Description of Staphylococcal Strains from Straw-Coloured Fruit Bat (Eidolon helvum) and Diamond Firetail (Stagonopleura guttata) and a Review of their Phylogenetic Relationships to Other Staphylococci

The phylogenetic tree of the Staphylococcus aureus complex consists of several distinct clades and the majority of human and veterinary S. aureus isolates form one large clade. In addition, two divergent clades have recently been described as separate species. One was named Staphylococcus argenteus, due to the lack of the “golden” pigment staphyloxanthin. The second one is S. schweitzeri, found in humans and animals from Central and West Africa. In late 2021, two additional species, S. roterodami and S. singaporensis, have been described from clinical samples from Southeast Asia. In the present study, isolates and their genome sequences from wild Straw-coloured fruit bats (Eidolon helvum) and a Diamond firetail (Stagonopleura guttata, an estrildid finch) kept in a German aviary are described. The isolates possessed staphyloxanthin genes and were closer related to S. argenteus and S. schweitzeri than to S. aureus. Phylogenetic analysis revealed that they were nearly identical to both, S. roterodami and S. singaporensis. We propose considering the study isolates, the recently described S. roterodami and S. singaporensis as well as some Chinese strains with MLST profiles stored in the PubMLST database as different clonal complexes within one new species. According to the principle of priority we propose it should be named S. roterodami. This species is more widespread than previously believed, being observed in West Africa, Southeast Asia and Southern China. It has a zoonotic connection to bats and has been shown to be capable of causing skin and soft tissue infections in humans. It is positive for staphyloxanthin, and it could be mis-identified as S. aureus (or S. argenteus) using routine procedures. However, it can be identified based on distinct MLST alleles, and “S. aureus” sequence types ST2470, ST3135, ST3952, ST3960, ST3961, ST3963, ST3965, ST3980, ST4014, ST4075, ST4076, ST4185, ST4326, ST4569, ST6105, ST6106, ST6107, ST6108, ST6109, ST6999 and ST7342 belong to this species.

Characterisation and Molecular Analysis of an Unusual Chimeric Methicillin Resistant Staphylococcus Aureus Strain and its Bacteriophages

In the context of microarray-based epidemiological typing of the clonal organism Staphylococcus aureus/MRSA, a strain was identified that did not belong to known clonal complexes. The molecular analysis by microarray-based typing yielded signals suggesting that it was a mosaic or hybrid strain of two lineages. To verify this result, the isolate was sequenced with both, short-read Illumina and long-read Nanopore technologies and analysed in detail. This supported the hypothesis that the genome of this strain, ST6610-MRSA-IVg comprised of segments originating from two different clonal complexes (CC). While the backbone of the strain’s genome, i.e., roughly 2 megabases, belongs to CC8, a continuous insert of 894 kb (approx. 30% of the genome) originated from CC140. Beside core genomic markers in the normal succession and orientation, this insert also included the mecA gene, coding for PbP2a and causing methicillin resistance, localised on an SCCmec IVg element. This particular SCCmec type was also previously observed in CC140 MRSA from African countries. A second conspicuous observation was the presence of the trimethoprim resistance gene dfrG within on a prophage that occupied an attachment site normally used by Panton-Valentine Leucocidin phages. This observation could indicate a role of large-scale chromosomal recombination in the evolution of S. aureus as well as a role of phages in the dissemination of antibiotic resistance genes.

Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function

Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.

EpiDope: a deep neural network for linear B-cell epitope prediction

MOTIVATION

By binding to specific structures on antigenic proteins, the so-called epitopes, B-cell antibodies can neutralize pathogens. The identification of B-cell epitopes is of great value for the development of specific serodiagnostic assays and the optimization of medical therapy. However, identifying diagnostically or therapeutically relevant epitopes is a challenging task that usually involves extensive laboratory work. In this study, we show that the time, cost and labor-intensive process of epitope detection in the lab can be significantly reduced using in silico prediction.

RESULTS

Here, we present EpiDope, a python tool which uses a deep neural network to detect linear B-cell epitope regions on individual protein sequences. With an area under the curve between 0.67 ± 0.07 in the receiver operating characteristic curve, EpiDope exceeds all other currently used linear B-cell epitope prediction tools. Our software is shown to reliably predict linear B-cell epitopes of a given protein sequence, thus contributing to a significant reduction of laboratory experiments and costs required for the conventional approach.

AVAILABILITYAND IMPLEMENTATION

EpiDope is available on GitHub (http://github.com/mcollatz/EpiDope).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A comprehensive annotation and differential expression analysis of short and long non-coding RNAs in 16 bat genomes

Although bats are increasingly becoming the focus of scientific studies due to their unique properties, these exceptional animals are still among the least studied mammals. Assembly quality and completeness of bat genomes vary a lot and especially non-coding RNA (ncRNA) annotations are incomplete or simply missing. Accordingly, standard bioinformatics pipelines for gene expression analysis often ignore ncRNAs such as microRNAs or long antisense RNAs. The main cause of this problem is the use of incomplete genome annotations. We present a complete screening for ncRNAs within 16 bat genomes. NcRNAs affect a remarkable variety of vital biological functions, including gene expression regulation, RNA processing, RNA interference and, as recently described, regulatory processes in viral infections. Within all investigated bat assemblies, we annotated 667 ncRNA families including 162 snoRNAs and 193 miRNAs as well as rRNAs, tRNAs, several snRNAs and lncRNAs, and other structural ncRNA elements. We validated our ncRNA candidates by six RNA-Seq data sets and show significant expression patterns that have never been described before in a bat species on such a large scale. Our annotations will be usable as a resource (rna.uni-jena.de/supplements/bats) for deeper studying of bat evolution, ncRNAs repertoire, gene expression and regulation, ecology and important host–virus interactions.

Massive Effect on LncRNAs in Human Monocytes During Fungal and Bacterial Infections and in Response to Vitamins A and D

Mycoses induced by C.albicans or A.fumigatus can cause important host damage either by deficient or exaggerated immune response. Regulation of chemokine and cytokine signaling plays a crucial role for an adequate inflammation, which can be modulated by vitamins A and D. Non-coding RNAs (ncRNAs) as transcription factors or cis-acting antisense RNAs are known to be involved in gene regulation. However, the processes during fungal infections and treatment with vitamins in terms of therapeutic impact are unknown. We show that in monocytes both vitamins regulate ncRNAs involved in amino acid metabolism and immune system processes using comprehensive RNA-Seq analyses. Compared to protein-coding genes, fungi and bacteria induced an expression change in relatively few ncRNAs, but with massive fold changes of up to 4000. We defined the landscape of long-ncRNAs (lncRNAs) in response to pathogens and observed variation in the isoforms composition for several lncRNA following infection and vitamin treatment. Most of the involved antisense RNAs are regulated and positively correlated with their sense protein-coding genes. We investigated lncRNAs with stimulus specific immunomodulatory activity as potential marker genes: LINC00595, SBF2-AS1 (A.fumigatus) and RP11-588G21.2, RP11-394l13.1 (C.albicans) might be detectable in the early phase of infection and serve as therapeutic targets in the future.