Forces that control self-organization of chemically-propelled Janus tori

Control of the individual and collective behavior of self-propelled synthetic micro-objects has immediate application for nanotechnology, robotics, and precision medicine. Despite significant progress in the synthesis and characterization of self-propelled Janus (two-faced) particles, predictive understanding of their behavior remains challenging, especially if the particles have anisotropic forms. Here, by using molecular simulation, we describe the interactions of chemically-propelled microtori near a wall. The results show that a torus hovers at a certain distance from the wall due to a combination of gravity and hydrodynamic flows generated by the chemical activity. Moreover, electrostatic dipolar interactions between the torus and the wall result in a spontaneous tilt and horizontal translation, in a qualitative agreement with the experiment. Simulations of the dynamics of two tori near a wall provide evidence for the formation of stable self-propelled bound states. Our results illustrate that self-organization at the microscale occurs due to a combination of multiple factors, including hydrodynamic, chemical, and electrostatic interactions.

Evolution of microscopic heterogeneity and dynamics in choline chloride-based deep eutectic solvents

Deep eutectic solvents (DESs) are an emerging class of non-aqueous solvents that are potentially scalable, easy to prepare and functionalize for many applications ranging from biomass processing to energy storage technologies. Predictive understanding of the fundamental correlations between local structure and macroscopic properties is needed to exploit the large design space and tunability of DESs for specific applications. Here, we employ a range of computational and experimental techniques that span length-scales from molecular to macroscopic and timescales from picoseconds to seconds to study the evolution of structure and dynamics in model DESs, namely Glyceline and Ethaline, starting from the parent compounds. We show that systematic addition of choline chloride leads to microscopic heterogeneities that alter the primary structural relaxation in glycerol and ethylene glycol and result in new dynamic modes that are strongly correlated to the macroscopic properties of the DES formed.

A functional view reveals substantial predictability of pollinator-mediated selection

A predictive understanding of adaptation to changing environments hinges on a mechanistic understanding of the extent and causes of variation in natural selection. Estimating variation in selection is difficult due to the complex relationships between phenotypic traits and fitness, and the uncertainty associated with individual selection estimates. Plant-pollinator interactions provide ideal systems for understanding variation in selection and its predictability, because both the selective agents (pollinators) and the process linking phenotypes to fitness (pollination) are generally known. Through examples from the pollination literature, I discuss how explicit consideration of the functional mechanisms underlying trait-performance relationships can clarify the relationship between traits and fitness, and how variation in the ecological context that generates selection can help disentangle biologically important variation in selection from sampling variation. I then evaluate the predictability of variation in pollinator-mediated selection through a survey, reanalysis, and synthesis of results from the literature. The synthesis demonstrates that pollinator-mediated selection often varies substantially among trait functional groups, as well as in time and space. Covariance between patterns of selection and ecological variables provides additional support for the biological importance of observed selection, but the detection of such covariance depends on careful choice of relevant predictor variables as well as consideration of quantitative measurements and their meaning, an aspect often neglected in selection studies.

Decoding Cancer Variants of Unknown Significance for Helicase–Nuclease–RPA Complexes Orchestrating DNA Repair During Transcription and Replication

