Biology subjects

Weilguny, L.

Publications and source records attributed to Weilguny, L..

6 recordsLinked to original sources

bioRxiv2026

A metagenomic framework for rapid Listeria monocytogenes surveillance in food production environments

Listeria monocytogenes remains a major foodborne pathogen with high mortality and costly persistence in food-processing environments. Established diagnostics rely on selective enrichment and single-colony isolation, which could introduce strong biases by favouring fast-growing strains or those more tolerant to enrichment broth inhibitors, while suppressing slow-growing, viable-but-nonculturable, and other co-occurring strains. This can obscure true pathogen diversity and may contribute to discrepancies between strains detected in food production environments and those associated with disease. To quantify the bias introduced by established culture-based diagnostics and to assess the potential advantage of metagenomics-based pathogen detection directly from the original sample matrix, we developed and evaluated a rapid nanopore sequencing-based metagenomic framework. We designed an artificial metagenomic community of several Listeria strains, comprising L. monocytogenes lineages I-III (including hypervirulent, persistent, and low-virulence strains), other Listeria spp., and a realistic background microbiome representative of food-processing environments. We then used this mock community to spike standard surveillance sponges and compared three workflows: (i) direct nanopore metagenomic sequencing of the original sample matrix, (ii) quasi-metagenomic sequencing after 4 h, 12 h, 24 h, or 48 h of selective enrichment, and (iii) ISO-based culture followed by whole-genome sequencing of a single presumptive L. monocytogenes isolate. We found that the culture-based approach recovered only a limited subset of strains, consistently underrepresenting diversity and failing to detect multi-strain contamination. These findings were reflected by the quasi-metagenomic results, where we found relative L. monocytogenes enrichment to be strain-dependent, indicating selective enrichment bias favouring specific strains. Metagenomics captured the full spectrum of spiked Listeria strains, enabling comprehensive strain-level resolution at all inoculation levels. We only observed relative enrichment of the L. monocytogenes strains by quasi-metagenomics compared with metagenomics after 48 h of selective enrichment. While driven primarily by the additional enrichment of L. innocua, these results suggest that quasi-metagenomics improves L. monocytogenes recovery only at the cost of a substantial reduction in speed. We finally showed that the sensitivity and accuracy of metagenomics could be improved by utilising different environmental sampling materials. We did not find any significant performance improvements from nanopore sequencing-based enrichment of L. monocytogenes through adaptive sampling approaches. We conclude that integrating long-read metagenomics into routine surveillance shows great promise to improve detection and source attribution in food safety systems.

microbiology↗

bioRxiv2024

Soil carbon in the world's tidal marshes

Tidal marshes are threatened coastal ecosystems known for their capacity to store large amounts of carbon in their water-logged soils. Accurate quantification and mapping of global tidal marshes soil organic carbon (SOC) stocks is of considerable value to conservation efforts. Here, we used training data from 3,710 unique locations, landscape-level environmental drivers and a newly developed global tidal marsh extent map to produce the first global, spatially-explicit map of SOC storage in tidal marshes at 30 m resolution. We estimate the total global SOC stock to 1 m to be 1.44 Pg C, with a third of this value stored in the United States of America. On average, SOC in tidal marshes 0-30 and 30-100 cm soil layers are estimated at 83.1 Mg C ha-1 (average predicted error 44.8 Mg C ha-1) and 185.3 Mg C ha-1 (average predicted error 105.7 Mg C ha-1), respectively. Our spatially-explicit model is able to capture 59% of the variability in SOC density, with elevation being the strongest driver aside from soil depth. Our study reveals regions with high prediction uncertainty and therefore highlights the need for more targeted sampling to fully capture SOC spatial variability.

