Evidence map›Paper›PMID 40198222›Full record

ArticleCell reports2025

Quantifying the evolutionary paths to endomembranes.

Paul E Schavemaker, Michael Lynch

Abstract read
In one paragraph

Article in Cell reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Energetics and evolution: Response to Martin.Biochimica et biophysica acta. Bioenergetics · 2026
    Article
  3. Quantifying the fitness contribution of phagocytosis.bioRxiv : the preprint server for biology · 2025
    Article
  4. Article
  5. Bioenergetics and the Evolution of Cellular Traits.Annual review of biophysics · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Paul E SchavemakerBiodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA. Electronic address: pschavem@asu.edu.
Michael LynchBiodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA.

Funding

Causes and Population-genetic Consequences of Molecular VariationR35GM122566 · NIGMS · TRUSTEES OF INDIANA UNIVERSITY · PI Michael R LYNCH · 2017 to 2026
$7.7M
NIGMS NIH HHS R35 GM122566
6 · The paper itself

Abstract

Eukaryotes exhibit a complex and dynamic internal meshwork of membranes-the endomembrane system-used to insert membrane proteins and ingest food. Verbal models explaining the origin of endomembranes abound, but quantitative considerations of fitness are lacking. Drawing on quantitative data on endomembranes allows for the derivation of two biologically grounded analytical models of endomembrane evolution that quantify organismal fitness: (1) vesicle-based uptake of small nutrient molecules, pinocytosis, and (2) vesicle-based insertion of membrane proteins, proto-endoplasmic reticulum. Surprisingly, pinocytosis of small-molecule nutrients does not provide a net fitness gain under biologically sensible parameter ranges, explaining why pinocytosis is primarily used for protein uptake in contemporary organisms. The proto-endoplasmic reticulum does provide net fitness gains, making it the more likely candidate for initiating the endomembrane system. With modifications, the approach developed here can be used more generally to understand the present-day endomembrane system and illuminate the origin of the eukaryotic cell.

Indexed as

Biological EvolutionCell MembraneIntracellular MembranesAnimalsEndoplasmic ReticulumMembrane ProteinsModels, BiologicalMembrane ProteinsCP: Cell biologyendomembranesendoplasmic reticulumeukaryogenesisevolutionary cell biologyfitnesspinocytosis

Identifiers

PMID40198222
PMCPMC12124869

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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.