Biology subjects

Tan, Y.

Publications and source records attributed to Tan, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Netrin G1 Ligand is a new stromal immunomodulator that promotes pancreatic cancer

Understanding pancreatic cancer biology is fundamental for identifying new targets and for developing more effective therapies. In particular, the contribution of the stromal microenvironment to pancreatic cancer tumorigenesis requires further exploration. Here, we report the stromal roles of the synaptic protein Netrin G1 Ligand (NGL-1) in pancreatic cancer, uncovering its pro-tumor functions in cancer-associated fibroblasts and in immune cells. We observed that the stromal expression of NGL-1 inversely correlated with patients overall survival. Moreover, germline knockout (KO) mice for NGL-1 presented decreased tumor burden, with a microenvironment that is less supportive of tumor growth. Of note, tumors from NGL-1 KO mice produced less immunosuppressive cytokines and displayed an increased percentage of CD8+ T cells than those from control mice, while preserving the physical structure of the tumor microenvironment. These effects were shown to be mediated by NGL-1 in both immune cells and in the local stroma, in a TGF-{beta}-dependent manner. While myeloid cells lacking NGL-1 decreased the production of immunosuppressive cytokines, NGL-1 KO T cells showed increased proliferation rates and overall polyfunctionality compared to control T cells. CAFs lacking NGL-1 were less immunosuppressive than controls, with overall decreased production of pro-tumor cytokines and compromised ability to inhibit CD8+ T cells activation. Mechanistically, these CAFs downregulated components of the TGF-{beta} pathway, AP-1 and NFAT transcription factor families, resulting in a less tumor-supportive phenotype. Finally, targeting NGL-1 genetically or using a functionally antagonistic small peptide phenocopied the effects of chemotherapy, while modulating the immunosuppressive tumor microenvironment (TME), rather than eliminating it. We propose NGL-1 as a new local stroma and immunomodulatory molecule, with pro-tumor roles in pancreatic cancer. Statement of SignificanceHere we uncovered the pro-tumor roles of the synaptic protein NGL-1 in the tumor microenvironment of pancreatic cancer, defining a new target that simultaneously modulates tumor cell, fibroblast, and immune cell functions. This study reports a new pathway where NGL-1 controls TGF-{beta}, AP-1 transcription factor members and NFAT1, modulating the immunosuppressive microenvironment in pancreatic cancer. Our findings highlight NGL-1 as a new stromal immunomodulator in pancreatic cancer.

cancer biology↗

bioRxiv2024

Tracing Homopolymers in Oikopleura dioica's mitogenome

Oikopleura dioica is a planktonic tunicate (Appendicularia class) found extensively across the marine waters of the globe. The genome of a single male individual collected from Okinawa, Japan was sequenced using the single-molecule PacBio Hi-Fi method and assembled with NOVOLoci. The mitogenome is 39,268 bp long, featuring a large control region of around 22,000 bp. We annotated the proteins atp6, cob, cox1, cox2, cox3, nad1, nad4 and nad5, and found one more open reading frame that did not match any known gene. This study marks the first complete mitogenome assembly for an appendicularian, and reveals that A and T homopolymers cumulatively account for nearly half of its length. This reference sequence will be an asset for environmental DNA and phylogenetic studies. http://dx.doi.org/10.1364/ao.XX.XXXXXX

genomics↗

bioRxiv2024

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy, have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA-seq datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

bioinformatics↗

bioRxiv2024

Flat-field superresolution structured illumination microscopy with joint temporal-spatial light modulation

AbstractSuper-resolution structured illumination microscope (SR-SIM) has been established as a powerful tool for visualizing subcellular dynamics and studying organelle interactions in live cells. However, the interfering Gaussian beams result in a limited and nonuniform field of view (FOV) which hinders its application for large whole-cell dynamics and pathological sample imaging. Here, we proposed a joint spatial-temporal light modulation (JSTLM) method to reshape the excitation light field into flat-field structured illumination without disturbing the interfering fringes. Our flat-field structured illumination microscopy (flat-field SIM) improves the uniformity across the whole FOV significantly, hence enabling SR image stitching. Skeleton dynamics and vesicle transportation in and between whole cells were visualized by flat-field SIM. With the stitching of multi-FOV flat-field SIM images, millimeter-sized SR images can be obtained which provides the possibility for cell heterogeneity studies and pathological diagnoses. The JSTLM method can be further incorporated with regions of interest to reduce unnecessary photodamage to live cells during multicolor imaging. ContributionsY.L. and X.H.C. conceived and designed the idea. Y.L., S.M.L., X.J., and G.W. built the SIM setup. Y.L. performed the data acquisitions. Y.L. and X.H.C. conducted the optical wave simulation. J.Z. prepared the cell samples. Y.T. and L.B.W. performed the image analyses. Y.L. prepared the illustrations. X.H.C. and J.G. supervised the project. Y.L. and H.L. wrote the manuscript.

