Action spectra for simulated sunlight were measured in clear water for two viruses: PRD1, a double-stranded DNA bacteriophage, and MS2, a single-stranded RNA bacteriophage. Viruses were diluted into phosphate buffered saline (20 mM PBS, pH 7.5) and exposed for 22 h to simulated sunlight either directly or through one of six glass filters with 50% cutoff wavelengths ranging from 280 to 350 nm. Virus survival was measured using the double agar layer plaque method. Both UVA (320-400 nm) and UVB (280-320 nm) light were found to contribute to PRD1 inactivation, while only UVB inactivated MS2. A computational model was developed for interpreting these action spectra with 3-nm resolution. Using these methods, we provide detailed estimates of the sensitivity of MS2 and PRD1 to photoinactivation from 285 to 345 nm. The resulting sensitivity coefficients can be combined with solar spectra to estimate inactivation rates in clear water under different sunlight conditions. This approach will be useful for modeling the inactivation of viruses and other microorganisms in sunlit natural and engineered systems.

Diel vertical migrations (DVMs) of many plankton species, including single-celled protists, are well documented in the field and form a core component of many large-scale numerical models of plankton transport and ecology. However, the sparse quantitative data available describing motility behaviors of individual protists have frequently indicated that motility exhibits only short-term correlation on the order of a few seconds or hundreds of micrometers, resembling diffusive transport at larger scales-a result incompatible with DVM, which requires ballistic (straight-line) motion. We interrogated an extensive set of three-dimensional protistan movement trajectories in an effort to identify spatial and temporal correlation scales. Whereas the horizontal components of movement were diffusive, the vertical component remained highly correlated (i.e., nonrandom) for nearly all species for the duration of observation (up to 120 s and 6.1 mm) and in the absence of any environmental cues besides gravity. These persistent motility patterns may have been obscured in some previous studies due to the use of restrictive containers, dimensionally lumped, isotropic analyses, and/or an observation bias, inherent to observing free-swimming organisms with stationary cameras, which we accounted for in this study. Extrapolated over a 12-h period, conservative estimates of vertical travel ranges for the protists observed here would be 3-10 m, while diffusive horizontal motion would result in about 10 cm of travel at most. Hence, these extended observations of phylogenetically diverse swimming protists, coupled with a quantitative analysis that accounts for anisotropy in the data, illustrate the small-scale mechanistic underpinnings of DVM.

Curved rods are a ubiquitous bacterial phenotype, but the fundamental question of why they are shaped this way remains unanswered. Through in silico experiments, we assessed freely swimming straight- and curved-rod bacteria of a wide diversity of equal-volume shapes parameterized by elongation and curvature, and predicted their performances in tasks likely to strongly influence overall fitness. Performance trade-offs between these tasks lead to a variety of shapes that are Pareto-optimal, including coccoids, all straight rods, and a range of curvatures. Comparison with an extensive morphological survey of motile curved-rod bacteria indicates that the vast majority of species fall within the Pareto-optimal region of morphospace. This result is consistent with evolutionary trade-offs between just three tasks: efficient swimming, chemotaxis, and low cell construction cost. We thus reveal the underlying selective pressures driving morphological diversity in a widespread component of microbial ecosystems.

The antennules of many marine crustaceans enable them to rapidly locate sources of odorant in turbulent environmental flows and may provide biological inspiration for engineered plume sampling systems. A substantial gap in knowledge concerns how the physical interaction between a sensing device and the chemical filaments forming a turbulent plume affects odorant detection and filters the information content of the plume. We modeled biological arrays of chemosensory hairs as infinite arrays of odorant flux-detecting cylinders and simulated the fluid flow around and odorant flux into the hair-like sensors as they intercepted a single odorant filament. As array geometry and sampling kinematics were varied, we quantified distortion of the flux time series relative to the spatial shape of the original odorant filament as well as flux metrics that may be important to both organisms and engineered systems attempting to measure plume structure and/or identify chemical composition. The most important predictor of signal distortion is the ratio of sensor diameter to odorant filament width. Achieving high peak properties (e.g. sharpness) of the flux time series and maximizing the total number of odorant molecules detected appear to be mutually exclusive design goals. Sensor arrays inspired specifically by the spiny lobster Panulirus argus and mantis shrimp Gonodactylaceus falcatus introduce little signal distortion but these species' neural systems may not be able to resolve plume structure at the level of individual filaments via temporal properties of the odorant flux. Current chemical sensors are similarly constrained. Our results suggest either that the spatial distribution of flux across the aesthetasc array is utilized by P. argus and G. falcatus, or that such high spatiotemporal resolution is unnecessary for effective plume tracking.

20Using a regularized Stokeslet Boundary Element Method (Methods, SI), we simulated the detailed kinematics of freely-swimming curved rods ( Fig. 2B, Movie S1), generating a "performance landscape" for Swimming Efficiency (Fig. 2A) over a broad theoretical morphospace spanning nearly all our observed body shapes as well as spheres, straight rods, and rings ( Fig. 2A, Fig. S 12). All shapes were equal-volume (1 µm 3 , similar to E. coli) to focus on 25 variation in shape, not size.