Extent of pre-translational regulation for the control of nucleocytoplasmic protein localization
© The Author(s). 2016
Received: 16 January 2016
Accepted: 22 June 2016
Published: 24 June 2016
Appropriate protein subcellular localization is essential for proper cellular function. Central to the regulation of protein localization are protein targeting motifs, stretches of amino acids serving as guides for protein entry in a specific cellular compartment. While the use of protein targeting motifs is modulated in a post-translational manner, mainly by protein conformational changes and post-translational modifications, the presence of these motifs in proteins can also be regulated in a pre-translational manner. Here, we investigate the extent of pre-translational regulation of the main signals controlling nucleo-cytoplasmic traffic: the nuclear localization signal (NLS) and the nuclear export signal (NES).
Motif databases and manual curation of the literature allowed the identification of 175 experimentally validated NLSs and 120 experimentally validated NESs in human. Following mapping onto annotated transcripts, these motifs were found to be modular, most (73 % for NLS and 88 % for NES) being encoded entirely in only one exon. The presence of a majority of these motifs is regulated in an alternative manner at the transcript level (61 % for NLS and 72 % for NES) while the remaining motifs are present in all coding isoforms of their encoding gene. NLSs and NESs are pre-translationally regulated using four main mechanisms: alternative transcription/translation initiation, alternative translation termination, alternative splicing of the exon encoding the motif and frameshift, the first two being by far the most prevalent mechanisms. Quantitative analysis of the presence of these motifs using RNA-seq data indicates that inclusion of these motifs can be regulated in a tissue-specific and a combinatorial manner, can be altered in disease states in a directed way and that alternative inclusion of these motifs is often used by proteins with diverse interactors and roles in diverse pathways, such as kinases.
The pre-translational regulation of the inclusion of protein targeting motifs is a prominent and tightly-regulated mechanism that adds another layer in the control of protein subcellular localization.
Protein subcellular localization requires tight and timely regulation, to ensure proper environment and interaction partners, and ultimately function . Localization regulation is achieved through diverse mechanisms which can act sequentially, combinatorially or competitively, the integration of which determines the localization distribution of proteins in the cell. In addition, protein localization is often dynamic, and mechanisms exist to allow translocation of proteins to respond to diverse changes in the cell and its environment.
Protein targeting motifs have been identified for all main eukaryotic cellular compartments and represent a highly prevalent mechanism regulating protein localization [2–5]. Targeting motifs typically involve short linear sequences of 3 to 30 amino acids, often found at protein ends or in accessible and/or disordered regions [6, 7]. The first targeting motifs that were described, over thirty years ago, were the signal peptide and the nuclear localization signal (NLS), specifying respectively entry into the secretory pathway through the endoplasmic reticulum, and targeting to the nucleus [8, 9]. In addition to targeting motifs, post-translational modifications (PTMs) are also often involved, either to modulate the accessibility of targeting motifs , to serve as a sorting signal [11, 12], or to anchor proteins in membranes by the addition of lipid chains [13, 14]. Other characterized mechanisms for the regulation of protein localization include targeting or more often retention through interactors which can include proteins, lipids and nucleic acid chains through the use of interaction domains [15–17]. Protein localization often results from the integration, in the proper order, of several of these mechanisms.
The regulation of translocation across the nuclear envelope has been particularly well characterized. Targeting to the nucleus from the cytoplasm typically involves NLSs, several classes of which have been described. Classical NLSs, the first to be identified, are short motifs involving basic residues, and can be divided into two main groups [18, 19]. Monopartite NLSs consist of a stretch of three to four basic residues [9, 18, 20] while bipartite NLSs are composed of two segments of basic residues separated by a linker of 10 to 12 residues . Classical NLSs are recognized by Kapα-Kapβ1 importin heterodimers, of the karyopherin superfamily, for translocation across the nuclear pore complex and into the nucleus . Many non-classical and more diverse NLSs have also been described, including combinations of polar/charged and non-polar residues [3, 21, 22]. More recently, longer nuclear targeting motifs recognized by the karyopherin Kapβ2 and averaging between 20 and 30 residues in length were described . These PY-NLSs (Proline-Tyrosine Nuclear Localization Signals), unlike the classical NLS, do not have a strong consensus for their motifs, which are composed of a hydrophobic or basic N-terminal region and a C-terminal RX2-5PY motif .
Nuclear export sequences (NESs), specifying translocation from the nucleus to the cytoplasm have also been extensively characterized . NESs are short motifs typically containing four hydrophobic residues, and most often leucines, separated by a small number of spacing residues . NESs are also recognized by a member of the karyopherin superfamily of transport receptors, the CRM1 exportin, for export to the cytoplasm .
