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Microglial-derived C1q integrates into neuronal ribonucleoprotein complexes and impacts protein homeostasis in the aging brain

Neuroimmune interactions mediate intercellular communication and underlie critical brain functions. Microglia, CNS-resident macrophages, modulate the brain through direct physical interactions and the secretion of molecules. One such secreted factor, the complement protein C1q, contributes to complement-mediated synapse elimination in both developmental and disease models, yet brain C1q protein levels increase significantly throughout aging. Here, we report that C1q interacts with neuronal ribonucleoprotein (RNP) complexes in an age-dependent manner. Purified C1q protein undergoes RNA-dependent liquid-liquid phase separation (LLPS) in vitro, and the interaction of C1q with neuronal RNP complexes in vivo is dependent on RNA and endocytosis. Mice lacking C1q have age-specific alterations in neuronal protein synthesis in vivo and impaired fear memory extinction. Together, our findings reveal a biophysical property of C1q that underlies RNA- and age-dependent neuronal interactions and demonstrate a role of C1q in critical intracellular neuronal processes.

Oncogenic mutations of KRAS modulate its turnover by the CUL3/LZTR1 E3 ligase complex

KRAS is a proto-oncogene encoding a small GTPase. Mutations contribute to ∼30% of human solid tumours, including lung adenocarcinoma, pancreatic, and colorectal carcinomas. Most KRAS activating mutations interfere with GTP hydrolysis, essential for its role as a molecular switch, leading to alterations in their molecular environment and oncogenic signalling. However, the precise signalling cascades these mutations affect are poorly understood. Here, APEX2 proximity labelling was used to profile the molecular environment of WT, G12D, G13D, and Q61H-activating KRAS mutants under starvation and stimulation conditions. Through quantitative proteomics, we demonstrate the presence of known KRAS interactors, including ARAF and LZTR1, which are differentially captured by WT and KRAS mutants. Notably, the KRAS mutations G12D, G13D, and Q61H abrogate their association with LZTR1, thereby affecting turnover. Elucidating the implications of LZTR1-mediated regulation of KRAS protein levels in cancer may offer insights into therapeutic strategies targeting KRAS-driven malignancies.

HHIP protein interactions in lung cells provide insight into COPD pathogenesis

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. The primary causes of COPD are environmental, including cigarette smoking; however, genetic susceptibility also contributes to COPD risk. Genome-Wide Association Studies (GWASes) have revealed more than 80 genetic loci associated with COPD, leading to the identification of multiple COPD GWAS genes. However, the biological relationships between the identified COPD susceptibility genes are largely unknown. Genes associated with a complex disease are often in close network proximity, i.e. their protein products often interact directly with each other and/or similar proteins. In this study, we use affinity purification mass spectrometry (AP-MS) to identify protein interactions with HHIP , a well-established COPD GWAS gene which is part of the sonic hedgehog pathway, in two disease-relevant lung cell lines (IMR90 and 16HBE). To better understand the network neighborhood of HHIP , its proximity to the protein products of other COPD GWAS genes, and its functional role in COPD pathogenesis, we create HUBRIS, a protein-protein interaction network compiled from 8 publicly available databases. We identified both common and cell type-specific protein-protein interactors of HHIP. We find that our newly identified interactions shorten the network distance between HHIP and the protein products of several COPD GWAS genes, including DSP, MFAP2, TET2 , and FBLN5 . These new shorter paths include proteins that are encoded by genes involved in extracellular matrix and tissue organization. We found and validated interactions to proteins that provide new insights into COPD pathobiology, including CAVIN1 (IMR90) and TP53 (16HBE). The newly discovered HHIP interactions with CAVIN1 and TP53 implicate HHIP in response to oxidative stress.

Induced-pluripotent stem cells and neuroproteomics as tools for studying neurodegeneration

The investigation of neurodegenerative diseases advanced significantly with the advent of cell-reprogramming technology, leading to the creation of new models of human illness. These models, derived from induced pluripotent stem cells (iPSCs), facilitate the study of sporadic as well as hereditary diseases and provide a comprehensive understanding of the molecular mechanisms involved with neurodegeneration. Through proteomics, a quantitative tool capable of identifying thousands of proteins from small sample volumes, researchers have attempted to identify disease mechanisms by detecting differentially expressed proteins and proteoforms in disease models, biofluids, and postmortem brain tissue. The integration of these two technologies allows for the identification of novel pathological targets within the realm of neurodegenerative diseases. Here, we highlight studies from the past 5 years on the contributions of iPSCs within neuroproteomic investigations, which uncover the molecular mechanisms behind these illnesses.

Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease

Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we perform interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their roles in CAD. The resulting PPI networks contain interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms. Several PPI networks derived from smooth muscle cells are significantly enriched for genetic variants associated with CAD and related vascular phenotypes. Furthermore, the networks identify 61 genes that are found in genetic loci associated with risk of CAD, prioritizing them as the causal candidates within these loci. These findings indicate that the PPI networks we have generated are a rich resource for guiding future research into the molecular pathogenesis of CAD.

