Protein aggregation profile of the bacterial cytosol

Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity

Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH-dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure-based predictors. Notably, A4D integrates advanced protein engineering protocols with pH-dependent calculations, enhancing its utility in advising solubility-enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/.

The hidden world of protein aggregation

Though the book's journey into The Hidden World of Protein Aggregation has come to an end, the search for knowledge, the development of healthier lives, and the discovery of nature's mysteries continue, promising new horizons and discoveries yet to be discovered. The intricacies of protein misfolding and aggregation remain a mystery in cellular biology, despite advances made in unraveling them. In this chapter, we will summarize the specific conclusions from the previous chapters and explore the persistent obstacles and unanswered questions that motivate scientists to pursue exploration of protein misfolding and aggregation.

A3D Model Organism Database (A3D-MODB): a database for proteome aggregation predictions in model organisms

Protein aggregation has been associated with aging and different pathologies and represents a bottleneck in the industrial production of biotherapeutics. Numerous past studies performed in Escherichia coli and other model organisms have allowed to dissect the biophysical principles underlying this process. This knowledge fuelled the development of computational tools, such as Aggrescan 3D (A3D) to forecast and re-design protein aggregation. Here, we present the A3D Model Organism Database (A3D-MODB) http://biocomp.chem.uw.edu.pl/A3D2/MODB, a comprehensive resource for the study of structural protein aggregation in the proteomes of 12 key model species spanning distant biological clades. In addition to A3D predictions, this resource incorporates information useful for contextualizing protein aggregation, including membrane protein topology and structural model confidence, as an indirect reporter of protein disorder. The database is openly accessible without any need for registration. We foresee A3D-MOBD evolving into a central hub for conducting comprehensive, multi-species analyses of protein aggregation, fostering the development of protein-based solutions for medical, biotechnological, agricultural and industrial applications.

Census of exposed aggregation-prone regions in proteomes

Loss of solubility usually leads to the detrimental elimination of protein function. In some cases, the protein aggregation is also required for beneficial functions. Given the duality of this phenomenon, it remains a fundamental question how natural selection controls the aggregation. The exponential growth of genomic sequence data and recent progress with in silico predictors of the aggregation allows approaching this problem by a large-scale bioinformatics analysis. Most of the aggregation-prone regions are hidden within the 3D structure, rendering them inaccessible for the intermolecular interactions responsible for aggregation. Thus, the most realistic census of the aggregation-prone regions requires crossing aggregation prediction with information about the location of the natively unfolded regions. This allows us to detect so-called 'exposed aggregation-prone regions' (EARs). Here, we analyzed the occurrence and distribution of the EARs in 76 reference proteomes from the three kingdoms of life. For this purpose, we used a bioinformatics pipeline, which provides a consensual result based on several predictors of aggregation. Our analysis revealed a number of new statistically significant correlations about the presence of EARs in different organisms, their dependence on protein length, cellular localizations, co-occurrence with short linear motifs and the level of protein expression. We also obtained a list of proteins with the conserved aggregation-prone sequences for further experimental tests. Insights gained from this work led to a deeper understanding of the relationship between protein evolution and aggregation.

Computational Analysis of the Ligand-Binding Sites of the Molecular Chaperone OppA from Yersinia pseudotuberculosis

The function of chaperones is to correct or degrade misfolded proteins inside the cell. Classic molecular chaperones such as GroEL and DnaK have not been found in the periplasm of Yersinia pseudotuberculosis. Some periplasmic substrate-binding proteins could be bifunctional, such as OppA. Using bioinformatic tools, we try to elucidate the nature of the interactions between OppA and ligands from four proteins with different oligomeric states. Using the crystal structure of the proteins Mal12 alpha-glucosidase from Saccharomyces cerevisiae S288C, LDH rabbit muscle lactate dehydrogenase, EcoRI endonuclease from Escherichia coli and THG Geotrichum candidum lipase, a hundred models were obtained in total, including five different ligands from each enzyme with five conformations of each ligand. The best values for Mal12 stem from ligands 4 and 5, with conformation 5 for both; for LDH, ligands 1 and 4, with conformations 2 and 4, respectively; for EcoRI, ligands 3 and 5, with conformation 1 for both; and for THG, ligands 2 and 3, with conformation 1 for both. The interactions were analyzed with LigProt, and the length of the hydrogen bridges has an average of 2.8 to 3.0 Å. The interaction within the OppA pocket is energetically favored due to the formation of hydrogen bonds both of OppA and of the selected enzymes. The Asp 419 residue is important in these junctions.

An Efficient Evaluation System Accelerates α-Helical Antimicrobial Peptide Discovery and Its Application to Global Human Genome Mining

Antimicrobial peptides (AMPs), as an important part of the innate immune system of an organism, is a kind of promising drug candidate for novel antibiotics due to their unique antibacterial mechanism. However, the discovery of novel AMPs is facing a great challenge due to the complexity of systematic experiments and the poor predictability of antimicrobial activity. Here, a novel and comprehensive screening system, the Multiple Descriptor Multiple Strategy (MultiDS), was proposed based on 59 physicochemical and structural parameters, three strategies, and four algorithms for the mining of α-helical AMPs. This approach was applied to mine the encrypted peptide antibiotics from the global human genome, including introns and exons. A library of approximately 70 billion peptides with 15–25 amino acid residues was screened by the MultiDS system and generated a list of peptides with the Multiple Descriptor Index (MD index) scores, which was the core part of the MultiDS system. Sixty peptides with top MD scores were chemically synthesized and experimentally tested their antimicrobial activity against 10 kinds of Gram-positive bacteria, Gram-negative bacteria (including drug-resistant pathogens). A total of fifty-nine out of 60 (98.3%) peptides exhibited antimicrobial activity (MIC ≤ 64 μg/mL), and 24 out of 60 (40%) peptides showed high activity (MIC ≤ 2 μg/mL), validating the MultiDS system was an effective and predictive screening tool with high hit rate and superior antimicrobial activity. For further investigation, AMPs S1, S2, and S3 with the highest MD scores were used to treat the skin infection mouse models in vivo caused by Escherichia coli, drug-resistance Escherichia coli, and Staphylococcus aureus, respectively. All of S1, S2, and S3 showed comparable therapeutic effects on promoting infection healing to or even better than the positive drug levofloxacin. A mechanism study discovered that rapid bactericidal action was caused by cell membrane disruption and content leakage. The MultiDS system not only provides a high-throughput approach that allows for the mining of candidate AMPs from the global genome sequence but also opens up a new route to accelerate the discovery of peptide antibiotics.

