Constructive Neutral Evolution 20 Years Later

Mutational biases favor complexity increases in protein interaction networks after gene duplication

Biological systems can gain complexity over time. While some of these transitions are likely driven by natural selection, the extent to which they occur without providing an adaptive benefit is unknown. At the molecular level, one example is heteromeric complexes replacing homomeric ones following gene duplication. Here, we build a biophysical model and simulate the evolution of homodimers and heterodimers following gene duplication using distributions of mutational effects inferred from available protein structures. We keep the specific activity of each dimer identical, so their concentrations drift neutrally without new functions. We show that for more than 60% of tested dimer structures, the relative concentration of the heteromer increases over time due to mutational biases that favor the heterodimer. However, allowing mutational effects on synthesis rates and differences in the specific activity of homo- and heterodimers can limit or reverse the observed bias toward heterodimers. Our results show that the accumulation of more complex protein quaternary structures is likely under neutral evolution, and that natural selection would be needed to reverse this tendency.

Emergence of an Orphan Nitrogenase Protein Following Atmospheric Oxygenation

Molecular innovations within key metabolisms can have profound impacts on element cycling and ecological distribution. Yet, much of the molecular foundations of early evolved enzymes and metabolisms are unknown. Here, we bring one such mystery to relief by probing the birth and evolution of the G-subunit protein, an integral component of certain members of the nitrogenase family, the only enzymes capable of biological nitrogen fixation. The G-subunit is a Paleoproterozoic-age orphan protein that appears more than 1 billion years after the origin of nitrogenases. We show that the G-subunit arose with novel nitrogenase metal dependence and the ecological expansion of nitrogen-fixing microbes following the transition in environmental metal availabilities and atmospheric oxygenation that began ∼2.5 billion years ago. We identify molecular features that suggest early G-subunit proteins mediated cofactor or protein interactions required for novel metal dependency, priming ancient nitrogenases and their hosts to exploit these newly diversified geochemical environments. We further examined the degree of functional specialization in G-subunit evolution with extant and ancestral homologs using laboratory reconstruction experiments. Our results indicate that permanent recruitment of the orphan protein depended on the prior establishment of conserved molecular features and showcase how contingent evolutionary novelties might shape ecologically important microbial innovations.

Euglena's atypical respiratory chain adapts to the discoidal cristae and flexible metabolism

Euglena gracilis, a model organism of the eukaryotic supergroup Discoba harbouring also clinically important parasitic species, possesses diverse metabolic strategies and an atypical electron transport chain. While structures of the electron transport chain complexes and supercomplexes of most other eukaryotic clades have been reported, no similar structure is currently available for Discoba, limiting the understandings of its core metabolism and leaving a gap in the evolutionary tree of eukaryotic bioenergetics. Here, we report high-resolution cryo-EM structures of Euglena's respirasome I + III2 + IV and supercomplex III2 + IV2. A previously unreported fatty acid synthesis domain locates on the tip of complex I's peripheral arm, providing a clear picture of its atypical subunit composition identified previously. Individual complexes are re-arranged in the respirasome to adapt to the non-uniform membrane curvature of the discoidal cristae. Furthermore, Euglena's conformationally rigid complex I is deactivated by restricting ubiquinone's access to its substrate tunnel. Our findings provide structural insights for therapeutic developments against euglenozoan parasite infections.

Four classic "de novo" genes all have plausible homologs and likely evolved from retro-duplicated or pseudogenic sequences

Despite being previously regarded as extremely unlikely, the idea that entirely novel protein-coding genes can emerge from non-coding sequences has gradually become accepted over the past two decades. Examples of "de novo origination", resulting in lineage-specific "orphan" genes, lacking coding orthologs, are now produced every year. However, many are likely cases of duplicates that are difficult to recognize. Here, I re-examine the claims and show that four very well-known examples of genes alleged to have emerged completely "from scratch"- FLJ33706 in humans, Goddard in fruit flies, BSC4 in baker's yeast and AFGP2 in codfish-may have plausible evolutionary ancestors in pre-existing genes. The first two are likely highly diverged retrogenes coding for regulatory proteins that have been misidentified as orphans. The antifreeze glycoprotein, moreover, may not have evolved from repetitive non-genic sequences but, as in several other related cases, from an apolipoprotein that could have become pseudogenized before later being reactivated. These findings detract from various claims made about de novo gene birth and show there has been a tendency not to invest the necessary effort in searching for homologs outside of a very limited syntenic or phylostratigraphic methodology. A robust approach is used for improving detection that draws upon similarities, not just in terms of statistical sequence analysis, but also relating to biochemistry and function, to obviate notable failures to identify homologs.

Moderating the neutralist-selectionist debate: exactly which propositions are we debating, and which arguments are valid?

Half a century after its foundation, the neutral theory of molecular evolution continues to attract controversy. The debate has been hampered by the coexistence of different interpretations of the core proposition of the neutral theory, the 'neutral mutation-random drift' hypothesis. In this review, we trace the origins of these ambiguities and suggest potential solutions. We highlight the difference between the original, the revised and the nearly neutral hypothesis, and re-emphasise that none of them equates to the null hypothesis of strict neutrality. We distinguish the neutral hypothesis of protein evolution, the main focus of the ongoing debate, from the neutral hypotheses of genomic and functional DNA evolution, which for many species are generally accepted. We advocate a further distinction between a narrow and an extended neutral hypothesis (of which the latter posits that random non-conservative amino acid substitutions can cause non-ecological phenotypic divergence), and we discuss the implications for evolutionary biology beyond the domain of molecular evolution. We furthermore point out that the debate has widened from its initial focus on point mutations, and also concerns the fitness effects of large-scale mutations, which can alter the dosage of genes and regulatory sequences. We evaluate the validity of neutralist and selectionist arguments and find that the tested predictions, apart from being sensitive to violation of underlying assumptions, are often derived from the null hypothesis of strict neutrality, or equally consistent with the opposing selectionist hypothesis, except when assuming molecular panselectionism. Our review aims to facilitate a constructive neutralist-selectionist debate, and thereby to contribute to answering a key question of evolutionary biology: what proportions of amino acid and nucleotide substitutions and polymorphisms are adaptive?

Why do hosts malfunction without microbes? Missing benefits versus evolutionary addiction

Microbes are widely recognized to be vital to host health. This new consensus rests, in part, on experiments showing how hosts malfunction when microbes are removed. More and more microbial dependencies are being discovered, even in fundamental processes such as development, immunity, physiology, and behavior. But why do they exist? The default explanation is that microbes are beneficial; when hosts lose microbes, they also lose benefits. Here I call attention to evolutionary addiction, whereby a host trait evolves a need for microbes without having been improved by them. Evolutionary addiction should be considered when interpreting microbe-removal experiments, as it is a distinct and potentially common process. Further, it may have unique implications for the evolution and stability of host-microbe interactions.

Coupling Cell Size Regulation and Proliferation Dynamics of C. glutamicum Reveals Cell Division Based on Surface Area

Single cells actively coordinate growth and division to regulate their size, yet how this size homeostasis at the single-cell level propagates over multiple generations to impact clonal expansion remains fundamentally unexplored. Classical timer models for cell proliferation (where the duration of the cell cycle is an independent variable) predict that the stochastic variation in colony size will increase monotonically over time. In stark contrast, implementing size control according to adder strategy (where on average a fixed size added from cell birth to division) leads to colony size variations that eventually decay to zero. While these results assume a fixed size of the colony-initiating progenitor cell, further analysis reveals that the magnitude of the intercolony variation in population number is sensitive to heterogeneity in the initial cell size. We validate these predictions by tracking the growth of isogenic microcolonies of Corynebacterium glutamicum in microfluidic chambers. Approximating their cell shape to a capsule, we observe that the degree of random variability in cell size is different depending on whether the cell size is quantified as per length, surface area, or volume, but size control remains an adder regardless of these size metrics. A comparison of the observed variability in the colony population with the predictions suggests that proliferation matches better with a cell division based on the cell surface. In summary, our integrated mathematical-experimental approach bridges the paradigms of single-cell size regulation and clonal expansion at the population levels. This innovative approach provides elucidation of the mechanisms of size homeostasis from the stochastic dynamics of colony size for rod-shaped microbes.

