Lactococcus lactis is one of the most extensively used lactic acid bacteria for the manufacture of dairy products. Exploring the biodiversity of L. lactis is extremely promising both to acquire new knowledge and for food and health-driven applications. L. lactis is divided into four subspecies: lactis, cremoris, hordniae and tructae, but only subsp. lactis and subsp. cremoris are of industrial interest. Due to its various biotopes, Lactococcus subsp. lactis is considered the most diverse. The diversity of L. lactis subsp. lactis has been assessed at genetic, genomic and phenotypic levels. Multi-Locus Sequence Type (MLST) analysis of strains from different origins revealed that the subsp. lactis can be classified in two groups: “domesticated” strains with low genetic diversity, and “environmental” strains that are the main contributors of the genetic diversity of the subsp. lactis. As expected, the phenotype investigation of L. lactis strains reported here revealed highly diverse carbohydrate metabolism, especially in plant- and gut-derived carbohydrates, diacetyl production and stress survival. The integration of genotypic and phenotypic studies could improve the relevance of screening culture collections for the selection of strains dedicated to specific functions and applications.

Adaptation of Lactococcus lactis towards progressive carbon starvation is mediated by three different types of transcriptomic responses: (i) global responses, i.e., general decreases of functions linked to bacterial growth and lack of induction of the general stress response; (ii) specific responses functionally related to glucose exhaustion, i.e., underexpression of central metabolism genes, induction of alternative sugar transport and metabolism, and induction of the arginine deiminase pathway; and (iii) other responses never described previously during carbon starvation.

Lactococcus lactis is used extensively for the production of various cheeses. At every stage of cheese fabrication, L. lactis has to face several stress-generating conditions that result from its own modification of the environment as well as externally imposed conditions. We present here the first in situ global gene expression profile of L. lactis in cheeses made from milk concentrated by ultrafiltration (UF-cheeses), a key economical cheese model. The transcriptomic response of L. lactis was analyzed directly in a cheese matrix, starting from as early as 2 h and continuing for 7 days. The growth of L. lactis stopped after 24 h, but metabolic activity was maintained for 7 days. Conservation of its viability relied on an efficient proteolytic activity measured by an increasing, quantified number of free amino acids in the absence of cell lysis. Extensive downregulation of genes under CodY repression was found at day 7. L. lactis developed multiple strategies of adaptation to stressful modifications of the cheese matrix. In particular, expression of genes involved in acidic- and oxidative-stress responses was induced. L. lactis underwent unexpected carbon limitation characterized by an upregulation of genes involved in carbon starvation, principally due to the release of the CcpA control. We report for the first time that in spite of only moderately stressful conditions, lactococci phage is repressed under UF-cheese conditions.

Lactococcus lactis NCDO 2118 was previously selected for its ability to decarboxylate glutamate to γ-aminobutyric acid (GABA), an interesting nutritional supplement able to improve mood and relaxation. Amino acid decarboxylation is generally considered as among the biochemical systems allowing lactic acid bacteria to counteracting acidic stress and obtaining metabolic energy. These strategies also include arginine deiminase pathway and malolactic fermentation but little is known about their possible interactions of with GABA production. In the present study, the effects of glutamate, arginine and malate (i.e., the substrates of these acid-resistance pathways) on L. lactis NCDO 2118 growth and GABA production performances were analyzed. Both malate and arginine supplementation resulted in an efficient reduction of acidity and improvement of bacterial biomass compared to glutamate supplementation. Glutamate decarboxylation was limited to narrow environmental conditions (pH < 5.1) and physiological state (stationary phase). However, some conditions were able to improve GABA production or activate glutamate decarboxylation system even outside of this compass. Arginine clearly stimulated glutamate decarboxylation: the highest GABA production (8.6 mM) was observed in cultures supplemented with both arginine and glutamate. The simultaneous addition of arginine, malate and glutamate enabled earlier GABA production (i.e., during exponential growth) at relatively high pH (6.5). As far as we know, no previous study has reported GABA production in such conditions. Although further studies are needed to understand the molecular basis of these phenomena, these results represent important keys suitable of application in GABA production processes.

Background: In bacteria, the weak correlations at the genome scale between mRNA and protein levels suggest that not all mRNAs are translated with the same efficiency. To experimentally explore mRNA translational level regulation at the systemic level, the detailed translational status (translatome) of all mRNAs was measured in the model bacterium Lactococcus lactis in exponential phase growth. Results: Results demonstrated that only part of the entire population of each mRNA species was engaged in translation. For transcripts involved in translation, the polysome size reached a maximum of 18 ribosomes. The fraction of mRNA engaged in translation (ribosome occupancy) and ribosome density were not constant for all genes. This high degree of variability was analyzed by bioinformatics and statistical modeling in order to identify general rules of translational regulation. For most of the genes, the ribosome density was lower than the maximum value revealing major control of translation by initiation. Gene function was a major translational regulatory determinant. Both ribosome occupancy and ribosome density were particularly high for transcriptional regulators, demonstrating the positive role of translational regulation in the coordination of transcriptional networks. mRNA stability was a negative regulatory factor of ribosome occupancy and ribosome density, suggesting antagonistic regulation of translation and mRNA stability. Furthermore, ribosome occupancy was identified as a key component of intracellular protein levels underlining the importance of translational regulation. Conclusions: We have determined, for the first time in a bacterium, the detailed translational status for all mRNAs present in the cell. We have demonstrated experimentally the high diversity of translational states allowing individual gene differentiation and the importance of translation-level regulation in the complex process linking gene expression to protein synthesis.