Biology subjects

Lim, E. T.

Publications and source records attributed to Lim, E. T..

9 recordsLinked to original sources

bioRxiv2026

MipSScs: Artificial neural network-based data integration of 2D/3D single-cell spatial RNA sequence data from virus-infected human cerebral organoids

There is interest in the use of recent single-cell spatial transcriptomic technologies to gain biological insights into disease mechanisms. Previously, we characterized the use of herpes simplex virus 1 (HSV-1) induced neuroinflammation in 2D dissociated cells from human cerebral organoids (dcOrgs) to model molecular and transcriptomic readouts associated with Alzheimers disease (AD). In this work, we generated two datasets by using single-cell non-spatial RNA sequencing and single-cell spatial RNA sequencing technologies on HSV-1-infected 2D dcOrgs and HSV-1-infected 3D cerebral organoids (cOrgs). We conducted cell type assignment for the cells in the 2D dcOrgs and 3D cOrgs, by using single-cell non-spatial RNA sequence data from human fetal brains and adult post-mortem brains, to infer the transcriptomic effects of AD-associated in-vitro perturbations through viral infections linked to AD. We evaluated computational and machine learning methods, including the use of multi-layer perceptrons (MLPs), and we used cross-2D/3D platform comparisons as a benchmark to evaluate the artificial neural network models. In the process, we found that the use of MLPs can lead to high validation rates for assigning cell type identities from 2D and 3D human cerebral organoids to cell types found in human adult post-mortem brain samples. Furthermore, the use of these technologies and systems enabled the identification of pseudotime trajectories and cell clusters associated with the viral transcriptional life cycle. We identified several cell types, including endothelial cells and astrocytes, with significantly more clustered cell-cell nearest neighbor distances in infected 3D cOrgs compared to mock 3D cOrgs. Permutation tests revealed that these differences in nearest neighbor distances are unlikely to be driven by overall structural differences between individual infected 3D cOrgs and mock 3D cOrgs, such as differences in the density of cells. Given that there are more large-scale single-cell non-spatial (2D) RNA sequence datasets that had been generated from human post-mortem brain samples, compared to single-cell spatial (3D) RNA sequence datasets from human post-mortem brain samples, the development of data integration approaches by using artificial neural networks such as MLPs, across 2D and 3D single-cell transcriptomics datasets generated from human post-mortem brain samples and human in-vitro systems such as brain organoids is likely to be critical to gain novel insights into neurodegenerative diseases such as AD.

genomics↗

bioRxiv2024

Unbiased multiplex antigen screening of Cerebrospinal Fluid detects microbial and autoantigenic epitopes associated with Multiple Sclerosis

To comprehensively investigate the intrathecal antibody profile of multiple sclerosis (MS), we examined the cerebrospinal fluid of 195 patients (92 MS and 103 non-MS) for antibodies using a multiplex unbiased bacteria peptide library. We first tested against Epstein-Barr nuclear antigen 1 (EBNA1) for epitope sites enriched in MS and found a significant enrichment at position 407-419. We then used the data to perform a high-throughput screen against a library of 129 viruses known to infect humans. We discovered several additional epitopes from viruses such as Hantaan virus, Human Herpesvirus 6A and Human respiratory syncytial virus B associated with MS. Besides viral epitopes, we also screened for potential autoantigens of the central nervous system (CNS). We discovered several autoantigenic epitopes in proteins such as ADRB3, HTR3A and MPO that were significantly enriched for MS. Because of previous associations of Toxoplasma gondii infection with MS, we also performed a Toxoplasma gondii specific analysis and discovered additional epitopes enriched for MS. We further assessed epitope-epitope correlations within the patient samples and found distinct patterns of association between these microbial and autoantigenic epitopes. Finally, we performed machine-learning to determine if these epitopes are predictive for MS and found that the model incorporating all the epitopes could most effectively discriminate between MS and non-MS (ROC-AUC score = 0.91). Our results demonstrate the effectiveness of multiplex unbiased screens to detect the identity of potentially cross-reactive antibodies targeting MS CNS epitopes and they can also be used as effective biomarkers for MS. One Sentence SummaryWe performed an unbiased multiplex bacteria peptide antibody library screen on cerebrospinal fluid samples of patients with multiple sclerosis (MS) as well as non-MS controls and detected multiple viral and autoantigenic epitopes that are significantly enriched in MS patient samples.

immunology↗

bioRxiv2024

Development of a high-throughput, quantitative platform using human cerebral organoids to study virus-induced neuroinflammation in Alzheimer's disease

