Browsing by Author "Garrido, Daniel"

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    A novel gene cluster allows preferential utilization of fucosylated milk oligosaccharides in Bifidobacterium longum subsp longum SC596
    (2016) Garrido, Daniel; Ruiz-Moyano, Santiago; Kirmiz, Nina; Davis, Jasmine C.; Totten, Sarah M.; Lemay, Danielle G.; Ugalde, Juan A.; German, J. Bruce; Lebrilla, Carlito B.; Mills, David A.
    The infant intestinal microbiota is often colonized by two subspecies of Bifidobacterium longum: subsp. infantis (B. infantis) and subsp. longum (B. longum). Competitive growth of B. infantis in the neonate intestine has been linked to the utilization of human milk oligosaccharides (HMO). However, little is known how B. longum consumes HMO. In this study, infant-borne B. longum strains exhibited varying HMO growth phenotypes. While all strains efficiently utilized lacto-N-tetraose, certain strains additionally metabolized fucosylated HMO. B. longum SC596 grew vigorously on HMO, and glycoprofiling revealed a preference for consumption of fucosylated HMO. Transcriptomes of SC596 during early-stage growth on HMO were more similar to growth on fucosyllactose, transiting later to a pattern similar to growth on neutral HMO. B. longum SC596 contains a novel gene cluster devoted to the utilization of fucosylated HMO, including genes for import of fucosylated molecules, fucose metabolism and two alpha-fucosidases. This cluster showed a modular induction during early growth on HMO and fucosyllactose. This work clarifies the genomic and physiological variation of infant-borne B. longum to HMO consumption, which resembles B. infantis. The capability to preferentially consume fucosylated HMO suggests a competitive advantage for these unique B. longum strains in the breast-fed infant gut.
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    Anti-inflammatory effect of microbial consortia during the utilization of dietary polysaccharides
    (2018) Thomson, Pamela; Medina, Daniel A.; Ortuzar, Veronica; Gotteland, Martin; Garrido, Daniel
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    Characterization and Identification of Probiotic Features in Lacticaseibacillus Paracasei Using a Comparative Genomic Analysis Approach
    (2022) Torres-Miranda, Alexis; Melis-Arcos, Felipe; Garrido, Daniel
    Lacticaseibacillus paracasei species are widely used for their health-promoting properties in food and agricultural applications. These bacteria have been isolated from various habitats such as the oral cavity, cereals, vegetables, meats, and dairy products conferring them the ability to consume different carbohydrates. Two subspecies are recognized, Lacticaseibacillus paracasei subsp. paracasei and Lacticaseibacillus paracasei subsp. tolerans according to their acid production from carbohydrates. Some strains are currently used as probiotics. In this study, we performed a comparative genomic analysis of 181 genomes of the Lacticaseibacillus paracasei species to reveal genomic differences at the subspecies level and to reveal adaptive and probiotic features, and special emphasis is given to inulin consumption. No clear distinction at the subspecies level for L. paracasei was shown using a phylogenetic tree with orthologous genes from the core-genome set. In general, a good correlation was observed between genomic distance and isolation origin, suggesting that L. paracasei strains are adapted to their natural habitat, giving rise to genetic differences at the genomic level. A low frequency of undesirable characteristics such as plasmids, prophages, antibiotic resistance genes, absence of virulence factors, and frequent bacteriocin production supports these species being good candidates for use as probiotics. Lastly, we found that the inulin gene cluster in L. paracasei strains seems to differ slightly in the presence or absence of some genes but maintains a core defined by at least three fructose-PTS proteins, one hypothetical protein, and extracellular beta-fructosidase. Finally, we conclude that further work has to be done for L. paracasei subspecies classification. Improving outgroup selection criteria is a key factor for their correct subspecies assignation.
