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

Multifactorial interaction and influence of culture conditions on yellow fluorescent protein production in Phaeodactylum tricornutum

Phaeodactylum tricornutum is a promising host for light-driven synthesis of heterologous proteins. However, the marine cold-water environment and alkaline-acidic pH shifts in the culture, necessitated by the diatom's growth requirements. In this study, we analyzed the influence of growth condition on maturation and dynamics of the yellow fluorescent protein (YFP) in episomal-transformant P. tricornutum. A mathematical model was developed to detect the parameters that affect biomass and YFP production. Optimized conditions increased YFP mean fluorescence intensity (MFI) per cell by 4.2-fold (3.6 ± 0.6 to 15.4 ± 1.1) and total protein levels in the culture by 1.8-fold (123 ± 4 to 219 ± 9 µg L-1), without affecting biomass. YFP stability studies in P. tricornutum showed that the ubiquitin-proteasome system contributes the degradation of the recombinant protein, whereas newly synthesized YFP remains stable for up to 12 h. This optimization provides insights into the fluorescent protein-based heterologous production in diatoms.

Prediction and design of thermostable proteins with a desired melting temperature

The stability of proteins at higher temperatures is crucial for their functionality, which is measured by their melting temperature (Tm). The Tm is the temperature at which 50% of the protein loses its native structure and activity. Existing methods for predicting Tm have two major limitations: first, they are often trained on redundant proteins, and second, they do not allow users to design proteins with the desired Tm. To address these limitations, we developed a regression method for predicting the Tm value of proteins using 17,312 non-redundant proteins, where no two proteins are more than 40% similar. We used 80% of the data for training and testing and the remaining 20% for validation. Initially, we developed a machine learning model using standard features from protein sequences. Our best model, developed using Shannon entropy for all residues, achieved the highest Pearson correlation of 0.80 with an R2 of 0.63 between the predicted and actual Tm of proteins on the validation dataset. Next, we fine-tuned large language models (e.g., ProtBert, ProtGPT2, ProtT5) on our training dataset and generated embeddings. These embeddings have been used to develop machine learning models. Our best model, developed using ProtBert embeddings, achieved a maximum correlation of 0.89 with an R2 of 0.80 on the validation dataset. Finally, we developed an ensemble method that combines standard protein features and embeddings. One of the aims of the study is to assist the scientific community in the design of targeted melting temperatures. Our standalone software can be used to screen thermostable proteins at the genome level. We demonstrated the application of PPTstab in identifying thermostable proteins in different organisms. We created a user-friendly web server, and a Python package for predicting and designing thermostable proteins is available at https://webs.iiitd.edu.in/raghava/pptstab , https://github.com/raghavagps/pptstab .

Natural Spy Chaperone Mimic: Tailored Nanochaperone with Electrostatic-Hydrophobic Synergy To Enhance Protein Folding Regulation

Protein folding regulation is of great significance for maintaining protein structures and biological functions. This fundamental process is assisted by molecular chaperones, which act in inhibiting undesired protein aggregation and facilitating misfolded protein refolding. Inspired by the unique structure and ingenious mechanisms of natural Spy chaperones, we innovate a nanochaperone-guided protein folding strategy by rationally designed nanochaperones (nChaps) with customizable surface structures and properties. In this strategy, the nChaps with tunable charged surfaces can first rapidly capture different client proteins through long-range electrostatic attraction, similar to Spy. Subsequently, the captured proteins can be dynamically bound into the Spy-mimetic hydrophobic microdomains via short-range hydrophobic interactions. As a result, the client proteins are sequestered and stabilized in the chaperone-mimicking confined spaces on the surface of nChaps, thereby facilitating dynamic regulation of protein folding through an electrostatic-hydrophobic synergy mechanism. Moreover, benefiting from the adjustable charge and multiple hydrophobic microdomains, this biomimetic nChap potentiates protein stability at harsh temperatures and long-term storage, which is hardly achieved by natural Spy. Additionally, this strategy is applicable to 9 different proteins with varying isoelectric points and molecular weights, showing superior generality than Spy. Therefore, this work provides new perspectives in developing an advanced strategy for enhanced protein folding regulation.

The thermodynamic hypothesis of protein aggregation

Protein misfolding and aggregation drive some of the most prevalent and lethal disorders of our time, including Alzheimer's and Parkinson's diseases, now affecting tens of millions of people worldwide. The complexity of these diseases, which are often multifactorial and related to age and lifestyle, has made it challenging to identify the causes of the accumulation of aberrant protein deposits. An insight into the origins of these deposits comes from reports of a widespread presence of protein aggregates even under normal cellular conditions. This observation is best accounted for by the thermodynamic hypothesis of protein aggregation. According to this hypothesis, many proteins are expressed at levels close to their supersaturation limits, so that their native states are metastable against aggregation. Here we integrate the evidence behind this hypothesis and outline actionable therapeutic strategies that could halt protein aggregation at its source.

Comparative analysis of physicochemical properties and functionalities of artificial oil bodies stabilized by different seed oil body proteins

In this study, ‌perilla seed oil body protein (PO), hempseed oil body protein (HO), and cucumber seed oil body protein (CO) were utilized to prepare artificial oil bodies (AOBs), and the impact of protein type on their physicochemical properties was investigated.‌ ‌Compared to HO and CO, PO exhibited a lower zeta potential value of -48.27 mV, a higher surface hydrophobicity of 21,122.67, and a smaller particle size of 105.71 nm. Its emulsifying activity index (EAI) and emulsion stability index (ESI) were 83.06 m2/g and 167.9 %, respectively. ‌Furthermore, AOBs stabilized by PO demonstrated smaller particle size and a higher amount of interfacial adsorbed protein compared to those prepared by HO and CO.‌ ‌Additionally, the encapsulation results indicated that PO-AOBs exhibited a higher encapsulation efficiency of 98.34 %. The retention rates of the loaded curcumin were 56.94 % after exposure to 90 °C and 94.06 % after UV light exposure for 7 h. ‌Moreover, both digestion and antioxidant experiments indicated that PO-AOBs facilitated better release of curcumin in the intestine, leading to enhanced antioxidant properties and increased bioavailability.‌ These findings offer ‌new insights into the development of novel AOBs, which hold promise for diverse applications in food delivery systems.

Protein O-glycosylation in the Bacteroidota phylum

Glycans play crucial roles in bacteria, such as providing structural integrity or enabling interactions with the ecosystem. They can be linked to lipids, peptides, or proteins. In proteins, they modify either asparagine (N-glycosylation) or serine or threonine (O-glycosylation). Species of the Bacteroidota phylum, a major component of the human microbiome and marine and soil ecosystems, have a unique type of O-glycosylation that modifies multiple noncytoplasmic proteins containing a specific amino acid sequence. Only a small number of species have currently been characterized, but within one species, generally all proteins are modified with the same glycan structure. Most species share a common inner part but differ in the sugar composition and branching of the outer part of their glycan. This suggests that the biosynthesis of the glycan occurs in two separate steps. Both the inner core and the outer glycan are likely assembled from nucleotide-activated monosaccharides on undecaprenyl phosphate on the cytoplasmic side of the inner membrane, prior to being flipped to the periplasm and transferred to the protein. A genomic locus responsible for the biosynthesis of the outer glycan has been identified, containing some conserved genes across species. Despite substantial progress in the characterization of this O-glycosylation system, its function, the overall diversity of glycan structures across the phylum, and the complete biosynthetic pathway remain mostly unknown. Due to the importance of this group of species for the human gut microbiome, elucidating these aspects can open up strategies to modulate the composition of the microbiome community toward a healthy state.

