MINRbase: a comprehensive database of nuclear- and mitochondrial-ribosomal-RNA-derived fragments (rRFs).

We describe the Mitochondrial and Nuclear rRNA fragment database (MINRbase), a knowledge repository aimed at facilitating the study of ribosomal RNA-derived fragments (rRFs). MINRbase provides interactive access to the profiles of 130 238 expressed rRFs arising from the four human nuclear rRNAs (18S, 5.8S, 28S, 5S), two mitochondrial rRNAs (12S, 16S) or four spacers of 45S pre-rRNA. We compiled these profiles by analyzing 11 632 datasets, including the GEUVADIS and The Cancer Genome Atlas (TCGA) repositories. MINRbase offers a user-friendly interface that lets researchers issue complex queries based on one or more criteria, such as parental rRNA identity, nucleotide sequence, rRF minimum abundance and metadata keywords (e.g. tissue type, disease). A 'summary' page for each rRF provides a granular breakdown of its expression by tissue type, disease, sex, ancestry and other variables; it also allows users to create publication-ready plots at the click of a button. MINRbase has already allowed us to generate support for three novel observations: the internal spacers of 45S are prolific producers of abundant rRFs; many abundant rRFs straddle the known boundaries of rRNAs; rRF production is regimented and depends on 'personal attributes' (sex, ancestry) and 'context' (tissue type, tissue state, disease). MINRbase is available at https://cm.jefferson.edu/MINRbase/.

Differential co-expression network analysis with DCoNA reveals isomiR targeting aberrations in prostate cancer.

MOTIVATION: One of the standard methods of high-throughput RNA sequencing analysis is differential expression. However, it does not detect changes in molecular regulation. In contrast to the standard differential expression analysis, differential co-expression one aims to detect pairs or clusters whose mutual expression changes between two conditions. RESULTS: We developed Differential Co-expression Network Analysis (DCoNA)-an open-source statistical tool that allows one to identify pair interactions, which correlation significantly changes between two conditions. Comparing DCoNA with the state-of-the-art analog, we showed that DCoNA is a faster, more accurate and less memory-consuming tool. We applied DCoNA to prostate mRNA/miRNA-seq data collected from The Cancer Genome Atlas (TCGA) and compared predicted regulatory interactions of miRNA isoforms (isomiRs) and their target mRNAs between normal and cancer samples. As a result, almost all highly expressed isomiRs lost negative correlation with their targets in prostate cancer samples compared to ones without the pathology. One exception to this trend was the canonical isomiR of hsa-miR-93-5p acquiring cancer-specific targets. Further analysis showed that cancer aggressiveness simultaneously increased with the expression level of this isomiR in both TCGA primary tumor samples and 153 blood plasma samples of P. Hertsen Moscow Oncology Research Institute patients' cohort analyzed by miRNA microarrays. AVAILABILITY AND IMPLEMENTATION: Source code and documentation of DCoNA are available at https://github.com/zhiyanov/DCoNA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

T-CoV: a comprehensive portal of HLA-peptide interactions affected by SARS-CoV-2 mutations.

Rapidly appearing SARS-CoV-2 mutations can affect T cell epitopes, which can help the virus to evade either CD8 or CD4 T-cell responses. We developed T-cell COVID-19 Atlas (T-CoV, https://t-cov.hse.ru) - the comprehensive web portal, which allows one to analyze how SARS-CoV-2 mutations alter the presentation of viral peptides by HLA molecules. The data are presented for common virus variants and the most frequent HLA class I and class II alleles. Binding affinities of HLA molecules and viral peptides were assessed with accurate in silico methods. The obtained results highlight the importance of taking HLA alleles diversity into account: mutation-mediated alterations in HLA-peptide interactions were highly dependent on HLA alleles. For example, we found that the essential number of peptides tightly bound to HLA-B*07:02 in the reference Wuhan variant ceased to be tight binders for the Indian (Delta) and the UK (Alpha) variants. In summary, we believe that T-CoV will help researchers and clinicians to predict the susceptibility of individuals with different HLA genotypes to infection with variants of SARS-CoV-2 and/or forecast its severity.

