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1 Frontiers in Life Science ISSN: (Print) (Online) Journal homepage: Bioinformatics-based study on prokaryotic, archaeal and eukaryotic nucleic acid-binding proteins for identification of low-complexity and intrinsically disordered regions Birendra Singh Yadav, Swati Singh, Prashant Kumar, Devika Mathur, Raj Kumar Meena, Rishij Kumar Agrawal & Ashutosh Mani To cite this article: Birendra Singh Yadav, Swati Singh, Prashant Kumar, Devika Mathur, Raj Kumar Meena, Rishij Kumar Agrawal & Ashutosh Mani (2016) Bioinformatics-based study on prokaryotic, archaeal and eukaryotic nucleic acid-binding proteins for identification of lowcomplexity and intrinsically disordered regions, Frontiers in Life Science, 9:1, 2-16, DOI: / To link to this article: Taylor & Francis Published online: 04 Sep Submit your article to this journal Article views: 227 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at Download by: [ ] Date: 02 January 2018, At: 07:33

2 FRONTIERS IN LIFE SCIENCE, 2016 VOL. 9, NO. 1, Bioinformatics-based study on prokaryotic, archaeal and eukaryotic nucleic acid-binding proteins for identification of low-complexity and intrinsically disordered regions Birendra Singh Yadav a, Swati Singh b, Prashant Kumar a, Devika Mathur a, Raj Kumar Meena a, Rishij Kumar Agrawal a and Ashutosh Mani a a Department of Biotechnology, Motilal Nehru National Institute of Technology Allahabad, Allahabad , India; b Center of Bioinformatics, University of Allahabad, Allahabad , India ABSTRACT Intrinsically disordered regions (IDRs) and low-complexity regions (LCRs) in transcription factors (TFs) are known to be key players in various cellular functions. Conformational flexibility of these regions allows them to recognize and interact with a large number of molecules. Previous studies show that certain TFs which are related to environmental response are significantly enriched in IDRs and LCRs. It has been proposed that all organisms in response to environmental conditions use these IDRs and LCRs for introducing versatility in the interactions in biological processes to quickly adapt and respond to challenging environmental conditions. A comparative study has been conducted on these regions to measure the average abundance of LCRs and IDRs in different types of TFs. In this project we have identified the IDRs and LCRs in prokaryotic, eukaryotic and archaeal TFs by using bioinformatics and compared them for average density of IDRs and LCRs. Introduction Low-complexity regions Particular segments of protein sequences having biased amino acid composition, frequently called lowcomplexity regions (LCRs), are abundant in the protein universe (Coletta et al. 2010). The degree of low complexity may be dependent on loosely clustered, irregularly spaced or periodically prevalent aminoacidspresentwithalimitedquantityofdiversity (DePristo et al. 2006). A number of studies have revealed that LCRs exhibit significant divergence across protein families and the genetic mechanisms from which they arise provide them remarkable degrees of compositional plasticity (Coletta et al. 2010). Evolution of LCRs is a rapid process caused by highly dynamic diversifications and high level of inter species variations (Marcotte et al. 1999; Ekman et al. 2006).Theseregionsarestructurallyandfunctionally neutral, with a high probability of fixation (Ekman et al. 2006). It has been proposed that construction of repeats is a common source of genetic variation among prokaryotes to generate novel surface antigens ARTICLE HISTORY Received 8 September 2014 Accepted 19 July 2015 KEYWORDS Low-complexity regions; intrinsically disordered regions; archaea and adapt to swiftly evolving environments (Moxon et al. 1994;Verstrepenetal.2005; Coletta et al. 2010). The flexibility of LCRs is thought to be accountable for their adaptable binding capabilities. This flexibility allows LCRs to bind with adverse classes of structurally variable targets (Dyson & Wright 2005). The effect of presence of repeats on the structure of the host protein depends on their amino acid composition, though LCRs have a tendency to form loops or disordered structure. LCRs are particularly frequent in transcription factors (TFs) and it has been shown that variations in length of particular single amino acid repeat such as glutamine, proline or alanine can result in transcriptional activity of the protein. Statistical analyses have revealed that approximately one-quarter of the amino acids are present in LCRs and generally more than half oftheproteinshaveatleastonelcr(wootton1994). Intrinsically disordered regions An intrinsically disordered region (IDR) in protein lacks a definite or ordered three-dimensional CONTACT Ashutosh Mani amani@mnnit.ac.in 2015 Taylor & Francis

3 FRONTIERS IN LIFE SCIENCE 3 structure. IDRs cover a spectrum of shapes from fully unstructured to partially structured and include random coils, (pre-) molten globules, and large multi-domain proteins connected by flexible linkers. IDRs lack stable structure while in some cases, they can acquire a fixed three-dimensional structure (a) Figure 1. (a) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to ligases and their homologs. (b) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to primases and their homologs. (c) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to ribonucleases and their homologs. (d) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to RNA polymerase II and their homologs. (e) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to RNA polymerases and their homologs. (f) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to DNA topoisomerases and their homologs.

