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A Drosophila screen identifies NKCC1 as a modifier of NGLY1 deficiency

  1. Dana M Talsness
  2. Katie G Owings
  3. Emily Coelho
  4. Gaelle Mercenne
  5. John M Pleinis
  6. Raghavendran Partha
  7. Kevin A Hope
  8. Aamir R Zuberi
  9. Nathan L Clark
  10. Cathleen M Lutz
  11. Aylin R Rodan
  12. Clement Y Chow  Is a corresponding author
  1. Department of Human Genetics, University of Utah School of Medicine, United States
  2. Department of Internal Medicine, Division of Nephrology and Hypertension, and Molecular Medicine Program, University of Utah, United States
  3. Department of Computational and Systems Biology, University of Pittsburgh, United States
  4. Genetic Resource Science, The Jackson Laboratory, United States
  5. Medical Service, Veterans Affairs Salt Lake City Health Care System, United States
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Cite this article as: eLife 2020;9:e57831 doi: 10.7554/eLife.57831

Abstract

N-Glycanase 1 (NGLY1) is a cytoplasmic deglycosylating enzyme. Loss-of-function mutations in the NGLY1 gene cause NGLY1 deficiency, which is characterized by developmental delay, seizures, and a lack of sweat and tears. To model the phenotypic variability observed among patients, we crossed a Drosophila model of NGLY1 deficiency onto a panel of genetically diverse strains. The resulting progeny showed a phenotypic spectrum from 0 to 100% lethality. Association analysis on the lethality phenotype, as well as an evolutionary rate covariation analysis, generated lists of modifying genes, providing insight into NGLY1 function and disease. The top association hit was Ncc69 (human NKCC1/2), a conserved ion transporter. Analyses in NGLY1-/- mouse cells demonstrated that NKCC1 has an altered average molecular weight and reduced function. The misregulation of this ion transporter may explain the observed defects in secretory epithelium function in NGLY1 deficiency patients.

Introduction

NGLY1 deficiency (OMIM 615273) is a rare, autosomal recessive disorder caused by loss-of-function mutations in the NGLY1 gene. Patients with NGLY1 deficiency have a variety of symptoms, including developmental delay, seizures, liver dysfunction, central and peripheral nervous system abnormalities, sweat gland abnormalities, and a lack of tears (alacrima) (Enns et al., 2014; Lam et al., 2017). While the first NGLY1 deficiency patient was only recently identified (Need et al., 2012), there have been rapid research advances thanks to the support of two patient organizations (NGLY1.org and Grace Science Foundation). Even though a great deal has been learned about the genetic disorder in a short amount of time, there are currently no cures or approved treatments for NGLY1 deficiency.

The NGLY1 gene encodes the N-Glycanase protein (NGLY1). NGLY1 functions as part of the Endoplasmic Reticulum (ER) Associated Degradation (ERAD) pathway as evidenced by its association with other ERAD components (Katiyar et al., 2005; McNeill et al., 2004; Park et al., 2001). The ERAD pathway retrotranslocates misfolded proteins from the ER lumen to the cytoplasm where they are degraded by the proteasome (reviewed in Qi et al., 2017). NGLY1 is localized to the cytoplasm where it is thought to remove N-linked glycans from misfolded proteins prior to their degradation (Hirsch et al., 2003). Recent evidence suggests that this deglycosylation is required for retrotranslocation for at least some protein substrates (Galeone et al., 2020). Nevertheless, it remains unclear whether NGLY1 is required to deglycosylate all misfolded proteins, or just a subset, or if it is necessary for protein degradation at all. It has been shown that model substrates can be degraded regardless of glycosylation state (Hirsch et al., 2003; Kario et al., 2008). While a recent report showed that ER stress markers were increased in NGLY1 -/- MEFs (Galeone et al., 2020), other experiments such as RNAi knockdown (KD) of NGLY1 in Drosophila (Owings et al., 2018) and loss of NGLY1 function in mouse, rat, and human cells (Asahina et al., 2020; Mueller et al., 2020; Tambe et al., 2019) have shown no evidence of ER stress. ER stress is often observed when there are mutations in proteins that are necessary for ERAD due to the accumulation of misfolded proteins in the ER. It may be that NGLY1 is not necessary for ERAD, or it is involved in a non-canonical ERAD function, or it may be deglycosylating cytoplasmic proteins for an entirely different purpose. These hypothesized functions are not mutually exclusive.

NGLY1 has been shown to deglycosylate various exogenous model substrates such as TCR-α (Hirsch et al., 2003) and RNaseB (Kario et al., 2008). To identify endogenous substrates several mass spectrometry experiments have been performed (Fujihira et al., 2017; Hosomi et al., 2016; Maynard et al., 2020; Zolekar et al., 2018). Yet, the first high-confidence substrate of NGLY1 deglycosylation, NRF1 (gene: NFE2L1), was discovered in a Caenorhabditis elegans genetic screen (Lehrbach and Ruvkun, 2016). NRF1 mediates a proteasome ‘bounce-back’ response. NRF1 is constitutively degraded by the proteasome through the ERAD pathway, until the proteasome is inhibited or overwhelmed by protein load. During this proteasome stress, NRF1 accumulates and is deglycosylated by NGLY1 (Tomlin et al., 2017). Rather than targeting the protein for degradation, the deglycosylation activates NRF1 by converting asparagine to aspartic acid residues (Lehrbach et al., 2019). NRF1 can then be imported into the nucleus to act as a transcription factor for proteasome subunits. The lack of NRF1 activation in NGLY1-deficient patients likely explains some of the disorder’s symptoms such as motor dysfunction (Kobayashi et al., 2011) and cognitive deficits (Lee et al., 2011). Recently, it was found that the protein BMP4 is deglycosylated by NGLY1 when overexpressed in either Drosophila or mammalian cells (Galeone et al., 2020). BMP4 is a signaling molecule and could explain several of the developmental symptoms of NGLY1 deficiency. However, not all symptoms can be explained by these two targets and therefore there is a pressing need to identify and validate more substrates of NGLY1 deglycosylation.

In addition to discovering new NGLY1 targets, there is a need to understand how background genetic variants affect the number and severity of symptoms in patients. While the majority of patients harbor two complete loss-of-function mutations in NGLY1 (He et al., 2015), there are many symptoms such as seizures and scoliosis that are only reported in a subset of the patients (Enns et al., 2014). All patients experience developmental delay, but it ranges from slightly below average IQ to completely non-verbal (Lam et al., 2017). This variability based on background genetics was also observed in the lab when an NGLY1 deficiency mouse model was crossed onto an outbred mouse strain which partially rescued the lethality of the model (Fujihira et al., 2017). In order to identify components of the genetic background that affect the range of symptoms and severity of disease, we have utilized a collection of genetically diverse Drosophila strains known as the Drosophila Genetic Reference Panel (DGRP) (Mackay et al., 2012). By crossing a fly model of NGLY1 deficiency onto the panel, we recapitulated the variable phenotype seen in the human population. Here, we report the results of this cross and a list of candidate modifier genes derived from the genome-wide association (GWA) of the cross. To contextualize the candidate modifier list, we also performed an evolutionary rate covariation (ERC) analysis to identify genes that are co-evolving with NGLY1. Together these two genetic analyses have generated a list of genes that (1) may explain some of the variation seen between NGLY1 patients, (2) may encode proteins that physically interact with NGLY1 in ERAD or other cellular processes, and (3) may be direct deglycosylation targets of NGLY1. The top candidate modifier gene from the GWA is NKCC1, a conserved Na/K/Cl ion co-transporter. We found that NKCC1 modifies multiple phenotypes in Drosophila, and in NGLY1 -/- mammalian cells, NKCC1 displays abnormal average molecular weight and has reduced activity. The misregulation of NKCC1 likely explains several prominent secretory epithelium-related phenotypes observed in NGLY1 deficiency patients.

Results

Variation in lethality associated with NGLY1 deficiency

We crossed a fly model of NGLY1 deficiency (Pngl in flies, hereon referred to as NGLY1) onto 163 strains of the DGRP in order to assess the effect of natural variation on loss of NGLY1 function. We have previously validated this NGLY1 deficiency model where an NGLY1 RNAi reduces NGLY1 transcript by >95% when driven by the ubiquitous Tubulin-GAL4 driver transgene (Tubulin > NGLY1 RNAi) (Owings et al., 2018). In order to cross a ubiquitously expressed NGLY1RNAi onto the DGRP strains in a single cross, we needed to overcome the lethality associated with loss of NGLY1 (Owings et al., 2018). To do this, a Tubulin-GAL80 transgene, which represses the effect of GAL4, was crossed onto the Tubulin > NGLY1 RNAi background, such that RNAi is not expressed and flies from this parent strain are healthy and viable (Figure 1A). This donor strain was crossed to each DGRP strain to generate F1 flies that have both ubiquitous KD of NGLY1 and 50% of their genome from each respective DGRP strain (Figure 1B). In this way, analyzing the F1 progeny was a direct measurement of the dominant effect of the DGRP genetic variants on the NGLY1 KD phenotype.

Figure 1 with 1 supplement see all
Lethality phenotype of NGLY1 knockdown is highly modifiable by strain background.

(A) Drosophila cross for NGLY1 knockdown in each Drosophila genetic reference panel (DGRP) strain. (B) Proportion of NGLY1 knockdown flies surviving for each cross was calculated based on the number eclosing compared to the expected number. Expected number was based on the largest control balancer class for each cross.

The phenotypic outcome used for this screen was adult survival through eclosion. We simply scored all adults emerging from each cross in the four balancer categories: CyO, Sb, double balanced, or no balancers, with the no balancer flies being the NGLY1 KD. If no lethality is present, Mendelian segregation should produce the expected 1:1:1:1 ratio of the genotypes. Given that there is a very low level of lethality associated with each balancer, the largest balancer class is the closest to the expected, and was used to calculate the ratio of lethality for NGLY1 KD. Results of the screen reveal that survival to adulthood was strongly influenced by DGRP genetic background (Figure 1B; Supplementary file 1), with proportion of surviving flies ranging from 0.0 to 0.967. Survival to adulthood was not correlated with efficiency of RNAi, as there was no difference in KD efficiency in flies from either end of the phenotypic distribution (low surviving: 92.0% ± 3.7; high surviving: 94.8% ± 3.7; p=0.4). There was no correlation between proportion of surviving flies and the absolute number of flies in the balancer class (R2 = 0.02; p=0.14), indicating that the ratio is not driven by the number of the balancer control flies.

Genome-wide association

We hypothesized that the observed variable survival to adulthood in NGLY1 KD flies was due to the underlying genetic variation in the DGRP. Therefore, genome-wide association (GWA) analysis of the fully sequenced DGRP was used to identify variants that associated with NGLY1 KD survival. We used a linear mixed model to test 2,007,145 single-nucleotide polymorphisms (SNPs; Supplementary file 2). We recognize that our study suffers from a multiple testing problem, making it difficult to interpret the role of any single SNP identified. Instead, the location of SNPs was used to identify candidate modifier genes. This type of approach has worked well in the past for other disease models (Ahlers et al., 2019; Chow et al., 2013a; Chow et al., 2013b; Lavoy et al., 2018; Palu et al., 2019) and provides an unbiased list of candidate genes that can be functionally tested for interactions with NGLY1.

At a nominal p-value of p<10−5, 125 variants are associated with survival to adulthood. Of these 125 variants, 21 fall outside of a gene region (+/- 1 kb from the 5’ or 3’ UTRs) (Supplementary file 3). The remaining 104 variants map to 61 protein coding candidate genes (Table 1). Eighty-five of these 104 variants are in noncoding regions (UTRs, introns, or upstream or downstream) and 19 are in coding regions. Of these 19, 12 are synonymous changes and 7 are nonsynonymous (exp, hiw, CG30048, SP2353, CG31690, Hrd3, and blue). When multiple testing correction is applied to all the variants, the top 12 remain significant. Nine of these SNPs reside in an intron of the Ncc69 gene. All nine SNPs are in strong linkage disequilibrium with each other, which is quite unusual for the DGRP. When we analyzed Ncc69 expression levels using previously published RNAseq data from the DGRP (Everett et al., 2020), we found there was no correlation with survival (Figure 1—figure supplement 1).

Table 1
Candidate modifier genes identified from GWA.

Rank order of candidate genes was established based on the most significant associated SNP in the respective gene.

