Modeling human activity-related spread of the spotted lanternfly (Lycorma delicatula) in the US.

The spotted lanternfly (Lycorma delicatula) has recently spread from its native range to several other countries and forecasts predict that it may become a global invasive pest. In particular, since its confirmed presence in the United States in 2014 it has established itself as a major invasive pest in the Mid-Atlantic region where it is damaging both naturally occurring and commercially important farmed plants. Quarantine zones have been introduced to contain the infestation, but the spread to new areas continues. At present the pathways and drivers of spread are not well-understood. In particular, several human activity related factors have been proposed to contribute to the spread; however, which features of the current spread can be attributed to these factors remains unclear. Here we collect county level data on infestation status and four specific human activity related factors and use statistical methods to determine whether there is evidence for an association between the factors and infestation. Then we construct a network model based on the factors found to be associated with infestation and use it to simulate local spread. We find that the model reproduces key features of the spread 2014 to 2021. In particular, the growth of the main infestation region and the opening of spread corridors in the westward and southwestern directions is consistent with data and the model accurately forecasts the correct infestation status at the county level in 2021 with 81% accuracy. We then use the model to forecast the spread up to 2025 in a larger region. Given that this model is based on a few human activity related factors that can be targeted, it may prove useful to incorporate it into more elaborate predictive forecasting models and in informing management efforts focused on interstate highway transport and garden centers in the US and potentially for current and future invasions elsewhere globally.

MSA: scalable DNA methylation screening BeadChip for high-throughput trait association studies.

The Infinium DNA Methylation BeadChips have significantly contributed to population-scale epigenetics research by enabling epigenome-wide trait association discoveries. Here, we design, describe, and experimentally verify a new iteration of this technology, the Methylation Screening Array (MSA), to focus on human trait screening and discovery. This array utilizes extensive data from previous Infinium platform-based epigenome-wide association studies (EWAS). It incorporates knowledge from the latest single-cell and cell type-resolution whole genome methylome profiles. The MSA is engineered to achieve scalable screening of epigenetics-trait association in an ultra-high sample throughput. Our design encompassed diverse human trait associations, including those with genetic, cellular, environmental, and demographical variables and human diseases such as genetic, neurodegenerative, cardiovascular, infectious, and immune diseases. We comprehensively evaluated this array's reproducibility, accuracy, and capacity for cell-type deconvolution and supporting 5-hydroxymethylation profiling in diverse human tissues. Our first atlas data using this platform uncovered the complex chromatin and tissue contexts of DNA modification variations and genetic variants linked to human phenotypes.

Chronic social defeat stress broadly inhibits gene expression in the peripheral taste system and alters taste responses in mice.

Human studies have linked stress exposure to unhealthy eating behavior. However, the mechanisms that drive stress-associated changes in eating behavior remain incompletely understood. The sense of taste plays important roles in food preference and intake. In this study, we use a chronic social defeat stress (CSDS) model in mice to address whether chronic stress impacts taste sensation and gene expression in taste buds and the gut. Our results showed that CSDS significantly elevated circulating levels of corticosterone and acylated ghrelin while lowering levels of leptin, suggesting a change in metabolic hormones that promotes food consumption. Stressed mice substantially increased their intake of food and water 3-5 days after the stress onset and gradually gained more body weight than that of controls. Moreover, CSDS significantly decreased the expression of multiple taste receptors and signaling molecules in taste buds and reduced mRNA levels of several taste progenitor/stem cell markers and regulators. Stressed mice showed significantly reduced sensitivity and response to umami and sweet taste compounds in behavioral tests. In the small intestine, the mRNA levels of Gnat3 and Tas1r2 were elevated in CSDS mice. The increased Gnat3 was mostly localized in a type of Gnat3+ and CD45+ immune cells, suggesting changes of immune cell distribution in the gut of stressed mice. Together, our study revealed broad effects of CSDS on the peripheral taste system and the gut, which may contribute to stress-associated changes in eating behavior.