Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort.

Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10-8 and 4.3 × 10-7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.

A lipidome landscape of aging in mice.

Understanding the molecular mechanisms of aging is crucial for enhancing healthy longevity. We conducted untargeted lipidomics across 13 biological samples from mice at various life stages (2, 12, 19 and 24 months) to explore the potential link between aging and lipid metabolism, considering sex (male or female) and microbiome (specific pathogen-free or germ-free) dependencies. By analyzing 2,704 molecules from 109 lipid subclasses, we characterized common and tissue-specific lipidome alterations associated with aging. For example, the levels of bis(monoacylglycero)phosphate containing polyunsaturated fatty acids increased in various organs during aging, whereas the levels of other phospholipids containing saturated and monounsaturated fatty acids decreased. In addition, we discovered age-dependent sulfonolipid accumulation, absent in germ-free mice, correlating with Alistipes abundance determined by 16S ribosomal RNA gene amplicon sequencing. In the male kidney, glycolipids such as galactosylceramides, galabiosylceramides (Gal2Cer), trihexosylceramides (Hex3Cer), and mono- and digalactosyldiacylglycerols were detected, with two lipid classes-Gal2Cer and Hex3Cer-being significantly enriched in aged mice. Integrated analysis of the kidney transcriptome revealed uridine diphosphate galactosyltransferase 8A (UGT8a), alkylglycerone phosphate synthase and fatty acyl-coenzyme A reductase 1 as potential enzymes responsible for the male-specific glycolipid biosynthesis in vivo, which would be relevant to sex dependency in kidney diseases. Inhibiting UGT8 reduced the levels of these glycolipids and the expression of inflammatory cytokines in the kidney. Our study provides a valuable resource for clarifying potential links between lipid metabolism and aging.

The phosphorylated pathway of serine biosynthesis affects sperm, embryo, and sporophyte development, and metabolism in Marchantia polymorpha.

Serine metabolism is involved in various biological processes. Here we investigate primary functions of the phosphorylated pathway of serine biosynthesis in a non-vascular plant Marchantia polymorpha by analyzing knockout mutants of MpPGDH encoding 3-phosphoglycerate dehydrogenase in this pathway. Growth phenotypes indicate that serine from the phosphorylated pathway in the dark is crucial for thallus growth. Sperm development requires serine from the phosphorylated pathway, while egg formation does not. Functional MpPGDH in the maternal genome is necessary for embryo and sporophyte development. Under high CO2 where the glycolate pathway of serine biosynthesis is inhibited, suppressed thallus growth of the mutants is not fully recovered by exogenously-supplemented serine, suggesting the importance of serine homeostasis involving the phosphorylated and glycolate pathways. Metabolomic phenotypes indicate that the phosphorylated pathway mainly influences the tricarboxylic acid cycle, the amino acid and nucleotide metabolism, and lipid metabolism. These results indicate the importance of the phosphorylated pathway of serine biosynthesis in the dark, in the development of sperm, embryo, and sporophyte, and metabolism in M. polymorpha.

Using Data-Dependent and -Independent Hybrid Acquisitions for Fast Liquid Chromatography-Based Untargeted Lipidomics.

Untargeted lipidomics using liquid chromatography (LC) coupled with tandem mass spectrometry (MS) is essential for large cohort studies. Using a fast LC gradient of less than 10 min for the rapid screening of lipids decreases the annotation rate, because of the lower coverage of the MS/MS spectra caused by the narrow peak width. A systematic procedure is proposed in this study to achieve a high annotation rate in fast LC-based untargeted lipidomics by integrating data-dependent acquisition (DDA) and sequential window acquisition of all-theoretical mass spectrometry data-independent acquisition (SWATH-DIA) techniques using the updated MS-DIAL program. This strategy uses variable SWATH-DIA methods for quality control (QC) samples, which are a mixture of biological samples that were analyzed multiple times to correct the MS signal drift. In contrast, biological samples are analyzed using DDA to facilitate the structural elucidation of lipids using the pure spectrum to the maximum extent. The workflow is demonstrated using an 8.6 min LC gradient, where the QC samples are analyzed using five different SWATH-DIA methods. The use of both DDA and SWATH-DIA achieves a 1.7-fold annotation coverage from publicly available benchmark data obtained using a fast LC-DDA-MS technique and offers 95.3% lipid coverage, as compared to the benchmark data set from a 25 min LC gradient. This study demonstrates that harmonized improvements in analytical conditions and informatics tools provide a comprehensive lipidome in fast LC-based untargeted lipidomics, not only for large-scale studies but also for small-scale experiments, contributing to both clinical applications and basic biology.