Robustness and complexity

When a system robustly corrects component-level errors, the direct pressure on component performance declines. Components become less reliable, maintain more genetic variability, or drift neutrally, creating new forms of complexity. Examples include the hourglass pattern of biological development and the hourglass architecture for robustly complex systems in engineering.

Scaling of Protein Function across the Tree of Life

Scaling laws are a powerful way to compare genomes because they put all organisms onto a single curve and reveal nontrivial generalities as genomes change in size. The abundance of functional categories across genomes has previously been found to show power law scaling with respect to the total number of functional categories, suggesting that universal constraints shape genomic category abundance. Here, we look across the tree of life to understand how genome evolution may be related to functional scaling. We revisit previous observations of functional genome scaling with an expanded taxonomy by analyzing 3,726 bacterial, 220 archaeal, and 79 unicellular eukaryotic genomes. We find that for some functional classes, scaling is best described by multiple exponents, revealing previously unobserved shifts in scaling as genome-encoded protein annotations increase or decrease. Furthermore, we find that scaling varies between phyletic groups at both the domain and phyla levels and is less universal than previously thought. This variability in functional scaling is not related to taxonomic phylogeny resolved at the phyla level, suggesting that differences in cell plan or physiology outweigh broad patterns of taxonomic evolution. Since genomes are maintained and replicated by the functional proteins encoded by them, these results point to functional degeneracy between taxonomic groups and unique evolutionary trajectories toward these. We also find that individual phyla frequently span scaling exponents of functional classes, revealing that individual clades can move across scaling exponents. Together, our results reveal unique shifts in functions across the tree of life and highlight that as genomes grow or shrink, proteins of various functions may be added or lost.

Lessons from the deep: mechanisms behind diversification of eukaryotic protein complexes

Genetic variation is the major mechanism behind adaptation and evolutionary change. As most proteins operate through interactions with other proteins, changes in protein complex composition and subunit sequence provide potentially new functions. Comparative genomics can reveal expansions, losses and sequence divergence within protein-coding genes, but in silico analysis cannot detect subunit substitutions or replacements of entire protein complexes. Insights into these fundamental evolutionary processes require broad and extensive comparative analyses, from both in silico and experimental evidence. Here, we combine data from both approaches and consider the gamut of possible protein complex compositional changes that arise during evolution, citing examples of complete conservation to partial and total replacement by functional analogues. We focus in part on complexes in trypanosomes as they represent one of the better studied non-animal/non-fungal lineages, but extend insights across the eukaryotes by extensive comparative genomic analysis. We argue that gene loss plays an important role in diversification of protein complexes and hence enhancement of eukaryotic diversity.

Phenotype Design Space Provides a Mechanistic Framework Relating Molecular Parameters to Phenotype Diversity Available for Selection

Two long-standing challenges in theoretical population genetics and evolution are predicting the distribution of phenotype diversity generated by mutation and available for selection, and determining the interaction of mutation, selection and drift to characterize evolutionary equilibria and dynamics. More fundamental for enabling such predictions is the current inability to causally link genotype to phenotype. There are three major mechanistic mappings required for such a linking - genetic sequence to kinetic parameters of the molecular processes, kinetic parameters to biochemical system phenotypes, and biochemical phenotypes to organismal phenotypes. This article introduces a theoretical framework, the Phenotype Design Space (PDS) framework, for addressing these challenges by focusing on the mapping of kinetic parameters to biochemical system phenotypes. It provides a quantitative theory whose key features include (1) a mathematically rigorous definition of phenotype based on biochemical kinetics, (2) enumeration of the full phenotypic repertoire, and (3) functional characterization of each phenotype independent of its context-dependent selection or fitness contributions. This framework is built on Design Space methods that relate system phenotypes to genetically determined parameters and environmentally determined variables. It also has the potential to automate prediction of phenotype-specific mutation rate constants and equilibrium distributions of phenotype diversity in microbial populations undergoing steady-state exponential growth, which provides an ideal reference to which more realistic cases can be compared. Although the framework is quite general and flexible, the details will undoubtedly differ for different functions, organisms and contexts. Here a hypothetical case study involving a small molecular system, a primordial circadian clock, is used to introduce this framework and to illustrate its use in a particular case. The framework is built on fundamental biochemical kinetics. Thus, the foundation is based on linear algebra and reasonable physical assumptions, which provide numerous opportunities for experimental testing and further elaboration to deal with complex multicellular organisms that are currently beyond its scope. The discussion provides a comparison of results from the PDS framework with those from other approaches in theoretical population genetics.

