Hepatic FoxOs link insulin signaling with plasma lipoprotein metabolism through an apolipoprotein M/sphingosine-1-phosphate pathway

Multiple beneficial cardiovascular effects of HDL depend on sphingosine-1-phosphate (S1P). S1P associates with HDL by binding to apolipoprotein M (ApoM). Insulin resistance is a major driver of dyslipidemia and cardiovascular risk. However, the mechanisms linking alterations in insulin signaling with plasma lipoprotein metabolism are incompletely understood. The insulin-repressible FoxO transcription factors mediate key effects of hepatic insulin action on glucose and lipoprotein metabolism. This work tested whether hepatic insulin signaling regulates HDL-S1P and aimed to identify the underlying molecular mechanisms. We report that insulin-resistant, nondiabetic individuals had decreased HDL-S1P levels, but no change in total plasma S1P. This also occurred in insulin-resistant db/db mice, which had low ApoM and a specific reduction of S1P in the HDL fraction, with no change in total plasma S1P levels. Using mice lacking hepatic FoxOs (L-FoxO1,3,4), we found that hepatic FoxOs were required for ApoM expression. Total plasma S1P levels were similar to those in controls, but S1P was nearly absent from HDL and was instead increased in the lipoprotein-depleted plasma fraction. This phenotype was restored to normal by rescuing ApoM in L-FoxO1,3,4 mice. Our findings show that insulin resistance in humans and mice is associated with decreased HDL-associated S1P. Our study shows that hepatic FoxO transcription factors are regulators of the ApoM/S1P pathway

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Hepatic FoxOs link insulin signaling with plasma lipoprotein metabolism through an apolipoprotein M/sphingosine-1-phosphate pathway

Multiple beneficial cardiovascular effects of HDL depend on sphingosine-1-phosphate (S1P). S1P associates with HDL by binding to apolipoprotein M (ApoM). Insulin resistance is a major driver of dyslipidemia and cardiovascular risk. However, the mechanisms linking alterations in insulin signaling with plasma lipoprotein metabolism are incompletely understood. The insulin-repressible FoxO transcription factors mediate key effects of hepatic insulin action on glucose and lipoprotein metabolism. This work tested whether hepatic insulin signaling regulates HDL-S1P and aimed to identify the underlying molecular mechanisms. We report that insulin-resistant, nondiabetic individuals had decreased HDL-S1P levels, but no change in total plasma S1P. This also occurred in insulin-resistant db/db mice, which had low ApoM and a specific reduction of S1P in the HDL fraction, with no change in total plasma S1P levels. Using mice lacking hepatic FoxOs (L-FoxO1,3,4), we found that hepatic FoxOs were required for ApoM expression. Total plasma S1P levels were similar to those in controls, but S1P was nearly absent from HDL and was instead increased in the lipoprotein-depleted plasma fraction. This phenotype was restored to normal by rescuing ApoM in L-FoxO1,3,4 mice. Our findings show that insulin resistance in humans and mice is associated with decreased HDL-associated S1P. Our study shows that hepatic FoxO transcription factors are regulators of the ApoM/S1P pathway.</p

sPlotOpen - An environmentally balanced, open-access, global dataset of vegetation plots

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called 'sPlot', compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01-40,000 m(2). Time period and grain 1888-2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked

A community-driven global reconstruction of human metabolism

Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ~2× more reactions and ~1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type–specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/

Characterization of the First “Candidatus Nitrotoga” Isolate Reveals Metabolic Versatility and Separate Evolution of Widespread Nitrite-Oxidizing Bacteria

Nitrification is a key process of the biogeochemical nitrogen cycle and of biological wastewater treatment. The second step, nitrite oxidation to nitrate, is catalyzed by phylogenetically diverse, chemolithoautotrophic nitrite-oxidizing bacteria (NOB). Uncultured NOB from the genus “Candidatus Nitrotoga” are widespread in natural and engineered ecosystems. Knowledge about their biology is sparse, because no genomic information and no pure “Ca. Nitrotoga” culture was available. Here we obtained the first “Ca. Nitrotoga” isolate from activated sludge. This organism, “Candidatus Nitrotoga fabula,” prefers higher temperatures (>20°C; optimum, 24 to 28°C) than previous “Ca. Nitrotoga” enrichments, which were described as cold-adapted NOB. “Ca. Nitrotoga fabula” also showed an unusually high tolerance to nitrite (activity at 30 mM NO2−) and nitrate (up to 25 mM NO3−). Nitrite oxidation followed Michaelis-Menten kinetics, with an apparent Km (Km(app)) of ~89 µM nitrite and a Vmax of ~28 µmol of nitrite per mg of protein per h. Key metabolic pathways of “Ca. Nitrotoga fabula” were reconstructed from the closed genome. “Ca. Nitrotoga fabula” possesses a new type of periplasmic nitrite oxidoreductase belonging to a lineage of mostly uncharacterized proteins. This novel enzyme indicates (i) separate evolution of nitrite oxidation in “Ca. Nitrotoga” and other NOB, (ii) the possible existence of phylogenetically diverse, unrecognized NOB, and (iii) together with new metagenomic data, the potential existence of nitrite-oxidizing archaea. For carbon fixation, “Ca. Nitrotoga fabula” uses the Calvin-Benson-Bassham cycle. It also carries genes encoding complete pathways for hydrogen and sulfite oxidation, suggesting that alternative energy metabolisms enable “Ca. Nitrotoga fabula” to survive nitrite depletion and colonize new niches. IMPORTANCE: Nitrite-oxidizing bacteria (NOB) are major players in the biogeochemical nitrogen cycle and critical for wastewater treatment. However, most NOB remain uncultured, and their biology is poorly understood. Here, we obtained the first isolate from the environmentally widespread NOB genus “Candidatus Nitrotoga” and performed a detailed physiological and genomic characterization of this organism (“Candidatus Nitrotoga fabula”). Differences between key phenotypic properties of “Ca. Nitrotoga fabula” and those of previously enriched “Ca. Nitrotoga” members reveal an unexpectedly broad range of physiological adaptations in this genus. Moreover, genes encoding components of energy metabolisms outside nitrification suggest that “Ca. Nitrotoga” are ecologically more flexible than previously anticipated. The identification of a novel nitrite-oxidizing enzyme in “Ca. Nitrotoga fabula” expands our picture of the evolutionary history of nitrification and might lead to discoveries of novel nitrite oxidizers. Altogether, this study provides urgently needed insights into the biology of understudied but environmentally and biotechnologically important microorganisms.© 2018 Kitzinger et a