Biology subjects

Chen, A.

Publications and source records attributed to Chen, A..

At least 127 records · Page 7Linked to original sources

bioRxiv2024

Biomarker Identification by Proteomic Analysis of Vitreous Humor and Plasma in Diabetic Retinopathy

ImportanceIdentify detectable plasma and/or vitreous signals to potentially predict diabetic retinopathy (DR) progression for earlier disease intervention. ObjectiveTo determine the mediators and potential disease progression biomarkers of DR in vitreous humor (VH) and plasma samples using the SomaScan proteome profiling platform. DesignDifferential expression analysis was conducted on VH and plasma samples using the SomaScan Assay. SettingA non-interventional study conducted to collect and analyze VH and plasma samples from patients with diabetic retinopathy. ParticipantsSamples from DR (60 nonproliferative diabetic retinopathy/NPDR, 60 proliferative diabetic retinopathy/PDR) and 60 control patients were collected. Main outcomes and MeasuresDifferentially expressed proteins between disease and control groups were identified. Pathway enrichment analysis was conducted to identify significantly perturbed pathways in DR. Finally, a random forest model was used to identify predictive biomarkers of disease progression. ResultsSomaScan v3 is a pooled aptamer hybridization assay using 5080 SOMAmers to probe over 4100 proteoforms in VH and plasma samples from 3 groups (control, NPDR, and PDR). The most profound protein content change was observed in the VH samples of PDR patients, while minimal changes were measured in plasma samples, highlighting the regionality of PDR pathogenesis. Many key molecules and molecular pathways such as VEGF-A, erythropoietin, and inflammation-associated proteins implicated in DR were significantly affected in the VH of PDR patients. In addition to the classic pathways (hypoxia, immune response, mTORC1 signaling) known to be involved in PDR, novel signaling pathways, including HEME metabolism and adipogenesis, were identified in VH samples. Application of a machine learning algorithm identified a panel of plasma PDR predictive biomarkers and revealed SCARA5 as the top one based on the largest average Gini decrease in the model. ConclusionOur study identified profound alteration of protein expression and molecular pathways in the VH of PDR patients, supporting the key role of local pathogenic changes in DR progression compared to systemic factors. Although the systemic changes related to DR were small, a few disease progression predictive candidate biomarkers (SCARA5, PTK7, FAM3Band FAM3D) were identified, prompting further investigation. Key PointsQuestion: Are plasma/ vitreous humor (VH) proteins predictive of diabetic retinopathy (DR) progression? Findings: This study identifies substantial protein changes in the VH of proliferative diabetic retinopathy (PDR) patients, while early nonproliferative DR (NPDR) patients show minimal change. We identify multiple proteins linked to angiogenesis, inflammation, immune cells (microglia/macrophage/neutrophil), and leukostasis associated with PDR and reveal a potential plasma panel of disease progression (from NPDR to PDR) biomarkers (SCARA5, PTK7, FAM3B, FAM3D). Meaning: Identified disease progression predictive biomarkers permits potential development of prognostic tools to identify individuals most at risk for PDR progression and offering reduced disease burden by earlier intervention.

physiology↗

bioRxiv2024

SCIITensor: A tensor decomposition based algorithm to construct actionable TME modules with spatially resolved intercellular communications

