Biology subjects

Ling, T.

Publications and source records attributed to Ling, T..

At least 19 recordsLinked to original sources

bioRxiv2026

π-MNovo improves de novo peptide sequencing through microbial-domain adaptation and evidence-guided candidate selection

The high taxonomic and strain-level diversity of microbial communities makes it difficult for reference databases to fully represent the protein sequences present in metaproteomic samples, limiting database-dependent peptide identification. De novo peptide sequencing can recover peptide sequences directly from tandem mass spectra without relying on reference databases, providing complementary peptide evidence for metaproteomics. However, most existing de novo sequencing models were developed largely from non-microbial proteomic data and lack specific adaptation to microbial spectra. Here, we established a dedicated microbial spectral resource comprising more than 10 million annotated high-quality tandem mass spectra from 72 cultured microbial isolates, with peptide digests from each isolate separated into five high-pH reversed-phase fractions to increase the opportunity for deeper and more diverse peptide sampling. Using this resource, we developed {pi}-MNovo, which combines adaptation to microbial spectra with evidence-guided candidate selection to improve full-length peptide sequencing precision. On a seven-species external benchmark, {pi}-MNovo achieved 66.30% complete-peptide recall under the same residue-mass-based complete-peptide matching criterion applied to all models, exceeding four published models by 6.9-21.7% in relative recall, with consistent gains across species and peptide-length groups. In two independent metaproteomic datasets, {pi}-MNovo increased reference-supported taxonomic coverage, while synthetic-community analysis recapitulated the designed abundance ranking. From pFind-unidentified spectra, {pi}-MNovo recovered 1,587 pFind-unreported, reference-matched peptides that passed spectrum-evidence filtering. These results show that {pi}-MNovo expands recoverable peptide evidence and enhances the utility of de novo sequencing for metaproteomic analysis.

bioinformatics↗

bioRxiv2026

False discovery rate control for trustworthy AI-based de novo peptide sequencing

AI-based de novo peptide sequencing predicts peptide sequences from tandem mass spectra, enabling identification beyond predefined databases but leaving prediction reliability difficult to assess, particularly with respect to false discovery rate (FDR). In database search, FDR control is provided by target-decoy competition over a finite search space, whereas de novo predictions are generated in open sequence space and lack naturally matched sequence-level decoys. Here we introduce Counterpart Calibration Theory (CCT), a theory-guided framework that reframes de novo FDR control as a four-group score-ranking and threshold-selection problem over target-side predictions and matched counterpart-side comparators. Implemented in {pi}-NovoQC, CCT provides dual-level FDR control at the peptide-spectrum match and peptide levels. Across models, datasets, instruments and acquisition modes, {pi}-NovoQC achieves stable FDR control while preserving identification yield. In large-scale proteomic applications, {pi}-NovoQC recovers low-abundance in-database peptides missed by database search and provides de novo-supported protein-group and variant evidence.

bioinformatics↗

bioRxiv2026

Secreted phospholipase A2α generates a pathogen-derived lysophospholipid to signal local immunity

In plants, effector-triggered immunity (ETI) is initiated when NLR receptors recognize pathogen effectors, yet the molecular signals linking this recognition to downstream defense activation remain poorly defined, in contrast to the well-characterized immunogenic signals of pattern-triggered immunity. Here, we show that a lysophospholipid is a previously unidentified ETI-mediating immune signal generated through host enzymatic conversion of pathogen membrane lipids. Upon recognition of avirulent Pseudomonas syringae, secretory phospholipase A2 (PLA2) is rapidly induced and secreted into the apoplast, where it hydrolyzes bacterial phosphatidylethanolamine to produce lysophosphatidylethanolamines (LPEs), predominantly LPE18:1. Genetic ablation of PLA2 compromises local immunity, hypersensitive response confinement, and defense gene activation, all of which are largely rescued by exogenous LPE18:1. Mechanistically, LPE18:1 promotes ICS1-dependent salicylic acid biosynthesis and NPR1-mediated transcriptional reprogramming. Together, these findings support pathogen-derived LPE18:1 as a newly identified lipid-based immune signal that links NLR activation to spatially confined defense responses. The evolutionary conservation of secretory PLA2 enzymes and lysophospholipid signaling from plants to mammals suggests that host-directed enzymatic remodeling of pathogen membranes into immune-activating lipid signals may constitute a conserved strategy of innate immunity.

