CRISPR-Cas12-based field-deployable system for rapid detection of synthetic DNA sequence of the monkeypox virus genome.

The global outbreak of the monkeypox virus (MPXV) highlights the need for rapid and cost-effective MPXV detection tools to effectively monitor and control the monkeypox disease. Herein, we demonstrated a portable CRISPR-Cas-based system for naked-eye detection of MPXV. The system harnesses the high selectivity of CRISPR-Cas12 and the isothermal nucleic acid amplification potential of recombinase polymerase amplification. It can detect both the current circulating MPXV clade and the original clades. We reached a limit of detection (LoD) of 22.4 aM (13.5 copies/µl) using a microtiter plate reader, while the visual LoD of the system is 75 aM (45 copies/µl) in a two-step assay, which is further reduced to 25 aM (15 copies/µl) in a one-pot system. We compared our results with quantitative polymerase chain reaction and obtained satisfactory consistency. For clinical application, we demonstrated a sensitive and precise visual detection method with attomolar sensitivity and a sample-to-answer time of 35 min.

Sparse deconvolution for background noise suppression with total variation regularization in light field microscopy.

In this Letter, we present a method aiming at background noise removal in the 3D reconstruction of light field microscopy (LFM). Sparsity and Hessian regularization are taken as two prior knowledges to process the original light field image before 3D deconvolution. Due to the noise suppression function of total variation (TV) regularization, we add the TV regularization term to the 3D Richardson-Lucy (RL) deconvolution. By comparing the light field reconstruction results of our method with another state-of-the-art method that is also based on RL deconvolution, the proposed method shows improved performance in terms of removing background noise and detail enhancement. This method will be beneficial to the application of LFM in biological high-quality imaging.

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning.

We report a fast, easy-to-implement, highly sensitive, sequence-specific, and point-of-care (POC) DNA virus detection system, which combines recombinase polymerase amplification (RPA) and CRISPR/Cas12a system for trace detection of DNA viruses. Target DNA is amplified and recognized by RPA and CRISPR/Cas12a separately, which triggers the collateral cleavage activity of Cas12a that cleaves a fluorophore-quencher labeled DNA reporter and generalizes fluorescence. For POC detection, portable smartphone microscopy is built to take fluorescent images. Besides, deep learning models for binary classification of positive or negative samples, achieving high accuracy, are deployed within the system. Frog virus 3 (FV3, genera Ranavirus, family Iridoviridae) was tested as an example for this DNA virus POC detection system, and the limits of detection (LoD) can achieve 10 aM within 40 min. Without skilled operators and bulky instruments, the portable and miniature RPA-CRISPR/Cas12a-SPM with artificial intelligence (AI) assisted classification shows great potential for POC DNA virus detection and can help prevent the spread of such viruses.

Detection of Frog Virus 3 by Integrating RPA-CRISPR/Cas12a-SPM with Deep Learning.

A fast, easy-to-implement, highly sensitive, and point-of-care (POC) detection system for frog virus 3 (FV3) is proposed. Combining recombinase polymerase amplification (RPA) and CRISPR/Cas12a, a limit of detection (LoD) of 100 aM (60.2 copies/µL) is achieved by optimizing RPA primers and CRISPR RNAs (crRNAs). For POC detection, smartphone microscopy is implemented, and an LoD of 10 aM is achieved in 40 min. The proposed system detects four positive animal-derived samples with a quantitation cycle (Cq) value of quantitative PCR (qPCR) in the range of 13 to 32. In addition, deep learning models are deployed for binary classification (positive or negative samples) and multiclass classification (different concentrations of FV3 and negative samples), achieving 100 and 98.75% accuracy, respectively. Without temperature regulation and expensive equipment, the proposed RPA-CRISPR/Cas12a combined with smartphone readouts and artificial-intelligence-assisted classification showcases the great potential for FV3 detection, specifically POC detection of DNA virus.

