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Zhou, Z.

Publications and source records attributed to Zhou, Z..

At least 37 records · Page 2Linked to original sources

Discovery of a taxusin-mediated route to baccatin III enables its complete biosynthesis in engineered microbes

Taxol (paclitaxel) is a frontline anticancer drug widely applied for the treatment of breast, ovarian and lung cancers. Currently, its supply mainly relies on the semi-synthesis using baccatin III from Taxus plants. Heterologous biosynthesis of baccatin III in microorganisms offers a promising solution to alleviate global Taxol supply shortage, but remains challenging due to pathway complexity. Here, we report a novel taxusin-mediated biosynthetic pathway for baccatin III production via the identification of C13 deacetylase, elucidation of the exact sequence underlying C1 hydroxylation, and stepwise enzymatic functional validation. Through protein engineering of the promiscuous C1 and C5 hydroxylases, coupled with the distribution of pathway modules in Saccharomyces cerevisiae and Escherichia coli, we achieved the de novo biosynthesis of baccatin III. Collectively, our findings remodel the current biosynthetic framework governing the formation of Taxol precursors and highlight the great potential of microbial cell factories for the production of complex plant-derived therapeutic compounds. Highlights* Discovery of C13 deacetylase reveals a novel biosynthetic route to baccatin III via taxusin * Stepwise verification of the complete biosynthetic route to baccatin III through taxusin and baccatin VI * Single-site mutation reversed the product selectivity of T1OH and converted T5OH into a specific taxoid C5 hydroxylase * Complete biosynthesis of baccatin III in engineered microbes

synthetic biology↗

Mesh convergence depends on the element formulation of finite element brain models

Finite element (FE) head models are virtual tools to study brain biomechanics and their predictions must be numerically convergent. Previous convergence studies focused on the influence of mesh size, but the potential effect of element formulation on model convergence was often ignored. To address this, one original model with brain mesh size as 6.4 {+/-} 1.9 mm was modified to generate three derivatives with the same mesh topology but different element sizes, i.e., a coarse model (mesh size: 12.2 {+/-} 3.9 mm), a medium model (mesh size: 3.2 {+/-} 1.0 mm), and a fine model (mesh size: 1.6 {+/-} 0.5 mm). Three commonly used element formulations, i.e., reduced integration, selectively reduced (S/R) integration, and full integration, were implemented to the brain elements. These models were subjected to rotational loadings along the axial, coronal, and sagittal axes, respectively. The maximum relative displacement at representative sites and 95th percentile maximum principal strain at the whole brain level were used to evaluate mesh convergency. The results showed that the S/R integration yielded a 5% difference between the original and medium meshes, while the reduced and full integration revealed a difference over 5% even between the medium and fine meshes. This study verified that the mesh convergence of FE brain models is affected by the choice of element formulation and the S/R integration contributes to the fastest convergence behavior than the reduced and full integrations. It provided practical information on how to develop numerically convergent and computationally efficient FE brain models. HighlightsO_LIThis study verifies that the choice of element formulation affects the mesh convergence behavior of finite element brain models C_LIO_LIThis study finds the selectively reduced integration yields the fastest convergence behavior than the reduced and full integration C_LIO_LIThis study provides practical guidance on the choice of mesh density and element formulation on how to develop numerically convergent and computationally efficient finite element brain models. C_LI

bioengineering↗

Oral Gut Microbial Axis in Inflammatory Bowel Disease and Primary Sclerosing Cholangitis

The oral cavity is increasingly recognized as a reservoir of microbes that can translocate to and influence the gut microbiome. This oral-gut microbial axis may contribute to the pathogenesis of chronic gastrointestinal and hepatobiliary disorders, including inflammatory bowel disease (IBD) and its comorbidity, primary sclerosing cholangitis (PSC). To investigate the oral-gut microbial axis in IBD and PSC, we enrolled 191 participants spanning Crohns disease (CD), ulcerative colitis (UC), CD with PSC (CD-PSC), UC with PSC (UC-PSC), and healthy controls. We generated and analyzed the whole-metagenome shotgun sequencing data from saliva, tongue swabs, and fecal samples. Across oral and gut niches, we identified multiple microbial species differentially enriched in participants with UC compared with healthy controls, including Fusobacterium nucleatum and Gemella sanguinis in saliva, Catonella massiliensis and Tannerella serpentiformis on the tongue, and G. sanguinis and Sellimonas intestinalis in feces. Paired oral-gut analyses revealed 15 potential oral-origin species enriched in fecal samples; notably, G. sanguinis and Veillonella rogosae were consistently enriched in participants with UC. These findings were further supported by an external validation dataset comprising 1,716 gut metagenomes from five independent IBD cohorts, highlighting the reproducibility of oral microbial signatures. In exploratory analyses, smoking history was associated with shifts in the oral microbiome toward a UC-like state in healthy controls, suggesting a possible environmental modifier of the oral-gut microbial axis. Collectively, our study identifies distinct oral microbial signatures and their potential translocation to the gut in IBD and PSC, underscoring the role of the oral- gut microbial axis in disease progression.