plant biology↗

bioRxiv2026

In vivo elastography of the human retina using light-evoked intrinsic actuation

The biomechanical properties of the retina govern its function, structural integrity, and susceptibility to disease, yet remain difficult to measure in vivo due to the lack of safe, spatially localized mechanical actuation. Here, we introduce a framework for probing retinal biomechanics in the living human eye by leveraging intrinsic optical actuation driven by phototransduction. Using phase-resolved optical coherence tomography with a local phase-referencing approach, we resolved signed, nanometer-scale displacements of the major outer retinal interfaces evoked by light. The resulting deformation field, originating in the photoreceptor outer segment, was distributed across retinal compartments in an eccentricity-dependent manner, with efficient axial transfer in the fovea and attenuated propagation in the parafovea. A hybrid analytical and finite-element framework was developed that retrieved the biomechanical properties of the retinal compartments based on their coordinated deformation and the anatomical variation in retinal structure versus eccentricity. In retinitis pigmentosa, the paradigm enabled the detection of light-evoked deformation in the transition zone despite the loss of native lamination, enabling a functional readout of the vulnerable photoreceptors at the leading edge of degeneration. Together, these results establish intrinsic optical stimulation as a basis for in vivo retinal elastography and enable the non-invasive, quantitative imaging of retinal biomechanics and function in the living human retina.

biophysics↗

bioRxiv2026

π-MSNet: A billion-scale, AI-ready living proteomics data portal

Artificial intelligence (AI) is reshaping proteomics workflows, delivering remarkable gains in both peptide identification sensitivity and quantitative performance. However, the potential of deep learning models in proteomics has not been fully exploited due to the scarcity of large-scale, high-quality and consistently labeled datasets. Here, we present {pi}-MSNet, a billion-scale, AI-ready living mass spectrometry (MS) data portal. Using a uniform identification and quality control workflow, it comprises over 1.66 billion MS/MS spectra, 501 million peptide-spectrum matches (PSMs), and 9 million precursors from 36,356 LC-MS/MS runs across ten instrument types and 55 diverse species. Through community collaboration, the data are shared via international, interactive, and living web resources. Enabled by the built-in MSNetLoader Python API for seamless and scalable data access--with native support for PyTorch and TensorFlow--{pi}-MSNet provides an AI-ready data framework for efficient training and systematic benchmarking of multiple models across three representative tasks (e.g., MS/MS spectrum prediction, retention time prediction, and de novo peptide sequencing). In particular, by retraining multiple models on {pi}-MSNet, we achieved consistent performance improvements over their original versions. These improved models were subsequently integrated into the {pi}-MSNet agent to enable interactive, deployment-free use. Through SDRF (Sample and Data Relationship Format) metadata, an open-source cloud analysis workflow, and a community-driven interactive data portal that supports continuous data submission, {pi}-MSNet serves as a living, AI-ready resource for reproducible benchmarking, robust model training, and accelerated AI innovation in proteomics.

bioinformatics↗

bioRxiv2026

Inhibition of the EBF1-ITGB8 Axis in Bone Marrow Niche Ameliorates Hallmarks of Myelofibrosis

