Biology subjects

Nieselt, K.

Publications and source records attributed to Nieselt, K..

At least 19 recordsLinked to original sources

bioRxiv2026

The PhageExpressionAtlas reveals shared and unique transcriptional patterns across phage-host interactions

Time-resolved transcriptomic profiling has been used to study phage-host interactions for more than a decade. However, the resulting datasets are not readily accessible for custom re-analysis, and resources are lacking that provide standardized processing, storage, and analysis of transcriptomes from phage infections. Here, we present the PhageExpressionAtlas, the first bioinformatics resource for storing time-resolved dual RNA-sequencing data from phage infections. This data was processed uniformly using a custom analysis pipeline and is presented for interactive exploration through visualisation. The PhageExpressionAtlas currently hosts 42 datasets from 23 studies. Using the PhageExpressionAtlas, we replicate key findings from original publications and extend hypothesis testing across multiple phage-host systems. By systematically querying and analyzing the underlying database, we evaluate approaches to phage gene classification and show that uncharacterized phage genes are expressed across all infection phases. Moreover, we provide a comprehensive view of the expression dynamics of anti-phage defenses as well as host- and phage-encoded anti-defense systems in the infection context, indicating unique and conserved patterns of transcriptional regulation underlying bacterial anti-phage immunity and phage counter-strategies. Together, the PhageExpressionAtlas is a unifying resource that democratizes transcriptomics-driven analyses of phage-host interactions and supports integrative cross-study assessment.

bioinformatics↗

bioRxiv2026

Gradient boosting regression and convolution improve deconvolution of bulk transcriptomes

Bulk cell type deconvolution aims to estimate cell type composition from bulk transcriptomic data. So-called pseudobulk simulation, where single-cell RNA-seq data is aggregated to bulk-like expression profiles, represents a central concept in training and testing of deconvolution tools. However, deconvolution methods often lack interpretability and struggle to generalize from simulated to real data. We present GrooD (GradientBoostedDeconvolution), a second-generation deconvolution tool that uses gradient boosted trees trained on pseudobulks from scRNA-seq references. GrooDs pseudobulk simulations account for donor and condition variability to better model the complexity of real-world transcriptomes. We show that GrooD achieves state-of-the-art and superior deconvolution performance on human blood biospecimen. Furthermore, Grood provides visualizations of feature loadings and deconvolution results, that allow mechanistic insights for biological interpretation. We further integrate a convolution framework to assess the transcriptomic similarity between bulk and pseudobulk data, showing that higher similarity can indicate better deconvolution performance. GrooD deconvolution of blood transcriptomes from a large sepsis patient cohort identifies meaningful shifts in immune cell type composition that are associated with disease severity. By combining interpretability, robustness, and heterogeneous pseudobulk simulation, GrooD represents a powerful, user-friendly second-generation tool for cell type deconvolution.

bioinformatics↗

bioRxiv2025

The E. coli PeptideAtlas Build: Characterizing the observed Escherichia coli pan-proteome and its post-translational modifications

Escherichia coli is a widely used model organism in molecular biology. Despite its pivotal role, a comprehensive proteome resource covering the E. coli pan-proteome and its post-translational modifications (PTMs) has been lacking. Here we present the E. coli PeptideAtlas build, the first comprehensive pan-proteome analysis of E. coli, generated from 40 high-quality public and in-house datasets spanning a broad diversity of strains, sample types, and experimental conditions, and comprising over 73 million MS/MS spectra. All datasets were reprocessed using both a closed search (Trans-Proteomic Pipeline using MSFragger) and an open search (ionbot). The E. coli PeptideAtlas build provides evidence for 4,755 proteins, including 1,410 previously lacking protein-level support in UniProt. The resource offers protein coverage, modification sites, raw spectra with matched peptides, and manually annotated metadata for the E. coli pan proteome. PTM profiling identified over 10,000 modification sites, including phosphorylation (3,806), acetylation (754), methylation (730), glutathionylation (352) and phosphoribosylation (226). Analysis of the glutathionylation sites revealed potential links to metal binding regulation. We also detected proteins likely associated with phages, underscoring the value of pan-proteomic approaches for studying host-phage interactions. All identifications are publicly accessible and traceable through the PeptideAtlas interface. We expect that the E. coli PeptideAtlas build will provide a useful resource for the community, which supports, for example, targeted MS experiment design, PTM enrichment method development, and strain typing. It allows straightforward lookups of protein and peptide identifications and facilitates comparative proteomic analyses by enabling the assessment of protein presence and variability across different E. coli strains. The build is available at https://db.systemsbiology.net/sbeams/cgi/PeptideAtlas/buildDetails?atlas_build_id=585.

bioinformatics↗

bioRxiv2025

PneumoWiki: A pan-genome-based database for the pathogen Streptococcus pneumoniae

The Gram-positive bacterium Streptococcus pneumoniae is a major human pathogen that exhibits more than 100 different capsular serotypes and considerable genomic variation. S. pneumoniae is also an important model organism for basic and biomedical research, with a number of strains with different characteristics being used. To address this, we have created the manually curated pan-genome database PneumoWiki (https://pneumowiki.med.uni-greifswald.de) that integrates genomic data from 43 S. pneumoniae strains with various aspects of functional annotation. All data relating to a specific gene and gene product are compiled on a Gene page. In addition to the gene and protein sequences and annotation from NCBI RefSeq, the Gene pages contain data on, for example, gene essentiality, protein function and localization, and transcriptional regulation. The information is supplemented with links to the data sources as well as to other databases and relevant literature. The basic concept of PneumoWiki is the interlinked presentation of pan-genome-based and strain-specific information. Therefore, register tabs with strain names at the top of the Gene pages allow switching between orthologous genes and the corresponding pan-genome page. The pan-genome gene pages contain a summary with functional information and the occurrence of the gene, an orthologue table for the 43 S. pneumoniae strains, a multiple-strain genome viewer as well as a protein sequence alignment. PneumoWiki was developed as a user-friendly tool and is available free of charge. The data collected in PneumoWiki are accessible via various download options to support bioinformatic applications. Overall, PneumoWiki is a resource for the pneumococcal research community that supports the analysis and interpretation of research data and, in particular, enables the integration of the knowledge available for different S. pneumoniae strains.

microbiology↗

bioRxiv2025

Beyond commensalism: Genomic insights into micrococcin P1-producing Staphylococcus chromogenes

Staphylococcus chromogenes (S. chromogenes) is a predominant non-aureus staphylococcal species colonizing the teat skin and mammary gland of dairy ruminants. Although often linked to mild or subclinical mastitis, specific strains may also play protective roles against major udder pathogens. In this study, we characterized two S. chromogenes isolates (4S77 and 4S90) that displayed antimicrobial activity against Gram-positive bacteria. Complete genome sequencing revealed a conserved, plasmid-encoded biosynthetic gene cluster for the thiopeptide bacteriocin micrococcin P1 (MP1). All genes necessary for MP1 biosynthesis, modification, export, and immunity were identified, and compound production was confirmed by HPLC and LC-MS. Comparative analysis with publicly available S. chromogenes genomes revealed that the MP1 cluster appears unique to these isolates. Both strains showed full phenotypic susceptibility to tested antibiotics, despite 4S90 carrying the lnuA gene, which did not confer detectable resistance under standard conditions. Classical staphylococcal toxin genes were also absent. Virulence gene profiling revealed a conserved repertoire of colonization- and persistence-associated genes, including factors involved in adhesion, capsule formation, and iron acquisition, but no markers of aggressive pathogenicity. Mobile genetic elements, including prophages and genomic islands, were common but did not carry antimicrobial resistance or virulence genes, suggesting a low risk of transmission of new pathogenic traits to the endogenous microbiome, including opportunistic bacteria. These findings suggest that MP1-producing S. chromogenes strains combine antimicrobial functionality with low virulence potential, highlighting their potential ecological role as protective commensals on the teat skin and in the broader mammary ecosystem of dairy ruminants.

