High-throughput single-microbe RNA sequencing reveals adaptive state heterogeneity and host-phage activity associations in human gut microbiome
Yifei Shen, Qinghong Qian, Liguo Ding, Wenxin Qu, Tianyu Zhang, Mengdi Song, Yingjuan Huang, Mengting Wang, Ziye Xu, Jiaye Chen, Ling Dong, Hongyu Chen, Enhui Shen, Shufa Zheng, Yu Chen, Jiong Liu, Longjiang Fan, Yongcheng Wang
High-throughput single-microbe RNA sequencing reveals adaptive state heterogeneity and host-phage activity associations in human gut microbiome
Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for 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 a comprehensive understanding of complex microbial communities together with their hosts are 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 response states among species in Prevotella and Roseburia genera 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 that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.
single-microbe RNA sequencing (smRNA-seq) / droplet microfluidics / microbiome / host-phage association / smRandom-seq2
[1] |
Almeida A, Nayfach S, Boland M et al. A unified catalog of 204, 938 reference genomes from the human gut microbiome. Nat Biotechnol 2021;39:105–114.
CrossRef
Google scholar
|
[2] |
Blattman SB, Jiang W, Oikonomou P et al. Prokaryotic single-cell RNA sequencing by in situ combinatorial indexing. Nat Microbiol 2020;5:1192–1201.
CrossRef
Google scholar
|
[3] |
Camarillo-Guerrero LF, Almeida A, Rangel-Pineros G et al. Massive expansion of human gut bacteriophage diversity. Cell 2021;184:1098–1109.e9.
CrossRef
Google scholar
|
[4] |
Chong S, Chen C, Ge H et al. Mechanism of transcriptional bursting in bacteria. Cell 2014;158:314–326.
CrossRef
Google scholar
|
[5] |
Dar D, Dar N, Cai L et al. Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution. Science 2021;373:eabi4882.
CrossRef
Google scholar
|
[6] |
Dobin A, Davis CA, Schlesinger F et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013;29:15–21.
CrossRef
Google scholar
|
[7] |
Fujimoto K, Kimura Y, Allegretti JR et al. Functional restoration of bacteriomes and viromes by fecal microbiota transplantation. Gastroenterology 2021;160:2089–2102.e12.
CrossRef
Google scholar
|
[8] |
Han J, Depinho RA, Maitra A. Single-cell RNA sequencing in pancreatic cancer. Nat Rev Gastroenterol Hepatol 2021;18:451–452.
CrossRef
Google scholar
|
[9] |
Hao Y, Hao S, Andersen-Nissen E et al. Integrated analysis of multimodal single-cell data. Cell 2021;184:3573–3587. e29.
CrossRef
Google scholar
|
[10] |
Ikeyama N, Murakami T, Toyoda A et al. Microbial interaction between the succinate-utilizing bacterium Phascolarctobacterium faecium and the gut commensal Bacteroides thetaiotaomicron. Microbiologyopen 2020;9:e1111.
CrossRef
Google scholar
|
[11] |
Imdahl F, Vafadarnejad E, Homberger C et al. Single-cell RNA-sequencing reports growth-condition-specific global transcriptomes of individual bacteria. Nat Microbiol 2020;5:1202–1206.
CrossRef
Google scholar
|
[12] |
Klein AM, Mazutis L, Akartuna I et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 2015;161:1187–1201.
CrossRef
Google scholar
|
[13] |
Ko J, Wang Y, Sheng K et al. Sequencing-based protein analysis of single extracellular vesicles. ACS Nano 2021;15:5631–5638.
CrossRef
Google scholar
|
[14] |
Kopylova E, Noé L, Touzet H. SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics 2012;28:3211–3217.
CrossRef
Google scholar
|
[15] |
Kuchina A, Brettner LM, Paleologu L et al. Microbial single-cell RNA sequencing by split-pool barcoding. Science 2021;371:eaba5257.
CrossRef
Google scholar
|
[16] |
Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 2014;30:923–930.
CrossRef
Google scholar
|
[17] |
Lu J, Rincon N, Wood DE et al. Metagenome analysis using the Kraken software suite. Nat Protoc 2022;17:2815–2839.
