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Additional file 1: Fig. S1. Silver staining on α-syn used in Protein aggregation experiments. Two replicate silver staining experiments performed on a 4-20% SDS-PAGE gel with 1 μg of purified α-syn after one (lane 3) and two (lane 2) size-exclusion chromatography steps. Fig. S2. T50 measured in Six different human CSF samples spiked with 20 fg of seeds. The measured T50 parameters were globally different, as assessed by one-way analysis of variance (ANOVA) and Fisher’s LSD post-hoc test for mean comparisons. *0.01 100 kDa CSF fraction in PBS. The residues experiencing the largest decreases in signal intensity (smaller by one or more standard deviations with respect to the average value) are highlighted in light blue. The intensity ratios corresponding to overlapping peaks are highlighted in red (their values were not considered in the calculation of the average decreases and standard deviations). Fig. S5. CSF pH drift. The pH change due to the exposure of CSF to air was monitored over time in 500 μL of undiluted pooled CSF (A) and in the presence of PBS (400 μL CSF + 200 μL PBS 3x) in polypropylene vials with a Thermo Scientific Orion pH-meter equipped with a glass 6 mm diameter pHenomenal MIC 220 Micro electrode. Right before each measurement, the sample was vortexed for 20 sec and left open to air for another 20 sec. Fig. S6. Different CSF fractions differently affect α-syn aggregation. Mean fitted t2 parameters of samples with 40 μl of PBS/CSF fractions. The values displayed result from the average of three replicates with error bars reflecting the SEM. For whole CSF and the >100 kDa fraction the total duration of the experiment is shown due to the absence of appreciable aggregation. Fig. S7. Raw images of the dot-blot assays. A-B) Native images of the dot-blot assay performed on α-syn alone replicates at different timepoints with OC (A) and A11 (B) conformational antibodies. C-D) Native image of the dot-blot assay performed on the HSA and HDL containing samples with OC (C) and A11 (D) conformational antibodies. Fig. S8. WB experiments to track α-syn aggregation in the presence of human HDL. A) α-Syn aggregation patterns in samples collected at different timepoints of the spontaneous aggregation process, was monitored by WB using Syn211 antibody (4-20% SDS-PAGE, 2 μg protein loaded). Monomeric α-syn decreases as t increases due to the formation of fibrils. B) In a similar way, a WB with Syn211 was performed on the reaction products obtained after 180 h, at different HDL concentrations with and without α-syn (exposure time 210 s). C) The experiment was then repeated by doubling the amount of sample loaded into the gel to better highlight the presence of oligomeric species (exposure time 30 s). Under these conditions, chosen to better visualize the signal at 150-200 kDa, the α-syn monomer bands at 1 and 0.3 mg/mL HDL may not quantitively reflect monomer concentration (overloaded lanes). Fig. S9. Representative TEM images of α-syn incubated with CSF. Representative TEM images obtained by analyzing samples obtained by the co-incubation of α-syn 0.7 mg/mL at 37 °C with pooled human CSF (1:5 ratio with respect to total reaction volume). Samples were subjected to cycles of incubation (13 min) and shaking (double-orbital, 2 min) at 500 rpm. Fig. S10. NMR titrations of α-syn with HDL, LDL and TTR. A) Intensity decreases of the signals of two-dimensional (2D) 15N–1H HSQC experiments acquired at 950 MHz at T = 283 K on 15N labelled α-syn (100 μM) in PBS after the addition of 0.57 mg/mL serum-derived HDL. The intensity ratios corresponding to overlapping peaks are highlighted in red. B) Intensity decreases of the signals of two-dimensional (2D) 15N–1H HSQC experiments acquired at 950 MHz at T = 283 K on 15N labelled α-syn (100 μM) in PBS after the addition of 1 mg/mL serum-derived LDL. C) Intensity decreases of the signals of two-dimensional (2D) 15N–1H HSQC experiments acquired at 950 MHz at T = 283 K on 15N labelled α-syn (100 μM) in PBS after the addition of 3 mg/mL TTR. Fig. S11. WB experiments performed on immunodepleted CSF. WB experiments were performed with anti-ApoA1 (MIA1404) and anti-ApoE (PA5-27088) antibodies on neat CSF and supernatants (400 μL CSF, 100 μL slurry) resulting from immunoprecipitation procedure performed using different quantities of the same antibodies (IP CSF samples), immunoprecipitation performed without antibodies (CSF IP no Ab). The conditions relative to IP CSF ApoA1 60 µg and IP CSF ApoE 20 µg were then selected for Protein aggregation assays. Table S1. Concentration factors and final volumes of the CSF fractions.

Plants and their associated microbiota share ecological and evolutionary traits that are considered to be inseparably woven. Their coexistence foresees the use of similar metabolic pathways, leading to the generation of molecules that can cross-regulate each other’s metabolism and ultimately influence plant phenotype. However, the extent to which the microbiota contributes to the overall plant metabolic landscape remains largely unexplored. Due to their early presence in the seed, seed-borne endophytic bacteria can intimately colonize the plant’s endosphere while conferring a series of phytobeneficial services to their host. Understanding the dynamics of these endophytic communities is a crucial step toward the formulation of microbial inoculants that can modulate the functionality of the plant-associated microbiota for improved plant fitness. In this work, wheat (Triticum aestivum) roots non-inoculated and inoculated with the bacterium Herbaspirillum seropedicae strain RAM10 were analyzed to explore the impact of inoculant–endophyte–wheat interrelationships on the regulation of tryptophan (Trp) metabolism in the endosphere environment. Root inoculation with H. seropedicae led to phylum-specific changes in the cultivable seed-borne endophytic community. This modulation shifted the metabolic potential of the community in light of its capacity to modulate the levels of key Trp-related metabolites involved in both indole-3-acetic acid (IAA) biosynthesis and in the kynurenine pathway. Our results support a mode of action of H. seropedicae relying on a shift in both the composition and functionality of the seed-borne endophytic community, which may govern important processes such as root growth. We finally provide a conceptual framework illustrating that interactions among roots, inoculants, and seed-borne endophytes are critical to fine-tuning the levels of IAA in the endosphere. Understanding the outcomes of these interactions is a crucial step toward the formulation of microbial inoculants based on their joint action with seed-borne endophytic communities to promote crop growth and health in a sustainable manner.