Hypoxia controls plasma membrane targeting of polarity proteins by dynamic turnover of PI4P and PI(4,5)P2

  1. Juan Lu
  2. Wei Dong
  3. Gerald R Hammond  Is a corresponding author
  4. Yang Hong  Is a corresponding author
  1. Department of Cell Biology, University of Pittsburgh, United States

Abstract

Phosphatidylinositol 4-phosphate (PI4P) and phosphatidylinositol 4,5-biphosphate (PIP2) are key phosphoinositides that determine the identity of the plasma membrane (PM) and regulate numerous key biological events there. To date, mechanisms regulating the homeostasis and dynamic turnover of PM PI4P and PIP2 in response to various physiological conditions and stresses remain to be fully elucidated. Here, we report that hypoxia in Drosophila induces acute and reversible depletion of PM PI4P and PIP2 that severely disrupts the electrostatic PM targeting of multiple polybasic polarity proteins. Genetically encoded ATP sensors confirmed that hypoxia induces acute and reversible reduction of cellular ATP levels which showed a strong real-time correlation with the levels of PM PI4P and PIP2 in cultured cells. By combining genetic manipulations with quantitative imaging assays we showed that PI4KIIIα, as well as Rbo/EFR3 and TTC7 that are essential for targeting PI4KIIIα to PM, are required for maintaining the homeostasis and dynamic turnover of PM PI4P and PIP2 under normoxia and hypoxia. Our results revealed that in cells challenged by energetic stresses triggered by hypoxia, ATP inhibition and possibly ischemia, dramatic turnover of PM PI4P and PIP2 could have profound impact on many cellular processes including electrostatic PM targeting of numerous polybasic proteins.

Editor's evaluation

The authors show that hypoxia leads to previously unappreciated effects on levels of plasma membrane PI4P and PIP2, which affects membrane targeting of proteins important for normal cellular physiology, including cell polarity. They provide insight into the identity of the PI4Ks that are responsible for regenerating plasma membrane PIP2 following return to normoxia. These findings are novel and provide multiple interesting insights for those studying phosphoinositide biology as well as cellular responses to hypoxic stress and recovery.

https://doi.org/10.7554/eLife.79582.sa0

Introduction

The inner leaflet of the plasma membrane (PM) is the most negatively charged membrane surface due to its enrichment of phospholipids including phosphatidylserine and phosphoinositides (PPIns) PI4P (phosphatidylinositol (PtdIns) 4-phosphate) and PIP2 (PtdIns 4,5-biphosphate (PI(4,5)P2)). The unique combination of PI4P and PIP2 is crucial to determine the PM identity by regulating many key biological events in the PM including cell signaling, endocytosis, and channel activation (Hammond et al., 2012). Moreover, for proteins with positively charged domains/surfaces, electrostatic binding to the PM is a fundamental mechanism underlying the regulation of their subcellular localization and biological activity (McLaughlin and Murray, 2005). One typical example can be found in polarity proteins that play essential and conserved roles in regulating various types of cell polarity such as apical-basal polarity in epithelial cells (Bailey and Prehoda, 2015; Dong et al., 2020; Dong et al., 2015; Hong, 2018; Lu et al., 2021). Recent discoveries from our group showed that multiple polarity proteins such as Lgl, aPKC, and Dlg contain positively charged polybasic motifs that electrostatically bind the negatively charged inner surface of PM (Dong et al., 2020; Dong et al., 2015; Lu et al., 2021), and such electrostatic PM targeting has now emerged as a mechanism essential for regulating their subcellular localization and biological activities in cell polarity.

While mechanisms regulating the interaction between polybasic motifs and PM have been relatively well studied (Bailey and Prehoda, 2015; Dong et al., 2020; Dong et al., 2015; Hong, 2018; Lu et al., 2021), much less is known how the homeostasis and turnover of PM PI4P and PIP2 may impact the electrostatic PM targeting. Although sophisticated mechanisms exist to maintain the steady state levels of PM PI4P and PIP2 under normal conditions (Chen et al., 2017; Dickson et al., 2014; Wang et al., 2019), our previous live imaging experiments in Drosophila showed a striking phenomenon that hypoxia induces acute and reversible loss of PM localization of polybasic polarity proteins Lgl, aPKC, and Dlg in epithelial cells (Dong et al., 2020; Dong et al., 2015; Lu et al., 2021), likely through reducing intracellular ATP levels (Dong et al., 2015). Our previous studies also showed that PM PIP2 could be reversibly depleted under hypoxia (Dong et al., 2015), suggesting that a potential connection from hypoxia to ATP inhibition to PM phospholipids depletion to loss of electrostatic PM targeting of polybasic proteins. However, to date how PM PI4P levels are regulated under hypoxia is unknown. Even less is known about the mechanisms through which hypoxia and ATP inhibition impact PM PI4P and PIP2 levels, and consequently the electrostatic PM targeting of numerous proteins.

In this report, we carried out quantitative live imaging experiments in Drosophila and cultured mammalian cells using multiple genetically encoded sensors to show that acute hypoxia induces dramatic but reversible depletion of PM PI4P and PIP2, accompanied by concurrent loss of PM localization of polybasic polarity protein Lgl. Using genetically encoded ATP sensors, we also confirmed a real-time correlation between the intracellular ATP levels and PM levels of PI4P and PIP2 in cultured cells. We further identified that PI4KIIIα (PtdIns-4 kinase IIIα) and its PM targeting machinery are required for the proper dynamic turnover of PM PI4P and PIP2 under hypoxia and ATP inhibition, as well as for properly restoring the post-hypoxia electrostatic PM targeting of Lgl. Our studies reveal a potential regulatory mechanism that dynamically controls PM PI4P and PIP2 levels in response to hypoxia and ATP inhibition. Our results suggest that genetic deficiencies in regulating such dynamic turnover of PM PI4P and PIP2 could have profound impact on cell physiology including polarity, when cells are challenged by energetic stresses triggered by hypoxia, ischemia and ATP inhibition.

Results

Hypoxia triggers acute and reversible loss of PM PI4P and PIP2

Based on a serendipitous observation that PM targeting of polybasic polarity protein Lgl appeared to be sensitive to hypoxia (Dong et al., 2015), we previously established custom live imaging assays (see below) to demonstrate that all three polybasic polarity proteins, Lgl, aPKC, and Dlg, showed acute and reversible loss of PM targeting under 30–60 min of hypoxia (0.5% O2) in Drosophila follicle and embryonic epithelial cells in vivo (Dong et al., 2020; Dong et al., 2015; Lu et al., 2021). Since PM PIP2 also appeared to be transiently depleted under hypoxia in such assays (Dong et al., 2015), we decided to systematically investigate how hypoxia impacts the PM PI4P and PIP2 levels in vivo. We used follicular epithelial cells of Drosophila ovaries as the primary system as they are well established for ex vivo live imaging (Prasad and Montell, 2007) and for genetic manipulations such as RNAi knock-down.

We generated transgenic flies that ubiquitously express the PI4P sensor P4M × 2::GFP (Sohn et al., 2018) as well as PIP2 sensors PLCδ-PH::GFP and PLCδ-PH::RFP (hereafter referred as PLC-PH::GFP and PLC-PH::RFP, respectively) (Wills et al., 2018). Consistent with PI4P being mostly enriched at both PM and membranes of intracellular compartments such as endosomes and Golgi, P4M × 2::GFP can be seen in both PM and intracellular puncta in follicle epithelial cells (Figure 1A). To investigate hypoxia-induced turnover of PI4P and PIP2, ovaries dissected from flies expressing both P4M × 2::GFP and PLC-PH::RFP were mounted and imaged in custom micro chambers that can be flushed with either 0.5% O2/99.5% N2 gas mixture for hypoxia or normal air for reoxygenation. Within ~60 minutes of hypoxia, both PI4P and PIP2 sensors were gradually lost from PM, with PM PLC-PH::RFP diminished faster than PI4P (Figure 1A, Figure 1—video 1). Once the imaging chamber was reoxygenated by flushing with normal air, both sensors rapidly recovered to the PM within ~10 min. At single-cell level, recovery of PM P4M × 2::GFP clearly and consistently preceded the PLC-PH::RFP (Figure 1A, Figure 1—video 1). Image quantification (see Materials and methods) further confirmed such differences in turnover dynamics between PM P4M × 2::GFP and PLC-PH::RFP (Figure 1A’). The faster depletion under hypoxia and delayed replenishment during reoxygenation of PM PIP2 suggest that PIP2 depletion likely involves its conversion to PI4P and its resynthesis depends on the recovery of PM PI4P.

Figure 1 with 3 supplements see all
Hypoxia induces acute and reversible loss of P4M × 2::GFP and PLC-PH::RFP from the PM in Drosophila follicle cells.

(A–C) Representative frames showing follicle cells coexpressing P4M × 2::GFP and PLC-PH::RFP (A) or P4M × 2::GFP and Lgl::RFP (B) or PLC-PH::GFP and Lgl::RFP (C) undergoing hypoxia and reoxygenation. In A, at 1:04:00, asterisks (*) highlight cells that had already recovered P4M × 2::GFP but not PLC-PH::RFP. (A’–C’) Quantification of PM localizations of P4M × 2::GFP and PLC-PH::RFP (A’, n=18, 18, Figure 1—source data 1) or P4M × 2::GFP and Lgl::RFP (B’, n=20, 20, Figure 1—source data 2) or PLC-PH::GFP and Lgl::RFP (C’, n=20, 20, Figure 1—source data 3) during hypoxia and reoxygenation. PM Index: ratio of mean intensity of PM and cytosolic signals, normalized by the average value of the first three frames. Time stamp in hr:min:sec format. Scale bars: 5 µm.

Figure 1—source data 1

Hypoxia induces acute and reversible loss of PM PI4P and PIP2 in Drosophila follicle cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig1-data1-v2.xlsx
Figure 1—source data 2

Hypoxia induces acute and reversible loss of PM PIP2 and Lgl in Drosophila follicle cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig1-data2-v2.xlsx
Figure 1—source data 3

Hypoxia induces acute and reversible loss of PM PI4P and Lgl in Drosophila follicle cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig1-data3-v2.xlsx

In addition, under hypoxia the disappearance of P4M × 2::GFP intracellular puncta always preceded the depletion of PM P4M × 2::GFP. PM PI4P showed a transient increase at early phase of hypoxia likely due to depletion of intracellular PI4P leading to increased amounts of free P4M × 2::GFP sensor that binds PM PI4P (Figure 1A and A’). Under reoxygenation, PM P4M × 2::GFP consistently recovered before the appearance of intracellular P4M × 2::GFP puncta, although the latter became brighter after recovery (Figure 1A, Figure 1—video 1). Such early depletion of intracellular PI4P pool under hypoxia and its delayed replenishment under reoxygenation suggest that cells appear to prioritize the maintenance of PM PI4P pool to the intracellular pool of PI4P under energetic stress such as hypoxia.

Finally, we investigated how electrostatic PM targeting of Lgl, a polybasic polarity protein carrying a typical polybasic motif (Dong et al., 2015), correlates with hypoxia-induced turnover of PM PI4P and PIP2. Quantitative live imaging of follicle epithelial cells expressing endogenous Lgl::RFP together with PLC-PH::GFP or P4M × 2::GFP showed that under hypoxia the loss of PM Lgl::RFP preceded PIP2 and PI4P, while under reoxygenation PM recovery of Lgl::RFP lagged behind both (Figure 1B, C, Figure 1—videos 2; 3). Such results are consistent with previous studies that electrostatic PM targeting of Lgl relies on both PIP2 and PI4P, although PIP2 appears to contribute more to the PM targeting of Lgl (Dong et al., 2015). Note that in Figure 1B Lgl::RFP recovery appears lower than in wild type, possibly due to the titration of PIP2 by PLC-PH::GFP expression.

Overall, our quantitatively live imaging data showed for the first time at high subcellular and temporal resolutions that hypoxia triggered a dramatic turnover of PM PI4P and PIP2 in vivo, which directly impacts the electrostatic PM targeting under hypoxia and reoxygenation.

PI4KIIIα regulates the dynamic turnover of PM PI4P and PIP2 under hypoxia

The seven species of PPIns including PI4P and PIP2 are synthesized and interconverted by several dozens of PPIn kinases and phosphatases, many of which are conserved in Drosophila (Balakrishnan et al., 2015). We carried out a targeted RNAi screen to identify which PPIn kinases and phosphatases may be required for regulating the hypoxia-triggered dynamic turnover of PM PI4P and PIP2, using PM Lgl::GFP as a quick readout (Supplementary file 1). By imaging mosaic follicle epithelia containing both wild type and marked RNAi-expressing cells (Figure 2A), we eliminated the variability of each individual hypoxia imaging assay, making it possible to consistently and quantitatively detect even subtle phenotypes in RNAi cells. Among the candidates we identified is PtdIns-4 kinases IIIα (PI4KIIIα), one of the PI4K enzymes that phosphorylate PI to PI4P. Among them, PI4KIIIα is primarily responsible for the biosynthesis of PI4P in the PM (Nakatsu et al., 2012; Tan et al., 2014; Yan et al., 2011), while PI4KIIα and PI4KIIIβ (encoded by four-wheel drive or fwd in Drosophila [Brill et al., 2000]) are responsible for the synthesis of PI4P in endosomes and Golgi (Baba et al., 2019; Burgess et al., 2012; Ketel et al., 2016; Tóth et al., 2006).