Gut microbial carbohydrate metabolism contributes to insulin resistance.

Insulin resistance is the primary pathophysiology underlying metabolic syndrome and type 2 diabetes1,2. Previous metagenomic studies have described the characteristics of gut microbiota and their roles in metabolizing major nutrients in insulin resistance3-9. In particular, carbohydrate metabolism of commensals has been proposed to contribute up to 10% of the host's overall energy extraction10, thereby playing a role in the pathogenesis of obesity and prediabetes3,4,6. Nevertheless, the underlying mechanism remains unclear. Here we investigate this relationship using a comprehensive multi-omics strategy in humans. We combine unbiased faecal metabolomics with metagenomics, host metabolomics and transcriptomics data to profile the involvement of the microbiome in insulin resistance. These data reveal that faecal carbohydrates, particularly host-accessible monosaccharides, are increased in individuals with insulin resistance and are associated with microbial carbohydrate metabolisms and host inflammatory cytokines. We identify gut bacteria associated with insulin resistance and insulin sensitivity that show a distinct pattern of carbohydrate metabolism, and demonstrate that insulin-sensitivity-associated bacteria ameliorate host phenotypes of insulin resistance in a mouse model. Our study, which provides a comprehensive view of the host-microorganism relationships in insulin resistance, reveals the impact of carbohydrate metabolism by microbiota, suggesting a potential therapeutic target for ameliorating insulin resistance.

Unique features of Entamoeba histolytica glycerophospholipid metabolism; has the E. histolytica lipid metabolism network evolved through gene loss and gain to enable parasitic life cycle adaptation?

Entamoeba histolytica, a protozoan parasite, causes amoebiasis, which is a global public health problem. During the life cycle of this parasite, the properties of the cell membrane are changed markedly. To clarify the mechanism of membrane lipid changes, we exploited state-of-the-art untargeted lipidomic analysis, and atypical features of glycerophospholipids, lysoglycerophospholipids, and sphingolipids were observed compared with human equivalents. Here, we overview an entire E. histolytica glycerophospholipid metabolic pathway based on re-evaluated whole lipidome and genome along with the results of metabolic labeling experiments. We also discuss whether the E. histolytica lipid metabolism network, including the glycerophospholipid metabolic pathway, has unique features necessary for parasitic life cycle adaptation through gene loss and/or gain, and raise important questions involving biochemistry, molecular cell biology, and physiology underlying this network. Answering these questions will advance the understanding of Entamoeba physiology and will provide potential targets to develop new anti-amoebiasis drugs.

Mechanism of rate controllability of water-soluble bifunctional cyclooctadiynes through cation-anion interactions.

Click reactions are used for chemoselective functionalization in many research fields. Despite the utility of small, bioinert azide groups as a counterpart, applications of strain-promoted alkyne-azide cycloaddition (SPAAC) reactions for this purpose are still limited by slow reaction kinetics. Here, we report ion-pair-guided reaction rate enhancement by the use of water-soluble cyclooctadiynes (WS-CODYs) composed of bifunctional strained alkynes and polar side chains. Arrhenius plot analysis revealed that the rate enhancement by WS-CODYs is due to a kinetic salt effect between the polar substituents and the target azide. We demonstrate the utility of these compounds for rapid protein labelling and isoelectric point-dependent labelling.

A liquid chromatography-mass spectrometry-based metabolomics strategy to explore plant metabolic diversity.

Plants are expert chemists producing millions of metabolites, only a fraction of which are known to date. Plant metabolomics explores the rationale for highly diverse metabolites evolved and synthesized by plants. Over two-thirds of modern medicines are somehow inspired and/or derived from plants, making the identification of phytochemicals a means of discovering new medicines to challenge existing and emerging diseases. This chapter introduces our established liquid chromatography-tandem mass spectrometry-based untargeted metabolomics approach centered around discovering specialized metabolites (so-called secondary metabolites) across broad lineages of nonmodel plant species. Detecting hundreds to thousands of metabolite peaks, including assigning chemical identity, makes metabolomics data generation and analysis a very complex process. Various mass spectrometry techniques are currently being developed to approach the comprehensive metabolome. Among them, untargeted metabolomics can provide new biological insights by simultaneously and unbiasedly measuring and analyzing all detected metabolites. We have provided a hands-on modular account for untargeted plant metabolomics, from preparing plant biological samples to data analysis and processing using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The methods described here offer a foundation and expert opinion on plant metabolome analysis.

