Total cell protein concentration as an evolutionary constraint on the metabolic control distribution in cells

Interplay of Proteostasis Capacity and Protein Aggregation: Implications for Cellular Function and Disease

Eukaryotic cells are equipped with an intricate proteostasis network (PN), comprising nearly 3,000 components dedicated to preserving proteome integrity and sustaining protein homeostasis. This protective system is particularly important under conditions of external and intrinsic cell stress, where inherently dynamic proteins may unfold and lose functionality. A decline in proteostasis capacity is associated with the aging process, resulting in a reduced folding efficiency of newly synthesized proteins and a deficit in the cellular capacity to degrade misfolded proteins. A critical consequence of PN insufficiency is the accumulation of cytotoxic protein aggregates that underlie various age-related neurodegenerative conditions and other pathologies. By interfering with specific proteostasis components, toxic aggregates place an excessive burden on the PN's ability to maintain proteome integrity. This initiates a feed-forward loop, wherein the generation of misfolded and aggregated proteins ultimately leads to proteostasis collapse and cellular demise.

Protecting Proteins from Desiccation Stress Using Molecular Glasses and Gels

Faced with desiccation stress, many organisms deploy strategies to maintain the integrity of their cellular components. Amorphous glassy media composed of small molecular solutes or protein gels present general strategies for protecting against drying. We review these strategies and the proposed molecular mechanisms to explain protein protection in a vitreous matrix under conditions of low hydration. We also describe efforts to exploit similar strategies in technological applications for protecting proteins in dry or highly desiccated states. Finally, we outline open questions and possibilities for future explorations.

Initial Primer Synthesis of a DNA Primase Monitored by Real-Time NMR Spectroscopy

Primases are crucial enzymes for DNA replication, as they synthesize a short primer required for initiating DNA replication. We herein present time-resolved nuclear magnetic resonance (NMR) spectroscopy in solution and in the solid state to study the initial dinucleotide formation reaction of archaeal pRN1 primase. Our findings show that the helix-bundle domain (HBD) of pRN1 primase prepares the two substrates and then hands them over to the catalytic domain to initiate the reaction. By using nucleotide triphosphate analogues, the reaction is substantially slowed down, allowing us to study the initial dinucleotide formation in real time. We show that the sedimented protein-DNA complex remains active in the solid-state NMR rotor and that time-resolved 31P-detected cross-polarization experiments allow monitoring the kinetics of dinucleotide formation. The kinetics in the sedimented protein sample are comparable to those determined by solution-state NMR. Protein conformational changes during primer synthesis are observed in time-resolved 1H-detected experiments at fast magic-angle spinning frequencies (100 kHz). A significant number of spectral changes cluster in the HBD pointing to the importance of the HBD for positioning the nucleotides and the dinucleotide.

Elemental and macromolecular plasticity of Chlamydomonas reinhardtii (Chlorophyta) in response to resource limitation and growth rate

With the ongoing differential disruption of the biogeochemical cycles of major elements that are essential for all life (carbon, nitrogen, and phosphorus), organisms are increasingly faced with a heterogenous supply of these elements in nature. Given that photosynthetic primary producers form the base of aquatic food webs, impacts of changed elemental supply on these organisms are particularly important. One way that phytoplankton cope with the differential availability of nutrients is through physiological changes, resulting in plasticity in macromolecular and elemental biomass composition. Here, we assessed how the green alga Chlamydomonas reinhardtii adjusts its macromolecular (e.g., carbohydrates, lipids, and proteins) and elemental (C, N, and P) biomass pools in response to changes in growth rate and the modification of resources (nutrients and light). We observed that Chlamydomonas exhibits considerable plasticity in elemental composition (e.g., molar ratios ranging from 124 to 971 for C:P, 4.5 to 25.9 for C:N, and 15.1 to 61.2 for N:P) under all tested conditions, pointing to the adaptive potential of Chlamydomonas in a changing environment. Exposure to low light modified the elemental and macromolecular composition of cells differently than limitation by nutrients. These observed differences, with potential consequences for higher trophic levels, included smaller cells, shifts in C:N and C:P ratios (due to proportionally greater N and P contents), and differential allocation of C among macromolecular pools (proportionally more lipids than carbohydrates) with different energetic value. However, substantial pools of N and P remained unaccounted for, especially at fast growth, indicating accumulation of N and P in forms we did not measure.

Optimal enzyme profiles in unbranched metabolic pathways

How to optimize the allocation of enzymes in metabolic pathways has been a topic of study for many decades. Although the general problem is complex and nonlinear, we have previously shown that it can be solved by convex optimization. In this paper, we focus on unbranched metabolic pathways with simplified enzymatic rate laws and derive analytic solutions to the optimization problem. We revisit existing solutions based on the limit of mass-action rate laws and present new solutions for other rate laws. Furthermore, we revisit a known relationship between flux control coefficients and enzyme abundances in optimal metabolic states. We generalize this relationship to models with density constraints on enzymes and metabolites, and present a new local relationship between optimal reaction elasticities and enzyme amounts. Finally, we apply our theory to derive simple kinetics-based formulae for protein allocation during bacterial growth.

Kinetic modeling of leucine-mediated signaling and protein metabolism in human skeletal muscle

Skeletal muscle protein levels are governed by the relative rates of muscle protein synthesis (MPS) and breakdown (MPB). The mechanisms controlling these rates are complex, and their integrated behaviors are challenging to study through experiments alone. The purpose of this study was to develop and analyze a kinetic model of leucine-mediated mTOR signaling and protein metabolism in the skeletal muscle of young adults. Our model amalgamates published cellular-level models of the IRS1-PI3K-Akt-mTORC1 signaling system and of skeletal-muscle leucine kinetics with physiological-level models of leucine digestion and transport and insulin dynamics. The model satisfactorily predicts experimental data from diverse leucine feeding protocols. Model analysis revealed that total levels of p70S6K are a primary determinant of MPS, insulin signaling substantially affects muscle net protein balance via its effects on MPB, and p70S6K-mediated feedback of mTORC1 signaling reduces MPS in a dose-dependent manner.

