1
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Abdel-Hady GN, Hino T, Murakami H, Miwa A, Thi Thuy Cao L, Kuroki T, Nimura-Matsune K, Ikeda T, Ishida T, Funabashi H, Watanabe S, Kuroda A, Hirota R. Laboratory evolution and characterization of nitrate-resistant phosphite dehydrogenase (PtxD) for enhanced cyanobacterial cultivation. J Biotechnol 2025; 402:59-68. [PMID: 40086668 DOI: 10.1016/j.jbiotec.2025.03.008] [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: 11/15/2024] [Revised: 02/28/2025] [Accepted: 03/08/2025] [Indexed: 03/16/2025]
Abstract
Phosphite dehydrogenase (PtxD) catalyzes NAD+-dependent oxidation of phosphite (Pt) to phosphate (Pi), offering various biotechnological applications, such as the creation of Pt-dependency for the biological containment of genetically modified organisms. Previously, we established a Pt-dependent cyanobacterial strain (RH714) by expressing PtxD and a reduced phosphorous compound-specific transporter (HtxBCDE) in Synechococcus elongatus PCC 7942 devoid of its endogenous Pi transporters. This strain demonstrated strict Pt dependency but failed to grow in unbuffered BG-11 medium supplemented with 2 % CO2 owing to medium acidification below approximately pH 6.5. The present study aimed to overcome this limitation by passaging the RH714 strain in an unbuffered growth medium, resulting in mutants capable of growing without buffering. The mutant strains carried a Gly157Ser mutation in the Rossmann fold domain of PtxD, leading to approximately five- and eight-fold higher Km values for NAD+ and Pt, respectively, compared with the wild-type enzyme. Interestingly, PtxDG157S exhibited enhanced resistance to nitrate, a major component of BG-11, suggesting that reduced substrate affinity mitigates nitrate inhibition at lower pH levels. Further kinetic analysis revealed that nitrate inhibits wild-type PtxD through an uncompetitive mechanism, targeting the enzyme-substrate complex at an allosteric site. Consequently, the PtxDG157S mutation reduces nitrate binding, facilitating sustained growth of Pt-dependent strains under conditions without pH buffering. These findings imply that PtxDG157S could significantly enhance the applicability of Pt-dependent cyanobacterial strain.
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Affiliation(s)
- Gamal Nasser Abdel-Hady
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan; Department of Genetics, Faculty of Agriculture, Minia University, Minia, Egypt
| | - Tomohito Hino
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan
| | - Hiroki Murakami
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan
| | - Akari Miwa
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan
| | - Linh Thi Thuy Cao
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan
| | - Tomomi Kuroki
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan
| | | | - Takeshi Ikeda
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan
| | - Takenori Ishida
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan
| | - Hisakage Funabashi
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan; Seto Inland Sea Carbon-neutral Research Center, Hiroshima University, Japan
| | - Satoru Watanabe
- Department of Bioscience, Tokyo University of Agriculture, Tokyo, Japan
| | - Akio Kuroda
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan; Seto Inland Sea Carbon-neutral Research Center, Hiroshima University, Japan
| | - Ryuichi Hirota
- Unit of Biotechnology, Division of Biological and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University, Hiroshima, Japan; Seto Inland Sea Carbon-neutral Research Center, Hiroshima University, Japan.
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2
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Phan N, Li Y, Yang M, Liu F. Tear Fluid Derived Extracellular Vesicles for New Biomarker Discovery. Ocul Surf 2025:S1542-0124(25)00062-X. [PMID: 40368029 DOI: 10.1016/j.jtos.2025.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2025] [Revised: 04/23/2025] [Accepted: 05/05/2025] [Indexed: 05/16/2025]
Abstract
Various cell types release extracellular vesicles (EVs) containing proteins, DNA, and RNA essential for intercellular communication. The bioactive molecules from EVs can reflect disease status and monitor progression, while their communication abilities suggest therapeutic potential. We will review various EV isolation methods, EV-enriched fluids, and studies analyzing differential mi-RNA and protein levels extracted from EVs. Specifically, tear-derived EVs, which protect their molecular content and allow for real-time monitoring of ocular conditions such as Dry Eye Disease (DED), Sjögren's disease (SJD), Ocular graft-versus-host disease (oGVHD), and Diabetic Retinopathy (DR), which all currently remain undiagnosed in patients. EVs also provide potential as carriers for gene transfer, and mesenchymal stem cell (MSCs)-derived EVs are shown to be immunomodulatory, demonstrating promise for autoimmune ocular diseases. Through the multi-omic analysis of tear-fluid content, EVs are promising biomarkers and therapeutic agents in ocular diseases.
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Affiliation(s)
- Natalie Phan
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, CA, 94720, USA
| | - Yi Li
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Menglu Yang
- Department of Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, MA, 02114, USA.
| | - Fei Liu
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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3
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Mao X, Wang J, Xu J, Xu P, Hu H, Li L, Zhang Z, Song Y. Current diagnosing strategies for Mycobacterium tuberculosis and its drug resistance: a review. J Appl Microbiol 2025; 136:lxaf100. [PMID: 40343775 DOI: 10.1093/jambio/lxaf100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2025] [Revised: 04/21/2025] [Accepted: 05/08/2025] [Indexed: 05/11/2025]
Abstract
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), remains a major global health threat, compounded by the rise of extensively drug-resistant (XDR) and multidrug-resistant (MDR) strains. This review critically examines the current landscape of laboratory diagnostic methods for MTB, encompassing both established techniques and recent advancements. We explore the growth and genetic characteristics of MTB that underpin drug resistance development and detection. We then provide a comparative analysis of smear microscopy, culture-based methods, antigen detection, molecular diagnostics (including nucleic acid amplification tests and whole-genome sequencing), spectroscopic techniques (such as Raman spectroscopy), and mass spectrometry-based approaches. Notably, this review focuses on pathogen-based diagnostic methods, excluding host immune response assays. The strengths and limitations of each method are evaluated in terms of sensitivity, specificity, turnaround time, cost-effectiveness, and suitability for resource-limited settings. Finally, we discuss the future of TB diagnostics, emphasizing the need for integrated, multi-modal platforms, the incorporation of artificial intelligence (AI) for enhanced data analysis, and the development of affordable, point-of-care testing to improve accessibility and impact in high-burden regions. Overcoming current diagnostic challenges is essential for improving patient outcomes and achieving global TB elimination goals.
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Affiliation(s)
- Xin Mao
- Department of Chemistry, College of Sciences, Shanghai University, 99 Shangda Road, Baoshan District, Shanghai 200444, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, 88 Keling Road, Gaoxin District, Suzhou 215163, China
| | - Jingkai Wang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, 88 Keling Road, Gaoxin District, Suzhou 215163, China
- Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, United Kingdom
| | - Junchi Xu
- Department of Clinical Laboratory, The Fifth People's Hospital of Suzhou, 10 Guangqian Road, Xiangcheng District, Suzhou 215163, China
| | - Ping Xu
- Department of Clinical Laboratory, The Fifth People's Hospital of Suzhou, 10 Guangqian Road, Xiangcheng District, Suzhou 215163, China
| | - Huijie Hu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, 88 Keling Road, Gaoxin District, Suzhou 215163, China
- Division of Life Sciences and Medicine, School of Biomedical Engineering (Suzhou), University of Science and Technology of China, 88 Keling Road, Gaoxin District, Suzhou 215163, China
| | - Li Li
- Department of Chemistry, College of Sciences, Shanghai University, 99 Shangda Road, Baoshan District, Shanghai 200444, China
| | - Zhiqiang Zhang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, 88 Keling Road, Gaoxin District, Suzhou 215163, China
- Division of Life Sciences and Medicine, School of Biomedical Engineering (Suzhou), University of Science and Technology of China, 88 Keling Road, Gaoxin District, Suzhou 215163, China
| | - Yizhi Song
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, 88 Keling Road, Gaoxin District, Suzhou 215163, China
- Division of Life Sciences and Medicine, School of Biomedical Engineering (Suzhou), University of Science and Technology of China, 88 Keling Road, Gaoxin District, Suzhou 215163, China
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4
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Zhang Y, Chen Y, Hou C, Wang C, Mu C. Analysis of cDNA microarrays revealed the effects of mating on the ovary and hepatopancreas of female swimming crab (Portunus trituberculatus) during the late stage of ovarian development. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY. PART D, GENOMICS & PROTEOMICS 2025; 55:101520. [PMID: 40315711 DOI: 10.1016/j.cbd.2025.101520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2024] [Revised: 04/21/2025] [Accepted: 04/21/2025] [Indexed: 05/04/2025]
Abstract
To investigate the differences in the ovaries and hepatopancreas of mated and unmated female Portunus trituberculatus during late ovarian development. This study constructed a cDNA library of the P. trituberculatus. The 113,858 sequences were obtained from the cDNA library and the NCBI database, and a total of 109,533 probes were designed for the cDNA microarray. Microarray analysis was performed on ovaries and hepatopancreas of mated and unmated crabs after six months of aquaculture. A total of 2072 differentially expressed genes (DEGs) were identified in the ovaries, and 1897 DEGs were identified in the hepatopancreas. Enrichment analysis revealed two differential pathways in the ovary, including Hippo signaling pathway and endocytosis, and fourteen differential pathways in the hepatopancreas, including insect hormone biosynthesis and glycolysis. The findings suggest that during late ovarian development, the ovaries focus on efficient energy use, with enhanced foreign substance recognition and a decrease in Vitellogenin (Vn) synthesis/absorption. In the hepatopancreas, there is an emphasis on nerve signal conduction, hormonal regulation, and energy metabolism. The immune and antioxidant capacities of both tissues showed fluctuations. In conclusion, the primary purpose of the P. trituberculatus during this stage is not to promote rapid ovarian development but to regulate energy intake, utilization, and maintain overall physiological stability. This study could provide valuable insights for the optimized breeding of female P. trituberculatus during late ovarian development.
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Affiliation(s)
- Yi Zhang
- Key Laboratory of Marine Biotechnology of Zhejiang Province, School of Marine Sciences, Ningbo University, Ningbo, China
| | - Yiner Chen
- Key Laboratory of Marine Biotechnology of Zhejiang Province, School of Marine Sciences, Ningbo University, Ningbo, China
| | - Congcong Hou
- Key Laboratory of Marine Biotechnology of Zhejiang Province, School of Marine Sciences, Ningbo University, Ningbo, China.
| | - Chunlin Wang
- Key Laboratory of Marine Biotechnology of Zhejiang Province, School of Marine Sciences, Ningbo University, Ningbo, China
| | - Changkao Mu
- Key Laboratory of Marine Biotechnology of Zhejiang Province, School of Marine Sciences, Ningbo University, Ningbo, China
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5
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Singh A, Yasheshwar, Kaushik NK, Kala D, Nagraik R, Gupta S, Kaushal A, Walia Y, Dhir S, Noorani MS. Conventional and cutting-edge advances in plant virus detection: emerging trends and techniques. 3 Biotech 2025; 15:100. [PMID: 40151342 PMCID: PMC11937476 DOI: 10.1007/s13205-025-04253-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2024] [Accepted: 02/20/2025] [Indexed: 03/29/2025] Open
Abstract
Plant viruses pose a significant threat to global agriculture. For a long time, conventional methods including detection based on visual symptoms, host range investigations, electron microscopy, serological assays (e.g., ELISA, Western blotting), and nucleic acid-based techniques (PCR, RT-PCR) have been used for virus identification. With increased sensitivity, speed, and specificity, new technologies like loop-mediated isothermal amplification (LAMP), high-throughput sequencing (HTS), nanotechnology-based biosensors, and CRISPR diagnostics have completely changed the way plant viruses are detected. Recent advances in detection techniques integrate artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) for real-time monitoring. Innovations like hyperspectral imaging, deep learning, and cloud-based IoT platforms further support disease identification and surveillance. Nanotechnology-based lateral flow assays and CRISPR-Cas systems provide rapid, field-deployable solutions. Despite these advancements, challenges such as sequence limitations, multiplexing constraints, and environmental concerns remain. Future research should focus on refining portable on-site diagnostic kits, optimizing nanotechnology applications, and enhancing global surveillance systems. Interdisciplinary collaboration across molecular biology, bioinformatics, and engineering is essential to developing scalable, cost-effective solutions for plant virus detection, ensuring agricultural sustainability and ecosystem protection.
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Affiliation(s)
- Anjana Singh
- Plant Molecular Virology Lab, Department of Botany, School of Chemical and Life Sciences, Jamia Hamdard, New Delhi, 110062 India
- Deshbandhu College, University of Delhi, New Delhi, 110019 India
| | - Yasheshwar
- Department of Botany, Acharya Narendra Dev College, University of Delhi, New Delhi, 110019 India
| | - Naveen K. Kaushik
- Department of Industrial Biotechnology, College of Biotechnology, Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana 125004 India
| | - Deepak Kala
- NL-11 Centera Tetrahertz Laboratory, Institute of High-Pressure Physics, Polish Academy of Sciences, 29/37 Sokolowska Street, 01142 Warsaw, Poland
| | - Rupak Nagraik
- School of Bioengineering and Food Technology, Faculty of Applied Sciences and Biotechnology, Shoolini University, Solan, Himachal Pradesh 173229 India
| | - Shagun Gupta
- Department of Bio-Sciences and Technology, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, 133207 India
| | - Ankur Kaushal
- Department of Bio-Sciences and Technology, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, 133207 India
| | - Yashika Walia
- Department of Bio-Sciences and Technology, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, 133207 India
| | - Sunny Dhir
- Department of Bio-Sciences and Technology, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, 133207 India
| | - Md Salik Noorani
- Plant Molecular Virology Lab, Department of Botany, School of Chemical and Life Sciences, Jamia Hamdard, New Delhi, 110062 India
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6
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Kim YK, Ramalho-Santos M. 20 years of stemness: From stem cells to hypertranscription and back. Stem Cell Reports 2025; 20:102406. [PMID: 39919752 PMCID: PMC11960510 DOI: 10.1016/j.stemcr.2025.102406] [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: 11/01/2024] [Revised: 01/08/2025] [Accepted: 01/09/2025] [Indexed: 02/09/2025] Open
Abstract
Transcriptional profiling of stem cells came of age at the beginning of the century with the use of microarrays to analyze cell populations in bulk. Since then, stem cell transcriptomics has become increasingly sophisticated, notably with the recent widespread use of single-cell RNA sequencing. Here, we provide a perspective on how an early signature of genes upregulated in embryonic and adult stem cells, identified using microarrays over 20 years ago, serendipitously led to the recent discovery that stem/progenitor cells across organs are in a state of hypertranscription, a global elevation of the transcriptome. Looking back, we find that the 2002 stemness signature is a robust marker of stem cell hypertranscription, even though it was developed well before it was known what hypertranscription meant or how to detect it. We anticipate that studies of stem cell hypertranscription will be rich in novel insights in physiological and disease contexts for years to come.
