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Lin, L.

Publications and source records attributed to Lin, L..

At least 91 records · Page 5Linked to original sources

Conditioned versus innate effort-based tasks reveal divergence in antidepressant effect on motivational state in male mice

Antidepressant-induced apathy syndrome is reported in a high number of patients. It is characterised by loss of motivation for daily activities and emotional blunting. It has a negative impact on quality of life and treatment outcome, yet the changes in underlying neurobiology driving this syndrome remain unclear. To begin to address this, a comprehensive understanding of how different classes of antidepressant treatment impact on behaviours relevant to apathy is critical. Rodent motivation for reward is commonly assessed using effort-based operant conditioning paradigms such as the Effort for Reward task. However, motivation to perform spontaneous/innate behaviours may provide additional insight into changes in behaviour reflective of daily activities. We tested the acute and chronic effects of antidepressants on the Effort for Reward task, and the spontaneous/innate Effort Based Forage task. Acute treatment revealed important divergence in drug effect between tasks, where selective serotonin reuptake inhibitor (SSRI)/serotonin and noradrenaline reuptake inhibitor (SNRI) treatment impaired foraging behaviour in the Effort Based Forage task, but enhanced high effort, high value reward responding in the Effort for Reward task. Treatment with a noradrenaline reuptake inhibitor (NRI) or multimodal agent impaired foraging behaviour but did not affect high reward responding in the Effort for Reward task. Conversely, chronic treatment with an SSRI but not SNRI enhanced motivated foraging behaviour but led to a general impairment in Effort for Reward task output. Together, these data demonstrate that SSRI treatment induces opposing effects on conditioned versus innate motivation which may have significant translational relevance when interpreting drug effect.

pharmacology and toxicology↗

Zmap: an intelligent region-allocation method to map single-cell into spatial data

Integration of single-cell and spatial transcriptome represents as a fundamental strategy to enhance spatial data quality. However, existing methods for mapping single-cell data to spatial coordinates struggle with large-scale datasets comprising millions of cells. Here, we introduce Zmap, an intelligent region-allocation method inspired by the region-of-interest (ROI) concept from image processing. By using gradient descent, Zmap allocates cells to structured spatial regions that matching the most significant biological information, optimizing the integration of data and improving speed and accuracy. Zmap excels in integrating data even in the presence of various sequencing artifacts, such as cell segmentation errors and imbalanced cell-type representations. Zmap outperforms state-of-the-art methods by 10 to 1000 times in speed, and it is the only approach capable of integrating datasets containing millions of cells in a single run. As a result, Zmap uncovers originally hidden gene expression patterns in the brain section, offers new insights into organogenesis and tumor microenvironments, all with exceptional efficiency and accuracy.

bioinformatics↗

Genetically Defined Organoid Models Reveal Mechanisms Driving Squamous Cell Neoplastic Evolution and Identify Potential Therapeutic Vulnerabilities

Upper aerodigestive squamous cell carcinoma (UASCC) is an aggressive and lethal neoplasm, with its early neoplastic transformation mechanisms remaining poorly understood. Here, we characterize over 25 genetically-defined organoid models derived from murine and human oral/esophageal tissues harboring key driver mutations. Double knockout of TP53 and CDKN2A induced morphological dysplasia, hyperproliferation, loss of squamous differentiation, and tumorigenicity, which were further exacerbated by additional driver mutations (e.g., PIK3CA, NOTCH1, KMT2C). Single-cell analysis revealed an expansion of quiescent basal cells and proliferative squamous cells, alongside a loss of differentiated squamous cells during malignant transformation. A distinct senescence program, regulated by ANXA1, was markedly diminished during early neoplastic evolution. Mechanistically, the ANXA1-SMAD3-p27KIP1 pathway was identified as a critical regulator of this senescence program, acting to suppress neoplastic features in organoid models. Lastly, our high-throughput, single-organoid-resolution drug screens unexpectedly revealed PIK3CA-driven organoids exhibited sensitivity to Mitomycin C and Onalespib. This study provides novel mechanistic insights into early neoplastic evolution and underscores the value of genetically-defined organoid models for investigating cancer biology and identifying targeted therapies.

