A non-canonical role for a small nucleolar RNA in ribosome biogenesis and senescence.

Cellular senescence is an irreversible state of cell-cycle arrest induced by various stresses, including aberrant oncogene activation, telomere shortening, and DNA damage. Through a genome-wide screen, we discovered a conserved small nucleolar RNA (snoRNA), SNORA13, that is required for multiple forms of senescence in human cells and mice. Although SNORA13 guides the pseudouridylation of a conserved nucleotide in the ribosomal decoding center, loss of this snoRNA minimally impacts translation. Instead, we found that SNORA13 negatively regulates ribosome biogenesis. Senescence-inducing stress perturbs ribosome biogenesis, resulting in the accumulation of free ribosomal proteins (RPs) that trigger p53 activation. SNORA13 interacts directly with RPL23, decreasing its incorporation into maturing 60S subunits and, consequently, increasing the pool of free RPs, thereby promoting p53-mediated senescence. Thus, SNORA13 regulates ribosome biogenesis and the p53 pathway through a non-canonical mechanism distinct from its role in guiding RNA modification. These findings expand our understanding of snoRNA functions and their roles in cellular signaling.

De novo and salvage purine synthesis pathways across tissues and tumors.

Purine nucleotides are vital for RNA and DNA synthesis, signaling, metabolism, and energy homeostasis. To synthesize purines, cells use two principal routes: the de novo and salvage pathways. Traditionally, it is believed that proliferating cells predominantly rely on de novo synthesis, whereas differentiated tissues favor the salvage pathway. Unexpectedly, we find that adenine and inosine are the most effective circulating precursors for supplying purine nucleotides to tissues and tumors, while hypoxanthine is rapidly catabolized and poorly salvaged in vivo. Quantitative metabolic analysis demonstrates comparative contribution from de novo synthesis and salvage pathways in maintaining purine nucleotide pools in tumors. Notably, feeding mice nucleotides accelerates tumor growth, while inhibiting purine salvage slows down tumor progression, revealing a crucial role of the salvage pathway in tumor metabolism. These findings provide fundamental insights into how normal tissues and tumors maintain purine nucleotides and highlight the significance of purine salvage in cancer.

Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease.

Somatic mutations in nonmalignant tissues accumulate with age and injury, but whether these mutations are adaptive on the cellular or organismal levels is unclear. To interrogate genes in human metabolic disease, we performed lineage tracing in mice harboring somatic mosaicism subjected to nonalcoholic steatohepatitis (NASH). Proof-of-concept studies with mosaic loss of Mboat7, a membrane lipid acyltransferase, showed that increased steatosis accelerated clonal disappearance. Next, we induced pooled mosaicism in 63 known NASH genes, allowing us to trace mutant clones side by side. This in vivo tracing platform, which we coined MOSAICS, selected for mutations that ameliorate lipotoxicity, including mutant genes identified in human NASH. To prioritize new genes, additional screening of 472 candidates identified 23 somatic perturbations that promoted clonal expansion. In validation studies, liver-wide deletion of Tbx3, Bcl6, or Smyd2 resulted in protection against hepatic steatosis. Selection for clonal fitness in mouse and human livers identifies pathways that regulate metabolic disease.

Somatic Mutations Increase Hepatic Clonal Fitness and Regeneration in Chronic Liver Disease.

Normal tissues accumulate genetic changes with age, but it is unknown if somatic mutations promote clonal expansion of non-malignant cells in the setting of chronic degenerative diseases. Exome sequencing of diseased liver samples from 82 patients revealed a complex mutational landscape in cirrhosis. Additional ultra-deep sequencing identified recurrent mutations in PKD1, PPARGC1B, KMT2D, and ARID1A. The number and size of mutant clones increased as a function of fibrosis stage and tissue damage. To interrogate the functional impact of mutated genes, a pooled in vivo CRISPR screening approach was established. In agreement with sequencing results, examination of 147 genes again revealed that loss of Pkd1, Kmt2d, and Arid1a promoted clonal expansion. Conditional heterozygous deletion of these genes in mice was also hepatoprotective in injury assays. Pre-malignant somatic alterations are often viewed through the lens of cancer, but we show that mutations can promote regeneration, likely independent of carcinogenesis.

