Efficient treatment and pre-exposure prophylaxis in rhesus macaques by an HIV fusion-inhibitory lipopeptide.

Two HIV fusion-inhibitory lipopeptides (LP-97 and LP-98) were designed with highly potent, long-acting antiviral activity. Monotherapy using a low dose of LP-98 sharply reduced viral loads and maintained long-term viral suppression in 21 SHIVSF162P3-infected rhesus macaques. We found that five treated monkeys achieved potential posttreatment control (PTC) efficacy and had lower viral DNA in deep lymph nodes, whereas monkeys with a stable viral rebound had higher viral DNA in superficial lymph nodes. The tissues of PTC monkeys exhibited significantly decreased quantitative viral outgrowth and fewer PD-1+ central memory CD4+ T cells, and CD8+ T cells contributed to virologic control efficacy. Moreover, LP-98 administrated as a pre-exposure prophylaxis (PrEP) provided complete protection against SHIVSF162P3 and SIVmac239 infections in 51 monkeys via intrarectal, intravaginal, or intravenous challenge. In conclusion, our lipopeptides exhibit high potential as an efficient HIV treatment or prevention strategy.

Molecular mechanism for target recognition, dimerization, and activation of Pyrococcus furiosus Argonaute.

The Argonaute nuclease from the thermophilic archaeon Pyrococcus furiosus (PfAgo) contributes to host defense and represents a promising biotechnology tool. Here, we report the structure of a PfAgo-guide DNA-target DNA ternary complex at the cleavage-compatible state. The ternary complex is predominantly dimerized, and the dimerization is solely mediated by PfAgo at PIWI-MID, PIWI-PIWI, and PAZ-N interfaces. Additionally, PfAgo accommodates a short 14-bp guide-target DNA duplex with a wedge-type N domain and specifically recognizes 5'-phosphorylated guide DNA. In contrast, the PfAgo-guide DNA binary complex is monomeric, and the engagement of target DNA with 14-bp complementarity induces sufficient dimerization and activation of PfAgo, accompanied by movement of PAZ and N domains. A closely related Argonaute from Thermococcus thioreducens adopts a similar dimerization configuration with an additional zinc finger formed at the dimerization interface. Dimerization of both Argonautes stabilizes the catalytic loops, highlighting the important role of Argonaute dimerization in the activation and target cleavage.

The pathogenicity of SARS-CoV-2 in hACE2 transgenic mice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease 2019 (COVID-19), which has become a public health emergency of international concern1. Angiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for severe acute respiratory syndrome coronavirus (SARS-CoV)2. Here we infected transgenic mice that express human ACE2 (hereafter, hACE2 mice) with SARS-CoV-2 and studied the pathogenicity of the virus. We observed weight loss as well as virus replication in the lungs of hACE2 mice infected with SARS-CoV-2. The typical histopathology was interstitial pneumonia with infiltration of considerable numbers of macrophages and lymphocytes into the alveolar interstitium, and the accumulation of macrophages in alveolar cavities. We observed viral antigens in bronchial epithelial cells, macrophages and alveolar epithelia. These phenomena were not found in wild-type mice infected with SARS-CoV-2. Notably, we have confirmed the pathogenicity of SARS-CoV-2 in hACE2 mice. This mouse model of SARS-CoV-2 infection will be valuable for evaluating antiviral therapeutic agents and vaccines, as well as understanding the pathogenesis of COVID-19.

The legacy environmental footprints of manufactured capital.

The foundations of today's societies are provided by manufactured capital accumulation driven by investment decisions through time. Reconceiving how the manufactured assets are harnessed in the production-consumption system is at the heart of the paradigm shifts necessary for long-term sustainability. Our research integrates 50 years of economic and environmental data to provide the global legacy environmental footprint (LEF) and unveil the historical material extractions, greenhouse gas emissions, and health impacts accrued in today's manufactured capital. We show that between 1995 and 2019, global LEF growth outpaced GDP and population growth, and the current high level of national capital stocks has been heavily relying on global supply chains in metals. The LEF shows a larger or growing gap between developed economies (DEs) and less-developed economies (LDEs) while economic returns from global asset supply chains disproportionately flow to DEs, resulting in a double burden for LDEs. Our results show that ensuring best practice in asset production while prioritizing well-being outcomes is essential in addressing global inequalities and protecting the environment. Achieving this requires a paradigm shift in sustainability science and policy, as well as in green finance decision-making, to move beyond the focus on the resource use and emissions of daily operations of the assets and instead take into account the long-term environmental footprints of capital accumulation.

