ライフサイエンスコーパス: metagenomic

1 sequencing DNA directly from an environment (metagenomics).

2 BRA bacterial community structure (V3V4 16 S metagenomics).

3 tance of detailed profiling methods, such as metagenomics.

4 biome alterations in ACLF using quantitative metagenomics.

5 s the increasing number of disciplines using metagenomics.

6 ture as evidenced by amplicon sequencing and metagenomics.

7 target-specific polymerase chain reaction or metagenomics.

8 obing, Raman-activated cell sorting and mini-metagenomics.

9 approaches from other fields to the field of metagenomics.

10 ence genome, limiting the potential of whole metagenomics.

11 We addressed this using RNA sequencing metagenomics(4-6) of placental samples from normal and c

12 Here we show, using metagenomics, a high temperature oil reservoir of marine

13 Metagenomic analyses of the reactor communities revealed

14 Genome-resolved microbial metagenomic analyses revealed reductions in genes, micro

15 16S metagenomic analyses revealed robust and significant eff

16 ity of PhyloPhlAn 3.0 to support genomic and metagenomic analyses.

17 Metagenomic analysis and gene expression studies reveal

18 Metagenomic analysis did not reveal significant differen

19 Shotgun metagenomic analysis functionally linked 26 metabolic pa

20 ls and compared to culture results and prior metagenomic analysis interpretation.

21 We carried out a metagenomic analysis of stations of the Tara Oceans expe

22 in chronic respiratory disease.Conclusions: Metagenomic analysis of the airway reveals a core macrol

23 In this study, we combine metagenomic analysis with (14) C-labelling to investigat

24 From metagenomic analysis, genes encoding ferritin, flavodoxi

25 of SSaDV with SSWS was originally drawn from metagenomic analysis, which was further studied through

26 A metagenomics analysis developed in under a week recovere

27 Using deep shotgun stool metagenomics analysis, we found a rapid increase in gut

28 chaeota by the use of a combination of viral metagenomic and bioinformatic approaches.

29 Metagenomic and metabolomic analyses of stool samples fr

30 Furthermore, metagenomic and metatranscriptomic analyses reveal a com

31 Analysis of metagenomic and metatranscriptomic data is complicated a

32 e sequencing of colon biopsies, coupled with metagenomic and metatranscriptomic sequencing of feces.

33 Cell Host & Microbe, Galvez et al. employed metagenomic and phylogenetic analysis to systemically ch

34 dy this "resource-driven selection" by using metagenomic and single-cell data of marine microbes, alo

35 ed and fecal DNA was sequenced using shotgun metagenomics and analyzed with specifically designed bio

36 microbial composition by performing shotgun metagenomics and de novo assembly of metagenome-assemble

37 Further metagenomics and metabolomic studies found that the hypo

38 By integrating paired metagenomics and metabolomics data from existing cohorts

39 lyzing 16S rRNA microbial profiling, shotgun metagenomics and SCFAs in 153 fecal samples from non-kid

40 and blood culture specimens, next-generation metagenomics, and gas chromatography mass spectrometry.

41 Our metagenomic approach may be extended to other metabolite

42 and environmentally-validated a quantitative metagenomic approach to mine for phenazine biosynthesis

43 y labeled genomes relative to a conventional metagenomic approach.

44 s new method complements virus culturing and metagenomic approaches and its advantages include target

45 Shotgun metagenomics approaches additionally can provide informa

46 iscuss how uHTS can inspire novel functional metagenomics approaches to identify natural biocatalysts

47 tions of targeted amplicon and shotgun-based metagenomics approaches to infectious disease diagnostic

48 s review, we highlight the benefits of using metagenomics as well as the breadth of conclusions that

49 attention, but the recovery of high-quality metagenomic assembled eukaryotic genomes is limited by t

50 view, we describe the challenges inherent in metagenomic assemblies and compare the different approac

51 tured bacterial genomes (reconstructed using metagenomic assembly and binning) associated with the ma

52 etaFlye, which addresses important long-read metagenomic assembly challenges, such as uneven bacteria

53 Here, we leverage metagenomic assembly followed by a reference-based binni

54 SPAdes tool for identifying viral genomes in metagenomic assembly graphs that is based on analyzing v

55 -ecosystem experiments to involve replicated metagenomic assessment.

