Machine Learning for Probiotic Strain Viability Testing

A method for screening personalized probiotics, prebiotics, foods, health functional foods, and drugs using fecal samples and a proprietary medium composition. The method involves treating fecal samples with candidate materials, culturing, and analyzing the resulting microbiota and metabolites to identify effective personalized microbiota-improving agents. The composition includes L-cysteine, sodium chloride, sodium carbonate, potassium chloride, and hemin, which are combined with fecal samples to create a controlled in vitro environment that mimics the human gut. The method enables rapid screening of personalized microbiota-improving agents using fecal samples and special media, and can be used to diagnose diseases caused by intestinal disorders.

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Using machine learning to design bacterial communities for specific tasks like suppressing pathogens or degrading contaminants. The method involves training a machine learning model to predict community performance based on bacterial strain composition. The training uses real experimental data on actual communities. The model is then used to identify communities with high predicted performance for a task. This allows efficient screening of large numbers of possible communities. The training strategy involves generating data with strains and task scores, and prioritizing genetically diverse communities to reduce redundancy.

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As a promising probiotic strain,

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Predicting environmental preferences of microorganisms through genomic analysis. The method leverages genomic data to infer optimal growth conditions for microorganisms that are difficult to culture in vitro. By analyzing genomic features associated with environmental adaptations, the system identifies genes and proteins that correlate with specific growth preferences across environmental gradients. This enables the prediction of optimal growth conditions for both cultivated and uncultivated microorganisms, expanding our understanding of microbial environmental preferences beyond cultivation-based methods.

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Using machine learning models to predict unmeasured cellular quantitative measures like viability to reduce lab experimentation burden in drug discovery. The models are trained on measured data and then used to generate predictions for untested conditions. The predictions can fill in gaps in dose-response matrices, identify synergistic effects, and reduce the number of experiments needed to find drugs with synergy. The models can handle sparse input data and process images as well as numerical values. They can also augment training data with external sources like genomic data.

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A method for identifying high-performing microorganisms for bioreactor production by correlating genotype with bioreactor fitness. The method involves culturing a library of genetically modified microorganisms in parallel bioreactors, tracking the frequency of each strain, and assigning a quantitative fitness score based on its relative abundance. This score is then used to select strains for further evaluation in high-throughput screening, enabling the identification of strains with superior bioreactor performance and improved genotypes.

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A method for rapidly determining the viability of individual spores using an α-glucosidase test. The method involves adding a spore suspension to a solid medium containing 4-methylumbelliferyl-α-D-glucoside (4-MUG), allowing viable spores to germinate and synthesize α-glucosidase, and then detecting the resulting 4-methylumbelliferone (4-MU) fluorescence under an excitation light source. The fluorescence pattern reveals the presence and viability of individual spores.

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Probiotics, such as

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The gut microbiota plays a crucial role in maintaining human health and influencing disease states. Recent advancements in artificial intelligence (AI) have opened new avenues for exploring the intricate functionalities of the gut microbiota. This article aims to provide an overview of the current state-of-the-art applications of AI in microbiome analysis, with examples related to metabolomics, transcriptomics, proteomics, and genomics. It also offers a perspective on the use of such AI solutions in probiotic interventions for various clinical settings. This comprehensive understanding can lead to the development of targeted therapies that modulate the gut microbiota to improve health outcomes. This article explores the innovative application of AI in understanding the complex interactions within the gut microbiota. By leveraging AI, researchers aim to uncover the microbiotas role in human health and disease, particularly focusing on CIDs and probiotic interventions.

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The probiotic properties of

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A method for determining optimal combinations of microbial strains for industrial applications, such as biotechnology and environmental engineering, using machine learning and genome analysis. The method integrates genomic, metabolic, and growth data to predict strain interactions and optimize productivity, efficiency, or production of specific metabolites. It employs reinforcement learning and collaborative filtering algorithms to identify strain combinations that maximize growth and metabolic interactions.

