Transcriptional drift in aging cells: A global de-controller.

As cells age, they undergo a remarkable global change: In transcriptional drift, hundreds of genes become overexpressed while hundreds of others become underexpressed. Using archetype modeling and Gene Ontology analysis on data from aging Caenorhabditis elegans worms, we find that the upregulated genes code for sensory proteins upstream of stress responses and downregulated genes are growth- and metabolism-related. We propose a simple mechanistic model for how such global coordination of multi-protein expression levels may be achieved by the binding of a single ligand that concentrates with age. A key implication is that a cell's own responses are part of its aging process, so unlike for wear-and-tear processes, intervention might be able to modulate these effects.

Proteostasis is adaptive: Balancing chaperone holdases against foldases.

Because a cell must adapt to different stresses and growth rates, its proteostasis system must too. How do cells detect and adjust proteome folding to different conditions? Here, we explore a biophysical cost-benefit principle, namely that the cell should keep its proteome as folded as possible at the minimum possible energy cost. This can be achieved by differential expression of chaperones-balancing foldases (which accelerate folding) against holdases (which act as parking spots). The model captures changes in the foldase-holdase ratio observed both within organisms during aging and across organisms of varying metabolic rates. This work describes a simple biophysical mechanism by which cellular proteostasis adapts to meet the needs of a changing growth environment.

Proteostasis collapse is a driver of cell aging and death.

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.

How Do Chaperones Protect a Cell's Proteins from Oxidative Damage?

The accumulation of protein damage in aging organisms is thought to contribute to many aging-related diseases. Yet the properties determining which proteins are most susceptible remain poorly understood. Are certain conformations more vulnerable? Which chaperones are the main guardians? We address these questions with a system-wide model of E. coli proteostasis. By predicting how proteins with different folding properties respond to each chaperone's concentration, the model computes "damage fingerprints" that identify unfolded conformations as the major damage target. What matters most is not a protein's stability or difficulty of folding, but its dwell time in an unfolded state. The main guardian chaperone is DnaK because its client proteins spend more time unfolded than clients of GroEL, providing a mechanism for why the cell's capacity to handle stress is more sensitive to DnaK levels. Also, we find that chaperones are protectors, not recyclers. This model describes how cells resist stress and indicates that designing chaperone-targeting drugs may require whole-cell, system-wide modeling.

Why Do Fast-Growing Bacteria Enter Overflow Metabolism? Testing the Membrane Real Estate Hypothesis.

Bacteria and other cells show a puzzling behavior. At high growth rates, E. coli switch from respiration (which is ATP-efficient) to using fermentation for additional ATP (which is inefficient). This overflow metabolism results in a several-fold decrease in ATP produced per glucose molecule provided as food. By integrating diverse types of experimental data into a simple biophysical model, we give evidence that this onset is the result of the membrane real estate hypothesis: Fast growth drives cells to be bigger, reducing their surface-to-volume ratios. This decreases the membrane area available for respiratory proteins despite growing demand, causing increased crowding. Only when respiratory proteins reach their crowding limit does the cell activate fermentation, since fermentation allows faster ATP production per unit membrane area. Surface limitation thus creates a Pareto trade-off between membrane efficiency and ATP yield that links metabolic choice to the size and shape of a bacterial cell. By exploring the predictions that emerge from this trade-off, we show how consideration of molecular structures, energetics, rates, and equilibria can provide important insight into cellular behavior.

Role of Proteome Physical Chemistry in Cell Behavior.

We review how major cell behaviors, such as bacterial growth laws, are derived from the physical chemistry of the cell's proteins. On one hand, cell actions depend on the individual biological functionalities of their many genes and proteins. On the other hand, the common physics among proteins can be as important as the unique biology that distinguishes them. For example, bacterial growth rates depend strongly on temperature. This dependence can be explained by the folding stabilities across a cell's proteome. Such modeling explains how thermophilic and mesophilic organisms differ, and how oxidative damage of highly charged proteins can lead to unfolding and aggregation in aging cells. Cells have characteristic time scales. For example, E. coli can duplicate as fast as 2-3 times per hour. These time scales can be explained by protein dynamics (the rates of synthesis and degradation, folding, and diffusional transport). It rationalizes how bacterial growth is slowed down by added salt. In the same way that the behaviors of inanimate materials can be expressed in terms of the statistical distributions of atoms and molecules, some cell behaviors can be expressed in terms of distributions of protein properties, giving insights into the microscopic basis of growth laws in simple cells.

