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Dovrolis N, Gazouli M, Rigal F, Whittaker RJ, Matthews TJ, Georgiou K, Theodoropoulos G, Triantis KA. Power-law scaling in intratumoral microbiota of colorectal cancer. Gut Pathog 2024; 16:34. [PMID: 38972996 PMCID: PMC11229225 DOI: 10.1186/s13099-024-00631-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 06/28/2024] [Indexed: 07/09/2024] Open
Abstract
It has recently been proposed that the study of microbial dynamics in humans may gain insights from island biogeographical theory. Here, we test whether the diversity of the intratumoral microbiota of colorectal cancer tumors (CRC) follows a power law with tumor size akin to the island species-area relationship. We confirm a direct correlation between the quantity of Amplicon Sequence Variants (ASVs) within CRC tumors and tumor sizes, following a (log)power model, explaining 47% of the variation. Understanding the processes involved, potentially through the analogy of tumors and islands, may ultimately contribute to future clinical and therapeutic strategies.
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Affiliation(s)
- Nikolas Dovrolis
- Department of Basic Medical Sciences, Laboratory of Biology, Medical School, National and Kapodistrian University of Athens, Athens, 11527, Greece.
| | - Maria Gazouli
- Department of Basic Medical Sciences, Laboratory of Biology, Medical School, National and Kapodistrian University of Athens, Athens, 11527, Greece.
| | - François Rigal
- Institut Des Sciences Analytiques et de Physico Chimie pour L'environnement et les Materiaux, CNRS - Université de Pau et des Pays de l'Adour - E2S UPPA, UMR5254, Pau, 64000, France
- CE3C - Centre for Ecology, Evolution and Environmental Changes/Azorean Biodiversity Group, Faculty of Agricultural Sciences and Environment, CHANGE - Global Change and Sustainability Institute and Universidade dos Açores, Angra do Heroísmo, Açores, PT-9700-042, Portugal
| | - Robert J Whittaker
- School of Geography and the Environment, University of Oxford, Oxford, UK
- Center for Macroecology, Evolution and Climate, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Thomas J Matthews
- CE3C - Centre for Ecology, Evolution and Environmental Changes/Azorean Biodiversity Group, Faculty of Agricultural Sciences and Environment, CHANGE - Global Change and Sustainability Institute and Universidade dos Açores, Angra do Heroísmo, Açores, PT-9700-042, Portugal
- GEES (School of Geography, Earth and Environmental Sciences, Birmingham Institute of Forest Research, University of Birmingham, Birmingham, UK
| | - Konstantinos Georgiou
- 1st Department of Propaedeutic Surgery, Medical School, National Kapodistrian University of Athens, Hippocratio Hospital, Athens, 11527, Greece
| | - George Theodoropoulos
- 1st Department of Propaedeutic Surgery, Medical School, National Kapodistrian University of Athens, Hippocratio Hospital, Athens, 11527, Greece
| | - Kostas A Triantis
- Department of Ecology and Taxonomy, National & Kapodistrian University of Athens, Athens, 11527, Greece.
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2
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Chakraborty S, Sharma G, Karmakar S, Banerjee S. Multi-OMICS approaches in cancer biology: New era in cancer therapy. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167120. [PMID: 38484941 DOI: 10.1016/j.bbadis.2024.167120] [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: 01/16/2024] [Revised: 03/06/2024] [Accepted: 03/06/2024] [Indexed: 04/01/2024]
Abstract
Innovative multi-omics frameworks integrate diverse datasets from the same patients to enhance our understanding of the molecular and clinical aspects of cancers. Advanced omics and multi-view clustering algorithms present unprecedented opportunities for classifying cancers into subtypes, refining survival predictions and treatment outcomes, and unravelling key pathophysiological processes across various molecular layers. However, with the increasing availability of cost-effective high-throughput technologies (HTT) that generate vast amounts of data, analyzing single layers often falls short of establishing causal relations. Integrating multi-omics data spanning genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes offers unique prospects to comprehend the underlying biology of complex diseases like cancer. This discussion explores algorithmic frameworks designed to uncover cancer subtypes, disease mechanisms, and methods for identifying pivotal genomic alterations. It also underscores the significance of multi-omics in tumor classifications, diagnostics, and prognostications. Despite its unparalleled advantages, the integration of multi-omics data has been slow to find its way into everyday clinics. A major hurdle is the uneven maturity of different omics approaches and the widening gap between the generation of large datasets and the capacity to process this data. Initiatives promoting the standardization of sample processing and analytical pipelines, as well as multidisciplinary training for experts in data analysis and interpretation, are crucial for translating theoretical findings into practical applications.