On the peptide binding affinity changes in population-specific HLA repertoires to the SARS-CoV-2 variants Delta and Omicron.

OBJECTIVE: To investigate the changes of Spike protein-HLA binding affinity profiles between the Wuhan strain and two dominant variants, the Delta and the Omicron strains, among the Taiwanese, the British and the Russian populations. METHODS: The HLA frequencies and the HLA-peptide binding affinity profiles in the T-CoV database were combined to conduct the study. We focused on the public alleles in the three populations (HLA-A, HLA-B, HLA-C, HLA-DRB1, and/or HLA-DPA1/DPB1 alleles) and the altered peptides of the spike protein (compared to the Wuhan strain) in the Delta G/478K·V1 (B.1.617.2 + AY.1 + AY.2) and the Omicron (BA.1) strains. RESULTS: For the Delta strain, tight bindings of the altered peptides to the HLA alleles decrease in all three populations and almost vanish in the Taiwanese population. For the Omicron strain, tight bindings are mostly preserved for both HLA classes and in the Taiwanese and the British populations, with a slight reduction in HLA class II in the Taiwanese (1.4%), while the Russian population preserves a relatively high fraction of tight bindings for both HLA classes. CONCLUSION: We comprehensively reported the changes in the HLA-associated SARS-CoV-2 Spike protein peptide binding profiles among the Taiwanese, the British, and the Russian populations. Further studies are needed to understand the immunological mechanisms and the clinical value of our findings.

Extensive editing of cellular and viral double-stranded RNA structures accounts for innate immunity suppression and the proviral activity of ADAR1p150.

The interferon (IFN)-mediated innate immune response is the first line of defense against viruses. However, an IFN-stimulated gene, the adenosine deaminase acting on RNA 1 (ADAR1), favors the replication of several viruses. ADAR1 binds double-stranded RNA and converts adenosine to inosine by deamination. This form of editing makes duplex RNA unstable, thereby preventing IFN induction. To better understand how ADAR1 works at the cellular level, we generated cell lines that express exclusively either the IFN-inducible, cytoplasmic isoform ADAR1p150, the constitutively expressed nuclear isoform ADAR1p110, or no isoform. By comparing the transcriptome of these cell lines, we identified more than 150 polymerase II transcripts that are extensively edited, and we attributed most editing events to ADAR1p150. Editing is focused on inverted transposable elements, located mainly within introns and untranslated regions, and predicted to form duplex RNA structures. Editing of these elements occurs also in primary human samples, and there is evidence for cross-species evolutionary conservation of editing patterns in primates and, to a lesser extent, in rodents. Whereas ADAR1p150 rarely edits tightly encapsidated standard measles virus (MeV) genomes, it efficiently edits genomes with inverted repeats accidentally generated by a mutant MeV. We also show that immune activation occurs in fully ADAR1-deficient (ADAR1KO) cells, restricting virus growth, and that complementation of these cells with ADAR1p150 rescues virus growth and suppresses innate immunity activation. Finally, by knocking out either protein kinase R (PKR) or mitochondrial antiviral signaling protein (MAVS)-another protein controlling the response to duplex RNA-in ADAR1KO cells, we show that PKR activation elicits a stronger antiviral response. Thus, ADAR1 prevents innate immunity activation by cellular transcripts that include extensive duplex RNA structures. The trade-off is that viruses take advantage of ADAR1 to elude innate immunity control.

Hairpin sequence and structure is associated with features of isomiR biogenesis.

