Biology subjects

Hall, M.

Publications and source records attributed to Hall, M..

7 recordsLinked to original sources

bioRxiv2018

Pollinator size and its consequences: Predictive allometry for pollinating insects

O_LIBody size is an integral functional trait that underlies pollination-related ecological processes, yet it is often impractical to measure directly. Allometric scaling laws have been used to overcome this problem. However, most existing models rely upon small sample sizes, geographically restricted sampling and have limited applicability for non-bee taxa. Predictive allometric models that consider biogeography, phylogenetic relatedness and intraspecific variation are urgently required to ensure greater accuracy.\nC_LIO_LIHere, we measured body size, as dry weight, and intertegular distance (ITD) of 391 bee species (4035 specimens) and 103 hoverfly species (399 specimens) across four biogeographic regions: Australia, Europe, North America and South America. We updated existing models within a Bayesian mixed-model framework to test the power of ITD to predict interspecific variation in pollinator dry weight in interaction with different co-variates: phylogeny or taxonomy, sexual dimorphism and biogeographic region. In addition, we used ordinary least squares (OLS) regression to assess intraspecific dry weight - ITD relationships for 10 bee and five hoverfly species.\nC_LIO_LIIncluding co-variates led to more robust interspecific body size predictions for both bees (Bayesian R2: 0.946; {Delta}R2 0.047) and hoverflies (Bayesian R2: 0.821; {Delta}R2 0.058) relative to models with ITD alone. In contrast, at the intraspecific level, our results demonstrate that ITD is an inconsistent predictor of body size for bees (R2: 0.02 - 0.66) and hoverflies (R2: -0.11 - 0.44).\nC_LIO_LITherefore, predictive allometry is more suitable for interspecific comparative analyses than assessing intraspecific variation. Collectively, these models form the basis of the dynamic R package, pollimetry, which provides a comprehensive resource for allometric research concerning insect pollinators worldwide.\nC_LI

ecology↗

bioRxiv2018

A comprehensive genomics solution for HIV surveillance and clinical monitoring in a global health setting

High-throughput viral genetic sequencing is needed to monitor the spread of drug resistance, direct optimal antiretroviral regimes, and to identify transmission dynamics in generalised HIV epidemics. Public health efforts to sequence HIV genomes at scale face three major technical challenges: (i) minimising assay cost and protocol complexity, (ii) maximising sensitivity, and (iii) recovering accurate and unbiased sequences of both the genome consensus and the within-host viral diversity. Here we present a novel, high-throughput, virus-enriched sequencing method and computational pipeline tailored specifically to HIV (veSEQ-HIV), which addresses all three technical challenges, and can be used directly on leftover blood drawn for routine CD4 testing. We demonstrate its performance on 1,620 plasma samples collected from consenting individuals attending 10 large urban clinics in Zambia, partners of HPTN 071 (PopART). We show that veSEQ-HIV consistently recovers complete HIV genomes from the majority of samples of different subtypes, and is also quantitative: the number of HIV reads per sample obtained by veSEQ-HIV estimates viral load without the need for additional testing. Both quantitativity and sensitivity were assessed on a subset of 126 samples with clinically measured viral loads, and with standardized quantification controls (VL 100 - 5,000,000 RNA copies/ml). Complete HIV genomes were recovered from 93% (85/91) of samples when viral load was over 1,000 copies per ml. The quantitative nature of the assay implies that variant frequencies estimated with veSEQ-HIV are representative of true variant frequencies in the sample. Detection of minority variants can be exploited for epidemiological analysis of transmission and drug resistance, and we show how the information contained in individual reads of a veSEQ-HIV sample can be used to detect linkage between multiple mutations associated with resistance to antiretroviral therapy. Less than 2% of reads obtained by veSEQ-HIV were identified as in silico contamination events using updates to the phyloscanner software (phyloscanner clean) that we show to be 95% sensitive and 99% specific at decontaminating NGS data. The cost of the assay -- approximately 45 USD per sample -- compares favourably with existing VL and HIV genotyping tests, and provides the additional value of viral load quantification and inference of drug resistance with a single test. veSEQ-HIV is well suited to large public health efforts and is being applied to all [~]9000 samples collected for the HPTN 071-2 (PopART Phylogenetics) study.