Application of quantitative protein mass spectrometric data in the early predictive analysis of membrane-bound target engagement by monoclonal antibodies

Model-informed drug discovery advocates the use of mathematical modeling and simulation for improved efficacy in drug discovery. In the case of monoclonal antibodies (mAbs) against cell membrane antigens, this requires quantitative insight into the target tissue concentration levels. Protein mass spectrometry data are often available but the values are expressed in relative, rather than in molar concentration units that are easier to incorporate into pharmacokinetic models. Here, we present an empirical correlation that converts the parts per million (ppm) concentrations in the PaxDb database to their molar equivalents that are more suitable for pharmacokinetic modeling. We evaluate the insight afforded to target tissue distribution by analyzing the likely tumor-targeting accuracy of mAbs recognizing either epidermal growth factor receptor or its homolog HER2. Surprisingly, the predicted tissue concentrations of both these targets exceed the Kd values of their respective therapeutic mAbs. Physiologically based pharmacokinetic (PBPK) modeling indicates that in these conditions only about 0.05% of the dosed mAb is likely to reach the solid tumor target cells. The rest of the dose is eliminated in healthy tissues via both nonspecific and target-mediated processes. The presented approach allows evaluation of the interplay between the target expression level in different tissues that determines the overall pharmacokinetic properties of the drug and the fraction that reaches the cells of interest. This methodology can help to evaluate the efficacy and safety properties of novel drugs, especially if the off-target cell degradation has cytotoxic outcomes, as in the case of antibody-drug conjugates.

Structural and functional complexity of HSP90 in cellular homeostasis and disease

Heat shock protein 90 (HSP90) is a chaperone with vital roles in regulating proteostasis, long recognized for its function in protein folding and maturation. A view is emerging that identifies HSP90 not as one protein that is structurally and functionally homogeneous but, rather, as a protein that is shaped by its environment. In this Review, we discuss evidence of multiple structural forms of HSP90 in health and disease, including homo-oligomers and hetero-oligomers, also termed epichaperomes, and examine the impact of stress, post-translational modifications and co-chaperones on their formation. We describe how these variations influence context-dependent functions of HSP90 as well as its interaction with other chaperones, co-chaperones and proteins, and how this structural complexity of HSP90 impacts and is impacted by its interaction with small molecule modulators. We close by discussing recent developments regarding the use of HSP90 inhibitors in cancer and how our new appreciation of the structural and functional heterogeneity of HSP90 invites a re-evaluation of how we discover and implement HSP90 therapeutics for disease treatment.

On paradoxes between optimal growth, metabolic control analysis, and flux balance analysis

In Microbiology it is often assumed that growth rate is maximal. This may be taken to suggest that the dependence of the growth rate on every enzyme activity is at the top of an inverse-parabolic function, i.e. that all flux control coefficients should equal zero. This might seem to imply that the sum of these flux control coefficients equals zero. According to the summation law of Metabolic Control Analysis (MCA) the sum of flux control coefficients should equal 1 however. And in Flux Balance Analysis (FBA) catabolism is often limited by a hard bound, causing catabolism to fully control the fluxes, again in apparent contrast with a flux control coefficient of zero. Here we resolve these paradoxes (apparent contradictions) in an analysis that uses the 'Edinburgh pathway', the 'Amsterdam pathway', as well as a generic metabolic network providing the building blocks or Gibbs energy for microbial growth. We review and show that (i) optimization depends on so-called enzyme control coefficients rather than the 'catalytic control coefficients' of MCA's summation law, (ii) when optimization occurs at fixed total protein, the former differ from the latter to the extent that they may all become equal to zero in the optimum state, (iii) in more realistic scenarios of optimization where catalytically inert biomass is compensating or maintenance metabolism is taken into consideration, the optimum enzyme concentrations should not be expected to equal those that maximize the specific growth rate, (iv) optimization may be in terms of yield rather than specific growth rate, which resolves the paradox because the sum of catalytic control coefficients on yield equals 0, (v) FBA effectively maximizes growth yield, and for yield the summation law states 0 rather than 1, thereby removing the paradox, (vi) furthermore, FBA then comes more often to a 'hard optimum' defined by a maximum catabolic flux and a catabolic-enzyme control coefficient of 1. The trade-off between maintenance metabolism and growth is highlighted as worthy of further analysis.

Unveiling protein-protein interaction potential through Monte Carlo simulation combined with small-angle X-ray scattering

Protein interactions are investigated under different conditions of lysozyme concentration, temperature and ionic strength by means of in-solution small angle X-Ray scattering (SAXS) experiments and Monte Carlo (MC) simulations. Initially, experimental data were analysed through a Hard-Sphere Double Yukawa (HSDY) model combined with Random Phase Approximation (RPA), a closure relationship commonly used in the literature for monodisperse systems. We realized by means of MC that the HSDY/RPA modelling fails to describe the protein-protein pair potential for moderated and dense systems at low ionic strength, mainly due to inherent distortions of the RPA approximation. Our SAXS/MC results thus show that lysozyme concentrations between 2 (diluted) and 20 mg/mL (not crowded) present similar protein-protein pair potential preserving the values of surface net charge around 7 e, protein diameter of 28 Å, decay range of attractive well potential of 3 Å and a depth of the well potential varying from 1 to 5 kBT depending on temperature and salt addition. Noteworthy, we here propose a novel method to analyse the SAXS data from interacting proteins through MC simulations, which overcomes the deficiencies presented by the use of a closure relationship. Furthermore, this new methodology of combining SAXS with MC simulations gives a step forward to investigate more complex systems as those composed of a mixture of proteins of distinct species presenting different molecular weights (and hence sizes) and surface net charges at low, moderate and very dense systems.

