Dataset Information

High throughput method of 16S rRNA gene sequencing library preparation for plant root microbial community profiling.

ABSTRACT: Microbiota are a major component of agroecosystems. Root microbiota, which inhabit the inside and surface of plant roots, play a significant role in plant growth and health. As next-generation sequencing technology allows the capture of microbial profiles without culturing the microbes, profiling of plant microbiota has become a staple tool in plant science and agriculture. Here, we have increased sample handling efficiency in a two-step PCR amplification protocol for 16S rRNA gene sequencing of plant root microbiota, improving DNA extraction using AMPure XP magnetic beads and PCR purification using exonuclease. These modifications reduce sample handling and capture microbial diversity comparable to that obtained by the manual method. We found a buffer with AMPure XP magnetic beads enabled efficient extraction of microbial DNA directly from plant roots. We also demonstrated that purification using exonuclease before the second PCR step enabled the capture of higher degrees of microbial diversity, thus allowing for the detection of minor bacteria compared with the purification using magnetic beads in this step. In addition, our method generated comparable microbiome profile data in plant roots and soils to that of using common commercially available DNA extraction kits, such as DNeasy PowerSoil Pro Kit and FastDNA SPIN Kit for Soil. Our method offers a simple and high-throughput option for maintaining the quality of plant root microbial community profiling.

SUBMITTER: Kumaishi K

PROVIDER: S-EPMC9652414 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High throughput method of 16S rRNA gene sequencing library preparation for plant root microbial community profiling.

Kumaishi Kie K Usui Erika E Suzuki Kenta K Kobori Shungo S Sato Takumi T Toda Yusuke Y Takanashi Hideki H Shinozaki Satoshi S Noda Munehiro M Takakura Akiko A Matsumoto Kayoko K Yamasaki Yuji Y Tsujimoto Hisashi H Iwata Hiroyoshi H Ichihashi Yasunori Y

Scientific reports 20221111 1

Microbiota are a major component of agroecosystems. Root microbiota, which inhabit the inside and surface of plant roots, play a significant role in plant growth and health. As next-generation sequencing technology allows the capture of microbial profiles without culturing the microbes, profiling of plant microbiota has become a staple tool in plant science and agriculture. Here, we have increased sample handling efficiency in a two-step PCR amplification protocol for 16S rRNA gene sequencing of ...[more]

PMID: 36369356

Similar Datasets

Project description:BackgroundAdvances in sequencing technologies and bioinformatics have made the analysis of microbial communities almost routine. Nonetheless, the need remains to improve on the techniques used for gathering such data, including increasing throughput while lowering cost and benchmarking the techniques so that potential sources of bias can be better characterized.MethodsWe present a triple-index amplicon sequencing strategy to sequence large numbers of samples at significantly lower c ost and in a shorter timeframe compared to existing methods. The design employs a two-stage PCR protocol, incorpo rating three barcodes to each sample, with the possibility to add a fourth-index. It also includes heterogeneity spacers to overcome low complexity issues faced when sequencing amplicons on Illumina platforms.ResultsThe library preparation method was extensively benchmarked through analysis of a mock community in order to assess biases introduced by sample indexing, number of PCR cycles, and template concentration. We further evaluated the method through re-sequencing of a standardized environmental sample. Finally, we evaluated our protocol on a set of fecal samples from a small cohort of healthy adults, demonstrating good performance in a realistic experimental setting. Between-sample variation was mainly related to batch effects, such as DNA extraction, while sample indexing was also a significant source of bias. PCR cycle number strongly influenced chimera formation and affected relative abundance estimates of species with high GC content. Libraries were sequenced using the Illumina HiSeq and MiSeq platforms to demonstrate that this protocol is highly scalable to sequence thousands of samples at a very low cost.ConclusionsHere, we provide the most comprehensive study of performance and bias inherent to a 16S rRNA gene amplicon sequencing method to date. Triple-indexing greatly reduces the number of long custom DNA oligos required for library preparation, while the inclusion of variable length heterogeneity spacers minimizes the need for PhiX spike-in. This design results in a significant cost reduction of highly multiplexed amplicon sequencing. The biases we characterize highlight the need for highly standardized protocols. Reassuringly, we find that the biological signal is a far stronger structuring factor than the various sources of bias.

Project description:Next-generation sequencing technologies have enabled many advances across biology, with microbial ecology benefiting primarily through expanded sample sizes. Although the cost of running sequencing instruments has decreased substantially over time, the price of library preparation methods has largely remained unchanged. In this study, we developed a low-cost miniaturized (5-µl volume) high-throughput (384-sample) amplicon library preparation method with the Echo 550 acoustic liquid handler. Our method reduces costs of library preparation to $1.42 per sample, a 58% reduction compared to existing automated methods and a 21-fold reduction from commercial kits, without compromising sequencing success or distorting the microbial community composition analysis. We further validated the optimized method by sampling five body sites from 46 Pacific chub mackerel fish caught across 16 sampling events over seven months from the Scripps Institution of Oceanography pier in La Jolla, CA. Fish microbiome samples were processed with the miniaturized 5-µl reaction volume with 0.2 µl of genomic DNA (gDNA) and the standard 25-µl reaction volume with 1 µl of gDNA. Between the two methods, alpha diversity was highly correlated (R 2 > 0.95), while distances of technical replicates were much lower than within-body-site variation (P < 0.0001), further validating the method. The cost savings of implementing the miniaturized library preparation (going from triplicate 25-µl reactions to triplicate 5-µl reactions) are large enough to cover a MiSeq sequencing run for 768 samples while preserving accurate microbiome measurements. IMPORTANCE Reduced costs of sequencing have tremendously impacted the field of microbial ecology, allowing scientists to design more studies with larger sample sizes that often exceed 10,000 samples. Library preparation costs have not kept pace with sequencing prices, although automated liquid handling robots provide a unique opportunity to bridge this gap while also decreasing human error. Here, we take advantage of an acoustic liquid handling robot to develop a high-throughput miniaturized library preparation method of a highly cited and broadly used 16S rRNA gene amplicon reaction. We evaluate the potential negative effects of reducing the PCR volume along with varying the amount of gDNA going into the reaction. Our optimized method reduces sample-processing costs while continuing to generate a high-quality microbiome readout that is indistinguishable from the original method.

Project description:Chicken gut microbiota has paramount roles in host performance, health and immunity. Understanding the topological difference in gut microbial community composition is crucial to provide knowledge on the functions of each members of microbiota to the physiological maintenance of the host. The gut microbiota profiling of the chicken was commonly performed previously using culture-dependent and early culture-independent methods which had limited coverage and accuracy. Advances in technology based on next-generation sequencing (NGS), offers unparalleled coverage and depth in determining microbial gut dynamics. Thus, the aim of this study was to investigate the ileal and caecal microbiota development as chicken aged, which is important for future effective gut modulation.Ileal and caecal contents of broiler chicken were extracted from 7, 14, 21 and 42-day old chicken. Genomic DNA was then extracted and amplified based on V3 hyper-variable region of 16S rRNA. Bioinformatics, ecological and statistical analyses such as Principal Coordinate Analysis (PCoA) was performed in mothur software and plotted using PRIMER 6. Additional analyses for predicted metagenomes were performed through PICRUSt and STAMP software package based on Greengenes databases.A distinctive difference in bacterial communities was observed between ilea and caeca as the chicken aged (P < 0.001). The microbial communities in the caeca were more diverse in comparison to the ilea communities. The potentially pathogenic bacteria such as Clostridium were elevated as the chicken aged and the population of beneficial microbe such as Lactobacillus was low at all intervals. On the other hand, based on predicted metagenomes analysed, clear distinction in functions and roles of gut microbiota such as gene pathways related to nutrient absorption (e.g. sugar and amino acid metabolism), and bacterial proliferation and colonization (e.g. bacterial motility proteins, two-component system and bacterial secretion system) were observed between ilea and caeca, respectively (P < 0.05).The caeca microbial communities were more diverse in comparison to ilea. The main functional differences between the two sites were found to be related to nutrient absorption and bacterial colonization. Based on the composition of the microbial community, future gut modulation with beneficial bacteria such as probiotics may benefit the host.