Role of electrostatics in cold adaptation: A comparative study of eury- and stenopsychrophilic triose phosphate isomerase

Psychrophilic (cold-active) organisms have developed enzymes that facilitate sufficient metabolic activity at low temperatures to sustain life. This occurs through molecular adaptations that tend to increase protein flexibility at the expense of stability. However, psychrophiles also vary in their growth conditions. Eurypsychrophiles thrive over a wide temperature range and often prefer temperatures above 20 °C, while stenopsychrophiles grow optimally below 15 °C and are more narrowly adapted to cold temperatures. To elucidate differences between these two classes of enzymes, we here compare the stability and unfolding kinetics of two orthologues of the basal household enzyme triose phosphate isomerase, one from the stenopsychrophilic Antarctic permafrost bacterium Rhodonellum psychrophilum (sTPI) and the other from the eurypsychrophilic Greenland ikaite column bacterium Rhodococcus sp. JG-3 (eTPI). Remarkably, sTPI proved significantly more thermostable and resistant to chemical denaturation than its eurypsychrophilic counterpart, eTPI, in the absence of ionic components in solution, whereas inclusion of electrostatic screening agents in the form of sodium chloride or the charged denaturant guanidinium chloride largely cancelled out this difference. Thus, electrostatics play a prominent role in stabilizing the stenopsychrophilic sTPI, and a mandatory low-temperature growth environment does not preclude the development of considerable thermotolerance for individual enzymes. We were able to increase the thermostability of sTPI using an evolutionary machine learning model, which transferred several sTPI residues into the eTPI active site. While the stabilizing effect was modest, the combination of individual mutations was additive, underscoring the potential of combining multiple beneficial mutations to achieve enhanced enzyme properties.

Analysis of Limited Proteolysis-Coupled Mass Spectrometry Data

Limited proteolysis combined with mass spectrometry (LiP-MS) facilitates probing structural changes on a proteome-wide scale. This method leverages differences in the proteinase K accessibility of native protein structures to concurrently assess structural alterations for thousands of proteins in situ. Distinguishing different contributions to the LiP-MS signal, such as changes in protein abundance or chemical modifications, from structural protein alterations remains challenging. Here, we present the first comprehensive computational pipeline to infer structural alterations for LiP-MS data using a two-step approach. 1) We remove unwanted variations from the LiP signal that are not caused by protein structural effects and 2) infer the effects of variables of interest on the remaining signal. Using LiP-MS data from three species, we demonstrate that this approach outperforms previously employed approaches. Our framework provides a uniquely powerful approach for deconvolving LiP-MS signals and separating protein structural changes from changes in protein abundance, posttranslational modifications, and alternative splicing. Our approach may also be applied to analyze other types of peptide-centric structural proteomics data, such as FPOP or molecular painting data.

Fluorescent Fingerprint Identification of Protein Structural Changes and Disease-Specific Amyloid Beta Aggregates Based on a Single-Nanozyme Sensor Array

The misfolding of amyloid β (Aβ) peptides into an aggregation state is a central hallmark of the onset of Alzheimer's disease (AD). However, conventional methods are mainly focused on detecting a specific Aβ peptide, which makes it difficult to recognize multiple analytes with different topological features and unfolded states at the same time. Here, we propose a simple and universal sensing strategy to construct a fluorescence sensor array by using a single-nanozyme probe combined with three fluorescent substrates as three recognition units to probe the protein structural changes and identify between multiple Aβ assemblies. In this sensor system, the fingerprint-like patterns are produced from the nonspecific interactions between topological proteins and the sensing units. As a result, this sensor array can accurately identify 13 kinds of proteins and their mixtures at different ratios. Moreover, the sensor array can discriminate against proteins with unfolded states and diverse conformational forms. Most importantly, the sensor array successfully distinguishes between multiple Aβ species, even in artificial cerebrospinal fluid samples and human serum samples. This work provides an attractive and reliable strategy for predicting pathologically relevant proteins and clinical diagnosis of AD.

Deciphering Polymer Interactions in Bioconjugates with Different Architectures by Structural Analysis via Time-Resolved Limited Proteolysis Mass Spectrometry

Therapeutic proteins are commonly conjugated with polymers to modulate their pharmacokinetics but often lack a description of the polymer-protein interaction. We deployed limited proteolysis mass spectrometry (LiP-MS) to reveal the interaction of polyethylene glycol (PEG) and PEG alternative polymers with interferon-α2a (IFN). Target conjugates were digested with the specific protease trypsin and a "heavy" 15N-IFN wild type (IFN-WT) for time-resolved quantification of the cleavage dynamics. Interactions between IFN-α2a and its high-affinity receptor were detailed by LiP-MS. Then, 10 kDa polymers of PEG, linear polyglycerol (LPG), and poly(2-oxazoline) (POX) with two different cyclooctyne linkers (BCN/DBCO) were used for site-specific bioconjugation to azide functionalized IFN-α2a. Tryptic events at each cleavage site and in different structural environments (loops/helices) were compared. PEG and LPG were similar, and POX showed a reduced interaction profile with the IFN-α2a surface. All-atom molecular dynamics simulations of IFN-DBCO-polymer conjugates revealed distinct and transient (below 50 ns) protein-interaction profiles for PEG, LPG, and POX. Cleavage dynamics of IFN-polymer conjugates from the BCN handle were homogeneous, pointing to a more conserved IFN structure than DBCO-polymer conjugates. In summary, time-resolved LiP-MS for quantification of cleavage events enhances the structural understanding of transient IFN-polymer interactions, which may be extended to other bioconjugate types.

A Closer Look at the Potential Mechanisms of Action of Protective Agents Used in the Drying of Microorganisms: A Review

Yeast, bacteria and sourdough are widely used in our daily lives, yet their drying and storage remains a significant challenge. A variety of techniques are used to improve the resistance of cells to thermal, dehydration, oxidative and osmotic stresses, which can occur at different stages of the process. The addition of protective agents prior to drying is a commonly used method, but the mechanisms that may lead to a change in viability following the addition of these agents, or more generally, the interaction between a protective agent and the drying process, are not yet fully understood. This review outlines seven main potential mechanisms, as highlighted in the literature, which can lead to internal or external modifications of the cells. The mechanisms in question are change of membrane fluidity, accumulation of compounds for osmoregulation, prior osmotic dehydration, prevention of oxidation, coating or encapsulation, enhancement in thermal resistance and change in drying kinetics. A comprehensive explanation of these mechanisms is provided. This review also highlights the connection between the mechanisms and the influence of the stresses occurring during drying and storage, which depend on the drying technique used and the operating conditions, the strains and the protective agents involved, on the importance of the different protection mechanisms. By gaining a deeper understanding of the mechanisms of action of protective agents, strategies to improve the quality of the microorganisms obtained after drying can be developed. One such strategy would be to combine several agents to achieve a synergistic effect.

