DOI: 10.5061/dryad.qnk98sfv8
title: High-throughput discovery of transmembrane helix dimers from human single-pass membrane proteins with TOXGREEN sort-seq

description: The oligomerization of the transmembrane helices of single-pass membrane
 proteins is crucial to biological function, and its misregulation can lead
 to many diseases. The study of transmembrane helix oligomerization is
 facilitated by the availability of genetic reporter assays, which are
 essential tools for understanding the organization and biology of
 single-pass systems. In particular, reporter assays are crucial for
 mapping the oligomerization interfaces of transmembrane helices through
 scanning mutagenesis, but their application is limited by the need to
 clone and measure each construct individually. Here, we present “TOXGREEN
 sort-seq”, a high-throughput version of the TOXGREEN assay that enables
 the direct measurement of transmembrane helix oligomerization in large
 libraries using fluorescence-activated cell sorting and next-generation
 sequencing. We show that TOXGREEN sort-seq is robust and reproduce the
 direct measurements of individual constructs with good accuracy and
 sensitivity. The method produced high-quality mutational profiles from a
 library of 17,400 constructs designed to probe the interface of 100
 potential GASrightdimers predicted from sequences of human single-pass
 membrane proteins. We report the validated structural model of twelve
 dimers involved in a variety of biological functions, including immune
 response (interleukin-22 receptor subunit alpha-1, butyrophilin-like
 protein 3, hepatitis A virus cellular receptor 2), transport (transferrin
 receptor protein 1), and cell-surface signaling and proliferation
 (syndecan-3; semaphorins 5A, 6B and 6D). Remarkably, all three semaphorins
 in the dataset formed strong dimers and produced mutational profiles
 consistent with the computational structure. These findings open the
 possibility that dimerization may be relevant to these proteins’ activity
 and provide a validated interface for assessing their biological role.
description: # High-throughput discovery of transmembrane helix dimers from human
 single-pass membrane proteins with TOXGREEN sort-seq Dataset DOI:
 [10.5061/dryad.qnk98sfv8](10.5061/dryad.qnk98sfv8) This repository
 contains: * Structural model of transmembrane helix dimers (PDB files) *
 Sort-seq Data * NGS data processing script (with example input data files)
 ## Structural model of transmembrane helix dimers (PDB files) ###
 Description of the data and file structure The files include the CATM and
 AlphaFold3 (AF3) models of the twelve GAS-right dimers validated by the
 mutagenesis. The files also include the CATM and AF3 models of the three
 proteins whose mutagenesis matches an AF3 model but not a CATM model. The
 CATM and AF3 models have been aligned with each other based on the
 transmembrane helices. #### Name scheme: ``&lt;.pdb&gt;`` #### Files of proteins matching the CATM model: *
 `O75056_syndecan-3_AF3_model_0.pdb` * `O75056_syndecan-3_CATM_model_1.pdb`
 * `P02786_TfR1_AF3_model_4.pdb` * `P02786_TfR1_CATM_model_1.pdb` *
 `Q13591_sema-5A_AF3_model_1.pdb` * `Q13591_sema-5A_CATM_model_1.pdb` *
 `Q6P7N7_TMEM81_AF3_model_0.pdb` * `Q6P7N7_TMEM81_CATM_model_1.pdb` *
 `Q6UW88_Epigen_AF3_model_3.pdb` * `Q6UW88_Epigen_CATM_model_1.pdb` *
 `Q6UXE8_BTNL3_AF3_model_4.pdb` * `Q6UXE8_BTNL3_CATM_model_3.pdb` *
 `Q8N6P7_IL22R1_AF3_model_0.pdb` * `Q8N6P7_IL22R1_CATM_model_1.pdb` *
 `Q8NEA5_C19orf18_AF3_model_0.pdb` * `Q8NEA5_C19orf18_CATM_model_2.pdb` *
 `Q8NFY4_sema-6D_AF3_model_2.pdb` * `Q8NFY4_sema-6D_CATM_model_1.pdb` *
 `Q8TDQ0_HAVCR2_AF3_model_3.pdb` * `Q8TDQ0_HAVCR2_CATM_model_1.pdb` *
 `Q9H3T3_sema-6B_AF3_model_4.pdb` * `Q9H3T3_sema-6B_CATM_model_1.pdb` *
 `Q9NVM1_EVA1B_AF3_model_2.pdb` * `Q9NVM1_EVA1B_CATM_model_1.pdb` ####
 Files of proteins matching only the AF3 model: *
 `P16410_CTLA4_AF3_model_3.pdb` * `P16410_CTLA4_CATM_model_1.pdb` *
 `P78380_OLR1_AF3_model_2.pdb` * `P78380_OLR1_CATM_model_1.pdb` *
 `Q9ULG6_CCPG1_AF3_model_0.pdb` * `Q9ULG6_CCPG1_CATM_model_1.pdb` ##
 Code/software PDB files are viewable with PyMol or other software that can
 read Protein Data Bank coordinate files. ## Sort-seq Data This repository
 contains processed data from high-throughput TOXGREEN sort-seq experiments
 used in the analysis presented in our manuscript. The data include deep
 sequencing results from three length libraries of single-pass membrane
 protein variants (wild-types and point mutants), as well as data
 describing the GFP fluorescence gates used during fluorescence-activated
 cell sorting. The following files contain processed sequencing data for
 three libraries of different transmembrane domain lengths: *
 `allSeqs17.csv` * `allSeqs19.csv` * `allSeqs21.csv` Each row in these
 files corresponds to a unique sequence observed in a specific library,
 replicate, and fluorescence bin. #### Column Descriptions: | Column Name |
 Description | | ----------- |
