Evidence map›Paper›PMID 27107125›Full record

ArticleApplied and environmental microbiology2016

Microbiota of an Italian Grana-Like Cheese during Manufacture and Ripening, Unraveled by 16S rRNA-Based Approaches.

Valentina Alessandria, Ilario Ferrocino, Francesca De Filippis, Mauro Fontana, Kalliopi Rantsiou, Danilo Ercolini, Luca Cocolin

Open access · bronzeAbstract read
In one paragraph

Article in Applied and environmental microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
14.3field-weighted citation impact, top 1% 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

34 citing papers in PubMed, 94 citations in OpenAlex.

  1. Article
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  4. Exploring the Multifaceted GenusJournal of microbiology and biotechnology · 2025
    Review
  5. Article
  6. Review
  7. Foods (Basel, Switzerland) · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. The Microbiota of Grana Padano Cheese. A Review.Foods (Basel, Switzerland) · 2021
    Review
  18. Article
  19. Review
  20. 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 at 2 institutions in 1 country.

Valentina AlessandriaDepartment of Agricultural, Forest and Food Science, University of Turin, Grugliasco, Italy.
Ilario FerrocinoDepartment of Agricultural, Forest and Food Science, University of Turin, Grugliasco, Italy.
Francesca De FilippisDepartment of Agricultural Sciences, Division of Microbiology, University of Naples Federico II, Portici, Italy.
Mauro FontanaBiraghi Spa, Cavallermaggiore (CN), Italy.
Kalliopi RantsiouDepartment of Agricultural, Forest and Food Science, University of Turin, Grugliasco, Italy.
Danilo ErcoliniDepartment of Agricultural Sciences, Division of Microbiology, University of Naples Federico II, Portici, Italy.
Luca CocolinDepartment of Agricultural, Forest and Food Science, University of Turin, Grugliasco, Italy lucasimone.cocolin@unito.it.
University of Turin · ITUniversity of Naples Federico II · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelledThe microbial ecology of cheese involves a rich and complex interaction between starter lactic acid bacteria and nonstarter lactic acid bacteria (NSLAB), mainly originating from raw milk and/or from the environment, that can contribute to the final characteristics of cheese. The aim of the present research was the exploration of the active microbiota by RNA-based approaches during the manufacturing and ripening of a Grana-like cheese. Reverse transcriptase PCR (RT-PCR)-denaturing gradient gel electrophoresis (DGGE) and RNA-based high-throughput sequencing were applied to profile microbial populations, while the enumeration of active bacteria was carried out by using quantitative PCR (qPCR). Three different cheese productions (named D, E, and F) collected in the same month from the same dairy plant were analyzed. The application of the qPCR protocol revealed the presence of 7 log CFU/ml of bacterial load in raw milk, while, during ripening, active bacterial populations ranged from <4 to 8 log CFU/ml. The natural whey starters used in the three productions showed the same microbiota composition, characterized by the presence of Lactobacillus helveticus and Lactobacillus delbrueckii Nevertheless, beta-diversity analysis of the 16S rRNA sequencing data and RT-PCR-DGGE showed a clear clustering of the samples according to the three productions, probably driven by the different milks used. Milk samples were found to be characterized by the presence of several contaminants, such as Propionibacterium acnes, Acidovorax, Acinetobacter, Pseudomonas, and NSLAB. The core genera of the starter tended to limit the development of the spoilage bacteria only in two of the three batches. This study underlines the influence of different factors that can affect the final microbiota composition of the artisanal cheese. IMPORTANCE: This study highlights the importance of the quality of the raw milk in the production of a hard cheese. Independent from the use of a starter culture, raw milk with low microbiological quality can negatively affect the populations of lactic acid bacteria and, as a consequence, impact the quality of the final product due to metabolic processes associated with spoilage bacteria.

Indexed as

BiotaBacteriaBacterial LoadCheeseCluster AnalysisDenaturing Gradient Gel ElectrophoresisDNA, BacterialDNA, RibosomalHigh-Throughput Nucleotide SequencingItalyReal-Time Polymerase Chain ReactionReverse Transcriptase Polymerase Chain ReactionRNA, Ribosomal, 16SSequence Analysis, DNADNA, BacterialDNA, RibosomalRNA, Ribosomal, 16S

Identifiers

PMID27107125
PMCPMC4907185
OpenAlexW2339133429

What OpenQuestion holds

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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.