Activation of cryptic biosynthetic gene clusters by fungal artificial chromosomes to produce novel secondary metabolites.

In 2017, we reported the discovery of Berkeleylactone A (BPLA), a novel, potent antibiotic produced exclusively in co-culture by two extremophilic fungi, Penicillium fuscum and P. camembertii/clavigerum, which were isolated from the Berkeley Pit, an acid mine waste lake, in Butte, Montana. Neither fungus synthesized BPLA when grown in axenic culture. Recent studies suggest that secondary metabolites (SMs) are often synthesized by enzymes encoded by co-localized genes that form "biosynthetic gene clusters" (BGCs), which might remain silent (inactive) under various fermentation conditions. Fungi may also harbor cryptic BGCs that are not associated with previously characterized molecules. We turned to the tools of Fungal Artificial Chromosomes (FAC)-Next-Gen-Sequencing (NGS) to understand how co-culture activated cryptic biosynthesis of BPLA and several related berkeleylactones and to further investigate the true biosynthetic potential of these two fungi. FAC-NGS enables the capture of BGCs as individual FACs for heterologous expression in a modified strain of Aspergillus nidulans (heterologous host, FAC-AnHH). With this methodology, we created ten BGC-FACs that yielded fourteen different SMs, including strobilurin, which was previously isolated exclusively from basidiomycetes. Eleven of these compounds were not detected in the extracts of the FAC-AnHH. Of this discrete set, only the novel compound citreohybriddional had been isolated from either Penicillium sp. before and only at very low yield. We propose that through heterologous expression, FACs activated these silent BGCs, resulting in the synthesis of new natural products (NPs) with yields as high as 50%-60% of the crude organic extracts.

Modeling the Pseudomonas Sulfur Regulome by Quantifying the Storage and Communication of Information.

Bacteria are not simply passive consumers of nutrients or merely steady-state systems. Rather, bacteria are active participants in their environments, collecting information from their surroundings and processing and using that information to adapt their behavior and optimize survival. The bacterial regulome is the set of physical interactions that link environmental information to the expression of genes by way of networks of sensors, transporters, signal cascades, and transcription factors. As bacteria cannot have one dedicated sensor and regulatory response system for every possible condition that they may encounter, the sensor systems must respond to a variety of overlapping stimuli and collate multiple forms of information to make "decisions" about the most appropriate response to a specific set of environmental conditions. Here, we analyze Pseudomonas fluorescens transcriptional responses to multiple sulfur nutrient sources to generate a predictive, computational model of the sulfur regulome. To model the regulome, we utilize a transmitter-channel-receiver scheme of information transfer and utilize principles from information theory to portray P. fluorescens as an informatics system. This approach enables us to exploit the well-established metrics associated with information theory to model the sulfur regulome. Our computational modeling analysis results in the accurate prediction of gene expression patterns in response to the specific sulfur nutrient environments and provides insights into the molecular mechanisms of Pseudomonas sensory capabilities and gene regulatory networks. In addition, modeling the bacterial regulome using the tools of information theory is a powerful and generalizable approach that will have multiple future applications to other bacterial regulomes. IMPORTANCE Bacteria sense and respond to their environments using a sophisticated array of sensors and regulatory networks to optimize their fitness and survival in a constantly changing environment. Understanding how these regulatory and sensory networks work will provide the capacity to predict bacterial behaviors and, potentially, to manipulate their interactions with an environment or host. Leveraging the information theory provides useful quantitative metrics for modeling the information processing capacity of bacterial regulatory networks. As our model accurately predicted gene expression profiles in a bacterial model system, we posit that the information theory-based approaches will be important to enhance our understanding of a wide variety of bacterial regulomes and our ability to engineer bacterial sensory and regulatory networks.

Dynamics of Aspen Roots Colonization by Pseudomonads Reveals Strain-Specific and Mycorrhizal-Specific Patterns of Biofilm Formation.

Rhizosphere-associated Pseudomonas fluorescens are known plant growth promoting (PGP) and mycorrhizal helper bacteria (MHB) of many plants and ectomycorrhizal fungi. We investigated the spatial and temporal dynamics of colonization of mycorrhizal and non-mycorrhizal Aspen seedlings roots by the P. fluorescens strains SBW25, WH6, Pf0-1, and the P. protegens strain Pf-5. Seedlings were grown in laboratory vertical plates systems, inoculated with a fluorescently labeled Pseudomonas strain, and root colonization was monitored over a period of 5 weeks. We observed unexpected diversity of bacterial assemblies on seedling roots that changed over time and were strongly affected by root mycorrhization. P. fluorescens SBW25 and WH6 stains developed highly structured biofilms with internal void spaces forming channels. On mycorrhizal roots bacteria appeared encased in a mucilaginous substance in which they aligned side by side in parallel arrangements. The different phenotypic classes of bacterial assemblies observed for the four Pseudomonas strains were summarized in a single model describing transitions between phenotypic classes. Our findings also reveal that bacterial assembly phenotypes are driven by interactions with mucilaginous materials present at roots.

Transport capabilities of environmental Pseudomonads for sulfur compounds.

Sulfur is an essential element in plant rhizospheres and microbial activity plays a key role in increasing the biological availability of sulfur in soil environments. To better understand the mechanisms facilitating the exchange of sulfur-containing molecules in soil, we profiled the binding specificities of eight previously uncharacterized ABC transporter solute-binding proteins from plant-associated Pseudomonads. A high-throughput screening procedure indicated eighteen significant organosulfur binding ligands, with at least one high-quality screening hit for each protein target. Calorimetric and spectroscopic methods were used to validate the best ligand assignments and catalog the thermodynamic properties of the protein-ligand interactions. Two novel high-affinity ligand-binding activities were identified and quantified in this set of solute-binding proteins. Bacteria were cultured in minimal media with screening library components supplied as the sole sulfur sources, demonstrating that these organosulfur compounds can be metabolized and confirming the relevance of ligand assignments. These results expand the set of experimentally validated ligands amenable to transport by this ABC transporter family and demonstrate the complex range of protein-ligand interactions that can be accomplished by solute-binding proteins. Characterizing new nutrient import pathways provides insight into Pseudomonad metabolic capabilities which can be used to further interrogate bacterial survival and participation in soil and rhizosphere communities.