Biology subjects

Meglecz, E.

Publications and source records attributed to Meglecz, E..

5 recordsLinked to original sources

bioRxiv2025

Separating faces in ARMS metabarcoding improves marine biodiversity monitoring: a comparison across protocols, experimental designs, and photographic surveys

Monitoring marine biodiversity requires approaches that capture its full complexity through space and time. DNA metabarcoding coupled with Autonomous Reef Monitoring Structures (ARMS) is increasingly used for this purpose, yet most applications still pool all sessile fractions and rarely benchmark molecular ouputs against photographic observations. Here, we combined photographic analysis with cytochrome c oxidase I (COI) metabarcoding across ten north-western Mediterranean sites to test, compare, and refine ARMS-based monitoring protocols. We first optimized laboratory procedures (DNA extraction and polymerase choice) and applied the control-driven, replicate-aware VTAM pipeline to minimize false positives and ensure full traceability. We then conducted the first face-by-face comparison of - and {beta}-diversity between imaging and eDNA in which each individual ARMS face was metabarcoded separately rather than pooled. Metabarcoding detected [~]15x higher site-level richness and revealed stronger correlations with geographic distance and environmental gradients, whereas photography provided complementary information on macro-taxa and surface cover. For metabarcoding, processing each face separately yielded much higher richness and markedly stronger {beta}-diversity-distance correlations than with the NOAA pooling protocol, demonstrating that pooling inflates sampling variance resulting in a loss of the ecological signal. Grouping faces into five structural categories offered a more operational alternative while further increasing -diversity and strengthening {beta}-diversity correlations. Overall, our results show that retaining ARMS microhabitat structure is critical for maximizing metabarcoding performance. Using five structural sessile fractions per ARMS combined with a control-driven bioinformatic workflow provides a reproducible, scalable framework for long-term eDNA monitoring and early detection of biodiversity change.

ecology↗

bioRxiv2022

COInr and mkCOInr: Building and customizing a non-redundant barcoding reference database from BOLD and NCBI using a lightweight pipeline.

The taxonomic assignment of metabarcoding data strongly depends on the taxonomic coverage of the reference database. Therefore, it is fundamental to access and pool data from the two major sources of COI sequences, the BOLD and the NCBI nucleotide databases, and enrich them with custom COI data, when available. The COInr database is a freely available, easy-to-access database of COI reference sequences extracted from the BOLD and NCBI nucleotide databases. It is a comprehensive database: not limited to a taxon, a gene region, or a taxonomic resolution; therefore, it is a good starting point for creating custom databases. Sequences are dereplicated between databases and within taxa. Each taxon has a unique taxonomic Identifier (taxID), fundamental to avoid ambiguous associations of homonyms and synonyms in the source database. TaxIDs form a coherent hierarchical system fully compatible with the NCBI taxIDs allowing to create their full or ranked linages. The mkCOInr tool is a series of Perl scripts necessary to download sequences from BOLD and NCBI, build the COInr database and customize it according to the users needs. It is possible to select or eliminate sequences for a list of taxa, select a specific gene region, select for minimum taxonomic resolution, add new custom sequences, and format the database for BLAST, QIIME, RDP classifier. The COInr database can be downloaded from https://doi.org/10.5281/zenodo.6555985 and mkCOInr and the full documentation is available at https://github.com/meglecz/mkCOInr.

bioinformatics↗

bioRxiv2021

Are marine biodiversity hotspots still blackspots for barcoding?

Marine biodiversity underpins ecosystem health and societal well-being. Preservation of biodiversity hotspots is a global challenge. Molecular tools, like DNA barcoding and metabarcoding, hold great potential for biodiversity monitoring, possibly outperforming more traditional taxonomic methods. However, metabarcoding-based biodiversity assessments are limited by the availability of sequences in barcoding reference databases; a lack thereof results in high percentages of unassigned sequences. In this study we (i) present the current status of known vs. barcoded marine species at a global scale based on online taxonomic and genetic databases; and (ii) compare the current status with data from ten years ago. Then we analyzed occurrence data of marine animal species from five Large Marine Ecosystems (LMEs) classified as biodiversity hotspots, to identify any consistent disparities in COI barcoding coverage between geographic regions and at phylum level. Barcoding coverage varied among LMEs (from 36.8% to 62.4% COI-barcoded species) and phyla (from 4.8% to 74.7% COI-barcoded species), with Porifera, Bryozoa and Platyhelminthes being highly underrepresented, compared to Chordata, Arthropoda and Mollusca. We demonstrate that although barcoded marine species increased from 9.5% to 14.2% since the last assessment in 2011, about 15,000 (corresponding to 7.8% increase) new species were described from 2011 to 2021. The next ten years will thus be crucial to enroll concrete collaborative measures and long term initiatives (e.g., Horizon 2030, Ocean Decade) to populate barcoding libraries for the marine realm.

ecology↗

bioRxiv2021

DNA metabarcoding reveals adaptive seasonal variation of individual trophic traits in a critically endangered fish

Dietary studies are critical for understanding foraging strategies and have important applications in conservation and habitat management. We applied a robust metabarcoding protocol to characterize the diet of the critically endangered freshwater fish Zingel asper and conducted modelling and simulation analyses to characterize and identify some of the drivers of individual trophic trait variation in this species. We found that intra-specific competition and ontogeny had minor effects on the trophic niche of Z. asper. Instead, our results suggest that the majority of trophic niche variation was driven by seasonal variation in ecological opportunity (in our case, the seasonal variation in the availability of preferred prey types). Overall, our results are in line with the optimal foraging theory and suggest that Z. asper is specialized on a few ephemeropteran prey species (Baetis fuscatus and Ecdyonurus) but adapts its foraging by becoming more opportunistic as its favoured prey seasonally decline. Despite the now widespread usage of metabarcoding, very few studies have attempted to study inter- and intra-populational individual trophic traits variation with metabarcoding data. This study illustrates how metabarcoding data obtained from feces can be combined with modelling and simulation approaches to test hypotheses in the conventional analytic framework of trophic analysis.

ecology↗

bioRxiv2020

VTAM: A robust pipeline for validating metabarcoding data using internal controls

O_LIMetabarcoding studies should be carefully designed to minimize false positives and false negative occurrences. The use of internal controls, replicates, and several overlapping markers is expected to improve the bioinformatics data analysis. C_LIO_LIVTAM is a tool to perform all steps of data curation from raw fastq data to taxonomically assigned ASV (Amplicon Sequence Variant or simply variant) table. It addresses all known technical error types and includes other features rarely present in existing pipelines for validating metabarcoding data: Filtering parameters are obtained from internal control samples; cross-sample contamination and tag-jump are controlled; technical replicates are used to ensure repeatability; it handles data obtained from several overlapping markers. C_LIO_LITwo datasets were analysed by VTAM and the results were compared to those obtained with a pipeline based on DADA2. The false positive occurrences in samples were considerably higher when curated by DADA2, which is likely due to the lack of control for tag-jump and cross-sample contamination. C_LIO_LIVTAM is a robust tool to validate metabarcoding data and improve traceability, reproducibility, and comparability between runs and datasets. C_LI

ecology↗