Mary E. Singer

PCR Amplification-Independent Methods for Detection of Microbial Communities by the High-Density Microarray PhyloChip

ABSTRACT Environmental microbial community analysis typically involves amplification by PCR, despite well-documented biases. We have developed two methods of PCR-independent microbial community analysis using the high-density microarray PhyloChip: direct hybridization of 16S rRNA (dirRNA) or rRNA converted to double-stranded cDNA (dscDNA). We compared dirRNA and dscDNA communities to PCR-amplified DNA communities using a mock community of eight taxa, as well as experiments derived from three environmental sample types: chromium-contaminated aquifer groundwater, tropical forest soil, and secondary sewage in seawater. Community profiles by both direct hybridization methods showed differences that were expected based on accompanying data but that were missing in PCR-amplified communities. Taxon richness decreased in RNA compared to that in DNA communities, suggesting a subset of 20% in soil and 60% in groundwater that is active; secondary sewage showed no difference between active and inactive populations. Direct hybridization of dscDNA and RNA is thus a viable alternative to PCR-amplified microbial community analysis, providing identification of the active populations within microbial communities that attenuate pollutants, drive global biogeochemical cycles, or proliferate disease states.

Survey of large protein complexes in D. vulgaris reveals great structural diversity

An unbiased survey has been made of the stable, most abundant multi-protein complexes in Desulfovibrio vulgaris Hildenborough (DvH) that are larger than Mr ≈ 400 k. The quaternary structures for 8 of the 16 complexes purified during this work were determined by single-particle reconstruction of negatively stained specimens, a success rate ≈10 times greater than that of previous “proteomic” screens. In addition, the subunit compositions and stoichiometries of the remaining complexes were determined by biochemical methods. Our data show that the structures of only two of these large complexes, out of the 13 in this set that have recognizable functions, can be modeled with confidence based on the structures of known homologs. These results indicate that there is significantly greater variability in the way that homologous prokaryotic macromolecular complexes are assembled than has generally been appreciated. As a consequence, we suggest that relying solely on previously determined quaternary structures for homologous proteins may not be sufficient to properly understand their role in another cell of interest.

Clinical Experience With Intravenous Zanamivir Under an Emergency Investigational New Drug Program in the United States

TO THE EDITOR—We read the article by Fraaij et al [1] and would like to summarize the available information on intravenous zanamivir from the Food and Drug Administration (FDA)s Emergency Investigational New Drug (EIND) application process [2]. No intravenous an-tiviral agents for treatment of severe influenza are currently approved in the United States. Since the emergence of 2009 pandemic influenza A virus subtype H1N1 (A[H1N1]pdm09), intravenous zanamivir has been authorized through an EIND application to the FDA as an investigational treatment for patients with serious and life-threatening influenza. As part of the EIND process, treating physicians are encouraged to submit data to the FDA, but reporting of requested data is voluntary. We reviewed the FDAs EIND database on influenza patients who received intravenous zanamivir from April 2009 through April 2011. For the 200 patients identified, we performed a descriptive analysis of reported patient information on age, sex, pregnancy status, baseline comorbidities, virologic test results , antiviral resistance data, other antiviral treatments, clinical complications, supportive care modalities used, intravenous zanamivir treatment duration, adverse events (AEs), and outcomes (Table 1). At the time of intravenous zanamivir request, many patients were critically ill with underlying comorbidities and required intensive care unit admission for severe complications of influenza A virus infection (predominantly due to A[H1N1]pdm09), including respiratory failure and renal failure. Most patients

High-throughput Isolation and Characterization of Untagged Membrane Protein Complexes: Outer Membrane Complexes of Desulfovibrio vulgaris

Cell membranes represent the “front line” of cellular defense and the interface between a cell and its environment. To determine the range of proteins and protein complexes that are present in the cell membranes of a target organism, we have utilized a “tagless” process for the system-wide isolation and identification of native membrane protein complexes. As an initial subject for study, we have chosen the Gram-negative sulfate-reducing bacterium Desulfovibrio vulgaris. With this tagless methodology, we have identified about two-thirds of the outer membrane- associated proteins anticipated. Approximately three-fourths of these appear to form homomeric complexes. Statistical and machine-learning methods used to analyze data compiled over multiple experiments revealed networks of additional protein–protein interactions providing insight into heteromeric contacts made between proteins across this region of the cell. Taken together, these results establish a D. vulgaris outer membrane protein data set that will be essential for the detection and characterization of environment-driven changes in the outer membrane proteome and in the modeling of stress response pathways. The workflow utilized here should be effective for the global characterization of membrane protein complexes in a wide range of organisms.