cancer biology↗

Single-cell and spatial transcriptomics uncover the role of B chromosomes in driving plant invasiveness

Invasive plants pose a major threat to global biodiversity, yet the molecular and genomic mechanisms underlying their success remain poorly understood. Here, we investigate the common reed (Phragmites australis), a grass species that became invasive in North America after introduction from Europe, to unravel the molecular mechanisms of its invasiveness. By integrating single-cell RNA sequencing, spatial transcriptomics, and comparative genomics, we constructed a single-cell atlas of P. australis and identified 19 transcriptionally distinct cell types, including shoot apical meristem, epidermal, and vascular tissues. Comparative analysis of common garden-grown native (European) and invasive (North American) populations revealed a significant proportion of differentially expressed genes (DEGs) located on B chromosomes, which underwent copy number expansion in invasive genomes. The proportion of B chromosome genes in DEGs varies across cell types, with the highest proportions observed in the epidermis and mesophyll, and lower proportions in the vascular tissues. Gene IMPA-3, a B chromosome gene likely derived from transposable element activity, exhibited an elevated mutation rate compared to its ancestral counterparts, potentially enhancing adaptive evolution in invasive populations. Invasive individuals also displayed molecular regulatory networks related to photosynthetic efficiency, stress tolerance, and growth-defense trade-offs. Together, our findings provide a cell-type-resolved molecular atlas of a non-model invasive plant and offer key insights into the cellular and genomic architecture of plant invasiveness, with implications for ecological management.

evolutionary biology↗

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina

Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the rapid advancements in deep-learning techniques, we developed sequence-based predictors to interpret non-coding risk variants of retina diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases, and provides a resource for studying the gene regulatory programs of the human retina and relevant diseases.

genomics↗

Clonal analysis of murine HSC self-renewal and differentiation in native hematopoiesis

Hematopoietic stem cells (HSC) maintain lifelong hematopoiesis. However, in current clonal analyses with unbiased "barcoding" approaches, steady-state hematopoietic clones in young and middle-aged adults rarely have detectable HSCs, which precludes comprehensive interrogation of HSC clonal behaviors. In the current study, we used the previously described Sleeping Beauty transposon model to investigate HSC self-renewal and differentiation at a clonal level following a lifelong chase that significantly enriched HSC-derived clones. From seventeen mice, we detected over seventy thousand clones in native hematopoiesis that reflected the known HSC differentiation biases observed in transplantation. Our data indicated an intimate connection between megakaryocytic-restricted differentiation and HSC self-renewal expansion. By comparing the differentiation patterns of clones derived from transplanted HSCs, we further demonstrated the abilities of HSCs to preserve their cell fates towards self-renewal or multilineage differentiation. Unlike HSCs, clonal expansion in multipotent progenitors was associated with either a differentiation-active or differentiation-indolent state. Moreover, the clonal expansion events in the more differentiated stem and progenitor cells, but not the most primitive HSCs, drove clonal expansion in the megakaryocyte and myeloid cell lineages. Our study provided a comprehensive portrait of native hematopoiesis at a clonal level and revealed the general patterns in which HSCs maintained self-renewal and multi-lineage differentiation.

developmental biology↗

Mechanical load conditions the spectrin network to `run-on' proteolysis and promotes early onset neurodegeneration

