Biology subjects

Chang, C.-W.

Publications and source records attributed to Chang, C.-W..

At least 19 recordsLinked to original sources

bioRxiv2026

Multiomic Spatial Imaging Assay (MSIA) -- A High-plex In Situ Detection Method for mRNAs, Proteins, and Protein-Protein Interactions using Manual And Semi-Automated Workflows

We report Multiomics Spatial Image Analysis (MSIA), a suite of technologies that include streamlined manual and semi-automated workflows to image 100s of RNAs from fresh frozen and formalin-fixed paraffin-embedded (FFPE) samples, contextualize RNAs with select protein markers including imaging synaptic protein interactions, a data analysis pipeline that includes corrections for chromatic aberration, algorithms for image stitching, deep learning models for image analysis (cell segmentation and RNA dot detection using hundreds of RNAscope images) from multiple stain-image cycles and proof of concept for a language model trained on extensive Parkinsons Disease (PD) literature. We used the language model to identify potential new biomarkers that were confirmed in MPTP-treated mouse model of PD. Furthermore, by incorporating more stain-image cycles alongside an additional fluorescent channel and advanced error-correcting decoding schemes, the MSIA workflow demonstrates the scalability to potentially quantify over 1,000 genes.

neuroscience↗

bioRxiv2025

Coronavirus NSP14 Drives Internal m7G Modification to Rewire Host Splicing and Promote Viral Replication

SARS-CoV-2, the causative agent of COVID-19, manipulates host gene expression through multiple mechanisms, including disruption of RNA processing. Here, we identify a novel function of the viral nonstructural protein 14 (NSP14) in inducing N7-methylguanosine (m7G) modification in the internal sequences of host mRNA. We demonstrate that NSP14 catalyzes the conversion of guanosine triphosphate (GTP) to m7GTP, which is subsequently incorporated into mRNA by RNA polymerase II, resulting in widespread internal m7G modification. This activity is dependent on NSP14s N7-methyltransferase (N7-MTase) domain and is enhanced by interaction with NSP10. Internal m7G modification by NSP14 predominantly occurs in the nucleus and is conserved across alpha-, beta- and gamma-coronaviruses. Mechanistically, we show that this RNA modification disrupts normal splicing by promoting intron retention and generating novel splice junctions, particularly in genes regulating genome stability, RNA metabolism and nuclear processes. Importantly, inhibition of m7G modification, through pharmacological targeting of NSP14 or RNA polymerase II, impairs SARS-CoV-2 replication, indicating that the virus hijacks host transcriptomic machinery to support infection. Our findings reveal a previously unrecognized epitranscriptomic mechanism by which coronaviruses reprogram host gene expression and suggest that NSP14-induced m7G modification is a potential therapeutic target.

microbiology↗

bioRxiv2025

Single-cell-resolved calcium and organelle dynamics in resistosome-mediated cell death

Plant nucleotide-binding domain leucine-rich repeat-containing (NLR) proteins act as intracellular immune receptors that assemble into resistosomes to execute immune responses. However, the subcellular processes during cell death following resistosome activation remain unclear. Here, we visualized the changes in calcium signaling and organelle behavior after activation of the NRC4 (NLR-required for cell death 4) resistosome. We found that NRC4 membrane enrichment coincided with calcium influx. This is followed by sequential mitochondria and plastid disruption, endoplasmic reticulum fragmentation and cytoskeleton depolymerization. Subsequent loss of plasma membrane integrity, nuclear shrinkage, and vacuolar collapse mark the terminal stage of cell death. Our findings reveal a spatiotemporally-resolved cascade of subcellular events downstream of resistosome activation, providing new mechanistic insight into the execution phase of plant immune cell death.

plant biology↗

bioRxiv2025

Type-I interferon priming signal balances anti-bacterial and anti-tumor trained immunity in alveolar macrophages

Tissue-resident macrophages may be trained to confer enhanced response to heterologous re-stimulation, and thus foster versatile trained immunity (TI) against both infections and tumors. However, key priming signals that contribute to such functional versatility in trained macrophages remain not fully understood. Here we show that influenza A virus (IAV) infection in mice induces lasting transcriptional imprints of acute type-I interferon (IFN-I) signaling in lung-resident alveolar macrophages (AMs) that confer balanced anti-bacterial and anti-tumor TI responses. In both IAV-infected mice and an ex vivo cytokine-mediated training system, IFN-I signaling is found to be critical to developing anti-tumor TI functions, although it limits anti-bacterial TI functions in AMs. Moreover, human AMs carrying transcriptional imprints of IFN-I signaling are associated with anti-tumor immunity and immune activation in lung cancer tissues. Our findings highlight IFN-I as a key priming signal required to developing versatile TI functions in AMs with balanced anti-bacterial and anti-tumor potential.