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Affiliation(s)
- Yun-Kyo Kim
- Program in Developmental and Stem Cell Biology, Hospital for Sick Children, Toronto ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto ON M5G 1X5, Canada.
| | - Miguel Ramalho-Santos
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto ON M5T 3L9, Canada; Department of Molecular Genetics, University of Toronto, Toronto ON M5G 1X5, Canada.
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7
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Rodov A, Baniadam H, Zeiser R, Amit I, Yosef N, Wertheimer T, Ingelfinger F. Towards the Next Generation of Data-Driven Therapeutics Using Spatially Resolved Single-Cell Technologies and Generative AI. Eur J Immunol 2025; 55:e202451234. [PMID: 39964048 PMCID: PMC11834372 DOI: 10.1002/eji.202451234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Revised: 01/28/2025] [Accepted: 02/03/2025] [Indexed: 02/21/2025]
Abstract
Recent advances in multi-omics and spatially resolved single-cell technologies have revolutionised our ability to profile millions of cellular states, offering unprecedented opportunities to understand the complex molecular landscapes of human tissues in both health and disease. These developments hold immense potential for precision medicine, particularly in the rational design of novel therapeutics for treating inflammatory and autoimmune diseases. However, the vast, high-dimensional data generated by these technologies present significant analytical challenges, such as distinguishing technical variation from biological variation or defining relevant questions that leverage the added spatial dimension to improve our understanding of tissue organisation. Generative artificial intelligence (AI), specifically variational autoencoder- or transformer-based latent variable models, provides a powerful and flexible approach to addressing these challenges. These models make inferences about a cell's intrinsic state by effectively identifying complex patterns, reducing data dimensionality and modelling the biological variability in single-cell datasets. This review explores the current landscape of single-cell and spatial multi-omics technologies, the application of generative AI in data analysis and modelling and their transformative impact on our understanding of autoimmune diseases. By combining spatial and single-cell data with advanced AI methodologies, we highlight novel insights into the pathogenesis of autoimmune disorders and outline future directions for leveraging these technologies to achieve the goal of AI-powered personalised medicine.
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Affiliation(s)
- Avital Rodov
- Department of Systems ImmunologyWeizmann Institute of ScienceRehovotIsrael
| | | | - Robert Zeiser
- Department of Internal Medicine IMedical Center‐University of FreiburgFreiburgGermany
| | - Ido Amit
- Department of Systems ImmunologyWeizmann Institute of ScienceRehovotIsrael
| | - Nir Yosef
- Department of Systems ImmunologyWeizmann Institute of ScienceRehovotIsrael
| | - Tobias Wertheimer
- Department of Internal Medicine IMedical Center‐University of FreiburgFreiburgGermany
| | - Florian Ingelfinger
- Department of Systems ImmunologyWeizmann Institute of ScienceRehovotIsrael
- Department of Internal Medicine IMedical Center‐University of FreiburgFreiburgGermany
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8
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Hasuike A, Easter QT, Clark D, Byrd KM. Application of Single-Cell Genomics to Animal Models of Periodontitis and Peri-Implantitis. J Clin Periodontol 2025; 52:268-279. [PMID: 39695834 PMCID: PMC11743042 DOI: 10.1111/jcpe.14093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Revised: 11/13/2024] [Accepted: 11/25/2024] [Indexed: 12/20/2024]
Abstract
AIMS This narrative review aims to synthesize current knowledge on integrating single-cell genomics technologies with animal models of periodontitis and peri-implantitis. REVIEW Single-cell RNA sequencing (scRNAseq) reveals cellular heterogeneity and specific cell roles in periodontitis and peri-implantitis, overcoming the limitations of bulk RNA sequencing. Under controlled conditions and genetic manipulation, animal models facilitate studying disease progression, gene functions and systemic disease links, aiding targeted therapy development. Knockout models have started to elucidate the impact of genetic mutations on periodontal disease and host responses. scRNAseq in animal models has been used to examine connections between periodontitis and systemic diseases, revealing altered immune environments and cellular interactions. Emerging studies are now applying these methods to animal models of peri-implantitis. Integrating these datasets into single-cell and spatially resolved atlases will enable future meta-analyses, providing deeper insights into disease mechanisms considering factors such as sex, strain, and age. CONCLUSIONS Integrating scRNAseq with animal models advances the understanding of periodontitis and peri-implantitis pathogenesis and precision therapies. The combined use of single-cell and spatial genomics and scRNAseq will further enhance data insights significantly for drug discovery and preclinical testing, making these technologies pivotal in validating animal models and translating findings into clinical practice.
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Affiliation(s)
- Akira Hasuike
- Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology ResearchADA Science & Research InstituteGaithersburgMarylandUSA
- Department of PeriodontologyNihon University School of DentistryTokyoJapan
| | - Quinn T. Easter
- Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology ResearchADA Science & Research InstituteGaithersburgMarylandUSA
- Department of Oral and Craniofacial Molecular BiologyVirginia Commonwealth University School of DentistryRichmondVirginiaUSA
| | - Daniel Clark
- Department of Periodontics and Preventive DentistryUniversity of Pittsburgh School of Dental MedicinePittsburghPennsylvaniaUSA
| | - Kevin M. Byrd
- Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology ResearchADA Science & Research InstituteGaithersburgMarylandUSA
- Department of Oral and Craniofacial Molecular BiologyVirginia Commonwealth University School of DentistryRichmondVirginiaUSA
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9
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Liu Y, Rao S, Hoskins I, Geng M, Zhao Q, Chacko J, Ghatpande V, Qi K, Persyn L, Wang J, Zheng D, Zhong Y, Park D, Cenik ES, Agarwal V, Ozadam H, Cenik C. Translation efficiency covariation across cell types is a conserved organizing principle of mammalian transcriptomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.08.11.607360. [PMID: 39149359 PMCID: PMC11326257 DOI: 10.1101/2024.08.11.607360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Characterization of shared patterns of RNA expression between genes across conditions has led to the discovery of regulatory networks and novel biological functions. However, it is unclear if such coordination extends to translation, a critical step in gene expression. Here, we uniformly analyzed 3,819 ribosome profiling datasets from 117 human and 94 mouse tissues and cell lines. We introduce the concept of Translation Efficiency Covariation (TEC), identifying coordinated translation patterns across cell types. We nominate potential mechanisms driving shared patterns of translation regulation. TEC is conserved across human and mouse cells and helps uncover gene functions. Moreover, our observations indicate that proteins that physically interact are highly enriched for positive covariation at both translational and transcriptional levels. Our findings establish translational covariation as a conserved organizing principle of mammalian transcriptomes.
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Affiliation(s)
- Yue Liu
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Shilpa Rao
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Ian Hoskins
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Michael Geng
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Qiuxia Zhao
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Jonathan Chacko
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Vighnesh Ghatpande
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Kangsheng Qi
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Logan Persyn
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Jun Wang
- mRNA Center of Excellence, Sanofi, Waltham, MA 02451, USA
| | - Dinghai Zheng
- mRNA Center of Excellence, Sanofi, Waltham, MA 02451, USA
| | - Yochen Zhong
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Dayea Park
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Elif Sarinay Cenik
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Vikram Agarwal
- mRNA Center of Excellence, Sanofi, Waltham, MA 02451, USA
| | - Hakan Ozadam
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
- Present address: Sail Biomedicines, Cambridge, MA, 02141, USA
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10
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Ayling K, Vedhara K, Fairclough L. Measuring Vaccine Responses in the Multiplex Era. Methods Mol Biol 2025; 2868:149-162. [PMID: 39546230 DOI: 10.1007/978-1-0716-4200-9_9] [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: 11/17/2024]
Abstract
Vaccine studies in psychoneuroimmunology (PNI) provide insight into biopsychosocial interactions and their role in infectious diseases. Methodologies to measure vaccine responses are therefore of critical importance for PNI researchers. In this chapter, traditional and modern immunoassays for the assessment of vaccine responses are discussed, highlighting how multiplex techniques provide researchers with greater capacity and opportunity for novel research relating to vaccine outcomes.
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Affiliation(s)
- Kieran Ayling
- School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Kavita Vedhara
- School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Lucy Fairclough
- School of Life Sciences, University of Nottingham, Nottingham, UK.
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11
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Rani S, Ramesh V, Khatoon M, Shijili M, Archana CA, Anand J, Sagar N, Sekar YS, Patil AV, Palavesam A, Barman NN, Patil SS, Hemadri D, Suresh KP. Identification of molecular and cellular infection response biomarkers associated with anthrax infection through comparative analysis of gene expression data. Comput Biol Med 2025; 184:109431. [PMID: 39556915 DOI: 10.1016/j.compbiomed.2024.109431] [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: 07/25/2024] [Revised: 10/16/2024] [Accepted: 11/11/2024] [Indexed: 11/20/2024]
Abstract
Bacillus anthracis, a gram-positive bacillus capable of forming spores, causes anthrax in mammals, including humans, and is recognized as a potential biological weapon agent. The diagnosis of anthrax is challenging due to variable symptoms resulting from exposure and infection severity. Despite the availability of a licensed vaccines, their limited long-term efficacy underscores the inadequacy of current human anthrax vaccines, highlighting the urgent need for next-generation alternatives. Our study aimed to identify molecular biomarkers and essential biological pathways for the early detection and accurate diagnosis of human anthrax infection. Using a comparative analysis of Bacillus anthracis gene expression data from the Gene Expression Omnibus (GEO) database, this cost-effective approach enables the identification of shared differentially expressed genes (DEGs) across separate microarray datasets without additional hybridization. Three microarray datasets (GSE34407, GSE14390, and GSE12131) of B. anthracis-infected human cell lines were analyzed via the GEO2R tool to identify shared DEGs. We identified 241 common DEGs (70 upregulated and 171 downregulated) from cell lines treated similarly to lethal toxins. Additionally, 10 common DEGs (5 upregulated and 5 downregulated) were identified across different treatments (lethal toxins and spores) and cell lines. Network meta-analysis identified JUN and GATAD2A as the top hub genes for overexpression, and NEDD4L and GULP1 for underexpression. Furthermore, prognostic analysis and SNP detection of the two identified upregulated hub genes were carried out in conjunction with machine learning classification models, with SVM yielding the best classification accuracy of 87.5 %. Our comparative analysis of Bacillus anthracis infection revealed striking similarities in gene expression 241 profiles across diverse datasets, despite variations in treatments and cell lines. These findings underscore how anthrax infection activates shared genes across different cell types, emphasizing this approach in the discovery of novel gene markers. These markers offer insights into pathogenesis and may lead to more effective therapeutic strategies. By identifying these genetic indicators, we can advance the development of precise immunotherapies, potentially enhancing vaccine efficacy and treatment outcomes.
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Affiliation(s)
- Swati Rani
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - Varsha Ramesh
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - Mehnaj Khatoon
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - M Shijili
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - C A Archana
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - Jayashree Anand
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - N Sagar
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - Yamini S Sekar
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - Archana V Patil
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - Azhahianambi Palavesam
- Translational Research Platform for Veterinary Biologicals, Centre for Animal Health Studies, Tamil Nadu Veterinary and Animal Sciences University, Chennai, Tamil Nadu, 600051, India
| | - N N Barman
- College of Veterinary Science, Assam Agricultural University, Guwahati, Assam, 781001, India
| | - S S Patil
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - Diwakar Hemadri
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India
| | - K P Suresh
- ICAR-National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, 560064, India.
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12
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Fang Z, Peltz G. Twenty-first century mouse genetics is again at an inflection point. Lab Anim (NY) 2025; 54:9-15. [PMID: 39592878 PMCID: PMC11695262 DOI: 10.1038/s41684-024-01491-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 11/12/2024] [Indexed: 11/28/2024]
Abstract
The laboratory mouse has been the premier model organism for biomedical research owing to the availability of multiple well-characterized inbred strains, its mammalian physiology and its homozygous genome, and because experiments can be performed under conditions that control environmental variables. Moreover, its genome can be genetically modified to assess the impact of allelic variation on phenotype. Mouse models have been used to discover or test many therapies that are commonly used today. Mouse genetic discoveries are often made using genome-wide association study methods that compare allelic differences in panels of inbred mouse strains with their phenotypic responses. Here we examine changes in the methods used to analyze mouse genetic models of biomedical traits during the twenty-first century. To do this, we first examine where mouse genetics was before the first inflection point, which was just before the revolution in genome sequencing that occurred 20 years ago, and then describe the factors that have accelerated the pace of mouse genetic discovery. We focus on mouse genetic studies that have generated findings that either were translated to humans or could impact clinical medicine or drug development. We next explore how advances in computational capabilities and in DNA sequencing methodology during the past 20 years could enhance the ability of mouse genetics to produce solutions for twenty-first century public-health problems.
