Biology subjects

Perera, M.

Publications and source records attributed to Perera, M..

14 recordsLinked to original sources

bioRxiv2026

Cryo-EM structure of human LRRC15 reveals the basis of therapeutic antibody recognition

Leucine-rich repeat containing 15 (LRRC15) is a structural uncharacterised membrane protein, which is highly upregulated in cancer-associated fibroblasts and enriched in desmoplastic tumours including pancreatic, breast and head-and-neck cancers, where it is associated with therapy resistance. The LRRC15-targeting antibody-drug conjugate samrotamab vedotin has advanced into Phase I clinical evaluation, yet mechanistic understanding of how samrotamab engages its target has remained elusive in the absence of structural data. Here, using hydrogen-deuterium exchange mass spectrometry and cryo-electron microscopy, we define the samrotamab epitope on LRRC15 and determine the structure of the LRRC15-samrotamab complex to 2.6 [A] resolution - the first high-resolution structure of this receptor. Samrotamab engages a membrane-proximal epitope within the C-terminal leucine-rich repeat region, leaving the canonical concave surface fully exposed for potential interactions. The lateral binding mode of samrotamab and the open arc geometry of LRRC15 provide a structural rationale for why antibody occupancy may leave signalling-competent surfaces intact. Guided by these insights, we computationally designed minibinders targeting the concave surface, identifying multiple binders with nanomolar affinity. Together, our work establishes the first structural framework for LRRC15, defines the molecular basis of therapeutic antibody recognition, and identifies the concave surface as a promising target for next-generation LRRC15-directed therapeutics.

biochemistry↗

bioRxiv2026

snputils: A High-Performance Python Library for Genetic Variation and Population Structure

The increasing size and resolution of genomic and population genetic datasets offer unprecedented opportunities to study population structure and uncover the genetic basis of complex traits and diseases. The collection of existing analytical tools, however, is characterized by format incompatibilities, limited functionality, and computational inefficiencies, forcing researchers to construct fragile pipelines that chain together fragmented command-line utilities and ad hoc scripts. These are difficult to maintain, scale, and reproduce. To address such limitations, we present snputils, a Python library that unifies high-performance I/O, transformation, and analysis of genotype, ancestry, and phenotypic information within a single framework suitable for biobank-scale research. The library provides efficient tools for essential operations, including querying, cleaning, merging, and statistical analysis. In addition, it offers classical population genetic statistics with optional ancestry-specific masking. An identity-by-descent module supports reading of multiple formats, filtering and ancestry-restricted segment trimming for relatedness and demographic inference. snputils also incorporates ancestry-masking and multi-array functionalities for dimensionality reduction methods, as well as efficient implementations of admixture simulation, admixture mapping, and advanced visualization capabilities. With support for the most commonly used file formats, snputils integrates smoothly with existing tools and clinical databases. At the same time, its modular and optimized design reduces technical overhead, facilitating reproducible workflows that accelerate discoveries in population genetics, genomic research, and precision medicine. Benchmarking demonstrates a significant reduction in genotype data loading speed compared to existing Python libraries. The open-source library is available at https://github.com/AI-sandbox/snputils, with full documentation and tutorials at snputils.org.

bioinformatics↗

bioRxiv2026

PartiNet is a dynamic adaptive neural network for high-performance particle picking in cryo-electron microscopy

Accurate, efficient and autonomous particle picking is a major bottleneck in high-resolution cryo-electron microscopy (cryo-EM). We introduce PartiNet, an Artificial Intelligence (AI)-based particle picker with size-agnostic detection and pre-trained models that eliminate manual parameter specification and dataset-specific training, pioneering dynamic neural network inference for single particle cryo-EM pipeline. Unlike static architectures, PartiNet employs a dynamic framework that adjusts network complexity in real-time based on perceived micrograph quality. This adaptive approach accelerates inference up to 7-fold compared to existing tools without sacrificing particle selection quality. Training on diverse protein datasets showed that PartiNet improves particle yields, enhances sampling of rare orientations, and is compatible with on-the-fly workflows. Comprehensive evaluation on benchmark datasets and validation on a new dataset of the chromatin remodeler MORC2 demonstrates superior precision and recall, with the ability to detect heterogeneous protein species, leading to more complete structural models and consistently higher-resolution reconstructions.

