Comparison of exoskeleton microbial communities of co-occurring native and invasive crayfish species.

Host-associated microbial communities are an important determinant of individual fitness and have recently been highlighted as one of the factors influencing the success of invasive species. Invasive hosts introduce their microbes into the new environment, and then both the host and its associated microbes enter into a series of interactions with the native macroscopic and microscopic biota. As these processes are largely unexplored, we aimed to compare the exoskeletal microbial communities of co-occurring and phylogenetically related crayfish: the native narrow-clawed crayfish Pontastacus leptodactylus and the invasive signal crayfish Pacifastacus leniusculus from the recently invaded Korana River, Croatia. The results of high-throughput 16S rRNA sequencing showed that the exoskeletal microbiome of both species is very diverse, significantly influenced by the local environment and dominated by low abundance bacterial families from the phylum Proteobacteria. Furthermore, the exoskeletal microbiomes of the crayfish species differed significantly in the composition and abundance of Amplicon Sequence Variants (ASVs), suggesting that they are to some extent shaped by species-specific intrinsic factors, despite sharing a common habitat. However, over 95% of the bacterial genera associated with the exoskeleton were detected in the exoskeleton samples of both native and invasive crayfish. We paid particular attention to two known crayfish pathogens, Aphanomyces astaci and Saprolegnia parasitica, and find that both species carry low amounts of both pathogens. On the side, we find that a non-standard ddPCR protocol outperforms standard qPCR test for A. astaci under low concentration conditions. Taken together, our results indicate the possibility of bidirectional mixing and homogenisation of exoskeleton microbiome. As such, they can serve as a baseline in future detangling of the processes that act together to shape the microbiomes of co-occuring native and invasive congeners during biological invasions.

Effects of Soluble Dietary Fibre on Exercise Performance and Perception of Fatigue in Young Basketball Players.

Research background: In this study, we investigated the effects of soluble dietary fibre on improving neuromuscular and cardiovascular endurance and perception of fatigue in a closely monitored group of basketball players. Prebiotics have been sidelined in sports nutrition and their effect on performance remains poorly investigated and understood. Experimental approach: Eighteen healthy male basketball players were divided into two groups; one received 17 g/day of soluble dietary fibre (Nutriose®) for four weeks and the other group received placebo. Their morphological characteristics, neuromuscular and cardiovascular endurance, and rating of perceived exertion according to the rating of perceived exertion (RPE) scale were assessed. Measurements were taken before supplementation and after four weeks of supplementation. Faecal samples were collected from all participants immediately before and after the supplementation period, their total DNA extracted and sent for amplicon sequencing. Results and conclusions: In this study, fibre had no statistically significant effect on the vertical-type explosive power, no statistically significant effect on sprint-type explosive power, nor on aerobic and anaerobic endurance in the experimental group. Soluble fibre had a statistically significant effect on reducing the rating of perceived exertion of basketball players during the competitive part of the season (RPE 7.27±0.04 versus 8.82±0.81). This was confirmed by two-way ANOVA with replication, which showed that within-group interaction (p=0.0193), before and after dietary intake (p=0.0049), and between-group interaction before and after dietary intake (p=0.0313) had a significant effect on the result. The overall conclusion of the study is that soluble dietary fibre supplementation does not improve neuromuscular and cardiovascular endurance over a 4-week period. However, fibre supplementation could have a significant effect on reducing the rating of perceived exertion, as shown by the statistics. Both amplicon sequencing and subsequent bioinformatics results suggest that this could be the result of the beneficial effect on the intestinal microbiota and its metabolites. Novelty and scientific contribution: This work highlights the importance of prebiotics in sports nutrition. Dietary fibre has been a neglected component of sports nutrition. This study demonstrated a statistically significant positive effect on the perception of fatigue, highlighting the need for further studies in this direction.

The Human Milk Microbiota Produces Potential Therapeutic Biomolecules and Shapes the Intestinal Microbiota of Infants.

