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. 2024 Dec 18;13:e103973. doi: 10.7554/eLife.103973

Drosulfakinin signaling encodes early-life memory for adaptive social plasticity

Jiwon Jeong 1,, Kujin Kwon 2,, Terezia Klaudia Geisseova 1, Jongbin Lee 3, Taejoon Kwon 2,4,5,, Chunghun Lim 3,6,7,
Editors: John Ewer8, Claude Desplan9
PMCID: PMC11706606  PMID: 39692597

Abstract

Drosophila establishes social clusters in groups, yet the underlying principles remain poorly understood. Here, we performed a systemic analysis of social network behavior (SNB) that quantifies individual social distance (SD) in a group over time. The SNB assessment in 175 inbred strains from the Drosophila Genetics Reference Panel showed a tight association of short SD with long developmental time, low food intake, and hypoactivity. The developmental inferiority in short-SD individuals was compensated by their group culturing. By contrast, developmental isolation silenced the beneficial effects of social interactions in adults and blunted the plasticity of SNB under physiological challenges. Transcriptome analyses revealed genetic diversity for SD traits, whereas social isolation reprogrammed select genetic pathways, regardless of SD phenotypes. In particular, social deprivation suppressed the expression of the neuropeptide Drosulfakinin (Dsk) in three pairs of adult brain neurons. Male-specific DSK signaling to cholecystokinin-like receptor 17D1 mediated the SNB plasticity. In fact, transgenic manipulations of the DSK neuron activity were sufficient to imitate the state of social experience. Given the functional conservation of mammalian Dsk homologs, we propose that animals may have evolved a dedicated neural mechanism to encode early-life experience and transform group properties adaptively.

Research organism: D. melanogaster

Introduction

Animals interact with other individuals in distinct social environments (Clutton-Brock, 2021; Jezovit et al., 2021; Sokolowski, 2010). For instance, a pair of animals display aggression or mating behaviors, whereas a group of individuals may show collective behaviors through intricate networks of social interactions. Such social network behaviors (SNBs) are believed to enhance group fitness and are conserved across many species, underscoring their evolutionary significance (Sokolowski, 2010; Blumstein et al., 2010). Additionally, social interactions influence various physiological activities in individuals, including feeding, sleep/circadian rhythms, aggression, stress response, and longevity (Levine et al., 2002; Ganguly-Fitzgerald et al., 2006; Arzate-Mejía et al., 2020; Li et al., 2021; Chen and Sokolowski, 2022; Vora et al., 2022; Xiong et al., 2023). Nonetheless, it remains elusive how group properties have evolved with other individual traits and how animals process social experiences to shape their behavior and physiology.

Drosophila has long been considered a solitary species. Yet a group of flies can display distinct SNB under specific experimental conditions (Schneider et al., 2012; Simon et al., 2012; Ramdya et al., 2015; Dombrovski et al., 2017; Sun et al., 2020; Burg et al., 2013), serving as an ideal genetic model to address our questions above (Jezovit et al., 2021). Previous studies have employed various biophysical parameters to quantify both individual and network behaviors in groups, establishing criteria for social interactions in Drosophila (Jezovit et al., 2021; Simon et al., 2012; Ramdya et al., 2015; Bentzur et al., 2021). While these measurements give a comprehensive view of group behaviors, our study focuses on the clustering property of social interactions within a group (Simon et al., 2012; Jiang et al., 2020). Social clustering is an intuitive measure that integrates diverse social interactions via multiple sensory cues (Schneider et al., 2012; Simon et al., 2012; Bentzur et al., 2021; Jiang et al., 2020), accompanying reductions in social distance (SD) among group members and their moving speed over time. We also reasoned that simple SD assessment could facilitate the alignment of large-scale datasets of group behaviors with physiological traits, differential gene expression, and neurogenetic manipulations.

These approaches lead to our demonstration that the group property for high social clustering (i.e., short SD) is closely associated with and compensates for inferior developmental traits in individuals. Moreover, Drosophila can adjust their social preferences according to physiological changes, indicating the adaptive plasticity of SNB. This social plasticity requires early-life social experiences that persist throughout development. We also define a specific neuropeptide signaling pathway that encodes social memory and supports SNB plasticity. Our findings thus provide new insights into the principles of SNB, offering a deeper understanding of the evolutionary and genetic bases of social behaviors in Drosophila and possibly other species.

Results

SNB is a quantitative trait in a natural Drosophila population

We employed the Drosophila Genetics Reference Panel (DGRP) to determine whether SNB has evolved with specific genetic factors and physiology. The DGRP consists of approximately 200 inbred wild-type strains and functions as a practical genetic library to explore the correlation between naturally occurring genetic variations and complex animal behaviors (Mackay et al., 2012; Mackay and Huang, 2018; Gardeux et al., 2024). We video-recorded a group of 16 male flies freely moving in an open arena for 10 min and quantitatively assessed their group properties over time (Figure 1A). These included SD between individual group members (Figure 1B), walking speed, and the centroid velocity of a given group. The DGRP lines displayed a range of distributions for the three parameters (Figure 1C, Figure 1—source data 1), and we found their significant correlations among 175 DGRP lines (Figure 1D, Figure 1—source data 1; Spearman correlation analysis). For instance, short-SD lines gradually reduced SD and walking speed over time to stay in the cluster, thereby exhibiting short travel distances, slow walking speeds, and low centroid velocities on average (e.g., DGRP73, DGRP 563, and DGRP370) (Figure 2A, Figure 2—figure supplement 1, Figure 2—source data 1, Video 1). By contrast, long-SD lines persistently explored the arena during video recording and sustained ‘social distancing’ to display long travel distances, fast walking speeds, and high centroid velocities (e.g., DGRP360, DGRP707, and DGRP317) (Figure 2B, Figure 2—figure supplement 1, Figure 2—source data 1, Video 2), although their locomotion was modestly slowed down over time. The locomotion trajectories of individual flies confirmed these characteristics (Figure 2C and D, Figure 2—source data 1), and long-SD individuals traveled much longer distances than short-SD individuals across the DGRP lines (Figure 2—figure supplement 1C, Figure 2—source data 1). Short-SD flies did not significantly change their locomotor activity over time when we placed a single fly in the same arena and assessed its behavior (Figure 2—figure supplement 2, Figure 2—source data 1). Thus, reduced activity in a group of short-SD flies is likely an effect of their clustering phenotypes but not necessarily the cause. Short- and long-SD flies retained their clustering properties even in a larger arena (Figure 2—figure supplement 3, Videos 3 and 4; 8.5 cm in diameter), indicating active social preferences that persist in different environments. Both types of DGRP lines displayed no chaining behaviors in the open arena, excluding the possible implication of male-to-male courtship in their SD phenotypes (Figure 2—figure supplement 4, Figure 2—source data 1). These results provide convincing evidence that SD is an inheritable group trait from natural Drosophila variants. Based on the average ranking of individual DGRP lines in the two group properties (i.e., SD and centroid velocity), we selected the top and bottom three DGRP lines representing short- and long-SD phenotypes, respectively, to elucidate the physiological significance of Drosophila SNB and its underlying mechanisms.

Figure 1. Social network behavior (SNB) is a quantitative trait in a natural Drosophila population.

Figure 1.

(A) The 10 min video recording of SNB in a group of 16 male flies. Representative snapshot images at each quarter time point (Q1, Q2, Q3, and Q4) were obtained from Drosophila strains with high (top, short social distance [SD]) or low clustering properties (bottom, long SD). (B) The definition of SD. SD was measured in each fly over the 10 min recording and averaged from a given group. Representative SD dynamics from short- (top) or long-SD strains (bottom) were shown. Dotted lines, group-averaged SD over the 10 min recordings. (C) Quantitative assessment of SNB by ranking SD, walking speed, and centroid velocity among 175 DGRP lines. Data represent means ± SEM (n = 5). (D) Significant correlation among SD, walking speed, and centroid velocity. ***p<0.001, as determined by Spearman correlation analysis. Red, representative short-SD lines; blue, representative long-SD lines.

Figure 1—source data 1. Correlation of SD, walking speed, and centroid velocity across 175 DGRP lines.

Figure 2. Short- and long-social distance (SD) lines exhibit distinct social network behavior (SNB).

(A, B) SNB dynamics in short-SD (A) and long-SD lines (B). SD dynamics in a representative group of 16 male flies over the 10 min recordings (left, n = 16), quarter-averaged SD (middle, n = 8), and quarter-averaged walking speed (right, n = 8) were shown for each Drosophila Genetics Reference Panel (DGRP) line. Error bars indicate SEM. n.s., not significant; *p<0.05, **p<0.01, ***p<0.001 as determined by paired t-test (DGRP73, DGRP563, DGRP370, DGRP707, and DGRP317 for quarter-averaged SD; DGRP563, DGRP360, and DGRP317 for quarter-averaged walking speed) or Wilcoxon matched-pairs signed rank test (DGRP360 for quarter-averaged SD; DGRP73, DGRP370, and DGRP707 for quarter-averaged walking speed). (C) The 10 min locomotion trajectories of representative individual flies from short- (red) or long-SD lines (blue). (D) Cumulative travel distances of individual flies over the 10 min recording. Colored lines represent means (n = 128).

Figure 2—source data 1. Quantitative locomotor metrics in short- and long-SD DGRP lines.

Figure 2.

Figure 2—figure supplement 1. Social network behaviors in the three representative Drosophila Genetics Reference Panel (DGRP) lines displaying short or long social distance (SD).

Figure 2—figure supplement 1.

(A) Centroid trajectories of short- (red; DGRP73, 563, 370) or long-SD lines (blue; DGRP360, 707, 317) over the 10 min video recording. (B) The short-SD lines exhibit slow walking speeds and low centroid velocities compared to the long-SD lines. Social isolation significantly impaired SNB only in the short-SD lines. Data represent means ± SEM (n = 8). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by unpaired t-test. (C) Long-SD individuals show longer travel distances than short-SD ones during the 10 min video recording. Data represent means ± SEM (n = 8 for averaged data; n = 128 for individual data). ***p<0.001 as determined by ordinary one-way ANOVA with Tukey’s multiple comparisons test (averaged data) or aligned ranks transformation ANOVA with Wilcoxon rank-sum test (individual data).
Figure 2—figure supplement 2. Neither short- nor long-social distance (SD) lines reduce their walking speeds over time when individual flies from group cultures are isolated.

Figure 2—figure supplement 2.

A single male fly from each Drosophila Genetics Reference Panel (DGRP) line was placed in the arena for social network behaviors (SNB) analysis and video-recorded for 10 min to quantify its locomotor activity. Data represent means ± SEM (n = 20). n.s., not significant; *p<0.05, **p<0.01, as determined by Wilcoxon matched-pairs signed rank test (DGRP73, DGRP563, DGRP370, and DGRP360) or paired t-test (DGRP707 and DGRP317).
Figure 2—figure supplement 3. The clustering property of each Drosophila Genetics Reference Panel (DGRP) line persists in a large arena.

Figure 2—figure supplement 3.

A group of 16 male flies was placed in a large arena (8.5 cm in diameter), and their locomotor behaviors were video-recorded for 10 min. Representative snapshot images were obtained at each quarter of the 10 min recording. The heatmap illustrates the relative distribution of individual flies in the arena.
Figure 2—figure supplement 4. Neither short- or long-social distance (SD) lines display male–male courtship behavior.

Figure 2—figure supplement 4.

(A) A representative snapshot image of courtship chaining behavior (dotted circle) in a group of rut1 mutant flies. (B) The chaining index was calculated from the 10 min video-recording of 16 male flies in the arena. Data represent means ± SEM (n = 8). Drosophila Genetics Reference Panel (DGRP) lines did not display any detectable courtship chaining behavior.

Video 1. Social network behavior (SNB) in DGRP73 (grp+ctrl).

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Video 2. Social network behavior (SNB) in DGRP360 (grp+ctrl).

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Video 3. Social network behavior (SNB) in DGRP73 (large arena).

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Video 4. Social network behavior (SNB) in DGRP360 (large arena).

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Social interactions compensate for developmental inferiority in short-SD larvae

Why do flies display SNB? One clue comes from the previous observation that Drosophila larvae collectively dig culture media and improve food accessibility, possibly facilitating their constitutive feeding during early development (Dombrovski et al., 2017). In fact, we found that the short-SD lines had higher numbers of larvae per cluster than the long-SD lines (Figure 3A, Figure 3—source data 1). These observations suggest that Drosophila express SNB traits from early development, and the sociality persists in adults. To better define the social-interaction effects on Drosophila physiology, we obtained socially enriched or deprived larvae from fertilized eggs (Figure 3B) and then compared their developmental phenotypes among DGRP lines. Social isolation substantially impaired larval activity and development in both short- and long-SD lines (Figure 3C–G, Figure 3—source data 1). We further found that the short-SD trait is tightly associated with inferior phenotypes, particularly in isolated larvae. For instance, socially isolated larvae from the short-SD lines displayed poor digging activity (Figure 3C, Figure 3—source data 1), low food intake (Figure 3D, Figure 3—source data 1), and long developmental time (Figure 3E, Figure 3—source data 1) compared to those from the long-SD lines. Short-SD larvae also had lower eclosion success (Figure 3F, Figure 3—source data 1) and a lower ratio of the adult male progeny (Figure 3G, Figure 3—source data 1) than long-SD larvae, although isolated cultures reduced the eclosion success regardless of the SD trait. Grouping of short-SD larvae blunted or partially rescued these phenotypes (i.e., digging activity, developmental time, eclosion success, and male progeny ratio). Our group culture was not a competitive environment for limited resources to delay developmental time (Horváth and Kalinka, 2016; Klepsatel et al., 2018), but it actually promoted food intake comparably in short- and long-SD larvae (Figure 3D, Figure 3—source data 1). The significant interaction effects of SD (i.e., short- vs. long-SD trait) and socialization (i.e., grouped vs. isolated cultures) on digging activity, developmental time, and male progeny ratio suggest that the clustering property of short-SD lines may have evolved as a compensation mechanism for the developmental inferiority in individuals. Considering that a low percentage of male likely limits mating choice, reproductive efficiency, and genetic diversity in a given group, social interactions may also contribute to the group fitness in short-SD lines across generations. We speculate that the feeding amount of isolated long-SD individuals is saturating for normal development (e.g., developmental time, male progeny ratio), possibly explaining the lack of interaction effects on food intake while displaying developmental inferiorities most evidently in isolated short-SD individuals.

