Ubiquitin-like protein 3 (UBL3) is required for MARCH ubiquitination of major histocompatibility complex class II and CD86

The MARCH E3 ubiquitin (Ub) ligase MARCH1 regulates trafficking of major histocompatibility complex class II (MHC II) and CD86, molecules of critical importance to immunity. Here we show, using a genome-wide CRISPR knockout screen, that ubiquitin-like protein 3 (UBL3) is a necessary component of ubiquitination-mediated trafficking of these molecules in mice and in humans. Ubl3-deficient mice have elevated MHC II and CD86 expression on the surface of professional and atypical antigen presenting cells. UBL3 also regulates MHC II and CD86 in human dendritic cells (DCs) and macrophages. UBL3 impacts ubiquitination of MARCH1 substrates, a mechanism that requires UBL3 plasma membrane anchoring via prenylation. Loss of UBL3 alters adaptive immunity with impaired development of thymic regulatory T cells, loss of conventional type 1 DCs, increased number of trogocytic marginal zone B cells, and defective in vivo MHC II and MHC I antigen presentation. In summary, we identify UBL3 as a conserved, critical factor in MARCH1-mediated ubiquitination with important roles in immune responses.

For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section.
n/a Confirmed The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.
A description of all covariates tested A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Give P values as exact values whenever suitable.

For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings
For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Software and code
Policy information about availability of computer code Data collection Flow cytometric data was obtained using FACSDiva version 9.0.1 (BD) and exported into FCS 3.0. Sequencing data collection for the CRISPR library were performed according to the instructions of the Illumina NextSeq 500 system. Western blot data was collected using ImageLab version 5.2.1 (Bio-Rad). Microscopy data was obtained using the LAS X software platform version 3.1.1. Mass Spectrometry data was obtained according to the instructions of the Q-Exactive system.

Data analysis
The CRISPR library screen was analysed in R using the edgeR package (https://bioconductor.org/packages/release/bioc/html/edgeR.html), flow cytometry data was analysed in Flowjo v9 and v10, microscopy data was analysed with the FIJI distrubition of ImageJ (2.0.0-rc-69/1.52p) (confocal microscopy), or Imaris v9.7 (proximity ligation assay). Statistical analysis of flow cytometric and western blot imaging data was performed in Prism versions v6, v8, and v9.0.0 (Graphpad). Mass Spectrometry data was analysed using MaxQuant software (ver. v1.6.17.0) and the LFQAnalyst portal (https://bioinformatics.erc.monash.edu/apps/LFQ-Analyst/ -accessed 14/07/2021) For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

April 2020
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Source data underlying Figures 1a 2b,3d,8,3c,5,, and 7c are provided as Source Data file. Proteomics data have been deposited to the ProteomeXchange Consortium via jPOST (accession codes JPST001444, PXD030790). The fasta file containing the mouse reference proteome used for the analysis of raw MS data using MaxQuant was retrieved from Uniprot (proteome id UP000000589, downloaded 09-03-2021).

Field-specific reporting
Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences
For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
All studies must disclose on these points even when the disclosure is negative.

Sample size
All relevant sample sizes are described in the legends in the figure and/or the materials and methods section. Sample sizes were determined based on prior experiences with each of the experimental systems and their expected variability. No statistical testing was used to predetermine saple size.
Data exclusions After optimising experimental conditions, all data that met predetermined quality control expectations (e.g. sufficient staining, successful injection) were included. Randomization No randomisation was done as no experimental groups were used in this study.

Blinding
No blinding was used in our experiments, since the readouts were quantitative and not prone to subjective judgement of investirators. however the CRISPR KO screen was unbiased in nature.

Authentication
Cell lines were authenticated by flow cytometry for expression of expected markers, and morphological analysis.

Mycoplasma contamination
All cell lines were routinely tested for mycoplasma and were negative.
Commonly misidentified lines (See ICLAC register) None were used.

Animals and other organisms
Policy information about studies involving animals; ARRIVE guidelines recommended for reporting animal research Laboratory animals C57BL/6J (H-2b), Marchf1−/−, Marchf8−/−, and Ubl3−/− age and sex matched mice (either female or male) were used at 6-12 weeks of age. Ubl3-/-mice were generated at the Melbourne Advanced Genome Editing Centre (MAGEC) facility via CRISPR/Cas9 system as described in Methods and Figure 2a. For other strains see methods for references.

Wild animals
No wild animals were used.
Field-collected samples No field collected samples were used.

Ethics oversight
Experimental procedures were approved by the Animal Ethics Committee of the University of Melbourne (protocol no. 1714375).
Note that full information on the approval of the study protocol must also be provided in the manuscript.

Flow Cytometry
Plots Confirm that: The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).
The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
All plots are contour plots with outliers or pseudocolor plots.
A numerical value for number of cells or percentage (with statistics) is provided.