Skip to main content

sHSPdb: a database for the analysis of small Heat Shock Proteins

Abstract

Background

small Heat Shock Proteins (sHSP) is a wide proteins family. SHSP are found in all kingdoms and they play critical roles in plant stress tolerance mechanisms (as well as in pathogenic microorganisms and are implicated in human diseases).

Results

sHSPdb (small Heat Shock Proteins database) is an integrated resource containing non-redundant, full-length and curated sequences of sHSP, classified on the basis of amino acids motifs and physico-chemical properties. sHSPdb gathers data about sHSP defined by various databases (Uniprot, PFAM, CDD, InterPro). It provides a browser interface for retrieving information from the whole database and a search interface using various criteria for retrieving a refined subset of entries. Physicochemical properties, amino acid composition and combinations are calculated for each entry. sHSPdb provides automatic statistical analysis of all sHSP properties. Among various possibilities, sHSPdb allows BLAST searches, alignment of selected sequences and submission of sequences.

Conclusions

sHSPdb is a new database containing information about sHSP from all kingdoms. sHSPdb provides a classification of sHSP, as well as tools and data for the analysis of the structure - function relationships of sHSP. Data are mainly related to various physico-chemical properties of the amino acids sequences of sHSP. sHSPdb is accessible at http://forge.info.univ-angers.fr/~gh/Shspdb/index.php.

Background

Heat Shock Proteins (HSP) are proteins whose expression is increased when cells are exposed to elevated temperatures or other stress. Among HSP, sHSP belong to the superfamily of protein chaperones. They counteract the irreversible aggregation of misfolded proteins. sHSP are ubiquitous proteins found in all living organisms, from bacteria to mammals and especially in plants [14]. Moreover, sHSP display a variety of sub-cellular localization and/or tissue distribution [3, 5].

sHSP contain : (i) a highly variable (in both length and in sequence) N-terminal domain; (ii) a very conserved central domain called the Alpha Crystallin Domain (ACD) involved in dimerization leading to the building block of higher order sHSP structure; (iii) a short C-terminal domain that links monomers inside dimmers [68]. A study of all sHSP merged have shown that the average length of ACD is 90 ± 10 residues [9] and this length is much more constant than the N- and C-terminal domains. However, we have classified sHSP into 21 classes and this value of average length of ACD does not apply anymore when considering sHSP class by class. The N-terminal part of ACD is likely not necessary for dimerization or chaperone activity, but seems required for higher order aggregates formation [10].

As members of the chaperone network, sHSP play important roles in cells exposed to heat and other stress, but their functional molecular mechanisms are not fully elucidated. sHSP monomers (12–42 kDa) usually associate into large homo-oligomers of mostly 24 subunits [9, 11]. sHSP quaternary structures have a high degree of plasticity due to changes in their oligomeric state under different cellular conditions or to exchange of their subunits. Loosening of subunit organization leads to more dynamic properties thus enhancing the available chaperone sites for the client proteins. For example, it was shown that the sequence RLFDQ (found at the N-terminal part of ACD of HSP27 - class number 12) contributes to the higher order assembly of their subunits as well as their structural stability [12]. Structural studies of numerous sHSP have brought details in monomer, transition of the oligomeric state [1315] and sHSP chaperone mechanism [12, 16].

However, such approaches do not allow the comparison of more than a few sHSP at a time. On the contrary, sHSPdb offers access to large-scale analysis of sHSP. Moreover, since sHSP is a very large protein family there is a wide discrepancy in annotation, definition and terminology: sHSPdb provides a classification of sHSP based on selective motifs, physicochemical properties and previous classification [1719]. sHSPdb has been conceived with multiple functions to search and describe the different sHSP. sHSPdb provides a global vision of sHSP physicochemical properties, amino acid usage, literature as well as statistical analysis on any sHSP dataset built by the user. Such a resource will be invaluable for computational analyses of sHSP structure - function relationships, especially regarding the specific roles of each of the three domains. sHSPdb is useful to gather information about sHSPs from all kingdom. sHSPdb provides the largest set of sHSP sequences, a new classification and a precise description of each class of sHSP. Physico-chemical properties and statistical analysis provided by sHSPdb represent an actual plus-value.

