Metabolomic profiling of rare cell populations isolated by flow cytometry from tissues

BMAL1 drives muscle repair through control of hypoxic NAD+ regeneration in satellite cells

The process of tissue regeneration occurs in a developmentally timed manner, yet the role of circadian timing is not understood. Here, we identify a role for the adult muscle stem cell (MuSC)-autonomous clock in the control of muscle regeneration following acute ischemic injury. We observed greater muscle repair capacity following injury during the active/wake period as compared with the inactive/rest period in mice, and loss of Bmal1 within MuSCs leads to impaired muscle regeneration. We demonstrate that Bmal1 loss in MuSCs leads to reduced activated MuSC number at day 3 postinjury, indicating a failure to properly expand the myogenic precursor pool. In cultured primary myoblasts, we observed that loss of Bmal1 impairs cell proliferation in hypoxia (a condition that occurs in the first 1-3 d following tissue injury in vivo), as well as subsequent myofiber differentiation. Loss of Bmal1 in both cultured myoblasts and in vivo activated MuSCs leads to reduced glycolysis and premature activation of prodifferentiation gene transcription and epigenetic remodeling. Finally, hypoxic cell proliferation and myofiber formation in Bmal1-deficient myoblasts are restored by increasing cytosolic NAD+ Together, we identify the MuSC clock as a pivotal regulator of oxygen-dependent myoblast cell fate and muscle repair through the control of the NAD+-driven response to injury.

New horizons in the stormy sea of multimodal single-cell data integration

While measurements of RNA expression have dominated the world of single-cell analyses, new single-cell techniques increasingly allow collection of different data modalities, measuring different molecules, structural connections, and intermolecular interactions. Integrating the resulting multimodal single-cell datasets is a new bioinformatics challenge. Equally important, it is a new experimental design challenge for the bench scientist, who is not only choosing from a myriad of techniques for each data modality but also faces new challenges in experimental design. The ultimate goal is to design, execute, and analyze multimodal single-cell experiments that are more than just descriptive but enable the learning of new causal and mechanistic biology. This objective requires strict consideration of the goals behind the analysis, which might range from mapping the heterogeneity of a cellular population to assembling system-wide causal networks that can further our understanding of cellular functions and eventually lead to models of tissues and organs. We review steps and challenges toward this goal. Single-cell transcriptomics is now a mature technology, and methods to measure proteins, lipids, small-molecule metabolites, and other molecular phenotypes at the single-cell level are rapidly developing. Integrating these single-cell readouts so that each cell has measurements of multiple types of data, e.g., transcriptomes, proteomes, and metabolomes, is expected to allow identification of highly specific cellular subpopulations and to provide the basis for inferring causal biological mechanisms.

Multilayer omics analysis reveals a non-classical retinoic acid signaling axis that regulates hematopoietic stem cell identity

Hematopoietic stem cells (HSCs) rely on complex regulatory networks to preserve stemness. Due to the scarcity of HSCs, technical challenges have limited our insights into the interplay between metabolites, transcription, and the epigenome. In this study, we generated low-input metabolomics, transcriptomics, chromatin accessibility, and chromatin immunoprecipitation data, revealing distinct metabolic hubs that are enriched in HSCs and their downstream multipotent progenitors. Mechanistically, we uncover a non-classical retinoic acid (RA) signaling axis that regulates HSC function. We show that HSCs rely on Cyp26b1, an enzyme conventionally considered to limit RA effects in the cell. In contrast to the traditional view, we demonstrate that Cyp26b1 is indispensable for production of the active metabolite 4-oxo-RA. Further, RA receptor beta (Rarb) is required for complete transmission of 4-oxo-RA-mediated signaling to maintain stem cells. Our findings emphasize that a single metabolite controls stem cell fate by instructing epigenetic and transcriptional attributes.