Guiding the choice of informatics software and tools for lipidomics research applications.

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

Bioinformatics in bioscience and bioengineering: Recent advances, applications, and perspectives.

Recent advances have led to the emergence of highly comprehensive and analytical approaches, such as omics analysis and high-resolution, time-resolved bioimaging analysis. These technologies have made it possible to obtain vast data from a single measurement. Subsequently, large datasets have pioneered the data-driven approach, an alternative to the traditional hypothesis-testing system, for researchers. However, processing, interpreting, and elucidating enormous datasets is no longer possible without computation. Bioinformatics is a field that has developed over long periods, intending to understand biological phenomena using methods collected from information science and statistics, thus solving this proposed research challenge. This review presents the latest methodologies and applications in sequencing, imaging, and mass spectrometry that were developed using bioinformatics. We presented the features of individual techniques and outlines in each part, avoiding the use of complex algorithms and formulas to allow beginning researchers to understand an overview. In the section on sequencing, we focused on comparative genomic, transcriptomic, and bacterial microbiome analyses, which are frequently used as applications of next-generation sequencing. Bioinformatic methods for handling sequence data and case studies were described. In the section on imaging, we introduced the analytical methods and microscopy imaging informatics techniques used in animal cell biology and plant physiology. We introduce informatics technologies for maximizing the value of measured data, including predicting the structure of unknown molecules and untargeted analysis in the section on mass spectrometry. Finally, we discuss the future outlook of this field. We anticipate that this review will assist biologists in using bioinformatics more effectively.

Pleiotropic Roles of Cholesteryl Sulfate during Entamoeba Encystation: Involvement in Cell Rounding and Development of Membrane Impermeability.

Entamoeba histolytica, a protozoan parasite, causes amoebiasis, which is a global public health problem. The major route of infection is oral ingestion of cysts, the only form that is able to transmit to a new host. Cysts are produced by cell differentiation from proliferative trophozoites in a process termed "encystation." During encystation, cell morphology is markedly changed; motile amoeboid cells become rounded, nonmotile cells. Concomitantly, cell components change and significant fluctuations of metabolites occur. Cholesteryl sulfate (CS) is a crucial metabolite for encystation. However, its precise role remains uncertain. To address this issue, we used in vitro culture of Entamoeba invadens as the model system for the E. histolytica encystation study and identified serum-free culture conditions with CS supplementation at concentrations similar to intracellular CS concentrations during natural encystation. Using this culture system, we show that CS exerts pleiotropic effects during Entamoeba encystation, affecting cell rounding and development of membrane impermeability. CS dose dependently induced and maintained encysting cells as spherical maturing cysts with almost no phagocytosis activity. Consequently, the percentage of mature cysts was increased. CS treatment also caused time- and dose-dependent development of membrane impermeability in encysting cells via induction of de novo synthesis of dihydroceramides containing very long N-acyl chains (≥26 carbons). These results indicate that CS-mediated morphological and physiological changes are necessary for the formation of mature cysts and the maintenance of the Entamoeba life cycle. Our findings also reveal important morphological aspects of the process of dormancy and the control of membrane structure. IMPORTANCE Entamoeba histolytica causes a parasitic infectious disease, amoebiasis. Amoebiasis is a global public health problem with a high occurrence of infection and inadequate clinical options. The parasite alternates its form between a proliferative trophozoite and a dormant cyst that enables the parasite to adapt to new environments. The transition stage in which trophozoites differentiate into cysts is termed "encystation." Cholesteryl sulfate is essential for encystation; however, its precise role remains to be determined. Here, we show that cholesteryl sulfate is a multifunctional metabolite exerting pleiotropic roles during Entamoeba encystation, including the rounding of cells and the development of membrane impermeability. Such morphological and physiological changes are required for Entamoeba to produce cysts that are transmissible to a new host, which is essential for maintenance of the Entamoeba life cycle. Our findings are therefore relevant not only to Entamoeba biology but also to general cell and lipid biology.

Computational mass spectrometry accelerates C = C position-resolved untargeted lipidomics using oxygen attachment dissociation.

