A segmentation model to detect cevical lesions based on machine learning of colposcopic images.

Background: Semantic segmentation is crucial in medical image diagnosis. Traditional deep convolutional neural networks excel in image classification and object detection but fall short in segmentation tasks. Enhancing the accuracy and efficiency of detecting high-level cervical lesions and invasive cancer poses a primary challenge in segmentation model development. Methods: Between 2018 and 2022, we retrospectively studied a total of 777 patients, comprising 339 patients with high-level cervical lesions and 313 patients with microinvasive or invasive cervical cancer. Overall, 1554 colposcopic images were put into the DeepLabv3+ model for learning. Accuracy, Precision, Specificity, and mIoU were employed to evaluate the performance of the model in the prediction of cervical high-level lesions and cancer. Results: Experiments showed that our segmentation model had better diagnosis efficiency than colposcopic experts and other artificial intelligence models, and reached Accuracy of 93.29 %, Precision of 87.2 %, Specificity of 90.1 %, and mIoU of 80.27 %, respectively. Conclution: The DeepLabv3+ model had good performance in the segmentation of cervical lesions in colposcopic post-acetic-acid images and can better assist colposcopists in improving the diagnosis.

Purification and functional validation of LtCas12a protein.

Here, we present a protocol for generating LtCas12a protein recognizing distinct TTNA (N represented A, T, C, G) protospacer adjacent motif sequence. We describe steps for transforming and harvesting bacterial cells and protein purification including nickel affinity chromatography and dialysis. We then detail procedures for verification of LtCas12a with cis- and trans-cleavage activities. For complete details on the use and execution of this protocol, please refer to Chen et al. (2023).1.

Massively parallel CRISPR off-target detection enables rapid off-target prediction model building.

BACKGROUND: CRISPR (clustered regularly interspaced short palindromic repeats) genome editing holds tremendous potential in clinical translation. However, the off-target effect has always been a major concern. METHODS: Here, we have developed a novel sensitive and specific off-target detection method, AID-seq (adaptor-mediated off-target identification by sequencing), that can comprehensively and faithfully detect the low-frequency off targets generated by different CRISPR nucleases (including Cas9 and Cas12a). FINDINGS: Based on AID-seq, we developed a pooled strategy to simultaneously identify the on/off targets of multiple gRNAs, as well as using mixed human and human papillomavirus (HPV) genomes to screen the most efficient and safe targets from 416 HPV gRNA candidates for antiviral therapy. Moreover, we used the pooled strategy with 2,069 single-guide RNAs (sgRNAs) at a pool size of about 500 to profile the properties of our newly discovered CRISPR, FrCas9. Importantly, we successfully built an off-target detection model using these off-target data via the CRISPR-Net deep learning method (area under the receiver operating characteristic curve [AUROC] = 0.97, area under the precision recall curve [AUPRC] = 0.29). CONCLUSIONS: To our knowledge, AID-seq is the most sensitive and specific in vitro off-target detection method to date. And the pooled AID-seq strategy can be used as a rapid and high-throughput platform to select the best sgRNAs and characterize the properties of new CRISPRs. FUNDING: This work was supported by The National Natural Science Foundation of China (grant nos. 32171465 and 82102392), the General Program of Natural Science Foundation of Guangdong Province of China (grant no. 2021A1515012438), Guangdong Basic and Applied Basic Research Foundation (grant no. 2020A1515110170), and the National Ten Thousand Plan-Young Top Talents of China (grant no. 80000-41180002).

A Cas12a ortholog with distinct TTNA PAM enables sensitive detection of HPV16/18.

CRISPR-associated (Cas) nucleases are multifunctional tools for gene editing. Cas12a possesses several advantages, including the requirement of a single guide RNA and high fidelity of gene editing. Here, we tested three Cas12a orthologs from human gut samples and identified a LtCas12a that utilizes a TTNA protospacer adjacent motif (PAM) distinct from the canonical TTTV PAM but with equivalent cleavage ability and specificity. These features significantly broadened the targeting scope of Cas12a family. Furthermore, we developed a sensitive, accurate, and rapid human papillomavirus (HPV) 16/18 gene detection platform based on LtCas12a DNA endonuclease-targeted CRISPR trans reporter (DETECTR) and lateral flow assay (LFA). LtCas12a showed comparable sensitivity to quantitative polymerase chain reaction (qPCR) and no cross-reaction with 13 other high-risk HPV genotypes in detecting the HPV16/18 L1 gene. Taken together, LtCas12a can broaden the applications of the CRISPR-Cas12a family and serve as a promising next-generation tool for therapeutic application and molecular diagnosis.

HPV integration generates a cellular super-enhancer which functions as ecDNA to regulate genome-wide transcription.

Human papillomavirus (HPV) integration is a critical step in cervical cancer development; however, the oncogenic mechanism at the genome-wide transcriptional level is still poorly understood. In this study, we employed integrative analysis on multi-omics data of six HPV-positive and three HPV-negative cell lines. Through HPV integration detection, super-enhancer (SE) identification, SE-associated gene expression and extrachromosomal DNA (ecDNA) investigation, we aimed to explore the genome-wide transcriptional influence of HPV integration. We identified seven high-ranking cellular SEs generated by HPV integration in total (the HPV breakpoint-induced cellular SEs, BP-cSEs), leading to intra-chromosomal and inter-chromosomal regulation of chromosomal genes. The pathway analysis revealed that the dysregulated chromosomal genes were correlated to cancer-related pathways. Importantly, we demonstrated that BP-cSEs existed in the HPV-human hybrid ecDNAs, explaining the above transcriptional alterations. Our results suggest that HPV integration generates cellular SEs that function as ecDNA to regulate unconstrained transcription, expanding the tumorigenic mechanism of HPV integration and providing insights for developing new diagnostic and therapeutic strategies.

