Ryan T. Jones

Bio: Ryan T. Jones is an academic researcher from University of Sydney. The author has contributed to research in topics: Flea & Bartonella. The author has an hindex of 13, co-authored 22 publications receiving 1845 citations. Previous affiliations of Ryan T. Jones include Cooperative Institute for Research in Environmental Sciences & University of Colorado Boulder.

A comprehensive survey of soil acidobacterial diversity using pyrosequencing and clone library analyses

Abstract: Acidobacteria are ubiquitous and abundant members of soil bacterial communities. However, an ecological understanding of this important phylum has remained elusive because its members have been difficult to culture and few molecular investigations have focused exclusively on this group. We generated an unprecedented number of acidobacterial DNA sequence data using pyrosequencing and clone libraries (39 707 and 1787 sequences, respectively) to characterize the relative abundance, diversity and composition of acidobacterial communities across a range of soil types. To gain insight into the ecological characteristics of acidobacterial taxa, we investigated the largescale biogeographic patterns exhibited by acidobacterial communities, and related soil and site characteristics to acidobacterial community assemblage patterns. The 87 soils analyzed by pyrosequencing contained more than 8600 unique acidobacterial phylotypes (at the 97% sequence similarity level). One phylotype belonging to Acidobacteria subgroup 1, but not closely related to any cultured representatives, was particularly abundant, accounting for 7.4% of bacterial sequences and 17.6% of acidobacterial sequences, on average, across the soils. The abundance of Acidobacteria relative to other bacterial taxa was highly variable across the soils examined, but correlated strongly with soil pH (R ¼� 0.80, Po0.001). Soil pH was also the best predictor of acidobacterial community composition, regardless of how the communities were characterized, and the relative abundances of the dominant Acidobacteria subgroups were readily predictable. Acidobacterial communities were more phylogenetically clustered as soil pH departed from neutrality, suggesting that pH is an effective habitat filter, restricting community membership to progressively more narrowly defined lineages as pH deviates from neutrality.

Metagenomic and Small-Subunit rRNA Analyses Reveal the Genetic Diversity of Bacteria, Archaea, Fungi, and Viruses in Soil

Abstract: Recent studies have highlighted the surprising richness of soil bacterial communities; however, bacteria are not the only microorganisms found in soil. To our knowledge, no study has compared the diversities of the four major microbial taxa, i.e., bacteria, archaea, fungi, and viruses, from an individual soil sample. We used metagenomic and small-subunit RNA-based sequence analysis techniques to compare the estimated richness and evenness of these groups in prairie, desert, and rainforest soils. By grouping sequences at the 97% sequence similarity level (an operational taxonomic unit [OTU]), we found that the archaeal and fungal communities were consistently less even than the bacterial communities. Although total richness levels are difficult to estimate with a high degree of certainty, the estimated number of unique archaeal or fungal OTUs appears to rival or exceed the number of unique bacterial OTUs in each of the collected soils. In this first study to comprehensively survey viral communities using a metagenomic approach, we found that soil viruses are taxonomically diverse and distinct from the communities of viruses found in other environments that have been surveyed using a similar approach. Within each of the four microbial groups, we observed minimal taxonomic overlap between sites, suggesting that soil archaea, bacteria, fungi, and viruses are globally as well as locally diverse.

A cross-taxon analysis of insect-associated bacterial diversity.

