Evidence map›Paper›PMID 38747618›Full record

ArticleMicrobiology spectrum2024

High-throughput DNA extraction strategy for fecal microbiome studies.

Heidi Isokääntä, Natalie Tomnikov, Sanja Vanhatalo, Eveliina Munukka, Pentti Huovinen, Antti J Hakanen, Teemu Kallonen

Abstract read
In one paragraph

Article in Microbiology spectrum, 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. Observational
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Gut Microbiota in T2DM Patients with Microvascular Complications: A 16S rRNA Sequencing Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025
    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

7 authors.

Heidi IsokääntäInfections and Immunity Unit, Institute of Biomedicine, University of Turku, Turku, Finland.ORCID 0000-0002-2443-575X
Natalie TomnikovDepartment of Clinical Microbiology, Tyks Laboratories, Turku University Hospital, Turku, Finland.
Sanja VanhataloInfections and Immunity Unit, Institute of Biomedicine, University of Turku, Turku, Finland.
Eveliina MunukkaClinical Microbiome Bank, Microbe Center, Turku University Hospital and University of Turku, Turku, Finland.
Pentti HuovinenInfections and Immunity Unit, Institute of Biomedicine, University of Turku, Turku, Finland.
Antti J HakanenInfections and Immunity Unit, Institute of Biomedicine, University of Turku, Turku, Finland.
Teemu KallonenInfections and Immunity Unit, Institute of Biomedicine, University of Turku, Turku, Finland.ORCID 0000-0003-1741-6486

Funding

Diabetesliitto (Finnish Diabetes Association)Signe ja Ane Gyllenbergin Säätiö (Signe and Ane Gyllenberg Foundation)Sydäntutkimussäätiö (Finnish Foundation for Cardiovascular Research)
6 · The paper itself

Abstract

Microbiome studies are becoming larger in size to detect the potentially small effect that environmental factors have on our gut microbiomes, or that the microbiome has on our health. Therefore, fast and reproducible DNA isolation methods are needed to handle thousands of fecal samples. We used the Chemagic 360 chemistry and Magnetic Separation Module I (MSMI) instrument to compare two sample preservatives and four different pre-treatment protocols to find an optimal method for DNA isolation from thousands of fecal samples. The pre-treatments included bead beating, sample handling in tube and plate format, and proteinase K incubation. The optimal method offers a sufficient yield of high-quality DNA without contamination. Three human fecal samples (adult, senior, and infant) with technical replicates were extracted. The extraction included negative controls (OMNIgeneGUT, DNA/RNA shield fluid, and Chemagic Lysis Buffer 1) to detect cross-contamination and ZymoBIOMICS Gut Microbiome Standard as a positive control to mimic the human gut microbiome and assess sensitivity of the extraction method. All samples were extracted using Chemagic DNA Stool 200 H96 kit (PerkinElmer, Finland). The samples were collected in two preservatives, OMNIgeneGUT and DNA/RNA shield fluid. DNA quantity was measured using Qubit-fluorometer, DNA purity and quality using gel electrophoresis, and taxonomic signatures with 16S rRNA gene-based sequencing with V3V4 and V4 regions. Bead beating increased bacterial diversity. The largest increase was detected in gram-positive genera IMPORTANCE: Next-generation sequencing (NGS) is a widely used method for determining the composition of the gut microbiota. Due to the differences in the gut microbiota composition between individuals, microbiome studies have expanded into large population studies to maximize detection of small effects on microbe-host interactions. Thus, the demand for a rapid and reliable microbial profiling is continuously increasing, making the optimization of high-throughput 96-format DNA extraction integral for NGS-based downstream applications. However, experimental protocols are prone to bias and errors from sample collection and storage, to DNA extraction, primer selection and sequencing, and bioinformatics analyses. Methodological bias can contribute to differences in microbiome profiles, causing variability across studies and laboratories using different protocols. To improve consistency and confidence of the measurements, the standardization of microbiome analysis methods has been recognized in many fields.

Indexed as

BacteriaDNA, BacterialFecesGastrointestinal MicrobiomeRNA, Ribosomal, 16SAdultAgedHigh-Throughput Nucleotide SequencingHumansInfantMicrobiotaSpecimen HandlingDNA, BacterialRNA, Ribosomal, 16SDNA extractionfecal samplegut microbiomehigh throughputmethod developmentsample preservative

Identifiers

PMID38747618
PMCPMC11237708

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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.