Transcriptomic characteristics and impaired immune function of patients who retest positive for SARS-CoV-2 RNA

Reconstitution of double-negative T cells after cord blood transplantation and its predictive value for acute graft-versus-host disease

BACKGROUND

With an increasing number of patients with hematological malignancies being treated with umbilical cord blood transplantation (UCBT), the correlation between immune reconstitution (IR) after UCBT and graft-versus-host disease (GVHD) has been reported successively, but reports on double-negative T (DNT) cell reconstitution and its association with acute GVHD (aGVHD) after UCBT are lacking.

METHODS

A population-based observational study was conducted among 131 patients with hematological malignancies who underwent single-unit UCBT as their first transplant at the Department of Hematology, the First Affiliated Hospital of USTC, between August 2018 and June 2021. IR differences were compared between the patients with and without aGVHD.

RESULTS

The absolute number of DNT cells in the healthy Chinese population was 109 (70-157)/μL, accounting for 5.82 (3.98-8.19)% of lymphocytes. DNT cells showed delayed recovery and could not reach their normal levels even one year after transplantation. Importantly, the absolute number and percentage of DNT cells were significantly higher in UCBT patients without aGVHD than in those with aGVHD within one year ( F = 4.684, P = 0.039 and F = 5.583, P = 0.026, respectively). In addition, the number of DNT cells in the first month after transplantation decreased significantly with the degree of aGVHD increased, and faster DNT cell reconstitution in the first month after UCBT was an independent protective factor for aGVHD (HR = 0.46, 95% confidence interval [CI]: 0.23-0.93; P = 0.031).

CONCLUSIONS

Compared to the number of DNT cells in Chinese healthy people, the reconstitution of DNT cells in adults with hematological malignancies after UCBT was slow. In addition, the faster reconstitution of DNT cells in the early stage after transplantation was associated with a lower incidence of aGVHD.

Parameterization of asymmetric sigmoid functions in weighted gene co-expression network analysis

In most the biological contexts, examining gene expressions at the genomic level gives more accurate results than examining genes individually. It can improve understanding of the molecular mechanisms that cause molecular alterations. Weighted gene co-expression network analysis (WGCNA), which has recently been widely used to cluster transcriptomic datasets, implements a soft thresholding procedure using power function. However, these functions may sometimes exaggerate minor differences in expression correlations. We have previously proposed to use asymmetric sigmoid functions in soft thresholding as an alternative solution. However, the number of variables in asymmetric sigmoid functions may vary and parameterization can be problematic. In this study, we have introduced a systematic procedure for parameterizing asymmetric sigmoid function to ease using it as an alternative soft-thresholding solution in WGCNA. The efficiency of the employment was shown on four different COVID-19 datasets, on a yeast dataset, and on an E.Coli dataset. The results indicate that this approach provides biologically plausible associations for the resulting modules.

The novel role of IFITM1-3 in myogenic differentiation of C2C12 cells

Interferon-induced transmembrane proteins (IFITMs 1, 2, and 3) play a critical role in preventing pathogen infection in vertebrates. They are also involved in the occurrence and prognosis of cancer. Myogenesis is a complex process regulated by several factors. This study disclosed that Ifitm1-3 were upregulated in the process of myogenic differentiation of C2C12 myoblasts on days 3, 5, and 7. This positively correlated with the expression of differentiation factors MyoD, myogenin, Mrf5, and desmin. Furthermore, knockdown of Ifitm1-3 by their individual siRNAs inhibited myogenesis of C2C12 myoblasts, with relative downregulation of MyoD, myogenin, Mrf5, and desmin. Subsequently, myotube formation and fusion percentage decreased. Co-immunoprecipitation combined with LC-MS/MS analysis uncovered the interaction proteins of IFITM1 and IFITM3 in C2C12 myoblasts. A total of 84 overlapped interaction proteins of IFITM1 and IFITM3 were identified, and one of the clusters was engaged in cytoskeletal and sarcomere proteins, including desmin, myosin, actin, vimentin, nestin, ankycorbin, and nucleolin. Hence, we hypothesize that these interacting proteins may function as scaffolds for IFITM1-3, possibly through the interaction protein desmin to initiate further interaction with other proteins to participate in myogenesis; however, the molecular mechanisms remain unclear. Our study may contribute to the development of novel therapeutics for myopathic diseases.

