Draft Genome Sequence of Lactobacillus plantarum Strain Lp91, a Promising Indian Probiotic Isolate of Human Gut Origin

Modulation of intestinal barrier function to ameliorate Salmonella infection in mice by oral administration of fermented milks produced with Lactobacillus plantarum MTCC 5690 - a probiotic strain of Indian gut origin

Probiotic Lactobacillus plantarum MTCC 5690, a probiotic strain of Indian gut origin, and milk formulations produced with the same were explored in this study as biotherapeutics by evaluating their functional efficacy against Salmonella infection in mice. The efficacy of milk formulations (fermented/unfermented) of MTCC 5690 for enhancement of intestinal barrier function was determined by monitoring the permeability and histopathology of the intestine. Infected mice fed with probiotic Dahi, fermented probiotic drink and sweetened fermented probiotic drink maintained the health and integrity of the intestinal epithelium as compared to those fed with PBS, milk, unfermented probiotic milk and Dahi. Our relative expression data revealed that the changes caused by MTCC 5690 in intestinal barrier function components were established through modulation of the key regulatory receptors Toll-like receptor 2 and Toll-like receptor 4. The results suggest that fermented milks of MTCC 5690 could enhance the defences of the intestinal barrier in enteric infection condition and, therefore, can be explored as a dietary-based strategy to reduce Salmonella infection in the human gut.

Prediction of Biofilm Inhibiting Peptides: An In silico Approach

Approximately 75% of microbial infections found in humans are caused by microbial biofilms. These biofilms are resistant to host immune system and most of the currently available antibiotics. Small peptides are extensively studied for their role as anti-microbial peptides, however, only a limited studies have shown their potential as inhibitors of biofilm. Therefore, to develop a unique computational method aimed at the prediction of biofilm inhibiting peptides, the experimentally validated biofilm inhibiting peptides sequences were used to extract sequence based features and to identify unique sequence motifs. Biofilm inhibiting peptides were observed to be abundant in positively charged and aromatic amino acids, and also showed selective abundance of some dipeptides and sequence motifs. These individual sequence based features were utilized to construct Support Vector Machine-based prediction models and additionally by including sequence motifs information, the hybrid models were constructed. Using 10-fold cross validation, the hybrid model displayed the accuracy and Matthews Correlation Coefficient (MCC) of 97.83% and 0.87, respectively. On the validation dataset, the hybrid model showed the accuracy and MCC value of 97.19% and 0.84, respectively. The validated model and other tools developed for the prediction of biofilm inhibiting peptides are available freely as web server at http://metagenomics.iiserb.ac.in/biofin/ and http://metabiosys.iiserb.ac.in/biofin/.

Prediction of Biofilm Inhibiting Peptides: An In silico Approach

Approximately 75% of microbial infections found in humans are caused by microbial biofilms. These biofilms are resistant to host immune system and most of the currently available antibiotics. Small peptides are extensively studied for their role as anti-microbial peptides, however, only a limited studies have shown their potential as inhibitors of biofilm. Therefore, to develop a unique computational method aimed at the prediction of biofilm inhibiting peptides, the experimentally validated biofilm inhibiting peptides sequences were used to extract sequence based features and to identify unique sequence motifs. Biofilm inhibiting peptides were observed to be abundant in positively charged and aromatic amino acids, and also showed selective abundance of some dipeptides and sequence motifs. These individual sequence based features were utilized to construct Support Vector Machine-based prediction models and additionally by including sequence motifs information, the hybrid models were constructed. Using 10-fold cross validation, the hybrid model displayed the accuracy and Matthews Correlation Coefficient (MCC) of 97.83% and 0.87, respectively. On the validation dataset, the hybrid model showed the accuracy and MCC value of 97.19% and 0.84, respectively. The validated model and other tools developed for the prediction of biofilm inhibiting peptides are available freely as web server at http://metagenomics.iiserb.ac.in/biofin/ and http://metabiosys.iiserb.ac.in/biofin/.

Comparative genome analysis of the candidate functional starter culture strains Lactobacillus fermentum 222 and Lactobacillus plantarum 80 for controlled cocoa bean fermentation processes

Background

Lactobacillus fermentum 222 and Lactobacillus plantarum 80, isolates from a spontaneous Ghanaian cocoa bean fermentation process, proved to be interesting functional starter culture strains for cocoa bean fermentations. Lactobacillus fermentum 222 is a thermotolerant strain, able to dominate the fermentation process, thereby converting citrate and producing mannitol. Lactobacillus plantarum 80 is an acid-tolerant and facultative heterofermentative strain that is competitive during cocoa bean fermentation processes. In this study, whole-genome sequencing and comparative genome analysis was used to investigate the mechanisms of these strains to dominate the cocoa bean fermentation process.

Results

Through functional annotation and analysis of the high-coverage contigs obtained through 454 pyrosequencing, plantaricin production was predicted for L. plantarum 80. For L. fermentum 222, genes encoding a complete arginine deiminase pathway were attributed. Further, in-depth functional analysis revealed the capacities of these strains associated with carbohydrate and amino acid metabolism, such as the ability to use alternative external electron acceptors, the presence of an extended pyruvate metabolism, and the occurrence of several amino acid conversion pathways. A comparative genome sequence analysis using publicly available genome sequences of strains of the species L. plantarum and L. fermentum revealed unique features of both strains studied. Indeed, L. fermentum 222 possessed genes encoding additional citrate transporters and enzymes involved in amino acid conversions, whereas L. plantarum 80 is the only member of this species that harboured a gene cluster involved in uptake and consumption of fructose and/or sorbose.

Conclusions

In-depth genome sequence analysis of the candidate functional starter culture strains L. fermentum 222 and L. plantarum 80 revealed their metabolic capacities, niche adaptations and functionalities that enable them to dominate the cocoa bean fermentation process. Further, these results offered insights into the cocoa bean fermentation ecosystem as a whole and will facilitate the selection of appropriate starter culture strains for controlled cocoa bean fermentation processes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1927-0) contains supplementary material, which is available to authorized users.