An impaired ubiquitin-proteasome system increases APOBEC3A abundance.

Apolipoprotein B messenger RNA (mRNA) editing enzyme, catalytic polypeptide-like (APOBEC) cytidine deaminases cause genetic instability during cancer development. Elevated APOBEC3A (A3A) levels result in APOBEC signature mutations; however, mechanisms regulating A3A abundance in breast cancer are unknown. Here, we show that dysregulating the ubiquitin-proteasome system with proteasome inhibitors, including Food and Drug Administration-approved anticancer drugs, increased A3A abundance in breast cancer and multiple myeloma cell lines. Unexpectedly, elevated A3A occurs via an ∼100-fold increase in A3A mRNA levels, indicating that proteasome inhibition triggers a transcriptional response as opposed to or in addition to blocking A3A degradation. This transcriptional regulation is mediated in part through FBXO22, a protein that functions in SKP1-cullin-F-box ubiquitin ligase complexes and becomes dysregulated during carcinogenesis. Proteasome inhibitors increased cellular cytidine deaminase activity, decreased cellular proliferation and increased genomic DNA damage in an A3A-dependent manner. Our findings suggest that proteasome dysfunction, either acquired during cancer development or induced therapeutically, could increase A3A-induced genetic heterogeneity and thereby influence therapeutic responses in patients.

APOBEC-Induced Mutagenesis in Cancer.

The initiation, progression, and relapse of cancers often result from mutations occurring within somatic cells. Consequently, processes that elevate mutation rates accelerate carcinogenesis and hinder the development of long-lasting therapeutics. Recent sequencing of human cancer genomes has identified patterns of mutations, termed mutation signatures, many of which correspond to specific environmentally induced and endogenous mutation processes. Some of the most frequently observed mutation signatures are caused by dysregulated activity of APOBECs, which deaminate cytidines in single-stranded DNA at specific sequence motifs causing C-to-T and C-to-G substitutions. In humans, APOBEC-generated genetic heterogeneity in tumor cells contributes to carcinogenesis, metastasis, and resistance to therapeutics. Here, we review the current understanding of APOBECs' role in cancer mutagenesis and impact on disease and the biological processes that influence APOBEC mutagenic capacity.

Outside the Safe Operating Space of the Planetary Boundary for Novel Entities.

We submit that the safe operating space of the planetary boundary of novel entities is exceeded since annual production and releases are increasing at a pace that outstrips the global capacity for assessment and monitoring. The novel entities boundary in the planetary boundaries framework refers to entities that are novel in a geological sense and that could have large-scale impacts that threaten the integrity of Earth system processes. We review the scientific literature relevant to quantifying the boundary for novel entities and highlight plastic pollution as a particular aspect of high concern. An impact pathway from production of novel entities to impacts on Earth system processes is presented. We define and apply three criteria for assessment of the suitability of control variables for the boundary: feasibility, relevance, and comprehensiveness. We propose several complementary control variables to capture the complexity of this boundary, while acknowledging major data limitations. We conclude that humanity is currently operating outside the planetary boundary based on the weight-of-evidence for several of these control variables. The increasing rate of production and releases of larger volumes and higher numbers of novel entities with diverse risk potentials exceed societies' ability to conduct safety related assessments and monitoring. We recommend taking urgent action to reduce the harm associated with exceeding the boundary by reducing the production and releases of novel entities, noting that even so, the persistence of many novel entities and/or their associated effects will continue to pose a threat.

Single-stranded DNA binding proteins influence APOBEC3A substrate preference.

The cytidine deaminase, APOBEC3A (A3A), is a prominent source of mutations in multiple cancer types. These APOBEC-signature mutations are non-uniformly distributed across cancer genomes, associating with single-stranded (ss) DNA formed during DNA replication and hairpin-forming sequences. The biochemical and cellular factors that influence these specificities are unclear. We measured A3A's cytidine deaminase activity in vitro on substrates that model potential sources of ssDNA in the cell and found that A3A is more active on hairpins containing 4 nt ssDNA loops compared to hairpins with larger loops, bubble structures, replication fork mimics, ssDNA gaps, or linear DNA. Despite pre-bent ssDNAs being expected to fit better in the A3A active site, we determined A3A favors a 4 nt hairpin substrate only 2- to fivefold over linear ssDNA substrates. Addition of whole cell lysates or purified RPA to cytidine deaminase assays more severely reduced A3A activity on linear ssDNA (45 nt) compared to hairpin substrates. These results indicate that the large enrichment of A3A-driven mutations in hairpin-forming sequences in tumor genomes is likely driven in part by other proteins that preferentially bind longer ssDNA regions, which limit A3A's access. Furthermore, A3A activity is reduced at ssDNA associated with a stalled T7 RNA polymerase, suggesting that potential protein occlusion by RNA polymerase also limits A3A activity. These results help explain the small transcriptional strand bias for APOBEC mutation signatures in cancer genomes and the general targeting of hairpin-forming sequences in the lagging strand template during DNA replication.

APOBEC3A is a prominent cytidine deaminase in breast cancer.

APOBEC cytidine deaminases are the second-most prominent source of mutagenesis in sequenced tumors. Previous studies have proposed that APOBEC3B (A3B) is the major source of mutagenesis in breast cancer (BRCA). We show that APOBEC3A (A3A) is the only APOBEC whose expression correlates with APOBEC-induced mutation load and that A3A expression is responsible for cytidine deamination in multiple BRCA cell lines. Comparative analysis of A3A and A3B expression by qRT-PCR, RSEM-normalized RNA-seq, and unambiguous RNA-seq validated the use of RNA-seq to measure APOBEC expression, which indicates that A3A is the primary correlate with APOBEC-mutation load in primary BRCA tumors. We also demonstrate that A3A has >100-fold more cytidine deamination activity than A3B in the presence of cellular RNA, likely explaining why higher levels of A3B expression contributes less to mutagenesis in BRCA. Our findings identify A3A as a major source of cytidine deaminase activity in breast cancer cells and possibly a prominent contributor to the APOBEC mutation signature.

Model intercomparison for the uptake of organic chemicals by plants.

Currently, a variety of models are available for predicting the uptake, translocation, and elimination of organic contaminants by plants. These models range from simple deterministic risk assessment screening tools to more complex models that consider physical, chemical, and biological processes in a mechanistic manner. This study evaluates the performance of a range of such models and model types against experimental data sets. Three dynamic, three regression-based, and three steady-state and equilibrium models have been selected for evaluation. These models differ in terms of their scope, methodological approach, and complexity. Data from nine published experiments were used to create scenarios to test model performance. These experiments consider plant contamination via both soil and aerial exposure pathways. A total of 19 different organic chemicals were used in the experiments along with 7 different plant species. Model predictions of chemical concentrations in the relevant plant compartments were compared with the experimentally recorded values. The results indicate that dynamic models offer performance advantages for acute exposure durations and for rapidly changing environmental media. Equilibrium/steady-state and regression-based models perform better for chronic exposure durations, where stable conditions are more likely to exist. The selection of an appropriate plant uptake model will therefore be dependent on the requirements of the assessment, the nature of the environmental media, and the duration of the source term. The results generated by the regression-based models suggest that in their current form these models are unsuitable for evaluating the uptake of organic chemicals from the air into plants.