Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking. Here, we present an automated and reproducible Metabolome Annotation Workflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS2) input data pre-processing, spectral and compound database matching with computational classification, and in silico annotation. MAW takes the LC-MS2 spectra as input and generates a list of putative candidates from spectral and compound databases. The databases are integrated via the R package Spectra and the metabolite annotation tool SIRIUS as part of the R segment of the workflow (MAW-R). The final candidate selection is performed using the cheminformatics tool RDKit in the Python segment (MAW-Py). Furthermore, each feature is assigned a chemical structure and can be imported to a chemical structure similarity network. MAW is following the FAIR (Findable, Accessible, Interoperable, Reusable) principles and has been made available as the docker images, maw-r and maw-py. The source code and documentation are available on GitHub. The performance of MAW is evaluated on two case studies. We found that MAW can improve candidate ranking by integrating spectral databases with annotation tools like SIRIUS which contributes to an efficient candidate selection procedure. The results from MAW are also reproducible and traceable, compliant with the FAIR guidelines. Taken together, MAW could greatly facilitate automated metabolite characterization in diverse fields such as clinical metabolomics and natural product discovery.

DNA double strand breaks (DSBs) are lethal threats that need to be repaired. Although many of the proteins involved in the early steps of DSB repair have been characterized, recent reports indicate that damage induced long and small RNAs also play an important role in DSB repair. Here, using a Nicotiana benthamiana transgenic line originally designed as a reporter for targeted knock-ins, we show that DSBs generated by Cas9 induce the transcription of long stable RNAs (damage-induced long RNAs - dilRNAs) that are translated into proteins. Using an array of single guide RNAs we show that the initiation of transcription takes place in the vicinity of the DSB. Single strand DNA nicks are not able to induce transcription, showing that cis DNA damage-induced transcription is specific for DSBs. Our results support a model in which a default and early event in the processing of DSBs is transcription into RNA which, depending on the genomic and genic context, can undergo distinct fates, including translation into protein, degradation or production of small RNAs. Our results have general implications for understanding the role of transcription in the repair of DSBs and, reciprocally, reveal DSBs as yet another way to regulate gene expression.

Protein engineering through directed evolution and (semi-)rational approaches has been applied successfully to optimize protein properties for broad applications in molecular biology, biotechnology, and biomedicine. The potential of protein engineering is not yet fully realized due to the limited screening throughput hampering the efficient exploration of the vast protein sequence space. Data-driven strategies have emerged as a powerful tool to leverage protein engineering by providing a model of the sequence-fitness landscape that can exhaustively be explored in silico and capitalize on the high diversity potential offered by nature However, as both the quality and quantity of the inputted data determine the success of such approaches, the applicability of data-driven strategies is often limited due to sparse data. Here, we present a hybrid model that combines direct coupling analysis and machine learning techniques to enable data-driven protein engineering when only few labeled sequences are available. Our method achieves high performance in predicting a protein’s fitness based on its sequence regardless of the number of sequences-fitness pairs in the training dataset. Besides reducing the computational effort compared to state-of-the-art methods, it outperforms them for sparse data situations, i.e., 50 − 250 labeled sequences available for training. In essence, the developed method is auspicious for data-driven protein engineering, especially for protein engineers who have only access to a limited amount of data for sequence-fitness landscape modeling.

The shape of tomato fruits is closely correlated to microtubule organization and the activity of microtubule associated proteins (MAP), but insights into the mechanism from a cell biology perspective are still largely elusive. Analysis of tissue expression profiles of different microtubule regulators revealed that functionally distinct classes of MAPs are highly expressed during fruit development. Among these, several members of the plant-specific MAP70 family are preferably expressed at the initiation stage of fruit development. Transgenic tomato lines overexpressing SlMAP70 produced elongated fruits that show reduced cell circularity and microtubule anisotropy, while SlMAP70 loss-of-function mutant showed an opposite effect with flatter fruits. Microtubule anisotropy of fruit endodermis cells exhibited dramatic rearrangement during tomato fruit development, and SlMAP70-1 is likely implicated in cortical microtubule organization and fruit elongation throughout this stage by interacting with SUN10/SlIQD21a. The expression of SlMAP70 (or co-expression of SlMAP70 and SUN10/SlIQD21a) induces microtubule stabilization and prevents its dynamic rearrangement, both activities are essential for fruit shape establishment after anthesis. Together, our results identify SlMAP70 as a novel regulator of fruit elongation, and demonstrate that manipulating microtubule stability and organization at the early fruit developmental stage has a strong impact on fruit shape.

