Biology subjects

Vogel, T. M.

Publications and source records attributed to Vogel, T. M..

5 recordsLinked to original sources

bioRxiv2025

Adding layers of information to scRNA-seq data using pre-trained language models

Pre-trained language models promise to enrich single-cell analyses with contextual information from large biomedical text corpora, but it remains unclear how to optimally align this knowledge with quantitative scRNA-seq data. To address this, we construct text-based training datasets from both scRNA-seq data and biomedical literature targeted to the experimental setting at hand. We then fine-tune lightweight encoder-only biomedical language models to learn a shared, literature-enriched representation. Controlled evaluations across immune and developmental datasets show that this representation preserves cell identity while adding robust and interpretable contextual layers of functional, disease-associated, and developmental information to single-cell analysis workflows.

bioinformatics↗

bioRxiv2025

Metagenomics and qPCR analysis of aerobic metabolic TCE degrading bacteria

Chloroethenes are common groundwater contaminants. While they were initially considered non-biodegradable, different pathways for both, anaerobic and aerobic degradation have been discovered over the last 40 years. Anaerobic reductive dechlorination of tetrachloroethene and trichloroethene (TCE) leads to the formation and possible accumulation of the toxic intermediate products, dichloroethene (DCE) and vinyl chloride (VC). In contrast, aerobic metabolic processes result in mineralization of the contaminants without the formation of stable intermediates. Therefore, productive aerobic degradation processes can have a considerable advantage, depending on site conditions and chloroethene molecule. The potential for aerobic degradation processes can be assessed by molecular biological analysis. In our study, aerobic metabolic TCE enrichment cultures, bioaugmented groundwater, and a microcosm with intrinsic aerobic TCE degradation potential were analyzed. Amplicon sequencing and shotgun metagenomics were used to identify the Rhodocyclaceae bacterial family in all samples, as well as functional gene sequences, which were relatives of monooxygenases and dehalogenases. Based on these sequencing data, qPCR detection methods for TCE assimilating Rhodocyclaceae (Rho) as well as for different functional genes that were associated with monooxygenases (moABC) and haloacid dehalogenases like hydrolases (hdlh) have been established. The specificity of the qPCR methods was demonstrated with a variety of environmental samples and different chloroethene degrading bacterial cultures. The new metagenomic insights and qPCR methods facilitate the assessment of biodegradation potential and monitoring of aerobic metabolic TCE degradation at contaminated sites. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/667672v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@10b51feorg.highwire.dtl.DTLVardef@3414e0org.highwire.dtl.DTLVardef@14694ccorg.highwire.dtl.DTLVardef@d2e4e9_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIRhodocyclaceae bacteria were identified in all aerobic TCE degrading samples C_LIO_LIFunctional monooxygenase and dehalogenase like genes were detected C_LIO_LIqPCR methods for monitoring of aerobic metabolic TCE degradation were developed C_LIO_LISpecificity of qPCR methods was shown with different aerobic chloroethene degrading cultures and environmental samples C_LI

microbiology↗

bioRxiv2022

EggVio: a user friendly and versatile pipeline for assembly and functional annotation of shallow depth sequenced samples

1We introduce a homemade pipeline allowing to improve the quality of the metagenomic annotations carried out when using shallow depth metagenomic datasets. The main motivation being to be able to quantify more precisely, with greater certainty, the genes involved in bacterial interactions. The limitation in our experimental design is that we use a sequencing technique with a low throughput (miSeq) compared to the metagenomic standard (hiSeq) because we carry out a fairly large sampling (almost a hundred samples) in time series. This methodological constraint from our study means that the assembly of the sequences is not very exhaustive (less than 50% of the sequences manage to be assembled). In this chapter, we will therefore present a new pipeline designed to specifically deal with such kind of data. We used co-assembly and a sequence annotation strategy in order to recover the sequences that could not be mapped on the assembled contigs. In addition, in order to avoid adding too much noise, when rescuing reads, we have built an algorithm to define a threshold of e-value based on the noise of the sequence annotation learned from sequences mapped in the assembly. We have selected several recent tools known to be effective for assembling, mapping and annotating these data. In addition, this pipeline was also built in order to be very user-friendly in terms of installation. In this idea of reproducibility, accessibility and transparency, we have designed an installation script to allow each user to install each tool required for the pipeline in a simple and reproducible way. Regarding the performances of this pipeline, we were able to show that the expected error rate (False discovery rate) for the annotation was close to 5%. Finally, we also used an actual dataset from a bioremediation site and showed that the representability of the samples seemed much better when we used our pipeline than when we used a classic metagenome assembly strategy.

microbiology↗

bioRxiv2021

Back to the Wild: Polluted Site Remediation and Biosphere Resilience

Worldwide efforts to depollute environments altered by human industrial activity have begun to produce an ever-increasing number of "clean" sites. "Clean" is defined by local regulatory processes and often responds to low compound concentrations or risk evaluations. Yet, these sites have been critically derailed from their historical biological activity by both the pollution event and the clean-up technology. This work explored the impact of contaminated (and remediated) sites on local microbial ecosystems. Different parcels of the same field site with the same relatively uniform microbial ecology were polluted and cleaned-up over the last 15 years. The statistical evaluation of the perturbation described changes to the local ecosystem that went back to the original baseline microbial composition although the pollution sources and the clean-up technologies affected the rate of return to the pre-disturbed condition. This rate reflected the intensity of the clean-up treatments. The role played by microbial communities on ecosystem maintenance and mitigation of pollution events lays the groundwork for predicting the microbial community responses to perturbations and the ability to reassert themselves. Predictions of ecosystem response to anthropogenic impacts could support decision-making on environmental management strategies for contaminated sites clean-up, depending on the ecosystem services desired to maintain or the risk posed to sensitive receptors.

bioengineering↗

bioRxiv2019

Transcriptomic responses to warming and cooling of an Arctic tundra soil microbiome

BackgroundArctic surface soils experience pronounced seasonal changes in temperature and chemistry. However, it is unclear how these changes affect microbial degradation of organic matter, nitrogen cycling and microbial stress responses. We combined measurements of microbiome transcriptional activity, CO2 production, and pools of carbon and nitrogen to investigate the microbial response to warming in the laboratory, from -10 {degrees}C to 2 {degrees}C, and subsequent cooling, from 2 {degrees}C to -10 {degrees}C, of a high Arctic tundra soil from Svalbard, Norway.\n\nResultsGene expression was unaffected by warming from -10 {degrees}C to -2 {degrees}C and by cooling from -2 {degrees}C to -10 {degrees}C, while upon freezing (2 {degrees}C to -2 {degrees}C) a defense response against oxidative stress was observed. Following modest transcriptional changes one day after soil thaw, a more pronounced response was observed after 17 days, involving numerous functions dominated by an upregulation of genes involved in transcription, translation and chaperone activity. Transcripts related to carbohydrate metabolism and degradation of complex polymers (e.g. cellulose, hemicellulose and chitin) were also enhanced following 17 days of soil thaw, which was accompanied by a four-fold increase in CO2 production. In addition, anaerobic ammonium oxidation and turnover of organic nitrogen were upregulated. In contrast, nitrification, denitrification and assimilatory nitrate reduction were downregulated leading to an increase in the concentration of soil inorganic nitrogen.\n\nConclusionthe microorganisms showed negligible response to changes in sub-zero temperatures and a delayed response to thaw, which after 17 days led to upregulation of soil organic matter degradation and enhanced CO2 production, as well as downregulation of key pathways in nitrogen cycling and a concomitant accumulation of inorganic nitrogen available for plants.

microbiology↗