Exploring the diversity of plant proteome

The Zea mays PeptideAtlas: A New Maize Community Resource

This study presents the Maize PeptideAtlas resource (www.peptideatlas.org/builds/maize) to help solve questions about the maize proteome. Publicly available raw tandem mass spectrometry (MS/MS) data for maize collected from ProteomeXchange were reanalyzed through a uniform processing and metadata annotation pipeline. These data are from a wide range of genetic backgrounds and many sample types and experimental conditions. The protein search space included different maize genome annotations for the B73 inbred line from MaizeGDB, UniProtKB, NCBI RefSeq, and for the W22 inbred line. 445 million MS/MS spectra were searched, of which 120 million were matched to 0.37 million distinct peptides. Peptides were matched to 66.2% of proteins in the most recent B73 nuclear genome annotation. Furthermore, most conserved plastid- and mitochondrial-encoded proteins (NCBI RefSeq annotations) were identified. Peptides and proteins identified in the other B73 genome annotations will improve maize genome annotation. We also illustrate the high-confidence detection of unique W22 proteins. N-terminal acetylation, phosphorylation, ubiquitination, and three lysine acylations (K-acetyl, K-malonyl, and K-hydroxyisobutyryl) were identified and can be inspected through a PTM viewer in PeptideAtlas. All matched MS/MS-derived peptide data are linked to spectral, technical, and biological metadata. This new PeptideAtlas is integrated in MaizeGDB with a peptide track in JBrowse.

Rapid and dynamic detection of endogenous proteins through in locus tagging in rice

Understanding the behavior of endogenous proteins is crucial for functional genomics, yet their dynamic characterization in plants presents substantial challenges. Whereas mammalian studies have leveraged in locus tagging with the luminescent HiBiT peptide and genome editing for rapid quantification of native proteins, this approach remains unexplored in plants. Here, we introduce the in locus HiBiT tagging of rice proteins and demonstrate its feasibility in plants. We found that although traditional HiBiT blotting works in rice, it failed to detect two of the three tagged proteins, a result attributable to low luminescence activity in plants. To overcome this limitation, we engaged in extensive optimization, culminating in a new luciferin substrate coupled with a refined reaction protocol that enhanced luminescence up to 6.9 fold. This innovation led to the development of TagBIT (tagging with HiBiT), a robust method for high-sensitivity protein characterization in plants. Our application of TagBIT to seven rice genes illustrates its versatility on endogenous proteins, enabling antibody-free protein blotting, real-time protein quantification via luminescence, in situ visualization using a cross-breeding strategy, and effective immunoprecipitation for analysis of protein interactions. The heritable nature of this system, confirmed across T1 to T3 generations, positions TagBIT as a powerful tool for protein study in plant biology.

Multi-Omics Approaches in Oil Palm Research: A Comprehensive Review of Metabolomics, Proteomics, and Transcriptomics Based on Low-Temperature Stress

Oil palm (Elaeis guineensis Jacq.) is a typical tropical oil crop with a temperature of 26-28 °C, providing approximately 35% of the total world's vegetable oil. Growth and productivity are significantly affected by low-temperature stress, resulting in inhibited growth and substantial yield losses. To comprehend the intricate molecular mechanisms underlying the response and acclimation of oil palm under low-temperature stress, multi-omics approaches, including metabolomics, proteomics, and transcriptomics, have emerged as powerful tools. This comprehensive review aims to provide an in-depth analysis of recent advancements in multi-omics studies on oil palm under low-temperature stress, including the key findings from omics-based research, highlighting changes in metabolite profiles, protein expression, and gene transcription, as well as including the potential of integrating multi-omics data to reveal novel insights into the molecular networks and regulatory pathways involved in the response to low-temperature stress. This review also emphasizes the challenges and prospects of multi-omics approaches in oil palm research, providing a roadmap for future investigations. Overall, a better understanding of the molecular basis of the response of oil palm to low-temperature stress will facilitate the development of effective breeding and biotechnological strategies to improve the crop's resilience and productivity in changing climate scenarios.

Plant genome information facilitates plant functional genomics

MAIN CONCLUSION

In this review, we give an overview of plant sequencing efforts and how this impacts plant functional genomics research. Plant genome sequence information greatly facilitates the studies of plant biology, functional genomics, evolution of genomes and genes, domestication processes, phylogenetic relationships, among many others. More than two decades of sequencing efforts have boosted the number of available sequenced plant genomes. The first plant genome, of Arabidopsis, was published in the year 2000 and currently, 4604 plant genomes from 1482 plant species have been published. Various large sequence initiatives are running, which are planning to produce tens of thousands of sequenced plant genomes in the near future. In this review, we give an overview on the status of sequenced plant genomes and on the use of genome information in different research areas.

