Nothing in Evolution Makes Sense Except in the Light of Genomics: Read-Write Genome Evolution as an Active Biological Process

The mega-evolution of life with its three memory systems depends on sender-receiver communication and problem-solving. A narrative review

It should be the ultimate goal of any theory of evolution to delineate the contours of an integrative system to answer the question: How does life (in all its complexity) evolve (which can be called mega-evolution)? But how to plausibly define 'life'? My answer (1994-2023) is: 'life' sounds like a noun, but denotes an activity, and thus is a verb. Life (L) denotes nothing else than the total sum (∑) of all acts of communication (transfer of information) (C) executed by any type of senders-receivers at all their levels (up to at least 15) of compartmental organization: L = ∑C. The 'communicating compartment' is better suited to serve as the universal unit of structure, function and evolution than the cell, the smallest such unit. By paying as much importance to communication activity as to the Central Dogma of molecular biology, a wealth of new insights unfold. The major ones are as follows. (1) Living compartments have not only a genetic memory (DNA), but also a still enigmatic cognitive and an electrical memory system (and thus a triple memory system). (2) Complex compartments can have up to three types of progeny: genetic descendants/children, pupils/learners and electricians. (3) Of particular importance to adaptation, any act of communication is a problem-solving act because all messages need to be decoded. Hence through problem-solving that precedes selection, life itself is the driving force of its own evolution (a very clever but counterintuitive and unexpected logical deduction). Perhaps, this is the 'vital force' philosopher and Nobel laureate (in 1927) Henri Bergson searched for but did not find.

The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

Advances in genomics and transcriptomics accompanying the rapid accumulation of omics data have provided new tools that have transformed and expanded the traditional concepts of model fungi. Evolutionary genomics and transcriptomics have flourished with the use of classical and newer fungal models that facilitate the study of diverse topics encompassing fungal biology and development. Technological advances have also created the opportunity to obtain and mine large datasets. One such continuously growing dataset is that of the Sordariomycetes, which exhibit a richness of species, ecological diversity, economic importance, and a profound research history on amenable models. Currently, 3,574 species of this class have been sequenced, comprising nearly one-third of the available ascomycete genomes. Among these genomes, multiple representatives of the model genera Fusarium, Neurospora, and Trichoderma are present. In this review, we examine recently published studies and data on the Sordariomycetes that have contributed novel insights to the field of fungal evolution via integrative analyses of the genetic, pathogenic, and other biological characteristics of the fungi. Some of these studies applied ancestral state analysis of gene expression among divergent lineages to infer regulatory network models, identify key genetic elements in fungal sexual development, and investigate the regulation of conidial germination and secondary metabolism. Such multispecies investigations address challenges in the study of fungal evolutionary genomics derived from studies that are often based on limited model genomes and that primarily focus on the aspects of biology driven by knowledge drawn from a few model species. Rapidly accumulating information and expanding capabilities for systems biological analysis of Big Data are setting the stage for the expansion of the concept of model systems from unitary taxonomic species/genera to inclusive clusters of well-studied models that can facilitate both the in-depth study of specific lineages and also investigation of trait diversity across lineages. The Sordariomycetes class, in particular, offers abundant omics data and a large and active global research community. As such, the Sordariomycetes can form a core omics clade, providing a blueprint for the expansion of our knowledge of evolution at the genomic scale in the exciting era of Big Data and artificial intelligence, and serving as a reference for the future analysis of different taxonomic levels within the fungal kingdom.

Reconfiguring SETI in the microbial context: Panspermia as a solution to Fermi's paradox

All SETI (Search for Extraterrestrial Intelligence) programmes that were conceived and put into practice since the 1960s have been based on anthropocentric ideas concerning the definition of intelligence on a cosmic-wide scale. Brain-based neuronal intelligence, augmented by AI, are currently thought of as being the only form of intelligence that can engage in SETI-type interactions, and this assumption is likely to be connected with the dilemma of the famous Fermi paradox. We argue that high levels of intelligence and cognition inherent in ensembles of bacteria are much more likely to be the dominant form of cosmic intelligence, and the transfer of such intelligence is enabled by the processes of panspermia. We outline the main principles of bacterial intelligence, and how this intelligence may be used by the planetary-scale bacterial system, or the bacteriosphere, through processes of biological tropism, to connect to any extra-terrestrial microbial forms, independently of human interference.

