Trend of amino acid composition of proteins of different taxa

Decoding the nexus: branched-chain amino acids and their connection with sleep, circadian rhythms, and cardiometabolic health

The sleep-wake cycle stands as an integrative process essential for sustaining optimal brain function and, either directly or indirectly, overall body health, encompassing metabolic and cardiovascular well-being. Given the heightened metabolic activity of the brain, there exists a considerable demand for nutrients in comparison to other organs. Among these, the branched-chain amino acids, comprising leucine, isoleucine, and valine, display distinctive significance, from their contribution to protein structure to their involvement in overall metabolism, especially in cerebral processes. Among the first amino acids that are released into circulation post-food intake, branched-chain amino acids assume a pivotal role in the regulation of protein synthesis, modulating insulin secretion and the amino acid sensing pathway of target of rapamycin. Branched-chain amino acids are key players in influencing the brain's uptake of monoamine precursors, competing for a shared transporter. Beyond their involvement in protein synthesis, these amino acids contribute to the metabolic cycles of γ-aminobutyric acid and glutamate, as well as energy metabolism. Notably, they impact GABAergic neurons and the excitation/inhibition balance. The rhythmicity of branched-chain amino acids in plasma concentrations, observed over a 24-hour cycle and conserved in rodent models, is under circadian clock control. The mechanisms underlying those rhythms and the physiological consequences of their disruption are not fully understood. Disturbed sleep, obesity, diabetes, and cardiovascular diseases can elevate branched-chain amino acid concentrations or modify their oscillatory dynamics. The mechanisms driving these effects are currently the focal point of ongoing research efforts, since normalizing branched-chain amino acid levels has the ability to alleviate the severity of these pathologies. In this context, the Drosophila model, though underutilized, holds promise in shedding new light on these mechanisms. Initial findings indicate its potential to introduce novel concepts, particularly in elucidating the intricate connections between the circadian clock, sleep/wake, and metabolism. Consequently, the use and transport of branched-chain amino acids emerge as critical components and orchestrators in the web of interactions across multiple organs throughout the sleep/wake cycle. They could represent one of the so far elusive mechanisms connecting sleep patterns to metabolic and cardiovascular health, paving the way for potential therapeutic interventions.

Di-Tyrosine Cross-Linking of Elastin-Like Polypeptides through Ruthenium Photoreaction To Form Scaffolds: Fine Tuning Mechanical Properties and Improving Cytocompatibility

Ensuring that the mechanical properties of tissue engineering scaffolds align with those of the target tissues is crucial for their successful integration and functional performance. Tyrosine-tyrosine cross-links are found in nature in numerous proteins including resilin that exhibit enhanced toughness and energy storage capacity. Herein, we investigated the potential of tuning the mechanical properties of scaffolds made from elastin-like polypeptides (ELPs) containing tyrosine residues. Ruthenium-based photoreaction was used to form tyrosine cross-links. To enhance the cytocompatibility of the ELP scaffold, a continuous mode of washing was developed to remove residual ruthenium from the scaffolds. The continuous mode of washing was significantly superior in removing ruthenium and did so in a significantly shorter time as compared to batch washing and the conventional semibatch washing (also called dialysis washing). The range of storage moduli of the fabricated scaffolds spanned tens of Pa to hundreds of kPa. Human fibroblast cells were found to grow in the scaffolds and proliferate. Overall, this work offers a rationale for further developing tyrosine cross-linked ELPs for a broad range of tissue engineering applications.

Genetically Predicted Leucine Level Mediates Association Between CD4/CD8br T Lymphocytes and Insomnia

Immune and metabolic factors play an important role in the onset and development of insomnia. This study aimed to investigate the causal relationship between insomnia and immune cells and metabolites. Data for 731 immune cell phenotypes, 1400 metabolites, and insomnia in this study were obtained from the GWAS open-access database. Two-way Mendelian randomization was used to (1) detect the causal relationship between immune cells and insomnia and (2) identify potential mediating metabolites. Mendelian randomization analysis identified eight immune cell phenotypes with a causal relationship to insomnia, and two immune cell phenotypes were protective factors for insomnia, namely CD8br %T cells and CD80 on CD62L + myeloid dendritic cells. The other six immune cell phenotypes were risk factors for insomnia, i.e., CD4/CD8br, CD16-CD56 on NKT, CCR2 on myeloid dendritic cells, CD40 on monocytes, CD38 on CD3-CD19-, and CD25 on CD45RA + CD4 not Treg. Further Mendelian randomization revealed 11 metabolites that were causally related to insomnia. Five metabolites were protective factors for insomnia, i.e., 3-hydroxy-3-methylglutarate, cholate, dodecanedioate, N-formylmethionine, and x-26054. Six metabolites were risk factors for insomnia, 3-amino-2-piperidone, 6-oxopiperdine-2-carboxylate, caffeine to theophylline ratio, leucine, maltose, and x-24736. In addition, our analysis showed that leucine mediated the association between CD4/CD8br and insomnia. From genetic information, we confirmed the causal relationship between insomnia, eight immune cell phenotypes, and eleven metabolite levels. Notably, we found a relationship between leucine-mediated CD4/CD8br and insomnia, providing evidence supporting the causal relationship between immune cell and insomnia, with plasma metabolites serving as mediators.

What Can Be Learned by Knowing Only the Amino Acid Composition of Proteins?

The amino acid composition of proteins depends on many factors. It varies in organisms that are distant in taxonomic position. The amino acid composition of proteins depends on the localization of proteins in cells and tissues and the structure of proteins. The question arises: is it possible to separate different proteomes using only the amino acid composition of proteins? Is it possible to determine, considering only its amino acid composition, to what structural class the protein under study will belong? We have developed a method and a measure that maximally separate two sets of proteins. As a result, we assign each protein an R-value, positive values of which are more characteristic of the first set, and negative ones-of the second. By studying the distribution of R in two sets, we can determine how much these sets differ in composition. Also, when examining a new protein, we can determine if it is more similar to the first set or the second. In this paper, we show that using only amino acid composition, it is possible to separate sets of proteins belonging to different organisms, as well as proteins that differ in function or structure. In all cases, we assign to proteins a measure R that maximally separates the studied sets. This approach can be further used to annotate proteins with unknown functions.

