Viral Kinetics Model of SARS-CoV-2 Infection Informs Drug Discovery, Clinical Dose, and Regimen Selection.

Quantitative systems pharmacology (QSP) has been an important tool to project safety and efficacy of novel or repurposed therapies for the SARS-CoV-2 virus. Here, we present a QSP modeling framework to predict response to antiviral therapeutics with three mechanisms of action (MoA): cell entry inhibitors, anti-replicatives, and neutralizing biologics. We parameterized three distinct model structures describing virus-host interaction by fitting to published viral kinetics data of untreated COVID-19 patients. The models were used to test theoretical behaviors and map therapeutic design criteria of the different MoAs, identifying the most rapid and robust antiviral activity from neutralizing biologic and anti-replicative MoAs. We found good agreement between model predictions and clinical viral load reduction observed with anti-replicative nirmatrelvir/ritonavir (Paxlovid®) and neutralizing biologics bamlanivimab and casirivimab/imdevimab (REGEN-COV®), building confidence in the modeling framework to inform a dose selection. Finally, the model was applied to predict antiviral response with ensovibep, a novel DARPin therapeutic designed as a neutralizing biologic. We developed a new in silico measure of antiviral activity, area under the curve (AUC) of free spike protein concentration, as a metric with larger dynamic range than viral load reduction. By benchmarking to bamlanivimab predictions, we justified dose levels of 75, 225, and 600 mg ensovibep to be administered intravenously in a Phase 2 clinical investigation. Upon trial completion, we found model predictions to be in good agreement with the observed patient data. These results demonstrate the utility of this modeling framework to guide the development of novel antiviral therapeutics.

An affinity for brainstem microglia in pediatric high-grade gliomas of brainstem origin.

Background: High-grade gliomas (HGG) in children have a devastating prognosis and occur in a remarkable spatiotemporal pattern. Diffuse midline gliomas (DMG), including diffuse intrinsic pontine gliomas (DIPG), typically occur in mid-childhood, while cortical HGGs are more frequent in older children and adults. The mechanisms behind this pattern are not clear. Methods: We used mouse organotypic slice cultures and glial cell cultures to test the impact of the microenvironment on human DIPG cells. Comparing the expression between brainstem and cortical microglia identified differentially expressed secreted proteins. The impact of some of these proteins on DIPGs was tested. Results: DIPGs, pediatric HGGs of brainstem origin, survive and divide more in organotypic slice cultures originating in the brainstem as compared to the cortex. Moreover, brainstem microglia are better able to support tumors of brainstem origin. A comparison between the two microglial populations revealed differentially expressed genes. One such gene, interleukin-33 (IL33), is highly expressed in the pons of young mice and its DIPG receptor is upregulated in this context. Consistent with this observation, the expression levels of IL33 and its receptor, IL1RL1, are higher in DIPG biopsies compared to low-grade cortical gliomas. Furthermore, IL33 can enhance proliferation and clonability of HGGs of brainstem origin, while blocking IL33 in brainstem organotypic slice cultures reduced the proliferation of these tumor cells. Conclusions: Crosstalk between DIPGs and the brainstem microenvironment, in particular microglia, through IL33 and other secreted factors, modulates spatiotemporal patterning of this HGG and could prove to be an important future therapeutic target.

Computational Interspecies Translation Between Alzheimer's Disease Mouse Models and Human Subjects Identifies Innate Immune Complement, TYROBP, and TAM Receptor Agonist Signatures, Distinct From Influences of Aging.

Mouse models are vital for preclinical research on Alzheimer's disease (AD) pathobiology. Many traditional models are driven by autosomal dominant mutations identified from early onset AD genetics whereas late onset and sporadic forms of the disease are predominant among human patients. Alongside ongoing experimental efforts to improve fidelity of mouse model representation of late onset AD, a computational framework termed Translatable Components Regression (TransComp-R) offers a complementary approach to leverage human and mouse datasets concurrently to enhance translation capabilities. We employ TransComp-R to integratively analyze transcriptomic data from human postmortem and traditional amyloid mouse model hippocampi to identify pathway-level signatures present in human patient samples yet predictive of mouse model disease status. This method allows concomitant evaluation of datasets across different species beyond observational seeking of direct commonalities between the species. Additional linear modeling focuses on decoupling disease signatures from effects of aging. Our results elucidated mouse-to-human translatable signatures associated with disease: excitatory synapses, inflammatory cytokine signaling, and complement cascade- and TYROBP-based innate immune activity; these signatures all find validation in previous literature. Additionally, we identified agonists of the Tyro3 / Axl / MerTK (TAM) receptor family as significant contributors to the cross-species innate immune signature; the mechanistic roles of the TAM receptor family in AD merit further dedicated study. We have demonstrated that TransComp-R can enhance translational understanding of relationships between AD mouse model data and human data, thus aiding generation of biological hypotheses concerning AD progression and holding promise for improved preclinical evaluation of therapies.

