High-throughput single-microbe RNA sequencing reveals adaptive state heterogeneity and host-phage activity associations in human gut microbiome

• Published in: Protein & cell 2024-05
• Main Authors: Shen, Yifei, Qian, Qinghong, Ding, Liguo, Qu, Wenxin, Zhang, Tianyu, Song, Mengdi, Huang, Yingjuan, Wang, Mengting, Xu, Ziye, Chen, Jiaye, Dong, Ling, Chen, Hongyu, Shen, Enhui, Zheng, Shufa, Chen, Yu, Liu, Jiong, Fan, Longjiang, Wang, Yongcheng
• Format: Article
• Language: English
• ISSN: 1674-800X; 1674-8018
• DOI: 10.1093/procel/pwae027

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications in health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve comprehensive understanding of complex microbial communities together with their hosts is therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive responses states among species in Prevotella and Roseburia genus and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated the smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-word situations and promises new perspectives in the understanding of human microbiomes.