Self-assembly of peptide nanocapsules by a solvent concentration gradient

Biological systems can create materials with intricate structures and specialized functions. In comparison, precise control of structures in human-made materials has been challenging. Here we report on insect cuticle peptides that spontaneously form nanocapsules through a single-step solvent exchange process, where the concentration gradient resulting from the mixing of water and acetone drives the localization and self-assembly of the peptides into hollow nanocapsules. The underlying driving force is found to be the intrinsic affinity of the peptides for a particular solvent concentration, while the diffusion of water and acetone creates a gradient interface that triggers peptide localization and self-assembly. This gradient-mediated self-assembly offers a transformative pathway towards simple generation of drug delivery systems based on peptide nanocapsules.

Omics data analysis reveals the system-level constraint on cellular amino acid composition

Proteins play a pivotal role in coordinating the functions of organisms, essentially governing their traits, as the dynamic arrangement of diverse amino acids leads to a multitude of folded configurations within peptide chains. Despite dynamic changes in amino acid composition of an individual protein (referred to as AAP) and great variance in protein expression levels under different conditions, our study, utilizing transcriptomics data from four model organisms uncovers surprising stability in the overall amino acid composition of the total cellular proteins (referred to as AACell). Although this value may vary between different species, we observed no significant differences among distinct strains of the same species. This indicates that organisms enforce system-level constraints to maintain a consistent AACell, even amid fluctuations in AAP and protein expression. Further exploration of this phenomenon promises insights into the intricate mechanisms orchestrating cellular protein expression and adaptation to varying environmental challenges.

Understanding the Energy Landscape of Intrinsically Disordered Protein Ensembles

A substantial portion of various organisms' proteomes comprises intrinsically disordered proteins (IDPs) that lack a defined three-dimensional structure. These IDPs exhibit a diverse array of conformations, displaying remarkable spatiotemporal heterogeneity and exceptional conformational flexibility. Characterizing the structure or structural ensemble of IDPs presents significant conceptual and methodological challenges owing to the absence of a well-defined native structure. While databases such as the Protein Ensemble Database (PED) provide IDP ensembles obtained through a combination of experimental data and molecular modeling, the absence of reaction coordinates poses challenges in comprehensively understanding pertinent aspects of the system. In this study, we leverage the energy landscape visualization method (JCTC, 6482, 2019) to scrutinize four IDP ensembles sourced from PED. ELViM, a methodology that circumvents the need for a priori reaction coordinates, aids in analyzing the ensembles. The specific IDP ensembles investigated are as follows: two fragments of nucleoporin (NUL: 884-993 and NUS: 1313-1390), yeast sic 1 N-terminal (1-90), and the N-terminal SH3 domain of Drk (1-59). Utilizing ELViM enables the comprehensive validation of ensembles, facilitating the detection of potential inconsistencies in the sampling process. Additionally, it allows for identifying and characterizing the most prevalent conformations within an ensemble. Moreover, ELViM facilitates the comparative analysis of ensembles obtained under diverse conditions, thereby providing a powerful tool for investigating the functional mechanisms of IDPs.

The Listeria monocytogenes persistence factor ClpL is a potent stand-alone disaggregase

Heat stress can cause cell death by triggering the aggregation of essential proteins. In bacteria, aggregated proteins are rescued by the canonical Hsp70/AAA+ (ClpB) bi-chaperone disaggregase. Man-made, severe stress conditions applied during, e.g., food processing represent a novel threat for bacteria by exceeding the capacity of the Hsp70/ClpB system. Here, we report on the potent autonomous AAA+ disaggregase ClpL from Listeria monocytogenes that provides enhanced heat resistance to the food-borne pathogen enabling persistence in adverse environments. ClpL shows increased thermal stability and enhanced disaggregation power compared to Hsp70/ClpB, enabling it to withstand severe heat stress and to solubilize tight aggregates. ClpL binds to protein aggregates via aromatic residues present in its N-terminal domain (NTD) that adopts a partially folded and dynamic conformation. Target specificity is achieved by simultaneous interactions of multiple NTDs with the aggregate surface. ClpL shows remarkable structural plasticity by forming diverse higher assembly states through interacting ClpL rings. NTDs become largely sequestered upon ClpL ring interactions. Stabilizing ring assemblies by engineered disulfide bonds strongly reduces disaggregation activity, suggesting that they represent storage states.

Experimental methods to study the structure and dynamics of intrinsically disordered regions in proteins

Eukaryotic proteins often feature long stretches of amino acids that lack a well-defined three-dimensional structure and are referred to as intrinsically disordered proteins (IDPs) or regions (IDRs). Although these proteins challenge conventional structure-function paradigms, they play vital roles in cellular processes. Recent progress in experimental techniques, such as NMR spectroscopy, single molecule FRET, high speed AFM and SAXS, have provided valuable insights into the biophysical basis of IDP function. This review discusses the advancements made in these techniques particularly for the study of disordered regions in proteins. In NMR spectroscopy new strategies such as 13C detection, non-uniform sampling, segmental isotope labeling, and rapid data acquisition methods address the challenges posed by spectral overcrowding and low stability of IDPs. The importance of various NMR parameters, including chemical shifts, hydrogen exchange rates, and relaxation measurements, to reveal transient secondary structures within IDRs and IDPs are presented. Given the high flexibility of IDPs, the review outlines NMR methods for assessing their dynamics at both fast (ps-ns) and slow (μs-ms) timescales. IDPs exert their functions through interactions with other molecules such as proteins, DNA, or RNA. NMR-based titration experiments yield insights into the thermodynamics and kinetics of these interactions. Detailed study of IDPs requires multiple experimental techniques, and thus, several methods are described for studying disordered proteins, highlighting their respective advantages and limitations. The potential for integrating these complementary techniques, each offering unique perspectives, is explored to achieve a comprehensive understanding of IDPs.

