Cell-wide analysis of protein thermal unfolding reveals determinants of thermostability

Protein Solubility Predictions Using the CamSol Method in the Study of Protein Homeostasis

One of the major functions of the protein homeostasis system is to maintain proteins in their soluble states, and indeed several human disorders are associated with the aberrant aggregation of proteins. An active involvement of the protein homeostasis system is necessary to avoid aggregation because proteins are expressed at levels close to their solubility limits, hence being poorly soluble. The mechanisms by which the protein homeostasis system acts to control protein aggregation are, however, still not known in much detail. To facilitate systematic investigations of these mechanisms, we describe here the CamSol method of predicting protein solubility, and illustrate its initial applications. We anticipate that with the advent of powerful proteomics and transcriptomic methods, in combination with the use of the CamSol method and related approaches to predict the solubility and other biophysical properties of proteins, it will become possible to increase our understanding of the principles of protein homeostasis related to the maintenance of the proteome in its soluble form.

Mass spectrometric approaches for profiling protein folding and stability

Protein stability reports on protein homeostasis, function, and binding interactions, such as to other proteins, metabolites and drugs. As such, there is a pressing need for technologies that can report on protein stability. The ideal technique could be applied in vitro or in vivo systems, proteome-wide, independently of matrix, under native conditions, with residue-level resolution, and on protein at endogenous levels. Mass spectrometry has rapidly become a preferred technology for identifying and quantifying proteins. As such, it has been increasingly incorporated into methodologies for interrogating protein stability and folding. Although no single technology can satisfy all desired applications, several emerging approaches have shown outstanding success at providing biological insight into the stability of the proteome. This chapter outlines some of these recent emerging technologies.

On the relationship between structure and catalytic effectiveness in solid surface-immobilized enzymes: Advances in methodology and the quest for a single-molecule perspective

The integration of enzymes with solid materials is important in many biotechnological applications, including the use of immobilized enzymes for biocatalytic synthesis. The development of functional enzyme-material composites is restrained by the lack of molecular-level insight into the behavior of enzymes in confined, surface-near environments. Here, we review recent advances in surface-sensitive spectroscopic techniques that push boundaries for the determination of enzyme structure and orientation at the solid-liquid interface. We discuss recent evidence from single-molecule studies showing that analyses sensitive to the temporal and spatial heterogeneities in immobilized enzymes can succeed in disentangling the effects of conformational stability and active-site accessibility on activity. Different immobilization methods involve distinct trade-off between these effects, thus emphasizing the need for a holistic (systems) view of immobilized enzymes for the rational development of practical biocatalysts.

ProTstab - predictor for cellular protein stability

BACKGROUND

Stability is one of the most fundamental intrinsic characteristics of proteins and can be determined with various methods. Characterization of protein properties does not keep pace with increase in new sequence data and therefore even basic properties are not known for far majority of identified proteins. There have been some attempts to develop predictors for protein stabilities; however, they have suffered from small numbers of known examples.

RESULTS

We took benefit of results from a recently developed cellular stability method, which is based on limited proteolysis and mass spectrometry, and developed a machine learning method using gradient boosting of regression trees. ProTstab method has high performance and is well suited for large scale prediction of protein stabilities.

CONCLUSIONS

The Pearson's correlation coefficient was 0.793 in 10-fold cross validation and 0.763 in independent blind test. The corresponding values for mean absolute error are 0.024 and 0.036, respectively. Comparison with a previously published method indicated ProTstab to have superior performance. We used the method to predict stabilities of all the remaining proteins in the entire human proteome and then correlated the predicted stabilities to protein chain lengths of isoforms and to localizations of proteins.

Nanosecond photochemically promoted click chemistry for enhanced neuropeptide visualization and rapid protein labeling

Comprehensive protein identification and concomitant structural probing of proteins are of great biological significance. However, this is challenging to accomplish simultaneously in one confined space. Here, we develop a nanosecond photochemical reaction (nsPCR)-based click chemistry, capable of structural probing of proteins and enhancing their identifications through on-demand removal of surrounding matrices within nanoseconds. The nsPCR is initiated using a photoactive compound, 2-nitrobenzaldehyde (NBA), and is examined by matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS). Benefiting from the on-demand matrix-removal effect, this nsPCR strategy enables enhanced neuropeptide identification and visualization from complex tissue samples such as mouse brain tissue. The design shows great promise for structural probing of proteins up to 155 kDa due to the exclusive accessibility of nsPCR to primary amine groups, as demonstrated by its general applicability using a series of proteins with various lysine residues from multiple sample sources, with accumulated labeling efficiencies greater than 90%.

Mass spectrometry-based quantitative proteomics aim to identify and quantify proteins from complex biological samples. Here, the authors developed a method for simultaneous high-throughput protein labelling and on-demand matrix removal within nanoseconds.

Thermal monitoring during photothermia: hybrid probes for simultaneous plasmonic heating and near-infrared optical nanothermometry

The control of temperature during photothermal therapy is key to preventing unwanted damage in surrounding tissue or post-treatment inflammatory responses. Lack of accurate thermal control is indeed one of the main limitations that hyperthermia techniques present to allow their translation into therapeutic applications. We developed a nanoprobe that allows controlled local heating, combined with in situ nanothermometry. The design of the probe follows a practical rationale that aims at simplifying experimental requirements and exploits exclusively optical wavelengths matching the first and second biological windows in the near-infrared. Methods: Hybrid nanostructures were chemically synthesized, and combine gold nanostars (photothermal agents) with CaF₂:Nd³⁺,Y³⁺ nanoparticles (luminescent nanothermometers). Both components were simultaneously excited in the near-infrared range, at 808 nm. Following the goal of simplifying the thermal monitoring technique, the luminescent signal was recorded with a portable near-infrared detector. The performance of the probes was tested in 3D tumor spheroids from a human glioblastoma (U87MG) cell line. The location of the beads within the spheroids was determined measuring Nd³⁺ emission in a commercial Lightsheet microscope, modified in-house to be able to select the required near-infrared wavelengths. The temperature achieved inside the tumor spheroids was deduced from the luminescence of Nd³⁺, following a protocol that we developed to provide reliable thermal readings. Results: The choice of materials was shown to work as an optically excited hybrid probe. Depending on the illumination parameters, temperature can be controlled in a range between 37 ºC and 100 ºC. The near-infrared emission of nanothermometers also allows microscopic tracking of the hybrid nanostructures, confirming that the probes can penetrate deeper into the spheroid mass. We observed that, application of optical thermometry in biological environments requires often neglected considerations, since the optical signal changes along the optical path. Accordingly, we developed data analysis protocols that guarantee reliable thermal readings. Conclusions: The prepared hybrid probes are internalized in 3D tumor spheroids and can be used to induce cell death through photothermal effects, while simultaneously measuring the local temperature in situ. We show that luminescent thermometry in biomedical applications requires the development of protocols that guarantee accurate readings. Regarding photothermal treatments, we observe a sharp thermal threshold at around 55 ºC (for 10 min treatments) that separates high survival ratio from complete cell death.

