Microglia mediate chronic neuroinflammation following central nervous system (CNS) disease or injury, and in doing so, damage the local brain environment by impairing recovery and contributing to disease processes. Microglia are critically dependent on signaling through the colony-stimulating factor 1 receptor (CSF1R) and can be eliminated via administration of CSF1R inhibitors. Resolving chronic neuroinflammation represents a universal goal for CNS disorders, but long-term microglial elimination may not be amenable to clinical use. Notably, withdrawal of CSF1R inhibitors stimulates new microglia to fully repopulate the CNS, affording an opportunity to renew this cellular compartment. To that end, we have explored the effects of acute microglial elimination, followed by microglial repopulation, in a mouse model of extensive neuronal loss. Neuronal loss leads to a prolonged neuroinflammatory response, characterized by the presence of swollen microglia expressing CD68 and CD45, as well as elevated levels of cytokines, chemokines, complement, and other inflammatory signals. These collective responses are largely resolved by microglial repopulation. Furthermore, microglial repopulation promotes functional recovery in mice, with elevated plus maze performance matching that of uninjured mice, despite the loss of 80% of hippocampal neurons. Analyses of synaptic surrogates revealed increases in PSD95 and synaptophysin puncta with microglial repopulation, suggesting that these cells sculpt and regulate the synaptic landscape. Thus, our results show that short-term microglial elimination followed by repopulation may represent a clinically feasible and novel approach to resolve neuroinflammatory events and promote brain recovery.

Alzheimer's is a crippling neurodegenerative disease that largely affects aged individuals. Decades of research have highlighted age-related changes in calcium homeostasis that occur before and throughout the duration of the disease, and the contributions of such dysregulation to Alzheimer's disease pathogenesis. We report an age-related decrease in expression of the CaV3.1 T-type calcium channel at the level of messenger RNA and protein in both humans and mice that is exacerbated with the presence of Alzheimer's disease. Downregulating T-type calcium channels in N2a cells and the 3xTg-AD mouse model of Alzheimer's disease, by way of pharmacologic inhibition with NNC-55-0396, results in a rapid increase in amyloid beta production via reductions in non-amyloidogenic processing, whereas genetic overexpression of the channel in human embryonic kidney cells expressing amyloid precursor protein produces complementary effects. The age-related decline in CaV3.1 expression may therefore contribute to a pro-amyloidogenic environment in the aging brain and represents a novel opportunity to intervene in the course of Alzheimer's disease pathogenesis.

Antibodies targeting specific antigens are widely utilized in biological research to investigate protein interactions or to quantify target antigens. Here, we introduce antigen-antibody proximity labeling (AAPL), a novel method to map the antigen interaction sites as well as interactors of antibody-targeted proteins. As a proof of concept, AAPL was demonstrated using sodium/potassium transporting ATPase (ATP1A1) and epidermal growth factor receptor 2 (ERBB2)-specific antibodies that were modified with an Fe(iii) catalytic probe. Once bound to their target proteins, Fe(iii)-induced catalytic oxidation occurred in proximity of the antigen's epitope. Oxidative proteomic analysis was then used to determine the degree of oxidation, the site of oxidation within the targeted antigen, and the interacting proteins that were in close proximity to the targeted antigen. An AAPL score was generated for each protein yielding the specificity of the oxidation and proximity of the interacting protein to the target antigen. As a final demonstration of its utility, the AAPL approach was applied to map the interactors of liver-intestine-cadherin (CDH17) in colon cancer cells.

In addition to amyloid-β plaque and tau neurofibrillary tangle deposition, neuroinflammation is considered a key feature of Alzheimer's disease pathology. Inflammation in Alzheimer's disease is characterized by the presence of reactive astrocytes and activated microglia surrounding amyloid plaques, implicating their role in disease pathogenesis. Microglia in the healthy adult mouse depend on colony-stimulating factor 1 receptor (CSF1R) signalling for survival, and pharmacological inhibition of this receptor results in rapid elimination of nearly all of the microglia in the central nervous system. In this study, we set out to determine if chronically activated microglia in the Alzheimer's disease brain are also dependent on CSF1R signalling, and if so, how these cells contribute to disease pathogenesis. Ten-month-old 5xfAD mice were treated with a selective CSF1R inhibitor for 1 month, resulting in the elimination of ∼80% of microglia. Chronic microglial elimination does not alter amyloid-β levels or plaque load; however, it does rescue dendritic spine loss and prevent neuronal loss in 5xfAD mice, as well as reduce overall neuroinflammation. Importantly, behavioural testing revealed improvements in contextual memory. Collectively, these results demonstrate that microglia contribute to neuronal loss, as well as memory impairments in 5xfAD mice, but do not mediate or protect from amyloid pathology.

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.