Biomedical subjects

Patrick D Schloss

Publications and source records attributed to Patrick D Schloss.

13 recordsLinked to original sources

PubMed2006

What is the extent of prokaryotic diversity?

The extent of microbial diversity is an intrinsically fascinating subject of profound practical importance. The term 'diversity' may allude to the number of taxa or species richness as well as their relative abundance. There is uncertainty about both, primarily because sample sizes are too small. Non-parametric diversity estimators make gross underestimates if used with small sample sizes on unevenly distributed communities. One can make richness estimates over many scales using small samples by assuming a species/taxa-abundance distribution. However, no one knows what the underlying taxa-abundance distributions are for bacterial communities. Latterly, diversity has been estimated by fitting data from gene clone libraries and extrapolating from this to taxa-abundance curves to estimate richness. However, since sample sizes are small, we cannot be sure that such samples are representative of the community from which they were drawn. It is however possible to formulate, and calibrate, models that predict the diversity of local communities and of samples drawn from that local community. The calibration of such models suggests that migration rates are small and decrease as the community gets larger. The preliminary predictions of the model are qualitatively consistent with the patterns seen in clone libraries in 'real life'. The validation of this model is also confounded by small sample sizes. However, if such models were properly validated, they could form invaluable tools for the prediction of microbial diversity and a basis for the systematic exploration of microbial diversity on the planet.

Archaea↗

PubMed2006

Toward a census of bacteria in soil.

For more than a century, microbiologists have sought to determine the species richness of bacteria in soil, but the extreme complexity and unknown structure of soil microbial communities have obscured the answer. We developed a statistical model that makes the problem of estimating richness statistically accessible by evaluating the characteristics of samples drawn from simulated communities with parametric community distributions. We identified simulated communities with rank-abundance distributions that followed a truncated lognormal distribution whose samples resembled the structure of 16S rRNA gene sequence collections made using Alaskan and Minnesotan soils. The simulated communities constructed based on the distribution of 16S rRNA gene sequences sampled from the Alaskan and Minnesotan soils had a richness of 5,000 and 2,000 operational taxonomic units (OTUs), respectively, where an OTU represents a collection of sequences not more than 3% distant from each other. To sample each of these OTUs in the Alaskan 16S rRNA gene library at least twice, 480,000 sequences would be required; however, to estimate the richness of the simulated communities using nonparametric richness estimators would require only 18,000 sequences. Quantifying the richness of complex environments such as soil is an important step in building an ecological framework. We have shown that generating sufficient sequence data to do so requires less sequencing effort than completely sequencing a bacterial genome.

Alaska↗

PubMed2006

Introducing SONS, a tool for operational taxonomic unit-based comparisons of microbial community memberships and structures.

The recent advent of tools enabling statistical inferences to be drawn from comparisons of microbial communities has enabled the focus of microbial ecology to move from characterizing biodiversity to describing the distribution of that biodiversity. Although statistical tools have been developed to compare community structures across a phylogenetic tree, we lack tools to compare the memberships and structures of two communities at a particular operational taxonomic unit (OTU) definition. Furthermore, current tests of community structure do not indicate the similarity of the communities but only report the probability of a statistical hypothesis. Here we present a computer program, SONS, which implements nonparametric estimators for the fraction and richness of OTUs shared between two communities.

Biodiversity↗

PubMed2006

Introducing TreeClimber, a test to compare microbial community structures.

The phylogenetic and ecological complexity of microbial communities necessitates the development of new methods to determine whether two or more communities have the same structure even though it is not possible to sample the communities exhaustively. To address this need, we adapted a method used in population genetics, the parsimony test, to determine the relatedness of communities. Here we describe our implementation of the parsimony test, TreeClimber, in which we reanalyzed six previously published studies and compared the results of the analysis to those obtained using integral-LIBSHUFF.

Algorithms↗

PubMed2005

Metagenomics for studying unculturable microorganisms: cutting the Gordian knot.

More than 99% of prokaryotes in the environment cannot be cultured in the laboratory, a phenomenon that limits our understanding of microbial physiology, genetics, and community ecology. One way around this problem is metagenomics, the culture-independent cloning and analysis of microbial DNA extracted directly from an environmental sample. Recent advances in shotgun sequencing and computational methods for genome assembly have advanced the field of metagenomics to provide glimpses into the life of uncultured microorganisms.

Genetics, Microbial↗

PubMed2005

Molecular characterization of fungal community dynamics in the initial stages of composting.

