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Cui J, Hu A, Xiong X, Wang Q, Zhu C, Chen Z, Lu Y, Xia X, Chen H, Liu G. Optimization of PCA Error Correction Conditions to Improve Efficiency of Virus Genome De Novo Synthesis. Int J Mol Sci 2024; 25:11514. [PMID: 39519066 PMCID: PMC11547124 DOI: 10.3390/ijms252111514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Revised: 10/18/2024] [Accepted: 10/25/2024] [Indexed: 11/16/2024] Open
Abstract
In recent years, there have been frequent global outbreaks of viral epidemics such as Zika, COVID-19, and monkeypox, which have had a huge impact on human health and society and have also spurred innovation in virus engineering technology. The rise of synthetic virus genome technology has provided researchers with a new platform to accelerate vaccine and drug development. Although DNA synthesis technology has made significant progress, the current virus genome synthesis technology still requires the assembly of short oligonucleotides of around 60 bp into kb-level lengths when constructing long segments, a process in which the commonly used polymerase chain reaction assembly (PCA) technology has high error rates and is cumbersome to operate. This study optimized the error correction conditions after PCA assembly, increasing the accuracy of synthesizing 1 kb DNA fragments from 4.2 ± 2.1% before error correction to 31.3 ± 3.1% after two rounds of correction, an improvement of over 6 times. This study provides a more efficient operational process for synthesizing virus genomes from scratch, indicating greater potential for virus engineering in epidemic prevention and control and the field of biomedicine.
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Affiliation(s)
- Jiazhen Cui
- Academy of Military Medical Sciences, Beijing 100850, China
| | - Ao Hu
- Academy of Military Medical Sciences, Beijing 100850, China
- Institutes of Physical Science and Information Technology, Anhui University, Hefei 230000, China
| | - Xianghua Xiong
- Academy of Military Medical Sciences, Beijing 100850, China
| | - Qingyang Wang
- Academy of Military Medical Sciences, Beijing 100850, China
| | - Chen Zhu
- Academy of Military Medical Sciences, Beijing 100850, China
| | - Zhili Chen
- Academy of Military Medical Sciences, Beijing 100850, China
| | - Yuanyuan Lu
- Academy of Military Medical Sciences, Beijing 100850, China
- Institutes of Physical Science and Information Technology, Anhui University, Hefei 230000, China
| | - Xianzhu Xia
- Academy of Military Medical Sciences, Beijing 100850, China
| | - Huipeng Chen
- Academy of Military Medical Sciences, Beijing 100850, China
| | - Gang Liu
- Academy of Military Medical Sciences, Beijing 100850, China
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Fulghum B, Tanker SH, White RA. DeGenPrime provides robust primer design and optimization unlocking the biosphere. BIOINFORMATICS ADVANCES 2024; 4:vbae044. [PMID: 38590916 PMCID: PMC11001487 DOI: 10.1093/bioadv/vbae044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Revised: 02/19/2024] [Accepted: 03/12/2024] [Indexed: 04/10/2024]
Abstract
Motivation Polymerase chain reaction (PCR) is the world's most important molecular diagnostic with applications ranging from medicine to ecology. PCR can fail because of poor primer design. The nearest-neighbor thermodynamic properties, picking conserved regions, and filtration via penalty of oligonucleotides form the basis for good primer design. Results DeGenPrime is a console-based high-quality PCR primer design tool that can utilize MSA formats and degenerate bases expanding the target range for a single primer set. Our software utilizes thermodynamic properties, filtration metrics, penalty scoring, and conserved region finding of any proposed primer. It has degeneracy, repeated k-mers, relative GC content, and temperature range filters. Minimal penalty scoring is included according to secondary structure self-dimerization metrics, GC clamping, tri- and tetra-loop hairpins, and internal repetition. We compared PrimerDesign-M, DegePrime, ConsensusPrimer, and DeGenPrime on acceptable primer yield. PrimerDesign-M, DegePrime, and ConsensusPrimer provided 0%, 11%, and 17% yield, respectively, for the alternative iron nitrogenase (anfD) gene target. DeGenPrime successfully identified quality primers within the conserved regions of the T4-like phage major capsid protein (g23), conserved regions of molybdenum-based nitrogenase (nif), and its alternatives vanadium (vnf) and iron (anf) nitrogenase. DeGenPrime provides a universal and scalable primer design tool for the entire tree of life. Availability and implementation DeGenPrime is written in C++ and distributed under a BSD-3-Clause license. The source code for DeGenPrime is freely available on www.github.com/raw-lab/degenprime.
