Two-photon synthetic aperture microscopy for minimally invasive fast 3D imaging of native subcellular behaviors in deep tissue.

Holistic understanding of physio-pathological processes requires noninvasive 3D imaging in deep tissue across multiple spatial and temporal scales to link diverse transient subcellular behaviors with long-term physiogenesis. Despite broad applications of two-photon microscopy (TPM), there remains an inevitable tradeoff among spatiotemporal resolution, imaging volumes, and durations due to the point-scanning scheme, accumulated phototoxicity, and optical aberrations. Here, we harnessed the concept of synthetic aperture radar in TPM to achieve aberration-corrected 3D imaging of subcellular dynamics at a millisecond scale for over 100,000 large volumes in deep tissue, with three orders of magnitude reduction in photobleaching. With its advantages, we identified direct intercellular communications through migrasome generation following traumatic brain injury, visualized the formation process of germinal center in the mouse lymph node, and characterized heterogeneous cellular states in the mouse visual cortex, opening up a horizon for intravital imaging to understand the organizations and functions of biological systems at a holistic level.

Iterative tomography with digital adaptive optics permits hour-long intravital observation of 3D subcellular dynamics at millisecond scale.

Long-term subcellular intravital imaging in mammals is vital to study diverse intercellular behaviors and organelle functions during native physiological processes. However, optical heterogeneity, tissue opacity, and phototoxicity pose great challenges. Here, we propose a computational imaging framework, termed digital adaptive optics scanning light-field mutual iterative tomography (DAOSLIMIT), featuring high-speed, high-resolution 3D imaging, tiled wavefront correction, and low phototoxicity with a compact system. By tomographic imaging of the entire volume simultaneously, we obtained volumetric imaging across 225 × 225 × 16 µm3, with a resolution of up to 220 nm laterally and 400 nm axially, at the millisecond scale, over hundreds of thousands of time points. To establish the capabilities, we investigated large-scale cell migration and neural activities in different species and observed various subcellular dynamics in mammals during neutrophil migration and tumor cell circulation.

Pervasive Chromatin-RNA Binding Protein Interactions Enable RNA-Based Regulation of Transcription.

Increasing evidence suggests that transcriptional control and chromatin activities at large involve regulatory RNAs, which likely enlist specific RNA-binding proteins (RBPs). Although multiple RBPs have been implicated in transcription control, it has remained unclear how extensively RBPs directly act on chromatin. We embarked on a large-scale RBP ChIP-seq analysis, revealing widespread RBP presence in active chromatin regions in the human genome. Like transcription factors (TFs), RBPs also show strong preference for hotspots in the genome, particularly gene promoters, where their association is frequently linked to transcriptional output. Unsupervised clustering reveals extensive co-association between TFs and RBPs, as exemplified by YY1, a known RNA-dependent TF, and RBM25, an RBP involved in splicing regulation. Remarkably, RBM25 depletion attenuates all YY1-dependent activities, including chromatin binding, DNA looping, and transcription. We propose that various RBPs may enhance network interaction through harnessing regulatory RNAs to control transcription.

An integrated imaging sensor for aberration-corrected 3D photography.

Planar digital image sensors facilitate broad applications in a wide range of areas1-5, and the number of pixels has scaled up rapidly in recent years2,6. However, the practical performance of imaging systems is fundamentally limited by spatially nonuniform optical aberrations originating from imperfect lenses or environmental disturbances7,8. Here we propose an integrated scanning light-field imaging sensor, termed a meta-imaging sensor, to achieve high-speed aberration-corrected three-dimensional photography for universal applications without additional hardware modifications. Instead of directly detecting a two-dimensional intensity projection, the meta-imaging sensor captures extra-fine four-dimensional light-field distributions through a vibrating coded microlens array, enabling flexible and precise synthesis of complex-field-modulated images in post-processing. Using the sensor, we achieve high-performance photography up to a gigapixel with a single spherical lens without a data prior, leading to orders-of-magnitude reductions in system capacity and costs for optical imaging. Even in the presence of dynamic atmosphere turbulence, the meta-imaging sensor enables multisite aberration correction across 1,000 arcseconds on an 80-centimetre ground-based telescope without reducing the acquisition speed, paving the way for high-resolution synoptic sky surveys. Moreover, high-density accurate depth maps can be retrieved simultaneously, facilitating diverse applications from autonomous driving to industrial inspections.

