DOI: 10.5061/dryad.xsj3tx9bd
title: A human IgSF cell-surface interactome reveals a complex network of protein-protein interactions

description: Cell-surface protein-protein interactions (PPIs) mediate cell-cell
 communication, recognition and responses. We executed an interactome
 screen of 564 human cell-surface and secreted proteins, most of which are
 immunoglobulin superfamily (IgSF) proteins, using a high-throughput,
 automated ELISA-based screening platform employing a pooled-protein
 strategy to test all 318,096 PPI combinations. Screen results, augmented
 by phylogenetic homology analysis, revealed ~380 previously unreported
 PPIs. We validated a subset using surface plasmon resonance and cell
 binding assays. Observed PPIs reveal a large and complex network of
 interactions both within and across biological systems. We identified new
 PPIs for receptors with well-characterized ligands, and binding partners
 for ‘orphan’ receptors. New PPIs include proteins expressed on multiple
 cell types, and involved in diverse processes including immune and nervous
 system development and function, differentiation/proliferation,
 metabolism, vascularization, and reproduction. These PPIs provide a
 resource for further biological investigation into their functional
 relevance, and may offer new therapeutic drug targets.
description: High-throughput, automated ELISA-based protein-protein
 interaction (PPI) screen of secreted proteins and the extracellular domain
 (ECD) region of cell-surface single-transmembrane proteins. 564 secreted
 and ECD proteins were produced in two different multimerized versions,
 'bait' and 'prey', and every combination was tested
 for binding (i.e., 564 x 564 = 318,096). The read-out of the assay is
 colorimetric and plates are read at O.D. 650 nm. Experiments were
 performed in triplicate. Background was determined by averaging the
 binding signal from all 564 'prey' proteins on each
 'bait'. The signal of each protein was divided by the background
 to determine fold-over-background binding (F.O.B.). Both raw and processed
 data are included in Wojtowicz et al_DataS4.  Multiple
 sequence alignment (MSA) of the 564 secreted and ECD proteins included in
 the screen was performed using MUltiple Sequence Comparison by Log-
 Expectation (MUSCLE) (https://www.ebi.ac.uk/Tools/msa/muscle/) and Multiple Alignment using Fast Fourier Transform (MAFFT) (https://mafft.cbrc.jp/alignment/server/) online resources and analyzed using both first iteration and  second iteration parameters (MUSCLE) and the default parameters (MAFFT) (https://www.ebi.ac.uk/Tools/msa/muscle/). MSA files were submitted to the Interactive Tree of Life (iTOL) (https://itol.embl.de/), an agglomerative hierarchical clustering algorithm, to build a cluster hierarchy and generate phylogenetic trees. Screen data were analyzed alongside the phylogenetic trees to predict additional PPIs between subfamily members that may have been missed in the screen (false negatives). MSA data files are provided as follows: Wojtowicz et al_DataS6 (MUSCLE, first iteration), Wojtowicz et al_DataS7 (MUSCLE, second iteration) and Wojtowicz et al_DataS8 (MAFFT).
description: MSA sequence files can be used to generate and visualize
 phylogenetic trees. We use the Interactive Tree of Life (iTOL) (https://itol.embl.de/), an
 agglomerative hierarchical clustering algorithm, to build a cluster
 hierarchy and generate the phylogenetic trees.