Lin28 enhances tissue repair by reprogramming cellular metabolism.

Regeneration capacity declines with age, but why juvenile organisms show enhanced tissue repair remains unexplained. Lin28a, a highly conserved RNA-binding protein expressed during embryogenesis, plays roles in development, pluripotency, and metabolism. To determine whether Lin28a might influence tissue repair in adults, we engineered the reactivation of Lin28a expression in several models of tissue injury. Lin28a reactivation improved hair regrowth by promoting anagen in hair follicles and accelerated regrowth of cartilage, bone, and mesenchyme after ear and digit injuries. Lin28a inhibits let-7 microRNA biogenesis; however, let-7 repression was necessary but insufficient to enhance repair. Lin28a bound to and enhanced the translation of mRNAs for several metabolic enzymes, thereby increasing glycolysis and oxidative phosphorylation (OxPhos). Lin28a-mediated enhancement of tissue repair was negated by OxPhos inhibition, whereas a pharmacologically induced increase in OxPhos enhanced repair. Thus, Lin28a enhances tissue repair in some adult tissues by reprogramming cellular bioenergetics. PAPERCLIP:

The Lin28/let-7 axis regulates glucose metabolism.

The let-7 tumor suppressor microRNAs are known for their regulation of oncogenes, while the RNA-binding proteins Lin28a/b promote malignancy by inhibiting let-7 biogenesis. We have uncovered unexpected roles for the Lin28/let-7 pathway in regulating metabolism. When overexpressed in mice, both Lin28a and LIN28B promote an insulin-sensitized state that resists high-fat-diet induced diabetes. Conversely, muscle-specific loss of Lin28a or overexpression of let-7 results in insulin resistance and impaired glucose tolerance. These phenomena occur, in part, through the let-7-mediated repression of multiple components of the insulin-PI3K-mTOR pathway, including IGF1R, INSR, and IRS2. In addition, the mTOR inhibitor, rapamycin, abrogates Lin28a-mediated insulin sensitivity and enhanced glucose uptake. Moreover, let-7 targets are enriched for genes containing SNPs associated with type 2 diabetes and control of fasting glucose in human genome-wide association studies. These data establish the Lin28/let-7 pathway as a central regulator of mammalian glucose metabolism.

Modulation of inner junction proteins contributes to axoneme differentiation.

Cilia build distinct subdomains with variable axonemal structures to perform diverse functions in cell motility and signaling. In sensory cilia across species, an axoneme differentiates longitudinally into a middle segment with nine microtubule (MT) doublets and a distal segment with nine MT singlets that extends from the A tubules of the doublets. Here, we study axoneme differentiation in Caenorhabditis elegans by analyzing the flagellar inner junction protein FAP20 and PCRG1 that connect A and B tubules in Chlamydomonas. The nematode CFAP-20 is restricted to the middle segment with doublets, and its loss disconnects A and B tubules. However, PCRG-1 is absent from most sensory cilia, and its deletion does not disrupt cilia. Ectopic introduction of PCRG-1 into cilia generated abnormal MT doublets in the distal segment and reduced intraflagellar transport and animal sensation. Thus, the absence of an inner junction protein prevents B-tubule extension, which contributes to axoneme differentiation and ciliary function.

The ETS transcription factor Spi2 regulates hematopoietic cell development in zebrafish.