Rank orderGeneFBgnHuman orthologPeriphery/membraneProteostasis
1expFBgn0033668---nono
2Ncc69FBgn0036279NKCC1/2yesno
3CG5888FBgn0028523---yesno
4CG16898FBgn0034480---nono
5bru3FBgn0264001CELF2/3/4/5/6nono
6CG31690FBgn0051690TMTC2noyes
7CG7227FBgn0031970SCARB1nono
8CR44997FBgn0266348---nono
9rgnFBgn0261258Manynono
10M6FBgn0037092GPM6Ayesno
11Rab26FBgn0086913RAB26yesyes
12Obp56iFBgn0043532---nono
135-HT1AFBgn0004168HTR1Ayesno
14CG33012FBgn0053012ERMP1noyes
15rstFBgn0003285---yesno
16CR43926FBgn0264547---nono
17CG7337FBgn0031374WDR62nono
18hiwFBgn0030600MYCBP2yesyes
19fidFBgn0259146TRMT9Bnono
20nmoFBgn0011817NLKnono
21SirupFBgn0031971SDHAF4nono
22tstFBgn0039117SKIV2Lnono
23Mdr50FBgn0010241manyyesno
24Cpr49AaFBgn0050045---nono
25COX7CFBgn0040773COX7Cnono
26Eip63EFBgn0005640CDK14/15yesno
27CG30048FBgn0050048PKD1nono
28CG15040FBgn0030940---nono
29SP2353FBgn0034070EGFLAMnono
30MfFBgn0038294---nono
31omeFBgn0259175manynono
32esnFBgn0263934PRICKLE1-3nono
33hafFBgn0261509manynono
34dallyFBgn0263930GPC3/5yesno
35robo2FBgn0002543ROBO1/2/3/4nono
36Gyc32EFBgn0010197NPR1/2yesno
37CG8170FBgn0033365manynono
38CG8405FBgn0034071TMEM259noyes
39scafFBgn0033033---yesno
40borrFBgn0032105CDCA8yesno
41Syx7FBgn0267849STX7/12yesno
42DIP-deltaFBgn0085420manyyesno
43cv-cFBgn0285955DLC1yesno
44Snmp2FBgn0035815CD36/SCARB1nono
45MerFBgn0086384NF2yesno
46sbaFBgn0016754---nono
47HsromegaFBgn0001234---noyes
48CCAP-RFBgn0039396NPSR1yesno
49Hrd3FBgn0028475SEL1Lnoyes
50blueFBgn0283709NEURL4noyes
51CG6262FBgn0034121TREHnono
52CG45186FBgn0266696SVILnono
53SpnFBgn0010905PPP1R9Ayesno
54dncFBgn0000479PDE4A/B/C/Dnono
55CG4374FBgn0039078manynono
56sffFBgn0036544manynoyes
57CG42383FBgn0259729NSFL1Cnoyes
58DybFBgn0033739DTNByesno
59CG34371FBgn0085400---nono
60CG4341FBgn0028481TMTC2noyes
61CG30043FBgn0050043ERMP1noyes

Gene ontology (GO) enrichment analysis of the 61 candidate genes did not identify enrichment in any biological process or molecular function. However, GO enrichment was identified for the cellular component categories ‘cell periphery’ (GO:0071944; 19/61; q < 0.0016) and ‘plasma membrane’ (GO:0005886; 17/61; q < 0.004). At least 12/61 candidate genes are involved in protein homeostasis: three are involved in ERAD (CG8405, CG42383, and Hrd3), six are ER resident or membrane proteins (CG33012, CG30043, CG31690, CG4341, Hrd3, and CG8405), four are involved in ubiquitination or the proteasome (hiw, blue, CG42383, and Hrd3), one regulates heatshock responses (Hsromega), and one regulates N-linked glycosylation (sff).

Three of the identified ERAD genes already have known interactions with NGLY1. CG8405 is the Drosophila ortholog of human TMEM259, which physically interacts with NGLY1 in co-immunoprecipitation experiments (Zhu et al., 2017). CG42383 is the Drosophila ortholog of human NSFL1C (cofactor p47). NSFL1C and NGLY1 interact with the VCP/P97 AAA-ATPase complex involved in delivering misfolded proteins from the ERAD complex to the proteasome for degradation (Kondo et al., 1997; McNeill et al., 2004). Hrd3 is the Drosophila ortholog of SEL1L. SEL1L is a component of the ERAD complex required for retrotranslocation of misfolded proteins from the ER to the cytoplasm for degradation. Recently, the C. elegans orthologs of NGLY1 and SEL1L were both identified as modifiers of NRF1 function (Lehrbach and Ruvkun, 2016). These candidate genes are a proof-of-principle that this screen has identified functionally relevant modifiers.

The four candidate genes that encode ER resident proteins are particularly interesting. CG31690 and CG4341 are both Drosophila orthologs of human TMTC2, an ER transmembrane protein that regulates calcium homeostasis. CG33012 and CG30043 are both Drosophila orthologs of human ERMP1, an ER metalloprotease. It is striking that in both cases, both Drosophila orthologs of a single human gene were identified as candidate modifiers, suggesting that the function of TMTC2 and ERMP1 might be particularly important for NGLY1 lethality. It is not clear how these genes might modify NGLY1 lethality, but their physical localization to the ER makes sense and suggests a possible role in protein homeostasis as well.

Gene set enrichment analysis

The rank-order candidate modifiers identified in our GWA ignores the majority of the association data by only considering one variant at a time, rather than all the variants associated with a particular gene. Therefore, we performed a gene set enrichment analysis (GSEA), which assigns each variant to the closest gene and generates a per gene metric for p-value enrichment (Palu et al., 2019; Subramanian et al., 2005). Given a defined set of genes annotated with a certain GO function, GSEA determines whether the members of that set are randomly distributed throughout the ranked list or if they are found primarily at the top or bottom of that list. We identified 21 gene sets positively associated with the ranked gene list (≥5 genes;>0.25 enrichment score; p<0.05) (Figure 2; Supplementary file 4). These data suggest that these GO categories are closely linked to NGLY1 activity and variation in individual genes in these categories contribute to the distribution of lethality observed in our screen.

Figure 2 with 1 supplement see all
Gene set enrichment analysis.

Top significant ontological categories identified by GSEA. p-values are indicated by red-to-blue gradient, with red the lowest p-values and blue the highest p-values. Gene number identified in each category is indicated by the size of the circle.

Some of the most significantly enriched categories such as nuclear transport, rRNA processing and signal transduction are broad categories that could have wide reaching implications for NGLY1 function. These processes, however, are difficult to test and require long-term investigation, beyond the scope of this study. Circadian rhythm, on the other hand, is a specific and testable category. The enriched category for circadian rhythm function contains a number of genes that directly modulate circadian rhythm, including, clock, period, timeless, and cycle. We hypothesized that if variation in circadian rhythm function modifies lethality associated with loss of NGLY1 function then NGLY1 must affect the circadian rhythm. To test this, we knocked down NGLY1 in the LNv pacemaker neurons in the central nervous system using the Pdf-GAL4 driver (Renn et al., 1999) and assayed rhythmicity of locomotor activity in constant darkness over 8 days in Drosophila Activity Monitors (DAM). Compared to Pdf-GAL4/+ and UAS-NGLY1RNAi controls, flies with NGLY1 KD exhibited a significantly longer period length (Figure 2—figure supplement 1), supporting the idea that NGLY1 function can affect sleep. Indeed it has been reported that patients with NGLY1 deficiency experience disturbed sleep patterns (Enns et al., 2014; Lam et al., 2017).

Evolutionary rate covariation

Many of the GWA and GSEA results are intriguing, but appear far removed from the currently known functions of NGLY1. We hypothesized that we could contextualize some of the gene and network results by discovering which of them might be co-evolving with NGLY1. Therefore, we employed evolutionary rate covariation (ERC) analysis (Wolfe and Clark, 2015). Gene pairs with high ERC values have correlated rates of substitution and are thought to function together in protein complexes or related pathways. ERC analysis identified hundreds of protein-coding genes with integrated ERC scores exceeding two with NGLY1 (column ‘sumnlogpvbest’ in Supplementary file 5). Of the 38 GWA candidates that have human orthologs, two were found in this group with elevated NGLY1 ERC values, CG4374 (many) and esn (PRICKLE1). While this overlap is not enriched above background, co-evolution suggests that these two genes might have a particularly important interaction with NGLY1.

GO analysis was used to determine if there was enrichment in any biological pathways among NGLY1 co-evolving genes. Among the top enriched pathways were ‘rRNA/ncRNA/ribosome biogenesis/metabolism-related functions’ and ‘functions related to nuclear pore complex’. This is particularly exciting as both processes overlap with the top GO enrichment categories observed in the GSEA analysis, suggesting that the same functional categories that contribute to variation in NGLY1-related lethality also appear to contain genes that co-evolve with NGLY1. The rRNA processing category (GO:0006364) contained six genes overlapping between the two analyses. This overlap is higher than expected, given two equally sized random groups of genes (GSEA: 23 genes; ERC: 37 genes; p<2.6×10−12). Among other ncRNA-related enriched GO categories from the ERC analysis are ncRNA metabolic process (GO:0034660), ncRNA processing (GO:0034470), tRNA metabolic process (GO:0006399), ribosome biogenesis (GO:0042254), and tRNA modification (GO:0006400). The functions related to the nuclear pore included nuclear export (GO:0051168), nuclear pore organization (GO:0006999), nuclear transport (GO:0051169), and nuclear pore complex assembly (GO:0051292). While there was no overlap between ERC and GSEA for exact nuclear pore function categories, GSEA results were enriched for functions related to nuclear import (GO:0042306 and GO:0006606). Together, these observations suggest previously unknown roles for NGLY1 in ncRNA and nuclear pore functions.

NGLY1 deficiency is part of a larger category of disorders known as Congenital Disorders of Glycosylation (CDG), with NGLY1 being the only protein that actually deglycosylates substrates. There are 151 known CDG genes. GO analysis of the ERC results identified enrichment of the GPI anchor biosynthetic process, which contains several of these CDG genes, leading us to believe that other CDG genes may have been ERC hits. However, the 151 CDG genes do not fall into one functional GO category, therefore, we manually curated the ERC list and identified 26 CDG genes that co-evolve with NGLY1 (see color coding in Supplementary file 5). This represents a significant overlap above what is expected by chance (p<7.6×10−10). In particular, 5 of the 21 genes involved in N-linked glycosylation and 9 of the 29 genes involved in GPI-anchor biogenesis are co-evolving with NGLY1. The remaining 10 genes are spread across the CDG functional spectrum. The identification of a number of CDG genes that co-evolve with NGLY1, suggests that NGLY1 function might be important to the broader glycosylation pathways.

Genetic interaction between NGLY1 and Ncc69 in Drosophila

While these genetic analyses revealed many promising modifying and co-evolving genes which should be investigated, we began by investigating Ncc69 because it was the top hit with a human ortholog in our GWA analysis. Further, Ncc69 is a glycoprotein, making it a potential target of NGLY1 deglycosylation. Ncc69 has two mammalian orthologs, NKCC1 and NKCC2. While Ncc69 is ubiquitously expressed in Drosophila, NKCC1 (gene: SLC12A2) is highly expressed in secretory epithelia and NKCC2 (gene: SLC12A1) is primarily expressed in the kidney (Delpire and Gagnon, 2018). In all cases, the protein is a 12-pass transmembrane cation-chloride co-transporter that brings Na+, K+, and Cl- into the cell (Delpire and Gagnon, 2018). Mutations in NKCC2 are known to cause type I Bartter syndrome (Simon and Lifton, 1996) and a recent clinical report shows homozygous loss-of-function mutations in NKCC1 cause the novel disease Kilquist syndrome (Macnamara et al., 2019).

To validate the genetic interaction observed between NGLY1 and Ncc69 in the GWA, we generated ubiquitous double knockdown (DKD) Drosophila and scored offspring that survived to eclosion (Figure 3A). The fraction of KD flies was calculated from observed offspring of the balancer phenotype. NGLY1 KD caused a decrease in survival to ~25%, in accordance with our previous report of this RNAi line (Owings et al., 2018). Ncc69 KD did not cause any significant decrease in survival (χ2=1.002, p=0.3168), as previously reported (Leiserson et al., 2011). The DKD, however, caused complete lethality. This synthetic lethality confirms Ncc69 as a hit from the NGLY1 modifier screen.

NGLY1 and Ncc69 interact genetically in Drosophila.