Fibrotic remodeling of the bone marrow (BM) niche is a characteristic feature of myelofibrosis (MF) that contributes to disease progression. In MF, mesenchymal stromal cells (MSCs) produce excessive amounts of inflammatory cytokines and extracellular matrix, leading to BM fibrosis, impaired blood production, extramedullary hematopoiesis, and progressive BM failure. While the genetic events that initiate MF in hematopoietic cells are well defined, our understanding of the mechanisms responsible for BM fibrosis remains incomplete. Here, we show that transcription factor EBF1 is a key regulator of the fibrotic gene program in mouse and human MSCs. EBF1 is upregulated in pre-fibrotic MSCs, while mice with MSC-specific deletion of Ebf1 exhibit reduced BM fibrosis, decreased expansion of myeloid cells and splenomegaly when transplanted with hematopoietic progenitors harboring the MF driver mutation MPLW515L. Moreover, we identify ITGB8 as an EBF1-regulated gene with therapeutic potential. MF mice treated with ITGB8-neutralizing antibodies or with MSC-specific Itgb8 deletion show reduced disease burden, as indicated by decreased marrow fibrosis, significantly reduced frequencies of MPL mutant cells, and reduced inflammation in the BM. Our data indicate that targeting the EBF1-ITGB8 axis in the MF MSCs may have therapeutic benefits.

cell biology↗

bioRxiv2025

Surface proteomics reveals arginine metabolism as a vulnerability in high grade serous ovarian cancer

The significant lethality of high-grade serous ovarian cancer (HGSC) is driven by the lack of long-term efficacy of current treatments, underscoring the need for developing additional therapeutics. Cell surface proteins represent attractive therapeutic targets yet remain underexplored in high-grade serous ovarian cancer. Here, we employed cell surface N-glycoproteomics to elucidate the cell surface proteomes of HGSC cells alongside normal epithelial and cancer-associated stromal cells, uncovering new opportunities for therapeutic intervention. Integration of cell surface N-glycoproteomics and functional screening revealed multiple minimally characterized, HGSC-enriched surface proteins that are critical for HGSC proliferation, most notably, SLC7A1. Multi-omic and functional characterization indicated that SLC7A1 is necessary for HGSC migration, protein synthesis and mitochondrial functions likely linked to its role as an arginine transporter. Finally, we demonstrate that elevated surface expression of SLC7A1 in HGSC reflects dysregulated arginine metabolism, pointing to a putative therapeutic vulnerability. Our work identifies SLC7A1 and arginine metabolism as a previously unrecognized molecular vulnerability in HGSC and provides a framework to guide future therapeutic development.

cancer biology↗

bioRxiv2025

Label-Free Mapping of Subcellular Dynamics using Wide-field Interferometric Scattering Microscopy and Spectral Exponent Analysis

Interferometric scattering (iSCAT) microscopy combines label-free detection with nanometer-scale motion sensitivity. It captures temporal signal fluctuations from sub-diffraction movements of scatterers in live cells, including macromolecules and cell membranes. Here, we investigate label-free mapping of subcellular dynamics by calculating the power spectral density (PSD) of the iSCAT time series. Using a wide-field iSCAT, we observe an inverse-power-law relationship S(f) = {beta}f- over 30 - 1250 Hz in multiple cell types. We compute pixel-wise PSDs and obtain a color-coded spectral exponent map based on the fitted spectral exponent () and amplitude ({beta}), which indicates the characteristics and strength of subcellular movements. We also incorporate the goodness-of-fit as color saturation to enhance the contrast of the spectral exponent map. Following this approach, we demonstrate label-free imaging of live cells while effectively distinguishing between benign and malignant thyroid cancer subtypes, mitotic and interphase cells, as well as live and apoptotic cells. Dynamic imaging using wide-field iSCAT provides an intrinsic, label-free marker of cellular states and mechanical properties, which may benefit studies in mechanobiology, cancer diagnostics, and stem cell therapies.

bioengineering↗

bioRxiv2025

Optoretinography reveals rapid rod photoreceptor movement upon photoisomerization

Rod photoreceptors are essential for vision under dim light conditions. The onset of rod-mediated vision is marked by the isomerization of rhodopsin. Here we demonstrate that human and rodent rods undergo a minute and rapid contraction of their outer segments immediately upon photoisomerization. The contraction is explained as an electro-mechanical manifestation of the rod early receptor potential generated in the disk membranes, which is challenging to access in electrophysiology. The bleach-strength dependence of the contraction was accounted by a voltage-dependent membrane tension model, developed earlier to explain a similar behavior in cones. The in vivo optical imaging of light-evoked electrical activity in rodent rods was facilitated by an ultrahigh-resolution point-scan optical coherence tomography (OCT) system coupled with unsupervised learning, while in humans, an adaptive optics line-scan OCT facilitated high-speed recordings in individual rods. The non-invasive in vivo optical imaging of rhodopsin activation will have a significant impact on diagnostics and treatment of retinal disease, especially given the vulnerability of rods in inherited and age-related macular degeneration.

