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Background In bacterial genomes, there are two mechanisms to terminate the DNA transcription: the “intrinsic” or Rho-independent termination and the Rho-dependent termination. Intrinsic terminators are characterized by a RNA hairpin followed by a run of 6–8 U residues relatively easy to identify using one of the numerous available prediction programs. In contrast, Rho-dependent termination is mediated by the Rho protein factor that, firstly, binds to ribosome-free mRNA in a site characterized by a C > G content and then reaches the RNA polymerase to induce its release. Conversely on intrinsic terminators, the computational prediction of Rho-dependent terminators in prokaryotes is a very difficult problem because the sequence features required for the function of Rho are complex and poorly defined. This is the reason why it still does not exist an exhaustive Rho-dependent terminators prediction program. Results In this study we introduce RhoTermPredict, the first published algorithm for an exhaustive Rho-dependent terminators prediction in bacterial genomes. RhoTermPredict identifies these elements based on a previously proposed consensus motif common to all Rho-dependent transcription terminators. It essentially searches for a 78 nt long RUT site characterized by a C > G content and with regularly spaced C residues, followed by a putative pause site for the RNA polymerase. We tested RhoTermPredict performances by using available genomic and transcriptomic data of the microorganism Escherichia coli K-12, both in limited-length sequences and in the whole-genome, and available genomic sequences from Bacillus subtilis 168 and Salmonella enterica LT2 genomes. We also estimated the overlap between the predictions of RhoTermPredict and those obtained by the predictor of intrinsic terminators ARNold webtool. Our results demonstrated that RhoTermPredict is a very performing algorithm both for limited-length sequences (F 1 -score obtained about 0.7) and for a genome-wide analysis. Furthermore the degree of overlap with ARNold predictions was very low. Conclusions Our analysis shows that RhoTermPredict is a powerful tool for Rho-dependent terminators search in the three analyzed genomes and could fill this gap in computational genomics. We conclude that RhoTermPredict could be used in combination with an intrinsic terminators predictor in order to predict all the transcription terminators in bacterial genomes. Electronic supplementary material The online version of this article (10.1186/s12859-019-2704-x) contains supplementary material, which is available to authorized users.

BackgroundOver the last few decades, computational genomics has tremendously contributed to decipher biology from genome sequences and related data. Considerable effort has been devoted to the prediction of transcription promoter and terminator sites that represent the essential “punctuation marks” for DNA transcription. Computational prediction of promoters in prokaryotes is a problem whose solution is far from being determined in computational genomics. The majority of published bacterial promoter prediction tools are based on a consensus-sequences search and they were designed specifically for vegetative σ70 promoters and, therefore, not suitable for promoter prediction in bacteria encoding a lot of σ factors, like actinomycetes.ResultsIn this study we investigated the possibility to identify putative promoters in prokaryotes based on evolutionarily conserved motifs, and focused our attention on GC-rich bacteria in which promoter prediction with conventional, consensus-based algorithms is often not-exhaustive. Here, we introduce G4PromFinder, a novel algorithm that predicts putative promoters based on AT-rich elements and G-quadruplex DNA motifs. We tested its performances by using available genomic and transcriptomic data of the model microorganisms Streptomyces coelicolor A3(2) and Pseudomonas aeruginosa PA14. We compared our results with those obtained by three currently available promoter predicting algorithms: the σ70consensus-based PePPER, the σ factors consensus-based bTSSfinder, and PromPredict which is based on double-helix DNA stability. Our results demonstrated that G4PromFinder is more suitable than the three reference tools for both the genomes. In fact our algorithm achieved the higher accuracy (F1-scores 0.61 and 0.53 in the two genomes) as compared to the next best tool that is PromPredict (F1-scores 0.46 and 0.48). Consensus-based algorithms produced lower performances with the analyzed GC-rich genomes.ConclusionsOur analysis shows that G4PromFinder is a powerful tool for promoter search in GC-rich bacteria, especially for bacteria coding for a lot of σ factors, such as the model microorganism S. coelicolor A3(2). Moreover consensus-based tools and, in general, tools that are based on specific features of bacterial σ factors seem to be less performing for promoter prediction in these types of bacterial genomes.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2049-x) contains supplementary material, which is available to authorized users.

Maculinea (= Phengaris ) are endangered butterflies that are characterized by a very complex biological cycle. Maculinea larvae behave as obligate parasites whose survival is strictly dependent on both particular food plants and species-specific Myrmica ants. In this interaction, Maculinea caterpillars induce Myrmica workers to retrieve and rear them in the nest by chemical and acoustic deception. Social insect symbiotic microorganisms play a key role in intraspecific and interspecific communication; therefore, it is possible that the Maculinea caterpillar microbiome might be involved in the chemical cross-talk by producing deceptive semiochemicals for host ants. To address this point, the microbiota of Maculinea alcon at different larval stages (phytophagous early larvae, intermediate larvae, carnivorous late larvae) was analyzed by using 16S rRNA-guided metabarcoding approach and compared to that of the host ant Myrmica scabrinodis . Structural and deduced functional profiles of the microbial communities were recorded, which were used to identify specific groups of microorganisms that may be involved in the chemical cross-talk. One of the most notable features was the presence in all larval stages and in the ants of two bacteria, Serratia marcescens and S . entomophila , which are involved in the chemical cross-talk between the microbes and their hosts.