Using Machine Learning Methods in Identifying Genes Associated with COVID-19 in Cardiomyocytes and Cardiac Vascular Endothelial Cells

Corona Virus Disease 2019 (COVID-19) not only causes respiratory system damage, but also imposes strain on the cardiovascular system. Vascular endothelial cells and cardiomyocytes play an important role in cardiac function. The aberrant expression of genes in vascular endothelial cells and cardiomyocytes can lead to cardiovascular diseases. In this study, we sought to explain the influence of respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the gene expression levels of vascular endothelial cells and cardiomyocytes. We designed an advanced machine learning-based workflow to analyze the gene expression profile data of vascular endothelial cells and cardiomyocytes from patients with COVID-19 and healthy controls. An incremental feature selection method with a decision tree was used in building efficient classifiers and summarizing quantitative classification genes and rules. Some key genes, such as MALAT1, MT-CO1, and CD36, were extracted, which exert important effects on cardiac function, from the gene expression matrix of 104,182 cardiomyocytes, including 12,007 cells from patients with COVID-19 and 92,175 cells from healthy controls, and 22,438 vascular endothelial cells, including 10,812 cells from patients with COVID-19 and 11,626 cells from healthy controls. The findings reported in this study may provide insights into the effect of COVID-19 on cardiac cells and further explain the pathogenesis of COVID-19, and they may facilitate the identification of potential therapeutic targets.

Human Endogenous Retrovirus (HERV) Transcriptome Is Dynamically Modulated during SARS-CoV-2 Infection and Allows Discrimination of COVID-19 Clinical Stages

SARS-CoV-2 infection is known to trigger an important inflammatory response, which has a major role in COVID-19 pathogenesis. In infectious and inflammatory contexts, the modulation of human endogenous retroviruses (HERV) has been broadly reported, being able to further sustain innate immune responses due to the expression of immunogenic viral transcripts, including double-stranded DNA (dsRNA), and eventually, immunogenic proteins. To gain insights on this poorly characterized interplay, we performed a high-throughput expression analysis of ~3,300 specific HERV loci in the peripheral blood mononuclear cells (PBMCs) of 10 healthy controls and 16 individuals being either convalescent after the infection (6) or retesting positive after convalescence (10) (Gene Expression Onmibus [GEO] data set GSE166253). Results showed that the exposure to SARS-CoV-2 infection modulates HERV expression according to the disease stage and reflecting COVID-19 immune signatures. The differential expression analysis between healthy control (HC) and COVID-19 patients allowed us to identify a total of 282 differentially expressed HERV loci (deHERV) in the individuals exposed to SARS-CoV-2 infection, independently from the clinical form. In addition, 278 and 60 deHERV loci that were specifically modulated in individuals convalescent after COVID19 infection (C) and patients that retested positive to SARS-CoV-2 after convalescence (RTP) as individually compared to HC, respectively, as well as 164 deHERV loci between C and RTP patients were identified. The identified HERV loci belonged to 36 different HERV groups, including members of all three classes. The present study provides an exhaustive picture of the HERV transcriptome in PBMCs and its dynamic variation in the presence of COVID-19, revealing specific modulation patterns according to the infection stage that can be relevant to the disease clinical manifestation and outcome. IMPORTANCE We report here the first high-throughput analysis of HERV loci expression along SARS-CoV-2 infection, as performed with peripheral blood mononuclear cells (PBMCs). Such cells are not directly infected by the virus but have a crucial role in the plethora of inflammatory and immune events that constitute a major hallmark of COVID-19 pathogenesis. Results provide a novel and exhaustive picture of HERV expression in PBMCs, revealing specific modulation patterns according to the disease condition and the concomitant immune activation. To our knowledge, this is the first set of deHERVs whose expression is dynamically modulated across COVID-19 stages, confirming a tight interplay between HERV and cellular immunity and revealing specific transcriptional signatures that can have an impact on the disease clinical manifestation and outcome.

Classification of tuberculosis-related programmed cell death-related patient subgroups and associated immune cell profiling

Background

Tuberculosis (TB) is the deadliest communicable disease in the world with the exception of the ongoing COVID-19 pandemic. Programmed cell death (PCD) patterns play key roles in the development and progression of many disease states such that they may offer value as effective biomarkers or therapeutic targets that can aid in identifying and treating TB patients.

Materials and methods

The Gene Expression Omnibus (GEO) was used to gather TB-related datasets after which immune cell profiles in these data were analyzed to examine the potential TB-related loss of immune homeostasis. Profiling of differentially expressed PCD-related genes was performed, after which candidate hub PCD-associated genes were selected via a machine learning approach. TB patients were then stratified into two subsets based on the expression of PCD-related genes via consensus clustering. The potential roles of these PCD-associated genes in other TB-related diseases were further examined.

Results

In total, 14 PCD-related differentially expressed genes (DEGs) were identified and highly expressed in TB patient samples and significantly correlated with the abundance of many immune cell types. Machine learning algorithms enabled the selection of seven hub PCD-related genes that were used to establish PCD-associated patient subgroups, followed by the validation of these subgroups in independent datasets. These findings, together with GSVA results, indicated that immune-related pathways were significantly enriched in TB patients exhibiting high levels of PCD-related gene expression, whereas metabolic pathways were significantly enriched in the other patient group. Single cell RNA-seq (scRNA-seq) further highlighted significant differences in the immune status of these different TB patient samples. Furthermore, we used CMap to predict five potential drugs for TB-related diseases.

