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

1H, 13C, and 15N NMR chemical shift assignment of the complex formed by the first EPEC EspF repeat and N-WASP GTPase binding domain

LEE-encoded effector EspF (EspF) is an effector protein part of enteropathogenic Escherichia coli's (EPEC's) arsenal for intestinal infection. This intrinsically disordered protein contains three highly conserved repeats which together compose over half of the protein's complete amino acid sequence. EPEC uses EspF to hijack host proteins in order to promote infection. In the attack EspF is translocated, together with other effector proteins, to host cell via type III secretion system. Inside host EspF stimulates actin polymerization by interacting with Neural Wiskott-Aldrich syndrome protein (N-WASP), a regulator in actin polymerization machinery. It is presumed that EspF acts by disrupting the autoinhibitory state of N-WASP GTPase binding domain. In this NMR spectroscopy study, we report the 1H, 13C, and 15N resonance assignments for the complex formed by the first 47-residue repeat of EspF and N-WASP GTPase binding domain. These near-complete resonance assignments provide the basis for further studies which aim to characterize structure, interactions, and dynamics between these two proteins in solution.

The SARS-CoV-2 nucleocapsid protein is dynamic, disordered, and phase separates with RNA

The SARS-CoV-2 nucleocapsid (N) protein is an abundant RNA-binding protein critical for viral genome packaging, yet the molecular details that underlie this process are poorly understood. Here we combine single-molecule spectroscopy with all-atom simulations to uncover the molecular details that contribute to N protein function. N protein contains three dynamic disordered regions that house putative transiently-helical binding motifs. The two folded domains interact minimally such that full-length N protein is a flexible and multivalent RNA-binding protein. N protein also undergoes liquid-liquid phase separation when mixed with RNA, and polymer theory predicts that the same multivalent interactions that drive phase separation also engender RNA compaction. We offer a simple symmetry-breaking model that provides a plausible route through which single-genome condensation preferentially occurs over phase separation, suggesting that phase separation offers a convenient macroscopic readout of a key nanoscopic interaction.

The Interaction Mechanism of Intrinsically Disordered PP2A Inhibitor Proteins ARPP-16 and ARPP-19 With PP2A

Protein phosphatase 2A (PP2A) activity is critical for maintaining normal physiological cellular functions. PP2A is inhibited by endogenous inhibitor proteins in several pathological conditions including cancer. A PP2A inhibitor protein, ARPP-19, has recently been connected to several human cancer types. Accordingly, the knowledge about ARPP-19—PP2A inhibition mechanism is crucial for the understanding the disease development and the therapeutic targeting of ARPP-19—PP2A. Here, we show the first structural characterization of ARPP-19, and its splice variant ARPP-16 using NMR spectroscopy, and SAXS. The results reveal that both ARPP proteins are intrinsically disordered but contain transient secondary structure elements. The interaction mechanism of ARPP-16/19 with PP2A was investigated using microscale thermophoresis and NMR spectroscopy. Our results suggest that ARPP—PP2A A-subunit interaction is mediated by linear motif and has modest affinity whereas, the interaction of ARPPs with B56-subunit is weak and transient. Like many IDPs, ARPPs are promiscuous binders that transiently interact with PP2A A- and B56 subunits using multiple interaction motifs. In summary, our results provide a good starting point for future studies and development of therapeutics that block ARPP-PP2A interactions.

Improving the clinical interpretation of missense variants in X linked genes using structural analysis

BACKGROUND

Improving the clinical interpretation of missense variants can increase the diagnostic yield of genomic testing and lead to personalised management strategies. Currently, due to the imprecision of bioinformatic tools that aim to predict variant pathogenicity, their role in clinical guidelines remains limited. There is a clear need for more accurate prediction algorithms and this study aims to improve performance by harnessing structural biology insights. The focus of this work is missense variants in a subset of genes associated with X linked disorders.

METHODS

We have developed a protein-specific variant interpreter (ProSper) that combines genetic and protein structural data. This algorithm predicts missense variant pathogenicity by applying machine learning approaches to the sequence and structural characteristics of variants.

RESULTS

ProSper outperformed seven previously described tools, including meta-predictors, in correctly evaluating whether or not variants are pathogenic; this was the case for 11 of the 21 genes associated with X linked disorders that met the inclusion criteria for this study. We also determined gene-specific pathogenicity thresholds that improved the performance of VEST4, REVEL and ClinPred, the three best-performing tools out of the seven that were evaluated; this was the case in 11, 11 and 12 different genes, respectively.

CONCLUSION

ProSper can form the basis of a molecule-specific prediction tool that can be implemented into diagnostic strategies. It can allow the accurate prioritisation of missense variants associated with X linked disorders, aiding precise and timely diagnosis. In addition, we demonstrate that gene-specific pathogenicity thresholds for a range of missense prioritisation tools can lead to an increase in prediction accuracy.

Co-Transcriptional RNA Processing in Plants: Exploring from the Perspective of Polyadenylation

Most protein-coding genes in eukaryotes possess at least two poly(A) sites, and alternative polyadenylation is considered a contributing factor to transcriptomic and proteomic diversity. Following transcription, a nascent RNA usually undergoes capping, splicing, cleavage, and polyadenylation, resulting in a mature messenger RNA (mRNA); however, increasing evidence suggests that transcription and RNA processing are coupled. Plants, which must produce rapid responses to environmental changes because of their limited mobility, exhibit such coupling. In this review, we summarize recent advances in our understanding of the coupling of transcription with RNA processing in plants, and we describe the possible spatial environment and important proteins involved. Moreover, we describe how liquid–liquid phase separation, mediated by the C-terminal domain of RNA polymerase II and RNA processing factors with intrinsically disordered regions, enables efficient co-transcriptional mRNA processing in plants.

A new type of flexible CP12 protein in the marine diatom Thalassiosira pseudonana

Background

CP12 is a small chloroplast protein that is widespread in various photosynthetic organisms and is an actor of the redox signaling pathway involved in the regulation of the Calvin Benson Bassham (CBB) cycle. The gene encoding this protein is conserved in many diatoms, but the protein has been overlooked in these organisms, despite their ecological importance and their complex and still enigmatic evolutionary background.

Methods

A combination of biochemical, bioinformatics and biophysical methods including electrospray ionization-mass spectrometry, circular dichroism, nuclear magnetic resonance spectroscopy and small X ray scattering, was used to characterize a diatom CP12.

Results

Here, we demonstrate that CP12 is expressed in the marine diatom Thalassiosira pseudonana constitutively in dark-treated and in continuous light-treated cells as well as in all growth phases. This CP12 similarly to its homologues in other species has some features of intrinsically disorder protein family: it behaves abnormally under gel electrophoresis and size exclusion chromatography, has a high net charge and a bias amino acid composition. By contrast, unlike other known CP12 proteins that are monomers, this protein is a dimer as suggested by native electrospray ionization-mass spectrometry and small angle X-ray scattering. In addition, small angle X-ray scattering revealed that this CP12 is an elongated cylinder with kinks. Circular dichroism spectra indicated that CP12 has a high content of α-helices, and nuclear magnetic resonance spectroscopy suggested that these helices are unstable and dynamic within a millisecond timescale. Together with in silico predictions, these results suggest that T. pseudonana CP12 has both coiled coil and disordered regions.

Conclusions

These findings bring new insights into the large family of dynamic proteins containing disordered regions, thus increasing the diversity of known CP12 proteins. As it is a protein that is more abundant in many stresses, it is not devoted to one metabolism and in particular, it is not specific to carbon metabolism. This raises questions about the role of this protein in addition to the well-established regulation of the CBB cycle.

Choregraphy of metabolism by CP12 proteins in Viridiplantae and Heterokonta.

