Complement in the Brain: Contributions to Neuroprotection, Neuronal Plasticity, and Neuroinflammation.

The complement system is an ancient collection of proteolytic cascades with well-described roles in regulation of innate and adaptive immunity. With the convergence of a revolution in complement-directed clinical therapeutics, the discovery of specific complement-associated targetable pathways in the central nervous system, and the development of integrated multi-omic technologies that have all emerged over the last 15 years, precision therapeutic targeting in Alzheimer disease and other neurodegenerative diseases and processes appears to be within reach. As a sensor of tissue distress, the complement system protects the brain from microbial challenge as well as the accumulation of dead and/or damaged molecules and cells. Additional more recently discovered diverse functions of complement make it of paramount importance to design complement-directed neurotherapeutics such that the beneficial roles in neurodevelopment, adult neural plasticity, and neuroprotective functions of the complement system are retained.

Single substitution in H3.3G34 alters DNMT3A recruitment to cause progressive neurodegeneration.

Germline histone H3.3 amino acid substitutions, including H3.3G34R/V, cause severe neurodevelopmental syndromes. To understand how these mutations impact brain development, we generated H3.3G34R/V/W knock-in mice and identified strikingly distinct developmental defects for each mutation. H3.3G34R-mutants exhibited progressive microcephaly and neurodegeneration, with abnormal accumulation of disease-associated microglia and concurrent neuronal depletion. G34R severely decreased H3K36me2 on the mutant H3.3 tail, impairing recruitment of DNA methyltransferase DNMT3A and its redistribution on chromatin. These changes were concurrent with sustained expression of complement and other innate immune genes possibly through loss of non-CG (CH) methylation and silencing of neuronal gene promoters through aberrant CG methylation. Complement expression in G34R brains may lead to neuroinflammation possibly accounting for progressive neurodegeneration. Our study reveals that H3.3G34-substitutions have differential impact on the epigenome, which underlie the diverse phenotypes observed, and uncovers potential roles for H3K36me2 and DNMT3A-dependent CH-methylation in modulating synaptic pruning and neuroinflammation in post-natal brains.

Rapid phagosome isolation enables unbiased multiomic analysis of human microglial phagosomes.

Microglia are the resident macrophages of the central nervous system (CNS). Their phagocytic activity is central during brain development and homeostasis-and in a plethora of brain pathologies. However, little is known about the composition, dynamics, and function of human microglial phagosomes under homeostatic and pathological conditions. Here, we developed a method for rapid isolation of pure and intact phagosomes from human pluripotent stem cell-derived microglia under various in vitro conditions, and from human brain biopsies, for unbiased multiomic analysis. Phagosome profiling revealed that microglial phagosomes were equipped to sense minute changes in their environment and were highly dynamic. We detected proteins involved in synapse homeostasis, or implicated in brain pathologies, and identified the phagosome as the site where quinolinic acid was stored and metabolized for de novo nicotinamide adenine dinucleotide (NAD+) generation in the cytoplasm. Our findings highlight the central role of phagosomes in microglial functioning in the healthy and diseased brain.

Microglia-synapse engulfment via PtdSer-TREM2 ameliorates neuronal hyperactivity in Alzheimer's disease models.

Neuronal hyperactivity is a key feature of early stages of Alzheimer's disease (AD). Genetic studies in AD support that microglia act as potential cellular drivers of disease risk, but the molecular determinants of microglia-synapse engulfment associated with neuronal hyperactivity in AD are unclear. Here, using super-resolution microscopy, 3D-live imaging of co-cultures, and in vivo imaging of lipids in genetic models, we found that spines become hyperactive upon Aß oligomer stimulation and externalize phosphatidylserine (ePtdSer), a canonical "eat-me" signal. These apoptotic-like spines are targeted by microglia for engulfment via TREM2 leading to amelioration of Aß oligomer-induced synaptic hyperactivity. We also show the in vivo relevance of ePtdSer-TREM2 signaling in microglia-synapse engulfment in the hAPP NL-F knock-in mouse model of AD. Higher levels of apoptotic-like synapses in mice as well as humans that carry TREM2 loss-of-function variants were also observed. Our work supports that microglia remove hyperactive ePtdSer+ synapses in Aß-relevant context and suggest a potential beneficial role for microglia in the earliest stages of AD.

Phospholipid scramblase Xkr8 is required for developmental axon pruning via phosphatidylserine exposure.

