Biology subjects

Herbert, A.

Publications and source records attributed to Herbert, A..

At least 19 recordsLinked to original sources

bioRxiv2026

The Greatwall/PP2A-B55α axis remodels the G2/M boundary and shapes cellular dependence on PKMYT1

The switch-like G2/M transition and mitotic exit depend on a feedback loop comprising CDK1, Greatwall kinase, and the PP2A-B55 phosphatase. Monogenic disruptions of these regulators impair cellular functions, drive genomic instability, and promote cancer-associated characteristics. Yet how perturbations of this feedback loop interact, and whether their effects depend on cellular context, remain unclear. Here, we assess how combinatorial perturbations of CDK1, Greatwall, and PP2A-B55 affect cell-cycle control in non-transformed RPE-1 and tumour-derived HeLa cells. We identify PP2A-B55 as a context-dependent G2/M repressor with a critical role in cancer cells, where it cooperates with PKMYT1 and, to a lesser extent, WEE1 to prevent premature mitosis. In cancer cells, but not in non-transformed cells, reduced PP2A-B55 activity and Greatwall overexpression produce marked sensitisation to the PKMYT1-selective RP-6306 and modest sensitisation to the WEE1-selective adavosertib. This asymmetric sensitisation reflects a functional separation between WEE1 and PKMYT1 in S- and G2-phase control. Our work outlines fundamental and cell-type-specific contributions of CDK1, Greatwall and PP2A-B55 to cell-cycle regulation and proposes G2/M plasticity as a vulnerability with utility in PKMYT1-targeted therapy.

cell biology↗

bioRxiv2026

The YTHDC1 glutamate-rich domain docks to the ADAR1 Zα Domain, linking the N6-methyladenosine modification of pre-mRNAs to dsRNA editing

The p150 isoform of the double-stranded RNA editing enzyme ADAR1 binds Z-DNA and Z-RNA through the conserved winged helix-turn-helix Z domain. Here, we describe an inverse computational design strategy to map protein interactors of Z. We used RFdiffusion and ProteinMPNN to generate [~]10,000 synthetic binders optimized for the Z recognition surface, then used their sequences as structural templates for BLASTp searches against the human proteome. Multi-stage screening of [~]1,200 candidate regions from 298 proteins via ColabFold pDockQ identified 79 candidates for high-resolution AlphaFold3 modeling, which revealed the m6A reader YTHDC1 as the top-ranked interactor. AlphaFold3 predicts that a glutamate-rich poly-E disordered region of YTHDC1 (residues 199-254) docks into the basic recognition pocket of Z through a charge-complementary mechanism that mimics the phosphate backbone of Z-RNA. Microsecond molecular dynamics simulations confirmed stability of the binary ADAR1p150-YTHDC1 complex, with the Z-poly-E interface maintaining RMSD below 3 [A] throughout. Ternary complex simulations showed that dsRNA acts as a co-anchoring scaffold stabilizing simultaneous engagement of both proteins in a catalytically dormant conformation. YTHDC1 localizes to transcription-associated YT bodies where nascent RNAs undergo m6A modification and negative supercoiling promotes Z-DNA formation, suggesting that YTHDC1 recruits ADAR1p150 to promote editing of intron-containing substrates prior to splicing. Short StatementADAR1 can edit RNAs after they are made, changing the message they carry and removing double-stranded RNAs that can activate inflammatory responses. Using AI-driven protein design, we discovered that ADAR1 physically interacts with YTHDC1, a protein that recognizes newly made self-RNAs. The interaction allows ADAR to edit RNAs as they are made. This unexpected connection between two fundamental RNA modification systems opens new avenues for understanding and potentially targeting autoimmune disorders and cancers driven by the mis-editing of RNA transcripts.

bioinformatics↗

bioRxiv2026

Divergent RNA structures support accurate splicing of the SF3B1-sensitive MAP3K7 intron