While the monomeric CP12 in Viridiplantae is involved in carbon assimilation, regulating phosphoribulokinase (PRK) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) through the formation of a ternary complex, in Heterokonta studied so far, the dimeric CP12 is associated with Ferredoxin-NADP reductase (FNR) and GAPDH. The Viridiplantae CP12 can bind metal ions and can be a chaperone, the Heterokonta CP12 is more abundant in all stresses (C, N, Si, P limited conditions) and is not specific to a metabolism.

Protein phase separation and its role in chromatin organization and diseases

In the physical sciences, solid, liquid, and gas are the most familiar phase states, whose essence is their existence reflecting the different spatial distribution of molecular components. The biological molecules in the living cell also have differences in spatial distribution. The molecules organized in the form of membrane-bound organelles are well recognized. However, the biomolecules organized in membraneless compartments called biomolecular condensates remain elusive. The liquid-liquid phase separation (LLPS), as a new emerging scientific breakthrough, describes the biomolecules assembled in special distribution and appeared as membraneless condensates in the form of a new "phase" compared with the surrounding liquid milieu. LLPS provides an important theoretical basis for explaining the composition of biological molecules and related biological reactions. Mounting evidence has emerged recently that phase-separated condensates participate in various biological activities. This article reviews the occurrence of LLPS and underlying regulatory mechanisms for understanding how multivalent molecules drive phase transitions to form the biomolecular condensates. And, it also summarizes recent major progress in elucidating the roles of LLPS in chromatin organization and provides clues for the development of new innovative therapeutic strategies for related diseases.

Reduced Translational Efficiency of Eukaryotic Genes after Duplication Events

Control of gene expression has been found to be predominantly determined at the level of protein translation. However, to date, reduced expression from duplicated genes in eukaryotes for dosage maintenance has only been linked to transcriptional control involving epigenetic mechanisms. Here, we hypothesize that dosage maintenance following gene duplication also involves regulation at the protein level. To test this hypothesis, we compared transcriptome and proteome data of yeast models, Saccharomyces cerevisiae and Schizosaccharomyces pombe, and worm models, Caenorhabditis elegans and Caenorhabditis briggsae, to investigate lineage-specifically duplicated genes. Duplicated genes in both eukaryotic models exhibited a reduced protein-to-mRNA abundance ratio. Moreover, dosage sensitive genes, represented by genes encoding protein complex subunits, reduced their protein-to-mRNA abundance ratios more significantly than the other genes after duplication events. An analysis of ribosome profiling (Ribo-Seq) data further showed that reduced translational efficiency was more prominent for dosage sensitive genes than for the other genes. Meanwhile, no difference in protein degradation rate was associated with duplication events. Translationally repressed duplicated genes were also more likely to be inhibited at the level of transcription. Taken together, these results suggest that translation-mediated dosage control is partially contributed by natural selection and it enhances transcriptional control in maintaining gene dosage after gene duplication events during eukaryotic genome evolution.

Unstructural Biology of TRP Ion Channels: The Role of Intrinsically Disordered Regions in Channel Function and Regulation

The first genuine high-resolution single particle cryo-electron microscopy structure of a membrane protein determined was a transient receptor potential (TRP) ion channel, TRPV1, in 2013. This methodical breakthrough opened up a whole new world for structural biology and ion channel aficionados alike. TRP channels capture the imagination due to the sheer endless number of tasks they carry out in all aspects of animal physiology. To date, structures of at least one representative member of each of the six mammalian TRP channel subfamilies as well as of a few non-mammalian families have been determined. These structures were instrumental for a better understanding of TRP channel function and regulation. However, all of the TRP channel structures solved so far are incomplete since they miss important information about highly flexible regions found mostly in the channel N- and C-termini. These intrinsically disordered regions (IDRs) can represent between a quarter to almost half of the entire protein sequence and act as important recruitment hubs for lipids and regulatory proteins. Here, we analyze the currently available TRP channel structures with regard to the extent of these "missing" regions and compare these findings to disorder predictions. We discuss select examples of intra- and intermolecular crosstalk of TRP channel IDRs with proteins and lipids as well as the effect of splicing and post-translational modifications, to illuminate their importance for channel function and to complement the prevalently discussed structural biology of these versatile and fascinating proteins with their equally relevant 'unstructural' biology.

The Fusion Gene Landscape in Taiwanese Patients with Non-Small Cell Lung Cancer

Simple Summary

Human cancer genomes show a variety of alterations, such as single base changes, deletions, insertions, copy number changes, and gene fusions. Analyzing fusion gene transcripts may yield a novel and effective approach for selecting cancer treatments. However, few comprehensive analyses of gene fusions in non-small cell lung cancer (NSCLC) patients have been performed. Here, we characterized the fusion gene landscape of NSCLC in a case study of Taiwanese lung cancer patients. We concluded that some fusion genes likely play driver roles in carcinogenesis, while others act as passengers. We demonstrated that by using RNA-sequencing to detect gene fusion events, putative therapeutic drug targets could be identified, potentially leading to more precise therapies for NSCLC.

Abstract

Background: Analyzing fusion gene transcripts may yield an effective approach for selecting cancer treatments. However, few comprehensive analyses of fusions in non-small cell lung cancer (NSCLC) patients have been performed. Methods: We enrolled 54 patients with NSCLC, and performed RNA-sequencing (RNA-Seq). STAR (Spliced Transcripts Alignment to a Reference)-Fusion was used to identify fusions. Results: Of the 218 fusions discovered, 24 had been reported and the rest were novel. Three fusions had the highest occurrence rates. After integrating our gene expression and fusion data, we found that samples harboring fusions containing ASXL1, CACNA1A, EEF1A1, and RET also exhibited increased expression of these genes. We then searched for mutations and fusions in cancer driver genes in each sample and found that nine patients carried both mutations and fusions in cancer driver genes. Furthermore, we found a trend for mutual exclusivity between gene fusions and mutations in the same gene, with the exception of DMD, and we found that EGFR mutations are associated with the number of fusion genes. Finally, we identified kinase gene fusions, and potentially druggable fusions, which may play roles in lung cancer therapy. Conclusion: The clinical use of RNA-Seq for detecting driver fusion genes may play an important role in the treatment of lung cancer.

Caspase cleavage releases a nuclear protein fragment that stimulates phospholipid scrambling at the plasma membrane

Phospholipid scrambling in dying cells promotes phosphatidylserine exposure, a critical process for efferocytosis. We previously identified the Xkr family protein Xkr4 as a phospholipid-scrambling protein, but its activation mechanisms remain unknown. Here we show that Xkr4 is activated in two steps: dimer formation by caspase-mediated cleavage and structural change caused by activating factors. To identify the factors, we developed a new screening system, "revival screening," using a CRISPR sgRNA library. Applying this system, we identified the nuclear protein XRCC4 as the single candidate for the Xkr4 activator. Upon apoptotic stimuli, XRCC4, contained in the DNA repair complex, is cleaved by caspases, and its C-terminal fragment with an intrinsically disordered region is released into the cytoplasm. Protein interaction screening showed that the fragment interacts directly with the Xkr4 dimer to activate it. This study demonstrates that caspase-mediated cleavage releases a nuclear protein fragment for direct regulation of lipid dynamics on the plasma membrane.

