Biology subjects

Duan, M.

Publications and source records attributed to Duan, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Longitudinal imaging of single cells in opaque tissue with cell chirp ultrasound

Small numbers of cells can determine the fate of an entire organism. For example, metastatic cancer cells seed distant organs, therapy-resistant clones repopulate tumors, and T cells infiltrate and expand in tissues with matching antigens. Visualizing the activity of such cells in living organisms requires highly sensitive, specific and repeatable imaging in optically opaque tissues. Here we introduce cell chirp, an ultrasound imaging method for real-time imaging of single cells in living organs inaccessible to light. Cell chirp exploits the harmonic response of genetically encoded gas vesicles to frequency-coded ultrasound to sensitively and specifically visualize single cells in scattering background. We first develop this method in tissue-mimicking phantoms, demonstrating the ability to quantitatively detect single cells as validated by optical cell counts. We then establish the ability of cell chirp to image thousands of genetically labeled cells within a million-cell background tissue, track reporter gene expression over days, and suppress background signals by more than two orders of magnitude. Finally, we use cell chirp to track the fate of antigen-positive or antigen-negative tumor-cell minorities during weeks-long T-cell engager treatments. Cell chirp reveals the dynamics of sparsely distributed, genetically defined cells in opaque tissues.

bioengineering↗

bioRxiv2026

SLECA: a single-cell atlas of systemic lupus erythematosus enabling rare cell discovery using graph transformer

Systemic lupus erythematosus (SLE) is a highly heterogeneous autoimmune disease with complex immune and molecular dysregulation. While rare immune cell populations are increasingly recognized as critical drivers of disease pathogenesis and progression, the lack of sufficiently powered, comprehensive single-cell atlases has limited their systematic identification and characterization. To address this gap, we present SLECA, the first large-scale single-cell atlas of SLE, enabled by a novel graph-transformer framework for the interpretable discovery and analysis of disease-relevant rare cell populations. SLECA integrates 366 single-cell samples with standardized clinical and biological metadata, providing a comprehensive and analytically unified atlas of systemic lupus erythematosus. By enabling scalable integration and interpretable analysis, SLECA resolves 54 distinct cell types, including rare populations with critical disease relevance. Notably, we identify double-negative T cells (DNTs) as a disease-expanded population whose abundance correlates with clinical severity. Through in silico perturbation, we demonstrate that key transcription factors, specifically JUN and EGR1, can reprogram DNT cells toward conventional T-cell phenotypes, highlighting actionable regulatory vulnerabilities in SLE.

bioinformatics↗

bioRxiv2026

Oxaloacetate damages mitochondria by perturbing MIC60-dependent membrane remodeling

Mitochondria catabolize nutrients by generating sequentially-ordered organic acid intermediates that are oxidized through the tricarboxylic acid cycle. Pathogenic accumulation of metabolic organic acids manifests as devastating organic acidemias/acidurias and other severe diseases, but the underlying mechanisms are largely unknown. Using unbiased C. elegans genetic screening, we here reveal that mutations in the phosphoenolpyruvate carboxykinases PCK-1 and PCK-2 cause buildup of oxaloacetate, a key tricarboxylic acid cycle intermediate, leading to severe mitochondrial damage. Depletion of mitochondrial GOT-2.1 or GOT-2.2, which catalyze oxaloacetate conversion to aspartate, also causes oxaloacetate accumulation and defective mitochondria with disrupted cristae. We demonstrate that oxaloacetate binds the MICOS complex subunit CHCH-3/MIC19 and inhibits its function of promoting IMMT-1/MIC60-dependent membrane shaping and remodeling. In mammalian cells, aberrant OAA buildup similarly causes mitochondrial impairment through MIC19 and MIC60. These findings not only provide important mechanistic insights into mitochondrial damage in the context of defective oxaloacetate metabolism, but also suggest therapeutic strategies for oxaloacetate-related mitochondriopathies.

cell biology↗

bioRxiv2026

Structural basis of underwound DNA topology bearing PAM-mutant recognition by AtCas9

The CRISPR-Cas9 system locates genomic targets through gRNA pairing and recognition a protospacer-adjacent motif (PAM). While PAM specificity is typically sequence-determined, we previously found that DNA topology can regulate PAM specificity, relaxing PAMs of various Cas9 effectors and allowing near-PAMless cleavage activity of a type II-C Alicyclobacillus tengchongensis Cas9 (AtCas9). However, the structural mechanism underlying this regulation remains unknown. Here, we report cryo-EM structures of AtCas9 bound to B-form DNA or a 340-bp underwound minicircle DNA bearing WT or mutant PAMs. Despite differences in PAM sequences, all three underwound complexes adopt an almost identical architecture that is distinct from the B-form DNA-bound state. On B-form DNA, AtCas9 recognizes the PAM via base-specific hydrogen bonds and steric exclusion, conferring preference for N4CNNN and N4RNNA (R = A/G). In contrast, underwound minicircle DNA widens the PAM major groove, reduces steric clashes, and enables a compensatory mode involving sequence-independent backbone contacts, explaining near-PAMless cleavage under underwound conformation. These findings uncover a topology-dependent mechanism of PAM recognition and establish a cryo-EM platform using underwound minicircle DNA for structural studies under native-like topological states.

biochemistry↗

bioRxiv2025

Deep-learning-enabled multi-omics analyses for prediction of future metastasis in cancer

Metastasis remains the leading cause of cancer-related mortality, yet predicting future metastasis is a major clinical challenge due to the lack of validated biomarkers and effective assessment methods. Here, we present EmitGCL, a deep-learning framework that accurately predicts future metastasis and its corresponding biomarkers. Based on a comprehensive benchmarking comparison, EmitGCL outperformed other computational tools across six cancer types from seven cohorts of patients with superior sensitivity and specificity. It captured occult metastatic cells in a patient with a lymph node-negative breast cancer, who was declared to have no evidence of disease by conventional imaging methods but was later confirmed to have a metastatic disease. Notably, EmitGCL identified HSP90AA1 and HSP90AB1 as predictable biomarkers for future breast cancer metastasis, which was validated across five independent cohorts of patients (n=420). Furthermore, we demonstrated YY1 transcription factor as a key driver of breast cancer metastasis which was validated through in-silico and CRISPR-based migration assays, suggesting that YY1 is a potential therapeutic target for deterring metastasis.

bioinformatics↗

bioRxiv2025

SIMIT-seq: a bead-free, scalable microfluidic platform for single cell mRNA sequencing with ultrahigh cell-indexing rate

SIMIT-seq is a bead-free, scalable microfluidic platform designed for high-efficiency single-cell mRNA sequencing. Conventional microfluidic-based single-cell RNA sequencing platforms rely heavily on barcoded beads and intricate co-encapsulation schemes, often constrained by double Poisson limitations and the complexities of bead synthesis. In contrast, SIMIT-seq eliminates the need for beads entirely by employing a deterministic, orthogonal barcoding strategy within a two-dimensional micro-well array. This platform achieves an impressive single-cell indexing rate of 96.6% without the need for complex microfluidic operations. Here, we describe the design and fabrication of the SIMIT-seq platform, outline its workflow for transcript capture and library preparation, and demonstrate its application in profiling K562 cells. Our results validate both the high fidelity of molecular barcode immobilization and the systems capability to support downstream single-cell mRNA sequencing. SIMIT-seq offers a cost-effective and scalable alternative for single-cell transcriptomics, providing a promising foundation for future single-cell omics applications.

bioinformatics↗

bioRxiv2024

Coordination of flux-related leaf and root traits impacts forest community assembly

