Biology subjects

Tan, D.

Publications and source records attributed to Tan, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Placental transcriptomics reveals alterations in metabolic and transport gene programs following prenatal cannabis smoke exposure

Background: Prenatal cannabis use is increasing, yet the effects of inhaled cannabis smoke on placental molecular function remain poorly defined. Objective: To characterize placental transcriptomic alterations following prenatal cannabis smoke exposure using a physiologically relevant murine inhalation model. Methods: Timed-pregnant CD-1 mice were exposed to cannabis cigarette smoke or room air from embryonic day (E)6.5 to 18.5. Placentae were collected at E18.5 for microarray-based transcriptomic profiling. Differential gene expression was assessed using fetal sex adjusted linear models and false discovery rate correction. Gene set variation and ranked pathway enrichment were performed to evaluate compartment-associated and biological transcriptional programs. Selected genes were validated by quantitative PCR. Results: Large-scale transcriptomic profiles revealed no clear visual clustering by exposure; however, 23 genes were differentially expressed (FDR <0.05, |log2 fold change| > 0.5). Labyrinth-associated transcriptional signatures were reduced, whereas junctional-associated signatures were increased in exposed placentae. Pathway analyses revealed negative enrichment of fatty acid metabolism, bioenergetic, and transmembrane transport pathways, alongside positive enrichment of RNA processing and transcriptional-regulatory pathways. Quantitative PCR confirmed altered expression of multiple transport-related genes. Electron transport chain-associated gene expression was altered despite preserved placental respiratory measurements. Conclusions: Prenatal cannabis smoke exposure is associated with subtle yet coordinated placental transcriptional alterations involving metabolic, transport-associated, and gene-regulatory pathways, alongside compartment-associated transcriptional shifts. These findings provide insight into placental responses to whole cannabis smoke exposure and identify pathways that may contribute to altered placental function during pregnancy.

physiology↗

bioRxiv2026

Multi-platform reassessment of human mitochondrial DNA methylation reveals signals consistent with technical artifacts

The existence and functional relevance of mitochondrial DNA methylation remain controversial. Here, we systematically profiled cytosine methylation and hydroxymethylation across human brain and blood tissues spanning healthy and malignant states using orthogonal sequencing approaches that avoid chemical conversion during library preparation. While nuclear DNA exhibited canonical methylation patterns, mitochondrial DNA consistently showed negligible signal, indistinguishable from background technical noise. By mapping cytosine-guanine sites between mitochondrial DNA and nuclear-embedded mitochondrial sequences, we demonstrate the potential of these nuclear counterparts to confound not only cytosine methylation but also hydroxymethylation measurements, corroborating and extending prior findings implicating nuclear contamination as a potential source of apparent mitochondrial epigenetic signals. Additional technical factors that inflate apparent mtDNA methylation signals were identified, including sequence context biases, flow cell chemistries, and coverage-dependent discrepancies between the heavy and light strands. Collectively, these results provide convergent evidence against the presence of biologically meaningful cytosine methylation or hydroxymethylation in mitochondrial DNA. These findings caution against interpreting apparent mtDNA methylation signals in human adult tissues as meaningful without rigorous orthogonal validation and comprehensive consideration of technical and analytical confounding factors.

bioinformatics↗

bioRxiv2026

LIME: a fully automated pipeline for high-throughput quantification of leaf lesions

Accurate quantification of leaf lesion severity is essential for plant disease research and phenotyping but is often limited by subjective visual scoring and time-intensive manual image analysis. We present LIME, a fully automated, open-source image analysis pipeline for high-throughput quantification of leaf lesions from disease assay images. LIME integrates zero-shot leaf segmentation using the Segment Anything Model with a convolutional neural network for lesion area estimation. Applied to Arabidopsis thaliana leaves infected with Sclerotinia sclerotiorum, the proposed approach achieved a mean absolute percentage error of 12.9%, comparable to observed intrarater variability in manual scoring. Stratified evaluation across lesion-size groups demonstrated consistent prediction accuracy for small, intermediate, and large lesions, and comparative analysis showed that the deep learning-based model substantially outperformed color-based baseline methods. Under GPU-accelerated execution, LIME processed complete assays containing approximately 200 leaves in 15 minutes, representing an approximate 13-fold reduction in processing time relative to manual annotation. Together, these results indicate that LIME enables objective, reproducible, and scalable quantification of leaf lesion severity in standardized plant pathology assays. The pipeline is released as an open-source tool to support quantitative phenotyping studies.

plant biology↗

bioRxiv2026

CoralBlox: A computationally efficient coral model for decision support

Coral reef management under climate change is challenging due to data sparsity and high uncertainty, yet it is essential for informing conservation strategies. We present CoralBlox, a mechanistic discrete time coral ecology model with the explicit aim of supporting rapid scenario exploration and decision making. The model represents discretized distributions of five coral functional groups across configurable spatial scales while incorporating key ecological processes, including coral growth, reproduction, thermal adaptation, and responses to disturbances. Validation against observed data demonstrates that CoralBlox effectively captures major trends in coral cover dynamics across the Great Barrier Reef, particularly for bleaching-driven mortality and recovery patterns. While simplifying ecological complexities, the model maintains sufficient ecological realism to evaluate and compare the result of distinct management strategies. CoralBlox enables comprehensive assessment of potential management interventions with high computational efficiency and interoperability. The model's flexible architecture makes it extensible to coral ecosystems worldwide, providing valuable exploratory capability for reef management.

ecology↗

bioRxiv2026

MacroH2A-Mediated Gene Repression through Nucleosome Compaction and Remodeling Inhibition

MacroH2A (mH2A) is a histone variant primarily implicated in heterochromatin maintenance and transcriptional repression, yet how its conserved histone-fold and its variant-specific domains reshape chromatin to enforce gene silencing remains poorly understood. Here, we dissect the domain-specific contributions of mH2A to nucleosome dynamics and chromatin remodeling. We show that, in addition to its linker region, the C-terminal tail of mH2A histone-fold also stabilizes nucleosome entry/exit DNA. Cryo-EM analysis reveals that this C-terminus tracks along nucleosomal DNA toward the dyad, adopting an on-dyad binding mode reminiscent of linker histone H1. Additionally, the mH2A linker potently inhibits DNA translocation by both the INO80 and Chd1 chromatin remodelers, while the histone fold selectively suppresses INO80 activity. In contrast, the macro domain has no detectable impact on terminal DNA accessibility or remodeling. Together, our results uncover a previously unappreciated architectural role for the mH2A histone fold and establish the linker domain as a dominant regulator of nucleosome dynamics and chromatin remodeling, providing a mechanistic framework for how mH2A enforces transcriptional repression.

biochemistry↗

bioRxiv2025

Adapting Epigenetic Clocks for Cell-Free DNA High-Throughput Sequencing Data

Background.Circulating cell-free DNA (cfDNA or ccfDNA) methylation sequencing holds promise for developing epigenetic aging clocks in minimally invasive aging assessment applications. However, current clocks--primarily trained on array-based data--do not readily generalize to methylation profiles of cfDNA, due to stochasticity and uncertainty arising from the limited input amounts of cfDNA and technical characteristics of high-throughput sequencing (HTS) platform. Due to lack of training to correct this uncertainty, direct application of legacy clocks to HTS data will inevitably produce unreliable estimates, introduce predictive discordance and undermine the trustworthiness of epigenetic biomarkers. Despite this urgent challenge, a systematic, model-agnostic framework for adapting existing epigenetic clocks to HTS-based cfDNA data remains lacking. Methods.Here, we generated a dedicated benchmark dataset comprising paired cfDNA and genomic DNA (gDNA), which was replicated and profiled across two methylation arrays and two targeted HTS platforms. We evaluated 53 epigenetic clocks for CpG coverage, reproducibility, cross-platform consistency, and age prediction accuracy. Further, we systematically explored and tested multiple adaptation strategies including depth filtering, beta-value imputation, and transfer learning via model distillation aiming at improving performance and clinical concordance of legacy epigenetic clocks on cfDNA HTS datasets. Results.Our results show that inherent technical noise of HTS platforms compromises diagnostic precision, presenting as a significant burden for applying legacy clocks on cfDNA HTS data. However, this technical limitation can be systematically neutralized. By enforcing stringent sequencing depth protocols ([≥]10x ideally 20x), employing robust algorithmic stabilization (L2-heavy clocks and imputation) and transfer learning, we can effectively isolate genuine physiological aging signals from technical artifacts. Ultimately, an adaptation pipeline incorporating all these methods effectively improved age prediction accuracy and, closed the gap between epigenetically induced aging status and clinically assessed realities. Besides, the pipeline demonstrated improved diagnostic sensitivity for neurodegenerative conditions such as amyotrophic lateral sclerosis, establishing a reliable foundation for non-invasive clinical monitoring. Conclusions.This study provided a comprehensive framework and practical guidelines for adapting epigenetic clocks to HTS-based cfDNA data, paved the path for more general application of cfDNA-based aging assessment and liquid biopsies.

bioinformatics↗

bioRxiv2025

Interaction networks within biomolecular condensates feature topological cliques near the interface

Biomolecular condensates, including those formed by prion-like low complexity domains (LCDs) of proteins, are typically maintained by networks of molecular interactions. Such collective interactions give rise to the rich array of material behaviors underlying condensate function. Previous work has uncovered distinct LCD conformations in condensates versus dilute phases, and recently, single-component LCD condensates have been predicted to exhibit microstructures with "small-world" networks--where molecular nodes are highly clustered and connected via short pathlengths. However, a framework linking single-molecule properties, condensate microstructure, and macroscopic material properties remains elusive. Here, we combine molecular simulation and graph-theoretic analysis to reveal how molecular features encode condensate microstructure, which impacts molecule-scale conformations and droplet-scale material properties. Using a residue-resolution coarse-grained model, we probe condensates comprising natural LCD sequences and generalize our findings by varying composition and patterning in binary sequences of hydrophobic and polar residues. We show that non-blocky sequences form condensates with small-world internal networks featuring "hubs"--molecules responsible for global connectivity--and "cliques", molecular clusters bound by persistent short-ranged associations. Cliques localize near interfaces without a secondary phase transition, suggesting a role in mediating molecular partitioning and condensate aging by tuning interfacial material properties. Moreover, we demonstrate that network smallworldness predicts droplet surface tension. We also track single-molecule structure and dynamics inside condensates, revealing that internal heterogeneity at the single-molecule level is systematically encoded by network topology. Collectively, our work establishes multiscale structure-property relationships in LCD condensates, providing general principles for designing and interpreting condensates with complex internal organization and material properties.

biophysics↗

bioRxiv2025

Prediction of small-molecule partitioning into biomolecular condensates from simulation

Predicting small-molecule partitioning into biomolecular condensates is key to developing drugs that selectively target aberrant condensates. However, the molecular mechanisms underlying small-molecule partitioning remain largely unknown. Here, we first exploit atomistic molecular dynamics simulations of model condensates to elucidate physicochemical rules governing small-molecule partitioning. We find that while hydrophobicity is a major determinant, solubility becomes a stronger regulator of partitioning in more polar condensates. Additionally, more polar condensates exhibit selectivity toward certain compounds, suggesting that condensate-specific therapeutics can be engineered. Building on these insights, we develop minimal models (MAPPS) for efficient prediction of small-molecule partitioning into biologically relevant condensates. We demonstrate that this approach reproduces atomistic partition co-efficients in both model systems and condensates composed of the low complexity domain (LCD) of FUS. Applying MAPPS to various LCD-based condensates shows that protein sequence can exert a selective pressure, thereby influencing small-molecule partitioning. Collectively, our findings reveal that partitioning is driven by both small-molecule-protein affinity and the complex interplay between the compounds and the condensate chemical environment.

