Evidence map›Paper›PMID 33809046›Full record

ArticleLife (Basel, Switzerland)2021

Classification of the Biogenicity of Complex Organic Mixtures for the Detection of Extraterrestrial Life.

Nicholas Guttenberg, Huan Chen, Tomohiro Mochizuki, H James Cleaves

Erratum issuedAbstract read
In one paragraph

Article in Life (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Molecular assembly as a universal biosignature measurable by mass spectrometry.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Organic geochemical evidence for life in Archean rocks identified by pyrolysis-GC-MS and supervised machine learning.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. Article
  4. A robust, agnostic molecular biosignature based on machine learning.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Nicholas GuttenbergEarth-Life Science Institute, Tokyo Institute of Technology, Ookayama, Tokyo 152-8550, Japan.
Huan ChenNational High Magnetic Field Laboratory, Florida State University, 1800 East Paul Dirac Drive, Tallahassee, FL 32310-4005, USA.ORCID 0000-0002-6032-6569
Tomohiro MochizukiEarth-Life Science Institute, Tokyo Institute of Technology, Ookayama, Tokyo 152-8550, Japan.ORCID 0000-0002-9096-6620
H James CleavesEarth-Life Science Institute, Tokyo Institute of Technology, Ookayama, Tokyo 152-8550, Japan.

Funding

Japan Society for the Promotion of Science JP26106003John Templeton Foundation ELSI Origins NetworkNational Science Foundation DMR 1157490, DMR-1644779
6 · The paper itself

Abstract

Searching for life in the Universe depends on unambiguously distinguishing biological features from background signals, which could take the form of chemical, morphological, or spectral signatures. The discovery and direct measurement of organic compounds unambiguously indicative of extraterrestrial (ET) life is a major goal of Solar System exploration. Biology processes matter and energy differently from abiological systems, and materials produced by biological systems may become enriched in planetary environments where biology is operative. However, ET biology might be composed of different components than terrestrial life. As ET sample return is difficult, in situ methods for identifying biology will be useful. Mass spectrometry (MS) is a potentially versatile life detection technique, which will be used to analyze numerous Solar System environments in the near future. We show here that simple algorithmic analysis of MS data from abiotic synthesis (natural and synthetic), microbial cells, and thermally processed biological materials (lab-grown organisms and petroleum) easily identifies relational organic compound distributions that distinguish pristine and aged biological and abiological materials, which likely can be attributed to the types of compounds these processes produce, as well as how they are formed and decompose. To our knowledge this is the first comprehensive demonstration of the utility of this analytical technique for the detection of biology. This method is independent of the detection of particular masses or molecular species samples may contain. This suggests a general method to agnostically detect evidence of biology using MS given a sufficiently strong signal in which the majority of the material in a sample has either a biological or abiological origin. Such metrics are also likely to be useful for studies of possible emergent living phenomena, and paleobiological samples.

Indexed as

astrobiologybiosignaturescomplexitylife detectionmachine learningmass spectrometryprebiotic chemistry

Identifiers

PMID33809046
PMCPMC8001260

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.