bioengineering↗

bioRxiv2025

Brain-wide mapping reveals temporal and sexually dimorphic opioid actions

While the molecular and cellular effects of opioids have been extensively studied, the precise mechanisms by which these drugs target specific brain regions over time remain unclear. Similarly, despite well-documented sex differences in opioid responses, the anatomical basis for this sexual dimorphism is not well characterized. To address these questions, we developed an automated, scalable, and unbiased approach for whole-brain anatomical mapping of the neuronal activity marker c-Fos in response to acute morphine exposure. Using ribbon scanning confocal microscopy, we imaged whole cleared brains from male and female wild-type mice at 1 hour and 4 hours post-morphine administration. Our whole-brain analysis of c-Fos expression revealed distinct patterns of morphine-induced regional brain activation across time and sex. Notably, we observed a greater number of structures with significant activity differences at 4 hours compared to 1 hour. In male mice, significant changes were primarily localized to regions within the dopamine system, whereas in female mice, they were concentrated in cortical regions. By combining high-throughput imaging with whole-brain expression analysis, particularly in the context of opioid actions, our approach provides a more comprehensive understanding of how drugs of abuse affect the brain.

neuroscience↗

bioRxiv2024

Retinal thermometry in-vivo using phase-sensitive optical coherence tomography

Controlling the tissue temperature rise during retinal laser therapy is essential for predictable outcomes, especially at non-damaging settings. We demonstrate a method for determining the temperature rise in the retina using phase-resolved optical coherence tomography (pOCT) in vivo. Measurements based on the thermally induced optical path length changes ({Delta}OPL) in the retina during a 10-ms laser pulse allow detection of the temperature rise with a precision less than 1 {degrees}C, which is sufficient for calibration of the laser power for patient-specific non-damaging therapy. We observed a significant difference in confinement of the retinal deformations between the normal and the degenerate retina: in wild-type rats, thermal deformations are localized between the retinal pigment epithelium (RPE) and the photoreceptors inner segments (IS), as opposed to a deep penetration of the deformations into the inner retinal layers in the degenerate retina. This implies the presence of a structural component within healthy photoreceptors that dampens the tissue expansion induced by the laser heating of the RPE and pigmented choroid. We hypothesize that the thin and soft cilium connecting the inner and outer segments (IS, OS) of photoreceptors may absorb the deformations of the OS and thereby preclude the tissue expansion further inward. Striking difference in the confinement of the retinal deformations induced by a laser pulse in healthy and degenerate retina may be used as a biomechanical diagnostic tool for the characterization of photoreceptor degeneration.

bioengineering↗

bioRxiv2024

Pi-PrimeNovo: An Accurate and Efficient Non-Autoregressive Deep Learning Model for De Novo Peptide Sequencing

Peptide sequencing via tandem mass spectrometry (MS/MS) is fundamental in proteomics data analysis, playing a pivotal role in unraveling the complex world of proteins within biological systems. In contrast to conventional database searching methods, deep learning models excel in de novo sequencing peptides absent from existing databases, thereby facilitating the identification and analysis of novel peptide sequences. Current deep learning models for peptide sequencing predominantly use an autoregressive generation approach, where early errors can cascade, largely affecting overall sequence accuracy. And the usage of sequential decoding algorithms such as beam search suffers from the low inference speed. To address this, we introduce{pi} -PrimeNovo, a non-autoregressive Transformer-based deep learning model designed to perform accurate and efficient de novo peptide sequencing. With the proposed novel architecture,{pi} -PrimeNovo achieves significantly higher accuracy and up to 69x faster sequencing compared to the state-of-the-art methods. This remarkable speed makes it highly suitable for computation-extensive peptide sequencing tasks such as metaproteomic research, where{pi} -PrimeNovo efficiently identifies the microbial species-specific peptides. Moreover,{pi} -PrimeNovo has been demonstrated to have a powerful capability in accurately mining phosphopeptides in a non-enriched phosphoproteomic dataset, showing an alternative solution to detect low-abundance post-translational modifications (PTMs). We suggest that this work not only advances the development of peptide sequencing techniques but also introduces a transformative computational model with wide-range implications for biological research.

