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Moeckel C, Mareboina M, Konnaris MA, Chan CS, Mouratidis I, Montgomery A, Chantzi N, Pavlopoulos GA, Georgakopoulos-Soares I. A survey of k-mer methods and applications in bioinformatics. Comput Struct Biotechnol J 2024; 23:2289-2303. [PMID: 38840832 PMCID: PMC11152613 DOI: 10.1016/j.csbj.2024.05.025] [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: 03/13/2024] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 06/07/2024] Open
Abstract
The rapid progression of genomics and proteomics has been driven by the advent of advanced sequencing technologies, large, diverse, and readily available omics datasets, and the evolution of computational data processing capabilities. The vast amount of data generated by these advancements necessitates efficient algorithms to extract meaningful information. K-mers serve as a valuable tool when working with large sequencing datasets, offering several advantages in computational speed and memory efficiency and carrying the potential for intrinsic biological functionality. This review provides an overview of the methods, applications, and significance of k-mers in genomic and proteomic data analyses, as well as the utility of absent sequences, including nullomers and nullpeptides, in disease detection, vaccine development, therapeutics, and forensic science. Therefore, the review highlights the pivotal role of k-mers in addressing current genomic and proteomic problems and underscores their potential for future breakthroughs in research.
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Affiliation(s)
- Camille Moeckel
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Manvita Mareboina
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Maxwell A. Konnaris
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Candace S.Y. Chan
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Ioannis Mouratidis
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA
- Huck Institute of the Life Sciences, Penn State University, University Park, Pennsylvania, USA
| | - Austin Montgomery
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Nikol Chantzi
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA
| | | | - Ilias Georgakopoulos-Soares
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA
- Huck Institute of the Life Sciences, Penn State University, University Park, Pennsylvania, USA
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Podgrajsek R, Hodzic A, Stimpfel M, Kunej T, Peterlin B. Insight into the complexity of male infertility: a multi-omics review. Syst Biol Reprod Med 2024; 70:73-90. [PMID: 38517373 DOI: 10.1080/19396368.2024.2317804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 02/06/2024] [Indexed: 03/23/2024]
Abstract
Male infertility is a reproductive disorder, accounting for 40-50% of infertility. Currently, in about 70% of infertile men, the cause remains unknown. With the introduction of novel omics and advancement in high-throughput technology, potential biomarkers are emerging. The main purpose of our work was to overview different aspects of omics approaches in association with idiopathic male infertility and highlight potential genes, transcripts, non-coding RNA, proteins, and metabolites worth further exploring. Using the Gene Ontology (GO) analysis, we aimed to compare enriched GO terms from each omics approach and determine their overlapping. A PubMed database screening for the literature published between February 2014 and June 2022 was performed using the keywords: male infertility in association with different omics approaches: genomics, epigenomics, transcriptomics, ncRNAomics, proteomics, and metabolomics. A GO enrichment analysis was performed using the Enrichr tool. We retrieved 281 global studies: 171 genomics (DNA level), 21 epigenomics (19 of methylation and two histone residue modifications), 15 transcriptomics, 31 non-coding RNA, 29 proteomics, two protein posttranslational modification, and 19 metabolomics studies. Gene ontology comparison showed that different omics approaches lead to the identification of different molecular factors and that the corresponding GO terms, obtained from different omics approaches, do not overlap to a larger extent. With the integration of novel omics levels into the research of idiopathic causes of male infertility, using multi-omic systems biology approaches, we will be closer to finding the potential biomarkers and consequently becoming aware of the entire spectrum of male infertility, their cause, prognosis, and potential treatment.
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Affiliation(s)
- Rebeka Podgrajsek
- Department of Human Reproduction, University Medical Center Ljubljana, Ljubljana, Slovenia
| | - Alenka Hodzic
- Clinical Institute of Genomic Medicine, University Medical Center Ljubljana, Ljubljana, Slovenia
- Faculty of Health Sciences, University of Novo mesto, Novo Mesto, Slovenia
| | - Martin Stimpfel
- Department of Human Reproduction, University Medical Center Ljubljana, Ljubljana, Slovenia
- Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Tanja Kunej
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, Slovenia
| | - Borut Peterlin
- Clinical Institute of Genomic Medicine, University Medical Center Ljubljana, Ljubljana, Slovenia
- Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
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3
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Labory J, Njomgue-Fotso E, Bottini S. Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data. Comput Struct Biotechnol J 2024; 23:1274-1287. [PMID: 38560281 PMCID: PMC10979063 DOI: 10.1016/j.csbj.2024.03.016] [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: 12/21/2023] [Revised: 03/12/2024] [Accepted: 03/18/2024] [Indexed: 04/04/2024] Open
Abstract
Objective Classification tasks are an open challenge in the field of biomedicine. While several machine-learning techniques exist to accomplish this objective, several peculiarities associated with biomedical data, especially when it comes to omics measurements, prevent their use or good performance achievements. Omics approaches aim to understand a complex biological system through systematic analysis of its content at the molecular level. On the other hand, omics data are heterogeneous, sparse and affected by the classical "curse of dimensionality" problem, i.e. having much fewer observation, samples (n) than omics features (p). Furthermore, a major problem with multi-omics data is the imbalance either at the class or feature level. The objective of this work is to study whether feature extraction and/or feature selection techniques can improve the performances of classification machine-learning algorithms on omics measurements. Methods Among all omics, metabolomics has emerged as a powerful tool in cancer research, facilitating a deeper understanding of the complex metabolic landscape associated with tumorigenesis and tumor progression. Thus, we selected three publicly available metabolomics datasets, and we applied several feature extraction techniques both linear and non-linear, coupled or not with feature selection methods, and evaluated the performances regarding patient classification in the different configurations for the three datasets. Results We provide general workflow and guidelines on when to use those techniques depending on the characteristics of the data available. To further test the extension of our approach to other omics data, we have included a transcriptomics and a proteomics data. Overall, for all datasets, we showed that applying supervised feature selection improves the performances of feature extraction methods for classification purposes. Scripts used to perform all analyses are available at: https://github.com/Plant-Net/Metabolomic_project/.
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Affiliation(s)
- Justine Labory
- Université Côte d′Azur, Center of Modeling Simulation and Interactions, Nice, France
- INRAE, Université Côte d′Azur, CNRS, Institut Sophia Agrobiotech, Sophia-Antipolis, France
- Université Côte d′Azur, Inserm U1081, CNRS UMR 7284, Institute for Research on Cancer and Aging, Nice (IRCAN), Nice, France
| | | | - Silvia Bottini
- Université Côte d′Azur, Center of Modeling Simulation and Interactions, Nice, France
- INRAE, Université Côte d′Azur, CNRS, Institut Sophia Agrobiotech, Sophia-Antipolis, France
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4
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Pitchika V, Büttner M, Schwendicke F. Artificial intelligence and personalized diagnostics in periodontology: A narrative review. Periodontol 2000 2024. [PMID: 38927004 DOI: 10.1111/prd.12586] [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: 02/06/2024] [Revised: 04/29/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024]
Abstract
Periodontal diseases pose a significant global health burden, requiring early detection and personalized treatment approaches. Traditional diagnostic approaches in periodontology often rely on a "one size fits all" approach, which may overlook the unique variations in disease progression and response to treatment among individuals. This narrative review explores the role of artificial intelligence (AI) and personalized diagnostics in periodontology, emphasizing the potential for tailored diagnostic strategies to enhance precision medicine in periodontal care. The review begins by elucidating the limitations of conventional diagnostic techniques. Subsequently, it delves into the application of AI models in analyzing diverse data sets, such as clinical records, imaging, and molecular information, and its role in periodontal training. Furthermore, the review also discusses the role of research community and policymakers in integrating personalized diagnostics in periodontal care. Challenges and ethical considerations associated with adopting AI-based personalized diagnostic tools are also explored, emphasizing the need for transparent algorithms, data safety and privacy, ongoing multidisciplinary collaboration, and patient involvement. In conclusion, this narrative review underscores the transformative potential of AI in advancing periodontal diagnostics toward a personalized paradigm, and their integration into clinical practice holds the promise of ushering in a new era of precision medicine for periodontal care.
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Affiliation(s)
- Vinay Pitchika
- Department of Conservative Dentistry and Periodontology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Martha Büttner
- Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Falk Schwendicke
- Department of Conservative Dentistry and Periodontology, LMU University Hospital, LMU Munich, Munich, Germany
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5
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Schiebout C, Frost HR. CAraCAl: CAMML with the integration of chromatin accessibility. BMC Bioinformatics 2024; 25:212. [PMID: 38872103 PMCID: PMC11170880 DOI: 10.1186/s12859-024-05833-3] [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: 03/07/2024] [Accepted: 06/10/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND A vital step in analyzing single-cell data is ascertaining which cell types are present in a dataset, and at what abundance. In many diseases, the proportions of varying cell types can have important implications for health and prognosis. Most approaches for cell type annotation have centered around cell typing for single-cell RNA-sequencing (scRNA-seq) and have had promising success. However, reliable methods are lacking for many other single-cell modalities such as single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), which quantifies the extent to which genes of interest in each cell are epigenetically "open" for expression. RESULTS To leverage the informative potential of scATAC-seq data, we developed CAMML with the integration of chromatin accessibility (CAraCAl), a bioinformatic method that performs cell typing on scATAC-seq data. CAraCAl performs cell typing by scoring each cell for its enrichment of cell type-specific gene sets. These gene sets are composed of the most upregulated or downregulated genes present in each cell type according to projected gene activity. CONCLUSIONS We found that CAraCAl does not improve performance beyond CAMML when scRNA-seq is present, but if only scATAC-seq is available, CAraCAl performs cell typing relatively successfully. As such, we also discuss best practices for cell typing and the strengths and weaknesses of various cell annotation options.
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Affiliation(s)
- Courtney Schiebout
- Department of Biomedical Data Science, Dartmouth College, Hanover, NH, 03766, USA.
| | - H Robert Frost
- Department of Biomedical Data Science, Dartmouth College, Hanover, NH, 03766, USA
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6
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Lockwood MB, Sung C, Alvernaz SA, Lee JR, Chin JL, Nayebpour M, Bernabé BP, Tussing-Humphreys LM, Li H, Spaggiari M, Martinino A, Park CG, Chlipala GE, Doorenbos AZ, Green SJ. The Gut Microbiome and Symptom Burden After Kidney Transplantation: An Overview and Research Opportunities. Biol Res Nurs 2024:10998004241256031. [PMID: 38836469 DOI: 10.1177/10998004241256031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
Many kidney transplant recipients continue to experience high symptom burden despite restoration of kidney function. High symptom burden is a significant driver of quality of life. In the post-transplant setting, high symptom burden has been linked to negative outcomes including medication non-adherence, allograft rejection, graft loss, and even mortality. Symbiotic bacteria (microbiota) in the human gastrointestinal tract critically interact with the immune, endocrine, and neurological systems to maintain homeostasis of the host. The gut microbiome has been proposed as an underlying mechanism mediating symptoms in several chronic medical conditions including irritable bowel syndrome, chronic fatigue syndrome, fibromyalgia, and psychoneurological disorders via the gut-brain-microbiota axis, a bidirectional signaling pathway between the enteric and central nervous system. Post-transplant exposure to antibiotics, antivirals, and immunosuppressant medications results in significant alterations in gut microbiota community composition and function, which in turn alter these commensal microorganisms' protective effects. This overview will discuss the current state of the science on the effects of the gut microbiome on symptom burden in kidney transplantation and future directions to guide this field of study.
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Affiliation(s)
- Mark B Lockwood
- Department of Biobehavioral Nursing Science, University of Illinois Chicago College of Nursing, Chicago, IL, USA
| | - Choa Sung
- Post-Doctoral Fellow, Department of Biobehavioral Nursing Science, University of Illinois Chicago College of Nursing, Chicago, IL, USA
| | - Suzanne A Alvernaz
- Graduate Student, Department of Biomedical Engineering, University of Illinois ChicagoColleges of Engineering and Medicine, Chicago, IL, USA
| | - John R Lee
- Division of Nephrology and Hypertension, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jennifer L Chin
- Medical Student, Touro College of Osteopathic Medicine, Middletown, NY, USA
| | - Mehdi Nayebpour
- Virginia BioAnalytics LLC, Washington, District of Columbia, USA
| | - Beatriz Peñalver Bernabé
- Graduate Student, Department of Biomedical Engineering, University of Illinois ChicagoColleges of Engineering and Medicine, Chicago, IL, USA
| | - Lisa M Tussing-Humphreys
- Department of Kinesiology and Nutrition, College of Applied Health Sciences, University of Illinois Chicago, Chicago, IL, USA
| | - Hongjin Li
- Department of Biobehavioral Nursing Science, University of Illinois Chicago College of Nursing, Chicago, IL, USA
| | - Mario Spaggiari
- Division of Transplantation, Department of Surgery, University of Illinois at Chicago, Chicago, IL, USA
| | - Alessandro Martinino
- Division of Transplantation, Department of Surgery, University of Illinois at Chicago, Chicago, IL, USA
| | - Chang G Park
- Department of Population Health Nursing Science, Office of Research Facilitation, University of Illinois Chicago, Chicago, IL, USA
| | - George E Chlipala
- Research Core Facility, Research Resources Center, University of Illinois Chicago, Chicago, IL, USA
| | - Ardith Z Doorenbos
- Department of Biobehavioral Nursing Science, University of Illinois ChicagoCollege of Nursing, Chicago, IL, USA
| | - Stefan J Green
- Department of Internal Medicine, Division of Infectious Diseases, Rush University Medical Center, Chicago, IL, USA
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7
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Lin W, Ji J, Su KJ, Qiu C, Tian Q, Zhao LJ, Luo Z, Wu C, Shen H, Deng H. omicsMIC: a comprehensive benchmarking platform for robust comparison of imputation methods in mass spectrometry-based omics data. NAR Genom Bioinform 2024; 6:lqae071. [PMID: 38881578 PMCID: PMC11177553 DOI: 10.1093/nargab/lqae071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 04/25/2024] [Accepted: 05/30/2024] [Indexed: 06/18/2024] Open
Abstract
Mass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in mass spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometry-based omics with Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. omicsMIC is freely available at https://github.com/WQLin8/omicsMIC.