The persistent homology of mitochondrial ATP synthases

Relatively little is known about ATP synthase structure in protists, and the investigated ones exhibit divergent structures distinct from yeast or animals. To clarify the subunit composition of ATP synthases across all eukaryotic lineages, we used homology detection techniques and molecular modeling tools to identify an ancestral set of 17 ATP synthase subunits. Most eukaryotes possess an ATP synthase comparable to those of animals and fungi, while some have undergone drastic divergence (e.g., ciliates, myzozoans, euglenozoans). Additionally, a ∼1 billion-year-old gene fusion between ATP synthase stator subunits was identified as a synapomorphy of the SAR (Stramenopila, Alveolata, Rhizaria) supergroup (stramenopile, alveolate, rhizaria). Our comparative approach highlights the persistence of ancestral subunits even amidst major structural changes. We conclude by urging that more ATP synthase structures (e.g., from jakobids, heteroloboseans, stramenopiles, rhizarians) are needed to provide a complete picture of the evolution of the structural diversity of this ancient and essential complex.

Energetics and evolution of anaerobic microbial eukaryotes

Mitochondria and aerobic respiration have been suggested to be required for the evolution of eukaryotic cell complexity. Aerobic respiration is several times more energetically efficient than fermentation. Moreover, aerobic respiration occurs at internalized mitochondrial membranes that are not constrained by a sublinear scaling with cell volume. However, diverse and complex anaerobic eukaryotes (for example, free-living and parasitic unicellular, and even small multicellular, eukaryotes) that exclusively rely on fermentation for energy generation have evolved repeatedly from aerobic ancestors. How do fermenting eukaryotes maintain their cell volumes and complexity while relying on such a low energy-yielding process? Here I propose that reduced rates of ATP generation in fermenting versus respiring eukaryotes are compensated for by longer cell cycles that satisfy lifetime energy demands. A literature survey and growth efficiency calculations show that fermenting eukaryotes divide approximately four to six times slower than aerobically respiring counterparts with similar cell volumes. Although ecological advantages such as competition avoidance offset lower growth rates and yields in the short term, fermenting eukaryotes inevitably have fewer physiological and ecological possibilities, which ultimately constrain their long-term evolutionary trajectories.

The Memory Problem for Neutral Mutational Models of Evolution

Models for the evolution of various phenotypes are sometimes constructed with an assumption that mutational effects will be symmetrically distributed about a static mean. This model produces a memory effect that over long evolutionary times results in an expectation that randomized sequences underlying the genetic architecture of the trait will on average retain the ancestral phenotype. This expectation is unrealistic and also inconsistent with our current understanding of processes of molecular evolution.

Supply-driven evolution: Mutation bias and trait-fitness distributions can drive macro-evolutionary dynamics

Many well-documented macro-evolutionary phenomena still challenge current evolutionary theory. Examples include long-term evolutionary trends, major transitions in evolution, conservation of certain biological features such as hox genes, and the episodic creation of new taxa. Here, we present a framework that may explain these phenomena. We do so by introducing a probabilistic relationship between trait value and reproductive fitness. This integration allows mutation bias to become a robust driver of long-term evolutionary trends against environmental bias, in a way that is consistent with all current evolutionary theories. In cases where mutation bias is strong, such as when detrimental mutations are more common than beneficial mutations, a regime called “supply-driven” evolution can arise. This regime can explain the irreversible persistence of higher structural hierarchies, which happens in the major transitions in evolution. We further generalize this result in the long-term dynamics of phenotype spaces. We show how mutations that open new phenotype spaces can become frozen in time. At the same time, new possibilities may be observed as a burst in the creation of new taxa.

