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Zhou Y, Bi K, Xu Q, Liu Q, Zhao X, Ge Q, Lu Z. Ultrafast and Accurate DNA Storage and Reading Integrated System Via Microfluidic Magnetic Beads Polymerase Chain Reaction. ACS NANO 2025; 19:7306-7316. [PMID: 39946680 DOI: 10.1021/acsnano.4c17817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/26/2025]
Abstract
DNA storage is expected to tackle the dilemma faced by electronic information technology for the effective storage and management of massive amounts of data in the era of big data. Efficient and reliable data retrieval is crucial for DNA storage. However, it is still challenging to actualize DNA storage with fast and accurate readout capabilities, which play a key role in the practicality and reliability of DNA storage. In this study, an integrated system was constructed using homemade microfluidic PCR and DNA magnetic beads for fast and accurate DNA storage and reading with reproducibility. The homemade microfluidic PCR and DNA magnetic beads constructed for the random access of DNA storage have the advantages of short time and low bias named MMBP. The homemade DNA magnetic beads are low cost, stable, and reproducible. The integrated DNA storage and reading system integrated by MMBP can read information not only more accurately and quickly but also at a lower sequencing depth than traditional PCR. Overall, the MMBP-based DNA information storage system (MMBP-DIS) has the advantages of reducing the cost, decreasing the random access time to 10 min, and improving the reading accuracy and sensitivity. In the future, it can be integrated with DNA electrochemical synthesis to develop a fast and accurate portable microfluidic device for DNA synthesis-preservation-reading integration.
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Affiliation(s)
- Ying Zhou
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Kun Bi
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Qi Xu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Quanjun Liu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Xiangwei Zhao
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Qinyu Ge
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zuhong Lu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
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Zhou Y, Bi K, Ge Q, Lu Z. Advances and Challenges in Random Access Techniques for In Vitro DNA Data Storage. ACS APPLIED MATERIALS & INTERFACES 2024; 16:43102-43113. [PMID: 39110103 DOI: 10.1021/acsami.4c07235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/23/2024]
Abstract
With digital transformation and the general application of new technologies, data storage is facing new challenges with the demand for high-density loading of massive information. In response, DNA storage technology has emerged as a promising research direction. Efficient and reliable data retrieval is critical for DNA storage, and the development of random access technology plays a key role in its practicality and reliability. However, achieving fast and accurate random access functions has proven difficult for existing DNA storage efforts, which limits its practical applications in industry. In this review, we summarize the recent advances in DNA storage technology that enable random access functionality, as well as the challenges that need to be overcome and the current solutions. This review aims to help researchers in the field of DNA storage better understand the importance of the random access step and its impact on the overall development of DNA storage. Furthermore, the remaining challenges and future research trends in random access technology of DNA storage are discussed, with the goal of providing a solid foundation for achieving random access in DNA storage under large-scale data conditions.
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Affiliation(s)
- Ying Zhou
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Kun Bi
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Qinyu Ge
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zuhong Lu
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
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Zhou Y, Yang Y, Qi T, Hou Z, Ge Q, Lu Z. Transcriptome Study of rd1Mouse Brain and Association with Parkinson's Disease. ACS OMEGA 2024; 9:25756-25765. [PMID: 38911794 PMCID: PMC11191077 DOI: 10.1021/acsomega.3c09938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 05/10/2024] [Accepted: 05/24/2024] [Indexed: 06/25/2024]
Abstract
Degeneration of the retina is intrinsically associated with the pathogenesis and progression of neurodegenerative diseases. However, the cellular and molecular mechanisms underlying the association between neurodegeneration and retinal degeneration are still under exploration due to the complexity of the connectivity network of the nervous system. In this study, RNA-seq data from the brains of model retinitis pigmentosa (RP) mice and previously studied Parkinson's disease (PD) mice were analyzed to explore the commonalities between retinal degenerative and neurodegenerative diseases. Differentially expressed genes in RP were compared with neurodegenerative disease-related genes and intersecting genes were identified, including Cnr1 and Septin14. These genes were verified by quantitative real-time reverse transcription PCR and Western blotting experiments. The key proteins CNR1 and SEPTIN14 were found to be potential cotherapeutic targets for retinal degeneration and neurodegenerative disease. In conclusion, understanding the commonalities between retinal degenerative diseases and neurodegenerative processes in the brain will not only facilitate the interpretation of the underlying pathomechanisms but also contribute to early diagnosis and the development of new therapeutic strategies.