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Affiliation(s)
- Weiqiang Lin
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Jiadong Ji
- Institute for Financial Studies, Shandong University, Jinan, Shandong 250100, China
| | - Kuan-Jui Su
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Chuan Qiu
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Qing Tian
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Lan-Juan Zhao
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Zhe Luo
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Hui Shen
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Hongwen Deng
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
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8
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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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9
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Kuraz Abebe B, Wang J, Guo J, Wang H, Li A, Zan L. A review of the role of epigenetic studies for intramuscular fat deposition in beef cattle. Gene 2024; 908:148295. [PMID: 38387707 DOI: 10.1016/j.gene.2024.148295] [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: 10/26/2023] [Revised: 01/23/2024] [Accepted: 02/15/2024] [Indexed: 02/24/2024]
Abstract
Intramuscular fat (IMF) deposition profoundly influences meat quality and economic value in beef cattle production. Meanwhile, contemporary developments in epigenetics have opened new outlooks for understanding the molecular basics of IMF regulation, and it has become a key area of research for world scholars. Therefore, the aim of this paper was to provide insight and synthesis into the intricate relationship between epigenetic mechanisms and IMF deposition in beef cattle. The methodology involves a thorough analysis of existing literature, including pertinent books, academic journals, and online resources, to provide a comprehensive overview of the role of epigenetic studies in IMF deposition in beef cattle. This review summarizes the contemporary studies in epigenetic mechanisms in IMF regulation, high-resolution epigenomic mapping, single-cell epigenomics, multi-omics integration, epigenome editing approaches, longitudinal studies in cattle growth, environmental epigenetics, machine learning in epigenetics, ethical and regulatory considerations, and translation to industry practices from perspectives of IMF deposition in beef cattle. Moreover, this paper highlights DNA methylation, histone modifications, acetylation, phosphorylation, ubiquitylation, non-coding RNAs, DNA hydroxymethylation, epigenetic readers, writers, and erasers, chromatin immunoprecipitation followed by sequencing, whole genome bisulfite sequencing, epigenome-wide association studies, and their profound impact on the expression of crucial genes governing adipogenesis and lipid metabolism. Nutrition and stress also have significant influences on epigenetic modifications and IMF deposition. The key findings underscore the pivotal role of epigenetic studies in understanding and enhancing IMF deposition in beef cattle, with implications for precision livestock farming and ethical livestock management. In conclusion, this review highlights the crucial significance of epigenetic pathways and environmental factors in affecting IMF deposition in beef cattle, providing insightful information for improving the economics and meat quality of cattle production.
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Affiliation(s)
- Belete Kuraz Abebe
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China; Department of Animal Science, Werabe University, P.O. Box 46, Werabe, Ethiopia
| | - Jianfang Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Juntao Guo
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Hongbao Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Anning Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China; National Beef Cattle Improvement Center, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China.
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10
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Lu Q, Yu A, Pu J, Chen D, Zhong Y, Bai D, Yang L. Post-stroke cognitive impairment: exploring molecular mechanisms and omics biomarkers for early identification and intervention. Front Mol Neurosci 2024; 17:1375973. [PMID: 38845616 PMCID: PMC11153683 DOI: 10.3389/fnmol.2024.1375973] [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: 01/24/2024] [Accepted: 05/08/2024] [Indexed: 06/09/2024] Open
Abstract
Post-stroke cognitive impairment (PSCI) is a major stroke consequence that has a severe impact on patients' quality of life and survival rate. For this reason, it is especially crucial to identify and intervene early in high-risk groups during the acute phase of stroke. Currently, there are no reliable and efficient techniques for the early diagnosis, appropriate evaluation, or prognostication of PSCI. Instead, plenty of biomarkers in stroke patients have progressively been linked to cognitive impairment in recent years. High-throughput omics techniques that generate large amounts of data and process it to a high quality have been used to screen and identify biomarkers of PSCI in order to investigate the molecular mechanisms of the disease. These techniques include metabolomics, which explores dynamic changes in the organism, gut microbiomics, which studies host-microbe interactions, genomics, which elucidates deeper disease mechanisms, transcriptomics and proteomics, which describe gene expression and regulation. We looked through electronic databases like PubMed, the Cochrane Library, Embase, Web of Science, and common databases for each omics to find biomarkers that might be connected to the pathophysiology of PSCI. As all, we found 34 studies: 14 in the field of metabolomics, 5 in the field of gut microbiomics, 5 in the field of genomics, 4 in the field of transcriptomics, and 7 in the field of proteomics. We discovered that neuroinflammation, oxidative stress, and atherosclerosis may be the primary causes of PSCI development, and that metabolomics may play a role in the molecular mechanisms of PSCI. In this study, we summarized the existing issues across omics technologies and discuss the latest discoveries of PSCI biomarkers in the context of omics, with the goal of investigating the molecular causes of post-stroke cognitive impairment. We also discuss the potential therapeutic utility of omics platforms for PSCI mechanisms, diagnosis, and intervention in order to promote the area's advancement towards precision PSCI treatment.
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Affiliation(s)
- Qiuyi Lu
- Department of Rehabilitation, The First Affiliated Hospital of Chongqing Medical University, Chonging, China
| | - Anqi Yu
- Department of Rehabilitation, The First Affiliated Hospital of Chongqing Medical University, Chonging, China
| | - Juncai Pu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chonging, China
| | - Dawei Chen
- Department of Rehabilitation, The First Affiliated Hospital of Chongqing Medical University, Chonging, China
| | - Yujie Zhong
- Department of Rehabilitation, The First Affiliated Hospital of Chongqing Medical University, Chonging, China
| | - Dingqun Bai
- Department of Rehabilitation, The First Affiliated Hospital of Chongqing Medical University, Chonging, China
| | - Lining Yang
- Department of Rehabilitation, The First Affiliated Hospital of Chongqing Medical University, Chonging, China
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11
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Jangid H, Garg S, Kashyap P, Karnwal A, Shidiki A, Kumar G. Bioprospecting of Aspergillus sp. as a promising repository for anti-cancer agents: a comprehensive bibliometric investigation. Front Microbiol 2024; 15:1379602. [PMID: 38812679 PMCID: PMC11133633 DOI: 10.3389/fmicb.2024.1379602] [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: 01/31/2024] [Accepted: 04/30/2024] [Indexed: 05/31/2024] Open
Abstract
Cancer remains a significant global health challenge, claiming nearly 10 million lives in 2020 according to the World Health Organization. In the quest for novel treatments, fungi, especially Aspergillus species, have emerged as a valuable source of bioactive compounds with promising anticancer properties. This study conducts a comprehensive bibliometric analysis to map the research landscape of Aspergillus in oncology, examining publications from 1982 to the present. We observed a marked increase in research activity starting in 2000, with a notable peak from 2005 onwards. The analysis identifies key contributors, including Mohamed GG, who has authored 15 papers with 322 citations, and El-Sayed Asa, with 14 papers and 264 citations. Leading countries in this research field include India, Egypt, and China, with King Saud University and Cairo University as the leading institutions. Prominent research themes identified are "endophyte," "green synthesis," "antimicrobial," "anti-cancer," and "biological activities," indicating a shift towards environmentally sustainable drug development. Our findings highlight the considerable potential of Aspergillus for developing new anticancer therapies and underscore the necessity for further research to harness these natural compounds for clinical use.
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Affiliation(s)
- Himanshu Jangid
- School of Bioengineering and Biosciences, Lovely Professional University, Jalandhar, Punjab, India
| | - Sonu Garg
- Department of Biotechnology, Mahatma Jyoti Rao Phoole University, Jaipur, Rajasthan, India
| | - Piyush Kashyap
- School of Agriculture, Lovely Professional University, Jalandhar, Punjab, India
| | - Arun Karnwal
- School of Bioengineering and Biosciences, Lovely Professional University, Jalandhar, Punjab, India
| | - Amrullah Shidiki
- Department of Microbiology, National Medical College & Teaching Hospital, Birgunj, Nepal
| | - Gaurav Kumar
- School of Bioengineering and Biosciences, Lovely Professional University, Jalandhar, Punjab, India
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12
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Khan Q, Wang Y, Xia G, Yang H, Luo Z, Zhang Y. Deleterious Effects of Heat Stress on the Tomato, Its Innate Responses, and Potential Preventive Strategies in the Realm of Emerging Technologies. Metabolites 2024; 14:283. [PMID: 38786760 PMCID: PMC11122942 DOI: 10.3390/metabo14050283] [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: 04/09/2024] [Revised: 04/28/2024] [Accepted: 05/08/2024] [Indexed: 05/25/2024] Open
Abstract
The tomato is a fruit vegetable rich in nutritional and medicinal value grown in greenhouses and fields worldwide. It is severely sensitive to heat stress, which frequently occurs with rising global warming. Predictions indicate a 0.2 °C increase in average surface temperatures per decade for the next three decades, which underlines the threat of austere heat stress in the future. Previous studies have reported that heat stress adversely affects tomato growth, limits nutrient availability, hammers photosynthesis, disrupts reproduction, denatures proteins, upsets signaling pathways, and damages cell membranes. The overproduction of reactive oxygen species in response to heat stress is toxic to tomato plants. The negative consequences of heat stress on the tomato have been the focus of much investigation, resulting in the emergence of several therapeutic interventions. However, a considerable distance remains to be covered to develop tomato varieties that are tolerant to current heat stress and durable in the perspective of increasing global warming. This current review provides a critical analysis of the heat stress consequences on the tomato in the context of global warming, its innate response to heat stress, and the elucidation of domains characterized by a scarcity of knowledge, along with potential avenues for enhancing sustainable tolerance against heat stress through the involvement of diverse advanced technologies. The particular mechanism underlying thermotolerance remains indeterminate and requires further elucidatory investigation. The precise roles and interplay of signaling pathways in response to heat stress remain unresolved. The etiology of tomato plants' physiological and molecular responses against heat stress remains unexplained. Utilizing modern functional genomics techniques, including transcriptomics, proteomics, and metabolomics, can assist in identifying potential candidate proteins, metabolites, genes, gene networks, and signaling pathways contributing to tomato stress tolerance. Improving tomato tolerance against heat stress urges a comprehensive and combined strategy including modern techniques, the latest apparatuses, speedy breeding, physiology, and molecular markers to regulate their physiological, molecular, and biochemical reactions.
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Affiliation(s)
| | | | | | | | | | - Yan Zhang
- Department of Landscape and Horticulture‚ Ecology College‚ Lishui University‚ Lishui 323000‚ China; (Q.K.); (Y.W.); (G.X.); (H.Y.); (Z.L.)
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13
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Al-Husinat L, Azzam S, Al Sharie S, Al Sharie AH, Battaglini D, Robba C, Marini JJ, Thornton LT, Cruz FF, Silva PL, Rocco PRM. Effects of mechanical ventilation on the interstitial extracellular matrix in healthy lungs and lungs affected by acute respiratory distress syndrome: a narrative review. Crit Care 2024; 28:165. [PMID: 38750543 PMCID: PMC11094887 DOI: 10.1186/s13054-024-04942-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: 01/17/2024] [Accepted: 05/06/2024] [Indexed: 05/19/2024] Open
Abstract
BACKGROUND Mechanical ventilation, a lifesaving intervention in critical care, can lead to damage in the extracellular matrix (ECM), triggering inflammation and ventilator-induced lung injury (VILI), particularly in conditions such as acute respiratory distress syndrome (ARDS). This review discusses the detailed structure of the ECM in healthy and ARDS-affected lungs under mechanical ventilation, aiming to bridge the gap between experimental insights and clinical practice by offering a thorough understanding of lung ECM organization and the dynamics of its alteration during mechanical ventilation. MAIN TEXT Focusing on the clinical implications, we explore the potential of precise interventions targeting the ECM and cellular signaling pathways to mitigate lung damage, reduce inflammation, and ultimately improve outcomes for critically ill patients. By analyzing a range of experimental studies and clinical papers, particular attention is paid to the roles of matrix metalloproteinases (MMPs), integrins, and other molecules in ECM damage and VILI. This synthesis not only sheds light on the structural changes induced by mechanical stress but also underscores the importance of cellular responses such as inflammation, fibrosis, and excessive activation of MMPs. CONCLUSIONS This review emphasizes the significance of mechanical cues transduced by integrins and their impact on cellular behavior during ventilation, offering insights into the complex interactions between mechanical ventilation, ECM damage, and cellular signaling. By understanding these mechanisms, healthcare professionals in critical care can anticipate the consequences of mechanical ventilation and use targeted strategies to prevent or minimize ECM damage, ultimately leading to better patient management and outcomes in critical care settings.
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Affiliation(s)
- Lou'i Al-Husinat
- Department of Clinical Sciences, Faculty of Medicine, Yarmouk University, Irbid, Jordan
| | - Saif Azzam
- Faculty of Medicine, Yarmouk University, Irbid, Jordan
| | | | - Ahmed H Al Sharie
- Department of Pathology and Microbiology, Jordan University of Science and Technology, Irbid, Jordan
| | - Denise Battaglini
- Anesthesia and Intensive Care, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Chiara Robba
- Anesthesia and Intensive Care, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Dipartimento di Scienze Chirurgiche e Diagnostiche, Università Degli Studi di Genova, Genoa, Italy
| | - John J Marini
- Department of Pulmonary and Critical Care Medicine, University of Minnesota, Minneapolis, St Paul, MN, USA
| | - Lauren T Thornton
- Department of Pulmonary and Critical Care Medicine, University of Minnesota, Minneapolis, St Paul, MN, USA
| | - Fernanda F Cruz
- Laboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Pedro L Silva
- Laboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Patricia R M Rocco
- Laboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
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14
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Jadhav Y, Thakur NR, Ingle KP, Ceasar SA. The role of phenomics and genomics in delineating the genetic basis of complex traits in millets. PHYSIOLOGIA PLANTARUM 2024; 176:e14349. [PMID: 38783512 DOI: 10.1111/ppl.14349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 04/22/2024] [Accepted: 04/26/2024] [Indexed: 05/25/2024]
Abstract
Millets, comprising a diverse group of small-seeded grains, have emerged as vital crops with immense nutritional, environmental, and economic significance. The comprehension of complex traits in millets, influenced by multifaceted genetic determinants, presents a compelling challenge and opportunity in agricultural research. This review delves into the transformative roles of phenomics and genomics in deciphering these intricate genetic architectures. On the phenomics front, high-throughput platforms generate rich datasets on plant morphology, physiology, and performance in diverse environments. This data, coupled with field trials and controlled conditions, helps to interpret how the environment interacts with genetics. Genomics provides the underlying blueprint for these complex traits. Genome sequencing and genotyping technologies have illuminated the millet genome landscape, revealing diverse gene pools and evolutionary relationships. Additionally, different omics approaches unveil the intricate information of gene expression, protein function, and metabolite accumulation driving phenotypic expression. This multi-omics approach is crucial for identifying candidate genes and unfolding the intricate pathways governing complex traits. The review highlights the synergy between phenomics and genomics. Genomically informed phenotyping targets specific traits, reducing the breeding size and cost. Conversely, phenomics identifies promising germplasm for genomic analysis, prioritizing variants with superior performance. This dynamic interplay accelerates breeding programs and facilitates the development of climate-smart, nutrient-rich millet varieties and hybrids. In conclusion, this review emphasizes the crucial roles of phenomics and genomics in unlocking the genetic enigma of millets.
