Characterisation of hepatic lipid signature distributed across the liver zonation using mass spectrometry imaging

Spatial lipidomics reveals zone-specific hepatic lipid alteration and remodeling in metabolic dysfunction-associated steatohepatitis

Alteration in lipid metabolism plays a pivotal role in developing metabolic dysfunction-associated steatohepatitis (MASH). However, our understanding of alteration in lipid metabolism across liver zonation in MASH remains limited. Within this study, we investigated MASH-associated zone-specific lipid metabolism in a diet and chemical-induced MASH mouse model. Spatial lipidomics using mass spectrometry imaging in a MASH mouse model revealed 130 lipids from various classes altered across liver zonation and exhibited zone-specific lipid signatures in MASH. Triacylglycerols, diacylglycerols, sphingolipids and ceramides showed distinct zone-specific changes and re-distribution from pericentral to periportal localization in MASH. Saturated and monounsaturated fatty acids (FA) were the primary FA composition of increased lipids in MASH, while polyunsaturated FAs were the major FA composition of decreased lipids. We observed elevated fibrosis in the periportal region, which could be the result of observed metabolic alteration across zonation. Our study provides valuable insights into zone-specific hepatic lipid metabolism and demonstrates the significance of spatial lipidomics in understanding liver lipid metabolism. Identifying unique lipid distribution patterns may offer valuable insights into the pathophysiology of MASH and facilitate the discovery of diagnostic markers associated with liver zonation.

The Effects of Long-Term High Fat and/or High Sugar Feeding on Sources of Postprandial Hepatic Glycogen and Triglyceride Synthesis in Mice

BACKGROUND

In MASLD (formerly called NAFLD) mouse models, oversupply of dietary fat and sugar is more lipogenic than either nutrient alone. Fatty acids suppress de novo lipogenesis (DNL) from sugars, while DNL inhibits fatty acid oxidation. How such factors interact to impact hepatic triglyceride levels are incompletely understood.

METHODS

Using deuterated water, we measured DNL in mice fed 18-weeks with standard chow (SC), SC supplemented with 55/45-fructose/glucose in the drinking water at 30% (w/v) (HS), high-fat chow (HF), and HF with HS supplementation (HFHS). Liver glycogen levels and its sources were also measured. For HS and HFHS mice, pentose phosphate (PP) fluxes and fructose contributions to DNL and glycogen were measured using [U-13C]fructose.

RESULTS

The lipogenic diets caused significantly higher liver triglyceride levels compared to SC. DNL rates were suppressed in HF compared to SC and were partially restored in HFHS but supplied a minority of the additional triglyceride in HFHS compared to HF. Fructose contributed a significantly greater fraction of newly synthesized saturated fatty acids compared to oleic acid in both HS and HFHS. Glycogen levels were not different between diets, but significant differences in Direct and Indirect pathway contributions to glycogen synthesis were found. PP fluxes were similar in HS and HFHS mice and were insufficient to account for DNL reducing equivalents.

CONCLUSIONS

Despite amplifying the lipogenic effects of fat, the fact that sugar-activated DNL per se barely contributes suggests that its role is likely more relevant in the inhibition of fatty acid oxidation. Fructose promotes lipogenesis of saturated over unsaturated fatty acids and contributes to maintenance of glycogen levels. PP fluxes associated with sugar conversion to fat account for a minor fraction of DNL reducing equivalents.

DESI-MSI-guided exploration of metabolic-phenotypic relationships reveals a correlation between PI 38:3 and proliferating cells in clear cell renal cell carcinoma via single-section co-registration of multimodal imaging

A workflow has been evaluated that utilizes a single tissue section to obtain spatially co-registered, molecular, and phenotypical information suitable for AI-enabled image analysis. Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was used to obtain molecular information followed by conventional histological staining and immunolabelling. The impact of varying DESI-MSI conditions (e.g., heated transfer line (HTL) temperature, scan rate, acquisition time) on the detection of small molecules and lipids as well as on tissue integrity crucial for integration into typical clinical pathology workflows was assessed in human kidney. Increasing the heated transfer line temperature from 150 to 450 °C resulted in a 1.8-fold enhancement in lipid signal at a scan rate of 10 scans/s, while preserving histological features. Moreover, increasing the acquisition speed to 30 scans/s yielded superior lipid signal when compared to 10 scans/s at 150 °C. Tissue morphology and protein epitopes remained intact allowing full histological assessment and further multiplex phenotyping by immunofluorescence (mIF) and immunohistochemistry (mIHC) of the same section. The successful integration of the workflow incorporating DESI-MSI, H&E, and immunolabelling on a single tissue section revealed an accumulation of ascorbic acid in regions of focal chronic inflammatory cell infiltrate within non-cancerous kidney tissue. Additionally, a strong positive correlation between PI 38:3 and proliferating cells was observed in clear cell renal cell carcinoma (ccRCC) showing the utility of this approach in uncovering molecular associations in disease pathology.

Deciphering metabolic crosstalk in context: lessons from inflammatory diseases

Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single-cell omics techniques, flow cytometry-based methods (Met-Flow, single-cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease-relevant contexts.