Accessible Region Conformation Capture (ARC-C) gives high-resolution insights into genome architecture and regulation.

Nuclear organization and chromatin interactions are important for genome function, yet determining chromatin connections at high resolution remains a major challenge. To address this, we developed Accessible Region Conformation Capture (ARC-C), which profiles interactions between regulatory elements genome-wide without a capture step. Applied to Caenorhabditis elegans, ARC-C identifies approximately 15,000 significant interactions between regulatory elements at 500-bp resolution. Of 105 TFs or chromatin regulators tested, we find that the binding sites of 60 are enriched for interacting with each other, making them candidates for mediating interactions. These include cohesin and condensin II. Applying ARC-C to a mutant of transcription factor BLMP-1 detected changes in interactions between its targets. ARC-C simultaneously profiles domain-level architecture, and we observe that C. elegans chromatin domains defined by either active or repressive modifications form topologically associating domains (TADs) that interact with A/B (active/inactive) compartment-like structure. Furthermore, we discover that inactive compartment interactions are dependent on H3K9 methylation. ARC-C is a powerful new tool to interrogate genome architecture and regulatory interactions at high resolution.

Rapid growth of Moso bamboo (Phyllostachys edulis): Cellular roadmaps, transcriptome dynamics, and environmental factors.

Moso bamboo (Phyllostachys edulis) shows remarkably rapid growth (114.5 cm/day), but the underlying biological mechanisms remain unclear. After examining more than 12,750 internodes from more than 510 culms from 17 Moso populations, we identified internode 18 as a representative internode for rapid growth. This internode includes a 2-cm cell division zone (DZ), a cell elongation zone up to 12 cm, and a secondary cell wall (SCW) thickening zone. These zones elongated 11.8 cm, produced approximately 570,000,000 cells, and deposited ∼28 mg g-1 dry weight (DW) lignin and ∼44 mg g-1 DW cellulose daily, far exceeding vegetative growth observed in other plants. We used anatomical, mathematical, physiological, and genomic data to characterize development and transcriptional networks during rapid growth in internode 18. Our results suggest that (1) gibberellin may directly trigger the rapid growth of Moso shoots, (2) decreased cytokinin and increased auxin accumulation may trigger cell DZ elongation, and (3) abscisic acid and mechanical pressure may stimulate rapid SCW thickening via MYB83L. We conclude that internode length involves a possible tradeoff mediated by mechanical pressure caused by rapid growth, possibly influenced by environmental temperature and regulated by genes related to cell division and elongation. Our results provide insight into the rapid growth of Moso bamboo.

Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery.

A common strategy for the functional interpretation of genome-wide association study (GWAS) findings has been the integrative analysis of GWAS and expression data. Using this strategy, many association methods (e.g., PrediXcan and FUSION) have been successful in identifying trait-associated genes via mediating effects on RNA expression. However, these approaches often ignore the effects of splicing, which can carry as much disease risk as expression. Compared to expression data, one challenge to detect associations using splicing data is the large multiple testing burden due to multidimensional splicing events within genes. Here, we introduce a multidimensional splicing gene (MSG) approach, which consists of two stages: 1) we use sparse canonical correlation analysis (sCCA) to construct latent canonical vectors (CVs) by identifying sparse linear combinations of genetic variants and splicing events that are maximally correlated with each other; and 2) we test for the association between the genetically regulated splicing CVs and the trait of interest using GWAS summary statistics. Simulations show that MSG has proper type I error control and substantial power gains over existing multidimensional expression analysis methods (i.e., S-MultiXcan, UTMOST, and sCCA+ACAT) under diverse scenarios. When applied to the Genotype-Tissue Expression Project data and GWAS summary statistics of 14 complex human traits, MSG identified on average 83%, 115%, and 223% more significant genes than sCCA+ACAT, S-MultiXcan, and UTMOST, respectively. We highlight MSG's applications to Alzheimer's disease, low-density lipoprotein cholesterol, and schizophrenia, and found that the majority of MSG-identified genes would have been missed from expression-based analyses. Our results demonstrate that aggregating splicing data through MSG can improve power in identifying gene-trait associations and help better understand the genetic risk of complex traits.

