IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding

Exploring liquid-liquid phase separation in the organisation of Golgi matrix proteins

The Golgi apparatus is a critical organelle in protein sorting and lipid metabolism. Characterized by its stacked, flattened cisternal structure, the Golgi exhibits distinct polarity with its cis- and trans-faces orchestrating various protein maturation and transport processes. At the heart of its structural integrity and organisation are the Golgi Matrix Proteins (GMPs), predominantly comprising Golgins and GRASPs. These proteins contribute to this organelle's unique stacked and polarized structure and ensure the precise localization of Golgi-resident enzymes, which is crucial for accurate protein processing. Despite over a century of research since its discovery, the Golgi architecture's intricate mechanisms still need to be fully understood. Here, we discuss that GMPs across different Eukaryotic lineages present a significant tendency to form biomolecular condensates. Moreover, we validated experimentally that members of the GRASP family also exhibit a strong tendency. Our findings offer a new perspective on the possible roles of protein disorder and condensation of GMPs in the Golgi organisation.

Biallelic variants in SNUPN cause a limb girdle muscular dystrophy with myofibrillar-like features

Alterations in RNA-splicing are a molecular hallmark of several neurological diseases, including muscular dystrophies, where mutations in genes involved in RNA metabolism or characterized by alterations in RNA splicing have been described. Here, we present five patients from two unrelated families with a limb-girdle muscular dystrophy (LGMD) phenotype carrying a biallelic variant in SNUPN gene. Snurportin-1, the protein encoded by SNUPN, plays an important role in the nuclear transport of small nuclear ribonucleoproteins (snRNPs), essential components of the spliceosome. We combine deep phenotyping, including clinical features, histopathology and muscle MRI, with functional studies in patient-derived cells and muscle biopsies to demonstrate that variants in SNUPN are the cause of a new type of LGMD according to current definition. Moreover, an in vivo model in Drosophila melanogaster further supports the relevance of Snurportin-1 in muscle. SNUPN patients show a similar phenotype characterized by proximal weakness starting in childhood, restrictive respiratory dysfunction and prominent contractures, although inter-individual variability in terms of severity even in individuals from the same family was found. Muscle biopsy showed myofibrillar-like features consisting of myotilin deposits and Z-disc disorganization. MRI showed predominant impairment of paravertebral, vasti, sartorius, gracilis, peroneal and medial gastrocnemius muscles. Conservation and structural analyses of Snurportin-1 p.Ile309Ser variant suggest an effect in nuclear-cytosol snRNP trafficking. In patient-derived fibroblasts and muscle, cytoplasmic accumulation of snRNP components is observed, while total expression of Snurportin-1 and snRNPs remains unchanged, which demonstrates a functional impact of SNUPN variant in snRNP metabolism. Furthermore, RNA-splicing analysis in patients' muscle showed widespread splicing deregulation, in particular in genes relevant for muscle development and splicing factors that participate in the early steps of spliceosome assembly. In conclusion, we report that SNUPN variants are a new cause of limb girdle muscular dystrophy with specific clinical, histopathological and imaging features, supporting SNUPN as a new gene to be included in genetic testing of myopathies. These results further support the relevance of splicing-related proteins in muscle disorders.

Elaboration of the Homer1 recognition landscape reveals incomplete divergence of paralogous EVH1 domains

Short sequences that mediate interactions with modular binding domains are ubiquitous throughout eukaryotic proteomes. Networks of short linear motifs (SLiMs) and their corresponding binding domains orchestrate many cellular processes, and the low mutational barrier to evolving novel interactions provides a way for biological systems to rapidly sample selectable phenotypes. Mapping SLiM binding specificity and the rules that govern SLiM evolution is fundamental to uncovering the pathways regulated by these networks and developing the tools to manipulate them. We used high-throughput screening of the human proteome to identify sequences that bind to the Enabled/VASP homology 1 (EVH1) domain of the postsynaptic density scaffolding protein Homer1. This expanded our understanding of the determinants of Homer EVH1 binding preferences and defined a new motif that can facilitate the discovery of additional Homer-mediated interactions. Interestingly, the Homer1 EVH1 domain preferentially binds to sequences containing an N-terminally overlapping motif that is bound by the paralogous family of Ena/VASP actin polymerases, and many of these sequences can bind to EVH1 domains from both protein families. We provide evidence from orthologous EVH1 domains in pre-metazoan organisms that the overlap in human Ena/VASP and Homer binding preferences corresponds to an incomplete divergence from a common Ena/VASP ancestor. Given this overlap in binding profiles, promiscuous sequences that can be recognized by both families either achieve specificity through extrinsic regulatory strategies or may provide functional benefits via multi-specificity. This may explain why these paralogs incompletely diverged despite the accessibility of further diverged isoforms.

The kinesin-3 KIF1C undergoes liquid-liquid phase separation for accumulation of specific transcripts at the cell periphery

In cells, mRNAs are transported to and positioned at subcellular areas to locally regulate protein production. Recent studies have identified the kinesin-3 family member motor protein KIF1C as an RNA transporter. However, it is not clear how KIF1C interacts with RNA molecules. Here, we show that the KIF1C C-terminal tail domain contains an intrinsically disordered region (IDR) that drives liquid-liquid phase separation (LLPS). KIF1C forms dynamic puncta in cells that display physical properties of liquid condensates and incorporate RNA molecules in a sequence-selective manner. Endogenous KIF1C forms condensates in cellular protrusions, where mRNAs are enriched in an IDR-dependent manner. Purified KIF1C tail constructs undergo LLPS in vitro at near-endogenous nM concentrations and in the absence of crowding agents and can directly recruit RNA molecules. Overall, our work uncovers an intrinsic correlation between the LLPS activity of KIF1C and its role in mRNA positioning. In addition, the LLPS activity of KIF1C's tail represents a new mode of motor-cargo interaction that extends our current understanding of cytoskeletal motor proteins.

Engineering Toxoplasma gondii secretion systems for intracellular delivery of multiple large therapeutic proteins to neurons

Delivering macromolecules across biological barriers such as the blood-brain barrier limits their application in vivo. Previous work has demonstrated that Toxoplasma gondii, a parasite that naturally travels from the human gut to the central nervous system (CNS), can deliver proteins to host cells. Here we engineered T. gondii's endogenous secretion systems, the rhoptries and dense granules, to deliver multiple large (>100 kDa) therapeutic proteins into neurons via translational fusions to toxofilin and GRA16. We demonstrate delivery in cultured cells, brain organoids and in vivo, and probe protein activity using imaging, pull-down assays, scRNA-seq and fluorescent reporters. We demonstrate robust delivery after intraperitoneal administration in mice and characterize 3D distribution throughout the brain. As proof of concept, we demonstrate GRA16-mediated brain delivery of the MeCP2 protein, a putative therapeutic target for Rett syndrome. By characterizing the potential and current limitations of the system, we aim to guide future improvements that will be required for broader application.

