Biology subjects

Leem, J.

Publications and source records attributed to Leem, J..

12 recordsLinked to original sources

bioRxiv2026

A cohesion optimum underlies chromosome segregation fidelity in oocytes

Chromosome segregation is compromised in eggs from women of both early and advanced reproductive ages. Deteriorating cohesion causes premature separation of sister-chromatids in eggs from older females. We show that the converse is true for oocytes of adolescents, with excessive cohesion impeding segregation. Oocytes from juvenile mice show severe chromosome lagging in anaphase I, leading to nondisjunction or, in extreme cases, failure of the first meiotic division. These defects are suppressed by experimentally weakening cohesion or enhancing its resolution during anaphase I. By contrast, lagging and nondisjunction are rare in the oocytes of young adults because cohesion is inherently weaker. Thus, relative cohesion strength underlies both the frequency and type of segregation errors observed in eggs throughout the female reproductive lifespan. One-Sentence SummaryIn eggs, errors in chromosome segregation arise from age-dependent imbalances in how tightly chromosomes are held together.

cell biology↗

bioRxiv2026

The cytoplasmic lattice in mammalian eggs sequesters ubiquitination machinery and tubulin in reserve

The cytoplasmic lattice (CPL) in mammalian eggs is essential for early embryonic development, but its molecular components, structural organization, and functional capacity have remained elusive. Here, using cryo-electron microscopy, we show that the CPL filament in mouse eggs contains repeating units with a periodicity of [~]37 nm, and determine its high-resolution, native structure and complete subunit composition. The CPL architecture organizes maternal-effect proteins, ubiquitination machinery, and tubulin into a highly structured reservoir. Maternal-effect proteins form the scaffold of the CPL to sequester a UBE2D-UHRF1 E2-E3 ubiquitination module and three distinct FBXW E3 ubiquitin ligases, notably all in activity-excluded states. The CPL further contains an {beta}-tubulin heterodimer in a GTP-bound state with a calcium ion coordinated to -tubulin, suggesting microtubule assembly-competent tubulin held in reserve. The CPL structure is capped at each end by a terminal unit that lacks a PADI6 dimer, a scaffold component, thereby preventing further oligomerization. Interactions between maternal-effect proteins in adjacent CPL units promote the assembly of a three-dimensional lattice in the egg cytoplasm. Taken together, our work defines how CPL assembly and architecture prime mammalian eggs for ubiquitin-mediated protein degradation and cytoskeletal remodeling during the egg-to-embryo transition.

biophysics↗

bioRxiv2025

A versatile cohesion manipulation system reveals CENP-A dysfunction accelerates female reproductive age-related egg aneuploidy.

Female reproductive aging is accompanied by a dramatic rise in the incidence of egg aneuploidy. Premature loss of chromosome cohesion proteins and untimely separation of chromosomes is thought to underly high rates egg aneuploidy during maternal aging. However, because chromosome cohesion loss occurs gradually over female reproductive lifespan and cytoskeletal defects alone can predispose eggs to chromosomal abnormalities, the root causes of exponential rise in egg aneuploidy at advanced reproductive ages remain a mystery. Here, we applied high-resolution live imaging to visualize for the first time cohesion protein dynamics underpinning meiotic chromosome segregation. To discover proteins whose dysfunction accelerates aneuploidies associated with female reproductive aging, we innovated the first experimental system in which chemically induced cohesion reduction rapidly triggers aging-like chromosomal abnormalities in young eggs. By integrating this direct cohesion manipulation system with quantitative high-resolution microscopy and targeted protein degradation tools, we identified the centromeric protein CENP-A as a new factor whose aging-like depletion causes a dramatic rise in premature separation of sister chromatids. Our work illuminates cohesion loss-independent origins of age-related egg aneuploidy and provides new avenues to discover therapeutic targets for extending the female reproductive lifespan.

cell biology↗

bioRxiv2024

A generative foundation model for antibody sequence understanding

Here we introduce FAbCon, a generative antibody-specific language model comprising 2.4 billion parameters. A commonly accepted wisdom in developing large language models is that increasing model scale will translate to higher performance on downstream tasks. Starting from a 144-million parameter setup, we show that progressively larger models achieve greater accuracy in predicting antigen binding and can also be used to design new antibodies with good predicted developability potential. FAbCon is available on huggingface.co/alchemab.

bioinformatics↗

bioRxiv2024

Enhancing Antibody Language Models with Structural Information

The central tenet of molecular biology is that a proteins amino acid sequence determines its three-dimensional structure, and thus its function. However, proteins with similar sequences do not always fold into the same shape, and vice-versa, dissimilar sequences can adopt similar folds. In this work, we explore antibodies, a class of proteins in the immune system, whose local shapes are highly unpredictable, even with small variations in their sequence. Inspired by the CLIP method [1], we propose a multimodal contrastive learning approach, contrastive sequence-structure pre-training (CSSP), which amalgamates the representations of antibody sequences and structures in a mutual latent space. Integrating structural information leads both antibody and protein language models to show better correspondence with structural similarity and improves accuracy and data efficiency in downstream binding prediction tasks. We provide an optimised CSSP-trained model, AntiBERTa2-CSSP, for non-commercial use at https://huggingface.co/alchemab.