Structure-function analysis of fission yeast cleavage and polyadenylation factor (CPF) subunit Ppn1 and its interactions with Dis2 and Swd22

Fission yeast Cleavage and Polyadenylation Factor (CPF), a 13-subunit complex, executes the cotranscriptional 3' processing of RNA polymerase II (Pol2) transcripts that precedes transcription termination. The three-subunit DPS sub-complex of CPF, consisting of a PP1-type phosphoprotein phosphatase Dis2, a WD-repeat protein Swd22, and a putative phosphatase regulatory factor Ppn1, associates with the CPF core to form the holo-CPF assembly. Here we probed the functional, physical, and genetic interactions of DPS by focusing on the Ppn1 subunit, which mediates association of DPS with the core. Transcriptional profiling by RNA-seq defined limited but highly concordant sets of protein-coding genes that were dysregulated in ppn1Δ, swd22Δ and dis2Δ cells, which included the DPSΔ down-regulated phosphate homeostasis genes pho1 and pho84 that are controlled by lncRNA-mediated transcriptional interference. Essential and inessential modules of the 710-aa Ppn1 protein were defined by testing the effects of Ppn1 truncations in multiple genetic backgrounds in which Ppn1 is required for growth. An N-terminal 172-aa disordered region was dispensable and its deletion alleviated hypomorphic phenotypes caused by deleting C-terminal aa 640-710. A TFIIS-like domain (aa 173-330) was not required for viability but was important for Ppn1 activity in phosphate homeostasis. Distinct sites within Ppn1 for binding to Dis2 (spanning Ppn1 aa 506 to 532) and Swd22 (from Ppn1 aa 533 to 578) were demarcated by yeast two-hybrid assays. Dis2 interaction-defective missense mutants of full-length Ppn1 (that retained Swd22 interaction) were employed to show that binding to Dis2 (or its paralog Sds21) was necessary for Ppn1 biological activity. Ppn1 function was severely compromised by missense mutations that selectively affected its binding to Swd22.

The Participation of the Intrinsically Disordered Regions of the bHLH-PAS Transcription Factors in Disease Development

The basic helix–loop–helix/Per-ARNT-SIM (bHLH-PAS) proteins are a family of transcription factors regulating expression of a wide range of genes involved in different functions, ranging from differentiation and development control by oxygen and toxins sensing to circadian clock setting. In addition to the well-preserved DNA-binding bHLH and PAS domains, bHLH-PAS proteins contain long intrinsically disordered C-terminal regions, responsible for regulation of their activity. Our aim was to analyze the potential connection between disordered regions of the bHLH-PAS transcription factors, post-transcriptional modifications and liquid-liquid phase separation, in the context of disease-associated missense mutations. Highly flexible disordered regions, enriched in short motives which are more ordered, are responsible for a wide spectrum of interactions with transcriptional co-regulators. Based on our in silico analysis and taking into account the fact that the functions of transcription factors can be modulated by posttranslational modifications and spontaneous phase separation, we assume that the locations of missense mutations inducing disease states are clearly related to sequences directly undergoing these processes or to sequences responsible for their regulation.

Phase Separation and Neurodegenerative Diseases: A Disturbance in the Force

Protein aggregation is the main hallmark of neurodegenerative diseases. Many proteins found in pathological inclusions are known to undergo liquid-liquid phase separation, a reversible process of molecular self-assembly. Emerging evidence supports the hypothesis that aberrant phase separation behavior may serve as a trigger of protein aggregation in neurodegeneration, and efforts to understand and control the underlying mechanisms are underway. Here, we review similarities and differences among four main proteins, α-synuclein, FUS, tau, and TDP-43, which are found aggregated in different diseases and were independently shown to phase separate. We discuss future directions in the field that will help shed light on the molecular mechanisms of aggregation and neurodegeneration.

Most non-canonical proteins uniquely populate the proteome or immunopeptidome

Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated as efficiently as canonical proteins, have more predicted disordered residues and lower stability, and critically generate MHC-I peptides 5-fold more efficiently per translation event. Translating 5' "untranslated" regions hinders downstream translation of genes involved in transcription, translation, and antiviral responses. Novel protein isoforms show strong enrichment for signaling pathways deregulated in cancer. Only a small fraction of cryptic proteins detected in the proteome contribute to the MHC-I immunopeptidome, demonstrating the high preferential access of cryptic defective ribosomal products to the class I pathway.

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

APOD: accurate sequence-based predictor of disordered flexible linkers

Motivation

Disordered flexible linkers (DFLs) are abundant and functionally important intrinsically disordered regions that connect protein domains and structural elements within domains and which facilitate disorder-based allosteric regulation. Although computational estimates suggest that thousands of proteins have DFLs, they were annotated experimentally in <200 proteins. This substantial annotation gap can be reduced with the help of accurate computational predictors. The sole predictor of DFLs, DFLpred, trade-off accuracy for shorter runtime by excluding relevant but computationally costly predictive inputs. Moreover, it relies on the local/window-based information while lacking to consider useful protein-level characteristics.

Results

We conceptualize, design and test APOD (Accurate Predictor Of DFLs), the first highly accurate predictor that utilizes both local- and protein-level inputs that quantify propensity for disorder, sequence composition, sequence conservation and selected putative structural properties. Consequently, APOD offers significantly more accurate predictions when compared with its faster predecessor, DFLpred, and several other alternative ways to predict DFLs. These improvements stem from the use of a more comprehensive set of inputs that cover the protein-level information and the application of a more sophisticated predictive model, a well-parametrized support vector machine. APOD achieves area under the curve = 0.82 (28% improvement over DFLpred) and Matthews correlation coefficient = 0.42 (180% increase over DFLpred) when tested on an independent/low-similarity test dataset. Consequently, APOD is a suitable choice for accurate and small-scale prediction of DFLs.

Availability and implementation

https://yanglab.nankai.edu.cn/APOD/.

The DBSAV Database: Predicting Deleteriousness of Single Amino Acid Variations in the Human Proteome

Deleterious single amino acid variation (SAV) is one of the leading causes of human diseases. Evaluating the functional impact of SAVs is crucial for diagnosis of genetic disorders. We previously developed a deep convolutional neural network predictor, DeepSAV, to evaluate the deleterious effects of SAVs on protein function based on various sequence, structural, and functional properties. DeepSAV scores of rare SAVs observed in the human population are aggregated into a gene-level score called GTS (Gene Tolerance of rare SAVs) that reflects a gene's tolerance to deleterious missense mutations and serves as a useful tool to study gene-disease associations. In this study, we aim to enhance the performance of DeepSAV by using expanded datasets of pathogenic and benign variants, more features, and neural network optimization. We found that multiple sequence alignments built from vertebrate-level orthologs yield better prediction results compared to those built from mammalian-level orthologs. For multiple sequence alignments built from BLAST searches, optimal performance was achieved with a sequence identify cutoff of 50% to remove distant homologs. The new version of DeepSAV exhibits the best performance among standalone predictors of deleterious effects of SAVs. We developed the DBSAV database (http://prodata.swmed.edu/DBSAV) that reports GTS scores of human genes and DeepSAV scores of SAVs in the human proteome, including pathogenic and benign SAVs, population-level SAVs, and all possible SAVs by single nucleotide variations. This database serves as a useful resource for research of human SAVs and their relationships with protein functions and human diseases.

Mutations of Intrinsically Disordered Protein Regions Can Drive Cancer but Lack Therapeutic Strategies

Many proteins contain intrinsically disordered regions (IDRs) which carry out important functions without relying on a single well-defined conformation. IDRs are increasingly recognized as critical elements of regulatory networks and have been also associated with cancer. However, it is unknown whether mutations targeting IDRs represent a distinct class of driver events associated with specific molecular and system-level properties, cancer types and treatment options. Here, we used an integrative computational approach to explore the direct role of intrinsically disordered protein regions driving cancer. We showed that around 20% of cancer drivers are primarily targeted through a disordered region. These IDRs can function in multiple ways which are distinct from the functional mechanisms of ordered drivers. Disordered drivers play a central role in context-dependent interaction networks and are enriched in specific biological processes such as transcription, gene expression regulation and protein degradation. Furthermore, their modulation represents an alternative mechanism for the emergence of all known cancer hallmarks. Importantly, in certain cancer patients, mutations of disordered drivers represent key driving events. However, treatment options for such patients are currently severely limited. The presented study highlights a largely overlooked class of cancer drivers associated with specific cancer types that need novel therapeutic options.

