Distribution and source assignments of polycyclic aromatic and aliphatic hydrocarbons in sediments and biota of the Lafayette River, VA.

The Lafayette River comprises a tidal sub-estuary constrained by an urban watershed that is bounded by residential areas at its upper reaches and port activity at its mouth. We determined the concentrations and distributions of polycyclic aromatic hydrocarbons (PAHs) and aliphatic n-alkanes across 19 sites from headwaters to river mouth in surface sediments (0-2 cm). Potential atmospheric sources were investigated through the analysis of wet and dry deposition samples and intact coals from a major export terminal nearby. The potential consequences for human consumption were examined through analysis of native oyster (Crassostrea virginica) and blue crab tissues (Callinectes sapidus). A suite of up to 66 parent and alkyl-substituted PAHs were detected in Lafayette sediments with total concentrations ranging from 0.75 to 39.00 µg g-1 dry wt. Concentrations of aliphatic n-alkanes (n-C16 - n-C31) ranged from 4.94 to 40.83 µg g-1 dry wt. Source assignment using diagnostic ratios and multivariate source analysis suggests multiple sources contribute to the hydrocarbon signature in this metropolitan system with automotive and atmospheric transport of coal dust as the major contributors. Oyster tissues showed similar trends as PAHs observed in sediments indicating similar sources to water column particles which ultimately accumulate in sediments with crabs showing altered distributions as a consequence of metabolism.

Nonlytic viral spread enhanced by autophagy components.

The cell-to-cell spread of cytoplasmic constituents such as nonenveloped viruses and aggregated proteins is usually thought to require cell lysis. However, mechanisms of unconventional secretion have been described that bypass the secretory pathway for the extracellular delivery of cytoplasmic molecules. Components of the autophagy pathway, an intracellular recycling process, have been shown to play a role in the unconventional secretion of cytoplasmic signaling proteins. Poliovirus is a lytic virus, although a few examples of apparently nonlytic spread have been documented. Real demonstration of nonlytic spread for poliovirus or any other cytoplasmic constituent thought to exit cells via unconventional secretion requires demonstration that a small amount of cell lysis in the cellular population is not responsible for the release of cytosolic material. Here, we use quantitative time-lapse microscopy to show the spread of infectious cytoplasmic material between cells in the absence of lysis. siRNA-mediated depletion of autophagy protein LC3 reduced nonlytic intercellular viral transfer. Conversely, pharmacological stimulation of the autophagy pathway caused more rapid viral spread in tissue culture and greater pathogenicity in mice. Thus, the unconventional secretion of infectious material in the absence of cell lysis is enabled by components of the autophagy pathway. It is likely that other nonenveloped viruses also use this pathway for nonlytic intercellular spread to affect pathogenesis in infected hosts.

Competing pathways control host resistance to virus via tRNA modification and programmed ribosomal frameshifting.

Viral infection depends on a complex interplay between host and viral factors. Here, we link host susceptibility to viral infection to a network encompassing sulfur metabolism, tRNA modification, competitive binding, and programmed ribosomal frameshifting (PRF). We first demonstrate that the iron-sulfur cluster biosynthesis pathway in Escherichia coli exerts a protective effect during lambda phage infection, while a tRNA thiolation pathway enhances viral infection. We show that tRNA(Lys) uridine 34 modification inhibits PRF to influence the ratio of lambda phage proteins gpG and gpGT. Computational modeling and experiments suggest that the role of the iron-sulfur cluster biosynthesis pathway in infection is indirect, via competitive binding of the shared sulfur donor IscS. Based on the universality of many key components of this network, in both the host and the virus, we anticipate that these findings may have broad relevance to understanding other infections, including viral infection of humans.

The virus as metabolic engineer.

Recent genome-wide screens of host genetic requirements for viral infection have reemphasized the critical role of host metabolism in enabling the production of viral particles. In this review, we highlight the metabolic aspects of viral infection found in these studies, and focus on the opportunities these requirements present for metabolic engineers. In particular, the objectives and approaches that metabolic engineers use are readily comparable to the behaviors exhibited by viruses during infection. As a result, metabolic engineers have a unique perspective that could lead to novel and effective methods to combat viral infection.

A forward-genetic screen and dynamic analysis of lambda phage host-dependencies reveals an extensive interaction network and a new anti-viral strategy.

Latently infecting viruses are an important class of virus that plays a key role in viral evolution and human health. Here we report a genome-scale forward-genetics screen for host-dependencies of the latently-infecting bacteriophage lambda. This screen identified 57 Escherichia coli (E. coli) genes--over half of which have not been previously associated with infection--that when knocked out inhibited lambda phage's ability to replicate. Our results demonstrate a highly integrated network between lambda and its host, in striking contrast to the results from a similar screen using the lytic-only infecting T7 virus. We then measured the growth of E. coli under normal and infected conditions, using wild-type and knockout strains deficient in one of the identified host genes, and found that genes from the same pathway often exhibited similar growth dynamics. This observation, combined with further computational and experimental analysis, led us to identify a previously unannotated gene, yneJ, as a novel regulator of lamB gene expression. A surprising result of this work was the identification of two highly conserved pathways involved in tRNA thiolation-one pathway is required for efficient lambda replication, while the other has anti-viral properties inhibiting lambda replication. Based on our data, it appears that 2-thiouridine modification of tRNAGlu, tRNAGln, and tRNALys is particularly important for the efficient production of infectious lambda phage particles.

A noisy paracrine signal determines the cellular NF-kappaB response to lipopolysaccharide.

Nearly identical cells can exhibit substantially different responses to the same stimulus. We monitored the nuclear localization dynamics of nuclear factor kappaB (NF-kappaB) in single cells stimulated with tumor necrosis factor-alpha (TNF-alpha) and lipopolysaccharide (LPS). Cells stimulated with TNF-alpha have quantitative differences in NF-kappaB nuclear localization, whereas LPS-stimulated cells can be clustered into transient or persistent responders, representing two qualitatively different groups based on the NF-kappaB response. These distinct behaviors can be linked to a secondary paracrine signal secreted at low concentrations, such that not all cells undergo a second round of NF-kappaB activation. From our single-cell data, we built a computational model that captures cell variability, as well as population behaviors. Our findings show that mammalian cells can create "noisy" environments to produce diversified responses to stimuli.

Genome-scale metabolic networks.

During the last decade, models have been developed to characterize cellular metabolism at the level of an entire metabolic network. The main concept that underlies whole-network metabolic modeling is the identification and mathematical definition of constraints. Here, we review large-scale metabolic network modeling, in particular, stoichiometric- and constraint-based approaches. Although many such models have been reconstructed, few networks have been extensively validated and tested experimentally, and we focus on these. We describe how metabolic networks can be represented using stoichiometric matrices and well-defined constraints on metabolic fluxes. We then discuss relatively successful approaches, including flux balance analysis (FBA), pathway analysis, and common extensions or modifications to these approaches. Finally, we describe techniques for integrating these approaches with models of other biological processes.

Genome-wide mapping of allele-specific protein-DNA interactions in human cells.

We describe a high-throughput method, named ChIP-SNP, for the identification of allele-specific protein-DNA interactions throughout the human genome. ChIP-SNP combines chromatin immunoprecipitation (ChIP) with whole-genome single nucleotide polymorphism (SNP) genotyping microarray analysis. We demonstrated that it can be used to accurately identify allele-specific binding of RNA polymerase II (RNAP) in the human fibroblast genome, uncovering imprinted genes and other allele-specific binding events. ChIP-SNP will facilitate the study of mechanisms of allele-specific gene expression.