Biology subjects

Bahram, M.

Publications and source records attributed to Bahram, M..

6 recordsLinked to original sources

bioRxiv2025

Functional diversity of soil microbial communities increases with ecosystem development

Land abandonment is the single largest process of land-use change in the Global North driving succession and afforestation at continental scales, but assessing its impacts on soil microbial communities remains a challenge. Here, we established a nationwide successional gradient of paired grassland and forest sites to track developments in microbial structure and functioning following land abandonment and gradually changing plant communities. We show that microbes generally respond through threshold dynamics, leading to increasing functional but decreasing taxonomic diversity. Succession also increased the specialization of microbial nutrient (C-N-P) cycling genes while decreasing genetic redundancy, highlighting a putative trade-off between two desirable ecosystem properties: functional diversity and functional redundancy. Increasing fungal functional diversity underpinned higher microbial C-cycling capacity, underscoring the causal link between functional traits and ecosystem processes. Changing litter quality similarly provided a mechanistic link between plant and microbial communities despite otherwise largely decoupled successional developments. Land abandonment is frequently touted as an opportunity to increase biodiversity and carbon storage. Our results show that deeper knowledge about the multifaceted development of soil microbial communities and its links to plant communities during succession may be needed to fully grasp the impacts of global land abandonment processes.

ecology↗

bioRxiv2023

Soil health is linked to primary productivity across Europe

A healthy soil is at the core of sustainable management and policy, but its importance for plant productivity across environmental gradients and land-use types remains poorly understood. To address this gap, we conducted a pan-European field study including 588 sites from 27 countries to investigate the link between soil health and primary productivity across three major land-use types: woodlands, grasslands, and croplands. We found that mean soil health (a composite index based on soil properties, biodiversity, and plant disease control) in woodlands was 31.4% higher than in grasslands, and 76.1% higher than in croplands. Soil health was positively linked to cropland and grassland productivity at the continental scale. Woodland productivity was best explained by climate. Among microbial diversity indicators, we observed a positive association between the richness of Acidobacteria, Firmicutes, and Proteobacteria and primary productivity. Among microbial functional groups, we found that nitrogen-fixing bacteria and mycorrhizal fungi positively related to primary productivity in croplands and grasslands, while plant pathogens showed a negative relationship. Together, our results point to the importance of soil biodiversity and soil health for maintaining primary productivity across contrasting land-use types.

ecology↗

bioRxiv2023

Improved taxonomic annotation of Archaea communities using LotuS2, the Genome Taxonomy Database and RNAseq data

Metabarcoding is increasingly used to uncover diversity and characterise communities of Archaea In various habitats, but taxonomic annotation of their sequences remains more challenging than for bacteria. Fewer reference sequences are available; widely used databases do not reflect recent revisions of higher level archaeal taxonomy and a substantial fraction of their phylogenetic diversity remains to be fully characterised. We address these gaps with a systematic and tractable approach based around the Genome Taxonomy Database (GTDB). GTDB provides a standardized taxonomy with normalized ranks based on protein coding genes, allowing us to identify and remove incongruent SSU sequences. We then use this in combination with the eukaryote PR2 database to annotate a collection of near full length rRNA sequences and the Archaea SSU sequences in SILVA, creating a new reference database, KSGP (Karst, Silva, GTDB and PR2). GTDB SSUs alone provides a small improvement in annotation of an example marine Archaea OTU data set over standardized SSU databases such as SILVA and Greengenes2, while KSGP increases Class and Order assignments by 145% and 280% respectively and is likely to provide some improvement in annotation of bacterial sequences too. We make the KSGP database and a cleaned and deduplicated subset of GTDB SSU sequences available at ksgp.earlham.ac.uk; integrate them into a metabarcoding pipeline, LotuS2 and outline rapid and robust strategies to generate a set of annotated Archaea OTUs and to determine the proportion of Archaea sequences in metatranscriptomic data. We also demonstrate simple tools to visualise the completeness of database coverage and outline strategies to further understand poorly characterised components of the archaeal community which will be equally applicable to bacteria.

microbiology↗

bioRxiv2022

Towards understanding diversity, endemicity and global change vulnerability of soil fungi

Fungi play pivotal roles in ecosystem functioning, but little is known about their global patterns of diversity, endemicity, vulnerability to global change drivers and conservation priority areas. We applied the high-resolution PacBio sequencing technique to identify fungi based on a long DNA marker that revealed a high proportion of hitherto unknown fungal taxa. We used a Global Soil Mycobiome consortium dataset to test relative performance of various sequencing depth standardization methods (calculation of residuals, exclusion of singletons, traditional and SRS rarefaction, use of Shannon index of diversity) to find optimal protocols for statistical analyses. Altogether, we used six global surveys to infer these patterns for soil-inhabiting fungi and their functional groups. We found that residuals of log-transformed richness (including singletons) against log-transformed sequencing depth yields significantly better model estimates compared with most other standardization methods. With respect to global patterns, fungal functional groups differed in the patterns of diversity, endemicity and vulnerability to main global change predictors. Unlike -diversity, endemicity and global-change vulnerability of fungi and most functional groups were greatest in the tropics. Fungi are vulnerable mostly to drought, heat, and land cover change. Fungal conservation areas of highest priority include wetlands and moist tropical ecosystems.

ecology↗

bioRxiv2021

LotuS2: An ultrafast and highly accurate tool for amplicon sequencing analysis

BackgroundAmplicon sequencing is an established and cost-efficient method for profiling microbiomes. However, many available tools to process this data require both bioinformatics skills and high computational power to process big datasets. Furthermore, there are only few tools that allow for long read amplicon data analysis. To bridge this gap, we developed the LotuS2 (Less OTU Scripts 2) pipeline, enabling user-friendly, resource friendly, and versatile analysis of raw amplicon sequences. ResultsIn LotuS2, six different sequence clustering algorithms as well as extensive pre- and post-processing options allow for flexible data analysis by both experts, where parameters can be fully adjusted, and novices, where defaults are provided for different scenarios. We benchmarked three independent gut and soil datasets, where LotuS2 was on average 29 times faster compared to other pipelines - yet could better reproduce the alpha- and beta-diversity of technical replicate samples. Further benchmarking a mock community with known taxa composition showed that, compared to the other pipelines, LotuS2 recovered a higher fraction of correctly identified genera and species (98% and 57%, respectively). At ASV/OTU level, precision and F-score were highest for LotuS2, as was the fraction of correctly reconstructed 16S sequences. ConclusionLotuS2 is a lightweight and user-friendly pipeline that is fast, precise and streamlined. High data usage rates and reliability enable high-throughput microbiome analysis in minutes. AvailabilityLotuS2 is available from GitHub, conda or via a Galaxy web interface, documented at http://lotus2.earlham.ac.uk/.

bioinformatics↗

bioRxiv2019

Relative performance of Oxford Nanopore MinION vs. Pacific Biosciences Sequel third-generation sequencing platforms in identification of agricultural and forest pathogens

Culture-based molecular characterization methods have revolutionized detection of pathogens, yet these methods are either slow or imprecise. The second-generation sequencing tools have much improved precision and sensitivity of detection, but the analysis processes are costly and take several days. Of third-generation techniques, the portable Oxford Nanopore MinION device has received much attention because of its small size and possibility of rapid analysis at reasonable cost. Here, we compare the relative performance of two third-generation sequencing instruments, MinION and Pacific Biosciences Sequel in identification and diagnostics of pathogens from conifer needles and potato leaves and tubers. We demonstrate that Sequel is efficient in metabarcoding of complex samples, whereas MinION is not suited for this purpose due to the high error rate and multiple biases. However, we find that MinION can be utilized for rapid and accurate identification of dominant pathogenic organisms from plant tissues following both amplicon-based and metagenomics-based approaches. Using the PCR-free approach with shortened extraction and incubation times, we performed the entire MinION workflow from sample preparation through DNA extraction, sequencing, bioinformatics and interpretation in two and half hours. We advocate the use of MinION for rapid diagnostics of pathogens, but care needs to be taken to control or account for all potential technical biases.\n\nIMPORTANCEWe develop new and rapid protocols for MinION-based third-generation diagnostics of plant pathogens that greatly improves the speed and precision of diagnostics. Due to high error rate and technical biases in MinION, PacBio Sequel platform is more useful for amplicon-based metabarcoding from complex biological samples.

microbiology↗