The Effects of Sequence Length and Composition of Random Sequence Peptides on the Growth of E. coli Cells

Random, de novo, and conserved proteins: How structure and disorder predictors perform differently

Understanding the emergence and structural characteristics of de novo and random proteins is crucial for unraveling protein evolution and designing novel enzymes. However, experimental determination of their structures remains challenging. Recent advancements in protein structure prediction, particularly with AlphaFold2 (AF2), have expanded our knowledge of protein structures, but their applicability to de novo and random proteins is unclear. In this study, we investigate the structural predictions and confidence scores of AF2 and protein language model-based predictor ESMFold for de novo and conserved proteins from Drosophila and a dataset of comparable random proteins. We find that the structural predictions for de novo and random proteins differ significantly from conserved proteins. Interestingly, a positive correlation between disorder and confidence scores (pLDDT) is observed for de novo and random proteins, in contrast to the negative correlation observed for conserved proteins. Furthermore, the performance of structure predictors for de novo and random proteins is hampered by the lack of sequence identity. We also observe fluctuating median predicted disorder among different sequence length quartiles for random proteins, suggesting an influence of sequence length on disorder predictions. In conclusion, while structure predictors provide initial insights into the structural composition of de novo and random proteins, their accuracy and applicability to such proteins remain limited. Experimental determination of their structures is necessary for a comprehensive understanding. The positive correlation between disorder and pLDDT could imply a potential for conditional folding and transient binding interactions of de novo and random proteins.

Experimental Evaluation of a Direct Fitness Effect of the De Novo Evolved Mouse Gene Pldi

De novo evolved genes emerge from random parts of noncoding sequences and have, therefore, no homologs from which a function could be inferred. While expression analysis and knockout experiments can provide insights into the function, they do not directly test whether the gene is beneficial for its carrier. Here, we have used a seminatural environment experiment to test the fitness of the previously identified de novo evolved mouse gene Pldi, which has been implicated to have a role in sperm differentiation. We used a knockout mouse strain for this gene and competed it against its parental wildtype strain for several generations of free reproduction. We found that the knockout (ko) allele frequency decreased consistently across three replicates of the experiment. Using an approximate Bayesian computation framework that simulated the data under a demographic scenario mimicking the experiment's demography, we could estimate a selection coefficient ranging between 0.21 and 0.61 for the wildtype allele compared to the ko allele in males, under various models. This implies a relatively strong selective advantage, which would fix the new gene in less than hundred generations after its emergence.

Evolution and implications of de novo genes in humans

Genes and translated open reading frames (ORFs) that emerged de novo from previously non-coding sequences provide species with opportunities for adaptation. When aberrantly activated, some human-specific de novo genes and ORFs have disease-promoting properties-for instance, driving tumour growth. Thousands of putative de novo coding sequences have been described in humans, but we still do not know what fraction of those ORFs has readily acquired a function. Here, we discuss the challenges and controversies surrounding the detection, mechanisms of origin, annotation, validation and characterization of de novo genes and ORFs. Through manual curation of literature and databases, we provide a thorough table with most de novo genes reported for humans to date. We re-evaluate each locus by tracing the enabling mutations and list proposed disease associations, protein characteristics and supporting evidence for translation and protein detection. This work will support future explorations of de novo genes and ORFs in humans.

Taxonomically Restricted Genes in Bacillus may Form Clusters of Homologs and Can be Traced to a Large Reservoir of Noncoding Sequences

Taxonomically restricted genes (TRGs) are unique for a defined group of organisms and may act as potential genetic determinants of lineage-specific, biological properties. Here, we explore the TRGs of highly diverse and economically important Bacillus bacteria by examining commonly used TRG identification parameters and data sources. We show the significant effects of sequence similarity thresholds, composition, and the size of the reference database in the identification process. Subsequently, we applied stringent TRG search parameters and expanded the identification procedure by incorporating an analysis of noncoding and non-syntenic regions of non-Bacillus genomes. A multiplex annotation procedure minimized the number of false-positive TRG predictions and showed nearly one-third of the alleged TRGs could be mapped to genes missed in genome annotations. We traced the putative origin of TRGs by identifying homologous, noncoding genomic regions in non-Bacillus species and detected sequence changes that could transform these regions into protein-coding genes. In addition, our analysis indicated that Bacillus TRGs represent a specific group of genes mostly showing intermediate sequence properties between genes that are conserved across multiple taxa and nonannotated peptides encoded by open reading frames.