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Affiliation(s)
- Sohini Chakraborty
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
| | - Gaurav Sharma
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
| | - Sricheta Karmakar
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
| | - Satarupa Banerjee
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.
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3
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Wei W, Millward A, Koslicki D. Finding phylogeny-aware and biologically meaningful averages of metagenomic samples: L2UniFrac. Bioinformatics 2023; 39:i57-i65. [PMID: 37387190 DOI: 10.1093/bioinformatics/btad238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023] Open
Abstract
MOTIVATION Metagenomic samples have high spatiotemporal variability. Hence, it is useful to summarize and characterize the microbial makeup of a given environment in a way that is biologically reasonable and interpretable. The UniFrac metric has been a robust and widely used metric for measuring the variability between metagenomic samples. We propose that the characterization of metagenomic environments can be improved by finding the average, a.k.a. the barycenter, among the samples with respect to the UniFrac distance. However, it is possible that such a UniFrac-average includes negative entries, making it no longer a valid representation of a metagenomic community. RESULTS To overcome this intrinsic issue, we propose a special version of the UniFrac metric, termed L2UniFrac, which inherits the phylogenetic nature of the traditional UniFrac and with respect to which one can easily compute the average, producing biologically meaningful environment-specific "representative samples." We demonstrate the usefulness of such representative samples as well as the extended usage of L2UniFrac in efficient clustering of metagenomic samples, and provide mathematical characterizations and proofs to the desired properties of L2UniFrac. AVAILABILITY AND IMPLEMENTATION A prototype implementation is provided at https://github.com/KoslickiLab/L2-UniFrac.git. All figures, data, and analysis can be reproduced at https://github.com/KoslickiLab/L2-UniFrac-Paper.
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Affiliation(s)
- Wei Wei
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, United States
| | - Andrew Millward
- Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16802, United States
| | - David Koslicki
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, United States
- Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16802, United States
- Department of Biology, Pennsylvania State University, University Park, PA 16802, United States
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4
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Ibañez-Lligoña M, Colomer-Castell S, González-Sánchez A, Gregori J, Campos C, Garcia-Cehic D, Andrés C, Piñana M, Pumarola T, Rodríguez-Frias F, Antón A, Quer J. Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses. Viruses 2023; 15:v15020587. [PMID: 36851800 PMCID: PMC9965957 DOI: 10.3390/v15020587] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 02/16/2023] [Accepted: 02/17/2023] [Indexed: 02/24/2023] Open
Abstract
Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens.
