov Chains ; Models, Biological ; Monte Carlo Method ; Probability
Language	English
Publishing date	2015-04
Publishing country	Germany
Document type	Journal Article
ISSN	1544-6115
ISSN (online)	1544-6115
DOI	10.1515/sagmb-2014-0070
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Article ; Online: Land-use change erodes trophic redundancy in tropical forest streams: Evidence from amino acid stable isotope analysis.

Chua, Kenny W J / Liew, Jia Huan / Wilkinson, Clare L / Ahmad, Amirrudin B / Tan, Heok Hui / Yeo, Darren C J

The Journal of animal ecology

2021 Volume 90, Issue 6, Page(s) 1433–1443

Abstract: Studies have shown that food chain length is governed by interactions between species richness, ecosystem size and resource availability. While redundant trophic links may buffer impacts of species loss on food chain length, higher extinction risks ... ...

Abstract	Studies have shown that food chain length is governed by interactions between species richness, ecosystem size and resource availability. While redundant trophic links may buffer impacts of species loss on food chain length, higher extinction risks associated with predators may result in bottom-heavy food webs with shorter food chains. The lack of consensus in earlier empirical studies relating species richness and food chain length reflects the need to account robustly for the factors described above. In response to this, we conducted an empirical study to elucidate impacts of land-use change on food chain length in tropical forest streams of Southeast Asia. Despite species losses associated with forest loss at our study areas, results from amino acid isotope analyses showed that food chain length was not linked to land use, ecosystem size or resource availability. Correspondingly, species losses did not have a significant effect on occurrence likelihoods of all trophic guilds except herbivores. Impacts of species losses were likely buffered by initial high levels of trophic redundancy, which declined with canopy cover. Declines in trophic redundancy were most drastic amongst invertivorous fishes. Declines in redundancy across trophic guilds were also more pronounced in wider and more resource-rich streams. While our study found limited evidence for immediate land-use impacts on stream food chains, the potential loss of trophic redundancy in the longer term implies increasing vulnerability of streams to future perturbations, as long as land conversion continues unabated.
MeSH term(s)	Amino Acids ; Animals ; Ecosystem ; Food Chain ; Forests ; Isotopes
Chemical Substances	Amino Acids ; Isotopes
Language	English
Publishing date	2021-03-19
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	3024-7
ISSN	1365-2656 ; 0021-8790
ISSN (online)	1365-2656
ISSN	0021-8790
DOI	10.1111/1365-2656.13462
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Article ; Online: Stochastic modelling for quantitative description of heterogeneous biological systems.

Wilkinson, Darren J

Nature reviews. Genetics

2009 Volume 10, Issue 2, Page(s) 122–133

Abstract: Two related developments are currently changing traditional approaches to computational systems biology modelling. First, stochastic models are being used increasingly in preference to deterministic models to describe biochemical network dynamics at the ... ...

Abstract	Two related developments are currently changing traditional approaches to computational systems biology modelling. First, stochastic models are being used increasingly in preference to deterministic models to describe biochemical network dynamics at the single-cell level. Second, sophisticated statistical methods and algorithms are being used to fit both deterministic and stochastic models to time course and other experimental data. Both frameworks are needed to adequately describe observed noise, variability and heterogeneity of biological systems over a range of scales of biological organization.
MeSH term(s)	Computational Biology/methods ; Data Interpretation, Statistical ; Gene Expression Regulation ; Models, Biological ; Proto-Oncogene Proteins c-mdm2/metabolism ; Stochastic Processes ; Systems Biology ; Tumor Suppressor Protein p53/metabolism
Chemical Substances	Tumor Suppressor Protein p53 ; MDM2 protein, human (EC 2.3.2.27) ; Proto-Oncogene Proteins c-mdm2 (EC 2.3.2.27)
Language	English
Publishing date	2009-01-13
Publishing country	England
Document type	Research Support, Non-U.S. Gov't ; Review
ZDB-ID	2035157-4
ISSN	1471-0064 ; 1471-0056
ISSN (online)	1471-0064
ISSN	1471-0056
DOI	10.1038/nrg2509
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