Actin filaments assemble inside the nucleus in response to multiple cellular perturbations, including heat shock, protein misfolding, integrin engagement, and serum stimulation. We find that DNA damage also generates nuclear actin filaments-detectable by phalloidin and live-cell actin probes-with three characteristic morphologies: (i) long, nucleoplasmic filaments; (ii) short, nucleolus-associated filaments; and (iii) dense, nucleoplasmic clusters. This DNA damage-induced nuclear actin assembly requires two biologically and physically linked nucleation factors: Formin-2 and Spire-1/Spire-2. Formin-2 accumulates in the nucleus after DNA damage, and depletion of either Formin-2 or actin's nuclear import factor, importin-9, increases the number of DNA double-strand breaks (DSBs), linking nuclear actin filaments to efficient DSB clearance. Nuclear actin filaments are also required for nuclear oxidation induced by acute genotoxic stress. Our results reveal a previously unknown role for nuclear actin filaments in DNA repair and identify the molecular mechanisms creating these nuclear filaments.

Lipid research represents a frontier for microbiology, as showcased by hopanoid lipids. Hopanoids, which resemble sterols and are found in the membranes of diverse bacteria, have left an extensive molecular fossil record. They were first discovered by petroleum geologists. Today, hopanoid-producing bacteria remain abundant in various ecosystems, such as the rhizosphere. Recently, great progress has been made in our understanding of hopanoid biosynthesis, facilitated in part by technical advances in lipid identification and quantification. A variety of genetically tractable, hopanoid-producing bacteria have been cultured, and tools to manipulate hopanoid biosynthesis and detect hopanoids are improving. However, we still have much to learn regarding how hopanoid production is regulated, how hopanoids act biophysically and biochemically, and how their production affects bacterial interactions with other organisms, such as plants. The study of hopanoids thus offers rich opportunities for discovery.

Hopanoids are steroid-like bacterial lipids that enhance membrane rigidity and promote bacterial growth under diverse stresses. Hopanoid biosynthesis genes are conserved in nitrogen-fixing plant symbionts, and we previously found that the extended (C-35) class of hopanoids in Bradyrhizobium diazoefficiens are required for efficient symbiotic nitrogen fixation in the tropical legume host Aeschynomene afraspera. Here, we demonstrate that the nitrogen-fixation defect conferred by extended hopanoid loss can be fully explained by a reduction in root nodule sizes rather than per-bacteroid nitrogen-fixation levels. Using a single-nodule tracking approach to quantify A. afraspera nodule development, we provide a quantitative model of root nodule development in this host, uncovering both the baseline growth parameters for wild-type nodules and a surprising heterogeneity of extended hopanoid mutant developmental phenotypes. These phenotypes include a delay in root nodule initiation and the presence of a subpopulation of nodules with slow growth rates and low final volumes, which are correlated with reduced motility and surface attachment in vitro and lower bacteroid densities in planta, respectively. This work provides a quantitative reference point for understanding the phenotypic diversity of ineffective symbionts in A. afraspera and identifies specific developmental stages affected by extended hopanoid loss for future mechanistic work.

Ecological communities exhibit regular shifts in structure along environmental gradients, but it has proved difficult to dissect the mechanisms by which environmental conditions determine the relative success of species. Functional traits may provide a link between environmental drivers and mechanisms of community membership, but this has not been well tested for phytoplankton, which dominate primary production in many aquatic ecosystems. Here we test whether functional traits of phytoplankton can explain how species respond to gradients of light and phosphorus across U.S. lakes. We find that traits related to light utilization and maximum growth rate can predict species' differential responses to the relative availability of these resources. These results show that laboratory-measured traits are predictive of species' performance under natural conditions, that functional traits provide a mechanistic foundation for community ecology, and that variation in community structure is predictable in spite of the complexity of ecological communities.

Microalgae represent one of the most promising groups of candidate organisms for replacing fossil fuels with contemporary primary production as a renewable source of energy. Algae can produce many times more biomass per unit area than terrestrial crop plants, easing the competing demands for land with food crops and native ecosystems. However, several aspects of algal biology present unique challenges to the industrial-scale aquaculture of photosynthetic microorganisms. These include high susceptibility to invading aquatic consumers and weeds, as well as prodigious requirements for nutrients that may compete with the fertiliser demands of other crops. Most research on algal biofuel technologies approaches these problems from a cellular or genetic perspective, attempting either to engineer or select algal strains with particular traits. However, inherent functional trade-offs may limit the capacity of genetic selection or synthetic biology to simultaneously optimise multiple functional traits for biofuel productivity and resilience. We argue that a community engineering approach that manages microalgal diversity, species composition and environmental conditions may lead to more robust and productive biofuel ecosystems. We review evidence for trade-offs, challenges and opportunities in algal biofuel cultivation with a goal of guiding research towards intensifying bioenergy production using established principles of community and ecosystem ecology.

The resources that organisms depend on often fluctuate over time, and a variety of common traits are thought to be adaptations to variable resource supply. To understand the trait structure of communities, it is necessary to understand the functional trade-offs that determine what trait combinations are possible and which species can persist and coexist in a given environment. We compare traits across phytoplankton species in order to test for proposed trade-offs between maximum growth rate, equilibrium competitive ability for phosphorus (P), and ability to store P. We find evidence for a three-way trade-off between these traits, and we use empirical trait covariation to parameterize a mechanistic model of competition under pulsed P supply. The model shows that different strategies are favored under different conditions of nutrient supply regime, productivity, and mortality. Furthermore, multiple strategies typically coexist, and the range of traits that persist in the model is similar to the range of traits found in real species. These results suggest that mechanistic models informed by empirical trait variation, in combination with data on the trait structure of natural communities, will play an important role in uncovering the mechanisms that underlie the diversity and structure of ecological communities.

Aquatic ecosystems and processes exhibit a high degree of spatial and temporal heterogeneity, which presents significant challenges for their monitoring. In this paper we report a novel underwater robot, called gliding robotic fish, as an emerging platform for mobile sensing in aquatic environments that can potentially provide high spatiotemporal coverage. The robot represents a hybrid of an underwater glider and a robotic fish, and is capable of exploiting gliding to achieve energy-efficient locomotion while using a fish-like active tail to achieve high maneuverability. Preliminary field-test results are presented, where the robot was used to sample the Kalamazoo River and the Wintergreen Lake in Michigan for concentrations of crude oil and harmful algae, respectively.

Trait-based approaches provide a mechanistic framework to understand and predict the structure and functioning of microbial communities. Resource utilization traits and tradeoffs are among key microbial traits that describe population dynamics and competition among microbes. Several important trade-offs have been identified for prokaryotic and eukaryotic microbial taxa that define contrasting ecological strategies and contribute to species coexistence and diversity. The shape, dimensionality, and hierarchy of trade-offs may determine coexistence patterns and need to be better characterized. Laboratory measured resource utilization traits can be used to explain temporal and spatial structure and dynamics of natural microbial communities and predict biogeochemical impacts. Global environmental change can alter microbial community composition through altering resource utilization by different microbes and, consequently, may modify biogeochemical impacts of microbes.