Frail hypotheses in evolutionary biology

Hunting the Cell Cycle Snark

In this very personal hunt for the meaning of the bacterial cell cycle, the snark, I briefly revisit and update some of the mechanisms we and many others have proposed to regulate the bacterial cell cycle. These mechanisms, which include the dynamics of calcium, membranes, hyperstructures, and networks, are based on physical and physico-chemical concepts such as ion condensation, phase transition, crowding, liquid crystal immiscibility, collective vibrational modes, reptation, and water availability. I draw on ideas from subjects such as the 'prebiotic ecology' and phenotypic diversity to help with the hunt. Given the fundamental nature of the snark, I would expect that its capture would make sense of other parts of biology. The route, therefore, followed by the hunt has involved trying to answer questions like "why do cells replicate their DNA?", "why is DNA replication semi-conservative?", "why is DNA a double helix?", "why do cells divide?", "is cell division a spandrel?", and "how are catabolism and anabolism balanced?". Here, I propose some relatively unexplored, experimental approaches to testing snark-related hypotheses and, finally, I propose some possibly original ideas about DNA packing, about phase separations, and about computing with populations of virtual bacteria.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Irregularities in genetic variation and mutation rates with environmental stresses

The appearance of new mutations is determined by the equilibrium between DNA error formation and repair. In bacteria like Escherichia coli, stresses are thought shift this balance towards increased mutagenesis. Recent findings, however, suggest a very uneven relationship between stress and mutations. Only a subset of stressful environments increase the net rate of mutation and different forms of nutritional stress (such as oxygen, carbon or phosphorus limitations) result in markedly different mutation rates after similar reductions in growth rate. Moreover, different stresses result in altered mutational spectra, with some increasing transposition and others increasing indel formation. Single-base substitution rates are lower with some stresses than in unstressed bacteria. Indeed, changes to the mix of mutations with stress are more widespread than a marked increase in net mutation rate. Much remains to be learned on how environments have unique mutational signatures and why some stresses are more mutagenic than others. Even beyond stress-induced genetic variation, the fundamental unresolved question in the stress-mutation relationship is the adaptive value of different types of mutations and mutation rates; is transposition, for example, more advantageous under anaerobic conditions? It remains to be investigated whether stress-specific genetic variation impacts on evolvability differentially in distinct environments.

Molecular hyperdiversity and evolution in very large populations

The genomic density of sequence polymorphisms critically affects the sensitivity of inferences about ongoing sequence evolution, function and demographic history. Most animal and plant genomes have relatively low densities of polymorphisms, but some species are hyperdiverse with neutral nucleotide heterozygosity exceeding 5%. Eukaryotes with extremely large populations, mimicking bacterial and viral populations, present novel opportunities for studying molecular evolution in sexually reproducing taxa with complex development. In particular, hyperdiverse species can help answer controversial questions about the evolution of genome complexity, the limits of natural selection, modes of adaptation and subtleties of the mutation process. However, such systems have some inherent complications and here we identify topics in need of theoretical developments. Close relatives of the model organisms Caenorhabditis elegans and Drosophila melanogaster provide known examples of hyperdiverse eukaryotes, encouraging functional dissection of resulting molecular evolutionary patterns. We recommend how best to exploit hyperdiverse populations for analysis, for example, in quantifying the impact of noncrossover recombination in genomes and for determining the identity and micro-evolutionary selective pressures on noncoding regulatory elements.

Culture history and population heterogeneity as determinants of bacterial adaptation: the adaptomics of a single environmental transition

Diversity in adaptive responses is common within species and populations, especially when the heterogeneity of the frequently large populations found in environments is considered. By focusing on events in a single clonal population undergoing a single transition, we discuss how environmental cues and changes in growth rate initiate a multiplicity of adaptive pathways. Adaptation is a comprehensive process, and stochastic, regulatory, epigenetic, and mutational changes can contribute to fitness and overlap in timing and frequency. We identify culture history as a major determinant of both regulatory adaptations and microevolutionary change. Population history before a transition determines heterogeneities due to errors in translation, stochastic differences in regulation, the presence of aged, damaged, cheating, or dormant cells, and variations in intracellular metabolite or regulator concentrations. It matters whether bacteria come from dense, slow-growing, stressed, or structured states. Genotypic adaptations are history dependent due to variations in mutation supply, contingency gene changes, phase variation, lateral gene transfer, and genome amplifications. Phenotypic adaptations underpin genotypic changes in situations such as stress-induced mutagenesis or prophage induction or in biofilms to give a continuum of adaptive possibilities. Evolutionary selection additionally provides diverse adaptive outcomes in a single transition and generally does not result in single fitter types. The totality of heterogeneities in an adapting population increases the chance that at least some individuals meet immediate or future challenges. However, heterogeneity complicates the adaptomics of single transitions, and we propose that subpopulations will need to be integrated into future population biology and systems biology predictions of bacterial behavior.