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In the present work, two complete genome sequences of SARS-CoV-2 were obtained from nasal swab samples of Tunisian SARS-CoV-2 PCR-positive patients using nanopore sequencing. The virus genomes of two of the patients examined, a Tunisian soldier returning from a mission in Morocco and a member of another Tunisian family, showed significant differences in analyses of the total genome and single nucleotide polymorphisms (SNPs). Phylogenetic relationships with known SARS-CoV-2 genomes in the African region, some European and Middle Eastern countries and initial epidemiological conclusions indicate that the introduction of SARS-CoV-2 into Tunisia from two independent sources was travel-related.

Q (query) fever is an infectious zoonotic disease caused by the Gram-negative bacterium Coxiella burnetii. Although the disease has been studied for decades, it still represents a threat due to sporadic outbreaks across farms in Europe. The absence of a central platform for Coxiella typing data management is an important epidemiological gap that is relevant in the case of an outbreak. To fill this gap, we have designed and implemented an online, open-source, web-based platform called CoxBase (https://coxbase.q-gaps.de). This platform includes a database that holds genotyping information on more than 400 Coxiella isolates alongside metadata that annotate them. We have also implemented features for in silico genotyping of completely or minimally assembled Coxiella sequences using five different typing methods, querying of existing isolates, visualization of isolate geodata via aggregation on a world map, and submission of new isolates. We tested our in silico typing method on 50 Coxiella genomes downloaded from the RefSeq database, and we successfully genotyped all genomes except for cases where the sequence quality was poor. We identified new spacer sequences using our implementation of the multispacer sequence typing (MST) in silico typing method and established adaA gene phenotypes for all 50 genomes as well as their plasmid types. IMPORTANCE Q fever is a zoonotic disease that is a source of active epidemiological concern due to its persistent threat to public health. In this project, we have identified areas in the field of Coxiella research, especially regarding public health and genomic analysis, where there is an inadequacy of resources to monitor, organize, and analyze genomic data from C. burnetii. Subsequently, we have created an open, web-based platform that contains epidemiological information, genome typing functions comprising all the available Coxiella typing methods, and tools for isolate data discovery and visualization that could help address the above-mentioned challenges. This is the first platform to combine all disparate genotyping systems for Coxiella burnetii as well as metadata assets with tools for genomic comparison and analyses. This platform is a valuable resource for laboratory researchers as well as research epidemiologists interested in investigating the relatedness or dissimilarity among C. burnetii strains.

The anthrax pathogen Bacillus anthracis poses a significant threat to human health. Identification of B. anthracis is challenging because of the bacterium’s close genetic relationship to other Bacillus cereus group species. Thus, molecular detection is founded on species-specific PCR targeting single-copy genes. Here, we validated a previously recognized multi-copy target, a species-specific single nucleotide polymorphism (SNP) present in 2–5 copies in every B. anthracis genome analyzed. For this, a hydrolysis probe-based real-time PCR assay was developed and rigorously tested. The assay was specific as only B. anthracis DNA yielded positive results, was linear over 9 log10 units, and was sensitive with a limit of detection (LoD) of 2.9 copies/reaction. Though not exhibiting a lower LoD than established single-copy PCR targets (dhp61 or PL3), the higher copy number of the B. anthracis–specific 16S rRNA gene alleles afforded ≤2 unit lower threshold (Ct) values. To push the detection limit even further, the assay was adapted for reverse transcription PCR on 16S rRNA transcripts. This RT-PCR assay was also linear over 9 log10 units and was sensitive with an LoD of 6.3 copies/reaction. In a dilution series of experiments, the 16S RT-PCR assay achieved a thousand-fold higher sensitivity than the DNA-targeting assays. For molecular diagnostics, we recommend a real-time RT-PCR assay variant in which both DNA and RNA serve as templates (thus, no requirement for DNase treatment). This can at least provide results equaling the DNA-based implementation if no RNA is present but is superior even at the lowest residual rRNA concentrations.

The anthrax pathogen Bacillus anthracis poses a significant threat to human health. Identification of B. anthracis is challenging because of the bacterium’s close genetic relationship to other Bacillus cereus group species. Thus, molecular detection is founded on species-specific PCR targeting single-copy genes. Here, we validated a previously recognized multi-copy target, a species-specific SNP present in 2-5 copies in every B. anthracis genome analyzed. For this, a hydrolysis probe-based real time PCR assay was developed and rigorously tested. The assay was specific as only B. anthracis DNA yielded positive results, was linear over 9 log10 units and was sensitive with a limit of detection (LoD) of 2.9 copies/reaction. Though not exhibiting a lower LoD than established single copy PCR targets (dhp61 or PL3), the higher copy number of the B. anthracis–specific 16S rRNA gene allele afforded ≤2 unit lower threshold (Ct) values. To push the detection limit even further, the assay was adapted for reverse transcription PCR on 16S rRNA transcripts. This RT-PCR assay was also linear over 9 log10 units and was sensitive with a LoD of 6.3 copies/reaction.In a dilution-series of experiments, the 16S RT-PCR assay achieved a thousand-fold higher sensitivity than the DNA-targeting assays. For molecular diagnostics, we recommend a real time RT-PCR assay variant in which both DNA and RNA serve as templates (thus, no requirement for DNase treatment). This will at least provide results equaling the DNA-based implementation if no RNA is present but will be superior even at the lowest residual rRNA concentrations.

Analysis of 16S rRNA (rRNA) genes provides a central means of taxonomic classification of bacterial species. Based on presumed sequence identity among species of the Bacillus cereus sensu lato group, the 16S rRNA genes of B. anthracis have been considered unsuitable for diagnosis of the anthrax pathogen. With the recent identification of a single nucleotide polymorphism in some 16S rRNA gene copies, specific identification of B. anthracis becomes feasible. Here, we designed and evaluated a set of in situ, in vitro, and in silico assays to assess the unknown 16S state of B. anthracis from different perspectives. Using a combination of digital PCR, fluorescence in situ hybridization, long-read genome sequencing, and bioinformatics, we were able to detect and quantify a unique 16S rRNA gene allele of B. anthracis (16S-BA-allele). This allele was found in all available B. anthracis genomes and may facilitate differentiation of the pathogen from any close relative. Bioinformatics analysis of 959 B. anthracis SRA data sets inferred that abundances and genomic arrangements of the 16S-BA-allele and the entire rRNA operon copy numbers differ considerably between strains. Expression ratios of 16S-BA-alleles were proportional to the respective genomic allele copy numbers. The findings and experimental tools presented here provide detailed insights into the intra- and intergenomic diversity of 16S rRNA genes and may pave the way for improved identification of B. anthracis and other pathogens with diverse rRNA operons. IMPORTANCE For severe infectious diseases, precise pathogen detection is crucial for antibiotic therapy and patient survival. Identification of Bacillus anthracis, the causative agent of the zoonosis anthrax, can be challenging when querying specific nucleotide sequences such as in small subunit rRNA (16S rRNA) genes, which are commonly used for typing of bacteria. This study analyzed on a broad genomic scale a cryptic and hitherto underappreciated allelic variant of the bacterium’s 16S rRNA genes and their transcripts using a set of in situ, in vitro, and in silico assays and found significant intra- and intergenomic heterogeneity in the distribution of the allele and overall rRNA operon copy numbers. This allelic variation was uniquely species specific, which enabled sensitive pathogen detection on both DNA and transcript levels. The methodology used here is likely also applicable to other pathogens that are otherwise difficult to discriminate from their less harmful relatives.

A number of RT-qPCR assays for the detection of SARS-CoV-2 have been published and are listed by the WHO as recommended assays. Furthermore, numerous commercial assays with undisclosed primer and probe sequences are on the market. As the SARS-CoV-2 pandemic progresses, the virus accrues mutations, which in some cases – as seen with the B.1.1.7 variant – can outperform and push back other strains of SARS-CoV-2. If mutations occur in primer or probe binding sites, this can impact RT-qPCR results and impede SARS-CoV-2 diagnostics. Here we tested the effect of primer mismatches on RT-qPCR performance in vitro using synthetic mismatch in vitro transcripts. The effects of the mismatches ranged from a shift in ct values from −0.13 to +7.61. Crucially, we found that a mismatch in the forward primer has a more detrimental effect for PCR performance than a mismatch in the reverse primer. Furthermore, we compared the performance of the original Charité RdRP primer set, which has several ambiguities, with a primer version without ambiguities and found that without ambiguities the ct values are ca. 3 ct lower. Finally, we investigated the shift in ct values observed with the Seegene Allplex kit with the B.1.1.7 SARS-CoV-2 variant and found a three-nucleotide mismatch in the forward primer of the N target.