Thermal sensitivity as a quality control attribute for biotherapeutics: The L-asparaginase case

Thermal sensitivity, as a practical measure of thermostability, is an interesting quality attribute that can be used in the quality control (QC) release of biopharmaceuticals. This article investigates circular dichroism (CD) spectroscopy and nano-differential scanning fluorimetry (nano-DSF) to evaluate the thermal stability of E.coli L-asparaginase (L-ASNase) for QC purposes. In CD, molar ellipticity as a function of temperature (from 20 to 80°C) was measured at 222 nm. Different L-ASNase samples dissolved in different diluents were investigated by determining the melting temperature (T_m ) from the first derivative curve as well as the slope of the fitted sigmoidal function of the temperature gradient CD data. The obtained T_m values could be correlated with the L-ASNase sample origin as well as with the pH of the diluent. The T_m values obtained from the CD data were moreover consistent with the T_m values determined by nano-DSF, confirming their reliability. Next to the T_m value, also the slope of the fitted sigmoidal CD-function was able to differentiate different L-ASNase samples, including unstressed from stressed protein. By using both the T_m and the curve slope, the thermal stability of L-ASNase was investigated, demonstrating and recommending the use of this heat-stress characteristic as a QC quality attribute of proteins, which can be applied to detect substandard and falsified proteins.

Protein Melting Temperature Cannot Fully Assess Whether Protein Folding Free Energy Underlies the Universal Abundance-Evolutionary Rate Correlation Seen in Proteins

The protein misfolding avoidance hypothesis explains the universal negative correlation between protein abundance and sequence evolutionary rate across the proteome by identifying protein folding free energy (ΔG) as the confounding variable. Abundant proteins resist toxic misfolding events by being more stable, and more stable proteins evolve slower because their mutations are more destabilizing. Direct supporting evidence consists only of computer simulations. A study taking advantage of a recent experimental breakthrough in measuring protein stability proteome-wide through melting temperature (Tm) (Leuenberger et al. 2017), found weak misfolding avoidance hypothesis support for the Escherichia coli proteome, and no support for the Saccharomyces cerevisiae, Homo sapiens, and Thermus thermophilus proteomes (Plata and Vitkup 2018). I find that the nontrivial relationship between Tm and ΔG and inaccuracy in Tm measurements by Leuenberger et al. 2017 can be responsible for not observing strong positive abundance-Tm and strong negative Tm-evolutionary rate correlations.

Solution thermochemistry of concanavalin A tetramer conformers measured by variable-temperature ESI-IMS-MS

Variable-temperature nano-electrospray ionization coupled with ion mobility spectrometry-mass spectrometry is used to investigate the thermal denaturation of the tetrameric protein concanavalin A. As the solution temperature is increased, changes in mass spectra and collision cross section distributions provide evidence for discrete structural changes that occur at temperatures that are ~40 to 50 degrees below the temperature required for tetramer dissociation. The subtle structural changes are associated with four distinct tetramer conformations with unique melting temperatures. Gibbs-Helmholtz analysis of the free energies determined with respect to the most abundant "native" state yields heat capacities of ΔC_p = 1.6 ± 0.3, -2.2 ± 0.4, and -2.9 ± 1.6 kJ·K^-1·mol^-1, and temperature dependent enthalpies and entropies for the three non-native conformations. Analysis of the thermochemistry indicates that the high-temperature products are entropically stable until the threshold for tetramer dissociation, and changes in heat capacity are consistent with increases in solvation of polar residues. Our findings suggest these high-temperature non-native states result from an increase in disorder at surface exposed regions. Such studies provide valuable insight towards the structural details of non-native states.

New insights on human essential genes based on integrated analysis and the construction of the HEGIAP web-based platform

Essential genes are those whose loss of function compromises organism viability or results in profound loss of fitness. Recent gene-editing technologies have provided new opportunities to characterize essential genes. Here, we present an integrated analysis that comprehensively and systematically elucidates the genetic and regulatory characteristics of human essential genes. First, we found that essential genes act as ‘hubs’ in protein–protein interaction networks, chromatin structure and epigenetic modification. Second, essential genes represent conserved biological processes across species, although gene essentiality changes differently among species. Third, essential genes are important for cell development due to their discriminate transcription activity in embryo development and oncogenesis. In addition, we developed an interactive web server, the Human Essential Genes Interactive Analysis Platform (http://sysomics.com/HEGIAP/), which integrates abundant analytical tools to enable global, multidimensional interpretation of gene essentiality. Our study provides new insights that improve the understanding of human essential genes.

Exploiting Interdata Relationships in Next-generation Proteomics Analysis

Mass spectrometry based proteomics and other technologies have matured to enable routine quantitative, system-wide analysis of concentrations, modifications, and interactions of proteins, mRNAs, and other molecules. These studies have allowed us to move toward a new field concerned with mining information from the combination of these orthogonal data sets, perhaps called "integromics." We highlight examples of recent studies and tools that aim at relating proteomic information to mRNAs, genetic associations, and changes in small molecules and lipids. We argue that productive data integration differs from parallel acquisition and interpretation and should move toward quantitative modeling of the relationships between the data. These relationships might be expressed by temporal information retrieved from time series experiments, rate equations to model synthesis and degradation, or networks of causal, evolutionary, physical, and other interactions. We outline steps and considerations toward such integromic studies to exploit the synergy between data sets.

