Variable Regions Of 16S rRNA Gene Research Articles

Salt concentration in substrate modulates the composition of bacterial and yeast microbiomes of Drosophila melanogaster

Aim: Microbiomes influence the physiology and behavior of multicellular organisms and contribute to their adaptation to changing environmental conditions. However, yeast and bacterial microbiota have usually been studied separately; therefore, the interaction between bacterial and yeast communities in the gut of Drosophila melanogaster (D. melanogaster ) is often overlooked. In this study, we investigate the correlation between bacterial and yeast communities in the gut of D. melanogaster . Methods: We studied the shifts in the joint microbiome of Drosophila melanogaster , encompassing both yeasts and bacteria, during adaptation to substrate with varying salt concentrations (0%, 2%, 4%, and 7%) using plating for both yeasts and bacteria and NGS-sequencing of variable 16S rRNA gene regions for bacteria. Results: The microbiome of flies and their substrates was gradually altered at moderate NaCl concentrations (2% and 4% compared with the 0% control) and completely transformed at high salt concentrations (7%). The relative abundance of Acetobacter , potentially beneficial to D. melanogaster , decreased as NaCl concentration increased, whereas the relative abundance of the more halotolerant lactobacilli first increased, peaking at 4% NaCl, and then declined dramatically at 7%. At this salinity level, potentially pathogenic bacteria of the genera Leuconostoc and Providencia were dominant. The yeast microbiome of D. melanogaster also undergoes significant changes with an increase in salt concentration in the substrate. The total yeast abundance undergoes nonlinear changes: it is lowest at 0% salt concentration and highest at 2%-4%. At a 7% concentration, the yeast abundance in flies and their substrate is lower than at 2%-4% but significantly higher than at 0%. Conclusions: The abundance and diversity of bacteria that are potentially beneficial to the flies decreased, while the proportion of potential pathogens, Leuconostoc and Providencia , increased with an increase in salt concentration in the substrate. In samples with a relatively high abundance and/or diversity of yeasts, the corresponding indicators for bacteria were often lowered, and vice versa . This may be due to the greater halotolerance of yeasts compared to bacteria and may also indicate antagonism between these groups of microorganisms.

Exotic airborne bacteria identified in urban resuspended dust by next generation sequencing

The airborne transport of bacteria is a well-known phenomenon, making it possible to exchange species between ecosystems, but it also provides a tool for spreading of pathogenic microorganisms. As part of a large-scale study, microbial community of inhalable and respirable fractions (PM1-10) of resuspended dust collected in Budapest (Hungary) has been characterised by culture-independent next generation sequencing (NGS) of variable 16S rRNA gene regions. Apart from common, mostly ubiqituos soil and organic material-dwelling bacteria, exotic airborne species have been identified, such as Variovorax ginsengisoli, previously isolated from Korean ginseng fields or Exiguobacterium sibiricum, isolated from the Siberian permafrost.

NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes.

Background:Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises meta-analyses, although this fact is often disregarded. Results:To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as a frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina's HiSeq2000 platform. This allowed for the evaluation of important causes of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR-error, and 3) region/primer specific amplification bias. Despite the short read length (~140 nt) and all technical biases, the average specificity of the taxonomic assignment for the phylotypes included in the mock communities was 97.78%. On average 99.95% and 88.43% of the reads could be assigned to at least family or genus level, respectively, while assignment to 'spurious genera' represented on average only 0.21% of the reads per sample. Analysis of α- and β-diversity confirmed conclusions guided by biology rather than the aforementioned methodological aspects, which was not achieved with QIIME. Conclusions:Different biological outcomes are commonly observed due to 16S rRNA region-specific performance. NG-Tax demonstrated high robustness against choice of region and other technical biases associated with 16S rRNA gene amplicon sequencing studies, diminishing their impact and providing accurate qualitative and quantitative representation of the true sample composition. This will improve comparability between studies and facilitate efforts towards standardization.

NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes

Background: Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises meta-analyses, although this fact is often disregarded. Results: To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as a frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina’s HiSeq2000 platform. This allowed for the evaluation of important causes of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR–error, and 3) region/primer specific amplification bias. Despite the short read length (~140 nt) and all technical biases, the average specificity of the taxonomic assignment for the phylotypes included in the mock communities was 97.78%. On average 99.95% and 88.43% of the reads could be assigned to at least family or genus level, respectively, while assignment to ‘spurious genera’ represented on average only 0.21% of the reads per sample. Analysis of α- and β-diversity confirmed conclusions guided by biology rather than the aforementioned methodological aspects, which was not achieved with QIIME. Conclusions: Different biological outcomes are commonly observed due to 16S rRNA region-specific performance. NG-Tax demonstrated high robustness against choice of region and other technical biases associated with 16S rRNA gene amplicon sequencing studies, diminishing their impact and providing accurate qualitative and quantitative representation of the true sample composition. This will improve comparability between studies and facilitate efforts towards standardization.

NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes.