microbiology↗

bioRxiv2025

Identification of the negamycin split biosynthetic gene cluster in Kitasatospora purpeofusca ATCC21470

Negamycin is a ribosome-targeting antibiotic with activity against Gram-positive and Gram-negative bacteria including ESKAPE pathogens. Furthermore, it promotes premature stop codon readthrough. Its therapeutic potential is limited by low natural production and synthetic complexity. To enable scalable biosynthesis, we identified and characterized its genetic basis in Kitasatospora purpeofusca ATCC 21470. Two distant chromosomal regions, neg1 and neg2, were found to be essential. Deletion of neg1, involved in nitrite provision for N-N bond formation, reduced production to [~]10%, while deletion of neg2, which directs {beta}-lysine generation and scaffold assembly, abolished it completely. Isotope-labeling experiments confirmed nitrite incorporation. Transcriptomic and proteomic analyses further supported the involvement of both regions. The heterologous expression of neg1 along with the neg2 region in Streptomyces albidoflavus reconstituted negamycin biosynthesis, confirming the unusual involvement of two distant gene clusters in the biosynthesis, and provides a foundation for biotechnological production and further development of this promising antibiotic. SIGNIFICANCEThe rapid rise of antimicrobial resistance (AMR), particularly among Gram-negative ESKAPE pathogens, represents one of the most urgent global health threats. Despite this, the discovery and development of new antibiotics have stagnated. Addressing this challenge requires the exploration of natural products with novel mechanisms of action, alongside the development of scalable production strategies. Negamycin has emerged as a compelling candidate in this regard, characterized by an unusual mechanism of action and therapeutic potential extending beyond traditional antibacterial use. However, its development has been constrained by low production yields in the native producer. In this study, we identify and characterize the biosynthetic genes responsible for negamycin production, providing a foundation for pathway engineering, yield optimization, and the rational design of new analogs.

microbiology↗

bioRxiv2025

A new typing scheme demonstrates high discriminatory power for Treponema pallidum subspecies

The global resurgence of treponematoses, particularly syphilis, poses a growing public health challenge. Despite recent advances in sequencing technologies, obtaining complete Treponema pallidum genome sequences for epidemiological studies remains time-consuming and challenging due to the difficulty related to procuring clinical samples with sufficient treponemal burden to fulfil the sequencing requirements. There is an urgent need for rapid, cost-effective and accessible typing methods suitable for laboratories with Sanger sequencing resources. Based on the analysis of 121 T. pallidum genomes from geographically diverse regions, we selected seven highly variable genes to form the basis of this new typing system. These seven genes show high discrimination capacity, identifying many allelic profiles among T. pallidum isolates. Importantly, the scheme employs a single-step PCR protocol for the amplification and sequencing of all seven targets enabling straightforward implementation in standard laboratory settings. The MLST was validated using a diverse set of T. pallidum clinical samples from across the globe. A significant proportion of the tested samples showed macrolide resistance, emphasizing the need for epidemiological surveillance. Utilizing this new tool, we have analyzed the genetic variation within and between populations of T. pallidum, considering the geographical origin of the samples. Population structure analysis revealed distinct genetic clusters, underlining complex transmission dynamics of T. pallidum, shaped by local epidemiological factors. The MLST scheme is publicly accessible through the PubMLST database, encouraging widespread adoption in standard laboratories due to this database being user-friendly, intuitive, and fast to implement. The novel MLST scheme offers a promising tool to advance the study of the molecular epidemiology of T. pallidum, facilitate tracking transmission, and establish a global surveillance network with the overall goal of strengthening public health interventions for syphilis control.

microbiology↗

bioRxiv2025

TSSpredator-Web: A web-application for transcription start site prediction and exploration