PairK: Pairwise k-mer alignment for quantifying protein motif conservation in disordered regions

Protein-protein interactions are often mediated by a modular peptide recognition domain binding to a short linear motif (SLiM) in the disordered region of another protein. The ability to predict domain-SLiM interactions would allow researchers to map protein interaction networks, predict the effects of perturbations to those networks, and develop biologically meaningful hypotheses. Unfortunately, sequence database searches for SLiMs generally yield mostly biologically irrelevant motif matches or false positives. To improve the prediction of novel SLiM interactions, researchers employ filters to discriminate between biologically relevant and improbable motif matches. One promising criterion for identifying biologically relevant SLiMs is the sequence conservation of the motif, exploiting the fact that functional motifs are more likely to be conserved than spurious motif matches. However, the difficulty of aligning disordered regions has significantly hampered the utility of this approach. We present PairK (pairwise k-mer alignment), an MSA-free method to quantify motif conservation in disordered regions. PairK outperforms both standard MSA-based conservation scores and a modern LLM-based conservation score predictor on the task of identifying biologically important motif instances. PairK can quantify conservation over wider phylogenetic distances than MSAs, indicating that SLiMs may be more conserved than is implied by MSA-based metrics. PairK is available as open-source code at https://github.com/jacksonh1/pairk.

The TSC22D, WNK, and NRBP gene families exhibit functional buffering and evolved with Metazoa for cell volume regulation

The ability to sense and respond to osmotic fluctuations is critical for the maintenance of cellular integrity. We used gene co-essentiality analysis to identify an unappreciated relationship between TSC22D2, WNK1, and NRBP1 in regulating cell volume homeostasis. All of these genes have paralogs and are functionally buffered for osmo-sensing and cell volume control. Within seconds of hyperosmotic stress, TSC22D, WNK, and NRBP family members physically associate into biomolecular condensates, a process that is dependent on intrinsically disordered regions (IDRs). A close examination of these protein families across metazoans revealed that TSC22D genes evolved alongside a domain in NRBPs that specifically binds to TSC22D proteins, which we have termed NbrT (NRBP binding region with TSC22D), and this co-evolution is accompanied by rapid IDR length expansion in WNK-family kinases. Our study reveals that TSC22D, WNK, and NRBP genes evolved in metazoans to co-regulate rapid cell volume changes in response to osmolarity.

Blending and separating dynamics of RNA-binding proteins develop architectural splicing networks spreading throughout the nucleus

The eukaryotic nucleus has a highly organized structure. Although the spatiotemporal arrangement of spliceosomes on nascent RNA drives splicing, the nuclear architecture that directly supports this process remains unclear. Here, we show that RNA-binding proteins (RBPs) assembled on RNA form meshworks in human and mouse cells. Core and accessory RBPs in RNA splicing make two distinct meshworks adjacently but distinctly distributed throughout the nucleus. This is achieved by mutual exclusion dynamics between the charged and uncharged intrinsically disordered regions (IDRs) of RBPs. These two types of meshworks compete for spatial occupancy on pre-mRNA to regulate splicing. Furthermore, the optogenetic enhancement of the RBP meshwork causes aberrant splicing, particularly of genes involved in neurodegeneration. Genetic mutations associated with neurodegenerative diseases are often found in the IDRs of RBPs, and cells harboring these mutations exhibit impaired meshwork formation. Our results uncovered the spatial organization of RBP networks to drive RNA splicing.

Lin28a forms an RNA-binding complex with Igf2bp3 to regulate m6A-modified stress response genes in stress granules of muscle stem cells

In the early embryonic stages, Lin-28 homologue A (Lin28a) is highly expressed and declines as the embryo matures. As an RNA-binding protein, Lin28a maintains some adult muscle stem cells (MuSCs) in an embryonic-like state, but its RNA metabolism regulation mechanism remains unclear. BioGPS analysis revealed that Lin28a expression is significantly higher in muscle tissues than in other tissues. Lin28a-positive muscle stem cells (Lin28a+ MuSCs) were sorted from Lin28a-CreERT2; LSL-tdTomato mouse skeletal muscle tissue, which exhibited a higher proliferation rate than the control group. Lin28a-bound transcripts are enriched in various biological processes such as DNA repair, cell cycle, mitochondrial tricarboxylic acid cycle and oxidative stress response. The expression of insulin-like growth factor 2 mRNA-binding protein 3 (Igf2bp3) was markedly elevated in the presence of Lin28a. Co-immunoprecipitation analysis further demonstrated that Lin28a associates with Igf2bp3. Immunofluorescence analyses confirmed that Lin28a, Igf2bp3 and G3bp1 colocalize to form stress granules (SG), and N6-methyladenosine (m6A) modification promotes the formation of Lin28a-SG. Sequencing of the transcriptome and RNAs immunoprecipitated by Lin28a, Igf2bp3 and m6A antibodies in Lin28a+ MuSCs further revealed that Lin28a and Igf2bp3 collaboratively regulate the expression of DNA repair-related genes, including Fancm and Usp1. Lin28a stabilises Igf2bp3, Usp1, and Fancm mRNAs, enhancing DNA repair against oxidative or proteotoxic stress, thus promoting MuSCs self-renewal. Understanding the intricate mechanisms through which Lin28a and Igf2bp3 regulate MuSCs provides a deeper understanding of stem cell self-renewal, with potential implications for regenerative medicine.

Identifying transcriptomic profiles in ovine spleen after repetitive vaccination

Aluminum hydroxide has long been employed as a vaccine adjuvant for its safety profile, although its precise mechanism of action remains elusive. In this study, we investigated the transcriptomic responses in sheep spleen following repetitive vaccination with aluminum adjuvanted vaccines and aluminum hydroxide alone. Notably, this work represents the first exploration of the sheep spleen transcriptome in such conditions. Animals were splitted in 3 treatment groups: vaccine group, adjuvant alone group and control group. A total of 18 high-depth RNA-seq libraries were sequenced, resulting in a rich dataset which also allowed isoform-level analysis. The comparisons between vaccine-treated and control groups (V vs C) as well as between vaccine-treated and adjuvant-alone groups (V vs A) revealed significant alterations in gene expression profiles, including protein coding genes and long non-coding RNAs. Among the differentially expressed genes, many were associated with processes such as endoplasmic reticulum (ER) stress, immune response and cell cycle. The analysis of co-expression modules further indicated a correlation between vaccine treatment and genes related to ER stress and unfolded protein response. Surprisingly, adjuvant-alone treatment had little impact on the spleen transcriptome. Additionally, the role of alternative splicing in the immune response was explored. We identified isoform switches in genes associated with immune regulation and inflammation, potentially influencing protein function. In conclusion, this study provides valuable insights into the transcriptomic changes in sheep spleen following vaccination with aluminum adjuvanted vaccines and aluminum hydroxide alone. These findings shed light on the molecular mechanisms underlying vaccine-induced immune responses and emphasize the significance of antigenic components in aluminum adjuvant mechanism of action. Furthermore, the analysis of alternative splicing revealed an additional layer of complexity in the immune response to vaccination in a livestock species.

FAM122A ensures cell cycle interphase progression and checkpoint control by inhibiting B55α/PP2A through helical motifs

The Ser/Thr protein phosphatase 2 A (PP2A) regulates the dephosphorylation of many phosphoproteins. Substrate recognition are mediated by B regulatory subunits. Here, we report the identification of a substrate conserved motif [RK]-V-x-x-[VI]-R in FAM122A, an inhibitor of B55α/PP2A. This motif is necessary for FAM122A binding to B55α, and computational structure prediction suggests the motif, which is helical, blocks substrate docking to the same site. In this model, FAM122A also spatially constrains substrate access by occluding the catalytic subunit. Consistently, FAM122A functions as a competitive inhibitor as it prevents substrate binding and dephosphorylation of CDK substrates by B55α/PP2A in cell lysates. FAM122A deficiency in human cell lines reduces the proliferation rate, cell cycle progression, and hinders G1/S and intra-S phase cell cycle checkpoints. FAM122A-KO in HEK293 cells attenuates CHK1 and CHK2 activation in response to replication stress. Overall, these data strongly suggest that FAM122A is a short helical motif (SHeM)-dependent, substrate-competitive inhibitor of B55α/PP2A that suppresses multiple functions of B55α in the DNA damage response and in timely progression through the cell cycle interphase.