Human milk not only provides a perfect balance of nutrients to meet all the needs of the infant in the first months of life but also contains a variety of bacteria that play a key role in tailoring the neonatal faecal microbiome. Microbiome analysis of human milk and infant faeces from mother-breastfed infant pairs was performed by sequencing the V1-V3 region of the 16S rRNA gene using the Illumina MiSeq platform. According to the results, there is a connection in the composition of the microbiome in each mother-breastfed infant pair, supporting the hypothesis that the infant's gut is colonised with bacteria from human milk. MiSeq sequencing also revealed high biodiversity of the human milk microbiome and the infant faecal microbiome, whose composition changes during lactation and infant development, respectively. A total of 28 genetically distinct strains were selected by hierarchical cluster analysis of RAPD-PCR (Random Amplified Polymorphic DNA-Polymerase Chain Reaction) electrophoresis profiles of 100 strains isolated from human milk and identified by 16S RNA sequencing. Since certain cellular molecules may support their use as probiotics, the next focus was to detect (S)-layer proteins, bacteriocins and exopolysaccharides (EPSs) that have potential as therapeutic biomolecules. SDS-PAGE (Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis) coupled with LC-MS (liquid chromatography-mass spectrometry) analysis revealed that four Levilactobacillus brevis strains expressed S-layer proteins, which were identified for the first time in strains isolated from human milk. The potential biosynthesis of plantaricin was detected in six Lactiplantibacillus plantarum strains by PCR analysis and in vitro antibacterial studies. 1H NMR (Proton Nuclear Magnetic Resonance) analysis confirmed EPS production in only one strain, Limosilactobacillus fermentum MC1. The overall microbiome analysis suggests that human milk contributes to the establishment of the intestinal microbiota of infants. In addition, it is a promising source of novel Lactobacillus strains expressing specific functional biomolecules.

Identification of pathogens from native urine samples by MALDI-TOF/TOF tandem mass spectrometry.

BACKGROUND: Reliable high-throughput microbial pathogen identification in human urine samples is crucial for patients with cystitis symptoms. Currently employed methods are time-consuming and could lead to unnecessary or inadequate antibiotic treatment. Purpose of this study was to assess the potential of mass spectrometry for uropathogen identification from a native urine sample. METHODS: In total, 16 urine samples having more than 105 CFU/mL were collected from clinical outpatients. These samples were analysed using standard urine culture methods, followed by 16S rRNA gene sequencing serving as control and here described culture-independent MALDI-TOF/TOF MS method being tested. RESULTS: Here we present advantages and disadvantages of bottom-up proteomics, using MALDI-TOF/TOF tandem mass spectrometry, for culture-independent identification of uropathogens (e.g. directly from urine samples). The direct approach provided reliable identification of bacteria at the genus level in monobacterial samples. Taxonomic identifications obtained by proteomics were compared both to standard urine culture test used in clinics and genomic test based on 16S rRNA sequencing. CONCLUSIONS: Our findings indicate that mass spectrometry has great potential as a reliable high-throughput tool for microbial pathogen identification in human urine samples. In this case, the MALDI-TOF/TOF, was used as an analytical tool for the determination of bacteria in urine samples, and the results obtained emphasize high importance of storage conditions and sample preparation method impacting reliability of MS2 data analysis. The proposed method is simple enough to be utilized in existing clinical settings and is highly suitable for suspected single organism infectious etiologies. Further research is required in order to identify pathogens in polymicrobial urine samples.

The functional capacity of plantaricin-producing Lactobacillus plantarum SF9C and S-layer-carrying Lactobacillus brevis SF9B to withstand gastrointestinal transit.