Figure 2 with 2 supplements see all
PI4KIIIα regulates PM PI4P and PIP2 homeostasis and dynamic turnover under hypoxia/reoxygenation.

(A) Representative frames showing follicle cells expressing P4M::GFP and PLC-PH::GFP undergoing hypoxia and reoxygenation. PI4KIIIα-RNAi cells are labeled by RFP. (A’) PM localization of P4M::GFP (n=24, 23, Figure 2—source data 1) and PLC-PH::GFP (n=24, 24, Figure 2—source data 2) quantified in boundaries between wild type (WT) cells and between PI4KIIIα-RNAi (RNAi) cell. (B) Kymographs showing the persistent P4M::GFP puncta in both wild type and RNAi cells after hypoxia. White arrowheads point to puncta in RNAi cells at onset of hypoxia. Kymograph made by the maximum projection of 250 pixel wide line reslice of the time-lapse movie. (C) Kymograph showing the transient PLC-PH::GFP puncta (white arrowhead) in RNAi cells only. Kymograph made by the maximum projection of 300pixel wide line reslice of the time-lapse movie. Time stamp in hr:min:sec format. Scale bars: 5 µm.

Figure 2—source data 1

PI4KIIIα regulates PM PI4P homeostasis and dynamic turnover under hypoxia/reoxygenation.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig2-data1-v2.xlsx
Figure 2—source data 2

PI4KIIIα regulates PM PIP2 homeostasis and dynamic turnover under hypoxia/reoxygenation.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig2-data2-v2.xlsx

Under normal (i.e. normoxia) conditions, PI4KIIIα-RNAi cells showed a moderate reduction of PM PI4P and increased intracellular PI4P puncta (Figure 2A). Under hypoxia, in both RNAi and wild-type cells PI4P intracellular puncta disappeared prior to the loss PM PI4P which showed similar depletion rates in two cell types (Figure 2A, Figure 2—video 1). Under reoxygenation, compared to wild-type cells, the recovery of PM PI4P in RNAi cells was significantly delayed while intracellular puncta showed much faster recovery (Figure 2A and B).

In contrast to P4M × 2::GFP, levels of PM PLC-PH::GFP in PI4KIIIα-RNAi cells were similar to the wild-type cells, suggesting a robust PM PIP2 homeostasis mechanism that compensates well the modest reduction of PI4P under normal conditions (consistent with [Hammond and Burke, 2020; Sohn et al., 2018]). However, once challenged by hypoxia, PI4KIIIα-RNAi cells showed much accelerated loss of PM PLC-PH::GFP (Figure 2A, C, Figure 2—video 2). Strikingly, under reoxygenation PLC-PH::GFP in PI4KIIIα-RNAi cells first formed transient but prominent intracellular puncta which were not seen in wild-type cells, and these puncta rapidly disappeared at the onset of PM PIP2 recovery which was strongly delayed compared to wild-type cells (Figure 2A and C, Figure 2—video 2).

In summary, our data support that PI4KIIIα is required for the efficient replenishment of PM PI4P and PIP2 after their hypoxia-triggered depletion. During reoxygenation, PI4KIIIα knock-down cells showed delayed PM PI4P recovery but enhanced replenishment of intracellular PI4P pool, although the latter could be due to increased amount of free P4M × 2::GFP sensors when PM P4P recovery was delayed. In addition, knocking down PI4KIIIα accelerates the depletion of PM PIP2 but not PI4P under hypoxia, suggesting an increased conversion of PIP2 to PI4P during depletion.

PI4KIIα and FWD contribute to both PM and intracellular PI4P and PIP2 hemostasis and dynamic turnover

We then investigated how other two PI4K enzymes, PI4KIIα and FWD, contribute to the dynamic turnover of PI4P of PM and intracellular pools. Since neither PI4KIIα nor fwd null mutants are lethal (Brill et al., 2000; Burgess et al., 2012; Polevoy et al., 2009) and single RNAi knock-down against each showed no obvious phenotypes, we used newly published multi-RNAi tools Qiao et al., 2018 to generate fly stocks simultaneously expressing multiple dsRNAs targeting either both PI4KIIα and fwd (‘PI4K-2KD’), or all three PI4Ks (‘PI4K-3KD’). While PI4K-2KD cells showed no discernable phenotypes under either normoxia or hypoxia in our hypoxia assays (Figure 3—figure supplement 1), PI4K-3KD cells showed severely reduced PM P4M × 2::GFP and dramatically increased intracellular P4M × 2::GFP puncta (Figure 3A, B); the latter could be due to more P4M × 2::GFP sensors being bound to the intracellular PI4P pool when PM PI4P is low (Sohn et al., 2018; Wills et al., 2018).

Figure 3 with 3 supplements see all
PM PI4P and PIP2 show accelerated loss under hypoxia and delayed recovery under reoxygenation in PI4K-3KD RNAi cells.

(A) Representative frames showing follicle cells expressing P4M × 2::GFP or PLC-PH::GFP undergoing hypoxia and reoxygenation. PI4K-3KD cells are labeled by RFP. (A’) PM localization of P4M × 2::GFP (n=10, 5, Figure 3—source data 1) and PLC-PH::GFP (n=14, 15, Figure 3—source data 2) quantified in boundaries between wild type (WT) cells and between PI4K-3KD (RNAi) cell during hypoxia and regoxygenation. (B) Strong reduction of PM P4M × 2::GFP (n=20, 17, Figure 3—source data 3) but not PLC-PH::GFP (n=20, 20, Figure 3—source data 4) in PI4K-3KD follicle cells. Time stamp in hr:min:sec format. Scale bars: 5µm.

Figure 3—source data 1

PI4P showed accelerated loss under hypoxia and delayed recovery under reoxygenation in PI4K-3KD RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig3-data1-v2.xlsx
Figure 3—source data 2

PIP2 showed accelerated loss under hypoxia and delayed recovery under reoxygenation in PI4K-3KD RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig3-data2-v2.xlsx
Figure 3—source data 3

Reduction of PM PI4P in PI4K-3KD RNAi cells.

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Figure 3—source data 4

PM PI4P unchanged in PI4K-3KD RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig3-data4-v2.xlsx
Figure 3—source data 5

Dynamic turnover of PM PI4P under hypoxia and reoxygenation in PI4K-2KD cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig3-data5-v2.xlsx
Figure 3—source data 6

Dynamic turnover of PM PIP2 under hypoxia and reoxygenation in PI4K-2KD cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig3-data6-v2.xlsx
Figure 3—source data 7

Dynamic turnover of PM Lgl under hypoxia and reoxygenation in PI4K-2KD cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig3-data7-v2.xlsx

Similar to PI4KIIIα-RNAi cells, PI4K-3KD cells under hypoxia first showed reduction of intracellular P4M × 2::GFP puncta and transient increase of PM P4M × 2::GFP, followed by accelerated depletion of PM P4M × 2::GFP (Figure 3A, Figure 3—video 1). Under reoxygenation, PI4K-3KD cells only showed recovery of P4M × 2::GFP in intracellular puncta but not in PM, suggesting that PI4K-3KD cells are severely deficient in acute resynthesis of PM PI4P after its hypoxia-induced depletion.

Remarkably, PM PLC-PH::GFP levels showed no reduction in PI4K-3KD cells under normal conditions, despite of the severe loss of PM PI4P (Figure 3A, B, Figure 3—video 2). Similar to PI4KIIIα-RNAi cells, in PI4K-3KD cells PM PLC-PH::GFP showed accelerated loss under hypoxia (Figure 3A), and formed transient intracellular puncta during reoxygenation. Despite the apparent absence of PM PI4P recovery in PI4K-3KD cells, PM PLC-PH::GFP still recovered under reoxygenation, although the recovery was much delayed (Figure 3A, Figure 3—video 2).

Our data support that PI4KIIα and/or FWD contribute significantly to the maintenance of PM PI4P under normoxic conditions and to the replenishment of PM PI4P after hypoxia-triggered depletion. The data also suggest that an apparently PM PI4P-independent mechanism maintains the homeostatic level of PM PIP2 under normal conditions and sustains its recovery after hypoxia-triggered depletion. However, rapid replenishment of PM PI4P is clearly required for the efficient recovery of PM PIP2 after hypoxia-triggered depletion.

PI4Ks regulate the electrostatic PM targeting and retargeting of Lgl::GFP

To investigate how electrostatic PM targeting is affected by the disruptions of PM PI4P and PIP2 turnover, we imaged the PM targeting of Lgl::GFP in PI4KIIIα-RNAi and PI4K-3KD cells undergoing hypoxia. In PI4KIIIα-RNAi cells, we found that Lgl::GFP essentially phenocopied the behavior of PLC-PH::GFP. As shown in Figure 4A, under normoxic conditions PM Lgl::GFP levels in PI4KIIIα-RNAi were similar to wild-type cells, but Lgl::GFP showed accelerated loss from PM under hypoxia and severely delayed recovery to PM during reoxygenation. In addition. Lgl::GFP also formed transient intracellular puncta prior to the onset of its PM recovery (Figure 4A, Figure 4—video 1). Such data are consistent with previous studies that electrostatic PM targeting of Lgl::GFP is more PIP2-dependent (Dong et al., 2015).

Figure 4 with 2 supplements see all
PI4Ks regulate the PM localization of Lgl::GFP under hypoxia and reoxygenation.

(A) Representative frames showing Lgl::GFP PM localization during hypoxia and reoxygenation. RNAi cells are labeled by RFP. Yellow arrowheads: transient Lgl::GFP puncta (only few highlighted). *: RNAi cells that failed to recover Lgl::GFP to PM. (A’) (TOP) PM localization of Lgl::GFP quantified in boundaries between wild type (WT) cells (n=23), between PI4KIIIα-RNAi (RNAi) cells (n=24) and between WT and RNAi (WT-RNAi) cells (n=24). (Figure 4—source data 1). (BOTTOM). PM localization of Lgl::GFP quantified in boundaries between wild-type (WT) cells (n=20), between PI4K-3KD (RNAi) cells (n=10) and between cells failed recovery (RNAi*) (n=10). (Figure 4—source data 2). (B) Kymograph highlights the transient Lgl::GFP puncta (arrowheads). Each kymograph was made by reslicing the movie with the maximum projection of a 150 or 250-pixel wide line (yellow bands in A). Time stamp in hr:min:sec format. Scale bars: 5 µm.

Figure 4—source data 1

Dynamic turnover of PM Lgl under hypoxia and reoxygenation in PI4K-IIIα-RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig4-data1-v2.xlsx
Figure 4—source data 2

Dynamic turnover of PM Lgl under hypoxia and reoxygenation in PI4K-3KD cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig4-data2-v2.xlsx

In PI4K-3KD cells, PM Lgl::GFP also showed accelerated loss under hypoxia and delayed recovery under reoxygenation (Figure 4A, Figure 4—video 2). Unlike PLC-PH::GFP, Lgl::GFP only formed few very transient puncta prior to the onset of PM recovery under reoxygenation (Figure 4A). However, in half (113/219) of PI4K-3KD cells PM Lgl::GFP was already partially diffused under normal conditions (asterisked in Figure 4A), and in these cells Lgl::GFP also failed to recover to PM during reoxygenation. Even in PI4K-3KD cells with normal PM Lgl::GFP, a third (36/106) failed to recover during reoxygenation. Such data suggest that the electrostatic PM targeting becomes much less resilient in PI4K-3KD cells, especially when cells are challenged by energetic stresses such as hypoxia.

PM localization of PI4KIIIα is required for the dynamic turnover of PM PI4P and PIP2

Unlike PI4KIIα and FWD, which localize to intracellular membranes, PI4KIIIα is primarily PM localized (Baskin et al., 2016; Nakatsu et al., 2012). We thus investigated how subcellular localization to PI4KIIIα affects the hypoxia-induced dynamic turnover of PM PI4P. The PM localization of yeast PI4KIIIα (‘Stt4p’) requires EFR3, YPP1and Sfk1 (mammalian TTC7 and TMEM150A, respectively) (Chung et al., 2015; Hammond et al., 2014; Nakatsu et al., 2012). All three proteins are conserved in Drosophila, including EFR3 homologue Rbo (‘Rolling blackout’) (Huang et al., 2004; Vijayakrishnan et al., 2009), dYPP1/dTTC7 (CG8325) and dTMEM150A (“dTMEM”, CG7990 and CG4025), (Liu et al., 2018). Consistent with that EFR3 is a peripheral membrane protein and that its PM targeting appears to be independent of PI4P/PIP2 (Nakatsu et al., 2012), in follicle epithelial cells Rbo::GFP (Huang et al., 2004; Vijayakrishnan et al., 2009) showed exclusive PM localization that was highly resistant to hypoxia (Figure 5—figure supplement 1, Figure 5—video 1). rbo-RNAi cells essentially phenocopied PI4KIIIα-RNAi cells in terms of the dynamic turnover of PM PI4P, PIP2 and Lgl::GFP under hypoxia, with one exception that under reoxygenation Lgl::GFP did not form transient puncta prior to PM recovery, even though PLC-PH::GFP still formed transient and prominent puncta in rbo-RNAi cells prior to the onset of the recovery of PM PLC-PH::GFP (Figure 5A, C and D, Figure 5—videos 2–4). The reason for such difference between Lgl::GFP and PLC-PH::GFP in rbo-RNAi cells is unclear.