The Origins and Functions of De Novo Genes: Against All Odds?

"De novo" genes evolve from previously non-genic DNA. This strikes many of us as remarkable, because it seems extraordinarily unlikely that random sequence would produce a functional gene. How is this possible? In this two-part review, I first summarize what is known about the origins and molecular functions of the small number of de novo genes for which such information is available. I then speculate on what these examples may tell us about how de novo genes manage to emerge despite what seem like enormous opposing odds.

Random peptides rich in small and disorder-promoting amino acids are less likely to be harmful

Proteins are the workhorses of the cell, yet they carry great potential for harm via misfolding and aggregation. Despite the dangers, proteins are sometimes born de novo from non-coding DNA. Proteins are more likely to be born from non-coding regions that produce peptides that do little to no harm when translated than from regions that produce harmful peptides. To investigate which newborn proteins are most likely to "first, do no harm", we estimate fitnesses from an experiment that competed Escherichia coli lineages that each expressed a unique random peptide. A variety of peptide metrics significantly predict lineage fitness, but this predictive power stems from simple amino acid frequencies rather than the ordering of amino acids. Amino acids that are smaller and that promote intrinsic structural disorder have more benign fitness effects. We validate that the amino acids that indicate benign effects in random peptides expressed in E. coli also do so in an independent dataset of random N-terminal tags in which it is possible to control for expression level. The same amino acids are also enriched in young animal proteins.

Evolution of a New Testis-Specific Functional Promoter Within the Highly Conserved Map2k7 Gene of the Mouse

Map2k7 (synonym Mkk7) is a conserved regulatory kinase gene and a central component of the JNK signaling cascade with key functions during cellular differentiation. It shows complex transcription patterns, and different transcript isoforms are known in the mouse (Mus musculus). We have previously identified a newly evolved testis-specific transcript for the Map2k7 gene in the subspecies M. m. domesticus. Here, we identify the new promoter that drives this transcript and find that it codes for an open reading frame (ORF) of 50 amino acids. The new promoter was gained in the stem lineage of closely related mouse species but was secondarily lost in the subspecies M. m. musculus and M. m. castaneus. A single mutation can be correlated with its transcriptional activity in M. m. domesticus, and cell culture assays demonstrate the capability of this mutation to drive expression. A mouse knockout line in which the promoter region of the new transcript is deleted reveals a functional contribution of the newly evolved promoter to sperm motility and the spermatid transcriptome. Our data show that a new functional transcript (and possibly protein) can evolve within an otherwise highly conserved gene, supporting the notion of regulatory changes contributing to the emergence of evolutionary novelties.

Effects of the Expression of Random Sequence Clones on Growth and Transcriptome Regulation in Escherichia coli

Comparative genomic analyses have provided evidence that new genetic functions can emerge out of random nucleotide sequences. Here, we apply a direct experimental approach to study the effects of plasmids harboring random sequence inserts under the control of an inducible promoter. Based on data from previously described experiments dealing with the growth of clones within whole libraries, we extracted specific clones that had shown either negative, neutral or positive effects on relative cell growth. We analyzed these individually with respect to growth characteristics and the impact on the transcriptome. We find that candidate clones for negative peptides lead to growth arrest by eliciting a general stress response. Overexpression of positive clones, on the other hand, does not change the exponential growth rates of hosts, and they show a growth advantage over a neutral clone when tested in direct competition experiments. Transcriptomic changes in positive clones are relatively moderate and specific to each clone. We conclude from our experiments that random sequence peptides are indeed a suitable source for the de novo evolution of genetic functions.