Serine, glycine and one‑carbon metabolism in cancer (Review)

Global untargeted and individual targeted plasma metabolomics of breast cancer recurrence modified by hormone receptors

BACKGROUND

Breast cancer is a heterogeneous and complex etiological disease. Understanding perturbations of circulating metabolites could improve prognosis.

METHODS

We recruited breast cancer patients from Kaohsiung Medical University (KMU) to perform untargeted (case-control design) and targeted (patient cohort) metabolomics analyses in the discovery and validation phases to evaluate interaction effects between clinical factors and plasma metabolites using multivariable Cox proportional hazards model.

RESULTS

In the discovery phase, partial least squares-discriminant analysis (PLS-DA) showed that plasma metabolites were significantly different between recurrent and non-recurrent breast cancer patients. Metabolite set enrichment analysis (MSEA) and metabolomic pathway analysis (MetPA) showed that valine, leucine, and isoleucine degradation was the significant pathway, and volcano plot showed significant ten upregulated and two downregulated metabolites between recurrent and non-recurrent cases. Combined with receiver operating characteristic (ROC) curve and biological significance, creatine, valine, methionine, and mannose were selected for the validation phase. In this patient cohort with 41 new-recurrent vs. 248 non-recurrent breast cancer cases, followed for 720.49 person-years, compared with low level of valine, high valine level was significantly negatively associated with recurrent breast cancer (aHR: 0.36, 95% CI: 0.18-0.72, P = 0.004), especially in ER-negative and PR-negative status. There were interaction effects between valine and ER (Pinteraction = 0.006) as well as PR (Pinteraction = 0.002) on recurrent breast cancer. After Bonferroni correction, stratification effects between valine and hormone receptors were still significant.

CONCLUSION

Our study revealed that plasma metabolites were significantly different between recurrent and non-recurrent patients, proposing therapeutic insights for breast cancer prognosis.

The m6A writer RBM15 drives the growth of triple-negative breast cancer cells through the stimulation of serine and glycine metabolism

N6-adenosine methylation (m6A) is critical for controlling cancer cell growth and tumorigenesis. However, the function and detailed mechanism of how m6A methyltransferases modulate m6A levels on specific targets remain unknown. In the current study, we identified significantly elevated levels of RBM15, an m6A writer, in basal-like breast cancer (BC) patients compared to nonbasal-like BC patients and linked this increase to worse clinical outcomes. Gene expression profiling revealed correlations between RBM15 and serine and glycine metabolic genes, including PHGDH, PSAT1, PSPH, and SHMT2. RBM15 influences m6A levels and, specifically, the m6A levels of serine and glycine metabolic genes via direct binding to target RNA. The effects of RBM15 on cell growth were largely dependent on serine and glycine metabolism. Thus, RBM15 coordinates cancer cell growth through altered serine and glycine metabolism, suggesting that RBM15 is a new therapeutic target in BC.

Role of dietary nutrients and metabolism in colorectal cancer

Colorectal cancer (CRC) is one of the most common malignancies and the leading causes of cancer related deaths worldwide. The development of CRC is driven by a combination of genetic and environmental factors. There is growing evidence that changes in dietary nutrition may modulate the CRC risk, and protective effects on the risk of developing CRC have been advocated for specific nutrients such as glucose, amino acids, lipid, vitamins, micronutrients and prebiotics. Metabolic crosstalk between tumor cells, tumor microenvironment components and intestinal flora further promote proliferation, invasion and metastasis of CRC cells and leads to treatment resistance. This review summarizes the research progress on CRC prevention, pathogenesis, and treatment by dietary supplementation or deficiency of glucose, amino acids, lipids, vitamins, micronutri-ents, and prebiotics, respectively. The roles played by different nutrients and dietary crosstalk in the tumor microenvironment and metabolism are discussed, and nutritional modulation is inspired to be beneficial in the prevention and treatment of CRC.

PDPR Gene Variants Predisposing to Papillary Thyroid Cancer

Background: Papillary thyroid cancer (PTC) is the predominant subtype of thyroid cancer (THCA), and it can cluster in families with an autosomal dominant (AD) inheritance pattern. The aim of this study was to identify novel genes and mechanisms underlying PTC susceptibility. Methods: Our previous investigation of 17 AD PTC families led us to conduct a deeper analysis on one family (Family Q) with whole-genome sequencing data from 3 PTC-affected individuals. In addition, 323 sporadic THCA cases from Avatar data and 12 familial adenomatous polyposis (FAP) individuals with secondary THCA were screened for pyruvate dehydrogenase phosphatase regulatory (PDPR) variants. CRISPR-Cas9 was used to create PDPR-deficient THCA (TPC1) and transformed normal thyroid cell lines (N-Thyori3-1) to study the metabolic consequences of PDPR loss. Results: We found truncating PDPR splice donor variants (NM_017990.4:c.361 + 1G>C) in all affected PTC Family Q members, and another PDPR splice donor variant (NM_017990.4:c.443 + 1G>C) in a sporadic PTC case. In addition, an ultra-rare missense variant was found in an FAP-PTC patient. The PDPR-deficient cells presented with elevated phosphorylation of pyruvate dehydrogenase and altered glucose metabolism, implying that PDPR plays an essential part in regulating glucose metabolism in thyroid cells. Conclusions: Our finding of novel truncating germline variants in PDPR in Family Q and additional cohorts suggests a role for PDPR loss in PTC predisposition. Also, somatic and RNA sequencing from the thyroid carcinoma (Firehouse Legacy) data showed that PDPR gene expression is much lower in THCA tumor tissue compared with matching normal tissue. Thus, PDPR appears to have a loss of function effect on THCA tumorigenesis.

Biomarkers of bipolar disorder based on metabolomics: A systematic review

Bipolar disorder (BD) is a severe affective disorder characterized by recurrent episodes of depression or mania/hypomania, which significantly impair cognitive function, life skills, and social abilities of patients. There is little understanding of the neurobiological mechanisms of BD. The diagnosis of BD is primarily based on clinical assessment and psychiatric examination, highlighting the urgent need for objective markers to facilitate the diagnosis of BD. Metabolomics can be used as a diagnostic tool for disease identification and evaluation. This study summarized the altered metabolites in BD and analyzed aberrant metabolic pathways, which might contribute to the diagnosis of BD. Search of PubMed and Web of science for human BD studies related to metabolism to identify articles published up to November 19, 2022 yielded 987 articles. After screening and applying the inclusion and exclusion criteria, 16 untargeted and 11 targeted metabolomics studies were included. Pathway analysis of the potential differential biometabolic markers was performed using the Kyoto encyclopedia of genes and genomes (KEGG). There were 72 upregulated and 134 downregulated biomarkers in the untargeted metabolomics studies using blood samples. Untargeted metabolomics studies utilizing urine specimens revealed the presence of 78 upregulated and 54 downregulated metabolites. The targeted metabolomics studies revealed abnormalities in the metabolism of glutamate and tryptophan. Enrichment analysis revealed that the differential metabolic pathways were mainly involved in the metabolism of glucose, amino acid and fatty acid. These findings suggested that certain metabolic biomarkers or metabolic biomarker panels might serve as a reference for the diagnosis of BD.

The enzymes of serine synthesis pathway in cancer metastasis

Metastasis, the major cause of cancer mortality, requires cancer cells to reprogram their metabolism to adapt to and thrive in different environments, thereby leaving metastatic cells metabolic characteristics different from their parental cells. Mounting research has revealed that the de novo serine synthesis pathway (SSP), a glycolytic branching pathway that consumes glucose carbons for serine makeup and α-ketoglutarate generation and thus supports the proliferation, survival, and motility of cancer cells, is one such reprogrammed metabolic pathway. During different metastatic cascades, the SSP enzyme proteins or their enzymatic activity are both dynamically altered; manipulating their expression or catalytic activity could effectively prevent the progression of cancer metastasis; and the SSP enzymatic proteins could even conduce to metastasis via their nonenzymatic functions. In this article we overview the SSP dynamics during cancer metastasis and put the focuses on the regulatory role of the SSP in metastasis and the underlying mechanisms that mainly involve cellular anabolism/catabolism, redox balance, and epigenetics, aiming to provide a theoretical basis for the development of therapeutic strategies for targeting metastatic lesions.

Prognostic Biomarkers for Hepatocellular Carcinoma Based on Serine and Glycine Metabolism-related Genes

Background and Aims

Targeted therapy and immunotherapy have emerged as treatment options for hepatocellular carcinoma (HCC) in recent years. The significance of serine and glycine metabolism in various cancers is widely acknowledged. This study aims to investigate their correlation with the prognosis and tumor immune microenvironment (TIME) of HCC.

Methods

Based on the public database, different subtypes were identified by cluster analysis, and the prognostic model was constructed through regression analysis. The gene expression omnibus (GEO) data set was used as the validation set to verify the performance of the model. The survival curve evaluated prognostic ability. CIBERSORT was used to evaluate the level of immune cell infiltration, and maftools analyzed the mutations. DsigDB screened small molecule compounds related to prognostic genes.

Results

HCC was found to have two distinct subtypes. Subsequently, we constructed a risk score prognostic model through regression analysis based on serine and glycine metabolism-related genes (SGMGs). A nomogram was constructed based on risk scores and other clinical factors. HCC patients with a higher risk score showed a poor prognosis, and there were significant differences in immune cell infiltration between the high- and low-risk groups. In addition, three potential drugs associated with prognostic genes, streptozocin, norfloxacin, and hydrocotarnine, were identified.