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Lactic acid bacteria have a long and extensive application record as probiotic strains. Lately, due to wide-spread use of molecular-genetic, transcirptomic, proteomic, metabolomic etc. studies and the massive accumulation of data on the structure and functions of symbiotic intestinal microbiota, the interest in probiotic microorganisms tends to expand year-by-year. Lactic acid bacteria were the first used probiotic species, are still of sharp market demand and have been recognized as the most thoroughly studied microbes among functional relatives. However, characteristics inherent to probiotic bacteria are strain-specific, as a rule, and for preparations with defined purpose it is essential to select special strains showing a complex of appropriate properties. It accentuates the top relevance of research aimed at selection of lactic acid bacterial strains suitable for diverse probiotic preparations. For several decades we curried out investigations to isolate strains of lactic acid bacteria from various natural sources, to characterize their properties and to derive technologies of p... Read More

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The probiotic potential of

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A computer-implemented method for real-time prediction of microorganism growth or inhibition in antimicrobial susceptibility testing (AST) using artificial intelligence. The method involves training a deep learning neural network to classify sequences of images of incubated microorganisms based on pixel intensity changes over time. The network extracts spatio-temporal features from the image sequences and predicts growth or inhibition based on an output score. The method enables rapid AST results without requiring high-resolution images, making it suitable for high-throughput testing systems.

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As a famous probiotic,

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This study evaluated the characteristics of lactic acid bacteria (LAB) isolated from kkakdugi for its use as a probiotic.In addition, the possibility of using it as a material for promoting antioxidant activity and skin functionality was evaluated.To verify the feasibility of LAB as probiotics, their survival rates in artificial gastric juice and artificial bile were evaluated.In artificial gastric juice, the average number of probiotics was maintained at 5.310 9 colony-forming units (CFU)/mL, showing a survival rate of about 99%.In artificial bile, the average number of probiotics was maintained at 1.210 9 CFU/mL, showing a survival rate of about 95%.The survival rate indicated their ability to reach the target site to exert their effects.In addition, autoaggregation and cell surface hydrophobicity experiments were conducted to indirectly confirm their ability to adhere to the gastrointestinal tract surface.The autoaggregation rate of all LAB strains increased over time.Specifically, L. plantarum K1-9 and L. brevis K2-9 strains showed high hydrophobicity.LAB culture supernatants w... Read More

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A method for predicting cell culture results that iteratively refines culture conditions through machine learning-based modeling of biological behavior. The method receives initial culture conditions, predicts biological behavior based on a trained model, updates the culture conditions based on the predicted behavior, and repeats the process until convergence. The trained model can be based on machine learning or biological mechanism-of-action models, including genome-scale metabolic models and cell signaling models.

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Predicting cell viability in bioreactors during biomolecule manufacturing using machine learning models trained on process parameters such as time elapsed, base addition, and volume, with higher importance assigned to parameters like time elapsed and base addition compared to parameters like pH and dissolved oxygen.

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The selection of appropriate probiotic strains is vital for their successful inclusion in foods. These strains must withstand processing to reach consumers with 10

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The gut microbiota is a potentially modifiable risk factor for various health complications. Therefore, advanced techniques are warranted to understand the relationship between gut microbiota, disease, and clinical relevance. This chapter focuses on the emerging application of artificial intelligence (AI) techniques in the studies of gut microbiota. It opens with a discussion on the role of gut microbiota in health, mentions an overview of AI techniques, and provides information on the application of AI in the study of the gut microbiome and its role in the diagnosis and treatment of diseases. It also gives a glimpse into the challenges and future direction of artificial intelligence in gut microbiome research. The chapter provides new insights into the extraordinary applications of AI in the study of the gut microbiome.

