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

Systematic thermal analysis of the Arabidopsis proteome: Thermal tolerance, organization, and evolution

Understanding the thermal stability of the plant proteome in the context of the native cellular environment would aid the design of crops with high thermal tolerance, but only limited such data are available. Here, we applied quantitative mass spectrometry to profile the thermal stability of the Arabidopsis proteome and identify thermo-sensitive and thermo-resilient protein networks in Arabidopsis, providing a basis for understanding heat-induced damage. We also show that the similarities of the protein-melting curves can be used as a proxy to evaluate system-wide protein-protein interactions in non-engineered plants and enable the identification of transient interactions exhibited by metabolons in the context of the cellular environment. Finally, we report a systematic comparison of the thermal stability of paralogs in Arabidopsis to aid the investigation and understanding of gene duplication and protein evolution. Taken together, our results could have broad implications for the fields of plant thermal tolerance, plant protein assemblies, and evolution.

Homologous Pairs of Low and High Temperature Originating Proteins Spanning the Known Prokaryotic Universe

Stability of proteins at high temperature has been a topic of interest for many years, as this attribute is favourable for applications ranging from therapeutics to industrial chemical manufacturing. Our current understanding and methods for designing high-temperature stability into target proteins are inadequate. To drive innovation in this space, we have curated a large dataset, learn2thermDB, of protein-temperature examples, totalling 24 million instances, and paired proteins across temperatures based on homology, yielding 69 million protein pairs - orders of magnitude larger than the current largest. This important step of pairing allows for study of high-temperature stability in a sequence-dependent manner in the big data era. The data pipeline is parameterized and open, allowing it to be tuned by downstream users. We further show that the data contains signal for deep learning. This data offers a new doorway towards thermal stability design models.

Principles and challenges of modeling temporal and spatial omics data

Studies with temporal or spatial resolution are crucial to understand the molecular dynamics and spatial dependencies underlying a biological process or system. With advances in high-throughput omic technologies, time- and space-resolved molecular measurements at scale are increasingly accessible, providing new opportunities to study the role of timing or structure in a wide range of biological questions. At the same time, analyses of the data being generated in the context of spatiotemporal studies entail new challenges that need to be considered, including the need to account for temporal and spatial dependencies and compare them across different scales, biological samples or conditions. In this Review, we provide an overview of common principles and challenges in the analysis of temporal and spatial omics data. We discuss statistical concepts to model temporal and spatial dependencies and highlight opportunities for adapting existing analysis methods to data with temporal and spatial dimensions.

Global analysis of aging-related protein structural changes uncovers enzyme-polymerization-based control of longevity

Aging is associated with progressive phenotypic changes. Virtually all cellular phenotypes are produced by proteins, and their structural alterations can lead to age-related diseases. However, we still lack comprehensive knowledge of proteins undergoing structural-functional changes during cellular aging and their contributions to age-related phenotypes. Here, we conducted proteome-wide analysis of early age-related protein structural changes in budding yeast using limited proteolysis-mass spectrometry (LiP-MS). The results, compiled in online ProtAge catalog, unraveled age-related functional changes in regulators of translation, protein folding, and amino acid metabolism. Mechanistically, we found that folded glutamate synthase Glt1 polymerizes into supramolecular self-assemblies during aging, causing breakdown of cellular amino acid homeostasis. Inhibiting Glt1 polymerization by mutating the polymerization interface restored amino acid levels in aged cells, attenuated mitochondrial dysfunction, and led to lifespan extension. Altogether, this comprehensive map of protein structural changes enables identifying mechanisms of age-related phenotypes and offers opportunities for their reversal.

Spotlight on Luminescence Thermometry: Basics, Challenges, and Cutting-Edge Applications

Luminescence (nano)thermometry is a remote sensing technique that relies on the temperature dependency of the luminescence features (e.g., bandshape, peak energy or intensity, and excited state lifetimes and risetimes) of a phosphor to measure temperature. This technique provides precise thermal readouts with superior spatial resolution in short acquisition times. Although luminescence thermometry is just starting to become a more mature subject, it exhibits enormous potential in several areas, e.g., optoelectronics, photonics, micro- and nanofluidics, and nanomedicine. This work reviews the latest trends in the field, including the establishment of a comprehensive theoretical background and standardized practices. The reliability, repeatability, and reproducibility of the technique are also discussed, along with the use of multiparametric analysis and artificial-intelligence algorithms to enhance thermal readouts. In addition, examples are provided to underscore the challenges that luminescence thermometry faces, alongside the need for a continuous search and design of new materials, experimental techniques, and analysis procedures to improve the competitiveness, accessibility, and popularity of the technology.

Predicting thermostability difference between cellular protein orthologs

MOTIVATION

Protein thermostability is of great interest, both in theory and in practice.

RESULTS

This study compared orthologous proteins with different cellular thermostability. A large number of physicochemical properties of protein were calculated and used to develop a series of machine learning models for predicting cellular thermostability differences between orthologous proteins. Most of the important features in these models are also highly correlated to relative cellular thermostability. A comparison between the present study with previous comparison of orthologous proteins from thermophilic and mesophilic organisms found that most highly correlated features are consistent in these studies, suggesting they may be important to protein thermostability.

AVAILABILITY AND IMPLEMENTATION

Data freely available for download at https://github.com/fangj3/cellular-protein-thermostability-dataset.

Nascent mitochondrial proteins initiate the localized condensation of cytosolic protein aggregates on the mitochondrial surface

Eukaryotes organize cellular contents into membrane-bound organelles and membrane-less condensates, for example, protein aggregates. An unsolved question is why the ubiquitously distributed proteins throughout the cytosol give rise to spatially localized protein aggregates on the organellar surface, like mitochondria. We report that the mitochondrial import receptor Tom70 is involved in the localized condensation of protein aggregates in budding yeast and human cells. This is because misfolded cytosolic proteins do not autonomously aggregate in vivo; instead, they are recruited to the condensation sites initiated by Tom70's substrates (nascent mitochondrial proteins) on the organellar membrane using multivalent hydrophobic interactions. Knocking out Tom70 partially impairs, while overexpressing Tom70 increases the formation and association between cytosolic protein aggregates and mitochondria. In addition, ectopic targeting Tom70 and its substrates to the vacuole surface is able to redirect the localized aggregation from mitochondria to the vacuolar surface. Although other redundant mechanisms may exist, this nascent mitochondrial proteins-based initiation of protein aggregation likely explains the localized condensation of otherwise ubiquitously distributed molecules on the mitochondria. Disrupting the mitochondrial association of aggregates impairs their asymmetric retention during mitosis and reduces the mitochondrial import of misfolded proteins, suggesting a proteostasis role of the organelle-condensate interactions.