Figure 3. Early-life social experience confers beneficial effects on Drosophila development.

Figure 3.

(A) Larval clustering in short- (red) or long-social distance (SD) lines (blue). % clusters were calculated from 30 vials. Arrows indicate individual larvae. Scale bar = 0.5 mm. (B) Schematic for grouped (grp) vs. developmentally isolated (iso) culture conditions. (C, D) Grouped culture compensated for low food accessibility in the short-SD larvae. Aligned ranks transformation ANOVA detected significant effects of SD trait and social isolation on both digging depth (C, p<0.0001) and food intake (D, p<0.0001), and their significant interaction effects were detected only on digging depth (C, p=0.0338). Data represent means ± SEM (n = 36; 12 per line × 3 lines). ***p<0.001, as determined by Wilcoxon rank sum test. (E–G) Grouped culture rescued developmental delay and low male-progeny ratio in the short-SD larvae. Aligned ranks transformation ANOVA or ordinary two-way ANOVA detected significant effects of SD trait and social isolation on developmental time (E, p<0.0001), eclosion success (F, p=0.0116 for SD trait; p<0.0001 for social isolation), and male progeny ratio (G, p<0.0001). Significant interaction effects between SD trait and social isolation were also detected on developmental time (E, p<0.0001) and male progeny ratio (G, p<0.0001). Data represent means ± SEM (n = 24; 8 per line × 3 lines). n.s., not significant; *p<0.05, ***p<0.001, as determined by Wilcoxon rank sum test (developmental time and male progeny ratio) or Tukey’s multiple comparisons test (eclosion success).

Figure 3—source data 1. Quantitative analysis of larval SNB and developmental metrics.

Early-life experience is necessary for social benefits on adult physiology and adaptive social plasticity

We further asked whether social interactions also benefit adult physiology in the short-SD lines. To this end, we designed a maze experiment where a group of flies were placed in a novel arena to determine how fast they could reach a food resource in the presence or absence of pretrained flies (Figure 4A). Our prediction was that social interactions between naïve and trained flies might facilitate their food-seeking, possibly mimicking social foraging in other species (Giraldeau and Caraco, 2000). We first confirmed that both short- and long-SD lines significantly shortened latency to the arrival of 75% of flies on food by iterative exposures to the maze (Figure 4B, Figure 4—figure supplement 1, Figure 4—source data 1). Representative plasticity mutants of the rutabaga (rut) gene did not significantly shorten the arrival latency after three consecutive training sessions in our maze paradigm (Figure 4—figure supplement 2A, Figure 4—source data 1), implicating rut-dependent learning and memory in this process (Levin et al., 1992). The short-SD lines displayed poor performance in the maze assay as assessed by longer latency to the arrival of 75% naïve flies on food than the long-SD lines (Figure 4B, Figure 4—figure supplement 1, Figure 4—source data 1). Combining the trained ‘pioneers’ with a group of naïve flies significantly improved the group property of food-seeking behaviors in both short- and long-SD lines (Figure 4B, Figure 4—figure supplement 1, Figure 4—source data 1). The pioneer effects disappeared when the naïve group consisted of socially isolated individuals from egg development. These results support that social foraging in our maze paradigm is unlikely a simple collective response in adults, but it specifically requires early-life social experience. Of note, social deprivation effects on pioneer-free group foraging somewhat varied across the long SD lines (Figure 4B, Figure 4—figure supplement 1, Figure 4—source data 1). We reason that the hyperactivity of individual long-SD flies facilitates their food-seeking behaviors in the maze, weakening the pioneer effects or even overriding the group property.

Figure 4. Early-life social experience confers beneficial effects on social foraging in adult Drosophila.

(A) Experimental scheme for assessing social interactions in a maze assay. Representative images were shown for a group of Drosophila strains with high (short latency) or low social foraging (long latency). (B) Pioneer groups of flies from either grouped (grp) or isolated cultures (iso) were effectively trained in the maze assay, but social isolation of both short- (red, DGRP73) and long-SD flies (blue, DGRP360) blunted the pioneer effects on food-seeking behaviors in a group of naive flies. Two-way repeated measures ANOVA detected significant effects of training (p<0.0001 for DGRP73 and DGRP360) but not social isolation on latency during the training session of pioneer groups. Ordinary two-way ANOVA also detected significant interaction effects of pioneer and social isolation on latency during the maze test (p=0.0131 for DGRP73; p=0.0310 for DGRP360). Data represent means ± SEM (n = 6‒16). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by Sidak’s multiple comparisons test (training session) or Tukey’s multiple comparisons test (maze test). (C) Experimental scheme for assessing injury-induced social network behavior (SNB) plasticity. GTI, grouped-to-isolated culture transition; ITG, isolated-to-grouped culture transition. (D) Physical injury induced clustering behaviors in group-cultured but not developmentally isolated flies. Data represent means ± SEM (n = 8). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by one-way ANOVA with Tukey’s multiple comparisons test.

Figure 4—source data 1. Quantitative analysis of adult SNB and social plasticity.

Figure 4.

Figure 4—figure supplement 1. Social isolation blunts pioneer effects on food-seeking behaviors in a group of naive flies.

Figure 4—figure supplement 1.

Pioneer groups of short- (DGRP563 and DGRP370) and long-social distance (SD) lines (DGRP707 and DGRP317) were effectively trained in the maze assay but they failed to improve the efficiency of food-seeking behaviors with groups of socially isolated flies. Data represent means ± SEM (n = 6–12). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by two-way repeated measures ANOVA with Sidak’s multiple comparisons test (pioneer training) or two-way ANOVA with Tukey’s multiple comparisons test (group test). Grp, grouped; iso, isolated.
Figure 4—figure supplement 2. Rutabaga-dependent working memory is dispensable for social memory.

Figure 4—figure supplement 2.

(A) Plasticity mutants of rutabaga (rut1 and rut2080) fail to improve food-seeking behaviors in the maze after repetitive trainings. Canton-S (CS) served as a wild-type control. Data represent means ± SEM (n = 9 for rut1; n = 8 for rut2080). n.s., not significant; **p<0.01, ***p<0.001, as determined by paired t-test. (B) rut mutants display injury-induced clustering comparable to control flies. Social distance (SD) was measured in group-cultured male flies under distinct experimental conditions (ctrl, control; inj, injured). Two-way ANOVA detected no significant interaction effects of genotype and inj on SD. Data represent means ± SEM (n = 8 for rut1; n = 10 for rut2080). *p<0.05, **p<0.01, as determined by Tukey’s multiple comparisons test.
Figure 4—figure supplement 3. Early-life social experience is necessary for social behavior plasticity in male flies.

Figure 4—figure supplement 3.

(A) Physical injury induced clustering behaviors in group-cultured but not developmentally isolated flies. Social distance (SD) was measured in a group of male flies under distinct experimental conditions (ctrl, control; inj, injured; rec, recovered; grp, grouped; iso, isolated; GTI, grouped-to-isolated culture transition; ITG, isolated-to-grouped culture transition). Data represent means ± SEM (n = 8). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by one-way ANOVA with Tukey’s multiple comparisons test. (B) Female flies did not display injury-induced clustering. SD was measured in group-cultured female flies from individual Drosophila Genetics Reference Panel (DGRP) lines. Data represent means ± SEM (n = 8). n.s., not significant as determined by one-way ANOVA with Tukey’s multiple comparisons test.
Figure 4—figure supplement 4. Mechanical injury reduces walking speed and centroid velocity only in group-cultured long-social distance (SD) flies.

Figure 4—figure supplement 4.

Locomotor activities were quantified in a group of long- and short-SD male flies under distinct experimental conditions (ctrl, control; inj, injured; rec, recovered; grp, grouped; iso, isolated). Two-way ANOVA detected significant interaction effects of inj and iso on walking speed and centroid velocity only in long-SD lines (***p<0.001 for DGRP360 and DGRP707; *p<0.05 for DGRP317, except centroid velocity). Data represent means ± SEM (n = 8). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by Tukey’s multiple comparisons test.
Figure 4—figure supplement 5. Loss of norpA function blocks injury-induced clustering in group-cultured male flies.

Figure 4—figure supplement 5.

Social distance (SD) was measured in a group of male mutants for each sensory-pathway gene as described in Figure 1. Data represent means ± SEM (n = 8). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by two-way ANOVA with Tukey’s multiple comparisons test. Ctrl, control; inj, injured.

The long-SD lines outcompeted the short-SD lines in both larval and adult assays, and the beneficial effects of their social experience were barely detectable. SNB in the long-SD adults was also insensitive to early-life experience, whereas the grouped culture promoted SNB in the short-SD lines (Bentzur et al., 2021; Figure 2—figure supplement 1B, Figure 2—source data 1). We hypothesized that superior traits in long-SD individuals led to their genetic selection toward the degeneration of social interaction effects. Alternatively, long-SD genomes may still encode genetic programs for social activity, but they only express social traits under physiologically challenging conditions. Given the positive correlation between locomotion activity and SD trait among DGRP lines (Figure 1D, Figure 1—source data 1), we reasoned that modest injury could serve as a physiological cue to reduce locomotor activity in individuals, facilitate their interactions in a group, and induce SNB even in the long-SD flies. We indeed discovered that mechanical injury shortened SD in both sociality types of DGRP lines (Figure 4C and D, Figure 4—figure supplement 3A, Figure 4—source data 1; Videos 5 and 6;) while reducing walking speed and centroid velocity only in the long-SD lines (Figure 4—figure supplement 4, Figure 4—source data 1). The injury effects were transient because 1 week of recovery was sufficient to restore the original SD traits (Figure 4D, Figure 4—figure supplement 3A, Figure 4—source data 1). The injury-induced plasticity of SNB and locomotor activity was not detectable in a group of socially isolated flies (Figure 4D, Figure 4—figure supplements 3A and 4, Figure 4—source data 1, Videos 710). We thus reason that the mechanical injury does not severely impair general locomotion per se to abolish or overestimate SNB under our experimental conditions, but low activity in grouped long-SD flies is likely a consequence of their injury-induced clustering. The injury-induced SNB plasticity required no receptor potential A (norpA) among sensory pathway genes tested (Figure 4—figure supplement 5, Figure 4—source data 1), indicating a crucial role of norpA-dependent visual sensing. It is consistent with the previous finding that vision is required for larval clustering behaviors in Drosophila (Dombrovski et al., 2017). We further found that an adult-specific grouping of developmentally isolated flies was insufficient to support the social plasticity (Figure 4D, Figure 4—figure supplement 3A, Figure 4—source data 1). Finally, the rut-dependent memory pathway seems dispensable for developmental ‘social memory’ since rut mutants displayed injury-induced social plasticity comparable to control flies (Figure 4—figure supplement 2B, Figure 4—source data 1). These results suggest that individual Drosophila strains differentially display social traits in adults; however, the potency of adaptive social plasticity is acquired through their early-life experience of social interactions.

Video 5. Social network behavior (SNB) in DGRP73 (grp+inj).

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Video 6. Social network behavior (SNB) in DGRP360 (grp+inj).

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Video 7. Social network behavior (SNB) in DGRP73 (iso+ctrl).

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Video 8. Social network behavior (SNB) in DGRP360 (iso+ctrl).

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Video 9. Social network behavior (SNB) in DGRP73 (iso+inj).

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Video 10. Social network behavior (SNB) in DGRP360 (iso+inj).

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Unraveling the genetic basis of SNB and its plasticity

How is early-life social experience encoded in individual larvae to persist throughout development? To define the molecular signatures of social interaction phenotypes and their plasticity, we profiled differentially expressed genes (DEGs) in adult fly heads among distinct contexts of genetic and environmental sociality. The transcriptome analyses revealed significantly upregulated genes in the short- and long-SD lines (n genes = 191 and 199, respectively), as well as in grouped and socially isolated flies (n genes = 159 and 755, respectively) (Figure 5A and B, Figure 5—source data 1,Figure 5—source data 2). Genes upregulated in socially isolated DGRP lines overlapped substantially with those identified in previous studies using independent wild-type strains (Li et al., 2021; Wang et al., 2008; Agrawal et al., 2020; Figure 5—figure supplement 1A, Figure 5—source data 3), whereas upregulated genes in short- or long-SD lines barely overlapped with DEGs between grouped and socially isolated flies (Figure 5—figure supplement 1B, Figure 5—source data 3). Gene Ontology (GO) analyses showed no significant enrichment of specific GO terms in DEGs between the short- and long-SD lines. We thus concluded that diverse genetic pathways shape baseline SD phenotypes, as suggested previously (Schneider et al., 2012). It is also consistent with the lack of the phylogenetic correlation between Drosophila species and their social network phenotypes (Jezovit et al., 2020). By contrast, select metabolic pathways were upregulated in both types of DGRP lines by social isolation (Figure 5C and D, Figure 5—source data 2;Figure 5—source data 4). These observations were consistent with previous findings that chronic social isolation acts as a hunger cue to suppress sleep, induce feeding, and alter metabolic gene expression, including those involved in lipid metabolism (Li et al., 2021; Liu et al., 2018). Considering that the number of commonly upregulated genes in group-cultured flies was very limited, we speculate that Drosophila has evolved a genetic reprogram where social isolation elevates metabolic gene expression to adaptively induce a metabolic shift for energy storage and fitness.

Figure 5. Social experience shapes gene expression profiles in Drosophila heads.

