Biology subjects

De Paepe, K.

Publications and source records attributed to De Paepe, K..

5 recordsLinked to original sources

bioRxiv2025

An optimized flow cytometry sorting-sequencing workflow reduces storage, sorting and extraction bias in sorted microbial communities

Fluorescence-Activated Cell Sorting (FACS) followed by metataxonomics is commonly used to probe the composition of microbial subpopulations with a functionality of interest. Metataxonomic analysis of sorted low microbial biomass samples is prone to contamination and bias introduced during sorting and DNA extraction. To improve metataxonomic accuracy, the DNA yield obtained by the DNeasy(R) PowerSoil(R) Pro kit was first maximized. FACS-sequencing using the optimized DNA extraction method distorted the composition of sorted microbiota by introducing sheath fluid contaminants, termed the FACSome. Carefully selected controls allowed for FACSome characterization and subsequent in silico decontamination of PacBio and Illumina metataxonomic sequencing data. The optimized extraction and decontamination were validated in soil, water, feces, saliva, gut reactor and mock microbial communities. Metataxonomic profiles of non-selectively sorted and unsorted samples derived from these ecosystems did not perfectly match due to relic DNA depletion during FACS. A nuclease-based digest enhanced the depletion of spiked and naturally present relic DNA, which can interfere with function-driven FACS. Since FACS depleted relic DNA, the preservation of intact cells prior to sorting is essential for activity- or viability-targeted FACS. Intact cells were best preserved during long-term -80{degrees}C storage of fecal samples that were not amended with glycerol-1X Tris-EDTA cryoprotectant.

microbiology↗

bioRxiv2025

Edited Filamin A in myeloid cells reduces intestinal inflammation and protects from colitis

Patho-mechanistic origins and disease dynamics of ulcerative colitis are still poorly understood. The actin-crosslinker Filamin A (FLNA) impacts cellular responses through interaction with cytosolic proteins. FLNA exists in two forms that differ only in one amino acid: genome-encoded FLNAQ and FLNAR - generated by post-transcriptional A-to-I editing. FLNA is edited in fibroblasts, smooth muscle- and endothelial cells in the colon. We identified the FLNA editing status as a key determinant of colitis severity. FLNA editing was highest in healthy colons and reduced during acute murine and human colitis. Mice that exclusively express edited FLNAR and do not downregulate editing upon challenge were highly resistant to DSS-induced colitis, whereas fully unedited FLNAQ animals developed severe inflammation. While the genetic induction of FLNA editing influenced transcriptional states of structural cells and the microbiome composition, we found that FLNAR exerts protection specifically via its influence on myeloid cells, which are not edited under physiological conditions. Introducing fixed, fully edited FLNAR did not hamper normal cell migration but reduced macrophage inflammation and rendered neutrophils less prone to NETosis. In conclusion, loss of FLNA editing correlates with colitis severity, and targeted FLNA editing of myeloid cells might serve as a novel therapeutic approach in intestinal inflammation. SummaryIn this study, Gawish et al. show that RNA editing of the actin cross-linker FLNA is similarly regulated in mice and humans and that the targeted induction of edited FLNAR in myeloid cells governs resistance to DSS-induced colitis, revealing its potential in IBD therapy.

molecular biology↗

bioRxiv2023

Resource-efficient nitrogen removal from source separated urine with partial nitritation/anammox in a membrane aerated biofilm reactor

Source separation and decentralized urine treatment can cut costs in centralized wastewater treatment by diverting 80% of the nitrogen load in sewage. One promising approach for nitrogen removal in this context is partial nitritation/anammox (PN/A), reducing the aeration demand by 67% and organics dosage by 100% compared to nitrification/denitrification. Whilst previous studies with suspended biomass have encountered stability issues during PN/A treatment of urine, a PN/A biofilm was hypothesized to be more resilient. Its use for urine treatment was pioneered here for maximum rates and efficiencies in the energy efficient membrane-aerated biofilm reactor (MABR). Nitrogen removal rates of 1.0 g N L-1 d-1 and removal efficiencies of 80-95% were achieved during a 335-day stable operation at 28{degrees}C on stabilized (pH>11), diluted urine (10%). A balance between N2 and NO3 - formation was observed whilst optimizing the supply of O2 and was rate limiting for the conversion towards N2. Short-term operation on less- and undiluted urine yielded N removal rates of 0.6-0.8 g N L-1 d-1 and removal efficiencies of 93% on 66% urine and 85% on undiluted urine. Metataxonomic analysis and fluorescence in-situ hybridization confirmed the presence of biofilms consisting of nitrifiers (Nitrosomonas, Nitrospira) at the membrane side and anammox bacteria ("Candidatus Brocadia") at the anoxic bulk side. The findings suggest that a biofilm approach to PN/A treatment of urine overcomes stability issues, and a PN/A-MABR has significant potential for resource efficient decentralized treatment. In human long-duration deep-space missions, this gravity-independent technology could produce N2 to compensate artificial atmosphere losses whilst facilitating water recovery from urine. [GRAPHICAL ABSTRACT, COLOR] O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/572732v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1680b0corg.highwire.dtl.DTLVardef@1ad822dorg.highwire.dtl.DTLVardef@3d5c4borg.highwire.dtl.DTLVardef@764841_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2020

