FELLS: fast estimator of latent local structure

Intrinsically disordered Pseudomonas chaperone FapA slows down the fibrillation of major biofilm-forming functional amyloid FapC

Functional bacterial amyloids play a crucial role in the formation of biofilms, which mediate chronic infections and contribute to antimicrobial resistance. This study focuses on the FapC amyloid fibrillar protein from Pseudomonas, a major contributor to biofilm formation. We investigate the initial steps of FapC amyloid formation and the impact of the chaperone-like protein FapA on this process. Using solution nuclear magnetic resonance (NMR), we recently showed that both FapC and FapA are intrinsically disordered proteins (IDPs). Here, the secondary structure propensities (SSPs) are compared to alphafold (DeepMind, protein structure prediction tool/algorithm: https://alphafold.ebi.ac.uk/) models. We further demonstrate that the FapA chaperone interacts with FapC and significantly slows down the formation of FapC fibrils. Our NMR titrations reveal ~ 18% of the resonances show FapA-induced chemical shift perturbations (CSPs), which has not been previously observed, the largest being for A82, N201, C237, C240, A241, and G245. These sites may suggest a specific interaction site and/or hotspots of fibrillation inhibition/control interface at the repeat-1 (R1)/loop-2 (L2) and L2/R3 transition areas and at the C-terminus of FapC. Remarkably, ~ 90% of FapA NMR signals exhibit substantial CSPs upon titration with FapC, the largest being for S63, A69, A80, and I92. A temperature-dependent effect of FapA was observed on FapC by thioflavin T (ThT) and NMR experiments. This study provides a detailed understanding of the interaction between the FapA and FapC, shedding light on the regulation and slowing down of amyloid formation, and has important implications for the development of therapeutic strategies targeting biofilms and associated infections.

Elucidating the Impact of Deleterious Mutations on IGHG1 and Their Association with Huntington's Disease

Huntington's disease (HD) is a chronic, inherited neurodegenerative condition marked by chorea, dementia, and changes in personality. The primary cause of HD is a mutation characterized by the expansion of a triplet repeat (CAG) within the huntingtin gene located on chromosome 4. Despite substantial progress in elucidating the molecular and cellular mechanisms of HD, an effective treatment for this disorder is not available so far. In recent years, researchers have been interested in studying cerebrospinal fluid (CSF) as a source of biomarkers that could aid in the diagnosis and therapeutic development of this disorder. Immunoglobulin heavy constant gamma 1 (IGHG1) is one of the CSF proteins found to increase significantly in HD. Considering this, it is reasonable to study the potential involvement of deleterious mutations in IGHG1 in the pathogenesis of this disorder. In this study, we explored the potential impact of deleterious mutations on IGHG1 and their subsequent association with HD. We evaluated 126 single-point amino acid substitutions for their impact on the structure and functionality of the IGHG1 protein while exploiting multiple computational resources such as SIFT, PolyPhen-2, FATHMM, SNPs&Go mCSM, DynaMut2, MAESTROweb, PremPS, MutPred2, and PhD-SNP. The sequence- and structure-based tools highlighted 10 amino acid substitutions that were deleterious and destabilizing. Subsequently, out of these 10 mutations, eight variants (Y32C, Y32D, P34S, V39E, C83R, C83Y, V85M, and H87Q) were identified as pathogenic by disease phenotype predictors. Finally, two pathogenic variants (Y32C and P34S) were found to reduce the solubility of the protein, suggesting their propensity to form protein aggregates. These variants also exhibited higher residual frustration within the protein structure. Considering these findings, the study hypothesized that the identified variants of IGHG1 may compromise its function and potentially contribute to HD pathogenesis.

Alternative conformations of a group 4 Late Embryogenesis Abundant protein associated to its in vitro protective activity

Late Embryogenesis Abundant (LEA) proteins are a group of intrinsically disordered proteins implicated in plant responses to water deficit. In vitro studies revealed that LEA proteins protect reporter enzymes from inactivation during low water availability. Group 4 LEA proteins constitute a conserved protein family, displaying in vitro protective capabilities. Under water deficiency or macromolecular crowding, the N-terminal of these proteins adopts an alpha-helix conformation. This region has been identified as responsible for the protein in vitro protective activity. This study investigates whether the attainment of alpha-helix conformation and/or particular amino acid residues are required for the in vitro protective activity. The LEA4-5 protein from Arabidopsis thaliana was used to generate mutant proteins. The mutations altered conserved residues, deleted specific conserved regions, or introduced prolines to hinder alpha-helix formation. The results indicate that conserved residues are not essential for LEA4-5 protective function. Interestingly, the C-terminal region was found to contribute to this function. Moreover, alpha-helix conformation is necessary for the protective activity only when the C-terminal region is deleted. Overall, LEA4-5 shows the ability to adopt alternative functional conformations under the tested conditions. These findings shed light on the in vitro mechanisms by which LEA proteins protect against water deficit stress.

Remote homology identification of the Drosophila melanogaster ortholog of the RNA Polymerase I subunit Rpa34/POLR1G

Highly conserved orthologous proteins are easily identified by sequence homology alone, whereas poorly conserved orthologs require additional structural information to be identified. All Drosophila orthologs of RNA polymerase I, II, and III subunits-except one-have been identified by sequence homology. Here, we identified CG11076 as the missing Rpa34/POLR1G ortholog in Drosophila . Remote homology detection and secondary structure analysis showed that CG11076 is predicted to have high structural conservation with Rpa34/POLR1G, and phylogenetic analysis demonstrated that these proteins are closely related. Our work underscores the importance of utilizing both sequence and structure to identify highly divergent orthologous proteins in different species.

Genome-wide identification of late embryogenesis abundant protein family and their key regulatory network in Pinus tabuliformis cold acclimation

Cold acclimation is a crucial biological process that enables conifers to overwinter safely. The late embryogenesis abundant (LEA) protein family plays a pivotal role in enhancing freezing tolerance during this process. Despite its importance, the identification, molecular functions and regulatory networks of the LEA protein family have not been extensively studied in conifers or gymnosperms. Pinus tabuliformis, a conifer with high ecological and economic values and with high-quality genome sequence, is an ideal candidate for such studies. Here, a total of 104 LEA genes were identified from P. tabuliformis, and we renamed them according to their subfamily group: PtLEA1-PtLEA92 (group LEA1-LEA6), PtSMP1-PtSMP6 (group seed maturation protein) and PtDHN1-PtDHN6 (group Dehydrin). While the sequence structure of P. tabuliformis  LEA genes are conserved, their physicochemical properties exhibit unique characteristics within different subfamily groupings. Notably, the abundance of low-temperature responsive elements in PtLEA genes was observed. Using annual rhythm and temperature gradient transcriptome data, PtLEA22 was identified as a key gene that responds to low-temperature induction while conforming to the annual cycle of cold acclimation. Overexpression of PtLEA22 enhanced Arabidopsis freezing tolerance. Furthermore, several transcription factors potentially co-expressed with PtLEA22 were validated using yeast one-hybrid and dual-luciferase assays, revealing that PtDREB1 could directly bind PtLEA22 promoter to positively regulate its expression. These findings reveal the genome-wide characterization of P. tabuliformis  LEA genes and their importance in the cold acclimation, while providing a theoretical basis for studying the molecular mechanisms of cold acclimation in conifers.