The mature mammalian brain connectome emerges during development via the extension and pruning of neuronal connections. Glial cells have been identified as key players in the phagocytic elimination of neuronal synapses and projections. Recently, phosphatidylserine has been identified as neuronal "eat-me" signal that guides elimination of unnecessary input sources, but the associated transduction systems involved in such pruning are yet to be described. Here, we identified Xk-related protein 8 (Xkr8), a phospholipid scramblase, as a key factor for the pruning of axons in the developing mammalian brain. We found that mouse Xkr8 is highly expressed immediately after birth and required for phosphatidylserine exposure in the hippocampus. Mice lacking Xkr8 showed excess excitatory nerve terminals, increased density of cortico-cortical and cortico-spinal projections, aberrant electrophysiological profiles of hippocampal neurons, and global brain hyperconnectivity. These data identify phospholipid scrambling by Xkr8 as a central process in the labeling and discrimination of developing neuronal projections for pruning in the mammalian brain.

Neuron-Glia Signaling in Synapse Elimination.

Maturation of neuronal circuits requires selective elimination of synaptic connections. Although neuron-intrinsic mechanisms are important in this process, it is increasingly recognized that glial cells also play a critical role. Without proper functioning of these cells, the number, morphology, and function of synaptic contacts are profoundly altered, resulting in abnormal connectivity and behavioral abnormalities. In addition to their role in synaptic refinement, glial cells have also been implicated in pathological synapse loss and dysfunction following injury or nervous system degeneration in adults. Although mechanisms regulating glia-mediated synaptic elimination are still being uncovered, it is clear this complex process involves many cues that promote and inhibit the removal of specific synaptic connections. Gaining a greater understanding of these signals and the contribution of different cell types will not only provide insight into this critical biological event but also be instrumental in advancing knowledge of brain development and neural disease.

Microglia in Brain Development, Homeostasis, and Neurodegeneration.

Advances in human genetics have implicated a growing number of genes in neurodegenerative diseases, providing insight into pathological processes. For Alzheimer disease in particular, genome-wide association studies and gene expression studies have emphasized the pathogenic contributions from microglial cells and motivated studies of microglial function/dysfunction. Here, we summarize recent genetic evidence for microglial involvement in neurodegenerative disease with a focus on Alzheimer disease, for which the evidence is most compelling. To provide context for these genetic discoveries, we discuss how microglia influence brain development and homeostasis, how microglial characteristics change in disease, and which microglial activities likely influence the course of neurodegeneration. In all, we aim to synthesize varied aspects of microglial biology and highlight microglia as possible targets for therapeutic interventions in neurodegenerative disease.

The Microglial Innate Immune Receptor TREM2 Is Required for Synapse Elimination and Normal Brain Connectivity.

The triggering receptor expressed on myeloid cells 2 (TREM2) is a microglial innate immune receptor associated with a lethal form of early, progressive dementia, Nasu-Hakola disease, and with an increased risk of Alzheimer's disease. Microglial defects in phagocytosis of toxic aggregates or apoptotic membranes were proposed to be at the origin of the pathological processes in the presence of Trem2 inactivating mutations. Here, we show that TREM2 is essential for microglia-mediated synaptic refinement during the early stages of brain development. The absence of Trem2 resulted in impaired synapse elimination, accompanied by enhanced excitatory neurotransmission and reduced long-range functional connectivity. Trem2-/- mice displayed repetitive behavior and altered sociability. TREM2 protein levels were also negatively correlated with the severity of symptoms in humans affected by autism. These data unveil the role of TREM2 in neuronal circuit sculpting and provide the evidence for the receptor's involvement in neurodevelopmental diseases.

Interplay between autophagy and CncC regulates dendrite pruning in Drosophila.

Autophagy is essential for the turnover of damaged organelles and long-lived proteins. It is responsible for many biological processes such as maintaining brain functions and aging. Impaired autophagy is often linked to neurodevelopmental and neurodegenerative diseases in humans. However, the role of autophagy in neuronal pruning during development remains poorly understood. Here, we report that autophagy regulates dendrite-specific pruning of ddaC sensory neurons in parallel to local caspase activation. Impaired autophagy causes the formation of ubiquitinated protein aggregates in ddaC neurons, dependent on the autophagic receptor Ref(2)P. Furthermore, the metabolic regulator AMP-activated protein kinase and the insulin-target of rapamycin pathway act upstream to regulate autophagy during dendrite pruning. Importantly, autophagy is required to activate the transcription factor CncC (Cap "n" collar isoform C), thereby promoting dendrite pruning. Conversely, CncC also indirectly affects autophagic activity via proteasomal degradation, as impaired CncC results in the inhibition of autophagy through sequestration of Atg8a into ubiquitinated protein aggregates. Thus, this study demonstrates the important role of autophagy in activating CncC prior to dendrite pruning, and further reveals an interplay between autophagy and CncC in neuronal pruning.

