Biology subjects

Perera, D.

Publications and source records attributed to Perera, D..

17 recordsLinked to original sources

bioRxiv2026

XL-MS and De Novo Protein Design Identified a Common Motif for TREM2 Binding

Apolipoprotein E (APOE) and Triggering Receptor Expressed on Myeloid cells 2 (TREM2) are the two strongest genetic risk factors of late-onset Alzheimers disease. ApoE binds to the low-density lipoprotein receptor (LDLR) to facilitate the uptake of ApoE-lipoprotein particles. TREM2 is a cell surface receptor expressed on microglia in the brain. The activation of TREM2 is essential for microglia to carry out protective functions against AD pathology. Several studies have shown that TREM2 signaling is activated through direct interaction between TREM2 and ApoE. In addition to its important role in AD pathogenesis, the ApoE/TREM2 interaction has been shown to induce immunosuppression of neutrophils within the tumor microenvironment. Despite its clinical importance, a high-resolution molecular understanding of the complex remains elusive. Here, we carried out chemical cross-linking mass spectrometry (XL-MS) analysis of the ApoE3/TREM2ECD complex to identify intra- and inter-protein cross-links, which were used as restraints to guide integrative protein-protein docking. Our data support a binding model in which a helix-loop-helix motif within the ApoE3 hinge and C-terminal region forms a transient hydrophobic pocket that wraps around the hydrophobic tip of the TREM2 ectodomain. This model is further supported by de novo-designed mini-protein binders, which show the same binding mode as identified by our XL-MS experiment. These results establish a robust framework for developing mini-protein-based TREM2 agonists.

biophysics↗

bioRxiv2024

Apollo: A comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell

Modern sequencing instruments bring unprecedented opportunity to study within-host viral evolution in conjunction with viral transmissions between hosts. However, no computational simulators are available to assist the characterization of within-host dynamics. This limits our ability to interpret epidemiological predictions incorporating within-host evolution and to validate computational inference tools. To fill this need we developed Apollo, a GPU-accelerated, out-of-core tool for within-host simulation of viral evolution and infection dynamics across population, tissue, and cellular levels. Apollo is scalable to hundreds of millions of viral genomes and can handle complex demographic and population genetic models. Apollo can replicate real within-host viral evolution; accurately recapturing observed viral sequences from an HIV cohort derived from initial population-genetic configurations. For practical applications, using Apollo-simulated viral genomes and transmission networks, we validated and uncovered the limitations of a widely used viral transmission inference tool.

bioinformatics↗

bioRxiv2023

Tissue-specific transfer-learning enables retasking of a general comprehensive model to a specific domain

Machine learning (ML) has proven successful in biological data analysis. However, may require massive training data. To allow broader use of ML in the full spectrum of biology and medicine, including sample-sparse domains, re-directing established models to specific tasks by add-on training via a moderate sample may be promising. Transfer learning (TL), a technique migrating pre-trained models to new tasks, fits in this requirement. Here, by TL, we retasked Enformer, a comprehensive model trained by massive data, tailored to breast cancers using breast-specific data. Its performance has been validated through statistical accuracy of predictions, annotation of genetic variants, and mapping of variants associated with breast cancer. By allowing the flexibility of adding dedicated training data, our TL protocol unlocks future discovery within specific domains with moderate add-on samples by standing on the shoulders of giant models.

bioinformatics↗

bioRxiv2023

CATE: A fast and scalable CUDA implementation to conduct highly parallelized evolutionary tests on large scale genomic data.

Statistical tests for molecular evolution provide quantifiable insights into the selection pressures that govern a genomes evolution. Increasing sample sizes used for analysis leads to higher statistical power. However, this requires more computational nodes or longer computational time. CATE (CUDA Accelerated Testing of Evolution) is a computational solution to this problem comprised of two main innovations. The first is a file organization system coupled with a novel search algorithm and the second is a large-scale parallelization of algorithms using both GPU and CPU. CATE is capable of conducting evolutionary tests such as Tajimas D, Fu and Lis, and Fay and Wus test statistics, McDonald-Kreitman Neutrality Index, Fixation Index, and Extended Haplotype Homozygosity. CATE is magnitudes faster than standard tools with benchmarks estimating it being on average over 180 times faster. For instance, CATE processes all 54,849 human genes for all 22 autosomal chromosomes across the five super populations present in the 1000 Genomes Project in less than thirty minutes while counterpart software took 3.62 days. This proven framework has the potential to be adapted for GPU-accelerated large-scale parallel analyses of many evolutionary and genomic analyses.

