A Pan-plant Protein Complex Map Reveals Deep Conservation and Novel Assemblies

Unexpected enzymatic function of an ancient nucleic acid-binding fold

Aminoacyl-tRNA synthetases (ARSs) are indispensable for all living organisms and their associated aminoacyl-tRNA editing domains ensure the fidelity of translation. In eukaryotes, ARSs form a multi-aminoacyl-tRNA synthetase complex (MSC), which is assembled together with several nonsynthetase scaffolding proteins. The MSC found in Trypanosoma brucei (Tb) includes two proteins with oligosaccharide/oligonucleotide-binding (OB) folds-MSC-associated protein 1 (MCP1) and MCP2-and one known trans-editing factor, MCP3, an Ala-tRNA deacylase. The activity of MCP1 was unexplored until now. Our study shows that recombinantly-expressed and purified MCP1 also deacylates Ala-tRNAs despite lacking known tRNA-editing domain homology. Domain deletion studies reveal that the OB-fold houses the catalytic pocket and mutation of any one of three conserved OB-fold residues (K326, R331, S335) abolishes activity. Assays with Saccharomyces cerevisiae Arc1p reveal that MCP1's deacylation activity is conserved across organisms. This discovery explains the 3' CCA-end binding activity of this protein family and uncovers an ancient nucleic acid binding domain's unexpected enzymatic function.

Enhancing bioavailability and functionality of plant peptides and proteins: A review of novel strategies for food and pharmaceutical applications

Plant-derived peptides and proteins are emerging as versatile bioactive ingredients in functional food and pharmaceutical sectors due to their diverse health benefits. However, their practical applications are often limited by poor bioavailability and functional instability. This review evaluates key determinants of plant peptide/protein bioactivity, including physicochemical properties, anti-nutritional components, food matrix interactions, and gastrointestinal digestion conditions. Strategies to enhance their functionality and bioavailability are systematically discussed, focusing on absorption enhancers, structural modifications, protease inhibitors, and colloidal delivery systems (e.g., liposomes, emulsions, nanoparticles). Recent advancements highlight targeted enzymatic hydrolysis and fermentation as effective methods to generate bioactive peptides with improved therapeutic properties. Additionally, physical/chemical modifications enhance stability against proteolysis and improve functional performance. Innovations in plant-derived protein-based delivery systems, such as nanoparticles, demonstrate promise in protecting bioactive compounds and optimizing bioavailability. Collectively, these approaches provide a roadmap for developing next-generation plant-protein products, addressing challenges in bioactivity retention and gastrointestinal absorption.

Hierarchical Regulatory Networks Reveal Conserved Drivers of Plant Drought Response at the Cell-Type Level

Drought is a critical environmental challenge affecting plant growth and productivity. Understanding the regulatory networks governing drought response at the cellular level remains an open question. Here, a comprehensive multi-omics integration framework that combines transcriptomic, proteomic, epigenetic, and network-based analyses to delineate cell-type-specific regulatory networks involved in plant drought response is presented. By analyzing nearly 30 000 multi-omics data samples across species, unique insights are revealed into conserved drought responses and cell-type-specific regulatory dynamics, leveraging novel integrative analytical workflows. Notably, CIPK23 emerges as a conserved protein kinase mediating drought tolerance through interactions with CBL4, as validated by yeast two-hybrid and BiFC assays. Experimental validation in Arabidopsis thaliana and Vitis vinifera confirms the functional conservation of CIPK23, which enhances drought resistance in overexpression lines. In addition, the authors' causal network analysis pinpoints critical regulatory drivers such as NLP7 and CIPK23, providing insights into the molecular mechanisms of drought adaptation. These findings advance understanding of plant drought tolerance and offer potential targets for improving crop resilience across diverse species.

SWI/SNF-type complexes-transcription factor interplay: a key regulatory interaction

ATP-dependent switch/sucrose nonfermenting-type chromatin remodeling complexes (SWI/SNF CRCs) are multiprotein machineries altering chromatin structure, thus controlling the accessibility of genomic DNA to various regulatory proteins including transcription factors (TFs). SWI/SNF CRCs are highly evolutionarily conserved among eukaryotes. There are three main subtypes of SWI/SNF CRCs: canonical (cBAF), polybromo (pBAF), and noncanonical (ncBAF) in humans and their functional Arabidopsis counterparts SYD-associated SWI/SNF (SAS), MINU-associated SWI/SNF (MAS), and BRAHMA (BRM)-associated SWI/SNF (BAS). Here, we highlight the importance of interplay between SWI/SNF CRCs and TFs in human and Arabidopsis and summarize recent advances demonstrating their role in controlling important regulatory processes. We discuss possible mechanisms involved in TFs and SWI/SNF CRCs-dependent transcriptional control of gene expression. We indicate that Arabidopsis may serve as a valuable model for the identification of evolutionarily conserved SWI/SNF-TF interactions and postulate that further exploration of the TFs and SWI/SNF CRCs-interplay, especially in the context of the role of particular SWI/SNF CRC subtypes, TF type, as well as cell/tissue and conditions, among others, will help address important questions related to the specificity of SWI/SNF-TF interactions and the sequence of events occurring on their target genes.

Integration of multi-omics data accelerates molecular analysis of common wheat traits

Integration of multi-omics data can provide information on biomolecules from different layers to illustrate the complex biology systematically. Here, we build a multi-omics atlas containing 132,570 transcripts, 44,473 proteins, 19,970 phosphoproteins, and 12,427 acetylproteins across wheat vegetative and reproductive phases. Using this atlas, we elucidate transcriptional regulation network, contributions of post-translational modification (PTM) and transcript level to protein abundance, and biased homoeolog expression and PTM in wheat. The genes/proteins related to wheat development and disease resistance are systematically analyzed, thus identifying phosphorylation and/or acetylation modifications for the seed proteins controlling wheat grain quality and the disease resistance-related genes. Lastly, a unique protein module TaHDA9-TaP5CS1, specifying de-acetylation of TaP5CS1 by TaHDA9, is discovered, which regulates wheat resistance to Fusarium crown rot via increasing proline content. Our atlas holds great promise for fast-tracking molecular biology and breeding studies in wheat and related crops.

