Biology subjects

Du, K.

Publications and source records attributed to Du, K..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

A Comprehensive Proteogenomic and Spatial Analysis of Innate and Acquired Resistance of Metastatic Melanoma to Immune Checkpoint Blockade Therapies

While a subset of patients with metastatic melanoma achieves durable responses to immune checkpoint blockade (ICB) therapies, the majority ultimately exhibit either innate or acquired resistance to these treatments. However, the molecular mechanisms underlying resistance to ICB therapies remain elusive and are warranted to elucidate. Here, we comprehensively investigated the tumor and tumor immune microenvironment (TIME) of paired pre- and post-treatment tumor specimens from metastatic melanoma patients who were primary or secondary resistance to anti-CTLA-4 and/or anti-PD-1/PD-L1 therapies. Differentially expressed gene (DEG) analysis and single-sample gene set enrichment analysis (ssGSEA) with transcriptomic data identified cell cycle and c-MYC signaling as pathway-based resistance signatures. And weighted gene co-expression network analysis (WGCNA) revealed the activation of a cross-resistance meta-program involving key signaling pathways related to tumor progression in ICB resistant melanoma. Moreover, spatially-resolved, image-based immune monitoring analysis by using NanoStrings digital spatial profiling (DSP) and Cyclic Immunofluorescence (CyCIF) showed infiltration of suppressive immune cells in the tumor microenvironment of melanoma with resistance to ICB therapies. Our study reveals the molecular mechanisms underlying resistance to ICB therapies in patients with metastatic melanoma by conducting such integrated analyses of multi-dimensional data, and provides rationale for salvage therapies that will potentially overcome resistance to ICB therapies. Statement of translational relevanceThis study paves the way for the creation of innovative therapeutic strategies, aimed at subverting resistance to immune checkpoint blockade (ICB) therapies in metastatic melanoma patients. By unraveling the specific molecular mechanisms underlying resistance, scientists can design effective alternative treatments that target pathways such as pathways associated with cell cycle dysregulation and c-MYC signaling. Furthermore, through the application of advanced immune monitoring techniques such as NanoString Digital Spatial Profiling (DSP) and Cyclic Immunofluorescence (CyCIF), this study has significantly enriched our understanding of the tumor microenvironment. This enhanced characterization facilitates the discovery of potential biomarkers that may forecast a patients response to ICB treatment. Ultimately, these advancements could potentially refine patient outcomes and foster the development of more personalized cancer treatments in the future.

genetics↗

bioRxiv2024

Durable Antimicrobial Microstructure Surface (DAMS) Enabled by 3D-Printing and ZnO Nanoflowers

A.Numerous studies have been trying to create nanomaterials based antimicrobial surfaces to combat the growing bacterial infection problems. Mechanical durability has become one of the major challenges to applying those surfaces in real life. In this study, we demonstrate the Durable Antimicrobial Microstructures Surface (DAMS) consisting of DLP 3D printed microstructures and zinc oxide (ZnO) nanoflowers. The microstructures serve as a protection armor for the nanoflowers during abrasion. The antimicrobial ability was tested by immersing in 2E8 CFU/mL Escherichia coli (E. coli) suspension and then evaluated using electron microscopy. Compared to the bare control, our results show that the DAMS reduces bacterial coverage by more than 90% after 12 hrs of incubation and approximately 50% after 48 hrs of incubation before abrasion. Importantly, bacterial coverage is reduced by approximately 50% after 2 min of abrasion with a tribometer, and DAMS remains effective even after 6 min of abrasion. These findings highlight the potential of DAMS as an affordable, scalable, and durable antimicrobial surface for various biomedical applications.

bioengineering↗

bioRxiv2024

Segregation between an ornamental and a disease driver gene provides insights into pigment cell regulation

