Biology subjects

Trinh, T.

Publications and source records attributed to Trinh, T..

12 recordsLinked to original sources

bioRxiv2026

CSF-Seq enables transcriptome-wide profiling of cerebrospinal fluid and identifies prognostic signature of leptomeningeal disease

Leptomeningeal disease (LMD) is a rapidly fatal complication of systemic cancer for which sensitive diagnostic tools and informative biomarkers remain limited. Here, we introduce CSF-Seq, a method for whole-transcriptome sequencing of cell-free RNA (cfRNA) from human cerebrospinal fluid (CSF), designed to enable molecular profiling of LMD and other central nervous system (CNS) conditions. Using a prospectively collected CSF biobank, we analyzed 125 samples spanning multiple pathologies, including breast and lung LMD, glioblastoma, traumatic brain injury, and non-cancer neurological controls. Through optimized RNA extraction, library preparation, and deep sequencing, CSF-Seq generated robust and reproducible transcriptome-wide profiles despite the low abundance and fragmentation of cfRNA in CSF. CSF transcriptomes exhibited disease-specific expression, separating LMD from non-cancer controls and from non-LMD cancers, independent of CSF collection modality. Tumor-associated epithelial transcripts, including CEACAM6 and MUC1, were consistently enriched in LMD samples, whereas immune and CNS-associated transcripts were broadly detected across disease states, consistent with contributions from both tumor and non-tumor sources. Cross-site processing of matched samples demonstrated high concordance, indicating preservation of sample-specific transcriptional signatures across independent workflows. Importantly, we identified a collection method- independent LMD gene expression signature that was significantly associated with overall survival, supporting its potential prognostic relevance. Together, these findings establish CSF-Seq as a technically robust and clinically informative platform for transcriptomic biomarker discovery in CNS metastatic disease, offering a minimally invasive approach for disease characterization, risk stratification, and longitudinal monitoring in patients with LMD.

cancer biology↗

bioRxiv2026

Whole blood transcriptional responses associated with bacterial burden in pulmonary tuberculosis

