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The Lipomyces clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of Lipomyces starkeyi NRRL Y-11557 was built using orthologous protein mappings to model yeast species. Phenotypic growth assays were used to validate the GSM (66% accuracy) and indicated that NRRL Y-11557 utilized diverse carbohydrates but had more limited catabolism of organic acids. The final GSM contained 2,193 reactions, 1,909 metabolites, and 996 genes and was thus named iLst996. The model contained 96 of the annotated carbohydrate-active enzymes. iLst996 predicted a flux distribution in line with oleaginous yeast measurements and was utilized to predict theoretical lipid yields. Twenty-five other yeasts in the Lipomyces clade were then genome sequenced and annotated. Sixteen of the Lipomyces species had orthologs for more than 97% of the iLst996 genes, demonstrating the usefulness of iLst996 as a broad GSM for Lipomyces metabolism. Pathways that diverged from iLst996 mainly revolved around alternate carbon metabolism, with ortholog groups excluding NRRL Y-11557 annotated to be involved in transport, glycerolipid, and starch metabolism, among others. Overall, this study provides a useful modeling tool and data for analyzing and understanding Lipomyces species metabolism and will assist further engineering efforts in Lipomyces.

Uncertainty rises in recessions and falls in booms. But what is the causal relationship? We construct cross-country panel data on stock market returns to proxy for first- and second-moment shocks and instrument these with natural disasters, terrorist attacks, and political shocks. Our IV regression results reveal a robust negative short-term impact of second moments (uncertainty) on growth. Employing multiple vector autoregression estimation approaches, relying on a range of identifying assumptions, also reveals a negative impact of uncertainty on growth. Finally, we show that these results are reproducible in a conventional micro–macro business cycle model with time-varying uncertainty. [ABSTRACT FROM AUTHOR]

More than two-thirds of middle school students do not read proficiently. Research has shown that targeted interventions using explicit instruction methods can improve reading outcomes for struggling readers. A central feature of explicit instruction is the systematic implementation of instructional interactions, but it is not clear what specific instructional interaction practices lead to stronger outcomes for middle school readers. This study used a regression discontinuity design to compare the frequency and impact of instructional interactions experienced by U.S. eighth-grade students who received a targeted reading intervention ( n = 1,461) with those who did not ( n = 4,292). Results indicated that students who received intervention experienced far more instructional interactions with their teachers than did students who did not. However, the association between rates of interaction and student need in the intervention group was minimal, and the relationship between the rate of instructional interactions and reading growth was mixed. Implications for intervening with struggling students in the middle grades are discussed., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Aspergillus terreus has attracted interest due to its application in industrial biotechnology, particularly for the production of itaconic acid and bioactive secondary metabolites. As related species also seem to possess a prosperous secondary metabolism, they are of high interest for genome mining and exploitation. Here, we present draft genome sequences for six species from Aspergillus section Terrei and one species from Aspergillus section Nidulantes . Whole-genome phylogeny confirmed that section Terrei is monophyletic. Genome analyses identified between 70 and 108 key secondary metabolism genes in each of the genomes of section Terrei , the highest rate found in the genus Aspergillus so far. The respective enzymes fall into 167 distinct families with most of them corresponding to potentially unique compounds or compound families. Moreover, 53% of the families were only found in a single species, which supports the suitability of species from section Terrei for further genome mining. Intriguingly, this analysis, combined with heterologous gene expression and metabolite identification, suggested that species from section Terrei use a strategy for UV protection different to other species from the genus Aspergillus . Section Terrei contains a complete plant polysaccharide degrading potential and an even higher cellulolytic potential than other Aspergilli, possibly facilitating additional applications for these species in biotechnology.