Ion mobility mass spectrometry unveils conformational effects of drug lead EPI-001 on the intrinsically disordered N-terminal domain of the androgen receptor

Intrinsically disordered proteins (IDPs) are important drug targets as they are key actors within cell signaling networks. However, the conformational plasticity of IDPs renders them challenging to characterize, which is a bottleneck in developing small molecule drugs that bind to IDPs and modulate their behavior. In relation to this, ion mobility mass spectrometry (IM-MS) is a useful tool to investigate IDPs, as it can reveal their conformational preferences. It can also offer important insights in drug discovery, as it can measure binding stoichiometry and unveil conformational shifts of IDPs exerted by the binding of small drug-like molecules. Herein, we have used IM-MS to investigate the effect of drug lead EPI-001 on the disordered N-terminal domain of the androgen receptor (AR-NTD). Despite structural heterogeneity rendering the NTD a challenging region of the protein to drug, this domain harbors most, if not all, of the transcriptional activity. We quantify the stoichiometry of EPI-001 binding to various constructs corresponding to functional domains of AR-NTD and show that it binds to separate constructs containing transactivation unit (TAU)-1 and TAU-5, respectively, and that 1-2 molecules bind to a larger construct containing both sequences. We also identify a conformational shift upon EPI-001 binding to the TAU-5, and to a much lesser extent with TAU-1 containing constructs. This work provides novel insight on the interactions of EPI-001 with the AR-NTD, and the structural alterations that it exerts, and positions IM-MS as an informative tool that will enhance the tractability of IDPs, potentially leading to better therapies.

Surviving the heat: the role of macromolecular assemblies in promoting cellular shutdown

During heat shock (HS), cells orchestrate a gene expression program that promotes the synthesis of HS proteins (HSPs) while simultaneously repressing the synthesis of other proteins, including growth-promoting housekeeping proteins. Recent studies show that mRNAs encoding housekeeping proteins, along with associated processing factors, form macromolecular assemblies during HS. These assemblies inhibit transcription, nuclear export, and translation of housekeeping mRNAs, and coincide with structural rearrangements in proteins. These findings reveal a mechanism linking temperature sensitivity through structural rearrangements and macromolecular assembly to the 'shut down' of housekeeping protein synthesis. This review delves into recent findings in yeast, with a focus on macromolecular assembly, offering perspectives into mechanisms that regulate gene expression during HS and how these processes may be conserved.

Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.

Discovering genetic modulators of the protein homeostasis system through multilevel analysis

Every protein progresses through a natural lifecycle from birth to maturation to death; this process is coordinated by the protein homeostasis system. Environmental or physiological conditions trigger pathways that maintain the homeostasis of the proteome. An open question is how these pathways are modulated to respond to the many stresses that an organism encounters during its lifetime. To address this question, we tested how the fitness landscape changes in response to environmental and genetic perturbations using directed and massively parallel transposon mutagenesis in Caulobacter crescentus. We developed a general computational pipeline for the analysis of gene-by-environment interactions in transposon mutagenesis experiments. This pipeline uses a combination of general linear models, statistical knockoffs, and a nonparametric Bayesian statistical model to identify essential genetic network components that are shared across environmental perturbations. This analysis allows us to quantify the similarity of proteotoxic environmental perturbations from the perspective of the fitness landscape. We find that essential genes vary more by genetic background than by environmental conditions, with limited overlap among mutant strains targeting different facets of the protein homeostasis system. We also identified 146 unique fitness determinants across different strains, with 19 genes common to at least two strains, showing varying resilience to proteotoxic stresses. Experiments exposing cells to a combination of genetic perturbations and dual environmental stressors show that perturbations that are quantitatively dissimilar from the perspective of the fitness landscape are likely to have a synergistic effect on the growth defect.

AI-empowered perturbation proteomics for complex biological systems

The insufficient availability of comprehensive protein-level perturbation data is impeding the widespread adoption of systems biology. In this perspective, we introduce the rationale, essentiality, and practicality of perturbation proteomics. Biological systems are perturbed with diverse biological, chemical, and/or physical factors, followed by proteomic measurements at various levels, including changes in protein expression and turnover, post-translational modifications, protein interactions, transport, and localization, along with phenotypic data. Computational models, employing traditional machine learning or deep learning, identify or predict perturbation responses, mechanisms of action, and protein functions, aiding in therapy selection, compound design, and efficient experiment design. We propose to outline a generic PMMP (perturbation, measurement, modeling to prediction) pipeline and build foundation models or other suitable mathematical models based on large-scale perturbation proteomic data. Finally, we contrast modeling between artificially and naturally perturbed systems and highlight the importance of perturbation proteomics for advancing our understanding and predictive modeling of biological systems.

Transgenic sensors reveal compartment-specific effects of aggregation-prone proteins on subcellular proteostasis during aging

Loss of proteostasis is a hallmark of aging that underlies many age-related diseases. Different cell compartments experience distinctive challenges in maintaining protein quality control, but how aging regulates subcellular proteostasis remains underexplored. Here, by targeting the misfolding-prone FlucDM luciferase to the cytoplasm, mitochondria, and nucleus, we established transgenic sensors to examine subcellular proteostasis in Drosophila. Analysis of detergent-insoluble and -soluble levels of compartment-targeted FlucDM variants indicates that thermal stress, cold shock, and pro-longevity inter-organ signaling differentially affect subcellular proteostasis during aging. Moreover, aggregation-prone proteins that cause different neurodegenerative diseases induce a diverse range of outcomes on FlucDM insolubility, suggesting that subcellular proteostasis is impaired in a disease-specific manner. Further analyses with FlucDM and mass spectrometry indicate that pathogenic tauV337M produces an unexpectedly complex regulation of solubility for different FlucDM variants and protein subsets. Altogether, compartment-targeted FlucDM sensors pinpoint a diverse modulation of subcellular proteostasis by aging regulators.

Cell stress and phase separation stabilize the monomeric state of pseudoisocyanine chloride employed as a self-assembly crowding sensor

Cellular stress and ageing involve an increase in crowding and aggregation of amylogenic proteins. We here investigate if crowding is the intrinsic cause of aggregation and utilise a previously established non-protein aggregation sensor, namely pseudoisocyanine chloride (PIC). PIC shows fibrillization in cells into a highly fluorescent J-aggregated state and is sensitive to crowding. Surprisingly, cell stress conditions stabilise the monomeric rather than the aggregated state of PIC both in the cytoplasm and in stress granules. Regarding the different physiochemical changes of the cytoplasm occurring upon cell stress, involving volume reduction, phase separation and solidification, the intrinsic crowding effect is not the key factor to drive associated self-assembly processes.

Molecular Mechanisms of Phase Separation and Amyloidosis of ALS/FTD-linked FUS and TDP-43

FUS and TDP-43, two RNA-binding proteins from the heterogeneous nuclear ribonucleoprotein family, have gained significant attention in the field of neurodegenerative diseases due to their association with amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). They possess folded domains for binding ATP and various nucleic acids including DNA and RNA, as well as substantial intrinsically disordered regions (IDRs) including prion-like domains (PLDs) and RG-/RGG-rich regions. They play vital roles in various cellular processes, including transcription, splicing, microRNA maturation, RNA stability and transport and DNA repair. In particular, they are key components for forming ribonucleoprotein granules and stress granules (SGs) through homotypic or heterotypic liquid-liquid phase separation (LLPS). Strikingly, liquid-like droplets formed by FUS and TDP-43 may undergo aging to transform into less dynamic assemblies such as hydrogels, inclusions, and amyloid fibrils, which are the pathological hallmarks of ALS and FTD. This review aims to synthesize and consolidate the biophysical knowledge of the sequences, structures, stability, dynamics, and inter-domain interactions of FUS and TDP-43 domains, so as to shed light on the molecular mechanisms underlying their liquid-liquid phase separation (LLPS) and amyloidosis. The review further delves into the mechanisms through which ALS-causing mutants of the well-folded hPFN1 disrupt the dynamics of LLPS of FUS prion-like domain, providing key insights into a potential mechanism for misfolding/aggregation-prone proteins to cause neurodegenerative diseases and aging by gain of functions. With better understanding of different biophysical aspects of FUS and TDP-43, the ultimate goal is to develop drugs targeting LLPS and amyloidosis, which could mediate protein homeostasis within cells and lead to new treatments for currently intractable diseases, particularly neurodegenerative diseases such as ALS, FTD and aging. However, the study of membrane-less organelles and condensates is still in its infancy and therefore the review also highlights key questions that require future investigation.

