bioRxiv Science⌕ Search

Biology subjects

Tang, H.

Publications and source records attributed to Tang, H..

At least 55 records · Page 3Linked to original sources

Inhibiting RhoA Activation via GDP-state Stabilization to Relieve Heart Failure

High rates of heart failure (HF) morbidity and mortality have made targeting myocardial remodeling--particularly hypertrophy and fibrosis--a key therapeutic focus. RhoA, which regulates cytoskeletal reorganization and cell migration, plays a role in this process. However, RhoA has long been considered "undruggable", due to its strong binding to its endogenous substrates, GDP/GTP, and the lack of well-defined pockets for drug targeting. Here, we discovered a cryptic pocket proximate to GDP within RhoA and identified a natural product, AH001, binds here and interacts with GDP, stabilizing RhoAs interaction with its endogenous inhibitor, RhoGDI. AH001 reduced the downstream MRTFA nuclear translocation and downregulated fibrosis/hypertrophy proteins. Consequently, AH001 mitigated myocardial remodeling in multiple HF animal models, and in the 3D myocardial tissue model. Our findings highlight the therapeutic potential of inhibiting RhoA activation in myocardial remodeling, ultimately targeting HF, and offer a promising avenue for developing reversible inhibitors against undruggable GTPases.

pharmacology and toxicology↗

A Global Thermodynamic-Kinetic Model Capturing the Hallmarks of Liquid-Liquid Phase Separation and Amyloid Aggregation

Aberrant aggregation of proteins into amyloid fibrils is associated with numerous neurodegenerative, systemic and metabolic diseases. Amyloidogenic proteins undergo spontaneous liquid-liquid phase separation (LLPS), rapidly forming protein-rich condensates prior to fibrillization. However, the exact effects of LLPS on amyloid aggregation remain unclear as contrasting fibrillization-promotion, inhibition and even biphasic effects have been reported in the literature. In this study, we integrate LLPS-induced heterogeneity of protein concentrations into a thermodynamic-kinetic model of amyloid aggregation. We adopt the phase transition theory and introduce protein condensates as an additional protein state alongside non-interacting monomers, oligomers and fibrils. Oligomerization and fibrillization can occur both in the protein-rich condensates and the protein-poor solution. This model allows us to derive the time evolution of different states - monomers, condensates, oligomers, and fibrils - spanning a wide range of concentrations, and determine how model parameters related to LLPS, fibrillization, and oligomerization influence fibrillization kinetics. Using this global model, we resolve the seemingly contradictory effects of LLPS on fibrillization. We expect the developed thermodynamic-kinetic model of LLPS, and amyloid aggregation will help advance our understanding, modulation, and mitigation of pathological aggregation processes in amyloid diseases. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=62 SRC="FIGDIR/small/655849v1_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@12eeb58org.highwire.dtl.DTLVardef@15cee66org.highwire.dtl.DTLVardef@278c10org.highwire.dtl.DTLVardef@5c8d4a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

An Optimized FungaLight LIVE/DEAD Assay Quantifies Post-Stress and Antifungal-Treatment Survival in Diverse Yeasts Using Flow Cytometry

Quantifying post-stress survival in yeasts is crucial for biological, biomedical, and industrial research. Traditional methods like Colony Forming Unit (CFU) assays are labor-intensive and time-consuming. In this study, we systematically characterize a two-dye (SYTO 9 / Propidium Iodide) LIVE/DEAD assay coupled with flow cytometry to rapidly and scalably quantify post-stress survival in diverse yeast species. By optimizing staining buffer, dye concentrations and staining time, we minimized artifacts and improved reproducibility. Notably, we identify an "Intermediate" population containing damaged cells with enhanced SYTO 9 uptake but little propidium iodide (PI) accumulation under sublethal stress, providing finer gradations of cellular damage compared to CFU or PI staining alone. We demonstrate the assays applicability across Candida glabrata, Saccharomyces cerevisiae, and Candida albicans after hydrogen peroxide treatment and in C. glabrata after Amphotericin B exposure. While CFU is more sensitive at lower stress levels, the SYTO 9/PI staining effectively distinguishes sublethal from lethal doses, offering a valuable alternative for rapid, high-throughput survival quantification.

