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Biology subjects

Cai, L.

Publications and source records attributed to Cai, L..

At least 37 records · Page 2Linked to original sources

Regenerative base editing enables deep lineage recording

Reconstructing the lineage histories of individual cells can reveal the dynamics of developmental and disease processes. In engineered recording systems, cells stochastically edit synthetic barcode sequences as they proliferate, creating distinct, heritable edit patterns that can be used to reconstruct the lineage trees relating individual cells in a manner analogous to phylogenetic reconstruction. However, recording depth is often limited by the kinetics of the editing process: the rate of editing declines exponentially over time for an array of independently editable targets, leading to most edits occurring in early generations. Here, we introduce the hypercascade, a regenerative molecular recording system that takes advantage of the predictability of A-to-G base editing to progressively create new target sites over time. The hypercascade packs 4 editable target sites in every 20 bp of sequence, enabling high density information storage. More importantly, the hypercascades regenerative logic leads to an approximately constant rate of mutation accumulation over time. This in turn facilitates reconstruction of deep lineage relationships. We demonstrate this by reconstructing trees spanning 23 days of editing and approximately 17 generations after a single polyclonal engineering step. Finally, simulations show that the hypercascade has the potential to record chromatin state transition dynamics across multiple genomic loci in parallel. The hypercascade thus provides a flexible and broadly useful tool for molecular recording.

bioengineering↗

An agentic framework turns patient-sourced records into a multimodal map of ALS heterogeneity

ALS progression is multidimensional, yet fragmented records and scalar outcomes obscure how patients move through disease states and how those states relate to molecular variation. MEDSTREM converts patient-held medical-record images into standardised longitudinal data, enabling bottom-up cohort construction. Using MEDSTREM-structured records from more than 8,000 AskHelpU participants together with PRO-ACT and Answer ALS, we developed DynaALS, the ALS Disease Dynamics Atlas. DynaALS represents ALS as a dynamic patient-state manifold that captures distinct directions of deterioration and patient movement between them over time. DynaALS retrieved population-referenced future states and decoded them into multidimensional clinical profiles without requiring patient-specific longitudinal histories. Motor-neuron RNA and chromatin profiles linked DynaALS states to developmental and regulatory programs, while neuromuscular-organoid single-cell multi-omics converged on a neural-developmental Netrin-DCC signalling axis across interacting cell types. By coupling MEDSTREM-enabled data construction to dynamic state modelling, DynaALS establishes a transferable patient-state engine for predictive and biologically interpretable disease models.

bioinformatics↗

Fast Loading and Transformation of Large-Volume Bioimaging Data Consistently Approaching the I/O Peak Speed

High-resolution large-volume biological imaging techniques are now widely used in biological research, but inefficiencies in data processing and visualization persist due to bottlenecks in loading/saving pipelines and limitations of conventional pyramid formats. To address these issues, we have decoupled data loading process into reading from disk and in-memory decompression, while data saving has been separated into in-memory compression and writing to disk. This approach allows us to dedicate more CPU cores to decompression and compression tasks, optimizing resource allocation and maximizing disk I/O throughput. As a result, both loading and saving processes operate near the disks peak data transfer capacity. Further, we integrated a video stream-inspired format into the pyramid structure, allowing direct access to regions of interest (ROIs) without loading extraneous data into RAM, reducing memory overhead. Compared to the latest methods, our approach improves pyramid data transformation efficiency by at least 6x and dramatically accelerates downstream tasks like visualization and deep learning inference. TeaserNovel bioimaging data processing pipeline achieves near-peak I/O throughput via decoupled architecture and video-formatting.