Integrating CORUM and co-fractionation mass spectrometry to create enhanced benchmarks for protein complex predictions

Co-fractionation mass spectrometry (CFMS) enables the discovery of protein complexes and the systems-level analysis of multimer dynamics that facilitate responses to environmental and developmental conditions. A major challenge in CFMS data analysis, and omics approaches in general, is the development of reliable benchmarks for accurate evaluation of prediction methods. CORUM is commonly used as a source of benchmark complexes for protein complex composition predictions; however, its assumption of fully assembled subunit pools often conflicts with size exclusion chromatography (SEC) and interaction predictions from CFMS experiments. To address this, we developed an integrative analysis method that leverages cross-kingdom evolutionary conservation among specific CORUM complexes and high-resolution SEC profile data from cell extracts. The resulting benchmark complexes are supported by statistical significance and consistent sizes between calculated and measured apparent masses. The approach was robust, revealing both conserved and species-specific complexes. Designed specifically for benchmark identification, this method can be applied to any species and used to evaluate protein complex predictions from other studies.

Global Protein Interactome Mapping in Rice Using Barcode-Indexed PCR Coupled with HiFi Long-Read Sequencing

Establishing the protein-protein interaction network sheds light on functional genomics studies by providing insights from known counterparts. However, the rice interactome has barely been studied due to the lack of massive, reliable, and cost-effective methodologies. Here, the development of a barcode-indexed PCR coupled with HiFi long-read sequencing pipeline (BIP-seq) is reported for high throughput Protein Protein Interaction (PPI)identification. BIP-seq is essentially built on the integration of library versus library Y2H mating strategy to facilitate the efficient acquisition of random PPI colonies, semi-mechanized dual barcode-indexed yeast colony PCR for the large-scale indexed amplification of bait and prey cDNAs, and massive pac-bio sequencing of PCR amplicon pools. It is demonstrated that BIP-seq could map over 15 000 high-confidence (≈62.5% could be verified by Bimolecular fluorescence Complementation (BiFC)) rice PPIs within 2 months, outperforming the other reported methods. In addition, the obtained 23 032 rice PPIs, including 22,665 newly identified PPIs, greatly expanded the current rice PPI dataset, provided a comprehensive overview of the rice PPIs networks, and could be a valuable asset in facilitating functional genomics research in rice.

Mapping the nanoscale organization of the human cell surface proteome reveals new functional associations and surface antigen clusters

The cell surface is a dynamic interface that controls cell-cell communication and signal transduction relevant to organ development, homeostasis and repair, immune reactivity, and pathologies driven by aberrant cell surface phenotypes. The spatial organization of cell surface proteins is central to these processes. High-resolution fluorescence microscopy and proximity labeling have advanced studies of surface protein associations, but the spatial organization of the complete surface proteome remains uncharted. In this study, we systematically mapped the surface proteome of human T-lymphocytes and B-lymphoblasts using proximity labeling of 85 antigens, identified from over 100 antibodies tested for binding to surface-exposed proteins. These experiments were coupled with an optimized data-independent acquisition mass spectrometry workflow to generate a robust dataset. Unsupervised clustering of the resulting interactome revealed functional modules, including well-characterized complexes such as the T-cell receptor and HLA class I/II, alongside novel clusters. Notably, we identified mitochondrial proteins localized to the surface, including the transcription factor TFAM, suggesting previously unappreciated roles for mitochondrial proteins at the plasma membrane. A high-accuracy machine learning classifier predicted over 6,000 surface protein associations, highlighting functional associations such as IL10RB's role as a negative regulator of type I interferon signaling. Spatial modeling of the surface proteome provided insights into protein dispersion patterns, distinguishing widely distributed proteins, such as CD45, from localized antigens, such as CD226 pointing to active mechanisms of regulating surface organization. This work provides a comprehensive map of the human surfaceome and a resource for exploring the spatial and functional dynamics of the cell membrane proteome.

A cell fractionation and quantitative proteomics pipeline to enable functional analyses of cotton fiber development

Cotton fibers are aerial trichoblasts that employ a highly polarized diffuse growth mechanism to emerge from the developing ovule epidermis. After executing a complicated morphogenetic program, the cells reach lengths over 2 cm and serve as the foundation of a multi-billion-dollar textile industry. Important traits such as fiber diameter, length, and strength are defined by the growth patterns and cell wall properties of individual cells. At present, the ability to engineer fiber traits is limited by our lack of understanding regarding the primary controls governing the rate, duration, and patterns of cell growth. To gain insights into the compartmentalized functions of proteins in cotton fiber cells, we developed a label-free liquid chromatography mass spectrometry method for systems-level analyses of fiber proteome. Purified fibers from a single locule were used to fractionate the fiber proteome into apoplast (APOT), membrane-associated (p200), and crude cytosolic (s200) fractions. Subsequently, proteins were identified, and their localizations and potential functions were analyzed using combinations of size exclusion chromatography, statistical and bioinformatic analyses. This method had good coverage of the p200 and APOT fractions, the latter of which was dominated by proteins associated with particulate membrane-enclosed compartments. The apoplastic proteome was diverse, the proteins were not degraded, and some displayed distinct multimerization states compared to their cytosolic pool. This quantitative proteomic pipeline can be used to improve coverage and functional analyses of the cotton fiber proteome as a function of developmental time or differing genotypes.

XYLAN O-ACETYLTRANSFERASE 6 promotes xylan synthesis by forming a complex with IRX10 and governs wall formation in rice

Xylan, a pivotal polymer with diversified structures, is indispensable for cell wall integrity and contributes to plant growth and biomass recalcitrance. Xylan is synthesized by multienzyme complexes named xylan synthase complexes (XSCs). However, the biochemical mechanism of XSCs and the functions of core components within XSC remain unclear. Here, we report that rice (Oryza sativa) XYLAN O-ACETYLTRANSFERASE 6 (XOAT6) and the xylan synthase IRREGULAR XYLEM10 (IRX10) represent core components of the XSC, acting together to biosynthesize acetyl-xylans. Co-fractionation mass spectrometry and protein-protein interaction analyses revealed that IRX10 and XOAT6 physically interact within XSC, corroborated by similar xylan defects in xoat6 and irx10 mutants. Biochemical assays showed that XOAT6 is an O-acetyltransferase of the xylan backbone and facilitates chain polymerization catalyzed by IRX10. Fluorescence correlation spectroscopy further visualized the xylooligomer polymerization process at a single-molecule level. Solid-state NMR analysis, electron microscopy observations, and nanoindentation examinations identified the altered xylan conformation, disorganized cellulosic structure, and increased wall rigidity and cellulose accessibility in the mutants, leading to brittleness and improved saccharification efficiency. Our findings provide insights into the assembly of XSCs and xylan biosynthesis and offer a framework for tailoring xylans to improve crop traits and biomass.