Splicing is governed by interactions between the spliceosome and precursor RNA sequence and structural elements. However, the relative contributions of RNA sequence and structural elements remain unclear. Here, we systematically dissect these determinants using a high-throughput mutagenesis approach with the MAP3K7 intron reporter. The MAP3K7 gene encodes a serine/threonine kinase involved in response to environmental stress. MAP3K7 precursor RNA contains a cryptic 3 splice site that increases in use when the core spliceosomal protein SF3B1 is mutated. SF3B1 mutations are known to promote aberrant splicing and are associated with cancer, particularly the lysine 700 to glutamate mutation (K700E). We designed a pooled library of 249 MAP3K7 mutants targeting branch points, RNA-binding protein motifs, nucleotide composition and predicted structural elements. The impact of these mutants on splicing was measured in the context of normal and SF3B1 K700E expression. RNA structure was assessed in parallel using in vitro high-throughput SHAPE-MAP chemical probing. We found that branchpoint mutations drive the strongest increases in cryptic splice-site use. There is no overall correlation between cryptic splice-site use and structural similarity to the wild-type MAP3K7 RNA. However, mutants within an RNA binding protein hotspot (containing U2AF2, U2AF1, KHSRP and SRSF2 sites) are associated with cryptic splice-site use and structural similarity to wild-type MAP3K7 RNA. These structural changes are associated with increased ensemble diversity. Our results demonstrate that although there are key structured regions within an RNA, there is also extensive variability where divergent RNA structures allow for accurate splicing.

molecular biology↗

bioRxiv2025

Zα and Zβ domains of ADAR1 and ZBP1 bind to G-quadruplexes with low micromolar affinity

1While it is well established that the Z domains of ADAR1 and ZBP1 proteins bind Z-form-prone nucleic acids (Z-NAs), it has also been shown that the Z domain of ADAR1 binds DNA G-Quadruplexes (GQ). However, no binding partner of the structurally homologous Z{beta} domain of ADAR1 has been identified to date. Based on AlphaFold and molecular dynamics simulations, it has recently been suggested that the Z{beta} domain of ADAR1 targets its substrate by recognizing GQs. Here, we provide the first experimental evidence for Z{beta} domain binding to select G-quadruplex RNA and DNA in vitro, with structural specificity and low micromolar affinity. We also demonstrate that the Z domains of ZBP1 bind to both DNA and RNA GQs with similar affinity. These findings extend the range of potential functional roles for these proteins and open new hypotheses for testing in cells.

biophysics↗

bioRxiv2025

OmicsFUSION: A Pretrained Hyena-Based Framework for Encoding, Reconstruction, and Representation of the Omics and DNA Data

Recent advances in Natural Language Processing (NLP) have spurred the application of Large Language Models (LLMs) to bioinformatics, enabling innovative approaches to DNA sequence encoding. However, genomic function is not solely determined by the primary DNA sequence--it also depends on complex, multi-layered omics data. This auxiliary data is inherently sparse, structured across multiple tracks, and poses a challenge for traditional unimodal approaches. Simultaneously, many bioinformatics tasks demand a unified signal source that encapsulates this information, rather than requiring researchers to input each omics feature individually. To overcome these limitations, we introduce a novel framework for the integrated representation of DNA sequences and their associated omics data. Central to our approach is a large-scale, batch-structured omics dataset optimized for deep learning at scale. Our framework is built around four key novelties: (1) a new model architecture that jointly processes DNA and omics signals; (2) an extension of Masked Language Modeling (MLM) to omics tracks for effective data reconstruction; (3) single-nucleotide embeddings that fuse all input modalities; and (4) interval-level embeddings that summarize broader genomic regions. We release a collection of pretrained models capable of reconstructing, embedding, and generating unified representations of DNA enriched with functional omics context. Codehttps://github.com/aaai-2025-submission/anomymous_submission_aaai2025 Model and Datasetshttps://drive.google.com/drive/folders/10hcuq4rTCr8bKQFqkpz7R91MGtKvR0Va?usp=sharing

bioinformatics↗

bioRxiv2025

Design and Characterisation of Photoactivatable and Lysine Reactive o-Nitrobenzyl Alcohol-Based Crosslinkers