While the use of NLSs and NESs for nucleocytoplasmic transport is prevalent, some nuclear proteins do not contain these signals [20, 27]. Several such proteins employ other strategies to shuttle to and from the nucleus (for example by piggy-back onto other proteins that do contain NLSs [27–29]) but for most, targeting mechanisms are currently unknown . NLSs and NESs are often regulated by PTMs, and their accessibility can also be regulated by conformational change, allowing a dynamic control of their usage [30, 31].
Here, we investigate of the extent of regulation of protein localization at the pre-translational level, through the study of targeting motif inclusion in transcripts, using the NLS and NES as model signals. The transcriptome-wide characterization of these targeting motifs reveals that 39 % of NLSs are constitutive in the sense that they are present in all coding isoforms of their encoding gene. The remaining 61 % of NLSs are considered to be alternatively regulated as they are not present in all coding transcripts of the same gene. In the case of NESs, 72 % are alternative. The inclusion of most alternative NLSs and NESs is regulated by alternative translation initiation and termination, although direct alternative splicing of the exon encoding the motif is also an important mechanism. The analysis of different deep-sequencing datasets in human indicates that the regulation of the inclusion of these targeting motifs at a pre-translational level can be dynamic and vary according to tissue-type, is more prominently used by proteins with diverse interactors, can be tightly regulated in a combinatorial way, and can be deregulated in disease states. Collectively, our findings show evidence of extensive and tightly-regulated use of pre-translational regulation mechanisms for the inclusion of the NLSs and NESs.
Distribution of NLSs and NESs in transcripts/proteins
The position of NLSs and NESs in protein sequences might also influence how the motif is regulated at a pre-translational level. As shown in Fig. 2c, NLSs and NESs can be present throughout the protein and do not have strong preferences for protein ends. Positioning of motifs in the protein will influence the modes of regulation used to control motif inclusion. To investigate this, we set out to classify and characterize the prevalence of mechanisms regulating the presence of these motifs in transcripts from all genes containing them.
Alternative regulation of the inclusion of NLSs and NESs
We investigated the distribution of the number of coding transcripts containing an NLS or NES constitutively or alternatively. Interestingly, alternative NLSs and NESs are found in genes encoding significantly more transcripts than those containing constitutive NLSs and NESs (Fig. 5b, p-value < 6.3*10−6 for NES and p-value < 5.2*10−12 for NLS using the two sample Kolmogorov-Smirnov test) indicating that genes containing such alternative motifs encode on average a larger and more diverse set of proteins than genes containing constitutive motifs and that the regulation of motif inclusion is responsible for some of the need for co- and post-transcriptional regulation, as previously shown for signal peptides and transmembrane domains [35, 36].
When NLSs are classified according to their subtype as described in the Methods, PY-NLSs are found to be the most regulated in an alternative manner and most likely to be present in more than one exon (67 % of PY-NLSs are alternative and 38 % are encoded in 2 exons; Additional file 4: Figure S1). Unlike monopartite NLSs, bipartite NLSs and non-classified NLSs which are two to four times more likely to be regulated by alternative translation initiation and termination than by splicing, PY-NLSs display equal counts for these three types of regulation (Additional file 4: Figure S1). Thus the diverse group of PY-NLS stands out as the most alternatively regulated subgroup of NLSs.
Quantitative analysis of motif inclusion across normal human tissues
Co-regulation of NLS and NES
Of the remaining 56 % of genes containing both an NLS and NES, but with less or no coordinated occurrence of the motifs (for example MIER1 and RIPK3 in Fig. 8b), the majority show a preference for one of the two motifs across all tissues. For example, the MIER1 NLS is much more prevalent than its NES, while in RIPK3, the NES is always present but the NLS can have a MII as low as 0.39. MIER1 (mesoderm induction early response protein 1) proteins are transcriptional corepressors known to function in the nucleus, although some have been detected in the cytoplasm . Alternative splicing and alternative translation initiation sites result in proteins differing in the presence of their NLS and/or NES  (as shown in Figs. 3d, 4b). The uniformly high NLS MII and low NES MII that we observe (Fig. 8b) are consistent the mainly nuclear role of the protein in normal tissues. In contrast, although known to be capable of translocating to the nucleus during necroptosis , RIPK3 is annotated as mainly functioning in the cytoplasm, propagating the signal from the tumor necrosis factor receptor by phosphorylating its substrates [57, 58], consistent with the presence of a constitutive NES and an alternative NLS. In general, many of the genes encoding both an NLS and NES that are not co-regulated encode proteins that have either large numbers of interactors and diverse functions, including for example PRKD2, SENP2 and KANK1, or have many isoforms annotated as localized in diverse and different compartments (for example MIER1 and PRKD2). Most of these regulate the presence of these motifs in a tissue-specific manner, some displaying switches between a strong presence of the motif (MII near 1) and a near absence (MII near 0) of one of their motifs between different tissues. A small number of patterns of motif inclusion are predominantly used by the cell, and represent tightly controlled programs.