Inactivation kinetics for surrogates of common foodborne pathogens during food residue drying

Postconsumer household food residues can act as useful substrates for other industries, but transporting high-moisture material corresponds to high fuel use and associated greenhouse gas production. Drying food residues at the household level reduces transportation weight, increases stability, and preserves the nutritional quality of recovered material. Mitigating foodborne microbiological safety risks is crucial to encourage the development of novel methods to rapidly dry and stabilize food residues. The objective of this study was to improve the prediction of bacterial pathogen inactivation under various thermal and drying processes in a synthetic mixture of residual food material (RFM). The log reduction rate was measured for Escherichia coli, Enterococcus faecium, and Listeria innocua (surrogates of common foodborne pathogens) in RFM under different moisture contents (12% and 25% by fresh weight) and temperatures (50, 55, and 60°C). Inactivation data were used to determine D- and z-values and to fit a multiple regression model to predict log(D-values) in response to temperature and moisture content. Across conditions, D-values were measured to be 5.1-120, 4.6-123, and 32-545 min for E. coli, L. innocua, and E. faecium, respectively. Temperature sensitivities were significantly higher in lower moisture RFM for E. coli and L. innocua. Applying E. coli inactivation models during RFM at 55°C yielded inactivation rates that aligned with experimental values after 5 min (0.1 vs. 0-0.1 logs), 30 min (2.1 vs. 1.3-2.3 logs), and 90 min (7.2 vs. 7.1-8.9 logs). These results can inform the design of RFM drying and stabilization processes to promote pathogen inactivation and safety in downstream applications of dried material.

In situ analysis of osmolyte mechanisms of proteome thermal stabilization

Organisms use organic molecules called osmolytes to adapt to environmental conditions. In vitro studies indicate that osmolytes thermally stabilize proteins, but mechanisms are controversial, and systematic studies within the cellular milieu are lacking. We analyzed Escherichia coli and human protein thermal stabilization by osmolytes in situ and across the proteome. Using structural proteomics, we probed osmolyte effects on protein thermal stability, structure and aggregation, revealing common mechanisms but also osmolyte- and protein-specific effects. All tested osmolytes (trimethylamine N-oxide, betaine, glycerol, proline, trehalose and glucose) stabilized many proteins, predominantly via a preferential exclusion mechanism, and caused an upward shift in temperatures at which most proteins aggregated. Thermal profiling of the human proteome provided evidence for intrinsic disorder in situ but also identified potential structure in predicted disordered regions. Our analysis provides mechanistic insight into osmolyte function within a complex biological matrix and sheds light on the in situ prevalence of intrinsically disordered regions.

Factors affecting protein recovery during Hsp40 affinity profiling

The identification and quantification of misfolded proteins from complex mixtures is important for biological characterization and disease diagnosis, but remains a major bioanalytical challenge. We have developed Hsp40 Affinity Profiling as a bioanalytical approach to profile protein stability in response to cellular stress. In this assay, we ectopically introduce the Hsp40 FlagDNAJB8H31Q into cells and use quantitative proteomics to determine how protein affinity for DNAJB8 changes in the presence of cellular stress, without regard for native clients. Herein, we evaluate potential approaches to improve the performance of this bioanalytical assay. We find that although intracellular crosslinking increases recovery of protein interactors, this is not enough to overcome the relative drop in DNAJB8 recovery. While the J-domain promotes Hsp70 association, it does not affect the yield of protein association with DNAJB8 under basal conditions. By contrast, crosslinking and J-domain ablation both substantially increase relative protein interactor recovery with the structurally distinct Class B Hsp40 DNAJB1 but are completely compensated by poorer yield of DNAJB1 itself. Cellular thermal stress promotes increased affinity between DNAJB8H31Q and interacting proteins, as expected for interactions driven by recognition of misfolded proteins. DNAJB8WT does not demonstrate such a property, suggesting that under stress misfolded proteins are handed off to Hsp70. Hence, we find that DNAJB8H31Q is still our most effective recognition element for the recovery of destabilized client proteins following cellular stress.

TemBERTure: advancing protein thermostability prediction with deep learning and attention mechanisms

Motivation

Understanding protein thermostability is essential for numerous biotechnological applications, but traditional experimental methods are time-consuming, expensive, and error-prone. Recently, deep learning (DL) techniques from natural language processing (NLP) was extended to the field of biology, since the primary sequence of proteins can be viewed as a string of amino acids that follow a physicochemical grammar.

Results

In this study, we developed TemBERTure, a DL framework that predicts thermostability class and melting temperature from protein sequences. Our findings emphasize the importance of data diversity for training robust models, especially by including sequences from a wider range of organisms. Additionally, we suggest using attention scores from Deep Learning models to gain deeper insights into protein thermostability. Analyzing these scores in conjunction with the 3D protein structure can enhance understanding of the complex interactions among amino acid properties, their positioning, and the surrounding microenvironment. By addressing the limitations of current prediction methods and introducing new exploration avenues, this research paves the way for more accurate and informative protein thermostability predictions, ultimately accelerating advancements in protein engineering.

Availability and implementation

TemBERTure model and the data are available at: https://github.com/ibmm-unibe-ch/TemBERTure.

Thermostability-assisted limited proteolysis-coupled mass spectrometry for capturing drug target proteins and sites

BACKGROUND

Identifying drug-binding targets and their corresponding sites is crucial for drug discovery and mechanism studies. Limited proteolysis-coupled mass spectrometry (LiP-MS) is a sophisticated method used for the detection of compound and protein interactions. However, in some cases, LiP-MS cannot identify the target proteins due to the small structure changes or the lack of enrichment of low-abundant protein. To overcome this drawback, we developed a thermostability-assisted limited proteolysis-coupled mass spectrometry (TALiP-MS) approach for efficient drug target discovery.

RESULTS

We proved that the novel strategy, TALiP-MS, could efficiently identify target proteins of various ligands, including cyclosporin A (a calcineurin inhibitor), geldanamycin (an HSP90 inhibitor), and staurosporine (a kinase inhibitor), with accurately recognizing drug-binding domains. The TALiP protocol increased the number of target peptides detected in LiP-MS experiments by 2- to 8-fold. Meanwhile, the TALiP-MS approach can not only identify both ligand-binding stability and destabilization proteins but also shows high complementarity with the thermal proteome profiling (TPP) and machine learning-based limited proteolysis (LiP-Quant) methods. The developed TALiP-MS approach was applied to identify the target proteins of celastrol (CEL), a natural product known for its strong antioxidant and anti-cancer angiogenesis effect. Among them, four proteins, MTHFD1, UBA1, ACLY, and SND1 were further validated for their strong affinity to CEL by using cellular thermal shift assay. Additionally, the destabilized proteins induced by CEL such as TAGLN2 and CFL1 were also validated.

