Biology subjects

Rothamel, K.

Publications and source records attributed to Rothamel, K..

6 recordsLinked to original sources

bioRxiv2024

The YTHDF Proteins Shape the Brain Gene Signatures of Alzheimer's Disease

The gene signatures of Alzheimers Disease (AD) brains reflect an output of a complex interplay of genetic, epigenetic, epi-transcriptomic, and post-transcriptional regulation., yet the dominant factor shaping these signatures remains unclear. To identify the most significant factor that shapes the AD brain signatures, we integrated cellular and molecular features with differential gene expression in in an explainable machine learning framework. Our result indicates that YTHDF proteins, the canonical readers of N6-methyladenosine RNA modification (m6A), are the most influential predictors of the AD brain signatures. We then show that protein modules containing YTHDFs are downregulated in human AD brains, and knocking down and pharmacologically inhibiting YTHDFs in iPSC-derived 2D and 3D neuronal models recapitulate the AD-associated transcriptional signatures. Furthermore, eCLIP-seq analysis revealed that YTHDF proteins influence AD signatures through both m6A-dependent and independent pathways. These results highlight the central role of YTHDF proteins in shaping the gene signatures of AD brains.

neuroscience↗

bioRxiv2023

Large-scale map of RNA binding protein interactomes across the mRNA life-cycle

Messenger RNAs (mRNAs) interact with RNA-binding proteins (RBPs) in diverse ribonucleoprotein complexes (RNPs) during distinct life-cycle stages for their processing and maturation. While substantial attention has focused on understanding RNA regulation by assigning proteins, particularly RBPs, to specific RNA substrates, there has been considerably less exploration leveraging protein-protein interaction (PPI) methodologies to identify and study the role of proteins in mRNA life-cycle stages. To address this gap, we generated an RNA-aware RBP-centric PPI map across the mRNA life-cycle by immunopurification (IP-MS) of [~]100 endogenous RBPs across the life-cycle in the presence or absence of RNase, augmented by size exclusion chromatography (SEC-MS). Aside from confirming 8,700 known and discovering 20,359 novel interactions between 1125 proteins, we determined that 73% of our IP interactions are regulated by the presence of RNA. Our PPI data enables us to link proteins to life-cycle stage functions, highlighting that nearly half of the proteins participate in at least two distinct stages. We show that one of the most highly interconnected proteins, ERH, engages in multiple RNA processes, including via interactions with nuclear speckles and the mRNA export machinery. We also demonstrate that the spliceosomal protein SNRNP200 participates in distinct stress granule-associated RNPs and occupies different RNA target regions in the cytoplasm during stress. Our comprehensive RBP-focused PPI network is a novel resource for identifying multi-stage RBPs and exploring RBP complexes in RNA maturation. HIGHLIGHTSO_LIAn RBP-centric RNA-aware PPI network focuses on the mRNA life-cycle in human cells C_LIO_LIPrey-prey correlation analysis assigns prey proteins to life-cycle stages, of which 536 proteins (half of the network) interact with multiple steps C_LIO_LIERH is highly connected to multiple RNPs to affect nuclear speckle organization and mRNA export C_LIO_LISplicing factor SNRNP200 interacts with stress granule proteins and has distinct RNA occupancy in the cytoplasm C_LI