immunology↗

bioRxiv2025

Fat-rich diet reprograms intrapulmonary neutrophils to boost tissue-specific antitumor immunity

Neutrophils adapt to tissue-specific signals and exert innate defense functions against infections and malignancies. Fat-rich diet (FRD), such as high-fat diet (HFD) and ketogenic diet (KD), has complex impacts on immunity. However, whether and how FRD shapes tissue-specific functions of neutrophils remain unclear. Here we show that both isocaloric HFD- and KD-fed mice demonstrate enhanced neutrophil-mediated pulmonary tumor resistance than chow diet-fed mice. Intrapulmonary but not systemic neutrophils in FRD-fed mice bear enhanced potential of reactive oxygen species (ROS) production and ROS-dependent tumor cytotoxicity. Mechanistically, FRD-induced increased serum saturated fatty acids and cholesterol stimulate lung vascular endothelial cells (LVECs), which reprogram intrapulmonary neutrophils via contact- and intercellular adhesion molecule-1 (ICAM-1)-dependent mechanisms. Analysis on human lung single-cell RNA sequencing data showed that intensified cell adhesion and priming signals from human LVECs are associated with enhanced antitumor functions in intrapulmonary neutrophils. Our findings highlight the roles of dietary fats in shaping neutrophil functions in a tissue-specific manner. Dietary intervention targeting tissue-specific reprogramming of neutrophils therefore represents a potential strategy against malignancies in the lungs.

immunology↗

bioRxiv2025

Effects of using deep learning to predict the geographic origin of barley genebank accessions on genome-environment association studies

AbstractGenome-environment association (GEA) is an approach for identifying adaptive loci by combining genetic variation with environmental parameters, offering potential for improving crop resilience. However, its application to genebank accessions is limited by missing geographic origin data. To address this limitation, we explored the use of neural networks to predict the geographic origins of barley accessions and integrate imputed environmental data into GEA. Neural networks demonstrated high accuracy in cross-validation but occasionally produced ecologically implausible predictions as models solely considered geographical proximity. For example, some predicted origins were located within non-arable regions, such as the Mediterranean Sea. Using barley flowering time genes as benchmarks, GEA integrating imputed environmental data (N=11,032) displayed partially concordant yet complementary detection of genomic regions near flowering time genes compared to regular GEA (N=1,626), highlighting the potential of GEA with imputed data to complement regular GEA in uncovering novel adaptive loci. Also, contrary to our initial hypothesis anticipating a significant improvement in GEA performance by increasing sample size, our simulations yield unexpected insights. Our study suggests potential limitations in the sensitivity of GEA approaches to the considerable expansion in sample size achieved through predicting missing geographical data. Overall, our study provides insights into leveraging incomplete geographical origin data by integrating deep learning with GEA. Our findings indicate the need for further development of GEA approaches to optimize the use of imputed environmental data, such as incorporating regional GEA patterns instead of solely focusing on global associations between allele frequencies and environmental gradients across large-scale landscapes.

plant biology↗

bioRxiv2024

Glioblastoma Drives Protease-Independent Extracellular Matrix Invasion of Microglia

Glioblastoma (GBM) is the most common and lethal form of primary brain cancer. Microglia infiltration into the tumor microenvironment is associated with immunosuppression and poor prognosis. Improved physicochemical understanding of microglia activation and invasion may provide novel GBM therapeutic strategies essential for improving long-term treatment efficacy. Here, we combine microfluidic systems with 3-D collagen hydrogels to systematically investigate microglia activation, invasion, contractility and cytokine secretion in response of GBM-microglia crosstalk. GBM inflammatory biomolecules significantly promote activation and 3D invasion of microglia. Interestingly, microglia invasion is not significantly affected by inhibitors of MMP activity or cellular glycolysis. In contrast, ROCK-pathway inhibition significantly impedes microglia invasion. Infrared microscopy analyses show that GBM co-culture does not significantly alter microglia lipid content. Further, GBM conditioned media resulted in significantly increased collagen hydrogel contraction, suggesting the importance of microglia contractility to physically remodel the local extracellular matrix (ECM). We also identify a panel of soluble proteins that may contribute to microglia chemotaxis, such as TIMP-1 and CXCL12. Taken together, this study suggests that the presence of GBM cells can enhance microglia invasion via increased cellular contractility, independent of MMP activity and cellular glycolysis.

