Ultraviolet-B (UV-B) radiation present in sunlight is an important trigger of photomorphogenic acclimation and stress responses in sessile land plants. Although numerous moss species grow in unshaded habitats, our understanding of their UV-B responses is very limited. The genome of the model moss Physcomitrella patens, which grows in sun-exposed open areas, encodes signaling and metabolic components that are implicated in the UV-B response in flowering plants. In this study, we describe the response of P. patens to UV-B radiation at the morphological and molecular levels. We find that P. patens is more capable of surviving UV-B stress than Arabidopsis (Arabidopsis thaliana) and describe the differential expression of approximately 400 moss genes in response to UV-B radiation. A comparative analysis of the UV-B response in P. patens and Arabidopsis reveals both distinct and conserved pathways.Ultraviolet-B (UV-B) radiation (280-315 nm) is intrinsic to sunlight reaching the surface of the earth. During the Phanerozoic period (within the last 545 million years), the levels of UV-B reaching the biosphere generally decreased (Rozema et al., 2009). In particular, the development of a stratospheric ozone layer filtering out all UV-C (less than 280 nm) and part of the UV-B radiation was likely a prerequisite for terrestrial plant life and accompanied by the development of phenolic sunscreens in plants (Rozema et al., 1997). During early land plant evolution, the divergence of the last common ancestor of bryophytes (comprising liverworts, true mosses, and hornworts) and vascular plants (comprising lycophytes, ferns, and seed plants) occurred shortly after the water-to-landtransition in the Ordovician period, at least 450 million years ago . If the level of UV-B reaching the ground was significantly higher at that time than today, it is to be expected that protective mechanisms and their corresponding signaling pathways evolved at that time and thus should be present in all land plants.Today, ambient UV-B radiation still has a broad effect on plants relying on sunlight for photosynthesis, and its level varies strongly with season and time of day as well as with latitude and altitude (Paul and Gwyn-Jones, 2003). As an environmental stress factor, it may evoke diverse damage to a broad range of cellular constituents, including DNA (Britt, 2004). However, plants in nature are seldom visibly damaged by UV-B but are generally rather well acclimated and thus protected. This largely results from effective repair and protection mechanisms (Frohnmeyer and Staiger, 2003;Ulm and Nagy, 2005;Jenkins, 2009). A common protective measure against UV-B radiation is the synthesis of secondary metabolites acting as UV-absorbing compounds and accumulating in the vacuoles of epidermal cells. These compounds are mostly phenolic, including flavonoids and sinapate esters, and are at least partly induced by UV-B (Jenkins, 2009;Stracke et al., 2010). Next to this protective sunscreen, plants contain effective DNA repair pathways, particularly inclu...

Although it is often tacitly assumed that gene regulatory interactions are finely tuned, how accurate gene regulation could evolve from a state without regulation is unclear. Moreover, gene expression noise would seem to impede the evolution of accurate gene regulation, and previous investigations have provided circumstantial evidence that natural selection has acted to lower noise levels. By evolving synthetic Escherichia coli promoters de novo, we here show that, contrary to expectations, promoters exhibit low noise by default. Instead, selection must have acted to increase the noise levels of highly regulated E. coli promoters. We present a general theory of the interplay between gene expression noise and gene regulation that explains these observations. The theory shows that propagation of expression noise from regulators to their targets is not an unwanted side-effect of regulation, but rather acts as a rudimentary form of regulation that facilitates the evolution of more accurate regulation.DOI: http://dx.doi.org/10.7554/eLife.05856.001

SUMMARYThe moss Physcomitrella patens is an important model organism for studying plant evolution, development, physiology and biotechnology. Here we have generated microarray gene expression data covering the principal developmental stages, culture forms and some environmental/stress conditions. Example analyses of developmental stages and growth conditions as well as abiotic stress treatments demonstrate that (i) growth stage is dominant over culture conditions, (ii) liquid culture is not stressful for the plant, (iii) low pH might aid protoplastation by reduced expression of cell wall structure genes, (iv) largely the same gene pool mediates response to dehydration and rehydration, and (v) AP2/EREBP transcription factors play important roles in stress response reactions. With regard to the AP2 gene family, phylogenetic analysis and comparison with Arabidopsis thaliana shows commonalities as well as uniquely expressed family members under drought, light perturbations and protoplastation. Gene expression profiles for P. patens are available for the scientific community via the easy-to-use tool at https://www.genevestigator.com. By providing large-scale expression profiles, the usability of this model organism is further enhanced, for example by enabling selection of control genes for quantitative real-time PCR. Now, gene expression levels across a broad range of conditions can be accessed online for P. patens.

