Publisher Correction: Extensive signal integration by the phytohormone protein network.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Extensive signal integration by the phytohormone protein network.

Plant hormones coordinate responses to environmental cues with developmental programs1, and are fundamental for stress resilience and agronomic yield2. The core signalling pathways underlying the effects of phytohormones have been elucidated by genetic screens and hypothesis-driven approaches, and extended by interactome studies of select pathways3. However, fundamental questions remain about how information from different pathways is integrated. Genetically, most phenotypes seem to be regulated by several hormones, but transcriptional profiling suggests that hormones trigger largely exclusive transcriptional programs4. We hypothesized that protein-protein interactions have an important role in phytohormone signal integration. Here, we experimentally generated a systems-level map of the Arabidopsis phytohormone signalling network, consisting of more than 2,000 binary protein-protein interactions. In the highly interconnected network, we identify pathway communities and hundreds of previously unknown pathway contacts that represent potential points of crosstalk. Functional validation of candidates in seven hormone pathways reveals new functions for 74% of tested proteins in 84% of candidate interactions, and indicates that a large majority of signalling proteins function pleiotropically in several pathways. Moreover, we identify several hundred largely small-molecule-dependent interactions of hormone receptors. Comparison with previous reports suggests that noncanonical and nontranscription-mediated receptor signalling is more common than hitherto appreciated.

A proteome-scale map of the SARS-CoV-2-human contactome.

Understanding the mechanisms of coronavirus disease 2019 (COVID-19) disease severity to efficiently design therapies for emerging virus variants remains an urgent challenge of the ongoing pandemic. Infection and immune reactions are mediated by direct contacts between viral molecules and the host proteome, and the vast majority of these virus-host contacts (the 'contactome') have not been identified. Here, we present a systematic contactome map of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with the human host encompassing more than 200 binary virus-host and intraviral protein-protein interactions. We find that host proteins genetically associated with comorbidities of severe illness and long COVID are enriched in SARS-CoV-2 targeted network communities. Evaluating contactome-derived hypotheses, we demonstrate that viral NSP14 activates nuclear factor κB (NF-κB)-dependent transcription, even in the presence of cytokine signaling. Moreover, for several tested host proteins, genetic knock-down substantially reduces viral replication. Additionally, we show for USP25 that this effect is phenocopied by the small-molecule inhibitor AZ1. Our results connect viral proteins to human genetic architecture for COVID-19 severity and offer potential therapeutic targets.

In vivo promoter engineering in plants: Are we ready?

Engineering plant promoter sequence for optimal expression of a gene has been a long standing goal for plant scientists. In recent times, Sequence Specific Nucleases (SSNs) like CRISPR/Cas9 are enabling researchers to achieve this goal, in vivo in the genome. It is well known that SSNs have met with unprecedented success in rapid transgene free crop improvement largely by targeting the coding sequence. Here, we discuss the strategies being employed by plant scientists in targeting SSNs to non-coding promoter regions/Cis Regulatory Elements (CRE). We collectively refer all such endeavors as in vivo promoter engineering (IPE). We further classify the IPE efforts into CRE addition, CRE deletion/disruption, promoter swap/insertion and targeted promoter polymorphism. Till date, IPE has proven useful in altering plant architecture in tomato, developing resistance against Xanthomonas sp in rice and citrus, and engineering drought tolerance in maize. However it is quite challenging to achieve predictable changes in gene expression using IPE at this point. In future years, data generated from high throughput techniques to investigate non coding genome may immensely augment the efforts in this direction. As IPE does not involve addition of the transgene for modifying crop traits, it will be relatively more conducive to public acceptance in crop improvement programs.