Hilary G. Morrison

Microbial diversity in the deep sea and the underexplored “rare biosphere”

The evolution of marine microbes over billions of years predicts that the composition of microbial communities should be much greater than the published estimates of a few thousand distinct kinds of microbes per liter of seawater. By adopting a massively parallel tag sequencing strategy, we show that bacterial communities of deep water masses of the North Atlantic and diffuse flow hydrothermal vents are one to two orders of magnitude more complex than previously reported for any microbial environment. A relatively small number of different populations dominate all samples, but thousands of low-abundance populations account for most of the observed phylogenetic diversity. This “rare biosphere” is very ancient and may represent a nearly inexhaustible source of genomic innovation. Members of the rare biosphere are highly divergent from each other and, at different times in earths history, may have had a profound impact on shaping planetary processes.

Reproducible Community Dynamics of the Gastrointestinal Microbiota following Antibiotic Perturbation

ABSTRACT Shifts in microbial communities are implicated in the pathogenesis of a number of gastrointestinal diseases, but we have limited understanding of the mechanisms that lead to altered community structures. One difficulty with studying these mechanisms in human subjects is the inherent baseline variability of the microbiota in different individuals. In an effort to overcome this baseline variability, we employed a mouse model to control the host genotype, diet, and other possible influences on the microbiota. This allowed us to determine whether the indigenous microbiota in such mice had a stable baseline community structure and whether this community exhibited a consistent response following antibiotic administration. We employed a tag-sequencing strategy targeting the V6 hypervariable region of the bacterial small-subunit (16S) rRNA combined with massively parallel sequencing to determine the community structure of the gut microbiota. Inbred mice in a controlled environment harbored a reproducible baseline community that was significantly impacted by antibiotic administration. The ability of the gut microbial community to recover to baseline following the cessation of antibiotic administration differed according to the antibiotic regimen administered. Severe antibiotic pressure resulted in reproducible, long-lasting alterations in the gut microbial community, including a decrease in overall diversity. The finding of stereotypic responses of the indigenous microbiota to ecologic stress suggests that a better understanding of the factors that govern community structure could lead to strategies for the intentional manipulation of this ecosystem so as to preserve or restore a healthy microbiota.

Accuracy and quality of massively parallel DNA pyrosequencing

BackgroundMassively parallel pyrosequencing systems have increased the efficiency of DNA sequencing, although the published per-base accuracy of a Roche GS20 is only 96%. In genome projects, highly redundant consensus assemblies can compensate for sequencing errors. In contrast, studies of microbial diversity that catalogue differences between PCR amplicons of ribosomal RNA genes (rDNA) or other conserved gene families cannot take advantage of consensus assemblies to detect and minimize incorrect base calls.ResultsWe performed an empirical study of the per-base error rate for the Roche GS20 system using sequences of the V6 hypervariable region from cloned microbial ribosomal DNA (tag sequencing). We calculated a 99.5% accuracy rate in unassembled sequences, and identified several factors that can be used to remove a small percentage of low-quality reads, improving the accuracy to 99.75% or better.ConclusionBy using objective criteria to eliminate low quality data, the quality of individual GS20 sequence reads in molecular ecological applications can surpass the accuracy of traditional capillary methods.

Ironing out the wrinkles in the rare biosphere through improved OTU clustering.

Deep sequencing of PCR amplicon libraries facilitates the detection of low-abundance populations in environmental DNA surveys of complex microbial communities. At the same time, deep sequencing can lead to overestimates of microbial diversity through the generation of low-frequency, error-prone reads. Even with sequencing error rates below 0.005 per nucleotide position, the common method of generating operational taxonomic units (OTUs) by multiple sequence alignment and complete-linkage clustering significantly increases the number of predicted OTUs and inflates richness estimates. We show that a 2% single-linkage preclustering methodology followed by an average-linkage clustering based on pairwise alignments more accurately predicts expected OTUs in both single and pooled template preparations of known taxonomic composition. This new clustering method can reduce the OTU richness in environmental samples by as much as 30–60% but does not reduce the fraction of OTUs in long-tailed rank abundance curves that defines the rare biosphere.