Photoreactive groups are invaluable tools in structural proteomics, offering reagent-free activation and temporal control of protein labelling. However, traditional UV-activatable functional groups often produce unstable intermediates and diverse products, making these chemistries difficult to deploy at scale. In this study, we performed a systematic analysis of ortho-nitrobenzyl alcohol (oNBA) reactivity for integration into novel reagents for chemical crosslinking-mass spectrometry. oNBA photochemistry represents a promising alternative to traditional photoactivatable crosslinkers due to its unique specificity towards lysine residues. Here, we synthesised two molecules comprising oNBA functional groups with different substituents and assessed their labelling efficiency against a model protein. To ensure high labelling yields while maintaining a short irradiation time, we constructed a high power 365 nm irradiation device which improves the efficiency of oNBA photolysis. Our studies identified an amide-substituted probe that labels proteins with high efficiency. We next incorporated this optimised oNBA moiety into a homo-bifunctional crosslinker and a hetero-bifunctional crosslinker in combination with an NHS ester, which both resulted in high yields of crosslinked products. Our findings highlight that optimised oNBA-based reactive groups are viable UV-activated warheads that can deliver high labelling yields and efficient protein crosslinking, unlocking a wealth of potential structural proteomics applications.

biophysics↗

bioRxiv2025

OmiXAI: An Ensemble XAI Pipeline for Interpretable Deep Learning in Omics Data

Deep learning methods have become methods of choice in the analysis of genomic data. The performance of deep learning models depends on the information available for training. A growing trend in deep learning applications involves leveraging multi-omics data--spanning genomics, transcriptomics, epigenomics, proteomics, metabolomics, and other domains. When a deep learning model trained on omics data achieves high performance, the important question is to define factors that contribute to models predictive power. Explainable AI (XAI) methods can be categorized as model-aware and model-agnostic. Model-agnostic approaches, which rely on combinatorial feature perturbations to assess impact, are often computationally prohibitive for deep learning models. To address this, we developed OmiXAI, a pipeline integrating ensemble model-aware XAI methods. Our framework incorporates gradient-based techniques--including Integrated Gradients, InputXGradients, Guided Backpropagation, and Deconvolution (for CNNs and GNNs)--as well as Saliency Maps and GNNExplainer (specifically for GNNs). We evaluated OmiXAI on Z-DNA prediction using multi-omics features, demonstrating its efficacy through feature importance analysis and benchmarking of XAI methods. Notably, OmiXAI enabled feature engineering, reducing the critical feature set from almost 2,000 to just 50. Its modular design allows seamless integration of additional attribution methods, ensuring adaptability beyond omics to diverse problem domains. While testing the ensemble approach we benchmarked individual XAI methods and discuss their drawbacks and limitations. OmiXAI is freely available at https://github.com/aameliig/OmiXAI.

bioinformatics↗

bioRxiv2025

Precursor RNA structural patterns at SF3B1 mutation sensitive cryptic 3' splice sites

SF3B1 is a core component of the spliceosome involved in branch point recognition and 3 splice site selection. SF3B1 mutation is common in myelodysplastic syndrome and other blood disorders. The most common mutation in SF3B1 is K700E, a lysine to glutamic acid change within the pre-mRNA interacting heat repeat domain. A hallmark of SF3B1 mutation is an increased use of cryptic 3 splice sites; however, the properties distinguishing SF3B1-sensitive splice junctions from other alternatively spliced junctions are unknown. We identify a subset of 192 core splice junctions that are mis-spliced with SF3B1 K700E mutation. We use our core set to test whether SF3B1-sensitive splice sites are different from control cryptic 3 splice sites via RNA structural accessibility. As a comparison, we define a set of SF3B1-resistant splice junctions with cryptic splice site use that does not change with SF3B1 K700E mutation. We find sequence differences between SF3B1-sensitive and SF3B1-resistant junctions, particularly at the cryptic sites. SF3B1-sensitive cryptic 3 splice sites are within an extended polypyrimidine tract and have lower splice site strength scores. We develop experimental RNA structure data for 83 SF3B1-sensitive junctions and 39 SF3B1-resistant junctions. We find that the pattern of structural accessibility at the NAG splicing motif in cryptic and canonical 3 splice sites is similar. In addition, this pattern can be found in both SF3B1-resistant and SF3B1-sensitive junctions. However, SF3B1-sensitive junctions have cryptic splice sites that are less structurally distinct from the canonical splice sites. In addition, SF3B1-sensitive splice junctions are overall more flexible than SF3B1-resistant junctions. Our results suggest that the SF3B1-sensitive splice junctions have unique structure and sequence properties, containing poorly differentiated, weak splice sites that lead to altered 3 splice site recognition in the presence of SF3B1 mutation.

