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Sub-nanowatt microfluidic single-cell calorimetry.

ABSTRACT: Non-invasive and label-free calorimetry could become a disruptive technique to study single cell metabolic heat production without altering the cell behavior, but it is currently limited by insufficient sensitivity. Here, we demonstrate microfluidic single-cell calorimetry with 0.2-nW sensitivity, representing more than ten-fold enhancement over previous record, which is enabled by (i) a low-noise thermometry platform with ultralow long-term (10-h) temperature noise (80 μK) and (ii) a microfluidic channel-in-vacuum design allowing cell flow and nutrient delivery while maintaining a low thermal conductance of 2.5 μW K^-1. Using Tetrahymena thermophila as an example, we demonstrate on-chip single-cell calorimetry measurement with metabolic heat rates ranging from 1 to 4 nW, which are found to correlate well with the cell size. Finally, we perform real-time monitoring of metabolic rate stimulation by introducing a mitochondrial uncoupling agent to the microchannel, enabling determination of the spare respiratory capacity of the cells.

SUBMITTER: Hong S

PROVIDER: S-EPMC7292832 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Sub-nanowatt microfluidic single-cell calorimetry.

Hong Sahngki S Dechaumphai Edward E Green Courtney R CR Lal Ratneshwar R Murphy Anne N AN Metallo Christian M CM Chen Renkun R

Nature communications 20200612 1

Non-invasive and label-free calorimetry could become a disruptive technique to study single cell metabolic heat production without altering the cell behavior, but it is currently limited by insufficient sensitivity. Here, we demonstrate microfluidic single-cell calorimetry with 0.2-nW sensitivity, representing more than ten-fold enhancement over previous record, which is enabled by (i) a low-noise thermometry platform with ultralow long-term (10-h) temperature noise (80 μK) and (ii) a microfluid ...[more]

PMID: 32532969

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Project description:Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole transcriptome analysis. In this approach, single cells are captured and lysed in a microfluidic device, where mRNAs with poly(A) tails are reverse-transcribed into cDNA. Double-stranded cDNA is then collected and sequenced using a next-generation sequencing platform. We prepared 94 libraries consisting of single mouse embryonic cells and technical replicates of extracted RNA and thoroughly characterized the performance of this technology. Microfluidic implementation increased mRNA detection sensitivity as well as improved measurement precision compared with tube-based protocols. With 0.2M reads per cell, we were able to reconstruct a majority of the bulk transcriptome with 10 single cells. We also quantified variation between and within different types of mouse embryonic cells and found that enhanced measurement precision, detection sensitivity, and experimental throughput aided the distinction between biological variability and technical noise. With this work, we validated the advantages of an early approach to single-cell RNA-Seq and showed that the benefits of combining microfluidic technology with high-throughput sequencing will be valuable for large-scale efforts in single-cell transcriptome analysis. We investigated gene expression in mouse embryonic cells using microfluidic-facilitated RNA-Seq to analyze 56 single mouse ES cell (mESC) transcriptomes and 6 single mouse embryonic fibroblast (MEF) transcriptomes. To quantitatively evaluate the sensitivity and precision of our technique, we also sequenced 23 libraries from extracted mESC RNA, representing three sets of technical replicates with varying starting amounts of material.

Dataset Information

Sub-nanowatt microfluidic single-cell calorimetry.

Publications

Sub-nanowatt microfluidic single-cell calorimetry.

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