Microbiome Analysis Techniques and Discovery

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Technologies and Resources for Genetics".

Deadline for manuscript submissions: closed (25 March 2024) | Viewed by 25304

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Department of Physiology and Biophysics, Cornell University (Weill Cornell Medicine), New York, NY, USA
Interests: computational genomics in computational biomedicine; quantitative prediction; molecular biology
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Dear Colleagues,

Metagenomics sequencing has evolved in pace with developments in next-generation sequencing and bioinformatic analysis. The identification of microbes at the genus and species level is achieved from environmental samples. The applications are diverse, since microbes have many niches.

We would like to put emphasis on currently established microbiome sequencing and analysis techniques such as the shotgun sequencing of DNA or RNA, metataxonomics (16S/18S/Internal Transcribed Spacer sequencing), and meta-transcriptomics (mRNA sequencing). Besides, third-generation sequencing techniques with long-read approaches are also of novel interest.

For more than 200 years, the study of the microbiome was based on morphological features, growth, and the selection of some biochemical profiles. However, current genetic and genomic techniques and developments enable much more accurate findings.

The Human Microbiome Project (2007–2016) is a clear example of such potential. Databases also play an important role for new and reusable sequencing data, enabling more robust comparative genomic and integrative functional studies. The Earth Microbiome Project (EMP) is an ongoing global effort with PathoMap or MetaSUB initiatives, amongst others.

We invite submissions of original research and methodological papers in the form of articles, communications, and perspective and review papers.

Dr. Christopher E. Mason
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Microbiome
  • Metagenomics
  • Shotgun sequencing
  • Amplicon sequencing
  • 16S or 18S sequencing
  • ITS sequencing
  • Metataxonomics
  • Meta-transcriptomics
  • Long-read sequencing
  • NGS
  • Third-generation sequencing
  • Earth Microbiome Project
  • PathoMap
  • MetaSUB
  • Microbial genetics

Published Papers (6 papers)

