A newly evolved rice-specific gene JAUP1 regulates jasmonate biosynthesis and signalling to promote root development and multi-stress tolerance.

Root architecture and function are critical for plants to secure water and nutrient supply from the soil, but environmental stresses alter root development. The phytohormone jasmonic acid (JA) regulates plant growth and responses to wounding and other stresses, but its role in root development for adaptation to environmental challenges had not been well investigated. We discovered a novel JA Upregulated Protein 1 gene (JAUP1) that has recently evolved in rice and is specific to modern rice accessions. JAUP1 regulates a self-perpetuating feed-forward loop to activate the expression of genes involved in JA biosynthesis and signalling that confers tolerance to abiotic stresses and regulates auxin-dependent root development. Ectopic expression of JAUP1 alleviates abscisic acid- and salt-mediated suppression of lateral root (LR) growth. JAUP1 is primarily expressed in the root cap and epidermal cells (EPCs) that protect the meristematic stem cells and emerging LRs. Wound-activated JA/JAUP1 signalling promotes crosstalk between the root cap of LR and parental root EPCs, as well as induces cell wall remodelling in EPCs overlaying the emerging LR, thereby facilitating LR emergence even under ABA-suppressive conditions. Elevated expression of JAUP1 in transgenic rice or natural rice accessions enhances abiotic stress tolerance and reduces grain yield loss under a limited water supply. We reveal a hitherto unappreciated role for wound-induced JA in LR development under abiotic stress and suggest that JAUP1 can be used in biotechnology and as a molecular marker for breeding rice adapted to extreme environmental challenges and for the conservation of water resources.

Effect of seed biopriming with selected endophytes on the growth and chilling tolerance of rice plants.

The aim of this study was to develop an efficient bioinoculant for amelioration of adverse effects from chilling stress (10°C), which are frequently occurred during rice seedling stage. Seed germination bioassay under chilling condition with rice (Oryza sativa L.) cv. Tainan 11 was performed to screen for plant growth-promoting (PGP) bacteria among 41 chilling-tolerant rice endophytes. And several agronomic traits were used to evaluate the effects of bacterial inoculation on rice seedling, which were experienced for 7-d chilling stress in walk-in growth chamber. The field trials were further used to verify the performance of potential PGP endophytes on rice growth. A total of three endophytes with multiple PGP traits were obtained. It was demonstrated that Pseudomonas sp. CC-LS37 inoculation led to 18% increase of maximal efficiency of Photosystem II (PSII) after 7-d chilling stress and 7% increase of chlorophyll a content, and 64% decline of malondialdehyde content in shoot after 10-d recovery at normal temperature in walk-in growth chamber. In field trial, biopriming of seeds with strain CC-LS37 caused rice plants to increase shoot chlorophyll soil plant analysis development values (by 2.9% and 2.5%, respectively) and tiller number (both by 61%) under natural climate and chilling stress during the end of tillering stage, afterward 30% more grain yield was achieved. In conclusion, strain CC-LS37 exerted its function in increase of tiller number of chilling stress-treated rice seedlings via improvement of photosynthetic characteristics, which in turn increases the rice grain yield. This study also proposed multiple indices used in the screening of potential endophytes for conferring chilling tolerance of rice plants.

A unique self-truncation of bacterial GH5 endoglucanases leads to enhanced activity and thermostability.

