J Agric Food Chem. 2025 Mar 7. doi: 10.1021/acs.jafc.4c09501. Online ahead of print.

ABSTRACT

Betalains, a group of pigments widely distributed in various plants, are extensively applied in the food, beverage, and medicinal industries. The biosynthesis of betalains involves the enzymatic action of 4,5-DOPA-dioxygenase, which catalyzes the key ring-opening reaction of DOPA to produce betalamic acid, a crucial intermediate in the pathway. The crystal structure of a 4,5-DOPA-dioxygenase from Beta vulgaris (BvDOD) was determined in this study. The structural analysis revealed that BvDOD exhibited a structural fold similar to that of other members of the extradiol dioxygenase family. Moreover, the Fe-ligand residues His15, His53, and His229 indicated the enzyme's reliance on nonheme iron for catalyzing the ring-opening reaction. Molecular docking and mutational analysis identified two conserved residues, His119 and His175, in the active site essential for the catalytic reaction. In addition, Thr17, Asp254, and Tyr260 contributed to properly positioning the substrate in the active site. This study has provided structural insights into substrate recognition and catalytic mechanisms of BvDOD, which can be applied to develop enzymes for improved betalain production.

PMID:40055856 | DOI:10.1021/acs.jafc.4c09501

J Phys Chem B. 2025 Mar 7. doi: 10.1021/acs.jpcb.4c07794. Online ahead of print.

ABSTRACT

Small molecule kinase inhibitors are critical in the modern treatment of cancers, evidenced by the existence of over 80 FDA-approved small-molecule kinase inhibitors. Unfortunately, intrinsic or acquired resistance, often causing therapy discontinuation, is frequently caused by mutations in the kinase therapeutic target. The advent of clinical tumor sequencing has opened additional opportunities for precision oncology to improve patient outcomes by pairing optimal therapies with tumor mutation profiles. However, modern precision oncology efforts are hindered by lack of sufficient biochemical or clinical evidence to classify each mutation as resistant or sensitive to existing inhibitors. Structure-based methods show promising accuracy in retrospective benchmarks at predicting whether a kinase mutation will perturb inhibitor binding, but comparisons are made by pooling disparate experimental measurements across different conditions. We present the first prospective benchmark of structure-based approaches on a blinded dataset of in-cell kinase inhibitor affinities to Abl kinase mutants using a NanoBRET reporter assay. We compare NanoBRET results to structure-based methods and their ability to estimate the impact of mutations on inhibitor binding (measured as ΔΔG). Comparing physics-based simulations, Rosetta, and previous machine learning models, we find that structure-based methods accurately classify kinase mutations as inhibitor-resistant or inhibitor-sensitizing, and each approach has a similar degree of accuracy. We show that physics-based simulations are best suited to estimate ΔΔG of mutations that are distal to the kinase active site. To probe modes of failure, we retrospectively investigate two clinically significant mutations poorly predicted by our methods, T315A and L298F, and find that starting configurations and protonation states significantly alter the accuracy of our predictions. Our experimental and computational measurements provide a benchmark for estimating the impact of mutations on inhibitor binding affinity for future methods and structure-based models. These structure-based methods have potential utility in identifying optimal therapies for tumor-specific mutations, predicting resistance mutations in the absence of clinical data, and identifying potential sensitizing mutations to established inhibitors.

PMID:40053698 | DOI:10.1021/acs.jpcb.4c07794

STAR Protoc. 2025 Mar 5;6(1):103671. doi: 10.1016/j.xpro.2025.103671. Online ahead of print.

ABSTRACT

Reverse vaccine technology, supported by advancements in immunoinformatics, facilitates the development of multi-epitope vaccines for rapidly evolving pathogens, thereby strengthening the immune defense. Here, we present a protocol for a peptide-based multi-epitope vaccine targeting monkeypox virus (MPXV) using an open-source approach. We describe steps for evaluating physicochemical properties and allergenicity. We then detail procedures for validating pattern recognition receptor (PRR)-binding affinity and stable major histocompatibility complex (MHC) I/II presentation. Molecular dynamics (MD) simulations confirm immune receptor interactions, enhancing vaccine stability. For complete details on the use and execution of this protocol, please refer to Kaur et al.1.

PMID:40053448 | DOI:10.1016/j.xpro.2025.103671

Elife. 2025 Mar 7;13:RP99545. doi: 10.7554/eLife.99545.