MiRNA isoforms (isomiRs) are single stranded small RNAs originating from the same pri-miRNA hairpin as a result of cleavage by Drosha and Dicer enzymes. Variations at the 5'-end of a miRNA alter the seed region of the molecule, thus affecting the targetome of the miRNA. In this manuscript, we analysed the distribution of miRNA cleavage positions across 31 different cancers using miRNA sequencing data of TCGA project. As a result, we found that the processing positions are not tissue specific and that all miRNAs could be correctly classified as ones exhibiting homogeneous or heterogeneous cleavage at one of the four cleavage sites. In 42% of cases (42 out of 100 miRNAs), we observed imprecise 5'-end Dicer cleavage, while this fraction was only 14% for Drosha (14 out of 99). To the contrary, almost all cleavage sites of 3'-ends (either Drosha or Dicer) were heterogeneous. With the use of only four nucleotides surrounding a 5'-end Dicer cleavage position we built a model which allowed us to distinguish between homogeneous and heterogeneous cleavage with the reliable quality (ROC AUC = 0.68). Finally, we showed the possible applications of the study by the analysis of two 5'-end isoforms originating from the same exogeneous shRNA hairpin. It turned out that the less expressed shRNA variant was functionally active, which led to the increased off-targeting. Thus, the obtained results could be applied to the design of shRNAs whose processing will result in a single 5'-variant.

A Post-Processing Algorithm for miRNA Microarray Data.

One of the main disadvantages of using DNA microarrays for miRNA expression profiling is the inability of adequate comparison of expression values across different miRNAs. This leads to a large amount of miRNAs with high scores which are actually not expressed in examined samples, i.e., false positives. We propose a post-processing algorithm which performs scoring of miRNAs in the results of microarray analysis based on expression values, time of discovery of miRNA, and correlation level between the expressions of miRNA and corresponding pre-miRNA in considered samples. The algorithm was successfully validated by the comparison of the results of its application to miRNA microarray breast tumor samples with publicly available miRNA-seq breast tumor data. Additionally, we obtained possible reasons why miRNA can appear as a false positive in microarray study using paired miRNA sequencing and array data. The use of DNA microarrays for estimating miRNA expression profile is limited by several factors. One of them consists of problems with comparing expression values of different miRNAs. In this work, we show that situation can be significantly improved if some additional information is taken into consideration in a comparison.

Spontaneous metastasis xenograft models link CD44 isoform 4 to angiogenesis, hypoxia, EMT and mitochondria-related pathways in colorectal cancer.

Hematogenous metastasis limits the survival of colorectal cancer (CRC) patients. Here, we illuminated the roles of CD44 isoforms in this process. Isoforms 3 and 4 were predominantly expressed in CRC patients. CD44 isoform 4 indicated poor outcome and correlated with epithelial-mesenchymal transition (EMT) and decreased oxidative phosphorylation (OxPhos) in patients; opposite associations were found for isoform 3. Pan-CD44 knockdown (kd) independently impaired primary tumor formation and abrogated distant metastasis in CRC xenografts. The xenograft tumors mainly expressed the clinically relevant CD44 isoforms 3 and 4. Both isoforms were enhanced in the paranecrotic, hypoxic tumor regions but were generally absent in lung metastases. Upon CD44 kd, tumor angiogenesis was increased in the paranecrotic areas, accompanied by reduced hypoxia-inducible factor-1α and CEACAM5 but increased E-cadherin expression. Mitochondrial genes and proteins were induced upon pan-CD44 kd, as were OxPhos genes. Hypoxia increased VEGF release from tumor spheres, particularly upon CD44 kd. Genes affected upon CD44 kd in xenografts specifically overlapped concordantly with genes correlating with CD44 isoform 4 (but not isoform 3) in patients, validating the clinical relevance of the used model and highlighting the metastasis-promoting role of CD44 isoform 4.

Development of a novel mathematical model that explains SARS-CoV-2 infection dynamics in Caco-2 cells.