4 4 B.S. YADAV ET AL. (b) Figure 1. Continued. after binding to their target (Dyson & Wright 2005; Tompa 2009; Uversky and Dunker 2010). The binding affinity of many disordered proteins with their receptors is regulated by post-translational modification and the flexibility of disordered proteins facilitates the different conformational requisites for binding the modifying enzymes as well as their targets. It has been reported that the proteins involved in binding with other macromolecules, regulatory and signalling functions inside the cell such as TFs and signalling proteins, have higher extent of IDRs (Ward et al. 2004; Dyson & Wright 2005;Tompa2009; Uversky & Dunker 2010). Absence of a fixed three-dimensional structure in aproteinhasseveraladvantages(gunasekaranetal. 2003; Dyson & Wright 2005;Diellaetal.2008;Gsponer &Babu2009; Tompa2009; Uversky & Dunker 2010).

5 FRONTIERS IN LIFE SCIENCE 5 Figure 1. Continued. First of all, the unstructured region provides a larger surface area for interaction in comparison to globular proteins of a similar length, and second they provide conformational flexibility, and the exposure of short linear peptide motifs and interaction-prone structural motifs, that is, Molecular Recognition Features, allow intrinsically disordered proteins to scaffold and interact with several other proteins. Finally, diverse post-translational modifications in these proteins facilitate the regulation of their function and stabilityinacell.inaddition,asmanyintrinsicallydisordered proteins fold upon binding, they frequently interact with their targets with relatively high specificity. But their affinity for their targets remains low. This specific mechanism of action, by which IDRs associate rapidly with their target in order to initiate

6 6 B.S. YADAV ET AL. (d) Figure 1. Continued. a signalling process and at the same time dissociate easily when the task is accomplished, is functionally significant (Dyson & Wright 2005). Archaeal transcriptional machinery Life on the earth is present in the form of three cellular domains, namely prokaryotes, eukaryotes and archaea (Woese 1998), and is composed of organisms highly diverse in morphology, physiology and natural habitats (Chaban et al. 2006; Clementinoetal.2007; Nam et al. 2008; Auguet et al. 2009). Archaea constitute one of the important cellular domains of life and the organisms included in this cellular domain possess basal transcription machinery resembling that of eukaryotes. Some of the eukaryotic-type machineries that archaea possess include TATA box promoter sequence,

7 FRONTIERS IN LIFE SCIENCE 7 (e) Figure 1. Continued. a TATA box-binding protein (TBP), a homolog of the TF TFIIB (TFB) and an RNA polymerase (RNAp) containing between 8 and 13 subunits (Goede et al. 2006; Rueda & Janga 2010). The archaeal TFs are significantly smaller in comparison to other proteins in archaea as well as bacterial TFs, suggesting that a large number of these small-sized TFs could compensate the probablescarcityoftfsinarchaea,bypossiblyforming different combinations of monomers similar to that observed in eukaryotic transcriptional machinery (Rueda & Janga 2010). The study by Bin and co-workers proposes that archaeal proteins are rich in intrinsic disorder which evolve to help archaea

8 8 B.S. YADAV ET AL. (f) Figure 1. Continued. toaccommodatetotheirhostilehabitats(xueetal. 2010). The aim of this study was to identify LCRs and IDRs in archaeal, bacterial and eukaryotic TFs and compare them with their homologs from other life forms. To identify LCRs, SEG server (Wootton 1994) has been used while DISMETA has been used to identify IDRs. Materials and methods Sequence search Initially 50 TF families were selected for the study and finally 15 sequences of archaeal TFs families were foundtohavehomologsinatleastoneprokaryote or eukaryote. These sequences were retrieved from ArchaeaTF database (Wu et al. 2008). Their closest

9 FRONTIERS IN LIFE SCIENCE 9 (a) (b) (c) (d) (e) (f) Figure 2. (a) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to FIC and their homologs. (b) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to FUR and their homologs. (c) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to GntR and their homologs. (d) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to LacI and their homologs. (e) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to LexA and their homologs. (f) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to LysR and their homologs. (g) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to MarR and their homologs. (h) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to PadR and their homologs. (i) The phylogenetic tree represents evolutionary relationship among 30 organisms from prokaryotes, eukaryotes and archaea with respect to PspC and their homologs.

10 10 B.S. YADAV ET AL. (g) (h) (i) Figure 2. Continued. homologs, available in public domain, from bacteria and eukaryotes were searched by using BLAST of NCBI (Altschul et al. 1997). Identification of LCRs A total of 180 amino acid sequences belonging to six nucleic acid-interacting protein families from 30 species (10 from each) of prokaryotes, eukaryotes and archaea were selected for the identification of LCRs (see Tables 1 6 in online supplemental data which is available from the article s Taylor & Francis Online page at / ). SEG server was used for LCR identification (Wootton 1994). For each sequence of any species, the overlapping regions of LCRs were identified to avoid repetitions in average calculation. The length of LCR was counted and average percentage of LCR was calculated for the whole length of amino acid sequence. Finally for the calculation of average density of LCRs in archaeal sequences, all the average percentage of LCR for individual sequence belonging to archaea were summed and their average was calculated. This method was also repeated for prokaryotic and eukaryotic sequences. Identification of disordered regions A total of 63 amino acid sequences belonging to 9 nucleic acid-interacting protein families from 32 speciesofprokaryotes,eukaryotesandarchaeawere selected for the identification of IDRs (see Tables 7 15 in supplemental data). DISMETA (Huang et al. 2014) server was used for IDR identification. The length of IDR was counted and average percentage of LCR was calculated for the whole length of amino acid sequence. Finally, for the calculation of average density of LCRs in archaeal sequences all the average percentage of IDR for individual sequence belonging to archaea were summed and their average was calculated. This method was repeated for the calculation of average density of IDRs in prokaryotic and eukaryotic sequences. Multiple sequence alignment and phylogenetic tree Multiple sequence alignment and phylogenetic tree construction were performed by using MEGA 6.06

11 FRONTIERS IN LIFE SCIENCE 11 (a) (b) (c) Figure 3. (a) Composition of sequences based on physicochemical property of amino acids present in LCRs of archaea. Numerical value represents the percentage of specific amino acid in the LCR region of archaea. (b) Composition of sequences based on physicochemical property of amino acids present in LCRs of eukaryotes. Numerical value represents the percentage of specific amino acid in the LCR region of eukaryotes. (c) Composition of sequences based on physicochemical property of amino acids present in LCRs of prokaryotes. Numerical value represents the percentage of specific amino acid in the LCR region of prokaryotes.

12 12 B.S. YADAV ET AL. (a) (b) (c) Figure 4. (a) Composition of sequences based on physicochemical property of amino acids present in IDRs of archaea. (b) Composition of sequences based on physicochemical property of amino acids present in IDRs of prokaryotes. (c) Composition of sequences based on physicochemical property of amino acids present in IDRs of eukaryotes.

13 FRONTIERS IN LIFE SCIENCE 13 (Tamura et al. 2013) software. All the homologous sequences were first aligned and then manually curated. Maximum likelihood method of construction was used for tree construction for sequences used in the identification of LCRs (Figure 1(a) (f)) and IDRs (Figure 2(a) (i)). Physicochemical property studies Forassessingthephysicochemicalpropertiesofthe residues involved in the construction of LCRs, COPID server was used ( copid/help.html). Percentage of small, polar and chargedresiduesintheseregionswascalculatedfor sequencesfallingintheregionoflcrs(figure3(a) (c)) and IDRs (Figure 4(a) (c)). Phosphorylation site prediction NetPhos 2.0 (Blom et al. 1999) server was used for prediction of phosphorylation sites in protein (a) sequences. Phosphorylation sites in disordered regions were predicted separately. The prediction included phosphorylation sites of tyrosine serine and threonine residues. Results and discussion The amino acid composition studies revealed that prokaryotic, eukaryotic and archaeal LCRs are having highest percentage of small residues followed by polar residues while in the IDRs of archaea small residues and neutral residues are leading type of amino acids. Eukaryotic IDRs follow the same pattern as in case of LCRs. Phosphorylation site studies revealed that in case of eukaryotes probability of occurrence of a serine, tyrosine or threonine phosphorylation site is lower (i.e. 7.3%) in comparison to full length sequence where the occurrence of phosphorylation site was foundtobe8.0%.onthesamepatternthesevalues were 7.99 and 5.9 for archaea. In previous reports intrinsically disordered proteins have been found (b) Figure 5. (a) Average density of LCRs in prokaryotes, eukaryotes and archaea for primases, DNA ligases, ribonucleases and their homologs. (b) Average density of LCRs in prokaryotes, eukaryotes and archaea for RNA polymerase II, RNA polymerase, topoisomerases and their homologs.