microbiology↗

Identifying Key Cells for Fibrosis by Systematically Calling Cell Type-Phenotype Associations across Massive Heterogenous Datasets

Fibrotic diseases pose a significant burden on health care, yet the key pathogenic fibroblasts involved remain unclear. We developed the fibrotic disease fibroblast atlas (FDFA), which comprises 394 single-cell and 38 spatial transcriptomic samples from 11 common fibrotic diseases. To perform a cell-type phenotype association study in large-scale heterogeneous datasets, we developed the single-cell phenotype association research kit for large-scale dataset exploration (SPARKLE). SPARKLE handles heterogeneity by incorporating confounding information into its generalized linear mixed models (GLMMs). The application of SPARKLE to FDFA revealed that matrix fibroblasts (MTFs) constitute a crucial pathogenic cell group in fibrosis. Their increased proportion correlate with the fibrotic process. MTFs also synergize with MYO-Fs, increasing their degree of fibrosis. Based on MTF, we identified 25 potential antifibrotic targets for broad-spectrum antifibrotic therapies. This study enhances our understanding of fibrosis and provides a reliable framework for large-scale cell type-phenotype association research. HighlightsO_LIA cross-tissue, multidisease fibrotic disease fibroblast atlas (FDFA) reveals diverse fibroblast subtypes in fibrosis diseases. C_LIO_LIA new toolkit, SPARKLE, is introduced for detecting robust cell type-phenotype associations in large-scale heterogeneous datasets. C_LIO_LIMultiple pathogenic fibroblasts associated with common fibrosis disease (MTF) onset and progression have been identified, suggesting potential cell-specific therapeutic strategies for fibrosis-related diseases. C_LI

bioinformatics↗

Progressively reduced cerebral oxygen metabolism and elevated plasma NfL levels in the zQ175DN mouse model of Huntington disease

Huntingtons disease (HD) is a progressive neurodegenerative disorder caused by a CAG-repeat expansion in exon-1 of the huntingtin gene. Currently, no disease-modifying therapies are available, with a significant challenge in evaluating therapeutic efficacy before clinical symptoms emerge. This highlights the need for early biomarkers and intervention strategies. Therefore, it is essential to develop and characterize accurate mouse models and identify early biomarkers for preclinical therapeutic development. In this study, we characterized the pathological progression of the heterozygous zQ175 neo-deleted knock in (zQ175DN) mouse model across four age groups: 3, 6, 10, and 16 months to identify human translatable outcome measures. T2-relaxation-under-spin-tagging (TRUST) MRI was used to assess global CMRO2, while T2-weighted MRI was used to analyze brain volumes. Significant brain volume loss was detected as early as 6 months of age, worsening progressively with age in the zQ175 DN mice, resembling HD brain volumetric changes. A decline in CMRO2 was observed in 6-month-old zQ175 DN mice, with significant and progressive reductions in 10- and 16-months old HD mice. Additionally, PHP1-positive mutant huntingtin (mHTT) aggregates were present in the striatum of zQ175 DN mice at all four age groups, with intranuclear localization prior to 6 months, transitioning to both intranuclear and neuropil aggregates in older zQ175 DN mice, suggesting that the localization of mHTT aggregates may reflect the severity of HD pathogenesis. Interestingly, plasma neurofilament light chain (NfL) protein concentrations were significantly elevated at 6 months of age and older zQ175DN mice. These findings provide valuable insights for selecting outcome measures in preclinical evaluations of HD therapies using the zQ175 DN mouse model.

neuroscience↗

An innovative approach in identifying a network of priority wetland sites in the East Asian-Australasian Flyway for a new sustainable management investment programme