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Affiliation(s)
- Yashoda Jadhav
- International Crops Research Institutes for the Semi-Arid Tropics, Patancheru, TS, India
| | - Niranjan Ravindra Thakur
- International Crops Research Institutes for the Semi-Arid Tropics, Patancheru, TS, India
- Vasantrao Naik Marathwada Agricultural University, Parbhani, MS, India
| | | | - Stanislaus Antony Ceasar
- Division of Plant Molecular Biology and Biotechnology, Department of Biosciences, Rajagiri College of Social Sciences, Kochi, KL, India
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15
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Chandy M, Hill T, Jimenez-Tellez N, Wu JC, Sarles SE, Hensel E, Wang Q, Rahman I, Conklin DJ. Addressing Cardiovascular Toxicity Risk of Electronic Nicotine Delivery Systems in the Twenty-First Century: "What Are the Tools Needed for the Job?" and "Do We Have Them?". Cardiovasc Toxicol 2024; 24:435-471. [PMID: 38555547 DOI: 10.1007/s12012-024-09850-9] [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: 12/07/2023] [Accepted: 03/19/2024] [Indexed: 04/02/2024]
Abstract
Cigarette smoking is positively and robustly associated with cardiovascular disease (CVD), including hypertension, atherosclerosis, cardiac arrhythmias, stroke, thromboembolism, myocardial infarctions, and heart failure. However, after more than a decade of ENDS presence in the U.S. marketplace, uncertainty persists regarding the long-term health consequences of ENDS use for CVD. New approach methods (NAMs) in the field of toxicology are being developed to enhance rapid prediction of human health hazards. Recent technical advances can now consider impact of biological factors such as sex and race/ethnicity, permitting application of NAMs findings to health equity and environmental justice issues. This has been the case for hazard assessments of drugs and environmental chemicals in areas such as cardiovascular, respiratory, and developmental toxicity. Despite these advances, a shortage of widely accepted methodologies to predict the impact of ENDS use on human health slows the application of regulatory oversight and the protection of public health. Minimizing the time between the emergence of risk (e.g., ENDS use) and the administration of well-founded regulatory policy requires thoughtful consideration of the currently available sources of data, their applicability to the prediction of health outcomes, and whether these available data streams are enough to support an actionable decision. This challenge forms the basis of this white paper on how best to reveal potential toxicities of ENDS use in the human cardiovascular system-a primary target of conventional tobacco smoking. We identify current approaches used to evaluate the impacts of tobacco on cardiovascular health, in particular emerging techniques that replace, reduce, and refine slower and more costly animal models with NAMs platforms that can be applied to tobacco regulatory science. The limitations of these emerging platforms are addressed, and systems biology approaches to close the knowledge gap between traditional models and NAMs are proposed. It is hoped that these suggestions and their adoption within the greater scientific community will result in fresh data streams that will support and enhance the scientific evaluation and subsequent decision-making of tobacco regulatory agencies worldwide.
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Affiliation(s)
- Mark Chandy
- Robarts Research Institute, Western University, London, N6A 5K8, Canada
| | - Thomas Hill
- Division of Nonclinical Science, Center for Tobacco Products, US Food and Drug Administration, Silver Spring, MD, 20993, USA
| | - Nerea Jimenez-Tellez
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - Joseph C Wu
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - S Emma Sarles
- Biomedical and Chemical Engineering PhD Program, Rochester Institute of Technology, Rochester, NY, 14623, USA
| | - Edward Hensel
- Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, NY, 14623, USA
| | - Qixin Wang
- Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Irfan Rahman
- Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Daniel J Conklin
- Division of Environmental Medicine, Department of Medicine, Center for Cardiometabolic Science, Christina Lee Brown Envirome Institute, University of Louisville, 580 S. Preston St., Delia Baxter, Rm. 404E, Louisville, KY, 40202, USA.
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16
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Chettiar V, Patel A, Chettiar SS, Jhala DD. Meta-analysis of endometrial transcriptome data reveals novel molecular targets for recurrent implantation failure. J Assist Reprod Genet 2024; 41:1417-1431. [PMID: 38456991 PMCID: PMC11143096 DOI: 10.1007/s10815-024-03077-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/27/2024] [Indexed: 03/09/2024] Open
Abstract
PURPOSE Gene expression analysis of the endometrium has been shown to be a useful approach for identifying the molecular signatures and pathways involved in recurrent implantation failure (RIF). Nevertheless, individual studies have limitations in terms of study design, methodology and analysis to detect minor changes in expression levels or identify novel gene signatures associated with RIF. METHOD To overcome this, we conducted an in silico meta-analysis of nine studies, the systematic collection and integration of gene expression data, utilizing rigorous selection criteria and statistical techniques to ensure the robustness of our findings. RESULTS Our meta-analysis successfully unveiled a meta-signature of 49 genes closely associated with RIF. Of these genes, 38 were upregulated and 11 downregulated in RIF patients' endometrium and believed to participate in key processes like cell differentiation, communication, and adhesion. GADD45A, IGF2, and LIF, known for their roles in implantation, were identified, along with lesser-studied genes like OPRK1, PSIP1, SMCHD1, and SOD2 related to female infertility. Many of these genes are involved in MAPK and PI3K-Akt pathways, indicating their role in inflammation. We also investigated to look for key miRNAs regulating these 49 dysregulated mRNAs as potential diagnostic biomarkers. Along with this, we went to associate protein-protein interactions of 49 genes, and we could recognize one cluster consisting of 11 genes (consisted of 22 nodes and 11 edges) with the highest score (p = 0.001). Finally, we validated some of the genes by qRT-PCR in our samples. CONCLUSION In summary, the meta-signature genes hold promise for improving RIF patient identification and facilitating the development of personalized treatment strategies, illuminating the multifaceted nature of this complex condition.
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Affiliation(s)
- Venkatlaxmi Chettiar
- Department of Life Sciences, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India
| | - Alpesh Patel
- GeneXplore Diagnostics and Research Centre PVT. LTD., Ahmedabad, Gujarat, India
| | | | - Devendrasinh D Jhala
- Department of Zoology, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
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17
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Trinks J, Mascardi MF, Gadano A, Marciano S. Omics-based biomarkers as useful tools in metabolic dysfunction-associated steatotic liver disease clinical practice: How far are we? World J Gastroenterol 2024; 30:1982-1989. [PMID: 38681130 PMCID: PMC11045490 DOI: 10.3748/wjg.v30.i14.1982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 02/19/2024] [Accepted: 03/25/2024] [Indexed: 04/12/2024] Open
Abstract
Unmet needs exist in metabolic dysfunction-associated steatotic liver disease (MASLD) risk stratification. Our ability to identify patients with MASLD with advanced fibrosis and at higher risk for adverse outcomes is still limited. Incorporating novel biomarkers could represent a meaningful improvement to current risk predictors. With this aim, omics technologies have revolutionized the process of MASLD biomarker discovery over the past decades. While the research in this field is thriving, much of the publication has been haphazard, often using single-omics data and specimen sets of convenience, with many identified candidate biomarkers but lacking clinical validation and utility. If we incorporate these biomarkers to direct patients' management, it should be considered that the roadmap for translating a newly discovered omics-based signature to an actual, analytically valid test useful in MASLD clinical practice is rigorous and, therefore, not easily accomplished. This article presents an overview of this area's current state, the conceivable opportunities and challenges of omics-based laboratory diagnostics, and a roadmap for improving MASLD biomarker research.
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Affiliation(s)
- Julieta Trinks
- Instituto de Medicina Traslacional e Ingeniería Biomédica - Consejo Nacional de Investigaciones Científicas y Técnicas - Instituto Universitario del Hospital Italiano - Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires C1199ACL, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires C1425FQB, Argentina
| | - María F Mascardi
- Instituto de Medicina Traslacional e Ingeniería Biomédica - Consejo Nacional de Investigaciones Científicas y Técnicas - Instituto Universitario del Hospital Italiano - Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires C1199ACL, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires C1425FQB, Argentina
| | - Adrián Gadano
- Liver Unit, Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires C1199DF, Argentina
- Department of Research, Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires C1199DF, Argentina
| | - Sebastián Marciano
- Instituto de Medicina Traslacional e Ingeniería Biomédica - Consejo Nacional de Investigaciones Científicas y Técnicas - Instituto Universitario del Hospital Italiano - Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires C1199ACL, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires C1425FQB, Argentina
- Liver Unit, Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires C1199DF, Argentina
- Department of Research, Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires C1199DF, Argentina
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18
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Plouviez M, Dubreucq E. Key Proteomics Tools for Fundamental and Applied Microalgal Research. Proteomes 2024; 12:13. [PMID: 38651372 PMCID: PMC11036299 DOI: 10.3390/proteomes12020013] [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: 12/29/2023] [Revised: 03/28/2024] [Accepted: 04/02/2024] [Indexed: 04/25/2024] Open
Abstract
Microscopic, photosynthetic prokaryotes and eukaryotes, collectively referred to as microalgae, are widely studied to improve our understanding of key metabolic pathways (e.g., photosynthesis) and for the development of biotechnological applications. Omics technologies, which are now common tools in biological research, have been shown to be critical in microalgal research. In the past decade, significant technological advancements have allowed omics technologies to become more affordable and efficient, with huge datasets being generated. In particular, where studies focused on a single or few proteins decades ago, it is now possible to study the whole proteome of a microalgae. The development of mass spectrometry-based methods has provided this leap forward with the high-throughput identification and quantification of proteins. This review specifically provides an overview of the use of proteomics in fundamental (e.g., photosynthesis) and applied (e.g., lipid production for biofuel) microalgal research, and presents future research directions in this field.
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Affiliation(s)
- Maxence Plouviez
- School of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand
- The Cawthron Institute, Nelson 7010, New Zealand
| | - Eric Dubreucq
- Agropolymer Engineering and Emerging Technologies, L’Institut Agro Montpellier, 34060 Montpellier, France;
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Barakat A, Munro G, Heegaard AM. Finding new analgesics: Computational pharmacology faces drug discovery challenges. Biochem Pharmacol 2024; 222:116091. [PMID: 38412924 DOI: 10.1016/j.bcp.2024.116091] [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: 10/02/2023] [Revised: 01/10/2024] [Accepted: 02/23/2024] [Indexed: 02/29/2024]
Abstract
Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.
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Affiliation(s)
- Ahmed Barakat
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Pharmacology and Toxicology, Faculty of Pharmacy, Assiut University, Assiut, Egypt.
| | | | - Anne-Marie Heegaard
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Bensoussan Y, Elemento O, Rameau A. Voice as an AI Biomarker of Health-Introducing Audiomics. JAMA Otolaryngol Head Neck Surg 2024; 150:283-284. [PMID: 38386315 DOI: 10.1001/jamaoto.2023.4807] [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: 02/23/2024]
Abstract
This Viewpoint discusses the need to create standards for audiomics to identify unique audio biomarkers of health and disease—now possible because of more efficient voice data analysis available through the use of artificial intelligence (AI)—and to improve patient care.
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Affiliation(s)
- Yaël Bensoussan
- USF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery, University of South Florida Health Morsani College of Medicine, Tampa
| | - Olivier Elemento
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York
| | - Anaïs Rameau
- Sean Parker Institute for the Voice, Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medicine, New York, New York
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21
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Fernando D, Ahmed AU, Williams BRG. Therapeutically targeting the unique disease landscape of pediatric high-grade gliomas. Front Oncol 2024; 14:1347694. [PMID: 38525424 PMCID: PMC10957575 DOI: 10.3389/fonc.2024.1347694] [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: 12/01/2023] [Accepted: 02/19/2024] [Indexed: 03/26/2024] Open
Abstract
Pediatric high-grade gliomas (pHGG) are a rare yet devastating malignancy of the central nervous system's glial support cells, affecting children, adolescents, and young adults. Tumors of the central nervous system account for the leading cause of pediatric mortality of which high-grade gliomas present a significantly grim prognosis. While the past few decades have seen many pediatric cancers experiencing significant improvements in overall survival, the prospect of survival for patients diagnosed with pHGGs has conversely remained unchanged. This can be attributed in part to tumor heterogeneity and the existence of the blood-brain barrier. Advances in discovery research have substantiated the existence of unique subgroups of pHGGs displaying alternate responses to different therapeutics and varying degrees of overall survival. This highlights a necessity to approach discovery research and clinical management of the disease in an alternative subtype-dependent manner. This review covers traditional approaches to the therapeutic management of pHGGs, limitations of such methods and emerging alternatives. Novel mutations which predominate the pHGG landscape are highlighted and the therapeutic potential of targeting them in a subtype specific manner discussed. Collectively, this provides an insight into issues in need of transformative progress which arise during the management of pHGGs.
