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Farrall T, Brawner J, Dinsdale A, Kehoe M. A Review of Probe-Based Enrichment Methods to Inform Plant Virus Diagnostics. Int J Mol Sci 2024; 25:8348. [PMID: 39125919 PMCID: PMC11312432 DOI: 10.3390/ijms25158348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 07/20/2024] [Accepted: 07/28/2024] [Indexed: 08/12/2024] Open
Abstract
Modern diagnostic techniques based on DNA sequence similarity are currently the gold standard for the detection of existing and emerging pathogens. Whilst individual assays are inexpensive to use, assay development is costly and carries risks of not being sensitive or specific enough to capture an increasingly diverse range of targets. Sequencing can provide the entire nucleic acid content of a sample and may be used to identify all pathogens present in the sample when the depth of coverage is sufficient. Targeted enrichment techniques have been used to increase sequence coverage and improve the sensitivity of detection within virus samples, specifically, to capture sequences for a range of different viruses or increase the number of reads from low-titre virus infections. Vertebrate viruses have been well characterised using in-solution hybridisation capture to target diverse virus families. The use of probes for genotyping and strain identification has been limited in plants, and uncertainty around sensitivity is an impediment to the development of a large-scale virus panel to use within regulatory settings and diagnostic pipelines. This review aims to compare significant studies that have used targeted enrichment of viruses to identify approaches to probe design and potential for use in plant virus detection and characterisation.
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Affiliation(s)
- Thomas Farrall
- Plant Innovation Centre, Australian Government, Department of Agriculture, Fisheries and Forestry (DAFF), Canberra, ACT 2601, Australia; (T.F.); (A.D.)
- Forest Research Institute, School of Science, Technology and Engineering, University of the Sunshine Coast, Sippy Downs, QLD 4556, Australia
| | - Jeremy Brawner
- Forest Research Institute, School of Science, Technology and Engineering, University of the Sunshine Coast, Sippy Downs, QLD 4556, Australia
- Plant Pathology Department, University of Florida, Gainesville, FL 32611, USA
| | - Adrian Dinsdale
- Plant Innovation Centre, Australian Government, Department of Agriculture, Fisheries and Forestry (DAFF), Canberra, ACT 2601, Australia; (T.F.); (A.D.)
| | - Monica Kehoe
- Diagnostic Laboratory Services, Biosecurity and Sustainability, Department of Primary Industries and Regional Development (DPIRD), Perth, WA 6151, Australia
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Wattanasombat S, Tongjai S. Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline. F1000Res 2024; 13:556. [PMID: 38984017 PMCID: PMC11231628 DOI: 10.12688/f1000research.149577.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/14/2024] [Indexed: 07/11/2024] Open
Abstract
Background Determining the appropriate computational requirements and software performance is essential for efficient genomic surveillance. The lack of standardized benchmarking complicates software selection, especially with limited resources. Methods We developed a containerized benchmarking pipeline to evaluate seven long-read assemblers-Canu, GoldRush, MetaFlye, Strainline, HaploDMF, iGDA, and RVHaplo-for viral haplotype reconstruction, using both simulated and experimental Oxford Nanopore sequencing data of HIV-1 and other viruses. Benchmarking was conducted on three computational systems to assess each assembler's performance, utilizing QUAST and BLASTN for quality assessment. Results Our findings show that assembler choice significantly impacts assembly time, with CPU and memory usage having minimal effect. Assembler selection also influences the size of the contigs, with a minimum read length of 2,000 nucleotides required for quality assembly. A 4,000-nucleotide read length improves quality further. Canu was efficient among de novo assemblers but not suitable for multi-strain mixtures, while GoldRush produced only consensus assemblies. Strainline and MetaFlye were suitable for metagenomic sequencing data, with Strainline requiring high memory and MetaFlye operable on low-specification machines. Among reference-based assemblers, iGDA had high error rates, RVHaplo showed the best runtime and accuracy but became ineffective with similar sequences, and HaploDMF, utilizing machine learning, had fewer errors with a slightly longer runtime. Conclusions The HIV-64148 pipeline, containerized using Docker, facilitates easy deployment and offers flexibility to select from a range of assemblers to match computational systems or study requirements. This tool aids in genome assembly and provides valuable information on HIV-1 sequences, enhancing viral evolution monitoring and understanding.
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Affiliation(s)
- Sara Wattanasombat
- Department of Microbiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand
| | - Siripong Tongjai
- Department of Microbiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand
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Wu J, Singleton SS, Bhuiyan U, Krammer L, Mazumder R. Multi-omics approaches to studying gastrointestinal microbiome in the context of precision medicine and machine learning. Front Mol Biosci 2024; 10:1337373. [PMID: 38313584 PMCID: PMC10834744 DOI: 10.3389/fmolb.2023.1337373] [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: 11/15/2023] [Accepted: 12/27/2023] [Indexed: 02/06/2024] Open
Abstract
The human gastrointestinal (gut) microbiome plays a critical role in maintaining host health and has been increasingly recognized as an important factor in precision medicine. High-throughput sequencing technologies have revolutionized -omics data generation, facilitating the characterization of the human gut microbiome with exceptional resolution. The analysis of various -omics data, including metatranscriptomics, metagenomics, glycomics, and metabolomics, holds potential for personalized therapies by revealing information about functional genes, microbial composition, glycans, and metabolites. This multi-omics approach has not only provided insights into the role of the gut microbiome in various diseases but has also facilitated the identification of microbial biomarkers for diagnosis, prognosis, and treatment. Machine learning algorithms have emerged as powerful tools for extracting meaningful insights from complex datasets, and more recently have been applied to metagenomics data via efficiently identifying microbial signatures, predicting disease states, and determining potential therapeutic targets. Despite these rapid advancements, several challenges remain, such as key knowledge gaps, algorithm selection, and bioinformatics software parametrization. In this mini-review, our primary focus is metagenomics, while recognizing that other -omics can enhance our understanding of the functional diversity of organisms and how they interact with the host. We aim to explore the current intersection of multi-omics, precision medicine, and machine learning in advancing our understanding of the gut microbiome. A multidisciplinary approach holds promise for improving patient outcomes in the era of precision medicine, as we unravel the intricate interactions between the microbiome and human health.
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Affiliation(s)
- Jingyue Wu
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States
| | - Stephanie S. Singleton
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States
| | - Urnisha Bhuiyan
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States
| | - Lori Krammer
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States
- Milken Institute School of Public Health, The George Washington University, Washington, DC, United States
| | - Raja Mazumder
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States
- The McCormick Genomic and Proteomic Center, The George Washington University, Washington, DC, United States
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4
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Engelhard CA, Khani S, Derdak S, Bilban M, Kornfeld JW. Nanopore sequencing unveils the complexity of the cold-activated murine brown adipose tissue transcriptome. iScience 2023; 26:107190. [PMID: 37564700 PMCID: PMC10410515 DOI: 10.1016/j.isci.2023.107190] [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: 01/30/2023] [Revised: 04/28/2023] [Accepted: 06/16/2023] [Indexed: 08/12/2023] Open
Abstract
Alternative transcription increases transcriptome complexity by expression of multiple transcripts per gene. Annotation and quantification of transcripts using short-read sequencing is non-trivial. Long-read sequencing aims at overcoming these problems by sequencing full-length transcripts. Activation of brown adipose tissue (BAT) thermogenesis involves major transcriptomic remodeling and positively affects metabolism via increased energy expenditure. We benchmark Oxford Nanopore Technology (ONT) long-read sequencing protocols to Illumina short-read sequencing assessing alignment characteristics, gene and transcript detection and quantification, differential gene and transcript expression, transcriptome reannotation, and differential transcript usage (DTU). We find ONT sequencing is superior to Illumina for transcriptome reassembly, reducing the risk of false-positive events by unambiguously mapping reads to transcripts. We identified novel isoforms of genes undergoing DTU in cold-activated BAT including Cars2, Adtrp, Acsl5, Scp2, Aldoa, and Pde4d, validated by real-time PCR. The reannotated murine BAT transcriptome established here provides a framework for future investigations into the regulation of BAT.
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Affiliation(s)
- Christoph Andreas Engelhard
- Department for Biochemistry and Molecular Biology (BMB), University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
| | - Sajjad Khani
- Max Planck Institute for Metabolism Research, Gleueler Strasse 50, 50931 Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Sophia Derdak
- Core Facilities, Medical University of Vienna, Lazarettgasse 14, 1090 Vienna, Austria
| | - Martin Bilban
- Department of Laboratory Medicine & Core Facilities, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Jan-Wilhelm Kornfeld
- Department for Biochemistry and Molecular Biology (BMB), University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
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Yu Z, Li M, Peng W. Exploring biomarkers of premature ovarian insufficiency based on oxford nanopore transcriptional profile and machine learning. Sci Rep 2023; 13:11498. [PMID: 37460774 PMCID: PMC10352282 DOI: 10.1038/s41598-023-38754-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 07/14/2023] [Indexed: 07/20/2023] Open
Abstract
Premature ovarian insufficiency (POI) is a reproductive endocrine disorder characterized by infertility and perimenopausal syndrome, with a highly heterogeneous genetic etiology and its mechanism is not fully understood. Therefore, we utilized Oxford Nanopore Technology (ONT) for the first time to characterize the full-length transcript profile, and revealed biomarkers, pathway and molecular mechanisms for POI by bioinformatics analysis and machine learning. Ultimately, we identified 272 differentially expressed genes, 858 core genes, and 25 hub genes by analysis of differential expression, gene set enrichment, and protein-protein interactions. Seven candidate genes were identified based on the intersection features of the random forest and Boruta algorithm. qRT-PCR results indicated that COX5A, UQCRFS1, LCK, RPS2 and EIF5A exhibited consistent expression trends with sequencing data and have potential as biomarkers. Additionally, GSEA analysis revealed that the pathophysiology of POI is closely associated with inhibition of the PI3K-AKT pathway, oxidative phosphorylation and DNA damage repair, as well as activation of inflammatory and apoptotic pathways. Furthermore, we emphasize that downregulation of respiratory chain enzyme complex subunits and inhibition of oxidative phosphorylation pathways play crucial roles in the pathophysiology of POI. In conclusion, our utilization of long-read sequencing has refined the annotation information within the POI transcriptional profile. This valuable data provides novel insights for further exploration into molecular regulatory networks and potential biomarkers associated with POI.