(A) Proportion of flies surviving to eclosion in ubiquitous knockdowns. NGLY1 knockdown (KD) are UAS-PnglRNAi/+; Tubulin-GAL4/+. Ncc69 KD are UAS-Ncc69RNAi/+; Tubulin-GAL4/+. NGLY1 Ncc69 double knockdown (DKD) are UAS-PnglRNAi/+ UAS-Ncc69RNAi/Tubulin-GAL4/+. Four separate matings were performed for each cross with at least 40 offspring generated for the balancer control for each. Fraction surviving is calculated compared to balancer offspring. Chi-square analysis was performed for the total number of flies compared to expected Mendelian numbers. NGLY1 KD χ2 = 109.7, p<0.0001; Ncc69 KD χ2 = 1.002, p=0.3168, and NGLY1 Ncc69 DKD χ2 = 186, p<0.0001. (B) Bang sensitivity assay to assess seizures in glial knockdown flies. WT flies are attP2 and attP40. NGLY1 KD are UAS-PnglRNAi/+; repo-GAL4/+. Ncc69 KD are UAS-Ncc69RNAi/+; repo-GAL4/+. NGLY1 Ncc69 DKD are UAS-PnglRNAi/+; UAS-Ncc69RNAi/ repo-GAL4. For each genotype, at least 45 4- to 7-day-old females were used to calculate the percent seizing at a given time after vortexing. Repeated measures ANOVA p-value=0.000176.

KD of cation-chloride cotransporters in glia has been shown previously to cause seizures in Drosophila (Rusan et al., 2014), and we wanted to test whether this phenotype could be modified by NGLY1 KD. We performed single and double knockdowns of NGLY1 and Ncc69 in glial cells using the repo-GAL4 driver. This Ncc69 RNAi line is the same as the one described above. Drosophila were assessed for seizure phenotype using the bang sensitivity assay (Figure 3B). Control, wild-type flies show immediate recovery, as expected. In NGLY1 KD flies, ~30% showed severe seizures in the form of complete immobility 5 s following vortex. However, by 10 s following vortex, NGLY1 KD flies were completely recovered. This is the first report of seizure phenotype in any NGLY1 deficiency model, mimicking what is observed in patients. Ncc69 KD flies showed severe seizures with 75% seizing at 5 s following vortex, in line with previous reports (Rusan et al., 2014). In the DKD, there was a partial rescue of the severe Ncc69 phenotype. At all time-points between 5 and 60 s, the DKD flies showed an intermediate phenotype relative to NGLY1 and Ncc69 single KDs, confirming a genetic interaction between NGLY1 and Ncc69.

Functional analysis of NKCC1 in NGLY1 null MEFs

To understand the cell biology behind the genetic interaction that was observed in Drosophila, we utilized NGLY1 knockout (-/-) mouse embryonic fibroblasts (MEFs) (jax.org/strain/027060). Fibroblasts should only express the ubiquitous ortholog, NKCC1 (Haas and Forbush, 1998). When the membrane fraction of NGLY1 -/- MEFs was analyzed by immunoblot for NKCC1 there was a noticeable shift in the average molecular weight of the band compared to wildtype, control cells (+/+) (Figure 4A). Using the molecular weight marker to calculate the size of the proteins (un-cropped blot in Figure 4—figure supplement 1), the upper limits of the bands were ~170 kDa for both +/+ and -/- cells (Figure 4B). The lower limit of the bands, however, were ~140 kDa for +/+ cells and ~150 kDa for the -/- cells (Figure 4C).

Figure 4 with 1 supplement see all
Endogenous NKCC1 is altered in NGLY1-deficient MEFs.

(A) Control (+/+) and NGLY1 null (-/-) MEFs were grown to confluency and then lysed to isolate the membrane and cytoplasmic fractions. Three separate membrane lysates for both genotypes were analyzed by immunoblotting for NKCC1 compared to a molecular weight marker (MWM). Blot was used for molecular weight calculations of the upper-most limit (see un-cropped blot in Figure 4—figure supplement 1) (B) And the lower-most limit (C) of the protein band. Red bar represents the mean. Two-tailed t-test was used to calculate p-values. (D) Membrane lysates from MEFs were treated with N-Glycosidase F (PNGase F), O-Glycosidase (O-Gly), or Endoglycosidase H (Endo H) for 1 hr then analyzed by immunoblot. Control (C)Samples were treated in all the same conditions but without the added enzyme. (E) MEFs were treated with 500 nM bortezomib (Bz) or equal volume of vehicle control (DMSO) for 4 hr then lysed to collect membrane and cytoplasmic fractions. Lysates were analyzed by immunoblotting for NKCC1. NRF1 was analyzed as a positive control of proteasome inhibition. Dark band at about 140 kDa in both (A), (D), and (E) is believed to be non-specific.

To determine if a glycosylation event might be responsible for this size difference, cell lysates were treated with deglycosylating enzymes (Figure 4D). PNGase F removes all N-linked glycans and this treatment caused a large decrease in the molecular weight, to ~125 kDa in NKCC1 proteins from both NGLY1 +/+ and -/- cells. The expected weight of mouse NKCC1 without any post-translational modifications is 130 kDa indicating that all post-translational modifications are likely N-linked glycans. This is in accordance with the prediction of two canonical N-linked glycosylation sites (Payne et al., 1995). The fact that there is no difference in molecular weight between the +/+ and -/- after treatment indicates the difference observed in the untreated state was eliminated by the PNGase enzyme. Treatment with O-Glycosidase had no effect on the molecular weight of the band in either the +/+ or -/- lysates. Although O-Glycosidase does not cleave every type of O-linked glycan, these results coupled with the PNGase results indicate there are likely no O-linked glycans on NKCC1. Finally, to determine the maturation state of the N-linked glycans Endoglycosidase H was used. No change in molecular weight was seen, indicating the N-linked glycans are no longer in the high-mannose state in both the +/+ and -/- cells.

The most well-studied substrate of NGLY1, NRF1, is degraded by the proteasome under normal conditions, and only when the proteasome is stressed or inhibited does NRF1 become active. Indeed, NGLY1 is thought to act in the ERAD pathway and therefore all its substrates may be regulated in some way by proteasomal degradation. To test if NKCC1 abundance is affected by the proteasome, MEFs were treated with the proteasome inhibitor bortezomib (Bz). As expected, there was an increase in NRF1 abundance during proteasome inhibition (Figure 4E). However, there was no noticeable increase in NKCC1 protein for either the +/+ or -/- MEFs, indicating proteasomal degradation is not a major regulator of NKCC1.

Given the altered glycosylation state of NKCC1 observed in NGLY1 -/- MEFs, we wanted to determine the functionality of NKCC1 in these cells. Previous reports have shown that inhibiting N-linked glycosylation can decrease functionality for both NKCC1 (Singh et al., 2015) and for NKCC2 (Paredes et al., 2006), and therefore, we hypothesized that the misglycosylation might also decrease function. The NKCC proteins and the Na+/K+-ATPase can both transport Rb+ in place of K+, so we incubated cells with radioactive 86Rb and measured cellular uptake. Cells were assayed in the presence or absence of 10 μM bumetanide, an NKCC inhibitor, or 100 μM ouabain, a Na+/K+-ATPase inhibitor, as compared to vehicle control. When the ouabain-sensitive and bumetanide-sensitive activities were summed, they accounted for all of the 86Rb flux observed (Figure 5—figure supplement 1). We found that bumetanide-sensitive 86Rb flux, but not ouabain-sensitive flux, was impaired by ~50% in the -/- MEFs, indicating a specific defect in NKCC1 activity without impairment in the Na+/K+-ATPase (Figure 5). We assayed ion transport activity under three conditions of isotonic, hypertonic, or hypotonic baths. Although both hypertonic and hypotonic low chloride baths can stimulate NKCC1 activity in other cell types (Darman and Forbush, 2002), we did not see any effect of bathing medium in the MEFs, consistent with a recent report of lack of hypertonic stimulation of NKCC1 in human fibroblasts (Delpire et al., 2016). Together, these data demonstrate that loss of NGLY1 results in a change in the glycosylation state of NKCC1 and a significant reduction in NKCC1 function.

Figure 5 with 1 supplement see all
NGLY1 -/- MEFs show decreased NKCC1-specific ion flux.

(A) Bumetanide-sensitive 86Rb flux was measured in NGLY1 +/+ and NGLY1 -/- MEFs to measure NKCC1 activity. Flux was examined in three bath conditions, isotonic (iso), hypotonic (hypo), and hypertonic (hyper). There was a significant effect of genotype (p<0.0001) in two-way ANOVA, with no significant effect of condition (p=0.5756) or interaction (p=0.8075). Adjusted p-values for Sidak’s multiple comparisons test between NGLY1 +/+ and NGLY1 -/- are shown in the figure. (B) Ouabain-sensitive 86Rb flux was measured in NGLY1 +/+ and NGLY1 -/- MEFs to measure Na+/K+-ATPase activity in the same three conditions as in A. There were no significant effects of genotype (p=0.0516), condition (p=0.3047) or interaction (p=0.4711) by two-way ANOVA, indicating the NGLY1 knockout has a specific effect on NKCC1 activity without affecting Na+/K+-ATPase activity.

Discussion

Like many rare diseases, research into the pathogenesis of NGLY1 deficiency has been narrowly focused, based on early hypotheses. This often limits how we understand the connection between a particular disease and other pathways. For NGLY1 deficiency specifically, basic research and potential therapies have focused intensely on NRF1, the first well-established substrate of NGLY1 deglycosylation. Motivated by the extensive phenotypic variation among NGLY1 deficiency patients, we took advantage of natural genetic variation in Drosophila to identify modifiers of NGLY1 deficiency. This unique screen demonstrated that (1) we can model the extensive phenotypic variation observed and (2) that genetic variation can cause this phenotypic variability. Association analysis then identified a number of exciting candidate modifier genes. Here, we have validated the novel and conserved modifier NKCC1 (Drosophila Ncc69), a new potential therapeutic target for NGLY1 deficiency.

A major advantage of screens is the identification of previously unanticipated biological connections. First, our association analysis of the lethality screen has generated a list of 61 genes that we hope the scientific and patient communities will be able to use. Second, GSEA identified several pathways, including rRNA metabolism and nuclear transport that are surprising based on known NGLY1 functions. Third, ERC analysis identified genes that are coevolving with NGLY1 across the animal kingdom, including both rRNA/ncRNA pathways and nuclear transport. It appears that rRNA metabolism and nuclear transport are likely important to NGLY1 function, yet it remains unclear how NGLY1 is connected to these pathways. Components of the ribosome and the nuclear pore are often O-glycosylated. While there is no direct connection between NGLY1 and O-GlcNAcylation, we have previously demonstrated that loss of NGLY1 impacts UDP-GlcNAc levels (Owings et al., 2018). It is highly plausible that a misregulation of UDP-GlcNAc levels could affect O-GlcNAcylated proteins. More work is needed to determine exactly how NGLY1 is connected to these unexpected pathways. Finally, the ERC analysis also identified 26/151 known Congenital Disorders of Glycosylation (CDG) genes. While NGLY1 is also classified as a CDG, it is unclear why there might be co-evolution with other CDG genes. Perhaps, there is a feedback mechanism, again, related to UDP-GlcNAc biosynthesis that connects these genes. These results suggest that there is a previously unknown connection between these loosely connected CDG genes.

When analyzing the list of modifier genes, it is apparent that many of the candidates are involved in ERAD. This offers a proof-of-principle that this screen is well suited for identifying bona fide biologically relevant modifiers. Several previous studies linked NGLY1 with the ERAD process (Bebök et al., 1998; Katiyar et al., 2005; Park et al., 2001). Yet, NGLY1 does not appear to be required for proper ERAD function (Hirsch et al., 2003; Misaghi et al., 2004). While perturbations to ERAD often result in ER stress, we have previously reported that there was no functional or transcriptome evidence for ER stress in a Drosophila model of NGLY1 deficiency (Owings et al., 2018). Others have reported no ER stress in NGLY1 -/- human cells, mice, and rats (Asahina et al., 2020; Mueller et al., 2020; Tambe et al., 2019). However, there is conflicting evidence for ER stress as it was recently reported that ER stress markers were upregulated in NGLY -/- MEFs (Galeone et al., 2020). Nevertheless, in our current screen, we did not identify any genes involved in canonical ER stress responses, suggesting that ER stress might not play a large role in the pathogenesis of the disease. Here, we have reported that NKCC1 is altered in NGLY1 -/- cells, however we found that inhibiting the proteasome had no effect on the protein abundance. Thus, it may be that NGLY1 functions to regulate proteins in various ways that are closely related to ERAD, but that do not result in direct proteasomal degradation, and thereby, do not cause an accumulation of misfolded protein and ER stress.

As with most hypothesis-free approaches, our analyses produced many exciting new avenues for exploration. In order to keep our work relevant and translatable to the clinic, we have focused our follow up experiments on genes with human orthologs. In this report we began with our top hit, Ncc69 (human NKCC1/2), which encodes an SLC12 Na+/K+/2Cl- transporter. In cells derived from an NGLY1 -/- mouse model, we found that NKCC1 protein migrated at a higher average molecular weight relative to +/+ cells. We found this altered glycosylation was accompanied by a ~ 50% reduction in NKCC1 activity.

NKCC1 contains two canonical N-linked glycosylation sites (Payne et al., 1995) similar to those validated in NKCC2 (Paredes et al., 2006). As expected, both sites are in an extracellular loop, and therefore, these sites face the lumen of the ER during protein translation and maturation. Because of this arrangement, these two sites are not predicted to be accessible by NGLY1, which is localized to the cytoplasm. However, recent work indicates that NGLY1 can deglycosylate proteins prior to their complete retrotranslocation out of the ER (Galeone et al., 2020). NGLY1 is recruited to the cytosolic surface of the ER where it deglycosylates BMP4, which is in fact necessary for its retrotranslocation to the cytoplasm. Perhaps NKCC1 is being deglycosylated on one of its two canonical N-linked glycosylation sites through a similar mechanism. Alternatively, it may be that NGLY1 is acting on a non-canonical, cytoplasmic N-linked glycosylation site. Sequence analysis reveals three other asparagine residue within the necessary N-X-S/T sequence for N-linked glycosylation, however, two are predicted to be in transmembrane domains; the third (human NKCC1 residue N168) is located in the amino-terminal cytoplasmic tail of the protein. The recent Cryo-EM structure determined that the amino-terminal tail is disordered and that the carboxy-terminal tail acts as a regulatory domain (Chew et al., 2019). Although rare, there have been reports of cytosolic N-linked glycosylation, including on the dog kidney Na+, K+-ATPase pump (reviewed in Hart et al., 2017). In all these cases, and in our case here, the mechanism for cytoplasmic glycosylation remains unknown. Determining if one of the two canonical sites is altered or if a non-canonical, cytoplasmic site is altered is a top priority for future work.

While we observe a glycosylation difference on NKCC1, and NGLY1 is a deglycosylating enzyme, we cannot eliminate the possibility that this NKCC1 regulation is a secondary effect. NGLY1 may be regulating an intermediary protein that in turn, regulates NKCC1. This was recently found to be the case for aquaporins in NGLY1-deficient cells (Tambe et al., 2019). NGLY1 was found to regulate the abundance of transcription factors Atf1/Creb1 independent of its enzymatic activity. Atf1/Creb1 then, in turn, regulates the transcription of several aquaporin subunits. Given that we show the abundance of NKCC1 does not change, but rather NKCC1 has a molecular weight shift, it is likely that the altered state is due to some difference in a post-translational modification. If this effect is secondary, it may be that NGLY1 is directly affecting Golgi-localized glycosyltransferases that in turn modify the already present glycans. Or that NGLY1 is altering the function of a sialyltransferase, thereby altering sialic acid residues on NKCC1 which are known to cause significant changes in migration on SDS-PAGE. This hypothesis is supported by the fact that Endo H treatment did not affect NKCC1 from either +/+ or -/- cells, indicating that NKCC1 has been fully processed through the Golgi. Future work to test this hypothesis could entail mass spectrometry analysis to determine the specific glycan structures on NKCC1.

Identification of targets and modifier genes should provide insight into the pathogenesis of a disease and help explain some of the patient phenotypes. When NRF1 was identified as the first target of NGLY1, it provided insight into some of the molecular defects observed in NGLY1-deficient cells, including deficits in proteasomal function and expression. These cellular phenotypes, however, did not translate well into insight into the complex patient symptoms. In contrast, decreased NKCC1 activity may explain some of the prominent features of NGLY1 deficiency. NKCC1 functions in many secretory epithelia, such as the salivary, sweat, and lacrimal glands, to allow basolateral ion uptake and subsequent secretion (Delpire and Gagnon, 2018). Therefore, a decrease in NKCC1 activity could well explain the alacrima and reduced saliva and sweat production seen in NGLY1 deficiency. Strikingly, a recent clinical report describes a patient with a homozygous deletion in NKCC1 (null) who has many overlapping features with NGLY1 deficiency patients, including absence of saliva, tears, and sweat (Kilquist syndrome) (Macnamara et al., 2019). The NKCC1 null mouse also displays defects in salivation (Evans et al., 2000). Other notable, but perhaps less specific, features in the NKCC1-deficient child, including developmental delay and gastrointestinal problems, also overlap with those observed in NGLY1 deficiency. The NKCC1-deficient patient also had severe hearing loss, cochlear defects, and abnormal auditory brainstem responses (ABRs). Several patients with missense mutations in NKCC1, rather than complete loss-of-function mutations, display bilateral sensorineural hearing loss (McNeill et al., 2020). NGLY1 deficiency patients do not have severe hearing loss, but do report abnormal ABRs. This difference may be explained by a 50% reduction in NKCC1 activity, rather than complete loss of activity. The overlap in a majority of the symptoms between this new syndrome and NGLY1 deficiency strengthens the case for both a genetic and functional connection between NGLY1 and NKCC1.

NKCC1 may be a promising target for the development of NGLY1 deficiency therapies. Given that it is a transporter and partially exposed to the extracellular space, NKCC1 could be particularly amenable to modulation by small molecules. Based on our work reported here, we predict that increasing function of NKCC1 may ameliorate some symptoms. Quercetin, a flavonoid, is a readily available molecule that has been shown to enhance NKCC1 activity (Asano et al., 2009; Nakajima et al., 2011). These studies demonstrated that quercetin significantly increased 86Rb uptake in cell culture and that this increase was bumetanide-sensitive, indicating specificity to NKCC1. This is similar to other studies showing flavonoids increasing the activity of channels, such as the flavonoid genistein increasing activity of the cystic fibrosis transmembrane conductance regulator (CFTR) (Sugawara and Nikaido, 2014), and several flavonoids targeting cardiovascular channels (Scholz et al., 2010). These quercetin studies, however, are in the context of normal functioning NKCC1 protein. In our study, NKCC1 is altered from the WT state and it is unknown whether quercetin would be able to modulate the activity of an altered NKCC1. Strikingly, however, quercetin was recently discovered in a drug screen to provide benefit to NGLY1-deficient C. elegans (Iyer et al., 2019). These results coupled with our discovery of NKCC1 as a NGLY1 substrate offer an exciting new avenue of treatment for NGLY1 deficiency patients. Targeted studies are needed to determine if quercetin or other molecules could specifically enhance NKCC1 function in the context of NGLY1 deficiency.

In this study, we took a series of unbiased approaches in Drosophila to identify modifiers of NGLY1 deficiency. This resulted in a number of new insights into the potential pathogenesis of NGLY1 that we hope others will also investigate. With rare diseases like NGLY1 deficiency, unbiased and forward genetic approaches are an efficient method for expanding possible avenues of investigation and therapeutic development. This study also highlights the power of using model organisms like Drosophila to uncover pathways and genes that can be validated in mammalian systems and targeted for therapeutic development.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or
reference
IdentifiersAdditional
information
Gene (Drosophila melanogaster)PnglGenBankID:35527
Dmel_CG7865
Gene (Drosophila melanogaster)Ncc69GenBankID: 39410
Dmel_CG4357
Gene (Mus musculus)NGLY1GenBankID: 59007
Gene (Mus musculus)NKCC1GenBankID: 20496Slc12a2
Genetic reagent (Drosophila melanogaster)Pngl-RNAiBloomington Drosophila Stock CenterRRID:BDSC_54853y1 v1; P{y+t7.7 v+t1.8=TRiP.HMJ21590}attP40
Genetic reagent (Drosophila melanogaster)Tubulin-GAL4Bloomington Drosophila Stock CenterRRID:BDSC_5138y1 w*;
P{w+mC = tubP-GAL4}LL7/TM3, Sb1 Ser1
Genetic reagent (Drosophila melanogaster)Tubulin-GAL80Bloomington Drosophila Stock CenterRRID:BDSC_5190y1 w[*]; P{w[+mC]=tubP-GAL80}LL9 P{w[+mW.hs]=FRT(w[hs])}2A/TM3, Sb1
Genetic reagent (Drosophila melanogaster)Drosophila Genetics Reference PanelBloomington Drosophila Stock CenterSet of 194 strains, example strain: BDSC:55014, RRID:BDSC_55014
Genetic reagent (Drosophila melanogaster)Pdf-GAL4Bloomington Drosophila Stock CenterRRID:BDSC_6899P{w[+mC]=Pdf-GAL4.P2.4}X, y1 w[*]
Genetic reagent (Drosophila melanogaster)UAS-Pngl-RNAiBloomington Drosophila Stock CenterRRID:BDSC_42592y1 sc* v1 sev21; P{y+t7.7 v+t1.8=TRiP.HMS02424}attP40
Genetic reagent (Drosophila melanogaster)UAS-Ncc69-RNAiBloomington Drosophila Stock CenterRRID:BDSC_28682y1 v1; P{y+t7.7 v+t1.8=TRiP.JF03097}attP2
Cell line (Mus musculus)Mouse embryonic fibroblasts (MEF)Jackson LabsPrimary line from mouse #027060,https://www.jax.org/strain/027060
AntibodyAnti-NKCC1 (Rabbit polyclonal)Cell SignalingCat#14581, RRID:AB_2798524IB: 1:1000
AntibodyAnti-TCF11/NRF1 (Rabbit monoclonal)Cell SignalingCat#8052, RRID:AB_11178947IB: 1:1000
AntibodyIRDye 800CW Goat-anti-rabbitAbcamCat#216773IB: 1:10,000
Commercial assay or kitCell Fractionation KitCell SignalingCat#9038
Chemical compound, drugBortezomibEMD MilliporeCat# 179324-69-7
Software, algorithmGenome Wide AssociationChow et al., 2016
Software, algorithmGene Set Enrichment AnalysisSubramanian et al., 2005
Software,
algorithm
Evolution Rate CovariationClark et al., 2012
Software, algorithmRhttps://www.r-project.org/

Drosophila lines

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Flies were maintained at 25°C on a 12 hr light/dark cycle and raised on a standard diet based on the Bloomington Stock Center standard medium with malt. All flies were aged 3–5 days old for experiments. For the DGRP screen, the following D. melanogaster stocks were used: PnglRNAi (Bloomington Drosophila Stock Center: 54853) and Tubulin-GAL4 driver (5138). The Tubulin-GAL80 strain was provided by Dr. Carl Thummel (University of Utah). The DGRP strains are available at the Bloomington Drosophila Stock Center. To measure circadian rhythm, the following stocks were used: a w- Berlin control strain, a w; Pdf-GAL4 strain (outcrossed to w- Berlin), and a yv; UAS-PnglRNAi strain (Bloomington stock center #42592). For bang sensitivity assays, the following stocks were used: UAS-PnglRNAi (BL #54853), UAS-Ncc69RNAi (BL #28682), and repo-GAL4. These stocks were obtained from the Bloomington Stock Center and Adrian Rothenfluh (University of Utah) respectively.

DGRP screen

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Virgin females from the DGRP strains were fed yeast overnight and then crossed with males from the donor strain UAS-PnglRNAi/Cyo,Tubulin-GAL80; Tubulin-GAL4/TM3,Sb in two replicate bottles. Progeny were collected and scored for the four balancer classes: CyO, Sb, double balanced, or no balancers, with the no balancer flies being the NGLY1 KD. This cross should produce the expected 1:1:1:1 ratio of the four genotypes. Given that there is always a very low level of lethality associated with each balancer, the largest balancer class was considered the closest to the expected number. We scored at least 200 flies per DGRP cross. Males and females were combined for a single count. To calculate the proportion of NGLY1 KD flies by generating a ratio of NGLY1 knockdown/largest balancer class. This metric was used for the GWA.

Genome wide association

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GWA was performed as previously described (Chow et al., 2016). DGRP genotypes were downloaded from the website, http://dgrp.gnets.ncsu.edu/. Variants were filtered for minor allele frequency (≥0.05), and non-biallelic sites were removed. A total of 2,007,145 variants were included in the analysis. The proportion of NGLY1 KD flies surviving was regressed on each SNP. To account for cryptic relatedness (He et al., 2014; Huang et al., 2014), GEMMA (v. 0.94) (Zhou and Stephens, 2012) was used to both estimate a centered genetic relatedness matrix and perform association tests using the following linear mixed model (LMM):

y=α+xβ+u+ϵuMVNn(0,λτ(1)K)εMVNn(0,τ(1)In)

where, as described and adapted from Zhou and Stephens, 2012, y is the n-vector of proportion lethality for the n lines, α is the intercept, x is the n-vector of marker genotypes, β is the effect size of the marker. u is a n x n matrix of random effects with a multivariate normal distribution (MVN_n) that depends on λ, the ratio between the two variance components, τ^(−1), the variance of residuals errors, and where the covariance matrix is informed by K, the calculated n x n marker-based relatedness matrix. K accounts for all pairwise non-random sharing of genetic material among lines. ϵ, is a n-vector of residual errors, with a multivariate normal distribution that depends on τ^(−1) and I_n, the identity matrix. Genes were identified from SNP coordinates using the BDGP R54/dm3 genome build. An SNP was assigned to a gene if it was +/- 1 kb from a gene body.

