The challenges of the genome-based identification of antifungal resistance in the clinical routine.

The increasing number of chronic and life-threatening infections caused by antimicrobial resistant fungal isolates is of critical concern. Low DNA sequencing cost may facilitate the identification of the genomic profile leading to resistance, the resistome, to rationally optimize the design of antifungal therapies. However, compared to bacteria, initiatives for resistome detection in eukaryotic pathogens are underdeveloped. Firstly, reported mutations in antifungal targets leading to reduced susceptibility must be extensively collected from the literature to generate comprehensive databases. This information should be complemented with specific laboratory screenings to detect the highest number possible of relevant genetic changes in primary targets and associations between resistance and other genomic markers. Strikingly, some drug resistant strains experience high-level genetic changes such as ploidy variation as much as duplications and reorganizations of specific chromosomes. Such variations involve allelic dominance, gene dosage increments and target expression regime effects that should be explicitly parameterized in antifungal resistome prediction algorithms. Clinical data indicate that predictors need to consider the precise pathogen species and drug levels of detail, instead of just genus and drug class. The concomitant needs for mutation accuracy and assembly quality assurance suggest hybrid sequencing approaches involving third-generation methods will be utilized. Moreover, fatal fast infections, like fungemia and meningitis, will further require both sequencing and analysis facilities are available in-house. Altogether, the complex nature of antifungal resistance demands extensive sequencing, data acquisition and processing, bioinformatic analysis pipelines, and standard protocols to be accomplished prior to genome-based protocols are applied in the clinical setting.

Association between HLA-C alleles and COVID-19 severity in a pilot study with a Spanish Mediterranean Caucasian cohort.

The clinical presentations of COVID-19 may range from an asymptomatic or mild infection to a critical or fatal disease. Several host factors such as elderly age, male gender, and previous comorbidities seem to be involved in the most severe outcomes, but also an impaired immune response that causes a hyperinflammatory state but is unable to clear the infection. In order to get further understanding about this impaired immune response, we aimed to determine the association of specific HLA alleles with different clinical presentations of COVID-19. Therefore, we analyzed HLA Class I and II, as well as KIR gene sequences, in 72 individuals with Spanish Mediterranean Caucasian ethnicity who presented mild, severe, or critical COVID-19, according to their clinical characteristics and management. This cohort was recruited in Madrid (Spain) during the first and second pandemic waves between April and October 2020. There were no significant differences in HLA-A or HLA-B alleles among groups. However, despite the small sample size, we found that HLA-C alleles from group C1 HLA-C*08:02, -C*12:03, or -C*16:01 were more frequently associated in individuals with mild COVID-19 (43.8%) than in individuals with severe (8.3%; p = 0.0030; pc = 0.033) and critical (16.1%; p = 0.0014; pc = 0.0154) disease. C1 alleles are supposed to be highly efficient to present peptides to T cells, and HLA-C*12:03 may present a high number of verified epitopes from abundant SARS-CoV-2 proteins M, N, and S, thereby being allegedly able to trigger an efficient antiviral response. On the contrary, C2 alleles are usually poorly expressed on the cell surface due to low association with ß2-microglobulin (ß2M) and peptides, which may impede the adequate formation of stable HLA-C/ß2M/peptide heterotrimers. Consequently, this pilot study described significant differences in the presence of specific HLA-C1 alleles in individuals with different clinical presentations of COVID-19, thereby suggesting that HLA haplotyping could be valuable to get further understanding in the underlying mechanisms of the impaired immune response during critical COVID-19.

Predicted impact of the viral mutational landscape on the cytotoxic response against SARS-CoV-2.

The massive assessment of immune evasion due to viral mutations that increase COVID-19 susceptibility can be computationally facilitated. The adaptive cytotoxic T response is critical during primary infection and the generation of long-term protection. Here, potential HLA class I epitopes in the SARS-CoV-2 proteome were predicted for 2,915 human alleles of 71 families using the netMHCIpan EL algorithm. Allele families showed extreme epitopic differences, underscoring genetic variability of protective capacity between humans. Up to 1,222 epitopes were associated with any of the twelve supertypes, that is, allele clusters covering 90% population. Next, from all mutations identified in ~118,000 viral NCBI isolates, those causing significant epitope score reduction were considered epitope escape mutations. These mutations mainly involved non-conservative substitutions at the second and C-terminal position of the ligand core, or total ligand removal by large recurrent deletions. Escape mutations affected 47% of supertype epitopes, which in 21% of cases concerned isolates from two or more sub-continental areas. Some of these changes were coupled, but never surpassed 15% of evaded epitopes for the same supertype in the same isolate, except for B27. In contrast to most supertypes, eight allele families mostly contained alleles with few SARS-CoV-2 ligands. Isolates harboring cytotoxic escape mutations for these families co-existed geographically within sub-Saharan and Asian populations enriched in these alleles according to the Allele Frequency Net Database. Collectively, our findings indicate that escape mutation events have already occurred for half of HLA class I supertype epitopes. However, it is presently unlikely that, overall, it poses a threat to the global population. In contrast, single and double mutations for susceptible alleles may be associated with viral selective pressure and alarming local outbreaks. The integration of genomic, geographical and immunoinformatic information eases the surveillance of variants potentially affecting the global population, as well as minority subpopulations.