Understanding the functions and coordination of plant traits is critical for predicting how diverse species respond to climate change. According to hydraulic and economic theories, leaves and roots--key organs for resource acquisition--are expected to function in coordination, such that species with faster resource utilization would possess leaf and root traits that facilitate rapid carbon, nutrient, and water uptake and fluxes. However, there has been limited evidence supporting leaf-root trait coordination and a role for that coordination on community structure. Here, we measured 13 leaf and root functional traits for 101 woody species from six tropical and subtropical forests, and assessed coordination and its association with community dominance. Hydraulic traits, such as leaf vein density and root vessel density, were coordinated between organs and showed compensation trade-offs between traits within organs, such as, leaf vein density and diameter. Economic traits relating to composition, such as nitrogen concentration, were coordinated between organs, whereas economic structural traits were decoupled, such as leaf mass per area and specific root length. Overall, hydraulic traits and economics traits were partially independent. The coordination of flux-related leaf and root traits was associated with ectomycorrhizal symbiosis and with dominance within the community. These findings indicate how trait organization within and across organs contributes to optimal whole plant function, with implications for performance in natural communities.

ecology↗

bioRxiv2024

Achieving Single Cell Acoustic Localisation with Deactivation Super Resolution

Super-resolution optical microscopy enables optical imaging of cells, molecules and other biological structures beyond the diffraction limit. However, no similar method exists to super-resolve specific cells with ultrasound. Here we introduce Deactivation Super Resolution (DSR), an ultrasound imaging method that uses the acoustic deactivation of genetically encodable contrast agents to super-resolve individual cells with ultrasound as they navigate through structures that cannot be resolved by conventional imaging methods. DSR takes advantage of gas vesicles, which are air-filled sub-micron protein particles that can be expressed in genetically engineered cells to produce ultrasound contrast. Our experimental results show that DSR can distinguish sub-wavelength microstructures that standard B-mode ultrasound images fail to resolve by super- localizing individual mammalian cells. This study provides a proof of concept for the potential of DSR to serve as a super- resolution ultrasound technique for individual cell localization, opening new horizons in the field.

bioengineering↗

bioRxiv2024

Nonlinear sound-sheet microscopy: imaging opaque organs at the capillary and cellular scale

Light-sheet fluorescence microscopy has revolutionized biology by visualizing dynamic cellular processes in three dimensions. However, light scattering in thick tissue and photobleaching of fluorescent reporters limit this method to studying thin or translucent specimens. Here we show that non-diffractive ultrasonic beams used in conjunction with a cross-amplitude modulation sequence and nonlinear acoustic reporters enable fast and volumetric imaging of targeted biological functions. We report volumetric imaging of tumor gene expression at the cm3 scale using genetically encoded gas vesicles, and localization microscopy of currently uncharted cerebral capillary networks using intravascular microbubble contrast agents. Nonlinear sound-sheet microscopy provides a [~]64x acceleration in imaging speed, [~]35x increase in imaged volume and [~]4x increase in classical imaging resolution compared to the state-of-the-art in biomolecular ultrasound.

bioengineering↗

bioRxiv2024

Association study of Plasmodium falciparum Acetyl-CoA Synthetase Mutations S868G and V949I with antimalarial drugs

Plasmodium falciparum acetyl-CoA synthetase (PfACAS) protein is an important source of acetyl-CoA. We detected the mutations S868G and V949I in PfACAS by whole-genome sequencing analysis in some recrudescent parasites after antimalarial treatment with artesunate and dihydroartemisinin-piperaquine, suggesting that they may confer drug resistance. Using CRISPR/Cas9 technology, we engineered parasite lines carrying the PfACAS S868G and V949I mutations in two genetic backgrounds and evaluated their susceptibility to antimalarial drugs in vitro. The results demonstrated that PfACAS S868G and V949I mutations alone or in combination were not enough to provide resistance to antimalarial drugs.

microbiology↗

bioRxiv2024

Discovery of a Heparan-Sulfate Binding Domain in Monkeypox Virus H3 Protein as a New Anti-poxviral Drug Target

Viral adhesion to host cells is a critical step in infection for many viruses, including monkeypox virus (MPXV). In MPXV, the H3 protein mediates viral adhesion through its interaction with heparan sulfate (HS), yet the structural details of this interaction have remained elusive. Using AI-based structural prediction tools and molecular dynamics (MD) simulations, we identified a novel, positively charged -helical domain in H3 that is essential for HS binding. This conserved domain, found across orthopoxviruses, was experimentally validated and shown to be critical for viral adhesion, making it an ideal target for antiviral drug development. Targeting this domain, we designed a protein inhibitor, which disrupted the H3-HS interaction, inhibited viral infection in vitro and viral replication in vivo, offering a promising antiviral candidate. Our findings reveal a novel therapeutic target of MPXV, demonstrating the potential of combination of AI-driven methods and MD simulations to accelerate antiviral drug discovery.