Conclusion

These results highlight clear enrichment of PCD-related gene expression in TB patients and suggest that this PCD activity is closely associated with immune cell abundance. This thus indicates that PCD may play a role in TB progression through the induction or dysregulation of an immune response. These findings provide a foundation for further research aimed at clarifying the molecular drivers of TB, the selection of appropriate diagnostic biomarkers, and the design of novel therapeutic interventions aimed at treating this deadly infectious disease.

Genomic Biomarker Heterogeneities between SARS-CoV-2 and COVID-19

Genes functionally associated with SARS-CoV-2 infection and genes functionally related to the COVID-19 disease can be different, whose distinction will become the first essential step for successfully fighting against the COVID-19 pandemic. Unfortunately, this first step has not been completed in all biological and medical research. Using a newly developed max-competing logistic classifier, two genes, ATP6V1B2 and IFI27, stand out to be critical in the transcriptional response to SARS-CoV-2 infection with differential expressions derived from NP/OP swab PCR. This finding is evidenced by combining these two genes with another gene in predicting disease status to achieve better-indicating accuracy than existing classifiers with the same number of genes. In addition, combining these two genes with three other genes to form a five-gene classifier outperforms existing classifiers with ten or more genes. These two genes can be critical in fighting against the COVID-19 pandemic as a new focus and direction with their exceptional predicting accuracy. Comparing the functional effects of these genes with a five-gene classifier with 100% accuracy identified and tested from blood samples in our earlier work, the genes and their transcriptional response and functional effects on SARS-CoV-2 infection, and the genes and their functional signature patterns on COVID-19 antibodies, are significantly different. We will use a total of fourteen cohort studies (including breakthrough infections and omicron variants) with 1481 samples to justify our results. Such significant findings can help explore the causal and pathological links between SARS-CoV-2 infection and the COVID-19 disease, and fight against the disease with more targeted genes, vaccines, antiviral drugs, and therapies.

Advances in Immunotherapy for Hepatitis B

Hepatitis B virus (HBV) is a hepatotropic virus with the potential to cause chronic infection, and it is one of the common causes of liver disease worldwide. Chronic HBV infection leads to liver cirrhosis and, ultimately, hepatocellular carcinoma (HCC). The persistence of covalently closed circular DNA (cccDNA) and the impaired immune response in patients with chronic hepatitis B (CHB) has been studied over the past few decades. Despite advances in the etiology of HBV and the development of potent virus-suppressing regimens, a cure for HBV has not been found. Both the innate and adaptive branches of immunity contribute to viral eradication. However, immune exhaustion and evasion have been demonstrated during CHB infection, although our understanding of the mechanism is still evolving. Recently, the successful use of an antiviral drug for hepatitis C has greatly encouraged the search for a cure for hepatitis B, which likely requires an approach focused on improving the antiviral immune response. In this review, we discuss our current knowledge of the immunopathogenic mechanisms and immunobiology of HBV infection. In addition, we touch upon why the existing therapeutic approaches may not achieve the goal of a functional cure. We also propose how combinations of new drugs, and especially novel immunotherapies, contribute to HBV clearance.

PEDOT:PSS in Solution Form Exhibits Strong Potential in Inhibiting SARS-CoV-2 Infection of the Host Cells by Targeting Viruses and Also the Host Cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic with over 5 million fatalities. Vaccines against this virus have been globally administered; however, SARS-CoV-2 variants with spike protein mutations are continuously identified with strong capability to escape vaccine-elicited protection. Due to the high mutation rate and transmission ability, the development of a broad-spectrum SARS-CoV-2 inhibitor is highly in demand. In this study, the effect of poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) against SARS-CoV-2 was investigated. The treatment of pseudoviruses carrying the SARS-CoV-2 spike protein with PEDOT:PSS strongly blocked SARS-CoV-2 pseudovirus infection in human ACE2-expressing cells without causing cytotoxicity. Specifically, PEDOT:PSS showed great potential in both inactivating viruses and rendering antiviral activity to the treated cells. The effects of other PEDOT:PSS solutions with different chemical ratios and properties were also validated to find the high inhibition capacity against SARS-CoV-2 pseudovirus infection. The transcriptomic data reveal that PEDOT:PSS-treated cells were endowed with transcriptional alteration, and it could be reverted after the removal of PEDOT:PSS from the culture medium. Importantly, PEDOT:PSS also exhibited broad-spectrum inhibition effects on the pseudovirus carrying the spike protein isolated from different variants. In combination with the advantage of high biocompatibility, PEDOT:PSS could thus be considered a potential therapeutic and prophylactic material against SARS-CoV-2.