SIGNIFICANCE

Collectively, these findings underscore the efficacy of the TALiP-MS method for identifying drug targets, elucidating binding sites, and even detecting drug-induced conformational changes in target proteins in complex proteomes.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a data merging scheme and a protein-centric multiple hypothesis correction scheme, enabling processed LiP-MS data sets to be more robust and less redundant. These improvements strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

Assessing the functional roles of coevolving PHD finger residues

Although in silico folding based on coevolving residue constraints in the deep-learning era has transformed protein structure prediction, the contributions of coevolving residues to protein folding, stability, and other functions in physical contexts remain to be clarified and experimentally validated. Herein, the PHD finger module, a well-known histone reader with distinct subtypes containing subtype-specific coevolving residues, was used as a model to experimentally assess the contributions of coevolving residues and to clarify their specific roles. The results of the assessment, including proteolysis and thermal unfolding of wildtype and mutant proteins, suggested that coevolving residues have varying contributions, despite their large in silico constraints. Residue positions with large constraints were found to contribute to stability in one subtype but not others. Computational sequence design and generative model-based energy estimates of individual structures were also implemented to complement the experimental assessment. Sequence design and energy estimates distinguish coevolving residues that contribute to folding from those that do not. The results of proteolytic analysis of mutations at positions contributing to folding were consistent with those suggested by sequence design and energy estimation. Thus, we report a comprehensive assessment of the contributions of coevolving residues, as well as a strategy based on a combination of approaches that should enable detailed understanding of the residue contributions in other large protein families.

Protein nanoparticles as drug delivery systems for cancer theranostics

Protein-based nanoparticles have garnered significant attention in theranostic applications due to their superior biocompatibility, exceptional biodegradability and ease of functionality. Compared to other nanocarriers, protein-based nanoparticles offer additional advantages, including biofunctionality and precise molecular recognition abilities, which make them highly effective in navigating complex biological environments. Moreover, proteins can serve as powerful tools with self-assembling structures and reagents that enhance cell penetration. And their derivation from abundant renewable sources and ability to degrade into harmless amino acids further enhance their suitability for biomedical applications. However, protein-based nanoparticles have so far not realized their full potential. In this review, we summarize recent advances in the use of protein nanoparticles in tumor diagnosis and treatment and outline typical methods for preparing protein nanoparticles. The review of protein nanoparticles may provide useful new insights into the development of biomaterial fabrication.

Design of a water-soluble transmembrane receptor kinase with intact molecular function by QTY code

Membrane proteins are critical to biological processes and central to life sciences and modern medicine. However, membrane proteins are notoriously challenging to study, mainly owing to difficulties dictated by their highly hydrophobic nature. Previously, we reported QTY code, which is a simple method for designing water-soluble membrane proteins. Here, we apply QTY code to a transmembrane receptor, histidine kinase CpxA, to render it completely water-soluble. The designed CpxAQTY exhibits expected biophysical properties and highly preserved native molecular function, including the activities of (i) autokinase, (ii) phosphotransferase, (iii) phosphatase, and (iv) signaling receptor, involving a water-solubilized transmembrane domain. We probe the principles underlying the balance of structural stability and activity in the water-solubilized transmembrane domain. Computational approaches suggest that an extensive and dynamic hydrogen-bond network introduced by QTY code and its flexibility may play an important role. Our successful functional preservation further substantiates the robustness and comprehensiveness of QTY code.

Review of predicting protein stability changes upon variations

Forecasting alterations in protein stability caused by variations holds immense importance. Improving the thermal stability of proteins is important for biomedical and industrial applications. This review discusses the latest methods for predicting the effects of mutations on protein stability, databases containing protein mutations and thermodynamic parameters, and experimental techniques for efficiently assessing protein stability in high-throughput settings. Various publicly available databases for protein stability prediction are introduced. Furthermore, state-of-the-art computational approaches for anticipating protein stability changes due to variants are reviewed. Each method's types of features, base algorithm, and prediction results are also detailed. Additionally, some experimental approaches for verifying the prediction results of computational methods are introduced. Finally, the review summarizes the progress and challenges of protein stability prediction and discusses potential models for future research directions.

Contribution of a C-Terminal Extension to the Substrate Affinity and Oligomeric Stability of Aldehyde Dehydrogenase from Thermus thermophilus HB27

Aldehyde dehydrogenase enzymes (ALDHs) are widely studied for their roles in disease propagation and cell metabolism. Their use in biocatalysis applications, for the conversion of aldehydes to carboxylic acids, has also been recognized. Understanding the structural features and functions of both prokaryotic and eukaryotic ALDHs is key to uncovering novel applications of the enzyme and probing its role in disease propagation. The thermostable enzyme ALDHTt originating fromThermus thermophilus, strain HB27, possesses a unique extension of its C-terminus, which has been evolutionarily excluded from mesophilic counterparts and other thermophilic enzymes in the same genus. In this work, the thermophilic adaptation is studied by the expression and optimized purification of mutant ALDHTt-508, with a 22-amino acid truncation of the C-terminus. The mutant shows increased activity throughout production compared to native ALDHTt, indicating an opening of the active site upon C-terminus truncation and giving rationale into the evolutionary exclusion of the C-terminal extension from similar thermophilic and mesophilic ALDH proteins. Additionally, the C-terminus is shown to play a role in controlling substrate specificity of native ALDH, particularly in excluding catalysis of certain large and certain aromatic ortho-substituted aldehydes, as well as modulating the protein's pH tolerance by increasing surface charge. Dynamic light scattering and size-exclusion HPLC methods are used to show the role of the C-terminus in ALDHTt oligomeric stability at the cost of catalytic efficiency. Studying the aggregation rate of ALDHTt with and without a C-terminal extension leads to the conclusion that ALDHTt follows a monomolecular reaction aggregation mechanism.

Poly-pharmacology of existing drugs: How to crack the code?

Drug development in oncology is highly challenging, with less than 5% success rate in clinical trials. This alarming figure points out the need to study in more details the multiple biological effects of drugs in specific contexts. Indeed, the comprehensive assessment of drug poly-pharmacology can provide insights into their therapeutic and adverse effects, to optimize their utilization and maximize the success rate of clinical trials. Recent technological advances have made possible in-depth investigation of drug poly-pharmacology. This review first highlights high-throughput methodologies that have been used to unveil new mechanisms of action of existing drugs. Then, we discuss how emerging chemo-proteomics strategies allow effectively dissecting the poly-pharmacology of drugs in an unsupervised manner.

The Impact of Conservative Surgical Treatment of Adenomyosis on Fertility and Perinatal Outcomes

Adenomyosis is a benign condition commonly encountered in patients with infertility. While the definitive surgical management is hysterectomy, conservative surgical management is gaining attention in patients desiring future fertility. This review explores whether the surgical treatment of adenomyosis affects fertility outcomes for patients trying to conceive. The PubMed and Medline databases were searched using the keywords: "adenomyosis", "surgery", "radiofrequency", "infertility", "pregnancy", "sterility", "conception", "miscarriage", and "endometrial receptivity". Abstracts were screened, and relevant articles were selected for review. This review reveals that surgery appears to improve fertility outcomes with or without medical therapy; however, the risk of uterine rupture remains high and the best technique to reduce this risk is still not known. More studies are needed to formulate the best surgical approach for preserving fertility in treating adenomyosis and to establish standardized guidelines.

