Metabolic alterations upon SARS-CoV-2 infection and potential therapeutic targets against coronavirus infection

The global prevalence and impact of steatotic liver disease and viral infections: A systematic review and meta-analysis

BACKGROUND

Steatotic liver disease (SLD) affects ~30% of adults worldwide. The global population is continuously threatened by epidemic and endemic viral diseases. This study aims to thoroughly examine the interaction between SLD and major viral diseases.

METHODS

We systematically searched databases from inception to April 2, 2024, for observational studies recording viral-infected adult patients with eligible data on the presence of hepatic steatosis.

RESULTS

Six hundred thirty-six eligible studies were included in the analysis of SLD prevalence. Among patients with monoinfections, the highest SLD prevalence was observed in those infected with HCV at 49% (95% CI: 47%-51%), followed by SARS-CoV-2 (39%, 95% CI [34%-44%]), HIV (39%, 95% CI [33%-44%]), and HBV (36%, 95% CI [32%-40%]). Additionally, co-infections, such as HCV-HIV and HBV-HCV, exhibit even higher SLD prevalence. The prevalence of steatohepatitis is particularly high in HIV-infected (24%, 95% CI: 17%-30%) and HCV-infected (18%, 95% CI: 13%-24%) populations. The co-existence of SLD with viral infections was associated not only with the progression of liver disease but also with more severe outcomes of the infections and poorer responses to antiviral treatment. The combination of cardiometabolic risk factors and viral-associated and host factors contributes to the higher risk of SLD in viral-infected populations.

CONCLUSIONS

SLD is highly prevalent in viral-infected populations, and the reciprocal interactions between SLD and viral diseases exacerbate both conditions, leading to poorer patient outcomes in general.

Possible link between steatotic liver diseases, severe COVID-19 and cognitive impairment in post-COVID-19 syndrome

PURPOSE

Steatotic liver diseases (SLD) have become more prevalent over the last decade and are associated not only with cardiometabolic diseases but also with psychological symptoms (depression, fatigue). These symptoms are also common in post-COVID syndrome (PCS). Therefore, the aim of the study was to analyze the burden of SLD in PCS patients.

METHODS

We systematically screened all PCS patients from our post-COVID outpatient clinic using transient elastography, structured questionnaires for neurocognitive evaluation and blood sample analysis. Controls without PCS and without known liver diseases were also recruited and assessed with the same approach.

RESULTS

560 PCS patients and 103 healthy controls were included. The overall prevalence of SLD was high in both cohorts (57 vs. 53%). PCS patients with SLD were more frequently male (41 vs. 24%), older (52 vs. 44 years) and had more cardiometabolic diseases (87.0 vs. 46.4%). Cognitive impairment was more related to SLD in PCS patients than in the no-SLD group (OR: 1.68, CI: 1.14-2.46, p = 0.008). The presence of SLD was related to severe COVID-19 with hospitalization (OR: 2.91, CI: 1.85-4.56, p < 0.001). Within 1 year of the follow-up, 152 of 289 patients described a resolution in PCS irrespective of the presence or absence of SLD (log-rank p = 0.96).

CONCLUSIONS

SLD is associated with severe COVID-19 and cognitive dysfunction in PCS. Longitudinal studies are needed to assess the role of hepatic steatosis, development of post-acute infection regulation (e.g., SARS-CoV-2) and to differentiate between SLD-associated symptoms and PCS.

Nanomechanical characterization of soft nanomaterial using atomic force microscopy

Atomic force microscopy (AFM) is a promising method for generating high-spatial-resolution images, providing insightful perspectives on the nanomechanical attributes of soft matter, including cells, bacteria, viruses, proteins, and nanoparticles. AFM is widely used in biological and pharmaceutical sciences because it can scrutinize mechanical properties under physiological conditions. We comprehensively reviewed experimental techniques and fundamental mathematical models to investigate the mechanical properties, including elastic moduli and binding forces, of soft materials. To determine these mechanical properties, two-dimensional arrays of force-distance (f-d) curves are obtained through AFM indentation experiments using the force volume technique. For elasticity determination, models are divided into approach f-d curve-based models, represented by the Hertz model, and retract f-d curve-based models, exemplified by the Johnson-Kendall-Roberts and Derjaguin-Müller-Toporov models. Especially, the Chen, Tu, and Cappella models, developed from the Hertz model, are used for thin samples on hard substrates. Additionally, the establishment of physical or chemical bonds during indentation experiments, observable in retract f-d curves, is crucial for the adhesive properties of samples and binding affinity between antibodies (receptors) and antigens (ligands). Chemical force microscopy, single-molecule force spectroscopy, and single-cell force spectroscopy are primary AFM methods that provide a comprehensive view of such properties through retract curve analysis. Furthermore, this paper, structured into key thematic sections, also reviews the exemplary application of AFM across multiple scientific disciplines. Notably, cancer cells are softer than healthy cells, although more sophisticated investigations are required for prognostic applications. AFM also investigates how bacteria adapt to antibiotics, addressing antimicrobial resistance, and reveals that stiffer virus capsids indicate reduced infectivity, aiding in the development of new strategies to combat viral infections. Moreover, AFM paves the way for innovative therapeutic approaches in designing effective drug delivery systems by providing insights into the physical properties of soft nanoparticles and the binding affinity of target moieties. Our review provides researchers with representative studies applying AFM to a wide range of cross-disciplinary research.