MRSL: a causal network pruning algorithm based on GWAS summary data.

Causal discovery is a powerful tool to disclose underlying structures by analyzing purely observational data. Genetic variants can provide useful complementary information for structure learning. Recently, Mendelian randomization (MR) studies have provided abundant marginal causal relationships of traits. Here, we propose a causal network pruning algorithm MRSL (MR-based structure learning algorithm) based on these marginal causal relationships. MRSL combines the graph theory with multivariable MR to learn the conditional causal structure using only genome-wide association analyses (GWAS) summary statistics. Specifically, MRSL utilizes topological sorting to improve the precision of structure learning. It proposes MR-separation instead of d-separation and three candidates of sufficient separating set for MR-separation. The results of simulations revealed that MRSL had up to 2-fold higher F1 score and 100 times faster computing time than other eight competitive methods. Furthermore, we applied MRSL to 26 biomarkers and 44 International Classification of Diseases 10 (ICD10)-defined diseases using GWAS summary data from UK Biobank. The results cover most of the expected causal links that have biological interpretations and several new links supported by clinical case reports or previous observational literatures.

Microtubule remodelling as a driving force of axon guidance and pruning.

The establishment of neuronal connectivity relies on the microtubule (MT) cytoskeleton, which provides mechanical support, roads for axonal transport and mediates signalling events. Fine-tuned spatiotemporal regulation of MT functions by tubulin post-translational modifications and MT-associated proteins is critical for the coarse wiring and subsequent refinement of neuronal connectivity. The defective regulation of these processes causes a wide range of neurodevelopmental disorders associated with connectivity defects. This review focuses on recent studies unravelling how MT composition, post-translational modifications and associated proteins influence MT functions in axon guidance and/or pruning to build functional neuronal circuits. We here summarise experimental evidence supporting the key role of this network as a driving force for growth cone steering and branch-specific axon elimination. We further provide a global overview of the MT-interactors that tune developing axon behaviours, with a special emphasis on their emerging versatility in the regulation of MT dynamics/structure. Recent studies establishing the key and highly selective role of the tubulin code in the regulation of MT functions in axon pathfinding are also reported. Finally, our review highlights the emerging molecular links between these MT regulation processes and guidance signals that wire the nervous system.

Drosophila GSK3ß promotes microtubule disassembly and dendrite pruning in sensory neurons.

The evolutionarily conserved Glycogen Synthase Kinase 3ß (GSK3ß), a negative regulator of microtubules, is crucial for neuronal polarization, growth and migration during animal development. However, it remains unknown whether GSK3ß regulates neuronal pruning, which is a regressive process. Here, we report that the Drosophila GSK3ß homologue Shaggy (Sgg) is cell-autonomously required for dendrite pruning of ddaC sensory neurons during metamorphosis. Sgg is necessary and sufficient to promote microtubule depolymerization, turnover and disassembly in the dendrites. Although Sgg is not required for the minus-end-out microtubule orientation in dendrites, hyperactivated Sgg can disturb the dendritic microtubule orientation. Moreover, our pharmacological and genetic data suggest that Sgg is required to promote dendrite pruning at least partly via microtubule disassembly. We show that Sgg and Par-1 kinases act synergistically to promote microtubule disassembly and dendrite pruning. Thus, Sgg and Par-1 might converge on and phosphorylate a common downstream microtubule-associated protein(s) to disassemble microtubules and thereby facilitate dendrite pruning.

AMPK activates the Nrf2-Keap1 pathway to govern dendrite pruning via the insulin pathway in Drosophila.

During Drosophila metamorphosis, the ddaC dendritic arborisation sensory neurons selectively prune their larval dendrites in response to steroid hormone ecdysone signalling. The Nrf2-Keap1 pathway acts downstream of ecdysone signalling to promote proteasomal degradation and thereby dendrite pruning. However, how the Nrf2-Keap1 pathway is activated remains largely unclear. Here, we demonstrate that the metabolic regulator AMP-activated protein kinase (AMPK) plays a cell-autonomous role in dendrite pruning. Importantly, AMPK is required for Mical and Headcase expression and for activation of the Nrf2-Keap1 pathway. We reveal that AMPK promotes the Nrf2-Keap1 pathway and dendrite pruning partly via inhibition of the insulin pathway. Moreover, the AMPK-insulin pathway is required for ecdysone signalling to activate the Nrf2-Keap1 pathway during dendrite pruning. Overall, this study reveals an important mechanism whereby ecdysone signalling activates the Nrf2-Keap1 pathway via the AMPK-insulin pathway to promote dendrite pruning, and further suggests that during the nonfeeding prepupal stage metabolic alterations lead to activation of the Nrf2-Keap1 pathway and dendrite pruning.