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    Cross-feeding interactions of gut microbes mediated by O-linked glycans from casein glycomacropeptide
    (2024) González-Morelo, Kevin J.; Garrido, Daniel
    The human gut microbiota plays an essential role in metabolizing complex compounds that host enzymes cannot degrade in the diet. In turn, the gut microbiota has the ability to interact with the host through mucus that protects epithelium cells. O-glycans have been proposed as emerging prebiotics due to their similarity to host-associated glycans instead of plant-derived prebiotics. Some gut microbes have been described to utilize the O-glycans as carbon sources for colonization. Changes in the protective barrier of host cells are linked to intestinal diseases. For this reason, trophic networks of microbial interactions play an important role in establishing a microbiome beneficial to the host’s health. Glycromacropeptide (GMP) is an O-glycopeptide obtained from whey during cheese manufacture. GMP could be considered as a simple model of O-glycans to analyze the molecular mechanisms involved in metabolic interactions between gut microbes. This work aimed to determine the molecular strategies and microbial interactions while utilizing glycomacropeptide as a carbon source. Individual cultures of representative bacteria allowed the identification of the major GMP-degraders. Unidirectional assays identified galacto-N-biose, galactose, N-Acetylgalactosamine, and sialic acid as by-products, providing a perspective on microbial interactions during GMP fermentation. Bidirectional assays demonstrated cross-feeding activity and competition between gut microbes, in addition to the promotion of butyrate from the fatty acids derived from the use of GMP. O-glycan-specific enzyme expression was identified for B. infantis ATCC 15697 and B. bifidum JCM 1254 during GMP cross-feeding consumption. This study highlights strategies for utilizing O-glycans in GMP consumption among gut microbes.
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    Differences in the composition and predicted functions of the intestinal microbiome of obese and normal weight adult dogs
    (2022) Thomson, Pamela; Santibanez, Rodrigo; Rodriguez-Salas, Camila; Flores-Yanez, Carla; Garrido, Daniel
    Obesity is a multifactorial nutritional disorder highly prevalent in dogs, observed in developed and developing countries. It is estimated that over 40% of the canine population suffers from obesity, which manifests in an increased risk of chronic osteoarticular, metabolic, and cardiovascular diseases. The intestinal microbiome of obese animals shows increases in the abundance of certain members capable of extracting energy from complex polysaccharides. The objective of this study was to compare the composition and predicted function of the intestinal microbiome of Chilean obese and normal weight adult dogs. Twenty clinically healthy dogs were classified according to their body condition score (BCS) as obese (n = 10) or normal weight (n = 10). DNA was extracted from stool samples, followed by next-generation sequencing of the 16S rRNA V3-V4 region and bioinformatics analysis targeting microbiome composition and function. Significant differences were observed between these groups at the phylum level, with anincrease in Firmicutes and a decrease in Bacteroidetes in obese dogs. Microbiome compositions of these animals correlated with their BCS, and obese dogs showed enrichment in pathways related to transport, chemotaxis, and flagellar assembly. These results highlight the differences in the gut microbiome between normal weight and obese dogs and prompt further research to improve animal health by modulating the gut microbiome.
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    Genome-scale metabolic modeling of the human milk oligosaccharide utilization by Bifidobacterium longum subsp. infantis
    (2024) Román Lagos, Loreto Andrea; Melis-Arcos, Felipe; Pröschle, Tomás; Saa, Pedro A.; Garrido, Daniel; Gilbert, Jack A.
