While competition targeting food-borne pathogens is being widely documented, few studies have focused on competition among non-pathogenic food bacteria. Carnobacterium maltaromaticum is a genetically diverse lactic acid bacterium known for comprising several bacteriocinogenic strains with bioprotective potentialities against the food-borne pathogen Listeria monocytogenes. The aim of our study is to examine the network properties of competition among a collection of 73 strains of C. maltaromaticum and to characterize their individual interaction potential. The performed high-throughput competition assays, investigating 5 329 pairwise interactions, showed that intraspecific competition was major in C. maltaromaticum with approximately 56% of the sender strains antagonizing at least one receiver strain. A high diversity of inhibitory and sensitivity spectra was identified along with a majority of narrow inhibitory as well as sensitivity spectra. Through network analysis approach, we determined the highly nested architecture of C. maltaromaticum competition network, thus showing that competition in this species is determined by both the spectrum width of the inhibitory activity of sender strains and the spectrum width of the sensitivity of receiver strains. This study provides knowledge of the competition network in C. maltaromaticum that could be used in rational assembly of compatible microbial strains for the design of mixed starter cultures.

Carnobacterium maltaromaticum is a non-starter lactic acid bacterium (LAB) of interest in the dairy industry for biopreservation. This study investigated the interference competition network and the specialized metabolites biosynthetic gene clusters (BGCs) content in this LAB in order to explore the relationship between the antimicrobial properties and the genome content. Network analysis revealed that the potency of inhibition tended to increase when the inhibition spectrum broadened, but also that several strains exhibited a high potency and narrow spectrum of inhibition. The C. maltaromaticum strains with potent anti-L. monocytogenes were characterized by high potency and a wide intraspecific spectrum. Genome mining of 29 strains revealed the presence of 12 bacteriocin BGCs: four of class I and eight of class II, among which seven belong to class IIa and one to class IIc. Overall, eight bacteriocins and one nonribosomal peptide synthetase and polyketide synthase (NRPS-PKS) BGCs were newly described. The comparison of the antimicrobial properties resulting from the analysis of the network and the BGC genome content allowed us to delineate candidate BGCs responsible for anti-L. monocytogenes and anti-C. maltaromaticum activity. However, it also highlighted that genome analysis is not suitable in the current state of the databases for the prediction of genes involved in the antimicrobial activity of strains with a narrow anti-C. maltaromaticum activity.

Microbial communities offer considerable potential for tackling environmental challenges by improving the functioning of ecosystems. Top-down community engineering is a promising strategy that could be used to obtain communities of desired function. However, the ecological factors that control the balance between community shaping and propagation are not well understood. Dairy backslopping, which consists of using part of the previous production to inoculate a new one, can be used as a model engineering approach to investigate community dynamics during serial propagations. In this study, 26 raw milk samples were serially propagated 6 times each, giving rise to 26 community lineages. Bacterial community structures were analyzed by metabarcoding, and acidification was recorded by pH monitoring. The results revealed that different types of community lineages could be obtained in terms of taxonomic composition and dynamics. Five lineages reached a repeatable community structure in a few propagation steps, with little variation between the final generations, giving rise to stable acidification kinetics. Moreover, these stabilized communities presented a high variability of structure and diverse acidification properties between community lineages. Besides, the other lineages were characterized by different levels of dynamics leading to parallel or divergent trajectories. The functional properties and dynamics of the communities were mainly related to the relative abundance and the taxonomic composition of lactic acid bacteria within the communities. These findings highlight that short-term schemes of serial fermentation can produce communities with a wide range of dynamics and that the balance between community shaping and propagation is intimately linked to community structure. IMPORTANCE: Microbiome applications require approaches for shaping and propagating microbial communities. Shaping allows the selection of communities with desired taxonomic and functional properties, while propagation allows the production of the biomass required to inoculate the engineered communities in the target ecosystem. In top-down community engineering, where communities are obtained from a pool of mixed microorganisms by acting on environmental variables, a major challenge is to master the balance between shaping and propagation. However, the ecological factors that favor high dynamics of community structure and, conversely, those that favor stability during propagation are not well understood. In this work, short-term dairy backslopping was used to investigate the key role of the taxonomic composition and structure of bacterial communities on their dynamics. The results obtained open up interesting prospects for the biotechnological use of microbiomes, particularly in the field of dairy fermentation, to diversify approaches for injecting microbial biodiversity into cheesemaking processes.

Color is one of the first criteria to assess the quality of cheese. However, very limited data are available on the color heterogeneity of the rind and its relationship with microbial community structure. In this study, the color of a wide range of smear-ripened Munster cheeses from various origins was monitored during storage by photographic imaging and data analysis in the CIELAB color space using luminance, chroma, and hue angle as descriptors. Different levels of inter- and intra-cheese heterogeneity were observed. The most heterogeneous Munster cheeses were the darkest with orange-red colors. The most homogeneous were the brightest with yellow-orange. K-means clustering revealed three clusters distinguished by their color heterogeneity. Color analysis coupled with metabarcoding showed that rinds with heterogeneous color exhibited higher microbial diversity associated with important changes in their microbial community structure during storage. In addition, intra-cheese community structure fluctuations were associated with heterogeneity in rind color. The species Glutamicibacter arilaitensis and Psychrobacter nivimaris/piscatorii were found to be positively associated with the presence of undesirable brown patches. This study highlights the close relationship between the heterogeneity of the cheese rind and its microbiota.