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Affiliation(s)
- Zhuoqing Fang
- Department of Anesthesia, Pain and Perioperative Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Gary Peltz
- Department of Anesthesia, Pain and Perioperative Medicine, Stanford University School of Medicine, Stanford, CA, USA.
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13
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Baumann A, Ahmadi N, Wolfien M. A Current Perspective of Medical Informatics Developments for a Clinical Translation of (Non-coding)RNAs and Single-Cell Technologies. Methods Mol Biol 2025; 2883:31-51. [PMID: 39702703 DOI: 10.1007/978-1-0716-4290-0_2] [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: 12/21/2024]
Abstract
The journey from laboratory research to clinical practice is marked by significant advancements in the fields of single-cell technologies and non-coding RNA (ncRNA) research. This convergence may reshape our approach to personalized medicine, offering groundbreaking insights and treatments in various clinical settings. This chapter discusses advancements in (nc)RNAs in the clinics, innovations in single-cell technologies and algorithms, and the impact on actual precision medicine, showing the integration of single-cell and ncRNA research can have a tangible impact on precision medicine. Case studies in Oncology, Immunology, and other fields demonstrate how these technologies can guide treatment decisions, tailor therapies to individual patients, and improve outcomes. This approach is particularly potent in addressing diseases with high inter- and intra-tumor heterogeneity. The final sections address standardization, data integration, and analysis challenges because the complexity and volume of data generated by single-cell and ncRNA research poses significant challenges. Medical Informatics is not just a support tool but could be seen as a pivotal component in advancing clinical applications of single-cell and ncRNA research by bridging the gap between bench and bedside. The future of personalized medicine depends on our ability to harness the power of these technologies, and Medical Informatics in combination with ncRNA and single-cell technologies may stand at the forefront of this endeavor.
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Affiliation(s)
- Alexandra Baumann
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany
| | - Najia Ahmadi
- Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Markus Wolfien
- Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
- Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Dresden/Leipzig, Germany.
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14
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Cipurko D, Ueda T, Mei L, Chevrier N. Repurposing large-format microarrays for scalable spatial transcriptomics. Nat Methods 2025; 22:145-155. [PMID: 39562752 PMCID: PMC11984966 DOI: 10.1038/s41592-024-02501-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 10/08/2024] [Indexed: 11/21/2024]
Abstract
Spatiomolecular analyses are key to study tissue functions and malfunctions. However, we lack profiling tools for spatial transcriptomics that are easy to adopt, low cost and scalable in terms of sample size and number. Here, we describe a method, Array-seq, to repurpose classical oligonucleotide microarrays for spatial transcriptomics profiling. We generate Array-seq slides from microarrays carrying custom-design probes that contain common sequences flanking unique barcodes at known coordinates. Then we perform a simple, two-step reaction that produces mRNA capture probes across all spots on the microarray. We demonstrate that Array-seq yields spatial transcriptomes with high detection sensitivity and localization specificity using histological sections from mouse tissues as test systems. Moreover, we show that the large surface area of Array-seq slides yields spatial transcriptomes (i) at high throughput by profiling multi-organ sections, (ii) in three dimensions by processing serial sections from one sample, and (iii) across whole human organs. Thus, by combining classical DNA microarrays and next-generation sequencing, we have created a simple and flexible platform for spatiomolecular studies of small-to-large specimens at scale.
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Affiliation(s)
- Denis Cipurko
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, USA
- Medical Scientist Training Program, University of Chicago, Chicago, IL, USA
| | - Tatsuki Ueda
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, USA
| | - Linghan Mei
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, USA
| | - Nicolas Chevrier
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, USA.
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15
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Kong W, Li T, Li Y, Zhang L, Xie J, Liu X. Transgenic Cotton Expressing ds AgCYP6CY3 Significantly Delays the Growth and Development of Aphis gossypii by Inhibiting Its Glycolysis and TCA Cycle. Int J Mol Sci 2024; 26:264. [PMID: 39796120 PMCID: PMC11720249 DOI: 10.3390/ijms26010264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Revised: 12/18/2024] [Accepted: 12/26/2024] [Indexed: 01/13/2025] Open
Abstract
In our previous research, we found that CYP6CY3 not only participates in the detoxification metabolism of neonicotinoid insecticides in cotton aphid but also affects their growth and development. However, how does transgenic cotton expressing dsAgCYP6CY3 affect the growth and development of cotton aphid? In this study, we combined transcriptome and metabolome to analyze how to inhibit the growth and development of cotton aphid treated with transgenic cotton expressing dsAgCYP6CY3-P1 (TG cotton). The results suggested that a total of 509 differentially expressed genes (DEGs) were identified based on the DESeq method, and a total of 431 differential metabolites (DAMs) were discovered using UPLC-MS in the metabolic analysis. Additionally, multiple DEGs and DAMs of glycolytic and The tricarboxylic acid (TCA) cycle pathways were significantly down-regulated. Pyruvate carboxylase (PC), citrate synthase (CS), malate dehydrogenase (MDH) enzyme activities and pyruvate content were reduced in cotton aphid treated with TG cotton. In addition, TG cotton could significantly decrease the total sugar content from the body and honeydew in cotton aphid. The above results indicated that TG cotton inhibited glycolysis and the TCA cycle, and this inhibition is consistent with previous studies showing that cotton aphid fed on TG cotton showed significantly reduced body length and weight as well as delayed molting. These findings provide a new strategy for reducing the transmission of viruses by cotton aphid honeydew, preventing fungal growth, mitigating impacts on normal photosynthesis and improving cotton quality.
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Affiliation(s)
| | | | | | | | | | - Xiaoning Liu
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China; (W.K.); (T.L.); (Y.L.); (L.Z.); (J.X.)
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16
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Dong H, Ma B, Meng Y, Wu Y, Liu Y, Zeng T, Huang J. GRNMOPT: Inference of gene regulatory networks based on a multi-objective optimization approach. Comput Biol Chem 2024; 113:108223. [PMID: 39340962 DOI: 10.1016/j.compbiolchem.2024.108223] [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: 06/17/2024] [Revised: 08/21/2024] [Accepted: 09/20/2024] [Indexed: 09/30/2024]
Abstract
BACKGROUND AND OBJECTIVE The reconstruction of gene regulatory networks (GRNs) stands as a vital approach in deciphering complex biological processes. The application of nonlinear ordinary differential equations (ODEs) models has demonstrated considerable efficacy in predicting GRNs. Notably, the decay rate and time delay are pivotal in authentic gene regulation, yet their systematic determination in ODEs models remains underexplored. The development of a comprehensive optimization framework for the effective estimation of these key parameters is essential for accurate GRN inference. METHOD This study introduces GRNMOPT, an innovative methodology for inferring GRNs from time-series and steady-state data. GRNMOPT employs a combined use of decay rate and time delay in constructing ODEs models to authentically represent gene regulatory processes. It incorporates a multi-objective optimization approach, optimizing decay rate and time delay concurrently to derive Pareto optimal sets for these factors, thereby maximizing accuracy metrics such as AUROC (Area Under the Receiver Operating Characteristic curve) and AUPR (Area Under the Precision-Recall curve). Additionally, the use of XGBoost for calculating feature importance aids in identifying potential regulatory gene links. RESULTS Comprehensive experimental evaluations on two simulated datasets from DREAM4 and three real gene expression datasets (Yeast, In vivo Reverse-engineering and Modeling Assessment [IRMA], and Escherichia coli [E. coli]) reveal that GRNMOPT performs commendably across varying network scales. Furthermore, cross-validation experiments substantiate the robustness of GRNMOPT. CONCLUSION We propose a novel approach called GRNMOPT to infer GRNs based on a multi-objective optimization framework, which effectively improves inference accuracy and provides a powerful tool for GRNs inference.
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Affiliation(s)
- Heng Dong
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Baoshan Ma
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China.
| | - Yangyang Meng
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Yiming Wu
- School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
| | - Yongjing Liu
- Biomedical big data center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Zhejiang University School of Medicine First Affiliated Hospital, Hangzhou 310003, China; Zhejiang University Cancer Center, Zhejiang University, Hangzhou 310058, China
| | - Tao Zeng
- Biomedical big data center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Zhejiang University School of Medicine First Affiliated Hospital, Hangzhou 310003, China; Zhejiang University Cancer Center, Zhejiang University, Hangzhou 310058, China
| | - Jinyan Huang
- Biomedical big data center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Zhejiang University School of Medicine First Affiliated Hospital, Hangzhou 310003, China; Zhejiang University Cancer Center, Zhejiang University, Hangzhou 310058, China.
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17
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Jerald I, Ravindran J, Babu MM. Fish in focus: Navigating organ damage assessment through analytical avenues - A comprehensive review. Toxicol Rep 2024; 13:101841. [PMID: 39717851 PMCID: PMC11665677 DOI: 10.1016/j.toxrep.2024.101841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Revised: 11/16/2024] [Accepted: 11/26/2024] [Indexed: 12/25/2024] Open
Abstract
Aquatic ecosystems, critical for biodiversity and food production, confront escalating threats from anthropogenic activities like pollution and climate change, impacting fish health. This review outlines various assays used to study organ damage in fish, ranging from traditional histopathology to advanced molecular and biochemical methods. The aim is to guide researchers in selecting suitable assays for their specific questions, considering the advantages and limitations of each technique. Covered methods include histopathological assessment, biomarker analysis, genotoxicity assays, oxidative stress indicators, and non-invasive imaging. The review explores their application in monitoring environmental stressors' impacts on fish organs, emphasizing emerging trends like omics technologies and non-destructive imaging for comprehensive assessments. These innovations hold promise for early detection and understanding the implications on fish populations and ecosystem health.
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Affiliation(s)
- Irine Jerald
- Department of Biotechnology, Rajalakshmi Engineering College, Thandalam, Chennai 602105, India
| | | | - Monica Muniendra Babu
- Department of Biotechnology, Rajalakshmi Engineering College, Thandalam, Chennai 602105, India
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18
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Kutchy NA, Morenikeji OB, Memili A, Ugur MR. Deciphering sperm functions using biological networks. Biotechnol Genet Eng Rev 2024; 40:3743-3767. [PMID: 36722689 DOI: 10.1080/02648725.2023.2168912] [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: 05/28/2022] [Indexed: 02/02/2023]
Abstract
The global human population is exponentially increasing, which requires the production of quality food through efficient reproduction as well as sustainable production of livestock. Lack of knowledge and technology for assessing semen quality and predicting bull fertility is hindering advances in animal science and food animal production and causing millions of dollars of economic losses annually. The intent of this systemic review is to summarize methods from computational biology for analysis of gene, metabolite, and protein networks to identify potential markers that can be applied to improve livestock reproduction, with a focus on bull fertility. We provide examples of available gene, metabolic, and protein networks and computational biology methods to show how the interactions between genes, proteins, and metabolites together drive the complex process of spermatogenesis and regulate fertility in animals. We demonstrate the use of the National Center for Biotechnology Information (NCBI) and Ensembl for finding gene sequences, and then use them to create and understand gene, protein and metabolite networks for sperm associated factors to elucidate global cellular processes in sperm. This study highlights the value of mapping complex biological pathways among livestock and potential for conducting studies on promoting livestock improvement for global food security.
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Affiliation(s)
- Naseer A Kutchy
- Department of Anatomy, Physiology and Pharmacology, School of Veterinary Medicine, St. George's University, St. George's, Grenada
- Department of Animal Sciences, School of Environmental and Biological Sciences Rutgers, The State University of New Jersey, New Brunswick, NJ, USA
| | - Olanrewaju B Morenikeji
- Division of Biological and Health Sciences, University of Pittsburgh at Bradford, Bradford, PA, USA
| | - Aylin Memili
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
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19
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Wu J, Koelzer VH. Towards generative digital twins in biomedical research. Comput Struct Biotechnol J 2024; 23:3481-3488. [PMID: 39435342 PMCID: PMC11491725 DOI: 10.1016/j.csbj.2024.09.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2024] [Revised: 09/30/2024] [Accepted: 09/30/2024] [Indexed: 10/23/2024] Open
Abstract
Digital twins in biomedical research, i.e. virtual replicas of biological entities such as cells, organs, or entire organisms, hold great potential to advance personalized healthcare. As all biological processes happen in space, there is a growing interest in modeling biological entities within their native context. Leveraging generative artificial intelligence (AI) and high-volume biomedical data profiled with spatial technologies, researchers can recreate spatially-resolved digital representations of a physical entity with high fidelity. In application to biomedical fields such as computational pathology, oncology, and cardiology, these generative digital twins (GDT) thus enable compelling in silico modeling for simulated interventions, facilitating the exploration of 'what if' causal scenarios for clinical diagnostics and treatments tailored to individual patients. Here, we outline recent advancements in this novel field and discuss the challenges and future research directions.
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Affiliation(s)
- Jiqing Wu
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Viktor H. Koelzer
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
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20
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Tyszka AS, Larson DA, Walker JF. Sequencing historical RNA: unrealized potential to increase understanding of the plant tree of life. TRENDS IN PLANT SCIENCE 2024:S1360-1385(24)00305-4. [PMID: 39613559 DOI: 10.1016/j.tplants.2024.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 10/22/2024] [Accepted: 11/04/2024] [Indexed: 12/01/2024]
Abstract
Recent studies have demonstrated that it is a misconception that transcriptome sequencing requires tissue preserved at ultracold temperatures. Here, we outline the potential origins of this misconception and its possible role in biasing the geographic distribution of published plant transcriptomes. We highlight the importance of ensuring diverse sampling by providing an overview of the questions that transcriptomes can answer about the forces shaping the plant tree of life. We discuss how broadening transcriptome sequencing to include existing specimens will allow the field to grow and more fully utilize biological collections. We hope this article encourages the expansion of the current trend in 'herbariomics' research to include whole-transcriptome sequencing of historical RNA.
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Affiliation(s)
- Alexa S Tyszka
- Department of Biological Sciences, The University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Drew A Larson
- Department of Biology, Indiana University, Bloomington, IN 47405, USA.
| | - Joseph F Walker
- Department of Biological Sciences, The University of Illinois at Chicago, Chicago, IL 60607, USA.
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21
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Khan B, Qahwaji R, Alfaifi MS, Athar T, Khan A, Mobashir M, Ashankyty I, Imtiyaz K, Alahmadi A, Rizvi MMA. Deciphering molecular landscape of breast cancer progression and insights from functional genomics and therapeutic explorations followed by in vitro validation. Sci Rep 2024; 14:28794. [PMID: 39567714 PMCID: PMC11579425 DOI: 10.1038/s41598-024-80455-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2024] [Accepted: 11/19/2024] [Indexed: 11/22/2024] Open
Abstract
Breast cancer is caused by aberrant breast cells that proliferate and develop into tumors. Tumors have the potential to spread throughout the body and become lethal if ignored. Metastasis is the process by which invasive tumors move to neighboring lymph nodes or other organs. Metastasis can be lethal and perhaps fatal. The objective of our study was to elucidate the molecular mechanisms underlying the transition of Ductal Carcinoma In Situ (DCIS) to Invasive Ductal Carcinoma (IDC), with a particular focus on hub genes and potential therapeutic agents. Using Weighted Gene Co-expression Network Analysis (WGCNA), we built a comprehensive network combining clinical and phenotypic data from both DCIS and IDC. Modules within this network, correlated with specific phenotypic traits, were identified, and hub genes were identified as critical markers. Receiver Operating Characteristic (ROC) analysis assessed their potential as biomarkers, while survival curve analysis gauged their prognostic value. Furthermore, molecular docking predicted interactions with potential therapeutic agents. Ten hub genes-CDK1, KIF11, NUF2, ASPM, CDCA8, CENPF, DTL, EXO1, KIF2C, and ZWINT-emerged as pivotal fibroblast-specific genes potentially involved in the DCIS to IDC transition. These genes exhibited pronounced positive correlations with key pathways like the cell cycle and DNA repair, Molecular docking revealed Fisetin, an anti-inflammatory compound, effectively binding to both CDK1 and DTL underscoring their role in orchestrating cellular transformation. CDK1 and DTL were selected for molecular docking with CDK1 inhibitors, revealing effective binding of Fisetin, an anti-inflammatory compound, to both. Of the identified hub genes, DTL-an E3 ubiquitin ligase linked to the CRL4 complex-plays a central role in cancer progression, impacting tumor growth, invasion, and metastasis, as well as cell cycle regulation and epithelial-mesenchymal transition (EMT). CDK1, another hub gene, is pivotal in cell cycle progression and associated with various biological processes. In conclusion, our study offers insights into the complex mechanisms driving the transition from DCIS to IDC. It underscores the importance of hub genes and their potential interactions with therapeutic agents, particularly Fisetin. By shedding light on the interplay between CDK1 and DTL expression, our findings contribute to understanding the regulatory landscape of invasive ductal carcinoma and pave the way for future investigations and novel therapeutic avenues.
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MESH Headings
- Humans
- Breast Neoplasms/genetics
- Breast Neoplasms/pathology
- Breast Neoplasms/drug therapy
- Female
- Gene Expression Regulation, Neoplastic
- Genomics/methods
- Gene Regulatory Networks
- Disease Progression
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Carcinoma, Ductal, Breast/genetics
- Carcinoma, Ductal, Breast/pathology
- Carcinoma, Ductal, Breast/drug therapy
- Carcinoma, Intraductal, Noninfiltrating/genetics
- Carcinoma, Intraductal, Noninfiltrating/pathology
- Carcinoma, Intraductal, Noninfiltrating/drug therapy
- Molecular Docking Simulation
- Gene Expression Profiling
- Prognosis
- Cell Line, Tumor
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Affiliation(s)
- Bushra Khan
- Department of Biosciences, Jamia Millia Islamia, New Delhi, India
| | - Rowaid Qahwaji
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, 22233, Saudi Arabia
- Hematology Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mashael S Alfaifi
- Department of Epidemiology, Faculty of Public Health and Health Informatics, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Tanwir Athar
- College of Dentistry and Pharmacy, Buraydah Private Colleges, Buraydah, 51418, Saudi Arabia
| | - Abdullah Khan
- Department of Mechanical Engineering, Faculty of Engineering, Jamia Millia Islamia, New Delhi, India
| | - Mohammad Mobashir
- Department of Biomedical Laboratory Science, Faculty of Natural Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, 7491, Norway.
| | - Ibraheem Ashankyty
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, 22233, Saudi Arabia
| | - Khalid Imtiyaz
- Department of Biosciences, Jamia Millia Islamia, New Delhi, India
| | - Areej Alahmadi
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, 22233, Saudi Arabia
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Taub L, Hampton TH, Sarkar S, Doing G, Neff SL, Finger CE, Ferreira Fukutani K, Stanton BA. E.PathDash, pathway activation analysis of publicly available pathogen gene expression data. mSystems 2024; 9:e0103024. [PMID: 39422483 PMCID: PMC11575265 DOI: 10.1128/msystems.01030-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Accepted: 09/20/2024] [Indexed: 10/19/2024] Open
Abstract
E.PathDash facilitates re-analysis of gene expression data from pathogens clinically relevant to chronic respiratory diseases, including a total of 48 studies, 548 samples, and 404 unique treatment comparisons. The application enables users to assess broad biological stress responses at the KEGG pathway or gene ontology level and also provides data for individual genes. E.PathDash reduces the time required to gain access to data from multiple hours per data set to seconds. Users can download high-quality images such as volcano plots and boxplots, differential gene expression results, and raw count data, making it fully interoperable with other tools. Importantly, users can rapidly toggle between experimental comparisons and different studies of the same phenomenon, enabling them to judge the extent to which observed responses are reproducible. As a proof of principle, we invited two cystic fibrosis scientists to use the application to explore scientific questions relevant to their specific research areas. Reassuringly, pathway activation analysis recapitulated results reported in original publications, but it also yielded new insights into pathogen responses to changes in their environments, validating the utility of the application. All software and data are freely accessible, and the application is available at scangeo.dartmouth.edu/EPathDash. IMPORTANCE Chronic respiratory illnesses impose a high disease burden on our communities and people with respiratory diseases are susceptible to robust bacterial infections from pathogens, including Pseudomonas aeruginosa and Staphylococcus aureus, that contribute to morbidity and mortality. Public gene expression datasets generated from these and other pathogens are abundantly available and an important resource for synthesizing existing pathogenic research, leading to interventions that improve patient outcomes. However, it can take many hours or weeks to render publicly available datasets usable; significant time and skills are needed to clean, standardize, and apply reproducible and robust bioinformatic pipelines to the data. Through collaboration with two microbiologists, we have shown that E.PathDash addresses this problem, enabling them to elucidate pathogen responses to a variety of over 400 experimental conditions and generate mechanistic hypotheses for cell-level behavior in response to disease-relevant exposures, all in a fraction of the time.
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Affiliation(s)
- Lily Taub
- Department of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - Thomas H Hampton
- Department of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - Sharanya Sarkar
- Department of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - Georgia Doing
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA
| | - Samuel L Neff
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA
| | - Carson E Finger
- Department of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - Kiyoshi Ferreira Fukutani
- Department of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
| | - Bruce A Stanton
- Department of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
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23
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Bahraini M, Fazeli A, Dorgalaleh A. Laboratory Diagnosis of Activated Protein C Resistance and Factor V Leiden. Semin Thromb Hemost 2024; 50:1067-1083. [PMID: 37429328 DOI: 10.1055/s-0043-1770773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
The factor V Leiden (FVL) polymorphism is known as the most common inherited risk factor for venous thrombosis. In turn, FVL is the leading cause of an activated protein C resistance (APCR) phenotype, in which the addition of exogenous activated protein C to plasma does not result in the expected anticoagulant effect. In the routine laboratory approach to the formal diagnosis of FVL, an initial positive screening plasma-based method for APCR is often performed, and only if needed, this is followed by a confirmatory DNA-based assay for FVL. Multiple methods with accepted sensitivity and specificity for determining an APCR/FVL phenotype are commonly categorized into two separate groups: (1) screening plasma-based assays, including qualitative functional clot-based assays, for APCR, and (2) confirmatory DNA-based molecular assays, entailing several tests and platforms, including polymerase chain reaction-based and non-PCR-based techniques, for FVL. This review will describe the methodological aspects of each laboratory test and prepare suggestions on the indication of APCR and FVL testing and method selection.
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Affiliation(s)
- Mehran Bahraini
- Department of Hematology and Blood Transfusion, School of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Alieh Fazeli
- Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
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24
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Fiorini MR, Dilliott AA, Thomas RA, Farhan SMK. Transcriptomics of Human Brain Tissue in Parkinson's Disease: a Comparison of Bulk and Single-cell RNA Sequencing. Mol Neurobiol 2024; 61:8996-9015. [PMID: 38578357 PMCID: PMC11496323 DOI: 10.1007/s12035-024-04124-5] [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: 10/11/2023] [Accepted: 03/12/2024] [Indexed: 04/06/2024]
Abstract
Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease leading to motor dysfunction and, in some cases, dementia. Transcriptome analysis is one promising approach for characterizing PD and other neurodegenerative disorders by informing how specific disease events influence gene expression and contribute to pathogenesis. With the emergence of single-cell and single-nucleus RNA sequencing (scnRNA-seq) technologies, the transcriptional landscape of neurodegenerative diseases can now be described at the cellular level. As the application of scnRNA-seq is becoming routine, it calls to question how results at a single-cell resolution compare to those obtained from RNA sequencing of whole tissues (bulk RNA-seq), whether the findings are compatible, and how the assays are complimentary for unraveling the elusive transcriptional changes that drive neurodegenerative disease. Herein, we review the studies that have leveraged RNA-seq technologies to investigate PD. Through the integration of bulk and scnRNA-seq findings from human, post-mortem brain tissue, we use the PD literature as a case study to evaluate the compatibility of the results generated from each assay and demonstrate the complementarity of the sequencing technologies. Finally, through the lens of the PD transcriptomic literature, we evaluate the current feasibility of bulk and scnRNA-seq technologies to illustrate the necessity of both technologies for achieving a comprehensive insight into the mechanism by which gene expression promotes neurodegenerative disease. We conclude that the continued application of both assays will provide the greatest insight into neurodegenerative disease pathology, providing both cell-specific and whole-tissue level information.
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Affiliation(s)
- Michael R Fiorini
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Allison A Dilliott
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Rhalena A Thomas
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
| | - Sali M K Farhan
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada.
- Department of Human Genetics, McGill University, Montreal, QC, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
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25
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Creighton CJ. Clinical proteomics towards multiomics in cancer. MASS SPECTROMETRY REVIEWS 2024; 43:1255-1269. [PMID: 36495097 DOI: 10.1002/mas.21827] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Recent technological advancements in mass spectrometry (MS)-based proteomics technologies have accelerated its application to study greater and greater numbers of human tumor specimens. Over the last several years, the Clinical Proteomic Tumor Analysis Consortium, the International Cancer Proteogenome Consortium, and others have generated MS-based proteomic profiling data combined with corresponding multiomics data on thousands of human tumors to date. Proteomic data sets in the public domain can be re-examined by other researchers with different questions in mind from what the original studies explored. In this review, we examine the increasing role of proteomics in studying cancer, along with the potential for previous studies and their associated data sets to contribute to improving the diagnosis and treatment of cancer in the clinical setting. We also explore publicly available proteomics and multi-omics data from cancer cell line models to show how such data may aid in identifying therapeutic strategies for cancer subsets.
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Affiliation(s)
- Chad J Creighton
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
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26
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Ananth AL, Lopez MA. A review of neurogenetics in fetal and neonatal clinical medicine. Semin Fetal Neonatal Med 2024; 29:101550. [PMID: 39551661 DOI: 10.1016/j.siny.2024.101550] [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: 11/19/2024]
Abstract
This review of neurogenetics serves as a primer for clinicians practicing in fetal-neonatal medicine. The review provides an update on neurogenetics, understanding the language of genetics, genetic testing approaches, and interpretation of genetic test results. Common examples of neurogenetic disease in fetal-neonatal medicine are used to enhance basic concepts. The results of genetic testing and their implications for patients and families are outlined. Genetics is becoming foundational to clinical practice across specialties. The advances are improving the speed of diagnosis, facilitating early treatments, and improving outcomes in neurogenetic disorders. A basic understanding of genetics is foundational to appropriate clinical-decision making and interpretation of those results to describe common fetal-neonatal neurological phenotypes.
