Biology subjects

Lim, T.

Publications and source records attributed to Lim, T..

13 recordsLinked to original sources

bioRxiv2025

Antiviral and anti-inflammatory effects of Tabamide A derivative, TA25, against human rhinovirus and multiple zoonotic viruses in vitro and in silico

Human rhinovirus (HRV), first isolated in 1956, belongs to the family Piconaviridae containing a positive-sense, single-stranded RNA genome. HRV causes mild cold and severe respiratory disease, such as asthma, COPD, and pneumonia. To date, no Food and Drug Administration-approved antiviral or anti-inflammatory drugs are available for HRV. TA25 is a phenolic amide derivative extracted from the leaves of Nicotiana tabacum. To investigate the potential candidate for antiviral therapeutics against zoonotic viruses, we evaluated the antiviral potency of TA25 for HRV and multiple zoonotic viruses. The antiviral and anti-inflammatory effects of TA25 were evaluated using RT-qPCR and RNA-seq. Strand-specific RT-qPCR was performed to measure genomic and anti-genomic RNA expression after TA25 treatment. In addition, an AI-based docking test was conducted to investigate the binding affinity of TA25 with viral target proteins. TA25 induced a significant reduction in viral replication and suppressed the expression of pro-inflammatory genes. Inhibition of viral replication by TA25 treatment was confirmed by strand-specific RT-qPCR. TA25 showed broad-spectrum antiviral activity against multiple viruses, including HRV-1A, Zika virus, Dengue virus, Vaccinia virus, and Influenza B virus Victoria. Using an AI-driven structure-based docking analysis, TA25 showed the strongest binding affinity with the HRV 2B protein. This study demonstrates that TA25 confers the broad antiviral and anti-inflammatory activity against HRV and multiple zoonotic viruses. These findings provide valuable insights into antiviral strategies of TA25 for a promising therapeutic candidate in response to emerging RNA and DNA viruses.

microbiology↗

bioRxiv2025

Modulation of Nutritional Composition and Aroma Volatiles in Cultivated Pork Fat by Culture Media Supplementation

Cultivated meat is emerging as a novel food source with the potential to contribute to a more sustainable and ethical food production system. However, limited research to date has explored the extent to which the nutrition and the aroma of such foods can be altered through cell culture conditions. Here, we aimed to modulate the aromatic volatile compounds in heated porcine cultivated fat cells by manipulating the media components while ensuring the preservation of robust fat differentiation. Using dynamic headspace gas chromatography-mass spectrometry (DHS-GC-MS), we demonstrated that supplementing cells with thiamine-HCl increased its intracellular concentration and promoted the production of 4-methyl-5-thiazoleethanol, contributing to milky aroma. Similarly, supplementation with L-methionine enhanced its intracellular concentration and increased the production of methional, a volatile compound with a potato-like aroma. Additionally, myoglobin significantly altered the volatile organic compound profile of cultivated fat. Notably, the concentration of {gamma}-nonalactone, (E,E)-2,4-decadienal and 2-pentylfuran were increased, which contribute to a coconut-like, deep fat, fruity aroma, respectively, as well as elevated levels of other alcohols, aldehydes and furans. These findings highlight the potential of culture media formulations to modulate the aroma in cultivated fat production, a unique opportunity to optimize sensory features using this novel food production technology. HighlightsNutrient composition and aroma profiles of cultivated pork fat upon baking were modulated by cell culture media supplementation. Supplementing with thiamine-HCl, L-methionine, or myoglobin increased intracellular levels of thiamine or methionine and modulated the formation of aroma volatiles, enhancing characteristic odors such as milky, potato-like, and coconut-like notes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/667495v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@11cd7c4org.highwire.dtl.DTLVardef@99b290org.highwire.dtl.DTLVardef@9a47beorg.highwire.dtl.DTLVardef@dc1689_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical overview of the methodology. Porcine dedifferentiated fat cells (pDFAT) were differentiated into adipocytes using adipogenesis media supplemented with aroma precursors. The cells were heated (cooked) and the resulting volatile compounds were analyzed using dynamic headspace gas chromatography-mass spectrometry (DHS-GC-MS).