Branched-chain keto acids inhibit mitochondrial pyruvate carrier and suppress gluconeogenesis in hepatocytes

Branched-chain amino acid (BCAA) metabolism is linked to glucose homeostasis, but the underlying signaling mechanisms are unclear. We find that gluconeogenesis is reduced in mice deficient of Ppm1k, a positive regulator of BCAA catabolism, which protects against obesity-induced glucose intolerance. Accumulation of branched-chain keto acids (BCKAs) inhibits glucose production in hepatocytes. BCKAs suppress liver mitochondrial pyruvate carrier (MPC) activity and pyruvate-supported respiration. Pyruvate-supported gluconeogenesis is selectively suppressed in Ppm1k-deficient mice and can be restored with pharmacological activation of BCKA catabolism by BT2. Finally, hepatocytes lack branched-chain aminotransferase that alleviates BCKA accumulation via reversible conversion between BCAAs and BCKAs. This renders liver MPC most susceptible to circulating BCKA levels hence a sensor of BCAA catabolism.

Hydrogen Deuterium Exchange and other Mass Spectrometry-based Approaches for Epitope Mapping

Antigen-antibody interactions are a fundamental subset of protein-protein interactions responsible for the "survival of the fittest". Determining the interacting interface of the antigen, called an epitope, and that on the antibody, called a paratope, is crucial to antibody development. Because each antigen presents multiple epitopes (unique footprints), sophisticated approaches are required to determine the target region for a given antibody. Although X-ray crystallography, Cryo-EM, and nuclear magnetic resonance can provide atomic details of an epitope, they are often laborious, poor in throughput, and insensitive. Mass spectrometry-based approaches offer rapid turnaround, intermediate structural resolution, and virtually no size limit for the antigen, making them a vital approach for epitope mapping. In this review, we describe in detail the principles of hydrogen deuterium exchange mass spectrometry in application to epitope mapping. We also show that a combination of MS-based approaches can assist or complement epitope mapping and push the limit of structural resolution to the residue level. We describe in detail the MS methods used in epitope mapping, provide our perspective about the approaches, and focus on elucidating the role that HDX-MS is playing now and in the future by organizing a discussion centered around several improvements in prototype instrument/applications used for epitope mapping. At the end, we provide a tabular summary of the current literature on HDX-MS-based epitope mapping.

Metabolic Control Analysis of triacylglycerol accumulation in oilseed rape

The increasing global demand for vegetable oils will only be met if there are significant improvements in the productivity of the major oil crops, such as oilseed rape. Metabolic engineering offers the prospect of further gains in yield beyond that already achieved by breeding and selection but requires guidance as to the changes that need to be made. Metabolic Control Analysis, through measurement and estimation of flux control coefficients, can indicate which enzymes have the most influence on a desired flux. Some experiments have previously reported flux control coefficients for oil accumulation in the seeds of oilseed rape, and others have measured control coefficient distributions for multi-enzyme segments of oil synthesis in seed embryo metabolism measured in vitro. In addition, other reported manipulations of oil accumulation contain results that are exploited further here to calculate previously unknown flux control coefficients. These results are then assembled within a framework that allows an integrated interpretation of the controls on oil accumulation from the assimilation of CO₂ to deposition of oil in the seed. The analysis shows that the control is distributed to an extent that the gains from amplifying any single target are necessarily limited, but there are candidates for joint amplification that are likely to act synergistically to produce much more significant gains.

Ion influence on surface water dynamics and proton exchange at protein surfaces - A unified model for transverse and longitudinal NMR relaxation dispersion

In all biologically relevant media, proteins interact in the presence of surrounding ions, and such interactions are water-mediated. Water molecules play a crucial role in the restructuring of proteins in solution and indeed in their biological activity. Surface water dynamics and proton exchange at protein surfaces is investigated here using NMR relaxometry, for two well-known globular proteins, lysozyme and bovine serum albumin, with particular attention to the role of surface ions. We present a unified model of surface water dynamics and proton exchange, accounting simultaneously for the observed longitudinal and transverse relaxation rates. The most notable effect of salt (0.1 M) concerns the slow surface water dynamics, related to rare water molecules embedded in energy wells on the protein surface. This response is protein-specific. On the other hand, the proton exchange time between labile protein-protons and water-protons at the protein surface seems to be very similar for the two proteins and is insensitive to the addition of salts at the concentration studied.

Cell growth and the cell cycle: New insights about persistent questions

Before a cell divides into two daughter cells, it typically doubles not only its DNA, but also its mass. Numerous studies in cells ranging from yeast to mammals have shown that cellular growth, stimulated by nutrients and/or growth factor signaling, is a prerequisite for cell cycle progression in most types of cells. The textbook view of growth-regulated cell cycles is that growth signaling activates the transcription of G1 Cyclin genes to induce cell proliferation, and also stimulates anabolic metabolism and cell growth in parallel. However, genetic knockout tests in model organisms indicate that this is not the whole story, and new studies show that additional, "smarter" mechanisms help to coordinate the cell cycle with growth itself. Here we summarize recent advances in this field, and discuss current models in which growth signaling regulates cell proliferation by targeting core cell cycle regulators via non-transcriptional mechanisms.

[Melatonin: A short clarification for the over-enthusiasts]

Melatonin is a naturally occurring molecule derived from tryptophan. Melatonin is a key player in relaying the circadian rhythm between our environment and our body. It has also a key role in rhythming the seasons (more production during long nights and less during short ones) as well as in the reproduction cycles of the mammals. Melatonin is often and surprisingly presented as a molecule with multiple therapeutic properties that can fix (or help to fix) many health issues, such as diseases (cancer, ageing, virus-induced affections including COVID-19, etc…) or toxicological situations (metals, venoms, chemical such as adriamycin [doxorubicin], methotrexate or paclitaxel). The mechanistics behind those wonders is still missing and this is puzzling. In the present commentary, the main well-established biological properties are presented and briefly discussed with the aim of delineating the borders between facts and wishful thinking.