Construction and content

Data sources and characteristics of the dataset

To fill sHSPdb, we used a two-stage process. The first step filled automatically the fields of the tables of the database using PHP and perl scripts, getting the information from text and XML files from the following databases: NCBI/Proteins, NCBI/CDD, NCBI/Taxonomy, EBI/Picr, UNIPROT, Interpro, SANGER/Pfam, AMIGO. Starting with the NCBI accession number, we retrieved the « GenPept » file to derive the GI number, the eventual PFAM, CDD and Interpro [8, 20, 21] identifiers and the textual information. Then, using the cross-references of EBI/Picr we obtained the Uniprot accession number and name to complete and double-check the data. The main sources to fill sHSPdb are information contained in « GenPept » files and in the corresponding Uniprot files. The primary request to get « GenPept » files from the public database NCBI contained a construction of Boolean and keywords. This allowed the retrieving of ≈ 17,300 « GenPept » files stored in sHSPdb. Nevertheless, there was a very high redundancy of sequences for many organisms. The second step was a manual check to ensure that all information and links were pertinent and relevant to the sHSP issue. The pertinence of the files annotation and that of the sequences were checked using: (i) the sHSPdb « Search » option (see below); (ii) BLAST homology analysis and multiple alignments software; (iii) MOCAR (http://forge.info.univ-angers.fr/~gh/wstat/Mocar/), a program developed specifically for our sHSP classification based on pattern motif recognition in any Fasta sequences dataset; (iv) the « Analyze » and the « Statistical analysis » tools implemented in sHSPdb; (v) Finally, the motifs determined for each class of sHSP were further used to perform PHI-Blast allowing to get additional sequences.

Sequence conflict (in particular in the case of AGI entries for Arabidopsis thaliana) was checked using annotations from the Uniprot files. Identical sequences were removed using a program developed for sHSPdb feeding. This allowed detecting truncated, ambiguous (e.g., annotated « unnamed protein », « hypothetical », « unknown product »…, although some few populated sHSP classes may contain such annotated files) or false sHSP sequences. Sequences containing the undefined amino acid symbol (X) were removed. All files are stored in sHSPdb but only non-redundant, full-length and annotated ones are accessible.

The two holding chaperones (holdases) families, i.e., HSP31 and HSP33, cannot be considered formally as sHSP since they do not harbor the ACD domain, and interact with client proteins through Cys and disulfide bonds formation [22]. However, these redox regulated molecular chaperones have physico-chemical properties close to those of sHSP and also contribute to protein homeostasis under stress conditions. Moreover, they are redox regulated molecular chaperones: they protect both thermally unfolded and oxidatively damaged proteins from irreversible aggregation and play an important role in the bacterial defense system toward oxidative stress. Therefore, the two classes HSP31 and HSP33 were incorporated into sHSPdb.

The main goal of sHSPdb is the analysis of the structure-function relationships of sHSP. This is why only amino acids sequences are implemented. Today the user can nevertheless BLASTX any nucleotide sequence against sHSPdb to check the existence of similar or homologous sHSP.

Finally, sHSPdb contains ≈ 4800 curated, non-redundant and full-length sHSP sequences. More than 3200 sequences (67 %) are classified into 21 classes on the basis of their corresponding unique sequence motif. Roughly 400 additional sequences are classified on the basis of various criteria, eye inspection and our expertise. The remaining unclassified sHSP sequences have been assigned to a class 99 with ≈ 530 of these sequences being annotated Hsp20. Even if we expect to which class sequences of class 99 belong, they are not yet classified because they do not match exactly the regular expression of any of the defined motifs. Since there is no program available to automatically determine such complex discriminants motifs for any set of sequences, we are currently developing appropriate methods to address this question. In particular, we are using the recent constraint programming approach, based on a two-stage program whose last stage reduces to the classical minimum set covering problem, though, as for now, the complete and « perfect » characterization of all classes is not achieved. Partials results have already been published [23, 24].

Sequences are mainly issued from ≈ 2355 Bacteria, ≈ 2259 Eukaryota (among which ≈ 1050 Viridiplantae) and ≈ 129 Archaea (Table 1).