Cellular Exposure to Chloroacetanilide Herbicides Induces Distinct Protein Destabilization Profiles

Herbicides in the widely used chloroacetanilide class harbor a potent electrophilic moiety, which can damage proteins through nucleophilic substitution. In general, damaged proteins are subject to misfolding. Accumulation of misfolded proteins compromises cellular integrity by disrupting cellular proteostasis networks, which can further destabilize the cellular proteome. While direct conjugation targets can be discovered through affinity-based protein profiling, there are few approaches to probe how cellular exposure to toxicants impacts the stability of the proteome. We apply a quantitative proteomics methodology to identify chloroacetanilide-destabilized proteins in HEK293T cells based on their binding to the H31Q mutant of the human Hsp40 chaperone DNAJB8. We find that a brief cellular exposure to the chloroacetanilides acetochlor, alachlor, and propachlor induces misfolding of dozens of cellular proteins. These herbicides feature distinct but overlapping profiles of protein destabilization, highly concentrated in proteins with reactive cysteine residues. Consistent with the recent literature from the pharmacology field, reactivity is driven by neither inherent nucleophilic nor electrophilic reactivity but is idiosyncratic. We discover that propachlor induces a general increase in protein aggregation and selectively targets GAPDH and PARK7, leading to a decrease in their cellular activities. Hsp40 affinity profiling identifies a majority of propachlor targets identified by competitive activity-based protein profiling (ABPP), but ABPP can only identify about 10% of protein targets identified by Hsp40 affinity profiling. GAPDH is primarily modified by the direct conjugation of propachlor at a catalytic cysteine residue, leading to global destabilization of the protein. The Hsp40 affinity strategy is an effective technique to profile cellular proteins that are destabilized by cellular toxin exposure. Raw proteomics data is available through the PRIDE Archive at PXD030635.

DiLeu Isobaric Labeling Coupled with Limited Proteolysis Mass Spectrometry for High-Throughput Profiling of Protein Structural Changes in Alzheimer's Disease

High-throughput quantitative analysis of protein conformational changes has a profound impact on our understanding of the pathological mechanisms of Alzheimer's disease (AD). To establish an effective workflow enabling quantitative analysis of changes in protein conformation within multiple samples simultaneously, here we report the combination of N,N-dimethyl leucine (DiLeu) isobaric tag labeling with limited proteolysis mass spectrometry (DiLeu-LiP-MS) for high-throughput structural protein quantitation in serum samples collected from AD patients and control donors. Twenty-three proteins were discovered to undergo structural changes, mapping to 35 unique conformotypic peptides with significant changes between the AD group and the control group. Seven out of 23 proteins, including CO3, CO9, C4BPA, APOA1, APOA4, C1R, and APOA, exhibited a potential correlation with AD. Moreover, we found that complement proteins (e.g., CO3, CO9, and C4BPA) related to AD exhibited elevated levels in the AD group compared to those in the control group. These results provide evidence that the established DiLeu-LiP-MS method can be used for high-throughput structural protein quantitation, which also showed great potential in achieving large-scale and in-depth quantitative analysis of protein conformational changes in other biological systems.

Highly Abundant Proteins Are Highly Thermostable

Highly abundant proteins tend to evolve slowly (a trend called E-R anticorrelation), and a number of hypotheses have been proposed to explain this phenomenon. The misfolding avoidance hypothesis attributes the E-R anticorrelation to the abundance-dependent toxic effects of protein misfolding. To avoid these toxic effects, protein sequences (particularly those of highly expressed proteins) would be under selection to fold properly. One prediction of the misfolding avoidance hypothesis is that highly abundant proteins should exhibit high thermostability (i.e., a highly negative free energy of folding, ΔG). Thus far, only a handful of analyses have tested for a relationship between protein abundance and thermostability, producing contradictory results. These analyses have been limited by 1) the scarcity of ΔG data, 2) the fact that these data have been obtained by different laboratories and under different experimental conditions, 3) the problems associated with using proteins' melting energy (Tm) as a proxy for ΔG, and 4) the difficulty of controlling for potentially confounding variables. Here, we use computational methods to compare the free energy of folding of pairs of human-mouse orthologous proteins with different expression levels. Even though the effect size is limited, the most highly expressed ortholog is often the one with a more negative ΔG of folding, indicating that highly expressed proteins are often more thermostable.

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics

Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.

Ion Mobility Mass Spectrometry Unveils Global Protein Conformations in Response to Conditions that Promote and Reverse Liquid-Liquid Phase Separation

Liquid-liquid phase separation (LLPS) is a process by which biomacromolecules, particularly proteins, condense into a dense phase that resembles liquid droplets. Dysregulation of LLPS is implicated in disease, yet the relationship between protein conformational changes and LLPS remains difficult to discern. This is due to the high flexibility and disordered nature of many proteins that phase separate under physiological conditions and their tendency to oligomerize. Here, we demonstrate that ion mobility mass spectrometry (IM-MS) overcomes these limitations. We used IM-MS to investigate the conformational states of full-length ubiquilin-2 (UBQLN2) protein, LLPS of which is driven by high-salt concentration and reversed by noncovalent interactions with ubiquitin (Ub). IM-MS revealed that UBQLN2 exists as a mixture of monomers and dimers and that increasing salt concentration causes the UBQLN2 dimers to undergo a subtle shift toward extended conformations. UBQLN2 binds to Ub in 2:1 and 2:2 UBQLN2/Ub complexes, which have compact geometries compared to free UBQLN2 dimers. Together, these results suggest that extended conformations of UBQLN2 are correlated with UBQLN2's ability to phase separate. Overall, delineating protein conformations that are implicit in LLPS will greatly increase understanding of the phase separation process, both in normal cell physiology and disease states.

Systematic conformation-to-phenotype mapping via limited deep sequencing of proteins

Non-native conformations drive protein-misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.