Neuroinflammation is a central process in the pathogenesis of several neurodegenerative diseases such as Alzheimers disease (AD), and there are active efforts to target pathways involved in neuroinflammation for molecular biomarker discovery and therapeutic development in neurodegenerative diseases. It was also proposed that there may be an infectious etiology in AD that is associated with viruses such as herpes simplex virus (HSV-1) and influenza A virus (IAV), leading to neuroinflammation-induced AD pathogenesis or disease progression. We sought to develop high-throughput, quantitative molecular biomarker assays using dissociated cells from human cerebral organoids (dcOrgs), that can used for screening compounds to reverse AD-associated neuroinflammation. We found that HSV-1 infection, but not IAV infection, in dcOrgs led to increased intracellular A{beta}42 and phosphorylated Tau-Thr212 (pTau-212) expression, lower ratios of secreted A{beta}42/40, as well as neuronal loss, and increased proportions of astrocytes and microglia, which are hallmarks of AD. Among the glia cell-type markers, Iba1 (microglia) and GFAP (astrocyte) expression were most strongly correlated with HSV-1 expression, which further supported that these biomarkers are perturbed by glia-mediated neuroinflammation. By performing large-scale RNA sequencing, we observed that differentially expressed transcripts in HSV-1 infected dcOrgs were specifically enriched for AD-associated GWAS genes, but not for genes associated with other common neurodegenerative, neuropsychiatric or autoimmune diseases. Immediate treatment of HSV-1 infected dcOrgs with anti-herpetic drug acyclovir (ACV) rescued most of the cellular and transcriptomic biomarkers in a dosage-dependent manner, indicating that it is possible to use our high-throughput platform to identify compounds or target genes that can reverse these neuroinflammation-induced biomarkers associated with AD.

genomics↗

bioRxiv2023

Modeling of mitochondrial genetic polymorphisms reveals induction of heteroplasmy by pleiotropic disease locus MT:10398A>G

Mitochondrial (MT) dysfunction has been associated with several neurodegenerative diseases including Alzheimers disease (AD). While MT-copy number differences have been implicated in AD, the effect of MT heteroplasmy on AD has not been well characterized. Here, we analyzed over 1,800 whole genome sequencing data from four AD cohorts in seven different tissue types to determine the extent of MT heteroplasmy present. While MT-heteroplasmy was present throughout the entire MT genome for blood samples, we detected MT-heteroplasmy only within the MT control region for brain samples. We observed that an MT variant 10398A>G (rs2853826) was significantly associated with overall MT-heteroplasmy in brain tissue while also being linked with the largest number of distinct disease phenotypes of all annotated MT variants in MitoMap. Using gene-expression data from our brain samples, our modeling discovered several gene networks involved in mitochondrial respiratory chain and Complex I function associated with 10398A>G. The variant was also found to be an expression quantitative trait loci (eQTL) for the gene MT-ND3. We further characterized the effect of 10398A>G by phenotyping a population of lymphoblastoid cell-lines (LCLs) with and without the variant allele. Examination of RNA sequence data from these LCLs reveal that 10398A>G was an eQTL for MT-ND4. We also observed in LCLs that 10398A>G was significantly associated with overall MT-heteroplasmy within the MT control region, confirming the initial findings observed in post-mortem brain tissue. These results provide novel evidence linking MT SNPs with MT heteroplasmy and open novel avenues for the investigation of pathomechanisms that are driven by this pleiotropic disease associated loci.

genomics↗

bioRxiv2023

Expression of ALS-PFN1 impairs vesicular degradation in iPSC-derived microglia

Microglia play a pivotal role in neurodegenerative disease pathogenesis, but the mechanisms underlying microglia dysfunction and toxicity remain to be fully elucidated. To investigate the effect of neurodegenerative disease-linked genes on the intrinsic properties of microglia, we studied microglia-like cells derived from human induced pluripotent stem cells (iPSCs), termed iMGs, harboring mutations in profilin-1 (PFN1) that are causative for amyotrophic lateral sclerosis (ALS). ALS-PFN1 iMGs exhibited lipid dysmetabolism and deficits in phagocytosis, a critical microglia function. Our cumulative data implicate an effect of ALS-linked PFN1 on the autophagy pathway, including enhanced binding of mutant PFN1 to the autophagy signaling molecule PI3P, as an underlying cause of defective phagocytosis in ALS-PFN1 iMGs. Indeed, phagocytic processing was restored in ALS-PFN1 iMGs with Rapamycin, an inducer of autophagic flux. These outcomes demonstrate the utility of iMGs for neurodegenerative disease research and highlight microglia vesicular degradation pathways as potential therapeutic targets for these disorders.

neuroscience↗

bioRxiv2022

Reliable multiplex generation of pooled induced pluripotent stem cells for genetic testing

