Mitochondrial Raf1 Regulates Glutamine Catabolism.

Raf kinases play vital roles in normal mitogenic signaling and cancer, however, the identities of functionally important Raf-proximal proteins throughout the cell are not fully known. Raf1 proximity proteomics/BioID in Raf1-dependent cancer cells unexpectedly identified Raf1-adjacent proteins known to reside in the mitochondrial matrix. Inner-mitochondrial localization of Raf1 was confirmed by mitochondrial purification and super-resolution microscopy. Inside mitochondria, Raf1 associated with glutaminase (GLS) in diverse human cancers and enabled glutaminolysis, an important source of biosynthetic precursors in cancer. These impacts required Raf1 kinase activity and were independent of canonical MAP kinase pathway signaling. Kinase-dead mitochondrial matrix-localized Raf1 impaired glutaminolysis and tumorigenesis in vivo. These data indicate that Raf1 localizes inside mitochondria where it interacts with GLS to engage glutamine catabolism and support tumorigenesis.

Integrative analyses highlight functional regulatory variants associated with neuropsychiatric diseases.

Noncoding variants of presumed regulatory function contribute to the heritability of neuropsychiatric disease. A total of 2,221 noncoding variants connected to risk for ten neuropsychiatric disorders, including autism spectrum disorder, attention deficit hyperactivity disorder, bipolar disorder, borderline personality disorder, major depression, generalized anxiety disorder, panic disorder, post-traumatic stress disorder, obsessive-compulsive disorder and schizophrenia, were studied in developing human neural cells. Integrating epigenomic and transcriptomic data with massively parallel reporter assays identified differentially-active single-nucleotide variants (daSNVs) in specific neural cell types. Expression-gene mapping, network analyses and chromatin looping nominated candidate disease-relevant target genes modulated by these daSNVs. Follow-up integration of daSNV gene editing with clinical cohort analyses suggested that magnesium transport dysfunction may increase neuropsychiatric disease risk and indicated that common genetic pathomechanisms may mediate specific symptoms that are shared across multiple neuropsychiatric diseases.

Advances in cutaneous squamous cell carcinoma.

Human malignancies arise predominantly in tissues of epithelial origin, where the stepwise transformation from healthy epithelium to premalignant dysplasia to invasive neoplasia involves sequential dysregulation of biological networks that govern essential functions of epithelial homeostasis. Cutaneous squamous cell carcinoma (cSCC) is a prototype epithelial malignancy, often with a high tumour mutational burden. A plethora of risk genes, dominated by UV-induced sun damage, drive disease progression in conjunction with stromal interactions and local immunomodulation, enabling continuous tumour growth. Recent studies have identified subpopulations of SCC cells that specifically interact with the tumour microenvironment. These advances, along with increased knowledge of the impact of germline genetics and somatic mutations on cSCC development, have led to a greater appreciation of the complexity of skin cancer pathogenesis and have enabled progress in neoadjuvant immunotherapy, which has improved pathological complete response rates. Although measures for the prevention and therapeutic management of cSCC are associated with clinical benefit, the prognosis remains poor for advanced disease. Elucidating how the genetic mechanisms that drive cSCC interact with the tumour microenvironment is a current focus in efforts to understand, prevent and treat cSCC.

Functional characterization of human genomic variation linked to polygenic diseases.

The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.

Glucose dissociates DDX21 dimers to regulate mRNA splicing and tissue differentiation.

Glucose is a universal bioenergy source; however, its role in controlling protein interactions is unappreciated, as are its actions during differentiation-associated intracellular glucose elevation. Azido-glucose click chemistry identified glucose binding to a variety of RNA binding proteins (RBPs), including the DDX21 RNA helicase, which was found to be essential for epidermal differentiation. Glucose bound the ATP-binding domain of DDX21, altering protein conformation, inhibiting helicase activity, and dissociating DDX21 dimers. Glucose elevation during differentiation was associated with DDX21 re-localization from the nucleolus to the nucleoplasm where DDX21 assembled into larger protein complexes containing RNA splicing factors. DDX21 localized to specific SCUGSDGC motif in mRNA introns in a glucose-dependent manner and promoted the splicing of key pro-differentiation genes, including GRHL3, KLF4, OVOL1, and RBPJ. These findings uncover a biochemical mechanism of action for glucose in modulating the dimerization and function of an RNA helicase essential for tissue differentiation.

Analyzing RNA-Protein Interactions by Cross-Link Rates and CLIP-seq Libraries.