The East Asian-Australasian Flyway (EAAF) is widely recognised to be the most threatened of the eight flyways in the world, with wetlands rapidly lost due to land cover change, unsustainable use, and the wider impacts of climate change. The recently established Regional Flyway Initiative aims to bring a network of priority wetlands in the EAAF under improved protection, management, and restoration in 10 Asian countries, while mobilising resources for sustainable agriculture, aquaculture, ecotourism, and other livelihoods for local communities. A major step in the development of this initiative is the identification of priority wetland sites through the application of international criteria, based on modern waterbird count data collated from wetland sites across Asia. Through existing analyses and stakeholder consultations, we short-listed 400 internationally important wetlands as candidate sites for further assessment. Count data of EAAF waterbird species was then assessed against international criteria aligned with the Convention on Wetlands (Ramsar Convention), the EAAF Partnerships Flyway Site Network and Important Bird Areas and Biodiversity for each site to iteratively identify a subset of priority sites, drawing on newly available species population thresholds. Each site was scored and ranked using a metric (Prioritisation Criterion1) calculated from the proportions of every occurring EAAF species against published population thresholds. We identified a total of 147 wetland sites of high conservation priority across the 10 countries, thereby representing the full suite of wetland landscapes and habitats in Asia, both freshwater and coastal, all critical sites for the conservation of migratory waterbirds in the flyway. At least 34 threatened species, including significant proportions of their global populations are represented in this network of 147 sites. To ensure that conservation opportunities are maximised for species and ecosystem services, there is a need to ensure that selected sites and landscapes are reconciled with the conservation and development priorities of each country, and to evaluate priority sites for their ecosystem services.

ecology↗

SPINK1-COL18A1 Crosstalk Shapes Epigenome and Drives Cancer Stemness in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a devastating cancer with an increasing incidence and extremely dismal prognosis. Discovery and mechanistic understanding of the genetic and epigenetic drivers of PDAC is therefore of critical importance. Here, we uncover serine protease inhibitor Kazal type 1 (SPINK1) as a putative determinant of clinical progression and demonstrate that it can have a non-canonical function as a regulator of epigenomic states of PDAC cells and associated extensive changes in gene expression. We show that SPINK1 expression, which varies in PDAC, is associated with key aggressive phenotypic cancer states and is correlated with the expression of stemness markers both in vitro and in patient samples. Mechanistically, our results strongly suggest that SPINK1 acts through a new signaling axis, by interacting with COL18A1 in the Golgi apparatus, promoting endostatin release and eventually inducing extensive histone H3 modifications. These results reveal a new function of SPINK1 in PDAC and suggest a potential therapeutic route to combat PDAC aggressiveness by targeting the SPINK1-COL18A1-endostatin signaling.

cancer biology↗

DMBT1 promotes SARS-CoV-2 infection and its SRCR-derived peptide inhibits SARS-CoV-2 infection

DMBT1 is a large scavenger receptor cysteine rich (SRCR) B protein that has been reported as a tumor suppressor gene and a co-receptor for HIV-1 infection. Here we found DMBT1 is a major mucosal protein bound to SARS-CoV-2. Overexpression of DMBT1 in 293T cells enhanced infection by SARS-CoV-2 in ACE2 dependent manner. Blocking experiments using overlapping peptide library of SRCR domain of DMBT1 showed that CQGRVEVLYRGSWGTV peptide, which contains bacteria-binding VEVLXXXXW motif, could inhibit SARS-CoV-2 infection. High concentration of the peptide can significantly inhibit the replication of SARS-CoV-2 in hamsters. Single cell sequencing analysis showed the highest expression abundance of DMBT1 at airway submucosal glands. These results demonstrate that membrane DMBT1 can promote SARS-CoV-2 infection, and serve as a candidate target for antiviral development. Author SummaryWe discovered that a protein named as DMBT1, which is found in our mucous membranes, plays a significant role in SARS-CoV-2 infection. DMBT1 is a large glycoprotein that has previously reported linked to tumor suppression and HIV-1 infection. Our single-cell sequencing analysis revealed that DMBT1 is most abundant in the airway submucosal glands. In our study, we found that when DMBT1 is overexpressed in cells, it enhances SARS-CoV-2 infection. Using a peptide library from DMBT1, we pinpointed a specific peptide, CQGRVEVLYRGSWGTV, which can inhibit SARS-CoV-2 infection. At high concentrations, it significantly reduces the viruss ability to replicate in hamsters. These findings suggest that DMBT1 on the cell membrane can promote SARS-CoV-2 infection and highlight DMBT1 as a potential target for developing antiviral treatments.