Abstract: Although it is well known that plants and animals harbor microbial symbionts that can influence host traits, the factors regulating the structure of these microbial communities often remain largely undetermined. This is particularly true for insect-associated microbial communities, as few cross-taxon comparisons have been conducted to date. To address this knowledge gap and determine how host phylogeny and ecology affect insect-associated microbial communities, we collected 137 insect specimens representing 39 species, 28 families, and 8 orders, and characterized the bacterial communities associated with each specimen via 16S rRNA gene sequencing. Bacterial taxa within the phylum Proteobacteria were dominant in nearly all insects sampled. On average, the insect-associated bacterial communities were not very diverse, with individuals typically harboring fewer than 8 bacterial phylotypes. Bacterial communities also tended to be dominated by a single phylotype; on average, the most abundant phylotype represented 54.7% of community membership. Bacterial communities were significantly more similar among closely related insects than among less-related insects, a pattern driven by within-species community similarity but detected at every level of insect taxonomy tested. Diet was a poor predictor of bacterial community composition. Individual insect species harbored remarkably unique communities: the distribution of 69.0% of bacterial phylotypes was limited to unique insect species, whereas only 5.7% of phylotypes were detected in more than five insect species. Together these results suggest that host characteristics strongly regulate the colonization and assembly of bacterial communities across insect lineages, patterns that are driven either by co-evolution between insects and their symbionts or by closely related insects sharing conserved traits that directly select for similar bacterial communities.

Why only some plants emit isoprene

Abstract: Isoprene (2-methyl-1,3-butadiene) is emitted from many plants and it appears to have an adaptive role in protecting leaves from abiotic stress. However, only some species emit isoprene. Isoprene emission has appeared and been lost many times independently during the evolution of plants. As an example, our phylogenetic analysis shows that isoprene emission is likely ancestral within the family Fabaceae (= Leguminosae), but that it has been lost at least 16 times and secondarily gained at least 10 times through independent evolutionary events. Within the division Pteridophyta (ferns), we conservatively estimate that isoprene emissions have been gained five times and lost two times through independent evolutionary events. Within the genus Quercus (oaks), isoprene emissions have been lost from one clade, but replaced by a novel type of light-dependent monoterpene emissions that uses the same metabolic pathways and substrates as isoprene emissions. This novel type of monoterpene emissions has appeared at least twice independently within Quercus, and has been lost from 9% of the individuals within a single population of Quercus suber. Gain and loss of gene function for isoprene synthase is possible through relatively few mutations. Thus, this trait appears frequently in lineages; but, once it appears, the time available for evolutionary radiation into environments that select for the trait is short relative to the time required for mutations capable of producing a non-functional isoprene synthase gene. The high frequency of gains and losses of the trait and its heterogeneous taxonomic distribution in plants may be explained by the relatively few mutations necessary to produce or lose the isoprene synthase gene combined with the assumption that isoprene emission is advantageous in a narrow range of environments and phenotypes.

Bacterial Communities of Two Parthenogenetic Aphid Species Cocolonizing Two Host Plants across the Hawaiian Islands

Abstract: Aphids (Hemiptera: Aphididae) have been the focus of several studies with respect to their interactions with inherited symbionts, but bacterial communities of most aphid species are still poorly characterized. In this research, we used bar-coded pyrosequencing to characterize bacterial communities in aphids. Specifically, we examined the diversity of bacteria in two obligately parthenogenetic aphid species (the melon aphid, Aphis gossypii, and the cardamom aphid, Pentalonia caladii) cocolonizing two plant species (taro, Colocasia esculenta, and ginger, Alpinia purpurata) across four Hawaiian Islands (Hawaii, Kauai, Maui, and Oahu). Results from this study revealed that heritable symbionts dominated the bacterial communities for both aphid species. The bacterial communities differed significantly between the two species, and A. gossypii harbored a more diverse bacterial community than P. caladii. The bacterial communities also differed across aphid populations sampled from the different islands; however, communities did not differ between aphids collected from the two host plants.

The Metagenomics RAST Server: A Public Resource for the Automatic Phylogenetic and Functional Analysis of Metagenomes

