multiomics depicting the immunometabolism landscape of steatotic livers undergoing bariatric surgery and diet intervention
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent chronic liver disease worldwide that encompasses a spectrum of steatosis, inflammation, and fibrosis. Evidence suggests that weight loss approaches such as dietary restriction (DR) and sleeve gastrectomy (SG) can lead to remission of hepatic steatosis and inflammation. However, it remains unclear about the effects of weight loss on the hepatic immune mechanisms in MASLD. Therefore, this study aims to elucidate the intricate immunometabolic landscape of steatotic livers following DI and BS by employing the sleeve gastrectomy (a typical BS procedure) and comparable food intake after sham surgery in a rat model of MASLD. Single-cell (sc) and single-nuclei (sn) transcriptome analysis together with spatial metabolomics and immunohistochemistry were utilized to depict immunometabolic landscape, while circulating markers were assessed in serum. Furthermore, artificial intelligence (AI)-based image analysis was introduced to characterize the distribution of hepatocytes, myeloid cells and lymphocytes. Overall design: Wild-type rats were administrated with high-fat diet (HFD) for 12 weeks to develop obesity and MASLD. Then, SG (sleeve gastrectomy) was performed on 3 MASLD rats, following by HFD. Simultaneously, 3 rats (DR group) were fed with reduced HFD  comparable to BS group, while 3 rats (Sham group) recieved sham surgery following by uncontrolled HFD. After 8 weeks, rats from each group were sacrificed for the acquisition of liver samples. Last, fresh liver samples were poceeded with sc/sn RNA-seq detection.