Uncertainties in life cycle greenhouse gas emissions from U.S. beef cattle

Beef cattle feedlots are estimated to contribute 26% of U.S. agricultural greenhouse gas (GHG) emissions, and future climate change policy could target reducing these emissions. Life cycle assessment (LCA) of GHG emissions from U.S. grain-fed beef cattle was conducted based on industry statistics and previous studies to identify the main sources of uncertainty in these estimations. Uncertainty associated with GHG emissions from indirect land use change, pasture soil emissions (e.g. soil carbon sequestration), enteric fermentation from cattle on pasture, and methane emissions from feedlot manure, respectively, contributed the most variability to life cycle GHG emissions from beef production. Feeding of coproducts from ethanol production was estimated to reduce life cycle emissions by 1.7%, but could increase emissions by 0.6–2.0% with higher feeding rates. Monte Carlo simulation found a range of life cycle emissions from 2.52 to 9.58 kg CO2 per kg live weight (5th and 95th percentiles), with a calculated average of 8.14, which is between recent estimates. Current methods used by the U.S. Environmental Protection Agency (EPA) associated with beef production in feedlots were found to account for only 3–20% of life cycle GHG emissions. Includes Supplementary Information/Appendix A

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Life Cycle Boundaries and Greenhouse Gas Emissions from Beef Cattle

Beef cattle are estimated to directly contribute 26% of U.S. agricultural greenhouse gas (GHG) emissions, and future climate change policy may target reducing these emissions. Life cycle assessment (LCA) of GHG emissions from U.S. feedlot beef cattle was conducted to compare methods of the U.S. Environmental Protection Agency (EPA) with a more complete evaluation of emissions. The inclusion of emissions from crop production for feed, associated land use change, and other minor factors nearly doubled GHG emissions associated with beef feedlots from the EPA Annual Inventory estimate of 1611 kgCO2e hd-1 yr-1 to 3182 ± 167 kgCO2e hd-1 yr-1. Feeding of coproducts from ethanol production is estimated to reduce feedlot emissions by 6%. Furthermore, inclusion of pasture and land use change emissions from the cow-calf stage of the animal life cycle nearly tripled GHG emissions compared to the feedlot LCA (6.0 to 16.67 ± 0.32 kgCO2e kg-1 beef). Despite use of expanded system boundaries in the LCA, U.S. beef cattle GHG emissions were lower than the majority of previous U.S. and international assessments of beef cattle. Nearly a 16-fold range in results can be found for U.S. beef using different system boundaries and assumptions. Use of LCA-driven carbon pricing on U.S. beef could reduce beef demand and associated beef GHG emissions by 2.7 to 21 Tg CO2e yr-1. Advisor: Adam J. Lisk

Cell-Free Mixing of <i>Escherichia coli</i> Crude Extracts to Prototype and Rationally Engineer High-Titer Mevalonate Synthesis

Cell-free metabolic engineering (CFME) is advancing a powerful paradigm for accelerating the design and synthesis of biosynthetic pathways. However, as most cell-free biomolecule synthesis systems to date use purified enzymes, energy and cofactor balance can be limiting. To address this challenge, we report a new CFME framework for building biosynthetic pathways by mixing multiple crude lysates, or extracts. In our modular approach, cell-free lysates, each selectively enriched with an overexpressed enzyme, are generated in parallel and then combinatorically mixed to construct a full biosynthetic pathway. Endogenous enzymes in the cell-free extract fuel high-level energy and cofactor regeneration. As a model, we apply our framework to synthesize mevalonate, an intermediate in isoprenoid synthesis. We use our approach to rapidly screen enzyme variants, optimize enzyme ratios, and explore cofactor landscapes for improving pathway performance. Further, we show that genomic deletions in the source strain redirect metabolic flux in resultant lysates. In an optimized system, mevalonate was synthesized at 17.6 g·L^–1 (119 mM) over 20 h, resulting in a volumetric productivity of 0.88 g·L^–1·hr^–1. We also demonstrate that this system can be lyophilized and retain biosynthesis capability. Our system catalyzes ∼1250 turnover events for the cofactor NAD⁺ and demonstrates the ability to rapidly prototype and debug enzymatic pathways <i>in vitro</i> for compelling metabolic engineering and synthetic biology applications

A mini-TGA protein modulates gene expression through heterogeneous association with transcription factors

TGA (TGACG-binding) transcription factors, which bind their target DNA through a conserved basic region leucine zipper (bZIP) domain, are vital regulators of gene expression in salicylic acid (SA)-mediated plant immunity. Here, we investigated the role of StTGA2.1, a potato (Solanum tuberosum) TGA lacking the full bZIP, which we named a mini-TGA. Such truncated proteins have been widely assigned as loss-of-function mutants. We, however, confirmed that StTGA2.1 overexpression compensates for SA-deficiency, indicating a distinct mechanism of action compared with model plant species. To understand the underlying mechanisms, we showed that StTGA2.1 can physically interact with StTGA2.2 and StTGA2.3, while its interaction with DNA was not detected. We investigated the changes in transcriptional regulation due to StTGA2.1 overexpression, identifying direct and indirect target genes. Using in planta transactivation assays, we confirmed that StTGA2.1 interacts with StTGA2.3 to activate StPRX07, a member of class III peroxidases (StPRX), which are known to play role in immune response. Finally, via structural modeling and molecular dynamics simulations, we hypothesized that the compact molecular architecture of StTGA2.1 distorts DNA conformation upon heterodimer binding to enable transcriptional activation. This study demonstrates how protein truncation can lead to distinct functions and that such events should be studied carefully in other protein families

A pressure test to make 10 molecules in 90 days: External evaluation of methods to engineer biology

© 2018 American Chemical Society. Centralized facilities for genetic engineering, or "biofoundries", offer the potential to design organisms to address emerging needs in medicine, agriculture, industry, and defense. The field has seen rapid advances in technology, but it is difficult to gauge current capabilities or identify gaps across projects. To this end, our foundry was assessed via a timed "pressure test", in which 3 months were given to build organisms to produce 10 molecules unknown to us in advance. By applying a diversity of new approaches, we produced the desired molecule or a closely related one for six out of 10 targets during the performance period and made advances toward production of the others as well. Specifically, we increased the titers of 1-hexadecanol, pyrrolnitrin, and pacidamycin D, found novel routes to the enediyne warhead underlying powerful antimicrobials, established a cell-free system for monoterpene production, produced an intermediate toward vincristine biosynthesis, and encoded 7802 individually retrievable pathways to 540 bisindoles in a DNA pool. Pathways to tetrahydrofuran and barbamide were designed and constructed, but toxicity or analytical tools inhibited further progress. In sum, we constructed 1.2 Mb DNA, built 215 strains spanning five species (Saccharomyces cerevisiae, Escherichia coli, Streptomyces albidoflavus, Streptomyces coelicolor, and Streptomyces albovinaceus), established two cell-free systems, and performed 690 assays developed in-house for the molecules