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Affiliation(s)
- Bryan Fulghum
- Department of Bioinformatics and Genomics, North Carolina Research Campus (NCRC), The University of North Carolina at Charlotte, Kannapolis, NC 28081, United States
- Department of Bioinformatics and Genomics, Computational Intelligence to Predict Health and Environmental Risks (CIPHER) Research Center, The University of North Carolina at Charlotte, Charlotte, NC 28223, United States
| | - Sophie H Tanker
- Department of Bioinformatics and Genomics, North Carolina Research Campus (NCRC), The University of North Carolina at Charlotte, Kannapolis, NC 28081, United States
- Department of Bioinformatics and Genomics, Computational Intelligence to Predict Health and Environmental Risks (CIPHER) Research Center, The University of North Carolina at Charlotte, Charlotte, NC 28223, United States
| | - Richard Allen White
- Department of Bioinformatics and Genomics, North Carolina Research Campus (NCRC), The University of North Carolina at Charlotte, Kannapolis, NC 28081, United States
- Department of Bioinformatics and Genomics, Computational Intelligence to Predict Health and Environmental Risks (CIPHER) Research Center, The University of North Carolina at Charlotte, Charlotte, NC 28223, United States
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Figueroa III JL, Dhungel E, Bellanger M, Brouwer CR, White III RA. MetaCerberus: distributed highly parallelized HMM-based processing for robust functional annotation across the tree of life. Bioinformatics 2024; 40:btae119. [PMID: 38426351 PMCID: PMC10955254 DOI: 10.1093/bioinformatics/btae119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 01/22/2024] [Accepted: 02/27/2024] [Indexed: 03/02/2024] Open
Abstract
MOTIVATION MetaCerberus is a massively parallel, fast, low memory, scalable annotation tool for inference gene function across genomes to metacommunities. MetaCerberus provides an elusive HMM/HMMER-based tool at a rapid scale with low memory. It offers scalable gene elucidation to major public databases, including KEGG (KO), COGs, CAZy, FOAM, and specific databases for viruses, including VOGs and PHROGs, from single genomes to metacommunities. RESULTS MetaCerberus is 1.3× as fast on a single node than eggNOG-mapper v2 on 5× less memory using an exclusively HMM/HMMER mode. In a direct comparison, MetaCerberus provides better annotation of viruses, phages, and archaeal viruses than DRAM, Prokka, or InterProScan. MetaCerberus annotates more KOs across domains when compared to DRAM, with a 186× smaller database, and with 63× less memory. MetaCerberus is fully integrated for automatic analysis of statistics and pathways using differential statistic tools (i.e. DESeq2 and edgeR), pathway enrichment (GAGE R), and pathview R. MetaCerberus provides a novel tool for unlocking the biosphere across the tree of life at scale. AVAILABILITY AND IMPLEMENTATION MetaCerberus is written in Python and distributed under a BSD-3 license. The source code of MetaCerberus is freely available at https://github.com/raw-lab/metacerberus compatible with Python 3 and works on both Mac OS X and Linux. MetaCerberus can also be easily installed using bioconda: mamba create -n metacerberus -c bioconda -c conda-forge metacerberus.
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Affiliation(s)
- Jose L Figueroa III
- North Carolina Research Campus (NCRC), Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Kannapolis, NC 28081, United States
- Computational Intelligence to Predict Health and Environmental Risks (CIPHER) Research Center, Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, United States
| | - Eliza Dhungel
- North Carolina Research Campus (NCRC), Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Kannapolis, NC 28081, United States
| | - Madeline Bellanger
- North Carolina Research Campus (NCRC), Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Kannapolis, NC 28081, United States
- Computational Intelligence to Predict Health and Environmental Risks (CIPHER) Research Center, Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, United States
| | - Cory R Brouwer
- North Carolina Research Campus (NCRC), Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Kannapolis, NC 28081, United States
| | - Richard Allen White III
- North Carolina Research Campus (NCRC), Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Kannapolis, NC 28081, United States
- Computational Intelligence to Predict Health and Environmental Risks (CIPHER) Research Center, Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, United States
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Bellanger M, Visscher P, White RA. Viral enumeration using cost-effective wet-mount epifluorescence microscopy for aquatic ecosystems and modern microbialites. Appl Environ Microbiol 2023; 89:e0174423. [PMID: 38014959 PMCID: PMC10734538 DOI: 10.1128/aem.01744-23] [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: 10/03/2023] [Accepted: 10/12/2023] [Indexed: 11/29/2023] Open
Abstract
IMPORTANCE Low-cost and robust viral enumeration is a critical first step toward understanding the global virome. Our method is a deep drive integration providing a window into viral dark matter within aquatic ecosystems. We enumerated the viruses within Green Lake and Great Salt Lake microbialites, EPS, and water column. The entire weight of all the viruses in Green Lake and Great Salt Lake are ~598 g and ~2.2 kg, respectively.
