A study of bias and increasing organismal complexity from their post-translational modifications and reaction site interplays

Abstract

Post-translational modifications (PTMs) are important steps in the biosynthesis of proteins. Aside from their integral contributions to protein development, i.e. perform specialized proteolytic cleavage of regulatory subunits, the covalent addition of functional groups of proteins or the degradation of entire proteins, PTMs are also involved in enabling proteins to withstand and recover from temporary environmental stresses (heat shock, microgravity and many others). The literature supports evidence of thousands of recently discovered PTMs, many of which may likely contribute similarly (perhaps, even, interchangeably) to protein stress response. Although there are many PTM actors on the biological stage, our study determines that these PTMs are generally cast into organism-specific, preferential roles. In this work, we study the PTM compositions across the mitochondrial (Mt) and non-Mt proteomes of 11 diverse organisms to illustrate that each organism appears to have a unique list of PTMs, and an equally unique list of PTM-associated residue reaction sites (RSs), where PTMs interact with protein. Despite the present limitation of available PTM data across different species, we apply existing and current protein data to illustrate particular organismal biases. We explore the relative frequencies of observed PTMs, the RSs and general amino-acid compositions of Mt and non-Mt proteomes. We apply these data to create networks and heatmaps to illustrate the evidence of bias. We show that the number of PTMs and RSs appears to grow along with organismal complexity, which may imply that environmental stress could play a role in this bias.

Keywords: PTM bias; amino acid bias; organism complexity; reaction site bias.

Figure 1

A comparison between the number of PTMs in our Mt and non-Mt sequence data. Here, we exclude all PTMs that are labeled by UniProt as ‘InterChain’ because of a lack of information available for our study.

Figure 2

All Mt and non-Mt proteins were examined in each organism of our study. We recorded the protein type (Mt or non-Mt), the PTMs of the protein and their associated RSs. This information was used to assemble relative frequency data.

Figure 3

An example of how relative frequency information was extracted from protein data. For each organism, all Mt and non-Mt protein records were queried to ascertain their observed PTMs that have been curated by UniProt. The type and count of each PTM, including its associated RS, were recorded to calculate frequencies by Equations (1) and (2). Not shown, the occurrence magnitudes of all amino acids (non-RSs) were also obtained and applied to Equation (3) to determine the general amino-acid compositions of each proteome.

Figure 4

Mt and non-Mt PTM compositions prepared using Equation (3). High magnitudes of frequency are described by lighter colors. We note that phosphorylation and acetylation were common PTMs across the organisms. We note that all frequency values > 0.18 (threshold) are included here.

Figure 5

Mt and non-Mt RS compositions prepared using Equation (2). High magnitudes of frequency are described by lighter colors. Unlike the non-Mt heatmap, where nearly all amino acids played a roles as RSs, there were many amino acidss in the Mt proteomes that were never involved with the PTMs.

Figure 6

Mt and non-Mt amino-acid compositions prepared using Equation (3). High magnitudes of frequency are described by lighter colors. Although all organisms display a common theme of color bands, indicating that their amino-acid composition is similar, we note that related organisms have especially similar patterns of color, indicating that the amino-acid distributions are similar.

Figure 7

Arabidopsis thaliana: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 8

Aspergillus nidulans: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 9

Caenorhabditis elegans: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 10

Canis familiaris: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 11

Danio rerio: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 12

Homo sapiens: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 13

Mus musculus: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 14

Oryctolagus cuniculus: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 15

Rattus norvegicus: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 16

Saccharomyces cerevisiae: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 17

Xenopus laevis: a network of PTM frequencies in Mt (left) and non-Mt (right) protein. We display the prominent PTMs across all organisms of our study having a frequency of at least 0.1.

Figure 18

We summarize the number of PTMs and RSs in the organismal networks. Here, we note that the higher organisms appear to have more PTMs and RSs. We note that the increasing numbers of PTMs and RSs are similar trends across the Mt and non-Mt data.

Figure 19

The number of isoforms of the organisms in our study. These counts were prepared by querying all organismal proteins in UniProt and then determining how many isoform proteins were present. The increasing number of isoforms may help to explain the increasing number of PTMs in higher organisms. Note that A. nidulans has been omitted because of the lack of isoform information.