Vitreoscilla Haemoglobin: A Tool to Reduce Overflow Metabolism

Overflow metabolism is a phenomenon extended in nature, ranging from microbial to cancer cells. Accumulation of overflow metabolites pose a challenge for large-scale bioprocesses. Yet, the causes of overflow metabolism are not fully clarified. In this work, the underlying mechanisms, reasons and consequences of overflow metabolism in different organisms have been summarized. The reported effect of aerobic expression of Vitreoscilla haemoglobin (VHb) in different organisms are revised. The use of VHb to reduce overflow metabolism is proposed and studied through flux balance analysis in E. coli at a fixed maximum substrate and oxygen uptake rates. Simulations showed that the presence of VHb increases the growth rate, while decreasing acetate production, in line with the experimental measurements. Therefore, aerobic VHb expression is considered a potential tool to reduce overflow metabolism in cells.

Ongoing Challenges to Develop High Concentration Monoclonal Antibody-based Formulations for Subcutaneous Administration: Quo Vadis?

Although many subcutaneously (s.c.) delivered, high-concentration antibody formulations (HCAF) have received regulatory approval and are widely used commercially, formulation scientists are still presented with many ongoing challenges during HCAF development with new mAb and mAb-based candidates. Depending on the specific physicochemical and biological properties of a particular mAb-based molecule, such challenges vary from pharmaceutical attributes e.g., stability, viscosity, manufacturability, to clinical performance e.g., bioavailability, immunogenicity, and finally to patient experience e.g., preference for s.c. vs. intravenous delivery and/or preferred interactions with health-care professionals. This commentary focuses on one key formulation obstacle encountered during HCAF development: how to maximize the dose of the drug? We examine methodologies for increasing the protein concentration, increasing the volume delivered, or combining both approaches together. We discuss commonly encountered hurdles, i.e., physical protein instability and solution volume limitations, and we provide recommendations to formulation scientists to facilitate their development of s.c. administered HCAF with new mAb-based product candidates.

Intelligent host engineering for metabolic flux optimisation in biotechnology

Optimising the function of a protein of length N amino acids by directed evolution involves navigating a 'search space' of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is 'making such biology predictable'. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.

Multiscale Water Dynamics on Protein Surfaces: Protein-Specific Response to Surface Ions

Proteins function in crowded aqueous environments, interacting with a diverse range of compounds, and among them, dissolved ions. These interactions are water-mediated. In the present study, we combine field-dependent NMR relaxation (NMRD) and theory to probe water dynamics on the surface of proteins in concentrated aqueous solutions of hen egg-white lysozyme (LZM) and bovine serum albumin (BSA). The experiments reveal that the presence of salts (NaCl or NaI) leads to an opposite ion-specific response for the two proteins: an addition of salt to LZM solutions increases water relaxation rates with respect to the salt-free case, while for BSA solutions, a decrease is observed. The magnitude of the change depends on the ion identity. The developed model accounts for the non-Lorentzian shape of the NMRD profiles and reproduces the experimental data over four decades in Larmor frequency (10 kHz to 110 MHz). It is applicable up to high protein concentrations. The model incorporates the observed ion-specific effects via changes in the protein surface roughness, represented by the surface fractal dimension, and the accompanying changes in the surface water residence times. The response is protein-specific, linked to geometrical aspects of the individual protein surfaces, and goes beyond protein-independent Hofmeister-style ordering of ions.

Measuring how two proteins affect each other's net charge in a crowded environment

Theory predicts that the net charge (Z) of a protein can be altered by the net charge of a neighboring protein as the two approach one another below the Debye length. This type of charge regulation suggests that a protein's charge and perhaps function might be affected by neighboring proteins without direct binding. Charge regulation during protein crowding has never been directly measured due to analytical challenges. Here, we show that lysine specific protein crosslinkers (NHS ester-Staudinger pairs) can be used to mimic crowding by linking two non-interacting proteins at a maximal distance of ~7.9 Å. The net charge of the regioisomeric dimers and preceding monomers can then be determined with lysine-acyl "protein charge ladders" and capillary electrophoresis. As a proof of concept, we covalently linked myoglobin (Z_monomer  = -0.43 ± 0.01) and α-lactalbumin (Z_monomer  = -4.63 ± 0.05). Amide hydrogen/deuterium exchange and circular dichroism spectroscopy demonstrated that crosslinking did not significantly alter the structure of either protein or result in direct binding (thus mimicking crowding). Ultimately, capillary electrophoretic analysis of the dimeric charge ladder detected a change in charge of ΔZ = -0.04 ± 0.09 upon crowding by this pair (Z_dimer  = -5.10 ± 0.07). These small values of ΔZ are not necessarily general to protein crowding (qualitatively or quantitatively) but will vary per protein size, charge, and solvent conditions.

In-Cell Double Electron-Electron Resonance at Nanomolar Protein Concentrations

Electron paramagnetic resonance (EPR) spectroscopy is an established technique to site-specifically monitor conformational changes of spin-labeled biomolecules. Emerging in-cell EPR approaches aiming to address spin-labeled proteins in their native environment still struggle to reach a broad applicability and to target physiologically relevant protein concentrations. Here, we present a comparative in vitro and in-cell double electron-electron resonance (DEER) study demonstrating that nanomolar protein concentrations are at reach to measure distances up to 4.5 nm between protein sites carrying commercial gadolinium spin labels.

Violacein-Induced Chaperone System Collapse Underlies Multistage Antiplasmodial Activity

Antimalarial drugs with novel modes of action and wide therapeutic potential are needed to pave the way for malaria eradication. Violacein is a natural compound known for its biological activity against cancer cells and several pathogens, including the malaria parasite, Plasmodium falciparum (Pf). Herein, using chemical genomic profiling (CGP), we found that violacein affects protein homeostasis. Mechanistically, violacein binds Pf chaperones, PfHsp90 and PfHsp70-1, compromising the latter's ATPase and chaperone activities. Additionally, violacein-treated parasites exhibited increased protein unfolding and proteasomal degradation. The uncoupling of the parasite stress response reflects the multistage growth inhibitory effect promoted by violacein. Despite evidence of proteotoxic stress, violacein did not inhibit global protein synthesis via UPR activation-a process that is highly dependent on chaperones, in agreement with the notion of a violacein-induced proteostasis collapse. Our data highlight the importance of a functioning chaperone-proteasome system for parasite development and differentiation. Thus, a violacein-like small molecule might provide a good scaffold for development of a novel probe for examining the molecular chaperone network and/or antiplasmodial drug design.

