Modelling of SHMT1 riboregulation predicts dynamic changes of serine and glycine levels across cellular compartments

Mechanism and Therapeutic Progress of One-Carbon Metabolic Key Enzyme: Serine Hydroxymethyltransferase 2 in Cancer

Serine hydroxymethyltransferase 2 (SHMT2) is a crucial mitochondrial enzyme in 1-carbon (1C) metabolism. It catalyzes the conversion of serine to glycine, generating 1C units essential for purine and pyrimidine synthesis, thereby supporting DNA replication and repair. Abnormally high expression is associated with malignant progression and treatment tolerance in various cancers. This review systematically summarizes the functions of SHMT2 in different types of cancer, underscoring on its roles in metabolism, immune microenvironment, and key signaling pathways (PI3K/AKT/mTOR, JAK-STAT, etc.) and outlines its epigenetic regulation and posttranslational modification mechanisms. Compared with the existing research, we focused on the latest regulatory mechanisms of SHMT2 and its potential in cancer treatment, such as the development and application of small-molecule inhibitors (SHIN2 and AGF347).

catGRANULE 2.0: accurate predictions of liquid-liquid phase separating proteins at single amino acid resolution

Liquid-liquid phase separation (LLPS) enables the formation of membraneless organelles, essential for cellular organization and implicated in diseases. We introduce catGRANULE 2.0 ROBOT, an algorithm integrating physicochemical properties and AlphaFold-derived structural features to predict LLPS at single-amino-acid resolution. The method achieves high performance and reliably evaluates mutation effects on LLPS propensity, providing detailed predictions of how specific mutations enhance or inhibit phase separation. Supported by experimental validations, including microscopy data, it predicts LLPS across diverse organisms and cellular compartments, offering valuable insights into LLPS mechanisms and mutational impacts. The tool is freely available at https://tools.tartaglialab.com/catgranule2 and https://doi.org/10.5281/zenodo.14205831 .

Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate

Primary aldosteronism (PA), characterized by autonomous aldosterone overproduction, is a major cause of secondary hypertension with significant cardiovascular complications. Current treatments mainly focus on symptom management rather than addressing underlying mechanisms. This study aims to discover novel therapeutic targets for PA using integrated bioinformatics and experimental validation approaches. We employed a systematic approach combining: gene identification through transcriptome-wide association studies (TWAS); causal inference using summary data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) analyses; additional analyses included phenome-wide association analysis, enrichment analysis, protein-protein interaction (PPI) networks, drug repurposing, molecular docking and clinical validation through aldosterone-producing adenomas (APAs) tissue. Through systematic screening and prioritization, we identified 163 PA-associated genes, of which seven emerged as potential drug targets: CEP104, HIP1, TONSL, ZNF100, SHMT1, and two long non-coding RNAs (AC006369.2 and MRPL23-AS1). SHMT1 was identified as the most promising target, showing significantly elevated expression in APAs compared to adjacent non-tumorous tissues. Drug repurposing analysis identified four potential SHMT1-targeting compounds (Mimosine, Pemetrexed, Leucovorin, and Irinotecan), supported by molecular docking studies. The integration of multiple bioinformatics methods and experimental validation successfully identified novel drug targets for hyperaldosteronism. SHMT1, in particular, represents a promising candidate for future therapeutic development. These findings provide new opportunities for developing causative treatments for PA, though further clinical validation is warranted.

Genetic architecture of cerebrospinal fluid and brain metabolite levels and the genetic colocalization of metabolites with human traits

Brain metabolism perturbation can contribute to traits and diseases. We conducted a genome-wide association study for cerebrospinal fluid (CSF) and brain metabolite levels, identifying 205 independent associations (47.3% new signals, containing 11 new loci) for 139 CSF metabolites, and 32 independent associations (43.8% new signals, containing 4 new loci) for 31 brain metabolites. Of these, 96.9% (CSF) and 71.4% (brain) of the new signals belonged to previously analyzed metabolites in blood or urine. We integrated the metabolite quantitative trait loci (MQTLs) with 23 neurological, psychiatric and common human traits and diseases through colocalization to identify metabolites and biological processes implicated in these phenotypes. Combining CSF and brain, we identified 71 metabolite-trait associations, such as glycerophosphocholines with Alzheimer's disease, O-sulfo-L-tyrosine with Parkinson's disease, glycine, xanthine with waist-to-hip ratio and ergothioneine with inflammatory bowel disease. Our study expanded the knowledge of MQTLs in the central nervous system, providing insights into human traits.