biophysics↗

bioRxiv2025

The graphene-based affinity cryo-EM grid for the endogenous protein structure determination

Following recent advancements in cryo-electron microscopy (cryo-EM) instrumentation and software algorithms, the next bottleneck in achieving high-resolution cryo-EM structures arises from sample preparation. To overcome this, we developed a graphene-based affinity cryo-EM grid, the Graffendor (GFD) grid, to target low-abundance endogenous protein complexes. To maintain grid quality and consistency within a single batch of 36 grids, we established a one-step crosslinking batch-production method using genetically modified ALFA nanobody as affinity probe (GFD-A grid). Using low concentrations of {beta}-galactosidase-2xALFA, we demonstrated the GFD-A grids efficiency in capturing tagged proteins and resolving its cryo-EM structure at 2.71 [A]. To test its application for endogenous proteins, we engineered yeast cells with a C-terminal tandem affinity tag (3xALFA-Tev-3xFlag: ATF) at Pop6, a shared component of RNase MRP and RNase P. Cryo-EM structures of RNase MRP and RNase P were resolved at 3.3 [A] and 3.0 [A] from cell lysates, and 3.6 [A] and 3.9 [A] from anti-flag elution, respectively. Notably, additional densities were observed in the structures obtained from cell lysates, which were absent in those from the anti-FLAG eluate. These findings establish the GFD-A grid as a robust platform for investigating endogenous proteins, capable of capturing transient interactions and enhancing the resolution of challenging cryo-EM structures with greater efficiency.

biochemistry↗

bioRxiv2025

Hidden in plain sight: Discovery of sand flies in Singapore and description of four species new to science

Phlebotomine sand flies (Diptera: Psychodidae) are small, blood-sucking insects that are of significant public and veterinary health importance for their role in the transmission of Leishmania parasites, bacteria and arboviruses. Although sand flies have been documented in most Southeast Asian countries, there are no published records confirming their presence in Singapore. Here, we provide the first documented evidence on the presence of sand flies in Singapore. Using an integrated taxonomic approach that combines morphological analysis with DNA barcoding of the mitochondrial cytochrome b (cytb) and cytochrome c oxidase subunit I (COI) genes, we identified eight sand fly species, including four newly described species - Phlebotomus seowpohi n. sp., Sergentomyia leechingae n. sp., Sergentomyia gubleri n. sp., and Sergentomyia retrocalcarae n. sp.. Phylogenetic analyses suggest that the new Phlebotomus species, belonging to subgenus Euphlebotomus, is closely related to Phlebotomus argentipes, an important vector of Leishmania donovani from the South Asian region. The discovery of phlebotomine sand flies in Singapore underscores the importance of biosurveillance of biting arthropods. Given Singapores status as a major travel hub, there is a potential risk of leishmaniasis being introduced either by residents returning, or visitors arriving from endemic regions. This risk is compounded by the recent detection of local canine leishmaniasis. Thus, continuous monitoring is essential to assess and manage the risk of disease transmission, support the development of an early warning system, and enable timely and targeted public health interventions. The findings from this study contributes to the global knowledge on sand fly and enhance our understanding of local sand fly diversity and distribution. Author SummaryPhlebotomine sand flies are small, blood-sucking insects recognized as significant vectors for various diseases including leishmaniasis. This study provides the first evidence of their presence in Singapore. Using an integrated taxonomic approach combining morphological analysis with DNA barcoding, we identified eight sand fly species that include four new species: Phlebotomus seowpohi n. sp., Sergentomyia leechingae n. sp., Sergentomyia gubleri n. sp., and Sergentomyia retrocalcarae n. sp. The presence of sand flies in Singapore highlights an important biosurveillance need, as the regions status as a major travel hub increases the risk of leishmaniasis being introduced. Importantly, recent findings of canine leishmaniasis in local dogs amplify the threat of disease transmission. Continuous monitoring and understanding of sand fly diversity and ecology are essential for developing effective public health strategies and early warning systems to manage this risk.

