Identify Sequence Motifs Research Articles

Meta-Analysis of Rice Phosphoproteomics Data to Understand Variation in Cell Signaling Across the Rice Pan-Genome.

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety and clustered the data to identify groups of sites with similar patterns across rice family groups. The data has been loaded into UniProt Knowledge-Base─enabling researchers to visualize sites alongside other data on rice proteins, e.g., structural models from AlphaFold2, PeptideAtlas, and the PRIDE database─enabling visualization of source evidence, including scores and supporting mass spectra.

Massively parallel identification of sequence motifs triggering ribosome-associated mRNA quality control.

Decay of mRNAs can be triggered by ribosome slowdown at stretches of rare codons or positively charged amino acids. However, the full diversity of sequences that trigger co-translational mRNA decay is poorly understood. To comprehensively identify sequence motifs that trigger mRNA decay, we use a massively parallel reporter assay to measure the effect of all possible combinations of codon pairs on mRNA levels in S. cerevisiae. In addition to known mRNA-destabilizing sequences, we identify several dipeptide repeats whose translation reduces mRNA levels. These include combinations of positively charged and bulky residues, as well as proline-glycine and proline-aspartate dipeptide repeats. Genetic deletion of the ribosome collision sensor Hel2 rescues the mRNA effects of these motifs, suggesting that they trigger ribosome slowdown and activate the ribosome-associated quality control (RQC) pathway. Deep mutational scanning of an mRNA-destabilizing dipeptide repeat reveals a complex interplay between the charge, bulkiness, and location of amino acid residues in conferring mRNA instability. Finally, we show that the mRNA effects of codon pairs are predictive of the effects of endogenous sequences. Our work highlights the complexity of sequence motifs driving co-translational mRNA decay in eukaryotes, and presents a high throughput approach to dissect their requirements at the codon level.

Riboformer: a deep learning framework for predicting context-dependent translation dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurements of translation at the genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts in these data and identify sequence determinants of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. When trained on an unbiased dataset, Riboformer corrects experimental artifacts in previously unseen datasets, which reveals subtle differences in synonymous codon translation and uncovers a bottleneck in translation elongation. Further, we show that Riboformer can be combined with in silico mutagenesis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

DARDN: A Deep-Learning Approach for CTCF Binding Sequence Classification and Oncogenic Regulatory Feature Discovery.

Characterization of gene regulatory mechanisms in cancer is a key task in cancer genomics. CCCTC-binding factor (CTCF), a DNA binding protein, exhibits specific binding patterns in the genome of cancer cells and has a non-canonical function to facilitate oncogenic transcription programs by cooperating with transcription factors bound at flanking distal regions. Identification of DNA sequence features from a broad genomic region that distinguish cancer-specific CTCF binding sites from regular CTCF binding sites can help find oncogenic transcription factors in a cancer type. However, the presence of long DNA sequences without localization information makes it difficult to perform conventional motif analysis. Here, we present DNAResDualNet (DARDN), a computational method that utilizes convolutional neural networks (CNNs) for predicting cancer-specific CTCF binding sites from long DNA sequences and employs DeepLIFT, a method for interpretability of deep learning models that explains the model's output in terms of the contributions of its input features. The method is used for identifying DNA sequence features associated with cancer-specific CTCF binding. Evaluation on DNA sequences associated with CTCF binding sites in T-cell acute lymphoblastic leukemia (T-ALL) and other cancer types demonstrates DARDN's ability in classifying DNA sequences surrounding cancer-specific CTCF binding from control constitutive CTCF binding and identifying sequence motifs for transcription factors potentially active in each specific cancer type. We identify potential oncogenic transcription factors in T-ALL, acute myeloid leukemia (AML), breast cancer (BRCA), colorectal cancer (CRC), lung adenocarcinoma (LUAD), and prostate cancer (PRAD). Our work demonstrates the power of advanced machine learning and feature discovery approach in finding biologically meaningful information from complex high-throughput sequencing data.

Delineating the mechanism of fragility at BCL6 breakpoint region associated with translocations in diffuse large B cell lymphoma.