Antibiofilm and Antivirulence Properties of 6-Polyaminosteroid Derivatives against Antibiotic-Resistant Bacteria

The emergence of multi-drug resistant pathogens is a major public health problem, leading us to rethink and innovate our bacterial control strategies. Here, we explore the antibiofilm and antivirulence activities of nineteen 6-polyaminosterol derivatives (squalamine-based), presenting a modulation of their polyamine side chain on four major pathogens, i.e., carbapenem-resistant A. baumannii (CRAB) and P. aeruginosa (CRPA), methicillin-resistant S. aureus (MRSA), and vancomycin-resistant E. faecium (VRE) strains. We screened the effect of these derivatives on biofilm formation and eradication. Derivatives 4e (for CRAB, VRE, and MRSA) and 4f (for all the strains) were the most potent ones and displayed activities as good as those of conventional antibiotics. We also identified 11 compounds able to decrease by more than 40% the production of pyocyanin, a major virulence factor of P. aeruginosa. We demonstrated that 4f treatment acts against bacterial infections in Galleria mellonella and significantly prolonged larvae survival (from 50% to 80%) after 24 h of CRAB, VRE, and MRSA infections. As shown by proteomic studies, 4f triggered distinct cellular responses depending on the bacterial species but essentially linked to cell envelope. Its interesting antibiofilm and antivirulence properties make it a promising a candidate for use in therapeutics.

Systematic differences in discovery of genetic effects on gene expression and complex traits

Most signals in genome-wide association studies (GWAS) of complex traits implicate noncoding genetic variants with putative gene regulatory effects. However, currently identified regulatory variants, notably expression quantitative trait loci (eQTLs), explain only a small fraction of GWAS signals. Here, we show that GWAS and cis-eQTL hits are systematically different: eQTLs cluster strongly near transcription start sites, whereas GWAS hits do not. Genes near GWAS hits are enriched in key functional annotations, are under strong selective constraint and have complex regulatory landscapes across different tissue/cell types, whereas genes near eQTLs are depleted of most functional annotations, show relaxed constraint, and have simpler regulatory landscapes. We describe a model to understand these observations, including how natural selection on complex traits hinders discovery of functionally relevant eQTLs. Our results imply that GWAS and eQTL studies are systematically biased toward different types of variant, and support the use of complementary functional approaches alongside the next generation of eQTL studies.

Outlining cardiac ion channel protein interactors and their signature in the human electrocardiogram

Protein-protein interactions are essential for normal cellular processes and signaling events. Defining these interaction networks is therefore crucial for understanding complex cellular functions and interpretation of disease-associated gene variants. We need to build a comprehensive picture of the interactions, their affinities and interdependencies in the specific organ to decipher hitherto poorly understood signaling mechanisms through ion channels. Here we report the experimental identification of the ensemble of protein interactors for 13 types of ion channels in murine cardiac tissue. Of these, we validated the functional importance of ten interactors on cardiac electrophysiology through genetic knockouts in zebrafish, gene silencing in mice, super-resolution microscopy and patch clamp experiments. Furthermore, we establish a computational framework to reconstruct human cardiomyocyte ion channel networks from deep proteome mapping of human heart tissue and human heart single-cell gene expression data. Finally, we integrate the ion channel interactome with human population genetics data to identify proteins that influence the electrocardiogram (ECG). We demonstrate that the combined channel network is enriched for proteins influencing the ECG, with 44% of the network proteins significantly associated with an ECG phenotype. Altogether, we define interactomes of 13 major cardiac ion channels, contextualize their relevance to human electrophysiology and validate functional roles of ten interactors, including two regulators of the sodium current (epsin-2 and gelsolin). Overall, our data provide a roadmap for our understanding of the molecular machinery that regulates cardiac electrophysiology.

Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia

Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.

Protein interaction studies in human induced neurons indicate convergent biology underlying autism spectrum disorders

Autism spectrum disorders (ASDs) have been linked to genes with enriched expression in the brain, but it is unclear how these genes converge into cell-type-specific networks. We built a protein-protein interaction network for 13 ASD-associated genes in human excitatory neurons derived from induced pluripotent stem cells (iPSCs). The network contains newly reported interactions and is enriched for genetic and transcriptional perturbations observed in individuals with ASDs. We leveraged the network data to show that the ASD-linked brain-specific isoform of ANK2 is important for its interactions with synaptic proteins and to characterize a PTEN-AKAP8L interaction that influences neuronal growth. The IGF2BP1-3 complex emerged as a convergent point in the network that may regulate a transcriptional circuit of ASD-associated genes. Our findings showcase cell-type-specific interactomes as a framework to complement genetic and transcriptomic data and illustrate how both individual and convergent interactions can lead to biological insights into ASDs.

Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms

Genome-Wide Association Studies (GWAS) have elucidated the genetic components of Parkinson's Disease (PD). However, because the vast majority of GWAS association signals fall within non-coding regions, translating these results into an interpretable, mechanistic understanding of the disease etiology remains a major challenge in the field. In this review, we provide an overview of the approaches to prioritize putative causal variants and genes as well as summarise the primary findings of previous studies. We then discuss recent efforts to integrate multi-omics data to identify likely pathogenic cell types and biological pathways implicated in PD pathogenesis. We have compiled full summary statistics of cell-type, tissue, and phentoype enrichment analyses from multiple studies of PD GWAS and provided them in a standardized format as a resource for the research community (https://github.com/RajLabMSSM/PD_omics_review). Finally, we discuss the experimental, computational, and conceptual advances that will be necessary to fully elucidate the effects of functional variants and genes on cellular dysregulation and disease risk.