IsoSearch: An Untargeted and Unbiased Metabolite and Lipid Isotopomer Tracing Strategy from HR-LC-MS/MS Datasets

Lipidome isotope labelling of gut microbes (LILGM): A method of discovering endogenous microbial lipids

Lipidomics analysis of gut microbiome has become critical in recent surge of extensive human disease studies that investigate microbiome contributions. However, challenges remain in comprehending the origins of thousands of lipid species produced by the diverse microbes. Here, we proposed the development and utilization of a liquid chromatography-mass spectrometry-based approach, named lipidome isotope labelling of gut microbes (LILGM), which enables confident detection and identification of endogenous gut microbial lipidome via 13C/15N labeling strategy and high-resolution mass spectrometry. Our method leveraged in vitro microbial cultures and stable isotope-labeled 13C and 15N, allowing a reasonable degree of isotope incorporation into microbial lipids over short-term of inoculation. We then systematically detected the mass spectral patterns of 182 labeled lipid species by our in-house data analysis pipeline. Further bioinformatics analyses confidently identified biologically relevant microbial lipids from lipid classes such as diacylglycerols (DGs), fatty acids (FAs), phosphatidylglycerols (PGs), and phosphatidylethanolamines (PEs) that may have profound impacts to human physiology. Our study also demonstrated the application of LILGM by showcasing the confident detection of dysregulated microbial lipids post antibiotic perturbation. The debiased sparse partial correlation analysis provides insights into lipid metabolism intricacies. Overall, our method can provide unambiguous analyses to the endogenous microbial lipids in given biological context, and can also instantly reflect the lipidomic changes of gut microbes in response to environmental factors. We believe our LILGM approach has the potential to provide new body of knowledge by combining promising analytical approaches for sensitive and specific lipid detection to support functional microbiome studies.

A phosphate-sensing organelle regulates phosphate and tissue homeostasis

Inorganic phosphate (Pi) is one of the essential molecules for life. However, little is known about intracellular Pi metabolism and signalling in animal tissues1. Following the observation that chronic Pi starvation causes hyperproliferation in the digestive epithelium of Drosophila melanogaster, we determined that Pi starvation triggers the downregulation of the Pi transporter PXo. In line with Pi starvation, PXo deficiency caused midgut hyperproliferation. Interestingly, immunostaining and ultrastructural analyses showed that PXo specifically marks non-canonical multilamellar organelles (PXo bodies). Further, by Pi imaging with a Förster resonance energy transfer (FRET)-based Pi sensor2, we found that PXo restricts cytosolic Pi levels. PXo bodies require PXo for biogenesis and undergo degradation following Pi starvation. Proteomic and lipidomic characterization of PXo bodies unveiled their distinct feature as an intracellular Pi reserve. Therefore, Pi starvation triggers PXo downregulation and PXo body degradation as a compensatory mechanism to increase cytosolic Pi. Finally, we identified connector of kinase to AP-1 (Cka), a component of the STRIPAK complex and JNK signalling3, as the mediator of PXo knockdown- or Pi starvation-induced hyperproliferation. Altogether, our study uncovers PXo bodies as a critical regulator of cytosolic Pi levels and identifies a Pi-dependent PXo-Cka-JNK signalling cascade controlling tissue homeostasis.

Lipidomics and Transcriptomics Differ Liposarcoma Differentiation Characteristics That Can Be Altered by Pentose Phosphate Pathway Intervention