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Affiliation(s)
- Madeline Bellanger
- Department of Bioinformatics and Genomics, North Carolina Research Campus, The University of North Carolina at Charlotte, Kannapolis, North Carolina, USA
- Computational Intelligence to Predict Health and Environmental Risks (CIPHER), The University of North Carolina at Charlotte, Charlotte, North Carolina, USA
| | - Pieter Visscher
- Department of Marine Sciences and Geoscience, University of Connecticut, Storrs, Connecticut, USA
| | - Richard Allen White
- Department of Bioinformatics and Genomics, North Carolina Research Campus, The University of North Carolina at Charlotte, Kannapolis, North Carolina, USA
- Computational Intelligence to Predict Health and Environmental Risks (CIPHER), The University of North Carolina at Charlotte, Charlotte, North Carolina, USA
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Abstract
Two decades of metagenomic analyses have revealed that in many environments, small (∼5 kb), single-stranded DNA phages of the family Microviridae dominate the virome. Although the emblematic microvirus phiX174 is ubiquitous in the laboratory, most other microviruses, particularly those of the gokushovirus and amoyvirus lineages, have proven to be much more elusive. This puzzling lack of representative isolates has hindered insights into microviral biology. Furthermore, the idiosyncratic size and nature of their genomes have resulted in considerable misjudgments of their actual abundance in nature. Fortunately, recent successes in microvirus isolation and improved metagenomic methodologies can now provide us with more accurate appraisals of their abundance, their hosts, and their interactions. The emerging picture is that phiX174 and its relatives are rather rare and atypical microviruses, and that a tremendous diversity of other microviruses is ready for exploration.
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Affiliation(s)
- Paul C Kirchberger
- Department of Molecular Biosciences, University of Texas at Austin, Austin, Texas, USA
- Department of Microbiology and Molecular Genetics, Oklahoma State University, Stillwater, Oklahoma, USA;
| | - Howard Ochman
- Department of Molecular Biosciences, University of Texas at Austin, Austin, Texas, USA
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Jin Y, Li W, Zhang H, Ba X, Li Z, Zhou J. The Post-Antibiotic Era: A New Dawn for Bacteriophages. BIOLOGY 2023; 12:biology12050681. [PMID: 37237494 DOI: 10.3390/biology12050681] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 04/19/2023] [Accepted: 04/24/2023] [Indexed: 05/28/2023]
Abstract
Phages are the most biologically diverse entities in the biosphere, infecting specific bacteria. Lytic phages quickly kill bacteria, while lysogenic phages integrate their genomes into bacteria and reproduce within the bacteria, participating in the evolution of natural populations. Thus, lytic phages are used to treat bacterial infections. However, due to the huge virus invasion, bacteria have also evolved a special immune mechanism (CRISPR-Cas systems, discovered in 1987). Therefore, it is necessary to develop phage cocktails and synthetic biology methods to infect bacteria, especially against multidrug-resistant bacteria infections, which are a major global threat. This review outlines the discovery and classification of phages and the associated achievements in the past century. The main applications of phages, including synthetic biology and PT, are also discussed, in addition to the effects of PT on immunity, intestinal microbes, and potential safety concerns. In the future, combining bioinformatics, synthetic biology, and classic phage research will be the way to deepen our understanding of phages. Overall, whether phages are an important element of the ecosystem or a carrier that mediates synthetic biology, they will greatly promote the progress of human society.
