## 3 Materials and Methods
### NanoLC-MS/MS Protein Identification and Quantification  
Samples were resuspended in 35 uL of 10% ACN and 0.1% TFA in HPLC-grade water. For immunoprecipitation experiments, single-shot MS analysis was performed. For each run, 2 uL was injected in a nanoRSLC-Q Exactive PLUS (RSLC Ultimate 3000) (Thermo Scientific, Waltham MA, USA). Peptides were loaded onto a u-precolumn (Acclaim PepMap 100 C18, cartridge, 300 um i.d. \(\times\) 5 mm, 5 um) (Thermo Scientific, Waltham MA, USA), and were separated on a 50 cm reversed-phase liquid chromatographic column (0.075 mm ID, Acclaim PepMap 100, C18, 2 um) (Thermo Scientific, Waltham MA, USA). Chromatography solvents were (A) 0.1% formic acid in water and (B) 80% acetonitrile and 0.08% formic acid. Peptides were eluted from the column with the following gradient 5-40% B (120 min) and 40-80% (1 min). At 121 min, the gradient stayed at 80% for 5 min, and at 126 min, it returned to 5% to re-equilibrate the column for 20 min before the next injection. One blank was run between each replicate to prevent sample carryover. Peptides eluting from the column were analyzed by data dependent MS/MS, using the top-10 acquisition method and fragmented using higher-energy collisional dissociation (HCD). Briefly, the instrument settings were as follows: the resolution was set to 70,000 for MS scans and 17,500 for the data dependent MS/MS scans in order to increase speed. The MS AGC target was set to 3 \(\times\) 10\({}^{6}\) counts with a maximum injection time set to 60 ms, while the MS/MS AGC target was set to 1 \(\times\) 10\({}^{5}\) with maximum injection time set to 120 ms. The MS scan range was from 400 to 2000 \(m/z\). Dynamic exclusion was set to a 30 s duration.  
The MS files were searched with the MaxQuant software version 1.6.6.0 and searched with the Andromeda search engine against the database of Mus musculus from Swiss-Prot 07/2020 and _Plasmodium berghei_ ANKA from PlasmoDB (v.37). To search parent mass and fragment ions, we set a mass deviation of 3 and 20 ppm, respectively. The minimum peptide length was set to 7 amino acids and strict specificity for trypsin cleavage was required, allowing up to two missed cleavage sites. Carbamidomethylation (Cys) was set as fixed modification, whereas oxidation (Met) and N-term acetylation were set as variable modifications. The false discovery rates (FDRs) at the protein and peptide levels were set to 1%. Scores were calculated in MaxQuant as described previously [36]. The reverse and common contaminants hits were removed from MaxQuant output. Proteins were quantified according to the MaxQuant label-free algorithm using LFQ intensities; protein quantification was obtained using at least 2 peptides per protein. Matches between runs were allowed.  
Statistical and bioinformatic analyses, were performed with Perseus software (version 1.6.12.0) freely available at www.perseus-framework.org [37]. For statistical comparison, we set six groups: PbWT schionts and gametocytes as the negative control (S_WT, G_WT), immunoprecipitates from schionts and gametocytes expressing PbPP1c-mCherry (i.e., S_PP1 and G-PP1), and immunoprecipitates from schionts and gametocytes expressing PbI2-mCherry (i.e., S_12 and G_12). Each group contained five biological replicates. We then filtered the data to keep only proteins with at least 5 valid values in at least one group.  
Next, the data were imputed to fill missing data points by creating a Gaussian distribution of random numbers with a standard deviation of 33% relative to the standard deviation of the measured values and 1.8 standard deviation downshift of the mean to simulate the distribution of low signal values. We performed a \(t\)-test represented on a volcano plot, FDR < 0.05, S0 = 1.