Photosynthetic Metabolism and Nitrogen Reshuffling Are Regulated by Reversible Cysteine Thiol Oxidation Following Nitrogen Deprivation in Chlamydomonas

From Feasting to Fasting: The Arginine Pathway as a Metabolic Switch in Nitrogen-Deprived Chlamydomonas reinhardtii

The metabolism of the model microalgae Chlamydomonas reinhardtii under nitrogen deprivation is of special interest due to its resulting increment of triacylglycerols (TAGs), that can be applied in biotechnological applications. However, this same condition impairs cell growth, which may limit the microalgae's large applications. Several studies have identified significant physiological and molecular changes that occur during the transition from an abundant to a low or absent nitrogen supply, explaining in detail the differences in the proteome, metabolome and transcriptome of the cells that may be responsible for and responsive to this condition. However, there are still some intriguing questions that reside in the core of the regulation of these cellular responses that make this process even more interesting and complex. In this scenario, we reviewed the main metabolic pathways that are involved in the response, mining and exploring, through a reanalysis of omics data from previously published datasets, the commonalities among the responses and unraveling unexplained or non-explored mechanisms of the possible regulatory aspects of the response. Proteomics, metabolomics and transcriptomics data were reanalysed using a common strategy, and an in silico gene promoter motif analysis was performed. Together, these results identified and suggested a strong association between the metabolism of amino acids, especially arginine, glutamate and ornithine pathways to the production of TAGs, via the de novo synthesis of lipids. Furthermore, our analysis and data mining indicate that signalling cascades orchestrated with the indirect participation of phosphorylation, nitrosylation and peroxidation events may be essential to the process. The amino acid pathways and the amount of arginine and ornithine available in the cells, at least transiently during nitrogen deprivation, may be in the core of the post-transcriptional, metabolic regulation of this complex phenomenon. Their further exploration is important to the discovery of novel advances in the understanding of microalgae lipids' production.

Molecular Response of Ulva prolifera to Short-Term High Light Stress Revealed by a Multi-Omics Approach

The main algal species of Ulva prolifera green tide in the coastal areas of China are four species, but after reaching the coast of Qingdao, U. prolifera becomes the dominant species, where the light intensity is one of the most important influencing factors. In order to explore the effects of short-term high light stress on the internal molecular level of cells and its coping mechanism, the transcriptome, proteome, metabolome, and lipid data of U. prolifera were collected. The algae were cultivated in high light environment conditions (400 μmol·m−2·s−1) for 12 h and measured, and the data with greater relative difference (p < 0.05) were selected, then analyzed with the KEGG pathway. The results showed that the high light stress inhibited the assimilation of U. prolifera, destroyed the cell structure, and arrested its growth and development. Cells entered the emergency defense state, the TCA cycle was weakened, and the energy consumption processes such as DNA activation, RNA transcription, protein synthesis and degradation, and lipid alienation were inhibited. A gradual increase in the proportion of the C4 pathway was recorded. This study showed that U. prolifera can reduce the reactive oxygen species produced by high light stress, inhibit respiration, and reduce the generation of NADPH. At the same time, the C3 pathway began to change to the C4 pathway which consumed more energy. Moreover, this research provides the basis for the study of algae coping with high light stress.

Abscisic acid-controlled redox proteome of Arabidopsis and its regulation by heterotrimeric Gβ protein

The plant hormone abscisic acid (ABA) plays crucial roles in regulation of stress responses and growth modulation. Heterotrimeric G-proteins are key mediators of ABA responses. Both ABA and G-proteins have also been implicated in intracellular redox regulation; however, the extent to which reversible protein oxidation manipulates ABA and/or G-protein signaling remains uncharacterized. To probe the role of reversible protein oxidation in plant stress response and its dependence on G-proteins, we determined the ABA-dependent reversible redoxome of wild-type and Gβ-protein null mutant agb1 of Arabidopsis. We quantified 6891 uniquely oxidized cysteine-containing peptides, 923 of which show significant changes in oxidation following ABA treatment. The majority of these changes required the presence of G-proteins. Divergent pathways including primary metabolism, reactive oxygen species response, translation and photosynthesis exhibited both ABA- and G-protein-dependent redox changes, many of which occurred on proteins not previously linked to them. We report the most comprehensive ABA-dependent plant redoxome and uncover a complex network of reversible oxidations that allow ABA and G-proteins to rapidly adjust cellular signaling to adapt to changing environments. Physiological validation of a subset of these observations suggests that functional G-proteins are required to maintain intracellular redox homeostasis and fully execute plant stress responses.

Maximizing Depth of PTM Coverage: Generating Robust MS Datasets for Computational Prediction Modeling

Post-translational modifications (PTMs) regulate complex biological processes through the modulation of protein activity, stability, and localization. Insights into the specific modification type and localization within a protein sequence can help ascertain functional significance. Computational models are increasingly demonstrated to offer a low-cost, high-throughput method for comprehensive PTM predictions. Algorithms are optimized using existing experimental PTM data, thus accurate prediction performance relies on the creation of robust datasets. Herein, advancements in mass spectrometry-based proteomics technologies to maximize PTM coverage are reviewed. Further, requisite experimental validation approaches for PTM predictions are explored to ensure that follow-up mechanistic studies are focused on accurate modification sites.