Genomic Minimalism in the Early Diverging Intestinal Parasite Giardia lamblia

The genome of the eukaryotic protist Giardia lamblia, an important human intestinal parasite, is compact in structure and content, contains few introns or mitochondrial relics, and has simplified machinery for DNA replication, transcription, RNA processing, and most metabolic pathways. Protein kinases comprise the single largest protein class and reflect Giardias requirement for a complex signal transduction network for coordinating differentiation. Lateral gene transfer from bacterial and archaeal donors has shaped Giardias genome, and previously unknown gene families, for example, cysteine-rich structural proteins, have been discovered. Unexpectedly, the genome shows little evidence of heterozygosity, supporting recent speculations that this organism is sexual. This genome sequence will not only be valuable for investigating the evolution of eukaryotes, but will also be applied to the search for new therapeutics for this parasite.

Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition

We characterize and extend a highly efficient method for constructing shotgun fragment libraries in which transposase catalyzes in vitro DNA fragmentation and adaptor incorporation simultaneously. We apply this method to sequencing a human genome and find that coverage biases are comparable to those of conventional protocols. We also extend its capabilities by developing protocols for sub-nanogram library construction, exome capture from 50 ng of input DNA, PCR-free and colony PCR library construction, and 96-plex sample indexing.

Oligotyping: differentiating between closely related microbial taxa using 16S rRNA gene data

Bacteria comprise the most diverse domain of life on Earth, where they occupy nearly every possible ecological niche and play key roles in biological and chemical processes. Studying the composition and ecology of bacterial ecosystems and understanding their function are of prime importance. High-throughput sequencing technologies enable nearly comprehensive descriptions of bacterial diversity through 16S ribosomal RNA gene amplicons. Analyses of these communities generally rely upon taxonomic assignments through reference data bases or clustering approaches using de facto sequence similarity thresholds to identify operational taxonomic units. However, these methods often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial data sets. In this paper, we describe oligotyping, a novel supervised computational method that allows researchers to investigate the diversity of closely related but distinct bacterial organisms in final operational taxonomic units identified in environmental data sets through 16S ribosomal RNA gene data by the canonical approaches. Our analysis of two data sets from two different environments demonstrates the capacity of oligotyping at discriminating distinct microbial populations of ecological importance. Oligotyping can resolve the distribution of closely related organisms across environments and unveil previously overlooked ecological patterns for microbial communities. The URL http://oligotyping.org offers an open-source software pipeline for oligotyping.

Analysis, optimization and verification of Illumina-generated 16S rRNA gene amplicon surveys.

The exploration of microbial communities by sequencing 16S rRNA genes has expanded with low-cost, high-throughput sequencing instruments. Illumina-based 16S rRNA gene sequencing has recently gained popularity over 454 pyrosequencing due to its lower costs, higher accuracy and greater throughput. Although recent reports suggest that Illumina and 454 pyrosequencing provide similar beta diversity measures, it remains to be demonstrated that pre-existing 454 pyrosequencing workflows can transfer directly from 454 to Illumina MiSeq sequencing by simply changing the sequencing adapters of the primers. In this study, we modified 454 pyrosequencing primers targeting the V4-V5 hyper-variable regions of the 16S rRNA gene to be compatible with Illumina sequencers. Microbial communities from cows, humans, leeches, mice, sewage, and termites and a mock community were analyzed by 454 and MiSeq sequencing of the V4-V5 region and MiSeq sequencing of the V4 region. Our analysis revealed that reference-based OTU clustering alone introduced biases compared to de novo clustering, preventing certain taxa from being observed in some samples. Based on this we devised and recommend an analysis pipeline that includes read merging, contaminant filtering, and reference-based clustering followed by de novo OTU clustering, which produces diversity measures consistent with de novo OTU clustering analysis. Low levels of dataset contamination with Illumina sequencing were discovered that could affect analyses that require highly sensitive approaches. While moving to Illumina-based sequencing platforms promises to provide deeper insights into the breadth and function of microbial diversity, our results show that care must be taken to ensure that sequencing and processing artifacts do not obscure true microbial diversity.