cell biology↗

bioRxiv2024

DeProt: A protein language model with quantizied structure and disentangled attention

Protein language models (PLMs) have shown remarkable capabilities in various protein function prediction tasks. However, while protein function is intricately tied to structure, most existing PLMs do not incorporate protein structure information. To address this issue, we introduce ProSST, a Transformer-based protein language model that seamlessly integrates both protein sequences and structures. ProSST incorporates a structure quantization module and a Transformer architecture with disentangled attention. The structure quantization module translates a 3D protein structure into a sequence of discrete tokens by first serializing the protein structure into residue-level local structures and then embeds them into dense vector space. These vectors are then quantized into discrete structure tokens by a pre-trained clustering model. These tokens serve as an effective protein structure representation. Furthermore, ProSST explicitly learns the relationship between protein residue token sequences and structure token sequences through the sequence-structure disentangled attention. We pre-train ProSST on millions of protein structures using a masked language model objective, enabling it to learn comprehensive contextual representations of proteins. To evaluate the proposed ProSST, we conduct extensive experiments on the zero-shot mutation effect prediction and several supervised downstream tasks, where ProSST achieves the state-of-the-art performance among all baselines. Our code and pretrained models are publicly available 2.

bioinformatics↗

bioRxiv2024

Caspase-8-mediated CYLD cleavage boots LPS-induced endotoxic shock.

Caspase-8, a pivotal protease intricately involved in various cellular signaling pathways related to cell death and inflammation, has been identified as a contributor to cytokine production during septic shock. However, the mechanisms governing this regulatory role remain enigmatic. In this study, we uncovered that mice harboring a specific mutation in CYLD at its D215 position (CyldD215A/D215A mutant mice), rendering CYLD resistant to caspase8 cleavage, exhibited marked protection against lethal endotoxic shock. Moreover, the removal of Cyld in Caspase8-/-Mlkl-/- mice restored their sensitivity to endotoxic shock, indicating Caspase8 promotes LPS-induced endotoxic shock by cleaving its substrate CYLD and maintaining CYLD stability confers resistance to endotoxic shock. Mechanistically, CYLD was found to catalyze the removal of LUBAC-mediated M1-linked ubiquitination of NF-kB p65 at K301/K303, thereby suppressing the nuclear translocation and activation of p65 for subsequent cytokines production. Notably, the cleaved N-terminal fragment of CYLD (named CP25) is secreted in a TRIF/Caspase8-dependent manner. Moreover, CP25 can be detected in the serum of septic mice, and its levels show a strong correlation with corresponding serum IL-1{beta}, suggesting its potential utility as an inflammatory biomarker. Overall, these findings highlight the significance of CYLD cleavage as a promising therapeutic target and diagnostic marker for endotoxic shock.

immunology↗

bioRxiv2024

iSORT: An Integrative Method for Reconstructing Spatial Organization of Cells using Transfer Learning

Spatial tissues exhibit complex gene expression and multicellular patterns that are difficult to dissect. Single-cell RNA sequencing (scRNA-seq) provides full coverages of genes, but lacking spatial information, whereas spatial transcriptomics (ST) measures spatial locations of individual or group of cells, with more restrictions on gene information. To integrate scRNA-seq and ST data, we introduce a transfer learning method to decipher spatial organization of cells named iSORT. iSORT trains a neural network that maps gene expressions to spatial locations using scRNA-seq data along with ST slices as references. iSORT can find spatial patterns at single-cell scale, identify key genes that drive the patterning, and infer pseudo-growth trajectories using a concept of SpaRNA velocity. Benchmarking on simulation data and comparing with multiple existing tools show iSORTs robustness and accuracy in reconstructing spatial organization. Using our own new human artery datasets, iSORT shows its capability of dissecting atherosclerosis. Applications to a range of biological systems, such as mouse embryo, mouse brain, Drosophila embryo, and human developmental heart, demonstrate that iSORT can utilize both scRNA-seq and ST datasets to uncover multilayer spatial information of single cells.