BackgroundPulmonary TB (PTB) patients present with a wide range of pre-treatment Mycobacterium tuberculosis (Mtb) burdens, which predict poor treatment outcomes. We sought to identify immune pathways and biomarkers associated with pre-treatment Mtb burden. MethodsWe conducted whole-blood RNA sequencing in 295 Vietnamese adults with PTB, quantifying bacterial load using GeneXpert Ct values. Weighted gene co-expression network analysis (WGCNA) identified gene modules, pathways, and hub genes associated with Mtb burden. Deconvolution analysis assessed contributions of immune cell types. Key findings were validated in independent PTB (n=171) and TB meningitis (TBM, n=281) cohorts, and publicly available animal datasets. We used non-linear regression for variable selection to identify gene predictors of Mtb burden and hurdle regression to model Mtb loads below the detection limit. FindingsHigher Mtb burden correlated with prolonged symptom duration, elevated neutrophil and monocyte counts, and severe lung pathology. WGCNA identified a 1,093-gene module associated with Mtb burden, characterized by coordinated innate-adaptive pathway interactions. Within this module, IFN-{gamma} signaling participates in modulating the increase of innate signaling (Toll-like, Nod-like receptors, TNF) and the decrease of adaptive signaling (T- and B-cell receptor) pathways in high-burden patients. These responses were primarily driven by neutrophils and classical monocytes. CNIH4 emerged as the strongest hub-gene and a top predictor of bacterial burden, with consistent validation across independent PTB and TBM cohorts. InterpretationOur study reveals systemic innate-adaptive immune dynamics underlying bacterial burden in PTB and identifies CNIH4 as a potential biomarker for treatment monitoring as well as a therapeutic target. FundingNational Institute of Health; Wellcome Trust, UK. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed from Jan 1, 2000, to Dec 10, 2025, without language restrictions, for human studies examining the relationship between Mycobacterium tuberculosis (Mtb) burden and host blood transcriptional responses in pulmonary tuberculosis. Search terms were used in combination as follows: ("Tuberculosis, Pulmonary" OR "pulmonary tuberculosis" OR PTB) AND ("Mycobacterium tuberculosis" OR mycobacter*) AND ("bacterial load" OR "bacterial burden" OR "sputum smear" OR "smear grade" OR xpert OR genexpert OR "cycle threshold" OR ct OR "time to positivity" OR TTP OR CFU OR "molecular bacterial load" OR MBLA)) AND (blood OR "whole blood" OR "peripheral blood") AND (RNA-seq OR "RNA sequencing" OR transcriptom* OR "gene expression" OR microarray). We included studies of active pulmonary tuberculosis that measured quantitative or semi-quantitative bacterial burden and profiled host blood transcriptome-wide responses at baseline, reporting either differential expression by burden strata or associations between bacterial burden and host gene expression. We excluded studies limited to latent tuberculosis, animal or in vitro models, diagnostic or prognostic signature studies without bacterial burden measurement, studies focused on treatment response, and studies using targeted assays without transcriptome-wide profiling. This search identified 12 articles describing blood transcriptional signatures for tuberculosis diagnosis, prognosis, and treatment response. However, only one study directly examined the relationship between pre-treatment bacterial burden and whole-blood transcriptome-wide profiles. That study demonstrated differences in systemic gene expression between patients with higher and lower sputum mycobacterial load and proposed a 20-gene blood signature associated with bacterial burden. However, the analysis was limited by small sample size, lack of pathway-level and cellular interpretation or assessment of correlation between signature with bacterial load. Added value of this studyOur study advances existing evidence by leveraging the wide spectrum of pre-treatment bacterial burden observed in routine clinical populations, quantified using GeneXpert Ct values, and integrating this with whole-blood RNA sequencing in large, well-characterized clinical cohorts. Through network-based transcriptomic analysis, immune cell deconvolution, and non-linear modelling, we identify a bacterial burden-associated gene network characterized by enhanced innate inflammatory signaling and relative suppression of adaptive immune pathways, predominantly driven by neutrophils and classical monocytes and modulated by IFN-{gamma} signaling. Within this network, CNIH4 emerges as a central hub gene and a robust predictor of bacterial burden, with consistent validation across independent pulmonary tuberculosis and tuberculous meningitis cohorts. Implications of all the available evidenceTaken together, the available evidence indicates that host blood transcriptional responses correlate with bacterial burden in pulmonary tuberculosis, but previous studies have provided limited insight into the underlying immune processes. Our findings strengthen the biological link between pre-treatment mycobacterial burden and systemic immune dysregulation, showing that higher bacterial burden is associated with transcriptional state marked by coordinated upregulation of innate immune responses and downregulation of adaptive immune pathways. These results support the use of host transcriptomic profiling as a biologically informative complement to sputum-based measures of bacterial burden and highlight burden-associated immune pathways, particularly CNIH4, as a potential target for treatment monitoring and host-directed therapeutic development.

immunology↗

bioRxiv2025

Single Cell Proteomics in the Developing Human Brain

Proteins are the functional effectors of virtually all biological processes, and accurately measuring their abundance and dynamics is essential for understanding development and disease. Although mRNA levels have historically been used as proxies for protein expression, growing evidence, especially from studies of the human cerebral cortex, has revealed widespread discordance between transcript and protein abundance. To directly address this limitation, we developed a rigorously optimized workflow that combines single-cell mass spectrometry with precise sample preparation to resolve, for the first time, quantitative proteomes of individual cells from the developing human brain. Our platform achieved deep proteomic coverage ([~]800 proteins per cell) even in immature prenatal human neurons (5-10 m diameter, [~]100 pg of protein per cell), capturing major brain cell types and enabling proteome-wide characterization at single-cell resolution. This approach revealed extensive transcriptome-proteome discordance across cell types, with particularly strong discrepancies in genes associated with neurodevelopmental disorders, a finding validated through orthogonal experiments. Proteins exhibited markedly higher cell-type specificity than their mRNA counterparts, underscoring the importance of proteomic-level analysis for resolving cellular identity and function. By reconstructing developmental trajectories from radial glia to excitatory neurons at the proteomic level, we identified dynamic stage-specific protein co-expression modules and pinpointed the intermediate progenitor-to-neuron transition as a molecularly vulnerable phase linked to autism. Altogether, by enabling single cell proteomics, this study establishes a foundational resource and technological advance for developmental neuroscience. It demonstrates that single-cell proteomics can capture critical developmental events and disease mechanisms that are undetectable at the transcript level. As this technology continues to improve in sensitivity and scalability, single-cell proteomics will become an indispensable tool for uncovering the molecular logic of brain development and for illuminating pathophysiological processes underlying neurodevelopmental disorders.