14 14 B.S. YADAV ET AL. to be substantially enriched in polar and disorderpromoting amino acids (Ala, Arg, Gly, Gln, Ser, Glu and Lys) as well as Pro residues that are hydrophobic in nature and have significant role in structure-breaking (Dunker et al. 2001; Romeroetal.2001; Williams et al. 2001). It is pertinent to mention here that these biases in the amino acid compositions of IDPs are also consistent with the low overall hydrophobicity and high net charge (Uversky et al. 2000). In the present study, it was observed that prokaryotic IDRs are high in small, neutral and hydrophobic residues while in eukaryotes these regions are (a) (b) (c) Figure 6. (a) Average density of IDRs in prokaryotes, eukaryotes and archaea for FUR proteins, GntR proteins, FIC proteins and their homologs. (b) Average density of IDRs in prokaryotes, eukaryotes and archaea for Lac I proteins, Lex A proteins, PadR proteins and their homologs. (c) Average density of IDRs in prokaryotes, eukaryotes and archaea for MarR I proteins, PspC A proteins, LysR proteins and their homologs.

15 FRONTIERS IN LIFE SCIENCE 15 rich in small, polar and neutral residues followed by hydrophobic residues. Archaeal IDRs were reported to be rich in small, polar and hydrophobic residues (Figure 4(a) (c)). Archaea have higher average percentage density of LCRs The average density of LCRs for ribonucleases, DNA ligase, DNA primase, DNA topoisomerase and RNA polymeraseiwasfoundtobehigherthanprokaryotes (Figure 5(a) and (b)). In all these cases, except for RNA polymerase II, these LCR densities are even higher than their homologs in eukaryotes. However, forribonucleaseproteintheaveragedensityoflcrs in prokaryotes is higher than eukaryotes. Finally, the averagedensityoflcrsinprokaryotic,eukaryoticand archaeal sequences is , and 19.25, respectively. Thus the archaeal transcriptional machinery has the highest density of LCRs in the proteins used in this study. For the proteins that were in life form but not present in any other life form, their closest homologs obtained by BLAST search in NCBI were used as representative of the protein. Archaeal TFs are generally not rich in terms of IDRs The average density of IDRs for FUR, GntR, LexA, MarR and LysR is higher than prokaryotes and eukaryotes (Figure 6(a) (c)). While in the case of FIC and PspC, it is higher than prokaryote and eukaryote, respectively. For PadR and LacI, the average density ofarchaealidrsislowerthanbothprokaryotesand eukaryotes. From the above results, it is clear that archaea generally possess higher average density of LCRs while they are not rich in IDRs. Though some proteins such as FUR, GntR, LexA, MarR and LysR have higher density for IDRs, this trend is generally not followed by other proteins such as PadR, FIC, PspC and LacI. All these proteins have higher average density of IDRs in prokaryotes in comparison to archaea. Conclusion The archaeal transcription apparatus is a simplified form of the eukaryotic transcription machinery. It is known that archaea have prokaryotic type of transcriptional machinery, since 53% of archaeal TFs are homologs of bacterial TFs, but they have to work foraneukaryotictypeofproteinsynthesissystem. Despite having relatively smaller TFs that is similar to prokaryotic TFs, archaea possess higher average density of LCRs in comparison to prokaryotes and eukaryotes. However, this correlation with complexity of functions is not true in the case of IDRs where no set trend was observed. Probably LCRs provide them enough flexibility for protein protein interactions for the formation of homo hetero multimers and work in a manner that resembles with eukaryotic-type mechanisms. Acknowledgements BSY and SS analyzed the data and helped in writing the manuscript. PK, DM, RKM and RJ performed sequence retrieval and software runs, and AM conceived and supervised this project. Disclosure statement No potential conflict of interest was reported by the authors. Funding Supplemental data Supplemental data for this article can be accessed here. [doi: / ] References AprojectresearchgrantTEQIP-IItoAMishighlyacknowledged. AltschulSF,MaddenTL,SchafferAA,ZhangJ,MillerW,Lipman DJ Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25: Auguet JC, Barberan A, Casamayor EO Global ecological patterns in uncultured archaea. ISME J. 4: Blom N, Gammeltoft S, Brunak S Sequence- and structure-based prediction of eukaryotic protein phosphorylation sites. J Mol Biol. 294(5): Chaban B, Ng SY, Jarrell KF Archaeal habitats from the extreme to the ordinary. Can J Microbiol. 52: Clementino MM, Fernandes CC, Vieira RP, Cardoso AM, Polycarpo CR, Martins OB Archaeal diversity in naturallyoccurringandimpactedenvironmentsfromatropical region. J Appl Microbiol. 103: Coletta A, Pinney JW, Solís DYW, Marsh J, Pettifer SR, Attwood TK Low-complexity regions within protein sequences have position-dependent roles. BMC Syst Biol. 4:43. doi: /