biochemistry↗

bioRxiv2025

PASTA: Versatile Tyramine-oligonucleotide Amplification for Multi-modal Spatial Biology

Spatial proteomics techniques have revolutionized our understanding of tissue architecture, but are frequently limited by detection sensitivity, bioconjugation limitations, multiplexing capacity, and multi-modal integration. Here we present Protein and nucleic Acid Serial Tyramine Amplification (PASTA), a novel signal amplification approach that significantly enhances detection sensitivity while maintaining compatibility with diverse spatial profiling methodologies. PASTA utilizes horseradish peroxidase (HRP) recruitment pathways to generate tyramine radicals that deposit oligonucleotides, enabling adaptable signal amplification across multiple biomarkers at high-plex via cyclical imaging using complementary fluorophore-labeled oligonucleotides. We demonstrate that PASTA achieves up to 100-fold signal enhancement for markers with minimal background in blank controls. The method is compatible with in situ hybridization for DNA/RNA detection, proximity ligation assays for protein-protein interactions, sequential antibody staining protocols, or any modular combination thereof. PASTA enables antibody rescue of markers with suboptimal signal-to-noise ratios and is versatile in its applications to unconjugated antibodies, and multi-round probe-based RNA detection systems beyond current capabilities. This technique addresses key limitations in spatial-omics by enhancing sensitivity for challenging targets while maintaining compatibility with established multiplexing strategies, providing a versatile, cost-efficient, and valuable tool for comprehensive spatial tissue analysis in both research and clinical applications.

molecular biology↗

bioRxiv2024

Microbial lysates as low-cost serum replacements in cellular agriculture media formulation

Cultivated meat, the process of generating meat in vitro without sacrificing animals, is a promising alternative to the traditional practice of livestock agriculture. However, the success of this field depends on finding sustainable and economical replacements for animal-derived and expensive fetal bovine serum (FBS) that is typically used in cell culture processes. Here, we outline an effective screening process to vet the suitability of microbial lysates to support the growth of immortalized bovine satellite cells (iBSCs) and mackerel (Mack1) cells. We show that easily producible, low-cost whole-cell lysates from Vibrio natriegens can be used to create serum-free media for the long-term growth of iBSCs. The optimized medium, named "VN40" (basal B8 media containing Vibrio natriegens lysate proteins at 40 {micro}g/mL), outperforms previously established serum-free media while maintaining cell phenotype and myogenicity. Overall, this study shows a novel approach to producing serum-free media for cultivated meat production using microbially-derived lysates.

bioengineering↗

bioRxiv2024

Single-cell and spatial atlas of steatotic liver-related hepatocellular carcinoma

Steatotic liver disease-related hepatocellular carcinoma (SLD-HCC) poses significant challenges in liver cancer management. Our current study investigates the tumor microenvironment (TME) of SLD-HCC using single-cell transcriptomic, proteomic and spatial transcriptomic analyses. We identified altered immune-related and lipid metabolism pathways, particularly in regulatory T cells (Tregs) and cancer-associated fibroblasts (CAFs) within the SLD-HCC microenvironment, suggesting distinct cellular adaptations to a high-fat TME and general immunosuppression. Cytometry by time-of-flight revealed a cold and immunosuppressive TME depleted with CD8+ T cells and enriched with Tregs, while spatial transcriptomics uncovered a unique spatial architecture with Treg/CAF clusters specifically located at the tumor margins in SLD-HCC. Crucially, we identified Treg-CAF interactions as a key mediator associated with lack of response to immunotherapy in SLD-HCC. Our findings highlight the intricate immune dynamics of SLD-HCC, indicating potential therapeutic targets to counteract immune evasion and restore anti-tumor immunity in SLD-HCC. HighlightsO_LIThe TME of SLD-HCC exhibits altered immune and lipid pathways C_LIO_LIImmunosuppressive SLD-HCC TME is depleted with CD8+ T cells and enriched with Tregs C_LIO_LISLD-HCC has a unique spatial architecture with Treg-CAF clusters at tumor margins C_LIO_LITreg-CAF interaction via TNFSF14-TNFRSF14 axis mediates immunotherapy resistance C_LI

immunology↗

bioRxiv2023

Comparing virtual staining artificial intelligence model performance on same-tissue versus serial-tissue sections based on CD3+ T-cell ground truth