 ----------------------------------------------------------------------------------------------------------------------------- | | `TM` | Amino acid sequence of the transmembrane construct | | `Count` | Number of reads for this sequence in the corresponding bin | | `Percent` | Percentage of total reads in the bin represented by this sequence | | `ID` | UniProt ID of the wild-type protein | | `Name` | Protein name (as annotated in UniProt) | | `StartRes` | Starting residue number of the TM segment in the full-length wild-type protein | | `Mutation` | Single-point mutation, formatted as WTPosMut (e.g., A123V) | | `MutRes` | Position of the mutation within the TM sequence. N/A represents not applicable as wild-type sequences do not have a mutation. | | `Library` | Library transmembrane construct length (17, 19, or 21) | | `Replicate` | Experimental replicate number | | `Bin` | FACS fluorescence bin from which the sequence was recovered | ### Sort Gate Information File * `SortGateInfo.csv` This file contains data from the FACS gating and binning used during the sorting of each library replicate. #### Column Descriptions: | Column Name | Description | | -------------- | ------------------------------------------------------------------------------------ | | `Bin` | Fluorescence bin number during sorting | | `ReflowMedian` | Median GFP fluorescence of the reflow test sort (used to assess sorting bin quality) | | `ReflowMean` | Mean GFP fluorescence of the reflow test sort | | `Fraction` | Fraction of the total cell population falling within the bin during reflow | | `SetMedian` | Median GFP fluorescence of the final sorted population in the gated bin | | `SetMean` | Mean GFP fluorescence of the final sorted population in the gated bin | | `SetMin` | Minimum GFP fluorescence obtained in the final sorted population in the gated bin | | `SetMax` | Maximum GFP fluorescence obtained in the final sorted population in the gated bin | | `Library` | Library length (17, 19, or 21) | | `Replicate` | Sorting replicate number | ## NGS data processing script This script `fastqToTxt.pl` processes NGS data in `.fastq` format by extracting high-quality reads, translating DNA sequences into protein sequences, and matching them against a reference list. It outputs a count and frequency of each detected sequence and preserves annotation information if the sequence is found in a reference sequence file. ### Features * Reads `.fastq` files and filters out low-quality reads. * Extracts regions between given forward and reverse primers. * Translates the DNA region into an amino acid sequence. * Filters sequences by expected N- and C-terminal residues. * Matches protein sequences to a reference sequence file. * Reports the count, percentage, and metadata for matched sequences. ### Input Files #### 1. FASTQ File (`--seqFile`) A standard `.fastq` file with 4-line entries (sequence on line 2, quality on line 4). #### 2. Reference File (`--refFile`) A **tab-delimited** file with **7 columns**, where: | Column | Description | | ------ | ---------------------------------------- | | 0 | (optional metadata) | | 1 | (optional metadata) | | 2 | (optional metadata) | | 3 | (optional metadata) | | 4 | (optional metadata) | | 5 | (optional metadata) | | 6 | Protein sequence (**used for matching**) | The protein sequence in column 6 is the key used to identify matches, and columns 0–5 are printed as annotation when a match is found. ### Usage ```bash perl fastqToTxt.pl --refFile reference.csv --seqFile reads.fastq --direction 1 ``` #### Arguments * `--refFile`: Path to the tab-delimited reference file. * `--seqFile`: Path to the `.fastq` file to be analyzed. * `--direction`: Direction of sequencing reads: * `1` = forward * `2` = reverse ### Output The script prints to standard output a tab-delimited table containing: ``` ``` If the sequence is found in the reference file, the annotation from columns 0–5 is printed. If not, the script checks for special fallback cases or prints `Unknown`. ### Notes * Only sequences with expected quality (≤1 expected error) are retained. * Primers are hard-coded and must match the sequences used in library construction. * Sequences must start with `"AS"` and end with `"L"` after translation and are trimmed accordingly. * Matches are based on **exact protein sequences**; partial or fuzzy matches are not considered. * A default count threshold of 10 is applied to reduce noise. ### Example input files Run the script with the example input files provided, `example_reference_file.csv` and `example.fastq` with: ``` perl fastqToTxt.pl --refFile example_reference_file.csv --seqFile example.fastq --direction 1 ``` ## Notes * Sequence data files reflect processed reads that passed quality and frequency filters. * Bin statistics in `SortGateInfo.csv` were used to reconstruct fluorescence values for each construct. * All fluorescence values are reported in arbitrary units based on the GFP signal detected during sorting. ## Contact Alessandro Senes, [senes@wisc.edu](mailto:senes@wisc.edu) ## Access information Other publicly accessible locations of the data: * The CATM files are available at catm.biochem.wisc.edu/CATM * The AlphaFold files can be computed at the AlphaFold server [https://alphafoldserver.com/](https://alphafoldserver.com/) Data was derived from the following sources: * The structural predictions were made from the protein sequence from the Uniprot database: [https://www.uniprot.org/](https://www.uniprot.org/)