Aspartate availability limits hematopoietic stem cell function during hematopoietic regeneration

The electron transport chain promotes aspartate synthesis, which is required for cancer cell proliferation. However, it is unclear whether aspartate is limiting in normal stem cells. We found that mouse hematopoietic stem cells (HSCs) depend entirely on cell-autonomous aspartate synthesis, which increases upon HSC activation. Overexpression of the glutamate/aspartate transporter, Glast, or deletion of glutamic-oxaloacetic transaminase 1 (Got1) each increased aspartate levels in HSCs/progenitor cells and increased the function of HSCs but not colony-forming progenitors. Conversely, deletion of Got2 reduced aspartate levels and the function of HSCs but not colony-forming progenitors. Deletion of Got1 and Got2 eliminated HSCs. Isotope tracing showed aspartate was used to synthesize asparagine and purines. Both contributed to increased HSC function as deletion of asparagine synthetase or treatment with 6-mercaptopurine attenuated the increased function of GLAST-overexpressing HSCs. HSC function is thus limited by aspartate, purine, and asparagine availability during hematopoietic regeneration.

The requirement for pyruvate dehydrogenase in leukemogenesis depends on cell lineage

Cancer cells are metabolically similar to their corresponding normal tissues. Differences between cancers and normal tissues may reflect reprogramming during transformation or maintenance of the metabolism of the specific normal cell type that originated the cancer. Here, we compare glucose metabolism in hematopoiesis and leukemia. Thymus T cell progenitors were glucose avid and oxidized more glucose in the tricarboxylic acid cycle through pyruvate dehydrogenase (PDH) as compared with other hematopoietic cells. PDH deletion decreased double-positive T cell progenitor cells but had no effect on hematopoietic stem cells, myeloid progenitors, or other hematopoietic cells. PDH deletion blocked the development of Pten-deficient T cell leukemia, but not the development of a Pten-deficient myeloid neoplasm. Therefore, the requirement for PDH in leukemia reflected the metabolism of the normal cell of origin independently of the driver genetic lesion. PDH was required to prevent pyruvate accumulation and maintain glutathione levels and redox homeostasis.

Identifying Cell-Type-Specific Metabolic Signatures Using Transcriptome and Proteome Analyses

Studies in various tissues have revealed a central role of metabolic pathways in regulating adult stem cell function in tissue regeneration and tumor initiation. The unique metabolic dependences or preferences of adult stem cells, therefore, are emerging as a new category of therapeutic target. Recently, advanced methods including high-resolution metabolomics, proteomics, and transcriptomics have been developed to address the growing interest in stem cell metabolism. A practical framework integrating the omics analyses is needed to systematically perform metabolic characterization in a cell-type-specific manner. Here, we leverage recent advances in transcriptomics and proteomics research to identify cell-type-specific metabolic features by reconstructing cell identity using genes and the encoded enzymes involved in major metabolic pathways. We provide protocols for cell isolation, transcriptome and proteome analyses, and metabolite profiling and measurement. The workflow for mapping cell-type-specific metabolic signatures presented here, although initially developed for intestinal crypt cells, can be easily implemented for cell populations in other tissues, and is highly compatible with most public datasets. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Intestinal crypt isolation and cell population purification Basic Protocol 2: Transcriptome analyses for cell-type-specific metabolic gene expression Basic Protocol 3: Proteome analyses for cell-type-specific metabolic enzyme levels Basic Protocol 4: Metabolite profiling and measurement.

The limitless applications of single-cell metabolomics

Single-cell metabolomics (SCM) is currently one of the most powerful tools for performing high-throughput metabolic analysis at the cellular level. The power of single-cell metabolomics to determine the metabolic profiles of individual cells makes it very suitable for decoding cell heterogeneity. SCM bears great potential in cell type identification and differentiation within cell colonies. With the development of various equipment and techniques, SCM analysis has become possible for a wide range of biological samples. Many fields have incorporated this cutting-edge analytic tool to generate fruitful findings. This review article pays close attention to the prevalent techniques utilized in SCM and the exciting new findings and applications developed by studies in phytology, neurology, and oncology using SCM.