Determining the molecular changes that give rise to functional innovations is a major unresolved problem in biology. The paucity of examples has served as a significant hindrance in furthering our understanding of this process. Here we used experimental evolution with the bacterium Escherichia coli to quantify the molecular changes underlying functional innovation in 68 independent instances ranging over 22 different metabolic functions. Using whole-genome sequencing, we show that the relative contribution of regulatory and structural mutations depends on the cellular context of the metabolic function. In addition, we find that regulatory mutations affect genes that act in pathways relevant to the novel function, whereas structural mutations affect genes that act in unrelated pathways. Finally, we use population genetic modeling to show that the relative contributions of regulatory and structural mutations during functional innovation may be affected by population size. These results provide a predictive framework for the molecular basis of evolutionary innovation, which is essential for anticipating future evolutionary trajectories in the face of rapid environmental change.adaptation | transcription | compensatory mutation | biosynthesis O ne of the most important questions in evolutionary biology concerns the molecular mechanisms that underlie functional innovations. These changes are often polarized into two classes: those that affect protein structure and those that affect protein expression level. Both of these classes have been shown to play important roles across a wide range of taxa, from vertebrates (1, 2) to bacteria (3, 4), and their relative importance has been the topic of considerable discussion (5-12). Significantly, many previous studies have addressed these questions by focusing on single instances of functional innovation (13-16) or selective regimes (17)(18)(19)(20)(21)(22). However, to identify general principles, it is necessary to study evolutionary innovation for a large number of different functions in parallel. Indeed, the fact that only a small number of examples exist has resulted in few hypotheses being put forth that identify general characteristics of the molecular changes underlying functional innovation. One prominent hypothesis states that if the development of a novel trait is spatially or temporally limited, then innovation frequently occurs through changes in regulation (23,24). Whether there are general patterns beyond this is not well-established.Here we used an experimental system that allows the analysis of a large number of independent cases of evolutionary innovation and investigation of the underlying genetic changes. We worked with a collection of 87 strains of Escherichia coli that each had a deletion of one gene encoding a different metabolic function (SI Appendix, Table S1). Each of these deletions resulted in an inability to grow in minimal glucose media. Then, for each of these 87 deleted metabolic functions, we used experimental evolution to select for novel func...

Identification of novel antibiotics remains a major challenge for drug discovery. The present study explores use of phenotypic readouts beyond classical antibacterial growth inhibition adopting a combined multiparametric high content screening and genomic approach. Deployment of the semi-automated bacterial phenotypic fingerprint (BPF) profiling platform in conjunction with a machine learning-powered dataset analysis, effectively allowed us to narrow down, compare and predict compound mode of action (MoA). The method identifies weak antibacterial hits allowing full exploitation of low potency hits frequently discovered by routine antibacterial screening. We demonstrate that BPF classification tool can be successfully used to guide chemical structure activity relationship optimization, enabling antibiotic development and that this approach can be fruitfully applied across species. The BPF classification tool could be potentially applied in primary screening, effectively enabling identification of novel antibacterial compound hits and differentiating their MoA, hence widening the known antibacterial chemical space of existing pharmaceutical compound libraries. More generally, beyond the specific objective of the present work, the proposed approach could be profitably applied to a broader range of diseases amenable to phenotypic drug discovery.

Across the plant kingdom, phytochrome (PHY) photoreceptors play an important role during adaptive and developmental responses to light. In , light-activated PHYs accumulate in the nucleus, where they regulate downstream signaling components, such as phytochrome interacting factors (PIFs). PIFs are transcription factors that act as repressors of photomorphogenesis; their inhibition by PHYs leads to substantial changes in gene expression. The nuclear function of PHYs, however, has so far been investigated in only a few non-seed plants. Here, we identified putative target genes of PHY signaling in the moss and found light-regulated genes that are putative orthologs of PIF-controlled genes in Arabidopsis. Phylogenetic analyses revealed that an ancestral PIF-like gene was already present in streptophyte algae, i.e., before the water-to-land transition of plants. The PIF homologs in the genome of resemble Arabidopsis PIFs in their protein domain structure, molecular properties, and physiological effects, albeit with notable differences in the motif-dependent PHY interaction. Our results suggest that PIFs are involved in PHY signaling. The PHY-PIF signaling node that relays light signals to target genes has been largely conserved during land plant evolution, with evidence of lineage-specific diversification.

Although it is often tacitly assumed that gene regulatory interactions are finely tuned, how accurate gene regulation could evolve from a state without regulation is unclear. Moreover, gene expression noise would seem to impede the evolution of accurate gene regulation, and previous investigations have provided circumstantial evidence that natural selection has acted to lower noise levels. By evolving synthetic Escherichia coli promoters de novo, we here show that, contrary to expectations, promoters exhibit low noise by default. Instead, selection must have acted to increase the noise levels of highly regulated E. coli promoters. We present a general theory of the interplay between gene expression noise and gene regulation that explains these observations. The theory shows that propagation of expression noise from regulators to their targets is not an unwanted side-effect of regulation, but rather acts as a rudimentary form of regulation that facilitates the evolution of more accurate regulation.

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