BCL6 translocation is one of the most common chromosomal translocations in cancer and results in its enhanced expression in germinal center B cells. It involves the fusion of BCL6 with any of its twenty-six Ig and non-Ig translocation partners associated with diffuse large B cell lymphoma (DLBCL). Despite being discovered long back, the mechanism of BCL6 fragility is largely unknown. Analysis of the translocation breakpoints in 5' UTR of BCL6 reveals the clustering of most of the breakpoints around a region termed Cluster II. In silico analysis of the breakpoint cluster sequence identified sequence motifs that could potentially fold into non-B DNA. Results revealed that the Cluster II sequence folded into overlapping hairpin structures and identified sequences that undergo base pairing at the stem region. Further, the formation of cruciform DNA blocked DNA replication. The sodium bisulfite modification assay revealed the single-strandedness of the region corresponding to hairpin DNA in both strands of the genome. Further, we report the formation of intramolecular parallel G4 and triplex DNA, at Cluster II. Taken together, our studies reveal that multiple non-canonical DNA structures exist at the BCL6 cluster II breakpoint region and contribute to the fragility leading to BCL6 translocation in DLBCL patients.

The tobacco GNTI stem region harbors a strong motif for homomeric protein complex formation

IntroductionThe Golgi apparatus of plants is the central cellular organelle for glycan processing and polysaccharide biosynthesis. These essential processes are catalyzed by a large number of Golgi-resident glycosyltransferases and glycosidases whose organization within the Golgi is still poorly understood.MethodsHere, we examined the role of the stem region of the cis/medial Golgi enzyme N-acetylglucosaminyltransferase I (GNTI) in homomeric complex formation in the Golgi of Nicotiana benthamiana using biochemical approaches and confocal microscopy.ResultsTransient expression of the N-terminal cytoplasmic, transmembrane, and stem (CTS) regions of GNTI leads to a block in N-glycan processing on a co-expressed recombinant glycoprotein. Overexpression of the CTS region from Golgi α-mannosidase I, which can form in planta complexes with GNTI, results in a similar block in N-glycan processing, while GNTI with altered subcellular localization or N-glycan processing enzymes located further downstream in the Golgi did not affect complex N-glycan processing. The GNTI-CTS-dependent alteration in N-glycan processing is caused by a specific nine-amino acid sequence motif in the stem that is required for efficient GNTI-GNTI interaction.DiscussionTaken together, we have identified a conserved motif in the stem region of the key N-glycan processing enzyme GNTI. We propose that the identified sequence motif in the GNTI stem region acts as a dominant negative motif that can be used in transient glycoengineering approaches to produce recombinant glycoproteins with predominantly mannosidic N-glycans.

The transcriptional regulator EarA and intergenic terminator sequences modulate archaellation in Pyrococcus furiosus.

The regulation of archaellation, the formation of archaeal-specific cell appendages called archaella, is crucial for the motility, adhesion, and survival of archaeal organisms. Although the heavily archaellated and highly motile Pyrococcus furiosus is a key model organism for understanding the production and function of archaella in Euryarchaea, the transcriptional regulation of archaellum assembly is so far unknown. Here we show that the transcription factor EarA is the master regulator of the archaellum (arl) operon transcription, which is further modulated by intergenic transcription termination signals. EarA deletion or overexpression strains demonstrate that EarA is essential for archaellation in P. furiosus and governs the degree of archaellation. Providing a single-molecule update on the transcriptional landscape of the arl operon in P. furiosus, we identify sequence motifs for EarA binding upstream of the arl operon and intergenic terminator sequences as critical elements for fine-tuning the expression of the multicistronic arl cluster. Furthermore, transcriptome re-analysis across different Thermococcales species demonstrated a heterogeneous production of major archaellins, suggesting a more diverse composition of archaella than previously recognized. Overall, our study provides novel insights into the transcriptional regulation of archaellation and highlights the essential role of EarA in Pyrococcus furiosus. These findings advance our understanding of the mechanisms governing archaellation and have implications for the functional diversity of archaella.

Single-cell multi-omics topic embedding reveals cell-type-specific and COVID-19 severity-related immune signatures

The advent of single-cell multi-omics sequencing technology makes it possible for researchers to leverage multiple modalities for individual cells and explore cell heterogeneity. However, the high-dimensional, discrete, and sparse nature of the data make the downstream analysis particularly challenging. Here, we propose an interpretable deep learning method called moETM to perform integrative analysis of high-dimensional single-cell multimodal data. moETM integrates multiple omics data via a product-of-experts in the encoder and employs multiple linear decoders to learn the multi-omics signatures. moETM demonstrates superior performance compared with six state-of-the-art methods on seven publicly available datasets. By applying moETM to the scRNA+ scATAC data, we identified sequence motifs corresponding to the transcription factors regulating immune gene signatures. Applying moETM to CITE-seq data from the COVID-19 patients revealed not only known immune cell-type-specific signatures but also composite multi-omics biomarkers of critical conditions due to COVID-19, thus providing insights from both biological and clinical perspectives.

