An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity

An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity Xiaodan Yan, Hebin Liao, Chenyi Wang, Chun Huang, Wei Zhang, Chunming Guo, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3329601/v3 This work is licensed under a CC BY 4.0 License Status: Posted Version 3 posted You are reading this latest preprint version Show more versions Abstract In contrast to mammalian cells, bacterial cells lack mRNA polyadenylated tails, presenting a hurdle in isolating mRNA amidst the prevalent rRNA during single-cell RNA-seq. This study introduces a novel method, Ribosomal RNA-derived cDNA Depletion (RiboD), seamlessly integrated into the PETRI-seq technique, yielding RiboD-PETRI. This innovative approach offers a cost-effective, equipment-free, and high-throughput solution for bacterial single-cell RNA sequencing (scRNA-seq). By efficiently eliminating rRNA reads and substantially enhancing mRNA detection rates (up to 92%), our method enables precise exploration of bacterial population heterogeneity. Applying RiboD-PETRI to investigate biofilm heterogeneity, distinctive subpopulations marked by unique genes within biofilms were successfully identified. Notably, PdeI, a marker for the cell-surface attachment subpopulation, was observed to elevate cyclic diguanylate (c-di-GMP) levels, promoting persister cell formation. Thus, we address a persistent challenge in bacterial single-cell RNA-seq regarding rRNA abundance, exemplifying the utility of this method in exploring biofilm heterogeneity. Our method effectively tackles a long-standing issue in bacterial scRNA-seq: the overwhelming abundance of rRNA. This advancement significantly enhances our ability to investigate the intricate heterogeneity within biofilms at unprecedented resolution. Biological sciences/Microbiology/Biofilms Biological sciences/Microbiology/Bacteria/Bacterial techniques and applications bacterial scRNA-seq biofilms heterogeneity Figures Figure 1 Figure 2 Figure 3 Figure 4 Full Text Additional Declarations The authors declare no competing interests. Supplementary Files movieS1.mp4 Movie S1. Time-lapse images of the persister assay using cells with different PdeI-BFP. TableS5.SequencingInformation.xls Table S5. Sequencing information of RiboD-PETRI libraries. TableS6.ThecostofRiboDPETRI.xls Table S6. The detailed cost breakdown of RiboD-PETRI. FigureS1.jpg Figure S1. (A, B) The number of UMIs detected per cell in recovered cells in different samples (≥15 UMIs/cell): (A) PETRI, (B) RiboD-PETRI at the same unsaturated sequencing depth. The cells are ranked from highest to lowest based on the number of detected UMIs, and cells with ≥15 UMIs are selected for plotting. The median number of UMIs is calculated for these selected cells. (C) Scatterplot illustrating the relationship between reads per cell and counts of UMIs per cell detected from exponential phase E. coli data. Each dot represents a cell. (D) Sequencing saturation of data of exponential period E. coli (3h). We extracted 20%, 40%, 60%, 80% and 100% of the data and further tested their saturation using the saturation calculation method of 10x Genomics. (E & F) Sequencing saturation analysis. We took 20%, 40%, 60%, 80% and 100% of the sequencing data for single-cell analysis and counted the number of genes and UMIs for each cell in these data. The cells were then sorted from largest to smallest values, and cells were taken to count the median number of genes (E) and UMIs (F). FigureS2.jpg Figure S2. Comprehensive Single-Cell Transcriptomic Analysis of S. aureus and C. crescentus using RiboD-PETRI. Technical Application of RiboD-PETRI in S. aureus (SA) (A-F), cultured for 9 hours in MHB medium at 37 °C (Table S14) and C. crescentus (CC) (G-L), incubated at 37 °C for 3 hours (Table S15). (A, G) The number of UMIs detected per cell in different samples (≥15 UMIs/cell): (A) S. aureus (SA) and (G) C. crescentus (CC). (B, H) Distribution of mRNA UMIs captured per cell in RiboD-PETRI data of (B) S. aureus (SA) and (H) C. crescentus (CC), presented as violin plots showing the upper quartile, median, and lower quartile lines. The cells are ranked from highest to lowest based on the number of UMIs detected. Then, specific numbers of cells (indicated above the panel) are selected for plotting. The median number of UMIs is calculated for these selected cells. (C, I) The number of genes detected per cell in different samples (C) S. aureus and (I) C. crescentus . The cells are ranked from highest to lowest based on the number of genes detected. Then, specific numbers of cells (indicated above the panel) are selected for plotting. The median number of genes is calculated for these selected cells. "SA" denotes S. aureus , and "CC" denotes C. crescentus . (D, J) UMAP visualization of (D) S. aureus and (J) C. crescentus , demonstrating the ability of RiboD-PETRI to distinguish population heterogeneity. (E, K) Normalized and Principal Component Analysis (PCA) performed on screened data of (E) S. aureus and (K) C. crescentus . The resulting scatterplots show heterogeneity among the populations, with each point representing a cell. (F, L) Distribution of UMIs on the UMAP results for (F) S. aureus and (L) C. crescentus . UMAP results reveal heterogeneity among populations, with each point representing a cell and