Liposarcoma (LPS) is a rare and heterogeneous malignancy of adipocytic origin. Well-differentiated liposarcoma (WDLPS) and dedifferentiated liposarcoma (DDLPS) are two of the most common subtypes, showing similar genetic characterizations but distinct biological behaviors and clinical prognosis. Compared to WDLPS, DDLPS is more aggressive and has the potential of metastasis, as the malignant adipocytic tumor's metabolic changes may have taken place during the tumorigenesis of LPSs. Therefore, to investigate the lipid alterations between the two subtypes, high-resolution liquid chromatography tandem mass spectrometry (LC-MS/MS) based untargeted lipidomic analysis was performed onto LPS tissues from 6 WDLPS and 7 DDLPS patients. The lipidomic analysis showed the upregulated phosphatidylcholines and phosphoethanolamines in DDLPS, and the upregulated triglycerides and diglycerides in WDLPS, which might be due to the uncompleted adipocytic dedifferentiation leading to such tumorigenesis. Such a finding was also confirmed by the similarity comparison of two LPS subtypes to the transcriptome of stromal vascular fraction at different differentiation stages. Transcriptomic analysis also demonstrated that metabolic pathways including the pentose phosphate pathway (PPP) were upregulated in WDLPS compared to DDLPS. Therefore, the cell line LPS853 was treated with the PPP inhibitor 6-aminonicotinamide ex vivo and the proliferation and invasion of LPS853 was significantly promoted by PPP inhibition, suggesting the potential role of PPP in the development and differentiation of LPS. In conclusion, this study described the altered lipid profiles of WDLPS and DDLPS for the first time, revealing the different differentiation stages of the two subtypes and providing a potential metabolic target for LPS treatment.

PI3K drives the de novo synthesis of coenzyme A from vitamin B5

In response to hormones and growth factors, the class I phosphoinositide-3-kinase (PI3K) signalling network functions as a major regulator of metabolism and growth, governing cellular nutrient uptake, energy generation, reducing cofactor production and macromolecule biosynthesis¹. Many of the driver mutations in cancer with the highest recurrence, including in receptor tyrosine kinases, Ras, PTEN and PI3K, pathologically activate PI3K signalling^2,3. However, our understanding of the core metabolic program controlled by PI3K is almost certainly incomplete. Here, using mass-spectrometry-based metabolomics and isotope tracing, we show that PI3K signalling stimulates the de novo synthesis of one of the most pivotal metabolic cofactors: coenzyme A (CoA). CoA is the major carrier of activated acyl groups in cells^4,5 and is synthesized from cysteine, ATP and the essential nutrient vitamin B5 (also known as pantothenate)^6,7. We identify pantothenate kinase 2 (PANK2) and PANK4 as substrates of the PI3K effector kinase AKT⁸. Although PANK2 is known to catalyse the rate-determining first step of CoA synthesis, we find that the minimally characterized but highly conserved PANK4⁹ is a rate-limiting suppressor of CoA synthesis through its metabolite phosphatase activity. Phosphorylation of PANK4 by AKT relieves this suppression. Ultimately, the PI3K–PANK4 axis regulates the abundance of acetyl-CoA and other acyl-CoAs, CoA-dependent processes such as lipid metabolism and proliferation. We propose that these regulatory mechanisms coordinate cellular CoA supplies with the demands of hormone/growth-factor-driven or oncogene-driven metabolism and growth.

The PI3K–PANK4 axis regulates coenzyme A synthesis, the abundance of acetyl-CoA, and CoA-dependent processes such as lipid metabolism, and these regulatory mechanisms coordinate cellular CoA supplies with the demands of hormone and growth-factor-driven or oncogene-driven metabolism and growth.

Identification of clinical and molecular features of recurrent serous borderline ovarian tumour

BACKGROUND

Serous borderline ovarian tumour (SBOT) is the most common type of BOT. Fertility sparing surgery (FSS) is an option for patients with SBOT, though it may increase the risk of recurrence. The clinical and molecular features of its recurrence are important and need to be investigated in detail.

METHODS

An internal cohort of 319 patients with SBOT was collected from Aug 1, 2009 to July 31, 2019 from the Obstetrics and Gynecology Hospital of Fudan University in China. An external cohort of 100 patients with SBOT was collected from Aug 1, 2009 to Nov 30, 2019 from the Shandong Provincial Hospital in China. The risk factors for the recurrence were identified by multivariate cox analysis. Several computational methods were tested to establish a prediction tool for recurrence. Whole genome sequencing, RNA-seq, metabolomics and lipidomics were used to understand the molecular characteristics of the recurrence of SBOT.