Advanced spatial transcriptomics (ST) technology has paved the way for elucidating the spatial architecture of the tumor microenvironment (TME) from multiple perspectives. However, available tools only focus on the static molecular and cellular composition of the TME when analyzing the high-throughput ST data, neglecting to uncover the in-depth spatial co-variation of intercellular communications arising from heterogeneous spatial TMEs. Here, we introduce SCIITensor, which decomposes TME modules from the perspective of spatially resolved intercellular communication by spatially quantifying the cellular and molecular interaction intensities between proximal cells within each domain. It then constructs a three-dimensional matrix, formulating the task as a matrix decomposition problem, and identifies biologically relevant spatial interactions and TME patterns using Non-Negative Tucker Decomposition (NTD). We evaluated the performance of SCIITensor on liver cancer datasets obtained from multiple ST platforms. At the research setting of a single-sample investigation, SCIITensor precisely identified a functional TME module indicating a tumor boundary structure specific domain with co-variant interaction contexts, which were involved in construction of immunosuppressive TME. Moreover, we also proved that SCIITensor was able to construct TME meta-modules across multiple samples and to further identify an immune-infiltration associated and sample-common meta-module. We demonstrate that SCIITensor is applicable for dissecting TME modules from a new perspective by constructing spatial interaction contexts using ST datasets of individual and multiple samples, providing new insights into tumor research and potential therapeutic targets.

bioinformatics↗

bioRxiv2024

ninjaCap: A fully customizable and 3D printable headgear for fNIRS and EEG brain imaging

SignificanceAccurate sensor placement is vital for non-invasive brain imaging, particularly for functional near infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT), which lack standardized layouts like EEG. Custom, manually prepared probe layouts on textile caps are often imprecise and labor-intensive. AimWe introduce a method for creating personalized, 3D-printed headgear, enabling accurate translation of 3D brain coordinates to 2D printable panels for custom fNIRS and EEG sensor layouts, reducing costs and manual labor. ApproachOur approach uses atlas-based or subject-specific head models and a spring-relaxation algorithm for flattening 3D coordinates onto 2D panels, using 10-5 EEG coordinates for reference. This process ensures geometrical fidelity, crucial for accurate probe placement. Probe geometries and holder types are customizable and printed directly on the cap, making the approach agnostic to instrument manufacturers and probe types. ResultsOur ninjaCap method offers 2.2{+/-}1.5 mm probe placement accuracy. Over the last five years, we have developed and validated this approach with over 50 cap models and 500 participants. A cloud-based ninjaCap generation pipeline along with detailed instructions is now available at openfnirs.org. ConclusionsThe ninjaCap marks a significant advancement in creating individualized neuroimaging caps, reducing costs and labor while improving probe placement accuracy, thereby reducing variability in research.

neuroscience↗

bioRxiv2024

Systematic Development of Reprogrammed Modular Integrases Enables Precise Genomic Integration of Large DNA Sequences

Despite recent progress in the ability to manipulate the genomes of eukaryotic cells1-3, there is still no effective and practical method to precisely integrate large synthetic DNA constructs into desired chromosomal sites using a programmable integrase. Serine integrases can perform the necessary molecular steps4, but only if their natural target site is first installed into the recipient genome by other methods. A more elegant approach would be to directly reprogram the serine integrase itself to target a desired genomic site that is different from the natural recognition site of the integrase5. Here, we describe the development of a Modular Integrase (MINT) platform, a versatile protein-guided genome editing tool that can facilitate site-directed targeted integration (TI) of synthetic DNA into chromosomal sites. Through a combination of structural modeling, directed evolution, and screening in human cells we have reprogrammed the specificity of the serine integrase Bxb1. We demonstrate the therapeutic potential of the MINT platform by retargeting Bxb1 to the human AAVS1 and TRAC loci where wild-type Bxb1 has no detectable activity. By combining the MINT platform with known activity-increasing Bxb1 mutants, we achieved 14% TI at the AAVS1 locus, and by additionally fusing zinc finger DNA binding domains to engineered Bxb1 variants, we achieved 35% TI at the TRAC locus in human K562 cells. To further demonstrate clinical potential, we achieved stable 15% TI of a functional donor construct in human T cells.

synthetic biology↗

bioRxiv2024

StereoMM: A Graph Fusion Model for Integrating Spatial Transcriptomic Data and Pathological Images

