Shao-shan Carol Huang

Processing and Subcellular Trafficking of ER-Tethered EIN2 Control Response to Ethylene Gas

Cleave and Leave Plants produce ethylene gas, which acts as a hormone and is essential for the ripening of fruit, the resistance of plants to pathogens, the adaptation of plants to stress conditions, and stem cell maintenance. Although many components of the ethylene gas signaling pathway have been well studied, little is known about how the ethylene receptors located in the endoplasmic reticulum (ER) membrane can transmit the signal to the nucleus. Studying Arabidopsis, Qiao et al. (p. 390, published online 30 August) found that perception of ethylene gas in the ER promotes signal transduction via cleavage and rapid ER-nucleus translocation of the cytosolic portion of the transmembrane ETHYLENE INSENSITIVE2 protein, which activates ethylene-dependent gene expression and other ethylene response phenotypes in plants. The plant hormone ethylene triggers cleavage and translocation to the nucleus of a signaling component. Ethylene gas is essential for many developmental processes and stress responses in plants. ETHYLENE INSENSITIVE2 (EIN2), an NRAMP-like integral membrane protein, plays an essential role in ethylene signaling, but its function remains enigmatic. Here we report that phosphorylation-regulated proteolytic processing of EIN2 triggers its endoplasmic reticulum (ER)–to–nucleus translocation. ER-tethered EIN2 shows CONSTITUTIVE TRIPLE RESPONSE1 (CTR1) kinase–dependent phosphorylation. Ethylene triggers dephosphorylation at several sites and proteolytic cleavage at one of these sites, resulting in nuclear translocation of a carboxyl-terminal EIN2 fragment (EIN2-C′). Mutations that mimic EIN2 dephosphorylation, or inactivate CTR1, show constitutive cleavage and nuclear localization of EIN2-C′ and EIN3 and EIN3-LIKE1–dependent activation of ethylene responses. These findings uncover a mechanism of subcellular communication whereby ethylene stimulates phosphorylation-dependent cleavage and nuclear movement of the EIN2-C′ peptide, linking hormone perception and signaling components in the ER with nuclear-localized transcriptional regulators.

Temporal transcriptional response to ethylene gas drives growth hormone cross-regulation in Arabidopsis

The gaseous plant hormone ethylene regulates a multitude of growth and developmental processes. How the numerous growth control pathways are coordinated by the ethylene transcriptional response remains elusive. We characterized the dynamic ethylene transcriptional response by identifying targets of the master regulator of the ethylene signaling pathway, ETHYLENE INSENSITIVE3 (EIN3), using chromatin immunoprecipitation sequencing and transcript sequencing during a timecourse of ethylene treatment. Ethylene-induced transcription occurs in temporal waves regulated by EIN3, suggesting distinct layers of transcriptional control. EIN3 binding was found to modulate a multitude of downstream transcriptional cascades, including a major feedback regulatory circuitry of the ethylene signaling pathway, as well as integrating numerous connections between most of the hormone mediated growth response pathways. These findings provide direct evidence linking each of the major plant growth and development networks in novel ways. DOI: http://dx.doi.org/10.7554/eLife.00675.001

Cryptochromes Interact Directly with PIFs to Control Plant Growth in Limiting Blue Light

Sun-loving plants have the ability to detect and avoid shading through sensing of both blue and red light wavelengths. Higher plant cryptochromes (CRYs) control how plants modulate growth in response to changes in blue light. For growth under a canopy, where blue light is diminished, CRY1 and CRY2 perceive this change and respond by directly contacting two bHLH transcription factors, PIF4 and PIF5. These factors are also known to be controlled by phytochromes, the red/far-red photoreceptors; however, transcriptome analyses indicate that the gene regulatory programs induced by the different light wavelengths are distinct. Our results indicate that CRYs signal by modulating PIF activity genome wide and that these factors integrate binding of different plant photoreceptors to facilitate growth changes under different light conditions.