molecular biology↗

bioRxiv2025

MeQTL Mapping in African American Hepatocytes Reveals Shared Genetic Regulators of DNA Methylation and Gene Expression

Methylation quantitative trait loci (meQTL) mapping can provide insight into the genetic architecture underlying the epigenome by identifying single-nucleotide polymorphisms (SNPs) associated with differential methylation at methylation sites (CpGs) across the genome. Given that the epigenetic architecture underlying differences in gene expression can vary across racial populations, performing epigenomic studies in African Americans is crucial for understanding the interplay between genetic variation, DNA methylation, and gene expression in this understudied group. By performing cis-meQTL mapping in African American hepatocytes, we identified 410,186 cis-meQTLs associated with methylation at 24,425 CpGs in the liver. Through colocalization analysis, we found that 18,206 of these meQTLs are also colocalized with known liver eQTLs. Additionally, we found that using African American eQTL data results in an increased ability to detect additional colocalized variants that exhibit strong differences in allele frequency between people of European and African ancestry. Furthermore, the presence of smaller linkage disequilibrium blocks in African Americans allows us to identify narrower genomic regions of potentially causal variants compared to when data from Europeans is used. Importantly, these colocalized SNPs are significantly enriched for genetic associations with lipid and inflammatory traits in the GWAS catalog, suggesting that DNA methylation may contribute to the etiologies of these diseases. Furthermore, while it is generally presumed that the genetic regulation of DNA methylation is shared between blood and liver, we found that only 5.4% of African American liver meQTLs colocalize with blood meQTLs. Overall, our results reveal that studying African American populations results in the identification of additional genetic and epigenetic factors that may regulate gene expression in the liver, thereby expanding our understanding of gene regulation in African Americans.

genomics↗

bioRxiv2024

Common modes of ERK induction resolve into context specific signalling via a combination of signal duration and cell type specific transcriptional repression.

Fibroblast Growth Factor (FGF) signalling via ERK exerts diverse roles in development and disease. In mammalian preimplantation embryos and naive pluripotent stem cells ERK promotes differentiation, whereas in primed pluripotent states closer to somatic differentiation ERK sustains self-renewal. How can the same pathway produce different outcomes in two related cell types? To explore context-dependent ERK signalling in embryonic development and differentiation we generated cell and mouse lines that allow for tissue- and time-specific cell intrinsic ERK activation. Using these tools, we find variations in response to ERK are mostly mediated by repression of transcriptional targets that occur in tandem with reductions in chromatin accessibility at regulatory regions. Furthermore, immediate early ERK responses are largely shared by different cell types, but become refined producing cell-specific programs as increasing durations of signalling interface with cell specific gene regulatory networks. Induction in naive pluripotency is accompanied by chromatin changes, whereas in later stages it is not, suggesting that chromatin context doesnt shape signalling response. Altogether, our data suggest that cell-type specific responses to ERK signalling exploit the same immediate early response, but then sculpt it to specific lineages via repression of distinct cellular programs and downstream indirect stimulation of available enhancer networks.

developmental biology↗

bioRxiv2023

Enhancer status in the primitive endoderm supports unrestricted lineage plasticity in regulative development

Mammalian blastocyst formation involves the specification of trophectoderm followed by the differentiation of the inner cell mass into either epiblast or primitive endoderm. During this time, the embryo maintains a window of plasticity and can redirect its cellular fate when challenged experimentally. In this context, we found that the primitive endoderm alone was sufficient to regenerate a complete blastocyst and continue normal postimplantation development to term. We identify an in vitro population similar to the early primitive endoderm in vivo, that exhibits the same embryonic and extra-embryonic potency, forming three dimensional embryoid structures. Commitment in early primitive endoderm is suppressed by JAK/STAT signalling, collaborating with OCT4 to safeguard enhancer status enabling multi-lineage differentiation. Our observations support the notion that transcription factor persistence underlies plasticity in regulative development and highlights the importance of primitive endoderm in perturbed development.

developmental biology↗

bioRxiv2023

Transcription Factor Co-Expression Mediates Lineage Priming for Embryonic and Extra-Embryonic Differentiation

