bims-mirnam 2026-09-13 papers

Issue of 2026–09–13
five papers selected by
Hana Antonicka, McGill University

Nat Commun. 2026 Aug 08. pii: 9538. [Epub ahead of print]17(1):

Quantitative RNA modification mapping by mass spectrometry with isobaric tags and nucleobase fragment analysis.

Junzhou Wu, Jingjing Sun, Yifeng Yuan, Shiuan Nee Goh, Hazel Chay, Dwijapriya, Valérie de Crécy-Lagard, Peter C Dedon.

RNA modifications regulate RNA stability, translation, stress responses, and disease processes, yet their function remains poorly understood due to technical limitations in sequence analysis. Here, we present an RNA-specific isobaric tandem mass tagging (RMT) platform for omic-scale quantitative mapping of RNA modifications. The platform combines RNA-specific tags adapted from proteomics with an end-to-end workflow spanning sample preparation through data processing. Validation using synthetic oligonucleotides and total tRNA from Pseudomonas aeruginosa yielded reproducible quantification, with coefficients of variation below 5%. Together with nucleobase fragment analysis, we identified and quantified 24 RNA modifications in PA14 tRNAs, including previously undescribed m2A38 and Gm/Cm39, and assigned their corresponding writer enzymes. Further analyses of tRNAs from writer knockout strains and stressed cells revealed dynamic modification patterns, modification interdependencies, and their potential roles in stress adaptation. This method provides a robust, cost-effective platform for quantitative RNA modification mapping, enabling deeper biological insights.

DOI: https://doi.org/10.1038/s41467-026-76537-w

Front Cell Dev Biol. 2026 ;14 1840428

Spatiotemporal control of mitoribosome-mediated metabolic reprogramming in cancer: implications for heterogeneity and therapeutic targeting.

Xiaojie Chen, Weidong Wang, Fangxin Shen, Zhiwei Zhao.

Mitochondrial ribosomes (mitoribosomes), particularly mitochondrial ribosomal subunit proteins (MRPS), are emerging as contributors to cancer metabolic reprogramming. Rather than static components of mitochondrial translation, MRPS exhibit pronounced spatiotemporal heterogeneity that shapes tumor metabolic plasticity and therapeutic response. This review systematically summarizes evidence that MRPS functions are dynamically regulated across tumor progression and spatial microenvironments. Temporally, MRPS mediate metabolic switching between oxidative phosphorylation (OXPHOS) and glycolysis, contributing to metabolic adaptation, treatment resistance, and tumor evolution. Spatially, MRPS display context-dependent functions across tumor regions, cancer types, and metabolic microenvironments, thereby contributing to intratumoral metabolic diversity. We further highlight that MRPS-associated metabolic plasticity is linked with lactate metabolism and hypoxia-inducible factor (HIF) signaling, forming feedback networks associated with tumor growth, immune escape, and therapy resistance. This spatiotemporal regulatory axis challenges the traditional static view of mitochondrial dysfunction in cancer. Targeting MRPS-associated metabolic adaptation may provide therapeutic opportunities beyond the traditional Warburg framework. Emerging technologies, including lactate-sensitive nanoprobes, reactive oxygen species (ROS)-responsive delivery systems, and MRPS-related imaging platforms, may support metabolic monitoring and targeted therapeutic intervention. Collectively, this framework links mitochondrial translation with tumor metabolism and microenvironmental regulation, providing additional insight into metabolic adaptation in cancer.

Keywords: MRPs; cancer metabolic reprogramming; mitoribosomes; spatial heterogeneity; targeted therapy; temporal heterogeneity

DOI: https://doi.org/10.3389/fcell.2026.1840428

Front Aging Neurosci. 2026 ;18 1884207

Striatal small RNA remodeling in MPTP-induced Parkinson's disease highlights coordinated downregulation of mitochondrial tsRNAs.

Mingyu Mao, Yan Wang, Qing Deng, Jun Xiang, Wentao Li.

