Michael Charleston

Bioacoustics data analysis - a taxonomy, survey and open challenges

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2020

DOI: 10.1109/ACCESS.2020.2978547

Wing patterning genes and coevolution of Müllerian mimicry inHeliconiusbutterflies: Support from phylogeography, cophylogeny, and divergence times

Publisher: Wiley

Date: 12-2015

DOI: 10.1111/EVO.12812

Abstract: Ex les of long-term coevolution are rare among free-living organisms. Müllerian mimicry in Heliconius butterflies had been suggested as a key ex le of coevolution by early genetic studies. However, research over the last two decades has been dominated by the idea that the best-studied comimics, H. erato and H. melpomene, did not coevolve at all. Recently sequenced genes associated with wing color pattern phenotype offer a new opportunity to resolve this controversy. Here, we test the hypothesis of coevolution between H. erato and H. melpomene using Bayesian multilocus analysis of five color pattern genes and five neutral genetic markers. We first explore the extent of phylogenetic agreement versus conflict between the different genes. Coevolution is then tested against three aspects of the mimicry ersifications: phylogenetic branching patterns, ergence times, and, for the first time, phylogeographic histories. We show that all three lines of evidence are compatible with strict coevolution of the erse mimicry wing patterns, contrary to some recent suggestions. Instead, these findings tally with a coevolutionary ersification driven primarily by the ecological force of Müllerian mimicry.

MrIML: Multi‐response interpretable machine learning to model genomic landscapes

Publisher: Wiley

Date: 06-09-2021

DOI: 10.1111/1755-0998.13495

Abstract: We introduce a new R package “MrIML” (“Mister iml” Multi‐response Interpretable Machine Learning). MrIML provides a powerful and interpretable framework that enables users to harness recent advances in machine learning to quantify multilocus genomic relationships, to identify loci of interest for future landscape genetics studies, and to gain new insights into adaptation across environmental gradients. Relationships between genetic variation and environment are often nonlinear and interactive these characteristics have been challenging to address using traditional landscape genetic approaches. Our package helps capture this complexity and offers functions that fit and interpret a wide range of highly flexible models that are routinely used for single‐locus landscape genetics studies but are rarely extended to estimate response functions for multiple loci. To demonstrate the package's broad functionality, we test its ability to recover landscape relationships from simulated genomic data. We also apply the package to two empirical case studies. In the first, we model genetic variation of North American balsam poplar ( Populus balsamifera , Salicaceae) populations across environmental gradients. In the second case study, we recover the landscape and host drivers of feline immunodeficiency virus genetic variation in bobcats ( Lynx rufus ). The ability to model thousands of loci collectively and compare models from linear regression to extreme gradient boosting, within the same analytical framework, has the potential to be transformative. The MrIML framework is also extendable and not limited to modelling genetic variation for ex le, it can quantify the environmental drivers of microbiomes and coinfection dynamics.

Draft Genome Sequences of Three Sub-Antarctic Rhodococcus spp., Including Two Novel Psychrophilic Genomospecies

Publisher: American Society for Microbiology

Date: 07-09-2017

DOI: 10.1128/GENOMEA.00898-17

Abstract: The draft genome sequences of three sub-Antarctic Rhodococcus sp. strains—1159, 1163, and 1168—are reported here. The estimated genome sizes were 7.09 Mb with a 62.3% GC content for strain 1159, 4.45 Mb with a 62.3% GC content for strain 1163, and 5.06 Mb with a 62.10% GC content for strain 1168.

The forecasting of dynamical Ross River virus outbreaks: Victoria, Australia

Publisher: Elsevier BV

Date: 03-2020

DOI: 10.1016/J.EPIDEM.2019.100377

Abstract: Ross River virus (RRV) is Australia's most epidemiologically important mosquito-borne disease. During RRV epidemics in the State of Victoria (such as 2010/11 and 2016/17) notifications can account for up to 30% of national RRV notifications. However, little is known about factors which can forecast RRV transmission in Victoria. We aimed to understand factors associated with RRV transmission in epidemiologically important regions of Victoria and establish an early warning forecast system. We developed negative binomial regression models to forecast human RRV notifications across 11 Local Government Areas (LGAs) using climatic, environmental, and oceanographic variables. Data were collected from July 2008 to June 2018. Data from July 2008 to June 2012 were used as a training data set, while July 2012 to June 2018 were used as a testing data set. Evapotranspiration and precipitation were found to be common factors for forecasting RRV notifications across sites. Several site-specific factors were also important in forecasting RRV notifications which varied between LGA. From the 11 LGAs examined, nine experienced an outbreak in 2011/12 of which the models for these sites were a good fit. All 11 LGAs experienced an outbreak in 2016/17, however only six LGAs could predict the outbreak using the same model. We document similarities and differences in factors useful for forecasting RRV notifications across Victoria and demonstrate that readily available and inexpensive climate and environmental data can be used to predict epidemic periods in some areas. Furthermore, we highlight in certain regions the complexity of RRV transmission where additional epidemiological information is needed to accurately predict RRV activity. Our findings have been applied to produce a Ross River virus Outbreak Surveillance System (ROSS) to aid in public health decision making in Victoria.