Structural properties of the HNF-1A transactivation domain

Hepatocyte nuclear factor 1α (HNF-1A) is a transcription factor with important gene regulatory roles in pancreatic β-cells. HNF1A gene variants are associated with a monogenic form of diabetes (HNF1A-MODY) or an increased risk for type 2 diabetes. While several pancreatic target genes of HNF-1A have been described, a lack of knowledge regarding the structure-function relationships in HNF-1A prohibits a detailed understanding of HNF-1A-mediated gene transcription, which is important for precision medicine and improved patient care. Therefore, we aimed to characterize the understudied transactivation domain (TAD) of HNF-1A in vitro. We present a bioinformatic approach to dissect the TAD sequence, analyzing protein structure, sequence composition, sequence conservation, and the existence of protein interaction motifs. Moreover, we developed the first protocol for the recombinant expression and purification of the HNF-1A TAD. Small-angle X-ray scattering and synchrotron radiation circular dichroism suggested a disordered conformation for the TAD. Furthermore, we present functional data on HNF-1A undergoing liquid-liquid phase separation, which is in line with in silico predictions and may be of biological relevance for gene transcriptional processes in pancreatic β-cells.

Prokaryotic membrane coat - like proteins: An update

Membrane coat proteins are essential players in the eukaryotic endomembrane traffic system. Previous work identified proteins with the membrane-coat architecture in prokaryotes, specifically in the Planctomycetes, Verrucomicrobia and Chlamydiae (PVC) superphylum, bacteria that display the most developed prokaryotic endomembrane system. Hence, the membrane coat-like (MCL) proteins are predicted to play a central role in this system but their actual function is still unknown. In this work we strengthened previous structure predictions for these prokaryotic MCL proteins. We also detected new putative MCL proteins in the Planctomycete Gemmata obscuriglobus. Structural analysis of these revealed the presence of additional domains apart from the β-propeller and α-solenoid combination, characteristic of the membrane-coat architecture. Functions associated with these domains include some related to carbohydrate or membrane/lipid binding. Using homology-based methods, we found MCL proteins in other bacterial phyla, but the most abundant hits are still restricted to Planctomycetes and Verrucomicrobia. Detailed inspection of neighbouring genes of MCL in G. obscuriglobus supports the idea that the function of these proteins is related to membrane manipulation. No significant hits were found in Archaea, including Asgard archaea. More than 10 years after their original detection, PVC bacteria are still uniquely linked to eukaryotes through the structure of the MCL proteins sustaining their endomembrane system.

A sequence-based foldability score combined with AlphaFold2 predictions to disentangle the protein order/disorder continuum

Order and disorder govern protein functions, but there is a great diversity in disorder, from regions that are-and stay-fully disordered to conditional order. This diversity is still difficult to decipher even though it is encoded in the amino acid sequences. Here, we developed an analytic Python package, named pyHCA, to estimate the foldability of a protein segment from the only information of its amino acid sequence and based on a measure of its density in regular secondary structures associated with hydrophobic clusters, as defined by the hydrophobic cluster analysis (HCA) approach. The tool was designed by optimizing the separation between foldable segments from databases of disorder (DisProt) and order (SCOPe [soluble domains] and OPM [transmembrane domains]). It allows to specify the ratio between order, embodied by regular secondary structures (either participating in the hydrophobic core of well-folded 3D structures or conditionally formed in intrinsically disordered regions) and disorder. We illustrated the relevance of pyHCA with several examples and applied it to the sequences of the proteomes of 21 species ranging from prokaryotes and archaea to unicellular and multicellular eukaryotes, for which structure models are provided in the AlphaFold protein structure database. Cases of low-confidence scores related to disorder were distinguished from those of sequences that we identified as foldable but are still excluded from accurate modeling by AlphaFold2 due to a lack of sequence homologs or to compositional biases. Overall, our approach is complementary to AlphaFold2, providing guides to map structural innovations through evolutionary processes, at proteome and gene scales.

The length of FOXE1 polyalanine tract in congenital hypothyroidism: Evidence for a pathogenic role from familial, molecular and cohort studies

INTRODUCTION

FOXE1 is required for thyroid function and its homozygous mutations cause a rare syndromic form of congenital hypothyroidism (CH). FOXE1 has a polymorphic polyalanine tract whose involvement in thyroid pathology is controversial. Starting from genetic studies in a CH family, we explored the functional role and involvement of FOXE1 variations in a large CH population.

METHODS

We applied NGS screening to a large CH family and a cohort of 1752 individuals and validated these results by in silico modeling and in vitro experiments.

RESULTS

A new heterozygous FOXE1 variant segregated with 14-Alanine tract homozygosity in 5 CH siblings with athyreosis. The p.L107V variant demonstrated to significantly reduce the FOXE1 transcriptional activity. The 14-Alanine-FOXE1 displayed altered subcellular localization and significantly impaired synergy with other transcription factors, when compared with the more common 16-Alanine-FOXE1. The CH group with thyroid dysgenesis was largely and significantly enriched with the 14-Alanine-FOXE1 homozygosity.

DISCUSSION

We provide new evidence that disentangle the pathophysiological role of FOXE1 polyalanine tract, thereby significantly broadening the perspective on the role of FOXE1 in the complex pathogenesis of CH. FOXE1 should be therefore added to the group of polyalanine disease-associated transcription factors.

Mutational screening of androgen receptor gene in 8224 men of infertile couples

CONTEXT

Mutations in Androgen receptor (AR) gene might be associated with infertility mainly because they cause various degree of androgen insensitivity.

OBJECTIVE

The aim of the study was to evaluate the frequency and type of AR variants in a large cohort of infertile males.

PATIENTS AND SETTING

8224 males of Italian idiopathic infertile couples referred University Hospital of Padova.

MAIN OUTCOME MEASURES

Mutational screening of AR, computational and functional analyses.

RESULTS

We found 131 patients (1.6%) harboring 45 variants in AR gene, of which 18 were novel missense AR variants. Patients with AR gene variants had lower sperm count (p = 0.048), higher testosterone concentration (p < 0.0001) and higher androgen sensitivity index (ASI) [LH x testosterone (T), p < 0.001] compared to patients without variants. Statistical analyses found T ≥ 15.38 nmol/l and ASI ≥180 IU × nmol/l2 as threshold values to discriminate with good accuracy patients with AR variants. Patients with oligozoospermia and T ≥ 15.38 nmol/l have a 9-fold increased risk of harboring mutations compared to patients with normal sperm count and T < 15.38 nmol/l (OR 9.29, 95% CI 5.07-17.02). Using computational and functional approaches, we identified two novel variants, L595P and L791I, as potentially pathogenic.

CONCLUSION

This is the largest study screening AR gene variants in men of idiopathic infertile couples. We found that the prevalence of variants increased to 3.4% in oligozoospermic subjects with T ≥ 15.38 nmol/l. Conversely, more than 80% of men with AR gene variants had low sperm count and high T levels. Based on our findings, we suggest AR sequencing as a routine genetic test in cases of idiopathic oligozoospermia with T ≥ 15.38 nmol/L.

