Cryptochromes are blue-light absorbing flavoproteins with multiple signaling roles. In plants, cryptochrome (cry1, cry2) biological activity has been linked to flavin photoreduction via an electron transport chain to the protein surface comprising 3 evolutionarily conserved tryptophan residues known as the 'Trp triad.' Mutation of any of the Trp triad residues abolishes photoreduction in isolated cryptochrome protein in vitro and therefore had been suggested as essential for electron transfer to the flavin. However, photoreduction of the flavin in Arabidopsis cry2 proteins occurs in vivo even with mutations in the Trp triad, indicating the existence of alternative electron transfer pathways to the flavin. These pathways are potentiated by metabolites in the intracellular environment including ATP, ADP, AMP, and NADH. In the present work we extend these observations to Arabidopsis cryptochrome 1 and demonstrate that Trp triad substitution mutants at W400F and W324F positions which are not photoreduced in vitro can be photoreduced in whole cell extracts, albeit with reduced efficiency. We further show that the flavin signaling state (FADH°) is stabilized in an in vivo context. These data illustrate that in vivo modulation by metabolites in the cellular environment may play an important role in cryptochrome signaling, and are discussed with respect to possible effects on the conformation of the C-terminal domain to generate the biologically active conformational state.

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.