Biology subjects

Lin, A.

Publications and source records attributed to Lin, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Suspended Tissue Open Microfluidic Patterning (STOMP)

Free-standing tissue structures tethered between pillars are powerful mechanobiology tools for studying cell contraction. To model interfaces ubiquitous in natural tissues and upgrade existing single-region suspended constructs, we developed Suspended Tissue Open Microfluidic Patterning (STOMP), a method to create multi-regional suspended tissues. STOMP uses open microfluidics and capillary pinning to pattern subregions within free-standing tissues, facilitating the study of complex tissue interfaces, such as diseased-healthy boundaries (e.g., fibrotic-healthy) and tissue-type interfaces (e.g., bone-ligament). We observed altered contractile dynamics in fibrotic-healthy engineered heart tissues compared to single-region tissues and differing contractility in bone-ligament enthesis constructs compared to single-tissue periodontal ligament models. STOMP is a versatile platform - surface tension-driven patterning removes material requirements common with other patterning methods (e.g., shear-thinning, photopolymerizable) allowing tissue generation in multiple geometries with native extracellular matrices and advanced 4D materials. STOMP combines the contractile functionality of suspended tissues with precise patterning, enabling dynamic and spatially controlled studies.

bioengineering↗

bioRxiv2024

TWINKLE: An open-source two-photon microscope for teaching and research

Many laboratories use two-photon microscopy through commercial suppliers, or homemade designs of considerable complexity. The integrated nature of these systems complicates customization, troubleshooting, and training on the principles of two-photon microscopy. Here, we present "Twinkle": a microscope for Two-photon Imaging in Neuroscience, and Kit for Learning and Education. It is a fully open, high performing and easy-to-set-up microscope that can effectively be used for both education and research. The instrument features a > 1 mm field of view, using a modern objective with 3 mm working distance and 2 inch diameter optics combined with GaAsP photomultiplier tubes to maximize the fluorescence signal. We document our experiences using this system as a teaching tool in several two week long workshops, exemplify scientific use cases, and conclude with a broader note on the place of our work in the growing space of open scientific instrumentation.

neuroscience↗

bioRxiv2024

Benchmarking Recent Computational Tools for DNA-binding Protein Identification

Identification of DNA-binding proteins (DBPs) is a crucial task in genome annotation, as it aids in understanding gene regulation, DNA replication, transcriptional control and various cellular processes. In this paper, we conduct an unbiased benchmarking of eleven state-of-the-art computational tools as well as traditional tools such as ScanProsite, BLAST, and HMMER for identifying DBPs. We highlight the data leakage issue in conventional datasets leading to inflated performance. We introduce new evaluation datasets to support further development. Through a comprehensive evaluation pipeline, we identify potential limitations in models, feature extraction techniques and training methods; and recommend solutions regarding these issues. We show that combining the predictions of the two best computational tools with BLAST based prediction significantly enhances DBP identification capability. We provide this consensus method as user-friendly software. The datasets and software are available at: https://github.com/Rafeed-bot/DNA_BP_Benchmarking. 1. Key PointsO_LIWe designed a comprehensive evaluation pipeline which systematically evaluates eleven recent machine learning (ML) based DBP identification tools. C_LIO_LIWe analyzed the test prediction mistakes made by top-performing tools identifying their potential limitations in terms of model architecture, feature extraction and class balancing. C_LIO_LIWe showed that although the best of these tools do not convincingly outperform BLAST, they still provide substantial value when integrated together with BLAST into a simple majority-voting ensemble. C_LIO_LIWe provide recommendations on more robust development & evaluation and better usability of future tools. C_LIO_LIWe provide the two best-performing ML-based tools, BLAST and the ensemble method as user-friendly software, as well as our proposed datasets, publicly available via GitHub. C_LI

bioinformatics↗

bioRxiv2024

Developmental and physiological impacts of pathogenic human huntingtin protein in the nervous system