Proteome-wide landscape of solubility limits in a bacterial cell

Proteins are prone to aggregate when expressed above their solubility limits. Aggregation may occur rapidly, potentially as early as proteins emerge from the ribosome, or slowly, following synthesis. However, in vivo data on aggregation rates are scarce. Here, we classified the Escherichia coli proteome into rapidly and slowly aggregating proteins using an in vivo image-based screen coupled with machine learning. We find that the majority (70%) of cytosolic proteins that become insoluble upon overexpression have relatively low rates of aggregation and are unlikely to aggregate co-translationally. Remarkably, such proteins exhibit higher folding rates compared to rapidly aggregating proteins, potentially implying that they aggregate after reaching their folded states. Furthermore, we find that a substantial fraction (~ 35%) of the proteome remain soluble at concentrations much higher than those found naturally, indicating a large margin of safety to tolerate gene expression changes. We show that high disorder content and low surface stickiness are major determinants of high solubility and are favored in abundant bacterial proteins. Overall, our study provides a global view of aggregation rates and hence solubility limits of proteins in a bacterial cell.

Cryptic amyloidogenic regions in intrinsically disordered proteins: Function and disease association

The amyloid conformation is considered a fundamental state of proteins and the propensity to populate it a generic property of polypeptides. Multiple proteome-wide analyses addressed the presence of amyloidogenic regions in proteins, nurturing our understanding of their nature and biological implications. However, these analyses focused on highly aggregation-prone and hydrophobic stretches that are only marginally found in intrinsically disordered regions (IDRs). Here, we explore the prevalence of cryptic amyloidogenic regions (CARs) of polar nature in IDRs. CARs are widespread in IDRs and associated with IDPs function, with particular involvement in protein–protein interactions, but their presence is also connected to a risk of malfunction. By exploring this function/malfunction dichotomy, we speculate that ancestral CARs might have evolved into functional interacting regions playing a significant role in protein evolution at the origins of life.

Coiled-Coil Based Inclusion Bodies and Their Potential Applications

The production of recombinant proteins using microbial cell factories is frequently associated with the formation of inclusion bodies (IBs). These proteinaceous entities can be sometimes a reservoir of stable and active protein, might display good biocompatibility, and are produced efficiently and cost-effectively. Thus, these submicrometric particles are increasingly exploited as functional biomaterials for biotechnological and biomedical purposes. The fusion of aggregation-prone sequences to the target protein is a successful strategy to sequester soluble recombinant polypeptides into IBs. Traditionally, the use of these IB-tags results in the formation of amyloid-like scaffolds where the protein of interest is trapped. This amyloid conformation might compromise the protein's activity and be potentially cytotoxic. One promising alternative to overcome these limitations exploits the coiled-coil fold, composed of two or more α-helices and widely used by nature to create supramolecular assemblies. In this review, we summarize the state-of-the-art of functional IBs technology, focusing on the coiled-coil-assembly strategy, describing its advantages and applications, delving into future developments and necessary improvements in the field.

Bacterial Protein Homeostasis Disruption as a Therapeutic Intervention

Cells have evolved a complex molecular network, collectively called the protein homeostasis (proteostasis) network, to produce and maintain proteins in the appropriate conformation, concentration and subcellular localization. Loss of proteostasis leads to a reduction in cell viability, which occurs to some degree during healthy ageing, but is also the root cause of a group of diverse human pathologies. The accumulation of proteins in aberrant conformations and their aggregation into specific beta-rich assemblies are particularly detrimental to cell viability and challenging to the protein homeostasis network. This is especially true for bacteria; it can be argued that the need to adapt to their changing environments and their high protein turnover rates render bacteria particularly vulnerable to the disruption of protein homeostasis in general, as well as protein misfolding and aggregation. Targeting bacterial proteostasis could therefore be an attractive strategy for the development of novel antibacterial therapeutics. This review highlights advances with an antibacterial strategy that is based on deliberately inducing aggregation of target proteins in bacterial cells aiming to induce a lethal collapse of protein homeostasis. The approach exploits the intrinsic aggregation propensity of regions residing in the hydrophobic core regions of the polypeptide sequence of proteins, which are genetically conserved because of their essential role in protein folding and stability. Moreover, the molecules were designed to target multiple proteins, to slow down the build-up of resistance. Although more research is required, results thus far allow the hope that this strategy may one day contribute to the arsenal to combat multidrug-resistant bacterial infections.

Evaluation of soluble expression of recombinant granulocyte macrophage stimulating factor (rGM-CSF) by three different E. coli strains

Background and purpose:

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a cytokine with a wide range of therapeutic applications although expression of GM-CSF in Escherichia coli (E. coli) usually leads to formation of insoluble aggregates mostly lack biological activity. The aim of this study was to compare the soluble expression level of GM-CSF in three E. coli strains, BL21 (DE3), SHuffle® T7 and Origami™ 2 (DE3).

Experimental approach:

The effect of different temperatures and inducer concentrations on soluble expression of GM-CSF was evaluated. The soluble GM-CSF was subjected to endotoxin removal and purification using nickel-nitrilotriacetic acid (Ni-NTA) affinity chromatography, ultrafiltration. The biological activity of produced GM-CSF was evaluated based on its growth promotion effect on TF-1 cell lines by MTT assay method.

Findings / Results:

A significant improvement of the soluble yield of GM-CSF (about 30% of GM-CSF was expressed as soluble proteins) was observed when protein expression was induced at 30 °C with 0.5 mM isopropyl β- d-1-thiogalactopyranoside (IPTG) in E. coli Shuffle T7. The soluble GM-CSF with a high purity up to 95 % and specific activity of 1.25 × 10⁴ IU/μg was obtained.

Conclusion and implications:

The proposed strategy here can be used to improve the soluble expression of other hard-to-express proteins with similar structural properties (i.e., containing disulfide binds or cysteine).