Spatially resolved omics technologies generating multimodal and high-throughput data lead to the urgent need for advanced analysis to allow the biological discoveries by comprehensively utilizing information from multi-omics data. The H&E image and spatial transcriptomic data indicate abundant features which are different and complementary to each other. AI algorithms can perform nonlinear analysis on these aligned or unaligned complex datasets to decode tumoral heterogeneity for detecting functional domain. However,the interpretability of AI-generated outcomes for human experts is a problem hindering application of multi-modal analysis in clinic. We presented a machine learning based toolchain called StereoMM, which is a graph fusion model that can integrate gene expression, histological images, and spatial location. StereoMM firstly performs information interaction on transcriptomic and imaging features through the attention module, guaranteeing explanations for its decision-making processes. The interactive features are input into the graph autoencoder together with the graph of spatial position, so that multimodal features are fused in a self-supervised manner. Here, StereoMM was subjected to mouse brain tissue, demonstrating its capability to discern fine tissue architecture, while highlighting its advantage in computational speed. Utilizing data from Stereo-seq of human lung adenosquamous carcinoma and 10X Visium of human breast cancer, we showed its superior performance in spatial domain recognition over competing software and its ability to reveal tumor heterogeneity. The fusion approach for imaging and gene expression data within StereoMM aids in the more accurate identification of domains, unveils critical molecular features, and elucidates the connections between different domains, thereby laying the groundwork for downstream analysis.

bioinformatics↗

bioRxiv2024

Insulin Resistance Increases TNBC Aggressiveness and Brain Metastasis via Adipocyte-derived Exosomes

Patients with triple negative breast cancer (TNBC) and comorbid Type 2 Diabetes (T2D), characterized by insulin resistance of adipose tissue, have higher risk of metastasis and shorter survival. Adipocytes are the main non-malignant cells of the breast tumor microenvironment (TME). However, adipocyte metabolism is usually ignored in oncology and mechanisms that couple T2D to TNBC outcomes are poorly understood. Here we hypothesized that exosomes, small vesicles secreted by TME breast adipocytes, drive epithelial-to-mesenchymal transition (EMT) and metastasis in TNBC via miRNAs. Exosomes were purified from conditioned media of 3T3-L1 mature adipocytes, either insulin-sensitive (IS) or insulin-resistant (IR). Murine 4T1 cells, a TNBC model, were treated with exosomes in vitro (72h). EMT, proliferation and angiogenesis were elevated in IR vs. control and IS. Brain metastases showed more mesenchymal morphology and EMT enrichment in the IR group. MiR-145a-3p is highly differentially expressed between IS and IR, and potentially regulates metastasis. SignificanceIR adipocyte exosomes modify TME, increase EMT and promote metastasis to distant organs, likely through miRNA pathways. We suggest metabolic diseases such as T2D reshape the TME, promoting metastasis and decreasing survival. Therefore, TNBC patients with T2D should be closely monitored for metastasis, with metabolic medications considered.

cancer biology↗

bioRxiv2024

Identification of Fibrinogen as a Plasma Protein Binding Partner for Lecanemab Biosimilar IgG: Implications for Alzheimer's Disease Therapy

ObjectiveRecombinant monoclonal therapeutic antibodies like lecanemab, which target amyloid beta in Alzheimers disease, offer a promising approach for modifying the disease progression. Due to its relatively short half-life, Lecanemab, administered as a bi-monthly infusion (typically 10mg/kg) has a relatively brief half-life. Interaction with abundant plasma proteins binder in the bloodstream can affect pharmacokinetics of drugs, including their half-life. In this study we investigated potential plasma protein binding interaction to lecanemab using lecanemab biosimilar. MethodsLecanemab biosimilar used in this study was based on publicly available sequences. ELISA and Western blotting were used to assess lecanemab biosimilar immunoreactivity in the fractions human plasma sample obtained through size exclusion chromatography. The binding of lecanemab biosimilar to candidate binders was confirmed by Western blotting, ELISA, and surface plasmon resonance analysis. ResultsUsing a combination of equilibrium dialysis, ELISA, and Western blotting in human plasma, we first describe the presence of likely plasma protein binding partner to lecanemab biosimilar, and then identify fibrinogen as one of them. Utilizing surface plasmon resonance, we confirmed that lecanemab biosimilar does bind to fibrinogen, although with lower affinity than to monomeric amyloid beta. InterpretationIn the context of lecanemab therapy, these results imply that fibrinogen levels could impact the levels of free antibodies in the bloodstream and that fibrinogen might serve as a reservoir for lecanemab. More broadly, these results indicate that plasma protein binding may be an important consideration when clinically utilizing therapeutic antibodies in neurodegenerative disease.