16 16 B.S. YADAV ET AL. DePristo M, Zilversmit M, Hartl D On the abundance, amino acid composition, and evolutionary dynamics of lowcomplexity regions in proteins. Gene. 378: DiellaF,HaslamN,ChicaC,BuddA,MichaelS,BrownNP, Trave G, Gibson TJ Understanding eukaryotic linear motifs and their role in cell signaling and regulation. Front Biosci. 13: Dunker AK, Lawson JD, Brown CJ, Williams RM, Romero P, Oh JS, Oldfield CJ, Campen AM, Ratliff CM, Hipps KW, et al Intrinsically disordered protein. J Mol Graph Model. 19(1): Dyson H, Wright P Intrinsically unstructured proteins and their functions. Nat Rev Mol Cell Biol. 6: Ekman D, Light S, Bjorklund A, Elofsson A What properties characterize the hub proteins of the protein-protein interaction network of the protein-protein interaction network of Saccharomyces cerevisiae? Gen Biol. 7(6):R45. doi: /gb r45 Goede B, Naji S, Kampen OV, Ilg K, Thomm M Protein protein interactions in the archaeal transcriptional machinery: binding studies of isolated RNA polymerase subunits and transcription factors. J Biol Chem. 281: Gsponer J, Babu MM The rules of disorder or why disorder rules. Prog Biophys Mol Biol. 99: Gunasekaran K, Tsai CJ, Kumar S, Zanuy D, Nussinov R Extended disordered proteins: targeting function with less scaffold. Trends Biochem Sci. 28: Huang YJ1, Acton TB, Montelione GT DisMeta: a meta server for construct design and optimization. Methods Mol Biol. 1091:3 16. Marcotte E, Pellegrini M, Yeates T, Eisenberg D A census of protein repeats. J Mol Biol. 293: Moxon E, Rainey P, Nowak M, Lenski R Adaptive evolution of highly mutable loci in pathogenic bacteria. Curr Biol. 4: Nam YD, Chang HW, Kim KH, Roh SW, Kim MS, Jung MJ, Lee SW, Kim JY, Yoon JH, Bae JW Bacterial, archaeal, and eukaryal diversity in the intestines of Korean people. J Microbiol. 46: Romero P, Obradovic Z, Li X, Garner EC, Brown CJ, Dunker AK Sequence complexity of disordered protein. Proteins. 42(1): Rueda EP, Janga SC Identification and genomic analysis of transcription factors in archaeal genomes exemplifies their functional architecture and evolutionary origin. Mol Biol Evol. 27(6): Tamura K, Stecher G, Peterson D, Filipski A, Kumar S MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol. 30: Tompa P Structure and function of intrinsically disordered proteins. 1st ed. Boca Raton: Chapman and Hall/CRC. Uversky VN, Dunker AK Understanding protein nonfolding. Biochim Biophys Acta. 1804: Uversky VN, Gillespie JR, Fink AL Why are natively unfolded proteins unstructured under physiologic conditions? Proteins. 41(3): Verstrepen K, Jansen A, Lewitter F, Fink G Intragenic tandem repeats generate functional variability. Nat Genet. 37(9): Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J Mol Biol. 337: Williams RM, Obradovi Z, Mathura V, Barun W, Garner EC, Young J, Takayama S, Brown CJ, Dunker AK The protein non-folding problem: amino acid determinants of intrinsic order and disorder. Pac Symp Biocomput. 6: Woese C The universal ancestor. Proc Natl Acad Sci USA. 95: Wootton JC Non-globular domains in protein sequences: automated segmentation using complexity measures. Comput Chem. 18(3): Wu J, Wang S, Bai J, Shi L, Li D, Xu Z, Niu Y, Lu J, Bao Q ArchaeaTF: an integrated database of putative transcription factors in archaea. Genomics. 91(1): Xue B, Williams RW, Oldfield CJ, Dunker AK, Uversky VN Archaic chaos: intrinsically disordered proteins in archaea. BMC Syst Biol. 4(Suppl 1): S1. doi: / s1-s1