Patterns of SARS-CoV-2 exposure and mortality suggest endemic infections, in addition to space and population factors, shape dynamics across countries

Publisher: Cold Spring Harbor Laboratory

Date: 16-07-2021

DOI: 10.1101/2021.07.12.21260394

Abstract: Some countries have been crippled by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic while others have emerged with few infections and fatalities the factors underscoring this macro-epidemiological variation is one of the mysteries of this global catastrophe. Variation in immune responses influence SARS-CoV-2 transmission and mortality, and factors shaping this variation at the country level, in addition to other socio-ecological drivers, may be important. Here, we construct spatially explicit Bayesian models that combine data on prevalence of endemic diseases and other socio-ecological characteristics to quantify patterns of confirmed deaths and cases across the globe before mass vaccination. We find that the prevalence of parasitic worms, human immunodeficiency virus and malaria play a surprisingly important role in predicting country-level SARS-CoV-2 patterns. When combined with factors such as population density, our models predict 63% (56-67) and 76% (69-81) of confirmed cases and deaths among countries, respectively. While our findings at this macro-scale are necessarily associative, they highlight a need for studies to consider factors, such as infection by other pathogens, on global SARS-CoV-2 dynamics. These relationships are vital for developing countries that already have the highest burden of endemic disease and are becoming the most affected by the SARS-CoV-2 pandemic.

Collective foraging in spatially complex nutritional environments

Publisher: The Royal Society

Date: 03-07-2017

DOI: 10.1098/RSTB.2016.0238

Abstract: Nutrition impinges on virtually all aspects of an animal's life, including social interactions. Recent advances in nutritional ecology show how social animals often trade-off in idual nutrition and group cohesion when foraging in simplified experimental environments. Here, we explore how the spatial structure of the nutritional landscape influences these complex collective foraging dynamics in ecologically realistic environments. We introduce an in idual-based model integrating key concepts of nutritional geometry, collective animal behaviour and spatial ecology to study the nutritional behaviour of animal groups in large heterogeneous environments containing foods with different abundance, patchiness and nutritional composition. Simulations show that the spatial distribution of foods constrains the ability of in iduals to balance their nutrient intake, the lowest performance being attained in environments with small isolated patches of nutritionally complementary foods. Social interactions improve in idual regulatory performances when food is scarce and clumpy, but not when it is abundant and scattered, suggesting that collective foraging is favoured in some environments only. These social effects are further lified if foragers adopt flexible search strategies based on their in idual nutritional state. Our model provides a conceptual and predictive framework for developing new empirically testable hypotheses in the emerging field of social nutrition. This article is part of the themed issue ‘Physiological determinants of social behaviour in animals’.

A review of visualisations of protein fold networks and their relationship with sequence and function

Publisher: Wiley

Date: 09-10-2023

DOI: 10.1111/BRV.12905

Abstract: Proteins form arguably the most significant link between genotype and phenotype. Understanding the relationship between protein sequence and structure, and applying this knowledge to predict function, is difficult. One way to investigate these relationships is by considering the space of protein folds and how one might move from fold to fold through similarity, or potential evolutionary relationships. The many in idual characterisations of fold space presented in the literature can tell us a lot about how well the current Protein Data Bank represents protein fold space, how convergence and ergence may affect protein evolution, how proteins affect the whole of which they are part, and how proteins themselves function. A synthesis of these different approaches and viewpoints seems the most likely way to further our knowledge of protein structure evolution and thus, facilitate improved protein structure design and prediction.

Evolving Nutritional Strategies in the Presence of Competition: A Geometric Agent-Based Model

Publisher: Public Library of Science (PLoS)

Date: 27-03-2015

DOI: 10.1371/JOURNAL.PCBI.1004111

Long‐Term Spatiotemporal Dynamics and Factors Associated with Trends in Bare‐Nosed Wombats

Publisher: Wiley

Date: 12-02-2021

DOI: 10.1002/JWMG.22014

Introducing TreeCollapse: a novel greedy algorithm to solve the cophylogeny reconstruction problem

Publisher: Springer Science and Business Media LLC

Date: 07-2017

DOI: 10.1186/1471-2105-15-S16-S14

Phylogenetic Codivergence Supports Coevolution of Mimetic Heliconius Butterflies

Publisher: Public Library of Science (PLoS)

Date: 07-05-2012

DOI: 10.1371/JOURNAL.PONE.0036464

Biological Network Edit Distance

Publisher: Mary Ann Liebert Inc

Date: 09-2016

DOI: 10.1089/CMB.2016.0062

Abstract: Interactions among biological entities contain more information than purely the similarities between the entities. For ex le, interactions between genes, and gene products, can be more informative than the sequence similarities of the genes involved. However, the study of biological networks and their evolution in particular is still in its infancy. Simplified theoretical models of the development of biological networks from a starting state exist, but the problem of finding a distance between existing biological networks, with an unknown history, has seen less research. Metrics for network distance can also be used to measure the fit between theoretically derived networks and their real-world counterpart. In this article, we present a useful model of biological network distance and demonstrate an implementation using simulated gene regulatory networks. We compared our method with existing methods for network alignment and showed that we are much better able to identify evolutionary changes in biological networks. In particular, we can recover the evolutionary trees that describe the relationship between these networks.

Network modelling of gene regulation

Publisher: Springer Science and Business Media LLC

Date: 23-12-2011

DOI: 10.1007/S12551-010-0041-4

Phylogeny ☆

Publisher: Elsevier

Date: 2017

DOI: 10.1016/B978-0-12-809633-8.06904-1

A SIMPLE MODEL EXPLAINS THE DYNAMICS OF PREFERENTIAL HOST SWITCHING AMONG MAMMAL RNA VIRUSES

Publisher: Wiley

Date: 19-02-2013

DOI: 10.1111/EVO.12064

Nutritional ecology beyond the individual: a conceptual framework for integrating nutrition and social interactions

Publisher: Wiley

Date: 14-01-2015

DOI: 10.1111/ELE.12406

Methods of analyzing patterns of multimorbidity using network analysis: a scoping review protocol.