All tumors have DNA mutations, and a predictive understanding of those mutations could inform clinical treatments. However, 40% of the mutations are variants of unknown significance (VUS), with the challenge being to objectively predict whether a VUS is pathogenic and supports the tumor or whether it is benign. To objectively decode VUS, we mapped cancer sequence data and evolutionary trace (ET) scores onto crystallography and cryo-electron microscopy structures with variant impacts quantitated by evolutionary action (EA) measures. As tumors depend on helicases and nucleases to deal with transcription/replication stress, we targeted helicase–nuclease–RPA complexes: (1) XPB-XPD (within TFIIH), XPF-ERCC1, XPG, and RPA for transcription and nucleotide excision repair pathways and (2) BLM, EXO5, and RPA plus DNA2 for stalled replication fork restart. As validation, EA scoring predicts severe effects for most disease mutations, but disease mutants with low ET scores not only are likely destabilizing but also disrupt sophisticated allosteric mechanisms. For sites of disease mutations and VUS predicted to be severe, we found strong co-localization to ordered regions. Rare discrepancies highlighted the different survival requirements between disease and tumor mutations, as well as the value of examining proteins within complexes. In a genome-wide analysis of 33 cancer types, we found correlation between the number of mutations in each tumor and which pathways or functional processes in which the mutations occur, revealing different mutagenic routes to tumorigenesis. We also found upregulation of ancient genes including BLM, which supports a non-random and concerted cancer process: reversion to a unicellular, proliferation-uncontrolled, status by breaking multicellular constraints on cell division. Together, these genes and global analyses challenge the binary “driver” and “passenger” mutation paradigm, support a gradient impact as revealed by EA scoring from moderate to severe at a single gene level, and indicate reduced regulation as well as activity. The objective quantitative assessment of VUS scoring and gene overexpression in the context of functional interactions and pathways provides insights for biology, oncology, and precision medicine.

523 Late-Breaking: Non-nutrient Factors in Colostrum: Systems Biology of Mammary Derived Bioactive Proteins and Gut Receptors That Network Functions in the Bovine Neonate

Maternal-offspring coevolution has introduced the biological concept of “neonatal programming,” in which soluble proteins of varying abundance in bovine colostrum can have targeted activities in the calf gut. Still, the identities and developmental programming mechanisms of the full profile of colostrum proteins on transiently expressed gut receptors/transporters, as well as the ultimate functional responses in the calf, remain to be completely elucidated. The objective of this study was to address this gap in knowledge using systems biology. First, we biopsied the mammary gland and examined the transcriptome in primiparous and multiparous Holstein cows (at parturition/day 0 contrasted to 40–50 days after parturition; n = 4–5/group; FDR< 0.05) and used a bioinformatics algorithm to delineate transcripts coding proteins destined to be secreted into colostrum. In parallel, we analyzed the neonatal small intestine (0 day-old contrasted to 7 day-old; n = 3–5/group; FDR< 0.05) to identify transcripts that code for membrane receptors/transporters precise to the period of colostrum consumption. Integrative analysis of these results highlighted 44 possible signaling circuits (cutoff: >10 nCPM) directed by colostrum in the neonatal gut, providing a consolidated predictive understanding of colostrum-mediated effects that might occur in the neonate during this crucial period in development. These findings also represent the first mechanistic insight into mammary-sourced components that target the neonatal gut to regulate aspects of postnatal development that encompass intestinal maturation, gut-based secondary signaling, and establishment of the gut microbiome, all relevant to long-term health and development. Towards applications, these results are poised to offer novel opportunities to enhance commercial supplements via biomimicry to better reflect the physiology supporting neonatal growth and development.

Weak impact of microorganisms on Ca, Mg-bearing silicate weathering

Assessment of the microbial impact on mineral dissolution is crucial for a predictive understanding of basic (Ca, Mg bearing) silicate weathering and the associated CO2 consumption, bioerosion, and CO2 storage in basaltic rocks. However, there are controversies about the mechanism of microbial effect, which ranges from inhibiting via nil to accelerating. Here we studied diopside interaction with the heterotrophic bacterium Pseudomonas reactants and the soil fungus Chaetomium brasiliense using a combination of mixed-flow and batch reactors and in situ (AFM) and ex situ (SEM) microscopy. The results provide new nano-level insights into the degree to which microorganisms modify silicate dissolution. Taking into account negligible effects of organic ligands on diopside dissolution as reported earlier, we conclude that the microbial effect on Ca-Mg silicates is weak and the acceleration of dissolution of “basic” silicate rocks in the presence of soil biota is solely due to pH decrease in porewaters.

Is the Radial Growth of Irrigated Urban Trees More Strongly Correlated to Light and Temperature than Water?