color shading indicating UMI counts. TableS10.E.coliRNAseqdata.xls Table S10. Read per gene of E.coli RNA-seq data in Fig 1E TableS1.Primersusedinthisstudy.xls Table S1. Primers used in this study TableS3.rRNAandmRNAexperssionofPETRIseqandRiboDPETRI.xls Table S3. Data of rRNA and mRNA experssion of PETRI-seq and RiboD-PETRI. FigureS3.jpg Figure S3. Evaluation of Transcriptomic Consistency and Batch Effect Analysis in Static Biofilm E. coli Samples (A) Scatterplot demonstrating the relationship between reads per cell and counts of UMIs per cell detected from static biofilm E. coli data. Two replicates of the sample are included. (B) Calculation of the Pearson correlation coefficient (r) of UMI counts per gene between replicate 1 and replicate 2 of static biofilm E. coli . The analysis involved 4,062 out of 4,141 total genes, with a significant correlation (p-value < 0.0001, r = 0.96), indicating good replication between samples. Each dot represents a gene. (C) Before batch effects were removed, UMAP plot based on the original identity of static biofilm E. coli samples (replicate 1 and replicate 2). Each dot represents a cell, with red indicating replicate 1 and green indicating replicate 2. (D) After batch effects were removed using Harmony, UMAP plot based on the original identity of static biofilm E. coli samples (replicate 1 and replicate 2). (E) Principal Component Analysis (PCA) performed on screened data of two replicates of static biofilm E. coli . The resulting scatterplots show heterogeneity among the populations, with each point representing a cell. (F) Distribution of UMIs on the UMAP results for two replicates of static biofilm E. coli . UMAP results reveal heterogeneity among populations, with each point representing a cell and color shading indicating UMI counts. TableS4.VariousmethodsinrRNAdepletion.xls Table S4. The comparison of various methods in rRNA depletion method FigureS4.jpg Figure S4. Profiling of Marker Genes in exponential phase E. coli culture by RiboD-PETRI. Expression levels of diverse marker genes across distinct clusters in exponential phase E. coli culture, visualized through violin plots. Each individual dot represents a single cell, demonstrating the high-resolution, single-cell nature of the RiboD-PETRI analysis. FigureS8.jpg Figure S8. Schematic chart for the structure of E. coli PdeI. FigureS5.jpg Figure S5. Marker Genes Identified in stationary phase S. aureus culture by RiboD-PETRI. Expression levels of different marker genes across different clusters in stationary phase S. aureus culture overlaid on the UMAP plot. Marker genes were selected based on a p-value greater than 0.001 and a log 2 FC greater than 0.2. Each dot represents a cell and color shading indicating UMI counts. FigureS7.jpg Figure S7. Marker Genes Identified in static E. coli biofilms by RiboD-PETRI. Expression levels of different marker genes across different clusters in static E. coli biofilms overlaid on the UMAP plot. Marker genes were selected based on a p-value greater than 0.001 and a log 2 FC greater than 3. Each dot represents a cell and color shading indicating UMI counts. FigureS6.jpg Figure S6. Marker Genes Identified in exponential phase C. crescentus culture by RiboD-PETRI. Expression levels of different marker genes across different clusters in exponential phase C. crescentus culture overlaid on the UMAP plot. Marker genes were selected based on a p-value greater than 0.001 and a log 2 FC greater than 0.2. Each dot represents a cell and color shading indicating UMI counts. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3329601","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":374991011,"identity":"3c19bcfe-8e57-4d05-864a-c35ba0272820","order_by":0,"name":"Xiaodan Yan","email":"","orcid":"","institution":"Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Xiaodan","middleName":"","lastName":"Yan","suffix":""},{"id":374991012,"identity":"b18056ba-7299-40d2-bbe8-55efc7fb168a","order_by":1,"name":"Hebin Liao","email":"","orcid":"","institution":"Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Hebin","middleName":"","lastName":"Liao","suffix":""},{"id":374991013,"identity":"bcea3600-7a4b-4ff3-b915-14136831df81","order_by":2,"name":"Chenyi Wang","email":"","orcid":"","institution":"Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Chenyi","middleName":"","lastName":"Wang","suffix":""},{"id":374991014,"identity":"49b6067b-d918-42c4-8bcf-87b4c9ab1f69","order_by":3,"name":"Chun Huang","email":"","orcid":"","institution":"Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Chun","middleName":"","lastName":"Huang","suffix":""},{"id":374991015,"identity":"3057d8ca-931d-460d-b610-ccf749ad4ce5","order_by":4,"name":"Wei Zhang","email":"","orcid":"","institution":"Wuhan University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhang","suffix":""},{"id":374991016,"identity":"97bf1175-895b-4346-a995-2270975087cc","order_by":5,"name":"Chunming Guo","email":"","orcid":"","institution":"Yunnan University","correspondingAuthor":false,"prefix":"","firstName":"Chunming","middleName":"","lastName":"Guo","suffix":""},{"id":374991017,"identity":"a4bc5452-d020-44d0-8b5d-6b5d48998065","order_by":6,"name":"Yingying