Project description:Proper preservation of stool samples to minimize microbial community shifts and inactivate infectious agents is important for self-collected specimens requiring shipment to laboratories when cold chain transport is not feasible. In this study, we evaluated the performance of six preservation solutions (Norgen, OMNI, RNAlater, CURNA, HEMA, and Shield) for these aspects. Following storage of human stool samples with these preservatives at room temperature for 7 days, three hypervariable regions of the bacterial 16S rRNA gene (V1-V2, V3-V4, and V4) were amplicon sequenced. We found that samples collected in two preservatives, Norgen and OMNI, showed the least shift in community composition relative to -80°C standards compared with other storage conditions, and both efficiently inhibited the growth of aerobic and anaerobic bacteria. RNAlater did not prevent bacterial activity and exhibited relatively larger community shift. Although the effect of preservation solution was small compared to intersubject variation, notable changes in microbiota composition were observed, which could create biases in downstream data analysis. When community profiles inferred from different 16S rRNA gene hypervariable regions were compared, we found differential sensitivity of primer sets in identifying overall microbial community and certain bacterial taxa. For example, reads generated by the V4 primer pair showed a higher alpha diversity of the gut microbial community. The degenerate 27f-YM primer failed to detect the majority of Bifidobacteriales. Our data indicate that choice of preservation solution and 16S rRNA gene primer pair are critical determinants affecting gut microbiota profiling. IMPORTANCE Large-scale human microbiota studies require specimens collected from multiple sites and/or time points to maximize detection of the small effects in microbe-host interactions. However, batch biases caused by experimental protocols, such as sample collection, massively parallel sequencing, and bioinformatics analyses, remain critical and should be minimized. This work evaluated the effects of preservation solutions and bacterial 16S rRNA gene primer pairs in revealing human gut microbiota composition. Since notable changes in detecting bacterial composition and abundance were observed among choice of preservatives and primer pairs, a consistent methodology is essential in minimizing their effects to facilitate comparisons between data sets.

Project description:At any given time, only a subset of microbial community members are active in their environment. The others are in a state of dormancy, with strongly reduced metabolic rates. It is of interest to distinguish active and inactive microbial cells and taxa to understand their functional contributions to ecosystem processes and to understand shifts in microbial activity in response to change. Of the methods used to assess microbial activity-dormancy dynamics, 16S rRNA/rRNA gene amplicons (16S ratios) and active cell staining with 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) are two of the most common, yet each method has limitations. Given that in situ activity-dormancy dynamics are proxied only by laboratory methods, further study is needed to assess the level of agreement and potential complementarity of these methods. We conducted two experiments investigating microbial activity in plant-associated soils. First, we treated corn field soil with phytohormones to simulate plant soil stress signaling, and second, we used rhizosphere soil from common bean plants exposed to drought or nutrient enrichment. Overall, the 16S ratio and CTC methods exhibited similar patterns of relative activity across treatments when treatment effects were large, and the instances in which they differed could be attributed to changes in community size (e.g., cell death or growth). Therefore, regardless of the method used to assess activity, we recommend quantifying community size to inform ecological interpretation. Our results suggest that the 16S ratio and CTC methods report comparable patterns of activity that can be applied to observe ecological dynamics over time, space, or experimental treatment. IMPORTANCE Although the majority of microorganisms in natural ecosystems are dormant, relatively little is known about the dynamics of the active and dormant microbial pools through both space and time. The limited knowledge of microbial activity-dormancy dynamics is in part due to uncertainty in the methods currently used to quantify active taxa. Here, we directly compared two of the most common methods (16S ratios and active cell staining) for estimating microbial activity in plant-associated soil and found that they were largely in agreement in the overarching patterns. Our results suggest that 16S ratios and active cell staining provide complementary information for measuring and interpreting microbial activity-dormancy dynamics in soils. They also support the idea that 16S rRNA/rRNA gene ratios have comparative value and offer a high-throughput, sequencing-based option for understanding relative changes in microbiome activity, as long as this method is coupled with quantification of community size.

Dataset Information

High throughput method of 16S rRNA gene sequencing library preparation for plant root microbial community profiling.

Publications

High throughput method of 16S rRNA gene sequencing library preparation for plant root microbial community profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets