Biology subjects

Davis, P.

Publications and source records attributed to Davis, P..

10 recordsLinked to original sources

bioRxiv2024

Rapid oxygen titration following cardiopulmonary resuscitation mitigates cerebral overperfusion and striatal mitochondrial dysfunction in asphyxiated newborn lambs

Asphyxiated neonates must have oxygenation rapidly restored to limit ongoing hypoxic-ischemic injury. However, the effects of transient hyperoxia after return of spontaneous circulation (ROSC) are poorly understood. We randomly allocated acutely asphyxiated, near-term lambs to cardiopulmonary resuscitation in 100% oxygen ("standard oxygen", n=8) or air (n=7) until 5 minutes after ROSC, or to resuscitation in 100% oxygen immediately weaned to air upon ROSC ("rapid-wean", n=7). From 5 minutes post-ROSC, oxygen was titrated to target preductal oxygen saturation between 90-95%. Cerebral tissue oxygenation was transiently but markedly elevated following ROSC in the standard oxygen group compared to the air and rapid-wean groups. The air group had a delayed rise in cerebral tissue oxygenation from 5 minutes after ROSC coincident with up-titration of oxygen. These alterations in oxygen kinetics corresponded with similar overshoots in cerebral perfusion (pressure and flow), indicating a physiological mechanism. Transient cerebral tissue hyperoxia in the standard oxygen and air groups resulted in significant alterations in mitochondrial respiration and dynamics, relative to the rapid-wean group. Overall, rapid-wean of oxygen following ROSC preserved striatal mitochondrial respiratory function and reduced the expression of genes involved in free radical generation and apoptosis, suggesting a potential therapeutic strategy to limit cerebral reperfusion injury.

physiology↗

bioRxiv2024

Endogenous opioids facilitate stress-induced binge eating via an insular cortex-claustrum pathway

Stress has been shown to promote the development and persistence of binge eating behaviors. However, the neural circuit mechanisms for stress-induced binge-eating behaviors are largely unreported. The endogenous dynorphin (dyn)/kappa opioid receptor (KOR) opioid neuropeptide system has been well established to be a crucial mediator of the anhedonic component of stress. Here, we aimed to dissect the basis of dynorphinergic control of stress-induced binge-like eating behavior. We first established a mouse behavioral model for stress-induced binge-like eating behaviors. We found that mice exposed to stress increased their food intake of familiar palatable food (high fat, high sugar, HPD) compared to non-stressed mice. Following a brain-wide analysis, we isolated robust cFos-positive cells in the Claustrum (CLA), a subcortical structure with highly abundant KOR expression, following stress-induced binge-eating behavior. We report that KOR signaling in CLA is necessary for this elevated stress-induced binge eating behavior using local pharmacology and local deletion of KOR. In vivo calcium recordings using fiber photometry revealed a disinhibition circuit structure in the CLA during the initiation of HPD feeding bouts. We further established the dynamics of endogenous dynorphinergic control of this behavior using a genetically encoded dynorphin biosensor, Klight. Combined with 1-photon single-cell calcium imaging, we report significant heterogeneity with the CLA population during stress-induced binge eating and such behavior attenuates local dynorphin tone. Furthermore, we isolate the anterior Insular cortex (aIC) as the potential source of endogenous dynorphin afferents in the CLA. By characterizing neural circuits and peptidergic mechanisms within the CLA, we uncover a pathway that implicates endogenous opioid regulation stress-induced binge eating.

neuroscience↗

bioRxiv2024

Symmetry in levels of axon-axon homophilic adhesion establishes topography in the corpus callosum and development of connectivity between brain hemispheres