Computational prediction of protein aggregation: Advances in proteomics, conformation-specific algorithms and biotechnological applications

Protein aggregation is a widespread phenomenon that stems from the establishment of non-native intermolecular contacts resulting in protein precipitation. Despite its deleterious impact on fitness, protein aggregation is a generic property of polypeptide chains, indissociable from protein structure and function. Protein aggregation is behind the onset of neurodegenerative disorders and one of the serious obstacles in the production of protein-based therapeutics. The development of computational tools opened a new avenue to rationalize this phenomenon, enabling prediction of the aggregation propensity of individual proteins as well as proteome-wide analysis. These studies spotted aggregation as a major force driving protein evolution. Actual algorithms work on both protein sequences and structures, some of them accounting also for conformational fluctuations around the native state and the protein microenvironment. This toolbox allows to delineate conformation-specific routines to assist in the identification of aggregation-prone regions and to guide the optimization of more soluble and stable biotherapeutics. Here we review how the advent of predictive tools has change the way we think and address protein aggregation.

Protein folding while chaperone bound is dependent on weak interactions

It is generally assumed that protein clients fold following their release from chaperones instead of folding while remaining chaperone-bound, in part because binding is assumed to constrain the mobility of bound clients. Previously, we made the surprising observation that the ATP-independent chaperone Spy allows its client protein Im7 to fold into the native state while continuously bound to the chaperone. Spy apparently permits sufficient client mobility to allow folding to occur while chaperone bound. Here, we show that strengthening the interaction between Spy and a recently discovered client SH3 strongly inhibits the ability of the client to fold while chaperone bound. The more tightly Spy binds to its client, the more it slows the folding rate of the bound client. Efficient chaperone-mediated folding while bound appears to represent an evolutionary balance between interactions of sufficient strength to mediate folding and interactions that are too tight, which tend to inhibit folding.

Spy is an ATP independent chaperone that allows folding of its client protein Im7 while continuously bound to Spy. Here the authors employ kinetics measurements to study the folding of another Spy client protein SH3 and find that Spy’s ability to allow a client to fold while bound is inversely related to how strongly it interacts with that client.

Computational Assessment of Bacterial Protein Structures Indicates a Selection Against Aggregation

The aggregation of proteins compromises cell fitness, either because it titrates functional proteins into non-productive inclusions or because it results in the formation of toxic assemblies. Accordingly, computational proteome-wide analyses suggest that prevention of aggregation upon misfolding plays a key role in sequence evolution. Most proteins spend their lifetimes in a folded state; therefore, it is conceivable that, in addition to sequences, protein structures would have also evolved to minimize the risk of aggregation in their natural environments. By exploiting the AGGRESCAN3D structure-based approach to predict the aggregation propensity of >600 Escherichia coli proteins, we show that the structural aggregation propensity of globular proteins is connected with their abundance, length, essentiality, subcellular location and quaternary structure. These data suggest that the avoidance of protein aggregation has contributed to shape the structural properties of proteins in bacterial cells.

Proteome-scale understanding of relationship between homo-repeat enrichments and protein aggregation properties

Expansion of homo-repeats is a molecular basis for human neurological diseases. We are the first who studied the influence of homo-repeats with lengths larger than four amino acid residues on the aggregation properties of 1449683 proteins across 122 eukaryotic and bacterial proteomes. Only 15% of proteins (215481) include homo-repeats of such length. We demonstrated that RNA-binding proteins with a prion-like domain are enriched with homo-repeats in comparison with other non-redundant protein sequences and those in the PDB. We performed a bioinformatics analysis for these proteins and found that proteins with homo-repeats are on average two times longer than those in the whole database. Moreover, we are first to discover that as a rule, homo-repeats appear in proteins not alone but in pairs: hydrophobic and aromatic homo-repeats appear with similar ones, while homo-repeats with small, polar and charged amino acids appear together with different preferences. We elaborated a new complementary approach to demonstrate the influence of homo-repeats on their host protein aggregation properties. We have shown that addition of artificial homo-repeats to natural and random proteins results in intensification of aggregation properties of the proteins. The maximal effect is observed for the insertion of artificial homo-repeats with 5–6 residues, which is consistent with the minimal length of an amyloidogenic region. We have also demonstrated that the ability of proteins with homo-repeats to aggregate cannot be explained only by the presence of long homo-repeats in them. There should be other characteristics of proteins intensifying the aggregation property including such as the appearance of homo-repeats in pairs in the same protein. We are the first who elaborated a new approach to study the influence of homo-repeats present in proteins on their aggregation properties and performed an appropriate analysis of the large number of proteomes and proteins.

Optimization of Haemophilus influenzae adhesin transmembrane domain expression in Escherichia coli

To obtain a high yield of the transmembrane domain of Haemophilus influenzae adhesin (HiaTD) in Escherichia coli, we attempted to express the HiaTD with and without a signal sequence using a T7 expression system. The expression level of HiaTD after induction was followed by quantification of the purified HiaTD, flow cytometric analysis of the outer membrane integrated HiaTD, and immunoblotting assay of fractionated cell lysate. In the expression system with a signal sequence, although the amount of cell-surface-expressed HiaTD increased over time, the number of HiaTD-expressing cells decreased, probably because of plasmid instability. As a result, the amount of purified HiaTD reached a plateau at 2 h postinduction. Although expression without the signal sequence provides a large amount of proteins as inclusion bodies in some membrane proteins, HiaTD expressed without a signal sequence was not observed as inclusion bodies and seemed to be assembled into the outer membrane during or after cell lysis.

Understanding and predicting protein misfolding and aggregation: Insights from proteomics

Protein misfolding and aggregation are being found to be associated with an increasing number of human diseases and premature aging, either because they promote a loss of protein function or, more frequently, because the aggregated species gain a toxic activity. Despite potentially harmful, aggregation seems to be a generic property of polypeptide chains and aggregation-prone protein sequences seem to be ubiquitous, which, counterintuitively, suggests that they serve evolutionary conserved functions. The in vitro study of individual aggregation reactions of a large number of proteins has provided important insights on the structural and sequential determinants of this process. However, it is clear that understanding the role played by protein aggregation and its regulation in health and disease at the cellular, developmental, and evolutionary levels require more global approaches. The use of model organisms and their proteomic analysis hold the power to provide answers to such issues. In the present review, we address how, initially, computational large-scale analysis and, more recently, experimental proteomics are helping us to rationalize how, why and when proteins aggregate, as well as to decipher the strategies organisms have developed to control proteins aggregation propensities.

