Avalilação PREreview de Cytokine control of systemic hypoxia tolerance in Drosophila

PREreview of “Cytokine control of systemic hypoxia tolerance in Drosophila”.

By Rebecca S. Moore of HHMI Transparent and Accountable Peer Review Training Pilot.

Ding et al. reveals that Unpaired-3 (upd3)- HIF-1a/sima mediates systemic hypoxia tolerance in Drosophila through a sex-specific gut-to-fat body/oenocyte signaling axis that regulates nitric oxide synthase expression.

This paper addresses several knowledge gaps leading to advancements in the field. Although gut-to-fat/oenocyte signaling has been documented in Drosophila, the context in which it functions was previously unknown. Additionally, HIF-1a/sima activation has been well studied as an adaptive response to hypoxia and stress, however the role of sima as a negative regulator of its own transcriptional activation has not been known. Lastly, while sex-specific differences in stress responses have been documented, specific requirements for cytokine signaling pathways in one sex for survival under hypoxia was unknown. This finding points to fundamental differences in how male and females physiologically adapt to low-oxygen stress.

Specifically, Ding et al identifies a previously unknown interorgan communication pathway where the cytokine upd3 is produced in the gut in response to hypoxia. Gut derived-upd3 then signals to the fat body/oenocytes to promote survival. The authors provide evidence that HIF-1a/sima functions in the fat body, acting as a non-cell autonomous molecular brake preventing lethal upd3 overproduction in the gut. This finding presents a more nuanced role for sima, suggesting it not only activates hypoxia response genes but also prevents detrimental hyper-inflammatory responses. Finally, the authors demonstrate a sex-specific requirement for upd3 in hypoxia.

The authors conclusions are supported, but there are areas in which the paper can be made clearer and/or additional experiments can further strengthen their findings.

General Major Points

1. The authors use one RNAi or mutant line in all experiments. Using additional RNAi lines or mutant alleles would help to support their data. This would help eliminate background effects and show reproducibility across genetic contexts.

2. The authors claims would benefit from rescue experiments (i.e. rescue of upd3 or STAT92E in upd3 mutants) to show sufficiency and complete the causal chain of events – hypoxia -> high upd3 in gut -> sima activity in fat body/oenocytes -| hyper activation of upd3 in gut.

Specific Major Points

The claim that hypoxia rapidly induces upd3 and JAK/STAT signaling is supported by consistent time-course qRT-PCR data showing increased upd3 and multiple STAT targets across sexes and developmental stages (Figure 1), and by two enterocyte drivers (Figure 3C-F). However, reliance on mRNA readouts without direct upd3 protein/secreted cytokine measures or canonical STAT activation assays leaves a gap between transcriptional induction and bona fide pathway activation. 

1. Use UAS STAT92E RNAi to test whether hypoxia-induced SOCS36E and Turandot transcripts require STAT92E in qRT-PCR experiments. The authors should perform qRT-PCR experiments for SOCS36E/Turandot mRNA levels under hypoxia conditions with STAT92E knocked down in the fat body or oenocytes. This will provide pathway-dependency evidence that transcript induction reflects JAK/STAT activation.

2. Add direct pathway activation readouts and cytokine measurements using GFP/LacZ-type reporters and quantify hypoxia-induced reporter activity in gut and abdominal tissues via microscopy or use immunofluorescence of phosphorylated STAT to assess nuclear accumulation under hypoxia. These experiments can be validated in a upd3 mutant. These experiments would validate JAK/STAT pathway activation rather than relying on mRNA readouts.

The evidence for abdominal JAK/STAT activation under hypoxia and induction of STAT target genes in the abdomen upon enterocyte upd3 overexpression is compelling at the whole tissue level (Figure 4B). However, these measurements were made on bulk abdomens and do not localize the response to oenocytes or the fat body.

1. Perform tissue specific STAT necessity by repeating these readouts in r4>STAT92E RNAi or desat>STAT92E RNAi backgrounds to test whether enterocyte upd3 driven inductions require STAT in each tissue/cell type. Additionally, the authors can use an imaging-based approach to visualize upd3 activation in each tissue/cell type. This would provide direct evidence of cell-type specific activation and necessity.

HIF-1a/sima functions as a molecular brake in the fat body that limits upd3 signaling in the gut during hypoxia. The authors provide 3 lines of evidence that support this claim including whole-body qRT-PCR and survival experiments (Figure 5 and 6). However, the key weakness includes the lack of direct validation of sima RNAi knockdown, absence of pathway epistasis or direct pathway activity showing that the sima-dependent activation is causally mediated by upd3-STAT signaling in the fat body/oenocytes. This would provide clear validation of the model.

1. Perform genetic epistasis experiments to test whether gut upd3 knockdown in the gut suppresses JAK/STAT pathway activation in the fat body/oenocytes and improves hypoxia survival. These experiments would provide pathway-specific evidence that fat body sima-dependent cytokine amplification requires gut upd3 and JAK/STAT in fat body/oenocytes.

2. Use reporter lines to image JAK/STAT activity in the tissues/cells of interest. These experiments would establish that sima restrains upd3 driven JAK/STAT signaling at the protein level.

Minor Points

1. In Figure 1A: the authors do not provide any statistical analysis of qRT-PCR data. Providing statistics would help readers understand if upd activation reaches a peak within the time frame studied or if it will continue to increase. Most commonly, qPCR statistics are run on DCt values and not relative expression as relative expression quantification is non linear. The authors can use a One-Way ANOVA followed by a Tukey’s multiple comparison test to achieve statistical power.

2. In Figure 1E-F: The finding that this mechanism is true in larvae and adult flies is interesting. There is missing information about the stage of the larvae that this was tested in. Providing clearer methods would help any scientist who wants to repeat and work on these findings.

3. Figure 6B is called out as Figure 6C. Please update the correct figure call out to account for Figure 6B.

4. The authors provide no information about an internal control in their qRT-PCR experiments. Internal controls are essential for normalization and would strengthen the findings that the expression changes identified are truly hypoxia responsive.

5. Readers would benefit from visualizing the entire survival curves and use of Kaplan Mier statistics which are typical for survival assays. This would allow readers to see if the LD50 were different depending on environmental treatment or if one fly survived much longer to skew the survival statistics.

6. It would be extremely helpful to have clarity in the methods about the survival assays done. More information would give readers clarity to repeat or interrupt data.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.