Synergistic Influence of Fibrous Pattern Orientation and Modulus on Cellular Mechanoresponse.

The fibrous extracellular matrix (ECM) is vital for tissue regeneration and impacts implanted device treatments. Previous research on fibrous biomaterials shows varying cellular reactions to surface orientation, often due to unclear interactions between surface topography and substrate elasticity. Our study addresses this gap by achieving the rapid creation of hydrogels with diverse fibrous topographies and varying substrate moduli through a surface printing strategy. Cells exhibit heightened traction force on nanopatterned soft hydrogels, particularly with randomly distributed patterns compared with regular soft hydrogels. Meanwhile, on stiff hydrogels featuring an aligned topography, optimal cellular mechanosensing is observed compared to random topography. Mechanistic investigations highlight that cellular force-sensing and adhesion are influenced by the interplay of pattern deformability and focal adhesion orientation, subsequently mediating stem cell differentiation. Our findings highlight the importance of combining substrate modulus and topography to guide cellular behavior in designing advanced tissue engineering biomaterials.

Fiber Flexibility Reconciles Matrix Recruitment and the Fiber Modulus to Promote Cell Mechanosensing.

The mechanical interaction between cells and the extracellular matrix is pervasive in biological systems. On fibrous substrates, cells possess the ability to recruit neighboring fibers, thereby augmenting their own adhesion and facilitating the generation of mechanical cues. However, the matrices with high moduli impede fiber recruitment, restricting the cell mechanoresponse. Herein, by harnessing the inherent swelling properties of gelatin, the flexible gelatin methacryloyl network empowers cells to recruit fibers spanning a broad spectrum of physiological moduli during adhesion. The high flexibility concurrently facilitates the optimization of fiber distribution, deformability, and modulus, contributing to the promotion of cell mechanosensing. Consequently, the randomly distributed flexible fibers with high moduli maximize the cell adhesive forces. This study uncovers the impact of fiber recruitment on cell mechanosensing and introduces fiber flexibility as a previously unexplored property, offering an innovative perspective for the design and development of novel biomaterials.

Dynamic Regulation of Cell Mechanotransduction through Sequentially Controlled Mobile Surfaces.

The physical properties of nanoscale cell-extracellular matrix (ECM) ligands profoundly impact biological processes, such as adhesion, motility, and differentiation. While the mechanoresponse of cells to static ligands is well-studied, the effect of dynamic ligand presentation with "adaptive" properties on cell mechanotransduction remains less understood. Utilizing a controllable diffusible ligand interface, we demonstrated that cells on surfaces with rapid ligand mobility could recruit ligands through activating integrin α5ß1, leading to faster focal adhesion growth and spreading at the early adhesion stage. By leveraging UV-light-sensitive anchor molecules to trigger a "dynamic to static" transformation of ligands, we sequentially activated α5ß1 and αvß3 integrins, significantly promoting osteogenic differentiation of mesenchymal stem cells. This study illustrates how manipulating molecular dynamics can directly influence stem cell fate, suggesting the potential of "sequentially" controlled mobile surfaces as adaptable platforms for engineering smart biomaterial coatings.

Artificial intelligence aids in development of nanomedicines for cancer management.

Over the last decade, the nanomedicine has experienced unprecedented development in diagnosis and management of diseases. A number of nanomedicines have been approved in clinical use, which has demonstrated the potential value of clinical transition of nanotechnology-modified medicines from bench to bedside. The application of artificial intelligence (AI) in development of nanotechnology-based products could transform the healthcare sector by realizing acquisition and analysis of large datasets, and tailoring precision nanomedicines for cancer management. AI-enabled nanotechnology could improve the accuracy of molecular profiling and early diagnosis of patients, and optimize the design pipeline of nanomedicines by tuning the properties of nanomedicines, achieving effective drug synergy, and decreasing the nanotoxicity, thereby, enhancing the targetability, personalized dosing and treatment potency of nanomedicines. Herein, the advances in AI-enabled nanomedicines in cancer management are elaborated and their application in diagnosis, monitoring and therapy as well in precision medicine development is discussed.

