James C. Wallace

High-throughput localization of functional elements by quantitative chromatin profiling

Identification of functional, noncoding elements that regulate transcription in the context of complex genomes is a major goal of modern biology. Localization of functionality to specific sequences is a requirement for genetic and computational studies. Here, we describe a generic approach, quantitative chromatin profiling, that uses quantitative analysis of in vivo chromatin structure over entire gene loci to rapidly and precisely localize cis-regulatory sequences and other functional modalities encoded by DNase I hypersensitive sites. To demonstrate the accuracy of this approach, we analyzed ∼300 kilobases of human genome sequence from diverse gene loci and cleanly delineated functional elements corresponding to a spectrum of classical cis-regulatory activities including enhancers, promoters, locus control regions and insulators as well as novel elements. Systematic, high-throughput identification of functional elements coinciding with DNase I hypersensitive sites will substantially expand our knowledge of transcriptional regulation and should simplify the search for noncoding genetic variation with phenotypic consequences.

Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments

Background: High-throughput genomic technologies offer new approaches for environmental health monitoring, including metagenomic surveillance of antibiotic resistance determinants (ARDs). Although natural environments serve as reservoirs for antibiotic resistance genes that can be transferred to pathogenic and human commensal bacteria, monitoring of these determinants has been infrequent and incomplete. Furthermore, surveillance efforts have not been integrated into public health decision making. Objectives: We used a metagenomic epidemiology–based approach to develop an ARD index that quantifies antibiotic resistance potential, and we analyzed this index for common modal patterns across environmental samples. We also explored how metagenomic data such as this index could be conceptually framed within an early risk management context. Methods: We analyzed 25 published data sets from shotgun pyrosequencing projects. The samples consisted of microbial community DNA collected from marine and freshwater environments across a gradient of human impact. We used principal component analysis to identify index patterns across samples. Results: We observed significant differences in the overall index and index subcategory levels when comparing ecosystems more proximal versus distal to human impact. The selection of different sequence similarity thresholds strongly influenced the index measurements. Unique index subcategory modes distinguished the different metagenomes. Conclusions: Broad-scale screening of ARD potential using this index revealed utility for framing environmental health monitoring and surveillance. This approach holds promise as a screening tool for establishing baseline ARD levels that can be used to inform and prioritize decision making regarding management of ARD sources and human exposure routes. Citation: Port JA, Cullen AC, Wallace JC, Smith MN, Faustman EM. 2014. Metagenomic frameworks for monitoring antibiotic resistance in aquatic environments. Environ Health Perspect 122:222–228; http://dx.doi.org/10.1289/ehp.1307009

Determinants of conglomerate and predatory acquisitions: evidence from the 1960s

Abstract We estimate continuous-time event-history models of the acquisition of conglomerate vs. non-conglomerate and predatory vs. friendly acquisitions among the 1962 Fortune 500 between January, 1963, and December, 1968. Our analysis of predatory acquisitions reveals that there were strong disciplinary motivations for these acquisitions in the 1960s. Q ratios were, by a large margin, the most important determinant of predatory acquisition likelihood. Surprisingly, however, corporate boards appear to have provided little alternative to predatory acquisition as a monitoring mechanism during this period. Friendly acquisitions, on the other hand, were concentrated among firms with low price-earnings ratios and high return on equity, suggestive of the earnings manipulation story often associated with conglomerate acquisitions. Our analysis of conglomerate acquisitions reveals that there were strong disciplinary motivations for conglomerate acquisitions during this period. Conglomerate targets had low Q ratios and were as likely as non-conglomerate targets to be acquired in a predatory fashion. We find no evidence that conglomerate acquisitions were motivated by a desire to improve earnings-per-share numbers, as some have maintained. In addition, regardless of type or tenor, we find managerial ownership, firm size, and industrial organization motivations for acquisition are consistently important determinants of acquisition likelihood.

Metagenomic Profiling of Microbial Composition and Antibiotic Resistance Determinants in Puget Sound

Human-health relevant impacts on marine ecosystems are increasing on both spatial and temporal scales. Traditional indicators for environmental health monitoring and microbial risk assessment have relied primarily on single species analyses and have provided only limited spatial and temporal information. More high-throughput, broad-scale approaches to evaluate these impacts are therefore needed to provide a platform for informing public health. This study uses shotgun metagenomics to survey the taxonomic composition and antibiotic resistance determinant content of surface water bacterial communities in the Puget Sound estuary. Metagenomic DNA was collected at six sites in Puget Sound in addition to one wastewater treatment plant (WWTP) that discharges into the Sound and pyrosequenced. A total of ∼550 Mbp (1.4 million reads) were obtained, 22 Mbp of which could be assembled into contigs. While the taxonomic and resistance determinant profiles across the open Sound samples were similar, unique signatures were identified when comparing these profiles across the open Sound, a nearshore marina and WWTP effluent. The open Sound was dominated by α-Proteobacteria (in particular Rhodobacterales sp.), γ-Proteobacteria and Bacteroidetes while the marina and effluent had increased abundances of Actinobacteria, β-Proteobacteria and Firmicutes. There was a significant increase in the antibiotic resistance gene signal from the open Sound to marina to WWTP effluent, suggestive of a potential link to human impacts. Mobile genetic elements associated with environmental and pathogenic bacteria were also differentially abundant across the samples. This study is the first comparative metagenomic survey of Puget Sound and provides baseline data for further assessments of community composition and antibiotic resistance determinants in the environment using next generation sequencing technologies. In addition, these genomic signals of potential human impact can be used to guide initial public health monitoring as well as more targeted and functionally-based investigations.

Application of functional genomics to the chimeric mouse model of HCV infection: optimization of microarray protocols and genomics analysis.

BackgroundMany model systems of human viral disease involve human-mouse chimeric tissue. One such system is the recently developed SCID-beige/Alb-uPA mouse model of hepatitis C virus (HCV) infection which involves a human-mouse chimeric liver. The use of functional genomics to study HCV infection in these chimeric tissues is complicated by the potential cross-hybridization of mouse mRNA on human oligonucleotide microarrays. To identify genes affected by mouse liver mRNA hybridization, mRNA from identical human liver samples labeled with either Cy3 or Cy5 was compared in the presence and absence of known amounts of mouse liver mRNA labeled in only one dye.ResultsThe results indicate that hybridization of mouse mRNA to the corresponding human gene probe on Agilent Human 22 K oligonucleotide microarray does occur. The number of genes affected by such cross-hybridization was subsequently reduced to approximately 300 genes both by increasing the hybridization temperature and using liver samples which contain at least 80% human tissue. In addition, Real Time quantitative RT-PCR using human specific probes was shown to be a valid method to verify the expression level in human cells of known cross-hybridizing genes.ConclusionThe identification of genes affected by cross-hybridization of mouse liver RNA on human oligonucleotide microarrays makes it feasible to use functional genomics approaches to study the chimeric SCID-beige/Alb-uPA mouse model of HCV infection. This approach used to study cross-species hybridization on oligonucleotide microarrays can be adapted to other chimeric systems of viral disease to facilitate selective analysis of human gene expression.

Identification of G protein-coupled receptor signaling pathway proteins in marine diatoms using comparative genomics

BackgroundThe G protein-coupled receptor (GPCR) signaling pathway plays an essential role in signal transmission and response to external stimuli in mammalian cells. Protein components of this pathway have been characterized in plants and simpler eukaryotes such as yeast, but their presence and role in unicellular photosynthetic eukaryotes have not been determined. We use a comparative genomics approach using whole genome sequences and gene expression libraries of four diatoms (Pseudo-nitzschia multiseries, Thalassiosira pseudonana, Phaeodactylum tricornutum and Fragilariopsis cylindrus) to search for evidence of GPCR signaling pathway proteins that share sequence conservation to known GPCR pathway proteins.ResultsThe majority of the core components of GPCR signaling were well conserved in all four diatoms, with protein sequence similarity to GPCRs, human G protein α- and β-subunits and downstream effectors. There was evidence for the Gγ-subunit and thus a full heterotrimeric G protein only in T. pseudonana. Phylogenetic analysis of putative diatom GPCRs indicated similarity but deep divergence to the class C GPCRs, with branches basal to the GABAB receptor subfamily. The extracellular and intracellular regions of these putative diatom GPCR sequences exhibited large variation in sequence length, and seven of these sequences contained the necessary ligand binding domain for class C GPCR activation. Transcriptional data indicated that a number of the putative GPCR sequences are expressed in diatoms under various stress conditions in culture, and that many of the GPCR-activated signaling proteins, including the G protein, are also expressed.ConclusionsThe presence of sequences in all four diatoms that code for the proteins required for a functional mammalian GPCR pathway highlights the highly conserved nature of this pathway and suggests a complex signaling machinery related to environmental perception and response in these unicellular organisms. The lack of evidence for some GPCR pathway proteins in one or more of the diatoms, such as the Gγ-subunit, may be due to differences in genome completeness and genome coverage for the four diatoms. The high divergence of putative diatom GPCR sequences to known class C GPCRs suggests these sequences may represent another, potentially ancestral, subfamily of class C GPCRs.