Background: Real-time monitoring of tree growth can provide novel information about trees in urban/suburban areas and the myriad ecosystem services they provide. By monitoring irrigated specimen trees, we tested the hypothesis that in trees with sufficient water, growth is governed by environmental factors regulating energy gain rather than by factors related to water use. Methods: Internet-enabled, high-resolution dendrometers were installed on 3 trees in Southampton, NY, USA. The instruments, along with a weather station, streamed data to a project web page that was updated once an hour. Growing periods were determined using a Hidden Markov Model based on a zero-growth model. Linear models and conditional inference trees correlated environmental variables to growth magnitude and rate of growth. Results: Growth was governed by the interacting environmental variables of air temperature, soil moisture, vapor pressure deficit (VPD), and took place primarily at night. Radial growth of spruce began April 14 after the accumulation of 69.7 °C growing degree days and ended September 7. Cedar growth began later (April 26) after the accumulation of 160.6 °C and ended later (November 3). During the observation period, these 3 modest suburban trees sequestered 115.1 kg of CO2. Conclusions: Though irrigated, residential tree growth in our experiment was affected by environmental factors relating to both water use and energy gain through photosynthesis. Linking tree growth to fluctuations in environmental conditions facilitates the development of a predictive understanding useful for ecosystem management and growth forecasting across future altering climates.

Promoting Instrument Development for New Research Avenues in Ocean Science: Opening the Black Box of Grazing

While recent research has provided increasing insight into ocean ecosystem functions and rapidly improving predictive ability, it has become clear that for some key processes, including grazing by zooplankton, there simply is no currently available instrumentation to quantify relevant stocks and rates, remotely or in situ. When measurement capacity is lacking, collaborative research between instrument manufacturers and researchers can bring us closer to addressing key knowledge gaps. By necessity, this high risk, high rewards research will require iterative steps from best case scenarios under highly controlled and often artificial laboratory conditions to empirical verification in complex in situ conditions with diverse biota. To illustrate our point, we highlight the example of zooplankton grazing in marine planktonic food webs. Grazing by single-celled zooplankton accounts for the majority of organic carbon loss from marine primary production but is still measured with logistically demanding, point-sample incubation methods that result in reproducible results but at insufficient resolution to adequately describe temporal and spatial dynamics of grazer induced impacts on primary production, export production and the annual cycle of marine plankton. We advance a collaborative research and development agenda to eliminate this knowledge gap. Resolving primary production losses through grazing is fundamental to a predictive understanding of the transfer of matter and energy through marine ecosystems, major reservoirs of the global carbon cycle.

The complex genetics of symbiotic extended phenotypes across environments in a model mutualism

A goal of modern biology is to develop the genotype-phenotype (G-P) map, a predictive understanding of how genomic information generates the organismal trait variation that forms the basis of both natural and managed communities. As microbiome research advances, however, it has become clear that many of these traits are governed by genetic variation encoded not only by the host's own genome, but also by the genomes of myriad cryptic symbionts. Thus many ecologically-important traits are likely symbiotic extended phenotypes, and this recognition adds even more complexity to our conceptions of the G-P map. In model symbioses such as the legume-rhizobium mutualism, host growth and fitness often depend on genetic variation in symbiont partner quality, and our ability to manipulate host and symbiont genotype combinations, combined with increasingly precise sequencing and mapping approaches, provides an opportunity to characterize the genetic nature of these symbiotic extended phenotypes. Here we use naturally-occurring genetic variation in 191 strains of the nitrogen-fixing symbiont Ensifer meliloti in four mapping experiments to study the genomic architecture of symbiotic partner quality within and across environmental contexts and host genotypes. We demonstrate the quantitative genetic nature of symbiotic extended phenotypes, including extensive context-dependency in both the identity and functions of symbiont loci that control host growth. We additionally resolve a core set of universal loci from populations in the native range that are likely important in all or most environments, and thus, serve as excellent targets both for genetic engineering and future coevolutionary studies of symbiosis.