UV cross-linking-based methods are the most common tool to explore in vivo RNA-protein interactions. UV cross-linking enables the freezing of direct interactions in the cell, which can then be mapped by high-throughput sequencing through a family of methods termed CLIP-seq. CLIP-seq measures the distribution of cross-link events by purifying a protein of interest and sequencing the covalently bound RNA fragments. However, there are disagreements and ambiguities as to which proteins are RNA-binding proteins and what interactions are significant as all proteins contact all RNAs at some frequency. Here we describe a protocol for both determining RNA-protein interactions through a combination of RNA library preparation and the measurement of absolute cross-link rates, which helps determine what proteins are RNA-binding proteins and what interactions are significant. This protocol, comprising an updated form of the easyCLIP protocol, describes guidelines for RNA library preparation, oligo and protein standard construction, and the measurement of cross-link rates. These methods are easily visualizable through their fluorescent labels and can be adapted to study RNA-binding properties of both functional, high affinity RNA-binding proteins, and the accidental RNA interactions of non-RNA-binding proteins. © 2023 Wiley Periodicals LLC. Basic Protocol 1: RNA library construction Basic Protocol 2: Determining UV cross-link rates Support Protocol 1: Cross-linking and lysing cells Support Protocol 2: Adapter preparation Support Protocol 3: Preparation of cross-linked RBP standard.

PROBER identifies proteins associated with programmable sequence-specific DNA in living cells.

DNA-protein interactions mediate physiologic gene regulation and may be altered by DNA variants linked to polygenic disease. To enhance the speed and signal-to-noise ratio (SNR) in the identification and quantification of proteins associated with specific DNA sequences in living cells, we developed proximal biotinylation by episomal recruitment (PROBER). PROBER uses high-copy episomes to amplify SNR, and proximity proteomics (BioID) to identify the transcription factors and additional gene regulators associated with short DNA sequences of interest. PROBER quantified both constitutive and inducible association of transcription factors and corresponding chromatin regulators to target DNA sequences and binding quantitative trait loci due to single-nucleotide variants. PROBER identified alterations in regulator associations due to cancer hotspot mutations in the hTERT promoter, indicating that these mutations increase promoter association with specific gene activators. PROBER provides an approach to rapidly identify proteins associated with specific DNA sequences and their variants in living cells.

Spatially resolved clonal copy number alterations in benign and malignant tissue.

Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

Targeted Proteomic Approaches for Proteome-Wide Characterizations of the AMP-Binding Capacities of Kinases.

Kinases play important roles in cell signaling, and adenosine monophosphate (AMP) is known to modulate cellular energy homeostasis through AMP-activated protein kinase (AMPK). Here, we explored novel AMP-binding kinases by employing a desthiobiotin-conjugated AMP acyl-phosphate probe to enrich efficiently AMP-binding proteins. Together with a parallel-reaction monitoring-based targeted proteomic approach, we uncovered 195 candidate AMP-binding kinases. We also enriched desthiobiotin-labeled peptides from adenine nucleotide-binding sites of kinases and analyzed them using LC-MS/MS in the multiple-reaction monitoring mode, which resulted in the identification of 44 peptides derived from 43 kinases displaying comparable or better binding affinities toward AMP relative to adenosine triphosphate (ATP). Moreover, our proteomic data revealed a potential involvement of AMP in the MAPK pathway through binding directly to the relevant kinases, especially MEK2 and MEK3. Together, we revealed the AMP-binding capacities of a large number of kinases, and our work built a strong foundation for understanding how AMP functions as a second messenger to modulate cell signaling.

Super-resolved spatial transcriptomics by deep data fusion.

Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.

A cis-regulatory lexicon of DNA motif combinations mediating cell-type-specific gene regulation.

Gene expression is controlled by transcription factors (TFs) that bind cognate DNA motif sequences in cis-regulatory elements (CREs). The combinations of DNA motifs acting within homeostasis and disease, however, are unclear. Gene expression, chromatin accessibility, TF footprinting, and H3K27ac-dependent DNA looping data were generated and a random-forest-based model was applied to identify 7,531 cell-type-specific cis-regulatory modules (CRMs) across 15 diploid human cell types. A co-enrichment framework within CRMs nominated 838 cell-type-specific, recurrent heterotypic DNA motif combinations (DMCs), which were functionally validated using massively parallel reporter assays. Cancer cells engaged DMCs linked to neoplasia-enabling processes operative in normal cells while also activating new DMCs only seen in the neoplastic state. This integrative approach identifies cell-type-specific cis-regulatory combinatorial DNA motifs in diverse normal and diseased human cells and represents a general framework for deciphering cis-regulatory sequence logic in gene regulation.