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Affiliation(s)
- Dasun Fernando
- Centre for Cancer Research, Hudson Institute of Medical Research, Monash University, Clayton, VIC, Australia
- Department of Molecular and Translational Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC, Australia
| | - Afsar U. Ahmed
- Centre for Cancer Research, Hudson Institute of Medical Research, Monash University, Clayton, VIC, Australia
- Department of Molecular and Translational Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC, Australia
| | - Bryan R. G. Williams
- Centre for Cancer Research, Hudson Institute of Medical Research, Monash University, Clayton, VIC, Australia
- Department of Molecular and Translational Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC, Australia
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22
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Kabbashi S, Roomaney IA, Chetty M. Bridging the gap between omics research and dental practice. BDJ Open 2024; 10:16. [PMID: 38438363 PMCID: PMC10912736 DOI: 10.1038/s41405-024-00199-3] [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: 10/02/2023] [Revised: 02/11/2024] [Accepted: 02/13/2024] [Indexed: 03/06/2024] Open
Abstract
AIM The burgeoning field of omics research has witnessed exponential growth in both medicine and dentistry. However, despite more than a decade of advancements, clinical dentistry, particularly in Low- and Middle-Income Countries (LMICs), has seen limited progress in integrating omics-based approaches into routine practice. This review aims to provide a comprehensive overview of the integration of omics approaches in dentistry, focusing on the challenges and opportunities for translating research findings into clinical practice. METHODS we conducted a literature review using key databases to provide a brief overview of the history of genomics in dentistry. Additionally, we summarised recent breakthroughs in omics relevant to oral health practitioners, emphasising the inadequate translation of omics research into clinical practice. RESULTS Despite significant growth in omics research in both medicine and dentistry, its translation into routine clinical practice in dentistry remains limited. We summarise recent breakthroughs in omics and highlight the gap between research advancements and clinical implementation. DISCUSSION AND CONCLUSION The integration of omics approaches holds promise for enhancing diagnostics, personalised treatment strategies, and preventive measures in dental practice, ushering in a new era of precision oral healthcare. However, several challenges, including infrastructure limitations, cost-effectiveness, and education gaps, hinder the widespread adoption of omics-based approaches in clinical dentistry. A strong commitment to transforming dentistry is required to embrace this transition. This shift has the potential to revolutionise oral healthcare by advancing precision diagnostics and treatment strategies tailored to individual patient needs.
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Affiliation(s)
- S Kabbashi
- Department of Craniofacial Biology, Pathology, and Radiology, Faculty of Dentistry, University of Western Cape, Cape Town, South Africa.
| | - I A Roomaney
- Department of Craniofacial Biology, Pathology, and Radiology, Faculty of Dentistry, University of Western Cape, Cape Town, South Africa
| | - M Chetty
- Department of Craniofacial Biology, Pathology, and Radiology, Faculty of Dentistry, University of Western Cape, Cape Town, South Africa
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Abbasi EY, Deng Z, Ali Q, Khan A, Shaikh A, Reshan MSA, Sulaiman A, Alshahrani H. A machine learning and deep learning-based integrated multi-omics technique for leukemia prediction. Heliyon 2024; 10:e25369. [PMID: 38352790 PMCID: PMC10862685 DOI: 10.1016/j.heliyon.2024.e25369] [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: 08/25/2023] [Revised: 12/13/2023] [Accepted: 01/25/2024] [Indexed: 02/16/2024] Open
Abstract
In recent years, scientific data on cancer has expanded, providing potential for a better understanding of malignancies and improved tailored care. Advances in Artificial Intelligence (AI) processing power and algorithmic development position Machine Learning (ML) and Deep Learning (DL) as crucial players in predicting Leukemia, a blood cancer, using integrated multi-omics technology. However, realizing these goals demands novel approaches to harness this data deluge. This study introduces a novel Leukemia diagnosis approach, analyzing multi-omics data for accuracy using ML and DL algorithms. ML techniques, including Random Forest (RF), Naive Bayes (NB), Decision Tree (DT), Logistic Regression (LR), Gradient Boosting (GB), and DL methods such as Recurrent Neural Networks (RNN) and Feedforward Neural Networks (FNN) are compared. GB achieved 97 % accuracy in ML, while RNN outperformed by achieving 98 % accuracy in DL. This approach filters unclassified data effectively, demonstrating the significance of DL for leukemia prediction. The testing validation was based on 17 different features such as patient age, sex, mutation type, treatment methods, chromosomes, and others. Our study compares ML and DL techniques and chooses the best technique that gives optimum results. The study emphasizes the implications of high-throughput technology in healthcare, offering improved patient care.
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Affiliation(s)
- Erum Yousef Abbasi
- State Key Laboratory of Wireless Network Positioning and Communication Engineering Integration Research, School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing, China
| | - Zhongliang Deng
- State Key Laboratory of Wireless Network Positioning and Communication Engineering Integration Research, School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing, China
| | - Qasim Ali
- Department of Software Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan
| | - Adil Khan
- State Key Laboratory of Wireless Network Positioning and Communication Engineering Integration Research, School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing, China
| | - Asadullah Shaikh
- Department of Information Systems, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia
| | - Mana Saleh Al Reshan
- Department of Information Systems, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia
- Scientific and Engineering Research Centre, Najran University, Najran, 61441, Saudi Arabia
| | - Adel Sulaiman
- Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia
| | - Hani Alshahrani
- Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia
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24
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Nijakowski K, Owecki W, Jankowski J, Surdacka A. Salivary Biomarkers for Parkinson's Disease: A Systematic Review with Meta-Analysis. Cells 2024; 13:340. [PMID: 38391952 PMCID: PMC10887027 DOI: 10.3390/cells13040340] [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: 01/18/2024] [Revised: 02/05/2024] [Accepted: 02/12/2024] [Indexed: 02/24/2024] Open
Abstract
Parkinson's Disease (PD) is a common neurodegenerative disease which manifests with motor features, such as bradykinesia, resting tremor, rigidity, and postural instability. Using the non-invasive technique of saliva collection, we designed a systematic review to answer the question "Are salivary biomarkers reliable for the diagnosis of Parkinson's Disease?". Following inclusion and exclusion criteria, 30 studies were included in this systematic review (according to the PRISMA statement guidelines). Mostly proteins were reported as potential biomarkers in saliva. Based on meta-analysis, in PD patients, salivary levels of total alpha-synuclein were significantly decreased, and those of oligomeric alpha-synuclein were significantly increased. Also, according to pooled AUC, heme oxygenase-1 demonstrated significant predictive value for saliva-based PD diagnosis. In conclusion, some potential biomarkers, especially alpha-synuclein, can be altered in the saliva of PD patients, which could be reliably useful for early diagnosis of this neurodegenerative disease differentiating other synucleopathies.
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Affiliation(s)
- Kacper Nijakowski
- Department of Conservative Dentistry and Endodontics, Poznan University of Medical Sciences, 60-812 Poznan, Poland;
| | - Wojciech Owecki
- Student’s Scientific Group in Department of Conservative Dentistry and Endodontics, Poznan University of Medical Sciences, 60-812 Poznan, Poland; (W.O.); (J.J.)
| | - Jakub Jankowski
- Student’s Scientific Group in Department of Conservative Dentistry and Endodontics, Poznan University of Medical Sciences, 60-812 Poznan, Poland; (W.O.); (J.J.)
| | - Anna Surdacka
- Department of Conservative Dentistry and Endodontics, Poznan University of Medical Sciences, 60-812 Poznan, Poland;
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25
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Zulfiqar M, Crusoe MR, König-Ries B, Steinbeck C, Peters K, Gadelha L. Implementation of FAIR Practices in Computational Metabolomics Workflows-A Case Study. Metabolites 2024; 14:118. [PMID: 38393009 PMCID: PMC10891576 DOI: 10.3390/metabo14020118] [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: 12/21/2023] [Revised: 01/30/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for metabolomics workflows using the Metabolome Annotation Workflow (MAW) as a case study. MAW is specified using the Common Workflow Language (CWL), allowing for the subsequent execution of the workflow on different workflow engines. MAW is registered using a CWL description on WorkflowHub. During the submission process on WorkflowHub, a CWL description is used for packaging MAW using the Workflow RO-Crate profile, which includes metadata in Bioschemas. Researchers can use this narrative discussion as a guideline to commence using FAIR practices for their bioinformatics or cheminformatics workflows while incorporating necessary amendments specific to their research area.
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Affiliation(s)
- Mahnoor Zulfiqar
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, 07743 Jena, Germany;
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Michael R. Crusoe
- ELIXIR (The European Life-Sciences Infrastructure for Biological Information) Germany, Institute of Bio- and Geosciences (IBG-5)—Computational Metagenomics, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany;
| | - Birgitta König-Ries
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07743 Jena, Germany;
- Institute for Informatics, Friedrich Schiller University Jena, 07743 Jena, Germany
- iDiv—German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig, 04103 Leipzig, Germany;
| | - Christoph Steinbeck
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, 07743 Jena, Germany;
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Kristian Peters
- iDiv—German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig, 04103 Leipzig, Germany;
- Geobotany and Botanical Gardens, Martin-Luther University of Halle-Wittenberg, 06108 Halle, Germany
- Leibniz Institute of Plant Biochemistry, 06120 Halle, Germany
| | - Luiz Gadelha
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, 07743 Jena, Germany;
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07743 Jena, Germany;
- Institute for Informatics, Friedrich Schiller University Jena, 07743 Jena, Germany
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
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26
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Gondane P, Kumbhakarn S, Maity P, Kapat K. Recent Advances and Challenges in the Early Diagnosis and Treatment of Preterm Labor. Bioengineering (Basel) 2024; 11:161. [PMID: 38391647 PMCID: PMC10886370 DOI: 10.3390/bioengineering11020161] [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: 12/30/2023] [Revised: 01/30/2024] [Accepted: 02/04/2024] [Indexed: 02/24/2024] Open
Abstract
Preterm birth (PTB) is the primary cause of neonatal mortality and long-term disabilities. The unknown mechanism behind PTB makes diagnosis difficult, yet early detection is necessary for controlling and averting related consequences. The primary focus of this work is to provide an overview of the known risk factors associated with preterm labor and the conventional and advanced procedures for early detection of PTB, including multi-omics and artificial intelligence/machine learning (AI/ML)- based approaches. It also discusses the principles of detecting various proteomic biomarkers based on lateral flow immunoassay and microfluidic chips, along with the commercially available point-of-care testing (POCT) devices and associated challenges. After briefing the therapeutic and preventive measures of PTB, this review summarizes with an outlook.
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Affiliation(s)
- Prashil Gondane
- Department of Medical Devices, National Institute of Pharmaceutical Education and Research Kolkata, 168, Maniktala Main Road, Kankurgachi, Kolkata 700054, India
| | - Sakshi Kumbhakarn
- Department of Medical Devices, National Institute of Pharmaceutical Education and Research Kolkata, 168, Maniktala Main Road, Kankurgachi, Kolkata 700054, India
| | - Pritiprasanna Maity
- Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Kausik Kapat
- Department of Medical Devices, National Institute of Pharmaceutical Education and Research Kolkata, 168, Maniktala Main Road, Kankurgachi, Kolkata 700054, India
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27
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Melekoglu R, Yasar S, Colak C, Kasap M, Dogan UK, Yologlu S, Yilmaz E, Shazly S. Determination of biomarker candidates for the placenta accreta spectrum by plasma proteomic analysis. Sci Rep 2024; 14:2803. [PMID: 38307924 PMCID: PMC10837117 DOI: 10.1038/s41598-024-53324-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 01/31/2024] [Indexed: 02/04/2024] Open
Abstract
Placenta accreta spectrum (PAS) presents a significant obstetric challenge, associated with considerable maternal and fetal-neonatal morbidity and mortality. Nevertheless, it is imperative to acknowledge that a noteworthy subset of PAS cases remains undetected until the time of delivery, thereby contributing to an augmented incidence of morbidity among the affected individuals. The delayed identification of PAS not only hinders timely intervention but also exacerbates the associated health risks for both the maternal and fetal outcomes. This underscores the urgency to innovate strategies for early PAS diagnosis. In this study, we aimed to explore plasma proteins as potential diagnostic biomarkers for PAS. Integrated transcriptome and proteomic analyses were conducted to establish a novel diagnostic approach. A cohort of 15 pregnant women diagnosed with PAS and delivering at Inonu University Faculty of Medicine between 01/04/2021 and 01/01/2023, along with a matched control group of 15 pregnant women without PAS complications, were enrolled. Plasma protein identification utilized enzymatic digestion and liquid chromatography-tandem mass spectrometry techniques. Proteomic analysis identified 228 plasma proteins, of which 85 showed significant differences (P < 0.001) between PAS and control cases. We refined this to a set of 20 proteins for model construction, resulting in a highly accurate classification model (96.9% accuracy). Notable associations were observed for proteins encoded by P01859 (Immunoglobulin heavy constant gamma 2), P02538 (Keratin type II cytoskeletal 6A), P29622 [Kallistatin (also known as Serpin A4)], P17900 (Ganglioside GM2 activator Calmodulin-like protein 5), and P01619 (Immunoglobulin kappa variable 3-20), with fold changes indicating their relevance in distinguishing PAS from control groups. In conclusion, our study has identified novel plasma proteins that could serve as potential biomarkers for early diagnosis of PAS in pregnant women. Further research and validation in larger PAS cohorts are necessary to determine the clinical utility and reliability of these proteomic biomarkers for diagnosing PAS.
