Genetically distinct pathways guide effector export through the type VI secretion system

Bacterial secretion systems often employ molecular chaperones to recognize and facilitate export of their substrates. Recent work demonstrated that a secreted component of the type VI secretion system (T6SS), haemolysin co‐regulated protein (Hcp), binds directly to effectors, enhancing their stability in the bacterial cytoplasm. Herein, we describe a quantitative cellular proteomics screen for T6S substrates that exploits this chaperone‐like quality of Hcp. Application of this approach to the Hcp secretion island I‐encoded T6SS (H1‐T6SS) of Pseudomonas aeruginosa led to the identification of a novel effector protein, termed Tse4 (t ype VI s ecretion e xported 4), subsequently shown to act as a potent intra‐specific H1‐T6SS‐delivered antibacterial toxin. Interestingly, our screen failed to identify two predicted H1‐T6SS effectors, Tse5 and Tse6, which differ from Hcp‐stabilized substrates by the presence of toxin‐associated PAAR‐repeat motifs and genetic linkage to members of the valine‐glycine repeat protein G (vgrG) genes. Genetic studies further distinguished these two groups of effectors: Hcp‐stabilized effectors were found to display redundancy in interbacterial competition with respect to the requirement for the two H1‐T6SS‐exported VgrG proteins, whereas Tse5 and Tse6 delivery strictly required a cognate VgrG. Together, we propose that interaction with either VgrG or Hcp defines distinct pathways for T6S effector export.     

Population genomic variation reveals roles of history,adaptation and ploidy in switchgrass

Geographic patterns of genetic variation are shaped by multiple evolutionary processes, including genetic drift, migration and natural selection. Switchgrass (Panicum virgatum L.) has strong genetic and adaptive differentiation despite life history characteristics that promote high levels of gene flow and can homogenize intraspecific differences, such as wind‐pollination and self‐incompatibility. To better understand how historical and contemporary factors shape variation in switchgrass, we use genotyping‐by‐sequencing to characterize switchgrass from across its range at 98 042 SNPs. Population structuring reflects biogeographic and ploidy differences within and between switchgrass ecotypes and indicates that biogeographic history, ploidy incompatibilities and differential adaptation each have important roles in shaping ecotypic differentiation in switchgrass. At one extreme, we determine that two Panicum taxa are not separate species but are actually conspecific, ecologically divergent types of switchgrass adapted to the extreme conditions of coastal sand dune habitats. Conversely, we identify natural hybrids among lowland and upland ecotypes and visualize their genome‐wide patterns of admixture. Furthermore, we determine that genetic differentiation between primarily tetraploid and octoploid lineages is not caused solely by ploidy differences. Rather, genetic diversity in primarily octoploid lineages is consistent with a history of admixture. This suggests that polyploidy in switchgrass is promoted by admixture of diverged lineages, which may be important for maintaining genetic differentiation between switchgrass ecotypes where they are sympatric. These results provide new insights into the mechanisms shaping variation in widespread species and provide a foundation for dissecting the genetic basis of adaptation in switchgrass.     

Radiation-induced bystander effects in the Atlantic salmon (salmo salar L.) following mixed exposure to copper and aluminum combined with low-dose gamma radiation

Very little is known about the combined effects of low doses of heavy metals and radiation. However, such “multiple stressor” exposure is the reality in the environment. In the work reported in this paper, fish were exposed to cobalt 60 gamma irradiation with or without copper or aluminum in the water. Doses of radiation ranged from 4 to 75 mGy delivered over 48 or 6 h. Copper doses ranged from 10 to 80 μg/L for the same time period. The aluminum dose was 250 μg/L. Gills and skin were removed from the fish after exposure and explanted in tissue culture flasks for investigation of bystander effects of the exposures using a stress signal reporter assay, which has been demonstrated to be a sensitive indicator of homeostatic perturbations in cells. The results show complex synergistic interactions of radiation and copper. Gills on the whole produce more toxic bystander signals than skin, but the additivity scores show highly variable results which depend on dose and time of exposure. The impacts of low doses of copper and low doses of radiation are greater than additive, medium levels of copper alone have a similar level of effect of bystander signal toxicity to the low dose. The addition of radiation stress, however, produces clear protective effects in the reporters treated with skin-derived medium. Gill-derived medium from the same fish did not show protective effects. Radiation exposure in the presence of 80 μg/L led to highly variable results, which due to animal variation were not significantly different from the effect of copper alone. The results are stressor type, stressor concentration and time dependent. Clearly co-exposure to radiation and heavy metals does not always lead to simple additive effects.     

