A novel uncultured marine cyanophage lineage with lysogenic potential linked to a putative marine Synechococcus 'relic' prophage

Marine cyanobacteria are important contributors to primary production in the ocean and their viruses (cyanophages) affect the ocean microbial communities. Despite reports of lysogeny in marine cyanobacteria, a genome sequence of such temperate cyanophages remains unknown although genomic analysis indicate potential for lysogeny in certain marine cyanophages. Using assemblies from Red Sea and Tara Oceans metagenomes, we recovered genomes of a novel uncultured marine cyanophage lineage, which contain, in addition to common cyanophage genes, a phycobilisome degradation protein NblA, an integrase and a split DNA polymerase. The DNA polymerase forms a monophyletic clade with a DNA polymerase from a genomic island in Synechococcus WH8016. The island contains a relic prophage that does not resemble any previously reported cyanophage but shares several genes with the newly identified cyanophages reported here. Metagenomic recruitment indicates that the novel cyanophages are widespread, albeit at low abundance. Here, we describe a novel potentially lysogenic cyanophage family, their abundance and distribution in the marine environment

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors

Background: The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-based inference, model-based inference allows for regional estimates of totals and means, but in addition for wall-to-wall mapping of forest characteristics. Recently Light Detection and Ranging (LiDAR)-based maps of forest attributes have been developed in many countries and been well received by users due to their accurate spatial representation of forest resources. However, the correspondence between such mapping and model-based inference is seldom appreciated. In this study we applied hierarchical model-based inference to produce aboveground biomass maps as well as maps of the corresponding prediction uncertainties with the same spatial resolution. Further, an estimator of mean biomass at regional level, and its uncertainty, was developed to demonstrate how mapping and regional level assessment can be combined within the framework of model-based inference. Results: Through a new version of hierarchical model-based estimation, allowing models to be nonlinear, we accounted for uncertainties in both the individual tree-level biomass models and the models linking plot level biomass predictions with LiDAR metrics. In a 5005 km(2)large study area in south-central Sweden the predicted aboveground biomass at the level of 18 m x18 m map units was found to range between 9 and 447 Mg center dot ha(-1). The corresponding root mean square errors ranged between 10 and 162 Mg center dot ha(-1). For the entire study region, the mean aboveground biomass was 55 Mg center dot ha(-1)and the corresponding relative root mean square error 8%. At this level 75% of the mean square error was due to the uncertainty associated with tree-level models. Conclusions: Through the proposed method it is possible to link mapping and estimation within the framework of model-based inference. Uncertainties in both tree-level biomass models and models linking plot level biomass with LiDAR data are accounted for, both for the uncertainty maps and the overall estimates. The development of hierarchical model-based inference to handle nonlinear models was an important prerequisite for the study

A myovirus encoding both photosystem I and II proteins enhances cyclic electron flow in infected Prochlorococcus cells

Fridman, Svetlana ... et al.-- This is contribution number 54 of Tara Oceans.-- 8 pages, 4 figures, supplementary material https://dx.doi.org/10.1038/s41564-017-0002-9Cyanobacteria are important contributors to primary production in the open oceans. Over the past decade, various photosynthesis-related genes have been found in viruses that infect cyanobacteria (cyanophages). Although photosystem II (PSII) genes are common in both cultured cyanophages and environmental samples , viral photosystem I (vPSI) genes have so far only been detected in environmental samples . Here, we have used a targeted strategy to isolate a cyanophage from the tropical Pacific Ocean that carries a PSI gene cassette with seven distinct PSI genes (psaJF, C, A, B, K, E, D) as well as two PSII genes (psbA, D). This cyanophage, P-TIM68, belongs to the T4-like myoviruses, has a prolate capsid, a long contractile tail and infects Prochlorococcus sp. strain MIT9515. Phage photosynthesis genes from both photosystems are expressed during infection, and the resultant proteins are incorporated into membranes of the infected host. Moreover, photosynthetic capacity in the cell is maintained throughout the infection cycle with enhancement of cyclic electron flow around PSI. Analysis of metagenomic data from the Tara Oceans expedition shows that phages carrying PSI gene cassettes are abundant in the tropical Pacific Ocean, composing up to 28% of T4-like cyanomyophages. They are also present in the tropical Indian and Atlantic Oceans. P-TIM68 populations, specifically, compose on average 22% of the PSI-gene-cassette carrying phages. Our results suggest that cyanophages carrying PSI and PSII genes are likely to maintain and even manipulate photosynthesis during infection of their Prochlorococcus hosts in the tropical oceansThis work was funded by a European Commission ERC Advanced Grant (no. 321647), the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013/ under REA Grant Agreement No. 317184, an Israel Science Foundation grant (no. 580/10) and the Louis and Lyra Richmond Memorial Chair in Life Sciences to O.B., a European Commission ERC starting grant (no. 203406) to D.L. and the Technion’s Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering and the Russell Berrie Nanotechnology Institute.Peer Reviewe

Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors

Abstract Background The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-based inference, model-based inference allows for regional estimates of totals and means, but in addition for wall-to-wall mapping of forest characteristics. Recently Light Detection and Ranging (LiDAR)-based maps of forest attributes have been developed in many countries and been well received by users due to their accurate spatial representation of forest resources. However, the correspondence between such mapping and model-based inference is seldom appreciated. In this study we applied hierarchical model-based inference to produce aboveground biomass maps as well as maps of the corresponding prediction uncertainties with the same spatial resolution. Further, an estimator of mean biomass at regional level, and its uncertainty, was developed to demonstrate how mapping and regional level assessment can be combined within the framework of model-based inference. Results Through a new version of hierarchical model-based estimation, allowing models to be nonlinear, we accounted for uncertainties in both the individual tree-level biomass models and the models linking plot level biomass predictions with LiDAR metrics. In a 5005 km2 large study area in south-central Sweden the predicted aboveground biomass at the level of 18 m ×18 m map units was found to range between 9 and 447 Mg ·ha −1. The corresponding root mean square errors ranged between 10 and 162 Mg ·ha −1. For the entire study region, the mean aboveground biomass was 55 Mg ·ha −1 and the corresponding relative root mean square error 8%. At this level 75% of the mean square error was due to the uncertainty associated with tree-level models. Conclusions Through the proposed method it is possible to link mapping and estimation within the framework of model-based inference. Uncertainties in both tree-level biomass models and models linking plot level biomass with LiDAR data are accounted for, both for the uncertainty maps and the overall estimates. The development of hierarchical model-based inference to handle nonlinear models was an important prerequisite for the study

Long Noncoding RNA GAS5 in Breast Cancer: Epigenetic Mechanisms and Biological Functions

Long noncoding RNAs (lncRNAs) have been identified as contributors to the development and progression of cancer through various functions and mechanisms. LncRNA GAS5 is downregulated in multiple cancers and acts as a tumor suppressor in breast cancer. GAS5 interacts with various proteins (e.g., E2F1, EZH2, and YAP), DNA (e.g., the insulin receptor promoter), and various microRNAs (miRNAs). In breast cancer, GAS5 binds with miR-21, miR-222, miR-221-3p, miR-196a-5p, and miR-378a-5p that indicates the presence of several elements for miRNA binding (MREs) in GAS5. Mediated by the listed miRNAs, GAS5 is involved in the upregulation of a number of mRNAs of suppressor proteins such as PTEN, PDCD4, DKK2, FOXO1, and SUFU. Furthermore, the aberrant promoter methylation is involved in the regulation of GAS5 gene expression in triple-negative breast cancer and some other carcinomas. GAS5 can stimulate apoptosis in breast cancer via diverse pathways, including cell death receptors and mitochondrial signaling pathways. GAS5 is also a key player in the regulation of some crucial signal pathways in breast cancer, such as PI3K/AKT/mTOR, Wnt/β-catenin, and NF-κB signaling. Through epigenetic and other mechanisms, GAS5 can increase sensitivity to multiple drugs and improve prognosis. GAS5 is thus a promising target in the treatment of breast cancer patients

Major Oncogenic Drivers and Their Clinicopathological Correlations in Sporadic Childhood Papillary Thyroid Carcinoma in Belarus

Childhood papillary thyroid carcinoma (PTC) diagnosed after the Chernobyl accident in Belarus displayed a high frequency of gene rearrangements and low frequency of point mutations. Since 2001, only sporadic thyroid cancer occurs in children aged up to 14 years but its molecular characteristics have not been reported. Here, we determine the major oncogenic events in PTC from non-exposed Belarusian children and assess their clinicopathological correlations. Among the 34 tumors, 23 (67.6%) harbored one of the mutually exclusive oncogenes: 5 (14.7%) BRAFV600E, 4 (11.8%) RET/PTC1, 6 (17.6%) RET/PTC3, 2 (5.9%) rare fusion genes, and 6 (17.6%) ETV6ex4/NTRK3. No mutations in codons 12, 13, and 61 of K-, N- and H-RAS, BRAFK601E, or ETV6ex5/NTRK3 or AKAP9/BRAF were detected. Fusion genes were significantly more frequent than BRAFV600E (p = 0.002). Clinicopathologically, RET/PTC3 was associated with solid growth pattern and higher tumor aggressiveness, BRAFV600E and RET/PTC1 with classic papillary morphology and mild clinical phenotype, and ETV6ex4/NTRK3 with follicular-patterned PTC and reduced aggressiveness. The spectrum of driver mutations in sporadic childhood PTC in Belarus largely parallels that in Chernobyl PTC, yet the frequencies of some oncogenes may likely differ from those in the early-onset Chernobyl PTC; clinicopathological features correlate with the oncogene typ

Major Oncogenic Drivers and Their Clinicopathological Correlations in Sporadic Childhood Papillary Thyroid Carcinoma in Belarus

Childhood papillary thyroid carcinoma (PTC) diagnosed after the Chernobyl accident in Belarus displayed a high frequency of gene rearrangements and low frequency of point mutations. Since 2001, only sporadic thyroid cancer occurs in children aged up to 14 years but its molecular characteristics have not been reported. Here, we determine the major oncogenic events in PTC from non-exposed Belarusian children and assess their clinicopathological correlations. Among the 34 tumors, 23 (67.6%) harbored one of the mutually exclusive oncogenes: 5 (14.7%) BRAFV600E, 4 (11.8%) RET/PTC1, 6 (17.6%) RET/PTC3, 2 (5.9%) rare fusion genes, and 6 (17.6%) ETV6ex4/NTRK3. No mutations in codons 12, 13, and 61 of K-, N- and H-RAS, BRAFK601E, or ETV6ex5/NTRK3 or AKAP9/BRAF were detected. Fusion genes were significantly more frequent than BRAFV600E (p = 0.002). Clinicopathologically, RET/PTC3 was associated with solid growth pattern and higher tumor aggressiveness, BRAFV600E and RET/PTC1 with classic papillary morphology and mild clinical phenotype, and ETV6ex4/NTRK3 with follicular-patterned PTC and reduced aggressiveness. The spectrum of driver mutations in sporadic childhood PTC in Belarus largely parallels that in Chernobyl PTC, yet the frequencies of some oncogenes may likely differ from those in the early-onset Chernobyl PTC; clinicopathological features correlate with the oncogene type