Leocarpinolide B Attenuates Collagen Type II-Induced Arthritis by Inhibiting DNA Binding Activity of NF-κB

Rheumatoid arthritis (RA) is a chronic autoimmune disease triggered by a cascading inflammatory response. Sigesbeckia Herba (SH) has long been utilized as a traditional remedy to alleviate symptoms associated with rheumatism. Our previous study found that leocarpinolide B (LB), a sesquiterpene lactone isolated from the whole plant of SH, possesses potent a anti-inflammatory effect on macrophages. This study was designed to evaluate the therapeutic effects of LB on RA, and further investigate the underlying mechanisms. In collagen type II-induced arthritic mice, LB was demonstrated to decrease the production of autoimmune antibodies in serum and inflammatory cytokines in the joint muscles and recover the decreased regulatory T lymphocytes in spleen. Moreover, LB significantly suppressed the inflammatory infiltration, formation of pannus and bone erosion in the paw joints. In vitro testing showed that LB inhibited the proliferation, migration, invasion, and secretion of inflammatory cytokines in IL-1β-induced human synovial SW982 cells. Network pharmacology and molecular docking suggested NF-κB p65 could be the potential target of LB on RA treatment, subsequent experimental investigation confirmed that LB directly interacted with NF-κB p65 and reduced the DNA binding activity of NF-κB in synovial cells. In conclusion, LB significantly attenuated the collagen type II-induced arthritis, which was at least involved in the inhibition of DNA binding activity of NF-κB through a direct binding to NF-κB p65. These findings suggest that LB could be a valuable lead compound for developing anti-RA drugs.

DeepSTABp: A Deep Learning Approach for the Prediction of Thermal Protein Stability

Proteins are essential macromolecules that carry out a plethora of biological functions. The thermal stability of proteins is an important property that affects their function and determines their suitability for various applications. However, current experimental approaches, primarily thermal proteome profiling, are expensive, labor-intensive, and have limited proteome and species coverage. To close the gap between available experimental data and sequence information, a novel protein thermal stability predictor called DeepSTABp has been developed. DeepSTABp uses a transformer-based protein language model for sequence embedding and state-of-the-art feature extraction in combination with other deep learning techniques for end-to-end protein melting temperature prediction. DeepSTABp can predict the thermal stability of a wide range of proteins, making it a powerful and efficient tool for large-scale prediction. The model captures the structural and biological properties that impact protein stability, and it allows for the identification of the structural features that contribute to protein stability. DeepSTABp is available to the public via a user-friendly web interface, making it accessible to researchers in various fields.

The utility of proteases in proteomics, from sequence profiling to structure and function analysis

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.

Expression of the 2Duf protein in wild-type Bacillus subtilis spores stabilizes inner membrane proteins and increases spore resistance to wet heat and hydrogen peroxide

AIMS

This work aimed to characterize spore inner membrane (IM) properties and the mechanism of spore killing by wet heat and H2O2 with spores overexpressing the 2Duf protein, which is naturally encoded from a transposon found only in some Bacillus strains with much higher spore resistance than wild-type spores.

METHODS AND RESULTS

Killing of Bacillus subtilis spores by wet heat or hydrogen peroxide (H2O2) was slower when 2Duf was present, and Ca-dipicolinic acid release was slower than killing. Viabilities on rich plates of wet heat- or H2O2 -treated spores +/- 2Duf were lower when NaCl was added, but higher with glucose. Addition of glucose but not Casamino acids addition increased treated spores' viability on minimal medium plates. Spores with 2Duf required higher heat activation for germination, and their germination was more wet-heat resistant than that of wild-type spores, processes that involve IM proteins. IM permeability and lipid mobility were lower in spores with 2Duf, although IM phospholipid composition was similar in spores +/- 2Duf.

CONCLUSIONS

These results and previous work suggests that wet heat and H2O2 kill spores by damaging an IM enzyme or enzymes involved in oxidative phosphorylation.

Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications

Proteins regulate biological processes by changing their structure or abundance to accomplish a specific function. In response to a perturbation, protein structure may be altered by various molecular events, such as post-translational modifications, protein-protein interactions, aggregation, allostery or binding to other molecules. The ability to probe these structural changes in thousands of proteins simultaneously in cells or tissues can provide valuable information about the functional state of biological processes and pathways. Here, we present an updated protocol for LiP-MS, a proteomics technique combining limited proteolysis with mass spectrometry, to detect protein structural alterations in complex backgrounds and on a proteome-wide scale. In LiP-MS, proteins undergo a brief proteolysis in native conditions followed by complete digestion in denaturing conditions, to generate structurally informative proteolytic fragments that are analyzed by mass spectrometry. We describe advances in the throughput and robustness of the LiP-MS workflow and implementation of data-independent acquisition-based mass spectrometry, which together achieve high reproducibility and sensitivity, even on large sample sizes. We introduce MSstatsLiP, an R package dedicated to the analysis of LiP-MS data for the identification of structurally altered peptides and differentially abundant proteins. The experimental procedures take 3 d, mass spectrometric measurement time and data processing depend on sample number and statistical analysis typically requires ~1 d. These improvements expand the adaptability of LiP-MS and enable wide use in functional proteomics and translational applications.

Colorimetric Sensor Array for Identification of Proteins and Classification of Metabolic Profiles under Various Osmolyte Conditions

Rapid and efficient detection and identification of proteins hold great promise in medical diagnostics, treatment of different diseases, and proteomics. Here, we present a simple colorimetric sensor array for the differentiation of proteins in various osmolyte solutions. Osmolytes have different influences on the conformation of proteins, which have differential binding to silver nanoparticles, resulting in color changes. The sensor array shows unique color change patterns for each of the 19 proteins, allowing unambiguous identification. Very interestingly, the differentiation of 19 proteins is related to their molecular weight. Moreover, the sensor array can be used to identify protein mixtures, thermal denaturized proteins, and unknown protein samples. Finally, the sensor array can also analyze the plasma or liver samples of the four groups of salt-sensitive rats fed with different diets, indicating that it has the potential for the classification of metabolic profiles.

Diffusive Dynamics of Bacterial Proteome as a Proxy of Cell Death

Temperature variations have a big impact on bacterial metabolism and death, yet an exhaustive molecular picture of these processes is still missing. For instance, whether thermal death is determined by the deterioration of the whole or a specific part of the proteome is hotly debated. Here, by monitoring the proteome dynamics of E. coli, we clearly show that only a minor fraction of the proteome unfolds at the cell death. First, we prove that the dynamical state of the E. coli proteome is an excellent proxy for temperature-dependent bacterial metabolism and death. The proteome diffusive dynamics peaks at about the bacterial optimal growth temperature, then a dramatic dynamical slowdown is observed that starts just below the cell's death temperature. Next, we show that this slowdown is caused by the unfolding of just a small fraction of proteins that establish an entangling interprotein network, dominated by hydrophobic interactions, across the cytoplasm. Finally, the deduced progress of the proteome unfolding and its diffusive dynamics are both key to correctly reproduce the E. coli growth rate.