Heterogeneity of Pancreatic Cancer Metastases in a Single Patient Revealed by Quantitative Proteomics

Many patients with pancreatic cancer have metastases to distant organs at the time of initial presentation. Recent studies examining the evolution of pancreatic cancer at the genetic level have shown that clonal complexity of metastatic pancreatic cancer is already initiated within primary tumors, and organ-specific metastases are derived from different subclones. However, we do not yet understand to what extent the evolution of pancreatic cancer contributes to proteomic and signaling alterations. We hypothesized that genetic heterogeneity of metastatic pancreatic cancer results in heterogeneity at the proteome level. To address this, we employed a model system in which cells isolated from three sites of metastasis (liver, lung, and peritoneum) from a single patient were compared. We used a SILAC-based accurate quantitative proteomic strategy combined with high-resolution mass spectrometry to analyze the total proteome and tyrosine phosphoproteome of each of the distal metastases. Our data revealed distinct patterns of both overall proteome expression and tyrosine kinase activities across the three different metastatic lesions. This heterogeneity was significant because it led to differential sensitivity of the neoplastic cells to small molecule inhibitors targeting various kinases and other pathways. For example, R428, a tyrosine kinase inhibitor that targets Axl receptor tyrosine kinase, was able to inhibit cells derived from lung and liver metastases much more effectively than cells from the peritoneal metastasis. Finally, we confirmed that administration of R428 in mice bearing xenografts of cells derived from the three different metastatic sites significantly diminished tumors formed from liver- and lung-metastasis-derived cell lines as compared with tumors derived from the peritoneal metastasis cell line. Overall, our data provide proof-of-principle support that personalized therapy of multiple organ metastases in a single patient should involve the administration of a combination of agents, with each agent targeted to the features of different subclones.Approximately half of the patients with pancreatic cancer are initially diagnosed with metastases to distal sites, with the commonest sites being the liver, lung, and peritoneum (1). Therapeutic strategies against metastases could help reduce the high mortality rates associated with this cancer (2). Understanding the nature of metastatic pancreatic cancer at a systems level can enable the discovery of potential targets for the development of targeted therapies.Pancreatic cancer has been shown to be a genetically evolving and heterogeneous disease (3–5). Clonal diversity and evolution of cancer genomes have also been demonstrated based on the isolation of distinct clonal populations purified directly from patient biopsies by means of flow cytometry followed by genomic characterization (6). A number of reports have documented the adoption of a proteomic approach for the discovery of potential biomarkers in pancreatic cancer (7, 8). However, these studies generally assume pancreatic cancers to be homogeneous, and the emphasis is placed on identifying molecules that are common across a broad array of tumors. There is a lack of studies systematically examining the proteomic changes or signaling pathways across pancreatic cancers to dissect the nature of the heterogeneity of each clone. An excellent setting in which the heterogeneity of tumors can be studied systematically is in a patient harboring metastases to several distant sites. To this end, we chose cells isolated from three metastatic pancreatic lesions of a single patient. The exomes of each tumor site were previously sequenced to study the progression of pancreatic cancer, and the results showed that all cell lines were identical for the genetic status of driver mutations (e.g. KRAS, TP53, and SMAD4) (9). Our hypothesis was that a better understanding of the proteomic consequences of the heterogeneity derived from genetic changes, and possibly other types of alterations, might provide additional opportunities to identify therapeutic targets.In order to precisely quantify differences across the proteomes of multiple metastatic pancreatic cancer lesions, we employed a SILAC-based¹ quantitative proteomics strategy combined with high-resolution mass spectrometry (10, 11). Based on changes observed at the whole-proteome level, we found that a class of cell surface receptors showed significant enrichment with the highest alteration of their expression among the three metastatic pancreatic cancer cell lines examined (i.e. peritoneum, lung, and liver). Because the total protein levels provide information about the static levels of proteins and not their activity per se, we decided to examine the activation of phosphorylation-driven pathways, many of which are activated by cell surface receptors. To globally examine tyrosine phosphorylation-based signaling pathways, we carried out mass spectrometric analysis of purified tyrosine phosphorylated peptides enriched using anti-phosphotyrosine antibodies. As a result, we observed differential activation of tyrosine kinases in the three different sites of metastases. For example, Axl receptor tyrosine kinase was found to be hyperphosphorylated in lung and liver metastases relative to peritoneal metastasis. Expression of Axl receptor tyrosine kinase in primary and matched pancreatic cancers on tissue microarrays was validated by immunohistochemistry. Given such unique patterns of activation of pathways, it was possible that tumors derived from different sites could show differences in their sensitivity to pathway inhibitors. To test this, we performed experiments in which we screened cell lines derived from each metastatic site against a panel of small molecule inhibitors. We observed that the three metastatic pancreatic cancers had differential sensitivities to different inhibitors. For example, cells derived from the peritoneal metastasis were highly sensitive to lapatinib, whereas greater sensitivity to the Axl inhibitor R428 was observed in the lung metastasis cell line. Finally, we showed that treatment of mice bearing xenografts from these different pancreatic cancer cell lines with R428, an inhibitor of Axl receptor tyrosine kinase, led to reduction of tumors with evidence of activation of Axl.     

