Biology subjects

Duan, B.

Publications and source records attributed to Duan, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Brainstem premotor circuits transform dental sensory input into coordinated jaw opening

Protective actions require the rapid transformation of damage into coordinated activity of motor pools, yet the brainstem circuits implementing this operation remain poorly defined. Here, we use the tooth-trigeminal system to identify molecularly specified pathways linking intradental sensory input to opposing jaw motor pools. Optogenetic activation of tooth-associated sensory afferents evoked rapid, stimulus-locked jaw-opening. Intradental afferents formed functional monosynaptic connections with Pdyn+ neurons in the 5Sol transition zone and Calb2+ neurons in the 5Tr transition zone, identifying these regions as sensory-recipient premotor interfaces. Predominantly excitatory Pdyn+ 5Sol neurons provided monosynaptic input to anterior digastric motor neurons, whereas predominantly inhibitory Calb2+ 5Tr neurons provided bilateral monosynaptic input to masseter motor neurons. Activation of Pdyn+ 5Sol neurons was sufficient to evoke jaw opening. Together, these findings define complementary brainstem pathways positioned to couple jaw-opening drive with inhibition of antagonistic jaw-closing output, revealing a withdrawal-like sensorimotor computation adapted to cranial biomechanics.

neuroscience↗

bioRxiv2025

Real-life ear-EEG Recordings of Auditory Responses to Ambient Sounds

Despite being one of the most researched neural responses, auditory potentials have primarily been measured in controlled laboratory environments. However, there is a big interest in measuring auditory potentials in more naturalistic environments, with stimuli resembling, to a higher degree, natural sounds. The objective of this study is to investigate auditory evoked potentials elicited by naturally occurring sounds in real-life environments. The paper presents an integration of a portable hearing aid research platform and a portable ear-EEG platform. This setup was validated through recordings of an Auditory Steady State Response (ASSR), elicited by real-time amplitude modulation of the ambient sound at 40Hz. Recordings were conducted in real-life under three conditions: walking and sitting with open and closed eyes. In addition to ear-EEG, scalp EEG was recorded as a reference. For analysis, EEG signals were categorized into three groups: scalp channels, cross-ear channels, and within-ear channels. For each condition and channel group, the signal-to-noise (SNR) of the ASSR was calculated. The ASSR was statistically significant across all channel groups and conditions. A post-hoc analysis assessed the recording duration required to obtain a significant ASSR, revealing that 10 minutes were enough for within ear ear-EEG for all but two cases, whereas less than 7 minutes were sufficient for all but one case when using scalp-EEG. Clinical relevanceThe Auditory Steady-State Response (ASSR) is a versatile tool for assessing various characteristics of the auditory pathway. The ability to measure ASSR in real-life conditions using ambient sound could facilitate the development of hearing aids capable of dynamically adapting to the users current hearing loss.

neuroscience↗

bioRxiv2025

SpaPheno: Linking Spatial Transcriptomics to Clinical Phenotypes with Interpretable Machine Learning

Linking spatial transcriptomic data to clinically relevant phenotypes is essential for advancing spatially informed precision oncology. Here, we present SpaPheno, an interpretable machine learning framework that integrates spatial transcriptomics with clinically annotated bulk RNA-seq to identify spatially resolved biomarkers predictive of patient outcomes, including survival, tumor stage, and immunotherapy response. SpaPheno provides multi-scale interpretability from tissue regions to cell types and individual spatial spots, enabling clear biological insights from complex spatial data. We validate SpaPheno through extensive simulations and applications to multiple cancer cohorts--primary liver cancer, clear cell renal cell carcinoma, breast cancer, and melanoma--demonstrating robust predictive performance alongside biologically meaningful spatial patterns. SpaPheno offers a generalizable strategy to translate spatial omics data into clinically actionable knowledge, facilitating precision oncology informed by tumor spatial architecture.