BIAPSS: A Comprehensive Physicochemical Analyzer of Proteins Undergoing Liquid-Liquid Phase Separation

The liquid-liquid phase separation (LLPS) of biomolecules is a phenomenon which is nowadays recognized as the driving force for the biogenesis of numerous functional membraneless organelles and cellular bodies. The interplay between the protein primary sequence and phase separation remains poorly understood, despite intensive research. To uncover the sequence-encoded signals of protein capable of undergoing LLPS, we developed a novel web platform named BIAPSS (Bioinformatics Analysis of LLPS Sequences). This web server provides on-the-fly analysis, visualization, and interpretation of the physicochemical and structural features for the superset of curated LLPS proteins.

Alpha-Synuclein Aggregation Pathway in Parkinson's Disease: Current Status and Novel Therapeutic Approaches

Following Alzheimer’s, Parkinson’s disease (PD) is the second-most common neurodegenerative disorder, sharing an unclear pathophysiology, a multifactorial profile, and massive social costs worldwide. Despite this, no disease-modifying therapy is available. PD is tightly associated with α-synuclein (α-Syn) deposits, which become organised into insoluble, amyloid fibrils. As a typical intrinsically disordered protein, α-Syn adopts a monomeric, random coil conformation in an aqueous solution, while its interaction with lipid membranes drives the transition of the molecule part into an α-helical structure. The central unstructured region of α-Syn is involved in fibril formation by converting to well-defined, β-sheet rich secondary structures. Presently, most therapeutic strategies against PD are focused on designing small molecules, peptides, and peptidomimetics that can directly target α-Syn and its aggregation pathway. Other approaches include gene silencing, cell transplantation, stimulation of intracellular clearance with autophagy promoters, and degradation pathways based on immunotherapy of amyloid fibrils. In the present review, we sum marise the current advances related to α-Syn aggregation/neurotoxicity. These findings present a valuable arsenal for the further development of efficient, nontoxic, and non-invasive therapeutic protocols for disease-modifying therapy that tackles disease onset and progression in the future.

Expanding the clinical-pathological and genetic spectrum of RYR1-related congenital myopathies with cores and minicores: an Italian population study

Mutations in the RYR1 gene, encoding ryanodine receptor 1 (RyR1), are a well-known cause of Central Core Disease (CCD) and Multi-minicore Disease (MmD). We screened a cohort of 153 patients carrying an histopathological diagnosis of core myopathy (cores and minicores) for RYR1 mutation. At least one RYR1 mutation was identified in 69 of them and these patients were further studied. Clinical and histopathological features were collected. Clinical phenotype was highly heterogeneous ranging from asymptomatic or paucisymptomatic hyperCKemia to severe muscle weakness and skeletal deformity with loss of ambulation. Sixty-eight RYR1 mutations, generally missense, were identified, of which 16 were novel. The combined analysis of the clinical presentation, disease progression and the structural bioinformatic analyses of RYR1 allowed to associate some phenotypes to mutations in specific domains. In addition, this study highlighted the structural bioinformatics potential in the prediction of the pathogenicity of RYR1 mutations. Further improvement in the comprehension of genotype-phenotype relationship of core myopathies can be expected in the next future: the actual lack of the human RyR1 crystal structure paired with the presence of large intrinsically disordered regions in RyR1, and the frequent presence of more than one RYR1 mutation in core myopathy patients, require designing novel investigation strategies to completely address RyR1 mutation effect.

In Silico Characterisation of the Late Embryogenesis Abundant (LEA) Protein Families and Their Role in Desiccation Tolerance in Ramonda serbica Panc

Ramonda serbica Panc. is an ancient resurrection plant able to survive a long desiccation period and recover metabolic functions upon watering. The accumulation of protective late embryogenesis abundant proteins (LEAPs) is a desiccation tolerance hallmark. To propose their role in R. serbica desiccation tolerance, we structurally characterised LEAPs and evaluated LEA gene expression levels in hydrated and desiccated leaves. By integrating de novo transcriptomics and homologues LEAP domains, 318 R. serbica LEAPs were identified and classified according to their conserved motifs and phylogeny. The in silico analysis revealed that hydrophilic LEA4 proteins exhibited an exceptionally high tendency to form amphipathic α-helices. The most abundant, atypical LEA2 group contained more hydrophobic proteins predicted to fold into the defined globular domains. Within the desiccation-upregulated LEA genes, the majority encoded highly disordered DEH1, LEA1, LEA4.2, and LEA4.3 proteins, while the greatest portion of downregulated genes encoded LEA2.3 and LEA2.5 proteins. While dehydrins might chelate metals and bind DNA under water deficit, other intrinsically disordered LEAPs might participate in forming intracellular proteinaceous condensates or adopt amphipathic α-helical conformation, enabling them to stabilise desiccation-sensitive proteins and membranes. This comprehensive LEAPs structural characterisation is essential to understanding their function and regulation during desiccation aiming at crop drought tolerance improvement.

MemDis: Predicting Disordered Regions in Transmembrane Proteins

Transmembrane proteins (TMPs) play important roles in cells, ranging from transport processes and cell adhesion to communication. Many of these functions are mediated by intrinsically disordered regions (IDRs), flexible protein segments without a well-defined structure. Although a variety of prediction methods are available for predicting IDRs, their accuracy is very limited on TMPs due to their special physico-chemical properties. We prepared a dataset containing membrane proteins exclusively, using X-ray crystallography data. MemDis is a novel prediction method, utilizing convolutional neural network and long short-term memory networks for predicting disordered regions in TMPs. In addition to attributes commonly used in IDR predictors, we defined several TMP specific features to enhance the accuracy of our method further. MemDis achieved the highest prediction accuracy on TMP-specific dataset among other popular IDR prediction methods.

Identification of Rare LRP5 Variants in a Cohort of Males with Impaired Bone Mass

Osteoporosis is the most common bone disease characterized by reduced bone mass and increased bone fragility. Genetic contribution is one of the main causes of primary osteoporosis; therefore, both genders are affected by this skeletal disorder. Nonetheless, osteoporosis in men has received little attention, thus being underestimated and undertreated. The aim of this study was to identify novel genetic variants in a cohort of 128 males with idiopathic low bone mass using a next-generation sequencing (NGS) panel including genes whose mutations could result in reduced bone mineral density (BMD). Genetic analysis detected in eleven patients ten rare heterozygous variants within the LRP5 gene, which were categorized as VUS (variant of uncertain significance), likely pathogenic and benign variants according to American College of Medical Genetics and Genomics (ACMG) guidelines. Protein structural and Bayesian analysis performed on identified LRP5 variants pointed out p.R1036Q and p.R1135C as pathogenic, therefore suggesting the likely association of these two variants with the low bone mass phenotype. In conclusion, this study expands our understanding on the importance of a functional LRP5 protein in bone formation and highlights the necessity to sequence this gene in subjects with idiopathic low BMD.

