Evidence map›Paper›PMID 24483235›Full record

ArticleBMC immunology2014

Validation and implementation of a method for microarray gene expression profiling of minor B-cell subpopulations in man.

Kim Steve Bergkvist, Mette Nyegaard, Martin Bøgsted, Alexander Schmitz, Julie Støve Bødker, Simon Mylius Rasmussen, Martin Perez-Andres, Steffen Falgreen, Anders Ellern Bilgrau, Malene Krag Kjeldsen and 8 more

Open access · goldAbstract 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

18 authors at 2 institutions in 1 country.

Kim Steve Bergkvist
Mette Nyegaard
Martin Bøgsted
Alexander Schmitz
Julie Støve Bødker
Simon Mylius Rasmussen
Martin Perez-Andres
Steffen Falgreen
Anders Ellern Bilgrau
Malene Krag Kjeldsen
Michael Gaihede
Martin Agge Nørgaard
John Bæch
Marie-Louise Grønholdt
Frank Svendsen Jensen
Preben Johansen
Karen Dybkær
Hans Erik JohnsenDepartment of Haematology, Aalborg University Hospital Science and Innovation Center, Sdr Skovvej 15, DK-9000 Aalborg, Denmark. haej@rn.dk.
Aalborg University Hospital · DKAalborg University · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis report describes a method for the generation of global gene expression profiles from low frequent B-cell subsets by using fluorescence-activated cell sorting and RNA amplification. However, some of the differentiating compartments involve a low number of cells and therefore it is important to optimize and validate each step in the procedure.

methodsNormal lymphoid tissues from blood, tonsils, thymus and bone marrow were immunophenotyped by the 8-colour Euroflow panel using multiparametric flow cytometry. Subsets of B-cells containing cell numbers ranging from 800 to 33,000 and with frequencies varying between 0.1 and 10 percent were sorted, subjected to mRNA purification, amplified by the NuGEN protocol and finally analysed by the Affymetrix platform.

resultsFollowing a step by step strategy, each step in the workflow was validated and the sorting/storage conditions optimized as described in this report. First, an analysis of four cancer cell lines on Affymetrix arrays, using either 100 ng RNA labelled with the Ambion standard protocol or 1 ng RNA amplified and labelled by the NuGEN protocol, revealed a significant correlation of gene expressions (r ≥ 0.9 for all). Comparison of qPCR data in samples with or without amplification for 8 genes showed that a relative difference between six cell lines was preserved (r ≥ 0.9). Second, a comparison of cells sorted into PrepProtect, RNAlater or directly into lysis/binding buffer showed a higher yield of purified mRNA following storage in lysis/binding buffer (p < 0.001). Third, the identity of the B-cell subsets validated by the cluster of differentiation (CD) membrane profile was highly concordant with the transcriptional gene expression (p-values <0.001). Finally, in normal bone marrow and tonsil samples, eight evaluated genes were expressed in accordance with the biology of lymphopoiesis (p-values < 0.001), which enabled the generation of a gene-specific B-cell atlas.

conclusionA description of the implementation and validation of commercially available kits in the laboratory has been examined. This included steps for cell sorting, cell lysis/stabilization, RNA isolation, RNA concentration and amplification for microarray analysis. The workflow described in this report will enable the generation of microarray data from minor sorted B-cell subsets.

Indexed as

Antigens, CDB-Lymphocyte SubsetsFlow CytometryGene Expression ProfilingHumansLymphoid TissueOligonucleotide Array Sequence AnalysisOrgan SpecificityReal-Time Polymerase Chain ReactionReproducibility of ResultsAntigens, CD

Identifiers

PMID24483235
PMCPMC3937209
OpenAlexW2143299729

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.