Rapid evolutionary change in trait correlations of single proteins

Many organismal traits are genetically determined and covary in evolving populations. The resulting trait correlations can either help or hinder evolvability - the ability to bring forth new and adaptive phenotypes. The evolution of evolvability requires that trait correlations themselves must be able to evolve, but we know little about this ability. To learn more about it, we here study two evolvable systems, a yellow fluorescent protein and the antibiotic resistance protein VIM-2 metallo beta-lactamase. We consider two traits in the fluorescent protein, namely the ability to emit yellow and green light, and three traits in our enzyme, namely the resistance against ampicillin, cefotaxime, and meropenem. We show that correlations between these traits can evolve rapidly through both mutation and selection on short evolutionary time scales. In addition, we show that these correlations are driven by a protein's ability to fold, because single mutations that alter foldability can dramatically change trait correlations. Since foldability is important for most proteins and their traits, mutations affecting protein folding may alter trait correlations mediated by many other proteins. Thus, mutations that affect protein foldability may also help shape the correlations of complex traits that are affected by hundreds of proteins.

Overcoming aggregation with laser heated nanoelectrospray mass spectrometry: thermal stability and pathways for loss of bicarbonate from carbonic anhydrase II

Variable temperature electrospray mass spectrometry is useful for multiplexed measurements of the thermal stabilities of biomolecules, but the ionization process can be disrupted by aggregation-prone proteins/complexes that have irreversible unfolding transitions. Resistively heating solutions containing a mixture of bovine carbonic anhydrase II (BCAII), a CO2 fixing enzyme involved in many biochemical pathways, and cytochrome c leads to complete loss of carbonic anhydrase signal and a significant reduction in cytochrome c signal above ∼72 °C due to aggregation. In contrast, when the tips of borosilicate glass nanoelectrospray emitters are heated with a laser, complete thermal denaturation curves for both proteins are obtained in <1 minute. The simultaneous measurements of the melting temperature of BCAII and BCAII bound to bicarbonate reveal that the bicarbonate stabilizes the folded form of this protein by ∼6.4 °C. Moreover, the temperature dependences of different bicarbonate loss pathways are obtained. Although protein analytes are directly heated by the laser for only 140 ms, heat conduction further up the emitter leads to a total analyte heating time of ∼41 s. Pulsed laser heating experiments could reduce this time to ∼0.5 s for protein aggregation that occurs on a faster time scale. Laser heating provides a powerful method for studying the detailed mechanisms of cofactor/ligand loss with increasing temperature and promises a new tool for studying the effect of ligands, drugs, growth conditions, buffer additives, or other treatments on the stabilities of aggregation-prone biomolecules.

High temperature delays and low temperature accelerates evolution of a new protein phenotype

Since the origin of life, temperatures on earth have fluctuated both on short and long time scales. How such changes affect the rate at which Darwinian evolution can bring forth new phenotypes remains unclear. On the one hand, high temperature may accelerate phenotypic evolution because it accelerates most biological processes. On the other hand, it may slow phenotypic evolution, because proteins are usually less stable at high temperatures and therefore less evolvable. Here, to test these hypotheses experimentally, we evolved a green fluorescent protein in E. coli towards the new phenotype of yellow fluorescence at different temperatures. Yellow fluorescence evolved most slowly at high temperature and most rapidly at low temperature, in contradiction to the first hypothesis. Using high-throughput population sequencing, protein engineering, and biochemical assays, we determined that this is due to the protein-destabilizing effect of neofunctionalizing mutations. Destabilization is highly detrimental at high temperature, where neofunctionalizing mutations cannot be tolerated. Their detrimental effects can be mitigated through excess stability at low temperature, leading to accelerated adaptive evolution. By modifying protein folding stability, temperature alters the accessibility of mutational paths towards high-fitness genotypes. Our observations have broad implications for our understanding of how temperature changes affect evolutionary adaptations and innovations.

Application of Machine Learning in the Quantitative Analysis of the Surface Characteristics of Highly Abundant Cytoplasmic Proteins: Toward AI-Based Biomimetics

Proteins in the crowded environment of human cells have often been studied regarding nonspecific interactions, misfolding, and aggregation, which may cause cellular malfunction and disease. Specifically, proteins with high abundance are more susceptible to these issues due to the law of mass action. Therefore, the surfaces of highly abundant cytoplasmic (HAC) proteins directly exposed to the environment can exhibit specific physicochemical, structural, and geometrical characteristics that reduce nonspecific interactions and adapt to the environment. However, the quantitative relationships between the overall surface descriptors still need clarification. Here, we used machine learning to identify HAC proteins using hydrophobicity, charge, roughness, secondary structures, and B-factor from the protein surfaces and quantified the contribution of each descriptor. First, several supervised learning algorithms were compared to solve binary classification problems for the surfaces of HAC and extracellular proteins. Then, logistic regression was used for the feature importance analysis of descriptors considering model performance (80.2% accuracy and 87.6% AUC) and interpretability. The HAC proteins showed positive correlations with negatively and positively charged areas but negative correlations with hydrophobicity, the B-factor, the proportion of beta structures, roughness, and the proportion of disordered regions. Finally, the details of each descriptor could be explained concerning adaptative surface strategies of HAC proteins to regulate nonspecific interactions, protein folding, flexibility, stability, and adsorption. This study presented a novel approach using various surface descriptors to identify HAC proteins and provided quantitative design rules for the surfaces well-suited to human cellular crowded environments.

CETSA-MS-based target profiling of anti-aging natural compound quercetin

BACKGROUND

Quercetin is widely distributed in nature and abundant in the human diet, which exhibits diverse biological activities and potential medical benefits. However, there remains a lack of comprehensive understanding about its cellular targets, impeding its in-depth mechanistic studies and clinical applications.

PURPOSE

This study aimed to profile protein targets of quercetin at the proteome level.

METHODS

A label-free CETSA-MS proteomics technique was employed for target enrichment and identification. The R package Inflect was used for melting curve fitting and target selection. D3Pocket and LiBiSco tools were used for binding pocket prediction and binding pocket analysis. Western blotting, molecular docking, site-directed mutagenesis and pull-down assays were used for target verification and validation.

RESULTS

We curated a library of direct binding targets of quercetin in cells. This library comprises 37 proteins that show increased thermal stability upon quercetin binding and 33 proteins that display decreased thermal stability. Through Western blotting, molecular docking, site-directed mutagenesis and pull-down assays, we validated CBR1 and GSK3A from the stabilized protein group and MAPK1 from the destabilized group as direct binding targets of quercetin. Moreover, we characterized the shared chemical properties of the binding pockets of quercetin with targets.

CONCLUSION

Our findings deepen our understanding of the proteins pivotal to the bioactivity of quercetin and lay the groundwork for further exploration into its mechanisms of action and potential clinical applications.

Discovering Genetic Modulators of the Protein Homeostasis System through Multilevel Analysis

Every protein progresses through a natural lifecycle from birth to maturation to death; this process is coordinated by the protein homeostasis system. Environmental or physiological conditions trigger pathways that maintain the homeostasis of the proteome. An open question is how these pathways are modulated to respond to the many stresses that an organism encounters during its lifetime. To address this question, we tested how the fitness landscape changes in response to environmental and genetic perturbations using directed and massively parallel transposon mutagenesis in Caulobacter crescentus. We developed a general computational pipeline for the analysis of gene-by-environment interactions in transposon mutagenesis experiments. This pipeline uses a combination of general linear models (GLMs), statistical knockoffs, and a nonparametric Bayesian statistical model to identify essential genetic network components that are shared across environmental perturbations. This analysis allows us to quantify the similarity of proteotoxic environmental perturbations from the perspective of the fitness landscape. We find that essential genes vary more by genetic background than by environmental conditions, with limited overlap among mutant strains targeting different facets of the protein homeostasis system. We also identified 146 unique fitness determinants across different strains, with 19 genes common to at least two strains, showing varying resilience to proteotoxic stresses. Experiments exposing cells to a combination of genetic perturbations and dual environmental stressors show that perturbations that are quantitatively dissimilar from the perspective of the fitness landscape are likely to have a synergistic effect on the growth defect.

