LNP bioinformatical analyses

The analysis of lnp sequence proved orthologus counterparts in a wide-range of organisms from plants to vertebrates. Database analyses suggest that in all species examined, a single gene is coding for LNP (Figure 1A- Ensembl evolutionary tree of LNP genes identified at the moment). Peptide stats for mouse, human and worm LNP as predicted and listed in Ensembl database are presented in the table below (Table 1).

Peptide stats Mouse Human C. elegans Ave. residue weight 111.76 111.46 112.74

Charge -8 -16 12

Isoeectric point 4.94 4.6 9.26

Molecular weight 47.5 47.15 38.557

Number of residues 425 423 342

Table 1. LNP predicted stats

4.3.1 PREDICTED DOMAINS

As protein features analyses identified for both mouse and human protein sequence are (Figure 1B and table 2):

- two transmembrane domains - several low-complexity regions - several coiled-coil regions - proline-rich domain

Mouse Human C. elegans

Region Start End Start End Start End

Transmembrane 44 66 39 61 40 62

Transmembrane 76 98 71 93 72 94

Proline-rich 178 245 173 245

Coiled coil 18 41 16 36

Coiled coil 102 122 97 117

Low complexity 177 198 173 193 33 46

Low complexity 228 245 228 245

Low complexity 383 401 326 340

Low complexity 382 394

Table 2. Predicted protein features in mouse, human and C. elegans LNP protein

The presence of predicted two transmembrane regions classifies the LNP proteins in the category of multi-pass membrane proteins. The C-terminal end is predicted to be an intracellular region.

The proline-rich domain is common for the small proline-rich proteins, which are expressed as a result of a signal transduction cascade activated by the presence of damage

Figure 1. A) left - Ensemble genomic structure for human, mouse and C. elegans lnp; right - the evolutionary tree as generated by Ensemble database B) LNP protein predicted structure presents 2 transmembrane domains and a putative atypical Zn-finger. Putative post-translational modification sites are presented in different colours.

and Gln and are either structural proteins or metal-binding proteins. They can also bind DNA, since they contain many Lys, Ser and Thr residues, which are known to mediate DNA-binding in repressor proteins.

Recently, a new prediction tool became available at National EMBnet node Austria (http://vienna.at.embnet.org/cgi-bin/EMBnet/9aaTAD/9aaTAD_v5.cgi) (Piskacek et al., 2007).

This tool is able to identify a Nine Amino Acids Transactivation Domain (9aaTAD). The 9aa motif that is present in a subset of mammalian, yeast and viral transcription factors has been proposed to mediate the interaction with general co-factors. It is an essential part of the transactivating function of, e.g., p53, VP16, HSF1, NF-kB, NF-IL16, NF-AT and Sox18, all of which interacting with the transcriptional cofactor TAF9 (Piskacek et al., 2007; Sandholzer et al., 2007) and possessing an autonomous transactivation activity in both yeast and mammalian cells. Using the 9aaTAD prediction tool, several “perfect match” of this motif was found in the

Q9C0E8-2 IVYLWYLPDEFTARLAMTLPFFAFPLIIWSIRTVIIFFFSKRTERNNEALDDLKSQRKKI 114 Q7TQ95-1 IVYLWYLPDEFTARLVMTLPFFAFPLIIWTLRTVLIFFFSKRTERNNEALDDLKSQKKKI 119 Q17667-1 MAHTWLRFEDPQKTYVACALMLGAIGIVLAGRYVINGFFSWRTNRTTQKLENAISQKTTL 114 :.: * :: . ::. *: : * *: *** **:*..: *:: **:..:

Q9C0E8-2 LEEVMEKETYKTAKLILERFDPDSKKAKECEPPSAGAAVTARPGQEIRQRTAAQRNLSPT 174 Q7TQ95-1 LEEVMEKETYKTAKLILERFDPDSKKAKEFEPPSAGAAVTAKPGQEIRQRTAAQRNLSPA 179 Q17667-1 LDLVKETLKFKEAKEILDRYEKIEQNTTIDK---NDSTLKSPSPIKKLTADSSMFATP 169 *: * *. .:* ** **:*:: .:::. : * :. . *:: ** . ::..

