Biology subjects

Kerbl-Knapp, J.

Publications and source records attributed to Kerbl-Knapp, J..

3 recordsLinked to original sources

bioRxiv2026

Multi-omics analysis identifies loci associated with pyrethroid resistance across sister species in the Anopheles gambiae species complex

The Anopheles gambiae species complex includes An. gambiae, An. coluzzii, and An. arabiensis, three of the four major malaria vector species across Africa. Insecticide-based vector control remains the most critical tool in the fight against malaria, with a heavy reliance on pyrethroid insecticides. However, widespread pyrethroid resistance jeopardises the effectiveness of these methods. Currently, the number of diagnostic markers available to track pyrethroid resistance in endemic settings is limited, focusing mainly on changes at the insecticide target site. Genetic analysis of seven insecticide-resistant populations from West Africa, a region with intense insecticide resistance, reveals shared loci associated with pyrethroid resistance among the sister species of the An. gambiae complex including kdr, GSTE1-8 and the CYP6P region. Notably, a mutation in the voltage-gated sodium channel, I1527T, previously identified in An. coluzzii and An. gambiae, was detected in wild-caught An. arabiensis from Burkina Faso. Additionally, a mutation, L207I, in GSTE7 common to An. coluzzii and An. arabiensis, significantly increases survivorship to deltamethrin. With the additional integration of RNAseq and data from the Anopheles gambiae 1000 genomes project, we were able to identify putative eQTLs associated with the expression of major insecticide resistance-related transcripts, such as CYP6P3, CYP9K1 and CYP6AA1. This study reveals several potential diagnostic markers of resistance that can be implemented in endemic settings and identifies putative introgression between An. arabiensis and An. coluzzii in Burkina Faso.

genetics↗

bioRxiv2024

A novel barcoded nanopore sequencing workflow of high-quality, full-length bacterial 16S amplicons for taxonomic annotation of bacterial isolates and complex microbial communities

IntroductionDue to recent improvements, Nanopore sequencing has become a promising method for experiments relying on amplicon sequencing. We describe a flexible workflow to generate and annotate high-quality, full-length 16S rDNA amplicons. We evaluated it for two applications, namely, i) identification of bacterial isolates and ii) species-level profiling of microbial communities. MethodsBacterial isolate identification by sequencing was tested on 47 isolates and compared to MALDI-TOF MS. 97 isolates were additionally sequenced to assess the resolution of phylogenetic classification. Species-level community profiling was tested with two full-length 16S primer pairs (A and B) with custom barcodes and compared to results obtained with Illumina sequencing using 27 stool samples. Finally, a Nextflow pipeline was developed to produce high-quality reads and taxonomically annotate them. ResultsWe found high agreement between our workflow and MALDI-TOF data for isolate identification (PPV = 0.90, Cramers V = 0.857 and, Theils U = 0.316). For species-level community profiling, we found strong correlations (rs > 0.6) of alpha diversity indices between the two primer sets and Illumina sequencing. At the community level, we found significant but small differences when comparing sequencing techniques. Finally, we found moderate to strong correlation when comparing relative abundances of individual species (average rs = 0.6 and 0.533, for primers A and B). DiscussionThe proposed workflow enabled accurate identification of single bacterial isolates, making it a worthwhile alternative to MALDI-TOF. While shortcomings have been identified, it enabled reliable identification of prominent features in microbial communities at a fraction of the cost of Illumina sequencing. ImportanceA quick, robust, simple, and cost-effective method to identify bacterial isolates and communities in each sample is indispensable in the fields of microbiology and infection biology. Recent technological advances in Oxford Nanopore Technologies sequencing make this technique an attractive option considering the adaptability, portability, and cost-effectiveness of the platform. Here, we validated a flexible workflow to identify bacterial isolates and characterize bacterial communities using the Oxford Nanopore Technologies sequencing platform combined with the most recent v14 chemistry kits. For bacterial isolates, we compared our nanopore-based approach to MALDI-TOF MS-based identification. For species-level profiling of complex bacterial communities we compared our nanopore-based approach to Illumina shotgun sequencing. For reproducibility purposes, we wrapped the code used to process the sequencing data into a ready-to-use and self-contained Nextflow pipeline.

microbiology↗

bioRxiv2021

Global analysis of protein arginine methylation

Quantitative information about the levels and dynamics of post-translational modifications (PTMs) is critical for an understanding of cellular functions. Protein arginine methylation (ArgMet) is an important subclass of PTMs and is involved in a plethora of (patho)physiological processes. However, due to the lack of methods for global analysis of ArgMet, the link between ArgMet levels, dynamics and (patho)physiology remains largely unknown. We utilized the high sensitivity and robustness of Nuclear Magnetic Resonance (NMR) spectroscopy to develop a general method for the quantification of global protein ArgMet. Our NMR-based approach enables the detection of protein ArgMet in purified proteins, cells, organoids, and mouse tissues. We demonstrate that the process of ArgMet is a highly prevalent PTM and can be modulated by small-molecule inhibitors and metabolites and changes in cancer and during ageing. Thus, our approach enables to address a wide range of biological questions related to ArgMet in health and disease. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/428036v1_ufig1.gif" ALT="Figure 1"> View larger version (68K): org.highwire.dtl.DTLVardef@37a0f1org.highwire.dtl.DTLVardef@273ebdorg.highwire.dtl.DTLVardef@87fcd6org.highwire.dtl.DTLVardef@1e84c07_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