56 A growing number of metagenomics-based approaches have been used for the dis

57 s should lead to (i) fundamental advances in metagenomic binning, (ii) development and refinement of

58 These results indicate that 16S V1-V2 metagenomics can greatly simplify diagnosis and accelera

59 Genome-resolved metagenomics can help unravel these complex interactions

60 genomics and subsequently as genome-resolved metagenomics, can circumvent this limitation by obtainin

61 detection in plasma samples using unbiased metagenomic cfDNA sequencing performed by a commercial l

62 ification faster than the existing Markovian metagenomic classifiers and can therefore be used as a s

63 quencing of known bacterial genomes within a metagenomics community, enriching the remaining species

64 Metagenomics confirmed M. smithii in five blood samples,

65 d models (ZINBMMs) for modeling longitudinal metagenomic count data and a fast EM-IWLS algorithm for

66 ach to analyze high-dimensional longitudinal metagenomic count data.

67 al content, while highlighting challenges of metagenomic data analysis.

68 In this study we mine metagenomic data and identify a clade of Caudovirales th

69 in the APM clade by using transcriptomic and metagenomic data and performed phylogenomic analyses to

70 pipeline designed to take unfiltered shotgun metagenomic data as input and generate functional profil

71 t was the most likely viral candidate in the metagenomic data based on its representation in symptoma

72 eqs streamlines access to publicly available metagenomic data by providing a single, easy-to-use inte

73 Here, we analyze gut metagenomic data from mother-infant pairs and patients u

74 ve database that integrates existing genomic/metagenomic data from oil environments with physicochemi

75 However, shotgun metagenomic data from treatment-naive patients are scarc

76 ypically as members of the rare biosphere in metagenomic data from uncontaminated field samples, impl

77 MGnify's growing focus on the assembly of metagenomic data has also seen the number of datasets it

78 Functional annotation of shotgun metagenomic data has become an increasingly popular meth

79 Microbiome/metagenomic data have specific characteristics, includin

80 ictive models for phenotype predictions from metagenomic data rely on alignments, assembly, extensive

81 There has been an explosion of metagenomic data representing human, animal, and environ

82 proteins from large and giant viruses using metagenomic data revealed the global distribution patter

83 Genomes computationally inferred from large metagenomic data sets are often incomplete and may be mi

84 se advances have not directly transferred to metagenomic data sets, as assumptions made by the single

85 iophage genome or phage-derived sequences in metagenomic data sets, we are unable to assign a functio

86 do display a higher likelihood of accessible metagenomic data sets.

87 of plasmid sequences and refined analysis of metagenomic data to read error correction and reference-

88 art by the wide range of analytic models and metagenomic data types available.

89 oblem of predicting human disease from whole-metagenomic data using Multiple Instance Learning (MIL),

90 The development of dedicated assemblers for metagenomic data was a relatively late innovation and fo

91 We reexamined the original metagenomic data with additional genomic data sets and f

92 of densoviruses with SSWS, we compiled past metagenomic data with new metagenomic-derived viral geno

93 o be inundated by ever increasing amounts of metagenomic data, the need for data analysis approaches

94 ro based on protein sequences recovered from metagenomic data.

95 ariants by systematically mining genomic and metagenomic data.

96 ne learning methods and 4 different types of metagenomic data.

97 cessed multilevel or longitudinal microbiome/metagenomic data.

98 provides useful tools for complex microbiome/metagenomics data analysis.