Table 1 Main taxonomy of the organisms in sHSPdb. Only groups containing more than 10 sequences are indicated

sHSPdb contains also ≈ 14,240 non-accessible entries (i.e., not retained after our curation). This dataset is important when the database is updated and for further analyses of sHSPdb since it may serve for statistical studies and forbid wrong entries in the curated set.

Organization and main features of sHSPdb

A link to a guided tour is proposed in the homepage to learn how to use the interface of sHSPdb. This guided tour proposes various scenarii of search. The user can select any entries through various parameters and conduct further analyses using the implemented tools. For this purpose, sHSPdb has three main features: (i) the browse mode that allows the user to consult all or part of the database; (ii) the search mode based upon multiple search criteria; (iii) the export mode to retrieve sequences in different formats.

The browse mode

It allows consulting the whole database (Fig. 1). The « Summary » option provides the NCBI-GenPept accession number and the Uniprot accession number, the name of the sequence and of the organism, the putative function of the sHSP (if any). The « Details » option provides more information (up to 20 fields from the GenPept or the Uniprot files). The accession numbers, the name of the organism, the PFAM, the CDD and the InterPro numbers provide a link to their relevant website. A series of physicochemical properties (length/pI/MW/FoldIndex/GRAVY/mean net charge at pH7/mean hydrophilicity/mean hydrophobicity < H>/flexibility/bulkiness/accessibility of residues/transmembrane tendancy of residues) are given by selecting the « Physicochemical properties » option. The « AA comp » option displays the amino acid composition of sHSP. Finally, the « Fasta » option provides all sequences in Fasta format. The « Align sequences » option allows to align selected sequences.

Fig. 1
figure 1

Browse interface for accessing the whole sHSPdb content. The « Search » mode provides an advanced search with multiple parameters and permits retrieval of very fine subsets of data. The user can also retrieve sequences by entering amino acids motif either exact or degenerated using regular expressions with sophisticated syntax. Among other information, the « Summary » option provides links to general databases, the name of the sHSP and its putative function. The « Details » option provides more information. A series of physicochemical properties are given by selecting the « Physicochemical properties » option. The « AA comp » option displays the amino acid composition of sHSP. Finally, the « Fasta » option provides all sequences in FASTA format

The search mode (multiple search capabilities)

It corresponds to an advanced search with multiple parameters and permits retrieval of very fine subsets of data (example of search: « sHSP of the PF00011 family from Arabidopsis thaliana, containing the motif of Class 1, associated to the key word « chromosome », published by an author called Walker in 2012, with a length comprised between 150 and 200 amino acids »). The search can be made by using a sophisticated text expression accepting wildcards and Booleans - this search applies to all fields of the whole database; by accession number (accepting wildcards) - one or multiple accession number(s) separated by a space can be searched at one time; by organism; by PFAM or CDD numbers; by date; by range of length of amino acids sequence. The user can also retrieve sequences by entering amino acids motif either exact or degenerated using regular expressions with sophisticated syntax, allowing to specify complex motifs. The known motifs (Table 2) implemented in sHSPdb result from our analysis.

Table 2 sHSP classification in sHSPdb

The user can perform a similarity search by using BLASTP implemented in sHSPdb. This allows obtaining additional information and retrieving the best scoring sequences through the classical BLAST output interface. It is also possible to BLASTX a nucleotide sequence against sHSPdb to check the existence of similar or homologous sHSP in order, for example, to construct a putative sHSP cDNA sequence from EST.

Many options are proposed for the output: (i) when entries have been retrieved, the information can be displayed in any of the views of the browse mode and the fields such as accession number, taxonomy, PFAM, CDD and InterPro numbers are linked to their original web site according to the relevant information found at the NCBI; (ii) the user can select or deselect any entry resulting from his search (« Toggle » option) and the final selection can be stored. This is true for all displays (browse mode, BLAST output, …); (iii) one original point is the re-ordering (ascending or descending sort) of data displayed in tables, for a better comparison and analysis of data, using any shown information as the sort criterion; (iv) the user can automatically align selected sequences.

The export mode

All sequences in SHSPdb can be exported trough the « Export » interface. The « View » menu displays the entries in the order of the last actions made by the user (all, filtered, selected or blasted). The « Format » menu displays three exporting formats: FASTA, XML and Excel (CSV).

