Comparative genomic analysis of the gut bacterium Bifidobacterium longum reveals loci susceptible to deletion during pure culture growth

<p>Abstract</p> <p>Background</p> <p>Bifidobacteria are frequently proposed to be associated with good intestinal health primarily because of their overriding dominance in the feces of breast fed infants. However, clinical feeding studies with exogenous bifidobacteria show they don't remain in the intestine, suggesting they may lose competitive fitness when grown outside the gut.</p> <p>Results</p> <p>To further the understanding of genetic attenuation that may be occurring in bifidobacteria cultures, we obtained the complete genome sequence of an intestinal isolate, <it>Bifidobacterium longum </it>DJO10A that was minimally cultured in the laboratory, and compared it to that of a culture collection strain, <it>B. longum </it>NCC2705. This comparison revealed colinear genomes that exhibited high sequence identity, except for the presence of 17 unique DNA regions in strain DJO10A and six in strain NCC2705. While the majority of these unique regions encoded proteins of diverse function, eight from the DJO10A genome and one from NCC2705, encoded gene clusters predicted to be involved in diverse traits pertinent to the human intestinal environment, specifically oligosaccharide and polyol utilization, arsenic resistance and lantibiotic production. Seven of these unique regions were suggested by a base deviation index analysis to have been precisely deleted from strain NCC2705 and this is substantiated by a DNA remnant from within one of the regions still remaining in the genome of NCC2705 at the same locus. This targeted loss of genomic regions was experimentally validated when growth of the intestinal <it>B. longum </it>in the laboratory for 1,000 generations resulted in two large deletions, one in a lantibiotic encoding region, analogous to a predicted deletion event for NCC2705. A simulated fecal growth study showed a significant reduced competitive ability of this deletion strain against <it>Clostridium difficile </it>and <it>E. coli</it>. The deleted region was between two IS<it>30 </it>elements which were experimentally demonstrated to be hyperactive within the genome. The other deleted region bordered a novel class of mobile elements, termed mobile integrase cassettes (MIC) substantiating the likely role of these elements in genome deletion events.</p> <p>Conclusion</p> <p>Deletion of genomic regions, often facilitated by mobile elements, allows bifidobacteria to adapt to fermentation environments in a very rapid manner (2 genome deletions per 1,000 generations) and the concomitant loss of possible competitive abilities in the gut.</p

Carbon Metabolism of Methylotrophic Methanogens and Asgard Archaea in Marine Sediments

Carbon is the central element of life, as it is involved in building up of biological constituents and energy metabolisms in the cell. Archaea, - the most recently recognized domain of life - hold a crucial phylogenetic position in the evolution of life, but for most archaeal phyla, little is known about their role and activity in carbon metabolism. Archaea inhabit a variety of environments such as soils, sediments, sea water, and the guts of animals. Specifically in marine sediments, Thaumarchaeota, Euryarchaeota, Bathyarchaeota, Woesearchaeota and Asgard archaea are commonly found in archaeal communities. Methanogens affiliated to Euryarchaeota are well-known players in carbon metabolism, i.e., acetoclastic, hydrogenotrophic, and methylotrophic methanogenesis. Based on pure culture studies and genomic evidence, significant amounts of the biomass of methylotrophic methanogens growing on methyl substrates is derived from inorganic carbon. However, the in situ activity of these methanogens in carbon assimilation is unclear as the large inorganic carbon pool in marine sediment potentially affects carbon utilization patterns. To address this hypothesis, we initially applied nucleic acid stable isotope probing (SIP) to detect methylotrophic methanogens in marine sediment incubations. SIP results showed that 13C-labeled dissolved inorganic carbon (DIC) is necessary to identify methylotrophic methanogens, as illustrated by the nucleic acid synthesis pathway in these methanogens that 70-80% of carbon stems from DIC rather than methanol. In parallel, lipid-SIP suggested that DIC contributed to more than 60% from incubations with sediment from the sulfate reduction zone (SRZ), i.e., 20% higher than expected from lipid synthesis pathway. We further unexpectedly found that up to 12% methane was formed from DIC in autoclaved slurry incubations inoculated with the marine methylotrophic methanogen Methanococcoides methylutens. Similarly, methane formation from CO2 during methylotrophic methanogenesis was also observed with SRZ sediment incubations. In the same sediment incubations a higher amount of inorganic carbon was incorporated into lipids than expected, indicating that more DIC was assimilated into biomass than expected. Thus, the CO2 conversion to methane and biomass may play an important role in marine sediments. In the most recently discovered super phylum of the Archaea, the Asgard archaea might hold the key to understand the evolutionary origin of eukaryotes. Unlike methanogens, however, the diversity, carbon metabolism and the activity of Asgard archaea in marine sediments are still unknown. In this study, five new groups of Asgard archaea namely Kariarchaeota, Balderarchaeota, Hodarchaeota, Lagarchaeota and Gerdarchaeota are reported. In experiments with 13C-DIC, potential electron donors and electron acceptors, subgroup of Asgard archaea i.e., Lokiarchaeota was detected in the heavy SIP fractions from the incubations amended with organic polymers or sulfur, suggesting their activities of carbon fixation, organic polymers (cellulose, lignin and humic acid) degradation and sulfur metabolism. Furthermore, metagenomes were sequenced from heavy fractions of DNA-SIP samples obtained in the aforementioned experiments and from DNA extracted from mangrove sediments in the southeast coast of China. These metagenomes indicate that Asgard archaea harbor pathways of inorganic carbon fixation and degradation of cellulose, protein, short-chain and medium-chain alkane as well as assimilatory sulfate reduction. Crucially, the methyl coenzyme M reductase genes found in Helarchaeota have extended the potential of short-chain hydrocarbon oxidation to the Asgard archaea in this study. Overall, these findings illustrate that Asgard archaea actively utilize organic and inorganic carbon at the same time in mixotrophic fashion, which might play critical roles in carbon cycling of marine sediments. In particular, the successful detection of methylotrophic methanogens and Asgard archaea in marine sediments by nucleic acid-SIP with 13C-DIC suggested a crucial role of inorganic carbon in carbon metabolisms of these archaea. Given that many archaea harbor the acetyl-CoA associated carbon fixation pathway, my findings indicate that inorganic carbon assimilation might be ubiquitous in archaea when supply or availability of organic carbon are not sufficient in marine sediments