Publisher: Ovid Technologies (Wolters Kluwer Health)

Date: 17-05-2021

DOI: 10.11124/JBIES-20-00498

From Gene to Organismal Phylogeny: Reconciled Trees and the Gene Tree/Species Tree Problem

Publisher: Elsevier BV

Date: 04-1997

DOI: 10.1006/MPEV.1996.0390

Abstract: The processes of gene duplication, loss, and lineage sorting can result in incongruence between the phylogenies of genes and those of species. This incongruence complicates the task of inferring the latter from the former. We describe the use of reconciled trees to reconstruct the history of a gene tree with respect to a species tree. Reconciled trees allow the history of the gene tree to be visualized and also quantify the relationship between the two trees. The cost of a reconciled tree is the total number of duplications and gene losses required to reconcile a gene tree with its species tree. We describe the use of heuristic searches to find the species tree which yields the reconciled tree with the lowest cost. This method can be used to infer species trees from one or more gene trees.

Evolution of endogenous retroviruses in the Suidae: evidence for different viral subpopulations in African and Eurasian host species

Publisher: Springer Science and Business Media LLC

Date: 24-05-2011

DOI: 10.1186/1471-2148-11-139

Abstract: Porcine endogenous retroviruses (PERVs) represent remnants of an exogenous form that have become integrated in the domestic pig ( Sus scrofa ) genome. Although they are usually inactive, the capacity of γ1 ERVs to infect human cells in vitro has raised concerns about xenotransplantation because the viruses could cross the species barrier to humans. Here we have analyzed the evolution of γ1 ERVs in ten species of Suidae (suids, pigs and hogs) from Eurasia and Africa using DNA sequences for their coding domains ( gag , pro / pol and env genes). For comparison with γ1 PERVs, we have also analysed γ2 ERVs which in domestic pigs are known to be inactive and do not pose a risk to xenotransplantation. Phylogenetic analysis using Bayesian inference showed that γ1 and γ2 ERVs have distinctive evolutionary histories. Firstly, two different viral lineages of γ1 ERVs were found and a coevolutionary analysis demonstrated that they correspond broadly to their host phylogeny, one of Eurasian and another of African species, and show no evidence of horizontal transmission. γ2 ERVs, however, show a bush-like evolution, suggesting a rapid viral radiation from a single common ancestor with no correspondence between host and viral evolutionary trees. Furthermore, though γ1 ERV env genes do not possess frequent stop codons, γ2 env genes do. To understand whether γ1 suid ERVs may be still replicating, we have also evaluated their likely mechanism of proliferation by statistically testing internal to terminal branches using nonsynonymous versus synonymous substitution ratios. Our results suggest that γ1 ERVs are increasing in copy number by reinfection, which requires the translocation of the virus from one cell to another. Evidence of at least two viral subpopulations was observed in γ1 ERVs from Eurasian and African host species. These results should be taken into account in xenotransplantation since γ1 ERVs appear to be co erging with their host and maintaining ongoing capacity to infect somatic and germ cells.

Performance of Akaike Information Criterion and Bayesian Information Criterion in Selecting Partition Models and Mixture Models

Publisher: Oxford University Press (OUP)

Date: 28-12-2022

DOI: 10.1093/SYSBIO/SYAC081

Abstract: In molecular phylogenetics, partition models and mixture models provide different approaches to accommodating heterogeneity in genomic sequencing data. Both types of models generally give a superior fit to data than models that assume the process of sequence evolution is homogeneous across sites and lineages. The Akaike Information Criterion (AIC), an estimator of Kullback–Leibler ergence, and the Bayesian Information Criterion (BIC) are popular tools to select models in phylogenetics. Recent work suggests that AIC should not be used for comparing mixture and partition models. In this work, we clarify that this difficulty is not fully explained by AIC misestimating the Kullback–Leibler ergence. We also investigate the performance of the AIC and BIC at comparing amongst mixture models and amongst partition models. We find that under nonstandard conditions (i.e. when some edges have small expected number of changes), AIC underestimates the expected Kullback–Leibler ergence. Under such conditions, AIC preferred the complex mixture models and BIC preferred the simpler mixture models. The mixture models selected by AIC had a better performance in estimating the edge length, while the simpler models selected by BIC performed better in estimating the base frequencies and substitution rate parameters. In contrast, AIC and BIC both prefer simpler partition models over more complex partition models under nonstandard conditions, despite the fact that the more complex partition model was the generating model. We also investigated how mispartitioning (i.e., grouping sites that have not evolved under the same process) affects both the performance of partition models compared with mixture models and the model selection process. We found that as the level of mispartitioning increases, the bias of AIC in estimating the expected Kullback–Leibler ergence remains the same, and the branch lengths and evolutionary parameters estimated by partition models become less accurate. We recommend that researchers are cautious when using AIC and BIC to select among partition and mixture models other alternatives, such as cross-validation and bootstrapping, should be explored, but may suffer similar limitations [AIC BIC mispartitioning partitioning partition model mixture model].

Cospeciation

Publisher: Elsevier

Date: 2016

DOI: 10.1016/B978-0-12-800049-6.00200-6

Macronutrient intakes and the lifespan-fecundity trade-off: a geometric framework agent-based model

Publisher: The Royal Society

Date: 02-2019

DOI: 10.1098/RSIF.2018.0733

Abstract: Lifespan and fecundity, the main components in evolutionary fitness, are both strongly affected by nutritional state. Geometric framework of nutrition (GFN) experiments has shown that lifespan and fecundity are separated in nutrient space leading to a functional trade-off between the two traits. Here we develop a spatially explicit agent-based model (ABM) using the GFN to explore how ecological factors may cause selection on macronutrient appetites to optimally balance these life-history traits. We show that increasing the risk of extrinsic mortality favours intake of a mixture of nutrients that is associated with maximal fecundity at the expense of reduced longevity and that this result is robust across spatial and nutritional environments. These model behaviours are consistent with what has been observed in studies that quantify changes in life history in response to environmental manipulations. Previous GFN-derived ABMs have treated fitness as a single value. This is the first such model to instead decompose fitness into its primary component traits, longevity and fecundity, allowing evolutionary fitness to be an emergent property of the two. Our model demonstrates that selection on macronutrient appetites may affect life-history trade-offs and makes predictions that can be directly tested in artificial selection experiments.

Phylogeny

Publisher: Elsevier

Date: 2013

DOI: 10.1016/B978-0-12-374984-0.01160-8

Emerging phylogenetic structure of the SARS-CoV-2 pandemic

Publisher: Oxford University Press (OUP)

Date: 07-2020

DOI: 10.1093/VE/VEAA082

Abstract: Since spilling over into humans, SARS-CoV-2 has rapidly spread across the globe, accumulating significant genetic ersity. The structure of this genetic ersity and whether it reveals epidemiological insights are fundamental questions for understanding the evolutionary trajectory of this virus. Here, we use a recently developed phylodynamic approach to uncover phylogenetic structures underlying the SARS-CoV-2 pandemic. We find support for three SARS-CoV-2 lineages co-circulating, each with significantly different demographic dynamics concordant with known epidemiological factors. For ex le, Lineage C emerged in Europe with a high growth rate in late February, just prior to the exponential increase in cases in several European countries. Non-synonymous mutations that characterize Lineage C occur in functionally important gene regions responsible for viral replication and cell entry. Even though Lineages A and B had distinct demographic patterns, they were much more difficult to distinguish. Continuous application of phylogenetic approaches to track the evolutionary epidemiology of SARS-CoV-2 lineages will be increasingly important to validate the efficacy of control efforts and monitor significant evolutionary events in the future.

Event-Based Cophylogenetic Comparative Analysis

Publisher: Springer Berlin Heidelberg

Date: 2014

DOI: 10.1007/978-3-662-43550-2_20

Node Handprinting: A Scalable and Accurate Algorithm for Aligning Multiple Biological Networks

Publisher: Mary Ann Liebert Inc

Date: 07-2015

DOI: 10.1089/CMB.2014.0247

Abstract: Due to recent advancements in high-throughput sequencing technologies, progressively more protein-protein interactions have been identified for a growing number of species. Subsequently, the protein-protein interaction networks for these species have been further refined. The increase in the quality and availability of these networks has in turn brought a demand for efficient methods to analyze such networks. The pairwise alignment of these networks has been moderately investigated, with numerous algorithms available, but there is very little progress in the field of multiple network alignment. Multiple alignment of networks from different organisms is ideal at finding abnormally conserved or disparate subnetworks. We present a fast and accurate algorithmic approach, Node Handprinting (NH), based on our previous work with Node Fingerprinting, which enables quick and accurate alignment of multiple networks. We also propose two new metrics for the analysis of multiple alignments, as the current metrics are not as sophisticated as their pairwise alignment counterparts. To assess the performance of NH, we use previously aligned datasets as well as protein interaction networks generated from the public database BioGRID. Our results indicate that NH compares favorably with current methodologies and is the only algorithm capable of performing the more complex alignments.

RASCAL: A Randomized Approach for Coevolutionary Analysis

Publisher: Mary Ann Liebert Inc

Date: 03-2016

DOI: 10.1089/CMB.2015.0111

Abstract: A popular method for coevolutionary inference is cophylogenetic reconstruction where the branch length of the phylogenies have been previously derived. This approach, unlike the more generalized reconstruction techniques that are NP-Hard, can reconcile the shared evolutionary history of a pair of phylogenetic trees in polynomial time. This approach, while proven to be highly successful, requires a high polynomial running time. This is quickly becoming a limiting factor of this approach due to the continual increase in size of coevolutionary data sets. One existing method that combats this issue proposes a trade-off of accuracy for an asymptotic time complexity reduction. This technique in almost 70% of cases converges on Pareto optimal solutions in linear time. We build on this prior work by proposing an alternate linear time algorithm (RASCAL) that offers a significant accuracy increase, with RASCAL converging on Pareto optimal solutions in 85% of cases and unlike prior methods can ensure, with high probability, that all optimal solutions can be recovered, provided sufficient replicates are performed.

