Pipeline to Identify Hydroxyproline-Rich Glycoproteins

Abstract

Intrinsically disordered proteins (IDPs) are functional proteins that lack a well-defined three-dimensional structure. The study of IDPs is a rapidly growing area as the crucial biological functions of more of these proteins are uncovered. In plants, IDPs are implicated in plant stress responses, signaling, and regulatory processes. A superfamily of cell wall proteins, the hydroxyprolinerich glycoproteins (HRGPs), have characteristic features of IDPs. Their protein backbones are rich in the disordering amino acid proline, they contain repeated sequence motifs and extensive posttranslational modifications (glycosylation), and they have been implicated in many biological functions. HRGPs are evolutionarily ancient, having been isolated from the protein-rich walls of chlorophyte algae to the cellulose-rich walls of embryophytes. Examination of HRGPs in a range of plant species should provide valuable insights into how they have evolved. Commonly divided into the arabinogalactan proteins, extensins, and proline-rich proteins, in reality, a continuum of structures exists within this diverse and heterogenous superfamily. An inability to accurately classify HRGPs leads to inconsistent gene ontologies limiting the identification of HRGP classes in existing and emerging omics data sets. We present a novel and robust motif and amino acid bias (MAAB) bioinformatics pipeline to classify HRGPs into 23 descriptive subclasses. Validation of MAAB was achieved using available genomic resources and then applied to the 1000 Plants transcriptome project (www.onekp.com) data set. Significant improvement in the detection of HRGPs using multiple-kmer transcriptome assembly methodology was observed. The MAAB pipeline is readily adaptable and can be modified to optimize the recovery of IDPs from other organisms.

Insights into the Evolution of Hydroxyproline-Rich Glycoproteins from 1000 Plant Transcriptomes

“…Classical AGPs are likely to exist in the chlorophyte algae, as one of the firstcloned HRGP genes (accession no. AAB23258.2) from Chlamydomonas reinhardtii, CrZSP1 (Woessner and Goodenough, 1989), is predicted to be a glycosylphosphatidylinositol (GPI)-AGP according to our criteria (Johnson et al, 2017). It is likely that AGPs in the chlorophyte algae have distinct functions from streptophytes, as no large arabino-3,6-galactan polysaccharides have been reported (Ferris et al, 2001).…”

“…The protein backbones of these HRGPs are distinguished by differences in amino acid bias and the repeat motifs characteristic to each family and include the posttranslational modification of Pro to Hyp (Johnson et al, 2017). Each of these families is further elaborated by chimeric and hybrid HRGPs, complicating not only the classification of members but also the elucidation of their functions.…”

“…These studies suggest that AGPs are evolutionarily ancient. O-Glycosylation occurs in bryophytes, some chlorophytes, and brown algae, as shown by the binding of b-Glc Yariv and/or the isolation of Hyp-containing glycoproteins (Godl et al, 1997;Ligrone et al, 2002;Lee et al, 2005;Shibaya and Sugawara, 2009;Hervé et al, 2016;Johnson et al, 2017). Classical AGPs are likely to exist in the chlorophyte algae, as one of the firstcloned HRGP genes (accession no.…”

“…EXTs from these other green plant lineages can have distinct features from embryophyte EXTs, and we use the term crosslinking (CL)-EXTs to distinguish EXTs with alternating SO n and Y-based motifs, which occur predominantly in land plants, from the HRGPs that have Y residues in a different domain from the SO n -rich domains, as occurs in volvocine algae (see Fig. 1 in Johnson et al, 2017). Exceptions may exist; for example, no classical EXTs were detected in the Hyp-poor cell walls of maize (Zea mays), which also do not have detectable isodityrosine, an intramolecular cross-link that occurs between Y residues in EXTs Kieliszewski and Lamport, 1994).…”

“…To study HRGP function throughout plant evolution, we developed a robust method for their detection that exploits the amino acid bias of the predicted protein backbone and characteristic glycomotifs (Johnson et al, 2017). The motif and amino acid bias (MAAB) pipeline classifies HRGP sequences into one of 24 predefined descriptive subclasses (23 HRGP classes and one MAAB class) and is optimized for the recovery of GPI-AGPs, non-GPI-AGPs, and CL-EXTs.…”