Q9C0E8-2 PASPNQGPPPQVPVSPGPPKDSSAPGGPPERTVTPALSSNVLPRHLGSPATSVPGMGLHP 234 Q7TQ95-1 PASSSQGPPPQGPVSPGPAKDASAPGGPPERTVAPAL---PRRLGSPATSVPGMGLHP 234 Q17667-1 KQEQKR---VETPTAQGPNSAMNSMNMTP---YHQRNRNAVP--- 205 . .: : *.: ** . .: . .* .:**

Q9C0E8-2 PGPPLARPILPRERGALDRIVEYLVGDGPQNRYALICQQCFSHNGMALKEEFEYIAFRCA 294 Q7TQ95-1 PGPPLARPILPRERGALDRIVEYLVGDGPQNRYALICQQCFSHNGMALKEEFEYIAFRCA 294 Q17667-1 ---IRPFL-RQTTAFDRVLDYFMSDGPNCRNALICSICHTHNGMSTPAEYPYISFRCF 259 **:* *: *:**:::*::.***: * ****. *.:****: *: **:***

Q9C0E8-2 YCFFLNPARKTRPQAPRLPEFSFEKRQVVEGSSSVGPLPSGSVLSSDNQFNEESLEH-DV 353 Q7TQ95-1 YCFFLNPARKTRPQAPRLPEFSFEKRQAVEGSSSTGPTLLESVPSAESQLIEDSLEEQDV 354 Q17667-1 ECGHLNPAKKMGPQIP-LTRPPMGPK-GIQHNGRVGPS--- 295 * .****:* ** * *.. .: : :: .. .**

Q9C0E8-2 LDDNTEQTDDKIPATEQTNQVIEKASDSEEPEEKQE-TENEEASVIETNSTVPGADSIPD 412 Q7TQ95-1 LDNSTEQRDDKIPVTEQTSQVIEKTSGPEEPAENQEETENEETSTNEAKSPVLRADSVPN 414 Q17667-1 -ENTHNMMENQKPSTDLT---PSASQNGSEKGSDSENEKVPESKTMETEFH--- 342 ::. : ::: * *: * .* .:: *: . :***:.. :: ..

Q9C0E8-2 PELSGESLTAE 423 Q7TQ95-1 LEPSEESLVTK 425 Q17667-1 ---

4.3.2 PREDICTED POST-TRANSLATIONAL MODIFICATIONS

A rapid and efficient method of modulating the properties of cellular proteins after their synthesis is the reversible, covalent attachment of modifying groups. Posttranslational modifications include small entities such as phosphate or acetyl groups, but also entire protein moieties, such as the members of the ubiquitin or SUMO families (Hunter, 2007).

Phosphorylation

Cell signalling mechanisms often transmit information via posttranslational protein modifications, most importantly reversible protein phosphorylation. Both mouse and human LNP are predicted to be phosphoproteins (http://ams2.bioinfo.pl) and included in the Phospho.ELM database of experimentally verified phosphorylation sites (http://phospho.elm.eu.org). This prediction was validated by several independent large-scale studies (Ballif et al., 2004; Munton et al., 2007; Olsen et al., 2006). In the phosphoproteomic analysis of the developing mouse brain, Ballif et al. reported that lunapark is harbouring minimal 14-3-3 family members binding motif RXXSXP (marked in blue on the alignment). The S424: S-X-X-pS/pT binding motif was reported to be phosphorilated by Olsen et al in another large-scale study about the phosphoproteins dynamics after epidermal growth factor (EGF) stimulation of HeLa cells. In this case the kinase thought to be responsible for the phosphorilation was CK1.

The NetPhosK 1.0 Server (http://www.cbs.dtu.dk/services/NetPhosK) predictions for the S411, S421, and T424 are listed in the table 3.

Phosphorilation site Kinase Score

RSK 0.52

CaM-II 0.51 S-411

PKA 0.72

S-421 CK1 0.57

T-424 PKC 0.52

Table 3. Predicted phosphorilation sites in LNP along with the most probable kinase responsible for the phosphorilation.