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The identification and quantification of viable bacteria at the species/strain level in compound probiotic products is challenging now. Molecular biology methods, e.g., propidium monoazide (PMA) combination with qPCR, have gained prominence for targeted viable cell counts. This study endeavors to establish a robust PMA-qPCR method for viable Lacticaseibacillus rhamnosus detection and systematically validated key metrics encompassing relative trueness, accuracy, limit of quantification, linear, and range. The inclusivity and exclusivity notably underscored high specificity of the primers for L. rhamnosus , which allowed accurate identification of the target bacteria. Furthermore, the conditions employed for PMA treatment were fully verified by 24 different L. rhamnosus including type strain, commercial strains, etc., confirming its effective discrimination between live and dead bacteria. A standard curve constructed by type strain could apply to commercial strains to convert qPCR C q values to viable cell numbers. The established PMA-qPCR method was applied to 46 samples including pur... Read More

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Abstract Screening probiotics with specific functions is essential for advancing probiotic research. Current screening methods primarily use animal studies or clinical trials, which are inefficient and costly in terms of time, money, and labor. An intelligent intestineonachip integrating machine learning (ML) is developed to screen reliefenteritis functional probiotics. A highthroughput microfluidic chip combined with environment control systems provides a standardized and scalable intestinal microenvironment for multiple probiotic cocultures. An unsupervised MLbased score analyzer is constructed to accurately, comprehensively, and efficiently evaluate interactions between 12 Bifidobacterium strains and host cells of the colitis model in the intestineonachips. The most effective contender, Bifidobacterium longum 314, is discovered to relieve intestinal inflammation and enhance epithelial barrier function in vitro and in vivo. A distinct advantage of this strategy is that it can intelligently differentiate small therapeutic variations in probiotic strains and prioritize thei... Read More

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The growing awareness of the health benefits associated with probiotics has led to an increasing interest in probiotic products. To develop probiotic functional foods that deliver health benefits, it is essential to characterize both probiotic viability (the ability to survive) and vitality (the ability to remain active and effective). However, traditional probiotic assays only provide limited information about their survival state. To gain a comprehensive understanding of probiotic states, a D-amino-acid-based metabolic labeling strategy was applied to quantitatively depict probiotic vitality. In this approach, probiotics were first metabolically incorporated with azido-modified D-lysine and then labeled with dibenzocyclooctyne-sulfo-Cy5 through click chemistry. This two-step labeling process provides a visual representation of the metabolic levels of probiotics as well as the bacterial membrane integrity. Besides, this method is capable of characterizing the influence of various environmental conditions, from manufacturing to oral administration, on probiotic vitality. With its rap... Read More

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Abstract The search for probiotic candidates is an area that accompanies the world trend of development of novel probiotic strains and new products. In recent years, unconventional sources of potential probiotic bacteria have been studied. Furthermore, nowadays there has been a growing interest in non-dairy probiotic products and fermented plant-based foods, which has led to the development of probiotic foods currently being presented as a research priority for the food industry. The aim of this work was to evaluate the probiotic potential of lactic acid bacteria (LAB) isolated from Jerusalem artichoke ( Helianthus tuberosus L.) tubers. The results proved that the selected isolated LAB strains exhibited a high survival rate in the simulated gastrointestinal treatment, with non-hemolytic nor DNAse activity and antibiotic sensitivity. The isolated strains also showed antimicrobial activity against pathogen microorganisms, due to their acidification capacity. The molecular identification of the bacilli strains showed a high similarity with the genus Lentilactobacillus and, within this g... Read More

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Microbes, including bacteria, archaea, fungi, and viruses, are fundamental to our ecosystems, health, and industries. Microbial data analysis has become indispensable in understanding their roles and interactions. In this era of big data, advanced techniques, such as high-throughput sequencing, metagenomics, and bioinformatics, have accelerated microbial research. This chapter explores the significance of intelligent techniques, particularly machine learning and artificial intelligence, in revolutionizing microbial data analysis. The aim of this chapter is to showcase the pivotal role of intelligent techniques in microbial data analysis across diverse domains, from ecology and public health to biotechnology. We delve into case studies that highlight the practical applications of these techniques and the transformative impact they have had on microbial research. Several case studies are presented, illustrating the applications of intelligent techniques in microbial research. These include predicting disease risk through gut microbiome analysis, antibiotic resistance prediction, enviro... Read More