Mass spectrometry-based untargeted lipidomics has revealed the lipidome atlas of living organisms at the molecular species level. Despite the double bond (C = C) position being a crucial factor in biological system, the C = C defined structures have not yet been characterized comprehensively. Here, we present an approach for C = C position-resolved untargeted lipidomics using a combination of oxygen attachment dissociation and computational mass spectrometry to increase the annotation rate. We validated the accuracy of our platform as per the authentic standards of 85 lipids and the biogenic standards of 52 molecules containing polyunsaturated fatty acids (PUFAs) from the cultured cells fed with various fatty acid-enriched media. By analyzing human and mice-derived samples, we characterized 648 unique lipids with the C = C position-resolved level encompassing 24 lipid subclasses defined by LIPIDMAPS. Our platform also illuminated the unique profiles of tissue-specific lipids containing n-3 and/or n-6 very long-chain PUFAs (carbon [Formula: see text] 28 and double bonds [Formula: see text] 4) in the eye, testis, and brain of the mouse.

Lipidomics and Redox Lipidomics Indicate Early Stage Alcohol-Induced Liver Damage.

Alcoholic fatty liver disease (AFLD) is characterized by lipid accumulation and inflammation and can progress to cirrhosis and cancer in the liver. AFLD diagnosis currently relies on histological analysis of liver biopsies. Early detection permits interventions that would prevent progression to cirrhosis or later stages of the disease. Herein, we have conducted the first comprehensive time-course study of lipids using novel state-of-the art lipidomics methods in plasma and liver in the early stages of a mouse model of AFLD, i.e., Lieber-DeCarli diet model. In ethanol-treated mice, changes in liver tissue included up-regulation of triglycerides (TGs) and oxidized TGs and down-regulation of phosphatidylcholine, lysophosphatidylcholine, and 20-22-carbon-containing lipid-mediator precursors. An increase in oxidized TGs preceded histological signs of early AFLD, i.e., steatosis, with these changes observed in both the liver and plasma. The major lipid classes dysregulated by ethanol play important roles in hepatic inflammation, steatosis, and oxidative damage. Conclusion: Alcohol consumption alters the liver lipidome before overt histological markers of early AFLD. This introduces the exciting possibility that specific lipids may serve as earlier biomarkers of AFLD than those currently being used.

Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective.

The concept of the exposome was introduced over 15 years ago to reflect the important role that the environment exerts on health and disease. While originally viewed as a call-to-arms to develop more comprehensive exposure assessment methods applicable at the individual level and throughout the life course, the scope of the exposome has now expanded to include the associated biological response. In order to explore these concepts, a workshop was hosted by the Gunma University Initiative for Advanced Research (GIAR, Japan) to discuss the scope of exposomics from an international and multidisciplinary perspective. This Global Perspective is a summary of the discussions with emphasis on (1) top-down, bottom-up, and functional approaches to exposomics, (2) the need for integration and standardization of LC- and GC-based high-resolution mass spectrometry methods for untargeted exposome analyses, (3) the design of an exposomics study, (4) the requirement for open science workflows including mass spectral libraries and public databases, (5) the necessity for large investments in mass spectrometry infrastructure in order to sequence the exposome, and (6) the role of the exposome in precision medicine and nutrition to create personalized environmental exposure profiles. Recommendations are made on key issues to encourage continued advancement and cooperation in exposomics.

Metabolomics and complementary techniques to investigate the plant phytochemical cosmos.

Covering: up to 2021Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and are speculated to possess novel bioactive properties. In addition to their role in plant physiology, these metabolites are also relevant as existing and next-generation medicine candidates. Elucidation of the plant metabolite diversity is thus valuable for the successful exploitation of natural resources for humankind. Herein, we present a comprehensive review on recent metabolomics approaches to illuminate molecular networks in plants, including chemical isolation and enzymatic production as well as the modern metabolomics approaches such as stable isotope labeling, ultrahigh-resolution mass spectrometry, metabolome imaging (spatial metabolomics), single-cell analysis, cheminformatics, and computational mass spectrometry. Mass spectrometry-based strategies to characterize plant metabolomes through metabolite identification and annotation are described in detail. We also highlight the use of phytochemical genomics to mine genes associated with specialized metabolites' biosynthesis. Understanding the metabolic diversity through biotechnological advances is fundamental to elucidate the functions of the plant-derived specialized metabolome.

Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment.

Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.

Global profiling of gut microbiota-associated lipid metabolites in antibiotic-treated mice by LC-MS/MS-based analyses.