MicroRNA Expression Profile Analysis of Chlamydomonas reinhardtii during Lipid Accumulation Process under Nitrogen Deprivation Stresses

Lipid accumulation in various microalgae has been found induced by nitrogen deprivation, and it controls many different genes expression. Yet, the underlying molecular mechanisms still remain largely unknown. MicroRNA (miRNAs) play a critical role in post-transcriptional gene regulation. In this study, miRNAs were hypothesized involved in lipid accumulation by nitrogen deprivation. A deep-sequencing platform was used to explore miRNAs-mediated responses induced by nitrogen deprivation in Chlamydomonas reinhardtii. The eukaryotic orthologous groups of proteins (KOG) function in the predicted target genes of miRNA with response to nitrogen deprivation were mainly involved in signal transduction mechanisms, including transcription, lipid transport, and metabolism. A total of 109 miRNA were predicted, including 79 known miRNA and 30 novel miRNA. A total of 29 miRNAs showed significantly differential expressions after nitrogen deprivation, and most of them were upregulated. A total of 10 miRNAs and their targeting genes might involve in lipid transport and metabolism biological process. This study first investigates nitrogen deprivation-regulated miRNAs in microalgae and broadens perspectives on miRNAs importance in microalgae lipid accumulation via nitrogen deprivation. This study provides theoretical guidance for the application of microalgae in bio-oil engineering production.

The Papain-like Cysteine Protease HpXBCP3 from Haematococcus pluvialis Involved in the Regulation of Growth, Salt Stress Tolerance and Chlorophyll Synthesis in Microalgae

The papain-like cysteine proteases (PLCPs), the most important group of cysteine proteases, have been reported to participate in the regulation of growth, senescence, and abiotic stresses in plants. However, the functions of PLCPs and their roles in stress response in microalgae was rarely reported. The responses to different abiotic stresses in Haematococcus pluvialis were often observed, including growth regulation and astaxanthin accumulation. In this study, the cDNA of HpXBCP3 containing 1515 bp open reading frame (ORF) was firstly cloned from H. pluvialis by RT-PCR. The analysis of protein domains and molecular evolution showed that HpXBCP3 was closely related to AtXBCP3 from Arabidopsis. The expression pattern analysis revealed that it significantly responds to NaCl stress in H. pluvialis. Subsequently, transformants expressing HpXBCP3 in Chlamydomonas reinhardtii were obtained and subjected to transcriptomic analysis. Results showed that HpXBCP3 might affect the cell cycle regulation and DNA replication in transgenic Chlamydomonas, resulting in abnormal growth of transformants. Moreover, the expression of HpXBCP3 might increase the sensitivity to NaCl stress by regulating ubiquitin and the expression of WD40 proteins in microalgae. Furthermore, the expression of HpXBCP3 might improve chlorophyll content by up-regulating the expression of NADH-dependent glutamate synthases in C. reinhardtii. This study indicated for the first time that HpXBCP3 was involved in the regulation of cell growth, salt stress response, and chlorophyll synthesis in microalgae. Results in this study might enrich the understanding of PLCPs in microalgae and provide a novel perspective for studying the mechanism of environmental stress responses in H. pluvialis.

Crosslinking mass spectrometry unveils novel interactions and structural distinctions in the model green alga Chlamydomonas reinhardtii

Interactomics is an emerging field that seeks to identify both transient and complex-bound protein interactions that are essential for metabolic functions. Crosslinking mass spectrometry (XL-MS) has enabled untargeted global analysis of these protein networks, permitting largescale simultaneous analysis of protein structure and interactions. Increased commercial availability of highly specific, cell permeable crosslinkers has propelled the study of these critical interactions forward, with the development of MS-cleavable crosslinkers further increasing confidence in identifications. Herein, the global interactome of the unicellular alga Chlamydomonas reinhardtii was analyzed via XL-MS by implementing the MS-cleavable disuccinimidyl sulfoxide (DSSO) crosslinker and enriching for crosslinks using strong cation exchange chromatography. Gentle lysis via repeated freeze-thaw cycles facilitated in vitro analysis of 157 protein-protein crosslinks (interlinks) and 612 peptides linked to peptides of the same protein (intralinks) at 1% FDR throughout the C. reinhardtii proteome. The interlinks confirmed known protein relationships across the cytosol and chloroplast, including coverage on 42% and 38% of the small and large ribosomal subunits, respectively. Of the 157 identified interlinks, 92% represent the first empirical evidence of interaction observed in C. reinhardtii. Several of these crosslinks point to novel associations between proteins, including the identification of a previously uncharacterized Mg-chelatase associated protein (Cre11.g477733.t1.2) bound to seven distinct lysines on Mg-chelatase (Cre06.g306300.t1.2). Additionally, the observed intralinks facilitated characterization of novel protein structures across the C. reinhardtii proteome. Together, these data establish a framework of protein-protein interactions that can be further explored to facilitate understanding of the dynamic protein landscape in C. reinhardtii.