In early mammalian development, cleavage stage blastomeres and cells of the inner cell mass (ICM) of the blastocyst co-express embryonic and extra-embryonic transcriptional determinants. Using a double protein-based reporter we identify embryonic stem cells (ESC) that co-express the extra-embryonic factor GATA6 alongside the embryonic factor SOX2 in specific conditions. Based on single cell transcriptomics we find these population resemble unsegregated ICM, exhibiting enhanced differentiation potential for endoderm while maintaining epiblast competence and suggesting they represent an ideal model to determine how GATA6 and SOX2 influence each others DNA binding. To relate this binding to future fate, we describe a complete enhancer set in both ESCs and naive extraembryonic endoderm stem cells and ask whether SOX2 and GATA6 recognize these elements in ICM-like ESC sub-population. Both factors support cooperative recognition in these lineages, with GATA6 bound alongside SOX2 on a fraction of pluripotency enhancers and SOX2 alongside GATA6 more extensively on endoderm enhancers. Our findings suggest that cooperative binding between these antagonistic factors both supports self-renewal and prepares progenitor cells for later differentiation.

developmental biology↗

bioRxiv2022

Function and phylogeny support the independent evolution of acid-sensing ion channels in the Placozoa

Acid-sensing ion channels (ASICs) are proton-gated cation channels that are part of the Deg/ENaC ion channel family, which also includes neuropeptide-, bile acid-, and mechanically-gated channels. Despite sharing common tertiary and quaternary structures, strong sequence divergence within the Deg/ENaC family has made it difficult to resolve their phylogenetic relationships, and by extension, whether channels with common functional features, such as proton-activation, share common ancestry or evolved independently. Here, we report that a Deg/ENaC channel from the early diverging placozoan species Trichoplax adhaerens, named TadNaC2, conducts proton-activated currents in vitro with biophysical features that resemble those of the mammalian ASIC1 to ASIC3 channels. Through a combined cluster- based and phylogenetic analysis, we successfully resolve the evolutionary relationships of most major lineages of metazoan Deg/ENaC channels, identifying two subfamilies within the larger Deg/ENaC family that are of ancient, pre-bilaterian origin. We also identify bona fide Deg/ENaC channel homologues from filasterean and heterokont single celled eukaryotes. Furthermore, we find that ASIC channels, TadNaC2, and various other proton-activated channels from vertebrates and invertebrates are part of phylogenetically distinct lineages. Through structural modelling and mutation analysis, we find that TadNaC2 proton-activation employs fundamentally different molecular determinants than ASIC channels, and identify two unique histidine residues in the placozoan channel that are required for its proton-activation. Together, our phylogenetic and functional analyses support the independent evolution of proton-activated channels in the phylum Placozoa. Spurred by our discovery of pH sensitive channels, we discovered that despite lacking a nervous system, Trichoplax can sense changes in extracellular pH to coordinate its various cell types to locomote away from acidic environments, and to contract upon rapid exposure to acidic pH in a Ca2+-dependent manner. Lastly, via yeast 2 hybrid screening, we find that the Trichoplax channels TadNaC2 and TadNaC10, belonging to the two separate Deg/ENaC subfamilies, interact with the cytoskeleton organizing protein filamin, similar to the interaction reported for the human ENaC channels.

evolutionary biology↗

bioRxiv2022

Leverage drug perturbation to reveal genetic regulators of hepatic gene expression in African Americans

BackgroundExpression quantitative loci (eQTL) studies have paved the way in identifying genetic variation impacting gene expression levels. African Americans (AAs) are disproportionately underrepresented in eQTL studies, resulting in a lack of power to identify population-specific regulatory variations especially related to drug response. Specific drugs are known to affect the biosynthesis of drug metabolism enzymes as well as other genes. We used drug perturbation in cultured primary hepatocytes derived from AAs to determine the effect of drug treatment on eQTL mapping and to identify the drug response eQTLs (reQTLs) that show altered effect size following drug treatment. MethodsWhole-genome genotyping (Illumina MEGA array) and RNA-sequencing were performed on 60 primary hepatocyte cultures after treatment with 6 drugs (Rifampin, Phenytoin, Carbamazepine, Dexamethasone, Phenobarbital, and Omeprazole) and at baseline (no treatment). eQTLs were mapped by treatment and jointly using Meta Tissue. ResultsWe found varying transcriptional changes across different drug treatments and identified Nrf2 as a potential general transcriptional regulator. We jointly mapped eQTL with gene expression data for across all drug treatments and baseline which increased our power to detect eQTLs by 2.7-fold. We also identified 2,988 reQTLs (eQTLs with altered effect size after drug treatment), which were more likely to overlap transcription factor binding sites and uncovered a novel reQTL, rs61017966 that increases CYP3A5 gene expression, a major drug metabolizing enzyme responsible for both drug response and adverse events across several drug classes. ConclusionsOur results provide novel insights into the genetic regulation of gene expression in hepatocytes through drug perturbation and provide insight into SNPs that effect the livers ability to respond to transcription upregulation.

