Biology subjects

Wang, S. S.

Publications and source records attributed to Wang, S. S..

6 recordsLinked to original sources

bioRxiv2023

Influenza A virus during pregnancy disrupts maternal intestinal immunity and fetal cortical development in a dose- and time-dependent manner

Epidemiological studies link neurodevelopmental disorders (NDDs) with exposure to maternal viral infection in utero. It is hypothesized that the mechanism governing this link involves the activation of maternal intestinal T helper 17 (TH17) cells, which produce effector cytokine interleukin (IL)-17. While IL-17 is implicated as a major driver of fetal brain abnormalities, this inflammation-induced TH17 pathway has not been thoroughly examined in models of live viral infection during pregnancy. Influenza A virus (IAV) infection is consistently linked to offspring NDDs and can result in host intestinal dysregulation. Therefore, it is possible that intestinal TH17 cells and subsequent production of IL-17 could drive fetal brain abnormalities during gestational IAV infection. To test this, we inoculated pregnant mice with two infectious doses of IAV and evaluated peak innate and adaptive immune responses in the dam and fetus. While respiratory IAV infection led to dose-dependent maternal colonic shortening and microbial dysregulation, there was no elevation in intestinal TH17 cells nor IL-17. Fetal cortical abnormalities and global changes in fetal brain transcripts were observable in the high-dose IAV group, despite a lack of IL-17 signaling. Profiling fetal microglia and border-associated macrophages (BAMs) -potential cellular mediators of IAV-induced cortical abnormalities -revealed dose-dependent differences in the numbers of BAMs but not microglia. Overall, our data support the idea of an infection severity threshold for downstream maternal inflammation and fetal cortical abnormalities, confirming the use of live pathogens in NDD modeling to better evaluate the complete immune response and to improve translation to the clinic.

neuroscience↗

bioRxiv2023

Beta and theta oscillations track effort and previous reward in human basal ganglia and prefrontal cortex during decision making

Choosing whether to exert effort to obtain rewards is fundamental to human motivated behavior. However, the neural dynamics underlying the evaluation of reward and effort in humans is poorly understood. Here, we investigate this with chronic intracranial recordings from prefrontal cortex (PFC) and basal ganglia (BG; subthalamic nuclei and globus pallidus) in people with Parkinsons disease performing a decision-making task with offers that varied in levels of reward and physical effort required. This revealed dissociable neural signatures of reward and effort, with BG beta (12-20 Hz) oscillations tracking subjective effort on a single trial basis and PFC theta (4-7 Hz) signaling previous trial reward. Stimulation of PFC increased overall acceptance of offers in addition to increasing the impact of reward on choices. This work uncovers oscillatory mechanisms that guide fundamental decisions to exert effort for reward across BG and PFC, as well as supporting a causal role of PFC for such choices.

neuroscience↗

bioRxiv2022

Parallel molecular computation on digital data stored in DNA

DNA is an incredibly dense storage medium for digital data, but computing on the stored information is expensive and slow (rounds of sequencing, in silico computation, and DNA synthesis). Augmenting DNA storage with "in-memory" molecular computation, we use strand displacement reactions to algorithmically modify data stored in the topological modification of DNA. A secondary sequence-level encoding allows high-throughput sequencing-based readout. We show multiple rounds of binary counting and cellular automaton Rule 110 computation on 4-bit data registers, as well as selective access and erasure. Avoiding stringent sequence design, we demonstrate large strand displacement cascades (122 distinct steps) on naturally-occurring DNA sequences. Our work merges DNA storage and DNA computing, setting the foundation of entirely molecular algorithms for parallel manipulation of digital information kept in DNA.

bioengineering↗

bioRxiv2021

Fast and sensitive GCaMP calcium indicators for imaging neural populations

Calcium imaging with protein-based indicators is widely used to follow neural activity in intact nervous systems. The popular GCaMP indicators are based on the calcium-binding protein calmodulin and the RS20 peptide. These sensors report neural activity at timescales much slower than electrical signaling, limited by their biophysical properties and trade-offs between sensitivity and speed. We used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators. The resulting jGCaMP8 sensors, based on calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (rise times, 2 ms) and still feature the highest sensitivity for neural activity reported for any protein-based sensor. jGCaMP8 sensors will allow tracking of larger populations of neurons on timescales relevant to neural computation.

neuroscience↗

bioRxiv2018

Fast animal pose estimation using deep neural networks

Recent work quantifying postural dynamics has attempted to define the repertoire of behaviors performed by an animal. However, a major drawback to these techniques has been their reliance on dimensionality reduction of images which destroys information about which parts of the body are used in each behavior. To address this issue, we introduce a deep learning-based method for pose estimation, LEAP (LEAP Estimates Animal Pose). LEAP automatically predicts the positions of animal body parts using a deep convolutional neural network with as little as 10 frames of labeled data for training. This framework consists of a graphical interface for interactive labeling of body parts and software for training the network and fast prediction on new data (1 hr to train, 185 Hz predictions). We validate LEAP using videos of freely behaving fruit flies (Drosophila melanogaster) and track 32 distinct points on the body to fully describe the pose of the head, body, wings, and legs with an error rate of <3% of the animals body length. We recapitulate a number of reported findings on insect gait dynamics and show LEAPs applicability as the first step in unsupervised behavioral classification. Finally, we extend the method to more challenging imaging situations (pairs of flies moving on a mesh-like background) and movies from freely moving mice (Mus musculus) where we track the full conformation of the head, body, and limbs.

animal behavior and cognition↗

bioRxiv2017

Rapid Sequential In Situ Multiplexing With DNA-Exchange-Imaging

To decipher the molecular mechanism of biological function, it is critical to map the molecular composition of individual cells in the context of their biological environment in situ. Immunofluorescence (IF) provides specific labeling for molecular profiling. However, conventional IF methods have finite multiplexing capabilities due to spectral overlap of the fluorophores. Various sequential imaging methods have been developed to circumvent this spectral limit, but are not widely adopted due to the common limitation of requiring multi-rounds of slow (typically over 2 hours at room temperature to overnight at 4 {degrees}C in practice) immunostaining. DNA-Exchange-Imaging is a practical platform for rapid in situ spectrally-unlimited multiplexing. This technique overcomes speed restrictions by allowing for single-step immunostaining with DNA-barcoded antibodies, followed by rapid (less than 10 minutes) buffer exchange of fluorophore-bearing DNA imager strands. By eliminating the need for multiple rounds of immunostaining, DEI enables rapid spectrally unlimited sequential imaging. The programmability of DNA-Exchange-Imaging allows us to further adapt it to diverse microscopy platforms (with Exchange-Confocal, Exchange-SIM, Exchange-STED, and Exchange-PAINT demonstrated here), achieving highly multiplexed in situ protein visualization in diverse samples (including neuronal and tumor cells as well as fresh-frozen or paraffin-embedded tissue sections) and at multiple desired resolution scales (from ~300 nm down to sub-20-nm). Validation highlights include 8-target imaging using single-channel Exchange-Confocal in tens of micron thick retina tissue sections in 2-3 hours (as compared to days required in principle by previous methods using comparable equipment), and 8-target super-resolution imaging with ~20 nm resolution using Exchange-PAINT in primary neurons. These results collectively suggest DNA-Exchange as a versatile, practical platform for rapid, highly multiplexed in situ imaging, potentially enabling new applications ranging from basic science, to drug discovery, and to clinical pathology.

bioengineering↗