Huntingtons Disease (HD) is a neurodegenerative disorder, part of the nine identified inherited polyglutamine (polyQ) diseases. Most commonly, HD pathophysiology manifests in middle-aged adults with symptoms including progressive loss of motor control, cognitive decline, and psychiatric disturbances. Associated with the pathophysiology of HD is the formation of insoluble fragments of the huntingtin protein (htt) that tend to aggregate in the nucleus and cytoplasm of neurons. To track both the intracellular progression of the aggregation phenotype as well as the physiological deficits associated with mutant htt, two constructs of human HTT were expressed with varying polyQ lengths, non-pathogenic-htt (Q15, NP-htt) and pathogenic-htt (Q138, P-htt), with an N-terminal RFP tag for in vivo visualization. P-htt aggregates accumulate in the ventral nerve cord cell bodies as early as 24 hours post hatching and significant aggregates form in the segmental nerve branches at 48 hours post hatching. Organelle trafficking up-and downstream of aggregates formed in motor neurons showed severe deficits in trafficking dynamics. To explore putative downstream deficits of htt aggregation, ultrastructural changes of presynaptic motor neurons and muscles were assessed, but no significant effects were observed. However, the force and kinetics of muscle contractions were severely affected in P-htt animals, reminiscent of human chorea. Reduced muscle force production translated to altered locomotory behavior. A novel HD aggregation model was established to track htt aggregation throughout adulthood in the wing, showing similar aggregation patterns with larvae. Expressing P-htt in the adult nervous system resulted in significantly reduced lifespan, which could be partially rescued by feeding flies the mTOR inhibitor rapamycin. These findings advance our understanding of htt aggregate progression as well the downstream physiological impacts on the nervous system and peripheral tissues.

neuroscience↗

bioRxiv2024

Detecting genetically variant peptides in non-human samples

During proteomics data analysis, experimental spectra are searched against a user-defined protein database consisting of proteins that are reasonably expected to be present in the sample. Typically, this database contains the proteome of the organism under study concatenated with expected contaminants such as trypsin and human keratins. However, there are additional contaminants that are not commonly added to the database. In this study, we describe a new set of protein contaminants and provide evidence that they are detectable in mass spectrometry-based proteomics data. Specifically, we provide evidence that human genetically variant peptides (GVPs) can be detected in non-human samples. GVPs are peptides that contain single amino acid polymorphisms that result from non-synonymous single nucleotide polymorphisms in protein coding regions of DNA. We reanalyzed previously collected non-human data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets and detected between 0 and 135 GVPs per dataset. In addition, we show that GVPs are unlikely to originate from non-human sources and that a subset of eight GVPs are commonly detected across datasets.

biochemistry↗

bioRxiv2024

A genetically engineered therapeutic lectin inhibits human influenza A virus infection and sustains robust virus-specific CD8 T cell expansion

Native banana lectin (BanLec) is antiviral but highly mitogenic, which limits its therapeutic value. In contrast, the genetically engineered H84T BanLec (H84T) is not mitogenic but remains effective against influenza A virus (IAV) infection in mouse models. However, the potency and effect of H84T on human immune cells and IAV-specific immune responses is undetermined. We found that H84T efficiently inhibited IAV replication in human dendritic cells (DCs) from blood and tonsils, which preserved DC viability and allowed acquisition and presentation of viral antigen. Consequently, H84T-treated DCs initiated effective expansion of IAV-specific CD8 T cells. Furthermore, H84T preserved the capacity of IAV-exposed DCs to present a second non-IAV antigen and induce robust CD8 T cell expansion. This supports H84T as a potent antiviral in humans as it effectively inhibits IAV infection without disrupting DC function, and preserves induction of antigen-specific adaptive immune responses against diverse antigens, which likely is clinically beneficial.