bioinformatics↗

bioRxiv2023

Building synthetic biosensors using red blood cell proteins

As the use of engineered cell therapies expands from pioneering efforts in cancer immunotherapy to other applications, an attractive but less explored approach is the use of engineered red blood cells (RBCs). Compared to other cells, RBCs have a very long circulation time and reside in the blood compartment, so they could be ideally suited for applications as sentinel cells that enable in situ sensing and diagnostics. However, we largely lack tools for converting RBCs into biosensors. A unique challenge is that RBCs remodel their membranes during maturation, shedding many membrane components, suggesting that an RBC-specific approach may be needed. Towards addressing this need, here we develop a biosensing architecture built on RBC membrane proteins that are retained through erythropoiesis. This biosensor employs a mechanism in which extracellular ligand binding is transduced into intracellular reconstitution of a split output protein (including either a fluorophore or an enzyme). By comparatively evaluating a range of biosensor architectures, linker types, scaffold choices, and output signals, we identify biosensor designs and design features that confer substantial ligand-induced signal in vitro. Finally, we demonstrate that erythroid precursor cells engineered with our RBC protein biosensors function in vivo. This study establishes a foundation for developing RBC-based biosensors that could ultimately address unmet needs including non-invasive monitoring of physiological signals for a range of diagnostic applications.

synthetic biology↗

bioRxiv2023

WTAP is Transcriptionally Regulated by p65 and Promotes Inflammation through m6A Modification and Phase Separation

Emerging evidence has linked dysregulation of N6-methyladenosine (m6A) to inflammation and inflammatory diseases, but the underlying mechanism still needs investigation. Here, we found that high m6A modification in a variety of hyperinflammatory states is p65-dependent, because Wilms tumor 1 associated protein (WTAP), a key component of the writer complex, is transcriptionally regulated by p65 and its overexpression can lead to higher m6A modification. Mechanistically, upregulated WTAP is more prone to phase separation to facilitate the aggregation of "writer" complex to nuclear speckles and the deposition of m6A marks onto transcriptionally active inflammatory transcripts, thereby accelerating proinflammatory response. Furthermore, myeloid deficiency of WTAP attenuates the severity of LPS-induced sepsis and DSS-induced IBD. Thus, the proinflammatory effect of WTAP is a general risk-increasing mechanism, and interrupting the assembly of m6A writer complex by targeting the phase separation of WTAP to reduce the global m6A level may be a potential and promising therapeutic strategy for alleviating hyperinflammation.

immunology↗

bioRxiv2023

Targeting Acute Myeloid Leukemia Stem Cells Through Perturbation of Mitochondrial Calcium

We previously reported that acute myeloid leukemia stem cells (LSCs) are uniquely reliant on oxidative phosphorylation (OXPHOS) for survival. Moreover, maintenance of OXPHOS is dependent on BCL2, creating a therapeutic opportunity to target LSCs using the BCL2 inhibitor drug venetoclax. While venetoclax-based regimens have indeed shown promising clinical activity, the emergence of drug resistance is prevalent. Thus, in the present study, we investigated how mitochondrial properties may influence mechanisms that dictate venetoclax responsiveness. Our data show that utilization of mitochondrial calcium is fundamentally different between drug responsive and non-responsive LSCs. By comparison, venetoclax-resistant LSCs demonstrate a more active metabolic (i.e., OXPHOS) status with relatively high steady-state levels of calcium. Consequently, we tested genetic and pharmacological approaches to target the mitochondrial calcium uniporter, MCU. We demonstrate that inhibition of calcium uptake sharply reduces OXPHOS and leads to eradication of venetoclax-resistant LSCs. These findings demonstrate a central role for calcium signaling in the biology of LSCs and provide a therapeutic avenue for clinical management of venetoclax resistance. SignificanceWe identify increased utilization of mitochondrial calcium as distinct metabolic requirement of venetoclax-resistant LSCs and demonstrate the potential of targeting mitochondrial calcium uptake as a therapeutic strategy.

