Environmental exposures associated with honey bee health.

Bee health is declining on a global scale, yet the exact causes and their interactions responsible for the decline remain unknown. To more objectively study bee health, recently biomarkers have been proposed as an essential tool, because they can be rapidly quantified and standardized, serving as a comparable measure across bee species and varying environments. Here, we used a systems biology approach to draw associations between endogenous and exogenous chemical profiles, with pesticide exposure, or the abundance of the 21 most common honey bee diseases. From the analysis we identified chemical biomarkers for both pesticide exposure and bee diseases along with the mechanistic biological pathways that may influence disease onset and progression. We found a total of 2352 chemical features, from 30 different hives, sampled from seven different locations. Of these, a total of 1088 significant associations were found that could serve as chemical biomarker profiles for predicting both pesticide exposure and the presence of diseases in a bee colony. In almost all cases we found novel external environmental exposures within the top seven associations with bee diseases and pesticide exposures, with the majority having previously unknown connections to bee health. We highlight the exposure-outcome paradigm and its ability to identify previously uncategorized interactions from different environmental exposures associated with bee diseases, pesticides, mechanisms, and potential synergistic interactions of these that are responsible for honey bee health decline.

ALC1 links chromatin accessibility to PARP inhibitor response in homologous recombination-deficient cells.

The response to poly(ADP-ribose) polymerase inhibitors (PARPi) is dictated by homologous recombination (HR) DNA repair and the abundance of lesions that trap PARP enzymes. It remains unclear, however, if the established role of PARP in promoting chromatin accessibility impacts viability in these settings. Using a CRISPR-based screen, we identified the PAR-binding chromatin remodeller ALC1/CHD1L as a key determinant of PARPi toxicity in HR-deficient cells. ALC1 loss reduced viability of breast cancer gene (BRCA)-mutant cells and enhanced sensitivity to PARPi by up to 250-fold, while overcoming several resistance mechanisms. ALC1 deficiency reduced chromatin accessibility concomitant with a decrease in the association of base damage repair factors. This resulted in an accumulation of replication-associated DNA damage, increased PARP trapping and a reliance on HR. These findings establish PAR-dependent chromatin remodelling as a mechanistically distinct aspect of PARPi responses and therapeutic target in HR-deficient cancers.

Illumination pattern design with deep learning for single-shot Fourier ptychographic microscopy.

Fourier ptychographic microscopy allows for the collection of images with a high space-bandwidth product at the cost of temporal resolution. In Fourier ptychographic microscopy, the light source of a conventional widefield microscope is replaced with a light-emitting diode (LED) matrix, and multiple images are collected with different LED illumination patterns. From these images, a higher-resolution image can be computationally reconstructed without sacrificing field-of-view. We use deep learning to achieve single-shot imaging without sacrificing the space-bandwidth product, reducing the acquisition time in Fourier ptychographic microscopy by a factor of 69. In our deep learning approach, a training dataset of high-resolution images is used to jointly optimize a single LED illumination pattern with the parameters of a reconstruction algorithm. Our work paves the way for high-throughput imaging in biological studies.