99 Next, we used our methods to analyze metagenomics data from 13 human stool samples.

100 address the main challenges of longitudinal metagenomics data, i.e. high-dimensionality, dependence

101 Longitudinal metagenomics data, including both 16S rRNA and whole-met

102 models (8th order or lower) was performed on metagenomic datasets constructed using sequenced prokary

103 inning, and apply it to a time series of 100 metagenomic datasets from seven connected lakes and estu

104 However, assembling complex metagenomic datasets remains difficult even for state-of

105 ic read assemblers by mixing reads from real metagenomic datasets with reads from known genomes and e

106 rial genomes from both cultured isolates and metagenomic datasets, revealing thousands of encoded ant

107 We benchmarked MetaviralSPAdes on diverse metagenomic datasets, verified our predictions using a s

108 uences, recovered from 29 planktonic shotgun metagenomic datasets.

109 , we compiled past metagenomic data with new metagenomic-derived viral genomes from sea stars collect

110 Microdissection could be a key to the metagenomic diagnosis of infectious diseases when a micr

111 One of the most impactful metagenomic discoveries is that of crAssphage, the most

112 plore the application of these techniques to metagenomics, discuss their pros and cons, and speculate

113 associated with integrons in saliva-derived metagenomic DNA of healthy human volunteers, two novel v

114 t MA-ARB from human gut microbiota, and mini-metagenomic DNA of the sorted bacteria was amplified, se

115 Have you ever sought to use metagenomic DNA sequences reported in scientific publica

116 Bioaerosols were analyzed by metagenomic DNA sequencing and traditional culturing met

117 ular genome, which can be crucial when using metagenomics experiments for pathogen detection.

118 nical laboratories are evaluating the use of metagenomics for identification of infectious agents dir

119 HOMs outperform other models in classifying metagenomic fragments as short as 100 nt at all taxonomi

120 MetaLAFFA is a new end-to-end metagenomic functional annotation pipeline with distribu

121 Currently available metagenomic functional annotation pipelines, however, su

122 unities, compared with the relatively stable metagenomic functional potential, suggests that microbio

123 The rise in metagenomics has led to an exponential growth in virus d

124 Over the past 2 years, MGnify (formerly EBI Metagenomics) has more than doubled the number of public

125 on exists, although single-cell genomics and metagenomics have alleviated some of this bottleneck.

126 Advances in metagenomics have associated inflammatory and autoimmune

127 ful culture-independent tools, in particular metagenomics, have substantially advanced virus discover

128 Metagenomics identified more than 22,000 gene families t

129 Metagenomic inferences of bacterial strain diversity and

130 bial life in hydrothermal deposits and their metagenomics-inferred physiology in light of the geologi

131 Metagenomics is challenging in samples dominated by host

132 Metagenomics is currently the primary means for identify

133 Metagenomics is the collective DNA sequencing of coexist

134 efficiently isolate novel biocatalysts from metagenomic libraries by processing single cells as many

135 sphatases from genomic DNA or recovered from metagenomic libraries or genes synthesized in vitro base

136 ed the power of this platform by screening a metagenomic library constructed from domestic running wa

137 In 2019, screening of a metagenomic library derived from the feces of an AB dono

138 d during functional screening of a human gut metagenomic library using Lactococcus lactis MG1363 as h

139 Combining DNA-SIP and metagenomics (metagenomic-SIP) allows us to link genomes

140 We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and me

141 Despite advances in shotgun whole-genome metagenomic methods, oral bacterial community profiling

142 genomic information from isolated bacteria, metagenomic microbial findings from primary specimens, m

143 Our findings show that metagenomic Nanopore sequencing can provide reliable dia

144 Plasma metagenomic next-generation sequencing (mNGS) is a new d

145 ative septic transfusion cases, we performed metagenomic next-generation sequencing (mNGS) of direct

146 Metagenomic next-generation sequencing (mNGS) of plasma

147 Metagenomic next-generation sequencing (mNGS) of RNA and

148 RNA metagenomic next-generation sequencing (mNGS) offers an

149 We developed a metagenomic next-generation sequencing (mNGS) test using

150 Metagenomic next-generation sequencing (mNGS), the shotg

151 Metagenomic next-generation sequencing for infectious di

152 This work used shotgun metagenomics of mucosal biopsies to explore the microbia

153 ersity of MDV protists, we performed shotgun metagenomics on 18 sites representing a variety of lands

154 Metagenomic pathway analysis identified steroid biosynth

155 chanistic understanding of the classes using metagenomic predictions (PiCRUST).

