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An improved bacterial single-cell RNA-seq reveals biofilm heterogeneity.

Xiaodan Yan | Hebin Liao | Chenyi Wang | Chun Huang | Wei Zhang | Chunming Guo | Yingying Pu
eLife | 2024

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.

Pubmed ID: 39689163

Associated grants

  • Agency: National Natural Science Foundation of China,
    Id: 31970089
  • Agency: National Key Research and Development Program of China,
    Id: 2021YFC2701602
  • Agency: Science Fund for Distinguished Young Scholars of Hunan Province,
    Id: 2022CFA077
  • Agency: Fundamental Research Funds for the Central Universities,
    Id: 2042022dx0003
  • Agency: Major Project of Guangzhou National Laboratory,
    Id: GZNL2024A01023
  • Agency: Natural Science Foundation of Yunnan Province,
    Id: 202001BB050005

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This is a list of tools and resources that we have found mentioned in this publication.


R Project for Statistical Computing (tool)

RRID:SCR_001905

Software environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.

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SAMTOOLS (tool)

RRID:SCR_002105

Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.

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FlowJo (tool)

RRID:SCR_008520

Software for single-cell flow cytometry analysis. Its functions include management, display, manipulation, analysis and publication of the data stream produced by flow and mass cytometers.

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Subread (tool)

RRID:SCR_009803

Software package for high-performance read alignment, quantification and mutation discovery.General purpose read aligner which can be used to map both genomic DNA-seq reads and RNA-seq reads. Subread aligner as fast, accurate and scalable read mapping by seed-and-vote.These programs were also implemented in Bioconductor R package Rsubread.

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featureCounts (tool)

RRID:SCR_012919

A read summarization program, which counts mapped reads for the genomic features such as genes and exons.

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Fiji (software resource)

RRID:SCR_002285

Software package as distribution of ImageJ and ImageJ2 together with Java, Java3D and plugins organized into coherent menu structure. Used to assist research in life sciences.

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