The E26 transformation-specific or E-twenty-six (ETS) genes encode a superfamily of transcription factors involved in diverse biological processes. Here, we report the identification and characterization of a previously unidentified member of the ETS transcription factors, Spi2, that is found exclusively in the ray-finned fish kingdom. We show that the expression of spi2 is restricted to hemogenic endothelial cells (HECs) and to hematopoietic stem and progenitor cells (HSPCs) in zebrafish. Using bacteria artificial chromosome transgenesis, we generate a spi2 reporter line, TgBAC(spi2:P2a-GFP), which manifests the GFP pattern recapitulating the endogenous spi2 expression. Genetic ablation of spi2 has little effect on HEC formation and the endothelial-to-hematopoietic transition, but results in compromised proliferation of HSPCs in the caudal hematopoietic tissue (CHT) during early development and in severe myeloid lineage defect in adulthood. Epistatic analysis shows that spi2 acts downstream of runx1 in regulating HSPC development in the CHT. Our study identifies Spi2 as an essential regulator for definitive hematopoietic cell development and creates a TgBAC(spi2:P2a-GFP) reporter line for tracking HECs, HSPCs, myeloid cells and thrombocytes from early development to adulthood.

scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data.

Recently a biochemistry experiment named methyl-3C was developed to simultaneously capture the chromosomal conformations and DNA methylation levels on individual single cells. However, the number of data sets generated from this experiment is still small in the scientific community compared with the greater amount of single-cell Hi-C data generated from separate single cells. Therefore, a computational tool to predict single-cell methylation levels based on single-cell Hi-C data on the same individual cells is needed. We developed a graph transformer named scHiMe to accurately predict the base-pair-specific (bp-specific) methylation levels based on both single-cell Hi-C data and DNA nucleotide sequences. We benchmarked scHiMe for predicting the bp-specific methylation levels on all of the promoters of the human genome, all of the promoter regions together with the corresponding first exon and intron regions, and random regions on the whole genome. Our evaluation showed a high consistency between the predicted and methyl-3C-detected methylation levels. Moreover, the predicted DNA methylation levels resulted in accurate classifications of cells into different cell types, which indicated that our algorithm successfully captured the cell-to-cell variability in the single-cell Hi-C data. scHiMe is freely available at http://dna.cs.miami.edu/scHiMe/.

An Ensemble Spectral Prediction (ESP) model for metabolite annotation.

MOTIVATION: A key challenge in metabolomics is annotating measured spectra from a biological sample with chemical identities. Currently, only a small fraction of measurements can be assigned identities. Two complementary computational approaches have emerged to address the annotation problem: mapping candidate molecules to spectra, and mapping query spectra to molecular candidates. In essence, the candidate molecule with the spectrum that best explains the query spectrum is recommended as the target molecule. Despite candidate ranking being fundamental in both approaches, limited prior works incorporated rank learning tasks in determining the target molecule. RESULTS: We propose a novel machine learning model, Ensemble Spectral Prediction (ESP), for metabolite annotation. ESP takes advantage of prior neural network-based annotation models that utilize multilayer perceptron (MLP) networks and Graph Neural Networks (GNNs). Based on the ranking results of the MLP- and GNN-based models, ESP learns a weighting for the outputs of MLP and GNN spectral predictors to generate a spectral prediction for a query molecule. Importantly, training data is stratified by molecular formula to provide candidate sets during model training. Further, baseline MLP and GNN models are enhanced by considering peak dependencies through label mixing and multi-tasking on spectral topic distributions. When trained on the NIST 2020 dataset and evaluated on the relevant candidate sets from PubChem, ESP improves average rank by 23.7% and 37.2% over the MLP and GNN baselines, respectively, demonstrating performance gain over state-of-the-art neural network approaches. However, MLP approaches remain strong contenders when considering top five ranks. Importantly, we show that annotation performance is dependent on the training dataset, the number of molecules in the candidate set and candidate similarity to the target molecule. AVAILABILITY AND IMPLEMENTATION: The ESP code, a trained model, and a Jupyter notebook that guide users on using the ESP tool is available at https://github.com/HassounLab/ESP.

Learning Micro-C from Hi-C with diffusion models.