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Affiliation(s)
- Marta Ibañez-Lligoña
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Sergi Colomer-Castell
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Alejandra González-Sánchez
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
| | - Josep Gregori
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
| | - Carolina Campos
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Damir Garcia-Cehic
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
| | - Cristina Andrés
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
| | - Maria Piñana
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
| | - Tomàs Pumarola
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Microbiology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Francisco Rodríguez-Frias
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Department of Basic Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, 08195 Barcelona, Spain
| | - Andrés Antón
- Microbiology Department, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Microbiology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
| | - Josep Quer
- Liver Diseases-Viral Hepatitis, Liver Unit, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Passeig Vall d’Hebron 119-129, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Campus de la UAB, Plaça Cívica, 08193 Bellaterra, Spain
- Correspondence:
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5
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Wei W, Millward A, Koslicki D. Finding phylogeny-aware and biologically meaningful averages of metagenomic samples: L 2 UniFrac. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.02.526854. [PMID: 36778267 PMCID: PMC9915697 DOI: 10.1101/2023.02.02.526854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Metagenomic samples have high spatiotemporal variability. Hence, it is useful to summarize and characterize the microbial makeup of a given environment in a way that is biologically reasonable and interpretable. The UniFrac metric has been a robust and widely-used metric for measuring the variability between metagenomic samples. We propose that the characterization of metagenomic environments can be achieved by finding the average, a.k.a. the barycenter, among the samples with respect to the UniFrac distance. However, it is possible that such a UniFrac-average includes negative entries, making it no longer a valid representation of a metagenomic community. To overcome this intrinsic issue, we propose a special version of the UniFrac metric, termed L 2 UniFrac, which inherits the phylogenetic nature of the traditional UniFrac and with respect to which one can easily compute the average, producing biologically meaningful environment-specific "representative samples". We demonstrate the usefulness of such representative samples as well as the extended usage of L 2 UniFrac in efficient clustering of metagenomic samples, and provide mathematical characterizations and proofs to the desired properties of L 2 UniFrac. A prototype implementation is provided at: https://github.com/KoslickiLab/L2-UniFrac.git .
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Affiliation(s)
- Wei Wei
- Huck Institutes of Life Sciences, Pennsylvania State University
| | - Andrew Millward
- Department of Computer Science and Engineering, Pennsylvania State University
| | - David Koslicki
- Huck Institutes of Life Sciences, Pennsylvania State University,Department of Computer Science and Engineering, Pennsylvania State University,Department of Biology, Pennsylvania State University
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6
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Liu Y, Zhang Y, Zhang G, Yang Z, Wang Y, Wu S, Chen D, Zhang H, Liu Y. Development and characterisation of anti-HPV16 monoclonal antibodies for assembly of an HPV16 detection kit. Biotechnol Appl Biochem 2022; 70:613-621. [PMID: 35841266 DOI: 10.1002/bab.2384] [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: 02/04/2022] [Accepted: 07/05/2022] [Indexed: 11/11/2022]
Abstract
Quality control is very important during the development of 3-valent (16/18/58), 9-valent (6/11/16/18/31/33/45/52/58), and 15-valent human papillomavirus (HPV) vaccines (6/11/16/18/31/33/35/39/45/52/56/58/59/68). All 3-valent, 9-valent, and 15-valent HPV vaccines contain the HPV16 antigen; therefore, a detection method that can specifically identify HPV16 in vaccines is urgently required. This study aimed to develop and characterise monoclonal antibodies to assemble a highly specific HPV16 detection kit. The HPV16 L1 pentameric protein developed as an immunogen was used to prepare monoclonal antibodies. From the pool of prepared monoclonal antibodies, we selected 4G12 and 5A6 to screen and evaluate their subtypes, specificity, neutralising activity, serum competition, binding affinity, and gene sequencing. After these characterisations, an enzyme-linked immunosorbent assay kit for these monoclonal antibodies was developed, and excellent quality was demonstrated in the assessment of linearity, repeatability, and specificity. The developed detection kit has great potential for wide use in clinical testing and quality control in vaccine production processes. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Yuying Liu
- Beijing Health Guard Biotechnology Inc., BDA, Daxing District, Beijing, 100176, China.,National Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, China.,School of Chemical and Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yao Zhang
- Beijing Health Guard Biotechnology Inc., BDA, Daxing District, Beijing, 100176, China
| | - Guifeng Zhang
- National Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, China
| | - Zengmin Yang
- Beijing Health Guard Biotechnology Inc., BDA, Daxing District, Beijing, 100176, China
