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Parallel detection of gene expression in single cells
05 August 2010
US chemical engineers have developed a tool to measure gene expression and how those genes affect cellular activity in thousands of cells at once. This could aid research into treatments for viruses such as HIV or tuberculosis.
The relationship between the expression of certain genes and the subsequent functional activities of a cell is a central question in cell biology. Traditional tests that study genetic and proteomic responses to applied external stimuli typically require more than 1000 cells for each analysis, but the resulting averages obscure variations that may exist among individual cells, which can lead to misinterpretations of the biology. Now Christopher Love at Massachusetts Institute of Technology in Cambridge have developed a simple, one-step process for detecting the expression of specific genes in thousands of single cells in parallel.
Love's method involves using a multiwell device to detect copies of mRNA transcripts from individual cells in a one-step, single-cell, reverse transcription polymerase chain reaction (PCR). A mRNA transcript is an exact copy of a corresponding DNA coding region and by looking at the mRNA transcripts present in a cell, scientists can find out which genes are expressed in that cell at different stages of development and under different conditions.
Arrays of microwells allows thousands of cells to be monitored at once
Simultaneous measurements to detect the presence of particular gene transcripts can be carried out for thousands of cells in parallel. A major advantage of the new approach is that it can be integrated with other techniques that capture additional information about the same cells, such as the secretion of particular proteins, says Love.
'This method should allow the detection of cells harbouring replicating intracellular pathogens such as HIV, endogenous retroviruses, or tuberculosis,' says Love. The ability to integrate this detection with other measures of phenotypes or functions should make it possible to correlate it with the functional profiles of those cells as well, he adds.
'In the context of HIV, this approach could allow detailed phenotypic analysis of latently or lytically infected cells,' says Love. Lytic infection is when the virus enters the cell, makes copies and kills the cell. Latently infected cells have HIV-1 DNA as a provirus but are not producing the virus. Such information about the characteristics of cells harbouring the pathogen may facilitate the development of therapies specifically targeted to those populations, explains Love.
Eric Rubins, a professor of immunology and infectious diseases at the Harvard School of Public Heath, says: 'This work provides an approach to extend the study of single-cells as opposed to populations. One can envision employing multiple modalities to monitor individual cells simultaneously, a capacity that extends the power of other single cell methods such as fluorescence activated cell sorting.'
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Link to journal article
Massively parallel detection of gene expression in single cells using subnanolitre wells
Yuan Gong, Adebola O. Ogunniyi and J. Christopher Love, Lab Chip, 2010, 10, 2334
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