Metabolite profiling of the cold adaptation of Pseudomonas putida KT2440 and cold‐sensitive mutants

Free-living bacteria such as Pseudomonas putida are frequently exposed to temperature shifts and non-optimal growth conditions. We compared the transcriptome and metabolome of the cold adaptation of Pseudomonas putida KT2440 and isogenic cold-sensitive transposon mutants carrying transposons in their cbrA, cbrB, pcnB, vacB and bipA genes. P. putida changes the mRNA expression of about 43% of all annotated ORFs during this initial phase of cold adaptation, but only a small number of six to 93 genes were differentially expressed at 10°C between wild type strain and the individual mutants. The spectrum of metabolites underwent major changes during cold adaptation particularly in the mutants. Both KT2440 strain and the mutants increased the levels of the most abundant sugars and amino acids which were more pronounced in the cold-sensitive mutants. All mutants depleted their pools for core metabolites of aromatic and sugar metabolism, but increased their pool of polar amino acids which should be advantageous to cope with the cold stress

Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome

The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions

Like Will to Like: Abundances of Closely Related Species Can Predict Susceptibility to Intestinal Colonization by Pathogenic and Commensal Bacteria

The intestinal ecosystem is formed by a complex, yet highly characteristic microbial community. The parameters defining whether this community permits invasion of a new bacterial species are unclear. In particular, inhibition of enteropathogen infection by the gut microbiota ( = colonization resistance) is poorly understood. To analyze the mechanisms of microbiota-mediated protection from Salmonella enterica induced enterocolitis, we used a mouse infection model and large scale high-throughput pyrosequencing. In contrast to conventional mice (CON), mice with a gut microbiota of low complexity (LCM) were highly susceptible to S. enterica induced colonization and enterocolitis. Colonization resistance was partially restored in LCM-animals by co-housing with conventional mice for 21 days (LCMcon21). 16S rRNA sequence analysis comparing LCM, LCMcon21 and CON gut microbiota revealed that gut microbiota complexity increased upon conventionalization and correlated with increased resistance to S. enterica infection. Comparative microbiota analysis of mice with varying degrees of colonization resistance allowed us to identify intestinal ecosystem characteristics associated with susceptibility to S. enterica infection. Moreover, this system enabled us to gain further insights into the general principles of gut ecosystem invasion by non-pathogenic, commensal bacteria. Mice harboring high commensal E. coli densities were more susceptible to S. enterica induced gut inflammation. Similarly, mice with high titers of Lactobacilli were more efficiently colonized by a commensal Lactobacillus reuteri RR strain after oral inoculation. Upon examination of 16S rRNA sequence data from 9 CON mice we found that closely related phylotypes generally display significantly correlated abundances (co-occurrence), more so than distantly related phylotypes. Thus, in essence, the presence of closely related species can increase the chance of invasion of newly incoming species into the gut ecosystem. We provide evidence that this principle might be of general validity for invasion of bacteria in preformed gut ecosystems. This might be of relevance for human enteropathogen infections as well as therapeutic use of probiotic commensal bacteria

The Microbiota Mediates Pathogen Clearance from the Gut Lumen after Non-Typhoidal Salmonella Diarrhea

Many enteropathogenic bacteria target the mammalian gut. The mechanisms protecting the host from infection are poorly understood. We have studied the protective functions of secretory antibodies (sIgA) and the microbiota, using a mouse model for S. typhimurium diarrhea. This pathogen is a common cause of diarrhea in humans world-wide. S. typhimurium (S. tmatt, sseD) causes a self-limiting gut infection in streptomycin-treated mice. After 40 days, all animals had overcome the disease, developed a sIgA response, and most had cleared the pathogen from the gut lumen. sIgA limited pathogen access to the mucosal surface and protected from gut inflammation in challenge infections. This protection was O-antigen specific, as demonstrated with pathogens lacking the S. typhimurium O-antigen (wbaP, S. enteritidis) and sIgA-deficient mice (TCRβ−/−δ−/−, JH−/−, IgA−/−, pIgR−/−). Surprisingly, sIgA-deficiency did not affect the kinetics of pathogen clearance from the gut lumen. Instead, this was mediated by the microbiota. This was confirmed using ‘L-mice’ which harbor a low complexity gut flora, lack colonization resistance and develop a normal sIgA response, but fail to clear S. tmatt from the gut lumen. In these mice, pathogen clearance was achieved by transferring a normal complex microbiota. Thus, besides colonization resistance ( = pathogen blockage by an intact microbiota), the microbiota mediates a second, novel protective function, i.e. pathogen clearance. Here, the normal microbiota re-grows from a state of depletion and disturbed composition and gradually clears even very high pathogen loads from the gut lumen, a site inaccessible to most “classical” immune effector mechanisms. In conclusion, sIgA and microbiota serve complementary protective functions. The microbiota confers colonization resistance and mediates pathogen clearance in primary infections, while sIgA protects from disease if the host re-encounters the same pathogen. This has implications for curing S. typhimurium diarrhea and for preventing transmission

Confined acoustic and optical plasmons in double-layered quantum-wire arrays with strong tunneling

We investigate electronic excitations in GaAs-AlxGa1-xAs double-layered quantum wire arrays with strong tunneling coupling by resonant inelastic light scattering. By applying an external electric field, we can change the one-dimensional (1D) electron density and the symmetry of the double quantum-well (DQW) structure at the same time. We identify confined optical 1D intersubband plasmons (COP) and confined acoustic 1D intersubband plasmons (CAP). Due to the tunneling coupling, the energies of the CAP exhibit a minimum for a symmetric DQW potential, whereas the energies of the COP are dominated by the total carrier density, and are nearly insensitive to the symmetry of the potential