Biology subjects

Wu, P.-H.

Publications and source records attributed to Wu, P.-H..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

A TBX5-dependent compartment boundary patterns the cardiac interventricular septum

Failure of septation of the interventricular septum (IVS) is the most common congenital heart defect (CHD), but mechanisms for patterning the IVS are largely unknown. Here, we show that a Tbx5+/Mef2cAHF+ progenitor lineage forms a compartment boundary bisecting the IVS. This coordinated population originates at a first- and second heart field interface. Ablation of Tbx5+/Mef2cAHF+ progenitors cause IVS disorganization, right ventricular hypoplasia and mixing of IVS lineages. Reduced dosage of the CHD transcription factor TBX5 disrupts boundary position and integrity, resulting in ventricular septation defects (VSDs) and patterning defects, including misexpression of Slit2 and Ntn1, which encode guidance cues. Reducing NTN1 dosage partly rescues cardiac defects in Tbx5 mutant embryos. Loss of Slit2 or Ntn1 causes VSDs and perturbed septal lineage distributions. Thus, we identify Tbx5 as a candidate selector gene, directing progenitors and regulating essential cues, to pattern a compartment boundary for proper cardiac septation, revealing mechanisms for cardiac birth defects.

developmental biology↗

bioRxiv2023

Engineering self-propelled tumor-infiltrating CAR T cells using synthetic velocity receptors

Chimeric antigen receptor (CAR) T cells express antigen-specific synthetic receptors, which upon binding to cancer cells, elicit T cell anti-tumor responses. CAR T cell therapy has enjoyed success in the clinic for hematological cancer indications, giving rise to decade-long remissions in some cases. However, CAR T therapy for patients with solid tumors has not seen similar success. Solid tumors constitute 90% of adult human cancers, representing an enormous unmet clinical need. Current approaches do not solve the central problem of limited ability of therapeutic cells to migrate through the stromal matrix. We discover that T cells at low and high density display low- and high-migration phenotypes, respectively. The highly migratory phenotype is mediated by a paracrine pathway from a group of self-produced cytokines that include IL5, TNF, IFN{gamma}, and IL8. We exploit this finding to "lock-in" a highly migratory phenotype by developing and expressing receptors, which we call velocity receptors (VRs). VRs target these cytokines and signal through these cytokines cognate receptors to increase T cell motility and infiltrate lung, ovarian, and pancreatic tumors in large numbers and at doses for which control CAR T cells remain confined to the tumor periphery. In contrast to CAR therapy alone, VR-CAR T cells significantly attenuate tumor growth and extend overall survival. This work suggests that approaches to the design of immune cell receptors that focus on migration signaling will help current and future CAR cellular therapies to infiltrate deep into solid tumors.

immunology↗

bioRxiv2023

Three-dimensional reconstruction of fetal rhesus macaque kidneys at single-cell resolution reveals complex inter-relation of structures

Kidneys are among the most structurally complex organs in the body. Their architecture is critical to ensure proper function and is often impacted by diseases such as diabetes and hypertension. Understanding the spatial interplay between the different structures of the nephron and renal vasculature is crucial. Recent efforts have demonstrated the value of three-dimensional (3D) imaging in revealing new insights into the various components of the kidney; however, these studies used antibodies or autofluorescence to detect structures and so were limited in their ability to compare the many subtle structures of the kidney at once. Here, through 3D reconstruction of fetal rhesus macaque kidneys at cellular resolution, we demonstrate the power of deep learning in exhaustively labelling seventeen microstructures of the kidney. Using these tissue maps, we interrogate the spatial distribution and spatial correlation of the glomeruli, renal arteries, and the nephron. This work demonstrates the power of deep learning applied to 3D tissue images to improve our ability to compare many microanatomical structures at once, paving the way for further works investigating renal pathologies.

developmental biology↗

bioRxiv2023

Three-dimensional assessments are necessary to determine the true spatial tissue composition of diseased tissues