bioinformatics↗

bioRxiv2025

DNA Data Storage Architecture via Ligation of Dynamic DNA Bytes

The explosive growth of digital data is overwhelming conventional storage media, creating an urgent need for more efficient solutions. DNA offers immense potential for digital data storage, yet most systems remain static and archival. Here, we present a modular DNA storage architecture based on dynamic DNA bytes (DynaBytes)-- pre-fabricated DNA segments that can be ligated into reconfigurable information units. Utilizing core, functional and control DynaBytes, we stored 210,776 bits (26,347 bytes) of digital information organized within a file-system, and demonstrated CRUD (Create-Read-Update-Delete)-like operations, hierarchical access and nanopore-based realtime retrieval. Robust data recovery was achieved under [~]100x error-prone sequencing using streamlined error correction and fuzzy decoding. By relying on in vitro ligation of standardized components, DynaBytes reduces cost, scales efficiently, and allows interactive, rewritable storage. These features advance DNA storage beyond passive archiving toward a reconfigurable framework, opening new possibilities for dynamic, practical and large-scale DNA-based data systems.

synthetic biology↗

bioRxiv2025

Mycobacterial Metallophosphatase MmpE Acts as a Nucleomodulin to Regulate Host Gene Expression and Promote Intracellular Survival

Mycobacterium tuberculosis, the causative agent of tuberculosis, remains a major global health challenge. Nucleomodulins, bacterial effectors that target the host cell nuclei, are increasingly recognized as key virulence factors, but their roles in mycobacterial pathogenesis remain incompletely elucidated. Here, we characterize a hypothetical protein Rv2577 (designated MmpE) not only as a Fe3+/Zn2+-dependent metallophosphatase but also as a critical nucleomodulin involved in immune evasion and intracellular persistence. MmpE utilizes two nuclear localization signals, RRR20-22 and RRK460-462, to enter the host cell nucleus, where it binds to the promoter region of the vitamin D receptor (VDR) gene, thereby inhibiting host inflammatory gene expression. Additionally, MmpE regulates the PI3K-Akt-mTOR signaling pathway, thereby arresting lysosome maturation. These actions collectively facilitate immune suppression and promote mycobacterial survival in macrophages and in mice. Our findings identify MmpE as a conserved nucleomodulin in mycobacteria and reveal a novel mechanism of MmpE-mediated intracellular survival.

microbiology↗

bioRxiv2025

A parallelly distributed microscope and software system for scalable high-throughput multispectral 3D imaging

Recent advances in high throughput optical microscopy have achieved whole-organism scale imaging at diffraction-limited resolutions. Current microscopes, however, require making compromises between achieving the optimal resolution, imaging depth, multispectral capability, and data throughput due to limitations in optical design and data stream handling. We have created a parallel-line scanning confocal microscope (plSCM) which provides 1.1 Gigavoxels/second high speed imaging while achieving an optical resolution of [~]180 x 220 x 650 nm with 2 millimeters of imaging depth in 3 simultaneous spectral channels. To handle such a massive imaging data stream, we have engineered a scalable network-distributed image acquisition/processing framework (SNDiF), which allows continuous capture, real-time processing, and cluster storage of petabyte-scale single image datasets in days. Together, our parallelly distributed microscope and software system presents a general solution for large-scale high-throughput and high-resolution multicolor imaging which can operate for days at a time.

bioengineering↗

bioRxiv2025

A Conserved Mycobacterial Nucleomodulin Hijacks the Host COMPASS Complex to Reprogram Pro-Inflammatory Transcription and Promote Intracellular Survival

Nucleomodulins are a class of effector proteins secreted by bacterial pathogens that translocate into the host cell nucleus to modulate nuclear processes. However, their target proteins and underlying molecular mechanisms remain poorly understood in mycobacteria. Herein, we identified a conserved hypothetical protein Rv1075c, designated MgdE, as a nucleomodulin that enhances mycobacterial intracellular survival. MgdE undergoes nuclear translocation via two nuclear localization signals, KRIR108-111 and RLRRPR300-305, and interacts with ASH2L and WDR5, two subunits of the host histone methyltransferase COMPASS complex. This interaction suppresses histone H3 lysine 4 (H3K4) methylation-mediated transcription of pro-inflammatory genes, including IL6 and IL1B, thereby promoting mycobacterial survival in both macrophages and mice. Our study provides the first experimental evidence that a bacterial nucleomodulin facilitates intracellular survival by directly targeting the host COMPASS complex. These findings advance our understanding of mycobacterial pathogenesis by revealing a novel mechanism that contributes to its intracellular survival strategy.