Cuticular wax in wheat: biosynthesis, genetics, and the stress response

All terrestrial plants possess a hydrophobic cuticle in the outermost layer of their aerial organs that is composed of cutin and wax. The cuticle serves as the first barrier between the plant and the surrounding environment and plays a key role in the resistance of plants to abiotic and biotic stressors. Additionally, they are closely associated with plant growth and development. Cuticular wax has attracted considerable attention as the main mediator of cuticular functions. In this review, we summarize the advances in the research investigating wheat cuticular wax, focusing on three aspects that include biosynthesis, genetics, and stress responses. Additionally, we discuss the applications of cuticular wax in wheat breeding.

Pairing omics to decode the diversity of plant specialized metabolism

Plants have evolved complex bouquets of specialized natural products that are utilized in medicine, agriculture, and industry. Untargeted natural product discovery has benefitted from growing plant omics data resources. Yet, plant genome complexity limits the identification and curation of biosynthetic pathways via single omics. Pairing multi-omics types within experiments provides multiple layers of evidence for biosynthetic pathway mining. The extraction of paired biological information facilitates connecting genes to transcripts and metabolites, especially when captured across time points, conditions and chemotypes. Experimental design requires specific adaptations to enable effective paired-omics analysis. Ultimately, metadata standards are required to support the integration of paired and unpaired public datasets and to accelerate collaborative efforts for natural product discovery in the plant research community.

Dehydrin Client Proteins Identified Using Phage Display Affinity Selected Libraries Processed With Paired-End Phage Sequencing

The late embryogenesis abundant proteins (LEAPs) are a class of noncatalytic, intrinsically disordered proteins with a malleable structure. Some LEAPs exhibit a protein and/or membrane binding capacity and LEAP binding to various targets has been positively correlated with abiotic stress tolerance. Regarding the LEAPs' presumptive role in protein protection, identifying client proteins (CtPs) to which LEAPs bind is one practicable means of revealing the mechanism by which they exert their function. To this end, we used phage display affinity selection to screen libraries derived from Arabidopsis thaliana seed mRNA with recombinant orthologous LEAPs from Arabidopsis and soybean (Glycine max). Subsequent high-throughput sequencing of DNA from affinity-purified phage was performed to characterize the entire subpopulation of phage retained by each LEAP ortholog. This entailed cataloging in-frame fusions, elimination of false positives, and aligning the hits on the CtP scaffold to reveal domains of respective CtPs that bound to orthologous LEAPs. This approach (paired-end phage sequencing) revealed a subpopulation of the proteome constituting the CtP repertoire in common between the two dehydrin orthologs (LEA14 and GmPm12) compared to bovine serum albumin (unrelated binding control). The veracity of LEAP:CtP binding for one of the CtPs (LEA14 and GmPM12 self-association) was independently assessed using temperature-related intensity change analysis. Moreover, LEAP:CtP interactions for four other CtPs were confirmed in planta using bimolecular fluorescence complementation assays. The results provide insights into the involvement of the dehydrin Y-segments and K-domains in protein binding.

Polyploidy drives autophagy to participate in plant-specific functions

Polyploidization promotes the functional diversification of autophagy in plants, expanding autophagy-associated genes (AAGs) to support processes like chloroplast division and flowering. Analysis of 92,967 AAGs in Arabidopsis thaliana, Solanum lycopersicum, Camellia oleifera, and 74 other plant species shows that 45.69% of AAGs are polyploidy-related, highlighting polyploidy's role in linking autophagy to plant-specific functions.

hu.MAP3.0: Atlas of human protein complexes by integration of > 25,000 proteomic experiments

Macromolecular protein complexes carry out most functions in the cell including essential functions required for cell survival. Unfortunately, we lack the subunit composition for all human protein complexes. To address this gap we integrated >25,000 mass spectrometry experiments using a machine learning approach to identify > 15,000 human protein complexes. We show our map of protein complexes is highly accurate and more comprehensive than previous maps, placing ~75% of human proteins into their physical contexts. We globally characterize our complexes using protein co-variation data (ProteomeHD.2) and identify co-varying complexes suggesting common functional associations. Our map also generates testable functional hypotheses for 472 uncharacterized proteins which we support using AlphaFold modeling. Additionally, we use AlphaFold modeling to identify 511 mutually exclusive protein pairs in hu.MAP3.0 complexes suggesting complexes serve different functional roles depending on their subunit composition. We identify expression as the primary way cells and organisms relieve the conflict of mutually exclusive subunits. Finally, we import our complexes to EMBL-EBI's Complex Portal (https://www.ebi.ac.uk/complexportal/home) as well as provide complexes through our hu.MAP3.0 web interface (https://humap3.proteincomplexes.org/). We expect our resource to be highly impactful to the broader research community.

Trends in co-fractionation mass spectrometry: A new gold-standard in global protein interaction network discovery

Co-fractionation mass spectrometry (CF-MS) uses biochemical fractionation to isolate and characterize macromolecular complexes from cellular lysates without the need for affinity tagging or capture. In recent years, this has emerged as a powerful technique for elucidating global protein-protein interaction networks in a wide variety of biospecimens. This review highlights the latest advancements in CF-MS experimental workflows including machine learning-guided analyses, for uncovering dynamic and high-resolution protein interaction landscapes with enhanced sensitivity, accuracy and throughput, enabling better biophysical characterization of endogenous protein complexes. By addressing challenges and emergent opportunities in the field, this review underscores the transformative potential of CF-MS in advancing our understanding of functional protein interaction networks in health and disease.

Methyltransferase ATMETTL5 writes m6A on 18S ribosomal RNA to regulate translation in Arabidopsis

Aberrant RNA modifications can lead to dysregulated gene expression and impeded growth in plants. Ribosomal RNA (rRNA) constitutes a substantial portion of total RNA, while the precise functions and molecular mechanisms underlying rRNA modifications in plants remain largely elusive. Here, we elucidated the exclusive occurrence of the canonical RNA modification N6-methyladenosine (m6A) solely 18S rRNA, but not 25S rRNA. We identified a completely uncharacterized protein, ATMETTL5, as an Arabidopsis m6A methyltransferase responsible for installing m6A methylation at the 1771 site of the 18S rRNA. ATMETTL5 is ubiquitously expressed and localized in both nucleus and cytoplasm, mediating rRNA m6A methylation. Mechanistically, the loss of ATMETTL5-mediated methylation results in attenuated translation. Furthermore, we uncovered the role of ATMETTL5-mediated methylation in coordinating blue light-mediated hypocotyl growth by regulating the translation of blue light-related messenger RNAs (mRNAs), specifically HYH and PRR9. Our findings provide mechanistic insights into how rRNA modification regulates ribosome function in mRNA translation and the response to blue light, thereby advancing our understanding of the role of epigenetic modifications in precisely regulating mRNA translation in plants.