| | - Yan Wang
- Beijing Health Guard Biotechnology Inc., BDA, Daxing District, Beijing, 100176, China
| | - Shuming Wu
- Beijing Health Guard Biotechnology Inc., BDA, Daxing District, Beijing, 100176, China
| | - Dan Chen
- Beijing Health Guard Biotechnology Inc., BDA, Daxing District, Beijing, 100176, China
| | - Haijiang Zhang
- Beijing Health Guard Biotechnology Inc., BDA, Daxing District, Beijing, 100176, China
| | - Yongjiang Liu
- Beijing Health Guard Biotechnology Inc., BDA, Daxing District, Beijing, 100176, China
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7
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Moradi N, Ohadian Moghadam S, Heidarzadeh S. Application of next-generation sequencing in the diagnosis of gastric cancer. Scand J Gastroenterol 2022; 57:842-855. [PMID: 35293278 DOI: 10.1080/00365521.2022.2041717] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Objectives: Gastric cancer (GC) is a disease with high mortality, poor prognosis and numerous risk factors. GC has an asymptomatic nature in early stages of the diseases, making timely diagnosis complicated using common conventional approaches, namely pathological examinations and imaging tests. Recently, molecular profiling of GC using next generation sequencing (NGS) has opened new doors to efficient prognostic, diagnostic, and therapeutic strategies. The current review aims to thoroughly discuss and compare the current NGS techniques and commercial platforms utilized for GC diagnosis and treatment, highlighting the most recent NGS-based GC studies. Furthermore, this review addresses the challenges of clinical implementation of NGS in GC.Materials and methods: This review was conducted according to the eligible studies identified via search of Web of Science, PubMed, Scopus, Embase and the Cochrane Library. In the present study, data on gastric cancer patients and NGS methods used to diagnose the disease were reviewed.Conclusion: Given the ever-rising advancements in NGS technologies, bioinformatics, healthcare guidelines and refined classifications, it is hoped that these technologies can actualize their advantages and optimize GC patients' experience.
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Affiliation(s)
- Narges Moradi
- Department of Life Technologies, University of Turku, Turku, Finland
| | | | - Siamak Heidarzadeh
- Department of Microbiology and Virology, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
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8
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Wang L, Li F, Gu B, Qu P, Liu Q, Wang J, Tang J, Cai S, Zhao Q, Ming Z. Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis. Front Microbiol 2022; 13:883734. [PMID: 35783436 PMCID: PMC9247514 DOI: 10.3389/fmicb.2022.883734] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open
Abstract
Currently, more and more studies suggested that reductionism was lack of holistic and integrative view of biological processes, leading to limited understanding of complex systems like microbiota and the associated diseases. In fact, microbes are rarely present in individuals but normally live in complex multispecies communities. With the recent development of a variety of metaomics techniques, microbes could be dissected dynamically in both temporal and spatial scales. Therefore, in-depth understanding of human microbiome from different aspects such as genomes, transcriptomes, proteomes, and metabolomes could provide novel insights into their functional roles, which also holds the potential in making them diagnostic biomarkers in many human diseases, though there is still a huge gap to fill for the purpose. In this mini-review, we went through the frontlines of the metaomics techniques and explored their potential applications in clinical diagnoses of human diseases, e.g., infectious diseases, through which we concluded that novel diagnostic methods based on human microbiomes shall be achieved in the near future, while the limitations of these techniques such as standard procedures and computational challenges for rapid and accurate analysis of metaomics data in clinical settings were also examined.
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Affiliation(s)
- Liang Wang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Fen Li
- Department of Laboratory Medicine, Huaiyin Hospital, Huai’an, China
| | - Bin Gu
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Pengfei Qu
- The First School of Clinical Medicine, Xuzhou Medical University, Xuzhou, China
| | - Qinghua Liu
- State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Taipa, Macao SAR, China
| | - Junjiao Wang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Jiawei Tang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Shubin Cai
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
| | - Qi Zhao
- School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, China
- *Correspondence: Qi Zhao,
| | - Zhong Ming
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
- Zhong Ming,
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9
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Music of metagenomics-a review of its applications, analysis pipeline, and associated tools. Funct Integr Genomics 2021; 22:3-26. [PMID: 34657989 DOI: 10.1007/s10142-021-00810-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 09/25/2021] [Accepted: 10/03/2021] [Indexed: 10/20/2022]
Abstract
This humble effort highlights the intricate details of metagenomics in a simple, poetic, and rhythmic way. The paper enforces the significance of the research area, provides details about major analytical methods, examines the taxonomy and assembly of genomes, emphasizes some tools, and concludes by celebrating the richness of the ecosystem populated by the "metagenome."
