Avoiding dead ends: the experimental evolution of constraint as adaptation to environmental variation in Saccharomyces cerevisiae

Environmental unpredictability results in the evolution of bet-hedging traits, which maximize long-term fitness but are, by definition, suboptimal over short time scales. However, because suboptimal traits are expected to be purged by selection in the shorter term, the persistence of bet hedging remains perplexing. Here, we test the hypothesis that bet hedging persists through the evolution of constraint on short-term adaptation. We experimentally evolve Saccharomyces cerevisiae across two sequential treatments in which the frequency of extreme heat shocks decreases. We predict that experimental evolution under lower frequency heat shocks will result in greater adaptive constraint, or “purge-resistant” bet hedging. Constraint is assayed as evolutionary persistence of heat shock tolerance (HST) under constant benign conditions. As predicted, we find the retention of HST only in lines evolved under reduced frequency detrimental conditions. Results help explain the evolution of bet hedging, and challenge the traditional view that evolutionary constraint is inherently maladaptive.

Dynamic collateral sensitivity profiles highlight challenges and opportunities for optimizing antibiotic sequences

As traditional antimicrobial therapies fail at escalating rates, recent focus has shifted to evolution-based therapies to slow resistance. Collateral sensitivity-the increased susceptibility to one drug associated with evolved resistance to a different drug-offers a potentially exploitable evolutionary constraint, but the manner in which collateral effects emerge over time is not well understood. Here, we use laboratory evolution in the opportunistic pathogen E. faecalis to phenotypically characterize collateral profiles through evolutionary time. Specifically, we measure collateral profiles for 400 strain-antibiotic combinations over the course of 4 evolutionary time points as strains are selected in increasing concentrations of antibiotic. We find that collateral resistance dominates during early phases of adaptation, whereas a diverse set of collateral profiles are accessible with further selection. Using simple numerical simulations, we illustrate how these temporally dynamic profiles potentially impact sequential drug therapies. Finally, we show experimentally how dynamic collateral sensitivity relationships can create optimal dosing windows that depend on finely timed switching between drugs.

Phylogenomic and Microsynteny Analysis Provides Evidence of Genome Arrangements of High-Affinity Nitrate Transporter Gene Families of Plants

Nitrate transporter 2 (NRT2) and NRT3 or nitrate-assimilation-related 2 (NAR2) proteins families form a two-component, high-affinity nitrate transport system, which is essential for the acquisition of nitrate from soils with low N availability. An extensive phylogenomic analysis across land plants for these families has not been performed. In this study, we performed a microsynteny and orthology analysis on the NRT2 and NRT3 genes families across 132 plants (Sensu lato) to decipher their evolutionary history. We identified significant differences in the number of sequences per taxonomic group and different genomic contexts within the NRT2 family that might have contributed to N acquisition by the plants. We hypothesized that the greater losses of NRT2 sequences correlate with specialized ecological adaptations, such as aquatic, epiphytic, and carnivory lifestyles. We also detected expansion on the NRT2 family in specific lineages that could be a source of key innovations for colonizing contrasting niches in N availability. Microsyntenic analysis on NRT3 family showed a deep conservation on land plants, suggesting a high evolutionary constraint to preserve their function. Our study provides novel information that could be used as guide for functional characterization of these gene families across plant lineages.

The long non-coding RNA landscape of Candida yeast pathogens

Long non-coding RNAs (lncRNAs) constitute a poorly studied class of transcripts with emerging roles in key cellular processes. Despite efforts to characterize lncRNAs across a wide range of species, these molecules remain largely unexplored in most eukaryotic microbes, including yeast pathogens of the Candida clade. Here, we analyze thousands of publicly available sequencing datasets to infer and characterize the lncRNA repertoires of five major Candida pathogens: Candida albicans, Candida tropicalis, Candida parapsilosis, Candida auris and Candida glabrata. Our results indicate that genomes of these species encode hundreds of lncRNAs that show levels of evolutionary constraint intermediate between those of intergenic genomic regions and protein-coding genes. Despite their low sequence conservation across the studied species, some lncRNAs are syntenic and are enriched in shared sequence motifs. We find co-expression of lncRNAs with certain protein-coding transcripts, hinting at potential functional associations. Finally, we identify lncRNAs that are differentially expressed during infection of human epithelial cells for four of the studied species. Our comprehensive bioinformatic analyses of Candida lncRNAs pave the way for future functional characterization of these transcripts.