Prediction of protein-binding residues: dichotomy of sequence-based methods developed using structured complexes versus disordered proteins

MOTIVATION

There are over 30 sequence-based predictors of the protein-binding residues (PBRs). They use either structure-annotated or disorder-annotated training datasets, potentially creating a dichotomy where the structure-/disorder-specific models may not be able to cross-over to accurately predict the other type. Moreover, the structure-trained predictors were shown to substantially cross-predict PBRs among residues that interact with non-protein partners (nucleic acids and small ligands). We address these issues by performing first-of-its-kind comparative study of a representative collection of disorder- and structure-trained predictors using a comprehensive benchmark set with the structure- and disorder-derived annotations of PBRs (to analyze the cross-over) and the protein-, nucleic acid- and small ligand-binding proteins (to study the cross-predictions).

RESULTS

Three predictors provide accurate results: SCRIBER, ANCHOR and disoRDPbind. Some of the structure-trained methods make accurate predictions on the structure-annotated proteins. Similarly, the disorder-trained predictors predict well on the disorder-annotated proteins. However, the considered predictors generally fail to cross-over, with the exception of SCRIBER. Our study also reveals that virtually all methods substantially cross-predict PBRs, except for SCRIBER for the structure-annotated proteins and disoRDPbind for the disorder-annotated proteins. We formulate a novel hybrid predictor, hybridPBRpred, that combines results produced by disoRDPbind and SCRIBER to accurately predict disorder- and structure-annotated PBRs. HybridPBRpred generates accurate results that cross-over structure- and disorder-annotated proteins and produces relatively low amount of cross-predictions, offering an accurate alternative to predict PBRs.

AVAILABILITY AND IMPLEMENTATION

HybridPBRpred webserver, benchmark dataset and supplementary information are available at http://biomine.cs.vcu.edu/servers/hybridPBRpred/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Arabidopsis Abscisic Acid Repressor 1 is a susceptibility hub that interacts with multiple Pseudomonas syringae effectors

Pathogens secrete effector proteins into host cells to suppress host immunity and promote pathogen virulence, although many features at the molecular interface of host-pathogen interactions remain to be characterized. In a yeast two-hybrid assay, we found that the Pseudomonas syringae effector HopZ1a interacts with the Arabidopsis transcriptional regulator Abscisic Acid Repressor 1 (ABR1). Further analysis revealed that ABR1 interacts with multiple P. syringae effectors, suggesting that it may be targeted as a susceptibility hub. Indeed, loss-of-function abr1 mutants exhibit reduced susceptibility to a number of P. syringae strains. The ABR1 protein comprises a conserved APETALA2 (AP2) domain flanked by long regions of predicted structural disorder. We verified the DNA-binding activity of the AP2 domain and demonstrated that the disordered domains act redundantly to enhance DNA binding and to facilitate transcriptional activation by ABR1. Finally, we compared gene expression profiles from wild-type and abr1 plants following inoculation with P. syringae, which suggested that the reduced susceptibility of abr1 mutants is due to the loss of a virulence target rather than an enhanced immune response. These data highlight ABR1 as a functionally important component at the host-pathogen interface.

Cells recognize osmotic stress through liquid-liquid phase separation lubricated with poly(ADP-ribose)

Cells are under threat of osmotic perturbation; cell volume maintenance is critical in cerebral edema, inflammation and aging, in which prominent changes in intracellular or extracellular osmolality emerge. After osmotic stress-enforced cell swelling or shrinkage, the cells regulate intracellular osmolality to recover their volume. However, the mechanisms recognizing osmotic stress remain obscured. We previously clarified that apoptosis signal-regulating kinase 3 (ASK3) bidirectionally responds to osmotic stress and regulates cell volume recovery. Here, we show that macromolecular crowding induces liquid-demixing condensates of ASK3 under hyperosmotic stress, which transduce osmosensing signal into ASK3 inactivation. A genome-wide small interfering RNA (siRNA) screen identifies an ASK3 inactivation regulator, nicotinamide phosphoribosyltransferase (NAMPT), related to poly(ADP-ribose) signaling. Furthermore, we clarify that poly(ADP-ribose) keeps ASK3 condensates in the liquid phase and enables ASK3 to become inactivated under hyperosmotic stress. Our findings demonstrate that cells rationally incorporate physicochemical phase separation into their osmosensing systems.

IDPology of the living cell: intrinsic disorder in the subcellular compartments of the human cell

Intrinsic disorder can be found in all proteomes of all kingdoms of life and in viruses, being particularly prevalent in the eukaryotes. We conduct a comprehensive analysis of the intrinsic disorder in the human proteins while mapping them into 24 compartments of the human cell. In agreement with previous studies, we show that human proteins are significantly enriched in disorder relative to a generic protein set that represents the protein universe. In fact, the fraction of proteins with long disordered regions and the average protein-level disorder content in the human proteome are about 3 times higher than in the protein universe. Furthermore, levels of intrinsic disorder in the majority of human subcellular compartments significantly exceed the average disorder content in the protein universe. Relative to the overall amount of disorder in the human proteome, proteins localized in the nucleus and cytoskeleton have significantly increased amounts of disorder, measured by both high disorder content and presence of multiple long intrinsically disordered regions. We empirically demonstrate that, on average, human proteins are assigned to 2.3 subcellular compartments, with proteins localized to few subcellular compartments being more disordered than the proteins that are localized to many compartments. Functionally, the disordered proteins localized in the most disorder-enriched subcellular compartments are primarily responsible for interactions with nucleic acids and protein partners. This is the first-time disorder is comprehensively mapped into the human cell. Our observations add a missing piece to the puzzle of functional disorder and its organization inside the cell.

FLIPPER: Predicting and Characterizing Linear Interacting Peptides in the Protein Data Bank

A large fraction of peptides or protein regions are disordered in isolation and fold upon binding. These regions, also called MoRFs, SLiMs or LIPs, are often associated with signaling and regulation processes. However, despite their importance, only a limited number of examples are available in public databases and their automatic detection at the proteome level is problematic. Here we present FLIPPER, an automatic method for the detection of structurally linear sub-regions or peptides that interact with another chain in a protein complex. FLIPPER is a random forest classification that takes the protein structure as input and provides the propensity of each amino acid to be part of a LIP region. Models are built taking into consideration structural features such as intra- and inter-chain contacts, secondary structure, solvent accessibility in both bound and unbound state, structural linearity and chain length. FLIPPER is accurate when evaluated on non-redundant independent datasets, 99% precision and 99% sensitivity on PixelDB-25 and 87% precision and 88% sensitivity on DIBS-25. Finally, we used FLIPPER to process the entire Protein Data Bank and identified different classes of LIPs based on different binding modes and partner molecules. We provide a detailed description of these LIP categories and show that a large fraction of these regions are not detected by disorder predictors. All FLIPPER predictions are integrated in the MobiDB 4.0 database.

Fibrogranular materials function as organizers to ensure the fidelity of multiciliary assembly

Multicilia are delicate motile machineries, and how they are accurately assembled is poorly understood. Here, we show that fibrogranular materials (FGMs), large arrays of electron-dense granules specific to multiciliated cells, are essential for their ultrastructural fidelity. Pcm1 forms the granular units that further network into widespread FGMs, which are abundant in spherical FGM cores. FGM cores selectively concentrate multiple important centriole-related proteins as clients, including Cep131 that specifically decorates a foot region of ciliary central pair (CP) microtubules. FGMs also tightly contact deuterosome-procentriole complexes. Disruption of FGMs in mouse cells undergoing multiciliogenesis by Pcm1 RNAi markedly deregulates centriolar targeting of FGM clients, elongates CP-foot, and alters deuterosome size, number, and distribution. Although the multicilia are produced in correct numbers, they display abnormal ultrastructure and motility. Our results suggest that FGMs organize deuterosomes and centriole-related proteins to facilitate the faithful assembly of basal bodies and multiciliary axonemes.

