Neuronal aging causes mislocalization of splicing proteins and unchecked cellular stress.

Aging is one of the most prominent risk factors for neurodegeneration, yet the molecular mechanisms underlying the deterioration of old neurons are mostly unknown. To efficiently study neurodegeneration in the context of aging, we transdifferentiated primary human fibroblasts from aged healthy donors directly into neurons, which retained their aging hallmarks, and we verified key findings in aged human and mouse brain tissue. Here we show that aged neurons are broadly depleted of RNA-binding proteins, especially spliceosome components.

Large-scale evaluation of the ability of RNA-binding proteins to activate exon inclusion.

RNA-binding proteins (RBPs) modulate alternative splicing outcomes to determine isoform expression and cellular survival. To identify RBPs that directly drive alternative exon inclusion, we developed tethered function luciferase-based splicing reporters that provide rapid, scalable and robust readouts of exon inclusion changes and used these to evaluate 718 human RBPs. We performed enhanced cross-linking immunoprecipitation, RNA sequencing and affinity purification-mass spectrometry to investigate a subset of candidates with no prior association with splicing.

LARP4 is an RNA-binding protein that binds nuclear-encoded mitochondrial mRNAs to promote mitochondrial function.

Mitochondria-associated RNA-binding proteins (RBPs) have emerged as key contributors to mitochondrial biogenesis and homeostasis. With few examples known, we set out to identify RBPs that regulate nuclear-encoded mitochondrial mRNAs (NEMmRNAs). Our systematic analysis of RNA targets of 150 RBPs identified RBPs with a preference for binding NEMmRNAs, including LARP4, a La RBP family member.

Skipper analysis of eCLIP datasets enables sensitive detection of constrained translation factor binding sites.

Technology for crosslinking and immunoprecipitation (CLIP) followed by sequencing (CLIP-seq) has identified the transcriptomic targets of hundreds of RNA-binding proteins in cells. To increase the power of existing and future CLIP-seq datasets, we introduce Skipper, an end-to-end workflow that converts unprocessed reads into annotated binding sites using an improved statistical framework. Compared with existing methods, Skipper on average calls 210%-320% more transcriptomic binding sites and sometimes >1,000% more sites, providing deeper insight into post-transcriptional gene regulation.

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.

Remodeling oncogenic transcriptomes by small molecules targeting NONO.

Much of the human proteome is involved in mRNA homeostasis, but most RNA-binding proteins lack chemical probes. Here we identify electrophilic small molecules that rapidly and stereoselectively decrease the expression of transcripts encoding the androgen receptor and its splice variants in prostate cancer cells. We show by chemical proteomics that the compounds engage C145 of the RNA-binding protein NONO.

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

Ultraviolet crosslinking 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 enhanced CLIP (eCLIP) protocol requires 4 days of hands-on time and lacks the ability to process several RBPs in parallel. We present a new method termed antibody-barcode eCLIP that utilizes DNA-barcoded antibodies and proximity ligation of the DNA oligonucleotides to RBP-protected RNA fragments to interrogate several RBPs simultaneously.

Inferring a spatial code of cell-cell interactions across a whole animal body.

Cell-cell interactions shape cellular function and ultimately organismal phenotype. Interacting cells can sense their mutual distance using combinations of ligand-receptor pairs, suggesting the existence of a spatial code, i.e.

Metadensity: a background-aware python pipeline for summarizing CLIP signals on various transcriptomic sites.

Motivation: Cross-linking and immunoprecipitation (CLIP) is a technology to map the binding sites of RNA-binding proteins (RBPs). The region where an RBP binds within RNA is often indicative of its molecular function in RNA processing. As an example, the binding sites of splicing factors are found within or proximal to alternatively spliced exons.

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.

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.

PangenomeNet: a pan-genome-based network reveals functional modules on antimicrobial resistome for Escherichia coli strains.

Background: Discerning genes crucial to antimicrobial resistance (AMR) mechanisms is becoming more and more important to accurately and swiftly identify AMR pathogenic strains. Pangenome-wide association studies (e.g.

A pan-genome-based machine learning approach for predicting antimicrobial resistance activities of the Escherichia coli strains.

Motivation: Antimicrobial resistance (AMR) is becoming a huge problem in both developed and developing countries, and identifying strains resistant or susceptible to certain antibiotics is essential in fighting against antibiotic-resistant pathogens. Whole-genome sequences have been collected for different microbial strains in order to identify crucial characteristics that allow certain strains to become resistant to antibiotics; however, a global inspection of the gene content responsible for AMR activities remains to be done.

Results: We propose a pan-genome-based approach to characterize antibiotic-resistant microbial strains and test this approach on the bacterial model organism Escherichia coli.