Rubrolone production by Dactylosporangium vinaceum: biosynthesis, modulation and possible biological function.

Rare actinomycetes are likely treasure troves for bioactive natural products, and it is therefore important that we enrich our understanding of biosynthetic potential of these relatively understudied bacteria. Dactylosporangium are a genus of such rare Actinobacteria that are known to produce a number of important antibacterial compounds, but for which there are still no fully assembled reference genomes, and where the extent of encoded biosynthetic capacity is not defined. Dactylosporangium vinaceum (NRRL B-16297) is known to readily produce a deep wine red-coloured diffusible pigment of unknown origin, and it was decided to define the chemical identity of this natural product pigment, and in parallel use whole genome sequencing and transcriptional analysis to lay a foundation for understanding the biosynthetic capacity of these bacteria. Results show that the produced pigment is made of various rubrolone conjugates, the spontaneous product of the reactive pre-rubrolone, produced by the bacterium. Genome and transcriptome analysis identified the highly expressed biosynthetic gene cluster (BGC) for pre-rubrolone. Further analysis of the fully assembled genome found it to carry 24 additional BGCs, of which the majority were poorly transcribed, confirming the encoded capacity of this bacterium to produce natural products but also illustrating the main bottleneck to exploiting this capacity. Finally, analysis of the potential environmental role of pre-rubrolone found it to react with a number of amine containing antibiotics, antimicrobial peptides and siderophores pointing to its potential role as a "minesweeper" of xenobiotic molecules in the bacterial environment. KEY POINTS: • D. vinaceum encodes many BGC, but the majority are transcriptionally silent. • Chemical screening identifies molecules that modulate rubrolone production. • Pre-rubrolone is efficient at binding and inactivating many natural antibiotics.

Use of whole-genome sequencing in the molecular investigation of care-associated HCoV-OC43 infections in a hematopoietic stem cell transplant unit.

BACKGROUND: While respiratory viral infections are recognized as a frequent cause of illness in hematopoietic stem cell transplantation (HSCT) recipients, HCoV-OC43 infections have rarely been investigated as healthcare-associated infections in this population. OBJECTIVES: In this report, HCoV-OC43 isolates collected from HSCT patients were retrospectively characterized to identify potential clusters of infection that may stand for a hospital transmission. STUDY DESIGN: Whole-genome and S gene sequences were obtained from nasal swabs using next-generation sequencing and phylogenetic trees were constructed. Similar identity matrix and determination of the most common ancestor were used to compare clusters of patient's sequences. Amino acids substitutions were analysed. RESULTS: Genotypes B, E, F and G were identified. Two clusters of patients were defined from chronological data and phylogenetic trees. Analyses of amino acids substitutions of the S protein sequences identified substitutions specific for genotype F strains circulating among European people. CONCLUSIONS: HCoV-OC43 may be implicated in healthcare-associated infections.

A complete protocol for whole-genome sequencing of virus from clinical samples: Application to coronavirus OC43.

Genome sequencing of virus has become a useful tool for better understanding of virus pathogenicity and epidemiological surveillance. Obtaining virus genome sequence directly from clinical samples is still a challenging task due to the low load of virus genetic material compared to the host DNA, and to the difficulty to get an accurate genome assembly. Here we introduce a complete sequencing and analyzing protocol called V-ASAP for Virus Amplicon Sequencing Assembly Pipeline. Our protocol is able to generate the viral dominant genome sequence starting from clinical samples. It is based on a multiplex PCR amplicon sequencing coupled with a reference-free analytical pipeline. This protocol was applied to 11 clinical samples infected with coronavirus OC43 (HcoV-OC43), and led to seven complete and two nearly complete genome assemblies. The protocol introduced here is shown to be robust, to produce a reliable sequence, and could be applied to other virus.

Large-Scale Modeling Approach Reveals Functional Metabolic Shifts during Hepatic Differentiation.

Being able to explore the metabolism of broad metabolizing cells is of critical importance in many research fields. This article presents an original modeling solution combining metabolic network and omics data to identify modulated metabolic pathways and changes in metabolic functions occurring during differentiation of a human hepatic cell line (HepaRG). Our results confirm the activation of hepato-specific functionalities and newly evidence modulation of other metabolic pathways, which could not be evidenced from transcriptomic data alone. Our method takes advantage of the network structure to detect changes in metabolic pathways that do not have gene annotations and exploits flux analyses techniques to identify activated metabolic functions. Compared to the usual cell-specific metabolic network reconstruction approaches, it limits false predictions by considering several possible network configurations to represent one phenotype rather than one arbitrarily selected network. Our approach significantly enhances the comprehensive and functional assessment of cell metabolism, opening further perspectives to investigate metabolic shifts occurring within various biological contexts.

Genome Sequences of Two Tunisian Field Strains of Avian Mycoplasma, M. meleagridis and M. gallinarum.

Mycoplasma meleagridis and Mycoplasma gallinarum are bacteria that affect birds, but little is known about the genetic basis of their interaction with chickens and other poultry. Here, we sequenced the genomes of M. meleagridis strain MM_26B8_IPT and M. gallinarum strain Mgn_IPT, both isolated from chickens showing respiratory symptoms, poor growth, reduction in hatchability, and loss of production.

Finishing bacterial genome assemblies with Mix.

MOTIVATION: Among challenges that hamper reaping the benefits of genome assembly are both unfinished assemblies and the ensuing experimental costs. First, numerous software solutions for genome de novo assembly are available, each having its advantages and drawbacks, without clear guidelines as to how to choose among them. Second, these solutions produce draft assemblies that often require a resource intensive finishing phase. METHODS: In this paper we address these two aspects by developing Mix , a tool that mixes two or more draft assemblies, without relying on a reference genome and having the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a set of paths in the extension graph that maximizes the cumulative contig length. RESULTS: We evaluate the performance of Mix on bacterial NGS data from the GAGE-B study and apply it to newly sequenced Mycoplasma genomes. Resulting final assemblies demonstrate a significant improvement in the overall assembly quality. In particular, Mix is consistent by providing better overall quality results even when the choice is guided solely by standard assembly statistics, as is the case for de novo projects. AVAILABILITY: Mix is implemented in Python and is available at https://github.com/cbib/MIX, novel data for our Mycoplasma study is available at http://services.cbib.u-bordeaux2.fr/mix/.

Methods and platforms for the quantification of splice variants' expression.

The relatively limited number of human protein encoding genes highlights the importance of the diversity generated at the level of the mRNA transcripts. As alternative RNA splicing plays a key role in mediating this diversity, it becomes critical to develop the tools and platforms that will deliver quantitative information on the specific expression levels associated with splice isoforms. This chapter describes the constraints generated by this global transcriptome analysis and the state-of-the-art techniques and products available to the scientific community.