Mathematical modeling is widely used to study within-host viral dynamics. However, to the best of our knowledge, for the case of SARS-CoV-2 such analyses were mainly conducted with the use of viral load data and for the wild type (WT) variant of the virus. In addition, only few studies analyzed models for in vitro data, which are less noisy and more reproducible. In this work we collected multiple data types for SARS-CoV-2-infected Caco-2 cell lines, including infectious virus titers, measurements of intracellular viral RNA, cell viability data and percentage of infected cells for the WT and Delta variants. We showed that standard models cannot explain some key observations given the absence of cytopathic effect in human cell lines. We propose a novel mathematical model for in vitro SARS-CoV-2 dynamics, which included explicit modeling of intracellular events such as exhaustion of cellular resources required for virus production. The model also explicitly considers innate immune response. The proposed model accurately explained experimental data. Attenuated replication of the Delta variant in Caco-2 cells could be explained by our model on the basis of just two parameters: decreased cell entry rate and increased cytokine production rate.

Characterization of all small RNAs in and comparisons across cultured megakaryocytes and platelets of healthy individuals and COVID-19 patients.

BACKGROUND: The small noncoding RNAs (sncRNAs) in megakaryocytes (MKs) and platelets are not well characterized. Neither is the impact of SARS-CoV-2 infection on the sncRNAs of platelets. OBJECTIVES: To investigate the sorting of MK sncRNAs into platelets, and the differences in the platelet sncRNAomes of healthy donors (HDs) and COVID-19 patients. METHODS: We comprehensively profiled sncRNAs from MKs cultured from cord blood-derived CD34+ cells, platelets from HDs, and platelets from patients with moderate and severe SARS-CoV-2 infection. We also comprehensively profiled Argonaute (AGO)-bound sncRNAs from the cultured MKs. RESULTS: We characterized the sncRNAs in MKs and platelets and can account for ∼95% of all sequenced reads. We found that MKs primarily comprise microRNA isoforms (isomiRs), tRNA-derived fragments (tRFs), rRNA-derived fragments (rRFs), and Y RNA-derived fragments (yRFs) in comparable abundances. The platelets of HDs showed a skewed distribution by comparison: 56.7% of all sncRNAs are yRFs, 34.4% are isomiRs, and <2.0% are tRFs and rRFs. Most isomiRs in MKs and platelets are either noncanonical, nontemplated, or both. When comparing MKs and platelets from HDs, we found numerous isomiRs, tRFs, rRFs, and yRFs showing opposite enrichments or depletions, including molecules from the same parental miRNA arm, tRNA, rRNA, or Y RNA. The sncRNAome of platelets from patients with COVID-19 is skewed compared to that of HDs with only 19.8% of all sncRNAs now being yRFs, isomiRs increasing to 63.6%, and tRFs and rRFs more than tripling their presence to 6.1%. CONCLUSION: The sncRNAomes of MKs and platelets are very rich and more complex than it has been believed. The evidence suggests complex mechanisms that sort MK sncRNAs into platelets. SARS-CoV-2 infection acutely alters the contents of platelets by changing the relative proportions of their sncRNAs.

HLA-A*01:01 allele diminishing in COVID-19 patients population associated with non-structural epitope abundance in CD8+ T-cell repertoire.

In mid-2021, the SARS-CoV-2 Delta variant caused the third wave of the COVID-19 pandemic in several countries worldwide. The pivotal studies were aimed at studying changes in the efficiency of neutralizing antibodies to the spike protein. However, much less attention was paid to the T-cell response and the presentation of virus peptides by MHC-I molecules. In this study, we compared the features of the HLA-I genotype in symptomatic patients with COVID-19 in the first and third waves of the pandemic. As a result, we could identify the diminishing of carriers of the HLA-A*01:01 allele in the third wave and demonstrate the unique properties of this allele. Thus, HLA-A*01:01-binding immunoprevalent epitopes are mostly derived from ORF1ab. A set of epitopes from ORF1ab was tested, and their high immunogenicity was confirmed. Moreover, analysis of the results of single-cell phenotyping of T-cells in recovered patients showed that the predominant phenotype in HLA-A*01:01 carriers is central memory T-cells. The predominance of T-lymphocytes of this phenotype may contribute to forming long-term T-cell immunity in carriers of this allele. Our results can be the basis for highly effective vaccines based on ORF1ab peptides.