A deep learning based approach for prediction of Chlamydomonas reinhardtii phosphorylation sites

Protein phosphorylation, which is one of the most important post-translational modifications (PTMs), is involved in regulating myriad cellular processes. Herein, we present a novel deep learning based approach for organism-specific protein phosphorylation site prediction in Chlamydomonas reinhardtii, a model algal phototroph. An ensemble model combining convolutional neural networks and long short-term memory (LSTM) achieves the best performance in predicting phosphorylation sites in C. reinhardtii. Deemed Chlamy-EnPhosSite, the measured best AUC and MCC are 0.90 and 0.64 respectively for a combined dataset of serine (S) and threonine (T) in independent testing higher than those measures for other predictors. When applied to the entire C. reinhardtii proteome (totaling 1,809,304 S and T sites), Chlamy-EnPhosSite yielded 499,411 phosphorylated sites with a cut-off value of 0.5 and 237,949 phosphorylated sites with a cut-off value of 0.7. These predictions were compared to an experimental dataset of phosphosites identified by liquid chromatography-tandem mass spectrometry (LC–MS/MS) in a blinded study and approximately 89.69% of 2,663 C. reinhardtii S and T phosphorylation sites were successfully predicted by Chlamy-EnPhosSite at a probability cut-off of 0.5 and 76.83% of sites were successfully identified at a more stringent 0.7 cut-off. Interestingly, Chlamy-EnPhosSite also successfully predicted experimentally confirmed phosphorylation sites in a protein sequence (e.g., RPS6 S245) which did not appear in the training dataset, highlighting prediction accuracy and the power of leveraging predictions to identify biologically relevant PTM sites. These results demonstrate that our method represents a robust and complementary technique for high-throughput phosphorylation site prediction in C. reinhardtii. It has potential to serve as a useful tool to the community. Chlamy-EnPhosSite will contribute to the understanding of how protein phosphorylation influences various biological processes in this important model microalga.

Mapping the plant proteome: tools for surveying coordinating pathways

Plants rapidly respond to environmental fluctuations through coordinated, multi-scalar regulation, enabling complex reactions despite their inherently sessile nature. In particular, protein post-translational signaling and protein-protein interactions combine to manipulate cellular responses and regulate plant homeostasis with precise temporal and spatial control. Understanding these proteomic networks are essential to addressing ongoing global crises, including those of food security, rising global temperatures, and the need for renewable materials and fuels. Technological advances in mass spectrometry-based proteomics are enabling investigations of unprecedented depth, and are increasingly being optimized for and applied to plant systems. This review highlights recent advances in plant proteomics, with an emphasis on spatially and temporally resolved analysis of post-translational modifications and protein interactions. It also details the necessity for generation of a comprehensive plant cell atlas while highlighting recent accomplishments within the field.

Proteomic response of Escherichia coli to a membrane lytic and iron chelating truncated Amaranthus tricolor defensin

BACKGROUND

Plant defensins are a broadly distributed family of antimicrobial peptides which have been primarily studied for agriculturally relevant antifungal activity. Recent studies have probed defensins against Gram-negative bacteria revealing evidence for multiple mechanisms of action including membrane lysis and ribosomal inhibition. Herein, a truncated synthetic analog containing the γ-core motif of Amaranthus tricolor DEF2 (Atr-DEF2) reveals Gram-negative antibacterial activity and its mechanism of action is probed via proteomics, outer membrane permeability studies, and iron reduction/chelation assays.

RESULTS

Atr-DEF2(G39-C54) demonstrated activity against two Gram-negative human bacterial pathogens, Escherichia coli and Klebsiella pneumoniae. Quantitative proteomics revealed changes in the E. coli proteome in response to treatment of sub-lethal concentrations of the truncated defensin, including bacterial outer membrane (OM) and iron acquisition/processing related proteins. Modification of OM charge is a common response of Gram-negative bacteria to membrane lytic antimicrobial peptides (AMPs) to reduce electrostatic interactions, and this mechanism of action was confirmed for Atr-DEF2(G39-C54) via an N-phenylnaphthalen-1-amine uptake assay. Additionally, in vitro assays confirmed the capacity of Atr-DEF2(G39-C54) to reduce Fe3+ and chelate Fe2+ at cell culture relevant concentrations, thus limiting the availability of essential enzymatic cofactors.

CONCLUSIONS

This study highlights the utility of plant defensin γ-core motif synthetic analogs for characterization of novel defensin activity. Proteomic changes in E. coli after treatment with Atr-DEF2(G39-C54) supported the hypothesis that membrane lysis is an important component of γ-core motif mediated antibacterial activity but also emphasized that other properties, such as metal sequestration, may contribute to a multifaceted mechanism of action.