Biology subjects

Robinson, J. F.

Publications and source records attributed to Robinson, J. F..

7 recordsLinked to original sources

bioRxiv2026

Untargeted cord blood metabolomics reveals altered lipid metabolism in neonates with gastroschisis

Gastroschisis is a congenital abdominal wall defect in which fetal intestines herniate into the amniotic cavity. Despite 97% surgical repair success rate, 40% of affected infants require hospital readmission due to gastrointestinal complications, where underlying mechanisms remain poorly characterized. We hypopthesized that the cord blood metabolome of neonates with gastroschisis differs systematically from controls and may reveal pathway-level alterations relevant to neonatal physiology. Cord blood plasma collected at delivery (23 samples each group) was analyzed using ultra-performance liquid chromatography coupled with tandem mass spectrometry. Unsupervised principal component analysis and hierarchical clustering demonstrated significant separation between groups (PERMANOVA pseudo-F = 4.632, R{superscript 2} = 0.095, p = 0.001). 53 metabolites met criteria for differential abundance, 75% were lipids. Key alterations included reduced free fatty acids, increased fatty acid amides and ceramides, disrupted steroid and bile acid metabolism, and decreased biliverdin and bilirubin isomers. Our findings provide insight into gastroschisis pathophysiology and identify potential biomarkers for future investigation.

systems biology↗

bioRxiv2026

Active field theory approach to explain size control of transcriptional condensates

Transcription factors organize into liquid-like condensates to facilitate gene expression, yet the physical mechanisms governing their formation and properties remain poorly understood. We study the size statistics of transcriptional condensates in human HAP1 cells using widefield and super-resolution microscopy tagging the epigenetic reader BRD4. We find that hubs that appear monolithic in widefield resolve into clusters of smaller droplets that resist coarsening. We link this size control to Active Model B+, a non-equilibrium field theory that captures a regime of reverse Ostwald ripening out of thermal equilibrium. In this regime, chemically driven currents cause larger droplets to transfer mass back to smaller ones, stabilizing a state of microphase segregation. The observed exponential size distribution of BRD4 foci quantitatively matches our numerical simulations, suggesting a universal physical picture for the non-equilibrium self-limitation of cellular condensates.

biophysics↗

bioRxiv2024

Placental Malaria Induces a Unique Placental Methylation Profile Associated with Fetal Growth Restriction

BackgroundFetal growth restriction (FGR) is associated with perinatal death and adverse birth outcomes, as well as long-term complications, including increased childhood morbidity, abnormal neurodevelopment, and cardio-metabolic diseases in adulthood. Placental epigenetic reprogramming associated with FGR may mediate these long-term outcomes. Placental malaria (PM), characterized by sequestration of Plasmodium falciparum-infected erythrocytes in placental intervillous space, is the leading global cause of FGR, but its impact on placental epigenetics is unknown. We hypothesized that placental methylomic profiling would reveal common and distinct mechanistic pathways of non-malarial and PM-associated FGR. ResultsWe analyzed placentas from a US cohort with no malaria exposure (n = 12) and a cohort from eastern Uganda, a region with a high prevalence of malaria (n = 12). From each site, 8 cases of FGR (defined as birth weight <10%ile for gestational age by Intergrowth-21 standard curves) and 4 healthy controls with normal weight were analyzed. PM was diagnosed by placental histopathology. We compared the methylation levels of over 850K CpGs of the placentas using Infinium MethylationEPIC v1 microarray. Non-malarial FGR was associated with 65 differentially methylated CpGs (DMCs), whereas PM-FGR was associated with 133 DMCs, compared to their corresponding controls without FGR. One DMC (cg16389901, located in the promoter region of BMP4) was commonly hypomethylated in both groups. We identified 522 DMCs between non-malarial FGR vs. PM-FGR placentas, which was independent of differing geographic location or cellular composition. ConclusionPlacentas with PM-associated FGR have distinct methylation profiles as compared to placentas with non-malarial FGR, suggesting novel epigenetic reprogramming in response to malaria. Larger cohort studies are needed to determine the distinct long-term health outcomes in PM-associated FGR pregnancies.

genetics↗

bioRxiv2024

RosetteArray Platform for Quantitative High-Throughput Screening of Human Neurodevelopmental Risk

