Functional metagenomics, the study of the collective genome of a microbial community by expressing it in a foreign host, is an emerging field in biotechnology. Over the past years, the possibility of novel product discovery through metagenomics has developed rapidly. Thus, metagenomics has been heralded as a promising mining strategy of resources for the biotechnological and pharmaceutical industry. However, in spite of innovative work in the field of functional genomics in recent years, yields from function-based metagenomics studies still fall short of producing significant amounts of new products that are valuable for biotechnological processes. Thus, a new set of strategies is required with respect to fostering gene expression in comparison to the traditional work. These new strategies should address a major issue, that is, how to successfully express a set of unknown genes of unknown origin in a foreign host in high throughput. This article is an opinionating review of functional metagenomic screening of natural microbial communities, with a focus on the optimization of new product discovery. It first summarizes current major bottlenecks in functional metagenomics and then provides an overview of the general metagenomic assessment strategies, with a focus on the challenges that are met in the screening for, and selection of, target genes in metagenomic libraries. To identify possible screening limitations, strategies to achieve optimal gene expression are reviewed, examining the molecular events all the way from the transcription level through to the secretion of the target gene product.

Microbial evolution experiments provide a powerful tool to unravel the molecular basis of adaptive evolution but their outcomes can be difficult to interpret, unless the selective forces that are applied during the experiment are carefully controlled. In this respect, experimental evolution in continuous cultures provides advantages over commonly used sequential batch‐culture protocols because continuous cultures allow for more accurate control over the induced selective environment. However, commercial continuous‐culture systems are large and expensive, while available DIY continuous‐culture systems are not versatile enough to allow for multiple sensors and rigorous stirring. We present a modular continuous‐culture system that adopts the commonly used GL45 glass laboratory bottle as a bioreactor vessel. Our design offers three advantages: first, it is equipped with a large head plate, fitting two sensors and seven input/output ports, enabling the customization of the system for many running modes (chemostat, auxostat, etc.). Second, the bioreactor is small (25–250 ml), which makes it feasible to run many replicates in parallel. Third, bioreactor modules can be coupled by uni‐ or bi‐directional flows to induce spatiotemporal variation in selection. These features result in a particularly flexible culturing platform that facilitates the investigation of a broad range of evolutionary and ecological questions. To illustrate the versatility of our culturing system, we outline two evolution experiments that impose a temporally or spatially variable regime of selection. The first experiment illustrates how controlled temporal variation in resource availability can be utilized to select for anticipatory switching. The second experiment illustrates a spatially structured morbidostat setup that is designed to probe epistatic interactions between adaptive mutations. Furthermore, we demonstrate how sensor data can be used to stabilize selection pressures or track evolutionary adaptation. Evolution experiments in which populations are exposed to controlled spatiotemporal variation, are essential to gain insight into the process of adaptation and the mechanisms that constrain evolution. Continuous‐culture systems, like the one presented here, offer control over key environmental parameters and establish a well‐defined regime of selection. As such, they create the opportunity to expose evolutionary constraints in the form of phenotypic trade‐offs, contributing to a mechanistic understanding of adaptive evolution.

The chaplin proteins are instrumental in the formation of reproductive aerial structures by the filamentous bacterium Streptomyces coelicolor. They lower the water surface tension thereby enabling aerial growth. In addition, chaplins provide surface hydrophobicity to the aerial hyphae by assembling on the cell surface into an amphipathic layer of amyloid fibrils. We here show that mixtures of cell wall-extracted chaplins can be used to modify a variety of hydrophilic and hydrophobic surfaces in vitro thereby changing their nature. Assembly on glass leads to a protein coating that makes the surface hydrophobic. Conversely, the assembly of chaplins on hydrophobic surfaces renders them hydrophilic. Furthermore, we show that chaplins can stabilize emulsions of oil into water and have an unprecedented surface activity at high pH. Interestingly, this high surface activity coincides with the interfacial assembly of chaplins into a semi-liquid membrane, as opposed to the rigid membrane formed at neutral pH. This semi-liquid membrane possibly represents a trapped intermediate in the assembly process towards the more rigid amyloidal conformation. Taken together, our data shows that chaplins are suitable candidate proteins for a wide range of biotechnological applications.

Mitigating trade-offs between different resource-utilization functions is key to an organism’s ecological and evolutionary success. These trade-offs often reflect metabolic constraints with a complex molecular underpinning; therefore, their consequences for evolutionary processes have remained elusive. Here, we investigate how metabolic architecture induces resource utilization constraints and how these constraints, in turn, elicit evolutionary specialization and diversification. Guided by the metabolic network structure of the bacterium Lactococcus cremoris, we selected two carbon sources (fructose and galactose) with predicted co-utilization constraints. By evolving L. cremoris on either fructose, galactose or a mix of both sugars, we imposed selection favoring divergent metabolic specializations or co-utilization of both resources, respectively. Phenotypic characterization revealed the evolution of either fructose or galactose specialists in the single-sugar treatments. In the mixed sugar regime, we observed adaptive diversification: both specialists coexisted, and no generalist evolved. Divergence from the ancestral phenotype occurred at key pathway junctions in the central carbon metabolism. Fructose specialists evolved mutations in the fbp and pfk genes that appear to balance anabolic and catabolic carbon fluxes. Galactose specialists evolved increased expression of pgmA (the primary metabolic bottleneck of galactose metabolism) and silencing of ptnABCD (the main glucose transporter) and ldh (regulator/enzyme of downstream carbon metabolism). Overall, our study shows how metabolic network architecture and historical contingency serve to predict targets of selection and inform the functional interpretation of evolved mutations. The elucidation of the relationship between molecular constraints and phenotypic trade-offs contributes to an integrative understanding of evolutionary specialization and diversification.

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