Word entropy-based approach to detect highly variable genetic markers for bacterial genotyping

Genotyping methods are used to distinguish bacterial strains from one species. Thus, distinguishing bacterial strains on a global scale, between countries or local districts in one country is possible. However, the highly selected bacterial populations (e.g. local populations in hospital) are typically closely related and low diversified. Therefore, currently used typing methods are not able to distinguish individual strains from each other. Here, we present a novel pipeline to detect highly variable genetic segments for genotyping a closely related bacterial population. The method is based on a degree of disorder in analyzed sequences that can be represented by sequence entropy. With the identified variable sequences, it is possible to find out transmission routes and sources of highly virulent and multiresistant strains. The proposed method can be used for any bacterial population, and due to its whole genome range, also noncoding regions are examined

First Complete Genome of the Thermophilic Polyhydroxyalkanoates Producing Bacterium Schlegelella thermodepolymerans DSM 15344

Schlegelella thermodepolymerans is a moderately thermophilic bacterium capable of producing polyhydroxyalkanoates (PHA) – biodegradable polymers representing an alternative to conventional plastics. Here, we present the first complete genome of the type strain S. thermodepolymerans DSM 15344 that was assembled by hybrid approach using both, long (Oxford Nanopore) and short (Illumina) reads. The genome consists of a single 3,858,501bp long circular chromosome with GC content of 70.3%. Genome annotation identified 3,650 genes in total while 3,598 open reading frames belonged to protein coding genes. Functional annotation of the genome and division of genes into clusters of orthologous groups (COG) revealed a relatively high number of 1,013 genes with unknown function or unknown COG, which reflects the fact that only a little is known about thermophilic PHA producing bacteria on a genome level. On the other hand, 270 genes involved in energy conversion and production were detected. This group covers genes involved in catabolic processes which suggests capability of S. thermodepolymerans DSM 15344 to utilize and biotechnologically convert various substrates such as lignocellulose-based saccharides, glycerol, or lipids. Based on the knowledge of its genome, it can be stated that S. thermodepolymerans DSM 15344 is a very interesting, metabolically versatile bacterium with great biotechnological potential

Cryptococcal Pneumonia: An Unusual Complication in a COVID-19 Patient

Cryptococcal superinfection is a rare but potentially fatal complication, especially if its detection and subsequent treatment are delayed. Histopathological findings of pulmonary parenchyma from a deceased patient with these complications were acquired. Quite interestingly, only a minimal inflammatory reaction could be seen in an individual with no previously known immune suppression, indicating a disturbance of the immune system. This finding was well in concordance with the described changes in cellular immunity in COVID-19. We report the case of a 60 year old male with critical coronavirus disease 2019 (COVID-19) complicated by cryptococcal pneumonia and multiorgan failure. Both X-ray and CT scans revealed lung infiltrates corresponding with COVID-19 infection early after the onset of symptoms. Despite receiving standard treatment, the patient progressed into multiple organ failure, requiring mechanical ventilation, circulatory support, and haemodialysis. Cryptococcus neoformans was detected by subsequent BAL, and specific antifungal treatment was instituted. His clinical status deteriorated despite all treatment, and he died of refractory circulatory failure after 21 days from hospital admission. Histopathological findings confirmed severe diffuse alveolar damage (DAD) caused by COVID-19 and cryptococcal pneumonia. Timely diagnosis of cryptococcal superinfection may be challenging; therefore, PCR panels detecting even uncommon pathogens should be implemented while taking care of critical COVID-19 patients

Using deep learning for gene detection and classification in raw nanopore signals

Recently, nanopore sequencing has come to the fore as library preparation is rapid and simple, sequencing can be done almost anywhere, and longer reads are obtained than with next-generation sequencing. The main bottleneck still lies in data postprocessing which consists of basecalling, genome assembly, and localizing significant sequences, which is time consuming and computationally demanding, thus prolonging delivery of crucial results for clinical practice. Here, we present a neural network-based method capable of detecting and classifying specific genomic regions already in raw nanopore signals—squiggles. Therefore, the basecalling process can be omitted entirely as the raw signals of significant genes, or intergenic regions can be directly analyzed, or if the nucleotide sequences are required, the identified squiggles can be basecalled, preferably to others. The proposed neural network could be included directly in the sequencing run, allowing real-time squiggle processing