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Affiliation(s)
- Amitha L Ananth
- Children's of Alabama, Birmingham, AL, 35233, USA; Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
| | - Michael A Lopez
- Children's of Alabama, Birmingham, AL, 35233, USA; Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
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27
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Park KH, Lee H, Lee JH, Yon DK, Choi YI, Chung HJ, Jung J, Jeong NY. Unique and Shared Molecular Mechanisms of Alcoholic and Non-Alcoholic Liver Cirrhosis Identified Through Transcriptomics Data Integration. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2024; 28:537-547. [PMID: 39417237 DOI: 10.1089/omi.2024.0168] [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: 10/19/2024]
Abstract
Liver cirrhosis is a severe chronic disease that results from various etiological factors and leads to substantial morbidity and mortality. Alcoholic cirrhosis (AC) and non-AC (NAC) arise from prolonged and excessive consumption of alcohol and metabolic syndromes, respectively. Precise molecular mechanisms of AC and NAC are yet to be comprehensively understood for diagnostics and therapeutic advances to materialize. This study reports novel findings to this end by utilizing high-throughput RNA sequencing and microarray data from the Gene Expression Omnibus (GEO). We performed a meta-analysis of transcriptomics data to identify the differentially expressed genes specific to AC and NAC. Functional enrichment and protein-protein interaction network analyses uncovered novel hub genes and transcription factors (TFs) critical to AC and NAC. We found that AC is primarily driven by metabolic dysregulation and oxidative stress, with key TFs such as RELA, NFKB1, and STAT3. NAC was characterized by fibrosis and tissue remodeling associated with metabolic dysfunction, with TFs including USF1, MYCN, and HIF1A. Key hub genes such as ESR1, JUN, FOS, and PKM in AC, and CD8A, MAPK3, CCND1, and CXCR4 in NAC were identified, along with their associated TFs, pointing to potential therapeutic targets. Our results underscore the unique and shared molecular mechanisms that underlie AC and NAC and inform the efforts toward precision medicine and improved patient outcomes in liver cirrhosis.
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Affiliation(s)
- Ki-Hoon Park
- Department of Anesthesiology and Pain Medicine, College of Medicine, Kosin University, Busan, South Korea
- Department of Anatomy and Neurobiology, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
| | - Hwajin Lee
- Department of Biomedical Science, Graduation School, Kyung Hee University, Dongdaemun-gu, South Korea
- Department of Precision Medicine, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
- Department of Biochemistry and Molecular Biology, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
| | - Ji Hyun Lee
- Department of Biomedical Science, Graduation School, Kyung Hee University, Dongdaemun-gu, South Korea
- Department of Precision Medicine, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
- Department of Clinical Pharmacology and Therapeutics, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
| | - Dong Keon Yon
- Department of Precision Medicine, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
- Department of Digital Health, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
| | - Young-Il Choi
- Department of Surgery, College of Medicine, Kosin University, Busan, South Korea
| | - Hyung-Joo Chung
- Department of Anesthesiology and Pain Medicine, College of Medicine, Kosin University, Busan, South Korea
| | - Junyang Jung
- Department of Anatomy and Neurobiology, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
- Department of Biomedical Science, Graduation School, Kyung Hee University, Dongdaemun-gu, South Korea
- Department of Precision Medicine, College of Medicine, Kyung Hee University, Dongdaemun-gu, South Korea
| | - Na Young Jeong
- Department of Anatomy and Cell Biology, College of Medicine, Dong-A University, Busan, South Korea
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28
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Peña-Martín MC, Marcos-Vadillo E, García-Berrocal B, Heredero-Jung DH, García-Salgado MJ, Lorenzo-Hernández SM, Larrue R, Lenski M, Drevin G, Sanz C, Isidoro-García M. A Comparison of Molecular Techniques for Improving the Methodology in the Laboratory of Pharmacogenetics. Int J Mol Sci 2024; 25:11505. [PMID: 39519058 PMCID: PMC11546559 DOI: 10.3390/ijms252111505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Revised: 10/20/2024] [Accepted: 10/24/2024] [Indexed: 11/16/2024] Open
Abstract
One of the most critical goals in healthcare is safe and effective drug therapy, which is directly related to an individual's response to treatment. Precision medicine can improve drug safety in many scenarios, including polypharmacy, and it requires the development of new genetic characterization methods. In this report, we use real-time PCR, microarray techniques, and mass spectrometry (MALDI-TOF), which allows us to compare them and identify the potential benefits of technological improvements, leading to better quality medical care. These comparative studies, as part of our pharmacogenetic Five-Step Precision Medicine (5SPM) approach, reveal the superiority of mass spectrometry over the other methods analyzed and highlight the importance of updating the laboratory's pharmacogenetic methodology to identify new variants with clinical impact.
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Affiliation(s)
- María Celsa Peña-Martín
- Department of Clinical Biochemistry, University Hospital of Salamanca, 37007 Salamanca, Spain; (M.C.P.-M.); (E.M.-V.); (B.G.-B.); (D.H.H.-J.); (M.J.G.-S.); (S.M.L.-H.); (M.I.-G.)
- Pharmacology-Toxicology and Pharmacovigilance Department, Angers University Hospital, F-49100 Angers, France;
- Institute for Biomedical Research of Salamanca, 37007 Salamanca, Spain
| | - Elena Marcos-Vadillo
- Department of Clinical Biochemistry, University Hospital of Salamanca, 37007 Salamanca, Spain; (M.C.P.-M.); (E.M.-V.); (B.G.-B.); (D.H.H.-J.); (M.J.G.-S.); (S.M.L.-H.); (M.I.-G.)
- Institute for Biomedical Research of Salamanca, 37007 Salamanca, Spain
| | - Belén García-Berrocal
- Department of Clinical Biochemistry, University Hospital of Salamanca, 37007 Salamanca, Spain; (M.C.P.-M.); (E.M.-V.); (B.G.-B.); (D.H.H.-J.); (M.J.G.-S.); (S.M.L.-H.); (M.I.-G.)
- Institute for Biomedical Research of Salamanca, 37007 Salamanca, Spain
| | - David Hansoe Heredero-Jung
- Department of Clinical Biochemistry, University Hospital of Salamanca, 37007 Salamanca, Spain; (M.C.P.-M.); (E.M.-V.); (B.G.-B.); (D.H.H.-J.); (M.J.G.-S.); (S.M.L.-H.); (M.I.-G.)
- Institute for Biomedical Research of Salamanca, 37007 Salamanca, Spain
| | - María Jesús García-Salgado
- Department of Clinical Biochemistry, University Hospital of Salamanca, 37007 Salamanca, Spain; (M.C.P.-M.); (E.M.-V.); (B.G.-B.); (D.H.H.-J.); (M.J.G.-S.); (S.M.L.-H.); (M.I.-G.)
- Institute for Biomedical Research of Salamanca, 37007 Salamanca, Spain
| | - Sandra Milagros Lorenzo-Hernández
- Department of Clinical Biochemistry, University Hospital of Salamanca, 37007 Salamanca, Spain; (M.C.P.-M.); (E.M.-V.); (B.G.-B.); (D.H.H.-J.); (M.J.G.-S.); (S.M.L.-H.); (M.I.-G.)
- Institute for Biomedical Research of Salamanca, 37007 Salamanca, Spain
| | - Romain Larrue
- CNRS, Inserm, CHU Lille, UMR9020-U1277—CANTHER—Cancer Heterogeneity Plasticity and Resistance to Therapies, University of Lille, F-59000 Lille, France;
| | - Marie Lenski
- CHU Lille, Institut Pasteur de Lille, ULR 4483, IMPECS-IMPact of the Chemical Environment on Health, University of Lille, F-59000 Lille, France;
| | - Guillaume Drevin
- Pharmacology-Toxicology and Pharmacovigilance Department, Angers University Hospital, F-49100 Angers, France;
| | - Catalina Sanz
- Institute for Biomedical Research of Salamanca, 37007 Salamanca, Spain
- Department of Microbiology and Genetics, University of Salamanca, 37007 Salamanca, Spain
| | - María Isidoro-García
- Department of Clinical Biochemistry, University Hospital of Salamanca, 37007 Salamanca, Spain; (M.C.P.-M.); (E.M.-V.); (B.G.-B.); (D.H.H.-J.); (M.J.G.-S.); (S.M.L.-H.); (M.I.-G.)
- Institute for Biomedical Research of Salamanca, 37007 Salamanca, Spain
- Department of Medicine, University of Salamanca, 37007 Salamanca, Spain
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29
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Cunningham AG, Gorospe M. Striving for clarity in language about gene expression. Nucleic Acids Res 2024; 52:10747-10753. [PMID: 39271127 PMCID: PMC11472038 DOI: 10.1093/nar/gkae764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Revised: 08/15/2024] [Accepted: 08/21/2024] [Indexed: 09/15/2024] Open
Abstract
What do we mean when we say 'gene expression'? In the decades following Crick's 1958 central dogma of molecular biology, whereby genetic information flows from DNA (genes) to RNA (transcripts) to protein (products), we have learned a great deal about DNA, RNA, proteins, and the ensuing phenotypic changes. With the advent of high-throughput technologies (1990s), molecular biologists and computer scientists forged critical collaborations to understand the vast amount of data being generated, rapidly escalating gene expression research to the 'omics' level: entire sets of genes (genomes), transcribed RNAs (transcriptomes), and synthesized proteins (proteomes). However, some concessions came to be made for molecular biologists and computer scientists to understand each other-one of the most prevalent being the increasingly widespread use of 'gene' to mean 'RNAs originating from a DNA segment'. This loosening of terminology, we will argue, creates ambiguity and confusion. We propose guidelines to increase precision and clarity when communicating about gene expression, most notably to reserve 'gene' for the DNA template and 'transcript' for the RNA transcribed from that gene. Striving to use perspicuous terminology will promote rigorous gene expression science and accelerate discovery in this highly promising area of biology.
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Affiliation(s)
- Ana S G Cunningham
- Laboratory of Genetics and Genomics, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Myriam Gorospe
- Laboratory of Genetics and Genomics, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
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30
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Alkhateeb MA, Aljarba NH, Yousafi Q, Anwar F, Biswas P. Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach. J Cell Mol Med 2024; 28:e70133. [PMID: 39434198 PMCID: PMC11493557 DOI: 10.1111/jcmm.70133] [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: 02/08/2024] [Revised: 05/05/2024] [Accepted: 09/09/2024] [Indexed: 10/23/2024] Open
Abstract
Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package. Gene Ontology (GO) analysis of DEGs was performed using DAVID. The protein-protein interaction network was constructed by STRING database plugin in Cytoscape. Subclusters/modules of important interacting genes in main network were extracted by using MCODE. The hub genes from in the network were identified by using Cytohubba. The miRNet tool built a hub gene/mRNA-miRNA network and Kaplan-Meier-Plotter conducted survival analysis. AutoDock Vina and GROMACS MD simulations were used for docking and stability analysis of marine compounds against the 5CNN protein. Total 734 DEGs (507 up-regulated and 228 down-regulated) were identified. Differentially expressed genes (DEGs) were enriched in processes like cell-cell adhesion and ATP binding. Eight hub genes (EGFR, HSPA90AA1, MAPK1, HSPA4, PPP2CA, CDKN2A, CDC20, and ATM) were selected for further analysis. A total of 23 miRNAs associated with hub genes were identified, with 12 of them targeting PPP2CA. EGFR displayed the highest expression and hazard rate in survival analyses. The kinase domain of EGFR (PDBID: 5CNN) was chosen as the drug target. Adociaquinone A from Petrosia alfiani, docked with 5CNN, showed the lowest binding energy with stable interactions across a 50 ns MD simulation, highlighting its potential as a lead molecule against EGFR. This study has identified crucial DEGs and hub genes in gastric cancer, proposing novel therapeutic targets. Specifically, Adociaquinone A demonstrates promising potential as a bioactive drug against EGFR in gastric cancer, warranting further investigation. The predicted miRNA against the hub gene/proteins can also be used as potential therapeutic targets.
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Affiliation(s)
| | - Nada H. Aljarba
- Department of Biology, College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia
| | - Qudsia Yousafi
- Department of BiosciencesCOMSATS University Islamabad, Sahiwal CampusSahiwalPakistan
| | - Fatima Anwar
- Department of BiosciencesCOMSATS University Islamabad, Sahiwal CampusSahiwalPakistan
| | - Partha Biswas
- Laboratory of Pharmaceutical Biotechnology and Bioinformatics, Department of Genetic Engineering and BiotechnologyJashore University of Science and TechnologyJashoreBangladesh
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31
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So KWL, Su Z, Cheung JPY, Choi SW. Single-Cell Analysis of Bone-Marrow-Disseminated Tumour Cells. Diagnostics (Basel) 2024; 14:2172. [PMID: 39410576 PMCID: PMC11475990 DOI: 10.3390/diagnostics14192172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 09/17/2024] [Accepted: 09/18/2024] [Indexed: 10/20/2024] Open
Abstract
Metastasis frequently targets bones, where cancer cells from the primary tumour migrate to the bone marrow, initiating new tumour growth. Not only is bone the most common site for metastasis, but it also often marks the first site of metastatic recurrence. Despite causing over 90% of cancer-related deaths, effective treatments for bone metastasis are lacking, with current approaches mainly focusing on palliative care. Circulating tumour cells (CTCs) are pivotal in metastasis, originating from primary tumours and circulating in the bloodstream. They facilitate metastasis through molecular interactions with the bone marrow environment, involving direct cell-to-cell contacts and signalling molecules. CTCs infiltrate the bone marrow, transforming into disseminated tumour cells (DTCs). While some DTCs remain dormant, others become activated, leading to metastatic growth. The presence of DTCs in the bone marrow strongly correlates with future bone and visceral metastases. Research on CTCs in peripheral blood has shed light on their release mechanisms, yet investigations into bone marrow DTCs have been limited. Challenges include the invasiveness of bone marrow aspiration and the rarity of DTCs, complicating their isolation. However, advancements in single-cell analysis have facilitated insights into these elusive cells. This review will summarize recent advancements in understanding bone marrow DTCs using single-cell analysis techniques.
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Affiliation(s)
| | | | | | - Siu-Wai Choi
- Department of Orthopaedics and Traumatology, School of Clinical Medicine, Faculty of Medicine, The University of Hong Kong, Hong Kong, China; (K.W.L.S.); (Z.S.); (J.P.Y.C.)
