Plasma biomarkers of hemoglobin loss in Plasmodium falciparum-infected children identified by quantitative proteomics.

Anemia is common among young children infected with Plasmodium falciparum and severe malarial anemia (SMA) is a major cause of their mortality. Two major mechanisms cause malarial anemia: hemolysis of uninfected as well as infected erythrocytes and insufficient erythropoiesis. In a longitudinal birth cohort in Mali, we commonly observed marked hemoglobin reductions during P falciparum infections with a small proportion that progressed to SMA. We sought biomarkers of these processes using quantitative proteomic analysis on plasma samples from 9 P falciparum-infected children, comparing those with reduced hemoglobin (with or without SMA) vs those with stable hemoglobin. We identified higher plasma levels of circulating 20S proteasome and lower insulin-like growth factor-1 (IGF-1) levels in children with reduced hemoglobin. We confirmed these findings in independent enzyme-linked immunosorbent assay-based validation studies of subsets of children from the same cohort (20S proteasome, N = 71; IGF-1, N = 78). We speculate that circulating 20S proteasome plays a role in digesting erythrocyte membrane proteins modified by oxidative stress, resulting in hemolysis, whereas decreased IGF-1, a critical factor for erythroid maturation, might contribute to insufficient erythropoiesis. Quantitative plasma proteomics identified soluble mediators that may contribute to the major mechanisms underlying malarial anemia. This study was registered at www.clinicaltrials.gov as #NCT01168271.

Proteomics Pipeline for Identifying Variant Proteins in Plasmodium falciparum Parasites Isolated from Children Presenting with Malaria.

Plasmodium falciparum variant antigens named erythrocyte membrane protein 1 (PfEMP1) are important targets for developing a protective immunity to malaria caused by P. falciparum. One of the major challenges in P. falciparum proteomics studies is identifying PfEMP1s at the protein level due to antigenic variation. To identify these PfEMP1s using shotgun proteomics, we developed a pipeline that searches high-resolution mass spectrometry spectra against a custom protein sequence database. A local alignment algorithm, LAX, was developed as a part of the pipeline that matches peptide sequences to the most similar PfEMP1 and calculates a weight value based on peptide's uniqueness used for PfEMP1 protein inference. The pipeline was first validated in the analysis of a laboratory strain with a known PfEMP1, then it was implemented on the analysis of parasite isolates from malaria-infected pregnant women and finally on the analysis of parasite isolates from malaria-infected children where there was an increase of PfEMP1s identified in 27 out of 31 isolates using the expanded database.