Biology subjects

Tran, E.

Publications and source records attributed to Tran, E..

29 records · Page 2Linked to original sources

bioRxiv2023

Multiomic Single Cell Sequencing Identifies Stemlike Nature of Mixed Phenotype Acute Leukemia and Provides Novel Risk Stratification

Mixed phenotype acute leukemia (MPAL) is a leukemia whose biologic drivers are poorly understood, therapeutic strategy remains unclear, and prognosis is poor. We performed multiomic single cell (SC) profiling of 14 newly diagnosed adult MPAL patients to characterize the immunophenotypic, genetic, and transcriptional landscapes of MPAL. We show that neither genetic profile nor transcriptome reliably correlate with specific MPAL immunophenotypes. However, progressive acquisition of mutations is associated with increased expression of immunophenotypic markers of immaturity. Using SC transcriptional profiling, we find that MPAL blasts express a stem cell-like transcriptional profile distinct from other acute leukemias and indicative of high differentiation potential. Further, patients with the highest differentiation potential demonstrated inferior survival in our dataset. A gene set score, MPAL95, derived from genes highly enriched in this cohort, is applicable to bulk RNA sequencing data and was predictive of survival in an independent patient cohort, suggesting utility for clinical risk stratification.

cancer biology↗

bioRxiv2023

Phyllosphere fungal diversity generates pervasive non-additive effects on plant performance

O_LIAll plants naturally harbor diverse microbiomes that can dramatically impact their health and productivity. However, it remains unclear how microbiome diversity, especially in the phyllosphere, impacts intermicrobial interactions and consequent non-additive effects on plant productivity. C_LIO_LICombining manipulative experiments, field collections, culturing, microbiome sequencing, and synthetic consortia, we experimentally tested for the first time how foliar fungal community diversity impacts plant productivity. We inoculated morning glories with 32 synthetic phyllosphere communities of either low or high diversity or with single fungal taxa, and measured effects on plant productivity and allocation. C_LIO_LIWe found 1) non-additive effects were pervasive with 56% of microbial communities interacting synergistically or antagonistically to impact plant productivity, including some consortia capable of generating acute synergism (e.g., >1000% increase in productivity above the additive expectation), 2) interactions among commensal fungi were responsible for this non-additivity in diverse communities, 3) synergistic interactions were ~4 times stronger than antagonistic effects, 4) fungal diversity affected the magnitude but not frequency or direction of non-additivity, and 5) diversity affected plant performance nonlinearly with highest performance in low microbial diversity treatments. C_LIO_LIThese findings highlight the importance of interpreting plant-microbial interactions under a framework that incorporates intermicrobial interactions and non-additive outcomes to understand natural complexity. C_LI

ecology↗

bioRxiv2022

Molecular glue CELMoD compounds are allosteric regulators of cereblon conformation

Cereblon (CRBN) is an ubiquitin ligase (E3) adaptor protein co-opted by CRBN E3 Ligase Modulatory Drugs (CELMoD) agents that target therapeutically-relevant proteins for degradation. Prior crystallographic studies defined the drug-binding site within CRBNs Thalidomide Binding Domain (TBD), but the allostery of drug-induced neosubstrate binding remains unclear. We therefore performed cryo-EM analyses of the DDB1[~]CRBN apo-complex, and compared these structures with DDB1[~]CRBN in the presence of CELMoD compounds alone and complexed with neosubstrates. Association of CELMoD compounds to the TBD is necessary and sufficient for triggering CRBN allosteric rearrangement from an "open" conformation to the canonical "closed" conformation. Importantly, the neosubstrate Ikaros only stably associates with the closed CRBN conformation, illustrating the importance of allostery for CELMoD compound efficacy, and informing structure-guided design strategies to improve therapeutic efficacy.

molecular biology↗

bioRxiv2022

A rapid and universal liquid chromatograph-mass spectrometry-based platform, refmAb-Q nSMOL, for monitoring monoclonal antibody therapeutics

