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Gs flx pyrosequencer

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The GS-FLX pyrosequencer is a DNA sequencing instrument developed by Roche. It utilizes pyrosequencing technology to determine the nucleotide sequence of DNA samples. The core function of the GS-FLX pyrosequencer is to perform high-throughput DNA sequencing.

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Lab products found in correlation

Purelink viral rna mini kit, by Thermo Fisher Scientific (1 mentions) Rna dna masterpure extraction kit, by Illumina (1 mentions) High capacity cdna reverse transcription kit, by Thermo Fisher Scientific (1 mentions)

5 protocols using gs flx pyrosequencer

1

RNA Extraction and NGS Sequencing Protocol

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Viral RNAs were extracted from the supernatant of infected VERO cells using the PureLink Viral RNA Mini Kit (Invitrogen, USA) following the manufactures instructions. Then, the strands of the RNA synthesis were performed using the kit cDNA Synthesis System and 400 μM Roche “random” Primer according to the manufacturer’s instructions. The cDNAs were prepared for HTS on a GS FLX+ pyrosequencer (Roche, 454 Life Sciences) at the Center for Technological Innovation at the Evandro Chagas Institute, Ministry of Health, Brazil. The de novo assembling strategy applied to obtain the genomes was used with program Newbler v. 3.0 [11 (link)]. Additionally, sequences for terminal untranslated regions (UTRs) were determined by 5’/3’ rapid amplification of cDNA ends (RACE) sequencing (S1 Table) [12 (link)].
Nunes M.R., de Souza W.M., Acrani G.O., Cardoso J.F., da Silva S.P., Badra S.J., Figueiredo L.T, & Vasconcelos P.F. (2018). Revalidation and genetic characterization of new members of Group C (Orthobunyavirus genus, Peribunyaviridae family) isolated in the Americas. PLoS ONE, 13(5), e0197294.
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2

Bar-coded 16S rRNA Gene Amplification

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Specifically, we have generated a set of 96 emulsion PCR fusion primers that contain the 454 emulsion PCR linkers on the 27F and 355R primers and a different 8 base “barcode” between the A adapter and 27F primer. Thus, each fecal sample was amplified with unique bar-coded forward 16S rRNA primers and then up to 96 samples were pooled and subjected to emulsion PCR and pyrosequenced using a GS-FLX pyrosequencer (Roche). Data from each pooled sample were “deconvoluted” by sorting the sequences into bins based on the barcodes using custom PERL scripts. Thus, we were able to normalize each sample by the total number of reads from each barcode. We have noted that ligating tagged primers to PCR amplicons distorts the abundances of the communities and thus it is critical to incorporate the tags during the original amplification step.
Bajaj J.S., Betrapally N.S., Hylemon P.B., Thacker L.R., Daita K., Kang D.J., White M.B., Unser A.B., Fagan A., Gavis E.A., Sikaroodi M., Dalmet S., Heuman D.M, & Gillevet P.M. (2015). Gut Microbiota Alterations can predict Hospitalizations in Cirrhosis Independent of Diabetes Mellitus. Scientific Reports, 5, 18559.
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3

Comprehensive 16S rRNA Gene Sequencing

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RNA was extracted after a combination of physical and chemical cell lysis as described above. RNA extraction and DNase treatment were performed using the RNA/DNA MasterPure extraction kit (Epicentre). Single-stranded cDNA was constructed with the high-capacity cDNA reverse transcription kit (Applied Biosystems) in 20-μl reaction mixtures (42 (link)). To assess the 16S rRNA gene region, we amplified regions V1 to V4 from the single-stranded cDNA (43 (link)). Amplicons were sequenced in the GS-FLX pyrosequencer (Roche) with Titanium-plus chemistry. For data analysis, only reads longer than 400 bp were selected to increase accuracy in taxonomic assignment.
Simon-Soro A., Ren Z., Krom B.P., Hoogenkamp M.A., Cabello-Yeves P.J., Daniel S.G., Bittinger K., Tomas I., Koo H, & Mira A. (2022). Polymicrobial Aggregates in Human Saliva Build the Oral Biofilm. mBio, 13(1), e00131-22.
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4

Barcoded 16S rRNA Amplicon Sequencing

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Specifically, we have generated a set of 96 emulsion PCR fusion primers that contain the 454 emulsion PCR linkers on the 27F and 355R primers and a different 8 base “barcode” between the A adapter and 27F primer. Thus, each fecal sample was amplified with unique bar-coded forward 16S rRNA primers and then up to 96 samples were pooled and subjected to emulsion PCR and pyrosequenced using a GS-FLX pyrosequencer (Roche). Data from each pooled sample were “deconvoluted” by sorting the sequences into bins based on the barcodes using custom PERL scripts. Thus, we were able to normalize each sample by the total number of reads from each barcode. We have noted that ligating tagged primers to PCR amplicons distorts the abundances of the communities and thus it is critical to incorporate the tags during the original amplification step29 (link).
Ahluwalia V., Betrapally N.S., Hylemon P.B., White M.B., Gillevet P.M., Unser A.B., Fagan A., Daita K., Heuman D.M., Zhou H., Sikaroodi M, & Bajaj J.S. (2016). Impaired Gut-Liver-Brain Axis in Patients with Cirrhosis. Scientific Reports, 6, 26800.
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5

Bar-coded 16S rRNA Gene Amplification

Check if the same lab product or an alternative is used in the 5 most similar protocols
Specifically, we have generated a set of 96 emulsion PCR fusion primers that contain the 454 emulsion PCR linkers on the 27F and 355R primers and a different 8 base “barcode” between the A adapter and 27F primer. Thus, each fecal sample was amplified with unique bar-coded forward 16S rRNA primers and then up to 96 samples were pooled and subjected to emulsion PCR and pyrosequenced using a GS-FLX pyrosequencer (Roche). Data from each pooled sample were “deconvoluted” by sorting the sequences into bins based on the barcodes using custom PERL scripts. Thus, we were able to normalize each sample by the total number of reads from each barcode. We have noted that ligating tagged primers to PCR amplicons distorts the abundances of the communities and thus it is critical to incorporate the tags during the original amplification step.
Kang D.J., Betrapally N.S., Ghosh S.A., Sartor R.B., Hylemon P.B., Gillevet P.M., Sanyal A.J., Heuman D.M., Carl D., Zhou H., Liu R., Wang X., Yang J., Jiao C., Herzog J., Lippmann H.R., Sikaroodi M., Brown R.R, & Bajaj J.S. (2016). Gut microbiota drive the development of neuro-inflammatory response in cirrhosis. Hepatology (Baltimore, Md.), 64(4), 1232-1248.
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