Highly Charged Proteins: The Achilles' Heel of Aging Proteomes.

As cells and organisms age, their proteins sustain increasing amounts of oxidative damage. It is estimated that half of all proteins are damaged in old organisms, yet the dominant mechanisms by which damage affects proteins and cellular phenotypes are not known. Here, we show that random modification of side chain charge induced by oxidative damage is likely to be a dominant source of protein stability loss in aging cells. Using an established model of protein electrostatics, we find that short, highly charged proteins are particularly susceptible to large destabilization from even a single side chain oxidation event. This mechanism identifies 20 proteins previously established to be important in aging that are at particularly high risk for oxidative destabilization, including transcription factors, histone and histone-modifying proteins, ribosomal and telomeric proteins, and proteins essential for homeostasis. Cellular processes enriched in high-risk proteins are shown to be particularly abundant in the aggregates of old organisms.

DNA Bending through Large Angles Is Aided by Ionic Screening.

We used adaptive umbrella sampling on a modified version of the roll angle to simulate the bending of DNA dodecamers. Simulations were carried out with the AMBER and CHARMM force fields for 10 sequences in which the central base pair step was varied. On long length scales, the DNA behavior was found to be consistent with the worm-like chain model. Persistence lengths calculated directly from the simulated structures and indirectly through the use of sequence-independent coarse-grained models based on simulation data were similar to literature values. On short length scales, the free energy cost of bending DNA was found to be consistent with the worm-like chain model for small and intermediate bending angles. At large angles, the bending free energy as a function of the roll angle became linear, suggesting a relative increase in flexibility at larger roll angles. Counterions congregated on the concave side of the highly bent DNA and screened the repulsion of the phosphate groups, facilitating the bending.

Protein unfolding under force: crack propagation in a network.

The mechanical unfolding of a set of 12 proteins with diverse topologies is investigated using an all-atom constraint-based model. Proteins are represented as polypeptides cross-linked by hydrogen bonds, salt bridges, and hydrophobic contacts, each modeled as a harmonic inequality constraint capable of supporting a finite load before breaking. Stereochemically acceptable unfolding pathways are generated by minimally overloading the network in an iterative fashion, analogous to crack propagation in solids. By comparing the pathways to those from molecular dynamics simulations and intermediates identified from experiment, it is demonstrated that the dominant unfolding pathways for 9 of the 12 proteins studied are well described by crack propagation in a network.

The long-wavelength limit of the structure factor of amorphous silicon and vitreous silica.

Liquids are in thermal equilibrium and have a non-zero structure factor S(Q --> 0) = [-(2)]/ = rho(0)k(B)Tchi(T) in the long-wavelength limit where rho(0) is the number density, T is the temperature, Q is the scattering vector and chi(T) is the isothermal compressibility. The first part of this result involving the number N (or density) fluctuations is a purely geometrical result and does not involve any assumptions about thermal equilibrium or ergodicity, so is obeyed by all materials. From a large computer model of amorphous silicon, local number fluctuations extrapolate to give S(0) = 0.035 +/- 0.001. The same computation on a large model of vitreous silica using only the silicon atoms and rescaling the distances gives S(0) = 0.039 +/- 0.001, which suggests that this numerical result is robust and perhaps similar for all amorphous tetrahedral networks. For vitreous silica, it is found that S(0) = 0.116 +/- 0.003, close to the experimental value of S(0) = 0.0900 +/- 0.0048 obtained recently by small-angle neutron scattering. Further experimental and modeling studies are needed to determine the relationship between the fictive temperature and structure.

Hierarchical plasticity from pair distance fluctuations.

Observations, experiments and simulations often generate large numbers of snapshots of configurations of complex many-body systems. It is important to find methods of extracting useful information from these ensembles of snapshots in order to document the motion as the system evolves in time. Some of the most interesting information is contained in the relative motion of individual constituents, rather than their absolute motion. We present a novel statistical method for identifying hierarchies of plastically connected objects in a system from a series of two or more snapshot configurations. These plastic clusters are distinctive in that although their members tend to remain loosely connected, the clusters may be deformed plastically. This method is demonstrated for a number of systems, including an exactly soluble freely jointed polymer chain model, a two-dimensional simulation of two species of interacting bodies and a protein. These concepts are implemented as TIMME, the Tool for Identifying Mobility in Macromolecular Ensembles.