bioengineering↗

bioRxiv2024

Engineering Human ARMMs as Therapeutic Non-Viral Vehicles for in vivo Delivery of Genome Editing Payloads

The ability to edit the human genome to treat previously incurable diseases or to modify previously undruggable targets has the potential to transform the lives of patients. However, delivery of genome editing machineries in vivo, and in a transient manner, continues to be a major challenge. We engineered human cell-derived ARRDC1-mediated microvesicles (ARMMs) as non-viral vehicles that mediate intracellular delivery of proteins, including DNA-modifying enzymes such as Cre recombinase and Cas9/guide RNA ribonucleoproteins (RNPs). ARMMs packaged multiple payloads per vesicle in our production system, yielding dose-dependent functional delivery of Cre or Cas9/gRNA RNP to a variety of cell types, including primary mouse and human cells. Oropharyngeal aspiration of ARMMs loaded with Cre led to biodistribution to alveolar macrophages (AMs), whereas intravenous administration predominantly to Kupffer cells (KCs), liver sinusoidal endothelial cells (LSECs), and splenocytes. Suprisingly, one administration of ARMMs loaded with Cas9 RNPs by oropharyngeal aspiration or intravenously resulted in efficient knockout of multiple genes in AMs or KCs, suggesting potential therapeutic utility. Through intravenous administration of ARMMs loaded with Cas9/NLRP3 gRNA we showed amelioration of drug-induced liver injury in a mouse model, supporting the use of ARMMs as human cell-derived therapeutic vehicles for genome editor delivery in vivo.

bioengineering↗

bioRxiv2024

Programmable Editing of Primary MicroRNA Switches Stem Cell Differentiation and Improves Tissue Regeneration

Programmable RNA editing is harnessed for modifying mRNA. Besides mRNA, miRNA also regulates numerous biological activities, but current RNA editors have yet to be exploited for miRNA manipulation. To engineer primary miRNA (pri-miRNA), the miRNA precursor, we present a customizable editor REPRESS (RNA Editing of Pri-miRNA for Efficient Suppression of miRNA) and characterize critical parameters. The optimized REPRESS is distinct from other mRNA editing tools in design rationale, hence enabling editing of pri-miRNAs that are not editable by other RNA editing systems. We edited various pri-miRNAs in different cells including adipose-derived stem cells (ASCs), hence attenuating mature miRNA levels without disturbing host gene expression. We further developed an improved REPRESS (iREPRESS) that enhances and prolongs pri-miR-21 editing for at least 10 days, with minimal perturbation of transcriptome and miRNAome. iREPRESS reprograms ASCs differentiation, promotes in vitro cartilage formation and augments calvarial bone regeneration in rats, thus implicating its potentials for engineering miRNA for many applications such as stem cell engineering and tissue regeneration.

bioengineering↗

bioRxiv2024

Single-cell transcriptomics reveal differences between chorionic and basal plate cytotrophoblasts and trophoblast stem cells

Cytotrophoblast (CTB) of the early gestation human placenta are bipotent progenitor epithelial cells, which can differentiate into invasive extravillous trophoblast (EVT) and multinucleated syncytiotrophoblast (STB). Trophoblast stem cells (TSC), derived from early first trimester placentae, have also been shown to be bipotential. In this study, we set out to probe the transcriptional diversity of first trimester CTB and compare TSC to various subgroups of CTB. We performed single-cell RNA sequencing on six normal placentae, four from early (6-8 weeks) and two from late (12-14 weeks) first trimester, of which two of the early first trimester cases were separated into basal (maternal) and chorionic (fetal) fractions prior to sequencing. We also sequenced three TSC lines, derived from 6-8 week placentae, to evaluate similarities and differences between primary CTB and TSC. CTB clusters displayed notable distinctions based on gestational age, with early first trimester placentae showing enrichment for specific CTB subtypes, further influenced by origin from the basal or chorionic plate. Differential expression analysis of CTB from basal versus chorionic plate highlighted pathways associated with proliferation, unfolded protein response, and oxidative phosphorylation. We identified trophoblast states representing initial progenitor CTB, precursor STB, precursor and mature EVT, and multiple CTB subtypes. CTB progenitors were enriched in early first trimester placentae, with basal plate cells biased toward EVT, and chorionic plate cells toward STB, precursors. Clustering and trajectory inference analysis indicated that TSC were most like EVT precursor cells, with only a small percentage of TSC on the pre-STB differentiation trajectory. This was confirmed by flow cytometric analysis of 6 different TSC lines, which showed uniform expression of proximal column markers ITGA2 and ITGA5. Additionally, we found that ITGA5+ CTB could be plated in 2D, forming only EVT upon spontaneous differentiation, but failed to form self-renewing organoids; conversely, ITGA5-CTB could not be plated in 2D, but readily formed organoids. Our findings suggest that distinct CTB states exist in different regions of the placenta as early as six weeks gestation and that current TSC lines most closely resemble ITGA5+ CTB, biased toward the EVT lineage.