microbiology↗

Housekeeping genes are enriched in rheumatoid arthritis-related genes

Housekeeping genes are often considered to be stably expressed in any tissue, cell, or disease state, and the relationship between housekeeping genes and rheumatoid arthritis (RA) has never been systematically analyzed. Therefore we aimed to explore whether housekeeping genes are abnormally expressed in RA by analyzing 15 datasets that were filtered from 140 gene expression profiles. By cumulative hypergeometric test, for 73.3% (11/15) of the datasets, housekeeping genes were significantly (p < 0.05) enriched in differentially expressed genes (DEGs) between RA patients and healthy controls. Using the relative enrichment factor (Re) as an effect size, a Meta-analysis strategy was adopted to integrate the individual results. The logarithmic Re estimation for multiple studies was 0.48 with the 95% confidence interval ranging from 0.17 to 0.80. The combined effect size was significantly higher than that of the randomized case (p = 0.0012) suggesting a consistent result with the hypergeometric test. The robustness of results was verified by sensitivity and subgroup analyses. Furthermore, the expression fluctuation of housekeeping genes was higher in RA patients than healthy controls and the correlation between DNA methylation and gene expression of housekeeping genes was significantly higher than that of non-housekeeping genes, which indicates the potential epigenetic regulation relationship between housekeeping genes and the pathogenesis of RA. This study identified for the first time a significant enrichment of housekeeping genes in DEGs of RA, which might provide new perspectives for understanding the potential role of housekeeping genes in RA.

bioinformatics↗

Highly efficient genome editing in Bacillus subtilis via miniature DNA nucleases IscB.

Existing CRISPR-based genome editing tools are limited in Bacillus subtilis due to the large cas gene. The recently reported DNA nuclease IscB has the potential to be developed into a novel genome editing tool due to its size being one-third of Cas9, while its application in B. subtilis remains unexplored. In this study, genome editing tools pBsuIscB/pBsuenIscB based on IscB and enIscB (enhanced IscB) were established in B. subtilis SCK6, and successfully deleted 0.6 kb to 4.3 kb genes with efficiencies up to 100%. Subsequently, the pBsuenIscB with higher deletion efficiency was used, whereby the large genomic fragment of 37.7 kb or 169.9 kb was deleted with only one {omega}RNA. Additionally, single-copy or multi-copy mCherry genes was integrated by using pBsuenIscB. Finally, the editing plasmid was eliminated and the second round of genome editing was completed. Overall, this study has successfully applied IscB to B.subtilis, expanded the genome editing toolbox of B. subtilis, and will help to construct B. subtilis chassis for production of a variety of biomolecules.

microbiology↗

Old World alphaviruses use distinct mechanisms to infect brain microvascular endothelial cells for neuroinvasion

Several alphaviruses bypass the blood-brain barrier (BBB), causing debilitating or fatal encephalitis. Sindbis virus (SINV) has been extensively studied in vivo to understand alphavirus neuropathogenesis; yet the molecular details of neuroinvasion at the BBB remain poorly understood. We investigated alphavirus-BBB interactions by pairing a physiologically relevant, human pluripotent stem cell derived model of brain microvascular endothelial cells (BMECs) with SINV strains of opposite neuroinvasiveness. Our system demonstrates that SINV neuroinvasion correlates with robust infection of the BBB. Specifically, SINV genetic determinants of neuroinvasion enhance viral entry into BMECs. We also identify solute carrier family 2 member 3 (SLC2A3, also named GLUT3) as a potential BMEC-specific entry factor exploited for neuroinvasion. Strikingly, efficient BBB infection is a conserved phenotype that correlates with the neuroinvasive capacity of several Old World alphaviruses, including chikungunya virus. Here, we reveal BBB infection as a shared pathway for alphavirus neuroinvasion that can be targeted for preventing alphavirus-induced encephalitis.

microbiology↗

Auxin fluctuation and PIN polarization in moss leaf cell reprogramming

Auxin and its PIN-FORMED (PIN) exporters are essential for tissue repair and regeneration in flowering plants. To gain insight into the evolution of this mechanism, we investigated their roles in leaves excised from Physcomitrium patens, a bryophyte known for its remarkable cell reprogramming capacity. We used various approaches to manipulate auxin levels, including exogenous application, pharmacological manipulations, and auxin biosynthesis mutants. We observed no significant effect on the rate of cell reprogramming. Rather, our analysis of auxin dynamics revealed a decrease in auxin levels upon excision, which was followed by a local increase before the reprogramming process began. Mutant analysis revealed that PpPINs are required for effective cell reprogramming, and endogenously expressed PpPINA-GFP accumulates polarly at sites that will develop into future filamentous stem cells. In addition, hyperpolarized PpPINA variants carrying mutated phosphorylation sites showed a marked delay in reprogramming, whereas endogenous or non-polar versions do not have this effect. These results underscore that both, the levels and the polarity of PpPINA are important for efficient cell reprogramming. Overall, these findings highlight the pivotal role of PIN polarity in plant regeneration. Furthermore, they suggest that understanding polarity mechanisms could have broader implications for improving regenerative processes across various plant species.

cell biology↗

A universal single-cell transcriptomics atlas of human lung decodes multiple pulmonary diseases

Human lung is a complex organ susceptible to various diseases. Single-cell transcriptomic studies provide rich data to targeting specific research questions. Here, we present uniLUNG, the largest lung transcriptomic cell atlas, comprising over 10 million cells across 20 disease states and healthy controls. We ensembled a universal hierarchical annotation framework and conducted a full benchmarking of data integration to define a standardized nomenclature and marker genes for lung cell types. Using uniLUNG, we identified Lym-monocyte and T-like B cells, new cell types in specific lung diseases, confirming their existence by comparing with external single-cell atlases. Additionally, we discovered the NSCLC-like SCLC subpopulation, a transitional malignant cell population associated with the transition from NSCLC to SCLC, which was validated and further characterized in spatial dimensions, revealing its complex role in tumour progression. Overall, uniLUNG represents a comprehensive range of human lung cell diversity, providing valuable data resources and a reliable foundation for lung single-cell research. HIGHLIGHTSO_LIThe largest scRNA atlas for human lung covers 10 million cells from 20 lung states. C_LIO_LIA four-level universal cell annotation framework encompasses 120 lung cell types. C_LIO_LIComprehensive benchmarking on 18 strategies guides data integration. C_LIO_LISpecific distribution of Lym-monocytes and T-like B cells in specific lung diseases. C_LIO_LIThe NSCLC-like SCLC subpopulation in transitional events of malignant cells from NSCLC to SCLC. C_LI

bioinformatics↗

CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

Monoclonal antibodies targeting CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients still experience disease relapse, and little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape has been implicated as a mechanism of tumor cell evasion in immunotherapy. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 67 patients at relapse with naivety to anti-CD38 antibodies, and 50 patients collected at relapse following anti-CD38 antibodies. We report a loss of CD38 in 20% (10/50) of patients post-CD38 therapy, three of which exhibited a loss of both copies. Two of these cases showed convergent evolution where distinct subclones independently acquired similar advantageous variants. Functional studies on missense mutations involved in biallelic CD38 events revealed that two variants, L153H and C275Y, decreased binding affinity and antibody-dependent cellular cytotoxicity of the commercial antibodies Daratumumab and Isatuximab. However, a third mutation, R140G, conferred selective resistance to Daratumumab, while retaining sensitivity to Isatuximab. Clinically, patients with MM are often rechallenged with CD38 antibodies following disease progression and these data support a role for next generation sequencing to guide treatment selection.

cancer biology↗

Instantaneous Frequency: A New Functional Biomarker for Dynamic Brain Causal Networks

This study introduces instantaneous frequency (IF) analysis as a novel method for characterizing dynamic brain causal networks from fMRI blood-oxygen-level-dependent (BOLD) signals. Effective connectivity, estimated using dynamic causal modeling (DCM), is analyzed to derive IF sequences, with the average IF across brain regions serving as a potential biomarker for global network oscillatory behavior. Analysis of data from the Alzheimers Disease Neuroimaging Initiative (ADNI), Open Access Series of Imaging Studies (OASIS), and Human Connectome Project (HCP) demonstrates the methods efficacy in distinguishing between clinical and demographic groups, such as cognitive decline stages, sex differences, and sleep quality levels. Statistical analyses reveal significant group differences in IF metrics, highlighting its potential as a sensitive indicator for early diagnosis and monitoring of neurodegenerative and cognitive conditions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/628965v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@10da58org.highwire.dtl.DTLVardef@6eee6borg.highwire.dtl.DTLVardef@e6e756org.highwire.dtl.DTLVardef@15dff2a_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe study introduces instantaneous frequency (IF) as a novel biomarker derived from dynamic brain effective connectivity, capturing temporal fluctuations in brain networks. C_LIO_LIThe proposed IF biomarker effectively differentiates between various clinical stages, such as Mild Cognitive Impairment (MCI) and Alzheimers Disease (AD), and demographic factors, including sex and sleep quality. C_LIO_LIThe robustness and clinical relevance of the IF biomarker are validated using three independent datasets: ADNI, OASIS, and HCP, demonstrating its potential in cognitive and neurological research. C_LI