Non-Random Genome Editing and Natural Cellular Engineering in Cognition-Based Evolution

Neo-Darwinism presumes that biological variation is a product of random genetic replication errors and natural selection. Cognition-Based Evolution (CBE) asserts a comprehensive alternative approach to phenotypic variation and the generation of biological novelty. In CBE, evolutionary variation is the product of natural cellular engineering that permits purposive genetic adjustments as cellular problem-solving. CBE upholds that the cornerstone of biology is the intelligent measuring cell. Since all biological information that is available to cells is ambiguous, multicellularity arises from the cellular requirement to maximize the validity of available environmental information. This is best accomplished through collective measurement purposed towards maintaining and optimizing individual cellular states of homeorhesis as dynamic flux that sustains cellular equipoise. The collective action of the multicellular measurement and assessment of information and its collaborative communication is natural cellular engineering. Its yield is linked cellular ecologies and mutualized niche constructions that comprise biofilms and holobionts. In this context, biological variation is the product of collective differential assessment of ambiguous environmental cues by networking intelligent cells. Such concerted action is enabled by non-random natural genomic editing in response to epigenetic impacts and environmental stresses. Random genetic activity can be either constrained or deployed as a 'harnessing of stochasticity'. Therefore, genes are cellular tools. Selection filters cellular solutions to environmental stresses to assure continuous cellular-organismal-environmental complementarity. Since all multicellular eukaryotes are holobionts as vast assemblages of participants of each of the three cellular domains (Prokaryota, Archaea, Eukaryota) and the virome, multicellular variation is necessarily a product of co-engineering among them.

What are the principles that govern life?

We know that living matter must behave in accordance with the universal laws of physics and chemistry. However, these laws are insufficient to explain the specific characteristics of the vital phenomenon and, therefore, we need new principles, intrinsic to biology, which are the basis for developing a theoretical framework for understanding life. Here I propose what I call the seven commandments of life (the Vital Order, the Principle of Inexorability, the reformulated Central Dogma, the Tyranny of Time, the Evolutionary Imperative, the Conservative Rule, the Cooperating Thrust) as a set of principles that help us explain the vital phenomenon from an evolutionary perspective. In a metaphorical way, we can consider life like an endless race in which living beings are the runners, who are changing as the race goes on (the evolutionary process), and the commandments the rules.

Living Organisms Author Their Read-Write Genomes in Evolution

Evolutionary variations generating phenotypic adaptations and novel taxa resulted from complex cellular activities altering genome content and expression: (i) Symbiogenetic cell mergers producing the mitochondrion-bearing ancestor of eukaryotes and chloroplast-bearing ancestors of photosynthetic eukaryotes; (ii) interspecific hybridizations and genome doublings generating new species and adaptive radiations of higher plants and animals; and, (iii) interspecific horizontal DNA transfer encoding virtually all of the cellular functions between organisms and their viruses in all domains of life. Consequently, assuming that evolutionary processes occur in isolated genomes of individual species has become an unrealistic abstraction. Adaptive variations also involved natural genetic engineering of mobile DNA elements to rewire regulatory networks. In the most highly evolved organisms, biological complexity scales with "non-coding" DNA content more closely than with protein-coding capacity. Coincidentally, we have learned how so-called "non-coding" RNAs that are rich in repetitive mobile DNA sequences are key regulators of complex phenotypes. Both biotic and abiotic ecological challenges serve as triggers for episodes of elevated genome change. The intersections of cell activities, biosphere interactions, horizontal DNA transfers, and non-random Read-Write genome modifications by natural genetic engineering provide a rich molecular and biological foundation for understanding how ecological disruptions can stimulate productive, often abrupt, evolutionary transformations.

