Over-expression of Pico affects Border Cell Migration Rate

To further test the hypothesis that pico function is mediated by the SCAR/WAVE complex, the migration rate was quantified using live cell imaging of border cell migration. Using an automated ImageJ plugin to accurately track the border cell cluster and protrusion dynamics made quantifying the time lapse movies more time effective, accurate and ensured

consistency between different egg chambers and genotypes, as described in Chapter 4, Section 4.4.

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specifically analyse border cell migration behaviour and protrusion dynamics. Poukkula et al.

further described a border cell migration phenotype for two receptor tyrosine kinase guidance cues by linking cluster behaviour and actin based protrusions, when a dominant negative form of the receptor was expressed. Multiple chemoattractants are responsible for the distinctive migratory behaviour of the border cell cluster. PVF1 (Platelet derived growth factor - PDGF) and vascular endothelial growth factor (VEGF) bind to two receptor tyrosine kinases present on follicle cells. When PVR and EGFR signalling is blocked border cell activity is disturbed, despite frequent protrusion activity (Duchek et al., 2001; Janssens et al., 2010; Prasad and Montell, 2007). The first half of migration has been shown to be mostly

controlled by PVR activation, whereas the second half relies on EGFR. In egg chambers where PVR guidance was reduced, EGFR activation occurred earlier resulting in premature tumbling behaviour normally only seen in the second half of migration. Active PVR receptors have been found to be highly concentrated at the front of polarised cells, compared to sides and been shown to play a key role in the stabilisation of forward facing protrusions

(Janssens et al., 2010; McDonald et al., 2006; Poukkula et al., 2011).

The custom macro was used to separate the cluster into front, back and side segments, and record and measure the protrusions for each of the sections. In addition to logging the protrusion behaviour, the macro automatically tracked the movement of the cluster in XY, enabling information such as migration speed and directed movement to be calculated.

c306-GAL4, UAS-Lifeact-eGFP female flies were crossed to males of various genotypes, generating adult flies expressing the UAS-Lifeact-eGFP construct and one of the following UAS transgenes, Dominant negative (DN)-PVR, picoRNAi49, Pico OE, SCAR RNAi, and both pico OE and SCAR RNAi together. c306-GAL4 expressed UAS transgenes in both the

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migratory border cells and the polar cells, as a result expression is switched on earlier than with slbo-GAL4, which expresses in the migratory follicle cells only. The first half of

migration was imaged by live cell imaging with a two minute time interval. Lifeact-eGFP was used to generate these movies, as it specifically labels actin-based protrusions (Riedl et al., 2008). The average duration of the first half of migration was calculated for the various genotypes using half the total distance of migration (As the crow flies), measured from the anterior tip of the egg chamber to the nurse cell-oocyte boundary. Frames where the cluster was still partially attached to the epithelium were not counted.

The results indicate that there is a significant decrease in migration duration between wild type (c306>Lifeact-eGFP) (48.6 mins) and DN-PVR (134.8 mins) (One-way ANOVA, Tukeys, P<0.001). However, this is not surprising as PVR is well documented to play an important role in border cell migration. Border cells deficient in PVR signalling have been characterised to show premature tumbling behaviour and a delay in the initial phases of migration

(Poukkula et al., 2011). Surprisingly there was no significant difference in migration duration when comparing wild type to picoRNAi49 ( 73.1 mins), picoOE (93.25 mins), SCAR RNAi (56 mins).

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To further investigate the function of different UAS transgenes GFP projected images were analysed using the custom border cell macro. The migration rate per frame was calculated for each of the genotypes, including wild type. The macro calculated the average migration rate based upon the distance travelled by the centre of the cluster between each frame. The results show that c306>GFP had a migration rate of 1.4 µm/min. The previously

documented DN-PVR had a migration rate of 0.88µm/min which was significantly lower than wild type (One-way ANOVA, Tukeys, P<0.001, n=9). This value differs from the published frame by frame rate of DN-PVR in early migration (Approximately 0.2 µm/min), however the wild type control also had a lower rate (Approximately 0.9 µm/min) (Poukkula et al., 2011). These differences can be explained by the difference in border cell specific driver and

Figure 5.6. Border cell migration duration is not an indicator of defective migration.

(A) Graph showing duration in minutes of Wildtype, DN-PVR, PicoRNAi49, PicoOE, SCAR RNAi and SCARRNAi + PicoOE, displayed in different colours. Error bars show the standard error of the mean. Significance bar represents a P value less than 0.001.

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reporters used (see Chapter 3 discussion). picoRNAi49 and picoOE also showed a significant decrease in migration rate, 1.2 µm/min and 1.1 µm/min, respectively relative to wild type, 1.4 µm/min (One-way ANOVA, Tukeys, P<0.05, n=12 and 12). There was no significant difference in the migration rate of SCAR RNAi, 1.4 µm/min (One-way ANOVA, Tukeys, P>0.05, n=8) which was surprising given that picoRNAi49 and SCAR RNAi displayed similar behaviour when fixed samples were analysed.

When both SCAR RNAi and pico OE were expressed together there was a slight increase in migration rate 1.8 µm/min, however this was not significant when compared to wild type (One-way ANOVA, Tukeys, P>0.05, n=7). When comparing pico OE + SCAR RNAi migration rates to the two transgenes individually, expressing both together showed a significant increase in migration rate, 1.79µm/min compared to picoOE (1.1 µm/min) and SCAR RNAi (1.4 µm/min) (One-way ANOVA, Tukeys, P<0.001). Expressing both together rescued the migration rate back to the wild type value, again suggesting that SCAR RNAI can suppress the negative effect of ectopic pico on border cell migration.

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