Pu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYDACZhBhAGYdALMZDhCvhS2BSC0IwGNAnBaD47yHX/MU3LHbLpHzTbqwjUGO70YC4+cCfFoO86VZ8xg8S945I3eb9Mw2BmPJGwnM0jPwauExM+YxOJxscCN3223eNobEDTcS2Jh5iNOS8wykpZ4YLcaPgVrsgFrYQFoSDAhpkQTawjjH4HCCZc8z89885yQMZ5552CyNTwvf+TPGH978OWxvzp782JinzEae73jywc/4tCgcYGCTAipI3ADhSwAxYwMeDQwM8g0MzB9/MDDYG+BVNgpGwSgYBSMaAAC+FkxNdI836gAAAABJRU5ErkJggg==","orcid":"","institution":"Wuhan University","correspondingAuthor":true,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Pu","suffix":""}],"badges":[],"createdAt":"2023-09-06 04:15:22","currentVersionCode":3,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3329601/v3","doiUrl":"https://doi.org/10.21203/rs.3.rs-3329601/v3","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68486798,"identity":"1e78e155-d80c-4635-a3af-83b8e9d0c303","added_by":"auto","created_at":"2024-11-07 19:48:12","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":894199,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 1. Development of RiboD-PETRI and validation of its technical performance in studying population heterogeneity.\u003c/strong\u003e\u0026nbsp;(A) Graphic summary of the RiboD-PETRI method illustrating the incorporation of RiboD after cell pooling and lysis in PETRI-seq. The RiboD protocol is represented by the dashed-line box. In this box, firstly, we perform template-switching oligonucleotides (TSOs) in the mixture of heterozygous chain, then we remove the RNA strand using RNaseH, at this point the system contains r-cDNA and m-cDNA single-stranded mixture. Then we add the r-cDNA probe, which specifically binds to the r-cDNA. The probes are then bound to magnetic beads, allowing the r-cDNA-probe-bead complexes to be separated from the rest of the library.\u0026nbsp;And then we remove the r-cDNA that is attached to the probe by Streptavidin magnetic beads. We then performed amplification of the libraries and sent them for sequencing. We designed separate probe sets for \u003cem\u003eE. coli\u003c/em\u003e, \u003cem\u003eC. crescentus\u003c/em\u003e, and \u003cem\u003eS. aureus\u003c/em\u003e. Each set was specifically constructed to be reverse complementary to the r-cDNA sequences of its respective bacterial species. This species-specific approach ensures high efficiency and specificity in rRNA depletion for each organism. (B) Comparison of non-rRNA (tRNA, mRNA and other non-rRNA) and rRNA UMI counts ratio among different bacterial scRNA-seq methods. Data from PETRI-seq (\u003cem\u003eE. coli\u003c/em\u003e), MicroSPLIT-seq (\u003cem\u003eE. coli\u003c/em\u003e), M3-seq (\u003cem\u003eE. coli\u003c/em\u003e) cited from previous studies. Error bars represent standard deviations of biological replicates. The \"ΔΔ\" label represents the RiboD-PETRI protocol; The \"Ctrl\" label represents the classic PETRI-seq protocol we performed.\u0026nbsp;(C) Comparison of UMI counts per cell between RiboD-PETRI\u0026nbsp;(Table S7)\u0026nbsp;and PETRI (Table S8) at the same unsaturated sequencing depth. (D) Assessment of the effect of rRNA depletion on transcriptional profiles. The Pearson correlation coefficient (r) of UMI counts per gene (log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;UMIs) between RiboD-PETRI\u0026nbsp;(Table S7) and PETRI (Table S9) was calculated for 3790 out of 4141 total genes, excluding those with zero counts in either library. Each point represents a gene. (E) Evaluation of the correlation between RiboD-PETRI (Table S7) data and bulk RNA-seq (Table S10) results. The Pearson correlation coefficient (r) of UMI counts per gene (log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;UMIs) among RiboD-PETRI data and the reads per gene (log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;reads) of bulk RNA-seq data was calculated for 3814 out of 4141 total genes, excluding those with zero counts in either library. Each point represents a gene. All data presented in Fig.1C, D, E were from our own sequencing experiments.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/34b65a6c50fe680a8b576c33.jpg"},{"id":68485872,"identity":"4cfd9a6e-5fa4-43d1-a5ad-f7f6a783786a","added_by":"auto","created_at":"2024-11-07 19:24:12","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3354425,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2. Comprehensive Analysis of single-cell mRNA Transcriptomic Profiles in Exponential Phase \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eusing RiboD-PETRI.\u0026nbsp;\u003c/strong\u003e(A)\u0026nbsp;The number of UMIs detected per cell in recovered cells\u0026nbsp;in exponential period \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;(≥15 UMIs/cell). The cells are ranked from highest to lowest based on the number of detected UMIs, and cells with ≥15 UMIs\u0026nbsp;are selected for plotting. The median number of UMIs is calculated for these selected cells.