SUMOylation

SUMO modification of proteins has several functions, of which the most frequent and best studied are protein stability, nuclear-cytosolic transport and transcriptional regulation (mostly transcriptional repression)(reviewed in (Wilson and Heaton, 2008). As opposed to ubiquitin modification, which targets proteins for degradation, SUMOylation increases a protein's lifetime. It can also change a protein's location in the cell. For example, the Sumo modification of hNinein leads to its movement from the centrosome to the nucleus (Cheng et al., 2006). In most cases, Sumo attachment to transcriptional regulators correlates with inhibition of transcription (reviewed in (Gill, 2005). Most SUMO-modified proteins contain the tetrapeptide motif B-K-x-D/E where B is a hydrophobic residue, K is the lysine conjugated to SUMO, x is any amino acid, D or E is an acidic residue. SUMOplot™ is an online free access software

developed to predict the probability for the SUMO consensus sequence (SUMO-CS) to be engaged in SUMO attachment (http://www.abgent.com.cn/doc/sumoplot).

Species Position Group Score

Human K288 HNGMA LKEE FEYIA 0.91

Mouse K284 HNGMA LKEE FEYIA 0.91

Rat K284 HNGMA LKEE FEYIA 0.91

C. elegans K151 KNDST LKSP SPIKK 0.80

Table 4. The most probable sites for SUMOylation for human, mouse, rat and C. elegans LNP protein.

The SUMOplot™ score system is based on two criteria: 1) direct amino acid match to the SUMO-CS observed and shown to bind Ubc9, and 2) substitution of the consensus amino acid residues with amino acid residues exhibiting similar hydrophobicity. SUMOplot™ has been extensively used in the past to predict Ubc9 dependent sites. The best SUMO sites predicted for LNP are listed in Table 4 (and marked in green on alignment). It is known that SUMOylation can provide protection against degradation and that certain amino acid sequences appear to be signals for degradation. One such sequence is known as the PEST sequence – a peptide rich in proline (P), glutamic acid (E), serine (S), and threonine (T) (Chevaillier, 1993). This sequence is associated with proteins that have a short intracellular half-life; hence, it is hypothesized that the PEST sequence acts as a signal peptide for protein degradation (Garcia-Alai et al., 2006). The degradation may be mediated possibly via the proteosome or calpain. An example of PEST containing protein is the transcription factor Gcn4p. This protein is 281 amino acids in length and the PEST sequence is found at positions 91-106. The normal half-life of this protein is about 5 minutes. However, if the PEST sequence (and only the PEST sequence) is removed, the half-life increases to 50 minutes (Pries et al., 2002). EMBnet Austria PESTfind program (https://emb1.bcc.univie.ac.at/cgi-bin/EMBnet/PESTfind) can provide information about putative PEST sequences and respectively, about the intracellular life span of LNP proteins, respectively (Table 5).

Human 199 KDSSAPGGPPER 210

PESTfind score : +8.80 mole fraction of PEDST : 42.73 hydrophobicity index : 29.41

Mouse 320 RQAVEGSSSTGPTLLESVPSAESQLIEDSLEEQDVLDNSTEQR 362 PESTfind score : +8.80

mole fraction of PEDST : 49.19 hydrophobicity index : 36.50 378 KTSGPEEPAENQEETENEETSTNEAK 403 PESTfind score : +23.41 mole fraction of PEDST : 61.72 hydrophobicity index : 21.07 C. elegans 306 KPSTDLTPSASQNGSEK 322

PESTfind score : +8.82

mole fraction of PEDST : 44.94 hydrophobicity index : 31.79

Table 5. The putative PEST sequences in human, mouse and C. elegans LNP proteins.

The presence of the atypical Zn-finger, the 9aaTAD motif and the PEST sequence in the LNP protein reinforce the hypothesis that LNP might be a transcription factor. Its intracellular life span is regulated by posttranslational modifications like phosphorilation and SUMOylation.