A proteome scale study reveals how plastic surfaces and agitation promote protein aggregation

Protein aggregation in biotherapeutics can reduce their activity and effectiveness. It may also promote immune reactions responsible for severe adverse effects. The impact of plastic materials on protein destabilization is not totally understood. Here, we propose to deconvolve the effects of material surface, air/liquid interface, and agitation to decipher their respective role in protein destabilization and aggregation. We analyzed the effect of polypropylene, TEFLON, glass and LOBIND surfaces on the stability of purified proteins (bovine serum albumin, hemoglobin and α-synuclein) and on a cell extract composed of 6000 soluble proteins during agitation (P = 0.1-1.2 W/kg). Proteomic analysis revealed that chaperonins, intrinsically disordered proteins and ribosomes were more sensitive to the combined effects of material surfaces and agitation while small metabolic oligomers could be protected in the same conditions. Protein loss observations coupled to Raman microscopy, dynamic light scattering and proteomic allowed us to propose a mechanistic model of protein destabilization by plastics. Our results suggest that protein loss is not primarily due to the nucleation of small aggregates in solution, but to the destabilization of proteins exposed to material surfaces and their subsequent aggregation at the sheared air/liquid interface, an effect that cannot be prevented by using LOBIND tubes. A guidance can be established on how to minimize these adverse effects. Remove one of the components of this combined stress - material, air (even partially), or agitation - and proteins will be preserved.

Profiling protein targets of cellular toxicant exposure

Environmental agents of exposure can damage proteins, affecting protein function and cellular protein homeostasis. Specific residues are inherently chemically susceptible to damage from individual types of exposure. Amino acid content is not completely predictive of protein susceptibility, as secondary, tertiary, and quaternary structures of proteins strongly influence the reactivity of the proteome to individual exposures. Because we cannot readily predict which proteins will be affected by which chemical exposures, mass spectrometry-based proteomic strategies are necessary to determine the protein targets of environmental toxins and toxicants. This review describes the mechanisms by which environmental exposure to toxins and toxicants can damage proteins and affect their function, and emerging omic methodologies that can be used to identify the protein targets of a given agent. These methods include target identification strategies that have recently revolutionized the drug discovery field, such as activity-based protein profiling, protein footprinting, and protein stability profiling technologies. In particular, we highlight the necessity of multiple, complementary approaches to fully interrogate how protein integrity is challenged by individual exposures.

Alleviating Cell Lysate-Induced Inhibition to Enable RT-PCR from Single Cells in Picoliter-Volume Double Emulsion Droplets

Microfluidic droplet assays enable single-cell polymerase chain reaction (PCR) and sequencing analyses at unprecedented scales, with most methods encapsulating cells within nanoliter-sized single emulsion droplets (water-in-oil). Encapsulating cells within picoliter double emulsion (DE) (water-in-oil-in-water) allows sorting droplets with commercially available fluorescence-activated cell sorter (FACS) machines, making it possible to isolate single cells based on phenotypes of interest for downstream analyses. However, sorting DE droplets with standard cytometers requires small droplets that can pass FACS nozzles. This poses challenges for molecular biology, as prior reports suggest that reverse transcription (RT) and PCR amplification cannot proceed efficiently at volumes below 1 nL due to cell lysate-induced inhibition. To overcome this limitation, we used a plate-based RT-PCR assay designed to mimic reactions in picoliter droplets to systematically quantify and ameliorate the inhibition. We find that RT-PCR is blocked by lysate-induced cleavage of nucleic acid probes and primers, which can be efficiently alleviated through heat lysis. We further show that the magnitude of inhibition depends on the cell type, but that RT-PCR can proceed in low-picoscale reaction volumes for most mouse and human cell lines tested. Finally, we demonstrate one-step RT-PCR from single cells in 20 pL DE droplets with fluorescence quantifiable via FACS. These results open up new avenues for improving picoscale droplet RT-PCR reactions and expanding microfluidic droplet-based single-cell analysis technologies.

Mass spectrometric insights into protein aggregation

Protein aggregation is now recognized as a generic and significant component of the protein energy landscape. Occurring through a complex and dynamic pathway of structural interconversion, the assembly of misfolded proteins to form soluble oligomers and insoluble aggregates remains a challenging topic of study, both in vitro and in vivo. Since the etiology of numerous human diseases has been associated with protein aggregation, and it has become a field of increasing importance in the biopharmaceutical industry, the biophysical characterization of protein misfolded states and their aggregation mechanisms continues to receive increased attention. Mass spectrometry (MS) has firmly established itself as a powerful analytical tool capable of both detection and characterization of proteins at all levels of structure. Given inherent advantages of biological MS, including high sensitivity, rapid timescales of analysis, and the ability to distinguish individual components from complex mixtures with unrivalled specificity, it has found widespread use in the study of protein aggregation, importantly, where traditional structural biology approaches are often not amenable. The present review aims to provide a brief overview of selected MS-based approaches that can provide a range of biophysical descriptors associated with protein conformation and the aggregation pathway. Recent examples highlight where this technology has provided unique structural and mechanistic understanding of protein aggregation.

Protein conformation stabilized by newly formed turns for thermal resilience

Thermally stable or resilient proteins are usually stabilized at intermediate states during thermal stress to prevent irreversible denaturation. However, the mechanism by which their conformations are stabilized to resist high temperature remains elusive. Herein, we investigate the conformational and thermal stability of transforming growth factor-β1 (TGF-β1), a key signaling molecule in numerous biological pathways. We report that the TGF-β1 molecule is thermally resilient as it gradually denatures during thermal treatment when the temperature increases to 90°C-100°C but recovers native folding when the temperature decreases. Using this protein as a model, further studies show the maintenance of its bioactive functional properties after thermal stress, as demonstrated by differentiation induction of NIH/3T3 fibroblasts and human mesenchymal stem cells into myofibroblasts and chondrocytes, respectively. Molecular dynamic simulations revealed that although the protein's secondary structure is unstable under thermal stress, its conformation is partially stabilized by newly formed turns. Given the importance and/or prevalence of TGF-β1 in biological processes, potential therapeutics, and the human diet, our findings encourage consideration of its thermostability for biomedical applications and nutrition.

