Evidence map›Paper›PMID 37990977›Full record

ArticleBiotechnology and bioengineering2024

On-line targeted metabolomics for real-time monitoring of relevant compounds in fermentation processes.

Joan Cortada-Garcia, Jennifer Haggarty, Stefan Weidt, Rónán Daly, S Alison Arnold, Karl Burgess

Open access · hybridAbstract read
In one paragraph

Article in Biotechnology and bioengineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 28% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

6 authors at 3 institutions in 2 countries.

Joan Cortada-GarciaSchool of Biological Sciences, Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh, UK.ORCID 0000-0001-5989-9215
Jennifer HaggartyGlasgow Polyomics, University of Glasgow, Glasgow, UK.
Stefan WeidtGlasgow Polyomics, University of Glasgow, Glasgow, UK.
Rónán DalyGlasgow Polyomics, University of Glasgow, Glasgow, UK.
S Alison ArnoldIngenza Ltd., Roslin Innovation Centre, Roslin, UK.
Karl BurgessSchool of Biological Sciences, Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-0881-715X
University of Glasgow · GBQuantitative BioSciences · USRoslin Institute · GB

Funding

Biotechnology and Biological Sciences Research CouncilBiotechnology and Biological Sciences Research Council BB/R505523/1
6 · The paper itself

Abstract

Fermentation monitoring is a powerful tool for bioprocess development and optimization. On-line metabolomics is a technology that is starting to gain attention as a bioprocess monitoring tool, allowing the direct measurement of many compounds in the fermentation broth at a very high time resolution. In this work, targeted on-line metabolomics was used to monitor 40 metabolites of interest during three Escherichia coli succinate production fermentation experiments every 5 min with a triple quadrupole mass spectrometer. This allowed capturing high-time resolution biological data that can provide critical information for process optimization. For nine of these metabolites, simple univariate regression models were used to model compound concentration from their on-line mass spectrometry peak area. These on-line metabolomics univariate models performed comparably to vibrational spectroscopy multivariate partial least squares regressions models reported in the literature, which typically are much more complex and time consuming to build. In conclusion, this work shows how on-line metabolomics can be used to directly monitor many bioprocess compounds of interest and obtain rich biological and bioprocess data.

Indexed as

MetabolomicsFermentationMass SpectrometrySpectrum Analysisbioprocess monitoringfermentation monitoringon-line metabolomicsprocess analytical technologiesreal-time metabolomics

Identifiers

PMID37990977
PMCPMC10953439
OpenAlexW4388913217

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.