Conclusions

This study investigated the expression patterns of SGMGs and their relationship with tumor characteristics, resulting in the development of a novel model for predicting the prognosis of HCC patients. The study provides a reference for clinical prognosis prediction and treatment of HCC patients.

Co-treatment with melatonin and ortho-topolin riboside reduces cell viability by altering metabolic profiles in non-small cell lung cancer cells

Lung cancer is a highly prevalent and lethal malignancy worldwide, with non-small cell lung cancer (NSCLC) accounting for 85% of cancer-related deaths. In this study, the effects of co-treatment with melatonin and ortho-topolin riboside (oTR) on the cell viability and alteration of metabolites and transcripts were investigated in NSCLC cells using gas chromatography-mass spectrometry (GC-MS) and next-generation sequencing (NGS). The co-treatment of melatonin and oTR exhibited synergistic effects on the reduction of cell viability and alteration of metabolic and transcriptomic profiles in NSCLC cells. We observed that the co-treatment inhibited glycolytic function and mitochondria respiration, and downregulated glycine, serine and threonine metabolism alongside tyrosine metabolism in NSCLC cells. In the glycine, serine and threonine metabolism pathway, the co-treatment resulted in a significant 8.4-fold reduction in the expression level of the SDS gene, which encodes the enzyme responsible for the breakdown of serine to pyruvate. Moreover, co-treatment decreased the gene expression of TH, DDC, and CYP1A1 in tyrosine metabolism. Additionally, we observed that the co-treatment resulted in a significant 146.9-fold reduction in the expression of the DISC1 gene. The alteration in metabolites and transcript expressions might provide information to explain the cytotoxicity of co-treatment of melatonin and oTR in NSCLC cells. Our study presents insights into the synergistic anticancer effect of the co-treatment of melatonin and oTR, which could be a potential future therapeutic strategy for the treatment of NSCLC patients.

Targeting SHMTs and MTHFDs in cancer: attractive opportunity for anti-tumor strategy

One-carbon metabolism is a universal metabolic process that mediates the transfer of one-carbon units for purine and thymidine synthesis. One-carbon metabolism has been found to be dysregulated in various cancer types due to its role in production of purine and pyrimidine nucleotides, epigenetic program, and redox homeostasis. One-carbon metabolism is composed a network of one-carbon metabolic enzymes. Disturbing the expression and enzymatic activity of these one-carbon metabolic enzymes could lead to fluctuations of metabolites in the tumor microenvironment. Serine hydroxymethyltransferases (SHMTs) and methylenetetrahydrofolate dehydrogenases (MTHFDs) are gradually recognized as important one-carbon metabolic enzymes for regulating tumor initiation and development, representing potential therapeutic targets for anti-tumor strategies. In the review, we primarily focused on the role of SHMTs and MTHFDs in cancer. Several inhibitors targeting MTHFDs and SHMTs have exert its potential to decrease tumor burden and inhibit tumor proliferation, highlighting the potential of targeting one-carbon metabolic enzymes for anti-cancer strategies.

Construction of a Lung Adenocarcinoma Prognostic Model Utilizing Serine and Glycine Metabolism-Related Genes

The objective of this study was to construct a prognostic model by utilizing serine/glycine metabolism-related genes (SGMGs), thus establishing a risk score for lung adenocarcinoma (LUAD). Based on the TCGA-LUAD and SGMG data set, two subtypes with different SGMG expression levels were identified by clustering analysis. Thirteen differential expression genes were used to construct RiskScore by Cox regression. GSE72094 data set was used for validation. The survival characteristics, immune features, and potential benefits of chemotherapy drugs were analyzed for two risk groups. RiskScore was constructed based on the genes ABCC12, RIC3, CYP4B1, SFTPB, CACNA2D2, IGF2BP1, NTSR1, DKK1, CREG2, PITX3, RGS20, FETUB, and IGFBP1. Patients in the low-risk (LR) group exhibited a superior overall survival. In addition, aDCs, iDSs, mast cells, neutrophils, HLA, and type II IFN were more abundant in the LR group with higher IPS scores and lower TIDE scores. In contrast, NK cells, APC coinhibition, and MHC-I were more common in the high-risk (HR) group, which may be more sensitive to chemotherapy drugs such as cisplatin, oxaliplatin, and nilotinib. RiskScore was a promising biomarker that can be used to distinguish LUAD prognosis, immune features, and sensitivity to chemotherapy drugs.

Metabolic Signature of Warburg Effect in Cancer: An Effective and Obligatory Interplay between Nutrient Transporters and Catabolic/Anabolic Pathways to Promote Tumor Growth

Aerobic glycolysis in cancer cells, originally observed by Warburg 100 years ago, which involves the production of lactate as the end product of glucose breakdown even in the presence of adequate oxygen, is the foundation for the current interest in the cancer-cell-specific reprograming of metabolic pathways. The renewed interest in cancer cell metabolism has now gone well beyond the original Warburg effect related to glycolysis to other metabolic pathways that include amino acid metabolism, one-carbon metabolism, the pentose phosphate pathway, nucleotide synthesis, antioxidant machinery, etc. Since glucose and amino acids constitute the primary nutrients that fuel the altered metabolic pathways in cancer cells, the transporters that mediate the transfer of these nutrients and their metabolites not only across the plasma membrane but also across the mitochondrial and lysosomal membranes have become an integral component of the expansion of the Warburg effect. In this review, we focus on the interplay between these transporters and metabolic pathways that facilitates metabolic reprogramming, which has become a hallmark of cancer cells. The beneficial outcome of this recent understanding of the unique metabolic signature surrounding the Warburg effect is the identification of novel drug targets for the development of a new generation of therapeutics to treat cancer.

Causal effects of human serum metabolites on occurrence and progress indicators of chronic kidney disease: a two-sample Mendelian randomization study

Background

Chronic kidney disease (CKD) is often accompanied by alterations in the metabolic profile of the body, yet the causative role of these metabolic changes in the onset of CKD remains a subject of ongoing debate. This study investigates the causative links between metabolites and CKD by leveraging the results of genomewide association study (GWAS) from 486 blood metabolites, employing bulk two-sample Mendelian randomization (MR) analyses. Building on the metabolites that exhibit a causal relationship with CKD, we delve deeper using enrichment analysis to identify the metabolic pathways that may contribute to the development and progression of CKD.

Methods

In conducting the Mendelian randomization analysis, we treated the GWAS data for 486 metabolic traits as exposure variables while using GWAS data for estimated glomerular filtration rate based on serum creatinine (eGFRcrea), microalbuminuria, and the urinary albumin-to-creatinine ratio (UACR) sourced from the CKDGen consortium as the outcome variables. Inverse-variance weighting (IVW) analysis was used to identify metabolites with a causal relationship to outcome. Using Bonferroni correction, metabolites with more robust causal relationships are screened. Additionally, the IVW-positive results were supplemented with the weighted median, MR-Egger, weighted mode, and simple mode. Furthermore, we performed sensitivity analyses using the Cochran Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out (LOO) test. Pathway enrichment analysis was conducted using two databases, KEGG and SMPDB, for eligible metabolites.

Results

During the batch Mendelian randomization (MR) analyses, upon completion of the inverse-variance weighted (IVW) approach, sensitivity analysis, and directional consistency checks, 78 metabolites were found to meet the criteria. The following four metabolites satisfy Bonferroni correction: mannose, N-acetylornithine, glycine, and bilirubin (Z, Z), and mannose is causally related to all outcomes of CKD. By pathway enrichment analysis, we identified eight metabolic pathways that contribute to CKD occurrence and progression.

Conclusion

Based on the present analysis, mannose met Bonferroni correction and had causal associations with CKD, eGFRcrea, microalbuminuria, and UACR. As a potential target for CKD diagnosis and treatment, mannose is believed to play an important role in the occurrence and development of CKD.

Specific changes in amino acid profiles in monocytes of patients with breast, lung, colorectal and ovarian cancers

Introduction

Immunometabolism is essential factor of tumor progression, and tumor-associated macrophages are characterized by substantial changes in their metabolic status. In this study for the first time, we applied targeted amino acid LC-MS/MS analysis to compare amino acid metabolism of circulating monocytes isolated from patients with breast, ovarian, lung, and colorectal cancer.

Methods

Monocyte metabolomics was analyzed by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/ MS) analysis of amino acid extracts. The targeted analysis of 26 amino acids was conducted by LCMS/MS on an Agilent 6460 triple quadrupole mass spectrometer equipped with an electrospray ionization source and an Agilent 1260 II liquid chromatograph.

Results

Comparison of monocytes of cancer patients with monocytes of healthy control individuals demonstrated that in breast cancer most pronounced changes were identified for tryptophan (AUC = 0.76); for ovarian cancer, aminobutyric acid was significantly elevated (AUC= 1.00); for lung cancer significant changes we indented for citrulline (AUC = 0.70). In order to identify key amino acids that are characteristic for monocytes in specific cancer types, we compared each individual cancer with other 3 types of cancer. We found, that aspartic acid and citrulline are specific for monocytes of patients with colorectal cancer (p<0.001, FC = 1.40 and p=0.003, FC = 1.42 respectively). Citrulline, sarcosine and glutamic acid are ovarian cancer-specific amino acids (p = 0.003, FC = 0.78, p = 0.003, FC = 0.62, p = 0.02, FC = 0.78 respectively). Glutamine, methionine and phenylalanine (p = 0.048, FC = 1.39. p = 0.03, FC = 1.27 and p = 0.02, FC = 1.41) are lung cancer-specific amino acids. Ornithine in monocytes demonstrated strong positive correlation (r = 0.63) with lymph node metastasis incidence in breast cancer patients. Methyl histidine and cysteine in monocytes had strong negative correlation with lymph node metastasis in ovarian cancer patients (r = -0.95 and r = -0.95 respectively). Arginine, citrulline and ornithine have strong negative correlation with tumor size (r = -0.78, citrulline) and lymph node metastasis (r = -0.63 for arginine and r = -0.66 for ornithine).