Structural Basis of the Subcellular Topology Landscape of Escherichia coli

Cellular proteomes are distributed in multiple compartments: on DNA, ribosomes, on and inside membranes, or they become secreted. Structural properties that allow polypeptides to occupy subcellular niches, particularly to after crossing membranes, remain unclear. We compared intrinsic and extrinsic features in cytoplasmic and secreted polypeptides of the Escherichia coli K-12 proteome. Structural features between the cytoplasmome and secretome are sharply distinct, such that a signal peptide-agnostic machine learning tool distinguishes cytoplasmic from secreted proteins with 95.5% success. Cytoplasmic polypeptides are enriched in aliphatic, aromatic, charged and hydrophobic residues, unique folds and higher early folding propensities. Secretory polypeptides are enriched in polar/small amino acids, β folds, have higher backbone dynamics, higher disorder and contact order and are more often intrinsically disordered. These non-random distributions and experimental evidence imply that evolutionary pressure selected enhanced secretome flexibility, slow folding and looser structures, placing the secretome in a distinct protein class. These adaptations protect the secretome from premature folding during its cytoplasmic transit, optimize its lipid bilayer crossing and allowed it to acquire cell envelope specific chemistries. The latter may favor promiscuous multi-ligand binding, sensing of stress and cell envelope structure changes. In conclusion, enhanced flexibility, slow folding, looser structures and unique folds differentiate the secretome from the cytoplasmome. These findings have wide implications on the structural diversity and evolution of modern proteomes and the protein folding problem.

A Suggestion of Converting Protein Intrinsic Disorder to Structural Entropy Using Shannon's Information Theory

We propose a framework to convert the protein intrinsic disorder content to structural entropy (H) using Shannon’s information theory (IT). The structural capacity (C), which is the sum of H and structural information (I), is equal to the amino acid sequence length of the protein. The structural entropy of the residues expands a continuous spectrum, ranging from 0 (fully ordered) to 1 (fully disordered), consistent with Shannon’s IT, which scores the fully-determined state 0 and the fully-uncertain state 1. The intrinsically disordered proteins (IDPs) in a living cell may participate in maintaining the high-energy-low-entropy state. In addition, under this framework, the biological functions performed by proteins and associated with the order or disorder of their 3D structures could be explained in terms of information-gains or entropy-losses, or the reverse processes.

Protein Phase Separation as a Stress Survival Strategy

Cells under stress must adjust their physiology, metabolism, and architecture to adapt to the new conditions. Most importantly, they must down-regulate general gene expression, but at the same time induce synthesis of stress-protective factors, such as molecular chaperones. Here, we investigate how the process of phase separation is used by cells to ensure adaptation to stress. We summarize recent findings and propose that the solubility of important translation factors is specifically affected by changes in physical-chemical parameters such temperature or pH and modulated by intrinsically disordered prion-like domains. These stress-triggered changes in protein solubility induce phase separation into condensates that regulate the activity of the translation factors and promote cellular fitness. Prion-like domains play important roles in this process as environmentally regulated stress sensors and modifier sequences that determine protein solubility and phase behavior. We propose that protein phase separation is an evolutionary conserved feature of proteins that cells harness to regulate adaptive stress responses and ensure survival in extreme environmental conditions.

Kinetic versus thermodynamic control of mutational effects on protein homeostasis: A perspective from computational modeling and experiment

The effect of mutations in individual proteins on protein homeostasis, or "proteostasis," can in principle depend on the mutations' effects on the thermodynamics or kinetics of folding, or both. Here, we explore this issue using a computational model of in vivo protein folding that we call FoldEcoSlim. Our model predicts that kinetic versus thermodynamic control of mutational effects on proteostasis hinges on the relationship between how fast a protein's folding reaction reaches equilibrium and a critical time scale that characterizes the lifetime of a protein in its environment: for rapidly dividing bacteria, this time scale is that of cell division; for proteins that are produced in heterologous expression systems, this time scale is the amount of time before the protein is harvested; for proteins that are synthesized in and then exported from the eukaryotic endoplasmic reticulum, this time scale is that of protein secretion, and so forth. This prediction was validated experimentally by examining the expression yields of the wild type and several destabilized mutants of a model protein, the mouse ortholog of cellular retinoic acid-binding protein 1.

Infinite Assembly of Folded Proteins in Evolution, Disease, and Engineering

Mutations and changes in a protein's environment are well known for their potential to induce misfolding and aggregation, including amyloid formation. Alternatively, such perturbations can trigger new interactions that lead to the polymerization of folded proteins. In contrast to aggregation, this process does not require misfolding and, to highlight this difference, we refer to it as agglomeration. This term encompasses the amorphous assembly of folded proteins as well as the polymerization in one, two, or three dimensions. We stress the remarkable potential of symmetric homo-oligomers to agglomerate even by single surface point mutations, and we review the double-edged nature of this potential: how aberrant assemblies resulting from agglomeration can lead to disease, but also how agglomeration can serve in cellular adaptation and be exploited for the rational design of novel biomaterials.

Single-Component Bismuth Nanoparticles as a Theranostic Agent for Multimodal Imaging-Guided Glioma Therapy

Single-component nanomaterials such as bismuth (Bi) based on nanoparticles (NPs) intrinsically having both diagnostic and therapeutic capabilities are widely needed in biomedical fields. However, their design and fabrication still face enormous challenges. Here, a kind of pure Bi NPs with ultrahigh X-ray attenuation coeffcient was developed and evaluated as a simple but powerful theranostic nanomaterals and potent light-to-heat conversion efficiency for photoacuostic imaging (PAI)/photothermal therapy (PTT) in this study. The prepared pure Bi NPs showed excellent photothermal performance and the temperature of NPs solution (1 mg/mL) increased to 70 °C under near-infrared light irradiation within 4 min. The pure Bi NPs showed obvious enhancement effect both in X-ray computed tomography (CT) and PA imaging modalities in vivo. In addition, the glioma growth was efficiently suppressed by the pure Bi NPs after 808 nm laser irradiation, while maintained the biosafety and low toxicity. Thus, it is notable that this type of Bi nanomaterial has great potential in multi-imaging guided cancer treatment.

Emerging roles of allosteric modulators in the regulation of protein-protein interactions (PPIs): A new paradigm for PPI drug discovery

Protein-protein interactions (PPIs) are closely implicated in various types of cellular activities and are thus pivotal to health and disease states. Given their fundamental roles in a wide range of biological processes, the modulation of PPIs has enormous potential in drug discovery. However, owing to the general properties of large, flat, and featureless interfaces of PPIs, previous attempts have demonstrated that the generation of therapeutic agents targeting PPI interfaces is challenging, rendering them almost "undruggable" for decades. To date, rapid progress in chemical and structural biology techniques has promoted the exploitation of allostery as a novel approach in drug discovery. By attaching to allosteric sites that are topologically and spatially distinct from PPI interfaces, allosteric modulators can achieve improved physiochemical properties. Thus, allosteric modulators may represent an alternative strategy to target intractable PPIs and have attracted intense pharmaceutical interest. In this review, we first briefly introduce the characteristics of PPIs and then present different approaches for investigating PPIs, as well as the latest methods for modulating PPIs. Importantly, we comprehensively review the recent progress in the development of allosteric modulators to inhibit or stabilize PPIs. Finally, we conclude with future perspectives on the discovery of allosteric PPI modulators, especially the application of computational methods to aid in allosteric PPI drug discovery.

Protein corona formed on silver nanoparticles in blood plasma is highly selective and resistant to physicochemical changes of the solution

Nanoparticles (NPs) in contact with protein-containing media such as biological fluids rapidly acquire a surface layer of proteins, known as the protein corona. The protein composition and structural properties of the protein corona are crucial for NP interactions with living cells. Although much has been learned about the protein corona phenomenon, further elucidation could benefit from extensive quantitative proteomics analysis. Herein we report a comprehensive quantitative characterization (>350 proteins) of the corona that formed on 60 nm silver NPs via interaction with human blood plasma, as a function of pH and temperature. By varying the pH and temperature one can access different conformational spaces and charge localizations of the plasma proteins, which in turn provide knowledge pertinent to how the proteome corresponds to binding affinity. Thirty-eight percent of the quantified proteins bind at all temperatures, 47% at all pH values, and of these most persistent proteins, approximately 60% do not significantly change in abundance within the protein corona. Evaluation of 544 protein properties (present in the Kyoto databank) suggests that binding of these proteins to NPs is determined by the extent of hydrophobicity, β-sheet propensity, α-helical structure (and turns), and amino acid composition. Protein binding is promoted by a larger amount of β-sheets, higher hydrophobicity, and a smaller amount of α-helices. Our work enhances researchers' knowledge of a long-standing, vexing aspect of the nano-bio interface.

Global analysis of methionine oxidation provides a census of folding stabilities for the human proteome

The stability of proteins influences their tendency to aggregate, undergo degradation, or become modified in cells. Despite their significance to understanding protein folding and function, quantitative analyses of thermodynamic stabilities have been mostly limited to soluble proteins in purified systems. We have used a highly multiplexed proteomics approach, based on analyses of methionine oxidation rates, to quantify stabilities of ∼10,000 unique regions within ∼3,000 proteins in human cell extracts. The data identify lysosomal and extracellular proteins as the most stable ontological subsets of the proteome. We show that the stability of proteins impacts their tendency to become oxidized and is globally altered by the osmolyte trimethylamine N-oxide (TMAO). We also show that most proteins designated as intrinsically disordered retain their unfolded structure in the complex environment of the cell. Together, the data provide a census of the stability of the human proteome and validate a methodology for global quantitation of folding thermodynamics.

Mapping Molecular Structure of Protein Locating on Nanoparticles with Limited Proteolysis

The molecular structure of a protein could be altered when it is attached to nanoparticles (NPs), affecting the performance of NPs present in biological systems. Limited proteolysis coupled with LC-MS/MS could reveal the changes in protein structure when it binds to a variety of entities, including macro-molecules and small drugs, but it has not yet been applied to study protein-NP interaction. Herein, adsorption of proteins, transferrin, and catalase on the polystyrene (PS) or iron oxide (IO) NPs was analyzed with this method. Both increased and decreased proteolytic efficiency in certain regions on the proteins were observed. Identification of the peptides affected by protein-NP interaction led to proper prediction of alterations to protein function as well as to colloidal stability of NPs. Overall, the present work has demonstrated the utility of limited proteolysis in helping to elucidate the potential biological outcomes of the protein-NP conjugate, obtaining knowledge to guide improvement of the rational design of the protein-conjugated NPs for biomedical applications and to understand the biological behaviors of the engineered NPs.

Ion Mobility Mass Spectrometry Uncovers the Impact of the Patterning of Oppositely Charged Residues on the Conformational Distributions of Intrinsically Disordered Proteins

The global dimensions and amplitudes of conformational fluctuations of intrinsically disordered proteins are governed, in part, by the linear segregation versus clustering of oppositely charged residues within the primary sequence. Ion mobility-mass spectrometry (IM-MS) affords unique advantages for probing the conformational consequences of the linear patterning of oppositely charged residues because it measures and separates proteins electrosprayed from solution on the basis of charge and shape. Here, we use IM-MS to measure the conformational consequences of charge patterning on the C-terminal intrinsically disordered region (p27 IDR) of the cell cycle inhibitory protein p27^Kip1. We report the range of charge states and accompanying collisional cross section distributions for wild-type p27 IDR and two variants with identical amino acid compositions, κ14 and κ56, distinguished by the extent of linear mixing versus segregation of oppositely charged residues. Wild-type p27 IDR (κ31) and κ14, where the oppositely charged residues are more evenly distributed, exhibit a broad distribution of charge states. This is concordant with high degrees of conformational heterogeneity in solution. By contrast, κ56 with linear segregation of oppositely charged residues leads to limited conformational heterogeneity and a narrow distribution of charged states. Gas-phase molecular dynamics simulations demonstrate that the interplay between chain solvation and intrachain interactions (self-solvation) leads to conformational distributions that are modulated by salt concentration, with the wild-type sequence showing the most sensitivity to changes in salt concentration. These results suggest that the charge patterning within the wild-type p27 IDR may be optimized to sample both highly solvated and self-solvated conformational states.