bioinformatics↗

bioRxiv2023

Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling

Immunoglobulins (Ig), which exist either as B-cell receptors (BCR) on the surface of B cells or as antibodies when secreted, play a key role in the recognition and response to antigenic threats. The capability to jointly characterize the BCR and antibody repertoire is crucial in understanding human adaptive immunity. From peripheral blood, bulk BCR sequencing (bulkBCR-seq) currently provides the highest sampling depth, single-cell BCR sequencing (scBCR-seq) allows for paired chain characterization, and antibody peptide sequencing by tandem mass spectrometry (Ab-seq) provides information on the composition of secreted antibodies in the serum. Although still rare, studies combining these three technologies would comprehensively capture the humoral immune response. Yet, it has not been benchmarked to what extent the datasets generated by these three technologies overlap and complement each other. To address this question, we isolated peripheral blood B cells from healthy donors and sequenced BCRs at bulk and single-cell level, in addition to utilizing publicly available sequencing data. Integrated analysis was performed on these datasets, resolved by replicates and across individuals. Simultaneously, serum antibodies were isolated, digested with multiple proteases, and analyzed with Ab-seq. Systems immunology analysis showed high concordance in repertoire features between bulk and scBCR-seq within individuals, especially when replicates were utilized. In addition, Ab-seq identified clonotype-specific peptides using both bulk and scBCR-seq library references, demonstrating the feasibility of combining scBCR-seq and Ab-seq for reconstructing paired-chain Ig sequences from the serum antibody repertoire. Collectively, our work serves as a proof-of-principle for combining bulk sequencing, single-cell sequencing, and mass spectrometry as complementary methods towards capturing humoral immunity in its entirety.

immunology↗

bioRxiv2022

Oocytes can repair DNA damage during meiosis via a microtubule-dependent recruitment of CIP2A-MDC1-TOPBP1 complex from spindle pole to chromosomes

Because DNA double-strand breaks (DSBs) greatly threaten genomic integrity, effective DNA damage sensing and repair are essential for cellular survival in all organisms. However, DSB repair mainly occurs during the interphase and is repressed during mitosis. Here, we show that, unlike mitotic cells, oocytes can repair DSBs during meiosis through microtubule-dependent chromosomal recruitment of the CIP2A-MDC1-TOPBP1 complex from spindle poles. After DSB induction, we observed spindle shrinkage and stabilization, as well as BRCA1 and 53BP1 recruitment to chromosomes and subsequent DSB repair during meiosis I. Moreover, p-MDC1 and p-TOPBP1 were recruited from spindle poles to chromosomes in a CIP2A-dependent manner. This pole-to-chromosome relocation of the CIP2A-MDC1-TOPBP1 complex was impaired not only by depolymerizing microtubules but also by depleting CENP-A or HEC1, indicating that the kinetochore/centromere serves as a structural hub for microtubule-dependent transport of the CIP2A-MDC1-TOPBP1 complex. Mechanistically, DSB-induced CIP2A-MDC1-TOPBP1 relocation is regulated by PLK1 but not by ATM activity. Our data provide new insights into the critical crosstalk between chromosomes and spindle microtubules in response to DNA damage to maintain genomic stability during oocyte meiosis.

cell biology↗

bioRxiv2021

Deciphering the language of antibodies using self-supervised learning

An individuals B cell receptor (BCR) repertoire encodes information about past immune responses, and potential for future disease protection. Deciphering the information stored in BCR sequence datasets will transform our fundamental understanding of disease and enable discovery of novel diagnostics and antibody therapeutics. One of the grand challenges of BCR sequence analysis is the prediction of BCR properties from their amino acid sequence alone. Here we present an antibody-specific language model, AntiBERTa, which provides a contextualised representation of BCR sequences. Following pre-training, we show that AntiBERTa embeddings learn biologically relevant information, generalizable to a range of applications. As a case study, we demonstrate how AntiBERTa can be fine-tuned to predict paratope positions from an antibody sequence, outperforming public tools across multiple metrics. To our knowledge, AntiBERTa is the deepest protein family-specific language model, providing a rich representation of BCRs. AntiBERTa embeddings are primed for multiple downstream tasks and can improve our understanding of the language of antibodies.

bioinformatics↗

bioRxiv2021

AbDiver - A tool to explore the natural antibody landscape to aid therapeutic design