Digital pathology and spatial omics in steatohepatitis: Clinical applications and discovery potentials

Steatohepatitis with diverse etiologies is the most common histological manifestation in patients with liver disease. However, there are currently no specific histopathological features pathognomonic for metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, or metabolic dysfunction-associated steatotic liver disease with increased alcohol intake. Digitizing traditional pathology slides has created an emerging field of digital pathology, allowing for easier access, storage, sharing, and analysis of whole-slide images. Artificial intelligence (AI) algorithms have been developed for whole-slide images to enhance the accuracy and speed of the histological interpretation of steatohepatitis and are currently employed in biomarker development. Spatial biology is a novel field that enables investigators to map gene and protein expression within a specific region of interest on liver histological sections, examine disease heterogeneity within tissues, and understand the relationship between molecular changes and distinct tissue morphology. Here, we review the utility of digital pathology (using linear and nonlinear microscopy) augmented with AI analysis to improve the accuracy of histological interpretation. We will also discuss the spatial omics landscape with special emphasis on the strengths and limitations of established spatial transcriptomics and proteomics technologies and their application in steatohepatitis. We then highlight the power of multimodal integration of digital pathology augmented by machine learning (ML)algorithms with spatial biology. The review concludes with a discussion of the current gaps in knowledge, the limitations and premises of these tools and technologies, and the areas of future research.

Recent Analytical Methodologies in Lipid Analysis

Lipids represent a large group of biomolecules that are responsible for various functions in organisms. Diseases such as diabetes, chronic inflammation, neurological disorders, or neurodegenerative and cardiovascular diseases can be caused by lipid imbalance. Due to the different stereochemical properties and composition of fatty acyl groups of molecules in most lipid classes, quantification of lipids and development of lipidomic analytical techniques are problematic. Identification of different lipid species from complex matrices is difficult, and therefore individual analytical steps, which include extraction, separation, and detection of lipids, must be chosen properly. This review critically documents recent strategies for lipid analysis from sample pretreatment to instrumental analysis and data interpretation published in the last five years (2019 to 2023). The advantages and disadvantages of various extraction methods are covered. The instrumental analysis step comprises methods for lipid identification and quantification. Mass spectrometry (MS) is the most used technique in lipid analysis, which can be performed by direct infusion MS approach or in combination with suitable separation techniques such as liquid chromatography or gas chromatography. Special attention is also given to the correct evaluation and interpretation of the data obtained from the lipid analyses. Only accurate, precise, robust and reliable analytical strategies are able to bring complex and useful lipidomic information, which may contribute to clarification of some diseases at the molecular level, and may be used as putative biomarkers and/or therapeutic targets.

Compartmentalization, cooperation, and communication: The 3Cs of Hepatocyte zonation

The unique architecture of the liver allows for spatial compartmentalization of its functions, also known as liver zonation. In contrast to organelles and cells, this compartment is devoid of a surrounding membrane, rendering traditional biochemical tools ineffective for studying liver zonation. Recent advancements in tissue imaging and single-cell technologies have provided new insights into the complexity of tissue organization, rich cellular composition, and the gradients that shape zonation. Hepatocyte gene expression profiles and metabolic programs differ based on their location. Non-parenchymal cells further support hepatocytes from different zones through local secretion of factors that instruct hepatocyte activities. Collectively, these elements form a cohesive and dynamic network of cell-cell interactions that vary across space, time, and disease states. This review will examine the cell biology of hepatocytes in vivo, presenting the latest discoveries and emerging principles that govern tissue-level and sub-cellular compartmentalization.

Loss of Carnitine Palmitoyltransferase 1a Reduces Docosahexaenoic Acid-Containing Phospholipids and Drives Sexually Dimorphic Liver Disease in Mice

Background and Aims

Genome and epigenome wide association studies identified variants in carnitine palmitoyltransferase 1a (CPT1a) that associate with lipid traits. The goal of this study was to determine the impact by which liver-specific CPT1a deletion impacts hepatic lipid metabolism.

Approach and Results

Six-to-eight-week old male and female liver-specific knockout (LKO) and littermate controls were placed on a low-fat or high-fat diet (HFD; 60% kcal fat) for 15 weeks. Mice were necropsied after a 16 hour fast, and tissues were collected for lipidomics, matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI), kinome analysis, RNA-sequencing, and protein expression by immunoblotting. Female LKO mice had increased serum alanine aminotransferase (ALT) levels which were associated with greater deposition of hepatic lipids, while male mice were not affected by CPT1a deletion relative to male control mice. Mice with CPT1a deletion had reductions in DHA-containing phospholipids at the expense of monounsaturated fatty acids (MUFA)-containing phospholipids in both whole liver and at the level of the lipid droplet (LD). Male and female LKO mice increased RNA levels of genes involved in LD lipolysis ( Plin2 , Cidec , G0S2 ) and in polyunsaturated fatty acid (PUFA) metabolism ( Elovl5, Fads1, Elovl2 ), while only female LKO mice increased genes involved in inflammation ( Ly6d, Mmp12, Cxcl2 ). Kinase profiling showed decreased protein kinase A (PKA) activity, which coincided with increased PLIN2, PLIN5, and G0S2 protein levels and decreased triglyceride hydrolysis in LKO mice.

Conclusions

Liver-specific deletion of CPT1a promotes sexually dimorphic steatotic liver disease (SLD) in mice, and here we have identified new mechanisms by which females are protected from HFD-induced liver injury.

Graphical Summary

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Tissue analysis, which is essential to histology and is considered the benchmark for the diagnosis and prognosis of many illnesses, including cancer, is significant. During surgery, the surgical margin of the tumor is assessed using the labor-intensive, challenging, and commonly subjective technique known as frozen section histopathology. In the biopsy section, large numbers of molecules can now be visualized at once (ion images) following recent developments in [MSI] mass spectrometry imaging under atmospheric conditions. This is vastly superior to and different from the single optical tissue image processing used in traditional histopathology. This review article will focus on the advancement of desorption electrospray ionization mass spectrometry imaging [DESI-MSI] technique, which is label-free and requires little to no sample preparation. Since the proportion of molecular species in normal and abnormal tissues is different, DESI-MSI can capture ion images of the distributions of lipids and metabolites on biopsy sections, which can provide rich diagnostic information. This is not a systematic review but a summary of well-known, cutting-edge and recent DESI-MSI applications in cancer research between 2018 and 2023.