Ben Woodcroft
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Ben Woodcroft

Centre for Microbiome Research, School of Biomedical Sciences, Queensland University of Technology (QUT), Translational Research Institute

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 September 2017 in Nature Microbiology
Verified
Journal Article
Open access
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DPDonovan H. Parks
Donovan H. Parks
CRChristian Rinke
Christian Rinke
MCMaria Chuvochina
Maria Chuvochina
PCPierre-Alain Chaumeil
Pierre-Alain Chaumeil
BWBen J. Woodcroft
Ben J. Woodcroft
GTGene W. Tyson
Gene W. Tyson
Challenges in cultivating microorganisms have limited the phylogenetic diversity of currently available microbial genomes. This is being addressed by advances in sequencing throughput and computational techniques that allow for the cultivation-independent recovery of genomes from metagenomes. Here, we report the reconstruction of 7,903 bacterial and archaeal genomes from >1,500 public metagenomes. All genomes are estimated to be ≥50% complete and nearly half are ≥90% complete with ≤5% contamination. These genomes increase the phylogenetic diversity of bacterial and archaeal genome trees by >30% and provide the first representatives of 17 bacterial and three archaeal candidate phyla. We also recovered 245 genomes from the Patescibacteria superphylum (also known as the Candidate Phyla Radiation) and find that the relative diversity of this group varies substantially with different protein marker sets. The scale and quality of this data set demonstrate that recovering genomes from metagenomes provides an expedient path forward to exploring microbial dark matter.

27 July 2023 in Nature Methods
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Journal Article
Closed access
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ACAlex Chklovski
Alex Chklovski
DPDonovan H. Parks
Donovan H. Parks
BWBen J. Woodcroft
Ben J. Woodcroft
GTGene W. Tyson
Gene W. Tyson

5 August 2010 in Nature
Verified
Journal Article
Open access
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MSMansi Srivastava
Mansi Srivastava
OSOleg Simakov
Oleg Simakov
JCJarrod Chapman
Jarrod Chapman
BFBryony Fahey
Bryony Fahey
MGMarie-Emilie Anais Gauthier
Marie-Emilie Anais Gauthier
DRDaniel S. Rokhsar
Daniel S. Rokhsar
Sponges are an ancient group of animals that diverged from other metazoans over 600 million years ago. Here we present the draft genome sequence of Amphimedon queenslandica, a demosponge from the Great Barrier Reef, and show that it is remarkably similar to other animal genomes in content, structure and organization. Comparative analysis enabled by the sequencing of the sponge genome reveals genomic events linked to the origin and early evolution of animals, including the appearance, expansion and diversification of pan-metazoan transcription factor, signalling pathway and structural genes. This diverse ‘toolkit’ of genes correlates with critical aspects of all metazoan body plans, and comprises cell cycle control and growth, development, somatic- and germ-cell specification, cell adhesion, innate immunity and allorecognition. Notably, many of the genes associated with the emergence of animals are also implicated in cancer, which arises from defects in basic processes associated with metazoan multicellularity.

1 October 2008 in Nature
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Journal Article
Closed access
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AGAndrew Grimson
Andrew Grimson
MSMansi Srivastava
Mansi Srivastava
BFBryony Fahey
Bryony Fahey
BWBen J. Woodcroft
Ben J. Woodcroft
HCH. Rosaria Chiang
H. Rosaria Chiang
DBDavid P. Bartel
David P. Bartel

29 March 2025 in Bioinformatics
Verified
Journal Article
Open access
SASamuel T N Aroney
Samuel T N Aroney
RNRhys J P Newell
Rhys J P Newell
JNJakob N Nissen
Jakob N Nissen
ACAntonio Pedro Camargo
Antonio Pedro Camargo
GTGene W Tyson
Gene W Tyson
BWBen J Woodcroft
Ben J Woodcroft
Summary: Genome-centric analysis of metagenomic samples is a powerful method for understanding the function of microbial communities. Calculating read coverage is a central part of analysis, enabling differential coverage binning for recovery of genomes and estimation of microbial community composition. Coverage is determined by processing read alignments to reference sequences of either contigs or genomes. Per-reference coverage is typically calculated in an ad-hoc manner, with each software package providing its own implementation and specific definition of coverage. Here we present a unified software package CoverM which calculates several coverage statistics for contigs and genomes in an ergonomic and flexible manner. It uses “Mosdepth arrays” for computational efficiency and avoids unnecessary I/O overhead by calculating coverage statistics from streamed read alignment results. Availability and implementation: CoverM is free software available at https://github.com/wwood/coverm. CoverM is implemented in Rust, with Python (https://github.com/apcamargo/pycoverm) and Julia (https://github.com/JuliaBinaryWrappers/CoverM_jll.jl) interfaces.

16 July 2018 in Nature Microbiology
Verified
Journal Article
Open access
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JEJoanne B. Emerson
Joanne B. Emerson
SRSimon Roux
Simon Roux
JBJennifer R. Brum
Jennifer R. Brum
BBBenjamin Bolduc
Benjamin Bolduc
BWBen J. Woodcroft
Ben J. Woodcroft
MSMatthew B Sullivan
Matthew B Sullivan
Climate change threatens to release abundant carbon that is sequestered at high latitudes, but the constraints on microbial metabolisms that mediate the release of methane and carbon dioxide are poorly understood1–7. The role of viruses, which are known to affect microbial dynamics, metabolism and biogeochemistry in the oceans8–10, remains largely unexplored in soil. Here, we aimed to investigate how viruses influence microbial ecology and carbon metabolism in peatland soils along a permafrost thaw gradient in Sweden. We recovered 1,907 viral populations (genomes and large genome fragments) from 197 bulk soil and size-fractionated metagenomes, 58% of which were detected in metatranscriptomes and presumed to be active. In silico predictions linked 35% of the viruses to microbial host populations, highlighting likely viral predators of key carbon-cycling microorganisms, including methanogens and methanotrophs. Lineage-specific virus/host ratios varied, suggesting that viral infection dynamics may differentially impact microbial responses to a changing climate. Virus-encoded glycoside hydrolases, including an endomannanase with confirmed functional activity, indicated that viruses influence complex carbon degradation and that viral abundances were significant predictors of methane dynamics. These findings suggest that viruses may impact ecosystem function in climate-critical, terrestrial habitats and identify multiple potential viral contributions to soil carbon cycling.