Minimum entropy decomposition: Unsupervised oligotyping for sensitive partitioning of high-throughput marker gene sequences

Molecular microbial ecology investigations often employ large marker gene datasets, for example, ribosomal RNAs, to represent the occurrence of single-cell genomes in microbial communities. Massively parallel DNA sequencing technologies enable extensive surveys of marker gene libraries that sometimes include nearly identical sequences. Computational approaches that rely on pairwise sequence alignments for similarity assessment and de novo clustering with de facto similarity thresholds to partition high-throughput sequencing datasets constrain fine-scale resolution descriptions of microbial communities. Minimum Entropy Decomposition (MED) provides a computationally efficient means to partition marker gene datasets into ‘MED nodes’, which represent homogeneous operational taxonomic units. By employing Shannon entropy, MED uses only the information-rich nucleotide positions across reads and iteratively partitions large datasets while omitting stochastic variation. When applied to analyses of microbiomes from two deep-sea cryptic sponges Hexadella dedritifera and Hexadella cf. dedritifera, MED resolved a key Gammaproteobacteria cluster into multiple MED nodes that are specific to different sponges, and revealed that these closely related sympatric sponge species maintain distinct microbial communities. MED analysis of a previously published human oral microbiome dataset also revealed that taxa separated by less than 1% sequence variation distributed to distinct niches in the oral cavity. The information theory-guided decomposition process behind the MED algorithm enables sensitive discrimination of closely related organisms in marker gene amplicon datasets without relying on extensive computational heuristics and user supervision.

Serial Analysis of the Gut and Respiratory Microbiome in Cystic Fibrosis in Infancy: Interaction between Intestinal and Respiratory Tracts and Impact of Nutritional Exposures

ABSTRACT Pulmonary damage caused by chronic colonization of the cystic fibrosis (CF) lung by microbial communities is the proximal cause of respiratory failure. While there has been an effort to document the microbiome of the CF lung in pediatric and adult patients, little is known regarding the developing microflora in infants. We examined the respiratory and intestinal microbiota development in infants with CF from birth to 21 months. Distinct genera dominated in the gut compared to those in the respiratory tract, yet some bacteria overlapped, demonstrating a core microbiota dominated by Veillonella and Streptococcus. Bacterial diversity increased significantly over time, with evidence of more rapidly acquired diversity in the respiratory tract. There was a high degree of concordance between the bacteria that were increasing or decreasing over time in both compartments; in particular, a significant proportion (14/16 genera) increasing in the gut were also increasing in the respiratory tract. For 7 genera, gut colonization presages their appearance in the respiratory tract. Clustering analysis of respiratory samples indicated profiles of bacteria associated with breast-feeding, and for gut samples, introduction of solid foods even after adjustment for the time at which the sample was collected. Furthermore, changes in diet also result in altered respiratory microflora, suggesting a link between nutrition and development of microbial communities in the respiratory tract. Our findings suggest that nutritional factors and gut colonization patterns are determinants of the microbial development of respiratory tract microbiota in infants with CF and present opportunities for early intervention in CF with altered dietary or probiotic strategies. IMPORTANCE While efforts have been focused on assessing the microbiome of pediatric and adult cystic fibrosis (CF) patients to understand how chronic colonization by these microbes contributes to pulmonary damage, little is known regarding the earliest development of respiratory and gut microflora in infants with CF. Our findings suggest that colonization of the respiratory tract by microbes is presaged by colonization of the gut and demonstrated a role of nutrition in development of the respiratory microflora. Thus, targeted dietary or probiotic strategies may be an effective means to change the course of the colonization of the CF lung and thereby improve patient outcomes. While efforts have been focused on assessing the microbiome of pediatric and adult cystic fibrosis (CF) patients to understand how chronic colonization by these microbes contributes to pulmonary damage, little is known regarding the earliest development of respiratory and gut microflora in infants with CF. Our findings suggest that colonization of the respiratory tract by microbes is presaged by colonization of the gut and demonstrated a role of nutrition in development of the respiratory microflora. Thus, targeted dietary or probiotic strategies may be an effective means to change the course of the colonization of the CF lung and thereby improve patient outcomes.