The story of rRNA expansion segments: Finding functionality amidst diversity

Expansion segments (ESs) are multinucleotide insertions present across phyla at specific conserved positions in eukaryotic rRNAs. ESs are generally absent in bacterial rRNAs with some exceptions, while the archaeal rRNAs have microexpansions at regions that coincide with those of eukaryotic ESs. Although there is an increasing prominence of ribosomes, especially the ribosomal proteins, in fine-tuning gene expression through translation regulation, the role of rRNA ESs is relatively underexplored. While rRNAs have been established as the major catalytic hub in ribosome function, the presence of ESs widens their scope as a species-specific regulatory hub of protein synthesis. In this comprehensive review, we have elaborately discussed the current understanding of the functional aspects of rRNA ESs of cytoplasmic eukaryotic ribosomes and discuss their past, present, and future. This article is categorized under: RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems Translation > Ribosome Structure/Function Translation > Regulation.

Evolution of the connectivity and indispensability of a transferable gene: the simplicity hypothesis

BACKGROUND

The number of interactions between a transferable gene or its protein product and genes or gene products native to its microbial host is referred to as connectivity. Such interactions impact the tendency of the gene to be retained by evolution following horizontal gene transfer (HGT) into a microbial population. The complexity hypothesis posits that the protein product of a transferable gene with lower connectivity is more likely to function in a way that is beneficial to a new microbial host compared to the protein product of a transferable gene with higher connectivity. A gene with lower connectivity is consequently more likely to be fixed in any microbial population it enters by HGT. The more recently proposed simplicity hypothesis posits that the connectivity of a transferable gene might increase over time within any single microbial population due to gene-host coevolution, but that differential rates of colonization of microbial populations by HGT in accordance with differences in connectivity might act to counter this and even reduce connectivity over time, comprising an evolutionary trade-off.

RESULTS

We present a theoretical model that can be used to predict the conditions under which gene-host coevolution might increase or decrease the connectivity of a transferable gene over time. We show that the opportunity to enter new microbial populations by HGT can cause the connectivity of a transferable gene to evolve toward lower values, particularly in an environment that is unstable with respect to the function of the gene's protein product. We also show that a lack of such opportunity in a stable environment can cause the connectivity of a transferable gene to evolve toward higher values.

CONCLUSION

Our theoretical model suggests that the connectivity of a transferable gene can change over time toward higher values corresponding to a more sessile state of lower transferability or lower values corresponding to a more itinerant state of higher transferability, depending on the ecological milieu in which the gene exists. We note, however, that a better understanding of gene-host coevolutionary dynamics in natural microbial systems is required before any further conclusions about the veracity of the simplicity hypothesis can be drawn.

Simple mechanisms for the evolution of protein complexity

Proteins are tiny models of biological complexity: specific interactions among their many amino acids cause proteins to fold into elaborate structures, assemble with other proteins into higher-order complexes, and change their functions and structures upon binding other molecules. These complex features are classically thought to evolve via long and gradual trajectories driven by persistent natural selection. But a growing body of evidence from biochemistry, protein engineering, and molecular evolution shows that naturally occurring proteins often exist at or near the genetic edge of multimerization, allostery, and even new folds, so just one or a few mutations can trigger acquisition of these properties. These sudden transitions can occur because many of the physical properties that underlie these features are present in simpler proteins as fortuitous by-products of their architecture. Moreover, complex features of proteins can be encoded by huge arrays of sequences, so they are accessible from many different starting points via many possible paths. Because the bridges to these features are both short and numerous, random chance can join selection as a key factor in explaining the evolution of molecular complexity.