Targeted inhibition of STAT3 induces immunogenic cell death of hepatocellular carcinoma cells via glycolysis.

In hepatocellular carcinoma (HCC), the signal transducer and activator of transcription 3 (STAT3) is present in an overactive state that is closely related to tumour development and immune escape. STAT3 inhibition reshapes the tumour immune microenvironment, but the underlying mechanisms have not been fully clarified. We found that STAT3 inhibition could induce immunogenic cell death (ICD) of HCC cells via translocation of the "eat me" molecule calreticulin to the cell surface and a significant reduction in the expression of the "don't eat me" molecule leucocyte surface antigen CD47. STAT3 inhibition promoted dendritic cell (DC) activation and enhanced the recognition and phagocytosis of HCC cells by macrophages. Furthermore, STAT3 inhibition prevented the expression of key glycolytic enzymes, facilitating the induction of ICD in HCC. Interestingly, STAT3 directly regulated the transcription of CD47 and solute carrier family 2 member 1 (SLC2A1; also known as GLUT1). In subcutaneous and orthotopic transplantation mouse tumour models, the STAT3 inhibitor napabucasin prevented tumour growth and induced the expression of calreticulin and the protein disulfide isomerase family A member 3 (PDIA3; also known as ERp57) but suppressed that of CD47 and GLUT1. Meanwhile, the amount of tumour-infiltrated DCs and macrophages increased, along with the expression of costimulatory molecules. More CD4+ and CD8+ T cells accumulated in tumour tissues, and CD8+ T cells had lower expression of checkpoint molecules such as lymphocyte activation gene 3 protein (LAG-3) and programmed cell death protein 1 (PD-1). Significantly, the antitumour immune memory response was induced by treatment targeting STAT3. These findings provide a new mechanism for targeting STAT3-induced ICD in HCC, and confirms STAT3 as a potential target for the treatment of HCC via reshaping the tumour immune microenvironment.

MERS-CoV nsp1 impairs the cellular metabolic processes by selectively downregulating mRNAs in a novel granules.

MERS-CoV infection can damage the cellular metabolic processes, but the underlying mechanisms are largely unknown. Through screening, we found non-structural protein 1 (nsp1) of MERS-CoV could inhibit cell viability, cell cycle, and cell migration through its endonuclease activity. Transcriptome sequencing revealed that MERS-CoV nsp1 specifically downregulated the mRNAs of ribosomal protein genes, oxidative phosphorylation protein genes, and antigen presentation genes, but upregulated the mRNAs of transcriptional regulatory genes. Further analysis shown nsp1 existed in a novel ribonucleosome complex formed via liquid-liquid phase separation, which did not co-localize with mitochondria, lysosomes, P-bodies, or stress granules. Interestingly, the nsp1-located granules specifically contained mRNAs of ribosomal protein genes and oxidative phosphorylation genes, which may explain why MERS-CoV nsp1 selectively degraded these mRNAs in cells. Finally, MERS-CoV nsp1 transgenic mice showed significant loss of body weight and an increased sensitivity to poly(I:C)-induced inflammatory death. These findings demonstrate a new mechanism by which MERS-CoV impairs cell viability, which serves as a potential novel target for preventing MERS-CoV infection-induced pathological damage.Abbreviations: (Middle East respiratory syndrome coronavirus (MERS-CoV), Actinomycin D (Act D), liquid-liquid phase separation (LLPS), stress granules (SGs), Mass spectrometry (IP-MS), RNA Binding Protein Immunoprecipitation (RIP)).

Exosome-mediated remodeling of the tumor microenvironment: From local to distant intercellular communication.