Methods for spatially resolved cellular profiling using thinly cut sections have enabled in-depth quantitative tissue mapping to study inter-sample and intra-sample differences in normal human anatomy and disease onset and progression. These methods often profile extremely limited regions, which may impact the evaluation of heterogeneity due to tissue sub-sampling. Here, we applied CODA, a deep learning-based tissue mapping platform, to reconstruct the three-dimensional (3D) microanatomy of grossly normal and cancer-containing human pancreas biospecimens obtained from individuals who underwent pancreatic resection. To compare inter-and intra-sample heterogeneity, we assessed bulk and spatially resolved tissue composition in a cohort of two-dimensional (2D) whole slide images (WSIs) and a cohort of thick slabs of pancreas tissue that were digitally reconstructed in 3D from serial sections. To demonstrate the marked under sampling of 2D assessments, we simulated the number of WSIs and tissue microarrays (TMAs) necessary to represent the compositional heterogeneity of 3D data within 10% error to reveal that tens of WSIs and hundreds of TMA cores are sometimes needed. We show that spatial correlation of different pancreatic structures decay significantly within a span of microns, demonstrating that 2D histological sections may not be representative of their neighboring tissues. In sum, we demonstrate that 3D assessments are necessary to accurately assess tissue composition in normal and abnormal specimens and in order to accurately determine neoplastic content. These results emphasize the importance of intra-sample heterogeneity in tissue mapping efforts.

cancer biology↗

bioRxiv2023

Colonization of Bacillus altitudinis on the Compatible Soybean Varieties to Provide Seed Rot Resistance

Seed health is crucial for plant growth and agricultural productivity. Recent studies have illustrated the importance of plant microbiome in disease resistance, however, it remains unclear whether the seed microbiome confers seed rot resistance against fungal pathogens. In this study, the application of antibiotics on the seeds of eight soybean varieties showed that seed-associated bacteria were involved in the seed rot resistance caused by Calonectria ilicicola, but this resistance cannot be carried to withstand root rot. Using PacBio 16S rDNA full-length sequencing and microbiome analyses, the seed microbiome was shown to mainly dependent on the soybean variety, and there was no consistent community network associated with seed rot resistance across soybean varieties. Instead, the seed-associated Bacillus altitudinis was identified through the differential abundance analysis and culture-dependent isolation. Moreover, qPCR confirmed the persistence of B. altitudinis on apical shoots till 21 days post-inoculation, but not on roots by 9 days post-inoculation. The short-term colonization of B. altitudinis on roots may explain the absence of root rot resistance. Furthermore, seed treated with B. altitudinis restored seed rot resistance, but only in the compatible soybean varieties. For the incompatible soybean varieties, B. altitudinis showed lower bacterial density and provided no seed protection. Collectively, this study advances the insight of B. altitudinis conferring seed rot resistance. These findings highlight the potential of using seed-associated bacteria for seed protection and underscore the importance of considering bacterial compatibility with plant genotypes and tissues.

plant biology↗

bioRxiv2023

Discrete somatotopic representation and neural response properties in hummingbird and zebra finch forebrain nuclei

Somatosensation allows animals to perceive the external world through touch, providing critical information about physical contact, temperature, pain, and body position. Somatosensory pathways, particularly those related to the rodent vibrissae, have been well-studied in mammals, illuminating principles of cortical organization and sensory processing 1,2. However, comparative studies across diverse vertebrate species are imperative to understand how somatosensory systems are shaped by evolutionary pressures and specialized ecological needs. Birds provide an excellent model for studying the evolution of somatosensation, as they exhibit remarkable diversity in body plans, sensory capabilities, and behavior. Prior work in pigeons3-6, parrots7, and finches8 have identified general tactile-responsive regions within the avian telencephalon. Yet how somatosensory maps and response properties vary across key avian groups remains unclear. Here, we aimed to elucidate somatotopic organization and neural coding in the telencephalon of Annas hummingbirds (Calypte anna) and zebra finches (Taeniopygia guttata). Using in vivo extracellular electrophysiological techniques, we recorded single and multi-unit activity in telencephalic regions of anesthetized hummingbirds and finches. We stimulated the beak, face, trunk, wings, and hindlimbs with controlled tactile stimuli and mapped somatosensory receptive fields. We found distinct representations of body regions distributed across multiple somatosensory zones, with surprising differences in relative areas devoted to key body surfaces, potentially as related to behavioral significance. Highlights{square} Somatosensation provides birds with critical information for behaviors necessary to survival including foraging and flight. {square}In vivo extracellular physiological recordings were used to monitor tactile responses in contralateral forebrain nuclei corresponding to the feather deflection in hummingbirds and finches including to air puff stimuli. {square}Both hummingbirds and finches show distinct separation of body and head receptive field representation in different nuclei. {square}A continuous somatotopic arrangement can be found in both the rostral Wulst (corresponding to the wings and body) and in nucleus basorostralis (corresponding to the head and beak), with particularly enlarged representations of the wing leading edge and the foot.