In the last few years, Micro-C has shown itself as an improved alternative to Hi-C. It replaced the restriction enzymes in Hi-C assays with micrococcal nuclease (MNase), resulting in capturing nucleosome resolution chromatin interactions. The signal-to-noise improvement of Micro-C allows it to detect more chromatin loops than high-resolution Hi-C. However, compared with massive Hi-C datasets available in the literature, there are only a limited number of Micro-C datasets. To take full advantage of these Hi-C datasets, we present HiC2MicroC, a computational method learning and then predicting Micro-C from Hi-C based on the denoising diffusion probabilistic models (DDPM). We trained our DDPM and other regression models in human foreskin fibroblast (HFFc6) cell line and evaluated these methods in six different cell types at 5-kb and 1-kb resolution. Our evaluations demonstrate that both HiC2MicroC and regression methods can markedly improve Hi-C towards Micro-C, and our DDPM-based HiC2MicroC outperforms regression in various terms. First, HiC2MicroC successfully recovers most of the Micro-C loops even those not detected in Hi-C maps. Second, a majority of the HiC2MicroC-recovered loops anchor CTCF binding sites in a convergent orientation. Third, HiC2MicroC loops share genomic and epigenetic properties with Micro-C loops, including linking promoters and enhancers, and their anchors are enriched for structural proteins (CTCF and cohesin) and histone modifications. Lastly, we find our recovered loops are also consistent with the loops identified from promoter capture Micro-C (PCMicro-C) and Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET). Overall, HiC2MicroC is an effective tool for further studying Hi-C data with Micro-C as a template. HiC2MicroC is publicly available at https://github.com/zwang-bioinformatics/HiC2MicroC/.

Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation.

Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. The question is how to extract critical information buried in vast data streams. Here we show that artificial intelligence (AI) and molecular simulation play key roles in transforming nanotoxicity data into critical information, i.e., constructing the quantitative nanostructure (physicochemical properties)-toxicity relationships, and elucidating the toxicity-related molecular mechanisms. For AI and molecular simulation to realize their full impacts in this mission, several obstacles must be overcome. These include the paucity of high-quality nanomaterials (NMs) and standardized nanotoxicity data, the lack of model-friendly databases, the scarcity of specific and universal nanodescriptors, and the inability to simulate NMs at realistic spatial and temporal scales. This review provides a comprehensive and representative, but not exhaustive, summary of the current capability gaps and tools required to fill these formidable gaps. Specifically, we discuss the applications of AI and molecular simulation, which can address the large-scale data challenge for nanotoxicology research. The need for model-friendly nanotoxicity databases, powerful nanodescriptors, new modeling approaches, molecular mechanism analysis, and design of the next-generation NMs are also critically discussed. Finally, we provide a perspective on future trends and challenges.

Cryo-electron tomography elucidates annular intraluminal configurations in Caenorhabditis elegans microtubules.

BACKGROUND INFORMATION: Microtubules serve as integral components in cellular operations such as cell division, intracellular trafficking, and cellular architecture. Composed of tubulin protein subunits, these hollow tubular structures have been increasingly elucidated through advanced cryo-electron microscopy (Cryo-EM), which has unveiled the presence of microtubule inner proteins (MIPs) within the microtubular lumen. RESULTS: In the present investigation, we employ a synergistic approach incorporating high-pressure freezing, cryo-focused ion beam milling, and Cryo-electron tomography (Cryo-ET) to interrogate the in situ architecture of microtubules in Caenorhabditis elegans larvae. Our Cryo-ET assessments across neuronal cilia and diverse tissue types consistently demonstrate the formation of annular configurations within the microtubular lumen. CONCLUSIONS: In concert with recently characterized MIPs, our in situ observations within a living organism corroborate the hypothesis that intricate luminal assemblages exist within microtubule scaffolds. These findings necessitate further exploration into the molecular constituents and functional ramifications of these internal microtubular configurations in both cellular physiology and pathophysiology.

Ciliogenesis requires sphingolipid-dependent membrane and axoneme interaction.