BackgroundWith the rapid development of high-throughput RNA-seq technologies, the transcriptome of prokaryotes can now be studied in unprecedented detail. Transcription start site (TSS) identification provides critical insights into transcriptional regulation, yet current command-line tools for the prediction of TSS remain challenging with respect to their usability and lack of integrated exploration features. ResultsWe introduce TSSpredator-Web an interactive web application that enhances the usability of the established yet unpublished tool, TSSpredator. TSSpredator-Web facilitates TSS prediction from non-enriched and enriched RNA-seq data, classifies TSS relative to annotated genes, and allows users to explore results through dynamic visualizations and interactive tables. For the visualizations we provide an UpSet plot summarizing TSS distribution across experiments or classes, and a genome viewer that integrates transcriptomic and genomic data that contextualizes the insights of the TSS predictions. To illustrate the usage of TSSpredator-Web, we provide a use case with Cappable-seq data from Escherichia coli. TSSpredator-Web is available at the TueVis visualization web-server at https://tsspredator-tuevis.cs.uni-tuebingen.de/. ConclusionsBy combining user-friendly accessibility with interactive data exploration, TSSpredator-Web significantly facilitates genome-wide TSS analysis and interpretation in prokaryotes, empowering a broader range of researchers to generate biological insights from transcriptomic data.

bioinformatics↗

bioRxiv2025

Sequence variability of BamA and FadL candidate vaccinogens suggests divergent evolutionary paths of Treponema pallidum outer membrane proteins

Knowledge of Treponema pallidum subspecies pallidum (TPA) outer membrane protein (OMP) sequence variability is essential for understanding spirochete proliferation within endemic populations as well as design of a globally effective syphilis vaccine. Our group has identified extracellular loops (ECLs) of TPA BamA (TP0326) and members of the FadL family (TP0548, TP0856, TP0858, TP0859, and TP0865) as potential components of a multivalent vaccine cocktail. As part of a consortium to explore TPA strain diversity, we mapped the variability of BamA and FadL orthologs in 186 TPA strains from Malawi, China and Colombia onto predicted 3D structures. The 186 genomes fell into eight subclades (five Nichols-, three SS14-lineage) with substantial geographic restriction. Single nucleotide variants accounted for the large majority of proteoforms, with variability notably higher within the Nichols-lineage strains. Most mutations were in regions of the proteins predicted to be extracellular and harboring B cell epitopes. We observed a striking difference in the degree of variability between the six OMPs, suggesting that these proteins are following divergent evolutionary paths. Concatenation of OMP sequences recapitulated the phylogenetic structure of the TPA strains, effectively segregating within clades and largely clustering by subclades. Lastly, we noted that BamA and FadL candidate ECL vaccinogens previously shown to elicit antibodies that kill treponemes during in vitro cultivation are well conserved. Taken as a whole, our study establishes a structural-phylogenetic approach for analyzing the forces shaping the host-pathogen interface in syphilis within endemic populations while informing selection of vaccine targets. IMPORTANCESyphilis remains a major global health concern, reinforcing the need for a safe and effective vaccine. Understanding the variability of TPA OMPs is essential for tracking pathogen evolution and informing vaccine design. Here, we analyzed the variability of six TPA OMPs in 186 strains from Malawi, China, and Colombia, identifying protein-specific evolutionary patterns. Most mutations were localized in extracellular regions and, notably, appeared to correlate with the phylogenetic structure of TPA. Despite OMP heterogeneity, several candidate vaccinogens remained highly conserved, reinforcing their potential as globally effective vaccine targets. Our study establishes a structural-phylogenetic framework for dissecting the forces shaping the host-spirochete interface within endemic populations and provides a foundation for designing a globally effective syphilis vaccine.

microbiology↗

bioRxiv2025

Genetic modification of intractable staphylococcal clones by heat-shock facilitated phage transduction