Improving enzyme functional annotation by integrating in vitro and in silico approaches: The example of histidinol phosphate phosphatases

Advances in sequencing technologies have led to a rapid growth of public protein sequence databases, whereby the fraction of proteins with experimentally verified function continuously decreases. This problem is currently addressed by automated functional annotations with computational tools, which however lack the accuracy of experimental approaches and are susceptible to error propagation. Here, we present an approach that combines the efficiency of functional annotation by in silico methods with the rigor of enzyme characterization in vitro. First, a thorough experimental analysis of a representative enzyme of a group of homologues is performed which includes a focused alanine scan of the active site to determine a fingerprint of function-determining residues. In a second step, this fingerprint is used in combination with a sequence similarity network to identify putative isofunctional enzymes among the homologues. Using this approach in a proof-of-principle study, homologues of the histidinol phosphate phosphatase (HolPase) from Pseudomonas aeruginosa, many of which were annotated as phosphoserine phosphatases, were predicted to be HolPases. This functional annotation of the homologues was verified by in vitro testing of several representatives and an analysis of the occurrence of annotated HolPases in the corresponding phylogenetic groups. Moreover, the application of the same approach to the homologues of the HolPase from the archaeon Nitrosopumilus maritimus, which is not related to the HolPase from P. aeruginosa and was newly discovered in the course of this work, led to the annotation of the putative HolPase from various archaeal species.

1,2,3-Triazoles in Biomolecular Crystallography: A Geometrical Data-Mining Approach

The 1,2,3-triazole scaffold has become very attractive to identify new chemical entities in drug discovery projects. Despite the widespread use of click chemistry to synthesize numerous 123Ts, there are few drugs on the market that incorporate this scaffold as a substructure. To investigate the true potential of 123Ts in protein-ligand interactions, we examined the noncovalent interactions between the 1,2,3-triazole ring and amino acids in protein-ligand cocrystals using a geometrical approach. For this purpose, we constructed a nonredundant database of 220 PDB IDs from available 123T-protein cocrystal structures. Subsequently, using the Protein Ligand Interaction Profiler web platform (PLIP), we determined whether 1,2,3-triazoles primarily act as linkers or if they can be considered interactive scaffolds. We then manually analyzed the geometrical descriptors from 333 interactions between 1,4-disubstituted 123T rings and amino acid residues in proteins. This study demonstrates that 1,2,3-triazoles exhibit diverse preferred interactions with amino acids, which contribute to protein-ligand binding.

The role of tandem repeats in bacterial functional amyloids

Repetitivity and modularity of proteins are two related notions incorporated into multiple evolutionary concepts. We discuss whether they may also be essential for functional amyloids. Amyloids are proteins that create very regular and usually highly insoluble fibrils, which are often associated with neurodegeneration. However, recent discoveries showed that amyloid structure of a protein could also be beneficial and desired, e.g., to promote cell adhesion. Functional amyloids are proteins which differ in their characteristics from pathological amyloids, so that the fibril formation could be more under control of an organism. We propose that repeats in the sequence could regulate the aggregation propensity of these proteins. The inclusion of multiple symmetric interactions, due to the presence of the repeats, could be supporting and strengthening the desirable structural properties of functional amyloids. Our results show that tandem repeats in bacterial functional amyloids have a distinct characteristic. The pattern of repeats supports the appropriate level of fibril formation and better controllability of fibril stability. The repeats tend to be more imperfect, which attenuates excessive aggregation propensity. Their desired structure and function are also reinforced by their amino acid profile. Although in the study we focused on bacterial functional amyloids, due to their importance in biofilm formation, we propose that similar mechanisms could be employed in other functional amyloids which are designed by evolution to aggregate in a desirable manner, but not necessarily in pathological amyloids.

Computational Analysis Predicts Correlations among Amino Acids in SARS-CoV-2 Proteomes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious global challenge requiring urgent and permanent therapeutic solutions. These solutions can only be engineered if the patterns and rate of mutations of the virus can be elucidated. Predicting mutations and the structure of proteins based on these mutations have become necessary for early drug and vaccine design purposes in anticipation of future viral mutations. The amino acid composition (AAC) of proteomes and individual viral proteins provide avenues for exploitation since AACs have been previously used to predict structure, shape and evolutionary rates. Herein, the frequency of amino acid residues found in 1637 complete proteomes belonging to 11 SARS-CoV-2 variants/lineages were analyzed. Leucine is the most abundant amino acid residue in the SARS-CoV-2 with an average AAC of 9.658% while tryptophan had the least abundance of 1.11%. The AAC and ranking of lysine and glycine varied in the proteome. For some variants, glycine had higher frequency and AAC than lysine and vice versa in other variants. Tryptophan was also observed to be the most intolerant to mutation in the various proteomes for the variants used. A correlogram revealed a very strong correlation of 0.999992 between B.1.525 (Eta) and B.1.526 (Iota) variants. Furthermore, isoleucine and threonine were observed to have a very strong negative correlation of -0.912, while cysteine and isoleucine had a very strong positive correlation of 0.835 at p < 0.001. Shapiro-Wilk normality test revealed that AAC values for all the amino acid residues except methionine showed no evidence of non-normality at p < 0.05. Thus, AACs of SARS-CoV-2 variants can be predicted using probability and z-scores. AACs may be beneficial in classifying viral strains, predicting viral disease types, members of protein families, protein interactions and for diagnostic purposes. They may also be used as a feature along with other crucial factors in machine-learning based algorithms to predict viral mutations. These mutation-predicting algorithms may help in developing effective therapeutics and vaccines for SARS-CoV-2.

