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Gehrig, J.

Publications and source records attributed to Gehrig, J..

4 recordsLinked to original sources

Improved Metagenomic Binning with Transformers

AO_SCPLOWBSTRACTC_SCPLOWTraditional metagenome binning methods cluster contiguous DNA sequences (contigs) based on uncontextualized features of the sequences which ignores both the semantic relationship between genes and the positional embedding of k-mers. This paper presents a novel binning method that addresses these concerns. Firstly, taken from natural language processing literature, a sequence representation model - Bidirectional Encoder Representations from Transformers (BERT) - is utilized to generate semantic and positional contig embeddings. Secondly, two workflows are presented; one which applies a hierarchical density-based clustering algorithm to find metagenomic bins and the other which incorporates contig embedding into a state-of-the-art binner. Experimental results on a publicly available metagenomic dataset show superior clustering for shorter contigs compared to traditionally used tetranucleotide frequency (TNF), reconstruction of up to 17% more high-precision genomes, and improved semantic understanding of contigs.

genomics↗

In vivo high-content screening in zebrafish for developmental nephrotoxicity of approved drugs

Despite widespread drug exposure, for example during gestation or in prematurely born children, organ-specific developmental toxicity of most drugs is poorly understood. Developmental and functional abnormalities are a major cause of kidney diseases during childhood; however, the potential causal relationship to exposure with nephrotoxic drugs during nephrogenesis is widely unknown. To identify developmental nephrotoxic drugs in a large scale, we established and performed an automated high-content screen to score for phenotypic renal alterations in the Tg(wt1b:EGFP) zebrafish line. During early nephrogenesis, embryos were exposed to a compound library of approved drugs. After treatment, embryos were aligned within microtiter plates using 3D-printed orientation tools enabling the robust acquisition of consistent dorsal views of pronephric kidneys by automated microscopy. To qualitatively and quantitatively score and visualize phenotypes, we developed software tools for the semi-automated analysis, processing and visualization of this large image-based dataset. Using this scoring scheme, we were able to categorize compounds based on their potential developmental nephrotoxic effects. About 10% of tested drugs induced pronephric phenotypes including glomerular and tubular malformations, or overall changes in kidney morphology. Major chemical compound groups identified to cause glomerular and tubular alterations included dihydropyridine derivatives, HMG CoA reductase inhibitors, fibrates, imidazole, benzimidazole and triazole derivatives, corticosteroids, glucocorticoids, acetic acid derivatives and propionic acid derivatives. In conclusion, the presented study demonstrates the large-scale screening of kidney-specific toxicity of approved drugs in a live vertebrate embryo. The associated technology and tool-sets can be easily adapted for other organ systems providing a unique platform for in vivo large-scale assessment of organ-specific developmental toxicity or other biomedical applications. Ultimately, the presented data and associated visualization and browsing tools provide a resource for potentially nephrotoxic drugs and for further investigations.

developmental biology↗

Multi-Template Matching: a versatile tool for object-localization in microscopy images

We implemented multiple template matching as both a Fiji plugin and a KNIME workflow, providing an easy-to-use method for the automatic localization of objects of interest in images. We demonstrate its application for the localization of entire or partial biological objects. The Fiji plugin can be installed by activating the Multi-Template-Matching and IJ-OpenCV update sites. The KNIME workflow can be downloaded from nodepit space or the associated GitHub repository. Python source codes and documentations are available on the following GitHub repositories: LauLauThom/MultiTemplateMatching and LauLauThom/MultipleTemplateMatching-KNIME.

bioinformatics↗

Automated high-throughput heart rate measurement in medaka and zebrafish embryos under physiological conditions

RationaleAccurate and efficient quantification of heartbeats in small fish models is an important readout to study cardiovascular biology, disease states and pharmacology at large scale. However, dependence on anesthesia, laborious sample orientation or requirement for fluorescent reporters have hampered the establishment of high-throughput heartbeat analysis. ObjectiveTo overcome these limitations, we aimed to develop a high-throughput assay with automated heart rate scoring in medaka (Oryzias latipes) and zebrafish (Danio rerio) embryos under physiological conditions designed for genetic screens and drug discovery and validation. Methods and ResultsWe established an efficient screening assay employing automated label-free heart rate determination of randomly oriented, non-anesthetized specimen in microtiter plates. Automatically acquired bright-field data feeds into an easy-to-use HeartBeat software, a MATLAB algorithm with graphical user interface developed for automated quantification of heart rate and rhythm. Sensitivity of the assay and algorithm was demonstrated by profiling heart rates during entire embryonic development. Our analysis pipeline revealed acute temperature changes triggering rapid adaption of heart rates, which has implications for standardization of experimental layout. The approach is scalable and allows scoring of multiple embryos per well resulting in a throughput of >500 embryos per 96-well plate. In a proof of principle screen for compound testing, our assay captured concentration-dependent effects of nifedipine and terfenadine over time. ConclusionA novel workflow and HeartBeat software provide efficient means for reliable and direct quantification of heart rate and rhythm of small fish in a physiological environment. Importantly, confounding factors such as anesthetics or laborious mounting are eliminated. We provide detailed profiles of embryonic heart rate dynamics in medaka and zebrafish as reference for future assay development. Ease of sample handling, automated imaging, physiological conditions and software-assisted analysis now facilitate various large-scale applications ranging from phenotypic screening, interrogation of gene functions to cardiovascular drug development pipelines.

developmental biology↗