No abstract

Pharmacological and functional genomic screens play an essential role in the discovery and characterization of therapeutic targets and associated pharmacological inhibitors. Although these screens affect thousands of gene products, the typical readout is based on low complexity rather than genome-wide assays. To address this limitation, we introduce pooled library amplification for transcriptome expression (PLATE-Seq), a low-cost, genome-wide mRNA profiling methodology specifically designed to complement high-throughput screening assays. Introduction of sample-specific barcodes during reverse transcription supports pooled library construction and low-depth sequencing that is 10- to 20-fold less expensive than conventional RNA-Seq. The use of network-based algorithms to infer protein activity from PLATE-Seq data results in comparable reproducibility to 30 M read sequencing. Indeed, PLATE-Seq reproducibility compares favorably to other large-scale perturbational profiling studies such as the connectivity map and library of integrated network-based cellular signatures.

To define the role of SV40 large T antigen in the transformation and immortalization of human cells, we have constructed a plasmid lacking most of the unique coding sequences of small t antigen as well as the SV40 origin of replication. The promoter for T antigen, which lies within the origin of replication, was deleted and replaced by the Rous sarcoma virus promoter. This minimal construct was co-electroporated into normal human fibroblasts of neonatal origin along with a plasmid containing the neomycin resistance gene (neo). Three G418-resistant, T antigen-positive clones were expanded and compared to three T antigen-positive clones that received the pSV3neo plasmid (capable of expressing large and small T proteins and having two origins of replication). Autonomous replication of plasmid DNA was observed in all three clones that received pSV3neo but not in any of the three origin minus clones. Immediately after clonal expansion, several parameters of neoplastic transformation were assayed. Low percentages of cells in T antigen-positive populations were anchorage independent or capable of forming colonies in 1% fetal bovine serum. The T antigen-positive clones generally exhibited an extended lifespan in culture but rarely became immortalized. Large numbers of dead cells were continually generated in all T antigen-positive, pre-crisis populations. Ninety-nine percent of all T antigen-positive cells had numerical or structural chromosome aberrations. Control cells that received the neo gene did not have an extended life span, did not have noticeable numbers of dead cells, and did not exhibit karyotype instability. We suggest that the role of T antigen protein in the transformation process is to generate genetic hypervariability, leading to various consequences including neoplastic transformation and cell death.

Estimates of cancer risks posed to space-flight crews by exposure to high atomic number, high-energy (HZE) ions are subject to considerable uncertainty because epidemiological data do not exist for human populations exposed to similar radiation qualities. We assessed the leukemogenic efficacy of one such HZE species, 1 GeV (56)Fe ions, a component of space radiation, in a mouse model for radiation-induced acute myeloid leukemia. CBA/CaJ mice were irradiated with 1 GeV/nucleon (56)Fe ions or (137)Cs gamma rays and followed until they were moribund or to 800 days of age. We found that 1 GeV/nucleon (56)Fe ions do not appear to be substantially more effective than gamma rays for the induction of acute myeloid leukemia (AML). However, (56)Fe-ion-irradiated mice had a much higher incidence of hepatocellular carcinoma (HCC) than gamma-irradiated mice, with an estimated RBE of approximately 50. These data suggest a difference in the effects of HZE iron ions on the induction of leukemia compared to solid tumors, suggesting potentially different mechanisms of tumorigenesis.

The COVID-19 virus has spread worldwide in a matter of a few months, while healthcare systems struggle to monitor and report current cases. Testing results have struggled with the relative capabilities, testing policies and preparedness of each affected country, making their comparison a non-trivial task. Since severe cases, which more likely lead to fatal outcomes, are detected at a higher rate than mild cases, the reported virus mortality is likely inflated in most countries. Lockdowns and changes in human behavior modulate the underlying growth rate of the virus. Under-sampling of infection cases may lead to the under-estimation of total cases, resulting in systematic mortality estimation biases. For healthcare systems worldwide it is important to know the expected number of cases that will need treatment. In this manuscript, we identify a generalizable growth rate decay reflecting behavioral change. We propose a method to correct the reported COVID-19 cases and death numbers by using a benchmark country (South Korea) with nearoptimal testing coverage, with considerations on population demographics. We extrapolate expected deaths and hospitalizations with respect to observations in countries that passed the exponential growth curve. By applying our correction, we predict that the number of cases is highly under-reported in most countries and a significant burden on worldwide hospital capacity.