The olive oil is an unfavorable substrate for microbial survival and growth. Only few microorganisms use olive oil fatty acids as carbon and energy sources, and survive in the presence of olive oil anti-microbial components. In this study, we have evaluated the occurrence of microorganisms in 1-year-stored extra-virgin olive oil samples. We detected the presence of bacterial and yeast species with a recurrence of the bacterium Stenotrophomonas rhizophila and yeast Sporobolomyces roseus. We then assayed the ability of all isolates to grow in a mineral medium supplemented with a commercial extra-virgin olive oil as a sole carbon and energy source, and analyzed the utilization of olive oil fatty acids during their growth. We finally focused on two bacterial isolates belonging to the species Pantoea septica. Both these isolates produce carotenoids, and one of them synthesizes bioemulsifiers enabling the bacteria to better survive/growth in this unfavorable substrate. Analyses point to a mixture of glycolipids with glucose, galactose and xylose as carbohydrate moieties whereas the lipid domain was constituted by C6–C10 β-hydroxy carboxylic acids.Electronic supplementary materialThe online version of this article (10.1186/s13568-018-0642-z) contains supplementary material, which is available to authorized users.

Spiramycin is a macrolide antibiotic and antiparasitic that is used to treat toxoplasmosis and various other infections of soft tissues. In the current study, we evaluated the effects of α-cyclodextrin, β-cyclodextrin, or methyl-β-cyclodextrin supplementation to a synthetic culture medium on biomass and spiramycin production by Streptomyces ambofaciens ATCC 23877. We found a high stimulatory effect on spiramycin production when the culture medium was supplemented with 0.5% (w/v) methyl-β-cyclodextrin, whereas α-cyclodextrin or β-cyclodextrin weakly enhanced antibiotic yields. As the stimulation of antibiotic production could be because of spiramycin complexation with cyclodextrins with effects on antibiotic stability and/or efflux, we analyzed the possible formation of complexes by physical–chemical methods. The results of Job plot experiment highlighted the formation of a nonhost@guest complex methyl-β-cyclodextrin@spiramycin I in the stoichiometric ratio of 3:1 while they excluded the formation of complex between spiramycin I and α- or β-cyclodextrin. Fourier-transform infrared spectroscopy measurements were then carried out to characterize the methyl-β-cyclodextrin@spiramycin I complex and individuate the chemical groups involved in the binding mechanism. These findings may help to improve the spiramycin fermentation process, providing at the same time a new device for better delivery of the antibiotic at the site of infection by methyl-β-cyclodextrin complexation, as it has been well-documented for other bioactive molecules.

Isolated sorghum (Sorghum bicolor) storage proteins (kafirins) have been successfully used in the production of several bio-materials including adhesives, films, micro-particles, fibers, and biological scaffold material. Comparatively little research has been conducted on the use of isolated kafirins in food products or to produce bioactive peptides via hydrolysis for nutritional uses. To support such research, the aim of this study was to compare existing methods for bulk isolation of sorghum kafirins with the goal of identifying a solvent with the least toxicity that maintained a high extraction rate from food grade sorghum flour. A secondary goal was to characterize the kafirin isolates produced from various extraction methods to provide some information on their potential use in food products to guide future research in this area. Five different extraction methods were compared including 1) aqueous ethanol containing NaOH and sodium metabisulfite, 2) glacial acetic acid, 3) aqueous ethanol with sodium metabisulfite, 4) aqueous ethanol at acidic pH, and 5) alkaline pH alone. The protein contents of the kafirin isolates obtained by the five methods ranged from 49.76% to 56.83%. Kafirin isolates were characterized using reversed phase (RP)-high performance liquid chromatography (HPLC), which revealed substantial variability in the various kafirin patterns among the extraction methods tested. However, characterization of the kafirin isolates by size exclusion chromatography (SEC) did not show a high degree of variability among the methods tested. Likewise, analysis of the samples using sodium dodecyl sulphate - polyacrylamide gel electrophoresis (SDS-PAGE) showed essentially the same band profiles but with different band intensities among kafirin extraction methods. Surface hydrophobicity of the kafirin isolates varied considerably with isolates extracted with glacial acetic acid and aqueous ethanol plus sodium metabisulfite the most hydrophobic as indicated by hydrophobic dye binding.

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida, a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence ‘quenching’ after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi.