Biology subjects

Truong, S.

Publications and source records attributed to Truong, S..

7 recordsLinked to original sources

bioRxiv2026

The Genome In A Bottle HG002 assembly-based variant benchmark set enables comprehensive benchmarking of small and structural variants.

High-accuracy, high-resolution benchmark data are fundamental to improving the accuracy and generalizability of sequencing technologies and associated algorithms. Most existing benchmarks for DNA sequencing rely on mapping to a single linear reference, omitting inaccessible and highly repetitive complex genomic regions. Here, we present the Genome in a Bottle (GIAB) Consortium's HG002 v5.0q benchmark set, a more comprehensive variant benchmark derived from a fully phased, highly curated, and accurate diploid assembly of HG002. Our approach leverages recent advances in long-read sequencing and assembly to provide confident small- and structural-variant calls across previously inaccessible regions, including segmental duplications, homopolymers, tandem repeats, and complex immune loci. The v5.0 benchmark significantly expands the callable genome relative to v4.2.1, adding x200 Mbp of sequence and increasing variant detection by 18 % for small variants and 3-fold for structural variants compared to previous benchmarks. The benchmark regions include more variants in repetitive regions, including 1.2 x segmental duplications, 1.8 x tandem repeats, and 2.0 x homopolymers, compared to v4.2.1. Separate and combined small- and structural-variant benchmarks are available for three versions of the human reference genome (GRCh37, GRCh38, and CHM13). We validate the reliability of this benchmark set by comparing multiple sequencing technologies and variant calling pipelines and curating differences. The v5.0q benchmark provides a critical resource for the development and validation of next-generation sequencing technologies and analysis methods.

genomics↗

bioRxiv2026

A complete human pancreatic cancer genome

Cancer genome sequencing is essential for understanding tumor evolution and advancing precision medicine.1 However, reference gaps and germline variants obscure detection of small and large somatic variants and methylation in repetitive regions.1-3 It is common for tumor cells to gain or lose chromosome arms due to somatic structural changes that occur inside highly repetitive satellite DNA sequences in the centromeres.4 To identify the full spectrum of somatic variants, including complex rearrangements, we construct and curate near-complete, haplotype-resolved assemblies of the most recent common ancestor of an early-passage broadly-consented hypodiploid pancreatic cancer cell line and matched normal tissues. The tumor assembly completely recapitulates all 35 tumor chromosomes observed with karyotyping, with multiple translocation-induced hybrid chromosomes. The hybrid chromosomes contain putative functional dicentric and fused centromeres, nested foldback inversions causing 14 breakpoints with a haplotype switch in a single event, and centromeric satellite tandem duplications up to 136 kbp. Direct comparison of tumor and normal assembly haplotypes uncovers >7,000 variants altering >1 Mbp of sequence in repetitive regions that have been hidden by reference gaps and germline variants. 44 % of somatic small variants change representation because they alter germline variants on GRCh38, impacting mutational signatures and kataegis/omikli clusters. Most somatic LINE insertions originate from two hypomethylated non-reference germline LINE insertions, highlighting their impact on insertion mutation burden. These assemblies demonstrate that centromeric, acrocentric, and telomeric regions conventionally excluded from analysis harbor extensive somatic and epigenetic changes. Resolving complete tumor genomes enables a deeper understanding of cancer structural plasticity and the endpoints of breakage-fusion-bridge cycles. These assembled, curated paired normal-tumor benchmarks will serve as a critical foundation for developing future algorithms to characterize the most intractable regions of cancer genomes.

genomics↗

bioRxiv2025

The inner dynamics of positive human-animal interactions: investigating the roles of oxytocin, opioids, dopamine, serotonin and the proteome

Research on the neuroendocrine basis of positive interactions has predominantly focused on oxytocin (OT), although dopamine (DA) and opioids also play crucial roles. Furthermore, these neurotransmitters are known to interact with each other but have seldom been studied concurrently. In this study, we quantified longitudinal changes in these neurotransmitters using a within-subject, 2 x 2 factorial design by varying human familiarity (familiar versus unfamiliar) and contact type (positive contacts versus ignoring) for 10 min human-pig interaction sessions. We repeatedly sampled cerebrospinal fluid from 10 pigs through a spinal catheter 65 and 5 min before the test and at 10, 30, 60, 120 and 240 min after the start of the test. Samples at various timepoints were analysed for OT, DA metabolites 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA), serotonin metabolite 5-hydroxyindoleacetic acid (5-HIAA), {beta}-endorphin opioids concentrations, and using proteomics to explore novel protein candidates. The test condition (human familiarity x contact type) had a significant effect on the concentration of {beta}-endorphin (F1,118.59 = 4.45; P = 0.04) and 5-HIAA (F1,73.47 = 5.02; P = 0.03), and tended to affect the concentration of oxytocin (F1, 119.8 = 3.19; P = 0.08) and DOPAC (F1,70.57 = 3.31; P = 0.07), but pair-wise comparisons were not significant. There was only a minor effect on the pigs behaviour, which suggests that the test conditions may have had limited effect. Nevertheless, this approach provides a valuable method to study neurotransmitter changes over time and simultaneously. Highlights- Oxytocin was higher when pigs were ignored than when they had positive contacts - Oxytocin was highest in the novel condition of an unfamiliar human ignoring the pig - Human familiarity and contact type affected {beta}-endorphin and 5-HIAA concentrations - Dopamine metabolites and the proteome were not affected by the test conditions

animal behavior and cognition↗

bioRxiv2024

Conditional CAR T cells with specificity to oncofetal glycosaminoglycans in solid tumors

Glycosaminoglycans are often deprioritized as targets for synthetic immunotherapy due to the complexity of glyco-epitopes and limited options for obtaining specific subtype-binding. Solid tumors express proteoglycans that are modified with oncofetal chondroitin sulfate (CS), a modification normally restricted to the placenta. Here, we report the design and functionality of conditional chimeric antigen receptor (CAR) T cells with selectivity to oncofetal CS. Following expression in T cells, the CAR could be armed with recombinant VAR2CSA lectins (rVAR2) to target tumor cells expressing oncofetal CS. While un-armed CAR T cells remained inactive in the presence of target cells, VAR2-armed CAR T cells displayed robust activation and the ability to eliminate diverse tumor cell types in vitro. Cytotoxicity of the CAR T cells was proportional to the concentration of rVAR2 available to the CAR, offering a potential molecular handle to finetune CAR T cell activity. In vivo, armed CAR T cells rapidly targeted bladder tumors and increased survival of tumor-bearing mice. Thus, our work indicates that cancer-restricted glycosaminoglycans can be exploited as potential targets for CAR T cell therapy.

cancer biology↗

bioRxiv2022

A bi-functional PARP-HDAC inhibitor with activity in Ewing sarcoma

HDAC inhibition has been shown to induce pharmacological BRCAness in cancer cells with proficient DNA repair activity. This provides a rationale for exploring combination treatments with HDAC and PARP inhibition in cancer types that are insensitive to single-agent PARP inhibitors. Here, we report the concept and characterization of a novel bifunctional PARP inhibitor (kt-3283) with dual activity towards PARP1/2 and HDAC enzymes in Ewing sarcoma cells. Compared to the FDA-approved PARP (olaparib) and HDAC (vorinostat) inhibitors, kt-3283 displayed enhanced cytotoxicity in Ewing sarcoma models. The kt-3283-induced cytotoxicity was associated with a strong S and G2/M cell cycle arrest in the nanomolar concentration range and elevated DNA damage as assessed by {gamma}H2AX tracking and comet assays. In three-dimensional spheroid models of Ewing sarcoma, kt-3283 showed efficacy in lower concentrations than olaparib and vorinostat and kt-3283 inhibited colonization of Ewing sarcoma cells in an ex vivo lung metastasis model. In summary, our data demonstrates the preclinical justification for studying the benefit of dual PARP and HDAC inhibition in the treatment of Ewing sarcoma in a clinical trial and provides proof-of-concept for a bi-functional single-molecule therapeutic strategy.

cancer biology↗

bioRxiv2022

Determination of the structure and dynamics of the fuzzy coat of an amyloid fibril of IAPP using cryo-electron microscopy

In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron-microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modelling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril the side-chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-{beta} structure of amyloid fibrils.

biophysics↗

bioRxiv2020

Two decades of creating drought tolerant maize and underpinning prediction technologies in the US corn-belt: Review and perspectives on the future of crop design

Over the last decade, society witnessed the largest expansion of agricultural land planted with drought tolerant (DT) maize (Zea mays L.) Dedicated efforts to drought breeding led to development of DT maize. Here we show that after two decades of sustained breeding efforts the rate of crop improvement under drought is in the range 1.0-1.6% yr-1, which is higher than rates (0.7% yr-1) reported prior to drought breeding. Prediction technologies that leverage biological understanding and statistical learning to improve upon the quantitative genetics framework will further accelerate genetic gain. A review of published and unpublished analyses conducted on data including 138 breeding populations and 93 environments between 2009 and 2019 demonstrated an average prediction skill (r) improvement around 0.2. These methods applied to pre-commercial stages showed accuracies higher that current statistical approaches (0.85 vs. 0.70). Improvement in hybrid and management choice can increase water productivity. Digital gap analyses are applicable at field scale suggesting the possibility of transition from evaluating hybrids to designing genotype x management (GxM) technologies for target cropping systems in drought prone areas. Due to the biocomplexity of drought, research and development efforts should be sustained to advance knowledge and iteratively improve models. HighlightCrop improvement rate in maize increased after implementation of drought breeding efforts. Harnessing crop, quantitative genetics and gap models will enable the transition from genetic evaluation to crop design.

plant biology↗