Virtual-scanning light-field microscopy for robust snapshot high-resolution volumetric imaging.

High-speed three-dimensional (3D) intravital imaging in animals is useful for studying transient subcellular interactions and functions in health and disease. Light-field microscopy (LFM) provides a computational solution for snapshot 3D imaging with low phototoxicity but is restricted by low resolution and reconstruction artifacts induced by optical aberrations, motion and noise. Here, we propose virtual-scanning LFM (VsLFM), a physics-based deep learning framework to increase the resolution of LFM up to the diffraction limit within a snapshot. By constructing a 40 GB high-resolution scanning LFM dataset across different species, we exploit physical priors between phase-correlated angular views to address the frequency aliasing problem. This enables us to bypass hardware scanning and associated motion artifacts. Here, we show that VsLFM achieves ultrafast 3D imaging of diverse processes such as the beating heart in embryonic zebrafish, voltage activity in Drosophila brains and neutrophil migration in the mouse liver at up to 500 volumes per second.

cfOmics: a cell-free multi-Omics database for diseases.

Liquid biopsy has emerged as a promising non-invasive approach for detecting, monitoring diseases, and predicting their recurrence. However, the effective utilization of liquid biopsy data to identify reliable biomarkers for various cancers and other diseases requires further exploration. Here, we present cfOmics, a web-accessible database (https://cfomics.ncRNAlab.org/) that integrates comprehensive multi-omics liquid biopsy data, including cfDNA, cfRNA based on next-generation sequencing, and proteome, metabolome based on mass-spectrometry data. As the first multi-omics database in the field, cfOmics encompasses a total of 17 distinct data types and 13 specimen variations across 69 disease conditions, with a collection of 11345 samples. Moreover, cfOmics includes reported potential biomarkers for reference. To facilitate effective analysis and visualization of multi-omics data, cfOmics offers powerful functionalities to its users. These functionalities include browsing, profile visualization, the Integrative Genomic Viewer, and correlation analysis, all centered around genes, microbes, or end-motifs. The primary objective of cfOmics is to assist researchers in the field of liquid biopsy by providing comprehensive multi-omics data. This enables them to explore cell-free data and extract profound insights that can significantly impact disease diagnosis, treatment monitoring, and management.

Persistent Tor-algebra for protein-protein interaction analysis.

Protein-protein interactions (PPIs) play crucial roles in almost all biological processes from cell-signaling and membrane transport to metabolism and immune systems. Efficient characterization of PPIs at the molecular level is key to the fundamental understanding of PPI mechanisms. Even with the gigantic amount of PPI models from graphs, networks, geometry and topology, it remains as a great challenge to design functional models that efficiently characterize the complicated multiphysical information within PPIs. Here we propose persistent Tor-algebra (PTA) model for a unified algebraic representation of the multiphysical interactions. Mathematically, our PTA is inherently algebraic data analysis. In our PTA model, protein structures and interactions are described as a series of face rings and Tor modules, from which PTA model is developed. The multiphysical information within/between biomolecules are implicitly characterized by PTA and further represented as PTA barcodes. To test our PTA models, we consider PTA-based ensemble learning for PPI binding affinity prediction. The two most commonly used datasets, i.e. SKEMPI and AB-Bind, are employed. It has been found that our model outperforms all the existing models as far as we know. Mathematically, our PTA model provides a highly efficient way for the characterization of molecular structures and interactions.

Pathformer: a biological pathway informed transformer for disease diagnosis and prognosis using multi-omics data.

