To maintain cell size homeostasis, proliferating cells double their mass from one division to the next and divide into similarly sized daughter cells. This stringent regulation of cell size exists in wide-ranging systems such as single-celled yeasts (Hartwell et al., 1974; Johnston et al., 1977; Nurse, 1975; Schmoller et al., 2015), animal cells in culture and within tissues (Ginzberg et al., 2018; Liu et al., 2018; Xie and Skotheim, 2020; Zatulovskiy et al., 2020), as well as plant meristem cells (D’Ario et al., 2021; Serrano-Mislata et al., 2015). Misregulation of cell size control results in increased size heterogeneity, which is typically observed during neoplastic growth and is a hallmark of malignancy in many tumors, including breast cancer and small cell lung cancer (Asadullah et al., 2021; Bell and Waizbard, 1986; Ginzberg et al., 2015; Lee et al., 1992).

How is cell size controlled and how does cellular growth in mass coordinate with the cell cycle program? A major mechanism is the cell size checkpoint, which hinders cell cycle progression for cells that are smaller than the target size. The mammalian G1/S cell size checkpoint was first reported by Zetterberg and Killander over 50 years ago (Killander and Zetterberg, 1965; Zetterberg and Killander, 1965). Subsequently, similar size checkpoints have been identified in single-celled yeasts (Hartwell et al., 1974; Nurse, 1975). In recent years, the functioning of cell size checkpoints has been investigated with increasingly powerful technologies (Cadart et al., 2018; D’Ario et al., 2021; Liu et al., 2018; Perez-Gonzalez et al., 2019; Schmoller et al., 2015; Varsano et al., 2017; Xie and Skotheim, 2020). With increased resolution, these newer studies directly confirmed that smaller cells spend longer periods of growth in G1, allowing cells to reach the target size as they transition into S phase. Although it is not yet clear how animal cells sense their size, studies have revealed roles for both the p38 MAPK (Liu et al., 2018; Sellam et al., 2019) and the CDK4/Rb pathways (Datar et al., 2000; Tan et al., 2021; Zatulovskiy et al., 2020).

In addition to cell size checkpoints, two independent studies suggest that mammalian cells also employ size-dependent regulation of cellular growth rate (Cadart et al., 2018; Ginzberg et al., 2018). Authors of the studies used different methods to measure the growth of individual cell size throughout the cell cycle and found that the rate of cell growth negatively correlated with cell size at various cell cycle stages. Ginzberg et al., 2018 further applied chemical and genetic perturbations that slowed down or accelerated cell cycle progression and observed compensatory changes in the rate of cellular growth, which buffered the initial effect on cell size (Figure 1A). For example, cells under CDK2 inhibition were forced to grow for a longer period in G1, resulting in an immediate increase in cell size. Remarkably, cells later compensated for this longer period of growth with slower rates of mass accumulation, resulting in only a small increase in cell size (Figure 1—figure supplement 1). To discriminate this mechanism from size checkpoints, we use the term size-dependent compensatory growth. Notably, this compensation does not occur with CDK4/6 inhibition (Ginzberg et al., 2018), which was found to reprogram cells to a larger target size (see Tan et al., 2021). Altogether, these studies suggest that cells sense their size to regulate not only cell cycle progression (e.g., cell cycle checkpoints), but also adapt the cell growth program to maintain cell size homeostasis.

In this study, we ask whether the size-dependent regulation of cellular growth is mediated by protein synthesis or protein degradation. We found that proteasome-mediated global protein degradation, rather than protein synthesis, underlies the size-dependent compensatory growth and functions in parallel with cell size checkpoints to promote cell size homeostasis.

To reliably induce a compensatory growth slowdown, we utilized a CDK2 inhibitor assay previously established by Ginzberg et al., 2018. We applied this assay to human retinal pigment epithelial-1 (RPE1) cells, a well-characterized non-transformed epithelial cell line. In this assay, unsynchronized cell populations were treated with a low dose of the CDK2 inhibitor, SNS-032, to induce a longer G1 phase. We optimized a concentration range that inhibits CDK2 function without arresting the cell cycle (Figure 1—figure supplement 1). Cells were subsequently fixed at different timepoints and profiled for proliferation rate, cell size, and cell cycle stage. Cell size was measured with Alexa fluorophore-conjugated succinimidyl ester (SE), which reacts with primary amines and quantifies total protein content of the cell as previously described (Kafri et al., 2013; Mugahid et al., 2020; Neurohr et al., 2019). As shown by Ginzberg et al., 2018, the temporal influence of CDK2 inhibition on cell size is characterized by a two-stage process: an early response followed by a delayed compensation. Although cell size initially increased for CDK2-inhibited cells as a result of the prolonged cell cycle, it gradually plateaus after ~24 hr due to a compensatory slowdown in growth (Figure 1—figure supplement 1). Average rates of cell proliferation and cell growth can be inferred from the dynamics of cell number and cell mass (see ‘Materials and methods’). This revealed that CDK2-inhibited cells initially grew at the same rate as control but later compensated with a 24% reduced rate of mass accumulation (Figure 1—figure supplement 1). In comparison, rates of cell proliferation remained unchanged (25% lower than control) throughout the experiment (Figure 1—figure supplement 1; Ginzberg et al., 2018). The delayed compensatory slowdown in cellular growth suggests that the influence of CDK2 inhibitor on growth rate is indirect and is mediated by a property that accumulates over time, presumably cell size.

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What underlies this size-dependent regulation of cell growth? The rate of macromolecular growth depends on the interplay between the biosynthesis and degradation of proteins, lipids, polysaccharides, and other macromolecules (Alber and Suter, 2019). In an actively proliferating mammalian cell, proteins represent more than half of the cell’s total dry mass (Mitchison, 1971) and are under active turnover (Ghenim et al., 2021; Liu et al., 2020). Total protein content also linearly scales with the dry mass and volume of cells at different cell cycle stages (Berenson et al., 2019; Kafri et al., 2013). The balance between protein translation and degradation has been shown to significantly influence cell size in various cell types, including neurons, muscles, and cancer cells (Acebron et al., 2014; Franklin and Johnson, 1998; Gordon et al., 2013; Sandri, 2013), suggesting a vital role of protein homeostasis in cell size control.

Compensatory changes in cellular growth rate are not regulated at the level of global protein synthesis

Because cell growth reflects the balance between rates of protein synthesis and protein degradation, we first asked whether the compensatory growth slowdown is mediated through reduced rates of protein synthesis in large cells. We used a multiplex, single-cell labeling strategy to jointly profile overall protein synthesis rates, macromolecular protein mass (by SE), and cell cycle state in thousands of asynchronized proliferating cells. To quantify global translation rates, we performed kinetic pulse measurements with a derivatized methionine analog, L-azidohomoalanine (AHA) (Calve et al., 2016), which measures the amount of AHA that is incorporated into newly synthesized proteins. We performed an AHA pulse for 3 hr to obtain a high signal-to-noise ratio in a relatively short period of the cell cycle. Treating cells with the protein synthesis inhibitor, cycloheximide (CHX), significantly reduces AHA incorporation (Figure 2A), confirming the efficacy of the assay.

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If the compensatory slowdown of growth is driven by slower rates of protein synthesis, larger cells should have lower rates of AHA incorporation. Our results, however, demonstrate the contrary. In unperturbed cells, AHA incorporation levels positively correlated with total protein content (R = 0.91) (Figure 2A), indicating a faster rate of protein synthesis in large cells. To test if the positive correlation between cell size and AHA incorporation is cell cycle dependent, we further segregated cells by their cell cycle stage and found that the dependence of AHA incorporation on size was consistent for G1, S, and G2 cells (Figure 2B). In all cell cycle stages, larger cells incorporated more AHA per unit time. Markedly, the linear dependence of AHA incorporation on cell size persists across a wide range of sizes, even for cells that are approximately twofold larger, as induced by CDK4/6 inhibition (Figure 2C).

Because we did not observe a compensatory slowdown of AHA incorporation in naturally large cells, we next examined whether the compensatory growth slowdown following CDK2 inhibition is regulated at the level of protein synthesis. We employed the same strategy described in Figure 1—figure supplement 1 and additionally measured rates of AHA incorporation. CDK2-inhibited cells demonstrated a slight increase in both cell size (~11%) and AHA incorporation (~4%) compared to that of control (Figure 2C), despite the compensatory slowdown of growth. Consistent with measurements in unperturbed cells, CDK2-inhibited cells maintained a similar linear correlation between cell size and AHA incorporation, both at the single-cell level and across different cell cycle stages (Figure 2B and C), suggesting that the protein synthesis machinery is not affected by CDK2 inhibition throughout the duration of the experiment. Together, results from the AHA pulse experiments suggest that the compensatory growth slowdown in CDK2-inhibited cells is not mediated through a decrease in overall rates of protein synthesis but likely through an increase in overall protein degradation.

Large cells have higher rates of global protein degradation

To measure rates of protein degradation, we implemented a CHX chase assay and quantified the loss of total protein mass over time. In this assay, protein synthesis was inhibited by CHX; therefore, the loss of macromolecular protein mass reflected changes resulting from protein degradation. Interestingly, we observed significantly increased rates of protein degradation in larger cells (80th percentile) compared to smaller cells (20th percentile) (Figure 3A, Figure 3—figure supplement 1), supporting the hypothesis that large cells may activate global protein degradation to initiate a compensatory growth slowdown.

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Proteasome-mediated protein degradation is a major route of protein turnover in non-starved cells (Lecker et al., 2006). The major targeting signal for proteasomal degradation is a post-translational modification involving ubiquitin chains linked through Lysine 48 (K48) (Yau and Rape, 2016). To further test whether larger cells undergo higher rates of proteasome-mediated degradation, we measured the turnover (i.e., clearance) of K48-linked polyubiquitinated proteins (K48-polyUb) in CDK2 inhibited cells that undergo a compensatory growth slowdown. K48-polyUb turnover rates were quantified as the increase in intracellular pools of K48-polyUb that is caused by a short (30 min) treatment with a potent irreversible proteasome inhibitor, carfilzomib (CFZ). The excess amount of K48-polyUb in CFZ-treated cells compared to that of untreated cells, which we term ΔK48-polyUb, estimates the amount of K48-polyUb proteins that would have been degraded during the 30 min had the proteasome not been inhibited. Cell size and the partitioning of cells into different cell cycle stages were not significantly influenced by the 30 min treatment with CFZ (Figure 3—figure supplement 2). Using this method, we measured the rates of proteasome-mediated protein degradation (ΔK48-polyUb) in CDK2-inhibited cells that were induced to undergo a compensatory slowdown of growth. CDK2-inhibited cells showed higher rates of ΔK48-polyUb, affirming a role of proteasomes in compensatory growth. The dependence of compensatory growth on proteasomal degradation is further supported by the temporal similarity of these two processes. Both the slowdown in growth rate and increase in ΔK48-polyUb showed delayed dynamics following CDK2 inhibition. CDK2-inhibited cells had similar ΔK48-polyUb as control during the first 8 hr of treatment, but later showed a significant increase in ΔK48-polyUb at 24 hr, indicating increased rates of protein degradation (Figure 3B and C). The enhanced turnover of K48-polyUb proteins aligns temporally with the compensatory growth rate changes observed in CDK2-inhibited cells (Figure 1—figure supplement 1). This pattern was consistently observed across G1, S, and G2+M phases in CDK2-inhibited cells (Figure 3—figure supplement 3). The delayed kinetics suggest that the increased ΔK48-polyUb is not triggered by the immediate inhibition of CDK2 activity but rather from the buildup of excessive cell mass triggered by the gradual influence of the longer cell cycle. Altogether, these results indicate that the compensatory slowdown of cell growth is mediated by increased clearance of K48-polyUb.

Large cells at the G1/S transition show hyperactive global protein degradation

To further dissect the cell cycle dependency of the increased global protein degradation observed in large cells, we compared ΔK48-polyUb levels across different cell cycle stages. Strikingly, cells at the G1/S transition exhibit the highest ΔK48-polyUb levels in both control and CDK2-inhibited cells (Figure 4A and B). Remarkably, rates of global protein degradation observed in these large G1/S cells surpassed those of similarly sized or even larger cells in S and G2 phases, suggesting a hyperactivation of global protein degradation at the G1/S transition.

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To better characterize the cell cycle dynamics of compensatory degradation, we performed pseudo-time trajectory analysis and aligned cells to a continuous cell cycle axis based on their DNA content and the FUCCI cell cycle marker mAG-hGem (Figure 4C, see ‘Materials and methods’; Kafri et al., 2013). This method allowed extraction of average cellular dynamics from single-cell snapshots of fixed steady-state populations (Kafri et al., 2013). Interestingly, the analysis revealed a subpopulation of exceptionally large cells at the G1/S transition, often comparable in size or even larger than cells in S and G2 phases (Figure 4D). Time-lapse imaging confirmed that large G1/S cells were not arrested but continued to progress through the cell cycle (Figure 4—figure supplement 1). These large G1/S cells exhibited high levels of ΔK48-polyUb per cell (Figure 4—figure supplement 1), and importantly, the highest levels of ΔK48-polyUb per unit mass (Figure 4E), further supporting the notion of hyperactive protein degradation in large G1/S cells.

To further test this observation, we used time-lapse imaging and examined the impact of partial protein synthesis inhibition on cellular growth rates before and after the G1/S transition. We applied mTOR inhibition and measured cellular growth rates separately for small and large cells. Under control conditions, large cells on average grew faster than small cells, both before and after the G1/S transition (Figure 4—figure supplement 2), and when averaged across the entire cell cycle (Figure 4—figure supplement 2), likely due to their higher protein synthesis rates (Figure 2, Figure 4—figure supplement 2). However, upon mTOR inhibition, the cellular growth rates of small and large cells converged before the G1/S transition but not after (Figure 4—figure supplement 2). This convergence occurred despite a proportional decrease in protein synthesis rates by mTOR inhibition for all cells, with large cells continuing to synthesize proteins faster than small cells (Figure 4—figure supplement 2). These results provide additional evidence that large cells prior to the G1/S transition exhibit elevated rates of protein degradation, which counterbalance the higher protein synthesis rates in large cells.

In summary, our results demonstrate that large cells exhibit elevated rates of protein degradation throughout interphase, with a particularly pronounced increase in large cells at the G1/S transition. This mechanism may function in conjunction with the cell size checkpoints to promote cell size uniformity.

Cell size is fundamental to cellular physiology as it sets the scale for subcellular compartments, biosynthetic capacity, and cellular function. Evidence of cell size control has been reported from single-celled yeasts to multicellular animals and plants (Dolznig et al., 2004; Hartwell et al., 1974; Neufeld et al., 1998; Nurse, 1975; Willis et al., 2016; Xie and Skotheim, 2020; Zetterberg and Killander, 1965). The precision with which size is controlled also manifests in the cell size regularity observed in healthy tissues. In contrast, deregulation of size control often signals cancerous growth as many tumors display increased heterogeneity in cell size (Asadullah et al., 2021; Bell and Waizbard, 1986; Lee et al., 1992).

Previous studies on cell size control have predominantly focused on cell size checkpoints, in that a critical size threshold is required for cell cycle progression (D’Ario et al., 2021; Ginzberg et al., 2018; Liu et al., 2018; Sellam et al., 2019; Zatulovskiy et al., 2020). In this study, we investigated size-dependent compensatory growth, which functions independently of cell cycle checkpoints. We employed a CDK2 inhibition assay to trigger compensatory growth, forcing cells to undergo prolonged growth periods, resulting in an initial increase in cell size followed by a delayed compensatory growth slowdown (Figure 1). We found that the rates of global protein synthesis and degradation increase with cell size in both perturbed and unperturbed conditions (Figures 2 and 3). Interestingly, although protein synthesis rates scaled proportionally with cell size, protein degradation rates were disproportionately higher in large CDK2-inhibited cells (i.e., higher rates of protein degradation per unit mass), suggesting active upregulation of the proteasomal degradation pathway (Figure 3). In contrast, CDK4/6 inhibition, which induces a larger target size without triggering compensatory growth slowdown, exhibited the same linear scaling between cell size and protein degradation rates as in control (Figure 3—figure supplement 4). We also tested two other perturbations that forced overgrowth in cell size by extending S or G2/M phases. Like CDK2 inhibition, these perturbations induced superlinear increases in protein degradation (Figure 3—figure supplement 4), suggesting that activation of protein degradation functions as a general compensatory mechanism of cell size control in response to prolonged growth periods, irrespective of the specific cell cycle stage affected. Further analysis across the cell cycle highlighted a particularly striking increase in global protein degradation in large cells at the G1/S transition (Figure 4), consistent with the stringent size control observed at the G1 exit (Ginzberg et al., 2018; Zetterberg and Killander, 1965). Based on these results, we propose a model in which oversized cells reduce their growth efficiency by activating global proteasome-mediated protein degradation to promote cell size homeostasis (Figure 5).

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While this study focused on human RPE1 cells, a non-cancerous epithelial cell line, previous work (Mu et al., 2020) on a cancerous mouse lymphocytic leukemia cell line found that large polyploid cells do not reduce growth efficiency compared to smaller diploid cells, suggesting that growth rate regulation may be cell type- and ploidy-dependent. Previous work has also suggested that small cells may accelerate their growth at certain cell cycle stages (Cadart et al., 2018; Ginzberg et al., 2018). It will be interesting to examine in future studies whether the growth acceleration observed in these small cells depends on reduced global protein degradation. High-throughput screens on both animal cells and yeasts identified that small cells activate the stress-responding p38 MAPK (Hog1) pathway to prolong the cell cycle (Liu et al., 2018; Sellam et al., 2019). Previous work on p38 also found that activation of the pathway by osmotic stress results in reduced protein degradation and lower proteasome activity (Lee et al., 2010), whereas p38 inhibition significantly promoted proteasome activity (Leestemaker et al., 2017). These reports suggest an intriguing possibility that the p38 MAPK activation in small cells may function in both the cell size checkpoint and growth rate regulation.

Our data also suggest hyperactivated rates of global protein degradation in large cells at the G1/S transition (Figure 4). This suggests that, in addition to accommodating cell size checkpoints, the G1/S transition may also serve as a critical regulatory point for protein degradation and growth rate control. These findings align with previous observation of decreased variability in both cell size and growth rate at the G1/S transition (Ginzberg et al., 2018; Kafri et al., 2013; Son et al., 2012; Zetterberg and Killander, 1965). It is well established that progression through the cell cycle, including the G1/S and G2/M transitions, is controlled by ubiquitin-mediated degradation of cell cycle regulators (Barr et al., 2016; Nakayama and Nakayama, 2006). It will be important in future studies to identify the molecular mechanisms underlying the compensatory protein degradation in large cells. For example, what are the enzymes responsible for the observed increase in K48-linked polyubiquitination in larger cells during the G1/S transition? Are compensatory degradation and cyclin turnover mediated by the same, or separate, factors?

In this work, we identified a size-dependent regulation of global protein degradation that contributes significantly to proteasome-mediated degradation. We also found that both nascent proteins and long-lived proteins are targeted for degradation during compensatory growth slowdown, with the relative contribution of each depending on the cell cycle stage (Figure 3G, Figure 3—figure supplement 6). While proteasomal degradation of nascent chains is classically associated with protein quality control, our data suggest that cells leverage this pathway to modulate their growth rate and maintain cell size homeostasis. Future work employing dynamic isotopic labeling and quantitative proteomics could provide valuable insights into the degradation rates of specific proteins in this context. Two recent studies Cheng et al., 2021; Lanz et al., 2021 used such an approach and measured individual protein concentrations in cells of different sizes. Proteasome subunits were found at higher concentrations in large cells, consistent with elevated rates of ubiquitylation and protein turnover. Interestingly, components involved in translation show slightly reduced concentrations in large cells. Previous work in yeast Neurohr et al., 2019 demonstrated that oversized cells show impaired gene expression. If translation integrity is disrupted in large cells, increased levels of ubiquitin-mediated degradation may be required for the clearance of aberrant nascent polypeptides through protein quality control pathways. This is consistent with our finding that nascent proteins can significantly contribute to compensatory degradation.