A deep attention model for wide-genome protein-peptide binding affinity prediction at a sequence level

Peptides are pivotal in numerous biological activities by engaging in up to 40 % of protein-protein interactions in many cellular processes. Due to their exceptional specificity and effectiveness, peptides have emerged as promising candidates for drug design. However, accurately predicting protein-peptide binding affinity remains a challenging. Aiming at the problem, we develop a prediction model PepPAP based on convolutional neural network and multi-head attention, which relies solely on sequence features. These features include physicochemical properties, intrinsic disorder, sequence encoding, and especially interface propensity which is extracted from 16,689 non-redundant protein-peptide complexes. Notably, the adopted regression stratification cross-validation scheme proposed in our previous work is beneficial to improve the prediction for the cases with extreme binding affinity values. On three benchmark test datasets: T100, a series of peptides targeting to PDZ domain and CXCR4, PepPAP shows excellent performance, outperforming the existing methods and demonstrating its good generalization ability. Furthermore, PepPAP has good results in binary interaction prediction, and the analysis of the feature space distribution visualization highlights PepPAP's effectiveness. To the best of our knowledge, PepPAP is the first sequence-based deep attention model for wide-genome protein-peptide binding affinity prediction, and holds the potential to offer valuable insights for the peptide-based drug design.

AIUPred: combining energy estimation with deep learning for the enhanced prediction of protein disorder

Intrinsically disordered proteins and protein regions (IDPs/IDRs) carry out important biological functions without relying on a single well-defined conformation. As these proteins are a challenge to study experimentally, computational methods play important roles in their characterization. One of the commonly used tools is the IUPred web server which provides prediction of disordered regions and their binding sites. IUPred is rooted in a simple biophysical model and uses a limited number of parameters largely derived on globular protein structures only. This enabled an incredibly fast and robust prediction method, however, its limitations have also become apparent in light of recent breakthrough methods using deep learning techniques. Here, we present AIUPred, a novel version of IUPred which incorporates deep learning techniques into the energy estimation framework. It achieves improved performance while keeping the robustness of the original method. Based on the evaluation of recent benchmark datasets, AIUPred scored amongst the top three single sequence based methods. With a new web server we offer fast and reliable visual analysis for users as well as options to analyze whole genomes in mere seconds with the downloadable package. AIUPred is available at https://aiupred.elte.hu.

Direct observation of translational activation by a ribonucleoprotein granule

Biomolecular condensates organize biochemical processes at the subcellular level and can provide spatiotemporal regulation within a cell. Among these, ribonucleoprotein (RNP) granules are storage hubs for translationally repressed mRNA. Whether RNP granules can also activate translation and how this could be achieved remains unclear. Here, using single-molecule imaging, we demonstrate that the germ cell-determining RNP granules in Drosophila embryos are sites for active translation of nanos mRNA. Nanos translation occurs preferentially at the germ granule surface with the 3' UTR buried within the granule. Smaug, a cytosolic RNA-binding protein, represses nanos translation, which is relieved when Smaug is sequestered to the germ granule by the scaffold protein Oskar. Together, our findings uncover a molecular process by which RNP granules achieve localized protein synthesis through the compartmentalized loss of translational repression.

Biomolecular condensates in plant cells: mediating and integrating environmental signals and development

In response to the spatiotemporal coordination of various biochemical reactions and membrane-encapsulated organelles, plants appear to provide another effective mechanism for cellular organization by phase separation that allows the internal compartmentalization of cells to form a variety of membrane-less organelles. Most of the research on phase separation has centralized in various non-plant systems, such as yeast and animal systems. Recent studies have shown a remarkable correlation between the formation of condensates in plant systems and the formation of condensates in these systems. Moreover, the last decade has made new advances in phase separation research in the context of plant biology. Here, we provide an overview of the physicochemical forces and molecular factors that drive liquid-liquid phase separation in plant cells and the biochemical characterization of condensates. We then explore new developments in phase separation research specific to plants, discussing examples of condensates found in green plants and detailing their role in plant growth and development. We propose that phase separation may be a conserved organizational mechanism in plant evolution to help plants respond rapidly and effectively to various environmental stresses as sessile organisms.

High Polymorphism Levels of De Novo ORFs in a Yoruba Human Population

During evolution, new open reading frames (ORFs) with the potential to give rise to novel proteins continuously emerge. A recent compilation of noncanonical ORFs with translation signatures in humans has identified thousands of cases with a putative de novo origin. However, it is not known which is their distribution in the population. Are they universally translated? Here, we use ribosome profiling data from 65 lymphoblastoid cell lines from individuals of Yoruba origin to investigate this question. We identify 2,587 de novo ORFs translated in at least one of the cell lines. In line with their de novo origin, the encoded proteins tend to be smaller than 100 amino acids and encode positively charged proteins. We observe that the de novo ORFs are more polymorphic in the population than the set of canonical proteins, with a substantial fraction of them being translated in only some of the cell lines. Remarkably, this difference remains significant after controlling for differences in the translation levels. These results suggest that variations in the level translation of de novo ORFs could be a relevant source of intraspecies phenotypic diversity in humans.

The impacts of the mitochondrial myopathy-associated G58R mutation on the dynamic structural properties of CHCHD10

The mitochondria are responsible for producing energy within the cell, and in mitochondrial myopathy, there is a defect in the energy production process. The CHCHD10 gene codes for a protein called coiled-coil-helix-coiled-coil-helix domain-containing protein 10 (CHCHD10), which is found in the mitochondria and is involved in the regulation of mitochondrial function. G58R mutation has been shown to disrupt the normal function of CHCHD10, leading to mitochondrial dysfunction and ultimately to the development of mitochondrial myopathy. The structures of G58R mutant CHCHD10 and how G58R mutation impacts the wild-type CHCHD10 protein at the monomeric level are unknown. To address this problem, we conducted homology modeling, multiple run molecular dynamics simulations and bioinformatics calculations. We represent herein the structural ensemble properties of the G58R mutant CHCHD10 (CHCHD10G58R) in aqueous solution. Moreover, we describe the impacts of G58R mutation on the structural ensembles of wild-type CHCHD10 (CHCHD10WT) in aqueous solution. The dynamics properties as well as structural properties of CHCHD10WT are impacted by the mitochondrial myopathy-related G58R mutation. Specifically, the secondary and tertiary structure properties, root mean square fluctuations, Ramachandran diagrams and results from principal component analysis demonstrate that the CHCHD10WT and CHCHD10G58R proteins possess different structural ensemble characteristics and describe the impacts of G58R mutation on CHCHD10WT. These findings may be helpful for designing new treatments for mitochondrial myopathy.Communicated by Ramaswamy H. Sarma.

