Identification of Universally Applicable and Species-Specific Marker Peptides for Bacillus anthracis.

Anthrax is a zoonotic infection caused by the bacterium Bacillus anthracis (BA). Specific identification of this pathogen often relies on targeting genes located on two extrachromosomal plasmids, which represent the major pathogenicity factors of BA. However, more recent findings show that these plasmids have also been found in other closely related Bacillus species. In this study, we investigated the possibility of identifying species-specific and universally applicable marker peptides for BA. For this purpose, we applied a high-resolution mass spectrometry-based approach for 42 BA isolates. Along with the genomic sequencing data and by developing a bioinformatics data evaluation pipeline, which uses a database containing most of the publicly available protein sequences worldwide (UniParc), we were able to identify eleven universal marker peptides unique to BA. These markers are located on the chromosome and therefore, might overcome known problems, such as observable loss of plasmids in environmental species, plasmid loss during cultivation in the lab, and the fact that the virulence plasmids are not necessarily a unique feature of BA. The identified chromosomally encoded markers in this study could extend the small panel of already existing chromosomal targets and along with targets for the virulence plasmids, may pave the way to an even more reliable identification of BA using genomics- as well as proteomics-based techniques.

De Novo-Whole Genome Assembly of the Roborovski Dwarf Hamster (Phodopus roborovskii) Genome: An Animal Model for Severe/Critical COVID-19.

The Roborovski dwarf hamster Phodopus roborovskii belongs to the Phodopus genus, one of the seven within Cricetinae subfamily. Like other rodents such as mice, rats, or ferrets, hamsters can be important animal models for a range of diseases. Whereas the Syrian hamster from the genus Mesocricetus is now widely used as a model for mild-to-moderate coronavirus disease 2019, Roborovski dwarf hamster shows a severe-to-lethal course of disease upon infection with the novel human coronavirus severe acute respiratory syndrome coronavirus 2.

Key benefits of dexamethasone and antibody treatment in COVID-19 hamster models revealed by single-cell transcriptomics.

For coronavirus disease 2019 (COVID-19), effective and well-understood treatment options are still scarce. Since vaccine efficacy is challenged by novel variants, short-lasting immunity, and vaccine hesitancy, understanding and optimizing therapeutic options remains essential. We aimed at better understanding the effects of two standard-of-care drugs, dexamethasone and anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies, on infection and host responses. By using two COVID-19 hamster models, pulmonary immune responses were analyzed to characterize effects of single or combinatorial treatments. Pulmonary viral burden was reduced by anti-SARS-CoV-2 antibody treatment and unaltered or increased by dexamethasone alone. Dexamethasone exhibited strong anti-inflammatory effects and prevented fulminant disease in a severe disease model. Combination therapy showed additive benefits with both anti-viral and anti-inflammatory potency. Bulk and single-cell transcriptomic analyses confirmed dampened inflammatory cell recruitment into lungs upon dexamethasone treatment and identified a specifically responsive subpopulation of neutrophils, thereby indicating a potential mechanism of action. Our analyses confirm the anti-inflammatory properties of dexamethasone and suggest possible mechanisms, validate anti-viral effects of anti-SARS-CoV-2 antibody treatment, and reveal synergistic effects of a combination therapy, thus informing more effective COVID-19 therapies.

Temporal omics analysis in Syrian hamsters unravel cellular effector responses to moderate COVID-19.

