How To sequence the 16s and ITS fungal gene affordably  MR DNA 16s sequencing microbiome and metagenome low prices

16s rRNA Sequencing with MR DNA

16S ribosomal  (rRNA) sequencing using next generation sequencing is a method used to identify and compare bacteria and archaea present within almost any type of sample. 16S rRNA gene sequencing is a well-established method for studying phylogeny and taxonomy of samples from complex microbiomes or environments that are difficult or impossible to study.

 

 

 

 

16s sequencing illumina or PGM low cost prices with MR DNA

MR DNA is a next generation sequencing provider with low cost 16s sequencing services.

 

 

 

 

Select item 26745269

 

46.

PLoS One. 2016 Jan 8;11(1):e0146406. doi: 10.1371/journal.pone.0146406. eCollection 2016.

Resistant Starch Alters the Microbiota-Gut Brain Axis: Implications for Dietary Modulation of Behavior.

Lyte M1,2, Chapel A3, Lyte JM4, Ai Y4, Proctor A2, Jane JL4, Phillips GJ2.

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Abstract

The increasing recognition that the gut microbiota plays a central role in behavior and cognition suggests that the manipulation of microbial taxa through diet may provide a means by which behavior may be altered in a reproducible and consistent manner in order to achieve a beneficial outcome for the host. Resistant starch continues to receive attention as a dietary intervention that can benefit the host through mechanisms that include altering the intestinal microbiota. Given the interest in dietary approaches to improve health, the aim of this study was to investigate whether the use of dietary resistant starch in mice to alter the gut microbiota also results in a change in behavior. Forty-eight 6 week-old male Swiss-Webster mice were randomly assigned to 3 treatment groups (n = 16 per group) and fed either a normal corn starch diet (NCS) or diets rich in resistant starches HA7 diet (HA7) or octenyl-succinate HA7 diet (OS-HA7) for 6 week and monitored for weight, behavior and fecal microbiota composition. Animals fed an HA7 diet displayed comparable weight gain over the feeding period to that recorded for NCS-fed animals while OS-HA7 displayed a lower weight gain as compared to either NCS or HA7 animals (ANOVA p = 0.0001; NCS:HA7 p = 0.244; HA7:OS-HA7 p<0.0001; NCS:OS-HA7 p<0.0001). Analysis of fecal microbiota using 16s rRNA gene taxonomic profiling revealed that each diet corresponded with a unique gut microbiota. The distribution of taxonomic classes was dynamic over the 6 week feeding period for each of the diets. At the end of the feeding periods, the distribution of taxa included statistically significant increases in members of the phylum Proteobacteria in OS-HA7 fed mice, while the Verrucomicrobia increased in HA7 fed mice over that of mice fed OS-HA7. At the class level, members of the class Bacilli decreased in the OS-HA7 fed group, and Actinobacteria, which includes the genus Bifidobacteria, was enriched in the HA7 fed group compared to the control diet. Behavioral analysis revealed that animals demonstrated profound anxiety-like behavior as observed by performance on the elevated-plus maze with time spent by the mice in the open arm (ANOVA p = 0.000; NCS:HA7 p = 0.004; NCS:OS-HA7 p = 1.000; HA7:OS-HA7 p = 0.0001) as well as entries in the open arm (ANOVA p = 0.039; NCS:HA7 p = 0.041; HA7:OS-HA7 p = 0.221; NCS:OS-HA7 p = 1.000). Open-field behavior, a measure of general locomotion and exploration, revealed statistically significant differences between groups in locomotion as a measure of transitions across quadrant boundaries. Additionally, the open-field assay revealed decreased exploration as well as decreased rearing in HA7 and OS-HA7 fed mice demonstrating a consistent pattern of increased anxiety-like behavior among these groups. Critically, behavior was not correlated with weight. These results indicate that diets based on resistant starch can be utilized to produce quantifiable changes in the gut microbiota and should be useful to "dial-in" a specific microbiome that is unique to a particular starch composition. However, undesirable effects can also be associated with resistant starch, including lack of weight gain and increased anxiety-like behaviors. These observations warrant careful consideration when developing diets rich in resistant starch in humans and animal models.

PMID: 26745269 PMCID: PMC4706316 DOI: 10.1371/journal.pone.0146406

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Select item 26738553

 

47.

FEMS Microbiol Ecol. 2016 Mar;92(3). pii: fiw003. doi: 10.1093/femsec/fiw003. Epub 2016 Jan 5.

Virome-associated antibiotic-resistance genes in an experimental aquaculture facility.

Colombo S1, Arioli S1, Guglielmetti S1, Lunelli F2, Mora D3.