neuroscience↗

bioRxiv2025

Spatial Profiling Reveals Equivalence-Derived Molecular Signatures of Brain Mimicry and Adaptation in Breast Cancer Brain Metastases

Brain metastases (BrMets), common for advanced-stage breast cancer patients, are associated with poor median survival and accompanied by severe neurologic decline. Halting the progression of breast cancer brain metastases (BCBMs) may require modulation of the tumor microenvironment (TME), yet little is known about the impact of the primary breast TME on brain tropism, or how, once there, metastatic breast cancer cells coexist with brain-resident cells (e.g., neurons and glia). Traditionally, studies in this space have focused on differential expression analysis, overlooking potential insights gained from investigating genes with equivalent expression between groups. This is particularly crucial in distant metastasis, where tumor cells may co-opt the transcriptional programs of the host organ (e.g., brain) to facilitate successful seeding and outgrowth. Prior to our work, no computational framework existed to determine biologically-relevant equivalent gene expression. To resolve molecular mechanisms of BCBM enabled by metastatic cancer cells and/or resident brain cells, we leveraged Nanostring GeoMx to perform spatially-resolved transcriptomic profiling on 235 patient-derived tissue cores from BCBM (including adjacent normal brain), primary invasive breast cancers, and normal (non-cancer) brain; analyzing 18,677 RNAs in 450 areas of interest (AOIs). We introduce the "Equivalent Expression Index" a highly specific and accurate algorithm that identifies statistically significant "Equivalently-Expressed Genes". This method facilitated the identification of molecular remodeling and mimicry genes within tissue-specific TMEs. By integrating differential expression analysis with the Equivalent Expression Index, we discovered multiple novel gene signatures associated with BCBM and primary tumor brain-metastatic potential. We demonstrate that the Equivalent Expression Index is a powerful tool to uncover shared gene expression programs representing the adaptation of metastatic cells and brain-resident cells to the BCBM microenvironment.

cancer biology↗

bioRxiv2024

Deep Kernel Inversion: Rapid and Accurate Molecular Interaction Prediction for Drug Design

Computational drug design offers the opportunity to dramatically accelerate novel therapeutics for untreated diseases. Designing compounds with optimal efficacy and specificity, however, requires understanding and optimizing immense numbers of molecular interactions. While advances in predicting one-to-one molecular interactions continue, there has been limited progress in scaling one-to-many or many-to-many molecular interaction models. In this paper, we introduce a deep learning framework that embeds molecules into a high-dimensional vector space, which we have named Deep Kernel Inversion. In this framework, the dot product between vectors accurately predicts molecular interactions. This approach reduces the complexity of predicting an entire molecular interaction network from O(n2) to O(n), enabling new molecular design tasks previously inaccessible to computational approaches. In the case of human protein-protein interactions (PPI), we demonstrate a 100,000 fold decrease in the computation required to map the full human PPI network. We also demonstrate best-in-class performance across multiple molecular interaction tasks with this approach. This work offers a new way forward in scaling accurate molecular interaction predictions with applications in mapping biological pathways, target discovery, drug design, and therapeutic development.

systems biology↗

bioRxiv2024

VieMedKG: Knowledge Graph and Benchmark for Traditional Vietnamese Medicine

Traditional Vietnamese Medicine (TVM) and Traditional Chinese Medicine (TCM) have shared significant similarities due to their geographical location, cultural exchanges, and hot and humid climatic conditions. However, unlike TCM, which has substantial works published to construct a knowledge graph, there is a notable absence of a comprehensive knowledge graph for TVM. This paper presents the first endeavor to build a knowledge graph for TVM based on extensive existing resources from TCM. We name our knowledge graph as VieMedKG. We propose a translation and filtration process to adapt TCM knowledge graphs to TVM, identifying the overlapping and unique elements of TVM. In addition, the constructed knowledge graph is then exploited further for developing a curated benchmark for the knowledge graph-based question-answering problem with the potential to support doctors and patients in assisting doctors and patients in identifying various diseases. Our work will not only bridge the gap between TCM and TVM but also set the foundation for future research into traditional Vietnamese medicine community. Our source code is publicly available at https://github.com/HySonLab/VieMedKG/.