Figure 5 with 5 supplements see all
Rbo regulates the homeostasis and dynamic turnover of PI4P, PIP2 and Lgl under hypoxia/reoxygenation.

(A) Representative frames follicle cells expressing P4M × 2::GFP or PLC-PH::GFP or Lgl::GFP undergoing hypoxia and reoxygenation. rbo-RNAi cells are labeled by RFP. Time stamp in min:sec format. (A’) PM localization of P4M::GFP (n=10, 10, Figure 5—source data 1), PLC-PH::GFP (n=20, 20, Figure 5—source data 2) and Lgl::GFP (n=20, 20, Figure 5—source data 3) in A quantified in wild type (WT) and rbo-RNAi (RNAi) cells. (B) Kymograph highlights the earlier onset of P4M::GFP puncta in post-hypoxia RNAi cells. White arrowheads point to the onset of puncta in post-hypoxia RNAi and WT cells. (C) Kymograph highlights the transient PLC-PH::GFP puncta (white arrowheads) seen only in post-hypoxia RNAi cells. (D) Kymograph showing the absence of Lgl::GFP puncta in post-hypoxia RNAi cells. Scale bars: 5µm.

Figure 5—source data 1

Dynamic turnover of PM PI4P under hypoxia and reoxygenation in rbo-RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig5-data1-v2.xlsx
Figure 5—source data 2

Dynamic turnover of PM PIP2 under hypoxia and reoxygenation in rbo-RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig5-data2-v2.xlsx
Figure 5—source data 3

Dynamic turnover of PM Lgl under hypoxia and reoxygenation in rbo-RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig5-data3-v2.xlsx
Figure 5—source data 4

PM localization of Rbo is resistant to hypoxia.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig5-data4-v2.xlsx

YPP1/TTC7 helps to link PI4KIIIα to Rbo/EFR3 and enhances the PM targeting of PI4KIIIα in cultured cells (Nakatsu et al., 2012). Consistently, ttc7-RNAi cells showed similar albeit milder phenotypes in hypoxia-triggered turnover of PM PI4P and PIP2 as well as the PM targeting and retargeting of Lgl (Figure 6A, Figure 6—videos 1–3). Interestingly, ttc7-RNAi cells also showed reduced PM Rbo::GFP (Figure 6B), suggesting that TTC7 enhances the PM targeting of Rbo and that phenotypes in ttc7-RNAi cells could be partially due to the reduction of PM Rbo. Although at present we do not have the tools to directly examine the PI4KIIIα localization in rbo- or ttc7-RNAi cells, our data strongly support a scenario where PM localization of PI4KIIIα is essential for the efficient recovery of PM PI4P and PIP2 after hypoxia-triggered depletion.

Figure 6 with 3 supplements see all
YPP1/TTC7 regulates the homeostasis and dynamic turnover of PI4P, PIP2 and Lgl in cells undergoing hypoxia and reoxygenation.

(A) Representative frames follicle cells expressing P4M × 2::GFP or PLC-PH::GFP or Lgl::GFP undergoing hypoxia and reoxygenation. ttc7-RNAi cells are labeled by RFP. Time stamp in min:sec format. (A’) PM localization changes of P4M × 2::GFP (n=10, 10, Figure 6—source data 1), PLC-PH::GFP (n=20, 20, Figure 6—source data 2) and Lgl::GFP (n=20, 20, Figure 6—source data 3) in A quantified in wild type (WT) and ttc7-RNAi (RNAi) cells.(B and C) Reduction of PM RBO::GFP in ttc7-1-RNAi cells (n=24, 24, Figure 6—source data 4). Scale bars: 5µm.

Figure 6—source data 1

Dynamic turnover of PM PI4P under hypoxia and reoxygenation in ttc7-RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig6-data1-v2.xlsx
Figure 6—source data 2

Dynamic turnover of PM PIP2 under hypoxia and reoxygenation in ttc7-RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig6-data2-v2.xlsx
Figure 6—source data 3

Dynamic turnover of PM Lgl under hypoxia and reoxygenation in ttc7-RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig6-data3-v2.xlsx
Figure 6—source data 4

Reduction of Rbo::GFP in ttc7-RNAi cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig6-data4-v2.xlsx

Acute ATP inhibition induces dynamic turnover of PM PI4P and PIP2 in HEK293 cells

How does hypoxia trigger the acute depletion of PM PI4P and PIP2? We showed previously that direct ATP inhibition by antimycin (AM) in follicle cells also induced loss of PM Lgl::GFP in follicle and embryonic epithelial cells (Dong et al., 2015), suggesting that the acute depletion of PM PI4P and PIP2 could be triggered by hypoxia-induced ATP inhibition. We first tested this hypothesis using a genetically encoded ATP sensor AT[NL], which is a FRET-based ratiometric ATP sensor that recently became available and validated in Drosophila (Imamura et al., 2009; Kioka et al., 2014; Tsuyama et al., 2017). As shown in Figure 7—figure supplement 1A, live imaging of follicle cells expressing AT[NL] confirmed an acute and reversible reduction of intracellular ATP levels under hypoxia and reoxygenation. Because AT[NL] is not suitable for imaging together with our current PI4P and PIP2 sensors, we also tested an intensimetric ATP sensor MaLionR (Arai et al., 2018) in HEK293 cells. Under hypoxia, HEK293 cells showed acute and reversible reduction of ATP levels as measured by MaLionR intensity changes (Figure 7—figure supplement 1B, Figure 7—video 1), as well as reversible depletions of PM P4M × 2::GFP and PLC-PH::GFP which correlate with MaLionR intensity changes (Figure 7—figure supplement 1C).

We then subjected HEK293 cells to acute ATP inhibition by the treatment of 2-deoxyglucose (2-DG) and AM, followed by washout to allow ATP recovery. Upon adding 2-DG and AM, MaLionR brightness dropped rapidly within 10–20 min and plateaued afterward (Figure 7A, B, Figure 7—videos 2; 3). In general, P4M × 2::GFP or PLC-PH::GFP began gradually lost from PM at the onset of the ATP drop and became completely cytosolic within ~40–60 min of ATP inhibition (Figure 7A, B). While the reduction of ATP as measured by MaLionR brightness was rather uniform across cells, ATP recovery after the washout of 2-DG and AM was slightly asynchronous across the cells. In general, the recovery of PM PI4P always preceded the detectable increase of MaLionR brightness (Figure 7A, Figure 7—video 2), while PM PIP2 recovery was concurrent with MaLionR brightness increase (Figure 7B, Figure 7—video 3). In some cells PM PI4P recovery appeared up to ten minutes ahead of MaLionR increase (Figure 7A). Given that MaLionR appears to have a dynamic range between ~50 µM and 2 mM of ATP (Arai et al., 2018), such data support that initial replenishment of PM PI4P could start under very low intracellular ATP levels.

Figure 7 with 6 supplements see all
ATP inhibition induces acute and reversible loss of P4M × 2::GFP and PLC-PH::RFP from the PM in HEK293 cells.

(A, B) Representative cells showing the PM localization of P4M × 2::GFP (A) or PLC-PH::GFP (B) and MaLionR ATP sensor during ATP inhibition and subsequent washout with low-glucose medium.(A) Top cell: P4M × 2::GFP recovery on PM was immediately followed by ATP sensor brightness increase (n=9). Bottom cell: measurable ATP increase lagged well behind the PM recovery of P4M × 2::GFP (n=6). Intracellular P4M × 2::GFP puncta were overexposed but excluded from quantification. (A’) Normalized quantification of PM localization of P4M × 2::GFP and MaLionR intensity (n=15, 19 cells, respectively). Figure 7—source data 1. (B) Top cell: synchronous PLC-PH::GFP recovery and ATP senor brightness increase (n=13). Bottom cell: PLC-PH::GFP PM recovery slightly preceded the detectable ATP increase (n=12). (B’) Normalized quantification of PM localization of PLC-PH::GFP (green) and MaLionR intensity (red) in ATP inhibition cells (solid dots, n=13) or serum-free medium treated cells (blank diamonds, n=12 cells) Figure 7—source data 2. (C) A representative cell showing the PM localization of P4M × 2::GFP and PLC-PH::RFP during ATP inhibition and subsequent washout. (C’) Quantification of PM P4M × 2::GFP and PLC-PH::GFP (n=13 cells) (Figure 7—source data 3). (D) Normalized PM localization index of P4M × 2::GFP, PLC-PH::RFP and cyto index of MaLionR sensor in cells treated with ATP inhibition followed by washout with buffer containing DMSO or Wortmannin (WM, 20 µm). (n=48, all samples). Figure 7—source data 4; 5. Scale bars: 10 µm.

Figure 7—source data 1

Correlation between ATP inhibition PM PI4P turnovery in HEK293 cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig7-data1-v2.xlsx
Figure 7—source data 2

Correlation between ATP inhibition PM PIP2 turnovery in HEK293 cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig7-data2-v2.xlsx
Figure 7—source data 3

ATP inhibition induces acute and reversible loss of PM PI4P and PIP2 in HEK293 cells.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig7-data3-v2.xlsx
Figure 7—source data 4

Wortmannin inhibits PM PI4P recovery post ATP inhibition.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig7-data4-v2.xlsx
Figure 7—source data 5

Post-inhibition recovery of ATP was not delayed by wortmannin treatment.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig7-data5-v2.xlsx
Figure 7—source data 6

Acute and reversible reduction of intracellular ATP in Drosophila follicle cells undery hypoxia.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig7-data6-v2.xlsx
Figure 7—source data 7

Acute and reversible reduction of intracellular ATP in HEK203 cells undery hypoxia.

https://cdn.elifesciences.org/articles/79582/elife-79582-fig7-data7-v2.xlsx

Similar to the results from hypoxia assays in Drosophila follicle cells (Figure 1A), in HEK293 cells under ATP inhibition the depletion of PM P4M × 2::GFP consistently lagged behind the loss of PM PLC-PH::GFP, while after drug washout PM P4M × 2::GFP recovery consistently preceded the recovery of PM PLC-PH::GFP (Figure 7C, Figure 7—video 4). We also investigated whether PI4KIIIα is required for the post-ATP inhibition recovery of PM PI4P in HEK293 cells. After ATP inhibition, we washed out drugs with medium containing 20 µM wortmannin (WM) which specifically inhibits PI4KIIIα/β isoforms but not PI4KIIα/β (Balla and Balla, 2006). Washout with WM caused no discernable delay in ATP recovery as measured by MaLionR brightness (Figure 7D), but strongly delayed PM recovery of PI4P, and to much less degree PIP2 (Figure 7D, Figure 7—figure supplement 2). Such results are consistent with the Drosophila RNAi results that PI4KIIIα is required for the efficient PM recovery of PI4P and PIP2 after hypoxia-triggered depletion.

In summary, ATP inhibition in human cultured cells also triggers acute and reversible depletion of PM PI4P and PIP2 similar to the dynamic turnover of PI4P and PIP2 in cells undergoing hypoxia. For reasons unknown, our efforts of making a transgenic MaLionR sensor in Drosophila was unsuccessful, limiting our ATP assays to HEK293 at present. However, our data strongly support that intracellular ATP levels directly dictate the homeostasis and turnover of PM PI4P and PIP2 in both Drosophila and human cultured cells.

Discussion

Dynamic turnover of PM PI4P and PIP2 trigged by hypoxia and ATP inhibition

We would speculate that the reduction of intracellular ATP levels, through either hypoxia or drug inhibition, triggers acute loss of PM PI4P and PIP2 by two possible mechanisms. PI4P and PIP2 could be maintained at slow turnover rates on the PM, but reduction of ATP activates a specific cellular response to acutely deplete PM PI4P and PIP2. Alternatively, a more parsimonious mechanism would be that PM PI4P and PIP2 are constantly under fast turnover, which requires high activity of PI and PIP kinases. ATP reduction, which directly inhibits the activity of these kinases, pivots the equilibrium to the dephosphorylation process which converts the PIP2 to PI4P and PI4P to PI.

Consistent with the critical role of PI4P in maintaining PM identity and its biological activity, our data revealed that cells undergoing hypoxia/ATP inhibition consistently prioritize the maintenance and recovery of PM PI4P over the intracellular PI4P pool in a PI4KIIIα-dependent manner. However, while PI4KIIIα is well characterized for its essential role in generating the PI4P on the PM (Balla, 2013; Nakatsu et al., 2012), KmATP values of PI4KIIIα (500–700 µM) and PI4KIIβ(Fwd) (~400 µM) are about one or two orders higher than that of PI4KIIα (10–50 µM) (Balla and Balla, 2006; Carpenter and Cantley, 1990). Such KmATP differences would suggest that, in contrast to our results, the intracellular PI4P pool should deplete more slowly and recover more quickly than the PM PI4P in cells undergoing hypoxia/ATP inhibition, as PI4KIIIα would be the first PI4K to lose activity under hypoxia and the last to become active under reoxygenation.

