Lactococcus lactis Diversity Revealed by Targeted Amplicon Sequencing of purR Gene, Metabolic Comparisons and Antimicrobial Properties in an Undefined Mixed Starter Culture Used for Soft-Cheese Manufacture.
Sabrina SaltajiOlivier RuéValérie SopenaSophie SabléFatoumata TambadouSandrine DidelotRomain ChevrotPublished in: Foods (Basel, Switzerland) (2020)
The undefined mixed starter culture (UMSC) is used in the manufacture of cheeses. Deciphering UMSC microbial diversity is important to optimize industrial processes. The UMSC was studied using culture-dependent and culture-independent based methods. MALDI-TOF MS enabled identification of species primarily from the Lactococcus genus. Comparisons of carbohydrate metabolism profiles allowed to discriminate five phenotypes of Lactococcus (n = 26/1616). The 16S sequences analysis (V1-V3, V3-V4 regions) clustered the UMSC microbial diversity into two Lactococcus operational taxonomic units (OTUs). These clustering results were improved with the DADA2 algorithm on the housekeeping purR sequences. Five L. lactis variants were detected among the UMSC. The whole-genome sequencing of six isolates allowed for the identification of the lactis subspecies using Illumina® (n = 5) and Pacbio® (n = 1) technologies. Kegg analysis confirmed the L. lactis species-specific niche adaptations and highlighted a progressive gene pseudogenization. Then, agar spot tests and agar well diffusion assays were used to assess UMSC antimicrobial activities. Of note, isolate supernatants (n = 34/1616) were shown to inhibit the growth of Salmonella ser. Typhimurium CIP 104115, Lactobacillus sakei CIP 104494, Staphylococcus aureus DSMZ 13661, Enterococcus faecalis CIP103015 and Listeria innocua CIP 80.11. Collectively, these results provide insightful information about UMSC L. lactis diversity and revealed a potential application as a bio-protective starter culture.
Keyphrases
- staphylococcus aureus
- copy number
- single cell
- genetic diversity
- microbial community
- machine learning
- escherichia coli
- listeria monocytogenes
- genome wide
- mass spectrometry
- health information
- deep learning
- lactic acid
- risk assessment
- pseudomonas aeruginosa
- transcription factor
- climate change
- rna seq
- genome wide identification