High-throughput and proteome-wide discovery of endogenous biomolecular condensates

Phase separation inside mammalian cells regulates the formation of the biomolecular condensates that are related to gene expression, signalling, development and disease. However, a large population of endogenous condensates and their candidate phase-separating proteins have yet to be discovered in a quantitative and high-throughput manner. Here we demonstrate that endogenously expressed biomolecular condensates can be identified across a cell's proteome by sorting proteins across varying oligomeric states. We employ volumetric compression to modulate the concentrations of intracellular proteins and the degree of crowdedness, which are physical regulators of cellular biomolecular condensates. The changes in degree of the partition of proteins into condensates or phase separation led to varying oligomeric states of the proteins, which can be detected by coupling density gradient ultracentrifugation and quantitative mass spectrometry. In total, we identified 1,518 endogenous condensate proteins, of which 538 have not been reported before. Furthermore, we demonstrate that our strategy can identify condensate proteins that respond to specific biological processes.

RNA modulates hnRNPA1A amyloid formation mediated by biomolecular condensates

Several RNA binding proteins involved in membraneless organelles can form pathological amyloids associated with neurodegenerative diseases, but the mechanisms of how this aggregation is modulated remain elusive. Here we investigate how heterotypic protein-RNA interactions modulate the condensation and the liquid to amyloid transition of hnRNPA1A, a protein involved in amyothropic lateral sclerosis. In the absence of RNA, formation of condensates promotes hnRNPA1A aggregation and fibrils are localized at the interface of the condensates. Addition of RNA modulates the soluble to amyloid transition of hnRNPA1A according to different pathways depending on RNA/protein stoichiometry. At low RNA concentrations, RNA promotes both condensation and amyloid formation, and the catalytic effect of RNA adds to the role of the interface between the dense and dilute phases. At higher RNA concentrations, condensation is suppressed according to re-entrant phase behaviour but formation of hnRNPA1A amyloids is observed over longer incubation times. Our findings show how heterotypic nucleic acid-protein interactions affect the kinetics and molecular pathways of amyloid formation.

The intrinsically disordered transactivation region of HOXA9 regulates its function by auto-inhibition of its DNA-binding activity

HOXA9 transcription factor is expressed in hematopoietic stem cells and is involved in the regulation of their differentiation and maturation to various blood cells. HOXA9 is linked to various leukemia and is a marker for poor prognosis of acute myeloid leukemia (AML). This protein has a conserved DNA-binding homeodomain and a transactivation domain. We show that this N-terminal transactivation domain is intrinsically disordered and inhibits DNA-binding by the homeodomain. Using NMR spectroscopy and molecular dynamics simulation, we show that the hexapeptide 197AANWLH202 in the disordered region transiently occludes the DNA-binding interface. The hexapeptide also forms a rigid segment, as determined by NMR dynamics, in an otherwise flexible disordered region. Interestingly, this hexapeptide is known to mediate the interaction of HOXA9 and its TALE partner proteins, such as PBX1, and help in cooperative DNA binding. Mutation of tryptophan to alanine in the hexapeptide abrogates the DNA-binding auto-inhibition. We propose that the disordered transactivation region plays a dual role in the regulation of HOXA9 function. In the absence of TALE partners, it inhibits DNA binding, and in the presence of TALE partners it interacts with the TALE protein and facilitates the cooperative DNA binding by the HOX-TALE complex.

MicroProteinDB: A database to provide knowledge on sequences, structures and function of ncRNA-derived microproteins

Omics-based technologies have revolutionized our comprehension of microproteins encoded by ncRNAs, revealing their abundant presence and pivotal roles within complex functional landscapes. Here, we developed MicroProteinDB (http://bio-bigdata.hrbmu.edu.cn/MicroProteinDB), which offers and visualizes the extensive knowledge to aid retrieval and analysis of computationally predicted and experimentally validated microproteins originating from various ncRNA types. Employing prediction algorithms grounded in diverse deep learning approaches, MicroProteinDB comprehensively documents the fundamental physicochemical properties, secondary and tertiary structures, interactions with functional proteins, family domains, and inter-species conservation of microproteins. With five major analytical modules, it will serve as a valuable knowledge for investigating ncRNA-derived microproteins.

Disordered sequences of transcription factors regulate genomic binding by integrating diverse sequence grammars and interaction types

Intrinsically disordered regions (IDRs) guide transcription factors (TFs) to their genomic binding sites, raising the question of how structure-lacking regions encode for complex binding patterns. We investigated this using the TF Gln3, revealing sets of IDR-embedded determinants that direct Gln3 binding to respective groups of functionally related promoters, and enable tuning binding preferences between environmental conditions, phospho-mimicking mutations, and orthologs. Through targeted mutations, we defined the role of short linear motifs (SLiMs) and co-binding TFs (Hap2) in stabilizing Gln3 at respiration-chain promoters, while providing evidence that Gln3 binding at nitrogen-associated promoters is encoded by the IDR amino-acid composition, independent of SLiMs or co-binding TFs. Therefore, despite their apparent simplicity, TF IDRs can direct and regulate complex genomic binding patterns through a combination of SLiM-mediated and composition-encoded interactions.

Computational evaluation and benchmark study of 342 crystallographic holo-structures of SARS-CoV-2 Mpro enzyme

The coronavirus disease 19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global health crisis with millions of confirmed cases and related deaths. The main protease (Mpro) of SARS-CoV-2 is crucial for viral replication and presents an attractive target for drug development. Despite the approval of some drugs, the search for effective treatments continues. In this study, we systematically evaluated 342 holo-crystal structures of Mpro to identify optimal conformations for structure-based virtual screening (SBVS). Our analysis revealed limited structural flexibility among the structures. Three docking programs, AutoDock Vina, rDock, and Glide were employed to assess the efficiency of virtual screening, revealing diverse performances across selected Mpro structures. We found that the structures 5RHE, 7DDC, and 7DPU (PDB Ids) consistently displayed the lowest EF, AUC, and BEDROCK scores. Furthermore, these structures demonstrated the worst pose prediction results in all docking programs. Two structural differences contribute to variations in docking performance: the absence of the S1 subsite in 7DDC and 7DPU, and the presence of a subpocket in the S2 subsite of 7DDC, 7DPU, and 5RHE. These findings underscore the importance of selecting appropriate Mpro conformations for SBVS, providing valuable insights for advancing drug discovery efforts.

Master corepressor inactivation through multivalent SLiM-induced polymerization mediated by the oncogene suppressor RAI2

While the elucidation of regulatory mechanisms of folded proteins is facilitated due to their amenability to high-resolution structural characterization, investigation of these mechanisms in disordered proteins is more challenging due to their structural heterogeneity, which can be captured by a variety of biophysical approaches. Here, we used the transcriptional master corepressor CtBP, which binds the putative metastasis suppressor RAI2 through repetitive SLiMs, as a model system. Using cryo-electron microscopy embedded in an integrative structural biology approach, we show that RAI2 unexpectedly induces CtBP polymerization through filaments of stacked tetrameric CtBP layers. These filaments lead to RAI2-mediated CtBP nuclear foci and relieve its corepressor function in RAI2-expressing cancer cells. The impact of RAI2-mediated CtBP loss-of-function is illustrated by the analysis of a diverse cohort of prostate cancer patients, which reveals a substantial decrease in RAI2 in advanced treatment-resistant cancer subtypes. As RAI2-like SLiM motifs are found in a wide range of organisms, including pathogenic viruses, our findings serve as a paradigm for diverse functional effects through multivalent interaction-mediated polymerization by disordered proteins in healthy and diseased conditions.