Composting relies on a complex network of bacteria and fungi to process crude organic material. Although it is known that these organisms drive dynamic changes in temperature and pH, little is known about the temporal dynamics of fungal populations during the rise to thermophilic conditions. This study employed F-ARISA (fungal-automated rRNA intergenic spacer analysis) and 18S rRNA gene cloning and sequencing to examine changes in community structure during this period. Sequencing of the 18S rRNA portion of cloned F-ARISA products revealed the presence of four distinct fungal genera including Backusella sp., Mucoraceae, Geotrichum sp. and the yeast Pichia sp. Based on the presence and absence of these ARISA operational taxonomic units (A-OTUs), we observed a shift in fungal community structure between 48 and 60 h. This change in community structure preceded a rise in pH and coincided with an increase in temperature. Clone libraries constructed using fungi-specific 18S rRNA primers contained sequences similar to several other fungal genera including Penicillium sp., Aspergillus sp., Hamigera sp., Neurospora sp. and the yeast Candida sp. While the fungal species richness was relatively low at any time point, the community structure was dynamic and paralleled changes in bacterial community structure.

Fungi↗

PubMed2005

Intracellular screen to identify metagenomic clones that induce or inhibit a quorum-sensing biosensor.

The goal of this study was to design and evaluate a rapid screen to identify metagenomic clones that produce biologically active small molecules. We built metagenomic libraries with DNA from soil on the floodplain of the Tanana River in Alaska. We extracted DNA directly from the soil and cloned it into fosmid and bacterial artificial chromosome vectors, constructing eight metagenomic libraries that contain 53,000 clones with inserts ranging from 1 to 190 kb. To identify clones of interest, we designed a high throughput "intracellular" screen, designated METREX, in which metagenomic DNA is in a host cell containing a biosensor for compounds that induce bacterial quorum sensing. If the metagenomic clone produces a quorum-sensing inducer, the cell produces green fluorescent protein (GFP) and can be identified by fluorescence microscopy or captured by fluorescence-activated cell sorting. Our initial screen identified 11 clones that induce and two that inhibit expression of GFP. The intracellular screen detected quorum-sensing inducers among metagenomic clones that a traditional overlay screen would not. One inducing clone carries a LuxI homologue that directs the synthesis of an N-acyl homoserine lactone quorum-sensing signal molecule. The LuxI homologue has 62% amino acid sequence identity to its closest match in GenBank, AmfI from Pseudomonas fluorescens, and is on a 78-kb insert that contains 67 open reading frames. Another inducing clone carries a gene with homology to homocitrate synthase. Our results demonstrate the power of an intracellular screen to identify functionally active clones and biologically active small molecules in metagenomic libraries.

Alaska↗

PubMed2005

Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness.

Although copious qualitative information describes the members of the diverse microbial communities on Earth, statistical approaches for quantifying and comparing the numbers and compositions of lineages in communities are lacking. We present a method that addresses the challenge of assigning sequences to operational taxonomic units (OTUs) based on the genetic distances between sequences. We developed a computer program, DOTUR, which assigns sequences to OTUs by using either the furthest, average, or nearest neighbor algorithm for each distance level. DOTUR uses the frequency at which each OTU is observed to construct rarefaction and collector's curves for various measures of richness and diversity. We analyzed 16S rRNA gene libraries derived from Scottish and Amazonian soils and the Sargasso Sea with DOTUR, which assigned sequences to OTUs rapidly and reliably based on the genetic distances between sequences and identified previous inconsistencies and errors in assigning sequences to OTUs. An analysis of the two 16S rRNA gene libraries from soil demonstrated that they do not contain enough sequences to support a claim that they contain different numbers of bacterial lineages with statistical confidence (P > 0.05), nor do they contain enough sequences to provide a robust estimate of species richness when an OTU is defined as containing sequences that are no more than 3% different from each other. In contrast, the richness of OTUs at the 3% level in the Sargasso Sea collection began to plateau after the sampling of 690 sequences. We anticipate that an equivalent extent of sampling for soil would require sampling more than 10,000 sequences, almost 100 times the size of typical sequence collections obtained from soil.

Algorithms↗

PubMed2004

Quantifying bacterial population dynamics in compost using 16S rRNA gene probes.

Composting provides a dynamic setting for studying ecological topics such as succession, competition, and community stability in a relatively short period of time. This study used hierarchical small sub-unit-based rRNA gene probes to quantify the change in the relative abundance of phylogenetic groups common to compost in laboratory scale reactors. Bacterial 16S rRNA gene targets accounted for only 37% of all small subunit (SSU) rRNA genes initially, but increased to a maximum of 83% of the total at 84 h. The sum of rRNA genes detected using probes specific to Pseudomonas and low-G+C Gram-positive rRNA genes represented between 16% and 87% of the total. The lack of hybridization to the taxon-specific probes was most pronounced between 36 h and 60 h, when the pH was between 4.6 and 4.8. During this period the relative abundance of taxon-specific gene targets accounted for only 17-33% of the total bacterial rRNA gene targets. Pseudomonas-type 16S rRNA genes were the most abundant of the groups measured until 72 h. Those genes had their highest relative abundance at 12 h (78% of bacterial rRNA genes; 30% of all rRNA genes), after which time their relative abundance began to decline as the temperature increased. Prior to 72 h, 16S rRNA genes from low-G+C Gram-positive bacteria (LGC-GPB) represented less than 7% of the bacterial rRNA genes. However, by 84 h the relative abundance of LGC-GPB and Bacillus rRNA genes had increased to 60% and 18% of the bacterial rRNA gene targets, respectively (50% and 15% of all rRNA genes, respectively).