Controlling and monitoring the still ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic regarding geographical distribution, evolution, and emergence of new mutations of the SARS-CoV-2 virus is only possible due to continuous next-generation sequencing (NGS) and sharing sequence data worldwide. Efficient sequencing strategies enable the retrieval of increasing numbers of high-quality, full-length genomes and are, hence, indispensable. Two opposed enrichment methods, tiling multiplex PCR and sequence hybridization by bait capture, have been established for SARS-CoV-2 sequencing and are both frequently used, depending on the quality of the patient sample and the question at hand. Here, we focused on the evaluation of the sequence hybridization method by studying five commercially available sequence capture bait panels with regard to sensitivity and capture efficiency. We discovered the SARS-CoV-2-specific panel of Twist Bioscience to be the most efficient panel, followed by two respiratory panels from Twist Bioscience and Illumina, respectively. Our results provide on the one hand a decision basis for the sequencing community including a computation for using the full capacity of the flow cell and on the other hand potential improvements for the manufacturers. IMPORTANCE Sequencing the genomes of the circulating SARS-CoV-2 strains is the only way to monitor the viral spread and evolution of the virus. Two different approaches, namely, tiling multiplex PCR and sequence hybridization by bait capture, are commonly used to fulfill this task. This study describes for the first time a combined approach of droplet digital PCR (ddPCR) and NGS to evaluate five commercially available sequence capture panels targeting SARS-CoV-2. In doing so, we were able to determine the most sensitive and efficient capture panel, distinguish the mode of action of the various bait panels, and compute the number of read pairs needed to recover a high-quality full-length genome. By calculating the minimum number of read pairs needed, we are providing optimized flow cell loading conditions for all sequencing laboratories worldwide that are striving for maximizing sequencing output and simultaneously minimizing time, costs, and sequencing resources.

Summary The Flexible Taxonomy Database framework provides a method for modification and merging official and custom taxonomic databases to create improved databases. Using such databases will increase accuracy and precision of existing methods to classify sequence reads. Availability and implementation Source code is freely available at https://github.com/FOI-Bioinformatics/flextaxd and installable through Bioconda.

The zoonosis anthrax caused by the bacterium Bacillus anthracis has a broad geographical distribution. Active enzootic areas are typically located away from central and northern Europe where cases of the disease occur only sporadically and in limited numbers. In contrast, a few out of the 64 districts of Bangladesh are hyper-endemic for anthrax and there the disease causes major losses in live-stock. In this study we genotyped eight strains of B. anthracis collected from the districts of Sirajganj and Tangail in 2013. All these strains belonged to canSNP group A.Br.001/002 Sterne differing only in a few of 31 tandem-repeat (MLVA)-markers. Whole genome sequences were obtained from five of these strains and compared with genomic information of B. anthracis strains originating from various geographical locations. Characteristic signatures were detected defining two “Bangladesh” clusters potentially useful for rapid molecular epidemiology. From this data high-resolution PCR assays were developed and subsequently tested on additional isolates from Bangladesh and Central Europe. Remarkably, this comparative genomic analysis focusing on SNP-discovery revealed a close genetic relationship between these strains from Bangladesh and historic strains collected between 1991 and 2008 in The Netherlands and Germany, respectively. Possible explanations for these phylogenetic relationships are discussed.

We report the draft genome sequence of clindamycin-resistant Bacillus safensis strain Ingolstadt isolated from a patient with bacterial colonization after heart surgery. The draft genome comprises 3.75 Mbp and harbors 3,793 predicted protein-encoding genes and a small plasmid.