Comparative Interactome Profiling of Nonstructural Protein 3 Across SARS-CoV-2 Variants Emerged During the COVID-19 Pandemic

SARS-CoV-2 virus and its variants remain a global health threat, due to their capacity for rapid evolution. Variants throughout the COVID-19 pandemic exhibited variations in virulence, impacting vaccine protection and disease severity. Investigating nonstructural protein variants is critical to understanding viral evolution and manipulation of host protein interactions. We focus on nonstructural protein 3 (nsp3), with multiple domains with different activities, including viral polyprotein cleavage, host deubiquitylation, de-ISGylation, and double-membrane vesicle formation. Using affinity purification-mass spectrometry (AP-MS), we identify differential protein interactions in nsp3 caused by mutations found in variants identified between 2019 and 2024: Alpha 20I, Beta 20H, Delta 21I, Delta 21J, Gamma 20J, Kappa 21B, Lambda 21G, Omicron 21K, and Omicron 21L. A small set of amino acid substitutions in the N-terminal region of nsp3 (nsp3.1) could be traced to increased interactions with RNA-binding proteins, which are vital in viral replication. Meanwhile, variants of the central region of nsp3 (nsp3.2) were found to share interactions with protein quality control machinery, including ER-associated degradation. In this construct, shared trends in interactor enrichment are observed between Omicron 21K and Delta 21I. These results underscore how minor mutations reshape host interactions, emphasizing the evolutionary arms race between the host and virus. We provide a roadmap to track the interaction changes driven by SARS-CoV-2 variant evolution.

Longitudinal multi-omics analysis of convalescent individuals with respiratory sequelae 6-36 months after COVID-19

BACKGROUND

Approximately 10-30% of individuals continue to experience symptoms classified as post-acute sequelae of coronavirus disease 2019 (COVID-19 (PASC)). PASC is a multisystem condition primarily characterized by respiratory symptoms, such as reduced diffusing capacity for carbon monoxide (DLco). Although many studies have investigated the pathogenesis of acute COVID-19, the long-term molecular changes in COVID-19 convalescents with PASC remain poorly understood.

METHODS

We prospectively recruited 70 individuals who had been diagnosed with COVID-19 from 7 January 2020 to 29 May 2020 (i.e., COVID-19 convalescents); we performed follow-up visits at 6 months, 1 year, 2 years, and 3 years after hospital discharge. Thirty-five healthy controls (CONs), recruited from a physical examination center before the COVID-19 pandemic, served as a comparison group. We explored the proteomic and metabolomic profiles of 174 plasma samples from the 70 COVID-19 convalescents and 35 CONs.

RESULTS

We performed a comprehensive molecular analysis of COVID-19 convalescents to investigate host changes up to 3 years after hospital discharge. Our multi-omics analysis revealed activation of cytoskeletal organization and glycolysis/gluconeogenesis, as well as suppression of gas transport and adaptive immune responses, in COVID-19 convalescents. Additionally, metabolites involved in glutathione metabolism; alanine, aspartate, and glutamate metabolism; and ascorbate and aldarate metabolism were significantly upregulated in COVID-19 convalescents. Pulmonary and molecular abnormalities persisted for 3 years in COVID-19 convalescents; impaired diffusing capacity for carbon monoxide (DLco) was the most prominent feature. We used this multi-omics profile to develop a model involving one protein (heterogeneous nuclear ribonucleoprotein K (HNRNPK)) and two metabolites (arachidonoyl-EA and 1-O-(2r-hydroxy-pentadecyl)-sn-glycerol)) for identification of COVID-19 convalescents with abnormal DLco.

CONCLUSIONS

These data provide insights concerning molecular sequelae among COVID-19 convalescents up to 3 years after hospital discharge, clarify mechanisms driving respiratory sequelae, and support the development of a novel model to predict reduced DLco. This longitudinal multi-omics analysis may illuminate the trajectory of altered lung function in COVID-19 convalescents.

Recent advances in nutritional metabolism studies on SARS-CoV-2 infection

In the context of the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), metabolic research has become crucial for in-depth exploration of viral infection mechanisms and in searching for therapeutic strategies. This paper summarizes the interrelationships between carbohydrate, lipid, and amino acid metabolism and COVID-19 infection, discussing their roles in infection progression. SARS-CoV-2 infection leads to insulin resistance and increased glycolysis, reducing glucose utilization and shifting metabolism to use fat as an energy source. Fat is crucial for viral replication, and imbalances in amino acid metabolism may interfere with immune regulation. Consequently, metabolic changes such as hyperglycemia, hypolipidemia, and deficiency of certain amino acids following SARS-CoV-2 infection can contribute to progression toward severe conditions. These metabolic pathways not only have potential value in prediction and diagnosis but also provide new perspectives for the development of therapeutic strategies. By monitoring metabolic changes, infection severity can be predicted early, and modulating these metabolic pathways may help reduce inflammatory responses, improve immune responses, and reduce the risk of thrombosis. Research on the relationship between metabolism and SARS-CoV-2 infection provides an important scientific basis for addressing the global challenge posed by COVID-19, however, further studies are needed to validate these findings and provide more effective strategies for disease control.

