Cellular heterogeneity is a universal property of living systems, and the interrogation of single cells facilitates in-depth understanding of distinct cellular states and functions in various biological processes. Co-analysis of transcripts and proteins from the same single cells opens the way to decipher complex RNA regulatory frameworks and phenotypes, facilitating the understanding of cellular fate and function regulations, discovery of novel cell types, and construction of a high-resolution cell atlas. Herein, we review the state-of-art advances in the development of methodologies for co-analysis of single-cell transcripts and proteins. First, imaging-based methods are summarized with particular emphasis on optical and mass spectrometry imaging. Next, sequencing-based approaches for high-throughput and sensitive co-analysis of single-cell transcripts and proteins are described, including droplet-, microwell-, and split-pool-based platforms. Subsequently, combined methods with more flexibility and universality are discussed. These methods commonly employ different strategies or reactions to convert transcripts and proteins of single cells into distinct signals simultaneously, which can be detected by different instruments or platforms. Lastly, some perspectives on the future challenges and development trends in this field are presented.

Despite the fast progress in our understanding of the complex functions of gut microbiota, it is still challenging to directly investigate the in vivo microbial activities and processes on an individual cell basis. To gain knowledge of the indigenous growth/division patterns of the diverse mouse gut bacteria with a relatively high throughput, here, we propose an integrative strategy, which combines the use of fluorescent probe labeling, confocal imaging with single-cell sorting, and sequencing. Mouse gut bacteria sequentially labeled by two fluorescent D-amino acid probes in vivo were first imaged by confocal microscopy to visualize their growth patterns, which can be unveiled by the distribution of the two fluorescence signals on each bacterium. Bacterial cells of interest on the imaging slide were then sorted using a laser ejection equipment, and the collected cells were then sequenced individually to identify their taxa. Our strategy allows integrated acquirement of the growth pattern knowledge of a variety of gut bacteria and their genomic information on a single-cell basis, which should also have great potential in studying many other complex bacterial systems.