Macromolecular Crowding, Phase Separation, and Homeostasis in the Orchestration of Bacterial Cellular Functions

Macromolecular crowding affects the activity of proteins and functional macromolecular complexes in all cells, including bacteria. Crowding, together with physicochemical parameters such as pH, ionic strength, and the energy status, influences the structure of the cytoplasm and thereby indirectly macromolecular function. Notably, crowding also promotes the formation of biomolecular condensates by phase separation, initially identified in eukaryotic cells but more recently discovered to play key functions in bacteria. Bacterial cells require a variety of mechanisms to maintain physicochemical homeostasis, in particular in environments with fluctuating conditions, and the formation of biomolecular condensates is emerging as one such mechanism. In this work, we connect physicochemical homeostasis and macromolecular crowding with the formation and function of biomolecular condensates in the bacterial cell and compare the supramolecular structures found in bacteria with those of eukaryotic cells. We focus on the effects of crowding and phase separation on the control of bacterial chromosome replication, segregation, and cell division, and we discuss the contribution of biomolecular condensates to bacterial cell fitness and adaptation to environmental stress.

Discovery of N-Benzyl-4-(1-bromonaphthalen-2-yl)oxybutan-1-amine as a Potential Antifungal Agent against Sporidia Growth and Teliospore Germination of Sporisorium scitamineum

The cultivation of sugar cane using perennial roots is the primary planting method, which is one of the reasons for the serious occurrence of sugar cane smut disease caused by the basidiomycetous fungus Sporisorium scitamineum in the sugar cane perennial root planting area. Consequently, it is crucial to eliminate pathogens from perennial sugar cane buds. In this study, we found that MAP kinase Hog1 is necessary for heat stress resistance. Subsequent investigations revealed a significant reduction in the expression of the heat shock protein 104-encoding gene, SsHSP104, in the ss1hog1Δ mutant. Additionally, the overexpression of SsHSP104 partially restored colony growth in the ss1hog1Δ strain following heat stress treatment, demonstrating the crucial role of SsHsp104 in SsHog1-mediated heat stress tolerance. Hence, we constructed the ss1hsp104:eGFP fusion strain in the wild type of S. scitamineum to identify small-molecule compounds that could inhibit the heat stress response, leading to the discovery of N-benzyl-4-(1-bromonaphthalen-2-yl)oxybutan-1-amine as a potential compound that targets the SsHog1 mediation SsHsp104 pathway during heat treatment. Furthermore, the combination of N-benzyl-4-(1-bromonaphthalen-2-yl)oxybutan-1-amine and warm water treatment (45 °C for 15 min) inhibits the growth of S. scitamineum and teliospore germination, thereby reducing the occurrence of sugar cane smut diseases and indicating its potential for eliminating pathogens from perennial sugar cane buds. In conclusion, these findings suggest that N-benzyl-4-(1-bromonaphthalen-2-yl)oxybutan-1-amine is promising as a targeted compound for the SsHog1-mediated SsHsp104 pathway and may enable the reduction of hot water treatment duration and/or temperature, thereby limiting the occurrence of sugar cane smut diseases caused by S. scitamineum.

Decoding the Role of the Global Proteome Dynamics for Cellular Thermal Stability

Molecular mechanisms underlying the thermal response of cells remain elusive. On the basis of the recent result that the short-time diffusive dynamics of the Escherichia coli proteome is an excellent indicator of temperature-dependent bacterial metabolism and death, we used neutron scattering (NS) spectroscopy and molecular dynamics (MD) simulations to investigate the sub-nanosecond proteome mobility in psychro-, meso-, and hyperthermophilic bacteria over a wide temperature range. The magnitude of thermal fluctuations, measured by atomic mean square displacements, is similar among all studied bacteria at their respective thermal cell death. Global roto-translational motions turn out to be the main factor distinguishing the bacterial dynamical properties. We ascribe this behavior to the difference in the average proteome net charge, which becomes less negative for increasing bacterial thermal stability. We propose that the chemical-physical properties of the cytoplasm and the global dynamics of the resulting proteome are fine-tuned by evolution to uphold optimal thermal stability conditions.

Systematic review and meta-analysis of reproductive outcomes after high-intensity focused ultrasound (HIFU) treatment of adenomyosis

High-intensity focused ultrasound (HIFU) has emerged as a promising uterus-sparing and possibly fertility-sparing treatment modality for women with adenomyosis, especially those who desire to conceive. We conducted this systematic review and performed a meta-analysis on clinical studies aimed to improve reproduction in women with adenomyosis. After extensive search of PubMed and CNKI, we identified 10 studies published in English and Chinese involving a total of 557 patients with adenomyosis who desired to conceive after HIFU treatment. We found a pooled estimate of pregnancy rate of 53.4% and of the live birth rate of 35.2%, and there was a substantial heterogeneity among these studies. While there is a potential for HIFU treatment to improve fertility for patients with adenomyosis who desired to conceive, such evidence is very weak as of now. Comparative studies with much higher methodological rigor, preferably randomized clinical trials, are badly needed to further illuminate this issue.

Chemoproteomics, A Broad Avenue to Target Deconvolution

As a vital project of forward chemical genetic research, target deconvolution aims to identify the molecular targets of an active hit compound. Chemoproteomics, either with chemical probe-facilitated target enrichment or probe-free, provides a straightforward and effective approach to profile the target landscape and unravel the mechanisms of action. Canonical methods rely on chemical probes to enable target engagement, enrichment, and identification, whereas click chemistry and photoaffinity labeling techniques improve the efficiency, sensitivity, and spatial accuracy of target recognition. In comparison, recently developed probe-free methods detect protein-ligand interactions without the need to modify the ligand molecule. This review provides a comprehensive overview of different approaches and recent advancements for target identification and highlights the significance of chemoproteomics in investigating biological processes and advancing drug discovery processes.

The Protein Response of Salt-Tolerant Zygosaccharomyces rouxii to High-Temperature Stress during the Lag Phase

Zygosaccharomyces rouxii used in soy sauce brewing is an osmotolerant and halotolerant yeast, but it is not tolerant to high temperatures and the underlying mechanisms remain poorly understood. Using a synthetic medium containing only Pro as a nitrogen source, the response of Z. rouxii in protein level to high-temperature stress (40 °C, HTS) during the lag phase was investigated. Within the first two h, the total intracellular protein concentration was significantly decreased from 220.99 ± 6.58 μg/mg DCW to 152.63 ± 10.49 μg/mg DCW. The analysis of the amino acid composition of the total protein through vacuum proteolysis technology and HPLC showed that new amino acids (Thr, Tyr, Ser, and His) were added to newborn protein over time during the lag phase under HTS. The nutritional conditions used in this study determined that the main source of amino acid supply for protein synthesis was through amino acid biosynthesis and ubiquitination-mediated protein degradation. Differential expression analysis of the amino acid biosynthesis-related genes in the transcriptome showed that most genes were upregulated under HTS, excluding ARO8, which was consistently repressed during the lag phase. RT-qPCR results showed that high-temperature stress significantly increased the upregulation of proteolysis genes, especially PSH1 (E3 ubiquitin ligase) by 13.23 ± 1.44 fold (p < 0.0001) within 4 h. Overall, these results indicated that Z. rouxii adapt to prolonged high temperatures stress by altering its basal protein composition. This protein renewal was related to the regulation of proteolysis and the biosynthesis of amino acids.