genomics↗

bioRxiv2022

Generative Moment Matching Networks for Genotype Simulation

The generation of synthetic genomic sequences using neural networks has potential to ameliorate privacy and data sharing concerns and to mitigate potential bias within datasets due to under-representation of some population groups. However, there is not a consensus on which architectures, training procedures, and evaluation metrics should be used when simulating single nucleotide polymorphism (SNP) sequences with neural networks. In this paper, we explore the use of Generative Moment Matching Networks (GMMNs) for SNP simulation, we present some architectural and procedural changes to properly train the networks, and we introduce an evaluation scheme to qualitatively and quantitatively assess the quality of the simulated sequences.

bioinformatics↗

bioRxiv2022

Transcriptional Heterogeneity and Cell Cycle Regulation as Central Determinants of Primitive Endoderm Priming.

During embryonic development cells acquire identity at the same time as they are proliferating, implying that an intrinsic facet of cell fate choice requires coupling lineage decisions to rates of cell division. How is the cell cycle regulated to promote or suppress heterogeneity and differentiation? We explore this question combining time lapse imaging with single cell RNA-seq in the contexts of self-renewal, priming and differentiation of embryonic stem cells (ESCs) towards the Primitive Endoderm lineage (PrE). Since ESCs are derived from the Inner Cell Mass of the mammalian blastocyst, ESCs in standard culture conditions are transcriptionally heterogeneous containing subfractions that are primed for either of the two ICM lineages, Epiblast and PrE. These subfractions represent dynamic states that can readily interconvert in culture, and the PrE subfraction is functionally primed for endoderm differentiation. Here we find that differential regulation of cell cycle can tip the balance between these primed populations, such that naive ESC culture conditions promote Epiblast-like expansion and PrE differentiation stimulates the selective proliferation of PrE-primed cells. In endoderm differentiation, we find that this change is accompanied by a counter-intuitive increase in G1 length that also appears replicated in vivo. While FGF/ERK signalling is a known key regulator of ESCs and PrE differentiation, we find it is not just responsible for ESCs heterogeneity, but also cell cycle synchronisation, required for the inheritance of similar cell cycles between sisters and cousins. Taken together, our results point to a tight relationship between transcriptional heterogeneity and cell cycle regulation in the context of lineage priming, with primed cell populations providing a pool of flexible cell types that can be expanded in a lineage-specific fashion while allowing plasticity during early determination.

developmental biology↗

bioRxiv2020

FAM72A antagonizes UNG2 to promote mutagenic uracil repair during antibody maturation

Activation-induced cytidine deaminase (AID) catalyzes the deamination of deoxycytidines within Immunoglobulin (Ig) genes to induce somatic hypermutation (SHM) and class switch recombination (CSR) 1,2. AID-induced deoxyuracils within Ig loci are recognized and processed by subverted base excision and mismatch repair pathways that ensure a mutagenic outcome in B lymphocytes 3-8. However, it is unclear why DNA repair pathways that remove deoxyuracil from DNA are not efficient at faithfully repairing AID-induced lesions. Here, we identified through a genome-wide CRISPR screen that FAM72A, a protein with no ascribed function, is a major determinant for the error-prone processing of deoxyuracil. Fam72a-deficient CH12F3-2 B cells and primary B cells from Fam72a-/- mice have reduced CSR and SHM frequencies. The SHM spectrum in B cells from Fam72a-/- mice is opposite to that observed in Ung2-/- mice 9, suggesting that UNG2 is hyperactive in FAM72A-deficient cells. Indeed, FAM72A binds to UNG2 resulting in reduced UNG2 activity, and significantly reduced protein levels in the G1 phase, coinciding with peak AID activity. This effect leads to increased genome-wide deoxyuracils in B cells. By antagonizing UNG2, FAM72A therefore increases U*G mispairs that engage mutagenic mismatch repair promoting error-prone processing of AID-induced deoxyuracils. This work shows that FAM72A bridges base-excision repair and mismatch repair to modulate antibody maturation.