Psidium guajava L. (guava) is a small tree known for its fruit flavor that is cultivated almost around the globe in tropical areas. Its fruit is amazingly rich in antioxidants, vitamin C, potassium, and dietary fiber. In different parts of the world, this plant holds a special place with respect to fruit and nutritional items. Pharmacological research has shown that this plant has more potential than just a fruit source; it also has beneficial effects against a variety of chronic diseases due to its rich nutritional and phytochemical profile. The primary goal of this document is to provide an updated overview of Psidium guajava L. and its bioactive secondary metabolites, as well as their availability for further study, with a focus on the health benefits and potential industrial applications. There have been several studies conducted on Psidium guajava L. in relation to its use in the pharmaceutical industry. However, its clinical efficacy and applications are still debatable. Therefore, in this review a detailed study with respect to phytochemistry of the plant through modern instruments such as GC and LC-MS has been discussed. The biological activities of secondary metabolites isolated from this plant have been extensively discussed. In order to perform long-term clinical trials to learn more about their effectiveness as drugs and applications for various health benefits, a structure activity relationship has been established. Based on the literature, it is concluded that this plant has a wide variety of biopharmaceutical applications. As a whole, this article calls for long-term clinical trials to obtain a greater understanding of how it can be used to treat different diseases.

E3 ubiquitin ligases mediate the last step of the ubiquitination pathway in the ubiquitin-proteasome system (UPS). By targeting transcriptional regulators for their turnover, E3s play a crucial role in every aspect of plant biology. In plants, SKP1/CULLIN1/F-BOX PROTEIN (SCF)-type E3 ubiquitin ligases are essential for the perception and signaling of several key hormones including auxins and jasmonates (JAs). F-box proteins, TRANSPORT INHIBITOR RESPONSE 1 (TIR1) and CORONATINE INSENSITIVE 1 (COI1), bind directly transcriptional repressors AUXIN/INDOLE-3-ACETIC ACID (AUX/IAA) and JASMONATE ZIM-DOMAIN (JAZ) in auxin- and JAs-depending manner, respectively, which permits the perception of the hormones and transcriptional activation of signaling pathways. Redox modification of proteins mainly by S-nitrosation of cysteines (Cys) residues via nitric oxide (NO) has emerged as a valued regulatory mechanism in physiological processes requiring its rapid and versatile integration. Previously, we demonstrated that TIR1 and Arabidopsis thaliana SKP1 (ASK1) are targets of S-nitrosation, and these NO-dependent posttranslational modifications enhance protein-protein interactions and positively regulate SCFTIR1 complex assembly and expression of auxin response genes. In this work, we confirmed S-nitrosation of Cys140 in TIR1, which was associated in planta to auxin-dependent developmental and stress-associated responses. In addition, we provide evidence on the modulation of the SCFCOI1 complex by different S-nitrosation events. We demonstrated that S-nitrosation of ASK1 Cys118 enhanced ASK1-COI1 protein-protein interaction. Overexpression of non-nitrosable ask1 mutant protein impaired the activation of JA-responsive genes mediated by SCFCOI1 illustrating the functional relevance of this redox-mediated regulation in planta. In silico analysis positions COI1 as a promising S-nitrosation target, and demonstrated that plants treated with methyl JA (MeJA) or S-nitrosocysteine (NO-Cys, S-nitrosation agent) develop shared responses at a genome-wide level. The regulation of SCF components involved in hormonal perception by S-nitrosation may represent a key strategy to determine the precise time and site-dependent activation of each hormonal signaling pathway and highlights NO as a pivotal molecular player in these scenarios.