neuroscience↗

bioRxiv2023

Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework--a cell behavior hypothesis grammar--that uses natural language statements (cell rules) to create mathematical models. This allows us to systematically integrate biological knowledge and multi-omics data to make them computable. We can then perform virtual "thought experiments" that challenge and extend our understanding of multicellular systems, and ultimately generate new testable hypotheses. In this paper, we motivate and describe the grammar, provide a reference implementation, and demonstrate its potential through a series of examples in tumor biology and immunotherapy. Altogether, this approach provides a bridge between biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.

systems biology↗

bioRxiv2023

Precision-engineered biomimetics: the human fallopian tube

The fallopian tube has an essential role in several physiological and pathological processes from pregnancy to ovarian cancer. However, there are no biologically relevant models to study its pathophysiology. The state-of-the-art organoid model has been compared to two-dimensional tissue sections and molecularly assessed providing only cursory analyses of the models accuracy. We developed a novel multi-compartment organoid model of the human fallopian tube that was meticulously tuned to reflect the compartmentalization and heterogeneity of the tissues composition. We validated this organoids molecular expression patterns, cilia-driven transport function, and structural accuracy through a highly iterative platform wherein organoids are compared to a three-dimensional, single-cell resolution reference map of a healthy, transplantation-quality human fallopian tube. This organoid model was precision-engineered to match the human microanatomy. One sentence summaryTunable organoid modeling and CODA architectural quantification in tandem help design a tissue-validated organoid model.

bioengineering↗

bioRxiv2023

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

cancer biology↗

bioRxiv2022

Relaxed targeting rules allow PIWI-clade Argonaute proteins to silence ever-mutating transposons

In animals, piRNAs direct PIWI-clade Argonaute proteins to slice complementary transposon transcripts. Transposons can evade silencing through target site mutations. We report that PIWIs efficiently cleave transcripts only partially paired to their piRNA guide. Measurements of mouse PIWI protein affinity and cleavage rates for thousands of RNAs in vitro and in vivo show that PIWI slicing tolerates mismatches to any target nucleotide, including those flanking the scissile phosphate. Although piRNA 5 terminal nucleotides accelerate target finding, they are dispensable for binding or catalysis--unlike AGO-clade Argonautes, which require uninterrupted siRNA:target pairing from the seed to the nucleotides past the scissile bond. PIWIs are thus better equipped than AGOs to target newly acquired or rapidly diverging endogenous transposons without recourse to novel small RNA guides.

molecular biology↗

bioRxiv2022

Spatial transcriptomics of FFPE pancreatic intraepithelial neoplasias reveals cellular and molecular alterations of progression to pancreatic ductal carcinoma

