The ‘Standard European Vector Architecture’ database (SEVA-DB, http://seva.cnb.csic.es) was conceived as a user-friendly, web-based resource and a material clone repository to assist in the choice of optimal plasmid vectors for de-constructing and re-constructing complex prokaryotic phenotypes. The SEVA-DB adopts simple design concepts that facilitate the swapping of functional modules and the extension of genome engineering options to microorganisms beyond typical laboratory strains. Under the SEVA standard, every DNA portion of the plasmid vectors is minimized, edited for flaws in their sequence and/or functionality, and endowed with physical connectivity through three inter-segment insulators that are flanked by fixed, rare restriction sites. Such a scaffold enables the exchangeability of multiple origins of replication and diverse antibiotic selection markers to shape a frame for their further combination with a large variety of cargo modules that can be used for varied end-applications. The core collection of constructs that are available at the SEVA-DB has been produced as a starting point for the further expansion of the formatted vector platform. We argue that adoption of the SEVA format can become a shortcut to fill the phenomenal gap between the existing power of DNA synthesis and the actual engineering of predictable and efficacious bacteria.

Robustness is the quality of any relational object (biological or otherwise) to maintain its components, its structure, and its function despite both external changes and endogenous fluctuations. Live systems are surprisingly robust, as they are able to not only preserve their physi-cochemical architecture in the face of variable nutritional and environmental conditions, but also tolerate stochastic variability in the concentrations of their components, fix errors resulting from hazardous events, and make virtually perfect copies of themselves. These qualities have started to be comprehended in full only since the application of network theory formalisms to regulatory phenomena. This review addresses the distinct role of network architecture (topology, logic) and biochemical/kinetic parameters in the materialization of various archetypical robust gene expression circuits in prokaryotes. Some take-home lessons for the construction of artificial regulatory networks (one of the trademarks of synthetic biology) are to be derived from such state of affairs.

The filamentous fungus Trichoderma reesei is a major producer of lignocellulolytic enzymes utilized by bioethanol industries. However, to achieve low cost second generation bioethanol production on an industrial scale an efficient mix of hydrolytic enzymes is required for the deconstruction of plant biomass. In this study, we investigated the molecular basis for lignocellulose-degrading enzyme production T. reesei during growth in cellulose, sophorose, and glucose. We examined and compared the transcriptome and differential secretome (2D-DIGE) of T. reesei grown in cellulose, sophorose, or glucose as the sole carbon sources. By applying a stringent cut-off threshold 2,060 genes were identified as being differentially expressed in at least one of the respective carbon source comparisons. Hierarchical clustering of the differentially expressed genes identified three possible regulons, representing 123 genes controlled by cellulose, 154 genes controlled by sophorose and 402 genes controlled by glucose. Gene regulatory network analyses of the 692 genes differentially expressed between cellulose and sophorose, identified only 75 and 107 genes as being specific to growth in sophorose and cellulose, respectively. 2D-DIGE analyses identified 30 proteins exclusive to sophorose and 37 exclusive to cellulose. A correlation of 70.17% was obtained between transcription and secreted protein profiles. Our data revealed new players in cellulose degradation such as accessory proteins with non-catalytic functions secreted in different carbon sources, transporters, transcription factors, and CAZymes, that specifically respond in response to either cellulose or sophorose.

Cryptococcus neoformans is an encapsulated fungal pathogen that causes cryptococcosis, which is a major opportunistic infection in immunosuppressed individuals. Mammalian β-galactoside-binding protein Galectin-3 (Gal-3) modulates the host innate and adaptive immunity, and plays significant roles during microbial infections including some fungal diseases. Here we show that this protein plays a role also in C. neoformans infection. We find augmented Gal-3 serum levels in human and experimental infections, as well as in spleen, lung, and brain tissues of infected mice. Gal-3-deficient mice are more susceptible to cryptococcosis than WT animals, as demonstrated by the higher fungal burden and lower animal survival. In vitro experiments show that Gal-3 inhibits fungal growth and exerts a direct lytic effect on C. neoformans extracellular vesicles (EVs). Our results indicate a direct role for Gal-3 in antifungal immunity whereby this molecule affects the outcome of C. neoformans infection by inhibiting fungal growth and reducing EV stability, which in turn could benefit the host.

Summary: When recombinant DNA technology was developed more than 40 years ago, no one could have imagined the impact it would have on both society and the scientific community. In the field of genetic engineering, the most important tool developed was the plasmid vector. This technology has been continuously expanding and undergoing adaptations. Here, we provide a detailed view following the evolution of vectors built throughout the years destined to study microorganisms and their peculiarities, including those whose genomes can only be revealed through metagenomics. We remark how synthetic biology became a turning point in designing these genetic tools to create meaningful innovations. We have placed special focus on the tools for engineering bacteria and fungi (both yeast and filamentous fungi) and those available to construct metagenomic libraries. Based on this overview, future goals would include the development of modular vectors bearing standardized parts and orthogonally designed circuits, a task not fully addressed thus far. Finally, we present some challenges that should be overcome to enable the next generation of vector design and ways to address it.