biophysics↗

bioRxiv2024

Harmonic imaging for nonlinear detection of acoustic biomolecules

Gas vesicles (GVs) based on acoustic reporter genes have emerged as potent contrast agents for cellular and molecular ultrasound imaging. These air-filled, genetically encoded protein nanostructures can be expressed in a variety of cell types in vivo to visualize cell location and activity or injected systemically to label and monitor tissue function. Distinguishing GVs from tissue signal deep inside intact organisms requires imaging approaches such as amplitude modulation (AM) or collapse-based pulse sequences, however they have limitations in sensitivity or require irreversible collapse of the GVs that restricts its scope for imaging dynamic cellular processes. To address these limitations, this study explores the utility of harmonic imaging to enhance the sensitivity of non-destructive imaging of GVs and cellular processes. Traditional fundamental-frequency imaging utilizing cross-wave AM (xAM) sequences has been deemed optimal for GV imaging. Contrary to this, we hypothesize that harmonic imaging, integrated with xAM could significantly elevate GV detection sensitivity. To verify our hypothesis, we conducted imaging on tissue-mimicking phantoms embedded with purified GVs, mammalian cells genetically modified to express GVs, and live mice after systemic GV infusion. Our findings reveal that harmonic xAM (HxAM) imaging markedly surpasses traditional xAM in isolating GVs nonlinear acoustic signature, showcasing significant enhancements in signal-to-background and contrast-to-background ratios across all tested samples. Further investigation into the backscattered spectra elucidates the efficacy of harmonic imaging in conjunction with xAM. HxAM imaging enables the detection of lower concentrations of GVs and cells with ultrasound and extends the imaging depth in vivo by up to 20% and imaging performance metrics by up to 10dB. These advancements bolster the capabilities of ultrasound for molecular and cellular imaging, underscoring the potential of using harmonic signals to amplify GV detection.

bioengineering↗

bioRxiv2024

Acetyl-CoA Synthetase Mutations S868G and V949I Do Not Confer Resistance to Antimalarial Drugs in vitro in Plasmodium falciparum.

microbiology↗

bioRxiv2023

Ultrasonic reporters of calcium for deep tissue imaging of cellular signals

Calcium imaging has enabled major biological discoveries. However, the scattering of light by tissue limits the use of standard fluorescent calcium indicators in living animals. To address this limitation, we introduce the first genetically encoded ultrasonic reporter of calcium (URoC). Based on a unique class of air-filled protein nanostructures called gas vesicles, we engineered URoC to produce elevated nonlinear ultrasound signal upon binding to calcium ions. With URoC expressed in mammalian cells, we demonstrate noninvasive ultrasound imaging of calcium signaling in vivo during drug-induced receptor activation. URoC brings the depth and resolution advantages of ultrasound to the in vivo imaging of dynamic cellular function and paves the way for acoustic biosensing of a broader variety of biological signals.

bioengineering↗

bioRxiv2023

Pan-genome analysis of different morphotypes reveals genomic basis of Brassica oleracea domestication and differential organogenesis

The domestication of Brassica oleracea has resulted in diverse morphological types with distinct patterns of organ development. Here we report a graph-based pan-genome of B. oleracea constructed with high-quality genome assemblies of different morphotypes. The pan-genome harbors over 200 structural variant (SV) hotspot regions enriched with auxin and flowering-related genes. Population genomic analyses reveal that early domestication of B. oleracea focused on leaf or stem selection. Gene flows resulting from agricultural practices and variety improvement are detected among different morphotypes. Selective sweep analysis identifies an auxin-responsive SAUR gene and a CLE family gene as the crucial players in the leaf-stem differentiation during the early stage of B. oleracea domestication, and the BoKAN1 gene as instrumental in shaping the leafy heads of cabbage and Brussels sprouts. Our pan-genome and functional analyses further discover that variations in the BoFLC2 gene play key roles in the divergence of vernalization and flowering characteristics among different morphotypes, and variations in the first intron of BoFLC3 are involved in fine-tuning the flowering process in cauliflower. This study provides a comprehensive understanding of the pan-genome of B. oleracea and sheds light on the domestication and differential organ development of this globally important crop species.