Adaptive Evolution and Environmental Durability Jointly Structure Phylodynamic Patterns in Avian Influenza Viruses

Avian influenza viruses (AIVs) have been pivotal to the origination of human pandemic strains. Despite their scientific and public health significance, however, there remains much to be understood about the ecology and evolution of AIVs in wild birds, where major pools of genetic diversity are generated and maintained. Here, we present comparative phylodynamic analyses of human and AIVs in North America, demonstrating (i) significantly higher standing genetic diversity and (ii) phylogenetic trees with a weaker signature of immune escape in AIVs than in human viruses. To explain these differences, we performed statistical analyses to quantify the relative contribution of several potential explanations. We found that HA genetic diversity in avian viruses is determined by a combination of factors, predominantly subtype-specific differences in host immune selective pressure and the ecology of transmission (in particular, the durability of subtypes in aquatic environments). Extending this analysis using a computational model demonstrated that virus durability may lead to long-term, indirect chains of transmission that, when coupled with a short host lifespan, can generate and maintain the observed high levels of genetic diversity. Further evidence in support of this novel finding was found by demonstrating an association between subtype-specific environmental durability and predicted phylogenetic signatures: genetic diversity, variation in phylogenetic tree branch lengths, and tree height. The conclusion that environmental transmission plays an important role in the evolutionary biology of avian influenza viruses—a manifestation of the “storage effect”—highlights the potentially unpredictable impact of wildlife reservoirs for future human pandemics and the need for improved understanding of the natural ecology of these viruses.     

ARTIST: High-Resolution Genome-Wide Assessment of Fitness Using Transposon-Insertion Sequencing

Transposon-insertion sequencing (TIS) is a powerful approach for deciphering genetic requirements for bacterial growth in different conditions, as it enables simultaneous genome-wide analysis of the fitness of thousands of mutants. However, current methods for comparative analysis of TIS data do not adjust for stochastic experimental variation between datasets and are limited to interrogation of annotated genomic elements. Here, we present ARTIST, an accessible TIS analysis pipeline for identifying essential regions that are required for growth under optimal conditions as well as conditionally essential loci that participate in survival only under specific conditions. ARTIST uses simulation-based normalization to model and compensate for experimental noise, and thereby enhances the statistical power in conditional TIS analyses. ARTIST also employs a novel adaptation of the hidden Markov model to generate statistically robust, high-resolution, annotation-independent maps of fitness-linked loci across the entire genome. Using ARTIST, we sensitively and comprehensively define Mycobacterium tuberculosis and Vibrio cholerae loci required for host infection while limiting inclusion of false positive loci. ARTIST is applicable to a broad range of organisms and will facilitate TIS-based dissection of pathways required for microbial growth and survival under a multitude of conditions.