Evidence map›Paper›PMID 39968047›Full record

ArticleFrontiers in microbiology2024

High throughput single cell metagenomic sequencing with semi-permeable capsules: unraveling microbial diversity at the single-cell level in sewage and fecal microbiomes.

Meilee Ling, Judit Szarvas, Vaida Kurmauskaitė, Vaidotas Kiseliovas, Rapolas Žilionis, Baptiste Avot, Patrick Munk, Frank M Aarestrup

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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  5. Review
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  8. Computational Metagenomics: State of the Art.International journal of molecular sciences · 2025
    Review
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Meilee Ling *Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kgs Lyngby, Denmark.
Judit Szarvas *Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kgs Lyngby, Denmark.
Vaida KurmauskaitėAtrandi Biosciences, Vilnius, Lithuania.
Vaidotas KiseliovasAtrandi Biosciences, Vilnius, Lithuania.
Rapolas ŽilionisAtrandi Biosciences, Vilnius, Lithuania.
Baptiste AvotResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kgs Lyngby, Denmark.
Patrick MunkResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kgs Lyngby, Denmark.
Frank M AarestrupResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kgs Lyngby, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell sequencing may serve as a powerful complementary technique to shotgun metagenomics to study microbiomes. This emerging technology allows the separation of complex microbial communities into individual bacterial cells, enabling high-throughput sequencing of genetic material from thousands of singular bacterial cells in parallel. Here, we validated the use of microfluidics and semi-permeable capsules (SPCs) technology (Atrandi) to isolate individual bacterial cells from sewage and pig fecal samples. Our method involves extracting and amplifying single bacterial DNA within individual SPCs, followed by combinatorial split-and-pool single-amplified genome (SAG) barcoding and short-read sequencing. We tested two different sequencing approaches with different numbers of SPCs from the same sample for each sequencing run. Using a deep sequencing approach, we detected 1,796 and 1,220 SAGs, of which 576 and 599 were used for further analysis from one sewage and one fecal sample, respectively. In shallow sequencing data, we aimed for 10-times more cells and detected 12,731 and 17,909 SAGs, of which we used 2,456 and 1,599 for further analysis for sewage and fecal samples, respectively. Additionally, we identified the top 10 antimicrobial resistance genes (ARGs) in both sewage and feces samples and linked them to their individual host bacterial species.

Indexed as

antimicrobial resistance (AMR)metagenomicsmicrobial diversitypig fecal samplesewagesingle cell sequencing

Identifiers

PMID39968047
PMCPMC11834865

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Registered trials

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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.