156 Metagenomic predictions based on 16S rRNA gene profiling

157 We aimed to build robust metagenomic predictors of host phenotype by comparing pr

158 Metagenomic profiling, predicting the presence and relat

159 forms efficient and accurate alignment-based metagenomic profiling.

160 benefits and limitations of using different metagenomic protocols, discuss the relative merits of va

161 rom isolate genomes, but culture-independent metagenomics provide a new window into their diversity.

162 While faecal metagenomics provided a good approximation of the averag

163 es, including the Sequence Read Archive, the Metagenomics Rapid Annotation through Subsystems Technol

164 In this paper, we benchmark the metagenomic read assemblers by mixing reads from real me

165 ), 97% were found in each sample (by >98% ID metagenomic read recruitment) to have relative abundance

166 ied via culturing, single-gene diversity and metagenomic read survey methods that are limited by cult

167 We found that the metagenomic relative abundance ratio of bacteria-to-fung

168 tial first step for the follow-up studies in metagenomic research.

169 , thus promoting convenient and reproducible metagenomics research.

170 plates on which to conduct culture-enriched metagenomics, resulting in the recovery of greater taxon

171 eting different biomolecules, including DNA (metagenomics), RNA (metatranscriptomics) and proteins (m

172 ms of a given gene across all organisms in a metagenomic sample would aid evolutionary and ecological

173 ped to facilitate the analysis of AMR within metagenomic samples (i.e. the resistome).

174 disentangling the N. gonorrhoeae genome from metagenomic samples and robustly identifying antimicrobi

175 ets may not reflect the real complexities of metagenomic samples and the estimated assembly accuracy

176 ghput genome sequencing of both isolates and metagenomic samples combined with the development of spe

177 lity to incorporate raw data, including some metagenomic samples containing a target organism (e.g. f

178 ongle flow cells) with NanoOK RT can process metagenomic samples to a rich dataset in < 5 h, which cr

179 ach to isolate and sequence gene clusters in metagenomic samples using microfluidic automated plasmid

180 a small fraction of genomic material in most metagenomic samples, it remains challenging to deeply se

181 ncing data set to quantify distances between metagenomics samples from various human body habitats, N

182 reen, and targeted and untargeted functional metagenomic screens to identify microbiome-encoded genes

183 ral sequences while simultaneously retaining metagenomic sensitivity for other pathogens.

184 gut microbiome 16S rRNA amplicon and shotgun metagenomic sequence data with quantification of pathoge

185 lassifiers for more robust classification of metagenomic sequences.

186 relied upon for taxonomic classification of metagenomic sequences.

187 nd assessed their performance in classifying metagenomic sequences.

188 re quantified with 16S rRNA gene and shotgun metagenomic sequencing (n = 101 six weeks, n = 103 one y

189 We performed shotgun metagenomic sequencing analyses of feces from wild-type

190 In addition, 18S rRNA metabarcoding and metagenomic sequencing analysis allowed the first descri

191 hanges in the gut microbiome, as measured by metagenomic sequencing and 16s ribosomal RNA.

192 Short-read metagenomic sequencing and de novo genome assembly of th

193 biome composition and function using shotgun metagenomic sequencing and phenotypes of T cells in bloo

194 anoOK RT software package to perform shotgun metagenomic sequencing and profile mock communities and

195 re, we examined metrics derived from shotgun metagenomic sequencing and relationship to human fecal m

196 ividuals in Guangdong using a combination of metagenomic sequencing and tiling amplicon approaches.

197 Shotgun metagenomic sequencing and untargeted metabolomics were

198 known natural reservoirs of filoviruses, and metagenomic sequencing can be the key to the discovery o

199 Shotgun metagenomic sequencing can detect nucleic acids from bac

200 Metagenomic sequencing combined with Oxford Nanopore Tec

201 eproducible pipelines for analyzing Nanopore metagenomic sequencing data are still lacking.