bioinformatics↗

bioRxiv2024

Single-cell multiomics reveals a gene regulatory circuit promoting leukemia cell differentiation

Cancer differentiation therapy aims to induce maturation of neoplastic cells, yet how cell fate is determined in oncogenic cellular contexts is poorly understood. Here we integrate chromatin accessibility and transcriptome analysis at single-cell levels to investigate the mechanism driving the differentiation trajectory of the PML/RAR+ acute promyeloid leukemia (APL) cell line model, NB4, under the induction of all-trans-retinoid acid (ATRA). We show that differentiating NB4 cells navigate through an intermediate cell fate decision point that leads to either terminal granulopoiesis or a transient immature-lymphocyte-like state. Functional perturbation studies indicate that ATRA signaling activates discrete PML/RAR-target enhancers to induce a positive feedforward gene regulatory circuit involving two myeloid-lineage transcription factors, SPI1 and CEBPE, which is both necessary and sufficient to activate a myelocytic gene expression program in NB4. Further, ectopic expression of SPI1 and CEBPE also promotes myelocytic differentiation in non-APL leukemia cell lines HL60 and K562. Together, these results shed light on the differentiation trajectory of therapy-induced cell decisions of APL and suggest a gene regulatory circuit that may be broadly exploited to promote terminal differentiation of leukemia.

cancer biology↗

bioRxiv2024

EmbB and EmbC Regulate the Sensitivity of Mycobacterium abscessus to Echinomycin

Treatment of Mycobacterium abscessus (Mab) infection is a major challenge due to its intrinsic resistance to most available drugs. It is thus imperative to find new anti-Mab drugs. In this study, we investigated the activity and intrinsic resistance mechanism of echinomycin (ECH) against Mab. ECH is active against Mab (MIC: 2 {micro}g/mL). The embC gene knockout strain (Mab{Delta}embC) showed hyper-sensitive to ECH (MIC: 0.0078-0.0156 {micro}g/mL). The MICs of ECH-resistant strains screened based on the Mab{Delta}embC strain were 0.25-1 {micro}g/mL. Mutations were found in the EmbB, including Asp306Ala, Asp306Asn, Arg350Gly, Val555Ile, and Gly581Ser, which led to increased resistance to ECH when overexpressed in Mab{Delta}embC individually (0.25-0.5 {micro}g/mL). The EmbB mutants edited by the CRISPR/Cpf1 system became more resistant to ECH (MIC: 0.25-0.5 {micro}g/mL). The permeability of gene-edited and overexpressed Mab strains was reduced, as shown by the ethidium bromide accumulation assay, but it was still significantly higher than that of the parent Mab. To summarize, our study demonstrates that ECH has a strong anti-Mab activity and confirms that EmbB and EmbC are related to the sensitivity of Mab to ECH. EmbB mutation may partially compensate for the function of EmbC. Impact StatementMycobacterium abscessus (Mab) is a rapidly growing, intrinsic multidrug-resistant Mycobacterium. This study demonstrated that echinomycin (ECH) has potent antibacterial activity against Mab, and the mechanism of ECH resistance to Mab is related to EmbB and EmbC. EmbB and EmbC can alter the sensitivity of Mab to ECH by altering the permeability of its cell wall. In addition, there is a functional complementary evolution between EmbB and EmbC to regulate sensitivity to ECH. Overall, our study provides a novel anti-Mab drug candidate ECH and a scientific foundation for developing effective strategies to prevent and control Mab.

microbiology↗

bioRxiv2024

Thyroid Hormone Suppresses Medulloblastoma Progression Through Promoting Terminal Differentiation of Tumor Cells