immunology↗

bioRxiv2024

Unraveling the Role of Ctla-4 in Intestinal Immune Homeostasis: Insights from a novel Zebrafish Model of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a chronic and relapsing immune-mediated disorder characterized by intestinal inflammation and epithelial injury. The underlying causes of IBD are not fully understood, but genetic factors have implicated in genome-wide association studies, including CTLA-4, an essential negative regulator of T cell activation. However, establishing a direct link between CTLA-4 and IBD has been challenging due to the early lethality of CTLA-4 knockout mice. In this study, we identified zebrafish Ctla-4 homolog and investigated its role in maintaining intestinal immune homeostasis by generating a Ctla-4-deficient (ctla-4-/-) zebrafish line. These mutant zebrafish exhibited reduced weight, along with impaired epithelial barrier integrity and lymphocytic infiltration in their intestines. Transcriptomics analysis revealed upregulation of inflammation-related genes, disturbing immune system homeostasis. Moreover, single-cell RNA-sequencing analysis indicated increased Th2 cells and interleukin 13 expression, along with decreased innate lymphoid cells and upregulated proinflammatory cytokines. Additionally, Ctla-4-deficient zebrafish exhibited reduced diversity and an altered composition of the intestinal microbiota. All these phenotypes closely resemble those found in mammalian IBD. Lastly, supplementation with Ctla-4-Ig successfully alleviated intestinal inflammation in these mutants. Altogether, our findings demonstrate the pivotal role of Ctla-4 in maintaining intestinal homeostasis. Additionally, they offer substantial evidence linking CTLA-4 to IBD and establish a novel zebrafish model for investigating both the pathogenesis and potential treatments.

immunology↗

bioRxiv2024

Artifact-Minimized High-Ratio Image Compression with Preserved Analysis Fidelity

Recent advances in microscopy have pushed imaging data generation to an unprecedented scale. While scientists benefit from higher spatiotemporal resolutions and larger imaging volumes, the increasing data size presents significant storage, visualization, sharing, and analysis challenges. Lossless compression typically reduces the data size by <4 fold, whereas lossy compression trades smaller data size for the loss of a precise reconstruction of the original data. Here, we develop a novel quantization method and an artifact metric for automated compression parameter optimization that preserves information fidelity. We show that, when combined with the AV1 video codec, we achieve tens to ten thousand folds of data compression while introducing negligible visual defects or quantification errors in single-molecule localization and segmentation analyses. We developed an HDF5 filter with FFMPEG library support for convenient community adaptation. For instance, HDF5-enabled ImageJ plugins can now be seamlessly extended to support AV1 compression and visualization to handle terabyte-scale images.

bioinformatics↗

bioRxiv2024

A multi-gene predictive model for the radiation sensitivity of nasopharyngeal carcinoma based on machine learning

BackgroundRadiotherapy resistance is a major obstacle to the long-term survival of nasopharyngeal cancer patients, as it is a primary cause of recurrence and metastasis. Identifying radiotherapy-associated biomarkers can help improve the survival prognosis of nasopharyngeal cancer patients. Consequently, discovering biomarkers associated with radiosensitization is crucial. MethodsWe evaluated 113 combinations of machine learning algorithms and ultimately selected 48 to construct a radiotherapy sensitivity score (NPC-RSS) that can predict radiosensitivity in nasopharyngeal cancer patients. Furthermore, we analyzed the relationship between NPC-RSS and the expression of genes associated with immune and radiotherapy sensitivity profiles. We employed GSEA and ssGSEA to investigate the connection between NPC-RSS and signaling pathways. ResultsWe selected the combined model glmBoost+NaiveBayes, which had the best AUC among 48 models, for our subsequent study. The NPC-RSS, built based on the 18 genes included in this model, can predict the results of the public dataset and the in-house dataset of Zhujiang Hospital, Southern Medical University, with considerable efficiency. The key genes of NPC-RSS are closely associated with immune characteristics, including chemokine and chemokine receptor families, and histocompatibility complex (MHC), and show more active immune processes. Meanwhile, these key genes were significantly associated with the expression of radiosensitization-related genes. Furthermore, GSVA and GSEA analyses demonstrated that different expression levels of key NPC-RSS genes influenced signaling pathways, such as the Wnt/{beta}-catenin signaling pathway, JAK-STAT signaling pathway,NF-kappa B signaling pathway and T cell receptor signaling pathway, which are associated with immunity and disease progression. The consistency of the expression of key genes SMARCA2 and CD9 with NPC-RSS was validated in in-house cell lines. The radiosensitive group, classified according to NPC-RSS, exhibited a more enriched and activated state of immune infiltration compared to the radioresistant group. Moreover, in single-cell samples, NPC-RSS was higher in the radiotherapy-sensitive group, with immune cells playing a predominant role. ConclusionsIn this study, we used machine learning to construct a predictive score, called NPC-RSS, associated with radiosensitivity in nasopharyngeal carcinoma patients; moreover, NPC-RSS is strongly associated with immune characteristics, expression of radiosensitivity-related genes, and signaling pathways related to disease progression. We hope that the NPC-RCC will enable more precise selection of the NPC population of potential beneficiaries of radiation therapy.