Specific and highly diverse connectivity between functionally specialized regions of the nervous system is controlled at multiple scales, from anatomically organized connectivity following macroscopic axon tracts to individual axon target-finding and synapse formation. Identifying mechanisms that enable entire subpopulations of related neurons to project their axons with regional specificity within stereotyped tracts to form appropriate long-range connectivity is key to understanding brain development, organization, and function. Here, we investigate how axons of the cerebral cortex form precise connections between the two cortical hemispheres via the corpus callosum. We identify topographic principles of the developing trans-hemispheric callosal tract that emerge through intrinsic guidance executed by growing axons in the corpus callosum within the first postnatal week in mice. Using micro-transplantation of regionally distinct neurons, subtype-specific growth cone purification, subcellular proteomics, and in utero gene manipulation, we investigate guidance mechanisms of transhemispheric axons. We find that adhesion molecule levels instruct tract topography and target field guidance. We propose a model in which transcallosal axons in the developing brain perform a "handshake" that is guided through co-fasciculation with symmetric contralateral axons, resulting in the stereotyped homotopic connectivity between the brains hemispheres.

neuroscience↗

bioRxiv2023

Modeling an ultra-rare epilepsy variant in wildtype mice with in utero prime editing

Generating animal models that mirror a patients seizures within clinically-useful timeframes is an important step toward advancing precision medicine for genetic epilepsies. Here we report a somatic cell genome editing approach that rapidly incorporated a patients genomic variant into mice, which developed seizures recapitulating elements of the patients pathology. This approach offers a versatile in vivo platform for clinical, preclinical, and basic research applications, including tailoring pharmacotherapy, assessing variants of uncertain significance, and screening compounds to develop drugs for rare epilepsies. As proof-of-principle, we modeled an epilepsy patient with an ultra-rare variant of the NMDA receptor subunit GRIN2A using prime editing in utero directly in the developing brain of wild-type mice. This methodology achieved high-fidelity genome editing in vivo sufficient to induce frequent spontaneous seizures without necessitating germline modification or extensive breeding. Leveraging the speed and versatility of this approach, we propose a generalizable workflow to generate bedside-to-bench animal models of individual patients within weeks. This advance holds promise for providing a cost-effective, expedient in vivo testing platform that reduces barriers to access for precision medicine, and accelerates drug development for rare and neglected neurological conditions.

neuroscience↗

bioRxiv2023

Structure-Property-Processing Correlations of Graphene Bioscaffolds for Proliferation and Differentiation of C2C12 Cells

Graphene - an atomically thin layer of carbon atoms arranged in a hexagonal lattice - has gained interest as a bioscaffold for tissue engineering due to its exceptional mechanical, electrical, and thermal properties. Graphenes structure and properties are tightly coupled to synthesis and processing conditions, yet their influence on biomolecular interactions at the graphene-cell interface remains unclear. In this study, C2C12 cells were grown on graphene bioscaffolds with specific structure-property- processing-performance (SP3) correlations. Bioscaffolds were prepared using three different methods - chemical vapor deposition (CVD), sublimation of silicon carbide (SiC), and printing of liquid phase exfoliated graphene. To investigate the biocompatibility of each scaffold, cellular morphology and gene expression patterns were investigated using the bipotential mouse C2C12 cell line. Using a combination of fluorescence microscopy and qRT-PCR, we demonstrate that graphene production methods determine the structural and mechanical properties of the resulting bioscaffold, which in turn determine cell morphology, gene expression patterns, and cell differentiation fate. Therefore, production methods and resultant structure and properties of graphene bioscaffolds must be chosen carefully when considering graphene as a bioscaffold for musculoskeletal tissue engineering.

bioengineering↗

bioRxiv2022

Performance of novel antibodies for lipoarabinomannan to develop diagnostic tests for Mycobacterium tuberculosis

