Evidence map›Paper›PMID 25318652›Full record

ArticleBMC immunology2014

Quantitative assessment of the robustness of next-generation sequencing of antibody variable gene repertoires from immunized mice.

Victor Greiff, Ulrike Menzel, Ulrike Haessler, Skylar C Cook, Simon Friedensohn, Tarik A Khan, Mark Pogson, Ina Hellmann, Sai T Reddy

Abstract read
In one paragraph

Article in BMC immunology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

42 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Victor Greiff
Ulrike Menzel
Ulrike Haessler
Skylar C Cook
Simon Friedensohn
Tarik A Khan
Mark Pogson
Ina Hellmann
Sai T Reddy

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNext-generation sequencing (NGS) of antibody variable regions has emerged as a powerful tool in systems immunology by providing quantitative molecular information on polyclonal humoral immune responses. Reproducible and robust information on antibody repertoires is valuable for basic and applied immunology studies: thus, it is essential to establish the reliability of antibody NGS data.

resultsWe isolated RNA from antibody-secreting cells (ASCs) from either 1 mouse or a pool of 9 immunized mice in order to simulate both normal and high diversity populations. Next, we prepared three technical replicates of antibody libraries by RT-PCR from each diversity scenario, which were sequenced using the Illumina MiSeq platform resulting in >106 250 bp paired-end reads per replicate. We then assessed the robustness of antibody repertoire data based on clonal identification defined by amino acid sequence of either full-length VDJ region or the complementarity determining region 3 (CDR3). Leveraging modeling approaches adapted from mathematical ecology, we found that in either diversity scenario both CDR3 and VDJ detection nears completeness indicating deep coverage of ASC repertoires. Additionally, we defined reliability thresholds for accurate quantification and ranking of CDR3s and VDJs. Importantly, we show that both factors-(i) replicate sequencing and (ii) sequencing depth-are crucial for robust CDR3 and VDJ detection and ranking.

conclusionsIn summary, we established widely applicable experimental and computational guidelines for robust antibody NGS and analysis, which will help advance systems immunology studies related to the quantitative profiling of antibody responses following infection and vaccination.

Indexed as

ImmunizationAnimalsAntibodiesClone CellsComplementarity Determining RegionsFemaleHigh-Throughput Nucleotide SequencingImmunoglobulin Variable RegionMice, Inbred BALB CReproducibility of ResultsV(D)J RecombinationAntibodiesComplementarity Determining RegionsImmunoglobulin Variable Region

Identifiers

PMID25318652
PMCPMC4233042

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.