systems biology↗

bioRxiv2022

HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence

RNA-binding proteins (RBPs) control RNA metabolism to orchestrate gene expression, and dysfunctional RBPs underlie many human diseases. Proteome-wide discovery efforts predict thousands of novel RBPs, many of which lack canonical RNA-binding domains. Here, we present a hybrid ensemble RBP classifier (HydRA) that leverages information from both intermolecular protein interactions and internal protein sequence patterns to predict RNA-binding capacity with unparalleled specificity and sensitivity using support vector machine, convolutional neural networks and transformer-based protein language models. HydRA enables Occlusion Mapping to robustly detect known RNA-binding domains and to predict hundreds of uncharacterized RNA-binding domains. Enhanced CLIP validation for a diverse collection of RBP candidates reveals genome-wide targets and confirms RNA-binding activity for HydRA-predicted domains. The HydRA computational framework accelerates construction of a comprehensive RBP catalogue and expands the set of known RNA-binding protein domains. HighlightsO_LIHydRA combines protein-protein interaction and amino acid sequence information to predict RNA binding activity for 1,487 candidate genes. C_LIO_LIHydRA predicts RNA binding with higher specificity and sensitivity than current approaches, notably for RBPs without well-defined RNA-binding domains. C_LIO_LIOcclusion Mapping with HydRA enables RNA-binding domain discovery. C_LIO_LIEnhanced CLIP confirms HydRA RBP predictions with RNA-binding domain resolution. C_LI

bioinformatics↗

bioRxiv2022

Proteomic discovery of chemical probes that perturb protein complexes in human cells

Most human proteins lack chemical probes, and several large-scale and generalizable small-molecule binding assays have been introduced to address this problem. How compounds discovered in such "binding-first" assays affect protein function, nonetheless, often remains unclear. Here, we describe a "function-first" proteomic strategy that uses size exclusion chromatography (SEC) to assess the global impact of electrophilic compounds on protein complexes in human cells. Integrating the SEC data with cysteine-directed activity-based protein profiling identifies changes in protein-protein interactions that are caused by site-specific liganding events, including the stereoselective engagement of cysteines in PSME1 and SF3B1 that disrupt the PA28 proteasome regulatory complex and stabilize a dynamic state of the spliceosome, respectively. Our findings thus show how multidimensional proteomic analysis of focused libraries of electrophilic compounds can expedite the discovery of chemical probes with site-specific functional effects on protein complexes in human cells.

biochemistry↗

bioRxiv2022

Multiplexed transcriptome discovery of RNA binding protein binding sites by antibody-barcode eCLIP

UV cross-linking and immunoprecipitation (CLIP) methodologies enable the identification of RNA binding sites of RNA-binding proteins (RBPs). Despite improvements in the library preparation of RNA fragments, the current enhanced CLIP (eCLIP) protocol requires 4 days of hands-on time and lacks the ability to process many RBPs in parallel. We present a new method termed antibody-barcode eCLIP (ABC) that utilizes DNA-barcoded antibodies and proximity ligation of the DNA oligonucleotides to RBP-protected RNA fragments to interrogate multiple RBPs simultaneously. We observe performance comparable to eCLIP with the advantage of a reduced hands-on time of 2 days and dramatically increased scaling while minimizing sample-to-sample variation and maintaining the same material requirement of a single eCLIP experiment.

genomics↗

bioRxiv2022

Discovery and functional interrogation of SARS-CoV-2 protein-RNA interactions

The COVID-19 pandemic is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The betacoronvirus has a positive sense RNA genome which encodes for several RNA binding proteins. Here, we use enhanced crosslinking and immunoprecipitation to investigate SARS-CoV-2 protein interactions with viral and host RNAs in authentic virus-infected cells. SARS-CoV-2 proteins, NSP8, NSP12, and nucleocapsid display distinct preferences to specific regions in the RNA viral genome, providing evidence for their shared and separate roles in replication, transcription, and viral packaging. SARS-CoV-2 proteins expressed in human lung epithelial cells bind to 4773 unique host coding RNAs. Nine SARS-CoV-2 proteins upregulate target gene expression, including NSP12 and ORF9c, whose RNA substrates are associated with pathways in protein N-linked glycosylation ER processing and mitochondrial processes. Furthermore, siRNA knockdown of host genes targeted by viral proteins in human lung organoid cells identify potential antiviral host targets across different SARS-CoV-2 variants. Conversely, NSP9 inhibits host gene expression by blocking mRNA export and dampens cytokine productions, including interleukin-1/{beta}. Our viral protein-RNA interactome provides a catalog of potential therapeutic targets and offers insight into the etiology of COVID-19 as a safeguard against future pandemics.

molecular biology↗