Characterisation and functional role of a novel C1qDC protein from a colonial ascidian

As an invertebrate, the compound ascidian Botryllus schlosseri faces nonself only with innate immunity. In this species, we already identified the key components of the lectin and alternative complement activation pathways. In the present work, by mining the transcriptome, we identified a single transcript codifying for a protein, member of the C1q-domain-containing protein family, with a signal peptide followed by two globular C1q (gC1q) domains. It shares a similar domain organisation with C1q/TNF-related proteins 4, the only vertebrate protein family with two gC1q domains. Our gC1q domain-containing protein, called BsC1qDC, is actively transcribed by immunocytes. The transcription is modulated during the Botryllus blastogenetic cycle and is upregulated following the injection of Bacillus clausii cells in the circulation. Furthermore, the injection of bsc1qdc iRNA in the vasculature results in decreased transcription of the gene and a significant impairment of phagocytosis and degranulation, suggesting the involvement of this molecule in immune responses.

Disentangling the complexity of low complexity proteins

There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, and more generally the overlaps between different properties related to LCRs, using examples. We argue that statistical measures alone cannot capture all structural aspects of LCRs and recommend the combined usage of a variety of predictive tools and measurements. While the methodologies available to study LCRs are already very advanced, we foresee that a more comprehensive annotation of sequences in the databases will enable the improvement of predictions and a better understanding of the evolution and the connection between structure and function of LCRs. This will require the use of standards for the generation and exchange of data describing all aspects of LCRs.

Short abstract

There are multiple definitions for low complexity regions (LCRs) in protein sequences. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, plus overlaps between different properties related to LCRs, using examples.

Order from disorder in the sarcomere: FATZ forms a fuzzy but tight complex and phase-separated condensates with α-actinin

In sarcomeres, α-actinin cross-links actin filaments and anchors them to the Z-disk. FATZ (filamin-, α-actinin-, and telethonin-binding protein of the Z-disk) proteins interact with α-actinin and other core Z-disk proteins, contributing to myofibril assembly and maintenance. Here, we report the first structure and its cellular validation of α-actinin-2 in complex with a Z-disk partner, FATZ-1, which is best described as a conformational ensemble. We show that FATZ-1 forms a tight fuzzy complex with α-actinin-2 and propose an interaction mechanism via main molecular recognition elements and secondary binding sites. The obtained integrative model reveals a polar architecture of the complex which, in combination with FATZ-1 multivalent scaffold function, might organize interaction partners and stabilize α-actinin-2 preferential orientation in Z-disk. Last, we uncover FATZ-1 ability to phase-separate and form biomolecular condensates with α-actinin-2, raising the question whether FATZ proteins can create an interaction hub for Z-disk proteins through membraneless compartmentalization during myofibrillogenesis.

TFG binds LC3C to regulate ULK1 localization and autophagosome formation

The early secretory pathway and autophagy are two essential and evolutionarily conserved endomembrane processes that are finely interlinked. Although growing evidence suggests that intracellular trafficking is important for autophagosome biogenesis, the molecular regulatory network involved is still not fully defined. In this study, we demonstrate a crucial effect of the COPII vesicle-related protein TFG (Trk-fused gene) on ULK1 puncta number and localization during autophagy induction. This, in turn, affects formation of the isolation membrane, as well as the correct dynamics of association between LC3B and early ATG proteins, leading to the proper formation of both omegasomes and autophagosomes. Consistently, fibroblasts derived from a hereditary spastic paraparesis (HSP) patient carrying mutated TFG (R106C) show defects in both autophagy and ULK1 puncta accumulation. In addition, we demonstrate that TFG activity in autophagy depends on its interaction with the ATG8 protein LC3C through a canonical LIR motif, thereby favouring LC3C-ULK1 binding. Altogether, our results uncover a link between TFG and autophagy and identify TFG as a molecular scaffold linking the early secretion pathway to autophagy.

In Silico Analysis of Huntingtin Homologs in Lower Eukaryotes

Huntington’s disease is a rare neurodegenerative and autosomal dominant disorder. HD is caused by a mutation in the gene coding for huntingtin (Htt). The result is the production of a mutant Htt with an abnormally long polyglutamine repeat that leads to pathological Htt aggregates. Although the structure of human Htt has been determined, albeit at low resolution, its functions and how they are performed are largely unknown. Moreover, there is little information on the structure and function of Htt in other organisms. The comparison of Htt homologs can help to understand if there is a functional conservation of domains in the evolution of Htt in eukaryotes. In this work, through a computational approach, Htt homologs from lower eukaryotes have been analysed, identifying ordered domains and modelling their structure. Based on the structural models, a putative function for most of the domains has been predicted. A putative C. elegans Htt-like protein has also been analysed following the same approach. The results obtained support the notion that this protein is a orthologue of human Htt.

The TUTase URT1 connects decapping activators and prevents the accumulation of excessively deadenylated mRNAs to avoid siRNA biogenesis

Uridylation is a widespread modification destabilizing eukaryotic mRNAs. Yet, molecular mechanisms underlying TUTase-mediated mRNA degradation remain mostly unresolved. Here, we report that the Arabidopsis TUTase URT1 participates in a molecular network connecting several translational repressors/decapping activators. URT1 directly interacts with DECAPPING 5 (DCP5), the Arabidopsis ortholog of human LSM14 and yeast Scd6, and this interaction connects URT1 to additional decay factors like DDX6/Dhh1-like RNA helicases. Nanopore direct RNA sequencing reveals a global role of URT1 in shaping poly(A) tail length, notably by preventing the accumulation of excessively deadenylated mRNAs. Based on in vitro and in planta data, we propose a model that explains how URT1 could reduce the accumulation of oligo(A)-tailed mRNAs both by favoring their degradation and because 3' terminal uridines intrinsically hinder deadenylation. Importantly, preventing the accumulation of excessively deadenylated mRNAs avoids the biogenesis of illegitimate siRNAs that silence endogenous mRNAs and perturb Arabidopsis growth and development.

SoluProt: Prediction of Soluble Protein Expression in Escherichia coli

Motivation

Poor protein solubility hinders the production of many therapeutic and industrially useful proteins. Experimental efforts to increase solubility are plagued by low success rates and often reduce biological activity. Computational prediction of protein expressibility and solubility in Escherichia coli using only sequence information could reduce the cost of experimental studies by enabling prioritization of highly soluble proteins.

Results

A new tool for sequence-based prediction of soluble protein expression in E.coli, SoluProt, was created using the gradient boosting machine technique with the TargetTrack database as a training set. When evaluated against a balanced independent test set derived from the NESG database, SoluProt’s accuracy of 58.5% and AUC of 0.62 exceeded those of a suite of alternative solubility prediction tools. There is also evidence that it could significantly increase the success rate of experimental protein studies. SoluProt is freely available as a standalone program and a user-friendly webserver at https://loschmidt.chemi.muni.cz/soluprot/.

Availability and implementation

https://loschmidt.chemi.muni.cz/soluprot/.

Supplementary information

Supplementary data are available at Bioinformatics online.