Immunophenotyping via multi-marker assays significantly contributes to patient selection, therapeutic monitoring, biomarker discovery, and personalized treatments. Despite its potential, the multiplex immunofluorescence (mIF) technique faces adoption challenges due to technical and financial constraints. Alternatively, hematoxylin and eosin (H&E)-based prediction models of cell phenotypes can provide crucial insights into tumor-immune cell interactions and advance immunotherapy. Current methods mostly rely on manually annotated cell label ground truths, with limitations including high variability and substantial labor costs. To mitigate these issues, researchers are increasingly turning to digitized cell-level data for accurate in-situ cell type prediction. Typically, immunohistochemical (IHC) staining is applied to a tissue section serial to one stained with H&E. However, this method may introduce distortions and tissue section shifts, challenging the assumption of consistent cellular locations. Conversely, mIF overcomes these limitations by allowing for mIF and H&E staining on the same tissue section. Importantly, the multiplexing capability of mIF allows for a thorough analysis of the tumor microenvironment by quantifying multiple cell markers within the same tissue section. In this study, we introduce a Pix2Pix generative adversarial network (P2P-GAN)-based virtual staining model, using CD3+ T-cells in lung cancer as a proof-of-concept. Using an independent CD3 IHC-stained lung cohort, we demonstrate that the model trained with cell label ground-truth from the same tissue section as H&E staining performed significantly better in both CD3+ and CD3- T-cell prediction. Moreover, the model also displayed prognostic significance on a public lung cohort, demonstrating its potential clinical utility. Notably, our proposed P2P-GAN virtual staining model facilitates image-to-image translation, enabling further spatial analysis of the predicted immune cells, deepening our understanding of tumor-immune interactions, and propelling advancements in personalized immunotherapy. This concept holds potential for the prediction of other cell phenotypes, including CD4+, CD8+, and CD20+ cells.

immunology↗

bioRxiv2023

In vitro broad-spectrum antiviral activity of MIT-001, a mitochondria-targeted reactive oxygen species scavenger, against severe acute respiratory syndrome coronavirus 2 and multiple zoonotic viruses

The COVID-19 pandemic caused by SARS-CoV-2 becomes a serious threat to global health and requires the development of effective antiviral therapies. Current therapies that target viral proteins have limited efficacy with side effects. In this study, we investigated the antiviral activity of MIT-001, a small molecule reactive oxygen species (ROS) scavenger targeting mitochondria, against SARS-CoV-2 and other zoonotic viruses in vitro. The antiviral activity of MIT-001 was quantified by RT-qPCR and plaque assay. We also evaluated the functional analysis of MIT-001 by JC-1 staining to measure mitochondrial depolarization, total RNA sequencing to investigate gene expression changes, and immunoblot to quantify protein expression levels. The results showed that MIT-001 effectively inhibited the replication of B.1.617.2 and BA.1 strains, Zika virus, Seoul virus, and Vaccinia virus. Treatment with MIT-001 restored the expression of heme oxygenase-1 (HMOX1) and NAD(P)H: quinone oxidoreductase 1 (NqO1) genes, anti-oxidant enzymes reduced by SARS-CoV-2, to normal levels. The presence of MIT-001 also alleviated mitochondrial depolarization caused by SARS-CoV-2 infection. These findings highlight the potential of MIT-001 as a broad-spectrum antiviral compound that targets for zoonotic RNA and DNA viruses, providing a promising therapeutic approach to combat viral infection.