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Affiliation(s)
- Rauf Melekoglu
- Department of Obstetrics and Gynecology, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey.
| | - Seyma Yasar
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey
| | - Cemil Colak
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey
| | - Murat Kasap
- Department of Medical Biology, Faculty of Medicine, Kocaeli University, Kocaeli, Turkey
| | - Umran Karabulut Dogan
- Clinic of Obstetrics and Gynecology, Malatya Education and Research Hospital, Malatya, Turkey
| | - Saim Yologlu
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey
| | - Ercan Yilmaz
- Department of Obstetrics and Gynecology, Faculty of Medicine, Inonu University, 44280, Malatya, Turkey
| | - Sherif Shazly
- Department of Obstetrics and Gynecology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
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28
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ZHI M, WANG J. [Advances in the applications of exposomics in the identification of environmental pollutants and their health hazards]. Se Pu 2024; 42:142-149. [PMID: 38374594 PMCID: PMC10877475 DOI: 10.3724/sp.j.1123.2023.12011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Indexed: 02/21/2024] Open
Abstract
Environmental pollution has become a prominent global problem, and the potential health hazards of pollutants have caused widespread concern. However, revealing the relationship between complex-pollutant exposure and disease development remains an immense challenge. The core of environmental-health research and risk assessment is the identification of contaminants and their effects. Exposomics provides a new approach in the study of the relationship between environmental factors and human health. Both "top-down" and "bottom-up" strategies are employed in exposomics research. The development of new technologies for chemical detection and "multi-omics" has greatly facilitated the implementation of these strategies. Exposomics focuses on the measurement of an individual's lifelong exposure and aims to identify the health effects of such exposure. It involves the dynamic monitoring of external and internal exposure levels at different stages of life through traditional biomonitoring and exposomic methods. It also includes the identification of biomarkers, which indicate specific environmental exposures and the adverse effects of these exposures on health. Compared with traditional environmental-health studies, exposomics can more accurately reflect the diversity of exposure factors such as pollutants, natural factors, and lifestyles in the real environment, as well as the complexity of their in vivo processes and the responses they trigger in an organism. Powerful chemical analytical tools such as high-resolution mass spectrometry (HRMS) are widely used in studies related to the field of exposomics. Liquid chromatography-mass spectrometry (LC-MS) has been applied in the detection and analysis of environmental pollutants. Proteomics and metabolomics, as two important tools for biomarker identification and effects analysis, are widely used to explore the relationship between environmental factors and diseases. Pollutants can lead to pathological changes and even toxic effects by interacting with proteins. In the case of mixed exposure, some contaminants may present joint toxicity. The interaction between contaminants may change their environmental behavior or the amount of each contaminant that enters the human body, which, in turn, affects their health effects.
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29
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Liikonen V, Gomez-Gallego C, Kolehmainen M. The effects of whole grain cereals on tryptophan metabolism and intestinal barrier function: underlying factors of health impact. Proc Nutr Soc 2024; 83:42-54. [PMID: 37843435 DOI: 10.1017/s0029665123003671] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
This review aims to investigate the relationship between the health impact of whole grains mediated via the interaction with intestinal microbiota and intestinal barrier function with special interest on tryptophan metabolism, focusing on the role of the intestinal microbiota and their impact on barrier function. Consuming various types of whole grains can lead to the growth of different microbiota species, which in turn leads to the production of diverse metabolites, including those derived from tryptophan metabolism, although the impact of whole grains on intestinal microbiota composition results remains inconclusive and vary among different studies. Whole grains can exert an influence on tryptophan metabolism through interactions with the intestinal microbiota, and the presence of fibre in whole grains plays a notable role in establishing this connection. The impact of whole grains on intestinal barrier function is closely related to their effects on the composition and activity of intestinal microbiota, and SCFA and tryptophan metabolites serve as potential links connecting whole grains, intestinal microbiota and the intestinal barrier function. Tryptophan metabolites affect various aspects of the intestinal barrier, such as immune balance, mucus and microbial barrier, tight junction complexes and the differentiation and proliferation of epithelial cells. Despite the encouraging discoveries in this area of research, the evidence regarding the effects of whole grain consumption on intestine-related activity remains limited. Hence, we can conclude that we are just starting to understand the actual complexity of the intestinal factors mediating in part the health impacts of whole grain cereals.
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Affiliation(s)
- Vilma Liikonen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O.Box 1627, 70211 Kuopio, Finland
| | - Carlos Gomez-Gallego
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O.Box 1627, 70211 Kuopio, Finland
| | - Marjukka Kolehmainen
- Department of Clinical Nutrition, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O.Box 1627, 70211 Kuopio, Finland
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30
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Ahluwalia P, Ballur K, Leeman T, Vashisht A, Singh H, Omar N, Mondal AK, Vaibhav K, Baban B, Kolhe R. Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine. Cancers (Basel) 2024; 16:480. [PMID: 38339232 PMCID: PMC10854941 DOI: 10.3390/cancers16030480] [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: 10/31/2023] [Revised: 01/10/2024] [Accepted: 01/13/2024] [Indexed: 02/12/2024] Open
Abstract
Colorectal cancer (CRC) is one of the most heterogeneous and deadly diseases, with a global incidence of 1.5 million cases per year. Genomics has revolutionized the clinical management of CRC by enabling comprehensive molecular profiling of cancer. However, a deeper understanding of the molecular factors is needed to identify new prognostic and predictive markers that can assist in designing more effective therapeutic regimens for the improved management of CRC. Recent breakthroughs in single-cell analysis have identified new cell subtypes that play a critical role in tumor progression and could serve as potential therapeutic targets. Spatial analysis of the transcriptome and proteome holds the key to unlocking pathogenic cellular interactions, while liquid biopsy profiling of molecular variables from serum holds great potential for monitoring therapy resistance. Furthermore, gene expression signatures from various pathways have emerged as promising prognostic indicators in colorectal cancer and have the potential to enhance the development of equitable medicine. The advancement of these technologies for identifying new markers, particularly in the domain of predictive and personalized medicine, has the potential to improve the management of patients with CRC. Further investigations utilizing similar methods could uncover molecular subtypes specific to emerging therapies, potentially strengthening the development of personalized medicine for CRC patients.
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Affiliation(s)
- Pankaj Ahluwalia
- Department of Pathology, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA; (P.A.); (K.B.); (T.L.); (A.V.); (H.S.); (N.O.); (A.K.M.)
| | - Kalyani Ballur
- Department of Pathology, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA; (P.A.); (K.B.); (T.L.); (A.V.); (H.S.); (N.O.); (A.K.M.)
| | - Tiffanie Leeman
- Department of Pathology, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA; (P.A.); (K.B.); (T.L.); (A.V.); (H.S.); (N.O.); (A.K.M.)
| | - Ashutosh Vashisht
- Department of Pathology, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA; (P.A.); (K.B.); (T.L.); (A.V.); (H.S.); (N.O.); (A.K.M.)
| | - Harmanpreet Singh
- Department of Pathology, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA; (P.A.); (K.B.); (T.L.); (A.V.); (H.S.); (N.O.); (A.K.M.)
| | - Nivin Omar
- Department of Pathology, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA; (P.A.); (K.B.); (T.L.); (A.V.); (H.S.); (N.O.); (A.K.M.)
| | - Ashis K. Mondal
- Department of Pathology, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA; (P.A.); (K.B.); (T.L.); (A.V.); (H.S.); (N.O.); (A.K.M.)
| | - Kumar Vaibhav
- Department of Neurosurgery, Augusta University, Augusta, GA 30912, USA;
| | - Babak Baban
- Departments of Neurology and Surgery, Augusta University, Augusta, GA 30912, USA;
| | - Ravindra Kolhe
- Department of Pathology, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA; (P.A.); (K.B.); (T.L.); (A.V.); (H.S.); (N.O.); (A.K.M.)
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31
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Nijakowski K, Owecki W, Jankowski J, Surdacka A. Salivary Biomarkers for Alzheimer's Disease: A Systematic Review with Meta-Analysis. Int J Mol Sci 2024; 25:1168. [PMID: 38256241 PMCID: PMC10817083 DOI: 10.3390/ijms25021168] [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: 12/06/2023] [Revised: 01/03/2024] [Accepted: 01/16/2024] [Indexed: 01/24/2024] Open
Abstract
Alzheimer's Disease (AD) is the most common neurodegenerative disease which manifests with progressive cognitive impairment, leading to dementia. Considering the noninvasive collection of saliva, we designed the systematic review to answer the question "Are salivary biomarkers reliable for the diagnosis of Alzheimer's Disease?" Following the inclusion and exclusion criteria, 30 studies were included in this systematic review (according to the PRISMA statement guidelines). Potential biomarkers include mainly proteins, metabolites and even miRNAs. Based on meta-analysis, in AD patients, salivary levels of beta-amyloid42 and p-tau levels were significantly increased, and t-tau and lactoferrin were decreased at borderline statistical significance. However, according to pooled AUC, lactoferrin and beta-amyloid42 showed a significant predictive value for salivary-based AD diagnosis. In conclusion, potential markers such as beta-amyloid42, tau and lactoferrin can be detected in the saliva of AD patients, which could reliably support the early diagnosis of this neurodegenerative disease.
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Affiliation(s)
- Kacper Nijakowski
- Department of Conservative Dentistry and Endodontics, Poznan University of Medical Sciences, 60-812 Poznan, Poland;
| | - Wojciech Owecki
- Student’s Scientific Group in Department of Conservative Dentistry and Endodontics, Poznan University of Medical Sciences, 60-812 Poznan, Poland (J.J.)
| | - Jakub Jankowski
- Student’s Scientific Group in Department of Conservative Dentistry and Endodontics, Poznan University of Medical Sciences, 60-812 Poznan, Poland (J.J.)
| | - Anna Surdacka
- Department of Conservative Dentistry and Endodontics, Poznan University of Medical Sciences, 60-812 Poznan, Poland;
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32
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Nazar NSBM, Ramanathan A, Ghani WMN, Rokhani FB, Jacob PS, Sabri NEB, Hassan MS, Kadir K, Dharmarajan L. Salivary metabolomics in oral potentially malignant disorders and oral cancer patients-a systematic review with meta-analysis. Clin Oral Investig 2024; 28:98. [PMID: 38225483 DOI: 10.1007/s00784-023-05481-6] [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: 08/10/2023] [Accepted: 12/27/2023] [Indexed: 01/17/2024]
Abstract
OBJECTIVES The aim of this systematic review and meta-analysis is to assess the diagnostic potential of salivary metabolomics in the detection of oral potentially malignant disorders (OPMDs) and oral cancer (OC). MATERIALS AND METHODS A systematic review was performed in accordance with the 3rd edition of the Centre for Reviews and Dissemination (CRD) and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Electronic searches for articles were carried out in the PubMed, Web of Science, and Scopus databases. The quality assessment of the included studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS) and the new version of the QUADOMICS tool. Meta-analysis was conducted whenever possible. The effect size was presented using the Forest plot, whereas the presence of publication bias was examined through Begg's funnel plot. RESULTS A total of nine studies were included in the systematic review. The metabolite profiling was heterogeneous across all the studies. The expression of several salivary metabolites was found to be significantly altered in OPMDs and OCs as compared to healthy controls. Meta-analysis was able to be conducted only for N-acetylglucosamine. There was no significant difference (SMD = 0.15; 95% CI - 0.25-0.56) in the level of N-acetylglucosamine between OPMDs, OC, and the control group. CONCLUSION Evidence for N-acetylglucosamine as a salivary biomarker for oral cancer is lacking. Although several salivary metabolites show changes between healthy, OPMDs, and OC, their diagnostic potential cannot be assessed in this review due to a lack of data. Therefore, further high-quality studies with detailed analysis and reporting are required to establish the diagnostic potential of the salivary metabolites in OPMDs and OC. CLINICAL RELEVANCE While some salivary metabolites exhibit significant changes in oral potentially malignant disorders (OPMDs) and oral cancer (OC) compared to healthy controls, the current evidence, especially for N-acetylglucosamine, is inadequate to confirm their reliability as diagnostic biomarkers. Additional high-quality studies are needed for a more conclusive assessment of salivary metabolites in oral disease diagnosis.
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Affiliation(s)
- Nur Syahirah Binti Mohd Nazar
- Department of Oral and Maxillofacial Clinical Sciences, Faculty of Dentistry, Universiti Malaya, Kuala Lumpur, Malaysia
- Department of Oral and Maxillofacial Surgery, Medicine and Pathology, Faculty of Dentistry, Universiti Sains Islam Malaysia, Kuala Lumpur, Malaysia
| | - Anand Ramanathan
- Department of Oral and Maxillofacial Clinical Sciences, Faculty of Dentistry, Universiti Malaya, Kuala Lumpur, Malaysia.
- Oral Cancer Research & Coordinating Center, Faculty of Dentistry, Universiti Malaya, Kuala Lumpur, Malaysia.
| | - Wan Maria Nabillah Ghani
- Oral Cancer Research & Coordinating Center, Faculty of Dentistry, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Faezah Binti Rokhani
- Department of Oral and Maxillofacial Surgery, Medicine and Pathology, Faculty of Dentistry, Universiti Sains Islam Malaysia, Kuala Lumpur, Malaysia
| | - Pulikkotil Shaju Jacob
- Division of Clinical Dentistry, School of Dentistry, International Medical University, Kuala Lumpur, Malaysia
| | - Nurul Elma Binti Sabri
- Department of Agrotechnology and Bioscience, Malaysian Nuclear Agency, Bangi, Selangor, Malaysia
| | - Mohd Sukri Hassan
- Faculty of Science and Technology, Universiti Sains Islam Malaysia, Kuala Lumpur, Malaysia
| | - Kathreena Kadir
- Department of Oral and Maxillofacial Clinical Sciences, Faculty of Dentistry, Universiti Malaya, Kuala Lumpur, Malaysia
- Oral Cancer Research & Coordinating Center, Faculty of Dentistry, Universiti Malaya, Kuala Lumpur, Malaysia
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33
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Mofijur M, Hasan MM, Ahmed SF, Djavanroodi F, Fattah IMR, Silitonga AS, Kalam MA, Zhou JL, Khan TMY. Advances in identifying and managing emerging contaminants in aquatic ecosystems: Analytical approaches, toxicity assessment, transformation pathways, environmental fate, and remediation strategies. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 341:122889. [PMID: 37972679 DOI: 10.1016/j.envpol.2023.122889] [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: 06/19/2023] [Revised: 10/30/2023] [Accepted: 11/05/2023] [Indexed: 11/19/2023]
Abstract
Emerging contaminants (ECs) are increasingly recognized as threats to human health and ecosystems. This review evaluates advanced analytical methods, particularly mass spectrometry, for detecting ECs and understanding their toxicity, transformation pathways, and environmental distribution. Our findings underscore the reliability of current techniques and the potential of upcoming methods. The adverse effects of ECs on aquatic life necessitate both in vitro and in vivo toxicity assessments. Evaluating the distribution and degradation of ECs reveals that they undergo physical, chemical, and biological transformations. Remediation strategies such as advanced oxidation, adsorption, and membrane bioreactors effectively treat EC-contaminated waters, with combinations of these techniques showing the highest efficacy. To minimize the impact of ECs, a proactive approach involving monitoring, regulations, and public education is vital. Future research should prioritize the refining of detection methods and formulation of robust policies for EC management.