A transcription factor hierarchy defines an environmental stress response network

Complex transcription factor interactions To respond to environmental changes, such as drought, plants must regulate numerous cellular processes. Working in the model plant Arabidopsis, Song et al. profiled the binding of 21 transcription factors to chromatin and mapped the complex gene regulatory networks involved in the response to the plant hormone abscisic acid. The work provides a framework for understanding and modulating plant responses to stress. Science, this issue p. 598 The response to the abscisic acid hormone in the model plant Arabidopsis involves complex transcription factor dynamics. INTRODUCTION Transcription factors (TFs) are often studied one by one or in clusters of a few related factors. However, the integration and networks of transcriptional changes to response to environmental stresses often involve many related TFs. In many organisms, such as plants, overlapping functions can make it difficult to understand how a biologically relevant end result can be achieved via the complex signaling networks controlled by these TFs. To better understand how the reference plant Arabidopsis deals with the stresses incurred by water limitation via the hormone abscisic acid (ABA), we characterized all DNA sequences that bind to the 21 ABA-related TFs in vivo. RATIONALE There have been limited systematic studies of stress-responsive TF networks in multicellular organisms. We chose ABA, an essential plant hormone that is required for both development and responses to osmotic stress, as an elicitor to investigate complex gene regulatory networks under stress. Combining differential binding (DB) of 21 ABA-related TFs at a single time point measured by chromatin immunoprecipitation sequencing (ChIP-seq) with differentially expressed genes from a time-series RNA sequencing (RNA-seq) data set, we analyzed the relationship between DB of TFs and differential expression (DE) of target genes, the determinants of DB, and the combinatorial effects of multi-TF binding. These data sets also provide a framework to construct an ABA TF network and to predict genes and cis-regulatory elements important to ABA responses and related environmental stresses. RESULTS We found that, in general, DNA binding is correlated with transcript and protein levels of TFs. Most TFs in our study are induced by ABA and gain binding sites (termed “peaks”) after the hormone treatment. ABA also increases the binding of the TFs at most peaks. However, in some peaks, TF binding may be static or even decrease after ABA exposure, revealing the complexity of locus-specific gene regulation. De novo motif discovery enabled us to identify distinct, primary motifs often centrally localized in the ChIP-seq peaks for most TFs. However, it is not uncommon to find motifs, such as the G-box, that are shared by peaks from multiple TFs and may contribute to binding dynamics at these sites. DB of multiple TFs is a robust predictor of both the DE and ABA-related functions of the target genes. Using the DB and DE data, we constructed a network of TFs and canonical ABA pathway genes and demonstrated a regulatory hierarchy of TFs and extensive feedback of ABA responses. On the basis of a “guilt-by-association” paradigm, we further predicted genes whose functions were previously not linked to ABA responses, and we thus functionally characterized a new family of transcriptional regulators. CONCLUSION These data sets will provide the plant community with a roadmap of ABA-elicited transcriptional regulation by 21 ABA-related TFs. We propose that dynamic, multi-TF binding could be a criterion for prioritizing the characterization of TF binding events, cis-regulatory elements, and functionally unknown genes in both plants and other species. In our proof-of-principle experiments, ectopic expression of the transcriptional regulators ranked highly in our model results in altered sensitivity to both ABA and high salinity. Together with the fact that our modeling recovered genes related to seed development and osmotic stresses, we believe such predictions are likely applicable to a broad range of developmental stages and osmotic stresses. Transcriptional landscape of the ABA response. ABA response pathway gene targets were identified by large-scale ChIP-seq and time-series RNA-seq experiments. A network model was built to reveal the hierarchy of TFs and the impact of multi-TF dynamic binding on gene expression. A new family of transcriptional regulators was predicted by the model and was functionally tested to evaluate the role of these regulators in osmotic stress in plants. Environmental stresses are universally encountered by microbes, plants, and animals. Yet systematic studies of stress-responsive transcription factor (TF) networks in multicellular organisms have been limited. The phytohormone abscisic acid (ABA) influences the expression of thousands of genes, allowing us to characterize complex stress-responsive regulatory networks. Using chromatin immunoprecipitation sequencing, we identified genome-wide targets of 21 ABA-related TFs to construct a comprehensive regulatory network in Arabidopsis thaliana. Determinants of dynamic TF binding and a hierarchy among TFs were defined, illuminating the relationship between differential gene expression patterns and ABA pathway feedback regulation. By extrapolating regulatory characteristics of observed canonical ABA pathway components, we identified a new family of transcriptional regulators modulating ABA and salt responsiveness and demonstrated their utility to modulate plant resilience to osmotic stress.

