ReviewNature protocols2024
ProBac-seq, a bacterial single-cell RNA sequencing methodology using droplet microfluidics and large oligonucleotide probe sets.
Review in Nature protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- A Microcapsule-Integrated smRandom-seq Platform Enables Fixation-Free Single Microbe RNA Sequencing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Simultaneous measurements of translation rate and transcriptome uncovers linked regulation within an active bacterial cell population.Science advances · 2026Article
- Decoding the spatiotemporal heterogeneity of bacterial virulence gene expression using single-cell approaches.Frontiers in microbiology · 2026Review
- Review
- The tumor microbiome in cancer progression: mechanisms and therapeutic potential.Molecular cancer · 2025Review
- Microbiome Single Cell Atlases Generated with a Commercial Instrument.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- From specialization to broad adoption: Key trends in droplet microfluidic innovations enhancing accessibility to non-experts.Biomicrofluidics · 2025Article
- The single-cell revolution in transplantation: high-resolution mapping of graft rejection, tolerance, and injury.Frontiers in immunology · 2025Review
- Multi-omics in exploring the pathophysiology of diabetic retinopathy.Frontiers in cell and developmental biology · 2024Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Methods that measure the transcriptomic state of thousands of individual cells have transformed our understanding of cellular heterogeneity in eukaryotic cells since their introduction in the past decade. While simple and accessible protocols and commercial products are now available for the processing of mammalian cells, these existing technologies are incompatible with use in bacterial samples for several fundamental reasons including the absence of polyadenylation on bacterial messenger RNA, the instability of bacterial transcripts and the incompatibility of bacterial cell morphology with existing methodologies. Recently, we developed ProBac sequencing (ProBac-seq), a method that overcomes these technical difficulties and provides high-quality single-cell gene expression data from thousands of bacterial cells by using messenger RNA-specific probes. Here we provide details for designing large oligonucleotide probe sets for an organism of choice, amplifying probe sets to produce sufficient quantities for repeated experiments, adding unique molecular indexes and poly-A tails to produce finalized probes, in situ probe hybridization and single-cell encapsulation and library preparation. This protocol, from the probe amplification to the library preparation, requires ~7 d to complete. ProBac-seq offers several advantages over other methods by capturing only the desired target sequences and avoiding nondesired transcripts, such as highly abundant ribosomal RNA, thus enriching for signal that better informs on cellular state. The use of multiple probes per gene can detect meaningful single-cell signals from cells expressing transcripts to a lesser degree or those grown in minimal media and other environmentally relevant conditions in which cells are less active. ProBac-seq is also compatible with other organisms that can be profiled by in situ hybridization techniques.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.