Evidence map›Paper›PMID 27261368›Full record

ReviewCellular and molecular life sciences : CMLS2017

Evolution of the archaeal and mammalian information processing systems: towards an archaeal model for human disease.

Zhe Lyu, William B Whitman

Abstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Dissection ofmBio · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
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.

Zhe LyuDepartment of Microbiology, University of Georgia, Athens, GA, 30602, USA.
William B WhitmanDepartment of Microbiology, University of Georgia, Athens, GA, 30602, USA. whitman@uga.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current evolutionary models suggest that Eukaryotes originated from within Archaea instead of being a sister lineage. To test this model of ancient evolution, we review recent studies and compare the three major information processing subsystems of replication, transcription and translation in the Archaea and Eukaryotes. Our hypothesis is that if the Eukaryotes arose within the archaeal radiation, their information processing systems will appear to be one of kind and not wholly original. Within the Eukaryotes, the mammalian or human systems are emphasized because of their importance in understanding health. Biochemical as well as genetic studies provide strong evidence for the functional similarity of archaeal homologs to the mammalian information processing system and their dissimilarity to the bacterial systems. In many independent instances, a simple archaeal system is functionally equivalent to more elaborate eukaryotic homologs, suggesting that evolution of complexity is likely an central feature of the eukaryotic information processing system. Because fewer components are often involved, biochemical characterizations of the archaeal systems are often easier to interpret. Similarly, the archaeal cell provides a genetically and metabolically simpler background, enabling convenient studies on the complex information processing system. Therefore, Archaea could serve as a parsimonious and tractable host for studying human diseases that arise in the information processing systems.

Indexed as

Biological EvolutionTranscription, GeneticAnimalsArchaeaDNA ReplicationHumansMammalsProtein BiosynthesisCancerGenomeHealthMedicineMethanococcusMutationProkaryoteTACK

Identifiers

PMID27261368
PMCPMC11107668

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.