HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search.

Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

Cost-effectiveness of Vitamin A supplementation among children in three sub-Saharan African countries: An individual-based simulation model using estimates from Global Burden of Disease 2019.

BACKGROUND: Vitamin A Supplementation (VAS) is a cost-effective intervention to decrease mortality associated with measles and diarrheal diseases among children aged 6-59 months in low-income countries. Recently, experts have suggested that other interventions like large-scale food fortification and increasing the coverage of measles vaccination might provide greater impact than VAS. In this study, we conducted a cost-effectiveness analysis of a VAS scale-up in three sub-Saharan African countries. METHODS: We developed an individual-based microsimulation using the Vivarium simulation framework to estimate the cost and effect of scaling up VAS from 2019 to 2023 in Nigeria, Kenya, and Burkina Faso, three countries with different levels of baseline coverage. We calibrated the model with disease and risk factor estimates from the Global Burden of Disease 2019 (GBD 2019). We obtained baseline coverage, intervention effects, and costs from a systematic review. After the model was validated against GBD inputs, we modeled an alternative scenario where we scaled-up VAS coverage from 2019 to a level that halved the exposure to lack of VAS in 2023. Based on the simulation outputs for DALYs averted and intervention cost, we determined estimates for the incremental cost-effectiveness ratio (ICER) in USD/DALY. FINDINGS: Our estimates for ICER are as follows: $860/DALY [95% UI; 320, 3530] in Nigeria, $550/DALY [240, 2230] in Kenya, and $220/DALY [80, 2470] in Burkina Faso. Examining the data for DALYs averted for the three countries over the time span, we found that the scale-up led to 21 [5, 56] DALYs averted per 100,000 person-years in Nigeria, 21 [5, 47] DALYs averted per 100,000 person-years in Kenya, and 14 [0, 37] DALYs averted per 100,000 person-years in Burkina Faso. CONCLUSIONS: VAS may no longer be as cost-effective in low-income regions as it has been previously. Updated estimates in GBD 2019 for the effect of Vitamin A Deficiency on causes of death are an additional driver of this lower estimate of cost-effectiveness.