Advances in crosslinking chemistry and proximity-enabled strategies: deciphering protein complexes and interactions

Mass spectrometry, coupled with innovative crosslinking techniques to decode protein conformations and interactions through uninterrupted signal connections, has undergone remarkable progress in recent years. It is crucial to develop selective crosslinking reagents that minimally disrupt protein structure and dynamics, providing insights into protein network regulation and biological functions. Compared to traditional crosslinkers, new bifunctional chemical crosslinkers exhibit high selectivity and specificity in connecting proximal amino acid residues, resulting in stable molecular crosslinked products. The conjugation with specific amino acid residues like lysine, cysteine, arginine and tyrosine expands the XL-MS toolbox, enabling more precise modeling of target substrates and leading to improved data quality and reliability. Another emerging crosslinking method utilizes unnatural amino acids (UAAs) derived from proximity-enabled reactivity with specific amino acids or sulfur-fluoride exchange (SuFEx) reactions with nucleophilic residues. These UAAs are genetically encoded into proteins for the formation of specific covalent bonds. This technique combines the benefits of genetic encoding for live cell compatibility with chemical crosslinking, providing a valuable method for capturing transient and weak protein-protein interactions (PPIs) for mapping PPI coordinates and improving the pharmacological properties of proteins. With continued advancements in technology and applications, crosslinking mass spectrometry is poised to play an increasingly significant role in guiding our understanding of protein dynamics and function in the future.

The era of panomics-driven gene discovery in plants

Panomics is an approach to integrate multiple 'omics' datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.

Alternative proteoforms and proteoform-dependent assemblies in humans and plants

The variability of proteins at the sequence level creates an enormous potential for proteome complexity. Exploring the depths and limits of this complexity is an ongoing goal in biology. Here, we systematically survey human and plant high-throughput bottom-up native proteomics data for protein truncation variants, where substantial regions of the full-length protein are missing from an observed protein product. In humans, Arabidopsis, and the green alga Chlamydomonas, approximately one percent of observed proteins show a short form, which we can assign by comparison to RNA isoforms as either likely deriving from transcript-directed processes or limited proteolysis. While some detected protein fragments align with known splice forms and protein cleavage events, multiple examples are previously undescribed, such as our observation of fibrocystin proteolysis and nuclear translocation in a green alga. We find that truncations occur almost entirely between structured protein domains, even when short forms are derived from transcript variants. Intriguingly, multiple endogenous protein truncations of phase-separating translational proteins resemble cleaved proteoforms produced by enteroviruses during infection. Some truncated proteins are also observed in both humans and plants, suggesting that they date to the last eukaryotic common ancestor. Finally, we describe novel proteoform-specific protein complexes, where the loss of a domain may accompany complex formation.

Comprehensive analysis of Alfin-like transcription factors associated with drought and salt stresses in wheat (Triticum aestivum L.)

BACKGROUND

Alfin-like proteins are a kind of plant-specific transcription factors, and play vital roles in plant growth, development and stress responses.

RESULTS

In this study, a total of 27 Alfin-like transcription factors were identified in wheat. TaAL genes were unevenly distributed on chromosome. Phylogenetic analysis showed TaAL genes were divided into AL-B and AL-C subfamilies, and TaALs with closer evolutionary relationships generally shared more similar exon-intron structures and conserved motifs. The cis-acting element analysis showed MBS, ABRE and CGTCA-motif were the most common in TaAL promoters. The interacting proteins and downstream target genes of TaAL genes were also investigated in wheat. The transcriptome data and real-time PCR results indicated TaAL genes were differentially expressed under drought and salt stresses, and TaAL1-B was significantly up-regulated in response to drought stress. In addition, association analysis revealed that TaAL1-B-Hap-I allelic variation had significantly higher survival rate compared to TaAL1-B-Hap-II under drought stress.

CONCLUSIONS

These results will provide vital information to increase our understanding of the Alfin-like gene family in wheat, and help us in breeding better wheat varieties in the future.

Trypanosoma brucei multi-aminoacyl-tRNA synthetase complex formation limits promiscuous tRNA proofreading

Faithful mRNA decoding depends on the accuracy of aminoacyl-tRNA synthetases (ARSs). Aminoacyl-tRNA proofreading mechanisms have been well-described in bacteria, humans, and plants. However, our knowledge of translational fidelity in protozoans is limited. Trypanosoma brucei (Tb) is a eukaryotic, protozoan pathogen that causes Human African Trypanosomiasis, a fatal disease if untreated. Tb undergoes many physiological changes that are dictated by nutrient availability throughout its insect-mammal lifecycle. In the glucose-deprived insect vector, the tsetse fly, Tb use proline to make ATP via mitochondrial respiration. Alanine is one of the major by-products of proline consumption. We hypothesize that the elevated alanine pool challenges Tb prolyl-tRNA synthetase (ProRS), an ARS known to misactivate alanine in all three domains of life, resulting in high levels of misaminoacylated Ala-tRNAPro. Tb encodes two domains that are members of the INS superfamily of aminoacyl-tRNA deacylases. One homolog is appended to the N-terminus of Tb ProRS, and a second is the major domain of multi-aminoacyl-tRNA synthetase complex (MSC)-associated protein 3 (MCP3). Both ProRS and MCP3 are housed in the Tb MSC. Here, we purified Tb ProRS and MCP3 and observed robust Ala-tRNAPro deacylation activity from both enzymes in vitro. Size-exclusion chromatography multi-angle light scattering used to probe the oligomerization state of MCP3 revealed that although its unique N-terminal extension confers homodimerization in the absence of tRNA, the protein binds to tRNA as a monomer. Kinetic assays showed MCP3 alone has relaxed tRNA specificity and promiscuously hydrolyzes cognate Ala-tRNAAla; this activity is significantly reduced in the presence of Tb alanyl-tRNA synthetase, also housed in the MSC. Taken together, our results provide insight into translational fidelity mechanisms in Tb and lay the foundation for exploring MSC-associated proteins as novel drug targets.