neuroscience↗

bioRxiv2024

Group social dynamics in a semi-natural setup reveal an adaptive value for aggression in male mice

BackgroundMaladaptive aggression in humans is associated with several psychiatric conditions and lacks effective treatment. Nevertheless, aggression constitutes an essential behavior throughout the animal kingdom as long as it is tightly regulated. Studying how social dominance hierarchies (SDH) regulate aggression and access to resources in an enriched environment (EE) can narrow the translational gap between aggression in animal models and humans normal and pathological behavior. MethodsThe social box (SB) is a semi-natural setup for automatic and prolonged monitoring of mouse group dynamics. We utilized the SB to decipher complex tradeoffs between aggression, social avoidance, resource allocation, and dominance in two mouse models of increased aggression: (i) a model of early exposure to EE and (ii) a model of oxytocin receptor deficiency (OxtR-/-). While EE increases aggression as an adaptive response to external stimuli, hyper-aggression in OxtR-/- mice is accompanied by marked abnormalities in social behavior. ResultsEE groups exhibited significant social avoidance, and an increased proportion of their encounters developed into aggressive interactions, resulting in lower levels of exploratory activity and overall aggression. The hierarchy in EE was more stable than in control groups, and dominance was correlated with access to resources. In OxtR-/- groups, mice engaged in excessive social encounters and aggressive chasing, accompanied by increased overall activity. In OxtR-/- groups, dominance hierarchies existed but were not correlated with access to resources. ConclusionMeasuring aggression and social dominance hierarchies in a semi-natural setup reveals the adaptive value of aggression in EE and OxtR-/- mice, respectively. This approach can enhance translational research of pathological aggression.

neuroscience↗

bioRxiv2024

Massively parallel interrogation of human functional variants modulating cancer immunosurveillance

Anti-PD-1/PD-L1 immune checkpoint blockade (ICB) therapy has revolutionized clinical cancer treatment, while abnormal PD-L1 or HLA-I expression in patients can significantly impact the therapeutic efficacy. Somatic mutations in cancer cells that modulate these critical immune regulators are closely associated with tumor progression and ICB response. However, a systematic interpretation of cancer immune-related mutations is still lacking. Here, we harnessed the ABEmax system to establish a large-scale sgRNA library encompassing approximately 820,000 sgRNAs that target all feasible Serine/Threonine/Tyrosine residues across the human genome, which systematically unveiled thousands of novel mutations that decrease or augment PD-L1 or HLA-I expression. Notably, we revealed functional mutations that co-regulate PD-L1 and HLA-I expression, represented by the clinically relevant mutation SETD2_Y1666, and verified that it can benefit from immunotherapy in vivo. Our findings generate an unprecedented resource of functional residues regulating cancer immunosurveillance, meanwhile, offer valuable guidance for clinical diagnosis, ICB therapy, and the development of innovative drugs in cancer treatment.

cancer biology↗

bioRxiv2024

A Quantitative Metric of Confidence For Segmentation of Nuclei in Large Spatially Variable Image Volumes