bioinformatics↗

bioRxiv2022

A transcriptional response to replication stress selectively expands a subset of BRCA2-mutant mammary epithelial cells

BRCA2 mutation carriers preferentially develop luminal-like breast cancers, but it remains unclear how BRCA2 mutations affect mammary epithelial subpopulations. Here, we report that Brca2mut/WT mammary organoids subjected to replication stress activated a transcriptional response that selectively expands Brca2mut/WT luminal cells lacking hormone receptor expression (HR-). While CyTOF analyses revealed comparable epithelial compositions among wildtype and Brca2mut/WT mammary glands, Brca2mut/WT HR- luminal cells exhibited greater organoid formation and preferentially survived and expanded under replication stress. ScRNA-seq analysis corroborated the expansion of HR- luminal cells which express elevated levels of Tetraspanin-8 (Tspan8) and Thrsp mRNA, and pathways implicated in replication stress survival including Type I interferon responses. Notably, CRISPR/Cas9-mediated deletion of Tspan8 or Thrsp prevented Brca2mut/WT HR- luminal cell expansion. Our findings indicate that Brca2mut/WT cells have an activate a transcriptional response after replication stress that preferentially favours outgrowth of HR- luminal cells through the expression of interferon-responsive and mammary alveolar genes.

cancer biology↗

bioRxiv2022

cLD: Rare-variant disequilibrium between genomic regions identifies novel genomic interactions

Linkage disequilibrium (LD) is a fundamental concept in genetics; critical for studying genetic associations and molecular evolution. However, LD measurements are only reliable for common genetic variants, leaving low-frequency variants unanalyzed. In this work, we introduce cumulative LD (cLD), a stable statistic that captures the rare-variant LD between genetic regions, which reflects more biological interactions between variants, in addition to lack of recombination. We derived the theoretical variance of cLD using delta methods to demonstrate its higher stability than LD for rare variants. This property is also verified by bootstrapped simulations using real data. In application, we find cLD reveals an increased genetic association between genes in 3D chromatin interactions, a phenomenon recently reported negatively by calculating standard LD between common variants. Additionally, we show that cLD is higher between gene pairs reported in interaction databases, identifies unreported protein-protein interactions, and reveals interacting genes distinguishing case/control samples in association studies.

bioinformatics↗

bioRxiv2021

Early neutrophilia marked by aerobic glycolysis sustains host metabolism and delays cancer cachexia

An elevated neutrophil-to-lymphocyte ratio negatively predicts the outcome of patients with cancer and is associated with cachexia, the terminal wasting syndrome. Here, we show using murine model systems of colorectal and pancreatic cancer that neutrophilia in the circulation and multiple organs, accompanied by extramedullary hematopoiesis, is an early event during cancer progression. Transcriptomic and metabolic assessment reveals that neutrophils in tumor-bearing animals utilize aerobic glycolysis, alike to cancer cells. Although pharmacological inhibition of aerobic glycolysis slows down tumor growth in C26 tumor-bearing mice, it precipitates cachexia, thereby shortening overall survival. This negative effect may be explained by our observation that acute depletion of neutrophils in pre-cachectic mice impairs systemic glucose homeostasis secondary to altered hepatic lipid processing. Thus, changes in neutrophil number, distribution and metabolism play an adaptive role in host metabolic homeostasis during cancer progression. Our findings provide insight into early events during cancer progression to cachexia, with implications for therapy.

cancer biology↗

bioRxiv2021

Rats in the city: implications for zoonotic disease risk in an urbanizing world

Urbanization is rapidly transforming much of Southeast Asia, altering the structure and function of the landscape, as well as the frequency and intensity of the interactions between people, animals, and the environment. In this study, we began to explore the impact of urbanization on zoonotic disease risk by simultaneously characterizing changes in the abundance and diversity of reservoir hosts (rodents), ectoparasite vectors (ticks), and microbial pathogens across a gradient of urbanization in Malaysian Borneo. We found that although rodent species diversity decreased with increasing urbanization, two species appeared to thrive in anthropogenic environments: the invasive urban exploiter, Rattus rattus and the native urban adapter, Sundamys muelleri. R. rattus was strongly associated with the presence of built infrastructure across the gradient and dominated the urban rodent community where it was associated with high microbial diversity and multi-host zoonoses capable of environmental transmission, including Leptospira spp., and Toxoplasma gondii. In contrast, S. muelleri was restricted to sites with a significant vegetative component where it was found at high densities in the urban location. This species was strongly associated with the presence of ticks, including the medically important genera Ambylomma, Haemaphysalis, and Ixodes. Overall, our results demonstrate that the response to urbanization varies by species at all levels: host, ectoparasite, and microbe. This may lead to increased zoonotic disease risk in a subset of environments across urban and urbanizing landscapes that can be reduced through improved pest management and public health messaging.

ecology↗

bioRxiv2020

Mechanisms underlying proximity between oral commensal bacteria

Complex polymicrobial biofilm communities are abundant in nature particularly in the human oral cavity where their composition and fitness can affect health. While the study of these communities during disease is essential and prevalent, little is known about interactions within the healthy plaque community. Here we describe interactions between two of the most abundant species in this healthy microbiome, Haemophilus parainfluenzae and Streptococcus mitis. We discovered that H. parainfluenzae typically exists adjacent to Mitis group streptococci in vivo with which it also positively correlated based on microbiome data. By comparing in vitro coculture data to ex vivo microscopy we revealed that this co-occurrence is density dependent and further influenced by H2O2 production. We discovered that H. parainfluenzae has a more redundant, multifactorial response to H2O2 than related organisms and that the integrity of this system enhances streptococcal fitness. We also show that Mitis group streptococci can act as an in vivo source of NAD for H. parainfluenzae and that streptococci in vitro evoke patterns of carbon utilization from H. parainfluenzae that are similar to those observed in vivo. Our findings describe mechanistic interactions between two of the most abundant and prevalent members of healthy supragingival plaque that contribute to their survival in vivo.

microbiology↗

bioRxiv2020

Statistical model integrating interactions into genotype-phenotype association mapping: an application to reveal 3D-genetic basis underlying Autism

Biological interactions are prevalent in the functioning organisms. Correspondingly, statistical geneticists developed various models to identify genetic interactions through genotype-phenotype association mapping. The current standard protocols in practice test single variants or single regions (that contain multiple local variants) sequentially along the genome, followed by functional annotations that involve various aspects including interactions. The testing of genetic interactions upfront is rare in practice due to the burden of testing a huge number of combinations, which lead to the multiple-test problem and the risk of overfitting. In this work, we developed interaction-integrated linear mixed model (ILMM), a novel model that integrates a priori knowledge into linear mixed models. ILMM enables statistical integration of genetic interactions upfront and overcomes the problems associated with combination searching. Three dimensional (3D) genomic interactions assessed by Hi-C experiments have led to unprecedented biological discoveries. However, the contribution of 3D genomic interactions to the genetic basis of complex diseases has yet to be quantified. Using 3D interacting regions as a priori information, we conducted both simulations and real data analysis to test ILMM. By applying ILMM to whole genome sequencing data for Autism Spectrum Disorders, or ASD (MSSNG) and transcriptome sequencing data (GTEx), we revealed the 3D-genetic basis of ASD and 3D-eQTLs for a substantial proportion of gene expression in brain tissues. Moreover, we have revealed a potential mechanism involving distal regulation between FOXP2 and DNMT3A conferring the risk of ASD. Software is freely available in our GitHub: https://github.com/theLongLab/Jawamix5

genetics↗

bioRxiv2020

Inhibitors of the Bub1 spindle assembly checkpoint kinase: Synthesis of BAY-320 and comparison with 2OH-BNPP1

SummaryBub1 is a serine/threonine kinase proposed to function centrally in both mitotic chromosome alignment and the spindle assembly checkpoint (SAC), however its role remains controversial. Although it is well documented that Bub1 phosphorylation of Histone 2A at T120 (H2ApT120) recruits Sgo1/2 to kinetochores, the requirement of its kinase activity for chromosome alignment and the SAC is debated. As small-molecule inhibitors can be invaluable tools for investigation of kinase function, we decided to evaluate the relative potential of two agents (2OH-BNPPI and BAY-320) as Bub1 inhibitors. After confirming that both agents inhibit Bub1 in vitro, we developed a cell based-assay to specifically measure Bub1 inhibition in vivo. For this assay we overexpressed a fusion of Histone 2B and the Bub1 kinase region (Bub1C) tethering it in close proximity to H2A, which generated a strong ectopic H2ApT120 signal along chromosome arms. The ectopic signal generated from Bub1C activity was effectively inhibited by BAY-320, but not 2OH-BNPP1. In addition, only BAY-320 was able to inhibit endogenous Bub1-mediated Sgo1 localisation. Preliminary experiments using BAY-320 suggested a minor role for Bub1 kinase activity in chromosome alignment and the SAC, however results suggest that BAY-320 may exhibit off-target effects at the concentration required to demonstrate these outcomes. In conclusion, 2OH-BNPP1 may not be an effective Bub1 inhibitor in vivo, and while BAY-320 is able to inhibit Bub1 in vivo, the high concentrations required and potential for off-target effects highlight the ongoing need for improved Bub1 inhibitors.Competing Interest StatementThe authors have declared no competing interest.View Full Text

cell biology↗

bioRxiv2020

Enhanced specificity of high sensitivity somatic variant profiling in cell-free DNA via paired normal sequencing: design, validation, and clinical experience of the MSK-ACCESS liquid biopsy assay

Circulating cell-free DNA (cfDNA) from blood plasma of cancer patients can be used to interrogate somatic tumor alterations non-invasively or when adequate tissue is unavailable. We have developed and clinically implemented MSK-ACCESS (Analysis of Circulating cfDNA to Evaluate Somatic Status), an NGS assay for detection of very low frequency somatic alterations in select exons and introns of 129 genes. Analytical validation demonstrated 92% sensitivity in de-novo mutation calling down to 0.5% allele frequency and 98% for a priori mutation profiling. To evaluate the performance and utility of MSK-ACCESS, we report results from the first 681 prospective blood samples (617 patients) that underwent clinical analysis to guide patient management. Somatic mutations, copy number, and/or structural variants were detected in 73% of the samples, and 56% of these circulating-tumor DNA (ctDNA) positive samples had clinically actionable alterations. The utilization of matched white blood cell sequencing allowed retention of somatic alterations while filtering out over 10,000 germline and clonal hematopoiesis variants, thereby greatly enhancing the specificity of the assay. Taken together, our experience illustrates the importance of analyzing a matched normal sample when interpreting cfDNA results and highlights the potential of cfDNA profiling to guide treatment selection, monitor treatment response, and identify mechanisms of treatment resistance.

genomics↗

bioRxiv2020

De novo reconstruction of microbial haplotypes by integrating statistical and physical linkage

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or haplotypes. However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

bioinformatics↗

bioRxiv2019

TREM-1 activation is a key regulator in driving severe pathogenesis of enterovirus 71 infection

Hand, foot and mouth disease (HFMD), caused by enterovirus 71 (EV71), presents mild to severe disease, and sometimes fatal neurological and respiratory manifestations. However, reasons for the severe pathogenesis remain undefined. To investigate this, infection and viral kinetics of EV71 isolates from clinical disease (mild, moderate and severe) from Sarawak, Malaysia, were characterized in human rhabdomyosarcoma (RD), neuroblastoma (SH-SY5Y) and peripheral blood mononuclear cells (PBMCs). High resolution transcriptomics was used to decipher EV71-host interactions in PBMCs. Ingenuity analyses revealed similar pathways triggered by all EV71 isolates, although the extent of activation varied. Importantly, several pathways were found to be specific to the severe isolate, including triggering receptor expressed on myeloid cells 1 (TREM-1) signaling. Depletion of TREM-1 in EV71-infected PBMCs with peptide LP17 resulted in decreased levels of pro-inflammatory genes, and reduced viral loads for the moderate and severe isolates. Mechanistically, this is the first report describing the transcriptome profiles during EV71 infections in primary human cells, and the involvement of TREM-1 in the severe disease pathogenesis, thus providing new insights for future treatment targets.