The correct homeostasis of the neuronal cytoskeleton and its dynamics is important for health and disease. Forces constantly act on the neurons in our body, leading to subtle axonal deformations and length changes. The spectrin cytoskeleton is known as a key player that protects neurons against mechanical damage. How the spectrin cytoskeleton changes with age and how it influences mechanoprotection in aging animals is not well understood. Using an interdisciplinary approach, we show that age causes a loss of proprioception during the first few days of adulthood in C. elegans via spectrin unfolding, loss of mechanical tension and degradation of the spectrin cytoskeleton. Guided by a proteomic screen to identify potential spectrin binding partners, we found that this early-onset neurodegeneration can be suppressed in clp-1 mutants and by targeted expression of an engineered chaperone derived from human B-crystallin. Our data suggest that the spectrin cytoskeleton is sensitized to proteolytic damage by calcium-sensitive proteases when mechanical stresses conspires with high-calcium concentrations as in proprioceptive signaling. These results may have implications for the etiology of diseases in which high calcium dynamics and mechanical stress co-incide.

neuroscience↗

SenSeqNet: A Deep Learning Framework for Cellular Senescence Detection from Protein Sequences

Cellular senescence, characterized by the irreversible cessation of division in normally proliferating cells due to various stressors, presents a significant challenge in the treatment of age-related diseases. Understanding and accurately detecting cellular senescence is crucial for identifying potential therapeutic targets. However, traditional wet lab assays for detecting cellular senescence are time-consuming and labor-intensive, limiting research and drug development efficiency. There is an urgent need for computational tools allowing swift and accurate detection of cellular senescence from protein sequences. We propose SenSeqNet, a novel deep learning framework for detecting cellular senescence directly from protein sequences. The framework begins with feature extraction using the Evolutionarily Scaled Model (ESM-2), a state-of-the-art protein language model that captures evolutionary information and complex sequence patterns. The extracted embeddings are then passed through a hybrid architecture consisting of long short-term memory (LSTM) networks and convolutional neural networks (CNNs) to further refine and learn from the embedded information. SenSeqNet achieved a final accuracy of 83.55% on independent testing, surpassing various machine learning and deep learning architectures. This performance underscoring the robustness and effectiveness of SenSeqNet for detecting cellular senescence from protein sequences. These results provide a solid foundation for future research on aging and age-related therapeutics.

bioinformatics↗

SPP1+ tumor-associated macrophages induce radioresistance of nasopharyngeal carcinoma through crosstalk with the tumor microenvironment

The function and phenotype of tumor-associated macrophages (TAMs) influence the efficacy of radiotherapy. However, the effect of different subsets of TAMs on the radioresistance in nasopharyngeal carcinoma (NPC) still needs to be further explored. This study utilized single-cell RNA sequencing (scRNA-seq) to analyze 120,579 cells obtained from 15 NPC samples. Cell annotation, cell-cell communication analysis, and functional annotation were used to investigate the impact of TAMs on the effectiveness of radiotherapy in NPC patients. Additionally, we employed RNA-seq data and clinical information from many patients, including 24 NPC samples from Zhujiang Hospital, 3,934 samples from patients with a history of radiotherapy, for further validation. We identified a hub TAM subpopulation, SPP1+ TAMs, that induced radioresistance in NPC based on single-cell RNA sequencing (scRNA-seq) data. We combined many public datasets to confirm their prognostic value in radiotherapy patients. We found that SPP1+ TAMs had stronger protumorigenic and immunosuppressive effects in the postradiotherapy recurrent tumor (PRRT) group. SPI1 transcription factor efficiently regulates the expression level of SPP1 in macrophages. In addition, we validated the underlying mechanisms by molecular docking, multiplex immunofluorescence and cellular experiments. In conclusions, by forming an immunosuppressive microenvironment and promoting tumor cell proliferation, SPP1+ TAMs leading to radioresistance and poor clinical prognosis in NPC patients. Targeting SPP1+ TAMs could provide new insights into improving the efficacy of radiotherapy in NPC patients.

