Evidence map›Paper›PMID 39185172›Full record

ArticlebioRxiv : the preprint server for biology2024

Microbial reaction rate estimation using proteins and proteomes.

J Scott P McCain, Gregory L Britten, Sean R Hackett, Michael J Follows, Gene-Wei Li

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

J Scott P McCainDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0001-8437-1420
Gregory L BrittenDepartment of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0003-1391-9086
Sean R HackettCalico Life Sciences LLC, San Francisco, CA, USA.ORCID 0000-0002-9553-4341
Michael J FollowsDepartment of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
Gene-Wei LiDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.

Funding

Evolution and Regulation of Bacterial Proteome CompositionR35GM124732 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Gene-Wei Li · 2017 to 2026
$3.8M
NIGMS NIH HHS R35 GM124732
6 · The paper itself

Abstract

Microbes transform their environments using diverse enzymatic reactions. However, it remains challenging to measure microbial reaction rates in natural environments. Despite advances in global quantification of enzyme abundances, the individual relationships between enzyme abundances and their reaction rates have not been systematically examined. Using matched proteomic and reaction rate data from microbial cultures, we show that enzyme abundance is often insufficient to predict its corresponding reaction rate. However, we discovered that global proteomic measurements can be used to make accurate rate predictions of individual reaction rates (median

Identifiers

PMID39185172
PMCPMC11343155

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.