Amplicon-based Sequencing Data Research Articles

Distinct relationships between fluorescence in situ hybridization and 16S rRNA gene- and amplicon-based sequencing data of bacterioplankton lineages

Catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) and amplicon sequencing of the total (16S rRNA gene) and potentially active (16S rRNA transcripts), community are the major state of the art approaches for assessing the composition of bacterial communities in marine pelagic and other ecosystems. However, CARD-FISH and amplicon sequencing methods have not yet been directly compared to assess the composition of bacterioplankton communities. Therefore, these approaches were used to study the composition of bacterial communities in two North Sea seawater mesocosm experiments supplemented with diatom-derived organic matter (OM). All approaches revealed Proteobacteria and Bacteroidetes as major components of the bacterioplankton communities. The Roseobacter group and its RCA cluster, as well as Bacteroidetes and Gammaproteobacteria, responded most strongly to OM addition, whereas the SAR11 clade responded in only one of the two mesocosms. A correlation analysis showed that CARD-FISH and amplicon sequencing data of the SAR11 clade and the Roseobacter group, together with its RCA cluster, were highly significantly correlated, whereas Bacteroidetes did not yield any significant correlation and Gammaproteobacteria was only correlated with the potentially active fraction. However, subgroups of these phylogenetic groups, the SAR92 clade, the genera Pseudoalteromonas and Polaribacter, exhibited significant correlations in one of the two mesocosms. Correlations of CARD-FISH with amplicon sequencing data from the total and potentially active fractions of these lineages exhibited distinct differences. The study showed that CARD-FISH and amplicon sequencing data of distinct bacterioplankton groups and especially the phylogenetic lineages at a higher taxonomic level were correlated but reflected different aspects of their growth dynamics.

Dynamics and Biodiversity of Bacterial and Yeast Communities during Fermentation of Cocoa Beans.

Forastero hybrid cocoa bean fermentations have been carried out in a box (B) and in a heap (H), with or without the inoculation of Saccharomyces cerevisiae and Torulaspora delbrueckii as starter cultures. The bacteria, yeasts, and microbial metabolites (volatile and nonvolatile organic compounds) were monitored during fermentation to assess the connection between microbiota and the release of metabolites during this process. The presence of starter cultures was detected, by means of culture-dependent analysis, during the first 2 days of both fermentations. However, no statistical difference was observed in any of the physicochemical or microbiological analyses. Plate counts revealed the dominance of yeasts at the beginning of both fermentations, and these were followed by acetic acid bacteria (AAB) and lactic acid bacteria (LAB). Hanseniaspora opuntiae, S. cerevisiae, Pichia pijperi, Acetobacter pasteurianus, and Lactobacillus fermentum were the most abundant operational taxonomic units (OTUs) during both fermentation processes (B and H), although different relative abundances were observed. Only the diversity of the fungal species indicated a higher level of complexity in the B fermentations than in the H fermentations (P < 0.05), as well as a statistically significant difference between the initially inoculated starter cultures (P < 0.01). However, the microbial metabolite analysis indicated different distributions of the volatile and nonvolatile compounds between the two procedures, that is, B and H (P < 0.05), rather than between the inoculated and noninoculated fermentations. The box fermentations showed faster carbohydrate metabolism and greater production of organic acid compounds, which boosted the formation of alcohols and esters, than did the heap fermentations. Overall, the microbial dynamics and associations between the bacteria, yeasts, and metabolites were found to depend on the type of fermentation.IMPORTANCE In spite of the limited effectiveness of the considered inoculated starter strains, this study provides new information on the microbial development of box and heap cocoa fermentations, under inoculated and noninoculated conditions, as we coupled yeast/bacterial amplicon-based sequencing data with microbial metabolite detection. The information so far available suggests that microbial communities have played an important role in the evolution of aroma compounds. Understanding the pathways that microorganisms follow during the formation of aromas could be used to improve the fermentation processes and to enhance chocolate quality.

Nimbus: a design-driven analyses suite for amplicon-based NGS data.

MotivationPCR-based DNA enrichment followed by massively parallel sequencing is a straightforward and cost effective method to sequence genes up to high depth. The full potential of amplicon-based sequencing assays is currently not achieved as analysis methods do not take into account the source amplicons of the detected variants. Tracking the source amplicons has the potential to identify systematic biases, enhance variant calling and improve the designs of future assays.ResultsWe present Nimbus, a software suite for the analysis of amplicon-based sequencing data. Nimbus includes tools for data pre-processing, alignment, single nucleotide polymorphism (SNP), insertion and deletion calling, quality control and visualization. Nimbus can detect SNPs in its alignment seeds and reduces alignment issues by the usage of decoy amplicons. Tracking the amplicons throughout analysis allows easy and fast design optimization by amplicon performance comparison. It enables detection of probable false positive variants present in a single amplicon from real variants present in multiple amplicons and provides multiple sample visualization. Nimbus was tested using HaloPlex Exome datasets and outperforms other callers for low-frequency variants. The variants called by Nimbus were highly concordant between twin samples and SNP-arrays. The Nimbus suite provides an end-to-end solution for variant calling, design optimization and visualization of amplicon-derived next-generation sequencing datasets.Availability and implementation https://github.com/erasmus-center-for-biomics/Nimbus.Supplementary information Supplementary data are available at Bioinformatics online.

Using Exome and Amplicon-Based Sequencing Data for High-Resolution HLA Typing with ATHLATES.

ATHLATES (accurate typing of human leukocyte antigen through exome sequencing) was originally developed to analyze whole-exome sequencing (exome-seq) data from the Illumina platform and to predict the HLA genotype at 2-field or higher resolution. HLA locus-specific reads are first collected by stringent read mapping to the IMGT/HLA database. ATHLATES then performs read assembly, candidate allele identification, and genotype inference. Here, we describe the protocol of using ATHLATES for the above purpose and expand the application to analyze targeted sequencing data using amplicons of full HLA genes.

Assessing Copy Number Alterations in Targeted, Amplicon-Based Next-Generation Sequencing Data

Changes in gene copy number are important in the setting of precision medicine. Recent studies have established that copy number alterations (CNAs) can be detected in sequencing libraries prepared by hybridization-capture, but there has been comparatively little attention given to CNA assessment in amplicon-based libraries prepared by PCR. In this study, we developed an algorithm for detecting CNAs in amplicon-based sequencing data. CNAs determined from the algorithm mirrored those from a hybridization-capture library. In addition, analysis of 14 pairs of matched normal and breast carcinoma tissues revealed that sequence data pooled from normal samples could be substituted for a matched normal tissue without affecting the detection of clinically relevant CNAs (>|2| copies). Comparison of CNAs identified by array comparative genomic hybridization and amplicon-based libraries across 10 breast carcinoma samples showed an excellent correlation. The CNA algorithm also compared favorably with fluorescence in situ hybridization, with agreement in 33 of 38 assessments across four different genes. Factors that influenced the detection of CNAs included the number of amplicons per gene, the average read depth, and, most important, the proportion of tumor within the sample. Our results show that CNAs can be identified in amplicon-based targeted sequencing data, and that their detection can be optimized by ensuring adequate tumor content and read coverage.