rRNA expansion segment 7 in eukaryotes: from Signature Fold to tentacles

The ribosomal core is universally conserved across the tree of life. However, eukaryotic ribosomes contain diverse rRNA expansion segments (ESs) on their surfaces. Sites of ES insertions are predicted from sites of insertion of micro-ESs in archaea. Expansion segment 7 (ES7) is one of the most diverse regions of the ribosome, emanating from a short stem loop and ranging to over 750 nucleotides in mammals. We present secondary and full-atom 3D structures of ES7 from species spanning eukaryotic diversity. Our results are based on experimental 3D structures, the accretion model of ribosomal evolution, phylogenetic relationships, multiple sequence alignments, RNA folding algorithms and 3D modeling by RNAComposer. ES7 contains a distinct motif, the 'ES7 Signature Fold', which is generally invariant in 2D topology and 3D structure in all eukaryotic ribosomes. We establish a model in which ES7 developed over evolution through a series of elementary and recursive growth events. The data are sufficient to support an atomic-level accretion path for rRNA growth. The non-monophyletic distribution of some ES7 features across the phylogeny suggests acquisition via convergent processes. And finally, illustrating the power of our approach, we constructed the 2D and 3D structure of the entire LSU rRNA of Mus musculus.

The origin of RNA interference: Adaptive or neutral evolution?

The origin of RNA interference (RNAi) is usually explained by a defense-based hypothesis, in which RNAi evolved as a defense against transposable elements (TEs) and RNA viruses and was already present in the last eukaryotic common ancestor (LECA). However, since RNA antisense regulation and double-stranded RNAs (dsRNAs) are ancient and widespread phenomena, the origin of defensive RNAi should have occurred in parallel with its regulative functions to avoid imbalances in gene regulation. Thus, we propose a neutral evolutionary hypothesis for the origin of RNAi in which qualitative system drift from a prokaryotic antisense RNA gene regulation mechanism leads to the formation of RNAi through constructive neutral evolution (CNE). We argue that RNAi was already present in the ancestor of LECA before the need for a new defense system arose and that its presence helped to shape eukaryotic genomic architecture and stability.

Where does RNA interference come from? This Essay describes a new step-by-step evolutionary model of how RNA interference might have originated in early eukaryotes through neutral events from the molecular machinery present in prokaryotes.

p166 links membrane and intramitochondrial modules of the trypanosomal tripartite attachment complex

The protist parasite Trypanosoma brucei has a single mitochondrion with a single unit genome termed kinetoplast DNA (kDNA). Faithfull segregation of replicated kDNA is ensured by a complicated structure termed tripartite attachment complex (TAC). The TAC physically links the basal body of the flagellum with the kDNA spanning the two mitochondrial membranes. Here, we characterized p166 as the only known TAC subunit that is anchored in the inner membrane. Its C-terminal transmembrane domain separates the protein into a large N-terminal region that interacts with the kDNA-localized TAC102 and a 34 aa C-tail that binds to the intermembrane space-exposed loop of the integral outer membrane protein TAC60. Whereas the outer membrane region requires four essential subunits for proper TAC function, the inner membrane integral p166, via its interaction with TAC60 and TAC102, would theoretically suffice to bridge the distance between the OM and the kDNA. Surprisingly, non-functional p166 lacking the C-terminal 34 aa still localizes to the TAC region. This suggests the existence of additional TAC-associated proteins which loosely bind to non-functional p166 lacking the C-terminal 34 aa and keep it at the TAC. However, binding of full length p166 to these TAC-associated proteins alone would not be sufficient to withstand the mechanical load imposed by the segregating basal bodies.