Neural organoids have revolutionized how human neurodevelopmental disorders (NDDs) are studied. Yet, their utility for screening chemical hazards and prospective therapeutics for NDDs is limited by a lack of morphological reproducibility and cost-effective scalability. Here, we describe the RosetteArray platform, which can be used as an off-the-shelf, 96-well plate assay that standardizes incipient forebrain and spinal cord organoid morphogenesis as adherent, micropatterned, 3-D, singularly polarized neural rosette tissues ([~]200 and [~]800 per well, respectively). Seeded directly from cryopreserved human pluripotent stem cells, RosetteArrays are cultured over 6-8 days and fixed, immunostained and imaged in situ to enable artificial intelligence-based quantitative analysis. By screening the inception of [~]75,000 neural organoids throughout this manuscript, we provide proof-of-concept demonstrations of the platforms utility for detecting developmental neurotoxicity hazard and screening genetic and environmental factors known to cause clinical Neural Tube Defect risk. Given the documented perturbation of rosette morphogenesis in neural organoid models of several NDDs, the RosetteArray platform could enable quantitative high-throughput screening (qHTS) of human neurodevelopmental risk across regulatory and precision medicine applications.

neuroscience↗

bioRxiv2024

Screening and characterization of 133 physiologically-relevant environmental chemicals for reproductive toxicity

Reproduction is a functional outcome that relies on complex cellular, tissue, and organ interactions that span the developmental period to adulthood. Thus, the assessment of its disruption by environmental chemicals is remarkably painstaking in conventional toxicological animal models and does not scale up to the number of chemicals present in our environment and requiring testing. We adapted a previously described low-throughput in vivo chromosome segregation assay using C. elegans predictive of reproductive toxicity and leveraged available public data sources (ToxCast, ICE) to screen and characterize 133 physiologically-relevant chemicals in a high-throughput manner. The screening outcome was further validated in a second, independent in vivo assay assessing embryonic viability. In total, 13 chemicals were classified as reproductive toxicants with the two most active chemicals belonging to the large family of Quaternary Ammonium Compounds (QACs) commonly used as disinfectants but with limited available reproductive toxicity data. We compared the results from the C. elegans assay with ToxCast in vitro data compiled from 700+ cell response assays and 300+ signaling pathways-based assays. We did not observe a difference in the bioactivity or in average potency (AC50) between the top and bottom chemicals. However, the intended target categories were significantly different between the classified chemicals with, in particular, an over-representation of steroid hormone targets for the high Z-score chemicals. Taken together, these results point to the value of in vivo models that scale to high-throughput level for reproductive toxicity assessment and to the need to prioritize the assessment of QACs impacts on reproduction.

pharmacology and toxicology↗

bioRxiv2023

Distinct transcriptional profiles of maternal and fetal placental macrophages at term are associated with gravidity

Maternal intervillous monocytes (MIMs) and fetal Hofbauer cells (HBCs) are myeloid-derived immune cells at the maternal-fetal interface. Little is known regarding the molecular phenotypes and roles of these distinct monocyte/macrophage populations. Here, we used RNA sequencing to investigate the transcriptional profiles of MIMs and HBCs in six normal term pregnancies. Our analyses revealed distinct transcriptomes of MIMs and HBCs. Genes involved in differentiation and cell organization pathways were more highly expressed in MIMs vs. HBCs. In contrast, HBCs had higher expression of genes involved in inflammatory responses and cell surface receptor signaling. Maternal gravidity influenced monocyte programming, as expression of pro-inflammatory molecules was significantly higher in MIMs from multigravidas compared to primigravidas. In HBCs, multigravidas displayed enrichment of gene pathways involved in cell-cell signaling and differentiation. In summary, our results demonstrated that MIMs and HBCs have highly divergent transcriptional signatures, reflecting their distinct origins, locations, functions, and roles in inflammatory responses. Our data further suggested that maternal gravidity influences the gene signatures of MIMs and HBCs, potentially modulating the interplay between tolerance and trained immunity. The phenomenon of reproductive immune memory may play a novel role in the differential susceptibility of primigravidas to pregnancy complications.

immunology↗

bioRxiv2019

Exautomate: A user-friendly tool for region-based rare variant association analysis (RVAA)

Region-based rare variant association analysis (RVAA) is a popular method to study rare genetic variation in large datasets, especially in the context of complex traits and diseases. Although this method shows great promise in increasing our understanding of the genetic architecture of complex phenotypes, performing a region-based RVAA can be challenging. The sequence kernel association test (SKAT) can be used to perform this analysis, but its inputs and modifiable parameters can be extremely overwhelming and may lead to results that are difficult to reproduce. We have developed a software package called \"Exautomate\" that contains the tools necessary to run a region-based RVAA using SKAT and is easy-to-use for any researcher, regardless of their previous bioinformatic experiences. In this report, we discuss the utilities of Exautomate and provide detailed examples of implementing our package. Importantly, we demonstrate a proof-of-principle analysis using a previously studied cohort of 313 familial hypercholesterolemia (FH) patients. Our results show an increased burden of rare variants in genes known to cause FH, thereby demonstrating a successful region-based RVAA using Exautomate. With our easy-to-use package, we hope researchers will be able to perform reproducible region-based RVAA to further our collective understanding behind the genetics of complex traits and diseases.

bioinformatics↗