Dietary emulsifiers alter composition and activity of the human gut microbiota in vitro, irrespective of chemical or natural emulsifier origin.

The use of additives in food products has become an important public health concern. In recent reports, dietary emulsifiers have been shown to affect the gut microbiota, contributing to a pro-inflammatory phenotype and metabolic syndrome. So far, it is not yet known whether similar microbiome shifts are observable for a more diverse set of emulsifier types and to what extent these effects vary with the unique features of an individuals microbiome. To bridge this gap, we investigated the effect of five dietary emulsifiers on the fecal microbiota from 10 human individuals upon a 48 hour exposure. Community structure was assessed with quantative microbial profiling, functionality was evaluated by measuring fermentation metabolites and pro-inflammatory properties were assessed with the phylogenetic prediction algorythm PICRUSt, together with a TLR5 reporter cell assay for flagellin. A comparison was made between two mainstream chemical emulsifiers (carboxymethylcellulose and P80), a natural extract (soy lecithin) and biotechnological emulsifiers (sophorolipids and rhamnolipids). While fecal microbiota responded in a donor-dependent manner to the different emulsifiers, profound differences between emulsifier were observed. Rhamnolipids, sophorolipids and soy lecithin eliminated 91% {+/-} 0%, 89% {+/-} 1% and 87% {+/-} 1% of the viable bacterial population after 48 hours, yet they all selectively increased the proportional abundance of putative pathogens. Moreover, profound shifts in butyrate (-96% {+/-} 6 %, -73% {+/-} 24% and -34 {+/-} 25% respectively) and propionate (+13% {+/-} 24 %, +88% {+/-} 50% and +29% {+/-} 16% respectively) production were observed for these emulsifiers. Phylogenetic prediction indicated higher motility, which was, however, not confirmed by increased flagellin levels using the TLR5 reporter cell assay. We conclude that dietary emulsifiers can severely impact the gut microbiota and this seems to be proportional to their emulsifying strength, rather than emulsifier type or origin. As biotechnological emulsifiers were especially more impactful than chemical emulsifiers, caution is warranted when considering them as more natural alternatives for clean label strategies.

microbiology↗

bioRxiv2017

Differential gene expression analysis tools exhibit substandard performance for long non-coding RNA-sequencing data

BackgroundProtein-coding RNAs (mRNA) have been the primary target of most transcriptome studies in the past, but in recent years, attention has expanded to include long non-coding RNAs (lncRNA). lncRNAs are typically expressed at low levels, and are inherently highly variable. This is a fundamental challenge for differential expression (DE) analysis. In this study, the performance of 14 popular tools for testing DE in RNA-seq data along with their normalization methods is comprehensively evaluated, with a particular focus on lncRNAs and low abundant mRNAs.\n\nResultsThirteen performance metrics were used to evaluate DE tools and normalization methods using simulations and analyses of six diverse RNA-seq datasets. Non-parametric procedures are used to simulate gene expression data in such a way that realistic levels of expression and variability are preserved in the simulated data. Throughout the assessment, we kept track of the results for mRNA and lncRNA separately. All statistical models exhibited inferior performance for lncRNAs compared to mRNAs across all simulated scenarios and analysis of benchmark RNA-seq datasets. No single tool uniformly outperformed the others.\n\nConclusionOverall, the linear modeling with empirical Bayes moderation (limma) and the nonparametric approach (SAMSeq) showed best performance: good control of the false discovery rate (FDR) and reasonable sensitivity. However, for achieving a sensitivity of at least 50%, more than 80 samples are required when studying expression levels in a realistic clinical settings such as in cancer research. About half of the methods showed severe excess of false discoveries, making these methods unreliable for differential expression analysis and jeopardizing reproducible science. The detailed results of our study can be consulted through a user-friendly web application, http://statapps.ugent.be/tools/AppDGE/

genomics↗