Protein embeddings predict binding residues in disordered regions

The identification of protein binding residues helps to understand their biological processes as protein function is often defined through ligand binding, such as to other proteins, small molecules, ions, or nucleotides. Methods predicting binding residues often err for intrinsically disordered proteins or regions (IDPs/IDPRs), often also referred to as molecular recognition features (MoRFs). Here, we presented a novel machine learning (ML) model trained to specifically predict binding regions in IDPRs. The proposed model, IDBindT5, leveraged embeddings from the protein language model (pLM) ProtT5 to reach a balanced accuracy of 57.2 ± 3.6% (95% confidence interval). Assessed on the same data set, this did not differ at the 95% CI from the state-of-the-art (SOTA) methods ANCHOR2 and DeepDISOBind that rely on expert-crafted features and evolutionary information from multiple sequence alignments (MSAs). Assessed on other data, methods such as SPOT-MoRF reached higher MCCs. IDBindT5's SOTA predictions are much faster than other methods, easily enabling full-proteome analyses. Our findings emphasize the potential of pLMs as a promising approach for exploring and predicting features of disordered proteins. The model and a comprehensive manual are publicly available at https://github.com/jahnl/binding_in_disorder .

Spectrin condensates provide a nidus for assembling the periodic axonal structure

Coordinated assembly of individual components into higher-order structures is a defining theme in biology, but underlying principles are not well-understood. In neurons, α/β spectrins, adducin, and actinfilaments assemble into a lattice wrapping underneath the axonal plasma membrane, but mechanistic events leading to this periodic axonal structure (PAS) are unclear. Visualizing PAS components in axons as they develop, we found focal patches in distal axons containing spectrins and adducin (but sparse actin filaments) with biophysical properties reminiscent of biomolecular condensation. Overexpressing spectrin-repeats - constituents of α/β-spectrins - in heterologous cells triggered condensate formation, and preventing association of βII-spectrin with actin-filaments/membranes also facilitated condensation. Finally, overexpressing condensate-triggering spectrin repeats in neurons before PAS establishment disrupted the lattice, presumably by competing with innate assembly, supporting a functional role for biomolecular condensation. We propose a condensation-assembly model where PAS components form focal phase-separated condensates that eventually unfurl into a stable lattice-structure by associating with subplasmalemmal actin. By providing local 'depots' of assembly parts, biomolecular condensation may play a wider role in the construction of intricate cytoskeletal structures.

A quantitative and site-specific atlas of the citrullinome reveals widespread existence of citrullination and insights into PADI4 substrates

Despite the importance of citrullination in physiology and disease, global identification of citrullinated proteins, and the precise targeted sites, has remained challenging. Here we employed quantitative-mass-spectrometry-based proteomics to generate a comprehensive atlas of citrullination sites within the HL60 leukemia cell line following differentiation into neutrophil-like cells. We identified 14,056 citrullination sites within 4,008 proteins and quantified their regulation upon inhibition of the citrullinating enzyme PADI4. With this resource, we provide quantitative and site-specific information on thousands of PADI4 substrates, including signature histone marks and transcriptional regulators. Additionally, using peptide microarrays, we demonstrate the potential clinical relevance of certain identified sites, through distinct reactivities of antibodies contained in synovial fluid from anti-CCP-positive and anti-CCP-negative people with rheumatoid arthritis. Collectively, we describe the human citrullinome at a systems-wide level, provide a resource for understanding citrullination at the mechanistic level and link the identified targeted sites to rheumatoid arthritis.

Unveiling the genetic tapestry: Rare disease genomics of spinal muscular atrophy and phenylketonuria proteins

Rare diseases, defined by their low prevalence, present significant challenges, including delayed detection, expensive treatments, and limited research. This study delves into the genetic basis of two noteworthy rare diseases in Saudi Arabia: Phenylketonuria (PKU) and Spinal Muscular Atrophy (SMA). PKU, resulting from mutations in the phenylalanine hydroxylase (PAH) gene, exhibits geographical variability and impacts intellectual abilities. SMA, characterized by motor neuron loss, is linked to mutations in the survival of motor neuron 1 (SMN1) gene. Recognizing the importance of unveiling signature genomics in rare diseases, we conducted a quantitative study on PAH and SMN1 proteins of multiple organisms by employing various quantitative techniques to assess genetic variations. The derived signature-genomics contributes to a deeper understanding of these critical genes, paving the way for enhanced diagnostics for disorders associated with PAH and SMN1.

Liquid-Liquid Phase Separation-Mediated Photocatalytic Subcellular Hybrid System for Highly Efficient Hydrogen Production

Plant chloroplasts have a highly compartmentalized interior, essential for executing photocatalytic functions. However, the construction of a photocatalytic reaction compartment similar to chloroplasts in inorganic-biological hybrid systems (IBS) has not been reported. Drawing inspiration from the compartmentalized chloroplast and the phenomenon of liquid-liquid phase separation, herein, a new strategy is first developed for constructing a photocatalytic subcellular hybrid system through liquid-liquid phase separation technology in living cells. Photosensitizers and in vivo expressed hydrogenases are designed to coassemble within the cell to create subcellular compartments for synergetic photocatalysis. This compartmentalization facilitates efficient electron transfer and light energy utilization, resulting in highly effective H2 production. The subcellular compartments hybrid system (HM/IBSCS) exhibits a nearly 87-fold increase in H2 production compared to the bare bacteria/hybrid system. Furthermore, the intracellular compartments of the photocatalytic reactor enhance the system's stability obviously, with the bacteria maintaining approximately 81% of their H2 production activity even after undergoing five cycles of photocatalytic hydrogen production. The research brings forward visionary prospects for the field of semi-artificial photosynthesis, offering new possibilities for advancements in areas such as renewable energy, biomanufacturing, and genetic engineering.

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

Protein family annotation for the Unified Human Gastrointestinal Proteome by DPCfam clustering

Technological advances in massively parallel sequencing have led to an exponential growth in the number of known protein sequences. Much of this growth originates from metagenomic projects producing new sequences from environmental and clinical samples. The Unified Human Gastrointestinal Proteome (UHGP) catalogue is one of the most relevant metagenomic datasets with applications ranging from medicine to biology. However, the low levels of sequence annotation may impair its usability. This work aims to produce a family classification of UHGP sequences to facilitate downstream structural and functional annotation. This is achieved through the release of the DPCfam-UHGP50 dataset containing 10,778 putative protein families generated using DPCfam clustering, an unsupervised pipeline grouping sequences into single or multi-domain architectures. DPCfam-UHGP50 considerably improves family coverage at protein and residue levels compared to the manually curated repository Pfam. In the hope that DPCfam-UHGP50 will foster future discoveries in the field of metagenomics of the human gut, we release a FAIR-compliant database of our results that is easily accessible via a searchable web server and Zenodo repository.

C-TERMINAL DOMAIN PHOSPHATASE-LIKE 3 contributes to GA-mediated growth and flowering by interaction with DELLA proteins

Gibberellic acid (GA) plays a central role in many plant developmental processes and is crucial for crop improvement. DELLA proteins, the core suppressors in the GA signaling pathway, are degraded by GA via the 26S proteasomal pathway to release the GA response. However, little is known about the phosphorylation-mediated regulation of DELLA proteins. In this study, we combined GA response assays with protein-protein interaction analysis to infer the connection between Arabidopsis thaliana DELLAs and the C-TERMINAL DOMAIN PHOSPHATASE-LIKE 3 (CPL3), a phosphatase involved in the dephosphorylation of RNA polymerase II. We show that CPL3 directly interacts with DELLA proteins and promotes DELLA protein stability by inhibiting its degradation by the 26S proteasome. Consequently, CPL3 negatively modulates multiple GA-mediated processes of plant development, including hypocotyl elongation, flowering time, and anthocyanin accumulation. Taken together, our findings demonstrate that CPL3 serves as a novel regulator that could improve DELLA stability and thereby participate in GA signaling transduction.