Gene set enrichment analysis

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GSEA was run to generate a rank-list of genes based on their enrichment for significantly associated polymorphisms as previously described (Palu et al., 2019). Polymorphisms within 1 kb of more than one gene were assigned to one gene based on a priority list of exon, UTR, intron, and upstream or downstream. Genes were assigned to GO categories, and calculation of enrichment score was performed as described (Subramanian et al., 2005). Only gene sets with ≥5 genes,>0.25 enrichment score, and a p<0.05 were considered.

Evolutionary rate covariation

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ERC is a method to examine the similarity of evolutionary histories of pairs of genes (Clark et al., 2012). The method examines the variation over time of a gene’s rate of sequence evolution. Using estimates of evolutionary rate over the branches of a gene’s phylogenetic tree, the method measures the correlation between genes of these branch-specific rates. Genes within correlated rate variation tend to be functionally related and have been used to discover new genes within pathways and diseases (Brunette et al., 2019; Priedigkeit et al., 2015; Raza et al., 2019).

ERC values in this study were taken from a compilation of ERC correlations calculated separately for three taxonomic groups: 62 mammals, 39 non-mammalian vertebrates, and 22 Drosophila species. Mammal and non-mammalian vertebrate alignments were taken from the multiz alignment available from the UCSC Genome Browser (Haeussler et al., 2019). For each alignment, we filtered out low-quality orthologs containing fewer than 50 non-gap amino acid sites or less than 70% non-gap sites and removed alignments with fewer than 15 species. Alignments were made for the Drosophila species after downloading protein-coding genome sequences from FlyBase and NCBI. Orthologous groups were identified using Orthofinder and alignments made with PRANK (Emms and Kelly, 2015; Löytynoja and Goldman, 2008). For each amino acid alignment, we estimated branch lengths using aaml in the phylogenetic analysis using maximum likelihood (PAML) package (Yang, 2007). ERC values (correlation coefficients) for all genes with NGLY1 were calculated using the RERconverge package (Kowalczyk et al., 2019). We report the ERC results for the mammalian group as the negative log of their p-values for each gene pair (Supplementary file 5 ‘nlogpvbest1’). Each gene pair also incorporated results from the vertebrate and Drosophila datasets by summing their negative log p-values, when orthologs were present for their respective datasets (Supplementary file 5 ‘sumnlogpvbest’). The resulting taxonomically integrated results of ERC with NGLY1 were sorted and used for gene set enrichment analysis (GSEA).

Drosophila circadian rhythm assay

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Male flies with the following genotypes were used in circadian rhythm assays: w/Y;Pdf-GAL4/+, yv/Y; UAS-PnglRNAi/+, and yv/Y; Pdf-GAL4/UAS-PnglRNAi/+. Two- to 5-day-old flies were entrained for at least 3 days to a 12 hr light: 12 hr dark regimen (LD) within a Drosophila Activity Monitor (DAM; TriKinetics, Waltham, MA) filled with standard fly food. After entrainment, flies were monitored in complete darkness (DD) for 8 days. The data was collected in 30 min bins, and analyzed for period length using ClockLab, Version 6. Graphs were generated and one-way ANOVA performed, with Tukey’s multiple comparison of all three genotypes, using GraphPad Prism, Version 8.

Drosophila seizure assay

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The Bang Sensitivity Assay (BSA) was performed on the following genotypes: UAS-PnglRNAi; repo-GAL4, UAS-Ncc69RNAi; repo-GAL4, and UAS-PnglRNAi/+; UAS-Ncc69RNAi/repo-GAL4. Females 4–7 days old were assayed. Flies were not exposed to CO2 for 3 days prior to BSA testing. Flies were flipped into empty vials and allowed to rest for 2 hr. They were then vortexed on a Thermo Scientific LP Vortex Mixer for 10 s at maximum speed. The vortexed flies were filmed for 60 s. The video was used to score seizures at 5, 10, 30, and 60 s.

Mammalian cell culture and proteasome inhibition

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MEFs were generated by Jackson Laboratory (Bar Harbor, Maine) from NGLY1 knockout mice and littermate controls (C57BL/6J-Ngly1em4Lutzy/J, #027060). MEFs were immortalized in the laboratory of Dr. Hamed Jafar-Nejad (Baylor College of Medicine) and then gifted to us. MEFs were grown in DMEM (Gibco 11965) supplemented with 10% fetal bovine serum (FBS) and penicillin/streptomycin in 5% CO2 at 37°C. For proteasome inhibition, MEFs were incubated with 500 nM bortezomib (EMD Millipore) or an equivalent volume of DMSO as a vehicle control, for 4 hr under standard conditions.

Western blotting

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MEFs were grown to 80–90% confluency then collected. Cell pellets were weighed and then resuspended in a proportional volume of phosphate buffered saline (PBS). Equivalent volumes of resuspension were always used for each lysis. Cells were lysed using a cell fractionation kit (Cell Signaling Technologies, #9038) with each buffer supplemented with 1 mM PMSF and 1x protease inhibitor cocktail (Cell Signaling Technologies, #5871).

Lysates were separated by SDS-PAGE on 3–8% Tris-acetate gels (BioRad #3450129) for 2.5 hr at 150V, then transferred to PVDF membrane by wet transfer at 50V for 1 hr. Membranes were blocked in either 5% milk or 5% BSA according to the recommendations of the primary antibody manufacturer. Primary antibodies were as follows: anti-NKCC1 (Cell Signaling Technologies #14581), anti-TCF11/NRF1 (Cell Signaling Technologies #8052). Membranes were incubated in primary antibody at 1:1000 in blocking buffer overnight. IRDye secondary antibody (Abcam #216773) was used for infrared detection at 1:10,000 dilution in blocking buffer for 1 hr. Membranes were scanned on an Odyssey CLx (Li-cor) and analyzed with the accompanying software, Image Studio.

Deglycosylation reactions

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MEFs were lysed in the same manner as described for western blotting. The membrane fraction was then incubated with one of the three deglycosylation enzymes: O-Glycosidase (New England Biolabs, #P0733), PNGase F (New England Biolabs, #P0704), Endoglycosidase F (New England Biolabs, #P0702) according to the manufacturer’s directions. Reactions were incubated at 37°C for 1 hr. Controls were treated with all the same buffers and reaction conditions but without the added enzyme.

Rb+ flux assay

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20,000 cells/well of immortalized MEFs from control or Ngly1 -/- mice were seeded into a 96-well plate. The following day, media was removed and the cells were washed with 1x PBS. Of pre-incubation medium (in mM, 135 Na gluconate, 5 K gluconate, 1 Ca gluconate, 1 Mg gluconate, 15 HEPES pH 7.4, 5 glucose), 100 μl was added to each well and the cells were incubated for 30 min at 37°C. Next, 100 μl of pre-incubation medium containing either DMSO, bumetanide, or ouabain was added to each well to achieve final concentrations of 0.1% (DMSO), 10 μM (bumetanide), or 0.1 mM (ouabain) and incubated for 30 min at room temperature. Then, 150 μL of medium containing DMSO (0.1%), bumetanide (10 μM) or ouabain (0.1 mM), as well as 86Rb (10 mCi/μl), was added to each well. Three different media were used. Isotonic media contained (in mM): 140 NaCl, 5 KCl, 2 CaCl2, 1 MgCl2, 5 glucose, 15 HEPES pH 7.4. Hypertonic medium was the same as isotonic medium, with the addition of 75 mM sucrose. For hypotonic medium, isotonic medium was diluted 1:2 in water. The cells were incubated for 7 min at room temperature. Medium was removed and the cells were washed three times with ice-cold 1x PBS. Cells were lysed in 100 μl 2% SDS and incubated for 15 min at room temperature. Radioactivity was measured in a liquid scintillation counter.

Data availability

All data generated by this study are included in the manuscript and supporting files.

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Decision letter

  1. Hugo J Bellen
    Reviewing Editor; Baylor College of Medicine, United States
  2. Patricia J Wittkopp
    Senior Editor; University of Michigan, United States
  3. Michael Tiemeyer
    Reviewer; University of Georgia, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for choosing to send your work, "A Drosophila screen identifies NKCC1 as a substrate of NGLY1 deglycosylation and a modifier of NGLY1 deficiency", for consideration at eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous. Although the work is of interest, we regret to inform you that the findings at this stage are too preliminary for further consideration at eLife.

The reviewers are all positive about your screen and clearly appreciate your work. However they question the mechanism that you propose. I suggest that you carefully read their critiques. As you will notice they are all three experts in the glycosylation field and make some excellent suggestions. If you think you can address their concerns, please write a rebuttal letter and I will share it with the reviewers. We can then determine a mode of action.

Reviewer #1:

In manuscript Talsness and colleagues use Drosophila genetics combined with evolutionary rate covariation analysis and experiments in mouse embryonic fibroblasts (MEFs) to identify the ion transporter NKCC1 as a genetic modifier and potentially a direct target of NGLY1. The authors started by an elegant genetic screen to ask whether any of the natural variations found in 163 genetically heterogeneous fly strains from the DGRP collection can suppress the lethality associated with ubiquitous NGLY1 knock-down. The screen helped them identify a number of DGRP strains that can reduce the lethality of NGLY1-KD in a rather wide range, some to astonishingly high levels (up to ~97% survival). They next performed genome-wide association studies (GWAS) to identify variants in these strains that show statistically significant association with the survival of NLGY1-KD animals. This resulted in the identification of variants in or close to a number of genes, some of which are related to pathways like ERAD and proteasomal degradation to which NGLY1 has previously been linked. As proof of principle, they chose one category (circadian rhythm) and performed tissue-specific RNAi to show that indeed NGLY1-KD in brain pacemaker neurons results in altered circadian rhythm in flies. As a complementary approach to the above screen, the authors performed evolutionary rate covariation (ERC) analysis and identified several interesting GO categories that seem to co-evolve with NGLY1, suggesting potential functional links. Moreover, two of the top ranking GWAS candidates from the genetic screen were also found in the ERC analysis.

The authors then chose the top ranking GWAS candidate with a human homolog for functional studies. This gene is called Ncc69 in flies and encodes a glycoprotein homologous to mammalian cation-chloride co-transporters NKCC1 and NKCC2. Based on two sets of double-KD experiments, the authors concluded that Ncc69 genetically interacts with NGLY1 in flies. They then performed Western blots on NGLY1-mutant and control MEFs with or without glycosidase treatment or proteasome inhibitor treatment, and concluded based on the data that NKCC1 (the homolog expressed in MEFs) is a substrate for deglycosylation by NGLY1. Finally, they used the transport of radioactive rubidium as a functional readout for NKCC1 activity and provided evidence suggesting that the NKCC1 activity is reduced ~50% in NGLY1-mutant MEFs. Based on all these data, the authors concluded that deglycosylation of NKCC1 by NGLY1 is required for NKCC1's full activity. Finally, the authors discussed the potential new avenues that their work can open in the NGLY1 field, the possibility that some NGLY1 deficiency phenotypes like lack of tears are due to reduced NKCC1 function, and that this ion transporter might be a novel therapeutic target for this disease.

The genetic screen and the follow-up GWAS analysis reported in this manuscript provides a beautiful example of the broad and sometime extreme effects of genetic background on a developmental phenotype and the possibility of identifying novel potential modifiers of a disease gene phenotype in an unbiased manner by these techniques. This also seems to be the first report on the circadian rhythm abnormalities in an animal model of NGLY1 deficiency, with potential mechanistic link to the sleep abnormalities that are commonly seen in the affected patients. Moreover, the GWAS and ERC datasets presented in this work are likely to be help push the research in this field forward. Unfortunately, there are a number of issues with the experiments performed on Ncc69/NKCC1, which in my opinion cast doubt on the conclusions of the manuscript. This is in part due to lack of sufficient controls in some experiments.

