Replicating Chromosomes in Whole-Cell Models of Bacteria.

Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication of genetic material. In a recent study, we presented a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics. This approach was used to investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell cycle. To achieve cell-scale chromosome structures that are realistic, we modeled the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. Additionally, the polymer interacts with ribosomes distributed according to cryo-electron tomograms of Syn3A. The polymer model was further augmented by computational models of loop extrusion by structural maintenance of chromosomes (SMC) protein complexes and topoisomerase action, and the modeling and analysis of multi-fork replication states.

Dynamics of chromosome organization in a minimal bacterial cell.

Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication and inheritance of genetic material. By creating a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics, we investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell-cycle. To achieve cell-scale chromosome structures that are realistic, we model the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. In addition, the conformations of the circular DNA must avoid overlapping with ribosomes identitied in cryo-electron tomograms. While Syn3A lacks the complex regulatory systems known to orchestrate chromosome segregation in other bacteria, its minimized genome retains essential loop-extruding structural maintenance of chromosomes (SMC) protein complexes (SMC-scpAB) and topoisomerases. Through implementing the effects of these proteins in our simulations of replicating chromosomes, we find that they alone are sufficient for simultaneous chromosome segregation across all generations within nested theta structures. This supports previous studies suggesting loop-extrusion serves as a near-universal mechanism for chromosome organization within bacterial and eukaryotic cells. Furthermore, we analyze ribosome diffusion under the influence of the chromosome and calculate in silico chromosome contact maps that capture inter-daughter interactions. Finally, we present a methodology to map the polymer model of the chromosome to a Martini coarse-grained representation to prepare molecular dynamics models of entire Syn3A cells, which serves as an ultimate means of validation for cell states predicted by the WCM.

Restoration ecology through the lens of coexistence theory.

Advances in restoration ecology are needed to guide ecological restoration in a variable and changing world. Coexistence theory provides a framework for how variability in environmental conditions and species interactions affects species success. Here, we conceptually link coexistence theory and restoration ecology. First, including low-density growth rates (LDGRs), a classic metric of coexistence, can improve abundance-based restoration goals, because abundances are sensitive to initial treatments and ongoing variability. Second, growth-rate partitioning, developed to identify coexistence mechanisms, can improve restoration practice by informing site selection and indicating necessary interventions (e.g., site amelioration or competitor removal). Finally, coexistence methods can improve restoration assessment, because initial growth rates indicate trajectories, average growth rates measure success, and growth partitioning highlights interventions needed in future.

Common Photo-oxidative Decarboxylation Mechanism in Iron Hydroxy Carboxylate Complexes.

Photochemical oxidation of dissolved organic matter is a crucial component of carbon cycling in surface waters. Photo-oxidation of iron(III)-carboxylate complexes is of particular interest because complexation with iron(III) can sensitize this functional group to photodecarboxylation. The photo-oxidation mechanism of ferrioxalate has been extensively characterized, but it is unclear whether the mechanism or timing is similar for other more complex carboxylates. In this study, we use time-resolved infrared spectroscopy to demonstrate that Fe(III)-citrate, an aliphatic carboxylate, and Fe(III)-salicylate, an aromatic carboxylate, follow the same photo-oxidation kinetics as ferrioxalate. Hence the data suggest a common mechanism for decarboxylation of iron hydroxy carbonates. Differences in the CO2 yield within 50 ps are qualitatively similar to the long-time-scale quantum yield for Fe(II) production.

Rapid Prediction of a Liquid Structure from a Single Molecular Configuration Using Deep Learning.

Molecular dynamics simulation is an indispensable tool for understanding the collective behavior of atoms and molecules and the phases they form. Statistical mechanics provides accurate routes for predicting macroscopic properties as time-averages over visited molecular configurations - microstates. However, to obtain convergence, we need a sufficiently long record of visited microstates, which translates to the high-computational cost of the molecular simulations. In this work, we show how to use a point cloud-based deep learning strategy to rapidly predict the structural properties of liquids from a single molecular configuration. We tested our approach using three homogeneous liquids with progressively more complex entities and interactions: Ar, NO, and H2O under varying pressure and temperature conditions within the liquid state domain. Our deep neural network architecture allows rapid insight into the liquid structure, here probed by the radial distribution function, and can be used with molecular/atomistic configurations generated by either simulation, first-principle, or experimental methods.