molecular biology↗

bioRxiv2024

Altered polyadenylation site usage in SERPINA1 3'UTR in response to cellular stress affects A1AT protein expression

Alternative polyadenylation results in different 3 isoforms of messenger RNA (mRNA) transcripts. Alternative polyadenylation in the 3 untranslated region (3UTR) can alter RNA localization, stability and translational efficiency. The SERPINA1 mRNA has two distinct 3 UTR isoforms, both of which express the protease inhibitor -1-antitrypsin (A1AT). A1AT is an acute phase protein that is expressed and secreted from liver hepatocytes and upregulated during inflammation. Low levels of A1AT in the lung contributes to chronic obstructive pulmonary disease, while misfolding of A1AT in the liver contributes to liver cirrhosis. We analyzed the dynamics of alternative polyadenylation during cellular stress by treating the liver cell line HepG2 with the cytokine interleukin 6 (IL-6), ethanol or peroxide. SERPINA1 is transcriptionally upregulated after IL-6 treatment and has altered polyadenylation, resulting in an increase in long 3UTR isoforms. We find that the long 3UTR represses endogenous A1AT protein expression even with high levels of SERPINA1 mRNA. SERPINA1 expression and 3 end processing were not affected by ethanol or peroxide. IL-6-induced changes in transcriptome-wide transcriptional regulation suggest changes to the endoplasmic reticulum and in secretory protein processing. Our data suggest that inflammation influences polyA site choice for SERPINA1 transcripts, resulting in reduced A1AT protein expression.

molecular biology↗

bioRxiv2024

Analysis of live cell data with G-DNABERT supports a role for G-quadruplexes in chromatin looping

Alternative DNA conformation formed by sequences called flipons potentially alter the readout of genetic information by directing the shape-specific assembly of complexes on DNA The biological roles of G-quadruplexes formed by motifs rich in guanosine repeats have been investigated experimentally using many different methodologies including G4-seq, G4 ChIP-seq, permanganate nuclease footprinting (KEx), KAS-seq, CUT&Tag with varying degrees of overlap between the results. Here we trained large language model DNABERT on existing data generated by KEx, a rapid chemical footprinting technique performed on live, intact cells using potassium permanganate. The snapshot of flipon state when combined with results from other in vitro methods that are performed on permeabilized cells, allows a high confidence mapping of G-flipons to proximal enhancer and promoter sequences. Using G4-DNABERT predictions,with data from ENdb, Zoonomia cCREs and single cell G4 CUT&Tag experiments, we found support for a model where G4-quadruplexes regulate gene expression through chromatin loop formation.

bioinformatics↗

bioRxiv2024

Centromere protection requires strict mitotic inactivation of the Bloom syndrome helicase complex

The BTRR (BLM/TOP3A/RMI1/RMI2) complex resolves various DNA replication and recombination intermediates to suppress genome instability. Alongside PICH, they target mitotic DNA intertwinements, known as ultrafine DNA bridges, facilitating chromosome segregation. Both BLM and PICH undergo transient mitotic hyper-phosphorylation, but the biological significance of this remains elusive. Here, we uncover that during early mitosis, multiple protein kinases act together to strictly constrain the BTRR complex for the protection of centromeres. Mechanistically, CDK1 destabilises the complex and suppresses its association with PICH at the chromatin underneath kinetochores. Inactivating the BLM and TOP3A interaction compromises the UFB-binding complex mitotic functions and can prevent centromere destruction. We further unravel how different clusters of mitotic phosphorylation on BLM affect its interaction with the TOP3A/RMI1/RMI2 subcomplex and illegitimate centromere unwinding. Furthermore, we identify specific phosphorylation sites targeted by the MPS1-PLK1 axis functioning to prevent BLM hyper-activation at centromeres. Notably, unleashing such activity after sister-chromatid cohesion loss facilitates separation of entangled chromosomes. Together, our study defines a centromere protection pathway in human mitotic cells, heavily reliant on a tight spatiotemporal control of the BTRR complex.

cell biology↗

bioRxiv2024

Engineering, structure, and immunogenicity of a Crimean-Congo hemorrhagic fever virus pre-fusion heterotrimeric glycoprotein complex