Utilization trend of prebiopsy multiparametric magnetic resonance imaging and its impact on prostate cancer detection: Real-world insights from a high-volume center in southwest China.

BACKGROUND: Data on the utilization and effects of prebiopsy prostate multiparametric magnetic resonance imaging (mpMRI) to support its routine use in real-world setting are still scarce. OBJECTIVE: To evaluate the change of clinical practice of prebiopsy mpMRI over time, and assess its diagnostic accuracy. DESIGN, SETTING, AND PARTICIPANTS: We retrospectively analyzed data from 6168 patients who underwent primary prostate biopsy (PBx) between January 2011 and December 2021 and had prostate-specific antigen (PSA) values ranging from 3 to 100 ng/mL. INTERVENTION: Prebiopsy MRI at the time of PBx. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We performed general linear regression and to elucidate trends in the annual use of prebiopsy mpMRI and conducted multivariable logistic regression to evaluate the potential benefits of incorporating prebiopsy mpMRI for prostate cancer (PCa) detection. RESULTS AND LIMITATIONS: The utilization of prebiopsy mpMRI significantly increased from 9.2% in 2011 to 75.0% in 2021 (p < 0.001). In addition, prebiopsy mpMRI significantly reduced negative PBx by 8.6% while improving the detection of clinically significant PCa (csPCa) by 7.0%. Regression analysis showed that the utilization of prebiopsy mpMRI was significantly associated with a 48% (95% confidence interval [CI]: 1.19-1.84) and 36% (95% CI: 1.12-1.66) increased PCa detection rate in the PSA 3-10 ng/mL and 10-20 ng/mL groups, respectively; and a 34% increased csPCa detection rate in the PSA 10-20 ng/mL group (95% CI: 1.09-1.64). The retrospective design and the single center cohort constituted the limitations of this study. CONCLUSIONS: Our study demonstrated a notable rise in the utilization of prebiopsy mpMRI in the past decade. The adoption of this imaging technique was significantly associated with an increased probability of detecting prostate cancer. PATIENT SUMMARY: From 2011 to 2021, we demonstrated a steady increase in the utilization of prebiopsy mpMRI among biopsy-naïve men. We also confirmed the positive impact of prebiopsy mpMRI utilization on the detection of prostate cancer.

Downregulation of N4-acetylcytidine modification in myeloid cells attenuates immunotherapy and exacerbates hepatocellular carcinoma progression.

BACKGROUND: N4-acetylcytidine (ac4C) is a conserved and abundant mRNA modification that controls protein expression by affecting translation efficiency and mRNA stability. Whether the ac4C modification of mRNA regulates hepatocellular carcinoma (HCC) development or affects the immunotherapy of HCC is unknown. METHODS: By constructing an orthotopic transplantation mouse HCC model and isolating tumour-infiltrated immunocytes, we evaluated the ac4C modification intensity using flow cytometry. Remodelin hydrobromide (REM), an ac4C modification inhibitor, was systematically used to understand the extensive role of ac4C modification in immunocyte phenotypes. Single-cell RNA-seq was performed to comprehensively evaluate the changes in the tumour-infiltrating immunocytes and identify targeted cell clusters. RNA-seq and RIP-seq analyses were performed to elucidate the underlying molecular mechanisms. Tyramide Signal Amplification (TSA) analysis on the HCC tissue microarray was performed to explore the clinical relatedness of our findings. RESULTS: Ac4C modification promoted M1 macrophage infiltration and reduced myeloid-derived suppressor cell MDSCs infiltration in HCC. The inhibition of ac4C modification induces PDL1 expression by stabilising mRNA in the myeloid cells, thereby attenuating the CTL-mediated tumour cell-killing ability. High infiltration of ac4C+CD11b+ cells is positively related to a better prognosis in patients with HCC. CONCLUSIONS: Ac4C modification of myeloid cells enhanced the HCC immunotherapy by suppressing PDL1 expression.

