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Biotin attachment domain-containing proteins mediate hydroxy fatty acid-dependent inhibition of acetyl CoA carboxylase
Hundreds of naturally occurring specialized fatty acids (FAs) have potential as desirable chemical feedstocks if they could be produced at large scale by crop plants; however, transgenic expression of their biosynthetic genes has generally been accompanied by dramatic reductions in oil yield. For example, expression of castor (Ricinus communis) FA hydroxylase (FAH) in the Arabidopsis thaliana FA elongation mutant fae1 resulted in a 50% reduction of FA synthesis rate that was attributed to inhibition of acetyl-CoA carboxylase (ACCase) by an undefined mechanism. Here, we tested the hypothesis that the ricinoleic acid-dependent decrease in ACCase activity is mediated by biotin attachment domain-containing (BADC) proteins. BADCs are inactive homologs of biotin carboxy carrier protein that lack a biotin cofactor and can inhibit ACCase. Arabidopsis contains three BADC genes. To reduce expression levels of BADC1 and BADC3 in fae1/FAH plants, a homozygous badc1,3/fae1/FAH line was created. The rate of FA synthesis in badc1,3/fae1/FAH seeds doubled relative to fae1/FAH, restoring it to fae1 levels, increasing both native FA and HFA accumulation. Total FA per seed, seed oil content, and seed yield per plant all increased in badc1,3/fae1/FAH, to 5.8 µg, 37%, and 162 mg, respectively, relative to 4.9 µg, 33%, and 126 mg, respectively, for fae1/FAH. Transcript levels of FA synthesis-related genes, including those encoding ACCase subunits, did not significantly differ between badc1,3/fae1/FAH and fae1/FAH. These results demonstrate that BADC1 and BADC3 mediate ricinoleic acid-dependent inhibition of FA synthesis. We propose that BADC-mediated FAS inhibition as a general mechanism that limits FA accumulation in specialized FA-accumulating seeds.
Plant Metabolic Network 15: A resource of genome-wide metabolism databases for 126 plants and algae
To understand and engineer plant metabolism, we need a comprehensive and accurate annotation of all metabolic information across plant species. As a step towards this goal, we, in this study, generated genome-scale metabolic pathway databases of 126 algal and plant genomes, ranging from model organisms to crops to medicinal plants (https://plantcyc.org). Of these, 104 have not been reported before. We systematically evaluated the quality of the databases, which revealed that our semi-automated validation pipeline dramatically improves the quality. We then compared the metabolic content across the 126 organisms using multiple correspondence analysis and found that Brassicaceae, Poaceae, and Chlorophyta appeared as metabolically distinct groups. To demonstrate the utility of this resource, we used recently published sorghum transcriptomics data to discover previously unreported trends of metabolism underlying drought tolerance. We also used single-cell transcriptomics data from the Arabidopsis root to infer cell type-specific metabolic pathways. This work shows the quality and quantity of our resource and demonstrates its wide-ranging utility in integrating metabolism with other areas of plant biology.
A multi-ancestry genetic study of pain intensity in 598,339 veterans
Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects the quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids had a central role in precipitating the opioid crisis. Despite an estimated heritability of 25–50%, the genetic architecture of chronic pain is not well-characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 126 independent genetic loci, 69 of which are new. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level and cognitive traits. Integration of the genome-wide association studies findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, β-blockers and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.
Abundance of Major Cell Wall Components in Natural Variants and Pedigrees of Populus trichocarpa
The rapid analysis of biopolymers including lignin and sugars in lignocellulosic biomass cell walls is essential for the analysis of the large sample populations needed for identifying heritable genetic variation in biomass feedstocks for biofuels and bioproducts. In this study, we reported the analysis of cell wall lignin content, syringyl/guaiacyl (S/G) ratio, as well as glucose and xylose content by high-throughput pyrolysis-molecular beam mass spectrometry (py-MBMS) for >3,600 samples derived from hundreds of accessions of Populus trichocarpa from natural populations, as well as pedigrees constructed from 14 parents (7 × 7). Partial Least Squares (PLS) regression models were built from the samples of known sugar composition previously determined by hydrolysis followed by nuclear magnetic resonance (NMR) analysis. Key spectral features positively correlated with glucose content consisted of m/z 126, 98, and 69, among others, deriving from pyrolyzates such as hydroxymethylfurfural, maltol, and other sugar-derived species. Xylose content positively correlated primarily with many lignin-derived ions and to a lesser degree with m/z 114, deriving from a lactone produced from xylose pyrolysis. Models were capable of predicting glucose and xylose contents with an average error of less than 4%, and accuracy was significantly improved over previously used methods. The differences in the models constructed from the two sample sets varied in training sample number, but the genetic and compositional uniformity of the pedigree set could be a potential driver in the slightly better performance of that model in comparison with the natural variants. Broad-sense heritability of glucose and xylose composition using these data was 0.32 and 0.34, respectively. In summary, we have demonstrated the use of a single high-throughput method to predict sugar and lignin composition in thousands of poplar samples to estimate the heritability and phenotypic plasticity of traits necessary to develop optimized feedstocks for bioenergy applications.