Thermophilic Adaptation in Prokaryotes Is Constrained by Metabolic Costs of Proteostasis

Prokaryotes evolved to thrive in an extremely diverse set of habitats, and their proteomes bear signatures of environmental conditions. Although correlations between amino acid usage and environmental temperature are well-documented, understanding of the mechanisms of thermal adaptation remains incomplete. Here, we couple the energetic costs of protein folding and protein homeostasis to build a microscopic model explaining both the overall amino acid composition and its temperature trends. Low biosynthesis costs lead to low diversity of physical interactions between amino acid residues, which in turn makes proteins less stable and drives up chaperone activity to maintain appropriate levels of folded, functional proteins. Assuming that the cost of chaperone activity is proportional to the fraction of unfolded client proteins, we simulated thermal adaptation of model proteins subject to minimization of the total cost of amino acid synthesis and chaperone activity. For the first time, we predicted both the proteome-average amino acid abundances and their temperature trends simultaneously, and found strong correlations between model predictions and 402 genomes of bacteria and archaea. The energetic constraint on protein evolution is more apparent in highly expressed proteins, selected by codon adaptation index. We found that in bacteria, highly expressed proteins are similar in composition to thermophilic ones, whereas in archaea no correlation between predicted expression level and thermostability was observed. At the same time, thermal adaptations of highly expressed proteins in bacteria and archaea are nearly identical, suggesting that universal energetic constraints prevail over the phylogenetic differences between these domains of life.

DnaJ chaperones contribute to canalization

Canalization, an intrinsic robustness of development to external (environmental) or internal (genetic) perturbations, was first proposed over half a century ago. However, whether the robustness to environmental stress (environmental canalization [EC]) and to genetic variation (genetic canalization) are underpinned by the same molecular basis remains elusive. The recent discovery of the involvement of two endoplasmic reticulum (ER)-associated DnaJ genes in developmental buffering, orthologues of which are conserved across Metazoa, indicates that the role of ER-associated DnaJ genes might be conserved across the animal kingdom. To test this, we surveyed the ER-associated DnaJ chaperones in the nematode Caenorhabditis elegans. We then quantified the phenotype, in the form of variance and mean of seam cell counts, from RNA interference knockdown of DnaJs under three different temperatures. We find that seven out of eight ER-associated DnaJs are involved in either EC or microenvironmental canalization. Moreover, we also found two DnaJ genes not specifically associated with ER (DNAJC2/dnj-11 and DNAJA2/dnj-19) were involved in canalization. Protein expression pattern showed that these DnaJs are upregulated by heat stress, yet not all of them are expressed in the seam cells. Moreover, we found that most of the buffering DnaJs also control lifespan. We therefore concluded that a number of DnaJ chaperones, not limited to those associated with the ER, are involved in canalization as a part of the complex system that underlies development.

Feeling the Heat: Searching for Plant Thermosensors

To draw the complete picture of plant thermal signaling, it is important to find the missing links between the temperature cue, the actual sensing, and the subsequent response. In this context, several plant thermosensors have been proposed. Here, we compare these with thermosensors in various other organisms, put them in the context of thermosensing in plants, and suggest a set of criteria to which a thermosensor must adhere. Finally, we propose that more emphasis should be given to structural analysis of DNA, RNA, and proteins in light of the activity of potential thermosensors.

Proteome-wide Analysis of Protein Thermal Stability in the Model Higher Plant Arabidopsis thaliana

Modern tandem MS-based sequencing technologies allow for the parallel measurement of concentration and covalent modifications for proteins within a complex sample. Recently, this capability has been extended to probe a proteome's three-dimensional structure and conformational state by determining the thermal denaturation profile of thousands of proteins simultaneously. Although many animals and their resident microbes exist under a relatively narrow, regulated physiological temperature range, plants take on the often widely ranging temperature of their surroundings, possibly influencing the evolution of protein thermal stability. In this report we present the first in-depth look at the thermal proteome of a plant species, the model organism Arabidopsis thaliana By profiling the melting curves of over 1700 Arabidopsis proteins using six biological replicates, we have observed significant correlation between protein thermostability and several known protein characteristics, including molecular weight and the composition ratio of charged to polar amino acids. We also report on a divergence of the thermostability of the core and regulatory domains of the plant 26S proteasome that may reflect a unique property of the way protein turnover is regulated during temperature stress. Lastly, the highly replicated database of Arabidopsis melting temperatures reported herein provides baseline data on the variability of protein behavior in the assay. Unfolding behavior and experiment-to-experiment variability were observed to be protein-specific traits, and thus this data can serve to inform the design and interpretation of future targeted assays to probe the conformational status of proteins from plants exposed to different chemical, environmental and genetic challenges.

Illuminating the dark phosphoproteome

Protein phosphorylation is a major regulator of protein function and biological outcomes. This was first recognized through functional biochemical experiments, and in the past decade, major technological advances in mass spectrometry have enabled the study of protein phosphorylation on a global scale. This rapidly growing field of phosphoproteomics has revealed that more than 100,000 distinct phosphorylation events occur in human cells, which likely affect the function of every protein. Phosphoproteomics has improved the understanding of the function of even the most well-characterized protein kinases by revealing new downstream substrates and biology. However, current biochemical and bioinformatic approaches have only identified kinases for less than 5% of the phosphoproteome, and functional assignments of phosphosites are almost negligible. Notably, our understanding of the relationship between kinases and their substrates follows a power law distribution, with almost 90% of phosphorylation sites currently assigned to the top 20% of kinases. In addition, more than 150 kinases do not have a single known substrate. Despite a small group of kinases dominating biomedical research, the number of substrates assigned to a kinase does not correlate with disease relevance as determined by pathogenic human mutation prevalence and mouse model phenotypes. Improving our understanding of the substrates targeted by all kinases and functionally annotating the phosphoproteome will be broadly beneficial. Advances in phosphoproteomics technologies, combined with functional screening approaches, should make it feasible to illuminate the connectivity and functionality of the entire phosphoproteome, providing enormous opportunities for discovering new biology, therapeutic targets, and possibly diagnostics.

Crystal structure of a Thermus aquaticus diversity-generating retroelement variable protein

Diversity-generating retroelements (DGRs) are widely distributed in bacteria, archaea, and microbial viruses, and bring about unparalleled levels of sequence variation in target proteins. While DGR variable proteins share low sequence identity, the structures of several such proteins have revealed the C-type lectin (CLec)-fold as a conserved scaffold for accommodating massive sequence variation. This conservation has led to the suggestion that the CLec-fold may be useful in molecular surface display applications. Thermostability is an attractive feature in such applications, and thus we studied the variable protein of a DGR encoded by a prophage of the thermophile Thermus aquaticus. We report here the 2.8 Å resolution crystal structure of the variable protein from the T. aquaticus DGR, called TaqVP, and confirm that it has a CLec-fold. Remarkably, its variable region is nearly identical in structure to those of several other CLec-fold DGR variable proteins despite low sequence identity among these. TaqVP was found to be thermostable, which appears to be a property shared by several CLec-fold DGR variable proteins. These results provide impetus for the pursuit of the DGR variable protein CLec-fold in molecular display applications.