Lipoarabinomannan (LAM), a component of the Mycobacterium tuberculosis (MTB) cell wall, is detectable in the urine of MTB infected patients with active tuberculosis (TB). LAM-specific antibodies (Igs) have been developed by a variety of traditional and recombinant methods for potential use in a rapid diagnostic test (RDT). We evaluated the analytical performance of the TB LAM Igs to identify pairs that offer superior performance over existing urine LAM tests. We assessed 25 new and 4 existing Igs in a matrixed format using a multiplex electrochemiluminescence-based liquid immunoassay. A total of 841 paired Ig combinations were challenged with in vitro cultured LAM (cLAM) derived from MTB strains representing diverse phylogenetic lineages, alongside urinary LAM (uLAM) from the urine of adults with active pulmonary TB. Analytical sensitivity of down-selected Ig pairs was determined using MTB Aoyama-B cLAM, while diagnostic accuracy was determined using clinical samples. When testing cLAM, the reactivity of Ig pairs was similar across MTB lineages 1-4 but lineage 5:6 had significantly more reactivity among Ig pairs. Overall, 41 Ig pairs had a strong binding affinity to cLAM, as compared to the reference pair of S4-20/A194-01, and 28 Ig pairs therein exhibited a strong affinity for both cLAM and uLAM. Retrospective testing on clinical urine specimens demonstrated varying sensitivities (12-80%) and specificities (14-100%). The five top pairs had a similar analytical limit of detection to the reference pair but in four instances, the sensitivity and specificity with clinical uLAM samples was poor. Overall, epitopes presented by uLAM are different from cLAM, which may affect antibody performance when testing uLAM in patient samples. Several new Ig pairs had similar ranges of high sensitivity to cLAM but overall, there were no new candidate Ig pairs identified in this round of screening with increased performance with uLAM as compared to an existing optimal pair.

microbiology↗

bioRxiv2021

Fast off-rate CD229 chimeric antigen receptor T cells efficiently target multiple myeloma, spare T cells, and exhibit reduced trogocytosis

T cells expressing chimeric antigen receptors have shown remarkable therapeutic activity against different types of cancer. However, their wider use has been hampered by the potential for life-threatening toxicities due to the unintended targeting of healthy cells expressing low levels of the targeted antigen. We have now developed an affinity-tuning approach for the generation of minimally modified, low-affinity antibody variants derived from existing high-affinity antibodies. Using this approach, we engineered low affinity variants of the fully human CD229-specific antibody 2D3. Parental 2D3 originally efficiently targeted multiple myeloma cells but also healthy T cells expressing low levels of CD229. We demonstrate that CAR T cells based on a low affinity variant of 2D3, engineered to also express CJUN to increase CAR T cell expansion, maintain the parental antibodys anti-tumor activity but lack its targeting of healthy T cells in vitro and in vivo. In addition, we found that low affinity CD229 CAR T cells show reduced trogocytosis potentially augmenting CAR T cell persistence. The fast off-rate CAR produced using our affinity tuning approach eliminates a key liability of CD229 CAR T cells and paves the way for the effective and safe treatment of patients with multiple myeloma and other lymphoid malignancies. One sentence summaryRational T cell engineering yields low affinity CD229 CAR T cells overexpressing CJUN, which maintain the parental cells anti-tumor activity but eliminate killing of healthy T cells, increasing CAR T cell expansion, and decreasing trogocytosis.

bioengineering↗

bioRxiv2021

A Genotype-to-Phenotype Modeling Framework to Predict Human Pathogenicity of Novel Coronaviruses

Leveraging prior viral genome sequencing data to make predictions on whether an unknown, emergent virus harbors a phenotype-of-concern has been a long-sought goal of genomic epidemiology. A predictive phenotype model built from nucleotide-level information alone has previously been considered un-tenable with respect to RNA viruses due to the ultra-high intra-sequence variance of their genomes, even within closely related clades. Building from our prior work developing a degenerate k-mer method to accommodate this high intra-sequence variation of RNA virus genomes for modeling frameworks, and leveraging a taxonomic group-shuffle-split paradigm on complete coronavirus assemblies from prior to October 2018, we trained multiple regularized logistic regression classifiers at the nucleotide k-mer level capable of accurately predicting withheld SARS-CoV-2 genome sequences as human pathogens and accurately predicting withheld Swine Acute Diarrhea Syndrome coronavirus (SADS-CoV) genome sequences as non-human pathogens. LASSO feature selection identified several degenerate nucleotide predictor motifs with high model coefficients for the human pathogen class that were present across widely disparate classes of coronaviruses. However, these motifs differed in which genes they were present in, what specific codons were used to encode them, and what the translated amino acid motif was. This emphasizes the importance of a phenetic view of emerging pathogenic RNA viruses, as opposed to the canonical phylogenetic interpretations most-commonly used to track and manage viral zoonoses. Applying our model to more recent Orthocoronavirinae genomes deposited since October 2018 yields a novel contextual view of pathogen-potential across bat-related, canine-related, porcine-related, and rodent-related coronaviruses and critical adaptations which may have contributed to the emergence of the pandemic SARS-CoV-2 virus. Finally, we discuss the utility of these predictive models (and their associated predictor motifs) to novel biosurveillance protocols that substantially increase the pound-for-pound information content of field-collected sequencing data and make a strong argument for the necessity of routine collection and sequencing of zoonotic viruses.