Abstract: Random community genomes (metagenomes) are now commonly used to study microbes in different environments. Over the past few years, the major challenge associated with metagenomics shifted from generating to analyzing sequences. High-throughput, low-cost next-generation sequencing has provided access to metagenomics to a wide range of researchers. A high-throughput pipeline has been constructed to provide high-performance computing to all researchers interested in using metagenomics. The pipeline produces automated functional assignments of sequences in the metagenome by comparing both protein and nucleotide databases. Phylogenetic and functional summaries of the metagenomes are generated, and tools for comparative metagenomics are incorporated into the standard views. User access is controlled to ensure data privacy, but the collaborative environment underpinning the service provides a framework for sharing datasets between multiple users. In the metagenomics RAST, all users retain full control of their data, and everything is available for download in a variety of formats. The open-source metagenomics RAST service provides a new paradigm for the annotation and analysis of metagenomes. With built-in support for multiple data sources and a back end that houses abstract data types, the metagenomics RAST is stable, extensible, and freely available to all researchers. This service has removed one of the primary bottlenecks in metagenome sequence analysis – the availability of high-performance computing for annotating the data. http://metagenomics.nmpdr.org

Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale.

Abstract: Soils harbor enormously diverse bacterial populations, and soil bacterial communities can vary greatly in composition across space. However, our understanding of the specific changes in soil bacterial community structure that occur across larger spatial scales is limited because most previous work has focused on either surveying a relatively small number of soils in detail or analyzing a larger number of soils with techniques that provide little detail about the phylogenetic structure of the bacterial communities. Here we used a bar-coded pyrosequencing technique to characterize bacterial communities in 88 soils from across North and South America, obtaining an average of 1,501 sequences per soil. We found that overall bacterial community composition, as measured by pairwise UniFrac distances, was significantly correlated with differences in soil pH (r = 0.79), largely driven by changes in the relative abundances of Acidobacteria, Actinobacteria, and Bacteroidetes across the range of soil pHs. In addition, soil pH explains a significant portion of the variability associated with observed changes in the phylogenetic structure within each dominant lineage. The overall phylogenetic diversity of the bacterial communities was also correlated with soil pH (R2 = 0.50), with peak diversity in soils with near-neutral pHs. Together, these results suggest that the structure of soil bacterial communities is predictable, to some degree, across larger spatial scales, and the effect of soil pH on bacterial community composition is evident at even relatively coarse levels of taxonomic resolution.

Soil bacterial and fungal communities across a pH gradient in an arable soil.

Abstract: Soils collected across a long-term liming experiment (pH 4.0-8.3), in which variation in factors other than pH have been minimized, were used to investigate the direct influence of pH on the abundance and composition of the two major soil microbial taxa, fungi and bacteria. We hypothesized that bacterial communities would be more strongly influenced by pH than fungal communities. To determine the relative abundance of bacteria and fungi, we used quantitative PCR (qPCR), and to analyze the composition and diversity of the bacterial and fungal communities, we used a bar-coded pyrosequencing technique. Both the relative abundance and diversity of bacteria were positively related to pH, the latter nearly doubling between pH 4 and 8. In contrast, the relative abundance of fungi was unaffected by pH and fungal diversity was only weakly related with pH. The composition of the bacterial communities was closely defined by soil pH; there was as much variability in bacterial community composition across the 180-m distance of this liming experiment as across soils collected from a wide range of biomes in North and South America, emphasizing the dominance of pH in structuring bacterial communities. The apparent direct influence of pH on bacterial community composition is probably due to the narrow pH ranges for optimal growth of bacteria. Fungal community composition was less strongly affected by pH, which is consistent with pure culture studies, demonstrating that fungi generally exhibit wider pH ranges for optimal growth.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

Next-Generation DNA Sequencing Methods

Abstract: Recent scientific discoveries that resulted from the application of nextgeneration DNA sequencing technologies highlight the striking impact of these massively parallel platforms on genetics. These new methods have expanded previously focused readouts from a variety of DNA preparation protocols to a genome-wide scale and have fine-tuned their resolution to single base precision. The sequencing of RNA also has transitioned and now includes full-length cDNA analyses, serial analysis of gene expression (SAGE)-based methods, and noncoding RNA discovery. Next-generation sequencing has also enabled novel applications such as the sequencing of ancient DNA samples, and has substantially widened the scope of metagenomic analysis of environmentally derived samples. Taken together, an astounding potential exists for these technologies to bring enormous change in genetic and biological research and to enhance our fundamental biological knowledge.