ABSTRACT

The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuroscience, it has remained unclear whether fundamental empirical properties of neural network activity can be explained solely based on this normative principle. Here, we derive the structural, coding, and biophysical properties of excitatory-inhibitory recurrent networks of spiking neurons that emerge directly from imposing that the network minimizes an instantaneous loss function and a time-averaged performance measure enacting efficient coding. We assumed that the network encodes a number of independent stimulus features varying with a time scale equal to the membrane time constant of excitatory and inhibitory neurons. The optimal network has biologically plausible biophysical features, including realistic integrate-and-fire spiking dynamics, spike-triggered adaptation, and a non-specific excitatory external input. The excitatory-inhibitory recurrent connectivity between neurons with similar stimulus tuning implements feature-specific competition, similar to that recently found in visual cortex. Networks with unstructured connectivity cannot reach comparable levels of coding efficiency. The optimal ratio of excitatory vs inhibitory neurons and the ratio of mean inhibitory-to-inhibitory vs excitatory-to-inhibitory connectivity are comparable to those of cortical sensory networks. The efficient network solution exhibits an instantaneous balance between excitation and inhibition. The network can perform efficient coding even when external stimuli vary over multiple time scales. Together, these results suggest that key properties of biological neural networks may be accounted for by efficient coding.

PMID:40053385 | DOI:10.7554/eLife.99545

FASEB J. 2025 Mar 15;39(5):e70411. doi: 10.1096/fj.202402726R.

ABSTRACT

Viral infections can cause cellular dysregulation of metabolic reactions. Viruses alter host metabolism to meet their replication needs. The impact of viruses on specific metabolic pathways is not well understood, even in well-studied viruses, such as human adenovirus. Adenoviral infection is known to influence cellular glycolysis and respiration; however, global effects on overall cellular metabolism in response to infection are unclear. Furthermore, few studies have employed an untargeted approach, combining emphasis on viral dosage and infection. To address this, we employed untargeted metabolomics to quantify the dynamic metabolic shifts in fibroblasts infected with human adenovirus serotype 5 (HAdV-5) at three dosages (0.5, 1.0, and 2.0 multiplicity of infection [MOI]) and across 4 time points (6-, 12-, 24-, and 36-h post-infection [HPI]). The greatest differences in individual metabolites were observed at 6- and 12-h post-infection, correlating with the early phase of the HAdV-5 infection cycle. In addition to its effects on glycolysis and respiration, adenoviral infection downregulates cysteine and unsaturated fatty acid metabolism while upregulating aspects of purine metabolism. These results reveal specific metabolic pathways dysregulated by adenoviral infection and the associated dynamic shifts in metabolism, suggesting that viral infections alter energetics via profound changes in lipid, nucleic acid, and protein metabolism. The results revealed previously unconsidered metabolic pathways disrupted by HAdV-5 that can alter cellular metabolism, thereby prompting further investigation into HAdV mechanisms and antiviral targeting.

PMID:40052831 | DOI:10.1096/fj.202402726R

Brief Bioinform. 2025 Mar 4;26(2):bbaf082. doi: 10.1093/bib/bbaf082.

ABSTRACT

Cancer cells acquire necessary functional capabilities for malignancy through the influence of the nervous system. We evaluate the extent of neural infiltration within the tumor microenvironment (TME) across multiple cancer types, highlighting its role as a cancer hallmark. We identify cancer-related neural genes using 40 bulk RNA-seq datasets across 10 cancer types, developing a predictive score for cancer-related neural infiltration (C-Neural score). Cancer samples with elevated C-Neural scores exhibit perineural invasion, recurrence, metastasis, higher stage or grade, or poor prognosis. Epithelial cells show the highest C-Neural scores among all cell types in 55 single-cell RNA sequencing datasets. The epithelial cells with high C-Neural scores (epi-highCNs) characterized by increased copy number variation, reduced cell differentiation, higher epithelial-mesenchymal transition scores, and elevated metabolic level. Epi-highCNs frequently communicate with Schwann cells by FN1 signaling pathway. The co-culture experiment indicates that Schwann cells may facilitate cancer progression through upregulation of VDAC1. Moreover, C-Neural scores positively correlate with the infiltration of antitumor immune cells, indicating potential response for immunotherapy. Melanoma patients with high C-Neural scores may benefit from trametinib. These analyses illuminate the extent of neural influence within TME, suggesting potential role as a cancer hallmark and offering implications for effective therapeutic strategies against cancer.