genomics↗

bioRxiv2018

Enhancement of Transgene Expression by NF-Y and CTCF

If a transgene is effectively delivered to a cell, its expression may still be limited by epigenetic mechanisms that silence the transgene. Indeed, once the transgene reaches the nucleus, it may be bound by histone proteins and condensed into heterochromatin or associated with repressor proteins that block transcription. In this study, we sought to enhance transgene expression by adding binding motifs for several different epigenetic enzymes either upstream or downstream of two promoters (CMV and EF1). Screening these plasmids revealed that luciferase expression was enhanced 10-fold by the addition of a CCAAT box just upstream of the EF1 promoter to recruit nuclear transcription factor Y (NF-Y), while inserting a CCCTC-binding factor (CTCF) motif downstream of the EF1 promoter enhanced expression 14-fold (14.03 {+/-} 6.54). ChIP assays confirmed that NF-Y and CTCF bound to the motifs that were added to each plasmid, but the presence of NF-Y and CTCF did not significantly affect the levels of histone acetylation (H3K9ac). Overall, these result show that transgene expression from the EF1 promoter can be significantly increased with motifs that recruit NF-Y or CTCF.

bioengineering↗

bioRxiv2018

Host sexual dimorphism affects the outcome of within-host pathogen competition

Natural infections often consist multiple pathogens of the same or different species. In multiple infections, pathogens compete for access to host resources and fitness is determined by how well a pathogen can reproduce compared to its competitors. Given the propensity for males and females to exhibit variation in pathogen-induced reduction in lifespan or fecundity, we explore how host sex may modulate the competitive ability of pathogens, potentially favouring the transmission of different pathogen genotypes. Using the Daphnia magna - Pasteuria ramosa model system, we exposed male and female hosts to either a single genotype infection or coinfections consisting of two pathogen genotypes of varying levels of virulence, measured as pathogen-induced reduction in host lifespan. We found that co-infections within females generally favoured the transmission of the more virulent pathogen genotype. Conversely, co-infections within male hosts resulted in equal transmission of competing genotypes, or favoured the transmission of the less virulent pathogen genotype in treatments where it established prior to the more virulent competitor. These results suggest that sex is a form of host heterogeneity which may influence the evolution of virulence within co-infection contexts and that one sex may be a reservoir for pathogen genetic diversity in nature.

evolutionary biology↗

bioRxiv2017

Copy-number signatures and mutational processes in ovarian carcinoma

Tumours with profound copy-number aberration elude molecular stratification due to their genomic complexity. By representing this complexity as a mixture of copy-number signatures, we provide molecular explanations for differing clinical outcomes. Here we present a method for copy-number signature identification, deriving eight signatures in 117 shallow whole-genome sequenced high-grade serous ovarian cancers (HGSOC), which validated on independent cohorts of 95 deep whole-genome sequenced, and 402 SNP array-profiled cases. Three copy-number signatures predicted longer overall survival, while the others predicted poorer outcome. We found evidence for the mutational processes giving rise to copy-number change for six of the eight signatures via correlations with other genomic features. Our results provide insights into the pathogenesis of HGSOC by uncovering multiple mutational processes that shape genomes following TP53 mutation. Importantly, our work shows that most HGSOC have a mixture of mutational processes suggesting that targeting a single mutator phenotype may be therapeutically suboptimal.

cancer biology↗

bioRxiv2017

PHYLOSCANNER: Analysing Within- and Between-Host Pathogen Genetic Diversity to Identify Transmission, Multiple Infection, Recombination and Contamination

A central feature of pathogen genomics is that different infectious particles (virions, bacterial cells, etc.) within an infected individual may be genetically distinct, with patterns of relatedness amongst infectious particles being the result of both within-host evolution and transmission from one host to the next. Here we present a new software tool, phyloscanner, which analyses pathogen diversity from multiple infected hosts. phyloscanner provides unprecedented resolution into the transmission process, allowing inference of the direction of transmission from sequence data alone. Multiply infected individuals are also identified, as they harbour subpopulations of infectious particles that are not connected by within-host evolution, except where recombinant types emerge. Low-level contamination is flagged and removed. We illustrate phyloscanner on both viral and bacterial pathogens, namely HIV-1 sequenced on Illumina and Roche 454 platforms, HCV sequenced with the Oxford Nanopore MinION platform, and Streptococcus pneumoniae with sequences from multiple colonies per individual. phyloscanner is available from https://github.com/BDI-pathogens/phyloscanner.

evolutionary biology↗

bioRxiv2016

Easy and Accurate Reconstruction of Whole HIV Genomes from Short-Read Sequence Data

Next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of rapid between- and within-host evolution may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by effectively aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to preprocess reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We use shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read data produced with the Illumina platform, for 65 existing publicly available samples and 50 new samples. We show the systematic superiority of mapping to shivers constructed reference over mapping the same reads to the standard reference HXB2: an average of 29 bases per sample are called differently, of which 98.5% are supported by higher coverage. We also provide a practical guide to working with imperfect contigs.

bioinformatics↗