Smectite phase separation is driven by hydration-mediated interfacial charge.

Smectite clay minerals have an outsize impact on the response of clay-rich media to common stimuli, such as hydration and ion exchange, motivating extensive effort to understand behaviors resulting from these processes such as swelling and exfoliation. Smectites are common and historic systems for investigating colloidal and interfacial phenomena, with two swelling regimes commonly identified across myriad clays: osmotic swelling at high water activity and crystalline swelling at low water activity. However, no current swelling model seamlessly spans the full ranges of water, salt and clay content encountered in natural or engineered settings. Here, we show that structures previously rationalized as either osmotic or crystalline coexist as a rich array of distinct colloidal phases that differ by water content, layer stacking thickness, and curvature. We present an analytical model for intermolecular potentials among water, salt and clay in both mono- and divalent electrolytes that predicts swelling pressures across high and low water activities. Our results indicate that all clay swelling is osmotic swelling, but that the osmotic pressure of charged mineral interfaces becomes attractive and dominates that of the electrolyte at high clay activities. Global energy minima are often not reached on experimental timescales due to many local energy minima that promote long-lived intermediate states with vast differences in clay, ion, and water mobilities, leading to hyperdiffusive layer dynamics driven by variable hydration-mediated interfacial charge. Teaser Distinct colloidal phases of swelling clays emerge via ion (de)hydration at mineral interfaces that drives hyperdiffusive layer dynamics as metastable smectites approach equilibrium.

River thorium concentrations can record bedrock fracture processes including some triggered by distant seismic events.

Fractures are integral to the hydrology and geochemistry of watersheds, but our understanding of fracture dynamics is very limited because of the challenge of monitoring the subsurface. Here we provide evidence that long-term, high-frequency measurements of the river concentration of the ultra-trace element thorium (Th) can provide a signature of bedrock fracture processes spanning neighboring watersheds in Colorado. River Th concentrations show abrupt (subdaily) excursions and biexponential decay with approximately 1-day and 1-week time constants, concentration patterns that are distinct from all other solutes except beryllium and arsenic. The patterns are uncorrelated with daily precipitation records or seasonal trends in atmospheric deposition. Groundwater Th analyses are consistent with bedrock release and dilution upon mixing with river water. Most Th excursions have no seismic signatures that are detectable 50 km from the site, suggesting the Th concentrations can reveal aseismic fracture or fault events. We find, however, a weak statistical correlation between Th and seismic motion caused by distant earthquakes, possibly the first chemical signature of dynamic earthquake triggering, a phenomenon previously identified only through geophysical methods.

Molecular dynamics simulation of an entire cell.

The ultimate microscope, directed at a cell, would reveal the dynamics of all the cell's components with atomic resolution. In contrast to their real-world counterparts, computational microscopes are currently on the brink of meeting this challenge. In this perspective, we show how an integrative approach can be employed to model an entire cell, the minimal cell, JCVI-syn3A, at full complexity. This step opens the way to interrogate the cell's spatio-temporal evolution with molecular dynamics simulations, an approach that can be extended to other cell types in the near future.

Extinction dynamics: The interplay of species traits and the spatial scales of metapopulation declines.

Global changes can lead to species declines and extinctions through their impacts on species habitats at two distinct spatial scales: habitat destruction, in which individual habitat patches are destroyed by land-use change or natural disasters, and habitat degradation, in which larger scale changes, such as nitrogen deposition or climate change, lower mean population abundances across landscapes. We developed a theory showing that, even when these two forms of global change have an identical impact on a species' total amount of habitat, they have qualitatively different consequences for species dynamics and extinction. Using metapopulation theory and simulations, we found distinct impacts of these global changes characterized through several responses: the rate at which populations are lost from the remaining patches, extinction thresholds, and the duration of extinction debts. Habitat degradation causes a faster decline in species populations when habitat reduction is low, making it particularly detrimental for rare species. Habitat destruction has smaller impacts for low habitat reduction, but shows clear thresholds beyond which it surpasses degradation's negative impact; the location and steepness of the threshold depends on species dispersal, with poor dispersers having steeper thresholds. These results highlight the challenge of using population monitoring to assess the consequences of global changes and predict consequences of further change: extinction trajectories cannot be predicted due to thresholds (habitat destruction) and lagged dynamics that lead to extinction debts (habitat degradation). Our research clarifies why the impacts of one type of global change may poorly predict the impacts of the other and suggests general rules for predicting the long-term impacts of global changes based on species traits.

