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Record W2753063766 · doi:10.17975/sfj-2017-012

A simulated metagenomic analysis of the gut microbiota of Anorexia Nervosa patients using PICRUSt

2017· article· en· W2753063766 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSTEM Fellowship Journal · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsPropionateMetagenomicsBiologyBiochemistry

Abstract

fetched live from OpenAlex

Introduction Mack et al. (2016) studied the fecal bacteria and archaea of 55 European normal-weight participants (NW), 55 European patients with anorexia nervosa (ANT1), and 44 ANT1 patients following a body mass index increase (ANT2). Spreadsheets of identified microbes and their relative abundance per patient were uploaded to the EBI Metagenomics web server by Mack et al. We aimed to further study the functions of the identified microbes using the PICUSt algorithm (Langille, 2013) and see if these functions are consistent with published literature. Methods Spreadsheets were downloaded from EBI Metagenomics (Project# ERP012549) in JSON Biom format and uploaded to a Galaxy cloud server hosting PICRUSt. All data transformations can be viewed at http://huttenhower.sph.harvard.edu/galaxy/u/farhaansgroup/h/anorexi-astem-2017 . Transformed datasets were downloaded, appended with a .biom file extension, converted to the SPF format using STAMP v2.1.3 (Parks, 2014), and merged into a single file using Microsoft Excel for analysis with STAMP. Differences in propionate metabolism between ANT1, ANT2, and NW samples was chosen for further study. Results & Discussion The proportion of propionate metabolism genes was not significantly different between ANT1 and NW samples (p=0.08), but was different between ANT2 and NW samples (p=0.01) using a pair-wise Welsh’s t-test (0.95 CI) with a Storey FDR multiple test correction. In comparison, Mack et al, detected no differences in propionate concentration between AN and NW fecal samples using gas chromatography while Morito et al (2015) found lower concentrations of propionate in Japanese AN versus NW fecal samples using liquid chromatography. Our discrepancy with Mack et al could have arisen since PICRUSt cannot analyze the genes of eukaryotes, PICRUSt is limited by the depth and breadth of the gene annotations in the KEGG database, and our experimental setup cannot provide data on gene expression. Moreover, 18% of V4 16S rRNA DNA sequences could not be matched to any bacteria or archaea by EBI Metagenomics. In conclusion, while in silico experiments can be useful to predict microbial functions in a sample, in this case, our PICRUSt-based hypothesis that fecal samples from Mack et al would have different concentrations of propionate between AN and NW samples was not borne out by Mack et al’s chromatography experiments. Nonetheless, the conflicting findings between us, Mack et al, and Morito et al warrants further research on whether microbes mediate carbohydrate metabolism differently in patients with a history of anorexia nervosa versus controls.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.290
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it