Simultaneous 3-Nitrophenylhydrazine Derivatization Strategy of Carbonyl, Carboxyl and Phosphoryl Submetabolome for LC-MS/MS-Based Targeted Metabolomics with Improved Sensitivity and Coverage

Metabolomics is a powerful and essential technology for profiling metabolic phenotypes and exploring metabolic reprogramming, which enables the identification of biomarkers and provides mechanistic insights into physiology and disease. However, its applications are still limited by the technical challenges particularly in its detection sensitivity for the analysis of biological samples with limited amount, necessitating the development of highly sensitive approaches. Here, we developed a highly sensitive liquid chromatography tandem mass spectrometry method based on a 3-nitrophenylhydrazine (3-NPH) derivatization strategy that simultaneously targets carbonyl, carboxyl, and phosphoryl groups for targeted metabolomic analysis (HSD^ccp-TM) in biological samples. By testing 130 endogenous metabolites including organic acids, amino acids, carbohydrates, nucleotides, carnitines, and vitamins, we showed that the derivatization strategy resulted in significantly improved detection sensitivity and chromatographic separation capability. Metabolic profiling of merely 60 oocytes and 5000 hematopoietic stem cells primarily isolated from mice demonstrated that this method enabled routine metabolomic analysis in trace amounts of biospecimens. Moreover, the derivatization strategy bypassed the tediousness of inferring the MS fragmentation patterns and simplified the complexity of monitoring ion pairs of metabolites, which greatly facilitated the metabolic flux analysis (MFA) for glycolysis, the tricarboxylic acid (TCA) cycle, and pentose phosphate pathway (PPP) in cell cultures. In summary, the novel 3-NPH derivatization-based method with high sensitivity, good chromatographic separation, and broad coverage showed great potential in promoting metabolomics and MFA, especially in trace amounts of biospecimens.

Metabolomics in cancer research and emerging applications in clinical oncology

Cancer has myriad effects on metabolism that include both rewiring of intracellular metabolism to enable cancer cells to proliferate inappropriately and adapt to the tumor microenvironment, and changes in normal tissue metabolism. With the recognition that fluorodeoxyglucose-positron emission tomography imaging is an important tool for the management of many cancers, other metabolites in biological samples have been in the spotlight for cancer diagnosis, monitoring, and therapy. Metabolomics is the global analysis of small molecule metabolites that like other -omics technologies can provide critical information about the cancer state that are otherwise not apparent. Here, the authors review how cancer and cancer therapies interact with metabolism at the cellular and systemic levels. An overview of metabolomics is provided with a focus on currently available technologies and how they have been applied in the clinical and translational research setting. The authors also discuss how metabolomics could be further leveraged in the future to improve the management of patients with cancer.

Challenges in Studying Stem Cell Metabolism

The expanding field of stem cell metabolism has been supported by technical advances in metabolite profiling and novel functional analyses. While use of these methodologies has been fruitful, many challenges are posed by the intricacies of culturing stem cells in vitro, along with the distinctive scarcity of adult tissue stem cells and the complexities of their niches in vivo. This review provides an examination of the methodologies used to characterize stem cell metabolism, highlighting their utility while placing a sharper focus on their limitations and hurdles the field needs to overcome for the optimal study of stem cell metabolic networks.

Hematopoietic stem cell (HSC) divisional memory: The journey of mitochondrial metabolism through HSC division

Hematopoietic stem cells (HSCs) are characterized by their ability to produce all cells of the blood and immune system and have been used for transplantation for decades. Although the regenerative potential of HSCs is high, their self-renewal potential is limited. HSC functions are inversely correlated with their divisional history. Recent advances in our understanding of the regulation of HSCs through cell division suggest that HSCs may never replicate into identical self, but rather replicate into progeny that gradually lose functionality at each round of division. HSC division is accompanied by major transcriptional and metabolic changes. In this perspective, the possibility that mitochondrial metabolism confers HSC division memory and programs HSCs for extinction is discussed.