Critical Evaluation and Compilation of Physicochemical Determinants and Membrane Interactions of MMGP1 Antifungal Peptide

A growing issue of pathogen resistance to antibiotics has fostered the development of innovative approaches for novel drug development. Here, we report the physicochemical and biological properties of an antifungal peptide, MMGP1, based on computational analysis. Computation of physicochemical properties has revealed that the natural biological activities of MMGP1 are coordinated by its intrinsic properties such as net positive charge (+5.04), amphipathicity, high hydrophobicity, low hydrophobic moment, and higher isoelectric point (11.915). Prediction of aggregation hot spots in MMGP1 had revealed the presence of potentially aggregation-prone segments that can nucleate in vivo aggregation (on the membrane), whereas no aggregating regions were predicted for in vitro aggregation (in solutions) of MMGP1. This ability of MMGP1 to form oligomeric aggregates on membrane further substantiates its direct-cell penetrating potency. Monte Carlo simulation of the interactions of MMGP1 in the aqueous phase and different membrane environments revealed that increasing the proportion of acidic lipids on membrane had led to increase in the peptide helicity. Furthermore, the peptide adopts energetically favorable transmembrane configuration, by inserting peptide loop and helix termini into the membrane containing >60% of anionic lipids. The charged lipid-based insertion of MMGP1 into membrane might be responsible for the selectivity of peptide toward fungal cells. Additionally, MMGP1 possessed DNA-binding property. Computational docking has identified DNA-binding residues (TRP3, SER4, MET7, ARG8, PHE10, ALA11, GLY20, THR21, ARG22, MET23, TRP34, and LYS36) in MMGP1 crucial for its DNA-binding property. Furthermore, computational mutation analysis revealed that aromatic amino acids are crucial for in vivo aggregation, membrane insertion, and DNA-binding property of MMGP1. These data provide new insight into the molecular determinants of MMGP1 antifungal activity and also serves as the template for the design of novel peptide antibiotics.

Diffusion within the cytoplasm: a mesoscale model of interacting macromolecules

Recent experiments carried out in the dense cytoplasm of living cells have highlighted the importance of proteome composition and nonspecific intermolecular interactions in regulating macromolecule diffusion and organization. Despite this, the dependence of diffusion-interaction on physicochemical properties such as the degree of poly-dispersity and the balance between steric repulsion and nonspecific attraction among macromolecules was not systematically addressed. In this work, we study the problem of diffusion-interaction in the bacterial cytoplasm, combining theory and experimental data to build a minimal coarse-grained representation of the cytoplasm, which also includes, for the first time to our knowledge, the nucleoid. With stochastic molecular-dynamics simulations of a virtual cytoplasm we are able to track the single biomolecule motion, sizing from 3 to 80 nm, on submillisecond-long trajectories. We demonstrate that the size dependence of diffusion coefficients, anomalous exponents, and the effective viscosity experienced by biomolecules in the cytoplasm is fine-tuned by the intermolecular interactions. Accounting only for excluded volume in these potentials gives a weaker size-dependence than that expected from experimental data. On the contrary, adding nonspecific attraction in the range of 1-10 thermal energy units produces a stronger variation of the transport properties at growing biopolymer sizes. Normal and anomalous diffusive regimes emerge straightforwardly from the combination of high macromolecular concentration, poly-dispersity, stochasticity, and weak nonspecific interactions. As a result, small biopolymers experience a viscous cytoplasm, while the motion of big ones is jammed because the entanglements produced by the network of interactions and the entropic effects caused by poly-dispersity are stronger.

Biochemical properties and aggregation propensity of transforming growth factor-induced protein (TGFBIp) and the amyloid forming mutants

TGFBI-associated corneal dystrophies are characterized by accumulation of insoluble deposits of the mutant protein transforming growth factor β-induced protein (TGFBIp) in the cornea. Depending on the nature of mutation, the lesions appear as granular (non-amyloid) or lattice lines (amyloid) in the Bowman's layer or in the stroma. This review article emphasizes the structural biology aspects of TGFBIp. We discuss the tinctorial properties and ultrastructure of deposits observed in granular and lattice corneal dystrophic mutants with amyloid and non-amyloid forms of other human protein deposition diseases and review the biochemical and putative functional role of the protein. Using bioinformatics tools, we identify intrinsic aggregation propensity and discuss the possible protective role of gatekeepers close to the "aggregation-prone" regions of native TGFBIp. We describe the relative aggregation rates of lattice corneal dystrophy (LCD) and granular corneal dystrophy (GCD2) mutants using the three-parameter model, which is based on intrinsic properties of polypeptide chains. The predictive power of this model is compared with two other algorithms. We conclude that the model is able to predict the aggregation rate of mutants which do not alter overall net charge of the protein. The need to understand the mechanism of corneal dystrophies from the structural biology viewpoint is emphasized.

Protein aggregation in E. coli : short term and long term effects of nutrient density

During exponential growth some cells of E. coli undergo senescence mediated by asymmetric segregation of damaged components, particularly protein aggregates. We showed previously that functional cell division asymmetry in E. coli was responsive to the nutritional environment. Short term exposure as well as long term selection in low calorie environments led to greater cell division symmetry and decreased frequency of senescent cells as compared to high calorie environments. We show here that long term selection in low nutrient environment decreased protein aggregation as revealed by fluorescence microscopy and proportion of insoluble proteins. Across selection lines protein aggregation was correlated significantly positively with the RNA content, presumably indicating metabolic rate. This suggests that the effects of caloric restriction on cell division symmetry and aging in E. coli may work via altered protein handling mechanisms. The demonstrable effects of long term selection on protein aggregation suggest that protein aggregation is an evolvable phenomenon rather than being a passive inevitable process. The aggregated proteins progressively disappeared on facing starvation indicating degradation and recycling demonstrating that protein aggregation is a reversible process in E. coli.

Association between foldability and aggregation propensity in small disulfide-rich proteins

AIMS

Disulfide-rich domains (DRDs) are small proteins whose native structure is stabilized by the presence of covalent disulfide bonds. These domains are versatile and can perform a wide range of functions. Many of these domains readily unfold on disulfide bond reduction, suggesting that in the absence of covalent bonding they might display significant disorder.