A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer.

A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman's correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)-the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3'-UTRs and coding mRNA sequences, while 5'-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples.

isomiRTar: a comprehensive portal of pan-cancer 5'-isomiR targeting.

Inaccurate cleavage of pri- and pre-miRNA hairpins by Drosha and Dicer results in the generation of miRNA isoforms known as isomiRs. isomiRs with 5'-end variations (5'-isomiRs) create a new dimension in miRNA research since they have different seed regions and distinct targetomes. We developed isomiRTar (https://isomirtar.hse.ru)-a comprehensive portal that allows one to analyze expression profiles and targeting activity of 5'-isomiRs in cancer. Using the Cancer Genome Atlas sequencing data, we compiled the list of 1022 5'-isomiRs expressed in 9282 tumor samples across 31 cancer types. Sequences of these isomiRs were used to predict target genes with miRDB and TargetScan. The putative interactions were then subjected to the co-expression analysis in each cancer type to identify isomiR-target pairs supported by significant negative correlations. Downstream analysis of the data deposited in isomiRTar revealed both cancer-specific and cancer-conserved 5'-isomiR expression landscapes. Pairs of isomiRs differing in one nucleotide shift from 5'-end had poorly overlapping targetomes with the median Jaccard index of 0.06. The analysis of colorectal cancer 5'-isomiR-mediated regulatory networks revealed promising candidate tumor suppressor isomiRs: hsa-miR-203a-3p-+1, hsa-miR-192-5p-+1 and hsa-miR-148a-3p-0. In summary, we believe that isomiRTar will help researchers find novel mechanisms of isomiR-mediated gene silencing in different types of cancer.

ExhauFS: exhaustive search-based feature selection for classification and survival regression.

Feature selection is one of the main techniques used to prevent overfitting in machine learning applications. The most straightforward approach for feature selection is an exhaustive search: one can go over all possible feature combinations and pick up the model with the highest accuracy. This method together with its optimizations were actively used in biomedical research, however, publicly available implementation is missing. We present ExhauFS-the user-friendly command-line implementation of the exhaustive search approach for classification and survival regression. Aside from tool description, we included three application examples in the manuscript to comprehensively review the implemented functionality. First, we executed ExhauFS on a toy cervical cancer dataset to illustrate basic concepts. Then, multi-cohort microarray breast cancer datasets were used to construct gene signatures for 5-year recurrence classification. The vast majority of signatures constructed by ExhauFS passed 0.65 threshold of sensitivity and specificity on all datasets, including the validation one. Moreover, a number of gene signatures demonstrated reliable performance on independent RNA-seq dataset without any coefficient re-tuning, i.e., turned out to be cross-platform. Finally, Cox survival regression models were used to fit isomiR signatures for overall survival prediction for patients with colorectal cancer. Similarly to the previous example, the major part of models passed the pre-defined concordance index threshold 0.65 on all datasets. In both real-world scenarios (breast and colorectal cancer datasets), ExhauFS was benchmarked against state-of-the-art feature selection models, including L1-regularized sparse models. In case of breast cancer, we were unable to construct reliable cross-platform classifiers using alternative feature selection approaches. In case of colorectal cancer not a single model passed the same 0.65 threshold. Source codes and documentation of ExhauFS are available on GitHub: https://github.com/s-a-nersisyan/ExhauFS.

Alterations in SARS-CoV-2 Omicron and Delta peptides presentation by HLA molecules.

