Tools for Genomic and Transcriptomic Analysis of Microbes at Single-Cell Level

Abstract

Microbiologists traditionally study population rather than individual cells, as it is generally assumed that the status of individual cells will be similar to that observed in the population. However, the recent studies have shown that the individual behavior of each single cell could be quite different from that of the whole population, suggesting the importance of extending traditional microbiology studies to single-cell level. With recent technological advances, such as flow cytometry, next-generation sequencing (NGS), and microspectroscopy, single-cell microbiology has greatly enhanced the understanding of individuality and heterogeneity of microbes in many biological systems. Notably, the application of multiple ‘omics’ in single-cell analysis has shed light on how individual cells perceive, respond, and adapt to the environment, how heterogeneity arises under external stress and finally determines the fate of the whole population, and how microbes survive under natural conditions. As single-cell analysis involves no axenic cultivation of target microorganism, it has also been demonstrated as a valuable tool for dissecting the microbial ‘dark matter.’ In this review, current state-of-the-art tools and methods for genomic and transcriptomic analysis of microbes at single-cell level were critically summarized, including single-cell isolation methods and experimental strategies of single-cell analysis with NGS. In addition, perspectives on the future trends of technology development in the field of single-cell analysis was also presented.

Unravelling interspecies interactions across heterogeneities in complex biofilm communities

“…If sorting of the individual cells from complex communities according to their functional properties could be done from biofilm micro-samples, it would improve our understanding of spatial functionality. Further down-stream analyses such as RNA-seq of the sorted individual cells could also be employed (Wang et al, 2015;Chen et al, 2017).…”

Single-Cell Omics Analyses Enabled by Microchip Technologies

“…Additionally, insufficient reverse transcription and amplification efficiency lead to the dropout of transcripts with low abundance, which biases downstream analysis (26,78). Moreover, the volatility and degradation of RNA molecules further decrease the number of transcripts, increasing the noise and jeopardizing the accuracy and reproducibility of measurements (63,(79)(80)(81)(82). To differentiate distinct cell types or states, discover rare subpopulations, and reduce the impact of the technical and intrinsic noise, high-throughput profiling of individual cells is necessary.…”

“…The droplet microfluidic platform also showed high-throughput capabilities for target cell sorting. The drawbacks of both FISH and RT-PCR platforms are that they are relative quantification methods that can detect only a finite number of known genes in each experiment (76,79). Thus, these methodologies are not able to uncover global information from a cell (76,79).…”

“…The drawbacks of both FISH and RT-PCR platforms are that they are relative quantification methods that can detect only a finite number of known genes in each experiment (76,79). Thus, these methodologies are not able to uncover global information from a cell (76,79). These approaches also rely on a priori knowledge of target transcripts in the cells of interest, impeding the discovery of novel genes (63).…”

Recent Developments in Single-Cell RNA-Seq of Microorganisms

“…A complete single-cell RNA-seq analysis includes sequential procedures for the isolation of single cells, single-cell lysis, cDNA synthesis and amplification, library preparation and sequencing, and RNA-seq data interpretation. A few recently published review articles cover most of these details (19)(20)(21)(22). Here, we focus mainly on single-cell lysis, cDNA synthesis and amplification, and RNA-seq data interpretation, which are critical to single-cell RNA-seq of microorganisms.…”