Discussion

These alterations in monocyte amino acid metabolism can reflect the reaction of systemic innate immunity on the growing tumor. Our data indicate that this metabolic programming is cancer specific and can be inhibiting cancer progression. Cancer-specific differences in citrulline, as molecular link between metabolic pathways and epigenetic programing, provide new option for the development and validation of anti-cancer therapies using inhibitors of enzymes catalyzing citrullination.

Exploring the complexities of 1C metabolism: implications in aging and neurodegenerative diseases

The intricate interplay of one-carbon metabolism (OCM) with various cellular processes has garnered substantial attention due to its fundamental implications in several biological processes. OCM serves as a pivotal hub for methyl group donation in vital biochemical reactions, influencing DNA methylation, protein synthesis, and redox balance. In the context of aging, OCM dysregulation can contribute to epigenetic modifications and aberrant redox states, accentuating cellular senescence and age-associated pathologies. Furthermore, OCM's intricate involvement in cancer progression is evident through its capacity to provide essential one-carbon units crucial for nucleotide synthesis and DNA methylation, thereby fueling uncontrolled cell proliferation and tumor development. In neurodegenerative disorders like Alzheimer's and Parkinson's, perturbations in OCM pathways are implicated in the dysregulation of neurotransmitter synthesis and mitochondrial dysfunction, contributing to disease pathophysiology. This review underscores the profound impact of OCM in diverse disease contexts, reinforcing the need for a comprehensive understanding of its molecular complexities to pave the way for targeted therapeutic interventions across inflammation, aging and neurodegenerative disorders.

Advanced progress of spatial metabolomics in head and neck cancer research

Head and neck cancer ranks as the sixth most prevalent malignancy, constituting 5 % of all cancer cases. Its inconspicuous onset often leads to advanced stage diagnoses, prompting the need for early detection to enhance patient prognosis. Currently, research into early diagnostic markers relies predominantly on genomics, proteomics, transcriptomics, and other methods, which, unfortunately, necessitate tumor tissue homogenization, resulting in the loss of temporal and spatial information. Emerging as a recent addition to the omics toolkit, spatial metabolomics stands out. This method conducts in situ mass spectrometry analyses on fresh tissue specimens while effectively preserving their spatiotemporal information. The utilization of spatial metabolomics in life science research offers distinct advantages. This article comprehensively reviews the progress of spatial metabolomics in head and neck cancer research, encompassing insights into cancer cell metabolic reprogramming. Various mass spectrometry imaging techniques, such as secondary ion mass spectrometry, stroma-assisted laser desorption/ionization, and desorption electrospray ionization, enable in situ metabolite analysis for head and neck cancer. Finally, significant emphasis is placed on the application of presently available techniques for early diagnosis, margin assessment, and prognosis of head and neck cancer.

Comparative transcriptome analysis of hepatopancreas reveals the potential mechanism of shrimp resistant to Vibrio parahaemolyticus infection

Vibrio parahaemolyticus carrying a pathogenic plasmid (VPAHPND) is one of the main causative agents of acute hepatopancreatic necrosis disease (AHPND) in shrimp aquaculture. Knowledge about the mechanism of shrimp resistant to VPAHPND is very helpful for developing efficient strategy for breeding AHPND resistant shrimp. In order to learn the mechanism of shrimp resistant to AHPND, comparative transcriptome was applied to analyze the different expressions of genes in the hepatopancreas of shrimp from different families with different resistance to VPAHPND. Through comparative analysis on the hepatopancreas of shrimp from VPAHPND resistant family and susceptible family, we found that differentially expressed genes (DEGs) were mainly involved in immune and metabolic processes. Most of the immune-related genes among DEGs were highly expressed in the hepatopancreas of shrimp from resistant family, involved in recognition of pathogen-associated molecular patterns, phagocytosis and elimination of pathogens, maintenance of reactive oxygen species homeostasis and other immune processes etc. However, most metabolic-related genes were highly expressed in the hepatopancreas of shrimp from susceptible family, involved in metabolism of lipid, vitamin, cofactors, glucose, carbohydrate and serine. Interestingly, when we analyzed the expression of above DEGs in the shrimp after VPAHPND infection, we found that the most of identified immune-related genes remained at high expression levels in the hepatopancreas of shrimp from the VPAHPND resistant family, and most of the identified metabolic-related genes were still at high expression levels in the hepatopancreas of shrimp from the VPAHPND susceptible family. The data suggested that the differential expression of these immune-related and metabolic-related genes in hepatopancreas might contribute to the resistance variations of shrimp to VPAHPND. These results provided valuable information for understanding the resistant mechanism of shrimp to VPAHPND.

Targeting one-carbon metabolism for cancer immunotherapy

BACKGROUND

One-carbon (1C) metabolism is a metabolic network that plays essential roles in biological reactions. In 1C metabolism, a series of nutrients are used to fuel metabolic pathways, including nucleotide metabolism, amino acid metabolism, cellular redox defence and epigenetic maintenance. At present, 1C metabolism is considered the hallmark of cancer. The 1C units obtained from the metabolic pathways increase the proliferation rate of cancer cells. In addition, anticancer drugs, such as methotrexate, which target 1C metabolism, have long been used in the clinic. In terms of immunotherapy, 1C metabolism has been used to explore biomarkers connected with immunotherapy response and immune-related adverse events in patients.

METHODS

We collected numerous literatures to explain the roles of one-carbon metabolism in cancer immunotherapy.

RESULTS

In this review, we focus on the important pathways in 1C metabolism and the function of 1C metabolism enzymes in cancer immunotherapy. Then, we summarise the inhibitors acting on 1C metabolism and their potential application on cancer immunotherapy. Finally, we provide a viewpoint and conclusion regarding the opportunities and challenges of targeting 1C metabolism for cancer immunotherapy in clinical practicability in the future.

CONCLUSION

Targeting one-carbon metabolism is useful for cancer immunotherapy.

Metabolomic Insight into Implications of Induction Chemotherapy Followed by Concomitant Chemoradiotherapy in Locally Advanced Head and Neck Cancer

The present study compares two groups of locally advanced patients with head and neck squamous cell carcinoma (LA-HNSCC) undergoing concurrent chemoradiotherapy (cCHRT), specifically those for whom it is a first-line treatment and those who have previously received induction chemotherapy (iCHT). The crucial question is whether iCHT is a serious burden during subsequent treatment for LA-HNSCC and how iCHT affects the tolerance to cCHRT. Of the 107 LA-HNSCC patients, 54 received cisplatin-based iCHT prior to cCHRT. The patients were clinically monitored at weekly intervals from the day before until the completion of the cCHRT. The 843 blood samples were collected and divided into two aliquots: for laboratory blood tests and for nuclear magnetic resonance (NMR) spectroscopy (a Bruker 400 MHz spectrometer). The NMR metabolites and the clinical parameters from the laboratory blood tests were analyzed using orthogonal partial least squares analysis (OPLS) and the Mann-Whitney U test (MWU). After iCHT, the patients begin cCHRT with significantly (MWU p-value < 0.05) elevated blood serum lipids, betaine, glycine, phosphocholine, and reticulocyte count, as well as significantly lowered NMR inflammatory markers, serine, hematocrit, neutrophile, monocyte, red blood cells, hemoglobin, and CRP. During cCHRT, a significant increase in albumin and psychological distress was observed, as well as a significant decrease in platelet, N-acetyl-cysteine, tyrosine, and phenylalanine, in patients who received iCHT. Importantly, all clinical symptoms (except the decreased platelets) and most metabolic alterations (except for betaine, serine, tyrosine, glucose, and phosphocholine) resolve until the completion of cCHRT. In conclusion, iCHT results in hematological toxicity, altered lipids, and one-carbon metabolism, as well as downregulated inflammation, as observed at the beginning and during cCHRT. However, these complications are temporary, and most of them resolve at the end of the treatment. This suggests that iCHT prior to cCHRT does not pose a significant burden and should be considered as a safe treatment option for LA-HNSCC.

Effect of Air Drying on the Metabolic Profile of Fresh Wild and Artificial Cordyceps sinensis

Fresh and dried Cordyceps sinensis are widely used by the public for medicinal and health purposes. However, the differences between them have not been examined. In this study, fresh wild and artificial C. sinensis (WFC and AFC) were dried to obtain dried wild and artificial C. sinensis (WDC and ADC). Non-targeted GC-MS was used to analyze the metabolic profile characteristics of the four groups of samples. The results showed that air drying significantly altered the composition and content of C. sinensis, mainly in the form of higher abundance of organic acids and derivatives and lower abundance of lipids and lipid-like molecules in fresh C. sinensis. Hierarchical cluster analysis (HCA) and quantitative analyses showed that air drying increased the abundance of Valine, Zinniol, Urocanate, Vulpinic acid, and Uridine 5'-diphosphate, and decreased Xanthotoxol, Vitexin-4-o-glucoside, Val-trp, and Wogonin. These differentially accumulated metabolites (DAMs) were also shown to be potential biomarkers for C. sinensis. KEGG enrichment analysis identified lysine biosynthesis as the most significantly enriched pathway. Annotation of these DAMs to lysine biosynthesis revealed that citrate cycle and pyruvate metabolism entered lysine biosynthesis via 2-oxohlutarate and Homocitrate, respectively, resulting in significant enrichment of L-saccharopine and L-lysine content was significantly higher. Alanine, aspartate, and Glutamate metabolism synthesized more L-aspartate to promote L-lysine synthesis. Thus, high levels of L-lysine result in lysine degradation and pymolysine, which are the most active metabolic pathways during the drying of fresh C. sinensis and indirectly lead to differences in metabolic profiles.

