Background: Alterations of oral microbiota are the main cause of the progression of caries. The goal of this study was to characterize the oral microbiota in childhood caries based on single-molecule real-time sequencing. Methods: A total of 21 preschoolers, aged 3-5 years old with severe early childhood caries, and 20 age-matched, caries-free children as controls were recruited. Saliva samples were collected, followed by DNA extraction, Pacbio sequencing and phylogenetic analyses of the oral microbial communities. Results: 876 species derived from 13 known bacterial phyla and 110 genera were detected from 41 children using Pacbio sequencing. At the species level, 38 species, including Veillonella spp., Streptococcus spp., Prevotella spp. and Lactobacillus spp., showed higher abundance in the caries group compared to the caries-free group (p<0.05). The core microbiota at the genus and species levels was more stable in the caries-free micro-ecological niche. At follow-up, oral examinations 6 months after sample collection, development of new dental caries was observed in 5 children (the transitional group) among the 21 caries free children. Compared with the caries-free children, in the transitional and caries groups, 6 species, which were more abundant in the caries-free group, exhibited a relatively low abundance in both the caries group and the transitional group (p<0.05). We conclude that Abiotrophia spp., Neisseria spp. and Veillonella spp., are essential for maintaining a healthy oral microbial ecosystem. Prevotella spp., Lactobacillus spp., Dialister spp. and Filifactor spp. may be related to the pathogenesis and progression of dental caries.
Ruminant farming and its environmental impact has long remained an economic concern. Metagenomics unravel the vast structural and functional diversity of the rumen microbial community that plays a major role in animal nutrition. Hereby, we summarize rumen metagenomic studies that have enhanced the knowledge of rumen microbe dynamics subsequently leading to development of better feed strategies to improve livestock production and reduce methane emissions.
Clinical PathoScope: rapid alignment and filtration for accurate pathogen identification in clinical samples using unassembled sequencing data.
The use of sequencing technologies to investigate the microbiome of a sample can positively impact patient healthcare by providing therapeutic targets for personalized disease treatment. However, these samples contain genomic sequences from various sources that complicate the identification of pathogens.Here we present Clinical PathoScope, a pipeline to rapidly and accurately remove host contamination, isolate microbial reads, and identify potential disease-causing pathogens. We have accomplished three essential tasks in the development of Clinical PathoScope. First, we developed an optimized framework for pathogen identification using a computational subtraction methodology in concordance with read trimming and ambiguous read reassignment. Second, we have demonstrated the ability of our approach to identify multiple pathogens in a single clinical sample, accurately identify pathogens at the subspecies level, and determine the nearest phylogenetic neighbor of novel or highly mutated pathogens using real clinical sequencing data. Finally, we have shown that Clinical PathoScope outperforms previously published pathogen identification methods with regard to computational speed, sensitivity, and specificity.Clinical PathoScope is the only pathogen identification method currently available that can identify multiple pathogens from mixed samples and distinguish between very closely related species and strains in samples with very few reads per pathogen. Furthermore, Clinical PathoScope does not rely on genome assembly and thus can more rapidly complete the analysis of a clinical sample when compared with current assembly-based methods. Clinical PathoScope is freely available at: http://sourceforge.net/projects/pathoscope/.
Establishing the time since death is critical in every death investigation, yet existing techniques are susceptible to a range of errors and biases. For example, forensic entomology is widely used to assess the postmortem interval (PMI), but errors can range from days to months. Microbes may provide a novel method for estimating PMI that avoids many of these limitations. Here we show that postmortem microbial community changes are dramatic, measurable, and repeatable in a mouse model system, allowing PMI to be estimated within approximately 3 days over 48 days. Our results provide a detailed understanding of bacterial and microbial eukaryotic ecology within a decomposing corpse system and suggest that microbial community data can be developed into a forensic tool for estimating PMI. DOI:http://dx.doi.org/10.7554/eLife.01104.001.