microbiology↗

Enhanced BCMA Antigen Density Increases Trogocytosis and Attenuates CAR T cell Function

BackgroundChimeric Antigen Receptor (CAR) T cell therapy targeting B-cell maturation antigen (BCMA) has demonstrated impressive clinical efficacy in relapsed/refractory multiple myeloma (MM). Nonetheless, disease relapse limits durable response for most patients. Trogocytosis of target antigen by effector cells has emerged as a potential contributor to reduced surface antigen density, CAR T cell dysfunction, and fratricide. Although {gamma}-secretase inhibitors (GSI) significantly increase cell surface BCMA density and decrease soluble BCMA (sBCMA), their effects on BCMA trogocytosis and the resulting impact on CAR T-cell function remain incompletely understood. MethodsWe investigated the effects of GSI on BCMA-directed CAR T cell function and trogocytosis using in vitro co-culture systems with MM cell lines across a spectrum of BCMA expression. We validated findings using confocal microscopy and cytotoxicity assays. Trogocytosis and fratricide were assessed in time-resolved functional studies. Phenotypic and functional differences between trogocytosis-positive (CAR T Trogo+) and trogocytosis-negative (CAR T) cells were evaluated using multiparametric flow cytometry, proteomic profiling, single-cell RNA sequencing (scRNA-seq), T-cell receptor (TCR) sequencing, and in vitro rechallenge assays. We also interrogated clinical samples from two Phase I trials (NCT03338972 and NCT03502577) which employed the identical CAR T cell construct with or without GSI respectively, to evaluate the relationship between trogocytosis, CAR T cell persistence, and treatment outcome. ResultsGSI driven increases in BCMA density on MM cell lines enhanced CAR T cell cytotoxicity but concomitantly increased trogocytosis, particularly in high-antigen-density cell lines-(H929+GSI vs H929; 30 min (P<0.0001), 1 h (P<0.0001), 2 h (P<0.0001), 6 h (P<0.0001), and 24 h (P<0.0001) and in CD4 CAR T cells (K562mCherry+GSI, CD4 vs CD8 CAR T cells;10 min (P=0.01), 2 h (P=0.01), and 6 h (P=0.004). Following BCMA acquisition, CAR T cells (CAR T Trogo) exhibited reduced proliferative capacity, diminished cytotoxic function (CAR T Trogo+ vs CAR T; (P=0.01), and an increase in markers of exhaustion/activation (CD4+ CAR T Trogo+ vs CD4 CAR T and CD8+ CAR T Trogo+ vs CAR T; PD-1+LAG-3+, PD-1+TIM-3+, and TOX+TIM-3 co-expression, (P=0.007, P<0.0001, P=0.006 and P=0.004, P=0.03, P=0.006). In fratricide assays, CAR T Trogo cells were susceptible to killing by naive CAR T cells. Single cell RNA-seq supports the phenotypic findings revealing transcriptional features of heightened activation and accelerated exhaustion in CAR T Trogo+ cells. Clinical phase I trial data confirm BCMA trogocytosis in patient samples. ConclusionsOur findings highlight the paradoxical effects of increased BCMA density on BCMA CAR T cell therapy: enhancement of initial tumor targeting and promotion of trogocytosis-associated dysfunction. Trogocytosis may contribute to antigen modulation, CAR T cell exhaustion, and fratricide, potentially muting the therapeutic benefits of enhanced antigen density. To optimize GSI and mitigate trogocytosis-associated resistance mechanism, future clinical trial designs should incorporate early time-point sampling, a sample size providing sufficient statistical power to determine an impact on CAR T cell persistence and treatment response, and mechanistic assessments.

cancer biology↗

Selenium-enriched rapeseed extract synergizes with chemotherapy drug cisplatin in inhibiting proliferation and promoting apoptosis of colorectal cancer cells

