Experimental characterisation of de novo proteins and their unevolved random-sequence counterparts

Abstract

De novo gene emergence provides a route for new proteins to be formed from previously non-coding DNA. Proteins born in this way are considered random sequences, and typically assumed to lack defined structure. While it remains unclear how likely a de novo protein is to assume a soluble and stable tertiary structure, intersecting evidence from random-sequence and de novo-designed proteins suggests that native-like biophysical properties are abundant in sequence space. Taking putative de novo proteins identified in human and fly, we experimentally characterise a library of these sequences to assess their solubility and structure propensity. We compare this library to a set of synthetic random proteins with no evolutionary history. Bioinformatic prediction suggests that de novo proteins may have remarkably similar distributions of biophysical properties to unevolved random sequences of a given length and amino acid composition. However, upon expression in vitro, de novo proteins exhibit moderately higher solubility which is further induced by the DnaK chaperone system. We suggest that while synthetic random sequences are a useful proxy for de novo proteins in terms of structure propensity, de novo proteins may be better integrated in the cellular system than random expectation, given their higher solubility.

Dataset description

A full description of the dataset can be found in the packaged README file. Data includes:

* Library sequences (synthesised oligo pool and CDSs)

* Sequence property predictions for each library

* Processed read counts from NGS data and peptide counts from mass spectrometry data

* Raw NGS reads, along with example code for demultiplexing the pooled samples and mapping/counting reads