One possible reason behind such a discrepancy could be that KmATP of PI4KIIIα was measured decades ago using purified PI4KIIIα enzymes from tissues such as bovine brains and uterus (Carpenter and Cantley, 1990). Recent data showed that PI4KIIIα forms a highly ordered multi-protein membrane targeting complex essential for its activity (Lees et al., 2017). It is thus possible that PI4KIIIα in the complex may have much lower KmATP in vivo, and/or has dramatically increased enzymatic activity to produce sufficient PI4P at the PM even when ATP levels are much lower than the measured Km. Alternatively, the KmATP of PI4KIIIα is indeed high and our live imaging results actually highlight a prioritized transfer of PI4P from the intracellular pool to maintain or replenish the PM PI4P levels. Phosphatidylinositol (PI) is abundant on intracellular membranes, but not the PM (Pemberton et al., 2020; Zewe et al., 2020). Therefore, during the early phase of reoxygenation when intracellular ATP levels are low, PI4P is first synthesized at the intracellular pool by PI4KIIα but is immediately transferred to the PM. Only after the full replenishment of PM PI4P is the intracellular PI4P pool filled. Supporting this transfer PI4P from intracellular pools to PM pools (Dickson et al., 2014), our data show loss of PM PI4P recovery in PI4K-3KD cells, in which the maintenance of intracellular pool of PI4P is supposedly impaired.

Out data are consistent with the view that in wild type cells under hypoxia/ATP inhibition, PM PIP2 depletes and recovers through direct inter-conversion with PI4P on the PM. Interestingly, in both PI4KIIIα-RNAi and PI4K-3KD cells, PM recovery of PIP2 is preceded with transient intracellular PIP2-positive puncta which were not seen in recovering wild-type cells. It is possible that in the absence or delay of PM PI4P recovery, enzymes such as PIP5K are instead electrostatically recruited to the intracellular PI4P-positive puncta (Dong et al., 2016; Fairn et al., 2009) to convert PI4P to PIP2. It is unclear, however, in PI4K knock down cells whether the delayed PM PIP2 recovery originates from the PIP2 generated in these puncta. Additional sensors are necessary to confirm the co-localization of PI4P and PIP2 on these transient puncta. Notably, MEF cells from PI4KIIIα knock-out mice also showed increased PIP2-positive intracellular vesicles (Dong et al., 2016; Nakatsu et al., 2012).

The existence of intracellular P4M × 2::GFP puncta in PI4K-3KD cells suggest that the knock down of PI4KIIα and fwd is unlikely complete, but the severe reduction of PM PI4P confirms the knock down is strong enough to greatly enhance the defects in PI4KIIIα-RNAi cells. Such partial knock-down by PI4K-3KD is actually necessary for our imaging assays, as completely blocking PI4P synthesis is cell lethal. It is striking that PM PIP2 is well maintained in the near absence of PM PI4P in PI4K-3KD cells. Synthetic biology-based evidence suggested that PIP5K can be sufficient to make PIP2 from PI in E. coli by phosphorylating both its fourth and fifth positions in the absence of PI4Ks (Botero et al., 2019), and it is possible that similar pathway maintains the steady state PM PIP2 levels in PI4K-3KD cells. Nonetheless, our imaging experiments showed that PI4K activity is essential for cells to maintain PM PIP2 levels when cells are subject to hypoxia. In this regard, our study of PI4K-compromised cells repeatedly revealed deficiencies in PI4P/PIP2 turnover and electrostatic PM targeting that can only be observed when cells are subject to energetic stress conditions.

PM targeting of PI4KIIIα is crucial for maintaining and replenishing the PM PI4P

PM targeting of PI4KIIIα strictly depends on its formation of an obligate superassembly with TTC7 (YPP1), FAM126 (Hycin) and EFR3 (Rbo) (Lees et al., 2017; Wu et al., 2014). A recent study also showed that RNAi knock-downs of PI4KIIIα, TTC7 and Rbo yielded similar phenotypes in Drosophila wing discs, such as moderately reduced PM PI4P but no obvious changes of PM PIP2 (Basu et al., 2020). Same RNAi knock-downs in Drosophila photoreceptors also showed similar phenotypes such as reduced PI4P levels and impaired light response, although PIP2 levels also appear to be reduced (Balakrishnan et al., 2018). Moreover, our data showed that knocking down TTC7 also reduced PM localization of Rbo, supporting that components in PI4KIIIα complex may act interdependently for proper PM targeting in vivo.

The hypoxia-resistant PM localization of Rbo/dEFR3 suggests that under hypoxia/ATP inhibition PI4KIIIα maintains its PM localization, which should be essential for its role in recovering the PM PI4P. The core complex of PI4KIIIα/TTC7/FAM126 forms a collective basic surface that electrostatically binds to the acidic inner leaflet of the PM which could be sensitive to the loss of PM PI4P and PIP2. However, TTC7 also interacts with the C-terminus of EFR3 (Chung et al., 2015; Lees et al., 2017). PM targeting of yeast EFR3 requires a basic patch that interacts with general acidic phospholipids but is not disrupted by the loss of PM PI4P and PIP2 (Wu et al., 2014). Mammalian EFR3 contains an additional N-terminal Cys-rich palmitoylation site that is also required for the PM targeting (Nakatsu et al., 2012). Such dual and PI4P/PIP2-independent mechanisms are supported by the hypoxia-resistant PM localization of Rbo as we observed. Future studies will be needed to directly investigate the PM targeting of PI4KIIIα, TTC7 and FAM126 in vivo under hypoxia/ATP inhibition.

Hypoxia/ATP inhibition-trigged PM PI4P and PIP2 turnover impacts the electrostatic targeting of polybasic proteins

While previous studies showed that genetically reducing PM PIP2 levels disrupts the PM localization of several polarity proteins including Lgl, it is difficult to conclude whether such loss of PM targeting is the direct consequence PIP2 reduction (Claret et al., 2014; Gervais et al., 2008). In this study, we are able to quantitatively and qualitatively demonstrate that in cells undergoing hypoxia-reoxygenation the acute and reversible loss of PM targeting of Lgl directly correlates with the turnover of PM PI4P and PIP2. Consistent with the idea that Lgl appears to depend more on PIP2 for its PM targeting, Lgl closely follows the dynamic turnover and relocation of PIP2 during hypoxia and reoxygenation. In particular, ectopic and transient puncta of Lgl::GFP seen in PI4KIIIα-RNAi or PI4K-3KD cells under reoxygenation appear to be strikingly similar to PIP2-positive puncta in these cells, although due to the limited array of biosensors we have not been able to directly confirm the co-localization of Lgl::GFP and PIP2 in these transient puncta. Additional genetically encoded biosensors for PI4P and PIP2 (e.g. P4M × 2::iRFP and PLC-PH::iRFP) are in development for such experiments.

It is notable that in rbo-RNAi cells, Lgl::GFP formed very few transient puncta prior to PM recovery during reoxygenation, even though PLC-PH::GFP showed plenty of prominent puncta. The reason for such difference between Lgl::GFP and PLC-PH::GFP in rbo-RNAi cells is unclear, though likely derives from the requirement of polybasic motif proteins for additional anionic lipids at the plasma membrane, specifically high molar fractions of phosphatidylserine in addition to lower concentrations of polyanionic phosphoinositides (Yeung et al., 2008).