Arg/Lys-containing IDRs are cryptic binding domains for ATP and nucleic acids that interplay to modulate LLPS

Most membrane-less organelles (MLOs) formed by LLPS contain both nucleic acids and IDR-rich proteins. Currently while IDRs are well-recognized to drive LLPS, nucleic acids are thought to exert non-specific electrostatic/salt effects. TDP-43 functions by binding RNA/ssDNA and its LLPS was characterized without nucleic acids to be driven mainly by PLD-oligomerization, which may further transit into aggregation characteristic of various neurodegenerative diseases. Here by NMR, we discovered unexpectedly for TDP-43 PLD: 1) ssDNAs drive and then dissolve LLPS by multivalently and specifically binding Arg/Lys. 2) LLPS is driven by nucleic-acid-binding coupled with PLD-oligomerization. 3) ATP and nucleic acids universally interplay in modulating LLPS by competing for binding Arg/Lys. However, the unique hydrophobic region within PLD renders LLPS to exaggerate into aggregation. The study not only unveils the first residue-resolution mechanism of the nucleic-acid-driven LLPS of TDP-43 PLD, but also decodes a general principle that not just TDP-43 PLD, all Arg/Lys-containing IDRs are cryptic nucleic-acid-binding domains that may phase separate upon binding nucleic acids. Strikingly, ATP shares a common mechanism with nucleic acids in binding IDRs, thus emerging as a universal mediator for interactions between IDRs and nucleic acids, which may underlie previously-unrecognized roles of ATP at mM in physiology and pathology.

Evolution of an Iron-Detoxifying Protein: Eukaryotic and Rickettsia Frataxins Contain a Conserved Site Which Is Not Present in Their Bacterial Homologues

Friedreich's ataxia is a neurodegenerative disease caused by mutations in the frataxin gene. Frataxin homologues, including bacterial CyaY proteins, can be found in most species and play a fundamental role in mitochondrial iron homeostasis, either promoting iron assembly into metaloproteins or contributing to iron detoxification. While several lines of evidence suggest that eukaryotic frataxins are more effective than bacterial ones in iron detoxification, the residues involved in this gain of function are unknown. In this work, we analyze conservation of amino acid sequence and protein structure among frataxins and CyaY proteins to identify four highly conserved residue clusters and group them into potential functional clusters. Clusters 1, 2, and 4 are present in eukaryotic frataxins and bacterial CyaY proteins. Cluster 3, containing two serines, a tyrosine, and a glutamate, is only present in eukaryotic frataxins and on CyaY proteins from the Rickettsia genus. Residues from cluster 3 are blocking a small cavity of about 40 Å present in E. coli's CyaY. The function of this cluster is unknown, but we hypothesize that its tyrosine may contribute to prevent formation of reactive oxygen species during iron detoxification. This cluster provides an example of gain of function during evolution in a protein involved in iron homeostasis, as our results suggests that Cluster 3 was present in the endosymbiont ancestor of mitochondria and was conserved in eukaryotic frataxins.

Labelling fish diets with 15 N -Leucine for monitoring feed consumption and bio-distribution in Atlantic salmon

Feeding represents 50-70% of the cost of production in salmon farming, higher than any other animal farm. The improvement of this percentage is challenging as the food is thrown into the fish tank, there is no quantification of the amount of food that is consumed by the fish. In consequence, it is difficult to adjust the food composition making it more nutritive or promoting food consumption by fish. In this study, to investigate food consumption, bio-distribution and food residues, leucine containing 15 N (a stable isotope of nitrogen) was used to label the fish food. Atlantic salmon (Salmo salar) weighing 100-120 g were maintained in 30 L tanks at a density of 14 kg/m3 . Fishes were fed daily at 1% of the fish weight with pellet labelled with 15 N-leucine. The 15 N incorporation was determined 14 hours after the feeding in all the fish organs. Results showed that 14 hours after the administration of a single dose of labelled food to Atlantic salmon enables the detection of the tracer in the whole organism allowing determining the food consumption. Through the analysis of nitrogen use efficiency (NUE), we showed that the trunk, pyloric caeca and head incorporate the highest level of the marker (72.7, 8.7 and 5.7%, respectively). This methodology would permit monitoring feeding to minimize food loss, improve administration methodologies or select the preferred foods for the fish, among others to reduce production costs.

Intrinsically Disordered Proteins: Critical Components of the Wetware

Despite the wealth of knowledge gained about intrinsically disordered proteins (IDPs) since their discovery, there are several aspects that remain unexplored and, hence, poorly understood. A living cell is a complex adaptive system that can be described as a wetware─a metaphor used to describe the cell as a computer comprising both hardware and software and attuned to logic gates─capable of "making" decisions. In this focused Review, we discuss how IDPs, as critical components of the wetware, influence cell-fate decisions by wiring protein interaction networks to keep them minimally frustrated. Because IDPs lie between order and chaos, we explore the possibility that they can be modeled as attractors. Further, we discuss how the conformational dynamics of IDPs manifests itself as conformational noise, which can potentially amplify transcriptional noise to stochastically switch cellular phenotypes. Finally, we explore the potential role of IDPs in prebiotic evolution, in forming proteinaceous membrane-less organelles, in the origin of multicellularity, and in protein conformation-based transgenerational inheritance of acquired characteristics. Together, these ideas provide a new conceptual framework to discern how IDPs may perform critical biological functions despite their lack of structure.

Tracking the amino acid changes of spike proteins across diverse host species of severe acute respiratory syndrome coronavirus 2

Knowledge of the host-specific properties of the spike protein is of crucial importance to understand the adaptability of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) to infect multiple species and alter transmissibility, particularly in humans. Here, we propose a spike protein predictor SPIKES incorporating with an inheritable bi-objective combinatorial genetic algorithm to identify the biochemical properties of spike proteins and determine their specificity to human hosts. SPIKES identified 20 informative physicochemical properties of the spike protein, including information measures for alpha helix and relative mutability, and amino acid and dipeptide compositions, which have shown compositional difference at the amino acid sequence level between human and diverse animal coronaviruses. We suggest that alterations of these amino acids between human and animal coronaviruses may provide insights into the development and transmission of SARS-CoV-2 in human and other species and support the discovery of targeted antiviral therapies.

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Differences exist in the amino acids within the S protein of diverse host species CoVs

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We developed SPIKES to identify informative properties of S protein

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SARS-CoV-2 variants have amino acid changes that alter infection and transmission

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The SPIKES identified changes in S protein properties from animal to human host CoVs

Predicting Protein Conformational Disorder and Disordered Binding Sites

In the last two decades it has become increasingly evident that a large number of proteins adopt either a fully or a partially disordered conformation. Intrinsically disordered proteins are ubiquitous proteins that fulfill essential biological functions while lacking a stable 3D structure. Their conformational heterogeneity is encoded by the amino acid sequence, thereby allowing intrinsically disordered proteins or regions to be recognized based on their sequence properties. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to crystallization. This chapter focuses on the methods currently employed for predicting protein disorder and identifying intrinsically disordered binding sites.

Disentangling the Roles of Functional Domains in the Aggregation and Adsorption of the Multimodular Sea Star Adhesive Protein Sfp1

Sea stars can adhere to various underwater substrata using an adhesive secretion of which Sfp1 is a major component. Sfp1 is a multimodular protein composed of four subunits (Sfp1 Alpha, Beta, Delta, and Gamma) displaying different functional domains. We recombinantly produced two fragments of Sfp1 comprising most of its functional domains: the C-terminal part of the Beta subunit (rSfp1 Beta C-term) and the Delta subunit (rSfp1 Delta). Surface plasmon resonance analyses of protein adsorption onto different model surfaces showed that rSfp1 Beta C-term exhibits a significantly higher adsorption than the fibrinogen control on hydrophobic, hydrophilic protein-resistant, and charged self-assembled monolayers, while rSfp1 Delta adsorbed more on negatively charged and on protein-resistant surfaces compared to fibrinogen. Truncated recombinant rSfp1 Beta C-term proteins were produced in order to investigate the role of the different functional domains in the adsorption of this protein. The analysis of their adsorption capacities on glass showed that two mechanisms are involved in rSfp1 Beta C-term adsorption: (1) one mediated by the EGF-like domain and involving Ca2+ and Mg2+ ions, and (2) one mediated by the sequence of Sfp1 Beta with no homology with known functional domain in databases, in the presence of Na+, Ca2+ and Mg2+ ions.

How Do Flaviviruses Hijack Host Cell Functions by Phase Separation?

Viral proteins interact with different sets of host cell components throughout the viral life cycle and are known to localize to the intracellular membraneless organelles (MLOs) of the host cell, where formation/dissolution is regulated by phase separation of intrinsically disordered proteins and regions (IDPs/IDRs). Viral proteins are rich in IDRs, implying that viruses utilize IDRs to regulate phase separation of the host cell organelles and augment replication by commandeering the functions of the organelles and/or sneaking into the organelles to evade the host immune response. This review aims to integrate current knowledge of the structural properties and intracellular localizations of viral IDPs to understand viral strategies in the host cell. First, the properties of viral IDRs are reviewed and similarities and differences with those of eukaryotes are described. The higher IDR content in viruses with smaller genomes suggests that IDRs are essential characteristics of viral proteins. Then, the interactions of the IDRs of flaviviruses with the MLOs of the host cell are investigated with emphasis on the viral proteins localized in the nucleoli and stress granules. Finally, the possible roles of viral IDRs in regulation of the phase separation of organelles and future possibilities for antiviral drug development are discussed.

Functional and pathological amyloid structures in the eyes of 2020 cryo-EM

The amyloid state of protein aggregation is associated with neurodegenerative and systemic diseases but can play physiological roles in many organisms, including as stress granules and virulence determinants. The recent resolution revolution in cryogenic electron microscopy (cryo-EM) has significantly expanded the repertoire of high-resolution amyloid structures, to include, for the first-time, fibrils extracted ex vivo in addition to those formed, or seeded, in vitro. Here, we review recently solved cryo-EM amyloid structures, and compare amino acid prevalence, in efforts to systematically distinguish between pathological and functional amyloids, even though such structural classification is hindered by extensive polymorphism even among fibrils of the same protein, and by dual functioning of some human amyloids in both physiological activities and disease mechanisms. Forthcoming structures of bacterial amyloids may expose specific, evolutionary-designed properties specific to functional fibrils.

The Ligand of Ate1 is intrinsically disordered and participates in nucleolar phase separation regulated by Jumonji Domain Containing 6

The Ligand of Ate1 (Liat1) is a protein of unknown function that was originally discovered through its interaction with arginyl-tRNA protein transferase 1 (Ate1), a component of the Arg/N-degron pathway of protein degradation. Here, we characterized the functional domains of mouse Liat1 and found that its N-terminal half comprises an intrinsically disordered region (IDR) that facilitates its liquid-liquid phase separation (LLPS) in the nucleolus. Using bimolecular fluorescence complementation and immunocytochemistry, we found that Liat1 is targeted to the nucleolus by a low-complexity poly-K region within its IDR. We also found that the lysyl-hydroxylase activity of Jumonji Domain Containing 6 (Jmjd6) modifies Liat1, in a manner that requires the Liat1 poly-K region, and inhibits its nucleolar targeting and potential functions. In sum, this study reveals that Liat1 participates in nucleolar LLPS regulated by Jmjd6.

Sequence Characterization and Molecular Modeling of Clinically Relevant Variants of the SARS-CoV-2 Main Protease

The SARS-CoV-2 main protease (Mpro) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new Mpro mutations arising over time. Identification and structural characterization of Mpro variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine Mpro variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery.