Virology in the 21st century: finding function with functional genomics

When functional genomics first appeared on the scene, the ability to perform global gene expression and protein profiling was hailed as a revolutionary new way to study biologic systems, likely to result in dramatic new discoveries. As time has passed, DNA microarrays and mass spectrometry have been used to generate huge amounts of data, and databases are overflowing with information. But how well is functional genomics living up to its promises, and has all this data resulted in an improved understanding of biologic processes? This article puts forward a perspective on what is required to ensure that data generated by microarrays and mass spectrometry provide real insights into how genes and proteins function and how this relates to the host response to infection.

FARME DB: a functional antibiotic resistance element database

Antibiotic resistance (AR) is a major global public health threat but few resources exist that catalog AR genes outside of a clinical context. Current AR sequence databases are assembled almost exclusively from genomic sequences derived from clinical bacterial isolates and thus do not include many microbial sequences derived from environmental samples that confer resistance in functional metagenomic studies. These environmental metagenomic sequences often show little or no similarity to AR sequences from clinical isolates using standard classification criteria. In addition, existing AR databases provide no information about flanking sequences containing regulatory or mobile genetic elements. To help address this issue, we created an annotated database of DNA and protein sequences derived exclusively from environmental metagenomic sequences showing AR in laboratory experiments. Our Functional Antibiotic Resistant Metagenomic Element (FARME) database is a compilation of publically available DNA sequences and predicted protein sequences conferring AR as well as regulatory elements, mobile genetic elements and predicted proteins flanking antibiotic resistant genes. FARME is the first database to focus on functional metagenomic AR gene elements and provides a resource to better understand AR in the 99% of bacteria which cannot be cultured and the relationship between environmental AR sequences and antibiotic resistant genes derived from cultured isolates. Database URL: http://staff.washington.edu/jwallace/farme

Variability in metagenomic samples from the Puget Sound: Relationship to temporal and anthropogenic impacts

Whole-metagenome sequencing (WMS) has emerged as a powerful tool to assess potential public health risks in marine environments by measuring changes in microbial community structure and function in uncultured bacteria. In addition to monitoring public health risks such as antibiotic resistance determinants, it is essential to measure predictors of microbial variation in order to identify natural versus anthropogenic factors as well as to evaluate reproducibility of metagenomic measurements.This study expands our previous metagenomic characterization of Puget Sound by sampling new nearshore environments including the Duwamish River, an EPA superfund site, and the Hood Canal, an area characterized by highly variable oxygen levels. We also resampled a wastewater treatment plant, nearshore and open ocean sites introducing a longitudinal component measuring seasonal and locational variations and establishing metagenomics sampling reproducibility. Microbial composition from samples collected in the open sound were highly similar within the same season and location across different years, while nearshore samples revealed multi-fold seasonal variation in microbial composition and diversity. Comparisons with recently sequenced predominant marine bacterial genomes helped provide much greater species level taxonomic detail compared to our previous study. Antibiotic resistance determinants and pollution and detoxification indicators largely grouped by location showing minor seasonal differences. Metal resistance, oxidative stress and detoxification systems showed no increase in samples proximal to an EPA superfund site indicating a lack of ecosystem adaptation to anthropogenic impacts. Taxonomic analysis of common sewage influent families showed a surprising similarity between wastewater treatment plant and open sound samples suggesting a low-level but pervasive sewage influent signature in Puget Sound surface waters. Our study shows reproducibility of metagenomic data sampling in multiple Puget Sound locations while establishing baseline measurements of antibiotic resistance determinants, pollution and detoxification systems. Combining seasonal and longitudinal data across these locations provides a foundation for evaluating variation in future studies.

A Resource Management Tool for Public Health Continuity of Operations During Disasters

OBJECTIVE We developed and validated a user-centered information system to support the local planning of public health continuity of operations for the Community Health Services Division, Public Health - Seattle & King County, Washington. METHODS The Continuity of Operations Data Analysis (CODA) system was designed as a prototype developed using requirements identified through participatory design. CODA uses open-source software that links personnel contact and licensing information with needed skills and clinic locations for 821 employees at 14 public health clinics in Seattle and King County. Using a web-based interface, CODA can visualize locations of personnel in relationship to clinics to assist clinic managers in allocating public health personnel and resources under dynamic conditions. RESULTS Based on user input, the CODA prototype was designed as a low-cost, user-friendly system to inventory and manage public health resources. In emergency conditions, the system can run on a stand-alone battery-powered laptop computer. A formative evaluation by managers of multiple public health centers confirmed the prototype designs usefulness. Emergency management administrators also provided positive feedback about the system during a separate demonstration. CONCLUSIONS Validation of the CODA information design prototype by public health managers and emergency management administrators demonstrates the potential usefulness of building a resource management system using open-source technologies and participatory design principles.