(A) Heatmaps for differentially expressed genes (DEGs, more than twofold difference with adjusted p<0.05) in short- vs. long-social distance (SD) lines (left); in grouped (grp) vs. isolated (iso) condition (right). Fly heads were harvested from individual Drosophila Genetics Reference Panel (DGRP) lines in grouped or isolated cultures and their gene expression profiles were analyzed by RNA sequencing. Averaged counts per million were converted to z-score for visualization. (B) Volcano plots for differentially expressed genes (DEGs) in short- vs. long-SD lines (top); in grp vs. iso flies (bottom). Social interactions evidently upregulated the neuropeptide Drosulfakinin (Dsk) expression. (C) Overlapping DEGs in grp vs. iso conditions across DGRP lines. Dsk was identified as a commonly upregulated gene by social interactions in short- (top, red) and long-SD lines (middle, blue). (D) Gene Ontology analysis reveals upregulation of select metabolic pathways upon social isolation. False discovery rate (FDR) < 0.05, as determined by Fisher’s exact test (grp vs. iso). (E) Significant phenotypic correlation of SNB to food intake, starvation-induced activity, and mean aggressive encounters among DGRP lines. Raw data for food intake (n = 52 DGRP lines), starvation-induced activity (n = 60 DGRP lines), and aggression (n = 57 DGRP lines) were obtained from previous studies (Garlapow et al., 2015; Shorter et al., 2015; Chi et al., 2021) and then aligned to SD, centroid velocity, and walking speed in the corresponding DGRP lines that were measured by our SNB analyses. *p<0.05, **p<0.01, ***p<0.001, as determined by Spearman correlation analysis. (F) Expression heatmap for genes implicated in feeding, adult locomotor behavior, and aggression. Downregulation of Dsk and its two receptors (CCKLR-17D1 and CCKLR-17D3) by social isolation was visualized in relevant gene categories.

Figure 5—source data 1. Normalized gene expression in individual DGRP lines under grouped vs. isolated culture conditions.
Figure 5—source data 2. DEG analyses between distinct social groups (short vs. long SD; or grouped vs. isolated).
Figure 5—source data 3. Comparative analyses of social group-specific DEGs from independent studies.
Figure 5—source data 4. DEG analyses among individual DGRP lines.
Figure 5—source data 5. Correlation of SNB to food intake, starvation-induced activity, and aggression among DGRP lines.

Figure 5.

Figure 5—figure supplement 1. Cross-study analyses of social context-dependent differentially expressed genes (DEGs) highlight Dsk as the most prominently upregulated gene under socially enriched conditions.

Figure 5—figure supplement 1.

(A) Venn diagrams depict the numbers of upregulated genes under grouped (top, grp) and socially isolated conditions (bottom, iso), as identified by the previous and current studies. The numbers of overlapping DEGs between independent gene expression analyses were shown accordingly. (B) Venn diagrams illustrate the overlap of DEGs between short-social distance (SD) lines and group-culturing conditions (top, short SD vs. grp) and between long-SD lines and socially isolated conditions (bottom, long SD vs. iso).
Figure 5—figure supplement 2. Long-social distance (SD) flies display higher aggression than short-SD flies.

Figure 5—figure supplement 2.

A pair of male flies from each Drosophila Genetics Reference Panel (DGRP) line were starved for 6 hr and then placed into a circular arena with yeast paste and a female carcass in the center. The number of lunges was counted during the 10 min video recording. Data represent means ± SEM (n = 6). *p<0.05, as determined by one-way ANOVA with Tukey’s multiple comparisons test.

Interestingly, the phenotypic alignment of DGRP lines revealed significant correlations of their social interaction behaviors to food intake, starvation-induced activity, and aggression, among others (Garlapow et al., 2015; Shorter et al., 2015; Chi et al., 2021; Figure 5E, Figure 5—source data 5). We validated that the long-SD lines showed more lunges than the short-SD lines, indicative of high aggression behaviors (Figure 5—figure supplement 2, Figure 5—source data 5, Videos 11 and 12). The association of multiple behaviors raised the possibility of their overlapping evolution of regulatory genes and mechanisms. The expression heatmaps of relevant gene categories visualized a subset of genes that indeed displayed social experience-dependent expression across the DGRP lines analyzed (Figure 5F, Figure 5—source data 1). These included Drosulfakinin (Dsk), a neuropeptide implicated in aggression, food intake, satiety, and sexual behaviors (Agrawal et al., 2020; Wu et al., 2019; Wu et al., 2020; Guo et al., 2021; Wang et al., 2022). The mammalian Dsk homolog cholecystokinin (CCK) has also been shown to play a similar role in relevant physiology, suggesting the possible conservation of Dsk function (Nichols et al., 1988; Staljanssens et al., 2011; Nässel and Wu, 2022). In fact, Dsk was the only overlapping gene that was downregulated upon social isolation across independent studies (Li et al., 2021; Wang et al., 2008; Agrawal et al., 2020; Figure 5—figure supplement 1A, Figure 5—source data 3). We also found that social isolation of the DGRP lines significantly downregulated the expression of Dsk and the two CCK-like receptors (i.e., CCKLR-17D1 and CCKLR-17D3), although Dsk receptor gene expression showed less than twofold change (Figure 5F, Figure 5—source data 2). These observations prompted us to ask whether DSK signaling contributes to the plasticity of social behaviors through early-life experience.

Video 11. Aggression behaviors in DGRP73.

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Video 12. Aggression behaviors in DGRP360.

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DSK neuron activity encodes early-life experience for SNB plasticity

Immunostaining of whole-mount brains identified three groups of DSK-expressing neurons with distinct neuroanatomical morphology (i.e., MP1a, MP1b, and MP3) (Wu et al., 2019; Wu et al., 2020; Figure 6A). The long-SD lines displayed relatively high DSK signals in the cell bodies compared to the short-SD lines (Figure 6B, Figure 6—source data 1). However, DSK levels in the neural projections were comparable between the two groups, raising the possibility that axonal transport or processing of the neuropeptide was limiting under the group-culture condition. Social isolation lowered DSK levels irrespective of the SD phenotype (Figure 6A and B, Figure 6—source data 1), consistent with our DEG analysis above. The social experience effects on DSK levels were most evident in the MP1a neuron projections. Live-brain imaging of the genetically encoded Ca2+ indicator GCaMP showed that DSK neuron activity correlated with social experience and plasticity in a wild-type background. Social deprivation reduced relative Ca2+ levels in DSK neurons, whereas mechanical injury generally elevated DSK neuron activity (Figure 6C, Figure 6—source data 1). The two conditions, however, acted independently on the GCaMP signals in DSK neurons since their interaction effects were not significantly detected. Nonetheless, MP1a neuron activity did not respond to injury when transgenic flies were socially deprived during development, which may contribute to the lack of social behavior plasticity upon isolation (Figure 6C, Figure 6—figure supplement 1, Figure 6—source data 1). These observations are unlikely due to transgenic Dsk-Gal4 activity per se given that social isolation did not comparably affect the Gal4-dependent expression of a dendritic marker transgene in the DSK neurons (Figure 6—figure supplement 1, Figure 6—source data 1). We also confirmed that GCaMP levels in other neuropeptide-expressing neurons (i.e., pigment-dispersing factor) were insensitive to social isolation or mechanical injury (Figure 6—figure supplement 2, Figure 6—source data 1).

Figure 6. Drosulfakinin (Dsk) neuron activity encodes social experience.

(A, B) Social experience elevates DSK levels in the Drosophila brains. Whole-mount brains from each Drosophila Genetics Reference Panel (DGRP) line in grouped (grp) or socially isolated cultures (iso) were co-immunostained with anti-DSK (green) and anti-BRUCHPILOT antibodies (BRP, a synaptic protein; magenta). The fluorescent DSK signals from confocal images were quantified using ImageJ. Ordinary two-way ANOVA or aligned ranks transformation ANOVA detected significant effects of social isolation on DSK levels in MP1a/MP1b/MP3 cell bodies and their projections (p<0.0001). The social distance (SD) trait effects (i.e., short vs. long SD) were more evident on DSK levels in cell bodies (p<0.0001). Data represent means ± SEM (n = 13). n.s., not significant; **p<0.01, ***p<0.001, as determined by Tukey’s multiple comparisons test (MP1a/MP1b cell bodies and MP1a projections) or Wilcoxon rank sum test (MP3 cell bodies and projections). Scale bar = 40 µm. (C) Social experience and physical injury elevate DSK neuron activity. Social isolation masked an injury-induced Ca2+ increase in the MP1a neurons among other DSK neurons as assessed by the genetically encoded Ca2+ sensor GCaMP in live-brain imaging. Two-way ANOVA detected significant effects of social isolation (p<0.0001) and injury (inj, p<0.01) on GCaMP levels in DSK neurons. Data represent means ± SEM (n = 10). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by Tukey’s multiple comparisons test. Scale bar = 5 µm. (D–F) Social experience strengthens postsynaptic signaling of DSK neurons only in males. Whole-mount brains were dissected from group-cultured (grp) or isolated (iso) flies and immunostained with anti-DSK antibody (white). Postsynaptic partner of DSK neurons was visualized by the heterologous ligand-receptor signaling embedded in the transsynaptic mapping transgene (Dsk>trans-Tango, magenta) while DSK neurons were further labeled by the presynaptic marker of the trans-Tango (green). The fluorescent trans-Tango signals and anti-DSK staining intensities from confocal images were quantified using ImageJ. Aligned ranks transformation ANOVA or ordinary 2-way ANOVA detected significant interaction effects of social isolation and gender on trans-Tango signals (E, p<0.0001) and DSK levels in MP1a projection (F, p<0.0001). Data represent means ± SEM (n = 13). n.s., not significant; ***p<0.001, as determined by Wilcoxon rank sum test (trans-Tango signals) or Tukey’s multiple comparisons test (DSK levels). Scale bar = 40 µm.

Figure 6—source data 1. Quantitative analysis of DSK neuron activities under distinct social contexts.

Figure 6.

Figure 6—figure supplement 1. Neither social experience nor physical injury affects transgenic DenMark expression in DSK neurons.

Figure 6—figure supplement 1.

(A) Transgenic Dsk-Gal4 flies (Dsk>GCaMP7f and Dsk>DenMark + SytGFP) and heterozygous controls (Dsk-Gal4/+) display social experience-dependent plasticity of social network behavior (SNB). Social distance (SD) was measured in a group of transgenic male flies under distinct experimental conditions (ctrl, control; inj, injured; grp, grouped; iso, isolated). Data represent means ± SEM (n = 8). n.s., not significant; ***p<0.001, as determined by two-way ANOVA with Tukey’s multiple comparisons test. (B) Dendrites (DenMark, magenta) and axons (SytGFP, green) in DSK neurons were visualized by confocal imaging of a whole-mount transgenic brain (Dsk>DenMark + SytGFP). Scale bar = 40 µm. (C) Social isolation or mechanical injury did not affect the transgenic DenMark expression in DSK neurons. The fluorescence intensities of the DenMark signals in DSK neurons were quantified from confocal images using ImageJ. Data represent means ± SEM (n = 6). n.s., not significant as determined by two-way ANOVA with Tukey’s multiple comparisons test. Dotted lines indicate ROI. Scale bar = 5 µm.
Figure 6—figure supplement 2. Neither social experience nor physical injury affects circadian-clock neuron activity.

Figure 6—figure supplement 2.

(A) Circadian-clock neurons expressing the neuropeptide pigment-dispersing factor were visualized in whole-mount adult brain by the combination of Pdf-Gal4 driver and red fluorescent protein transgenes (Pdf>mRFP). Arrows in each hemisphere indicate PDF-expressing large ventral lateral neurons (l-LNv). Scale bar = 40 µm. (B) The genetically encoded Ca2+ sensor GCaMP was expressed by the Pdf-Gal4 driver (Pdf>GCaMP7f) and the transgenic flies were harvested under distinct experimental conditions (ctrl, control; inj, injured; grp, grouped; iso, isolated). Live-brain Ca2+ imaging was then conducted in dissected brains. The GCaMP signals in l-LNv were quantified using ImageJ. Data represent means ± SEM (n = 5). n.s., not significant as determined by two-way ANOVA with Tukey’s multiple comparisons test. Scale bar = 5 µm.

We used the transsynaptic mapping transgene trans-Tango to visualize the postsynaptic partner of DSK neurons via heterologous ligand-receptor signaling (Talay et al., 2017; Sorkaç et al., 2023). Socially enriched, but not socially isolated, male flies displayed strong postsynaptic signals of the trans-Tango-expressing DSK neurons in the lateral protocerebrum where transgenic signals of DSK neuron axons (Dsk>SytGFP) were readily detectable (Figure 6D and E, Figure 6—figure supplement 1B, Figure 6—source data 1). Previous studies also demonstrated that MP1a neuron projections are specifically enriched in this brain region (Wu et al., 2019; Wu et al., 2020). DSK neurons have gender-specific presynaptic partners, which may mediate distinct signaling for sexual behaviors (Wu et al., 2019; Wu et al., 2020; Wang et al., 2022). To our surprise, socially enriched female brains did not show trans-Tango signals as evidently as male brains (Figure 6D and E, Figure 6—source data 1). Moreover, social deprivation downregulated DSK levels in the MP1a projections less potently in females than in males (Figure 6D and F, Figure 6—source data 1). These observations suggest sexual dimorphism in social behavior plasticity. Indeed, female flies from select DGRP lines showed baseline SD phenotypes consistent with their male counterparts, yet mechanical injury did not significantly affect female SD (Figure 4—figure supplement 3B, Figure 4—source data 1; also see Figure 7G, Figure 7—source data 1). Considering that DSK-expressing MP1 neurons originate from the larval brain (Oikawa et al., 2023), we hypothesized that early-life experience is developmentally encoded in DSK neuron activity via the male-specific neural pathway and adaptively expressed for social plasticity in adults. We further reason that low food intake upon social isolation may not directly implicate DSK expression or DSK neuron activity since DSK signaling has been shown to suppress feeding behavior as a satiety cue (Wu et al., 2020; Guo et al., 2021; Söderberg et al., 2012; Williams et al., 2014).

Figure 7. Genetic manipulations of Drosulfakinin (DSK) signaling imitate social experience.

(A) DskattP mutant brain expresses barely detectable DSK peptides. Whole-mount brains from Canton S (CS, a wild-type control) and DskattP mutant flies were co-immunostained with anti-DSK (green) and anti-BRUCHPILOT antibodies (BRP, a synaptic protein; magenta). Scale bar = 40 µm. (B, C) Genetic silencing of DSK-CCKLR-17D1 signaling by genomic deletions (DskattP or CCKLR-17D1attP) or DSK depletion (Dsk >DskRNAi) blocks injury-induced clustering behaviors. Data represent means ± SEM (n = 8). n.s., not significant; **p<0.01, ***p<0.001, as determined by two-way ANOVA with Tukey’s multiple comparisons test. (D, E) Conditional blockade of DSK neuron transmission at larval stage is sufficient to blunt social experience-dependent plasticity of social network behavior (SNB). Transgenic crosses for DSK-specific expression of the temperature-sensitive shibire allele (Dsk >shits) were kept at either restrictive (29°C) or permissive temperature (18°C) for synaptic transmission until the end of larval stage. Two-way ANOVA detected significant interaction effects of injury (inj) and temperature on social distance (SD) in Dsk>shits flies (p=0.0169) but not in heterozygous controls (p=0.7549 for Dsk-Gal4/+; p=0.2030 for shits/+). Data represent means ± SEM (n = 6). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by Tukey’s multiple comparisons test. (F) CCKLR-17D1 neurons display sexually dimorphic dendrites around MP1 projections. Transgenic male or female brains (CCKLR-17D1>DenMark + SytGFP) were immunostained with anti-DSK antibody to visualize DSK neuron projections (white) along with dendrites (DenMark, magenta) and axons (SytGFP, green) of neurons expressing CCKLR-17D1-Gal4 knock-in. Scale bar = 40 µm. (G) Transgenic excitation of CCKLR-17D1 neurons confers injury-induced plasticity of SNB in socially isolated males but not females. Two-way ANOVA detected significant interaction effects of injury (inj) and social isolation on SD in male heterozygous controls (p=0.0040 for 17D1-Gal4/+; p=0.0007 for NaChBac/+) but not in all the other genotypes. Data represent means ± SEM (n = 8). n.s., not significant; *p<0.05, **p<0.01, as determined by Tukey’s multiple comparisons test.

Figure 7—source data 1. Quantitative analysis of SNB plasticity in genetic and transgenic Drosophila models for DSK-DSK receptor signaling.

Figure 7.

Figure 7—figure supplement 1. Transgenic Dsk RNAi effectively depletes DSK peptides in the adult brain.

Figure 7—figure supplement 1.

The Dsk RNAi transgene was expressed in DSK neurons by the Dsk-Gal4 knock-in driver (Dsk>DskRNAi). Whole-mount transgenic brains were co-immunostained with anti-DSK (green) and anti-BRP (magenta) antibodies. Heterozygous flies for Gal4 (Dsk-Gal4/+) or RNAi transgenes (DskRNAi/+) served as negative controls. Scale bar = 40 µm.
Figure 7—figure supplement 2. Genomic deletions of CCKLR-17D1 but not CCKLR-17D3 suppress injury-induced clustering in group-cultured male flies.

Figure 7—figure supplement 2.

Deletion mutants of the two Dsk receptor genes (CCKLR-17D1 and CCKLR-17D3) and hemizygous control flies (+/Y) were obtained from standard group cultures. Social distance (SD) was measured in a group of male flies as described in Figure 1. Two-way ANOVA detected significant interaction effects of injury (inj) with CCKLR-17D1 deletions (p=0.0404 for CCKLR-17D1Δ1; p=0.0254 for CCKLR-17D1Δ2) but not with CCKLR-17D3 deletions (p=0.1051 for CCKLR-17D3Δ1; p=0.6697 for CCKLR-17D3Δ2) on SD. Data represent means ± SEM (n = 8). n.s., not significant; *p<0.05, **p<0.01, ***p<0.001, as determined by Tukey’s multiple comparisons test.
Figure 7—figure supplement 3. Transgenic silencing of CCKLR-17D1 neurons suppresses injury-induced clustering in group-cultured male flies.

Figure 7—figure supplement 3.

Synaptic transmission in CCKLR-17D1 neurons was blocked by transgenic expression of a tetanus toxin light chain (17D1>TNT). Heterozygous flies for Gal4 (17D1-Gal4/+) or TNT transgenes (TNT/+) served as negative controls. Two-way ANOVA detected significant interaction effects of genotype and injury (inj) on SD (p=0.0003 for 17D1-Gal4/+vs. 17D1>TNT; p=0.0012 for TNT/+vs. 17D1>TNT). Data represent means ± SEM (n = 8). n.s., not significant; ***p<0.001, as determined by Tukey’s multiple comparisons test.

Male-specific DSK-CCKLR-17D1 signaling mediates SNB plasticity

To determine whether DSK signaling actually contributes to social behavior plasticity, we first examined the loss-of-function effects of relevant genes. Genomic deletion of the Dsk locus (DskattP) or DSK depletion by RNA interference (Dsk>DskRNAi) abolished injury-induced clustering behaviors (Figure 7A–C, Figure 7—figure supplement 1, Figure 7—source data 1). Furthermore, genomic deletions of the Dsk receptor CCKLR-17D1 (CCKLR-17D1attP and CCKLR-17D1Δ) but not CCKLR-17D3 (CCKLR-17D3attP and CCKLR-17D3Δ) comparably masked injury-induced social interactions (Figure 7B, Figure 7—figure supplement 2, Figure 7—source data 1). Genetic effects of Dsk deletion and DSK depletion were not consistent on baseline SD in grouped cultures. These observations suggest that Dsk is not crucial for shaping the SD traits per se, but genetic backgrounds may substantially contribute to it. Nonetheless, genetic evidence from independent alleles and transgenic RNAi convincingly supports specific implication of the DSK-CCKLR-17D1 pathway in experience-dependent social plasticity.

We further validated if neuronal activity or synaptic transmission for DSK-CCLKR-17D1 signaling controls injury-induced SNB plasticity. To this end, a temperature-sensitive allele of Drosophila dynamin (shibirets) (Kitamoto, 2001) was transgenically expressed in DSK neurons to block their synaptic transmission only at restrictive temperatures (Figure 7D). The conditional manipulation of larval DSK neurons was sufficient to suppress injury-induced clustering in group-cultured adults (Figure 7E, Figure 7—source data 1). CCKLR-17D1-expressing neurons displayed a gender-specific distribution in the adult brain when their dendrites and axons were visualized using specific transgenic markers (i.e., DenMark and SytGFP, respectively) (Figure 7F). In particular, male brains expressing the CCKLR-17D1 knock-in transgene showed more signals for cell bodies and dendrites around MP1a axon projections than females (Wu et al., 2020). This was consistent with the high levels of axonal DSK expression and trans-Tango signals in the same region of male brains (Figure 6D–F, Figure 6—source data 1). We hypothesized that transgenic activation of DSK-CCKLR-17D1 signaling genetically mimics social experience in developmentally isolated flies. Supporting this idea, transgenic excitation of CCKLR-17D1 neurons was sufficient to confer injury-induced social interactions to isolated male flies (Figure 7G, Figure 7—source data 1). The same transgenic manipulation of CCKLR-17D1 neurons did not induce social plasticity in females, irrespective of their early-life experience. On the other hand, blocking synaptic transmission in CCKLR-17D1 neurons suppressed injury-induced clustering in group-cultured male flies (Figure 7—figure supplement 3, Figure 7—source data 1). These findings convincingly provide a neuroanatomical basis for early-life social memory and male-specific social plasticity.

Discussion

Our study demonstrated that conspecific individuals show a wide range of preferences for social distancing, and it has likely co-evolved with their inferior traits as a compensatory mechanism (Figure 8). Physiological challenges (e.g., mechanical injury) may adaptively modify the clustering property of a given group. However, the plasticity of group behaviors requires social experience during development. We propose that a subset of the Drosophila brain neurons expressing the neuropeptide DSK serves as a neural substrate for social memory, as supported by the intimate coupling of early-life social experience and SNB plasticity to DSK expression, DSK neuron activity, and postsynaptic signaling.

Figure 8. A working model for early-life social memory and the experience-dependent plasticity of social network behavior (SNB).

Figure 8.

Social distancing is an inheritable trait in Drosophila. Diverse genetic pathways contribute to active social preferences while the clustering property may have evolved to compensate for inferior traits in individuals and confer their group fitness. Nonetheless, Drosophila can tune their social distance depending on physiological states (e.g., mechanical injury) and this feature of SNB is defined as ‘social plasticity’. In fact, the social plasticity requires early-life social experience or ‘social memory’ during development. Group culturing elevates DSK expression and DSK neuron activity to reinforce its postsynaptic signals likely to the cognate receptor CCKLR-17D1. The activation of DSK-CCKLR-17D1 pathway thus encodes early-life social experience in developing brains to support social plasticity in adults.

Distinct social behaviors in Drosophila (i.e., aggression and mating) have been commonly mapped to specific pairs of DSK neurons (Wu et al., 2019; Wu et al., 2020; Wang et al., 2022). Presynaptic partners of DSK neurons are sexually dimorphic, while their postsynaptic effects are differentially mediated via the two DSK receptor pathways (i.e., CCKLR-17D1 for aggression and SNB plasticity; CCKLR-17D3 for sexual behaviors). Intriguingly, this neural architecture for balancing aggression and mating behaviors has been proposed to be analogously conserved between flies and mammals (Anderson, 2016). Furthermore, DSK neuron activity correlates with social dominance (i.e., winner effects from aggression) (Wu et al., 2020) and group housing (Wu et al., 2019), but not with mating status (Wang et al., 2022). Accordingly, the DSK-CCKLR-17D1 pathway meets the necessary criteria for male-specific SNB plasticity.

The phenotypic correlates of aggression and SNB in natural populations (i.e., DGRP lines) are consistent with their common neural locus. However, these findings do not necessarily imply that DSK neurons control the two social behaviors in a similar manner. For instance, DSK excitation promotes aggression in both males and females (Wu et al., 2020), whereas DSK signaling is unlikely to trigger grouping behaviors per se. What remains to be clarified is how DSK signaling gates SNB plasticity and why this process is missing in female flies. Considering that social hierarchy is established in male fights only (Nilsen et al., 2004; Simon and Heberlein, 2020), we speculate that male-specific DSK pathways may include extra circuit modalities for contextual processing of social environments and adaptive social structures. The development of neuroanatomical differences between male and female brains may coincide with the acquisition of gender-specified demands for innate behaviors and physiology during evolution (e.g., a reproductive advantage of male clustering under physiologically challenging conditions).

The mammalian DSK homolog CCK shows sexual dimorphism in brain expression and mating behavior response (Bloch et al., 1987; Bloch et al., 1988; Micevych et al., 1988). Moreover, CCK activation is implicated in aggression and exploratory behaviors (Raud et al., 2005; Li et al., 2007). It would thus be interesting to determine whether DSK/CCK signaling indeed represents an ancestral mechanism for social memory, sexually dimorphic social behaviors, and their plasticity.

Materials and methods

Fly stocks

Flies were raised on standard cornmeal-yeast-agar food at 25°C and 40–50% humidity under 12 hr light:12 hr dark cycles. Behavioral experiments were primarily conducted between Zeitgeber time (ZT) 4 and 8 (lights-on at ZT0; lights-off at ZT12). DGRP lines, Canton-S (BL64349), rut1 (BL9404), rut2080 (BL9405), DskattP (BL84497), Dsk2A-Gal4 (BL84630), UAS-DskRNAi (BL25869), CCKLR-17D1attP (BL84462), CCKLR-17D12A-Gal4 (BL84605), CCKLR-17D3attP (BL84463), Orco1 (BL23129), UAS-myrGFP.QUAS-mtdTomato-3xHA; trans-Tango (BL77124), 20XUAS-IVS-jGCaMP7f (BL80906), and UAS-DenMark, UAS-syt.eGFP (BL33065) were obtained from Bloomington Drosophila Stock Center. CCKLR-17D1Δ1 (119026), CCKLR-17D1Δ2 (119027), CCKLR-17D3Δ1 (119029), CCKLR-17D3Δ2 (119030), iav1 (101174), norpA7 (108362), and Poxn68 (119155) were obtained from Kyoto Drosophila Stock Center. UAS-shits, UAS-NaChBac, and UAS-TNT have been described previously (Kitamoto, 2001; Nitabach et al., 2006).

SNB analysis

A Petri dish (5.5 cm [d] × 1.5 cm [h]) was filled with 2% agar media (1.3 cm [h]) to prepare a circular arena for SNB analysis. This setup minimizes side-wall walking or z-stacking of individual flies that interferes with tracing group behaviors over time (Simon and Dickinson, 2010). Three-to-five-day-old flies from standard cultures (n = 16) were briefly cold-anesthetized (<15 s) and then transferred to the circular arena. Each arena was video-recorded for 10 min using a cellular phone (Samsung Galaxy Note 8 or Samsung Galaxy Note 20). Time-series coordinates of each fly’s position in the arena were extracted from raw video data using an in-house Python code (https://github.com/taejoonlab/tracking-fly, copy archived at Jeong et al., 2021a). SD was calculated from the position coordinates of individual flies at a given time and averaged over time. The average walking speed of individual flies and the interquartile ranges of the positional centroid in a given group of flies were also calculated over time (https://github.com/KJKwon/2023_FlyBehavior, copy archived at Jeong et al., 2023). The centroid velocity was determined from the fourth quarter of video-recording data, given more evident clustering phenotypes at the later period. Single-fly recordings in the circular arena were analyzed using a MATLAB-based fly_tracker code (https://github.com/jstaf/fly_tracker, copy archived at Stafford, 2016).