MobiDB: intrinsically disordered proteins in 2021

The MobiDB database (URL: https://mobidb.org/) provides predictions and annotations for intrinsically disordered proteins. Here, we report recent developments implemented in MobiDB version 4, regarding the database format, with novel types of annotations and an improved update process. The new website includes a re-designed user interface, a more effective search engine and advanced API for programmatic access. The new database schema gives more flexibility for the users, as well as simplifying the maintenance and updates. In addition, the new entry page provides more visualisation tools including customizable feature viewer and graphs of the residue contact maps. MobiDB v4 annotates the binding modes of disordered proteins, whether they undergo disorder-to-order transitions or remain disordered in the bound state. In addition, disordered regions undergoing liquid-liquid phase separation or post-translational modifications are defined. The integrated information is presented in a simplified interface, which enables faster searches and allows large customized datasets to be downloaded in TSV, Fasta or JSON formats. An alternative advanced interface allows users to drill deeper into features of interest. A new statistics page provides information at database and proteome levels. The new MobiDB version presents state-of-the-art knowledge on disordered proteins and improves data accessibility for both computational and experimental users.

Ensemble description of the intrinsically disordered N-terminal domain of the Nipah virus P/V protein from combined NMR and SAXS

Using SAXS and NMR spectroscopy, we herein provide a high-resolution description of the intrinsically disordered N-terminal domain (PNT, aa 1-406) shared by the Nipah virus (NiV) phosphoprotein (P) and V protein, two key players in viral genome replication and in evasion of the host innate immune response, respectively. The use of multidimensional NMR spectroscopy allowed us to assign as much as 91% of the residues of this intrinsically disordered domain whose size constitutes a technical challenge for NMR studies. Chemical shifts and nuclear relaxation measurements provide the picture of a highly flexible protein. The combination of SAXS and NMR information enabled the description of the conformational ensemble of the protein in solution. The present results, beyond providing an overall description of the conformational behavior of this intrinsically disordered region, also constitute an asset for obtaining atomistic information in future interaction studies with viral and/or cellular partners. The present study can thus be regarded as the starting point towards the design of inhibitors that by targeting crucial protein-protein interactions involving PNT might be instrumental to combat this deadly virus.

Bioinformatic Analysis and Biophysical Characterization Reveal Structural Disorder in G0S2 Protein

G0S2 is a small protein of 103 residues in length that is involved in multiple cellular processes. To date, several reports have shown that G0S2 functions by making direct protein-protein interactions with key proteins. In lipolysis, G0S2 specifically interacts with adipose triglyceride lipase, inhibiting its activity and resulting in lipolysis being downregulated. In a similar way, G0S2 also participates in the regulation of apoptosis, cell proliferation, and oxidative phosphorylation; however, information regarding G0S2 structural and biophysical properties is limited. In this work, we conducted a comparative structural analysis of human and mouse G0S2 proteins. Bioinformatics suggests the presence of a disordered C-terminal region in human G0S2. Experimental characterization by size-exclusion chromatography and dynamic light scattering showed that human and mouse G0S2 have different hydrodynamic properties. In comparison to the mouse G0S2, which behaves similar to a globular protein, the human G0S2 shows an elongated conformation, most likely by displaying a disordered C-terminal region. Further analysis of hydrodynamic properties under denaturing conditions suggests the presence of a structural element in the mouse protein that undergoes an order to disorder transition at low urea concentration. Structural analysis by circular dichroism revealed that in native conditions, both proteins are mainly unstructured, showing the presence of beta sheet structures. Further analysis of CD data suggests that both proteins belong to the premolten globule family of intrinsically disordered proteins. We suggest that the intrinsic disorder observed in the G0S2 protein may facilitate its interaction with multiple partners in the regulation of cellular metabolism.

The E3 ubiquitin-protein ligase MDM2 is a novel interactor of the von Hippel-Lindau tumor suppressor

Mutations of the von Hippel-Lindau (pVHL) tumor suppressor are causative of a familiar predisposition to develop different types of cancer. pVHL is mainly known for its role in regulating hypoxia-inducible factor 1 α (HIF-1α) degradation, thus modulating the hypoxia response. There are different pVHL isoforms, including pVHL30 and pVHL19. However, little is known about isoform-specific functions and protein-protein interactions. Integrating in silico predictions with in vitro and in vivo assays, we describe a novel interaction between pVHL and mouse double minute 2 homolog (MDM2). We found that pVHL30, and not pVHL19, forms a complex with MDM2, and that the N-terminal acidic tail of pVHL30 is required for its association with MDM2. Further, we demonstrate that an intrinsically disordered region upstream of the tetramerization domain of MDM2 is responsible for its isoform-specific association with pVHL30. This region is highly conserved in higher mammals, including primates, similarly to what has been already shown for the N-terminal tail of pVHL30. Finally, we show that overexpression of pVHL30 and MDM2 together reduces cell metabolic activity and necrosis, suggesting a synergistic effect of these E3 ubiquitin ligases. Collectively, our data show an isoform-specific interaction of pVHL with MDM2, suggesting an interplay between these two E3 ubiquitin ligases.

A pan-cancer assessment of alterations of the kinase domain of ULK1, an upstream regulator of autophagy

Autophagy is a key clearance process to recycle damaged cellular components. One important upstream regulator of autophagy is ULK1 kinase. Several three-dimensional structures of the ULK1 catalytic domain are available, but a comprehensive study, including molecular dynamics, is missing. Also, an exhaustive description of ULK1 alterations found in cancer samples is presently lacking. We here applied a framework which links -omics data to structural protein ensembles to study ULK1 alterations from genomics data available for more than 30 cancer types. We predicted the effects of mutations on ULK1 function and structural stability, accounting for protein dynamics, and the different layers of changes that a mutation can induce in a protein at the functional and structural level. ULK1 is down-regulated in gynecological tumors. In other cancer types, ULK2 could compensate for ULK1 downregulation and, in the majority of the cases, no marked changes in expression have been found. 36 missense mutations of ULK1, not limited to the catalytic domain, are co-occurring with mutations in a large number of ULK1 interactors or substrates, suggesting a pronounced effect of the upstream steps of autophagy in many cancer types. Moreover, our results pinpoint that more than 50% of the mutations in the kinase domain of ULK1, here investigated, are predicted to affect protein stability. Three mutations (S184F, D102N, and A28V) are predicted with only impact on kinase activity, either modifying the functional dynamics or the capability to exert effects from distal sites to the functional and catalytic regions. The framework here applied could be extended to other protein targets to aid the classification of missense mutations from cancer genomics studies, as well as to prioritize variants for experimental validation, or to select the appropriate biological readouts for experiments.

ODiNPred: comprehensive prediction of protein order and disorder

Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however, notoriously difficult to predict the degree of local flexibility within structured domains and the presence and nuances of localized rigidity within intrinsically disordered regions. To identify such instances, we used the CheZOD database, which encompasses accurate, balanced, and continuous-valued quantification of protein (dis)order at amino acid resolution based on NMR chemical shifts. To computationally forecast the spectrum of protein disorder in the most comprehensive manner possible, we constructed the sequence-based protein order/disorder predictor ODiNPred, trained on an expanded version of CheZOD. ODiNPred applies a deep neural network comprising 157 unique sequence features to 1325 protein sequences together with the experimental NMR chemical shift data. Cross-validation for 117 protein sequences shows that ODiNPred better predicts the continuous variation in order along the protein sequence, suggesting that contemporary predictors are limited by the quality of training data. The inclusion of evolutionary features reduces the performance gap between ODiNPred and its peers, but analysis shows that it retains greater accuracy for the more challenging prediction of intermediate disorder.