bioinformatics↗

bioRxiv2023

A Methylation-Phosphorylation Switch Controls EZH2 Stability and Hematopoiesis

The Polycomb Repressive Complex 2 (PRC2) methylates H3K27 to regulate development and cell fate by transcriptional silencing. Alteration of PRC2 is associated with various cancers. Here, we show that mouse Lsd1/Kdm1a deletion causes dramatic reduction of PRC2 proteins, whereas mouse null mutation of L3mbtl3 or Dcaf5 results in PRC2 accumulation and increased H3K27 trimethylation. The catalytic subunit of PRC2, EZH2, is mono-methylated at lysine 20 (K20), promoting EZH2 proteolysis by L3MBTL3 and the CLR4DCAF5 ubiquitin ligase. LSD1 demethylates the methylated K20 to stabilize EZH2. K20 methylation is inhibited by AKT-mediated phosphorylation of serine 21 in EZH2. Mouse K20R mutants develop hepatosplenomegaly associated with high GFI1B expression, and K20R mutant bone marrows expand hematopoietic stem cells and downstream hematopoietic populations. Our studies reveal that EZH2 is regulated by methylation dependent proteolysis, which is negatively controlled by AKT-mediated S21 phosphorylation to establish a methylation-phosphorylation switch to control the PRC2 activity and hematopoiesis.

biochemistry↗

bioRxiv2022

A high-throughput 3D cantilever array to model airway smooth muscle hypercontractility in asthma

Asthma is often characterized by tissue-level mechanical phenotypes that include remodeling of the airway and an increase in airway tightening driven by the underlying smooth muscle. Existing therapies only provide symptom relief and do not improve the baseline narrowing of the airway or halt progression of the disease. To investigate such targeted therapeutics, there is a need for models that can recapitulate the 3D environment present in this tissue, provide phenotypic readouts of contractility, and be easily integrated into existing assay plate designs and laboratory automation used in drug discovery campaigns. To address this, we have developed DEFLCT, a high-throughput plate insert that can be paired with standard labware to easily generate high volumes of microscale tissues in vitro for screening applications. Using this platform, we exposed primary human airway smooth muscle cell-derived microtissues to a panel of six of inflammatory cytokines present in the asthmatic niche, identifying TGF-{beta}1 and IL-13 as strong contractile modulators. RNAseq analysis further demonstrated enrichment of contractile and remodeling-relevant pathways in TGF-{beta}1 and IL-13 treated tissues as well as pathways generally associated with asthma. Taken together, these data establish a disease relevant, 3D tissue model for the asthmatic airway which combines niche specific inflammatory cues and complex mechanical readouts that can be utilized in drug discovery efforts.

bioengineering↗

bioRxiv2022

Metadata preservation and stewardship for genomic data is possible, but must happen now

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species and population resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies of evolutionary biology, molecular ecology and conservation genetics produce large amounts of genome-scale genetic diversity data for wild populations. While open data policies have ensured an abundance of freely available genomic data stored in the databases of the International Nucleotide Sequence Database Collaboration (INSDC), only about 13% of current accessions have the associated spatial and temporal metadata in INSDC necessary to be reused in monitoring programs, macrogenetic studies, or for acknowledging the sovereignty of nations or Indigenous Peoples. We undertook a "distributed datathon" to quantify the availability of these missing metadata in sources external to the INSDC and to test the hypothesis that these metadata decay with time. We also worked to remediate these missing metadata by extracting them, when present, from associated published papers, online repositories, and/or from direct communication with authors. Starting with 848 programmatically identified candidate datasets (INSDC BioProjects), we manually determined that 561 contained samples from wild populations. We successfully restored spatiotemporal metadata (locality name and/or geospatial coordinates and collection year) for 78% of these 561 datasets (N = 440 BioProjects comprising 45,105 individuals or BioSamples from 762 species in 17 phyla). We also quantified the availability of 33 additional categories of metadata in sources external to the INSDC. Information about associated publications and the type of habitat from which the samples were taken was the most easily found; information about sampling permits was the most challenging to locate. Looking at papers and online repositories was much more fruitful than contacting authors, who only replied to our email requests 45% of the time. Overall, 23% of our email queries to authors discovered useful metadata. Importantly, we found that the probability of retrieving spatiotemporal metadata declines significantly with the age of the dataset, with a 13.5% yearly decrease for metadata located in published papers or online repositories and up to a 22% yearly decrease for metadata that were only available from authors. This observable metadata decay, mirrored in studies of other types of biological data, should motivate swift updates to data sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost forever.

bioinformatics↗

bioRxiv2022

A modular intramolecular triplex photo-switching motif that enables rapid and reversible control of aptamer binding activity

DNA switches that can change conformation in response to certain wavelengths of light could enable rapid and non-invasive control of chemical processes for a wide range of applications. However, most current photo-responsive DNA switches are limited either by irreversible switching or reversible switching with impractically slow kinetics. Here, we report the design of an intramolecular triplex photoswitch (TPS) design based on single-stranded DNA that undergoes rapid and reversible photoswitching between folded and unfolded states through isomerization of internal azobenzene modifications. After optimizing the performance of our photoswitch design, we used molecular dynamics (MD) simulations to reveal how individual azobenzenes contribute to the stabilization or destabilization of the triplex depending on their photoisomerization state. By coupling our TPS to an existing aptamer, we can reversibly modulate its binding affinity with less than 15 seconds of UV light exposure. We further demonstrate reproducible shifting in affinity over multiple cycles of UV and blue light irradiation without substantial photobleaching. Given that our TPS can introduce switching functionality to aptamers without manipulating the aptamer sequence itself, we believe our design methodology should offer a versatile means for integrating photo-responsive properties into DNA nanostructures.

bioengineering↗

bioRxiv2021

A conserved trans regulatory loop involving an odorant binding protein controls male mating behavior in flies

Y chromosomes have male-limited inheritance, which favors the fixation of alleles that affect spermatogenesis, courtship, and other male-specific traits. Y-linked male-beneficial alleles can also have female-deleterious (sexually antagonistic) effects because they never experience direct selection in females. However, determining the mechanisms underlying these male-beneficial effects is challenging because it can require studying Y-linked alleles while they still segregate as polymorphism. We used a Y chromosome polymorphism in the house fly, Musca domestica, to address this challenge. Two common male-determining Y chromosomes (YM and IIIM) segregate as stable polymorphisms in natural house fly populations, and they differentially affect multiple traits, including male courtship performance. We performed a meta-analysis of RNA-seq data and identified differentially expressed genes encoding odorant binding proteins (in the Obp56h family) as candidate causal agents in the courtship differences. The Obp56h genes are not found on either the YM or IIIM chromosomes, suggesting that they must be regulated in trans by one of the house fly sex chromosomes. Using a network analysis and allele-specific expression measurements, we identified multiple genes on the house fly IIIM chromosome that could serve as trans inhibitors of Obp56h gene expression. One of those genes is homologous to D. melanogaster CG2120, which encodes a transcription factor that binds both up- and down-stream of Obp56h. We found that up-regulation of CG2120 in D. melanogaster nervous tissues reduces copulation latency, consistent with this transcription factor acting as a negative regulator of Obp56h expression. We propose the name speed date (spdt) for CG2120, with the house fly homolog named Md-spdt. The expression of spdt across D. melanogaster development and tissues suggests that evolution of higher expression in neurons may be constrained by pleiotropic or sexual antagonistic effects. We hypothesize that a cis-regulatory allele that increases expression of Md-spdt on the IIIM chromosome exists because Y-linkage of this allele releases it from those constraints. This provides evidence for a molecular mechanism by which a Y-linked gene can evolve a male-beneficial function regardless of the negative effects on females.

evolutionary biology↗

bioRxiv2020

Genetic underpinnings of host manipulation by Ophiocordyceps as revealed by comparative transcriptomics

AO_SCPLOWBSTRACTC_SCPLOWThe ant-infecting Ophiocordyceps fungi are globally distributed, host manipulating, specialist parasites that drive aberrant behaviors in infected ants, at a lethal cost to the host. An apparent increase in activity and wandering behaviors precedes a final summiting and biting behavior on to vegetation, positioning the manipulated ant in a site beneficial for fungal growth and transmission. Notably, across Ophiocordyceps species and other known host manipulators, the molecular mechanisms underlying behavioral changes remain largely unclear. We explored possible genetic underpinnings of host manipulation by: (i) producing a hybrid assembly of the Ophiocordyceps camponoti-floridani genome, (ii) conducting laboratory infections coupled with RNAseq of both O. camponoti-floridani and its host, Campontous floridanus, and (iii) using these data for a comparative analysis to similar work performed in Ophiocordyceps kimflemingiae and Camponotus castaneus. We propose differentially expressed genes tied to ant neurobiology, odor response, circadian rhythms, and foraging behavior may be the result of putative fungal effectors such as enterotoxins, aflatrem, and mechanisms disrupting nutrition-sensing or caste-identity pathways.

genomics↗