Hypothyroidism is commonly detected in patients with medulloblastoma (MB). A possible link between thyroid hormone (TH) signaling and MB pathogenicity has not been reported. Here, we find that TH plays a critical role in promoting tumor cell differentiation. Reduction in TH levels frees the TH receptor, TR1, to bind to EZH2 and repress expression of NeuroD1, a transcription factor that drives tumor cell differentiation. Increased TH reverses EZH2-mediated repression of NeuroD1 by abrogating the binding of EZH2 and TR1, thereby stimulating tumor cell differentiation and reducing MB growth. Importantly, TH-induced differentiation of tumor cells is not restricted by the molecular subgroup of MB. These findings establish an unprecedented association between TH signaling and MB pathogenicity, providing solid evidence for TH as a promising modality for MB treatment.

cancer biology↗

bioRxiv2024

Single-molecule chromatin configurations link transcription factor binding to expression in human cells

The binding of multiple transcription factors (TFs) to genomic enhancers activates gene expression in mammalian cells. However, the molecular details that link enhancer sequence to TF binding, promoter state, and gene expression levels remain opaque. We applied single-molecule footprinting (SMF) to measure the simultaneous occupancy of TFs, nucleosomes, and components of the transcription machinery on engineered enhancer/promoter constructs with variable numbers of TF binding sites for both a synthetic and an endogenous TF. We find that activation domains enhance a TFs capacity to compete with nucleosomes for binding to DNA in a BAF-dependent manner, TF binding on nucleosome-free DNA is consistent with independent binding between TFs, and average TF occupancy linearly contributes to promoter activation rates. We also decompose TF strength into separable binding and activation terms, which can be tuned and perturbed independently. Finally, we develop thermodynamic and kinetic models that quantitatively predict both the binding microstates observed at the enhancer and subsequent time-dependent gene expression. This work provides a template for quantitative dissection of distinct contributors to gene activation, including the activity of chromatin remodelers, TF activation domains, chromatin acetylation, TF concentration, TF binding affinity, and TF binding site configuration.

molecular biology↗

bioRxiv2024

A Conserved Mechanism of Cardiac Hypertrophy Regression through FoxO1

The heart is a highly plastic organ that responds to diverse stimuli to modify form and function. The molecular mechanisms of adaptive physiological cardiac hypertrophy are well-established; however, the regulation of hypertrophy regression is poorly understood. To identify molecular features of regression, we studied Burmese pythons which experience reversible cardiac hypertrophy following large, infrequent meals. Using multi-omics screens followed by targeted analyses, we found forkhead box protein O1 (FoxO1) transcription factor signaling, and downstream autophagy activity, were downregulated during hypertrophy, but re-activated with regression. To determine whether these events were mechanistically related to regression, we established an in vitro platform of cardiomyocyte hypertrophy and regression from treatment with fed python plasma. FoxO1 inhibition prevented regression in this system, while FoxO1 activation reversed fed python plasma-induced hypertrophy in an autophagy-dependent manner. We next examined whether FoxO1 was implicated in mammalian models of reversible hypertrophy from exercise and pregnancy and found that in both cases FoxO1 was activated during regression. In these models, as in pythons, activation of FoxO1 was associated with increased expression FoxO1 target genes involved in autophagy. Taken together, our findings suggest FoxO1-dependent autophagy is a conserved mechanism for regression of physiological cardiac hypertrophy across species. HIGHLIGHTSO_LIPost-prandial cardiac remodeling in Burmese pythons is associated with dynamic regulation of FoxO1 and autophagy. C_LIO_LIRegression of fed python plasma-induced hypertrophy in mammalian cardiomyocytes is FoxO1-dependent. C_LIO_LIActivation of FoxO1-dependent autophagy is a conserved feature of physiological hypertrophy regression in mammalian models. C_LI

physiology↗

bioRxiv2024

Leptin Activated Hypothalamic BNC2 Neurons Acutely Suppress Food Intake

Leptin is an adipose tissue hormone that maintains homeostatic control of adipose tissue mass by regulating the activity of specific neural populations controlling appetite and metabolism1. Leptin regulates food intake by inhibiting orexigenic agouti-related protein (AGRP) neurons and activating anorexigenic pro-opiomelanocortin (POMC) neurons2. However, while AGRP neurons regulate food intake on a rapid time scale, acute activation of POMC neurons has only a minimal effect3-5. This has raised the possibility that there is a heretofore unidentified leptin-regulated neural population that suppresses appetite on a rapid time scale. Here, we report the discovery of a novel population of leptin-target neurons expressing basonuclin 2 (Bnc2) that acutely suppress appetite by directly inhibiting AGRP neurons. Opposite to the effect of AGRP activation, BNC2 neuronal activation elicited a place preference indicative of positive valence in hungry but not fed mice. The activity of BNC2 neurons is finely tuned by leptin, sensory food cues, and nutritional status. Finally, deleting leptin receptors in BNC2 neurons caused marked hyperphagia and obesity, similar to that observed in a leptin receptor knockout in AGRP neurons. These data indicate that BNC2-expressing neurons are a key component of the neural circuit that maintains energy balance, thus filling an important gap in our understanding of the regulation of food intake and leptin action.

neuroscience↗

bioRxiv2023

Umbrella toxin particles produced by Streptomyces block mycelial growth of competing species

The Streptomyces are a genus of ubiquitous soil bacteria from which the majority of clinically utilized antibiotics derive. The production of these antibacterial molecules reflects the relentless competition Streptomyces engage in with other bacteria, including other Streptomyces species. Here we show that in addition to small molecule antibiotics, Streptomyces produce and secrete antibacterial protein complexes that feature a large, degenerate repeat-containing polymorphic toxin protein. A cryo-EM structure of these particles reveals an extended stalk topped by a ringed crown comprising the toxin repeats scaffolding five lectin-tipped spokes, leading to our naming them umbrella particles. S. coelicolor encodes three umbrella particles with distinct toxin and lectin composition, and supernatant containing these toxins specifically and potently inhibits the growth of select Streptomyces species from among a diverse collection of bacteria screened. For one target, S. griseus, we find inhibition relies on a single toxin and that intoxication manifests as rapid cessation of vegetative mycelial growth. Our data show that Streptomyces umbrella particles mediate competition between vegetative mycelia of related species, a function distinct from small molecule antibiotics, which are produced at the onset of reproductive growth and act broadly. Sequence analyses suggest this role of umbrella particles extends beyond Streptomyces, as we find umbrella loci in nearly one-thousand species across Actinobacteria.

microbiology↗

bioRxiv2023

Semantical and Topological Protein Encoding Toward Enhanced Bioactivity and Thermostability

Protein engineering is a pivotal aspect of synthetic biology, involving the modification of amino acids within existing protein sequences to achieve novel or enhanced functionalities and physical properties. Accurate prediction of protein variant effects requires a thorough understanding of protein sequence, structure, and function. Deep learning methods have demonstrated remarkable performance in guiding protein modification for improved functionality. However, existing approaches predominantly rely on protein sequences, which face challenges in efficiently encoding the geometric aspects of amino acids local environment and often fall short in capturing crucial details related to protein folding stability, internal molecular interactions, and bio-functions. Furthermore, there lacks a fundamental evaluation for developed methods in predicting protein thermostability, although it is a key physical property that is frequently investigated in practice. To address these challenges, this paper introduces a novel pre-training framework that integrates sequential and geometric encoders for protein primary and tertiary structures. This framework guides mutation directions toward desired traits by simulating natural selection on wild-type proteins and evaluates variant effects based on their fitness to perform specific functions. We assess the proposed approach using three benchmarks comprising over 300 deep mutational scanning assays. The prediction results showcase exceptional performance across extensive experiments when compared to other zero-shot learning methods, all while maintaining a minimal cost in terms of trainable parameters. This study not only proposes an effective framework for more accurate and comprehensive predictions to facilitate efficient protein engineering, but also enhances the in silico assessment system for future deep learning models to better align with empirical requirements. The PyTorch implementation are available at https://github.com/tyang816/ProtSSN.

bioengineering↗

bioRxiv2023

MitoTracer facilitates the identification of informative mitochondrial mutations for precise lineage reconstruction

Mitochondrial (MT) mutations serve as natural genetic markers for inferring clonal relationships using single cell sequencing data. However, the fundamental challenge of MT mutation-based lineage tracing is automated identification of informative MT mutations. Here, we introduced an open-source computational algorithm called "MitoTracer", which accurately identified clonally informative MT mutations and inferred evolutionary lineage from scRNA-seq or scATAC-seq samples. We benchmarked MitoTracer using the ground-truth experimental lineage sequencing data and demonstrated its superior performance over the existing methods measured by high sensitivity and specificity. MitoTracer is compatible with multiple single cell sequencing platforms. Its application to a cancer evolution dataset revealed the genes related to primary BRAF-inhibitor resistance from scRNA-seq data of BRAF-mutated cancer cells. Overall, our work provided a valuable tool for capturing real informative MT mutations and tracing the lineages among cells. TeaserMitoTracer enables automatically and accurately discover informative mitochondrial mutations for lineage tracing.