Optical plasticity of mammalian cells

Transparency is widespread in nature, ranging from transparent insect wings to ocular tissues that enable you to read this text, and transparent marine vertebrates. And yet, cells and tissue models in biology are usually strongly light scattering and optically opaque, precluding deep optical microscopy. Here we describe the directed evolution of cultured mammalian cells toward increased transparency. We find that mutations greatly diversify the optical phenotype of Chinese Hamster Ovary cells, a cultured mammalian cell line. Furthermore, only three rounds of high-throughput optical selection and competitive growth are required to yield fit cells with greatly improved transparency. Based on 15 monoclonal cell lines derived from this directed evolution experiment, we find that the evolved transparency frequently goes along with a reduction of nuclear granularity and physiological shifts in gene expression profiles. In the future this optical plasticity of mammalian cells may facilitate genetic clearance of living tissues for in vivo microscopy.

RNA-seeded membraneless bodies: Role of tandemly repeated RNA

Membraneless organelles (bodies, granules, etc.) are spatially distinct sub-nuclear and cytoplasmic foci involved in all the processes in a living cell, such as development, cell death, carcinogenesis, proliferation, and differentiation. Today the list of the membraneless organelles includes a wide spectrum of intranuclear and cytoplasmic bodies. Proteins with intrinsically disordered regions are the key players in the membraneless body assembly. However, recent data assume an important role of RNA molecules in the process of the liquid-liquid phase separation. High-level expression of RNA above a critical concentration threshold is mandatory to nucleate interactions with specific proteins and for seeding membraneless organelles. RNA components are considered by many authors as the principal determinants of organelle identity. Tandemly repeated (TR) DNA of big satellites (a TR family that includes centromeric and pericentromeric DNA sequences) was believed to be transcriptionally silent for a long period. Now we know about the TR transcription upregulation during gameto- and embryogenesis, carcinogenesis, stress response. In the review, we summarize the recent data about the involvement of TR RNA in the formation of nuclear membraneless granules, bodies, etc., with different functions being in some cases an initiator of the structures assembly. These RNP structures sequestrate and inactivate different proteins and transcripts. The TR induced sequestration is one of the key principles of nuclear architecture and genome functioning. Studying the role of the TR-based membraneless organelles in stress and disease will bring some new ideas for translational medicine.

In situ Electron Microscopy of Complex Biological and Nanoscale Systems: Challenges and Opportunities

In situ imaging for direct visualization is important for physical and biological sciences. Research endeavors into elucidating dynamic biological and nanoscale phenomena frequently necessitate in situ and time-resolved imaging. In situ liquid cell electron microscopy (LC-EM) can overcome certain limitations of conventional electron microscopies and offer great promise. This review aims to examine the status-quo and practical challenges of in situ LC-EM and its applications, and to offer insights into a novel correlative technique termed microfluidic liquid cell electron microscopy. We conclude by suggesting a few research ideas adopting microfluidic LC-EM for in situ imaging of biological and nanoscale systems.

Enhancing intracellular accumulation and target engagement of PROTACs with reversible covalent chemistry

Current efforts in the proteolysis targeting chimera (PROTAC) field mostly focus on choosing an appropriate E3 ligase for the target protein, improving the binding affinities towards the target protein and the E3 ligase, and optimizing the PROTAC linker. However, due to the large molecular weights of PROTACs, their cellular uptake remains an issue. Through comparing how different warhead chemistry, reversible noncovalent (RNC), reversible covalent (RC), and irreversible covalent (IRC) binders, affects the degradation of Bruton's Tyrosine Kinase (BTK), we serendipitously discover that cyano-acrylamide-based reversible covalent chemistry can significantly enhance the intracellular accumulation and target engagement of PROTACs and develop RC-1 as a reversible covalent BTK PROTAC with a high target occupancy as its corresponding kinase inhibitor and effectiveness as a dual functional inhibitor and degrader, a different mechanism-of-action for PROTACs. Importantly, this reversible covalent strategy is generalizable to improve other PROTACs, opening a path to enhance PROTAC efficacy.

Survival of the cheapest: how proteome cost minimization drives evolution

Darwin's theory of evolution emphasized that positive selection of functional proficiency provides the fitness that ultimately determines the structure of life, a view that has dominated biochemical thinking of enzymes as perfectly optimized for their specific functions. The 20th-century modern synthesis, structural biology, and the central dogma explained the machinery of evolution, and nearly neutral theory explained how selection competes with random fixation dynamics that produce molecular clocks essential e.g. for dating evolutionary histories. However, quantitative proteomics revealed that selection pressures not relating to optimal function play much larger roles than previously thought, acting perhaps most importantly via protein expression levels. This paper first summarizes recent progress in the 21st century toward recovering this universal selection pressure. Then, the paper argues that proteome cost minimization is the dominant, underlying 'non-function' selection pressure controlling most of the evolution of already functionally adapted living systems. A theory of proteome cost minimization is described and argued to have consequences for understanding evolutionary trade-offs, aging, cancer, and neurodegenerative protein-misfolding diseases.

Mass spectrometry-based methods for structural biology on a proteome-wide scale

Mass spectrometry (MS) has long been used to study proteins mainly via sequence identification and quantitation of expression abundance. In recent years, MS has emerged as a tool for structural biology. Intact protein structural analysis has been enabled by the development of methods such as native MS, top-down proteomics, and ion mobility MS. Other MS-based structural methods include affinity purification MS, chemical cross-linking, and protein footprinting. These methods have enabled the study of protein–protein and protein–ligand interactions and regions of conformational change. The coupling of MS with liquid chromatography has permitted the analysis of complex samples. This bottom-up proteomics workflow enables the study of protein structure in the native cellular environment and provides structural information across the proteome. It has been demonstrated that the crowded environment of the cell affects protein binding interactions and affinities. Performing studies in this complex environment is essential for understanding the functional roles of proteins. MS-based structural methods permit analysis of samples such as cell lysates, intact cells, and tissue to provide a more physiological view of protein structure. This mini-review discusses the various MS-based methods that can be used for proteome-wide structural studies and highlights some of their application.