Crimean-Congo hemorrhagic fever virus (CCHFV) is a tick-borne virus that can cause severe disease in humans with case fatality rates of 10-40%. Although structures of CCHFV glycoproteins GP38 and Gc have provided insights into viral entry and defined epitopes of neutralizing and protective antibodies, the structure of glycoprotein Gn and its interactions with GP38 and Gc have remained elusive. Here, we used structure-guided protein engineering to produce a stabilized GP38-Gn-Gc heterotrimeric glycoprotein complex (GP38-GnH-DS-Gc). A cryo-EM structure of this complex provides the molecular basis for GP38s association on the viral surface, reveals the structure of Gn, and demonstrates that GP38-Gn restrains the Gc fusion loops in the prefusion conformation, facilitated by an N-linked glycan attached to Gn. Immunization with GP38-GnH-DS-Gc conferred 40% protection against lethal IbAr10200 challenge in mice. These data define the architecture of a GP38-Gn-Gc protomer and provide a template for structure-guided vaccine antigen development.

microbiology↗

bioRxiv2023

Z-Flipons conserved between human and mouse are associated with increased transcription initiation rates

A long-standing question concerns the role of Z-DNA in transcription. Here we use a deep learning approach based on the published DeepZ algorithm that predicts Z-flipons based on DNA sequence, structural properties of nucleotides and omics data. We examined Z-flipons that are conserved between human and mouse genomes after generating whole-genome Z-flipons maps by training DeepZ on ChIP-seq Z-DNA data, then overlapping the results with a common set of omics data features. We revealed similar pattern of transcription factors and histone marks associated with conserved Z-flipons, showing enrichment for transcription regulation coupled with chromatin organization. 15% and 7% of conserved Z-flipons fell in alternative and bidirectional promoters. We found that conserved Z-flipons in CpG-promoters are associated with increased transcription initiation rates. Our findings empower further experimental explorations to examine how the flip to Z-DNA alters the readout of genetic information by facilitating the transition of one epigenetic state to another.

bioinformatics↗

bioRxiv2023

Z-Flipon Variants reveal the many roles of Z-DNA and Z-RNA in health and disease

Identifying roles for Z-flipons remains challenging given their dynamic nature. Here we perform genome-wide interrogation with the DNABERT transformer algorithm trained on experimentally identified Z-DNA sequences. We show Z-flipons are enriched in promoters and telomeres and overlap quantitative trait loci for RNA expression, RNA editing, splicing and disease associated variants. Surprisingly, many effects are mediated through Z-RNA formation. We describe Z-RNA motifs present in SCARF2, SMAD1 and CACNA1 transcripts and others in non-coding RNAs. We also provide evidence for another Z-RNA motif that likely enables an adaptive anti-viral intracellular defense through alternative splicing of KRAB domain zinc finger proteins. An analysis of OMIM and gnomAD predicted loss-of-function datasets reveals an overlap of predicted and experimentally validated Z-flipons with disease causing variants in 8.6% and 2.9% of mendelian disease genes respectively, with frameshift variants present in 22% of cases. The work greatly extends the number of phenotypes mapped to Z-flipon variants.

genomics↗

bioRxiv2022

Graph Neural Networks for Z-DNA prediction in Genomes

Deep learning methods have been successfully applied to the tasks of predicting functional genomic elements such as histone marks, transcriptions factor binding sites, non-B DNA structures, and regulatory variants. Initially convolutional neural networks (CNN) and recurrent neural networks (RNN) or hybrid CNN-RNN models appeared to be the methods of choice for genomic studies. With the advance of machine learning algorithms other deep learning architectures started to outperform CNN and RNN in various applications. Thus, graph neural network (GNN) applications improved the prediction of drug effects, disease associations, protein-protein interactions, protein structures and their functions. The performance of GNN is yet to be fully explored in genomics. Earlier we developed DeepZ approach in which deep learning model is trained on information both from sequence and omics data. Initially this approach was implemented with CNN and RNN but is not limited to these classes of neural networks. In this study we implemented the DeepZ approach by substituting RNN with GNN. We tested three different GNN architectures - Graph Convolutional Network (GCN), Graph Attention Network (GAT) and inductive representation learning network GraphSAGE. The GNN models outperformed current state-of the art RNN model from initial DeepZ realization. Graph SAGE showed the best performance for the small training set of human Z-DNA ChIP-seq data while Graph Convolutional Network was superior for specific curaxin-induced mouse Z-DNA data that was recently reported. Our results show the potential of GNN applications for the task of predicting genomic functional elements based on DNA sequence and omics data. Availability and implementationThe code is freely available at https://github.com/MrARVO/GraphZ.

bioinformatics↗

bioRxiv2022

A role for Flipons and miRNAs in Promoter Specification during Development?