Fly manipulations

Drosophila eggs were collected on a plate filled with grape juice media (https://cshprotocols.cshlp.org/content/2007/9/pdb.rec11113). Each egg was gently transferred to an isolation chamber containing 300 ul of cornmeal-yeast-agar food for social isolation. The chamber was sealed using parafilm with a tiny hole for air circulation and kept at 25°C before relevant experiments. To generate grouped-to-isolated (GTI) flies, 3-day-old flies from standard culture vials were individually transferred to each isolation chamber and further incubated for a week. To generate isolated-to-grouped (ITG) flies, 3-day-old flies eclosed from isolated eggs were collected into a standard food vial for group-culturing (~20 isolated flies per vial) and further incubated for a week. To assess SNB in isolated or GTI flies, each fly was reared in the isolation chamber before collectively transferring into the SNB arena. Flies were briefly cold-anesthetized during GTI/ITG transitions or before transferring to the SNB arena. For physical injury, the mesothoracic segment of 3-day-old flies was pierced (<1 mm depth) using a sterilized needle.

Larval behavior and developmental analyses

For clustering assay, third-instar larvae were obtained from grouped-egg cultures (50 eggs per culture). A group of the third-instar larvae (n = 20) were then loaded onto a cylinder vial (2.3 cm [d] × 9.5 cm [h]) containing standard cornmeal-yeast-agar food. The food vial was divided into four sectors. The maximum number of clustering larvae per sector was scored from each vial, and the percentage of clusters with given larvae numbers was calculated from 30 vials. For digging assay, a 3D arena (2 cm [w] × 0.5 cm [d] × 4 cm [h]) was filled up to 2 cm with standard cornmeal-yeast-agar food. Either a group of third-instar larvae (n = 20) from standard culture vials or an isolated third-instar larva from single-egg cultures (one egg per culture) was transferred to the digging-assay arena and then allowed to explore it for 12 hr before measuring digging depth from the surface (Dombrovski et al., 2017). For food intake assay, a wider 3D arena (8 cm [w] × 0.5 cm [d] × 4 cm [h]) was filled up to 2 cm with standard cornmeal-yeast-agar media containing 1% brilliant blue FCF (JUNSEI, 64350-0410). A group of third-instar larvae (n = 20) from standard culture vials or an isolated third-instar larva from single-egg cultures was transferred to the food intake arena and then allowed to explore it for 12 hr. Each larva was gently homogenized in 50 ul of distilled water, and the absorbance of individual larval extracts was measured at 627 nm using a microplate reader (Tecan, Infinite M200). Developmental time was measured by the first eclosion day in a grouped-egg culture (50 eggs per culture) vs. a set of 81 single-egg cultures per experiment. The percentage of eclosed flies was scored from a grouped-egg culture (100 eggs per culture) vs. a set of 81 single-egg cultures per experiment, and the ratio of males to total flies was then calculated accordingly.

Maze assay

Yeast paste was placed at the corner of a 14 cm × 14 cm transparent maze, and the maze was put on a white-light box to avoid any phototatic effects. A group of four flies was starved for 6 hr and then transferred to the maze by an aspirator. A training session was completed when three or more pioneer flies reached the food, and the trained flies were transferred to an empty vial containing water only. The pioneer training was repeated three times. For the maze test, a group of 16 flies (16 naive or 12 naive + 4 pioneer flies) was briefly cold-anesthetized (<15 s) and then placed at the opposite corner of the maze to the yeast paste. The 75% arrival time was recorded when 12 or more flies reached the food.

Aggression assay

Quantitative assessment of aggression behaviors was performed as described previously with minor modifications (Chen et al., 2002). Three-to-five-day-old male flies were separated from females and starved for 6 hr. A pair of male flies with the same genotype were then transferred by gentle aspiration into a cylinder arena (1.4 cm [d] × 0.5 cm [h]), where a thin droplet of yeast paste with a decapitated female carcass was placed in the center. The arena was video-recorded for 10 min, and the number of lunges was counted manually.

Courtship chaining behavior assay

Male–male courtship was quantified by the courtship chaining index as described previously with minor modifications (Kitamoto, 2002). A group of 3-to-5-day-old male flies (n = 16) from standard cultures were briefly cold-anesthetized (<15 s), transferred to the circular arena for SNB analysis, and then video-recorded for 10 min. Courtship chain was scored when three or more male flies were engaged in chaining with courtship behavior (Kitamoto, 2002). The chaining index was calculated by the percentage of courtship chaining duration over the 10 min recording.

Transcriptome analysis

Three-to-five-day-old flies were harvested at ZT4-6. Total RNAs were extracted from 35 fly heads and purified using the PureLink RNA mini kit according to the manufacturer’s instructions (Invitrogen). RNA quality was assessed by Bioanalyzer using the Agilent RNA 6000 pico kit (Agilent Technologies). RNA-seq libraries were constructed using the NEBNext Ultra Directional RNA Library Prep Kit for Illumina (New England Biolabs), together with NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs) and subsequently sequenced by Illumina NovaSeq 6000 or Illumina NextSeq 500/550 (LabGenomics, Republic of Korea). RNA-seq reads were processed using trimmomatic (Bolger et al., 2014) (version 0.39) with the default option to remove bases with low-quality scores or from sequencing adapters. The trimmed reads were then mapped to the Drosophila melanogaster reference genome R6.46 using STAR (Dobin et al., 2013) (version 2.7.10b). DEGs were determined using DEseq2 (Love et al., 2014) (version 1.40.0; more than twofold change with adjusted p<0.05). Transcripts undetectable in more than half of the RNA-seq libraries were excluded from the analysis. Overrepresented GO terms were identified by Fisher’s exact test (false discovery rate < 0.05) with PANTHER (Thomas et al., 2022) (version 17.0).

Quantitative brain imaging

Whole-mount brain imaging was performed as described previously (Jeong et al., 2021b). The primary antibodies used in immunostaining included rabbit anti-DSK (Boster Bio, DZ41371; diluted at 0.5 ug/ml) and mouse anti-BRP antibodies (Developmental Studies Hybridoma Bank, nc82; diluted at 1:1,000). The GCaMP signals from live brains were recorded at room temperature using an FV1000 (Olympus) or A1 confocal microscope (Nikon). Fluorescence intensities from regions of interest in confocal images were quantified by background normalization [(S-B)/B] using ImageJ software.

Statistical analysis

Statistical analyses were performed using GraphPad Prism or R (version 4.2.3). Shapiro–Wilk test was followed by F-test (two samples) or Brown–Forsythe test (multiple samples) to check normality (p<0.05) and equality of variances (p<0.05), respectively. For two-sample comparisons, parametric datasets with equal variance were analyzed by unpaired t-test. For multiple-sample comparisons, (1) parametric datasets with equal variance were analyzed by ordinary ANOVA with Tukey’s multiple comparisons test; (2) parametric datasets with unequal variance were analyzed by Welch’s ANOVA with Dunnett’s T3 multiple comparisons test (one-way) or by aligned ranks transformation ANOVA with Wilcoxon rank sum test (two-way); and (3) nonparametric datasets with equal variance were analyzed by Kruskal–Wallis test with Dunn’s multiple comparisons test (one-way) or by aligned ranks transformation ANOVA with Wilcoxon rank sum test (two-way). For comparisons between repeatedly measured samples, datasets were analyzed by paired t-test (two samples) or two-way repeated measures ANOVA with Sidak’s multiple comparisons test (multiple samples). The significance of the correlation among SD, walking speed, centroid velocity, food intake, starvation-induced activity, and aggression in DGRP strains was determined by Spearman correlation analysis. Sample sizes and p values obtained from individual statistical analyses were all summarized in each source data and indicated in the figure legends accordingly.

Acknowledgements

We thank Bloomington Drosophila Stock Center, Developmental Studies Hybridoma Bank, Korea Drosophila Resource Center, and Kyoto Drosophila Stock Center for reagents; Kenneth Wilson and Pankaj Kapahi for raw data from their phenotypic DGRP screens. This work was supported by grants from the Suh Kyungbae Foundation (SUHF-17020101[CL]); from the National Research Foundation funded by the Ministry of Science and Information & Communication Technology (MSIT), Republic of Korea (NRF-2021M3A9G8022960 [CL]; NRF-2018R1A5A1024261 [CL]; NRF-2023R1A2C100627511 [TK]); from Basic Science Research Program through the National Research Foundation funded by Ministry of Education (NRF-2018R1A6A1A03025810 [TK]).

Funding Statement

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

Contributor Information

Taejoon Kwon, Email: tkwon@unist.ac.kr.

Chunghun Lim, Email: clim@kaist.ac.kr.

John Ewer, Universidad de Valparaiso, Chile.

Claude Desplan, New York University, United States.

Funding Information

This paper was supported by the following grants:

  • Suh Kyungbae Foundation SUHF-17020101 to Chunghun Lim.

  • National Research Foundation of Korea NRF-2021M3A9G8022960 to Chunghun Lim.

  • National Research Foundation of Korea NRF-2018R1A5A1024261 to Chunghun Lim.

  • National Research Foundation of Korea NRF-2023R1A2C100627511 to Taejoon Kwon.

  • National Research Foundation of Korea NRF-2018R1A6A1A03025810 to Taejoon Kwon.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft.

Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft.

Investigation.

Investigation.

Conceptualization, Formal analysis, Supervision, Funding acquisition, Visualization, Writing – original draft, Writing – review and editing.

Conceptualization, Formal analysis, Supervision, Funding acquisition, Visualization, Writing – original draft, Writing – review and editing.

Additional files

MDAR checklist

Data availability

The datasets generated and analyzed during the current study are included in source data files or available in the European Nucleotide Archive repository (accession number PRJEB61423). The python scripts that support the findings of this study are available from the author's GitHub webpage under the links https://github.com/taejoonlab/tracking-fly, (copy archived at Jeong et al., 2021a) and https://github.com/KJKwon/2023_FlyBehavior, (copy archived at Jeong et al., 2023).

The following dataset was generated:

Lim C. 2023. Gene expression analysis of 6 DGRP lines based on clustering behavior and housing. EBI European Nucleotide Archive. PRJEB61423

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Editor's evaluation

John Ewer 1

This study presents important findings on the role of Drosulfakinin signaling in encoding early-life social memory in Drosophila, which influences adaptive social plasticity in adulthood. The research demonstrates the neurogenetic basis of social clustering and behavioral adaptation, advancing our understanding of social behavior's molecular and evolutionary bases. The evidence is solid, given the robust genetic, behavioral, and transcriptomic analyses.

Decision letter

Editor: John Ewer1
Reviewed by: Yufeng Pan2

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

[Editors' note: this paper was reviewed by Review Commons.]

eLife. 2024 Dec 18;13:e103973. doi: 10.7554/eLife.103973.sa2

Author response


General Statements [optional]

Our original manuscript entitled, “Drosulfakinin signaling encodes early-life memory for adaptive social plasticity” (manuscript number: RC-2024-02466R), was reviewed by four reviewers via the Review Commons, and we are now transferring the fully revised manuscript to eLife for your consideration. As you will see in our point-by-point responses below, the review was generally favorable, requiring additional data supplemental to our main conclusions, better clarification of method details, and statistical justifications. Please refer to the summary of our biological questions and key findings in the manuscript.

Question: animal species display differential preferences for social networks among conspecific individuals, and social interactions can further impact physiological properties in individuals. Nonetheless, it remains elusive how group properties have evolved with individual traits; and how animals process social experience to shape their physiology. We employ Drosophila as a genetic model for social network behavior (SNB) to address these questions.

Key findings: our approaches align large-scale datasets of Drosophila behaviors in groups to physiological traits, differential gene expression, and neurogenetic manipulations and unveil novel principles of SNB and the underlying mechanisms:

Drosophila social interactions provide a compensatory mechanism for inferior individual traits during development and in adult physiology.

Drosophila SNB shows robust plasticity depending on early-life social experience and physiological challenges, and the adaptive “social plasticity” is actually accompanied by conserved genetic reprogramming.

The neuropeptide signaling from pairs of brain neurons expressing Drosulfakinin (DSK) serves as a neural substrate for early-life “social memory” that persists throughout development and supports SNB plasticity.

Given the important advances of significance our work made, we believe that our revised manuscript compares favorably with the high-quality research published by eLife and will be of keen interest to the journal’s broad readership, including those interested in the neural basis of social behaviors and their evolution. I hope you find our revised manuscript ready for publication in eLife.

Point-by-point description of the revisions

Please find our point-by-point responses in blue to the reviewers' comments below.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

The manuscript by Jeong et al. describes effects of neuronal signalling on collective behavior by measuring social distance (SD) which is used as a measure for social network behavior. Authors screened for a panel of inbred DGRP lines and compared the SD due to prior experience of group or single culturing when flies are recorded in a 55 mm diameter petri-dish. The screen uncovered 3 short Sd and three long-SD lines, and subsequent experiments showed differences in various behaviors such as recovery from injury, search for food and SD. Using RNA-seq from heads of flies they implicate Dsk signalling and show neuronal architecture and activity differences between grouped and isolated male flies. They implicate Dsk signalling in recovery from injury affecting SD but it was dispensable for grouped vs. isolated flies. I have suggestions to support the claims made, analysis and interpretation of the data and improve the clarity of writing. See my specific comments below.

Major comments:

1. For recording social behaviour in flies, arenas with sloped walls have been extensively used called 'fly bowl' (Simon et al. 2010 doi:10.1371/journal.pone.0008793; Robie et al., 2017, doi: 10.1016/j.cell.2017.06.032), or 'flyworld' (Liu et al., 2018 doi:10.1371/journal.pcbi.1006410). Such geometry ensures that flies don't walk on the side of the arena, and don't occlude each other. However, in the screen carried out in this manuscript, a petri-dish of 5.5 cm diameter filled with agar was used to record social network formation. Given the propensity of flies to walk on the walls of such circular arena, it will be difficult to know if the long and short SD behavior resulting from propensity to form clusters is an artefact of the assay condition used. It would be important to test the SNB and SD of at least the 6 selected short and long SD lines in arena with sloped walls to rule out this possibility.