immunology↗

bioRxiv2020

Incorporation of DNA methylation into eQTL mapping in African Americans.

Epigenetics is a reversible molecular mechanism that plays a critical role in many developmental, adaptive, and disease processes. DNA methylation has been shown to regulate gene expression and the advent of high throughput technologies has made genome-wide DNA methylation analysis possible. We investigated the effect of DNA methylation in eQTL mapping (methylation-adjusted eQTLs), by incorporating DNA methylation as a SNP-based covariate in eQTL mapping in African American derived hepatocytes. We found that the addition of DNA methylation uncovered new eQTLs and eGenes. Previously discovered eQTLs were significantly altered by the addition of DNA methylation data suggesting that methylation may modulate the association of SNPs to gene expression. We found that methylation-adjusted eQTLs which were less significant compared to PC-adjusted eQTLs were enriched in lipoprotein measurements (FDR = 0.0040), immune system disorders (FDR = 0.0042), and liver enzyme measurements (FDR = 0.047), suggesting a role of DNA methylation in regulating the genetic basis of these phenotypes. Our methylation-adjusted eQTL analysis also uncovered novel SNP-gene pairs. For example, our study found the SNP, rs11546996, was associated to PNKP. In a previous GWAS, this SNP was associated with primary biliary cirrhosis although the causal gene was thought to be SPIB. Our methylation-adjusted method potentially adds new understanding to the genetic basis of complex diseases that disproportionally affect African Americans.

genomics↗

bioRxiv2018

Uncovering the role admixture in health disparity: characterization of hepatocyte gene expression and DNA methylation in African-Americans

BackgroundAfrican Americans (AAs) are an admixed population with portions of their genome derived from West Africans and Europeans. In AAs, the proportion of West African ancestry (WAA) can vary widely and may explain the genetic drivers of disease, specifically those that disproportionately affect this understudied population. To examine the relationship between the proportion of WAA and gene expression, we used high dimensional data obtained from AA primary hepatocytes, a tissue important in disease and drug response. MethodsRNA sequencing (Illumina HiSeq Platform) was conducted on 60 AA-derived primary hepatocytes, with methylation profiling (Illumina MethylationEPIC BeadChip) of 44 overlapping samples. WAA for each sample was calculated using fastSTRUCTURE and correlated to both gene expression and DNA methylation. The GTEx consortium (n = 15) was used for replication and a second cohort (n = 206) was using used for validation using differential gene expression between AAs and European-Americans. ResultsWe identified 131 genes associated with WAA (FDR< 0.1), of which 28 gene expression traits were replicated (FDR<0.1) and enriched in angiogenesis and inflammatory pathways (FDR<0.1). These 28 replicated gene expression traits represented 257 GWAS catalog phenotypes. Among the PharmGKB pharmacogenes, VDR, PTGIS, ALDH1A1, CYP2C19 and P2RY1 were associated with WAA (p < 0.05) with replication of CYP2C19 and VDR in GTEx. Association of DNA methylation with WAA identified 1037 differentially methylated regions (FDR<0.05), with hypomethylated genes enriched in drug response pathways. Overlapping of differentially methylated regions with the 131 significantly correlated gene expression traits identified 5 genes with concordant directions of effect: COL26A1, HIC1, MKNK2, RNF135, SNAI1 and TRIM39. ConclusionsWe conclude that WAA contributes to variability in hepatic gene expression and DNA methylation with identified genes indicative of diseases disproportionately affecting AAs. Specifically, WAA-associated genes were linked to previously identified loci in cardiovascular disease (PTGIS, PLAT), renal disease (APOL1) and drug response (CYP2C19).

genomics↗