Bayesian Phylogenetic Analysis on Multi-Core Compute Architectures: Implementation and Evaluation of BEAGLE in RevBayes With MPI.

Phylogenies are central to many research areas in biology and commonly estimated using likelihood-based methods. Unfortunately, any likelihood-based method, including Bayesian inference, can be restrictively slow for large datasets-with many taxa and/or many sites in the sequence alignment-or complex substitutions models. The primary limiting factor when using large datasets and/or complex models in probabilistic phylogenetic analyses is the likelihood calculation, which dominates the total computation time. To address this bottleneck, we incorporated the high-performance phylogenetic library BEAGLE into RevBayes, which enables multi-threading on multi-core CPUs and GPUs, as well as hardware specific vectorized instructions for faster likelihood calculations. Our new implementation of RevBayes+BEAGLE retains the flexibility and dynamic nature that users expect from vanilla RevBayes. In addition, we implemented native parallelization within RevBayes without an external library using the message passing interface (MPI); RevBayes+MPI. We evaluated our new implementation of RevBayes+BEAGLE using multi-threading on CPUs and 2 different powerful GPUs (NVidia Titan V and NVIDIA A100) against our native implementation of RevBayes+MPI. We found good improvements in speedup when multiple cores were used, with up to 20-fold speedup when using multiple CPU cores and over 90-fold speedup when using multiple GPU cores. The improvement depended on the data type used, DNA or amino acids, and the size of the alignment, but less on the size of the tree. We additionally investigated the cost of rescaling partial likelihoods to avoid numerical underflow and showed that unnecessarily frequent and inefficient rescaling can increase runtimes up to 4-fold. Finally, we presented and compared a new approach to store partial likelihoods on branches instead of nodes that can speed up computations up to 1.7 times but comes at twice the memory requirements.

Hybrid multimodal fusion for graph learning in disease prediction.

Graph neural networks (GNNs) have gained significant attention in disease prediction where the latent embeddings of patients are modeled as nodes and the similarities among patients are represented through edges. The graph structure, which determines how information is aggregated and propagated, plays a crucial role in graph learning. Recent approaches typically create graphs based on patients' latent embeddings, which may not accurately reflect their real-world closeness. Our analysis reveals that raw data, such as demographic attributes and laboratory results, offers a wealth of information for assessing patient similarities and can serve as a compensatory measure for graphs constructed exclusively from latent embeddings. In this study, we first construct adaptive graphs from both latent representations and raw data respectively, and then merge these graphs via weighted summation. Given that the graphs may contain extraneous and noisy connections, we apply degree-sensitive edge pruning and kNN sparsification techniques to selectively sparsify and prune these edges. We conducted intensive experiments on two diagnostic prediction datasets, and the results demonstrate that our proposed method surpasses current state-of-the-art techniques.

Pruning recurrent neural networks replicates adolescent changes in working memory and reinforcement learning.

Adolescent development is characterized by an improvement in multiple cognitive processes. While performance on cognitive operations improves during this period, the ability to learn new skills quickly, for example, a new language, decreases. During this time, there is substantial pruning of excitatory synapses in cortex and specifically in prefrontal cortex. We have trained a series of recurrent neural networks to solve a working memory task and a reinforcement learning (RL) task. Performance on both of these tasks is known to improve during adolescence. After training, we pruned the networks by removing weak synapses. Pruning was done incrementally, and the networks were retrained during pruning. We found that pruned networks trained on the working memory task were more resistant to distraction. The pruned RL networks were able to produce more accurate value estimates and also make optimal choices more consistently. Both results are consistent with developmental improvements on these tasks. Pruned networks, however, learned some, but not all, new problems more slowly. Thus, improvements in task performance can come at the cost of flexibility. Our results show that overproduction and subsequent pruning of synapses is a computationally advantageous approach to building a competent brain.

Oligodendrocyte precursor cells ingest axons in the mouse neocortex.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form. This physical transformation of neurons is facilitated by the engulfment and degradation of axonal branches and synapses by surrounding glial cells, including microglia and astrocytes. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia have made it difficult to define the contribution of these and other glial cell types to this crucial process. Here, we used large-scale, serial section transmission electron microscopy (TEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex, providing unprecedented resolution of their morphology and composition. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors, frequently surrounded small branches of axons. Numerous phagosomes and phagolysosomes (PLs) containing fragments of axons and vesicular structures were present inside their processes, suggesting that OPCs engage in axon pruning. Single-nucleus RNA sequencing from the developing mouse cortex revealed that OPCs express key phagocytic genes at this stage, as well as neuronal transcripts, consistent with active axon engulfment. Although microglia are thought to be responsible for the majority of synaptic pruning and structural refinement, PLs were ten times more abundant in OPCs than in microglia at this stage, and these structures were markedly less abundant in newly generated oligodendrocytes, suggesting that OPCs contribute substantially to the refinement of neuronal circuits during cortical development.