BACKGROUND: We evaluated the functional capacity of plantaricin-producing Lactobacillus plantarum SF9C and S-layer-carrying Lactobacillus brevis SF9B to withstand gastrointestinal transit and to compete among the gut microbiota in vivo. Considering the probiotic potential of Lb. brevis SF9B, this study aims to investigate the antibacterial activity of Lb. plantarum SF9C and their potential for in vivo colonisation in rats, which could be the basis for the investigation of their synergistic functionality. RESULTS: A plantaricin-encoding cluster was identified in Lb. plantarum SF9C, a strain which efficiently inhibited the growth of Listeria monocytogenes ATCC® 19111™ and Staphylococcus aureus 3048. Homology-based three-dimensional (3D) structures of SF9C plantaricins PlnJK and PlnEF were predicted using SWISS-MODEL workspace and the helical wheel representations of the plantaricin peptide helices were generated by HELIQUEST. Contrary to the plantaricin-producing SF9C strain, the S-layer-carrying SF9B strain excluded Escherichia coli 3014 and Salmonella enterica serovar Typhimurium FP1 from the adhesion to Caco-2 cells. Finally, PCR-DGGE analysis of the V2-V3 regions of the 16S rRNA gene confirmed the transit of the two selected lactobacilli through the gastrointestinal tract (GIT). Microbiome profiling via the Illumina MiSeq platform revealed the prevalence of Lactobacillus spp. in the gut microbiota of the Lactobacillus-treated rats, even on the 10th day after the Lactobacillus application, compared to the microbiota of the healthy and AlCl3-exposed rats before Lactobacillus treatment. CONCLUSION: The combined application of Lb. plantarum SF9C and Lb. brevis SF9B was able to influence the intestinal microbiota composition in rats, which was reflected in the increased abundance of Lactobacillus genus, but also in the altered abundances of other bacterial genera, either in the model of healthy or aberrant gut microbiota of rats. The antibacterial activity and capacity to withstand in GIT conditions contributed to the functional aspects of SF9C and SF9B strains that could be incorporated in the probiotic-containing functional foods with a possibility to positively modulate the gut microbiota composition.

Bioprospecting for Genes Encoding Hydrocarbon-Degrading Enzymes from Metagenomic Samples Isolated from Northern Adriatic Sea Sediments.

Three metagenomic libraries were constructed using surface sediment samples from the northern Adriatic Sea. Two of the samples were taken from a highly polluted and an unpolluted site respectively. The third sample from a polluted site had been enriched using crude oil. The results of the metagenome analyses were incorporated in the REDPET relational database (http://redpet.bioinfo.pbf.hr/REDPET), which was generated using the previously developed MEGGASENSE platform. The database includes taxonomic data to allow the assessment of the biodiversity of metagenomic libraries and a general functional analysis of genes using hidden Markov model (HMM) profiles based on the KEGG database. A set of 22 specialised HMM profiles was developed to detect putative genes for hydrocarbon-degrading enzymes. Use of these profiles showed that the metagenomic library generated after selection on crude oil had enriched genes for aerobic n-alkane degradation. The use of this system for bioprospecting was exemplified using potential alkB and almA genes from this library.

MEGGASENSE - The Metagenome/Genome Annotated Sequence Natural Language Search Engine: A Platform for the Construction of Sequence Data Warehouses.

The MEGGASENSE platform constructs relational databases of DNA or protein sequences. The default functional analysis uses 14 106 hidden Markov model (HMM) profiles based on sequences in the KEGG database. The Solr search engine allows sophisticated queries and a BLAST search function is also incorporated. These standard capabilities were used to generate the SCATT database from the predicted proteome of Streptomyces cattleya. The implementation of a specialised metagenome database (AMYLOMICS) for bioprospecting of carbohydrate-modifying enzymes is described. In addition to standard assembly of reads, a novel 'functional' assembly was developed, in which screening of reads with the HMM profiles occurs before the assembly. The AMYLOMICS database incorporates additional HMM profiles for carbohydrate-modifying enzymes and it is illustrated how the combination of HMM and BLAST analyses helps identify interesting genes. A variety of different proteome and metagenome databases have been generated by MEGGASENSE.

Predicting substrate specificity of adenylation domains of nonribosomal peptide synthetases and other protein properties by latent semantic indexing.

