NEXTFLEX 16S V4 Amplicon-Seq Kit 2.0

Product information

Overview

16S V4 rRNA library prep for broad-range analysis of mixed microbial populations

Fast and easy library prep protocol
Low input – Only 1 ng of input required
Multiplex up to 384 libraries
Custom sequencing primers are not required
Automation protocols are now available for the Sciclone^® NGS and NGSx Workstations to automate your 16S sequencing
Functionally tested with Illumina^® sequencing platforms

Analysis Powered by CosmosID HUB^®

The NEXTFLEX 16S V4 rRNA Amplicon-seq panels are now available bundled with access to CosmosID-HUB; an online software solution that enables fast and easy analysis of complex microbiome data. CosmosID-HUB gives scientists user-friendly access to version-controlled and validated 16S pipelines. The machine-learning powered software also enables rapid data interpretation through a comparative analysis software with features such as tables, heatmaps, bar charts, multiple Alpha & Beta Diversity indexes, abundance distribution plots, differential abundance testing, as well as comprehensive statistics between groups. Learn more about CosmosID-HUB.

Additional product information

Low Input Requirements for 16S rRNA Sequencing

As little as 1 ng of genomic DNA can be used to generate libraries using the NEXTFLEX 16S V4 Amplicon-Seq Library Prep Kit 2.0.

fig-1 genera diversity measured by 16s v4 sequencing

Fig 1. Genera measured by analysis of 16S V4 reads

Optimized Protocol Offers Lower PCR Bias and Fewer Off-target Reads

The NEXTFLEX 16S V4 Amplicon-Seq Kit 2.0 incorporates a second PCR step in the protocol for the addition of the sample-specific index which reduces off-target reads encountered during amplicon sequencing.

384 Barcodes Available for Cost-effective 16S V4 rRNA Sequencing

The NEXTFLEX 16S V4 Amplicon-Seq Library Prep Kit 2.0 can be used for multiplexing up to 384 samples, to greatly reduce the cost of sequencing. The barcodes are offered in sets of 12, 48 or 96 barcodes and supplied with 2 reactions worth of each barcode.

Automate your 16S V4 Library Prep to Increase Throughput and Reduce Errors

A NEXTFLEX^® automation protocol is now available on the Sciclone^® NGS and NGSx workstations to help labs increase their throughput and reduce human errors.

Specifications

Other Specifications

Analysis	Not Included
Barcodes	12 barcodes
Shipping Conditions	Shipped in Dry Ice
Unit Size	24 rxns

Selected Publications / Citations / References

Bekker, V., Zwittink, R. D., Knetsch, C. W., Sanders, I. M., Berghuis, D., Heidt, P. J., . . . Kuijper, E. J. (2019). Dynamics of the Gut Microbiota in Children Receiving Selective or Total Gut Decontamination Treatment During Hematopoietic Stem Cell Transplantation. Biology of Blood and Marrow Transplantation. doi:10.1016/j.bbmt.2019.01.037.
Bruce-Keller, A. J., Fernandez-Kim, S., Townsend, R. L., Kruger, C., Carmouche, R., Newman, S., . . . Berthoud, H. (2017). Maternal obese-type gut microbiota differentially impact cognition, anxiety and compulsive behavior in male and female offspring in mice. Plos One, 12(4). doi:10.1371/journal.pone.0175577.
Davey, M. P., Norman, L., Sterk, P., Huete-Ortega, M., Bunbury, F., Loh, B. K., . . . Smith, A. G. (2019). Snow algae communities in Antarctica – metabolic and taxonomic composition. New Phytologist. doi:10.1111/nph.15701.
Ford, S. L., Lohmann, P., Preidis, G. A., Gordon, P. S., Odonnell, A., Hagan, J., . . . Hair, A. B. (2019). Improved feeding tolerance and growth are linked to increased gut microbial community diversity in very-low-birth-weight infants fed mothers own milk compared with donor breast milk. The American Journal of Clinical Nutrition,109(4), 1088-1097. doi:10.1093/ajcn/nqz006.
Luk, B., Veeraragavan, S., Engevik, M., Balderas, M., Major, A., Runge, J., . . . Versalovic, J. (2018). Postnatal colonization with human “infant-type” Bifidobacterium species alters behavior of adult gnotobiotic mice. Plos One, 13(5). doi:10.1371/journal.pone.0196510.
Luna, R. A., Oezguen, N., Balderas, M., Venkatachalam, A., Runge, J. K., Versalovic, J., . . . Williams, K. C. (2017). Distinct Microbiome-Neuroimmune Signatures Correlate With Functional Abdominal Pain in Children With Autism Spectrum Disorder. Cellular and Molecular Gastroenterology and Hepatology, 3(2), 218-230. doi:10.1016/j.jcmgh.2016.11.008
Moon, C., Stupp, G. S., Su, A. I., & Wolan, D. W. (2017). Metaproteomics of colonic microbiota unveils discrete protein functions among colitic mice and control groups. doi:10.1101/219782.
Stalenhoef, J. E., et al. (2017) Fecal Microbiota Transfer for Multidrug-Resistant Gram-Negatives: A Clinical Success Combined With Microbiological Failure. Open Forum Infectious Diseases, 4(2). doi:10.1093/ofid/ofx047.
Svensson, K., Paruch, L., Gaby, J. C., & Linjordet, R. (2018). Feeding frequency influences process performance and microbial community composition in anaerobic digesters treating steam exploded food waste. Bioresource Technology, 269, 276-284. doi:10.1016/j.biortech.2018.08.096.
Sylvia, K. E., Deyoe, J. E., & Demas, G. E. (2018). Early-life sickness may predispose Siberian hamsters to behavioral changes following alterations of the gut microbiome in adulthood. Brain, Behavior, and Immunity, 73, 571-583. doi:10.1016/j.bbi.2018.07.001.
Whon, T. W., Chung, W., Lim, M. Y., Song, E., Kim, P. S., Hyun, D., . . . Nam, Y. (2018). The effects of sequencing platforms on phylogenetic resolution in 16 S rRNA gene profiling of human feces. Scientific Data, 5, 180068. doi:10.1038/sdata.2018.68.
Wotzkas, S. Y., Kreuzer, M., Maier, L., Zuend, M., Schlumberger, M., Nguyen, B., . . . Misselwitz, B. (2018). Microbiota stability in healthy individuals after single-dose lactulose challenge – a randomized controlled study. doi:10.1101/424531.
Zhao, R., Yang, W., Pei, F., Zhao, L., & Hu, Q. (2018). In vitro fermentation of six kinds of edible mushrooms and its effects on fecal microbiota composition. Lwt, 96, 627-635. doi:10.1016/j.lwt.2018.06.012.