BACKGROUND: ß-1,4-endoglucanase (EG) is one of the three types of cellulases used in cellulose saccharification during lignocellulosic biofuel/biomaterial production. GsCelA is an EG secreted by the thermophilic bacterium Geobacillus sp. 70PC53 isolated from rice straw compost in southern Taiwan. This enzyme belongs to glycoside hydrolase family 5 (GH5) with a TIM-barrel structure common among all members of this family. GsCelA exhibits excellent lignocellulolytic activity and thermostability. In the course of investigating the regulation of this enzyme, it was fortuitously discovered that GsCelA undergoes a novel self-truncation/activation process that appears to be common among GH5 enzymes. RESULTS: Three diverse Gram-positive bacterial GH5 EGs, but not a GH12 EG, undergo an unexpected self-truncation process by removing a part of their C-terminal region. This unique process has been studied in detail with GsCelA. The purified recombinant GsCelA was capable of removing a 53-amino-acid peptide from the C-terminus. Natural or engineered GsCelA truncated variants, with up to 60-amino-acid deletion from the C-terminus, exhibited higher specific activity and thermostability than the full-length enzyme. Interestingly, the C-terminal part that is removed in this self-truncation process is capable of binding to cellulosic substrates of EGs. The protein truncation, which is pH and temperature dependent, occurred between amino acids 315 and 316, but removal of these two amino acids did not stop the process. Furthermore, mutations of E142A and E231A, which are essential for EG activity, did not affect the protein self-truncation process. Conversely, two single amino acid substitution mutations affected the self-truncation activity without much impact on EG activities. In Geobacillus sp. 70PC53, the full-length GsCelA was first synthesized in the cell but progressively transformed into the truncated form and eventually secreted. The GsCelA self-truncation was not affected by standard protease inhibitors, but could be suppressed by EDTA and EGTA and enhanced by certain divalent ions, such as Ca2+, Mg2+, and Cu2+. CONCLUSIONS: This study reveals novel insights into the strategy of Gram-positive bacteria for directing their GH5 EGs to the substrate, and then releasing the catalytic part for enhanced activity via a spontaneous self-truncation process.

Sugar starvation-regulated MYBS2 and 14-3-3 protein interactions enhance plant growth, stress tolerance, and grain weight in rice.

Autotrophic plants have evolved distinctive mechanisms for maintaining a range of homeostatic states for sugars. The on/off switch of reversible gene expression by sugar starvation/provision represents one of the major mechanisms by which sugar levels are maintained, but the details remain unclear. α-Amylase (αAmy) is the key enzyme for hydrolyzing starch into sugars for plant growth, and it is induced by sugar starvation and repressed by sugar provision. αAmy can also be induced by various other stresses, but the physiological significance is unclear. Here, we reveal that the on/off switch of αAmy expression is regulated by 2 MYB transcription factors competing for the same promoter element. MYBS1 promotes αAmy expression under sugar starvation, whereas MYBS2 represses it. Sugar starvation promotes nuclear import of MYBS1 and nuclear export of MYBS2, whereas sugar provision has the opposite effects. Phosphorylation of MYBS2 at distinct serine residues plays important roles in regulating its sugar-dependent nucleocytoplasmic shuttling and maintenance in cytoplasm by 14-3-3 proteins. Moreover, dehydration, heat, and osmotic stress repress MYBS2 expression, thereby inducing αAmy3 Importantly, activation of αAmy3 and suppression of MYBS2 enhances plant growth, stress tolerance, and total grain weight per plant in rice. Our findings reveal insights into a unique regulatory mechanism for an on/off switch of reversible gene expression in maintaining sugar homeostatic states, which tightly regulates plant growth and development, and also highlight MYBS2 and αAmy3 as potential targets for crop improvement.

Improved Discrimination of Disease States Using Proteomics Data with the Updated Aristotle Classifier.

Mass spectrometry data sets from omics studies are an optimal information source for discriminating patients with disease and identifying biomarkers. Thousands of proteins or endogenous metabolites can be queried in each analysis, spanning several orders of magnitude in abundance. Machine learning tools that effectively leverage these data to accurately identify disease states are in high demand. While mass spectrometry data sets are rich with potentially useful information, using the data effectively can be challenging because of missing entries in the data sets and because the number of samples is typically much smaller than the number of features, two challenges that make machine learning difficult. To address this problem, we have modified a new supervised classification tool, the Aristotle Classifier, so that omics data sets can be better leveraged for identifying disease states. The optimized classifier, AC.2021, is benchmarked on multiple data sets against its predecessor and two leading supervised classification tools, Support Vector Machine (SVM) and XGBoost. The new classifier, AC.2021, outperformed existing tools on multiple tests using proteomics data. The underlying code for the classifier, provided herein, would be useful for researchers who desire improved classification accuracy when using their omics data sets to identify disease states.

How does rice cope with too little oxygen during its early life?

Most crops cannot germinate underwater. Rice exhibits certain degrees of tolerance to oxygen deficiency for anaerobic germination (AG) and anaerobic seedling development (ASD). Direct rice seeding, whereby seeds are sown into soil rather than transplanting seedlings from the nursery, becomes an increasingly popular cultivation method due to labor shortages and opportunities for sustainable cultivation. Flooding is common under direct seeding, but most rice varieties have poor capability of AG/ASD, which is a major obstacle to broad adoption of direct seeding. A better understanding of the physiological basis and molecular mechanisms regulating AG/ASD should facilitate rice breeding for enhanced seedling vigor under flooding. This review highlights recent advances on molecular and physiological mechanisms and future breeding strategies of rice AG/ASD.

An Intrinsically Disordered Protein Interacts with the Cytoskeleton for Adaptive Root Growth under Stress.

Intrinsically disordered proteins function as flexible stress modulators in vivo through largely unknown mechanisms. Here, we elucidated the mechanistic role of an intrinsically disordered protein, REPETITIVE PRO-RICH PROTEIN (RePRP), in regulating rice (Oryza sativa) root growth under water deficit. With nearly 40% Pro, RePRP is induced by water deficit and abscisic acid (ABA) in the root elongation zone. RePRP is sufficient and necessary for repression of root development by water deficit or ABA. We showed that RePRP interacts with the highly ordered cytoskeleton components actin and tubulin both in vivo and in vitro. Binding of RePRP reduces the abundance of actin filaments, thus diminishing noncellulosic polysaccharide transport to the cell wall and increasing the enzyme activity of Suc synthase. RePRP also reorients the microtubule network, which leads to disordered cellulose microfibril organization in the cell wall. The cell wall modification suppresses root cell elongation, thereby generating short roots, whereas increased Suc synthase activity triggers starch accumulation in "heavy" roots. Intrinsically disordered proteins control cell elongation and carbon reserves via an order-by-disorder mechanism, regulating the highly ordered cytoskeleton for development of "short-but-heavy" roots as an adaptive response to water deficit in rice.

The local-balanced model for improved machine learning outcomes on mass spectrometry data sets and other instrumental data.

One unifying challenge when classifying biological samples with mass spectrometry data is overcoming the obstacle of sample-to-sample variability so that differences between groups, such as between a healthy set and a disease set, can be identified. Similarly, when the same sample is re-analyzed under identical conditions, instrument signals can fluctuate by more than 10%. This signal inconsistency imposes difficulties in identifying subtle differences across a set of samples, and it weakens the mass spectrometrist's ability to effectively leverage data in domains as diverse as proteomics, metabolomics, glycomics, and imaging. We selected challenging data sets in the fields of glycomics, mass spectrometry imaging, and bacterial typing to study the problem of within-group signal variability and adapted a 30-year-old statistical approach to address the problem. The solution, "local-balanced model," relies on using balanced subsets of training data to classify test samples. This analysis strategy was assessed on ESI-MS data of IgG-based glycopeptides and MALDI-MS imaging data of endogenous lipids, and MALDI-MS data of bacterial proteins. Two preliminary examples on non-mass spectrometry data sets are also included to show the potential generality of the method outside the field of MS analysis. We demonstrate that this approach is superior to simple normalization methods, generalizable to multiple mass spectrometry domains, and potentially appropriate in fields as diverse as physics and satellite imaging. In some cases, improvements in classification can be dramatic, with accuracy escalating from 60% with normalization alone to over 90% with the additional development described herein.

Adaption of the Aristotle Classifier for Accurately Identifying Highly Similar Bacteria Analyzed by MALDI-TOF MS.

MALDI-TOF MS has shown great utility for rapidly identifying microbial species. It can be used to successfully type bacteria and fungi from a variety of sources more rapidly and cost-effectively than traditional methods. One area where improvements are necessary is in the typing of highly similar samples, such as those samples from the same genus but different species or samples from within a single species but from different strains. One promising way to address this current limitation is by using advanced machine learning techniques. In this work, we adapt a newly developed machine learning tool, the Aristotle Classifier, to bacterial classification of MALDI-TOF MS data. This tool was originally developed for classifying glycomics and glycoproteomics data, so we modified it to be well-suited for assigning mass spectral data from bacterial proteins. The classifier exceeds existing benchmarks in classifying bacteria, and it shows particularly strong performance when the samples to be identified are highly similar. The combination of mass spectrometry data and tools like the Aristotle Classifier could ameliorate the ambiguities associated with challenging bacterial classification problems.