Successful genome mining is dependent on accurate prediction of protein function from sequence. This often involves dividing protein families into functional subtypes (e.g., with different substrates). In many cases, there are only a small number of known functional subtypes, but in the case of the adenylation domains of nonribosomal peptide synthetases (NRPS), there are >500 known substrates. Latent semantic indexing (LSI) was originally developed for text processing but has also been used to assign proteins to families. Proteins are treated as ''documents'' and it is necessary to encode properties of the amino acid sequence as ''terms'' in order to construct a term-document matrix, which counts the terms in each document. This matrix is then processed to produce a document-concept matrix, where each protein is represented as a row vector. A standard measure of the closeness of vectors to each other (cosines of the angle between them) provides a measure of protein similarity. Previous work encoded proteins as oligopeptide terms, i.e. counted oligopeptides, but used no information regarding location of oligopeptides in the proteins. A novel tokenization method was developed to analyze information from multiple alignments. LSI successfully distinguished between two functional subtypes in five well-characterized families. Visualization of different ''concept'' dimensions allows exploration of the structure of protein families. LSI was also used to predict the amino acid substrate of adenylation domains of NRPS. Better results were obtained when selected residues from multiple alignments were used rather than the total sequence of the adenylation domains. Using ten residues from the substrate binding pocket performed better than using 34 residues within 8 Å of the active site. Prediction efficiency was somewhat better than that of the best published method using a support vector machine.

Evolutionary concepts in natural products discovery: what actinomycetes have taught us.

Actinomycetes are a very important source of natural products for the pharmaceutical industry and other applications. Most of the strains belong to Streptomyces or related genera, partly because they are particularly amenable to growth in the laboratory and industrial fermenters. It is unlikely that chemical synthesis can fulfil the needs of the pharmaceutical industry for novel compounds so there is a continuing need to find novel natural products. An evolutionary perspective can help this process in several ways. Genome mining attempts to identify secondary metabolite biosynthetic clusters in DNA sequences, which are likely to produce interesting chemical entities. There are often technical problems in assembling the DNA sequences of large modular clusters in genome and metagenome projects, which can be overcome partially using information about the evolution of the domain sequences. Understanding the evolutionary mechanisms of modular clusters should allow simulation of evolutionary pathways in the laboratory to generate novel compounds.

Mediterranean Diet Adherence, Physical Activity, and Advanced Glycation End Products in Complex PTSD: A Comprehensive Examination of Lifestyle and Cardiovascular Risk in War Veterans.

As accumulated evidence suggests that individuals with post-traumatic stress disorder (PTSD) encounter earlier and more frequent occurrences of cardiovascular diseases, the aim of this study was to ascertain the differences in lifestyle and cardiovascular risk between PTSD and complex PTSD patients. We enrolled 137 male war veterans with PTSD (89 had complex PTSD). The diagnosis was established based on 11th revision of International Classification of Diseases (ICD-11), and cardiovascular risk was estimated by the measurement of advanced glycation end products. Adherence to Mediterranean diet (MD) was lower in the complex PTSD group (2.2% vs. 12.5%, p = 0.015). Accordingly, patients with complex PTSD had lower healthy lifestyle scores in comparison to PTSD counterparts (50.6 ± 9.7 vs. 59.6 ± 10.1, p < 0.001), and a positive association was noted between MD adherence and a healthy lifestyle (r = 0.183, p = 0.022). On the other hand, differences were not noted in terms of physical activity (p = 0.424), fat % (p = 0.571) or cardiovascular risk (p = 0.573). Although complex PTSD patients exhibit worse adherence to MD and lower healthy lifestyle scores, these differences do not seem to impact physical activity, body composition, or estimated cardiovascular risk. More research is needed to clarify if this lack of association accurately reflects the state of the PTSD population or results from insufficient statistical power.

KEGG orthology-based annotation of the predicted proteome of Acropora digitifera: ZoophyteBase - an open access and searchable database of a coral genome.

