Evidence map›Paper›PMID 38414081›Full record

ArticleIrish veterinary journal2024

The mechanistic role of natural antimicrobials in preventing Staphylococcus aureus invasion of MAC-T cells using an in vitro mastitis model.

Igori Balta, David McCleery, Saida Roxana Feier David, Elena Pet, Ducu Stef, Tiberiu Iancu, Ioan Pet, Lavinia Stef, Nicolae Corcionivoschi

Open access · goldAbstract read
In one paragraph

Article in Irish veterinary journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.4field-weighted citation impact, top 9% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Annexin A2: A Double-Edged Sword in Pathogen Infection.Pathogens (Basel, Switzerland) · 2024
    Review
  5. 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

9 authors at 2 institutions in 2 countries.

Igori BaltaFaculty of Bioengineering of Animal Resources, University of Life Sciences King Mihai I from Timisoara, Timisoara, 300645, Romania.
David McCleeryBacteriology Branch, Veterinary Sciences Division, Agri-Food and Biosciences Institute, Northern Ireland, Belfast, BT4 3SD, UK.
Saida Roxana Feier DavidFaculty of Bioengineering of Animal Resources, University of Life Sciences King Mihai I from Timisoara, Timisoara, 300645, Romania.
Elena PetFaculty of Management and Rural Development, University of Life Sciences King Mihai I from Timisoara, Timisoara, 300645, Romania.
Ducu StefFaculty of Food Engineering, University of Life Sciences King Mihai I from Timisoara, Timisoara, 300645, Romania.
Tiberiu IancuFaculty of Management and Rural Development, University of Life Sciences King Mihai I from Timisoara, Timisoara, 300645, Romania.
Ioan PetBacteriology Branch, Veterinary Sciences Division, Agri-Food and Biosciences Institute, Northern Ireland, Belfast, BT4 3SD, UK.
Lavinia StefBacteriology Branch, Veterinary Sciences Division, Agri-Food and Biosciences Institute, Northern Ireland, Belfast, BT4 3SD, UK.
Nicolae CorcionivoschiFaculty of Bioengineering of Animal Resources, University of Life Sciences King Mihai I from Timisoara, Timisoara, 300645, Romania. Nicolae.corcionivoschi@afbini.gov.uk.
Agri Food and Biosciences Institute · GBWest University of Timişoara · RO

Funding

Environtech 49650
6 · The paper itself

Abstract

backgroundStarting primarily as an inflammation of the mammary gland, mastitis is frequently driven by infectious agents such as Staphylococcus aureus. Mastitis has a large economic impact globally, which includes diagnostic, treatment, and the production costs not to mention the potential milk contamination with antimicrobial residues. Currently, mastitis prevention and cure depends on intramammary infusion of antimicrobials, yet, their overuse risks engendering resistant pathogens, posing further threats to livestock.

methodsIn our study we aimed to investigate, in vitro, using bovine mammary epithelial cells (MAC-T), the efficacy of the AuraShield an antimicrobial mixture (As) in preventing S. aureus attachment, internalisation, and inflammation. The antimicrobial mixture (As) included: 5% maltodextrin, 1% sodium chloride, 42% citric acid, 18% sodium citrate, 10% silica, 12% malic acid, 9% citrus extract and 3% olive extract (w/w). RESULTS AND DISCUSSION: Herein we show that As can significantly reduce both adherence and invasion of MAC-T cells by S. aureus, with no impact on cell viability at all concentrations tested (0.1, 0.2, 0.5, 1%) compared with untreated controls. The anti-apoptotic effect of As was achieved by significantly reducing cellular caspase 1, 3 and 8 activities in the infected MAC-T cells. All As concentrations were proven to be subinhibitory, suggesting that Ac can reduce S. aureus virulence without bacterial killing and that the effect could be dual including a host modulation effect. In this context, we show that As can reduce the expression of S. aureus clumping factor (ClfB) and block its interaction with the host Annexin A2 (AnxA2), resulting in decreased bacterial adherence in infection of MAC-T cells. Moreover, the ability of As to block AnxA2 had a significant decreasing effect on the levels of pro inflammatory cytokine released upon S. aureus interaction with MAC-T cells.

conclusionThe results presented in this study indicate that mixtures of natural antimicrobials could potentially be considered an efficient alternative to antibiotics in treating S. aureus induced mastitis.

Indexed as

AnxA2Bovine mammary epithelial cellsClfBMastitisNatural antimicrobialsStaphylococcus aureus

Identifiers

PMID38414081
PMCPMC10898119
OpenAlexW4392195137

What OpenQuestion 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 OpenQuestion graph.