Biology subjects

Goodall, T.

Publications and source records attributed to Goodall, T..

12 recordsLinked to original sources

bioRxiv2026

Environmental drivers of soil virus diversity across UK habitats

Soil viruses are critical members of the soil microbiome, shaping terrestrial ecosystem processes and microbial dynamics. However, the environmental factors governing their landscape-scale biogeography remain poorly characterised. Here, we analysed bulk soil metagenomic data from the UKCEH Countryside Survey across broad habitat classes to identify the key drivers of viral diversity and community assembly in UK soils. We show that soil pH is the primary predictor of both viral species richness and overall community composition, alongside significant contributions from the co-related soil organic matter and broad habitat type. Viral species diversity exhibited a strongly non-linear relationship with pH, peaking in neutral to slightly acidic soils. Viral community dissimilarity strongly correlated with 16S rRNA bacterial community structure across all taxonomic ranks, with the strongest association at ASV-level resolution. Despite high spatial turnover among viral contigs, and significant habitat-specific enrichment of particular anti-phage defence systems, viral lifestyle proxies like integrase gene frequencies showed no habitat-specific variation. Together, our results demonstrate that UK soil viral communities are primarily structured by soil pH and habitat parameters and closely coupled to patterns of bacterial host distribution, providing a baseline for future investigations and monitoring of change.

microbiology↗

bioRxiv2026

Soil microenvironment and microbial community composition jointly regulate carbon accrual in agricultural soils

Much of the persistent soil organic carbon (SOC) pool is microbial in origin: microorganisms process plant carbon into biomass and their necromass can associate with mineral surfaces, contributing to long-term carbon persistence. This has generated interest in microbial interventions such as inoculation to restore carbon in degraded croplands, yet their efficacy remains uncertain. The uncertainty reflects a more fundamental, unresolved question: are microbially-mediated carbon transformations governed principally by the composition of the microbial community or by the soil microenvironment? To disentangle these drivers, we conducted a reciprocal microbial community transplant experiment, introducing communities of contrasting origin from locally adjacent grassland and cropland soils into sterilised grassland and cropland soils, and incubating them for eight months with regular organic inputs. This design decouples the inoculum from the microenvironment, allowing their individual and interactive contributions to be quantified. Fungal assembly was influenced more by the inoculum, consistent with dispersal limitation, whereas bacterial assembly was governed more by the microenvironment, consistent with environmental selection. Despite receiving the same organic carbon inputs, grassland and cropland recipient soils showed distinct SOC trajectories, indicating that the soil microenvironment strongly constrained net carbon retention. Within this constraint, community composition also mattered: introducing grassland rather than cropland communities increased fungal diversity and fungal necromass and led to better SOC outcomes, expressed as net gain or reduced loss. These results show that SOC accrual emerges from interactions between the soil microenvironment and microbial community composition, with fungal community assembly particularly associated with necromass accumulation and carbon retention. They highlight the need to consider both soil conditions and microbial community composition when developing strategies to enhance SOC accrual.

ecology↗

bioRxiv2026

Taxonomic filtering accompanies functional expansion during long-term soil restoration

The restoration of species-rich calcareous grasslands is a critical conservation objective, yet the recovery of the invisible below-ground microbiome remains poorly quantified compared to above-ground vegetation. Using a unique 143-year land-use chronosequence on Salisbury Plain, UK, we investigated the trajectory of ecosystem reassembly across arable, regenerating (23 and 67 years), and ancient grasslands. By integrating vegetation surveys with soil physiochemistry, microbial profiling, and shotgun metagenomics, we identified a profound functional decoupling between floral and edaphic recovery. While vegetation diversity recovered relatively rapidly, approaching saturation within 23-67 years, soil properties exhibited persistent legacy effects and slow convergence. Bacterial richness decreased with restoration age, reflecting a transition from disturbance-adapted copiotrophs in arable soils to a specialised, oligotrophic community in ancient sites. This taxonomic contraction was conversely matched by an expansion in functional potential, driven by the emergence of specific taxa (e.g., Microthrixaceae, Aquihabitans sp.) and metabolic pathways associated with complex carbon cycling and stress tolerance. Crucially, the soil ecosystem did not reach equilibrium even after 67 years, characterised by persistent legacy phosphorus and a slow accumulation of soil organic matter. These findings suggest that passive regeneration alone may be insufficient for full soil functional recovery, and that strategies targeting microbial assembly and long-term carbon dynamics warrant further evaluation.