Evolutionary epistemology: Reviewing and reviving with new data the research programme for distributed biological intelligence

Numerous studies in microbiology, eukaryotic cell biology, plant biology, biomimetics, synthetic biology, and philosophy of science appear to support the principles of the epistemological theory inspired by evolution, also known as "Evolutionary Epistemology", or EE. However, that none of the studies acknowledged EE suggests that its principles have not been formulated with sufficient clarity and depth to resonate with the interests of the empirical research community. In this paper I review evidence in favor of EE, and also reformulate EE principles to better inform future research. The revamped programme may be tentatively called Research Programme for Distributed Biological Intelligence. Intelligence I define as the capacity of organisms to gain information about their environment, process that information internally, and translate it into phenotypic forms. This multistage progression may be expressed through the acronym IGPT (information-gain-process-translate). The key principles of the programme may be summarized as follows. (i) Intelligence, a universal biological phenomenon promoting individual fitness, is required for effective organism-environment interactions. Given that animals represent less than 0.01% of the planetary biomass, neural intelligence is not the evolutionary norm. (ii) The basic unit of intelligence is a single cell prokaryote. All other forms of intelligence are derived. (iii) Intelligence is hierarchical. It ranges from bacteria to the biosphere or Gaia. (iv) The concept of "information" acquires a new meaning because information processing is at the heart of biological intelligence. All biological systems, from bacteria to Gaia, are intelligent, open thermodynamic systems that exchange information, matter and energy with the environment. (v) The organism-environment interaction is cybernetic. As much as the organism changes due to the influence of the environment, the organism's responses to induced changes affect the environment and subsequent organism-environment interactions. Based on the above principles a new research agenda can be formulated to explore different forms of biological intelligence.

Cultural macroevolution matters

Evolutionary thinking can be applied to both cultural microevolution and macroevolution. However, much of the current literature focuses on cultural microevolution. In this article, we argue that the growing availability of large cross-cultural datasets facilitates the use of computational methods derived from evolutionary biology to answer broad-scale questions about the major transitions in human social organization. Biological methods can be extended to human cultural evolution. We illustrate this argument with examples drawn from our recent work on the roles of Big Gods and ritual human sacrifice in the evolution of large, stratified societies. These analyses show that, although the presence of Big Gods is correlated with the evolution of political complexity, in Austronesian cultures at least, they do not play a causal role in ratcheting up political complexity. In contrast, ritual human sacrifice does play a causal role in promoting and sustaining the evolution of stratified societies by maintaining and legitimizing the power of elites. We briefly discuss some common objections to the application of phylogenetic modeling to cultural evolution and argue that the use of these methods does not require a commitment to either gene-like cultural inheritance or to the view that cultures are like vertebrate species. We conclude that the careful application of these methods can substantially enhance the prospects of an evolutionary science of human history.

Diversity and Evolutionary Analysis of Iron-Containing (Type-III) Alcohol Dehydrogenases in Eukaryotes

BACKGROUND

Alcohol dehydrogenase (ADH) activity is widely distributed in the three domains of life. Currently, there are three non-homologous NAD(P)+-dependent ADH families reported: Type I ADH comprises Zn-dependent ADHs; type II ADH comprises short-chain ADHs described first in Drosophila; and, type III ADH comprises iron-containing ADHs (FeADHs). These three families arose independently throughout evolution and possess different structures and mechanisms of reaction. While types I and II ADHs have been extensively studied, analyses about the evolution and diversity of (type III) FeADHs have not been published yet. Therefore in this work, a phylogenetic analysis of FeADHs was performed to get insights into the evolution of this protein family, as well as explore the diversity of FeADHs in eukaryotes.

PRINCIPAL FINDINGS

Results showed that FeADHs from eukaryotes are distributed in thirteen protein subfamilies, eight of them possessing protein sequences distributed in the three domains of life. Interestingly, none of these protein subfamilies possess protein sequences found simultaneously in animals, plants and fungi. Many FeADHs are activated by or contain Fe2+, but many others bind to a variety of metals, or even lack of metal cofactor. Animal FeADHs are found in just one protein subfamily, the hydroxyacid-oxoacid transhydrogenase (HOT) subfamily, which includes protein sequences widely distributed in fungi, but not in plants), and in several taxa from lower eukaryotes, bacteria and archaea. Fungi FeADHs are found mainly in two subfamilies: HOT and maleylacetate reductase (MAR), but some can be found also in other three different protein subfamilies. Plant FeADHs are found only in chlorophyta but not in higher plants, and are distributed in three different protein subfamilies.

CONCLUSIONS/SIGNIFICANCE

FeADHs are a diverse and ancient protein family that shares a common 3D scaffold with a patchy distribution in eukaryotes. The majority of sequenced FeADHs from eukaryotes are distributed in just two subfamilies, HOT and MAR (found mainly in animals and fungi). These two subfamilies comprise almost 85% of all sequenced FeADHs in eukaryotes.