Mapping transcription factor interactome networks using HaloTag protein arrays

Significance Using a newly developed technology, HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we increase the capacity of in situ protein microarray technology several-fold, such that proteome-scale screening becomes feasible. Many examples of novel protein–protein interactions (PPIs) among plant signaling pathways were observed. With few exceptions, nearly all of these connections are undocumented in the existing literature. This study has resulted in an important new resource for the plant biology community—a plant transcription factor-anchored protein–protein interaction network map. Such transcription factor- and transcriptional regulator-based PPI networks may help in the identification of novel genes for use in the improvement of agronomic traits such as grain quality, disease resistance, and stress tolerance. Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein–protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor–protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

Erratum: Cistrome and Epicistrome Features Shape the Regulatory DNA Landscape (Cell (2016) 165(5) (1280–1292))

In the Supplemental Experimental Procedures, the Adaptor B sequence shown was missing the 50 phosphate modification required for ligation, and the Illumina TruSeq Index primer was shown as the reverse complement of the sequence used in the analyses. The correct sequences are: Adaptor B: 50 P-GATCGGAAGAGCACACGTCTG and TruSeq Index primer: 50-CAAGCAGAAGACGGCATAC GAGAT-NNNNNN GTGACTGGAGTTCAGACGTGTGCTCTTCCGATC (where the NNNNNN represents the six-base-pair sequence index used for sample identification).

Mapping genome-wide transcription-factor binding sites using DAP-seq

To enable low-cost, high-throughput generation of cistrome and epicistrome maps for any organism, we developed DNA affinity purification sequencing (DAP-seq), a transcription factor (TF)-binding site (TFBS) discovery assay that couples affinity-purified TFs with next-generation sequencing of a genomic DNA library. The method is fast, inexpensive, and more easily scaled than chromatin immunoprecipitation sequencing (ChIP-seq). DNA libraries are constructed using native genomic DNA from any source of interest, preserving cell- and tissue-specific chemical modifications that are known to affect TF binding (such as DNA methylation) and providing increased specificity as compared with in silico predictions based on motifs from methods such as protein-binding microarrays (PBMs) and systematic evolution of ligands by exponential enrichment (SELEX). The resulting DNA library is incubated with an affinity-tagged in vitro-expressed TF, and TF–DNA complexes are purified using magnetic separation of the affinity tag. Bound genomic DNA is eluted from the TF and sequenced using next-generation sequencing. Sequence reads are mapped to a reference genome, identifying genome-wide binding locations for each TF assayed, from which sequence motifs can then be derived. A researcher with molecular biology experience should be able to follow this protocol, processing up to 400 samples per week.

Response to perspective: "separation anxiety: An analysis of ethylene-induced cleavage of EIN2"

Cooper questions one specific technical aspect of our study—the site of cleavage in EIN2—and suggests that cleavage of EIN2 likely occurs elsewhere. Here, we explain how our immunoblotting, mass spectrometry and genetic mutation studies justify our conclusions.

Next Generation Protein Interactomes for Plant Systems Biology and Biomass Feedstock Research

In order to keep up with global energy demands, it is imperitive we acquire more knowledge of biofuel feedstocks for improving their cultivation and energy yield. Knowledge of protein-protein interaction (PPI) networks that promote robust plant growth or that are perturbed by pathogens causing disease could progress strategies for improving cultivation. However, current technologies available for obtaining PPI data are insufficient and unrealistic for non-model organisms because of time, cost, and sensitivity constraints. Even the largest high quality PPI map for the model plant Arabidopsis thaliana (Arabidopsis Interactome 1 or AI-1), that we generated, contains only 2% of all potential interactions, and took upwards of 5 years and

Cistrome and epicistrome features shape the regulatory DNA landscape

8 million to finish. To address this problem, we are developing a next-generation sequencing integrated yeast two-hybrid (Y2H) system that will greatly improve the rate at which PPI data can be obtained and will be applicable to virtually any cell from which RNA can be extracted.