Fluralaner as a novel treatment for sarcoptic mange in the bare-nosed wombat (Vombatus ursinus): safety, pharmacokinetics, efficacy and practicable use

Publisher: Springer Science and Business Media LLC

Date: 06-01-2021

DOI: 10.1186/S13071-020-04500-9

Abstract: Sarcoptic mange causes significant animal welfare and occasional conservation concerns for bare-nosed wombats ( Vombatus ursinus ) throughout their range. To date, in situ chemotherapeutic interventions have involved macrocytic lactones, but their short duration of action and need for frequent re-administration has limited treatment success. Fluralaner (Bravecto® MSD Animal Health), a novel isoxazoline class ectoparasiticide, has several advantageous properties that may overcome such limitations. Fluralaner was administered topically at 25 mg/kg ( n = 5) and 85 mg/kg ( n = 2) to healthy captive bare-nosed wombats. Safety was assessed over 12 weeks by clinical observation and monitoring of haematological and biochemical parameters. Fluralaner plasma pharmacokinetics were quantified using ultra-performance liquid chromatography and tandem mass spectrometry. Efficacy was evaluated through clinical assessment of response to treatment, including mange and body condition scoring, for 15 weeks after topical administration of 25 mg/kg fluralaner to sarcoptic mange-affected wild bare-nosed wombats ( n = 3). Duration of action was determined through analysis of pharmacokinetic parameters and visual inspection of study subjects for ticks during the monitoring period. Methods for diluting fluralaner to enable ‘pour-on’ application were compared, and an economic and treatment effort analysis of fluralaner relative to moxidectin was undertaken. No deleterious health impacts were detected following fluralaner administration. Fluralaner was absorbed and remained quantifiable in plasma throughout the monitoring period. For the 25 mg/kg and 85 mg/kg treatment groups, the respective means for maximum recorded plasma concentrations (C max ) were 6.2 and 16.4 ng/ml for maximum recorded times to C max , 3.0 and 37.5 days and for plasma elimination half-lives, 40.1 and 166.5 days. Clinical resolution of sarcoptic mange was observed in all study animals within 3–4 weeks of treatment, and all wombats remained tick-free for 15 weeks. A suitable product for diluting fluralaner into a ‘pour-on’ was found. Treatment costs were competitive, and predicted treatment effort was substantially lower relative to moxidectin. Fluralaner appears to be a safe and efficacious treatment for sarcoptic mange in the bare-nosed wombat, with a single dose lasting over 1–3 months. It has economic and treatment-effort-related advantages over moxidectin, the most commonly used alternative. We recommend a dose of 25 mg/kg fluralaner and, based on the conservative assumption that at least 50% of a dose makes dermal contact, Bravecto Spot-On for Large Dogs as the most appropriate formulation for adult bare-nosed wombats.

The spectral underpinnings of pathogen spread on animal networks

Publisher: Cold Spring Harbor Laboratory

Date: 08-2022

DOI: 10.1101/2022.07.28.501936

Abstract: Predicting what factors promote or protect populations from infectious disease is a fundamental epidemiological challenge. Social networks, where nodes represent hosts and edges represent direct or indirect contacts between them, are important in quantifying these aspects of infectious disease dynamics. However, how network structure and epidemic parameters interact in empirical networks to promote or protect animal populations from infectious disease remains a challenge. Here we draw on advances in spectral graph theory and machine learning to build predictive models of pathogen spread on a large collection of empirical networks from across the animal kingdom. We show that the spectral features of an animal network are powerful predictors of pathogen spread for a variety of hosts and pathogens and can be a valuable proxy for the vulnerability of animal networks to pathogen spread. We validate our findings using interpretable machine learning techniques and provide a flexible web application for animal health practitioners to assess the vulnerability of a particular network to pathogen spread.

Towards sub-quadratic time and space complexity solutions for the dated tree reconciliation problem

Publisher: Springer Science and Business Media LLC

Date: 21-05-2016

DOI: 10.1186/S13015-016-0077-5

Fungal identification using a Bayesian classifier and the Warcup training set of internal transcribed spacer sequences

Publisher: Informa UK Limited

Date: 2016

DOI: 10.3852/14-293

Abstract: Fungi are key organisms in many ecological processes and communities. Rapid and low cost surveys of the fungal members of a community can be undertaken by isolating and sequencing a taxonomically informative genomic region, such as the ITS (internal transcribed spacer), from DNA extracted from a metagenomic s le, and then classifying these sequences to determine which organisms are present. This paper announces the availability of the Warcup ITS training set and shows how it can be used with the Ribosomal Database Project (RDP) Bayesian Classifier to rapidly and accurately identify fungi using ITS sequences. The classifications can be down to species level and use conventional literature-based mycological nomenclature and taxonomic assignments.

A Sub-quadratic Time and Space Complexity Solution for the Dated Tree Reconciliation Problem for Select Tree Topologies

Publisher: Springer Berlin Heidelberg

Date: 2015

DOI: 10.1007/978-3-662-48221-6_7

A time and space complexity reduction for coevolutionary analysis of trees generated under both a Yule and Uniform model

Publisher: Elsevier BV

Date: 08-2015

DOI: 10.1016/J.COMPBIOLCHEM.2015.02.003

Abstract: The topology or shape of evolutionary trees and their unbalanced nature has been a long standing area of interest in the field of phylogenetics. Coevolutionary analysis, which considers the evolutionary relationships between a pair of phylogenetic trees, has to date not considered leveraging this unbalanced nature as a means to reduce the complexity of coevolutionary analysis. In this work we apply previous analyses of tree shapes to improve the efficiency of inferring coevolutionary events. In particular, we use this prior research to derive a new data structure for inferring coevolutionary histories. Our new data structure is proven to provide a reduction in the time and space required to infer coevolutionary events. It is integrated into an existing framework for coevolutionary analysis and has been validated using both synthetic and previously published biological data sets. This proposed data structure performs twice as fast as algorithms implemented using existing data structures with no degradation in the algorithm's accuracy. As the coevolutionary data sets increase in size so too does the running time reduction provided by the newly proposed data structure. This is due to our data structure offering a logarithmic time and space complexity improvement. As a result, the proposed update to existing coevolutionary analysis algorithms outlined herein should enable the inference of larger coevolutionary systems in the future.

