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We demonstrate that contrastive representation learning is a computationally efficient and flexible method to incorporate physical constraints, especially those defined by equalities, in machine-learning-based density functional design.

Intracellular plant immune receptors, termed NLRs (Nucleotide-binding Leucine-rich repeat Receptors), confer effector-triggered immunity. Sensor NLRs are responsible for pathogen effector recognition. Helper NLRs function downstream of sensor NLRs to transduce signaling and induce cell death and immunity. Activation of sensor NLRs that contain TIR (Toll/interleukin-1receptor) domains generates small molecules that induce an association between a downstream heterodimer signalosome of EDS1 (EnhancedDisease Susceptibility 1)/SAG101 (Senescence-AssociatedGene 101) and the helper NLR of NRG1 (NRequired Gene 1). Autoactive NRG1s oligomerize and form calcium signaling channels largely localized at the plasma membrane (PM). The molecular mechanisms of helper NLR PM association and effector-induced NRG1 oligomerization are not well characterized. We demonstrate that helper NLRs require positively charged residues in their N-terminal domains for phospholipid binding and PM association before and after activation, despite oligomerization and conformational changes that accompany activation. We demonstrate that effector activation of a TIR-containing sensor NLR induces NRG1 oligomerization at the PM and that the cytoplasmic pool of EDS1/SAG101 is critical for cell death function. EDS1/SAG101 cannot be detected in the oligomerized NRG1 resistosome, suggesting that additional unknown triggers might be required to induce the dissociation of EDS1/SAG101 from the previously described NRG1/EDS1/SAG101 heterotrimer before subsequent NRG1 oligomerization. Alternatively, the conformational changes resulting from NRG1 oligomerization abrogate the interface for EDS1/SAG101 association. Our data provide observations regarding dynamic PM association during helper NLR activation and underpin an updated model for effector-induced NRG1 resistosome formation.

Study Analysis Group 21 (SAG21) of NASA’s Exoplanet Exploration Program Analysis Group was organized to study the effect of stellar contamination on space-based transmission spectroscopy, a method for studying exoplanetary atmospheres by measuring the wavelength-dependent radius of a planet as it transits its star. Transmission spectroscopy relies on a precise understanding of the spectrum of the star being occulted. However, stars are not homogeneous, constant light sources but have temporally evolving photospheres and chromospheres with inhomogeneities like spots, faculae, plages, granules, and flares. This SAG brought together an interdisciplinary team of more than 100 scientists, with observers and theorists from the heliophysics, stellar astrophysics, planetary science, and exoplanetary atmosphere research communities, to study the current research needs that can be addressed in this context to make the most of transit studies from current NASA facilities like Hubble Space Telescope and JWST. The analysis produced 14 findings, which fall into three science themes encompassing (i) how the Sun is used as our best laboratory to calibrate our understanding of stellar heterogeneities (‘The Sun as the Stellar Benchmark’), (ii) how stars other than the Sun extend our knowledge of heterogeneities (‘Surface Heterogeneities of Other Stars’), and (iii) how to incorporate information gathered for the Sun and other stars into transit studies (‘Mapping Stellar Knowledge to Transit Studies’). In this invited review, we largely reproduce the final report of SAG21 as a contribution to the peer-reviewed literature.