Determining whether life can progress arbitrarily slowly may reveal fundamental barriers to staying out of thermal equilibrium for living systems. By monitoring budding yeast’s slowed-down life at frigid temperatures and with modeling, we establish that Reactive Oxygen Species (ROS) and a global gene-expression speed quantitatively determine yeast’s pace of life and impose temperature-dependent speed limits - shortest and longest possible cell-doubling times. Increasing cells’ ROS concentration increases their doubling time by elongating the cell-growth (G1-phase) duration that precedes the cell-replication (S-G2-M) phase. Gene-expression speed constrains cells’ ROS-reducing rate and sets the shortest possible doubling-time. To replicate, cells require below-threshold concentrations of ROS. Thus, cells with sufficiently abundant ROS remain in G1, become unsustainably large and, consequently, burst. Therefore, at a given temperature, yeast’s replicative life cannot progress arbitrarily slowly and cells with the lowest ROS-levels replicate most rapidly. Fundamental barriers may constrain the thermal slowing of other organisms’ lives.

Computationally efficient evaluation of penalized estimators of multivariate exponential family distributions is sought. These distributions encompass among others Markov random fields with variates of mixed type (e.g., binary and continuous) as special case of interest. The model parameter is estimated by maximization of the pseudo-likelihood augmented with a convex penalty. The estimator is shown to be consistent. With a world of multi-core computers in mind, a computationally efficient parallel Newton–Raphson algorithm is presented for numerical evaluation of the estimator alongside conditions for its convergence. Parallelization comprises the division of the parameter vector into subvectors that are estimated simultaneously and subsequently aggregated to form an estimate of the original parameter. This approach may also enable efficient numerical evaluation of other high-dimensional estimators. The performance of the proposed estimator and algorithm are evaluated and compared in a simulation study. Finally, the presented methodology is applied to data of an integrative omics study.

The conventional view is that high temperatures cause microorganisms to replicate slowly or die. In this view, microorganisms autonomously combat heat-induced damages. However, microorganisms co-exist with each other, which raises the underexplored and timely question of whether microorganisms can cooperatively combat heat-induced damages at high temperatures. Here, we use the budding yeast Saccharomyces cerevisiae to show that cells can help each other and their future generations to survive and replicate at high temperatures. As a consequence, even at the same temperature, a yeast population can exponentially grow, never grow or grow after unpredictable durations (hours to days) of stasis, depending on its population density. Through the same mechanism, yeasts collectively delay and can eventually stop their approach to extinction, with higher population densities stopping faster. These features arise from yeasts secreting and extracellularly accumulating glutathione—a ubiquitous heat-damage-preventing antioxidant. We show that the secretion of glutathione, which eliminates harmful extracellular chemicals, is both necessary and sufficient for yeasts to collectively survive at high temperatures. A mathematical model, which is generally applicable to any cells that cooperatively replicate by secreting molecules, recapitulates all of these features. Our study demonstrates how organisms can cooperatively define and extend the boundaries of life-permitting temperatures.

One snapshot of the peer review process for “Death Rate of E. coli during Starvation Is Set by Maintenance Cost and Biomass Recycling” (Schink et al., 2019).

The nuclear pore complex (NPC) is the gatekeeper for nuclear transport in eukaryotic cells. A key component of the NPC is the central shaft lined with intrinsically disordered proteins (IDPs) known as FG-Nups, which control the selective molecular traffic. Here, we present an approach to realize artificial NPC mimics that allows controlling the type and copy number of FG-Nups. We constructed 34 nm-wide 3D DNA origami rings and attached different numbers of NSP1, a model yeast FG-Nup, or NSP1-S, a hydrophilic mutant. Using (cryo) electron microscopy, we find that NSP1 forms denser cohesive networks inside the ring compared to NSP1-S. Consistent with this, the measured ionic conductance is lower for NSP1 than for NSP1-S. Molecular dynamics simulations reveal spatially varying protein densities and conductances in good agreement with the experiments. Our technique provides an experimental platform for deciphering the collective behavior of IDPs with full control of their type and position.