ecology↗

bioRxiv2025

High-quality metagenome assembly from nanopore reads with nanoMDBG

Third-generation long-read sequencing technologies, have been shown to significantly enhance the quality of metagenome assemblies. The results obtained using the highly accurate reads generated by PacBio HiFi have been particularly notable yielding hundreds of circularized, complete genomes as metagenome-assembled genomes (MAGs) without manual intervention. Oxford Nanopore Technologies (ONT) has recently improved the accuracy of its sequencing reads, achieving a per-base error rate of approximately 1-2%. Given the high-throughput, convenience and low-cost of ONT sequencing this could accelerate the uptake of long read metagenomics. However, current metagenome assemblers are optimized for PacBio HiFi data and underperform on the latest ONT data and do not scale to the large data sets that it enables. We present nanoMDBG, an evolution of the metaMDBG HiFi assembler, designed to support newer ONT sequencing data through a novel pre-processing step that performs fast and accurate error correction in minimizer-space. Across a range of ONT datasets, including a large 400 Gbp soil sample sequenced specifically for this study, nanoMDBG reconstructs up to twice as many high-quality MAGs as the next best ONT assembler, metaFlye, while requiring a third of the CPU time and memory. As a result of these advances, we show that the latest ONT technology can now produce results comparable to those obtained using PacBio HiFi sequencing at the same sequencing depth.

bioinformatics↗

bioRxiv2024

Land use effects on soil microbiome composition and traits with consequences for its ecosystem carbon use efficiency

The soil microbiome determines the fate of belowground inputs of plant fixed carbon. The shifts in soil properties caused by changes in land use leads to modifications in microbiome structure and function, resulting in either loss or gain of soil organic carbon (SOC). Soil pH is the primary factor regulating microbiome characteristics leading to distinct pathways of microbial carbon cycling, but the underlying mechanisms remain understudied. Here, the taxa-trait relationships behind the variable fate of SOC were investigated across two temperate paired land use intensity contrasts with differing soil pH using metaproteomics, metabarcoding and a 13C labelled litter decomposition experiment. 13C incorporation into microbial biomass increased with land use intensification in low pH soils but decreased in high pH soils, impacting ecosystem carbon use efficiency (CUE) in opposing directions. Reduction in biosynthesis traits across land use intensity contrasts was due to increased abundance of proteins linked to resource acquisition and stress tolerance. These community-level trait trade-offs were underpinned by land use intensification-induced changes in dominant taxa with distinct traits. These trait changes alter the balance of decomposition and stabilisation of carbon in soil through divergent pH-controlled pathways. In low pH soils, land use intensification alleviates microbial abiotic stress resulting in increased CUE but promotes decomposition and SOC loss. In contrast, in high pH soils, land use intensification increases microbial physiological constraints and decreases CUE, leading to reduced necromass build-up and SOC stabilisation. We demonstrate how microbial CUE can be decoupled from SOC highlighting the need for its careful consideration in predicting or managing SOC storage for soil health and climate change mitigation.

ecology↗

bioRxiv2022

Soil bacterial and fungal communities show within field heterogeneity that varies by land management and distance metric

Increasing interest in the use of microbial metrics to evaluate soil health raises the issue of how fine-scale heterogeneity can affect microbial community measurements. Here we analyse bacterial and fungal communities of over 100 soil samples across 17 pasture farms and evaluate beta diversity at different scales. We find large variation in microbial communities between different points in the same field, and if Aitchison distance is used we find that within-field variation is as high as between-farm variation. However, if Bray-Curtis or Jaccard distance are used this variation is partially explained by differences in soil pH and vegetation and is higher under mob grazing for fungi. Hence, field scale variation in microbial communities can impact the evaluation of soil health.

ecology↗

bioRxiv2022

High-resolution characterisation of short-term temporal variability in the taxonomic and resistome composition of wastewater influent

Wastewater-based epidemiology (WBE) for population-level surveillance of antimicrobial resistance (AMR) is gaining significant traction, but the impact of wastewater sampling methods on results is unclear. In this study we characterised taxonomic and resistome differences between single-timepoint-grab and 24H-composites of wastewater influent from a large UK-based wastewater treatment work (WWTW [population equivalent:223,435]). We autosampled hourly influent grab samples (n=72) over three consecutive weekdays, and prepared additional 24H-composites (n=3) from respective grabs. For taxonomic profiling, metagenomic DNA was extracted from all samples and 16S-rRNA gene sequenced. One composite and six grabs from day one underwent metagenomic sequencing for metagenomic dissimilarity estimation and resistome profiling. Taxonomic abundances of phyla varied significantly across hourly grab samples but followed a repeating diurnal pattern for all three days. Hierarchical clustering grouped grab samples into four time periods dissimilar in both 16S rRNA gene-based profiles and metagenomic distances. 24H-composites resembled mean daily phyla abundances and showed low variability of taxonomic profiles. Of the 122 AMR gene families (AGFs) identified across all day one samples, single grab samples identified a median of 6 (IQR:5-8) AGFs not seen in the composite. However, 36/36 of these hits were at lateral coverage <0.5 (median:0.19; IQR:0.16-0.22) and potential false positives. Conversely, the 24H-composite identified three AGFs not seen in any grab with higher lateral coverage (0.82; 0.55-0.84). Additionally, several clinically significant human AGFs (blaVIM, blaIMP, blaKPC) were intermittently or completely missed by grab sampling but captured by the 24H-composite. Wastewater influent undergoes significant taxonomic and resistome changes on short timescales potentially affecting interpretation of results based on sampling strategy. Grab samples are more convenient and potentially capture low-prevalence/transient targets but are less comprehensive and temporally variable. Therefore, we recommend 24H-composite sampling where feasible. Further validation and optimisation of WBE methods is vital for its development into a robust AMR surveillance approach. HighlightsO_LIInfluent undergoes significant taxonomic/resistome changes over short timescales. C_LIO_LITaxonomic abundances fluctuate diurnally but repeat for the 3 weekdays sampled. C_LIO_LIDetection of less prevalent AMR determinants is time-dependent for grab sampling. C_LIO_LISingle timepoint grab samples may produce temporally variable metagenomic profiles. C_LIO_LI24H-composites reflect mean daily taxa and more reliably captured AMR determinants. C_LI

genomics↗

bioRxiv2022

Evaluation of metagenomic, 16S rRNA gene and ultra-plexed PCR-based sequencing approaches for profiling antimicrobial resistance gene and bacterial taxonomic composition of polymicrobial samples

BackgroundShotgun metagenomic sequencing is increasingly popular in taxonomic and resistome-profiling of polymicrobial samples due to its agnostic nature and data versatility. However, caveats include high- cost, sequencing depth/sensitivity trade-offs, and challenging bioinformatic deconvolution. Targeted PCR-based profiling optimises sensitivity and cost-effectiveness, but can only identify prespecified targets and may introduce amplification biases. Ultra-high multiplexed PCR is a potential compromise. As no comprehensive comparative evaluation exists, we evaluated performance of each method in taxonomic/resistome-profiling of a well-defined DNA mock sample and seven "real- world" wastewater samples. ResultsWe tested three sequencing approaches (short-read shotgun metagenomics, Illumina Ampliseq ultra-plexed AMR Research Panel, 16S rRNA gene sequencing) with seven bioinformatic pipelines (ResPipe, Illumina DNA Amplicon App, One Codex Metagenomic-/Targeted Loci classification and Ampliseq Report, DADA2, and an in-house pipeline for AmpliSeq data [AmpliSeek]). Metagenomics outperformed 16S rRNA gene sequencing in accurately reconstituting a mock taxonomic profile and optimising the identification of diverse wastewater taxa, while 16S rRNA gene sequencing produced more even taxonomic outputs which may be quantitatively inaccurate but enhance detection of low abundance taxa. Shotgun metagenomic and AmpliSeq sequencing performed equally well in profiling AMR genes present in a mock sample, but AmpliSeq identified more genes in more complex, "real-world" samples, likely related to sensitivity of detection at the metagenomic sequencing depth used. ConclusionsA complementary sequencing approach employing 16S rRNA gene or shallow-metagenomic sequencing for taxonomic profiling, and the AmpliSeq AMR panel for high-resolution resistome profiling represents a potential lower-cost alternative to deep shotgun sequencing and may also be more sensitive for the detection of low-prevalence AMR genes. However, our evaluation highlights that both the sequencing and bioinformatics approach used can significantly influence results; for AmpliSeq AMR gene profiling, we developed AmpliSeek which outperformed the other pipelines tested and is open source. Sequencing approach and bioinformatic pipeline should be considered in the context of study goals and sample type, with study-specific validation when feasible.

genomics↗

bioRxiv2021

Pasture age impacts soil fungal composition while bacteria respond to soil chemistry