Draft Genome Sequence of Subantarctic Rhodococcus sp. Strain 1139

Publisher: American Society for Microbiology

Date: 06-04-2017

DOI: 10.1128/GENOMEA.00090-17

Abstract: The draft genome sequence of subantarctic Rhodococcus sp. strain 1139 is reported here. The genome size is 7.04 Mb with high G+C content (62.3%) and it contains a large number of genes involved in lipid synthesis. This lipid synthesis system is characteristic of oleaginous Actinobacteria , which are of interest for biofuel production.

Modelling nutrition across organizational levels: from individuals to superorganisms

Publisher: Elsevier BV

Date: 10-2014

DOI: 10.1016/J.JINSPHYS.2014.03.004

Abstract: The Geometric Framework for nutrition has been increasingly used to describe how in idual animals regulate their intake of multiple nutrients to maintain target physiological states maximizing growth and reproduction. However, only a few studies have considered the potential influences of the social context in which these nutritional decisions are made. Social insects, for instance, have evolved extreme levels of nutritional interdependence in which food collection, processing, storage and disposal are performed by different in iduals with different nutritional needs. These social interactions considerably complicate nutrition and raise the question of how nutrient regulation is achieved at multiple organizational levels, by in iduals and groups. Here, we explore the connections between in idual- and collective-level nutrition by developing a modelling framework integrating concepts of nutritional geometry into in idual-based models. Using this approach, we investigate how simple nutritional interactions between in iduals can mediate a range of emergent collective-level phenomena in social arthropods (insects and spiders) and provide ex les of novel and empirically testable predictions. We discuss how our approach could be expanded to a wider range of species and social systems.

Benchmarking Methods of Protein Structure Alignment

Publisher: Springer Science and Business Media LLC

Date: 28-07-2020

DOI: 10.1007/S00239-020-09960-2

Node Fingerprinting: An Efficient Heuristic for Aligning Biological Networks

Publisher: Mary Ann Liebert Inc

Date: 10-2014

DOI: 10.1089/CMB.2014.0114

Abstract: With the continuing increase in availability of biological data and improvements to biological models, biological network analysis has become a promising area of research. An emerging technique for the analysis of biological networks is through network alignment. Network alignment has been used to calculate genetic distance, similarities between regulatory structures, and the effect of external forces on gene expression, and to depict conditional activity of expression modules in cancer. Network alignment is algorithmically complex, and therefore we must rely on heuristics, ideally as efficient and accurate as possible. The majority of current techniques for network alignment rely on precomputed information, such as with protein sequence alignment, or on tunable network alignment parameters, which may introduce an increased computational overhead. Our presented algorithm, which we call Node Fingerprinting (NF), is appropriate for performing global pairwise network alignment without precomputation or tuning, can be fully parallelized, and is able to quickly compute an accurate alignment between two biological networks. It has performed as well as or better than existing algorithms on biological and simulated data, and with fewer computational resources. The algorithmic validation performed demonstrates the low computational resource requirements of NF.

How to test bioinformatics software?

Publisher: Springer Science and Business Media LLC

Date: 13-08-2015

DOI: 10.1007/S12551-015-0177-3

Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia

Publisher: Oxford University Press (OUP)

Date: 30-06-2017

DOI: 10.1093/BIB/BBX071

Simple, rapid and accurate genotyping-by-sequencing from aligned whole genomes with ArrayMaker

Publisher: Oxford University Press (OUP)

Date: 21-10-2014

DOI: 10.1093/BIOINFORMATICS/BTU691

Abstract: Summary: Whole-genome sequencing has revolutionized the study of genetics. Genotyping-by-sequencing is now a viable method of genotyping, yet the bioinformatics involved can be daunting if not prohibitive for some laboratories. Here we present ArrayMaker, a user-friendly tool that extracts accurate single nucleotide polymorphism genotypes at pre-defined loci from whole-genome alignments and presents them in a standard genotyping format compatible with association analysis software and datasets genotyped on commercial array platforms. Using this tool, geneticists with only basic computing ability can genotype s les at any desired list of markers, facilitating genome-wide association analysis, fine mapping, candidate variant assessment, data sharing and compatibility of data sourced from multiple technologies. Availability and implementation: ArrayMaker is licensed under The MIT License and can be freely obtained at w2014/ArrayMaker/. The program is implemented in Perl and runs on Linux operating systems. Supplementary information: Supplementary Data are available at Bioinformatics online. Contact: cali.willet@sydney.edu.au

Methods of analysing patterns of multimorbidity using network analysis: a scoping review.