microbiology↗

bioRxiv2025

ZNF638 represses the transcription of HBV closed circular DNA involving HUSH complex-mediated histone modifications of epigenetic silencing

Hepatitis B virus (HBV) infection poses a critical threat to public health burden worldwide. As the major template of viral transcription, the covalently closed circular DNAs (cccDNAs) of HBV was known to form microchromosomes and interact with various host proteins. In the present study, ZNF638 was found to significantly reduce the transcription of HBV into pgRNAs, and subsequently reduce cccDNA formation and viral propagation. We discovered that ZNF638 was able to bind the preS and S gene regions of HBV, repressing the transcription of cccDNA upon increased modification of H3K9me3 mediated by SETDB1. This epigenetic silencing of cccDNA transcription was further demonstrated to involve the activity of HUSH, a multi-protein complex to mediate epigenetic modifications of histone into suppressed nucleosomes. In in vivo models, we evaluated the effects of ZNF638 deficiency on HBV-targeting siRNA therapy. A significant reduction of the efficacy was observed in animals with reduced ZNF638 expression. In summary, we report that ZNF638 is a potent host factor to repress the transcription of HBV DNAs and to attenuate HBV infection. The role of ZNF638 on HBV repression involves its binding to cccDNA at specific regions for recruiting HUSH complex to write H3K9me3 histone marks for epigenetic silencing. ZNF638 serves as a critical host factor to associate HBV infection and disease progression. Additionally, ZNF638 serves as a potential indicator to predict the outcome of HBV-targeting siRNA therapy.

biochemistry↗

bioRxiv2025

Thermal and mechanical modalities converge in the noxious range

SummaryThere are competing theories on how nociceptive input is encoded by sensory fibers. That sensory modalities are exclusively conveyed by distinct populations of fibers is supported by ablation studies, indicating that TRPV1+and MrgprD+afferents selectively encode for heat and mechanical input, respectively. However, interpreting ablation results can be clouded by compensatory plasticity. Furthermore, a population-level parametric analysis of afferent response profiles to natural stimuliin vivois still scarce. Using functional imagingin vivoin mice, we found that most TRPV1+neurons responded to noxious heat, but not cooling. While none of them responded to innocuous mechanical input, about half were also sensitive to noxious mechanical stimuli. In contrast, 80% of MrgprD+neurons responded to noxious mechanical stimuli. Yet, 70% were also sensitive to noxious thermal stimuli. Of innocuous mechanosensitive MrgprD+neurons, <15% responded to innocuous warming and none to innocuous cooling. Polymodality in the innocuous thermal and mechanical range also occurred in <10% of all primary afferents. Acute silencing of TRPV1+or MrgprD+afferents inhibited both thermal and mechanical nociception. In contrast, ablation did not reproduce a combined loss of sensitivity, which appeared to be due to compensatory central disinhibition. Our findings reveal that modality separation dominates in the innocuous regime, while polymodality predominates in the noxious range.

neuroscience↗

bioRxiv2024

A browser-based platform for storage, visualization, and analysis of large-scale 3D images in HPC environments

High-throughput microscopy necessitates 3D image storage, visualization, and analysis in terabyte to petabyte scales. Centralized high-performance computing (HPC) infrastructure provides the resources, but interfacing software is limited. We developed an extensible platform with a scalable image storage format (SISF) and content delivery network (CDN) to enable fast, random access to compressed data. Additionally, we built a cloud-based nTracer2 software to annotate neuron morphology from SISF images in a web browser.