Pasture is a globally important managed habitat providing both food and income. The way in which it is managed leads to a wide range of impacts on soil microbial communities and associated soil health. While there have been several studies comparing pasture farming to other forms of land use, we still have limited understanding of how the soil microbial communities vary between pasture farms and according to management practices. Here we present the results of a field survey across 56 UK livestock farms that are managed by members of the Pasture fed Livestock Association, using amplicon sequencing of the 16S and ITS regions to characterise the soil bacterial and fungal community within fields that have been under pasture for differing durations. We show that grazing management intensity has only limited effects upon microbial community structure, while the duration of pasture since ploughing (ranging from 1 year to over 100 years) impacted the fungal community structure. The impact of management duration was conditional upon soil physicochemical properties, particularly pH. Plant community effects on upon soil bacterial and fungal composition appear to also interact with the soil chemistry, highlighting the importance of plant-soil interactions in determining microbial community structure. Analyses of microbial indicators revealed proportionally more fungal taxa that responded to multiple ecosystem health associated properties than bacterial taxa. We also identified several fungal taxa that both acted as indicators of soil health related properties within our dataset and showed differentiation between grassland types in a national survey, indicating the generality of some fungal indicators to the national level. Members of the Agaricomycetes were associated with multiple indicators of soil health. Our results show the importance of maintaining grassland for the development of plant-soil interactions and microbial community structure with concomitant effects on soil and general ecosystem health. HighlightsO_LISoil bacteria and fungi from >50 pastures were analysed using DNA metabarcoding C_LIO_LIDuration of pasture since ploughing impacted fungal community composition C_LIO_LIBacteria were more associated with soil physicochemical properties than fungi C_LIO_LIPlant effects on soil microbes were through interactions with soil chemistry C_LIO_LIMicrobial indicators of soil health were disproportionately fungal taxa C_LI

ecology↗

bioRxiv2020

The effect of plant-derived carbon on rhizospheric microbial communities decomposing different litter types and nutrient return

Interactions between plants and microorganisms strongly affect ecosystem functioning as processes of plant productivity, litter decomposition and nutrient cycling are controlled by both organisms. Though two-sided interactions between plants and microorganisms and between microorganisms and litter decomposition are areas of major scientific research, our understanding of the three-sided interactions of plant-derived carbon flow into the soil microbial community and their follow-on effects on ecosystem processes like litter decomposition and plant nutrient uptake remains limited. Therefore, we performed a greenhouse experiment with two plant communities differing in their ability to associate with arbuscular mycorrhizal fungi (AMF). By applying a 13CO2 pulse label to the plant communities and adding various 15N labelled substrate types to ingrowth cores, we simultaneously traced the flow of plant-derived carbon into soil microbial communities and the return of mineralized nitrogen back to the plant communities. We observed that net 13C assimilation by the rhizosphere microbial communities and their community composition not only depended on plant-AMF association but also type of substrate being decomposed. AMF-association resulted in lower net 13C investment into the decomposer community than absence of the association for similar 15N uptake. This effect was driven by a reduced carbon flow to fungal and bacterial saprotrophs and a simultaneous increase of carbon flow to AMF. Additionally, in presence of AMF association CN flux also depended on the type of substrate being decomposed. Lower net 13C assimilation was observed for decomposition of plant-derived and microorganism-derived substrates whereas opposite was true for inorganic nitrogen. Interestingly, the decomposer communities assembled in the rhizosphere were structured by both the plant community and substrate amendments which suggests existence of functional overlap between the two soil contexts. Moreover, we present preliminary evidence that AMF association helps plants access nutrients that are locked in bacterial and plant necromass at a lower carbon cost. Therefore, we conclude that a better understanding of ecosystem processes like decomposition can only be achieved when the whole plant-microorganism-litter context is investigated.

microbiology↗

bioRxiv2019

Beyond taxonomic identification: integration of ecological responses to a soil bacterial 16S rRNA gene database.

High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalising syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterise taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth "CS") to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from the survey metadata. Specifically, we modelled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on putative landscape scale pH-abundance responses. We identify that most of the soil OTUs examined exhibit predictable abundance responses across soil pH gradients, though with the exception of known acidophilic lineages, the pH optima of OTU relative abundance was variable and could not be generalised by broad taxonomy. This highlights the need for tools and databases to predict ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER), and as a DADA2 database for use in bioinformatics pipelines. The further development of advanced informatics infrastructures incorporating modelled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.

microbiology↗

bioRxiv2018

Soil microbial communities with greater investment in resource acquisition have lower growth yield

Resource acquisition and growth yield are fundamental traits of microorganisms that have consequences for ecosystem functioning. However, there is a lack of empirical observations linking these traits. Using a landscape-scale survey of temperate near-neutral pH soils, we show tradeoffs in key community-level parameters linked to these traits. Increased investment into extracellular enzymes was associated with reduced growth yield; this reduction was linked more to carbon than nitrogen acquisition enzymes suggesting smaller stoichiometric constraints on community metabolism in examined soils.

ecology↗