plant biology↗

bioRxiv2023

Monkeybread: A Python toolkit for the analysis of cellular niches in single-cell resolution spatial transcriptomics data

Spatial transcriptomics technologies enable the spatially resolved measurement of gene expression within a tissue specimen. With these technologies, researchers can investigate how cells organize into cellular niches which are defined as distinct regions in the tissue comprising a specific composition of cell types or phenotypes. While general-purpose software tools for the exploratory analysis of spatial transcriptomics data exist, there is a need for tools that specialize in the analysis of cellular organization into niches. This can further enhance the downstream application of these data towards drug target discovery, target validation, and biomarker development. We present Monkeybread: A Python toolkit for analyzing cellular organization and intercellular communication in single-cell resolution spatial transcriptomics data. We applied Monkeybread to a human melanoma sample to demonstrate its utility in identifying cellular niches with diverse immunogenic compositions in the tumor microenvironment. We found that these niches were differentially enriched for immunogenic and tolerogenic macrophage populations that could be correlated to T cell abundance. These findings highlight how Monkeybread can be used for revealing underlying biology of the tumor microenvironment, and in the future, for understanding the influence of these niches on response to available treatments and discovery of novel drug targets.

bioinformatics↗

bioRxiv2023

MarsGT: Multi-omics analysis for rare population inference using single-cell graph transformer

Rare cell populations are key in neoplastic progression and therapeutic response, offering potential intervention targets. However, their computational identification and analysis often lag behind major cell types. To fill this gap, we introduced MarsGT: Multi-omics Analysis for Rare population inference using Single-cell Graph Transformer. It identifies rare cell populations using a probability-based heterogeneous graph transformer on single-cell multi-omics data. MarsGT outperformed existing tools in identifying rare cells across 400 simulated and four real human datasets. In mouse retina data, it revealed unique subpopulations of rare bipolar cells and a Muller glia cell subpopulation. In human lymph node data, MarsGT detected an intermediate B cell population potentially acting as lymphoma precursors. In human melanoma data, it identified a rare MAIT-like population impacted by a high IFN-I response and revealed the mechanism of immunotherapy. Hence, MarsGT offers biological insights and suggests potential strategies for early detection and therapeutic intervention of disease.

bioinformatics↗

bioRxiv2023

Stoichiometric expression of messenger polycistrons by eukaryotic ribosomes (SEMPER) for compact, ratio-tunable multi-gene expression from single mRNAs

Applications of mammalian synthetic biology increasingly require the ability to express multiple proteins at user-determined stoichiometries from single, compactly encoded transcripts. Here we present an approach for expressing multiple open reading frames (ORFs) from a single transcript, taking advantage of the leaky scanning model of translation initiation. In this method, adjacent ORFs are translated from a single messenger RNA at tunable ratios determined by their order in the sequence and the strength of their translation initiation sites. We call this approach Stoichiometric Expression of Messenger Polycistrons by Eukaryotic Ribosomes (SEMPER). We demonstrate the principles of this approach by expressing up to three fluorescent proteins from one plasmid in two different cell lines. We then use it to encode a stoichiometrically tuned polycistronic construct encoding gas vesicle acoustic reporter genes, showing that enforcing the optimal ratio in every cell enables efficient formation of the multi-protein complex while minimizing cellular toxicity. Finally, we demonstrate the polycistronic expression of two fluorescent proteins from single mRNAs made through in vitro transcription and delivered to cells. SEMPER will enable a broad range of applications requiring tunable expression from compact eukaryotic constructs.

synthetic biology↗