Multifunctionality and intrinsic disorder of royal jelly proteome

Royal Jelly (RJ) is a gelatinous white-yellowish fluid, possessing a sour taste and a slight phenolic smell that is secreted by the hypopharyngeal and mandibular salivary glands of the nurse honeybees, and is used in nutrition of larvae and adult queens. Similar to other substances associated with the activities of honeybees, RJ not only contains nutritive components, such as carbohydrates, proteins, peptides, lipids, vitamins, and mineral salts, but also represents a natural ingredient with cosmetic and health-promoting properties. RJ is characterized by remarkable multifunctionality, possessing numerous biological activities. Although this multifunctionality of RJ can be considered as a consequence of its complex nature, many proteins and peptides in RJ are polyfunctional entities themselves. In this article, we show that RJ proteins contain different levels of intrinsic disorder, have sites of post-translational modifications, can be found in multiple isoforms, and many of them possess disorder-based binding sites, suggesting that the conformational ensembles of the RJ proteins might undergo change as a result of their interaction with specific binding partners. All these observations suggest that the multifunctionality of proteins and peptides from RJ is determined by their structural heterogeneity and polymorphism, and serve as an illustration of the protein structure-function continuum concept.

The PHLPP1 N-Terminal Extension Is a Mitotic Cdk1 Substrate and Controls an Interactome Switch

PH domain leucine-rich repeat protein phosphatase 1 (PHLPP1) is a tumor suppressor that directly dephosphorylates a wide array of substrates, most notably the prosurvival kinase Akt. However, little is known about the molecular mechanisms governing PHLPP1 itself. Here, we report that PHLPP1 is dynamically regulated in a cell cycle-dependent manner and deletion of PHLPP1 results in mitotic delays and increased rates of chromosomal segregation errors. We show that PHLPP1 is hyperphosphorylated during mitosis by Cdk1 in a functionally uncharacterized region known as the PHLPP1 N-terminal extension (NTE). A proximity-dependent biotin identification (BioID) interaction screen revealed that during mitosis, PHLPP1 dissociates from plasma membrane scaffolds, such as Scribble, by a mechanism that depends on its NTE and gains proximity to kinetochore and mitotic spindle proteins such as KNL1 and TPX2. Our data are consistent with a model in which phosphorylation of PHLPP1 during mitosis regulates binding to its mitotic partners and allows accurate progression through mitosis. The finding that PHLPP1 binds mitotic proteins in a cell cycle- and phosphorylation-dependent manner may have relevance to its tumor-suppressive function.

Secondary Structures of Proteins: A Comparison of Models and Experimental Results

Secondary structure predictions of proteins were compared to experimental results by wide-line ¹H NMR. IUPred2A was used to generate predictions of disordered protein or binding regions. Thymosin-β₄ and the stabilin-2 cytoplasmic domain were found to be mainly disordered, in agreement with the experimental results. α-Synuclein variants were predicted to be disordered, as in the experiments, but the A53T mutant showed less predicted disorder, in contrast with the wide-line ¹H NMR result. A disordered binding site was found for thymosin-β₄, whereas the stabilin-2 cytoplasmic domain was indicated as such in its entire length. The last third of the α-synuclein variant's sequence was a disordered binding site. Thymosin-β₄ and the stabilin-2 cytoplasmic domain contained only coils and helices according to five secondary structure prediction methods (SPIDER3-SPOT-1D, PSRSM, MUFold-SSW, Porter 5, and RaptorX). β-Sheets are present in α-synucleins, and they extend to more amino acid residues in the A53T mutant according to the predictions. The latter is verified by experiments. The comparison of the predictions with the experiments suggests that helical parts are buried.

EDEM3 Domains Cooperate to Perform Its Overall Cell Functioning

EDEM3 recognizes and directs misfolded proteins to the ER-associated protein degradation (ERAD) process. EDEM3 was predicted to act as lectin or as a mannosidase because of its homology with the GH47 catalytic domain of the Man1B1, but the contribution of the other regions remained unresolved. Here, we dissect the molecular determinants governing EDEM3 function and its cellular interactions. LC/MS analysis indicates very few stable ER interactors, suggesting EDEM3 availability for transient substrate interactions. Sequence analysis reveals that EDEM3 consists of four consecutive modules defined as GH47, intermediate (IMD), protease-associated (PA), and intrinsically disordered (IDD) domain. Using an EDEM3 knock-out cell line, we expressed EDEM3 and domain deletion mutants to address EDEM3 function. We find that the mannosidase domain provides substrate binding even in the absence of mannose trimming and requires the IMD domain for folding. The PA and IDD domains deletions do not impair the trimming, but specifically modulate the turnover of two misfolded proteins, NHK and the soluble tyrosinase mutant. Hence, we demonstrate that EDEM3 provides a unique ERAD timing to misfolded glycoproteins, not only by its mannose trimming activity, but also by the positive and negative feedback modulated by the protease-associated and intrinsically disordered domain, respectively.

On the Prevalence and Potential Functionality of an Intrinsic Disorder in the MERS-CoV Proteome

Middle East respiratory syndrome is a severe respiratory illness caused by an infectious coronavirus. This virus is associated with a high mortality rate, but there is as of yet no effective vaccine or antibody available for human immunity/treatment. Drug design relies on understanding the 3D structures of viral proteins; however, arriving at such understanding is difficult for intrinsically disordered proteins, whose disorder-dependent functions are key to the virus’s biology. Disorder is suggested to provide viral proteins with highly flexible structures and diverse functions that are utilized when invading host organisms and adjusting to new habitats. To date, the functional roles of intrinsically disordered proteins in the mechanisms of MERS-CoV pathogenesis, transmission, and treatment remain unclear. In this study, we performed structural analysis to evaluate the abundance of intrinsic disorder in the MERS-CoV proteome and in individual proteins derived from the MERS-CoV genome. Moreover, we detected disordered protein binding regions, namely, molecular recognition features and short linear motifs. Studying disordered proteins/regions in MERS-CoV could contribute to unlocking the complex riddles of viral infection, exploitation strategies, and drug development approaches in the near future by making it possible to target these important (yet challenging) unstructured regions.

On the irrationality of rational design of an HIV vaccine in light of protein intrinsic disorder

The lack of progress in finding an efficient vaccine for a human immunodeficiency virus (HIV) is daunting. In fact, this search has spanned nearly four decades without much success. There are several objective reasons for such a failure, which include the highly glycosylated nature of HIV-1, the presence of neotopes, and high mutation rates. This article argues that the presence of highly flexible and intrinsically disordered regions in both human anti-HIV-1 antibodies and the major HIV-1immunogen, its surface glycoprotein gp120, represent one of the major causes for the lack of success in utilization of structure-based reverse vaccinology.

The analysis on the human protein domain targets and host-like interacting motifs for the MERS-CoV and SARS-CoV/CoV-2 infers the molecular mimicry of coronavirus

The MERS-CoV, SARS-CoV, and SARS-CoV-2 are highly pathogenic viruses that can cause severe pneumonic diseases in humans. Unfortunately, there is a non-available effective treatment to combat these viruses. Domain-motif interactions (DMIs) are an essential means by which viruses mimic and hijack the biological processes of host cells. To disentangle how viruses achieve this process can help to develop new rational therapies. Data mining was performed to obtain DMIs stored as regular expressions (regexp) in 3DID and ELM databases. The mined regexp information was mapped on the coronaviruses' proteomes. Most motifs on viral protein that could interact with human proteins are shared across the coronavirus species, indicating that molecular mimicry is a common strategy for coronavirus infection. Enrichment ontology analysis for protein domains showed a shared biological process and molecular function terms related to carbon source utilization and potassium channel regulation. Some of the mapped motifs were nested on B, and T cell epitopes, suggesting that it could be as an alternative way for reverse vaccinology. The information obtained in this study could be used for further theoretic and experimental explorations on coronavirus infection mechanism and development of medicines for treatment.

