Crop yield loss due to flooding is a threat to food security. Submergence-induced hypoxia in plants results in stabilisation of group VII ETHYLENE RESPONSE FACTORS (ERF-VIIs), which aid survival under these adverse conditions. ERF-VII stability is controlled by the N-end rule pathway, which proposes that ERF-VII N-terminal cysteine oxidation in normoxia enables arginylation followed by proteasomal degradation. The PLANT CYSTEINE OXIDASEs (PCOs) have been identified as catalysts of this oxidation. ERF-VII stabilisation in hypoxia presumably arises from reduced PCO activity. We directly demonstrate that PCO dioxygenase activity produces Cys-sulfinic acid at the N-terminus of an ERF-VII peptide, which then undergoes efficient arginylation by an arginyl transferase (ATE1). This is the first molecular evidence showing N-terminal Cys-sulfinic acid formation and arginylation by N-end rule pathway components, and the first ATE1 substrate in plants. The PCOs and ATE1 may be viable intervention targets to stabilise N-end rule substrates, including ERF-VIIs to enhance submergence tolerance in agronomy.

Auxin is an essential regulator of plant growth and development and auxin signaling components are conserved among land plants. Yet, a remarkable degree of natural variation in physiological and transcriptional auxin responses has been described among Arabidopsis thaliana accessions. As intra-species comparisons offer only limited genetic variation, we here inspect the variation of auxin responses between A. thaliana and A. lyrata. This approach allowed the identification of conserved auxin response genes including novel genes with potential relevance for auxin biology. Furthermore, promoter divergences were analyzed for putative sources of variation. De novo motif discovery identified novel and variants of known elements with potential relevance for auxin responses, emphasizing the complex, and yet elusive, code of element combinations accounting for the diversity in transcriptional auxin responses. Furthermore, network analysis revealed correlations of inter-species differences in the expression of AUX/IAA gene clusters and classic auxin-related genes. We conclude that variation in general transcriptional and physiological auxin responses may originate substantially from functional or transcriptional variations in the TIR1/AFB, AUX/IAA, and ARF signaling network. In that respect, AUX/IAA gene expression divergence potentially reflects differences in the manner in which different species transduce identical auxin signals into gene expression responses.

The N-end rule pathway has emerged as a major system for regulating protein functions by controlling their turn-over in medical, animal and plant sciences as well as agriculture. Although novel functions and enzymes of the pathway were discovered, ubiquitination mechanism and substrate specificity of N-end rule pathway E3 Ubiquitin ligases remained elusive. Taking the first discovered bona fide plant N-end rule E3 ligase PROTEOLYSIS1 (PRT1) as a model, we use a novel tool to molecularly characterize polyubiquitination live, in real-time.We gained mechanistic insights in PRT1 substrate preference and activation by monitoring live ubiquitination by using a fluorescent chemical probe coupled to artificial substrate reporters. Ubiquitination was measured by rapid in-gel fluorescence scanning as well as in real time by fluorescence polarization.Enzymatic activity, substrate specificity, mechanisms and reaction optimization of PRT1-mediated ubiquitination were investigated ad hoc in short time and with significantly reduced reagent consumption.We demonstrated for the first time that PRT1 is indeed an E3 ligase, which was hypothesized for over two decades. These results demonstrate that PRT1 has the potential to be involved in polyubiquitination of various substrates and therefore pave the way to understanding recently discovered phenotypes of prt1 mutants.

Combining transcriptome data of biological processes or response to stimuli with evolutionary information such as the phylogenetic conservation of genes or their sequence divergence rates enables the investigation of evolutionary constraints on these processes or responses. Such phylotranscriptomic analyses recently unraveled that mid-developmental transcriptomes of fly, fish, and cress were dominated by evolutionarily conserved genes and genes under negative selection and thus recapitulated the developmental hourglass on the transcriptomic level. Here, we present a protocol for performing phylotranscriptomic analyses on any biological process of interest. When applying this protocol, users are capable of detecting different evolutionary constraints acting on different stages of the biological process of interest in any species. For each step of the protocol, modular and easy-to-use open-source software tools are provided, which enable a broad range of scientists to apply phylotranscriptomic analyses to a wide spectrum of biological questions.

The characteristic shapes and sizes of organs are established by cell proliferation patterns and final cell sizes, but the underlying molecular mechanisms coordinating these are poorly understood. Here we characterize a ubiquitin-activated peptidase called DA1 that limits the duration of cell proliferation during organ growth in Arabidopsis thaliana. The peptidase is activated by two RING E3 ligases, BB and DA2, which are subsequently cleaved by the activated peptidase and destabilized. In the case of BB, cleavage leads to destabilization by the RING E3 ligase PRT1 of the N-end rule pathway. DA1 peptidase activity also cleaves the de-ubiquitylase UBP15, which promotes cell proliferation, and the transcription factors TCP15 and TCP22, which promote cell proliferation proliferation and repress endoreduplication. We propose that DA1 peptidase activity regulates the duration of cell proliferation and the transition to endoreduplication and differentiation during organ formation in plants by coordinating the destabilization of regulatory proteins.

Hydrated Arabidopsis thaliana seeds are coated by a gelatinous layer called mucilage, which is mainly composed of cell wall polysaccharides. Since mucilage is rich in pectin, its architecture can be visualized with the ruthenium red (RR) dye. We screened the seeds of around 280 Arabidopsis natural accessions for variation in mucilage structure, and identified a large number of novel variants that differed from the Col-0 wild-type. Most of the accessions released smaller RR-stained capsules compared to the Col-0 reference. By biochemically characterizing the phenotypes of 25 of these accessions in greater detail, we discovered that distinct changes in polysaccharide structure resulted in gelatinous coatings with a deceptively similar appearance. Monosaccharide composition analysis of total mucilage extracts revealed a remarkable variation (from 50 to 200% of Col-0 levels) in the content of galactose and mannose, which are important subunits of heteromannan. In addition, most of the natural variants had altered Pontamine Fast Scarlet 4B staining of cellulose and significantly reduced birefringence of crystalline structures. This indicates that the production or organization of cellulose may be affected by the presence of different amounts of hemicellulose. Although, the accessions described in this study were primarily collected from Western Europe, they form five different phenotypic classes based on the combined results of our experiments. This suggests that polymorphisms at multiple loci are likely responsible for the observed mucilage structure. The transcription of MUCILAGE-RELATED10 (MUCI10), which encodes a key enzyme for galactoglucomannan synthesis, was severely reduced in multiple variants that phenocopied the muci10-1 insertion mutant. Although, we could not pinpoint any causal polymorphisms in this gene, constitutive expression of fluorescently-tagged MUCI10 proteins complemented the mucilage defects of a muci10-like accession. This leads us to hypothesize that some accessions might disrupt a transcriptional regulator of MUCI10. Therefore, this collection of publicly-available variants should provide insight into plant cell wall organization and facilitate the discovery of genes that regulate polysaccharide biosynthesis.

The Arabidopsis thaliana seed coat epidermis produces copious amounts of mucilage polysaccharides (Haughn and Western, 2012). Characterization of mucilage mutants has identified novel genes required for cell wall biosynthesis and modification (North et al., 2014). The biochemical analysis of seed mucilage is essential to evaluate how different mutations affect cell wall structure (Voiniciuc et al., 2015c). Here we describe a robust method to screen the monosaccharide composition of Arabidopsis seed mucilage using ion chromatography (IC). Mucilage from up to 48 samples can be extracted and prepared for IC analysis within 24 h (only 4 h hands-on). Furthermore, this protocol enables fast separation (31 min per sample), automatic detection and quantification of both neutral and acidic sugars.

At present, mass spectrometry (MS)-based metabolomics has been widely used to obtain new insights into human, plant, and microbial biochemistry; drug and biomarker discovery; nutrition research; and food control. Despite the high research interest, identifying and characterizing the structure of metabolites has become a major drawback for converting raw MS data into biological knowledge. Comprehensive and well-annotated MS-based spectral databases play a key role in serving this purpose via the formation of metabolite annotations. The main characteristics of the mass spectral databases currently used in MS-based metabolomics are reviewed in this study, underlining their advantages and limitations. In addition, the overlap of compounds with MSn (n ≥ 2) spectra from authentic chemical standards in most public and commercial databases has been calculated for the first time. Finally, future prospects of mass spectral databases are discussed in terms of the needs posed by novel applications and instrumental advancements.

Mass spectrometry is a key analytical platform for metabolomics. The precise quantification and identification of small molecules is a prerequisite for elucidating the metabolism and the detection, validation, and evaluation of isotope clusters in LC-MS data is important for this task. Here, we present an approach for the improved detection of isotope clusters using chemical prior knowledge and the validation of detected isotope clusters depending on the substance mass using database statistics. We find remarkable improvements regarding the number of detected isotope clusters and are able to predict the correct molecular formula in the top three ranks in 92%of the cases. We make our methodology freely available as part of the Bioconductor packages xcms version 1.50.0 and CAMERA version 1.30.0.

The identification of metabolites by mass spectrometry constitutes a major bottleneck which considerably limits the throughput of metabolomics studies in biomedical or plant research. Here, we present a novel approach to analyze metabolomics data from untargeted, data-independent LC-MS/MS measurements. By integrated analysis of MS1 abundances and MS/MS spectra, the identification of regulated metabolite families is achieved. This approach offers a global view on metabolic regulation in comparative metabolomics. We implemented our approach in the web application “MetFamily”, which is freely available at http://msbi.ipb-halle.de/MetFamily/. MetFamily provides a dynamic link between the patterns based on MS1-signal intensity and the corresponding structural similarity at the MS/MS level. Structurally related metabolites are annotated as metabolite families based on a hierarchical cluster analysis of measured MS/MS spectra. Joint examination with principal component analysis of MS1 patterns, where this annotation is preserved in the loadings, facilitates the interpretation of comparative metabolomics data at the level of metabolite families. As a proof of concept, we identified two trichome-specific metabolite families from wild-type tomato Solanum habrochaites LA1777 in a fully unsupervised manner and validated our findings based on earlier publications and with NMR.