Nuclei segmentation is an important step for quantitative analysis of fluorescence microscopy images. A large volume generally has many different regions containing nuclei with varying spatial characteristics. Automatically identifying nuclei that are challenging to segment can speed up the analysis of biological tissues. Here we show a segmentation technique that provides a metric of segmentation "confidence" for each segmented object in an image volume. This confidence metric can be used either to generate a "confidence map" for visual distinction of reliable from unreliable regions, or in the data space to identify questionable measurements that can be analyzed separately or eliminated from analysis. In an analysis of nuclei in a 3-dimensional image volume, we show that the confidence map correlates well with visual evaluations of segmentation quality, and that the confidence metric correlates well with F1 scores within subregions of the image volume. In addition, we also describe three visualization methods that can visualize the segmentation differences between a segmented volume and a reference volume.

cell biology↗

bioRxiv2024

Circulating tumor cells shed large extracellular vesicles in capillary-sized bifurcations

Circulating tumor cells (CTCs) and their clusters are the drivers of metastasis, but we have an incomplete understanding of how they interact with capillary beds. Using microfluidic models mimicking human capillary bifurcations, we observed cell size- and bifurcation-dependent shedding of nuclei-free fragments by patient CTCs, CTC-derived explant cells and numerous cancer cell lines. Shedding reduced cell sizes up to 61%, facilitating their transit through bifurcations. We demonstrated that shed fragments were a novel subclass of large extracellular vesicles (LEVs), "shearosomes", that require shear stress for their biogenesis and whose proteome was associated with immune-related pathways. Shearosomes exhibited functions characteristic of previously identified EVs including cell-directed internalization by endothelial and immune cells, and intercellular communication abilities such as disruption of endothelial barrier integrity, polarization of monocytes into M2 tumor-promoting macrophages and interactions between endothelial and immune cells. Cumulatively, these findings suggest that CTCs shed shearosomes in capillary beds that drive key processes involved in the formation of pre-metastatic niches.

cancer biology↗

bioRxiv2024

Proteomic profile analysis of plasma and aqueous humor from glaucoma and non-glaucomatous patients

PurposeGlaucoma, a multifactorial ocular neuropathy, can lead to irreversible vision loss. Diagnosis involves assessing optic cupping (increased cup-to-disc ratios) and structural changes (like retinal nerve fiber layer thinning) through clinical imaging. Elevated intraocular pressure (IOP) is commonly associated with glaucoma, but not always. However, understanding disease progression is hindered by limited access to donor ocular tissue and consistent clinical data. We hypothesize that the proteome of aqueous humor and plasma may be altered in disease and correlates with clinical parameters such as IOP and cup-to-disc ratios. MethodsAqueous humor (AH) and plasma samples were collected from 36 glaucoma patients (17 male, 19 female), and 35 non-glaucomatous control patients (16 male, 19 female) undergoing cataract surgery. The protein profile was compared using the SOMAscan(R) assay system for proteome profiling. From glaucomatous donors, correlations between IOP and cup- to-disc ratios to proteome differences were determined. ResultsOverall proteomics profiles between both AH and plasma were compared by combining all samples (glaucoma and non-glaucoma) and then performing correlation analyses. This study revealed similar protein abundance in the two biological fluids. Additionally, it identified different abundance of proteins in plasma and AH between glaucoma and non- glaucoma samples. The differential proteins identified were involved in pathways related to vascular integrity, inflammation, immune response, cell adhesion, and complement activation. Generally, glaucomatous AH showed higher protein levels. Neurofilament light chain (NEFL) protein correlated with elevated IOP and inflammatory markers, but not with cup-to-disc ratios. ConclusionsTogether, our data demonstrate that the proteins identified in this study from glaucomatous donors correspond to markers of neurodegeneration and those that may inhibit cell proliferation or disrupt vascular integrity.

cell biology↗

bioRxiv2024

Spatiotemporal transcriptomic profiling reveals the dynamic immunological landscape of alveolar echinococcosis