To minimize complications from side-wall walking or z-stacking of individual flies, the circular arena used in our study was filled with agar, making a space of 5.5 cm in diameter x ~0.15 cm in height (see Author response image 1). In fact, the surface tension of the agar solution led to a rounded interface between the agar bed and the side wall that could prevent side-wall walking and partially mimic the sloped wall effects. We included representative video clips for SNB recording in the revised manuscript to further justify our experimental conditions (Video S1-S10). We also revised our method text accordingly and cited the relevant reference.

Author response image 1. The circular arena for SNB recording.

Author response image 1.

2. Methods section would require additional details about the SNB assay for instance, the height of the agar bed and the effective height in which interactions was recorded is not mentioned.

As described in our response to reviewer #1, major comment #1 above, we revised our method text accordingly.

3. Figure 2C and 2D results in larvae seems to contradict previous studies that have shown that isolated flies eat more as adults (Li et al. Nature, 2021) and Dsk-RNAi increases feeding in larvae and adults (Soderberg et al., 2012). It might be due to unique characteristic of DGRP lines used and would be helpful to discuss this.

We reason that high-digging activity in a group of individual larvae can increase the accessibility to “solid” food, thereby promoting their food intake over 12-h during development. However, food consumption rates and their regulation can vary depending on developmental stages or feeding conditions (e.g., larvae vs. adults; liquid vs. solid food; long-term vs. short-term) (https://pubmed.ncbi.nlm.nih.gov/30914005/; https://pubmed.ncbi.nlm.nih.gov/24937262/). It is thus not fair to align our results directly to those observed under very different biological/experimental contexts. For instance, Li et al. measured the amount of liquid food consumption in individually isolated adults from group culture vs. transient social isolation (i.e., 1-week isolation after eclosion). Soderberg et al. assessed the 15-minute feeding activities of larvae or adults on solid food but did not compare the feeding activity between grouped vs. isolated individuals. Therefore, it is not conclusive whether the DSK-depletion phenotypes are relevant to social experience or whether DSK signaling controls short-term feeding per se. Accordingly, we believe our observations do not necessarily contradict previous studies or indicate characteristics unique to the DGRP lines used in our study.

4. Rutabaga mutants for Figure S3 are directly compared with CS flies in the maze assay and it appears from methods that these lines were not isogenized, this can significantly impact the results. Similarly for some of the subsequent Dsk experiments it appears that lines were not isogenized (see below). These experiments would either need to be repeated of this caveat needs to be explicitly mentioned to avoid misinterpretation of the data.

Since genetic backgrounds could substantially contribute to mutant phenotypes, we mentioned the caveat in our revised manuscript. As the reviewer suggested above, testing isogenized lines could be one option to confirm the genetic effects. Our study took an alternative approach where the observed phenotypes were validated by independent genetic models. For instance, the importance of DSK signaling in injury-induced SNB plasticity was validated by genomic deletions of DSK and DSK receptor genes, as well as by transgenic RNAi (Figure 7B and 7C). In the revised manuscript, we examined additional mutant alleles of rutabaga (Figure S6, rut[1] and rut[2080]), CCKLR-17D1 (Figure S15, CCKLR-17D1[delta1] and CCKLR-17D1[delta2]), and CCKLR-17D3 genes (Figure S15, CCKLR-17D3[delta1] and CCKLR-17D3[delta2]) to substantiate our original findings.

5. For Figure 3 describing RNA-seq data additional analysis would be helpful. Gene expression from isolated and grouped flies have been studied earlier by microarray and RNA-seq methods (Wang et al., PNAS 2008; Agrawal et al., JEB 2020; Li et al. Nature, 2021). Data from these studies should be compared with to see if there are common patterns of gene expression between long and short SD flies vs. group and isolated flies.

According to the reviewer's suggestion, we compared our DEG analysis with those reported in the previous studies. Genes upregulated in socially deprived flies overlapped substantially between our data and the published ones. However, the number of genes commonly upregulated in grouped cultures was very limited in the pairwise comparisons, and Dsk was the only gene upregulated across DEG analyses. Also, DEGs between the short vs. long SD lines barely overlapped with those between grouped vs. isolated flies across independent studies. We speculate that Drosophila has evolved a genetic reprogram where social isolation robustly induces the expression of select genes regardless of genetic backgrounds (i.e., DGRP lines in our study vs. Canton-S in the previous studies), whereas diverse genetic pathways shape the baseline SD traits. We revised our text accordingly and included these new analyses in the revised manuscript (Figure S10 and Dataset S3).

6. GEO accession number and the analyzed list of DEGs should be provided as supplementary information.

As described in our original manuscript, we submitted our raw data to the European Nucleotide Archive (ENA accession number PRJEB61423). Since ENA and GEO share their data, uploading our data redundantly onto the GEO should not be necessary. Our original manuscript also included all the DEG lists as supplementary tables (Dataset S1-S3).

7. Figure 3E & F are not referred to in the main text, also there is no description of how the data was generated. Is this based on published data from Mackay lab about DGRP lines, if so, aggression experiments were not convincing in those studies and have been shown to not recapitulate 'real' aggression by other labs for several of the DGRP lines tested (Chowdhury et al., 2021, doi: 10.1038/s42003-020-01617-6).

The main text of our original manuscript actually referred to Figure 3E and 3F. We revised our figure legends to indicate the resources of raw DGRP data and clarified the method for the correlation comparisons. Since we employed the published aggression data from the Mackay lab study (https://pubmed.ncbi.nlm.nih.gov/26100892), we experimentally validated that the long-SD lines indeed show more lunges (i.e., a well-established indicator of aggression behaviors) than the short-SD lines in our revised manuscript (Figure S11).

8. Dsk was shown to be reduced in isolated flies by RNA-seq and play a role in aggression by an earlier study (Agrawal et al., 2020) and should be cited appropriately (line 180-181) and elsewhere.

The paper was appropriately cited in our original/revised manuscript.

9. For Figure 4A-B, source images for other two DGRP lines should be included at least in supplementary information, if not as main figure.

Representative confocal images for the other DGRP lines were included in the revised manuscript (Figure 6A).

10. For Figure 5, what is the reason that uninjured flies don't show any SD phenotype? Are there any changes in their velocity? This is mentioned in passing on line 228-29 but should be properly discussed.

Genomic deletions or transgenic manipulations of the DSK-CCKLR-17D1 pathway gave consistent effects on the injury-induced clustering but not on baseline SD or walking speed. We reason that the DSK-CCKLR-17D1 pathway is dedicated to encoding early-life social experience by enforcing DSK neuron activity and their male-specific postsynaptic signaling. We clarified our text including the genetic background issue in the revised manuscript. Please also see our response to reviewer #1, major comment #4 above.

11. Trans-Tango and UAS-Denmark, SytGFP experiments were performed previously by Wu et al., 2020 and Wang et al., 2021 for Dsk, these two studies observed that P1 neurons are presynaptic and Dsk neurons are post synaptic but in Figure 4 it's not clear what are the presynaptic and post synaptic neurons. Also these studies are not cited appropriately in this section.

The two studies expressed trans-Tango in P1 neurons (P1>trans-Tango) to demonstrate that DSK-expressing neurons are postsynaptic to P1 neurons. They further visualized some overlaps between axon terminals of P1 neurons (P1>sytGFP) and dendrites of DSK neurons (Dsk>DenMark). On the other hand, we expressed the trans-Tango in DSK neurons (Dsk>trans-Tango) to visualize their male-specific/social experience-dependent postsynaptic targets. We also visualized brain regions positive for both synaptic signals from Dsk>sytGFP and the postsynaptic signals from Dsk>trans-Tango. The two studies were cited in our original manuscript to discuss presynaptic partners of DSK neurons and their distinct roles in animal behaviors. We further cited the two studies in this result section of our revised manuscript.

Minor comments:

1. Line no. 286: please mention about the relative humidity and light & dark cycle conditions and when experiments were conducted (ZT).

Flies were reared at 40-50% humidity under 12-h light: 12-h dark cycles. Behavioral experiments were primarily conducted between ZT4 and ZT8. We revised the method text accordingly.

2. Line no. 311: How many days old flies were used (isolated and group housed) for the behavior and transcriptomic studies?

We revised the method text to better describe our experimental conditions.

3. Line no. 349: for RNA extraction please mention how many fly heads were used and ZT for collection.

Flies were harvested at ZT4-6, and total RNAs were extracted from 35 fly heads. We revised the method text accordingly.

4. Line no. 358: Italicize "Drosophila melanogaster".

Corrected.

Reviewer #1 (Significance (Required)):

This manuscript will be of interest to neuroscientists studying Drosophila social behaviors. The manuscript asks interesting questions and authors have done extensive set of experiments but the progress appears incremental given the current state of the field, especially for the later part of the manuscript. Some of the interpretation would also require additional data to bolster the claims made. Finally, the findings from this study could be better discussed in the context of what it is already known.

We believe our revised text and additional data in the revised manuscript clarify the reviewer concerns and better support our original findings.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

The article explores the social network behavior (SNB) of Drosophila, focusing on individual social distance (SD) within groups over time. A systemic analysis revealed that short SD is associated with long developmental time, low food intake, and hypoactivity. Group culturing compensates for developmental inferiority in short social distance individuals. Social interactions during early development positively impact adult physiology and adaptive social plasticity. Transcriptome analyses show genetic diversity for SD traits. The neuropeptide Drosulfakinin (DSK) signaling mediates social network behavior plasticity via receptor CCKLR-17D1, particularly in males, suggesting a dedicated neural mechanism encoding early-life experiences to adaptively transform group properties. The research suggests that animals have developed neural mechanisms to encode early-life experiences. It offers insights into the genetic foundation and adaptability of social behavior in Drosophila, shedding light on the neural processes involved in social memory and the adaptive behaviors of groups. These findings have broader implications for understanding similar neural mechanisms governing social memory and group behaviors in other species.

Major concerns:

Major 1. In Figure 2H, the latency to 75% arrival of short-SD isolated fruit flies (no matter with or without pioneers) is close to that of group fruit flies with pioneers while the latency to 75% arrival of long-SD isolated fruit flies (no matter with or without pioneers) is close to that of group fruit flies without pioneers; How to explain the difference in latency to 75% array between long-SD and short-SD isolated fruit flies? It seems that only in the long-SD fruit flies from the grouped experience, the absence of pioneers will increase the time it takes to reach the target food in the maze.

Social deprivation effects on pioneer-free group foraging somewhat varied across the long SD lines (Figure 4B and S5, blue). We reason that the hyperactivity of individual long-SD flies facilitates their food-seeking behaviors in the maze, weakening the pioneer effects or even overriding the group property. Nonetheless, our statistical analyses validated that (1) prior social experience did not significantly affect the group performance of 16 naive flies in the maze assay (the only exception was DGRP707, a long-SD line that showed longer latency in group-cultured naive flies than in socially isolated ones), (2) the presence of pioneers significantly shortened the latency in both short- and long-SD lines, and (3) the pioneer effects were evident only in group-cultured flies. We accordingly revised our result text to better elucidate our conclusion.

Major 2. In Figure 3C, there are two up-regulated genes in the Drosophila group that overlap in short-SD and long-SD strains. Apart from Dsk, what is the other gene? In addition, for isolated fruit flies, both short-SD and long-SD lines have more gene expression upregulated. How to explain this phenomenon? Can you briefly explore the reasons for their upregulation and instead of involvement in SNB plasticity, what kind of physiological functions may they have?

The other gene commonly upregulated in group-cultured DGRP flies was Arc1 (Activity-regulated cytoskeleton-associated protein), implicated in synaptic plasticity and fat metabolism (https://flybase.org/reports/FBgn0033926.htm). Arc1 downregulation upon social isolation could be relevant to the weak postsynaptic signaling of DSK neurons (Figure 6D and 6E) or be a part of the metabolic reprogramming (Figure 5D; also see below). Nonetheless, we focused on the neuropeptide DSK, given its unique expression in the brain and relevance to other social behaviors (e.g., mating, aggression). In fact, Dsk was the only overlapping gene that was downregulated upon social isolation across independent studies (Figure S10A).

As the reviewer pointed out, social isolation upregulated many genes, including those involved in metabolism. Our revised manuscript additionally showed that upregulated but not downregulated genes upon social isolation were substantially conserved across genetic backgrounds or independent DEG studies (Figure 5C and S10A). We speculate that Drosophila has evolved a genetic reprogram where social isolation elevates metabolic gene expression to adaptively induce a metabolic shift for energy storage and fitness. We revised our text accordingly.

Major 3. In lines 219-223, the genomic deletion by mutant or depletion by RNA interference emphasizes the role of neuropeptides DSK and its receptor CCKLR-17D1 in injury-induced clustering behaviors. How about the effect of neuropeptides overexpression? Do they confer injury-induced social interactions to isolated male flies. Meanwhile, in line 238, the transgenic excitation of CCKLR-17D1 neurons emphasizes the function of neuronal synaptic transmission in the pathway. Indeed, both neuropeptide expression and neuronal synaptic connections may be involved in the regulation of injury-induced clustering behaviors. It is recommended to separate the discussion of protein expression and the respective regulatory modes at the neuronal circuit level.

We could not test DSK overexpression effects on injury-induced clustering in socially isolated males since we failed to validate DSK overexpression from a relevant transgenic line (https://flybase.org/reports/FBal0184043.htm). Instead, we provided additional data in the revised manuscript that independent genomic deletions of the CCKLR-17D1 locus (Figure S15) or transgenic silencing of the synaptic transmission in CCKLR-17D1 neurons (Figure S16) suppressed the injury-induced clustering in group-cultured male flies. According to the reviewer's suggestion, we modified our text to better distinguish between the effects of gene/protein expression vs. relevant neuron activities on social behavior plasticity.