Rice Big Grain 1 promotes cell division to enhance organ development, stress tolerance and grain yield.

Grain/seed yield and plant stress tolerance are two major traits that determine the yield potential of many crops. In cereals, grain size is one of the key factors affecting grain yield. Here, we identify and characterize a newly discovered gene Rice Big Grain 1 (RBG1) that regulates grain and organ development, as well as abiotic stress tolerance. Ectopic expression of RBG1 leads to significant increases in the size of not only grains but also other major organs such as roots, shoots and panicles. Increased grain size is primarily due to elevated cell numbers rather than cell enlargement. RBG1 is preferentially expressed in meristematic and proliferating tissues. Ectopic expression of RBG1 promotes cell division, and RBG1 co-localizes with microtubules known to be involved in cell division, which may account for the increase in organ size. Ectopic expression of RBG1 also increases auxin accumulation and sensitivity, which facilitates root development, particularly crown roots. Moreover, overexpression of RBG1 up-regulated a large number of heat-shock proteins, leading to enhanced tolerance to heat, osmotic and salt stresses, as well as rapid recovery from water-deficit stress. Ectopic expression of RBG1 regulated by a specific constitutive promoter, GOS2, enhanced harvest index and grain yield in rice. Taken together, we have discovered that RBG1 regulates two distinct and important traits in rice, namely grain yield and stress tolerance, via its effects on cell division, auxin and stress protein induction.

DecoyDeveloper: An On-Demand, De Novo Decoy Glycopeptide Generator.

Glycopeptide analysis is a growing field that is struggling to adopt effective, automated tools. Many creative workflows and software apps have emerged recently that offer promising capabilities for assigning glycopeptides to MS data in an automated fashion. The effectiveness of these tools is best measured and improved by determining how often they would select a glycopeptide decoy as a spectral match, instead of its correct assignment; yet generating the appropriate number and type of glycopeptide decoys can be challenging. To address this need, we have designed DecoyDeveloper, an on-demand decoy glycopeptide generator that can produce a high volume of decoys with low mass differences. DecoyDeveloper has a simple user interface and is capable of producing large sets of decoys containing complete, biologically relevant glycan and peptide sequences. We demonstrate the tool's efficiency by applying it to a set of 80 glycopeptide targets. This tool is freely available and can be found at http://glycopro.chem.ku.edu/J1.php .

The Aristotle Classifier: Using the Whole Glycomic Profile To Indicate a Disease State.

"The totality is not, as it were, a mere heap, but the whole is something besides the parts."-Aristotle. We built a classifier that uses the totality of the glycomic profile, not restricted to a few glycoforms, to differentiate samples from two different sources. This approach, which relies on using thousands of features, is a radical departure from current strategies, where most of the glycomic profile is ignored in favor of selecting a few features, or even a single feature, meant to capture the differences in sample types. The classifier can be used to differentiate the source of the material; applicable sources may be different species of animals, different protein production methods, or, most importantly, different biological states (disease vs healthy). The classifier can be used on glycomic data in any form, including derivatized monosaccharides, intact glycans, or glycopeptides. It takes advantage of the fact that changing the source material can cause a change in the glycomic profile in many subtle ways: some glycoforms can be upregulated, some downregulated, some may appear unchanged, yet their proportion-with respect to other forms present-can be altered to a detectable degree. By classifying samples using the entirety of their glycan abundances, along with the glycans' relative proportions to each other, the "Aristotle Classifier" is more effective at capturing the underlying trends than standard classification procedures used in glycomics, including PCA (principal components analysis). It also outperforms workflows where a single, representative glycomic-based biomarker is used to classify samples. We describe the Aristotle Classifier and provide several examples of its utility for biomarker studies and other classification problems using glycomic data from several sources.

Glycosylation Benchmark Profile for HIV-1 Envelope Glycoprotein Production Based on Eleven Env Trimers.