\u0026nbsp;(B) Distribution of mRNA UMIs captured per cell in RiboD-PETRI data of exponential period \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e, presented as violin plots showing the upper quartile, median, and lower quartile lines. The cells are ranked from highest to lowest based on the number of UMIs detected. Then, specific numbers of cells (indicated above the panel) are selected for plotting. The median number of UMIs is calculated for these selected cells. (C) The number of genes detected per cell in exponential period \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e. The cells are ranked from highest to lowest based on the number of genes detected. Then, specific numbers of cells (indicated above the panel) are selected for plotting. The median number of genes is calculated for these selected cells. (D) Uniform Manifold Approximation and Projection (UMAP) visualization of \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;bacteria during the exponential phase. Data were filtered for cells with UMIs between 200 and 5,000, resulting in 1,464 cells. Each dot represents a cell. (E) Heatmap illustrating the normalized gene expression levels of marker genes in different clusters of exponential period \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e. Marker genes with relatively high expression levels are depicted in yellow, while lower expression levels are shown in purple. Each row represents a gene, and each column represents a cell. (F) Functional enrichment analysis of marker genes of exponential period \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;in cluster 2. Marker genes were selected based on screening criteria of p-value \u0026lt; 0.001 and log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;fold change (FC) \u0026gt; 0.2. The color blocks in these figures represent the p-values of the data points. The color scale ranges from red to blue. Red colors indicate smaller p-values, suggesting higher statistical significance and more reliable results. Blue colors indicate larger p-values, suggesting lower statistical significance and less reliable results. Count is the number of genes enriched into this pathway. (G) Expression levels of marker genes in cluster 2 during the 3-hour exponential period of \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;overlaid on the UMAP plot. Cells with high expression levels are depicted in blue. Marker genes were selected based on a p-value greater than 0.001 and a log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;FC greater than 3. (H) Principal Component Analysis (PCA) performed on screened data of exponential phase \u003cem\u003eE. coli\u003c/em\u003e. The resulting scatterplots show heterogeneity among the populations, with each point representing a cell. (I) Distribution of UMIs on the UMAP results for exponential phase \u003cem\u003eE. coli\u003c/em\u003e. UMAP results reveal heterogeneity among populations, with each point representing a cell and color shading indicating UMI counts (Table S11).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/c4df73b1ea2c01a13e67f544.jpg"},{"id":68486256,"identity":"a6fa8aaf-8e82-430a-8dc1-3708a4622c21","added_by":"auto","created_at":"2024-11-07 19:32:12","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3192034,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3. Single-cell Transcriptomic Analysis and Characterization of Static \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;Biofilm using RiboD-PETRI\u003c/strong\u003e (A-F, H)\u0026nbsp;RiboD-PETRI data from static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm (\u003cem\u003eE. coli \u003c/em\u003e24h static culture)\u0026nbsp;(Table S12, 13). RiboD-PETRI data of static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm\u0026nbsp;were screened for cells with UMIs between 100 and 2000, resulting in 1621 and 3999 cells. (A)\u0026nbsp;The number of UMIs detected per cell in recovered cells\u0026nbsp;in Static \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;biofilms\u0026nbsp;(≥15 UMIs/cell). The cells are ranked from highest to lowest based on the number of detected UMIs, and cells with ≥15 UMIs\u0026nbsp;are selected for plotting. (B) Distribution of mRNA UMIs captured per cell in RiboD-PETRI data of\u0026nbsp;static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm. (C) The number of genes detected per cell in static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm. (D) UMAP visualization of static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm, revealing two small populations of heterogeneous cells in clusters 2 and 3. (E) Inferred expression levels of marker genes from static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm\u0026nbsp;of \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;across different clusters. (F) Enrichment pathways for marker genes of static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm\u0026nbsp;data in cluster 2, selected based on screening criteria of p-value \u0026lt; 0.001 and log\u003csub\u003e2\u003c/sub\u003e\u0026nbsp;fold change (FC) \u0026gt; 0.2. The color blocks in these figures represent the p-values of the data points. (G\u0026nbsp;\u0026amp; H) Dot plot displaying scaled expression levels of marker genes in different clusters of \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;in exponential phase (G) and \u003cem\u003eE. coli \u003c/em\u003ein static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm\u0026nbsp;(H). These genes were markers of static \u003cem\u003eE. coli \u003c/em\u003ebiofilms in cluster 2, identified with screening criteria of p-value \u0026lt; 0.001 and log\u003csub\u003e2 \u003c/sub\u003eFC \u0026gt; 3. Dot size represents the percentage expression of the gene in the cluster, while color indicates the average expression level normalized from 0 to 1 across all clusters for each gene.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/8484321a1934fb55a5d3cae3.jpg"},{"id":68486507,"identity":"115d2e08-f1d3-481b-a934-c0630eab5f96","added_by":"auto","created_at":"2024-11-07 19:40:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1398898,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4. Functional Investigation of Marker Gene \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePdeI\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;in Static \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;Biofilm \u003c/strong\u003e(A\u0026nbsp;\u0026amp; B) UMAP plots showing the distribution of \u003cem\u003epdeI\u003c/em\u003e\u0026nbsp;in single-cell data of exponential period\u003cem\u003e\u0026nbsp;E. coli\u003c/em\u003e\u0026nbsp;(A) and static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm\u0026nbsp;(B). Each dot represents a cell colored by normalized expression levels of genes. (C) Subcellular localization of PdeI-GFP and GFP. Scale bar, 1 μm. (D) c-di-GMP levels (R\u003csup\u003e-1\u003c/sup\u003e\u0026nbsp;score) in \u003cem\u003eE. coli \u003c/em\u003ecells with different BFP, PdeI-BFP,\u0026nbsp;PdeI(G412S)-BFP expression levels (low or high), under the control of the\u003cem\u003e\u0026nbsp;pdeI\u003c/em\u003e\u0026nbsp;native promoter,\u0026nbsp;in static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm. c-di-GMP levels are measured using the c-di-GMP sensor system integrated into \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;cells. R\u003csup\u003e-1\u003c/sup\u003e\u0026nbsp;score was determined using the fluorescent intensity of mVenusNB and mScarlet-I in the system. The fluorescent intensity is measured by\u0026nbsp;flow cytometry. (E) Determination of cellular concentrations of c-di-GMP by HPLC-MS/MS in cells overexpressing PdeI under the control of arabinose promoter, with 0.002% arabinose induction for 2 h (n=3). (F \u0026amp; G) Localization of PdeI-high cells in the biofilm matrix. Cells expressing PdeI-BFP under the control of the\u003cem\u003e\u0026nbsp;pdeI\u003c/em\u003e\u0026nbsp;native promoter were grown in a glass-bottom cell culture dish and stained with SYTO™ 24 for bacterial DNA.\u0026nbsp;Cells expressing BFP under the control of arabinose promoter, with 0.00001% arabinose induction for 24h in a glass-bottom cell culture dish and stained with SYTO\u003csup\u003eTM \u003c/sup\u003e24 for bacterial DNA.\u0026nbsp;(H\u0026nbsp;\u0026amp; I) Heterogeneous expression of PdeI in single-cell data of exponential period\u003cem\u003e\u0026nbsp;E. coli\u003c/em\u003e\u0026nbsp;(H) and \u003cem\u003eE. coli \u003c/em\u003ein static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm (\u003cem\u003eE. coli \u003c/em\u003e24h static culture)\u0026nbsp;(I). Biofilm cells with high or low expression levels of PdeI-BFP were sorted by\u0026nbsp;flow cytometry. (J) Persister counting assay using 150 μg/ml ampicillin on cells with high or low expression levels of BFP, PdeI-BFP and PdeI(G412S)-BFP from static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilm, sorted by\u0026nbsp;flow cytometry.These strains were under the control of the\u003cem\u003e\u0026nbsp;pdeI\u003c/em\u003e\u0026nbsp;native promoter.\u0026nbsp;(K) Time-lapse images of the persister assay observed under a microscope. Static biofilm cells of the PdeI-GFP strain were spotted on a gel pad and treated with 150 μg/ml ampicillin in LB broth. Images were captured over 6 hours at 37\u0026nbsp;°C, followed by the replacement of fresh LB broth to allow persister cell resuscitation. Scale bar, 2 μm. Error bars represent standard deviations of biological replicates. Significance was ascertained by unpaired Student’s \u003cem\u003et\u003c/em\u003e-test; Statistical significance is denoted as\u0026nbsp;*P \u0026lt;0.05, **P \u0026lt; 0.01, \u0026nbsp;***P \u0026lt; 0.001, and ****P \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/a221cf2edfb0b05bbac231ac.png"},{"id":68487062,"identity":"7200e9f5-4785-4ce3-9506-3e4f25a834a2","added_by":"auto","created_at":"2024-11-07 19:56:12","extension":"mp4","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":775516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMovie S1. Time-lapse images of the persister assay using cells with different PdeI-BFP.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"movieS1.mp4","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/31d6409bb89478670b5e6b23.mp4"},{"id":68486260,"identity":"0a7a4f11-24a2-4bba-bdb7-08a46bba82c5","added_by":"auto","created_at":"2024-11-07 19:32:12","extension":"xls","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":25088,"visible":true,"origin":"","legend":"\u003cp\u003eTable S5. Sequencing information of RiboD-PETRI libraries.\u003c/p\u003e","description":"","filename":"TableS5.SequencingInformation.xls","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/005a91d0ddd07ad560315493.xls"},{"id":68485881,"identity":"86e3f224-b458-4f6d-a6fc-84d227ab4354","added_by":"auto","created_at":"2024-11-07 19:24:12","extension":"xls","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":195072,"visible":true,"origin":"","legend":"\u003cp\u003eTable S6. The detailed cost breakdown of RiboD-PETRI.