Accurate quantitation of antibody is critical for development of monoclonal antibody therapeutics (mAbs). Therapeutic drug monitoring has been applied to measure levels of mAbs in clinics for dose adjustment for autoimmune disease. Trough levels of mAbs can be a biomarker for cancer immunotherapy. Thus, the deployment of a rapid and universal platform for mAb monitoring may benefit processes ranging from drug development to clinical practice for a wide spectrum of diseases. However, mAb monitoring often requires development and conduct of an individual ligand binding assay such as ELISA, which is impractical to scale. We streamlined quantitation of antibody therapeutics by a nano-surface and molecular-orientation limited (nSMOL) proteolysis assay using LC-MS with a universal reference antibody (refmAb-Q), for accurate multiplexed quantitation of unique signature peptides derived from mAbs. This innovative refmAb-Q nSMOL platform may provide a practical solution for quantitating an ever-increasing number of mAbs from developmental to clinical use settings.

immunology↗

bioRxiv2022

Decoding the IGF1 Signaling Gene Regulatory Network Behind Alveologenesis from A Mouse Model of Bronchopulmonary Dysplasia

Lung development is precisely controlled by underlying Gene Regulatory Networks (GRN). Disruption of genes in the network can interrupt normal development and cause diseases such as bronchopulmonary dysplasia (BPD)-a chronic lung disease in preterm infants with morbid and sometimes lethal consequences characterized by lung immaturity and reduced alveolarization. Here, we generated a transgenic mouse exhibiting a moderate severity BPD phenotype by blocking IGF1 signaling in secondary crest myofibroblasts (SCMF) at the onset of alveologenesis. Using approaches mirroring the construction of the model GRN in sea urchins development, we constructed the IGF1 signaling network underlying alveologenesis using this mouse model that phenocopies BPD. The constructed GRN, consisting of 43 genes, provides a birds-eye view of how the genes downstream of IGF1 are regulatorily connected. The GRN also reveals a mechanistic interpretation of how the effects of IGF1 signaling are transduced within SCMF from its specification genes to its effector genes and then from SCMF to its neighboring alveolar epithelial cells with WNT5A and FGF10 signaling as the bridge. Consistently, blocking WNT5A signaling in mice phenocopies BPD as inferred by the network. A comparative study on human samples suggests that a GRN of similar components and wiring underlies human BPD. Our network view of alveologenesis is transforming our perspective to understand and treat BPD. This new perspective calls for the construction of the full signaling GRN underlying alveologenesis, upon which targeted therapies for this neonatal chronic lung disease can be viably developed.

developmental biology↗

bioRxiv2021

Comprehensive epigenomic profiling of human alveolar epithelial differentiation identifies key epigenetic states and transcription factor co-regulatory networks for maintenance of distal lung identity

