Neumannmiles1979

In the current study, however, we demonstrate that the highly conserved bba30 gene is not required by the Lyme disease spirochete at any stage of the experimental mouse/tick infectious cycle. We conclude that the undefined circumstances under which bba30 potentially confers a fitness advantage in the natural life cycle of B. burgdorferi are not factors of the experimental infectious cycle that we employ.The type IV secretion system of Neisseria gonorrhoeae translocates single-stranded DNA into the extracellular space, facilitating horizontal gene transfer and initiating biofilm formation. Expression of this system has been observed to be low under laboratory conditions, and multiple levels of regulation have been identified. We used a translational fusion of lacZ to traD, the gene for the type IV secretion system coupling protein, to screen for increased type IV secretion system expression. We identified several physiologically relevant conditions, including surface adherence, decreased manganese or iron, and increased zinc or copper, which increase gonococcal type IV secretion system protein levels through transcriptional and/or translational mechanisms. These metal treatments are reminiscent of the conditions in the macrophage phagosome. The ferric uptake regulator, Fur, was found to repress traD transcript levels, but to also have a second role, acting to allow TraD protein levels to increase only in the absence of iron. To better understand type IV secretion system regulation during infection, we examined transcriptomic data from active urethral infection samples from five men. These data demonstrated differential expression of 20 of 21 type IV secretion system genes during infection, indicating upregulation of genes necessary for DNA secretion during host infection.Understanding the environmental factors that affect the production of virulence factors has major implications in evolution and medicine. While spatial structure is important in virulence factor production, observations of this relationship have occurred in undisturbed or continuously disturbed environments. However, natural environments are subject to periodic fluctuations, including changes in physical forces, which could alter the spatial structure of bacterial populations and impact virulence factor production. Using Pseudomonas aeruginosa PA14, we periodically applied a physical force to biofilms and examined production of pyoverdine. Intermediate frequencies of disturbance reduced the amount of pyoverdine produced compared to undisturbed or frequently disturbed conditions. To explore the generality of this finding, we examined how an intermediate disturbance frequency affected pyoverdine production in 21 different strains of P. aeruginosa. Periodic disturbance increased, decreased, or did not change then increase the production of some virulence factors, including pyoverdine, which is produced by Pseudomonas aeruginosa. Pyoverdine is essential for the infection process, and reducing its production can limit infections. We have discovered that periodically changing the spatial structure of a biofilm of P. aeruginosa strain PA14 using a physical force can reduce the production of pyoverdine. A mathematical model suggests that this is due to the disruption of spatial organization. Using additional strains of P. aeruginosa isolated from patients and the environment, we use experiments and modeling to show that this reduction in pyoverdine is due to interactions between biofilm density and the synthesis rate of pyoverdine. Our results identify conditions where pyoverdine production is reduced and may lead to novel ways to treat infections.Microbial gene clusters encoding the biosynthesis of primary and secondary metabolites play key roles in shaping microbial ecosystems and driving microbiome-associated phenotypes. Although effective approaches exist to evaluate the metabolic potential of such bacteria through identification of these metabolic gene clusters in their genomes, no automated pipelines exist to profile the abundance and expression levels of such gene clusters in microbiome samples to generate hypotheses about their functional roles, and to find associations with phenotypes of interest. Here, we describe BiG-MAP, a bioinformatic tool to profile abundance and expression levels of gene clusters across metagenomic and metatranscriptomic data and evaluate their differential abundance and expression under different conditions. To illustrate its usefulness, we analyzed 96 metagenomic samples from healthy and caries-associated human oral microbiome samples and identified 252 gene clusters, including unreported ones, that were significantlyic genomic regions, also known as gene clusters. With the increasing numbers of (multi)omics data sets that can help in understanding complex ecosystems at a much deeper level, there is a need to create tools that can automate the process of analyzing these gene clusters across omics data sets. This report presents a new software tool called BiG-MAP, which allows assessing gene cluster abundance and expression in microbiome samples using metagenomic and metatranscriptomic data. Here, we describe the tool and its functionalities, as well as its validation using a mock community. Finally, using an oral microbiome data set, we show how it can be used to generate hypotheses regarding the functional roles of gene clusters in mediating host phenotypes.Prior to the advent of milk pasteurization and the use of defined-strain starter cultures, the production and ripening of cheese relied on the introduction and growth of adventitious microbes from the environment. This study characterized microbial community structures throughout a