Towards a Rigorous Network of Protein-Protein Interactions of the Model Sulfate Reducer Desulfovibrio vulgaris Hildenborough

Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study Escherichia coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio vulgaris Hildenborough, a model obligate anaerobe and sulfate reducer and the subject of this study. Here we carried out affinity purification followed by mass spectrometry to reconstruct an interaction network among 12 chromosomally encoded bait and 90 prey proteins based on 134 bait-prey interactions identified to be of high confidence. Protein-protein interaction data are often plagued by the lack of adequate controls and replication analyses necessary to assess confidence in the results, including identification of potential false positives. We addressed these issues through the use of biological replication, exponentially modified protein abundance indices, results from an experimental negative control, and a statistical test to assign confidence to each putative interacting pair applicable to small interaction data studies. We discuss the biological significance of metabolic features of D. vulgaris revealed by these protein-protein interaction data and the observed protein modifications. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

Generalized Schemes for High-Throughput Manipulation of the Desulfovibrio vulgaris Genome

ABSTRACT The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high-throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA “parts” to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications, including gene replacement and the creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.

Use of immunomagnetic separation for the detection of Desulfovibrio vulgaris from environmental samples

Immunomagnetic separation (IMS) has proved highly efficient for recovering microorganisms from heterogeneous samples. Current investigation targeted the separation of viable cells of the sulfate-reducing bacterium, Desulfovibrio vulgaris. Streptavidin-coupled paramagnetic beads and biotin labeled antibodies raised against surface antigens of this microorganism were used to capture D. vulgaris cells in both bioreactor grown laboratory samples and from extremely low-biomass environmental soil and subsurface drilling samples. Initial studies on detection, recovery efficiency and viability for IMS were performed with laboratory grown D. vulgaris cells using various cell densities. Efficiency of cell isolation and recovery (i.e., release of the microbial cells from the beads following separation) was followed by microscopic imaging and acridine orange direct counts (AODC). Excellent recovery efficiency encouraged the use of IMS to capture Desulfovibrio spp. cells from low-biomass environmental samples. The environmental samples were obtained from a radionuclide-contaminated site in Germany and the chromium (VI)-contaminated Hanford site, an ongoing bioremediation project of the U.S. Department of Energy. Field deployable IMS technology may greatly facilitate environmental sampling and bioremediation process monitoring and enable transcriptomics and proteomics/metabolomics-based studies directly on cells collected from the field.

Bacterial Interactomes: Interacting Protein Partners Share Similar Function and Are Validated in Independent Assays More Frequently Than Previously Reported

Numerous affinity purification-mass spectrometry (AP-MS) and yeast two-hybrid screens have each defined thousands of pairwise protein-protein interactions (PPIs), most of which are between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here, we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial yeast two-hybrid and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared with the nine published interactomes, our two networks are smaller, are much less highly connected, and have significantly lower false discovery rates. In addition, our interactomes are much more enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays than the pairs reported in prior studies. Our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification of endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.

Why did the FDA approve efavirenz 800 mg when co-administered with rifampin?

OBJECTIVES Literature reports regarding the efficacy of efavirenz (EFV) 600 mg with rifampin (RIF) are not consistent. Evaluation of a drug-drug interaction (DDI) study and supportive semi-mechanistic population pharmacokinetic (PK) analyses were undertaken to help delineate this issue. DESIGN/METHODS DDI study and supportive semi-mechanistic population PK analyses were provided by BMS. Population PK analysis was based on six studies with intensive EFV PK sampling. An ACTG study with sparse PK sampling was used for model evaluation. Simulations compared EFV exposure at various doses in combination with RIF to EFV exposures at 600 mg once daily (QD). Effects of CYP2B6 genotypes on the magnitude of EFV-RIF interaction were also explored. RESULTS In DDI study, co-administering EFV 600 mg QD and RIF reduced mean EFV exposure by ~ 30%. Population PK model provided acceptable predictive performance of central tendency and variability for EFV C0, Cmax, and AUC. Simulations predicted that increasing EFV to 800 mg QD with RIF would result in EFV AUC and Cmax similar to EFV 600 mg QD alone. EFV AUC and Cmax were ~ 2 times higher in subjects with reduced function CYP2B6 genotypes. However, the RIF effect was consistent across all genotypes. EFV dose adjustment to 800 mg QD did not increase the risk of overexposure compared to 600 mg EFV QD within each genotype. CONCLUSION Dose adjustment based on matching systemic exposure was recommended to mitigate the potential for sub-therapeutic EFV exposures. Our review did not reveal any safety concerns in subjects receiving EFV 800 mg QD with RIF.