PMID:40052442 | DOI:10.1093/bib/bbaf082

Clin J Pain. 2025 Mar 7. doi: 10.1097/AJP.0000000000001279. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aimed to characterize pain intensity (average, worst) and disease severity in youth with inflammatory bowel disease in the 12-months post-diagnosis, and to examine the relation between pain and risk (disease severity) and resilience (optimism, pain self-efficacy) factors over time.

METHODS: Data collection ran from February 2019 to March 2022. Newly diagnosed youth aged 8-17 with IBD completed numerical rating scales for average and worst pain intensity, Youth Life Orientation Test for optimism, and Pain Self-Efficacy Scale for pain self-efficacy via REDCap; weighted Pediatric Crohn's Disease Activity Index and the Pediatric Ulcerative Colitis Activity Index were used as indicators of disease severity. Descriptive statistics characterized pain and disease severity. Multilevel modeling explored relations between variables over time, including moderation effects of optimism and pain self-efficacy.

RESULTS: At baseline, 83 youth (Mage=13.9, SD=2.6; 60.2% Crohn's disease; 39.8% female) were included. Attrition rates at 4 and 12 months were 6.0% and 9.6%, respectively. Across time, at least 52% of participants reported pain. Participants in disease remission increased from 4% to 70% over 12-months. Higher disease severity predicted higher worst pain, regardless of time since diagnosis. Higher pain self-efficacy: (a) predicted lower average and worst pain, especially at later time points; and (b) attenuated the association between disease severity and worst pain when included as a moderator. Higher optimism predicted lower worst pain.

DISCUSSION: Pain is prevalent in pediatric inflammatory bowel disease and impacted by disease severity, pain self-efficacy, and optimism. Findings highlight modifiable intervention targets.

PMID:40052200 | DOI:10.1097/AJP.0000000000001279

NPJ Metab Health Dis. 2025;3(1):7. doi: 10.1038/s44324-024-00047-w. Epub 2025 Mar 4.

ABSTRACT

Organisms have to adapt to changes in their environment. Cellular adaptation requires sensing, signalling and ultimately the activation of cellular programs. Metabolites are environmental signals that are sensed by proteins, such as metabolic enzymes, protein kinases and nuclear receptors. Recent studies have discovered novel metabolite sensors that function as gene regulatory proteins such as chromatin associated factors or RNA binding proteins. Due to their function in regulating gene expression, metabolite-induced allosteric control of these proteins facilitates a crosstalk between metabolism and gene expression. Here we discuss the direct control of gene regulatory processes by metabolites and recent progresses that expand our abilities to systematically characterize metabolite-protein interaction networks. Obtaining a profound map of such networks is of great interest for aiding metabolic disease treatment and drug target identification.

PMID:40052108 | PMC:PMC11879850 | DOI:10.1038/s44324-024-00047-w

Front Genet. 2025 Feb 20;16:1572285. doi: 10.3389/fgene.2025.1572285. eCollection 2025.

ABSTRACT

[This corrects the article DOI: 10.3389/fgene.2021.753839.].

PMID:40051703 | PMC:PMC11882524 | DOI:10.3389/fgene.2025.1572285

Front Mol Biosci. 2025 Feb 20;12:1493891. doi: 10.3389/fmolb.2025.1493891. eCollection 2025.