Human physiomimetic model integrating microphysiological systems of the gut, liver, and brain for studies of neurodegenerative diseases.

Slow progress in the fight against neurodegenerative diseases (NDs) motivates an urgent need for highly controlled in vitro systems to investigate organ-organ- and organ-immune-specific interactions relevant for disease pathophysiology. Of particular interest is the gut/microbiome-liver-brain axis for parsing out how genetic and environmental factors contribute to NDs. We have developed a mesofluidic platform technology to study gut-liver-cerebral interactions in the context of Parkinson's disease (PD). It connects microphysiological systems (MPSs) of the primary human gut and liver with a human induced pluripotent stem cell-derived cerebral MPS in a systemically circulated common culture medium containing CD4+ regulatory T and T helper 17 cells. We demonstrate this approach using a patient-derived cerebral MPS carrying the PD-causing A53T mutation, gaining two important findings: (i) that systemic interaction enhances features of in vivo-like behavior of cerebral MPSs, and (ii) that microbiome-associated short-chain fatty acids increase expression of pathology-associated pathways in PD.

Quantitative phosphoproteomics uncovers dysregulated kinase networks in Alzheimer's disease.

Alzheimer's disease (AD) is a form of dementia characterized by amyloid-ß plaques and tau neurofibrillary tangles that progressively disrupt neural circuits in the brain. The signaling networks underlying AD pathological changes are poorly characterized at the phosphoproteome level. Using mass spectrometry, we analyzed the proteome and tyrosine, serine and threonine phosphoproteomes of temporal cortex tissue from patients with AD and aged-matched controls. We identified cocorrelated peptide clusters that were linked to varying levels of phospho-tau, oligodendrocyte, astrocyte, microglia and neuron pathologies. We found that neuronal synaptic protein abundances were strongly anti-correlated with markers of microglial reactivity. We also observed that phosphorylation sites on kinases targeting tau and other new signaling factors were correlated with these peptide modules. Finally, we used data-driven statistical modeling to identify individual peptides and peptide clusters that were predictive of AD histopathologies. Together, these results build a map of pathology-associated phosphorylation signaling events occurring in AD.

Contractile force generation by 3D hiPSC-derived cardiac tissues is enhanced by rapid establishment of cellular interconnection in matrix with muscle-mimicking stiffness.

Engineering 3D human cardiac tissues is of great importance for therapeutic and pharmaceutical applications. As cardiac tissue substitutes, extracellular matrix-derived hydrogels have been widely explored. However, they exhibit premature degradation and their stiffness is often orders of magnitude lower than that of native cardiac tissue. There are no reports on establishing interconnected cardiomyocytes in 3D hydrogels at physiologically-relevant cell density and matrix stiffness. Here we bioengineer human cardiac microtissues by encapsulating human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) in chemically-crosslinked gelatin hydrogels (1.25 × 108/mL) with tunable stiffness and degradation. In comparison to the cells in high stiffness (16 kPa)/slow degrading hydrogels, hiPSC-CMs in low stiffness (2 kPa)/fast degrading and intermediate stiffness (9 kPa)/intermediate degrading hydrogels exhibit increased intercellular network formation, α-actinin and connexin-43 expression, and contraction velocity. Only the 9 kPa microtissues exhibit organized sarcomeric structure and significantly increased contractile stress. This demonstrates that muscle-mimicking stiffness together with robust cellular interconnection contributes to enhancement in sarcomeric organization and contractile function of the engineered cardiac tissue. This study highlights the importance of intercellular connectivity, physiologically-relevant cell density, and matrix stiffness to best support 3D cardiac tissue engineering.