Base Composition↗

PubMed2004

Integration of microbial ecology and statistics: a test to compare gene libraries.

Libraries of 16S rRNA genes provide insight into the membership of microbial communities. Statistical methods help to determine whether differences in library composition are artifacts of sampling or are due to underlying differences in the communities from which they are derived. To contribute to a growing statistical framework for comparing 16S rRNA libraries, we present a computer program, integral -LIBSHUFF, which calculates the integral form of the Cramér-von Mises statistic. This implementation builds upon the LIBSHUFF program, which uses an approximation of the statistic and makes a number of modifications that improve precision and accuracy. Once integral -LIBSHUFF calculates the P values, when pairwise comparisons are tested at the 0.05 level, the probability of falsely identifying a significant P value is 0.098 for a study with two libraries, 0.265 for three libraries, and 0.460 for four libraries. The potential negative effects of making the multiple pairwise comparisons necessitate correcting for the increased likelihood that differences between treatments are due to chance and do not reflect biological differences. Using integral -LIBSHUFF, we found that previously published 16S rRNA gene libraries constructed from Scottish and Wisconsin soils contained different bacterial lineages. We also analyzed the published libraries constructed for the zebrafish gut microflora and found statistically significant changes in the community during development of the host. These analyses illustrate the power of integral -LIBSHUFF to detect differences between communities, providing the basis for ecological inference about the association of soil productivity or host gene expression and microbial community composition.

Aeromonas↗

PubMed2004

Status of the microbial census.

Over the past 20 years, more than 78,000 16S rRNA gene sequences have been deposited in GenBank and the Ribosomal Database Project, making the 16S rRNA gene the most widely studied gene for reconstructing bacterial phylogeny. While there is a general appreciation that these sequences are largely unique and derived from diverse species of bacteria, there has not been a quantitative attempt to describe the extent of sequencing efforts to date. We constructed rarefaction curves for each bacterial phylum and for the entire bacterial domain to assess the current state of sampling and the relative taxonomic richness of each phylum. This analysis quantifies the general sense among microbiologists that we are a long way from a complete census of the bacteria on Earth. Moreover, the analysis indicates that current sampling strategies might not be the most effective ones to describe novel diversity because there remain numerous phyla that are globally distributed yet poorly sampled. Based on the current level of sampling, it is not possible to estimate the total number of bacterial species on Earth, but the minimum species richness is 35,498. Considering previous global species richness estimates of 10(7) to 10(9), we are certain that this estimate will increase with additional sequencing efforts. The data support previous calls for extensive surveys of multiple chemically disparate environments and of specific phylogenetic groups to advance the census most rapidly.

Bacteria↗

PubMed2004

Metagenomics: genomic analysis of microbial communities.

Uncultured microorganisms comprise the majority of the planet's biological diversity. Microorganisms represent two of the three domains of life and contain vast diversity that is the product of an estimated 3.8 billion years of evolution. In many environments, as many as 99% of the microorganisms cannot be cultured by standard techniques, and the uncultured fraction includes diverse organisms that are only distantly related to the cultured ones. Therefore, culture-independent methods are essential to understand the genetic diversity, population structure, and ecological roles of the majority of microorganisms. Metagenomics, or the culture-independent genomic analysis of an assemblage of microorganisms, has potential to answer fundamental questions in microbial ecology. This review describes progress toward understanding the biology of uncultured Bacteria, Archaea, and viruses through metagenomic analyses.

Archaea↗

PubMed2003

Biotechnological prospects from metagenomics.

The recognition that most microorganisms in the environment cannot be cultured by standard methods stimulated the development of metagenomics, which is the genomic analysis of uncultured microorganisms. Two types of analysis have been used to obtain information from metagenomic libraries: a function-driven approach, in which metagenomic libraries are initially screened for an expressed trait, and a sequence-driven approach, in which libraries are initially screened for particular DNA sequences. New antibiotics and enzymes are among the early discoveries from metagenomics. Future refinement of methods that enrich for genes of particular function will accelerate the rate of discovery of useful molecules.

Bacterial Proteins↗