Biodiversity patterns diverge along geographic temperature gradients.

Models applying space-for-time substitution, including those projecting ecological responses to climate change, generally assume an elevational and latitudinal equivalence that is rarely tested. However, a mismatch may lead to different capacities for providing climatic refuge to dispersing species. We compiled community data on zooplankton, ectothermic animals that form the consumer basis of most aquatic food webs, from over 1200 mountain lakes and ponds across western North America to assess biodiversity along geographic temperature gradients spanning nearly 3750 m elevation and 30° latitude. Species richness, phylogenetic relationships, and functional diversity all showed contrasting responses across gradients, with richness metrics plateauing at low elevations but exhibiting intermediate latitudinal maxima. The nonmonotonic/hump-shaped diversity trends with latitude emerged from geographic interactions, including weaker latitudinal relationships at higher elevations (i.e. in alpine lakes) linked to different underlying drivers. Here, divergent patterns of phylogenetic and functional trait dispersion indicate shifting roles of environmental filters and limiting similarity in the assembly of communities with increasing elevation and latitude. We further tested whether gradients showed common responses to warmer temperatures and found that mean annual (but not seasonal) temperatures predicted elevational richness patterns but failed to capture consistent trends with latitude, meaning that predictions of how climate change will influence diversity also differ between gradients. Contrasting responses to elevation- and latitude-driven warming suggest different limits on climatic refugia and likely greater barriers to northward range expansion.

High field magnetometry with hyperpolarized nuclear spins.

Quantum sensors have attracted broad interest in the quest towards sub-micronscale NMR spectroscopy. Such sensors predominantly operate at low magnetic fields. Instead, however, for high resolution spectroscopy, the high-field regime is naturally advantageous because it allows high absolute chemical shift discrimination. Here we demonstrate a high-field spin magnetometer constructed from an ensemble of hyperpolarized 13C nuclear spins in diamond. They are initialized by Nitrogen Vacancy (NV) centers and protected along a transverse Bloch sphere axis for minute-long periods. When exposed to a time-varying (AC) magnetic field, they undergo secondary precessions that carry an imprint of its frequency and amplitude. For quantum sensing at 7T, we demonstrate detection bandwidth up to 7 kHz, a spectral resolution < 100mHz, and single-shot sensitivity of 410pT[Formula: see text]. This work anticipates opportunities for microscale NMR chemical sensors constructed from hyperpolarized nanodiamonds and suggests applications of dynamic nuclear polarization (DNP) in quantum sensing.

Ab initio modeling of H2S dissociative chemisorption on Ag(100).

Natural sulfidation of silver nanomaterials can passivate the surface, while preserving desirable optical and electrical properties, which is beneficial for limiting Ag+ release and cytotoxicity. But little is known at the atomic scale about silver sulfidation mechanisms, particularly on different crystallographic terminations. Using density functional theory (DFT) calculations, we examined the process of H2S sorption and reaction on Ag(100) surfaces relevant to Ag nanowires (AgNWs). DFT energy minimizations predict a strong dissociative chemisorption of H2S on the surface yielding co-adsorbed sulfide and hydrogen atoms in specific surface sites. However, nudged elastic band (NEB) calculations suggest relatively large activation energies for both the first and second dissociation steps, due in part to overcoming the energy to cleave the S-H bond and attendant site migration from an on-top Ag site position to a hollow site position of the bound S atom. The large barriers associated with the dissociative chemisorption reaction for gas-phase H2S points to the importance of including thermochemical contributions and the influence of other components in more complex environmental media such as air or water to help complete the mechanistic picture of silver sulfidation and passivation for realistic systems.

Ion complexation waves emerge at the curved interfaces of layered minerals.