CrossRef
Google scholar
|
[18] |
Ma P, Amemiya HM, He LL et al. Bacterial droplet-based single-cell RNA-seq reveals antibiotic-associated heterogeneous cellular states. Cell 2023;186:877–891.e14.
CrossRef
Google scholar
|
[19] |
Manrique P, Bolduc B, Walk S T et al. Healthy human gut phageome. Proc Natl Acad Sci U S A 2016;113:10400–10405.
CrossRef
Google scholar
|
[20] |
Mayneris-Perxachs J, Castells-Nobau A, Arnoriaga-Rodríguez M et al. Microbiota alterations in proline metabolism impact depression. Cell Metab 2022;34:681–701.e10.
CrossRef
Google scholar
|
[21] |
Mcnulty R, Sritharan D, Pahng SH et al. Probe-based bacterial single-cell RNA sequencing predicts toxin regulation. Nat Microbiol 2023;8:934–945.
CrossRef
Google scholar
|
[22] |
Natarajan A, Bhatt AS. Microbes and microbiomes in 2020 and beyond. Nat Commun 2020;11:4988.
CrossRef
Google scholar
|
[23] |
Paik DT, Cho S, Tian L et al. Single-cell RNA sequencing in cardiovascular development, disease and medicine. Nat Rev Cardiol 2020;17:457–473.
CrossRef
Google scholar
|
[24] |
Papalexi E, Satija R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immunol 2018;18:35–45.
CrossRef
Google scholar
|
[25] |
Patterson AM, Mulder IE, Travis AJ et al. Human gut symbiont roseburia hominis promotes and regulates innate immunity. Front Immunol 2017;8:1166.
CrossRef
Google scholar
|
[26] |
Prasoodanan PKV, Sharma AK, Mahajan S et al. Western and non-western gut microbiomes reveal new roles of Prevotella in carbohydrate metabolism and mouth-gut axis. npj Biofilms Microbiomes 2021;7:77.
CrossRef
Google scholar
|
[27] |
Roemhild R, Bollenbach T, Andersson DI. The physiology and genetics of bacterial responses to antibiotic combinations. Nat Rev Microbiol 2022;20:478–490.
CrossRef
Google scholar
|
[28] |
Sharma A, Gilbert JA. Microbial exposure and human health. Curr Opin Microbiol 2018;44:79–87.
CrossRef
Google scholar
|
[29] |
Sheng K, Cao W, Niu Y et al. Effective detection of variation in single-cell transcriptomes using MATQ-seq. Nat Methods 2017;14:267–270.
CrossRef
Google scholar
|
[30] |
Shkoporov AN, Turkington CJ, Hill C. Mutualistic interplay between bacteriophages and bacteria in the human gut. Nat Rev Microbiol 2022;20:737–749.
CrossRef
Google scholar
|
[31] |
Smith T, Heger A, Sudbery I. UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy. Genome Res 2017;27:491–499.
CrossRef
Google scholar
|
[32] |
Smith, WPJ, Wucher BR, Nadell CD et al. Bacterial defences: mechanisms, evolution and antimicrobial resistance. Nat Rev Microbiol 2023;21:519–534.
CrossRef
Google scholar
|
[33] |
Van De Sande B, Lee JS, Mutasa-Gottgens E et al. applications of single-cell RNA sequencing in drug discovery and development. Nat Rev Drug Discov 2023;22:496–520.
CrossRef
Google scholar
|
[34] |
Van Der Leun AM, Thommen DS, Schumacher TN. CD8(+) T cell states in human cancer: insights from single-cell analysis. Nat Rev Cancer 2020;20:218–232.
CrossRef
Google scholar
|
[35] |
Wang Y, Cao T, Ko J et al. Dissolvable polyacrylamide beads for high-throughput droplet DNA barcoding. Adv Sci (Weinh) 2020;7:1903463.
CrossRef
Google scholar
|
[36] |
Xu Z, Wang Y, Sheng K et al. Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq. Nat Commun 2023a;14:5130.
CrossRef
Google scholar
|
[37] |
Xu Z, Zhang T, Chen H et al. High-throughput single nucleus total RNA sequencing of formalin-fixed paraffin-embedded tissues by snRandom-seq. Nat Commun 2023b;14:2734.
CrossRef
Google scholar
|
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