microbiology↗

bioRxiv2023

Signal recovery in single cell batch integration

Data integration to align cells across batches has become a cornerstone of single cell data analysis, critically affecting downstream results. Yet, how much biological signal is erased during integration? Currently, there are no guidelines for when the biological differences between samples are separable from batch effects, and thus, data integration usually involve a lot of guesswork: Cells across batches should be aligned to be "appropriately" mixed, while preserving "main cell type clusters". We show evidence that current paradigms for single cell data integration are unnecessarily aggressive, removing biologically meaningful variation. To remedy this, we present a novel statistical model and computationally scalable algorithm, CellANOVA, to recover biological signal that is lost during single cell data integration. CellANOVA utilizes a "pool-of-controls" design concept, applicable across diverse settings, to separate unwanted variation from biological variation of interest. When applied with existing integration methods, CellANOVA allows the recovery of subtle biological signals and corrects, to a large extent, the data distortion introduced by integration. Further, CellANOVA explicitly estimates cell- and gene-specific batch effect terms which can be used to identify the cell types and pathways exhibiting the largest batch variations, providing clarity as to which biological signals can be recovered. These concepts are illustrated on studies of diverse designs, where the biological signals that are recovered by CellANOVA are shown to be validated by orthogonal assays. In particular, we show that CellANOVA is effective in the challenging case of single-cell and single-nuclei data integration, where the recovered biological signals are replicated in an independent study.

bioinformatics↗

bioRxiv2022

Continuous Fish Muscle Cell Line with Capacity for Myogenic and Adipogenic-like Phenotypes

Cell-cultivated fish offers the potential for a more ethical, sustainable, and safe seafood system. However, fish cell culture is relatively understudied in comparison to mammalian cells. Here, we established and characterized a continuous Atlantic mackerel (Scomber scombrus) skeletal muscle cell line ("Mack" cells). The cells were isolated from muscle biopsies of fresh-caught fish, with separate isolations performed from two distinct fish. Mack1 cells (cells from the first isolation) were cultured for over a year and subcultured over 130 times. The cells proliferated at initial doubling times of 63.9 hr ({+/-} 19.1 SD). After a spontaneous immortalization crisis from passages 37-43, the cells proliferated at doubling times of 24.3 hr ({+/-} 4.91 SD). A muscle phenotype was confirmed through characterization of muscle stemness and differentiation via paired-box protein 7 (PAX7) and myosin heavy chain (MHC) immunostaining, respectively. An adipocyte-like phenotype was also demonstrated for the cells through lipid accumulation, confirmed via Oil Red O (ORO) staining and quantification of neutral lipids. New qPCR primers (HPRT, PAX3B, MYOD1, MYOG, TNNT3A, and PPARG) were tailored to the mackerel genome and used to characterize mackerel cell genotypes. This work provides the first spontaneously immortalized fish muscle cell line for research, ideally serving as a reference for subsequent investigation.

bioengineering↗

bioRxiv2019

Detection of genomic alterations in breast cancer with circulating tumour DNA sequencing

Analysis of circulating cell-free DNA (cfDNA) data has opened new opportunities for characterizing tumour mutational landscapes with many applications in genomic-driven oncology. We developed a customized targeted cfDNA sequencing approach for breast cancer (BC) using unique molecular identifiers (UMIs) for error correction. Our assay, spanning a 284.5 kb target region, is combined with freely-available bioinformatics pipelines that provide ultra-sensitive detection of single nucleotide variants (SNVs), and reliable identification of copy number variations (CNVs) directly from plasma DNA. In a cohort of 35 BC patients, our approach detected actionable driver and clonal SNVs at low (~0.5%) frequency levels in cfDNA that were concordant (83.3%) with sequencing of primary and/or metastatic solid tumour sites. We also detected ERRB2 gene CNVs used for HER2 subtype classification with 80% precision compared to immunohistochemistry. Further, we evaluated fragmentation profiles of cfDNA in BC and observed distinct differences compared to data from healthy individuals. Our results show that the developed assay addresses the majority of tumour associated aberrations directly from plasma DNA, and thus may be used to elucidate genomic alterations in liquid biopsy studies.

genomics↗

bioRxiv2019

Comparison Between UMAP and t-SNE for Multiplex-Immunofluorescence Derived Single-Cell Data from Tissue Sections