IgE Epitope Profiling for Allergy Diagnosis and Therapy - Parallel Analysis of a Multitude of Potential Linear Epitopes Using a High Throughput Screening Platform

Immunoglobulin E (IgE) is pivotal for manifestation and persistence of most immediate-type allergies and some asthma phenotypes. Consequently, IgE represents a crucial target for both, diagnostic purposes as well as therapeutic approaches. In fact, allergen-specific immunotherapy – aiming to re-route an IgE-based inflammatory response into an innocuous immune reaction against the allergen – is the only curative approach for IgE-mediated allergic diseases known so far. However, this requires the cognate allergen to be known. Unfortunately, even in well-characterized allergics or asthmatics, often just a small fraction of total IgE can be assigned to specific target allergens. To overcome this knowledge gap, we have devised an analytical platform for unbiased IgE target epitope detection. The system relies on chemically produced random peptide libraries immobilized on polystyrene beads (“one-bead-one-compound (OBOC) libraries”) capable to present millions of different peptide motifs simultaneously to immunoglobulins from biological samples. Beads binding IgE are highlighted with a fluorophore-labeled anti-IgE antibody allowing fluorescence-based detection and isolation of positives, which then can be characterized by peptide sequencing. Setting-up this platform required an elaborate optimization process including proper choice of background suppressants, secondary antibody and fluorophore label as well as incubation conditions. For optimal performance our procedure involves a sophisticated pre-adsorption step to eliminate beads that react nonspecifically with anti-IgE secondary antibodies. This step turned out to be important for minimizing detection of “false positive” motifs that otherwise would erroneously be classified as IgE epitopes. In validation studies we were able to retrieve artificial test-peptide beads spiked into our library by using IgE directed against those test-peptides at physiological concentrations (≤20 IU/ml of specific IgE), and disease-relevant bead-bound epitopes of the major peanut allergen Ara h 2 by screening with sera from peanut allergics. Thus, we established a platform with which one can find and validate new immunoglobulin targets using patient material which displays a largely unknown immunoglobulin repertoire.

Sequence characterization and molecular modeling of clinically relevant variants of the SARS-CoV-2 main protease

The SARS-CoV-2 main protease (M ^pro ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant selection pressure, with new M ^pro mutations arising over time. Identification and structural characterization of M ^pro variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine M ^pro variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery.

Kinetics Analysis of the Reactions between Peroxynitric Acid and Amino Acids

Plasma disinfection using low-temperature atmospheric pressure plasma is widely studied in many applications, and the use of plasma-treated water (PTW) for disinfection is being developed by many researchers. Exposing plasma to water supplies and preserves reactive oxygen and nitrogen species (RONS) in the water, and this PTW exhibits bactericidal activity. In our previous study, it was revealed that peroxynitric acid (O₂NOOH, PNA) was the dominant bactericidal component in PTW. PNA can be easily synthesized without plasma treatment, and the physicochemical properties of PNA have been well-analyzed. As the application of PNA in fields related to medicine and biology has not been reported, a basic study on the behavior of PNA is required. In this study, the bactericidal activity of PNA and its reactivities with 20 naturally occurring amino acids were evaluated to understand its reaction mechanism with biomolecules. Interestingly, PNA exhibited 10^-6 times lower reactivities with amino acids when compared with hypochlorous acid and other RONS, although its bactericidal activity was 310 times higher than that of sodium hypochlorite. In addition, the reactivity of PNA with methionine was over 100 times higher than that with other amino acids, indicating that the reactions of PNA with amino acids are highly specific. No other oxidants have been reported to react selectively with only methionine. As methionine is involved in specific activities in cells, the unique reaction profile of PNA was examined in the context of biological systems.

Divergent Allele Advantage at Human MHC Genes: Signatures of Past and Ongoing Selection

The highly polymorphic genes of the major histocompatibility complex (MHC) play a key role in adaptive immunity. Divergent allele advantage, a mechanism of balancing selection, is proposed to contribute to their exceptional polymorphism. It assumes that MHC genotypes with more divergent alleles allow for broader antigen-presentation to immune effector cells, by that increasing immunocompetence. However, the direct correlation between pairwise sequence divergence and the corresponding repertoire of bound peptides has not been studied systematically across different MHC genes. Here, we investigated this relationship for five key classical human MHC genes (human leukocyte antigen; HLA-A, -B, -C, -DRB1, and -DQB1), using allele-specific computational binding prediction to 118,097 peptides derived from a broad range of human pathogens. For all five human MHC genes, the genetic distance between two alleles of a heterozygous genotype was positively correlated with the total number of peptides bound by these two alleles. In accordance with the major antigen-presentation pathway of MHC class I molecules, HLA-B and HLA-C alleles showed particularly strong correlations for peptides derived from intracellular pathogens. Intriguingly, this bias coincides with distinct protein compositions between intra- and extracellular pathogens, possibly suggesting adaptation of MHC I molecules to present specifically intracellular peptides. Eventually, we observed significant positive correlations between an allele’s average divergence and its population frequency. Overall, our results support the divergent allele advantage as a meaningful quantitative mechanism through which pathogen-mediated selection leads to the evolution of MHC diversity.

Tryptophan in health and disease

Tryptophan (TRP), an essential amino acid in mammals, is involved in several physiological processes including neuronal function, immunity, and gut homeostasis. In humans, TRP is metabolized via the kynurenine and serotonin pathways, leading to the generation of biologically active compounds, such as serotonin, melatonin and niacin. In addition to endogenous TRP metabolism, resident gut microbiota also contributes to the production of specific TRP metabolites and indirectly influences host physiology. The variety of physiologic functions regulated by TRP reflects the complex pattern of diseases associated with altered homeostasis. Indeed, an imbalance in the synthesis of TRP metabolites has been associated with pathophysiologic mechanisms occurring in neurologic and psychiatric disorders, in chronic immune activation and in the immune escape of cancer. In this chapter, the role of TRP metabolism in health and disease is presented. Disorders involving the central nervous system, malignancy, inflammatory bowel and cardiovascular disease are discussed.

Engineered Interspecies Amino Acid Cross-Feeding Increases Population Evenness in a Synthetic Bacterial Consortium

In nature, microbes interact antagonistically, neutrally, or beneficially. To shed light on the effects of positive interactions in microbial consortia, we introduced metabolic dependencies and metabolite overproduction into four bacterial species. While antagonistic interactions govern the wild-type consortium behavior, the genetic modifications alleviated antagonistic interactions and resulted in beneficial interactions. Engineered cross-feeding increased population evenness, a component of ecological diversity, in different environments, including in a more complex gnotobiotic mouse gut environment. Our findings suggest that metabolite cross-feeding could be used as a tool for intentionally shaping microbial consortia in complex environments.IMPORTANCE Microbial communities are ubiquitous in nature. Bacterial consortia live in and on our body and in our environment, and more recently, biotechnology is applying microbial consortia for bioproduction. As part of our body, bacterial consortia influence us in health and disease. Microbial consortium function is determined by its composition, which in turn is driven by the interactions between species. Further understanding of microbial interactions will help us in deciphering how consortia function in complex environments and may enable us to modify microbial consortia for health and environmental benefits.