bioinformatics↗

bioRxiv2024

An unbiased method to partition diverse neuronal responses into functional ensembles reveals interpretable population dynamics during innate social behavior

In neuroscience, understanding how single-neuron firing contributes to distributed neural ensembles is crucial. Traditional methods of analysis have been limited to descriptions of whole population activity, or, when analyzing individual neurons, criteria for response categorization varied significantly across experiments. Current methods lack scalability for large datasets, fail to capture temporal changes and rely on parametric assumptions. Theres a need for a robust, scalable, and non-parametric functional clustering approach to capture interpretable dynamics. To address this challenge, we developed a model-based, statistical framework for unsupervised clustering of multiple time series datasets that exhibit nonlinear dynamics into an a-priori-unknown number of parameterized ensembles called Functional Encoding Units (FEUs). FEU outperforms existing techniques in accuracy and benchmark scores. Here, we apply this FEU formalism to single-unit recordings collected during social behaviors in rodents and primates and demonstrate its hypothesis-generating and testing capacities. This novel pipeline serves as an analytic bridge, translating neural ensemble codes across model systems.

neuroscience↗

bioRxiv2024

HIV-1 controllers possess a unique CD8+ T-cell activation phenotype and loss of control is associated with increased expression of exhaustion markers

HIV-1 controllers are a rare population of individuals that exhibit spontaneous control of HIV-1 infection without antiretroviral therapy. These controllers can be categorized based on the level and mechanism of control. Understanding the mechanisms by which controllers maintain and eventually lose this ability would be highly valuable in HIV-1 cure or vaccine research. We explored whether CD8+ T cell exhaustion plays a role in the maintenance and loss of control by examining immune characteristics of HIV-1 controllers and controllers who lost control within the duration of the study. Previous work revealed the ability of CD8+ T-cells isolated from HIV-1 controllers to suppress HIV-1 replication in matched CD4+ T-cells ex vivo. Using flow cytometry, we analyzed exhaustion marker expression on CD8+ T-cells from these controllers and determined that they maintain a unique exhaustion profile as compared to HIV-negative individuals and standard progressors. The low level of T-cell exhaustion seen in controllers was reversed when these individuals lost control and showed increased viral loads. Immune checkpoint blockade targeting exhaustion markers was able to restore ex vivo control by CD8+ T-cells from former controllers. These results suggest that CD8+ T cell exhaustion compromises the ability to control viral replication in HIV-1 controllers. AUTHOR SUMMARYDespite the use of antiretroviral therapy, HIV continues to be a major public health issue that affects the lives of millions of people. Some infected people can control viral infection without therapy. The mechanism by which some people can control HIV infection at low, but detectable levels is unknown. In this study we examined the state of cytotoxic CD8+ T-cells in a group of HIV controllers and found that controllers maintain low levels of markers for a chronic state of activation called exhaustion. Loss of control correlated with increase in exhausted T-cells and for individuals who had recently lost control of infection we could restore protection in the cell culture dish by using immune checkpoint blockade drugs that affect exhaustion.