FINDINGS

Five factors were significantly correlated with SBOT recurrence in a Han population: micropapillary pattern, advanced stage, FSS, microinvasion, and lymph node invasion. A random forest-based online recurrence prediction tool was established and validated using an internal cohort and an independent external cohort for patients with SBOT. The multi-omics analysis on the original SBOT samples revealed that recurrence is related to metabolic regulation of immunological suppression.

INTERPRETATION

Our study identified several important clinical and molecular features of recurrent SBOT. The prediction tool we established could help physicians to estimate the prognosis of patients with SBOT. These findings will contribute to the development of personalised and targeted therapies to improve prognosis.

FUNDING

JL was funded by MOST 2020YFA0803600, 2018YFA0801300, NSFC 32071138, and SKLGE-2118 to Jin Li; JY was funded by the Initial Project for Young and Middle-aged Medical Talents of Wuhan City, Hubei Province ([2014] 41); HH was funded by MOST 2019YFA0801900 and 2020YF1402600 to He Huang; JS was funded by NSFC 22,104,080; CG was funded by Natural Science Foundation of Shanghai 20ZR1408800 and NSFC82171633; BL was funded by Natural Science Foundation of Shanghai 19ZR1406800.

Kendrick Mass Defect Variation to Decipher Isotopic Labeling in Brain Metastases Studied by Mass Spectrometry Imaging

Besides many other applications, isotopic labeling is commonly used to decipher the metabolism of living biological systems. By giving a stable isotopically labeled compound as a substrate, the biological system will use this labeled nutrient as it would with a regular substrate and incorporate stable heavy atoms into new metabolites. Utilizing mass spectrometry, by comparing heavy atom enriched isotopic profiles and naturally occurring ones, it is possible to identify these metabolites and deduce valuable information about metabolism and biochemical pathways. The coupling of this approach with mass spectrometry imaging (MSI) allows one then to obtain 2D maps of metabolisms used by living specimens. As metabolic networks are convoluted, a global overview of the isotopically labeled data set to detect unexpected metabolites is crucial. Unfortunately, due to the complexity of MSI spectra, such untargeted processing approaches are difficult to decipher. In this technical note, we demonstrate the potential of a variation around the Kendrick analysis concept to detect the incorporation of stable heavy atoms into metabolites. The Kendrick analysis uses as a base unit the difference between the mass of the most abundant isotope and the mass of the corresponding stable isotopic tracer (namely, ¹²C and ¹³C). The resulting Kendrick plot offers an alternative method to process the MSI data set with a new perspective allowing for the rapid detection of the ¹³C-enriched metabolites and separating unrelated compounds. This processing method of MS data could therefore be a useful tool to decipher isotopic labeling and study metabolic networks, especially as it does not require advanced computational capabilities.

Characterization and Determination of 13C-Labeled Nonessential Amino Acids in a 13C5-Glutamine Isotope Tracer Experiment with a Mass Spectrometry Strategy Combining Parallel Reaction Monitoring and Multiple Reaction Monitoring

Isotopic tracer, a powerful technique for metabolic pathway analysis, is currently widely applied in metabolic flux analysis. However, the qualitative and quantitative analyses of ¹³C-labeled metabolites pose great challenges, especially in complex biological sample matrices. Here, we present an integrated method for the qualitative and quantitative analyses of various isotopologues and isotopomers of ¹³C-labeled nonessential amino acids (NEAAs) in HepG2 cells incubated with ¹³C₅-glutamine (Gln) based on ultra-high-performance liquid chromatography (UHPLC) coupled with tandem mass spectrometry (MS). First, accurate mass-to-charge (m/z) values of protonated isotopologues and elution time of standards were simultaneously analyzed to characterize ¹³C-labeled NEAAs by high-resolution Orbitrap MS in the parallel reaction monitoring (PRM) mode. Second, isotopologues and isotopomers of ¹³C-labeled NEAAs were investigated in HepG2 cells incubated with ¹³C₅-Gln at different time points. Ultimately, a total of 66 multiple reaction monitoring (MRM) transitions were performed by UHPLC coupled with triple quadrupole MS. Among them, 29 MRM transitions were monitored for pure metabolites (unambiguously identified). The other 37 MRM transitions were monitored for mixtures with exactly identical MRM transitions and retention time. The application of targeted profiling of ¹³C-labeled NEAAs in the dynamic ¹³C-labeling experiment indicated that the concentration-time profiles of NEAAs were different from each other. The concentrations of most ¹³C-labeled Gln, Glu, Pro, and Asp altered after ¹³C₅-Gln incubation, indicating that Gln plays a fundamental role in the biosynthesis of Glu, Pro, and Asp. The proposed PRM-MRM combination mode LC-MS approach is expected to provide valuable insights into analyses of isotope-labeled metabolites in isotope tracer experiments.

Identification of novel inhibitory metabolites and impact verification on growth and protein synthesis in mammalian cells

Mammalian cells consume large amount of nutrients during growth and production. However, endogenous metabolic inefficiencies often prevent cells to fully utilize nutrients to support growth and protein production. Instead, significant fraction of fed nutrients is diverted into extracellular accumulation of waste by-products and metabolites, further inhibiting proliferation and protein synthesis. In this study, an LC-MS/MS based metabolomics pipeline was used to screen Chinese hamster ovary (CHO) extracellular metabolites. Six out of eight identified inhibitory metabolites, caused by the inefficient cell metabolism, were not previously studied in CHO cells: aconitic acid, 2-hydroxyisocaproic acid, methylsuccinic acid, cytidine monophosphate, trigonelline, and n-acetyl putrescine. When supplemented back into a fed-batch culture, significant reduction in cellular growth was observed in the presence of each metabolite and all the identified metabolites were shown to impact the glycosylation of a model secreted antibody, with seven of these also reducing CHO cellular productivity (titer) and all eight inhibiting the formation of mono-galactosylated biantennary (G1F) and biantennary galactosylated (G2F) N-glycans. These inhibitory metabolites further impact the metabolism of cells, leading to a significant reduction in CHO cellular growth and specific productivity in fed-batch culture (maximum reductions of 27.2% and 40.6% respectively). In-depth pathway analysis revealed that these metabolites are produced when cells utilize major energy sources such as glucose and select amino acids (tryptophan, arginine, isoleucine, and leucine) for growth, maintenance, and protein production. Furthermore, these novel inhibitory metabolites were observed to accumulate in multiple CHO cell lines (CHO–K1 and CHO-GS) as well as HEK293 cell line. This study provides a robust and holistic methodology to incorporate global metabolomic analysis into cell culture studies for elucidation and structural verification of novel metabolites that participate in key metabolic pathways to growth, production, and post-translational modification in biopharmaceutical production.

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Mammalian metabolic inefficiencies lead to accumulation of waste by-products.

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Untargeted and targeted metabolomics for identification of novel metabolites.

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Identified six CHO metabolic inhibitors negatively impact growth and titer production.

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Inhibitors were shown to accumulate across different mammalian cell lines.

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A holistic methodology incorporating metabolomics analysis into cell culture studies.

Metabolomics Analysis Discovers Estrogen Altering Cell Proliferation via the Pentose Phosphate Pathway in Infertility Patient Endometria

Estrogen therapy is widely used as a supplementary treatment after hysteroscopy for female infertility patients owing to its protective function that improves endometrial regeneration and menstruation, inhibits recurrent adhesions, and improves subsequent conception rate. The endometrial protective function of such estrogen administration pre-surgery is still controversial. In the current study, 12 infertility patients were enrolled, who were treated with estrogen before hysteroscopy surgery. Using cutting-edge metabolomic analysis, we observed alterations in the pentose phosphate pathway (PPP) intermediates of the patient's endometrial tissues. Furthermore, using Ishikawa endometrial cells, we validated our clinical discovery and identified estrogen-ESR-G6PD-PPP axial function, which promotes estrogen-induced cell proliferation.