Quantitative analysis of motif inclusion across a panel of breast cancer tissues
As done for the Human body map RNA-seq datasets, the motif inclusion of NLS and NES was quantified across a panel of breast cancer datasets comparing estrogen-positive tumors (ER+), triple negative tumors, HER2-positive tumors (HER2+) and benign tumors  (Additional file 4: Figures S2–S3). Once again, amongst the alternative motifs, a subset of genes display strongly included or strongly excluded NLSs and NESs, with high overlap and same general distribution with the equivalent subsets in the Human Body Map datasets. Despite these general trends, cancer type specific patterns also emerge. For example, the benign breast cancer samples generally cluster separately from the ER+, triple negative and HER2+ breast tumors, in particular for the NLS heatmap, when looking at genes displaying variable MII values, indicating that the inclusion of a subset of these alternative motifs is differentially regulated between benign cell lines and tumors. Such genes include CPSF6, PABPN1, ARNTL, KANK1 and DST, which show striking differences in the NLS MII when benign and non-benign samples are compared (Additional file 4: Figure S2). While some of these genes have been described as either strongly mutated, deleted, deregulated or involved in pathways that are deregulated in specific types of breast-cancer [60, 61], their potential deregulation of localization has not been investigated. These results suggest that specific changes in the inclusion of protein targeting motifs, as regulated at pre-translational levels, might represent events specific to certain tumor types, and could be used as novel biomarkers. They might contribute to cancer phenotype and their study could lead to insight into cancer maintenance and progression.
Discussion and Conclusions
Timely regulation of protein subcellular localization is crucial and underlies many cellular pathways. While protein localization can be controlled through several post-translational mechanisms, cells also regulate protein localization by varying the inclusion of targeting motifs at pre-translational levels [32, 33, 37, 38]. Here, we describe the extensive cellular use of these mechanisms for the control of nucleo-cytoplasmic traffic through the study of the inclusion of NLSs and NESs. The analysis of experimentally validated human NLSs and NESs indicates that these motifs are modular and that their inclusion is regulated by the use of alternative promoter and/or translation initiation, as previously described for signal peptides [35, 36], as well as by alternative splicing, by alternative translation termination, and also by coding frameshift for a small number of genes. Alternative initiation and termination are the predominant mechanisms in use for this regulation as was found for signal peptides and transmembrane domains . The inclusion levels of these motifs, as analyzed quantitatively using RNA-seq datasets, vary from 0 to 100 %, depending on the gene and the tissue type. While many NLSs and NESs are highly included (most or all transcripts generated from the gene containing the motif), others are included at very low levels or at variable levels which, for well characterized proteins, can be explained by their molecular function. A majority of these motifs are not present in a constitutive manner (61 % of NLSs and 72 % of NESs are alternative) making the pre-translational regulation of the inclusion of these motifs a widely used mechanism in the regulation of protein cellular localization.
The pre-translational regulation of the inclusion of targeting motifs is the first of several levels of regulation for these localization signals. Subsequently, once included in proteins, the accessibility of targeting motifs can be modulated by interaction with other molecules or by allostery, and can also be regulated by post-translational modification . In addition, the presence of different targeting motifs within the same protein can lead to competition between the motifs to determine the final localization. These distinct levels of regulation serve different purposes and exhibit different characteristics. While the regulation of targeting motif accessibility is typically a reversible regulation, the pre-translational regulation of their inclusion is irreversible [37, 39], and thus the cell commits to the level of motif inclusion it chooses, and has less flexibility for immediate responses requiring localization translocation. Nonetheless, this mode of regulation does provide the possibility of co-regulation in the case of proteins with significantly different sets of interactors depending on their localization, as seems to be the case in particular for some kinases shuttling between the nucleus and cytoplasm. Thus the inclusion of specific targeting motifs could be coordinated to occur when their substrates/interactors present in the targeted compartment are expressed, for example. The further characterization of this widespread mechanism of regulation of protein localization and the study of its use in combination with post-translational regulation mechanisms will shed light on and lead to better models of the regulation of this fundamental protein characteristic and the causes of its deregulation in disease states.
Human NLSs and NESs were obtained from specialized databases and by manual curation of the literature. 58 NLSs were obtained from the database of experimentally validated localization signals LocSigDB  including 19 NLSs that are also present in NLSdb . Many additional NLSs were identified by manual curation of the literature including 24 PY-NLSs described and listed in . To be included in the list, we required experimental validation including deletion/mutation analysis and targeting of reporter proteins to the nucleus. 116 NESs were obtained from the database of validated NESs ValidNES  and 4 additional NESs by literature curation. References for all NLSs and NESs considered are available in Additional file 1 as well as information regarding the database from which they were extracted and a reference to the article in which their validation is described. NLSs and NESs were only kept if they could be mapped onto their corresponding encoding protein and if their reported amino acid sequence did not exceed 50 amino acids in length , to ensure we are not working with signal patches.
