Evidence map›Paper›PMID 22950515›Full record

ArticleMalaria journal2012

Optimization of flow cytometric detection and cell sorting of transgenic Plasmodium parasites using interchangeable optical filters.

Ivan A Vorobjev, Kathrin Buchholz, Prashant Prabhat, Kenneth Ketman, Elizabeth S Egan, Matthias Marti, Manoj T Duraisingh, Natasha S Barteneva

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Malaria journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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  3. Article
  4. Article
  5. Fluorescent Immunohistochemistry.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
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  7. Article
  8. Review
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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

8 authors at 2 institutions in 1 country.

Ivan A VorobjevImmune Disease Institute and Program in Cellular and Molecular Medicine, Children's Hospital, D-239, 200 Longwood Avenue, 02115, Boston, MA, USA.
Kathrin Buchholz
Prashant Prabhat
Kenneth Ketman
Elizabeth S Egan
Matthias Marti
Manoj T Duraisingh
Natasha S Barteneva
Harvard University · USBoston Children's Hospital · US

Funding

Functional analysis of erythrocyte determinants of malaria infectionR01AI091787 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI DURAISINGH, MANOJ T · 2011 to 2015
$2.0M
Cytoadherence and sequestration in malaria transmission stagesR01AI077558 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI MARTI, MATTHIAS · 2010 to 2013
$1.6M
A forward genetic screen to identify determinants of malaria stage conversionR21AI105328 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI MARTI, MATTHIAS · 2013 to 2014
$443k
Biocontained ImageStream 100 Multispectral Imaging CytometerS10RR023459 · NCRR · IMMUNE DISEASE INSTITUTE, INC. · PI LIEBERMAN, JUDY · 2007 to 2007
$358k
NCRR NIH HHS S10 RR023459NIAID NIH HHS R01 AI077558NIAID NIH HHS R01 AI091787NIAID NIH HHS R01AI091787NIAID NIH HHS R21 AI105328PHS HHS R01A107755801
6 · The paper itself

Abstract

backgroundMalaria remains a major cause of morbidity and mortality worldwide. Flow cytometry-based assays that take advantage of fluorescent protein (FP)-expressing malaria parasites have proven to be valuable tools for quantification and sorting of specific subpopulations of parasite-infected red blood cells. However, identification of rare subpopulations of parasites using green fluorescent protein (GFP) labelling is complicated by autofluorescence (AF) of red blood cells and low signal from transgenic parasites. It has been suggested that cell sorting yield could be improved by using filters that precisely match the emission spectrum of GFP.

methodsDetection of transgenic Plasmodium falciparum parasites expressing either tdTomato or GFP was performed using a flow cytometer with interchangeable optical filters. Parasitaemia was evaluated using different optical filters and, after optimization of optics, the GFP-expressing parasites were sorted and analysed by microscopy after cytospin preparation and by imaging cytometry.

resultsA new approach to evaluate filter performance in flow cytometry using two-dimensional dot blot was developed. By selecting optical filters with narrow bandpass (BP) and maximum position of filter emission close to GFP maximum emission in the FL1 channel (510/20, 512/20 and 517/20; dichroics 502LP and 466LP), AF was markedly decreased and signal-background improve dramatically. Sorting of GFP-expressing parasite populations in infected red blood cells at 90 or 95% purity with these filters resulted in 50-150% increased yield when compared to the standard filter set-up. The purity of the sorted population was confirmed using imaging cytometry and microscopy of cytospin preparations of sorted red blood cells infected with transgenic malaria parasites. DISCUSSION: Filter optimization is particularly important for applications where the FP signal and percentage of positive events are relatively low, such as analysis of parasite-infected samples with in the intention of gene-expression profiling and analysis. The approach outlined here results in substantially improved yield of GFP-expressing parasites, and requires decreased sorting time in comparison to standard methods. It is anticipated that this protocol will be useful for a wide range of applications involving rare events.

Indexed as

AnimalsAnimals, Genetically ModifiedErythrocytesFiltrationFlow CytometryGreen Fluorescent ProteinsHumansMalaria, FalciparumOptical DevicesParasitemiaPlasmodium falciparumRecombinant ProteinsGreen Fluorescent ProteinsRecombinant Proteins

Identifiers

PMID22950515
PMCPMC3544587
OpenAlexW2160712367

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.