HIV-1 envelope glycoprotein (Env) glycosylation is important because individual glycans are components of multiple broadly neutralizing antibody epitopes, while shielding other sites that might otherwise be immunogenic. The glycosylation on Env is influenced by a variety of factors, including the genotype of the protein, the cell line used for its expression, and the details of the construct design. Here, we used a mass spectrometry (MS)-based approach to map the complete glycosylation profile at every site in multiple HIV-1 Env trimers, accomplishing two goals. (i) We determined which glycosylation sites contain conserved glycan profiles across many trimeric Envs. (ii) We identified the variables that impact Env's glycosylation profile at sites with divergent glycosylation. Over half of the gp120 glycosylation sites on 11 different trimeric Envs have a conserved glycan profile, indicating that a native consensus glycosylation profile does indeed exist among trimers. We showed that some soluble gp120s and gp140s exhibit highly divergent glycosylation profiles compared to trimeric Env. We also assessed the impact of several variables on Env glycosylation: truncating the full-length Env; producing Env, instead of the more virologically relevant T lymphocytes, in CHO cells; and purifying Env with different chromatographic platforms, including nickel-nitrilotriacetic acid (Ni-NTA), 2G12, and PGT151 affinity. This report provides the first consensus glycosylation profile of Env trimers, which should serve as a useful benchmark for HIV-1 vaccine developers. This report also defines the sites where glycosylation may be impacted when Env trimers are truncated or produced in CHO cells.IMPORTANCE A protective HIV-1 vaccine will likely include a recombinant version of the viral envelope glycoprotein (Env). Env is highly glycosylated, and yet vaccine developers have lacked guidance on how to assess whether their immunogens have optimal glycosylation. The following important questions are still unanswered. (i) What is the "target" glycosylation profile, when the goal is to generate a natively glycosylated protein? (ii) What variables exert the greatest influence on Env glycosylation? We identified numerous sites on Env where the glycosylation profile does not deviate in 11 different Env trimers, and we investigated the impact on the divergent glycosylation profiles of changing the genotype of the Env sequence, the construct design, the purification method, and the producer cell type. The data presented here give vaccine developers a "glycosylation target" for their immunogens, and they show how protein production variables can impact Env glycosylation.

Two New Tools for Glycopeptide Analysis Researchers: A Glycopeptide Decoy Generator and a Large Data Set of Assigned CID Spectra of Glycopeptides.

The glycopeptide analysis field is tightly constrained by a lack of effective tools that translate mass spectrometry data into meaningful chemical information, and perhaps the most challenging aspect of building effective glycopeptide analysis software is designing an accurate scoring algorithm for MS/MS data. We provide the glycoproteomics community with two tools to address this challenge. The first tool, a curated set of 100 expert-assigned CID spectra of glycopeptides, contains a diverse set of spectra from a variety of glycan types; the second tool, Glycopeptide Decoy Generator, is a new software application that generates glycopeptide decoys de novo. We developed these tools so that emerging methods of assigning glycopeptides' CID spectra could be rigorously tested. Software developers or those interested in developing skills in expert (manual) analysis can use these tools to facilitate their work. We demonstrate the tools' utility in assessing the quality of one particular glycopeptide software package, GlycoPep Grader, which assigns glycopeptides to CID spectra. We first acquired the set of 100 expert assigned CID spectra; then, we used the Decoy Generator (described herein) to generate 20 decoys per target glycopeptide. The assigned spectra and decoys were used to test the accuracy of GlycoPep Grader's scoring algorithm; new strengths and weaknesses were identified in the algorithm using this approach. Both newly developed tools are freely available. The software can be downloaded at http://glycopro.chem.ku.edu/GPJ.jar.

Ectopic Expression of WINDING 1 Leads to Asymmetrical Distribution of Auxin and a Spiral Phenotype in Rice.