Alveolar echinococcosis (AE) is caused by the invasive growth of the metacestodes of Echinococcus multilocularis (E. multilocularis). The early diagnosis, management, and treatment of AE remains challenging. Herein, we integrated bulk RNA-seq, scRNA-seq, and ST technologies to reveal the immune characteristics both spatially and chronologically in E. multilocularis infected mouse liver. An unprecedented high-resolution spatial atlas of the E. multilocularis infection foci was obtained, revealing the pivotal role of neutrophils, Spp1+ monocyte-derived macrophages (MoMFs), and fibroblasts in AE progression. We observed continuous recruitment of neutrophils and macrophages into the infected tissues, indicating prolonged immune stimulation by the growing metacestodes. However, their spatial distribution patterns and functions changed during the infection cause. At the early infection stage, Il1bhi neutrophils aggregated in the lesion displayed the highest pattern-recognition receptor activity and may kill the metacestodes through NETosis, but their death in the infection foci might also trigger immune suppression. Meanwhile, Spp1+ MoMFs attached to the protoscoleces to clear the infection. At the late infection stage, the neutrophils failed to infiltrate into the lesion although their continuous recruitment into the infected liver. Even though the Spp1+ MoMFs enclosing the microcysts of E. multilocularis may retain their pathogen-killing ability, they may also promote fibrosis and angiogenesis through interaction with fibroblasts. The pro- and anti-inflammatory phenotype balance of these immune cells may be associated with the transition of parasite control strategy from "active killing" to "negative segregation" by the host. Our findings identify key molecular traits involved in AE development, which may benefit the treatment of echinococcosis.

immunology↗

bioRxiv2024

Development of BODIPY-based fluorescent probes for highly selective amino acid identification

Amino acid sensing is a powerful tool for intra- and extra-cellular assays. We report herein the generation and optimization of bioconjugatable fluorescent reporter for pan-amino acid sensing, the OMNI probe, that through inductive electronics produces a unique photophysical response upon coupling to the -amino group of an amino acid depending on the identity of the adjacent side chain. Using an auto-photocatalyzed Meerwein arylation reaction, we created a library of bis-arylated 8-methylthio-BODIPY dye derivatives exhibiting improved spectral variation, brightness, dynamic range, robustness, water solubility, and reactivity. Aryl groups with optimal photophysical behaviors were combined to create asymmetric versions conferring high spectral range, brightness, and water solubility. Combining aryl group modifications yielded a set of engineered asymmetric probes that achieved complete spectral resolution in a multi-variable analysis (fluorescent emission, lifetime, brightness) for all twenty native amino acid-dye conjugates while increasing reactivity toward amino acids in aqueous buffer. With our robust OMNI probe design, pan-amino acid resolution and identification through high sensitivity fluorescence down to single molecules is now routinely possible for diverse potential applications including protein sequencing.

biochemistry↗

bioRxiv2024

Mechanisms of genomic instability dictate cytosolic DNA composition and dendritic cell mediated anti-tumor immunity

Patients with microsatellite instable (MSI) colorectal cancers (CRC) face better prognosis than those with the more common chromosomal instable (CIN) subtype due to improved anti-tumor immune responses characterized by high cytotoxic T cell infiltration. Previous investigation identified the cytosolic DNA (cyDNA) sensor STING as necessary for chemokine-mediated T cell recruitment in MSI CRCs. Here, we find cyDNA from MSI CRC cells is inherently more capable of inducing STING activation and induces improved cytotoxic T cell activation by dendritic cells (DCs). Sequencing indicates MSI cyDNA is enriched for microsatellites, which upon DC uptake induce anti-tumor immunity in a manner consistent with clinical MSI CRCs. Radiation also modulates cyDNA stimulation capacity through larger cyDNA size and increased mitochondrial DNA content. Identifying highly stimulatory cyDNA arising from genomic instability such as in MSI CRCs allows for optimized development of DNA-based STING agonist therapies to improve responses of CIN CRC patients to immunotherapies.