The analyze tool

One original feature of sHSPdb is the possibility to obtain numerous information of any self-built dataset using the left panel. The right panel allows selecting the desired information. For categorical data, results are sorted tables of counts, respectively with respect to alphabetic order and values of counts; for quantitative data, classical descriptive statistics and graphics (such as means, median, histograms…) are provided.

The statistical analysis tool

Another original feature of sHSPdb is the possibility to dynamically generate plots of physico-chemical properties or amino acids usage of sHSP using different criteria. Therefore, one can immediately make multiple comparisons of self datasets. The user can access to statistical data through the menu « Statistical analysis ». This option displays « Class description » (examination of all physico-chemical properties or all amino acids usage or all combinations of amino acids for a given sHSP class) or « Class comparison » (comparison of a given physico-chemical property for the sHSP classes). Plots are automatically generated and are clickable to be resized (Fig. 2). The statistical analysis includes both descriptive (means, medians…) and inferential (parametric or non parametric ANOVA) computations and graphics (histograms with density and normal approximation, boxplots, beanplots when accurate…).

Fig. 2
figure 2

The statistical analysis tool. One original feature of sHSPdb is the possibility to dynamically generate plots of physico-chemical properties or amino acids usage of sHSP using different criteria. Therefore, one can immediately make multiple comparisons of self datasets. The user can access to statistical data through the menu « Statistical analysis ». This option displays « Class description » (examination of all physico-chemical properties or all amino acids usage or all combinations of amino acids for a given sHSP class) or « Class comparison » (comparison of a given physico-chemical property for the sHSP classes). Plots are automatically generated and are clickable to be resized

The submission form

The user can submit sequence(s) through a submission form. After verification of their relevance, they will be integrated in sHSPdb.

Database implementation

sHSPdb is a fast, interactive, platform independent Web-based database with a user-friendly interface written in PHP. Some options need Javascript to be activated. Information is provided to the user from a MySQL relational database. The statistical computations are performed using the R software called by a PHP script.

Utility and discussion

sHSPdb versus other sHSP datasets

Poulain et al. [9] reported about a dataset including 3787 sHSP sequences. However, this dataset contains some redundancy: 774 sequences from this dataset were aligned and 70 sequences are identical, corresponding to a redundancy of 9 %. It can be thus estimated that the entire dataset correspond roughly to 3400 different sHSP, i.e., less than the number of sHSP contained in sHSPdb. Moreover, this dataset is limited to a flat PDF file with accession numbers and thus does not provide any details or functionalities. Our selection is very stringent since we excluded most of all files annotated « putative », « probable », « unknown », « hypothetical », « unnamed protein product », « synthetic construct », … in order to increase the quality of annotation even if less sequences were retained. We did not consider fragments, i.e., files annotated « partial ». Sequences with such annotation but additional indication and/or classifiable on the basis of a motif were retained.

To our knowledge, there is only one other database dedicated to HSP (HSPIR: http://pdslab.biochem.iisc.ernet.in/hspir/shsp.php) which gather accession numbers and FASTA files for HSP protein sequences, and provides general information about the structure and function of the different families of HSPs [25]. However, HSPIR contains only ≈ 1300 sequences of sHSP, and offers access to only basic search and BLAST tools. sHSPdb appears thus as a unique comprehensive and highly implemented database for the computational and statistical analysis of sHSP.

Classification of sHSP

sHSP constitute a very large protein sub-divised family of proteins. However, there is a wide discrepancy in annotation, definition and terminology. sHSPdb provides a unified and homogeneous classification of sHSP. One of the most important parameter for the sHSP classification is the consensus motif discriminating each class from another (Table 2). The proposed classification in classes is based on the expertise brought by sHSPdb, literature data and previous classifications [1, 2, 9, 17, 19, 2630].

The quite simple C-terminal motif [ADHKNQ]G.[AILV] matches ≈ 89 % of the sequences and a more sophisticated central motif [APS][EGM].{4,5}[ADENQSK] matches ≈ 99 % of the sequences. Such motifs therefore describe almost all sHSP and are therefore not pertinent for discrimination. Since most of sHSP classes contain the ACD (with exception of sHSP classes 9, 16, 17 and 21), we searched selective motifs either in the N-terminal or the C-terminal domains, if any (Table 3).

Table 3 Some length characteristics of sHSP and « alpha-crystalin-unrelated sHSPs »

This motifs search underlined the difficulties with annotation. For example, the motif [AFLSTVWY]P[AGPS][FHY][DN][ILV] matches ≈ 540 sequences whose annotations are mainly « heat shock protein HSP20, « HSP20 family protein » or « Hsp20/alpha crystallin family protein ». Therefore, the high selectivity of our motifs helps to ameliorate global annotation such as the generic « HSP20 ».

Previous classifications were first based on the intracellular localization of the sHSP: cytoplasmic-nuclear compartment (classes CI, CII and CIII), plastids (class P), endoplasmic reticulum (class ER), mitochondria (class M), peroxisomal (class Po or Px). These seven plant sHSP classes are to date the best characterized of the plant sHSP (they are coded by 14 genes in Arabidopsis thaliana). The complete analysis of Arabidopsis thaliana genome led to four additional cytoplasmic-nuclear sHSP and a second unique family of sHSP targeted to the mitochondria. Thus, higher plants may contain at least 12 conserved sHSP subfamilies. Organelle-targeted sHSP are so far specific of plants, with some exceptions (mitochondria-targeted sHSP from Drosophila melanogaster and from Toxoplasma gondii) [31, 32]. However, it remains difficult to ascertain the sub-cellular localization of proteins, especially on large numbers of proteins because predictors are not reliable enough. Finally, the taxonomy of organism among each class is homogeneous indicating that our classification of sHSP is accurate (Table 2).

Such classification together with the statistical data automatically generated is thus useful. For example, sHSPdb help for analyzing the respective role of each of the three domains characterizing sHSP in oligomerization and substrate binding on a very large scale. A conserved motif, [ILV].[ILV], located in the C-terminal domain is critical for oligomer formation through contacts with a hydrophobic patch in ACD [9, 13, 33]. The ACD domain is an emblematic signature of sHSP in the literature [19, 28] and it is indeed found in 17 of the 21 classes in sHSPdb. Table 3 and Fig. 3 show the comparison of the mean value of the size of the N-terminal domain, ACD and the C-terminal domain.

Fig. 3
figure 3

Comparison of the mean value of the size of the N-terminal domain, ACD and the C-terminal domain. Only HSP classes containing an ACD are represented (see Table 3). The upper scale indicates the size of the sequences in amino acids. ER: endoplasmic reticulum

Nevertheless, some heat shock proteins lacking an ACD sequence should be in our opinion considered as sHSP and defined as « alpha-crystallin unrelated sHSP ». Therefore, we have implemented 4 classes of sHSP without ACD. This classes of sHSP devoid of the ACD domain fall well within the molecular weight expected for sHSP. Their implementation provides additional information and allows more comparisons and analyses of sHSP.

Short example of use of sHSPdb: analysis of mitochondrial sHSP

A phylogenetic tree of plants mitochondrial sHSP (class 6) has been built (Fig. 4). Five sequences correspond to mitochondrial sHSP from Arabidopsis thaliana (AAM63747, CAA67022, HS235_ARATH, HS23M_ARATH and HS26M_ARATH, all from class 6). The differences between AAM63747 and HS235_ARATH are [S/A]31 and [D/H]69 and the difference between CAA67022 and HS23M_ARATH is [D/H]143. The sequences of ACD and C-terminal domain are very similar (Fig. 5). The sequences of the N-terminal domain of HS235_ARATH and HS23M_ARATH are different from that of HS26M_ARATH and are more intrinsically disordered (negative FoldIndex for HS26M_ARATH). This may have a possible incidence on the dimer formation [34, 35].

Fig. 4
figure 4

Phylogenetic tree of plant mitochondrial sHSP. 91 sequences of mitochondrial sHSP from 47 plant organisms were analyzed. The characteristics of the sequences are: a length from 187 to 248 amino acids; an isoelectric point from 4.620 to 10.15; a net charge at pH 7 from  0.041 to +0.031; a FoldIndex from  0.044 to 0.138; a hydropathy (GRAVY) from  0.908 to  0.274. The alignment was made using Clustal-W and the figure was drawn using Dendroscope [36]

Fig. 5
figure 5

Alignment of three mitochondrial sHSP from Arabidopsis thaliana. The alignment was made using Multalin [37] and the figure was drawn using ESPript [38]

Conclusions

sHSPdb harbors a comprehensive dataset available for sHSP, together with tools designed for their online analysis. To our knowledge, there is no equivalent database for sHSP. sHSP are classified into classes on the basis of various parameters, especially on the basis of amino acids motifs that discriminate the classes. sHSPdb thus constitute an efficient tool: (i) for the compilation and the organization of growing data concerning sHSP; (ii) for the classification of the various sub-families of sHSP; (iii) for the design of experiments to elucidate the function of this important proteins; (iv) to help the analysis of the sHSP structure-function relationships.

Future developments and perspectives: (i) sHSP physico-chemical properties and sHSP amino acids usage are statistically analyzed for all sHSP classes. We will thus be able to compare the three domains (i.e., the N-terminal, the ACD and the C-terminal), thus bringing additional information to those already determined by structural methodologies. (ii) We are currently developing software for the analysis of sequence submitted by the users in order to predict if it belongs to any of the sHSP classes. (iii) Since deciphering the molecular functions of sHSP is a major issue, we will provide lexical tools (dictionaries by alphabetic order or occurrence or synonyms…) for a better semantic analysis of the words that describe the known elements of the function of sHSP. (iv) As previously noted, retained proteins that are not fully classified are under study with the help of some predicting values and of a constraint programming software under development.

Availability and requirements

sHSPdb is a free database and visualization tool open to all users with no login requirements and can be accessed at the following URL: http://forge.info.univ-angers.fr/~gh/Shspdb/index.php. The web tool is functional on all modern web browsing environments including Mozilla Firefox, Safari and Google Chrome.

Abbreviations

ACD, alpha crystallin domain; ER, endoplasmic reticulum; NA, not applicable; sHSP, small heat shock proteins; sHSPdb, small heat shock proteins database

References

  1. Siddique M, Gernhard S, von Koskull-Döring P, Vierling E, Scharf KD. The plant sHSP superfamily: five new members in Arabidopsis thaliana with unexpected properties. Cell Stress Chaperones. 2008;13:183–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Sarkar NK, Kim YK, Grover A. Rice sHsp genes: genomic organization and expression profiling under stress and development. BMC Genomics. 2009;10:393.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Kampinga HH, Hageman J, Vos MJ, Kubota H, Tanguay RM, Bruford EA, Cheetham ME, Chen B, Hightower LE. Guidelines for the nomenclature of the human heat shock proteins. Cell Stress Chaperones. 2009;14:105–11.

    Article  CAS  PubMed  Google Scholar 

  4. Reddy PS, Kishor PBK, Seiler C, Kuhlmann M, Eschen-Lippold L, Lee J, Reddy MK, Sreenivasulu N. Unraveling regulation of the small heat shock proteins by the heat Shock factor HvHsfB2c in barley: its implications in drought stress response and seed development. PLoS One. 2014;9:e89125.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Waters ER, Aevermann BD, Sanders-Reed Z. Comparative analysis of the small heat shock proteins in three angiosperm genomes identifies new subfamilies and reveals diverse evolutionary patterns. Cell Stress Chaperones. 2008;13:127–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Kriehuber T, Rattei T, Weinmaier T, Bepperling A, Haslbeck M, Buchner J. Independent evolution of the core domain and its flanking sequences in small heat shock proteins. FASEB J. 2010;24:3633–42.

    Article  CAS  PubMed  Google Scholar 

  7. Stamler R, Kappé G, Boelens W, Slingsby C. Wrapping the alpha-crystallin domain fold in a chaperone assembly. J Mol Biol. 2005;353:68–79.

    Article  CAS  PubMed  Google Scholar 

  8. Finn RD, Mistry J, Schuster-Böckler B, Griffiths-Jones S, Hollich V, Lassmann T, Moxon S, Marshall M, Khanna A, Durbin R, Eddy SR, Sonnhammer EL, Bateman A. Pfam: clans, web tools and services. Nucleic Acids Res. 2006;34:D247–251.

    Article  CAS  PubMed  Google Scholar 

  9. Poulain P, Gelly JC, Flatters D. Detection and architecture of small heat shock protein monomers. PLoS One. 2010;5:e9990.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Feil IK, Malfois M, Hendle J, van Der Zandt H, Svergun DI. A novel quaternary structure of the dimeric alpha-crystallin domain with chaperone-like activity. J Biol Chem. 2001;276:12024–9.

