Detecting host factors involved in virus infection by observing the clustering of infected cells in siRNA screening images.
BACKGROUND
Detecting human proteins that are involved in virus entry and replication is facilitated by modern high-throughput RNAi screening technology. However, hit lists from different laboratories have shown only little consistency. This may be caused by not only experimental discrepancies, but also not fully explored possibilities of the data analysis. We wanted to improve reliability of such screens by combining a population analysis of infected cells with an established dye intensity readout.


RESULTS
Viral infection is mainly spread by cell-cell contacts and clustering of infected cells can be observed during spreading of the infection in situ and in vivo. We employed this clustering feature to define knockdowns which harm viral infection efficiency of human Hepatitis C Virus. Images of knocked down cells for 719 human kinase genes were analyzed with an established point pattern analysis method (Ripley's K-function) to detect knockdowns in which virally infected cells did not show any clustering and therefore were hindered to spread their infection to their neighboring cells. The results were compared with a statistical analysis using a common intensity readout of the GFP-expressing viruses and a luciferase-based secondary screen yielding five promising host factors which may suit as potential targets for drug therapy.


CONCLUSIONS
We report of an alternative method for high-throughput imaging methods to detect host factors being relevant for the infection efficiency of viruses. The method is generic and has the potential to be used for a large variety of different viruses and treatments being screened by imaging techniques.
Suratanee
Apichat
A
Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.
Rebhan
Ilka
I
Matula
Petr
P
Kumar
Anil
A
Kaderali
Lars
L
Rohr
Karl
K
Bartenschlager
Ralf
R
Eils
Roland
R
König
Rainer
R
D015703:Antigens, CD / Q000032:analysis; D001685:Biological Factors / Q000032:analysis*; D047390:Casein Kinase II / Q000032:analysis; D045744:Cell Line, Tumor; D003627:Data Interpretation, Statistical; D003716:Dengue Virus / Q000502:physiology; D016174:Hepacivirus / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015778:Minor Histocompatibility Antigens; D017853:Phosphotransferases (Alcohol Group Acceptor) / Q000032:analysis; D011494:Protein Kinases / Q000235:genetics; D034622:RNA Interference; D034741:RNA, Small Interfering; D011956:Receptors, Cell Surface / Q000032:analysis; D000071177:Signaling Lymphocytic Activation Molecule Family Member 1; D060225:Tetraspanin 28; D040321:Vascular Endothelial Growth Factor Receptor-3 / Q000032:analysis; D014779:Virus Replication
D015703:Antigens, CD; D001685:Biological Factors; C554798:CD81 protein, human; D015778:Minor Histocompatibility Antigens; D034741:RNA, Small Interfering; D011956:Receptors, Cell Surface; D060225:Tetraspanin 28; D000071177:Signaling Lymphocytic Activation Molecule Family Member 1; D011494:Protein Kinases; D017853:Phosphotransferases (Alcohol Group Acceptor); C402182:phosphatidylinositol phosphate 4-kinase; D040321:Vascular Endothelial Growth Factor Receptor-3; D047390:Casein Kinase II
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