(LOW PHOSPHATE ROOT 1), a bacterial-type plant ferroxidase, is crucial for local root phosphate (Pi) sensing. Here, we present a detailed protocol for native (tag-free) protein purification of LPR1 from leaf extracts by differential ammonium sulfate precipitation, size exclusion, and cation exchange chromatography of a transgenic Arabidopsis thaliana line overexpressing LPR1. We outline steps for LPR1 purification tracking via immune blot analysis and ferroxidase activity assay. The protocol yields highly pure and active LPR1 protein for biochemical analysis. For complete details on the use and execution of this protocol, please refer to Naumann et al. (2022)

In vivo localization of proteins using fluorescence-based approaches by fusion of the protein of interest (POI) to a fluorescent protein is a cost- and time-effective tool to gain insights into its physiological function in a plant cell. Determining the proper localization, however, requires the co-expression of defined organelle markers (OM). Several marker sets are available but, so far, the procedure requires successful co-transformation of POI and OM into the same cell and/or several cloning steps. We developed a set of vectors containing markers for basic cell organelles that enables the insertion of the gene of interest (GOI) by a single cloning step using the Golden Gate cloning approach and resulting in POI–GFP fusions. The set includes markers for plasma membrane, tonoplast, nucleus, endoplasmic reticulum, Golgi apparatus, peroxisomes, plastids, and mitochondria, all labelled with mCherry. Most of them were derived from well-established marker sets, but those localized in plasma membrane and tonoplast were improved by using different proteins. The final vectors are usable for localization studies in isolated protoplasts and for transient transformation of leaves of Nicotiana benthamiana. Their functionality is demonstrated using two enzymes involved in biosynthesis of jasmonic acid and located in either plastids or peroxisomes.

Drought dramatically affects crop productivity worldwide. For legumes this effect is especially pronounced, as their symbiotic association with rhizobia is highly-sensitive to dehydration. This might be attributed to the oxidative stress, which ultimately accompanies plants’ response to water deficit. Indeed, enhanced formation of reactive oxygen species in root nodules might result in up-regulation of lipid peroxidation and overproduction of reactive carbonyl compounds (RCCs), which readily modify biomolecules and disrupt cell functions. Thus, the knowledge of the nodule carbonyl metabolome dynamics is critically important for understanding the drought-related losses of nitrogen fixation efficiency and plant productivity. Therefore, here we provide, to the best of our knowledge, for the first time a comprehensive overview of the pea root nodule carbonyl metabolome and address its alterations in response to polyethylene glycol-induced osmotic stress as the first step to examine the changes of RCC patterns in drought treated plants. RCCs were extracted from the nodules and derivatized with 7-(diethylamino)coumarin-3-carbohydrazide (CHH). The relative quantification of CHH-derivatives by liquid chromatography-high resolution mass spectrometry with a post-run correction for derivative stability revealed in total 194 features with intensities above 1 × 105 counts, 19 of which were down- and three were upregulated. The upregulation of glyceraldehyde could accompany non-enzymatic conversion of glyceraldehyde-3-phosphate to methylglyoxal. The accumulation of 4,5-dioxovaleric acid could be the reason for down-regulation of porphyrin metabolism, suppression of leghemoglobin synthesis, inhibition of nitrogenase and degradation of legume-rhizobial symbiosis in response to polyethylene glycol (PEG)-induced osmotic stress effect. This effect needs to be confirmed with soil-based drought models.

The seed-to-seedling transition is a crucial step in the plant life cycle. The transition occurs at the end of seed germination and corresponds to the initiation of embryonic root growth. To improve our understanding of how a seed transforms into a seedling, we germinated the Pisum sativum L. seeds for 72 h and divided them into samples before and after radicle protrusion. Before radicle protrusion, seeds survived after drying and formed normally developed seedlings upon rehydration. Radicle protrusion increased the moisture content level in seed axes, and the accumulation of ROS first generated in the embryonic root and plumule. The water and oxidative status shift correlated with the desiccation tolerance loss. Then, we compared RNA sequencing-based transcriptomics in the embryonic axes isolated from pea seeds before and after radicle protrusion. We identified 24,184 differentially expressed genes during the transition to the post-germination stage. Among them, 2101 genes showed more prominent expression. They were related to primary and secondary metabolism, photosynthesis, biosynthesis of cell wall components, redox status, and responses to biotic stress. On the other hand, 415 genes showed significantly decreased expression, including the groups related to water deprivation (eight genes) and response to the ABA stimulus (fifteen genes). We assume that the water deprivation group, especially three genes also belonging to ABA stimulus (LTI65, LTP4, and HVA22E), may be crucial for the desiccation tolerance loss during a metabolic switch from seed to seedling. The latter is also accompanied by the suppression of ABA-related transcription factors ABI3, ABI4, and ABI5. Among them, HVA22E, ABI4, and ABI5 were highly conservative in functional domains and showed homologous sequences in different drought-tolerant species. These findings elaborate on the critical biochemical pathways and genes regulating seed-to-seedling transition.