cancer biology↗

bioRxiv2024

Biophysics of microRNA-34a targeting and its influence on down-regulation

microRNAs (miRNAs) regulate target mRNA expression post-transcriptionally through their association with Argonaute 2 (AGO2) proteins. Predicting the efficiency of mRNA repression by miRNA has been limited by our comprehension of the structure-function relationship within miRNA binding sites. Using a combination of EMSA, luciferase reporter assays, and structural probing, we investigated the interaction between the human tumour suppressor miR-34a and 12 mRNA targets. Comparison of direct RNA:RNA interactions and those within the functional AGO2 protein revealed that the isolated mRNA:miRNA duplex serves as a strong predictor for duplex affinity and structure within AGO2. Our findings reveal that AGO2 has a bidirectional capacity to modulate affinity; weakening tight RNA:RNA binders while strengthening weak ones. We identified three distinct structural groups that form upon miR-34a binding and reveal a novel structural group that exhibits a guide strand bulge. MD simulations indicate a conceivable fit of this miRNA-bulge structure within AGO2. Our results demonstrate that the structural characteristics of mRNA:miRNA duplexes could serve as contributing determinants of repression efficacy.

biophysics↗

bioRxiv2024

Early life adversity drives sex-dependent changes in 5-mC DNA methylation of parvalbumin cells in the prefrontal cortex in rats

Early life adversity (ELA) can result in increased risk for developing affective disorders, such as anxiety or depression, later in life, with women showing increased risk. Interactions between an individuals genes and their environment play key roles in producing, as well as mitigating, later life neuropathology. Our current understanding of the underlying epigenomic drivers of ELA associated anxiety and depression are limited, and this stems in part from the complexity of underlying biochemical processes associated with how early experiences shapes later life behavior. Epigenetic alterations, or experience-driven modifications to DNA, can be leveraged to understand the interplay between genes and the environment. The present study characterized DNA methylation patterning, assessed via evaluation of 5-methylcytosine (5-mC), following ELA in a Sprague Dawley rat model of ELA induced by early caregiver deprivation. This study utilized maternal separation to investigate sex- and age-specific outcomes of ELA on epigenetic patterning in parvalbumin (PV)-containing interneurons in the prefrontal cortex (PFC), a subpopulation of inhibitory neurons which are associated with ELA and affective dysfunction. While global analysis of 5-mC methylation and CpG site specific pyrosequencing of the PV promoter, Pvalb, showed no obvious effects of ELA, when analyses were restricted to assessing 5-mC intensity in colocalized PV cells, there were significant sex and age dependent effects. We found that ELA leads sex-specific changes in PV cell counts, and that cell counts can be predicted by 5-mC intensity, with males and females showing distinct patterns of methylation and PV outcomes. ELA also produced sex-specific effects in corticosterone reactivity, with juvenile females showing a blunted stress hormone response compared to controls. Overall, ELA led to a sex-specific developmental shift in PV profile, which is comparable to profiles that are seen at a later developmental timepoint, and this shift may be mediated in part by epigenomic alterations driven by altered DNA methylation.

neuroscience↗

bioRxiv2024

Surface Patterned Omniphobic Tiles (SPOTs): a versatile platform for scalable liquid handling

Manipulating liquids is a ubiquitous need for experiments across numerous scientific disciplines. To overcome limitations of current methods, we introduce Surface Patterned Omniphobic Tiles (SPOTs). This platform combines geometry and surface engineering, building on discontinuous wetting approaches to leverage capillarity for metering liquids. The SPOTs platform allows manipulation of hundreds to thousands of independent experiments without expensive equipment or large consumable costs. These devices can handle a wide range of liquid types and volumes (<10 nanoliters to >10 microliters) with better precision than pipetting. The platform is inexpensive and easy to fabricate, fast and intuitive to use, and cross-compatible with existing microwell plate layouts. We demonstrate how these capabilities facilitate diverse experiments including testing antibiotic combinations for synergy and antagonism, material screening of perovskites, and genotyping microbial isolates. We anticipate SPOTs will enable users from disparate domains to quickly and easily run a wide range of high-throughput experiments.

bioengineering↗