Comparative metabolomic analysis reveals shared and unique features of COVID-19 cytokine storm and surgical sepsis

The clinical manifestations of the cytokine storm (CS) associated with COVID-19 resemble the acute phase of sepsis. Metabolomics may contribute to understanding the specific pathobiology of these two syndromes. The aim of this study was to compare serum metabolomic profiles in CS associated with COVID-19 vs. septic surgery patients. In a retrospective cross-sectional study, serum samples from patients with CS associated with COVID-19, with and without comorbidity, as well as serum samples from patients with surgical sepsis were investigated. Targeted metabolomic analysis was performed on all samples using LC-MS/MS. Analysis revealed that similar alterations in the serum metabolome of patients with COVID-19 and surgical septic patients were associated with amino acid metabolism, nitrogen metabolism, inflammatory status, methionine cycle and glycolysis. The most significant difference was found for serum levels of metabolites of kynurenine synthesis, tricarboxylic acid cycle, gamma-aminobutyric acid and niacinamide. The metabolic pathway of cysteine and methionine metabolism was significantly disturbed in COVID-19 and surgical septic patients. For the first time, the similarities and differences between the serum metabolomic profiles of patients with CS associated with COVID-19 and patients with surgical sepsis were investigated for patients from the Northwest of the Russian Federation.

Longitudinal Metabolomics Reveals Metabolic Dysregulation Dynamics in Patients with Severe COVID-19

Background/Objective: A dysregulated metabolism has been studied as a key aspect of the COVID-19 pathophysiology, but its longitudinal progression in severe cases remains unclear. In this study, we aimed to investigate metabolic dysregulation over time in patients with severe COVID-19 requiring mechanical ventilation (MV). Methods: In this single-center, prospective, observational study, we obtained 236 serum samples from 118 adult patients on MV in an ICU. The metabolite measurements were performed using capillary electrophoresis Fourier transform mass spectrometry, and we categorized the sampling time points into three time zones to align them with the disease progression: time zone 1 (T1) (the hyperacute phase, days 1-3 post-MV initiation), T2 (the acute phase, days 4-14), and T3 (the chronic phase, days 15-30). Using volcano plots and enrichment pathway analyses, we identified the differential metabolites (DMs) and enriched pathways (EPs) between the survivors and non-survivors for each time zone. The DMs and EPs were further grouped into early-stage, late-stage, and consistent groups based on the time zones in which they were detected. Results: With the 566 annotated metabolites, we identified 38 DMs and 17 EPs as the early-stage group, which indicated enhanced energy production in glucose, amino acid, and fatty acid metabolisms in non-survivors. As the late-stage group, 84 DMs and 10 EPs showed upregulated sphingolipid, taurine, and tryptophan-kynurenine metabolisms with downregulated steroid hormone synthesis in non-survivors. Three DMs and 23 EPs in the consistent group showed more pronounced dysregulation in the dopamine and arachidonic acid metabolisms across all three time zones in non-survivors. Conclusions: This study elucidated the temporal differences in metabolic dysregulation between survivors and non-survivors of severe COVID-19, offering insights into its longitudinal progression and disease mechanisms.

The Multiple Challenges of Nutritional Microbiome Research During COVID-19-A Perspective and Results of a Single-Case Study

The global coronavirus disease 2019 (COVID-19) pandemic has affected multiple aspects of people's lives, which may also influence the results of studies conducted during this period across diverse research domains. This particularly includes the field of nutritional science, investigating the gut microbiota as a potential mediator in the association between dietary intake and health-related outcomes. This article identifies the challenges currently facing this area of research, points out potential solutions, and highlights the necessity to consider a range of issues when interpreting trials conducted during this period. Some of these issues have arisen specifically because of the measures implemented to interrupt the spread of small acute respiratory syndrome coronavirus 2 (SARS-CoV-2), while others remain relevant beyond the pandemic.

Emerging small-molecule antiviral agents in long COVID prevention

Long COVID, or Post-Acute Sequelae of COVID-19 (PASC), was characterized by persistent symptoms such as fatigue, shortness of breath, and cognitive impairments. These symptoms, emerging one to 2 months post-infection and persisting for several months, cannot be attributed to other diagnoses. The pathophysiology of long COVID remained elusive; however, emerging studies suggested multiple potential mechanisms, including the reactivation of Epstein-Barr virus, persistent SARS-CoV-2 reservoirs, neuroinflammation, and vascular damage, which may contribute to its development. Long COVID affected multiple organ systems, including respiratory, circulatory, and nervous systems, leading to a range of functional impairments. Additionally, it showed a profound impact on mental health, manifesting as anxiety and depression, which significantly degraded the quality of life. The absence of definitive treatments underscored the importance of prevention. Recent evidence indicated that early antiviral intervention-particularly with small-molecule drugs such as Metformin, Ensitrelvir, Molnupiravir, and Nirmatrelvir-may effectively reduce the incidence of long COVID. This underscored the promising role of small-molecule compounds in mitigating long-term COVID-19 consequences, offering a novel preventive strategy against long COVID and its extensive impacts on patients.