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32
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Pfeiffer P, Nilsson J, Gallud A, Baladi T, Le HN, Bood M, Lemurell M, Dahlén A, Grøtli M, Esbjörner E, Wilhelmsson L. Metabolic RNA labeling in non-engineered cells following spontaneous uptake of fluorescent nucleoside phosphate analogues. Nucleic Acids Res 2024; 52:10102-10118. [PMID: 39162218 PMCID: PMC11417403 DOI: 10.1093/nar/gkae722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 07/04/2024] [Accepted: 08/07/2024] [Indexed: 08/21/2024] Open
Abstract
RNA and its building blocks play central roles in biology and have become increasingly important as therapeutic agents and targets. Hence, probing and understanding their dynamics in cells is important. Fluorescence microscopy offers live-cell spatiotemporal monitoring but requires labels. We present two fluorescent adenine analogue nucleoside phosphates which show spontaneous uptake and accumulation in cultured human cells, likely via nucleoside transporters, and show their potential utilization as cellular RNA labels. Upon uptake, one nucleotide analogue, 2CNqAXP, localizes to the cytosol and the nucleus. We show that it could then be incorporated into de novo synthesized cellular RNA, i.e. it was possible to achieve metabolic fluorescence RNA labeling without using genetic engineering to enhance incorporation, uptake-promoting strategies, or post-labeling through bio-orthogonal chemistries. By contrast, another nucleotide analogue, pAXP, only accumulated outside of the nucleus and was rapidly excreted. Consequently, this analogue did not incorporate into RNA. This difference in subcellular accumulation and retention results from a minor change in nucleobase chemical structure. This demonstrates the importance of careful design of nucleoside-based drugs, e.g. antivirals to direct their subcellular localization, and shows the potential of fine-tuning fluorescent base analogue structures to enhance the understanding of the function of such drugs.
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Affiliation(s)
- Pauline Pfeiffer
- Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Kemivägen 10, SE-41296 Gothenburg, Sweden
| | - Jesper R Nilsson
- Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Kemivägen 10, SE-41296 Gothenburg, Sweden
- LanteRNA (Stealth Labels Biotech AB), c/o Chalmers Ventures AB, Vera Sandbergs allé 8, SE-41296 Gothenburg, Sweden
| | - Audrey Gallud
- Department of Life Sciences, Chalmers University of Technology, Kemivägen 10, SE-41296 Gothenburg, Sweden
- Advanced Drug Delivery, Pharmaceutical Sciences, BioPharmaceuticals R&D, AstraZeneca, SE-43181 Gothenburg, Sweden
| | - Tom Baladi
- Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Kemivägen 10, SE-41296 Gothenburg, Sweden
- Oligonucleotide Discovery, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Hoang-Ngoan Le
- Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Kemivägen 10, SE-41296 Gothenburg, Sweden
- Oligonucleotide Discovery, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Mattias Bood
- Oligonucleotide Discovery, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
- Department of Chemistry and Molecular Biology, University of Gothenburg, P.O. Box 462, SE-40530 Gothenburg, Sweden
| | - Malin Lemurell
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Anders Dahlén
- Oligonucleotide Discovery, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Morten Grøtli
- Department of Chemistry and Molecular Biology, University of Gothenburg, P.O. Box 462, SE-40530 Gothenburg, Sweden
| | - Elin K Esbjörner
- Department of Life Sciences, Chalmers University of Technology, Kemivägen 10, SE-41296 Gothenburg, Sweden
| | - L Marcus Wilhelmsson
- Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Kemivägen 10, SE-41296 Gothenburg, Sweden
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Subhashini N, Kerler Y, Menger MM, Böhm O, Witte J, Stadler C, Griberman A. Enhancing Colorimetric Detection of Nucleic Acids on Nitrocellulose Membranes: Cutting-Edge Applications in Diagnostics and Forensics. BIOSENSORS 2024; 14:430. [PMID: 39329805 PMCID: PMC11429540 DOI: 10.3390/bios14090430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2024] [Revised: 08/30/2024] [Accepted: 08/30/2024] [Indexed: 09/28/2024]
Abstract
This study re-introduces a protein-free rapid test method for nucleic acids on paper based lateral flow assays utilizing special multichannel nitrocellulose membranes and DNA-Gold conjugates, achieving significantly enhanced sensitivity, easier protocols, reduced time of detection, reduced costs of production and advanced multiplexing possibilities. A protein-free nucleic acid-based lateral flow assay (NALFA) with a limit of detection of 1 pmol of DNA is shown for the first time. The total production duration of such an assay was successfully reduced from the currently known several days to just a few hours. The simplification and acceleration of the protocol make the method more accessible and practical for various applications. The developed method supports multiplexing, enabling the simultaneous detection of up to six DNA targets. This multiplexing capability is a significant improvement over traditional line tests and offers more comprehensive diagnostic potential in a single assay. The approach significantly reduces the run time compared to traditional line tests, which enhances the efficiency of diagnostic procedures. The protein-free aspect of this assay minimizes the prevalent complications of cross-reactivity in immunoassays especially in cases of multiplexing. It is also demonstrated that the NALFA developed in this study is amplification-free and hence does not rely on specialized technicians, nor does it involve labour-intensive steps like DNA extraction and PCR processes. Overall, this study presents a robust, efficient, and highly sensitive platform for DNA or RNA detection, addressing several limitations of current methods documented in the literature. The advancements in sensitivity, cost reduction, production time, and multiplexing capabilities mark a substantial improvement, holding great potential for various applications in diagnostics, forensics, and molecular biology.
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Affiliation(s)
- Nidhi Subhashini
- SERATEC Gesellschaft für Biotechnologie mbH, Ernst-Ruhstrat-Str. 5, 37079 Goettingen, Germany
| | - Yannick Kerler
- Fraunhofer Institute for Cell Therapy and Immunology (IZI), Branch Bioanalytics and Bioprocesses (IZI-BB), Am Mühlenberg 13, 14476 Potsdam, Germany
- Institute for Biochemistry and Biology, University of Potsdam, D-14476 Potsdam, Germany
| | - Marcus M. Menger
- Fraunhofer Institute for Cell Therapy and Immunology (IZI), Branch Bioanalytics and Bioprocesses (IZI-BB), Am Mühlenberg 13, 14476 Potsdam, Germany
| | - Olga Böhm
- Sartorius Stedim Biotech GmbH, August-Spindler-Str. 11, 37079 Goettingen, Germany
| | - Judith Witte
- Sartorius Stedim Biotech GmbH, August-Spindler-Str. 11, 37079 Goettingen, Germany
| | - Christian Stadler
- SERATEC Gesellschaft für Biotechnologie mbH, Ernst-Ruhstrat-Str. 5, 37079 Goettingen, Germany
| | - Alexander Griberman
- SERATEC Gesellschaft für Biotechnologie mbH, Ernst-Ruhstrat-Str. 5, 37079 Goettingen, Germany
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Ashraf MA, Raza MA, Amjad MN, Ud Din G, Yue L, Shen B, Chen L, Dong W, Xu H, Hu Y. A comprehensive review of influenza B virus, its biological and clinical aspects. Front Microbiol 2024; 15:1467029. [PMID: 39296301 PMCID: PMC11408344 DOI: 10.3389/fmicb.2024.1467029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Accepted: 08/22/2024] [Indexed: 09/21/2024] Open
Abstract
Influenza B virus (IBV) stands as a paradox, often overshadowed by its more notorious counterpart, influenza A virus (IAV). Yet, it remains a captivating and elusive subject of scientific inquiry. Influenza B is important because it causes seasonal flu outbreaks that can lead to severe respiratory illnesses, including bronchitis, pneumonia, and exacerbations of chronic conditions like asthma. Limitations in the influenza B virus's epidemiological, immunological, and etiological evolution must be addressed promptly. This comprehensive review covers evolutionary epidemiology and pathogenesis, host-virus interactions, viral isolation and propagation, advanced molecular detection assays, vaccine composition and no animal reservoir for influenza B virus. Complex viral etiology begins with intranasal transmission of influenza B virus with the release of a segmented RNA genome that attacks host cell machinery for transcription and translation within the nucleus and the release of viral progeny. Influenza B virus prevalence in domesticated and wild canines, sea mammals, and birds is frequent, yet there is no zoonosis. The periodic circulation of influenza B virus indicates a 1-3-year cycle for monophyletic strain replacement within the Victoria strain due to frequent antigenic drift in the HA near the receptor-binding site (RBS), while the antigenic stability of Yamagata viruses portrays a more conservative evolutionary pattern. Additionally, this article outlines contemporary antiviral strategies, including pharmacological interventions and vaccination efforts. This article serves as a resource for researchers, healthcare professionals, and anyone interested in the mysterious nature of the influenza B virus. It provides valuable insights and knowledge essential for comprehending and effectively countering this viral foe, which continues to pose a significant public health threat.
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Affiliation(s)
- Muhammad Awais Ashraf
- CAS Key Laboratory of Molecular Virology and Immunology, Institutional Center for Shared Technologies and Facilities, Pathogen Discovery and Big Data Platform, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Muhammad Asif Raza
- CAS Key Laboratory of Molecular Virology and Immunology, Institutional Center for Shared Technologies and Facilities, Pathogen Discovery and Big Data Platform, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Muhammad Nabeel Amjad
- CAS Key Laboratory of Molecular Virology and Immunology, Institutional Center for Shared Technologies and Facilities, Pathogen Discovery and Big Data Platform, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ghayyas Ud Din
- CAS Key Laboratory of Molecular Virology and Immunology, Institutional Center for Shared Technologies and Facilities, Pathogen Discovery and Big Data Platform, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lihuan Yue
- CAS Key Laboratory of Molecular Virology and Immunology, Institutional Center for Shared Technologies and Facilities, Pathogen Discovery and Big Data Platform, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
| | - Bei Shen
- CAS Key Laboratory of Molecular Virology and Immunology, Institutional Center for Shared Technologies and Facilities, Pathogen Discovery and Big Data Platform, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
| | - Lingdie Chen
- CAS Key Laboratory of Molecular Virology and Immunology, Institutional Center for Shared Technologies and Facilities, Pathogen Discovery and Big Data Platform, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wei Dong
- Pediatric Department, Nanxiang Branch of Ruijin Hospital, Shanghai, China
| | - Huiting Xu
- Pediatric Department, Nanxiang Branch of Ruijin Hospital, Shanghai, China
| | - Yihong Hu
- CAS Key Laboratory of Molecular Virology and Immunology, Institutional Center for Shared Technologies and Facilities, Pathogen Discovery and Big Data Platform, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
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35
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Pavlou A, Mulenge F, Gern OL, Busker LM, Greimel E, Waltl I, Kalinke U. Orchestration of antiviral responses within the infected central nervous system. Cell Mol Immunol 2024; 21:943-958. [PMID: 38997413 PMCID: PMC11364666 DOI: 10.1038/s41423-024-01181-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 05/05/2024] [Indexed: 07/14/2024] Open
Abstract
Many newly emerging and re-emerging viruses have neuroinvasive potential, underscoring viral encephalitis as a global research priority. Upon entry of the virus into the CNS, severe neurological life-threatening conditions may manifest that are associated with high morbidity and mortality. The currently available therapeutic arsenal against viral encephalitis is rather limited, emphasizing the need to better understand the conditions of local antiviral immunity within the infected CNS. In this review, we discuss new insights into the pathophysiology of viral encephalitis, with a focus on myeloid cells and CD8+ T cells, which critically contribute to protection against viral CNS infection. By illuminating the prerequisites of myeloid and T cell activation, discussing new discoveries regarding their transcriptional signatures, and dissecting the mechanisms of their recruitment to sites of viral replication within the CNS, we aim to further delineate the complexity of antiviral responses within the infected CNS. Moreover, we summarize the current knowledge in the field of virus infection and neurodegeneration and discuss the potential links of some neurotropic viruses with certain pathological hallmarks observed in neurodegeneration.
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Affiliation(s)
- Andreas Pavlou
- Institute for Experimental Infection Research, TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research and the Hannover Medical School, 30625, Hannover, Germany
| | - Felix Mulenge
- Institute for Experimental Infection Research, TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research and the Hannover Medical School, 30625, Hannover, Germany
| | - Olivia Luise Gern
- Institute for Experimental Infection Research, TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research and the Hannover Medical School, 30625, Hannover, Germany
| | - Lena Mareike Busker
- Institute for Experimental Infection Research, TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research and the Hannover Medical School, 30625, Hannover, Germany
- Department of Pathology, University of Veterinary Medicine Hannover, Foundation, 30559, Hannover, Germany
| | - Elisabeth Greimel
- Institute for Experimental Infection Research, TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research and the Hannover Medical School, 30625, Hannover, Germany
| | - Inken Waltl
- Institute for Experimental Infection Research, TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research and the Hannover Medical School, 30625, Hannover, Germany
| | - Ulrich Kalinke
- Institute for Experimental Infection Research, TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research and the Hannover Medical School, 30625, Hannover, Germany.
- Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, 30625, Hannover, Germany.
