Reference-Grade Genome and Large Linear Plasmid of Streptomyces rimosus: Pushing the Limits of Nanopore Sequencing.

Streptomyces rimosus ATCC 10970 is the parental strain of industrial strains used for the commercial production of the important antibiotic oxytetracycline. As an actinobacterium with a large linear chromosome containing numerous long repeat regions, high GC content, and a single giant linear plasmid (GLP), these genomes are challenging to assemble. Here, we apply a hybrid sequencing approach relying on the combination of short- and long-read next-generation sequencing platforms and whole-genome restriction analysis by using pulsed-field gel electrophoresis (PFGE) to produce a high-quality reference genome for this biotechnologically important bacterium. By using PFGE to separate and isolate plasmid DNA from chromosomal DNA, we successfully sequenced the GLP using Nanopore data alone. Using this approach, we compared the sequence of GLP in the parent strain ATCC 10970 with those found in two semi-industrial progenitor strains, R6-500 and M4018. Sequencing of the GLP of these three S. rimosus strains shed light on several rearrangements accompanied by transposase genes, suggesting that transposases play an important role in plasmid and genome plasticity in S. rimosus. The polished annotation of secondary metabolite biosynthetic pathways compared to metabolite analysis in the ATCC 10970 strain also refined our knowledge of the secondary metabolite arsenal of these strains. The proposed methodology is highly applicable to a variety of sequencing projects, as evidenced by the reliable assemblies obtained. IMPORTANCE The genomes of Streptomyces species are difficult to assemble due to long repeats, extrachromosomal elements (giant linear plasmids [GLPs]), rearrangements, and high GC content. To improve the quality of the S. rimosus ATCC 10970 genome, producer of oxytetracycline, we validated the assembly of GLPs by applying a new approach to combine pulsed-field gel electrophoresis separation and GLP isolation and sequenced the isolated GLP with Oxford Nanopore technology. By examining the sequenced plasmids of ATCC 10970 and two industrial progenitor strains, R6-500 and M4018, we identified large GLP rearrangements. Analysis of the assembled plasmid sequences shed light on the role of transposases in genome plasticity of this species. The new methodological approach developed for Nanopore sequencing is highly applicable to a variety of sequencing projects. In addition, we present the annotated reference genome sequence of ATCC 10970 with a detailed analysis of the biosynthetic gene clusters.

Synthetic biology approaches to actinomycete strain improvement.

Their biochemical versatility and biotechnological importance make actinomycete bacteria attractive targets for ambitious genetic engineering using the toolkit of synthetic biology. But their complex biology also poses unique challenges. This mini review discusses some of the recent advances in synthetic biology approaches from an actinomycete perspective and presents examples of their application to the rational improvement of industrially relevant strains.

Growth and division in a dynamic protocell model.

In this paper a new model of growing and dividing protocells is described, whose main features are (i) a lipid container that grows according to the composition of the molecular milieu (ii) a set of "genetic memory molecules" (GMMs) that undergo catalytic reactions in the internal aqueous phase and (iii) a set of stochastic kinetic equations for the GMMs. The mass exchange between the external environment and the internal phase is described by simulating a semipermeable membrane and a flow driven by the differences in chemical potentials, thereby avoiding to resort to sometimes misleading simplifications, e.g., that of a flow reactor. Under simple assumptions, it is shown that synchronization takes place between the rate of replication of the GMMs and that of the container, provided that the set of reactions hosts a so-called RAF (Reflexive Autocatalytic, Food-generated) set whose influence on synchronization is hereafter discussed. It is also shown that a slight modification of the basic model that takes into account a rate-limiting term, makes possible the growth of novelties, allowing in such a way suitable evolution: so the model represents an effective basis for understanding the main abstract properties of populations of protocells.

Parameter sensitivity analysis of stochastic models: application to catalytic reaction networks.

A general numerical methodology for parametric sensitivity analysis is proposed, which allows to determine the parameters exerting the greatest influence on the output of a stochastic computational model, especially when the knowledge about the actual value of a parameter is insufficient. An application of the procedure is performed on a model of protocell, in order to detect the kinetic rates mainly affecting the capability of a catalytic reaction network enclosed in a semi-permeable membrane to retain material from its environment and to generate a variety of molecular species within its boundaries. It is shown that the former capability is scarcely sensitive to variations in the model parameters, whereas a kinetic rate responsible for profound modifications of the latter can be identified and it depends on the specific reaction network. A faster uptaking of limited resources from the environment may have represented a significant advantage from an evolutionary point of view and this result is a first indication in order to decipher which kind of structures are more suitable to achieve a viable evolution.

A stochastic model of autocatalytic reaction networks.

Autocatalytic cycles are rather widespread in nature and in several theoretical models of catalytic reaction networks their emergence is hypothesized to be inevitable when the network is or becomes sufficiently complex. Nevertheless, the emergence of autocatalytic cycles has been never observed in wet laboratory experiments. Here, we present a novel model of catalytic reaction networks with the explicit goal of filling the gap between theoretical predictions and experimental findings. The model is based on previous study of Kauffman, with new features in the introduction of a stochastic algorithm to describe the dynamics and in the possibility to increase the number of elements and reactions according to the dynamical evolution of the system. Furthermore, the introduction of a temporal threshold allows the detection of cycles even in our context of a stochastic model with asynchronous update. In this study, we describe the model and present results concerning the effect on the overall dynamics of varying (a) the average residence time of the elements in the reactor, (b) both the composition of the firing disk and the concentration of the molecules belonging to it, (c) the composition of the incoming flux.