In summary, our study revealed an acute and reversible loss of PI4P and PIP2 from PM under hypoxia/ATP inhibition in both Drosophila and human cultured cells. Such dynamic turnover of PM PI4P and PIP2 explains the dramatic loss of the PM targeting of polybasic polarity proteins such as Lgl under hypoxia. How cells meticulously maintain steady state PM PI4P and PIP2 levels under normal physiological conditions has been extensively studied; our studies highlight the importance of understanding mechanisms controlling this homeostasis and dynamics of phosphoinositides under energetic stresses triggered by hypoxia, ATP inhibition and ischemia, and the critical role of the interplay between polarity proteins and PM phosphoinositides in controlling cell polarity under normal and disease conditions.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Genetic reagent (D. melanogaster)ubi-P4M::GFPThis paperSee “Materials and methods”
Genetic reagent (D. melanogaster)ubi-P4M × 2::GFPThis paperSee “Materials and methods”
Genetic reagent (D. melanogaster)ubi-PLC-PH::GFPThis paperSee “Materials and methods”
Genetic reagent (D. melanogaster)ubi-PLC-PH::RFPThis paperSee “Materials and methods”
Genetic reagent(D. melanogaster)y[1] M{RFP[3xP3.PB] GFP[E.3xP3]=vas int.Dm}ZH-2A w[*]; PBac{y[+]-attP-9A}VK00022Bloomington Drosophila Stock CenterBDSC:24868; RRID:BDSC_24868
Genetic reagent (D. melanogaster)y[1] w[*] P{y[+t7.7]=nos-phiC31\int.NLS}X; PBac{y[+]-attP-3B}VK00040Bloomington Drosophila Stock CenterBDSC:35568; RRID:BDSC_35568
Genetic reagent (D. melanogaster)PI4K-2KDThis paperSee “Materials and methods”
Genetic reagent (D. melanogaster)PI4K-3KDThis paperSee “Materials and methods”
Genetic reagent (D. melanogaster)UAS-AT1.03NL1DGRC#117,011 Tsuyama et al., 2017DGRC#117,011
Genetic reagent (D. melanogaster)Cy2-Gal4Gift from David Bilder Queenan et al., 1997
Genetic reagent (D. melanogaster)rbo::GFPGift from Kendal Broadie Huang et al., 2004
Genetic reagent (D. melanogaster)lgl::mCherryDong et al., 2015
Genetic reagent (D. melanogaster)lgl::GFPDong et al., 2015
Genetic reagent (D. melanogaster)UAS-PI4KIIIα-RNAiBloomington Drosophila Stock CenterBDSC:35256; FLYB:FBst0035256; RRID:BDSC_35256FlyBase symbol: P{TRiP.GL00144}attP2
Genetic reagent (D. melanogaster)UAS-Rbo-RNAiVienna Drosophila Resource CenterVDRC:v47751; FLYB:Bst0467525FlyBase symbol: P{GD14013}v47751
Genetic reagent (D. melanogaster)UAS-ttc7-RNAiVienna Drosophila Resource CenterVDRC:v35881; FLYB: FBst0461391FlyBase symbol: P{GD13893}v35881
Genetic reagent (D. melanogaster)UAS-Plc21C-RNAiBloomington Drosophila Stock CenterBDSC:33719; FBst0033719 RRID:BDSC_33719
Genetic reagent (D. melanogaster)UAS-pis-RNAiBloomington Drosophila Stock CenterBDSC:55602; FBst0055602; RRID:BDSC_55602
Genetic reagent (D. melanogaster)UAS-PI4KIIIα-RNAiBloomington Drosophila Stock CenterBDSC:38242; FBst0038242; RRID:BDSC_38242
Genetic reagent (D. melanogaster)UAS-synj-RNAiBloomington Drosophila Stock CenterBDSC:44420; FBst0044420; RRID:BDSC_44420
Genetic reagent (D. melanogaster)UAS-rdgβ-RNAiBloomington Drosophila Stock CenterBDSC:44523; FBst0044523; RRID:BDSC_44523
Genetic reagent (D. melanogaster)UAS-INPP5E-RNAiBloomington Drosophila Stock CenterBDSC:41701; FBst0041701; RRID:BDSC_41701
Genetic reagent (D. melanogaster)UAS-CG5026-RNAiBloomington Drosophila Stock CenterBDSC:42759; FBst0042759; RRID:BDSC_42759
Genetic reagent (D. melanogaster)UAS-Pten-RNAiBloomington Drosophila Stock CenterBDSC:33643; FBst0033643; RRID:BDSC_33643
Genetic reagent (D. melanogaster)UAS-Pi3k21B-RNAiBloomington Drosophila Stock CenterBDSC:36810; FBst0036810; RRID:BDSC_36810
Genetic reagent (D. melanogaster)UAS-fwd-RNAiBloomington Drosophila Stock CenterBDSC:35257; FBst0035257; RRID:BDSC_35257
Genetic reagent (D. melanogaster)UAS-mtm-RNAiBloomington Drosophila Stock CenterBDSC:31552; FBst0031552; RRID:BDSC_31552
Genetic reagent (D. melanogaster)UAS-PIP4K-RNAiBloomington Drosophila Stock CenterBDSC:35660; FBst0035660; RRID:BDSC_35660
Genetic reagent (D. melanogaster)UAS-PI4KIIIα-RNAiBloomington Drosophila Stock CenterBDSC:35643; FBst0035643; RRID:BDSC_35643
Genetic reagent (D. melanogaster)UAS-INPP5E-RNAiBloomington Drosophila Stock CenterBDSC:34037; FBst0034037; RRID:BDSC_34037
Genetic reagent (D. melanogaster)UAS-CG3632-RNAiBloomington Drosophila Stock CenterBDSC:38341; FBst0038341; RRID:BDSC_38341
Genetic reagent (D. melanogaster)UAS-mtm-RNAiBloomington Drosophila Stock CenterBDSC:38339; FBst0038339; RRID:BDSC_38339
Genetic reagent (D. melanogaster)UAS-PIP4K-RNAiBloomington Drosophila Stock CenterBDSC:35338; FBst0035338; RRID:BDSC_35338
Genetic reagent (D. melanogaster)UAS-INPP5E-RNAiBloomington Drosophila Stock CenterBDSC:34037; FBst0034037; RRID:BDSC_34037
Genetic reagent (D. melanogaster)UAS-CG3632-RNAiBloomington Drosophila Stock CenterBDSC:38341; FBst0038341; RRID:BDSC_38341
Genetic reagent (D. melanogaster)UAS-mtm-RNAiBloomington Drosophila Stock CenterBDSC:38339; FBst0038339; RRID:BDSC_38339
Genetic reagent (D. melanogaster)UAS-PIP4K-RNAiBloomington Drosophila Stock CenterBDSC:35338; FBst0035338; RRID:BDSC_35338
Genetic reagent (D. melanogaster)UAS-FIG4-RNAiBloomington Drosophila Stock CenterBDSC:38291; FBst0038291; RRID:BDSC_38291
Genetic reagent (D. melanogaster)UAS-CG5026-RNAiBloomington Drosophila Stock CenterBDSC:38309; FBst0038309; RRID:BDSC_38309
Genetic reagent (D. melanogaster)UAS-PI4KIIα-RNAiBloomington Drosophila Stock CenterBDSC:35278; FBst0035278; RRID:BDSC_35278
Genetic reagent (D. melanogaster)UAS-norpA-RNAiBloomington Drosophila Stock CenterBDSC:31113; FBst0031113; RRID:BDSC_31113
Genetic reagent (D. melanogaster)UAS-sktl-RNAiBloomington Drosophila Stock CenterBDSC:27715; FBst0027715; RRID:BDSC_27715
Genetic reagent (D. melanogaster)UAS-fwd-RNAiBloomington Drosophila Stock CenterBDSC:29396; FBst0029396; RRID:BDSC_29396
Genetic reagent (D. melanogaster)UAS-CG6707-RNAiBloomington Drosophila Stock CenterBDSC:28316; FBst0028316; RRID:BDSC_28316
Genetic reagent (D. melanogaster)UAS-synj-RNAiBloomington Drosophila Stock CenterBDSC:34378; FBst0034378; RRID:BDSC_34378
Genetic reagent (D. melanogaster)UAS-pis-RNAiBloomington Drosophila Stock CenterBDSC:29383; FBst0029383; RRID:BDSC_29383
Genetic reagent (D. melanogaster)UAS-sl-RNAiBloomington Drosophila Stock CenterBDSC:32385; FBst0032385; RRID:BDSC_32385
Genetic reagent (D. melanogaster)UAS-CG42271-RNAiBloomington Drosophila Stock CenterBDSC:29411; FBst0029411; RRID:BDSC_29411
Genetic reagent (D. melanogaster)UAS-Plc21C-RNAiBloomington Drosophila Stock CenterBDSC:31270; FBst0031270; RRID:BDSC_31270
Genetic reagent (D. melanogaster)UAS-Pi3K92E-RNAiBloomington Drosophila Stock CenterBDSC:35798; FBst0035798; RRID:BDSC_35798
Genetic reagent (D. melanogaster)UAS-Pi3K59F-RNAiBloomington Drosophila Stock CenterBDSC:33384; FBst0033384; RRID:BDSC_33384
Genetic reagent (D. melanogaster)UAS-sl-RNAiBloomington Drosophila Stock CenterBDSC:35604; FBst0035604; RRID:BDSC_35604
Genetic reagent (D. melanogaster)UAS-CG9784-RNAiBloomington Drosophila Stock CenterBDSC:34723; FBst0034723; RRID:BDSC_34723
Genetic reagent (D. melanogaster)UAS-Pi3K68D-RNAiBloomington Drosophila Stock CenterBDSC:34621; FBst0034621; RRID:BDSC_34621
Genetic reagent (D. melanogaster)UAS-Ocrl-RNAiBloomington Drosophila Stock CenterBDSC:34722; FBst0034722; RRID:BDSC_34722
Genetic reagent (D. melanogaster)UAS-sktl-RNAiBloomington Drosophila Stock CenterBDSC:35198; FBst0035198; RRID:BDSC_35198
Genetic reagent (D. melanogaster)UAS-Pten-RNAiBloomington Drosophila Stock CenterBDSC:25841; FBst0025841; RRID:BDSC_25841
Genetic reagent (D. melanogaster)UAS-CG33981,fab1-RNAiBloomington Drosophila Stock CenterBDSC:35793; FBst0035793; RRID:BDSC_35793
Genetic reagent (D. melanogaster)UAS-Plc21C-RNAiBloomington Drosophila Stock CenterBDSC:32438; FBst0032438; RRID:BDSC_32438
Genetic reagent (D. melanogaster)UAS-rdgB-RNAiBloomington Drosophila Stock CenterBDSC:28796; FBst0028796; RRID:BDSC_28796
Genetic reagent (D. melanogaster)UAS-CG3530-RNAiBloomington Drosophila Stock CenterBDSC:25864; FBst0025864; RRID:BDSC_25864
Genetic reagent (D. melanogaster)UAS-Synj-RNAiBloomington Drosophila Stock CenterBDSC:27489; FBst0027489; RRID:BDSC_27489
Genetic reagent (D. melanogaster)UAS-Pi3K68D-RNAiBloomington Drosophila Stock CenterBDSC:31252; FBst0031252; RRID:BDSC_31252
Genetic reagent (D. melanogaster)UAS-Pten-RNAiBloomington Drosophila Stock CenterBDSC:25967; FBst0025967; RRID:BDSC_25967
Genetic reagent (D. melanogaster)UAS-Pi3K92E-RNAiBloomington Drosophila Stock CenterBDSC:27690; FBst0027690; RRID:BDSC_27690
Genetic reagent (D. melanogaster)UAS-norpA-RNAiBloomington Drosophila Stock CenterBDSC:31197; FBst0031197; RRID:BDSC_31197
Genetic reagent (D. melanogaster)UAS-fwd-RNAiBloomington Drosophila Stock CenterBDSC:31187; FBst0031187; RRID:BDSC_31187
Genetic reagent (D. melanogaster)UAS-Plc21C-RNAiBloomington Drosophila Stock CenterBDSC:31269; FBst0031269; RRID:BDSC_31269
Genetic reagent (D. melanogaster)UAS-sl-RNAiBloomington Drosophila Stock CenterBDSC:32906; FBst0032906; RRID:BDSC_32906
Genetic reagent (D. melanogaster)UAS-CG3530-RNAiBloomington Drosophila Stock CenterBDSC:38340; FBst0038340; RRID:BDSC_38340
Genetic reagent (D. melanogaster)UAS-CG5026-RNAiBloomington Drosophila Stock CenterBDSC:57020; FBst0057020; RRID:BDSC_57020
Genetic reagent (D. melanogaster)UAS-PIP4K-RNAiBloomington Drosophila Stock CenterBDSC:65891; FBst0065891; RRID:BDSC_65891
Genetic reagent (D. melanogaster)UAS-Sac1-RNAiBloomington Drosophila Stock CenterBDSC:56013; FBst0056013; RRID:BDSC_56013
Genetic reagent (D. melanogaster)UAS-Pi3K59F-RNAiBloomington Drosophila Stock CenterBDSC:64011; FBst0064011; RRID:BDSC_64011
Genetic reagent (D. melanogaster)UAS-Pi3K68D-RNAiBloomington Drosophila Stock CenterBDSC:35265; FBst0035265; RRID:BDSC_35265
Genetic reagent (D. melanogaster)UAS-PIP5K59B-RNAiBloomington Drosophila Stock CenterBDSC:62855; FBst0062855; RRID:BDSC_62855
Genetic reagent (D. melanogaster)UAS-Pi3K93E-RNAiBloomington Drosophila Stock CenterBDSC:61182; FBst0061182; RRID:BDSC_61182
Genetic reagent (D. melanogaster)UAS-mtm-RNAiBloomington Drosophila Stock CenterBDSC:57298; FBst0057298; RRID:BDSC_57298
Genetic reagent (D. melanogaster)UAS-Pi3K21B-RNAiBloomington Drosophila Stock CenterBDSC:38991; FBst0038991; RRID:BDSC_38991
Genetic reagent (D. melanogaster)UAS-Pi3K59F-RNAiBloomington Drosophila Stock CenterBDSC:36056; FBst0036056; RRID:BDSC_36056
Genetic reagent (D. melanogaster)UAS-FIG4-RNAiBloomington Drosophila Stock CenterBDSC:58063; FBst0058063; RRID:BDSC_5806335265
Cell line (Homo-sapiens)HEK293ATCCCRL-1573
Recombinant DNA reagentP4M::GFP (plasmid)Hammond et al., 2014
Recombinant DNA reagentP4M × 2::GFP (plasmid)Hammond et al., 2014
Recombinant DNA reagentPLC-PH::GFP (plasmid)Hammond et al., 2014
Recombinant DNA reagentpGU (plasmid)Lu et al., 2021
Recombinant DNA reagentMaLionR (plasmid)AddgeneAddgene #113908
Recombinant DNA reagentpNP (plasmid)Qiao et al., 2018
Recombinant DNA reagentpNP-fwd-KD (plasmid)This paper
Recombinant DNA reagentpNP-PI4KII-KD (plasmid)This paper
Recombinant DNA reagentpNP-PI4KIIIα-KD (plasmid)This paper
Recombinant DNA reagentpNP-PI4K-2KD (plasmid)This paper
Recombinant DNA reagentpNP-PI4K-3KD (plasmid)This paper
Commercial assay or kitPlasmid midi kidQiagenCat#12,143
Commercial assay or kitPlasmid mini kitThermo ScientificCat#K0503
Commercial assay or kitGel extractionThermo ScientificCat#K0692
Chemical compound, drugHalocarbon oilHalocarbon 95 oilCat#9002-83-9
Chemical compound, drugX-treme Gene 9 DNA transfection reagentSigmaCat#6365787001
Chemical compound, drugFluorescent PM dyeThermoFisherThermoFisher, Cat#C10046
Chemical compound, drug2-Deoxy-D-glucoseSigmaCat#D8375
Chemical compound, drugAntimycin ASigmaCat#A8674
Chemical compound, drugMembrane dyeInvitrogen CellMaskCat# C10046
Chemical compound, drugWortmanninSigmaCat# 19545-26-7
Software, algorithmFiji (ImageJ)https://imagej.net/Fijihttps://imagej.net/Fiji
Software, algorithmGraphPad Prism 8.0GraphPad Softwarehttp://www.graphpad.com/
Otherair-permeable membraneYSI IncYSI Membrane Model #5,793YSI Inc, Yellow Springs, OH

Fly stocks

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Flies of carrying transgenic ubi-P4M::GFP, ubi-P4M × 2::GFP, ubi-PLC-PH::GFP and ubi-PLC-PH::RFP alleles were generated by phiC31-mediated integration protocol (Huang et al., 2009). attPVK00022 (BL#24868) and attPVK00040 (BL#35568) stocks were used to integrate the above constructs to the 2nd chromosome and 3rd chromosome, respectively.

PI4K-3KD was generated using pNP plasmid based on the published protocol Qiao et al., 2018. The pNP vector was cut with Nhe I and EcoR I and ligated with annealed oligo-dimmer o to generate pNP-fwd-KD, pNP-PI4KII-KD, and pNP-PI4KIIIα-KD. Primers used for annealing oligo-dimmer were listed in Supplementary file 2:

The pNP-fwd-KD was digested with Spe I and ligated with the shortest fragment cut by Spe I and Xba I from pNP-PI4KIIα-KD to make pNP-PI4K-2KD. To make pNP-PI4K-3KD, pNP-PI4KIIIα-KD was digested with Spe I and ligated with the shortest fragment cut by Spe I and Xba I from pNP-PI4K-2KD. pNP-PI4K-2KD and pNP-PI4K-3KD were used to generate transgenic stocks with the standard protocol.

UAS-AT1.03NL1(DGRC#117011) was used to express the Drosophila-optimized ATeam ATP sensor ‘AT[NL]’ in follicle cells (Tsuyama et al., 2017). cy2-Gal4 (Queenan et al., 1997) was a gift from David Bilder, UC Berkeley. rbo::GFP was a gift from Kendal Broadie, Vanderbilt University (Huang et al., 2004).

w; lgl::mCherry and w; lgl::GFP knock-in stock were previously published (Dong et al., 2015).

Drosophila cultures and genetic crosses are carried out at 25 °C.

Additional stocks used were: UAS-PI4KIIIα-RNAi (BL#35256), UAS-Rbo-RNAi (VDRC#47751), UAS-ttc7-RNAi (VDRC#35881).

Molecular cloning

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Mammalian constructs of P4M::GFP, P4M × 2::GFP, and PLC-PH::GFP were as previously described (Hammond et al., 2014; Hammond et al., 2012; Várnai and Balla, 1998). DNA fragments encoding PLC-PH::GFP, P4M::GFP and P4M × 2::GFP were inserted into pGU vector (Lu et al., 2021) which contains a ubiquitin promoter. MaLionR ATP sensor was obtained from Addgene (#113908) (Arai et al., 2018).

Generation of RNAi mutant clones in Drosophila follicle epithelia

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Follicle cells containing over-expressing or RNAi clones were generated by heat-shocking 3 days old (after eclosion) young females of the correct genotype at 37 °C for 15–30 min and ovaries were dissected 3 days later.