Identifying CD1c as a potential biomarker by the comprehensive exploration of tumor mutational burden and immune infiltration in diffuse large B cell lymphoma

Background

Tumor mutational burden (TMB) is a valuable prognostic biomarker. This study explored the predictive value of TMB and the potential association between TMB and immune infiltration in diffuse large B-cell lymphoma (DLBCL).

Methods

We downloaded the gene expression profile, somatic mutation, and clinical data of DLBCL patients from The Cancer Genome Atlas (TCGA) database. We classified the samples into high-and low-TMB groups to identify differentially expressed genes (DEGs). Functional enrichment analyses were performed to determine the biological functions of the DEGs. We utilized the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to estimate the abundance of 22 immune cells, and the significant difference was determined by the Wilcoxon rank-sum test between the high- and low-TMB group. Hub gene had been screened as the prognostic TMB-related immune biomarker by the combination of the Immunology Database and Analysis Portal (ImmPort) database and the univariate Cox analysis from the Gene Expression Omnibus (GEO) database including six DLBCL datasets. Various database applications such as Tumor Immune Estimation Resource (TIMER), CellMiner, konckTF, and Genotype-Tissue Expression (GTEx) verified the functions of the target gene. Wet assay confirmed the target gene expression at RNA and protein levels in DLBCL tissue and cell samples.

Results

Single nucleotide polymorphism (SNP) occurred more frequently than insertion and deletion, and C > T was the most common single nucleotide variant (SNV) in DLBCL. Survival analysis showed that the high-TMB group conferred poor survival outcomes. A total of 62 DEGs were obtained, and 13 TMB-related immune genes were identified. Univariate Cox analysis results illustrated that CD1c mutation was associated with lower TMB and manifested a satisfactory clinical prognosis by analysis of large samples from the GEO database. In addition, infiltration levels of immune cells in the high-TMB group were lower. Using the TIMER database, we systematically analyzed that the expression of CD1c was positively correlated with B cells, neutrophils, and dendritic cells and negatively correlated with CD8+ T cells, CD4+ T cells, and macrophages. Drug sensitivity showed a significant positive correlation between CD1c expression level and clinical drug sensitivity from the CellMiner database. CREB1, AHR, and TOX were used to comprehensively explore the regulation of CD1c-related transcription factors and signaling pathways by the KnockTF database. We searched the GETx database to compare the mRNA expression levels of CD1c between DLBCL and normal tissues, and the results suggested a significant difference between them. Moreover, wet experiments were conducted to verify the high expression of CD1c in DLBCL at the RNA and protein levels.

Conclusions

Higher TMB correlated with poor survival outcomes and inhibited the immune infiltrates in DLBCL. Our results suggest that CD1c is a TMB-related prognostic biomarker.

HOXD8 suppresses renal cell carcinoma growth by upregulating SHMT1 expression

Amplification of amino acids synthesis is reported to promote tumorigenesis. The serine/glycine biosynthesis pathway is a reversible conversion of serine and glycine catalyzed by cytoplasmic serine hydroxymethyltransferase (SHMT)1 and mitochondrial SHMT2; however, the role of SHTM1 in renal cell carcinoma (RCC) is still unclear. We found that low SHMT1 expression is correlated with poor survival of RCC patients. The in vitro study showed that overexpression of SHMT1 suppressed RCC proliferation and migration. In the mouse tumor model, SHMT1 significantly retarded RCC tumor growth. Furthermore, by gene network analysis, we found several SHMT1-related genes, among which homeobox D8 (HOXD8) was identified as the SHMT1 regulator. Knockdown of HOXD8 decreased SHMT1 expression, resulting in faster RCC growth, and rescued the SHMT1 overexpression-induced cell migration defects. Additionally, ChIP assay found the binding site of HOXD8 to SHMT1 promoter was at the -456~-254 bp region. Taken together, SHMT1 functions as a tumor suppressor in RCC. The transcription factor HOXD8 can promote SHMT1 expression and suppress RCC cell proliferation and migration, which provides new mechanisms of SHMT1 in RCC tumor growth and might be used as a potential therapeutic target candidate for clinical treatment.

T Lymphocyte Metabolic Features and Techniques to Modulate Them

T cells demonstrate high degree of complexity and broad range of functions, which distinguish them from other immune cells. Throughout their lifetime, T lymphocytes experience several functional states: quiescence, activation, proliferation, differentiation, performance of effector and regulatory functions, memory formation, and apoptosis. Metabolism supports all functions of T cells, providing lymphocytes with energy, biosynthetic substrates, and signaling molecules. Therefore, T cells usually restructure their metabolism as they transition from one functional state to another. Strong association between the metabolism and T cell functions implies that the immune response can be controlled by manipulating metabolic processes within T lymphocytes. This review aims to highlight the main metabolic adaptations necessary for the T cell function, as well as the recent progress in techniques to modulate metabolic features of lymphocytes.

Metabolism of pancreatic neuroendocrine tumors: what can omics tell us?

Introduction

Reprogramming of cellular metabolism is now a hallmark of tumorigenesis. In recent years, research on pancreatic neuroendocrine tumors (pNETs) has focused on genetic and epigenetic modifications and related signaling pathways, but few studies have been devoted to characterizing the metabolic profile of these tumors. In this review, we thoroughly investigate the metabolic pathways in pNETs by analyzing the transcriptomic and metabolomic data available in the literature.

Methodology

We retrieved and downloaded gene expression profiles from all publicly available gene set enrichments (GSE43797, GSE73338, and GSE117851) to compare the differences in expressed genes based on both the stage and MEN1 mutational status. In addition, we conducted a systematic review of metabolomic data in NETs.

Results

By combining transcriptomic and metabolomic approaches, we have identified a distinctive metabolism in pNETs compared with controls without pNETs. Our analysis showed dysregulations in the one-carbon, glutathione, and polyamine metabolisms, fatty acid biosynthesis, and branched-chain amino acid catabolism, which supply the tricarboxylic acid cycle. These targets are implicated in pNET cell proliferation and metastasis and could also have a prognostic impact. When analyzing the profiles of patients with or without metastasis, or with or without MEN1 mutation, we observed only a few differences due to the scarcity of published clinical data in the existing research. Consequently, further studies are now necessary to validate our data and investigate these potential targets as biomarkers or therapeutic solutions, with a specific focus on pNETs.

Joint analysis of the metabolomics and transcriptomics uncovers the dysregulated network and develops the diagnostic model of high-risk neuroblastoma

High-risk neuroblastoma (HR-NB) has a significantly lower survival rate compared to low- and intermediate-risk NB (LIR-NB) due to the lack of risk classification diagnostic models and effective therapeutic targets. The present study aims to characterize the differences between neuroblastomas with different risks through transcriptomic and metabolomic, and establish an early diagnostic model for risk classification of neuroblastoma.Plasma samples from 58 HR-NB and 38 LIR-NB patients were used for metabolomics analysis. Meanwhile, NB tissue samples from 32 HR-NB and 23 LIR-NB patients were used for transcriptomics analysis. In particular, integrative metabolomics and transcriptomic analysis was performed between HR-NB and LIR-NB. A total of 44 metabolites (P < 0.05 and fold change > 1.5) were altered, including 12 that increased and 32 that decreased in HR-NB. A total of 1,408 mRNAs (P < 0.05 and |log2(fold change)|> 1) showed significantly altered in HR-NB, of which 1,116 were upregulated and 292 were downregulated. Joint analysis of both omic data identified 4 aberrant pathways (P < 0.05 and impact ≥ 0.5) consisting of glycerolipid metabolism, retinol metabolism, arginine biosynthesis and linoleic acid metabolism. Importantly, a HR-NB risk classification diagnostic model was developed using plasma circulating-free S100A9, CDK2, and UNC5D, with an area under receiver operating characteristic curve of 0.837 where the sensitivity and specificity in the validation set were both 80.0%. This study presents a novel pioneering study demonstrating the metabolomics and transcriptomics profiles of HR-NB. The glycerolipid metabolism, retinol metabolism, arginine biosynthesis and linoleic acid metabolism were altered in HR-NB. The risk classification diagnostic model based on S100A9, CDK2, and UNC5D can be clinically used for HR-NB risk classification.

