We developed a cell culture-based assay system to measure the cis interactions between different ligand–receptor pairs (Figure 2). As a base cell line, we used CHO-K1 cells that support Notch signaling, but do not endogenously express Notch receptors and ligands. We constructed a stable CHO-K1 cell line constitutively expressing a ‘diverted’ Notch1 receptor, hN1(ΔICD)-Gal4^esn (Struhl and Adachi, 1998; Sprinzak et al., 2010) where the intracellular domain of Notch1 is replaced with yeast Gal4. This receptor activates a UAS-reporter gene but not endogenous Notch targets. Next, we stably integrated tetracycline-inducible Dll1 or Jag1 ligands fused to the Cerulean fluorescent protein, allowing us to control and read out ligand expression with the inducer 4-epitetracycline (4-epiTc) and readout the expression level by cerulean fluorescence. We denote these cell lines ‘Notch1+Dll1’ and ‘Notch1+Jag1’, respectively (Figure 2A,B).

Figure 2

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In order to analyze cis interactions in these cell lines, we induced ligand expression and measured the levels of free receptors and ligands on the cell surface. To detect Notch1 receptors, we incubated cells with saturating concentrations of a fragment of the Dll1 ligand fused to the Fc epitope (Dll1^ext-Fc, ‘Materials and methods’ and Figure 3—figure supplement 1). We established that this reagent specifically labels Notch receptors that are available to participate in trans interactions with DSL ligands, but does not label Notch-ligand cis interaction complexes (Figure 2C,D). Similarly, we used saturating concentrations of a Notch1 receptor fragment-Fc fusion protein (N1^ext-Fc) to specifically bind available ligands on the cell surface (‘Materials and methods’ and Figure 3—figure supplement 1). In both cases, we detected bound chimeric Fc ligands or receptors with a fluorescently labeled anti-Fc antibody. We used the parental Notch1 cell line to quantify receptor availability in the absence of cis-ligand, and cell lines expressing only Dll1-Cerulean or Jag1-Cerulean to quantify ligand availability in the absence of Notch1 (Figure 3—figure supplement 1). As a negative staining control, we incubated CHO-K1 cells with both the ligand and receptor availability assay reagents to establish background staining levels. We plated cells at low density to minimize trans interactions, and included only single, isolated cells in our analysis (Figure 3—figure supplement 3).

Using this assay, we first verified that receptor and ligand availability correlated with receiving and sending ability, respectively. For example, siRNA knockdown of the Notch receptor decreased Notch availability (Figure 3—figure supplement 2A) and reduced Notch activation by Dll1 ligands adhered to cell culture plate surfaces (Figure 3—figure supplement 2B). Likewise, inducing ligand expression with 4-epiTc led to both increased ligand availability (Figure 3—figure supplement 2C), and increased ability to trans-activate a Notch reporter cell line in a co-culture assay (Figure 3—figure supplement 2D).

In principle, the C-terminal fusion of CFP to the ligand could affect its trafficking or other aspects of its regulation, such as binding to proteins that interact with its PDZ domain (Pintar et al., 2007). We therefore compared the ability of untagged DSL ligands to cis inhibit Notch receptors with that of the CFP-tagged ligands. We transiently transfected either tagged or untagged ligands into our Notch receiver cells and measured the resulting decrease in receptor availability. We observed qualitatively similar results with untagged ligands as we did with the CFP fusions (Figure 3—figure supplement 4). Thus, although CFP fusions could affect other properties of DSL ligands, it does not appear to qualitatively affect the results shown here.

Next, we compared the relative abilities of Dll1 and Jag1 to cis-inhibit Notch1. We induced varying levels of ligand expression in the Notch1+Dll1 and Notch1+Jag1 cell lines, and analyzed the cells with the availability assay. These experiments produced three key observations (Figure 3):

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First, both Dll1 and Jag1 can fully cis-inhibit Notch1 receptors (Figure 2C,D, Figure 3A,B). Available Notch1 staining decreased to background levels in a dose-dependent fashion with increasing expression of either Dll1 or Jag1, indicating that both Dll1 and Jag1 ligands can fully reduce Notch availability. To confirm that this reduction in Notch availability was not an artifact of ligand overexpression, we compared wild-type Dll1 to Dll1-F199A, which contains a point mutation in the DSL domain that was previously shown to be partially deficient in trans-activation and cis-inhibition (Cordle et al., 2008). While transiently expressed wild-type Dll1-mCherry reduced Notch availability to background levels, the Dll1-F199A ligand showed only a partial reduction in Notch availability (Figure 3C).

Second, Dll1 appeared to be more potent than Jag1 as a cis-inhibitor of Notch1. We fit a simple model describing cis interactions (see Figure 1 and ‘Materials and methods’) to the single cell data from each condition, and found that approximately twice as much available Jag1 on the cell surface was needed to reduce Notch availability by 50% compared to Dll1 (Figure 3D). Dll1 is also more potent than Jag1 as an activator of Notch1 in trans (Figure 3—figure supplement 2D), suggesting the possibility that cis and trans interaction strengths between a receptor and ligand could be correlated.