ecology↗

bioRxiv2021

phastSim: efficient simulation of sequence evolution for pandemic-scale datasets

Sequence simulators are fundamental tools in bioinformatics, as they allow us to test data processing and inference tools, as well as being part of some inference methods. The ongoing surge in available sequence data is however testing the limits of our bioinformatics software. One example is the large number of SARS-CoV-2 genomes available, which are beyond the processing power of many methods, and simulating such large datasets is also proving difficult. Here we present a new algorithm and software for efficiently simulating sequence evolution along extremely large trees (e.g. < 100, 000 tips) when the branches of the tree are short, as is typical in genomic epidemiology. Our algorithm is based on the Gillespie approach, and implements an efficient multi-layered search tree structure that provides high computational efficiency by taking advantage of the fact that only a small proportion of the genome is likely to mutate at each branch of the considered phylogeny. Our open source software is available from https://github.com/NicolaDM/phastSim and allows easy integration with other Python packages as well as a variety of evolutionary models, including indel models and new hypermutatability models that we developed to more realistically represent SARS-CoV-2 genome evolution. Author summaryOne of the most influential responses to the SARS-CoV-2 pandemic has been the widespread adoption of genome sequencing to keep track of viral spread and evolution. This has resulted in vast availability of genomic sequence data, that, while extremely useful and promising, is also increasingly hard to store and process efficiently. An important task in the processing of this genetic data is simulation, that is, recreating potential histories of past and future virus evolution, to benchmark data analysis methods and make statistical inference. Here, we address the problem of efficiently simulating large numbers of closely related genomes, similar to those sequenced during SARS-CoV-2 pandemic, or indeed to most scenarios in genomic epidemiology. We develop a new algorithm to perform this task, that provides not only computational efficiency, but also extreme flexibility in terms of possible evolutionary models, allowing variation in mutation rates, non-stationary evolution, and indels; all phenomena that play an important role in SARS-CoV-2 evolution, as well as many other real-life epidemiological scenarios.

bioinformatics↗

bioRxiv2020

Sea anemone genomes reveal ancestral metazoan chromosomal macrosynteny

Draft genome sequences of non-bilaterian species have provided important insights into the evolution of the metazoan gene repertoire. However, there is little information about the evolution of gene clusters, genome architectures and karyotypes during animal evolution. In this regard, slowly evolving anthozoan Cnidaria, the sister group of Bilateria, are particularly informative. Here we report chromosome-level genome assemblies of two related cnidarians, the sea anemones Nematostella vectensis and Scolanthus callimorphus. We find a robust set of 15 chromosomes with a clear one-to-one correspondence between the two species. Both sea anemone genomes show remarkable chromosomal conservation with other cnidarians, several bilaterians and the sponge Ephydatia muelleri, allowing us to reconstruct ancestral cnidarian and metazoan chromosomal blocks, consisting of at least 19 and 16 ancestral linkage groups, respectively. We show that, in contrast to Bilateria, the Hox and NK clusters of investigated cnidarians are largely disintegrated, despite the presence of staggered hox/gbx expression in Nematostella. This loss of microsynteny conservation may be facilitated by shorter distances between cis-regulatory sequences and their cognate transcriptional start sites. In line with that, we find no clear evidence for topologically associated domains, suggesting fundamental differences in long-range gene regulation compared to vertebrates. These data suggest that large sets of ancestral metazoan genes have been retained in ancestral linkage groups of some extant lineages, yet, higher order gene regulation with associated 3D architecture may have evolved only after the cnidarian-bilaterian split.

genomics↗

bioRxiv2019

Reconstructing the invasion route of DNA transposons using extant population samples

Reconstructing invasion routes of transposable elements (TEs), so far, required capturing an ongoing invasion with population samples from different geographic regions and time points. Here, we propose a more accessible approach. Abundantly occurring internal deletions of DNA transposons allow to trace the direction as well as the path of an invasion, even hundreds of generations after the spread of a TE. We validated this hypothesis with computer simulations and by accurately reproducing the route of the P-element invasion in Drosophila melanogaster. Finally, we used our method to shed light on the controversial hobo invasion in D. melanogaster. Our approach solely requires sequenced samples from extant populations and sequences of TEs of interest. Hence, DNA transposons in a wide range of model and non-model organisms may be analyzed. Our approach will further our understanding of TE dynamics, migration patterns, and the ecology of species.

evolutionary biology↗

bioRxiv2017

Video rate volumetric Ca2+ imaging across cortical layersusing Seeded Iterative Demixing (SID) microscopy

Light-field microscopy (LFM) is a scalable approach for volumetric Ca2+ imaging with the highest volumetric acquisition rates (up to 100 Hz). While this has enabled high-speed whole-brain Ca2+ imaging in small semi-transparent specimen, tissue scattering has limited its application in the rodent brain. Here we introduce Seeded Iterative Demixing (SID), a computational source extraction technique that extends LFM to the scattering mammalian cortex. Using GCaMP-expressing mice we demonstrate SIDs ability to capture neuronal dynamics in vivo within a volume of 900x900x260m located as deep as 380 m in the mouse cortex and hippocampus at 30 Hz volume rate while faithfully discriminating signals from neurons as close as 20 m, at three orders of magnitude reduced computational cost. The simplicity and scalability of LFM, coupled with the performance of SID opens up a range of new applications including closed-loop experiments and is expected to propel its wide dissemination within the neuroscience community.

neuroscience↗