Third generation antibody discovery methods: in silico rational design

Owing to their outstanding performances in molecular recognition, antibodies are extensively used in research and applications in molecular biology, biotechnology and medicine. Recent advances in experimental and computational methods are making it possible to complement well-established in vivo (first generation) and in vitro (second generation) methods of antibody discovery with novel in silico (third generation) approaches. Here we describe the principles of computational antibody design and review the state of the art in this field. We then present Modular, a method that implements the rational design of antibodies in a modular manner, and describe the opportunities offered by this approach.

Ancestral diterpene cyclases show increased thermostability and substrate acceptance

Bacterial diterpene cyclases are receiving increasing attention in biocatalysis and synthetic biology for the sustainable generation of complex multicyclic building blocks. Herein, we explore the potential of ancestral sequence reconstruction (ASR) to generate remodeled cyclases with enhanced stability, activity, and promiscuity. Putative ancestors of spiroviolene synthase, a bacterial class I diterpene cyclase, display an increased yield of soluble protein of up to fourfold upon expression in the model organism Escherichia coli. Two of the resurrected enzymes, with an estimated age of approximately 1.7 million years, display an upward shift in thermostability of 7-13 °C. Ancestral spiroviolene synthases catalyze cyclization of the natural C₂₀ -substrate geranylgeranyl diphosphate (GGPP) and also accept C₁₅ farnesyl diphosphate (FPP), which is not converted by the extant enzyme. In contrast, the consensus sequence generated from the corresponding multiple sequence alignment was found to be inactive toward both substrates. Mutation of a nonconserved position within the aspartate-rich motif of the reconstructed ancestral cyclases was associated with modest effects on activity and relative substrate specificity (i.e., k_cat /K_M for GGPP over k_cat /K_M for FPP). Kinetic analyses performed at different temperatures reveal a loss of substrate saturation, when going from the ancestor with highest thermostability to the modern enzyme. The kinetics data also illustrate how an increase in temperature optimum of biocatalysis is reflected in altered entropy and enthalpy of activation. Our findings further highlight the potential and limitations of applying ASR to biosynthetic machineries in secondary metabolism.

Multiscale effects of heating and cooling on genes and gene networks

Fluctuating environments such as changes in ambient temperature represent a fundamental challenge to life. Cells must protect gene networks that protect them from such stresses, making it difficult to understand how temperature affects gene network function in general. Here, we focus on single genes and small synthetic network modules to reveal four key effects of nonoptimal temperatures at different biological scales: (i) a cell fate choice between arrest and resistance, (ii) slower growth rates, (iii) Arrhenius reaction rates, and (iv) protein structure changes. We develop a multiscale computational modeling framework that captures and predicts all of these effects. These findings promote our understanding of how temperature affects living systems and enables more robust cellular engineering for real-world applications.

Most organisms must cope with temperature changes. This involves genes and gene networks both as subjects and agents of cellular protection, creating difficulties in understanding. Here, we study how heating and cooling affect expression of single genes and synthetic gene circuits in Saccharomyces cerevisiae. We discovered that nonoptimal temperatures induce a cell fate choice between stress resistance and growth arrest. This creates dramatic gene expression bimodality in isogenic cell populations, as arrest abolishes gene expression. Multiscale models incorporating population dynamics, temperature-dependent growth rates, and Arrhenius scaling of reaction rates captured the effects of cooling, but not those of heating in resistant cells. Molecular-dynamics simulations revealed how heating alters the conformational dynamics of the TetR repressor, fully explaining the experimental observations. Overall, nonoptimal temperatures induce a cell fate decision and corrupt gene and gene network function in computationally predictable ways, which may aid future applications of engineered microbes in nonstandard temperatures.

Genetic dissection of interspecific differences in yeast thermotolerance

Some of the most unique and compelling survival strategies in the natural world are fixed in isolated species1. To date, molecular insight into these ancient adaptations has been limited, as classic experimental genetics has focused on interfertile individuals in populations2. Here we use a new mapping approach, which screens mutants in a sterile interspecific hybrid, to identify eight housekeeping genes that underlie the growth advantage of Saccharomyces cerevisiae over its distant relative S. paradoxus at high temperature. Pro-thermotolerance alleles at these mapped loci were required for the adaptive trait in S. cerevisiae and sufficient for its partial reconstruction in S. paradoxus. The emerging picture is one in which S. cerevisiae improved the heat resistance of multiple components of the fundamental growth machinery in response to selective pressure. Our study lays the groundwork for the mapping of genotype to phenotype in clades of sister species across Eukarya.

RankProt: A multi criteria-ranking platform to attain protein thermostabilizing mutations and its in vitro applications - Attribute based prediction method on the principles of Analytical Hierarchical Process

Attaining recombinant thermostable proteins is still a challenge for protein engineering. The complexity is the length of time and enormous efforts required to achieve the desired results. Present work proposes a novel and economic strategy of attaining protein thermostability by predicting site-specific mutations at the shortest possible time. The success of the approach can be attributed to Analytical Hierarchical Process and the outcome was a rationalized thermostable mutation(s) prediction tool- RankProt. Briefly the method involved ranking of 17 biophysical protein features as class predictors, derived from 127 pairs of thermostable and mesostable proteins. Among the 17 predictors, ionic interactions and main-chain to main-chain hydrogen bonds were the highest ranked features with eigen value of 0.091. The success of the tool was judged by multi-fold in silico validation tests and it achieved the prediction accuracy of 91% with AUC 0.927. Further, in vitro validation was carried out by predicting thermostabilizing mutations for mesostable Bacillus subtilis lipase and performing the predicted mutations by multi-site directed mutagenesis. The rationalized method was successful to render the lipase thermostable with optimum temperature stability and T_m increase by 20°C and 7°C respectively. Conclusively it can be said that it was the minimum number of mutations in comparison to the number of mutations incorporated to render Bacillus subtilis lipase thermostable, by directed evolution techniques. The present work shows that protein stabilizing mutations can be rationally designed by balancing the biophysical pleiotropy of proteins, in accordance to the selection pressure.