MOTIVATION: Multi-omics data provide a comprehensive view of gene regulation at multiple levels, which is helpful in achieving accurate diagnosis of complex diseases like cancer. However, conventional integration methods rarely utilize prior biological knowledge and lack interpretability. RESULTS: To integrate various multi-omics data of tissue and liquid biopsies for disease diagnosis and prognosis, we developed a biological pathway informed Transformer, Pathformer. It embeds multi-omics input with a compacted multi-modal vector and a pathway-based sparse neural network. Pathformer also leverages criss-cross attention mechanism to capture the crosstalk between different pathways and modalities. We first benchmarked Pathformer with 18 comparable methods on multiple cancer datasets, where Pathformer outperformed all the other methods, with an average improvement of 6.3%-14.7% in F1 score for cancer survival prediction, 5.1%-12% for cancer stage prediction, and 8.1%-13.6% for cancer drug response prediction. Subsequently, for cancer prognosis prediction based on tissue multi-omics data, we used a case study to demonstrate the biological interpretability of Pathformer by identifying key pathways and their biological crosstalk. Then, for cancer early diagnosis based on liquid biopsy data, we used plasma and platelet datasets to demonstrate Pathformer's potential of clinical applications in cancer screening. Moreover, we revealed deregulation of interesting pathways (e.g. scavenger receptor pathway) and their crosstalk in cancer patients' blood, providing potential candidate targets for cancer microenvironment study. AVAILABILITY AND IMPLEMENTATION: Pathformer is implemented and freely available at https://github.com/lulab/Pathformer.

Circulating small extracellular vesicle-based miRNA classifier for follicular thyroid carcinoma: a diagnostic study.

BACKGROUND: The diagnosis of follicular thyroid carcinoma (FTC) prior to surgery remains a major challenge in the clinic. METHODS: This multicentre diagnostic study involved 41 and 150 age- and sex-matched patients in the training cohort and validation cohort, respectively. The diagnostic properties of circulating small extracellular vesicle (sEV)-associated and cell-free RNAs were compared by RNA sequencing in the training cohort. Subsequently, using a quantitative real-time polymerase chain reaction (qRT‒PCR) assay, high-quality candidates were identified to construct an RNA classifier for FTC and verified in the validation cohort. The parallel expression, stability and influence of the RNA classifier on surgical strategy were also investigated. RESULTS: The diagnostic properties of sEV long RNAs, cell-free long RNAs and sEV microRNAs (miRNAs) were comparable and superior to those of cell-free miRNAs in RNA sequencing. Given the clinical application, the circulating sEV miRNA (CirsEV-miR) classifier was developed from five miRNAs based on qRT‒PCR data, which could well identify FTC patients (area under curve [AUC] of 0.924 in the training cohort and 0.844 in the multicentre validation cohort). Further tests revealed that the CirsEV-miR score was significantly correlated with the tumour burden, and the levels of sEV miRNAs were also higher in sEVs from the FTC cell line, organoid and tissue. Additionally, circulating sEV miRNAs remained constant after different treatments, and the addition of the CirsEV-miR classifier as a biomarker improves the current surgical strategy. CONCLUSIONS: The CirsEV-miR classifier could serve as a noninvasive, convenient, specific and stable auxiliary test to help diagnose FTC following ultrasonography.

Highly Reversible Molecular Photoswitches with Transition Metal Dichalcogenides Electrodes.

The molecule-electrode coupling plays an essential role in photoresponsive devices with photochromic molecules, and the strong coupling between the molecule and the conventional electrodes leads to/ the quenching effect and limits the reversibility of molecular photoswitches. In this work, we developed a strategy of using transition metal dichalcogenides (TMDCs) electrodes to fabricate the thiol azobenzene (TAB) self-assembled monolayers (SAMs) junctions with the eutectic gallium-indium (EGaIn) technique. The current-voltage characteristics of the EGaIn/GaOx //TAB/TMDCs photoswitches showed an almost 100% reversible photoswitching behavior, which increased by ∼28% compared to EGaIn/GaOx //TAB/AuTS photoswitches. Density functional theory (DFT) calculations showed the coupling strength of the TAB-TMDCs electrode decreased by 42% compared to that of the TAB-AuTS electrode, giving rise to improved reversibility. our work demonstrated the feasibility of 2D TMDCs for fabricating SAMs-based photoswitches with unprecedentedly high reversibility.

Sodium Octahydridotriborate as a Solid Electrolyte with Excellent Stability Against Sodium-Metal Anode.

Solid-state sodium metal batteries have been extensively investigated because of their potential to improve safety, cost-effectiveness, and energy density. The development of such batteries urgently required a solid-state electrolyte with fast Na-ion conduction and favorable interfacial compatibility. Herein, the progress on developing the NaB3H8 solid-state electrolytes is reported, which show a liquid-like ionic conductivity of 0.05 S cm-1 at 56 °C with an activation energy of 0.35 eV after an order-disorder phase transformation, matching or surpassing the best single-anion hydridoborate conductors investigated up to now. The steady polarization voltage and significantly decreased resistance are achieved in the symmetric Na/NaB3H8/Na cell, indicating the great electrochemical stability and favorable interfacial contact with the Na metal of NaB3H8. Furthermore, a Na/NaB3H8/TiS2 battery, the first high-rate (up to 1 C) solid-state sodium metal battery using the single-anion hydridoborate electrolyte, is demonstrated, which exhibits superior rate capability (168.2 mAh g-1 at 0.1 C and 141.2 mAh g-1 at 1 C) and long-term cycling stability (70.9% capacity retention at 1 C after 300 cycles) at 30 °C. This work may present a new possibility to solve the interfacial limitations and find a new group of solid-state electrolytes for high-performance sodium metal batteries.

Soybean steroids improve crop abiotic stress tolerance and increase yield.

Sterols have long been associated with diverse fields, such as cancer treatment, drug development, and plant growth; however, their underlying mechanisms and functions remain enigmatic. Here, we unveil a critical role played by a GmNF-YC9-mediated CCAAT-box transcription complex in modulating the steroid metabolism pathway within soybeans. Specifically, this complex directly activates squalene monooxygenase (GmSQE1), which is a rate-limiting enzyme in steroid synthesis. Our findings demonstrate that overexpression of either GmNF-YC9 or GmSQE1 significantly enhances soybean stress tolerance, while the inhibition of SQE weakens this tolerance. Field experiments conducted over two seasons further reveal increased yields per plant in both GmNF-YC9 and GmSQE1 overexpressing plants under drought stress conditions. This enhanced stress tolerance is attributed to the reduction of abiotic stress-induced cell oxidative damage. Transcriptome and metabolome analyses shed light on the upregulation of multiple sterol compounds, including fucosterol and soyasaponin II, in GmNF-YC9 and GmSQE1 overexpressing soybean plants under stress conditions. Intriguingly, the application of soybean steroids, including fucosterol and soyasaponin II, significantly improves drought tolerance in soybean, wheat, foxtail millet, and maize. These findings underscore the pivotal role of soybean steroids in countering oxidative stress in plants and offer a new research strategy for enhancing crop stress tolerance and quality from gene regulation to chemical intervention.

Spatiotemporal heterogeneity of LMOD1 expression summarizes two modes of cell communication in colorectal cancer.

Cellular communication (CC) influences tumor development by mediating intercellular junctions between cells. However, the role and underlying mechanisms of CC in malignant transformation remain unknown. Here, we investigated the spatiotemporal heterogeneity of CC molecular expression during malignant transformation. It was found that although both tight junctions (TJs) and gap junctions (GJs) were involved in maintaining the tumor microenvironment (TME), they exhibited opposite characteristics. Mechanistically, for epithelial cells (parenchymal component), the expression of TJ molecules consistently decreased during normal-cancer transformation and is a potential oncogenic factor. For fibroblasts (mesenchymal component), the expression of GJs consistently increased during normal-cancer transformation and is a potential oncogenic factor. In addition, the molecular profiles of TJs and GJs were used to stratify colorectal cancer (CRC) patients, where subtypes characterized by high GJ levels and low TJ levels exhibited enhanced mesenchymal signals. Importantly, we propose that leiomodin 1 (LMOD1) is biphasic, with features of both TJs and GJs. LMOD1 not only promotes the activation of cancer-associated fibroblasts (CAFs) but also inhibits the Epithelial-mesenchymal transition (EMT) program in cancer cells. In conclusion, these findings demonstrate the molecular heterogeneity of CC and provide new insights into further understanding of TME heterogeneity.

A dual-reference study design for understanding and improving AAV genome size analysis.

Recombinant adeno-associated virus (rAAV) is the leading platform of gene delivery for its long-lasting gene transformation and low immunogenicity. Characterization of the integrity and purity of the rAAV genome is critical to ensure clinical potency and safety. However, current rAAV genome characterization methods that can provide size assessment are either time-consuming or not easily accessible to general labs. Additionally, there is a lack of right reference standard for analyzing long single-stranded DNA (ssDNA) fragments. Here, we have developed an ssDNA assay on a microfluidic capillary electrophoresis platform using ssDNA reference standard. This assay provides size calling for ssDNA fragment, a detection sensitivity at ∼89 pg/µL (3 × 1010  GC/mL AAV) for 5.1 kb ssDNA fragment, and a turnaround time at ∼100 s per sample with a high throughput sample analyzing capability. Moreover, we have observed that the annealing of AAV ssDNA subsequent to its release from the capsid might introduce an additional double-stranded DNA (dsDNA) peak. This phenomenon is dependent on the sample processing workflow. To avoid the risk of mischaracterization, we recommend the use of dual-reference standards in combination with other orthogonal methods to have a comprehensive understanding of the rAAV genome size and integrity.

Palladium-Catalyzed Synthesis of Indanone via C-H Annulation Reaction of Aldehydes with Norbornenes.

A novel methodology for the synthesis of indanone derivates has been developed. The palladium-catalyzed annulation reaction of o-bromobenzaldehydes with norbornene derivatives is achieved through extremely concise reaction processes. The indanone skeleton was established directly via C-H activation of the aldehyde group under a mild reaction condition. This method is simple and practical, which simplified the traditional synthesis method for the rapid construction of indanone.

Liver receptor homolog-1: structures, related diseases, and drug discovery.

Liver receptor homolog-1 (LRH-1), a member of the nuclear receptor superfamily, is a ligand-regulated transcription factor that plays crucial roles in metabolism, development, and immunity. Despite being classified as an 'orphan' receptor due to the ongoing debate surrounding its endogenous ligands, recent researches have demonstrated that LRH-1 can be modulated by various synthetic ligands. This highlights the potential of LRH-1 as an attractive drug target for the treatment of inflammation, metabolic disorders, and cancer. In this review, we provide an overview of the structural basis, functional activities, associated diseases, and advancements in therapeutic ligand research targeting LRH-1.

Discovery and pharmacological characterization of 1,2,3,4-tetrahydroquinoline derivatives as RORγ inverse agonists against prostate cancer.

The retinoic acid receptor-related orphan receptor γ (RORγ) is regarded as an attractive therapeutic target for the treatment of prostate cancer. Herein, we report the identification, optimization, and evaluation of 1,2,3,4-tetrahydroquinoline derivatives as novel RORγ inverse agonists, starting from high throughput screening using a thermal stability shift assay (TSA). The representative compounds 13e (designated as XY039) and 14a (designated as XY077) effectively inhibited the RORγ transcriptional activity and exhibited excellent selectivity against other nuclear receptor subtypes. The structural basis for their inhibitory potency was elucidated through the crystallographic study of RORγ LBD complex with 13e. Both 13e and 14a demonstrated reasonable antiproliferative activity, potently inhibited colony formation and the expression of AR, AR regulated genes, and other oncogene in AR positive prostate cancer cell lines. Moreover, 13e and 14a effectively suppressed tumor growth in a 22Rv1 xenograft tumor model in mice. This work provides new and valuable lead compounds for further development of drugs against prostate cancer.

Adenoviral vectors infect B lymphocytes in vivo.

B cells are the antibody-producing arm of the adaptive immune system and play a critical role in controlling pathogens. Several groups have now demonstrated the feasibility of using engineered B cells as a therapy, including infectious disease control and gene therapy of serum deficiencies. These studies have largely utilized ex vivo modification of the cells. Direct in vivo engineering would be of utility to the field, particularly in infectious disease control where the infrastructure needs of ex vivo cell modification would make a broad vaccination campaign highly challenging. In this study we demonstrate that engineered adenoviral vectors are capable of efficiently transducing murine and human primary B cells both ex vivo and in vivo. We found that unmodified human adenovirus C5 was capable of infecting B cells in vivo, likely due to interactions between the virus penton base protein and integrins. We further describe vector modification with B cell-specific gene promoters and successfully restrict transgene expression to B cells, resulting in a strong reduction in gene expression from the liver, the main site of human adenovirus C5 infection in vivo.

Widespread autogenous mRNA-protein interactions detected by CLIP-seq.

Autogenous interactions between mRNAs and the proteins they encode are implicated in cellular feedback-loop regulation, but their extent and mechanistic foundation are unclear. It was recently hypothesized that such interactions may be common, reflecting the role of intrinsic nucleobase-amino acid affinities in shaping the genetic code's structure. Here we analyze a comprehensive set of CLIP-seq experiments involving multiple protocols and report on widespread autogenous interactions across different organisms. Specifically, 230 of 341 (67%) studied RNA-binding proteins (RBPs) interact with their own mRNAs, with a heavy enrichment among high-confidence hits and a preference for coding sequence binding. We account for different confounding variables, including physical (overexpression and proximity during translation), methodological (difference in CLIP protocols, peak callers and cell types) and statistical (treatment of null backgrounds). In particular, we demonstrate a high statistical significance of autogenous interactions by sampling null distributions of fixed-margin interaction matrices. Furthermore, we study the dependence of autogenous binding on the presence of RNA-binding motifs and structured domains in RBPs. Finally, we show that intrinsic nucleobase-amino acid affinities favor co-aligned binding between mRNA coding regions and the proteins they encode. Our results suggest a central role for autogenous interactions in RBP regulation and support the possibility of a fundamental connection between coding and binding.

POSTAR3: an updated platform for exploring post-transcriptional regulation coordinated by RNA-binding proteins.

RNA-binding proteins (RBPs) play key roles in post-transcriptional regulation. Accurate identification of RBP binding sites in multiple cell lines and tissue types from diverse species is a fundamental endeavor towards understanding the regulatory mechanisms of RBPs under both physiological and pathological conditions. Our POSTAR annotation processes make use of publicly available large-scale CLIP-seq datasets and external functional genomic annotations to generate a comprehensive map of RBP binding sites and their association with other regulatory events as well as functional variants. Here, we present POSTAR3, an updated database with improvements in data collection, annotation infrastructure, and analysis that support the annotation of post-transcriptional regulation in multiple species including: we made a comprehensive update on the CLIP-seq and Ribo-seq datasets which cover more biological conditions, technologies, and species; we added RNA secondary structure profiling for RBP binding sites; we provided miRNA-mediated degradation events validated by degradome-seq; we included RBP binding sites at circRNA junction regions; we expanded the annotation of RBP binding sites, particularly using updated genomic variants and mutations associated with diseases. POSTAR3 is freely available at http://postar.ncrnalab.org.