RESULTS

Here, we analyzed the degree of disorder in 97 domains representative of the different DRDs families and demonstrate that, in terms of sequence, many of them can be classified as intrinsically disordered proteins (IDPs) or contain predicted disordered regions. The analysis of the aggregation propensity of these domains indicates that, similar to IDPs, their sequences are more soluble and have less aggregating regions than those of other globular domains, suggesting that they might have evolved to avoid aggregation after protein synthesis and before they can attain its compact and covalently linked native structure.

INNOVATION AND CONCLUSION

DRDs, which resemble IDPs in the reduced state and become globular when their disulfide bonds are formed, illustrate the link between protein folding and aggregation propensities and how these two properties cannot be easily dissociated, determining the main traits of the folding routes followed by these small proteins to attain their native oxidized states.

A genome-wide sequence-structure analysis suggests aggregation gatekeepers constitute an evolutionary constrained functional class

Protein aggregation is geared by aggregation-prone regions that self-associate by β-strand interactions. Charged residues and prolines are enriched at the flanks of aggregation-prone regions resulting in decreased aggregation. It is still unclear what drives the overrepresentation of these "aggregation gatekeepers", that is, whether their presence results from structural constraints determining protein stability or whether they constitute a bona fide functional class selectively maintained to control protein aggregation. As functional residues are typically conserved regardless of their cost to protein stability, we compared sequence conservation and thermodynamic cost of these residues in 2659 protein families in Escherichia coli. Across protein families, we find gatekeepers to be under strong selective conservation while at the same time representing a significant thermodynamic cost to protein structure. This finding supports the notion that aggregation gatekeepers are not structurally determined but evolutionary selected to control protein aggregation.

Production and characterization of a retinoic acid receptor RARγ construction encompassing the DNA binding domain and the disordered N-terminal proline rich domain

Gene activation by retinoic acid nuclear receptors (RAR) is regulated by a number of molecular events such as ligand binding, interaction with cognate DNA sequences and co-regulatory proteins, and phosphorylation. Among the several phosphorylation sites that are involved in the non-genomic regulatory pathways of the RAR, two are located in a proline rich domain (PRD) within the N-terminal domain (NTD) of the receptor. This region is predicted to be intrinsically disordered, complicating its production and purification. We present here an approach enabling the high yield production of RAR fragments encompassing the PRD and the DNA binding domain (DBD). We found that expression levels were dependent on where the position of the N-terminal boundary of the fragment was placed within the RAR sequence. The purification protocol involves the use of maltose binding protein as a solubilising tag and extensive centrifugation steps at critical points of the purification process. This protocol is suitable to express (15)N, (13)C labeled proteins enabling nuclear magnetic resonance studies. The resulting proteins were characterized by biophysical methods including Small Angle X-ray Scattering and NMR. These studies showed that PRD extension of RARγ is disordered in solution, a state that is compatible with modifications such as phosphorylation.

Inclusion bodies: not that bad…

The formation of inclusion bodies (IBs) constitute a frequent event during the production of heterologous proteins in bacterial hosts. Although the mechanisms leading to their formation are not completely understood, empirical data have been exploited trying to predict the aggregation propensity of specific proteins while a great number of strategies have been developed to avoid the generation of IBs. However, in many cases, the formation of such aggregates can be considered an advantage for basic research as for protein production. In this review, we focus on this positive side of IBs formation in bacteria. We present a compilation on recent advances on the understanding of IBs formation and their utilization as a model to understand protein aggregation and to explore strategies to control this process. We include recent information about their composition and structure, their use as an attractive approach to produce low cost proteins and other promising applications in Biomedicine.

Protein aggregation in bacteria: the thin boundary between functionality and toxicity

Misfolding and aggregation of proteins have a negative impact on all living organisms. In recent years, aggregation has been studied in detail due to its involvement in neurodegenerative diseases, including Alzheimer's, Parkinson's and Huntington's diseases, and type II diabetes--all associated with accumulation of amyloid fibrils. This research highlighted the central importance of protein homeostasis, or proteostasis for short, defined as the cellular state in which the proteome is both stable and functional. It implicates an equilibrium between synthesis, folding, trafficking, aggregation, disaggregation and degradation. In accordance with the eukaryotic systems, it has been documented that protein aggregation also reduces fitness of bacterial cells, but although our understanding of the cellular protein quality control systems is perhaps most detailed in bacteria, the use of bacterial proteostasis as a drug target remains little explored. Here we describe protein aggregation as a normal physiological process and its role in bacterial virulence and we shed light on how bacteria defend themselves against the toxic threat of aggregates. We review the impact of aggregates on bacterial viability and look at the ways that bacteria use to maintain a balance between aggregation and functionality. The proteostasis in bacteria can be interrupted via overexpression of proteins, certain antibiotics such as aminoglycosides, as well as antimicrobial peptides--all leading to loss of cell viability. Therefore intracellular protein aggregation and disruption of proteostatic balance in bacteria open up another strategy that should be explored towards the discovery of new antimicrobials.

Sulfur-34S stable isotope labeling of amino acids for quantification (SULAQ34) of proteomic changes in Pseudomonas fluorescens during naphthalene degradation

The relative quantification of proteins is one of the major techniques used to elucidate physiological reactions. Because it allows one to avoid artifacts due to chemical labeling, the metabolic introduction of heavy isotopes into proteins and peptides is the preferred method for relative quantification. For eukaryotic cells, stable isotope labeling by amino acids in cell culture (SILAC) has become the gold standard and can be readily applied in a vast number of scenarios. In the microbial realm, with its highly versatile metabolic capabilities, SILAC is often not feasible, and the use of other (13)C or (15)N labeled substrates might not be practical. Here, the incorporation of heavy sulfur isotopes is shown to be a useful alternative. We introduce (34)S stable isotope labeling of amino acids for quantification and the corresponding tools required for spectra extraction and disintegration of the isotopic overlaps caused by the small mass shift. As proof of principle, we investigated the proteomic changes related to naphthalene degradation in P. fluorescens ATCC 17483 and uncovered a specific oxidative-stress-like response.