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Research

22 pages, 4503 KiB  
Article
Amplicon-Based Microbiome Profiling: From Second- to Third-Generation Sequencing for Higher Taxonomic Resolution
by Elisabetta Notario, Grazia Visci, Bruno Fosso, Carmela Gissi, Nina Tanaskovic, Maria Rescigno, Marinella Marzano and Graziano Pesole
Genes 2023, 14(8), 1567; https://doi.org/10.3390/genes14081567 - 31 Jul 2023
Cited by 2 | Viewed by 2650
Abstract
The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the [...] Read more.
The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary. Full article
(This article belongs to the Special Issue Microbiome Analysis Techniques and Discovery)
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17 pages, 2326 KiB  
Article
Ozone Disinfection for Elimination of Bacteria and Degradation of SARS-CoV2 RNA for Medical Environments
by Craig Westover, Savlatjon Rahmatulloev, David Danko, Evan E. Afshin, Niamh B. O’Hara, Rachid Ounit, Daniela Bezdan and Christopher E. Mason
Genes 2023, 14(1), 85; https://doi.org/10.3390/genes14010085 - 28 Dec 2022
Cited by 4 | Viewed by 4304
Abstract
Pathogenic bacteria and viruses in medical environments can lead to treatment complications and hospital-acquired infections. Current disinfection protocols do not address hard-to-access areas or may be beyond line-of-sight treatment, such as with ultraviolet radiation. The COVID-19 pandemic further underscores the demand for reliable [...] Read more.
Pathogenic bacteria and viruses in medical environments can lead to treatment complications and hospital-acquired infections. Current disinfection protocols do not address hard-to-access areas or may be beyond line-of-sight treatment, such as with ultraviolet radiation. The COVID-19 pandemic further underscores the demand for reliable and effective disinfection methods to sterilize a wide array of surfaces and to keep up with the supply of personal protective equipment (PPE). We tested the efficacy of Sani Sport ozone devices to treat hospital equipment and surfaces for killing Escherichia coli, Enterococcus faecalis, Bacillus subtilis, and Deinococcus radiodurans by assessing Colony Forming Units (CFUs) after 30 min, 1 h, and 2 h of ozone treatment. Further gene expression analysis was conducted on live E. coli K12 immediately post treatment to understand the oxidative damage stress response transcriptome profile. Ozone treatment was also used to degrade synthetic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA as assessed by qPCR CT values. We observed significant and rapid killing of medically relevant and environmental bacteria across four surfaces (blankets, catheter, remotes, and syringes) within 30 min, and up to a 99% reduction in viable bacteria at the end of 2 h treatment cycles. RNA-seq analysis of E. coli K12 revealed 447 differentially expressed genes in response to ozone treatment and an enrichment for oxidative stress response and related pathways. RNA degradation of synthetic SARS-CoV-2 RNA was seen an hour into ozone treatment as compared to non-treated controls, and a non-replicative form of the virus was shown to have significant RNA degradation at 30 min. These results show the strong promise of ozone treatment of surfaces for reducing the risk of hospital-acquired infections and as a method for degradation of SARS-CoV-2 RNA. Full article
(This article belongs to the Special Issue Microbiome Analysis Techniques and Discovery)
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11 pages, 1818 KiB  
Article
Evaluation of Bacteria and Fungi DNA Abundance in Human Tissues
by Gabriela E. de Albuquerque, Bruno S. Moda, Marianna S. Serpa, Gabriela P. Branco, Alexandre Defelicibus, Isabella K. T. M. Takenaka, Maria G. de Amorim, Elizabeth C. Miola, Valquiria C. A. Martins, Katia L. Torres, Stephania M. Bezerra, Laura C. L. Claro, Adriane G. Pelosof, Claudia Z. Sztokfisz, Lais L. S. Abrantes, Felipe J. F. Coimbra, Luiz P. Kowalski, Fábio A. Alves, Stênio C. Zequi, Klas I. Udekwu, Israel T. Silva, Diana N. Nunes, Thais F. Bartelli and Emmanuel Dias-Netoadd Show full author list remove Hide full author list
Genes 2022, 13(2), 237; https://doi.org/10.3390/genes13020237 - 27 Jan 2022
Cited by 3 | Viewed by 3681
Abstract
Whereas targeted and shotgun sequencing approaches are both powerful in allowing the study of tissue-associated microbiota, the human: microorganism abundance ratios in tissues of interest will ultimately determine the most suitable sequencing approach. In addition, it is possible that the knowledge of the [...] Read more.
Whereas targeted and shotgun sequencing approaches are both powerful in allowing the study of tissue-associated microbiota, the human: microorganism abundance ratios in tissues of interest will ultimately determine the most suitable sequencing approach. In addition, it is possible that the knowledge of the relative abundance of bacteria and fungi during a treatment course or in pathological conditions can be relevant in many medical conditions. Here, we present a qPCR-targeted approach to determine the absolute and relative amounts of bacteria and fungi and demonstrate their relative DNA abundance in nine different human tissue types for a total of 87 samples. In these tissues, fungi genomes are more abundant in stool and skin samples but have much lower levels in other tissues. Bacteria genomes prevail in stool, skin, oral swabs, saliva, and gastric fluids. These findings were confirmed by shotgun sequencing for stool and gastric fluids. This approach may contribute to a more comprehensive view of the human microbiota in targeted studies for assessing the abundance levels of microorganisms during disease treatment/progression and to indicate the most informative methods for studying microbial composition (shotgun versus targeted sequencing) for various samples types. Full article
(This article belongs to the Special Issue Microbiome Analysis Techniques and Discovery)
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17 pages, 2007 KiB  
Article
Metagenomic Information Recovery from Human Stool Samples Is Influenced by Sequencing Depth and Profiling Method
by Tasha M. Santiago-Rodriguez, Aaron Garoutte, Emmase Adams, Waleed Nasser, Matthew C. Ross, Alex La Reau, Zachariah Henseler, Tonya Ward, Dan Knights, Joseph F. Petrosino and Emily B. Hollister