Chemotherapy treatment of colorectal cancers (CRC) using cisplatin (CDDP) encounters problems of drug resistance by the cancer cells and cytotoxicity to normal cells, highlighting the urgent need for joint therapeutical strategies. Selenium-enriched rapeseed extracts exhibit anti-cancer effects but the bioactive components and mechanisms remain unclear. Here, we applied different solvents to fractionate the extracts from Selenium-enriched rapeseed and found that the water extract (WE) fraction significantly enhanced the cytotoxic effect of CDDP on cancer cells but no damage on normal cells. HPLC-ICP-MS analysis revealed that methylselenocysteine (MSC) and selenocystine (SeCys2) were the main selenium speciation in WE. Through cell biology and integrative multi-omics analysis, we found a synergistic anti-CRC cell effect when combining CDDP with MSC, sulforaphane (SFN), celastrol (Cel), Indole-3-carbinol (I3C), -linolenic acid (ALA) or linoleic acid (LA). We propose that the CDDP-WE combination treatment holds the promise for improving curative efficacy for chemo-refractory CRC patients in the future.

cancer biology↗

PFOS aggravates atherosclerosis via Bacteroides caecimuris expansion-driven bile acid remodeling and subsequent intestinal FXR-TLR3 signaling cascade

BACKGROUNDPerfluorooctane sulfonate (PFOS) is a widely distributed persistent organic pollutant in the environment and has been associated with an increased risk of atherosclerosis. However, the underlying pathogenic mechanisms remain largely unclear. This study aimed to investigate the effects of PFOS on atherosclerosis and its associated gut-vascular axis. METHODSPseudo-germ-free mouse models and fecal microbiota transplantation (FMT) were used to determine the role of the gut microbiota in PFOS-induced atherosclerosis. Metagenomic sequencing was performed to characterize alterations in gut microbial composition following PFOS exposure, and targeted metabolomics was used to assess bile acid profiles in the ileum and plasma. Transcriptomic analysis of Bacteroides caecimuris (B.caecimuris) was conducted to explore the reasons for the increased abundance of B.caecimuris after PFOS exposure. In addition, intestinal transcriptomics and ChIP-qPCR were performed to validate transcriptional regulation within the FXR-TLR3 signaling axis. RESULTSAmong 127 participants with paired serum and fecal samples, including 82 patients undergoing coronary angiography with Gensini scores (GS score), fecal PFOS levels were significantly associated with lipid profiles and GS score, whereas serum PFOS showed no such association.Mechanistically, PFOS exposure promotes intestinal enrichment of B.caecimuris by upregulating its tolC gene, thereby enhancing efflux capacity.This microbial shift was accompanied by reduced levels of tauro-ursodeoxycholic acid (TUDCA) and aberrant activation of intestinal FXR signaling.Further analyses demonstrated that FXR activation upregulated TLR3 expression and promoted inflammatory responses and atherosclerosis progression via the TLR3-NF-{kappa}B signaling axis. Both intestinal epithelial-specific FXR deficiency (Fxr{Delta}IE) and TUDCA supplementation significantly suppressed pathway activation and alleviated disease phenotypes.Functional experiments identified TLR3 as a key downstream effector of FXR. Overexpression of TLR3 abolished the protective effects observed in Fxr{Delta}IE mice. Moreover, pharmacological inhibition of TLR3 using CU CPT-4a significantly improved established atherosclerotic lesions in vivo. CONCLUSIONSThis study identifies a gut microbiota-driven FXR-TLR3 signaling axis that mediates PFOS-induced atherosclerosis. These findings provide new mechanistic insights into environmentally induced cardiovascular disease and suggest potential targets for risk assessment and therapeutic intervention.

pathology↗

Designing Fidelity of CRISPR-Cas Endonucleases by Kinetic Insights

Finding high-fidelity CRISPR-Cas variants is critical for both the precision of in vitro DNA detection and the safety of in vivo gene-editing therapeutics. However, the large size of the Cas enzyme and the distinct selection criteria between its natural evolution and clinical practice lead to extensive experimental trials and limited success rate for de novo design, directed evolution, protein language model (PLM)-based filtering. Here, we present a PLM-assisted physics-driven approach that utilizes atomistic molecular dynamics simulations and automated path searching to efficiently obtain the complete kinetic insights, including the transition state structures, for the conformational changes of Cas before DNA cleavage. We show that these kinetic insights can pinpoint a few fidelity-diminishing protein residues during the early stage of target recognition, and have led to SpyCas9 and FnCas12a variants with ultra-high fidelity surpassing previously reported counterparts at minimal cost of a few wet-lab trials.