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Abstract In recent years, more and more scientific community, food producers, and food industry show increased interest in functional foods containing probiotics, which is a big challenge. The consumption of probiotics in the context of a balanced diet through the consumption of functional foods or through the intake of pharmaceutical preparations has proven to contribute to the improvement of human health, even contributing to the prevention of diseases. In order for probiotics to be considered suitable for consumption, they must contain a minimum concentration of viable cells, namely, at least 10 7 colony forming units of beneficial microbes per gram. Ensuring the viability of bacterial cells until the moment of consumption is the overriding priority of functional probiotic food manufacturers. Probiotic bacteria are subject to stress conditions not only during food manufacturing but also during gastrointestinal passage, which limit or even compromise their functionality. This paper first examines all the stressful conditions faced by probiotic cells in their production stages and r... Read More

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Probiotics are the largest non-herbal/traditional dietary supplements category worldwide. To be effective, a probiotic strain must be delivered viable at an adequate dose proven to deliver a health benefit. The objective of this article is to provide an overview of the various technologies available for probiotic enumeration, including a general description of each technology, their advantages and limitations, and their potential for the future of the probiotics industry. The current gold standard for analytical quantification of probiotics in the probiotic industry is the Plate Count method (PC). PC measures the bacterial cells ability to proliferate into detectable colonies, thus PC relies on cultivability as a measure of viability. Although viability has widely been measured by cultivability, there has been agreement that the definition of viability is not limited to cultivability. For example, bacterial cells may exist in a state known as viable but not culturable (VBNC) where the cells lose cultivability but can maintain some of the characteristics of viable cells as well as ... Read More

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The symbiosis of probiotic bacteria with humans has rendered various health benefits while providing nutrition and a suitable environment for their survival. However, the probiotics must survive unfavorable gut conditions to exert beneficial effects. The intrinsic resistance of probiotics to survive harsh conditions results from a myriad of proteins. Interaction of microbial proteins with the host is indispensable for modulating the gut microbiome, such as interaction with cell receptors and protective action against pathogens. The complex interplay of proteins should be unraveled by utilizing metaproteomic strategies. The contribution of probiotics to health is now widely accepted. However, due to the inconsistency of generalized probiotics, contemporary research toward precision probiotics has gained momentum for customized treatment. This review explores the application of metaproteomics and AI/ML algorithms in resolving multiomics data analysis and in silico prediction of microbial features for screening specific beneficial probiotic organisms. Implementing these integrative stra... Read More

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The interest in the use of probiotics to treat and prevent vaginal infections is known. The new regulation of medical devices by the European Medical Agency (EMA) introduced big changes in Europe regarding probiotic products for vaginal application, as they are no longer considered as medical devices. As the future classification will be as drugs, it will stress the need to define robust and reliable pre-clinical in vitro testing in order to assess the quality, safety and efficacy of probiotics for human use. Before discussing the efficacy in human pathology, it is mandatory to evaluate the survival and multiplication potential of probiotic strains when brought into contact with vaginal fluid. In this work, our objective was to assess the recovery and stability profile of lactobacilli from six vaginal probiotic formulations brought in contact with specific culture media or vaginal fluid simulants (VFS). Overall, the recovery of viable lactobacilli cells from a modified vaginal fluid simulant (MVFS) solution was comparable to the recovery pattern obtained in standard culture medium. T... Read More

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Probiotics are microorganisms that exert strain-specific health-promoting effects on the host. hey are employed in the production of functional dairy or non-dairy food products; still, their detection in these complex matrices is a challenging task. Several culture-dependent and culture-independent methods have been developed in this direction; however, they present low discrimination at the strain level. Here, we developed a multiplex PCR assay for the detection of two potential probiotic lactic acid bacteria (LAB) strains, Lactiplantibacillus plantarum L125 and Lp. pentosus L33, in monocultures and yogurt samples. Unique genomic regions were identified via comparative genomic analysis and were used to produce strain-specific primers. Then, primer sets were selected that produced distinct electrophoretic DNA banding patterns in multiplex PCR for each target strain. This method was further implemented for the detection of the two strains in yogurt samples, highlighting its biotechnological applicability. Moreover, it can be applied with appropriate modifications to detect any bacter... Read More