Subcellular compartmentalization in the biosynthesis and engineering of plant natural products

Plant natural products (PNPs) are specialized metabolites with diverse bioactivities. They are extensively used in the pharmaceutical, cosmeceutical and food industries. PNPs are synthesized in plant cells by enzymes that are distributed in different subcellular compartments with unique microenvironments, such as ions, co-factors and substrates. Plant metabolic engineering is an emerging and promising approach for the sustainable production of PNPs, for which the knowledge of the subcellular compartmentalization of their biosynthesis is instrumental. In this review we describe the state of the art on the role of subcellular compartments in the biosynthesis of major types of PNPs, including terpenoids, phenylpropanoids, alkaloids and glucosinolates, and highlight the efforts to target biosynthetic pathways to subcellular compartments in plants. In addition, we will discuss the challenges and strategies in the field of plant synthetic biology and subcellular engineering. We expect that newly developed methods and tools, together with the knowledge gained from the microbial chassis, will greatly advance plant metabolic engineering.

A community resource to mass explore the wheat grain proteome and its application to the late-maturity alpha-amylase (LMA) problem

BACKGROUND

Late-maturity alpha-amylase (LMA) is a wheat genetic defect causing the synthesis of high isoelectric point alpha-amylase following a temperature shock during mid-grain development or prolonged cold throughout grain development, both leading to starch degradation. While the physiology is well understood, the biochemical mechanisms involved in grain LMA response remain unclear. We have applied high-throughput proteomics to 4,061 wheat flours displaying a range of LMA activities. Using an array of statistical analyses to select LMA-responsive biomarkers, we have mined them using a suite of tools applicable to wheat proteins.

RESULTS

We observed that LMA-affected grains activated their primary metabolisms such as glycolysis and gluconeogenesis; TCA cycle, along with DNA- and RNA- binding mechanisms; and protein translation. This logically transitioned to protein folding activities driven by chaperones and protein disulfide isomerase, as well as protein assembly via dimerisation and complexing. The secondary metabolism was also mobilized with the upregulation of phytohormones and chemical and defence responses. LMA further invoked cellular structures, including ribosomes, microtubules, and chromatin. Finally, and unsurprisingly, LMA expression greatly impacted grain storage proteins, as well as starch and other carbohydrates, with the upregulation of alpha-gliadins and starch metabolism, whereas LMW glutenin, stachyose, sucrose, UDP-galactose, and UDP-glucose were downregulated.

CONCLUSIONS

To our knowledge, this is not only the first proteomics study tackling the wheat LMA issue but also the largest plant-based proteomics study published to date. Logistics, technicalities, requirements, and bottlenecks of such an ambitious large-scale high-throughput proteomics experiment along with the challenges associated with big data analyses are discussed.

Advances in mass spectrometry-based phosphoproteomics for elucidating abscisic acid signaling and plant responses to abiotic stress

Abiotic stresses have significant impacts on crop yield and quality. Even though significant efforts during the past decade have been devoted to uncovering the core signaling pathways associated with the phytohormone abscisic acid (ABA) and abiotic stress in plants, abiotic stress signaling mechanisms in most crops remain largely unclear. The core components of the ABA signaling pathway, including early events in the osmotic stress-induced phosphorylation network, have recently been elucidated in Arabidopsis with the aid of phosphoproteomics technologies. We now know that SNF1-related kinases 2 (SnRK2s) are not only inhibited by the clade A type 2C protein phosphatases (PP2Cs) through dephosphorylation, but also phosphorylated and activated by upstream mitogen-activated protein kinase kinase kinases (MAP3Ks). Through describing the course of studies to elucidate abiotic stress and ABA signaling, we will discuss how we can take advantage of the latest innovations in mass-spectrometry-based phosphoproteomics and structural proteomics to boost our investigation of plant regulation and responses to ABA and abiotic stress.