Extracellular vesicles (EVs) are membrane-enveloped nanoscale particles that carry various bioactive signaling molecules secreted by cells. Their biological roles depend on the original cell type from which they are derived and their inclusions. Exosomes, a class of EVs, are released by almost all eukaryotic cell types, including tumor cells. Tumor cell-derived exosomes mediate signal transduction between tumor cells and surrounding non-tumor cells. This intercellular communication actively contributes to the remodeling of the tumor microenvironment (TME) to enable tumor growth, invasion, and metastasis. This review summarizes the latest progress in the exploration of exosome-mediated cell-cell communication implicated in TME remodeling and underlying mechanisms. We focus on the role of cell-cell interactions mediated by tumor cell-derived exosomes in promoting invasion and metastasis, and their potential as a therapeutic intervention target against distant metastasis. We also discuss the clinical translational significance of tumor-derived exosomes for early diagnosis, efficacy and progression evaluations.

MERS-CoV nsp1 regulates autophagic flux via mTOR signalling and dysfunctional lysosomes.

Autophagy, a cellular surveillance mechanism, plays an important role in combating invading pathogens. However, viruses have evolved various strategies to disrupt autophagy and even hijack it for replication and release. Here, we demonstrated that Middle East respiratory syndrome coronavirus (MERS-CoV) non-structural protein 1(nsp1) induces autophagy but inhibits autophagic activity. MERS-CoV nsp1 expression increased ROS and reduced ATP levels in cells, which activated AMPK and inhibited the mTOR signalling pathway, resulting in autophagy induction. Meanwhile, as an endonuclease, MERS-CoV nsp1 downregulated the mRNA of lysosome-related genes that were enriched in nsp1-located granules, which diminished lysosomal biogenesis and acidification, and inhibited autophagic flux. Importantly, MERS-CoV nsp1-induced autophagy can lead to cell death in vitro and in vivo. These findings clarify the mechanism by which MERS-CoV nsp1-mediated autophagy regulation, providing new insights for the prevention and treatment of the coronavirus.

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive therapy, and chemotherapy. Although a satisfactory remission of the disease can be achieved, the risk of recurrence is still high. Therefore, novel treatments are demanding. Chimeric antigen receptor-T (CAR-T) therapy has emerged as a promising approach to treating and curing acute leukemia. To harness the therapeutic potential of CAR-T cell therapy for blood diseases, reliable cell morphological identification is crucial. Nevertheless, the identification of CAR-T cells is a big challenge posed by their phenotypic similarity with other blood cells. To address this substantial clinical challenge, herein we first construct a CAR-T dataset with 500 original microscopy images after staining. Following that, we create a novel integrated model called RCMNet (ResNet18 with Convolutional Block Attention Module and Multi-Head Self-Attention) that combines the convolutional neural network (CNN) and Transformer. The model shows 99.63% top-1 accuracy on the public dataset. Compared with previous reports, our model obtains satisfactory results for image classification. Although testing on the CAR-T cell dataset, a decent performance is observed, which is attributed to the limited size of the dataset. Transfer learning is adapted for RCMNet and a maximum of 83.36% accuracy is achieved, which is higher than that of other state-of-the-art models. This study evaluates the effectiveness of RCMNet on a big public dataset and translates it to a clinical dataset for diagnostic applications.

Current and Perspective Sensing Methods for Monkeypox Virus.

The outbreak of the monkeypox virus (MPXV) in non-endemic countries is an emerging global health threat and may have an economic impact if proactive actions are not taken. As shown by the COVID-19 pandemic, rapid, accurate, and cost-effective virus detection techniques play a pivotal role in disease diagnosis and control. Considering the sudden multicountry MPXV outbreak, a critical evaluation of the MPXV detection approaches would be a timely addition to the endeavors in progress for MPXV control and prevention. Herein, we evaluate the current MPXV detection methods, discuss their pros and cons, and provide recommended solutions to the problems. We review the traditional and emerging nucleic acid detection approaches, immunodiagnostics, whole-particle detection, and imaging-based MPXV detection techniques. The insights provided in this article will help researchers to develop novel techniques for the diagnosis of MPXV.