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Through the implementation of designable genetic circuits, engineered probiotic microorganisms could be used as noninvasive diagnostic tools for the gastrointestinal tract. For these living cells to report detected biomarkers or signals after exiting the gut, the genetic circuits must be able to record these signals by using genetically encoded memory. Complex memory register circuits could enable multiplex interrogation of biomarkers and signals. A theory-based approach to create genetic circuits containing memory, known as sequential logic circuits, was previously established for a model laboratory strain of Escherichia coli, yet how circuit component performance varies for nonmodel and clinically relevant bacterial strains is poorly understood. Here, we develop a scalable computational approach to design robust sequential logic circuits in probiotic strain Escherichia coli Nissle 1917 (EcN). In this work, we used TetR-family transcriptional repressors to build genetic logic gates that can be composed into sequential logic circuits, along with a set of engineered sensors relevant f... Read More

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There is growing scientific and commercial interest in multi-species probiotic products due to their potential benefits in maintaining gut health. Determining the viability of probiotic microorganisms in these products is essential to ensure that they confer maximal health benefits. The gold standard for enumerating probiotic viability is the plate count method. However, this may be inaccurate for enumerating mixed probiotic populations, with recognised limitations including difficulty measuring metabolically active yet unculturable, very slow growing microbes, microencapsulated, enteric coated microbes, or multi-strain formulations that require differing growth media. Here, we developed a flow-cytometry-based approach using SYTOXTM Green dye to assess the viability of probiotic microorganisms in a multi-species, fibre-containing probiotic product and compared this to the traditional plate count method. This method was suitable for enumerating both total bacterial cells and the viable cell fraction in the complete product mixture, and could also be used to assess how stressors, such ... Read More

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Predicting the survival potential of individual cells at single-cell resolution using machine learning models trained on omics data, enabling early detection of cell vulnerability and effectiveness of therapeutic agents in neurodegenerative diseases.

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Probiotics, live microorganisms that promote health by balancing the gut microbiota, have gained popularity in food and supplements.This study aimed to identify potential probiotic strains of Lactobacillus acidophilus isolated from available yoghurt/fermented food sources in Bangladesh.The research addressed the need for indigenous strains to cater to the local population's health requirements in the face of imported probiotic products dominating the market.Eight yoghurt samples from Bogra District were collected and cultured using Man Rogosa and Sharp (MRS) broth and agar.The isolated lactobacilli were further characterised through sequencing, and the Lactobacillus acidophilus LA-5 strain was identified in all isolates.Lactobacillus acidophilus LA-5 is a probiotic strain that has been employed in food and dietary supplements.Additionally, a stock contamination test was conducted to ensure sample purity.In vitro tests were performed to assess the probiotic potential, including acid tolerance, bile salt tolerance, antibiotic sensitivity, and storage ability in order to mimic the gut e... Read More

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The probiotic strain Lacticaseibacillus paracasei (previously Lactobacillus casei) strain Shirota (LcS) has demonstrated its survivability in the gastrointestinal tract across populations in different countries. The objective of this study was to validate this survivability in the United States, where evidence is lacking. Faecal samples were collected from 26 healthy individuals (age: 32.0 5.9 years) at baseline, after 7 and 14 days of daily consumption of 80 mL fermented milk containing 108 colony forming units (CFU) LcS/mL, and after a subsequent 14-days of no product consumption. Live LcS counts significantly (p < 0.001) increased after 7 and 14 days of product consumption (6.37 1.18 and 5.24 1.81 log10 CFU/g faeces, respectively) and returned to baseline in 87% of participants. These results indicate LcS survives passage through the gastrointestinal tract of generally healthy U.S. adults, providing support for its uniquely accumulated evidence of universal survival capacity in the gastrointestinal tract.