Crop Proteomics under Abiotic Stress: From Data to Insights

Food security is a major challenge in the present world due to erratic weather and climatic changes. Environmental stress negatively affects plant growth and development which leads to reduced crop yields. Technological advancements have caused remarkable improvements in crop-breeding programs. Proteins have an indispensable role in developing stress resilience and tolerance in crops. Genomic and biotechnological advancements have made the process of crop improvement more accurate and targeted. Proteomic studies provide the information required for such targeted approaches. The crosstalk among cellular components is being analyzed by subcellular proteomics. Additionally, the functional diversity of proteins is being unraveled by post-translational modifications during abiotic stress. The exploration of precise cellular responses and the networking among different cellular organelles help in the prediction of signaling pathways and protein-protein interactions. High-throughput mass-spectrometry-based protein studies are now possible due to incremental advancements in mass-spectrometry techniques, sample protocols, and bioinformatic tools as well as the increasing availability of plant genome sequence information for multiple species. In this review, the key role of proteomic analysis in identifying the abiotic-stress-responsive mechanisms in various crops was summarized. The development and availability of advanced computational tools were discussed in detail. The highly variable protein responses among different crops have provided a wide avenue for molecular-marker-assisted genetic buildup studies to develop smart, high-yielding, and stress-tolerant varieties to cope with food-security challenges.

Plant Kinases in the Perception and Signaling Networks Associated With Arthropod Herbivory

The success in the response of plants to environmental stressors depends on the regulatory networks that connect plant perception and plant response. In these networks, phosphorylation is a key mechanism to activate or deactivate the proteins involved. Protein kinases are responsible for phosphorylations and play a very relevant role in transmitting the signals. Here, we review the present knowledge on the contribution of protein kinases to herbivore-triggered responses in plants, with a focus on the information related to the regulated kinases accompanying herbivory in Arabidopsis. A meta-analysis of transcriptomic responses revealed the importance of several kinase groups directly involved in the perception of the attacker or typically associated with the transmission of stress-related signals. To highlight the importance of these protein kinase families in the response to arthropod herbivores, a compilation of previous knowledge on their members is offered. When available, this information is compared with previous findings on their role against pathogens. Besides, knowledge of their homologous counterparts in other plant-herbivore interactions is provided. Altogether, these observations resemble the complexity of the kinase-related mechanisms involved in the plant response. Understanding how kinase-based pathways coordinate in response to a specific threat remains a major challenge for future research.

Data Management and Modeling in Plant Biology

The study of plant-environment interactions is a multidisciplinary research field. With the emergence of quantitative large-scale and high-throughput techniques, amount and dimensionality of experimental data have strongly increased. Appropriate strategies for data storage, management, and evaluation are needed to make efficient use of experimental findings. Computational approaches of data mining are essential for deriving statistical trends and signatures contained in data matrices. Although, current biology is challenged by high data dimensionality in general, this is particularly true for plant biology. Plants as sessile organisms have to cope with environmental fluctuations. This typically results in strong dynamics of metabolite and protein concentrations which are often challenging to quantify. Summarizing experimental output results in complex data arrays, which need computational statistics and numerical methods for building quantitative models. Experimental findings need to be combined by computational models to gain a mechanistic understanding of plant metabolism. For this, bioinformatics and mathematics need to be combined with experimental setups in physiology, biochemistry, and molecular biology. This review presents and discusses concepts at the interface of experiment and computation, which are likely to shape current and future plant biology. Finally, this interface is discussed with regard to its capabilities and limitations to develop a quantitative model of plant-environment interactions.

Moonlighting Proteins: The Case of the Hexokinases

Moonlighting proteins are defined as proteins with two or more functions that are unrelated and independent to each other, so that inactivation of one of them should not affect the second one and vice versa. Intriguingly, all the glycolytic enzymes are described as moonlighting proteins in some organisms. Hexokinase (HXK) is a critical enzyme in the glycolytic pathway and displays a wide range of functions in different organisms such as fungi, parasites, mammals, and plants. This review discusses HXKs moonlighting functions in depth since they have a profound impact on the responses to nutritional, environmental, and disease challenges. HXKs’ activities can be as diverse as performing metabolic activities, as a gene repressor complexing with other proteins, as protein kinase, as immune receptor and regulating processes like autophagy, programmed cell death or immune system responses. However, most of those functions are particular for some organisms while the most common moonlighting HXK function in several kingdoms is being a glucose sensor. In this review, we also analyze how different regulation mechanisms cause HXK to change its subcellular localization, oligomeric or conformational state, the response to substrate and product concentration, and its interactions with membrane, proteins, or RNA, all of which might impact the HXK moonlighting functions.