BACKGROUND: Contemporary coral reef research has firmly established that a genomic approach is urgently needed to better understand the effects of anthropogenic environmental stress and global climate change on coral holobiont interactions. Here we present KEGG orthology-based annotation of the complete genome sequence of the scleractinian coral Acropora digitifera and provide the first comprehensive view of the genome of a reef-building coral by applying advanced bioinformatics. DESCRIPTION: Sequences from the KEGG database of protein function were used to construct hidden Markov models. These models were used to search the predicted proteome of A. digitifera to establish complete genomic annotation. The annotated dataset is published in ZoophyteBase, an open access format with different options for searching the data. A particularly useful feature is the ability to use a Google-like search engine that links query words to protein attributes. We present features of the annotation that underpin the molecular structure of key processes of coral physiology that include (1) regulatory proteins of symbiosis, (2) planula and early developmental proteins, (3) neural messengers, receptors and sensory proteins, (4) calcification and Ca2+-signalling proteins, (5) plant-derived proteins, (6) proteins of nitrogen metabolism, (7) DNA repair proteins, (8) stress response proteins, (9) antioxidant and redox-protective proteins, (10) proteins of cellular apoptosis, (11) microbial symbioses and pathogenicity proteins, (12) proteins of viral pathogenicity, (13) toxins and venom, (14) proteins of the chemical defensome and (15) coral epigenetics. CONCLUSIONS: We advocate that providing annotation in an open-access searchable database available to the public domain will give an unprecedented foundation to interrogate the fundamental molecular structure and interactions of coral symbiosis and allow critical questions to be addressed at the genomic level based on combined aspects of evolutionary, developmental, metabolic, and environmental perspectives.

Databases of the thiotemplate modular systems (CSDB) and their in silico recombinants (r-CSDB).

Modular biosynthetic clusters are responsible for the synthesis of many important pharmaceutical products. They include polyketide synthases (PKS clusters), non-ribosomal synthetases (NRPS clusters), and mixed clusters (containing both PKS and NRPS modules). The ClustScan database (CSDB) contains highly annotated descriptions of 170 clusters. The database has a hierarchical organization, which allows easy extraction of DNA and protein sequences of polypeptides, modules, and domains as well as an organization of the annotation so as to be able to predict the product chemistry to view it or export it in a standard SMILES format. The recombinant ClustScan database contains information about predicted recombinants between PKS clusters. The recombinants are generated by modeling homologous recombination and are associated with annotation and prediction of product chemistry automatically generated by the model. The database contains over 20,000 recombinants and is a resource for in silico approaches to detecting promising new compounds. Methods are available to construct the corresponding recombinants in the laboratory.

The mycobiome of a successful crayfish invader and its changes along the environmental gradient.

BACKGROUND: The microbiome plays an important role in biological invasions, since it affects various interactions between host and environment. However, most studies focus on the bacteriome, insufficiently addressing other components of the microbiome such as the mycobiome. Microbial fungi are among the most damaging pathogens in freshwater crayfish populations, colonizing and infecting both native and invasive crayfish species. Invading crayfish may transmit novel fungal species to native populations, but also, dispersal process and characteristics of the novel environment may affect the invaders' mycobiome composition, directly and indirectly affecting their fitness and invasion success. This study analyzes the mycobiome of a successful invader in Europe, the signal crayfish, using the ITS rRNA amplicon sequencing approach. We explored the mycobiomes of crayfish samples (exoskeletal biofilm, hemolymph, hepatopancreas, intestine), compared them to environmental samples (water, sediment), and examined the differences in fungal diversity and abundance between upstream and downstream segments of the signal crayfish invasion range in the Korana River, Croatia. RESULTS: A low number of ASVs (indicating low abundance and/or diversity of fungal taxa) was obtained in hemolymph and hepatopancreas samples. Thus, only exoskeleton, intestine, sediment and water samples were analyzed further. Significant differences were recorded between their mycobiomes, confirming their uniqueness. Generally, environmental mycobiomes showed higher diversity than crayfish-associated mycobiomes. The intestinal mycobiome showed significantly lower richness compared to other mycobiomes. Significant differences in the diversity of sediment and exoskeletal mycobiomes were recorded between different river segments (but not for water and intestinal mycobiomes). Together with the high observed portion of shared ASVs between sediment and exoskeleton, this indicates that the environment (i.e. sediment mycobiome) at least partly shapes the exoskeletal mycobiome of crayfish. CONCLUSION: This study presents the first data on crayfish-associated fungal communities across different tissues, which is valuable given the lack of studies on the crayfish mycobiome. We demonstrate significant differences in the crayfish exoskeletal mycobiome along the invasion range, suggesting that different local environmental conditions may shape the exoskeletal mycobiome during range expansion, while the mycobiome of the internal organ (intestine) remained more stable. Our results provide a basis for assessing how the mycobiome contributes to the overall health of the signal crayfish and its further invasion success.

Current Viewpoint on Female Urogenital Microbiome-The Cause or the Consequence?

An increasing amount of evidence implies that native microbiota is a constituent part of a healthy urinary tract (UT), making it an ecosystem on its own. What is still not clear is whether the origin of the urinary microbial community is the indirect consequence of the more abundant gut microbiota or a more distinct separation exists between these two systems. Another area of uncertainty is the existence of a link between the shifts in UT microbial composition and both the onset and persistence of cystitis symptoms. Cystitis is one of the most common reasons for antimicrobial drugs prescriptions in primary and secondary care and an important contributor to the problem of antimicrobial resistance. Despite this fact, we still have trouble distinguishing whether the primary cause of the majority of cystitis cases is a single pathogen overgrowth or a systemic disorder affecting the entire urinary microbiota. There is an increasing trend in studies monitoring changes and dynamics of UT microbiota, but this field of research is still in its infancy. Using NGS and bioinformatics, it is possible to obtain microbiota taxonomic profiles directly from urine samples, which can provide a window into microbial diversity (or the lack of) underlying each patient's cystitis symptoms. However, while microbiota refers to the living collection of microorganisms, an interchangeably used term microbiome referring to the genetic material of the microbiota is more often used in conjunction with sequencing data. It is this vast amount of sequences, which are truly "Big Data", that allow us to create models that describe interactions between different species contributing to an UT ecosystem, when coupled with machine-learning techniques. Although in a simplified predator-prey form these multi-species interaction models have the potential to further validate or disprove current beliefs; whether it is the presence or the absence of particular key players in a UT microbial ecosystem, the exact cause or consequence of the otherwise unknown etiology in the majority of cystitis cases. These insights might prove to be vital in our ongoing struggle against pathogen resistance and offer us new and promising clinical markers.

Obesity, Gut Microbiota, and Metabolome: From Pathophysiology to Nutritional Interventions.

Obesity is a disorder identified by an inappropriate increase in weight in relation to height and is considered by many international health institutions to be a major pandemic of the 21st century. The gut microbial ecosystem impacts obesity in multiple ways that yield downstream metabolic consequences, such as affecting systemic inflammation, immune response, and energy harvest, but also the gut-host interface. Metabolomics, a systematized study of low-molecular-weight molecules that take part in metabolic pathways, represents a serviceable method for elucidation of the crosstalk between hosts' metabolism and gut microbiota. In the present review, we confer about clinical and preclinical studies exploring the association of obesity and related metabolic disorders with various gut microbiome profiles, and the effects of several dietary interventions on gut microbiome composition and the metabolome. It is well established that various nutritional interventions may serve as an efficient therapeutic approach to support weight loss in obese individuals, yet no agreement exists in regard to the most effective dietary protocol, both in the short and long term. However, metabolite profiling and the gut microbiota composition might represent an opportunity to methodically establish predictors for obesity control that are relatively simple to measure in comparison to traditional approaches, and it may also present a tool to determine the optimal nutritional intervention to ameliorate obesity in an individual. Nevertheless, a lack of adequately powered randomized trials impedes the application of observations to clinical practice.

Annotation of the modular polyketide synthase and nonribosomal peptide synthetase gene clusters in the genome of Streptomyces tsukubaensis NRRL18488.