ABSTRACT

Pseudomonas aeruginosa (PA) is a ubiquitous, Gram-negative, bacteria that can attribute its survivability to numerous sensing and signaling pathways; conferring fitness due to speed of response. Post-transcriptional regulation is an energy efficient approach to quickly shift gene expression in response to the environment. The conserved post-transcriptional regulator RsmA is involved in regulating translation of genes involved in pathways that contribute to virulence, metabolism, and antibiotic resistance. Prior high-throughput approaches to map the full regulatory landscape of RsmA have estimated a target pool of approximately 500 genes; however, these approaches have been limited to a narrow range of growth phase, strain, and media conditions. Computational modeling presents a condition-independent approach to generating predictions for binding between the RsmA protein and highest affinity mRNAs. In this study, we improve upon a two-state thermodynamic model to predict the likelihood of RsmA binding to the 5' UTR sequence of genes present in the PA genome. Our modeling approach predicts 1043 direct RsmA-mRNA binding interactions, including 457 novel mRNA targets. We then perform GO term enrichment tests on our predictions that reveal significant enrichment for DNA binding transcriptional regulators. In addition, quorum sensing, biofilm formation, and two-component signaling pathways were represented in KEGG enrichment analysis. We confirm binding predictions using in vitro binding assays, and regulatory effects using in vivo translational reporters. These reveal RsmA binding and regulation of a broader number of genes not previously reported. An important new observation of this work is the direct regulation of several novel mRNA targets encoding for factors involved in Quorum Sensing and the Type IV Secretion system, such as rsaL and mvaT. Our study demonstrates the utility of thermodynamic modeling for predicting interactions independent of complex and environmentally-sensitive systems, specifically for profiling the post-transcriptional regulator RsmA. Our experimental validation of RsmA binding to novel targets both supports our model and expands upon the pool of characterized target genes in PA. Overall, our findings demonstrate that a modeling approach can differentiate direct from indirect binding interactions and predict specific sites of binding for this global regulatory protein, thus broadening our understanding of the role of RsmA regulation in this relevant pathogen.

PMID:40051501 | PMC:PMC11882435 | DOI:10.3389/fmolb.2025.1493891

J Basic Microbiol. 2025 Mar 6:e70013. doi: 10.1002/jobm.70013. Online ahead of print.

ABSTRACT

Speciation in prokaryotes is often driven by complex genetic exchanges such as horizontal gene transfer (HGT), which facilitates genomic divergence and adaptation. In this study, we inferred the evolutionary transitions of the mobilome (plasmids, transposons, and phages) between Methanosarcina and bacteria in driving speciation within the Methanosarcina genus. By conducting evolutionary and phylogenetic analyses of Methanosarcina acetivorans, M. barkeri, M. mazei, and M. siciliae, we identified key mobilome elements acquired through HGT from distantly related bacterial species. These mobile genetic elements have shaped genomic plasticity, enabling Methanosarcina to adapt to diverse environmental niches and potentially facilitating lineage divergence. The acquisition of mobilome-associated genes involved in antibiotic resistance, DNA repair, and stress responses suggests their significant role in the ecological speciation of Methanosarcina. Overall, we hypothesized that their mobile genetic element might have been acquired from distantly related bacteria by HGT and subsequently established as new functional homologs in the present lineage. This study provides insight into how mobilome-mediated gene flow contributes to genomic divergence and speciation within microbial populations, highlighting the broader significance of mobilome in microbial evolution and speciation processes.

PMID:40051073 | DOI:10.1002/jobm.70013

J Basic Microbiol. 2025 Mar 6:e70015. doi: 10.1002/jobm.70015. Online ahead of print.

ABSTRACT

The convergent evolution of coenzyme metabolism in methanogens provides critical insights into primitive life and metabolic adaptations. This study investigated the molecular evolution and functional dynamics of eight coenzymes and cofactors in Methanosarcina mazei, a model methanogen essential for methane production and energy conservation in anaerobic environments. Phylogenetic and genetic diversity analyses of the 706 protein sequences revealed conserved evolutionary trajectories interspersed with lineage-specific adaptations driven by gene duplication, horizontal gene transfer, and selective pressures. Key findings included the purifying selection of methanofuran (Tajima's D = -2.9589) and coenzyme A (Tajima's D = -2.8555), indicating the conservation of critical metabolic functions. The coenzyme B biosynthesis pathway showed balanced selection (Tajima's D = 2.38602), reflecting its evolutionary plasticity. Phylogenetic analyses linked coenzyme F420 biosynthetic enzymes closely to Methanosarcina horonobensis, while coenzyme F430 enzymes highlighted prokaryotic specialization distinct from their eukaryotes. Coenzyme M biosynthetic genes have demonstrated unique evolutionary connections with species across domains, such as Methanothermobacter thermautotrophicus and Gekko japonicus, emphasizing their broad adaptive significance. These evolutionary trajectories reveal how M. mazei optimized its metabolic pathways to thrive in extreme anaerobic environments, bridging ancient metabolic systems from the Last Universal Common Ancestor with contemporary ecological adaptations.

PMID:40051064 | DOI:10.1002/jobm.70015

Plant Genome. 2025 Mar;18(1):e70004. doi: 10.1002/tpg2.70004.