Genetic interactions are adaptive within a species. Hybridization can disrupt such species-specific genetic interactions and creates novel interactions that alter the hybrid progeny overall fitness. Hybrid incompatibility, which refers to degenerative genetic interactions that decrease the overall hybrid survival, is one of the results from combining two diverged genomes in hybrids. The discovery of spontaneous lethal tumorigenesis and underlying genetic interactions in select hybrids between diverged Xiphophorus species showed that lethal pathological process can result from degenerative genetic interactions. Such genetic interactions leading to lethal phenotype are thought to shield gene flow between diverged species. However, hybrids between certain Xiphophorus species do not develop such tumors. Here we report the identification of a locus residing in the genome of one Xiphophorus species that represses an oncogene from a different species. Our finding provides insights into normal and pathological pigment cell development, regulation and molecular mechanism in hybrid incompatibility. SignificanceThe Dobzhansky-Muller model states epistatic interactions occurred between genes in diverged species underlies hybrid incompatibility. There are a few vertebrate interspecies hybrid cases that support the Dobzhansky-Muller model. This study reports a fish hybrid system where incompatible genetic interactions are involved in neuronal regulation of pigment cell biology, and also identified a novel point of regulation for pigment cells.

genetics↗

bioRxiv2024

Population origin, body mass, and viral infections influence drone honey bee (Apis mellifera) heat tolerance

Extreme temperatures associated with climate change are expected to impact the physiology and fertility of a variety of insects, including honey bees. Most previous work has focused on female honey bees, and comparatively little research has investigated how heat exposure affects males (drones). To address this gap, we tested how body mass, viral infections, Africanization, and geographic origin (including stocks from Australia, California, and Ukraine as well as diverse locations within British Columbia, Canada) influenced drone and sperm heat tolerance. We found that individual body size was highly influential, with heavier drones being more likely to survive a heat challenge than smaller drones. Drones originating from feral colonies in Southern California (which are enriched for African genetics) were also more likely to survive a heat challenge than drones originating from commercially-supplied Californian stock. We found no association between drone mass and thermal tolerance of sperm over time in an in vitro challenge assay, but experimental viral infection decreased the heat tolerance of sperm. Overall, there is ample variation in sperm heat tolerance, with sperm from some groups displaying remarkable heat resilience and sperm from others being highly sensitive, with additional factors influencing heat tolerance of the drones themselves.

physiology↗

bioRxiv2024

Complex structural variation and behavioral interactions underpin a balanced sexual mimicry polymorphism

How phenotypic diversity originates and persists within populations are classic puzzles in evolutionary biology. While polymorphisms hypothesized to be under balancing selection segregate within many species, it remains rare for the genetic basis and the selective forces to both be known for the same trait, leading to an incomplete understanding of many classes of polymorphisms. Here, we uncover the genetic architecture of a balanced sexual mimicry polymorphism and identify behavioral mechanisms that may be involved in its maintenance in the swordtail fish Xiphophorus birchmanni. We find that [~]40% of X. birchmanni males develop a "false gravid spot", a melanic pigmentation pattern that mimics the "pregnancy spot" associated with sexual maturity in female live-bearing fish. Using genome-wide association mapping, we detect a single intergenic region associated with variation in the false gravid spot, which is upstream of kitlga, a gene involved in melanophore patterning. By performing long-read sequencing within and across populations, we identify complex structural rearrangements between alternate alleles at this locus. The false gravid spot haplotype drives increased allele-specific expression of kitlga, which provides a mechanistic explanation for the increased melanophore abundance that causes the spot. By studying social interactions in the laboratory and in nature, we find that males with the false gravid spot experience less aggression; however, they also receive increased attention from other males and are disdained by females. These behavioral interactions may play a role in maintaining this phenotypic polymorphism in natural populations. We speculate that structural variants affecting gene regulation may be an underappreciated driver of balanced polymorphisms across diverse species.