Library Screening Reveals Sequence Motifs That Enable ADAR2 Editing at Recalcitrant Sites.

Adenosine deaminases acting on RNA (ADARs) catalyze the hydrolytic deamination of adenosine to inosine in duplex RNA. The inosine product preferentially base pairs with cytidine resulting in an effective A-to-G edit in RNA. ADAR editing can result in a recoding event alongside other alterations to RNA function. A consequence of ADARs' selective activity on duplex RNA is that guide RNAs (gRNAs) can be designed to target an adenosine of interest and promote a desired recoding event. One of ADAR's main limitations is its preference to edit adenosines with specific 5' and 3' nearest neighbor nucleotides (e.g., 5' U, 3' G). Current rational design approaches are well-suited for this ideal sequence context, but limited when applied to difficult-to-edit sites. Here we describe a strategy for the in vitro evaluation of very large libraries of ADAR substrates (En Masse Evaluation of RNA Guides, EMERGe). EMERGe allows for a comprehensive screening of ADAR substrate RNAs that complements current design approaches. We used this approach to identify sequence motifs for gRNAs that enable editing in otherwise difficult-to-edit target sites. A guide RNA bearing one of these sequence motifs enabled the cellular repair of a premature termination codon arising from mutation of the MECP2 gene associated with Rett Syndrome. EMERGe provides an advancement in screening that not only allows for novel gRNA design, but also furthers our understanding of ADARs' specific RNA-protein interactions.

Recombination Hotspots in Soybean [Glycine Max (L.) Merr.

Recombination allows for the exchange of genetic material between two parents which plant breeders exploit to make improved cultivars. This recombination is not distributed evenly across the chromosome. Recombination mostly occurs in euchromatic regions of the genome and even then, recombination is focused into clusters of crossovers termed recombination hotspots. Understanding the distribution of these hotspots along with the sequence motifs associated with them may lead to methods that enable breeders to better exploit recombination in breeding. To map recombination hotspots and identify sequence motifs associated with hotspots in soybean [Glycine max (L.) Merr.], two bi-parental recombinant inbred lines populations were genotyped with the SoySNP50k Illumina Infinium assay. A total of 451 recombination hotspots were identified in the two populations. Despite being half-sib populations, only 18 hotspots were in common between the two populations. While pericentromeric regions did exhibit extreme suppression of recombination, twenty-seven percent of the detected hotspots were located in the pericentromeric regions of the chromosomes. Two genomic motifs associated with hotspots are similar to human, dog, rice, wheat, drosophila, and arabidopsis. These motifs were a CCN repeat motif and a poly-A motif. Genomic regions spanning other hotspots were significantly enriched with the tourist family of mini-inverted-repeat transposable elements that resides in less than 0.34% of the soybean genome. The characterization of recombination hotspots in these two large soybean bi-parental populations demonstrates that hotspots do occur throughout the soybean genome and are enriched for specific motifs but their locations may not be conserved between different populations.

AlphaFold-multimer predicts ATG8 protein binding motifs crucial for autophagy research.

In this issue of PLOS Biology, Ibrahim and colleagues demonstrate how AlphaFold-multimer, an artificial intelligence-based structure prediction tool, can be used to identify sequence motifs binding to the ATG8 family of proteins central to autophagy.

Intramembrane client recognition potentiates the chaperone functions of calnexin

One‐third of the human proteome is comprised of membrane proteins, which are particularly vulnerable to misfolding and often require folding assistance by molecular chaperones. Calnexin (CNX), which engages client proteins via its sugar‐binding lectin domain, is one of the most abundant ER chaperones, and plays an important role in membrane protein biogenesis. Based on mass spectrometric analyses, we here show that calnexin interacts with a large number of nonglycosylated membrane proteins, indicative of additional nonlectin binding modes. We find that calnexin preferentially bind misfolded membrane proteins and that it uses its single transmembrane domain (TMD) for client recognition. Combining experimental and computational approaches, we systematically dissect signatures for intramembrane client recognition by calnexin, and identify sequence motifs within the calnexin TMD region that mediate client binding. Building on this, we show that intramembrane client binding potentiates the chaperone functions of calnexin. Together, these data reveal a widespread role of calnexin client recognition in the lipid bilayer, which synergizes with its established lectin‐based substrate binding. Molecular chaperones thus can combine different interaction modes to support the biogenesis of the diverse eukaryotic membrane proteome.

Method for Identifying Sequence Motifs in Pre-miRNAs for Small-Molecule Binding.