zoology↗

bioRxiv2025

Persistent antigen is essential for sustaining Leishmania-specific memory CD4+ T cells and long-term immunity

Memory T cells are critical for secondary immunity against pathogens, yet their persistence in the absence of antigen remains unclear. While memory CD8+ T cells are known to persist independently of their cognate antigen, the durability of memory CD4+ T cells in the absence of antigen remains controversial. Recovery from cutaneous leishmaniasis confers lifelong immunity, largely mediated by CD4+ T cells, but the necessity of persistent parasites for sustaining this immunity has not been empirically confirmed. We investigated immunity in mice infected with a dihydrofolate reductase-thymidylate synthase (dhfr-ts)-deficient Leishmania major, which cannot persist due to their thymidine salvage deficiency. These mice lost protection against wild-type challenge, correlating with a decline in Leishmania (PEPCK)-specific CD4+ T cells. To further dissect this relationship, we generated PEPCK-specific CD4+ TCR transgenic (PEG) mice, enabling precise tracking of Leishmania-specific memory CD4+ T cells. Both in vitro and in vivo-generated memory PEG cells gradually disappeared over time in the absence of antigen, irrespective of the hosts MHC II status, and this loss paralleled the erosion of infection-induced immunity. PEG and endogenous PEPCK-specific memory cells were not maintained in mice infected with dhfr-ts- or PEPCK-deficient L. major, resulting in loss of recall responses and secondary immunity. These findings demonstrate that continuous antigen presence is crucial for maintaining Leishmania-specific memory CD4+ T cells and highlight the role of persistent antigen in sustaining long-term immunity against chronic infections.

immunology↗

bioRxiv2024

Pyramidal cell types and 5-HT2A receptors are essential for psilocybin's lasting drug action

Psilocybin is a serotonergic psychedelic with therapeutic potential for treating mental illnesses1-4. At the cellular level, psychedelics induce structural neural plasticity5,6, exemplified by the drug-evoked growth and remodeling of dendritic spines in cortical pyramidal cells7-9. A key question is how these cellular modifications map onto cell type-specific circuits to produce psychedelics behavioral actions10. Here, we use in vivo optical imaging, chemogenetic perturbation, and cell type-specific electrophysiology to investigate the impact of psilocybin on the two main types of pyramidal cells in the mouse medial frontal cortex. We find that a single dose of psilocybin increased the density of dendritic spines in both the subcortical-projecting, pyramidal tract (PT) and intratelencephalic (IT) cell types. Behaviorally, silencing the PT neurons eliminates psilocybins ability to ameliorate stress-related phenotypes, whereas silencing IT neurons has no detectable effect. In PT neurons only, psilocybin boosts synaptic calcium transients and elevates firing rates acutely after administration. Targeted knockout of 5-HT2A receptors abolishes psilocybins effects on stress-related behavior and structural plasticity. Collectively these results identify a pyramidal cell type and the 5-HT2A receptor in the medial frontal cortex as playing essential roles for psilocybins long-term drug action.

neuroscience↗

bioRxiv2024

Nitrogen ionome dynamics on leafy vegetables in tropical climate

Nitrogen is known to be a critical macro-nutrient influencing plant physiology, growth, and mineral composition. In tropical conditions, which are challenging for leafy vegetable farming, the nitrogen delivery effect is unclear. In this study, we aimed to investigate the effect of nitrogen application on key physiological traits and the mineral composition of the plants, the plant ionome. Experiments were conducted under tropical conditions greenhouse with varying levels of nitrogen supply to examine the effect on plant transpiration, yield, use efficiency of water and nitrogen, and nutrient uptake dynamics followed by cross-correlation analysis, trying to understand the physiological behavior-uptake dynamics relationships. The results demonstrated that transpiration, yield and WUE theoretic optimum curve, which peaking in nitrogen concentration of 120 mg/L for Chinese spinach and 200 mg/L for Chinese broccoli. Conversely, NUE reduce significantly with increasing nitrogen delivery which reflected on antagonistic increase of excess nitrogen. In terms of mineral composition, nitrogen application resulted in an increase I nitrogen content in the plant leaf tissue, while concentration of certain macronutrients and micronutrients were affected, including potassium, phosphorus, calcium, magnesium, iron, zinc, and molybdenum. Part of the minerals exhibited decreasing pattern due to potential competitive uptake mechanism, iron revealed increasing pattern that correlated with nitrogen delivery, and some minerals correlated with the measured physiological parameters. These results underscore the importance of optimizing nitrogen fertilization to balance plant growth, physiological processes, and plant nutrient homeostasis. The study offers valuable insights for sustainable nitrogen management in agricultural systems aimed at maximizing crop yield while maintaining nutritional quality.