    Bifidobacterium longum subsp. infantis is a representative and dominant species in the infant gut and is considered a beneficial microbe. This organism displays multiple adaptations to thrive in the infant gut, regarded as a model for human milk oligosaccharides (HMOs) utilization. These carbohydrates are abundant in breast milk and include different molecules based on lactose. They contain fucose, sialic acid, and N-acetylglucosamine. Bifidobacterium metabolism is complex, and a systems view of relevant metabolic pathways and exchange metabolites during HMO consumption is missing. To address this limitation, a refined genome-scale network reconstruction of this bacterium is presented using a previous reconstruction of B. infantis ATCC 15967 as a template. The latter was expanded based on an extensive revision of genome annotations, current literature, and transcriptomic data integration. The metabolic reconstruction (iLR578) accounted for 578 genes, 1,047 reactions, and 924 metabolites. Starting from this reconstruction, we built context-specific genome-scale metabolic models using RNA-seq data from cultures growing in lactose and three HMOs. The models revealed notable differences in HMO metabolism depending on the functional characteristics of the substrates. Particularly, fucosyl-lactose showed a divergent metabolism due to a fucose moiety. High yields of lactate and acetate were predicted under growth rate maximization in all conditions, whereas formate, ethanol, and 1,2-propanediol were substantially lower. Similar results were also obtained under near-optimal growth on each substrate when varying the empirically observed acetate-to-lactate production ratio. Model predictions displayed reasonable agreement between central carbon metabolism fluxes and expression data across all conditions. Flux coupling analysis revealed additional connections between succinate exchange and arginine and sulfate metabolism and a strong coupling between central carbon reactions and adenine metabolism. More importantly, specific networks of coupled reactions under each carbon source were derived and analyzed. Overall, the presented network reconstruction constitutes a valuable platform for probing the metabolism of this prominent infant gut bifidobacteria.
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    Hydrolysis of milk gangliosides by infant-gut associated bifidobacteria determined by microfluidic chips and high-resolution mass spectrometry
    (2014) Lee, Hyeyoung; Garrido, Daniel; Mills, David A.; Barile, Daniela
    Gangliosides are receiving considerable attention because they participate in diverse biological processes. Milk gangliosides appear to block pathogen adhesion and modify the intestinal ecology of newborns. However, the interaction of milk gangliosides with gut bifidobacteria has been little investigated. The digestion products of a mixture of gangliosides isolated from milk following incubation with six strains of bifidobacteria were studied using nanoHPLC Chip Q-TOF MS. To understand ganglioside catabolism in vitro, the two major milk gangliosidesGM3 and GD3remaining in the media after incubation with bifidobacteria were quantified. Individual gangliosides were identified through postprocessing precursor ion scans, and quantitated with the find by molecular feature algorithm of MassHunter Qualitative Analysis software. Bifidobacterium infantis and B. bifidum substantially degraded the GM3 and GD3, whereas B. longum subsp. longum and B. animalis subsp. lactis only showed moderate degradation. MALDI FTICR MS analysis enabled a deeper investigation of the degradation and identified ganglioside degradation specifically at the outer portions of the glycan molecules. These results indicate that certain infant gut-associated bifidobacteria have the ability to degrade milk gangliosides releasing sialic acid, and that these glycolipids could play a prebiotic role in the infant gut.
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    Screening competition and cross-feeding interactions during utilization of human milk oligosaccharides by gut microbes
    (2024) Diaz, Romina; Garrido, Daniel
    Background: The infant gut microbiome is a complex community that influences short- and long-term health. Its assembly and composition are governed by variables such as the feeding type. Breast milk provides infants an important supply of human milk oligosaccharides (HMO), a broad family of carbohydrates comprising neutral, fucosylated, and sialylated molecules. There is a positive association between HMOs and the overrepresentation of Bifidobacterium species in the infant gut, which is sustained by multiple molecular determinants present in the genomes of these species. Infant-gut-associated Bifidobacterium species usually share a similar niche and display similar HMO inclinations, suggesting they compete for these resources. There is also strong evidence of cross-feeding interactions between HMO-derived molecules and bifidobacteria. Methods: In this study, we screened for unidirectional and bidirectional interactions between Bifidobacterium and other species using individual HMO. Bifidobacterium bifidum and Bacteroides thetaiotaomicron increased the growth of several other species when their supernatants were used, probably mediated by the partial degradation of HMO. In contrast, Bifidobacterium longum subsp. infantis. supernatants did not exhibit positive growth. Results: Bifidobacterium species compete for lacto-N-tetraose, N-tetraose, which is associated with reduced bidirectional growth. The outcome of these interactions was HMO-dependent, in which the two species could compete for one substrate but cross-feed on another. 2'-fucosyllactose and lacto-N-neotetraose N-neotetraose are associated with several positive interactions that generally originate from the partial degradation of these HMOs. Conclusion: This study presents evidence for complex interactions during HMO utilization, which can be cooperative or competitive, depending on the nature of the HMO. This information could be useful for understanding how breast milk supports the growth of some Bifidobacterium species, shaping the ecology of this important microbial community.