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Affiliation(s)
- M Mofijur
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia.
| | - M M Hasan
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia; School of Engineering and Technology, Central Queensland University, QLD, 4701, Australia
| | - Shams Forruque Ahmed
- Science and Math Program, Asian University for Women, Chattogram, 4000, Bangladesh
| | - F Djavanroodi
- Mechanical Engineering Department, Prince Mohammad Bin Fahd University, Al Khobar, 31952, Saudi Arabia
| | - I M R Fattah
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia
| | - A S Silitonga
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia
| | - M A Kalam
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia
| | - John L Zhou
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia; Centre for Green Technology, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia
| | - T M Yunus Khan
- Mechanical Engineering Department, College of Engineering, King Khalid University, Abha, Saudi Arabia
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Li H, Wang Y, Zhu G, Ma Q, Huang S, Guo G, Zhu F. Application progress of single-cell sequencing technology in mesenchymal stem cells research. Front Cell Dev Biol 2024; 11:1336482. [PMID: 38264356 PMCID: PMC10803637 DOI: 10.3389/fcell.2023.1336482] [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: 11/10/2023] [Accepted: 12/26/2023] [Indexed: 01/25/2024] Open
Abstract
Single-Cell Sequencing (SCS) technology plays an important role in the field of Mesenchymal Stem Cells (MSCs) research. This paper comprehensively describes the application of SCS technology in the field of MSCs research, including (1) SCS enables more precise MSCs characterization and biomarker definition. (2) SCS reveals the prevalent gene expression heterogeneity among different subclusters within MSCs, which contributes to a more comprehensive understanding of MSCs function and diversity in developmental, regenerative, and pathological contexts. (3) SCS provides insights into the dynamic transcriptional changes experienced by MSCs during differentiation and the complex web of important signaling pathways and regulatory factors controlling key processes within MSCs, including proliferation, differentiation and regulation, and interactions mechanisms. (4) The analytical methods underpinning SCS data are rapidly evolving and converging with the field of histological research to systematically deconstruct the functions and mechanisms of MSCs. This review provides new perspectives for unraveling the biological properties, heterogeneity, differentiation potential, biological functions, and clinical potential of MSCs at the single-cell level.
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Affiliation(s)
- Hao Li
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Yusong Wang
- Department of Burns, The First Affiliated Hospital, Naval Medical University, Shanghai, China
| | - Gehua Zhu
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Qimin Ma
- Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Shengyu Huang
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Guanghua Guo
- Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Feng Zhu
- Department of Burns, The First Affiliated Hospital, Naval Medical University, Shanghai, China
- Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
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Samad SS, Schwartz JM, Francavilla C. Functional selectivity of Receptor Tyrosine Kinases regulates distinct cellular outputs. Front Cell Dev Biol 2024; 11:1348056. [PMID: 38259512 PMCID: PMC10800419 DOI: 10.3389/fcell.2023.1348056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 12/19/2023] [Indexed: 01/24/2024] Open
Abstract
Functional selectivity refers to the activation of differential signalling and cellular outputs downstream of the same membrane-bound receptor when activated by two or more different ligands. Functional selectivity has been described and extensively studied for G-protein Coupled Receptors (GPCRs), leading to specific therapeutic options for dysregulated GPCRs functions. However, studies regarding the functional selectivity of Receptor Tyrosine Kinases (RTKs) remain sparse. Here, we will summarize recent data about RTK functional selectivity focusing on how the nature and the amount of RTK ligands and the crosstalk of RTKs with other membrane proteins regulate the specificity of RTK signalling. In addition, we will discuss how structural changes in RTKs upon ligand binding affects selective signalling pathways. Much remains to be known about the integration of different signals affecting RTK signalling specificity to orchestrate long-term cellular outcomes. Recent advancements in omics, specifically quantitative phosphoproteomics, and in systems biology methods to study, model and integrate different types of large-scale omics data have increased our ability to compare several signals affecting RTK functional selectivity in a global, system-wide fashion. We will discuss how such methods facilitate the exploration of important signalling hubs and enable data-driven predictions aiming at improving the efficacy of therapeutics for diseases like cancer, where redundant RTK signalling pathways often compromise treatment efficacy.
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Affiliation(s)
- Sakim S. Samad
- Division of Molecular and Cellular Functions, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Division of Evolution, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Jean-Marc Schwartz
- Division of Evolution, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Chiara Francavilla
- Division of Molecular and Cellular Functions, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Section of Protein Science and Biotherapeutics, Department of Bioengineering and Biomedicine, Danish Technical University, Lyngby, Denmark
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Zhang Z, Zhou Z, Li H. The role of lipid dysregulation in gestational diabetes mellitus: Early prediction and postpartum prognosis. J Diabetes Investig 2024; 15:15-25. [PMID: 38095269 PMCID: PMC10759727 DOI: 10.1111/jdi.14119] [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: 09/27/2023] [Revised: 11/06/2023] [Accepted: 11/14/2023] [Indexed: 01/03/2024] Open
Abstract
Gestational diabetes mellitus (GDM) is a pathological condition during pregnancy characterized by impaired glucose tolerance, and the failure of pancreatic beta-cells to respond appropriately to an increased insulin demand. However, while the majority of women with GDM will return to normoglycemia after delivery, they have up to a seven times higher risk of developing type 2 diabetes during midlife, compared with those with no history of GDM. Gestational diabetes mellitus also increases the risk of multiple metabolic disorders, including non-alcoholic fatty liver disease, obesity, and cardiovascular diseases. Lipid metabolism undergoes significant changes throughout the gestational period, and lipid dysregulation is strongly associated with GDM and the progression to future type 2 diabetes. In addition to common lipid variables, discovery-based omics techniques, such as metabolomics and lipidomics, have identified lipid biomarkers that correlate with GDM. These lipid species also show considerable potential in predicting the onset of GDM and subsequent type 2 diabetes post-delivery. This review aims to update the current knowledge of the role that lipids play in the onset of GDM, with a focus on potential lipid biomarkers or metabolic pathways. These biomarkers may be useful in establishing predictive models to accurately predict the future onset of GDM and type 2 diabetes, and early intervention may help to reduce the complications associated with GDM.
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Affiliation(s)
- Ziyi Zhang
- Department of Endocrinology, Sir Run Run Shaw HospitalZhejiang University, School of MedicineHangzhouChina
| | - Zheng Zhou
- Zhejiang University, School of MedicineHangzhouChina
| | - Hong Li
- Department of Endocrinology, Sir Run Run Shaw HospitalZhejiang University, School of MedicineHangzhouChina
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van der Zon AAM, Verduin J, van den Hurk RS, Gargano AFG, Pirok BWJ. Sample transformation in online separations: how chemical conversion advances analytical technology. Chem Commun (Camb) 2023; 60:36-50. [PMID: 38053451 PMCID: PMC10729587 DOI: 10.1039/d3cc03599a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/13/2023] [Indexed: 12/07/2023]
Abstract
While the advent of modern analytical technology has allowed scientists to determine the complexity of mixtures, it also spurred the demand to understand these sophisticated mixtures better. Chemical transformation can be used to provide insights into properties of complex samples such as degradation pathways or molecular heterogeneity that are otherwise unaccessible. In this article, we explore how sample transformation is exploited across different application fields to empower analytical methods. Transformation mechanisms include molecular-weight reduction, controlled degradation, and derivatization. Both offline and online transformation methods have been explored. The covered studies show that sample transformation facilitates faster reactions (e.g. several hours to minutes), reduces sample complexity, unlocks new sample dimensions (e.g. functional groups), provides correlations between multiple sample dimensions, and improves detectability. The article highlights the state-of-the-art and future prospects, focusing in particular on the characterization of protein and nucleic-acid therapeutics, nanoparticles, synthetic polymers, and small molecules.
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Affiliation(s)
- Annika A M van der Zon
- University of Amsterdam, van't Hoff Institute for Molecular Sciences, Analytical Chemistry Group, Science Park 904, 1098 XH Amsterdam, The Netherlands.
- Centre of Analytical Sciences Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Joshka Verduin
- Centre of Analytical Sciences Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Vrije Universiteit Amsterdam, Amsterdam Institute of Molecular and Life Sciences, Division of BioAnalytical Chemistry, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
| | - Rick S van den Hurk
- University of Amsterdam, van't Hoff Institute for Molecular Sciences, Analytical Chemistry Group, Science Park 904, 1098 XH Amsterdam, The Netherlands.
- Centre of Analytical Sciences Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Andrea F G Gargano
- University of Amsterdam, van't Hoff Institute for Molecular Sciences, Analytical Chemistry Group, Science Park 904, 1098 XH Amsterdam, The Netherlands.
- Centre of Analytical Sciences Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Bob W J Pirok
- University of Amsterdam, van't Hoff Institute for Molecular Sciences, Analytical Chemistry Group, Science Park 904, 1098 XH Amsterdam, The Netherlands.
- Centre of Analytical Sciences Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
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Constantin M, Chifiriuc MC, Mihaescu G, Vrancianu CO, Dobre EG, Cristian RE, Bleotu C, Bertesteanu SV, Grigore R, Serban B, Cirstoiu C. Implications of oral dysbiosis and HPV infection in head and neck cancer: from molecular and cellular mechanisms to early diagnosis and therapy. Front Oncol 2023; 13:1273516. [PMID: 38179168 PMCID: PMC10765588 DOI: 10.3389/fonc.2023.1273516] [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: 08/06/2023] [Accepted: 11/30/2023] [Indexed: 01/06/2024] Open
Abstract
Head and neck cancer (HNC) is the sixth most common type of cancer, with more than half a million new cases annually. This review focuses on the role of oral dysbiosis and HPV infection in HNCs, presenting the involved taxons, molecular effectors and pathways, as well as the HPV-associated particularities of genetic and epigenetic changes and of the tumor microenvironment occurred in different stages of tumor development. Oral dysbiosis is associated with the evolution of HNCs, through multiple mechanisms such as inflammation, genotoxins release, modulation of the innate and acquired immune response, carcinogens and anticarcinogens production, generation of oxidative stress, induction of mutations. Thus, novel microbiome-derived biomarkers and interventions could significantly contribute to achieving the desideratum of personalized management of oncologic patients, regarding both early diagnosis and treatment. The results reported by different studies are not always congruent regarding the variations in the abundance of different taxons in HNCs. However, there is a consistent reporting of a higher abundance of Gram-negative species such as Fusobacterium, Leptotrichia, Treponema, Porphyromonas gingivalis, Prevotella, Bacteroidetes, Haemophilus, Veillonella, Pseudomonas, Enterobacterales, which are probably responsible of chronic inflammation and modulation of tumor microenvironment. Candida albicans is the dominant fungi found in oral carcinoma being also associated with shorter survival rate. Specific microbial signatures (e.g., F. nucleatum, Bacteroidetes and Peptostreptococcus) have been associated with later stages and larger tumor, suggesting their potential to be used as biomarkers for tumor stratification and prognosis. On the other hand, increased abundance of Corynebacterium, Kingella, Abiotrophia is associated with a reduced risk of HNC. Microbiome could also provide biomarkers for differentiating between oropharyngeal and hypopharyngeal cancers as well as between HPV-positive and HPV-negative tumors. Ongoing clinical trials aim to validate non-invasive tests for microbiome-derived biomarkers detection in oral and throat cancers, especially within high-risk populations. Oro-pharyngeal dysbiosis could also impact the HNCs therapy and associated side-effects of radiotherapy, chemotherapy, and immunotherapy. HPV-positive tumors harbor fewer mutations, as well as different DNA methylation pattern and tumor microenvironment. Therefore, elucidation of the molecular mechanisms by which oral microbiota and HPV infection influence the HNC initiation and progression, screening for HPV infection and vaccination against HPV, adopting a good oral hygiene, and preventing oral dysbiosis are important tools for advancing in the battle with this public health global challenge.
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Affiliation(s)
- Marian Constantin
- Department of Microbiology, Institute of Biology of Romanian Academy, Bucharest, Romania
- The Research Institute of the University of Bucharest, ICUB, Bucharest, Romania
| | - Mariana Carmen Chifiriuc
- The Research Institute of the University of Bucharest, ICUB, Bucharest, Romania
- Microbiology Immunology Department, Faculty of Biology, University of Bucharest, Bucharest, Romania
- Department of Life, Medical and Agricultural Sciences, Biological Sciences Section, Romanian Academy, Bucharest, Romania
| | - Grigore Mihaescu
- Microbiology Immunology Department, Faculty of Biology, University of Bucharest, Bucharest, Romania
| | - Corneliu Ovidiu Vrancianu
- The Research Institute of the University of Bucharest, ICUB, Bucharest, Romania
- Microbiology Immunology Department, Faculty of Biology, University of Bucharest, Bucharest, Romania
- DANUBIUS Department, National Institute of Research and Development for Biological Sciences, Bucharest, Romania
| | - Elena-Georgiana Dobre
- The Research Institute of the University of Bucharest, ICUB, Bucharest, Romania
- Immunology Department, “Victor Babes” National Institute of Pathology, Bucharest, Romania
| | - Roxana-Elena Cristian
- The Research Institute of the University of Bucharest, ICUB, Bucharest, Romania
- DANUBIUS Department, National Institute of Research and Development for Biological Sciences, Bucharest, Romania
- Department of Biochemistry and Molecular Biology, Faculty of Biology, University of Bucharest, Bucharest, Romania
| | - Coralia Bleotu
- The Research Institute of the University of Bucharest, ICUB, Bucharest, Romania
- Cellular and Molecular Pathology Department, Ştefan S. Nicolau Institute of Virology, Bucharest, Romania
| | - Serban Vifor Bertesteanu
- Coltea Clinical Hospital, ENT, Head & Neck Surgery Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Raluca Grigore
- Coltea Clinical Hospital, ENT, Head & Neck Surgery Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Bogdan Serban
- University Emergency Hospital, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Catalin Cirstoiu
- University Emergency Hospital, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
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William N, Osmani R, Acker JP. Towards the crux of sex-dependent variability in red cell concentrates. Transfus Apher Sci 2023; 62:103827. [PMID: 37793959 DOI: 10.1016/j.transci.2023.103827] [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: 10/06/2023]
Abstract
Donor sex can alter the RBC 'storage lesion' progression, contributing to dissimilarities in blood product quality, and thus adverse post-transfusion reactions. The mechanisms underlying the reduced sensitivity of female RBCs to storage-induced stress are partially ascribed to the differential effects of testosterone, progesterone, and estrogen on hemolytic propensity. Contributing to this is the increased proportion of more robust, biologically 'young' subpopulations of RBCs in females. Herein, we discuss the impact of sex hormones on RBCs and the relevance of these biological subpopulations to provide further insight into sex-dependent blood product variability.