In COVID-19, immune responses are key in determining disease severity. However, cellular mechanisms at the onset of inflammatory lung injury in SARS-CoV-2 infection, particularly involving endothelial cells, remain ill-defined. Using Syrian hamsters as a model for moderate COVID-19, we conduct a detailed longitudinal analysis of systemic and pulmonary cellular responses, and corroborate it with datasets from COVID-19 patients. Monocyte-derived macrophages in lungs exert the earliest and strongest transcriptional response to infection, including induction of pro-inflammatory genes, while epithelial cells show weak alterations. Without evidence for productive infection, endothelial cells react, depending on cell subtypes, by strong and early expression of anti-viral, pro-inflammatory, and T cell recruiting genes. Recruitment of cytotoxic T cells as well as emergence of IgM antibodies precede viral clearance at day 5 post infection. Investigating SARS-CoV-2 infected Syrian hamsters thus identifies cell type-specific effector functions, providing detailed insights into pathomechanisms of COVID-19 and informing therapeutic strategies.

Equine Herpesvirus Type 4 (EHV-4) Outbreak in Germany: Virological, Serological, and Molecular Investigations.

Equine herpesvirus type 4 (EHV-4) is enzootic in equine populations throughout the world. A large outbreak of EHV-4 respiratory infection occurred at a Standardbred horse-breeding farm in northern Germany in 2017. Respiratory illness was observed in a group of in-housed foals and mares, which subsequently resulted in disease outbreak. Out of 84 horses in the stud, 76 were tested and 41 horses were affected, including 20 foals, 10 stallions, and 11 mares. Virological investigations revealed the involvement of EHV-4 in all cases of respiratory illness, as confirmed by virus isolation, qPCR, and/or serological follow-up using virus neutralization test and peptide-specific ELISA. Among infected mares, 73% (8 out of 11) and their corresponding foals shed the virus at the same time. EHV-4 was successfully isolated from four animals (including one stallion and three foals), and molecular studies revealed a different restriction fragment length polymorphism (RFLP) profile in all four isolates. We determined the complete 144 kbp genome sequence of EHV-4 isolated from infected horses by next-generation sequencing and de novo assembly. Hence, EHV-4 is genetically stable in nature, different RFLP profiles, and genome sequences of the isolates, suggesting the involvement of more than one animal as a source of infection due to either true infection or reactivation from a latent state. In addition, epidemiological investigation revealed that stress caused by seasonal changes, management practices, routine equestrian activities, and exercises contributed as a multifactorial causation for disease outbreak. This study shows the importance of implementing stress alleviating measures and management practices in breeding farms in order to avoid immunosuppression and occurrence of disease.

SCORE: Smart Consensus Of RNA Expression-a consensus tool for detecting differentially expressed genes in bacteria.

SUMMARY: RNA-sequencing (RNA-Seq) is the current method of choice for studying bacterial transcriptomes. To date, many computational pipelines have been developed to predict differentially expressed genes from RNA-Seq data, but no gold-standard has been widely accepted. We present the Snakemake-based tool Smart Consensus Of RNA Expression (SCORE) which uses a consensus approach founded on a selection of well-established tools for differential gene expression analysis. This allows SCORE to increase the overall prediction accuracy and to merge varying results into a single, human-readable output. SCORE performs all steps for the analysis of bacterial RNA-Seq data, from read preprocessing to the overrepresentation analysis of significantly associated ontologies. Development of consensus approaches like SCORE will help to streamline future RNA-Seq workflows and will fundamentally contribute to the creation of new gold-standards for the analysis of these types of data. AVAILABILITY AND IMPLEMENTATION: https://github.com/SiWolf/SCORE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Rapid and Culture Free Identification of Francisella in Hare Carcasses by High-Resolution Tandem Mass Spectrometry Proteotyping.

Zoonotic pathogens that can be transmitted via food to humans have a high potential for large-scale emergencies, comprising severe effects on public health, critical infrastructures, and the economy. In this context, the development of laboratory methods to rapidly detect zoonotic bacteria in the food supply chain, including high-resolution mass spectrometry proteotyping are needed. In this work, an optimized sample preparation method for liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteome profiling was established for Francisella isolates, and a cluster analysis, as well as a phylogenetic tree, was generated to shed light on evolutionary relationships. Furthermore, this method was applied to tissues of infected hare carcasses from Germany. Even though the non-informative data outnumbered by a manifold the information of the zoonotic pathogen in the resulting proteome profiles, the standardized evaluation of MS data within an established automated analysis pipeline identified Francisella (F.) tularensis and, thus, could be, in principle, an applicable method to monitor food supply chains.

Fatal Elephant Endotheliotropic Herpesvirus Infection of Two Young Asian Elephants.

Elephant endotheliotropic herpesvirus (EEHV) can cause a devastating haemorrhagic disease in young Asian elephants worldwide. Here, we report the death of two young Asian elephants after suffering from acute haemorrhagic disease due to EEHV-1A infection. We detected widespread distribution of EEHV-1A in various organs and tissues of the infected elephants. Enveloped viral particles accumulated within and around cytoplasmic electron-dense bodies in hepatic endothelial cells were detected. Attempts to isolate the virus on different cell cultures showed limited virus replication; however, late viral protein expression was detected in infected cells. We further showed that glycoprotein B (gB) of EEHV-1A possesses a conserved cleavage site Arg-X-Lys/Arg-Arg that is targeted by the cellular protease furin, similar to other members of the Herpesviridae. We have determined the complete 180 kb genome sequence of EEHV-1A isolated from the liver by next-generation sequencing and de novo assembly. As virus isolation in vitro has been unsuccessful and limited information is available regarding the function of viral proteins, we have attempted to take the initial steps in the development of suitable cell culture system and virus characterization. In addition, the complete genome sequence of an EEHV-1A in Europe will facilitate future studies on the epidemiology and diagnosis of EEHV infection in elephants.

Guided Reconstruction of Full-Length Isoforms from Short Reads by CIDANE.

Alternative splicing allows genes to express isoforms with different coding or regulatory functions on demand. While short read deep sequencing technologies (RNA-seq) provide an immediate measurement of local splicing events, the phasing of these events along full-length isoforms requires the computational inference of long-range dependencies from short-range data points. We introduce CIDANE, a tool for the assembly and quantification of full-length isoforms from short read RNA-seq data. CIDANE bridges the gap between RNA quantification methods that rely on a complete annotation of a species' transcriptome, and transcript assembly methods that will detect novel isoforms at the cost of a lower accuracy.

High-performance liquid chromatography with electrospray ionization ion mobility spectrometry: Characterization, data management, and applications.

The combination of high-performance liquid chromatography and electrospray ionization ion mobility spectrometry facilitates the two-dimensional separation of complex mixtures in the retention and drift time plane. The ion mobility spectrometer presented here was optimized for flow rates customarily used in high-performance liquid chromatography between 100 and 1500 µL/min. The characterization of the system with respect to such parameters as the peak capacity of each time dimension and of the 2D spectrum was carried out based on a separation of a pesticide mixture containing 24 substances. While the total ion current chromatogram is coarsely resolved, exhibiting coelutions for a number of compounds, all substances can be separately detected in the 2D plane due to the orthogonality of the separations in retention and drift dimensions. Another major advantage of the ion mobility detector is the identification of substances based on their characteristic mobilities. Electrospray ionization allows the detection of substances lacking a chromophore. As an example, the separation of a mixture of 18 amino acids is presented. A software built upon the free mass spectrometry package OpenMS was developed for processing the extensive 2D data. The different processing steps are implemented as separate modules which can be arranged in a graphic workflow facilitating automated processing of data.

OpenMS: a flexible open-source software platform for mass spectrometry data analysis.

High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.

CIDANE: comprehensive isoform discovery and abundance estimation.

We present CIDANE, a novel framework for genome-based transcript reconstruction and quantification from RNA-seq reads. CIDANE assembles transcripts efficiently with significantly higher sensitivity and precision than existing tools. Its algorithmic core not only reconstructs transcripts ab initio, but also allows the use of the growing annotation of known splice sites, transcription start and end sites, or full-length transcripts, which are available for most model organisms. CIDANE supports the integrated analysis of RNA-seq and additional gene-boundary data and recovers splice junctions that are invisible to other methods. CIDANE is available at http://ccb.jhu.edu/software/cidane/.

The duplication-loss small phylogeny problem: from cherries to trees.

The reconstruction of the history of evolutionary genome-wide events among a set of related organisms is of great biological interest since it can help to reveal the genomic basis of phenotypes. The sequencing of whole genomes faciliates the study of gene families that vary in size through duplication and loss events, like transfer RNA. However, a high sequence similarity often does not allow one to distinguish between orthologs and paralogs. Previous methods have addressed this difficulty by taking into account flanking regions of members of a family independently. We go one step further by inferring the order of genes of (a set of) families for ancestral genomes by considering the order of these genes on sequenced genomes. We present a novel branch-and-cut algorithm to solve the two species small phylogeny problem in the evolutionary model of duplications and losses. On average, our implementation, DupLoCut, improves the running time of a recently proposed method in the experiments on six Vibrionaceae lineages by a factor of ∼200. Besides the mere improvement in running time, the efficiency of our approach allows us to extend our model from cherries of a species tree, that is, subtrees with two leaves, to the median of three species setting. Being able to determine the median of three species is of key importance to one of the most common approaches to ancestral reconstruction, and our experiments show that its repeated computation considerably reduces the number of duplications and losses along the tree both on simulated instances comprising 128 leaves and a set of Bacillus genomes. Furthermore, in our simulations we show that a reduction in cost goes hand in hand with an improvement of the predicted ancestral genomes. Finally, we prove that the small phylogeny problem in the duplication-loss model is NP-complete already for two species.

Antilope--a Lagrangian relaxation approach to the de novo peptide sequencing problem.

Peptide sequencing from mass spectrometry data is a key step in proteome research. Especially de novo sequencing, the identification of a peptide from its spectrum alone, is still a challenge even for state-of-the-art algorithmic approaches. In this paper, we present ANTILOPE, a new fast and flexible approach based on mathematical programming. It builds on the spectrum graph model and works with a variety of scoring schemes. ANTILOPE combines Lagrangian relaxation for solving an integer linear programming formulation with an adaptation of Yen's k shortest paths algorithm. It shows a significant improvement in running time compared to mixed integer optimization and performs at the same speed like other state-of-the-art tools. We also implemented a generic probabilistic scoring scheme that can be trained automatically for a data set of annotated spectra and is independent of the mass spectrometer type. Evaluations on benchmark data show that ANTILOPE is competitive to the popular state-of-the-art programs PepNovo and NovoHMM both in terms of runtime and accuracy. Furthermore, it offers increased flexibility in the number of considered ion types. ANTILOPE will be freely available as part of the open source proteomics library OpenMS.

MSSimulator: Simulation of mass spectrometry data.

Mass spectrometry coupled to liquid chromatography (LC-MS and LC-MS/MS) is commonly used to analyze the protein content of biological samples in large scale studies, enabling quantitation and identification of proteins and peptides using a wide range of experimental protocols, algorithms, and statistical models to analyze the data. Currently it is difficult to compare the plethora of algorithms for these tasks. So far, curated benchmark data exists for peptide identification algorithms but data that represents a ground truth for the evaluation of LC-MS data is limited. Hence there have been attempts to simulate such data in a controlled fashion to evaluate and compare algorithms. We present MSSimulator, a simulation software for LC-MS and LC-MS/MS experiments. Starting from a list of proteins from a FASTA file, the simulation will perform in-silico digestion, retention time prediction, ionization filtering, and raw signal simulation (including MS/MS), while providing many options to change the properties of the resulting data like elution profile shape, resolution and sampling rate. Several protocols for SILAC, iTRAQ or MS(E) are available, in addition to the usual label-free approach, making MSSimulator the most comprehensive simulator for LC-MS and LC-MS/MS data.