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Abstract

We report the comprehensive characterization of viral and microbial communities within an aquaculture wastewater sample, by a shotgun sequencing and 16S rRNA gene profiling metagenomic approach. Caudovirales had the largest representation within the sample, with over 50% of the total taxonomic abundance, whereas approximately 30% of the total open reading frames (ORFs) identified were from eukaryotic viruses (Mimiviridae and Phycodnaviridae). Antibiotic resistance genes (ARGs) within the virome accounted for 0.85% of the total viral ORFs and showed a similar distribution both in virome and in microbiome. Among the ARGs, those encoding proteins involved in the modulation of antibiotic efflux pumps were the most abundant. Interestingly, the taxonomy of the bacterial ORFs identified in the viral metagenome did not reflect the microbial taxonomy as deduced by 16S rRNA gene profiling and shotgun metagenomic analysis. A limited number of ARGs appeared to be mobilized from bacteria to phages or vice versa, together with other bacterial genes encoding products involved in general metabolic functions, even in the absence of any antibiotic treatment within the aquaculture plant. Thus, these results confirm the presence of a complex phage-bacterial network in the aquaculture environment.

© FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

KEYWORDS:

antibiotic resistance genes; aquaculture; horizontal gene transfer; microbiome; virome

PMID: 26738553 DOI: 10.1093/femsec/fiw003

[PubMed - in process]

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Select item 26718401

 

48.

Biochem Biophys Res Commun. 2016 Jan 22;469(4):967-77. doi: 10.1016/j.bbrc.2015.12.083. Epub 2015 Dec 22.

Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing.

Ranjan R1, Rani A2, Metwally A3, McGee HS4, Perkins DL5.

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Abstract

The human microbiome has emerged as a major player in regulating human health and disease. Translational studies of the microbiome have the potential to indicate clinical applications such as fecal transplants and probiotics. However, one major issue is accurate identification of microbes constituting the microbiota. Studies of the microbiome have frequently utilized sequencing of the conserved 16S ribosomal RNA (rRNA) gene. We present a comparative study of an alternative approach using whole genome shotgun sequencing (WGS). In the present study, we analyzed the human fecal microbiome compiling a total of 194.1 × 10(6) reads from a single sample using multiple sequencing methods and platforms. Specifically, after establishing the reproducibility of our methods with extensive multiplexing, we compared: 1) The 16S rRNA amplicon versus the WGS method, 2) the Illumina HiSeq versus MiSeq platforms, 3) the analysis of reads versus de novo assembled contigs, and 4) the effect of shorter versus longer reads. Our study demonstrates that whole genome shotgun sequencing has multiple advantages compared with the 16S amplicon method including enhanced detection of bacterial species, increased detection of diversity and increased prediction of genes. In addition, increased length, either due to longer reads or the assembly of contigs, improved the accuracy of species detection.

Copyright © 2015 Elsevier Inc. All rights reserved.

KEYWORDS:

16S rRNA; Amplicon sequencing; Metagenomics; Microbiome; Microbiota; Next-generation sequencing; Whole genome shotgun sequencing

PMID: 26718401 PMCID: PMC4830092 [Available on 2017-01-22] DOI: 10.1016/j.bbrc.2015.12.083

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Select item 26715502

 

49.

Dig Dis Sci. 2016 Jun;61(6):1628-34. doi: 10.1007/s10620-015-4011-3. Epub 2015 Dec 29.

Metagenomic Analysis Reveals Dynamic Changes of Whole Gut Microbiota in the Acute Phase of Intensive Care Unit Patients.

Ojima M1, Motooka D2, Shimizu K3, Gotoh K2, Shintani A4, Yoshiya K3, Nakamura S2, Ogura H3, Iida T2, Shimazu T3.

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Abstract

BACKGROUND:

Metagenomic analysis targeting the 16S rRNA gene has made it possible to characterize the vast array of microorganisms contained in the gut.

AIM:

The purpose of this study was to evaluate how gut microbiota change in intensive care unit (ICU) patients in the acute phase after admission.

METHODS:

This prospective observational cohort study investigated 12 patients admitted to a single ICU of a large urban tertiary referral hospital. All patients were mechanically ventilated on admission. Fecal samples were collected from patients on days 1-2, 2-4, 5-8, and 7-10 after admission. DNA was extracted from fecal samples, and 16S rRNA deep sequencing was performed to monitor gut changes.

RESULTS:

Bacteria belonging to the phyla Firmicutes or Bacteroidetes were predominant in each sample. We observed serial dynamic changes in the percentages of Bacteroidetes and Firmicutes that were significantly altered during study period (p < 0.05). A ratio of Bacteroidetes to Firmicutes (B/F ratio) of >10 was seen in four of the six patients who died, whereas a B/F ratio of <0.10 was seen in only one of the six deaths. None of the survivors had a B/F ratio of >10 or <0.10. There was a statistical difference in the B/F ratio between the dead patients and survivors (p = 0.022).

CONCLUSIONS:

Dynamic changes in gut microbiota at the phylum level of ICU patients during the acute phase were identified by high-throughput DNA sequencing. An extreme imbalance in gut microbiota may be associated with prognosis in critically ill patients.