developmental biology↗

bioRxiv2023

Microscopy-guided subcellular proteomic discovery by high-speed ultra-content photo-biotinylation

Microscopy-guided proteomics at an organelle-dimension resolution is desired for revealing unknown protein constituents at specific disease- or functional-associated regions at the molecular-molecular interactions level. Here, we achieve protein spatial purification by introducing a firmware-integrated microscopy platform that triggers in situ subcellular photo-biotinylation of proteins at user-defined regions of interest (ROIs) one field of view (FOV) at a time for thousands of FOVs fully automatically. An illumination pattern at the analogous ROIs of each FOV is calculated on the fly by either machine learning or traditional image processing. Photoactivatable amino acid crosslinkers are activated by a two-photon focal light one spot at a time at a sub-millisecond illumination duration per spot. Imaging, pattern generation, targeted illumination, and FOV movement are coordinated and cycled with high-speed mechatronic control to complete illumination on millions of ROI spots within hours. Once enough proteins are biotinylated in a cell or tissue sample, the sample is scraped and lysed, and avidin pulldown is used to enrich proteins to achieve spatial protein scooping at a 240-nm precision. Subsequent LC-MS/MS is implemented to reveal the subcellular proteome in high sensitivity, specificity, and resolution. Using this technology termed optoproteomics, we have revealed novel stress granule-localized and amyloid {beta}-localized proteins validated by immunostaining. Together, spatial purification by ultra-content, high-speed microscopy-targeted photo-biotinylation enables unprecedented subcellular spatial proteomics discovery in any microscopically recognizable regions.

cell biology↗

bioRxiv2023

GGoutlieR: an R package to identify and visualize unusual geo-genetic patterns of biological samples

Landscape genomics is an emerging field of research that integrates genomic and environmental information to explore the drivers of evolution. Reliable data on the geographical origin of biological samples is a prerequisite for accurate landscape genomics studies. Traditionally, researchers discover potentially questionable samples using visualization-based tools. However, such approaches cannot handle large sample sizes due to overlapping data points on a graph and can hinder reproducible research. To address this shortcoming, we developed Geo-Genetic outlier (GGoutlieR), an R package of a heuristic framework for detecting and visualizing samples with unusual geo-genetic patterns. Outliers are identified by calculating empirical p-values for each sample, allowing users to identify them in data sets with thousands of samples. The package also provides a plotting function to display the geo-genetic patterns of outliers on a geographical map. GGoutlieR could significantly reduce the amount of data cleaning that researchers need to do before carrying out landscape genomics analyses.

bioinformatics↗

bioRxiv2023

Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy

BackgroundCancer immunotherapy has transformed the clinical approach to patients with malignancies as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment (TME) to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. MethodsWe developed approaches to categorize solid tumors into "Desert", "Excluded" and "Inflamed" types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. ResultsWe show that categorization based on "manual" observation is predictive for clinical benefit from anti-programmed cell death ligand-1 (PD-L1) therapy in two large cohorts of patients with non-small cell lung cancer (NSCLC) or triple-negative breast cancer (TNBC). For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based read-outs and patient response to therapy. ConclusionsOur findings suggest tumor immunophenotype (IP) generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. What is already known on this topicClinical benefit from checkpoint inhibitor-targeted therapies is realized only in a subset of patients. Robust biomarkers to identify patients who may respond to such therapies are needed. What this study addsWe have developed manual and automated approaches to categorize tumors into immunophenotypes based on the spatial distribution of CD8+ T effector cells that predict clinical benefit from anti-PD-L1 immunotherapy for patients with advanced non-small cell lung cancer or triple-negative breast cancer. How this study might affect research, practice or policyTumor immunophenotypes should be further validated as predictive biomarker for checkpoint inhibitor-targeted therapies in prospective clinical studies.