A novel exploration technique using the microbial fingerprint of shallow sediment to detect hydrocarbon microseepage and predict hydrocarbon charge — An Argentinian case study

The fundamental assumption of many successful geochemical and geomicrobial technologies developed in the last 80 years is that hydrocarbons leak from subsurface accumulations vertically to the surface. Driven by buoyancy, the process involves sufficiently large volumes directly measurable or indirectly inferable from their surface expressions. Even when the additional hydrocarbons are not measurable, their presence slightly changes the environment, where complex microbial communities live, and acts as an evolutionary constraint on their development. Since the ecology of this ecosystem is very complicated, we propose to use the full-microbiome analysis of the shallow sediments samples instead of targeting a selected number of known species, and the use of machine learning for uncovering the meaningful correlations in these data. We achieve this by sequencing the microbial biomass and generating its “DNA fingerprint”, and by analyzing the abundance and distribution of the microbes over the dataset. The proposed technology uses machine learning as an accurate tool for determining the detailed interactions among the various microorganisms and their environment in the presence or absence of hydrocarbons, thus overcoming data complexity. In a proof-of-technology study, we have taken more than 1000 samples in the Neuqu謠Basin in Argentina over three distinct areas, namely, an oil field, a gas field, and a dry location outside the basin, and created several successful predictive models. A subset of randomly selected samples was kept outside of the training set and blinded by the client operator, providing the means for objectively validating the prediction performance of this methodology. Uncovering the blinded dataset after estimating the prospectivity revealed that most of these samples were correctly predicted. This very encouraging result shows that analyzing the microbial ecosystem in the shallow sediment can be an additional de-risking method for assessing hydrocarbon prospects and improving the Probability Of Success(POS) of a drilling campaign.

Running With Scissors: Evolutionary Conflicts Between Viral Proteases and the Host Immune System

Many pathogens encode proteases that serve to antagonize the host immune system. In particular, viruses with a positive-sense single-stranded RNA genome [(+)ssRNA], including picornaviruses, flaviviruses, and coronaviruses, encode proteases that are not only required for processing viral polyproteins into functional units but also manipulate crucial host cellular processes through their proteolytic activity. Because these proteases must cleave numerous polyprotein sites as well as diverse host targets, evolution of these viral proteases is expected to be highly constrained. However, despite this strong evolutionary constraint, mounting evidence suggests that viral proteases such as picornavirus 3C, flavivirus NS3, and coronavirus 3CL, are engaged in molecular ‘arms races’ with their targeted host factors, resulting in host- and virus-specific determinants of protease cleavage. In cases where protease-mediated cleavage results in host immune inactivation, recurrent host gene evolution can result in avoidance of cleavage by viral proteases. In other cases, such as recently described examples in NLRP1 and CARD8, hosts have evolved ‘tripwire’ sequences that mimic protease cleavage sites and activate an immune response upon cleavage. In both cases, host evolution may be responsible for driving viral protease evolution, helping explain why viral proteases and polyprotein sites are divergent among related viruses despite such strong evolutionary constraint. Importantly, these evolutionary conflicts result in diverse protease-host interactions even within closely related host and viral species, thereby contributing to host range, zoonotic potential, and pathogenicity of viral infection. Such examples highlight the importance of examining viral protease-host interactions through an evolutionary lens.

The intronic branch point sequence is under strong evolutionary constraint in the bovine and human genome

The branch point sequence is a cis-acting intronic motif required for mRNA splicing. Despite their functional importance, branch point sequences are not routinely annotated. Here we predict branch point sequences in 179,476 bovine introns and investigate their variability using a catalogue of 29.4 million variants detected in 266 cattle genomes. We localize the bovine branch point within a degenerate heptamer “nnyTrAy”. An adenine residue at position 6, that acts as branch point, and a thymine residue at position 4 of the heptamer are more strongly depleted for mutations than coding sequences suggesting extreme purifying selection. We provide evidence that mutations affecting these evolutionarily constrained residues lead to alternative splicing. We confirm evolutionary constraints on branch point sequences using a catalogue of 115 million SNPs established from 3,942 human genomes of the gnomAD database.