Spatial transcriptomics (ST) is a powerful new approach to characterize the cellular and molecular architecture of the tumor microenvironment. Previous single-cell RNA-sequencing (scRNA-seq) studies of pancreatic ductal adenocarcinoma (PDAC) have revealed a complex immunosuppressive environment characterized by numerous cancer associated fibroblasts (CAFs) subtypes that contributes to poor outcomes. Nonetheless, the evolutionary processes yielding that microenvironment remain unknown. Pancreatic intraepithelial neoplasia (PanIN) is a premalignant lesion with potential to develop into PDAC, but the formalin-fixed and paraffin-embedded (FFPE) specimens required for PanIN diagnosis preclude scRNA-seq profiling. We developed a new experimental pipeline for FFPE ST analysis of PanINs that preserves clinical specimens for diagnosis. We further developed novel multi-omics analysis methods for threefold integration of imaging, ST, and scRNA-seq data to analyze the premalignant microenvironment. The integration of ST and imaging enables automated cell type annotation of ST spots at a single-cell resolution, enabling spot selection and deconvolution for unique cellular components of the tumor microenvironment (TME). Overall, this approach demonstrates that PanINs are surrounded by the same subtypes of CAFs present in invasive PDACs, and that the PanIN lesions are predominantly of the classical PDAC subtype. Moreover, this new experimental and computational protocol for ST analysis suggests a biological model in which CAF-PanIN interactions promote inflammatory signaling in neoplastic cells which transitions to proliferative signaling as PanINs progress to PDAC. SummaryPancreatic intraepithelial neoplasia (PanINs) are pre-malignant lesions that progress into pancreatic ductal adenocarcinoma (PDAC). Recent advances in single-cell technologies have allowed for detailed insights into the molecular and cellular processes of PDAC. However, human PanINs are stored as formalin-fixed and paraffin-embedded (FFPE) specimens limiting similar profiling of human carcinogenesis. Here, we describe a new analysis protocol that enables spatial transcriptomics (ST) analysis of PanINs while preserving the FFPE blocks required for clinical assessment. The matched H&E imaging for the ST data enables novel machine learning approaches to automate cell type annotations at a single-cell resolution and isolate neoplastic regions on the tissue. Transcriptional profiles of these annotated cells enable further refinement of imaging-based cellular annotations, showing that PanINs are predominatly of the classical subtype and surrounded by PDAC cancer associated fibroblast (CAF) subtypes. Applying transfer learning to integrate ST PanIN data with PDAC scRNA-seq data enables the analysis of cellular and molecular progression from PanINs to PDAC. This analysis identified a transition between inflammatory signaling induced by CAFs and proliferative signaling in PanIN cells as they become invasive cancers. Altogether, this integration of imaging, ST, and scRNA-seq data provides an experimental and computational approach for the analysis of cancer development and progression.

cancer biology↗

bioRxiv2022

Mechanotransductive feedback control of endothelial cell motility and vascular morphogenesis

Vascular morphogenesis requires persistent endothelial cell motility that is responsive to diverse and dynamic mechanical stimuli. Here, we interrogated the mechanotransductive feedback dynamics that govern endothelial cell motility and vascular morphogenesis. We show that the transcriptional regulators, YAP and TAZ, are activated by mechanical cues to transcriptionally limit cytoskeletal and focal adhesion maturation, forming a conserved mechanotransductive feedback loop that mediates human endothelial cell motility in vitro and zebrafish intersegmental vessel (ISV) morphogenesis in vivo. This feedback loop closes in 4 hours, achieving cytoskeletal equilibrium in 8 hours. Feedback loop inhibition arrested endothelial cell migration in vitro and ISV morphogenesis in vivo. Inhibitor washout at 3 hrs, prior to feedback loop closure, restored vessel growth, but washout at 8 hours, longer than the feedback timescale, did not, establishing lower and upper bounds for feedback kinetics in vivo. Mechanistically, YAP and TAZ induced transcriptional suppression of RhoA signaling to maintain dynamic cytoskeletal equilibria. Together, these data establish the mechanoresponsive dynamics of a transcriptional feedback loop necessary for persistent endothelial cell migration and vascular morphogenesis.

cell biology↗

bioRxiv2022

Quantum CART (qCART), a piggyBac-based system for development and production of virus-free multiplex CAR-T cell therapy

Chimeric antigen receptor T (CAR-T) cell therapy has the potential to transform cancer treatment. However, CAR-T therapy application is currently limited to certain types of relapsed/refractory B cell lymphomas. To unlock the full potential of CAR-T therapy, technologic breakthroughs will be needed in multiple areas, including optimization of autologous CAR-T development, shortening the innovation cycle, and further manufacturing advancement of next-generation CAR-T therapies. Here, we established a simple and robust virus-free multiplex Quantum CART system that seamlessly and synergistically integrates four platforms: 1. GTailor for rapid identification of lead CAR construct design, 2. Quantum Nufect for effective but gentle electroporation-based gene delivery, 3. Quantum pBac, featuring a virus-free transposon-based vector with large payload capacity and integration profile similar to retrovirus, and 4. iCellar for robust and high-quality CAR+ T memory stem cell expansion. This robust, virus-free multiplex Quantum CART system is expected to unleash the full potential of CAR-T therapy for treating diseases.

cancer biology↗

bioRxiv2022

Manufacturing highly potent CD20/CD19-targeted iCasp9 regulatable CAR-T cells using the Quantum pBac-based CAR-T (qCART) system for clinical application