The dynamic, combinatorial cis-regulatory lexicon of epidermal differentiation.

Transcription factors bind DNA sequence motif vocabularies in cis-regulatory elements (CREs) to modulate chromatin state and gene expression during cell state transitions. A quantitative understanding of how motif lexicons influence dynamic regulatory activity has been elusive due to the combinatorial nature of the cis-regulatory code. To address this, we undertook multiomic data profiling of chromatin and expression dynamics across epidermal differentiation to identify 40,103 dynamic CREs associated with 3,609 dynamically expressed genes, then applied an interpretable deep-learning framework to model the cis-regulatory logic of chromatin accessibility. This analysis framework identified cooperative DNA sequence rules in dynamic CREs regulating synchronous gene modules with diverse roles in skin differentiation. Massively parallel reporter assay analysis validated temporal dynamics and cooperative cis-regulatory logic. Variants linked to human polygenic skin disease were enriched in these time-dependent combinatorial motif rules. This integrative approach shows the combinatorial cis-regulatory lexicon of epidermal differentiation and represents a general framework for deciphering the organizational principles of the cis-regulatory code of dynamic gene regulation.

The proximal proteome of 17 SARS-CoV-2 proteins links to disrupted antiviral signaling and host translation.

Viral proteins localize within subcellular compartments to subvert host machinery and promote pathogenesis. To study SARS-CoV-2 biology, we generated an atlas of 2422 human proteins vicinal to 17 SARS-CoV-2 viral proteins using proximity proteomics. This identified viral proteins at specific intracellular locations, such as association of accessary proteins with intracellular membranes, and projected SARS-CoV-2 impacts on innate immune signaling, ER-Golgi transport, and protein translation. It identified viral protein adjacency to specific host proteins whose regulatory variants are linked to COVID-19 severity, including the TRIM4 interferon signaling regulator which was found proximal to the SARS-CoV-2 M protein. Viral NSP1 protein adjacency to the EIF3 complex was associated with inhibited host protein translation whereas ORF6 localization with MAVS was associated with inhibited RIG-I 2CARD-mediated IFNB1 promoter activation. Quantitative proteomics identified candidate host targets for the NSP5 protease, with specific functional cleavage sequences in host proteins CWC22 and FANCD2. This data resource identifies host factors proximal to viral proteins in living human cells and nominates pathogenic mechanisms employed by SARS-CoV-2.

Mutant collagen COL11A1 enhances cancerous invasion.

Collagens are the most abundant proteins in the body and comprise the basement membranes and stroma through which cancerous invasion occurs; however, a pro-neoplastic function for mutant collagens is undefined. Here we identify COL11A1 mutations in 66 of 100 cutaneous squamous cell carcinomas (cSCCs), the second most common U.S. cancer, concentrated in a triple helical region known to produce trans-dominant collagens. Analysis of COL11A1 and other collagen genes found that they are mutated across common epithelial malignancies. Knockout of mutant COL11A1 impairs cSCC tumorigenesis in vivo. Compared to otherwise genetically identical COL11A1 wild-type tissue, gene-edited mutant COL11A1 skin is characterized by induction of ß1 integrin targets and accelerated neoplastic invasion. In mosaic tissue, mutant COL11A1 cells enhanced invasion by neighboring wild-type cells. These results suggest that specific collagens are commonly mutated in cancer and that mutant collagens may accelerate this process.

Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics.

Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but does not capture their spatial distribution nor reveal local networks of intercellular communication acting in situ. A suite of recently developed techniques that localize RNA within tissue, including multiplexed in situ hybridization and in situ sequencing (here defined as high-plex RNA imaging) and spatial barcoding, can help address this issue. However, no method currently provides as complete a scope of the transcriptome as does scRNA-seq, underscoring the need for approaches to integrate single-cell and spatial data. Here, we review efforts to integrate scRNA-seq with spatial transcriptomics, including emerging integrative computational methods, and propose ways to effectively combine current methodologies.

easyCLIP analysis of RNA-protein interactions incorporating absolute quantification.