EIF4A3-negatively driven circular RNA ß-catenin (circß-catenin) promotes colorectal cancer progression via miR-197-3p/CTNND1 regulatory axis.

BACKGROUND: Circß-catenin, our first reported circRNA, has been reported to mediate tumorigenesis in various cancers. However, its biological functions and underlying mechanisms in colorectal cancer (CRC) remain unknown. METHODS: The qRT-PCR examination was used to detect the expression of circß-catenin, miR-197-3p, and CTNND1 in cells and human tissues. Western blot was conducted to detect the protein expression levels. The biological function of circß-catenin was verified by MTT, colony formation, wound healing, and transwell assays. The in vivo effects of circß-catenin were verified by nude mice xenograft and metastasis models. The regulatory network of circß-catenin/miR-197-3p/CTNND1 was confirmed via dual-luciferase reporter and RIP assays. RESULTS: In the present study, circß-catenin was found to promote CRC cell proliferation and metastasis in vitro and in vivo. Mechanistically, circß-catenin served as miRNA decoy to directly bind to miR-197-3p, then antagonized the repression of the target gene CTNND1, and eventually promoted the malignant phenotype of CRC. More interestingly, the inverted repeated Alu pairs termed AluJb1/2 and AluY facilitated the biogenesis of circß-catenin, which could be partially reversed by EIF4A3 binding to Alu element AluJb2. CONCLUSIONS: Our findings illustrated a novel mechanism of circß-catenin in modulating CRC tumorigenesis and metastasis, which provides a potential therapeutic target for CRC patients.

Title: Bona Fide Plant Steroid Receptors Are Innovated in Seed Plants and Angiosperms through Successive Whole Genome Duplication Events.

Whole genome duplication (WGD) events are widespread in plants and animals, thus their long-term evolutionary contribution has long been speculated, yet a specific contribution is difficult to verify. Here, we show that ɛ-WGD and ζ-WGD contribute to the origin and evolution of bona fide brassinosteroid (BR) signaling through the innovation of active BR biosynthetic enzymes and active BR receptors from their respective ancestors. We found that BR receptors BRI1 (BR Insensitive 1) and BRL1/3 (BRI1-likes 1/3) derived by ɛ-WGD and ζ-WGD, which occurred in the common ancestor of angiosperms and seed plants, respectively, while orphan BR receptor BRL2 first appeared in stomatophytes. Additionally, CYP85A enzymes synthesizing the bioactive BRs derived from a common ancestor of seed plants while its sister enzymes CYP90 synthesizing BR precursors presented in all land plants, implying possible ligand-receptor coevolution. Consistently, the island domains (IDs) responsible for BR perception in BR receptors were most divergent among different receptor branches, supporting ligand-driven evolution. As a result, BRI1 was the most diversified BR receptor in angiosperms. Importantly, relative to the BR biosynthetic DET2 gene presented in all land plants, BRL2, BRL1/3 and BRI1 had high expression in vascular plants ferns, gymnosperms and angiosperms, respectively. Notably, BRI1 is the most diversified BR receptor with the most abundant expression in angiosperms, suggesting potential positive selection. Therefore, WGDs initiate a neofunctionalization process diverged by ligand-perception and transcriptional expression, which might optimize both BR biosynthetic enzymes and BR receptors, likely contributing to the evolution of land plants, especially seed plants and angiosperms.

A multimodal atlas of hepatocellular carcinoma reveals convergent evolutionary paths and 'bad apple' effect on clinical trajectory.