Using human hepatocellular carcinoma (HCC) tissue samples stained with seven immune markers including one nuclear counterstain, we compared and evaluated the use of a new dimensionality reduction technique called Uniform Manifold Approximation and Projection (UMAP), as an alternative to t-Distributed Stochastic Neighbor Embedding (t-SNE) in analysing multiplex-immunofluorescence (mIF) derived single-cell data. We adopted an unsupervised clustering algorithm called FlowSOM to identify eight major cell types present in human HCC tissues. UMAP and t-SNE were ran independently on the dataset to qualitatively compare the distribution of clustered cell types in both reduced dimensions. Our comparison shows that UMAP is superior in runtime. Both techniques provide similar arrangements of cell clusters, with the key difference being UMAPs extensive characteristic branching. Most interestingly, UMAPs branching was able to highlight biological lineages, especially in identifying potential hybrid tumour cells (HTC). Survival analysis shows patients with higher proportion of HTC have a worse prognosis (p-value = 0.019). We conclude that both techniques are similar in their visualisation capabilities, but UMAP has a clear advantage over t-SNE in runtime, making it highly plausible to employ UMAP as an alternative to t-SNE in mIF data analysis.

bioinformatics↗

bioRxiv2018

Maternal immunity and antibodies to dengue promote Zika virus-induced microcephaly in fetuses

Zika virus (ZIKV), a recently emerged flaviviral pathogen, has been linked to microcephaly in neonates1. Yet, it is not understood why some fetuses develop severe microcephaly due to maternal ZIKV infection while others do not. The risk for ZIKV-induced microcephaly is greatest during the first trimester of pregnancy in humans2,3, yet this alone cannot account for the varied presentation of microcephaly observed. Given the antigenic similarity between ZIKV and closely related dengue virus (DENV)4, combined with the substantial immunity to DENV in ZIKV target populations in recent outbreaks, we hypothesized that maternal antibodies against DENV could promote ZIKV-induced microcephaly. Here, using immune-competent mice, we show that maternal to fetal transmission of ZIKV occurs, leading to fetal infection and disproportionate microcephaly. DENV-specific antibodies in pregnant female mice enhance vertical transmission of infection and result in a severe microcephaly like-syndrome during ZIKV infection. Furthermore, fetal infection was promoted by the neonatal Fc receptor (FcRN). Our results identify a novel immune-mediated mechanism of vertical transmission of viral infection and raise caution since ZIKV epidemic regions are also endemic to DENV.

immunology↗

bioRxiv2017

A Multi-Species Functional Embedding Integrating Sequence and Network Structure

A key challenge to transferring knowledge between species is that different species have fundamentally different genetic architectures. Initial computational approaches to transfer knowledge across species have relied on measures of heredity such as genetic homology, but these approaches suffer from limitations. First, only a small subset of genes have homologs, limiting the amount of knowledge that can be transferred, and second, genes change or repurpose functions, complicating the transfer of knowledge. Many approaches address this problem by expanding the notion of homology by leveraging high-throughput genomic and proteomic measurements, such as through network alignment.\n\nIn this work, we take a new approach to transferring knowledge across species by expanding the notion of homology through explicit measures of functional similarity between proteins in different species. Specifically, our kernel-based method, HO_SCPLOWANDLC_SCPLOW (Homology Assessment across Networks using Diffusion and Landmarks), integrates sequence and network structure to create a functional embedding in which proteins from different species are embedded in the same vector space. We show that inner products in this space capture functional similarity across species, and the vectors themselves are useful for a variety of cross species tasks. We perform the first whole-genome method for predicting phenologs, generating many that were previously identified, but also predicting new phenologs supported from the biological literature. We also demonstrate the HO_SCPLOWANDLC_SCPLOW-embedding captures pairwise gene function, in that gene pairs with synthetic lethal interactions are co-located in HO_SCPLOWANDLC_SCPLOW-space both within and across species. Software for the HO_SCPLOWANDLC_SCPLOW algorithm is available at http://github.com/lrgr/HANDL.

bioinformatics↗