Publisher: Springer Science and Business Media LLC

Date: 21-01-2023

DOI: 10.1007/S10389-021-01685-W

Mainstreaming microbes across biomes

Publisher: Oxford University Press (OUP)

Date: 17-06-2020

DOI: 10.1093/BIOSCI/BIAA057

Abstract: Bacteria, fungi, and other microorganisms in the environment (i.e., environmental microbiomes) provide vital ecosystem services and affect human health. Despite their importance, public awareness of environmental microbiomes has lagged behind that of human microbiomes. A key problem has been a scarcity of research demonstrating the microbial connections across environmental biomes (e.g., marine, soil) and between environmental and human microbiomes. We show in the present article, through analyses of almost 10,000 microbiome papers and three global data sets, that there are significant taxonomic similarities in microbial communities across biomes, but very little cross-biome research exists. This disconnect may be hindering advances in microbiome knowledge and translation. In this article, we highlight current and potential applications of environmental microbiome research and the benefits of an interdisciplinary, cross-biome approach. Microbiome scientists need to engage with each other, government, industry, and the public to ensure that research and applications proceed ethically, maximizing the potential benefits to society.

Optimising predictive modelling of Ross River virus using meteorological variables

Publisher: Public Library of Science (PLoS)

Date: 09-03-2021

DOI: 10.1371/JOURNAL.PNTD.0009252

Abstract: Statistical models are regularly used in the forecasting and surveillance of infectious diseases to guide public health. Variable selection assists in determining factors associated with disease transmission, however, often overlooked in this process is the evaluation and suitability of the statistical model used in forecasting disease transmission and outbreaks. Here we aim to evaluate several modelling methods to optimise predictive modelling of Ross River virus (RRV) disease notifications and outbreaks in epidemiological important regions of Victoria and Western Australia. We developed several statistical methods using meteorological and RRV surveillance data from July 2000 until June 2018 in Victoria and from July 1991 until June 2018 in Western Australia. Models were developed for 11 Local Government Areas (LGAs) in Victoria and seven LGAs in Western Australia. We found generalised additive models and generalised boosted regression models, and generalised additive models and negative binomial models to be the best fit models when predicting RRV outbreaks and notifications, respectively. No association was found with a model’s ability to predict RRV notifications in LGAs with greater RRV activity, or for outbreak predictions to have a higher accuracy in LGAs with greater RRV notifications. Moreover, we assessed the use of factor analysis to generate independent variables used in predictive modelling. In the majority of LGAs, this method did not result in better model predictive performance. We demonstrate that models which are developed and used for predicting disease notifications may not be suitable for predicting disease outbreaks, or vice versa . Furthermore, poor predictive performance in modelling disease transmissions may be the result of inappropriate model selection methods. Our findings provide approaches and methods to facilitate the selection of the best fit statistical model for predicting mosquito-borne disease notifications and outbreaks used for disease surveillance.

Australian spiny mountain crayfish and their temnocephalan ectosymbionts: an ancient association on the edge of coextinction?

Publisher: The Royal Society

Date: 25-05-2016

DOI: 10.1098/RSPB.2016.0585

Abstract: Australian spiny mountain crayfish ( Euastacu s, Parastacidae) and their ecotosymbiotic temnocephalan flatworms (Temnocephalida, Platyhelminthes) may have co-occurred and interacted through deep time, during a period of major environmental change. Therefore, reconstructing the history of their association is of evolutionary, ecological, and conservation significance. Here, time-calibrated Bayesian phylogenies of Euastacus species and their temnocephalans ( Temnohaswellia and Temnosewellia ) indicate near-synchronous ersifications from the Cretaceous. Statistically significant cophylogeny correlations between associated clades suggest linked evolutionary histories. However, there is a stronger signal of co ergence and greater host specificity in Temnosewellia , which co-occurs with Euastacus across its range. Phylogeography and analyses of evolutionary distinctiveness (ED) suggest that regional differences in the impact of climate warming and drying had major effects both on crayfish and associated temnocephalans. In particular, Euastacus and Temnosewellia show strong latitudinal gradients in ED and, conversely, in geographical range size, with the most distinctive, northern lineages facing the greatest risk of extinction. Therefore, environmental change has, in some cases, strengthened ecological and evolutionary associations, leaving host-specific temnocephalans vulnerable to coextinction with endangered hosts. Consequently, the extinction of all Euastacus species currently endangered (75%) predicts coextinction of approximately 60% of the studied temnocephalans, with greatest loss of the most evolutionarily distinctive lineages.

Active subnetwork recovery with a mechanism-dependent scoring function; with application to angiogenesis and organogenesis studies

Publisher: Springer Science and Business Media LLC

Date: 21-02-2013

DOI: 10.1186/1471-2105-14-59

An improved node mapping algorithm for the cophylogeny reconstruction problem

Publisher: Informa UK Limited

Date: 02-01-2014

DOI: 10.1080/23256214.2014.906070

Emerging phylogenetic structure of the SARS-CoV-2 pandemic

Publisher: Cold Spring Harbor Laboratory

Date: 19-05-2020

DOI: 10.1101/2020.05.19.103846

Abstract: Since spilling over into humans, SARS-CoV-2 has rapidly spread across the globe, accumulating significant genetic ersity. The structure of this genetic ersity, and whether it reveals epidemiological insights, are fundamental questions for understanding the evolutionary trajectory of this virus. Here we use a recently developed phylodynamic approach to uncover phylogenetic structures underlying the SARS-CoV-2 pandemic. We find support for three SARS-CoV-2 lineages co-circulating, each with significantly different demographic dynamics concordant with known epidemiological factors. For ex le, Lineage C emerged in Europe with a high growth rate in late February, just prior to the exponential increase in cases in several European countries. Mutations that characterize Lineage C in particular are non-synonymous and occur in functionally important gene regions responsible for viral replication and cell entry. Even though Lineages A and B had distinct demographic patterns, they were much more difficult to distinguish. Continuous application of phylogenetic approaches to track the evolutionary epidemiology of SARS-CoV-2 lineages will be increasingly important to validate the efficacy of control efforts and monitor significant evolutionary events in the future.