Biology/Disease-Driven Initiative on Protein-Aggregation Diseases of the Human Proteome Project: Goals and Progress to Date

The Biology/Disease-driven (B/D) working groups of the Human Proteome Project are alliances of research groups aimed at developing or improving proteomic tools to support specific biological or disease-related research areas. Here, we describe the activities and progress to date of the B/D working group focused on protein aggregation diseases (PADs). PADs are characterized by the intra- or extracellular accumulation of aggregated proteins and include devastating diseases such as Parkinson's and Alzheimer's disease and systemic amyloidosis. The PAD B/D working group aims for the development of proteomic assays for the quantification of aggregation-prone proteins involved in PADs to support basic and clinical research on PADs. Because the proteins in PADs undergo aberrant conformational changes, a goal is to quantitatively resolve altered protein structures and aggregation states in complex biological specimens. We have developed protein-extraction protocols and a set of mass spectrometric (MS) methods that enable the detection and quantification of proteins involved in the systemic and localized amyloidosis and the probing of aberrant protein conformational transitions in cell and tissue extracts. In several studies, we have demonstrated the potential of MS-based proteomics approaches for specific and sensitive clinical diagnoses and for the subtyping of PADs. The developed methods have been detailed in both protocol papers and manuscripts describing applications to facilitate implementation by nonspecialized laboratories, and assay coordinates are shared through public repositories and databases. Clinicians actively involved in the PAD working group support the transfer to clinical practice of the developed methods, such as assays to quantify specific disease-related proteins and their fragments in biofluids and multiplexed MS-based methods for the diagnosis and typing of systemic amyloidosis. We believe that the increasing availability of tools to precisely measure proteins involved in PADs will positively impact research on the molecular bases of these diseases and support early disease diagnosis and a more-confident subtyping.

Role of simple descriptors and applicability domain in predicting change in protein thermostability

The melting temperature (Tm) of a protein is the temperature at which half of the protein population is in a folded state. Therefore, Tm is a measure of the thermostability of a protein. Increasing the Tm of a protein is a critical goal in biotechnology and biomedicine. However, predicting the change in melting temperature (dTm) due to mutations at a single residue is difficult because it depends on an intricate balance of forces. Existing methods for predicting dTm have had similar levels of success using generally complex models. We find that training a machine learning model with a simple set of easy to calculate physicochemical descriptors describing the local environment of the mutation performed as well as more complicated machine learning models and is 2-6 orders of magnitude faster. Importantly, unlike in most previous publications, we perform a blind prospective test on our simple model by designing 96 variants of a protein not in the training set. Results from retrospective and prospective predictions reveal the limited applicability domain of each model. This study highlights the current deficiencies in the available dTm dataset and is a call to the community to systematically design a larger and more diverse experimental dataset of mutants to prospectively predict dTm with greater certainty.

Large-scale investigation of the reasons why potentially important genes are ignored

Biomedical research has been previously reported to primarily focus on a minority of all known genes. Here, we demonstrate that these differences in attention can be explained, to a large extent, exclusively from a small set of identifiable chemical, physical, and biological properties of genes. Together with knowledge about homologous genes from model organisms, these features allow us to accurately predict the number of publications on individual human genes, the year of their first report, the levels of funding awarded by the National Institutes of Health (NIH), and the development of drugs against disease-associated genes. By explicitly identifying the reasons for gene-specific bias and performing a meta-analysis of existing computational and experimental knowledge bases, we describe gene-specific strategies for the identification of important but hitherto ignored genes that can open novel directions for future investigation.

Biologically Targeted Magnetic Hyperthermia: Potential and Limitations

Hyperthermia, the mild elevation of temperature to 40–43°C, can induce cancer cell death and enhance the effects of radiotherapy and chemotherapy. However, achievement of its full potential as a clinically relevant treatment modality has been restricted by its inability to effectively and preferentially heat malignant cells. The limited spatial resolution may be circumvented by the intravenous administration of cancer-targeting magnetic nanoparticles that accumulate in the tumor, followed by the application of an alternating magnetic field to raise the temperature of the nanoparticles located in the tumor tissue. This targeted approach enables preferential heating of malignant cancer cells whilst sparing the surrounding normal tissue, potentially improving the effectiveness and safety of hyperthermia. Despite promising results in preclinical studies, there are numerous challenges that must be addressed before this technique can progress to the clinic. This review discusses these challenges and highlights the current understanding of targeted magnetic hyperthermia.

Thermal proteome profiling in bacteria: probing protein state in vivo

Increasing antibiotic resistance urges for new technologies for studying microbes and antimicrobial mechanism of action. We adapted thermal proteome profiling (TPP) to probe the thermostability of Escherichia coli proteins in vivoE. coli had a more thermostable proteome than human cells, with protein thermostability depending on subcellular location-forming a high-to-low gradient from the cell surface to the cytoplasm. While subunits of protein complexes residing in one compartment melted similarly, protein complexes spanning compartments often had their subunits melting in a location-wise manner. Monitoring the E. coli meltome and proteome at different growth phases captured changes in metabolism. Cells lacking TolC, a component of multiple efflux pumps, exhibited major physiological changes, including differential thermostability and levels of its interaction partners, signaling cascades, and periplasmic quality control. Finally, we combined in vitro and in vivo TPP to identify targets of known antimicrobial drugs and to map their downstream effects. In conclusion, we demonstrate that TPP can be used in bacteria to probe protein complex architecture, metabolic pathways, and intracellular drug target engagement.

Structural and functional aspects of the interaction partners of the small heat-shock protein in Synechocystis

The canonical function of small heat-shock proteins (sHSPs) is to interact with proteins destabilized under conditions of cellular stress. While the breadth of interactions made by many sHSPs is well-known, there is currently little knowledge about what structural features of the interactors form the basis for their recognition. Here, we have identified 83 in vivo interactors of the sole sHSP in the cyanobacterium Synechocystis sp. PCC 6803, HSP16.6, reflective of stable associations with soluble proteins made under heat-shock conditions. By performing bioinformatic analyses on these interactors, we identify primary and secondary structural elements that are enriched relative to expectations from the cyanobacterial genome. In addition, by examining the Synechocystis interactors and comparing them with those identified to bind sHSPs in other prokaryotes, we show that sHSPs associate with specific proteins and biological processes. Our data are therefore consistent with a picture of sHSPs being broadly specific molecular chaperones that act to protect multiple cellular pathways.