KEYWORDS:

Bacteroidetes; DNA sequencing; Intensive care; Metagenome; Metagenomics; Microbiota; RNA, Ribosomal, 16S; Sepsis

PMID: 26715502 PMCID: PMC4875048 DOI: 10.1007/s10620-015-4011-3

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Select item 26713550

 

50.

Plant Physiol Biochem. 2016 Feb;99:39-48. doi: 10.1016/j.plaphy.2015.12.002. Epub 2015 Dec 9.

The interaction between iron nutrition, plant species and soil type shapes the rhizosphere microbiome.

Pii Y1, Borruso L2, Brusetti L2, Crecchio C3, Cesco S2, Mimmo T2.

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Abstract

Plant-associated microorganisms can stimulate plants growth and influence both crops yield and quality by nutrient mobilization and transport. Therefore, rhizosphere microbiome appears to be one of the key determinants of plant health and productivity. The roots of plants have the ability to influence its surrounding microbiology, the rhizosphere microbiome, through the creation of specific chemical niches in the soil mediated by the release of phytochemicals (i.e. root exudates) that depends on several factors, such as plants genotype, soil properties, plant nutritional status, climatic conditions. In the present research, two different crop species, namely barley and tomato, characterized by different strategies for Fe acquisition, have been grown in the RHIZOtest system using either complete or Fe-free nutrient solution to induce Fe starvation. Afterward, plants were cultivated for 6 days on two different calcareous soils. Total DNA was extracted from rhizosphere and bulk soil and 454 pyrosequencing technology was applied to V1-V3 16S rRNA gene region. Approximately 5000 sequences were obtained for each sample. The analysis of the bacterial population confirmed that the two bulk soils showed a different microbial community. The presence of the two plant species, as well as the nutritional status (Fe-deficiency and Fe-sufficiency), could promote a differentiation of the rhizosphere microbiome, as highlighted by non-metric multidimensional scaling (NMDS) analysis. Alphaproteobacteria, Actinobacteria, Chloracidobacteria, Thermoleophilia, Betaproteobacteria, Saprospirae, Gemmatimonadetes, Gammaproteobacteria, Acidobacteria were the most represented classes in all the samples analyzed even though their relative abundance changed as a function of the soil, plant species and nutritional status. To our knowledge, this research demonstrate for the first time that different plants species with a diverse nutritional status can promote the development of a peculiar rhizosphere microbiome, depending on the growth substrate.

Copyright © 2015 Elsevier Masson SAS. All rights reserved.

KEYWORDS:

Barley; Fe deficiency; PGPR; Pyrosequencing; Rhizosphere metagenome; Tomato

PMID: 26713550 DOI: 10.1016/j.plaphy.2015.12.002

[PubMed - in process]

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Select item 26671497

 

51.

J Infect Public Health. 2016 May-Jun;9(3):362-5. doi: 10.1016/j.jiph.2015.11.008. Epub 2015 Dec 3.

First microbiota assessments of children's paddling pool waters evaluated using 16S rRNA gene-based metagenome analysis.

Sawabe T1, Suda W2, Ohshima K3, Hattori M4, Sawabe T5.

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Abstract

Insufficient chloric sterilization of children's paddling pool waters increases the risk of diarrheal illness. Therefore, we investigated the microbiota changes after children use pools. First, we applied 16S rRNA gene-based metagenome analysis to understand the dynamics of microbiota in pool water, especially with respect to the bio-contamination by potential pathogens. Proteobacteria were major taxa detected in every pool water sample after children spent time in the pool. In more detail, Gammaproteobacteria comprised the dominant class, which was followed by Betaproteobacteria. Five phyla, Bacteroidetes, Firmicutes, Actinobacteria and Deinococcus-Thermus phyla were minor groups. The pool water microbiota are likely to be a consortium of intestinal and skin microbiota from humans. Interestingly, the ratio of Gammaproteobacteria and Betaproteobacteria differed according to the age of the children who used the pool, which means the pool water was additionally contaminated by soil microbiota as a result of the children's behavior. Furthermore, potential pathogens, such as Campylobacter spp., Comamonas testosteroni and Burkholderia pseudomallei, were also found. Considering the standard plate counts, the abundances of these human pathogens are unlikely to be a sufficiently infectious dose. We suggest the importance of sanitary measures in paddling pool waters to reduce bio-contamination from both humans and the environment.

Copyright © 2015 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

KEYWORDS:

Children's paddling pool; Contamination; Metagenome; Microbiota; Small subunit rRNA gene

PMID: 26671497 DOI: 10.1016/j.jiph.2015.11.008

[PubMed - in process]

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Select item 26642878

 

52.

Microbiome. 2015 Dec 8;3:62. doi: 10.1186/s40168-015-0129-y.

A viability-linked metagenomic analysis of cleanroom environments: eukarya, prokaryotes, and viruses.

Weinmaier T1, Probst AJ2, La Duc MT3,4, Ciobanu D5, Cheng JF6, Ivanova N7, Rattei T8, Vaishampayan P9.