Non-coding RNAs are emerging targets for drug development because they are involved in various cellular processes. However, there are a few reliable design strategies for small molecules that can target RNAs. This paper reports a simple and efficient method to comprehensively analyze RNA motifs that can be bound by a specific small molecule. The method involves Dicer-mediated pre-miRNA cleavage and subsequent analysis of the reaction products by high-throughput sequencing. A pre-miRNA mutant library containing a randomized region at the Dicer cleavage site was used as the substrate for the reaction. Sequencing analysis of the products of the reaction carried out in the presence or absence of a synthetic small molecule identified the pre-miRNA mutants whose Dicer-mediated cleavage was significantly altered by the addition of the small molecule. The binding of the small molecule to the identified pre-miRNA mutants was confirmed by surface plasmon resonance, demonstrating the feasibility of our method.

Direct Detection of Conserved Viral Sequences and Other Nucleic Acid Motifs with Solid-State Nanopores.

The rapid and reliable recognition of nucleic acid sequences is essential to a broad range of fields including genotyping, gene expression analysis, and pathogen screening. For viral detection in particular, the capability is critical for optimal therapeutic response and preventing disease transmission. Here, we report an approach for detecting identifying sequence motifs within genome-scale single-strand DNA and RNA based on solid-state nanopores. By designing DNA oligonucleotide probes with complementarity to target sequences within a target genome, we establish a protocol to yield affinity-tagged duplex molecules the same length as the probe only if the target is present. The product can subsequently be bound to a protein chaperone and analyzed quantitatively with a selective solid-state nanopore assay. We first use a model DNA genome (M13mp18) to validate the approach, showing the successful isolation and detection of multiple target sequences simultaneously. We then demonstrate the protocol for the detection of RNA viruses by identifying and targeting a highly conserved sequence within human immunodeficiency virus (HIV-1B).

Changes in ambient temperature are the prevailing cue in determining Brachypodium distachyon diurnal gene regulation.

Plants are continuously exposed to diurnal fluctuations in light and temperature, and spontaneous changes in their physical or biotic environment. The circadian clock coordinates regulation of gene expression with a 24h period, enabling the anticipation of these events. We used RNA sequencing to characterize the Brachypodium distachyon transcriptome under light and temperature cycles, as well as under constant conditions. Approximately 3% of the transcriptome was regulated by the circadian clock, a smaller proportion than reported in most other species. For most transcripts that were rhythmic under all conditions, including many known clock genes, the period of gene expression lengthened from 24 to 27h in the absence of external cues. To functionally characterize the cyclic transcriptome in B.distachyon, we used Gene Ontology enrichment analysis, and found several terms significantly associated with peak expression at particular times of the day. Furthermore, we identified sequence motifs enriched in the promoters of similarly phased genes, some potentially associated with transcription factors. When considering the overlap in rhythmic gene expression and specific pathway behavior, thermocycles was the prevailing cue that controlled diurnal gene regulation. Taken together, our characterization of the rhythmic B.distachyon transcriptome represents a foundational resource with implications in other grass species.

Influence of the spacer region between the Shine-Dalgarno box and the start codon for fine-tuning of the translation efficiency in Escherichia coli.

SummaryTranslation efficiency contributes several orders of magnitude difference in the overall yield of exogenous gene expression in bacteria. In diverse bacteria, the translation initiation site, whose sequence is the primary determinant of the translation performance, is comprised of the start codon and the Shine–Dalgarno box located upstream. Here, we have examined how the sequence of a spacer between these main components of the translation initiation site contributes to the yield of synthesized protein. We have created a library of reporter constructs with the randomized spacer region, performed fluorescently activated cell sorting and applied next‐generation sequencing analysis (the FlowSeq protocol). As a result, we have identified sequence motifs for the spacer region between the Shine–Dalgarno box and AUG start codon that may modulate the translation efficiency in a 100‐fold range.

A survey of TIR domain sequence and structure divergence

Toll-interleukin-1R resistance (TIR) domains are ubiquitously present in all forms of cellular life. They are most commonly found in signaling proteins, as units responsible for signal-dependent formation of protein complexes that enable amplification and spatial propagation of the signal. A less common function of TIR domains is their ability to catalyze nicotinamide adenine dinucleotide degradation. This survey analyzes 26,414 TIR domains, automatically classified based on group-specific sequence patterns presumably determining biological function, using a statistical approach termed Bayesian partitioning with pattern selection (BPPS). We examine these groups and patterns in the light of available structures and biochemical analyses. Proteins within each of thirteen eukaryotic groups (10 metazoans and 3 plants) typically appear to perform similar functions, whereas proteins within each prokaryotic group typically exhibit diverse domain architectures, suggesting divergent functions. Groups are often uniquely characterized by structural fold variations associated with group-specific sequence patterns and by herein identified sequence motifs defining TIR domain functional divergence. For example, BPPS identifies, in helices C and D of TIRAP and MyD88 orthologs, conserved surface-exposed residues apparently responsible for specificity of TIR domain interactions. In addition, BPPS clarifies the functional significance of the previously described Box 2 and Box 3 motifs, each of which is a part of a larger, group-specific block of conserved, intramolecularly interacting residues.