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Affiliation(s)
- Zhaoyang Yu
- The First Affiliated Clinical College of Guangxi Medical University, Nanning, China
| | - Mujun Li
- Reproductive Medicine Research Center, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
| | - Weilong Peng
- School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, China.
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Esteller-Cucala P, Palmada-Flores M, Kuderna LFK, Fontsere C, Serres-Armero A, Dabad M, Torralvo M, Faella A, Ferrández-Peral L, Llovera L, Fornas O, Julià E, Ramírez E, González I, Hecht J, Lizano E, Juan D, Marquès-Bonet T. Y chromosome sequence and epigenomic reconstruction across human populations. Commun Biol 2023; 6:623. [PMID: 37296226 PMCID: PMC10256797 DOI: 10.1038/s42003-023-05004-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 05/31/2023] [Indexed: 06/12/2023] Open
Abstract
Recent advances in long-read sequencing technologies have allowed the generation and curation of more complete genome assemblies, enabling the analysis of traditionally neglected chromosomes, such as the human Y chromosome (chrY). Native DNA was sequenced on a MinION Oxford Nanopore Technologies sequencing device to generate genome assemblies for seven major chrY human haplogroups. We analyzed and compared the chrY enrichment of sequencing data obtained using two different selective sequencing approaches: adaptive sampling and flow cytometry chromosome sorting. We show that adaptive sampling can produce data to create assemblies comparable to chromosome sorting while being a less expensive and time-consuming technique. We also assessed haplogroup-specific structural variants, which would be otherwise difficult to study using short-read sequencing data only. Finally, we took advantage of this technology to detect and profile epigenetic modifications among the considered haplogroups. Altogether, we provide a framework to study complex genomic regions with a simple, fast, and affordable methodology that could be applied to larger population genomics datasets.
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Affiliation(s)
- Paula Esteller-Cucala
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain.
| | - Marc Palmada-Flores
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Lukas F K Kuderna
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Claudia Fontsere
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Aitor Serres-Armero
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Marc Dabad
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, Barcelona, Spain
| | - María Torralvo
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Armida Faella
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Luis Ferrández-Peral
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Laia Llovera
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Oscar Fornas
- Centre for Genomic Regulation (CRG), Barcelona Institute for Science and Technology (BIST), Doctor Aiguader 88, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Doctor Aiguader 88, Barcelona, Spain
| | - Eva Julià
- Centre for Genomic Regulation (CRG), Barcelona Institute for Science and Technology (BIST), Doctor Aiguader 88, Barcelona, Spain
| | - Erika Ramírez
- Centre for Genomic Regulation (CRG), Barcelona Institute for Science and Technology (BIST), Doctor Aiguader 88, Barcelona, Spain
| | - Irene González
- Centre for Genomic Regulation (CRG), Barcelona Institute for Science and Technology (BIST), Doctor Aiguader 88, Barcelona, Spain
| | - Jochen Hecht
- Centre for Genomic Regulation (CRG), Barcelona Institute for Science and Technology (BIST), Doctor Aiguader 88, Barcelona, Spain
| | - Esther Lizano
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, Cerdanyola del Vallès, Spain
| | - David Juan
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain
| | - Tomàs Marquès-Bonet
- Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Doctor Aiguader 88, Barcelona, Spain.
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, Barcelona, Spain.
- Universitat Pompeu Fabra (UPF), Doctor Aiguader 88, Barcelona, Spain.
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, Cerdanyola del Vallès, Spain.
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, Spain.