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Ancient eukaryotic protein interactions illuminate modern genetic traits and disorders

All eukaryotes share a common ancestor from roughly 1.5 - 1.8 billion years ago, a single-celled, swimming microbe known as LECA, the Last Eukaryotic Common Ancestor. Nearly half of the genes in modern eukaryotes were present in LECA, and many current genetic diseases and traits stem from these ancient molecular systems. To better understand these systems, we compared genes across modern organisms and identified a core set of 10,092 shared protein-coding gene families likely present in LECA, a quarter of which are uncharacterized. We then integrated >26,000 mass spectrometry proteomics analyses from 31 species to infer how these proteins interact in higher-order complexes. The resulting interactome describes the biochemical organization of LECA, revealing both known and new assemblies. We analyzed these ancient protein interactions to find new human gene-disease relationships for bone density and congenital birth defects, demonstrating the value of ancestral protein interactions for guiding functional genetics today.

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

Harnessing the predicted maize pan-interactome for putative gene function prediction and prioritization of candidate genes for important traits

The recent assembly and annotation of the 26 maize nested association mapping population founder inbreds have enabled large-scale pan-genomic comparative studies. These studies have expanded our understanding of agronomically important traits by integrating pan-transcriptomic data with trait-specific gene candidates from previous association mapping results. In contrast to the availability of pan-transcriptomic data, obtaining reliable protein-protein interaction (PPI) data has remained a challenge due to its high cost and complexity. We generated predicted PPI networks for each of the 26 genomes using the established STRING database. The individual genome-interactomes were then integrated to generate core- and pan-interactomes. We deployed the PPI clustering algorithm ClusterONE to identify numerous PPI clusters that were functionally annotated using gene ontology (GO) functional enrichment, demonstrating a diverse range of enriched GO terms across different clusters. Additional cluster annotations were generated by integrating gene coexpression data and gene description annotations, providing additional useful information. We show that the functionally annotated PPI clusters establish a useful framework for protein function prediction and prioritization of candidate genes of interest. Our study not only provides a comprehensive resource of predicted PPI networks for 26 maize genomes but also offers annotated interactome clusters for predicting protein functions and prioritizing gene candidates. The source code for the Python implementation of the analysis workflow and a standalone web application for accessing the analysis results are available at https://github.com/eporetsky/PanPPI.

Nuclear lamina component KAKU4 regulates chromatin states and transcriptional regulation in the Arabidopsis genome

BACKGROUND

The nuclear lamina links the nuclear membrane to chromosomes and plays a crucial role in regulating chromatin states and gene expression. However, current knowledge of nuclear lamina in plants is limited compared to animals and humans.

RESULTS

This study mainly focused on elucidating the mechanism through which the putative nuclear lamina component protein KAKU4 regulates chromatin states and gene expression in Arabidopsis leaves. Thus, we constructed a network using the association proteins of lamin-like proteins, revealing that KAKU4 is strongly associated with chromatin or epigenetic modifiers. Then, we conducted ChIP-seq technology to generate global epigenomic profiles of H3K4me3, H3K27me3, and H3K9me2 in Arabidopsis leaves for mutant (kaku4-2) and wild-type (WT) plants alongside RNA-seq method to generate gene expression profiles. The comprehensive chromatin state-based analyses indicate that the knockdown of KAKU4 has the strongest effect on H3K27me3, followed by H3K9me2, and the least impact on H3K4me3, leading to significant changes in chromatin states in the Arabidopsis genome. We discovered that the knockdown of the KAKU4 gene caused a transition between two types of repressive epigenetics marks, H3K9me2 and H3K27me3, in some specific PLAD regions. The combination analyses of epigenomic and transcriptomic data between the kaku4-2 mutant and WT suggested that KAKU4 may regulate key biological processes, such as programmed cell death and hormone signaling pathways, by affecting H3K27me3 modification in Arabidopsis leaves.

CONCLUSIONS

In summary, our results indicated that KAKU4 is directly and/or indirectly associated with chromatin/epigenetic modifiers and demonstrated the essential roles of KAKU4 in regulating chromatin states, transcriptional regulation, and diverse biological processes in Arabidopsis.

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.

Profiling Protein-Protein Interactions in the Human Brain by Refined Cofractionation Mass Spectrometry

Proteins usually execute their biological functions through interactions with other proteins and by forming macromolecular complexes, but global profiling of protein complexes directly from human tissue samples has been limited. In this study, we utilized cofractionation mass spectrometry (CF-MS) to map protein complexes within the postmortem human brain with experimental replicates. First, we used concatenated anion and cation Ion Exchange Chromatography (IEX) to separate native protein complexes in 192 fractions and then proceeded with Data-Independent Acquisition (DIA) mass spectrometry to analyze the proteins in each fraction, quantifying a total of 4,804 proteins with 3,260 overlapping in both replicates. We improved the DIA's quantitative accuracy by implementing a constant amount of bovine serum albumin (BSA) in each fraction as an internal standard. Next, advanced computational pipelines, which integrate both a database-based complex analysis and an unbiased protein-protein interaction (PPI) search, were applied to identify protein complexes and construct protein-protein interaction networks in the human brain. Our study led to the identification of 486 protein complexes and 10054 binary protein-protein interactions, which represents the first global profiling of human brain PPIs using CF-MS. Overall, this study offers a resource and tool for a wide range of human brain research, including the identification of disease-specific protein complexes in the future.

Adaptive evolution of chloroplast division mechanisms during plant terrestrialization

Despite extensive research, the origin and evolution of the chloroplast division machinery remain unclear. Here, we employ recently sequenced genomes and transcriptomes of Archaeplastida clades to identify the core components of chloroplast division and reconstruct their evolutionary histories, respectively. Our findings show that complete division ring structures emerged in Charophytes. We find that Glaucophytes experienced strong selection pressure, generating diverse variants adapted to the changing terrestrial environments. By integrating the functions of chloroplast division genes (CDGs) annotated in a workflow developed using large-scale multi-omics data, we further show that dispersed duplications acquire more species-specific functions under stronger selection pressures. Notably, PARC6, a dispersed duplicate CDG, regulates leaf color and plant growth in Solanum lycopersicum, demonstrating neofunctionalization. Our findings provide an integrated perspective on the functional evolution of chloroplast division machinery and highlight the potential of dispersed duplicate genes as the primary source of adaptive evolution of chloroplast division.

Systematic profiling of ale yeast protein dynamics across fermentation and repitching

Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is among the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout 2 fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.)