Neoantigens retention in patient derived xenograft models mediates autologous T cells activation in ovarian cancer

ABSTRACTOvarian cancer (OC) has an overall modest number of mutations that facilitate a functional immune infiltrate able to recognize tumor mutated antigens, or neoantigens. Although patient-derived xenografts (PDXs) can partially model the tumor mutational load and mimic response to chemotherapy, no study profiled a neoantigen-driven response in OC PDXs. Here we demonstrate that the genomic status of the primary tumor from an OC patient can be recapitulated in vivo in a PDX model, with the goal of defining autologous T cells activation by neoantigens using in silico, in vitro and in vivo approaches. By profiling the PDX mutanome we discovered three main clusters of mutations defining the expansion, retraction or conservation of tumor clones based on their variant allele frequencies (VAF). RNASeq analyses revealed a strong functional conservation between the primary tumor and PDXs, highlighted by the upregulation of antigen presenting pathways. We tested in vitro a set of 30 neoantigens for recognition by autologous T cells and identified a core of six neoantigens that define a potent T cell activation able to slow tumor growth in vivo. The pattern of recognition of these six neoantigens indicates the pre-existence of anti-tumor immunity in the patient. To evaluate the breadth of T cell activation, we performed single cell sequencing profiling the TCR repertoire upon stimulation with neoantigenic moieties and identified sequence motifs that define an oligoclonal and autologous T cell response. Overall, these results indicate that OC PDXs can be a valid tool to model OC response to immunotherapy.

The Disordered Landscape of the 20S Proteasome Substrates and the Mechanism of Their in vitro and in vivo Degradation.

Proteasomal degradation is the main route of regulated proteostasis. The 20S proteasome is the core particle (CP) responsible for the catalytic activity of all proteasome complexes. Intrinsically disordered proteins (IDPs) being naturally unfolded may enter the catalytic core of the 20S proteasome. However, what are the attributes of the IDPs that are 20S CP substrates remained an open question. Based on a proteomic analysis of the degradome of the 20S CP activity in vitro we identified a subset of IDPs that are preferential 20S CP substrates (20S-IDPs). The 20S-IDPs are highly disordered, having significantly more protein binding partners and subjected to intensive post-translational modification. Interestingly, the majority of the 20S-IDPs are RNA binding proteins including mainly those involved in splicing and mRNA processing. Cellular peptidome analysis revealed a group of proteins with the 20S-IDP attributes, suggesting that 20S is active in the cells. To further substantiate this notion we identified sequence motifs that are preferred 20S-IDPs cleavage sites and found that IDPs with this motif are highly labile in the cells. We further found 50 amino acid region of the one of the 20S subunits that specifically recognizes IDP and termed it IDP Trapper. The Trapper in isolation binds IDPs and blocks their degradation both in vitro and in the cells. We propose a model whereby a group of IDPs is selectively targeted to the 20S CP in facilitating IDP degradation possibly by the mechanism of 20S gate opening. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Coproheme decarboxylases - Phylogenetic prediction versus biochemical experiments

Coproheme decarboxylases (ChdCs) are enzymes responsible for the catalysis of the terminal step in the coproporphyrin-dependent heme biosynthesis pathway. Phylogenetic analyses confirm that the gene encoding for ChdCs is widespread throughout the bacterial world. It is found in monoderm bacteria (Firmicutes, Actinobacteria), diderm bacteria (e. g. Nitrospirae) and also in Archaea. In order to test phylogenetic prediction ChdC representatives from all clades were expressed and examined for their coproheme decarboxylase activity. Based on available biochemical data and phylogenetic analyses a sequence motif (-Y-P-M/F-X-K/R-) is defined for ChdCs. We show for the first time that in diderm bacteria an active coproheme decarboxylase is present and that the archaeal ChdC homolog from Sulfolobus solfataricus is inactive and its physiological role remains elusive. This shows the limitation of phylogenetic prediction of an enzymatic activity, since the identified sequence motif is equally conserved across all previously defined clades.