Verification of phylogenetic inference programs using metamorphic testing

Publisher: World Scientific Pub Co Pte Lt

Date: 12-2011

DOI: 10.1142/S021972001100563X

Abstract: Many phylogenetic inference programs are available to infer evolutionary relationships among taxa using aligned sequences of characters, typically DNA or amino acids. These programs are often used to infer the evolutionary history of species. However, in most cases it is impossible to systematically verify the correctness of the tree returned by these programs, as the correct evolutionary history is generally unknown and unknowable. In addition, it is nearly impossible to verify whether any non-trivial tree is correct in accordance to the specification of the often complicated search and scoring algorithms. This difficulty is known as the oracle problem of software testing: there is no oracle that we can use to verify the correctness of the returned tree. This makes it very challenging to test the correctness of any phylogenetic inference programs. Here, we demonstrate how to apply a simple software testing technique, called Metamorphic Testing, to alleviate the oracle problem in testing phylogenetic inference programs. We have used both real and randomly generated test inputs to evaluate the effectiveness of metamorphic testing, and found that metamorphic testing can detect failures effectively in faulty phylogenetic inference programs with both types of test inputs.

Adaptive collective foraging in groups with conflicting nutritional needs

Publisher: The Royal Society

Date: 04-2016

DOI: 10.1098/RSOS.150638

Abstract: Collective foraging, based on positive feedback and quorum responses, is believed to improve the foraging efficiency of animals. Nutritional models suggest that social information transfer increases the ability of foragers with closely aligned nutritional needs to find nutrients and maintain a balanced diet. However, whether or not collective foraging is adaptive in a heterogeneous group composed of in iduals with differing nutritional needs is virtually unexplored. Here we develop an evolutionary agent-based model using concepts of nutritional ecology to address this knowledge gap. Our aim was to evaluate how collective foraging, mediated by social retention on foods, can improve nutrient balancing in in iduals with different requirements. The model suggests that in groups where inter-in idual nutritional needs are unimodally distributed, high levels of collective foraging yield optimal in idual fitness by reducing search times that result from moving between nutritionally imbalanced foods. However, where nutritional needs are highly bimodal (e.g. where the requirements of males and females differ) collective foraging is selected against, leading to group fission. In this case, additional mechanisms such as assortative interactions can coevolve to allow collective foraging by subgroups of in iduals with aligned requirements. Our findings indicate that collective foraging is an efficient strategy for nutrient regulation in animals inhabiting complex nutritional environments and exhibiting a range of social forms.

Draft Genome Sequences of Two Novel Sub-Antarctic Williamsia Species

Publisher: American Society for Microbiology

Date: 12-10-2017

DOI: 10.1128/GENOMEA.01047-17

Abstract: Illumina MiSeq shotgun sequencing technology was used to sequence the genomes of two novel sub-Antarctic Williamsia species, designated strains 1135 and 1138. The estimated genome sizes for strains 1135 and 1138 are 5.99 Mb and 6.08 Mb, respectively. This genome sequence information will aid in understanding the lipid metabolic pathways of cold-tolerant Williamsia species.

Mining autograding data in computer science education

Publisher: ACM

Date: 02-2016

DOI: 10.1145/2843043.2843070

Hunting alters viral transmission and evolution in a large carnivore

Publisher: Springer Science and Business Media LLC

Date: 27-01-2022

DOI: 10.1038/S41559-021-01635-5

Abstract: Hunting can fundamentally alter wildlife population dynamics but the consequences of hunting on pathogen transmission and evolution remain poorly understood. Here, we present a study that leverages a unique landscape-scale quasi-experiment coupled with pathogen-transmission tracing, network simulation and phylodynamics to provide insights into how hunting shapes feline immunodeficiency virus (FIV) dynamics in puma (Puma concolor). We show that removing hunting pressure enhances the role of males in transmission, increases the viral population growth rate and increases the role of evolutionary forces on the pathogen compared to when hunting was reinstated. Changes in transmission observed with the removal of hunting could be linked to short-term social changes while the male puma population increased. These findings are supported through comparison with a region with stable hunting management over the same time period. This study shows that routine wildlife management can have impacts on pathogen transmission and evolution not previously considered.

University Of Tasmania

Location: Australia

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Linkage Projects - Grant ID: LP140100075

Start Date: 04-2015

End Date: 12-2019

Amount: $410,933.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP180101251

Start Date: 05-2020

End Date: 12-2023

Amount: $178,117.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP0667266

Start Date: 03-2006

End Date: 09-2008

Amount: $366,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP1094891

Start Date: 07-2010

End Date: 12-2013

Amount: $290,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP190102020

Start Date: 05-2019

End Date: 09-2024

Amount: $397,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP0770991

Start Date: 03-2007

End Date: 10-2010

Amount: $263,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP220102976

Start Date: 2022

End Date: 12-2024

Amount: $380,124.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP0985137

Start Date: 05-2009

End Date: 10-2013

Amount: $390,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP150101253

Start Date: 02-2015

End Date: 02-2018

Amount: $469,800.00

Funder: Australian Research Council