Exploring Protein Intrinsic Disorder with MobiDB

Nowadays, it is well established that many proteins or regions under physiological conditions lack a fixed three-dimensional structure and are intrinsically disordered. MobiDB is the main repository of protein disorder and mobility annotations, combining different data sources to provide an exhaustive overview of intrinsic disorder. MobiDB includes curated annotations from other databases, indirect disorder evidence from structural data, and disorder predictions from protein sequences. It provides an easy-to-use web server to visualize and explore disorder information. This chapter describes the data available in MobiDB, emphasizing how to use and access the intrinsic disorder data. MobiDB is available at URL http://mobidb.bio.unipd.it .

Systematic Discovery of Short Linear Motifs Decodes Calcineurin Phosphatase Signaling

Short linear motifs (SLiMs) drive dynamic protein-protein interactions essential for signaling, but sequence degeneracy and low binding affinities make them difficult to identify. We harnessed unbiased systematic approaches for SLiM discovery to elucidate the regulatory network of calcineurin (CN)/PP2B, the Ca²⁺-activated phosphatase that recognizes LxVP and PxIxIT motifs. In vitro proteome-wide detection of CN-binding peptides, in vivo SLiM-dependent proximity labeling, and in silico modeling of motif determinants uncovered unanticipated CN interactors, including NOTCH1, which we establish as a CN substrate. Unexpectedly, CN shows SLiM-dependent proximity to centrosomal and nuclear pore complex (NPC) proteins-structures where Ca²⁺ signaling is largely uncharacterized. CN dephosphorylates human and yeast NPC proteins and promotes accumulation of a nuclear transport reporter, suggesting conserved NPC regulation by CN. The CN network assembled here provides a resource to investigate Ca²⁺ and CN signaling and demonstrates synergy between experimental and computational methods, establishing a blueprint for examining SLiM-based networks.

Assessing predictors for new post translational modification sites: A case study on hydroxylation

Post-translational modification (PTM) sites have become popular for predictor development. However, with the exception of phosphorylation and a handful of other examples, PTMs suffer from a limited number of available training examples and sparsity in protein sequences. Here, proline hydroxylation is taken as an example to compare different methods and evaluate their performance on new experimentally determined sites. As a guide for effective experimental design, predictors require both high specificity and sensitivity. However, the self-reported performance may often not be indicative of prediction quality and detection of new sites is not guaranteed. We have benchmarked seven published hydroxylation site predictors on two newly constructed independent datasets. The self-reported performance is found to widely overestimate the real accuracy measured on independent datasets. No predictor performs better than random on new examples, indicating the refined models do not sufficiently generalize to detect new sites. The number of false positives is high and precision low, in particular for non-collagen proteins whose motifs are not conserved. As hydroxylation site predictors do not generalize for new data, caution is advised when using PTM predictors in the absence of independent evaluations, in particular for highly specific sites involved in signalling.

Machine learning methods are extensively used by biologists to design and interpret experiments. Predictors which take the only sequence as input are of particular interest due to the large amount of available sequence data and high self-reported performance. In this work, we evaluated post-translational modification (PTM) predictors for hydroxylation sites and found that they perform no better than random, in strong contrast to performances reported in their original publications. PTMs are chemical amino acid alterations providing the cell with conditional mechanisms to fine tune protein function, regulating complex biological processes such as signalling and cell cycle. Hydroxylation sites are a good PTM test case due to the availability of a range of predictors and an abundance of newly experimentally detected modification sites. Poor performances in our results highlight the overlooked problem of predicting PTMs when best practices are not followed and training data are likely incomplete. Experimentalists should be careful when using PTM predictors blindly and more independent assessments are needed to establish their usefulness in practice.

Alterations of the interactome of Bcl-2 proteins in breast cancer at the transcriptional, mutational and structural level

Apoptosis is an essential defensive mechanism against tumorigenesis. Proteins of the B-cell lymphoma-2 (Bcl-2) family regulate programmed cell death by the mitochondrial apoptosis pathway. In response to intracellular stress, the apoptotic balance is governed by interactions of three distinct subgroups of proteins; the activator/sensitizer BH3 (Bcl-2 homology 3)-only proteins, the pro-survival, and the pro-apoptotic executioner proteins. Changes in expression levels, stability, and functional impairment of pro-survival proteins can lead to an imbalance in tissue homeostasis. Their overexpression or hyperactivation can result in oncogenic effects. Pro-survival Bcl-2 family members carry out their function by binding the BH3 short linear motif of pro-apoptotic proteins in a modular way, creating a complex network of protein-protein interactions. Their dysfunction enables cancer cells to evade cell death. The critical role of Bcl-2 proteins in homeostasis and tumorigenesis, coupled with mounting insight in their structural properties, make them therapeutic targets of interest. A better understanding of gene expression, mutational profile, and molecular mechanisms of pro-survival Bcl-2 proteins in different cancer types, could help to clarify their role in cancer development and may guide advancement in drug discovery. Here, we shed light on the pro-survival Bcl-2 proteins in breast cancer using different bioinformatic approaches, linking -omics with structural data. We analyzed the changes in the expression of the Bcl-2 proteins and their BH3-containing interactors in breast cancer samples. We then studied, at the structural level, a selection of interactions, accounting for effects induced by mutations found in the breast cancer samples. We find two complexes between the up-regulated Bcl2A1 and two down-regulated BH3-only candidates (i.e., Hrk and Nr4a1) as targets associated with reduced apoptosis in breast cancer samples for future experimental validation. Furthermore, we predict L99R, M75R as damaging mutations altering protein stability, and Y120C as a possible allosteric mutation from an exposed surface to the BH3-binding site.

Performance of computational methods for the evaluation of pericentriolar material 1 missense variants in CAGI-5

The CAGI-5 pericentriolar material 1 (PCM1) challenge aimed to predict the effect of 38 transgenic human missense mutations in the PCM1 protein implicated in schizophrenia. Participants were provided with 16 benign variants (negative controls), 10 hypomorphic, and 12 loss of function variants. Six groups participated and were asked to predict the probability of effect and standard deviation associated to each mutation. Here, we present the challenge assessment. Prediction performance was evaluated using different measures to conclude in a final ranking which highlights the strengths and weaknesses of each group. The results show a great variety of predictions where some methods performed significantly better than others. Benign variants played an important role as negative controls, highlighting predictors biased to identify disease phenotypes. The best predictor, Bromberg lab, used a neural-network-based method able to discriminate between neutral and non-neutral single nucleotide polymorphisms. The CAGI-5 PCM1 challenge allowed us to evaluate the state of the art techniques for interpreting the effect of novel variants for a difficult target protein.