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

Label-free proteomic comparison reveals ciliary and nonciliary phenotypes of IFT-A mutants

DIFFRAC is a powerful method for systematically comparing proteome content and organization between samples in a high-throughput manner. By subjecting control and experimental protein extracts to native chromatography and quantifying the contents of each fraction using mass spectrometry, it enables the quantitative detection of alterations to protein complexes and abundances. Here, we applied DIFFRAC to investigate the consequences of genetic loss of Ift122, a subunit of the intraflagellar transport-A (IFT-A) protein complex that plays a vital role in the formation and function of cilia and flagella, on the proteome of Tetrahymena thermophila. A single DIFFRAC experiment was sufficient to detect changes in protein behavior that mirrored known effects of IFT-A loss and revealed new biology. We uncovered several novel IFT-A-regulated proteins, which we validated through live imaging in Xenopus multiciliated cells, shedding new light on both the ciliary and non-ciliary functions of IFT-A. Our findings underscore the robustness of DIFFRAC for revealing proteomic changes in response to genetic or biochemical perturbation.

Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry

We present CFdb, a harmonized resource of interaction proteomics data from 411 co-fractionation mass spectrometry (CF-MS) datasets spanning 21,703 fractions. Meta-analysis of this resource charts protein abundance, phosphorylation, and interactions throughout the tree of life, including a reference map of the human interactome. We show how large-scale CF-MS data can enhance analyses of individual CF-MS datasets, and exemplify this strategy by mapping the honey bee interactome.

Co-fractionation-mass spectrometry to characterize native mitochondrial protein assemblies in mammalian neurons and brain

Human mitochondrial (mt) protein assemblies are vital for neuronal and brain function, and their alteration contributes to many human disorders, e.g., neurodegenerative diseases resulting from abnormal protein-protein interactions (PPIs). Knowledge of the composition of mt protein complexes is, however, still limited. Affinity purification mass spectrometry (MS) and proximity-dependent biotinylation MS have defined protein partners of some mt proteins, but are too technically challenging and laborious to be practical for analyzing large numbers of samples at the proteome level, e.g., for the study of neuronal or brain-specific mt assemblies, as well as altered mtPPIs on a proteome-wide scale for a disease of interest in brain regions, disease tissues or neurons derived from patients. To address this challenge, we adapted a co-fractionation-MS platform to survey native mt assemblies in adult mouse brain and in human NTERA-2 embryonal carcinoma stem cells or differentiated neuronal-like cells. The workflow consists of orthogonal separations of mt extracts isolated from chemically cross-linked samples to stabilize PPIs, data-dependent acquisition MS to identify co-eluted mt protein profiles from collected fractions and a computational scoring pipeline to predict mtPPIs, followed by network partitioning to define complexes linked to mt functions as well as those essential for neuronal and brain physiological homeostasis. We developed an R/CRAN software package, Macromolecular Assemblies from Co-elution Profiles for automated scoring of co-fractionation-MS data to define complexes from mtPPI networks. Presently, the co-fractionation-MS procedure takes 1.5-3.5 d of proteomic sample preparation, 31 d of MS data acquisition and 8.5 d of data analyses to produce meaningful biological insights.

Integration of data-independent acquisition (DIA) with co-fractionation mass spectrometry (CF-MS) to enhance interactome mapping capabilities

Proteomics technologies are continually advancing, providing opportunities to develop stronger and more robust protein interaction networks (PINs). In part, this is due to the ever-growing number of high-throughput proteomics methods that are available. This review discusses how data-independent acquisition (DIA) and co-fractionation mass spectrometry (CF-MS) can be integrated to enhance interactome mapping abilities. Furthermore, integrating these two techniques can improve data quality and network generation through extended protein coverage, less missing data, and reduced noise. CF-DIA-MS shows promise in expanding our knowledge of interactomes, notably for non-model organisms (NMOs). CF-MS is a valuable technique on its own, but upon the integration of DIA, the potential to develop robust PINs increases, offering a unique approach for researchers to gain an in-depth understanding into the dynamics of numerous biological processes.

Three consecutive cytosolic glycolysis enzymes modulate autophagic flux

Autophagy serves as an important recycling route for the growth and survival of eukaryotic organisms in nutrient-deficient conditions. Since starvation induces massive changes in the metabolic flux that are coordinated by key metabolic enzymes, specific processing steps of autophagy may be linked with metabolic flux-monitoring enzymes. We attempted to identify carbon metabolic genes that modulate autophagy using VIGS screening of 45 glycolysis- and Calvin-Benson cycle-related genes in Arabidopsis (Arabidopsis thaliana). Here, we report that three consecutive triose-phosphate-processing enzymes involved in cytosolic glycolysis, triose-phosphate-isomerase (TPI), glyceraldehyde-3-phosphate dehydrogenase (GAPC), and phosphoglycerate kinase (PGK), designated TGP, negatively regulate autophagy. Depletion of TGP enzymes causes spontaneous autophagy induction and increases AUTOPHAGY-RELATED 1 (ATG1) kinase activity. TGP enzymes interact with ATG101, a regulatory component of the ATG1 kinase complex. Spontaneous autophagy induction and abnormal growth under insufficient sugar in TGP mutants are suppressed by crossing with the atg101 mutant. Considering that triose-phosphates are photosynthates transported to the cytosol from active chloroplasts, the TGP enzymes would be strategically positioned to monitor the flow of photosynthetic sugars and modulate autophagy accordingly. Collectively, these results suggest that TGP enzymes negatively control autophagy acting upstream of the ATG1 complex, which is critical for seedling development.

Systematic thermal analysis of the Arabidopsis proteome: Thermal tolerance, organization, and evolution

Understanding the thermal stability of the plant proteome in the context of the native cellular environment would aid the design of crops with high thermal tolerance, but only limited such data are available. Here, we applied quantitative mass spectrometry to profile the thermal stability of the Arabidopsis proteome and identify thermo-sensitive and thermo-resilient protein networks in Arabidopsis, providing a basis for understanding heat-induced damage. We also show that the similarities of the protein-melting curves can be used as a proxy to evaluate system-wide protein-protein interactions in non-engineered plants and enable the identification of transient interactions exhibited by metabolons in the context of the cellular environment. Finally, we report a systematic comparison of the thermal stability of paralogs in Arabidopsis to aid the investigation and understanding of gene duplication and protein evolution. Taken together, our results could have broad implications for the fields of plant thermal tolerance, plant protein assemblies, and evolution.

