Role of Proteome Physical Chemistry in Cell Behavior

A Divalent Metal Cation-Metabolite Interaction Model Reveals Cation Buffering and Speciation

I present the perspective that the divalent metalome and the metabolome can be modeled as a network of chelating interactions instead of separate entities. I review progress in understanding the complex cellular environment, in particular recent contributions to modeling metabolite-Mg2+ interactions. I then demonstrate a simple extension of these strategies based approximately on intracellular Escherichia coli concentrations. This model is composed of four divalent metal cations with a range of cellular concentrations and physical properties (Mg2+, Ca2+, Mn2+, and Zn2+), eight representative metabolites, and interaction constants. I applied this model to predict the speciation of divalent metal cations between free and metabolite-chelated species. This approach reveals potentially beneficial properties, including maintenance of free divalent metal cations at biologically relevant concentrations, buffering of free divalent metal cations, and enrichment of functional metabolite-chelated species. While currently limited by available interaction coefficients, this modeling strategy can be generalized to more complex systems. In summary, biochemists should consider the potential of cellular metabolites to form chelating interactions with divalent metal cations.

Energetic cost of biosynthesis is a missing link between growth and longevity in mammals

The comparative studies of aging have established a negative correlation between Gompertz postnatal growth constant and maximum lifespan across mammalian species, but the underlying physiological mechanism remains unclear. This study shows that the Gompertz growth constant can be decomposed into two energetic components, mass-specific metabolic rate and the energetic cost of biosynthesis, and that after controlling the former as a confounder, the negative correlation between growth constant and lifespan still exists due to a 100-fold variation in the latter, revealing that the energetic cost of biosynthesis is a link between growth and longevity in mammals. Previously, the energetic cost of biosynthesis has been thought to be a constant across species and therefore was not considered a contributor to the variation in any life history traits, such as growth and lifespan. This study employs a recently proposed model based on energy conservation to explain the physiological effect of the variation in this energetic cost on the aging process and illustrates its role in linking growth and lifespan. The conventional life history theory suggested a tradeoff between growth and somatic maintenance, but the findings in this study suggest that allocating more energy to biosynthesis may enhance the somatic maintenance and extend lifespan and, hence, reveal a more complex nature of the tradeoff.

Two-state swimming: Strategy and survival of a model bacterial predator in response to environmental cues

Bdellovibrio bacteriovorus is a predatory bacterium preying upon Gram-negative bacteria. As such, B. bacteriovorus has the potential to control antibiotic-resistant pathogens and biofilm populations. To survive and reproduce, B. bacteriovorus must locate and infect a host cell. However, in the temporary absence of prey, it is largely unknown how B. bacteriovorus modulate their motility patterns in response to physical or chemical environmental cues to optimize their energy expenditure. To investigate B. bacteriovorus' predation strategy, we track and quantify their motion by measuring speed distributions as a function of starvation time. While an initial unimodal speed distribution relaxing to one for pure diffusion at long times may be expected, instead we observe a bimodal speed distribution with one mode centered around that expected from diffusion and the other centered at higher speeds. What is more, for an increasing amount of time over which B. bacteriovorus is starved, we observe a progressive reweighting from the active swimming state to an apparent diffusive state in the speed distribution. Distributions of trajectory-averaged speeds for B. bacteriovorus are largely unimodal, indicating switching between a faster swim speed and an apparent diffusive state within individual observed trajectories rather than there being distinct active swimming and apparent diffusive populations. We also find that B. bacteriovorus' apparent diffusive state is not merely caused by the diffusion of inviable bacteria as subsequent spiking experiments show that bacteria can be resuscitated and bimodality restored. Indeed, starved B. bacteriovorus may modulate the frequency and duration of active swimming as a means of balancing energy consumption and procurement. Our results thus point to a reweighting of the swimming frequency on a trajectory basis rather than a population level basis.

Mapping the multimodal connectome: On the architects of brain network science

Delineating the human brain network and analyzing its architecture is one of the major goals of modern neuroscience. Here, we commemorate a 2008 landmark structural connectome study in PLOS Biology and gauge how it shaped the field of brain network science.