We describe a protocol for identifying bacteria-derived lipid metabolites produced in the guts using antibiotic-treated mice, liquid chromatography tandem mass spectrometry-based lipidomics, and feature-based molecular spectrum networking (FBMN). Untargeted lipidomics using the MS-DIAL 4 program provides information on known and unknown complex lipid molecules. The FBMN technique clusters similar MS2 spectra, facilitating the identification of bacterial lipids. Targeted analysis was used as a complementary method to cover oxylipins. Here, we provide details for targeted and untargeted analyses. For complete details on the use and execution of this protocol, please refer to Yasuda et al. (2020).

OS-PCA: Orthogonal Smoothed Principal Component Analysis Applied to Metabolome Data.

Principal component analysis (PCA) has been widely used in metabolomics. However, it is not always possible to detect phenotype-associated principal component (PC) scores. Previously, we proposed a smoothed PCA for samples acquired with a time course or rank order, but hypothesis testing to select significant metabolite candidates was not possible. Here, we modified the smoothed PCA as an orthogonal smoothed PCA (OS-PCA) so that statistical hypothesis testing in OS-PC loadings could be performed with the same PC projections provided by the smoothed PCA. Statistical hypothesis testing is especially useful in metabolomics because biological interpretations are made based on statistically significant metabolites. We applied the OS-PCA method to two real metabolome datasets, one for metabolic turnover analysis and the other for evaluating the taste of Japanese green tea. The OS-PCA successfully extracted similar PC scores as the smoothed PCA; these scores reflected the expected phenotypes. The significant metabolites that were selected using statistical hypothesis testing of OS-PC loading facilitated biological interpretations that were consistent with the results of our previous study. Our results suggest that OS-PCA combined with statistical hypothesis testing of OS-PC loading is a useful method for the analysis of metabolome data.

Stage-Specific De Novo Synthesis of Very-Long-Chain Dihydroceramides Confers Dormancy to Entamoeba Parasites.

Amoebiasis is a parasitic disease caused by Entamoeba histolytica infection and is a serious public health problem worldwide due to ill-prepared preventive measures as well as its high morbidity and mortality rates. Amoebiasis transmission is solely mediated by cysts. Cysts are produced by the differentiation of proliferative trophozoites in a process termed "encystation." Entamoeba encystation is a fundamental cell differentiation process and proceeds with substantial changes in cell metabolites, components, and morphology, which occur sequentially in an orchestrated manner. Lipids are plausibly among these metabolites that function as key factors for encystation. However, a comprehensive lipid analysis has not been reported, and the involved lipid metabolic pathways remain largely unknown. Here, we exploited the state-of-the-art untargeted lipidomics and characterized 339 molecules of 17 lipid subclasses. Of these, dihydroceramide (Cer-NDS) was found to be among the most induced lipid species during encystation. Notably, in encysting cells, amounts of Cer-NDS containing very long N-acyl chains (≥26 carbon) were more than 30-fold induced as the terminal product of a de novo metabolic pathway. We also identified three ceramide synthase genes responsible for producing the very-long-chain Cer-NDS molecules. These genes were upregulated during encystation. Furthermore, these ceramide species were shown to be indispensable for generating membrane impermeability, a prerequisite for becoming dormant cyst that shows resistance to environmental assault inside and outside the host for transmission. Hence, the lipid subclass of Cer-NDS plays a crucial role for Entamoeba cell differentiation and morphogenesis by alternating the membrane properties.IMPORTANCEEntamoeba is a protozoan parasite that thrives in its niche by alternating its two forms between a proliferative trophozoite and dormant cyst. Cysts are the only form able to transmit to a new host and are differentiated from trophozoites in a process termed "encystation." During Entamoeba encystation, cell metabolites, components, and morphology drastically change, which occur sequentially in an orchestrated manner. Lipids are plausibly among these metabolites. However, the involved lipid species and their metabolic pathways remain largely unknown. Here, we identified dihydroceramides (Cer-NDSs) containing very long N-acyl chains (C26 to C30) as a key metabolite for Entamoeba encystation by our state-of-the-art untargeted lipidomics. We also showed that these Cer-NDSs are critical to generate the membrane impermeability, a prerequisite for this parasite to show dormancy as a cyst that repels substances and prevents water loss. Hence, ceramide metabolism is essential for Entamoeba to maintain the parasitic lifestyle.