202 orrhoeae diagnostic workflow for analysis of metagenomic sequencing data obtained from clinical sampl

203 tool for the quantification of strains from metagenomic sequencing data, enabling the identification

204 ous contexts - in particular the analysis of metagenomic sequencing data.

205 tatives of four viral lineages only found in metagenomic sequencing datasets previously.

206 is is essential to decide the sample size of metagenomic sequencing experiments in a case-control stu

207 Here we demonstrate the power of metagenomic sequencing for identifying ongoing outbreaks

208 Shotgun metagenomic sequencing has revolutionized our ability to

209 Recent advances in metagenomic sequencing have enabled discovery of diverse

210 Shotgun metagenomic sequencing identified 144 AMR genes in total

211 Targeted metagenomic sequencing is an evolving method to detect m

212 However, metagenomic sequencing is needed to identify the genetic

213 De novo assembly of metagenomic sequencing obtained 527 metagenome-assembled

214 Metagenomic sequencing of 39 viral genomes suggested tha

215 We performed shotgun metagenomic sequencing of five stages of pulque fermenta

216 We have previously shown metagenomic sequencing of urine samples from men with ur

217 gin of these viral populations using shotgun metagenomic sequencing of virus-enriched preparations an

218 We performed shotgun metagenomic sequencing of virus-like particles.

219 Here we performed viral metagenomic sequencing on 3 serially collected stool sam

220 While high throughput metagenomic sequencing reveals genotypes of microbial co

221 retrospectively reviewed results of shotgun metagenomic sequencing testing requested on cerebrospina

222 sease, and bronchiectasis) were subjected to metagenomic sequencing to an average depth exceeding 20

223 In this study, we used shotgun metagenomic sequencing to characterise the microbial met

224 Here, we used isotopic rate measurements and metagenomic sequencing to study how cross-feeding relati

225 sing differential filtration techniques, and metagenomic sequencing was performed to characterize int

226 Shotgun metagenomic sequencing was used to measure the microbial

227 PCR, 16S rRNA gene metabarcoding and shotgun metagenomic sequencing were used to track faecal AMR gen

228 e, Osun State, Nigeria, where we carried out metagenomic sequencing which implicated yellow fever vir

229 Here, we combine advances in amplicon and metagenomic sequencing with culture-enriched molecular p

230 Here, we developed metagenomic sequencing with spiked primer enrichment (MS

231 e communities are often examined via shotgun metagenomic sequencing, a technology which can offer uni

232 ng bacterial sequences than standard shotgun metagenomic sequencing, and is able to successfully reco

233 Advances in metagenomic sequencing, coupled with bioinformatics tool

234 d 16S ribosomal RNA gene sequencing, shotgun metagenomic sequencing, in vitro functional assays, and

235 uch as reverse transcription PCR or unbiased metagenomic sequencing, is limited to the minority of pa

236 Here, a combination of metagenomic sequencing, metabolomic profiling, and epifl

237 Using metagenomic sequencing, we recapitulated the effects of

238 harles Chiu discuss the pros of using direct metagenomic sequencing, while Kyle Rodino and Melissa Mi

239 rom the first year after birth using shotgun metagenomic sequencing.

240 biome, we used 16S ribosomal RNA and shotgun metagenomic sequencing.

241 ymerase chain reaction and 16S ribosomal RNA metagenomic sequencing.

242 ic and gene abundances of short-read shotgun metagenomics sequencing data.

243 e gut microbiota was analyzed using 16S rRNA metagenomics sequencing.

244 are based on targeted amplicon and unbiased metagenomic shotgun NGS approaches.

245 Metagenomic shotgun sequencing for the identification of

246 Three commercial metagenomic shotgun sequencing tools, CosmosID, One Code

247 ents with IBD without PSC, were subjected to metagenomic shotgun sequencing, generating 17 billion pa

248 uct more definitive microbial analyses using metagenomic shotgun sequencing.