Formation of Amyloid-Like Conformational States of β-Structured Membrane Proteins on the Example of OMPF Porin from the Yersinia pseudotuberculosis Outer Membrane

The work presents results of the in vitro and in silico study of formation of amyloid-like structures under harsh denaturing conditions by non-specific OmpF porin of Yersinia pseudotuberculosis (YpOmpF), a membrane protein with β-barrel conformation. It has been shown that in order to obtain amyloid-like porin aggregates, preliminary destabilization of its structure in a buffer solution with acidic pH at elevated temperature followed by long-term incubation at room temperature is necessary. After heating at 95°C in a solution with pH 4.5, significant conformational rearrangements are observed in the porin molecule at the level of tertiary and secondary structure of the protein, which are accompanied by the increase in the content of total β-structure and sharp decrease in the value of characteristic viscosity of the protein solution. Subsequent long-term exposure of the resulting unstable intermediate YpOmpF at room temperature leads to formation of porin aggregates of various shapes and sizes that bind thioflavin T, a specific fluorescent dye for the detection of amyloid-like protein structures. Compared to the initial protein, early intermediates of the amyloidogenic porin pathway, oligomers, have been shown to have increased toxicity to the Neuro-2aCCL-131™ mouse neuroblastoma cells. The results of computer modeling and analysis of the changes in intrinsic fluorescence during protein aggregation suggest that during formation of amyloid-like aggregates, changes in the structure of YpOmpF affect not only the areas with an internally disordered structure corresponding to the external loops of the porin, but also main framework of the molecule, which has a rigid spatial structure inherent to β-barrel.

Functional conservation of GENOMES UNCOUPLED1 in plastid-to-nucleus retrograde signaling in tomato

Retrograde signaling between plastids and the nucleus is vital for chloroplast biogenesis and environmental responses. GENOMES UNCOUPLED1 (GUN1) was proposed to be a central integrator of multiple retrograde signaling pathways in the model plant Arabidopsis thaliana (Arabidopsis). However, the function of GUN1 orthologs in other plant species has not been well studied. Here, we found that many GUN1 orthologs from the Solanaceae family have a short N-terminus before the first pentatricopeptide repeat (PPR) motif which is predicted as intrinsically disordered regions (IDRs). Functional analyses of tomato (Solanum lycopersicum L.) GUN1 (SlGUN1), which does not contain N-terminal IDRs, show that it can complement the GUN phenotype of the Arabidopsis gun1 mutant (Atgun1). However, in contrast to the AtGUN1 protein, which does contain the N-terminal IDRs, the SlGUN1 protein is highly accumulated even after chloroplast biogenesis is completed, suggesting that the N-terminal IDRs may determine the stability of the GUN1 protein. Furthermore, we generated tomato Slgun1 genome-edited mutants via the CRISPR-Cas9 system. The Slgun1 mutants exhibited a typical GUN phenotype under lincomycin (Lin) or norflurazon (NF) treatment. Moreover, Slgun1 mutants are hypersensitive to low concentrations of Lin or NF. Taken together, our results suggest that, although lacking the N-terminal IDRs, SlGUN1 plays conserved roles in plastid retrograde signaling in tomato plants.

Exploring the functionality and conservation of Alba proteins in Trypanosoma cruzi: A focus on biological diversity and RNA binding ability

Trypanosoma cruzi is the causative agent of Chagas disease, as well as a trypanosomatid parasite with a complex biological cycle that requires precise mechanisms for regulating gene expression. In Trypanosomatidae, gene regulation occurs mainly at the mRNA level through the recognition of cis elements by RNA-binding proteins (RBPs). Alba family members are ubiquitous DNA/RNA-binding proteins with representatives in trypanosomatid parasites functionally related to gene expression regulation. Although T. cruzi possesses two groups of Alba proteins (Alba1/2 and Alba30/40), their functional role remains poorly understood. Thus, herein, a characterization of T. cruzi Alba (TcAlba) proteins was undertaken. Physicochemical, structural, and phylogenetic analysis of TcAlba showed features compatible with RBPs, such as hydrophilicity, RBP domains/motifs, and evolutionary conservation of the Alba-domain, mainly regarding other trypanosomatid Alba. However, in silico RNA interaction analysis of T. cruzi Alba proteins showed that TcAlba30/40 proteins, but not TcAlba1/2, would directly interact with the assayed RNA molecules, suggesting that these two groups of TcAlba proteins have different targets. Given the marked differences existing between both T. cruzi Alba groups (TcAlba1/2 and TcAlba30/40), regarding sequence divergence, RNA binding potential, and life-cycle expression patterns, we suggest that they would be involved in different biological processes.

Disruption of PABPN1 phase separation by SNRPD2 drives colorectal cancer cell proliferation and migration through promoting alternative polyadenylation of CTNNBIP1

Generally shortened 3' UTR due to alternative polyadenylation (APA) is widely observed in cancer, but its regulation mechanisms for cancer are not well characterized. Here, with profiling of APA in colorectal cancer tissues and poly(A) signal editing, we firstly identified that the shortened 3' UTR of CTNNIBP1 in colorectal cancer promotes cell proliferation and migration. We found that liquid-liquid phase separation (LLPS) of PABPN1 is reduced albeit with higher expression in cancer, and the reduction of LLPS leads to the shortened 3' UTR of CTNNBIP1 and promotes cell proliferation and migration. Notably, the splicing factor SNRPD2 upregulated in colorectal cancer, can interact with glutamic-proline (EP) domain of PABPN1, and then disrupt LLPS of PABPN1, which attenuates the repression effect of PABPN1 on the proximal poly(A) sites. Our results firstly reveal a new regulation mechanism of APA by disruption of LLPS of PABPN1, suggesting that regulation of APA by interfering LLPS of 3' end processing factor may have the potential as a new way for the treatment of cancer.

Spa2 remodels ADP-actin via molecular condensation under glucose starvation

Actin nucleotide-dependent actin remodeling is essential to orchestrate signal transduction and cell adaptation. Rapid energy starvation requires accurate and timely reorganization of the actin network. Despite distinct treadmilling mechanisms of ADP- and ATP-actin filaments, their filament structures are nearly identical. How other actin-binding proteins regulate ADP-actin filament assembly is unclear. Here, we show that Spa2 which is the polarisome scaffold protein specifically remodels ADP-actin upon energy starvation in budding yeast. Spa2 triggers ADP-actin monomer nucleation rapidly through a dimeric core of Spa2 (aa 281-535). Concurrently, the intrinsically disordered region (IDR, aa 1-281) guides Spa2 undergoing phase separation and wetting on the surface of ADP-G-actin-derived F-actin and bundles the filaments. Both ADP-actin-specific nucleation and bundling activities of Spa2 are actin D-loop dependent. The IDR and nucleation core of Spa2 are evolutionarily conserved by coexistence in the fungus kingdom, suggesting a universal adaptation mechanism in the fungal kingdom in response to glucose starvation, regulating ADP-G-actin and ADP-F-actin with high nucleotide homogeneity.