pathology↗

bioRxiv2022

Sensitive and specific miRNA in situ hybridization using partially methylated phosphotriester antisense DNA probes

Neutralized DNA (nDNA) is an emerging class of DNA oligonucleotides chemically synthesized with site-specific internucleoside methyl phosphotriester linkages, changing the negatively charged DNA phosphodiester backbone to a neutral methyl phosphotriester backbone. The reduction of inter-strand charge repulsion of nucleotide duplexes results in stronger binding between nDNA and other nucleic acids, and as such, nDNA has been used as a sensitive antisense probe for sequencing nucleotides. From a thermodynamic perspective due to steric effects, a hybrid duplex between DNA and partially methylated nDNA should possess higher specificity than a duplex between DNA with fully methylated nDNA, while retaining binding affinity. However, the application of nDNA for ex vivo RNA hybridization at low transcript abundance remains completely unexplored. Here, we determined that partially methylated nDNA (N4 nDNA; with 4 methylated nucleotides) probes inhibited reverse transcription of oncogenic miRNA miR-21 more efficiently than canonical DNA probes or highly methylated nDNA probes (all probes share the same sequence) and with an efficiency rivaling LNA probes. Subsequently, we performed in situ hybridization analysis using a miR-21-expressing colorectal cancer cell line (HCT116). HCT116 stained with N4 nDNA probes revealed a greater detection intensity and specificity than HCT116 stained with canonical DNA probes. Consistently, enzyme-linked immunosorbent assays revealed that miRNA hybridization efficiency of N4 nDNA probes was greater than that of canonical DNA probes at cellular transcript levels. Given that N4 nDNA probe is immune-negative and DNase I-resistant, partially methylated nDNA could be further developed to have significant applications in biotechnology and medicine.

bioengineering↗

bioRxiv2022

ECM-derived biophysical cues mediate interstitial flow-induced sprouting angiogenesis

Sprouting angiogenesis is orchestrated by an intricate balance of biochemical and mechanical cues in the local microenvironment. Interstitial flow has been established as a potent regulator of angiogenesis. Similarly, extracellular matrix (ECM) physical properties, such as stiffness and microarchitecture, have also emerged as important mediators of angiogenesis. Yet, the interplay between interstitial flow and ECM physical properties in the initiation and control of angiogenesis is poorly understood. Using a 3-D microfluidic tissue analogue of angiogenic sprouting with defined interstitial flow, we found that the addition of hyaluronan (HA) to collagen-based matrices significantly enhances sprouting induced by interstitial flow compared to responses in collagen-only hydrogels. We confirmed that both the stiffness and matrix pore size of collagen-only hydrogels were increased by the addition of HA. Interestingly, interstitial flow-potentiated sprouting responses in collagen/HA matrices were not affected when functionally blocking the HA receptor CD44. In contrast, enzymatic depletion of HA in collagen/HA matrices with hyaluronidase (HAdase) resulted in decreased stiffness, pore size, and interstitial flow-mediated sprouting to the levels observed in collagen-only matrices. Taken together, these results suggest that HA enhances interstitial flow-mediated angiogenic sprouting through its alterations to collagen ECM stiffness and pore size.

bioengineering↗

bioRxiv2022

Cell culture model system utilizing engineered A549 cells to express high levels of ACE2 and TMPRSS2 for investigating SARS-CoV-2 infection and antivirals

Novel pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to pose an imminent global threat since its initial outbreak in December 2019. A simple in vitro model system using cell lines highly susceptible to SARS-CoV-2 infection are critical to facilitate the study of the virus cycle and to discover effective antivirals against the virus. Human lung alveolar A549 cells are regarded as a useful and valuable model for respiratory virus infection. However, SARS-CoV-2 uses the ACE2 as receptor for viral entry and the TMPRSS2 to prime the Spike protein, both of which are negligibly expressed in A549 cells. Here, we report the generation of a robust human lung epithelial cell-based model by transducing ACE2 and TMPRSS2 into A549 cells and show that the ACE2 enriched A549ACE2/TMPRSS2 cells (ACE2plus) and its single-cell-derived subclone (ACE2plusC3) are highly susceptible to SARS-CoV-2 infection. These engineered ACE2plus showed higher ACE2 and TMPRSS2 mRNA expression levels than currently used Calu3 and commercial A549ACE2/TMPRSS2 cells. ACE2 and TMPRSS2 proteins were also highly and ubiquitously expressed in ACE2plusC3 cells. Additionally, antiviral drugs like Camostat mesylate, EIDD-1931, and Remdesivir strongly inhibited SARS-CoV-2 replication. Notably, multinucleated syncytia, a clinical feature commonly observed in severe COVID-19 patients was induced in ACE2plusC3 cells either by virus infection or by overexpressing the Spike proteins of different variants of SARS-CoV-2. Syncytial process was effectively blocked by the furin protease inhibitor, Decanoyl-RVKR-CMK. Taken together, we have developed a robust human A549 lung epithelial cell-based model that can be applied to probe SARS-CoV-2 replication and to facilitate the discovery of SARS-CoV-2 inhibitors.