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36
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Zhu G, Wang X, Wang Y, Huang T, Zhang X, He J, Shi N, Chen J, Zhang J, Zhang M, Li J. Comparative transcriptomic study on the ovarian cancer between chicken and human. Poult Sci 2024; 103:104021. [PMID: 39002367 PMCID: PMC11298922 DOI: 10.1016/j.psj.2024.104021] [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: 04/12/2024] [Revised: 06/05/2024] [Accepted: 06/19/2024] [Indexed: 07/15/2024] Open
Abstract
The laying hen is the spontaneous model of ovarian tumor. A comprehensive comparison based on RNA-seq from hens and women may shed light on the molecular mechanisms of ovarian cancer. We performed next-generation sequencing of microRNA and mRNA expression profiles in 9 chicken ovarian cancers and 4 normal ovaries, which has been deposited in GSE246604. Together with 6 public datasets (GSE21706, GSE40376, GSE18520, GSE27651, GSE66957, TCGA-OV), we conducted a comparative transcriptomics study between chicken and human. In the present study, miR-451, miR-2188-5p, and miR-10b-5p were differentially expressed in normal ovaries, early- and late-stage ovarian cancers. We also disclosed 499 up-regulated genes and 1,061 down-regulated genes in chicken ovarian cancer. The molecular signals from 9 cancer hallmarks, 25 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and 369 Gene Ontology (GO) pathways exhibited abnormalities in ovarian cancer compared to normal ovaries via Gene Set Enrichment Analysis (GSEA). In the comparative analysis across species, we have uncovered the conservation of 5 KEGG and 76 GO pathways between chicken and human including the mismatch repair and ECM receptor interaction pathways. Moreover, a total of 174 genes contributed to the core enrichment for these KEGG and GO pathways were identified. Among these genes, the 22 genes were found to be associated with overall survival in patients with ovarian cancer. In general, we revealed the microRNA profiles of ovarian cancers in hens and updated the mRNA profiles previously derived from microarrays. And we also disclosed the molecular pathways and core genes of ovarian cancer shared between hens and women, which informs model animal studies and gene-targeted drug development.
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Affiliation(s)
- Guoqiang Zhu
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Xinglong Wang
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Yajun Wang
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Tianjiao Huang
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Xiao Zhang
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Jiliang He
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Ningkun Shi
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Juntao Chen
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Jiannan Zhang
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China
| | - Mao Zhang
- Division of Vascular Surgery, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Juan Li
- Key laboratory of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, College of Life Sciences, Sichuan University, Chengdu, China.
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37
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Khaledi M, Khatami M, Hemmati J, Bakhti S, Hoseini SA, Ghahramanpour H. Role of Small Non-Coding RNA in Gram-Negative Bacteria: New Insights and Comprehensive Review of Mechanisms, Functions, and Potential Applications. Mol Biotechnol 2024:10.1007/s12033-024-01248-w. [PMID: 39153013 DOI: 10.1007/s12033-024-01248-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 08/02/2024] [Indexed: 08/19/2024]
Abstract
Small non-coding RNAs (sRNAs) are a key part of gene expression regulation in bacteria. Many physiologic activities like adaptation to environmental stresses, antibiotic resistance, quorum sensing, and modulation of the host immune response are regulated directly or indirectly by sRNAs in Gram-negative bacteria. Therefore, sRNAs can be considered as potentially useful therapeutic options. They have opened promising perspectives in the field of diagnosis of pathogens and treatment of infections caused by antibiotic-resistant organisms. Identification of sRNAs can be executed by sequence and expression-based methods. Despite the valuable progress in the last two decades, and discovery of new sRNAs, their exact role in biological pathways especially in co-operation with other biomolecules involved in gene expression regulation such as RNA-binding proteins (RBPs), riboswitches, and other sRNAs needs further investigation. Although the numerous RNA databases are available, including 59 databases used by RNAcentral, there remains a significant gap in the absence of a comprehensive and professional database that categorizes experimentally validated sRNAs in Gram-negative pathogens. Here, we review the present knowledge about most recent and important sRNAs and their regulatory mechanism, strengths and weaknesses of current methods of sRNAs identification. Also, we try to demonstrate the potential applications and new insights of sRNAs for future studies.
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Affiliation(s)
- Mansoor Khaledi
- Cellular and Molecular Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran
- Department of Microbiology and Immunology, School of Medicine, Shahrekord University of Medical Sciences, Shahrekord, Iran
| | - Mehrdad Khatami
- Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Jaber Hemmati
- Department of Microbiology, Faculty of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Shahriar Bakhti
- Department of Microbiology, Faculty of Medicine, Shahed University, Tehran, Iran
| | | | - Hossein Ghahramanpour
- Department of Bacteriology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
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38
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Sato Y. Transcriptome analysis: a powerful tool to understand individual microbial behaviors and interactions in ecosystems. Biosci Biotechnol Biochem 2024; 88:850-856. [PMID: 38749545 DOI: 10.1093/bbb/zbae064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/06/2024] [Indexed: 07/23/2024]
Abstract
Transcriptome analysis is a powerful tool for studying microbial ecology, especially individual microbial functions in an ecosystem and their interactions. With the development of high-throughput sequencing technology, great progress has been made in analytical methods for microbial communities in natural environments. 16S rRNA gene amplicon sequencing (ie microbial community structure analysis) and shotgun metagenome analysis have been widely used to determine the composition and potential metabolic capability of microorganisms in target environments without requiring culture. However, even if the types of microorganisms present and their genes are known, it is difficult to determine what they are doing in an ecosystem. Gene expression analysis (transcriptome analysis; RNA-seq) is a powerful tool to address these issues. The history and basic information of gene expression analysis, as well as examples of studies using this method to analyze microbial ecosystems, are presented.
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Affiliation(s)
- Yuya Sato
- Environmental Management Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan
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39
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Wen Y, Yang H, Hong Y. Transcriptomic Approaches to Cardiomyocyte-Biomaterial Interactions: A Review. ACS Biomater Sci Eng 2024; 10:4175-4194. [PMID: 38934720 DOI: 10.1021/acsbiomaterials.4c00303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2024]
Abstract
Biomaterials, essential for supporting, enhancing, and repairing damaged tissues, play a critical role in various medical applications. This Review focuses on the interaction of biomaterials and cardiomyocytes, emphasizing the unique significance of transcriptomic approaches in understanding their interactions, which are pivotal in cardiac bioengineering and regenerative medicine. Transcriptomic approaches serve as powerful tools to investigate how cardiomyocytes respond to biomaterials, shedding light on the gene expression patterns, regulatory pathways, and cellular processes involved in these interactions. Emerging technologies such as bulk RNA-seq, single-cell RNA-seq, single-nucleus RNA-seq, and spatial transcriptomics offer promising avenues for more precise and in-depth investigations. Longitudinal studies, pathway analyses, and machine learning techniques further improve the ability to explore the complex regulatory mechanisms involved. This review also discusses the challenges and opportunities of utilizing transcriptomic techniques in cardiomyocyte-biomaterial research. Although there are ongoing challenges such as costs, cell size limitation, sample differences, and complex analytical process, there exist exciting prospects in comprehensive gene expression analyses, biomaterial design, cardiac disease treatment, and drug testing. These multimodal methodologies have the capacity to deepen our understanding of the intricate interaction network between cardiomyocytes and biomaterials, potentially revolutionizing cardiac research with the aim of promoting heart health, and they are also promising for studying interactions between biomaterials and other cell types.
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Affiliation(s)
- Yufeng Wen
- Department of Bioengineering, University of Texas at Arlington, Arlington, Texas 76019, United States
| | - Huaxiao Yang
- Department of Biomedical Engineering, University of North Texas, Denton, Texas 76207, United States
| | - Yi Hong
- Department of Bioengineering, University of Texas at Arlington, Arlington, Texas 76019, United States
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40
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Kazmi SSUH, Tayyab M, Pastorino P, Barcelò D, Yaseen ZM, Grossart HP, Khan ZH, Li G. Decoding the molecular concerto: Toxicotranscriptomic evaluation of microplastic and nanoplastic impacts on aquatic organisms. JOURNAL OF HAZARDOUS MATERIALS 2024; 472:134574. [PMID: 38739959 DOI: 10.1016/j.jhazmat.2024.134574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/30/2024] [Accepted: 05/08/2024] [Indexed: 05/16/2024]
Abstract
The pervasive and steadily increasing presence of microplastics/nanoplastics (MPs/NPs) in aquatic environments has raised significant concerns regarding their potential adverse effects on aquatic organisms and their integration into trophic dynamics. This emerging issue has garnered the attention of (eco)toxicologists, promoting the utilization of toxicotranscriptomics to unravel the responses of aquatic organisms not only to MPs/NPs but also to a wide spectrum of environmental pollutants. This review aims to systematically explore the broad repertoire of predicted molecular responses by aquatic organisms, providing valuable intuitions into complex interactions between plastic pollutants and aquatic biota. By synthesizing the latest literature, present analysis sheds light on transcriptomic signatures like gene expression, interconnected pathways and overall molecular mechanisms influenced by various plasticizers. Harmful effects of these contaminants on key genes/protein transcripts associated with crucial pathways lead to abnormal immune response, metabolic response, neural response, apoptosis and DNA damage, growth, development, reproductive abnormalities, detoxification, and oxidative stress in aquatic organisms. However, unique challenge lies in enhancing the fingerprint of MPs/NPs, presenting complicated enigma that requires decoding their specific impact at molecular levels. The exploration endeavors, not only to consolidate existing knowledge, but also to identify critical gaps in understanding, push forward the frontiers of knowledge about transcriptomic signatures of plastic contaminants. Moreover, this appraisal emphasizes the imperative to monitor and mitigate the contamination of commercially important aquatic species by MPs/NPs, highlighting the pivotal role that regulatory frameworks must play in protecting all aquatic ecosystems. This commitment aligns with the broader goal of ensuring the sustainability of aquatic resources and the resilience of ecosystems facing the growing threat of plastic pollutants.
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Affiliation(s)
- Syed Shabi Ul Hassan Kazmi
- Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, PR China; Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, CAS Haixi Industrial Technology Innovation Center in Beilun, Ningbo 315830, PR China
| | - Muhammad Tayyab
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou 515063, PR China
| | - Paolo Pastorino
- Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d'Aosta, 10154 Torino, Italy
| | - Damià Barcelò
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034 Barcelona, Spain
| | - Zaher Mundher Yaseen
- Civil and Environmental Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia; Interdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
| | - Hans-Peter Grossart
- Plankton and Microbial Ecology, Leibniz Institute for Freshwater Ecology and Inland Fisheries, (IGB), Alte Fischerhuette 2, Neuglobsow, D-16775, Germany; Institute of Biochemistry and Biology, Potsdam University, Maulbeerallee 2, D-14469 Potsdam, Germany
| | - Zulqarnain Haider Khan
- Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, PR China; Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, CAS Haixi Industrial Technology Innovation Center in Beilun, Ningbo 315830, PR China
| | - Gang Li
- Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, PR China; Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, CAS Haixi Industrial Technology Innovation Center in Beilun, Ningbo 315830, PR China.
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Ramos YFM, Rice SJ, Ali SA, Pastrello C, Jurisica I, Rai MF, Collins KH, Lang A, Maerz T, Geurts J, Ruiz-Romero C, June RK, Thomas Appleton C, Rockel JS, Kapoor M. Evolution and advancements in genomics and epigenomics in OA research: How far we have come. Osteoarthritis Cartilage 2024; 32:858-868. [PMID: 38428513 DOI: 10.1016/j.joca.2024.02.656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/29/2024] [Accepted: 02/25/2024] [Indexed: 03/03/2024]
Abstract
OBJECTIVE Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease. DESIGN In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients. RESULTS Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease. CONCLUSIONS Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.
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Affiliation(s)
- Yolande F M Ramos
- Dept. Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Sarah J Rice
- Biosciences Institute, International Centre for Life, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Shabana Amanda Ali
- Henry Ford Health + Michigan State University Health Sciences, Detroit, MI, USA
| | - Chiara Pastrello
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, UHN, Toronto, Ontario, Canada
| | - Igor Jurisica
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, UHN, Toronto, Ontario, Canada; Departments of Medical Biophysics and Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Muhammad Farooq Rai
- Department of Biological Sciences, Center for Biotechnology, College of Medicine & Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Kelsey H Collins
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Annemarie Lang
- Departments of Orthopaedic Surgery and Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Tristan Maerz
- Department of Orthopaedic Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Jeroen Geurts
- Rheumatology, Department of Musculoskeletal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Cristina Ruiz-Romero
- Grupo de Investigación de Reumatología (GIR), Unidad de Proteómica, INIBIC -Hospital Universitario A Coruña, SERGAS, A Coruña, Spain
| | - Ronald K June
- Department of Mechanical & Industrial Engineering, Montana State University, Bozeman, MT, USA
| | - C Thomas Appleton
- Department of Medicine, University of Western Ontario, London, Ontario, Canada
| | - Jason S Rockel
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, UHN, Toronto, Ontario, Canada
| | - Mohit Kapoor
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, UHN, Toronto, Ontario, Canada.
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Rolando JC, Melkonian AV, Walt DR. The Present and Future Landscapes of Molecular Diagnostics. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2024; 17:459-474. [PMID: 38360553 DOI: 10.1146/annurev-anchem-061622-015112] [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: 02/17/2024]
Abstract
Nucleic acid testing is the cornerstone of modern molecular diagnostics. This review describes the current status and future directions of molecular diagnostics, focusing on four major techniques: polymerase chain reaction (PCR), next-generation sequencing (NGS), isothermal amplification methods such as recombinase polymerase amplification (RPA) and loop-mediated isothermal amplification (LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR)-based detection methods. We explore the advantages and limitations of each technique, describe how each overlaps with or complements other techniques, and examine current clinical offerings. This review provides a broad perspective into the landscape of molecular diagnostics and highlights potential future directions in this rapidly evolving field.