\u003c/p\u003e","description":"","filename":"TableS6.ThecostofRiboDPETRI.xls","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/3e32b654084bafdf04436b97.xls"},{"id":68486262,"identity":"9c1884ff-c1b6-4931-bf42-6c7d6f15e5b3","added_by":"auto","created_at":"2024-11-07 19:32:12","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1001483,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S1. \u003c/strong\u003e(A, B) The number of UMIs detected per cell \u0026nbsp;in recovered cells in different samples (≥15 UMIs/cell): (A) PETRI, (B) RiboD-PETRI at the same unsaturated sequencing depth. The cells are ranked from highest to lowest based on the number of detected UMIs, and cells with ≥15 UMIs are selected for plotting. The median number of UMIs is calculated for these selected cells. (C) Scatterplot illustrating the relationship between reads per cell and counts of UMIs per cell detected from exponential phase \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;data. Each dot represents a cell. (D) Sequencing saturation of data of exponential period \u003cem\u003eE. coli\u003c/em\u003e (3h). We extracted 20%, 40%, 60%, 80% and 100% of the data and further tested their saturation using the saturation calculation method of 10x Genomics. (E\u0026nbsp;\u0026amp; F) Sequencing saturation analysis. We took 20%, 40%, 60%, 80% and 100% of the sequencing data for single-cell analysis and counted the number of genes and UMIs for each cell in these data. The cells were then sorted from largest to smallest values, and cells were taken to count the median number of genes (E) and UMIs (F).\u003c/p\u003e","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/45a6868b28feb93dc70e1d66.jpg"},{"id":68485890,"identity":"3ab7cd91-6a2d-4f9e-9b84-d3a9b5d58fa6","added_by":"auto","created_at":"2024-11-07 19:24:13","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1239776,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure\u0026nbsp;S2. \u0026nbsp;Comprehensive Single-Cell Transcriptomic Analysis of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. aureus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. crescentus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;using RiboD-PETRI. \u003c/strong\u003eTechnical Application of RiboD-PETRI in \u003cem\u003eS. aureus \u003c/em\u003e(SA) (A-F), cultured for 9 hours in MHB medium at 37 °C (Table S14) and \u003cem\u003eC. crescentus\u003c/em\u003e\u0026nbsp;(CC) (G-L), incubated at 37 °C\u0026nbsp;for 3 hours (Table S15). (A, G) The number of UMIs detected per cell in different samples (≥15 UMIs/cell): (A) \u003cem\u003eS. aureus\u003c/em\u003e (SA) and (G) \u003cem\u003eC. crescentus\u003c/em\u003e (CC). (B, H) Distribution of mRNA UMIs captured per cell in RiboD-PETRI data of (B)\u003cem\u003e\u0026nbsp;S. aureus \u003c/em\u003e(SA)\u0026nbsp;and (H) \u003cem\u003eC. crescentus\u003c/em\u003e\u0026nbsp;(CC), presented as violin plots showing the upper quartile, median, and lower quartile lines. The cells are ranked from highest to lowest based on the number of UMIs detected. Then, specific numbers of cells (indicated above the panel) are selected for plotting. The median number of UMIs is calculated for these selected cells. (C, I) The number of genes detected per cell in different samples (C) \u003cem\u003eS. aureus\u003c/em\u003e and\u0026nbsp;(I) \u003cem\u003eC. crescentus\u003c/em\u003e. The cells are ranked from\u0026nbsp;highest to lowest based on the number of genes detected. Then, specific numbers of cells (indicated above the panel) are selected for plotting. The median number of genes is calculated for these selected cells. \"SA\" denotes \u003cem\u003eS. aureus\u003c/em\u003e, and \"CC\" denotes \u003cem\u003eC. crescentus\u003c/em\u003e. (D, J) UMAP visualization of (D) \u003cem\u003eS. aureus\u003c/em\u003e\u0026nbsp;and (J) \u003cem\u003eC. crescentus\u003c/em\u003e, demonstrating the ability of RiboD-PETRI to distinguish population heterogeneity. (E, K) Normalized and Principal Component Analysis (PCA) performed on screened data of (E) \u003cem\u003eS. aureus\u003c/em\u003e and (K) \u003cem\u003eC. crescentus\u003c/em\u003e. The resulting scatterplots show heterogeneity among the populations, with each point representing a cell. (F, L) Distribution of UMIs on the UMAP results for (F) \u003cem\u003eS. aureus\u003c/em\u003e and (L) \u003cem\u003eC. crescentus\u003c/em\u003e. UMAP results reveal heterogeneity among populations, with each point representing a cell and color shading indicating UMI counts.\u003c/p\u003e","description":"","filename":"FigureS2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/fd8cd2adc89cd596cc836b9b.jpg"},{"id":68485885,"identity":"a1d8203e-6ddf-4a8c-9ac6-141c0b3db37d","added_by":"auto","created_at":"2024-11-07 19:24:12","extension":"xls","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":486912,"visible":true,"origin":"","legend":"\u003cp\u003eTable S10. Read per gene of E.coli RNA-seq data in Fig 1E\u003c/p\u003e","description":"","filename":"TableS10.E.coliRNAseqdata.xls","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/439426ea8dd7ad56aa7454ba.xls"},{"id":68485882,"identity":"e38ae4dc-10db-4a8c-bc3d-8b441e33ffb4","added_by":"auto","created_at":"2024-11-07 19:24:12","extension":"xls","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":150528,"visible":true,"origin":"","legend":"\u003cp\u003eTable S1. Primers used in this study\u003c/p\u003e","description":"","filename":"TableS1.Primersusedinthisstudy.xls","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/de993895e5baadd5c28320fa.xls"},{"id":68485883,"identity":"9a2cdf48-6854-4cc8-ae64-d044cb6ca4b2","added_by":"auto","created_at":"2024-11-07 19:24:12","extension":"xls","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":2060288,"visible":true,"origin":"","legend":"\u003cp\u003eTable S3. Data of rRNA and mRNA experssion of PETRI-seq and RiboD-PETRI.