Protein multiplicity: exemplifying an overwhelmingly likely pattern of molecular evolution?

Conservation of Hartley–Shannon Information (CoHSI) is a purely probabilistic, general theory of discrete systems. It is not a theory of evolution per se, but if it is correct, CoHSI can predict and help explain emergent patterns of macroevolution. In this study, we test both the falsifiability and utility of predictions from the CoHSI theory in the context of molecular evolution. First, we test whether CoHSI accurately predicts a heretofore unknown outcome of macroevolution, the distribution of protein multiplicity. Multiplicity is the occurrence identically of a protein in more than a single species (or species equivalent). We observe over 13 million multiplicious proteins, ranging from the highly conserved (including histones, components of photosystems, and the electron transport chain) to the rapidly evolving viral proteins that are involved in infection and adaptation to novel host species. CoHSI predicts that when considered globally across all three domains of life and the viruses, multiplicity will show a distinctive variant of the Zipfian distribution. We show that the predictions of the CoHSI theory are borne out to a high degree of statistical robustness for the multiplicious proteins of eukaryotes, bacteria, archaea, and viruses whether considered separately or in totality. Second, we test whether deviations from CoHSI predictions can be informative of underlying evolutionary processes. We show that observed perturbations of the CoHSI-predicted distribution are strongly associated with enterobacterial species in which rapid microevolution facilitated by the horizontal transfer of genes is prevalent.

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Publication Details

Journal
Academia Biology
Published
2024-10-31
DOI
https://doi.org/10.20935/acadbiol7396
Citations
3
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
Field-Weighted Citation Impact
0.70
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article

Protein multiplicity: exemplifying an overwhelmingly likely pattern of molecular evolution?

Les Hatton, Greg Warr
3 citations
Academia Biology
Microbial Metabolic Engineering and Bioproduction
0.70
article

Protein multiplicity: exemplifying an overwhelmingly likely pattern of molecular evolution?

Les Hatton, Greg Warr
article en
3 citations

Abstract

Conservation of Hartley–Shannon Information (CoHSI) is a purely probabilistic, general theory of discrete systems. It is not a theory of evolution per se, but if it is correct, CoHSI can predict and help explain emergent patterns of macroevolution. In this study, we test both the falsifiability and utility of predictions from the CoHSI theory in the context of molecular evolution. First, we test whether CoHSI accurately predicts a heretofore unknown outcome of macroevolution, the distribution of protein multiplicity. Multiplicity is the occurrence identically of a protein in more than a single species (or species equivalent). We observe over 13 million multiplicious proteins, ranging from the highly conserved (including histones, components of photosystems, and the electron transport chain) to the rapidly evolving viral proteins that are involved in infection and adaptation to novel host species. CoHSI predicts that when considered globally across all three domains of life and the viruses, multiplicity will show a distinctive variant of the Zipfian distribution. We show that the predictions of the CoHSI theory are borne out to a high degree of statistical robustness for the multiplicious proteins of eukaryotes, bacteria, archaea, and viruses whether considered separately or in totality. Second, we test whether deviations from CoHSI predictions can be informative of underlying evolutionary processes. We show that observed perturbations of the CoHSI-predicted distribution are strongly associated with enterobacterial species in which rapid microevolution facilitated by the horizontal transfer of genes is prevalent.

Academia BiologyVol. 2(4)
Medical University of South Carolina (US), Kingston University London (GB)
Zero hunger
Openalex Percentile: Top 29%
Microbial Metabolic Engineering and Bioproduction
0.70
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