BACKGROUND & AIMS: Hepatocellular Carcinoma (HCC) is a highly fatal cancer characterized by high intra-tumor heterogeneity (ITH). A panoramic understanding of its tumor evolution, in relation to its clinical trajectory, may provide novel prognostic and treatment strategies. METHODS: Through the Asia-Pacific Hepatocellular Carcinoma (AHCC) trials group (NCT03267641), we recruited one of the largest prospective cohorts of HCC with over 600 whole genome and transcriptome samples from 123 treatment-naïve patients. RESULTS: Using a multi-region sampling approach, we revealed seven convergent genetic evolutionary paths governed by the early driver mutations, late copy number variations and viral integrations, which stratify patient clinical trajectories after surgical resection. Furthermore, such evolutionary paths shaped the molecular profiles, leading to distinct transcriptomic subtypes. Most significantly, although we found the coexistence of multiple transcriptomic subtypes within certain tumors, patient prognosis was best predicted by the most aggressive cell fraction of the tumor, rather than by overall degree of transcriptomic ITH level - a phenomenon we termed the 'bad apple' effect. Finally, we found that characteristics throughout early and late tumor evolution provide significant and complementary prognostic power in predicting patient survival. CONCLUSIONS: Taken together, our study generated a comprehensive landscape of evolutionary history for HCC and provided a rich multi-omics resource for understanding tumor heterogeneity and clinical trajectories. CLINICAL TRIAL NUMBER: NCT03267641 (Observational cohort) IMPACT AND IMPLICATIONS: This prospective study, utilizing comprehensive multi-sector, multi-omics sequencing and clinical data from surgically resected HCC, reveals critical insights into the role of tumor evolution and intra-tumor heterogeneity (ITH) in determining the prognosis of Hepatocellular Carcinoma (HCC). These findings are invaluable for oncology researchers and clinicians, as they underscore the influence of distinct evolutionary paths and the 'bad apple' effect, where the most aggressive tumor fraction dictates disease progression. These insights not only enhance prognostic accuracy post-surgical resection but also pave the way for developing personalized therapies tailored to specific tumor evolutionary and transcriptomic profiles. The co-existence of multiple sub-types within the same tumor prompts a re-appraisal of the utilities of depending on single samples to represent the entire tumor and suggests the need for clinical molecular imaging. This research thus marks a significant step forward in the clinical understanding and management of HCC, underscoring the importance of integrating tumor evolutionary dynamics and multi-omics biomarkers into therapeutic decision-making.

Age-Dependent Female Survival Advantage in Hepatocellular Carcinoma: A Multicenter Cohort Study.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) has a higher incidence in males, but the association of sex with survival remains controversial. This study aimed to examine the effect of sex on HCC survival and its association with age. METHODS: Among 33,238 patients with HCC from 12 Chinese tertiary hospitals, 4175 patients who underwent curative-intent hepatectomy or ablation were analyzed. Cancer-specific survival (CSS) was analyzed using Cox regression and Kaplan-Meier methods. Two propensity score methods and multiple mediation analysis were applied to mitigate confounding. To explore the effect of estrogen, a candidate sex-specific factor that changes with age, female participants' history of estrogen use, and survival were analyzed. RESULTS: There were 3321 males and 854 females included. A sex-related disparity of CSS was present and showed a typical age-dependent pattern: a female survival advantage over males appeared at the perimenopausal age of 45 to 54 years (hazard risk [HR], 0.77; 5-year CSS, 85.7% vs 70.6%; P = .018), peaked at the early postmenopausal age of 55 to 59 years (HR, 0.57; 5-year CSS, 89.8% vs 73.5%; P = .015), and was not present in the premenopausal (<45 y) and late postmenopausal groups (≥60 y). Consistent patterns were observed in patients after either ablation or hepatectomy. These results were sustained with propensity score analyses. Confounding or mediation effects accounted for only 19.5% of sex survival disparity. Female estrogen users had significantly longer CSS than nonusers (HR, 0.74; 5-year CSS, 79.6% vs 72.5%; P = .038). CONCLUSIONS: A female survival advantage in HCC depends on age, and this may be associated with age-dependent, sex-specific factors.

HSPA5 Promotes Attachment and Internalization of Porcine Epidemic Diarrhea Virus through Interaction with the Spike Protein and the Endo-/Lysosomal Pathway.

