Evidence map›Paper›PMID 27838895›Full record

ArticleJournal of industrial microbiology & biotechnology2017

A novel concentration and viability detection method for Brettanomyces using the Cellometer image cytometry.

Brian Martyniak, Jason Bolton, Dmitry Kuksin, Suzanne M Shahin, Leo Li-Ying Chan

Abstract read
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In one paragraph

Article in Journal of industrial microbiology & biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 26% 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

1 citing paper in PubMed, 10 citations in OpenAlex.

  1. 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

5 authors at 1 institution in 1 country.

Brian MartyniakCooperative Extension and the School of Food and Agriculture, University of Maine, Orono, ME, 04469, USA.
Jason BoltonCooperative Extension and the School of Food and Agriculture, University of Maine, Orono, ME, 04469, USA.
Dmitry KuksinDepartment of Technology R&D, Nexcelom Bioscience LLC, 360 Merrimack St. Building 9, Lawrence, MA, 01843, USA.
Suzanne M ShahinDepartment of Technology R&D, Nexcelom Bioscience LLC, 360 Merrimack St. Building 9, Lawrence, MA, 01843, USA.
Leo Li-Ying ChanDepartment of Technology R&D, Nexcelom Bioscience LLC, 360 Merrimack St. Building 9, Lawrence, MA, 01843, USA. lchan@nexcelom.com.
University of Maine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brettanomyces spp. can present unique cell morphologies comprised of excessive pseudohyphae and budding, leading to difficulties in enumerating cells. The current cell counting methods include manual counting of methylene blue-stained yeasts or measuring optical densities using a spectrophotometer. However, manual counting can be time-consuming and has high operator-dependent variations due to subjectivity. Optical density measurement can also introduce uncertainties where instead of individual cells counted, an average of a cell population is measured. In contrast, by utilizing the fluorescence capability of an image cytometer to detect acridine orange and propidium iodide viability dyes, individual cell nuclei can be counted directly in the pseudohyphae chains, which can improve the accuracy and efficiency of cell counting, as well as eliminating the subjectivity from manual counting. In this work, two experiments were performed to demonstrate the capability of Cellometer image cytometer to monitor Brettanomyces concentrations, viabilities, and budding/pseudohyphae percentages. First, a yeast propagation experiment was conducted to optimize software counting parameters for monitoring the growth of Brettanomyces clausenii, Brettanomyces bruxellensis, and Brettanomyces lambicus, which showed increasing cell concentrations, and varying pseudohyphae percentages. The pseudohyphae formed during propagation were counted either as multiple nuclei or a single multi-nuclei organism, where the results of counting the yeast as a single multi-nuclei organism were directly compared to manual counting. Second, a yeast fermentation experiment was conducted to demonstrate that the proposed image cytometric analysis method can monitor the growth pattern of B. lambicus and B. clausenii during beer fermentation. The results from both experiments displayed different growth patterns, viability, and budding/pseudohyphae percentages for each Brettanomyces species. The proposed Cellometer image cytometry method can improve efficiency and eliminate operator-dependent variations of cell counting compared with the traditional methods, which can potentially improve the quality of beverage products employing Brettanomyces yeasts.

Indexed as

BeerFermentationBrettanomycesCell CountCell NucleusImage CytometryIndustrial MicrobiologyMicroscopy, FluorescencePropidiumSaccharomyces cerevisiaePropidiumBrettanomycesBuddingCell countingCellometerFermentationImage cytometryPropagationPseudohyphae

Identifiers

PMID27838895
OpenAlexW2549526615

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.