Spatial Lymphocyte Dynamics in Lymph Nodes Predicts the Cytotoxic T Cell Frequency Needed for HIV Infection Control

The surveillance of host body tissues by immune cells is central for mediating their defense function. In vivo imaging technologies have been used to quantitatively characterize target cell scanning and migration of lymphocytes within lymph nodes (LNs). The translation of these quantitative insights into a predictive understanding of immune system functioning in response to various perturbations critically depends on computational tools linking the individual immune cell properties with the emergent behavior of the immune system. By choosing the Newtonian second law for the governing equations, we developed a broadly applicable mathematical model linking individual and coordinated T-cell behaviors. The spatial cell dynamics is described by a superposition of autonomous locomotion, intercellular interaction, and viscous damping processes. The model is calibrated using in vivo data on T-cell motility metrics in LNs such as the translational speeds, turning angle speeds, and meandering indices. The model is applied to predict the impact of T-cell motility on protection against HIV infection, i.e., to estimate the threshold frequency of HIV-specific cytotoxic T cells (CTLs) that is required to detect productively infected cells before the release of viral particles starts. With this, it provides guidance for HIV vaccine studies allowing for the migration of cells in fibrotic LNs.

SERS Probing of Proteins in Gold Nanoparticle Agglomerates

The collection of surface-enhanced Raman scattering (SERS) spectra of proteins and other biomolecules in complex biological samples such as animal cells has been achieved with gold nanoparticles that are introduced to the sample. As a model for such a situation, SERS spectra were measured in protein solutions using gold nanoparticles in the absence of aggregating agents, allowing for the free formation of a protein corona. The SERS spectra indicate a varied interaction of the protein molecule with the gold nanoparticles, depending on protein concentration. The concentration-dependent optical properties of the formed agglomerates result in strong variation in SERS enhancement. At protein concentrations that correspond to those inside cells, SERS signals are found to be very low. The results suggest that in living cells the successful collection of SERS spectra must be due to the positioning of the aggregates rather than the crowded biomolecular environment inside the cells. Experiments with DNA suggest the suitability of the applied sample preparation approach for an improved understanding of SERS nanoprobes and nanoparticle-biomolecule interactions in general.

Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield

Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM) and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.

Anodically Grown Titania Nanotube Induced Cytotoxicity has Genotoxic Origins

Nanoarchitectures of titania (TiO₂) have been widely investigated for a number of medical applications including implants and drug delivery. Although titania is extensively used in the food, drug and cosmetic industries, biocompatibility of nanoscale titania is still under careful scrutiny due to the conflicting reports on its interaction with cellular matter. For an accurate insight, we performed in vitro studies on the response of human dermal fibroblast cells toward pristine titania nanotubes fabricated by anodic oxidation. The nanotubes at low concentrations were seen to induce toxicity to the cells, whereas at higher concentrations the cell vitality remained on par with controls. Further investigations revealed an increase in the G₀ phase cell population depicting that majority of cells were in the resting rather than active phase. Though the mitochondrial set-up did not exhibit any signs of stress, significantly enhanced reactive oxygen species production in the nuclear compartment was noted. The TiO₂ nanotubes were believed to have gained access to the nuclear machinery and caused increased stress leading to genotoxicity. This interesting property of the nanotubes could be utilized to kill cancer cells, especially if the nanotubes are functionalized for a specific target, thus eliminating the need for any chemotherapeutic agents.

A Theoretical Lower Bound for Selection on the Expression Levels of Proteins

We use simple models of the costs and benefits of microbial gene expression to show that changing a protein's expression away from its optimum by 2-fold should reduce fitness by at least [Formula: see text], where P is the fraction the cell's protein that the gene accounts for. As microbial genes are usually expressed at above 5 parts per million, and effective population sizes are likely to be above 10(6), this implies that 2-fold changes to gene expression levels are under strong selection, as [Formula: see text], where Ne is the effective population size and s is the selection coefficient. Thus, most gene duplications should be selected against. On the other hand, we predict that for most genes, small changes in the expression will be effectively neutral.

Proteomics Unveils Fibroblast-Cardiomyocyte Lactate Shuttle and Hexokinase Paradox in Mouse Muscles

Quantitative mapping, given in biochemically interpretable units such as mol per mg of total protein, of tissue-specific proteomes is prerequisite for the analysis of any process in cells. We applied label- and standard-free proteomics to characterize three types of striated muscles: white, red, and cardiac muscle. The analysis presented here uncovers several unexpected and novel features of striated muscles. In addition to differences in protein expression levels, the three muscle types substantially differ in their patterns of basic metabolic pathways and isoforms of regulatory proteins. Importantly, some of the conclusions drawn on the basis of our results, such as the potential existence of a "fibroblast-cardiomyocyte lactate shuttle" and the "hexokinase paradox" point to the necessity of reinterpretation of some basic aspects of striated muscle metabolism. The data presented here constitute a powerful database and a resource for future studies of muscle physiology and for the design of pharmaceutics for the treatment of muscular disorders.

In-depth quantitative analysis and comparison of the human hepatocyte and hepatoma cell line HepG2 proteomes

Hepatocytes play a pivotal role in human homeostasis. They are essential in regulation of glucose and lipid levels in blood and play a central role in metabolism of amino acids, lipids, drugs and xenobiotic-compounds. In addition, hepatocytes produce a major portion of proteins circulating in the blood. Hepatocytes were isolated from liver tissue obtained from surgical resections. Proteins were extracted and processed using filter aided sample preparation protocol and were analyzed by LC-MS/MS using high accuracy mass spectrometry. Proteins were quantified by the 'Total Protein Approach' and 'Proteomic Ruler'. We report a comprehensive proteomic analysis of purified human hepatocytes and the human hepatoma cell line HepG2. The complete dataset comprises 9400 proteins and provides a comprehensive and quantitative depiction of the proteomes of hepatocytes and HepG2 cells at the protein titer and copy number dimensions. We describe basic cell organization and in detail energy metabolism pathways and metabolite transport. We provide quantitative insights into protein synthesis and drug and xenobiotics catabolism. Our data delineate differences between the native human hepatocytes and HepG2 cells by providing for the first time quantitative data at protein concentrations and copy numbers.