cancer biology↗

bioRxiv2023

Introducing PandaNovo for practical large-scale de novo peptide sequencing

De novo peptide sequencing is a promising approach for novel peptide discovery. We use a novel concept of complementary spectra to enhance ion information and propose a de novo sequencing model{pi} -HelixNovo based on Transformer architecture.{pi} -HelixNovo outperforms other state-of-the-art models and enhances the taxonomic resolution of gut metaproteome, taking a significant step forward in de novo sequencing.

bioinformatics↗

bioRxiv2023

Automated, unbiased optoretinography reveals comprehensive nanoscopic dynamics of the outer retina in rodents

Phototransduction involves changes in concentration of ions and other solutes within photoreceptors and in subretinal space, which affect osmotic pressure and the associated water flow. Corresponding expansion and contraction of cellular layers can be imaged using optoretinography (ORG), based on phase-resolved optical coherence tomography (OCT). Until now, ORG could reliably detect only photoisomerization and phototransduction in photoreceptors, primarily in cones under very bright stimuli. By employing a novel subpixel bulk motion correction algorithm, which enabled imaging of the nanometer-scale tissue dynamics during minute-long recordings, and unsupervised learning of spatiotemporal patterns, we discovered optical signatures of the other retinal structures response to visual stimuli. These include inner and outer segments of rod photoreceptors, retinal pigment epithelium, and subretinal space in general. High sensitivity of our technique enabled detection of the retinal responses to very dim stimuli: down to 0.01% bleach level, corresponding to natural levels of scotopic illumination. We also demonstrated that with a single flash, the optoretinogram can map retinal responses across a 12{degrees}field of view, potentially replacing multifocal electroretinography, with its long acquisition time and low spatial resolution. This new technique expands the diagnostic capabilities and practical applicability of optoretinography, providing a more complete replacement of electroretinography, while combining structural and functional retinal imaging in the same OCT machine.

bioengineering↗

bioRxiv2022

Shot-noise limited phase-sensitive imaging of moving samples by phase-restoring subpixel motion correction in Fourier-domain optical coherence tomography

Phase-sensitive Fourier-domain optical coherence tomography (FD-OCT) enables in-vivo, label- free imaging of cellular movements with detection sensitivity down to the nanometer scale, and it is widely employed in emerging functional imaging modalities, such as optoretinography (ORG), Doppler OCT, and optical coherence elastography. However, when imaging tissue dynamics in vivo, tissue movement or bulk motion introduces decorrelation noise that compromises motion detection performance, particularly in terms of sensitivity and accuracy. Here, we demonstrate that the motion-related decorrelation noise in FD-OCT can be accurately corrected by restoring the initial sampling points using our proposed Phase-Restoring Subpixel Image Registration (PRESIR) method. Derived from a general FD-OCT model, the PRESIR method enables translational shifting of complex-valued OCT images over arbitrary displacements with subpixel precision, while accurately restoring phase components. Unlike conventional approaches that shift OCT images either in the spatial domain at the pixel level or in the spatial frequency domain for subpixel correction, our method reconstructs OCT images by correcting axial displacement in the spectral domain (k domain) and lateral displacement in the spatial frequency domain. We validated the PRESIR method through simulations, phantom experiments, and in-vivo optoretinography in both rodents and human subjects. Our approach significantly reduced decorrelation noise during the imaging of moving samples, achieving phase sensitivity close to the fundamental limit determined by the signal-to-noise ratio (SNR).

bioengineering↗