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Probiotic formula for the vaginal tract must contain high numbers of viable beneficial bacteria that maintain their characteristics during the production and further storage, in order to exert the claimed probiotic effect. Four probiotic strainsLactobacillus gasseri CRL1320, Limosilactobacillus reuteri CRL1324, Ligilactobacillus salivarius CRL1328 and Lacticaseibacillus rhamnosus CRL1332originally isolated from vagina of healthy women exhibiting beneficial properties were evaluated. Therefore, the optimization of growth parameters and dry biomass production with high viability while preserving probiotic features of strains is a great challenge. Different growth conditions in MRS medium were set up in a laboratory bioreactor; two initial pH and agitation were recorded speeds during static or controlled fermentations. Production conditions of 37 C with controlled pH 6.5 and 5.5-MRS with 150 and 75 rpm stirring speeds were used for CRL1329 and CRL1332 strains, respectively, while static and free pH MRS for CRL1324 and CRL1328 probiotics allowed us to obtain maximal cell viability cou... Read More

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A method for training artificial intelligence (AI) to determine cell viability from digital holographic microscopy (DHM) images without labeling the cells. The method involves obtaining a fluorescence image of a cell sample to determine its viability, labeling the corresponding DHM image with the viability information, and using the labeled DHM image as a training model for the AI. The trained AI can then analyze new DHM images to determine cell viability without requiring labeling or physical modification of the cells.

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Dietary sources have an abundance of bacteria, mainly lactic acid bacteria (LABs), which have long been regarded as probiotics in humans and animals. Lactic acid bacteria (LAB) have been used as probiotic agents due to their ability to produce a variety of beneficial compounds for cultivars and their status as safe microorganisms.In this current study, the lactic acid bacteria (LAB) were isolated from several dietary sources such as curd, pickle, milk, and wheat dough. The principal focus of this study was to determine the survivability of these microorganisms in the gastrointestinal tract and to use promising strains to create probiotic drinks with numerous health benefits. The isolates were identified using a combination of morphological, biochemical, molecular and sugar fermentation patterns, like phenotypic characteristics, sugar fermentation, MR-VP reaction, catalase test, urease test, oxidase test, H2S production, NH3 production synthesis from arginine, citrate utilization, indole test, and 16s rRNA sequencing.Two (CM1 and OS1) of the 60 isolates obtained showed the best probio... Read More

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A high-throughput system for early detection and classification of live microorganisms using time-lapse coherent imaging and deep neural networks. The system captures holographic images of bacterial growth on agar plates and analyzes them using multiple neural networks to rapidly detect and identify microorganism species. The system can detect microorganisms as early as 12 hours after inoculation, with a sensitivity of 1 CFU/100-1000 mL, and can classify bacteria with high accuracy.

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Introduction Reliable and accurate methods for probiotic identification and enumeration, at the strain level plays a major role in confirming product efficacy since probiotic health benefits are strain-specific and dose-dependent. In this study, real-time PCR methods were developed for strain specific identification and enumeration of L. paracasei 8700:2, a probiotic strain that plays a role in fighting the common cold. Methods The assay was designed to target a unique region in L. paracasei 8700:2 genome sequence to achieve strain level specificity. The identification assay was evaluated for specificity and sensitivity. The enumeration viability real-time PCR (v-qPCR) method was first optimized for the viability treatment, then the method was evaluated for efficiency, limit of quantification, precision, and its performance was compared to plate count (PC) and viability droplet digital PCR (v-ddPCR) methods. Results The identification method proved to be strain specific and highly sensitive with a limit of detection of 0.5 pg of DNA. The optimal viability dye (PMAxx) concentration wa... Read More

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ProbioMinServer is a platform designed to help researchers access information on probiotics regarding a wide variety of characteristics, such as safety (e.g. antimicrobial resistance, virulence, pathogenic, plasmid, and prophage genes) and functionality (e.g. functional classes, carbohydrate-active enzyme, and metabolite gene cluster profile). Because probiotics are functional foods, their safety and functionality are a crucial part of health care. Genomics has become a crucial methodology for investigating the safety and functionality of probiotics in food and feed. This shift is primarily attributed to the growing affordability of next-generation sequencing technologies. However, no integrated platform is available for simultaneously evaluating probiotic strain safety, investigating probiotic functionality, and identifying known phylogenetically related strains.Thus, we constructed a new platform, ProbioMinServer, which incorporates these functions. ProbioMinServer accepts whole-genome sequence files in the FASTA format. If the query genome belongs to the 25 common probiotic specie... Read More