immunology↗

bioRxiv2024

Blocker-SELEX: A Structure-guided Strategy for Developing Inhibitory Aptamers Disrupting Undruggable Transcription Factor Interactions

Despite the well-established significance of transcription factors (TFs) in pathogenesis, their utilization as pharmacological targets has been limited by the inherent challenges associated with modulating their protein-protein and protein-DNA interactions. The lack of defined small-molecule binding pockets and the nuclear localization of TFs do not favor the use of small-molecule inhibitors, or neutral antibodies, in blocking TF interactions. Aptamers are short oligonucleotides exhibiting high affinity and specificity for a diverse range of targets. Large molecular weights, expansive blocking surfaces and efficient cellular internalization make aptamers a compelling molecular tool for use as traditional TF interaction modulators. Here, we report a structure-guided design strategy called Blocker-SELEX to develop inhibitory aptamers (iAptamer) that selectively block TF interactions. Our approach led to the discovery of iAptamers that cooperatively disrupts SCAF4/SCAF8-RNA Polymerase II (RNAP2) interactions, thereby dysregulating RNAP2-dependent gene expression and splicing and, in turn, leading to the impairment of cell proliferation. This approach was further applied to develop iAptamers to efficiently block WDR5-MYC interaction with a nexus in cancer. Taken together, our study highlights the potential of Blocker-SELEX in developing iAptamers that effectively disrupt potentially pathogenic TF interactions with attendant implications for iAptamers as chemical tools for use in the study of biological functions of TF interactions, but also for potential use in nucleic acids drug discovery.

biochemistry↗

bioRxiv2023

Predicting the similarity of two mass spectrometry runs using only MS1 data

BackgroundTraditionally researchers can compare the similarity between a pair of mass spectrometry-based proteomics samples by comparing the lists of detected peptides that result from database searching or spectral library searching. Unfortunately, this strategy requires having substantial knowledge of the sample and parameterization of the peptide detection step. Therefore, new methods are needed that can rapidly compare proteomics samples against each other without extensive knowledge of the sample. ResultsWe present a set of neural network architectures that predict the proportion of confidently detected peptides in common between two proteomics runs using solely MS1 information as input. Specifically, when compared to several baseline models, we found that the convolutional and siamese neural networks obtained the best performance. In addition, we demonstrate that unsupervised clustering techniques can leverage the predicted output from our method to perform sample-level characterizations. Our methodology allows for the rapid comparison and characterization of proteomics samples sourced from various different acquisition methods, organisms, and instrument types. ConclusionsWe find that machine learning models, using only MS1 information, can be used to predict the similarity between liquid chromatography-tandem mass spectrometry proteomics runs.

bioinformatics↗

bioRxiv2023

THER: Integrative Web Tool for Tumor Hypoxia Exploration and Research

Hypoxia is an important factor in the adaptation of tumor cells to their environment, contributes to their malignant progression, and affects tumor prognosis and drug sensitivity. Although there is a wealth of transcriptomic data stored in public databases, there is a lack of web-based tools for analyzing these data to explore the link between hypoxia and the mechanisms of tumorigenesis and progression. To this end, we have developed an interactive web-based tool called THER, which is designed to help users easily identify potential targets, mechanisms of action and effective drugs for treating hypoxic tumors. THER integrates 63 transcriptomic tumor hypoxia datasets from the Gene Expression Omnibus (GEO) database, covering 3 species, 18 tumor types and 42 cell line types. This web tool provides five modules that allow users to perform differential expression analysis, expression profiling analysis, correlation analysis, enrichment analysis and drug sensitivity analysis on different datasets based on different oxygen statuses. We expect that users will be able to use the tool to identify valuable biomarkers, further reveal the molecular mechanisms of tumor hypoxia, and identify effective drugs, thus providing a scientific basis for tumor diagnosis and treatment. THER is open to all users and can be accessed without login at https://smuonco.shinyapps.io/THER/.