Dynamic Studies on Intrinsically Disordered Regions of Two Paralogous Transcription Factors Reveal Rigid Segments with Important Biological Functions

Long stretches of intrinsically disordered regions (IDRs) are abundantly present in eukaryotic transcription factors. Although their biological significance is well appreciated, the underlying structural and dynamic mechanisms of their function are still not clear. Using solution NMR spectroscopy, we have studied the structural and dynamic features of two paralogous HOX transcription factors, SCR and DFD, from Drosophila. Both proteins have a conserved DNA-binding homeodomain and a long stretch of functionally important IDR. Using NMR dynamics, we determined flexibility of each residue in these proteins. The flexibility of the residues in the disordered region is not uniform. In both proteins, the IDRs have short stretches of consecutive residues with relatively less flexibility, that is, higher rigidity. We show that one such rigid segment is specifically recognized by another co-transcription factor, thus highlighting the importance of these rigid segments in IDR-mediated protein-protein interactions. Using molecular dynamics simulation, we further show that the rigid segments sample less conformations compared to the rest of the residues in the disordered region. The restrained conformational sampling of these rigid residues should lower the loss in conformational entropy during their interactions with binding partners resulting in sequence specific binding. This work provides experimental evidence of a "rigid-segment" model of IDRs, where functionally important rigid segments are connected by highly flexible linkers. Furthermore, a comparative study of IDRs in paralogous proteins reveals that in spite of low-sequence conservation, the rigid and flexible segments are sequentially maintained to preserve related functions and regulations of these proteins.

Proteome-wide comparison between the amino acid composition of domains and linkers

Objective

Amino acid composition is a sequence feature that has been extensively used to characterize proteomes of many species and protein families. Yet the analysis of amino acid composition of protein domains and the linkers connecting them has received less attention. Here, we perform both a comprehensive full-proteome amino acid composition analysis and a similar analysis focusing on domains and linkers, to uncover domain- or linker-specific differential amino acid usage patterns.

Results

The amino acid composition in the 38 proteomes studied showcase the greater variability found in archaea and bacteria species compared to eukaryotes. When focusing on domains and linkers, we describe the preferential use of polar residues in linkers and hydrophobic residues in domains. To let any user perform this analysis on a given domain (or set of them), we developed a dedicated R script called RACCOON, which can be easily used and can provide interesting insights into the compositional differences between a domain and its surrounding linkers.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3221-0) contains supplementary material, which is available to authorized users.

How disordered is my protein and what is its disorder for? A guide through the "dark side" of the protein universe

In the last 2 decades it has become increasingly evident that a large number of proteins are either fully or partially disordered. Intrinsically disordered proteins lack a stable 3D structure, are ubiquitous and fulfill essential biological functions. Their conformational heterogeneity is encoded in their amino acid sequences, thereby allowing intrinsically disordered proteins or regions to be recognized based on properties of these sequences. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to structural determination with X-ray crystallization. This article discusses a comprehensive selection of databases and methods currently employed to disseminate experimental and putative annotations of disorder, predict disorder and identify regions involved in induced folding. It also provides a set of detailed instructions that should be followed to perform computational analysis of disorder.

A Mutation Model from First Principles of the Genetic Code

The paper presents a neutral Codons Probability Mutations (CPM) model of molecular evolution and genetic decay of an organism. The CPM model uses a Markov process with a 20-dimensional state space of probability distributions over amino acids. The transition matrix of the Markov process includes the mutation rate and those single point mutations compatible with the genetic code. This is an alternative to the standard Point Accepted Mutation (PAM) and BLOcks of amino acid SUbstitution Matrix (BLOSUM). Genetic decay is quantified as a similarity between the amino acid distribution of proteins from a (group of) species on one hand, and the equilibrium distribution of the Markov chain on the other. Amino acid data for the eukaryote, bacterium, and archaea families are used to illustrate how both the CPM and PAM models predict their genetic decay towards the equilibrium value of 1. A family of bacteria is studied in more detail. It is found that warm environment organisms on average have a higher degree of genetic decay compared to those species that live in cold environments. The paper addresses a new codon-based approach to quantify genetic decay due to single point mutations compatible with the genetic code. The present work may be seen as a first approach to use codon-based Markov models to study how genetic entropy increases with time in an effectively neutral biological regime. Various extensions of the model are also discussed.

Predicting Conformational Disorder

In the last two decades, it has become increasingly evident that a large number of proteins are either fully or partially disordered. Intrinsically disordered proteins are ubiquitous proteins that fulfill essential biological functions while lacking a stable 3D structure. Their conformational heterogeneity is encoded at the amino acid sequence level, thereby allowing intrinsically disordered proteins or regions to be recognized based on their sequence properties. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to crystallization. This chapter focuses on the methods currently employed for predicting disorder and identifying regions involved in induced folding.

Asparagine requirement in Plasmodium berghei as a target to prevent malaria transmission and liver infections

The proteins of Plasmodium, the malaria parasite, are strikingly rich in asparagine. Plasmodium depends primarily on host haemoglobin degradation for amino acids and has a rudimentary pathway for amino acid biosynthesis, but retains a gene encoding asparagine synthetase (AS). Here we show that deletion of AS in Plasmodium berghei (Pb) delays the asexual- and liver-stage development with substantial reduction in the formation of ookinetes, oocysts and sporozoites in mosquitoes. In the absence of asparagine synthesis, extracellular asparagine supports suboptimal survival of PbAS knockout (KO) parasites. Depletion of blood asparagine levels by treating PbASKO-infected mice with asparaginase completely prevents the development of liver stages, exflagellation of male gametocytes and the subsequent formation of sexual stages. In vivo supplementation of asparagine in mice restores the exflagellation of PbASKO parasites. Thus, the parasite life cycle has an absolute requirement for asparagine, which we propose could be targeted to prevent malaria transmission and liver infections.