MobiDB 3.0: more annotations for intrinsic disorder, conformational diversity and interactions in proteins

The MobiDB (URL: mobidb.bio.unipd.it) database of protein disorder and mobility annotations has been significantly updated and upgraded since its last major renewal in 2014. Several curated datasets for intrinsic disorder and folding upon binding have been integrated from specialized databases. The indirect evidence has also been expanded to better capture information available in the PDB, such as high temperature residues in X-ray structures and overall conformational diversity. Novel nuclear magnetic resonance chemical shift data provides an additional experimental information layer on conformational dynamics. Predictions have been expanded to provide new types of annotation on backbone rigidity, secondary structure preference and disordered binding regions. MobiDB 3.0 contains information for the complete UniProt protein set and synchronization has been improved by covering all UniParc sequences. An advanced search function allows the creation of a wide array of custom-made datasets for download and further analysis. A large amount of information and cross-links to more specialized databases are intended to make MobiDB the central resource for the scientific community working on protein intrinsic disorder and mobility.

SODA: prediction of protein solubility from disorder and aggregation propensity

Solubility is an important, albeit not well understood, feature determining protein behavior. It is of paramount importance in protein engineering, where similar folded proteins may behave in very different ways in solution. Here we present SODA, a novel method to predict the changes of protein solubility based on several physico-chemical properties of the protein. SODA uses the propensity of the protein sequence to aggregate as well as intrinsic disorder, plus hydrophobicity and secondary structure preferences to estimate changes in solubility. It has been trained and benchmarked on two different datasets. The comparison to other recently published methods shows that SODA has state-of-the-art performance and is particularly well suited to predict mutations decreasing solubility. The method is fast, returning results for single mutations in seconds. A usage example estimating the full repertoire of mutations for a human germline antibody highlights several solubility hotspots on the surface. The web server, complete with RESTful interface and extensive help, can be accessed from URL: http://protein.bio.unipd.it/soda.

Structural and functional impact of non-synonymous SNPs in the CST complex subunit TEN1: structural genomics approach

TEN1 protein is a key component of CST complex, implicated in maintaining the telomere homeostasis, and provides stability to the eukaryotic genome. Mutations in TEN1 gene have higher chances of deleterious impact; thus, interpreting the number of mutations and their consequential impact on the structure, stability, and function is essentially important. Here, we have investigated the structural and functional consequences of nsSNPs in the TEN1 gene. A wide array of sequence- and structure-based computational prediction tools were employed to identify the effects of 78 nsSNPs on the structure and function of TEN1 protein and to identify the deleterious nsSNPs. These deleterious or destabilizing nsSNPs are scattered throughout the structure of TEN1. However, major mutations were observed in the α1-helix (12–16 residues) and β5-strand (88–96 residues). We further observed that mutations at the C-terminal region were having higher tendency to form aggregate. In-depth structural analysis of these mutations reveals that the pathogenicity of these mutations are driven mainly through larger structural changes because of alterations in non-covalent interactions. This work provides a blueprint to pinpoint the possible consequences of pathogenic mutations in the CST complex subunit TEN1.

Genotype-phenotype relations of the von Hippel-Lindau tumor suppressor inferred from a large-scale analysis of disease mutations and interactors

Familiar cancers represent a privileged point of view for studying the complex cellular events inducing tumor transformation. Von Hippel-Lindau syndrome, a familiar predisposition to develop cancer is a clear example. Here, we present our efforts to decipher the role of von Hippel-Lindau tumor suppressor protein (pVHL) in cancer insurgence. We collected high quality information about both pVHL mutations and interactors to investigate the association between patient phenotypes, mutated protein surface and impaired interactions. Our data suggest that different phenotypes correlate with localized perturbations of the pVHL structure, with specific cell functions associated to different protein surfaces. We propose five different pVHL interfaces to be selectively involved in modulating proteins regulating gene expression, protein homeostasis as well as to address extracellular matrix (ECM) and ciliogenesis associated functions. These data were used to drive molecular docking of pVHL with its interactors and guide Petri net simulations of the most promising alterations. We predict that disruption of pVHL association with certain interactors can trigger tumor transformation, inducing metabolism imbalance and ECM remodeling. Collectively taken, our findings provide novel insights into VHL-associated tumorigenesis. This highly integrated in silico approach may help elucidate novel treatment paradigms for VHL disease.

Cancer is generally caused by a series of mutations accumulating over time in a healthy tissue, which becomes re-programmed to proliferate at the expense of the hosting organism. This process is difficult to follow and understand as events in a multitude of different genes can lead to similar outcomes without apparent cause. The von Hippel-Lindau (VHL) tumor suppressor is one of the few genes harboring a familiar cancer syndrome, i.e. VHL mutations are known to cause a predictable series of events leading cancer in the kidneys and a few selected other tissues. This article describes a large-scale analysis to relate known VHL mutations to specific cancer pathways by looking at the molecular interactions. Different cancer types appear to be caused by mutations changing the surface of specific parts of the VHL protein. By looking at the VHL interactors involved, it is therefore possible to identify other candidate genes for mutations leading to very similar cancer types.

Protein Secondary Structure Determination (PSSD): A New and Simple Approach

Background:

Our present investigation was conducted to explore the computational algorithm for the protein secondary structure prediction as per the property of evolutionary transient and large number (each 50) of homologous mesophilic-thermophilic proteins. </P><P> Objectives: These mesophilic-thermophilic proteins were used for numerical measurement of helix-sheetcoil and turn tendency for which each amino-acid residue is screened to build up the propensity-table.

Methods:

In the current study, two different propensity windows have been introduced that allowed predicting the secondary structure of protein more than 80% accuracy.

Results:

Using this propensity matrix and dynamic algorithm-based programme, a significant and decisive outcome in the determination of protein (both thermophilic and mesophilic) secondary structure was noticed over the previous algorithm based programme. It was demonstrated after comparison with other standard methods including DSSP adopted by PDB with the help of multiple comparisons ANOVA and Dunnett’s t-test.

Conclusion:

The PSSD is of great importance in the prediction of structural features of any unknown, unresolved proteins. It is also useful in the studies of proteins structure-function relationship.

Order in Disorder as Observed by the "Hydrophobic Cluster Analysis" of Protein Sequences

Hydrophobic cluster analysis (HCA) is an original approach for protein sequence analysis, which provides access to the foldable repertoire of the protein universe, including yet unannotated protein segments ("dark proteome"). Foldable segments correspond to ordered regions, as well as to intrinsically disordered regions (IDRs) undergoing disorder to order transitions. In this review, how HCA can be used to give insight into this last category of foldable segments is illustrated, with examples matching known 3D structures. After reviewing the HCA principles, examples of short foldable segments are given, which often contain short linear motifs, typically matching hydrophobic clusters. These segments become ordered upon contact with partners, with secondary structure preferences generally corresponding to those observed in the 3D structures within the complexes. Such small foldable segments are sometimes larger than the segments of known 3D structures, including flanking hydrophobic clusters that may be critical for interaction specificity or regulation, as well as intervening sequences allowing fuzziness. Cases of larger conditionally disordered domains are also presented, with lower density in hydrophobic clusters than well-folded globular domains or with exposed hydrophobic patches, which are stabilized by interaction with partners.