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Affiliation(s)
- Justin C Rolando
- 1Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts, USA;
- 2Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA
- 3Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Arek V Melkonian
- 1Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts, USA;
- 2Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA
- 3Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - David R Walt
- 1Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts, USA;
- 2Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA
- 3Harvard Medical School, Harvard University, Boston, Massachusetts, USA
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Adamer MF, Brüningk SC, Chen D, Borgwardt K. Biomarker identification by interpretable maximum mean discrepancy. Bioinformatics 2024; 40:i501-i510. [PMID: 38940158 PMCID: PMC11211810 DOI: 10.1093/bioinformatics/btae251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024] Open
Abstract
MOTIVATION In many biomedical applications, we are confronted with paired groups of samples, such as treated versus control. The aim is to detect discriminating features, i.e. biomarkers, based on high-dimensional (omics-) data. This problem can be phrased more generally as a two-sample problem requiring statistical significance testing to establish differences, and interpretations to identify distinguishing features. The multivariate maximum mean discrepancy (MMD) test quantifies group-level differences, whereas statistically significantly associated features are usually found by univariate feature selection. Currently, few general-purpose methods simultaneously perform multivariate feature selection and two-sample testing. RESULTS We introduce a sparse, interpretable, and optimized MMD test (SpInOpt-MMD) that enables two-sample testing and feature selection in the same experiment. SpInOpt-MMD is a versatile method and we demonstrate its application to a variety of synthetic and real-world data types including images, gene expression measurements, and text data. SpInOpt-MMD is effective in identifying relevant features in small sample sizes and outperforms other feature selection methods such as SHapley Additive exPlanations and univariate association analysis in several experiments. AVAILABILITY AND IMPLEMENTATION The code and links to our public data are available at https://github.com/BorgwardtLab/spinoptmmd.
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Affiliation(s)
- Michael F Adamer
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- Swiss Institute for Bioinformatics (SIB), Amphipôle, Quartier UNIL-Sorge, Lausanne 1015, Switzerland
| | - Sarah C Brüningk
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- Swiss Institute for Bioinformatics (SIB), Amphipôle, Quartier UNIL-Sorge, Lausanne 1015, Switzerland
- Department of Health Sciences and Technology, ETH Zurich, Zurich 8008, Switzerland
| | - Dexiong Chen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- Swiss Institute for Bioinformatics (SIB), Amphipôle, Quartier UNIL-Sorge, Lausanne 1015, Switzerland
- Department of Machine Learning and Systems Biology, Max Planck Institute of Biochemistry, Martinsried 82152, Germany
| | - Karsten Borgwardt
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- Swiss Institute for Bioinformatics (SIB), Amphipôle, Quartier UNIL-Sorge, Lausanne 1015, Switzerland
- Department of Machine Learning and Systems Biology, Max Planck Institute of Biochemistry, Martinsried 82152, Germany
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Roy SD, Ramasamy S, Obbineni JM. An evaluation of nucleic acid-based molecular methods for the detection of plant viruses: a systematic review. Virusdisease 2024; 35:357-376. [PMID: 39071869 PMCID: PMC11269559 DOI: 10.1007/s13337-024-00863-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 04/15/2024] [Indexed: 07/30/2024] Open
Abstract
Precise and timely diagnosis of plant viruses is a prerequisite for the implementation of efficient management strategies, considering factors like globalization of trade and climate change facilitating the spread of viruses that lead to agriculture yield losses of billions yearly worldwide. Symptomatic diagnosis alone may not be reliable due to the diverse symptoms and confusion with plant abiotic stresses. It is crucial to detect plant viruses accurately and reliably and do so with little time. A complete understanding of the various detection methods is necessary to achieve this. Enzyme-linked immunosorbent assay (ELISA), has become more popular as a method for detecting viruses but faces limitations such as antibody availability, cost, sample volume, and time. Advanced techniques like polymerase chain reaction (PCR) have surpassed ELISA with its various sensitive variants. Over the last decade, nucleic acid-based molecular methods have gained popularity and have quickly replaced other techniques, such as serological techniques for detecting plant viruses due to their specificity and accuracy. Hence, this review enables the reader to understand the strengths and weaknesses of each molecular technique starting with PCR and its variations, along with various isothermal amplification followed by DNA microarrays, and next-generation sequencing (NGS). As a result of the development of new technologies, NGS is becoming more and more accessible and cheaper, and it looks possible that this approach will replace others as a favoured approach for carrying out regular diagnosis. NGS is also becoming the method of choice for identifying novel viruses. Supplementary Information The online version contains supplementary material available at 10.1007/s13337-024-00863-0.
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Affiliation(s)
- Subha Deep Roy
- School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu India
- School of Agricultural Innovations and Advanced Learning, Vellore Institute of Technology, Vellore, Tamil Nadu India
| | | | - Jagan M. Obbineni
- School of Agricultural Innovations and Advanced Learning, Vellore Institute of Technology, Vellore, Tamil Nadu India
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Bonilla DA, Orozco CA, Forero DA, Odriozola A. Techniques, procedures, and applications in host genetic analysis. ADVANCES IN GENETICS 2024; 111:1-79. [PMID: 38908897 DOI: 10.1016/bs.adgen.2024.05.001] [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: 06/24/2024]
Abstract
This chapter overviews genetic techniques' fundamentals and methodological features, including different approaches, analyses, and applications that have contributed to advancing health and disease. The aim is to describe laboratory methodologies and analyses employed to understand the genetic landscape of different biological contexts, from conventional techniques to cutting-edge technologies. Besides describing detailed aspects of the polymerase chain reaction (PCR) and derived types as one of the principles for many novel techniques, we also discuss microarray analysis, next-generation sequencing, and genome editing technologies such as transcription activator-like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems. These techniques study several phenotypes, ranging from autoimmune disorders to viral diseases. The significance of integrating diverse genetic methodologies and tools to understand host genetics comprehensively and addressing the ethical, legal, and social implications (ELSI) associated with using genetic information is highlighted. Overall, the methods, procedures, and applications in host genetic analysis provided in this chapter furnish researchers and practitioners with a roadmap for navigating the dynamic landscape of host-genome interactions.
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Affiliation(s)
- Diego A Bonilla
- Hologenomiks Research Group, Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain; Research Division, Dynamical Business & Science Society-DBSS International SAS, Bogotá, Colombia.
| | - Carlos A Orozco
- Grupo de Investigación en Biología del Cáncer, Instituto Nacional de Cancerología de Colombia, Bogotá, Colombia
| | - Diego A Forero
- School of Health and Sport Sciences, Fundación Universitaria del Área Andina, Bogotá, Colombia
| | - Adrián Odriozola
- Hologenomiks Research Group, Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain
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Procopio N, Bonicelli A. From flesh to bones: Multi-omics approaches in forensic science. Proteomics 2024; 24:e2200335. [PMID: 38683823 DOI: 10.1002/pmic.202200335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 03/12/2024] [Accepted: 03/26/2024] [Indexed: 05/02/2024]
Abstract
Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.
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Affiliation(s)
- Noemi Procopio
- Research Centre for Field Archaeology and Experimental Taphonomy, School of Law and Policing, University of Central Lancashire, Preston, UK
| | - Andrea Bonicelli
- Research Centre for Field Archaeology and Experimental Taphonomy, School of Law and Policing, University of Central Lancashire, Preston, UK
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Mani K, Rajaguru H. A framework for performance enhancement of classifiers in detection of prostate cancer from microarray gene. Heliyon 2024; 10:e29630. [PMID: 38720727 PMCID: PMC11076651 DOI: 10.1016/j.heliyon.2024.e29630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 03/26/2024] [Accepted: 04/11/2024] [Indexed: 05/12/2024] Open
Abstract
Prostate cancer is a major world health problem for men. This shows how important early detection and accurate diagnosis are for better treatment and patient outcomes. This study compares different ways to find Prostate Cancer (PCa) and label tumors as normal or abnormal, with the goal of speeding up current work in microarray gene data analysis. The study looks at how well several feature extraction methods work with three feature selection strategies: Harmonic Search (HS), Firefly Algorithm (FA), and Elephant Herding Optimization (EHO). The techniques tested are Expectation Maximization (EM), Nonlinear Regression (NLR), K-means, Principal Component Analysis (PCA), and Discrete Cosine Transform (DCT). Eight classifiers are used for the task of classification. These are Random Forest, Decision Tree, Adaboost, XGBoost, and Support Vector Machine (SVM) with linear, polynomial, and radial basis function kernels. This study looks at how well these classifiers work with and without feature selection methods. It finds that the SVM with radial basis function kernel, using DCT for feature extraction and EHO for feature selection, does the best of all of them, with an accuracy of 94.8 % and an error rate of 5.15 %.
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Guan Q, Yan X, Wu Y, Zhou D, Hu J. Biclustering analysis on tree-shaped time-series single cell gene expression data of Caenorhabditis elegans. BMC Bioinformatics 2024; 25:183. [PMID: 38724908 PMCID: PMC11080145 DOI: 10.1186/s12859-024-05800-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 05/01/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND In recent years, gene clustering analysis has become a widely used tool for studying gene functions, efficiently categorizing genes with similar expression patterns to aid in identifying gene functions. Caenorhabditis elegans is commonly used in embryonic research due to its consistent cell lineage from fertilized egg to adulthood. Biologists use 4D confocal imaging to observe gene expression dynamics at the single-cell level. However, on one hand, the observed tree-shaped time-series datasets have characteristics such as non-pairwise data points between different individuals. On the other hand, the influence of cell type heterogeneity should also be considered during clustering, aiming to obtain more biologically significant clustering results. RESULTS A biclustering model is proposed for tree-shaped single-cell gene expression data of Caenorhabditis elegans. Detailedly, a tree-shaped piecewise polynomial function is first employed to fit non-pairwise gene expression time series data. Then, four factors are considered in the objective function, including Pearson correlation coefficients capturing gene correlations, p-values from the Kolmogorov-Smirnov test measuring the similarity between cells, as well as gene expression size and bicluster overlapping size. After that, Genetic Algorithm is utilized to optimize the function. CONCLUSION The results on the small-scale dataset analysis validate the feasibility and effectiveness of our model and are superior to existing classical biclustering models. Besides, gene enrichment analysis is employed to assess the results on the complete real dataset analysis, confirming that the discovered biclustering results hold significant biological relevance.
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Affiliation(s)
- Qi Guan
- School of Mathematical Sciences, Xiamen University, Xiamen, 361005, Fujian, China
| | - Xianzhong Yan
- School of Mathematical Sciences, Xiamen University, Xiamen, 361005, Fujian, China
| | - Yida Wu
- School of Mathematical Sciences, Xiamen University, Xiamen, 361005, Fujian, China
| | - Da Zhou
- School of Mathematical Sciences, Xiamen University, Xiamen, 361005, Fujian, China
| | - Jie Hu
- School of Mathematical Sciences, Xiamen University, Xiamen, 361005, Fujian, China.
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Barreiro C, Albillos SM, García-Estrada C. Penicillium chrysogenum: Beyond the penicillin. ADVANCES IN APPLIED MICROBIOLOGY 2024; 127:143-221. [PMID: 38763527 DOI: 10.1016/bs.aambs.2024.02.006] [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: 05/21/2024]
Abstract
Almost one century after the Sir Alexander Fleming's fortuitous discovery of penicillin and the identification of the fungal producer as Penicillium notatum, later Penicillium chrysogenum (currently reidentified as Penicillium rubens), the molecular mechanisms behind the massive production of penicillin titers by industrial strains could be considered almost fully characterized. However, this filamentous fungus is not only circumscribed to penicillin, and instead, it seems to be full of surprises, thereby producing important metabolites and providing expanded biotechnological applications. This review, in addition to summarizing the classical role of P. chrysogenum as penicillin producer, highlights its ability to generate an array of additional bioactive secondary metabolites and enzymes, together with the use of this microorganism in relevant biotechnological processes, such as bioremediation, biocontrol, production of bioactive nanoparticles and compounds with pharmaceutical interest, revalorization of agricultural and food-derived wastes or the enhancement of food industrial processes and the agricultural production.
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Affiliation(s)
- Carlos Barreiro
- Área de Bioquímica y Biología Molecular, Departamento de Biología Molecular, Facultad de Veterinaria, Universidad de León, León, Spain; Instituto de Biología Molecular, Genómica y Proteómica (INBIOMIC), Universidad de León, León, Spain.
| | - Silvia M Albillos
- Área de Bioquímica y Biología Molecular, Departamento de Biotecnología y Ciencia de los Alimentos, Facultad de Ciencias, Universidad de Burgos, Burgos, Spain
| | - Carlos García-Estrada
- Departamento de Ciencias Biomédicas, Facultad de Veterinaria, Universidad de León, León, Spain; Instituto de Biomedicina (IBIOMED), Universidad de León, León, Spain
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Rentzsch P, Kollotzek A, Mohammadi P, Lappalainen T. Recalibrating differential gene expression by genetic dosage variance prioritizes functionally relevant genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588830. [PMID: 38645217 PMCID: PMC11030425 DOI: 10.1101/2024.04.10.588830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Differential expression (DE) analysis is a widely used method for identifying genes that are functionally relevant for an observed phenotype or biological response. However, typical DE analysis includes selection of genes based on a threshold of fold change in expression under the implicit assumption that all genes are equally sensitive to dosage changes of their transcripts. This tends to favor highly variable genes over more constrained genes where even small changes in expression may be biologically relevant. To address this limitation, we have developed a method to recalibrate each gene's differential expression fold change based on genetic expression variance observed in the human population. The newly established metric ranks statistically differentially expressed genes not by nominal change of expression, but by relative change in comparison to natural dosage variation for each gene. We apply our method to RNA sequencing datasets from rare disease and in-vitro stimulus response experiments. Compared to the standard approach, our method adjusts the bias in discovery towards highly variable genes, and enriches for pathways and biological processes related to metabolic and regulatory activity, indicating a prioritization of functionally relevant driver genes. With that, our method provides a novel view on DE and contributes towards bridging the existing gap between statistical and biological significance. We believe that this approach will simplify the identification of disease causing genes and enhance the discovery of therapeutic targets.
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Affiliation(s)
- Philipp Rentzsch
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden
| | - Aaron Kollotzek
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden
| | - Pejman Mohammadi
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA; Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA; Department of Genome Science, University of Washington, Seattle, WA, USA
| | - Tuuli Lappalainen
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden
- New York Genome Center, New York, NY, USA
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