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Affiliation(s)
- Youshun Jin
- State Key Laboratory for Animal Disease Control and Prevention, College of Veterinary Medicine, Lanzhou University, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou 730000, China
| | - Wei Li
- College of Agriculture, Ningxia University, Yinchuan 750021, China
| | - Huaiyu Zhang
- Animal Pathology Laboratory, College of Veterinary Medicine, Northwest A&F University, Xianyang 712100, China
| | - Xuli Ba
- State Key Laboratory for Animal Disease Control and Prevention, College of Veterinary Medicine, Lanzhou University, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou 730000, China
| | - Zhaocai Li
- State Key Laboratory of Veterinary Etiological Biology, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou 730046, China
| | - Jizhang Zhou
- State Key Laboratory for Animal Disease Control and Prevention, College of Veterinary Medicine, Lanzhou University, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou 730000, China
- State Key Laboratory of Veterinary Etiological Biology, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou 730046, China
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Abstract
EMBL-EBI The European Bioinformatics Institute; E. coli Escherichia coli; E. faecalis Enterobacter faecalis; B. fragilis Bacteroides fragilis; B. vulgatus Bacteroides vulgatus; SaPIs Staphylococcus aureus pathogenicity islands; ARGs Antibiotic resistance genes; STEC Shiga toxigenic E. coli; Stx Shiga toxin; BLAST Basic Local Alignment Search Tool; TSST-1 Toxic shock toxin 1; RBPs Receptor-binding proteins; LPS lipopolysaccharide; OMVs Outer membrane vesicles; PT Phosphorothioate; BREX Bacteriophage exclusion; OCR Overcome classical restriction; Pgl Phage growth limitation; DISARM Defense island system associated with restrictionmodification; R-M system Restriction-modification system; BREX system Bacteriophage exclusion system; CRISPR Clustered regularly interspaced short palindromic repeats; Cas CRISPR-associated; PAMs Prospacer adjacent motifs; crRNA CRISPR RNA; SIE; OMPs; Superinfection exclusion; Outer membrane proteins; Abi Abortive infection; TA Toxin-antitoxin; TLR Toll-like receptor; APCs Antigen-presenting cells; DSS Dextran sulfate sodium; IELs Intraepithelial lymphocytes; FMT Fecal microbiota transfer; IFN-γ Interferon-gamma; IBD Inflammatory bowel disease; AgNPs Silver nanoparticles; MDSC Myeloid-derived suppressor cell; CRC Colorectal cancer; VLPs Virus-like particles; TMP Tape measure protein; PSMB4 Proteasome subunit beta type-4; ALD Alcohol-related liver disease; GVHD Graft-versus-host disease; ROS Reactive oxygen species; RA Rheumatoid arthritis; CCP Cyclic citrullinated protein; AMGs Accessory metabolic genes; T1DM Type 1 diabetes mellitus; T2DM Type 2 diabetes mellitus; SCFAs Short-chain fatty acids; GLP-1 Glucagon-like peptide-1; A. baumannii Acinetobacter baumannii; CpG Deoxycytidylinate-phosphodeoxyguanosine; PEG Polyethylene glycol; MetS Metabolic syndrome; OprM Outer membrane porin M.
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Affiliation(s)
- Han Shuwen
- Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China,Department of Medical Oncology, Huzhou Central Hospital, Huzhou, China
| | - Ding Kefeng
- Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China,Department of Colorectal Surgery and Oncology, Cancer Center Zhejiang University, Hangzhou, China,CONTACT Ding Kefeng Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Building 6 room 2018, Hangzhou, Zhejiang310009, China
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Abstract
Microfluidics has enabled a new era of cellular and molecular assays due to the small length scales, parallelization, and the modularity of various analysis and actuation functions. Droplet microfluidics, in particular, has been instrumental in providing new tools for biology with its ability to quickly and reproducibly generate drops that act as individual reactors. A notable beneficiary of this technology has been single-cell RNA sequencing, which has revealed new heterogeneities and interactions for the fundamental unit of life. However, viruses far surpass the diversity of cellular life, affect the dynamics of all ecosystems, and are a chronic source of global health crises. Despite their impact on the world, high-throughput and high-resolution viral profiling has been difficult, with conventional methods being limited to population-level averaging, large sample volumes, and few cultivable hosts. Consequently, most viruses have not been identified and studied. Droplet microfluidics holds the potential to address many of these limitations and offers new levels of sensitivity and throughput for virology. This Feature highlights recent efforts that have applied droplet microfluidics to the detection and study of viruses, including for diagnostics, virus-host interactions, and cell-independent virus assays. In combination with traditional virology methods, droplet microfluidics should prove a potent tool toward achieving a better understanding of the most abundant biological species on Earth.
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Affiliation(s)
- Wenyang Jing
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Hee-Sun Han
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, Illinois 61801, United States
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