Biology subjects

Engelmann, J. C.

Publications and source records attributed to Engelmann, J. C..

5 recordsLinked to original sources

bioRxiv2023

Organic matter degradation in the deep, sulfidic waters of the Black Sea: Insights into the ecophysiology of novel anaerobic bacteria

Our knowledge about the physiology of deep sea (>1,000 m) microorganisms involved in organic matter (OM) degradation is still scare due to the lack of available isolates, especially from sulfidic environments. In this study, we successfully cultivated and characterized the physiology of a wide range of novel piezotolerant anaerobic bacteria affiliated with the phyla Fusobacteriota, Bacillota, Spirochaetota, Bacteroidota, Cloacimonadota, Planctomycetota, Mycoplasmatota and Chloroflexota involved in OM degradation in deep sulfidic waters of the Black Sea. The novel taxa are specialized in degrading specific types of OM and cover a wide range of physiological categories, including primary degraders, fermenters, and terminal oxidizers. This is the first report which demonstrates this for such a diverse physiological group from any sulfidic marine habitat. Collectively, this study provides a step forward in our understanding of the microbes thriving in the extreme conditions of the deep sulfidic waters of the Black Sea.

microbiology↗

bioRxiv2022

Disentangling the lipid divide: Identification of key enzymes for the biosynthesis of unusual Membrane-spanning and Ether lipids in Bacteria

Bacterial membranes are composed of fatty acids (FAs) ester-linked to glycerol-3-phosphate, while archaea possess membranes made of isoprenoid chains ether-linked to glycerol-1-phosphate. Many archaeal species organize their membrane as a monolayer of membrane-spanning lipids (MSLs). Exceptions to this lipid divide are the production by some bacterial species of (ether-bound) MSLs, formed by tail-tail condensation of fatty acids resulting in the formation of (iso) diabolic acids (DAs), which are the likely precursors of paleoclimatological relevant branched glycerol dialkyl glycerol tetraether molecules. However, the enzymes responsible for their production are unknown. Here, we report the discovery of bacterial enzymes responsible for the condensation reaction of fatty acids and for ether bond formation, and confirm that the building blocks of iso-DA are branched iso-FAs. Phylogenomic analyses of the key biosynthetic genes reveal a much wider diversity of potential MSL (ether)-producing bacteria than previously thought, with significant implications for our understanding of the evolution of lipid membranes.

microbiology↗

bioRxiv2019

Cascabel: a flexible, scalable and easy-to-use amplicon sequence data analysis pipeline

Marker gene sequencing of the rRNA operon (16S, 18S, ITS) or cytochrome c oxidase I (CO1) is a popular means to assess microbial communities of the environment, microbiomes associated with plants and animals, as well as communities of multicellular organisms via environmental DNA sequencing. Since this technique is based on sequencing a single gene rather than the entire genome, the number of reads needed per sample is lower than that required for metagenome sequencing, making marker gene sequencing affordable to nearly any laboratory. Despite the relative ease and cost-efficiency of data generation, analyzing the resulting sequence data requires computational skills that may go beyond the standard repertoire of a current molecular biologist/ecologist. We have developed Cascabel, a flexible and easy-to-use amplicon sequence data analysis pipeline, which uses Snakemake and a combination of existing and newly developed solutions for its computational steps. Cascabel takes the raw data as input and delivers a table of operational taxonomic units (OTUs) and a representative sequence tree. Our pipeline allows customizing the analyses by offering several choices for most of the steps, for example different OTU generating methods. The pipeline can make use of multiple computing nodes and scales from personal computers to computing servers. The analyses and results are fully reproducible and documented in an HTML and optional pdf report. Cascabel is freely available at Github: https://github.com/AlejandroAb/CASCABEL and licensed under GNU GPLv3.

bioinformatics↗

bioRxiv2019

Elucidating small RNA pathways in Arabidopsis thaliana egg cells

O_LISmall RNA pathway components and small RNA profiles of flowering plant egg cells are largely unexplored, mainly because they are not easily accessible but deeply buried inside the ovary.\nC_LIO_LIWe describe here the utilization of proliferating callus tissue that adopted transcriptome features of Arabidopsis egg cell as a tool to explore small RNA pathway components and small RNA profiles in egg cells. We furthermore complement our studies with mRNA-Seq data from isolated Arabidopsis egg cells and provide data validation by promoter-reporter studies and whole mount in situ hybridization.\nC_LIO_LISequencing of small RNA libraries demonstrate the predominance of TE-derived siRNAs in the egg cell-related callus. TE-features and expression profiles suggest post-transcriptional silencing of activated Gypsy-like LTR retrotransposons, whereas the majority of class II DNA transposons belonging to Copia, CACTA, hAT-like and Mutator superfamilies are subjected to transcriptional silencing.\nC_LIO_LISmall RNA-seq furthermore led to the identification of differentially expressed known and novel miRNAs whose expression in the egg cell was verified by small RNA whole mount in situ hybridization. Both the strong expression of miRNAs in the egg-cell-adjoining synergids and the secretion of miRNAs into the micropyle suggest hitherto undescribed roles for these accessory cells in intercellular communication with the egg cell and the arriving pollen tube.\nC_LIO_LIIn conclusion, our datasets provide valuable and comprehensive resources to study small RNA pathways and small-RNA-mediated epigenetic reprogramming during egg cell differentiation and the onset of plant embryogenesis.\nC_LI

plant biology↗

bioRxiv2018

FastqPuri: high-performance preprocessing of RNA-seq data

BackgroundRNA sequencing (RNA-seq) has become the standard means of analyzing gene and transcript expression in high-throughput. While previously sequence alignment was a time demanding step, fast alignment methods and even more so transcript counting methods which avoid mapping and quantify gene and transcript expression by evaluating whether a read is compatible with a transcript, have led to significant speed-ups in data analysis. Now, the most time demanding step in the analysis of RNA-seq data is preprocessing the raw sequence data, such as running quality control and adapter, contamination and quality filtering before transcript or gene quantification. To do so, many researchers chain different tools, but a comprehensive, flexible and fast software that covers all preprocessing steps is currently missing.\n\nResultsWe here present FastqPuri, a light-weight and highly efficient preprocessing tool for fastq data. FastqPuri provides sequence quality reports on the sample and dataset level with new plots which facilitate decision making for subsequent quality filtering. Moreover, FastqPuri efficiently removes adapter sequences and sequences from biological contamination from the data. It accepts both single- and paired-end data in uncompressed or compressed fastq files. FastqPuri can be run stand-alone and is suitable to be run within pipelines. We benchmarked FastqPuri against existing tools and found that FastqPuri is superior in terms of speed, memory usage, versatility and comprehensiveness. Conclusions: FastqPuri is a new tool which covers all aspects of short read sequence data preprocessing. It was designed for RNA-seq data to meet the needs for fast preprocessing of fastq data to allow transcript and gene counting, but it is suitable to process any short read sequencing data of which high sequence quality is needed, such as for genome assembly or SNV (single nucleotide variant) detection. FastqPuri is most flexible in filtering undesired biological sequences by offering two approaches to optimize speed and memory usage dependent on the total size of the potential contaminating sequences. FastqPuri is available at https://github.com/jengelmann/FastqPuri. It is implemented in C and R and licensed under GPL v3.

bioinformatics↗