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Abstract Anthropogenic perturbations to the nitrogen cycle, primarily through use of synthetic fertilizers, is driving an unprecedented increase in the emission of nitrous oxide (N2O), a potent greenhouse gas and an ozone depleting substance, causing urgency in identifying the sources and sinks of N2O. Microbial denitrification is a primary contributor to biotic production of N2O in anoxic regions of soil, marine systems, and wastewater treatment facilities. Here, through comprehensive genome analysis, we show that pathway partitioning is a ubiquitous mechanism of complete denitrification within microbial communities. We have investigated mechanisms and consequences of process partitioning of denitrification through detailed physiological characterization and kinetic modeling of a synthetic community of Rhodanobacter thiooxydans FW510-R12 and Acidovorax sp. GW101-3H11. We have discovered that these two bacterial isolates, from a heavily nitrate (NO3−) contaminated superfund site, complete denitrification through the exchange of nitrite (NO2−) and nitric oxide (NO). The process partitioning of denitrification and other processes, including amino acid metabolism, contribute to increased cooperativity within this denitrifying community. We demonstrate that certain contexts, such as high NO3−, cause unbalanced growth of community members, due to differences in their substrate utilization kinetics. The altered growth characteristics of community members drives accumulation of toxic NO2−, which disrupts denitrification causing N2O off gassing. 

Abstract The ionizable lipidoid is a key component of lipid nanoparticles (LNPs). Degradable lipidoids containing extended alkyl branches have received tremendous attention, yet their optimization and investigation are underappreciated. Here, we devise an in situ construction method for the combinatorial synthesis of degradable branched (DB) lipidoids. We find that appending branch tails to inefficacious lipidoids via degradable linkers boosts mRNA delivery efficiency up to three orders of magnitude. Combinatorial screening and systematic investigation of two libraries of DB-lipidoids reveal important structural criteria that govern their in vivo potency. The lead DB-LNP demonstrates robust delivery of mRNA therapeutics and gene editors into the liver. In a diet-induced obese mouse model, we show that repeated administration of DB-LNP encapsulating mRNA encoding human fibroblast growth factor 21 alleviates obesity and fatty liver. Together, we offer a construction strategy for high-throughput and cost-efficient synthesis of DB-lipidoids. This study provides insights into branched lipidoids for efficient mRNA delivery. 

ABSTRACT The goals of open science are driven by policies requiring data management, sharing, and accessibility. One way of measuring the impact of open science policies on scientific knowledge is to access data that has been prepared for re‐use. But how accessible/available are data resources? In this paper, we discuss a method for exploring and locating datasets made available by scientists from federally funded projects in the US. The data pathways method was tested on federal awards. Here we describe the method and the results from analyzing fifty federal awards granted by the National Science Foundation to pursue data resources and their availability in publications, data repositories, or institutional repositories. The data pathways approach contributes to the development of a practical approach on availability that captures the current ways in which data are accessible from federally funded science projects –ranging from institutional repositories, journal data deposit, PI and project web pages, and science data platforms, among other found possibilities. This paper discusses some background and motivations for such a method, the method, research design, barriers encountered when searching for data resources from projects, and how this method can be useful to future studies of data availability. 

Flowing fluid past chiral objects has been used for centuries to power rotary motion in man-made machines. By contrast, rotary motion in nanoscale biological or chemical systems is produced by biasing Brownian motion through cyclic chemical reactions. Here we show that a chiral biological molecule, a DNA or RNA duplex rotates unidirectionally at billions of revolutions per minute when an electric field is applied along the duplex, with the rotation direction being determined by the chirality of the duplex. The rotation is found to be powered by the drag force of the electro-osmotic flow, realizing the operating principle of a macroscopic turbine at the nanoscale. The resulting torques are sufficient to power rotation of nanoscale beads and rods, offering an engineering principle for constructing nanoscale systems powered by electric field. 

Abstract The 2,5-diketopiperazines are a prominent class of bioactive molecules. The nocardioazines are actinomycete natural products that feature a pyrroloindoline diketopiperazine scaffold composed of two D-tryptophan residues functionalized byN- andC-methylation, prenylation, and diannulation. Here we identify and characterize the nocardioazine B biosynthetic pathway from marineNocardiopsissp. CMB-M0232 by using heterologous biotransformations, in vitro biochemical assays, and macromolecular modeling. Assembly of thecyclo-L-Trp-L-Trp diketopiperazine precursor is catalyzed by a cyclodipeptide synthase. A separate genomic locus encodes tailoring of this precursor and includes an aspartate/glutamate racemase homolog as an unusualD/Lisomerase acting upon diketopiperazine substrates, a phytoene synthase-like prenyltransferase as the catalyst of indole alkaloid diketopiperazine prenylation, and a rare dual function methyltransferase as the catalyst of bothN- andC-methylation as the final steps of nocardioazine B biosynthesis. The biosynthetic paradigms revealed herein showcase Nature’s molecular ingenuity and lay the foundation for diketopiperazine diversification via biocatalytic approaches. 

Abstract Across the social sciences, scholars regularly pool effects over substantial periods of time, a practice that produces faulty inferences if the underlying data generating process is dynamic. To help researchers better perform principled analyses of time-varying processes, we develop a two-stage procedure based upon techniques for permutation testing and statistical process monitoring. Given time series cross-sectional data, we break the role of time through permutation inference and produce a null distribution that reflects a time-invariant data generating process. The null distribution then serves as a stable reference point, enabling the detection of effect changepoints. In Monte Carlo simulations, our randomization technique outperforms alternatives for changepoint analysis. A particular benefit of our method is that, by establishing the bounds for time-invariant effects before interacting with actual estimates, it is able to differentiate stochastic fluctuations from genuine changes. We demonstrate the method’s utility by applying it to a popular study on the relationship between alliances and the initiation of militarized interstate disputes. The example illustrates how the technique can help researchers make inferences about where changes occur in dynamic relationships and ask important questions about such changes.