Exploring proteome-wide occurrence of clusters of charged residues in eukaryotes

Screening clusters of charged residues in plants' mitochondrial proteins and biological significance

Protein function is dependent on charge interactions and charge biased regions, which are involved in a wide range of cellular and biochemical processes. We report the development of a new algorithm implemented in Python and its use to identify charge clusters CC (NegativeCC: NCC, PositiveCC: PCC and MixedCC: MCC) and compare their presence in mitochondrial proteins of plant groups. To characterize the resulting CC, statistical, structural and functional analyses were conducted. The screening of 105 399 protein sequences showed that 2.6 %, 0.48 % and 0.03 % of the proteins contain NCC, PCC and MCC, respectively. Mitochondrial proteins encoded by the nuclear genome of green algae have the biggest proportion of both PCC (1.6 %) and MCC (0.4 %) and mitochondrial proteins coded by the nuclear genome of other plants group have the highest portion of NCC (7.5 %). The mapping of the identified CC showed that they are mainly located in the terminal regions of the protein. Annotation showed that proteins with CC are classified as binding proteins, are included in the transmembrane transport processes, and are mainly located in the membrane. The CC scanning revealed the presence of 2373 and 784 sites and 192 and 149 motif profiles within NCC and PCC, respectively. The investigation of CC within pentatricopeptide repeat-containing proteins revealed that they are involved in correct and specific RNA editing. CC were proven to play a key role in providing insightful structural and functional information of complex protein assemblies which could be useful in biotechnological applications.

Charge cluster occurrence in land plants' mitochondrial proteomes with functional and structural insights

The Charge Clusters (CCs) are involved in key functions and are distributed according to the organism, the protein's type, and the charge of amino acids. In the present study, we have explored the occurrence, position, and annotation as a first large-scale study of the CCs in land plants mitochondrial proteomes. A new python script was used for data curation. The Finding Clusters Charge in Protein Sequences Program was performed after adjusting the reading window size. A 44316 protein sequences belonging to 52 species of land plants were analysed. The occurrence of Negative Charge Clusters (NCCs) (1.2%) is two times more frequent than the Positive Charge Clusters (PCCs) (0.64%). Moreover, 39 and 30 NCCs were conserved in 88 and 41 proteins in intra and in inter proteomes respectively, while 14 and 21 PCCs were conserved in 53 and 85 protein sequences in intra and inter proteomes consecutively. Sequences carrying mixed CCs are rare (0.12%). Despite this low abundance, CCs play a crucial role in protein function. The CCs tend to be located mainly in the terminal regions of proteins which guarantees specific protein targeting and import into the mitochondria. In addition, the functional annotation of CCs according to Gene Ontology shows that CCs are involved in binding functions of either proteins or macromolecules which are deployed in different metabolic and cellular processes such as RNA editing and transcription. This study may provide valuable information while considering the CCs in understanding the environmental adaptation of plants.Communicated by Ramaswamy H. Sarma.

Charge clusters signatures in prokaryotic proteomes: Temperature-dependence and distribution

The identification and the screening of Charged Clusters (CCs) residues in proteins is a key analysis to assess any quantitative structure-function correlation in proteins. Here, we present a proteome wide scan for the occurrence of (CCs) in 99292 proteins using a new tool. Finding Clusters Charge in Protein Sequences Program (FCCP). The FCCP has been employed to search CCs in 35 prokaryotic proteomes (7 Psychrophiles, 10 Mesophiles, 9 thermophiles and for 9 hyperthermophiles). A new repository of 855 CC has been created. Results showed that the mapped proteins containing positive and negative charge clusters are mostly transmembrane proteins while the conserved CCs within the same proteome are transposases or involved in DNA binding and integration. Interestingly, the negative charged cluster was associated to bacteria growth's temperature (p=0.002) acting as proteins' core signature. Taken together the various results provide a consistent picture of these screened CCs in terms of its potentials functional roles.

Screening of nucleotide variations in genomic sequences encoding charged protein regions in the human genome

Background

Studying genetic variation distribution in proteins containing charged regions, called charge clusters (CCs), is of great interest to unravel their functional role. Charge clusters are 20 to 75 residue segments with high net positive charge, high net negative charge, or high total charge relative to the overall charge composition of the protein. We previously developed a bioinformatics tool (FCCP) to detect charge clusters in proteomes and scanned the human proteome for the occurrence of CCs. In this paper we investigate the genetic variations in the human proteins harbouring CCs.

Results

We studied the coding regions of 317 positively charged clusters and 1020 negatively charged ones previously detected in human proteins. Results revealed that coding parts of CCs are richer in sequence variants than their corresponding genes, full mRNAs, and exonic + intronic sequences and that these variants are predominately rare (Minor allele frequency < 0.005). Furthermore, variants occurring in the coding parts of positively charged regions of proteins are more often pathogenic than those occurring in negatively charged ones. Classification of variants according to their types showed that substitution is the major type followed by Indels (Insertions-deletions). Concerning substitutions, it was found that within clusters of both charges, the charged amino acids were the greatest loser groups whereas polar residues were the greatest gainers.

Conclusions

Our findings highlight the prominent features of the human charged regions from the DNA up to the protein sequence which might provide potential clues to improve the current understanding of those charged regions and their implication in the emergence of diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4000-3) contains supplementary material, which is available to authorized users.

Screening for clusters of charge in human virus proteomes

Background

The identification of charge clusters (runs of charged residues) in proteins and their mapping within the protein structure sequence is an important step toward a comprehensive analysis of how these particular motifs mediate, via electrostatic interactions, various molecular processes such as protein sorting, translocation, docking, orientation and binding to DNA and to other proteins. Few algorithms that specifically identify these charge clusters have been designed and described in the literature. In this study, 197 distinctive human viral proteomes were screened for the occurrence of charge clusters (CC) using a new computational approach.

Results

Three hundred and seventy three CC have been identified within the 2549 viral protein sequences screened. The number of protein sequences that are CC-free is 2176 (85.3 %) while 150 and 180 proteins contained positive charge (PCC) and negative charge clusters (NCC), respectively. The NCCs (211 detected) were more prevalent than PCC (162). PCC-containing proteins are significantly longer than those having NCCs (p = 2.10^-16). The most prevalent virus families having PCC and NCC were Herpesviridae followed by Papillomaviridae. However, the single-strand RNA group has in average three times more NCC than PCC. According to the functional domain classification, a significant difference in distribution was observed between PCC and NCC (p = 2. 10⁻⁸) with the occurrence of NCCs being more frequent in C-terminal region while PCC more often fall within functional domains. Only 29 proteins sequences contained both NCC and PCC. Moreover, 101 NCC were conserved in 84 proteins while only 62 PCC were conserved in 60 protein sequences. To understand the mechanism by which the membrane translocation functionalities are embedded in viral proteins, we screened our PCC for sequences corresponding to cell-penetrating peptides (CPPs) using two online databases: CellPPd and CPPpred. We found that all our PCCs, having length varying from 7 to 30 amino-acids were predicted as CPPs. Experimental validation is required to improve our understanding of the role of these PCCs in viral infection process.

Conclusions

Screening distinctive cluster charges in viral proteomes suggested a functional role of these protein regions and might provide potential clues to improve the current understanding of viral diseases in order to tailor better preventive and therapeutic approaches.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3086-3) contains supplementary material, which is available to authorized users.