The clinical spectrum of CASQ1-related myopathy

OBJECTIVE

To identify and characterize patients with calsequestrin 1 (CASQ1)-related myopathy.

METHODS

Patients selected according to histopathologic features underwent CASQ1 genetic screening. CASQ1-mutated patients were clinically evaluated and underwent muscle MRI. Vacuole morphology and vacuolated fiber type were characterized.

RESULTS

Twenty-two CASQ1-mutated patients (12 families) were identified, 21 sharing the previously described founder mutation (p.Asp244Gly) and 1 with the p.Gly103Asp mutation. Patients usually presented in the sixth decade with exercise intolerance and myalgias and later developed mild to moderate, slowly progressive proximal weakness with quadriceps atrophy and scapular winging. Muscle MRI (n = 11) showed a recurrent fibrofatty substitution pattern. Three patients presented subclinical cardiac abnormalities. Muscle histopathology in patients with p.Asp244Gly showed vacuoles in type II fibers appearing empty in hematoxylin-eosin, Gomori, and nicotinamide adenine dinucleotide (NADH) tetrazolium reductase stains but strongly positive for sarcoplasmic reticulum proteins. The muscle histopathology of p.Gly103Asp mutation was different, showing also NADH-positive accumulation consistent with tubular aggregates.

CONCLUSIONS

We report the clinical and molecular details of the largest cohort of CASQ1-mutated patients. A possible heart involvement is presented, further expanding the phenotype of the disease. One mutation is common due to a founder effect, but other mutations are possible. Because of a paucity of symptoms, it is likely that CASQ1 mutations may remain undiagnosed if a muscle biopsy is not performed.

Calmodulin Enhances Cryptochrome Binding to INAD in Drosophila Photoreceptors

Light is the main environmental stimulus that synchronizes the endogenous timekeeping systems in most terrestrial organisms. Drosophila cryptochrome (dCRY) is a light-responsive flavoprotein that detects changes in light intensity and wavelength around dawn and dusk. We have previously shown that dCRY acts through Inactivation No Afterpotential D (INAD) in a light-dependent manner on the Signalplex, a multiprotein complex that includes visual-signaling molecules, suggesting a role for dCRY in fly vision. Here, we predict and demonstrate a novel Ca²⁺-dependent interaction between dCRY and calmodulin (CaM). Through yeast two hybrid, coimmunoprecipitation (Co-IP), nuclear magnetic resonance (NMR) and calorimetric analyses we were able to identify and characterize a CaM binding motif in the dCRY C-terminus. Similarly, we also detailed the CaM binding site of the scaffold protein INAD and demonstrated that CaM bridges dCRY and INAD to form a ternary complex in vivo. Our results suggest a process whereby a rapid dCRY light response stimulates an interaction with INAD, which can be further consolidated by a novel mechanism regulated by CaM.

Arginine 107 of yeast ATP synthase subunit g mediates sensitivity of the mitochondrial permeability transition to phenylglyoxal

Modification with arginine-specific glyoxals modulates the permeability transition (PT) of rat liver mitochondria, with inhibitory or inducing effects that depend on the net charge of the adduct(s). Here, we show that phenylglyoxal (PGO) affects the PT in a species-specific manner (inhibition in mouse and yeast, induction in human and Drosophila mitochondria). Following the hypotheses (i) that the effects are mediated by conserved arginine(s) and (ii) that the PT is mediated by the F-ATP synthase, we have narrowed the search to 60 arginines. Most of these residues are located in subunits α, β, γ, ϵ, a, and c and were excluded because PGO modification did not significantly affect enzyme catalysis. On the other hand, yeast mitochondria lacking subunit g or bearing a subunit g R107A mutation were totally resistant to PT inhibition by PGO. Thus, the effect of PGO on the PT is specifically mediated by Arg-107, the only subunit g arginine that has been conserved across species. These findings are evidence that the PT is mediated by F-ATP synthase.

The Disordered C-Terminus of Yeast Hsf1 Contains a Cryptic Low-Complexity Amyloidogenic Region

Response mechanisms to external stress rely on networks of proteins able to activate specific signaling pathways to ensure the maintenance of cell proteostasis. Many of the proteins mediating this kind of response contain intrinsically disordered regions, which lack a defined structure, but still are able to interact with a wide range of clients that modulate the protein function. Some of these interactions are mediated by specific short sequences embedded in the longer disordered regions. Because the physicochemical properties that promote functional and abnormal interactions are similar, it has been shown that, in globular proteins, aggregation-prone and binding regions tend to overlap. It could be that the same principle applies for disordered protein regions. In this context, we show here that a predicted low-complexity interacting region in the disordered C-terminus of the stress response master regulator heat shock factor 1 (Hsf1) protein corresponds to a cryptic amyloid region able to self-assemble into fibrillary structures resembling those found in neurodegenerative disorders.

PhytoTypeDB: a database of plant protein inter-cultivar variability and function

Despite a fast-growing number of available plant genomes, available computational resources are poorly integrated and provide only limited access to the underlying data. Most existing databases focus on DNA/RNA data or specific gene families, with less emphasis on protein structure, function and variability. In particular, despite the economic importance of many plant accessions, there are no straightforward ways to retrieve or visualize information on their differences. To fill this gap, we developed PhytoTypeDB (http://phytotypedb.bio.unipd.it/), a scalable database containing plant protein annotations and genetic variants from resequencing of different accessions. The database content is generated by an integrated pipeline, exploiting state-of-the-art methods for protein characterization requiring only the proteome reference sequence and variant calling files. Protein names for unknown proteins are inferred by homology for over 95% of the entries. Single-nucleotide variants are visualized along with protein annotation in a user-friendly web interface. The server offers an effective querying system, which allows to compare variability among different species and accessions, to generate custom data sets based on shared functional features or to perform sequence searches. A documented set of exposed RESTful endpoints make the data accessible programmatically by third-party clients.

Novel interactions of the von Hippel-Lindau (pVHL) tumor suppressor with the CDKN1 family of cell cycle inhibitors

Germline inactivation of the von Hippel-Lindau (VHL) tumor suppressor predisposes patients to develop different highly vascularized cancers. pVHL targets the hypoxia-inducible transcription factor (HIF-1α) for degradation, modulating the activation of various genes involved in hypoxia response. Hypoxia plays a relevant role in regulating cell cycle progression, inducing growth arrest in cells exposed to prolonged oxygen deprivation. However, the exact molecular details driving this transition are far from understood. Here, we present novel interactions between pVHL and the cyclin-dependent kinase inhibitor family CDKN1 (p21, p27 and p57). Bioinformatics analysis, yeast two-hybrid screening and co-immunoprecipitation assays were used to predict, dissect and validate the interactions. We found that the CDKN1 proteins share a conserved region mimicking the HIF-1α motif responsible for pVHL binding. Intriguingly, a p27 site-specific mutation associated to cancer is shown to modulate this novel interaction. Our findings suggest a new connection between the pathways regulating hypoxia and cell cycle progression.