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    Structure of co-expression networks of Bifidobacterium species in response to human milk oligosaccharides
    (2023) Gonzalez-Morelo, Kevin J.; Galan-Vasquez, Edgardo; Melis, Felipe; Perez-Rueda, Ernesto; Garrido, Daniel
    Biological systems respond to environmental perturbations and a large diversity of compounds through gene interactions, and these genetic factors comprise complex networks. Experimental information from transcriptomic studies has allowed the identification of gene networks that contribute to our understanding of microbial adaptations. In this study, we analyzed the gene co-expression networks of three Bifidobacterium species in response to different types of human milk oligosaccharides (HMO) using weighted gene co-expression analysis (WGCNA). RNA-seq data obtained from Geo Datasets were obtained for Bifidobacterium longum subsp. Infantis, Bifidobacterium bifidum and Bifidobacterium longum subsp. Longum. Between 10 and 20 co-expressing modules were obtained for each dataset. HMO-associated genes appeared in the modules with more genes for B. infantis and B. bifidum, in contrast with B. longum. Hub genes were identified in each module, and in general they participated in conserved essential processes. Certain modules were differentially enriched with LacI-like transcription factors, and others with certain metabolic pathways such as the biosynthesis of secondary metabolites. The three Bifidobacterium transcriptomes showed distinct regulation patterns for HMO utilization. HMO-associated genes in B. infantis co-expressed in two modules according to their participation in galactose or N-Acetylglucosamine utilization. Instead, B. bifidum showed a less structured co-expression of genes participating in HMO utilization. Finally, this category of genes in B. longum clustered in a small module, indicating a lack of co-expression with main cell processes and suggesting a recent acquisition. This study highlights distinct co-expression architectures in these bifidobacterial genomes during HMO consumption, and contributes to understanding gene regulation and co-expression in these species of the gut microbiome.
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    Using metabolic networks to predict cross-feeding and competition interactions between microorganisms
    (2024) Silva-Andrade, Claudia; Rodriguez-Fernández, María; Garrido, Daniel; Martin, Alberto J. M.; Jensen, Paul A.
    Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbiology. Different methods, relying on experimental or mathematical approaches based on the diverse properties of bacteria, are currently employed to study these interactions. Recently, the use of metabolic networks to understand the interactions between bacterial pairs has increased, highlighting the relevance of this approach in characterizing bacteria. In this study, we leverage the representation of bacteria through their metabolic networks to build a predictive model aimed at reducing the number of experimental assays required for designing bacterial consortia with specific behaviors. Our novel method for predicting cross-feeding or competition interactions between pairs of microorganisms utilizes metabolic network features. Machine learning classifiers are employed to determine the type of interaction from automatically reconstructed metabolic networks. Several algorithms were assessed and selected based on comprehensive testing and careful separation of manually compiled data sets obtained from literature sources. We used different classification algorithms, including K Nearest Neighbors, XGBoost, Support Vector Machine, and Random Forest, tested different parameter values, and implemented several data curation approaches to reduce the biological bias associated with our data set, ultimately achieving an accuracy of over 0.9. Our method holds substantial potential to advance the understanding of community behavior and contribute to the development of more effective approaches for consortia design.