Effects of Protein Crowders and Charge on the Folding of Superoxide Dismutase 1 Variants: A Computational Study

The neurodegenerative disease amyotrophic lateral sclerosis (ALS) is associated with the misfolding and aggregation of the metalloenzyme protein superoxide dismutase 1 (SOD1) via mutations that destabilize the monomer-dimer interface. In a cellular environment, crowding and electrostatic screening play essential roles in the folding and aggregation of the SOD1 monomers. Despite numerous studies on the effects of mutations on SOD1 folding, a clear understanding of the interplay between crowding, folding, and aggregation in vivo remains lacking. Using a structure-based minimal model for molecular dynamics simulations, we investigate the role of self-crowding and charge on the folding stability of SOD1 and the G41D mutant where experimentalists were intrigued by an alteration of the folding mechanism by a single point mutation from glycine to charged aspartic acid. We show that unfolded SOD1 configurations are significantly affected by charge and crowding, a finding that would be extremely costly to achieve with all-atom simulations, while the native state is not significantly altered. The mutation at residue 41 alters the interactions between proteins in the unfolded states instead of those within a protein. This paper suggests electrostatics may play an important role in the folding pathway of SOD1 and modifying the charge via mutation and ion concentration may change the dominant interactions between proteins, with potential impacts for aggregation of the mutants. This work provides a plausible reason for the alteration of the unfolded states to address why the mutant G41D causes the changes to the folding mechanism of SOD1 that have intrigued experimentalists.

Rules of Physical Mathematics Govern Intrinsically Disordered Proteins

In stark contrast to foldable proteins with a unique folded state, intrinsically disordered proteins and regions (IDPs) persist in perpetually disordered ensembles. Yet an IDP ensemble has conformational features-even when averaged-that are specific to its sequence. In fact, subtle changes in an IDP sequence can modulate its conformational features and its function. Recent advances in theoretical physics reveal a set of elegant mathematical expressions that describe the intricate relationships among IDP sequences, their ensemble conformations, and the regulation of their biological functions. These equations also describe the molecular properties of IDP sequences that predict similarities and dissimilarities in their functions and facilitate classification of sequences by function, an unmet challenge to traditional bioinformatics. These physical sequence-patterning metrics offer a promising new avenue for advancing synthetic biology at a time when multiple novel functional modes mediated by IDPs are emerging.

A thermodynamic atlas of proteomes reveals energetic innovation across the tree of life

Protein stability is a fundamental molecular property enabling organisms to adapt to their biological niches. How this is facilitated and whether there are kingdom specific or more general universal strategies is not known. A principal obstacle to addressing this issue is that the vast majority of proteins lack annotation, specifically thermodynamic annotation, beyond the amino acid and chromosome information derived from genome sequencing. To address this gap and facilitate future investigation into large-scale patterns of protein stability and dynamics within and between organisms, we applied a unique ensemble-based thermodynamic characterization of protein folds to a substantial portion of extant sequenced genomes. Using this approach, we compiled a database resource focused on the position-specific variation in protein stability. Interrogation of the database reveals; 1) domains of life exhibit distinguishing thermodynamic features, with eukaryotes particularly different from both archaea and bacteria, 2) the optimal growth temperature of an organism is proportional to the average apolar enthalpy of its proteome, 3) intrinsic disorder content is also proportional to the apolar enthalpy (but unexpectedly not the predicted stability at 25 °C), and 4) secondary structure and global stability information of individual proteins is extractable. We hypothesize that wider access to residue-specific thermodynamic information of proteomes will result in deeper understanding of mechanisms driving functional adaptation and protein evolution. Our database is free for download at https://afc-science.github.io/thermo-env-atlas/.

Protein dynamics implications of the low- and high-temperature denaturation of myoglobin

We reinvestigate a simple model used in the literature concerning the thermodynamic analysis of protein cold denaturation. We derive an exact thermodynamic expression for cold denaturation and give a better approximation than exists in the literature for predicting cold denaturation temperatures in the two-state model. We discuss the "dark-side" implications of this work for previous temperature-dependent protein dynamics experiments and discuss microfluidic experimental technologies, which could explore the thermal stability range of proteins below the bulk freezing point of water.

Thermal Analysis of a Mixture of Ribosomal Proteins by vT-ESI-MS: Toward a Parallel Approach for Characterizing the Stabilitome

The thermal stabilities of endogenous, intact proteins and protein assemblies in complex mixtures were characterized in parallel by means of variable-temperature electrospray ionization coupled to mass spectrometry (vT-ESI-MS). The method is demonstrated by directly measuring the melting transitions of seven proteins from a mixture of proteins derived from ribosomes. A proof-of-concept measurement of a fraction of an Escherichia coli lysate is provided to extend this approach to characterize the thermal stability of a proteome. As the solution temperature is increased, proteins and protein complexes undergo structural and organizational transitions; for each species, the folded ↔ unfolded and assembled ↔ disassembled populations are monitored based on changes in vT-ESI-MS charge state distributions and masses. The robustness of the approach illustrates a step toward the proteome-wide characterization of thermal stabilities and structural transitions-the stabilitome.