Cilium formation and regeneration requires new protein synthesis, but the underlying cytosolic translational reprogramming remains largely unknown. Using ribosome footprinting, we performed global translatome profiling during cilia regeneration in Chlamydomonas and uncovered that flagellar genes undergo an early transcriptional activation but late translational repression. This pattern guided our identification of sphingolipid metabolism enzymes, including serine palmitoyltransferase (SPT), as essential regulators for ciliogenesis. Cryo-electron tomography showed that ceramide loss abnormally increased the membrane-axoneme distance and generated bulged cilia. We found that ceramides interact with intraflagellar transport (IFT) particle proteins that IFT motors transport along axoneme microtubules (MTs), suggesting that ceramide-IFT particle-IFT motor-MT interactions connect the ciliary membrane with the axoneme to form rod-shaped cilia. SPT-deficient vertebrate cells were defective in ciliogenesis, and SPT mutations from patients with hereditary sensory neuropathy disrupted cilia, which could be restored by sphingolipid supplementation. These results reveal a conserved role of sphingolipid in cilium formation and link compromised sphingolipid production with ciliopathies.

In situ structure of intestinal apical surface reveals nanobristles on microvilli.

Microvilli are actin-bundle-supported membrane protrusions essential for absorption, secretion, and sensation. Microvilli defects cause gastrointestinal disorders; however, mechanisms controlling microvilli formation and organization remain unresolved. Here, we study microvilli by vitrifying the Caenorhabditis elegans larvae and mouse intestinal tissues with high-pressure freezing, thinning them with cryo-focused ion-beam milling, followed by cryo-electron tomography and subtomogram averaging. We find that many radial nanometer bristles referred to as nanobristles project from the lateral surface of nematode and mouse microvilli. The C. elegans nanobristles are 37.5 nm long and 4.5 nm wide. Nanobristle formation requires a protocadherin family protein, CDH-8, in C. elegans. The loss of nanobristles in cdh-8 mutants slows down animal growth and ectopically increases the number of Y-shaped microvilli, the putative intermediate structures if microvilli split from tips. Our results reveal a potential role of nanobristles in separating microvilli and suggest that microvilli division may help generate nascent microvilli with uniformity.

An Online Nanoinformatics Platform Empowering Computational Modeling of Nanomaterials by Nanostructure Annotations and Machine Learning Toolkits.

Modern nanotechnology has generated numerous datasets from in vitro and in vivo studies on nanomaterials, with some available on nanoinformatics portals. However, these existing databases lack the digital data and tools suitable for machine learning studies. Here, we report a nanoinformatics platform that accurately annotates nanostructures into machine-readable data files and provides modeling toolkits. This platform, accessible to the public at https://vinas-toolbox.com/, has annotated nanostructures of 14 material types. The associated nanodescriptor data and assay test results are appropriate for modeling purposes. The modeling toolkits enable data standardization, data visualization, and machine learning model development to predict properties and bioactivities of new nanomaterials. Moreover, a library of virtual nanostructures with their predicted properties and bioactivities is available, directing the synthesis of new nanomaterials. This platform provides a data-driven computational modeling platform for the nanoscience community, significantly aiding in the development of safe and effective nanomaterials.

Self-Rectifying All-Optical Modulated Optoelectronic Multistates Memristor Crossbar Array for Neuromorphic Computing.

Researching optoelectronic memristors capable of integrating sensory and processing functions is essential for advancing the development of efficient neuromorphic vision. Here, we experimentally demonstrated an all-optical controlled and self-rectifying optoelectronic memristor (OEM) crossbar array with the function of multilevel storage under light stimuli. The NiO/TiO2 device exhibits an ultrahigh (>104) rectifying ratio (RR) thus overcoming the presence of sneak current. The reversible conductance modulation without electric signal involvement provides a novel way to realize ultrafast information processing. The proposed OEM array realized synaptic functions observed in the human brain, including long-term potentiation (LTP), long-term depression (LTD), paired-pulse facilitation (PPF), the transition from short-term memory (STM) to long-term memory (LTM), and learning experience behaviors successfully. The authors present a novel OEM crossbar that possesses complete light-modulation capabilities, potentially advancing the future development of efficient neuromorphic vision.

Novel Three-Dimensional Artificial Neural Network Based on an Eight-Layer Vertical Memristor with an Ultrahigh Rectify Ratio (>107) and an Ultrahigh Nonlinearity (>105) for Neuromorphic Computing.