Cross-Recognition of SARS-CoV-2 B-Cell Epitopes with Other Betacoronavirus Nucleoproteins.

The B and T lymphocytes of the adaptive immune system are important for the control of most viral infections, including COVID-19. Identification of epitopes recognized by these cells is fundamental for understanding how the immune system detects and removes pathogens, and for antiviral vaccine design. Intriguingly, several cross-reactive T lymphocyte epitopes from SARS-CoV-2 with other betacoronaviruses responsible for the common cold have been identified. In addition, antibodies that cross-recognize the spike protein, but not the nucleoprotein (N protein), from different betacoronavirus have also been reported. Using a consensus of eight bioinformatic methods for predicting B-cell epitopes and the collection of experimentally detected epitopes for SARS-CoV and SARS-CoV-2, we identified four surface-exposed, conserved, and hypothetical antigenic regions that are exclusive of the N protein. These regions were analyzed using ELISA assays with two cohorts: SARS-CoV-2 infected patients and pre-COVID-19 samples. Here we describe four epitopes from SARS-CoV-2 N protein that are recognized by the humoral response from multiple individuals infected with COVID-19, and are conserved in other human coronaviruses. Three of these linear surface-exposed sequences and their peptide homologs in SARS-CoV-2 and HCoV-OC43 were also recognized by antibodies from pre-COVID-19 serum samples, indicating cross-reactivity of antibodies against coronavirus N proteins. Different conserved human coronaviruses (HCoVs) cross-reactive B epitopes against SARS-CoV-2 N protein are detected in a significant fraction of individuals not exposed to this pandemic virus. These results have potential clinical implications.

Predicted Epitope Abundance Supports Vaccine-Induced Cytotoxic Protection Against SARS-CoV-2 Variants of Concern

The effect of emerging SARS-CoV-2 variants on vaccine efficacy is of critical importance. In this study, the potential impact of mutations that facilitate escape from the cytotoxic cellular immune response in these new virus variants for the 551 most abundant HLA class I alleles was analyzed. Computational prediction showed that most of these alleles, that cover >90% of the population, contain enough epitopes without escape mutations in the principal SARS-CoV-2 variants. These data suggest that the cytotoxic cellular immune protection elicited by vaccination is not greatly affected by emerging SARS-CoV-2 variants.

Identification and Analysis of Unstructured, Linear B-Cell Epitopes in SARS-CoV-2 Virion Proteins for Vaccine Development.

The efficacy of SARS-CoV-2 nucleic acid-based vaccines may be limited by proteolysis of the translated product due to anomalous protein folding. This may be the case for vaccines employing linear SARS-CoV-2 B-cell epitopes identified in previous studies since most of them participate in secondary structure formation. In contrast, we have employed a consensus of predictors for epitopic zones plus a structural filter for identifying 20 unstructured B-cell epitope-containing loops (uBCELs) in S, M, and N proteins. Phylogenetic comparison suggests epitope switching with respect to SARS-CoV in some of the identified uBCELs. Such events may be associated with the reported lack of serum cross-protection between the 2003 and 2019 pandemic strains. Incipient variability within a sample of 1639 SARS-CoV-2 isolates was also detected for 10 uBCELs which could cause vaccine failure. Intermediate stages of the putative epitope switch events were observed in bat coronaviruses in which additive mutational processes possibly facilitating evasion of the bat immune system appear to have taken place prior to transfer to humans. While there was some overlap between uBCELs and previously validated SARS-CoV B-cell epitopes, multiple uBCELs had not been identified in prior studies. Overall, these uBCELs may facilitate the development of biomedical products for SARS-CoV-2.