Quantifying In Situ Structural Stabilities of Human Blood Plasma Proteins Using a Novel Iodination Protein Stability Assay

Many of the diseases that plague society today are driven by a loss of protein quality. One method to quantify protein quality is to measure the protein folding stability (PFS). Here, we present a novel mass spectrometry (MS)-based approach for PFS measurement, iodination protein stability assay (IPSA). IPSA quantifies the PFS by tracking the surface-accessibility differences of tyrosine, histidine, methionine, and cysteine under denaturing conditions. Relative to current methods, IPSA increases protein coverage and granularity to track the PFS changes of a protein along its sequence. To our knowledge, this study is the first time the PFS of human serum proteins has been measured in the context of the blood serum (in situ). We show that IPSA can quantify the PFS differences between different transferrin iron-binding states in near in vivo conditions. We also show that the direction of the denaturation curve reflects the in vivo surface accessibility of the amino acid residue and reproducibly reports a residue-specific PFS. Along with IPSA, we introduce an analysis tool Chalf that provides a simple workflow to calculate the residue-specific PFS. The introduction of IPSA increases the potential to use protein structural stability as a structural quality metric in understanding the etiology and progression of human disease. Data is openly available at Chorusproject.org (project ID 1771).

Learning deep representations of enzyme thermal adaptation

Temperature is a fundamental environmental factor that shapes the evolution of organisms. Learning thermal determinants of protein sequences in evolution thus has profound significance for basic biology, drug discovery, and protein engineering. Here, we use a data set of over 3 million BRENDA enzymes labeled with optimal growth temperatures (OGTs) of their source organisms to train a deep neural network model (DeepET). The protein-temperature representations learned by DeepET provide a temperature-related statistical summary of protein sequences and capture structural properties that affect thermal stability. For prediction of enzyme optimal catalytic temperatures and protein melting temperatures via a transfer learning approach, our DeepET model outperforms classical regression models trained on rationally designed features and other deep-learning-based representations. DeepET thus holds promise for understanding enzyme thermal adaptation and guiding the engineering of thermostable enzymes.

Protein painting reveals pervasive remodeling of conserved proteostasis machinery in response to pharmacological stimuli

The correct spatio-temporal organization of the proteome is essential for cellular homeostasis. However, a detailed mechanistic understanding of this organization and how it is altered in response to external stimuli in the intact cellular environment is as-yet unrealized. ‘Protein painting methods provide a means to address this gap in knowledge by monitoring the conformational status of proteins within cells at the proteome-wide scale. Here, we demonstrate the ability of a protein painting method employing tetraphenylethene maleimide (TPE-MI) to reveal proteome network remodeling in whole cells in response to a cohort of commonly used pharmacological stimuli of varying specificity. We report specific, albeit heterogeneous, responses to individual stimuli that coalesce on a conserved set of core cellular machineries. This work expands our understanding of proteome conformational remodeling in response to cellular stimuli, and provides a blueprint for assessing how these conformational changes may contribute to disorders characterized by proteostasis imbalance.

Thermostable Proteins from HaCaT Keratinocytes Identify a Wide Breadth of Intrinsically Disordered Proteins and Candidates for Liquid-Liquid Phase Separation

Intrinsically disordered proteins (IDPs) move through an ensemble of conformations which allows multitudinous roles within a cell. Keratinocytes, the predominant cell type in mammalian epidermis, have had only a few individual proteins assessed for intrinsic disorder and its possible contribution to liquid-liquid phase separation (LLPS), especially in regard to what functions or structures these proteins provide. We took a holistic approach to keratinocyte IDPs starting with enrichment via the isolation of thermostable proteins. The keratinocyte protein involucrin, known for its resistance to heat denaturation, served as a marker. It and other thermostable proteins were identified by liquid chromatography tandem mass spectrometry and subjected to extensive bioinformatic analysis covering gene ontology, intrinsic disorder, and potential for LLPS. Numerous proteins unique to keratinocytes and other proteins with shared expression in multiple cell types were identified to have IDP traits (e.g., compositional bias, nucleic acid binding, and repeat motifs). Among keratinocyte-specific proteins, many that co-assemble with involucrin into the cell-specific structure known as the cornified envelope scored highly for intrinsic disorder and potential for LLPS. This suggests intrinsic disorder and LLPS are previously unrecognized traits for assembly of the cornified envelope, echoing the contribution of intrinsic disorder and LLPS to more widely encountered features such as stress granules and PML bodies.

Molecular Information Theory Meets Protein Folding

We propose an application of molecular information theory to analyze the folding of single domain proteins. We analyze results from various areas of protein science, such as sequence-based potentials, reduced amino acid alphabets, backbone configurational entropy, secondary structure content, residue burial layers, and mutational studies of protein stability changes. We found that the average information contained in the sequences of evolved proteins is very close to the average information needed to specify a fold ∼2.2 ± 0.3 bits/(site·operation). The effective alphabet size in evolved proteins equals the effective number of conformations of a residue in the compact unfolded state at around 5. We calculated an energy-to-information conversion efficiency upon folding of around 50%, lower than the theoretical limit of 70%, but much higher than human-built macroscopic machines. We propose a simple mapping between molecular information theory and energy landscape theory and explore the connections between sequence evolution, configurational entropy, and the energetics of protein folding.

Rewiring of the protein-protein-metabolite interactome during the diauxic shift in yeast

In budding yeast Saccharomyces cerevisiae, the switch from aerobic fermentation to respiratory growth is separated by a period of growth arrest, known as the diauxic shift, accompanied by a significant metabolic rewiring, including the derepression of gluconeogenesis and the establishment of mitochondrial respiration. Previous studies reported hundreds of proteins and tens of metabolites accumulating differentially across the diauxic shift transition. To assess the differences in the protein-protein (PPIs) and protein-metabolite interactions (PMIs) yeast samples harvested in the glucose-utilizing, fermentative phase, ethanol-utilizing and early stationary respiratory phases were analysed using isothermal shift assay (iTSA) and a co-fractionation mass spectrometry approach, PROMIS. Whereas iTSA monitors changes in protein stability and is informative towards protein interaction status, PROMIS uses co-elution to delineate putative PPIs and PMIs. The resulting dataset comprises 1627 proteins and 247 metabolites, hundreds of proteins and tens of metabolites characterized by differential thermal stability and/or fractionation profile, constituting a novel resource to be mined for the regulatory PPIs and PMIs. The examples discussed here include (i) dissociation of the core and regulatory particle of the proteasome in the early stationary phase, (ii) the differential binding of a co-factor pyridoxal phosphate to the enzymes of amino acid metabolism and (iii) the putative, phase-specific interactions between proline-containing dipeptides and enzymes of central carbon metabolism.