In recent years, memristors have successfully demonstrated their significant potential in artificial neural networks (ANNs) and neuromorphic computing. Nonetheless, ANNs constructed by crossbar arrays suffer from cross-talk issues and low integration densities. Here, we propose an eight-layer three-dimensional (3D) vertical crossbar memristor with an ultrahigh rectify ratio (RR > 107) and an ultrahigh nonlinearity (>105) to overcome these limitations, which enables it to reach a >1 Tb array size without reading failure. Furthermore, the proposed 3D RRAM shows advanced endurance (>1010 cycles), retention (>104 s), and uniformity. In addition, several synaptic functions observed in the human brain were mimicked. On the basis of the advanced performance, we constructed a novel 3D ANN, whose learning efficiency and recognition accuracy were enhanced significantly compared with those of conventional single-layer ANNs. These findings hold promise for the development of highly efficient, precise, integrated, and stable VLSI neuromorphic computing systems.

Novel Two-Terminal Synapse/Neuron Based on an Antiferroelectric Hafnium Zirconium Oxide Device for Neuromorphic Computing.

Functionally diverse devices with artificial neuron and synapse properties are critical for neuromorphic systems. We present a two-terminal artificial leaky-integrate-fire (LIF) neuron based on 6 nm Hf0.1Zr0.9O2 (HZO) antiferroelectric (AFE) thin films and develop a synaptic device through work function (WF) engineering. LIF neuron characteristics, including integration, firing, and leakage, are achieved in W/HZO/W devices due to the accumulated polarization and spontaneous depolarization of AFE HZO films. By engineering the top electrode with asymmetric WFs, we found that Au/Ti/HZO/W devices exhibit synaptic weight plasticity, such as paired-pulse facilitation and long-term potentiation/depression, achieving >90% accuracy in digit recognition within constructed artificial neural network systems. These findings suggest that AFE HZO capacitor-based neurons and WF-engineered artificial synapses hold promise for constructing efficient spiking neuron networks and artificial neural networks, thereby advancing neuromorphic computing applications based on emerging AFE HZO devices.

The N-terminal intrinsically disordered region of Ncb5or docks with the cytochrome b5 core to form a helical motif that is of ancient origin.

NADH cytochrome b5 oxidoreductase (Ncb5or) is a cytosolic ferric reductase implicated in diabetes and neurological conditions. Ncb5or comprises cytochrome b5 (b5 ) and cytochrome b5 reductase (b5 R) domains separated by a CHORD-Sgt1 (CS) linker domain. Ncb5or redox activity depends on proper inter-domain interactions to mediate electron transfer from NADH or NADPH via FAD to heme. While full-length human Ncb5or has proven resistant to crystallization, we have succeeded in obtaining high-resolution atomic structures of the b5 domain and a construct containing the CS and b5 R domains (CS/b5 R). Ncb5or also contains an N-terminal intrinsically disordered region of 50 residues that has no homologs in other protein families in animals but features a distinctive, conserved L34 MDWIRL40 motif also present in reduced lateral root formation (RLF) protein in rice and increased recombination center 21 in baker's yeast, all attaching to a b5 domain. After unsuccessful attempts at crystallizing a human Ncb5or construct comprising the N-terminal region naturally fused to the b5 domain, we were able to obtain a high-resolution atomic structure of a recombinant rice RLF construct corresponding to residues 25-129 of human Ncb5or (52% sequence identity; 74% similarity). The structure reveals Trp120 (corresponding to invariant Trp37 in Ncb5or) to be part of an 11-residue α-helix (S116 QMDWLKLTRT126 ) packing against two of the four helices in the b5 domain that surround heme (α2 and α5). The Trp120 side chain forms a network of interactions with the side chains of four highly conserved residues corresponding to Tyr85 and Tyr88 (α2), Cys124 (α5), and Leu47 in Ncb5or. Circular dichroism measurements of human Ncb5or fragments further support a key role of Trp37 in nucleating the formation of the N-terminal helix, whose location in the N/b5 module suggests a role in regulating the function of this multi-domain redox enzyme. This study revealed for the first time an ancient origin of a helical motif in the N/b5 module as reflected by its existence in a class of cytochrome b5 proteins from three kingdoms among eukaryotes.