An update on malignant tumor-related stiff person syndrome spectrum disorders: clinical mechanism, treatment, and outcomes

Stiff person syndrome (SPS) is a rare central nervous system disorder associated with malignancies. In this review, we retrieved information from PubMed, up until August 2023, using various search terms and their combinations, including SPS, stiff person syndrome spectrum disorders (SPSSDs), paraneoplastic, cancer, and malignant tumor. Data from peer-reviewed journals printed in English were organized to explain the possible relationships between different carcinomas and SPSSD subtypes, as well as related autoantigens. From literature searching, it was revealed that breast cancer was the most prevalent carcinoma linked to SPSSDs, followed by lung cancer and lymphoma. Furthermore, classic SPS was the most common SPSSD subtype, followed by stiff limb syndrome and progressive encephalomyelitis with rigidity and myoclonus. GAD65 was the most common autoantigen in patients with cancer and SPSSDs, followed by amphiphysin and GlyR. Patients with cancer subtypes might have multiple SPSSD subtypes, and conversely, patients with SPSSD subtypes might have multiple carcinoma subtypes. The first aim of this review was to highlight the complex nature of the relationships among cancers, autoantigens, and SPSSDs as new information in this field continues to be generated globally. The adoption of an open-minded approach to updating information on new cancer subtypes, autoantigens, and SPSSDs is recommended to renew our database. The second aim of this review was to discuss SPS animal models, which will help us to understand the mechanisms underlying the pathogenesis of SPS. In future, elucidating the relationship among cancers, autoantigens, and SPSSDs is critical for the early prediction of cancer and discovery of new therapeutic modalities.

Identification and dynamics of novel scaffolds against Enterococcus faecium serine hydroxymethyltransferase enzyme: a potential target for antibiotics development

Serine hydroxymethyltransferase enzyme is a significant player in purine, thymidylate, and L-serine biosynthesis and has been tagged as a potential target for cancer, viruses, and parasites. However, this enzyme as an anti-bacterial druggable target has not been explored much. Herein, in this work, different computational chemistry and biophysics techniques were applied to identify potential computational predicted inhibitory molecules against Enterococcus faecium serine hydroxymethyltransferase enzyme. By structure based virtual screening process of ASINEX antibacterial library against the enzyme two main compounds: Top-1_BDC_21204033 and Top-2_BDC_20700155 were reported as best binding molecules. The Top-1_BDC_21204033 and Top-2_BDC_20700155 binding energy value is -9.3 and -8.9 kcal/mol, respectively. The control molecule binding energy score is -6.55 kcal/mol. The mean RMSD of Top-1-BDC_21204033, Top-2-BDC_20700155 and control is 3.7 Å (maximum 5.03 Å), 1.7 Å (maximum 3.05 Å), and 3.84 Å (maximum of 6.7 Å), respectively. During the simulation time, the intermolecular docked conformation and interactions were seen stable despite of few small jumps by the compounds/control, responsible for high RMSD in some frames. The MM/GBSA and MM/PBSA binding free energy of lead Top-2-BDC_20700155 complex is -79.52 and -82.63 kcal/mol, respectively. This complex was seen as the most stable compared to the control. Furthermore, the lead molecules and control showed good druglikeness and pharmacokinetics profile. The lead molecules were non-toxic and non-mutagenic. In short, the compounds are promising in terms of binding to the serine hydroxymethyltransferase enzyme and need to be subjected to experimental studies.Communicated by Ramaswamy H. Sarma.

Advancements in Analyzing Tumor Metabolites through Chemical Derivatization-Based Chromatography

Understanding the metabolic abnormalities of tumors is crucial for early diagnosis, prognosis, and treatment. Accurate identification and quantification of metabolites in biological samples are essential to investigate the relationship between metabolite variations and tumor development. Common techniques like LC-MS and GC-MS face challenges in measuring aberrant metabolites in tumors due to their strong polarity, isomerism, or low ionization efficiency during MS detection. Chemical derivatization of metabolites offers an effective solution to overcome these challenges. This review focuses on the difficulties encountered in analyzing aberrant metabolites in tumors, the principles behind chemical derivatization methods, and the advancements in analyzing tumor metabolites using derivatization-based chromatography. It serves as a comprehensive reference for understanding the analysis and detection of tumor metabolites, particularly those that are highly polar and exhibit low ionization efficiency.

Increased serine synthesis in cumulus cells of young infertile women with diminished ovarian reserve

STUDY QUESTION

What are the differences in gene expression of cumulus cells (CCs) between young women with diminished ovarian reserve (DOR) and those of similar age with normal ovarian reserve (NOR)?

SUMMARY ANSWER

Gene expression and metabolome profiling analysis demonstrate that the de novo serine synthesis pathway (SSP) is increased in the CCs of young women with DOR.

WHAT IS KNOWN ALREADY

The incidence of DOR has risen, tending to present at younger ages. Its mechanisms and aetiologies are still poorly understood. Abnormal metabolism is present in luteinized CCs of patients with DOR. Previous studies have revealed that mitochondrial dysfunction and impaired oxidative phosphorylation in CCs are related to DOR in women of advanced age. The pathogenic mechanisms likely differ between young women with DOR and cases associated with advanced maternal age. Several studies have examined amino acid metabolism in the follicle, with a focus on embryo development, but less information is available about CCs. The physiological significance of de novo serine synthesis in follicles and oocytes remains largely unknown.

STUDY DESIGN, SIZE, DURATION

CC samples were obtained from 107 young infertile women (age <38 years) undergoing ICSI, from July 2017 to June 2019, including 54 patients with DOR and 53 patients with NOR.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Oocyte development data were analysed retrospectively. Comprehensive genome-wide transcriptomics of CCs was performed. Differentially expressed genes (DEGs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to categorize the functions of the DEGs and identify significantly enriched pathways. The transcript and protein levels of key enzymes involved in serine synthesis were verified in additional samples using quantitative real-time PCR (qRT-PCR) (n = 10) and capillary western blotting (n = 36). Targeted metabolomics of amino acids in CC extracts was performed by ultrahigh-performance liquid MS (UHPLC-MS/MS).

MAIN RESULTS AND THE ROLE OF CHANCE

The number of oocytes (2.4 ± 2.2 versus 12.1 ± 5.3) and metaphase II oocytes (2.1 ± 2.0 versus 9.9 ± 4.9) retrieved was significantly decreased in the DOR versus the NOR group, respectively (P < 0.0001). The rates of fertilization (80.7% versus 78.8%), viable embryos (73.7% versus 72.5%), and high-quality embryos (42.8% versus 49.0%) did not differ between the DOR and NOR groups, respectively (P > 0.05). A total of 95 DEGs were found by transcriptome sequencing. GO and KEGG analyses demonstrated that the DEGs were linked to amino acid metabolism and suggested significantly higher activity of the de novo SSP in the CCs of young women with DOR. Further qRT-PCR and capillary western blotting revealed that key enzymes (PHGDH, PSAT1, PSPH, and SHMT2) involved in de novo serine synthesis were upregulated, and UHPLC-MS/MS analysis showed increases in serine and glycine (a downstream product of serine) levels in the CCs of young patients with DOR. Our data clearly demonstrate that the de novo SSP, which diverts 3-phosphoglycerate from glycolysis to serine synthesis, was upregulated in young DOR CCs.

LARGE SCALE DATA

N/A.

LIMITATIONS, REASONS FOR CAUTION

Regarding the reproductive capacity of young patients DOR, the pregnancy outcomes were not analysed. The sample size was limited, and only women undergoing ICSI were examined since this was a prerequisite for the acquisition of CCs, which may cause selection bias. The exact mechanisms by which the SSP in CCs regulates ovarian reserve still require further study.

WIDER IMPLICATIONS OF THE FINDINGS

Our research presents new evidence that alterations of the SSP in CCs of young infertile women are associated with DOR. We believe this is a significant contribution to the field, which should be key for understanding the cause and mechanisms of ovarian hypofunction in young women.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by grants from the Ministry of Science and Technology of China (2018YFC1005001) and National Natural Science Foundation of China (31601197). There were no competing interests.

TRIAL REGISTRATION NUMBER

N/A.

Drivers of de novo Serine/Glycine synthesis in acute leukemia

Cancer cells hijack metabolic pathways in order to provide themselves with building blocks to support their proliferation and survival. Upregulation and addiction to de novo serine/glycine synthesis is an example of metabolic rewiring in cancer cells whereby serine and glycine are synthesised via a side branch of glycolysis. In this review, we focus on upregulation of endogenous serine/glycine production in acute leukemia, namely T-cell acute leukemia (T-ALL) and acute myeloid leukemia (AML). Several genetic lesions directly driving the serine/glycine addiction in acute leukemia have been established. Additionally, indirect regulation of de novo serine/glycine synthesis is observed in acute leukemia.

Serine Metabolic Reprogramming in Tumorigenesis, Tumor Immunity, and Clinical Treatment

Serine has been recently identified as an essential metabolite for oncogenesis, progression, and adaptive immunity. Influenced by many physiologic or tumor environmental factors, the metabolic pathways of serine synthesis, uptake, and usage are heterogeneously reprogrammed and frequently amplified in tumor or tumor-associated cells. The hyperactivation of serine metabolism promotes abnormal cellular nucleotide/protein/lipid synthesis, mitochondrial function, and epigenetic modifications, which drive malignant transformation, unlimited proliferation, metastasis, immunosuppression, and drug resistance of tumor cells. Dietary restriction of serine or phosphoglycerate dehydrogenase depletion mitigates tumor growth and extends the survival of tumor patients. Correspondingly, these findings triggered a boom in the development of novel therapeutic agents targeting serine metabolism. In this study, recent discoveries in the underlying mechanism and cellular function of serine metabolic reprogramming are summarized. The vital role of serine metabolism in oncogenesis, tumor stemness, tumor immunity, and therapeutic resistance is outlined. Finally, some potential tumor therapeutic concepts, strategies, and limitations of targeting the serine metabolic pathway are described in detail. Taken together, this review underscores the importance of serine metabolic reprogramming in tumorigenesis and progression and highlights new opportunities for dietary restriction or selective pharmacologic intervention.

Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity

Metabolic reprogramming in a subpopulation of cancer cells is a hallmark of tumor chemoresistance. However, single-cell metabolic profiling is difficult because of the lack of a method that can simultaneously detect multiple metabolites at the single-cell level. In this study, through hyperspectral stimulated Raman scattering (hSRS) imaging in the carbon-hydrogen (C-H) window and sparsity-driven hyperspectral image decomposition, we demonstrate a high-content hSRS (h2SRS) imaging approach that enables the simultaneous mapping of five major biomolecules, including proteins, carbohydrates, fatty acids, cholesterol, and nucleic acids at the single-cell level. h2SRS imaging of brain and pancreatic cancer cells under chemotherapy revealed acute and adapted chemotherapy-induced metabolic reprogramming and the unique metabolic features of chemoresistance. Our approach is expected to facilitate the discovery of therapeutic targets to combat chemoresistance. This study illustrates a high-content, label-free chemical imaging approach that measures metabolic profiles at the single-cell level and warrants further research on cellular metabolism.

One-carbon metabolizing enzyme ALDH1L1 influences mitochondrial metabolism through 5-aminoimidazole-4-carboxamide ribonucleotide accumulation and serine depletion, contributing to tumor suppression

Tumor cells generally require large amounts of nucleotides, and thus activate de novo purine synthesis (dnPS). In the dnPS reactions, 10-formyltetrahydorofolate (10-fTHF) supplied by one-carbon metabolism is utilized as a formyl group donor. We focused on aldehyde dehydrogenase 1 family member L1 (ALDH1L1), which metabolizes 10-fTHF to tetrahydrofolate and whose expression is often attenuated in hepatocellular carcinoma (HCC). We generated ALDH1L1-expressing HuH-7 cells to perform metabolome analysis and found that intracellular levels of serine were reduced and glycine was increased. In addition, 5-aminoimidazole-4-carboxamide ribonucleotide (ZMP), a dnPS intermediate, accumulated due to the consumption of 10-fTHF by ALDH1L1, which inhibited ZMP formylation. Importantly, ALDH1L1-expressing cells showed reduced ZMP sensitivity and higher mitochondrial activity. The suppression of mitochondrial serine catabolism by ALDH1L1 expression was speculated to be closely related to this phenotype. Gene set enrichment analysis utilizing The Cancer Genome Atlas data revealed that genes related to oxidative phosphorylation were enriched in HCC patients with high ALDH1L1 expression. Moreover, drug sensitivity data analysis demonstrated that HCC cell lines with low expression of ALDH1L1 were sensitive to ZMP and cordycepin, a structural analog of ZMP and AMP. Our study revealed that ZMP and AMP analogs might be effective in the pharmacotherapy of HCC patients with low expression of ALDH1L1.

Serine-associated one-carbon metabolic reprogramming: a new anti-cancer therapeutic strategy

Tumour metabolism is a major focus of cancer research, and metabolic reprogramming is an important feature of malignant tumours. Serine is an important non-essential amino acid, which is a main resource of one-carbon units in tumours. Cancer cells proliferate more than normal cells and require more serine for proliferation. The cancer-related genes that are involved in serine metabolism also show changes corresponding to metabolic alterations. Here, we reviewed the serine-associated one-carbon metabolism and its potential as a target for anti-tumour therapeutic strategies.

Transcriptional regulation of amino acid metabolism by KDM2B, in the context of ncPRC1.1 and in concert with MYC and ATF4

Introduction

KDM2B encodes a JmjC domain-containing histone lysine demethylase, which functions as an oncogene in several types of tumors, including TNBC. This study was initiated to address the cancer relevance of the results of our earlier work, which had shown that overexpression of KDM2B renders mouse embryonic fibroblasts (MEFs) resistant to oxidative stress by regulating antioxidant mechanisms.

Methods

We mainly employed a multi-omics strategy consisting of RNA-Seq, quantitative TMT proteomics, Mass-spectrometry-based global metabolomics, ATAC-Seq and ChIP-seq, to explore the role of KDM2B in the resistance to oxidative stress and intermediary metabolism. These data and data from existing patient datasets were analyzed using bioinformatic tools, including exon-intron-split analysis (EISA), FLUFF and clustering analyses. The main genetic strategy we employed was gene silencing with shRNAs. ROS were measured by flow cytometry, following staining with CellROX and various metabolites were measured with biochemical assays, using commercially available kits. Gene expression was monitored with qRT-PCR and immunoblotting, as indicated.

Results

The knockdown of KDM2B in basal-like breast cancer cell lines lowers the levels of GSH and sensitizes the cells to ROS inducers, GSH targeting molecules, and DUB inhibitors. To address the mechanism of GSH regulation, we knocked down KDM2B in MDA-MB-231 cells and we examined the effects of the knockdown, using a multi-omics strategy. The results showed that KDM2B, functioning in the context of ncPRC1.1, regulates a network of epigenetic and transcription factors, which control a host of metabolic enzymes, including those involved in the SGOC, glutamate, and GSH metabolism. They also showed that KDM2B enhances the chromatin accessibility and expression of MYC and ATF4, and that it binds in concert with MYC and ATF4, the promoters of a large number of transcriptionally active genes, including many, encoding metabolic enzymes. Additionally, MYC and ATF4 binding sites were enriched in genes whose accessibility depends on KDM2B, and analysis of a cohort of TNBCs expressing high or low levels of KDM2B, but similar levels of MYC and ATF4 identified a subset of MYC targets, whose expression correlates with the expression of KDM2B. Further analyses of basal-like TNBCs in the same cohort, revealed that tumors expressing high levels of all three regulators exhibit a distinct metabolic signature that carries a poor prognosis.

Conclusions

The present study links KDM2B, ATF4, and MYC in a transcriptional network that regulates the expression of multiple metabolic enzymes, including those that control the interconnected SGOC, glutamate, and GSH metabolic pathways. The co-occupancy of the promoters of many transcriptionally active genes, by all three factors, the enrichment of MYC binding sites in genes whose chromatin accessibility depends on KDM2B, and the correlation of the levels of KDM2B with the expression of a subset of MYC target genes in tumors that express similar levels of MYC, suggest that KDM2B regulates both the expression and the transcriptional activity of MYC. Importantly, the concerted expression of all three factors also defines a distinct metabolic subset of TNBCs with poor prognosis. Overall, this study identifies novel mechanisms of SGOC regulation, suggests novel KDM2B-dependent metabolic vulnerabilities in TNBC, and provides new insights into the role of KDM2B in the epigenetic regulation of transcription.

Serine signaling governs metabolic homeostasis and health

Serine has functions that are involved in metabolic homeostasis and health in pathological or stressful situations. Notably, the de novo serine synthesis pathway (SSP) plays a vital role in targeted regulation of immune responses, cell proliferation, and lipid/protein metabolism. The presentation of serine residues derived from SSP may be a signal of stress and provide novel insights into the relationship between metabolic homeostasis and diseases. Here, we summarize the current trends in understanding the regulatory mechanisms of serine metabolism, discuss how serine signaling governs metabolic and antistress processes, including oxidative stress, immunity, energy and lipid metabolism, intestinal microbiota, and the neurological system. We present a possible framework by which serine metabolism maintains metabolic homeostasis and treats human diseases.

20-Hydroxyecdysone Confers Antioxidant and Antineoplastic Properties in Human Non-Small Cell Lung Cancer Cells

20-Hydroxyecdysone (20E) is an arthropod hormone which is synthesized by some plants as part of their defense mechanism. In humans, 20E has no hormonal activity but possesses a number of beneficial pharmacological properties including anabolic, adaptogenic, hypoglycemic, and antioxidant properties, as well as cardio-, hepato-, and neuroprotective features. Recent studies have shown that 20E may also possess antineoplastic activity. In the present study, we reveal the anticancer properties of 20E in Non-Small Cell Lung Cancer (NSCLC) cell lines. 20E displayed significant antioxidant capacities and induced the expression of antioxidative stress response genes. The RNA-seq analysis of 20E-treated lung cancer cells revealed the attenuation of genes involved in different metabolic processes. Indeed, 20E suppressed several enzymes of glycolysis and one-carbon metabolism, as well as their key transcriptional regulators-c-Myc and ATF4, respectively. Accordingly, using the SeaHorse energy profiling approach, we observed the inhibition of glycolysis and respiration mediated by 20E treatment. Furthermore, 20E sensibilized lung cancer cells to metabolic inhibitors and markedly suppressed the expression of Cancer Stem Cells (CSCs) markers. Thus, in addition to the known beneficial pharmacological activities of 20E, our data uncovered novel antineoplastic properties of 20E in NSCLC cells.

Targeting serine-glycine-one-carbon metabolism as a vulnerability in cancers

The serine-glycine-one-carbon (SGOC) metabolic pathway is critical for DNA methylation, histone methylation, and redox homeostasis, in addition to protein, lipid, and nucleotide biosynthesis. The SGOC pathway is a crucial metabolic network in tumorigenesis, wherein the outputs are required for cell survival and proliferation and are particularly likely to be co-opted by aggressive cancers. SGOC metabolism provides an integration point in cell metabolism and is of crucial clinical significance. The mechanism of how this network is regulated is the key to understanding tumor heterogeneity and overcoming the potential mechanism of tumor recurrence. Herein, we review the role of SGOC metabolism in cancer by focusing on key enzymes with tumor-promoting functions and important products with physiological significance in tumorigenesis. In addition, we introduce the ways in which cancer cells acquire and use one-carbon unit, and discuss the recently clarified role of SGOC metabolic enzymes in tumorigenesis and development, as well as their relationship with cancer immunotherapy and ferroptosis. The targeting of SGOC metabolism may be a potential therapeutic strategy to improve clinical outcomes in cancers.

The Metabolic Landscape of Breast Cancer and Its Therapeutic Implications

Breast cancer is the most common malignant tumor globally as of 2020 and remains the second leading cause of cancer-related death among female individuals worldwide. Metabolic reprogramming is well recognized as a hallmark of malignancy owing to the rewiring of multiple biological processes, notably, glycolysis, oxidative phosphorylation, pentose phosphate pathway, as well as lipid metabolism, which support the demands for the relentless growth of tumor cells and allows distant metastasis of cancer cells. Breast cancer cells are well documented to reprogram their metabolism via mutations or inactivation of intrinsic factors such as c-Myc, TP53, hypoxia-inducible factor, and the PI3K/AKT/mTOR pathway or crosstalk with the surrounding tumor microenvironments, including hypoxia, extracellular acidification and interaction with immune cells, cancer-associated fibroblasts, and adipocytes. Furthermore, altered metabolism contributes to acquired or inherent therapeutic resistance. Therefore, there is an urgent need to understand the metabolic plasticity underlying breast cancer progression as well as to dictate metabolic reprogramming that accounts for the resistance to standard of care. This review aims to illustrate the altered metabolism in breast cancer and its underlying mechanisms, as well as metabolic interventions in breast cancer treatment, with the intention to provide strategies for developing novel therapeutic treatments for breast cancer.

Targeting Oncometabolites in Peritoneal Cancers: Preclinical Insights and Therapeutic Strategies

Peritoneal cancers present significant clinical challenges with poor prognosis. Understanding the role of cancer cell metabolism and cancer-promoting metabolites in peritoneal cancers can provide new insights into the mechanisms that drive tumor progression and can identify novel therapeutic targets and biomarkers for early detection, prognosis, and treatment response. Cancer cells dynamically reprogram their metabolism to facilitate tumor growth and overcome metabolic stress, with cancer-promoting metabolites such as kynurenines, lactate, and sphingosine-1-phosphate promoting cell proliferation, angiogenesis, and immune evasion. Targeting cancer-promoting metabolites could also lead to the development of effective combinatorial and adjuvant therapies involving metabolic inhibitors for the treatment of peritoneal cancers. With the observed metabolomic heterogeneity in cancer patients, defining peritoneal cancer metabolome and cancer-promoting metabolites holds great promise for improving outcomes for patients with peritoneal tumors and advancing the field of precision cancer medicine. This review provides an overview of the metabolic signatures of peritoneal cancer cells, explores the role of cancer-promoting metabolites as potential therapeutic targets, and discusses the implications for advancing precision cancer medicine in peritoneal cancers.

Amino acid metabolic reprogramming in tumor metastatic colonization

Metastasis is considered as the major cause of cancer death. Cancer cells can be released from primary tumors into the circulation and then colonize in distant organs. How cancer cells acquire the ability to colonize in distant organs has always been the focus of tumor biology. To enable survival and growth in the new environment, metastases commonly reprogram their metabolic states and therefore display different metabolic properties and preferences compared with the primary lesions. For different microenvironments in various colonization sites, cancer cells must transfer to specific metabolic states to colonize in different distant organs, which provides the possibility of evaluating metastasis tendency by tumor metabolic states. Amino acids provide crucial precursors for many biosynthesis and play an essential role in cancer metastasis. Evidence has proved the hyperactivation of several amino acid biosynthetic pathways in metastatic cancer cells, including glutamine, serine, glycine, branched chain amino acids (BCAAs), proline, and asparagine metabolism. The reprogramming of amino acid metabolism can orchestrate energy supply, redox homeostasis, and other metabolism-associated pathways during cancer metastasis. Here, we review the role and function of amino acid metabolic reprogramming in cancer cells colonizing in common metastatic organs, including lung, liver, brain, peritoneum, and bone. In addition, we summarize the current biomarker identification and drug development of cancer metastasis under the amino acid metabolism reprogramming, and discuss the possibility and prospect of targeting organ-specific metastasis for cancer treatment.

Flavonoids attenuate cancer metabolism by modulating Lipid metabolism, amino acids, ketone bodies and redox state mediated by Nrf2

Metabolic reprogramming of cancer cells is a common hallmark of malignant transformation. The preference for aerobic glycolysis over oxidative phosphorylation in tumors is a well-studied phenomenon known as the Warburg effect. Importantly, metabolic transformation of cancer cells also involves alterations in signaling cascades contributing to lipid metabolism, amino acid flux and synthesis, and utilization of ketone bodies. Also, redox regulation interacts with metabolic reprogramming during malignant transformation. Flavonoids, widely distributed phytochemicals in plants, exert various beneficial effects on human health through modulating molecular cascades altered in the pathological cancer phenotype. Recent evidence has identified numerous flavonoids as modulators of critical components of cancer metabolism and associated pathways interacting with metabolic cascades such as redox balance. Flavonoids affect lipid metabolism by regulating fatty acid synthase, redox balance by modulating nuclear factor-erythroid factor 2-related factor 2 (Nrf2) activity, or amino acid flux and synthesis by phosphoglycerate mutase 1. Here, we discuss recent preclinical evidence evaluating the impact of flavonoids on cancer metabolism, focusing on lipid and amino acid metabolic cascades, redox balance, and ketone bodies.

Transcriptome Analysis on Hepatopancreas Reveals the Metabolic Dysregulation Caused by Vibrio parahaemolyticus Infection in Litopenaeus vannamei

Acute hepatopancreas necrosis disease (AHPND) has caused massive deaths of shrimp and has led to huge economic losses in aquaculture. Vibrio parahaemolyticus (VPAHPND) carrying a plasmid encoding binary toxins homologous to the photorhabdus insect-related (Pir) toxins is one of the main pathogens causing this disease. Previous studies have reported many immune-related genes of shrimp in response to this pathogenic bacteria. However, few studies have so far focused on the metabolic changes in Litopenaeus vannamei upon VPAHPND infection. In the present study, comparative transcriptomic analysis was performed on the hepatopancreas of shrimp at different times during VPAHPND infection. Functional analyses on the differentially expressed genes (DEGs) during infection showed that pathways related to glucose, energy and amino acid metabolism, as well as nucleic acid synthesis, were obviously changed in the hepatopancreas after VPAHPND infection. Additionally, three signaling pathways, which could regulate metabolic processes, including HIF-1 signaling pathway, PI3K-Akt signaling pathway and NF-KappaB signaling pathway, also changed significantly. Collectively, these data reveal a close relationship between host metabolism processes and Vibrio infection. The information will enrich our understanding of the interaction mechanism between the shrimp and Vibrio.

Metabolomics Analysis Reveals Novel Targets of Chemosensitizing Polyphenols and Omega-3 Polyunsaturated Fatty Acids in Triple Negative Breast Cancer Cells

Triple negative breast cancer (TNBC) is a subtype of breast cancer with typically poorer outcomes due to its aggressive clinical behavior and lack of targeted treatment options. Currently, treatment is limited to the administration of high-dose chemotherapeutics, which results in significant toxicities and drug resistance. As such, there is a need to de-escalate chemotherapeutic doses in TNBC while also retaining/improving treatment efficacy. Dietary polyphenols and omega-3 polyunsaturated fatty acids (PUFAs) have been demonstrated to have unique properties in experimental models of TNBC, improving the efficacy of doxorubicin and reversing multi-drug resistance. However, the pleiotropic nature of these compounds has caused their mechanisms to remain elusive, preventing the development of more potent mimetics to take advantage of their properties. Using untargeted metabolomics, we identify a diverse set of metabolites/metabolic pathways that are targeted by these compounds following treatment in MDA-MB-231 cells. Furthermore, we demonstrate that these chemosensitizers do not all target the same metabolic processes, but rather organize into distinct clusters based on similarities among metabolic targets. Common themes in metabolic targets included amino acid metabolism (particularly one-carbon and glutamine metabolism) and alterations in fatty acid oxidation. Moreover, doxorubicin treatment alone generally targeted different metabolites/pathways than chemosensitizers. This information provides novel insights into chemosensitization mechanisms in TNBC.

Prognostic Significance of Amino Acid Metabolism-Related Genes in Prostate Cancer Retrieved by Machine Learning

Prostate cancer is among the leading cancers according to both incidence and mortality. Due to the high molecular, morphological and clinical heterogeneity, the course of prostate cancer ranges from slow growth that usually does not require immediate therapeutic intervention to aggressive and fatal disease that spreads quickly. However, currently available biomarkers cannot precisely predict the course of a disease, and novel strategies are needed to guide prostate cancer management. Amino acids serve numerous roles in cancers, among which are energy production, building block reservoirs, maintenance of redox homeostasis, epigenetic regulation, immune system modulation and resistance to therapy. In this article, by using The Cancer Genome Atlas (TCGA) data, we found that the expression of amino acid metabolism-related genes is highly aberrant in prostate cancer, which holds potential to be exploited in biomarker design or in treatment strategies. This change in expression is especially evident for catabolism genes and transporters from the solute carrier family. Furthermore, by using recursive partitioning, we confirmed that the Gleason score is strongly prognostic for progression-free survival. However, the expression of the genes SERINC3 (phosphatidylserine and sphingolipids generation) and CSAD (hypotaurine generation) can refine prognosis for high and low Gleason scores, respectively. Therefore, our results hold potential for novel prostate cancer progression biomarkers.