249 nd environmental microbiomes using ultradeep metagenomic shotgun sequencing.Methods: Airway specimens

250 MetaSIPSim allows for simulation of metagenomic-SIP datasets which facilitates the optimizat

251 ity is isotopically labeled, the benefits of metagenomic-SIP decline.

252 ilitates the optimization and development of metagenomic-SIP experiments and analytical approaches fo

253 ,' to simulate sequencing read libraries for metagenomic-SIP experiments.

254 Through simulation we show that metagenomic-SIP improves the assembly and binning of iso

255 Metagenomic-SIP is a valuable method for recovering isot

256 However, empirical development of metagenomic-SIP methods is hindered by the complexity an

257 We show that metagenomic-SIP performance depends on optimization of e

258 Combining DNA-SIP and metagenomics (metagenomic-SIP) allows us to link genomes from complex

259 nity G + C generally reduced the benefits of metagenomic-SIP.

260 genes were grouped into clusters, denoted as metagenomic species.

261 specificity for S. pneumoniae) for clinical metagenomic sputum samples.

262 valuate our method on well-known large-scale metagenomic studies and show that our proposed approach

263 Many microbiome/metagenomic studies follow a longitudinal design to coll

264 ntly contributed to this field, ranging from metagenomic studies in humans and mechanistic studies of

265 In metagenomic studies of microbial communities, the short

266 In addition, lung metagenomic studies on infected patients revealed overre

267 New metagenomic studies vastly expanded the crAss-like phage

268 lowing researchers to easily apply Seeker in metagenomic studies, for the detection of diverse unknow

269 chnology hold the key to the success of most metagenomic studies.

270 to evaluate the various read assemblers for metagenomic studies.

271 istics and the complex designs in microbiome/metagenomic studies.

272 Metagenomics studies microbial genomes in an ecosystem s

273 Motivated by microbiome and metagenomics studies, where the data are often over-disp

274 hich is a more prevalent type of data set in metagenomics studies.

275 Here we report a comparative metagenomic study of microbial response to natural hydro

276 Here, we performed a longitudinal metagenomic survey of 106 samples of airborne PM(2.5) an

277 Metagenomic surveys have revealed that partitivirus-like

278 theory and the complex dynamics observed in metagenomic surveys.

279 A29 status, likely due to differences in the metagenomic techniques employed.

280 Metagenomic techniques have enabled genome sequencing of

281 ated in Northern Portugal were studied using metagenomic techniques.

282 By coupling metagenomics to a predictive atmospheric model, we aim t

283 lenging cases demonstrated the potential for metagenomics to advance existing methods for investigati

284 At these sites, we used shotgun metagenomics to characterize microorganisms with the Hg-

285 we combined 16S rRNA sequencing and shotgun metagenomics to characterize the whole-organism microbio

286 We used amplicon targeted metagenomics to compare microbial communities from EDC a

287 Furthermore, it demonstrates the power of metagenomics to glean large amounts of comparative data

288 Here we use functional metagenomics to investigate the community composition an

289 g spatial variation in host tolerance, using metagenomics to quantify spatial variation in parasite p

290 n of metatranscriptomics and genome-resolved metagenomics to study microbial activities in oil-contam

291 Deep shotgun metagenomics unveiled distinct ecological niches of micr

292 Targeted metagenomics using strand-specific libraries with target

293 tend the knowledge gained in human gut virus metagenomics (viromics) to disentangle the potential rol

294 Functional metagenomics was performed using PICRUSt.

295 Using metagenomics, we identified 17 novel viruses in Clinch R

296 Using genome-resolved metagenomics, we identified organisms with hgcA (hgcA+)

297 ives on in the age of microbial genomics and metagenomics, we propose an automated approach, employin

298 s, Nubeam is ideal to analyze data sets from metagenomics whole genome shotgun (WGS) sequencing, wher

299 Quasi-metagenomics with nanopore sequencing provided thousands

300 CDS platform is a robust tool for functional metagenomics, with the potential to significantly improv