Both phosphorilation and sumoylation sites are conserved though evolution, suggesting their biologically meaningfulness. Another well-established fact is that the ubiquitin/proteasome system plays a major role in transcription factor degradation. A prominent example is p53, whose degradation by means of ubiquitin-mediated proteolysis is initiated by the ubiquitin ligase Mdm2 (reviewed in (Clegg et al., 2008). At the same time, however, ubiquitylation of transcription factors within transcriptional activation domains has been demonstrated in many cases to promote rather than repress gene expression. Consistent with the concept of SUMO acting as an ubiquitin antagonist, the SUMO system has been found to be associated predominantly with transcriptional repression. However, there is no example of a case where both of these regulatory principles apply to the same protein. Although SUMO-dependent stabilization has been reported for the short-lived transcription factor c-Myb (Bies et al., 2002), this does not appear to be due to competition with ubiquitylation, as mutation of the SUMO acceptor sites does not abolish ubiquitylation or degradation of the protein. Instead, the stabilizing effect of SUMO might be due to sequestration of the protein into a transcriptionally repressive environment. An alternative silencing strategy might involve the recruitment of co-repressors, such as histone deacetylases, by sumoylation of promoter-associated proteins.

Even histones have been found to be targets of the SUMO system, with a negative impact on transcription, but again, despite the fact that histone ubiquitylation is often found associated with transcriptionally active chromatin, there is no evidence for competition between the two modifiers. Antagonistic effects of ubiquitin and SUMO are also observed in the case of the cAMP-response element-binding protein CREB. While hypoxia elicits ubiquitin-dependent degradation of CREB and thus promotes the expression of proinflammatory genes, this effect is transient, and the downregulation of inflammation upon prolonged exposure to hypoxic conditions was found to be accompanied by the sumoylation of CREB, resulting in stabilization and nuclear localization of the protein. Thus, the two modifiers impose an opposite fate on their common target, but instead of competing, they act successively. The mechanisms by which SUMO mediates transcriptional silencing appear to be largely independent of the ubiquitin system (Ulrich, 2005).

4.3.3 PREDICTED INTERACTIONS

A large-scale mapping of human protein-protein interactions by mass spectrometry (Ewing et al., 2007) reported one predicted partner for LNP: CHMP1A, a component of the endosomal sorting required for transport complex III (ESCRT-III), which is composed of at least

CHMP1A, CHMP1B, CHMP2A, CHMP2B, CHMP3/VPS24, CHMP4A/SHAX2,

CHMP4B/SHAX1, CHMP4C/SHAX3, CHMP5/SNF7DC2 and CHMP6/VPS20. The ESCRT-III complex is required for multivesicular bodies (MVBs) formation and sorting of the endosomal cargo proteins into MVBs (Hurley, 2008). The MVB pathway mediates delivery of transmembrane proteins into the lumen of the lysosome for degradation. The ESCRT-III complex is probably involved in the concentration of MVB cargo and may be involved in chromosome condensation (targets the Polycomb group (PcG) protein BMI1/PCGF4 to regions of condensed chromatin), may play a role in stable cell cycle progression and in PcG gene silencing. In case of infection, the HIV-1 virus takes advantage of the ESCRT-III complex for budding and exocytic cargos of viral proteins (von Schwedler et al., 2003). The subcellular compartments which contain CHMP1A are cytoplasm, endosome membrane, peripheral membrane and nucleus matrix. The cytoplasmic form of CHMP1A is partially membrane-associated and localizes to early endosomes, the nuclear form remains membrane-associated with the chromosome scaffold during mitosis. On overexpression, it localizes to nuclear bodies characterized by nuclease-resistant condensed chromatin.

Although the bioinformatical analyses of the LNP-1 gene could not provide a definitive answer concerning its function, the results obtained by applying these tools were valuable as they either confirmed our previous experimental findings or suggested new research directions for deciphering the LNP-1 function. Using the results of the bioinformatical analyses presented above we were able to plan new experimental approaches designed to:

1. confirm the importance of the functional domains found in the LNP-1;

1. understand the specific role of LNP-1 in the nervous system;

2. identify new partners and pathway in which LNP-1 is acting.

For example, the domain prediction tools pointed out several regions with putative functional importance for LNP-1 such as the 9aaTAD domain. By altering these domains we could gather insights into the regulatory role of LNP-1. Moreover the type of the post-translational modifications, such as phosphorylation and SUMO-ylation and the tissular and subcellular predicted localization reconfirmed a functional (versus structural) role for LNP-1 and allowed us to narrow down the number of pathways in which this protein might be involved.