bioinformatics↗

bioRxiv2024

Artifact-Minimized High-Ratio Image Compression with Preserved Analysis Fidelity

Recent advances in microscopy have pushed imaging data generation to an unprecedented scale. While scientists benefit from higher spatiotemporal resolutions and larger imaging volumes, the increasing data size presents significant storage, visualization, sharing, and analysis challenges. Lossless compression typically reduces the data size by <4 fold, whereas lossy compression trades smaller data size for the loss of a precise reconstruction of the original data. Here, we develop a novel quantization method and an artifact metric for automated compression parameter optimization that preserves information fidelity. We show that, when combined with the AV1 video codec, we achieve tens to ten thousand folds of data compression while introducing negligible visual defects or quantification errors in single-molecule localization and segmentation analyses. We developed an HDF5 filter with FFMPEG library support for convenient community adaptation. For instance, HDF5-enabled ImageJ plugins can now be seamlessly extended to support AV1 compression and visualization to handle terabyte-scale images.

bioinformatics↗

bioRxiv2024

Cost-effective DNA storage with DNA movable type

In the face of exponential data growth, DNA-based storage offers a promising solution for preserving big-data. However, most existing DNA storage methods, akin to traditional block printing, require costly chemical synthesis for each individual data file, adopting a sequential, one-time-use synthesis approach. To overcome these limitations, we introduce a novel, cost-effective "DNA-Movable-Type Storage" system, inspired by movable type printing. This system utilizes pre-fabricated DNA movable types-short, double-stranded DNA oligonucleotides encoding specific payload, address, and checksum data. These DNA-MTs are enzymatically ligated/assembled into cohesive sequences, termed "DNA movable type blocks", streamlining the assembly process with the automated BISHENG-1 DNA-MT inkjet printer. Using BISHENG-1, we successfully printed, assembled, stored and accurately retrieved 43.7 KB of data files in diverse formats (text, image, audio, and video) in vitro and in vivo, using only 350 DNA-MTs. Notably, each DNA-MT, synthesized once (2 OD), can be used up to 10,000 times, reducing costs to 122 $/MB-outperforming existing DNA storage methods. This innovation circumvents the need to synthesize entire DNA sequences encoding files from scratch, offering significant cost and efficiency advantages. Furthermore, it has considerable untapped potential to advance a robust DNA storage system, better meeting the extensive data storage demands of the big-data era.

bioinformatics↗

bioRxiv2024

Mechanisms for dysregulation of excitatory-inhibitory balance underlying allodynia in dorsal horn neural subcircuits

Chronic pain is a wide-spread condition that is debilitating and expensive to manage, costing the United States alone around $600 billion in 2010. In a common type of chronic pain called allodynia, non-painful stimuli produce painful responses with highly variable presentations across individuals. While the specific mechanisms remain unclear, allodynia is hypothesized to be caused by the dysregulation of excitatory-inhibitory (E-I) balance in pain-processing neural circuitry in the dorsal horn of the spinal cord. In this work, we analyze biophysically-motivated subcircuit structures that represent common motifs in neural circuits in layers I-II of the dorsal horn. These circuits are hypothesized to be part of the neural pathways that mediate two different types of allodynia: static and dynamic. We use neural firing rate models to describe the activity of populations of excitatory and inhibitory interneurons within each subcircuit. By accounting for experimentally-observed responses under healthy conditions, we specify model parameters defining populations of subcircuits that yield typical behavior under normal conditions. Then, we implement a sensitivity analysis approach to identify the mechanisms most likely to cause allodynia-producing dysregulation of the subcircuits E-I signaling. We find that disruption of E-I balance generally occurs either due to downregulation of inhibitory signaling so that excitatory neurons are "released" from inhibitory control, or due to upregulation of excitatory neuron responses so that excitatory neurons "escape" their inhibitory control. Which of these mechanisms is most likely to occur, the subcircuit components involved in the mechanism, and the proportion of subcircuits exhibiting the mechanism can vary depending on the subcircuit structure. These results suggest specific hypotheses about diverse mechanisms that may be most likely responsible for allodynia, thus offering predictions for the high interindividual variability observed in allodynia and identifying targets for further experimental studies on the underlying mechanisms of this chronic pain condition. Author summaryWhile chronic pain affects roughly 20% of the US adult population [1], symptoms and presentations of the condition are highly variable across individuals and its causes remain largely unknown. A prevailing hypothesis for the cause of a type of chronic pain called allodynia is that the balance between excitatory and inhibitory signaling pathways between neuron populations in the spinal cord dorsal horn may be disrupted. To help better understand neural mechanisms underlying allodynia, we analyze biologically-motivated mathematical models of subcircuits of neuron populations that are part of the pain processing signaling pathway in the dorsal horn of the spinal cord. We use a novel sensitivity analysis approach to identify mechanisms of subcircuit dysregulation that may contribute to two different types of allodynia. The model results identify specific subcircuit components that are most likely to contribute to each type of allodynia. These mechanisms suggest targets for further experimental study, as well as for pharmacological intervention for better pain treatments.