Motivation: Accurate automatic assignment of protein functions remains a challenge for genome annotation. We have developed and compared the automatic annotation of four bacterial genomes employing a 5-fold cross-validation procedure and several machine learning methods. Results: The analyzed genomes were manually annotated with FunCat categories in MIPS providing a gold standard. Features describing a pair of sequences rather than each sequence alone were used. The descriptors were derived from sequence alignment scores, InterPro domains, synteny information, sequence length and calculated protein properties. Following training we scored all pairs from the validation sets, selected a pair with the highest predicted score and annotated the target protein with functional categories of the prototype protein. The data integration using machine-learning methods provided significantly higher annotation accuracy compared to the use of individual descriptors alone. The neural network approach showed the best performance. The descriptors derived from the InterPro domains and sequence similarity provided the highest contribution to the method performance. The predicted annotation scores allow differentiation of reliable versus non-reliable annotations. The developed approach was applied to annotate the protein sequences from 180 complete bacterial genomes. Availability: The FUNcat Annotation Tool (FUNAT) is available on-line as Web Services at http://mips.gsf.de/proj/funat Contact: i.tetko@gsf.de Supplementary information: Supplementary data are available at Bioinformatics online.

Due to their economic relevance, the study of plant pathogen interactions is of importance. However, elucidating these interactions and their underlying molecular mechanisms remains challenging since both host and pathogen need to be fully genetically accessible organisms. Here we present milestones in the establishment of a new biotrophic model pathosystem: Ustilago bromivora and Brachypodium sp. We provide a complete toolset, including an annotated fungal genome and methods for genetic manipulation of the fungus and its host plant. This toolset will enable researchers to easily study biotrophic interactions at the molecular level on both the pathogen and the host side. Moreover, our research on the fungal life cycle revealed a mating type bias phenomenon. U. bromivora harbors a haplo-lethal allele that is linked to one mating type region. As a result, the identified mating type bias strongly promotes inbreeding, which we consider to be a potential speciation driver. DOI: http://dx.doi.org/10.7554/eLife.20522.001, eLife digest Fungi cause many diseases in plants, and reduce the yield of important crops like wheat, corn and rice – all of which belong to the family of grasses. Much research into how disease-causing fungi infect plants will look at a given fungus that infects a specific plant in order to understand plant diseases in general. Over the years, scientists have generated suites of research tools to study these pairs of fungi and plants. However, many of these organism pairs (often called “model pathosystems”) have drawbacks when it comes to research in the laboratory, either on the side of the fungus or the side of plant. Brachypodium is a small grass that grows quickly and, unlike crop plants, it grows well in the laboratory. These characteristics make Brachypodium a promising model organism for studying many aspects of plant biology. Recently, a fungus called Ustilago bromivora – which is related to a fungus that infects corn – was reported to infect Brachypodium. This raised the question: could this fungus and this small grass become a new model pathosystem? Rabe, Bosch et al. set out to answer this question and now provide a toolkit that will help to establish U. bromivora and Brachypodium as a new model pathosystem. In all of U. bromivora’s close relatives, two compatible strains must meet and mate before the fungus can infect the plant; first Rabe, Bosch et al. confirmed that this is also the case for U. bromivora. Studying the life cycle of the U. bromivora fungus also unexpectedly revealed that while both mating partners are needed to infect the plant, only one of the strains survives outside of the plant after the infection. This phenomenon, referred to as a “mating type bias”, has been described for a few other related fungi. Next, Rabe, Bosch et al. conducted a genetic screen and identified two compatible strains that can grow without the plant as yeast-like cells. This means that these cells can be manipulated genetically, and indeed protocols to grow and genetically engineer the fungus and plant to address different research questions are included in the toolkit as well. Other new tools include the complete genetic sequence of the fungus with all its genes annotated, and a dataset of which genes are active in U. bromivora growing yeast-like in liquid culture versus those active when the fungus grows as a pathogen inside the plant. Together these new tools and datasets will provide a foundation to study different aspects of the interactions between grasses and disease-causing fungi. This in turn may lead to new methods to reduce fungal growth and reduce yield losses caused by fungal diseases in crop plants. Finally, the discovery that U. bromivora shows a mating type bias could provide a starting point for future studies into sexual reproduction in fungi and how new species arise. DOI: http://dx.doi.org/10.7554/eLife.20522.002

Coxiella burnetii strain AuQ01 was isolated from the serum of an Australian acute Q fever patient and represents the first whole genome from this historical Q fever country. This new genome shows distinct differences from existing genomic data and will enhance the understanding of this query pathogen.