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Abstract

BACKGROUND:

Recent studies posit a reciprocal dependency between the microbiomes associated with humans and indoor environments. However, none of these metagenome surveys has considered the viability of constituent microorganisms when inferring impact on human health.

RESULTS:

Reported here are the results of a viability-linked metagenomics assay, which (1) unveil a remarkably complex community profile for bacteria, fungi, and viruses and (2) bolster the detection of underrepresented taxa by eliminating biases resulting from extraneous DNA. This approach enabled, for the first time ever, the elucidation of viral genomes from a cleanroom environment. Upon comparing the viable biomes and distribution of phylotypes within a cleanroom and adjoining (uncontrolled) gowning enclosure, the rigorous cleaning and stringent control countermeasures of the former were observed to select for a greater presence of anaerobes and spore-forming microflora. Sequence abundance and correlation analyses suggest that the viable indoor microbiome is influenced by both the human microbiome and the surrounding ecosystem(s).

CONCLUSIONS:

The findings of this investigation constitute the literature's first ever account of the indoor metagenome derived from DNA originating solely from the potential viable microbial population. Results presented in this study should prove valuable to the conceptualization and experimental design of future studies on indoor microbiomes aimed at inferring impact on human health.

PMID: 26642878 PMCID: PMC4672508 DOI: 10.1186/s40168-015-0129-y

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Select item 26633628

 

53.

Nature. 2015 Dec 10;528(7581):262-6. doi: 10.1038/nature15766. Epub 2015 Dec 2.

Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota.

Forslund K1, Hildebrand F1,2,3, Nielsen T4, Falony G2,5, Le Chatelier E6,7, Sunagawa S1, Prifti E6,7,8, Vieira-Silva S2,5, Gudmundsdottir V9, Krogh Pedersen H9, Arumugam M4, Kristiansen K10, Voigt AY1,11,12, Vestergaard H4, Hercog R1, Igor Costea P1, Kultima JR1, Li J13, Jørgensen T14,15,16, Levenez F6,7, Dore J6,7; MetaHIT consortium, Nielsen HB9, Brunak S9,17, Raes J2,3,5, Hansen T4,18, Wang J10,13,19,20,21, Ehrlich SD6,7,22, Bork P1,12,23,24, Pedersen O4.

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Abstract

In recent years, several associations between common chronic human disorders and altered gut microbiome composition and function have been reported. In most of these reports, treatment regimens were not controlled for and conclusions could thus be confounded by the effects of various drugs on the microbiota, which may obscure microbial causes, protective factors or diagnostically relevant signals. Our study addresses disease and drug signatures in the human gut microbiome of type 2 diabetes mellitus (T2D). Two previous quantitative gut metagenomics studies of T2D patients that were unstratified for treatment yielded divergent conclusions regarding its associated gut microbial dysbiosis. Here we show, using 784 available human gut metagenomes, how antidiabetic medication confounds these results, and analyse in detail the effects of the most widely used antidiabetic drug metformin. We provide support for microbial mediation of the therapeutic effects of metformin through short-chain fatty acid production, as well as for potential microbiota-mediated mechanisms behind known intestinal adverse effects in the form of a relative increase in abundance of Escherichia species. Controlling for metformin treatment, we report a unified signature of gut microbiome shifts in T2D with a depletion of butyrate-producing taxa. These in turn cause functional microbiome shifts, in part alleviated by metformin-induced changes. Overall, the present study emphasizes the need to disentangle gut microbiota signatures of specific human diseases from those of medication.

Comment in

Gut microbiota: Antidiabetic drug treatment confounds gut dysbiosis associated with type 2 diabetes mellitus. [Nat Rev Endocrinol. 2016]

Metformin Joins Forces with Microbes. [Cell Host Microbe. 2016]

Confounding Effects of Metformin on the Human Gut Microbiome in Type 2 Diabetes. [Cell Metab. 2016]

MICROBIOME. Prescription drugs obscure microbiome analyses. [Science. 2016]

PMID: 26633628 PMCID: PMC4681099 DOI: 10.1038/nature15766

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Select item 26632844

 

54.

PLoS One. 2015 Dec 3;10(12):e0144448. doi: 10.1371/journal.pone.0144448. eCollection 2015.

Functional Metagenomics of the Bronchial Microbiome in COPD.

Millares L1,2,3,4, Pérez-Brocal V5,6,7, Ferrari R5,6,7, Gallego M8, Pomares X2,8, García-Núñez M1,2,3,4, Montón C2,8, Capilla S9, Monsó E2,3,8, Moya A5,6,7.