The T-cell immune response is a major determinant of effective SARS-CoV-2 clearance. Here, using the recently developed T-CoV bioinformatics pipeline (https://t-cov.hse.ru) we analyzed the peculiarities of the viral peptide presentation for the Omicron, Delta and Wuhan variants of SARS-CoV-2. First, we showed the absence of significant differences in the presentation of SARS-CoV-2-derived peptides by the most frequent HLA class I/II alleles and the corresponding HLA haplotypes. Then, the analysis was limited to the set of peptides originating from the Spike proteins of the considered SARS-CoV-2 variants. The major finding was the destructive effect of the Omicron mutations on PINLVRDLPQGFSAL peptide, which was the only tight binder from the Spike protein for HLA-DRB1*03:01 allele and some associated haplotypes. Specifically, we predicted a dramatical decline in binding affinity of HLA-DRB1*03:01 and this peptide both because of the Omicron BA.1 mutations (N211 deletion, L212I substitution and EPE 212-214 insertion) and the Omicron BA.2 mutations (V213G substitution). The computational prediction was experimentally validated by ELISA with the use of corresponding thioredoxin-fused peptides and recombinant HLA-DR molecules. Another finding was the significant reduction in the number of tightly binding Spike peptides for HLA-B*07:02 HLA class I allele (both for Omicron and Delta variants). Overall, the majority of HLA alleles and haplotypes was not significantly affected by the mutations, suggesting the maintenance of effective T-cell immunity against the Omicron and Delta variants. Finally, we introduced the Omicron variant to T-CoV portal and added the functionality of haplotype-level analysis to it.

Fra-2 overexpression upregulates pro-metastatic cell-adhesion molecules, promotes pulmonary metastasis, and reduces survival in a spontaneous xenograft model of human breast cancer.

PURPOSE: The transcription factor Fra-2 affects the invasive potential of breast cancer cells by dysregulating adhesion molecules in vitro. Previous results suggested that it upregulates the expression of E- and P-selectin ligands. Such selectin ligands are important members of the leukocyte adhesion cascade, which govern the adhesion and transmigration of cancer cells into the stroma of the host organ of metastasis. As so far, no in vivo data are available, this study was designed to elucidate the role of Fra-2 expression in a spontaneous breast cancer metastasis xenograft model. METHODS: The effect of Fra-2 overexpression in two stable Fra-2 overexpressing clones of the human breast cancer cell line MDA MB231 on survival and metastatic load was studied after subcutaneous injection into scid and E- and P-selectin-deficient scid mice. RESULTS: Fra-2 overexpression leads to a significantly shorter overall survival and a higher amount of spontaneous lung metastases not only in scid mice, but also in E- and P-deficient mice, indicating that it regulates not only selectin ligands, but also selectin-independent adhesion processes. CONCLUSION: Thus, Fra-2 expression influences the metastatic potential of breast cancer cells by changing the expression of adhesion molecules, resulting in increased adherence to endothelial cells in a breast cancer xenograft model.

Low expression of CD24 is associated with poor survival in colorectal cancer.

In this study we analyzed expression of CD24 in a cohort of colorectal cancer patients using immunohistochemistry staining of CD24. We found a significant association between absence or low expression of CD24 (10% of membranous and 55% of cytoplasmic staining) and shortened patient survival. Protein localization played a crucial role in the prognosis: membranous form was the major and prognostic one in primary tumors, while cytoplasmic expression was elevated in liver metastases compared to the primary tumors and contained prognostic information. Then, using The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) RNA-seq data, we showed that CD24 mRNA level was two-fold decreased in primary colorectal cancers compared to adjacent normal mucosa. Like the protein staining data, ten percent of patients with the lowest mRNA expression levels of CD24 in primary tumors had reduced survival compared to the ones with higher expression. To explain these findings mechanistically, shRNA-mediated CD24 knockdown was performed in HT-29 colorectal cancer cells. It resulted in the increase of cell migration in vitro, no changes in proliferation and apoptosis, and a slight decrease in cell invasion. As increased cell migration is a hallmark of metastasis formation, this finding corroborates the association of a decreased CD24 expression with poor prognosis. Differential gene expression analysis revealed upregulation of genes involved in cell migration in the group of patients with low CD24 expression, including integrin subunit α3 and α3, ß3 subunits of laminin 332. Further co-expression analysis identified SPI1, STAT1 and IRF1 transcription factors as putative master-regulators in this group.