The FXR1 network acts as signaling scaffold for actomyosin remodeling

It is currently not known whether mRNAs fulfill structural roles in the cytoplasm. Here, we report the FXR1 network, an mRNA-protein (mRNP) network present throughout the cytoplasm, formed by FXR1-mediated packaging of exceptionally long mRNAs. These mRNAs serve as underlying condensate scaffold and concentrate FXR1 molecules. The FXR1 network contains multiple protein binding sites and functions as a signaling scaffold for interacting proteins. We show that it is necessary for RhoA signaling-induced actomyosin reorganization to provide spatial proximity between kinases and their substrates. Point mutations in FXR1, found in its homolog FMR1, where they cause Fragile X syndrome, disrupt the network. FXR1 network disruption prevents actomyosin remodeling-an essential and ubiquitous process for the regulation of cell shape, migration, and synaptic function. These findings uncover a structural role for cytoplasmic mRNA and show how the FXR1 RNA-binding protein as part of the FXR1 network acts as organizer of signaling reactions.

Identification of the RSX interactome in a marsupial shows functional coherence with the Xist interactome during X inactivation

The marsupial specific RSX lncRNA is the functional analogue of the eutherian specific XIST, which coordinates X chromosome inactivation. We characterized the RSX interactome in a marsupial representative (the opossum Monodelphis domestica), identifying 135 proteins, of which 54 had orthologues in the XIST interactome. Both interactomes were enriched for biological pathways related to RNA processing, regulation of translation, and epigenetic transcriptional silencing. This represents a remarkable example showcasing the functional coherence of independently evolved lncRNAs in distantly related mammalian lineages.

Using structure prediction of negative sense RNA virus nucleoproteins to assess evolutionary relationships

Negative sense RNA viruses (NSV) include some of the most detrimental human pathogens, including the influenza, Ebola and measles viruses. NSV genomes consist of one or multiple single-stranded RNA molecules that are encapsidated into one or more ribonucleoprotein (RNP) complexes. These RNPs consist of viral RNA, a viral RNA polymerase, and many copies of the viral nucleoprotein (NP). Current evolutionary relationships within the NSV phylum are based on alignment of conserved RNA-directed RNA polymerase (RdRp) domain amino acid sequences. However, the RdRp domain-based phylogeny does not address whether NP, the other core protein in the NSV genome, evolved along the same trajectory or whether several RdRp-NP pairs evolved through convergent evolution in the segmented and non-segmented NSV genomes architectures. Addressing how NP and the RdRp domain evolved may help us better understand NSV diversity. Since NP sequences are too short to infer robust phylogenetic relationships, we here used experimentally-obtained and AlphaFold 2.0-predicted NP structures to probe whether evolutionary relationships can be estimated using NSV NP sequences. Following flexible structure alignments of modeled structures, we find that the structural homology of the NSV NPs reveals phylogenetic clusters that are consistent with RdRp-based clustering. In addition, we were able to assign viruses for which RdRp sequences are currently missing to phylogenetic clusters based on the available NP sequence. Both our RdRp-based and NP-based relationships deviate from the current NSV classification of the segmented Naedrevirales, which cluster with the other segmented NSVs in our analysis. Overall, our results suggest that the NSV RdRp and NP genes largely evolved along similar trajectories and that even short pieces of genetic, protein-coding information can be used to infer evolutionary relationships, potentially making metagenomic analyses more valuable.

In silico evidence that substitution of glycine for valine (p.G8V) in a common variant of TMPRSS2 isoform 1 increases accessibility to an endocytic signal: Implication for SARS-cov-2 entry into host cells and susceptibility to COVID-19

The TMPRSS2 protease plays a key role in the entry of the SARS-CoV-2 into cells. The TMPRSS2 gene is highly polymorphic in humans, and some polymorphisms may affect the susceptibility to COVID-19 or disease severity. rs75603675 (c.23G > T) is a missense variant that causes the replacement of glycine with valine at position 8 (p.G8V) in the TMPRSS2 isoform 1. According to GnomAD v4.0.0 database, the allele frequency of the rs75603675 on a global scale is 38.10 %, and range from 0.92 % in East Asian to 40.77 % in non-Finnish European (NFE) population. We analyzed the occurrence of the rs75603675 in two cohorts of patients, the first with severe/critical COVID-19 enrolled in a French hospital (42 patients), and the second with predominantly asymptomatic/pauci-symptomatic/mild COVID-19 enrolled in an Italian hospital (69 patients). We found that the TMPRSS2-c.23T minor allele frequency was similar in the two cohorts, 46.43 % and 46.38 %, respectively, and higher than the frequency in the NFE population (40.77 %). Chi-square test provided significant results (p < 0.05) when the genotype data (TMPRSS2-c.23T/c.23T homozygotes + TMPRSS2-c.23G/c.23T heterozygotes vs. TMPRSS2-c.23G/c.23G homozygotes) of the two patient groups were pooled and compared to the expected data for the NFE population, suggesting a possible pathogenetic mechanism of the p.G8V substitution. We explored the possible effects of the p.G8V substitution and found that the N-terminal region of the TMPRSS2 isoform 1 contains a signal for clathrin/AP-2-dependent endocytosis. In silico analysis predicted that the p.G8V substitution may increase the accessibility to the endocytic signal, which could help SARS-CoV-2 enter cells.

AlphaFold2 modeling and molecular dynamics simulations of an intrinsically disordered protein

We use AlphaFold2 (AF2) to model the monomer and dimer structures of an intrinsically disordered protein (IDP), Nvjp-1, assisted by molecular dynamics (MD) simulations. We observe relatively rigid dimeric structures of Nvjp-1 when compared with the monomer structures. We suggest that protein conformations from multiple AF2 models and those from MD trajectories exhibit a coherent trend: the conformations of an IDP are deviated from each other and the conformations of a well-folded protein are consistent with each other. We use a residue-residue interaction network (RIN) derived from the contact map which show that the residue-residue interactions in Nvjp-1 are mainly transient; however, those in a well-folded protein are mainly persistent. Despite the variation in 3D shapes, we show that the AF2 models of both disordered and ordered proteins exhibit highly consistent profiles of the pLDDT (predicted local distance difference test) scores. These results indicate a potential protocol to justify the IDPs based on multiple AF2 models and MD simulations.

A phase-separated protein hub modulates resistance to Fusarium head blight in wheat

Fusarium head blight (FHB) is a devastating wheat disease. Fhb1, the most widely applied genetic locus for FHB resistance, is conferred by TaHRC of an unknown mode of action. Here, we show that TaHRC alleles distinctly drive liquid-liquid phase separation (LLPS) within a proteinaceous complex, determining FHB susceptibility or resistance. TaHRC-S (susceptible) exhibits stronger LLPS ability than TaHRC-R (resistant), and this distinction is further intensified by fungal mycotoxin deoxynivalenol, leading to opposing FHB symptoms. TaHRC recruits a protein class with intrinsic LLPS potentials, referred to as an "HRC-containing hub." TaHRC-S drives condensation of hub components, while TaHRC-R comparatively suppresses hub condensate formation. The function of TaSR45a splicing factor, a hub member, depends on TaHRC-driven condensate state, which in turn differentially directs alternative splicing, switching between susceptibility and resistance to wheat FHB. These findings reveal a mechanism for FHB spread within a spike and shed light on the roles of complex condensates in controlling plant disease.

