Spenito-dependent metabolic sexual dimorphism intrinsic to fat storage cells

Metabolism in males and females is distinct. Differences are usually linked to sexual reproduction, with circulating signals (e.g. hormones) playing major roles. By contrast, sex differences prior to sexual maturity and intrinsic to individual metabolic tissues are less understood. We analyzed Drosophila melanogaster larvae and find that males store more fat than females, the opposite of the sexual dimorphism in adults. We show that metabolic differences are intrinsic to the major fat storage tissue, including many differences in the expression of metabolic genes. Our previous work identified fat storage roles for Spenito (Nito), a conserved RNA-binding protein and regulator of sex determination. Nito knockdown specifically in the fat storage tissue abolished fat differences between males and females. We further show that Nito is required for sex-specific expression of the master regulator of sex determination, Sex-lethal (Sxl). “Feminization” of fat storage cells via tissue-specific overexpression of a Sxl target gene made larvae lean, reduced the fat differences between males and females, and induced female-like metabolic gene expression. Altogether, this study supports a model in which Nito autonomously controls sexual dimorphisms and differential expression of metabolic genes in fat cells in part through its regulation of the sex determination pathway. Overall design: Total RNA from 50 dissected sexed, third-instar-larval fat bodies was extracted from 50 third-instar FBs dissected from sexed larvae using 500uL of TRIzol (ambion Cat # 15596018cat number), volumes and purified using the Direct-zol Miniprep Plus kit digested with DNase I (Zymo Cat # R2072cat number). cDNA was generated with 500ng of RNA sequencing and library prep was performed at the University of Colorado Anschutz medical campus Genomics Core. Transcriptome analysis was performed using pseudo-alignment with salmon [PMID 28263959] using the D. melanogaster transcriptome (version dmel_r6.48_FB2022_05). DESeq2 [59] (version 1.40.1) was used for differential expression analysis. Pathway analysis was performed using gProfiler [44] (version 0.2.1).