Visualizing hydrated interfaces is of widespread interest across the physical sciences and is a particularly acute need for layered minerals, whose properties are governed by the structure of the electric double layer (EDL) where mineral and solution meet. Here, we show that cryo electron microscopy and tomography enable direct imaging of the EDL at montmorillonite interfaces in monovalent electrolytes with ångstrom resolution over micron length scales. A learning-based multiple-scattering reconstruction method for cryo electron tomography reveals ions bound asymmetrically on opposite sides of curved, exfoliated layers. We observe conserved ion-density asymmetry across stacks of interacting layers in cryo electron microscopy that is associated with configurations of inner- and outer-sphere ion-water-mineral complexes that we term complexation waves. Coherent X-ray scattering confirms that complexation waves propagate at room-temperature via a competition between ion dehydration and charge interactions that are coupled across opposing sides of a layer, driving dynamic transitions between stacked and aggregated states via layer exfoliation.

Application of modern coexistence theory to rare plant restoration provides early indication of restoration trajectories.

Restoration ecology commonly seeks to re-establish species of interest in degraded habitats. Despite a rich understanding of how succession influences re-establishment, there are several outstanding questions that remain unaddressed: are short-term abundances sufficient to determine long-term re-establishment success, and what factors contribute to unpredictable restorations outcomes? In other words, when restoration fails, is it because the restored habitat is substandard, because of strong competition with invasive species, or alternatively due to changing environmental conditions that would equally impact established populations? Here, we re-purpose tools developed from modern coexistence theory to address these questions, and apply them to an effort to restore the endangered Contra Costa goldfields (Lasthenia conjugens) in constructed ("restored") California vernal pools. Using 16 years of data, we construct a population model of L. conjugens, a species of conservation concern due primarily to habitat loss and invasion of exotic grasses. We show that initial, short-term appearances of restoration success from population abundances is misleading, as year-to-year fluctuations cause long-term population growth rates to fall below zero. The failure of constructed pools is driven by lower maximum growth rates compared with reference ("natural") pools, coupled with a stronger negative sensitivity to annual fluctuations in abiotic conditions that yield decreased maximum growth rates. Nonetheless, our modeling shows that fluctuations in competition (mainly with exotic grasses) benefit L. conjugens through periods of competitive release, especially in constructed pools of intermediate pool depth. We therefore show how reductions in invasives and seed addition in pools of particular depths could change the outcome of restoration for L. conjugens. By applying a largely theoretical framework to the urgent goal of ecological restoration, our study provides a blueprint for predicting restoration success, and identifies future actions to reverse species loss.

Integrating cellular and molecular structures and dynamics into whole-cell models.

A complete description of the state of the cell requires knowledge of its size, shape, components, intracellular reactions, and interactions with its environment-all of these as a function of time and cell growth. Adding to this list is the need for theoretical models and simulations that integrate and help to interpret this daunting amount of experimental data. It seems like an overwhelming list of requirements, but progress is being made on many fronts. In this review, we discuss the current challenges and problems in obtaining sufficient information about each aspect of a dynamical whole-cell model (DWCM) for simple and well-studied bacterial systems.

Biomineralization: Integrating mechanism and evolutionary history.

Calcium carbonate (CaCO3) biomineralizing organisms have played major roles in the history of life and the global carbon cycle during the past 541 Ma. Both marine diversification and mass extinctions reflect physiological responses to environmental changes through time. An integrated understanding of carbonate biomineralization is necessary to illuminate this evolutionary record and to understand how modern organisms will respond to 21st century global change. Biomineralization evolved independently but convergently across phyla, suggesting a unity of mechanism that transcends biological differences. In this review, we combine CaCO3 skeleton formation mechanisms with constraints from evolutionary history, omics, and a meta-analysis of isotopic data to develop a plausible model for CaCO3 biomineralization applicable to all phyla. The model provides a framework for understanding the environmental sensitivity of marine calcifiers, past mass extinctions, and resilience in 21st century acidifying oceans. Thus, it frames questions about the past, present, and future of CaCO3 biomineralizing organisms.

The hard x-ray nanotomography microscope at the advanced light source.