neuroscience↗

bioRxiv2024

PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization

Single-cell perturbation sequencing techniques (scPerturbation), represented by single cell genetic perturbation sequencing (e.g., Perturb-seq) and single cell chemical perturbation sequencing (e.g., sci-Plex), result from the integration of single-cell toolkits with conventional bulk screening methods. These innovative sequencing techniques empower researchers to dissect perturbation functions and mechanisms in complex biological systems at an unprecedented resolution. Despite these advancements, a notable gap exists in the availability of a dedicated database for exploring and querying scPerturbation data. To address this gap and facilitate seamless data sharing for researchers, we present PerturBase--the first and most comprehensive database designed for the analysis and visualization of scPerturbation data (http://www.perturbase.cn/). PerturBase consolidates 122 datasets from 46 publicly accessible research studies, covering 115 single-modal and 7 multi-modal datasets that include 24254 genetic and 230 chemical perturbations from about 6 million cells. The database provides insights through various software-analyzed results, encompassing quality control, denoising, differential expression gene analysis, perturbation function analysis, and correlation characterization between perturbations. All datasets and in-depth analyses are presented in user-friendly, easy-to-browse pages and can be visualized through intuitive tables and various image formats. In summary, PerturBase stands as a pioneering high-content database, intended for searching, visualizing, and analyzing scPerturbation datasets, contributing to an enhanced understanding of perturbation functions and mechanisms. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/578767v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@15bdfcborg.highwire.dtl.DTLVardef@c1be77org.highwire.dtl.DTLVardef@1bf7e32org.highwire.dtl.DTLVardef@f62e8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Higher-order epistasis within Pol II trigger loop haplotypes

RNA polymerase II (Pol II) has a highly conserved domain, the trigger loop (TL), that controls transcription fidelity and speed. We previously probed pairwise genetic interactions between residues within and surrounding the TL for the purpose of understand functional interactions between residues and to understand how individual mutants might alter TL function. We identified widespread incompatibility between TLs of different species when placed in the Saccharomyces cerevisiae Pol II context, indicating species-specific interactions between otherwise highly conserved TLs and its surroundings. These interactions represent epistasis between TL residues and the rest of Pol II. We sought to understand why certain TL sequences are incompatible with S. cerevisiae Pol II and to dissect the nature of genetic interactions within multiply substituted TLs as a window on higher order epistasis in this system. We identified both positive and negative higher-order residue interactions within example TL haplotypes. Intricate higher-order epistasis formed by TL residues was sometimes only apparent from analysis of intermediate genotypes, emphasizing complexity of epistatic interactions. Furthermore, we distinguished TL substitutions with distinct classes of epistatic patterns, suggesting specific TL residues that potentially influence TL evolution. Our examples of complex residue interactions suggest possible pathways for epistasis to facilitate Pol II evolution.

