Dataset Information

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing.

ABSTRACT: The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the immune system. Perturbation of the healthy gut microbiome has been suggested to play a role in the development of inflammatory diseases, including multiple sclerosis (MS). Environmental and genetic factors can influence the composition of the microbiome; therefore, identification of microbial communities linked with a disease phenotype has become the first step towards defining the microbiome's role in health and disease. Use of 16S rRNA metagenomic sequencing for profiling bacterial community has helped in advancing microbiome research. Despite its wide use, there is no uniform protocol for 16S rRNA-based taxonomic profiling analysis. Another limitation is the low resolution of taxonomic assignment due to technical difficulties such as smaller sequencing reads, as well as use of only forward (R1) reads in the final analysis due to low quality of reverse (R2) reads. There is need for a simplified method with high resolution to characterize bacterial diversity in a given biospecimen. Advancements in sequencing technology with the ability to sequence longer reads at high resolution have helped to overcome some of these challenges. Present sequencing technology combined with a publicly available metagenomic analysis pipeline such as R-based Divisive Amplicon Denoising Algorithm-2 (DADA2) has helped advance microbial profiling at high resolution, as DADA2 can assign sequence at the genus and species levels. Described here is a guide for performing bacterial profiling using two-step amplification of the V3-V4 region of the 16S rRNA gene, followed by analysis using freely available analysis tools (i.e., DADA2, Phyloseq, and METAGENassist). It is believed that this simple and complete workflow will serve as an excellent tool for researchers interested in performing microbiome profiling studies.

SUBMITTER: Shahi SK

PROVIDER: S-EPMC6945761 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Publications

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing.

Shahi Shailesh K SK Zarei Kasra K Guseva Natalya V NV Mangalam Ashutosh K AK

Journal of visualized experiments : JoVE 20191015 152

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the immune system. Perturbation of the healthy gut microbiome has been suggested to play a role in the development of inflammatory diseases, including multiple sclerosis (MS). Environmental and genetic factors can influence the composition of the microbiome; therefore, identification of microbial communities linked with a disease phenotype has becom ...[more]

PMID: 31680682

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Project description:This study aimed to evaluate the number of 16S rRNA genes in the complete genomes of the bacterial and archaeal species inhabiting the human mouth and to assess how the use of different primer pairs would affect the detection and classification of redundant amplicons and matching amplicons (MAs) from different taxa. A total of 518 oral-bacterial and 191 oral-archaeal complete genomes were downloaded from the NCBI database, and their complete 16S rRNA genes were extracted. The numbers of genes and variants per genome were calculated. Next, 39 primer pairs were used to search for matches in the genomes and obtain amplicons. For each primer, we calculated the number of gene amplicons, variants, genomes, and species detected and the percentage of coverage at the species level with no MAs (SC-NMA). The results showed that 94.09% of oral bacteria and 52.59% of oral archaea had more than one intragenomic 16S rRNA gene. From 1.29% to 46.70% of bacterial species and from 4.65% to 38.89% of archaea detected by the primers had MAs. The best primers were the following (SC-NMA; region; position for Escherichia coli [GenBank version no. J01859.1]): KP_F048-OP_R030 for bacteria (93.55%; V3 to V7; 342 to 1079), KP_F018-KP_R063 for archaea (89.63%; V3 to V9; undefined to 1506), and OP_F114-OP_R121 for both domains (92.52%; V3 to V9; 340 to 1405). In addition to 16S rRNA gene redundancy, the presence of MAs must be controlled to ensure an accurate interpretation of microbial diversity data. The SC-NMA is a more useful parameter than the conventional coverage percentage for selecting the best primer pairs. The pairs used the most in the oral microbiome literature were not among the best performers. IMPORTANCE Hundreds of publications have studied the oral microbiome through 16S rRNA gene sequencing. However, none have assessed the number of 16S rRNA genes in the genomes of oral microbes, or how the use of primer pairs targeting different regions affects the detection of MAs from different taxa. Here, we found that almost all oral bacteria and more than half of oral archaea have more than one intragenomic 16S rRNA gene. The performance of the primer pairs in not detecting MAs increases as the length of the amplicon augments. As none of those most employed in the oral literature were among the best performers, we selected a series of primers to detect bacteria and/or archaea based on their percentage of species detected without MAs. The intragenomic 16S rRNA gene redundancy and the presence of MAs between distinct taxa need to be considered to ensure an accurate interpretation of microbial diversity data.

Project description:Fermented fruits and vegetables play an important role in safeguarding food security world-wide. Recently, robust sequencing-based microbial community analysis platforms have improved microbial safety assessment. This study aimed to examine the composition of bacteria and evaluate the bacterial safety of fermented fruit products using high-throughput 16S-rRNA metagenomic analysis. The operational taxonomic unit-based taxonomic classification of DNA sequences revealed 53 bacterial genera. However, the amplicon sequencing variant (ASV)-based clustering revealed 43 classifiable bacterial genera. Taxonomic classifications revealed that the abundance of Sphingomonas, which was the predominant genus in the majority of tested samples, was more than 85-90% among the total identified bacterial community in most samples. Among these identified genera, 13 low abundance genera were potential opportunistic pathogens, including Acinetobacter, Bacillus, Staphylococcus, Clostridium, Klebsiella, Mycobacterium, Ochrobactrum, Chryseobacterium, Stenotrophomonas, and Streptococcus. Of these 13 genera, 13 major opportunistic pathogenic species were validated using polymerase chain reaction. The pathogens were not detected in the samples of different stages and the final products of fermentation, except in one sample from the first stage of fermentation in which S. aureus was detected. This finding was consistent with that of ASV-based taxonomic classification according to which S. aureus was detected only in the sample from the first stage of fermentation. However, S. aureus was not significantly correlated with the human disease pathways. These results indicated that fermentation is a reliable and safe process as pathogenic bacteria were not detected in the fermentation products. The hybrid method reported in this study can be used simultaneously to evaluate the bacterial diversity, their functional predictions and safety assessment of novel fermentation products. Additionally, this hybrid method does not involve the random detection of pathogens, which can markedly decrease the time of detection and food safety verification. Furthermore, this hybrid method can be used for the quality control of products and the identification of external contamination.

Dataset Information

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing.

Publications

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing.

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