ABSTRACT

Fusarium wilt (FW) significantly affects the growth and development of chickpea (Cicer arietinum L.), leading to substantial economic losses. FW resistance is a quantitative trait that is controlled by multiple genomic regions. In this study, a meta-analysis was conducted on 32 quantitative trait loci (QTLs) associated with FW resistance, leading to the identification of seven meta-QTL (MQTL) regions distributed across CaLG2, CaLG4, CaLG5, and CaLG6 of the chickpea linkage groups. The integrated analysis revealed several candidate genes potentially important for FW resistance, including genes associated with sensing (e.g., LRR-RLK), signaling (e.g., mitogen-activated protein kinase [MAPK1]), and transcription regulation (e.g., NAC, WRKY, and bZIP). Subsequently, a marker-assisted backcrossing (MABC) trial was executed leveraging the MQTL outcomes to introgress FW resistance from an FW-resistant chickpea cultivar (Ana) into a superior high-yielding Kabuli cultivar (Hashem). The breeding process was extended over 5 years (2018-2023) and resulted in the development of BC3F2 genotypes. Consequently, 12 genotypes carrying homozygous resistance alleles were chosen, with three genotypes showing genetic backgrounds matching 90%-96% of the recurrent parent. The findings of this study have significant implications for upcoming programs, encompassing fine-mapping, marker-assisted breeding, and genetic engineering, consequently contributing to the effective control of FW and the improved production of chickpea.

PMID:40050693 | DOI:10.1002/tpg2.70004

Nat Immunol. 2025 Mar 6. doi: 10.1038/s41590-025-02105-x. Online ahead of print.

ABSTRACT

Tissue-resident memory T (TRM) cells are a specialized T cell population that reside in tissues and provide a rapid protective response upon activation. Here, we showed that human and mouse CD4+ TRM cells existed in a poised state and stored messenger RNAs encoding proinflammatory cytokines without protein production. At steady state, cytokine mRNA translation in TRM cells was suppressed by the integrated stress response (ISR) pathway. Upon activation, the central ISR regulator, eIF2α, was dephosphorylated and stored cytokine mRNA was translated for immediate cytokine production. Genetic or pharmacological activation of the ISR-eIF2α pathway reduced cytokine production and ameliorated autoimmune kidney disease in mice. Consistent with these results, the ISR pathway in CD4+ TRM cells was downregulated in patients with immune-mediated diseases of the kidney and the intestine compared to healthy controls. Our results indicated that stored cytokine mRNA and translational regulation in CD4+ TRM cells facilitate rapid cytokine production during local immune response.

PMID:40050432 | DOI:10.1038/s41590-025-02105-x

Nat Commun. 2025 Mar 6;16(1):2256. doi: 10.1038/s41467-025-57430-4.

ABSTRACT

Functional proteomics provides critical insights into cancer mechanisms, facilitating the discovery of novel biomarkers and therapeutic targets. We have developed a comprehensive cancer functional proteomics resource using reverse phase protein arrays, incorporating data from nearly 8000 patient samples from The Cancer Genome Atlas and approximately 900 samples from the Cancer Cell Line Encyclopedia. Our dataset includes a curated panel of nearly 500 high-quality antibodies, covering all major cancer hallmark pathways. To enhance the accessibility and analytic power of this resource, we introduce DrBioRight 2.0 ( https://drbioright.org ), an intuitive bioinformatic platform powered by state-of-the-art large language models. DrBioRight enables researchers to explore protein-centric cancer omics data, perform advanced analyses, visualize results, and engage in interactive discussions using natural language. By streamlining complex proteogenomic analyses, this tool accelerates the translation of large-scale functional proteomics data into meaningful biomedical insights.

PMID:40050282 | DOI:10.1038/s41467-025-57430-4

Metab Eng. 2025 Mar 4:S1096-7176(25)00031-X. doi: 10.1016/j.ymben.2025.03.001. Online ahead of print.

ABSTRACT

The utilization of microorganisms to transform biomass into biofuels and biochemicals presents a viable and competitive alternative to conventional petroleum refining processes. Halomonas species are salt-tolerant and alkaliphilic, endowed with various beneficial properties rendering them as contamination resistant platforms for industrial biotechnology, facilitating the commercial-scale production of valuable bioproducts. Here we summarized the metabolic and genomic engineering approaches, as well as the biochemical products synthesized by Halomonas. Methods were presented for expanding substrates utilization in Halomonas to enhance its capabilities as a robust workhorse for bioproducts. In addition, we briefly reviewed the Next Generation Industrial Biotechnology (NGIB) based on Halomonas for open and continuous fermentation. In particular, we proposed the industrial attempts from Halomonas chassis and the rising prospects and essential strategies to enable the successful development of Halomonas as microbial NGIB manufacturing platforms.