evolutionary biology↗

bioRxiv2024

MetaWorm: A Complete Model Bridging Brain, Body and Environment of C. elegans

The behavior of an organism is profoundly influenced by the complex interplay between its brain, body, and environment. Existing data-driven models focusing on either the brain or the body-environment separately. A model that integrates these two components is yet to be developed. Here, we present MetaWorm, an integrative data-driven model of a widely studied organism, C. elegans. This model consists of two sub-models: the brain model and the body & environment model. The brain model was built by multi-compartment models with realistic morphology, connectome, and neural population dynamics based on experimental data. Simultaneously, the body & environment model employed a lifelike body and a 3D physical environment, facilitating easy behavior quantification. Through the closed-loop interaction between two sub-models, MetaWorm faithfully reproduced the realistic zigzag movement towards attractors observed in C. elegans. Notably, MetaWorm is the first model to achieve seamless integration of detailed brain, body, and environment simulations, enabling unprecedented insights into the intricate relationships between neural structures, neural activities, and behaviors. Leveraging this model, we investigated the impact of neural system structure on both neural activities and behaviors. Consequently, MetaWorm can enhance our understanding of how the brain controls the body to interact with its surrounding environment.

neuroscience↗

bioRxiv2024

Phylogenomics analyses of all species of Swordtails (Genus Xiphophorus) highlights hybridization precedes speciation

Hybridization has been recognized as an important driving force for evolution, however studies of the genetic consequence and its cause are still lagging behind in vertebrates due to the lack of appropriate experimental systems. Fish of the central American genus Xiphophorus were proposed to have evolved with multiple ancient and ongoing hybridization events, and served as a valuable research model in evolutionary biology and in biomedical research on human disease for more than a century. Here, we provide the complete genome resource and its annotation of all 26 Xiphophorus species. On this dataset we resolved the so far conflicting phylogeny. Through comparative genomic analyses we investigated the molecular evolution of genes related to melanoma, for a main sexually selected trait and for the genetic control of puberty timing, which are predicted to be involved in pre-and postzygotic isolation and thus to influence the probability of interspecific hybridization in Xiphophorus. We demonstrate dramatic size-variation of some gene families across species, despite the reticulate evolution and short divergence time. Finally, we clarify the hybridization history in the genus Xiphophorus genus, settle the long dispute on the hybridization origin of two Southern swordtails, highlight hybridizations precedes speciation, and reveal the distribution of hybridization ancestry remaining in the fused genome.

genomics↗

bioRxiv2023

Genome evolution is surprisingly predictable after initial hybridization

Over the past two decades, evolutionary biologists have come to appreciate that hybridization, or genetic exchange between distinct lineages, is remarkably common - not just in particular lineages but in taxonomic groups across the tree of life. As a result, the genomes of many modern species harbor regions inherited from related species. This observation has raised fundamental questions about the degree to which the genomic outcomes of hybridization are repeatable and the degree to which natural selection drives such repeatability. However, a lack of appropriate systems to answer these questions has limited empirical progress in this area. Here, we leverage independently formed hybrid populations between the swordtail fish Xiphophorus birchmanni and X. cortezi to address this fundamental question. We find that local ancestry in one hybrid population is remarkably predictive of local ancestry in another, demographically independent hybrid population. Applying newly developed methods, we can attribute much of this repeatability to strong selection in the earliest generations after initial hybridization. We complement these analyses with time-series data that demonstrates that ancestry at regions under selection has remained stable over the past [~]40 generations of evolution. Finally, we compare our results to the well-studied X. birchmannixX. malinche hybrid populations and conclude that deeper evolutionary divergence has resulted in stronger selection and higher repeatability in patterns of local ancestry in hybrids between X. birchmanni and X. cortezi.

evolutionary biology↗

bioRxiv2023

Micropillar enhanced FRET-CRISPR biosensor for nucleic acid detection

CRISPR technology has gained widespread adoption for pathogen detection due to its exceptional sensitivity and specificity. Although recent studies have investigated the potential of high-aspect-ratio microstructures in enhancing biochemical applications, their application in CRISPR-based detection has been relatively rare. In this study, we developed a FRET-based biosensor in combination with high-aspect-ratio microstructures and Cas12a-mediated trans-cleavage for detecting HPV 16 DNA fragments. Remarkably, our results show that micropillars with higher density exhibit superior molecular binding capabilities, leading to a tenfold increase in detection sensitivity. Furthermore, we investigated the effectiveness of two surface chemical treatment methods for enhancing the developed FRET assay. A simple and effective approach was also developed to mitigate bubble generation in microfluidic devices, a crucial issue in biochemical reactions within such devices. Overall, this work introduces a novel approach using micropillars for CRISPR-based viral detection and provides valuable insights into optimizing biochemical reactions within microfluidic devices.

bioengineering↗

bioRxiv2023

Pneumatic Nano-Sieve for CRISPR-based Detection of Drug-resistant Bacteria

The increasing prevalence of antibiotic-resistant bacterial infections, particularly methicillin-resistant Staphylococcus aureus (MRSA), presents a significant public health concern. Timely detection of MRSA is crucial to enable prompt medical intervention, limit its spread, and reduce antimicrobial resistance. Here, we introduce a miniaturized nano-sieve device featuring a pneumatically-regulated chamber for highly efficient MRSA purification from human plasma samples. By using packed magnetic beads as a filter and leveraging the deformability of the nano-sieve channel, we achieve an on-chip concentration factor of 15 for MRSA. We integrated this device with recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas detection system, resulting in an on-chip limit of detection (LOD) of approximately 100 CFU/mL. This developed approach provides a rapid, precise, and centrifuge-free solution suitable for point-of-care diagnostics, with the potential to significantly improve patient outcomes in resource-limited medical conditions.

bioengineering↗

bioRxiv2023

Extracting herbicide and antibiotic natural products from a plant-microbe interaction system

Plants and their associated microbes live in complicated, changeable, and unpredictable environments. They usually interact with each other in many ways by proceeding in multi-dimensional, multi-scale and multi-level coupling manners, leading to challenges of the co-existence of randomness and determinism, or continuity and discreteness. Gaining a deeper understanding of these diverse interaction mechanisms can facilitate the development of new data mining theories and methods for complex systems, new coupled modelling for the system with different spatiotemporal scales and functional properties, or even universal theory of information and information interactions. In this study, we use a "close-loop" model to present a plant-microbe interaction system and describe the probable functions from the microbial natural products. Specifically, we report a rhizosphere species, Streptomyces ginsengnesis G7, which produces polyketide lydicamycins and other active metabolites. Interestingly, these distinct molecules have the potential to function both as antibiotics and herbicides for crop protection. Detailed laboratory experiments combined with comprehensive bioinformatics analysis allow us to rationalise a model for this specific plant-microbe interaction process. Our work reveals the benefits of exploring otherwise neglectable resources for the identification of novel functional molecules and provides a good reference to better understand the system biology in the complex ecosystems.

cell biology↗

bioRxiv2023

Superhydrophobic Rotation-Chip for Computer-Vision Identification of Drug-Resistant Bacteria

The transport, distribution, and mixing of microfluidics often require additional instruments, such as pumps and valves, which are not feasible when operated in point-of-care (POC) settings. Here, we present a simple microfluidic pathogen detection system known as Rotation-Chip that transfers the reagents between wells by manually rotating two concentric layers without using external instruments. The Rotation-Chip is fabricated by a simple computer numerical control (CNC) machining process and is capable of carrying out 60 multiplexed reactions with a simple 30-degree or 60-degree rotation. Leveraging superhydrophobic coating, a high fluid transport efficiency of 92.78% is achieved without observable leaking. Integrated with an intracellular fluorescent assay, an on-chip detection limit of 1.8x106 CFU/mL is achieved for ampicillin-resistant Escherichia coli (E. coli), which is similar to our off-chip results. We also develop a computer vision method to automatically distinguish positive and negative samples on the chip, showing 100% accuracy. Our Rotation-Chip is simple, low-cost, high-throughput, and can display test results with a single chip image, ideal for various multiplexing POC applications in resource-limited settings.