biophysics↗

Preserved Barrier Integrity and Altered Immune Profiles in Chronic Cannabis Users: Potential Roles of Δ9-Tetrahydrocannabinol

Although cannabinoids such as delta-9-tetrahydrocannabinol (THC) are generally immunosuppressive in preclinical models, chronic cannabis use in humans is paradoxically associated with increased infection risk and systemic inflammation. In this study, we demonstrate that THC directly strengthens intestinal epithelial barrier function in vitro by increasing trans-epithelial electrical resistance in a concentration-dependent manner in Caco-2 monolayers. In a cross-sectional study of chronic cannabis users via smoking or snorting compared with non-using controls, plasma lipopolysaccharide (LPS), and microbial translocation-driven inflammatory cytokines (IL-23, MCP-1, IL-8) were significantly reduced, while some cytokines (IL-6, IL-1{beta}, TNF-, IL-10) remained unchanged. Concurrently, users exhibited elevated macrophage-derived chemokine (MDC) and homeostatic cytokines IL-15 and IL-21, markedly suppressed IL-7 and IL-4. Plasma IL-15 and MDC levels correlated with consumption intensity, and IL-23, IL-7, and IP-10 correlated with age of first use or during heaviest use. These findings suggest that habitual cannabis use may protect gut barrier integrity and reduce microbial translocation and associated inflammation, while simultaneously disrupting systemic immune homeostasis through selective cytokine dysregulation. This dual, dose-dependent immunomodulatory profile highlights the complex balance between potential benefits and risks in both recreational and therapeutic cannabis use.

immunology↗

Family Conflict and Parent-Child Similarity in Affective Valuation

How children come to evaluate social-affective cues is shaped within the family, yet the neural expression of this process and its dependence on family relationships remain unclear. We tested whether parent-child similarity in the neural coding of affective judgment varies with family environment, and whether it relates to youth affective distress. Twenty-five parent-child dyads (youth, mean age 11.8; parents mean age 42 years) judged faces morphed along an angry-to-happy continuum as positive or negative during fMRI. For each participant, we defined an evaluative choice axis distinguishing faces judged positive from negative, independent of expression intensity. Using searchlight-based parent-child cross-decoding, we tested whether one dyad members evaluative coding predicted the other members judgments, indexing shared evaluative coding rather than shared sensitivity to expression intensity. Inference focused a priori on medial prefrontal cortex. There was no reliable average parent-child neural similarity across the sample. Instead, higher family conflict was associated with lower parent-child neural similarity in ventromedial prefrontal cortex (vmPFC). Demonstrating specificity to negative relational strain, this effect was not observed for complementary dimensions of family cohesion or identity. Moreover, the effect was specific to true dyads rather than random pairings and to vmPFC rather than a face-selective network or other medial prefrontal regions. Lower vmPFC similarity showed a preliminary association with higher youth affective distress. These findings indicate that affective valuation, rather than sensory encoding, may be a representational level at which perceived family conflict is reflected in parent-child neural similarity.

neuroscience↗

The peculiar property of pia mater on the prediction of acute subdural hematoma

Acute subdural hematoma (ASDH) is a prevalent injury with high mortality and morbidity, often resulting from bridging vein (BV) disruption secondary to cortical relative motion. As a thin membrane enveloping the brain surface and anchoring BVs, the pia mater is hypothesized to play a critical mechanical role in cortical response and hence ASDH pathogenesis. Finite element (FE) head models are valuable tools to predict ASDH occurrence during impacts. However, the pia mater is often represented as an elastic material in existing FE head models, despite experimental evidence reporting its nonlinear mechanical behavior. In this study, both linear (Youngs modulus of 11.5 MPa) and nonlinear (the stress-strain curve derived from pial tension tests) material models of the pia mater were implemented in one FE head model. The models were subjected to three experimental impact loadings, one of which was known to cause ASDH and two of which were not. Results demonstrated that, across all simulated impacts, the model with nonlinear pia mater properties predicted larger cortical displacements and BV responses than the linear model. For the impact with known ASDH occurrence, the predicted BV strain was 0.17 for the nonlinear model and 0.094 for the linear model, with only the former approaching the reported rupture strain range of the BV-superior sagittal sinus complex (0.29 {+/-} 0.13). These findings verified the mechanical importance of the pia mater in cortical responses and hence the prediction of ASDH, suggesting that conventional linear pia modeling might over-constrain cortical motion, leading to underestimation of BV strain and ASDH risk. The current study supported the adoption of experimentally derived nonlinear pia mater properties in FE head models to improve the reliability of ASDH prediction.

biophysics↗

Mesothelial Plasticity Specifies a Pleural Immune Circuit that Orchestrates Lung Regeneration

Following injury, predisposition towards regenerative repair and away from degenerative remodeling is central to organismal health, yet the upstream determinants that instruct this fate choice remain poorly understood. Here, we identify mesothelial cell plasticity as a central determinant between regeneration and degeneration by comparing mouse models of pneumonectomy (PNX) versus chronic lung allograft dysfunction (CLAD). While mesothelial cells expand in both settings, following PNX, these cells undergo differentiation through multiple transitional states, culminating in an inflammatory population that orchestrates monocyte recruitment and subsequent tissue regeneration. In contrast, in CLAD, mesothelial cells enrich in an extracellular matrix-enriched state that lacks pro-regenerative signaling capacity. Using single cell epigenomic profiling and in vivo genetics, we define a mesothelium-specific TWIST1-CCL2 axis that governs mesothelium plasticity and signaling, monocyte recruitment and lung regrowth. Together, these findings demonstrate that context-dependent reprogramming of a pleural population, known to protect organs, can be leveraged to drive regeneration.

Developmental Biology↗

Computational reconstruction of hierarchical cis-regulatory networks reveals synergistic transcription control and disease-associated rewiring

Gene regulation emerges from coordinated interactions among dispersed cis-regulatory elements, yet how these elements integrate into functional regulatory networks and collectively regulate gene transcription remains poorly understood. Here, we present ORIGAMI, a multi-omics, gene-centric deep learning framework that reconstructs functional cis-regulatory networks constrained by transcriptional output. ORIGAMI formulates cis-regulatory modeling as a latent graph inference task, which integrates DNA sequence, epigenomic signals, and three-dimensional chromatin priors to infer denoised regulatory graphs that capture functional interactions rather than structural proximity alone. The inferred regulatory graphs exhibit distinct topological regimes, where hierarchical and modular organization encodes cell-state-specific functional demands and enables synergistic transcriptional control. Furthermore, we show that these regulatory architectures undergo measurable state-dependent rewiring across disease contexts. Finally, ORIGAMI accurately predicts the transcriptional consequences of both cis- and trans-regulatory perturbations and links the rearrangement of regulatory architecture to perturbation response. Together, ORIGAMI advances a network-based view of gene regulation and establishes a foundation for virtual cell modeling of regulatory dynamics.

bioinformatics↗

Complete elucidation and heterologous reconstruction of the biosynthetic pathway of camptothecin

Camptothecin derivatives are first-line anticancer drugs used worldwide for the treatment of diverse malignant tumors. However, the biosynthetic pathway of camptothecin has remained elusive for five decades. Here, we fully map its entire biosynthetic route. We discovered five key missing enzymes (OpCAR, OpSDR11, OpCS, OpGH1, and OpSTR) via the combination of MALDI mass spectrometry imaging, single-cell RNA sequencing and co-expression analysis. Meanwhile, we demonstrated a free flavin mononucleotide triggered the non-enzymatic 6-5-6 to 6-6-5 fused-ring skeleton rearrangement, filling the last gap in camptothecin biosynthesis. Finally, we validated this identified pathway and achieved the de novo biosynthesis of camptothecin in Saccharomyces cerevisiae. These discoveries uncover the long-standing mystery underlying camptothecin and pave the way for manufacturing camptothecin and its derivatives through synthetic biology approaches.

synthetic biology↗

Scout-based Multi-Echo NAvigator (SMENA) for high temporal resolution motion and B0 estimation and correction: applications to multi-echo GRE and EPTI