bioinformatics↗

Synaptic MEMOIR: mapping individual synapses of neurons with protein barcodes

Obtaining wiring diagrams of brains has been a major achievement for neuroscience. However, an underlying challenge in connectomics is the fundamental tradeoff between the imaging resolution needed to resolve synapses and the volume of the brain that can be imaged. For example, electron microscopy (EM) visualizes synaptic sites with ~5 nm resolution, but is difficult to scale beyond volumes of 1 mm3. Here, we present Synaptic MEMOIR (Memory with Engineered Mutagenesis with Optical in situ Readout) that enables imaging of neuronal projections in animal brains with single-synapse resolution. Synaptic MEMOIR is built around three key design features. First, protein barcodes are transported to synapses to allow matching of synaptic barcodes to cell body barcodes without high resolution imaging and the error-prone process of tracing neuronal processes across long distances. Second, Synaptic MEMOIR uses continuous mutagenesis to generate a large diversity of barcodes to uniquely label cell bodies and synapses. Last, the timing of recombination and transport can be tuned to record synaptic age or projection information. Combining these features, we demonstrated projection mapping of 113 neurons in the Drosophila melanogaster optic lobe in a volume of 9.5 million m3. Because synapses are identified by transported barcodes with optical microscopy at 300 nm resolution, this approach can potentially scale to much larger volumes, similar at least to those imaged in recent mouse brain transcriptomics atlases. In addition, synaptic MEMOIR can match barcodes across brain sections, and does not require tissue clearing to track long-range projections. Together, these results provide the foundation for a scalable optical image-based system for reconstructing the neural wiring diagrams of brains across different developmental stages, genetic backgrounds and perturbations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=46 SRC="FIGDIR/small/690442v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@8363cdorg.highwire.dtl.DTLVardef@d3240org.highwire.dtl.DTLVardef@5e2793org.highwire.dtl.DTLVardef@1784f2a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

A reference genome and transcriptome of haustorial development in Pedicularis groenlandica reveal diverse trajectories of haustoria-associated gene evolution in parasitic plants

O_LINovel traits frequently evolve by co-opting existing genetic pathways through direct repurposing of existing genes or neofunctionalization of duplicated genes. Parasitism represents a major innovation in plants, where a novel organ--the haustorium--evolved to penetrate hosts and extract water and nutrients. Previous studies hypothesized that haustoria-associated genes primarily evolve from root and pollen-associated pathways. C_LIO_LITo examine evolutionary trajectories of haustoria-associated genes, we generated a chromosome-scale genome of Pedicularis groenlandica (Orobanchaceae) and sampled transcriptomes throughout haustorial development. We examined differential expression of haustoria-associated genes and their paralogs and investigated orthology among haustoria-associated genes in five parasitic plants. C_LIO_LIWe identified 5,635 haustoria-associated genes in P. groenlandica, of which a greater proportion were associated with pollen tubes (67%) than roots (33%), evidenced by being differentially expressed in pollen tubes, nested within pollen tube-associated gene families, or both. Haustoria-associated genes with paralogs that arose after the evolution of parasitism in Orobanchaceae are more likely to be uniquely expressed in haustoria, consistent with neofunctionalization. C_LIO_LIOur results support both pleiotropy and neofunctionalization as mechanisms by which genetic pathways are co-opted for haustorial function. Haustoria-associated genes are highly lineage-specific, highlighting a dynamic and ongoing process of haustorial co-option of genes among parasitic plant lineages. C_LI

evolutionary biology↗

Global disruption of plant biogeography by non-native species

Biogeographical regions reflect differences in biotic composition resulting from long-term isolation and biogeographical processes, but how human-mediated introductions of non-native species have altered these biogeographical patterns remains unclear. Using global distribution data of 279,441 native and 10,067 non-native seed plant species, we analyzed the impact of species introductions on global organization of biogeographical regions. We show that species introductions have disrupted plant biogeography, causing the loss of distinct floristic realms and subrealms. Due to the impact of non-native species, geographic proximity and dispersal barriers are less important-- particularly as trade-facilitated species exchange drives floristic homogenization--while environmental factors remain critical in structuring floristic regions. Our findings reveal that plant introductions erode biogeographical distinctness and highlight the urgent need for coordinated action to protect native biotas.

ecology↗

Generalized brain-state modeling with KenazLBM

The large-scale functional state of a human brain remains difficult to characterize, much less predict. Regardless, techniques have been engineered to electrically neuromodulate the brain to treat a subset of neurologic and psychiatric disorders with moderate efficacy. Accurate characterization of a brains instantaneous functional state has stymied the development of more effective neuromodulation paradigms. Advanced computational methods are required to address this gap and enable large-scale neuroscience. Here we define the concept of generalized brain-state modeling across humans as Large Brain-State Modeling (LBM) and present KenazLBM as the worlds first example. KenazLBM can instantaneously characterize the functional state of a persons brain with raw iEEG data, and predict future brain-states. KenazLBM was trained on over 17.9 billion unique multichannel tokens from people undergoing intracranial electroencephalography (iEEG) recordings, and has learned to interrelate brain-states between people into a common interpretable topology. Most importantly, the model generalizes to unseen subject data with significant recording channel heterogeneity from the training set. We offer KenazLBM as a first generalized brain-state model to serve as a new paradigm of basic neuroscience inquiry and potential translation into neuromodulation therapeutics.

neuroscience↗

YY1 relieves p300 autoinhibition to promote histone acetylation in advanced prostate cancer, enhancing the oncogenic signaling of Androgen Receptor Splice Variant 7

Genetic and epigenetic aberrations often act in concert to establish oncogenic transcriptomic programs in aggressive cancers. For example, the development of castration-resistant prostate cancer (CRPC), an advanced prostate cancer form, is closely associated with over-expression and/or hyper-activation of transcription factors (TFs) such as Androgen Receptor (AR) and Yin Yang 1 (YY1), as well as p300, a prominent histone acetyltransferase. How exactly these cancer-related lesions are coordinated to generate a malignant cell state remains elusive. Here, we demonstrate that YY1, which is frequently over-expressed in advanced prostate cancers, allosterically stimulates the acetyltransferase activity of p300 in cis, leading to the globally elevated acetylation of histone H3 lysine 18 and 27 (H3K18ac and H3K27ac). Mechanistically, YY1s N-terminal activation domain (AD) directly interacts with p300s TAZ2 domain, relieving the autoinhibition of p300 to facilitate substrate acetylation. Our integrated genome-wide mapping and transcriptomic studies reveal significant co-localization of genomic binding sites of YY1, androgen receptor splice variant 7 (AR-V7, a constitutively active form of AR) and p300 in CRPC cells, where the YY1-mediated p300 activation and resultant histone acetylation increases promote the oncogenic gene-expression programs downstream of YY1 and AR/AR-V7. Both in vitro and in vivo functional assays demonstrate a critical requirement of the above signaling for the advanced disease progression and drug resistance seen in CRPC. Altogether, this study uncovers that YY1 acts to alleviate p300s autoinhibition at target genes co-bound by oncogenic TFs (YY1 and/or AR/AR-V7) in CRPC, thereby sustaining tumorigenicity. Additionally, the blockade of YY1-mediated gene activation resensitizes CRPC to treatment to the clinic anti-AR agent (enzalutamide), which provides a rationale for overcoming the therapeutic resistance often seen in advanced prostate cancers.

cancer biology↗

Untangling overlapping barcodes in spatial genomics data

Difficulty in resolving spatially overlapping barcodes is a major bottleneck for imaging-based spatial genomics methods. Here, we present an approach for untangling spatially overlapping barcodes by using strong encoding and global optimization to reduce spurious solutions resulting from recombinations of barcode signals. We demonstrate experimentally that cellular regions with average local densities of 127 barcodes per {micro}m2 can be decoded with an estimated FDR of less than 4%, enabling a new type of super-resolution microscopy by coding.

bioengineering↗

Spatial Proofreading Amplification of in situ Transcript and Protein Signals

Spatial transcriptomics experiments greatly benefit from brighter signals that improve detection efficiency and shorten imaging times. Here, we introduce a new enzyme-free signal amplification method inspired by the kinetic proofreading principle, in which short oligonucleotide probes are iteratively deposited at their target site and covalently photo-crosslinked to the cell, forming highly stable DNA assemblies. The method results in more than 500-fold signal amplification and supports multiplex readout capabilities.

molecular biology↗

Oblique Thick Light-Sheet Microscopy with Spatiotemporal 3D Localization for RNA Imaging in Intact 50 μm-Thick Sections

Neuron typing in intact brain sections demands 3D imaging reconciling thickness compatibility with large-area coverage--a persistent challenge for RNA imaging methods limited by either restricted fields-of-view (<1 mm2) or thin-section constraints (<20 m). Here we introduce oblique thick light-sheet microscopy integrated with spatiotemporal 3D localization, enabling multiplexed RNA imaging across 50 m-thick tissue sections and centimeter-scale regions. The 45{degrees} illumination geometry achieves optical-interference-free imaging in >100 m-thick tissues during single-plane scans, while a spatiotemporal localization algorithm recovers submicron resolution by pinpointing fluorescence in situ hybridization (FISH) spots within volumetric excitation. This strategy reveals layer-spanning neuronal distributions and region-specific expression gradients unattainable with conventional RNA imaging approaches. By resolving the historical trade-off between imaging depth and spatial coverage, our platform advances whole-brain transcriptomics, enabling 3D neuron typing capability critical for deciphering brain-wide cellular architectures.

biophysics↗

Neural organoids protect engineered heart tissues from glucolipotoxicity by transferring versican in a co-culture system

Metabolic disorders could cause dysregulated glucose and lipid at the systemic level, but how inter-tissue/organ communications contribute to glucolipotoxicity is difficult to dissect in animal models. To solve this problem, myocardium and nerve tissues were modeled by 3D engineered heart tissues (EHTs) and neural organoids (NOs), which were co-cultured in a generalized medium with normal or elevated glucose/fatty acid contents. Morphology, gene expression, cell death and functional assessments detected no apparent alterations of EHTs and NOs in co-culture under normal conditions. By contrast, NOs significantly ameliorated glucolipotoxicity in EHTs. Transcriptomic and protein secretion assays identified the extracellular matrix protein versican as a key molecule that was transferred from NOs into EHTs in the high-glucose/fatty acid condition. Recombinant versican protein treatment was sufficient to reduce glucolipotoxicity in EHTs. Adeno-associated virus-delivered versican overexpression was sufficient to ameliorate cardiac dysfunction in a murine model of diabetic cardiomyopathy. These data provide the proof-of-concept evidence that inter-tissue/organ communications exist in the co-culture of engineered tissues and organoids, which could be systemically studied to explore potential pathological mechanisms and therapeutic strategies for multi-organ diseases in vitro.

cell biology↗

Corn rust population genomics reveals a cryptic virulent group and adaptive effectorome

Understanding the population structure of pathogens and the genetic determinants driving virulence gains is crucial for managing epidemic plant diseases. Puccinia polysora, a giga-scale fungal pathogen causing southern corn rust, has posed significant threat to global food security recently. Traditionally, P. polysora was considered clonal with minimal genetic variation. However, our population genomic and transcriptomic studies conducted in China, the emerging epicentre of the disease, have challenged this view. By adopting variant analyses appropriate to the dikaryotic nature of the pathogen, we discovered an unexpectedly clear population structure with six distinct groups. A cryptic group exhibits high virulence, facilitated by group-specific variation, and diversification of effectors. Although the Chinese population of P. polysora is predominantly asexual, internuclear exchange on some chromosomes have introduced recombination signals. The comprehensive pan-effectorome analyses revealed substantial presence/absence variation and alternative splicing events on effectors, shaping a highly adaptive effector repertoire in P. polysora. In conclusion, our findings highlight the tandem mapping on exploring clear genetic structure of dikaryotic species and reported the emergence of a virulent group and an adaptive effectorome of P. polysora. Effective containment strategies must be flexible to counter the threats posed by the unexpectedly dynamic evolution of this pathogen.

molecular biology↗

The influence of ceftriaxone, ceftazidime-avibactam, and piperacillin-tazobactam on the gut microbiota

PurposeThe administration of antibiotics can induce dysbiosis of the gut microbiota, leading to diseases, e.g., irritable bowel syndrome, metabolic syndrome, and Clostridium difficile infection. However, the specific effects of different {beta}-lactam antibiotics on the dysbiosis of the gut microbiota remain poorly understood, particularly in human studies. MethodsThis study assessed the impacts of ceftriaxone, ceftazidime-avibactam, and piperacillin-tazobactam on the diversity, composition, and bacterial interactions within the gut microbiota at days 1, 6, and 37 after administration. ResultsAll three antibiotics significantly altered beta diversity of the gut microbiota by day 6, with ceftriaxone showing the most prolonged effects. Changes in the composition of the gut microbiota were more similar between the ceftazidime-avibactam and piperacillin-tazobactam groups and differed markedly from those in the ceftriaxone group. Consistent with beta diversity changes, bacterial interaction networks showed greater and longer-lasting disruptions of bacterial interaction in the gut microbiota in the ceftriaxone group compared to the ceftazidime-avibactam and piperacillin-tazobactam groups. ConclusionThese findings highlight distinct patterns of microbiota disruption following ceftriaxone, ceftazidime-avibactam, and piperacillin-tazobactam treatments and provide insights for mitigating dysbiosis of the gut microbiota during {beta}-lactam therapy.

microbiology↗

L-2-hydroxyglutarate impairs neuronal differentiation through epigenetic activation of MYC expression

High levels of L- and D-2-hydroxyglutarate, the reduced forms of -ketoglutarate (KG), are implicated in human neurodevelopmental disorders and cancer. Both enantiomers exert effects on epigenetics by modulating a family of KG-dependent dioxygenases involved in histone, DNA and RNA demethylation. L-2HG dehydrogenase (L2HGDH) converts L-2HG to KG. Its deficiency is a rare, autosomal recessive inborn error of metabolism (IEM) characterized by systemic elevations of L-2HG, progressive neurological disability and a high risk of malignancy in the brain. The mechanisms behind these aberrations are unknown. Here we used an isogenic, patient-derived induced pluripotent stem cell (iPSC) system to study the impact of L2HGDH deficiency on neural progenitor cell (NPC) function and neuronal differentiation. We demonstrate that L2HGDH deficiency causes accumulation of L-2HG, NPC hyperproliferation, increased clonogenicity, excessive growth, and defective neuronal differentiation in 2D cultures and cortical spheroids. Editing the L2HGDH locus to wild-type reverses these effects. Blocking L-2HG accumulation in NPCs with a glutaminase inhibitor also induces neuronal differentiation. L-2HG-dependent inhibition of KDM5 histone demethylases leads to widespread retention of H3K4me2 and H3K4me3, markers of active gene expression. These marks are prominently elevated at the MYC locus in L2HGDH-deficient cells, and consequently cells express high MYC both in 2D culture and in many distinct cell types within cortical spheroids. Although thousands of loci display altered histone methylation, genetically or pharmacologically normalizing MYC is sufficient to completely reverse defective neuronal differentiation. These data indicate that the primary metabolic disturbance in an iPSC IEM model activates the MYC oncogene, favoring stem cell self-renewal and suppressing lineage commitment to neurons.

genetics↗

Imputation Disparities Driven by Recent Selectionand Their Impact on Disease Risk Estimation in East and Southeast Asian Populations

Using genotype data consisting of 8,316 individuals, we systematically evaluated imputation performance across six state-of-the-art reference panels for Chinese and Thai populations. A substantial proportion of variants identified through whole-genome sequencing, especially low-frequency variants, remained undetected by existing reference panels. In the Chinese population, the TOPMed panel required an R2 threshold of 0.60-0.70 to achieve comparable imputation accuracy of the ChinaMAP panel without R2 filtering, challenging the standard practice of applying a fixed R2 threshold for downstream analyses. Regional analysis highlighted the role of recent selection in imputation discrepancies and revealed an enrichment of immune-related genes in poorly imputed regions. In addition, we showed that the selection of reference panels and R2 thresholds could significantly influence estimation of polygenic risk score for disease prediction. These findings underscore the importance of developing ancestrally diverse reference panels and provide valuable guidelines for improving genotype imputation in East and Southeast Asian populations.

genomics↗

Attention Guided Mechanism Interpretable Drug-Gene Interaction (MIDI) Modeling for Cancer Drug Response Prediction and Target Effect Explanation

Cancer drug discovery using genetic information is still poorly developed. Precisely locating drug atoms and explaining the targeting effect is crucial in precision medicine since it helps understand the drugs mechanism of action. Much data has been collected regarding drug response against cancer cell lines, and many models predict the drug response based on genomic information. However, to our knowledge, none of the data-driven techniques propose to detect the targeting mechanism of small drug molecules against genetic targets. In this work, we propose MIDI (Mechanism Interpretable Drug-Gene Interaction) model to delve deep into the targeting relation between drug molecules against genetic patterns. We show that purely based on a data-driven approach, the attention mechanism in our model could capture the important binding effect of small molecules towards gene targets. We provide both theoretical derivation and experiment results to show the information flow regarding the attention mechanism. In the meantime, we demonstrate that our model presents much higher prediction performance with the interpretation mechanism than the other state-of-the-art drug response prediction models.

cancer biology↗

scBiopsy-seq: a platform for temporal single-cell RNA-seq analysis

The development of temporal single-cell RNA-seq (scRNA-seq) assay enabled us to systemically investigate the effects of various types of perturbations in a time course with single-cell resolution. However, the existing temporal scRNA-seq technologies have certain limitations in reliability, detection efficacy and detection diversity. In the current study, we develop scBiopsy-seq assay, which combines a synergistic electroosmosis-electrophoresis extraction method for efficient RNA extraction and digital microfluidics with contamination-isolated hydrophobic interface for high-performance sample processing. scBiopsy-seq extracts the cytoplasm at well-controlled volume to detect >10K genes per extraction with 90% successful rate. Functional enrichment analysis revealed that the genes robustly detected by scBiopsy-seq were associated to diverse biological processes, demonstrating its superb diversity of detection. scBiopsy-seq can perform the sequential extraction of the cytoplasm from the same cell multiple times, which allows us to associate the cell phenotypic responses with its transcriptional dynamics. We employed scBiopsy-seq to analyze the temporal response to a BRD4 degrader induced transcriptional suppression, which identified the key roles of fatty acid beta oxidation in this biological process. scBiopsy-seq with similar data quality as scRNA-seq will dramatically expand the application of temporal scRNA-seq towards a broader spectrum of cell biology research.

bioengineering↗