Background: The molecular mechanisms altered by the traditional mutation and screening approach during the improvement of antibiotic-producing microorganisms are still poorly understood although this information is essential to design rational strategies for industrial strain improvement. In this study, we applied comparative genomics to identify all genetic changes occurring during the development of an erythromycin overproducer obtained using the traditional mutate-and- screen method. Results: Compared with the parental Saccharopolyspora erythraea NRRL 2338, the genome of the overproducing strain presents 117 deletion, 78 insertion and 12 transposition sites, with 71 insertion/deletion sites mapping within coding sequences (CDSs) and generating frame-shift mutations. Single nucleotide variations are present in 144 CDSs. Overall, the genomic variations affect 227 proteins of the overproducing strain and a considerable number of mutations alter genes of key enzymes in the central carbon and nitrogen metabolism and in the biosynthesis of secondary metabolites, resulting in the redirection of common precursors toward erythromycin biosynthesis. Interestingly, several mutations inactivate genes coding for proteins that play fundamental roles in basic transcription and translation machineries including the transcription anti-termination factor NusB and the transcription elongation factor Efp. These mutations, along with those affecting genes coding for pleiotropic or pathway-specific regulators, affect global expression profile as demonstrated by a comparative analysis of the parental and overproducer expression profiles. Genomic data, finally, suggest that the mutate-and-screen process might have been accelerated by mutations in DNA repair genes. Conclusions: This study helps to clarify the mechanisms underlying antibiotic overproduction providing valuable information about new possible molecular targets for rationale strain improvement.

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. 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. 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.

A peculiar feature of all living beings is their capability to communicate. With the discovery of the quorum sensing phenomenon in bioluminescent bacteria in the late 1960s, it became clear that intraspecies and interspecies communications and social behaviors also occur in simple microorganisms such as bacteria. However, at that time, it was difficult to imagine how such small organisms—invisible to the naked eye—could influence the behavior and wellbeing of the larger, more complex and visible organisms they colonize. Now that we know this information, the challenge is to identify the myriad of bacterial chemical signals and communication networks that regulate the life of what can be defined, in a whole, as a meta-organism. In this review, we described the transkingdom crosstalk between bacteria, insects, and plants from an ecological perspective, providing some paradigmatic examples. Second, we reviewed what is known about the genetic and biochemical bases of the bacterial chemical communication with other organisms and how explore the semiochemical potential of a bacterium can be explored. Finally, we illustrated how bacterial semiochemicals managing the transkingdom communication may be exploited from a biotechnological point of view.

Pyroptosis is a gasdermin-mediated pro-inflammatory programmed cell death that, during microbial infections, aims to restrict the spreading of bacteria. Nevertheless, excessive pyroptosis activation leads to inflammation levels that are detrimental to the host. Pathogen-associated molecular patterns (PAMPs) present in bacteria and outer membrane vesicles (OMVs) can trigger pyroptosis pathways in different cell types with different outcomes. Moreover, some pathogens have evolved virulence factors that directly interfere with pyroptosis pathways, like Yersinia pestis YopM and Shigella flexneri IpaH7.8. Other virulence factors, such as those of Neisseria meningitidis, Neisseria gonorrhoeae, Salmonella enterica, and Helicobacter pylori affect pyroptosis pathways indirectly with important differences between pathogenic and commensal species of the same family. These pathogens deserve special attention because of the increasing antimicrobial resistance of S. flexneri and N. gonorrhoeae, the high prevalence of S. enterica and H. pylori, and the life-threatening diseases caused by N. meningitidis and Y. pestis. While inflammation due to macrophage pyroptosis has been extensively addressed, the effects of activation of pyroptosis pathways on modulation of cell cytoskeleton and cell–cell junctions in epithelia and endothelia and on the bacterial crossing of epithelial and endothelial barriers have only been partly investigated. Another important point is the diverse consequences of pyroptosis pathways on calcium influx, like activation of calcium-dependent enzymes and mitochondria dysregulation. This review will discuss the pyroptotic pathways activated by Gram-negative bacteria and their OMVs, analyzing the differences between pathogens and commensal bacteria. Particular attention will also be paid to the experimental models adopted and the main results obtained in the different models. Finally, strategies adopted by pathogens to modulate these pathways will be discussed with a perspective on the use of pyroptosis inhibitors as adjuvants in the treatment of infections.