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Affiliation(s)
- Ying Zhou
- State Key Laboratory of Digital
Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Yuwei Yang
- State Key Laboratory of Digital
Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Ting Qi
- State Key Laboratory of Digital
Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zhuoran Hou
- State Key Laboratory of Digital
Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Qinyu Ge
- State Key Laboratory of Digital
Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zuhong Lu
- State Key Laboratory of Digital
Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
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Zhou Y, Qi T, Yang Y, Li Z, Hou Z, Zhao X, Ge Q, Lu Z. Effect of Different Staining Methods on Brain Cryosections. ACS Chem Neurosci 2024; 15:2243-2252. [PMID: 38779816 DOI: 10.1021/acschemneuro.4c00069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024] Open
Abstract
Staining frozen sections is often required to distinguish cell types for spatial transcriptomic studies of the brain. The impact of the staining methods on the RNA integrity of the cells becomes one of the limitations of spatial transcriptome technology with microdissection. However, there is a lack of systematic comparisons of different staining modalities for the pretreatment of frozen sections of brain tissue as well as their effects on transcriptome sequencing results. In this study, four different staining methods were analyzed for their effect on RNA integrity in frozen sections of brain tissue. Subsequently, differences in RNA quality in frozen sections under different staining conditions and their impact on transcriptome sequencing results were assessed by RNA-seq. As one of the most commonly used methods for staining pathological sections, HE staining seriously affects the RNA quality of frozen sections of brain tissue. In contrast, the homemade cresyl violet staining method developed in this study has the advantages of short staining time, low cost, and less RNA degradation. The homemade cresyl violet staining proposed in this study can be applied instead of HE staining as an advance staining step for transcriptome studies in frozen sections of brain tissue. In the future, this staining method may be suitable for wide application in brain-related studies of frozen tissue sections. Moreover, it is expected to become a routine step for staining cells before sampling in brain science.
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Affiliation(s)
- Ying Zhou
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Ting Qi
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Yuwei Yang
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zhihui Li
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zhuoran Hou
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Xiangwei Zhao
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Qinyu Ge
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zuhong Lu
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
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Zhou Y, Qi T, Pan M, Tu J, Zhao X, Ge Q, Lu Z. Deep-Cloud: A Deep Neural Network-Based Approach for Analyzing Differentially Expressed Genes of RNA-seq Data. J Chem Inf Model 2024; 64:2302-2310. [PMID: 37682833 DOI: 10.1021/acs.jcim.3c00766] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/10/2023]
Abstract
Presently, the field of analyzing differentially expressed genes (DEGs) of RNA-seq data is still in its infancy, with new approaches constantly being proposed. Taking advantage of deep neural networks to explore gene expression information on RNA-seq data can provide a novel possibility in the biomedical field. In this study, a novel approach based on a deep learning algorithm and cloud model was developed, named Deep-Cloud. Its main advantage is not only using a convolutional neural network and long short-term memory to extract original data features and estimate gene expression of RNA-seq data but also combining the statistical method of the cloud model to quantify the uncertainty and carry out in-depth analysis of the DEGs between the disease groups and the control groups. Compared with traditional analysis software of DEGs, the Deep-cloud model further improves the sensitivity and accuracy of obtaining DEGs from RNA-seq data. Overall, the proposed new approach Deep-cloud paves a new pathway for mining RNA-seq data in the biomedical field.
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Affiliation(s)
- Ying Zhou
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Ting Qi
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Min Pan
- School of Medicine, Southeast University, Nanjing 210097, China
| | - Jing Tu
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Xiangwei Zhao
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Qinyu Ge
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zuhong Lu
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
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Shi H, Ge Q, Pan M, Sheng Y, Qi T, Zhou Y, Sun Y, Bai Y, Cai L. Agarose amplification based sequencing characterization cell-free RNA in preimplantation spent embryo medium. Anal Chim Acta 2024; 1296:342331. [PMID: 38401939 DOI: 10.1016/j.aca.2024.342331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 02/01/2024] [Accepted: 02/03/2024] [Indexed: 02/26/2024]
Abstract
BACKGROUND The cell-free RNA (cf-RNA) of spent embryo medium (SEM) has aroused a concern of academic and clinical researchers for its potential use in non-invasive embryo screening. However, comprehensive characterization of cf-RNA from SEM still presents significant technical challenges, primarily due to the limited volume of SEM. Hence, there is urgently need to a small input liquid volume and ultralow amount of cf-RNA library preparation method to unbiased cf-RNA sequencing from SEM. (75) RESULT: Here, we report a high sensitivity agarose amplification-based cf-RNA sequencing method (SEM-Acf) for human preimplantation SEM cf-RNA analysis. It is a cf-RNA sequencing library preparation method by adding agarose amplification. The agarose amplification sensitivity (0.005 pg) and efficiency (105.35 %) were increased than that of without agarose addition (0.45 pg and 96.06 %) by ∼ 90 fold and 9.29 %, respectively. Compared with SMART sequencing (SMART-seq), the correlation of gene expression was stronger in different SEM samples by using SEM-Acf. The cf-RNA number of detected and coverage uniformity of 3' end were significantly increased. The proportion of 5' end adenine, alternative splicing events and short fragments (<400 bp) were increased. It is also found that 4-mer end motifs of cf-RNA fragments was significantly differences between different embryonic stage by day3 spent cleavage medium and day5/6 spent blastocyst medium. (141) SIGNIFICANCE: This study established an efficient SEM amplification and library preparation method. Additionally, we successfully described the characterizations of SEM cf-RNA in preimplantation embryo using SEM-Acf, including expression features and fragment lengths. SEM-Acf facilitates the exploration of cf-RNA as a noninvasive embryo screening biomarker, and opens up potential clinical utilities of small input liquid volume and ultralow amount cf-RNA sequencing. (59).
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Affiliation(s)
- Huajuan Shi
- State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Qinyu Ge
- State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China.
| | - Min Pan
- School of Medicine, Southeast University, Nanjing, 210097, China
| | - Yuqi Sheng
- State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Ting Qi
- State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Ying Zhou
- State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Yuqing Sun
- State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Yunfei Bai
- State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Lingbo Cai
- Clinical Center of Reproductive Medicine, State Key Laboratory of Reproductive Medicine, First Affiliated Hospital, Nanjing Medical University, Nanjing, China.
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Ma Y, Ma X, Bu L, Shan J, Liu D, Zhang L, Qi X, Chu Y, Wu H, Zou B, Zhou G. Flap Endonuclease-Induced Steric Hindrance Change Enables the Construction of Multiplex and Versatile Lateral Flow Strips for DNA Detection. Anal Chem 2022; 94:14725-14733. [PMID: 36223239 DOI: 10.1021/acs.analchem.2c03143] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A lateral flow strip (LFS) is an ideal tool for point-of-care testing (POCT), but traditional LFSs cannot be used for multiplex detection. Herein, a multiplex and versatile LFS based on flap endonuclease 1 (FEN1)-induced steric hindrance change (FISH-LFS) is proposed. In this method, multiplex PCR coupled with cascade invasive reactions was employed to yield single-stranded flaps, which were target-specific but independent of target sequences. Then, the amplicons were applied for FISH-LFS, and the single-stranded flaps would be efficiently captured by the complementary LFS-probes at different test lines. As flaps were cleaved from the specially designed hairpin probes, competition among flaps and hairpin probes would occur in capturing the probes at test lines. We enabled the hairpin probes to flow through the test lines while the flaps to stay at the test lines by making use of the difference in steric hindrance between hairpin probes and flaps. The assay is able to detect as low as two copies of blood pathogens (HBV, HCV, and HIV), to pick up as low as 0.1% mutants from wild-type gDNA, and to genotype 200 copies of SARS-CoV-2 variants α and β within 75 min at a conventional PCR engine. As the method is free of dye, a portable PCR engine could be used for a cost-effective multiplex detection on site. Results using an ultrafast mobile PCR system for FISH-LFS showed that as fast as 30 min was achieved for detecting three pathogens (HBV, HCV, and HIV) in blood, very suitable for POCT of pathogen screening. The method is convenient in operation, simple in instrumentation, specific in genotyping, and very easy in setting up multiplex POCT assays.
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Affiliation(s)
- Yi Ma
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Xueping Ma
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Li Bu
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Jingwen Shan
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Danni Liu
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
| | - Likun Zhang
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Xiemin Qi
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Yanan Chu
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China
| | - Haiping Wu
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China.,School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Bingjie Zou
- Key Laboratory of Drug Quality Control and Pharmacovigilance of Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Guohua Zhou
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, China.,School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China.,School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China.,School of Pharmacy, Nanjing Medical University, Nanjing 211166, China
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