Third, Notch1 reduced both Dll1 and Jag1 availability, supporting the mutual inhibition model of cis interactions for both ligands (Sprinzak et al., 2010). In the Notch1+Jag1 and Notch1+Dll1 cell lines, we observed significantly reduced ligand availability compared to corresponding ligand-only cell lines at the same levels of total ligand expression. Moreover, this effect on available ligand could be rescued by knocking down expression of Notch1 with siRNA (Figure 3E,F). Because ligand availability correlates with sending ability (Figure 3—figure supplement 2), these results support a role for Notch1 in decreasing Dll11 and Jag1 sending ability in cis, consistent with the mutual inhibition model of cis interactions.

We next asked whether and how Fringe proteins modulate cis interactions. We constructed stable Notch1+Dll1 and Notch1+Jag1 cell lines constitutively expressing Lfng, Mfng, or Rfng. These constructs increased the trans response to plate-bound Dll1 ligands and decreased the response to Jag1 (in the case of Lfng or Mfng), or increased the response to both ligands (in the case of Rfng) consistent with previous results (Hicks et al., 2000).

To analyze the effect of Fringe proteins on cis interactions, we compared Notch availability in these cell lines to parental cell lines that lack ectopic Fringe expression. For the Notch1+Dll1 cell lines expressing Lfng, Mfng, or Rfng, Notch1 availability decreased to background levels in response to increasing Dll1 expression (Figure 4A). Note that absolute levels of fluorescence in the assay increase with Fringe expression, as can be observed at low total ligand levels in Figure 4A (inset), because Fringes enhance binding of the Dll1-Fc detection reagent to available Notch1. To account for this change in binding, we normalized the curves to the level of Notch availability measured when ligand levels were uninduced. After normalizing for this change, cell lines with Fringe expression appear to have stronger cis interactions (Figure 4A). Consistent with this, available Dll1 ligand assays revealed reduced available Dll1 when any of the Fringes was expressed (Figure 4B). Together, these results suggest that all three Fringe proteins preserve, or strengthen, Notch1-Dll1 cis interactions.

Figure 4

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Fringe proteins had markedly different effects on Notch1-Jag1 cis interactions. In cell lines expressing Lfng or Mfng, even saturating expression of Jag1 was not sufficient to reduce Notch1 availability to background levels, in contrast to Dll1, indicating that Lfng and Mfng reduce cis interactions for Jag1, but not Dll1 (Figure 4C). In contrast, Rfng still allowed Notch1 availability to reach background levels at high cis-Jag1 levels. Note that here, as in Figure 4A, we observed an increased binding of the Dll1-Fc detection reagent in cell lines expressing Fringe proteins. However, when Lfng or Mfng is expressed, only Dll1, and not Jag1, is able to reduce Notch availability to background levels. In the ligand availability assay, we did not detect a significant increase in Jag1 availability due to Lfng or Mfng expression (Figure 4D). Because the basal Jag1-Notch1 cis-inhibition strength is already weak compared to the Dll1-Notch1 cis interaction strength (Figure 3D,F), the Jag1 availability assay may not be sensitive enough to detect further reductions in cis-inhibition.

Together, these results suggest that Fringe expression modulates cis-inhibition between Notch1 receptor and ligands. Lfng and Mfng preserve and possibly strengthen interactions between Notch1 and Dll1, in cis and in trans, and weaken interactions between Notch1 and Jag1, in cis and in trans, while Rfng preserves or enhances the cis interactions with both ligands. Thus, the effects of Fringe proteins on cis interactions are in the same direction (strengthening or weakening) as their effects on trans interactions.

Because Lfng or Mfng expression weakens Notch1-Jag1 cis interactions, a Lfng-expressing cell could maintain high expression levels of cis-Jag1 without compromising its ability to receive signals from trans Dll1 ligands through Notch1. To test this prediction, we used a previously developed time-lapse video assay to titrate ligand levels over time in individual cells (Figure 5A) (Sprinzak et al., 2010). We constructed cell lines constitutively expressing the diverted chimeric receptor, hN1ΔICD-Gal4^esn, and incorporating a UAS-H2B-Citrine reporter activated by Gal4 released by activated chimeric Notch1 (Figure 5B). To these cell lines we added a tetracycline-inducible Jag1-mCherry ligand. Finally, to analyze the effect of Lfng on Notch1-Jag1 cis-inhibition, we added to this parental cell line a stably integrated, constitutively expressed Lfng gene. We also constructed similar cell lines with Dll1-mCherry in place of Jag1-mCherry.

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Both parental and Lfng-expressing cell lines were seeded on plates coated with Dll1^ext-Fc recombinant protein to activate Notch1 in trans, but signaling was initially blocked with the Notch signaling inhibitor DAPT. 24 hr before the start of the video (t = −24 hr), we added 4-epiTc to induce cis-Jag1 production. 1 day later, at a time defined as t = 0, we washed out 4-epiTc and DAPT, halting further cis-Jag1-mCherry production, and allowing Notch signaling to commence. We then monitored the cells for 2 days using time-lapse fluorescent microscopy. As the cells divided, cis-Jag1 levels gradually diminished in individual cells, predominantly through dilution (Figure 5C). To measure the dependence of Notch activation on cis ligand levels, we used custom image analysis software to quantify fluorescence in individual cells in the video (‘Materials and methods’). We then plotted the rate of increase of H2B-Citrine, a measure of Notch activity, against mCherry fluorescence, a measure of total ligand abundance, for each cell.

In the parental cell lines Notch reporter activation was delayed by ∼24 hr, indicative of cis-inhibition (Figure 5D, Video 1). By contrast, the Lfng cell line responded earlier to the plate-bound Dll1^ext-Fc despite high cis-Jag1 levels, and not significantly later than in cells lacking ligand expression altogether, indicating that Lfng reduces Notch1-Jag1 cis interaction, and thereby prevents high cis-Jag1 levels from blocking Notch activation (Figure 5C,D, Video 2). In contrast, when we performed the same experiment with cell lines expressing Dll1-mCherry, we observed no corresponding relief of cis-inhibition due to Lfng, suggesting that Lfng does not weaken Dll1-Notch1 cis interactions. These results, consistent with those from the availability assay, support the finding that Lfng inhibits Jag1-Notch1, but not Dll1-Notch1, cis-inhibition.

Video 1

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Video 2

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To determine whether Fringe modulation of cis interactions occurs in a developmental context, we turned to Drosophila wing imaginal disc as a model system. Although the Notch pathway has fewer components in flies than vertebrates, the Drosophila wing disc provides a tractable system to examine related behaviors in a developmental context. Moreover, previous work has established both an effect of Fringe on trans interactions that is qualitatively similar to the mammalian Lfng and Mfng, as well as a clear role for cis-inhibition of Notch by its ligands Delta and Serrate (related to mammalian Jag1) in this process (Doherty et al., 1996; Micchelli et al., 1997; Panin et al., 1997).

The adult Drosophila wing has a smooth margin lined with bristles and is patterned with five wing veins (Figure 6A). Normal development of both the margin and the wing veins relies on spatially restricted Notch signaling. In the case of the wing margin, a sharp stripe of Notch signaling occurs at the boundary between dorsal wing cells that express Notch, Fringe, and the Delta and Serrate ligands, and ventral wing cells that express Notch and Delta. This Notch signaling drives the expression of the downstream targets E(spl), Wingless, and Cut, that proceed to further activate the expression of ligands and to direct the patterning and development of the wing margin (de Celis and Bray, 1997). The wing veins are specified by a gradient of Delta ligand expression that drives Notch signaling in two stripes of cells that form the edges of the wing veins (de Celis et al., 1997; De Celis, 2003).

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Removing one copy of Notch results in wing vein thickening and the classic ‘notched’ wing phenotypes (Figure 6B) (Mohr, 1919). If Notch and its ligands were solely involved in trans-activation, one would expect the Notch haploinsufficient phenotypes to be enhanced by a simultaneous decrease in ligand expression. However, loss of one copy of Delta was reported to suppress the Notch^+/− wing vein phenotype (de Celis and Bray, 2000), indicating that the haploinsufficient phenotypes observed in Notch^+/− animals are caused by cis-inhibition of Notch due to an increase in the relative levels of ligands to Notch.

The cell-based assays indicated that Lfng and Mfng preserve the cis-inhibition of Notch by Dll1 but weaken the cis-inhibition of Notch by Jag1. To examine whether Drosophila Fringe affects the ability of Delta and Serrate to cis-inhibit Notch in a manner similar to Lfng and Mfng, we performed genetic interaction studies in a Notch^+/− background, which seems to be more sensitive to cis-inhibition by ligands. Because the wing margin loss phenotype is only partially penetrant in Notch^+/− animals, we used a classification system to quantify this phenotype in various genotypes (Figure 6L): A wild-type wing is scored as 0, a wing with mild margin loss adjacent to the L3 wing vein is scored as 1, a wing with more extensive wing margin loss extending to L3 and L4 wing vein regions is scored as 2, and a wing with margin loss in L3-L4 and anterior regions of the wing is scored as 3. Based on this scoring system, only 40% of Notch^+/− wings show a margin defect, all of them with a score of 1 (Figure 6M).

First, we sought to examine the effects of increasing ligand gene dosage on Notch haploinsufficient phenotypes. To this end, we first generated transgenic flies harboring the Delta locus (Dl^gt-wt) or the Serrate locus (Ser^gt-wt), in which the expression of Delta or Serrate is driven by endogenous promoter/enhancers, and showed that these transgenes behave similarly to their endogenous counterparts in flies (Figure 6—figure supplement 1). Animals with one or two copies of the Dl^gt-wt transgene in a wild-type background did not exhibit any wing defects (Figure 6—figure supplement 1C and not shown). Similar effects have been observed in Dp(3;3)bxd¹¹⁰/+ flies (not shown), which harbor one copy of a homozygous lethal intrachromosomal duplication containing the Delta locus (Vassin and Campos-Ortega, 1987). However, in Notch^+/− animals, one copy of the Dl^gt-wt transgene resulted in a slight increase in the penetrance of class 1 wing margin defects and a moderate enhancement of the wing vein thickening (Figure 6C,M). Two copies of Dl^gt-wt strongly enhanced the wing vein thickening phenotype in Notch^+/− animals (Figure 6D). These animals also showed a moderate enhancement of the wing margin loss phenotype (Figure 6D,M). These observations indicate that although Delta-Notch cis-inhibition affects both wing vein and wing margin formation, Notch is more sensitive to Delta cis-inhibition during wing vein formation.

The effects of increasing the gene dosage of Serrate on the Notch haploinsufficient phenotypes were quite different from those of increasing Delta dosage. Two copies of the Ser^gt-wt transgene did not cause any wing abnormalities in a wild-type background (Figure 6—figure supplement 1D). However, one copy of Ser^gt-wt significantly enhanced the wing margin loss phenotype of Notch^+/− animals without affecting their wing vein phenotype (Figure 6E). A second copy of Ser^gt-wt further enhanced the wing margin loss (Figure 6F). Indeed, 44% of the Notch^+/−; Ser^gt-wt/Ser^gt-wt wings showed a Class 3 wing margin loss, which was not observed in any of the other genotypes analyzed in this study so far (Figure 6M). Of note, despite their severe wing margin loss, Notch^+/−; Ser^gt-wt/Ser^gt-wt animals only showed a mild enhancement of the wing vein thickening compared to Notch^+/− flies (Figure 6F, compare to Figure 6B). These observations indicate that although both Delta and Serrate can cis-inhibit Notch during wing development, Notch is more sensitive to cis-Delta during wing vein formation and more sensitive to cis-Serrate during wing margin formation.

Next we tested whether and how altering Fringe activity changed these distinct Delta and Serrate cis-inhibition phenotypes. We used fringe¹³ and fringe^L73 strains that harbor severe loss-of-function alleles with nonsense mutations in Fringe (Correia et al., 2003). Animals heterozygous for fringe have normal wings (Correia et al., 2003). However, loss of one copy of fringe alters the Notch haploinsufficient wing margin and wing vein phenotypes in opposite directions: it enhances the Serrate-dependent wing margin loss but suppresses the Delta-dependent wing vein thickening (Figure 6G,M). Addition of one copy of Serrate, but not one copy of Dl, enhances the wing margin loss in Notch^+/−; fng^+/− animals (Figure 6H,I,M). Indeed, even in fng^+/− animals with wild-type Notch gene dosage, addition of a copy of Serrate results in a low penetrance Class 1 wing margin loss (Figure 6M) and addition of two copies of Serrate enhances this phenotype by generating Class 2 wing margin loss in ∼8% of wings (Figure 6K,M). Of note, adding one or two copies of Delta does not result in any wing phenotypes in a fng^+/− background (Figure 6J,M and data not shown). If Fringe only affects the trans activation of Notch by ligands, one would expect to see increased signaling and therefore wing margin duplication in fng^+/− animals with additional copies of Serrate. However, not only do we not see an enhancement of Notch signaling in these animals, we also observe a wing margin loss which becomes more severe as we increase Serrate gene dosage. This indicates that in addition to its effect on Notch trans activation by Serrate, Fringe also regulates the cis-inhibition of Notch by Serrate. Altogether, these observations strongly support the conclusion that during Drosophila wing development, Fringe increases the sensitivity of Notch to cis-Delta but decreases its sensitivity to cis-Serrate, similar to the effect of Lfng and Mfng in the mammalian context.

The signaling states shown in Figure 7 can provide insights into developmental processes. For example, consider boundary formation in the Drosophila wing imaginal disc, a well-characterized developmental process involving both Notch ligands and Fringe (Micchelli et al., 1997; Panin et al., 1997; de Celis and Bray, 1997; Irvine, 1999; Troost and Klein, 2012). In the first stage of boundary formation, cells within the dorsal and ventral compartments of the wing disc signal to one another, forming a sharp stripe of Notch activation at the interface between the two cell populations. This Notch activity drives the expression of the Notch target genes E(spl), Wingless, and Cut, which together refine the expression patterns of Notch ligands and regulate the spatial pattern of Notch activation in subsequent stages (de Celis and Bray, 1997). For this discussion, we focus on the initial step before these feedback mechanisms become active. Dorsal cells express Notch, Delta, Serrate, and Fringe, while ventral cells express Notch and Delta only (Figure 8). Because Fringe blocks Serrate-Notch trans signaling, dorsal cells do not signal to one another with Serrate, but can signal with Serrate to ventral cells (Irvine, 1999). However, Fringe also promotes Delta-Notch trans signaling, so dorsal cells respond to Delta expressed by ventral cells. In this way, signaling can only occur at the interface between the two cell populations (Fortini, 2009).

Figure 8

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This picture of boundary formation appeared to challenge the notion that send and receive signaling states are exclusive (Figure 1A). Indeed, elegant mosaic experiments based on mis-expression of ligands (de Celis and Bray, 1997), have suggested that both dorsal and ventral cells are capable of receiving signals, that is, all cells are in a receiving state. But in order for signaling to occur, some cells must also possess the capability to send signals. Thus, it appears that some cells should be able to send and receive signal simultaneously.

Fringe modulation of cis interactions, reported above, together with a recent developmental study of this system (Troost and Klein, 2012) suggest a potential resolution to this discrepancy. Troost and Klein (2012) recently examined signaling at the boundary with higher time resolution than in previous work. They found that in the early stages of wing margin formation, signaling occurred in two sequential phases: first, dorsal cells signal via Serrate to ventral cells. Subsequently, ventral cells up-regulate Delta and signal back to dorsal cells.

In this model, because ventral cells are initially capable of receiving, they should have an excess of Notch over Delta, as shown in Figure 8B (ventral). The data presented here suggest that in dorsal cells, Fringe should strengthen cis-inhibition between Delta and Notch, while weakening cis-inhibition between Serrate and Notch. Because dorsal cells are initially in a receiving state (de Celis and Bray, 1997), Delta expressed by these cells should not efficiently activate Notch in neighboring dorsal cells. Indeed, Delta mutant clones in the dorsal compartment do not affect adult wing margin formation (Doherty et al., 1996), indicating that Delta-mediated signaling among dorsal cells, which occurs at most very weakly (Lei et al., 2003), is dispensable for normal wing margin formation. The formation of a mutually inactivating, cis-inhibitory interaction between Delta and Notch could explain why dorsal cells do not strongly activate one another even though they express and are responsive to Delta (Doherty et al., 1996; Lei et al., 2003). At the same time, Fringe could allow Serrate and Notch to both remain available simultaneously (Figure 8B, dorsal), a state resembling that in Figure 7E (far right panel). Thus, in the first phase, signaling would occur only from dorsal to ventral, as observed (Troost and Klein, 2012). It is worth mentioning that the dynamic and complex expression patterns of Notch, ligands and Fringe in developmental contexts could superimpose additional layers of regulation on the effects of Fringe on cis and trans interactions between Notch and ligands.

Notch activation in ventral cells in the first phase (Figure 8B) causes them to up-regulate Delta expression, switching them to a Delta-sending state (de Celis and Bray, 1997) (Figure 8C). In this second phase, ventral cells can trans-activate dorsal cells, which remain responsive to Delta. In principle, ventral sender cells could send to adjacent ventral cells; however it seems that at least in flies, Delta cannot send efficiently to cells that lack Fringe expression, and therefore in the flanking ventral cells Notch activity cannot achieve high enough levels to induce Cut and Wingless expression (de Celis and Bray, 1997). This interpretation requires Fringe modulation of cis interactions, as observed here, and implies that signaling during boundary formation is heterotypic (Troost and Klein, 2012). It will be interesting to see if other Notch-dependent boundary formation processes involve similar Notch signaling states and dynamics (Irvine, 1999).

These results could help explain other puzzling observations. For example, one of the most striking vertebrate Notch phenotypes is disorganized somitogenesis in Notch pathway mutants (Irvine, 1999). In mice and chicks, Lfng is required for this process (Lewis, 1998). However, Lfng inhibits Notch1-Dll1 signaling (Dale et al., 2003), rather than promoting signaling as expected from previous analysis of its effect on trans interactions (Hicks et al., 2000). The ability of Lfng to strengthen Dll1-Notch1 cis interactions could explain this phenomenon, since Lfng would tend to reduce the abundance of Dll1 and Notch1 available for trans signaling interactions.

Based on these results and others, different configurations of receptors and ligands, through cis interactions, could work to specify distinct signaling states in cells (Figure 7B–E). These states are more complex than just ‘send’ and ‘receive’ but are still highly constrained by cis interactions and the ways they can be modulated. Understanding what signaling states are possible, how expression levels of various pathway components determine those signaling states, and how cells in different signaling states interact with one another, could provide a useful way to think about the Notch signaling system more generally and to infer the directionality and specificity of signaling in more complex contexts.

However, many questions remain. We still lack systematic measurements of the interaction strengths, in cis and in trans, for the full repertoire of ligand–receptor pairs, and their quantitative dependence on Fringe expression levels. Given that multiple Fringe proteins are co-expressed in many systems, we will need to examine how Fringe proteins combine to influence Notch signaling. Fringe proteins are also known to modify the DSL ligands (Panin et al., 2002); however, a functional role for sugar modifications of the DSL ligands has not been forthcoming (Muller et al., 2014). A potential effect of these modifications on cis interactions, if it exists, would also need to be accounted for in a more complete model. Finally, additional components beyond ligands, receptors, and Fringes may need to be considered in developing a more predictive view of Notch signaling. We anticipate that the experimental approaches developed here can be generalized to address these questions and provide a deeper understanding of the basic design principles of the Notch signaling system.

CHO-K1 cells were maintained as described in Sprinzak et al. (2010). Briefly, cells were maintained in Alpha-MEM Earle's Salts media (Irvine Scientific, Santa Ana, CA) supplemented with 10% Tet-system approved FBS (Clontech, Mountain View, CA), and L-glutamine, penicillin and streptomycin additive (Gibco, Carlsbad, CA), and stored in an incubator at 37°C at 5% CO₂.

Genetic constructs, including siRNA constructs, were introduced into cells using Lipofectamine 2000 reagent according to the manufacturer's protocol (Life Technologies, Carlsbad, CA), or FugeneHD reagent (Promega, Madison, WI). Selection was performed using 400 μg/ml Zeocin (Life Technologies), 10 μg/ml Blasticidin (InvivoGen, San Diego, CA), 600 μg/ml Geneticin (Life Technologies), 500 μg/ml Hygromycin (InvivoGen) and/or 3 μg/ml Puromycin (Life Technologies) (See supplementary materials for the antibiotic resistance genes used to integrate each genetic construct). Single clones were obtained using FACS sorting or limiting dilution. Single clones were chosen based on fluorescence or quantitative PCR for non-fluorescent constructs.

The availability assay was based on the ‘binding’ assays in Shimizu et al. (1999) where soluble ligands bound to surface-expressed Notch2 receptors. Test cells were plated in 24-well plates (BD Falcon, San Jose, CA) at 25% confluence and treated with one of eight concentrations of 4-epiTc ranging from 0 to 200 ng/ml. In siRNA transfection experiments, silencing constructs were delivered after 24 hr of induction. After 48 hr of induction, cells from all 4-epiTc induction conditions were trypsinized, pooled into a single tube, and replated in triplicate at low (5–10% confluent) density. CHO-K1 and hN1(ΔICD)-Gal4^esn cell lines were also plated as staining controls. After 4–6 hr, cells were blocked for 30 min at 37°C in blocking buffer (PBS with 2% FBS and 100 μg/ml CaCl₂). Next, cells were incubated with 10 μg/ml soluble Mouse Recombinant Dll1^ext-Fc chimera (receptor availability) or Mouse Recombinant Notch1^ext-Fc chimera (ligand availability), both from R&D Systems (5267-TK and 5026-DL, respectively, Minneapolis, MN) diluted in binding buffer (PBS with 2% Sigma bovine serum albumin and 100 μg/ml CaCl₂), for 1 hr at 4°C. After incubation, cells were washed three times with binding buffer and fixed with 4% methanol-free formaldehyde (Polysciences Inc., Warrington, PA). Cells were washed three times with binding buffer and permeabilized with 0.5% Triton X-100 (Thermo Scientific, Waltham, MA) and washed three more times.

Next, cells were blocked with blocking buffer for 30 min at room temperature and then incubated for 1 hr at room temperature with the following fluorescent secondary reagents: 1:500 dilution of anti-mouse IgG conjugated to Alexa 488 (Life Technologies) to stain cell-bound recombinant protein-Fc, 1:500 dilution of anti-GFP conjugated to Alexa 594 (Life Technologies) to visualize the ligand-CFP expressed by the cells, and a 1:10 dilution of HCS Cell Mask Blue (Life Technologies) to label the cells' cytoplasm for automatic segmentation. All reagents were diluted in binding buffer. Finally, cells were washed three times with binding buffer and mounted in 70% glycerol for microscopy analysis.

Images were acquired with a CoolSnap HQ2 camera on a Nikon inverted TI-E microscope using a 20× long working distance objective. Metamorph 7.5 (Molecular Devices, Sunnyvale, CA) controlled the microscope, camera, stage (ASI instruments, Warren, MI) and brightfield and epifluorescence shutters (Sutter Instruments, Novato, CA) and collected the images. Fluorescent illumination was generated by the Sola LED light source (Lumencor, Beaverton, OR) and filtered through the Chroma filter sets SpGold, SpRed, and SpGreen. Brightfield illumination was generated by a halogen bulb.

Images were analyzed in Matlab 2012 (Mathworks, Natick, MA). First, cells were segmented on their labeling with the HCS Cell Mask Blue cytoplasmic stain. Next, total fluorescence in each fluorescence channel for each cell was calculated as follows. First, the value of the background fluorescence was computed in the neighborhood of the cell by taking the median of the unsegmented pixels in the neighborhood of the cell. Next, this background value was subtracted from each pixel's fluorescence value in the cell. Finally, all of the background-subtracted pixels were averaged to give the mean fluorescence for that cell. Image analysis code is posted on GitHub (https://github.com/llebon/image-analysis).

After this automatic processing, manual correction of the data was performed. This included imposing a gate on the segmented cell area to filter out multiple cells and segmentation errors. Next, cells were screened by eye such that cells in physical contact with another cell were rejected, and only single, isolated cells were included in the analysis.