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Abstract

The course of chronic obstructive pulmonary disease (COPD) is frequently aggravated by exacerbations, and changes in the composition and activity of the microbiome may be implicated in their appearance. The aim of this study was to analyse the composition and the gene content of the microbial community in bronchial secretions of COPD patients in both stability and exacerbation. Taxonomic data were obtained by 16S rRNA gene amplification and pyrosequencing, and metabolic information through shotgun metagenomics, using the Metagenomics RAST server (MG-RAST), and the PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) programme, which predict metagenomes from 16S data. Eight severe COPD patients provided good quality sputum samples, and no significant differences in the relative abundance of any phyla and genera were found between stability and exacerbation. Bacterial biodiversity (Chao1 and Shannon indexes) did not show statistical differences and beta-diversity analysis (Bray-Curtis dissimilarity index) showed a similar microbial composition in the two clinical situations. Four functional categories showed statistically significant differences with MG-RAST at KEGG level 2: in exacerbation, Cell growth and Death and Transport and Catabolism decreased in abundance [1.6 (0.2-2.3) vs 3.6 (3.3-6.9), p = 0.012; and 1.8 (0-3.3) vs 3.6 (1.8-5.1), p = 0.025 respectively], while Cancer and Carbohydrate Metabolism increased [0.8 (0-1.5) vs 0 (0-0.5), p = 0.043; and 7 (6.4-9) vs 5.9 (6.3-6.1), p = 0.012 respectively]. In conclusion, the bronchial microbiome as a whole is not significantly modified when exacerbation symptoms appear in severe COPD patients, but its functional metabolic capabilities show significant changes in several pathways.

PMID: 26632844 PMCID: PMC4669145 DOI: 10.1371/journal.pone.0144448

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Select item 27092122

 

21.

Front Microbiol. 2016 Apr 5;7:462. doi: 10.3389/fmicb.2016.00462. eCollection 2016.

Carrageenan Gum and Adherent Invasive Escherichia coli in a Piglet Model of Inflammatory Bowel Disease: Impact on Intestinal Mucosa-associated Microbiota.

Munyaka PM1, Sepehri S2, Ghia JE3, Khafipour E4.

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Abstract

Inflammatory bowel diseases (IBD) including Crohn's disease (CD), and ulcerative colitis (UC), are chronic conditions characterized by chronic intestinal inflammation. Adherent invasive Escherichia coli (AIEC) pathotype has been increasingly implicated in the etiopathogenesis of IBD. In a 21-day study, we investigated the effects of AIEC strain UM146 inoculation on microbiota profile of the ileal, cecal, ascending and descending colon in a pig model of experimental colitis. Carrageenan gum (CG) was used to induce colitis in weaner piglets whereas AIEC strain UM146 previously isolated from a CD patient was included to investigate a cause or consequence effect in IBD. Treatments were: (1) control; (2) CG; (3) AIEC strain UM146; and (4) CG+UM146. Pigs in groups 2 and 4 received 1% CG in drinking water from day 1 of the study while pigs in groups 3 and 4 were inoculated with UM146 on day 8. Following euthanization on day 21, tissue mucosal scrapings were collected and used for DNA extraction. The V4 region of bacterial 16S rRNA gene was then subjected to Illumina sequencing. Microbial diversity, composition, and the predicted functional metagenome were determined in addition to short chain fatty acids profiles in the digesta and inflammatory cytokines in the intestinal tissue. CG-induced colitis decreased bacterial species richness and shifted community composition. At the phylum level, an increase in Proteobacteria and Deferribacteres and a decrease in Firmicutes, Actinobacteria, and Bacteroidetes were observed in CG and CGUM146 compared to control and UM146. The metabolic capacity of the microbiome was also altered in CG and CGUM146 compared to UM146 and control in the colon. We demonstrated that CG resulted in bacterial dysbiosis and shifted community composition similar to what has been previously observed in IBD patients. However, AIEC strain UM146 alone did not cause any clear changes compared to CG or control in our experimental IBD pig model.

KEYWORDS:

16S rRNA gene sequencing; Crohn's disease; adherent invasive Escherichia coli; carrageenan gum; microbiome; pigs; ulcerative colitis

PMID: 27092122 PMCID: PMC4820460 DOI: 10.3389/fmicb.2016.00462

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Select item 27072196

 

22.

Sci Rep. 2016 Apr 13;6:24340. doi: 10.1038/srep24340.

The gut microbiome and degradation enzyme activity of wild freshwater fishes influenced by their trophic levels.

Liu H1, Guo X2, Gooneratne R3, Lai R1, Zeng C1, Zhan F1, Wang W1,4.

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Abstract

Vertebrate gut microbiome often underpins the metabolic capability and provides many beneficial effects on their hosts. However, little was known about how host trophic level influences fish gut microbiota and metabolic activity. In this study, more than 985,000 quality-filtered sequences from 24 16S rRNA libraries were obtained and the results revealed distinct compositions and diversities of gut microbiota in four trophic categories. PCoA test showed that gut bacterial communities of carnivorous and herbivorous fishes formed distinctly different clusters in PCoA space. Although fish in different trophic levels shared a large size of OTUs comprising a core microbiota community, at the genus level a strong distinction existed. Cellulose-degrading bacteria Clostridium, Citrobacter and Leptotrichia were dominant in the herbivorous, while Cetobacterium and protease-producing bacteria Halomonas were dominant in the carnivorous. PICRUSt predictions of metagenome function revealed that fishes in different trophic levels affected the metabolic capacity of their gut microbiota. Moreover, cellulase and amylase activities in herbivorous fishes were significantly higher than in the carnivorous, while trypsin activity in the carnivorous was much higher than in the herbivorous. These results indicated that host trophic level influenced the structure and composition of gut microbiota, metabolic capacity and gut content enzyme activity.

