Foldability of a Natural De Novo Evolved Protein

Bungard, Dixie; Copple, J.S.; Yan, Juntao; Chhun, Jimmy J.; Kumirov, Vlad K.; Foy, Scott G.; Masel, Joanna; Wysocki, Vicki H.; Cordes, Matthew

doi:10.1016/j.str.2017.09.006

Cited by 48 publications

(76 citation statements)

References 74 publications

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“…S11g-i). This is in agreement with findings that secondary structure is already present in random polypeptides (Tretyachenko et al 2017), and suggests that newly born proteins may represent promising starting points for the evolution of structured and foldable proteins (Bungard et al 2017).…”

Section: De Novo Genes Encode More Disordered Proteins Than Both Oldesupporting

confidence: 91%

A Continuum of Evolving De Novo Genes Drives Protein-Coding Novelty in Drosophila

2020

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Orphan genes, lacking detectable homologs in outgroup species, typically represent 10-30% of eukaryotic genomes. Efforts to find the source of these young genes indicate that de novo emergence from non-coding DNA may in part explain their prevalence. Here, we investigate the roots of orphan gene emergence in the Drosophila genus. Across the annotated proteomes of twelve species, we find 6297 orphan genes within 4953 taxon-specific clusters of orthologs. By inferring the ancestral DNA as non-coding for between 550 and 2467 (8.7-39.2%) of these genes, we describe for the first time how de novo emergence contributes to the abundance of clade-specific Drosophila genes. In support of them having functional roles, we show that de novo genes have robust expression and translational support. However, the distinct nucleotide sequences of de novo genes, which have characteristics intermediate between intergenic regions and conserved genes, reflect their recent birth from non-coding DNA. We find that de novo genes encode more disordered proteins than both older genes and intergenic regions. Together, our results suggest that gene emergence from non-coding DNA provides an abundant source of material for the evolution of new proteins. Following gene birth, gradual evolution over large evolutionary timescales moulds sequence properties towards those of conserved genes, resulting in a continuum of properties whose starting points depend on the nucleotide sequences of an initial pool of novel genes.

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Section: De Novo Genes Encode More Disordered Proteins Than Both Oldesupporting

confidence: 91%

A Continuum of Evolving De Novo Genes Drives Protein-Coding Novelty in Drosophila

2020

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“…UniDec [19] offers uniquely powerful deconvolution of native and intact protein MS data because it is fast, able to analyze complex spectra, and requires minimal user input. It has been used by a number of research groups [3, 19, 21, 22, 24, 31–50]. UniDec uses a Bayesian deconvolution algorithm to determine the charge state distribution of each m/z data point, which is captured in a two-dimensional matrix of intensity values as a function of m/z and charge.…”

Section: Introductionmentioning

confidence: 99%

MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra

Reid

Diesing

Miller

et al. 2018

J. Am. Soc. Mass Spectrom.

102

103

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The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. Graphical abstract ᅟ.

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“…Historically, one argument against the notion of widespread de novo gene birth is the evolved complexity of protein folding. Interestingly, Bsc4 was later shown to adopt a partially folded state that combines properties of native and non-native protein folding [39]. Another well-characterized example in yeast is MDF1 , which both represses mating efficiency and promotes vegetative growth, and is intricately regulated by a conserved antisense ORF [40, 41].…”

Section: History Of the Study Of De Novo Gene Birthmentioning

confidence: 99%