plant biology↗

bioRxiv2024

Caution when using network partners for target identification in drug discovery

Identifying novel, high-yield drug targets is challenging and often results in a high failure rate. However, recent data indicates that leveraging human genetic evidence to identify and validate these targets significantly increases the likelihood of success in drug development. Two recent papers from Open Targets claimed that around half of FDA-approved drugs had targets with direct human genetic evidence. By expanding target identification to include protein network partners--molecules in physical contact--the proportion of drug targets with genetic evidence support increased to two-thirds. However, the efficacy of using these network partners for target identification was not formally tested. To address this, we tested the approach on a list of robust positive control genes. We used the IntAct database to find molecular interacting proteins of genes identified by exome-wide association studies (ExWAS) and genome-wide association studies (GWAS) combined with a locus-to-gene mapping algorithm called the Effector Index (Ei). We assessed how accurately including interacting genes with the ExWAS and Effector Index selected genes identified positive controls, focusing on precision, sensitivity, and specificity. Our results indicated that although molecular interactions led to higher sensitivity in identifying positive control genes, their practical application is limited by low precision. Hence, expanding genetically identified targets to include network partners did not increase the chance of identifying drug targets, suggesting that such results should be interpreted with caution.

pharmacology and toxicology↗

bioRxiv2024

Chalkophore mediated respiratory oxidase flexibility controls M. tuberculosis virulence

Oxidative phosphorylation has emerged as a critical therapeutic vulnerability of M. tuberculosis (Mtb). However, it is unknown how intracellular bacterial pathogens such as Mtb maintain respiration during infection despite the chemical effectors of host immunity. Mtb synthesizes diisonitrile lipopeptides that tightly chelate copper, but the role of these chalkophores in host-pathogen interactions is also unknown. We demonstrate that M. tuberculosis chalkophores maintain the function of the heme-copper bcc:aa3 respiratory supercomplex under copper limitation. Chalkophore deficiency impairs Mtb survival, respiration to oxygen, and ATP production under copper deprivation in culture, effects that are exacerbated by loss of the heme dependent Cytochrome BD respiratory oxidase. Our genetic analyses indicate that maintenance of respiration is the only cellular target of chalkophore mediated copper acquisition. M. tuberculosis lacking chalkophore biosynthesis is attenuated in mice, a phenotype that is also severely exacerbated by loss of the CytBD respiratory oxidase. We find that the host immune pressure that attenuates chalkophore deficient Mtb is independent of adaptive immunity and neutrophils. These data demonstrate that chalkophores counter host inflicted copper deprivation and highlight a multilayered system by which M. tuberculosis maintains respiration during infection.

microbiology↗

bioRxiv2024

A Novel Mouse Model for LAMA2-Related Muscular Dystrophy: Analysis of Molecular Pathogenesis and Clinical Phenotype

Our understanding of the molecular pathogenesis of LAMA2-related muscular dystrophy (LAMA2-MD) requires improving. Here, we report the phenotype, neuropathology and transcriptomics data (scRNA-seq and bulk RNA-seq) of a new Lama2 knockout mouse (dyH/dyH) which was created based on the human LAMA2-MD mutation hotspot region using CRISPR-Cas9. The dyH/dyH mice presented severe phenotype with muscular dystrophy. Mouse brain scRNA-seq showed that Lama2 gene was expressed predominantly and specifically in vascular and leptomeningeal fibroblasts and vascular smooth muscle cells, and weakly in astrocytes in wild-type mouse. Laminin 2 expression on the cortical surface was observed with immunofluorescence. In dyH/dyH, Lama2 expression was decreased in those cell types, which might be associated with the disruption of gliovascular basal lamina assembly. Additionally, transcriptomic investigation of muscles showed 2020 differentially expressed genes, mainly associated with the impaired muscle cytoskeleton and development. In summary, this study provided potentially useful information for understanding the molecular pathogenesis of LAMA2-MD.

neuroscience↗

bioRxiv2023

Structural mechanism of HP1-dependent transcriptional repression and chromatin compaction

Heterochromatin protein 1 (HP1) plays a central role in establishing and maintaining constitutive heterochromatin. However, the mechanisms underlying HP1-nucleosome interactions and their contributions to heterochromatin functions remain elusive. In this study, we employed a multidisciplinary approach to unravel the interactions between human HP1 and nucleosomes. We have elucidated the cryo-EM structure of an HP1 dimer bound to an H2A.Z nucleosome, revealing that the HP1 dimer interfaces with nucleosomes at two distinct sites. The primary binding site is located at the N-terminus of histone H3, specifically at the trimethylated K9 (K9me3) region, while a novel secondary binding site is situated near histone H2B, close to nucleosome superhelical location 4 (SHL4). Our biochemical data further demonstrates that HP1 binding influences the dynamics of DNA on the nucleosome. It promotes DNA unwrapping near the nucleosome entry and exit sites while concurrently restricting DNA accessibility in the vicinity of SHL4. This study offers a model that explains how HP1 functions in heterochromatin maintenance and gene silencing, particularly in the context of H3K9me-dependent mechanisms. Additionally, it sheds light on the H3K9me-independent role of HP1 in responding to DNA damage.

biochemistry↗

bioRxiv2023

Comparing virtual staining artificial intelligence model performance on same-tissue versus serial-tissue sections based on CD3+ T-cell ground truth

Immunophenotyping via multi-marker assays significantly contributes to patient selection, therapeutic monitoring, biomarker discovery, and personalized treatments. Despite its potential, the multiplex immunofluorescence (mIF) technique faces adoption challenges due to technical and financial constraints. Alternatively, hematoxylin and eosin (H&E)-based prediction models of cell phenotypes can provide crucial insights into tumor-immune cell interactions and advance immunotherapy. Current methods mostly rely on manually annotated cell label ground truths, with limitations including high variability and substantial labor costs. To mitigate these issues, researchers are increasingly turning to digitized cell-level data for accurate in-situ cell type prediction. Typically, immunohistochemical (IHC) staining is applied to a tissue section serial to one stained with H&E. However, this method may introduce distortions and tissue section shifts, challenging the assumption of consistent cellular locations. Conversely, mIF overcomes these limitations by allowing for mIF and H&E staining on the same tissue section. Importantly, the multiplexing capability of mIF allows for a thorough analysis of the tumor microenvironment by quantifying multiple cell markers within the same tissue section. In this study, we introduce a Pix2Pix generative adversarial network (P2P-GAN)-based virtual staining model, using CD3+ T-cells in lung cancer as a proof-of-concept. Using an independent CD3 IHC-stained lung cohort, we demonstrate that the model trained with cell label ground-truth from the same tissue section as H&E staining performed significantly better in both CD3+ and CD3- T-cell prediction. Moreover, the model also displayed prognostic significance on a public lung cohort, demonstrating its potential clinical utility. Notably, our proposed P2P-GAN virtual staining model facilitates image-to-image translation, enabling further spatial analysis of the predicted immune cells, deepening our understanding of tumor-immune interactions, and propelling advancements in personalized immunotherapy. This concept holds potential for the prediction of other cell phenotypes, including CD4+, CD8+, and CD20+ cells.

immunology↗