Project description:The relative contribution of genetic and environmental factors to variation in immune response is still poorly understood. Here, we performed a deep phenotypic analysis of immunological parameters and molecular profiles of laboratory mice released into an outdoor enclosure, carrying genetic susceptibility genes (Nod2 and Atg16l1) implicated in the development of inflammatory bowel diseases. Differences in lymphocyte populations were largely driven by the lab and wild environment. However, cytokine production after stimulation with microbial antigens showed a stronger genetic component in the lab, which was reduced after exposure to the wild environment. Multi-omic models identified key transcriptional factors associated with lymphocyte changes predictive of the environment, as well as sub-networks associated with cytokine responses against Candida albicans and Bacteroides vulgatus. Hence, exposing laboratory mice of different genetic backgrounds to the outdoor environment may identify important contributors to immune variation.
Project description:Here, we report 17 metagenome-assembled genomes (MAGs) recovered from microbial consortia of forest and pasture soils in the Brazilian Eastern Amazon. The bacterial MAGs have the potential to act in important ecological processes, including carbohydrate degradation and sulfur and nitrogen cycling.
Project description:The metagenomes of complex microbial communities are rich sources of novel biocatalysts. We exploited the metagenome of a mixed microbial population for isolation of more than 15 different genes encoding novel biocatalysts by using a combined cultivation and direct cloning strategy. A 16S rRNA sequence analysis revealed the presence of hitherto uncultured microbes closely related to the genera Pseudomonas, Agrobacterium, Xanthomonas, Microbulbifer, and Janthinobacterium. Total genomic DNA from this bacterial community was used to construct cosmid DNA libraries, which were functionally searched for novel enzymes of biotechnological value. Our searches in combination with cosmid sequencing resulted in identification of four clones encoding 12 putative agarase genes, most of which were organized in clusters consisting of two or three genes. Interestingly, nine of these agarase genes probably originated from gene duplications. Furthermore, we identified by DNA sequencing several other biocatalyst-encoding genes, including genes encoding a putative stereoselective amidase (amiA), two cellulases (gnuB and uvs080), an alpha-amylase (amyA), a 1,4-alpha-glucan branching enzyme (amyB), and two pectate lyases (pelA and uvs119). Also, a conserved cluster of two lipase genes was identified, which was linked to genes encoding a type I secretion system. The novel gene aguB was overexpressed in Escherichia coli, and the enzyme activities were determined. Finally, we describe more than 162 kb of DNA sequence that provides a strong platform for further characterization of this microbial consortium.
Project description:Soil microbial communities contain the highest level of prokaryotic diversity of any environment, and metagenomic approaches involving the extraction of DNA from soil can improve our access to these communities. Most analyses of soil biodiversity and function assume that the DNA extracted represents the microbial community in the soil, but subsequent interpretations are limited by the DNA recovered from the soil. Unfortunately, extraction methods do not provide a uniform and unbiased subsample of metagenomic DNA, and as a consequence, accurate species distributions cannot be determined. Moreover, any bias will propagate errors in estimations of overall microbial diversity and may exclude some microbial classes from study and exploitation. To improve metagenomic approaches, investigate DNA extraction biases, and provide tools for assessing the relative abundances of different groups, we explored the biodiversity of the accessible community DNA by fractioning the metagenomic DNA as a function of (i) vertical soil sampling, (ii) density gradients (cell separation), (iii) cell lysis stringency, and (iv) DNA fragment size distribution. Each fraction had a unique genetic diversity, with different predominant and rare species (based on ribosomal intergenic spacer analysis [RISA] fingerprinting and phylochips). All fractions contributed to the number of bacterial groups uncovered in the metagenome, thus increasing the DNA pool for further applications. Indeed, we were able to access a more genetically diverse proportion of the metagenome (a gain of more than 80% compared to the best single extraction method), limit the predominance of a few genomes, and increase the species richness per sequencing effort. This work stresses the difference between extracted DNA pools and the currently inaccessible complete soil metagenome.
Project description:The Arecibo Observatory (AO) located in Arecibo, Puerto Rico, is the most sensitive, powerful and active planetary radar system in the world [1]. One of its principal components is the 305 m-diameter spherical reflector dish (AORD), which is exposed to high frequency electromagnetic waves. To unravel the microbial communities that inhabit this environment, soil samples from underneath the AORD were collected, DNA extracted, and sequenced using Illumina MiSeq. Taxonomic and functional profiles were generated using the MG-RAST server. The most abundant domain was Bacteria (91%), followed by Virus (8%), Archaea (0.9%) and Eukaryota (0.9%). The most abundant phylum was Proteobacteria (54%), followed by Actinobacteria (8%), Bacteroidetes (5%) and Firmicutes (4%). In terms of functions, the most abundant among the metagenome corresponded to phages, transposable elements and plasmids (16%), followed by clustering-based subsystems (11%), carbohydrates (10%), and amino acids and derivatives (9%). This is the first soil metagenomic dataset from dish antennas and radar systems, specifically, underneath the AORD. Data can be used to explore the effect of high frequency electromagnetic waves in soil microbial composition, as well as the possibility of finding bioprospects with potential biomedical and biotechnological applications.
Project description:Bacteriophages are abundant in soils. However, the majority are uncharacterized, and their hosts are unknown. Here, we apply high-throughput chromosome conformation capture (Hi-C) to directly capture phage-host relationships. Some hosts have high centralities in bacterial community co-occurrence networks, suggesting phage infections have an important impact on the soil bacterial community interactions. We observe increased average viral copies per host (VPH) and decreased viral transcriptional activity following a two-week soil-drying incubation, indicating an increase in lysogenic infections. Soil drying also alters the observed phage host range. A significant negative correlation between VPH and host abundance prior to drying indicates more lytic infections result in more host death and inversely influence host abundance. This study provides empirical evidence of phage-mediated bacterial population dynamics in soil by directly capturing specific phage-host interactions.
Project description:Nine Curtobacterium strains (three from three clades) were subjected to a lab desiccation experiment with no access to moisture or nutrients to compare between clades. RNA was extracted at days 0, 1, and 32 and sequenced
Project description:In our lab we detected focal genomic amplification of PDE1C in 90% of short term GBM cultures. Knocking down of PDE1C was associated with compromised capacity opf these cultures to proliferate, migrate and invade. Therefore we carried out affymetric whole genome expression analysis to identify the down stream gene effectors of this function effects.
Project description:This experiment was annotated by TAIR (http://arabidopsis.org). This experiment looks at changes in gene expression in Col-0 plants grown in soil in response to low temperature over time. Experimenter name = Jonathan Vogel Experimenter phone = 517-355-2299 Experimenter fax = 517-353-5174 Experimenter department = MSU-DOE Plant Research Lab Experimenter institute = Michigan State University Experimenter address = East Lansing Experimenter zip/postal_code = MI 48824 Experimenter country = USA Keywords: time_series_design