Effects of Crowding and Cosolutes on Biomolecular Function at Extreme Environmental Conditions

The extent of the effect of cellular crowding and cosolutes on the functioning of proteins and cells is manifold and includes the stabilization of the biomolecular systems, the excluded volume effect, and the modulation of molecular dynamics. Simultaneously, it is becoming increasingly clear how important it is to take the environment into account if we are to shed light on biological function under various external conditions. Many biosystems thrive under extreme conditions, including the deep sea and subseafloor crust, and can take advantage of some of the effects of crowding. These relationships have been studied in recent years using various biophysical techniques, including neutron and X-ray scattering, calorimetry, FTIR, UV-vis and fluorescence spectroscopies. Combining knowledge of the structure and conformational dynamics of biomolecules under extreme conditions, such as temperature, high hydrostatic pressure, and high salinity, we highlight the importance of considering all results in the context of the environment. Here we discuss crowding and cosolute effects on proteins, nucleic acids, membranes, and live cells and explain how it is possible to experimentally separate crowding-induced effects from other influences. Such findings will contribute to a better understanding of the homeoviscous adaptation of organisms and the limits of life in general.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Datasets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage the fast, sensitive, and accurate search and label-free quantification algorithms in FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a new data merging scheme (from ions to cut-sites) and a protein-centric multiple hypothesis correction scheme, collectively enabling processed LiP-MS datasets to be more robust and less redundant. These improvements substantially strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. As a final feature, FLiPPR facilitates the collection of structural metadata to identify correlations between experiments and structural features. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

Advanced Techniques for Detecting Protein Misfolding and Aggregation in Cellular Environments

Protein misfolding and aggregation, a key contributor to the progression of numerous neurodegenerative diseases, results in functional deficiencies and the creation of harmful intermediates. Detailed visualization of this misfolding process is of paramount importance for improving our understanding of disease mechanisms and for the development of potential therapeutic strategies. While in vitro studies using purified proteins have been instrumental in delivering significant insights into protein misfolding, the behavior of these proteins in the complex milieu of living cells often diverges significantly from such simplified environments. Biomedical imaging performed in cell provides cellular-level information with high physiological and pathological relevance, often surpassing the depth of information attainable through in vitro methods. This review highlights a variety of methodologies used to scrutinize protein misfolding within biological systems. This includes optical-based methods, strategies leaning on mass spectrometry, in-cell nuclear magnetic resonance, and cryo-electron microscopy. Recent advancements in these techniques have notably deepened our understanding of protein misfolding processes and the features of the resulting misfolded species within living cells. The progression in these fields promises to catalyze further breakthroughs in our comprehension of neurodegenerative disease mechanisms and potential therapeutic interventions.

Shift of the insoluble content of the proteome in the aging mouse brain

During aging, the cellular response to unfolded proteins is believed to decline, resulting in diminished proteostasis. In model organisms, such as Caenorhabditis elegans, proteostatic decline with age has been linked to proteome solubility shifts and the onset of protein aggregation. However, this correlation has not been extensively characterized in aging mammals. To uncover age-dependent changes in the insoluble portion of a mammalian proteome, we analyzed the detergent-insoluble fraction of mouse brain tissue by mass spectrometry. We identified a group of 171 proteins, including the small heat shock protein α-crystallin, that become enriched in the detergent-insoluble fraction obtained from old mice. To enhance our ability to detect features associated with proteins in that fraction, we complemented our data with a meta-analysis of studies reporting the detergent-insoluble proteins in various mouse models of aging and neurodegeneration. Strikingly, insoluble proteins from young and old mice are distinct in several features in our study and across the collected literature data. In younger mice, proteins are more likely to be disordered, part of membraneless organelles, and involved in RNA binding. These traits become less prominent with age, as an increased number of structured proteins enter the pellet fraction. This analysis suggests that age-related changes to proteome organization lead a group of proteins with specific features to become detergent-insoluble. Importantly, these features are not consistent with those associated with proteins driving membraneless organelle formation. We see no evidence in our system of a general increase of condensate proteins in the detergent-insoluble fraction with age.

Core Body Temperatures in Intermittent Sports: A Systematic Review

BACKGROUND

Hyperthermia (and associated health and performance implications) can be a significant problem for athletes and teams involved in intermittent sports. Quantifying the highest thermal strain (i.e. peak core body temperature [peak Tc]) from a range of intermittent sports would enhance our understanding of the thermal requirements of sport and assist in making informed decisions about training or match-day interventions to reduce thermally induced harm and/or performance decline.

OBJECTIVE

The objective of this systematic review was to synthesise and characterise the available thermal strain data collected in competition from intermittent sport athletes.

METHODS

A systematic literature search was performed on Web of Science, MEDLINE, and SPORTDiscus to identify studies up to 17 April 2023. Electronic databases were searched using a text mining method to provide a partially automated and systematic search strategy retrieving terms related to core body temperature measurement and intermittent sport. Records were eligible if they included core body temperature measurement during competition, without experimental intervention that may influence thermal strain (e.g. cooling), in healthy, adult, intermittent sport athletes at any level. Due to the lack of an available tool that specifically includes potential sources of bias for physiological responses in descriptive studies, a methodological evaluation checklist was developed and used to document important methodological considerations. Data were not meta-analysed given the methodological heterogeneity between studies and therefore were presented descriptively in tabular and graphical format.

RESULTS

A total of 34 studies were selected for review; 27 were observational, 5 were experimental (2 parallel group and 3 repeated measures randomised controlled trials), and 2 were quasi-experimental (1 parallel group and 1 repeated measures non-randomised controlled trial). Across all included studies, 386 participants (plus participant numbers not reported in two studies) were recruited after accounting for shared data between studies. A total of 4 studies (~ 12%) found no evidence of hyperthermia, 24 (~ 71%) found evidence of 'modest' hyperthermia (peak Tc between 38.5 and 39.5 °C), and 6 (~ 18%) found evidence of 'marked' hyperthermia (peak Tc of 39.5 °C or greater) during intermittent sports competition.

CONCLUSIONS

Practitioners and coaches supporting intermittent sport athletes are justified to seek interventions aimed at mitigating the high heat strain observed in competition. More research is required to determine the most effective interventions for this population that are practically viable in intermittent sports settings (often constrained by many competing demands). Greater statistical power and homogeneity among studies are required to quantify the independent effects of wet bulb globe temperature, competition duration, sport and level of competition on peak Tc, all of which are likely to be key modulators of the thermal strain experienced by competing athletes.

REGISTRATION

This systematic review was registered on the Open Science Framework ( https://osf.io/vfb4s ; https://doi.org/10.17605/OSF.IO/EZYFA , 4 January 2021).

A physicochemical perspective on cellular ageing

Cellular ageing described at the molecular level is a multifactorial process that leads to a spectrum of ageing trajectories. There has been recent discussion about whether a decline in physicochemical homeostasis causes aberrant phase transitions, which are a driver of ageing. Indeed, the function of all biological macromolecules, regardless of their participation in biomolecular condensates, depends on parameters such as pH, crowding, and redox state. We expand on the physicochemical homeostasis hypothesis and summarise recent evidence that the intracellular milieu influences molecular processes involved in ageing.