Motif position analysis in exons and proteins
Transcripts and protein sequences, and their genomic positions as well as exon positions were obtained from the Ensembl database human genome build hg38, version 82 . No patches were applied. All data was managed in an in house MySQL database. Motif sequences were mapped onto the encoding protein and then onto the corresponding transcript and ultimately onto the corresponding exon(s), by considering the position of the start codon (coding start) and the positions of all exons obtained from the Ensembl annotations , allowing the evaluation of the number of exons in which the motif is present. A sampling procedure randomly choosing the same number of subsequences of same length as NLSs or NESs from all proteins defined in hg38 was used to evaluate the random distributions.
The relative motif positions were then binned and the resulting counts represented as histograms. To ensure equal representation of genes regardless of the number of isoforms encoded, each gene was given an equal weight in the counts. As genes can code for different isoforms that do not all encode the motif at the same position in the resulting proteins, each coding isoform encoding the motif was considered and given a partial count for the gene, the total count for the gene totaling 1.
Classification of NLSs
Bipartite NLSs were defined as those matching the PDOC00015 prosite profile (two adjacent basic amino acids (Arg or Lys), a spacer region of any 10 residues, at least three basic residues (Arg or Lys) in the five positions after the spacer region) .
Monopartite NLSs were required to conform to the consensus sequence K(K/R)X(K/R) defined in .
PY-NLSs were defined in the paper .
All remaining NLSs were annotated as non-classified with respect to their subtype.
Mode of pre-translational regulation of motif inclusion
A custom track specifying the positions of all NLSs and NESs was generated for visualization with the UCSC Genome Browser by considering the relative position of the motif in the protein sequence, the absolute position of the coding start of the transcript in the hg38 genome build and the absolute positions of the exons of the transcripts in the hg38 genome build. Constitutive motifs were defined as motifs present in all coding transcripts of a gene. In contrast, motifs are considered alternative if there exists at least one coding transcript of the encoding gene that does not contain the motif. Motifs were classified according to the types of pre-translational regulation modulating their inclusion (as defined in Fig. 1) by considering all coding transcripts of the encoding genes using in house scripts. Motifs are considered absent from a transcript if their sequence (according to Additional file 1) is not entirely included in an isoform.
Quantification of motif inclusion by RNA-seq
To quantitatively determine the relative abundance of the transcripts containing the motif compared to the other transcripts of the same gene, we analyzed high-throughput sequencing datasets of 16 different normal human tissues from the Illumina Human Body Map Project (NCBI GEO accession GSE30611). The RNA-seq datasets for the 16 tissues consisted of between 74 and 82 million paired-end reads. The sra-toolkit was used to extract the fastq files from the sra archived datasets  using the fastq-dump command with split-files option. Reads were aligned to the hg38 assembly of the human genome, and quantified per transcript using Kallisto, with the command line kallisto index –k21 .
The GSE45419 datasets consisting of benign breast lesions, ER positive, triple negative and HER2 positive primary breast tumors  were analyzed in the same way as the Human Body Map Project datasets as described above.
The authors are grateful to Profs. Sherif Abou Elela and Martin Bisaillon for their insightful comments and suggestions as well as Leandro Fequino for technical support. SM was supported by a summer student scholarship from the Faculty of Medicine and Health Sciences of the University of Sherbrooke. DCT was supported by a Global Excel scholarship. MSS is a recipient of a Fonds de Recherche du Québec – Santé Research Scholar Junior 1 Career Award. MSS is a member of the RNA group and the Centre de recherche du Centre hospitalier universitaire de Sherbrooke (CRCHUS).
This research project is funded by a grant to MSS by the Natural Sciences and Engineering Research Council of Canada (NSERC). The funder played no role in the design of the study, the collection, analysis, and interpretation of data and in writing the manuscript.
Availability of supporting data and materials
The data sets supporting the results of this article are included within the article and its additional files.
SM, AAA, MJL, DCT and MSS participated in building the database and curating the literature for experimentally validated NLSs and NESs. MJL wrote the SQL queries to map the motifs and their position in transcripts, quantified their inclusion by analyzing RNA-seq data. MJL, DCT and MSS performed the statistical analyses, plotted the data and helped to interpret the results in light of the literature. AAA participated in the design of the experiments and the analysis of the data. MSS conceived and designed the study, participated in the analysis and interpretation of the results and wrote the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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