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10
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Huang G, Yang J, Chen L, Wu T. Editorial: Applications of Metagenomics in Studying Human Cancer. Front Genet 2021; 12:760141. [PMID: 34603403 PMCID: PMC8481774 DOI: 10.3389/fgene.2021.760141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 09/06/2021] [Indexed: 12/02/2022] Open
Affiliation(s)
- Guohua Huang
- School of Electrical Engineering, Shaoyang University, Shaoyang, China
| | | | - Lei Chen
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Taoyang Wu
- School of Computing Sciences, University of East Anglia, Norwich, United Kingdom
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11
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Neagu AN, Whitham D, Buonanno E, Jenkins A, Alexa-Stratulat T, Tamba BI, Darie CC. Proteomics and its applications in breast cancer. Am J Cancer Res 2021; 11:4006-4049. [PMID: 34659875 PMCID: PMC8493401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 07/05/2021] [Indexed: 06/13/2023] Open
Abstract
Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.
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Affiliation(s)
- Anca-Narcisa Neagu
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson UniversityPotsdam, NY 13699-5810, USA
- Laboratory of Animal Histology, Faculty of Biology, “Alexandru Ioan Cuza” University of IașiCarol I bvd. No. 22, Iași 700505, Romania
| | - Danielle Whitham
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson UniversityPotsdam, NY 13699-5810, USA
| | - Emma Buonanno
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson UniversityPotsdam, NY 13699-5810, USA
| | - Avalon Jenkins
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson UniversityPotsdam, NY 13699-5810, USA
| | - Teodora Alexa-Stratulat
- Department of Medical Oncology-Radiotherapy, “Grigore T. Popa” University of Medicine and PharmacyIndependenței bvd. No. 16-18, Iași 700021, Romania
| | - Bogdan Ionel Tamba
- Advanced Center for Research and Development in Experimental Medicine (CEMEX), “Grigore T. Popa” University of Medicine and PharmacyMihail Kogălniceanu Street No. 9-13, Iași 700454, Romania
| | - Costel C Darie
- Biochemistry & Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson UniversityPotsdam, NY 13699-5810, USA
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12
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Macaluso JN. EDITORIAL COMMENT. Urology 2021; 155:115-116. [PMID: 34488993 DOI: 10.1016/j.urology.2021.04.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Joseph N Macaluso
- Department of Urology, Louisiana State University Health Center, New Orleans, LA; Department of Urology, Louisiana State University Health Foundation, New Orleans, LA
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El Jaddaoui I, Allali I, Sehli S, Ouldim K, Hamdi S, Al Idrissi N, Nejjari C, Amzazi S, Bakri Y, Ghazal H. Cancer Omics in Africa: Present and Prospects. Front Oncol 2020; 10:606428. [PMID: 33425763 PMCID: PMC7793679 DOI: 10.3389/fonc.2020.606428] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 11/11/2020] [Indexed: 12/15/2022] Open
Abstract
During the last century, cancer biology has been arguably one of the most investigated research fields. To gain deeper insight into cancer mechanisms, scientists have been attempting to integrate multi omics data in cancer research. Cancer genomics, transcriptomics, metabolomics, proteomics, and metagenomics are the main multi omics strategies used currently in the diagnosis, prognosis, treatment, and biomarker discovery in cancer. In this review, we describe the use of different multi omics strategies in cancer research in the African continent and discuss the main challenges facing the implementation of these approaches in African countries such as the lack of training programs in bioinformatics in general and omics strategies in particular and suggest paths to address deficiencies. As a way forward, we advocate for the establishment of an "African Cancer Genomics Consortium" to promote intracontinental collaborative projects and enhance engagement in research activities that address indigenous aspects for cancer precision medicine.