Live imaging and hypoxia treatment in Drosophila epithelial cells

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Ovaries from adult females of 2 days old were dissected in halocarbon oil (#95) and were imaged according to previously published protocol (Dong et al., 2015; Huang et al., 2011). To ensure sufficient air exchange to samples during the imaging session, dissected ovaries were mounted in halocarbon oil on an air-permeable membrane (YSI Membrane Model #5793, YSI Inc, Yellow Springs, OH) sealed by vacuum grease on a custom-made plastic slide over a 10 × 10 mm2 cut-through window. The slide was then mounted in a custom made air-tight micro chamber (~5 cm3) for live imaging under confocal microscope. Oxygen levels inside the chamber were controlled by flow of either air or custom O2/N2 gas mixture at the rate of approximately 1–5 cc/s. Images were captured at room temperature (25 °C) on an Olympus FV1000 confocal microscope (60 x Uplan FL N oil objective, NA = 1.3) by Olympus FV10-ASW software, or on a Nikon A1 confocal microscope (Plan Fluo 60 x oil objective, NA = 1.3) by NIS-Elements AR software.

Cell culture and imaging

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HEK293 cells were cultured in glass bottom dishes (In Vitro Scientific) and were transfected with DNA using X-treme Gene 9 DNA transfection reagent (Sigma Cat# 6365787001). After 24–40 hr of transfection cells were mounted and imaged on a Nikon A1 confocal microscope (Plan Fluo 40 x oil objective, NA = 1.3) by NIS-Elements AR software. For images to be used for quantification, parameters were carefully adjusted to ensure no or minimum overexposure. In addition, when necessary, a fluorescent PM dye (CellMask DeepRed Plasma Membrane Stain, ThermoFisher, Cat#C10046) was added to the cell culture prior to live imaging to help in visualizing the PM for later quantifications.

Hypoxia and ATP inhibition experiments in HEK293 cells

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HEK293 cells one day after transfection were imaged live in temperature control chamber at 37 °C. For hypoxia and ATP inhibition experiments, cells were starved in glucose-free medium six hours prior to live imaging. Hypoxia treatment was carried out using a custom designed culture dish lid which seals the 35-mm glass-bottom culture dish but allows gas to be flushed in and out the sealed dish chamber through two small built-in nozzles. Prior to the sealing, medium inside dish was reduced to ~200 µl and was covered by an air permeable membrane to prevent evaporation. Oxygen levels inside the chamber were controlled by flow of either air or custom O2/N2 gas mixture at the rate of approximately 0.1 cc/s. ATP inhibition was initiated by adding equal volume of serum containing 2-DG and antimycin to the final concentrations of 10 mM and 2 µM, respectively. After the end of inhibition, drugs were washout by replacing with normal media. For wortmannin inhibition experiment, wortmannin was added to the washout media to final concentration of 10 µM.

Image processing and quantification

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Time-lapse movies were first stabilized by HyperStackReg plug-in in ImageJ. Images or movies containing excessively noisy channels were denoised by PureDenoise plugin in ImageJ prior to quantification. PM localization of GFP or RFP in images or movies was measured in Image J by custom macro scripts. For Drosophila samples, ROIs approximately 20–40 µm2 were drawn across selected cell junctions in the first frame of the movie. Custom macros were used to automatically generate PM masks by threshold-segmentation using the mean pixel value of the ROI.

For HEK293 cells, PM masks were generated by an à trous waveleta decomposition method (Hammond et al., 2014; Olivo-Marin, 2002) base on the channel that either contains PM-localized proteins or fluorescent PM dyes. Cytosol masks were generated by segmentation using threshold based on the mean pixel value of the ROI. Cells expressing all transfected fluorescent proteins were selected for measurement. For each cell, one ROI was drawn to cover part of cell that contains PM and cytoplasm.

Due to the use of computer generated PM and cytosol masks, the exact shape of the ROI was not critical, except that PM segments in contact with neighboring expressing cells were avoided. Nuclei and intracellular puncta were also avoided. Custom macros were used to automatically measure PM and cytosolic intensities of each fluorescent protein in each cell marked by ROI in the sample image. Background was auto-detected by the macro based on the minimal pixel value of the whole image.

The PM localization index for each fluorescent protein was auto-calculated by the macro as the ratio of [PM - background]/[cytosol - background]. In live imaging experiments, “Normalized PM Index” was calculated by normalizing (PM Index –1) over the period of recording against the (PM Index –1) at 0 min. Data were further processed in Excel, visualized and analyzed in Graphpad Prism.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

References

Decision letter

  1. Elisabeth Knust
    Reviewing Editor; Max-Planck Institute of Molecular Cell Biology and Genetics, Germany
  2. David Ron
    Senior Editor; University of Cambridge, United Kingdom

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.]

https://doi.org/10.7554/eLife.79582.sa1

Author response

We would like to thank all three reviewers for their comprehensive and constructive comments. We are in particular grateful to reviewer#3 for the long and detailed suggestions on improving the manuscript text and figures. We have already incorporated most of these suggestions into the preliminary revision of manuscript. In addition to the changes already made in initial submission to eLife, in this submission:

1. We have successfully carried out hypoxia assays in live HEK293 cells as requested by the reviewers. Such results are presented in updated Figure 7—figure supplement 1B&C. In Brief, we showed that hypoxia in HEK293 cells induced acute and reversible reduction of intracellular ATP as measured in real time by ATP sensor MaLionR, as well as depletion of PM PI4P and PIP2. Such results are fully consistent with our hypoxia assays in Drosophila tissues, further supporting the hypothesis that hypoxia triggers acute and reversible depletion of PM PI4P and PIP2 through ATP inhibition. We also added a new video (Figure 7 video-1) to show the changes of MaLionR sensor in HEK293 cells undergoing hypoxia and reoxygenation. Establishing hypoxia assay for imaging live HEK293 was more challenging than we expected, but we hope reviewers find the data in this manuscript satisfying.

2. We revised and streamlined the Discussion, making it ~200 words shorter and more concise.

3. We also reformatted the manuscript and added additional files such as raw data to meet eLife requirements.

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

Summary:

This manuscript takes a closer look at how hypoxia affects the accumulation of PI4P and PI4,5P2 (PIP2) in the plasma membrane of Drosophila ovarian follicular epithelial cells and how ATP depletion similarly affects the localization of the same phospholipids in HEK293 cells. They demonstrate that hypoxia results in the reversible loss of plasma membrane (PM) association of both lipids, with PIP2 disappearing ahead of PI4P, and recovering more slowly than PI4P when oocytes are returned to normoxia. They also show that the intracellular vesicular pools of PI4P are depleted ahead of the PM pools and the PI4P recovery occurs first in PM, then in the vesicles. They show that the disappearance and recovery of the polarity protein Lethal giant larvae (Lgl) parallels that of PIP2 during hypoxia and subsequent normoxia, with a very slight delay. The authors then go on to show the RNAi knockdown of the PM enzyme (PI4KIIIa) that phosphorylates PIP delays the recovery of PI4P at the membrane, with recovery first occurring in the vesicular pools. This knockdown also delays the recovery of PIP2 and, as with recovery of PI4P, the recovery of PIP2 now occurs first in vesicular pools. Lgl recovery follows that of PI4P and PIP2 with RNAi knockdown of PI4KIIIa. The knockdown of all three of the enzymes that phosphorylate PIP to generate PI4P delays recovery of PI4P, PIP2 and Lgl at the membrane even more. The authors show that proteins required for the PM localization of PI4KIIIa have similar effects on the recovery of PM PI4P, PIP2 and Lgl (with delays and recovery of vesicular pools before PM pools). Independently, the authors show that ATP depletion in HEK293 cells result in similar reversible depletion of PI4P, PIP2 and Lgl from the PM. From these studies and their previous findings, the authors conclude that pools of PI4P and PIP2 are likely rapidly turned over in the membrane even during normoxia and that this rapid recovery is dependent on the PM localized enzyme that phosphorylates phosphoinositol.

Major comments:

Overall, the data are beautifully presented; it is quite helpful to have a video of each experimental treatment showing the corresponding response of all three molecules that are being monitored. Signal quantification over time is carefully documented. With the exception that a link between hypoxia and depletion of ATP has not been demonstrated here, the key conclusions are convincing. However, as pointed out below (in the significance section), some of the major points have already been published by this group. Their conclusion that hypoxia induces acute and reversible reduction of cellular ATP levels (which are then proposed to affect the activities of the enzymes required for PI4P and, consequently, PIP2 production) was not shown. They did demonstrate that acute depletion of ATP had the same consequences on PM phospholipids as acute hypoxia (in HEK293 cells). And, indeed, it makes sense that hypoxia could affect enzymes required for ATP synthesis, but the authors would have to show that acute hypoxia results in acute reduction in cellular ATP pools to make the links they suggest. This is something they should be able to do in the HEK293 cells now that they have their ATP sensor. Just to note, this group did show that hypoxia can reduce levels of ATP in Drosophila oocytes in their previous paper (Dong et al., 2015, Figure S3), but it is unclear if this is reversible and happens in the time frame of the experiments presented in this current manuscript.

We appreciate reviewer’s point on our previous studies on hypoxia and ATP inhibition. In Dong et al. 2015 we biochemically measured ATP levels in embryos treated by hypoxia, but due to lack of ATP biosensors it was not possible then to show real time ATP level changes in cells undergoing hypoxia and reoxygenation. Instead, we showed that direct ATP inhibition by antimycin treatment mimics the effect of hypoxia, supporting the hypothesis that hypoxia acts through ATP inhibition.

In the current manuscript, we are able to demonstrate for the first time that hypoxia triggered acute and reversible ATP level reduction in Drosophila follicular epithelial cells (Figure 7—figure supplement 1A). Furthermore, we are able to show the close correlation of ATP and PM PI4P/PIP2 levels, and identified PI4KIIIa as one of the key enzymes in the process. In the finalized manuscript we also added data to show ATP level changes in HEK293 cells under hypoxia, as suggested by the reviewer (Figure 7—figure supplement 1B).

My suggestions are the following:

(1) The authors need to make it absolutely clear what was already known, including the following: (A) hypoxia reversibly affects PM pools of PI4P, PIP2, and Lgl (and other membrane associated proteins), (B) that hypoxia can affect ATP levels in Drosophila oocytes (although these previous studies do not show anything about the dynamics) and (C) that reducing ATP levels affects PM pools of PI4P, PIP2 and Lgl.

We agree with reviewer and have revised the introduction (p3, second paragraph) to better summarize what we previously observed on hypoxia/ATP and PIP2 turnover. It should be noted though that our previous studies did not contain any data regarding PI4P changes under hypoxia or ATP inhibition, as the current manuscript is the first time we reported the making and use of PI4P sensor such as P4Mx2::GFP in Drosophila.

(2) They should demonstrate that acute hypoxia and return to normoxia has acute and reversible effects on cellular ATP levels – they now have the tools to do this, at least in HEK293 cells.

We agree with reviewer and are happy that we are able to add this data to the final revision. Such experiments did require significantly modified setup for imaging live HEK293 cells with controlled hypoxia/reoxygenation and we had to spend more than a month to optimize the experiments. The data are presented in Figure 7—figure supplement 1C

Minor comments:

The manuscript is too long and the discussion unnecessarily repeats everything already presented in the results. The authors should find a way to streamline the discussion.

We revised the final manuscript and make the discussion ~200 words shorter and more concise. Paragraphs rephrasing the results were removed.

N values should be given for all figures and experiments, and the N=23/24 versus N=24/24 needs to be explained the first time it is used.

We have revised manuscript so all N values are clearly provided and easier to understand.

There are a few mismatches in terms of plural nouns and singular verbs and vice versa sprinkled into the manuscript, so some careful editing would be useful.

We have revised the manuscript to eliminate such errors/typos, especially with the help of the generous and comprehensive list of by reviewer#3.

Significance:

I was initially quite excited about the novelty of their findings and the potential insight into the dynamics of PM pools of the two phospholipids that are critical to cell polarity and that play important signaling roles. However, at least a subset of their conclusions were either published in their earlier work or do not necessarily follow from what they have done in this manuscript. Their statement that hypoxia in Drosophila induces acute and reversible depletion of PM PI4P and PIP2 was presented in a previous publication (See Figure 8 of Dong et al., 2015).

We greatly appreciate reviewer’s comments on the significance of our discovery. Again all data regarding PI4P are new in this manuscript and have not been published before. We only published very preliminary data suggesting the reversible depletion of PIP2 and PIP3 (but not PI4P) under hypoxia (Dong et al., 2015). The current manuscript provides a comprehensive set of quantitative live imaging data with high spatial and temporal resolution that demonstrate for the first time the dynamic turnover of PM PI4P under hypoxia and ATP inhibition, the correlation between such turnovers of PM PI4P and PIP2, and the direct correlations between PI4P/PIP2 turnover and Lgl electrostatic PM targeting and intracellular ATP levels. In addition, studies on the role of PI4KIIIa complex in such process have not been done before.

This manuscript would appeal to an audience interested in the mechanisms of cell polarity and phosphoinositide signaling.

I am a Drosophila developmental geneticist quite familiar with the topics that this paper addresses.

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

Summary:

This manuscript describes the effect of hypoxia on the levels of PI4P and PI45P2 , two key PPIs that are enriched on the inner leaflet of the plasma membrane. These PPIs are synthesized by the sequential phosphorylation of π by a PI-4 kinase and subsequently a PI4P 5 kinases, both of which use ATP. The relevant PI-4 kinase at the plasma membrane, PI4KIIIa has been conclusively identified previously in mammalian cells by the DeCamilli lab (Nakatsu et.al JCB 2012) and its role in regulating the synthesis of PI4P and PI(4,5)P2 in two Drosophila cell types in vivo shown by two previous studies. Balakrishanan et.al J.Cell Sci 2018 (photoreceptors during PLC signalling) and Basu et.al Dev.Biol 2020 ( in multiple larval cell types ). PI4KIIIa has been shown to exist as a complex of the enzymatic polypeptide, EFR3 and TTC7. The studies by Nakatsu, Balakrishnan and Basu have shown the importance of the complex subunits is regulating PI4P and PI45P2 levels in cultured mammalian cells and Drosophila cell types in vivo.

