DOI: 10.5061/dryad.m905qfv6g
title: The midnolin-proteasome pathway catches proteins for ubiquitination-independent degradation

description: Cells use ubiquitin to mark proteins for proteasomal degradation. While
 the proteasome also eliminates proteins that are not modified by
 ubiquitin, how this occurs mechanistically is unclear. We show
 here that midnolin promotes the destruction of many nuclear proteins
 including transcription factors encoded by
 the immediate-early-genes. Diverse environmental
 cues induce midnolin and its overexpression is sufficient to
 cause the degradation of its targets by a mechanism, which, remarkably,
 does not require ubiquitination. Instead, midnolin associates with the
 proteasome via an alpha-helix, employs its Catch-domain to bind a region
 within substrates that adopts a beta-strand conformation, and uses a
 ubiquitin-like-domain to promote substrate destruction. Thus, midnolin
 contains three regions that function in concert to target a large set of
 nuclear proteins to the proteasome for degradation. 
description: DataS1: EGR1 and FosB genome-wide CRISPR-Cas9 screens
 Genome-wide CRISPR-Cas9 screens were performed to uncover
 regulators of EGR1 and FosB protein stability. Specifically, the plasmid
 library was packaged into lentivirus by transfecting HEK-293T cells using
 PolyJet as described earlier, and the lentivirus was titered to obtain a
 multiplicity of infection around 0.3. HEK-293T cells were generated to
 express the GPS 3.0 FosB or GPS 3.2 EGR1 reporters by selecting using
 hygromycin (200 µg/mL). These
 cells were then transduced with the titered CRISPR-Cas9 genome-wide Root
 library lentivirus at an MOI ~0.3 to maintain a 500x representation
 throughout. Cells were selected 48 hours post-transduction for 7 days
 using puromycin (2
 µg/mL) to remove uninfected cells. On the ninth day of puromycin
 selection, the 95<sup>th</sup> percentile most stable cell
 population was collected based on the GFP/DsRed ratio by FACS using a
 MoFlo Astrios instrument (Beckman Coulter). Additionally, the unsorted
 input cells were collected based on the number of cells collected in the
 enriched population. Collected cells were rinsed once with PBS, pelleted,
 and stored at -80°C. DataS2: Midnolin GPS
 ORFeome screen Sufficient cell numbers were used to
 maintain at least a 300-fold coverage of the library throughout. The
 library was packaged into lentivirus, which were used to transduce
 <em>MIDN</em> KO HEK-293T at a multiplicity of infection of
 0.2. Two days post-transduction, the HEK-293T cells were treated with 2
 µg/mL of puromycin for 6 days
 to remove uninfected cells, passaging the library once in between the
 selection period. The library-expressing cells were plated at 4 million
 cells/plate in a 15 cm dish and were transfected two days later using
 Polyjet with EF1a-Midnolin
 co-expressing BFP, or BFP alone as a negative control. The cells were harvested two days
 post-transfection and were sorted into six stability bins based on the
 GFP/DsRed ratio by FACS using a MoFlo Astrios instrument (Beckman
 Coulter). The sorting gates were established using the BFP control to
 ensure 1/6<sup>th</sup> of the population was collected per
 bin. Once the control populations were collected, the cells overexpressing
 midnolin were partitioned using the exact same sorting and gating settings
 as the control. The collected cells from each stability bin were rinsed
 once with PBS, pelleted, and frozen at -80°C for at least 12
 hours.  
 Deconvolution of the pooled screens for DataS1 and
 DataS2 Cell
 pellets were thawed, and genomic DNA was harvested using a Gentra Puregene
 Core Kit, Qiagen. The sgRNAs or barcodes were then amplified by PCR using
 all the genomic DNA as template (4 µg DNA per reaction) to include stagger
 sequences and Q5 Hot Start High-Fidelity DNA Polymerase from NEB. A second
 round of PCR was performed using the clean PCR1 product to add the
 Illumina P5 and P7 adaptor sequences. PCR2 samples were cleaned, pooled in
 the correct ratio, and sequenced on a NextSeq 500 instrument. The
 abundance of sgRNAs or barcodes was extracted from the raw sequencing data
 using Cutadapt and
 was mapped onto the reference library using Bowtie2.