Ectopic expression of the rice WINDING 1 (WIN1) gene leads to a spiral phenotype only in shoots but not in roots. Rice WIN1 belongs to a specific class of proteins in cereal plants containing a Bric-a-Brac/Tramtrack/Broad (BTB) complex, a non-phototropic hypocotyl 3 (NPH3) domain and a coiled-coil motif. The WIN1 protein is predominantly localized to the plasma membrane, but is also co-localized to plasmodesmata, where it exhibits a punctate pattern. It is observed that WIN1 is normally expressed in roots and the shoot-root junction, but not in the rest of shoots. In roots, WIN1 is largely localized to the apical and basal sides of cells. However, upon ectopic expression, WIN1 appears on the longitudinal sides of leaf sheath cells, correlated with the appearance of a spiral phenotype in shoots. Despite the spiral phenotype, WIN1-overexpressing plants exhibit a normal phototropic response. Although treatments with exogenous auxins or a polar auxin transport inhibitor do not alter the spiral phenotype, the excurvature side has a higher auxin concentration than the incurvature side. Furthermore, actin filaments are more prominent in the excurvature side than in the incurvature side, which correlates with cell size differences between these two sides. Interestingly, ectopic expression of WIN1 does not cause either unequal auxin distribution or actin filament differences in roots, so a spiral phenotype is not observed in roots. The action of WIN1 appears to be different from that of other proteins causing a spiral phenotype, and it is likely that WIN1 is involved in 1-N-naphthylphthalamic acid-insensitive plasmodesmata-mediated auxin transport.

Ectopic expression of specific GA2 oxidase mutants promotes yield and stress tolerance in rice.

A major challenge of modern agricultural biotechnology is the optimization of plant architecture for enhanced productivity, stress tolerance and water use efficiency (WUE). To optimize plant height and tillering that directly link to grain yield in cereals and are known to be tightly regulated by gibberellins (GAs), we attenuated the endogenous levels of GAs in rice via its degradation. GA 2-oxidase (GA2ox) is a key enzyme that inactivates endogenous GAs and their precursors. We identified three conserved domains in a unique class of C20 GA2ox, GA2ox6, which is known to regulate the architecture and function of rice plants. We mutated nine specific amino acids in these conserved domains and observed a gradient of effects on plant height. Ectopic expression of some of these GA2ox6 mutants moderately lowered GA levels and reprogrammed transcriptional networks, leading to reduced plant height, more productive tillers, expanded root system, higher WUE and photosynthesis rate, and elevated abiotic and biotic stress tolerance in transgenic rice. Combinations of these beneficial traits conferred not only drought and disease tolerance but also increased grain yield by 10-30% in field trials. Our studies hold the promise of manipulating GA levels to substantially improve plant architecture, stress tolerance and grain yield in rice and possibly in other major crops.

Transcriptomic analysis of rice aleurone cells identified a novel abscisic acid response element.

Seeds serve as a great model to study plant responses to drought stress, which is largely mediated by abscisic acid (ABA). The ABA responsive element (ABRE) is a key cis-regulatory element in ABA signalling. However, its consensus sequence (ACGTG(G/T)C) is present in the promoters of only about 40% of ABA-induced genes in rice aleurone cells, suggesting other ABREs may exist. To identify novel ABREs, RNA sequencing was performed on aleurone cells of rice seeds treated with 20 µM ABA. Gibbs sampling was used to identify enriched elements, and particle bombardment-mediated transient expression studies were performed to verify the function. Gene ontology analysis was performed to predict the roles of genes containing the novel ABREs. This study revealed 2443 ABA-inducible genes and a novel ABRE, designated as ABREN, which was experimentally verified to mediate ABA signalling in rice aleurone cells. Many of the ABREN-containing genes are predicted to be involved in stress responses and transcription. Analysis of other species suggests that the ABREN may be monocot specific. This study also revealed interesting expression patterns of genes involved in ABA metabolism and signalling. Collectively, this study advanced our understanding of diverse cis-regulatory sequences and the transcriptomes underlying ABA responses in rice aleurone cells.

SnRK1A-interacting negative regulators modulate the nutrient starvation signaling sensor SnRK1 in source-sink communication in cereal seedlings under abiotic stress.

In plants, source-sink communication plays a pivotal role in crop productivity, yet the underlying regulatory mechanisms are largely unknown. The SnRK1A protein kinase and transcription factor MYBS1 regulate the sugar starvation signaling pathway during seedling growth in cereals. Here, we identified plant-specific SnRK1A-interacting negative regulators (SKINs). SKINs antagonize the function of SnRK1A, and the highly conserved GKSKSF domain is essential for SKINs to function as repressors. Overexpression of SKINs inhibits the expression of MYBS1 and hydrolases essential for mobilization of nutrient reserves in the endosperm, leading to inhibition of seedling growth. The expression of SKINs is highly inducible by drought and moderately by various stresses, which is likely related to the abscisic acid (ABA)-mediated repression of SnRK1A under stress. Overexpression of SKINs enhances ABA sensitivity for inhibition of seedling growth. ABA promotes the interaction between SnRK1A and SKINs and shifts the localization of SKINs from the nucleus to the cytoplasm, where it binds SnRK1A and prevents SnRK1A and MYBS1 from entering the nucleus. Our findings demonstrate that SnRK1A plays a key role regulating source-sink communication during seedling growth. Under abiotic stress, SKINs antagonize the function of SnRK1A, which is likely a key factor restricting seedling vigor.