Inducing somatic cells into pluripotent stem cells (iPSCs) provides an excellent model for studying systems in-vitro. Understanding the impact of individual donor genetic backgrounds on reprogramming ability would allow researchers to harness these genetic differences and increase the efficiency of the reprogramming process. To better understand the genetic basis of reprogramming cells into iPSCs, we present Induction of Pluripotency from Pooled Cells (iPPC) - an efficient, scalable, and reliable reprogramming procedure. Using our deconvolution algorithm that employs low-coverage pooled sequencing and single nucleotide polymorphisms (SNPs), we estimate individual donor proportions of cell lines within large cohorts. With iPPC, we concurrently reprogrammed over one hundred donor LCLs into iPSCs and found strong correlations of individual donors reprogramming ability across multiple experiments. We note that individual donors reprogramming ability remains consistent across both same-day replicates and multiple experimental runs, and that the expression of certain immunoglobulin precursor genes (IGLV10-54, IGLV3-9, IGLV1-17, IGLV1-6, and IGLV3-1) may impact reprogramming ability. Our process enables a multiplex framework to study the reprogramming ability of different donor cells into iPSCs and also provides a reliable method along with a pooled library of donor iPSCs for downstream research and investigation of other in-vitro phenotypes.

molecular biology↗

bioRxiv2022

Iterative transcription factor screening enables rapid generation of microglia-like cells from human iPSC

The ability to differentiate stem cells into human cell types is essential to define basic mechanisms and therapeutics, especially for cell types not routinely accessible by biopsies. But while engineered expression of transcription factors (TFs) identified through TF screens has been found to rapidly and efficiently produce some cell types, generation of other cell types that require complex combinations of TFs has been elusive. Here we develop an iterative, pooled single-cell TF screening method that improves the identification of effective TF combinations using the generation of human microglia-like cells as a testbed: Two iterations identified a combination of SPI1, CEBPA, FLI1, MEF2C, CEBPB, and IRF8 as sufficient to differentiate human iPSC into microglia-like cells in 4 days. Characterization of TF-induced microglia demonstrated molecular and functional similarity to primary microglia. We explore the use of single-cell atlas reference datasets to confirm identified TFs and how combining single-cell TF perturbation and gene expression data can enable the construction of causal gene regulatory networks. We describe what will be needed to fashion these methods into a generalized integrated pipeline, further ideas for enhancement, and possible applications.

bioengineering↗

bioRxiv2020

Identifying cell type specific driver genes in autism-associated copy number loci from cerebral organoids

Neuropsychiatric and neurodevelopmental disorders have been particularly challenging to study using animal models, and recently, human-derived cerebral organoids demonstrate great promise for discovering molecular processes that are important in these disorders. However, several challenges remain in achieving robust phenotyping to discover cell type specific genes. We perform RNA sequencing on 71 samples comprising of 1,420 cerebral organoids from 25 donors, and describe a framework (Orgo-Seq) to identify cell type specific driver genes, for 16p11.2 deletions and 15q11-13 duplications. We identify neuroepithelial cells as critical cell types for 16p11.2 deletions, and discover novel and previously reported cell type specific driver genes. Finally, we validated our results that mutations in KCTD13 in the 16p11.2 locus lead to imbalances in the proportion of neuroepithelial cells, using CRISPR/Cas9-edited mosaic organoids. Our work presents a quantitative discovery and validation framework for identifying cell type specific driver genes associated with complex diseases using cerebral organoids.

genomics↗

bioRxiv2018

The Genetic Landscape of Diamond-Blackfan Anemia

Diamond-Blackfan anemia (DBA) is a rare bone marrow failure disorder that affects 1 in 100,000 to 200,000 live births and has been associated with mutations in components of the ribosome. In order to characterize the genetic landscape of this genetically heterogeneous disorder, we recruited a cohort of 472 individuals with a clinical diagnosis of DBA and performed whole exome sequencing (WES). Overall, we identified rare and predicted damaging mutations in likely causal genes for 78% of individuals. The majority of mutations were singletons, absent from population databases, predicted to cause loss of function, and in one of 19 previously reported genes encoding for a diverse set of ribosomal proteins (RPs). Using WES exon coverage estimates, we were able to identify and validate 31 deletions in DBA associated genes. We also observed an enrichment for extended splice site mutations and validated the diverse effects of these mutations using RNA sequencing in patientderived cell lines. Leveraging the size of our cohort, we observed several robust genotype-phenotype associations with congenital abnormalities and treatment outcomes. In addition to comprehensively identifying mutations in known genes, we further identified rare mutations in 7 previously unreported RP genes that may cause DBA. We also identified several distinct disorders that appear to phenocopy DBA, including 9 individuals with biallelic CECR1 mutations that result in deficiency of ADA2. However, no new genes were identified at exome-wide significance, suggesting that there are no unidentified genes containing mutations readily identified by WES that explain > 5% of DBA cases. Overall, this comprehensive report should not only inform clinical practice for DBA patients, but also the design and analysis of future rare variant studies for heterogeneous Mendelian disorders.

genetics↗