Background Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises true meta-analyses, although this fact is often disregarded. Results To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as the currently most frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina's HiSeq2000 platform. This allowed evaluating important factors of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR-error, and 3) region/primer specific amplification bias. Despite the short read length (~140 nt) and all technical biases, the average specificity of the taxonomic assignment for the phylotypes included in the mock communities was 96%. On average 99.94% and 92.02% of the reads could be assigned to at least family or genus level, respectively, while assignment to 'spurious genera' represented on average only 0.02% of the reads per sample. Analysis of α- and β-diversity confirmed conclusions guided by biology rather than the aforementioned methodological aspects, which was not the case when samples were analysed using QIIME. Conclusions Different biological outcomes are commonly observed due to 16S rRNA region-specific performance. NG-Tax demonstrated high robustness against choice of region and other technical biases associated with 16S rRNA gene amplicon sequencing studies, diminishing their impact and providing accurate qualitative and quantitative representation of the true sample composition. This will improve comparability between studies and facilitate efforts towards standardization.

Comparing Apples and Oranges?: Next Generation Sequencing and Its Impact on Microbiome Analysis.

Rapid advancements in sequencing technologies along with falling costs present widespread opportunities for microbiome studies across a vast and diverse array of environments. These impressive technological developments have been accompanied by a considerable growth in the number of methodological variables, including sampling, storage, DNA extraction, primer pairs, sequencing technology, chemistry version, read length, insert size, and analysis pipelines, amongst others. This increase in variability threatens to compromise both the reproducibility and the comparability of studies conducted. Here we perform the first reported study comparing both amplicon and shotgun sequencing for the three leading next-generation sequencing technologies. These were applied to six human stool samples using Illumina HiSeq, MiSeq and Ion PGM shotgun sequencing, as well as amplicon sequencing across two variable 16S rRNA gene regions. Notably, we found that the factor responsible for the greatest variance in microbiota composition was the chosen methodology rather than the natural inter-individual variance, which is commonly one of the most significant drivers in microbiome studies. Amplicon sequencing suffered from this to a large extent, and this issue was particularly apparent when the 16S rRNA V1-V2 region amplicons were sequenced with MiSeq. Somewhat surprisingly, the choice of taxonomic binning software for shotgun sequences proved to be of crucial importance with even greater discriminatory power than sequencing technology and choice of amplicon. Optimal N50 assembly values for the HiSeq was obtained for 10 million reads per sample, whereas the applied MiSeq and PGM sequencing depths proved less sufficient for shotgun sequencing of stool samples. The latter technologies, on the other hand, provide a better basis for functional gene categorisation, possibly due to their longer read lengths. Hence, in addition to highlighting methodological biases, this study demonstrates the risks associated with comparing data generated using different strategies. We also recommend that laboratories with particular interests in certain microbes should optimise their protocols to accurately detect these taxa using different techniques.

Characterization of the bacterial communities of life stages of free living lone star ticks (Amblyomma americanum).

The lone star tick (Amblyomma americanum) is an abundant and aggressive biter of humans, domestic animals, and wildlife in the southeastern-central USA and an important vector of several known and suspected zoonotic bacterial pathogens. However, the biological drivers of bacterial community variation in this tick are still poorly defined. Knowing the community context in which tick-borne bacterial pathogens exist and evolve is required to fully understand the ecology and immunobiology of the ticks and to design effective public health and veterinary interventions. We performed a metagenomic survey of the bacterial communities of questing A. americanum and tested 131 individuals (66 nymphs, 24 males, and 41 females) from five sites in three states. Pyrosequencing was performed with barcoded eubacterial primers targeting variable 16S rRNA gene regions 5–3. The bacterial communities were dominated by Rickettsia (likely R. amblyommii) and an obligate Coxiella symbiont, together accounting for 6.7–100% of sequences per tick. DNAs from Midichloria, Borrelia, Wolbachia, Ehrlichia, Pseudomonas, or unidentified Bacillales, Enterobacteriaceae, or Rhizobiales groups were also detected frequently. Wolbachia and Midichloria significantly co-occurred in Georgia (p<0.00001), but not in other states. The significance of the Midichloria-Wolbachia co-occurrence is unknown. Among ticks collected in Georgia, nymphs differed from adults in both the composition (p = 0.002) and structure (p = 0.002) of their bacterial communities. Adults differed only in their community structure (p = 0.002) with males containing more Rickettsia and females containing more Coxiella. Comparisons among adult ticks collected in New York and North Carolina supported the findings from the Georgia collection despite differences in geography, collection date, and sample handling, implying that the differences detected are consistent attributes. The data also suggest that some members of the bacterial community change during the tick life cycle and that some sex-specific attributes may be detectable in nymphs.

Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions

High-throughput molecular technologies can profile microbial communities at high resolution even in complex environments like the intestinal microbiota. Recent improvements in next-generation sequencing technologies allow for even finer resolution. We compared phylogenetic profiling of both longer (454 Titanium) sequence reads with shorter, but more numerous, paired-end reads (Illumina). For both approaches, we targeted six tandem combinations of 16S rRNA gene variable regions, in microbial DNA extracted from a human faecal sample, in order to investigate their limitations and potentials. In silico evaluations predicted that the V3/V4 and V4/V5 regions would provide the highest classification accuracies for both technologies. However, experimental sequencing of the V3/V4 region revealed significant amplification bias compared to the other regions, emphasising the necessity for experimental validation of primer pairs. The latest developments of 454 and Illumina technologies offered higher resolution compared to their previous versions, and showed relative consistency with each other. However, the majority of the Illumina reads could not be classified down to genus level due to their shorter length and higher error rates beyond 60 nt. Nonetheless, with improved quality and longer reads, the far greater coverage of Illumina promises unparalleled insights into highly diverse and complex environments such as the human gut.