The meso-octoploid Heliophila variabilis genome sheds a new light on the impact of polyploidization and diploidization on the diversity of the Cape flora

Although the South African Cape flora is one of the most remarkable biodiversity hotspots, its high diversity has not been associated with polyploidy. Here, we report the chromosome-scale genome assembly of an ephemeral cruciferous species Heliophila variabilis (~334 Mb, n = 11) adapted to South African semiarid biomes. Two pairs of differently fractionated subgenomes suggest an allo-octoploid origin of the genome at least 12 million years ago. The ancestral octoploid Heliophila genome (2n = 8x = ~60) has probably originated through hybridization between two allotetraploids (2n = 4x = ~30) formed by distant, intertribal, hybridization. Rediploidization of the ancestral genome was marked by extensive reorganization of parental subgenomes, genome downsizing, and speciation events in the genus Heliophila. We found evidence for loss-of-function changes in genes associated with leaf development and early flowering, and over-retention and sub/neofunctionalization of genes involved in pathogen response and chemical defense. The genomic resources of H. variabilis will help elucidate the role of polyploidization and genome diploidization in plant adaptation to hot arid environments and origin of the Cape flora. The sequenced H. variabilis represents the first chromosome-scale genome assembly of a meso-octoploid representative of the mustard family.

Systematic Profiling of Ale Yeast Protein Dynamics across Fermentation and Repitching

Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is amongst the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout two fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.

Protein nonadditive expression and solubility contribute to heterosis in Arabidopsis hybrids and allotetraploids

Hybrid vigor or heterosis has been widely applied in agriculture and extensively studied using genetic and gene expression approaches. However, the biochemical mechanism underlying heterosis remains elusive. One theory suggests that a decrease in protein aggregation may occur in hybrids due to the presence of protein variants between parental alleles, but it has not been experimentally tested. Here, we report comparative analysis of soluble and insoluble proteomes in Arabidopsis intraspecific and interspecific hybrids or allotetraploids formed between A. thaliana and A. arenosa. Both allotetraploids and intraspecific hybrids displayed nonadditive expression (unequal to the sum of the two parents) of the proteins, most of which were involved in biotic and abiotic stress responses. In the allotetraploids, homoeolog-expression bias was not observed among all proteins examined but accounted for 17-20% of the nonadditively expressed proteins, consistent with the transcriptome results. Among expression-biased homoeologs, there were more A. thaliana-biased than A. arenosa-biased homoeologs. Analysis of the insoluble and soluble proteomes revealed more soluble proteins in the hybrids than their parents but not in the allotetraploids. Most proteins in ribosomal biosynthesis and in the thylakoid lumen, membrane, and stroma were in the soluble fractions, indicating a role of protein stability in photosynthetic activities for promoting growth. Thus, nonadditive expression of stress-responsive proteins and increased solubility of photosynthetic proteins may contribute to heterosis in Arabidopsis hybrids and allotetraploids and possibly hybrid crops.

The conditional mitochondrial protein complexome in the Arabidopsis thaliana root and shoot

Protein complexes are important for almost all biological processes. Hence, to fully understand how cells work, it is also necessary to characterize protein complexes and their dynamics in response to various cellular cues. Moreover, the dynamics of protein interaction play crucial roles in regulating the (dis)association of protein complexes and, in turn, regulating biological processes such as metabolism. Here, mitochondrial protein complexes were investigated by blue native PAGE and size-exclusion chromatography under conditions of oxidative stress in order to monitor their dynamic (dis)associations. Rearrangements of enzyme interactions and changes in protein complex abundance were observed in response to oxidative stress induced by menadione treatment. These included changes in enzymatic protein complexes involving γ-amino butyric acid transaminase (GABA-T), Δ-ornithine aminotransferase (Δ-OAT), or proline dehydrogenase 1 (POX1) that are expected to affect proline metabolism. Menadione treatment also affected interactions between several enzymes of the tricarboxylic acid (TCA) cycle and the abundance of complexes of the oxidative phosphorylation pathway. In addition, we compared the mitochondrial complexes of roots and shoots. Considerable differences between the two tissues were observed in the mitochondrial import/export apparatus, the formation of super-complexes in the oxidative phosphorylation pathway, and specific interactions between enzymes of the TCA cycle that we postulate may be related to the metabolic/energetic requirements of roots and shoots.

Physiological and engineered tRNA aminoacylation

Aminoacyl-tRNA synthetases form the protein family that controls the interpretation of the genetic code, with tRNA aminoacylation being the key chemical step during which an amino acid is assigned to a corresponding sequence of nucleic acids. In consequence, aminoacyl-tRNA synthetases have been studied in their physiological context, in disease states, and as tools for synthetic biology to enable the expansion of the genetic code. Here, we review the fundamentals of aminoacyl-tRNA synthetase biology and classification, with a focus on mammalian cytoplasmic enzymes. We compile evidence that the localization of aminoacyl-tRNA synthetases can be critical in health and disease. In addition, we discuss evidence from synthetic biology which made use of the importance of subcellular localization for efficient manipulation of the protein synthesis machinery. This article is categorized under: RNA Processing Translation > Translation Regulation RNA Processing > tRNA Processing RNA Export and Localization > RNA Localization.

QTG-Miner aids rapid dissection of the genetic base of tassel branch number in maize

Genetic dissection of agronomic traits is important for crop improvement and global food security. Phenotypic variation of tassel branch number (TBN), a major breeding target, is controlled by many quantitative trait loci (QTLs). The lack of large-scale QTL cloning methodology constrains the systematic dissection of TBN, which hinders modern maize breeding. Here, we devise QTG-Miner, a multi-omics data-based technique for large-scale and rapid cloning of quantitative trait genes (QTGs) in maize. Using QTG-Miner, we clone and verify seven genes underlying seven TBN QTLs. Compared to conventional methods, QTG-Miner performs well for both major- and minor-effect TBN QTLs. Selection analysis indicates that a substantial number of genes and network modules have been subjected to selection during maize improvement. Selection signatures are significantly enriched in multiple biological pathways between female heterotic groups and male heterotic groups. In summary, QTG-Miner provides a large-scale approach for rapid cloning of QTGs in crops and dissects the genetic base of TBN for further maize breeding.