immunology↗

bioRxiv2018

Multi-Omic Profiling Reveals Dynamics of the Phased Progression of Pluripotency

Pluripotency is highly dynamic and progresses through a continuum of pluripotent stem-cell states. The two states that bookend the pluripotency continuum, naive and primed, are well characterized, but our understanding of the intermediate states and transitions between them remain incomplete. Here, we dissect the dynamics of pluripotent state transitions underlying pre-to post-implantation epiblast differentiation. Through comprehensive mapping of the proteome, phosphoproteome, transcriptome, and epigenome of mouse embryonic stem cells transitioning from naive to primed pluripotency, we find that rapid, acute, and widespread changes to the phosphoproteome precede ordered changes to the epigenome, transcriptome, and proteome. Reconstruction of kinase-substrate networks reveals signaling cascades, dynamics, and crosstalk. Distinct waves of global proteomic changes demarcate discrete phases of pluripotency, characterized by cell-state-specific surface marker expression. Our data provide new insights into the multi-layered control of the phased progression of pluripotency and a foundation for modeling mechanisms underlying pre-to post-implantation epiblast differentiation.\n\nHIGHLIGHTSO_LIMulti-ome maps of cells transitioning from naive to primed pluripotency\nC_LIO_LIPhosphoproteome dynamics precede changes to epigenome, transcriptome, and proteome\nC_LIO_LIKinase-substrate network reconstruction uncovers signaling dynamics and crosstalk\nC_LIO_LIProteins and cell surface markers that track pluripotent state transitions\nC_LIO_LIComparative analysis of mouse and human pluripotent states\nC_LI

genomics↗

bioRxiv2018

Transcriptome-wide profiling of mammalian spliceosome and branchpoints with iCLIP

Studies of spliceosomal interactions are challenging due to their dynamic nature. Here we employed spliceosome iCLIP, which immunoprecipitates SmB along with snRNPs and auxiliary RNA binding proteins (RBPs), to map human spliceosome engagement with snRNAs and pre-mRNAs. This identified over 50,000 branchpoints (BPs) that have canonical sequence and structural features. Moreover, it revealed 7 binding peaks around BPs and splice sites, each precisely overlapping with binding profiles of specific splicing factors. We show how the binding patterns of these RBPs are affected by the position and strength of BPs. For example, strong or proximally located BPs preferentially bind SF3 rather than U2AF complex. Notably, these effects are partly neutralized during spliceosomal assembly in a way that depends on the core spliceosomal protein PRPF8. These insights exemplify spliceosome iCLIP as a broadly applicable method for transcriptomic studies of splicing mechanisms.

genomics↗

bioRxiv2018

In search of non-coding driver mutations by deep sequencing of regulatory elements in colorectal cancer

Large-scale whole cancer-genome sequencing projects have led to the identification of a handful of cis-regulatory driver mutations in cancer genomes. However, recent studies have demonstrated that very large cancer cohorts will be required in order to identify low frequency non-coding drivers. To further this endeavour, in this study, we performed highdepth sequencing across 95 colorectal cancers and matched normal samples using a unique target capture sequencing (TCS) assay focusing on over 35 megabases of gene regulatory elements. We first assessed coverage and variant detection capability from our TCS data, and compared this with a sample that was additionally whole-genome sequenced (WGS). TCS enabled substantially deeper sequencing and thus we detected 51% more somatic single nucleotide variants (n = 2,457) and 144% more somatic insertions and deletions (n = 39) by TCS than WGS. Variants obtained from TCS data were suitable for somatic mutational signature detection, enabling us to define the signatures associated with germline deleterious variants in MSH6 and MUTYH in samples within our cohort. Finally, we surveyed regulatory mutations to find putative drivers by assessing variant recurrence and function, identifying some regulatory variants that may influence oncogenesis. Our study demonstrates TCS to be a sequencing-efficient alternative to traditional WGS, enabling improved coverage and variant detection when seeking to identify variants at specific loci among larger cohorts. Interestingly, we found no candidate variants that have a clear driver function, suggesting that regulatory drivers may be rare in a colorectal cancer cohort of this size.\n\nAuthor SummaryIn recent years, some cancer research focus has turned towards the role of somatic mutations in the 98% of the genome that is non-coding. To investigate such mutations, we performed deep sequencing of regulatory regions and a selection of coding genes across 95 colorectal cancer and matched-normal samples. To determine the ability of our targeted deep sequencing methodology to accurately detect variants, we compared our results with those from a sample that was additionally whole-genome sequenced. We found target capture sequencing to enable greater sequencing depth, allowing the detection of 51% and 144% more somatic single nucleotide and insertion/deletion mutations, respectively. Our study here demonstrates target capture sequencing to be a useful approach for researchers seeking to identify variants at specific loci among larger cohorts. Our results also enabled the generation of mutational signatures, implicating deleterious germline single nucleotide variants in coding exons of MSH6 and MUTYH in samples within our cohort. Finally, we surveyed regulatory elements in search of somatic cancer driver mutations. We identified some regulatory variants that may influence oncogenesis, but found no candidate variants with clear driver function. These findings suggest that regulatory driver mutations may be rare in a colorectal cancer cohort of this size.

biochemistry↗