BackgroundCD19-targeted chimeric antigen receptor therapies (CAR19) have driven a paradigm shift in the treatment of relapsed/refractory B-cell malignancies. However, >50% of CAR19-treated patients experienced progressive disease mainly due to antigen escape and low persistence. Clinical prognosis is heavily influenced by CAR-T cell function and systemic cytokine toxicities. Furthermore, it remains a challenge to efficiently, cost-effectively, and consistently manufacture clinically relevant number of virally engineered CAR-T cells. MethodsUsing a highly efficient piggyBac transposon-based vector, Quantum pBac, we developed a virus-free cell engineering system, Quantum CART (qCART), for development and production of multiplex CAR-T therapies. ResultsHere, we demonstrated in vitro and in vivo that consistent, robust, and functional CD20/CD19 dual-targeted CAR-T stem cell memory (TSCM) cells can be efficiently manufactured using the qCART system for clinical application. qCART-manufactured CAR-T cells from cancer patients expanded efficiently, rapidly eradicated tumors, and can be safely controlled via an iCasp9 suicide gene-inducing drug. ConclusionsThe qCART system is an elegant system for the manufacturing of CAR-T products having all the desired CAR-T therapy attributes. We believe that the simplicity of manufacturing multiplex CAR-T cells using the qCART system will not only significantly enhance the accessibility of CAR-T therapy but also unlock the full potential of armored CAR-T therapy for the treatment of solid tumors in the future. What is already known on this topicDespite the considerable success which has been achieved with CD19-targeted chimeric antigen receptor therapies (CAR19), >50% of CAR19-treated patients still experienced progressive disease. Therefore, there is a need to further improve CAR19 therapies. Current CAR19 therapies commonly utilize virus-based cell engineering methods. CAR-T production using these methods face multiple hurdles, including difficulties to efficiently, cost-effectively, and consistently manufacture clinically relevant number of CAR-T cells. We have previously used a highly efficient piggyBac transposon-based vector, Quantum pBac, to establish Quantum CART (qCART) which is a virus-free cell engineering system for development and production of multiplex CAR-T therapies. What this study addsIn this report, we further demonstrate in vitro and in vivo that consistent, robust, and functional iCasp9-regulatable, CD20/CD19 dual-targeted CAR-T stem cell memory (TSCM) cells can be efficiently manufactured using the qCART system for clinical application. These cells possess all the desired attributes for ensuring therapeutic efficacy in CAR-T therapy, including high CAR-TSCM, balanced CD8/CD4 ratio, low exhaustion and senescence marker expressions, and high ex vivo and in vivo expansion capacity. Importantly, we show that qCART-manufactured CAR-T cells from hematological cancer patients expanded efficiently, effectively eradicated tumors, and can be safely controlled via an iCasp9 suicide gene-inducing drug. We believe that the simplicity of manufacturing multiplex CAR-T cells using the qCART system will not only significantly enhance the accessibility of CAR-T therapy but also unlock the full potential of armored CAR-T therapy for the treatment of solid tumors in the future. How this study might affect research, practice or policyOur findings demonstrate that qCART is a virus-free CAR-T engineering system for manufacturing CAR-TSCM cells from either healthy donors or hematological cancer patients, that possess all the desired attributes for a successful CAR-T therapy. These cells expanded efficiently, rapidly eradicated tumors, and can be safely controlled via activation of iCasp9. We expect that this simple yet robust system for manufacturing multiplex CAR-T cells will advance the CAR-T field.

cancer biology↗

bioRxiv2020

Deep Learning Identification of Stiffness Markers in Breast Cancer

While essential to our understanding of solid tumor progression, the study of cell and tissue mechanics has yet to find traction in the clinic. Determining tissue stiffness, a mechanical property known to promote a malignant phenotype in vitro and in vivo, is not part of the standard algorithm for the diagnosis and treatment of breast cancer. Instead, clinicians routinely use mammograms to identify malignant lesions and radiographically dense breast tissue is associated with an increased risk of developing cancer. Whether breast density is related to tumor tissue stiffness, and what cellular and non-cellular components of the tumor contribute the most to its stiffness are not well understood. Through training of a deep learning network and mechanical measurements of fresh patient tissue, we create a bridge in understanding between clinical and mechanical markers. The automatic identification of cellular and extracellular features from hematoxylin and eosin (H&E)-stained slides reveals that global and local breast tissue stiffness best correlate with the percentage of straight collagen. Global breast tissue mechanics correlate weakly with the percentage of blood vessels and fibrotic tissue, and non-significantly with the percentage of fat, ducts, tumor cells, and wavy collagen in tissue. Importantly, the percentage of dense breast tissue does not directly correlate with tissue stiffness or straight collagen content.

