Spatial multi-omics characterizes GPR35-relevant lipid metabolism signatures across liver zonation in MASLD

Metabolic dysfunction-associated steatotic liver disease(MASLD)is a metabolic disease that can progress to metabolic dysfunction-associated steatohepatitis(MASH),cirrhosis,and cancer.The zonal distribution of biomolecules in the liver is implicated in mediat-ing the disease progression.Recently,G-protein-coupled receptor 35(GPR35)has been highlighted to play a role in MASLD,but the precise mechanism is not fully understood,particularly,in a liver-zonal manner.Here,we aimed to identify spatially distributed specific genes and metabolites in different liver zonation that are regulated by GPR35 in MASLD,by combining lipid metabolomics,spatial transcriptomics(ST),and spatial metabolomics(SM).We found that GPR35 influenced lipid accumulation,inflammatory and metabolism-related factors in specific regions,notably affecting the anti-inflammation factor ELF4(E74 like E-twenty six(ETS)tran-scription factor 4),lipid homeostasis key factor CIDEA(cell death-inducing DNA fragmentation factor alpha(DFFA)-like effector A),and the injury response-related genes SAA1/2/3(serum amyloid A1/2/3),thereby impacting MASLD progression.Furthermore,SM elucidated specific metabolite distributions across different liver regions,such as C10H11N4O7P(3ʹ,5ʹ-cyclic inosine monophosphate(3ʹ,5ʹ-IMP))for the central vein,and this metabolite significantly decreased in the liver zones of GPR35-deficient mice during MASLD progression.Taken together,GPR35 regulates hepatocyte damage repair,controls inflammation,and prevents MASLD progression by influencing phospholipid homeostasis and gene expression in a zonal manner.

clusterProfiler 4.0:A universal enrichment tool for interpreting omics data

Functional enrichment analysis is pivotal for interpreting highthroughput omics data in life science.It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible.To meet these requirements,we present here an updated version of our popular Bioconductor package,clusterProfiler 4.0.This package has been enhanced considerably compared with its original version published 9 years ago.The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases.It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization.Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists.We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms.

MicrobiotaProcess:A comprehensive R package for deep mining microbiome

The data output from microbiome research is growing at an accelerating rate,yet mining the data quickly and efficiently remains difficult.There is still a lack of an effective data structure to represent and manage data,as well as flexible and composable analysis methods.In response to these two issues,we designed and developed the MicrobiotaProcess package.It provides a comprehensive data structure,MPSE,to better integrate the primary and intermediate data,which improves the integration and exploration of the downstream data.Around this data structure,the downstream analysis tasks are decomposed and a set of functions are designed under a tidy framework.These functions independently perform simple tasks and can be combined to perform complex tasks.