PMID:40049362 | DOI:10.1016/j.ymben.2025.03.001

Food Chem. 2025 Mar 1;478:143663. doi: 10.1016/j.foodchem.2025.143663. Online ahead of print.

ABSTRACT

Southern Thailand sweet pickled mango (MBC) is a famous delicacy and economically important for the local communities. This study aimed to elucidate important metabolites related to MBC deterioration at 4 °C (STR4) and 30 °C (STR30). The results show that deterioration of MBCs was linked to increased levels of ethyl acetate, isopropyl alcohol, trans-β-ocimene, isopentyl acetate, 2-phenethyl acetate, glucose, and fructose, along with a decrease in sucrose. Moreover, isopentyl acetate, ethyl acetate, and 2-phenethyl acetate were significantly higher in STR4 compared to STR30 with log 2[fold change (FC)] 3.2, 2.0, and 1.0, respectively. Meanwhile, STR4 had a lower sucrose level (log [FC] -1.4) than STR30. It was postulated that a longer storage time of STR4 than STR30 affects sucrose hydrolysis. Due to the abundance of volatile metabolites in deteriorated MBC, applying odor/flavor absorber film on MBC packaging might help prolong its shelf life.

PMID:40049138 | DOI:10.1016/j.foodchem.2025.143663

Diabetes. 2025 Mar 6:db240655. doi: 10.2337/db24-0655. Online ahead of print.

ABSTRACT

Genome-wide association studies have identified SH2B3 as an important non-MHC gene for islet autoimmunity and type 1 diabetes (T1D). In this study, we found a single SH2B3 haplotype significantly associated with increased risk for human T1D. Fine mapping has demonstrated the most credible causative variant is the single nucleotide rs3184504*T polymorphism in SH2B3. To better characterize the role of SH2B3 in T1D, we used mouse modeling and found a T cellintrinsic role for SH2B3 regulating peripheral tolerance. SH2B3 deficiency had minimal effect on TCR signaling or proliferation across antigen doses, yet enhanced cell survival and cytokine signaling including common gamma chain-dependent and interferon-gamma receptor signaling. SH2B3 deficient naïve CD8+ T cells showed augmented STAT5-MYC and effector-related gene expression partially reversed with blocking autocrine IL-2 in culture. Using the RIP-mOVA model, we found CD8+ T cells lacking SH2B3 promoted early islet destruction and diabetes without requiring CD4+ T cell help. SH2B3-deficient cells demonstrated increased survival and reduced activation-induced cell death. Lastly, we created a spontaneous NOD.Sh2b3-/- mouse model and found markedly increased incidence and accelerated T1D across sexes. Collectively, these studies identify SH2B3 as a critical mediator of peripheral T cell tolerance limiting the T cell response to self-antigens.

PMID:40048557 | DOI:10.2337/db24-0655

Science. 2025 Mar 7;387(6738):eadn2623. doi: 10.1126/science.adn2623. Epub 2025 Mar 7.

ABSTRACT

Millions of ribosomes are packed within mammalian cells, yet we lack tools to visualize them in toto and characterize their subcellular composition. In this study, we present ribosome expansion microscopy (RiboExM) to visualize individual ribosomes and an optogenetic proximity-labeling technique (ALIBi) to probe their composition. We generated a super-resolution ribosomal map, revealing subcellular translational hotspots and enrichment of 60S subunits near polysomes at the endoplasmic reticulum (ER). We found that Lsg1 tethers 60S to the ER and regulates translation of select proteins. Additionally, we discovered ribosome heterogeneity at mitochondria guiding translation of metabolism-related transcripts. Lastly, we visualized ribosomes in neurons, revealing a dynamic switch between monosomes and polysomes in neuronal translation. Together, these approaches enable exploration of ribosomal localization and composition at unprecedented resolution.

PMID:40048539 | DOI:10.1126/science.adn2623

Aging (Albany NY). 2025 Feb 28;17(2):607. doi: 10.18632/aging.206208. Epub 2025 Feb 28.

NO ABSTRACT

PMID:40048354 | DOI:10.18632/aging.206208