Improved OTU-picking using long-read 16S rRNA gene amplicon sequencing and generic hierarchical clustering
BACKGROUND: High-throughput bacterial 16S rRNA gene sequencing followed by clustering of short sequences into operational taxonomic units (OTUs) is widely used for microbiome profiling. However, clustering of short 16S rRNA gene reads into biologically meaningful OTUs is challenging, in part because nucleotide variation along the 16S rRNA gene is only partially captured by short reads. The recent emergence of long-read platforms, such as single-molecule real-time (SMRT) sequencing from Pacific Biosciences, offers the potential for improved taxonomic and phylogenetic profiling. Here, we evaluate the performance of long- and short-read 16S rRNA gene sequencing using simulated and experimental data, followed by OTU inference using computational pipelines based on heuristic and complete-linkage hierarchical clustering. RESULTS: In simulated data, long-read sequencing was shown to improve OTU quality and decrease variance. We then profiled 40 human gut microbiome samples using a combination of Illumina MiSeq and Blautia-specific SMRT sequencing, further supporting the notion that long reads can identify additional OTUs. We implemented a complete-linkage hierarchical clustering strategy using a flexible computational pipeline, tailored specifically for PacBio circular consensus sequencing (CCS) data that outperforms heuristic methods in most settings: https://github.com/oscar-franzen/oclust/. CONCLUSION: Our data demonstrate that long reads can improve OTU inference; however, the choice of clustering algorithm and associated clustering thresholds has significant impact on performance.
Ticks are of medical importance owing to their ability to transmit pathogens to humans and animals. The Rocky Mountain wood tick, Dermacentor andersoni, is a vector of a number of pathogens, including Anaplasma marginale, which is the most widespread tick-borne pathogen of livestock. Although ticks host pathogenic bacteria, they also harbor bacterial endosymbionts that have a role in tick physiology, survival, as well as pathogen acquisition and transmission. The goal of this study was to characterize the bacterial microbiome and examine the impact of microbiome disruption on pathogen susceptibility. The bacterial microbiome of two populations of D. andersoni with historically different susceptibilities to A. marginale was characterized. In this study, the microbiome was disrupted and then ticks were exposed to A. marginale or Francisella novicida to determine whether the microbiome correlated with pathogen susceptibility. Our study showed that an increase in proportion and quantity of Rickettsia bellii in the microbiome was negatively correlated to A. marginale levels in ticks. Furthermore, a decrease in Francisella endosymbionts was associated with lower F. novicida infection levels, demonstrating a positive pathogen-endosymbiont relationship. We demonstrate that endosymbionts and pathogens have varying interactions, and suggest that microbiome manipulation may provide a possible method for biocontrol by decreasing pathogen susceptibility of ticks.
Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities.
Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes.
Pan-bacterial 16S rRNA microbiome surveys performed with massively parallel DNA sequencing technologies have transformed community microbiological studies. Current 16S profiling methods, however, fail to provide sufficient taxonomic resolution and accuracy to adequately perform species-level associative studies for specific conditions. This is due to the amplification and sequencing of only short 16S rRNA gene regions, typically providing for only family- or genus-level taxonomy. Moreover, sequencing errors often inflate the number of taxa present. Pacific Biosciences’ (PacBio’s) long-read technology in particular suffers from high error rates per base. Herein, we present a microbiome analysis pipeline that takes advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error correct full-length bacterial 16S rRNA genes, which provides high-fidelity species-level microbiome data.Analysis of a mock community with 20 bacterial species demonstrated 100% specificity and sensitivity with regard to taxonomic classification. Examination of a 250-plus species mock community demonstrated correct species-level classification of >?90% of taxa, and relative abundances were accurately captured. The majority of the remaining taxa were demonstrated to be multiply, incorrectly, or incompletely classified. Using this methodology, we examined the microgeographic variation present among the microbiomes of six sinonasal sites, by both swab and biopsy, from the anterior nasal cavity to the sphenoid sinus from 12 subjects undergoing trans-sphenoidal hypophysectomy. We found greater variation among subjects than among sites within a subject, although significant within-individual differences were also observed. Propiniobacterium acnes (recently renamed Cutibacterium acnes) was the predominant species throughout, but was found at distinct relative abundances by site.Our microbial composition analysis pipeline for single-molecule real-time 16S rRNA gene sequencing (MCSMRT, https://github.com/jpearl01/mcsmrt ) overcomes deficits of standard marker gene-based microbiome analyses by using CCS of entire 16S rRNA genes to provide increased taxonomic and phylogenetic resolution. Extensions of this approach to other marker genes could help refine taxonomic assignments of microbial species and improve reference databases, as well as strengthen the specificity of associations between microbial communities and dysbiotic states.
In ecological studies, microbial diversity is nowadays mostly assessed via the detection of phylogenetic marker genes, such as 16S rRNA. However, PCR amplification of these marker genes produces a significant amount of artificial sequences, often referred to as chimeras. Different algorithms have been developed to remove these chimeras, but efforts to combine different methodologies are limited. Therefore, two machine learning classifiers (reference-based and de novo CATCh) were developed by integrating the output of existing chimera detection tools into a new, more powerful method. When comparing our classifiers with existing tools in either the reference-based or de novo mode, a higher performance of our ensemble method was observed on a wide range of sequencing data, including simulated, 454 pyrosequencing, and Illumina MiSeq data sets. Since our algorithm combines the advantages of different individual chimera detection tools, our approach produces more robust results when challenged with chimeric sequences having a low parent divergence, short length of the chimeric range, and various numbers of parents. Additionally, it could be shown that integrating CATCh in the preprocessing pipeline has a beneficial effect on the quality of the clustering in operational taxonomic units. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
Analysis of the duodenal microbiotas of weaned piglet fed with epidermal growth factor-expressed Saccharomyces cerevisiae.
The bacterial community of the small intestine is a key factor that has strong influence on the health of gastrointestinal tract (GIT) in mammals during and shortly after weaning. The aim of this study was to analyze the effects of the diets of supplemented with epidermal growth factor (EGF)-expressed Saccharomyces cerevisiae (S. cerevisiae) on the duodenal microbiotas of weaned piglets.Revealed in this study, at day 7, 14 and 21, respectively, the compositional sequencing analysis of the 16S rRNA in the duodenum had no marked difference in microbial diversity from the phylum to species levels between the INVSc1(EV) and other recombinant strains encompassing INVSc1-EE(+), INVSc1-TE(-), and INVSc1-IE(+). Furthermore, the populations of potentially enterobacteria (e.g., Clostridium and Prevotella) and probiotic (e.g., Lactobacilli and Lactococcus) also remained unchanged among recombinant S. cerevisiae groups (P?>?0.05). However, the compositional sequencing analysis of the 16S rRNA in the duodenum revealed significant difference in microbial diversity from phylum to species levels between the control group and recombinant S. cerevisiae groups. In terms of the control group (the lack of S. cerevisiae), these data confirmed that dietary exogenous S. cerevisiae had the feasibility to be used as a supplement for enhancing potentially probiotic (e.g., Lactobacilli and Lactococcus) (P?0.01), and reducing potentially pathogenic bacteria (e.g., Clostridium and Prevotella) (P?0.01).Herein, altered the microbiome effect was really S. cerevisiae, and then different forms of recombinant EGF, including T-EGF, EE-EGF and IE-EGF, did not appear to make a significant difference to the microbiome of weaned piglets.
PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes.
Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into ‘bins’ representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies ‘training’ sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4-6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki.
Daily HIV pre-exposure prophylaxis (PrEP) with tenofovir disoproxil fumarate-emtricitabine reduced Streptococcus and increased Erysipelotrichaceae in rectal microbiota.
Daily PrEP is highly effective at preventing HIV-1 acquisition, but risks of long-term tenofovir disoproxil fumarate plus emtricitabine (TDF-FTC) include renal decline and bone mineral density decrease in addition to initial gastrointestinal side effects. We investigated the impact of TDF-FTC on the enteric microbiome using rectal swabs collected from healthy MSM before PrEP initiation and after 48 to 72 weeks of adherent PrEP use. The V4 region of the 16S ribosomal RNA gene sequencing showed that Streptococcus was significantly reduced from 12.0% to 1.2% (p?=?0.036) and Erysipelotrichaceae family was significantly increased from 0.79% to 3.3% (p?=?0.028) after 48-72 weeks of daily PrEP. Catenibacterium mitsuokai, Holdemanella biformis and Turicibacter sanguinis were increased within the Erysipelotrichaceae family and Streptococcus agalactiae, Streptococcus oralis, Streptococcus mitis were reduced. These changes were not associated with host factors including PrEP duration, age, race, tenofovir diphosphate blood level, any drug use and drug abuse, suggesting that the observed microbiome shifts were likely induced by daily PrEP use. Long-term PrEP resulted in increases of Catenibacterium mitsuokai and Holdemanella biformis, which have been associated with gut microbiome dysbiosis. Our observations can aid in characterizing PrEP’s side effects, which is likely to improve PrEP adherence, and thus HIV-1 prevention.
