Biology subjects

Brandt, M. I.

Publications and source records attributed to Brandt, M. I..

3 recordsLinked to original sources

bioRxiv2026

Taxonomic vs. Functional Diversity for the Impact Assessment of Offshore Oil & Gas Activities: An Exploratory Study on Benthic Prokaryotes

Improving environmental management in the offshore Oil & Gas sector requires approaches that capture the ecosystem services (ES) provided by marine sediments, particularly their roles in carbon and nutrient cycling. Microbial communities are central to these processes, and molecular tools offer new opportunities to assess their functional diversity. To explore how different sequencing approaches inform environmental impact assessment, we compared taxonomic and functional prediction based on 16S metabarcoding, shotgun metagenomics and messenger RNA-based metatranscriptomics, targeting prokaryotic communities. Our aims were to evaluate the ability of each approach to detect impact and to determine how well they captured functions relevant to ES. All approaches revealed clear differences in community composition between impacted and non-impacted sediments at both taxonomic and functional levels, with impact significantly associated with hydrocarbon and barium content. Functional inventories showed substantial overlap across the three approaches, and 48-55 ES-related processes were detectable in all datasets. While metagenomics provided the strongest statistical discrimination between impact groups, metatranscriptomics resolved the actively expressed pathways underpinning ES, yielding the most biologically meaningful functional profiles despite its lower statistical power. All approaches indicated that Oil & Gas activity drives shift towards anaerobic, hydrocarbon-degrading, and sulfur-respiring microbial communities, with hydrocarbon degradation, sulfur cycling, and metal detoxification being the dominant ES processes in impacted sediments. Metabarcoding was confirmed as a cost-effective option for impact assessment when focused on taxonomic composition. However, functional prediction from metabarcoding data proved less reliable, as several ES showed contrasting associations to impact category between metabarcoding and shotgun sequencing approaches.

microbiology↗

bioRxiv2019

An assessment of environmental metabarcoding protocols aiming at favouring contemporary biodiversity in inventories of deep-sea communities

O_LIThe abyssal seafloor covers more than 50% of planet Earth and is a large reservoir of still mostly undescribed biodiversity. It is increasingly under target of resource-extraction industries although being drastically understudied. In such remote and hard-to-access ecosystems, environmental DNA (eDNA) metabarcoding is a useful and efficient tool for studying biodiversity and implementing environmental impact assessments. Yet, eDNA analysis outcomes may be biased towards describing past rather than present communities as sediments contain both contemporary and ancient DNA. C_LIO_LIUsing commercially available kits, we investigated the impacts of five molecular processing methods on DNA metabarcoding biodiversity inventories targeting prokaryotes (16S-V4V5), unicellular eukaryotes (18S-V4), and metazoans (18S-V1, COI). As the size distribution of ancient DNA is skewed towards small fragments, we evaluated the effect of removing short DNA fragments via size-selection and ethanol reconcentration using DNA extracted from 10 g of sediment at five deep-sea sites. We also compare communities revealed by DNA and RNA co-extracted from 2 g of sediment at the same sites. C_LIO_LIResults show that removing short DNA fragments does not affect alpha and beta diversity estimates in any of the biological compartments investigated. Results also confirm doubts regarding the possibility to better describe live communities using environmental RNA (eRNA). With ribosomal loci, RNA, while resolving similar spatial patterns than co-extracted DNA, resulted in significantly higher richness estimates, supporting hypotheses of increased persistence of ribosomal RNA (rRNA) in the environment and unmeasured bias due to over-abundance of rRNA and RNA release. With the mitochondrial locus, RNA detected lower metazoan richness and resolved less spatial patterns than co-extracted DNA, reflecting high messenger RNA lability. Results also highlight the importance of using large amounts of sediment ([≥]10 g) for accurately surveying eukaryotic diversity. C_LIO_LIWe conclude that DNA should be favoured over RNA for logistically realistic, repeatable, and reliable surveys, and confirm that large sediment samples ([≥]10 g) deliver more complete and accurate assessments of benthic eukaryotic biodiversity and that increasing the number of biological rather than technical replicates is important to infer robust ecological patterns. C_LI

genomics↗

bioRxiv2019

A flexible pipeline combining bioinformatic correction tools for prokaryotic and eukaryotic metabarcoding

Environmental metabarcoding is an increasingly popular tool for studying biodiversity in marine and terrestrial biomes. With sequencing costs decreasing, multiple-marker metabarcoding, spanning several branches of the tree of life, is becoming more accessible. However, bioinformatic approaches need to adjust to the diversity of taxonomic compartments targeted as well as to each barcode gene specificities. We built and tested a pipeline based on Illumina read correction with DADA2 allowing analyzing metabarcoding data from prokaryotic (16S) and eukaryotic (18S, COI) life compartments. We implemented the option to cluster Amplicon Sequence Variants (ASVs) into Operational Taxonomic Units (OTUs) with swarm v2, a network-based clustering algorithm, and to further curate the ASVs/OTUs based on sequence similarity and co-occurrence rates using a recently developed algorithm, LULU. Finally, flexible taxonomic assignment was implemented via Ribosomal Database Project (RDP) Bayesian classifier and BLAST. We validate this pipeline with ribosomal and mitochondrial markers using eukaryotic mock communities and 42 deep-sea sediment samples. The results show that ASVs, reflecting genetic diversity, may not be appropriate for alpha diversity estimation of organisms fitting the biological species concept. The results underline the advantages of clustering and LULU-curation for producing more reliable metazoan biodiversity inventories, and show that LULU is an effective tool for filtering metazoan molecular clusters, although the minimum identity threshold applied to co-occurring OTUs has to be increased for 18S. The comparison of BLAST and the RDP Classifier underlined the potential of the latter to deliver very good assignments, but highlighted the need for a concerted effort to build comprehensive, ecosystem-specific, databases adapted to the studied communities.

bioinformatics↗