Disruption of alveolar epithelial cell (AEC) differentiation is implicated in peripheral lung diseases strongly impacting morbidity and mortality worldwide, such as chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, and lung adenocarcinoma. Elucidating underlying disease pathogenesis requires a mechanistic molecular understanding of AEC differentiation. However, to date no study has comprehensively characterized the dynamic epigenomic alterations that facilitate this critical process in humans. We comprehensively profiled the epigenomic states of human AECs during type 2 to type 1-like cell differentiation, including the methylome and chromatin functional domains, and integrated this with transcriptome-wide RNA expression. Enhancer regions were drastically altered during AEC differentiation. Transcription factor binding analysis within enhancer regions revealed diverse interactive networks with enrichment for dozens of transcription factors, including NKX2-1 and FOXA family members, as well as transcription factors with previously uncharacterized roles in lung differentiation, such as members of the MEF2, TEAD, and AP1 families. Additionally, associations between transcription factors changed during differentiation, implicating a complex network of heterotrimeric complex switching may be involved in facilitating differentiation. Integration of AEC enhancer states with the catalog of enhancer elements in the Roadmap Epigenomics Mapping Consortium and Encyclopedia of DNA Elements (ENCODE) revealed that human mammary epithelial cells (HMEC) have a similar epigenomic structure to alveolar epithelium, with NKX2-1 serving as a distinguishing feature of distal lung differentiation. Taken together, our results suggest that enhancer regions with dynamic transcription factor interactions are hotspots of epigenomic alteration that help to facilitate AEC differentiation. Author SummaryHuman health and disease states are heavily influenced by the critical cellular processes that regulate and protect our genomes. One of these safeguards is the epigenome; the coordinated set of signals overlaid on top of our DNA that controls what can happen to a given stretch DNA. Hence, epigenomic signatures play a critical role in the development and maintenance of cellular fate and function. To determine the relationship between epigenomic alterations and cellular fates of distal lung cells in humans during the process that regenerates the human lung epithelial layer after injury, we performed comprehensive genome-wide profiling of many epigenetic modifications that have roles in regulating the function of the underlying DNA. We found that changes to enhancer regions, which act to turn on associated gene expression, were the major alterations to the epigenome during distal lung differentiation, and that within those regions dynamic changes in transcription factor associations were occurring to facilitate this process. We then characterize what was similar and distinct to the enhancers of distal lung from among other epithelial tissues and describe a novel role for specific transcription factors in this process that previously had no known role in normal lung repair.

genomics↗

bioRxiv2021

HolistiC: Leveraging Hi-C and Whole Genome Shotgun Sequencing for Double Minute Chromosome Discovery

Double minute chromosomes are acentric extrachromosomal DNA artifacts that are frequently observed in the cells of numerous cancers. They are highly amplified and contain oncogenes and drug resistance genes, making their presence a challenge for effective cancer treatment. Algorithmic discovery of double minutes (DM) can potentially improve bench-derived therapies for cancer treatment. A hindrance to this task is that DMs evolve, yielding circular chromatin that shares segments from progenitor double minutes. This creates double minutes with overlapping amplicon coordinates. Existing DM discovery algorithms use whole genome shotgun sequencing in isolation, which can potentially incorrectly classify DMs that share overlapping coordinates. In this study, we describe an algorithm called " HolistIC" that can predict double minutes in tumor genomes by integrating whole genome shotgun sequencing (WGS) and Hi-C sequencing data. The consolidation of these sources of information resolves ambiguity in double minute amplicon prediction that exists in DM prediction with WGS data used in isolation. We implemented and tested our algorithm on the tandem Hi-C and WGS datasets of three cancer datasets and a simulated dataset. Results on the cancer datasets demonstrated HolistICs ability to predict DMs from Hi-C and WGS data in tandem. The results on the simulated data showed the HolistIC can accurately distinguish double minutes that have overlapping amplicon coordinates, an advance over methods that predict extrachromosomal amplification using WGS data in isolation. AvailabilityOur software is available at http://www.github.com/mhayes20/HolistIC.

bioinformatics↗

bioRxiv2020

Development of novel in vitro human alveolar epithelial cell models to study distal lung biology and disease

Many acute and chronic lung diseases affect the distal lung alveoli. Although airway-derived human cell lines exist, alveolar epithelial cell (AEC)-derived lines are needed to better model these diseases. We have generated and characterized novel immortalized cell lines derived from human AECs. They grow as epithelial monolayers expressing lung progenitor markers SOX9 and SOX2, with little to no expression of mature AEC markers. Co-cultured in 3-dimensions (3D) with lung fibroblasts, the cells form NKX2-1+ organoids expressing mature AEC markers AQP5 and GPRC5A. Single-cell RNA sequencing of an AEC line in 2D versus 3D revealed increased cellular heterogeneity and induction of cytokine and lipoprotein signaling, consistent with organoid formation. Activating WNT and FGF pathways resulted in larger organoids. Our approach appears to yield lung progenitor lines that retain a genetic and structural memory of their alveolar cell lineage despite long-term expansion and whose differentiation may be modulated under various 3D conditions. These cell lines provide a valuable new system to model the distal lung in vitro.