Genes 2020, 11(11), 1380; https://doi.org/10.3390/genes11111380 - 21 Nov 2020
Cited by 11 | Viewed by 4715
Abstract
Sequencing of the 16S rRNA gene (16S) has long been a go-to method for microbiome characterization due to its accessibility and lower cost compared to shotgun metagenomic sequencing (SMS). However, 16S sequencing rarely provides species-level resolution and cannot provide direct assessment of other [...] Read more.
Sequencing of the 16S rRNA gene (16S) has long been a go-to method for microbiome characterization due to its accessibility and lower cost compared to shotgun metagenomic sequencing (SMS). However, 16S sequencing rarely provides species-level resolution and cannot provide direct assessment of other taxa (e.g., viruses and fungi) or functional gene content. Shallow shotgun metagenomic sequencing (SSMS) has emerged as an approach to bridge the gap between 16S sequencing and deep metagenomic sequencing. SSMS is cost-competitive with 16S sequencing, while also providing species-level resolution and functional gene content insights. In the present study, we evaluated the effects of sequencing depth on marker gene-mapping- and alignment-based annotation of bacteria in healthy human stool samples. The number of identified taxa decreased with lower sequencing depths, particularly with the marker gene-mapping-based approach. Other annotations, including viruses and pathways, also showed a depth-dependent effect on feature recovery. These results refine the understanding of the suitability and shortcomings of SSMS, as well as annotation tools for metagenomic analyses in human stool samples. Results may also translate to other sample types and may open the opportunity to explore the effect of sequencing depth and annotation method. Full article
(This article belongs to the Special Issue Microbiome Analysis Techniques and Discovery)
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11 pages, 447 KiB  
Article
Assembling Reads Improves Taxonomic Classification of Species
by Quang Tran and Vinhthuy Phan
Genes 2020, 11(8), 946; https://doi.org/10.3390/genes11080946 - 17 Aug 2020
Cited by 12 | Viewed by 2920
Abstract
Most current approach to metagenomic classification employ short next generation sequencing (NGS) reads that are present in metagenomic samples to identify unique genomic regions. NGS reads, however, might not be long enough to differentiate similar genomes. This suggests a potential for using longer [...] Read more.
Most current approach to metagenomic classification employ short next generation sequencing (NGS) reads that are present in metagenomic samples to identify unique genomic regions. NGS reads, however, might not be long enough to differentiate similar genomes. This suggests a potential for using longer reads to improve classification performance. Presently, longer reads tend to have a higher rate of sequencing errors. Thus, given the pros and cons, it remains unclear which types of reads is better for metagenomic classification. We compared two taxonomic classification protocols: a traditional assembly-free protocol and a novel assembly-based protocol. The novel assembly-based protocol consists of assembling short-reads into longer reads, which will be subsequently classified by a traditional taxonomic classifier. We discovered that most classifiers made fewer predictions with longer reads and that they achieved higher classification performance on synthetic metagenomic data. Generally, we observed a significant increase in precision, while having similar recall rates. On real data, we observed similar characteristics that suggest that the classifiers might have similar performance of higher precision with similar recall with longer reads. We have shown a noticeable difference in performance between assembly-based and assembly-free taxonomic classification. This finding strongly suggests that classifying species in metagenomic environments can be achieved with higher overall performance simply by assembling short reads. Further, it also suggests that long-read technologies might be better for species classification. Full article
(This article belongs to the Special Issue Microbiome Analysis Techniques and Discovery)
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12 pages, 1120 KiB  
Article
The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community
by Maria A. Sierra, Qianhao Li, Smruti Pushalkar, Bidisha Paul, Tito A. Sandoval, Angela R. Kamer, Patricia Corby, Yuqi Guo, Ryan Richard Ruff, Alexander V. Alekseyenko, Xin Li and Deepak Saxena
Genes 2020, 11(8), 878; https://doi.org/10.3390/genes11080878 - 3 Aug 2020
Cited by 29 | Viewed by 5498
Abstract
There is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity [...] Read more.
There is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity comparisons analyzing the human oral microbiome. We compared the results of taxonomical classification by Greengenes, the Human Oral Microbiome Database (HOMD), National Center for Biotechnology Information (NCBI) 16S, SILVA, and the Ribosomal Database Project (RDP) using Quantitative Insights Into Microbial Ecology (QIIME) and the Divisive Amplicon Denoising Algorithm (DADA2). There were 15 phyla present in all of the analyses, four phyla exclusive to certain databases, and different numbers of genera were identified in each database. Common genera found in the oral microbiome, such as Veillonella, Rothia, and Prevotella, are annotated by all databases; however, less common genera, such as Bulleidia and Paludibacter, are only annotated by large databases, such as Greengenes. Our results indicate that using different reference databases in 16S rRNA amplicon data analysis could lead to different taxonomic compositions, especially at genus level. There are a variety of databases available, but there are no defined criteria for data curation and validation of annotations, which can affect the accuracy and reproducibility of results, making it difficult to compare data across studies. Full article
(This article belongs to the Special Issue Microbiome Analysis Techniques and Discovery)
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