    Article  CAS  PubMed  Google Scholar 

  11. van Montfort RL, Basha E, Friedrich KL, Slingsby C, Vierling E. Crystal structure and assembly of a eukaryotic small heat shock protein. Nat Struct Biol. 2001;8:1025–30.

    Article  PubMed  Google Scholar 

  12. Pasta SY, Raman B, Ramakrishna T, Rao CM. Role of the conserved SRLFDQFFG region of α-crystallin, a small heat shock protein. Effect on oligomeric size, subunit exchange, and chaperone-like activity. J Biol Chem. 2003;278:51159–66.

    Article  CAS  PubMed  Google Scholar 

  13. Saji H, Iizuka R, Yoshida T, Abe T, Kidokoro S, Ishii N, Yohda M. Role of the IXI/V motif in oligomer assembly and function of StHsp14.0., a small heat shock protein from the acidothermophilic archaeon., Sulfolobus tokodaii strain 7. Proteins. 2008;71:771–82.

    Article  CAS  PubMed  Google Scholar 

  14. Bagnéris C, Bateman OA, Naylor CE, Cronin N, Boelens WC, Keep NH, Slingsby C. Crystal structures of α-crystallin domain dimers of αB-crystallin and Hsp20. J Mol Biol. 2009;392:1242–52.

    Article  PubMed  Google Scholar 

  15. Healy EF. A model for heterooligomer formation in the heat shock response of Escherichia coli. Biochem Biophys Res Commun. 2012;420:639–43.

    Article  CAS  PubMed  Google Scholar 

  16. Jaya N, Garcia V, Vierling E. Substrate binding site flexibility of the small heat shock protein molecular chaperones. Proc Natl Acad Sci U S A. 2009;106:15604–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Ma C, Haslbeck M, Babujee L, Jahn O, Reumann S. Identification and characterization of a stress-inducible and a constitutive small heat-shock protein targeted to the matrix of plant peroxisomes. Plant Physiol. 2006;141:47–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. de Jong WW, Leunissen JA, Voorter CE. Evolution of the alpha-crystallin/small heat-shock protein family. Mol Biol Evol. 1993;10:103–26.

    PubMed  Google Scholar 

  19. Basha E, O’Neill H, Vierling E. Small heat shock proteins and α-crystallins: dynamic proteins with flexible functions. Trends Biochem Sci. 2012;37:106–17.

    Article  CAS  PubMed  Google Scholar 

  20. Marchler-Bauer A, Anderson JB, Derbyshire MK, DeWeese-Scott C, Gonzales NR, Gwadz M, Hao L, He S, Hurwitz DI, Jackson JD, Ke Z, Krylov D, Lanczycki CJ, Liebert CA, Liu C, Lu F, Lu S, Marchler GH, Mullokandov M, Song JS, Thanki N, Yamashita RA, Yin JJ, Zhang D, Bryant SH. CDD: a conserved domain database for interactive domain family analysis. Nucleic Acids Res. 2007;35:D237–240.

    Article  CAS  PubMed  Google Scholar 

  21. Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, Finn RD, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Laugraud A, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, Mistry J, Mitchell A, Mulder N, Natale D, Orengo C, Quinn AF, Selengut JD, Sigrist CJ, Thimma M, Thomas PD, Valentin F, Wilson D, Wu CH, Yeats C. InterPro: the integrative protein signature database. Nucleic Acids Res. 2009;37:D224–228.

    Article  Google Scholar 

  22. Baneyx F. Molecular chaperones. 2008. http://faculty.washington.edu/baneyx/Chaperones/Chaperones.html#Hsp33.

    Google Scholar 

  23. Lesaint D, Mehta D, O’Sullivan B. Soft pattern discovery in pre-classified protein families through constraint optimization. 9th Workshop on Constraint-based methods for Bioinformatics (WCB) at CP-2013, Uppsala: 2013.

  24. Lesaint D, Mehta D, O’Sullivan B, Vigneron V. A decomposition approach for discovering discriminative motifs in a sequence database. 21st European Conference on Artificial Intelligence (ECAI), IOS Press, Prague: 2014.