Evolution and diversification of mitochondrial protein import systems

More than 95% of mitochondrial proteins are encoded in the nucleus, synthesised in the cytosol and imported into the organelle. The evolution of mitochondrial protein import systems was therefore a prerequisite for the conversion of the α-proteobacterial mitochondrial ancestor into an organelle. Here, I review that the origin of the mitochondrial outer membrane import receptors can best be understood by convergent evolution. Subsequently, I discuss an evolutionary scenario that was proposed to explain the diversification of the inner membrane carrier protein translocases between yeast and mammals. Finally, I illustrate a scenario that can explain how the two specialised inner membrane protein translocase complexes found in most eukaryotes were reduced to a single multifunctional one in trypanosomes.

Adaptation and Exaptation: From Small Molecules to Feathers

Evolution works by adaptation and exaptation. At an organismal level, exaptation and adaptation are seen in the formation of organelles and the advent of multicellularity. At the sub-organismal level, molecular systems such as proteins and RNAs readily undergo adaptation and exaptation. Here we suggest that the concepts of adaptation and exaptation are universal, synergistic, and recursive and apply to small molecules such as metabolites, cofactors, and the building blocks of extant polymers. For example, adenosine has been extensively adapted and exapted throughout biological evolution. Chemical variants of adenosine that are products of adaptation include 2' deoxyadenosine in DNA and a wide array of modified forms in mRNAs, tRNAs, rRNAs, and viral RNAs. Adenosine and its variants have been extensively exapted for various functions, including informational polymers (RNA, DNA), energy storage (ATP), metabolism (e.g., coenzyme A), and signaling (cyclic AMP). According to Gould, Vrba, and Darwin, exaptation imposes a general constraint on interpretation of history and origins; because of exaptation, extant function should not be used to explain evolutionary history. While this notion is accepted in evolutionary biology, it can also guide the study of the chemical origins of life. We propose that (i) evolutionary theory is broadly applicable from the dawn of life to the present time from molecules to organisms, (ii) exaptation and adaptation were important and simultaneous processes, and (iii) robust origin of life models can be constructed without conflating extant utility with historical basis of origins.

Non-adaptive complexity and biochemical function

Intricate biochemical structures are usually thought to be useful, because natural selection preserves them from degradation by a constant hail of destructive mutations. Biochemists therefore often deliberately disrupt them to understand how complexity improves protein function or fitness. However, evolutionary theory suggests that even useless complexity that never improved fitness can become completely essential if a simple set of evolutionary conditions is fulfilled. We review evidence that stable protein complexes, protein-chaperone interactions, and complexes consisting of several paralogs all fulfill these conditions. This makes reverse genetics or destructive mutagenesis unsuitable for assigning functions to these kinds of complexity. Instead, we advocate that incorporating evolutionary approaches into biochemistry overcomes this difficulty and allows us to distinguish useless from useful biochemical complexity.

OUP accepted manuscript

“Junk DNA” is a popular yet controversial concept that states that organisms carry in their genomes DNA that has no positive impact on their fitness. Nonetheless, biochemical functions have been identified for an increasing fraction of DNA elements traditionally seen as “Junk DNA”. These findings have been interpreted as fundamentally undermining the “Junk DNA” concept. Here, we reinforce previous arguments that this interpretation relies on an inadequate concept of biological function that does not consider the selected effect of a given genomic structure, which is central to the “Junk DNA” concept. Next, we suggest that another (though ignored) confounding factor is that the discussion about biological functions includes two different dimensions: a horizontal, ecological dimension that reflects how a given genomic element affects fitness in a specific time, and a vertical, temporal dimension that reflects how a given genomic element persisted along time. We suggest that “Junk DNA” should be used exclusively relative to the horizontal dimension, while for the vertical dimension, we propose a new term, “Spam DNA”, that reflects the fact that a given genomic element may persist in the genome even if not selected for on their origin. Importantly, these concepts are complementary. An element can be both “Spam DNA” and “Junk DNA”, and “Spam DNA” can also be recruited to perform evolved biological functions, as illustrated in processes of exaptation or constructive neutral evolution.

A computational exploration of resilience and evolvability of protein-protein interaction networks

Protein-protein interaction (PPI) networks represent complex intra-cellular protein interactions, and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype's PPI network's resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks' resilience. We use publicly available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms-random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits.