The biological processes of interest to agro-industry involve numerous bacterial species. Lactic acid bacteria produce metabolites capable of fermenting food products and modifying their organoleptic properties, and plant-growth-promoting rhizobacteria can act as biofertilizers, biostimulants, or biocontrol agents in agriculture. The protocol of conventional techniques for bacterial identification, currently based on genotyping and phenotyping, require specific sample preparation and destruction. The work presented herein details a method for rapid identification of lactic acid bacteria and rhizobacteria at the genus and species level. To develop the method, bacteria were inoculated on an agar medium and analyzed by near infrared (NIR) and ultraviolet-visible-NIR (UV-Vis-NIR) spectroscopy. Artificial neural network models applied to the UV-Vis-NIR spectra correctly identified the genus (species) of 70% (63%) of the lactic acid bacteria and 67% of the rhizobacteria on an independent prediction set of unknown bacterial strains. These results demonstrate the potential of UV-Vis-NIR spectroscopy to identify bacteria directly on agar plates.
Lactococcus lactis group (composed of the lactis and cremoris subspecies, recently reassigned as two distinct species) plays a major role in dairy fermentations. Usually present in starter cultures, the two species enable efficient acidification and improve the organoleptic qualities of the final product. Biovar diacetylactis strains produce diacetyl and acetoin, aromas from the citrate metabolization. As these populations have distinct genomic and phenotypic characteristics, the proportions of each other will affect the final product. Today, there is no quantitative test able to distinguish between the two species and the biovar in dairy ecosystems. In this study, we developed a specific, reliable, and accurate strategy to quantify these populations using, species-, and diacetylactis-specific fluorescent probes in digital droplet PCR assays (ddPCR). Species were distinguished based on three single nucleotide polymorphisms in the glutamate decarboxylase gadB gene, and the citD gene involved in citrate metabolism was used to target the biovar. Used in duplex or singleplex, these probes made it possible to measure the proportion of each population. At 59 • C, the probes showed target specificity and responded negatively to the non-target species usually found in dairy environments. Depending on the probe, limit of detection values in milk matrix ranged from 3.6 × 10 3 to 1.8 × 10 4 copies/ml. The test was applied to quantify sub-populations in the L. lactis group during milk fermentation with a commercial starter. The effect of temperature and pH on the balance of the different populations was pointed out. At the initial state, lactis and cremoris species represent, respectively, 75% and 28% of the total L. lactis group and biovar diacetylactis strains represent 21% of the lactis species strains. These ratios varied as a function of temperature (22 • C or 35 • C) and acidity (pH 4.5 or 4.3) with cremoris species promoted at 22 • C and pH4.5 compared to at 35 • C. The biovar diacetylactis strains were less sensitive to acid stress at 35 • C. This methodology proved to be useful for quantifying lactis and cremoris species and biovar diacetylactis, and could complete 16S metagenomics studies for the deeply description of L. lactis group in complex ecosystems.
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