The development and optimization of microbial molecular biomarkers for the in situ assessment of trace metal toxicity

Merged with duplicate record 10026.1/2607 on 06.20.2017 by CS (TIS)Microorganisms are fundamental components of many geochemical transformations occurring in the aquatic environment. Microbial redox and methylation of metals within the environment can alter metal speciation, mobility and ultimately, toxicity to eukaryotes. It is therefore practical that any environmental monitoring framework advocating the application of `early-warning biomarker system' should incorporate a holistic view of the environment beginning with microbial activity. This thesis describes the development of protocols for assessing the in situ condition of microbial ecosystems within a gradient of metal contaminated sites radiating downstream of the Anaconda Smelter, a USEPA-designated superfund site and within two control sites. Experiments focus on evaluating the incidence (i. e. prevalence and absence) of genes related to general stress and specific metal detoxification reactions. Moreover, a number of selected genes were quantified directly from the environment and statistically correlated with metal concentrations. Furthermore, the influence of metals on structuring microbial communities was also investigated by evaluating temporal communities shifts in response to changing metal concentrations using denaturant gradient gel electrophoresis (DGGE). The data recorded the highest prevalence of all genes was found at the most polluted site directly downstream of the Anaconda Smelter. Furthermore, significant correlations were observed between gene prevalence and metals (arsenic, copper and zinc) (P < 0.05) and organic carbon concentration (P < 0.05). A number of genes were successfully amplified from sediment with significantly higher gene copy number (/ ng DNA) at the more polluted sites when compared to corresponding control sites. Examination of community diversity found that long-term metal-contaminated sediments, adjacent to the Smelter, had microbial communities twice as diverse as corresponding reference sites. In addition, multivariate statistical techniques identified factors important to community structuring, concluding that geographic position and localized geochemistry fundamentally influence the structuring of communities. This thesis represents a significant advance in the use of microorganisms as `early warning systems' of deterioration in ecosystem health, while the application of advanced molecular methods facilitates their intergration within a traditional ecotoxicological framework.Montana State Universit