We found that for the same measured ligand-CFP level, we obtained different levels of surface availability, suggesting the ligands reach the cell surface with different efficiencies. To account for this difference, we normalized total ligand-CFP fluorescence in the Notch1+Dll1 and Notch1+Jag1 cell lines. Total ligand was plotted as ‘Effective total ligand’.

We then plotted each cell’s effective total ligand and availability fluorescence, and grouped cells into bins logarithmically-spaced along the effective total ligand axis. We plotted the median of these bins, and used a bootstrapped estimate of the median (MATLAB function bootci) to find the 95% confidence intervals of the bin median.

The snapshots in Figure 2 were acquired on a Leica DMIRB/E fluorescence microscope with a 20× objective using the Chroma filter sets ECFP (31055v2) and EYFP (41028).

Videos were performed as described previously in Sprinzak et al. (2010). Cells were seeded onto glass-bottom plates (MatTek, Ashland, MA) coated with 5% fibronectin (Innovative Research, Novi, MI) in low-fluorescence imaging media, Alpha-MEM that includes 5% FBS and omits phenol red, riboflavin, folic acid, and vitamin B12 (Life Technologies, custom made). Cells were maintained at 37°C and 5% CO₂ in a chamber enclosing the microscope, an inverted Olympus IX81 equipped with Zero Drift Control (ZDC), a 20× NA 0.7 objective, and an iKon-M CCD camera (Andor, Belfast, NIR). All devices were controlled by Metamorph software.

Videos were analyzed in Matlab. Cell nuclei in each frame were identified automatically based on the CFP nuclear fluorescence, and the total fluorescence from each channel in each cell nuclei was recorded. Background subtraction was applied to each fluorescence value. In the plots, the average fluorescence from all of the cells in the frame is plotted vs time. Video analysis code is posted on GitHub (https://github.com/llebon/movie-analysis).

For analysis with flow cytometry, cells were dissociated with 0.25% trypsin (Life Technologies), diluted in FACS buffer (1× Hank's Balanced Salt Solution [Gibco] with 2.5 mg/ml BSA), and filtered through 40 μm strainers (BD Falcon). The cell suspension was screened for single-cell forward and side scatter and fluorescence intensity on a MacsQuant VYB instrument (Miltenyi Biotech, Bergisch Gladbach, Germany). Data was imported into Matlab 2012 for analysis. Analysis included imposing a gate on the forward and side-scatter area to omit dead cells and doublets and then analyzing the single-cell fluorescence intensity for each channel.

Quantitative PCR was used to confirm gene expression of non-fluorescent components. RNA was isolated from samples using the Qiagen RNAeasy kit according to the manufacturer's protocol. cDNA was synthesized from 1 μg of RNA using the iScript cDNA synthesis kit (Bio-Rad, Hercules, CA). For the real-time PCR reactions, 2 μl of cDNA was added to one reaction of SsoFast Probes Supermix (Bio-Rad). Each reaction was performed in triplicate. In parallel, three real-time PCR reactions were performed to measure β-actin levels in the sample, allowing us to compute a delta–delta CT value for the gene of interest in our cell lines. Reactions were performed on a Bio-Rad CFX Real-Time PCR Detection System.

Probe sets included the following:

siRNA against Notch1-ECD was delivered to cells using Lipofectamine 2000 reagent. Three dicer-substrate (dsiRNA from Integrated DNA Technologies, Coralville, IA) oligonucleotide duplexes against Notch1-ECD were pooled and 20 pmol of the mix were added to each well. IDT Universal Negative Control duplex was also transfected alongside each sample as a control.

Animals were grown in standard food at room temperature (22°C) unless specified otherwise. The following fly strains were used in this study: (1) y w, (2) Dl^9P/TM6, Tb¹, (3) N^55e11/FM7c, (4) fng¹³/TM3, Sb¹, (5) fng^L73/TM3, Sb¹, (6) Dp(3;3)bxd¹¹⁰/TM6, Tb¹, (7) Dl^RF/TM6C, Sb¹ Tb¹, (8) y¹ sc¹ v¹ P{nos-phiC31\int.NLS}X; P{CaryP}attP2, (Groth et al., 2004; Bischof et al., 2007), (9) y¹ M{vas-int.Dm}ZH-2A w*; PBac{y⁺-attP-3B}VK37 (Bloomington Drosophila Stock Center), (10) FRT 82B Ser^RX106/TM6, Tb¹, (Venken et al., 2006), (11) Ser^rev2−11/TM3, Sb¹ Ser¹, Df(3R)Ser^+R82f24 Tb¹/TM3, Sb¹ Ser¹, (Fleming et al., 1990), (12) P{Dl^gt-wt}attP2, (13) PBac{Dl^gt-wt}VK37, (14) PBac{Ser^gt-wt}VK37 (this study).

To generate a Delta genomic transgene, an 83.5-kb fragment containing the Delta locus and its flanking regions was transferred from BACR48K23 (BACPAC Resources Center, CHORI) to the attB-P[acman]-Ap^R vector by using ‘recombineering-mediated gap repair’ (Venken et al., 2009). To generate a Delta genomic transgene, an 83.5-kb fragment containing the Delta locus and its flanking regions was transferred from BACR48K23 (BACPAC Resources Center, CHORI) to the attB-P[acman]-Ap^R vector by using ‘recombineering-mediated gap repair’ (Muller et al., 2014). First, left and right homology arms (LA and RA, respectively) for the region of interest flanked by appropriate enzymes were generated by PCR using BACR48K23 as template and the following primers (restriction sites underlined):

The LA and RA were then cloned into the AscI-PacI digested attB- P[acman]-Amp^R vector via three-way ligation. The resulting construct was linearized by BamHI digestion and used to retrieve the 83.5-kb fragment from BACR48K23 by recombineering as described previously (Groth et al., 2004). All exons and exon-intron boundaries were verified by sequencing.

To generate a Serrate genomic transgene, a BAC clone with an 81.9-kb insert harboring the Serrate locus and its flanking regions was obtained from BACPAC Resources Center (attB- P[acman]-Cm^R-CH321-69C08 [Venken et al., 2009]). ΦC31-mediated integration (Venken et al., 2006; Bischof et al., 2007)was used to insert the Delta and Serrate constructs into the attP2 and VK37 docking sites and to generate the P{Dl^gt-wt}attP2 (Dl^gt-wt), PBac{Dl^gt-wt}VK37 (Dl^gt-wt) and PBac{Ser^gt-wt}VK37 (Ser^gt-wt) transgenes.

Adult wings were separated from anesthetized flies, incubated in 100% ethanol for 3 min, dried, and mounted in the DPX medium (Electron Microscopy Sciences, Hatfield PA). Wing images were obtained by using an AxioCam MRc5 camera mounted on a Zeiss Axioplan 2 microscope.

In order to interpret cis interaction measurements, we built on the model of interactions among receptors and ligands from Sprinzak et al. (2010). This model was used to generate the schematic plots in Figure 1A, as well as to fit the single-cell data in Figures 3 and 4.

The model is based on two reactions between the Notch in cell i (N_i), and its interactions with ligands in the same cell (D_i), or a neighboring cell j (D_j),

$N_i+\hspace{0.17em}{D}_j\leftrightharpoons \left[N_i{D}_j\right]\to \hspace{0.17em}{S}_i$ Trans-activation, with association and dissociation rates $k_D^{\pm }$ and activation rate k_S.

$N_i+\hspace{0.17em}{D}_{i\hspace{0.17em}}\leftrightharpoons \left[N_i{D}_i\right]\to \varnothing$ Cis-inhibition, with association and dissociation rates $k_C^{\pm }$ and inactivation rate k_I.

Notch is created with a constant rate ${\beta }_N$ and degraded at a linear rate ${\gamma }_N{N}_i.$ Ligand is produced at a constant rate ${\beta }_D$ and degraded with a linear rate ${\gamma }_D{D}_i\hspace{0.17em}$. $N_i{D}_j$ represents the complex of a Notch receptor in cell i bound to a ligand in cell j. When i = j this terms describes a cis interaction. Because we chose cell-plating conditions to isolate cis interaction, we can ignore the trans-activation terms.

These two reactions can be rewritten as a set of ordinary differential equations:

We assume that the bound cis-complex achieves a quasi-steady state $\left(\frac{d\left[N_i{D}_i\right]}{dt}\approx 0\right)$. Using this assumption, we derive the following relationship:

where $k_c^{-1}$ is defined as $\frac{k_C^{+}{k}_I}{k_C^{-}+k_I}$. The physical meaning of this expression is that available Notch receptor is a decreasing function of cis-Delta concentration. When there is no cis-Delta expression, steady state receptor levels are ${\beta }_N/{\gamma }_N$. However, as cis-Delta increases, the level of available Notch drops below this maximal value. The amount of Delta necessary to deplete Notch receptor to one half of its maximal concentration in the absence of cis-Delta is $k_c{\gamma }_N$.

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

This work was supported by the Gordon and Betty Moore Foundation through Grant GBMF2809 to the Caltech Programmable Molecular Technology Initiative; the National Science Foundation under Grant No. EFRI 1137269 and The NIH under grant R01 HD705335. We also acknowledge support from the NIH/NIGMS (R01GM084135 to HJN) and the March of Dimes Foundation (#1-FY10-501 to HJN). We thank Pulin Li, Joseph Markson, Sandy Nandagopal, Amit Lakhanpal, Emily Capra, Fangyuan Ding, and Leah Santat for technical assistance, as well as discussions and comments, Gerry Weinmaster for helpful comments on the manuscript, Yi-Dong Li and Jessica Leonardi for assistance with the generation of transgenic flies, and Robert Fleming, Shinya Yamamoto, and The Bloomington Drosophila Stock Center for fly strains.

© 2014, LeBon et al.

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