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Vascular plants direct large amounts of carbon to produce the aromatic amino acid phenylalanine to support the production of lignin and other phenylpropanoids. Uniquely, grasses, which include many major crops, can synthesize lignin and phenylpropanoids from both phenylalanine and tyrosine. However, how grasses regulate aromatic amino acid biosynthesis to feed this dual lignin pathway is unknown. Here we show, by stable-isotope labeling, that grasses produce tyrosine >10-times faster than Arabidopsis without compromising phenylalanine biosynthesis. Detailed in vitro enzyme characterization and combinatorialin plantaexpression uncovered that coordinated expression of specific enzyme isoforms at the entry and exit steps of the aromatic amino acid pathway enables grasses to maintain high production of both tyrosine and phenylalanine, the precursors of the dual lignin pathway. These findings highlight the complex regulation of plant aromatic amino acid biosynthesis and provide novel genetic tools to engineer the interface of primary and specialized metabolism in plants.

 

The measurement of the charge asymmetry for highly boosted top quark pairs decaying to a single lepton and jets is presented. The analysis is performed using 138 fb−1 of data collected in pp collisions at s√=13 TeV with the CMS detector during Run 2 of the Large Hadron Collider. The selection is optimized for top quark-antiquark pairs produced with large Lorentz boosts, resulting in non-isolated leptons and overlapping jets. The top quark charge asymmetry is measured for events with tt⎯⎯ invariant mass larger than 750 GeV and corrected for detector and acceptance effects using a binned maximum likelihood fit. The measured top quark charge asymmetry is in good agreement with the standard model prediction at next-to-next-to-leading order in perturbation theory with next-to-leading order electroweak corrections. Differential distributions for two invariant mass ranges are also presented. 

Climate change models often assume similar responses to temperatures across the range of a species, but local adaptation or phenotypic plasticity can lead plants and animals to respond differently to temperature in different parts of their range. To date, there have been few tests of this assumption at the scale of continents, so it is unclear if this is a large‐scale problem. Here, we examined the assumption that insect taxa show similar responses to temperature at 96 sites in grassy habitats across North America. We sampled insects with Malaise traps during 2019–2021 (N = 1041 samples) and examined the biomass of insects in relation to temperature and time of season. Our samples mostly contained Diptera (33%), Lepidoptera (19%), Hymenoptera (18%), and Coleoptera (10%). We found strong regional differences in the phenology of insects and their response to temperature, even within the same taxonomic group, habitat type, and time of season. For example, the biomass of nematoceran flies increased across the season in the central part of the continent, but it only showed a small increase in the Northeast and a seasonal decline in the Southeast and West. At a smaller scale, insect biomass at different traps operating on the same days was correlated up to ~75 km apart. Large‐scale geographic and phenological variation in insect biomass and abundance has not been studied well, and it is a major source of controversy in previous analyses of insect declines that have aggregated studies from different locations and time periods. Our study illustrates that large‐scale predictions about changes in insect populations, and their causes, will need to incorporate regional and taxonomic differences in the response to temperature.

 

l‐Tyrosine is an essential aromatic amino acid required for the synthesis of proteins and a diverse array of plant natural products; however, little is known on how the levels of tyrosine are controlledin plantaand linked to overall growth and development. Most plants synthesize tyrosine by TyrA arogenate dehydrogenases, which are strongly feedback‐inhibited by tyrosine and encoded byTyrA1andTyrA2genes inArabidopsis thaliana. While TyrA enzymes have been extensively characterized at biochemical levels, theirin plantafunctions remain uncertain. Here we found thatTyrA1suppression reduces seed yield due to impaired anther dehiscence, whereasTyrA2knockout leads to slow growth with reticulate leaves. Thetyra2mutant phenotypes were exacerbated byTyrA1suppression and rescued by the expression ofTyrA2,TyrA1or tyrosine feeding. Low‐light conditions synchronized thetyra2and wild‐type growth, and ameliorated thetyra2leaf reticulation. After shifting to normal light,tyra2transiently decreased tyrosine and subsequently increased aspartate before the appearance of the leaf phenotypes. Overexpression of the deregulated TyrA enzymes led to hyper‐accumulation of tyrosine, which was also accompanied by elevated aspartate and reticulate leaves. These results revealed that TyrA1 and TyrA2 have distinct and overlapping functions in flower and leaf development, respectively, and that imbalance of tyrosine, caused by altered TyrA activity and regulation, impacts growth and development of Arabidopsis. The findings provide critical bases for improving the production of tyrosine and its derived natural products, and further elucidating the coordinated metabolic and physiological processes to maintain tyrosine levels in plants.

 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.