Genetic interaction between NGLY1 and Ncc69 in flies

The authors have used a double KD strategy to examine the genetic interaction between NGLY1 and Ncc69. They state that NGLY1 KD with tubulin-Gal4 did not cause significant lethality (Figure 3A). Wasn't the same genotype used in the genetic screen and mentioned to show lethality, prompting the authors to use a tubulin-Gal80 in the background? The authors' previous work (Owings et al) also indicated only ~30% eclosion to adulthood in tubulin-Gal4 UAS-Ngly1-RNAi. The authors should address the reason for this discrepancy and repeat the genetic interaction studies in the same context as the original screen. Moreover, given the potential off target effects with RNAi, the genetic interaction should be confirmed by either rescue by an RNAi-resistant transgene of one of these genes (for example, the human homolog), or by using loss-of-function allele(s) (or at least by using additional independent RNAi strains for each gene). If I understood correctly, the authors have found Ncc69 SNPs in 9 of the DGRP strains which modified the NGLY1 KD lethality. How are these 9 strains distributed across the data shown in Figure 1B? Based on the statement ("that deletions encompassing these nine Ncc69 intronic SNPs result in a null allele") and in light of the genetic interaction suggested in Figure 3A, one would think that Ncc69-lines from DGRP would show a high degree of lethality when combined with NGLY1-KD. Do the authors find it surprising that so many SNPs in this gene were actually associated with survival to adulthood in NGLY1 KD animals? This might be caused by an increase in Ncc69 expression in those strains and should be tested. In fact, if what I have written above is correct, it would have been better to show that Ncc69 overexpression can rescue the lethality of NGLY1-KD animals.

The data in Figure 3B seems to be in the same direction as the results of the genetic screen. However, it has the same technical issues as 3A, in the sense that only one RNAi has been used for each gene and the degree of KD is not known. In this case, it will be more difficult to determine KD efficiency, so using independent RNAi lines and/or heterozygosity for NGLY1 in an Ncc69-KD background might be good alternatives. For 3B, please show a control or state the percentage of the control animals that show bang sensitivity.

NKCC1 as a direct target of NGLY1

There is discrepancy between the data shown in Figure 4A and 4D. In 4A, the NKCC1 bands show a bigger apparent size in Ngly1-/- cells compared to control cells, compatible with the idea that NGLY1 normally deglycosylates some NKCC1 molecules. However, in control lanes of 4D for all three digestions, the NKCC1 bands in Ngly1-/- and control cells look similar to each other. It is hard to explain these data, and they make the digestion results inconclusive. The idea is that in Ngly1-/- cells, NKCC1 becomes bigger (N-glycan retention) and then upon PNGase F and potentially Endo-H digestion it loses N-glycans and becomes the same size as the NKCC1 from wild-type cells. But if the two cells start with the same pattern for a potential target protein, then the glucosidase digestion results apply to those N-glycans that would not normally be removed by NGLY1 (i.e., N-glycans on properly folded NKCC1 molecules) and therefore cannot be used to conclude that the protein is normally deglycosylated by NGLY1. In addition, given that ERAD substrates do not traffic to Golgi, they should harbor high mannose glycans. Therefore, when an NGLY1 target is not deglycosylated in Ngly1-/- cells, the retained glycans should be Endo-H sensitive, not Endo-H resistant.

On a related note, the authors wrote "Together these data indicate that NGLY1 has deglycosylation activity that is independent of both the retrotranslocation and the degradation components of the ERAD pathway." This conclusion is against everything so far discovered about NGLY1. The authors are cognizant of this issue and hypothesize in the paragraph following this sentence that an asparagine in the cytoplasmic region of NKCC1 might be N-glycosylated by an unknown enzymatic machinery and deglycosylated by NGLY1. They refer to a dog kidney sodium pump as an example of a protein with a cytoplasmic N-glycosylation. However, to my knowledge, presence of N-glycans on this protein or any other cytoplasmic protein has not been confirmed by mass spectrometry and site-directed mutagenesis (please provide references to relevant research articles if there are such reports). Moreover, the identity of the cytoplasmic enzymes that would presumably add N-glycans to cytoplasmic proteins remains unknown. This is not to say that we should not consider any idea that is outside of what has been proposed about N-glycosylation and NGLY1 function. However, to make this argument, the authors need to at least make a mutation in that site (N168) and test whether NKCC1-N184Q shows a decrease in apparent molecular weight compared to NKCC1-WT in control cells, fails to shift up in Western blots in Ngly1-/- cells, and ideally whether NKCC1-N184Q can rescue the effect of NGLY1 loss on the function of NKCC1. Similar experiments on the two confirmed N-glycosylation sites of this protein would make the authors' conclusion about NKCC1 being a target of NGLY1 much stronger.

Reviewer #2:

The manuscript presents a powerful approach for identifying modifying genes that may be relevant to a human genetic disease whose clinical presentation is very heterogeneous. The background, results, and data discussion are well organized and clearly written. In general, the conclusions are supported by the data. Although additional discussion and consideration of alternative hypotheses could be expanded. Substantive concerns are as follows:

1) Tadashi Suzuki's group identified and published the importance of genetic background for NGLY1 deficiency in mouse in 2017. The authors cite this work (Fujihara, et al.) in their Introduction, but only in relation to the identification of endogenous NGLY1 substrates by mass spectrometry. Additional credit and discussion should be given to the Suzuki observations related to the impact of genetic background, a major aspect of this current manuscript.

2) The authors pursue orthogonal validation and further characterization of one of their top modifier hits, NKCC1. This work is well done, includes appropriate controls, and is described clearly. However, the authors provide little insight into how NKCC1, a cell surface protein modified with complex glycans (according to the authors), is able to come into contact with NGLY1. The authors assert that it must because the mass of the protein revealed by SDS-PAGE and western blot is larger in the KO MEFs than in control MEFs. The authors initially propose that NKCC1 carries two glycans in the KO and only 1 in the control. Based on the topology model for the protein and the canonical sequence (uniprot accession P55012-1) two N-liked sequons sit very close to each other in an extracellular loop and three other sequons are predicted to be on cytoplasm-oriented loops. The sequon information is summarized at GlyGen Protein Detail page:

https://www.glygen.org/glycoprotein_detail.html?uniprot_canonical_ac=P55012-1&listID=8dd9dc26a96c1912593c86492827bbb7&gs=NKCC1

The authors recognize a sequon at N163, predicted to be cytoplasm oriented and suggest that a cytoplasmic glycosylation event may occur by an unidentified enzyme or mechanism. Glycosylation at this site would seem to bring the total to 3 sites, not 2. They do not mention the other cytoplasmic glycosylation sequons at N599 and N683. These Asn residues would also seem to be reasonable candidates for cytoplasmic N-glycosylation if such a process exists. The problem that the authors need to more effectively discuss is that no such process is known. In order for a complex glycan to be placed on a cytoplasmic sequon, not only would the unknown enzyme have to transfer a precursor from a Dol-P-donor (localized to the ER lumen), but that modification would then have to be accessible to the entire secretory pathway to be processed toward EndoH resistance. How do the authors envision this happening?

The only definitive way to test this hypothesis is to obtain proteomic characterization of the protein expressed in wild type and KO MEFS. If any of the cytoplasmic sequon Asn residues can be shown to be converted to Asp residues in wild type but not in KO, the authors would have very strong support for their hypothesis. This sort of experiment falls into the category of perhaps beyond the resources or expertise of the authors and is probably an undertaking that would take significant effort. Nonetheless, it should be acknowledged somewhere in the Discussion that this sort of information would provide definitive support for the mechanism they propose.

In the absence of this proof, the proposal that a cytoplasmic glycosylation machinery may exist seems less likely than other possibilities that could be discussed. For instance, the authors do offer the possibility that NGLY1 has functions independent of its enzymatic activity. Perhaps one of those activities influences the efficiency of the oligosaccharyltransferase complex such that it is less likely to modify both of the extracellular Asn residues. Loss of NGLY1 might then lead to more efficient glycosylation of NKCC1. This mechanism does not require the invocation of an unknown cytoplasmic N-linked glycosylation machinery. A more well-reasoned discussion of other possibilities is warranted.

Reviewer #3:

In this manuscript the authors examined how genetic modifiers affect the phenotypes of flies where Pngl (fly homolog of NGLY1) is knocked down by RNAi. The authors crossed the Pngl knockdown flies with a collection of genetically diverse Drosophila strains (Drosophila Genetic Reference Panel). Using GWA analysis, they identified 125 variants that associated with enhanced survival. After detailed analysis of their results (GSEA, ERC, GO), they chose to analyze one of the top hits, Ncc69, the fly homolog of the conserved ion transporters, NKCC1 and 2. They confirmed a genetic interaction between Pngl and Ncc69 by knocking both down, which resulted in synthetic lethality. They also knocked down Ncc69 alone in glial cells, which showed a "bang" seizure phenotype, which was partially rescued in the Pngl knockdown flies. Although the phenotypes were not consistent (rescue in the initial screen, synthetic lethality, rescue of seizure phenotype), these data suggested some sort of genetic interaction. To see if this held true in mammals, they analyzed NKCC1 in WT and NGLY1-null mouse embryonic fibroblasts (MEFs). Western blots showed NKCC1 migrating as a large smear in the WT cells, centering around 150 kDa, but the lower half of the smear was less intense in the NGLY-1 samples. PNGaseF digestions of both samples resulted in a band migrating at the same place, suggesting that the difference involved N-glycans. Lack of digestion with EndoH suggested the difference was in complex-type N-glycans. They also performed ion flux assays and showed that the NGLY1-null cells had a lower Bumetanide-sensitive ion flux (due to NKCC1) than the WT cells. Based on these data the authors concluded the NKCC1 is a direct substrate for NGLY1 de-glycosylation and that this de-glycosylation alters NKCC1 function.

1) Although most of this work is well done, the data does not support the conclusion that NKCC1 is a direct substrate for NGLY1. As the authors point out, the two predicted N-glycans are on an extracelluar loop of NKCC1 and are of the complex-type, so it is unlikely that a cytoplasmically localized NGLY1 could access the sites to de-glycosylate them. Instead, the authors invoked a cytoplasmic N-glycosylation event with an unknown cytoplasmic glycosyltransferase modifying N168, which is cytoplasmic. The authors reference a review by Hart and Wells, 2017, which describes a report that the α-subunit of the dog kidney sodium pump Na+, K+-ATPase is modified on a cytoplasmic domain with an N-glycan. The paper referred to was published in 1990 (https://www.ncbi.nlm.nih.gov/pubmed/2175915 ) and has not been rigorously confirmed using mutagenesis or mass spectral glycoproteomic site mapping. In the review, Hart and Wells conclude, "This provocative claim has remained unresolved". In addition, the large shift in size in Figure 4A, estimated to be as much as 20 kDa (Figure 4C) suggests that the change is much more than a simple complex-type N-glycan. A typical biantennary complex N-glycan with two sialic acids has a mass of just over 2 kDa. This suggests that the N-glycans on the extracellular loop of NKCC1 are extended in some way, possibly by poly-N-acetyl-lactosamine repeats or polysialic acid. Thus, a much simpler explanation for the change in molecular weight in Figure 4A is that loss of NGLY1 in these cells induces, indirectly, expression of glycosyltransferases responsible for enhanced extension of the 2 N-glycans on the extracellular loop of NKCC1. Without more experimentation, the authors cannot conclude that NKCC1 is a direct substrate of NGLY1. Other possibilities are more likely.

2) It is not clear why KD of Ncc69 rescued the Pngl phenotype in the initial screen while KD of both in Figure 3A caused synthetic lethality.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "A Drosophila screen identifies NKCC1 as a modifier of NGLY1 deficiency" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by Reviewing Editor Hugo Bellen and Patricia Wittkopp, Senior Editor. The reviewers have opted to remain anonymous.

We are glad to conditionally accept the manuscript for publication in eLife. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.

In the revised version, the authors have addressed my comments, in some cases by additional experiments but more often by changing the text to tone down the previous conclusions. The revised manuscript is improved, as most of the statements made in the manuscript are supported by the data. The mechanistic link between NGLY1 and NKCC1 remains largely unknown, and this makes several paragraphs in the Discussion section rather speculative. However, the fly and bioinformatic screens, the genetic interactions, and the reduced NKCC1 function in Ngly1 mutant MEF cells, combined with the phenotypic similarities between NKCC1 and NGLY1 mutants in humans and mice, are important contributions to our understanding of NGLY1 biology and potentially the pathophysiology of NGLY1 deficiency.

Please address the following points:

Impact statement: Please add "potentially" before "explaining several symptoms of NGLY1 deficiency such as lack of sweat and tears.".