Evolutionary selection for protein aggregation

Protein aggregation is being found to be associated with an increasing number of human diseases. Aggregation can lead to a loss of function (lack of active protein) or to a toxic gain of function (cytotoxicity associated with protein aggregates). Although potentially harmful, protein sequences predisposed to aggregation seem to be ubiquitous in all kingdoms of life, which suggests an evolutionary advantage to having such segments in polypeptide sequences. In fact, aggregation-prone segments are essential for protein folding and for mediating certain protein-protein interactions. Moreover, cells use protein aggregates for a wide range of functions. Against this background, life has adapted to tolerate the presence of potentially dangerous aggregation-prone sequences by constraining and counteracting the aggregation process. In the present review, we summarize the current knowledge of the advantages associated with aggregation-prone stretches in proteomes and the strategies that cellular systems have developed to control the aggregation process.

Protein aggregation profile of the human kinome

Protein aggregation into amyloid fibrils is associated with the onset of an increasing number of human disorders, including Alzheimer's disease, diabetes, and some types of cancer. The ability to form toxic amyloids appears to be a property of most polypeptides. Accordingly, it has been proposed that reducing aggregation and its effect in cell fitness is a driving force in the evolution of proteins sequences. This control of protein solubility should be especially important for regulatory hubs in biological networks, like protein kinases. These enzymes are implicated in practically all processes in normal and abnormal cell physiology, and phosphorylation is one of the most frequent protein modifications used to control protein activity. Here, we use the AGGRESCAN algorithm to study the aggregation propensity of kinase sequences. We compared them with the rest of globular proteins to decipher whether they display differential aggregation properties. In addition, we compared the human kinase complement with the kinomes of other organisms to see if we can identify any evolutionary trend in the aggregational properties of this protein superfamily. Our analysis indicates that kinase domains display significant aggregation propensity, a property that decreases with increasing organism complexity.

Cellular strategies for regulating functional and nonfunctional protein aggregation

Growing evidence suggests that aggregation-prone proteins are both harmful and functional for a cell. How do cellular systems balance the detrimental and beneficial effect of protein aggregation? We reveal that aggregation-prone proteins are subject to differential transcriptional, translational, and degradation control compared to nonaggregation-prone proteins, which leads to their decreased synthesis, low abundance, and high turnover. Genetic modulators that enhance the aggregation phenotype are enriched in genes that influence expression homeostasis. Moreover, genes encoding aggregation-prone proteins are more likely to be harmful when overexpressed. The trends are evolutionarily conserved and suggest a strategy whereby cellular mechanisms specifically modulate the availability of aggregation-prone proteins to (1) keep concentrations below the critical ones required for aggregation and (2) shift the equilibrium between the monomeric and oligomeric/aggregate form, as explained by Le Chatelier’s principle. This strategy may prevent formation of undesirable aggregates and keep functional assemblies/aggregates under control.

Thioflavin-S staining coupled to flow cytometry. A screening tool to detect in vivo protein aggregation

Amyloid deposits are associated with an increasing number of human disorders, including Alzheimer's and Parkinson's diseases. Recent studies provide compelling evidence for the existence of amyloid-like conformations in the insoluble bacterial inclusion bodies (IBs) produced during the recombinant expression of amyloidogenic proteins. This makes prokaryotic cells a physiologically relevant system to study the mechanisms of in vivo amyloid deposition. We show here that the application of flow cytometry to detect Thioflavin-S (Th-S) fluorescence provides a fast, robust, quantitative, non-invasive method to screen for the presence of in vivo intracellular amyloid-like aggregates in bacteria, with potential application in the analysis of the impact of genetic mutations or chemical compounds on the aggregation of disease-associated polypeptides.

AGGRESCAN: method, application, and perspectives for drug design

Protein aggregation underlies the development of an increasing number of conformational human diseases of growing incidence, such as Alzheimer's and Parkinson's diseases. Furthermore, the accumulation of recombinant proteins as intracellular aggregates represents a critical obstacle for the biotechnological production of polypeptides. Also, ordered protein aggregates constitute novel and versatile nanobiomaterials. Consequently, there is an increasing interest in the development of methods able to forecast the aggregation properties of polypeptides in order to modulate their intrinsic solubility. In this context, we have developed AGGRESCAN, a simple and fast algorithm that predicts aggregation-prone segments in protein sequences, compares the aggregation properties of different proteins or protein sets and analyses the effect of mutations on protein aggregation propensities.

Expression screening of fusion partners from an E. coli genome for soluble expression of recombinant proteins in a cell-free protein synthesis system

While access to soluble recombinant proteins is essential for a number of proteome studies, preparation of purified functional proteins is often limited by the protein solubility. In this study, potent solubility-enhancing fusion partners were screened from the repertoire of endogenous E. coli proteins. Based on the presumed correlation between the intracellular abundance and folding efficiency of proteins, PCR-amplified ORFs of a series of highly abundant E. coli proteins were fused with aggregation-prone heterologous proteins and then directly expressed for quantitative estimation of the expression efficiency of soluble translation products. Through two-step screening procedures involving the expression of 552 fusion constructs targeted against a series of cytokine proteins, we were able to discover a number of endogenous E. coli proteins that dramatically enhanced the soluble expression of the target proteins. This strategy of cell-free expression screening can be extended to quantitative, global analysis of genomic resources for various purposes.

An evolutionary trade-off between protein turnover rate and protein aggregation favors a higher aggregation propensity in fast degrading proteins

We previously showed the existence of selective pressure against protein aggregation by the enrichment of aggregation-opposing ‘gatekeeper’ residues at strategic places along the sequence of proteins. Here we analyzed the relationship between protein lifetime and protein aggregation by combining experimentally determined turnover rates, expression data, structural data and chaperone interaction data on a set of more than 500 proteins. We find that selective pressure on protein sequences against aggregation is not homogeneous but that short-living proteins on average have a higher aggregation propensity and fewer chaperone interactions than long-living proteins. We also find that short-living proteins are more often associated to deposition diseases. These findings suggest that the efficient degradation of high-turnover proteins is sufficient to preclude aggregation, but also that factors that inhibit proteasomal activity, such as physiological ageing, will primarily affect the aggregation of short-living proteins.