Malaria parasites obtain amino acids primarily from the host, but possess a gene encoding a putative asparagine synthetase. Here, the authors show that this enzyme is functional and that asparagine is crucial for the development of the parasite's sexual stages in mosquitoes and liver stages in mice.

How Common Is Disorder? Occurrence of Disordered Residues in Four Domains of Life

Disordered regions play important roles in protein adaptation to challenging environmental conditions. Flexible and disordered residues have the highest propensities to alter the protein packing. Therefore, identification of disordered/flexible regions is important for structural and functional analysis of proteins. We used the IsUnstruct program to predict the ordered or disordered status of residues in 122 proteomes, including 97 eukaryotic and 25 large bacterial proteomes larger than 2,500,000 residues. We found that bacterial and eukaryotic proteomes contain comparable fraction of disordered residues, which was 0.31 in the bacterial and 0.38 in the eukaryotic proteomes. Additional analysis of the total of 1540 bacterial proteomes of various sizes yielded a smaller fraction of disordered residues, which was only 0.26. Together, the results showed that the larger is the size of the proteome, the larger is the fraction of the disordered residues. A continuous dependence of the fraction of disordered residues on the size of the proteome is observed for four domains of life: Eukaryota, Bacteria, Archaea, and Viruses. Furthermore, our analysis of 122 proteomes showed that the fraction of disordered residues increased with increasing the length of homo-repeats for polar, charged, and small residues, and decreased for hydrophobic residues. The maximal fraction of disordered residues was obtained for proteins containing lysine and arginine homo-repeats. The minimal fraction was found in valine and leucine homo-repeats. For 15-residue long homo-repeats these values were 0.2 (for Val and Leu) and 0.7 (for Lys and Arg).

An N-terminal, 830 residues intrinsically disordered region of the cytoskeleton-regulatory protein supervillin contains Myosin II- and F-actin-binding sites

Supervillin, the largest member of the villin/gelsolin family, is a cytoskeleton regulating, peripheral membrane protein. Supervillin increases cell motility and promotes invasive activity in tumors. Major cytoskeletal interactors, including filamentous actin and myosin II, bind within the unique supervillin amino terminus, amino acids 1-830. The structural features of this key region of the supervillin polypeptide are unknown. Here, we utilize circular dichroism and bioinformatics sequence analysis to demonstrate that the N-terminal part of supervillin forms an extended intrinsically disordered region (IDR). Our combined data indicate that the N-terminus of human and bovine supervillin sequences (positions 1-830) represents an IDR, which is the largest IDR known to date in the villin/gelsolin family. Moreover, this result suggests a potentially novel mechanism of regulation of myosin II and F-actin via the intrinsically disordered N-terminal region of hub protein supervillin.

Computational analysis of position-dependent disorder content in DisProt database

A bioinformatics analysis of disorder content of proteins from the DisProt database has been performed with respect to position of disordered residues. Each protein chain was divided into three parts: N- and C- terminal parts with each containing 30 amino acid (AA) residues and the middle region containing the remaining AA residues. The results show that in terminal parts, the percentage of disordered AA residues is higher than that of all AA residues (17% of disordered AA residues and 11% of all). We analyzed the percentage of disorder for each of 20 AA residues in the three parts of proteins with respect to their hydropathy and molecular weight. For each AA, the percentage of disorder in the middle part is lower than that in terminal parts which is comparable at the two termini. A new scale of AAs has been introduced according to their disorder content in the middle part of proteins: CIFWMLYHRNVTAGQDSKEP. All big hydrophobic AAs are less frequently disordered, while almost all small hydrophilic AAs are more frequently disordered. The results obtained may be useful for construction and improving predictors for protein disorder.

Estimating intrinsic structural preferences of de novo emerging random-sequence proteins: is aggregation the main bottleneck?

Present-day proteins are believed to have evolved features to reduce the risk of aggregation. However, proteins can emerge de novo by translation of non-coding DNA segments. In this study we assess the aggregation, disorder and transmembrane propensity of protein sequences generated by translating random nucleotide sequences of varying GC-content. Potential de novo random-sequence proteins translated from regions with GC content between 40% and 60% do not show stronger aggregation propensity than existing ones and exhibit similar tendency to be disordered. We suggest that de novo emerging proteins do not mean an unavoidable aggregation threat to evolving organisms.

Unique peptide substrate binding properties of 110-kDa heat-shock protein (Hsp110) determine its distinct chaperone activity

The molecular chaperone 70-kDa heat-shock proteins (Hsp70s) play essential roles in maintaining protein homeostasis. Hsp110, an Hsp70 homolog, is highly efficient in preventing protein aggregation but lacks the hallmark folding activity seen in Hsp70s. To understand the mechanistic differences between these two chaperones, we first characterized the distinct peptide substrate binding properties of Hsp110s. In contrast to Hsp70s, Hsp110s prefer aromatic residues in their substrates, and the substrate binding and release exhibit remarkably fast kinetics. Sequence and structure comparison revealed significant differences in the two peptide-binding loops: the length and properties are switched. When we swapped these two loops in an Hsp70, the peptide binding properties of this mutant Hsp70 were converted to Hsp110-like, and more impressively, it functionally behaved like an Hsp110. Thus, the peptide substrate binding properties implemented in the peptide-binding loops may determine the chaperone activity differences between Hsp70s and Hsp110s.

Bacterial proteins fold faster than eukaryotic proteins with simple folding kinetics

Protein domain frequency and distribution among kingdoms was statistically analyzed using the SCOP structural database. It appeared that among chosen protein domains with the best resolution, eukaryotic proteins more often belong to α-helical and β-structural proteins, while proteins of bacterial origin belong to α/β structural class. Statistical analysis of folding rates of 73 proteins with known experimental data revealed that bacterial proteins with simple kinetics (23 proteins) exhibit a higher folding rate compared to eukaryotic proteins with simple folding kinetics (27 proteins). Analysis of protein domain amino acid composition showed that the frequency of amino acid residues in proteins of eukaryotic and bacterial origin is different for proteins with simple and complex folding kinetics.