Encapsulation of ribozymes inside model protocells leads to faster evolutionary adaptation

Functional biomolecules, such as RNA, encapsulated inside a protocellular membrane are believed to have comprised a very early, critical stage in the evolution of life, since membrane vesicles allow selective permeability and create a unit of selection enabling cooperative phenotypes. The biophysical environment inside a protocell would differ fundamentally from bulk solution due to the microscopic confinement. However, the effect of the encapsulated environment on ribozyme evolution has not been previously studied experimentally. Here, we examine the effect of encapsulation inside model protocells on the self-aminoacylation activity of tens of thousands of RNA sequences using a high-throughput sequencing assay. We find that encapsulation of these ribozymes generally increases their activity, giving encapsulated sequences an advantage over nonencapsulated sequences in an amphiphile-rich environment. In addition, highly active ribozymes benefit disproportionately more from encapsulation. The asymmetry in fitness gain broadens the distribution of fitness in the system. Consistent with Fisher's fundamental theorem of natural selection, encapsulation therefore leads to faster adaptation when the RNAs are encapsulated inside a protocell during in vitro selection. Thus, protocells would not only provide a compartmentalization function but also promote activity and evolutionary adaptation during the origin of life.

Kramers’ Theory and the Dependence of Enzyme Dynamics on Trehalose-Mediated Viscosity

The disaccharide trehalose is accumulated in the cytoplasm of some organisms in response to harsh environmental conditions. Trehalose biosynthesis and accumulation are important for the survival of such organisms by protecting the structure and function of proteins and membranes. Trehalose affects the dynamics of proteins and water molecules in the bulk and the protein hydration shell. Enzyme catalysis and other processes dependent on protein dynamics are affected by the viscosity generated by trehalose, as described by the Kramers’ theory of rate reactions. Enzyme/protein stabilization by trehalose against thermal inactivation/unfolding is also explained by the viscosity mediated hindering of the thermally generated structural dynamics, as described by Kramers’ theory. The analysis of the relationship of viscosity–protein dynamics, and its effects on enzyme/protein function and other processes (thermal inactivation and unfolding/folding), is the focus of the present work regarding the disaccharide trehalose as the viscosity generating solute. Finally, trehalose is widely used (alone or in combination with other compounds) in the stabilization of enzymes in the laboratory and in biotechnological applications; hence, considering the effect of viscosity on catalysis and stability of enzymes may help to improve the results of trehalose in its diverse uses/applications.

How Do Cells Adapt? Stories Told in Landscapes

Cells adapt to changing environments. Perturb a cell and it returns to a point of homeostasis. Perturb a population and it evolves toward a fitness peak. We review quantitative models of the forces of adaptation and their visualizations on landscapes. While some adaptations result from single mutations or few-gene effects, others are more cooperative, more delocalized in the genome, and more universal and physical. For example, homeostasis and evolution depend on protein folding and aggregation, energy and protein production, protein diffusion, molecular motor speeds and efficiencies, and protein expression levels. Models provide a way to learn about the fitness of cells and cell populations by making and testing hypotheses.

Adaptations of Escherichia coli strains to oxidative stress are reflected in properties of their structural proteomes

BACKGROUND

The reconstruction of metabolic networks and the three-dimensional coverage of protein structures have reached the genome-scale in the widely studied Escherichia coli K-12 MG1655 strain. The combination of the two leads to the formation of a structural systems biology framework, which we have used to analyze differences between the reactive oxygen species (ROS) sensitivity of the proteomes of sequenced strains of E. coli. As proteins are one of the main targets of oxidative damage, understanding how the genetic changes of different strains of a species relates to its oxidative environment can reveal hypotheses as to why these variations arise and suggest directions of future experimental work.