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Background: The plate count technique had traditionally been used for the determination of viability and counting of probiotic bacteria, which had obvious disadvantages. Efficient tools to identify and count probiotics (alone or in combination) have evolved. Objective: This study aimed to compare two methods of counting and identifying probiotics such as Real-time PCR and flow cytometry, with the culture method and suggest an inexpensive method for the diagnosis of probiotics in dairy products. Methods: Electronic databases such as Scopus, PubMed, and Science Direct were systematically searched, identified, screened, and reviewed from June 2001 to December 2022. Results: This study showed that each technology has its strengths, advantages, and disadvantages, but the Real-time PCR method is more suitable than other methods and can identify and count live cells of probiotics. Conclusion: In conclusion, it should be mentioned that due to the superiority of the Real-time PCR method, we recommend the use of this molecular method, but for more assurance and comparison, several methods can ... Read More

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Multi-strain probiotics are widely regarded as effective products for improving gut microbiota stability and host health, providing advantages over single-strain probiotics.However, in general, it is unclear to what extent different strains would cooperate or compete for resources, and how the establishment of a common biofilm microenvironment could influence their interactions.In this work, we develop an integrative experimental and computational approach to comprehensively assess the metabolic functionality and interactions of probiotics across growth conditions.Our approach combines co-culture assays with genome-scale modelling of metabolism and multivariate data analysis, thus exploiting complementary data-and knowledge-driven systems biology techniques.To show the advantages of the proposed approach, we apply it to the study of the interactions between two widely used probiotic strains of Lactobacillus reuteri and Saccharomyces boulardii, characterising their production potential for compounds that can be beneficial to human health.Our results show that these strains can establi... Read More

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Long-term colonization of desired probiotic bacteria in human colon environment is still tough to achieve for now. In this exploratory in vitro study, we demonstrated the difficulties in proliferation of Lactobacillus rhamnosus GG (LGG) and Bifidobacterium animalis subsp. lactis BB-12 (BB-12) in the substrate of post intestinal digestion products (PIPD) made from skimmed milk. Results of poor growth in the digesta (1.54 log N/N0 for LGG, while 0.54 log N/N0 for BB-12) provided evidence on mechanisms of low survival of the two strains in simulated colon environment. Adscititious glucose significantly promoted viable counts of LGG and BB-12 in PIPD, thus is promising to serve as possible tailor made 'food' for colon fermentation of probiotics. Based on the results, we propose a new concept that may be called as 'food parcel for colon microbes', which can be delivered to simulated human colon environment and assist the growth of the probiotics already existing there. In the current study, we selected the 'glucose parcel' as an initial example. The 'glucose parcel' can be released into ... Read More

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Research background. Increasing awareness of the importance of nutrition in health promotion and disease prevention has driven to the development of foods for special medical purposes (FSMPs). In this study, the probiotic strain Lacticaseibacillus paracasei ssp. paracasei (Lacticaseibacillus casei 431) was incorporated into FSMPs to develop an innovative product. The aim was to investigate the influence of the FSMP matrix on the specific probiotic properties of L. casei 431 in vitro. Experimental approach. A series of in vitro experiments were performed as part of the probiotic approach. After evaluation of antibiotic susceptibility profiles, functional properties such as survival under simulated gastrointestinal tract (GIT) conditions, bile salt deconjugation activities, cholesterol assimilation, antagonistic activity against spoilage bacteria and adhesion to Caco-2 cell line monolayers and extracellular matrix proteins were investigated. Results andconclusions. The L. casei 431 strain, both the lyophilised strain and the strain isolated from the FSMP matrix, effectively survived... Read More