Diversity and Evolution of Clostridium beijerinckii and Complete Genome of the Type Strain DSM 791T

Clostridium beijerinckii is a relatively widely studied, yet non-model, bacterium. While 246 genome assemblies of its various strains are available currently, the diversity of the whole species has not been studied, and it has only been analyzed in part for a missing genome of the type strain. Here, we sequenced and assembled the complete genome of the type strain Clostridium beijerinckii DSM 791T, composed of a circular chromosome and a circular megaplasmid, and used it for a comparison with other genomes to evaluate diversity and capture the evolution of the whole species. We found that strains WB53 and HUN142 were misidentified and did not belong to the Clostridium beijerinckii species. Additionally, we filtered possibly misassembled genomes, and we used the remaining 237 high-quality genomes to define the pangenome of the whole species. By its functional annotation, we showed that the core genome contains genes responsible for basic metabolism, while the accessory genome has genes affecting final phenotype that may vary among different strains. We used the core genome to reconstruct the phylogeny of the species and showed its great diversity, which complicates the identification of particular strains, yet hides possibilities to reveal hitherto unreported phenotypic features and processes utilizable in biotechnology

Application of mini-MLST and whole genome sequencing in low diversity hospital extended-spectrum beta-lactamase producing Klebsiella pneumoniae population

Studying bacterial population diversity is important to understand healthcare associated infections’ epidemiology and has a significant impact on dealing with multidrug resistant bacterial outbreaks. We characterised the extended-spectrum beta-lactamase producing K. pneumoniae (ESBLp KPN) population in our hospital using mini-MLST. Then we used whole genome sequencing (WGS) to compare selected isolates belonging to the most prevalent melting types (MelTs) and the colonization/infection pair isolates collected from one patient to study the ESBLp KPN population’s genetic diversity. A total of 922 ESBLp KPN isolates collected between 7/2016 and 5/2018 were divided into 38 MelTs using mini-MLST with only 6 MelTs forming 82.8% of all isolates. For WGS, 14 isolates from the most prominent MelTs collected in the monitored period and 10 isolates belonging to the same MelTs collected in our hospital in 2014 were randomly selected. Resistome, virulome and ST were MelT specific and stable over time. A maximum of 23 SNV per core genome and 58 SNV per core and accessory genome were found. To determine the SNV relatedness cut-off values, 22 isolates representing colonization/infection pair samples obtained from 11 different patients were analysed by WGS with a maximum of 22 SNV in the core genome and 40 SNV in the core and accessory genome within pairs. The mini-MLST showed its potential for real-time epidemiology in clinical practice. However, for outbreak evaluation in a low diversity bacterial population, mini-MLST should be combined with more sensitive methods like WGS. Our findings showed there were only minimal differences within the core and accessory genome in the low diversity hospital population and gene based SNV analysis does not have enough discriminatory power to differentiate isolate relatedness. Thus, intergenic regions and mobile elements should be incorporated into the analysis scheme to increase discriminatory power

Rapid high-resolution melting genotyping scheme for Escherichia coli based on MLST derived single nucleotide polymorphisms

Routinely used typing methods including MLST, rep-PCR and whole genome sequencing (WGS) are time-consuming, costly, and often low throughput. Here, we describe a novel mini-MLST scheme for Eschericha coli as an alternative method for rapid genotyping. Using the proposed mini-MLST scheme, 10,946 existing STs were converted into 1,038 Melting Types (MelTs). To validate the new mini-MLST scheme, in silico analysis was performed on 73,704 strains retrieved from EnteroBase resulting in discriminatory power D = 0.9465 (CI 95% 0.9726-0.9736) for mini-MLST and D = 0.9731 (CI 95% 0.9726-0.9736) for MLST. Moreover, validation on clinical isolates was conducted with a significant concordance between MLST, rep-PCR and WGS. To conclude, the great portability, efficient processing, cost-effectiveness, and high throughput of mini-MLST represents immense benefits, even when accompanied with a slightly lower discriminatory power than other typing methods. This study proved mini-MLST is an ideal method to screen and subgroup large sets of isolates and/or quick strain typing during outbreaks. In addition, our results clearly showed its suitability for prospective surveillance monitoring of emergent and high-risk E. coli clones'