Our findings provide mechanistic insight into the process of compensatory growth which, unlike cell size checkpoints, can be employed in the homeostatic size control of nonproliferating cells. This has important implications for understanding how terminally differentiated cells, which constitute the majority of cells in an adult body, maintain their size and function. Maintaining cells within their optimal size range is crucial for cellular and organ function. In adipocytes, the release of fatty acid induced by epinephrine was found to be highly dependent on the cell surface area (Zinder and Shapiro, 1971). Pancreatic beta cells undergoing hypertrophy show enhanced insulin secretion and improved glucose homeostasis in vivo (Helman et al., 2016). Across tissue types, cells dynamically control their size to modulate cell- and tissue-level functions in response to physiological demand; these include compensatory hypertrophy in pancreatic and hepatic cells (Dhawan et al., 2007; Ginzberg et al., 2015; Miettinen et al., 2014), compensatory renal cell hypertrophy following nephrectomy (Rojas-Canales et al., 2019) or increased urine flow (Boehlke et al., 2010), growth of neurons (axons) in coordination with animal development (Albus et al., 2013), and the likely regulation of functional mass of the hormone-secreting glands in response to stress (Karin et al., 2020; Karin et al., 2021). These examples highlight the importance of cell size control in nonproliferating, differentiated cells. The experimental pipeline used in this study can be adapted to study the roles of protein synthesis and degradation in cell size control of nonproliferating cells, whether certain mechanisms are shared between proliferating and nonproliferating cells, and how these processes affect cellular functions.

This study did not generate new unique reagents. All compounds were purchased from Selleckchem (SNS-032, S1145; palbociclib, S4482; bortezomib, S1013; cycloheximide, S7418; carfilzomib S2853; JNJ-26854165, S1172; barasertib, S1147). Click-IT L-azidohomoalaine was purchased from Thermo Scientific (C10102). The activity-based active proteasome probe (ABP) MV151 Bodipy-TMR was a kind gift from the Florea Lab at Leiden University. The anti-ubiquitin K48-specific antibody (Clone Apu2.07) was a kind gift from Genentech.

All data presented in this study are included in the manuscript and supporting files. Source data files have been provided for all figures.

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Author details

1. Shixuan Liu

   1. Department of Molecular Genetics, University of Toronto, Toronto, Canada
   2. Cell Biology, The Hospital for Sick Children, Toronto, Toronto, Canada
   3. Department of Chemical and Systems Biology, Stanford University, Stanford, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   shixuan@stanford.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4972-415X

2. Ceryl Tan

   1. Department of Molecular Genetics, University of Toronto, Toronto, Canada
   2. Cell Biology, The Hospital for Sick Children, Toronto, Toronto, Canada

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9010-9039

3. Chloe Melo-Gavin

   1. Department of Molecular Genetics, University of Toronto, Toronto, Canada
   2. Cell Biology, The Hospital for Sick Children, Toronto, Toronto, Canada

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

4. Miriam B Ginzberg

   Cell Biology, The Hospital for Sick Children, Toronto, Toronto, Canada

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

5. Ron Blutrich

   1. Department of Molecular Genetics, University of Toronto, Toronto, Canada
   2. Cell Biology, The Hospital for Sick Children, Toronto, Toronto, Canada

   Contribution

   Investigation, Methodology

   Competing interests

   No competing interests declared

6. Nish Patel

   Cell Biology, The Hospital for Sick Children, Toronto, Toronto, Canada

   Contribution

   Supervision, Investigation, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

7. Michael Rape

   Department of Molecular Cell Biology, University of California at Berkeley, Berkeley, United States

   Contribution

   Resources, Supervision, Investigation, Methodology, Project administration, Writing – review and editing

   Competing interests

   Reviewing Editor eLife, founder and member of the scientific advisory board of Nurix Therapeutics, a member of the scientific advisory board of Monte Rosa Therapeutics, and an iPartner with The Column Group

   "This ORCID iD identifies the author of this article:" 0000-0003-4849-6343

8. Kevin G Mark

   1. Department of Molecular Cell Biology, University of California at Berkeley, Berkeley, United States
   2. Department of Cell Biology, UT Southwestern Medical Center, Dallas, United States

   Contribution

   Resources, Data curation, Supervision, Validation, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

9. Ran Kafri

   1. Department of Molecular Genetics, University of Toronto, Toronto, Canada
   2. Cell Biology, The Hospital for Sick Children, Toronto, Toronto, Canada

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   ran.kafri@sickkids.ca

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9656-0189

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