cell biology↗

bioRxiv2020

Power-law scaling of brain wave activity associated with mental fatigue

This paper investigates the cause and detection of power-law scaling of brain wave activity due to the heterogeneity of the brain cortex, considered as a complex system, and the initial condition such as the alert or fatigue state of the brain. Our starting point is the construction of a mathematical model of global brain wave activity based on EEG measurements on the cortical surface. The model takes the form of a stochastic delay-differential equation (SDDE). Its fractional diffusion operator and delay operator capture the responses due to the heterogeneous medium and the initial condition. The analytical solution of the model is obtained in the form of a Karhunen-Loeve expansion. A method to estimate the key parameters of the model and the corresponding numerical schemes are given. Real EEG data on driver fatigue at 32 channels measured on 50 participants are used to estimate these parameters. Interpretation of the results is given by comparing and contrasting the alert and fatigue states of the brain. The EEG time series at each electrode on the scalp display power-law scaling, as indicated by their spectral slopes in the low-frequency range. The diffusion of the EEG random field is non-Gaussian, reflecting the heterogeneity of the brain cortex. This non-Gaussianity is more pronounced for the alert state than the fatigue state. The response of the system to the initial condition is also more significant for the alert state than the fatigue state. These results demonstrate the usefulness of global SDDE modelling complementing the time series approach for EEG analysis.

bioinformatics↗

bioRxiv2020

Injectable Myocardial Matrix Hydrogel Mitigates Negative Left Ventricular Remodeling in a Chronic Myocardial Infarction Model

A first-in-man clinical study on a myocardial-derived decellularized extracellular matrix (ECM) hydrogel yielded evidence for potential efficacy in ischemic heart failure (HF) patients. However, little is understood about the mechanism of action in chronic myocardial infarction (MI). In this study we investigated efficacy and mechanism by which the myocardial matrix hydrogel can mitigate negative left ventricular (LV) remodeling in a chronic model of MI. Assessment of cardiac function via magnetic resonance imaging (MRI) demonstrated preservation of LV volumes and apical wall thickening. Differential gene expression analyses showed the matrix is able to prevent worsening HF in a small animal chronic MI model through modulation of the immune response, downregulation of pathways involved in HF progression and fibrosis, and upregulation of genes important for cardiac muscle contraction.

bioengineering↗

bioRxiv2018

Profiling grapevine trunk pathogens in planta: A case for community-targeted DNA metabarcoding

DNA metabarcoding, commonly used in exploratory microbial ecology studies, is a promising method for the simultaneous in planta-detection of multiple pathogens associated with disease complexes, such as the grapevine trunk diseases. Their detection is particularly challenging, due to the presence within an individual wood lesion of multiple co-infecting trunk pathogens and other wood-colonizing fungi, which span a broad range of taxa in the Fungal Kingdom. As such, we designed metabarcoding primers, using as template the ribosomal internal transcribed spacer of grapevine trunk-associated Ascomycete fungi (GTAA) and compared them to two universal primer widely used in microbial ecology. We first performed in silico simulations and then tested the primers by high-throughput amplicon sequencing of (i) multiple combinations of mock communities, (ii) time-course experiments with controlled inoculations, and (iii) diseased field samples from vineyards under natural levels of infection. All analyses showed that GTAA had greater affinity and sensitivity, compared to those of the universal primers. Importantly, with GTAA, profiling of mock communities and comparisons with shotgun-sequencing metagenomics of field samples gave an accurate representation of genera of important trunk pathogens, namely Phaeomoniella, Phaeoacremonium, and Eutypa, the abundances of which were greatly over- or under-estimated with universal primers. Overall, our findings not only demonstrate that DNA metabarcoding gives qualitatively and quantitatively accurate results when applied to grapevine trunk diseases, but also that primer customization and testing are crucial to ensure the validity of DNA metabarcoding results.

microbiology↗