Heteromeric clusters of ubiquitinated ER-shaping proteins drive ER-phagy

Membrane-shaping proteins characterized by reticulon homology domains play an important part in the dynamic remodelling of the endoplasmic reticulum (ER). An example of such a protein is FAM134B, which can bind LC3 proteins and mediate the degradation of ER sheets through selective autophagy (ER-phagy)1. Mutations in FAM134B result in a neurodegenerative disorder in humans that mainly affects sensory and autonomic neurons2. Here we report that ARL6IP1, another ER-shaping protein that contains a reticulon homology domain and is associated with sensory loss3, interacts with FAM134B and participates in the formation of heteromeric multi-protein clusters required for ER-phagy. Moreover, ubiquitination of ARL6IP1 promotes this process. Accordingly, disruption of Arl6ip1 in mice causes an expansion of ER sheets in sensory neurons that degenerate over time. Primary cells obtained from Arl6ip1-deficient mice or from patients display incomplete budding of ER membranes and severe impairment of ER-phagy flux. Therefore, we propose that the clustering of ubiquitinated ER-shaping proteins facilitates the dynamic remodelling of the ER during ER-phagy and is important for neuronal maintenance.

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.

March 2021
7. The Perseus software (version 2.0.7.0) was used and first filtered for contaminants and reverse entries as well as proteins that were only identified by a modified peptide. 8. The data analysis and graphs were generated with GraphPad Prism 8.2.1 and 9.4.1 9. Diameters of liposomes were determined using ImageJ (version 1.53t). 10. The predicted structural model of ARL6IP1 was obtained with AlphaFold (https://alphafold.ebi.ac.uk) 11. Helical wheel representation was obtained with Heliquest (https://heliquest.ipmc.cnrs.fr) 12. The alignment of FAM134B and ARL6IP1 was carried out with the BioPython implementation of BLAST (https://biopython.org) 13. Modelling and simulations were performed using Pymol v2.54 (https://pymol.org/2) and gromacs (v.2019.3) (https://www.gromacs.or 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 Portfolio guidelines for submitting code & software for further information.

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 description of any restrictions on data availability -For clinical datasets or third party data, please ensure that the statement adheres to our policy The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers pxd032718, pxd032720 and pxd039184. All source data in main and extended data figures are provided as supplementary information. This also includes gels and blots. Materials and associated protocols are available upon request without undue qualifications.

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.

Replication
To ensure reproducibility all data presented in this manuscript was repeated three times as far as possible or confirmed by different experimental approaches. E.g. ubiquitination of FAM134B was validated in different cell lines by mass spectrometry and by biochemical approaches. Single cell analysis included at least three replicates and representative images are presented (confocal and TEM images). Results from all technical-and biological replicates were consistent.
Randomization Mass spectrometry samples were grouped as specified in the manuscript. Every data set was analyzed together (between group same experiment) to determine ubiquitination status. Littermates of the correct genotype were randomly assigned to the respective experimental cohorts. Cells for image analysis were selected randomly.

Blinding
The experimenter or the analyzing person was always blinded to the genotypes.

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

Study description
Briefly describe the study type including whether data are quantitative, qualitative, or mixed-methods (e.g. qualitative cross-sectional, quantitative experimental, mixed-methods case study).

Sampling strategy
Describe the sampling procedure (e.g. random, snowball, stratified, convenience). Describe the statistical methods that were used to predetermine sample size OR if no sample-size calculation was performed, describe how sample sizes were chosen and provide a rationale for why these sample sizes are sufficient. For qualitative data, please indicate whether data saturation was considered, and what criteria were used to decide that no further sampling was needed.

Data collection
Provide details about the data collection procedure, including the instruments or devices used to record the data (e.g. pen and paper, computer, eye tracker, video or audio equipment) whether anyone was present besides the participant(s) and the researcher, and whether the researcher was blind to experimental condition and/or the study hypothesis during data collection.

Timing
Indicate the start and stop dates of data collection. If there is a gap between collection periods, state the dates for each sample cohort.

Data exclusions
If no data were excluded from the analyses, state so OR if data were excluded, provide the exact number of exclusions and the rationale behind them, indicating whether exclusion criteria were pre-established.

Non-participation
State how many participants dropped out/declined participation and the reason(s) given OR provide response rate OR state that no participants dropped out/declined participation.

Randomization
If participants were not allocated into experimental groups, state so OR describe how participants were allocated to groups, and if allocation was not random, describe how covariates were controlled.

Ecological, evolutionary & environmental sciences study design
All studies must disclose on these points even when the disclosure is negative.

Sampling strategy
Note the sampling procedure. Describe the statistical methods that were used to predetermine sample size OR if no sample-size calculation was performed, describe how sample sizes were chosen and provide a rationale for why these sample sizes are sufficient.

Data collection
Describe the data collection procedure, including who recorded the data and how.