Immunogenic epitope panel for accurate detection of non-cross-reactive T cell response to SARS-CoV-2.

The ongoing COVID-19 pandemic calls for more effective diagnostic tools. T cell response assessment serves as an independent indicator of prior COVID-19 exposure while also contributing to a more comprehensive characterization of SARS-CoV-2 immunity. In this study, we systematically assessed the immunogenicity of 118 epitopes with immune cells collected from multiple cohorts of vaccinated, convalescent, healthy unexposed, and SARS-CoV-2-exposed donors. We identified 75 immunogenic epitopes, 24 of which were immunodominant. We further confirmed HLA restriction for 49 epitopes and described association with more than 1 HLA allele for 14 of these. Exclusion of 2 cross-reactive epitopes that generated a response in prepandemic samples left us with a 73-epitope set that offered excellent diagnostic specificity without losing sensitivity compared with full-length antigens, and this evoked a robust cross-reactive response. We subsequently incorporated this set of epitopes into an in vitro diagnostic Corona-T-test, which achieved a diagnostic accuracy of 95% in a clinical trial. In a cohort of asymptomatic seronegative individuals with a history of prolonged SARS-CoV-2 exposure, we observed a complete absence of T cell response to our epitope panel. In combination with strong reactivity to full-length antigens, this suggests that a cross-reactive response might protect these individuals.

Endocytosis and Transcytosis of SARS-CoV-2 Across the Intestinal Epithelium and Other Tissue Barriers.

Since 2003, the world has been confronted with three new betacoronaviruses that cause human respiratory infections: SARS-CoV, which causes severe acute respiratory syndrome (SARS), MERS-CoV, which causes Middle East respiratory syndrome (MERS), and SARS-CoV-2, which causes Coronavirus Disease 2019 (COVID-19). The mechanisms of coronavirus transmission and dissemination in the human body determine the diagnostic and therapeutic strategies. An important problem is the possibility that viral particles overcome tissue barriers such as the intestine, respiratory tract, blood-brain barrier, and placenta. In this work, we will 1) consider the issue of endocytosis and the possibility of transcytosis and paracellular trafficking of coronaviruses across tissue barriers with an emphasis on the intestinal epithelium; 2) discuss the possibility of antibody-mediated transcytosis of opsonized viruses due to complexes of immunoglobulins with their receptors; 3) assess the possibility of the virus transfer into extracellular vesicles during intracellular transport; and 4) describe the clinical significance of these processes. Models of the intestinal epithelium and other barrier tissues for in vitro transcytosis studies will also be briefly characterized.

Hypoxia-Induced miR-148a Downregulation Contributes to Poor Survival in Colorectal Cancer.

Hypoxia is an extensively investigated condition due to its contribution to various pathophysiological processes including cancer progression and metastasis formation. MicroRNAs (miRNAs) are well-known post-transcriptional gene expression regulators. However, their contribution to molecular response to hypoxia is highly dependent on cell/tissue types and causes of hypoxia. One of the most important examples is colorectal cancer, where no consensus on hypoxia-regulated miRNAs has been reached so far. In this work, we applied integrated mRNA and small RNA sequencing, followed by bioinformatics analysis, to study the landscape of hypoxia-induced miRNA and mRNA expression alterations in human colorectal cancer cell lines (HT-29 and Caco-2). A hypoxic microenvironment was chemically modeled using two different treatments: cobalt(II) chloride and oxyquinoline. Only one miRNA, hsa-miR-210-3p, was upregulated in all experimental conditions, while there were nine differentially expressed miRNAs under both treatments within the same cell line. Further bioinformatics analysis revealed a complex hypoxia-induced regulatory network: hypoxic downregulation of hsa-miR-148a-3p led to the upregulation of its two target genes, ITGA5 and PRNP, which was shown to be a factor contributing to tumor progression and poor survival in colorectal cancer patients.