Comparative Analysis of the Glycosylation Profiles of Membrane-Anchored HIV-1 Envelope Glycoprotein Trimers and Soluble gp140.

UNLABELLED: The human immunodeficiency virus type 1 (HIV-1) envelope glycoprotein (Env) trimer, which consists of the gp120 and gp41 subunits, is the focus of multiple strategies for vaccine development. Extensive Env glycosylation provides HIV-1 with protection from the immune system, yet the glycans are also essential components of binding epitopes for numerous broadly neutralizing antibodies. Recent studies have shown that when Env is isolated from virions, its glycosylation profile differs significantly from that of soluble forms of Env (gp120 or gp140) predominantly used in vaccine discovery research. Here we show that exogenous membrane-anchored Envs, which can be produced in large quantities in mammalian cells, also display a virion-like glycan profile, where the glycoprotein is extensively decorated with high-mannose glycans. Additionally, because we characterized the glycosylation with a high-fidelity profiling method, glycopeptide analysis, an unprecedented level of molecular detail regarding membrane Env glycosylation and its heterogeneity is presented. Each glycosylation site was characterized individually, with about 500 glycoforms characterized per Env protein. While many of the sites contain exclusively high-mannose glycans, others retain complex glycans, resulting in a glycan profile that cannot currently be mimicked on soluble gp120 or gp140 preparations. These site-level studies are important for understanding antibody-glycan interactions on native Env trimers. Additionally, we report a newly observed O-linked glycosylation site, T606, and we show that the full O-linked glycosylation profile of membrane-associated Env is similar to that of soluble gp140. These findings provide new insight into Env glycosylation and clarify key molecular-level differences between membrane-anchored Env and soluble gp140. IMPORTANCE: A vaccine that protects against human immunodeficiency virus type 1 (HIV-1) infection should elicit antibodies that bind to the surface envelope glycoproteins on the membrane of the virus. The envelope glycoproteins have an extensive coat of carbohydrates (glycans), some of which are recognized by virus-neutralizing antibodies and some of which protect the virus from neutralizing antibodies. We found that the HIV-1 membrane envelope glycoproteins have a unique pattern of carbohydrates, with many high-mannose glycans and also, in some places, complex glycans. This pattern was very different from the carbohydrate profile seen for a more easily produced soluble version of the envelope glycoprotein. Our results provide a detailed characterization of the glycans on the natural membrane envelope glycoproteins of HIV-1, a carbohydrate profile that would be desirable to mimic with a vaccine.

Genetic resources offer efficient tools for rice functional genomics research.

Rice is an important crop and major model plant for monocot functional genomics studies. With the establishment of various genetic resources for rice genomics, the next challenge is to systematically assign functions to predicted genes in the rice genome. Compared with the robustness of genome sequencing and bioinformatics techniques, progress in understanding the function of rice genes has lagged, hampering the utilization of rice genes for cereal crop improvement. The use of transfer DNA (T-DNA) insertional mutagenesis offers the advantage of uniform distribution throughout the rice genome, but preferentially in gene-rich regions, resulting in direct gene knockout or activation of genes within 20-30 kb up- and downstream of the T-DNA insertion site and high gene tagging efficiency. Here, we summarize the recent progress in functional genomics using the T-DNA-tagged rice mutant population. We also discuss important features of T-DNA activation- and knockout-tagging and promoter-trapping of the rice genome in relation to mutant and candidate gene characterizations and how to more efficiently utilize rice mutant populations and datasets for high-throughput functional genomics and phenomics studies by forward and reverse genetics approaches. These studies may facilitate the translation of rice functional genomics research to improvements of rice and other cereal crops.