Biology subjects

Greenfield, P.

Publications and source records attributed to Greenfield, P..

3 recordsLinked to original sources

bioRxiv2023

Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity

Arthropods contribute importantly to ecosystem functioning but remain understudied. This undermines the validity of conservation decisions. Modern methods are now making arthropods easier to study, since arthropods can be mass-trapped, mass-identified, and semi-mass-quantified into many-row (observation), many-column (species) datasets, with homogeneous error, high resolution, and copious environmental-covariate information. These novel community datasets let us efficiently generate information on arthropod species distributions, conservation values, uncertainty, and the magnitude and direction of human impacts. We use a DNA-based method (barcode mapping) to produce an arthropod-community dataset from 121 Malaise-trap samples, and combine it with 29 remote-imagery layers within a joint species distribution model. With this approach, we generate distribution maps for 76 arthro-pod species across a 225 km2 temperate-zone forested landscape. We combine the maps to visualise the fine-scale spatial distributions of species richness, community composition, and site irreplaceability. Old-growth forests show distinct community composition and higher species richness, and stream courses have the highest site-irreplaceability values. With this sideways biodiversity modelling method, we demonstrate the feasibility of biodiversity mapping at sufficient spatial resolution to inform local management choices, while also being efficient enough to scale up to thousands of square kilometres.

ecology↗

bioRxiv2023

Krumholzibacteriota and Deltaproteobacteria contain rare genetic potential to liberate carbon from monoaromatic compounds in subsurface coal seams

Biogenic methane in subsurface coal seam environments is produced by diverse consortia of microbes. Although this methane is useful for global energy security, it remains unclear which microbes can liberate carbon from the coal. Most of this carbon is relatively resistant to biodegradation, as it is contained within aromatic rings. Thus, to explore for coal-degrading taxa in the subsurface, this study used coal seam metagenomes to reconstruct important metagenome-assembled genomes (MAGs) using a key genomic marker for the anaerobic degradation of monoaromatic compounds as a guide: the benzoyl-CoA reductase gene (bcrABCD). Three taxa were identified with this genetic potential. The first was a novel taxon from the Krumholzibacteriota phylum, which this study is the first to describe. This Krumholzibacteriota sp. contained a full set of genes for benzoyl-CoA dearomatisation, in addition to other genes for anaerobic catabolism of monoaromatics. Analysis of Krumholzibacteriota MAGs from other environments revealed that this genetic potential may be common within this phylum, and thus they may be important organisms for the liberation of recalcitrant carbon on a global scale. Further, two taxa from the Deltaproteobacteria class were also implicated in monoaromatic degradation; two geographically unrelated Syntrophorhabdus aromaticivorans MAGs, and a Syntrophaceae sp. MAG. Each of these three taxa are potential rate-limiting organisms for subsurface coal-to-methane biodegradation. Their description here provides an understanding of their function within the coal seam microbiome, and will help inform future efforts in coal bed methane stimulation, anoxic bioremediation of organic pollutants, and assessments of anoxic carbon cycling and emissions. ImportanceSubsurface coal seams are highly anoxic and oligotrophic environments, where the main source of carbon is "locked away" within aromatic rings. Despite these challenges, biogenic methane accumulates within many of these coal seams, which implies that the coal seam microbiome can "unlock" this carbon source in situ. For over two decades, researchers have been working to understand which organisms are responsible for these processes. This study provides the first descriptions of these organisms. Here, we report metagenomic insights into the liberation of carbon from aromatic molecules typically found within coal, the degradation pathways involved, and descriptions of the Krumholzibacteriota sp., Syntrophorhabdus aromaticivorans, and Syntrophaceae sp. that contain this genetic potential. Additionally, this is the first time that the Krumholzibacteriota phylum has been implicated in anaerobic dearomatisation of aromatic hydrocarbons. This potential is identified here in numerous taxa within the phylum from other subsurface environments, implicating Krumholzibacteriota in global-scale carbon-cycling processes.

microbiology↗

bioRxiv2017

K-mer Similarity, Networks Of Microbial Genomes And Taxonomic Rank

Alignment-free (AF) methods have recently been adopted to infer phylogenetic trees. However, the evolutionary relationships among microbes, impacted by common phenomena such as lateral genetic transfer and rearrangement, cannot be adequately captured in a strictly tree-like structure. Bacterial and archaeal genomes consist of highly conserved regions, e.g. ribosomal RNA genes (commonly used as phylogenetic markers), more-variable regions and extrachromosomal elements, i.e. plasmids (that contain genes critical under a selective condition e.g. antibiotic resistance). The impact of these elements on genome-scale inference of microbial phylogeny remains little known. Here, using an AF approach, we inferred phylogenomic networks of microbial life based on 2785 completely sequenced bacterial and archaeal genomes, and systematically assessed the impact of ribosomal RNA genes and plasmid sequences in this network. Our results indicate that k-mer similarity can correlate with taxonomic rank of microbes. Using a relational database approach, we linked the implicated k-mers to annotated genomic regions (thus functions), and defined core functions in specific phyletic groups and genera. We found that, in most phyla, highly conserved functions are often related to Amino acid metabolism and transport, and Energy production and conversion. Our findings indicate that AF phylogenomics can be used to infer reticulate relationships in a scalable manner and provide new perspective into microbial biology and evolution.

evolutionary biology↗