SARS-CoV-2 uses Spike glycoprotein to control the host's anaerobic metabolism by inhibiting LDHB

The SARS-CoV-2 pandemic, responsible for approximately 7 million deaths worldwide, highlights the urgent need to understand the molecular mechanisms of the virus in order to prevent future outbreaks. The Spike glycoprotein of SARS-CoV-2, which is critical for viral entry through its interaction with ACE2 and other host cell receptors, has been a focus of this study. The present research goes beyond receptor recognition to explore Spike's influence on cellular metabolism. AP-MS interactome analysis revealed an interaction between the Spike S1 domain and lactate dehydrogenase B (LDHB), which was further confirmed by co-immunoprecipitation and immunofluorescence, indicating colocalisation in cells expressing the S1 domain. The study showed that Spike inhibits the catalytic activity of LDHB, leading to increased lactate levels in HEK-293T cells overexpressing the S1 subunit. In the hypothesised mechanism, Spike deprives LDHB of NAD+, facilitating a metabolic switch from aerobic to anaerobic energy production during infection. The Spike-NAD+ interacting region was characterised and mainly involves the W436 within the RDB domain. This novel hypothesis suggests that the Spike protein may play a broader role in altering host cell metabolism, thereby contributing to the pathophysiology of viral infection.

Exploring metabolic anomalies in COVID-19 and post-COVID-19: a machine learning approach with explainable artificial intelligence

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant challenges worldwide, including diverse clinical outcomes and prolonged post-recovery symptoms known as Long COVID or Post-COVID-19 syndrome. Emerging evidence suggests a crucial role of metabolic reprogramming in the infection's long-term consequences. This study employs a novel approach utilizing machine learning (ML) and explainable artificial intelligence (XAI) to analyze metabolic alterations in COVID-19 and Post-COVID-19 patients. Samples were taken from a cohort of 142 COVID-19, 48 Post-COVID-19, and 38 control patients, comprising 111 identified metabolites. Traditional analysis methods, like PCA and PLS-DA, were compared with ML techniques, particularly eXtreme Gradient Boosting (XGBoost) enhanced by SHAP (SHapley Additive exPlanations) values for explainability. XGBoost, combined with SHAP, outperformed traditional methods, demonstrating superior predictive performance and providing new insights into the metabolic basis of the disease's progression and aftermath. The analysis revealed metabolomic subgroups within the COVID-19 and Post-COVID-19 conditions, suggesting heterogeneous metabolic responses to the infection and its long-term impacts. Key metabolic signatures in Post-COVID-19 include taurine, glutamine, alpha-Ketoglutaric acid, and LysoPC a C16:0. This study highlights the potential of integrating ML and XAI for a fine-grained description in metabolomics research, offering a more detailed understanding of metabolic anomalies in COVID-19 and Post-COVID-19 conditions.

Emerging Microorganisms and Infectious Diseases: One Health Approach for Health Shared Vision

Emerging infectious diseases (EIDs) are newly emerging and reemerging infectious diseases. The National Institute of Allergy and Infectious Diseases identifies the following as emerging infectious diseases: SARS, MERS, COVID-19, influenza, fungal diseases, plague, schistosomiasis, smallpox, tick-borne diseases, and West Nile fever. The factors that should be taken into consideration are the genetic adaptation of microbial agents and the characteristics of the human host or environment. The new approach to identifying new possible pathogens will have to go through the One Health approach and omics integration data, which are capable of identifying high-priority microorganisms in a short period of time. New bioinformatics technologies enable global integration and sharing of surveillance data for rapid public health decision-making to detect and prevent epidemics and pandemics, ensuring timely response and effective prevention measures. Machine learning tools are being more frequently utilized in the realm of infectious diseases to predict sepsis in patients, diagnose infectious diseases early, and forecast the effectiveness of treatment or the appropriate choice of antibiotic regimen based on clinical data. We will discuss emerging microorganisms, omics techniques applied to infectious diseases, new computational solutions to evaluate biomarkers, and innovative tools that are useful for integrating omics data and electronic medical records data for the clinical management of emerging infectious diseases.

