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.

Chaperones are protein complexes that help to fold and disaggregate a cell's proteins. It is not understood how four major chaperone systems of Escherichia coli work together in proteostasis: the recognition, sorting, folding, and disaggregating of the cell's many different proteins. Here, we model this machine. We combine extensive data on chaperoning, folding, and aggregation rates with expression levels of proteins and chaperones measured at different growth rates. We find that the proteostasis machine recognizes and sorts a client protein based on two biophysical properties of the client's misfolded state (M state): its stability and its kinetic accessibility from its unfolded state (U state). The machine is energy-efficient (the sickest proteins use the most ATP-expensive chaperones), comprehensive (it can handle any type of protein), and economical (the chaperone concentrations are just high enough to keep the whole proteome folded and disaggregated but no higher). The cell needs higher chaperone levels in two situations: fast growth (when protein production rates are high) and very slow growth (to mitigate the effects of protein degradation). This type of model complements experimental knowledge by showing how the various chaperones work together to achieve the broad folding and disaggregation needs of the cell.proteostasis | chaperone | protein folding | shields up | shields down A major action of cells is proteostasis (1-4). A cell's proteostasis "machine" is the collection of chaperones and synthesis and degradation processes that maintain the homeostatic balance of the folding and disaggregation of the cell's proteins. It is a machine in the sense that it is an energy-driven cyclic device that has component parts that work together to create its action. Proteostasis can become unbalanced under stresses, such as temperature, osmotic shock, oxidation, or drugs, or different growth conditions. Proteome health can fail if the machine is pushed beyond its tipping point (for example, in cell aging, cancer, or neurodegenerative diseases, such as Alzheimer's and Parkinson's) (1, 2, 4, 5).Much is now understood about the component parts (i.e., the structures of some chaperones, the folding equilibria and kinetics of isolated proteins in vitro, and the rates at which particular chaperones help fold and disaggregate particular proteins). The organism in which this is best understood is arguably Escherichia coli. What is not yet known is how the component chaperones act together as a machine on the many different proteins to meet the cell's needs. It is not known how "decisions" are made for trafficking different proteins through different chaperones.Cells have multiple types of chaperones. Also, different classes of proteins have different relationships with each chaperone (6). E. coli has four major chaperone systems: GroEL/GroES (GroE), DnaK/DnaJ/GrpE (KJE), Trigger Factor (TF), and ClpB (B) (7). Complex cells have more (8). E. coli proteins fall into three classes of interaction with GroEL (7): class I protei...

In many systems, nucleation of a stable solid may occur in the presence of other (often more than one) metastable phases. These may be polymorphic solids or even liquid phases. Sometimes, the metastable phase might have a lower free energy minimum than the liquid but higher than the stable-solid-phase minimum and have characteristics in between the parent liquid and the globally stable solid phase. In such cases, nucleation of the solid phase from the melt may be facilitated by the metastable phase because the latter can "wet" the interface between the parent and the daughter phases, even though there may be no signature of the existence of metastable phase in the thermodynamic properties of the parent liquid and the stable solid phase. Straightforward application of classical nucleation theory (CNT) is flawed here as it overestimates the nucleation barrier because surface tension is overestimated (by neglecting the metastable phases of intermediate order) while the thermodynamic free energy gap between daughter and parent phases remains unchanged. In this work, we discuss a density functional theory (DFT)-based statistical mechanical approach to explore and quantify such facilitation. We construct a simple order-parameter-dependent free energy surface that we then use in DFT to calculate (i) the order parameter profile, (ii) the overall nucleation free energy barrier, and (iii) the surface tension between the parent liquid and the metastable solid and also parent liquid and stable solid phases. The theory indeed finds that the nucleation free energy barrier can decrease significantly in the presence of wetting. This approach can provide a microscopic explanation of the Ostwald step rule and the well-known phenomenon of "disappearing polymorphs" that depends on temperature and other thermodynamic conditions. Theory reveals a diverse scenario for phase transformation kinetics, some of which may be explored via modern nanoscopic synthetic methods.

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