Beamline 11.3.1 at the Advanced Light Source is a tender/hard (6-17 keV) x-ray bend magnet beamline recently re-purposed with a new full-field, nanoscale transmission x-ray microscope. The microscope is designed to image composite and porous materials possessing a submicrometer structure and compositional heterogeneity that determine materials' performance and geologic behavior. The theoretical and achieved resolutions are 55 and <100 nm, respectively. The microscope is used in tandem with a <25 nm eccentricity rotation stage for high-resolution volume imaging using nanoscale computed tomography. The system also features a novel bipolar illumination condenser for the illumination of an ∼100 µm spot of interest on the sample, followed by a phase-type zone plate magnifying objective of ∼52 µm field of view and a phase detection ring. The zone plate serves as the system objective and magnifies the sample with projection onto an indirect x-ray detection system, consisting of a polished single crystal CsI(Tl) scintillator and a range of high-quality Plan Fluorite visible light objectives. The objectives project the final visible light image onto a water-cooled CMOS 2048 × 2048-pixel2 detector. Here, we will discuss the salient features of this instrument and describe early results from imaging the internal three-dimensional microstructure and nanostructure of target materials, including fiber-reinforced composites and geomaterials.

Fundamental behaviors emerge from simulations of a living minimal cell.

We present a whole-cell fully dynamical kinetic model (WCM) of JCVI-syn3A, a minimal cell with a reduced genome of 493 genes that has retained few regulatory proteins or small RNAs. Cryo-electron tomograms provide the cell geometry and ribosome distributions. Time-dependent behaviors of concentrations and reaction fluxes from stochastic-deterministic simulations over a cell cycle reveal how the cell balances demands of its metabolism, genetic information processes, and growth, and offer insight into the principles of life for this minimal cell. The energy economy of each process including active transport of amino acids, nucleosides, and ions is analyzed. WCM reveals how emergent imbalances lead to slowdowns in the rates of transcription and translation. Integration of experimental data is critical in building a kinetic model from which emerges a genome-wide distribution of mRNA half-lives, multiple DNA replication events that can be compared to qPCR results, and the experimentally observed doubling behavior.

Actin Crosslinking Family Protein 7 Deficiency Does Not Impair Hearing in Young Mice.

To enable hearing, the sensory hair cell contains specialized subcellular structures at its apical region, including the actin-rich cuticular plate and circumferential band. ACF7 (actin crosslinking family protein 7), encoded by the gene Macf1 (microtubule and actin crosslinking factor 1), is a large cytoskeletal crosslinking protein that interacts with microtubules and filamentous actin to shape cells. ACF7 localizes to the cuticular plate and the circumferential band in the hair cells of vertebrates. The compelling expression pattern of ACF7 in hair cells, combined with conserved roles of this protein in the cytoskeleton of various cell types in invertebrates and vertebrates, led to the hypothesis that ACF7 performs a key function in the subcellular architecture of hair cells. To test the hypothesis, we conditionally target Macf1 in the inner ears of mice. Surprisingly, our data show that in young, but mature, conditional knockout mice cochlear hair cell survival, planar cell polarity, organization of the hair cells within the organ of Corti, and capacity to hear are not significantly impacted. Overall, these results fail to support the hypothesis that ACF7 is an essential hair cell protein in young mice, and the purpose of ACF7 expression in the hair cell remains to be understood.

Floquet Prethermalization with Lifetime Exceeding 90 s in a Bulk Hyperpolarized Solid.

We report the observation of long-lived Floquet prethermal states in a bulk solid composed of dipolar-coupled ^{13}C nuclei in diamond at room temperature. For precessing nuclear spins prepared in an initial transverse state, we demonstrate pulsed spin-lock Floquet control that prevents their decay over multiple-minute-long periods. We observe Floquet prethermal lifetimes T_{2}^{'}≈90.9 s, extended >60 000-fold over the nuclear free induction decay times. The spins themselves are continuously interrogated for ∼10 min, corresponding to the application of ≈5.8×10^{6} control pulses. The ^{13}C nuclei are optically hyperpolarized by lattice nitrogen vacancy centers; the combination of hyperpolarization and continuous spin readout yields significant signal-to-noise ratio in the measurements. This allows probing the Floquet thermalization dynamics with unprecedented clarity. We identify four characteristic regimes of the thermalization process, discerning short-time transient processes leading to the prethermal plateau and long-time system heating toward infinite temperature. This Letter points to new opportunities possible via Floquet control in networks of dilute, randomly distributed, low-sensitivity nuclei. In particular, the combination of minutes-long prethermal lifetimes and continuous spin interrogation opens avenues for quantum sensors constructed from hyperpolarized Floquet prethermal nuclei.