 For DataS1, MAGeCK was
 used to determine the enrichment of sgRNAs in the
 95<sup>th</sup> percentile relative to the input
 population. The
 MAGeCK score plotted on the Y-axis represents the negative log10 of the
 “pos|score” value generated by MAGeCK. 
 For the GPS ORFeome
 analysis in DataS2, the abundance of each ORF was corrected to account for
 sequencing depth and a protein stability index (PSI) score between 1 (most
 unstable) and 6 (most stable) was calculated using the following formula
 for each extracted ORF:<em> </em>where <em>i</em>=the number
 of the stability bin denoted as an integer and R<em>i</em> =
 the Illumina read proportion extracted from the bin
 <em>i</em>. The change in protein stability between midnolin
 and BFP is denoted as the difference in PSI (deltaPSI). 
 DataS3: Endogenous Midnolin Immunoprecipitation and Mass
 Spectrometry HEK-293T cells expressing endogenous
 3xHA-tagged midnolin were cultured to 90% confluency in 5 15 cm plates per
 condition and unedited wild-type HEK-293T cells were cultured in 5 15 cm
 plates. The knock-in cells were treated was DMSO or 10 µM MG132 for 6
 hours while the unedited wild-type HEK-293T served as background and were
 treated with 10 µM MG132 for 6 hours. An anti-HA immunoprecipitation was
 performed using the same lysis conditions and protocol as described in the
 immunoprecipitation section of the methods. After the final wash, the
 beads were resuspended in 100 µL of 50 mM Tris pH 8.5 containing 5% SDS, and
 the samples were heated at 95°C for 5 minutes to elute the
 proteins.
 Eluted proteins were then digested using
 trypsin on S-Trap Micro columns (Protifi, C02-micro-10) following the
 manufacturer’s protocol. Specifically, proteins were first reduced using 5
 mM TCEP for 15 minutes at 55°C and were subsequently alkylated with 20 mM
 iodoacetamide for 30 minutes in the dark at room temperature. After
 alkylation, the samples were acidified using phosphoric acid to a final
 concentration of 2.5% (v/v), and 10 volumes of 100 mM Tris, pH 7.55 in 90%
 methanol/10% water were added to the samples to dilute the protein. This
 solution was then passed through S-Trap column by centrifuging for 30
 seconds at 4,000xg. Multiple rounds of centrifugation were needed to load
 the entirety of one sample onto one column. Once the protein was trapped,
 the column was rinsed three times using 100 mM Tris, pH 7.55 in 90%
 methanol/10% water, followed by a dry spin, before adding 2 µg of trypsin
 suspended in 20 µL 50 mM ammonium bicarbonate, pH 8. Columns were kept
 overnight at 37°C in a humid environment. After digestion, the peptides on
 the column were eluted by centrifuging three times for 1 minute at 4,000xg
 using three buffers applied sequentially: first 40 µL ammonium bicarbonate
 pH 8, second 40 µL 0.2% formic acid in water, and third 40 µL 50%
 acetonitrile in water. The pooled peptides were dried under reduced
 pressure using a SpeedVac and were resuspended in 30 µL 0.1% formic acid
 in water. LC-MS/MS data were acquired by injecting 10 µL of resuspended
 peptide sample. A protein database consisting of the
 Human UniProt SwissProt proteome (downloaded on November
 13<sup>th</sup>, 2022) was used to identify proteins that
 co-immunoprecipitated with endogenous 3xHA-midnolin. Specifically, the
 FragPipe graphical user interface (v18.0) was used to search the data
 using the MSFragger search engine and to perform post-processing of the
 search results. The following parameters were used in the search. Tryptic
 peptides with a maximum of two missed cleavages were considered.