Increasing recognition of commensal bacteria as a requirement for microbiome integrity and pathogen exclusion puts urgency to the molecular characterization of commensal interactions. However, many commensals cannot be transformed with available methodology because of potent restriction barriers. We developed a new method for the introduction of plasmid DNA into otherwise intractable non-Staphylococcus aureus (NAS) staphylococci, important commensal members of human nose and skin microbiomes, by phage transduction. We demonstrate that a precise pulse of recipient bacteria with elevated temperatures prior to exposure to transducing phages renders NAS isolates effectively and transiently amenable to transduction. Transduction of NAS mutants lacking restriction-modification (RM) systems did not profit from a heat shock indicating that it is the transient deactivation of RM enzymes that permit transduction. Our method also facilitated the transduction of other Bacillota from the genera Bacillus and Listeria indicating that it will support research on different bacterial groups from diverse ecosystems. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/647181v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@233348org.highwire.dtl.DTLVardef@fbf57corg.highwire.dtl.DTLVardef@1b1abadorg.highwire.dtl.DTLVardef@17e283f_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Biotic interactions shape infection outcomes in Arabidopsis

The plant microbiome protects plants from stresses, including pathogen attacks. However, identifying microbes that provide plant protection remains challenging in complex microbial communities. In this study, we analysed samples from natural A. thaliana populations, including both plants infected with the pathogenic oomycete Albugo laibachii and uninfected plants, over six years. Using machine learning classification models, we achieved high accuracy in distinguishing infected and uninfected plants based on microbiome abundance. We identified 80 key taxa associated with health and disease. Among the health-associated microbes (HCom), we selected bacteria, fungi, and cercozoa that effectively reduced pathogen presence in co-inoculation assays. In comparison, disease-associated microbes (DCom) were less effective in conferring protection. Our findings highlight the complexity of plant-microbe interactions and advance our understanding of microbial roles in plant disease ecology. By integrating ecological insights with machine learning, we take a significant step towards designing robust microbial consortia that enhance plant resilience against pathogens.

microbiology↗

bioRxiv2024

TSS-Captur: A User-Friendly Characterization Pipeline for Transcribed but Unclassified RNA transcripts

AO_SCPLOWBSTRACTC_SCPLOWRNA-seq and its 5-enrichment-based methods for prokaryotes have enabled the base-exact identification of transcription starting sites (TSSs) and have improved gene expression analysis. Computational methods analyze this experimental data to identify TSSs and classify them based on proximal annotated genes. While some TSSs cannot be classified at all (orphan TSSs), other TSSs are found on the reverse strand of known genes (antisense TSSs), but are not associated with the direct transcription of any known gene. Here, we introduce TSS-Captur, a novel pipeline, that uses computational approaches to characterize genomic regions starting from experimentally confirmed, but unclassified TSSs. By analyzing experimental TSS data, TSS-Captur characterizes unclassified signals, hence complementing prokaryotic genome annotation tools and enhancing the bacterial transcriptome understanding. TSS-Captur classifies extracted transcripts into coding or non-coding genes and predicts for each putative transcript its transcription termination site. For non-coding genes, the secondary structure is computed. Furthermore, putative promoter regions are analyzed to identify enriched motifs. An interactive report allows a seamless data exploration. We validated TSS-Captur with a Campylobacter jejuni dataset and characterized unlabeled non-coding RNAs in Streptomyces coelicolor. Besides its usage over the command-line, TSS-Captur is available as a web-application to enhance its user accessibility and explorative capabilities.

bioinformatics↗

bioRxiv2024

Multiple regulators control the biosynthesis of brasilicardin in Nocardia terpenica