A novel approach for the analysis of single-cell RNA sequencing identifies TMEM14B as a novel poor prognostic marker in hepatocellular carcinoma

A fundamental goal in cancer-associated genome sequencing is to identify the key genes. Protein-protein interactions (PPIs) play a crucially important role in this goal. Here, human reference interactome (HuRI) map was generated and 64,006 PPIs involving 9094 proteins were identified. Here, we developed a physical link and co-expression combinatory network construction (PLACE) method for genes of interest, which provides a rapid way to analyze genome sequencing datasets. Next, Kaplan‒Meier survival analysis, CCK8 assays, scratch wound assays and Transwell assays were applied to confirm the results. In this study, we selected single-cell sequencing data from patients with hepatocellular carcinoma (HCC) in GSE149614. The PLACE method constructs a protein connection network for genes of interest, and a large fraction (80%) of the genes (screened by the PLACE method) were associated with survival. Then, PLACE discovered that transmembrane protein 14B (TMEM14B) was the most significant prognostic key gene, and target genes of TMEM14B were predicted. The TMEM14B-target gene regulatory network was constructed by PLACE. We also detected that TMEM14B-knockdown inhibited proliferation and migration. The results demonstrate that we proposed a new effective method for identifying key genes. The PLACE method can be used widely and make outstanding contributions to the tumor research field.

The formation and function of plant metabolons

Metabolons are temporary structural-functional complexes of sequential enzymes of a metabolic pathway that are distinct from stable multi-enzyme complexes. Here we provide a brief history of the study of enzyme-enzyme assemblies with a particular focus on those that mediate substrate channeling in plants. Large numbers of protein complexes have been proposed for both primary and secondary metabolic pathways in plants. However, to date only four substrate channels have been demonstrated. We provide an overview of current knowledge concerning these four metabolons and explain the methodologies that are currently being applied to unravel their functions. Although the assembly of metabolons has been documented to arise through diverse mechanisms, the physical interaction within the characterized plant metabolons all appear to be driven by interaction with structural elements of the cell. We therefore pose the question as to what methodologies could be brought to bear to enhance our knowledge of plant metabolons that assemble via different mechanisms? In addressing this question, we review recent findings in non-plant systems concerning liquid droplet phase separation and enzyme chemotaxis and propose strategies via which such metabolons could be identified in plants. We additionally discuss the possibilities that could be opened up by novel approaches based on: (i) subcellular-level mass spectral imaging, (ii) proteomics, and (iii) emergent methods in structural and computational biology.

Proximity Labeling in Plants

Proteins are workhorses in the cell; they form stable and more often dynamic, transient protein-protein interactions, assemblies, and networks and have an intimate interplay with DNA and RNA. These network interactions underlie fundamental biological processes and play essential roles in cellular function. The proximity-dependent biotinylation labeling approach combined with mass spectrometry (PL-MS) has recently emerged as a powerful technique to dissect the complex cellular network at the molecular level. In PL-MS, by fusing a genetically encoded proximity-labeling (PL) enzyme to a protein or a localization signal peptide, the enzyme is targeted to a protein complex of interest or to an organelle, allowing labeling of proximity proteins within a zoom radius. These biotinylated proteins can then be captured by streptavidin beads and identified and quantified by mass spectrometry. Recently engineered PL enzymes such as TurboID have a much-improved enzymatic activity, enabling spatiotemporal mapping with a dramatically increased signal-to-noise ratio. PL-MS has revolutionized the way we perform proteomics by overcoming several hurdles imposed by traditional technology, such as biochemical fractionation and affinity purification mass spectrometry. In this review, we focus on biotin ligase-based PL-MS applications that have been, or are likely to be, adopted by the plant field. We discuss the experimental designs and review the different choices for engineered biotin ligases, enrichment, and quantification strategies. Lastly, we review the validation and discuss future perspectives.

Capturing the hierarchically assorted modules of protein-protein interactions in the organized nucleome

Nuclear proteins are major constituents and key regulators of nucleome topological organization and manipulators of nuclear events. To decipher the global connectivity of nuclear proteins and the hierarchically organized modules of their interactions, we conducted two rounds of cross-linking mass spectrometry (XL-MS) analysis, one of which followed a quantitative double chemical cross-linking mass spectrometry (in vivoqXL-MS) workflow, and identified 24,140 unique crosslinks in total from the nuclei of soybean seedlings. This in vivo quantitative interactomics enabled the identification of 5340 crosslinks that can be converted into 1297 nuclear protein-protein interactions (PPIs), 1220 (94%) of which were non-confirmative (or novel) nuclear PPIs compared with those in repositories. There were 250 and 26 novel interactors of histones and the nucleolar box C/D small nucleolar ribonucleoprotein complex, respectively. Modulomic analysis of orthologous Arabidopsis PPIs produced 27 and 24 master nuclear PPI modules (NPIMs) that contain the condensate-forming protein(s) and the intrinsically disordered region-containing proteins, respectively. These NPIMs successfully captured previously reported nuclear protein complexes and nuclear bodies in the nucleus. Surprisingly, these NPIMs were hierarchically assorted into four higher-order communities in a nucleomic graph, including genome and nucleolus communities. This combinatorial pipeline of 4C quantitative interactomics and PPI network modularization revealed 17 ethylene-specific module variants that participate in a broad range of nuclear events. The pipeline was able to capture both nuclear protein complexes and nuclear bodies, construct the topological architectures of PPI modules and module variants in the nucleome, and probably map the protein compositions of biomolecular condensates.

m6A readers ECT2/ECT3/ECT4 enhance mRNA stability through direct recruitment of the poly(A) binding proteins in Arabidopsis

BACKGROUND

RNA N⁶-methyladenosine (m⁶A) modification is critical for plant growth and crop yield. m⁶A reader proteins can recognize m⁶A modifications to facilitate the functions of m⁶A in gene regulation. ECT2, ECT3, and ECT4 are m⁶A readers that are known to redundantly regulate trichome branching and leaf growth, but their molecular functions remain unclear.

RESULTS

Here, we show that ECT2, ECT3, and ECT4 directly interact with each other in the cytoplasm and perform genetically redundant functions in abscisic acid (ABA) response regulation during seed germination and post-germination growth. We reveal that ECT2/ECT3/ECT4 promote the stabilization of their targeted m⁶A-modified mRNAs, but have no function in alternative polyadenylation and translation. We find that ECT2 directly interacts with the poly(A) binding proteins, PAB2 and PAB4, and maintains the stabilization of m⁶A-modified mRNAs. Disruption of ECT2/ECT3/ECT4 destabilizes mRNAs of ABA signaling-related genes, thereby promoting the accumulation of ABI5 and leading to ABA hypersensitivity.

CONCLUSION

Our study reveals a unified functional model of m⁶A mediated by m⁶A readers in plants. In this model, ECT2/ECT3/ECT4 promote stabilization of their target mRNAs in the cytoplasm.