Parkinson's disease (PD) is characterized by progressive nigrostriatal degeneration, yet the contribution of modification-rich small RNAs to PD pathology remains unclear. Here, we used PANDORA-seq to profile the striatal small RNA landscape in a subacute MPTP-induced mouse model of PD. MPTP-treated mice exhibited significant motor deficits together with reduced striatal tyrosine hydroxylase and dopamine transporter expression, confirming successful model establishment. Small RNA profiling revealed that transfer RNA-derived small RNAs and ribosomal RNA-derived small RNAs, rather than microRNAs, dominated the striatal small RNA transcriptome. Among the dysregulated small RNA classes, mitochondrial tsRNAs showed the most prominent and coordinated downregulation. Bioinformatic analysis suggested that predicted targets of differentially expressed mt-tsRNAs were enriched in synaptic organization, presynaptic function, membrane contact sites, and lipid-related pathways. In SH-SY5Y cells, transfection of an mt-tsRNA mimic partially reversed MPP+ induced increases in reactive oxygen species and restored mitochondrial membrane potential. These findings provide a modification-aware small RNA landscape of the PD striatum and identify mt-tsRNA downregulation as a notable feature of MPTP-induced parkinsonism.

Keywords: MPTP; Parkinson’s disease; mitochondrial dysfunction; mitochondrial tsRNAs; pANDORA-seq; striatum

DOI: https://doi.org/10.3389/fnagi.2026.1884207

Science. 2026 Sep 10. 393(6816): 1107-1116

Chronic type II interferon promotes tumor growth through mitochondrial RNA-induced type I interferon and prostaglandin synthesis.

Interferons (IFNs) are proinflammatory cytokines that promote immune cell engagement to eliminate malignant cells. Paradoxically, chronic interferon signaling can also activate anti-inflammatory mechanisms that allow cancer cells to evade the immune system. In this study, we sought to determine the cellular mechanisms underlying this switch from antitumorigenic to protumorigenic interferon activity. We show that chronic type II interferon (IFN-II) exposure distinctively induced tumor growth by activating a type I interferon (IFN-I) response mediated by release of double-stranded mitochondrial RNA (ds-mtRNA) into the cytoplasm. This IFN-I signal synergized with IFN-II to enhance tumor growth by increasing immunosuppressive prostaglandin E2 (PGE2) synthesis through increased cyclooxygenase 2 expression. Elimination of PGE2 synthesis in immunotherapy-resistant melanoma cells restored their responsiveness to anti-PD1 treatment, indicating that this covert mtRNA-IFN-prostaglandin pathway could be a therapeutic target to combat immunotherapy resistance.

DOI: https://doi.org/10.1126/science.aec0002

Nucleic Acids Res. 2026 Sep 07. pii: gkag870. [Epub ahead of print]54(17):

ProRB: a structure-free unified framework for joint prediction and design of protein-RNA interactions.

Yiming Xue, Xiaojian Liu, Weimin Zhu, Shengfan Wang, Hong-Bin Shen, Xiaoyong Pan.

While protein-RNA interactions are fundamental to post-transcriptional processes, achieving a holistic understanding of their regulatory logic remains challenging. Current computational models often treat binding affinity, interface mapping, and RNA design as isolated tasks, thereby failing to provide a unified perspective of the protein-RNA interactome. Here, we introduce ProRB, a unified sequence-based framework that jointly estimates protein-RNA binding affinity, predicts binding interfaces in proteins and RNAs, and generates protein-binding RNA sequences from protein sequences. By fusing protein and RNA embeddings from language models via adaptive cross-modal attention, ProRB learns contextual and relational features for predicting protein-RNA binding affinity and interface contacts, outperforming or achieving competitive performance compared to structure-based methods. Notably, its cross-attention maps reveal interpretable, motif-centric binding logic hidden in protein-RNA interactions. Building on this interpretability, ProRB enables computationally prioritized design of protein-binding RNA sequences with enhanced biophysical properties and functional motifs. By unifying the prediction, interpretation, and generation tasks, ProRB provides a scalable unified model for decoding the protein-RNA interaction and engineering motif-guided RNA therapeutics.

DOI: https://doi.org/10.1093/nar/gkag870