Host factors of SARS-CoV-2 in infection, pathogenesis, and long-term effects

SARS-CoV-2 is the causative virus of the devastating COVID-19 pandemic that results in an unparalleled global health and economic crisis. Despite unprecedented scientific efforts and therapeutic interventions, the fight against COVID-19 continues as the rapid emergence of different SARS-CoV-2 variants of concern and the increasing challenge of long COVID-19, raising a vast demand to understand the pathomechanisms of COVID-19 and its long-term sequelae and develop therapeutic strategies beyond the virus per se. Notably, in addition to the virus itself, the replication cycle of SARS-CoV-2 and clinical severity of COVID-19 is also governed by host factors. In this review, we therefore comprehensively overview the replication cycle and pathogenesis of SARS-CoV-2 from the perspective of host factors and host-virus interactions. We sequentially outline the pathological implications of molecular interactions between host factors and SARS-CoV-2 in multi-organ and multi-system long COVID-19, and summarize current therapeutic strategies and agents targeting host factors for treating these diseases. This knowledge would be key for the identification of new pathophysiological aspects and mechanisms, and the development of actionable therapeutic targets and strategies for tackling COVID-19 and its sequelae.

Metabolic regulation of type I interferon production

Over the past decade, there has been a surge in discoveries of how metabolic pathways regulate immune cell function in health and disease, establishing the field of immunometabolism. Specifically, pathways such as glycolysis, the tricarboxylic acid (TCA) cycle, and those involving lipid metabolism have been implicated in regulating immune cell function. Viral infections cause immunometabolic changes which lead to antiviral immunity, but little is known about how metabolic changes regulate interferon responses. Interferons are critical cytokines in host defense, rapidly induced upon pathogen recognition, but are also involved in autoimmune diseases. This review summarizes how metabolic change impacts interferon production. We describe how glycolysis, lipid metabolism (specifically involving eicosanoids and cholesterol), and the TCA cycle-linked intermediates itaconate and fumarate impact type I interferons. Targeting these metabolic changes presents new therapeutic possibilities to modulate type I interferons during host defense or autoimmune disorders.

Effect of the SARS-CoV-2 pandemic on metabolic control in patients with type 2 diabetes: a 5-year cohort follow-up managed by a dynamic multidisciplinary team in Northeastern Mexico

BACKGROUND

The SARS-CoV-2 pandemic brought a radical shift in the healthcare system and suboptimal care for vulnerable patients, such as those with Type 2 Diabetes Mellitus (T2D). Therefore, we compared metabolic control and macro/microvascular complications of patients with T2D before and throughout the three-year SARS-CoV-2 pandemic.

RESEARCH DESIGN AND METHODS

A retrospective observational cohort of subjects with T2D studied from 2018 to 2022 in Northern Mexico was treated by a dynamic multidisciplinary team. Levels of Glycated hemoglobin (HbA1c), fasting serum glucose (FG), LDL-Cholesterol (LDL-C), blood pressure (BP), albuminuria, triglycerides, Body Mass Index (BMI), and FIB-4 score, micro and macrovascular complications were evaluated.

RESULTS

A total of 999 patients were studied, 51.7% males with a mean (SD) age of 60.1 (12.7) years. Adequate glycemic control based on HbA1c increased by 15.2% and 42.3% in FSG (p < 0.001) between the beginning 2018 and the end of 2022. LDL-C control decreased by 5.1% between 2018 and 2022 (p < 0.001). Systolic BP control decreased by 2.6% (p < 0.001), whereas diastolic BP control increased by 1.8% (p = 0.01) between 2018 and 2022. Albuminuria control increased by 8.5% (p = 0.002). When comparing the Area Under the Curve (AUC) of metabolic parameters between patients who developed SARS-CoV-2 vs. those who did not, AUC was statistically higher in those who developed SARS-CoV-2 (p < 0.05). Diabetic neuropathy was the most prevalent microvascular complication (n = 35; 3.6%); ischemic heart disease was the most frequent macrovascular complication (n = 11;1.1%).

CONCLUSIONS

A multidisciplinary dynamic team that adapts to the pandemic SARS-CoV-2 maintains and increases metabolic control in subjects with type 2 diabetes in Mexico. This represents a low percentage of chronic complications. The AUC of metabolic parameters of subjects with SARS-CoV-2 infection is higher, reflecting more variability in metabolic control.

1-L Transcription of SARS-CoV-2 Spike Protein S1 Subunit

The COVID-19 pandemic prompted rapid research on SARS-CoV-2 pathogenicity. Consequently, new data can be used to advance the molecular understanding of SARS-CoV-2 infection. The present bioinformatics study discusses the "spikeopathy" at the molecular level and focuses on the possible post-transcriptional regulation of the SARS-CoV-2 spike protein S1 subunit in the host cell/tissue. A theoretical protein-RNA recognition code was used to check the compatibility of the SARS-CoV-2 spike protein S1 subunit with mRNAs in the human transcriptome (1-L transcription). The principle for this method is elucidated on the defined RNA binding protein GEMIN5 (gem nuclear organelle-associated protein 5) and RNU2-1 (U2 spliceosomal RNA). Using the method described here, it was shown that 45% of the genes/proteins identified by 1-L transcription of the SARS-CoV-2 spike protein S1 subunit are directly linked to COVID-19, 39% are indirectly linked to COVID-19, and 16% cannot currently be associated with COVID-19. The identified genes/proteins are associated with stroke, diabetes, and cardiac injury.

Regulation of lipid and serine metabolism by the oncogene c-Myc

Tumor formation is supported by metabolic reprogramming, characterized by increase nutrient uptake, glycolysis and glutaminolysis. The c-Myc proto-oncogene is a transcription factor, upregulated in most cancers and several reports showed the role of c-Myc in other metabolic pathways such as glucose, amino acid, and nucleotide metabolism. In this short report, we tried to summarize the existing takeaway points from studies conducted in different cancer types with respect to c-Myc and lipid and serine metabolism. Here, we report that c-Myc can activate both lipid and serine metabolism against the backdrop of tumor formation, and different therapies like aspirin and lomitapide target the links between c-Myc and metabolism to slow down tumor progression and invasion. We also report diverse upstream regulators that influence c-Myc in different cancers, and interestingly components of the lipid metabolism (like lipid phosphate phosphatase and leptin) and serine metabolism can also act upstream of c-Myc in certain occasions. Finally, we also summarize the existing knowledge on the involvement of epigenetic pathways and non-coding RNAs in regulating lipid and serine metabolism and c-Myc in tumor cells. Identification of non-coding factors and epigenetic mechanisms present a promising avenue of study that could empower researchers with novel anticancer treatment targeting c-Myc and lipid and serine metabolism pathways!

Decoding HiPSC-CM's Response to SARS-CoV-2: mapping the molecular landscape of cardiac injury

BACKGROUND

Acute cardiac injury caused by coronavirus disease 2019 (COVID-19) increases mortality. Acute cardiac injury caused by COVID-19 requires understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) directly infects cardiomyocytes. This study provides a solid foundation for related studies by using a model of SARS-CoV-2 infection in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) at the transcriptome level, highlighting the relevance of this study to related studies. SARS-CoV-2 infection in hiPSC-CMs has previously been studied by bioinformatics without presenting the full molecular biological process. We present a unique bioinformatics view of the complete molecular biological process of SARS-CoV-2 infection in hiPSC-CMs.

METHODS

To validate the RNA-seq datasets, we used GSE184715 and GSE150392 for the analytical studies, GSE193722 for validation at the cellular level, and GSE169241 for validation in heart tissue samples. GeneCards and MsigDB databases were used to find genes associated with the phenotype. In addition to differential expression analysis and principal component analysis (PCA), we also performed protein-protein interaction (PPI) analysis, functional enrichment analysis, hub gene analysis, upstream transcription factor prediction, and drug prediction.

RESULTS

Differentially expressed genes (DEGs) were classified into four categories: cardiomyocyte cytoskeletal protein inhibition, proto-oncogene activation and inflammation, mitochondrial dysfunction, and intracellular cytoplasmic physiological function. Each of the hub genes showed good diagnostic prediction, which was well validated in other datasets. Inhibited biological functions included cardiomyocyte cytoskeletal proteins, adenosine triphosphate (ATP) synthesis and electron transport chain (ETC), glucose metabolism, amino acid metabolism, fatty acid metabolism, pyruvate metabolism, citric acid cycle, nucleic acid metabolism, replication, transcription, translation, ubiquitination, autophagy, and cellular transport. Proto-oncogenes, inflammation, nuclear factor-kappaB (NF-κB) pathways, and interferon signaling were activated, as well as inflammatory factors. Viral infection activates multiple pathways, including the interferon pathway, proto-oncogenes and mitochondrial oxidative stress, while inhibiting cardiomyocyte backbone proteins and energy metabolism. Infection limits intracellular synthesis and metabolism, as well as the raw materials for mitochondrial energy synthesis. Mitochondrial dysfunction and energy abnormalities are ultimately caused by proto-oncogene activation and SARS-CoV-2 infection. Activation of the interferon pathway, proto-oncogene up-regulation, and mitochondrial oxidative stress cause the inflammatory response and lead to diminished cardiomyocyte contraction. Replication, transcription, translation, ubiquitination, autophagy, and cellular transport are among the functions that decline physiologically.

CONCLUSION

SARS-CoV-2 infection in hiPSC-CMs is fundamentally mediated via mitochondrial dysfunction. Therapeutic interventions targeting mitochondrial dysfunction may alleviate the cardiovascular complications associated with SARS-CoV-2 infection.

Exploring the plant lipidome: techniques, challenges, and prospects

Plant lipids are a diverse group of biomolecules that play essential roles in plant architecture, physiology, and signaling. To advance our understanding of plant biology and facilitate innovations in plant-based product development, we must have precise methods for the comprehensive analysis of plant lipids. Here, we present a comprehensive overview of current research investigating plant lipids, including their structures, metabolism, and functions. We explore major lipid classes, i.e. fatty acids, glyceroglycolipids, glycerophospholipids, sphingolipids, and phytosterols, and discuss their subcellular distributions. Furthermore, we emphasize the significance of lipidomics research techniques, particularly chromatography-mass spectrometry, for accurate lipid analysis. Special attention is given to lipids as crucial signal receptors and signaling molecules that influence plant growth and responses to environmental challenges. We address research challenges in lipidomics, such as in identifying and quantifying lipids, separating isomers, and avoiding batch effects and ion suppression. Finally, we delve into the practical applications of lipidomics, including its integration with other omics methodologies, lipid visualization, and innovative analytical approaches. This review thus provides valuable insights into the field of plant lipidomics and its potential contributions to plant biology.

Pre-Infection Innate Immunity Attenuates SARS-CoV-2 Infection and Viral Load in iPSC-Derived Alveolar Epithelial Type 2 Cells

A large portion of the heterogeneity in coronavirus disease 2019 (COVID-19) susceptibility and severity of illness (SOI) remains poorly understood. Recent evidence suggests that SARS-CoV-2 infection-associated damage to alveolar epithelial type 2 cells (AT2s) in the distal lung may directly contribute to disease severity and poor prognosis in COVID-19 patients. Our in vitro modeling of SARS-CoV-2 infection in induced pluripotent stem cell (iPSC)-derived AT2s from 10 different individuals showed interindividual variability in infection susceptibility and the postinfection cellular viral load. To understand the underlying mechanism of the AT2's capacity to regulate SARS-CoV-2 infection and cellular viral load, a genome-wide differential gene expression analysis between the mock and SARS-CoV-2 infection-challenged AT2s was performed. The 1393 genes, which were significantly (one-way ANOVA FDR-corrected p ≤ 0.05; FC abs ≥ 2.0) differentially expressed (DE), suggest significant upregulation of viral infection-related cellular innate immune response pathways (p-value ≤ 0.05; activation z-score ≥ 3.5), and significant downregulation of the cholesterol- and xenobiotic-related metabolic pathways (p-value ≤ 0.05; activation z-score ≤ -3.5). Whilst the effect of post-SARS-CoV-2 infection response on the infection susceptibility and postinfection viral load in AT2s is not clear, interestingly, pre-infection (mock-challenged) expression of 238 DE genes showed a high correlation with the postinfection SARS-CoV-2 viral load (FDR-corrected p-value ≤ 0.05 and r2-absolute ≥ 0.57). The 85 genes whose expression was negatively correlated with the viral load showed significant enrichment in viral recognition and cytokine-mediated innate immune GO biological processes (p-value range: 4.65 × 10-10 to 2.24 × 10-6). The 153 genes whose expression was positively correlated with the viral load showed significant enrichment in cholesterol homeostasis, extracellular matrix, and MAPK/ERK pathway-related GO biological processes (p-value range: 5.06 × 10-5 to 6.53 × 10-4). Overall, our results strongly suggest that AT2s' pre-infection innate immunity and metabolic state affect their susceptibility to SARS-CoV-2 infection and viral load.

Targeting SARS-CoV-2 entry processes: The promising potential and future of host-targeted small-molecule inhibitors

The COVID-19 pandemic, caused by SARS-CoV-2, has had a huge impact on global health. To respond to rapidly mutating viruses and to prepare for the next pandemic, there is an urgent need to develop small molecule therapies that target critical stages of the SARS-CoV-2 life cycle. Inhibiting the entry process of the virus can effectively control viral infection and play a role in prevention and treatment. Host factors involved in this process, such as ACE2, TMPRSS2, ADAM17, furin, PIKfyve, TPC2, CTSL, AAK1, V-ATPase, HSPG, and NRP1, have been found to be potentially good targets with stability. Through further exploration of the cell entry process of SARS-CoV-2, small-molecule drugs targeting these host factors have been developed. This review focuses on the structural functions of potential host cell targets during the entry of SARS-CoV-2 into host cells. The research progress, chemical structure, structure-activity relationship, and clinical value of small-molecule inhibitors against COVID-19 are reviewed to provide a reference for the development of small-molecule drugs against COVID-19.

Lipid Metabolism Modulation during SARS-CoV-2 Infection: A Spotlight on Extracellular Vesicles and Therapeutic Prospects

Extracellular vesicles (EVs) have a significant impact on the pathophysiological processes associated with various diseases such as tumors, inflammation, and infection. They exhibit molecular, biochemical, and entry control characteristics similar to viral infections. Viruses, on the other hand, depend on host metabolic machineries to fulfill their biosynthetic requirements. Due to potential advantages such as biocompatibility, biodegradation, and efficient immune activation, EVs have emerged as potential therapeutic targets against the SARS-CoV-2 infection. Studies on COVID-19 patients have shown that they frequently have dysregulated lipid profiles, which are associated with an increased risk of severe repercussions. Lipid droplets (LDs) serve as organelles with significant roles in lipid metabolism and energy homeostasis as well as having a wide range of functions in infections. The down-modulation of lipids, such as sphingolipid ceramide and eicosanoids, or of the transcriptional factors involved in lipogenesis seem to inhibit the viral multiplication, suggesting their involvement in the virus replication and pathogenesis as well as highlighting their potential as targets for drug development. Hence, this review focuses on the role of modulation of lipid metabolism and EVs in the mechanism of immune system evasion during SARS-CoV-2 infection and explores the therapeutic potential of EVs as well as application for delivering therapeutic substances to mitigate viral infections.

Early decrease in blood lymphocyte count is associated with poor prognosis in COVID-19 patients: a retrospective cohort study

BACKGROUND

Previous studies have declared that baseline lymphocyte count is associated with COVID-19-related death. However, whether dynamic lymphocyte change over time affects prognosis in COVID-19 patients is unknown. This study aims to investigate the significance of lymphocyte count during the progression of the disease in COVID-19 patients.

METHODS

The retrospective cohort study recruited COVID-19 patients at the First People's Hospital of Jiangxia District in Wuhan from January 7, 2020, to February 28, 2020. The demographics, medical histories, results of the blood routine test, and patients' outcomes were collected. We utilized a generalized additive mixed model to compare trends in lymphocyte count over time among survivors and non-survivors, with an adjustment for potential confounders. The statistical analysis used R software and EmpowerStats. Significance was determined at a P-value of less than 0.05 (two-sided).

RESULTS

A total of 532 patients were included in the study. Overall, there were 29/532 in-hospital deaths (5.45%). Lymphocytes declined over time in the non-survivor group and increased in the survivor group in the first 10 days of hospitalization. Within 10 days after admission, lymphocyte count increased in the survivor group and decreased in the non-survivor group. The difference in lymphocyte counts between survivors and non-survivors increased by an average of 0.0732 × 109/L daily. After adjusting for several covariables, the increasing value remained at 0.0731 × 109/L per day.

CONCLUSION

In the early stage, lymphocyte count can dynamically reflect the pathophysiological changes in COVID-19 patients. An early decrease in lymphocyte count is associated with mortality in COVID-19 patients.

Genomic communication via circulating extracellular vesicles and long-term health consequences of COVID-19

COVID-19 continues to affect an unprecedented number of people with the emergence of new variants posing a serious challenge to global health. There is an expansion of knowledge in understanding the pathogenesis of Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the impact of the acute disease on multiple organs. In addition, growing evidence reports that the impact of COVID-19 on different organs persists long after the recovery phase of the disease, leading to long-term consequences of COVID-19. These long-term consequences involve pulmonary as well as extra-pulmonary sequelae of the disease. Noteably, recent research has shown a potential association between COVID-19 and change in the molecular cargo of extracellular vesicles (EVs). EVs are vesicles released by cells and play an important role in cell communication by transfer of bioactive molecules between cells. Emerging evidence shows a strong link between EVs and their molecular cargo, and regulation of metabolism in health and disease. This review focuses on current knowledge about EVs and their potential role in COVID-19 pathogenesis, their current and future implications as tools for biomarker and therapeutic development and their possible effects on long-term impact of COVID-19.

Association between Lipid Levels, Anti-SARS-CoV-2 Spike Antibodies and COVID-19 Mortality: A Prospective Cohort Study

BACKGROUND

Recent studies suggest that both lipid levels and anti-severe-acute-respiratory-syndrome-coronavirus-2 (SARS-CoV-2) antibody levels are associated with outcome in coronavirus disease 2019 (COVID-19). While both parameters have separately been implicated in the neutralization and clearance of pathogens during severe infections, it is currently unclear whether the interplay of these parameters affects outcome in COVID-19. We therefore aimed to determine whether there was a relationship between lipoproteins, anti-SARS-CoV-2 antibodies, and COVID-19 mortality.

METHODS

In this prospective, multicenter cohort study, we recruited 1152 hospitalized patients with COVID-19 from five hospitals. Total cholesterol (TC), LDL-C, HDL-C, triglycerides, and anti-SARS-CoV-2 spike antibodies were measured on hospital admission. The investigated endpoint was in-hospital mortality.

RESULTS

LDL-C, HDL-C, and TC were significantly lower in non-survivors than in survivors (mg/dL, 95%CI; 56.1, 50.4-61.8 vs. 72.6, 70.2-75.0, p < 0.001; 34.2, 31.7-36.8 vs. 38.1, 37.2-39.1, p = 0.025; 139.3, 130.9-147.7 vs. 157.4, 54.1-160.6, p = 0.002). Mortality risk increased progressively with lower levels of LDL-C, HDL-C, and TC (aOR 1.73, 1.30-2.31, p < 0.001; 1.44, 1.10-1.88, p = 0.008; 1.49, 1.14-1.94, p < 0.001). Mortality rates varied between 2.1% for high levels of both LDL-C and anti-SARS-CoV-2 antibodies and 16.3% for low levels of LDL-C and anti-SARS-CoV-2 antibodies (aOR 9.14, 95%CI 3.17-26.34, p < 0.001). Accordingly, for total cholesterol and anti-SARS-CoV-2 antibodies, mortality rates varied between 2.1% and 15.0% (aOR 8.01, 95%CI 2.77-23.18, p < 0.001).

CONCLUSION

The combination of serum lipid levels and anti-SARS-CoV-2 antibodies is strongly associated with in-hospital mortality of patients with COVID-19. Patients with low levels of LDL-C and total cholesterol combined with low levels of anti-SARS-CoV-2 antibodies exhibited the highest mortality rates.