Proximity proteomics in a marine diatom reveals a putative cell surface-to-chloroplast iron trafficking pathway

Iron is a biochemically critical metal cofactor in enzymes involved in photosynthesis, cellular respiration, nitrate assimilation, nitrogen fixation, and reactive oxygen species defense. Marine microeukaryotes have evolved a phytotransferrin-based iron uptake system to cope with iron scarcity, a major factor limiting primary productivity in the global ocean. Diatom phytotransferrin is endocytosed; however, proteins downstream of this environmentally ubiquitous iron receptor are unknown. We applied engineered ascorbate peroxidase APEX2-based subcellular proteomics to catalog proximal proteins of phytotransferrin in the model marine diatom Phaeodactylum tricornutum. Proteins encoded by poorly characterized iron-sensitive genes were identified including three that are expressed from a chromosomal gene cluster. Two of them showed unambiguous colocalization with phytotransferrin adjacent to the chloroplast. Further phylogenetic, domain, and biochemical analyses suggest their involvement in intracellular iron processing. Proximity proteomics holds enormous potential to glean new insights into iron acquisition pathways and beyond in these evolutionarily, ecologically, and biotechnologically important microalgae.

Secondary structure dependence of amyloid-β(1-40) on simulation techniques and force field parameters

Our recent studies revealed that none of the selected widely used force field parameters and molecular dynamics simulation techniques yield structural properties for the intrinsically disordered α-synuclein that are in agreement with various experiments via testing different force field parameters. Here, we extend our studies on the secondary structure properties of the disordered amyloid-β(1-40) peptide in aqueous solution. For these purposes, we conducted extensive replica exchange molecular dynamics simulations and obtained extensive molecular dynamics simulation trajectories from David E. Shaw group. Specifically, these molecular dynamics simulations were conducted using various force field parameters and obtained results are compared to our replica exchange molecular dynamics simulations and experiments. In this study, we calculated the secondary structure abundances and radius of gyration values for amyloid-β(1-40) that were simulated using varying force field parameter sets and different simulation techniques. In addition, the intrinsic disorder propensity, as well as sequence-based secondary structure predisposition of amyloid-β(1-40) and compared the findings with the results obtained from molecular simulations using various force field parameters and different simulation techniques. Our studies clearly show that the epitope region identification of amyloid-β(1-40) depends on the chosen simulation technique and chosen force field parameters. Based on comparison with experiments, we find that best computational results in agreement with experiments are obtained using the a99sb*-ildn, charmm36m, and a99sb-disp parameters for the amyloid-β(1-40) peptide in molecular dynamics simulations without parallel tempering or via replica exchange molecular dynamics simulations.

The Role of Low Complexity Regions in Protein Interaction Modes: An Illustration in Huntingtin

Low complexity regions (LCRs) are very frequent in protein sequences, generally having a lower propensity to form structured domains and tending to be much less evolutionarily conserved than globular domains. Their higher abundance in eukaryotes and in species with more cellular types agrees with a growing number of reports on their function in protein interactions regulated by post-translational modifications. LCRs facilitate the increase of regulatory and network complexity required with the emergence of organisms with more complex tissue distribution and development. Although the low conservation and structural flexibility of LCRs complicate their study, evolutionary studies of proteins across species have been used to evaluate their significance and function. To investigate how to apply this evolutionary approach to the study of LCR function in protein-protein interactions, we performed a detailed analysis for Huntingtin (HTT), a large protein that is a hub for interaction with hundreds of proteins, has a variety of LCRs, and for which partial structural information (in complex with HAP40) is available. We hypothesize that proteins RASA1, SYN2, and KAT2B may compete with HAP40 for their attachment to the core of HTT using similar LCRs. Our results illustrate how evolution might favor the interplay of LCRs with domains, and the possibility of detecting multiple modes of LCR-mediated protein-protein interactions with a large hub such as HTT when enough protein interaction data is available.

Genomic diversity in a population of Spodoptera frugiperda nucleopolyhedrovirus

Spodoptera frugiperda multiple nucleopolyhedrovirus (SfMNPV) represents a strong candidate to develop environmental-friendly pesticides against the fall armyworm (Spodoptera frugiperda), a widespread pest that poses a severe threat to different crops around the world. To date, SfMNPV genomic diversity of different isolates has been mainly studied by means of restriction pattern analyses and by sequencing of the egt region. Here, the genomic diversity present inside an isolate of SfMNPV was explored using high-throughput sequencing for the first time. We identified 704 intrahost single nucleotide variants, from which 184 are nonsynonymous mutations distributed among 82 different coding sequences. We detected several structural variants affecting SfMNPV genome, including two previously reported deletions inside the egt region. A comparative analysis between polymorphisms present in different SfMNPV isolates and our intraisolate diversity data suggests that coding regions with higher genetic diversity are associated with oral infectivity or unknown functions. In this context, through molecular evolution studies we provide evidence of diversifying selection acting on sf29, a putative collagenase which could contribute to the oral infectivity of SfMNPV. Overall, our results contribute to deepen our understanding of the coevolution between SfMNPV and the fall armyworm and will be useful to improve the applicability of this virus as a biological control agent.

Potential Pathogenicity Determinants Identified from Structural Proteomics of SARS-CoV and SARS-CoV-2

Despite SARS-CoV and SARS-CoV-2 being equipped with highly similar protein arsenals, the corresponding zoonoses have spread among humans at extremely different rates. The specific characteristics of these viruses that led to such distinct outcomes remain unclear. Here, we apply proteome-wide comparative structural analysis aiming to identify the unique molecular elements in the SARS-CoV-2 proteome that may explain the differing consequences. By combining protein modeling and molecular dynamics simulations, we suggest nonconservative substitutions in functional regions of the spike glycoprotein (S), nsp1, and nsp3 that are contributing to differences in virulence. Particularly, we explain why the substitutions at the receptor-binding domain of S affect the structure–dynamics behavior in complexes with putative host receptors. Conservation of functional protein regions within the two taxa is also noteworthy. We suggest that the highly conserved main protease, nsp5, of SARS-CoV and SARS-CoV-2 is part of their mechanism of circumventing the host interferon antiviral response. Overall, most substitutions occur on the protein surfaces and may be modulating their antigenic properties and interactions with other macromolecules. Our results imply that the striking difference in the pervasiveness of SARS-CoV-2 and SARS-CoV among humans seems to significantly derive from molecular features that modulate the efficiency of viral particles in entering the host cells and blocking the host immune response.

Predicting protein condensate formation using machine learning

Membraneless organelles are liquid condensates, which form through liquid-liquid phase separation. Recent advances show that phase separation is essential for cellular homeostasis by regulating basic cellular processes, including transcription and signal transduction. The reported number of proteins with the capacity to mediate protein phase separation (PPS) is continuously growing. While computational tools for predicting PPS have been developed, obtaining a proteome-wide overview of PPS probabilities has remained challenging. Here, we present a phase separation analysis and prediction (PSAP) machine-learning classifier that, based solely on the amino acid content of a training set of known PPS proteins, can determine the phase separation likelihood for each protein in a given proteome. Through comparison with PPS databases, existing predictors, and experimental evidence, we demonstrate the validity and advantages of the PSAP classifier. We anticipate that the PSAP predictor provides a useful tool for future research aimed at identifying phase separating proteins in health and disease.