PMID: 27072196 PMCID: PMC4829839 DOI: 10.1038/srep24340

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Select item 27057545

 

23.

Biomed Res Int. 2016;2016:6598307. doi: 10.1155/2016/6598307. Epub 2016 Feb 14.

Motif-Based Text Mining of Microbial Metagenome Redundancy Profiling Data for Disease Classification.

Wang Y1, Li R2, Zhou Y3, Ling Z4, Guo X3, Xie L5, Liu L1.

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Abstract

BACKGROUND:

Text data of 16S rRNA are informative for classifications of microbiota-associated diseases. However, the raw text data need to be systematically processed so that features for classification can be defined/extracted; moreover, the high-dimension feature spaces generated by the text data also pose an additional difficulty.

RESULTS:

Here we present a Phylogenetic Tree-Based Motif Finding algorithm (PMF) to analyze 16S rRNA text data. By integrating phylogenetic rules and other statistical indexes for classification, we can effectively reduce the dimension of the large feature spaces generated by the text datasets. Using the retrieved motifs in combination with common classification methods, we can discriminate different samples of both pneumonia and dental caries better than other existing methods.

CONCLUSIONS:

We extend the phylogenetic approaches to perform supervised learning on microbiota text data to discriminate the pathological states for pneumonia and dental caries. The results have shown that PMF may enhance the efficiency and reliability in analyzing high-dimension text data.

PMID: 27057545 PMCID: PMC4769744 DOI: 10.1155/2016/6598307

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Select item 27055030

 

24.

PLoS One. 2016 Apr 7;11(4):e0153215. doi: 10.1371/journal.pone.0153215. eCollection 2016.

Age-Related Differences in the Gastrointestinal Microbiota of Chinstrap Penguins (Pygoscelis antarctica).

Barbosa A1, Balagué V2, Valera F3, Martínez A4, Benzal J3, Motas M5, Diaz JI6, Mira A7, Pedrós-Alió C2.

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Abstract

The gastrointestinal tract microbiota is known to play very important roles in the well being of animals. It is a complex community composed by hundreds of microbial species interacting closely among them and with their host, that is, a microbial ecosystem. The development of high throughput sequencing techniques allows studying the diversity of such communities in a realistic way and considerable work has been carried out in mammals and some birds such as chickens. Wild birds have received less attention and in particular, in the case of penguins, only a few individuals of five species have been examined with molecular techniques. We collected cloacal samples from Chinstrap penguins in the Vapour Col rookery in Deception Island, Antarctica, and carried out pyrosequencing of the V1-V3 region of the 16S rDNA in samples from 53 individuals, 27 adults and 26 chicks. This provided the first description of the Chinstrap penguin gastrointestinal tract microbiota and the most extensive in any penguin species. Firmicutes, Bacteoridetes, Proteobacteria, Fusobacteria, Actinobacteria, and Tenericutes were the main components. There were large differences between chicks and adults. The former had more Firmicutes and the latter more Bacteroidetes and Proteobacteria. In addition, adults had richer and more diverse bacterial communities than chicks. These differences were also observed between parents and their offspring. On the other hand, nests explained differences in bacterial communities only among chicks. We suggest that environmental factors have a higher importance than genetic factors in the microbiota composition of chicks. The results also showed surprisingly large differences in community composition with other Antarctic penguins including the congeneric Adélie and Gentoo penguins.

PMID: 27055030 PMCID: PMC4824521 DOI: 10.1371/journal.pone.0153215

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Select item 27052710

 

25.

Food Microbiol. 2016 Aug;57:116-27. doi: 10.1016/j.fm.2016.02.004. Epub 2016 Feb 18.

Metagenomic analysis of a Mexican ripened cheese reveals a unique complex microbiota.

Escobar-Zepeda A1, Sanchez-Flores A2, Quirasco Baruch M3.

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Abstract

Cotija cheese is a Mexican handcrafted product made from raw cow milk whose ripening process occurs spontaneously and, presumably, it is influenced by environmental conditions. Its sensory characteristics and safety are probably the result of the balance between microbial populations and their metabolic capacity. In this work, we studied the dominance and richness of the bacteria in the Cotija cheese microbiome, as well as their metabolic potential by high-throughput sequencing. By the analysis of 16S ribosomal sequences, it was found that this metagenome is composed mainly of three dominant genera: Lactobacillus, Leuconostoc and Weissella, and more than 500 of non-dominant genera grouped in 31 phyla of both bacteria and archaea. The analysis of single-copy marker genes reported a similar result for dominant genera, although with greater resolution that reached the species level. Pathogenic bacteria such as Salmonella, Listeria monocytogenes, Brucella or Mycobacterium were not found. The Cotija cheese microbiome has the metabolic capacity for the synthesis of a wide range of flavor compounds, mainly involved with the metabolism of branched chain amino acids and free fatty acids. Genes associated with bacteriocin production and immunity were also found. Arguably, this is one of the most diverse metagenomes among the microbial communities related to fermented products.