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Affiliation(s)
- Islam El Jaddaoui
- Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco
| | - Imane Allali
- Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco
| | - Sofia Sehli
- Department of Fundamental Sciences, School of Medicine, Mohammed VI University of Health Sciences, Casablanca, Morocco
| | | | - Salsabil Hamdi
- Environmental Health Laboratory, Pasteur Institute, Casablanca, Morocco
| | - Najib Al Idrissi
- Department of Surgery, School of Medicine, Mohammed VI University of Health Sciences, Casablanca, Morocco
| | - Chakib Nejjari
- Department of Medicine, School of Medicine, Mohammed VI University of Health Sciences, Casablanca, Morocco
| | - Saaïd Amzazi
- Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco
| | - Youssef Bakri
- Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco
| | - Hassan Ghazal
- Department of Fundamental Sciences, School of Medicine, Mohammed VI University of Health Sciences, Casablanca, Morocco
- National Center for Scientific and Technical Research, Rabat, Morocco
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Metatax: Metataxonomics with a Compi-Based Pipeline for Precision Medicine. Interdiscip Sci 2020; 12:252-257. [PMID: 32350726 DOI: 10.1007/s12539-020-00368-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 03/17/2020] [Accepted: 04/16/2020] [Indexed: 01/20/2023]
Abstract
The human body immune system, metabolism and homeostasis are affected by microbes. Dysbiosis occurs when the homeostatic equilibrium is disrupted due to an alteration in the normal microbiota of the intestine. Dysbiosis can cause cancer, and also affect a patient's ability to respond to treatment. Metataxonomics seeks to identify the bacteria present in a biological sample, based on the sequencing of the 16S rRNA genetic marker. Precision medicine attempts to find relationships between the microbiota and the risk of acquiring cancer, and design new therapies targeting bacteria. Flexible and portable bioinformatic pipelines are necessary to be able to bring metataxonomics to the clinical field, which allow groups of biological samples to be classified according to their diversity in the microbiota. With this aim we implemented Metatax, a new pipeline to analyze biological samples based on 16S rRNA gene sequencing. The results obtained with our pipeline should complement those obtained by sequencing a patient's DNA and RNA, in addition to clinical data, to improve knowledge of the possible reasons for a disease or a worse response to treatment.
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Shah UJ, Nasiruddin M, Dar SA, Khan MKA, Akhter MR, Singh N, Rabaan AA, Haque S. Emerging biomarkers and clinical significance of HPV genotyping in prevention and management of cervical cancer. Microb Pathog 2020; 143:104131. [PMID: 32169490 DOI: 10.1016/j.micpath.2020.104131] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 02/10/2020] [Accepted: 03/06/2020] [Indexed: 12/15/2022]
Abstract
Cervical cancer is a growing and serious problem world-wide in women, but more acute in developing countries especially in Indian subcontinent. The main causative agent for the disease is Human Papilloma Virus (HPV). The history of the cervical cancer goes back to eighteenth century as the HPV infection is reported since 1800s. Presently, the genetic structure of HPV is well defined. Several screening tests including cytology and visual based screening and high risk HPV testing are available. Also available are various clinical and commercial diagnostic tests. However due to the lack of awareness and population-based screening programs, the morbidity and mortality rate is alarmingly high. There are new emerging biomarkers including E6/E7 mRNA, p16ink4a, markers of aberrant S-phase induction, chromosomal abnormalities and miRNAs along with advanced genotyping methods. These markers have clinical significance and are helpful in disease prevention and management. Further, recent advancement in the field of metagenomics has increased the prospects of identifying newer microbes, viruses hitherto reported thus far in the context of HPV infection. Analysis of HPV cases using modern tools including genotyping using more powerful biomarkers is envisaged to enhance the prospects of early diagnosis, better prognosis, more reliable treatment and eventual management of the disease.
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Affiliation(s)
- Ushma Jaykamal Shah
- MedGenome Labs Ltd., Kailash Cancer Hospital and Research Center, Muni Seva Ashram, P.O. Goraj, Tal. Waghodia, Dist. Vadodara, 391760, Gujarat, India
| | - Mohammad Nasiruddin
- Anand Diagnostic Laboratory (A Neuberg Associate), Neuberg Anand Reference Laboratory, Anand Tower, 54, Bowring Hospital Road, Shivajinagar, Bangalore - 560001, India.
| | - Sajad Ahmad Dar
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, 45142, Saudi Arabia
| | - Md Khurshid Alam Khan
- School of Life Sciences, BS Abdur Rahman Crescent Institute of Science and Technology, Chennai, 600048, Tamil Nadu, India
| | - Mohammad Riyaz Akhter
- MedGenome Labs Ltd., 3rd Floor, Narayana Nethralaya Building, Narayana Health City, # 258/A, Bommasandra, Hosur Road, Bangalore, 560099, Karnataka, India
| | - Nidhi Singh
- Department of Obstetrics and Gynecology, Prasad Institute of Medical Sciences, Lucknow, 226401, Uttar Pradesh, India
| | - Ali A Rabaan
- Molecular Diagnostic Laboratory, Johns Hopkins Aramco Healthcare, Saudi Aramco, Dhahran, 31311, Saudi Arabia
| | - Shafiul Haque
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan, 45142, Saudi Arabia.
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Singh H, Kamble A, Sawant S. 16S ribosomal RNA gene-based metagenomics: A review. BIOMEDICAL RESEARCH JOURNAL 2020. [DOI: 10.4103/bmrj.bmrj_4_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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17
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Mikó E, Kovács T, Sebő É, Tóth J, Csonka T, Ujlaki G, Sipos A, Szabó J, Méhes G, Bai P. Microbiome-Microbial Metabolome-Cancer Cell Interactions in Breast Cancer-Familiar, but Unexplored. Cells 2019; 8:E293. [PMID: 30934972 PMCID: PMC6523810 DOI: 10.3390/cells8040293] [Citation(s) in RCA: 109] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 03/22/2019] [Accepted: 03/26/2019] [Indexed: 12/18/2022] Open
Abstract
Breast cancer is a leading cause of death among women worldwide. Dysbiosis, an aberrant composition of the microbiome, characterizes breast cancer. In this review we discuss the changes to the metabolism of breast cancer cells, as well as the composition of the breast and gut microbiome in breast cancer. The role of the breast microbiome in breast cancer is unresolved, nevertheless it seems that the gut microbiome does have a role in the pathology of the disease. The gut microbiome secretes bioactive metabolites (reactivated estrogens, short chain fatty acids, amino acid metabolites, or secondary bile acids) that modulate breast cancer. We highlight the bacterial species or taxonomical units that generate these metabolites, we show their mode of action, and discuss how the metabolites affect mitochondrial metabolism and other molecular events in breast cancer. These metabolites resemble human hormones, as they are produced in a "gland" (in this case, the microbiome) and they are subsequently transferred to distant sites of action through the circulation. These metabolites appear to be important constituents of the tumor microenvironment. Finally, we discuss how bacterial dysbiosis interferes with breast cancer treatment through interfering with chemotherapeutic drug metabolism and availability.
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Affiliation(s)
- Edit Mikó
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
- Department of Microbiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
| | - Tünde Kovács
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
| | - Éva Sebő
- Kenézy Breast Center, Kenézy Gyula County Hospital, 4032 Debrecen, Hungary.
| | - Judit Tóth
- Kenézy Breast Center, Kenézy Gyula County Hospital, 4032 Debrecen, Hungary.
| | - Tamás Csonka
- Department of Pathology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
| | - Gyula Ujlaki
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
| | - Adrienn Sipos
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
| | - Judit Szabó
- Department of Microbiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
| | - Gábor Méhes
- Department of Pathology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
| | - Péter Bai
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
- MTA-DE Lendület Laboratory of Cellular Metabolism, 4032 Debrecen, Hungary.
- Research Center for Molecular Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
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Müller CA, Obermeier MM, Berg G. Bioprospecting plant-associated microbiomes. J Biotechnol 2016; 235:171-80. [DOI: 10.1016/j.jbiotec.2016.03.033] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Revised: 03/17/2016] [Accepted: 03/21/2016] [Indexed: 10/22/2022]
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