Prediction of evolutionary constraint by genomic annotations improves prioritization of causal variants in maize

Crop improvement through cross-population genomic prediction and genome editing requires identification of causal variants at single-site resolution. Most genetic mapping studies have generally lacked such resolution. In contrast, evolutionary approaches can detect genetic effects at high resolution, but they are limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Here we used genomic annotations to accurately predict nucleotide conservation across Angiosperms, as a proxy for fitness effect of mutations. Using only sequence analysis, we annotated non-synonymous mutations in 25,824 maize gene models, with information from bioinformatics (SIFT scores, GC content, transposon insertion, k-mer frequency) and deep learning (predicted effects of polymorphisms on protein representations by UniRep). Our predictions were validated by experimental information: within-species conservation, chromatin accessibility, gene expression and gene ontology enrichment. Importantly, they also improved genomic prediction for fitness-related traits (grain yield) in elite maize panels (+5% and +38% prediction accuracy within and across panels, respectively), by stringent prioritization of ≤ 1% of single-site variants (e.g., 104 sites and approximately 15 deleterious alleles per haploid genome). Together, our results suggest that our proposed approach may effectively prioritize sites most likely to impact fitness-related traits in crops. Such prioritizations could be useful to select polymorphisms for accurate genomic prediction, and candidate mutations for efficient base editing.

Genome size in cyclopoid copepods (Copepoda: Cyclopoida): chromatin diminution as a hypothesized mechanism of evolutionary constraint

Genome size is a fundamental property of organisms that impacts their molecular evolution and life histories. The hypothesis that somatic genome sizes in copepods in the order Cyclopoida are small and evolutionary constrained relative to those in the order Calanoida was proposed 15 years ago. Since then, the number of estimates has almost doubled and the taxon sampling has broadened. Here we add 14 new estimates from eight genera of freshwater cyclopoids that vary from 0.2 to 6.6 pg of DNA per nucleus in the soma; all except one are 2.0 pg DNA per nucleus or smaller. This new sample adds to the pattern of genome size in copepods and is remarkably similar to the distribution on which the original hypothesis was based, as well as those of subsequently published estimates. Embryonic chromatin diminution, during which large portions of DNA are excised from the presomatic cell lineage, is reported in Paracyclops affinis (G.O. Sars, 1863). This diminution results in a somatic genome that is one half the size of the germline genome. When the sizes of the germline genomes carried in presomatic cells of cyclopoid species that possess chromatin diminution are considered, the prediminuted germline genome sizes of cyclopoid embryos overlap with the distribution of calanoid somatic genome sizes, supporting the hypothesis that chromatin diminution has functioned as a mechanism to constrain somatic nuclear DNA content in cyclopoid copepods. Geographically based variation in genome size among populations is also reviewed.

Ankyrin repeats in context with human population variation

Ankyrin protein repeats bind to a wide range of substrates and are one of the most common protein motifs in nature. Here, we collate a high-quality alignment of 7,407 ankyrin repeats and examine for the first time, the distribution of human population variants from large-scale sequencing of healthy individuals across this family. Population variants are not randomly distributed across the genome but are constrained by gene essentiality and function. Accordingly, we interpret the population variants in context with evolutionary constraint and structural features including secondary structure, accessibility and protein-protein interactions across 383 three-dimensional structures of ankyrin repeats. We find five positions that are highly conserved across homologues and also depleted in missense variants within the human population. These positions are significantly enriched in intra-domain contacts and so likely to be key for repeat packing. In contrast, a group of evolutionarily divergent positions are found to be depleted in missense variants in human but significantly enriched in protein-protein interactions. Our analysis also suggests the domain has three, not two surfaces, each with different patterns of enrichment in protein-substrate interactions and missense variants. Our findings will be of interest to those studying or engineering ankyrin-repeat containing proteins as well as those interpreting the significance of disease variants.