Laboratory of Molecular Genetics

Age is a key risk factor for morbidity in coronavirus disease 2019 (COVID-19). This study investigates how "inflammaging" predisposes older hosts to severe SARS-CoV-2 outcomes through systemic and localized metabolic shifts. SARS-CoV-2 infection experiments were conducted respectively on 8 week-old mice and 16 week-old mice. An integrated multiomics approach was employed to delineate age-dependent molecular signatures and metabolic-immune crosstalk. 16 week-old mice exhibited significantly exacerbated weight loss and pulmonary pathology, successfully recapitulating age-related susceptibility. Multiomics integration revealed a "systemic bioenergetic gap": suppressed plasma TCA cycle metabolites correlated with depleted pulmonary nucleotide pools (AMP, GMP, UMP and uracil). This metabolic failure led to a paradoxical proteomic profile: despite interferon pathway activation, key antiviral effectors (RSAD2, ISG15, IFIT3B) were downregulated, while stress markers (CYP1A1, MAPK8) increased. Furthermore, threonic acid, betaine, and d-ribose were identified as robust, age-dependent biomarkers of infection severity. Our findings suggest that COVID-19 severity in the aging host is driven by the failure of a systemic-to-local metabolic-immune axis. The exhaustion of circulating energetic precursors constrains localized pulmonary nucleotide metabolism, thereby impairing essential antiviral responses and tissue repair. This study identifies the "systemic bioenergetic gap" as a novel therapeutic target, suggesting that systemic metabolic resuscitation may improve clinical outcomes in elderly populations.

Degenerative eye diseases are major causes of irreversible vision loss worldwide, but effective treatments remain limited, partly due to the lack of effective human models. Retinal organoids derived from stem cells can recapitulate key structural and physiological features of the human retina, offering powerful tools to study disease mechanisms and develop new therapies. Here, we review recent progress in engineering retinal organoids and eye-on-a-chip models for modeling degenerative eye diseases, with a focus on engineering innovations. We first describe conventional methods for organoid differentiation and characterization along with current outstanding challenges. To better engineer retinal organoids, new strategies that leverage microfluidics and biomaterials have emerged to regulate dynamic and physiologically relevant environments for organoid differentiation. Moreover, the integration of artificial intelligence, multimodal sensing, and data analytics improves the monitoring and prediction of retinal function and therapeutic outcomes. Finally, we discuss future directions in innovating next-generation retinal organoid and eye-on-a-chip models for disease modeling, drug discovery, and vision restoration, highlighting their potential for precision ophthalmology.

Repetitive mild traumatic brain injury (rmTBI) produces cumulative cellular stress that can lead to progressive brain dysfunction, yet the mechanisms governing vulnerability to repeated injury remain unclear. Protein kinase RNA-like endoplasmic reticulum kinase (PERK) regulates cellular proteostasis through the unfolded protein response and is implicated in neurodegeneration and acute brain injury. Here, we directly tested the role of PERK deficiency in shaping the brain’s response to rmTBI. Using a mouse model of neuronal PERK deficiency, we combined spatial proteomics and tissue analyses with resting-state functional MRI and diffusion tensor imaging to assess molecular, functional, and structural outcomes after rmTBI. PERK deficiency increased susceptibility to rmTBI-induced disruption of protein homeostasis, altered large-scale functional connectivity, and exacerbated white matter microstructural changes consistent with axonal and myelin damage. Molecular alterations were spatially aligned with imaging-defined network and white matter abnormalities. These findings identify PERK signaling as a key determinant of brain resilience to repetitive mild injury and link ER stress dysregulation to network-level dysfunction following rmTBI.

Macrophages (Mϕ) are an extremely heterogeneous and rapidly adapting set of innate immune cells that are scattered throughout all tissues in humans from mid-gestation onwards. Their original definition as key players in phagocytosis and defense against pathogens is too restrictive nowadays, as Mϕ are central to tissue homeostasis, repair, and complex immune regulations involving adaptive immunity. The Mϕ exhibit different ontogenies, originating from either embryonic progenitors or bone marrow, and their fate is shaped by tissue-specific microenvironments, which determine their adaptive phenotypes. This results in functional flexibility, exemplified by their ability to polarize into pro- (M1) or anti- (M2) inflammatory states in response to environmental cues. Such a dynamic process is critical for resolving infections, repairing tissue, and maintaining immune balance. Dysregulated Mϕ polarization is indeed implicated in various pathologies, including chronic inflammation, cancer, and fibrosis. Despite their importance, the study of tissue-resident Mϕ is still limited by technical challenges related to their isolation, maintenance, and donor variability. As an alternative, monocyte-derived macrophages (MDMs) represent an easier in vitro system to model human Mϕ biology under controlled conditions. However, MDMs differ from tissue-resident Mϕ in their developmental origin and functional specialization. This review outlines the key principles and limitations of MDM-based models, discusses commonly used differentiation protocols, and proposes methodological strategies to enhance reproducibility and physiological relevance in macrophage research.

Background & Objective: Alterations in global DNA methylation levels and repetitive elements are commonly observed in various cancers and in response to environmental pollutants, particularly petroleum products such as benzene. Long-term benzene exposure is harmful to human health and is associated with an increased risk of hematological malignancies. This study aimed to investigate the association between chronic occupational exposure to benzene and DNA methylation status in TGFβ2, MAGE-A1, and LINE-1 repetitive elements among gasoline station workers. Material and Methods: This case–control study included 30 male gasoline station workers and 30 male controls. Genomic DNA was extracted from peripheral blood samples using the QIAamp DNA Mini Kit (QIAGEN) and treated with sodium bisulfite via the EpiTect Fast DNA Bisulfite Kit. Singleplex MethyLight PCR was performed to assess methylation status of MAGE-A1, TGFβ2, and LINE-1. Results: Significant differences were observed in working hours (p = 0.004) and direct benzene exposure (p < 0.0001) between workers and controls. Percent MethyLight Reference (PMR) values were significantly different between the two groups for LINE-1 (p < 0.0001), TGFβ2 (p = 0.0194), and MAGE-A1 (p < 0.0001). Conclusion: Chronic benzene exposure is associated with altered DNA methylation patterns. Singleplex MethyLight analysis revealed significant PMR differences for MAGE-A1, LINE-1, and TGFβ2 between benzene-exposed workers and controls, highlighting the potential of DNA methylation profiling in occupational health risk assessment.

Protein structure prediction, a fundamental challenge emerging from the protein folding problem, forms the basis of modern computational biology. This field addresses the critical question of how the amino acids sequence determines its three-dimensional structure, a relationship critical to understanding biological function. Over the last four decades, methodologies have evolved from template-based modeling (TBM) and free modeling (FM) to advanced hybrid and end-to-end deep learning approaches. TBM explores sequence homology and threading to predict structures based on a known template, while FM applies physics-based principles to navigate the rugged energy landscape that governs protein folding, predicting de novo stable native conformations. Recent breakthrough methods in protein structure prediction include hybrid methods that integrate physics, bioinformatics, and machine learning, as well as end-to-end methods such as AlphaFold2 and RoseTTAFold, which have revolutionized the field by using neural networks to directly predict atomic coordinates from sequences, achieving near-experimental accuracy. Protein language models further advance the field by learning sequence-structure-function relationships directly from amino acid sequences, bypassing the need for multiple-sequence alignments. These innovations address the sequence-structure-function paradigm and find applications in drug discovery, enzyme engineering, and disease research. This chapter explores the principles, advances, and transformative impact of these methodologies on the structural biology field.

In genetic studies with the Hybrid Mouse Diversity Panel, we previously identified a chromosome 9 locus for atherosclerosis. We now identify NNMT (nicotinamide N-methyltransferase), an enzyme that degrades nicotinamide, as the causal gene in the locus and show that the underlying mechanism involves salvage of nicotinamide to nicotinamide adenine dinucleotide (NAD). Gain/loss of function studies in macrophages were performed to examine the role of NAD levels in macrophage proliferation and apoptosis in atherosclerosis. Global inhibition of NNMT using an antisense oligonucleotide reduced atherosclerosis lesion area 5- to 10-fold in both male and female mice on a hyperlipidemic background. Selective inhibition of NNMT in liver and adipose, the major tissues expressing high levels of the enzyme, using siRNA (small interfering RNA), had little or no effect on atherosclerosis. Therefore, we hypothesized that levels of NAD in macrophages might contribute. This was confirmed by showing that transplantation with bone marrow from Nnmt knockout mice resulted in reduced lesional macrophage proliferation, increased macrophage apoptosis, and reduced atherosclerosis. Consistent with this conclusion, reduced expression of macrophage CD38, an enzyme that degrades NAD, reduced both macrophage proliferation and atherosclerosis. Moreover, cultured macrophages from heterozygous Nnmt knockout mice exhibited reduced proliferation, increased apoptosis, and an increased NAD/NADH (nicotinamide adenine dinucleotide, reduced) ratio. These findings reveal a role for nicotinamide salvage and NAD turnover in macrophage proliferation and survival in the context of atherosclerosis.

FOXP3+ natural regulatory T cells (nTregs) promote resolution of inflammation and repair of epithelial damage following viral pneumonia–induced lung injury, thus representing a cellular therapy for patients with severe viral pneumonia and the acute respiratory distress syndrome. Whether in vitro–induced Tregs (iTregs), which can be rapidly generated in substantial numbers from conventional T cells, also promote lung recovery is unknown. nTregs require specific DNA methylation patterns maintained by the epigenetic regulator ubiquitin-like with PHD and RING finger domains 1 (UHRF1). Here, we tested whether iTregs promote recovery following viral pneumonia and whether iTregs require UHRF1 for their pro-recovery function. We found that adoptive transfer of iTregs to mice with influenza virus pneumonia promotes lung recovery and that loss of UHRF1-mediated maintenance DNA methylation in iTregs leads to reduced engraftment and a delayed repair response. Transcriptional and DNA methylation profiling of adoptively transferred UHRF1-deficient iTregs that had trafficked to influenza-injured lungs demonstrated transcriptional instability with gain of transcription factors that define effector T cell lineage. Strategies to promote the stability of iTregs could be leveraged to further augment their pro-recovery function during viral pneumonia and other causes of severe lung injury.

Genotyping is significant in identifying pathogen gene types and disease-related allele genes. Multiplex nucleic acid detection is convenient and useful for genotyping. Though CRISPR-Cas has great advantages in nucleic acid detection, multiplex detection strategies remain to be developed. Here, we propose a novel CRISPR-Cas strategy characterized by using stoichiometry coding of multiplex crRNAs. Different targets can be recognized by the corresponding crRNA with a certain amount, leading to distinguishable fluorescence difference. We employed this strategy to achieve Brucella species identification and human cell ABO blood genotyping. The detection can be conveniently visualized in a time-resolved way using a single tube, single Cas, and single reporter. The strategy can be employed in a PCR-coupled, RAA-coupled, or amplification-free way. The multiplex crRNA-coding CRISPR-Cas has potential application in differentiating gene types in various fields.

Post-intensive care syndrome (PICS) is a serious condition involving physical weakness, depression, and cognitive impairment that develop during or after an ICU stay, often resulting in long-term declines in quality of life. Patients with acute respiratory distress syndrome and severe coronavirus disease (COVID-19) are at particularly high risk, yet the molecular mechanisms underlying PICS remain poorly understood. Here, we identify impaired Apelin-APJ signaling as a potential contributor to PICS pathogenesis through the disruption of interorgan homeostasis. Using a mouse model combining acute lung injury and hindlimb immobilization, we observed PICS-like features, including muscle atrophy, lung inflammation, and neurobehavioral abnormalities such as anxiety-like behavior and special working memory. Single-cell RNA sequencing in brain revealed upregulation of gene programs associated with Alzheimer's disease, depression, and neuroinflammation, particularly in endothelial cells and microglia. Concurrently, Apelin-APJ signaling was downregulated in skeletal muscle. These changes were exacerbated in Apelin-deficient mice and attenuated by muscle-specific Apelin overexpression, which also reduced systemic IL-6 and restored circulating Apelin levels. In survivors of ARDS who had severe COVID-19, ICU-acquired weakness was associated with reduced plasma Apelin and elevated IL-6 levels. Transcriptomic profiling of peripheral blood mononuclear cells from patients with ICU-acquired weakness showed gene expression signatures linked to depression and neurodegeneration, mirroring murine findings. These data suggest that impaired Apelin-APJ signaling may play a role in PICS pathophysiology. Although skeletal muscle appears to contribute to systemic Apelin levels, further studies are needed to clarify tissue-specific roles. Modulating this pathway could offer a therapeutic strategy to mitigate long-term outcomes in ICU survivors.