cell biology↗

bioRxiv2021

Physical geography, isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum in the Southern Levant

Determining the extent of genetic variation that reflects local adaptation in crop wild relatives is of interest to discovering useful genetic diversity for plant breeding. We investigated the association of genomic variation with geographical and environmental factors in wild barley (Hordeum vulgare L. ssp. spontaneum) populations of the Southern Levant using genotyping-by-sequencing (GBS) of 244 accessions of the Barley1K+ collection. Inference of population structure resulted in four genetic clusters that corresponded to eco-geographical habitats and a significant association of lower gene flow rates with geographical barriers, e.g. the Judaean Mountains and the Sea of Galilee. Redundancy analysis (RDA) revealed that spatial autocorrelation explained 45% and environmental variables explained 15% of total genomic variation. Only 4.5% of genomic variation was exclusively attributed to environmental variation if the component confounded with spatial autocorrelation was excluded. A synthetic environmental variable combining latitude, solar radiation, and accumulated precipitation explained the highest proportion of genomic variation (3.9%). After correcting for population structure, soil water capacity was the most important environmental variable explaining 1.18% of genomic variation. Genome scans with outlier analysis and genome-environment association studies were conducted to identify signatures of adaptation. RDA and outlier methods jointly detected selection signatures in the pericentromeric regions of chromosome 3H, 4H, and 5H, but they mostly disappeared after correction for population structure. In conclusion, adaptation to the highly diverse environments of the Southern Levant over short geographical ranges has a small effect on the genomic diversity of wild barley highlighting the importance of non-selective forces in genetic differentiation.

evolutionary biology↗

bioRxiv2021

A glimpse into the diverse cellular immunity against SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific cellular immune response may prove to be essential for long-term immune protection against the novel coronavirus disease 2019 (COVID-19). To assess COVID-19-specific immunity in the population, we synthesized selected peptide pools of SARS-CoV-2 structural and functional proteins, including Spike (S), Membrane (M), Envelope (E), Nucleocapsid (N) and Protease (P) as target antigens. Survey of the T cell precursur frequencies in healthy individuals specific to these viral antigens demonstrated a diverse cellular immunity, including high, medium, low and no responders. This was further confirmed by in vitro induction of anti-SARS-CoV-2 T cell immune responses using dendritic cell (DC)/T cell coculture, which supported the corresponding T cell precursor frequencies in each of the individuals tested. In general, the combination of all five viral antigen pools induced the strongest cellular immune response, yet individual donors responded differently to different viral antigens. Importantly, in vitro restimulation of the T cells with the DC-peptides induced increased anti-viral immune responses in all individuals even in the no responders, suggesting that repeated antigen stimulation could elicit a broad protection in immune naive population. Our analysis recapitulates the critical role of cellular immunity in fighting COVID-19 and the importance of analyzing anti-SARS-CoV-2 T cell response in addition to antibody response in the population. ImportanceFacing the rapid evolving SARS-CoV-2 variants in the world, current emphasis on antibody-producing vaccines needs a quick revisit. The virus-specific cellular immunity may prove to be essential for long-term protection against COVID-19. This study designed a series of antigenic peptides encompassing the conserved and/or essential domains of Spike (S), Membrane (M), envelope (E), Nucleocapsid (N) and Protease (P) as targets to assess Covid-19-specific immunity in the population. The results demonstrated a diverse cellular immunity, including high, medium, low and no responders. This was verified by in vitro generation of anti-SARS-CoV-2 T-cells from these subjects. The study suggested that individuals responded differently to the different viral antigens, and importantly, repeated stimulation could produce virus specific T cells in all individuals, including the no responders. This study illustrates the needs for assessing anti-viral cellular immunity in addition to antibody response in the general population.

microbiology↗