Geobiology of marine magnetotactic bacteria

Submitted in partial fulfillment of the requirements of the degree of Doctor of Philosophy in Biological Oceanography at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2006Magnetotactic bacteria (MTB) biomineralize intracellular membrane-bound crystals of magnetite (Fe3O4) or greigite (Fe3S4), and are abundant in the suboxic to anoxic zones of stratified marine environments worldwide. Their population densities (up to 105 cells ml−1) and high intracellular iron content suggest a potentially significant role in iron cycling, but very little is known about their population dynamics and regulation by environmental geochemistry. The MTB community in Salt Pond (Falmouth, MA), a small stratified marine basin, was used as a model system for quantitative community studies. Magnetiteproducing MTB predominate slightly above the oxic-anoxic interface and greigiteproducing MTB predominate in sulfidic waters. A quantitative PCR (QPCR) assay was developed and applied to enumerate four major groups of MTB in Salt Pond: magnetite-producing cocci, barbells, the greigite-producing many-celled magnetotactic prokaryote (MMP), and a greigite-producing rod. The barbells were identified as δ-Proteobacteria while the rod was identified as the first MTB in the γ-Proteobacteria. The MMP, previously thought to be a single species, consists of at least five clades with greater than 5% divergence in their 16s rRNA. Fluorescent in situ hybridization probes showed significant variation in clade abundances across a seasonal cycle in salt marsh productivity. FISH also showed that aggregates consist of genetically identical cells. QPCR data indicated that populations are finely layered around the oxic-anoxic interface: cocci immediately above the dissolved Fe(II) peak, barbells immediately below, the MMP in microsulfidic waters, and the greigite-producing rod in low numbers (100 cells ml−1) below the gradient region. The barbell reached 1-10% of total eubacteria in the late season, and abundances of cocci and barbells appeared to vary inversely. Calculations based on qPCR data suggest that MTB are significant unrecognized contributors to iron flux in stratified environments. Barbells can respond to high oxygen levels by swimming toward geomagnetic south, the opposite of all previously reported magnetotactic behavior. This behavior is at least partially dependent on environmental oxidation-reduction potential. The co-existence of MTB with opposing polarities in the same redox environment conflicts with current models of the adaptive value of magnetotaxis.Funding for the research described in this thesis was provided by the Rinehart Coastal Research Center at WHOI, the WHOI Ocean Life Institute, and the WHOI Ocean Venture Fund

Leaf-FISH : microscale imaging of bacterial taxa on phyllosphere

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Frontiers in Microbiology 8 (2018): 2669, doi:10.3389/fmicb.2017.02669.Molecular methods for microbial community characterization have uncovered environmental and plant-associated factors shaping phyllosphere communities. Variables undetectable using bulk methods can play an important role in shaping plant-microbe interactions. Microscale analysis of bacterial dynamics in the phyllosphere requires imaging techniques specially adapted to the high autoflouresence and 3-D structure of the leaf surface. We present an easily-transferable method (Leaf-FISH) to generate high-resolution tridimensional images of leaf surfaces that allows simultaneous visualization of multiple bacterial taxa in a structurally informed context, using taxon-specific fluorescently labeled oligonucleotide probes. Using a combination of leaf pretreatments coupled with spectral imaging confocal microscopy, we demonstrate the successful imaging bacterial taxa at the genus level on cuticular and subcuticular leaf areas. Our results confirm that different bacterial species, including closely related isolates, colonize distinct microhabitats in the leaf. We demonstrate that highly related Methylobacterium species have distinct colonization patterns that could not be predicted by shared physiological traits, such as carbon source requirements or phytohormone production. High-resolution characterization of microbial colonization patterns is critical for an accurate understanding of microbe-microbe and microbe-plant interactions, and for the development of foliar bacteria as plant-protective agents.Funding was provided by the J. Unger Vetleson Foundation to SS

The dynamic genetic repertoire of microbial communities

Community genomic data have revealed multiple levels of variation between and within microbial consortia. This variation includes large-scale differences in gene content between ecosystems as well as within-population sequence heterogeneity. In the present review, we focus specifically on how fine-scale variation within microbial and viral populations is apparent from community genomic data. A major unresolved question is how much of the observed variation is due to neutral vs. adaptive processes. Limited experimental data hint that some of this fine-scale variation may be in part functionally relevant, whereas sequence-based and modeling analyses suggest that much of it may be neutral. While methods for interpreting population genomic data are still in their infancy, we discuss current interpretations of existing datasets in the light of evolutionary processes and models. Finally, we highlight the importance of virus–host dynamics in generating and shaping within-population diversity

Ecological succession and stochastic variation in the assembly of Arabidopsis thaliana phyllosphere communities