Sequential metabolic phases as a means to optimize cellular output in a constant environment

Temporal changes of gene expression are a well-known regulatory feature of all cells, which is commonly perceived as a strategy to adapt the proteome to varying external conditions. However, temporal (rhythmic and non-rhythmic) changes of gene expression are also observed under virtually constant external conditions. Here we hypothesize that such changes are a means to render the synthesis of the metabolic output more efficient than under conditions of constant gene activities. In order to substantiate this hypothesis, we used a flux-balance model of the cellular metabolism. The total time span spent on the production of a given set of target metabolites was split into a series of shorter time intervals (metabolic phases) during which only selected groups of metabolic genes are active. The related flux distributions were calculated under the constraint that genes can be either active or inactive whereby the amount of protein related to an active gene is only controlled by the number of active genes: the lower the number of active genes the more protein can be allocated to the enzymes carrying non-zero fluxes. This concept of a predominantly protein-limited efficiency of gene expression clearly differs from other concepts resting on the assumption of an optimal gene regulation capable of allocating to all enzymes and transporters just that fraction of protein necessary to prevent rate limitation. Applying this concept to a simplified metabolic network of the central carbon metabolism with glucose or lactate as alternative substrates, we demonstrate that switching between optimally chosen stationary flux modes comprising different sets of active genes allows producing a demanded amount of target metabolites in a significantly shorter time than by a single optimal flux mode at fixed gene activities. Our model-based findings suggest that temporal expression of metabolic genes can be advantageous even under conditions of constant external substrate supply.

Absolute quantitative profiling of the key metabolic pathways in slow and fast skeletal muscle

Slow and fast skeletal muscles are composed of, respectively, mainly oxidative and glycolytic muscle fibers, which are the basic cellular motor units of the motility apparatus. They largely differ in excitability, contraction mechanism, and metabolism. Because of their pivotal role in body motion and homeostasis, the skeletal muscles have been extensively studied using biochemical and molecular biology approaches. Here we describe a simple analytical and computational approach to estimate titers of enzymes of basic metabolic pathways and proteins of the contractile machinery in the skeletal muscles. Proteomic analysis of mouse slow and fast muscles allowed estimation of the titers of enzymes involved in the carbohydrate, lipid, and energy metabolism. Notably, we observed that differences observed between the two muscle types occur simultaneously for all proteins involved in a specific process such as glycolysis, free fatty acid catabolism, Krebs cycle, or oxidative phosphorylation. These differences are in a good agreement with the well-established biochemical picture of the muscle types. We show a correlation between maximal activity and the enzyme titer, suggesting that change in enzyme concentration is a good proxy for its catalytic potential in vivo. As a consequence, proteomic profiling of enzyme titers can be used to monitor metabolic changes in cells. Additionally, quantitative data of structural proteins allowed studying muscle type specific cell architecture and its remodeling. The presented proteomic approach can be applied to study metabolism in any other tissue or cell line.

A "proteomic ruler" for protein copy number and concentration estimation without spike-in standards

Absolute protein quantification using mass spectrometry (MS)-based proteomics delivers protein concentrations or copy numbers per cell. Existing methodologies typically require a combination of isotope-labeled spike-in references, cell counting, and protein concentration measurements. Here we present a novel method that delivers similar quantitative results directly from deep eukaryotic proteome datasets without any additional experimental steps. We show that the MS signal of histones can be used as a "proteomic ruler" because it is proportional to the amount of DNA in the sample, which in turn depends on the number of cells. As a result, our proteomic ruler approach adds an absolute scale to the MS readout and allows estimation of the copy numbers of individual proteins per cell. We compare our protein quantifications with values derived via the use of stable isotope labeling by amino acids in cell culture and protein epitope signature tags in a method that combines spike-in protein fragment standards with precise isotope label quantification. The proteomic ruler approach yields quantitative readouts that are in remarkably good agreement with results from the precision method. We attribute this surprising result to the fact that the proteomic ruler approach omits error-prone steps such as cell counting or protein concentration measurements. The proteomic ruler approach is readily applicable to any deep eukaryotic proteome dataset-even in retrospective analysis-and we demonstrate its usefulness with a series of mouse organ proteomes.

Why to compare absolute numbers of mitochondria

Prompted by pronounced structural differences between rat liver and rat hepatocellular carcinoma mitochondria, we suspected these mitochondrial populations to differ massively in their molecular composition. Aiming to reveal these mitochondrial differences, we came across the issue on how to normalize such comparisons and decided to focus on the absolute number of mitochondria. To this end, fluorescently stained mitochondria were quantified by flow cytometry. For rat liver mitochondria, this approach resulted in mitochondrial protein contents comparable to earlier reports using alternative methods. We determined similar protein contents for rat liver, heart and kidney mitochondria. In contrast, however, lower protein contents were determined for rat brain mitochondria and for mitochondria from the rat hepatocellular carcinoma cell line McA 7777. This result challenges mitochondrial comparisons that rely on equal protein amounts as a typical normalization method. Exemplarily, we therefore compared the activity and susceptibility toward inhibition of complex II of rat liver and hepatocellular carcinoma mitochondria and obtained significant discrepancies by either normalizing to protein amount or to absolute mitochondrial number. Importantly, the latter normalization, in contrast to the former, demonstrated a lower complex II activity and higher susceptibility toward inhibition in hepatocellular carcinoma mitochondria compared to liver mitochondria. These findings demonstrate that solely normalizing to protein amount may obscure essential molecular differences between mitochondrial populations.