cancer biology↗

Mechanical control of germ cell specification in Arabidopsis anthers

A central question in developmental biology is how the germline is established. We have studied the specification of the male germ cells (GCs) within the anther1-3. Hereby, we have focused on the potential role of mechanics, an aspect of anther development which has been very poorly characterized2,4. Using a combination of live imaging and mechanical measurements, we provide evidence that GCs originate in a special micro-mechanical niche, where inner tissues exert push on outer cell layers, placing them under compression. Mechanical perturbations significantly disrupted the GC specification and patterning. Moreover, we found that the master genetic regulator SPOROCYTELESS/NOZZLE (SPL/NZZ)5,6 is central in establishing this micro-mechanical environment by softening the cell wall. The mechanical cues, in turn, stabilize the transcription of SPL/NZZ. We propose here an intrinsic growth-derived mechano-chemical feedback loop that drives germ-cell fate acquisition.

developmental biology↗

DEMINERS enables clinical metagenomics and comparative transcriptomic analysis by increasing throughput and accuracy of nanopore direct RNA sequencing

Nanopore direct RNA sequencing (DRS) advances RNA biology but is limited by relatively low basecalling accuracy, low throughput, yet high RNA input and costs. Here we introduce a novel DRS toolkit, DEMINERS, which integrates an RNA multiplexing experimental workflow, a machine-learning barcode classifier based on Random Forest and a novel basecaller built on an optimized convolutional neural network providing an additional species-specific training module. With the increased accuracy in barcode classification and basecalling, DEMINERS can demultiplex up to 24 samples and the required RNA input and running time are both substantially reduced. We demonstrated the applications of DEMINERS in clinical metagenomics, cancer transcriptomics and parallel comparison of transcriptomic features in different biological conditions, revealing altered airway microbial diversity in COVID-19 and a potential role of m6A in increasing transcriptomic diversity in glioma and the mature blood-stage of malaria parasites. Overall, DEMINERS is a simple, robust, high-throughput DRS method for accurately estimating transcript levels, poly(A) lengths, and mutation and RNA modification heterogeneity at single-read level, with minimal sequencing biases.

bioinformatics↗

A ZO-2 scaffolding mechanism regulates the Hippo signalling pathway.

Inhibition of proliferation upon contact is a critical cell density control mechanism governed by the Hippo signalling pathway. The biochemical signalling underlying cell density-dependent cues regulating Hippo signalling and its downstream effectors, YAP, remains poorly understood. Here, we reveal that the tight junction protein ZO-2 is required for the contact-mediated inhibition of proliferation. We additionally determined that the well-established molecular players of contact inhibition of proliferation, namely Hippo kinase LATS1 and YAP, are regulated by ZO-2, and that the scaffolding function of ZO-2 promotes the interaction with and phosphorylation of YAP by LATS1. Mechanistically, YAP is phosphorylated when ZO-2 brings LATS1 and YAP together via its SH3 and PDZ domains, respectively, subsequently leading to the cytoplasmic retention and inactivation of YAP. In conclusion, we demonstrate that ZO-2 maintains Hippo signalling pathway activation by promoting the stability of LATS1 to inactivate YAP.

cell biology↗

SAMPL-seq reveals micron-scale spatial hubs in the human gut microbiome

The local arrangement of microbes can profoundly impact community assembly, function, and stability. To date, little is known about the spatial organization of the human gut microbiome. Here, we describe a high-throughput and streamlined method, dubbed SAMPL-seq, that samples microbial composition of micron-scale sub-communities with split-and-pool barcoding to capture spatial colocalization in a complex consortium. SAMPL-seq analysis of the gut microbiome of healthy humans identified bacterial taxa pairs that consistently co-occurred both over time and across multiple individuals. These colocalized microbes organize into spatially distinct groups or "spatial hubs" dominated by Bacteroideceae, Ruminococceae, and Lachnospiraceae families. From a dietary perturbation using inulin, we observed reversible spatial rearrangement of the gut microbiome, where specific taxa form new local partnerships. Spatial metagenomics using SAMPL-seq can unlock new insights to improve the study of microbial communities. One Sentence SummaryHigh throughput micron-scale subcommunity sampling and sequencing identifies distinct spatial associations of gut bacteria within and across individuals.

systems biology↗

Development of Clinically Viable Non-Muscle Myosin II Small Molecule Inhibitors with Broad Therapeutic Potential

Non-muscle myosin II (NMII), a molecular motor that regulates critical processes such as cytokinesis and neuronal synaptic plasticity, has substantial therapeutic potential. However, translating this potential to in vivo use has been hampered by the lack of selective tools. The most prototypical non-selective inhibitor, blebbistatin inactivates both NMII and cardiac myosin II (CMII), a key regulator of heart function. Using rational drug design, we developed a series of NMII inhibitors that improve tolerability by selectively targeting NMII over CMII, including MT-228, which has excellent properties such as high brain penetration and efficacy in preclinical models of stimulant use disorder, which has no current FDA-approved therapies. The structure of MT-228 bound to myosin II provides insight into its 17-fold selectivity for NMII over CMII. MT-228s broad therapeutic window opens the door to new disease treatments and provides valuable tools for the scientific community, along with promising leads for future medication development. HighlightsO_LIResearch suggests numerous indications, from axon regeneration and cancer, would benefit from a small molecule inhibitor of non-muscle myosin II, a molecular motor that regulates the actin cytoskeleton. C_LIO_LICurrent chemical probe options are very limited and lack sufficient safety for in vivo C_LIO_LIstudies, which we show is primarily due to potent inhibition of cardiac myosin II. C_LIO_LIRational design that focused on improving target selectivity over the pan-myosin II inhibitor, blebbistatin, led to the identification of MT-228, a small molecule inhibitor with a wide therapeutic window. C_LIO_LIHigh-resolution structure of MT-228 bound to myosin II reveals that selectivity results from a different positioning compared to blebbistatin and an important sequence difference between cardiac and non-muscle myosin II in the inhibitor binding pocket. C_LIO_LIA single administration of MT-228 shows long-lasting efficacy in animal models of stimulant use disorder, a current unmet and rapidly escalating need with no FDA-approved treatments. C_LI

cell biology↗

Molecular signatures of altered energy metabolism and circadian rhythm perturbations in a model of extra-nigral Synucleinopathy.

A pathological role of alpha-Synuclein (aSyn) aggregation in the central nervous system (CNS) is a recognized feature in Parkinson disease (PD) and related neurodegenerative conditions termed synucleinopathies. In order to characterize the cellular response in CNS to incipient and advanced aSyn pathology, we applied spatial transcriptomics on brain sections derived from a transgenic mouse model (M83+/+ line, Prnp-SNCA*A53T) in which aSyn aggregation was induced in a prion-like fashion through hindlimb intramuscular delivery of pre-formed fibrillar (PFF) murine aSyn. Our spatially-resolved transcriptomics (ST) data point to unique perturbations in brain energy metabolism during the progression of aSyn pathology, such that the early stage of aSyn aggregate pathology activates molecular pathways controlling metabolic flux through glycolysis, oxidative phosphorylation and fatty acid metabolism. In contrast, the ST data indicate a profound decline in mitochondrial metabolism in the brains of symptomatic animals with advanced aSyn pathology. The latter stage was also associated with drastic reduction in mRNA translation machinery, along with aberrant expression of molecular drivers involved in RNA splicing and inflammatory response. Intriguingly, our ST data also point to perturbed regulation of circadian rhythm, was corroborated by increased immunodetection of CREB-binding protein (a modulator of core clock machinery) in the brains of symptomatic animals, and transcriptional upregulation of CREBBP in 4 independent PD microarray datasets. Collectively, we anticipate that our findings offer novel opportunities in knowledge translation for mechanism-based drug discovery and biomarkers in neurodegenerative synucleinopathies.

neuroscience↗

Defining the Vascular Niche of Human Adipose Tissue Across Metabolic Conditions

IntroductionAdipose tissue homeostasis depends on a healthy vascular network. Vascular malfunction is a hallmark of obesity1, and vascular endothelial dysfunction, in particular, accelerates metabolic diseases, including obesity and diabetes. Single-cell transcriptomics studies have mapped the cellular landscape of human white adipose tissue (WAT)2-8. However, the vascular niche remains relatively undefined9, especially regarding its heterogeneity, function, and role in metabolic disease. To address this gap, we created a single-cell transcriptome atlas of human subcutaneous adipose tissue (SAT), comprising nearly 70,000 vascular cells from 65 individuals. We characterized seven canonical adipose tissue endothelial cell (AdEC) subtypes and identified a distinct heterogenous population, here referred to as sub-AdECs. Sub-AdECs exhibit gene signatures characteristic of multiple cell types, including mesenchymal, adipocytic, and immune, suggesting they possess diverse properties and identities. Through computational analyses and whole-mount imaging, we validated the occurrence of sub-AdECs and show that these cells likely arise through endothelial-mesenchymal transition (EndMT), the modulation of which limits obesity-associated adipose tissue inflammation and fibrosis. Furthermore, we compared the transcriptomes of vascular cells from individuals living with or without obesity and type 2 diabetes and find metabolic disease-associated inflammatory and fibrotic transcriptomic patterns. The atlas and accompanying analyses establish a solid foundation for investigations into the biology of the adipose tissue vascular niche and its contribution to the pathogenesis of metabolic disease.

cell biology↗

Varying recombination landscapes between individuals are driven by polymorphic transposable elements

AbstractsMeiotic recombination is a prominent force shaping genome evolution, and understanding the causes for varying recombination landscapes within and between species has remained a central, though challenging, question. Recombination rates are widely observed to negatively associate with the abundance of transposable elements (TEs), selfish genetic elements that move between genomic locations. While such associations are usually interpreted as recombination influencing the efficacy of selection at removing TEs, accumulating findings suggest that TEs could instead be the cause rather than the consequence. To test this prediction, we formally investigated the influence of polymorphic, putatively active TEs on recombination rates. We developed and benchmarked a novel approach that uses PacBio long-read sequencing to efficiently, accurately, and cost-effectively identify crossovers (COs), a key recombination product, among large numbers of pooled recombinant individuals. By applying this approach to Drosophila strains with distinct TE insertion profiles, we found that polymorphic TEs, especially RNA-based TEs and TEs with local enrichment of repressive marks, reduce the occurrence of COs. Such an effect leads to different CO frequencies between homologous sequences with and without TEs, contributing to varying CO maps between individuals. The suppressive effect of TEs on CO is further supported by two orthogonal approaches-analyzing the distributions of COs in panels of recombinant inbred lines in relation to TE polymorphism and applying marker-assisted estimations of CO frequencies to isogenic strains with and without transgenically inserted TEs. Our investigations reveal how the constantly changing mobilome can actively modify recombination landscapes, shaping genome evolution within and between species.

genomics↗

Quantitative site-specific glycoproteomics by ZenoTOF reveals glyco-signatures for breast cancer diagnosis

Intact glycopeptide characterization by mass spectrometry has proven a versatile tool for site-specific glycoproteomics analysis and biomarker screening. Here, we present a method using the ZenoTOF instrument with optimized fragmentation for intact glycopeptide identification and demonstrate its ability to analyze large-cohort glycoproteomes. From 124 clinical serum samples of breast cancer, non-cancerous diseases, and non-disease controls, a total of 6901 unique site-specific glycans on 807 gly-cosites of proteins were detected. Much more differences of glycoproteome were observed in breast diseases than the proteome. By employing machine learning, 15 site-specific glycans were determined as potential glyco-signatures in detecting breast cancer. The results demonstrate that our method provides a powerful tool in glycoproteomic analyses for biomarker discovery studies.

cancer biology↗