PurposeTo develop a data-driven technique, Scout-based Multi-Echo NAvigator (SMENA), for joint estimation of motion and B0 inhomogeneity ({delta}B0) at a temporal resolution of [~]200 ms with minimal additional scan time for gradient-echo acquisition. MethodsSMENA consists of two key acquisition components: SMENA-scout and SMENA-nav. SMENA-scout is a rapid 3D 4-mm multi-echo acquisition completed in less than 8 seconds, providing images with matched contrast and phase at multiple echo times. SMENA-nav captures signal variations induced by motion and{delta} B0 during the scan using compact multi-echo navigator trajectories (3.5 ms) embedded within each TR. Motion and{delta} B0 maps were jointly estimated every [~]200 ms through a model-based optimization framework relating SMENA-scout to SMENA-nav. The estimation accuracy and correction performance of SMENA were evaluated in simulations and in vivo using multi-echo GRE and GRE-EPTI acquisitions. Multiple prospective motion experiments, including large continuous movement and deep breathing, were investigated. ResultsIn both simulations and in vivo experiments, accurate motion and{delta} B0 estimation were achieved. Compared with motion-only estimation, joint estimation reduced rotation and translation errors. Joint motion and{delta} B0 correction resulted in substantial improvements in image quality, particularly at longer echo times, producing an NRMSE of 10.4% compared to 31.6% with motion-only correction. High-temporal-resolution tracking of motion and{delta} B0 enabled improved reconstruction quality in scenarios involving continuous motion and deep breathing. ConclusionSMENA enables high-temporal-resolution joint estimation of motion and{delta} B0 with minimal additional acquisition cost, providing a practical solution for motion- and{delta} B0-robust MRI.

neuroscience↗

Sequence-encoded H2A.Z nucleosome dynamics control DNA unwrapping and SUV420H1 recognition

H2A.Z and canonical H2A adopt nearly identical nucleosomal folds, yet their distinct chromatin functions are not captured by static structural analysis. Using fast magic-angle spinning 1H-detected solid-state NMR, we show that H2A.Z possesses enhanced backbone flexibility in the L1 loop and the 2-L2 region (M2) relative to H2A. Chimeric segment-swapping demonstrates that these dynamic signatures are locally sequence-encoded and functionally transplantable. The inherent mobility of the M2 region promotes nucleosomal DNA-end unwrapping and persists when DNA ends are stabilized by linker histone H1 or opened by SUV420H1, indicating that this mobility is intrinsic rather than a passive consequence of DNA detachment. Chemical shift perturbation mapping and catalytic assays further show that SUV420H1 reads this H2A.Z-specific conformational landscape: the M2 region, together with the H2A.Z DS motif, supports variant-selective methyltransferase activity. These findings establish an axis of sequence-dynamics-accessibility-recognition along which local backbone fluctuations serve as physical determinants of epigenetic enzyme specificity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/731474v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@a50ceforg.highwire.dtl.DTLVardef@1f43af0org.highwire.dtl.DTLVardef@14969b8org.highwire.dtl.DTLVardef@bbbe0d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

CLASPP: A unified model for predicting post-translational modifications

Post-Translational Modifications (PTMs) are a fundamental mechanism for regulating cellular pathways and increasing the functional diversity of the proteome. Accurately predicting the PTM types that are likely to occur at a given site in the primary sequence is a key challenge in functional proteomics. Existing PTM prediction models predominantly focus on either single PTM types or employ ensemble methods that combine multiple models to predict different PTM types. This fragmentation is largely driven by the vast imbalance in data availability across PTM types, making it difficult to predict multiple PTM types with a single model. To address this limitation, we present the Contrastively Learned Attention-based Stratified PTM Predictor (CLASPP), a unified PTM prediction model. CLASPP addresses imbalance challenges by leveraging unsupervised clustering-based undersampling and a novel contrastive learning framework tailored to PTM data. Additionally, our hierarchical data organization and curation are shown to improve CLASPPs performance by balancing the representation of individual PTM types and provides a standardized dataset to train and validate future model designs. Drawing inspiration from advancements in image and natural language processing, the CLASPP model employs a multi-stage training strategy and a high-quality, curated training dataset to improve PTM prediction performance. To uncover what is learned during the contrastive learning stage, the CLASPP model is shown to distinguish known protein kinase substrate specificity profiles as a form of explainability. Finally, we evaluate the application of CLASPP in predicting PTMs in different model organisms and experimentally validated ubiquitination sites in the understudied DCLK3 kinase. Overall, CLASPP represents a unified model for PTM prediction that addresses key bottlenecks in data imbalance and offers new strategies for biological data curation, thereby improving PTM-type prediction performance across diverse organisms. Author summaryPost-translational modifications (PTMs) are essential changes that proteins undergo, influencing nearly every aspect of cell function, communication, and disease. Accurately predicting where and how these modifications occur is challenging due to the diversity of PTM types and the limitations of existing annotation pipelines. This study introduces a unified deep learning approach, termed CLASPP, leveraging contrastive learning to predict multiple PTM types simultaneously from primary protein sequence alone. By employing advanced data balancing and sampling methods, CLASPP ensures reliable predictions for rare and common modifications. The model utilizes a pre-trained protein language model to capture sequence and structural features encoded in the primary protein sequence. Test results demonstrate that CLASPP consistently surpasses existing tools in predicting 12 major PTM types, and its versatility enables robust predictions across species, not just in human proteins. The final model, data curation, and training datasets are freely accessible for broader use and reproducibility (https://github.com/gravelCompBio/Claspp_forward).