The classical view of gene regulation is based on prokaryotic models and the operon concept with protein-based transcription factors controlling the expression of metabolic pathways essential for bacterial adaptations in response to environmental changes. A new view for establishing cell identity is emerging in eukaryotes where RNA-based pathways provide the framework for the readout of genomic information. Another perspective poses that alternative DNA structures encoded by flipons enable switching of cellular responses from one state to another. Here we provide evidence that these RNA and DNA mechanisms are deeply connected. We present data supporting a model where flipons open up binding sites for microRNAs (miRNAs), leading to the establishment of bivalent promoters early in development whose location structures lineage-specific events. These outcomes are potentially influenced by ovarian and spermatozoan miRNAs, transmissions with evident evolutionary ramifications. The data supports a new perspective on genetic regulation, one in which the genome provides a canvas framed by flipons, sketched with miRNAs and embellished by proteins.

genetics↗

bioRxiv2022

Z-RNA and the flipside of the SARS Nsp13 helicase

We present evidence that the severe acute respiratory syndrome coronavirus (SARS) non-structural protein 13 (Nsp13) modulates the Z-RNA dependent regulated cell death pathways [1]. We show that Z-prone sequences (called flipons [2]) exist in coronavirus and provide a signature (Z-sig) that enables identification of the animal viruses from which the human pathogens arose. We also identify a potential RIP Homology Interaction Motif (RHIM) in the helicase Nsp13 that resembles those present in proteins that initiate Z-RNA-dependent cell death through interactions with the Z-RNA sensor protein ZBP1. These two observations allow us to suggest a model in which Nsp13 down regulates Z-RNA activated innate immunity by two distinct mechanisms. The first involves a novel ATP-independent Z-flipon helicase (flipase) activity in Nsp13 that differs from that of canonical A-RNA helicases. This flipase prevents formation of Z-RNAs that would otherwise activate cell death pathways. The second mechanism likely inhibits the interactions between ZBP1 and the Receptor Interacting Proteins Kinases RIPK1 and RIPK3 by targeting their RHIM domains. Together the described Nsp13 RHIM and flipase activities have the potential to alter the host response to coronaviruses and impact the design of drugs targeting the Nsp13 protein. The Z-sig and RHIM domains may provide a way of identifying previously uncharacterized viruses that are potentially pathogenic for humans.

microbiology↗

bioRxiv2021

Synthetic repertoires derived from convalescent COVID-19 patients enable discovery of SARS-CoV-2 neutralizing antibodies and a novel quaternary binding modality

The ongoing evolution of SARS-CoV-2 into more easily transmissible and infectious variants has sparked concern over the continued effectiveness of existing therapeutic antibodies and vaccines. Hence, together with increased genomic surveillance, methods to rapidly develop and assess effective interventions are critically needed. Here we report the discovery of SARS-CoV-2 neutralizing antibodies isolated from COVID-19 patients using a high-throughput platform. Antibodies were identified from unpaired donor B-cell and serum repertoires using yeast surface display, proteomics, and public light chain screening. Cryo-EM and functional characterization of the antibodies identified N3-1, an antibody that binds avidly (Kd,app = 68 pM) to the receptor binding domain (RBD) of the spike protein and robustly neutralizes the virus in vitro. This antibody likely binds all three RBDs of the trimeric spike protein with a single IgG. Importantly, N3-1 equivalently binds spike proteins from emerging SARS-CoV-2 variants of concern, neutralizes UK variant B.1.1.7, and binds SARS-CoV spike with nanomolar affinity. Taken together, the strategies described herein will prove broadly applicable in interrogating adaptive immunity and developing rapid response biological countermeasures to emerging pathogens.

synthetic biology↗