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      Optimum ratio of dietary protein and carbohydrate that maximises lifespan is shared among related insect species

      1 , 2
      Aging Cell
      Wiley

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          Abstract

          Animals often regulate the intake and quantity of nutrients to maximise fitness through life‐history traits such as lifespan, but we still lack a proper understanding of how specific nutrients influence these traits. Here, I developed an algorithm which allowed me to create a nutrient‐specific database from literature data, and investigated how the requirements of protein (P) and carbohydrate (C) needed to maximise lifespan evolved across nine insect species. I found moderate evidence of a phylogenetic signal on the optimal ratio of protein to carbohydrate ratio (PC ratio) that maximised lifespan, suggesting that optimal PC ratio for lifespan could have evolved non‐independently among related species. I also found evidence for weak‐to‐strong sex‐specific optimal PC ratios for lifespan, suggesting that sex‐specific nutritional needs to maximise lifespan can emerge and persist in some species. Although limited in the number of species, the approach adopted here is portable to experiments with number of nutrients and, thus, can be used in complex comparative precision nutrition studies for insights into the evolution of animal nutrition.

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          phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

          Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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                Author and article information

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                Journal
                Aging Cell
                Aging Cell
                Wiley
                1474-9718
                1474-9726
                December 13 2023
                Affiliations
                [1 ] Institute of Mathematics, University of Aberdeen, King's College Aberdeen UK
                [2 ] Programa de Pós‐graduação em Ecologia e Conservação Universidade Federal do Paraná Curitiba Brazil
                Article
                10.1111/acel.14067
                c416f8f5-109b-4ed0-a8b9-0d0f260c5d7b
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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