bioengineering↗

bioRxiv2022

Domain Adaptive Neural Inference for Neurons, Microcircuits and Networks

Accurately inferring neural circuit connectivity from in vivo recordings is essential for understanding the computations that support behavior and cognition. However, current deep learning approaches are limited by incomplete observability and the lack of ground-truth labels in real experiments. Consequently, models are often trained on synthetic data, which leads to the well-known "model mismatch" problem when simulated dynamics diverge from true neural activity. To overcome these challenges, we present Deep Domain-Adaptive Matching (DeepDAM), a training framework that adaptively matches synthetic and in vivo data domains for neural connectivity inference. Specifically, DeepDAM fine-tunes deep neural networks on a combined dataset of synthetic simulations and unlabeled in vivo recordings, aligning the models feature representations with real neural dynamics to mitigate model mismatch. We demonstrate this approach in rodent hippocampal CA1 circuits as a proof-of-concept, achieving near-perfect connectivity inference performance (Matthews correlation coefficient [~]0.97-1.0) and substantially surpassing classical methods ([~]0.6-0.7). We further demonstrate robustness across multiple recording conditions within this hippocampal dataset. Additionally, to illustrate its broader applicability, we extend the framework to two distinct systems without altering the core methodology: a stomatogastric microcircuit in Cancer borealis (ex vivo) and single-neuron intracellular recordings in mouse, where DeepDAM significantly improves efficiency and accuracy over standard approaches. By effectively leveraging synthetic data for in vivo and ex vivo analysis, DeepDAM offers a generalizable strategy for overcoming model mismatch and represents a critical step towards data-driven reconstruction of functional neural circuits.

neuroscience↗

bioRxiv2022

Pneumatic Controlled Nano-Sieve for Efficient Capture and Release of Nanoparticles

A pneumatic controlled nano-sieve device is demonstrated for the efficient capture and release of 15 nm quantum dots. This device consists of a 200 nm deep glass channel and a PDMS-based pneumatic pressure layer to enhance target capture. The fluid motion inside the nano-sieve is studied by computational fluidic dynamics (CFD) and microfluidic experiments, enabling efficient target capture with a flow rate as high as 100 L/min. In addition, micro-grooves are fabricated inside the nano-sieve to create low flow rate regions, which further improves the target capture efficiency. A velocity contour plot is constructed with CFD, revealing the flow rate is lowest at the top and bottom of the micro-grooves. This phenomenon is supported by the observed nanoparticle clusters surrounding the micro-grooves. By changing the morphology and pneumatic pressure, this device will also facilitate rapid capture and release of various biomolecules.

bioengineering↗

bioRxiv2022

A computational framework linking synaptic adaptation to circuit behaviors in the early visual system

Retina ribbon synapses are the first synapses in the visual system. Unlike the conventional synapses in the central nervous system triggered by action potentials, ribbon synapses are uniquely driven by graded membrane potentials and are thought to transfer early sensory information faithfully. However, how ribbon synapses compress the visual signals and contribute to visual adaptation in retina circuits is less understood. To this end, we introduce a physiologically constrained module for the ribbon synapse, termed Ribbon Adaptive Block (RAB), and an extended "hierarchical Linear-Nonlinear-Synapse" (hLNS) framework for the retina circuit. Our models can elegantly reproduce a wide range of experimental recordings on synaptic and circuit-level adaptive behaviors across different cell types and species. In particular, it shows strong robustness to unseen stimulus protocols. Intriguingly, when using the hLNS framework to fit intra-cellular recordings from the retina circuit under stimuli similar to natural conditions, we revealed rich and diverse adaptive time constants of ribbon synapses. Furthermore, we predicted a frequency-sensitive gain-control strategy for the synapse between the photoreceptor and the CX bipolar cell, which differ from the classic contrast-based strategy in retina circuits. Overall, our framework provides a powerful analytical tool for exploring synaptic adaptation mechanisms in early sensory coding.