The authors write "there is no evidence of ER stress upon RNAi knockdown of NGLY1 in Drosophila, (Owings et al., 2018) or upon loss of NGLY1 function in mouse, rat, and human cells (Asahina et al., 2020; Mueller et al., 2020; Tambe, Ng and Freeze, 2019)." Also, in the Discussion a similar statement has been made. Loss of Ngly1 in mouse embryonic fibroblasts has recently been shown to significantly increase the level of several ER stress markers (BiP, phopho-IRE1α and OS9), and this was further enhanced when an NGLY1 substrate was overexpressed in these cells (Galeone et al., 2020). This paper has been already cited by the authors in a different part of the manuscript. Please revise these sentence to incorporate the findings of this report.

In the response letter, the authors have acknowledged that the PNGase F and Endo H data are difficult to interpret and have agreed with the reviewers' comments that the data are not sufficient for calling NKCC1 a target of NGLY1. In accordance with this, the following sentence (between quotation marks) should be removed, as it implies otherwise (The authors wrote: In cells derived from an NGLY1 -/- mouse model we found that NKCC1 protein migrated at a higher molecular weight relative to +/+ cells. "Treatment with PNGase eliminated this size difference, confirming that this is due to N-linked glycosylation.")

A similar sentence that needs to be removed, as it is not supported by the data: "but rather NKCC1 has a molecular weight shift that can be eliminated with PNGase treatment".

Just for the authors' information: In response to question #3 of reviewer 3, the authors mentioned that they have used attP2 and attP40 lines without RNAi insertion as negative control. Sometimes adding a second UAS transgene (with or without RNAi) can dilute the effects of a GAL4 driver on a specific RNAi line. In other words, to prove that the partial rescue of the Ncc69 KD phenotype by adding UAS-Ngly1-RNAi chromosome is due to simultaneous Ngly1 KD (shown in Figure 3B), it would have been better to use a UAS-GFP line (to generate UAS-GFP; UAS-Ncc69-RNAi; repo-GAL4 animals) to show that it's the Ngly1 KD that is partially rescuing, not the UAS element. This only becomes important when the second transgene improves the phenotype of the first transgene (like 3B) and is not necessary when the phenotype is enhanced (like 3A).

https://doi.org/10.7554/eLife.57831.sa1

Author response

[Editors’ note: The authors appealed the original decision. What follows is the authors’ response to the first round of review.]

Reviewer #1:

[…]

Genetic interaction between NGLY1 and Ncc69 in flies

The authors have used a double KD strategy to examine the genetic interaction between NGLY1 and Ncc69. They state that NGLY1 KD with tubulin-Gal4 did not cause significant lethality (Figure 3A). Wasn't the same genotype used in the genetic screen and mentioned to show lethality, prompting the authors to use a tubulin-Gal80 in the background? The authors' previous work (Owings et al) also indicated only ~30% eclosion to adulthood in tubulin-Gal4 UAS-Ngly1-RNAi. The authors should address the reason for this discrepancy and repeat the genetic interaction studies in the same context as the original screen.

It is true that this same NGLY1 RNAi line showed ~30% eclosion in our previous publication (Owings et al., 2018). In the process of preparing this manuscript, we were also surprised by the significant change in lethality for this line (multiple experiments were consistent). After receiving the reviews, we suspected contamination of the original NGLY1 RNAi line, to correct this we re-ordered the strains and repeated these crosses. Our new results show ~25% eclosion, similar to our previous publication. We have replaced Figure 3A and the wording in the Results section.

It should be noted that the potential contamination does affect the screen data, as that was performed in 2016 and the follow-up experiments in question were performed in 2019.

The data in Figure 3B seems to be in the same direction as the results of the genetic screen. However, it has the same technical issues as 3A, in the sense that only one RNAi has been used for each gene and the degree of KD is not known. In this case, it will be more difficult to determine KD efficiency, so using independent RNAi lines and/or heterozygosity for NGLY1 in an Ncc69-KD background might be good alternatives.

The NGLY1 RNAi was previously validated (Owings et al., 2018). In that publication we used multiple NGLY1 RNAi lines which showed similar results. We have added this explanation into the Results section of the manuscript. The Ncc69 RNAi line was validated by another group (Leiserson, Forbush and Keshishian, 2011) and we have added this reference to the manuscript as well. As far as using heterozygous NGLY1-null animals, we have found that they do not have seizures.

For 3B, please show a control or state the percentage of the control animals that show bang sensitivity.

We apologize for not adding in this data. The percentage of control animals that show bang sensitivity is 0%, and we have added this control group into Figure 3 and in the text.

Moreover, given the potential off target effects with RNAi, the genetic interaction should be confirmed by either rescue by an RNAi-resistant transgene of one of these genes (for example, the human homolog), or by using loss-of-function allele(s) (or at least by using additional independent RNAi strains for each gene). If I understood correctly, the authors have found Ncc69 SNPs in 9 of the DGRP strains which modified the NGLY1 KD lethality. How are these 9 strains distributed across the data shown in Figure 1B?

We apologize for not being clear. There were not 9 DGRP strains that contained SNPs, rather there were many strains that contained a number of these 9 SNPs. These 9 SNPs are not independent, rather, they are contained in a 54 bp region and are in near perfect linkage disequilibrium. We have revised this section so that it is more clear.

Based on the statement ("that deletions encompassing these nine Ncc69 intronic SNPs result in a null allele") and in light of the genetic interaction suggested in Figure 3A, one would think that Ncc69-lines from DGRP would show a high degree of lethality when combined with NGLY1-KD. Do the authors find it surprising that so many SNPs in this gene were actually associated with survival to adulthood in NGLY1 KD animals? This might be caused by an increase in Ncc69 expression in those strains and should be tested. In fact, if what I have written above is correct, it would have been better to show that Ncc69 overexpression can rescue the lethality of NGLY1-KD animals.

We apologize for being very unclear in this section. These 9 linked SNPs are in a region encompassed by a much larger deletion allele of the Ncc69 gene. This statement was imprecise and was simply meant to convey that this region was deleted as part of a larger deletion and not meant to convey that these 9 SNPs are causative of the deleted allele. We eliminated this statement to prevent further confusion. Additionally, we have analyzed Ncc69 expression levels in the DGRP strains using previously published RNAseq data from the 200 strains. We found that there was no correlation between Ncc69 expression and survival and have included the data in the text and as Figure 1—figure supplement 1. This lack of correlation is not particularly surprising, as the expression data available is from whole, adult flies and we are not sure which time points or tissues are most important for the genetic interaction we identified.

NKCC1 as a direct target of NGLY1

There is discrepancy between the data shown in Figure 4A and 4D. In 4A, the NKCC1 bands show a bigger apparent size in Ngly1-/- cells compared to control cells, compatible with the idea that NGLY1 normally deglycosylates some NKCC1 molecules. However, in control lanes of 4D for all three digestions, the NKCC1 bands in Ngly1-/- and control cells look similar to each other. It is hard to explain these data, and they make the digestion results inconclusive. The idea is that in Ngly1-/- cells, NKCC1 becomes bigger (N-glycan retention) and then upon PNGase F and potentially Endo-H digestion it loses N-glycans and becomes the same size as the NKCC1 from wild-type cells. But if the two cells start with the same pattern for a potential target protein, then the glucosidase digestion results apply to those N-glycans that would not normally be removed by NGLY1 (i.e., N-glycans on properly folded NKCC1 molecules) and therefore cannot be used to conclude that the protein is normally deglycosylated by NGLY1.

We agree that the controls for the enzyme digestion make it difficult to interpret the results. The size difference observed in Figure 4A is very reproducible (also see Figure 4E). We have since repeated this experiment in Figure 4D multiple times with very similar results. We believe that incubating the lysate at 37°C for 60 minutes decreases the integrity of the 150kDa, 12-pass membrane, glycoprotein NKCC1 and therefore it is difficult to see the size difference in the untreated state. Because the difference is not an “all or none” difference in Figure 4A, we think that this instability makes it even harder to observe in the control treatments. However, we believe that in our most recent Endo H treatment the size difference is more visible and therefore we have replaced this blot in Figure 4D.

In addition, given that ERAD substrates do not traffic to Golgi, they should harbor high mannose glycans. Therefore, when an NGLY1 target is not deglycosylated in Ngly1-/- cells, the retained glycans should be Endo-H sensitive, not Endo-H resistant.

We regret that our language made it sounds as if NKCC1 was an ERAD substrate. We believe that by eliminating all of the language about NKCC1 being a direct substrate of NGLY1 deglycosylation, that we have also removed the assumption that it is undergoing ERAD, and therefore it is completely plausible that they should be Endo-H resistant.

On a related note, the authors wrote "Together these data indicate that NGLY1 has deglycosylation activity that is independent of both the retrotranslocation and the degradation components of the ERAD pathway." This conclusion is against everything so far discovered about NGLY1. The authors are cognizant of this issue and hypothesize in the paragraph following this sentence that an asparagine in the cytoplasmic region of NKCC1 might be N-glycosyalted by an unknown enzymatic machinery and deglycosylated by NGLY1. They refer to a dog kidney sodium pump as an example of a protein with a cytoplasmic N-glycosylation. However, to my knowledge, presence of N-glycans on this protein or any other cytoplasmic protein has not been confirmed by mass spectrometry and site-directed mutagenesis (please provide references to relevant research articles if there are such reports). Moreover, the identity of the cytoplasmic enzymes that would presumably add N-glycans to cytoplasmic proteins remains unknown. This is not to say that we should not consider any idea that is outside of what has been proposed about N-glycosylation and NGLY1 function. However, to make this argument, the authors need to at least make a mutation in that site (N168) and test whether NKCC1-N184Q shows a decrease in apparent molecular weight compared to NKCC1-WT in control cells, fails to shift up in Western blots in Ngly1-/- cells, and ideally whether NKCC1-N184Q can rescue the effect of NGLY1 loss on the function of NKCC1. Similar experiments on the two confirmed N-glycosylation sites of this protein would make the authors' conclusion about NKCC1 being a target of NGLY1 much stronger.

We completely agree that site directed mutagenesis is the next step in this scientific story, and have noted such in the Discussion section. However, as we stated in our rebuttal letter, we believe that these experiments are beyond the scope of this manuscript.

Reviewer #2:

The manuscript presents a powerful approach for identifying modifying genes that may be relevant to a human genetic disease whose clinical presentation is very heterogeneous. The background, results, and data discussion are well organized and clearly written. In general, the conclusions are supported by the data. Although additional discussion and consideration of alternative hypotheses could be expanded. Substantive concerns are as follows:

1) Tadashi Suzuki's group identified and published the importance of genetic background for NGLY1 deficiency in mouse in 2017. The authors cite this work (Fujihara, et al.) in their Introduction, but only in relation to the identification of endogenous NGLY1 substrates by mass spectrometry. Additional credit and discussion should be given to the Suzuki observations related to the impact of genetic background, a major aspect of this current manuscript.

Thank you for pointing this out. We regret this oversight and we have added the following sentence into the Introduction, “This variability based on background genetics was also observed in the lab when an NGLY1 deficiency mouse model was crossed onto an outbred mouse strain which partially rescued the lethality of the model (Fujihira et al., 2017)”.

2) The authors pursue orthogonal validation and further characterization of one of their top modifier hits, NKCC1. This work is well done, includes appropriate controls, and is described clearly. However, the authors provide little insight into how NKCC1, a cell surface protein modified with complex glycans (according to the authors), is able to come into contact with NGLY1. The authors assert that it must because the mass of the protein revealed by SDS-PAGE and western blot is larger in the KO MEFs than in control MEFs. The authors initially propose that NKCC1 carries two glycans in the KO and only 1 in the control. Based on the topology model for the protein and the canonical sequence (uniprot accession P55012-1) two N-liked sequons sit very close to each other in an extracellular loop and three other sequons are predicted to be on cytoplasm-oriented loops. The sequon information is summarized at GlyGen Protein Detail page:

https://www.glygen.org/glycoprotein_detail.html?uniprot_canonical_ac=P55012-1&listID=8dd9dc26a96c1912593c86492827bbb7&gs=NKCC1

The authors recognize a sequon at N163, predicted to be cytoplasm oriented and suggest that a cytoplasmic glycosylation event may occur by an unidentified enzyme or mechanism. Glycosylation at this site would seem to bring the total to 3 sites, not 2. They do not mention the other cytoplasmic glycosylation sequons at N599 and N683. These Asn residues would also seem to be reasonable candidates for cytoplasmic N-glycosylation if such a process exists.

