Genetic Basis of Tetracycline Resistance in Bifidobacterium animalis subsp lactis

All strains of Bifidobacterium animalis subsp. lactis described to date show medium level resistance to tetracycline. Screening of 26 strains from a variety of sources revealed the presence of tet(W) in all isolates. A transposase gene upstream of tet(W) was found in all strains, and both genes were cotranscribed in strain IPLAIC4. Mutants with increased tetracycline resistance as well as tetracycline-sensitive mutants of IPLAIC4 were isolated and genetically characterized. The native tet(W) gene was able to restore the resistance phenotype to a mutant with an alteration in tet(W) by functional complementation, indicating that tet(W) is necessary and sufficient for the tetracycline resistance seen in B. animalis subsp. lactis

Characterization of the bile and gall bladder microbiota of healthy pigs

MicrobiologyOpen published by John Wiley & Sons Ltd. Bile is a biological fluid synthesized in the liver, stored and concentrated in the gall bladder (interdigestive), and released into the duodenum after food intake. The microbial populations of different parts of mammal's gastrointestinal tract (stomach, small and large intestine) have been extensively studied; however, the characterization of bile microbiota had not been tackled until now. We have studied, by culture-dependent techniques and a 16S rRNA gene-based analysis, the microbiota present in the bile, gall bladder mucus, and biopsies of healthy sows. Also, we have identified the most abundant bacterial proteins in the bile samples. Our data show that the gall bladder ecosystem is mainly populated by members of the phyla Proteobacteria, Firmicutes, and Bacteroidetes. Furthermore, fluorescent in situ hybridization (FISH) and transmission electron microscopy (TEM) allowed us to visualize the presence of individual bacteria of different morphological types, in close association with either the epithelium or the erythrocytes, or inside the epithelial cells. Our work has generated new knowledge of bile microbial profiles and functions and might provide the basis for future studies on the relationship between bile microbiota, gut microbiota, and health. © 2014 The Authors.This work was supported by AGL2013-44761-P and AGL2013-41980-P projects from the Ministerio de Ciencia e Innovación (Spain). Borja Sánchez was the recipient of a Ramón y Cajal postdoctoral contract from MINECO.Peer Reviewe

The infant gut microbiome as a microbial organ influencing host well-being

Initial establishment of the human gut microbiota is generally believed to occur immediately following birth, involving key gut commensals such as bifidobacteria that are acquired from the mother. The subsequent development of this early gut microbiota is driven and modulated by specific dietary compounds present in human milk that support selective colonization. This represents a very intriguing example of host-microbe co-evolution, where both partners are believed to benefit. In recent years, various publications have focused on dissecting microbial infant gut communities and their interaction with their human host, being a determining factor in host physiology and metabolic activities. Such studies have highlighted a reduction of microbial diversity and/or an aberrant microbiota composition, sometimes referred to as dysbiosis, which may manifest itself during the early stage of life, i.e., in infants, or later stages of life. There are growing experimental data that may explain how the early human gut microbiota affects risk factors related to adult health conditions. This concept has fueled the development of various nutritional strategies, many of which are based on probiotics and/or prebiotics, to shape the infant microbiota. In this review, we will present the current state of the art regarding the infant gut microbiota and the role of key commensal microorganisms like bifidobacteria in the establishment of the first microbial communities in the human gut

Decoding the genomic variability among members of the bifidobacterium dentium species

Members of the Bifidobacterium dentium species are usually identified in the oral cavity of humans and associated with the development of plaque and dental caries. Nevertheless, they have also been detected from fecal samples, highlighting a widespread distribution among mammals. To explore the genetic variability of this species, we isolated and sequenced the genomes of 18 different B. dentium strains collected from fecal samples of several primate species and an Ursus arctos. Thus, we investigated the genomic variability and metabolic abilities of the new B. dentium isolates together with 20 public genome sequences. Comparative genomic analyses provided insights into the vast metabolic repertoire of the species, highlighting 19 glycosyl hydrolases families shared between each analyzed strain. Phylogenetic analysis of the B. dentium taxon, involving 1140 conserved genes, revealed a very close phylogenetic relatedness among members of this species. Furthermore, low genomic variability between strains was also confirmed by an average nucleotide identity analysis showing values higher than 98.2%. Investigating the genetic features of each strain, few putative functional mobile elements were identified. Besides, a consistent occurrence of defense mechanisms such as CRISPR–Cas and restriction–modification systems may be responsible for the high genome synteny identified among members of this taxon

Impact of prematurity and perinatal antibiotics on the developing intestinal microbiota: A functional inference study

The microbial colonization of the neonatal gut provides a critical stimulus for normal maturation and development. This process of early microbiota establishment, known to be affected by several factors, constitutes an important determinant for later health. Methods: We studied the establishment of the microbiota in preterm and full-term infants and the impact of perinatal antibiotics upon this process in premature babies. To this end, 16S rRNA gene sequence-based microbiota assessment was performed at phylum level and functional inference analyses were conducted. Moreover, the levels of the main intestinal microbial metabolites, the short-chain fatty acids (SCFA) acetate, propionate and butyrate, were measured by Gas-Chromatography Flame ionization/Mass spectrometry detection. Results: Prematurity affects microbiota composition at phylum level, leading to increases of Proteobacteria and reduction of other intestinal microorganisms. Perinatal antibiotic use further affected the microbiota of the preterm infant. These changes involved a concomitant alteration in the levels of intestinal SCFA. Moreover, functional inference analyses allowed for identifying metabolic pathways potentially affected by prematurity and perinatal antibiotics use. Conclusion: A deficiency or delay in the establishment of normal microbiota function seems to be present in preterm infants. Perinatal antibiotic use, such as intrapartum prophylaxis, affected the early life microbiota establishment in preterm newborns, which may have consequences for later healt

