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. 2012 Aug 11;12:142.
doi: 10.1186/1471-2229-12-142.

Non-canonical Peroxisome Targeting Signals: Identification of Novel PTS1 Tripeptides and Characterization of Enhancer Elements by Computational Permutation Analysis

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Free PMC article

Non-canonical Peroxisome Targeting Signals: Identification of Novel PTS1 Tripeptides and Characterization of Enhancer Elements by Computational Permutation Analysis

Gopal Chowdhary et al. BMC Plant Biol. .
Free PMC article

Abstract

Background: High-accuracy prediction tools are essential in the post-genomic era to define organellar proteomes in their full complexity. We recently applied a discriminative machine learning approach to predict plant proteins carrying peroxisome targeting signals (PTS) type 1 from genome sequences. For Arabidopsis thaliana 392 gene models were predicted to be peroxisome-targeted. The predictions were extensively tested in vivo, resulting in a high experimental verification rate of Arabidopsis proteins previously not known to be peroxisomal.

Results: In this study, we experimentally validated the predictions in greater depth by focusing on the most challenging Arabidopsis proteins with unknown non-canonical PTS1 tripeptides and prediction scores close to the threshold. By in vivo subcellular targeting analysis, three novel PTS1 tripeptides (QRL>, SQM>, and SDL>) and two novel tripeptide residues (Q at position -3 and D at pos. -2) were identified. To understand why, among many Arabidopsis proteins carrying the same C-terminal tripeptides, these proteins were specifically predicted as peroxisomal, the residues upstream of the PTS1 tripeptide were computationally permuted and the changes in prediction scores were analyzed. The newly identified Arabidopsis proteins were found to contain four to five amino acid residues of high predicted targeting enhancing properties at position -4 to -12 in front of the non-canonical PTS1 tripeptide. The identity of the predicted targeting enhancing residues was unexpectedly diverse, comprising besides basic residues also proline, hydroxylated (Ser, Thr), hydrophobic (Ala, Val), and even acidic residues.

Conclusions: Our computational and experimental analyses demonstrate that the plant PTS1 tripeptide motif is more diverse than previously thought, including an increasing number of non-canonical sequences and allowed residues. Specific targeting enhancing elements can be predicted for particular sequences of interest and are far more diverse in amino acid composition and positioning than previously assumed. Machine learning methods become indispensable to predict which specific proteins, among numerous candidate proteins carrying the same non-canonical PTS1 tripeptide, contain sufficient enhancer elements in terms of number, positioning and total strength to cause peroxisome targeting.

Figures

Figure 1
Figure 1
Number of Arabidopsis gene models (A) and gene loci (B) terminating with one of five predicted non-canonical PTS1 tripeptides. The number of Arabidopsis gene models (loci) predicted as peroxisomal is indicated by black columns, and those predicted as non-peroxisomal are represented by grey columns.
Figure 2
Figure 2
Experimental validation of Arabidopsis proteins carrying newly predicted non-canonical PTS1 domains byin vivosubcellular targeting analysis. Onion epidermal cells were transformed biolistically with EYFP fusion constructs that were C-terminally extended by the C-terminal decapeptides of Arabidopsis proteins carrying newly predicted non-canonical PTS1 domains. Subcellular targeting was analyzed by fluorescence microscopy after ca. 48 h expression (ca. 18 h RT plus 30 h ca. 10 °C), or ca. 7 d (ca. 18 h RT plus 6 d ca. 10 °C). Cytosolic constructs, for which subcellular targeting data are shown after short-term expression times, were reproducibly confirmed as cytosolic also after long-term expression. Possibly novel aa residues of PTS1 tripeptides are underlined. To document the efficiency of peroxisome targeting, EYFP images of single transformants were not modified for brightness or contrast (A-H). In double transformants, peroxisomes were labeled with DsRed-SKL or PTS2-CFP with cyan fluorescence having been converted to red for image overlay (I-K). In Figure2K the arrows point at six EYFP-labeled peroxisomes (yellow), while two organelles are only fluorescing in red or green, most likely due to quick organelle movement. EYFP alone was included as negative control (A).
Figure 3
Figure 3
Transcriptional variants of a DNAJ homolog (At1g18700) with one splice variant carrying the PTS1 tripeptide QRL > and a functional PTS1 domain. (A) Schematic diagram showing the CDS structure and multiple sequence alignment and (B) multiple sequence alignment of four transcriptional variants (At1g18700.1-4) of an Arabidopsis DNAJ homolog.
Figure 4
Figure 4
Experimentally validated aa residues of the plant PTS1 motif. Tripeptide residues identified as novel plant PTS1 tripeptides in this study (Q at pos. -3 and D at pos. -2) are indicated by white boxes. According to experimental data and PWM model predictions [16], at least two of the seven high-abundance residues of predicted high targeting strength ([SA][KR][LMI]>, black boxes) must be combined with one low-abundance residue (grey or white boxes) to yield functional plant PTS1 tripeptides (x[KR][LMI]>, [SA]y[LMI]>, [SA][KR]z>).
Figure 5
Figure 5
General PWM score matrix of plant PTS1 proteins displayed as a heat map. The PWM matrix values are listed in Additional file 1. The values are visualized by a heat map. To account for the different position-specific score ranges, different heat map scales were used for the PTS1 tripeptide and the eleven upstream residues (A). From the matrix values of each aa residue the position-specific range of values has been determined (B).
Figure 6
Figure 6
Computational permutation analysis of three Arabidopsis proteins carrying non-canonical PTS1 domains. The eleven residues upstream of the novel non-canonical PTS1 tripeptides (pos. -4 to −14) of three Arabidopsis proteins (1, QRL>, At1g18700.2; 2, SQM>, At5g45160.1; 3, SDL>, At5g03730.1) were computationally permuted one by one in all possible 209 combinations (11 x 19 = 209) and the changes in PWM prediction scores investigated. (A) Pattern of PWM score range windows of permuted sequences, (B) total PWM score optimization potential and (C) relative PWM score optimization potential in percentage. The absolute magnitude of the PWM score range window on the y axis and its positioning relative to the PWM prediction score of the original Arabidopsis QRL > sequence (grey line) indicates the absolute optimization potential of a position-specific residue (A). In A1-C1 the PWM prediction score of the original Arabidopsis sequences is indicated by a grey line. Important residues that are predicted to enhance peroxisome targeting are shaded in grey.

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