Major 4. Since a significant portion of the work in the first half of this paper is focused on elucidating two types of social distance in SNB, is there any difference in the regulation of social network plasticity by Dsk signaling pathway in the short-SD and long-SD lines?

As the reviewer suggested, it will be informative to determine if Dsk signaling for social behavior plasticity is differentially regulated in short- vs. long-SD lines. One technical issue is that genetic factors shaping their SD traits still need to be defined. So, we are limited to performing standard genetic/transgenic experiments using the DGRP lines while retaining their SD phenotypes. Accordingly, our current approach was to compare DSK expression in short- vs. long-SD lines under grouped- vs. isolated-culture conditions. Future studies should address the review comment above.

Minor ones:

Minor 1. There is a color difference between the data spots and the figure legends in Figure 2H.

Corrected.

Minor 2. The anatomical sample images in Figure 4 and Figure 5 require scale bars.

We added scale bars to Figure 6 and 7 in the revised manuscript.

Minor 3. The "grouped" and "grp" in Figures 3B-3F can be unified as "grp", while the "isolated" and "iso" can be unified as "iso". So that the male and female symbols in Figure 3F will not have any deviation in the mark.

We unified the labels throughout the revised manuscript according to the reviewer's suggestion.

Minor 4. The difference in Denmark signals of each group of neurons under the condition of injury should also be compared in Figure 4C.

The DenMark signals were also compared between control and injury conditions (Figure S12).

Minor 5. What is the effect of inactivating CCKLR-17D1 or CCKLR-17D3 by shibire on injury-induced clustering in group-cultured adults in Figure 5E? (This relates to major comment 3)

We actually employed a tetanus toxin light chain (TNT) to block synaptic transmission in CCKLR-17D1 neurons and found that the transgenic manipulation of CCKLR-17D1 neuron activity suppressed injury-induced clustering in group-cultured males (Figure S16). Since (1) our additional data using independent deletion alleles further excluded the possible implication of CCKLR-17D3 in the SNB plasticity (Figure S15) and (2) a transgenic Gal4 knock-in for the CCKLR-17D-3 locus is not available, we focused on the CCKLR-17D1 experiments in our current study and wished to leave more detailed circuit analyses for future studies.

Reviewer #2 (Significance (Required)):

General assessment:

The strengths of this work is that the authors have identified specific lines with short social distance or long social distance by conducting extensive screening experiments. By transcriptome analyses and gene ontology (GO) analyses they revealed genes up or down regulation in the social experience. They have also narrowed down to the DSK signaling involved in the social experience encoding process. However, the study's limitation lies in the lack of clarity regarding the DSK signaling pathway. The mechanisms through which social experiences affect neuronal activity and synaptic connections remain unclear. Further research on upstream and downstream pathways could enhance understanding. Although the article proposes injury-induced clustering behaviors, the key sensory pathways involved in social network behavior plasticity during early social experiences are not well-defined. Conducting sensory deprivation experiments could elucidate sensory involvement. Overall, the study's strengths lie in its comprehensive approach, large sample size, and translational potential. To enhance future research, investigating the complexity of neural mechanisms and expanding the exploration of regulating pathways could be beneficial. Additionally, exploring the ecological relevance of the findings could deepen our understanding of social behavior in natural environments.

Our current work provides a neuroanatomical basis for early-life social memory and experience-dependent plasticity of social-interaction behaviors. We believe future studies will build up the mechanical details for social experience-dependent DSK expression, DSK neuron activity, and behavioral outputs. Regarding the key sensory pathways, we examined injury-induced SNB plasticity of distinct sensory mutants (e.g., olfactory, visual, auditory, etc.) and our revised manuscript provided additional data that norpA-dependent visual sensing might play a crucial role in this process (Figure S9), consistent with the previous finding that vision is required for larval clustering behaviors in Drosophila (https://pubmed.ncbi.nlm.nih.gov/28918946/).

Advance:

Compared to previous studies such as Heiko Dankert et al.'s publication in 2009 in Nature Methods and Assa Bentzur et al.'s publication in 2020 in Current Biology, which also investigated the impact of early life experiences on male social behavior and examined various aspects of social network construction, this study employs a systematic analysis of social network behavior (SNB) in Drosophila, integrating genetic, physiological, and behavioral assessments. The authors conducted detailed and systematic analyses through transcriptome and gene ontology (GO) analyses, including the visualization of gene expression heatmaps, volcano plots, and overlapping analysis of differentially expressed genes (DEGs) between grouped and isolated conditions. Additionally, this research delved into the regulatory pathway of DSK signaling in male-specific SNB plasticity, with a particular focus on the DSK to CCKLR-17D1 signaling, which encodes early social experiences. The research provides valuable insights into the genetic basis and adaptability of social behavior in Drosophila. Moreover, it illuminates the neural mechanisms that underlie social memory and the ability of groups to adapt across different species.

Audience:

Researchers conducting basic research in genetics, neuroscience, behavioral biology, and evolutionary biology, particularly those focused on understanding social behavior and its underlying genetic and neural mechanisms, will find this study highly relevant. Additionally, researchers studying social cognition, social memory, and group dynamics in various species may also be interested in these findings.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Jeong et al. investigate the influence of genetic factors and early-life social experience on social network behaviors in adult Drosophila. Utilizing isogenic DGRP lines, the study correlates social distances with key developmental and physiological traits-developmental time, digging activity, and food intake. The findings suggest that adult flies with shorter social distance -indicating closer proximity to each other-face developmental disadvantages that are offset by the benefits of social grouping. The authors argue for an evolutionary advantage in such social behaviors, suggesting they help compensate for individual developmental deficits. The study further identifies the Dsk signaling pathway as a key mediator of social network behavior plasticity in male flies, particularly under challenging conditions like mechanical injury.

The study undertakes a broad range of behavioral and neurogenetic approaches, demonstrating an extensive scope of research efforts. Despite its ambitious scope, the manuscript lacks a clear rationale and cohesive flow among its sections. The numerous experiments do not merge into a unified narrative, leaving the reader questioning the reasoning and progression behind the experimental choices. The manuscript needs a clearer structure, well-defined hypotheses, and more detailed methodological descriptions. Greater emphasis on novelty and better integration with existing literature are also needed. The lack of control experiments and adequate statistical analysis weakens some conclusions.

Major comments

1. The authors show that flies in short SD lines reduce their activity over time, leading to the formation of social clusters (Figure 1B). This clustering could potentially be attributed to reduced activity rather than active social preferences. It would be informative to test whether these SD flies exhibit similar social behaviors when placed in a larger arena, to test if the clustering persists under varied environmental conditions.

Short-SD flies did not reduce their moving speed over time when we placed a single fly in the original arena and assessed its locomotor behavior individually (Figure S2). Thus, it is likely that the reduced activity in a group of short-SD flies is an effect of clustering over time but not necessarily the cause. We also confirmed that short and long SD lines retain their clustering property even in a larger arena (8.5 cm in diameter) (Figure S3). We included these new data in our revised manuscript to better demonstrate active social preferences in the DGRP lines.

2. In lines 78-79, the authors claim that "short-SD flies gradually reduced SD over time and stayed in the cluster." However, the study established SD clustering by only analyzing behavior during the last quarter of a 10-minute window, assigning a single data point to each fly and taking the average for group SD. Yet, a single value cannot demonstrate whether initially formed clusters remained stable-unchanged-over time. To strengthen this point, the authors could investigate dynamic changes in SD over a longer period to demonstrate stability, or alternatively, adjust the language to better convey the findings. Additionally, including a time scale in Figure 1B would enhance the clarity of these findings.

We traced dynamic changes in SD and walking speed of representative DGRP lines over the 10-minute window (Figure 2A and 2B) and modified our text accordingly in the revised manuscript. We also included a time scale in Figure 1B and relevant figures.

3. The statistical analysis presented in Figure 2C-D raises concerns. It appears that feeding and digging efficiency in both SD type lines benefit from socialization, suggesting that the effects attributed to SD might stem from the overall digging and feeding activity of each line. Therefore, it is crucial to integrate both social distance (short vs. long) and socialization (grouped vs. isolated) into the analysis using methods that allow for the assessment of confounding effects (interaction), such as two-way ANOVA or regression, depending on the data. This would help authors to clarify whether isolation reduces feeding overall (both line types) and determine if this reduction is more pronounced in short-SD lines. Additionally, it is counterintuitive that lines with more larvae per cluster show worse digging efficiency when previous studies, such as Dombrovski et al. (2017), have shown that larger groups of larvae typically exhibit better digging efficiency. This discrepancy highlights the need for a thorough re-evaluation of the data and assumptions regarding group dynamics and their impact on resource access.

As the reviewer suggested, we employed ordinary or aligned ranks transformation 2-way ANOVA (depending on the normality and equal variance of a given dataset) to determine if social distance and socialization cooperatively contribute to developmental phenotypes. Our new analyses confirmed significant interaction effects of social distance and socialization on most developmental phenotypes tested (i.e., larval digging activity, developmental time, %male progeny, and %eclosion success). These results convincingly support that short-SD larvae benefit more from socialization than long-SD larvae to compensate for the inferior phenotypes in isolated individuals. We speculate that the feeding amount of isolated long-SD individuals may be saturating for normal development (i.e., developmental time, %male progeny), possibly explaining the lack of interaction effects on food intake while displaying developmental inferiorities only in isolated short-SD individuals. We reason that grouped long-SD flies should not necessarily display poorer digging activity than grouped short-SD flies since isolated long-SD individuals displayed much higher digging activity than isolated short-SD individuals. Consistent with the previous finding, both SD lines showed better digging efficiency when grouped than isolated. We included these new analyses in the revised manuscript and modified our text accordingly. To clarify any statistical issues, we included a summary of all our statistical analyses performed in the revised manuscript (Dataset S5).

4. The choice to use the percentage of male progeny as a measure of developmental success is confusing, especially without an explanation for why it is favored over measures like overall progeny survival rates. As with digging and feeding, the statistical analysis should include an examination of potential interaction effects to fully assess how social conditions impact developmental outcomes.

The percentage of male progeny was one of the most evident developmental phenotypes on which social distance and socialization showed significant interaction effects. In the revised manuscript, we further included the percentage of eclosed flies as a measure for the overall progeny survival rate (Figure 3F) and performed 2-way analyses to validate the significant interaction effects of social distance and socialization on various larval/developmental phenotypes. Please see our response to reviewer #3, major comment #3 above.

5. The rationale for using physical injury to induce SNB in the study is not clearly explained, raising concerns about the potential impact of injury on overall locomotion. Before employing such a method in sociality experiments, it is crucial to demonstrate that the injury does not affect locomotion. Additionally, the study's methodologies for transitioning between grouped and isolated cultures (present only in Figure 2I and not in the methods section), as well as the specific methods used to measure social distance (SD) in isolated flies, are not sufficiently detailed. This lack of clarity complicates the evaluation of the study's conclusions.

To determine if the long-SD lines express their social behaviors selectively (e.g., upon physiological challenges), we introduced physical injury to the SNB analysis. There was a positive correlation between locomotion activity and SD trait among DGRP lines (i.e., DGRP lines with low walking speed and centroid velocity exhibited short-SD phenotypes in general) (Figure 1D). This observation thus prompted us to hypothesize that modest injury may reduce locomotor activity in individuals, facilitate their interactions in a group, and shorten the overall SD. The mechanical injury actually shortened SD in both the short- and long-SD lines (Figure 4D and S7A). Under the same experimental condition, mechanical injury reduced walking speed and centroid velocity only in the long-SD lines (Figure S8), whereas social isolation blunted the injury effects (Figure 4D, S7A, and S8). We reason that our injury condition does not severely impair general locomotion per se to abolish or overestimate SNB, but low activity in grouped long-SD flies is likely a consequence of their injury-induced clustering. We clarified our original text for the rationale and included the new data in the revised manuscript (Figure S8). We also revised the method text for the transitions between grouped and isolated cultures, as well as for measuring SD in isolated flies.

6. Lines 104-106 "The clustering property of short-SD lines may have evolved as a compensation mechanism for their developmental inferiority in individuals". To support this claim, the authors should assess the significance of interactions terms as stated earlier.

Please see our responses to the reviewer’s relevant comments above (reviewer #3, major comments #3 and #4).

7. In Figure 4, the authors conclude that Drosulfakinin (DSK) signaling encodes early-life experiences for SNB plasticity. It is crucial for the authors to differentiate whether changes in feeding behavior are directly due to DSK or if they are secondary effects resulting from altered social interactions mediated by DSK.

Previous studies demonstrated that DSK is a satiety-signaling molecule whose expression is elevated upon feeding to suppress food intake (https://pubmed.ncbi.nlm.nih.gov/34398892/; https://pubmed.ncbi.nlm.nih.gov/32314736/; https://pubmed.ncbi.nlm.nih.gov/25187989/; https://pubmed.ncbi.nlm.nih.gov/22969751/). Under our experimental context, social isolation downregulated DSK expression and DSK neuron activity, whereas isolated larvae rather reduced their food intake. It is thus unlikely that changes in the feeding behavior of isolated larvae directly implicate DSK-dependent satiety signaling. We discussed this issue in our revised manuscript.

8. In Figure 4, the data show that DSK peptide is significantly increased in cell bodies in grouped long DS lines when compared with grouped short DS lines (Figure 4B). However, no changes are reported at the level of DSK projection levels when comparing these groups. Can the authors clarify this?

The SD-trait effects on DSK levels were evident in cell bodies but not in DSK neuron projections. We reason that axonal transport or processing of the neuropeptide was limiting under the group-culture condition. These observations might also be relevant to our conclusion that Dsk is not crucial for shaping the SD traits per se. We revised our text accordingly.

9. Additionally, the data show that DSK activity is reduced by isolation in both types of SD. To clarify if this effect is driven by isolation only, and not type of line (short vs long SD line), the interaction term should be tested. Furthermore, it is not clear what lines are used in live imaging (e.g., Figure 4C-F).