Brasilicardin A, BraA, is a secondary metabolite produced by the bacterium Nocardia terpenica, and a promising drug due to its potent immunosuppressive activity and low cytotoxicity. Currently, a semisynthetic approach confers production of a complete compound but suffers from insufficient heterologous biosynthesis of BraA intermediates used in the chemical semi-synthesis steps leading to only lab scale quantities of the compound. A better understanding of the involved gene expression regulatory pathways within the brasilicardin biosynthetic gene cluster, Bra-BGC, is a prerequisite to further improve production titers. However, the transcriptional regulation of the Bra-BGC has only been superficially analyzed, till now. In this study, we comprehensively analyze the functions of several unstudied transcriptional regulators, KstR, SdpR and OmpR, encoded within the close vicinity of the Bra-BGC, and delve into the role of the previously described cluster-situated activator Bra12. We present, that Bra12 and the novel regulator SdpR, bind several DNA sequences located in the promoter regions of the genes essential for BraA biosynthesis. Subsequently, we demonstrate the complex regulatory network through which both regulators are capable of controlling activity of those gene promoters and thus gene expression in Bra-BGC. Furthermore, using the heterologous producer strain Amycolatopsis japonicum, we present, that Bra12 and SdpR regulators play opposite roles in brasilicardin congener biosynthesis. Finally, we propose a comprehensive model of multilevel gene expression regulation in Bra-BGC and propose the roles of locally encoded transcriptional regulators.

molecular biology↗

bioRxiv2023

Seasonality adaptation patterns of the natural Arabidopsis leaf microbiome over several plant generations are shaped by environmental factors

Leaf-associated microbial communities can promote plant health and resistance to biotic and abiotic stresses. However, the importance of environmental cues in the assembly of the leaf endo- and epi-microbiota remains elusive. Here we aimed to investigate the impact of seasonal environmental variations, on the establishment of the leaf microbiome, focusing on long-term changes (five years) in bacterial, fungal, and non-fungal eukaryotic communities colonizing the surface and endosphere of six wild Arabidopsis thaliana populations. While leaf-microbial communities were found to be highly stochastic, the leaf niche had a predominant importance with endophytic microbial communities consistently exhibiting a lower diversity and variability. Furthermore, our analyses revealed that among environmental factors, radiation and humidity-related factors are the most important drivers of diversity paderns in the leaf, albeit with stronger effects on epiphytic communities. Using linear models, we further identified 30 important genera whose relative abundance in leaf compartments could be modeled from environmental variables, suggesting specific niche preferences for these taxa. With the hypothesis that these environmental factors could impact interactions within microbial communities, we analyzed the seasonal paderns of microbial interaction networks across leaf compartments. We showed that epiphytic networks are more complex than endophytic, and that the complexity and connectivity of these networks are partially correlated with the mentioned environmental cues. Our results indicate that humidity and solar radiation function as major environmental cues shaping the phyllosphere microbiome at the micro-scale (leaf compartment) and macro-scale (site). These findings could have practical implications for selecting and developing field-adapted microbes in the face of, and for predicting microbial invasions in response to global change.

microbiology↗

bioRxiv2022

Technical report on best practices for hybrid and long read de novo assembly of bacterial genomes utilizing Illumina and Oxford Nanopore Technologies reads

The emergence of commercial long read sequencing technologies in the 2010s and the concomitant development of new bioinformatics tools bears the potential of de novo genome assemblies of unprecedented contiguity and quality. However, until today these novel technologies suffer from high rates of sequencing errors. These may be overcome by using long and short reads in combination, in so called hybrid approaches, or by increasing the through-put and thereby the coverage of sequencing runs. In particular the latter will thereby increase the cost of the assembly inevitably. Herein, to-date long read and hybrid assemblers were tested on real whole genome sequencing Illumina and Oxford Nanopore Technologies read data sets and sub samples of these in order to elaborate a best practice for de novo assembly. The findings suggest that although long reads alone can be used to reconstruct complete and contiguous genomes, in particular the single-nucleotide and indel error rate remains high compared to hybrid approaches and that this can impact downstream applications such as variation discovery and gene prediction negatively.

bioinformatics↗

bioRxiv2022

Horizontal transfer of bacteriocin biosynthesis genes requires metabolic adaptation to improve compound production and cellular fitness