The reviewer is correct that there are three additional N-X-S/T sites in the mouse (and human) NKCC1. We have added this sentence to the Discussion to clarify our reasoning, “Amino acid analysis reveals three other asparagine residue within the necessary N-X-S/T sequence for N-linked glycosylation, however two are predicted to be in transmembrane domains; the third (human NKCC1 residue N168) is located in the amino-terminal cytoplasmic tail of the protein.”.

The problem that the authors need to more effectively discuss is that no such process is known. In order for a complex glycan to be placed on a cytoplasmic sequon, not only would the unknown enzyme have to transfer a precursor from a Dol-P-donor (localized to the ER lumen), but that modification would then have to be accessible to the entire secretory pathway to be processed toward EndoH resistance. How do the authors envision this happening?

At this point, the exact mechanism is unclear. We apologize for jumping to conclusions that were not warranted by our data. We believe that by eliminating all of the language about NKCC1 being a direct substrate of NGLY1 that we have eliminated these concerns.

The only definitive way to test this hypothesis is to obtain proteomic characterization of the protein expressed in wild type and KO MEFS. If any of the cytoplasmic sequon Asn residues can be shown to be converted to Asp residues in wild type but not in KO, the authors would have very strong support for their hypothesis. This sort of experiment falls into the category of perhaps beyond the resources or expertise of the authors and is probably an undertaking that would take significant effort. Nonetheless, it should be acknowledged somewhere in the Discussion that this sort of information would provide definitive support for the mechanism they propose.

Since the review of our manuscript, we were able to send a gel slice corresponding to the molecular weight range of NKCC1 for mass spec analysis. The analysis was able to identify several peptides mapping to NKCC1 (SLC12A2), see Author response image 1.

Author response image 1

However, these peptides gave only ~10% protein coverage, as was predicted by the personnel at our mass spec core given the hydrophobic nature of the 12-pass transmembrane domains. Unfortunately, none of the peptides included a potential N-linked glycosylation site. We plan to perform more mass spec analysis with varied parameters, but we believe this is beyond the scope of this manuscript. As suggested, we have added language to the Discussion about future mass spec analysis.

In the absence of this proof, the proposal that a cytoplasmic glycosylation machinery may exist seems less likely than other possibilities that could be discussed. For instance, the authors do offer the possibility that NGLY1 has functions independent of its enzymatic activity. Perhaps one of those activities influences the efficiency of the oligosaccharyltransferase complex such that it is less likely to modify both of the extracellular Asn residues. Loss of NGLY1 might then lead to more efficient glycosylation of NKCC1. This mechanism does not require the invocation of an unknown cytoplasmic N-linked glycosylation machinery. A more well-reasoned discussion of other possibilities is warranted.

This is a good suggestion and we have added the following sentences to the Discussion:

“If this effect is secondary, it may be that NGLY1 is directly affecting an oligosaccharyltransferase complex that in turn modifies the already present glycans. This hypothesis is supported by the fact that Endo H treatment did not affect NKCC1 from either +/+ or -/- cells, indicating that NKCC1 has been fully processed through the Golgi.”.

Reviewer #3:

[…]

1) Although most of this work is well done, the data does not support the conclusion that NKCC1 is a direct substrate for NGLY1. As the authors point out, the two predicted N-glycans are on an extracelluar loop of NKCC1 and are of the complex-type, so it is unlikely that a cytoplasmically localized NGLY1 could access the sites to de-glycosylate them. Instead, the authors invoked a cytoplasmic N-glycosylation event with an unknown cytoplasmic glycosyltransferase modifying N168, which is cytoplasmic. The authors reference a review by Hart and Wells, 2017, which describes a report that the α-subunit of the dog kidney sodium pump Na+, K+-ATPase is modified on a cytoplasmic domain with an N-glycan. The paper referred to was published in 1990 (https://www.ncbi.nlm.nih.gov/pubmed/2175915 ) and has not been rigorously confirmed using mutagenesis or mass spectral glycoproteomic site mapping. In the review, Hart and Wells conclude, "This provocative claim has remained unresolved". In addition, the large shift in size in Figure 4A, estimated to be as much as 20 kDa (Figure 4C) suggests that the change is much more than a simple complex-type N-glycan. A typical biantennary complex N-glycan with two sialic acids has a mass of just over 2 kDa. This suggests that the N-glycans on the extracellular loop of NKCC1 are extended in some way, possibly by poly-N-acetyl-lactosamine repeats or polysialic acid. Thus, a much simpler explanation for the change in molecular weight in Figure 4A is that loss of NGLY1 in these cells induces, indirectly, expression of glycosyltransferases responsible for enhanced extension of the 2 N-glycans on the extracellular loop of NKCC1. Without more experimentation, the authors cannot conclude that NKCC1 is a direct substrate of NGLY1. Other possibilities are more likely.

We agree that this conclusion was unwarranted by the data and have changed all mentions of it in the manuscript. In regards to the hypothesis about glycosyltransferases we have added these sentences to the Discussion: “If this effect is secondary, it may be that NGLY1 is directly affecting an oligosaccharyltransferase complex that in turn modifies the already present glycans. This hypothesis is supported by the fact that Endo H treatment did not affect NKCC1 from either +/+ or -/- cells, indicating that NKCC1 has been fully processed through the Golgi.”.

2) It is not clear why KD of Ncc69 rescued the Pngl phenotype in the initial screen while KD of both in Figure 3A caused synthetic lethality.

The initial screen did not utilize KD of any genes aside from Pngl, but rather used natural genetic variation in the DGRP fly lines. None of the SNPs associated with Ncc69 are known to cause a decrease in the expression levels. We have tried to make this more clear by adding a plot of the Ncc69 expression from each DGRP line versus our survival data (Figure 1—figure supplement 1), and adding language into the Results section.

[Editors’ note: what follows is the authors’ response to the second round of review.]

Please address the following points:

Impact statement: Please add "potentially" before "explaining several symptoms of NGLY1 deficiency such as lack of sweat and tears.".

We have added the word “potentially”.

The authors write "there is no evidence of ER stress upon RNAi knockdown of NGLY1 in Drosophila, (Owings et al., 2018) or upon loss of NGLY1 function in mouse, rat, and human cells (Asahina et al., 2020; Mueller et al., 2020; Tambe, Ng and Freeze, 2019)." Also, in the Discussion a similar statement has been made. Loss of Ngly1 in mouse embryonic fibroblasts has recently been shown to significantly increase the level of several ER stress markers (BiP, phopho-IRE1α and OS9), and this was further enhanced when an NGLY1 substrate was overexpressed in these cells (Galeone et al., 2020). This paper has been already cited by the authors in a different part of the manuscript. Please revise these sentence to incorporate the findings of this report.

The text have been changed as such “While a recent report showed that ER stress markers were increased in NGLY1 -/- MEFs (Galeone et al., 2020), other experiments such as RNAi knockdown of NGLY1 in Drosophila, (Owings et al., 2018) and loss of NGLY1 function in mouse, rat, and human cells (Asahina et al., 2020; Mueller et al., 2020; Tambe, Ng and Freeze, 2019) have shown no evidence of ER stress.”

And “While perturbations to ERAD often result in ER stress, we have previously reported that there was no functional or transcriptome evidence for ER stress in a Drosophila model of NGLY1 deficiency (Owings et al., 2018). Others have reported no ER stress in NGLY1 -/- human cells, mice, and rats (Asahina et al., 2020; Mueller et al., 2020; Tambe et al., 2019). However, there is conflicting evidence for ER stress as it was recently reported that ER stress markers were upregulated in NGLY -/- MEFs (Galeone et al., 2020). Nevertheless, in our current screen, we did not identify any genes involved in canonical ER stress responses, suggesting that ER stress might not play a large role in the pathogenesis of the disease.”

In the response letter, the authors have acknowledged that the PNGase F and Endo H data are difficult to interpret and have agreed with the reviewers' comments that the data are not sufficient for calling NKCC1 a target of NGLY1. In accordance with this, the following sentence (between quotation marks) should be removed, as it implies otherwise (The authors wrote: In cells derived from an NGLY1 -/- mouse model we found that NKCC1 protein migrated at a higher molecular weight relative to +/+ cells. "Treatment with PNGase eliminated this size difference, confirming that this is due to N-linked glycosylation.")

We have removed this sentence.

A similar sentence that needs to be removed, as it is not supported by the data: "but rather NKCC1 has a molecular weight shift that can be eliminated with PNGase treatment".

This sentence has been changed to read: “Given that we show the abundance of NKCC1 does not change, but rather NKCC1 has a molecular weight shift, it is likely that the altered state is due to some difference in a post-translational modification.”.

https://doi.org/10.7554/eLife.57831.sa2

Article and author information

Author details

  1. Dana M Talsness

    Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, United States
    Contribution
    Data curation, Formal analysis, Investigation, Visualization, Writing - original draft, Writing - review and editing
    Contributed equally with
    Katie G Owings
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7823-1616
  2. Katie G Owings

    Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, United States
    Contribution
    Data curation, Formal analysis, Visualization
    Contributed equally with
    Dana M Talsness
    Competing interests
    No competing interests declared
  3. Emily Coelho

    Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, United States
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  4. Gaelle Mercenne

    Department of Internal Medicine, Division of Nephrology and Hypertension, and Molecular Medicine Program, University of Utah, Salt Lake City, United States
    Contribution
    Data curation
    Competing interests
    No competing interests declared
  5. John M Pleinis

    Department of Internal Medicine, Division of Nephrology and Hypertension, and Molecular Medicine Program, University of Utah, Salt Lake City, United States
    Contribution
    Data curation
    Competing interests
    No competing interests declared
  6. Raghavendran Partha

    Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7900-4375
  7. Kevin A Hope

    Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, United States
    Contribution
    Data curation
    Competing interests
    No competing interests declared
  8. Aamir R Zuberi

    Genetic Resource Science, The Jackson Laboratory, Bar Harbor, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
  9. Nathan L Clark

    Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, United States
    Contribution
    Formal analysis, Supervision, Writing - review and editing
    Competing interests
    No competing interests declared
  10. Cathleen M Lutz

    Genetic Resource Science, The Jackson Laboratory, Bar Harbor, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
  11. Aylin R Rodan

    1. Department of Internal Medicine, Division of Nephrology and Hypertension, and Molecular Medicine Program, University of Utah, Salt Lake City, United States
    2. Medical Service, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, United States
    Contribution
    Supervision, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9202-2378
  12. Clement Y Chow

    Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Writing - original draft, Writing - review and editing
    For correspondence
    cchow@genetics.utah.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3104-7923

Funding

National Institute of General Medical Sciences (R35GM124780)

  • Clement Y Chow

National Institute of Diabetes and Digestive and Kidney Diseases (R01DK110358)

  • Aylin R Rodan

National Human Genome Research Institute (R01HG009299)

  • Nathan L Clark

Glenn Foundation for Medical Research (Glenn Award)

  • Clement Y Chow

National Human Genome Research Institute (T32HG008962)

  • Dana M Talsness
  • Kevin A Hope

Might family (Bertrand T Might Fellowship)

  • Dana M Talsness

National Institute of General Medical Sciences (T32GM007464)

  • Katie G Owings

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This study is dedicated to Bertrand Might, the first child diagnosed with NGLY1 deficiency. We thank Dr. Hamed Jafar-Nejad (Baylor College of Medicine) for the gift of immortalized NGLY1-null MEFs. This research was supported by the NIH through an NIGMS R35 award (R35GM124780) (CYC), NIDDK R01 award (R01 DK110358) (ARR), and NHGRI R01 award (R01 HG009299) (NLC). This work was also supported by a Glenn Award from the Glenn Foundation for Medical Research to CYC. CYC was the Mario R Capecchi Endowed Chair in Genetics. DMT and KSH were supported on an NIH/NHGRI Genomic Medicine T32 postdoctoral training grant from the University of Utah (T32 HG008962) and by a generous gift from the Might family through the Bertrand T Might Fellowship. KGO was supported by the NIH/NIGMS Genetics T32 Fellowship from the University of Utah (T32 GM007464). The MEFs were derived from NGLY1 knockout mice which were funded by the Grace Science Foundation to CML.

Senior Editor

  1. Patricia J Wittkopp, University of Michigan, United States

Reviewing Editor

  1. Hugo J Bellen, Baylor College of Medicine, United States

Reviewer

  1. Michael Tiemeyer, University of Georgia, United States

Publication history

  1. Received: April 14, 2020
  2. Accepted: December 12, 2020
  3. Accepted Manuscript published: December 14, 2020 (version 1)
  4. Accepted Manuscript updated: December 17, 2020 (version 2)
  5. Version of Record published: December 23, 2020 (version 3)

Copyright

© 2020, Talsness et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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