Leukocyte analysis and differentiation using high speed microfluidic single cell impedance cytometry

Holmes, David; Pettigrew, D.; Reccius, Christian H.; Gwyer, James D.; Berkel, C. van; Holloway, Judith A.; Davies, Donna E.; Morgan, Hywel

doi:10.1039/b910053a

Cited by 364 publications

(389 citation statements)

References 17 publications

Supporting

Mentioning

374

Contrasting

Order By: Relevance

“…Conceptually, this approach represents a downscaling of the classical metabolomics approach. The complete setup has not yet been realized, but many different units required for the microfluidic chip have been developed separately, such as lysis (see, for example, [32]), impedance-based cell size measurement [33], CE separation (e.g. [34]).…”

Section: Ms-based Approaches For Single Cell Metabolomicsmentioning

confidence: 99%

Single cell metabolomics

Heinemann

Zenobi

2011

Current Opinion in Biotechnology

116

View full text Add to dashboard Cite

Recent discoveries suggest that cells of a clonal population often display multiple metabolic phenotypes at the same time. Motivated by the success of mass spectrometry (MS) in the investigation of population-level metabolomics, the analytical community has initiated efforts towards MS-based single cell metabolomics to investigate metabolic phenomena that are buried under the population average. Here, we review the current approaches and illustrate their advantages and disadvantages. Because of significant advances in the field, different technologies are now at the verge of generating data that are useful for exploring and investigating metabolic heterogeneity. IntroductionQuantitative metabolomics, the technology for large-scale quantification of intracellular metabolite concentrations, is a powerful tool in systems biology research that has recently led to a series of interesting findings (e.g. [1][2][3][4]). Because of the metabolome's chemical diversity, mass spectrometry (MS) is the analytical method of choice [5]. In addition to analytical challenges, quantitative metabolomics as required for addressing (systems) biology questions poses significant challenges in sample processing. One important challenge is the need to preserve the original metabolome during sample processing, which is often difficult because of the presence of enzymes in the sample and the fast metabolic turnover rates.For sensitivity reasons, current metabolomics methods require samples that contain a large number of cells. However, cell populations are not necessarily homogeneous. Besides genetic differences, several other sources for population heterogeneity exist, of which several are also known to cause metabolic differences. Today, methods capable of resolving differences in metabolite levels on the single cell level are provided, within limits, by molecular sensors such as FRET sensors [6,7] or aptamer-based technology [8 ,9]. Both types of molecular sensors, however, are difficult to develop, are limited to specific analytes, and quantitative analyses (e.g. in terms of mol/L) are hardly possible with them. Laserinduced fluorescence, as introduced by Dovichi for single cell proteomics, is limited to fluorescent compounds or labelled species [10,11]. In addition, all these existing methods share the limitation that they can never be extended to the ''-omics'' level, that is to measuring a large number of metabolites at the same time. They will thus not be applicable to discovery type research and research that requires a large number of metabolites to be measured in the same cell.Because of the success of mass spectrometry in population-level metabolome analyses, the analytical community has recently made great strides towards single cell level metabolite analyses (for a review, see [12]). So far, however, hardly any new biological insight has been generated from these endeavours. In this Current Opinion paper, we will thus not only review the current status of MS-based single cell metabolomics but also discuss which of the differ...

show abstract

Section: Ms-based Approaches For Single Cell Metabolomicsmentioning

confidence: 99%

Single cell metabolomics

Heinemann

Zenobi

2011

Current Opinion in Biotechnology

116

View full text Add to dashboard Cite

show abstract

“…The corresponding values of S x and S y were calculated by extracting their magnitude with respect to the current signal baseline (I 0,x and I 0,y ). The anisotropy index was calculated as: AI = (S x /S y ) at (x,y)=0 (7) Results and discussion…”

Section: Discussionmentioning

confidence: 99%

An impedance-based flow microcytometer for single cell morphology discrimination

et al. 2014

View full text Add to dashboard Cite

Cell shape is a fundamental biological feature, providing specific information about physiological or pathological cellular conditions. Most of the state-of-the-art microfluidic cytometers, however, only allow simple cell analysis, including viability studies, cell counting and sorting. In this work, we present a non-invasive, label-free device capable of single cell morphology discrimination in continuous flow. The device is based on the principle of liquid electrodes, fabricated in a cross configuration around a sensing zone. This arrangement allows measurement of cell impedance along orthogonal orientations and extraction of an index describing cell shape anisotropy. By adding prior to the sensing volume a series of lateral liquid electrodes, the particle stream was focused toward the channel midline and each cell was oriented in a specific direction before shape sensing. We demonstrate the proof of concept by performing spherical and elongated particle discrimination. As an application, we show that the shape changes experienced during cell division can be monitored and characterized. In particular, budding yeasts at different stages of the mitotic cycle were identified by extracting their anisotropy index.

show abstract

“…In addition to WBC count, microfluidic flow cytometry has also been used for analyzing a variety of particles. [126][127][128][129][130] An impedance flow cytometry design using coplanar electrodes was demonstrated by Gawad et al 126 As shown in Fig. 4(a), three microfabricated electrodes were integrated on the bottom of the microfluidic channel.…”

Section: Impedance Flow Cytometry (Ifc)mentioning

confidence: 99%

“…129 This device design enabled direct correlation of impedance signals from individual cells with their biochemical phenotypes. A 3-part WBC differential count of human blood was well achieved.…”

Section: Impedance Flow Cytometry (Ifc)mentioning

confidence: 99%