The high G+C content and large genome size make the sequencing and assembly of Streptomyces genomes more difficult than for other bacteria. Many pharmaceutically important natural products are synthesized by modular polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The analysis of such gene clusters is difficult if the genome sequence is not of the highest quality, because clusters can be distributed over several contigs, and sequencing errors can introduce apparent frameshifts into the large PKS and NRPS proteins. An additional problem is that the modular nature of the clusters results in the presence of imperfect repeats, which may cause assembly errors. The genome sequence of Streptomyces tsukubaensis NRRL18488 was scanned for potential PKS and NRPS modular clusters. A phylogenetic approach was used to identify multiple contigs belonging to the same cluster. Four PKS clusters and six NRPS clusters were identified. Contigs containing cluster sequences were analyzed in detail by using the ClustScan program, which suggested the order and orientation of the contigs. The sequencing of the appropriate PCR products confirmed the ordering and allowed the correction of apparent frameshifts resulting from sequencing errors. The product chemistry of such correctly assembled clusters could also be predicted. The analysis of one PKS cluster showed that it should produce a bafilomycin-like compound, and reverse transcription (RT)-PCR was used to show that the cluster was transcribed.

Horizontal gene transfer and gene conversion drive evolution of modular polyketide synthases.

Soil bacteria live in a very competitive environment and produce many secondary metabolites; there appears to be strong selective pressure for evolution of new compounds. Secondary metabolites are the most important source of chemical structures for the pharmaceutical industry and an understanding of the evolutionary process should help in finding novel chemical entities. Modular polyketide synthases are a particularly interesting case for evolutionary studies, because much of the chemical structure can be predicted from DNA sequence. Previous evolutionary studies have concentrated on individual modules or domains and were not able to study the evolution of orthologues. This study overcame this problem by considering complete clusters as "organisms", so that orthologous modules and domains could be identified and used to characterise evolutionary pathways. Seventeen modular polyketide synthase clusters were identified that fell into six classes. Gene conversion within clusters was very common (affecting about 15 % of domains) and was detected by discordance in phylogenetic trees. An evolutionary model is proposed in which a single cross over between two different clusters (i.e. horizontal gene transfer) would generate a cluster of very different architecture with radically different chemical products; subsequent gene conversion and deletions would explore chemical variants. Two probable examples of such recombination were found. This model suggests strategies for detecting horizontal gene transfer in cluster evolution.

Recombinatorial biosynthesis of polyketides.

Modular polyketide synthases (PKSs) from Streptomyces and related genera of bacteria produce many important pharmaceuticals. A program called CompGen was developed to carry out in silico homologous recombination between gene clusters encoding PKSs and determine whether recombinants have cluster architectures compatible with the production of polyketides. The chemical structure of recombinant polyketides was also predicted. In silico recombination was carried out for 47 well-characterised clusters. The predicted recombinants would produce 11,796 different polyketide structures. The molecular weights and average degree of reduction of the chemical structures are dispersed around the parental structures indicating that they are likely to include pharmaceutically interesting compounds. The details of the recombinants and the chemical structures were entered in a database called r-CSDB. The virtual compound library is a useful resource for computer-aided drug design and chemoinformatics strategies for finding pharmaceutically relevant chemical entities. A strategy to construct recombinant Streptomyces strains to produce these polyketides is described and the critical steps of mobilizing large biosynthetic clusters and producing new linear cloning vectors are illustrated by experimental data.

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.

A novel docking domain interface model predicting recombination between homoeologous modular biosynthetic gene clusters.

An in silico model for homoeologous recombination between gene clusters encoding modular polyketide synthases (PKS) or non-ribosomal peptide synthetases (NRPS) was developed. This model was used to analyze recombination between 12 PKS clusters from Streptomyces species and related genera to predict if new clusters might give rise to new products. In many cases, there were only a limited number of recombination sites (about 13 per cluster pair), suggesting that recombination may pose constraints on the evolution of PKS clusters. Most recombination events occurred between pairs of ketosynthase (KS) domains, allowing the biosynthetic outcome of the recombinant modules to be predicted. About 30% of recombinants were predicted to produce polyketides. Four NRPS clusters from Streptomyces strains were also used for in silico recombination. They yielded a comparable number of recombinants to PKS clusters, but the adenylation (A) domains contained the largest proportion of recombination events; this might be a mechanism for producing new substrate specificities. The extreme G + C-content, the presence of linear chromosomes and plasmids, as well as the lack of a mutSL-mismatch repair system should favor production of recombinants in Streptomyces species.