Computational resources for identifying and describing proteins driving liquid-liquid phase separation

One of the most intriguing fields emerging in current molecular biology is the study of membraneless organelles formed via liquid–liquid phase separation (LLPS). These organelles perform crucial functions in cell regulation and signalling, and recent years have also brought about the understanding of the molecular mechanism of their formation. The LLPS field is continuously developing and optimizing dedicated in vitro and in vivo methods to identify and characterize these non-stoichiometric molecular condensates and the proteins able to drive or contribute to LLPS. Building on these observations, several computational tools and resources have emerged in parallel to serve as platforms for the collection, annotation and prediction of membraneless organelle-linked proteins. In this survey, we showcase recent advancements in LLPS bioinformatics, focusing on (i) available databases and ontologies that are necessary to describe the studied phenomena and the experimental results in an unambiguous way and (ii) prediction methods to assess the potential LLPS involvement of proteins. Through hands-on application of these resources on example proteins and representative datasets, we give a practical guide to show how they can be used in conjunction to provide in silico information on LLPS.

Anti-tumour immunity induces aberrant peptide presentation in melanoma

Extensive tumour inflammation, which is reflected by high levels of infiltrating T cells and interferon-γ (IFNγ) signalling, improves the response of patients with melanoma to checkpoint immunotherapy^1,2. Many tumours, however, escape by activating cellular pathways that lead to immunosuppression. One such mechanism is the production of tryptophan metabolites along the kynurenine pathway by the enzyme indoleamine 2,3-dioxygenase 1 (IDO1), which is induced by IFNγ^3-5. However, clinical trials using inhibition of IDO1 in combination with blockade of the PD1 pathway in patients with melanoma did not improve the efficacy of treatment compared to PD1 pathway blockade alone^6,7, pointing to an incomplete understanding of the role of IDO1 and the consequent degradation of tryptophan in mRNA translation and cancer progression. Here we used ribosome profiling in melanoma cells to investigate the effects of prolonged IFNγ treatment on mRNA translation. Notably, we observed accumulations of ribosomes downstream of tryptophan codons, along with their expected stalling at the tryptophan codon. This suggested that ribosomes bypass tryptophan codons in the absence of tryptophan. A detailed examination of these tryptophan-associated accumulations of ribosomes-which we term 'W-bumps'-showed that they were characterized by ribosomal frameshifting events. Consistently, reporter assays combined with proteomic and immunopeptidomic analyses demonstrated the induction of ribosomal frameshifting, and the generation and presentation of aberrant trans-frame peptides at the cell surface after treatment with IFNγ. Priming of naive T cells from healthy donors with aberrant peptides induced peptide-specific T cells. Together, our results suggest that IDO1-mediated depletion of tryptophan, which is induced by IFNγ, has a role in the immune recognition of melanoma cells by contributing to diversification of the peptidome landscape.

Understanding COVID-19 via comparative analysis of dark proteomes of SARS-CoV-2, human SARS and bat SARS-like coronaviruses

The recently emerged coronavirus designated as SARS-CoV-2 (also known as 2019 novel coronavirus (2019-nCoV) or Wuhan coronavirus) is a causative agent of coronavirus disease 2019 (COVID-19), which is rapidly spreading throughout the world now. More than 1.21 million cases of SARS-CoV-2 infection and more than 67,000 COVID-19-associated mortalities have been reported worldwide till the writing of this article, and these numbers are increasing every passing hour. The World Health Organization (WHO) has declared the SARS-CoV-2 spread as a global public health emergency and admitted COVID-19 as a pandemic now. Multiple sequence alignment data correlated with the already published reports on SARS-CoV-2 evolution indicated that this virus is closely related to the bat severe acute respiratory syndrome-like coronavirus (bat SARS-like CoV) and the well-studied human SARS coronavirus (SARS-CoV). The disordered regions in viral proteins are associated with the viral infectivity and pathogenicity. Therefore, in this study, we have exploited a set of complementary computational approaches to examine the dark proteomes of SARS-CoV-2, bat SARS-like, and human SARS CoVs by analysing the prevalence of intrinsic disorder in their proteins. According to our findings, SARS-CoV-2 proteome contains very significant levels of structural order. In fact, except for nucleocapsid, Nsp8, and ORF6, the vast majority of SARS-CoV-2 proteins are mostly ordered proteins containing less intrinsically disordered protein regions (IDPRs). However, IDPRs found in SARS-CoV-2 proteins are functionally important. For example, cleavage sites in its replicase 1ab polyprotein are found to be highly disordered, and almost all SARS-CoV-2 proteins contains molecular recognition features (MoRFs), which are intrinsic disorder-based protein-protein interaction sites that are commonly utilized by proteins for interaction with specific partners. The results of our extensive investigation of the dark side of SARS-CoV-2 proteome will have important implications in understanding the structural and non-structural biology of SARS or SARS-like coronaviruses.

Design of intrinsically disordered proteins that undergo phase transitions with lower critical solution temperatures

Many naturally occurring elastomers are intrinsically disordered proteins (IDPs) built up of repeating units and they can demonstrate two types of thermoresponsive phase behavior. Systems characterized by lower critical solution temperatures (LCST) undergo phase separation above the LCST whereas systems characterized by upper critical solution temperatures (UCST) undergo phase separation below the UCST. There is congruence between thermoresponsive coil-globule transitions and phase behavior whereby the theta temperatures above or below which the IDPs transition from coils to globules serve as useful proxies for the LCST / UCST values. This implies that one can design sequences with desired values for the theta temperature with either increasing or decreasing radii of gyration above the theta temperature. Here, we show that the Monte Carlo simulations performed in the so-called intrinsic solvation (IS) limit version of the temperature-dependent the ABSINTH (self-Assembly of Biomolecules Studied by an Implicit, Novel, Tunable Hamiltonian) implicit solvation model, yields a useful heuristic for discriminating between sequences with known LCST versus UCST phase behavior. Accordingly, we use this heuristic in a supervised approach, integrate it with a genetic algorithm, combine this with IS limit simulations, and demonstrate that novel sequences can be designed with LCST phase behavior. These calculations are aided by direct estimates of temperature dependent free energies of solvation for model compounds that are derived using the polarizable AMOEBA (atomic multipole optimized energetics for biomolecular applications) forcefield. To demonstrate the validity of our designs, we calculate coil-globule transition profiles using the full ABSINTH model and combine these with Gaussian Cluster Theory calculations to establish the LCST phase behavior of designed IDPs.

Spatiotemporal dissection of the cell cycle with single-cell proteogenomics

The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer^1-3. The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation.

The MemMoRF database for recognizing disordered protein regions interacting with cellular membranes

Protein and lipid membrane interactions play fundamental roles in a large number of cellular processes (e.g. signalling, vesicle trafficking, or viral invasion). A growing number of examples indicate that such interactions can also rely on intrinsically disordered protein regions (IDRs), which can form specific reversible interactions not only with proteins but also with lipids. We named IDRs involved in such membrane lipid-induced disorder-to-order transition as MemMoRFs, in an analogy to IDRs exhibiting disorder-to-order transition upon interaction with protein partners termed Molecular Recognition Features (MoRFs). Currently, both the experimental detection and computational characterization of MemMoRFs are challenging, and information about these regions are scattered in the literature. To facilitate the related investigations we generated a comprehensive database of experimentally validated MemMoRFs based on manual curation of literature and structural data. To characterize the dynamics of MemMoRFs, secondary structure propensity and flexibility calculated from nuclear magnetic resonance chemical shifts were incorporated into the database. These data were supplemented by inclusion of sentences from papers, functional data and disease-related information. The MemMoRF database can be accessed via a user-friendly interface at https://memmorf.hegelab.org, potentially providing a central resource for the characterization of disordered regions in transmembrane and membrane-associated proteins.