ProTstab2 for Prediction of Protein Thermal Stabilities

The stability of proteins is an essential property that has several biological implications. Knowledge about protein stability is important in many ways, ranging from protein purification and structure determination to stability in cells and biotechnological applications. Experimental determination of thermal stabilities has been tedious and available data have been limited. The introduction of limited proteolysis and mass spectrometry approaches has facilitated more extensive cellular protein stability data production. We collected melting temperature information for 34,913 proteins and developed a machine learning predictor, ProTstab2, by utilizing a gradient boosting algorithm after testing seven algorithms. The method performance was assessed on a blind test data set and showed a Pearson correlation coefficient of 0.753 and root mean square error of 7.005. Comparison to previous methods indicated that ProTstab2 had superior performance. The method is fast, so it was applied to predict and compare the stabilities of all proteins in human, mouse, and zebrafish proteomes for which experimental data were not determined. The tool is freely available.

Elucidation of the interaction proteome of mitochondrial chaperone Hsp78 highlights its role in protein aggregation during heat stress

Chaperones of the Hsp100/Clp family represent major components of protein homeostasis, conferring maintenance of protein activity under stress. The ClpB-type members of the family, present in bacteria, fungi, and plants, are able to resolubilize aggregated proteins. The mitochondrial member of the ClpB family in Saccharomyces cerevisiae is Hsp78. Although Hsp78 has been shown to contribute to proteostasis in elevated temperatures, the biochemical mechanisms underlying this mitochondria-specific thermotolerance are still largely unclear. To identify endogenous chaperone substrate proteins, here, we generated an Hsp78-ATPase mutant with stabilized substrate-binding behavior. We used two stable isotope labeling–based quantitative mass spectrometry approaches to analyze the role of Hsp78 during heat stress–induced mitochondrial protein aggregation and disaggregation on a proteomic level. We first identified the endogenous substrate spectrum of the Hsp78 chaperone, comprising a wide variety of proteins related to metabolic functions including energy production and protein synthesis, as well as other chaperones, indicating its crucial functions in mitochondrial stress resistance. We then compared these interaction data with aggregation and disaggregation processes in mitochondria under heat stress, which revealed specific aggregation-prone protein populations and demonstrated the direct quantitative impact of Hsp78 on stress-dependent protein solubility under different conditions. We conclude that Hsp78, together with its cofactors, represents a recovery system that protects major mitochondrial metabolic functions during heat stress as well as restores protein biogenesis capacity after the return to normal conditions.

The role of structural dynamics in the thermal adaptation of hyperthermophilic enzymes

Proteins from hyperthermophilic organisms are evolutionary optimised to adopt functional structures and dynamics under conditions in which their mesophilic homologues are generally inactive or unfolded. Understanding the nature of such adaptation is of crucial interest to clarify the underlying mechanisms of biological activity in proteins. Here we measured NMR residual dipolar couplings of a hyperthermophilic acylphosphatase enzyme at 80°C and used these data to generate an accurate structural ensemble representative of its native state. The resulting energy landscape was compared to that obtained for a human homologue at 37°C, and additional NMR experiments were carried out to probe fast (¹⁵N relaxation) and slow (H/D exchange) backbone dynamics, collectively sampling fluctuations of the two proteins ranging from the nanosecond to the millisecond timescale. The results identified key differences in the strategies for protein-protein and protein-ligand interactions of the two enzymes at the respective physiological temperatures. These include the dynamical behaviour of a β-strand involved in the protection against aberrant protein aggregation and concerted motions of loops involved in substrate binding and catalysis. Taken together these results elucidate the structure-dynamics-function relationship associated with the strategies of thermal adaptation of protein molecules.

Activity-based annotation: the emergence of systems biochemistry

Current tools to annotate protein function have failed to keep pace with the speed of DNA sequencing and exponentially growing number of proteins of unknown function (PUFs). A major contributing factor to this mismatch is the historical lack of high-throughput methods to experimentally determine biochemical activity. Activity-based methods, such as activity-based metabolite and protein profiling, are emerging as new approaches for unbiased, global, biochemical annotation of protein function. In this review, we highlight recent experimental, activity-based approaches that offer new opportunities to determine protein function in a biologically agnostic and systems-level manner.

Effectiveness of mechanical cleaning, antibiotics, and induction heating on eradication of Staphylococcus aureus in mature biofilms

Aims

Here we used a mature seven-day biofilm model of Staphylococcus aureus, exposed to antibiotics up to an additional seven days, to establish the effectiveness of either mechanical cleaning or antibiotics or non-contact induction heating, and which combinations could eradicate S. aureus in mature biofilms.

Methods

Mature biofilms of S. aureus (ATCC 29213) were grown on titanium alloy (Ti6Al4V) coupons for seven days and were subjected to the following treatments or their combinations: antibiotics, mechanical cleaning, or heat shock by induction heating of 60°C for one minute. Experiments were repeated at least five times.

Results

In the untreated biofilm, growth up to 1.8×10¹¹ colony-forming units (CFU)/cm² was observed. Treatment with ciprofloxacin, flucloxacillin, vancomycin, cefuroxime, and amoxicillin all with rifampicin gave 6.0 log, 6.1 log, 1.4 log, 4.8 log, and 3.6 log reduction in CFU/cm², respectively. Mechanical cleaning alone resulted in 4.9 log reduction and induction heating in 7.3 log reduction. There was an additional effect of ciprofloxacin, flucloxacillin, and induction heating when used in combinations. There was no additional effect for mechanical cleaning. No bacterial growth could be detected after induction heating followed by seven days of ciprofloxacin with rifampicin.

Conclusion

Mechanical cleaning, antibiotics, and non-contact induction heating reduced the bacterial load of mature S. aureus biofilms with approximately 5 log or more as a single treatment. The effect of mechanical cleaning on mature S. aureus biofilms was limited when used in combination with antibiotics and/or induction heating.