In order to carry out their biological function, proteins need to fold into well-defined three-dimensional structures. Protein aggregation is a process whereby proteins misfold into inactive and often toxic higher order structures, which is implied in about 30 human diseases such as Alzheimer's disease, Parkinson's disease and systemic amyloidosis. In earlier work it has been shown that although protein aggregation is an intrinsic property of polypeptide chains that cannot be entirely avoided, evolution has optimized protein sequences to minimize the risk of aggregation in a proteome. Here we show that this pressure is not uniform, but that proteins with a short lifetime have on average a higher aggregation propensity than long-living proteins. In addition, we show that high turnover proteins also make fewer interactions with chaperones. Taken together, these observations suggest that under normal physiological conditions the aggregation propensity of short-lived proteins does not represent a significant treat for the biochemistry of the cell. Presumably the strong dependence of these proteins on proteasomal degradation is sufficient to preclude the accumulation of aggregates. As proteasomal activity declines with age this would also explain why we observe a higher association of high turnover proteins with age-dependent aggregation-related diseases.

The aggregation properties of Escherichia coli proteins associated with their cellular abundance

Proteins are key players in most cellular processes. Therefore, their abundances are thought to be tightly regulated at the gene-expression level. Recent studies indicate, however, that steady-state cellular-protein concentrations correlate better across species than the levels of the corresponding mRNAs; this supports the existence of selective forces to maintain precise cellular-protein concentrations and homeostasis, even if gene-expression levels diverge. One of these forces might be the avoidance of protein aggregation because, in the cell, the folding of proteins into functional conformations might be in competition with anomalous aggregation into non-functional and usually toxic structures in a concentration-dependent manner. The data in the present work provide support for this hypothesis because, in E. coli, the experimental solubility of proteins correlates better with the cellular abundance than with the gene-expression levels. We found that the divergence between protein and mRNAs levels is low for high-abundance proteins. This suggests that because abundant proteins are at higher risk of aggregation, cellular concentrations need to be stringently regulated by gene expression.

Deciphering the role of the thermodynamic and kinetic stabilities of SH3 domains on their aggregation inside bacteria

The formation of insoluble deposits by globular proteins underlies the onset of many human diseases. Recent studies suggest a relationship between the thermodynamic stability of proteins and their in vivo aggregation. However, it has been argued that, in the cell, the occurrence of irreversible aggregation might shift the system from equilibrium, in such a way that it could be the rate of unfolding and associated kinetic stability instead of the conformational stability that controls protein deposition. This is an important but difficult to decipher question, because kinetic and thermodynamic stabilities appear usually correlated. Here we address this issue by comparing the in vitro folding kinetics and stability features of a set of non-natural SH3 domains with their aggregation properties when expressed in bacteria. In addition, we compare the in vitro stability of the isolated domains with their effective stability in conditions that mimic the cytosolic environment. Overall, the data argue in favor of a thermodynamic rather than a kinetic control of the intracellular aggregation propensities of small globular proteins in which folding and unfolding velocities largely exceed aggregation rates. These results have implications regarding the evolution of proteins.

Connecting peptide physicochemical and antimicrobial properties by a rational prediction model

The increasing rate in antibiotic-resistant bacterial strains has become an imperative health issue. Thus, pharmaceutical industries have focussed their efforts to find new potent, non-toxic compounds to treat bacterial infections. Antimicrobial peptides (AMPs) are promising candidates in the fight against antibiotic-resistant pathogens due to their low toxicity, broad range of activity and unspecific mechanism of action. In this context, bioinformatics' strategies can inspire the design of new peptide leads with enhanced activity. Here, we describe an artificial neural network approach, based on the AMP's physicochemical characteristics, that is able not only to identify active peptides but also to assess its antimicrobial potency. The physicochemical properties considered are directly derived from the peptide sequence and comprise a complete set of parameters that accurately describe AMPs. Most interesting, the results obtained dovetail with a model for the AMP's mechanism of action that takes into account new concepts such as peptide aggregation. Moreover, this classification system displays high accuracy and is well correlated with the experimentally reported data. All together, these results suggest that the physicochemical properties of AMPs determine its action. In addition, we conclude that sequence derived parameters are enough to characterize antimicrobial peptides.

Impact of translational error-induced and error-free misfolding on the rate of protein evolution

Theoretical calculations suggest that, in addition to translational error-induced protein misfolding, a non-negligible fraction of misfolded proteins are error free.

We propose that the anticorrelation between the expression level of a protein and its rate of sequence evolution be explained by an overarching protein-misfolding-avoidance hypothesis that includes selection against both error-induced and error-free protein misfolding, and verify this model by a molecular-level evolutionary simulation.

We provide strong empirical evidence for the protein-misfolding-avoidance hypothesis, including a positive correlation between protein expression level and stability, enrichment of misfolding-minimizing codons and amino acids in highly expressed genes, and stronger evolutionary conservation of residues in which nonsynonymous changes are more likely to increase protein misfolding.

The rate of protein sequence evolution has long been of central interest to molecular evolutionists. Different proteins of the same species evolve at vastly different rates, which is commonly explained by a variation in functional constraint among different proteins (Kimura and Ohta, 1974). However, it is unclear how to quantify the functional constraint of a protein from the knowledge of its function. In the past decade, various types of genomic data from model organisms have been examined to look for the determinants of the rate of protein sequence evolution. The most unexpected discovery was a very strong anticorrelation between the expression level and evolutionary rate of a protein (E–R anticorrelation) (Pal et al, 2001). The prevailing explanation of the E–R anticorrelation is the translational robustness hypothesis (Drummond et al, 2005). This hypothesis posits that mistranslation induces protein misfolding, which is toxic to cells (Figure 1). Consequently, highly expressed proteins are under stronger pressures to be translationally robust and thus are more constrained in sequence evolution. However, the impact of the other source of misfolded proteins, translational error-free proteins (Figure 1), has not been evaluated. By theoretical calculation, computer simulation, and empirical data analysis, we examined the role of selection against both error-induced and error-free protein misfolding in creating the E–R correlation.

Our theoretical calculations suggested that a non-negligible fraction of misfolded proteins are error free. We estimated that when a protein is not very stable, on average ∼20% of misfolded molecules are error free. However, when a protein is very stable, this fraction reduces to ∼5%, which is probably a result of natural selection against protein misfolding.