Quantitative criteria to identify proteins as RNA-binding proteins (RBPs) are presently lacking, as are criteria to define RBP target RNAs. Here, we develop an ultraviolet (UV) cross-linking immunoprecipitation (CLIP)-sequencing method, easyCLIP. easyCLIP provides absolute cross-link rates, as well as increased simplicity, efficiency, and capacity to visualize RNA libraries during sequencing library preparation. Measurement of >200 independent cross-link experiments across >35 proteins identifies an RNA cross-link rate threshold that distinguishes RBPs from non-RBPs and defines target RNAs as those with a complex frequency unlikely for a random protein. We apply easyCLIP to the 33 most recurrent cancer mutations across 28 RBPs, finding increased RNA binding per RBP molecule for KHDRBS2 R168C, A1CF E34K and PCBP1 L100P/Q cancer mutations. Quantitating RBP-RNA interactions can thus nominate proteins as RBPs and define the impact of specific disease-associated RBP mutations on RNA association.

The proximal proteome of 17 SARS-CoV-2 proteins links to disrupted antiviral signaling and host translation.

Viral proteins localize within subcellular compartments to subvert host machinery and promote pathogenesis. To study SARS-CoV-2 biology, we generated an atlas of 2422 human proteins vicinal to 17 SARS-CoV-2 viral proteins using proximity proteomics. This identified viral proteins at specific intracellular locations, such as association of accessary proteins with intracellular membranes, and projected SARS-CoV-2 impacts on innate immune signaling, ER-Golgi transport, and protein translation. It identified viral protein adjacency to specific host proteins whose regulatory variants are linked to COVID-19 severity, including the TRIM4 interferon signaling regulator which was found proximal to the SARS-CoV-2 M protein. Viral NSP1 protein adjacency to the EIF3 complex was associated with inhibited host protein translation whereas ORF6 localization with MAVS was associated with inhibited RIG-I 2CARD-mediated IFNB1 promoter activation. Quantitative proteomics identified candidate host targets for the NSP5 protease, with specific functional cleavage sequences in host proteins CWC22 and FANCD2. This data resource identifies host factors proximal to viral proteins in living human cells and nominates pathogenic mechanisms employed by SARS-CoV-2. AUTHOR SUMMARY: SARS-CoV-2 is the latest pathogenic coronavirus to emerge as a public health threat. We create a database of proximal host proteins to 17 SARS-CoV-2 viral proteins. We validate that NSP1 is proximal to the EIF3 translation initiation complex and is a potent inhibitor of translation. We also identify ORF6 antagonism of RNA-mediate innate immune signaling. We produce a database of potential host targets of the viral protease NSP5, and create a fluorescence-based assay to screen cleavage of peptide sequences. We believe that this data will be useful for identifying roles for many of the uncharacterized SARS-CoV-2 proteins and provide insights into the pathogenicity of new or emerging coronaviruses.

SARS-CoV-2 B.1.1.7 and B.1.351 Spike variants bind human ACE2 with increased affinity.

SARS-CoV2 being highly infectious has been particularly effective in causing widespread infection globally and more variants of SARS-CoV2 are constantly being reported with increased genomic surveillance. In particular, the focus is on mutations of Spike protein, which binds human ACE2 protein enabling SARS-CoV2 entry and infection. Here we present a rapid experimental method leveraging the speed and flexibility of Mircoscale Thermopheresis (MST) to characterize the interaction between Spike Receptor Binding Domain (RBD) and human ACE2 protein. The B.1.351 variant harboring three mutations, (E484K, N501Y, and K417N) binds the ACE2 at nearly five-fold greater affinity than the original SARS-COV-2 RBD. We also find that the B.1.1.7 variant, binds two-fold more tightly to ACE2 than the SARS-COV-2 RBD.

Structural modularity of the XIST ribonucleoprotein complex.

Long noncoding RNAs are thought to regulate gene expression by organizing protein complexes through unclear mechanisms. XIST controls the inactivation of an entire X chromosome in female placental mammals. Here we develop and integrate several orthogonal structure-interaction methods to demonstrate that XIST RNA-protein complex folds into an evolutionarily conserved modular architecture. Chimeric RNAs and clustered protein binding in fRIP and eCLIP experiments align with long-range RNA secondary structure, revealing discrete XIST domains that interact with distinct sets of effector proteins. CRISPR-Cas9-mediated permutation of the Xist A-repeat location shows that A-repeat serves as a nucleation center for multiple Xist-associated proteins and m6A modification. Thus modular architecture plays an essential role, in addition to sequence motifs, in determining the specificity of RBP binding and m6A modification. Together, this work builds a comprehensive structure-function model for the XIST RNA-protein complex, and suggests a general strategy for mechanistic studies of large ribonucleoprotein assemblies.