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Probiotics have been used for decades to alleviate the negative side-effects of oral antibiotics, but our mechanistic understanding on how they work is so far incomplete. Here, we performed a metagenomic analysis of the fecal microbiota in participants who underwent a 14-d Helicobacter pylori eradication therapy with or without consumption of a multi-strain probiotic intervention (L. paracasei CNCM I-1518, L. paracasei CNCM I-3689, L. rhamnosus CNCM I-3690, and four yogurt strains) in a randomized, double-blinded, controlled clinical trial. Using a strain-level analysis for detection and metagenomic determination of replication rate, ingested strains were detected and replicated transiently in fecal samples and in the gut during and following antibiotic administration. Consumption of the fermented milk product led to a significant, although modest, improvement in the recovery of microbiota composition. Stratification of participants into two groups based on the degree to which their microbiome recovered showed i) a higher fecal abundance of the probiotic L. paracasei and L. rhamnosus... Read More

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Foods are not only intended to placate hunger and supply essential nutrients but also to prevent the nutrition-related diseases and to improve physiological and mental wellbeing of consumers. This led to the development of probiotic foods. Probiotics are said to be live microorganisms which when adequately (106/107 CFU/mL) administered confer health benefits to the host. Probiotic drinks both dairy and non-dairy have been found to be carriers of these organisms to their site of action. This research aims at determining the survivability of probiotic lactic acid bacteria in some locally produced drinks. The isolation of the organisms from yoghurt and nono were conducted using cultural methods and further characterized using biochemical tests. Cell surface hydrophobicity (CSH), cellular auto-aggregation assays (CAA), hemolytic activities, bile salt and NaCl tolerance test were conducted to determine the probiotic properties of the organisms. The survivability of the organisms was evaluated after standardizing the inoculum using 0.5 McFarland standard and then serial dilution, plating... Read More

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Probiotic bacteria, capable of conferring benefits to the host, can present challenges in design, development, scale-up, manufacturing, commercialization, and life cycle management. Strain identification is one of the main quality parameters; nevertheless, this task can be challenging since established methodologies can lack resolution at the strain level for some microorganisms and\or are labor-intensive and time-consuming. Fourier transform infrared spectroscopy (FTIRS) has been largely used for the investigation of pathogenic species in the clinical field, whereas only recently has been proposed for the identification of probiotic strains. Within the probiotic industrial production, bacterial strains can be subjected to stressful conditions that may affect genomic and phenotypic characteristics; therefore, real-time monitoring of all the sequential growth steps is requested. Considering the fast, low-cost, and high-throughput features, FTIRS is an innovative and functional technology for typing probiotic strains from bench-top experiments to large-scale industrial production, allo... Read More

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Research surrounding health benefits from probiotics is becoming popular because of the increasing demand for safer products with protective and therapeutic effects. Proven benefits are species- or genus-specific; however, no certified assays are available for their characterization and quantification at the strain level in the food supplement industry. The objective of this study was to develop a strain-specific Real-time quantitative polymerase chain reaction (RT-qPCR)-based method to be implemented in routine tests for the identification and quantification of Bifidobacterium longum, Bifidobacterium animalis spp. lactis, Lactobacillus paracasei, Lactobacillus rhamnosus, Lactobacillus casei, Bifidobacterium breve, Lactobacillus acidophilus, Lactobacillus plantarum, and Lactobacillus helveticus, starting from a powder mixture of food supplements. The method optimization was carried out in combination with flow cytometry to compare results between the two strategies and implement the analytical workflow with the information also regarding cell viability. These assays were validated in... Read More

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The consumption of probiotics is widely encouraged due to reports of their positive effects on human health. In particular, Lacticaseibacillus rhamnosus strain GG (LGG) is an approved probiotic that has been reported to improve health outcomes, especially for gastrointestinal disorders. However, how LGG cooperates with the gut microbiome has not been fully explored. To understand the interaction between LGG and its ability to survive and grow within the gut microbiome, this study introduced LGG into established microbial communities using an in vitro model of the colon. LGG was inoculated into the simulated ascending colon and its persistence in, and transit through the subsequent transverse and descending colon regions was monitored over two weeks. The impact of LGG on the existing bacterial communities was investigated using 16S rRNA sequencing and short-chain fatty acid analysis. LGG was able to engraft and proliferate in the ascending region for at least 10 days but was diminished in the transverse and descending colon regions with little effect on short-chain fatty acid abundanc... Read More

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