 Additionally, carbamidomethylation of cysteine was set as a fixed
 modification, and oxidation of methionine was allowed as a variable
 modification, with a maximum of four variable modifications per peptide.
 The allowed mass tolerances were 10 ppm for precursor ions and 0.04 Da for
 product ions. Peptide hits were filtered to a false discovery rate of 1%
 using PeptideProphet as implemented in FragPipe.
 DataS4: AlphaFold PDB Models and summary of predicted beta
 strand degrons AlphaFold multimer
 predictions To identify beta strands within hits
 identified in the ORFeome GPS screen, genes with deltaPSI &lt; -0.5
 were taken (n=508) and the longest sequence across corresponding protein
 accession IDs (either NCBI Reference Sequence or Ensembl ID) was used as
 the input sequence for downstream steps (as barcodes from the screen were
 grouped at the gene level but could represent multiple isoforms).  These
 sequences were individually paired with the MIDN sequence (UniProtKB:
 Q504T8) as a two-sequence FASTA file input into AlphaFold (v2.2.0) for
 multimer prediction with default reference databases and
 max_template_date=2022-01-01.  Any selenocysteines were recoded as
 cysteines and three substrates (ACSBG2, ACSS2, and RIMBP3) that failed MSA
 using the default settings were rerun successfully by replacing the
 UniClust30_2018_08 database with UniRef30_2022_02.
 Identification of substrate beta strands within Midnolin beta
 sheet The 25 ranked PDB models from each AlphaFold run
 with MIDN and one of the substrates were then processed by a custom Python
 script to identify PDB models that folded a linear stretch of the
 substrate into beta strand conformation placed between beta strands of the
 corresponding MIDN domain.  In more detail, a pairwise distance matrix was
 first computed between each ?-carbon atom in MIDN and each
 ?-carbon atom in the substrate as: 
 D<sub>i,j
 </sub>= square root((x<sub>i </sub>- xj)<sup>2
 </sup>+ (y<sub>i </sub>- yj)<sup>2 </sup>+
 (z<sub>i </sub>- zj)<sup>2</sup>)
 where x<sub>i</sub>,y<sub>i</sub>, and
 z<sub>i</sub> are the coordinates of the
 i<sup>th</sup> substrate ?-carbon atom and x<sub>j</sub>,
 y<sub>j</sub>, and z<sub>j</sub> are the
 coordinates of the j<sup>th</sup> MIDN ?-carbon atom.  As most beta sheets have
 inter-strand distances &lt; 5 Å, the distance matrix was scanned to
 identify sequential substrate residues &lt; 5.5 Å from corresponding
 linear stretches within each adjacent MIDN beta strand (ie.
 D<sub>i,j</sub> &lt; 5.5 for both some sequential set of
 <em>i</em> with some sequential set of <em>j</em>,
 where 148 ≤ j ≤157, as well as the same set of <em>i</em> with
 another sequential set of <em>j</em>, where 279 ≤
 <em>j</em> ≤ 286). Secondary structure
 assignment for the PDB model was done with the DSSP algorithm. Substrate
 residues satisfying the distance requirements specified above were then
 retained if they were assigned the extended beta strand secondary
 structure (ie. “E” coding).  As DSSP relies on flanking residues to call
 secondary structure, the most N- and C-terminal residues are not assigned
 secondary structure.  To avoid excluding them from beta strand
 assignments, they were assigned “E” coding if the adjacent residue had
 been assigned “E” coding. To catch residues that are part of a beta
 strand, but slightly further from one or both of the MIDN beta strands,
 this set of residues was then expanded by 7 residues in each direction and
 again only those with extended beta strand secondary structure were kept. 
 Finally, the longest contiguous stretch of beta strand secondary structure
 was kept (if any) for final reporting in DataS4.  
description: PDB files for AlphaFold multimer predictions can be opened with
 softwares such as PyMOL and ChimeraX.