Biosynthetic gene clusters (BGCs) encoding the production of bacteriocins are widespread amongst bacterial isolates and are important genetic determinants of competitive fitness within a given habitat. Staphylococci produce a tremendous diversity of compounds and the corresponding BGCs are frequently associated with mobile genetic elements, suggesting gain and loss of biosynthetic capacity. Pharmaceutical biology has shown that compound production in heterologous hosts is often challenging and many BGC recipients produce initially low compound amounts or show reduced growth rates. To assess whether transfer of BGCs between closely related S. aureus strains can be instantly effective or requires elaborate metabolic adaptation, we investigated the intra species transfer of a BGC encoding the ribosomally synthesized and post-translationally modified peptide (RiPP) micrococcin P1 (MP1). We found that acquisition of the BGC by S. aureus RN4220 enabled immediate MP1 production but also imposed a metabolic burden, which was relieved after prolonged cultivation by adaptive mutation. We used a multiomics approach to study this phenomenon and found adaptive evolution to select for strains with increased activity of the tricarboxylic acid cycle (TCA), which enhanced metabolic fitness and levels of compound production. Metabolome analysis revealed increases of central metabolites including citrate and -ketoglutarate in the adapted strain, suggesting metabolic adaptation to overcome the BGC-associated growth defects. Our results indicate that BCG acquisition requires genetic and metabolic predispositions allowing the integration of bacteriocin production into the cellular metabolism. Inappropriate metabolic characteristics of recipients can entail physiological burdens, negatively impacting the competitive fitness of recipients within natural bacterial communities. ImportanceHuman microbiomes are critically associated with human health and disease. Importantly, pathogenic bacteria can hide in human associated communities and can cause disease when the composition of the community becomes dysbalanced. Bacteriocin producing commensals are able to displace pathogens from microbial communities, suggesting that their targeted introduction in human microbiomes might prevent pathogen colonisation and infection. However, in view of future probiotic approaches, strains are needed that produce high levels of bioactive compounds and retain cellular fitness within mixed bacterial communities. Our work offers insights into the metabolic burdens associated with the production of the bacteriocin micrococcin P1 and highlights evolutionary strategies that increase cellular fitness in the context of production. Most likely metabolic adaptations are broadly relevant for bacteriocin producers and need to be considered for the future development of effective microbiome editing strategies.

microbiology↗

bioRxiv2022

Prokaryotic phospholipid translocation by ubiquitous PplT domain proteins

Flippase proteins exchanging phospholipids between the cytoplasmic membrane leaflets have been identified in Eukaryotes but remained largely unknown in Prokaryotes. Only MprF proteins that synthesize aminoacyl phospholipids in some bacteria have been found to contain a domain that translocates the produced lipids. We show here that this domain, which we named prokaryotic phospholipid translocator (PplT), is widespread in Bacteria and Archaea, encoded as a separate protein or fused to different types of enzymes. We also demonstrate that the Escherichia coli PplT protein interacts with many phospholipid-synthetic enzymes and deletion of pplT impaired bacterial growth, which supports its potential role in membrane lipid metabolism. PplT domain proteins may be general prokaryotic lipid flippases with critical roles in cellular homeostasis.

microbiology↗

bioRxiv2020

DamageProfiler: Fast damage pattern calculation for ancient DNA

In ancient DNA research, the authentication of ancient samples based on specific features remains a crucial step in data analysis. Because of this central importance, researchers lacking deeper programming knowledge should be able to run a basic damage authentication analysis. Such software should be user-friendly and easy to integrate into an analysis pipeline. Here, we present DamageProfiler, a Java based, stand-alone software to determine damage patterns in ancient DNA. The results are provided in various file formats and plots for further processing. DamageProfiler has an intuitive graphical as well as command line interface that allows the tool to be easily embedded into an analysis pipeline.

bioinformatics↗