genetics↗

bioRxiv2023

Widespread epistasis shapes RNA Polymerase II active site function and evolution

Multi-subunit RNA Polymerases (msRNAPs) are responsible for transcription in all kingdoms of life. These enzymes rely on dynamic, highly conserved active site domains such as the so-called "trigger loop" (TL) to accomplish steps in the transcription cycle. Mutations in the RNA polymerase II (Pol II) TL confer a spectrum of biochemical and genetic phenotypes that suggest two main classes, which decrease or increase catalysis or other nucleotide addition cycle (NAC) events. The Pol II active site relies on networks of residue interactions to function, and mutations likely perturb these networks in ways that may alter mechanisms. We have undertaken a structural genetics approach to reveal residue interactions within and surrounding the Pol II TL - determining its "interaction landscape" - by deep mutational scanning in Saccharomyces cerevisiae Pol II. This analysis reveals connections between TL residues and surrounding domains, demonstrating that TL function is tightly coupled to its specific enzyme context.

genetics↗

bioRxiv2023

Cell Instance Segmentation via Multi-Scale Non-local Correlation

For cell instance segmentation on Electron Microscopy (EM) images, state-of-the-art methods either conduct pixel-wise classification or follow a detection and segmentation manner. However, both approaches suffer from the enormous cell instances of EM images where cells are tightly close to each other and show inconsistent morphological properties and/or homogeneous appearances. This fact can easily lead to over-segmentation and under-segmentation problems for model prediction, i.e., falsely splitting and merging adjacent instances. In this paper, we propose a novel approach incorporating non-local correlation in the embedding space to make pixel features distinct or similar to their neighbors and thus address the over- and under-segmentation problems. We perform experiments on five different EM datasets where our proposed method yields better results than several strong baselines. More importantly, by using non-local correlation, we observe fewer false separations within one cell and fewer false fusions between cells.

bioinformatics↗

bioRxiv2022

Characterization of RNA Polymerase II Trigger Loop Mutations using Molecular Dynamics Simulations and Machine Learning

Catalysis and fidelity of multisubunit RNA polymerases rely on a highly conserved active site domain called the trigger loop (TL), which achieves roles in transcription through conformational changes and interaction with NTP substrates. The mutations of TL residues cause distinct effects on catalysis including hypo- and hyperactivity and altered fidelity. We applied molecular dynamics simulation (MD) and machine learning (ML) techniques to characterize TL mutations in the Saccharomyces cerevisiae RNA Polymerase II (Pol II) system. We did so to determine relationships between individual mutations and phenotypes and to associate phenotypes with MD simulated structural alterations. Using fitness values of mutants under various stress conditions, we modeled phenotypes along a spectrum of continual values. We found that ML could predict the phenotypes with 0.68 R2 correlation from amino acid sequences alone. It was more difficult to incorporate MD data to improve predictions from machine learning, presumably because MD data is too noisy and possibly incomplete to directly infer functional phenotypes. However, a variational auto-encoder model based on the MD data allowed the clustering of mutants with different phenotypes based on structural details. Overall, we found that lethal mutations tended to increase distances of TL residues to the NTP substrate, while viable loss-of-function (LOF) substitutions tended to confer an increase in distances between TL and bridge helix (BH). In contrast, GOF mutants generally have a disrupting effect on hydrophobic contacts among TL and nearby helices. AUTHOR SUMMARYRNA polymerase II (Pol II) synthesizes RNA with the help of an active site domain called trigger loop (TL). The mutations of TL cause changes in the activity of Pol II that could range from gain-of function (GOF) to loss-of-function (LOF) or lethal. This study provides a systematic characterization of the structural and functional outcomes of the TL mutations using molecular dynamics (MD) simulations and machine learning (ML). We obtained functional phenotypes of mutants by ML using the genetic fitness scores as the input. We revealed that mutant TL sequences could predict the functional outcomes at a relatively high correlation. Then, we performed MD simulations to relate the structural information to the phenotypes. The analysis of the MD data suggested that the lethal mutants had increased distances between the TL and the substrate, while a subset of LOF mutants showed increased distances between TL and another active site domain called bridge helix (BH). On the other hand, GOF mutants had effects on the hydrophobic interactions around the active site. Overall, this study enhances our understanding of the effects of TL mutations to the Pol II function.

biophysics↗