traditional farmstead cheese production continuum and evaluated the role of the environment in microbial transfer. In total, 118 samples (e.g., raw milk, cheese, and environmental surfaces) were collected from milk harvesting through cheese ripening. Microbial communities were characterized based on amplicon sequencing of bacterial 16S rRNA and fungal internal transcribed spacer genes using the Illumina MiSeq platform. Results indicated that the environment in each processing room harbored unique microbial ecosystems and consistently contributed microbes to milk, curd, and cheese. The diverse microbial composition of milk was initially attributed to milker hands and cow teats and then changed substantially following overnight ripenheese microbial diversity. The rapid growth of the artisanal cheese industry in the United States has renewed interest in recapturing the diversity of dairy products and the microbes involved in their production. Here, we demonstrate the essential role of the environment, including the use of wooden tools and cheesemaking equipment, as sources of dominant microbes that shape the fermentation and ripening processes of a traditional farmstead cheese produced without the addition of starter cultures or direct inoculation of any other bacteria or fungi. These data enrich our understanding of the microbial interactions between products and the environment and identify taxa that contribute to the microbial diversity of cheese and cheese production.Cropping system diversity provides yield benefits that may result from shifts in the composition of root-associated bacterial and fungal communities, which either enhance nutrient availability or limit nutrient loss. We investigated whether temporal diversity of annual cropping systems (four versus two crops in rotation) influences the composition and metabolic activities of root-associated microbial communities in maize at a developmental stage when the peak rate of nitrogen uptake occurs. We monitored total (DNA-based) and potentially active (RNA-based) bacterial communities and total (DNA-based) fungal communities in the soil, rhizosphere, and endosphere. Cropping system diversity strongly influenced the composition of the soil microbial communities, which influenced the recruitment of the resident microbial communities and, in particular, the potentially active rhizosphere and endosphere bacterial communities. The diversified cropping system rhizosphere recruited a more diverse bacterial community (specie potential for loss of nitrate from these systems.Bacterial communities in water, soil, and humans play an essential role in environmental ecology and human health. PCR-based amplicon analysis, such as 16S rRNA sequencing, is a fundamental tool for quantifying and studying microbial composition, dynamics, and interactions. However, given the complexity of microbial communities, a substantial number of samples becomes necessary for analyses that parse the factors that determine microbial composition. A common bottleneck in performing these kinds of experiments is genomic DNA (gDNA) extraction, which is time-consuming, expensive, and often biased based on the types of species present. Direct PCR method is a potentially simpler and more accurate alternative to gDNA extraction methods that do not require the intervening purification step. In this study, we evaluated three variations of direct PCR methods using diverse heterogeneous bacterial cultures, including both Gram-positive and Gram-negative species, ZymoBIOMICS microbial community standards, and groundwat experimental load. However, the current DNA extraction methods, including cell disruption and genomic DNA purification, are normally biased, costly, time-consuming, labor-intensive, and not amenable to miniaturization by droplets or 1,536-well plates due to the significant DNA loss during the purification step for tiny-volume and low-cell-density samples. A direct PCR method could potentially solve these problems. click here In this study, we developed a direct PCR method which exhibits similar efficiency as the widely used method, the DNeasy PowerSoil protocol, while being 1,600 times less expensive and 10 times faster to execute. This simple, cost-effective, and automation-friendly direct-PCR-based 16S rRNA sequencing method allows us to study the dynamics, microbial interaction, and assembly of various microbial communities in a high-throughput fashion.Streptococcus pyogenes is known to cause both mucosal and systemic infections in humans. In this study, we used a combination of quantitative and structural mass spectrometry techniques to determine the composition and structure of the interaction network formed between human plasma proteins and the surfaces of different S. pyogenes serotypes. Quantitative network analysis revealed that S. pyogenes forms serotype-specific interaction networks that are highly dependent on the domain arrangement of the surface-attached M protein. Subsequent structural mass spectrometry analysis and computational modeling of one of the M proteins, M28, revealed that the network structure changes across different host microenvironments. We report that M28 binds secretory IgA via two separate binding sites with high affinity in saliva. During vascular leakage mimicked by increasing plasma concentrations in saliva, the binding of secretory IgA was replaced by the binding of monomeric IgA and C4b-binding protein (C4BP). This indicatrotein interactions formed around one of the foremost human pathogens. This strategy allowed us to decipher the protein interaction networks around different S. pyogenes strains on a global scale and to compare and visualize how such interactions are mediated by M proteins.