neuroscience↗

bioRxiv2022

The Effects of CdSe/ZnS Quantum Dots on the Photosynthesis Rate of the Chlorella Vulgaris Beads

Photosynthesizing microalgae produce more than 50% of oxygen in the atmosphere and are crucial for the survival of many living systems such as coral reefs. To address the declining of coral reefs, artificial reefs have been introduced to encapsulate the aglae cells in a polymer matrix but the effects of nanoscale pollutants on these engineered systems have not been fully understood. In this work, quantum dots with a size smaller than 10 nm are being used to elucidate the photosynthesis performance of the sodium alginate beads encapsulated with Chlorella vulgaris (C. vulgaris). The fluorescent quantum dots can move into the alginate matrix and the fluorescence intensity in the algae beads is correlated with the quantum dot concentration. We further show that the photosynthesis of the algae beads are sensitive to the quantum dot concentration and are also time sensitive. In the first 48 min of quantum dot exposure, both carbon dioxide absorption and oxygen production are low, suggesting limited photosynthesis. After the initial incubation, the photosynthesis rate quickly increases even though more inhibition is still observed with higher concentration of the quantum dots.

bioengineering↗

bioRxiv2022

linc-mipep and linc-wrb encode micropeptides that regulate chromatin accessibility in vertebrate-specific neural cells

Thousands of long intergenic non-coding RNAs (lincRNAs) are transcribed throughout the vertebrate genome. A subset of lincRNAs enriched in developing brains has recently been found to contain cryptic open reading frames and are speculated to encode micropeptides. However, systematic identification and functional assessment of these transcripts have been hindered by technical challenges caused by their small size. Here we show that two putative lincRNAs (linc-mipep and linc-wrb) encode micropeptides with homology to the vertebrate-specific chromatin architectural protein, Hmgn1, and demonstrate that they are required for development of vertebrate-specific brain cell types. Specifically, we show that NMDA receptor-mediated pathways are dysregulated in zebrafish lacking these micropeptides and that their loss preferentially alters the gene regulatory networks that establish cerebellar cells and oligodendrocytes - evolutionarily newer cell types that develop postnatally in humans. These findings highlight the power of screening for unexplored micropeptide functions by revealing a key missing link in the evolution of vertebrate brain cell development and illustrating a genetic basis for how some neural cell types are more susceptible to chromatin disruptions, with implications for neurodevelopmental disorders and disease.

developmental biology↗

bioRxiv2022

On-Demand Fully-Enclosed Superhydrophobic-Optofluidic Device Enabled by High Precision Microstereolithography

Superhydrophobic surface-based optofluidics have been introduced to biosensors and unconventional optics with unique advantages such as low light loss and power consumption. However, most of these platforms were made with planar-like micro- and nano-structures, which may cause bonding issues and resulting in significant waveguide loss. Here, we introduce a fully-enclosed superhydrophobic-based optofluidics system, enabled by a one-step high precision microstereolithography procedure. Various micro-structured cladding designs with a feature size down to 100 m were studied and a "T-type" overhang design exhibits the lowest optical loss, regardless of the excitation wavelength. Surprisingly, the optical loss of superhydrophobic-based optofluidics is not solely decided by the solid area fraction at the solid/water/air interface, but also the cross-section shape and the effective cladding layer composition. We show that this fully-enclosed optofluidic system can be used for CRISPR-labeled quantum dot quantification, intended for in vitro and in vivo CRISPR therapeutics.

bioengineering↗