Protein G-quadruplex interactions and their effects on phase transitions and protein aggregation

The SERF family of proteins were originally discovered for their ability to accelerate amyloid formation. Znf706 is an uncharacterized protein whose N-terminus is homologous to SERF proteins. We show here that human Znf706 can promote protein aggregation and amyloid formation. Unexpectedly, Znf706 specifically interacts with stable, non-canonical nucleic acid structures known as G-quadruplexes. G-quadruplexes can affect gene regulation and suppress protein aggregation; however, it is unknown if and how these two activities are linked. We find Znf706 binds preferentially to parallel G-quadruplexes with low micromolar affinity, primarily using its N-terminus, and upon interaction, its dynamics are constrained. G-quadruplex binding suppresses Znf706's ability to promote protein aggregation. Znf706 in conjunction with G-quadruplexes therefore may play a role in regulating protein folding. RNAseq analysis shows that Znf706 depletion specifically impacts the mRNA abundance of genes that are predicted to contain high G-quadruplex density. Our studies give insight into how proteins and G-quadruplexes interact, and how these interactions affect both partners and lead to the modulation of protein aggregation and cellular mRNA levels. These observations suggest that the SERF family of proteins, in conjunction with G-quadruplexes, may have a broader role in regulating protein folding and gene expression than previously appreciated.

Leveraging machine learning models for peptide-protein interaction prediction

Peptides play a pivotal role in a wide range of biological activities through participating in up to 40% protein-protein interactions in cellular processes. They also demonstrate remarkable specificity and efficacy, making them promising candidates for drug development. However, predicting peptide-protein complexes by traditional computational approaches, such as docking and molecular dynamics simulations, still remains a challenge due to high computational cost, flexible nature of peptides, and limited structural information of peptide-protein complexes. In recent years, the surge of available biological data has given rise to the development of an increasing number of machine learning models for predicting peptide-protein interactions. These models offer efficient solutions to address the challenges associated with traditional computational approaches. Furthermore, they offer enhanced accuracy, robustness, and interpretability in their predictive outcomes. This review presents a comprehensive overview of machine learning and deep learning models that have emerged in recent years for the prediction of peptide-protein interactions.

Phase separation of S-RNase promotes self-incompatibility in Petunia hybrida

Self-incompatibility (SI) is an intraspecific reproductive barrier widely present in angiosperms. The SI system with the broadest occurrence in angiosperms is based on an S-RNase linked to a cluster of multiple S-locus F-box (SLF) genes found in the Solanaceae, Plantaginaceae, Rosaceae, and Rutaceae. Recent studies reveal that non-self S-RNase is degraded by the Skip Cullin F-box (SCF)SLF-mediated ubiquitin-proteasome system in a collaborative manner in Petunia, but how self-RNase functions largely remains mysterious. Here, we show that S-RNases form S-RNase condensates (SRCs) in the self-pollen tube cytoplasm through phase separation and the disruption of SRC formation breaks SI in self-incompatible Petunia hybrida. We further find that the pistil SI factors of a small asparagine-rich protein HT-B and thioredoxin h together with a reduced state of the pollen tube all promote the expansion of SRCs, which then sequester several actin-binding proteins, including the actin polymerization factor PhABRACL, the actin polymerization activity of which is reduced by S-RNase in vitro. Meanwhile, we find that S-RNase variants lacking condensation ability fail to recruit PhABRACL and are unable to induce actin foci formation required for pollen tube growth inhibition. Taken together, our results demonstrate that phase separation of S-RNase promotes SI response in P. hybrida, revealing a new mode of S-RNase action.

Comprehensive Proteomics Analysis of Polyhydroxyalkanoate (PHA) Biology in Pseudomonas putida KT2440: The Outer Membrane Lipoprotein OprL is a Newly Identified Phasin

Pseudomonas putida KT2440 is an important bioplastic-producing industrial microorganism capable of synthesizing the polymeric carbon-rich storage material, polyhydroxyalkanoate (PHA). PHA is sequestered in discrete PHA granules, or carbonosomes, and accumulates under conditions of stress, for example, low levels of available nitrogen. The pha locus responsible for PHA metabolism encodes both anabolic and catabolic enzymes, a transcription factor, and carbonosome-localized proteins termed phasins. The functions of phasins are incompletely understood but genetic disruption of their function causes PHA-related phenotypes. To improve our understanding of these proteins, we investigated the PHA pathways of P.putida KT2440 using three types of experiments. First, we profiled cells grown in nitrogen-limited and nitrogen-excess media using global expression proteomics, identifying sets of proteins found to coordinately increase or decrease within clustered pathways. Next, we analyzed the protein composition of isolated carbonosomes, identifying two new putative components. We carried out physical interaction screens focused on PHA-related proteins, generating a protein-protein network comprising 434 connected proteins. Finally, we confirmed that the outer membrane protein OprL (the Pal component of the Pal-Tol system) localizes to the carbonosome and shows a PHA-related phenotype and therefore is a novel phasin. The combined datasets represent a valuable overview of the protein components of the PHA system in P.putida highlighting the complex nature of regulatory interactions responsive to nutrient stress.

Order wrapped in chaos: On the roles of intrinsically disordered proteins and RNAs in the arrangement of the mitochondrial enzymatic machines

The analysis of cryo-electron tomography images of human and rat mitochondria revealed that the mitochondrial matrix is at least as crowded as the cytosol. To mitigate the crowding effects, metabolite transport in the mitochondria primarily occurs through the intermembrane space, which is significantly less crowded. The scientific literature largely ignores how enzyme systems and metabolite transport are organized in the crowded environment of the mitochondrial matrix. Under crowded conditions, multivalent interactions carried out by disordered protein regions (IDRs), may become extremely important. We analyzed the human mitochondrial proteome to determine the presence and physiological significance of IDRs. Despite mitochondrial proteins being generally more ordered than cytosolic or overall proteome proteins, disordered regions plays a significant role in certain mitochondrial compartments and processes. Even in highly ordered enzyme systems, there are proteins with long IDRs. Some IDRs act as binding elements between highly ordered subunits, while the roles of others are not yet established. Mitochondrial systems, like their bacterial ancestors, rely less on IDRs and more on RNA for LLPS compartmentalization. More evolutionarily advanced subsystems that enable mitochondria-cell interactions contain more IDRs. The study highlights the crucial and often overlooked role played by IDRs and non-coding RNAs in mitochondrial organization.

DR-BERT: A protein language model to annotate disordered regions

Despite their lack of a rigid structure, intrinsically disordered regions (IDRs) in proteins play important roles in cellular functions, including mediating protein-protein interactions. Therefore, it is important to computationally annotate IDRs with high accuracy. In this study, we present Disordered Region prediction using Bidirectional Encoder Representations from Transformers (DR-BERT), a compact protein language model. Unlike most popular tools, DR-BERT is pretrained on unannotated proteins and trained to predict IDRs without relying on explicit evolutionary or biophysical data. Despite this, DR-BERT demonstrates significant improvement over existing methods on the Critical Assessment of protein Intrinsic Disorder (CAID) evaluation dataset and outperforms competitors on two out of four test cases in the CAID 2 dataset, while maintaining competitiveness in the others. This performance is due to the information learned during pretraining and DR-BERT's ability to use contextual information.

Reexamining the diverse functions of arginine in biochemistry

Arginine in a free-state and as part of peptides and proteins shows distinct tendency to form clusters. In free-form, it has been found useful in cryoprotection, as a drug excipient for both solid and liquid formulations, as an aggregation suppressor, and an eluent in protein chromatography. In many cases, the mechanisms by which arginine acts in all these applications is either debatable or at least continues to attract interest. It is quite possible that arginine clusters may be involved in many such applications. Furthermore, it is possible that such clusters are likely to behave as intrinsically disordered polypeptides. These considerations may help in understanding the roles of arginine in diverse applications and may even lead to better strategies for using arginine in different situations.