MotivationRational design of therapeutic antibodies can be improved by harnessing the natural sequence diversity of these molecules. Our understanding of the diversity of antibodies has recently been greatly facilitated through the deposition of hundreds of millions of human antibody sequences in next-generation sequencing (NGS) repositories. Contrasting a query therapeutic antibody sequence to naturally observed diversity in similar antibody sequences from NGS can provide a mutational road-map for antibody engineers designing biotherapeutics. Because of the sheer scale of the antibody NGS datasets, performing queries across them is computationally challenging. ResultsTo facilitate harnessing antibody NGS data, we developed AbDiver (http://naturalantibody.com/abdiver), a free portal allowing users to compare their query sequences to those observed in the natural repertoires. AbDiver offers three antibody-specific use-cases: 1) compare a query antibody to positional variability statistics precomputed from multiple independent studies 2) retrieve close full variable sequence matches to a query antibody and 3) retrieve CDR3 or clonotype matches to a query antibody. We applied our system to a set of 742 therapeutic antibodies, demonstrating that for each use-case our system can retrieve relevant results for most sequences. AbDiver facilitates the navigation of vast antibody mutation space for the purpose of rational therapeutic antibody design and engineering. AvailabilityAbDiver is freely accessible at http://naturalantibody.com/abdiver.

bioinformatics↗

bioRxiv2020

Synapsin-caveolin-1 mitigates cognitive deficits and neurodegeneration in Alzheimer's disease mice

AD presents with severe neurodegeneration which leads to cognitive deficits and dementia. Identifying the molecular signals that attenuate neurodegeneration in AD may be exploited as therapeutic targets. This study revealed that transgenic AD mice (PSAPP) exhibit decreased caveolin-1 (Cav-1), a membrane/lipid raft (MLR) scaffolding protein that organizes synaptic signaling components. Subcellularly, Cav-1 and full length (fl)-TrkB were significantly decreased in MLRs. We thus developed an in vivo gene therapy that re-expresses neuronal-targeted Cav-1 using the synapsin promoter (SynCav1). While AD mice showed significant learning and memory deficits at 9 and 11 months, AD mice that received hippocampal SynCav1 (AD-SynCav1) maintained normal learning and memory at 9 and 11 months respectively. Furthermore, AD-SynCav1 mice showed preserved hippocampal MLR-localized fl-TrkB, synaptic ultrastructure, dendritic arborization and axonal myelin content, all of which occurred independent of reducing amyloid deposit and astrogliosis. Thus, SynCav1 demonstrates translational potential to treat AD by delaying neurodegeneration. SummaryTransgenic PSAPP mice exhibit decreased hippocampal expression of the membrane lipid raft (MLR) scaffolding protein caveolin-1. Synapsin-promoted re-expression of Cav-1 (termed SynCav1) mitigated neuropathology and cognitive deficits. SynCav1 gene therapy has the potential to treat AD and other forms of neurodegeneration.

neuroscience↗

bioRxiv2019

Comparative analysis of the CDR loops of antigen receptors

The adaptive immune system uses two main types of antigen receptors: T-cell receptors (TCRs) and antibodies. While both proteins share a globally similar {beta}-sandwich architecture, TCRs are specialised to recognise peptide antigens in the binding groove of the major histocompatibility complex, while antibodies can bind an almost infinite range of molecules. For both proteins, the main determinants of target recognition are the complementarity-determining region (CDR) loops. Five of the six CDRs adopt a limited number of backbone conformations, known as the canonical classes; the remaining CDR ({beta}3 in TCRs and H3 in antibodies) is more structurally diverse. In this paper, we first update the definition of canonical forms in TCRs, build an auto-updating sequence-based prediction tool (available at http://opig.stats.ox.ac.uk/resources) and demonstrate its application on large scale sequencing studies. Given the global similarity of TCRs and antibodies, we then examine the structural similarity of their CDRs. We find that TCR and antibody CDRs tend to have different length distributions, and where they have similar lengths, they mostly occupy distinct structural spaces. In the rare cases where we found structural similarity, the underlying sequence patterns for the TCR and antibody version are different. Finally, where multiple structures have been solved for the same CDR sequence, the structural variability in TCR loops is higher than that in antibodies, suggesting TCR CDRs are more flexible. These structural differences between TCR and antibody CDRs may be important to their different biological functions.

bioinformatics↗

bioRxiv2018

Observed Antibody Space: a resource for data mining next generation sequencing antibody repertoires

Antibodies are immune system proteins that recognize noxious molecules for elimination. Their sequence diversity and binding versatility have made antibodies the primary class of biopharmaceuticals. Recently it has become possible to query their immense natural diversity using next-generation sequencing of immunoglobulin gene repertoires (Ig-seq). However, Ig-seq outputs are currently fragmented across repositories and tend to be presented as raw nucleotide reads, which means nontrivial effort is required to reuse the data for analysis. To address this issue, we have collected Ig-seq outputs from 53 studies, covering more than half a billion antibody sequences across diverse immune states, organisms and individuals. We have sorted, cleaned, annotated, translated and numbered these sequences and make the data available via our Observed Antibody Space (OAS) resource at antibodymap.org. The data within OAS will be regularly updated with newly released Ig-seq datasets. We believe OAS will facilitate data mining of immune repertoires for improved understanding of the immune system and development of better biotherapeutics.

immunology↗