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Wongsurawat T, Jenjaroenpun P, Wanchai V, Nookaew I. Native RNA or cDNA Sequencing for Transcriptomic Analysis: A Case Study on Saccharomyces cerevisiae. Front Bioeng Biotechnol 2022; 10:842299. [PMID: 35497361 PMCID: PMC9039254 DOI: 10.3389/fbioe.2022.842299] [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: 12/23/2021] [Accepted: 03/01/2022] [Indexed: 11/13/2022] Open
Abstract
Direct sequencing of single molecules through nanopores allows for accurate quantification and full-length characterization of native RNA or complementary DNA (cDNA) without amplification. Both nanopore-based native RNA and cDNA approaches involve complex transcriptome procedures at a lower cost. However, there are several differences between the two approaches. In this study, we perform matched native RNA sequencing and cDNA sequencing to enable relevant comparisons and evaluation. Using Saccharomyces cerevisiae, a eukaryotic model organism widely used in industrial biotechnology, two different growing conditions are considered for comparison, including the poly-A messenger RNA isolated from yeast cells grown in minimum media under respirofermentative conditions supplemented with glucose (glucose growth conditions) and from cells that had shifted to ethanol as a carbon source (ethanol growth conditions). Library preparation for direct RNA sequencing is shorter than that for direct cDNA sequencing. The sequence characteristics of the two methods were different, such as sequence yields, quality score of reads, read length distribution, and mapped on reference ability of reads. However, differential gene expression analyses derived from the two approaches are comparable. The unique feature of direct RNA sequencing is RNA modification; we found that the RNA modification at the 5' end of a transcript was underestimated due to the 3' bias behavior of the direct RNA sequencing. Our comprehensive evaluation from this work could help researchers make informed choices when selecting an appropriate long-read sequencing method for understanding gene functions, pathways, and detailed functional characterization.
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Affiliation(s)
- Thidathip Wongsurawat
- Division of Bioinformatics and Data Management for Research, Research Group and Research Network Division, Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Piroon Jenjaroenpun
- Division of Bioinformatics and Data Management for Research, Research Group and Research Network Division, Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Visanu Wanchai
- Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Intawat Nookaew
- Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States
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Khezri A, Avershina E, Ahmad R. Hybrid Assembly Provides Improved Resolution of Plasmids, Antimicrobial Resistance Genes, and Virulence Factors in Escherichia coli and Klebsiella pneumoniae Clinical Isolates. Microorganisms 2021; 9:microorganisms9122560. [PMID: 34946161 PMCID: PMC8704702 DOI: 10.3390/microorganisms9122560] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 12/03/2021] [Accepted: 12/06/2021] [Indexed: 12/28/2022] Open
Abstract
Emerging new sequencing technologies have provided researchers with a unique opportunity to study factors related to microbial pathogenicity, such as antimicrobial resistance (AMR) genes and virulence factors. However, the use of whole-genome sequence (WGS) data requires good knowledge of the bioinformatics involved, as well as the necessary techniques. In this study, a total of nine Escherichia coli and Klebsiella pneumoniae isolates from Norwegian clinical samples were sequenced using both MinION and Illumina platforms. Three out of nine samples were sequenced directly from blood culture, and one sample was sequenced from a mixed-blood culture. For genome assembly, several long-read, (Canu, Flye, Unicycler, and Miniasm), short-read (ABySS, Unicycler and SPAdes) and hybrid assemblers (Unicycler, hybridSPAdes, and MaSurCa) were tested. Assembled genomes from the best-performing assemblers (according to quality checks using QUAST and BUSCO) were subjected to downstream analyses. Flye and Unicycler assemblers performed best for the assembly of long and short reads, respectively. For hybrid assembly, Unicycler was the top-performing assembler and produced more circularized and complete genome assemblies. Hybrid assembled genomes performed substantially better in downstream analyses to predict putative plasmids, AMR genes and β-lactamase gene variants, compared to MinION and Illumina assemblies. Thus, hybrid assembly has the potential to reveal factors related to microbial pathogenicity in clinical and mixed samples.
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Affiliation(s)
- Abdolrahman Khezri
- Department of Biotechnology, Inland Norway University of Applied Sciences, 2318 Hamar, Norway; (A.K.); (E.A.)
| | - Ekaterina Avershina
- Department of Biotechnology, Inland Norway University of Applied Sciences, 2318 Hamar, Norway; (A.K.); (E.A.)
| | - Rafi Ahmad
- Department of Biotechnology, Inland Norway University of Applied Sciences, 2318 Hamar, Norway; (A.K.); (E.A.)
- Faculty of Health Sciences, Institute of Clinical Medicine, UiT-The Arctic University of Norway, Hansine Hansens veg 18, 9019 Tromsø, Norway
- Correspondence:
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