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Affiliation(s)
- Nishaka William
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Rafay Osmani
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Jason P Acker
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Innovation and Portfolio Management, Canadian Blood Services, Edmonton, Alberta, Canada.
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40
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Mukherjee A, Kar I, Patra AK. Understanding anthelmintic resistance in livestock using "omics" approaches. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:125439-125463. [PMID: 38015400 DOI: 10.1007/s11356-023-31045-y] [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: 08/29/2023] [Accepted: 11/08/2023] [Indexed: 11/29/2023]
Abstract
Widespread and improper use of various anthelmintics, genetic, and epidemiological factors has resulted in anthelmintic-resistant (AR) helminth populations in livestock. This is currently quite common globally in different livestock animals including sheep, goats, and cattle to gastrointestinal nematode (GIN) infections. Therefore, the mechanisms underlying AR in parasitic worm species have been the subject of ample research to tackle this challenge. Current and emerging technologies in the disciplines of genomics, transcriptomics, metabolomics, and proteomics in livestock species have advanced the understanding of the intricate molecular AR mechanisms in many major parasites. The technologies have improved the identification of possible biomarkers of resistant parasites, the ability to find actual causative genes, regulatory networks, and pathways of parasites governing the AR development including the dynamics of helminth infection and host-parasite infections. In this review, various "omics"-driven technologies including genome scan, candidate gene, quantitative trait loci, transcriptomic, proteomic, and metabolomic approaches have been described to understand AR of parasites of veterinary importance. Also, challenges and future prospects of these "omics" approaches are also discussed.
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Affiliation(s)
- Ayan Mukherjee
- Department of Animal Biotechnology, West Bengal University of Animal and Fishery Sciences, Nadia, Mohanpur, West Bengal, India
| | - Indrajit Kar
- Department of Avian Sciences, West Bengal University of Animal and Fishery Sciences, Nadia, Mohanpur, West Bengal, India
| | - Amlan Kumar Patra
- American Institute for Goat Research, Langston University, Oklahoma, 73050, USA.
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Zhang M, Xing Y, Ma J, Zhang Y, Yu J, Wang X, Jia X. Investigation of the response of Platycodongrandiflorus (Jacq.) A. DC to salt stress using combined transcriptomics and metabolomics. BMC PLANT BIOLOGY 2023; 23:589. [PMID: 38001405 PMCID: PMC10675982 DOI: 10.1186/s12870-023-04536-w] [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: 01/26/2023] [Accepted: 10/18/2023] [Indexed: 11/26/2023]
Abstract
BACKGROUND Platycodon grandiflorus (Jacq.) A. DC is a famous traditional Chinese medicine in China and an authentic medicine in Inner Mongolia. It has been traditionally used as an expectorant in cough and also has anti-inflammatory and other pharmacological effects. As a homologous plant of medicine and food, P. grandiflorus is widely planted in Northeast China. Soil salinity isa limiting factor for its cultivation. In this study, we comprehensively described the physiological characteristics of P. grandiflorus and combined transcriptomics and metabolomics to study the response of roots of P. grandiflorus to salt stress. RESULTS Overall, 8,988 differentially expressed genes were activated and significantly altered the metabolic processes. In total, 428 differentially abundant metabolites were affected by salt stress. After moderate and severe salt stress, most of the differentially abundant metabolites were enriched in the L-phenylalanine metabolic pathway. Through the comprehensive analysis of the interaction between key genes and metabolites, the main pathways such as lignin compound biosynthesis and triterpene saponin biosynthesis were completed. The relative content of compounds related to lignin biosynthesis, such as caffeic acid, coniferin, and syringing, increased under salt stress, and the related genes such as PAL, C4H, and the key enzyme gene UGT72E2 were activated to adapt to the salt stress. Platycodon saponin is one of the major triterpene saponins in P. grandiflorus, and Platycodin D is its most abundant major bioactive component. Under severe salt stress, Platycodin D level increased by nearly 1.77-fold compared with the control group. Most of the genes involved insynthetic pathway of Platycodin D, such as HMGCR, GGPS, SE, and LUP, were upregulated under salt stress. CONCLUSION Salt stress led to a decrease in the biomass and affected the activities of antioxidant enzymes and contents of osmotic regulators in the plant. These results provided not only novel insights into the underlying mechanisms of response of P. grandiflorus to salt stress but also a foundation for future studies on the function of genes related to salt tolerance in the triterpenoid saponin biosynthesis pathway.
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Affiliation(s)
- Meixi Zhang
- College of Pharmacy, Inner Mongolia Medical University, Hohhot, China
| | - Yushu Xing
- College of Pharmacy, Inner Mongolia Medical University, Hohhot, China
| | - Jiannan Ma
- College of Pharmacy, Inner Mongolia Medical University, Hohhot, China
| | - Ying Zhang
- College of Pharmacy, Inner Mongolia Medical University, Hohhot, China
| | - Juan Yu
- College of Pharmacy, Inner Mongolia Medical University, Hohhot, China
| | - Xiaoqin Wang
- College of Pharmacy, Inner Mongolia Medical University, Hohhot, China.
| | - Xin Jia
- College of Pharmacy, Inner Mongolia Medical University, Hohhot, China.
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Pant P, Sircar R, Prasad R, Prasad HO, Chitme HR. Protein Expression and Bioinformatics Study of Granulosa Cells of Polycystic Ovary Syndrome Expressed Under the Influence of DHEA. Clin Med Insights Endocrinol Diabetes 2023; 16:11795514231206732. [PMID: 38023736 PMCID: PMC10644732 DOI: 10.1177/11795514231206732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 09/22/2023] [Indexed: 12/01/2023] Open
Abstract
Background The reproductive system is heavily dependent on ovarian follicles, which are made up of germ cells (oocytes) and granulosa cells (GCs), including cumulus granulosa cells (CGCs) and mural granulosa cells (MGCs). Understanding their normal and steroid-induced functions is the key to understanding the pathophysiology of endocrinal diseases in women. Objective This study investigated the differentially expressed proteins by CGCs and MGCs of patients with polycystic ovarian syndrome (PCOS) and without subsequent exposure to dehydroepiandrosterone sulfate (DHEAS) and functional differentiation. Design The present study was observational and experimental study carried out in hospital involving 80 female patients undergoing IVF for infertility. Methods In this study, we isolated CGCs and MGCs from the follicular fluid of both PCOS and non-PCOS patients undergoing in vitro fertilization (IVF). The cells were cultured and treated with DHEAS for 48 hours, and these cells were extracted, digested, and analyzed by tandem mass spectrometry followed by processing of the results using open-source bioinformatics tools. Results The present investigation discovered 276 and 341 proteins in CGCs and MGCs, respectively. DHEAS reduced the number of proteins expressed by CGCs and MGCs to 34 and 57 from 91 and 94, respectively. Venn results of CGCs revealed 49, 53, 36, and 21 proteins in normal CGCs, PCOS-CGCs, post-DHEAS, and PCOS-CGCs, respectively. Venn analysis of MGCs showed 51 proteins specific to PCOS and 29 shared by normal and PCOS samples after DHEAS therapy. MGCs express the most binding and catalytic proteins, whereas CGCs express transporter-related proteins. A protein pathway study demonstrated considerable differences between normal and PCOS samples, while DHEAS-treated samples of both cell lines showed distinct pathways. String findings identified important network route components such as albumin, actin, apolipoprotein, complement component C3, and heat shock protein. Conclusion This is the first study to show how DHEAS-induced stress affects the expression of proteins by MGCs and CGCs isolated from normal and PCOS patients. Further studies are recommended to identify PCOS biomarkers from CGCs and MGCs expressed under the influence of DHEAS.
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Affiliation(s)
- Pankaj Pant
- Faculty of Pharmacy, DIT University, Dehradun, Uttarakhand, India
| | - Reema Sircar
- Indira IVF Hospital, Dehradun, Uttarakhand, India
| | - Ritu Prasad
- Morpheus Prasad International Hospital, Dehradun, Uttarakhand, India
| | - Hari Om Prasad
- Morpheus Prasad International Hospital, Dehradun, Uttarakhand, India
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Zhang Z, Wang XJ. N6-Methyladenosine mRNA Modification: From Modification Site Selectivity to Neurological Functions. Acc Chem Res 2023; 56:2992-2999. [PMID: 37847868 PMCID: PMC10634299 DOI: 10.1021/acs.accounts.3c00440] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Indexed: 10/19/2023]
Abstract
The development of various chemical methods has enabled scientists to decipher the distribution features and biological functions of RNA modifications in the past decade. In addition to modifying noncoding RNAs such as tRNAs and rRNAs, N6-methyladenosine (m6A) has been proven to be the most abundant internal chemical modification on mRNAs in eukaryotic cells and is also the most widely studied mRNA modification to date. Extensive studies have repeatedly demonstrated the important functions of m6A in various biological conditions, ranging from embryonic organ development to adult organ function and pathogenesis. Unlike DNA methylation which is relatively stable, the reversible m6A modification on mRNA is highly dynamic and easily influenced by various internal or external factors, such as cell type, developmental stage, nutrient supply, circadian rhythm, and environmental stresses.In this Account, we review our previous findings on the site selectivity mechanisms regulating m6A formation, as well as the physiological roles of m6A modification in cerebellum development and long-term memory consolidation. In our initial efforts to profile m6A in various types of mouse and human cells, we surprisingly found that the sequence motifs surrounding m6A sites were often complementary with the seed sequences of miRNAs. By manipulating the abundance of the miRNA biogenesis enzyme Dicer or individual miRNAs or mutating miRNA sequences, we were able to reveal a new role of nucleus localized miRNAs, which is to guide the m6A methyltransferase METTL3 to bind to mRNAs and to promote m6A formation. As a result, we partially answered the question of why only a small proportion of m6A motifs within an mRNA could have m6A modification at a certain time point. We further explored the functions of m6A modification in regulating brain development and brain functions. We found that cerebellum had the most severe defects when Mettl3 was knocked out in developing mouse embryonic brain and revealed that the underlying mechanisms could be attributed to aberrant mRNA splicing and enhanced cell apoptosis under m6A deficit conditions. On the other hand, knocking out Mettl3 in postnatal hippocampus did not cause morphological defects in the mouse brain but impaired the efficacy of long-term memory consolidation. Under learning stimuli, formation of m6A modifications could be detected on transcripts encoding proteins related to dendrite growth, synapse formation, and other memory related functions. Loss of m6A modifications on these transcripts would result in translation deficiency and reduced protein production, particularly in the translation of early response genes, and therefore would compromise the efficacy of long-term memory consolidation. Interestingly, excessive training sessions or increased training intensity could overcome such m6A deficiency related memory defects, which is likely due to the longer turnover cycle and the cumulative abundance of proteins throughout the training process. In addition to revealing the roles of m6A modification in regulating long-term memory formation, our work also demonstrated an effective method for studying memory formation efficacy. As the lack of an appropriate model for studying memory formation efficacy has been a long-lasting problem in the field of neural science, our hippocampus-specific postnatal m6A knockout model could also be utilized to study other questions related to memory formation efficacy.
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Affiliation(s)
- Zeyu Zhang
- Institute
of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiu-Jie Wang
- Institute
of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
- School
of Future Technology, University of Chinese
Academy of Sciences, Beijing 100049, China
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Baldwin M, Buckley CD, Guilak F, Hulley P, Cribbs AP, Snelling S. A roadmap for delivering a human musculoskeletal cell atlas. Nat Rev Rheumatol 2023; 19:738-752. [PMID: 37798481 DOI: 10.1038/s41584-023-01031-2] [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] [Accepted: 08/31/2023] [Indexed: 10/07/2023]
Abstract
Advances in single-cell technologies have transformed the ability to identify the individual cell types present within tissues and organs. The musculoskeletal bionetwork, part of the wider Human Cell Atlas project, aims to create a detailed map of the healthy musculoskeletal system at a single-cell resolution throughout tissue development and across the human lifespan, with complementary generation of data from diseased tissues. Given the prevalence of musculoskeletal disorders, this detailed reference dataset will be critical to understanding normal musculoskeletal function in growth, homeostasis and ageing. The endeavour will also help to identify the cellular basis for disease and lay the foundations for novel therapeutic approaches to treating diseases of the joints, soft tissues and bone. Here, we present a Roadmap delineating the critical steps required to construct the first draft of a human musculoskeletal cell atlas. We describe the key challenges involved in mapping the extracellular matrix-rich, but cell-poor, tissues of the musculoskeletal system, outline early milestones that have been achieved and describe the vision and directions for a comprehensive musculoskeletal cell atlas. By embracing cutting-edge technologies, integrating diverse datasets and fostering international collaborations, this endeavour has the potential to drive transformative changes in musculoskeletal medicine.
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Affiliation(s)
- Mathew Baldwin
- The Botnar Institute for Musculoskeletal Sciences, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Oxford, UK
| | - Christopher D Buckley
- The Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Oxford, UK
| | - Farshid Guilak
- Department of Orthopaedic Surgery, Washington University in St. Louis, St. Louis, MO, USA
- Shriners Hospitals for Children, St. Louis, MO, USA
| | - Philippa Hulley
- The Botnar Institute for Musculoskeletal Sciences, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Oxford, UK
| | - Adam P Cribbs
- The Botnar Institute for Musculoskeletal Sciences, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Oxford, UK
| | - Sarah Snelling
- The Botnar Institute for Musculoskeletal Sciences, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Oxford, UK.
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Tisi A, Palaniappan S, Maccarrone M. Advanced Omics Techniques for Understanding Cochlear Genome, Epigenome, and Transcriptome in Health and Disease. Biomolecules 2023; 13:1534. [PMID: 37892216 PMCID: PMC10605747 DOI: 10.3390/biom13101534] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/10/2023] [Accepted: 10/13/2023] [Indexed: 10/29/2023] Open
Abstract
Advanced genomics, transcriptomics, and epigenomics techniques are providing unprecedented insights into the understanding of the molecular underpinnings of the central nervous system, including the neuro-sensory cochlea of the inner ear. Here, we report for the first time a comprehensive and updated overview of the most advanced omics techniques for the study of nucleic acids and their applications in cochlear research. We describe the available in vitro and in vivo models for hearing research and the principles of genomics, transcriptomics, and epigenomics, alongside their most advanced technologies (like single-cell omics and spatial omics), which allow for the investigation of the molecular events that occur at a single-cell resolution while retaining the spatial information.