Elucidation of the Role of SHMT2 in L-Serine Homeostasis in Hypoxic Hepa1-6 Cells

Hypoxia is a characteristic feature of malignancy; however, its effect on metabolism remains unclear. In this study, Hepa1-6 cells were cultured under hypoxic conditions and their metabolites were analyzed. Elevated levels of L-serine along with increased glycolytic activity are prominent features of hypoxia. Transcriptome sequencing revealed the downregulation of genes involved in L-serine synthesis and metabolism, which was confirmed by PCR analysis and comparison with public databases. Further experimental evidence indicates that the accumulation of L-serine under hypoxic conditions is attributable not only to enhanced glycolysis but also to a reduction in the catabolism of L-serine mediated by serine hydroxymethyltransferase 2 (SHMT2).

Structure-based mechanism of riboregulation of the metabolic enzyme SHMT1

RNA can directly control protein activity in a process called riboregulation; only a few mechanisms of riboregulation have been described in detail, none of which have been characterized on structural grounds. Here, we present a comprehensive structural, functional, and phylogenetic analysis of riboregulation of cytosolic serine hydroxymethyltransferase (SHMT1), the enzyme interconverting serine and glycine in one-carbon metabolism. We have determined the cryoelectron microscopy (cryo-EM) structure of human SHMT1 in its free- and RNA-bound states, and we show that the RNA modulator competes with polyglutamylated folates and acts as an allosteric switch, selectively altering the enzyme's reactivity vs. serine. In addition, we identify the tetrameric assembly and a flap structural motif as key structural elements necessary for binding of RNA to eukaryotic SHMT1. The results presented here suggest that riboregulation may have played a role in evolution of eukaryotic SHMT1 and in compartmentalization of one-carbon metabolism. Our findings provide insights for RNA-based therapeutic strategies targeting this cancer-linked metabolic pathway.

RNA-binding proteins in cardiovascular biology and disease: the beat goes on

Cardiac development and function are becoming increasingly well understood from different angles, including signalling, transcriptional and epigenetic mechanisms. By contrast, the importance of the post-transcriptional landscape of cardiac biology largely remains to be uncovered, building on the foundation of a few existing paradigms. The discovery during the past decade of hundreds of additional RNA-binding proteins in mammalian cells and organs, including the heart, is expected to accelerate progress and has raised intriguing possibilities for better understanding the intricacies of cardiac development, metabolism and adaptive alterations. In this Review, we discuss the progress and new concepts on RNA-binding proteins and RNA biology and appraise them in the context of common cardiovascular clinical conditions, from cell and organ-wide perspectives. We also discuss how a better understanding of cardiac RNA-binding proteins can fill crucial knowledge gaps in cardiology and might pave the way to developing better treatments to reduce cardiovascular morbidity and mortality.

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.

Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts

BACKGROUND

Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways.

METHODS

We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed.

RESULTS

We identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism.

CONCLUSION

Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.

Mechanisms of folate metabolism-related substances affecting Staphylococcus aureus infection

Staphylococcus aureus (S. aureus) is one of the critical clinical pathogens which can cause multiple diseases ranging from skin infections to fatal sepsis. S. aureus is generally considered to be an extracellular pathogen. However, more and more evidence has shown that S. aureus can survive inside various cells. Folate plays an essential role in multiple life activities, including the conversion of serine and glycine, the remethylation of homocysteine to methionine, and the de novo synthesis of purine /dTMP, et al. More and more studies reported that S. aureus intracellular infection requires the involvement of folate metabolism. This review focused on the mechanisms of folate metabolism and related substances affecting S. aureus infection. Loss of tetrahydrofolic acid (THF)-dependent dTMP directly inhibits the nucleotide synthesis pathway of the S. aureus due to pabA deficiency. Besides, trimethoprim-sulfamethoxazole (TMP/SMX), a potent antibiotic that treats S. aureus infections, interferes in the process of the folate mechanism and leads to the production of thymidine-dependent small-colony variants (TD-SCVs). In addition, S. aureus is resistant to lysostaphin in the presence of serine hydroxymethyltransferase (SHMT). We provide new insights for understanding the molecular pathogenesis of S. aureus infection.

News from around the RNA world: new avenues in RNA biology, biotechnology and therapeutics from the 2022 SIBBM meeting

Since the formalization of the Central Dogma of molecular biology, the relevance of RNA in modulating the flow of information from DNA to proteins has been clear. More recently, the discovery of a vast set of non-coding transcripts involved in crucial aspects of cellular biology has renewed the enthusiasm of the RNA community. Moreover, the remarkable impact of RNA therapies in facing the COVID19 pandemics has bolstered interest in the translational opportunities provided by this incredible molecule. For all these reasons, the Italian Society of Biophysics and Molecular Biology (SIBBM) decided to dedicate its 17th yearly meeting, held in June 2022 in Rome, to the many fascinating aspects of RNA biology. More than thirty national and international speakers covered the properties, modes of action and applications of RNA, from its role in the control of development and cell differentiation to its involvement in disease. Here, we summarize the scientific content of the conference, highlighting the take-home message of each presentation, and we stress the directions the community is currently exploring to push forward our comprehension of the RNA World 3.0.

Prediction of Time Series Gene Expression and Structural Analysis of Gene Regulatory Networks Using Recurrent Neural Networks

Methods for time series prediction and classification of gene regulatory networks (GRNs) from gene expression data have been treated separately so far. The recent emergence of attention-based recurrent neural network (RNN) models boosted the interpretability of RNN parameters, making them appealing for the understanding of gene interactions. In this work, we generated synthetic time series gene expression data from a range of archetypal GRNs and we relied on a dual attention RNN to predict the gene temporal dynamics. We show that the prediction is extremely accurate for GRNs with different architectures. Next, we focused on the attention mechanism of the RNN and, using tools from graph theory, we found that its graph properties allow one to hierarchically distinguish different architectures of the GRN. We show that the GRN responded differently to the addition of noise in the prediction by the RNN and we related the noise response to the analysis of the attention mechanism. In conclusion, this work provides a way to understand and exploit the attention mechanism of RNNs and it paves the way to RNN-based methods for time series prediction and inference of GRNs from gene expression data.

Cytosolic localization and in vitro assembly of human de novo thymidylate synthesis complex

De novo thymidylate synthesis is a crucial pathway for normal and cancer cells. Deoxythymidine monophosphate (dTMP) is synthesized by the combined action of three enzymes: serine hydroxymethyltransferase (SHMT1), dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), with the latter two being targets of widely used chemotherapeutics such as antifolates and 5‐fluorouracil. These proteins translocate to the nucleus after SUMOylation and are suggested to assemble in this compartment into the thymidylate synthesis complex. We report the intracellular dynamics of the complex in cancer cells by an in situ proximity ligation assay, showing that it is also detected in the cytoplasm. This result indicates that the role of the thymidylate synthesis complex assembly may go beyond dTMP synthesis. We have successfully assembled the dTMP synthesis complex in vitro, employing tetrameric SHMT1 and a bifunctional chimeric enzyme comprising human thymidylate synthase and dihydrofolate reductase. We show that the SHMT1 tetrameric state is required for efficient complex assembly, indicating that this aggregation state is evolutionarily selected in eukaryotes to optimize protein–protein interactions. Lastly, our results regarding the activity of the complete thymidylate cycle in vitro may provide a useful tool with respect to developing drugs targeting the entire complex instead of the individual components.