Insights into RNA structure by melding experiment and computation

The ability of RNA to perform diverse cellular functions depends on its capability to form complex structures. Therefore, determining RNA structure is critical to understanding RNA function. Computational methods allow for quick determination of RNA structures, but are often prone to inaccuracies in their predictions. A newly developed technology, known as SHAPE, can be used to probe RNA structure and identify nucleotides that are likely to be single stranded and base paired. This SHAPE data can be inputted into an RNA structure program to refine predictions. Previous studies have shown that the incorporation of SHAPE data can increase the accuracy of prediction by over 30% compared to traditional mFold class algorithms. In this work, I utilize SHAPE technology to refine RNA predictions and solve new challenges. First, I create an algorithm, ShapeKnots, which incorporates SHAPE data and the prediction of pseudoknots. Pseudoknots are relatively rare RNA structural motifs that have a tendency of occurring in functional regions, but, due to their complexity, are often eliminated from structural prediction. Second, I utilize the ShapeKnots algorithm to identify pseudoknots in HIV-1 and test their role in viral replication. Third, I develop a modified partition function calculation to identify the de novo accuracy of secondary structure predictions. This allows end users to not only obtain a predicted structure, but also, to know the confidence of that prediction. Fourth, I utilize SHAPE-directed folding to identify potential alternative structures in the ribosome. Finally, I create a method to identify the accuracy of tertiary structure predictions. This allows for a quantitative measurement of accuracy when comparing predicted tertiary structures with previously determined conventional structures.Doctor of Philosoph

Investigation of the genetic basis of antibiotic resistance in Mycobacterium tuberculosis

The emergence of antibiotic resistant strains of Mycobacterium tuberculosis, coupled with the time it takes to perform phenotypic drug susceptibility testing of this organism, makes the treatment of tuberculosis increasingly difficult. Several genotypic assays for the rapid detection of drug resistance in M. tuberculosis have been developed, but the sensitivity with which these assays identify resistance differs geographically. Additionally, the identification of phenotypically resistant isolates with no identifiable genotypic marker suggests that other factors, such as differential gene expression, may play a role in the development of drug resistance in M. tuberculosis. This investigation aims to both develop and evaluate rapid genotypic assays for the detection of resistance to both first- and second-line drugs in M. tuberculosis, and to investigate the role of alternative sigma factors in the progression to multidrug resistant M. tuberculosis

The genetics of geochemistry

Bacteria are remarkable in their metabolic diversity due to their ability to harvest energy from myriad oxidation and reduction reactions. In some cases, their metabolisms involve redox transformations of metal(loid)s, which lead to the precipitation, transformation, or dissolution of minerals. Microorganism/mineral interactions not only affect the geochemistry of modern environments, but may also have contributed to shaping the near-surface environment of the early Earth. For example, bacterial anaerobic respiration of ferric iron or the toxic metalloid arsenic is well known to affect water quality in many parts of the world today, whereas the utilization of ferrous iron as an electron donor in anoxygenic photosynthesis may help explain the origin of Banded Iron Formations, a class of ancient sedimentary deposits. Bacterial genetics holds the key to understanding how these metabolisms work. Once the genes and gene products that catalyze geochemically relevant reactions are understood, as well as the conditions that trigger their expression, we may begin to predict when and to what extent these metabolisms influence modern geochemical cycles, as well as develop a basis for deciphering their origins and how organisms that utilized them may have altered the chemical and physical features of our planet

SkewIT, Bracken, and Kraken: Methods for Analyzing a Complex, But Invisible World

As the DNA of the invisible world provides insight into the countless microscopic organisms living amongst us, the integrity of these genomes and the methods by which we analyze them become increasingly important. In the following, I introduce methods for both evaluating genomic integrity and analyzing microbial communities. For the analysis of bacterial genomes, I developed SkewIT (Skew Index Test) based on GC Skew, a bacterial genome phenomenon wherein the two replication strands of the same chromosome contain different proportions of guanine and cytosine nucleotides. SkewIT calculates a single metric representing the degree of GC skew for a single genome. Applied across 15,000+ complete bacterial genomes, SkewIT quickly detects assembly patterns and highlights potential bacterial mis-assemblies. Although eukaryotic microorganisms are abundant worldwide and as human pathogens, eukaryotic pathogen genomes are underrepresented in genomic databases and contain significant contamination. I therefore developed a bioinformatics system for eliminating contamination, generating a “clean” eukaryotic pathogen database (EuPathDB-Clean) of nearly 400 genomes. With the final database, I identify eukaryotic pathogens in human samples, demonstrating the increased sensitivity and reduction in false positives of the final database as compared to the originally contaminated genomes. As metagenomics captures the genomic data of all microbial organisms in any environment, I developed Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) for a quick and accurate characterization of the full microbial environment. Bracken uses the taxonomic assignments made by Kraken, a very fast read-level classifier, along with information about the genomes themselves to estimate abundance at the species level, the genus level, or above. I demonstrate that Bracken produces accurate abundance estimates even when a sample contains multiple near-identical species for both shotgun metagenomics projects and for 16S ribosomal RNA (rRNA) bacterial projects. SkewIT, Bracken, and EuPathDB-Clean are all publicly available for use in future metagenomics projects