Evolutionary development and co-phylogeny of primate-associated bifidobacteria

In recent years, bifidobacterial populations in the gut of various monkey species have been assessed in several ecological surveys, unveiling a diverse, yet unexplored ecosystem harbouring novel species. In the current study, we investigated the species distribution of bifidobacteria present in 23 different species of primates, including human samples, by means of 16S rRNA microbial profiling and internal transcribed spacer bifidobacterial profiling. Based on the observed bifidobacterial-host co-phylogeny, we found a statistically significant correlation between the Hominidae family and particular bifidobacterial species isolated from humans, indicating phylosymbiosis between these lineages. Furthermore, phylogenetic and glycobiome analyses, based on 40 bifidobacterial species isolated from primates, revealed that members of the Bifidobacterium tissieri phylogenetic group, which are typical gut inhabitants of members of the Cebidae family, descend from an ancient ancestor with respect to other bifidobacterial taxa isolated from primates

Proton Motive Force-Dependent Hoechst 33342 Transport by the ABC Transporter LmrA of Lactococcus lactis

The fluorescent compound Hoechst 33342 is a substrate for many multidrug resistance (MDR) transporters and is widely used to characterize their transport activity. We have constructed mutants of the adenosine triphosphate (ATP) binding cassette (ABC)-type MDR transporter LmrA of Lactococcus lactis that are defective in ATP hydrolysis. These mutants and wild-type LmrA exhibited an atypical behavior in the Hoechst 33342 transport assay. In membrane vesicles, Hoechst 33342 transport was shown to be independent of the ATPase activity of LmrA, and it was not inhibited by orthovanadate but sensitive to uncouplers that collapse the proton gradient and to N,N'-dicyclohexylcarbodiimide, an inhibitor of the F0F1-ATPase. In contrast, transport of Hoechst 33342 by the homologous, heterodimeric MDR transporter LmrCD showed a normal ATP dependence and was insensitive to uncouplers of the proton gradient. With intact cells, expression of LmrA resulted in an increased rate of Hoechst 33342 influx while LmrCD caused a decrease in the rate of Hoechst 33342 influx. Cellular toxicity assays using a triple knockout strain, i.e., L. lactis ΔlmrA ΔlmrCD, demonstrate that expression of LmrCD protects cells against the growth inhibitory effects of Hoechst 33342, while in the presence of LmrA, cells are more susceptible to Hoechst 33342. Our data demonstrate that the LmrA-mediated Hoechst 33342 transport in membrane vesicles is influenced by the transmembrane pH gradient due to a pH-dependent partitioning of Hoechst 33342 into the membrane.

Bifidobacterium adolescentis as a key member of the human gut microbiota in the production of GABA

Gamma aminobutyric acid (GABA) is the principal inhibitory neurotransmitter playing a key role in anxiety and depression disorders in mammals. Recent studies revealed that members of the gut microbiota are able to produce GABA modulating the gut–brain axis response. Among members of the human gut microbiota, bifidobacteria are well known to establish many metabolic and physiologic interactions with the host. In this study, we performed genome analyses of more than 1,000 bifidobacterial strains publicly available revealing that Bifidobacterium adolescentis taxon might represent a model GABA producer in human gastrointestinal tract. Moreover, the in silico screening of human/animal metagenomic datasets showed an intriguing association/correlation between B. adolescentis load and mental disorders such as depression and anxiety. Interestingly, in vitro screening of 82 B. adolescentis strains allowed identifying two high GABA producers, i.e. B. adolescentis PRL2019 and B. adolescentis HD17T2H, which were employed in an in vivo trial in rats. Feeding Groningen rats with a supplementation of B. adolescentis strains, confirmed the ability of these microorganisms to stimulate the in vivo production of GABA highlighting their potential implication in gut–brain axis interactions

Computer Vision and Metrics Learning for Hypothesis Testing: An Application of Q-Q Plot for Normality Test

This paper proposes a new procedure to construct test statistics for hypothesis testing by computer vision and metrics learning. The application highlighted in this paper is applying computer vision on Q-Q plot to construct a new test statistic for normality test. Traditionally, there are two families of approaches for verifying the probability distribution of a random variable. Researchers either subjectively assess the Q-Q plot or objectively use a mathematical formula, such as Kolmogorov-Smirnov test, to formally conduct a normality test. Graphical assessment by human beings is not rigorous whereas normality test statistics may not be accurate enough when the uniformly most powerful test does not exist. It may take tens of years for statistician to develop a new and more powerful test statistic. The first step of the proposed method is to apply computer vision techniques, such as pre-trained ResNet, to convert a Q-Q plot into a numerical vector. Next step is to apply metric learning to find an appropriate distance function between a Q-Q plot and the centroid of all Q-Q plots under the null hypothesis, which assumes the target variable is normally distributed. This distance metric is the new test statistic for normality test. Our experimentation results show that the machine-learning-based test statistics can outperform traditional normality tests in all cases, particularly when the sample size is small. This study provides convincing evidence that the proposed method could objectively create a powerful test statistic based on Q-Q plots and this method could be modified to construct many more powerful test statistics for other applications in the future