Copyright © 2016 Elsevier Ltd. All rights reserved.

KEYWORDS:

Bacteriocins; Fermented food metagenomics; High-throughput sequencing; Lactic acid bacteria; Raw-milk ripened cheese

PMID: 27052710 DOI: 10.1016/j.fm.2016.02.004

[PubMed - in process]

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Select item 27048805

 

26.

MBio. 2016 Apr 5;7(2):e02234-15. doi: 10.1128/mBio.02234-15.

Lateral Gene Transfer in a Heavy Metal-Contaminated-Groundwater Microbial Community.

Hemme CL1, Green SJ2, Rishishwar L3, Prakash O4, Pettenato A5, Chakraborty R5, Deutschbauer AM6, Van Nostrand JD7, Wu L7, He Z7, Jordan IK8, Hazen TC9, Arkin AP10, Kostka JE3, Zhou J11.

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Abstract

Unraveling the drivers controlling the response and adaptation of biological communities to environmental change, especially anthropogenic activities, is a central but poorly understood issue in ecology and evolution. Comparative genomics studies suggest that lateral gene transfer (LGT) is a major force driving microbial genome evolution, but its role in the evolution of microbial communities remains elusive. To delineate the importance of LGT in mediating the response of a groundwater microbial community to heavy metal contamination, representative Rhodanobacter reference genomes were sequenced and compared to shotgun metagenome sequences. 16S rRNA gene-based amplicon sequence analysis indicated that Rhodanobacter populations were highly abundant in contaminated wells with low pHs and high levels of nitrate and heavy metals but remained rare in the uncontaminated wells. Sequence comparisons revealed that multiple geochemically important genes, including genes encoding Fe(2+)/Pb(2+) permeases, most denitrification enzymes, and cytochrome c553, were native to Rhodanobacter and not subjected to LGT. In contrast, the Rhodanobacter pangenome contained a recombinational hot spot in which numerous metal resistance genes were subjected to LGT and/or duplication. In particular, Co(2+)/Zn(2+)/Cd(2+) efflux and mercuric resistance operon genes appeared to be highly mobile within Rhodanobacter populations. Evidence of multiple duplications of a mercuric resistance operon common to most Rhodanobacter strains was also observed. Collectively, our analyses indicated the importance of LGT during the evolution of groundwater microbial communities in response to heavy metal contamination, and a conceptual model was developed to display such adaptive evolutionary processes for explaining the extreme dominance of Rhodanobacter populations in the contaminated groundwater microbiome.

IMPORTANCE:

Lateral gene transfer (LGT), along with positive selection and gene duplication, are the three main mechanisms that drive adaptive evolution of microbial genomes and communities, but their relative importance is unclear. Some recent studies suggested that LGT is a major adaptive mechanism for microbial populations in response to changing environments, and hence, it could also be critical in shaping microbial community structure. However, direct evidence of LGT and its rates in extant natural microbial communities in response to changing environments is still lacking. Our results presented in this study provide explicit evidence that LGT played a crucial role in driving the evolution of a groundwater microbial community in response to extreme heavy metal contamination. It appears that acquisition of genes critical for survival, growth, and reproduction via LGT is the most rapid and effective way to enable microorganisms and associated microbial communities to quickly adapt to abrupt harsh environmental stresses.

Copyright © 2016 Hemme et al.

PMID: 27048805 PMCID: PMC4817265 DOI: 10.1128/mBio.02234-15

[PubMed - in process] Free PMC Article

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17.

Colorectal Dis. 2016 Sep 27. doi: 10.1111/codi.13534. [Epub ahead of print]

A collaborative study of the current concepts and challenges for treatment of anastomotic leakage in colorectal surgery.

Vallance A1,2, Wexner S3, Berho M4, Cahill R5, Coleman M6, Haboubi N7, Heald RJ8, Kennedy RH9, Moran B8, Mortensen N2, Motson RW10, Novell R11, O'Connell PR5, Ris F12, Rockall T13, Senapati A14, Windsor A15, Jayne DG16.

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Abstract

The reduction of the incidence, detection, and treatment of anastomotic leakage (AL) continues to challenge the colorectal surgical community. AL is not consistently defined and reported in clinical studies, its occurrence is variably reported and its impact on long-term morbidity and healthcare resources has received relatively little attention. Controversy continues about the best strategies to reduce the risk. Diagnostic tests lack sensitivity and specificity, resulting in delayed diagnosis and increased morbidity. Intraoperative fluorescence angiography has recently been introduced as a means of real-time assessment of anastomotic perfusion with preliminary evidence suggesting that it may reduce the rate of AL. In addition, concepts are emerging about the role of the rectal mucosal microbiome in AL and the possible role of new prophylactic therapies. In January 2016 a meeting of expert colorectal surgeons and pathologists was held in London, UK to identify the ongoing controversies surrounding AL in colorectal surgery. The outcome of the meeting is presented in the form of research challenges that need to be addressed. This article is protected by copyright. All rights reserved.