Application of Machine Learning to Metabolomic Profile Characterization in Glioblastoma Patients Undergoing Concurrent Chemoradiation

We here characterize changes in metabolite patterns in glioblastoma patients undergoing surgery and concurrent chemoradiation using machine learning (ML) algorithms to characterize metabolic changes during different stages of the treatment protocol. We examined 105 plasma specimens (before surgery, 2 days after surgical resection, before starting concurrent chemoradiation, and immediately after chemoradiation) from 36 patients with isocitrate dehydrogenase (IDH) wildtype glioblastoma. Untargeted GC-TOF mass spectrometry-based metabolomics was used given its superiority in identifying and quantitating small metabolites; this yielded 157 structurally identified metabolites. Using Multinomial Logistic Regression (MLR) and GradientBoostingClassifier (GB Classifier), ML models classified specimens based on metabolic changes. The classification performance of these models was evaluated using performance metrics and area under the curve (AUC) scores. Comparing post-radiation to pre-radiation showed increased levels of 15 metabolites: glycine, serine, threonine, oxoproline, 6-deoxyglucose, gluconic acid, glycerol-alpha-phosphate, ethanolamine, propyleneglycol, triethanolamine, xylitol, succinic acid, arachidonic acid, linoleic acid, and fumaric acid. After chemoradiation, a significant decrease was detected in 3-aminopiperidine 2,6-dione. An MLR classification of the treatment phases was performed with 78% accuracy and 75% precision (AUC = 0.89). The alternative GB Classifier algorithm achieved 75% accuracy and 77% precision (AUC = 0.91). Finally, we investigated specific patterns for metabolite changes in highly correlated metabolites. We identified metabolites with characteristic changing patterns between pre-surgery and post-surgery and post-radiation samples. To the best of our knowledge, this is the first study to describe blood metabolic signatures using ML algorithms during different treatment phases in patients with glioblastoma. A larger study is needed to validate the results and the potential application of this algorithm for the characterization of treatment responses.

SFXN3 is Associated with Poor Clinical Outcomes and Sensitivity to the Hypomethylating Therapy in Non-M3 Acute Myeloid Leukemia Patients

BACKGROUND

DNA hypermethylation plays a critical role in the occurrence and progression of acute myeloid leukemia (AML). The mitochondrial serine transporter, SFXN3, is vital for onecarbon metabolism and DNA methylation. However, the impact of SFXN3 on the occurrence and progression of AML has not been reported yet.

OBJECTIVE

In this study, we hypothesized that SFXN3 indicates a poor prognosis and suggested tailored treatment for AML patients.

METHODS

We used GEPIA and TCGA repository data to analyze the expression of SFXN3 and its correlation with survival in AML patients. RT-qPCR was used to detect the SFXN3 level in our enrolled AML patients and volunteers. Additionally, Whole Genome Bisulfite Sequencing (WGBS) was used to detect the genomic methylation level in individuals.

RESULTS

Through the TCGA and GEPIA databases, we found that SFXN3 was enriched in AML patients, predicting shorter survival. Furthermore, we confirmed that SFXN3 was primarily overexpressed in AML patients, especially non-M3 patients, and that high SFXN3 in non-M3 AML patients was found to be associated with poor outcomes and frequent blast cells. Interestingly, non-M3 AML patients with high SFXN3 levels who received hypomethylating therapy showed a higher CR ratio. Finally, we found that SFXN3 could promote DNA methylation at transcription start sites (TSS) in non-M3 AML patients. These sites were found to be clustered in multiple vital cell functions and frequently accompanied by mutations in DNMT3A and NPM1.

CONCLUSION

In conclusion, SXFN3 plays an important role in the progression and hypermethylation in non-M3 AML patients and could be a potential biomarker for indicating a high CR rate for hypomethylating therapy.

Peculiarities of amino acid profile in monocytes in breast cancer

Monocytes are large circulating white blood cells that are the main precursors of tissue macrophages as well as tumor-associated macrophages in the adult body. Different types of monocytes have multidirectional effects on the growth and metastatic spread of cancer cells, both activating and inhibiting these processes. Tumor progression is associated with the triggering of a whole cascade of inflammatory and immune reactions. These pathological processes are associated with changes in the amino acid content of monocytes, which can lead to disruption of their function, in particular their migration, division and maturation. The aim of the work was to profile the amino acids of monocytes, followed by a study of the amino acid composition of monocytes from patients with breast cancer using liquid chromatography with mass spectrometric detection. Significant differences in metabolite levels in monocytes of breast cancer patients and monocytes of healthy donors were found for glycine (p-value = 0.0127), asparagine (p-value = 0.0197), proline (p-value = 0.0159), methionine (p-value = 0.0357), tryptophan (p-value = 0.0028), tyrosine (p-value = 0.0127). In the study, we identified biological networks that could potentially be involved in altering the phenotype of monocytes affected by breast cancer (BC), using bioinformatic analysis of metabolic pathways involving the discovered amino acids. Mathematical models based on amino acid combinations with 100% sensitivity and specificity have been developed. Features of immune system cell metabolism in BC have been identified and potential diagnostic biomarkers have been proposed.

Tracing the electron flow in redox metabolism: The appropriate distribution of electrons is essential to maintain redox balance in cancer cells

Cancer cells are characterized by sustained proliferation, which requires a huge demand of fuels to support energy production and biosynthesis. Energy is produced by the oxidation of the fuels during catabolism, and biosynthesis is achieved by the reduction of smaller units or precursors. Therefore, the oxidation-reduction (redox) reactions in cancer cells are more active compared to those in the normal counterparts. The higher activity of redox metabolism also induces a more severe oxidative stress, raising the question of how cancer cells maintain the redox balance. In this review, we overview the redox metabolism of cancer cells in an electron-tracing view. The electrons are derived from the nutrients in the tumor microenvironment and released during catabolism. Most of the electrons are transferred to NAD(P) system and then directed to four destinations: energy production, ROS generation, reductive biosynthesis and antioxidant system. The appropriate distribution of these electrons achieved by the function of redox regulation network is essential to maintain redox homeostasis in cancer cells. Interfering with the electron distribution and disrupting redox balance by targeting the redox regulation network may provide therapeutic implications for cancer treatment.

Characteristics of gut microbiota and fecal metabolomes in patients with celiac disease in Northwest China

Celiac disease (CD) is an autoimmune small bowel disease. The pattern of gut microbiota is closely related to dietary habits, genetic background, and geographical factors. There is a lack of research on CD-related gut microbiota in China. This study aimed to use 16S rDNA sequencing and metabolomics to analyze the fecal microbial composition and metabolome characteristics in patients diagnosed with CD in Northwest China, and to screen potential biomarkers that could be used for its diagnosis. A significant difference in the gut microbiota composition was observed between the CD and healthy controls groups. At the genus level, the abundance of Streptococcus, Lactobacillus, Veillonella, and Allisonella communities in the CD group were increased (Q < 0.05). Furthermore, the abundance of Ruminococcus, Faecalibacterium, Blautia, Gemmiger, and Anaerostipes community in this group were decreased (Q < 0.05). A total of 222 different fecal metabolites were identified in the two groups, suggesting that CD patients have a one-carbon metabolism defect. Four species of bacteria and six metabolites were selected as potential biomarkers using a random forest model. Correlation analysis showed that changes in the gut microbiota were significantly correlated with changes in fecal metabolite levels. In conclusion, the patterns of distribution of gut microbiota and metabolomics in patients with CD in Northwest China were found to be unique to these individuals. This has opened up a new way to explore potential beneficial effects of supplementing specific nutrients and potential diagnostic and therapeutic targets in the future.

Genome-wide identification of SHMT family genes in cucumber (Cucumis sativus L.) and functional analyses of CsSHMTs in response to hormones and abiotic stresses

Serine hydroxymethyltransferase (SHMT) is a pyridoxal phosphate-dependent enzyme that plays crucial roles in the photorespiration and one-carbon metabolism of plants. In the present research, we conducted a systematic analysis of the SHMT gene family in cucumber (Cucumis sativus L). Results show that a total of 6 SHMT members were identified from the cucumber genome database. CsSHMT1 and CsSHMT2 participate in a fragment duplication event, indicating that CsSHMTs may complete the expansion of family members through fragment duplication. Gene structure analysis found that the number of exons of CsSHMTs ranges from 4 to 15. Members with the same number of exons are classified into the same class in the phylogenetic analysis. Each class reflects its subcellular distribution. Expression and function analysis reveals that CsSHMTs express in a variety of plant tissues, indicating that SHMT gene expression pattern is not organ-specific. qRT-PCR analysis found that CsSHMT3 and CsSHMT5 positively respond to abscisic acid (ABA), and CsSHMT2-6 are induced by indole-3-acetic acid (IAA) and methyl jasmonate (MeJA). Abiotic stress analysis shows that CsSHMT3 is significantly induced by drought and salt stress. These results may provide useful information for further function and evolution analysis of cucumber SHMT genes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03378-x.