Biology subjects

Hoang, M.

Publications and source records attributed to Hoang, M..

10 recordsLinked to original sources

bioRxiv2026

Personalized Neoantigen Vaccines Synergize with Immune Checkpoint Therapy and CD8-Targeted Cytokines to Control B-Cell Lymphoma

Personalized neoantigen (neoAg) vaccines have shown clinical promise in solid tumors1-8, yet their efficacy and mechanism of action in hematopoietic malignancies remain poorly defined9-11. Herein, we establish an immunocompetent syngeneic A20 B-cell lymphoma platform to test the efficacy of neoAg vaccines used either as mono- or combinatorial therapies with other immunotherapies12-17. Whereas subcutaneous A20 tumors were refractory to single-agent PD-1 or CTLA4 therapy, they were eradicated in a T cell-dependent manner in 90% of syngeneic hosts treated with dual immune checkpoint therapy (dual ICT, i.e., PD-1 + CTLA4). By mapping antigen specificity of dual-ICT-elicited T cells, we identified and validated dominant endogenous A20 MHC-I and MHC-II neoantigens and designed therapeutic synthetic long peptide (SLP) vaccines containing these neoepitopes. This vaccine (A20 neoVAX) promoted robust neoAg-specific CD4{square} and CD8{square} T cell responses in naive syngeneic BALB/c mice and induced tumor rejection in [~]70% of subcutaneous tumor-bearing mice. In addition, nearly all mice rejected their subcutaneous A20 tumors when A20 neoVAX was combined with PD-1. To render the results of this study more physiologic, we developed a systemic A20 lymphoma model and found that dual ICT failed to control tumor progression and A20 neoVAX delayed tumor progression and prolonged animal survival but did not induce tumor rejection. In contrast, A20 neoVAX plus dual ICT achieved durable systemic tumor elimination. Mechanistically, the combination of A20 neoVAX plus dual ICT amplified priming of A20 neoAg-specific T cells, prevented T cell dysfunction, sustained the cytotoxic capacity of tumor-specific CD8+ T cells, and induced Th1-skewing of CD4+ T cells in tumor and peripheral compartments. To increase the clinical relevance of these findings and to minimize potential adverse events in tumor-bearing, therapeutically treated individuals, we substituted CD8-targeted cytokine muteins (CD8-IL2 or CD8-IL21) for CTLA4. These agents represent genetically modified forms of IL-2 or IL-21 that selectively stimulate CD8+ T cells but have significantly reduced capacity to activate chronic inflammation and immunosuppressive functions of other immune cells. Whereas mice bearing systemic A20 lymphoma treated with either nothing, A20 neoVAX, or A20 neoVAX + CD8-IL2 failed to control tumor outgrowth, 66.7% of tumor-bearing mice treated with A20 neoVAX + CD8-IL2 + PD-1 rejected their tumors. In similar experiments in which CD8-IL21 was substituted for CD8-IL2, tumor clearance was also observed in two-thirds of A20-bearing mice but now rejection occurred in the absence of PD1. Together, these data define a framework for optimal personalized neoAg vaccination in B-lymphoma and demonstrate that neoAg vaccines can safely synergize with CD8+ T cell-selective immunotherapies to prevent T-cell dysfunction and generate durable systemic anti-tumor immunity.

immunology↗

bioRxiv2026

Fast, accurate construction of multiple sequence alignments from protein language embeddings

Multiple sequence alignment (MSA) is a foundational task in computational biology, under-pinning protein structure prediction, evolutionary analysis, and domain annotation. Traditional MSA algorithms rely on pairwise amino acid substitution matrices derived from conserved protein families. While effective for aligning closely related sequences, these scoring schemes struggle in the low-identity "twilight zone." Here, we present a new approach for constructing MSAs leveraging amino acid embeddings generated by protein language models (PLMs), which capture rich evolutionary and contextual information from massive and diverse sequence datasets. We introduce a windowed reciprocal-weighted embedding similarity metric that is surprisingly effective in identifying corresponding amino acids across sequences. Building on this metric, we develop ARIES (Alignment via RecIprocal Embedding Similarity), an algorithm that constructs a PLM-generated template embedding and aligns each sequence to this template via dynamic time warping in order to build a global MSA. Across diverse benchmark datasets, ARIES achieves higher accuracies than existing state-of-the-art approaches, especially in low-identity regimes where traditional methods degrade, while scaling almost linearly with the number of sequences to be aligned. Together, these results provide the first large-scale demonstration of the power of PLMs for accurate and scalable MSA construction across protein families of varying sizes and levels of similarity, highlighting the potential of PLMs to transform comparative sequence analysis. Code availabilityhttps://github.com/Singh-Lab/ARIES

bioinformatics↗

bioRxiv2025

Advanced illumination-imaging reveals photosynthesis-triggered pH, ATP and NAD redox signatures across plant cell compartments

Photosynthesis provides energy and organic substrates to most life. In plants, photosynthesis dominates chloroplast physiology but represents only a fraction of the tightly interconnected metabolic network that spans the entire cell. Here, we explore how photosynthetic activity affects energy physiology within and beyond the chloroplast. We developed a new standard for the live-monitoring of subcellular energy physiology by combining confocal imaging of genetically encoded fluorescent protein biosensors with advanced on-stage illumination technology to investigate pH, MgATP2- and NADH/NAD+ dynamics at dark-light transitions in Arabidopsis mesophyll cells. Our findings reveal a stromal alkalinization signature induced by photosynthetic proton pumping, extending to the cytosol and mitochondria as an alkalinization wave. Photosynthesis leads to increased MgATP2- levels in both the stroma and cytosol. Additionally, we observed reduction of the NAD pool driven by photosynthesis-derived electron export. Arabidopsis lines defective in chloroplast NADP- and mitochondrial NAD-dependent malate dehydrogenases show more reduced cytosolic NAD redox status even in darkness, highlighting the involvement of chloroplasts and mitochondria in shaping cytosolic redox metabolism via malate metabolism. Our study sets a novel methodological standard for precision live-monitoring of photosynthetic cell physiology. Applying this technology reveals signatures of photosynthetic physiology within and beyond the chloroplast with unprecedented resolution. Those signatures link photosynthetic activity and the fundamental biochemical functions of phototrophic cells. Significance statementBy applying novel live microscopy monitoring using fluorescent protein biosensors in plant cells, we reveal that dark-light transitions trigger profound re-orchestration of subcellular pH, ATP and NAD redox physiology not limited to chloroplasts but extending into the cytosol and the mitochondria.

plant biology↗

bioRxiv2024

A Scalable Optimization Algorithm for Solving the Beltway and Turnpike Problems with Uncertain Measurements

The BO_SCPLOWELTWAYC_SCPLOW and TO_SCPLOWURNPIKEC_SCPLOW problems entail the reconstruction of circular and linear one-dimensional point sets from unordered pairwise distances. These problems arise in computational biology when the measurements provide distances but do not associate those distances with the entities that gave rise to them. Such applications include molecular structure determination, genomic sequencing, tandem mass spectrometry, and molecular error-correcting codes (since sequencing and mass spec technologies can give lengths or weights, usually without connecting them to endpoints). Practical algorithms for TO_SCPLOWURNPIKC_SCPLOWe are known when the distance measurements are accurate, but both problems become strongly NP-hard under any level of measurement uncertainty. This is problematic since all known applications experience some degree of uncertainty from uncontrollable factors. Traditional algorithms cope with this complexity by exploring a much larger solution space, leading to exponential blowup in terms of both time and space. To alleviate both issues, we propose a novel alternating optimization algorithm that can scale to large, uncertain distance sets with as many as 100,000 points. This algorithm is space and time-efficient, with each step running in O(m log(m)) time and requiring only [Formula] working space for a distance set of size m. Evaluations of this approach on synthetic and partial digest data showcase improved accuracy and scalability in the presence of uncertain, duplicated, and missing distances. Our implementation of the algorithm is available at https://github.com/Kingsford-Group/turnpikesolvermm.

bioinformatics↗

bioRxiv2022

An international scholastic network to generate LexA enhancer-trap lines for Drosophila

Conditional gene regulation in Drosophila through binary expression systems like the LexA-LexAop system provides a superb tool for investigating gene and tissue function. To increase the availability of defined LexA enhancer trap insertions, we present molecular, genetic and tissue expression studies of 301 novel Stan-X LexA enhancer traps derived from mobilization of the index SX4 line. This includes insertions into distinct loci on the X, II and III chromosomes that were not previously associated with enhancer traps or targeted LexA constructs, an insertion into ptc, and eleven insertions into natural transposons. A subset of enhancer traps was expressed in CNS neurons known to produce and secrete insulin, an essential regulator of growth, development and metabolism. Fly lines described here were generated and characterized through studies by students and teachers in an international network of genetics classes at public, independent high schools, and universities serving a diversity of students, including those underrepresented in science. Thus, a unique partnership between secondary schools and university-based programs has produced and characterized novel resources in Drosophila, establishing instructional paradigms devoted to unscripted experimental science.

genetics↗

bioRxiv2022

Masked Minimizers: Unifying sequence sketching methods

Minimizers and syncmers are sequence sketching methods that extract representative substrings from a long sequence. We show that both these sampling rules are different instantiations of a new unifying concept we call masked minimizers, which applies a sub-sampling binary mask on a minimizer sketch. This unification leads to the first formal procedure to meaningfully compare minimizers, syncmers and other comparable masked minimizers. We further demonstrate that existing sequence sketching metrics, such as density (which measures the sketch sparseness) and conservation (which measures the likelihood of the sketch being preserved under random mutations), should not be independently measured when evaluating masked minimizers. We propose a new metric that reflects the trade-off between these quantities called the generalized sketch score, or GSS. Finally, we introduce a sequence-specific and gradient-based learning objective that efficiently optimizes masked minimizer schemes with respect to the proposed GSS metric. We show that our method finds sketches with better overall density and conservation compared to existing expected and sequence-specific approaches, enabling more efficient and robust genomic analyses in the many settings where minimizers and syncmers are used.

genomics↗

bioRxiv2022

An alternative mechanism for skeletal muscle dysfunction in long-term post-viral lung disease

Chronic lung disease is often accompanied by disabling extrapulmonary symptoms, notably skeletal muscle dysfunction and atrophy. Moreover, the severity of respiratory symptoms correlates with decreased muscle mass and in turn lowered physical activity and survival rates. Previous models of muscle atrophy in chronic lung disease often modeled COPD and relied on cigarette smoke exposure and LPS-stimulation, but these conditions independently affect skeletal muscle even without accompanying lung disease. Moreover, there is an emerging and pressing need to understand the extrapulmonary manifestations of long-term post-viral lung disease (PVLD) as found in Covid-19. Here, we examine the development of skeletal muscle dysfunction in the setting of chronic pulmonary disease using a mouse model of PVLD caused by infection due to the natural pathogen Sendai virus. We identify a significant decrease in myofiber size when PVLD is maximal at 49 d after infection. We find no change in the relative types of myofibers, but the greatest decrease in fiber size is localized to fast-twitch type IIB myofibers based on myosin heavy chain immunostaining. Remarkably, all biomarkers of myocyte protein synthesis and degradation (total RNA, ribosomal abundance, and ubiquitin-proteasome expression) were stable throughout the acute infectious illness and chronic post-viral disease process. Together, the results demonstrate a distinct pattern of skeletal muscle dysfunction in a mouse model of long-term PVLD. The findings thereby provide new insight into prolonged limitations in exercise capacity in patients with chronic lung disease after viral infections and perhaps other types of lung injury.

physiology↗

bioRxiv2022

DeepMinimizer: A Differentiable Framework for Optimizing Sequence-Specific Minimizer Schemes

Minimizers are k-mer sampling schemes designed to generate sketches for large sequences that preserve sufficiently long matches between sequences. Despite their widespread application, learning an effective minimizer scheme with optimal sketch size is still an open question. Most work in this direction focuses on designing schemes that work well on expectation over random sequences, which have limited applicability to many practical tools. On the other hand, several methods have been proposed to construct minimizer schemes for a specific target sequence. These methods, however, require greedy approximations to solve an intractable discrete optimization problem on the permutation space of k-mer orderings. To address this challenge, we propose: (a) a reformulation of the combinatorial solution space using a deep neural network re-parameterization; and (b) a fully differentiable approximation of the discrete objective. We demonstrate that our framework, DO_SCPLOWEEPC_SCPLOWMO_SCPLOWINIMIZERC_SCPLOW, discovers minimizer schemes that significantly outperform state-of-the-art constructions on genomic sequences.

bioinformatics↗

bioRxiv2021

Annotation of Putative Circadian Rhythm-Associated Genes in Diaphorina citri (Hemiptera : Liviidae)

The circadian rhythm is a process involving multiple genes that generates an internal molecular clock, allowing organisms to anticipate environmental conditions produced by the earths rotation on its axis. This report presents the results of the manual curation of twenty-seven genes likely associated with circadian rhythm in the genome of Diaphorina citri, the Asian citrus psyllid. This insect acts as the vector of the bacterial pathogen Candidatus Liberibacter asiaticus (CLas), the causal agent of citrus greening disease (Huanglongbing). This disease is the most severe detriment to citrus industries and has drastically decreased crop yields worldwide. Based on the genes identified in the psyllid genome, namely cry1 and cry2, D. citri likely possesses a circadian model similar to that of the lepidopteran butterfly, Danaus plexippus. Manual annotation of these genes will allow future molecular therapeutics to be developed that can disrupt the psyllid biology.

bioinformatics↗

bioRxiv2019

High multiplex, digital spatial profiling of proteins and RNA in fixed tissue using genomic detection methods

We have developed Digital Spatial Profiling (DSP), a non-destructive method for high-plex spatial profiling of proteins and RNA, using oligonucleotide detection technologies with unlimited multiplexing capability. The key breakthroughs underlying DSP are threefold: (1) multiplexed readout of proteins/RNA using oligo-tags; (2) oligo-tags attached to affinity reagents (antibodies/RNA probes) through a photocleavable (PC) linker; (3) photocleaving light projected onto the tissue sample to release PC-oligos in any spatial pattern. Here we show precise analyte reproducibility, validation, and cellular resolution using DSP. We also demonstrate biological proof-of-concept using lymphoid, colorectal tumor, and autoimmune tissue as models to profile immune cell populations, stroma, and cancer cells to identify factors specific for the diseased microenvironment. DSP utilizes the unlimited multiplexing capability of modern genomic approaches, while simultaneously providing spatial context of protein and RNA to examine biological questions based on analyte location and distribution.

pathology↗