VIS Atlas: A Database of Virus Integration Sites in Human Genome from NGS Data to Explore Integration Patterns.

Integration of oncogenic DNA viruses into the human genome is a key step in most virus-induced carcinogenesis. Here, we constructed a virus integration site (VIS) Atlas database, an extensive collection of integration breakpoints for three most prevalent oncoviruses, human papillomavirus, hepatitis B virus, and Epstein-Barr virus based on the next-generation sequencing (NGS) data, literature, and experimental data. There are 63,179 breakpoints and 47,411 junctional sequences with full annotations deposited in the VIS Atlas database, comprising 47 virus genotypes and 17 disease types. The VIS Atlas database provides (1) a genome browser for NGS breakpoint quality check, visualization of VISs, and the local genomic context; (2) a novel platform to discover integration patterns; and (3) a statistics interface for a comprehensive investigation of genotype-specific integration features. Data collected in the VIS Atlas aid to provide insights into virus pathogenic mechanisms and the development of novel antitumor drugs. The VIS Atlas database is available at https://www.vis-atlas.tech/.

FrCas9 is a CRISPR/Cas9 system with high editing efficiency and fidelity.

Genome editing technologies hold tremendous potential in biomedical research and drug development. Therefore, it is imperative to discover gene editing tools with superior cutting efficiency, good fidelity, and fewer genomic restrictions. Here, we report a CRISPR/Cas9 from Faecalibaculum rodentium, which is characterized by a simple PAM (5'-NNTA-3') and a guide RNA length of 21-22 bp. We find that FrCas9 could achieve comparable efficiency and specificity to SpCas9. Interestingly, the PAM of FrCas9 presents a palindromic sequence, which greatly expands its targeting scope. Due to the PAM sequence, FrCas9 possesses double editing-windows for base editor and could directly target the TATA-box in eukaryotic promoters for TATA-box related diseases. Together, our results broaden the understanding of CRISPR/Cas-mediated genome engineering and establish FrCas9 as a safe and efficient platform for wide applications in research, biotechnology and therapeutics.

Gene knock-out chain reaction enables high disruption efficiency of HPV18 E6/E7 genes in cervical cancer cells.

A genome editing tool targeting the high-risk human papillomavirus (HPV) oncogene is a promising therapeutic strategy to treat HPV-related cervical cancer. To improve gene knockout efficiency, we developed a gene knockout chain reaction (GKCR) method for continually generating mutagenic disruptions and used this method to disrupt the HPV18 E6 and E7 genes. We verified that the GKCR Cas9/guide RNA (gRNA) cassettes could integrated into the targeted loci via homology-independent targeted insertion (HITI). The qPCR results revealed that the GKCR method enabled a relatively higher Cas9/gRNA cassette insertion rate than a control method (the common CRISPR-Cas9 strategy). Tracking of Indels by DEcomposition (TIDE) assay results showed that the GKCR method produced a significantly higher percentage of insertions or deletions (indels) in the HPV18 E6 and E7 genes. Furthermore, by targeting the HPV18 E6/E7 oncogenes, we found that the GKCR method significantly upregulated the P53/RB proteins and inhibited the proliferation and motility of HeLa cells. The GKCR method significantly improved the gene knockout efficiency of the HPV18 E6/E7 oncogenes, which might provide new insights into treatment of HPV infection and related cervical cancer.

The comparison of ZFNs, TALENs, and SpCas9 by GUIDE-seq in HPV-targeted gene therapy.

Zinc-finger nucleases (ZFNs), transcription activator-like endonucleases (TALENs), and CRISPR-associated Cas9 endonucleases are three major generations of genome editing tools. However, no parallel comparison about the efficiencies and off-target activity of the three nucleases has been reported, which is critical for the final clinical decision. We for the first time developed the genome-wide unbiased identification of double-stranded breaks enabled by sequencing (GUIDE-seq) method in ZFNs and TALENs with novel bioinformatics algorithms to evaluate the off-targets. By targeting human papillomavirus 16 (HPV16), we compared the performance of ZFNs, TALENs, and SpCas9 in vivo. Our data showed that ZFNs with similar targets could generate distinct massive off-targets (287-1,856), and the specificity could be reversely correlated with the counts of middle "G" in zinc finger proteins (ZFPs). We also compared the TALENs with different N-terminal domains (wild-type [WT]/αN/ßN) and G recognition modules (NN/NH) and found the design (αN or NN) to improve the efficiency of TALEN inevitably increased off-targets. Finally, our results showed that SpCas9 was more efficient and specific than ZFNs and TALENs. Specifically, SpCas9 had fewer off-target counts in URR (SpCas9, n = 0; TALEN, n = 1; ZFN, n = 287), E6 (SpCas9, n = 0; TALEN, n = 7), and E7 (SpCas9, n = 4; TALEN, n = 36). Taken together, we suggest that for HPV gene therapies, SpCas9 is a more efficient and safer genome editing tool. Our off-target data could be used to improve the design of ZFNs and TALENs, and the universal in vivo off-target detection pipeline for three generations of artificial nucleases provided useful tools for genome engineering-based gene therapy.