Single-cell rapid identification, in situ viability and vitality profiling, and genome-based source-tracking for probiotics products

Rapid identification of lactic acid bacteria at species/subspecies level via ensemble learning of Ramanomes

Rapid and accurate identification of lactic acid bacteria (LAB) species would greatly improve the screening rate for functional LAB. Although many conventional and molecular methods have proven efficient and reliable, LAB identification using these methods has generally been slow and tedious. Single-cell Raman spectroscopy (SCRS) provides the phenotypic profile of a single cell and can be performed by Raman spectroscopy (which directly detects vibrations of chemical bonds through inelastic scattering by a laser light) using an individual live cell. Recently, owing to its affordability, non-invasiveness, and label-free features, the Ramanome has emerged as a potential technique for fast bacterial detection. Here, we established a reference Ramanome database consisting of SCRS data from 1,650 cells from nine LAB species/subspecies and conducted further analysis using machine learning approaches, which have high efficiency and accuracy. We chose the ensemble meta-classifier (EMC), which is suitable for solving multi-classification problems, to perform in-depth mining and analysis of the Ramanome data. To optimize the accuracy and efficiency of the machine learning algorithm, we compared nine classifiers: LDA, SVM, RF, XGBoost, KNN, PLS-DA, CNN, LSTM, and EMC. EMC achieved the highest average prediction accuracy of 97.3% for recognizing LAB at the species/subspecies level. In summary, Ramanomes, with the integration of EMC, have promising potential for fast LAB species/subspecies identification in laboratories and may thus be further developed and sharpened for the direct identification and prediction of LAB species from fermented food.

Bifidobacterium species viability in dairy-based probiotic foods: challenges and innovative approaches for accurate viability determination and monitoring of probiotic functionality

Bifidobacterium species are essential members of a healthy human gut microbiota. Their presence in the gut is associated with numerous health outcomes such as protection against gastrointestinal tract infections, inflammation, and metabolic diseases. Regular intake of Bifidobacterium in foods is a sustainable way of maintaining the health benefits associated with its use as a probiotic. Owing to their global acceptance, fermented dairy products (particularly yogurt) are considered the ideal probiotic carrier foods. As envisioned in the definition of probiotics as "live organisms," the therapeutic functionalities of Bifidobacterium spp. depend on maintaining their viability in the foods up to the point of consumption. However, sustaining Bifidobacterium spp. viability during the manufacture and shelf-life of fermented dairy products remains challenging. Hence, this paper discusses the significance of viability as a prerequisite for Bifidobacterium spp. probiotic functionality. The paper focuses on the stress factors that influence Bifidobacterium spp. viability during the manufacture and shelf life of yogurt as an archetypical fermented dairy product that is widely accepted as a delivery vehicle for probiotics. It further expounds the Bifidobacterium spp. physiological and genetic stress response mechanisms as well as the methods for viability retention in yogurt, such as microencapsulation, use of oxygen scavenging lactic acid bacterial strains, and stress-protective agents. The report also explores the topic of viability determination as a critical factor in probiotic quality assurance, wherein, the limitations of culture-based enumeration methods, the challenges of species and strain resolution in the presence of lactic acid bacterial starter and probiotic species are discussed. Finally, new developments and potential applications of next-generation viability determination methods such as flow cytometry, propidium monoazide-quantitative polymerase chain reaction (PMA-qPCR), next-generation sequencing, and single-cell Raman spectroscopy (SCRS) methods are examined.

Culture-free identification of fast-growing cyanobacteria cells by Raman-activated gravity-driven encapsulation and sequencing

By directly converting solar energy and carbon dioxide into biobased products, cyanobacteria are promising chassis for photosynthetic biosynthesis. To make cyanobacterial photosynthetic biosynthesis technology economically feasible on industrial scales, exploring and engineering cyanobacterial chassis and cell factories with fast growth rates and carbon fixation activities facing environmental stresses are of great significance. To simplify and accelerate the screening for fast-growing cyanobacteria strains, a method called Individual Cyanobacteria Vitality Tests and Screening (iCyanVS) was established. We show that the 13C incorporation ratio of carotenoids can be used to measure differences in cell growth and carbon fixation rates in individual cyanobacterial cells of distinct genotypes that differ in growth rates in bulk cultivations, thus greatly accelerating the process screening for fastest-growing cells. The feasibility of this approach is further demonstrated by phenotypically and then genotypically identifying individual cyanobacterial cells with higher salt tolerance from an artificial mutant library via Raman-activated gravity-driven encapsulation and sequencing. Therefore, this method should find broad applications in growth rate or carbon intake rate based screening of cyanobacteria and other photosynthetic cell factories.