  25. Ratheesh KR, Nagarajan NS, Arunraj SP, Sinha D, Veedin Rajan VB, Esthaki VK, D’Silva P. HSPIR: a manually annotated heat shock protein information resource. Bioinformatics. 2012;28:2853–5.

    Article  Google Scholar 

  26. Scharf KD, Siddique M, Vierling E. The expanding family of Arabidopsis thaliana small heat stress proteins and a new family of proteins containing α-crystallin domains ACD proteins. Cell Stress Chaperones. 2001;6:225–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Tao P, Guo WL, Li BY, Wang WH, Yue ZC, Lei JL, Zhong XM. Genome-wide identification, classification, and expression analysis of sHSP genes in Chinese cabbage (Brassica rapa ssp pekinensis). Genet MolRes 2015;14:11975-93.

  28. Bondino HG, Valle EM, Ten Have A. Evolution and functional diversification of the small heat shock protein/α-crystallin family in higher plants. Planta. 2012;235:1299–313.

    Article  CAS  PubMed  Google Scholar 

  29. Waters ER. The evolution, function, structure, and expression of the plant sHSPs. J Exp Bot. 2013;64:391–403.

    Article  CAS  PubMed  Google Scholar 

  30. Zhang J, Liu B, Li J, Zhang L, Wang Y, Zheng H, Lu M, Chen J. Hsf and Hsp gene families in Populus: genome-wide identification, organization and correlated expression during development and in stress responses. BMC Genomics. 2015;16:181.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Morrow G, Inaguma Y, Kato K, Tanguay RM. The small heat shock protein Hsp22 of Drosophila melanogaster is a mitochondrial protein displaying oligomeric organization. J Biol Chem. 2000;275:31204–10.

    Article  CAS  PubMed  Google Scholar 

  32. de Miguel N, Echeverria PC, Angel SO. Differential subcellular localization of members of the toxoplasma gondii small heat shock protein family. Eukaryot Cell. 2005;4:1990–7.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Sun Y, MacRae TH. Small heat shock proteins: molecular structure and chaperone function. Cell Mol Life Sci. 2005;62:2460–76.

    Article  CAS  PubMed  Google Scholar 

  34. Chen J, Feige MJ, Franzmann TM, Bepperling A, Buchner J. Regions outside the alpha-crystallin domain of the small heat shock protein Hsp26 are required for its dimerization. J Mol Biol. 2010;398:122–31.

    Article  CAS  PubMed  Google Scholar 

  35. Sudnitsyna MV, Mymrikov EV, Seit-Nebi AS, Gusev NB. The role of intrinsically disordered regions in the structure and functioning of small heat shock proteins. Curr Protein Pept Sci. 2012;13:76–85.

    Article  CAS  PubMed  Google Scholar 

  36. Huson DH, Richter DC, Rausch C, Dezulian T, Franz M, Rupp R. Dendroscope: an interactive viewer for large phylogenetic trees. BMC Bioinf. 2007;22:460.

    Article  Google Scholar 

  37. Corpet F. Multiple sequence alignment with hierarchical clustering. Nucleic Acids Res. 1988;16:10881–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Gouet P, Robert X, Courcelle E. ESPript/ENDscript: extracting and rendering sequence and 3D information from atomic structures of proteins. Nucleic Acids Res. 2003;31:3320–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This research was supported by a grant ANR Blanc MITOZEN (ANR-12-BSV8-0021-01) and by a grant from University of Angers (ACS13LES).

Availability of data and materials

The datasets supporting the conclusions of this article are available in the sHSPdb repository freely accessible at http://forge.info.univ-angers.fr/~gh/Shspdb/index.php.

Authors’ contributions

EJ served as project advisor. GH implemented the MySQL database, PHP and Perl scripts, and the interface design. EJ collected data, checked data integrity and entered them into the database. GH and EJ wrote the manuscript, checked the accuracy of the database and web interface, read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Emmanuel Jaspard.

Rights and permissions

Open Access This 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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jaspard, E., Hunault, G. sHSPdb: a database for the analysis of small Heat Shock Proteins. BMC Plant Biol 16, 135 (2016). https://doi.org/10.1186/s12870-016-0820-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12870-016-0820-6

Keywords