Steric contribution of macromolecular crowding to the time and activation energy for preprotein translocation across the endoplasmic reticulum membrane

Protein translocation from the cytosol to the endoplasmic reticulum (ER) or vice versa, an essential process for cell function, includes the transport of preproteins destined to become secretory, luminal, or integral membrane proteins (translocation) or misfolded proteins returned to the cytoplasm to be degraded (retrotranslocation). An important aspect in this process that has not been fully studied is the molecular crowding at both sides of the ER membrane. By using models of polymers crossing a membrane through a pore, in an environment crowded by either static or dynamic spherical agents, we computed the following transport properties: the free energy, the activation energy, the force, and the transport times for translocation and retrotranslocation. Using experimental protein crowding data for the cytoplasm and ER sides, we showed that dynamic crowding, which resembles biological environments where proteins are translocated or retrotranslocated, increases markedly all the physical properties of translocation and retrotranslocation as compared with translocation in a diluted system. By contrast, transport properties in static crowded systems were similar to those in diluted conditions. In the dynamic regime, the effects of crowding were more notorious in the transport times, leading to a huge difference for large chains. We indicate that this difference is the result of the synergy between the free energy and the diffusivity of the translocating chain. That synergy leads to translocation rates similar to experimental measures in diluted systems, which indicates that the effects of crowding can be measured. Our data also indicate that effects of crowding cannot be neglected when studying translocation because protein dynamic crowding has a relevant steric contribution, which changes the properties of translocation.

An agent-based model of cellular dynamics and circadian variability in human endotoxemia

As cellular variability and circadian rhythmicity play critical roles in immune and inflammatory responses, we present in this study an agent-based model of human endotoxemia to examine the interplay between circadian controls, cellular variability and stochastic dynamics of inflammatory cytokines. The model is qualitatively validated by its ability to reproduce circadian dynamics of inflammatory mediators and critical inflammatory responses after endotoxin administration in vivo. Novel computational concepts are proposed to characterize the cellular variability and synchronization of inflammatory cytokines in a population of heterogeneous leukocytes. Our results suggest that there is a decrease in cell-to-cell variability of inflammatory cytokines while their synchronization is increased after endotoxin challenge. Model parameters that are responsible for IκB production stimulated by NFκB activation and for the production of anti-inflammatory cytokines have large impacts on system behaviors. Additionally, examining time-dependent systemic responses revealed that the system is least vulnerable to endotoxin in the early morning and most vulnerable around midnight. Although much remains to be explored, proposed computational concepts and the model we have pioneered will provide important insights for future investigations and extensions, especially for single-cell studies to discover how cellular variability contributes to clinical implications.

The Langevin Hull: Constant pressure and temperature dynamics for non-periodic systems

We have developed a new isobaric-isothermal (NPT) algorithm which applies an external pressure to the facets comprising the convex hull surrounding the system. A Langevin thermostat is also applied to the facets to mimic contact with an external heat bath. This new method, the "Langevin Hull", can handle heterogeneous mixtures of materials with different compressibilities. These systems are problematic for traditional affine transform methods. The Langevin Hull does not suffer from the edge effects of boundary potential methods, and allows realistic treatment of both external pressure and thermal conductivity due to the presence of an implicit solvent. We apply this method to several different systems including bare metal nanoparticles, nanoparticles in an explicit solvent, as well as clusters of liquid water. The predicted mechanical properties of these systems are in good agreement with experimental data and previous simulation work.

The principle of sufficiency and the evolution of control: using control analysis to understand the design principles of biological systems

Control analysis can be used to try to understand why (quantitatively) systems are the way that they are, from rate constants within proteins to the relative amount of different tissues in organisms. Many biological parameters appear to be optimized to maximize rates under the constraint of minimizing space utilization. For any biological process with multiple steps that compete for control in series, evolution by natural selection will tend to even out the control exerted by each step. This is for two reasons: (i) shared control maximizes the flux for minimum protein concentration, and (ii) the selection pressure on any step is proportional to its control, and selection will, by increasing the rate of a step (relative to other steps), decrease its control over a pathway. The control coefficient of a parameter P over fitness can be defined as (∂N/N)/(∂P/P), where N is the number of individuals in the population, and ∂N is the change in that number as a result of the change in P. This control coefficient is equal to the selection pressure on P. I argue that biological systems optimized by natural selection will conform to a principle of sufficiency, such that the control coefficient of all parameters over fitness is 0. Thus in an optimized system small changes in parameters will have a negligible effect on fitness. This principle naturally leads to (and is supported by) the dominance of wild-type alleles over null mutants.

Design and analysis of synthetic carbon fixation pathways

Carbon fixation is the process by which CO(2) is incorporated into organic compounds. In modern agriculture in which water, light, and nutrients can be abundant, carbon fixation could become a significant growth-limiting factor. Hence, increasing the fixation rate is of major importance in the road toward sustainability in food and energy production. There have been recent attempts to improve the rate and specificity of Rubisco, the carboxylating enzyme operating in the Calvin-Benson cycle; however, they have achieved only limited success. Nature employs several alternative carbon fixation pathways, which prompted us to ask whether more efficient novel synthetic cycles could be devised. Using the entire repertoire of approximately 5,000 metabolic enzymes known to occur in nature, we computationally identified alternative carbon fixation pathways that combine existing metabolic building blocks from various organisms. We compared the natural and synthetic pathways based on physicochemical criteria that include kinetics, energetics, and topology. Our study suggests that some of the proposed synthetic pathways could have significant quantitative advantages over their natural counterparts, such as the overall kinetic rate. One such cycle, which is predicted to be two to three times faster than the Calvin-Benson cycle, employs the most effective carboxylating enzyme, phosphoenolpyruvate carboxylase, using the core of the naturally evolved C4 cycle. Although implementing such alternative cycles presents daunting challenges related to expression levels, activity, stability, localization, and regulation, we believe our findings suggest exciting avenues of exploration in the grand challenge of enhancing food and renewable fuel production via metabolic engineering and synthetic biology.