Cite this article: Bone Joint Res 2022;11(9):629–638.

Sequence grammar underlying the unfolding and phase separation of globular proteins

Aberrant phase separation of globular proteins is associated with many diseases. Here, we use a model protein system to understand how the unfolded states of globular proteins drive phase separation and the formation of unfolded protein deposits (UPODs). We find that for UPODs to form, the concentrations of unfolded molecules must be above a threshold value. Additionally, unfolded molecules must possess appropriate sequence grammars to drive phase separation. While UPODs recruit molecular chaperones, their compositional profiles are also influenced by synergistic physicochemical interactions governed by the sequence grammars of unfolded proteins and cellular proteins. Overall, the driving forces for phase separation and the compositional profiles of UPODs are governed by the sequence grammars of unfolded proteins. Our studies highlight the need for uncovering the sequence grammars of unfolded proteins that drive UPOD formation and cause gain-of-function interactions whereby proteins are aberrantly recruited into UPODs.

MetA is a "thermal fuse" that inhibits growth and protects Escherichia coli at elevated temperatures

Adaptive stress resistance in microbes is mostly attributed to the expression of stress response genes, including heat-shock proteins. Here, we report a response of E. coli to heat stress caused by degradation of an enzyme in the methionine biosynthesis pathway (MetA). While MetA degradation can inhibit growth, which by itself is detrimental for fitness, we show that it directly benefits survival at temperatures exceeding 50°C, increasing survival chances by more than 1,000-fold. Using both experiments and mathematical modeling, we show quantitatively how protein expression, degradation rates, and environmental stressors cause long-term growth inhibition in otherwise habitable conditions. Because growth inhibition can be abolished with simple mutations, namely point mutations of MetA and protease knockouts, we interpret the breakdown of methionine synthesis as a system that has evolved to halt growth at high temperatures, analogous to "thermal fuses" in engineering that shut off electricity to prevent overheating.

Stability profile of the neuronal SNARE complex reflects its potency to drive fast membrane fusion

Soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) form the SNARE complex to mediate most fusion events of the secretory pathway. The neuronal SNARE complex is featured by its high stability and half-zippered conformation required for driving robust and fast synaptic exocytosis. However, these two features seem to be thermodynamically mutually exclusive. In this study, we have employed temperature-dependent disassociation assays and single-molecule Förster resonance energy transfer (FRET) experiments to analyze the stability and conformation of the neuronal SNARE complex. We reclassified the amino acids of the SNARE motif into four sub-groups (core, core-side I and II, and non-contact). Our data showed that the core residues predominantly contribute to the complex stability to meet a basal requirement for SNARE-mediated membrane fusion, while the core-side residues exert an unbalanced effect on the N- and C-half bundle stability that determines the half-zippered conformation of the neuronal SNARE complex, which would accommodate essential regulations by complexins and synaptotagmins for fast Ca2+-triggered membrane fusion. Furthermore, our data confirmed a strong coupling of folding energy between the N- and C-half assembly of the neuronal SNARE complex, which rationalizes the strong potency of the half-zippered conformation to conduct robust and fast fusion. Overall, these results uncovered that the stability profile of the neuronal SNARE complex reflects its potency to drive fast and robust membrane fusion. Based on these results, we also developed a new parameter, the stability factor (Fs), to characterize the overall stability of the neuronal SNARE complex and resolved a linear correlation between the stability and inter-residue coulombic interactions of the neuronal SNARE complex, which would help rationally design artificial SNARE complexes and remold functional SNARE complexes with desirable stability.

Low protein expression enhances phenotypic evolvability by intensifying selection on folding stability

Protein abundance affects the evolution of protein genotypes, but we do not know how it affects the evolution of protein phenotypes. Here we investigate the role of protein abundance in the evolvability of green fluorescent protein (GFP) towards the novel phenotype of cyan fluorescence. We evolve GFP in E. coli through multiple cycles of mutation and selection and show that low GFP expression facilitates the evolution of cyan fluorescence. A computational model whose predictions we test experimentally helps explain why: lowly expressed proteins are under stronger selection for proper folding, which facilitates their evolvability on short evolutionary time scales. The reason is that high fluorescence can be achieved by either few proteins that fold well or by many proteins that fold less well. In other words, we observe a synergy between a protein's scarcity and its stability. Because many proteins meet the essential requirements for this scarcity-stability synergy, it may be a widespread mechanism by which low expression helps proteins evolve new phenotypes and functions.

Bioluminescent test systems based on firefly luciferase for studying stress effects on living cells

The bioluminescent luciferin-luciferase reaction is based on the oxidation of D-luciferin by oxygen in the presence of ATP and magnesium ions, catalyzed by firefly luciferase. The possibilities of using this reaction to study the influence of external effectors of a physical and chemical nature (temperature exposure, additions of drugs, membrane-active compounds, etc.) on living cells (prokaryotes and eukaryotes) are considered. Examples of the use of test systems based on living cells producing thermostable firefly luciferase for monitoring cellular homeostasis are given. The study of the kinetics of changes in the concentration of ATP and luciferase inside and outside cells made it possible to determine in dynamics the metabolic activity, cytotoxicity, and survival of cells under conditions of cellular stress, to study the processes of ATP synthesis/hydrolysis, and to evaluate the effectiveness of lytic agents in changing the permeability of the cell membrane.

Genetics of adaptation

The rediscovery of Mendel’s work showing that the heredity of phenotypes is controlled by discrete genes was followed by the reconciliation of Mendelian genetics with evolution by natural selection in the middle of the last century with the Modern Synthesis. In the past two decades, dramatic advances in genomic methods have facilitated the identification of the loci, genes, and even individual mutations that underlie phenotypic variants that are the putative targets of natural selection. Moreover, these methods have also changed how we can study adaptation by flipping the problem around, allowing us to first examine what loci show evidence of having been under selection, and then connecting these genetic variants to phenotypic variation. As a result, we now have an expanding list of actual genetic changes that underlie potentially adaptive phenotypic variation. Here, we synthesize how considering the effects of these adaptive loci in the context of cellular environments, genomes, organisms, and populations has provided new insights to the genetic architecture of adaptation.

