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. 2018 Sep 13;16(9):e2005895. doi: 10.1371/journal.pbio.2005895

Fig 2. Accurate, unbiased identification of apicoplast proteins using BioID.

Fig 2

(A) Abundances of 728 proteins identified by mass spectrometry in BioID–Ap and BioID–ER parasites. Protein abundances were calculated by summing the total MS1 area of all matched peptides for a given protein and normalized by the total summed intensity of all P. falciparum peptides matched. Dotted line represents 5-fold apicoplast:ER enrichment. (B) ROC curve used to identify the apicoplast:ER enrichment that maximized true positives while minimizing false positives. Dotted lines denote the sensitivity and false positive rate of the 5-fold cutoff used. False positive rates for hypothetical 2-fold and 1-fold enrichments are shown for reference. (C) Sensitivities of BioID, PATS, PlasmoAP, and ApicoAP based on identification of 96 known apicoplast proteins. (D) PPV of BioID, PATS, PlasmoAP, ApicoAP, and a data set consisting of proteins predicted to localize to the apicoplast by all 3 bioinformatic algorithms. Calculated as the number of true positives divided by the total number of true positives and false positives. Error bars in (C) and (D) represent 95% confidence intervals. Tabulated data are available in S1 Data. ApicoAP, Apicomplexan Apicoplast Proteins algorithm; BioID, proximity-dependent biotin identification; ER, endoplasmic reticulum; ND, not detected; PlasmoAP, Plasmodium falciparum Apicoplast-targeted Proteins algorithm; PATS, Predict Apicoplast-Targeted Sequences algorithm; PPV, positive predictive value; ROC, receiver operating characteristic.