bioinformatics↗

Assessing and Optimizing Low-Frequency Somatic Mutation Detection: A Multi-Platform High-Throughput Sequencing Perspective

The availability of multiple commercial short-read sequencing platforms necessitates systematic cross-platform performance comparisons, particularly for challenging applications such as low-frequency somatic mutation detection. Here, a large-scale targeted sequencing dataset from five Genome in a Bottle (GIAB) human genomic DNA reference standards, HG001 to HG005, alongside Twist Biosciences cfDNA reference standards featuring 1% variant allele frequency (VAF), was generated by six platforms (NovaSeq 6000, NovaSeq X, FASTASeq 300, GenoLab M, SURFSeq 5000, and MGISEQ-T7). To build a realistic benchmark while keeping authentic sequencing backgrounds, we developed PosMix, a simulating tool that generates position-specific VAFs. To overcome the limitations of conventional variant callers (high recall with poor precision for VarScan2, higher precision with lower recall for Strelka2/Mutect2), we developed SomaticXGB, a machine learning-based caller. In this study, SURFSeq 5000 consistently exhibited the lowest error rates and achieved superior accuracy for VAFs as low as 0.5%, outperforming all other sequencing platforms. On the other hand, SomaticXGB attained F1 scores of approximately 0.92 on simulated datasets with VAFs ranging from 0.5% to 1.5% and 0.89 on Twist 1% standards, substantially outperforming conventional methods. This work delivers a valuable rich multi-platform data resource, offering a standardized pipeline for performance benchmarking and a machine learning-based strategy for optimized somatic mutation detection.

bioinformatics↗

Alveolar Epithelial Cell Loss of the Mitochondrial Regulator TFAM Drives Progressive Lung Fibrosis

Idiopathic pulmonary fibrosis (IPF) is characterized by failed alveolar epithelial repair and progressive fibrotic remodeling. Although aberrant reprogramming of alveolar type 2 (AT2) cells and accumulation of transitional AT2 states are increasing recognized as central features of IPF, the epithelial-intrinsic mechanisms that initiate these pathogenic states remain incompletely understood. Here, we identify mitochondrial transcription factor A (TFAM), a regulator of mitochondrial DNA maintenance, as a critical regulator of AT2 cell homeostasis. TFAM expression was reduced in AT2 cells from human IPF lungs. Inducible AT2 cell-specific Tfam deletion in mice caused spontaneous fibrotic remodeling and increased susceptibility to bleomycin-induced lung injury. TFAM-deficient AT2 cells acquired KRT8+ transitional and p21+ senescence-associated features before the onset of fibrotic transformation, accompanied by impaired oxidative phosphorylation, redox imbalance, mitochondrial superoxide accumulation, repression of mtDNA-encoded respiratory genes, and disrupted mitochondrial ultrastructure. TFAM-deficient AT2 cells developed a profibrotic secretory program that promoted extracellular matrix deposition and fibroblast activation. We further identified insulin-like growth factor-binding protein 2 (IGFBP2) as a secreted mediator induced in TFAM-deficient AT2 cells. IGFBP2 was elevated in AT2 cells in human IPF lung tissue and bronchoalveolar lavage fluid (BALF) from patients with IPF. IGFBP2 was detected in supernatants from fibrotic human precision-cut lung slices (hPCLS). IGFBP2 neutralization attenuated profibrotic remodeling in fibrotic hPCLS. Collectively, our findings identify TFAM-dependent mitochondrial homeostasis as an epithelial checkpoint linking AT2 cell-state stability to impaired epithelial-mesenchymal crosstalk driving pulmonary fibrosis.

pathology↗