neuroscience↗

Improving design and normalization of multiplex proteomics study

Advances in multiplex mass spectrometry-based technologies have enabled high-throughput, quantitative proteome profiling of large cohort. However, certain experimental design configurations can amplify sample variability and introduce systematic biases. To address these challenges, we incorporated two novel features in a recent proteogenomic investigation: (1) the inclusion of two reference samples within each mass spectrometry run to serve as internal standards, and (2) the analysis of each specimen as technical replicates across two distinct mass spectrometry runs. Building on these enhancements, we present ProMix, a flexible analytical framework designed to fully leverage these supplementary experimental components. Using both simulated and real-world datasets, we demonstrate the improved performance of ProMix and highlight the advantages conferred by these refined experimental design strategies.

bioinformatics↗

Single-cell analysis reveals multi-faceted features of B cell development together with age-associated B cell subpopulations

The development and maturation of B lymphocytes involve intricate orchestrated processes, where dedicated gene regulations (GR) take place within specific microenvironments shaped by both extracellular matrix and neighboring cells. Despite extensive investigations aimed at deepening our comprehension of these mechanisms, there remains a dearth of high-dimensional and integrated analysis concerning B cell heterogeneity, gene regulation, and external factors implicated in B cell development. In this study, we scrutinized single-cell transcriptomic data and B cell receptor (BCR) sequencing data obtained from B cells and their surrounding counterparts in the bone marrow, tonsil, and peripheral blood. A full picture of the GR dynamics, the heterogeneity of conventional B cells and cell-cell interactions (CCIs) along B cell development axis was depicted. We found immature B cells represent the most quiescent stage characterized by the least number of expressed genes and low RNA velocity. The homeostatic proliferation and activation of naive B cells is niche-confined and individualized, respectively. Two development models for memory B cell subpopulations seem not mutually exclusive and warrant in-depth investigation. Moreover, CCI analysis reveals a pivotal role of myeloid cells and two dominant and stage-dependent CCI categories, TNF and adhesion signaling, in B cell development. Besides, we unexpectedly identified two age-associated B cell subpopulations that respectively express S100A8/S100A9 and C1q and experimentally confirmed the secretion of S100A8/A9 from human B cells in vitro, suggesting a senescence-associated secretion phenotype. Our integrated analysis provides valuable insights into GR dynamics, the evolution of B cells, and potential intercellular communication networks involved in B cell development and revealed novel phenotypes of age-associated B cell aberrance. This study serves as a valuable resource for in-depth exploration of the intricacies of B cell biology.

cell biology↗

FIDDLE: a deep learning method for chemical formulas prediction from tandem mass spectra

Molecular identification through tandem mass spectrometry is fundamental in small molecule analysis, with formula identification serving as an initial step in the process. Current computational methods often struggle with accuracy, speed, and scalability for relatively larger molecules, limiting high-throughput workflows. We present FIDDLE (Formula IDentification by Deep LEarning), a deep learning-based method trained on over 38,000 molecules and 1 million MS/MS spectra from various Quadrupole Time-of-Flight (Q-TOF) and Orbitrap instruments. FIDDLE accelerates formula identification by more than 10-fold and achieves top-1 and top-5 accuracies of 88.3% and 93.6%, respectively, outperforming state-of-the-art methods based on top-down (SIRIUS) and bottom-up (BUDDY) approaches by over 10%. On external metabolomics datasets, FIDDLE achieves top-5 accuracies of 75.1% (positive ion mode) and 66.2% (negative ion mode), with further improvements to 80.0% and 73.8% when combined with SIRIUS and BUDDY.

bioinformatics↗