A limit on the evolutionary rescue of an Antarctic bacterium from rising temperatures

Climate change is gradual, but it can also cause brief extreme heat waves that can exceed the upper thermal limit of any one organism. To study the evolutionary potential of upper thermal tolerance, we evolved the cold-adapted Antarctic bacterium Pseudoalteromonas haloplanktis to survive at 30°C, beyond its ancestral thermal limit. This high-temperature adaptation occurred rapidly and in multiple populations. It involved genomic changes that occurred in a highly parallel fashion and mitigated the effects of protein misfolding. However, it also confronted a physiological limit, because populations failed to grow beyond 30°C. Our experiments aimed to facilitate evolutionary rescue by using a small organism with large populations living at temperatures several degrees below their upper thermal limit. Larger organisms with smaller populations and living at temperatures closer to their upper thermal tolerances are even more likely to go extinct during extreme heat waves.

Proteome-wide analysis of stress response to temperature in Sulfolobus islandicus

Sulfolobus islandicus is thermophilic archaea that live in an extreme environment of 75 °C-80 °C and pH 2-3. Currently, the molecular mechanism of archaeal adaptation to high temperatures and the stability of proteins at high temperatures are still unclear. This study utilizes proteomics to analyze the differential expression of S. islandicus proteins at different temperatures. We found that ribosomes, glycolysis, nucleotide metabolism, RNA metabolism, transport system, and sulfur metabolism are all affected by temperature. Methylation modification of some proteins changed with temperature. Thermal proteome profiling (TPP) was used to analyze the thermal stability of proteins under 65 °C-85 °C growth conditions. It is suggested that the T_m values of proteins are mainly distributed around the optimum growth temperature (OGT). The proteins in the glycolysis pathway had high thermal stability. Meanwhile, proteins related to DNA replication and translation showed low thermal stability. The protein thermal stability of S. islandicus cultured under 65 °C and 85 °C was higher than that of 75 °C. Our study reveals that S. islandicus may adapt to temperature changes by regulating protein synthesis and carbon metabolism pathways, changing post-translational modifications, and improving protein stability at the same time. SIGNIFICANCE: The molecular mechanism of archaeal adaptation to high temperatures and the stability of proteins at high temperatures are still unclear. Our proteomics study identified 477 differentially expressed proteins of S. islandicus at different temperatures, suggesting that ribosomes, glycolysis, nucleotide metabolism, RNA metabolism, transport system, and sulfur metabolism are affected by temperature. Meanwhile, we found that methylation modification of some proteins changed with temperature. To evaluate the thermal stability of the proteome, we performed thermal proteome profiling to analyze the Tm of proteins under 65 °C-85 °C growth conditions. T_m values of proteins are mainly distributed around the optimum growth temperature. The proteins in the glycolysis pathway had high thermal stability. Meanwhile, proteins related to DNA replication and translation showed low thermal stability. Our study reveals that S. islandicus may adapt to temperature changes by regulating protein synthesis and carbon metabolism pathways, changing post-translational modifications, and improving protein stability at the same time.

Evolution of homo-oligomerization of methionine S-adenosyltransferases is replete with structure-function constrains

Homomers are prevalent in bacterial proteomes, particularly among core metabolic enzymes. Homomerization is often key to function and regulation, and interfaces that facilitate the formation of homomeric enzymes are subject to intense evolutionary change. However, our understanding of the molecular mechanisms that drive evolutionary variation in homomeric complexes is still lacking. How is the diversification of protein interfaces linked to variation in functional regulation and structural integrity of homomeric complexes? To address this question, we studied quaternary structure evolution of bacterial methionine S-adenosyltransferases (MATs)-dihedral homotetramers formed along a large and conserved dimeric interface harboring two active sites, and a small, recently evolved, interdimeric interface. Here, we show that diversity in the physicochemical properties of small interfaces is directly linked to variability in the kinetic stability of MAT quaternary complexes and in modes of their functional regulation. Specifically, hydrophobic interactions within the small interface of Escherichia coli MAT render the functional homotetramer kinetically stable yet impose severe aggregation constraints on complex assembly. These constraints are alleviated by electrostatic interactions that accelerate dimer-dimer assembly. In contrast, Neisseria gonorrhoeae MAT adopts a nonfunctional dimeric state due to the low hydrophobicity of its small interface and the high flexibility of its active site loops, which perturbs small interface integrity. Remarkably, in the presence of methionine and ATP, N. gonorrhoeae MAT undergoes substrate-induced assembly into a functional tetrameric state. We suggest that evolution acts on the interdimeric interfaces of MATs to tailor the regulation of their activity and stability to unique organismal needs.

AlphaFold2 models indicate that protein sequence determines both structure and dynamics

AlphaFold 2 (AF2) has placed Molecular Biology in a new era where we can visualize, analyze and interpret the structures and functions of all proteins solely from their primary sequences. We performed AF2 structure predictions for various protein systems, including globular proteins, a multi-domain protein, an intrinsically disordered protein (IDP), a randomized protein, two larger proteins (> 1000 AA), a heterodimer and a homodimer protein complex. Our results show that along with the three dimensional (3D) structures, AF2 also decodes protein sequences into residue flexibilities via both the predicted local distance difference test (pLDDT) scores of the models, and the predicted aligned error (PAE) maps. We show that PAE maps from AF2 are correlated with the distance variation (DV) matrices from molecular dynamics (MD) simulations, which reveals that the PAE maps can predict the dynamical nature of protein residues. Here, we introduce the AF2-scores, which are simply derived from pLDDT scores and are in the range of [0, 1]. We found that for most protein models, including large proteins and protein complexes, the AF2-scores are highly correlated with the root mean square fluctuations (RMSF) calculated from MD simulations. However, for an IDP and a randomized protein, the AF2-scores do not correlate with the RMSF from MD, especially for the IDP. Our results indicate that the protein structures predicted by AF2 also convey information of the residue flexibility, i.e., protein dynamics.

Turning Failures into Applications: The Problem of Protein ΔΔG Prediction

After nearly two decades of research in the field of computational methods based on machine learning and knowledge-based potentials for ΔG and ΔΔG prediction upon variations, we now realize that all the approaches are poorly performing when tested on specific cases and that there is large space for improvement. Why this is so? Is it wrong the underlying assumption that experimental protein thermodynamics in solution reflects the thermodynamics of a single protein? Both machine learning and knowledge-based computational methods are rigorous and we know the solid theory behind. We are now in a critical situation, which suggests that predictions of protein instability upon variation should be considered with care. In the following, we will show how to cope with the problem of understanding which protein positions may be of interest for biotechnological and biomedical purposes. By applying a consensus procedure, we indicate possible strategies for the result interpretation.