AcrHub: an integrative hub for investigating, predicting and mapping anti-CRISPR proteins

Anti-CRISPR (Acr) proteins naturally inhibit CRISPR-Cas adaptive immune systems across bacterial and archaeal domains of life. This emerging field has caused a paradigm shift in the way we think about the CRISPR-Cas system, and promises a number of useful applications from gene editing to phage therapy. As the number of verified and predicted Acrs rapidly expands, few online resources have been developed to deal with this wealth of information. To overcome this shortcoming, we developed AcrHub, an integrative database to provide an all-in-one solution for investigating, predicting and mapping Acr proteins. AcrHub catalogs 339 non-redundant experimentally validated Acrs and over 70 000 predicted Acrs extracted from genome sequence data from a diverse range of prokaryotic organisms and their viruses. It integrates state-of-the-art predictors to predict potential Acrs, and incorporates three analytical modules: similarity analysis, phylogenetic analysis and homology network analysis, to analyze their relationships with known Acrs. By interconnecting all modules as a platform, AcrHub presents enriched and in-depth analysis of known and potential Acrs and therefore provides new and exciting insights into the future of Acr discovery and validation. AcrHub is freely available at http://pacrispr.erc.monash.edu/AcrHub/.

Principles of dengue virus evolvability derived from genotype-fitness maps in human and mosquito cells

Dengue virus (DENV) cycles between mosquito and mammalian hosts. To examine how DENV populations adapt to these different host environments, we used serial passage in human and mosquito cell lines and estimated fitness effects for all single-nucleotide variants in these populations using ultra-deep sequencing. This allowed us to determine the contributions of beneficial and deleterious mutations to the collective fitness of the population. Our analysis revealed that the continuous influx of a large burden of deleterious mutations counterbalances the effect of rare, host-specific beneficial mutations to shape the path of adaptation. Beneficial mutations preferentially map to intrinsically disordered domains in the viral proteome and cluster to defined regions in the genome. These phenotypically redundant adaptive alleles may facilitate host-specific DENV adaptation. Importantly, the evolutionary constraints described in our simple system mirror trends observed across DENV and Zika strains, indicating it recapitulates key biophysical and biological constraints shaping long-term viral evolution.

Tuning intrinsic disorder predictors for virus proteins

Many virus-encoded proteins have intrinsically disordered regions that lack a stable, folded three-dimensional structure. These disordered proteins often play important functional roles in virus replication, such as down-regulating host defense mechanisms. With the widespread availability of next-generation sequencing, the number of new virus genomes with predicted open reading frames is rapidly outpacing our capacity for directly characterizing protein structures through crystallography. Hence, computational methods for structural prediction play an important role. A large number of predictors focus on the problem of classifying residues into ordered and disordered regions, and these methods tend to be validated on a diverse training set of proteins from eukaryotes, prokaryotes, and viruses. In this study, we investigate whether some predictors outperform others in the context of virus proteins and compared our findings with data from non-viral proteins. We evaluate the prediction accuracy of 21 methods, many of which are only available as web applications, on a curated set of 126 proteins encoded by viruses. Furthermore, we apply a random forest classifier to these predictor outputs. Based on cross-validation experiments, this ensemble approach confers a substantial improvement in accuracy, e.g., a mean 36 per cent gain in Matthews correlation coefficient. Lastly, we apply the random forest predictor to severe acute respiratory syndrome coronavirus 2 ORF6, an accessory gene that encodes a short (61 AA) and moderately disordered protein that inhibits the host innate immune response. We show that disorder prediction methods perform differently for viral and non-viral proteins, and that an ensemble approach can yield more robust and accurate predictions.

Recombinant pebulin protein, a type 2 ribosome-inactivating protein isolated from dwarf elder (Sambucus ebulus L.) shows anticancer and antifungal activities in vitro

In this study, encoding sequence of a new type 2 RIP (pebulin) was isolated and cloned from dwarf elder (Sambucus ebulus L.) native to the northern regions of Iran. The nucleotide sequence of pebulin was ligated to the pET-28a(+) expression plasmid and cloned into the E. coli strain BL21 (DE3) in order to express heterologously of recombinant protein. The recombinant pebulin protein was mainly produced in the form of insoluble inclusion bodies probably because to absence of N-glycosylation process in E. coli. Therefore, in order to increase the expression of recombinant protein in soluble form, co-expression of the target protein with the pG-Tf2 chaperone plasmid and incubation of bacterial culture under low temperature were used to enhance solubility and accumulation of recombinant protein. After purification of the recombinant protein using affinity chromatography method, the bioactivity of pebulin was analyzed by hemagglutination, anticancer, and antifungal assays. The results of the hemagglutination assay showed that purified pebulin agglutinated erythrocytes in all human blood groups. In addition, pebulin considerably inhibited the proliferation of cancer cell lines MCF-7 and HT-29 in a time- and dose-dependent manner and indicated remarkably growth-inhibiting effect against the plant pathogenic fungi such as Alternaria solani and Fusarium oxysporum.

Crystal and solution structure of NDRG1, a membrane-binding protein linked to myelination and tumour suppression

N-myc downstream-regulated gene 1 (NDRG1) is a tumour suppressor involved in vesicular trafficking and stress response. NDRG1 participates in peripheral nerve myelination, and mutations in the NDRG1 gene lead to Charcot-Marie-Tooth neuropathy. The 43-kDa NDRG1 is considered as an inactive member of the α/β hydrolase superfamily. In addition to a central α/β hydrolase fold domain, NDRG1 consists of a short N terminus and a C-terminal region with three 10-residue repeats. We determined the crystal structure of the α/β hydrolase domain of human NDRG1 and characterised the structure and dynamics of full-length NDRG1. The structure of the α/β hydrolase domain resembles the canonical α/β hydrolase fold with a central β sheet surrounded by α helices. Small-angle X-ray scattering and CD spectroscopy indicated a variable conformation for the N- and C-terminal regions. NDRG1 binds to various types of lipid vesicles, and the conformation of the C-terminal region is modulated upon lipid interaction. Intriguingly, NDRG1 interacts with metal ions, such as nickel, but is prone to aggregation in their presence. Our results uncover the structural and dynamic features of NDRG1, as well as elucidate its interactions with metals and lipids, and encourage studies to identify a putative hydrolase activity of NDRG1. DATABASES: The coordinates and structure factors for the crystal structure of human NDRG1 were deposited to PDB (PDB ID: 6ZMM).

Membrane Binding and Homodimerization of Atg16 Via Two Distinct Protein Regions is Essential for Autophagy in Yeast

Macroautophagy is a bulk degradation mechanism in eukaryotic cells. Efficiency of an essential step of this process in yeast, Atg8 lipidation, relies on the presence of Atg16, a subunit of the Atg12-Atg5-Atg16 complex acting as the E3-like enzyme in the ubiquitination-like reaction. A current view on the functional structure of Atg16 in the yeast S. cerevisiae comes from the two crystal structures that reveal the Atg5-interacting α-helix linked via a flexible linker to another α-helix of Atg16, which then assembles into a homodimer. This view does not explain the results of previous in vitro studies revealing Atg16-dependent deformations of membranes and liposome-binding of the Atg12-Atg5 conjugate upon addition of Atg16. Here we show that Atg16 acts as both a homodimerizing and peripheral membrane-binding polypeptide. These two characteristics are imposed by the two distinct regions that are disordered in the nascent protein. Atg16 binds to membranes in vivo via the amphipathic α-helix (amino acid residues 113-131) that has a coiled-coil-like propensity and a strong hydrophobic face for insertion into the membrane. The other protein region (residues 64-99) possesses a coiled-coil propensity, but not amphipathicity, and is dispensable for membrane anchoring of Atg16. This region acts as a Leu-zipper essential for formation of the Atg16 homodimer. Mutagenic disruption in either of these two distinct domains renders Atg16 proteins that, in contrast to wild type, completely fail to rescue the autophagy-defective phenotype of atg16Δ cells. Together, the results of this study yield a model for the molecular mechanism of Atg16 function in macroautophagy.