This article is protected by copyright. All rights reserved.

PMID: 27671222 DOI: 10.1111/codi.13534

 

16s rRNA Sequencing with MR DNA

16S ribosomal  (rRNA) sequencing using next generation sequencing is a method used to identify and compare bacteria and archaea present within almost any type of sample. 16S rRNA gene sequencing is a well-established method for studying phylogeny and taxonomy of samples from complex microbiomes or environments that are difficult or impossible to study.

 

 

 

 

16s sequencing illumina or PGM low cost prices with MR DNA

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Select item 27670882

 

19.

Sci Rep. 2016 Sep 27;6:33965. doi: 10.1038/srep33965.

Probiotic legacy effects on gut microbial assembly in tilapia larvae.

Giatsis C1, Sipkema D2, Ramiro-Garcia J2,3,4, Bacanu GM2, Abernathy J5, Verreth J1, Smidt H2, Verdegem M1.

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Abstract

The exposure of fish to environmental free-living microbes and its effect on early colonization in the gut have been studied in recent years. However, little is known regarding how the host and environment interact to shape gut communities during early life. Here, we tested whether the early microbial exposure of tilapia larvae affects the gut microbiota at later life stages. The experimental period was divided into three stages: axenic, probiotic and active suspension. Axenic tilapia larvae were reared either under conventional conditions (active suspension systems) or exposed to a single strain probiotic (Bacillus subtilis) added to the water. Microbial characterization by Illumina HiSeq sequencing of 16S rRNA gene amplicons showed the presence of B. subtilis in the gut during the seven days of probiotic application. Although B. subtilis was no longer detected in the guts of fish exposed to the probiotic after day 7, gut microbiota of the exposed tilapia larvae remained significantly different from that of the control treatment. Compared with the control, fish gut microbiota under probiotic treatment was less affected by spatial differences resulting from tank replication, suggesting that the early probiotic contact contributed to the subsequent observation of low inter-individual variation.

PMID: 27670882 DOI: 10.1038/srep33965

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Select item 27670644

 

20.

Mol Nutr Food Res. 2016 Sep 27. doi: 10.1002/mnfr.201600552. [Epub ahead of print]

Reduction in cardiometabolic risk factors by a multifunctional diet is mediated via several branches of metabolism as evidenced by non-targeted metabolite profiling approach.

Tovar J1, de Mello VD2, Nilsson A3, Johansson M3, Paananen J2, Lehtonen M4, Hanhineva K2, Björck I3.

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Abstract

SCOPE:

MFD, a diet based on multiple functional concepts and ingredients with antiinflammatory activity, was previously shown to improve different cardiometabolic risk-associated markers in healthy subjects. Here, we assessed the impact of MFD on plasma metabolome and explored associations of the differential metabolites with clinical parameters, searching for metabolic determinants related to the effects of MFD.

METHODS AND RESULTS:

Forty-four overweight healthy volunteers completed a randomized crossover intervention comparing MFD with a control diet devoid of the active components of MFD. Fasting plasma samples were analyzed with non-targeted metabolite profiling at baseline and at the end (4 wk) of each diet period by liquid chromatography coupled to quadrupole-time of flight-MS system, revealing a vast impact of MFD on metabolic homeostasis. Main metabolite classes affected included acylcarnitines, furan fatty acids, phospholipids (plasmalogens, phosphatidylcholines, phosphatidylethanolamines), and various low-molecular weight products from the bioactivity of gut microbiota. Circulating levels of several of these metabolites correlated with changes in clinical blood lipid biomarkers.

CONCLUSIONS:

The metabolomics approach revealed that consumption of MFD affected different areas of metabolism, highlighting the impact of a healthy diet on plasma metabolome. This seems linked to reduced cardiometabolic risk and provides mechanistic insight into the effects of MFD. This article is protected by copyright. All rights reserved.

This article is protected by copyright. All rights reserved.

KEYWORDS:

Cardiometabolic diseases; Dietary prevention; Functional foods; Metabolic syndrome; Plasma metabolomics

PMID: 27670644 DOI: 10.1002/mnfr.201600552

[PubMed - as supplied by publisher]

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16s rRNA Sequencing with MR DNA

16S ribosomal  (rRNA) sequencing using next generation sequencing is a method used to identify and compare bacteria and archaea present within almost any type of sample. 16S rRNA gene sequencing is a well-established method for studying phylogeny and taxonomy of samples from complex microbiomes or environments that are difficult or impossible to study.

 

 

 

 

16s sequencing illumina or PGM low cost prices with MR DNA

MR DNA is a next generation sequencing provider with low cost 16s sequencing services.

 

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