Porcine epidemic diarrhea virus (PEDV) has caused huge economic losses to the global pig industry. The swine enteric coronavirus spike (S) protein recognizes various cell surface molecules to regulate viral infection. In this study, we identified 211 host membrane proteins related to the S1 protein by pulldown combined with liquid-chromatography tandem mass spectrometry (LC-MS/MS) analysis. Among these, heat shock protein family A member 5 (HSPA5) was identified through screening as having a specific interaction with the PEDV S protein, and positive regulation of PEDV infection was validated by knockdown and overexpression tests. Further studies verified the role of HSPA5 in viral attachment and internalization. In addition, we found that HSPA5 interacts with S proteins through its nucleotide-binding structural domain (NBD) and that polyclonal antibodies can block viral infection. In detail, HSPA5 was found to be involved in viral trafficking via the endo-/lysosomal pathway. Inhibition of HSPA5 activity during internalization would reduce the subcellular colocalization of PEDV with lysosomes in the endo-/lysosomal pathway. Together, these findings show that HSPA5 is a novel PEDV potential target for the creation of therapeutic drugs. IMPORTANCE PEDV infection causes severe piglet mortality and threatens the global pig industry. However, the complex invasion mechanism of PEDV makes its prevention and control difficult. Here, we determined that HSPA5 is a novel target for PEDV which interacts with its S protein and is involved in viral attachment and internalization, influencing its transport via the endo-/lysosomal pathway. Our work extends knowledge about the relationship between the PEDV S and host proteins and provides a new therapeutic target against PEDV infection.

A computational framework to unify orthogonal information in DNA methylation and copy number aberrations in cell-free DNA for early cancer detection.

Cell-free DNA (cfDNA) provides a convenient diagnosis avenue for noninvasive cancer detection. The current methods are focused on identifying circulating tumor DNA (ctDNA)s genomic aberrations, e.g. mutations, copy number aberrations (CNAs) or methylation changes. In this study, we report a new computational method that unifies two orthogonal pieces of information, namely methylation and CNAs, derived from whole-genome bisulfite sequencing (WGBS) data to quantify low tumor content in cfDNA. It implements a Bayes model to enrich ctDNA from WGBS data based on hypomethylation haplotypes, and subsequently, models CNAs for cancer detection. We generated WGBS data in a total of 262 samples, including high-depth (>20×, deduped high mapping quality reads) data in 76 samples with matched triplets (tumor, adjacent normal and cfDNA) and low-depth (~2.5×, deduped high mapping quality reads) data in 186 samples. We identified a total of 54 Mb regions of hypomethylation haplotypes for model building, a vast majority of which are not covered in the HumanMethylation450 arrays. We showed that our model is able to substantially enrich ctDNA reads (tens of folds), with clearly elevated CNAs that faithfully match the CNAs in the paired tumor samples. In the 19 hepatocellular carcinoma cfDNA samples, the estimated enrichment is as high as 16 fold, and in the simulation data, it can achieve over 30-fold enrichment for a ctDNA level of 0.5% with a sequencing depth of 600×. We also found that these hypomethylation regions are also shared among many cancer types, thus demonstrating the potential of our framework for pancancer early detection.

Sortilin-Driven Cancer Secretome Enhances Tumorigenic Properties of Hepatocellular Carcinoma via de Novo Lipogenesis.

A growing body of evidence suggests de novo lipogenesis as a key metabolic pathway adopted by cancers to fuel tumorigenic processes. While increased de novo lipogenesis has also been reported in hepatocellular carcinoma (HCC), understanding on molecular mechanisms driving de novo lipogenesis remains limited. In the present study, the functional role of sortilin, a member of the vacuolar protein sorting 10 protein receptor family, in HCC was investigated. Sortilin was overexpressed in HCC and was associated with poorer survival outcome. In functional studies, sortilin-overexpressing cells conferred tumorigenic phenotypes, namely, self-renewal and metastatic potential, of HCC cells via the cancer secretome. Proteomic profiling highlighted fatty acid metabolism as a potential molecular pathway associated with sortilin-driven cancer secretome. This finding was validated by the increased lipid content and expression of fatty acid synthase (FASN) in HCC cells treated with conditioned medium collected from sortilin-overexpressing cells. The enhanced tumorigenic properties endowed by sortilin-driven cancer secretome were partly abrogated by co-administration of FASN inhibitor C75. Further mechanistic dissection suggested protein stabilization by post-translational modification with O-GlcNAcylation as a major mechanism leading to augmented FASN expression. In conclusion, the present study uncovered the role of sortilin in hepatocarcinogenesis via modulation of the cancer secretome and deregulated lipid metabolism.