bioinformatics↗

bioRxiv2021

Comparative assessment of genes driving cancer and somatic evolution.

Genetic alterations of somatic cells can drive nonmalignant clone formation and promote cancer initiation. However, the link between these processes remains unclear hampering our understanding of tissue homeostasis and cancer development. Here we collect a literature-based repertoire of 3355 well-known or predicted drivers of cancer and noncancer somatic evolution in 122 cancer types and 12 noncancer tissues. Mapping the alterations of these genes in 7953 pancancer samples reveals that, despite the large size, the known compendium of drivers is still incomplete and biased towards frequently occurring coding mutations. High overlap exists between drivers of cancer and noncancer somatic evolution, although significant differences emerge in their recurrence. We confirm and expand the unique properties of drivers and identify a core of evolutionarily conserved and essential genes whose germline variation is strongly counter-selected. Somatic alteration in even one of these genes is sufficient to drive clonal expansion but not malignant transformation. Our study offers a comprehensive overview of our current understanding of the genetic events initiating clone expansion and cancer revealing significant gaps and biases that still need to be addressed. The compendium of cancer and noncancer somatic drivers, their literature support and properties are accessible at http://www.network-cancer-genes.org/.

cancer biology↗

bioRxiv2020

Vorpal: A Novel RNA Virus Feature-Extraction Algorithm Demonstrated Through Interpretable Genotype-to-Phenotype Linear Models

In the analysis of genomic sequence data, so-called "alignment free" approaches are often selected for their relative speed compared to alignment-based approaches, especially in the application of distance comparisons and taxonomic classification1,2,3,4. These methods are typically reliant on excising K-length substrings of the input sequence, called K-mers5. In the context of machine learning, K-mer based feature vectors have been used in applications ranging from amplicon sequencing classification to predictive modeling for antimicrobial resistance genes6,7,8. This can be seen as an analogy of the "bag-of-words" model successfully employed in natural language processing and computer vision for document and image classification9,10. Feature extraction techniques from natural language processing have previously been analogized to genomics data11; however, the "bag-of-words" approach is brittle in the RNA virus space due to the high intersequence variance and the exact matching requirement of K-mers. To reconcile the simplicity of "bag-of-words" methods with the complications presented by the intrinsic variance of RNA virus space, a method to resolve the fragility of extracted K-mers in a way that faithfully reflects an underlying biological phenomenon was devised. Our algorithm, Vorpal, allows the construction of interpretable linear models with clustered, representative degenerate K-mers as the input vector and, through regularization, sparse predictors of binary phenotypes as the output. Here, we demonstrate the utility of Vorpal by identifying nucleotide-level genomic motif predictors for binary phenotypes in three separate RNA virus clades; human pathogen vs. non-human pathogen in Orthocoronavirinae, hemorrhagic fever causing vs. non-hemorrhagic fever causing in Ebolavirus, and human-host vs. non-human host in Influenza A. The capacity of this approach for in silico identification of hypotheses which can be validated by direct experimentation, as well as identification of genomic targets for preemptive biosurveillance of emerging viruses, is discussed. The code is available for download at https://github.com/mriglobal/vorpal.

bioinformatics↗