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in mBio 5 (2014): e00682-13, doi:10.1128/mBio.00682-13.Bacteria living on the aerial parts of plants (the phyllosphere) are globally abundant and ecologically significant communities and can have significant effects on their plant hosts. Despite their importance, little is known about the ecological processes that drive phyllosphere dynamics. Here, we describe the development of phyllosphere bacterial communities over time on the model plant Arabidopsis thaliana in a controlled greenhouse environment. We used a large number of replicate plants to identify repeatable dynamics in phyllosphere community assembly and reconstructed assembly history by measuring the composition of the airborne community immigrating to plant leaves. We used more than 260,000 sequences from the v5v6 hypervariable region of the 16S rRNA gene to characterize bacterial community structure on 32 plant and 21 air samples over 73 days. We observed strong, reproducible successional dynamics: phyllosphere communities initially mirrored airborne communities and subsequently converged to a distinct community composition. While the presence or absence of particular taxa in the phyllosphere was conserved across replicates, suggesting strong selection for community composition, the relative abundance of these taxa was highly variable and related to the spatial association of individual plants. Our results suggest that stochastic events in early colonization, coupled with dispersal limitation, generated alternate trajectories of bacterial community assembly within the context of deterministic selection for community membership.Funding was provided by the J. Unger Vetleson Foundation to S.L.S

Community-wide analysis of microbial genome sequence signatures

Genome signatures are used to identify and cluster sequences de novo from an acid biofilm microbial community metagenomic dataset, revealing information about the low-abundance community members

A Semi-Quantitative, Synteny-Based Method to Improve Functional Predictions for Hypothetical and Poorly Annotated Bacterial and Archaeal Genes

During microbial evolution, genome rearrangement increases with increasing sequence divergence. If the relationship between synteny and sequence divergence can be modeled, gene clusters in genomes of distantly related organisms exhibiting anomalous synteny can be identified and used to infer functional conservation. We applied the phylogenetic pairwise comparison method to establish and model a strong correlation between synteny and sequence divergence in all 634 available Archaeal and Bacterial genomes from the NCBI database and four newly assembled genomes of uncultivated Archaea from an acid mine drainage (AMD) community. In parallel, we established and modeled the trend between synteny and functional relatedness in the 118 genomes available in the STRING database. By combining these models, we developed a gene functional annotation method that weights evolutionary distance to estimate the probability of functional associations of syntenous proteins between genome pairs. The method was applied to the hypothetical proteins and poorly annotated genes in newly assembled acid mine drainage Archaeal genomes to add or improve gene annotations. This is the first method to assign possible functions to poorly annotated genes through quantification of the probability of gene functional relationships based on synteny at a significant evolutionary distance, and has the potential for broad application

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates

© The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Systems Biology 5 Suppl 2 (2011): S15, doi:10.1186/1752-0509-5-S2-S15.The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsaThis research is partially supported by the National Science Foundation (NSF) DMS-1043075 and OCE 1136818

Population Genomic Analysis of Strain Variation in Leptospirillum Group II Bacteria Involved in Acid Mine Drainage Formation

Deeply sampled community genomic (metagenomic) datasets enable comprehensive analysis of heterogeneity in natural microbial populations. In this study, we used sequence data obtained from the dominant member of a low-diversity natural chemoautotrophic microbial community to determine how coexisting closely related individuals differ from each other in terms of gene sequence and gene content, and to uncover evidence of evolutionary processes that occur over short timescales. DNA sequence obtained from an acid mine drainage biofilm was reconstructed, taking into account the effects of strain variation, to generate a nearly complete genome tiling path for a Leptospirillum group II species closely related to L. ferriphilum (sampling depth ∼20×). The population is dominated by one sequence type, yet we detected evidence for relatively abundant variants (>99.5% sequence identity to the dominant type) at multiple loci, and a few rare variants. Blocks of other Leptospirillum group II types (∼94% sequence identity) have recombined into one or more variants. Variant blocks of both types are more numerous near the origin of replication. Heterogeneity in genetic potential within the population arises from localized variation in gene content, typically focused in integrated plasmid/phage-like regions. Some laterally transferred gene blocks encode physiologically important genes, including quorum-sensing genes of the LuxIR system. Overall, results suggest inter- and intrapopulation genetic exchange involving distinct parental genome types and implicate gain and loss of phage and plasmid genes in recent evolution of this Leptospirillum group II population. Population genetic analyses of single nucleotide polymorphisms indicate variation between closely related strains is not maintained by positive selection, suggesting that these regions do not represent adaptive differences between strains. Thus, the most likely explanation for the observed patterns of polymorphism is divergence of ancestral strains due to geographic isolation, followed by mixing and subsequent recombination