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Affiliation(s)
- Annamaria Tisi
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy;
| | - Sakthimala Palaniappan
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy;
| | - Mauro Maccarrone
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy;
- Laboratory of Lipid Neurochemistry, European Center for Brain Research (CERC), Santa Lucia Foundation IRCCS, 00143 Rome, Italy
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Shoaib M, Shah B, Sayed N, Ali F, Ullah R, Hussain I. Deep learning for plant bioinformatics: an explainable gradient-based approach for disease detection. FRONTIERS IN PLANT SCIENCE 2023; 14:1283235. [PMID: 37900739 PMCID: PMC10612337 DOI: 10.3389/fpls.2023.1283235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 09/27/2023] [Indexed: 10/31/2023]
Abstract
Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a combination of these omics data to learn crucial plant disease detection characteristics. We trained our model with multiple hyperparameters, such as the learning rate, number of hidden layers, and dropout rate, and attained a test set accuracy of 95.5%. We also conducted a sensitivity analysis to determine the model's resistance to hyperparameter variations. Our analysis revealed that our model exhibited a notable degree of resilience in the face of these variations, resulting in only marginal changes in performance. Furthermore, we conducted a comparative examination of the time efficiency of our EG-CNN model in relation to baseline models, including SVM, Random Forest, and Logistic Regression. Although our model necessitates additional time for training and validation due to its intricate architecture, it demonstrates a faster testing time per sample, offering potential advantages in real-world scenarios where speed is paramount. To gain insights into the internal representations of our EG-CNN model, we employed saliency maps for a qualitative analysis. This visualization approach allowed us to ascertain that our model effectively captures crucial aspects of plant disease, encompassing alterations in gene expression, metabolite levels, and spectral discrepancies within plant tissues. Leveraging omics data and hyperspectral images, this study underscores the potential of deep learning methods in the realm of plant disease detection. The proposed EG-CNN model exhibited impressive accuracy and displayed a remarkable degree of insensitivity to hyperparameter variations, which holds promise for future plant bioinformatics applications.
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Affiliation(s)
- Muhammad Shoaib
- Department of Computer Science, CECOS University of IT and Emerging Sciences, Peshawar, Pakistan
| | - Babar Shah
- College of Technological Innovation, Zayed University, Dubai, United Arab Emirates
| | - Nasir Sayed
- Department of Computer Science, Islamia College Peshawar, Peshawar, Pakistan
| | - Farman Ali
- Department of Computer Science and Engineering, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul, Republic of Korea
| | - Rafi Ullah
- Department of Medical Laboratory Technology, Riphah International University, Islamabad, Pakistan
| | - Irfan Hussain
- Centre for Autonomous Robotic Systems, Khalifa University, Abu Dhabi, United Arab Emirates
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Hsieh TF, Shen YM, Huang JH, Tsai JN, Lu MT, Lin CP. Insights into Grape Ripe Rot: A Focus on the Colletotrichum gloeosporioides Species Complex and Its Management Strategies. PLANTS (BASEL, SWITZERLAND) 2023; 12:2873. [PMID: 37571026 PMCID: PMC10421077 DOI: 10.3390/plants12152873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 07/27/2023] [Accepted: 08/03/2023] [Indexed: 08/13/2023]
Abstract
Grape ripe rot, which is predominantly caused by the Colletotrichum species, presents a growing threat to global grape cultivation. This threat is amplified by the increasing populations of the Colletotrichum species in response to warmer climates. In this review, we investigate the wide-ranging spectrum of grape ripe rot, specifically highlighting the role and characteristics of the C. gloeosporioides species complex (CGSC). We incorporate this understanding as we explore the diverse symptoms that lead to infected grapevines, their intricate life cycle and epidemiology, and the escalating prevalence of C. viniferum in Asia and globally. Furthermore, we delve into numerous disease management strategies, both conventional and emerging, such as prevention and mitigation measures. These strategies include the examination of host resistances, beneficial cultivation practices, sanitation measures, microbiome health maintenance, fungicide choice and resistance, as well as integrated management approaches. This review seeks to enhance our understanding of this globally significant disease, aspiring to assist in the development and improvement of effective prevention and control strategies.
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Affiliation(s)
- Ting-Fang Hsieh
- Plant Pathology Division, Taiwan Agricultural Research Institute, Taichung City 41362, Taiwan; (T.-F.H.); (J.-H.H.); (J.-N.T.)
| | - Yuan-Min Shen
- Master Program for Plant Medicine, College of Bio-Resources and Agriculture, National Taiwan University, Taipei 10617, Taiwan;
| | - Jin-Hsing Huang
- Plant Pathology Division, Taiwan Agricultural Research Institute, Taichung City 41362, Taiwan; (T.-F.H.); (J.-H.H.); (J.-N.T.)
| | - Jyh-Nong Tsai
- Plant Pathology Division, Taiwan Agricultural Research Institute, Taichung City 41362, Taiwan; (T.-F.H.); (J.-H.H.); (J.-N.T.)
| | - Ming-Te Lu
- Crop Science Division, Taiwan Agricultural Research Institute, Taichung City 41326, Taiwan;
| | - Chu-Ping Lin
- Plant Pathology Division, Taiwan Agricultural Research Institute, Taichung City 41362, Taiwan; (T.-F.H.); (J.-H.H.); (J.-N.T.)
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Li Z, Vacanti NM. A Tale of Three Proteomes: Visualizing Protein and Transcript Abundance Relationships in the Breast Cancer Proteome Portal. J Proteome Res 2023; 22:2727-2733. [PMID: 37493333 DOI: 10.1021/acs.jproteome.3c00290] [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: 07/27/2023]
Abstract
Molecular characterization is transforming research on novel therapeutics in breast cancer. High-throughput methodologies are unbiased to hypotheses; thus, data produced are relevant to address unlimited questions and provide resources for the experimental design process. However, the opportunity is often overlooked because data are not readily accessed or analyzed. Herein, the Breast Cancer Proteome Portal, the only online tool for analyzing protein and transcript abundances across the three breast cancer proteomics studies, is presented. The tool is applied to demonstrate that cofunctioning protein abundances are highly correlated and, conversely, high abundance correlation may be an indicator of cofunction. Furthermore, the cofunction-correlation relationship is less resolved at the transcript level. By applying analysis and visualization tools within the Breast Cancer Proteome Portal, insights are garnered about serine synthesis and the compartmentalization of one-carbon metabolism in breast cancer, and a transcription factor tumorigenic regulatory network of glutamine deamination and oxidation is proposed, illustrating that the Breast Cancer Proteome Portal provides an interface for garnering insights from the information-rich studies of the breast cancer proteome.
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Affiliation(s)
- Zhuoheng Li
- Division of Nutritional Sciences, Cornell University, Ithaca, New York 14853-0001, United States
| | - Nathaniel M Vacanti
- Division of Nutritional Sciences, Cornell University, Ithaca, New York 14853-0001, United States
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Silva C, Requicha J, Dias I, Bastos E, Viegas C. Genomic Medicine in Canine Periodontal Disease: A Systematic Review. Animals (Basel) 2023; 13:2463. [PMID: 37570272 PMCID: PMC10417655 DOI: 10.3390/ani13152463] [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: 06/19/2023] [Revised: 07/28/2023] [Accepted: 07/29/2023] [Indexed: 08/13/2023] Open
Abstract
Genomic medicine has become a growing reality; however, it is still taking its first steps in veterinary medicine. Through this approach, it will be possible to trace the genetic profile of a given individual and thus know their susceptibility to certain diseases, namely periodontal disease. This condition is one of the most frequently diagnosed in companion animal clinics, especially in dogs. Due to the limited existing information and the lack of comprehensive studies, the objective of the present study was to systematically review the existing scientific literature regarding genomic medicine in canine periodontal disease and determine which genes have already been studied and their probable potential. This study followed the recommendations of the PRISMA 2020 methodology. Canine periodontal disease allied to genomic medicine were the subjects of this systematic review. Only six articles met all of the inclusion criteria, and these were analyzed in detail. These studies described genetic variations in the following genes: interleukin-6, interleukin-10, interleukin-1, lactotransferrin, toll-like receptor 9, and receptor activator of nuclear factor-kappa B. Only in two of them, namely interleukin-1 and toll-like receptor 9 genes, may the identified genetic variations explain the susceptibility that certain individuals have to the development of periodontal disease. It is necessary to expand the studies on the existing polymorphic variations in genes and their relationship with the development of periodontal disease. Only then will it be possible to fully understand the biological mechanisms that are involved in this disease and that determine the susceptibility to its development.
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Affiliation(s)
- Carolina Silva
- Department of Veterinary Sciences, School of Agricultural and Veterinary Sciences (ECAV), University of Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal; (C.S.); (J.R.); (I.D.)
- CECAV—Centre for Animal Sciences and Veterinary Studies, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal
| | - João Requicha
- Department of Veterinary Sciences, School of Agricultural and Veterinary Sciences (ECAV), University of Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal; (C.S.); (J.R.); (I.D.)
- CECAV—Centre for Animal Sciences and Veterinary Studies, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal
- AL4AnimalS—Associate Laboratory for Animal and Veterinary Sciences, 1300-477 Lisboa, Portugal
| | - Isabel Dias
- Department of Veterinary Sciences, School of Agricultural and Veterinary Sciences (ECAV), University of Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal; (C.S.); (J.R.); (I.D.)
- CECAV—Centre for Animal Sciences and Veterinary Studies, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal
- AL4AnimalS—Associate Laboratory for Animal and Veterinary Sciences, 1300-477 Lisboa, Portugal
- CITAB—Center for the Research and Technology of Agro-Environmental and Biological Sciences, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal;
- Inov4Agro-Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, 5000-801 Vila Real, Portugal
| | - Estela Bastos
- CITAB—Center for the Research and Technology of Agro-Environmental and Biological Sciences, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal;
- Inov4Agro-Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, 5000-801 Vila Real, Portugal
- Department of Genetics and Biotechnology, School of Life and Environmental Sciences, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal
| | - Carlos Viegas
- Department of Veterinary Sciences, School of Agricultural and Veterinary Sciences (ECAV), University of Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal; (C.S.); (J.R.); (I.D.)
- CECAV—Centre for Animal Sciences and Veterinary Studies, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal
- AL4AnimalS—Associate Laboratory for Animal and Veterinary Sciences, 1300-477 Lisboa, Portugal
- CITAB—Center for the Research and Technology of Agro-Environmental and Biological Sciences, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal;
- Inov4Agro-Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, 5000-801 Vila Real, Portugal
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Zhu X, Zhao Y, Sun N, Li C, Jiang Q, Zhang Y, Wei H, Li Y, Hu Q, Li X. Comparison of the gut microbiota and untargeted gut tissue metabolome of Chinese mitten crabs ( Eriocheir sinensis) with different shell colors. Front Microbiol 2023; 14:1218152. [PMID: 37520354 PMCID: PMC10374289 DOI: 10.3389/fmicb.2023.1218152] [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: 05/06/2023] [Accepted: 06/21/2023] [Indexed: 08/01/2023] Open
Abstract
Introduction The Chinese mitten crab (Eriocheir sinensis) is a highly valued freshwater crustacean in China. While the natural shell color of E. sinensis is greenish brown (GH), we found a variety with a brownish-orange shell color (RH). Although RH is more expensive, it exhibits a lower molting frequency and growth rate compared with GH, which significantly reduces its yield and hinders large-scale farming. The growth and development of animals are closely related to their gut microbiota and gut tissue metabolic profiles. Methods In this study, we compared the gut microbiome communities and metabolic profiles of juvenile RH and GH crabs using 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS), respectively. Results Our findings indicated that the intestinal microbial composition and metabolic characteristics of E. sinensis differed significantly between RH and GH. At the operational taxonomic unit (OTU) level, the α-diversity of the gut microbiota did not differ significantly between RH and GH, while the β-diversity of the RH gut microbiota was higher than that of the GH gut microbiota. At the species level, the richness of unclassified_c_Alphaproteobacteria was significantly higher in the GH group, while the RH group had a significantly higher richness of three low-abundance species, Flavobacteria bacterium BAL38, Paraburkholderia ferrariae, and uncultured_bacterium_g__Legionella. In the current study, 598 gut tissue metabolites were identified, and 159 metabolites were significantly different between GH and RH. The metabolite profile of RH was characteristic of a low level of most amino acids and lipid metabolites and a high level of several pigments compared with that of GH. These metabolites were enriched in 102 KEGG pathways. Four pathways, including (1) Central carbon metabolism in cancer, (2) protein digestion and absorption, (3) alanine, aspartate and glutamate metabolism, and (4) aminoacyl-tRNA biosynthesis, were significantly enriched. The correlation analysis between metabolites and microbiotas indicated that most key differential metabolites were positively correlated with the abundance of Shewanella_sp_MR-7. Discussion This research provided a greater understanding of the physiological conditions of E. sinensis varieties with different shell colors by comparing the gut microbiota and gut tissue metabolome.
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Affiliation(s)
- Xiaochen Zhu
- College of Science and Engineering, Flinders University, Adelaide, SA, Australia
| | - Yingying Zhao
- College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
- Liaoning Panjin Wetland Ecosystem National Observation and Research Station, Shenyang, China
| | - Na Sun
- Panjin Guanghe Crab Industry Co. Ltd., Panjin, China
| | - Changlei Li
- College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Qing Jiang
- College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yazhao Zhang
- College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Hua Wei
- College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
- Liaoning Panjin Wetland Ecosystem National Observation and Research Station, Shenyang, China
| | - Yingdong Li
- College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
- Liaoning Panjin Wetland Ecosystem National Observation and Research Station, Shenyang, China
| | - Qingbiao Hu
- College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
- Liaoning Panjin Wetland Ecosystem National Observation and Research Station, Shenyang, China
| | - Xiaodong Li
- College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, China
- Liaoning Panjin Wetland Ecosystem National Observation and Research Station, Shenyang, China
- Panjin Guanghe Crab Industry Co. Ltd., Panjin, China
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