We detected no significant interaction effects of SD type and social isolation on DSK expression (Figure 6B). Live-brain imaging of the GCaMP-expressing DSK neurons was performed using a transgenic line (i.e., Dsk-Gal4>UAS-GCaMP) in a wild-type background. Since genetic factors shaping the SD traits were not defined in each DGRP line, we could not combine the transgenes with DGRP backgrounds while retaining their respective SD phenotypes (please also see our response to reviewer #2 major comment #4 above). Nonetheless, the GCaMP imaging demonstrates that (1) either injury or social isolation alone significantly affects DSK neuron activity, but (2) the two conditions act independently on the GCaMP signals (i.e., no significant interaction effects). We clarified it in our revised manuscript and displayed each genotype used in our imaging experiments.

10. In the 'Male-specific DSK-CCKLR-17D1 signalling mediates SNB plasticity' section (line 217), the analysis should include an interaction term to account for the possible confounding effects of isolation and injury on SD. This would aid in determining whether the impacts of social isolation and injury on DSK signalling and SNB plasticity are independent of each other or if they interact in significant ways, as stated by the authors.

Throughout our revised manuscript, we performed 2-way analyses to validate the interaction effects of isolation and injury on SD and support our conclusion. We also included a summary of all our statistical analyses performed in the revised manuscript (Dataset S5).

Minor comments

1. The introduction section would also benefit from major rewriting to clearly indicate the research gap and hypothesis tested. The introduction section would also benefit from major rewriting to clearly indicate the research gap and hypothesis tested. The manuscript would benefit from a more thorough integration of previous studies related to Drosophila social behavior (e.g., Blumstein, D. T. et al., 2010; Schneider, J., Dickinson, M. H., & Levine, J. D., 2012; Simon, A. F. et al., 2012; Ramdya, P. et al., 2015). While the current references are adequate, a more detailed discussion of how this study builds upon and diverges from existing literature would be beneficial.

The introduction of our original manuscript starts from previous findings on Drosophila social behaviors and clearly indicates what remains elusive, thereby defining our biological questions. We further explain why we focus on SD among other social network measures published previously and outline our approaches for new findings in this study (i.e., the principles of social network behavior and its plasticity). Since our original text was written in a concise manner, we revised our text in both the introduction and result sections to give a more detailed description of what earlier studies have discovered according to the reviewer suggestion.

2. A better description of methods, especially behavioral approaches, could vastly help in understanding the results. Clarifying the methodologiy, particularly the behavioral approaches, would greatly enhance the understanding of the results. Also, the method for quantifying the total number of larvae per vial is unclear, particularly whether variations in larval density were considered. This is crucial, as different densities could affect the available sensory cues necessary for larval aggregation, such as vision (e.g. Dombrovski et al. Curr Biol. 2019). Better descriptions of the results and inclusion of exact statistical analyses used in support of the claims are also needed.

We revised our method text to better describe our experimental conditions. We further described how we controlled larval density to prepare group-cultured larvae and adults for analyzing larval behaviors and developmental phenotypes. Finally, we included a summary of all our statistical analyses performed in the revised manuscript (Dataset S5).

3. Some terms and descriptions in the manuscript are somewhat ambiguous, such as "social memory" and "adaptive social plasticity" and should be better defined.

We better defined the two key short terms in the introduction of our revised manuscript.

4. Line 86-89: "Social interactions compensate for developmental inferiority in short-SD larvae Why do flies display SNB? One clue comes from the previous observation that Drosophila larvae collectively dig culture media and improve food accessibility, possibly facilitating their constitutive feeding during early development…" – This paragraph could be moved to the introduction section.

As we reorganized the introduction in our revised manuscript, we feel it should be fine to leave the paragraph above in the original context.

5. In lines 77-78, the manuscript mentions that the locomotion trajectories of individual flies confirm certain characteristics but fails to provide an analysis of individual locomotion metrics, e.g., tortuosity, distance walked, etc. The authors should add quantitative analysis to support claims about trajectories or alternatively rephrase the sentence to remove any claims about the trajectories of flies.

As the reviewer suggested, we added quantitative analyses of cumulative walking distances over time and total walking distances in individual flies to our revised manuscript (Figure 2D and S1C).

6. After screening 175 strains, three short and long SD lines were selected. It would be good if justification for the authors' choice were included, as the selected lines were not the ones with the longest or shortest SD as seen in Figure 1C.

We ranked individual DGRP lines for each of the two group properties (i.e., SD and centroid velocity) and then selected the top and bottom three lines based on their average ranking. We included this rationale in our revised manuscript.

7. Other comments:

• Line 72-73: What correlation was performed? This should be included in the results/methods section.

As described in the figure legend of our original manuscript, the significance of the correlation was determined by Spearman correlation analysis. We further included the method description in the results and methods section of our revised manuscript.

• Line 113: Change "pre-trained colleagues" to "pre-trained flies".

Changed.

• Lines 321 and 325: Use "3D" instead of "2D" as three dimensions are given?

Corrected.

• Ensure all figures are correctly scaled and aligned.

We revised our figures to avoid any of these issues.

• Video: Including short videos for each behavioral test (e.g., feeding) would help in understanding it.

We included representative video files for SNB and aggression assays in the revised manuscript (Video S1-S12).

• Figure 4 should include control neurons that do not change with social grouping; authors should also show ROI.

We included new data for control neurons (Figure S13, Pdf-Gal4>UAS-GCaMP7f) and also showed ROI for quantification in our revised manuscript (Figure 6C and S13).

• Line 27, 86: Change "inferiority" to "disadvantage".

We feel inferiority fits better in the context of our overall study.

Reviewer #3 (Significance (Required)):

This study extends existing knowledge by linking specific genetic pathways to behavioral outcomes in a well-established model system, providing new insights into the genetic and neural basis of social behavior. The use of DGRP lines to dissect the impact of genetic variation on behavior is particularly valuable. The identification of the Dsk signaling pathway as a mediator of these behaviors under stress is interesting. However, the study would benefit from more in-depth statistical analysis and expanded experimental designs to solidify the conclusions. It should also more clearly highlight the novelty of its findings and better integrate them with the current literature on Dsk signaling and social behaviors.

My expertise is in behavioral neuroscience. The insights from this study promise to deepen our understanding of the genetic and neural mechanisms behind social behaviors. The potential implications of this research are likely to extend well beyond Drosophila, influencing studies across various species.

Reviewer #4 (Evidence, reproducibility and clarity (Required)):

Summary:

The manuscript investigates the role of Drosulfakinin (Dsk) signaling in Drosophila social network behavior (SNB) and its plasticity based on early-life experiences. The study employs a systematic analysis using 175 inbred strains to link short social distance (SD) with developmental time, food intake, and activity levels. Key findings suggest that social interactions during development compensate for individual developmental inferiority and that early-life social experience is necessary for adaptive social behaviors in adults. The genetic basis of SNB is further explored through transcriptome analyses, implicating Dsk and one of its receptors in mediating these behaviors.

Major comments:

Are the key conclusions convincing?

The key conclusions are well-supported by the data presented. The association between early-life social interactions and adult social behaviors is convincingly demonstrated through multiple experimental setups.

We appreciate the reviewer’s positive feedback on our rigorous approaches and key conclusions.

Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

Some claims, particularly those regarding the evolutionary implications of Dsk signaling and its conservation across species, might benefit from being presented as hypotheses or speculations rather than definitive conclusions. This would align with the current evidence while acknowledging the need for further investigation.

As the reviewer suggested, we toned down our claims on the evolutionary implications of Dsk signaling.

Would additional experiments be essential to support the claims of the paper?

Measure aggression and male-male courtship behavior in the 6 DGRP lines to examine whether SD correlates with these behaviors.

Aggression but not male-male courtship behaviors correlated with SD phenotypes in the 6 DGRP lines. We included the new data in our revised manuscript (Figure S4 and S11). Please also see our response to a relevant reviewer comment above (reviewer #1, major comment #7).

Include behavior results of flies tested in Figures 4C and D.

We included the behavior data in our revised manuscript (Figure S12A).

Repeat the CCKLR-17D1 experiments shown in Figures 5 F and G for CCKLR-17D3 to provide extra evidence that CCKLR-17D1 mediates DSK's effects on SNB.

We employed a transgenic Gal4 knock-in for the CCKLR-17D1 locus to specifically manipulate the activity of CCKLR-17D1-expressing neurons. However, a Gal4 knock-in line for the CCKLR-17D3 locus was not available for pairwise comparison. We instead provide extra evidence for CCKLR-17D1 function in SNB plasticity by showing that (1) independent genomic deletions of CCKLR-17D1 but not CCKLR-17D3 suppressed injury-induced clustering in group-cultured males (Figure S15) and (2) blocking of synaptic transmission in CCKLR-17D1 neurons phenocopied CCKLR-17D1 deletion (Figure S16). Please also see our response to a relevant reviewer comment above (reviewer #2, minor comment #5)

Are the suggested experiments realistic in terms of time and resources?

These experiments are realistic and feasible within typical research timelines. These might require a few months and moderate funding.

According to the reviewer suggestions, we included new pieces of data in our revised manuscript to address the reviewer concerns and further support our conclusions.

Are the data and the methods presented in such a way that they can be reproduced?

The methods section is detailed, providing sufficient information for replication.

We appreciate the reviewer’s positive feedback on our method description.

Are the experiments adequately replicated and statistical analysis adequate?

The experiments appear to be adequately replicated, and the statistical analyses are generally appropriate. However, ensuring consistent selection of statistical methods can further support the evidence presented (Figures 2C and D).

We performed more appropriate statistical analyses in the revised manuscript (e.g., 2-way ANOVA of the data presented in our original Figure 2C and 2D) and included a summary of all the statistical analyses in the revised manuscript (Dataset S5). Please also see our responses to the reviewer comments above (reviewer #3, major comments #3 and #10; reviewer #3, minor comment #2).

Minor comments:

Specific experimental issues that are easily addressable:

Ensure clarity in the presentation of figures and legends. Some figures could benefit from more detailed legends explaining all aspects of the data shown.

We revised our figures and figure legends to address this issue and improve clarity.

Are prior studies referenced appropriately?

The manuscript references prior studies appropriately, providing a solid context for the current research.

We appreciate the reviewer comment.

Are the text and figures clear and accurate?

The text is clear, but some figures, particularly those with complex data, could be more informative with additional annotations.

We revised our figures and figure legends to address this issue.

The larvae pictures in Figure 2A should be replaced with ones with higher resolution with drawn larval contours.

We replaced the larval pictures with higher resolution and indicated individual larvae with arrows in the revised manuscript (Figure 3A).

Scale bars are missing in most of the images shown.

We added scale bars to our revised figures.

Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Consider providing a graphical abstract summarizing the key findings. This would aid readers in quickly grasping the main conclusions. Additionally, breaking down complex figures into simpler, more focused panels might improve readability.

As the reviewer suggested, we split complex figures into simpler ones to improve the readability of our revised manuscript and data. We also provided a graphical abstract summarizing our findings (Figure 8).

Reviewer #4 (Significance (Required)):

Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

This study provides significant conceptual advances in understanding the genetic and neurobiological basis of social behavior in Drosophila. By linking early-life social experiences to adult social behaviors, it highlights the importance of developmental context in shaping adult phenotypes.

Place the work in the context of the existing literature (provide references, where appropriate).

The work builds on previous studies on Drosophila social behavior and neurogenetics. It extends the current understanding by integrating developmental and adult behaviors with genetic and molecular analyses. References to foundational works in Drosophila social behavior and recent studies on neuropeptide signaling are well-placed.

State what audience might be interested in and influenced by the reported findings.

Researchers in the fields of neurogenetics, behavioral ecology, developmental biology, and evolutionary biology will find this work particularly relevant. It also has implications for those studying social behavior across species, including mammals.

Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

Expertise: Neurogenetics, Behavioral Neuroscience, Drosophila Genetics, Social Behavior, Bioinformatics. I have sufficient expertise to evaluate the genetic, behavioral, and transcriptomics aspects of the study. Specific details on the imaging studies might require additional expert evaluation.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Lim C. 2023. Gene expression analysis of 6 DGRP lines based on clustering behavior and housing. EBI European Nucleotide Archive. PRJEB61423

    Supplementary Materials

    Figure 1—source data 1. Correlation of SD, walking speed, and centroid velocity across 175 DGRP lines.
    Figure 2—source data 1. Quantitative locomotor metrics in short- and long-SD DGRP lines.
    Figure 3—source data 1. Quantitative analysis of larval SNB and developmental metrics.
    Figure 4—source data 1. Quantitative analysis of adult SNB and social plasticity.
    Figure 5—source data 1. Normalized gene expression in individual DGRP lines under grouped vs. isolated culture conditions.
    Figure 5—source data 2. DEG analyses between distinct social groups (short vs. long SD; or grouped vs. isolated).
    Figure 5—source data 3. Comparative analyses of social group-specific DEGs from independent studies.
    Figure 5—source data 4. DEG analyses among individual DGRP lines.
    Figure 5—source data 5. Correlation of SNB to food intake, starvation-induced activity, and aggression among DGRP lines.
    Figure 6—source data 1. Quantitative analysis of DSK neuron activities under distinct social contexts.
    Figure 7—source data 1. Quantitative analysis of SNB plasticity in genetic and transgenic Drosophila models for DSK-DSK receptor signaling.
    MDAR checklist

    Data Availability Statement

    The datasets generated and analyzed during the current study are included in source data files or available in the European Nucleotide Archive repository (accession number PRJEB61423). The python scripts that support the findings of this study are available from the author's GitHub webpage under the links https://github.com/taejoonlab/tracking-fly, (copy archived at Jeong et al., 2021a) and https://github.com/KJKwon/2023_FlyBehavior, (copy archived at Jeong et al., 2023).

    The following dataset was generated:

    Lim C. 2023. Gene expression analysis of 6 DGRP lines based on clustering behavior and housing. EBI European Nucleotide Archive. PRJEB61423


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