\u003c/p\u003e","description":"","filename":"TableS3.rRNAandmRNAexperssionofPETRIseqandRiboDPETRI.xls","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/6e35b58b63a7a3c689270214.xls"},{"id":68486263,"identity":"bc03eeee-fd4c-4db3-96c2-758176e3d72c","added_by":"auto","created_at":"2024-11-07 19:32:13","extension":"jpg","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":2248548,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S3\u003c/strong\u003e. \u003cstrong\u003eEvaluation of Transcriptomic Consistency and Batch Effect Analysis in Static Biofilm \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;Samples \u003c/strong\u003e(A) Scatterplot demonstrating the relationship between reads per cell and counts of UMIs per cell detected from static biofilm \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;data. Two replicates of the sample are included. (B) Calculation of the Pearson correlation coefficient (r) of UMI counts per gene between replicate 1 and replicate 2 of static biofilm \u003cem\u003eE. coli\u003c/em\u003e. The analysis involved 4,062 out of 4,141 total genes, with a significant correlation (p-value \u0026lt; 0.0001, r = 0.96), indicating good replication between samples. Each dot represents a gene. (C) Before\u0026nbsp;batch effects were removed, UMAP plot based on the original identity of static biofilm \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;samples (replicate 1 and replicate 2). Each dot represents a cell, with red indicating replicate 1 and green indicating replicate 2. (D) After\u0026nbsp;batch effects were removed using Harmony,\u0026nbsp;UMAP plot based on the original identity of static biofilm \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;samples (replicate 1 and replicate 2). (E) Principal Component Analysis (PCA) performed on screened data of two replicates of static biofilm \u003cem\u003eE. coli\u003c/em\u003e.\u0026nbsp;The resulting scatterplots show heterogeneity among the populations, with each point representing a cell. (F) Distribution of UMIs on the UMAP results for two replicates of static biofilm \u003cem\u003eE. coli\u003c/em\u003e. UMAP results reveal heterogeneity among populations, with each point representing a cell and color shading indicating UMI counts.\u003c/p\u003e","description":"","filename":"FigureS3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/4a14b54185deec7f6ccd76a1.jpg"},{"id":68485875,"identity":"d598e6fd-005a-44e8-9694-c3703ac953f8","added_by":"auto","created_at":"2024-11-07 19:24:12","extension":"xls","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":23552,"visible":true,"origin":"","legend":"\u003cp\u003eTable S4. The comparison of various methods in rRNA depletion method\u003c/p\u003e","description":"","filename":"TableS4.VariousmethodsinrRNAdepletion.xls","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/c436846fbfa5dcbbd547cca5.xls"},{"id":68485886,"identity":"e2c464e6-e63f-4f1b-a35c-8f73ded03ad5","added_by":"auto","created_at":"2024-11-07 19:24:13","extension":"jpg","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":352013,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S4. Profiling of Marker Genes in exponential phase \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eculture by RiboD-PETRI. \u003c/strong\u003eExpression levels of diverse marker genes across distinct clusters in exponential phase \u003cem\u003eE. coli\u003c/em\u003e\u0026nbsp;culture, visualized through violin plots. Each individual dot represents a single cell, demonstrating the high-resolution, single-cell nature of the RiboD-PETRI analysis.\u003c/p\u003e","description":"","filename":"FigureS4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/4fc7d13718d44f467aa416b2.jpg"},{"id":68485889,"identity":"814ee9fc-5f4e-4e0e-ac98-6dbd9254c793","added_by":"auto","created_at":"2024-11-07 19:24:13","extension":"jpg","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":3209654,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S8. Schematic chart for the structure of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ePdeI.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"FigureS8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/debeb8025296df5cd75b6fe7.jpg"},{"id":68485884,"identity":"21b924fa-2544-4639-aadd-55620666b8c5","added_by":"auto","created_at":"2024-11-07 19:24:12","extension":"jpg","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":489813,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S5\u003c/strong\u003e.\u0026nbsp;\u003cstrong\u003eMarker Genes Identified in stationary phase \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. aureus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;culture by RiboD-PETRI\u003c/strong\u003e. Expression levels of different marker genes\u0026nbsp;across different clusters\u0026nbsp;in stationary phase \u003cem\u003eS. aureus\u003c/em\u003e\u0026nbsp;culture\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eoverlaid on the UMAP plot. Marker genes were selected based on a p-value greater than 0.001 and a log\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eFC greater than 0.2. Each dot represents a cell and color shading indicating UMI counts.\u003c/p\u003e","description":"","filename":"FigureS5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/4ea8e701d232f7ce4b48dc1d.jpg"},{"id":68485888,"identity":"51c33d08-f173-4300-ab45-6fbeafec6e54","added_by":"auto","created_at":"2024-11-07 19:24:13","extension":"jpg","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":464046,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S7\u003c/strong\u003e.\u0026nbsp;\u003cstrong\u003eMarker Genes Identified in static \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE.\u0026nbsp;coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;biofilms by RiboD-PETRI.\u003c/strong\u003e\u0026nbsp;Expression levels of different marker genes\u0026nbsp;across different clusters\u0026nbsp;in static \u003cem\u003eE.\u0026nbsp;coli\u003c/em\u003e\u0026nbsp;biofilms overlaid on the UMAP plot. Marker genes were selected based on a p-value greater than 0.001 and a log\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eFC greater than 3. Each dot represents a cell and color shading indicating UMI counts.\u003c/p\u003e","description":"","filename":"FigureS7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/773ad7b6adb14ca3ba76795b.jpg"},{"id":68485887,"identity":"0e5cb36e-0ad5-4725-b80a-d3ea1848f957","added_by":"auto","created_at":"2024-11-07 19:24:13","extension":"jpg","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":482777,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S6\u003c/strong\u003e.\u0026nbsp;\u003cstrong\u003eMarker Genes Identified in exponential phase \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC. crescentus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;culture by RiboD-PETRI\u003c/strong\u003e. Expression levels of different marker genes\u0026nbsp;across different clusters\u0026nbsp;in exponential phase \u003cem\u003eC. crescentus\u003c/em\u003e\u0026nbsp;culture\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eoverlaid on the UMAP plot. Marker genes were selected based on a p-value greater than 0.001 and a log\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eFC greater than 0.2. Each dot represents a cell\u0026nbsp;and color shading indicating UMI counts.\u003c/p\u003e","description":"","filename":"FigureS6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3329601/v3/cd10a89a52ebf70d6cbd7ac8.jpg"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"bacterial scRNA-seq, biofilms, heterogeneity","lastPublishedDoi":"10.21203/rs.3.rs-3329601/v3","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3329601/v3","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn contrast to mammalian cells, bacterial cells lack mRNA polyadenylated tails, presenting a hurdle in isolating mRNA amidst the prevalent rRNA during single-cell RNA-seq. This study introduces a novel method, Ribosomal RNA-derived cDNA Depletion (RiboD), seamlessly integrated into the PETRI-seq technique, yielding RiboD-PETRI. This innovative approach offers a cost-effective, equipment-free, and high-throughput solution for bacterial single-cell RNA sequencing (scRNA-seq). By efficiently eliminating rRNA reads and substantially enhancing mRNA detection rates (up to 92%), our method enables precise exploration of bacterial population heterogeneity. Applying RiboD-PETRI to investigate biofilm heterogeneity, distinctive subpopulations marked by unique genes within biofilms were successfully identified. Notably, PdeI, a marker for the cell-surface attachment subpopulation, was observed to elevate cyclic diguanylate (c-di-GMP) levels, promoting persister cell formation. Thus, we address a persistent challenge in bacterial single-cell RNA-seq regarding rRNA abundance, exemplifying the utility of this method in exploring biofilm heterogeneity. Our method effectively tackles a long-standing issue in bacterial scRNA-seq: the overwhelming abundance of rRNA. This advancement significantly enhances our ability to investigate the intricate heterogeneity within biofilms at unprecedented resolution.\u003c/p\u003e","manuscriptTitle":"An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity","msid":"","msnumber":"","nonDraftVersions":[{"code":3,"date":"2024-11-07 19:24:07","doi":"10.21203/rs.3.rs-3329601/v3","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":2,"date":"2024-04-01 22:36:18","doi":"10.21203/rs.3.rs-3329601/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2023-10-03 12:46:18","doi":"10.21203/rs.3.rs-3329601/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cdd9e7f2-82ed-433e-9d2f-f8a7f8656fa0","owner":[],"postedDate":"November 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39925141,"name":"Biological sciences/Microbiology/Biofilms"},{"id":39925142,"name":"Biological sciences/Microbiology/Bacteria/Bacterial techniques and applications"}],"tags":[],"updatedAt":"2023-11-21T09:26:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-07 19:24:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v3","identity":"rs-3329601","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3329601","identity":"rs-3329601","version":["v3"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}