A role for axon-glial interactions and Netrin-G1 signaling in the formation of low-threshold mechanoreceptor end organs.

Low-threshold mechanoreceptors (LTMRs) and their cutaneous end organs convert light mechanical forces acting on the skin into electrical signals that propagate to the central nervous system. In mouse hairy skin, hair follicle-associated longitudinal lanceolate complexes, which are end organs comprising LTMR axonal endings that intimately associate with terminal Schwann cell (TSC) processes, mediate LTMR responses to hair deflection and skin indentation. Here, we characterized developmental steps leading to the formation of Aß rapidly adapting (RA)-LTMR and Aδ-LTMR lanceolate complexes. During early postnatal development, Aß RA-LTMRs and Aδ-LTMRs extend and prune cutaneous axonal branches in close association with nascent TSC processes. Netrin-G1 is expressed in these developing Aß RA-LTMR and Aδ-LTMR lanceolate endings, and Ntng1 ablation experiments indicate that Netrin-G1 functions in sensory neurons to promote lanceolate ending elaboration around hair follicles. The Netrin-G ligand (NGL-1), encoded by Lrrc4c, is expressed in TSCs, and ablation of Lrrc4c partially phenocopied the lanceolate complex deficits observed in Ntng1 mutants. Moreover, NGL-1-Netrin-G1 signaling is a general mediator of LTMR end organ formation across diverse tissue types demonstrated by the fact that Aß RA-LTMR endings associated with Meissner corpuscles and Pacinian corpuscles are also compromised in the Ntng1 and Lrrc4c mutant mice. Thus, axon-glia interactions, mediated in part by NGL-1-Netrin-G1 signaling, promote LTMR end organ formation.

Cost-effective genomic prediction of critical economic traits in sturgeons through low-coverage sequencing.

Low-coverage whole-genome sequencing (LCS) offers a cost-effective alternative for sturgeon breeding, especially given the lack of SNP chips and the high costs associated with whole-genome sequencing. In this study, the efficiency of LCS for genotype imputation and genomic prediction was assessed in 643 sequenced Russian sturgeons (∼13.68×). The results showed that using BaseVar+STITCH at a sequencing depth of 2× with a sample size larger than 300 resulted in the highest genotyping accuracy. In addition, when the sequencing depth reached 0.5× and SNP density was reduced to 50 K through linkage disequilibrium pruning, the prediction accuracy was comparable to that of whole sequencing depth. Furthermore, an incremental feature selection method has the potential to improve prediction accuracy. This study suggests that the combination of LCS and imputation can be a cost-effective strategy, contributing to the genetic improvement of economic traits and promoting genetic gains in aquaculture species.

Changes in Behavior and Neural Dynamics across Adolescent Development.

Adolescence is an important developmental period, during which substantial changes occur in brain function and behavior. Several aspects of executive function, including response inhibition, improve during this period. Correspondingly, structural imaging studies have documented consistent decreases in cortical and subcortical gray matter volume, and postmortem histologic studies have found substantial (∼40%) decreases in excitatory synapses in prefrontal cortex. Recent computational modeling work suggests that the change in synaptic density underlie improvements in task performance. These models also predict changes in neural dynamics related to the depth of attractor basins, where deeper basins can underlie better task performance. In this study, we analyzed task-related neural dynamics in a large cohort of longitudinally followed subjects (male and female) spanning early to late adolescence. We found that age correlated positively with behavioral performance in the Eriksen Flanker task. Older subjects were also characterized by deeper attractor basins around task related evoked EEG potentials during specific cognitive operations. Thus, consistent with computational models examining the effects of excitatory synaptic pruning, older adolescents showed stronger attractor dynamics during task performance.SIGNIFICANCE STATEMENT There are well-documented changes in brain and behavior during adolescent development. However, there are few mechanistic theories that link changes in the brain to changes in behavior. Here, we tested a hypothesis, put forward on the basis of computational modeling, that pruning of excitatory synapses in cortex during adolescence changes neural dynamics. We found, consistent with the hypothesis, that variability around event-related potentials shows faster decay dynamics in older adolescent subjects. The faster decay dynamics are consistent with the hypothesis that synaptic pruning during adolescent development leads to stronger attractor basins in task-related neural activity.