The influence of energy harvesting strategies on performance and microbial community for sediment microbial fuel cells
Sediment microbial fuel cells (SMFCs) are being developed as potential energy sources where remote sensing and monitoring would be useful. Several energy harvesting techniques for SMFCs have emerged, but effects of these different strategies on startup, performance, and microbial community are not well understood. We investigated these effects by comparing a continuous energy harvesting (CEH) strategy with an intermittent energy harvesting (IEH) strategy. During startup, IEH systems immediately produced higher power and were cathode limited. CEH systems exhibited a gradual power increase and were anode-limited during startup. Both system types produced similar amounts of steady-state power, 1.5 mW ft-2 (16 mW m-2) when optimized. However, an IEH system using unoptimized settings could not be subsequently switched to optimal settings and produce expected power levels. The choice of energy harvester did not appear to significantly affect steady-state community structure. Anodes were dominated by ?- and d-proteobacteria while a- and ?-proteobacteria dominated cathodes. The results suggest performance and community structure are unaffected by energy harvesting strategy, but that startup conditions influence the initial amount of harvested energy and steady-state performance, suggesting future investigations into optimizing startup of these systems are critical for rapidly generating maximum power.
Bacterial community structure in simultaneous nitrification, denitrification and organic matter removal process treating saline mustard tuber wastewater as revealed by 16S rRNA sequencing.
A simultaneous nitrification, denitrification and organic matter removal (SNDOR) process in sequencing batch biofilm reactor (SBBR) was established to treat saline mustard tuber wastewater (MTWW) in this study. An average COD removal efficiency of 86.48% and total nitrogen removal efficiency of 86.48% were achieved at 30gNaClL(-1) during 100days’ operation. The underlying mechanisms were investigated by PacBio SMRT DNA sequencing (V1-V9) to analyze the microbial community structures and its variation from low salinity at 10gNaClL(-1) to high salinity at 30gNaClL(-1). Results showed elevated salinity did not affect biological performance but reduced microbial diversity in SBBR, and halophilic bacteria gradually predominated by succession. Despite of high C/N, autotrophic ammonia-oxidizing bacteria (AOB) Nitrosomonas and ammonia-oxidizing archaea (AOA) Candidatus Nitrososphaera both contributed to ammonium oxidation. As salinity increasing, nitrite-oxidizing bacteria (NOB) were significantly inhibited, partial nitrification and denitrification (PND) process gradually contributed to nitrogen removal. Copyright © 2016 Elsevier Ltd. All rights reserved.
Koumiss consumption alleviates symptoms of patients with chronic atrophic gastritis: A possible link To modulation of gut microbiota
Intestinal dysbiosisis closely related to a variety of medical conditions, especially gastrointestinal diseases. The present study aimed to investigate the effects of koumiss on chronic atrophic gastritis (CAG) in an out-patient clinical trial (n = 10; all female subjects aged 41-55; body mass index ranging from 19.5 to 25.8). Each patient consumed three servings of koumiss per day (i.e. 250 ml daily before each of 3 meals) for a 60-day period. The improvement of patients’ symptoms was monitored by comparing the total scores of symptoms before and after the treatment. Meanwhile, the changes in the patients’ fecal microbiota composition and specific blood parameters were determined. After the 60-day koumiss administration, significant symptom improvements were observed, as evidenced by the reduction of the total symptoms score, and changes in blood platelet and cholesterol levels. The changes in patients’ fecal microbiota composition were found. The patients’ fecal microbiota fell into two distinct enterotypes, Bacteroides dorei/ Bacteroides uniformis (BB-enterotype) and Prevotella copri (P-enterotype). Significant less Bacteroides uniformis was found in the BB-enterotype patient group, while significant more butyrate-producing bacteria (e.g. Eubacterium rectale and Faecalibacterium prausnitzii) were found in the P-enterotype patient group, following koumiss administration. After stopping koumiss consumption, the relative abundance of some biomarker taxa returned to the original level, suggesting that the gut microbiota modulatory effect was not permanent and that continuous koumiss administration was required to maintain the therapeutic effect. In conclusion, koumiss consumption could alleviate the symptoms of CAG patients. Our results may help understand the mechanism of koumiss in alleviating CAG disease symptoms, facilitating the development of such products with desired therapeutic functions.