We thank reviewer for pointing out the work of Balakrishanan et.al 2018. We have added a brief summary this reference to the Discussion in revised manuscript (p13, line 10-12)

In the present study, Lu et. al build on their previous work showing that the polarity protein Lgl undergoes hypoxia induced translocation. They show that hypoxia also induces loss of PI4P and PI45P2 at the plasma membrane in these cells correlated with loss of Lgl localization to the PM. The manuscript then goes on to establish the requirement of the PI4KIIIa complex in regulating Lgl localization as well as PI4P and PI45P2 levels at the plasma membrane during hypoxia and the subsequent recovery of these at the plasma membrane.

The strength of the manuscript is twofold.

(i) The work is done to a high technical standard and the investigators have carried out the measurements of LGL localization, PI4P and PI45P2 levels along with simultaneous measurements of ATP levels in vivo. The work would be strengthened further if the authors could show the level of depletion of PI4K isoforms or PI4KIIIa complex subunits units induced in ovarian tissue under their experimental conditions by the GAL4 drivers used in this study. This is not a persnickety detail as RNAi lines can have very different effectiveness in Drosophila ovarian tissue compared to other fly cell types. This point is, in particular, important in cases where an RNAi line is being used and the conclusion is a lack of impact on a phenotype being studied.

We are fully aware of the potential caveat of RNAi. In our previous publications we were able to validate RNAi knock-down efficiency against endogenously or ectopically expressed GFP-tagged target proteins (Dong et al., 2020; Dong et al., 2015; Lu et al., 2021) or endogenous proteins with available antibodies (Dong et al., 2015). It is regrettable that presently such reagents are not available for directly examining the level of RNAi knock-down for PI4KIIIa and PI4KIIa etc. We did show that rbo-RNAi efficiently knocked down the expression levels of Rbo::GFP (Figure5—figure supplement 1C). In current manuscript, we have been very careful to draw conclusions based on negative RNAi results.

(ii) A second strength is that the authors now illuminate a further in vivo cell type where the function of the PI4KIIIa complex in regulating PI4P and PI45P2 levels. This adds to the earlier work of Nakatsu, Balakrishnan and Basu.

A key difficulty with the current story is the lack of specificity of the phenotype they demonstrate under hypoxia. Of course, hypoxia is expected to deplete cellular ATP levels but PI4KIIIa is not the only enzyme that this lack of ATP will impact. There will be dozens or more other kinases, both protein and lipid kinases whose function will be impacted by the drop in ATP levels. Therefore, it is hard to attribute a specific/particular role to the PI4KIIIa complex under these conditions. The mislocalization of LGL::mCherry while correlated with PI4P and PI45P2 levels at the plasma membrane may be just that- a correlation. It is quite possible, indeed likely, that the mislocalization of LGL-mCherry under hypoxia conditions is due to the reduction of the activity of another lipid or protein kinase due to the drop in ATP levels due to hypoxia (PKC is a possibility too).

We agree with reviewer that PI4KIIIa almost certainly is only one of the enzymes that are involved in regulating the PM PI4P/PIP2 turnover triggered by hypoxia. This manuscript is our first effort to investigate the potential regulatory network underlying the hypoxia-triggered turnover of PM PI4P and PIP2, and it is our long term goal to identify more components in the regulatory network.

As to underlying mechanisms of the loss of PM Lgl under hypoxia, we previously showed that PM targeting of Lgl dependents on both PI4P and PIP2 and acute depletion of PI4P and PIP2 in cultured cells completely blocks the PM targeting of Lgl (Dong et al., 2015). Thus, although we cannot exclude contributions from other lipids, it is highly plausible that loss of PM PI4P and PIP2 triggered by hypoxia is the main driving force disrupting the electrostatic PM targeting of Lgl.

Lgl is phosphorylated by aPKC and such phosphorylation inhibits Lgl PM targeting by neutralizing the positive charges on Lgl’s polybasic motif (Dong et al., 2015, Bailey et al., 2015). Thus, potential inhibition of aPKC activity by hypoxia should not inhibit the PM targeting of Lgl. Consistently, we previously showed that aPKC-/- mutant cells showed same acute and reversible loss of PM Lgl under hypoxia (Dong et al., 2015).

Minor comments:

The authors must reference all published work on the PI4KIIIa complex in the literature. Some of it is excluded in the present version

We apologize for the missing references and in the revised manuscript we have already added several additional references based on the suggestions of reviewer#1 and #3. In the finalized manuscript we had made our best effort to cover all the relevant studies.

The Drosophila work, particularly cell types used, etc are not accessible to people who are not fly experts. This should be done.

We added a sentence to the end of the first paragraph in Results to specifically highlight that all Drosophila studies were based on follicular epithelial cells from female ovary (p4, line 25-27).

Significance:

Adds to knowledge on the PI4KIIIa complex.

Builds on existing knowledge in the PI4KIIIa field and maybe also cell polarity field.

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

Summary:

Phosphatidylinositol phosphates (PIPs) are key determinants of membrane identity and regulate crucial cellular processes such as polarization, lipid transfer and membrane trafficking. Despite decades of study, surprisingly little is known about how levels of PIPs are regulated in response to cellular stress. Here, using Drosophila ovarian follicular epithelial cells and human HEK293 cells, the authors show that levels of plasma membrane (PM) PI4P and PIP2 decrease rapidly in response to hypoxia, resulting in loss of polybasic proteins from the PM. These effects are reversed in response to reoxygenation. Similarly, hypoxia leads to acute depletion of ATP levels, which also regenerate following reoxygenation. Using a combination of quantitative image analysis and genetic analysis, they show that PI4KIIIalpha and its binding partners Rbo/ EFR3 and TTC7 are needed to maintain PI4P and PIP2 at the PM under normal and hypoxic conditions, whereas the other two Drosophila π 4-kinases, Fwd/PI4KIIIbeta and PI4KII, play a less important role in PM PIP homeostasis. Their results suggest that manipulations with indirect effects on PIPs (hypoxia, ATP depletion, ischemia) can have a profound impact on electrostatic charge at the PM, as well as downstream processes that require PM PI4P and PIP2.

Major Comments:

1. In general, the authors' conclusions are convincing. However, some of the results are less evident from the still images and graphs provided in the figures than from the videos that accompany the figures. Some suggested improvements are below.

2. No additional experiments are essential to support the claims of the paper, although some additional quantitation would be helpful to the reader, as detailed below.

3. Data and methods are generally presented in such a way that they can be reproduced, although some additional details would be helpful, as listed below.

4. Experiments were adequately replicated, and statistical analysis appears adequate.

We are extremely grateful to the generous efforts of the reviewer providing such a detailed list of suggested improvements. We have incorporated all the text revisions into the revised manuscript and revised the figures accordingly too.

Minor comments:

1. Although the data are generally quantified quite well, there are two instances in the first full paragraph on p. 5 where this is not the case. First, PM PI4P is described as "oftentimes" as showing a transient increase in the early phase of hypoxia. However, this is not quantified. How often did this occur among the samples examined? How large is the transient increase when it occurs (Figure 1A' error bars are not obvious on the colored background)? Second, the authors state that the P4Mx2-GFP puncta "often" became brighter after recovery. How often did this occur? No quantitation is provided.

Upon close inspection of the data, we conclude that during the early phase of hypoxia PM P4Mx2::GFP always showed an initial drop followed a transient increase. Thus we revised the sentence to delete “oftentimes”.

We did not specifically quantify the transient increase of the PM P4Mx2::GFP during the early phase of hypoxia since it is likely an artifact as discussed in the manuscript, making its quantification less meaningful.

As to the P4Mx2::GFP puncta, regretfully we do not have imaging tools that can accurately and automatically recognize/measure such puncta in our live recordings. We are actively developing such software using trainable Weka segmentation tool (https://imagej.net/plugins/tws/) and hopefully such puncta quantifications will be possible in our future experiments.

2. The authors conclude that "PI4KIIalpha and Fwd contribute significantly to the maintenance of PM PI4P" (bottom of p. 7), yet they did not validate their RNAi knockdowns of these two genes, so they do not know whether it is one or both of these PI4Ks that contribute.

We agree with reviewer that our RNAi knockdowns on PI4KIIa and Fwd are not sufficient to tell whether one or both contribute to the PM PI4P maintenance. We revised the sentence to “Our data support that PI4KIIα and/or FWD contribute significantly to the maintenance of PM PI4P…” (p7, line 33-34)

3. In Figure 4B, a subset of the cells "show failed recovery of PM Lgl::GFP". However, some cells did recover. This average percentage of cells that recovered should be quantified, if possible.

Added numbers of PI4K-3KD cells that show normal or failed hypoxia response of Lgl::GFP and revised the sentences accordingly (p8, line20-23)

4. In Figure 7A, B, the bottom cell in each example lags behind the top cell in recovery of the MaLionR sensor. The frequency of observed cells in each class for 7A, B should be quantified.

Added n numbers of each cell class to Figure 7A, B legend.

5. In most cases, prior studies were referenced appropriately. However, two previous studies in Drosophila showing the effects of Sktl/PIP2 reduction on localization of polybasic proteins Lgl, Baz/Par-3 and Par-1 were not cited (relevant to the first paragraph of the Introduction, p. 3): Gervais et al., Development (2008), Claret et al. Curr Biol (2014). In addition, two studies showing the importance of Drosophila PI4KIIIalpha in synthesizing PM PI4P and PIP2 were not cited (relevant to the description of this enzyme, top of p. 6): Yan et al., Development (2011), Tan et al., J Cell Sci (2014). Data showing fwd null mutants are not lethal (relevant to top of p. 7) were published in Brill et al., Development (2000).

We thank reviewer for suggesting additional references. We added Yan et al. and Tan et al. for referencing PI4PIIIa, and Brill et al. for referencing the original characterization of fwd. We discussed work from Gervais et al. and Claret et al. in the revised discussion (p6, line 11-16).

6. For the most part, text and figures are clear and accurate. However, there are quite a few typos and grammatical mistakes, as well as instances of lack of clarity in the writing that should be addressed. In addition, there are a number of improvements to presentation of data that would make the figures easier to understand. These are listed below.

7. Suggestions to improve presentation of data and conclusions are below.

Again, we greatly appreciate such generous efforts from the reviewer and have incorporated all the text revisions into the revised manuscript.

Significance:

Overall, the authors do a nice job of showing that hypoxia leads to previously unappreciated effects on levels of PM PI4P and PIP2, resulting in loss of PM association of proteins important for normal cellular physiology. This finding is quite novel. Moreover, the authors provide insight into the identity of the PI4Ks that are responsible for regenerating PM PIP2 following return to normoxia. Their analysis of the dynamics of these changes provides multiple interesting insights, including the potential roles of intracellular pools of PI4P in replenishing PM PIP2 and the observation that intracellular accumulation of PIP2 is occasionally observed in association with the appearance of intracellular PI4P puncta, suggesting a novel route for PIP2 replenishment in response to hypoxic stress. Their results will provide the basis for future studies examining the cellular mechanisms involved. This study will be of interest to those studying phosphoinositide biology as well as cellular responses to hypoxic stress and recovery, such as occur during ischemia and reperfusion.

Reviewer expertise: Drosophila molecular genetics, cell biology, developmental biology, phosphoinositides, PIP pathway enzymes, PIP effectors

Referees cross-commenting

This session includes the comments of all reviewers.

Reviewer 3: I agree with reviewer #1 that the authors did not do a good job of clarifying what they and others had previously shown, and I must confess I didn't carefully examine their previous papers carefully enough before preparing my review. In fact, they previously showed that hypoxia affects localization of Dlg at the plasma membrane and that its recovery depends on PI4KIIIalpha and PIP2 (Lu et al., Development 2021). This is in addition to their previous data showing effects of hypoxia on Lgl (Dong et al., J Cell Biol 2015). Thus, less of the information in the current manuscript is novel than I thought when I initially read it.

I also agree with reviewer #2 that they need to do a better job of citing the relevant literature and considering the possibility that hypoxia and reduced levels of ATP might affect many different enzymes. In addition, as suggested by reviewer #1, it seems important

Reviewer 1: I agree with what Reviewer 3 is suggesting and with reviewer 2 that the authors should do a better job of citing all of the relevant literature. I also appreciate the detailed edits provided by Reviewer 3 – it was very generous of them to do this.

Reviewer 2: The points raised by reviewer 1 and 3 with regard to the citing or prior work (from the authors or other labs) also applies to their citing of literature on π and PI4K signalling. Here too citing or prior work has been less than satisfactory making it difficult to do this.

We want to thank all three reviewers for their thoughtful and constructive comments. We have revised the introduction to better summarize what we had observed in our previous studies. On the other hand, this manuscript presents a systematic study on the hypoxia-triggered turnover of PM PI4P and PIP2, the correlation between PI4P/PIP2 turnover and electrostatic PM targeting of Lgl, as well as a potential role of PI4KIIIa and its PM targeting mechanism in regulating the turnover of the PM PI4P and PIP2 under hypoxia. Although the latter by no means indicates that PI4KIIIa is the only enzyme in regulating such process, its characterization is the beginning for us to further identify additional enzymes and regulators in this hypoxia triggered phenomenon.

We have added additional references as suggested by the reviewers in the revised manuscript, and made our best efforts to have all relevant references cited.

Description of the revisions that have already been incorporated in the transferred manuscript

(Note: Current resubmission is formatted to meet eLife style. To avoid confusions, we kept the figure references etc as the same in the original manuscript)

We have incorporated nearly all of the suggestions from reviewer#3 into the current revision, with few exceptions as listed at the end of this letter. Below are point-to-point responses to selected suggestions involving data interpretation and comprehensive text revisions

p. 5, first paragraph, line 2: replace "oftentimes" with "often" and provide quantitation (see above)

Deleted the “oftentimes”. Upon close inspection of our data we conclude that PI4P always showed transient increase of PM signal in early hypoxia.

p. 5, first paragraph, line 6: the claim of "often" should be quantified (see above)

Deleted the “often”. PI4P puncta actually were consistently brighter after recovering from hypoxia.

p. 5, second paragraph: the extent of recovery of Lgl is less when Lgl-RFP is coexpressed with PLC-PH-GFP, potentially due to titration of PIP2 by PLC-PH; the authors should comment on this

This is a good suggestion from the reviewer. Revised by adding to the end of paragraph: “Note that in Figure 1B Lgl::RFP recovery appears lower than in wild type, possibly due to the titration of PIP2 by PLC-PH::GFP expression.”

p. 5, last line: the authors should provide information about the "targeted RNAi screen"; which genes were tested? did any others give relevant phenotypes? a table showing the results of the screen should be provided as supplementary information

Added Table S1 which summarizes the results of RNAi screen.

p. 11, first full paragraph, line 6: what about PI4KIIIbeta? is the KmATP for this enzyme known?

Based on literature, KmATP of PI4KIIIbeat is similar to PI4KIIIa’s (~400uM, Balla and Balla 2006). We added the PI4KIIIb KmATP value to the revised discussion (p11, line25)

p. 11, last paragraph, line 2: what is meant by "etc." is unclear; remove "etc." and include specific information related to what was reported in the literature (with proper references)

Revised the sentence to “…that KmATP of PI4KIIIα was measured decades ago using purified PI4KIIIα enzymes from tissues such as bovine brains and uterus (Carpenter and Cantley, 1990)”. The reference (Carpenter and Cantley, 1990) is a review which contains details of biochemical characterizations of PI4K kinases from numerous publications.

p. 12, line 3: why do the authors claim that the intracellular pool of PI4P is first synthesized by PI4KIIalpha? what about PI4KIIIbeta? their results do not distinguish between these enzymes

We favor the hypothesis that PI4KIIa is responsible for synthesizing the intracellular pool of PI4P because the very low KmATP of PI4KIIa. PI4KIIIbeta has high KmATP similar to PI4KIIIa.

p. 12, last paragraph, lines 6-7: for the reader, please clarity the mechanism that was invoked to explain how PIP5K can make PIP2 from π in E. coli (Botero et al., 2019)

Revised the sentence to “PIP5K can be sufficient to make PIP2 from π in E. coli by phosphorylating its fourth and fifth positions (Botero et al., 2019) in the absence of PI4Ks

p. 13, first paragraph, last line: cannot conclude that components of PI4KIIIalpha are "highly interdependent" without testing effect of knockdown of PI4KIIIalpha on Rbo and TTC7, etc.; instead, can conclude that the data are consistent with all of the components acting in the same process; also, delete "the" before "proper"

Revised the sentence to “.. supporting that components in PI4KIIIαa complex may act interdependently for the proper PM targeting in vivo.

p. 14, second paragraph, lines 3-5: expand on this idea; what additional lipids could be important here? are there examples of other proteins that require these additional lipids?

We revise the sentence to “The reason for such difference between Lgl::GFP and PLC-PH::GFP in rbo-RNAi cells is unclear, though likely derives from the requirement of polybasic motif proteins for additional anionic lipids at the plasma membrane, specifically high mol fractions of phosphatidylserine in addition to lower concentrations of polyanionic phosphoinositides (Yeung et al., 2008).

p. 16, line 6: explain in brief what "pNP plasmid" is and how the multi-RNAi method works (what promoters drive expression of the shRNAs, how many shRNAs are included in the plasmid, etc.)

Added a section in Material and Methods to describe the details of the generation of pNP constructs and fly stocks.

p. 16, lines 8-3: appropriate references should be included for each stock where available

Added references to stocks cy2-Gal4, rbo::GFP and UAS-AT1.03NL1.

p. 16, line 11: explain what UAS-AT1.03NL1 is

Added: “UAS-AT1.03NL1(DGRC#117011) was used to express the Drosophila-optimized ATeam ATP sensor AT[NL] in follicle cells (Tsuyama et al., 2017)

p. 16, lines 16-17: Gerry Hammond should not be listed as providing these constructs if he is a coauthor on the manuscript; appropriate references should be cited for these constructs

Revised the sentence to “Mammalian constructs of P4M::GFP, P4Mx2::GFP, and PLC-PH::GFP were as previously described (Hammond et al., 2014; Hammond et al., 2012; Várnai and Balla, 1998).

p. 17, lines 3-4: sentence fragment "Images were further" is not complete

This was a typo, deleted.

p. 19, lines 5-6 from bottom: title doesn't accurately reflect that PI4P doesn't appear to recover in WT control; why is this the case? recovery was observed in other experiments

Live recording showed that PM PI4P did recover during reoxygenation (Figure 3A, Video S7). This particular recording in Figure 3A/Video S7 was a bit difficult for automatic quantification by our custom software due to that P4Mx2::GFP signal somehow was weak and noisy, resulting in less than “ideal” recovery curves.

p. 22, line 16: fix typo in "uncalibrated"; spell out what "AT[NL] sensor shows

Revised to “Heat map of the (uncalibrated) FRET ratio of ATeam ATP sensor AT[Nl] in follicle cells of a dissected ovary undergoing hypoxia and reoxygenation ex vivo”

Reviewer#3’s suggestions to improve the figures and videos:

- replace colored labels on black boxes with colored labels on white background (Figure 5A (left), Figure 5B-D (top), Figure 6A (left), Figure 7A-C (left), Figure S1A (left), Figure S1C (top), Figure S2A (left), Figure S4 (left))

We have revised the figures accordingly.

- provide scale bars throughout (Figures2-7, S1-S4)

We have revised the figures accordingly.

- provide vertical lines similar to those in Figure 4A' in all of the time-course graphs and/or making the background colors slightly darker (Figures2A', 3A', 5A', 6A'); also make the error bars darker (Figure 1A'-C', Figure 4, Figure 5A', Figure S2B)

We revised all backgrounds in charts to make them similar to Figure 4A’.

- for consistency, label PM index graphs in Figure 4 and Figure S2 as Figure 4A' and Figure S2A'

We revised figures 4 and S2 accordingly.

- why are some of the PM index graphs labeled "PM index" and others labeled "PM index-1" on the Y-axis? this should be explained or changed for consistency

The mixed use of “PM index” and “PM index-1” were relics due to different versions of software used throughout the project. We revised all graphs to make Y-axis “PM Index” label consistent.

- "blank diamonds" described in figure legend for Figure 7B' are barely visible when printed

Revised Figure 7B’ by filling blank diamonds with grey color to increase their visibility.

- Figure 7C is mislabeled (MaLionR label should be replaced with PLC-PH-RFP)

We corrected this error in revised Figure 7C.

- in Figure S3A, it would help to know the size of the cells (i.e., how many were present in the area examined)

Revised the Figure S3A legend to clarify that each circle covers approximately three to four cells.

- in Video S19, "PLC-PH::RFP" is mislabeled "PLC-PH::GFP" (both P4MX2 and PLC-PH are labeled GFP in the video)

We renamed the video file to correct this typo.

Description of analyses that authors prefer not to carry out

(Note: Current resubmission is formatted to meet eLife style. To avoid confusions we kept the figure references etc as the same in the original manuscript)

Reviewer#2: The work would be strengthened further if the authors could show the level of depletion of PI4K isoforms or PI4KIIIa complex subunits units induced in ovarian tissue under their experimental conditions by the GAL4 drivers used in this study.

We are regretful that we are unable to directly evaluate the RNAi knock-down efficiency of several genes such as PI4KIIIa. We have nonetheless been careful to draw the conclusions in the manuscript in accordance with the potential caveat of RNAi experiments. We did directly show that rbo-RNAi directly knocked down the Rbo::GFP (Figure S1C). In addition, although we could not confirm the knock-down of ttc7-RNAi, we showed it can reduced level of Rbo::GFP, which is likely due to an effective knock-down of TTC7 (Figure 6B).

Reviewer #3:

p. 6, second full paragraph, lines 6 and 9: the callouts should be to Videos S5, not Video S4

p. 7, second paragraph, line 3: change name of Video S7 to S6, and call out Video S6 here

p. 7, third paragraph, line 2: change name of Video S8 to S7, and call out Video S7 here

p. 8, first paragraph, line 8: change name of Video S6 to S8, and call out Video S8 here

- Videos should be referred to in order (current Videos S7 and S8 should be renamed S6 and S7, and current Video S6 should be renamed S8)

We appreciate reviewer’s suggestion but decided to keep the videos in current order. Current resubmission is formatted to meet eLife style and each videos follow the main figures, which is easy for the readers to follow.

Reviewer #3: – replace pale colored boxes under labels for "hypoxia" and "air" with slightly darker boxes (Figure 1A-C, Figure 2A, Figure 3A, Figure 5A', Figure 6A', Figure S2B)

We tested many different combinations of colors and the current set appears to give the best contrast so far. We decided to keep the original color.

Reviewer #3- show single-color images in grayscale, which is easier to see on black and helpful for colorblind readers (applies to all figures except Figure S3); videos and merged still images should be shown in green and magenta for colorblind (not sure if channels in videos are difficult to change)

We converted Figure 1A to gray scale but found it visually inferior to the color version, as the gray images make the temporal differences between green and red channels much less pronounced. We have converted red channel in all videos to magenta color and also added text labels for each channel to reduce potential confusions since the manuscript contains total of nineteen video. Regrettably, to convert red channels in figures requires a very laborious process to recapture, recrop and recompose all the frames used in all figures. We hope that reviewer understand our decision to keep colors in figures unchanged.

https://doi.org/10.7554/eLife.79582.sa2

Article and author information

Author details

  1. Juan Lu

    Department of Cell Biology, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – review and editing
    Contributed equally with
    Wei Dong
    Competing interests
    No competing interests declared
  2. Wei Dong

    Department of Cell Biology, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Data curation, Formal analysis, Investigation, Project administration, Validation, Visualization, Writing – review and editing
    Contributed equally with
    Juan Lu
    Competing interests
    No competing interests declared
  3. Gerald R Hammond

    Department of Cell Biology, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Conceptualization, Formal analysis, Funding acquisition, Methodology, Software, Supervision, Writing – original draft, Writing – review and editing
    For correspondence
    ghammond@pitt.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6660-3272
  4. Yang Hong

    Department of Cell Biology, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing
    For correspondence
    yhong@pitt.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2252-0798

Funding

National Institute of General Medical Sciences (R01GM121534)

  • Yang Hong

National Institute of General Medical Sciences (R01GM086423)

  • Yang Hong

National Institute of General Medical Sciences (R35GM119412)

  • Gerald R Hammond

National Institute of General Medical Sciences (R21RR024869)

  • Yang Hong

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

Acknowledgements

We are grateful to Drs Kendal Broadie, David Bilder and Tadashi Uemura for reagents and fly stocks, Kriti Sanghi for technical assistances, anonymous reviewers for their helpful comments, Dr Simon Watkins and University of Pittsburgh Medical School Center for Biologic Imaging for generous imaging and microscopy support, Bloomington and Kyoto Stock Centers for fly stocks, and Developmental Studies Hybridoma Bank (DSHB) for antibodies. Funding: This work was supported by grants NIH- NCRR R21RR024869 (Y H), NIH-NIGMS R01GM086423 and R01GM121534 (Y H), NIH 1R35GM119412-01 (G R H). University of Pittsburgh Medical School Center for Biologic Imaging is supported by grant 1S10OD019973-01 from NIH.

Senior Editor

  1. David Ron, University of Cambridge, United Kingdom

Reviewing Editor

  1. Elisabeth Knust, Max-Planck Institute of Molecular Cell Biology and Genetics, Germany

Publication history

  1. Preprint posted: January 9, 2022 (view preprint)
  2. Received: April 20, 2022
  3. Accepted: June 6, 2022
  4. Accepted Manuscript published: June 9, 2022 (version 1)
  5. Version of Record published: June 29, 2022 (version 2)

Copyright

© 2022, Lu, Dong et al.

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

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  1. Juan Lu
  2. Wei Dong
  3. Gerald R Hammond
  4. Yang Hong
(2022)
Hypoxia controls plasma membrane targeting of polarity proteins by dynamic turnover of PI4P and PI(4,5)P2
eLife 11:e79582.
https://doi.org/10.7554/eLife.79582
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