bioinformatics↗

bioRxiv2023

Protein Engineering with Lightweight Graph Denoising Neural Networks

Protein engineering faces challenges in finding optimal mutants from the massive pool of candidate mutants. In this study, we introduce a deep learning-based data-efficient fitness prediction tool to steer protein engineering. Our methodology establishes a lightweight graph neural network scheme for protein structures, which efficiently analyzes the microenvironment of amino acids in wild-type proteins and reconstructs the distribution of the amino acid sequences that are more likely to pass natural selection. This distribution serves as a general guidance for scoring proteins toward arbitrary properties on any order of mutations. Our proposed solution undergoes extensive wet-lab experimental validation spanning diverse physicochemical properties of various proteins, including fluorescence intensity, antigen-antibody affinity, thermostability, and DNA cleavage activity. More than 40% of PO_SCPLOWROTC_SCPLOWLGN-designed single-site mutants outperform their wild-type counterparts across all studied proteins and targeted properties. More importantly, our model can bypass the negative epistatic effect to combine single mutation sites and form deep mutants with up to 7 mutation sites in a single round, whose physicochemical properties are significantly improved. This observation provides compelling evidence of the structure-based models potential to guide deep mutations in protein engineering. Overall, our approach emerges as a versatile tool for protein engineering, benefiting both the computational and bioengineering communities.

bioengineering↗

bioRxiv2023

Class A capsid assembly modulator apoptotic elimination of hepatocytes with high HBV core antigen level in vivo is dependent on de novo core protein translation

Background and aimsCapsid assembly (CA) is a critical step in the hepatitis B virus (HBV) life cycle, mediated by the viral core protein. CA is the target for various new anti-viral candidate therapeutics known as capsid assembly modulators (CAMs) of which the CAM-aberrant (CAM-A) class induces aberrant shaped core protein structures and lead to hepatocyte cell death. The aim of the studies was to identify the mechanism of action of the CAM-A modulators leading to HBV infected hepatocyte elimination. MethodsThe CAM-A mediated mechanism of HBsAg reduction was evaluated in vitro in a stable HBV replicating cell line and in vivo in AAV-HBV transduced C57BL/6, C57BL/6 SCID and HBV-infected chimeric mice with humanized livers. ResultsIn vivo treatment with CAM-A modulators induced pronounced reductions in HBe- and HBsAg which were associated with a transient increase in ALT. Both HBs- and HBeAg reduction and ALT increase were delayed in C57BL/6 SCID and chimeric mice, suggesting that adaptive immune responses may indirectly contribute to this phenotype. However, depletion of CD8+ T-cells in transduced wild-type mice did not have a negative impact on antigen reduction, indicating that CD8+ T-cell responses are not essential. Coinciding with the transient ALT elevation in AAV-HBV transduced mice, we observed a transient increase in markers related to endoplasmic reticulum stress and apoptosis as well as cytokines related to apoptosis pathways, followed by the detection of a proliferation marker. Pathway enrichment analysis of microarray data revealed that antigen presentation pathway (MHC-I) was upregulated, overlapping with observed apoptosis. Combination treatment with HBV-specific siRNA demonstrated that CAM-A mediated HBsAg reduction is dependent on de novo core protein translation and that the effect is dependent on high levels of core protein expression, which will likely focus the CHB sub-population that could respond. ConclusionCAM-A treatment eradicates HBV infected hepatocytes with high core protein levels through the induction of apoptosis a promising approach as part of a regimen to achieve functional cure. Lay summaryTreatment with hepatitis B virus (HBV) capsid assembly modulators that induce the formation of aberrant HBV core protein structures (CAM-A) leads to programmed cell death, apoptosis, of HBV-infected hepatocytes and subsequent reduction of HBV antigens, which differentiates CAM-A from other CAMs. The effect is dependent on the de novo synthesis and high levels of core protein.

microbiology↗