cancer biology↗

bioRxiv2020

In situ characterization of the 3D microanatomy of the pancreas and pancreatic cancer at single cell resolution

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest forms of cancer. Accumulating evidence indicates the tumor microenvironment is highly associated with tumorigenesis through regulation of cellular physiology, signaling systems, and gene expression profiles of cancer cells. Yet the mechanisms by which the microenvironment evolves from normal pancreas architecture to precursor lesions and invasive cancer is poorly understood. Obtaining high-content and high-resolution information from a complex tumor microenvironment in large volumetric landscapes represents a key challenge in the field of cancer biology. To address this challenge, we established a novel method to reconstruct three-dimensional (3D) centimeter-scale tissues containing billions of cells from serially sectioned histological samples, utilizing deep learning approaches to recognize eight distinct tissue subtypes from hematoxylin and eosin stained sections at micrometer and single-cell resolution. Using samples from a range of normal, precancerous, and invasive pancreatic cancer tissue, we map in 3D modes of cancer invasion in the tumor microenvironment, and emphasize the need for further 3D quantification of biological systems.

cancer biology↗

bioRxiv2020

Mycena genomes resolve the evolution of fungal bioluminescence

Mushroom-forming fungi in the order Agaricales represent an independent origin of bioluminescence in the tree of life, yet the diversity, evolutionary history, and timing of the origin of fungal luciferases remain elusive. We sequenced the genomes and transcriptomes of five bonnet mushroom species (Mycena spp.), a diverse lineage comprising the majority of bioluminescent fungi. Two species with haploid genome assemblies [~]150Mb are amongst the largest in Agaricales, and we found that a variety of repeats between Mycena species were differentially mediated by DNA methylation. We show that bioluminescence evolved in the last common ancestor of mycenoid and the marasmioid clade of Agaricales and was maintained through at least 160 million years of evolution. Analyses of synteny across genomes of bioluminescent species resolved how the luciferase cluster was derived by duplication and translocation, frequently rearranged and lost in most Mycena species, but conserved in the Armillaria lineage. Luciferase cluster members were co-expressed across developmental stages, with highest expression in fruiting body caps and stipes, suggesting fruiting-related adaptive functions. Our results contribute to understanding a de novo origin of bioluminescence and the corresponding gene cluster in a diverse group of enigmatic fungal species. SignificanceWe present the genomes of five new bonnet mushroom Mycena species, formerly the last fungal bioluminescent lineage lacking reference genomes. These genome-scale datasets allowed us to construct an evolutionary model pinpointing all possible changes in the luciferase cluster across all fungi and additional genes involved in bioluminescence. We show that luciferase clusters were differentially lost in different fungal lineages and in particular a substantial loss was observed in the Mycena lineage. This can be attributed to genome regions of Mycena underwent different evolutionary dynamics. Our findings offer insights into the evolution of how a gene cluster that emerged 160 million years ago and was frequently lost or maintained due to differences in genome plasticity.

genomics↗

bioRxiv2020

Fractional re-distribution among cell motility states during ageing

Ageing in humans is associated with a decreased capacity to regulate cell physiology. Cellular properties, such as cell morphology and cell mechanics, encode ageing information and as a result can be used as robust ageing biomarkers. Using a panel of dermal fibroblasts derived from healthy donors spanning a wide age range, we observe an age-related reduction in average cell motility, which we show is not due to the decreased motility of all cells, but results from fractional re-distribution among motility states. By taking advantage of the single-cell nature of our motility data, we show that cells can be classified based on spatial and activity patterns that define age-dependent motility states. These findings highlight an important feature of ageing cells shown by the decrease in the heterogeneity of cell movement in older adults, that potentially offer new mechanistic insights into the ageing process and avenues for novel biomarker development.

bioengineering↗