RESULTS

Creating a reference structural proteome for E. coli allows us to comprehensively map genetic changes in 1764 different strains to their locations on 4118 3D protein structures. We use metabolic modeling to predict basal ROS production levels (ROStype) for 695 of these strains, finding that strains with both higher and lower basal levels tend to enrich their proteomes with antioxidative properties, and speculate as to why that is. We computationally assess a strain's sensitivity to an oxidative environment, based on known chemical mechanisms of oxidative damage to protein groups, defined by their localization and functionality. Two general groups - metalloproteins and periplasmic proteins - show enrichment of their antioxidative properties between the 695 strains with a predicted ROStype as well as 116 strains with an assigned pathotype. Specifically, proteins that a) utilize a molybdenum ion as a cofactor and b) are involved in the biogenesis of fimbriae show intriguing protective properties to resist oxidative damage. Overall, these findings indicate that a strain's sensitivity to oxidative damage can be elucidated from the structural proteome, though future experimental work is needed to validate our model assumptions and findings.

CONCLUSION

We thus demonstrate that structural systems biology enables a proteome-wide, computational assessment of changes to atomic-level physicochemical properties and of oxidative damage mechanisms for multiple strains in a species. This integrative approach opens new avenues to study adaptation to a particular environment based on physiological properties predicted from sequence alone.

Structural disorder originates beyond narrow stoichiometric margins of amino acids in naturally occurring folded proteins

Rigorous analyses of Euclidean distances between non-peptide bonded residues in structures of several thousand naturally occurring folded proteins yielded a surprising "margin of life" for percentage occurrence of individual amino acids in naturally occurring folded proteins. On one hand, the concept of "margin of life", referring to lower than expected variances in average stoichiometric occurrences of individual amino acids in folded proteins, remains unchallenged since its discovery a decade ago. On the other hand, within this past decade there has been a strong emergence of a gradual paradigm shift in biology, from sequence-structure-function in proteins to sequence-disorder-function, fuelled by discoveries on functional implications of intrinsically disordered proteins (primary sequences that do not form stable structures). Thus the applicability of "margin of life" to peptide-bonded residues in all known natural proteins, adopting stable structures vis-à-vis intrinsically disordered needs to be explored. Therefore in this work, we analyze compositions of the complete naturally occurring primary sequence space (over 560000 sequences) after dividing it into mutually exclusive subsets of structured and intrinsically disordered proteins along with a subset without any structural information. While finding that occurrence of different peptides (up to pentapeptides) is a direct consequence of the relative occurrences of their constituting residues in folded proteins, we report that structural disorder in natural proteins originates beyond the narrow stoichiometric margins of amino acids found in structured proteins.Communicated by Ramaswamy H. Sarma.

Modeling and Exploiting Microbial Temperature Response

Temperature is an important parameter in bioprocesses, influencing the structure and functionality of almost every biomolecule, as well as affecting metabolic reaction rates. In industrial biotechnology, the temperature is usually tightly controlled at an optimum value. Smart variation of the temperature to optimize the performance of a bioprocess brings about multiple complex and interconnected metabolic changes and is so far only rarely applied. Mathematical descriptions and models facilitate a reduction in complexity, as well as an understanding, of these interconnections. Starting in the 19th century with the “primal” temperature model of Svante Arrhenius, a variety of models have evolved over time to describe growth and enzymatic reaction rates as functions of temperature. Data-driven empirical approaches, as well as complex mechanistic models based on thermodynamic knowledge of biomolecular behavior at different temperatures, have been developed. Even though underlying biological mechanisms and mathematical models have been well-described, temperature as a control variable is only scarcely applied in bioprocess engineering, and as a conclusion, an exploitation strategy merging both in context has not yet been established. In this review, the most important models for physiological, biochemical, and physical properties governed by temperature are presented and discussed, along with application perspectives. As such, this review provides a toolset for future exploitation perspectives of temperature in bioprocess engineering.

Proteostasis collapse is a driver of cell aging and death

Cells and organisms grow old and die. We develop a biophysical model of the mechanism. Young cells are kept healthy by the positive processes of protein synthesis, degradation, and chaperoning (the activity of keeping proteins properly folded). But, with age, negative processes increase: Oxidative damage accumulates randomly in the cell’s proteins, healthy synthesis and degradation slow down, and—like overfilled garbage cans—chaperone capacity is exceeded. The chaperones are distracted trying to fold irreversibly damaged proteins, leading to accumulating misfolded and aggregated proteins in the cell. The tipping point to death happens when the negative overwhelms the positive. The model makes several quantitative predictions of the life span of the worm Caenorhabditis elegans.

What molecular processes drive cell aging and death? Here, we model how proteostasis—i.e., the folding, chaperoning, and maintenance of protein function—collapses with age from slowed translation and cumulative oxidative damage. Irreparably damaged proteins accumulate with age, increasingly distracting the chaperones from folding the healthy proteins the cell needs. The tipping point to death occurs when replenishing good proteins no longer keeps up with depletion from misfolding, aggregation, and damage. The model agrees with experiments in the worm Caenorhabditis elegans that show the following: Life span shortens nonlinearly with increased temperature or added oxidant concentration, and life span increases in mutants having more chaperones or proteasomes. It predicts observed increases in cellular oxidative damage with age and provides a mechanism for the Gompertz-like rise in mortality observed in humans and other organisms. Overall, the model shows how the instability of proteins sets the rate at which damage accumulates with age and upends a cell’s normal proteostasis balance.

Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins

We present an analytical theory to compute conformations of heteropolymers-applicable to describe disordered proteins-as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence-while maintaining the same charge composition-can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at a high-throughput level can provide valuable insights into the different mechanisms by which phosphorylation/charge mutation controls IDP function.

Modulating charge patterning and ionic strength as a strategy to induce conformational changes in intrinsically disordered proteins

We present an analytical theory to describe conformational changes as a function of salt for polymers with a given sequence of charges. We apply this model to describe Intrinsically Disordered Proteins (IDPs) by explicitly accounting for charged residues and their exact placement in the primary sequence while approximating the effect of non-electrostatic interactions at a mean-field level by effective short-range (two body and three-body) interaction parameters. The effect of ions is introduced by treating electrostatic interactions within Debye-Huckle approximation. Using typical values of the short-range mean-field parameters derived from all-atom Monte Carlo simulations (at zero salt), we predict the conformational changes as a function of salt concentration. We notice that conformational transitions in response to changes in ionic strength strongly depend on sequence specific charge patterning. For example, globule to coil transition can be observed upon increasing salt concentration, in stark contrast to uniformly charged polyelectrolyte theories based on net charge only. In addition, it is possible to observe non-monotonic behavior with salt as well. Drastic differences in salt-induced conformational transitions is also evident between two doubly phosphorylated sequences-derived from the same wild type sequence-that only differ in the site of phosphorylation. Similar effects are also predicted between two sequences derived from the same parent sequence differing by a single site mutation where a negative charge is replaced by a positive charge. These effects are purely a result of charge decoration and can only be understood in terms of metrics based on specific placement of charges, and cannot be explained by models based on charge composition alone. Identifying sequences and hot spots within sequences-for post translational modification or charge mutation-using our high-throughput theory will yield fundamental insights into design and biological regulation mediated by phosphorylation and/or local changes in salt concentration.

Protein evolution speed depends on its stability and abundance and on chaperone concentrations

Some biological evolution is slow (millions of years), and some is fast (months to years). The speed at which a protein evolves depends on how stable a protein’s folded structure is, how well it avoids aggregation, and how well-chaperoned it is. What are the mechanisms? We compute fitness landscapes by combining a model of protein-folding equilibria with sequence-change dynamics. We find that adapting to a new environment is fastest for proteins that are least stably folded, because those sit on steep downhill parts of fitness potentials. The modeling shows that cells should adapt to warmer environments faster than to colder ones, explains why increasing a protein’s abundance slows cell evolution, and explains how chaperones accelerate evolution by mitigating this effect.

Proteins evolve at different rates. What drives the speed of protein sequence changes? Two main factors are a protein’s folding stability and aggregation propensity. By combining the hydrophobic–polar (HP) model with the Zwanzig–Szabo–Bagchi rate theory, we find that: (i) Adaptation is strongly accelerated by selection pressure, explaining the broad variation from days to thousands of years over which organisms adapt to new environments. (ii) The proteins that adapt fastest are those that are not very stably folded, because their fitness landscapes are steepest. And because heating destabilizes folded proteins, we predict that cells should adapt faster when put into warmer rather than cooler environments. (iii) Increasing protein abundance slows down evolution (the substitution rate of the sequence) because a typical protein is not perfectly fit, so increasing its number of copies reduces the cell’s fitness. (iv) However, chaperones can mitigate this abundance effect and accelerate evolution (also called evolutionary capacitance) by effectively enhancing protein stability. This model explains key observations about protein evolution rates.