A novel approach to Lactiplantibacillus plantarum: From probiotic properties to the omics insights

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Abstract

Lactiplantibacillus plantarum (previously known as Lactobacillus plantarum) strains are one of the lactic acid bacteria (LAB) commonly used in fermentation and their probiotic and functional properties along with their health-promoting roles come to the fore. Food-derived L. plantarum strains have shown good resistance and adhesion in the gastrointestinal tract (GI) and excellent antioxidant and antimicrobial properties. Furthermore, many strains of L. plantarum can produce bacteriocins with interesting antimicrobial activity. This probiotic properties of L. plantarum and existing in different niches give a great potential to have beneficial effects on health. It is also has been shown that L. plantarum can regulate the intestinal microbiota composition in a good way. Recently, omics approaches such as metabolomics, secretomics, proteomics, transcriptomics and genomics try to understand the roles and mechanisms of L. plantarum that are related to its functional characteristics. This review provides an overview of the probiotic properties, including the specific interactions between microbiota and host, and omics insights of L. plantarum.

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A taxonomic note on the genus Lactobacillus: Description of 23 novel genera, emended description of the genus Lactobacillus Beijerinck 1901, and union of Lactobacillaceae and Leuconostocaceae

Jinshui Zheng, Stijn Wittouck, Elisa Salvetti … (2020)

The genus Lactobacillus comprises 261 species (at March 2020) that are extremely diverse at phenotypic, ecological and genotypic levels. This study evaluated the taxonomy of Lactobacillaceae and Leuconostocaceae on the basis of whole genome sequences. Parameters that were evaluated included core genome phylogeny, (conserved) pairwise average amino acid identity, clade-specific signature genes, physiological criteria and the ecology of the organisms. Based on this polyphasic approach, we propose reclassification of the genus Lactobacillus into 25 genera including the emended genus Lactobacillus, which includes host-adapted organisms that have been referred to as the Lactobacillus delbrueckii group, Paralactobacillus and 23 novel genera for which the names Holzapfelia, Amylolactobacillus, Bombilactobacillus, Companilactobacillus, Lapidilactobacillus, Agrilactobacillus, Schleiferilactobacillus, Loigolactobacilus, Lacticaseibacillus, Latilactobacillus, Dellaglioa, Liquorilactobacillus, Ligilactobacillus, Lactiplantibacillus, Furfurilactobacillus, Paucilactobacillus, Limosilactobacillus, Fructilactobacillus, Acetilactobacillus, Apilactobacillus, Levilactobacillus, Secundilactobacillus and Lentilactobacillus are proposed. We also propose to emend the description of the family Lactobacillaceae to include all genera that were previously included in families Lactobacillaceae and Leuconostocaceae. The generic term 'lactobacilli' will remain useful to designate all organisms that were classified as Lactobacillaceae until 2020. This reclassification reflects the phylogenetic position of the micro-organisms, and groups lactobacilli into robust clades with shared ecological and metabolic properties, as exemplified for the emended genus Lactobacillus encompassing species adapted to vertebrates (such as Lactobacillus delbrueckii, Lactobacillus iners, Lactobacillus crispatus, Lactobacillus jensensii, Lactobacillus johnsonii and Lactobacillus acidophilus) or invertebrates (such as Lactobacillus apis and Lactobacillus bombicola).

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More Is Better: Recent Progress in Multi-Omics Data Integration Methods

Sijia Huang, Kumardeep Chaudhary, Lana Garmire (2017)

Multi-omics data integration is one of the major challenges in the era of precision medicine. Considerable work has been done with the advent of high-throughput studies, which have enabled the data access for downstream analyses. To improve the clinical outcome prediction, a gamut of software tools has been developed. This review outlines the progress done in the field of multi-omics integration and comprehensive tools developed so far in this field. Further, we discuss the integration methods to predict patient survival at the end of the review.

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Transcriptomics technologies

Rohan Lowe, Neil Shirley, Mark Bleackley … (2017)

Transcriptomics technologies are the techniques used to study an organism’s transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst noncoding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. The first attempts to study the whole transcriptome began in the early 1990s, and technological advances since the late 1990s have made transcriptomics a widespread discipline. Transcriptomics has been defined by repeated technological innovations that transform the field. There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA sequencing (RNA-Seq), which uses high-throughput sequencing to capture all sequences. Measuring the expression of an organism’s genes in different tissues, conditions, or time points gives information on how genes are regulated and reveals details of an organism’s biology. It can also help to infer the functions of previously unannotated genes. Transcriptomic analysis has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease. An analysis of gene expression in its entirety allows detection of broad coordinated trends which cannot be discerned by more targeted assays.