Hypervirulent K. pneumoniae (hvKp) is a distinct pathotype that causes invasive community-acquired infections in healthy individuals. Hypermucoviscosity (hmv) is a major phenotype associated with hvKp characterized by copious capsule production and poor sedimentation. Dissecting the individual functions of CPS production and hmv in hvKp has been hindered by the conflation of these two properties. Although hmv requires capsular polysaccharide (CPS) biosynthesis, other cellular factors may also be required and some fitness phenotypes ascribed to CPS may be distinctly attributed to hmv. To address this challenge, we systematically identified genes that impact capsule and hmv. We generated a condensed, ordered transposon library in hypervirulent strain KPPR1, then evaluated the CPS production and hmv phenotypes of the 3,733 transposon mutants, representing 72% of all open reading frames in the genome. We employed forward and reverse genetic screens to evaluate effects of novel and known genes on CPS biosynthesis and hmv. These screens expand our understanding of core genes that coordinate CPS biosynthesis and hmv, as well as identify central metabolism genes that distinctly impact CPS biosynthesis or hmv, specifically those related to purine metabolism, pyruvate metabolism and the TCA cycle. Six representative mutants, with varying effect on CPS biosynthesis and hmv, were evaluated for their impact on CPS thickness, serum resistance, host cell association, and fitness in a murine model of disseminating pneumonia. Altogether, these data demonstrate that hmv requires both CPS biosynthesis and other cellular factors, and that hmv and CPS may serve distinct functions during pathogenesis. The integration of hmv and CPS to the metabolic status of the cell suggests that hvKp may require certain nutrients to specifically cause deep tissue infections.

We use N-body simulations to quantify how the escape velocity in cluster-sized halos maps to the gravitational potential in a ΛCDM universe. Using spherical density-potential pairs and the Poisson equation, we find that the matter density inferred gravitational potential profile predicts the escape velocity profile to within a few percent accuracy for group and cluster-sized halos (10 < < M 1013 200 15 M  , with respect to the critical density). The accuracy holds from just outside the core to beyond the virial radius. We show the importance of explicitly incorporating a cosmological constant when inferring the potential from the Poisson equation. We consider three density models and find that the Einasto and Gamma profiles provide a better joint estimate of the density and potential profiles than the Navarro, Frenk, and White profile, which fails to accurately represent the escape velocity. For individual halos, the 1σ scatter between the measured escape velocity and the density-inferred potential profile is small (<5%). Finally, while the sub-halos show 15% biases in their representation of the particle velocity dispersion profile, the sub-halo escape velocity profile matches the dark matter escape velocity profile to high accuracy with no evidence of velocity bias outside 0.4r 200 .

Shortly after its discovery, General Relativity (GR) was applied to predict the behavior of our Universe on the largest scales, and later became the foundation of modern cosmology. Its validity has been verified on a range of scales and environments from the Solar system to merging black holes. However, experimental confirmations of GR on cosmological scales have so far lacked the accuracy one would hope for — its applications on those scales being largely based on extrapolation and its validity there sometimes questioned in the shadow of the discovery of the unexpected cosmic acceleration. Future astronomical instruments surveying the distribution and evolution of galaxies over substantial portions of the observable Universe, such as the Dark Energy Spectroscopic Instrument (DESI), will be able to measure the fingerprints of gravity and their statistical power will allow strong constraints on alternatives to GR. In this paper, based on a set of N-body simulations and mock galaxy catalogs, we study the predictions of a number of traditional and novel summary statistics beyond linear redshift distortions in two well-studied modified gravity models — chameleon f(R) gravity and a braneworld model — and the potential of testing these deviations from GR using DESI. These summary statistics employ a wide array of statistical properties of the galaxy and the underlying dark matter field, including two-point and higher-order statistics, environmental dependence, redshift space distortions and weak lensing. We find that they hold promising power for testing GR to unprecedented precision. The major future challenge is to make realistic, simulation-based mock galaxy catalogs for both GR and alternative models to fully exploit the statistic power of the DESI survey (by matching the volumes and galaxy number densities of the mocks to those in the real survey) and to better understand the impact of key systematic effects. Using these, we identify future simulation and analysis needs for gravity tests using DESI.