Methods to validate Hsp90 inhibitor specificity, to identify off-target effects, and to rethink approaches for further clinical development

The molecular chaperone Hsp90 is one component of a highly complex and interactive cellular proteostasis network (PN) that participates in protein folding, directs misfolded and damaged proteins for destruction, and participates in regulating cellular transcriptional responses to environmental stress, thus promoting cell and organismal survival. Over the last 20 years, it has become clear that various disease states, including cancer, neurodegeneration, metabolic disorders, and infection by diverse microbes, impact the PN. Among PN components, Hsp90 was among the first to be pharmacologically targeted with small molecules. While the number of Hsp90 inhibitors described in the literature has dramatically increased since the first such small molecule was described in 1994, it has become increasingly apparent that not all of these agents have been sufficiently validated for specificity, mechanism of action, and lack of off-target effects. Given the less than expected activity of Hsp90 inhibitors in cancer-related human clinical trials, a re-evaluation of potentially confounding off-target effects, as well as confidence in target specificity and mechanism of action, is warranted. In this commentary, we provide feasible approaches to achieve these goals and we discuss additional considerations to improve the clinical efficacy of Hsp90 inhibitors in treating cancer and other diseases.

Reliable Tracking In-Solution Protein Unfolding via Ultrafast Thermal Unfolding/Ion Mobility-Mass Spectrometry

Sequential unfolding of monomeric proteins is important for the global understanding of local conformational elements (e.g., secondary structures and domain connections) within those protein assemblies. Ion mobility-mass spectrometry (IM-MS) is an emerging and promising technique for probing gradual protein structural perturbations in the gas phase. However, it is still challenging to track sequential unfolding in the solution phase. Here, we extended IM-MS to track in-solution sequential unfolding of monomeric proteins having single and/or multidomains. The present method combines ultrafast local heating effect (LHE)-driven sequential unfolding with IM-MS identification. Protein sequential unfolding in solution is demonstrated by the rapid and controllable IM-MS data switch between native and gradually unfolded states. Our results show that LHE induces gradual protein conformational transitions associated with biological functions, where IM-MS tracks the sequential unfolding of monomeric proteins.

A Solid-State Conceptualization of Information Transfer from Gene to Message to Protein

In this review, we describe speculative ideas and early stage research concerning the flow of genetic information from the nuclear residence of genes to the disparate, cytoplasmic sites of protein synthesis. We propose that this process of information transfer is meticulously guided by transient structures formed from protein segments of low sequence complexity/intrinsic disorder. These low complexity domains are ubiquitously associated with regulatory proteins that control gene expression and RNA biogenesis, but they are also found in the central channel of nuclear pores, the nexus points of intermediate filament assembly, and the locations of action of other well-studied cellular proteins and pathways. Upon being organized into localized cellular positions via mechanisms utilizing properly folded protein domains, thereby facilitating elevated local concentration, certain low complexity domains adopt cross-β interactions that are both structurally specific and labile to disassembly. These weakly tethered assemblies, we propose, are built to relay the passage of genetic information from one site to another within a cell, ensuring that the process is of extreme fidelity.

Analysis of heat-induced protein aggregation in human mitochondria

Proteins in mammalian cells exhibit optimal stability at physiological temperatures, and even small temperature variations may cause unfolding and nonspecific aggregation. Because this process leads to a loss of function of the affected polypeptides and to cytotoxic stress, formation of protein aggregates has been recognized as a major pathogenic factor in human diseases. In this study, we determined the impact of physiological heat stress on mitochondria isolated from HeLa cells. We found that the heat-stressed mitochondria had lower membrane potential and ATP level and exhibited a decreased production of reactive oxygen species. An analysis of the mitochondrial proteome by 2D PAGE showed that the overall solubility of endogenous proteins was only marginally affected by elevated temperatures. However, a small subset of polypeptides exhibited an high sensitivity to heat stress. The mitochondrial translation elongation factor Tu (Tufm), a protein essential for organellar protein biosynthesis, was highly aggregation-prone and lost its solubility already under mild heat-stress conditions. Moreover, mitochondrial translation and the import of cytosolic proteins were defective in the heat-stressed mitochondria. Both types of nascent polypeptides, produced by translation or imported into the mitochondria, exhibited a strong tendency to aggregate in the heat-exposed mitochondria. We propose that a fast and specific inactivation of elongation factors may prevent the accumulation of misfolded nascent polypeptides and may thereby attenuate proteotoxicity under heat stress.

PAGE4 and Conformational Switching: Insights from Molecular Dynamics Simulations and Implications for Prostate Cancer

Prostate-associated gene 4 (PAGE4) is an intrinsically disordered protein implicated in prostate cancer. Thestress-response kinase homeodomain-interacting protein kinase 1 (HIPK1) phosphorylates two residues in PAGE4, serine 9 and threonine 51. Phosphorylation of these two residues facilitates the interaction of PAGE4 with activator protein-1 (AP-1) transcription factor complex to potentiate AP-1's activity. In contrast, hyperphosphorylation of PAGE4 by CDC-like kinase 2 (CLK2) attenuates this interaction with AP-1. Small-angleX-ray scattering and single-molecule fluorescence resonance energy transfer measurements have shown that PAGE4 expands upon hyperphosphorylation and that this expansion is localized to its N-terminal half. To understand the interactions underlying this structural transition, we performed molecular dynamics simulations using Atomistic AWSEM, a multi-scale molecular model that combines atomistic and coarse-grained simulation approaches. Our simulations show that electrostatic interactions drive transient formation of an N-terminal loop, the destabilization of which accounts for the dramatic change in size upon hyperphosphorylation. Phosphorylation also changes the preference of secondary structure formation of the PAGE4 ensemble, which leads to a transition between states that display different degrees of disorder. Finally, we construct a mechanism-based mathematical model that allows us to capture the interactions ofdifferent phosphoforms of PAGE4 with AP-1 and its downstream target, the androgen receptor (AR)-a key therapeutic target in prostate cancer. Our model predicts intracellular oscillatory dynamics of HIPK1-PAGE4, CLK2-PAGE4, and AR activity, indicating phenotypic heterogeneity in an isogenic cell population. Thus, conformational switching of PAGE4 may potentially affect the efficiency of therapeutically targeting AR activity.