An Integrative, Multiparametric Approach for the Comprehensive Assessment of Microbial Quality and Pollution in Aquaculture Systems.

As the aquaculture sector significantly expanded worldwide in the past decades, the concept of sustainable aquaculture has developed with the challenge of not only maximizing benefits but also minimizing the negative impacts on the environment assuring, at the same time, food security. In this framework, monitoring and improving the microbiological water quality and animal health are a central topic. In the present study, we evaluated the seawater microbiological quality in a mariculture system located in a Mediterranean coastal area (Northern Ionian Sea, Italy). We furnished, for the first time, a microbial inventory based on conventional culture-based methods, integrated with the 16S rRNA gene metabarcoding approach for vibrios identification and diversity analyses, and further implemented with microbial metabolic profiling data obtained from the Biolog EcoPlate system. Microbiological pollution indicators, vibrios diversity, and microbial metabolism were determined in two different times of the year (July and December). All microbial parameters measured in July were markedly increased compared to those measured in December. The presence of potentially pathogenic vibrios is discussed concerning the risk of fish disease and human infections. Thus, the microbial inventory here proposed might represent a new multiparametric approach for the suitable surveillance of the microbial quality in a mariculture system. Consequently, it could be useful for ensuring the safety of both the reared species and the consumers in the light of sustainable, eco-friendly aquaculture management.

DUETS (Dallas UtErus Transplant Study): Complete report of 6-month and initial 2-year outcomes following open donor hysterectomy.

INTRODUCTION: Uterus transplantation has shown success in treating women with uterine factor infertility who want to carry their own pregnancy. METHODS: We report the medical, sexual, and psychological outcomes of our first cohort of 13 living donor hysterectomies. As we have transitioned from open to robotically assisted hysterectomy, this report represents the complete series of open donor hysterectomies at our center, all with ≥6-month postoperative outcomes. RESULTS: The open donor hysterectomy had a median of a 6.5-hour surgical time, 0.8 L estimated blood loss, 6-day hospital stay, and 28-day sick leave. Three donors had a grade III or IV complications, one reported new-onset psychological symptoms, and 9 experienced transient sexual discomfort. All complications were addressed and resolved, and all donors returned to their presurgical social and physical activities. CONCLUSION: Since uterus transplantation is not life-saving or life-extending, the risks in living uterus donation must be weighed against the benefit of giving another woman the opportunity to give birth to her own child. This report provides data to support more detailed informed consent regarding the medical, psychological, and sexual complications of open living donor hysterectomy and allows for further evaluation of the ethical acceptability of this procedure.

Airborne bacteria in the Central Mediterranean: Structure and role of meteorology and air mass transport.

The 16S rRNA gene metabarcoding approach has been used to characterize the structure of the airborne bacterial community of PM10 samples, and investigate the dependence on meteorology, seasons, and long-range transported air masses. The PM10 samples were collected at a Central Mediterranean coastal site, away from large sources of local pollution. Proteobacteria, Cyanobacteria, Actinobacteria, Firmicutes, and Bacteroidetes, which were found in all samples, were the most abundant phyla. Calothrix, Pseudomonas, and Bacillus were the most abundant genera. The within-sample relative abundance (RA) of each phylum/genus varied from sample to sample. Calothrix was the most abundant genus during the advection of desert dust and Atlantic air masses, Pseudomonas was the most abundant genus when the advected air flows spent several hours over lands or close to lands affected by anthropogenic activities, before reaching the study site. The bacterial community richness and biodiversity of the PM10 samples on average increased from winter to spring, while the sample dissimilarity on average decreased from winter to spring. The spring meteorological conditions over the Mediterranean, which have likely contributed to maintain for longer time the bacterial community in the atmosphere, could have been responsible for the above results. The analysis of the presumptive species-level characterization of the airborne bacterial community has revealed that the abundance of human (opportunistic) pathogens was highly inhomogeneous among samples, without any significant change from winter to spring. We also found that the PM10 samples collected during the advection of desert dust and Atlantic air masses were on average the less enriched in human (opportunistic) pathogenic species.

The Microbiome of the Maculinea-Myrmica Host-Parasite Interaction.

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.

RhoTermPredict: an algorithm for predicting Rho-dependent transcription terminators based on Escherichia coli, Bacillus subtilis and Salmonella enterica databases.

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 (F1-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.

Stimulatory Effects of Methyl-ß-cyclodextrin on Spiramycin Production and Physical-Chemical Characterization of Nonhost@Guest Complexes.

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, ß-cyclodextrin, or methyl-ß-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-ß-cyclodextrin, whereas α-cyclodextrin or ß-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-ß-cyclodextrin@spiramycin I in the stoichiometric ratio of 3:1 while they excluded the formation of complex between spiramycin I and α- or ß-cyclodextrin. Fourier-transform infrared spectroscopy measurements were then carried out to characterize the methyl-ß-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-ß-cyclodextrin complexation, as it has been well-documented for other bioactive molecules.

Mitochondrial ribosomal proteins involved in tellurite resistance in yeast Saccharomyces cerevisiae.

A considerable body of evidence links together mitochondrial dysfunctions, toxic action of metalloid oxyanions, and system and neurodegenerative disorders. In this study we have used the model yeast Saccharomyces cerevisiae to investigate the genetic determinants associated with tellurite resistance/sensitivity. Nitrosoguanidine-induced K2TeO3-resistant mutants were isolated, and one of these mutants, named Sc57-Te5R, was characterized. Both random spore analysis and tetrad analysis and growth of heterozygous (TeS/Te5R) diploid from Sc57-Te5R mutant revealed that nuclear and recessive mutation(s) was responsible for the resistance. To get insight into the mechanisms responsible for K2TeO3-resistance, RNA microarray analyses were performed with K2TeO3-treated and untreated Sc57-Te5R cells. A total of 372 differentially expressed loci were identified corresponding to 6.37% of the S. cerevisiae transcriptome. Of these, 288 transcripts were up-regulated upon K2TeO3 treatment. About half of up-regulated transcripts were associated with the following molecular functions: oxidoreductase activity, structural constituent of cell wall, transporter activity. Comparative whole-genome sequencing allowed us to identify nucleotide variants distinguishing Sc57-Te5R from parental strain Sc57. We detected 15 CDS-inactivating mutations, and found that 3 of them affected genes coding mitochondrial ribosomal proteins (MRPL44 and NAM9) and mitochondrial ribosomal biogenesis (GEP3) pointing out to alteration of mitochondrial ribosome as main determinant of tellurite resistance.

Characterization of two Pantoea strains isolated from extra-virgin olive oil.

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 ß-hydroxy carboxylic acids.

G4PromFinder: an algorithm for predicting transcription promoters in GC-rich bacterial genomes based on AT-rich elements and G-quadruplex motifs.

BACKGROUND: Over 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. RESULTS: In 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. CONCLUSIONS: Our 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.

Bacterial bioluminescence onset and quenching: a dynamical model for a quorum sensing-mediated property.

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.