cancer biology↗

bioRxiv2023

An immunohistochemical atlas of necroptotic pathway expression

Necroptosis is a lytic form of regulated cell death reported to contribute to inflammatory diseases of the gut, skin and lung, as well as ischemic-reperfusion injuries of the kidney, heart and brain. However, precise identification of the cells and tissues that undergo necroptotic cell death in vivo has proven challenging in the absence of robust protocols for immunohistochemical detection. Here, we provide automated immunohistochemistry protocols to detect core necroptosis regulators - Caspase-8, RIPK1, RIPK3 and MLKL - in formalin-fixed mouse and human tissues. We observed surprising heterogeneity in protein expression within tissues, whereby short-lived immune barrier cells were replete with necroptotic effectors, whereas long-lived cells lacked RIPK3 or MLKL expression. Local changes in the expression of necroptotic effectors occurred in response to insults such as inflammation, dysbiosis or immune challenge, consistent with necroptosis being dysregulated in disease contexts. These methods will facilitate the precise localisation and evaluation of necroptotic signaling in vivo. HighlightsO_LI13 automated immunohistochemistry protocols for detecting the necroptotic pathway C_LIO_LINecroptotic pathway expression is confined to fast-cycling immune barriers C_LIO_LINecroptotic pathway expression changes at sites of immunoinflammatory challenge C_LIO_LIImmunodetection of necrosomes in IBD patients is a putative new diagnostic tool C_LI

cell biology↗

bioRxiv2023

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

bioinformatics↗

bioRxiv2023

Single-cell RNA sequencing unveils the hidden powers of zebrafish kidney for generating both hematopoiesis and adaptive antiviral immunity

The vertebrate kidneys play two evolutionary conserved roles in waste excretion and osmoregulation. Besides, the kidney of fish is considered as a functional ortholog of mammalian bone marrow that serves as a hematopoietic hub for generating blood cell lineages and immunological responses. However, knowledge about the properties of kidney hematopoietic cells, and the functionality of kidney in fish immune systems remain to be elucidated. To this end, our present study generated a comprehensive atlas with 59 hematopoietic stem/progenitor cell (HSPC) and immune-cell types from zebrafish kidney via single-cell transcriptome profiling analysis. These populations included almost all known cells associated with innate and adaptive immunity, and displayed differential responses to viral infection, indicating their diverse functional roles in antiviral immunity. Remarkably, HSPCs were found to have extensive reactivities to viral infection, and the trained immunity can be effectively induced in certain HSPCs. In addition, the antigen-stimulated adaptive immunity can be fully generated in kidney, suggesting kidney acting as a secondary lymphoid organ. These results indicated that fish kidney is a dual-functional entity with functionalities of both primary and secondary lymphoid organs. Our findings illustrated the unique features of fish immune system, and highlighted the multifaced biology of kidney in ancient vertebrates.

immunology↗

bioRxiv2023

Colchicine promotes atherosclerotic plaque stability independently of inflammation

Atherosclerosis is a chronic inflammatory disease which is driven in part by the aberrant trans-differentiation of vascular smooth muscle cells (SMCs). No therapeutic drug has been shown to reverse detrimental SMC-derived cell phenotypes into protective phenotypes, a hypothesized enabler of plaque regression and improved patient outcome. Herein, we describe a novel function of colchicine in the beneficial modulation of SMC-derived cell phenotype, independent of its conventional anti-inflammatory effects. Using SMC fate mapping in an advanced atherosclerotic lesion model, colchicine induced plaque regression by converting pathogenic SMC-derived macrophage-like and osteoblast-like cells into protective myofibroblast-like cells which thickened, and thereby stabilized, the fibrous cap. This was dependent on Notch3 signaling in SMC-derived plaque cells. These findings may help explain the success of colchicine in clinical trials relative to other anti-inflammatory drugs. Thus, we demonstrate the potential of regulating SMC phenotype in advanced plaque regression through Notch3 signaling, in addition to the canonical anti-inflammatory actions of drugs to treat atherosclerosis.

cell biology↗