The function and evolution of the restriction factor viperin in primates was not driven by lentiviruses

Abstract Background Viperin, also known as RSAD2, is an interferon-inducible protein that potently restricts a broad range of different viruses such as influenza, hepatitis C virus, human cytomegalovirus and West Nile virus. Viperin is thought to affect virus budding by modification of the lipid environment within the cell. Since HIV-1 and other retroviruses depend on lipid domains of the host cell for budding and infectivity, we investigated the possibility that Viperin also restricts human immunodeficiency virus and other retroviruses. Results Like other host restriction factors that have a broad antiviral range, we find that viperin has also been evolving under positive selection in primates. The pattern of positive selection is indicative of Viperin's escape from multiple viral antagonists over the course of primate evolution. Furthermore, we find that Viperin is interferon-induced in HIV primary target cells. We show that exogenous expression of Viperin restricts the LAI strain of HIV-1 at the stage of virus release from the cell. Nonetheless, the effect of Viperin restriction is highly strain-specific and does not affect most HIV-1 strains or other retroviruses tested. Moreover, knockdown of endogenous Viperin in a lymphocytic cell line did not significantly affect the spreading infection of HIV-1. Conclusion Despite positive selection having acted on Viperin throughout primate evolution, our findings indicate that Viperin is not a major restriction factor against HIV-1 and other retroviruses. Therefore, other viral lineages are likely responsible for the evolutionary signatures of positive selection in viperin among primates.</p

Tumor heterogeneity in VHL drives metastasis in clear cell renal cell carcinoma

Loss of function of the von Hippel-Lindau (VHL) tumor suppressor gene is a hallmark of clear cell renal cell carcinoma (ccRCC). The importance of heterogeneity in the loss of this tumor suppressor has been under reported. To study the impact of intratumoral VHL heterogeneity observed in human ccRCC, we engineered VHL gene deletion in four RCC models, including a new primary tumor cell line derived from an aggressive metastatic case. The VHL gene-deleted (VHL-KO) cells underwent epithelial-to-mesenchymal transition (EMT) and exhibited increased motility but diminished proliferation and tumorigenicity compared to the parental VHL-expressing (VHL+) cells. Renal tumors with either VHL+ or VHL-KO cells alone exhibit minimal metastatic potential. Combined tumors displayed rampant lung metastases, highlighting a novel cooperative metastatic mechanism. The poorly proliferative VHL-KO cells stimulated the proliferation, EMT, and motility of neighboring VHL+ cells. Periostin (POSTN), a soluble protein overexpressed and secreted by VHL non-expressing (VHL-) cells, promoted metastasis by enhancing the motility of VHL-WT cells and facilitating tumor cell vascular escape. Genetic deletion or antibody blockade of POSTN dramatically suppressed lung metastases in our preclinical models. This work supports a new strategy to halt the progression of ccRCC by disrupting the critical metastatic crosstalk between heterogeneous cell populations within a tumor

Persistence of DNA threads in human anaphase cells suggests late completion of sister chromatid decatenation

PICH (Plk1-interacting checkpoint helicase) was recently identified as an essential component of the spindle assembly checkpoint and shown to localize to kinetochores, inner centromeres, and thin threads connecting separating chromosomes even during anaphase. In this paper, we have used immuno-fiber fluorescence in situ hybridization and chromatin-immunoprecipitation to demonstrate that PICH associates with centromeric chromatin during anaphase. Furthermore, by careful analysis of PICH-positive anaphase threads through FISH as well as bromo-deoxyurdine and CREST labeling, we strengthen the evidence that these threads comprise mainly alphoid centromere deoxyribonucleic acid. Finally, by timing the addition of ICRF-193 (a specific inhibitor of topoisomerase-II alpha) to cells synchronized in anaphase, we demonstrate that topoisomerase activity is required specifically to resolve PICH-positive threads during anaphase (as opposed to being required to prevent the formation of such threads during earlier cell cycle stages). These data indicate that PICH associates with centromeres during anaphase and that most PICH-positive threads evolve from inner centromeres as these stretch in response to tension. Moreover, they show that topoisomerase activity is required during anaphase for the resolution of PICH-positive threads, implying that the complete separation of sister chromatids occurs later than previously assumed

Chimpanzee APOBEC3 proteins deter SIVs from any monkey business

Cross-species transmissions of viruses from animals to humans are at the origin of major human pathogenic viruses. While the role of ecological and epidemiological factors in the emergence of new pathogens is well documented, the importance of host factors is often unknown. Chimpanzees are the closest relatives of humans and the animal reservoir at the origin of the human AIDS pandemic. However, despite being regularly exposed to monkey lentiviruses through hunting, chimpanzees are naturally infected by only a single simian immunodeficiency virus, SIVcpz. Here, we asked why chimpanzees appear to be protected against the successful emergence of other SIVs. In particular, we investigated the role of the chimpanzee APOBEC3 genes in providing a barrier to infection by most monkey lentiviruses. We found that most SIV Vifs, including Vif from SIVwrc infecting western-red colobus, the chimpanzee's main monkey prey in West Africa, could not antagonize chimpanzee APOBEC3G. Moreover, chimpanzee APOBEC3D, as well as APOBEC3F and APOBEC3H, provided additional protection against SIV Vif antagonism. Consequently, lentiviral replication in primary chimpanzee CD4(+) T cells was dependent on the presence of a lentiviral vif gene that could antagonize chimpanzee APOBEC3s. Finally, by identifying and functionally characterizing several APOBEC3 gene polymorphisms in both common chimpanzees and bonobos, we found that these ape populations encode APOBEC3 proteins that are uniformly resistant to antagonism by monkey lentiviruses

Metabolic Stress Responses in Drosophila Are Modulated by Brain Neurosecretory Cells That Produce Multiple Neuropeptides

In Drosophila, neurosecretory cells that release peptide hormones play a prominent role in the regulation of development, growth, metabolism, and reproduction. Several types of peptidergic neurosecretory cells have been identified in the brain of Drosophila with release sites in the corpora cardiaca and anterior aorta. We show here that in adult flies the products of three neuropeptide precursors are colocalized in five pairs of large protocerebral neurosecretory cells in two clusters (designated ipc-1 and ipc-2a): Drosophila tachykinin (DTK), short neuropeptide F (sNPF) and ion transport peptide (ITP). These peptides were detected by immunocytochemistry in combination with GFP expression driven by the enhancer trap Gal4 lines c929 and Kurs-6, both of which are expressed in ipc-1 and 2a cells. This mix of colocalized peptides with seemingly unrelated functions is intriguing and prompted us to initiate analysis of the function of the ten neurosecretory cells. We investigated the role of peptide signaling from large ipc-1 and 2a cells in stress responses by monitoring the effect of starvation and desiccation in flies with levels of DTK or sNPF diminished by RNA interference. Using the Gal4-UAS system we targeted the peptide knockdown specifically to ipc-1 and 2a cells with the c929 and Kurs-6 drivers. Flies with reduced DTK or sNPF levels in these cells displayed decreased survival time at desiccation and starvation, as well as increased water loss at desiccation. Our data suggest that homeostasis during metabolic stress requires intact peptide signaling by ipc-1 and 2a neurosecretory cells

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse

Genomic–transcriptomic evolution in lung cancer and metastasis

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic–transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary–metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis