Biology subjects

Novoa, E.

Publications and source records attributed to Novoa, E..

3 recordsLinked to original sources

bioRxiv2026

Harmonized nucleoside mass spectrometry enables reproducible cross-platform RNA modification quantification

RNA modification analysis by LC-MS/MS is central to epitranscriptomics, yet quantitative comparison across laboratories and instrument platforms remains poorly standardized. Here, we performed a community-driven benchmarking study during the first Human RNome Project workshop to systematically evaluate cross-platform reproducibility of ribonucleoside mass spectrometry workflows. Using the same analytical column and gradient, standardized RNA samples, and shared reagents, we compared nucleoside quantification across quadrupole, time-of-flight, and orbitrap-based LC-MS platforms employing distinct acquisition strategies. While chromatographic separation was highly reproducible across systems, nucleoside-specific MS response behavior differed substantially between platforms and limited direct comparability of relative signal intensities. These response differences varied across analytes and concentration ranges, demonstrating that harmonized chromatography alone is insufficient for transferable quantitative analysis. Stable isotope-labeled internal standard (SILIS) normalization substantially reduced platform-and method-dependent response and improved agreement for most evaluated modifications. External calibration improved agreement between qTOF and Orbitrap workflows for a subset of modifications but did not fully resolve residual intersystem differences. Based on these findings, we establish benchmark-derived recommendations for harmonized relative and absolute RNA modification quantification, including guidance for calibration design, quality control, and data reporting. Together, this work provides a methodological framework for reproducible nucleoside LC-MS/MS workflows and establishes a foundation for large-scale comparative epitranscriptomic studies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/739095v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@6e4e98org.highwire.dtl.DTLVardef@1ea13beorg.highwire.dtl.DTLVardef@b65858org.highwire.dtl.DTLVardef@1623337_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

Inhibition of p107 alleviates liver steatosis by reducing de novo fatty acid synthesis.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by excessive hepatic lipid accumulation driven by increased de novo lipogenesis (DNL) and impaired lipid oxidation. p107, a member of the retinoblastoma (Rb) family, extensively studied in the context of cell cycle regulation and adipocyte differentiation recently has been identified as a metabolic regulator controlling thermogenic activity. However, its role in hepatic lipid homeostasis remains poorly understood. Here, we identify the cell cycle regulator p107 as a key modulator of hepatic lipid metabolism. p107 expression is increased in patients with MASLD and correlates with disease severity. In mouse models, global and liver-specific p107 deficiency protect against high-fat diet-induced steatosis without affecting body weight. This is associated with reduced expression of lipogenic enzymes including fatty acid synthase (FASN), and enhanced mitochondrial oxidative pathways. Conversely, hepatic restoration of p107 reversed these effects and promoted lipid accumulation and endoplasmic reticulum stress. Consistent with this in human hepatocytes, p107 silencing reduces lipid accumulation, decreases DNL and enhances mitochondrial respiration, whereas p107 overexpression induces the opposite phenotype. Notably, FASN knockdown attenuates the pro-steatotic effects of p107, indicating that it is a critical downstream mediator of p107. Together, these findings establish p107 as a physiological regulator of hepatic lipid metabolism, with its dysregulation contributing to the development of MASLD.

physiology↗

bioRxiv2019

Integrative analyses of the RNA modification machinery reveal tissue- and cancer-specific signatures

BackgroundRNA modifications play central roles in cellular fate and differentiation. These features have placed the epitranscriptome in the forefront of developmental biology and cancer research. However, the machinery responsible for placing, removing and recognizing more than 170 RNA modifications remains largely uncharacterized and poorly annotated, and we currently lack integrative studies that identify which RNA modification-related proteins (RMPs) may be dysregulated in each cancer type. ResultsHere we have performed a comprehensive annotation and evolutionary analysis of human RMPs as well as an integrative analysis of their expression patterns across 32 tissues, 10 species and 13,358 paired tumor-normal human samples. Our analysis reveals an unanticipated heterogeneity of RMP expression patterns across mammalian tissues, with a vast proportion of duplicated enzymes displaying testis-specific expression, suggesting a key role for RNA modifications in sperm formation and possibly intergenerational inheritance. Moreover, through the analysis of paired tumor-normal human samples we uncover many RMPs that are dysregulated in various types of cancer, and whose expression levels are predictive of cancer progression. Surprisingly, we find that several commonly studied RNA modification enzymes such as METTL3 or FTO, are not significantly up-regulated in most cancer types, once the sample is properly scaled and normalized to the full dataset, whereas several less-characterized RMPs, such as LAGE3 and HENMT1, are dysregulated in many cancers. ConclusionsOur analyses reveal an unanticipated heterogeneity in the expression patterns of RMPs across mammalian tissues, and uncover a large proportion of dysregulated RMPs in multiple cancer types. We provide novel targets for future cancer research studies targeting the human epitranscriptome, as well as foundations to understand cell type-specific behaviours that are orchestrated by RNA modifications.

molecular biology↗