Protein microarray is an emerging technology that provides a versatile platform for characterization of hundreds of thousands of proteins in a highly parallel and high-throughput way. Two major classes of protein microarrays are defined to describe their applications: analytical and functional protein microarrays. In addition, tissue or cell lysates can also be fractionated and spotted on a slide to form a reverse-phase protein microarray. While the fabrication technology is maturing, applications of protein microarrays, especially functional protein microarrays, have flourished during the past decade. Here, we will first review recent advances in the protein microarray technologies, and then present a series of examples to illustrate the applications of analytical and functional protein microarrays in both basic and clinical research. The research areas will include detection of various binding properties of proteins, study of protein posttranslational modifications, analysis of host-microbe interactions, profiling antibody specificity, and identification of biomarkers in autoimmune diseases. As a powerful technology platform, it would not be surprising if protein microarrays will become one of the leading technologies in proteomic and diagnostic fields in the next decade.

Mutations causing aberrant splicing are frequently implicated in human diseases including cancer. Here, we establish a high-throughput screen of randomly mutated minigenes to decode the cis-regulatory landscape that determines alternative splicing of exon 11 in the proto-oncogene MST1R (RON). Mathematical modelling of splicing kinetics enables us to identify more than 1000 mutations affecting RON exon 11 skipping, which corresponds to the pathological isoform RON∆165. Importantly, the effects correlate with RON alternative splicing in cancer patients bearing the same mutations. Moreover, we highlight heterogeneous nuclear ribonucleoprotein H (HNRNPH) as a key regulator of RON splicing in healthy tissues and cancer. Using iCLIP and synergy analysis, we pinpoint the functionally most relevant HNRNPH binding sites and demonstrate how cooperative HNRNPH binding facilitates a splicing switch of RON exon 11. Our results thereby offer insights into splicing regulation and the impact of mutations on alternative splicing in cancer.

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Alternative splicing generates distinct mRNA isoforms and is crucial for proteome diversity in eukaryotes. The RNA-binding protein (RBP) U2AF2 is central to splicing decisions, as it recognizes 3' splice sites and recruits the spliceosome. We establish "in vitro iCLIP" experiments, in which recombinant RBPs are incubated with long transcripts, to study how U2AF2 recognizes RNA sequences and how this is modulated by -acting RBPs. We measure U2AF2 affinities at hundreds of binding sites and compare in vitro and in vivo binding landscapes by mathematical modeling. We find that-acting RBPs extensively regulate U2AF2 binding in vivo, including enhanced recruitment to 3' splice sites and clearance of introns. Using machine learning, we identify and experimentally validate novel -acting RBPs (including FUBP1, CELF6, and PCBP1) that modulate U2AF2 binding and affect splicing outcomes. Our study offers a blueprint for the high-throughput characterization of in vitro mRNP assembly and in vivo splicing regulation.

N6‐methyladenosine (m6A) regulates a variety of physiological processes through modulation of RNA metabolism. This modification is particularly enriched in the nervous system of several species, and its dysregulation has been associated with neurodevelopmental defects and neural dysfunctions. In Drosophila, loss of m6A alters fly behavior, albeit the underlying molecular mechanism and the role of m6A during nervous system development have remained elusive. Here we find that impairment of the m6A pathway leads to axonal overgrowth and misguidance at larval neuromuscular junctions as well as in the adult mushroom bodies. We identify Ythdf as the main m6A reader in the nervous system, being required to limit axonal growth. Mechanistically, we show that the m6A reader Ythdf directly interacts with Fmr1, the fly homolog of Fragile X mental retardation RNA binding protein (FMRP), to inhibit the translation of key transcripts involved in axonal growth regulation. Altogether, this study demonstrates that the m6A pathway controls development of the nervous system and modulates Fmr1 target transcript selection.

N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present miCLIP2 in combination with machine learning to significantly improve m6A detection. The optimized miCLIP2 results in high-complexity libraries from less input material. Importantly, we established a robust computational pipeline to tackle the inherent issue of false positives in antibody-based m6A detection. The analyses were calibrated with Mettl3 knockout cells to learn the characteristics of m6A deposition, including m6A sites outside of DRACH motifs. To make our results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP2 data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.

Stem-loop I (SL1) located in the 5 untranslated region of the hepatitis C virus (HCV) genome initiates binding to miR-122, a microRNA required for hepatitis HCV replication. However, proteins that bind SL1 remain elusive. In this study, we employed a human proteome microarray, comprised of ϳ17,000 individually purified human proteins in full-length, and identified 313 proteins that recognize HCV SL1. Eighty-three of the identified proteins were annotated as liver-expressing proteins, and twelve of which were known to be associated with hepatitis virus. siRNA-induced silencing of eight out of 12 candidate genes led to at least 25% decrease in HCV replication efficiency. In particular, knockdown of heterogeneous nuclear ribonucleoprotein K (hnRNP K) reduced HCV replication in a concentration-dependent manner. Ultra-violetcrosslinking assay also showed that hnRNP K, which functions in pre-mRNA processing and transport, showed the strongest binding to the HCV SL1. We observed that hnRNP K, a nuclear protein, is relocated in the cytoplasm in HCV-expressing cells. Immunoprecipitation of the hnRNP K from Huh7.5 cells stably expressing HCV replicon resulted in the co-immunoprecipitation of SL1. This work identifies a cellular protein that could have an important role in the regulation of HCV RNA gene expression and metabolism. Molecular & Cellular

In pancreatic β-cells, the expression of the splicing factor SRSF6 is regulated by GLIS3, a transcription factor encoded by a diabetes susceptibility gene. SRSF6 down-regulation promotes β-cell demise through splicing dysregulation of central genes for β-cells function and survival, but how RNAs are targeted by SRSF6 remains poorly understood. Here, we define the SRSF6 binding landscape in the human pancreatic β-cell line EndoC-βH1 by integrating individual-nucleotide resolution UV cross-linking and immunoprecipitation (iCLIP) under basal conditions with RNA sequencing after SRSF6 knockdown. We detect thousands of SRSF6 bindings sites in coding sequences. Motif analyses suggest that SRSF6 specifically recognizes a purine-rich consensus motif consisting of GAA triplets and that the number of contiguous GAA triplets correlates with increasing binding site strength. The SRSF6 positioning determines the splicing fate. In line with its role in β-cell function, we identify SRSF6 binding sites on regulated exons in several diabetes susceptibility genes. In a proof-of-principle, the splicing of the susceptibility gene LMO7 is modulated by antisense oligonucleotides. Our present study unveils the splicing regulatory landscape of SRSF6 in immortalized human pancreatic β-cells.