We conducted a molecular-level evolutionary simulation (Figure 2A) using three different schemes: error-induced misfolding only, error-free misfolding only, and both types of misfolding. As expected, results from the first simulation are similar to those from a previous study that considers only error-induced misfolding (Drummond and Wilke, 2008). Interestingly, the second and third simulations can also generate the same patterns, including a positive correlation between the protein expression level and the unfolding energy (ΔG) of the error-free protein (Figure 2B), a negative correlation between the expression level and the fraction of protein molecules that misfold after being mistranslated (Figure 2C), a negative correlation between ΔG and the evolutionary rate (Figure 2D), and a negative correlation between the expression level and the evolutionary rate (i.e., the E–R anticorrelation) (Figure 2E). Furthermore, we found that selection against protein misfolding is more effective in reducing error-free misfolding than error-induced misfolding.

Based on these results, we propose that an overarching protein-misfolding-avoidance hypothesis that includes both sources of misfolding is superior to the prevailing translational robustness hypothesis, which considers only error-induced misfolding. We tested three key predictions of the protein-misfolding-avoidance hypotheses using yeast data. First, we showed that, consistent with our prediction, a positive correlation exists between the protein expression level and stability, which is measured by the unfolding energy or melting temperature. In addition, protein expression level is negatively correlated with protein aggregation propensity. Second, we found that codons minimizing protein misfolding are used more frequently in highly expressed proteins than in lowly expressed ones. Third, we showed that, within the same protein, amino acid residues in which random nonsynonymous mutations are more likely to increase protein misfolding are evolutionarily more conserved.

Together, these results provide unambiguous evidence that avoidance of both error-induced and error-free protein misfolding is a major source of the E–R anticorrelation and that protein stability and mistranslation have important roles in protein evolution.

What determines the rate of protein evolution is a fundamental question in biology. Recent genomic studies revealed a surprisingly strong anticorrelation between the expression level of a protein and its rate of sequence evolution. This observation is currently explained by the translational robustness hypothesis in which the toxicity of translational error-induced protein misfolding selects for higher translational robustness of more abundant proteins, which constrains sequence evolution. However, the impact of error-free protein misfolding has not been evaluated. We estimate that a non-negligible fraction of misfolded proteins are error free and demonstrate by a molecular-level evolutionary simulation that selection against protein misfolding results in a greater reduction of error-free misfolding than error-induced misfolding. Thus, an overarching protein-misfolding-avoidance hypothesis that includes both sources of misfolding is superior to the translational robustness hypothesis. We show that misfolding-minimizing amino acids are preferentially used in highly abundant yeast proteins and that these residues are evolutionarily more conserved than other residues of the same proteins. These findings provide unambiguous support to the role of protein-misfolding-avoidance in determining the rate of protein sequence evolution.

Translationally optimal codons associate with aggregation-prone sites in proteins

We analyze the relationship between codon usage bias and residue aggregation propensity in the genomes of four model organisms, Escherichia coli, yeast, fly, and mouse, as well as the archaeon Halobacterium species NRC-1. Using the Mantel-Haenszel procedure, we find that translationally optimal codons associate with aggregation-prone residues. Our results are qualitatively and quantitatively similar to those of an earlier study where we found an association between translationally optimal codons and buried residues. We also combine the aggregation-propensity data with solvent-accessibility data. Although the resulting data set is small, and hence statistical power low, results indicate that the association between optimal codons and aggregation-prone residues exists both at buried and at exposed sites. By comparing codon usage at different combinations of sites (exposed, aggregation-prone sites versus buried, non-aggregation-prone sites; buried, aggregation-prone sites versus exposed, non-aggregation-prone sites), we find that aggregation propensity and solvent accessibility seem to have independent effects of (on average) comparable magnitude on codon usage. Finally, in fly, we assess whether optimal codons associate with sites at which amino acid substitutions lead to an increase in aggregation propensity, and find only a very weak effect. These results suggest that optimal codons may be required to reduce the frequency of translation errors at aggregation-prone sites that coincide with certain functional sites, such as protein-protein interfaces. Alternatively, optimal codons may be required for rapid translation of aggregation-prone regions.

The rate of the molecular clock and the cost of gratuitous protein synthesis

Background

The nature of the protein molecular clock, the protein-specific rate of amino acid substitutions, is among the central questions of molecular evolution. Protein expression level is the dominant determinant of the clock rate in a number of organisms. It has been suggested that highly expressed proteins evolve slowly in all species mainly to maintain robustness to translation errors that generate toxic misfolded proteins. Here we investigate this hypothesis experimentally by comparing the growth rate of Escherichia coli expressing wild type and misfolding-prone variants of the LacZ protein.

Results

We show that the cost of toxic protein misfolding is small compared to other costs associated with protein synthesis. Complementary computational analyses demonstrate that there is also a relatively weaker, but statistically significant, selection for increasing solubility and polarity in highly expressed E. coli proteins.

Conclusions

Although we cannot rule out the possibility that selection against misfolding toxicity significantly affects the protein clock in species other than E. coli, our results suggest that it is unlikely to be the dominant and universal factor determining the clock rate in all organisms. We find that in this bacterium other costs associated with protein synthesis are likely to play an important role. Interestingly, our experiments also suggest significant costs associated with volume effects, such as jamming of the cellular environment with unnecessary proteins.

Protein folding and aggregation in bacteria

Proteins might experience many conformational changes and interactions during their lifetimes, from their synthesis at ribosomes to their controlled degradation. Because, in most cases, only folded proteins are functional, protein folding in bacteria is tightly controlled genetically, transcriptionally, and at the protein sequence level. In addition, important cellular machinery assists the folding of polypeptides to avoid misfolding and ensure the attainment of functional structures. When these redundant protective strategies are overcome, misfolded polypeptides are recruited into insoluble inclusion bodies. The protein embedded in these intracellular deposits might display different conformations including functional and beta-sheet-rich structures. The latter assemblies are similar to the amyloid fibrils characteristic of several human neurodegenerative diseases. Interestingly, bacteria exploit the same structural principles for functional properties such as adhesion or cytotoxicity. Overall, this review illustrates how prokaryotic organisms might provide the bedrock on which to understand the complexity of protein folding and aggregation in the cell.