T cell reactivity to the SARS-CoV-2 Omicron variant is preserved in most but not all individuals.

The SARS-CoV-2 Omicron variant (B.1.1.529) contains mutations that mediate escape from antibody responses, although the extent to which these substitutions in spike and non-spike proteins affect T cell recognition is unknown. In this study, we show that T cell responses in individuals with prior infection, vaccination, both prior infection and vaccination, and boosted vaccination are largely preserved to Omicron spike and non-spike proteins. However, we also identify a subset of individuals (∼21%) with a >50% reduction in T cell reactivity to the Omicron spike. Evaluation of functional CD4+ and CD8+ memory T cell responses confirmed these findings and revealed that reduced recognition to Omicron spike is primarily observed within the CD8+ T cell compartment potentially due to escape from HLA binding. Booster vaccination enhanced T cell responses to Omicron spike. In contrast to neutralizing immunity, these findings suggest preservation of T cell responses to the Omicron variant, although with reduced reactivity in some individuals.

Structure-guided T cell vaccine design for SARS-CoV-2 variants and sarbecoviruses.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that escape convalescent and vaccine-induced antibody responses has renewed focus on the development of broadly protective T-cell-based vaccines. Here, we apply structure-based network analysis and assessments of HLA class I peptide stability to define mutationally constrained CD8+ T cell epitopes across the SARS-CoV-2 proteome. Highly networked residues are conserved temporally among circulating variants and sarbecoviruses and disproportionately impair spike pseudotyped lentivirus infectivity when mutated. Evaluation of HLA class I stabilizing activity for 18 globally prevalent alleles identifies CD8+ T cell epitopes within highly networked regions with limited mutational frequencies in circulating SARS-CoV-2 variants and deep-sequenced primary isolates. Moreover, these epitopes elicit demonstrable CD8+ T cell reactivity in convalescent individuals but reduced recognition in recipients of mRNA-based vaccines. These data thereby elucidate key mutationally constrained regions and immunogenic epitopes in the SARS-CoV-2 proteome for a global T-cell-based vaccine against emerging variants and SARS-like coronaviruses.

Structure-based network analysis predicts pathogenic variants in human proteins associated with inherited retinal disease.

Advances in gene sequencing technologies have accelerated the identification of genetic variants, but better tools are needed to understand which are causal of disease. This would be particularly useful in fields where gene therapy is a potential therapeutic modality for a disease-causing variant such as inherited retinal disease (IRD). Here, we apply structure-based network analysis (SBNA), which has been successfully utilized to identify variant-constrained amino acid residues in viral proteins, to identify residues that may cause IRD if subject to missense mutation. SBNA is based entirely on structural first principles and is not fit to specific outcome data, which makes it distinct from other contemporary missense prediction tools. In 4 well-studied human disease-associated proteins (BRCA1, HRAS, PTEN, and ERK2) with high-quality structural data, we find that SBNA scores correlate strongly with deep mutagenesis data. When applied to 47 IRD genes with available high-quality crystal structure data, SBNA scores reliably identified disease-causing variants according to phenotype definitions from the ClinVar database. Finally, we applied this approach to 63 patients at Massachusetts Eye and Ear (MEE) with IRD but for whom no genetic cause had been identified. Untrained models built using SBNA scores and BLOSUM62 scores for IRD-associated genes successfully predicted the pathogenicity of novel variants (AUC = 0.851), allowing us to identify likely causative disease variants in 40 IRD patients. Model performance was further augmented by incorporating orthogonal data from EVE scores (AUC = 0.927), which are based on evolutionary multiple sequence alignments. In conclusion, SBNA can used to successfully identify variants as causal of disease in human proteins and may help predict variants causative of IRD in an unbiased fashion.

Identification of mouse CD4+ T cell epitopes in SARS-CoV-2 BA.1 spike and nucleocapsid for use in peptide:MHCII tetramers.

Understanding adaptive immunity against SARS-CoV-2 is a major requisite for the development of effective vaccines and treatments for COVID-19. CD4+ T cells play an integral role in this process primarily by generating antiviral cytokines and providing help to antibody-producing B cells. To empower detailed studies of SARS-CoV-2-specific CD4+ T cell responses in mouse models, we comprehensively mapped I-Ab-restricted epitopes for the spike and nucleocapsid proteins of the BA.1 variant of concern via IFNγ ELISpot assay. This was followed by the generation of corresponding peptide:MHCII tetramer reagents to directly stain epitope-specific T cells. Using this rigorous validation strategy, we identified 6 immunogenic epitopes in spike and 3 in nucleocapsid, all of which are conserved in the ancestral Wuhan strain. We also validated a previously identified epitope from Wuhan that is absent in BA.1. These epitopes and tetramers will be invaluable tools for SARS-CoV-2 antigen-specific CD4+ T cell studies in mice.

SARS-CoV-2 viral clearance and evolution varies by type and severity of immunodeficiency.

Despite vaccination and antiviral therapies, immunocompromised individuals are at risk for prolonged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but the immune defects that predispose an individual to persistent coronavirus disease 2019 (COVID-19) remain incompletely understood. In this study, we performed detailed viro-immunologic analyses of a prospective cohort of participants with COVID-19. The median times to nasal viral RNA and culture clearance in individuals with severe immunosuppression due to hematologic malignancy or transplant (S-HT) were 72 and 40 days, respectively, both of which were significantly longer than clearance rates in individuals with severe immunosuppression due to autoimmunity or B cell deficiency (S-A), individuals with nonsevere immunodeficiency, and nonimmunocompromised groups (P < 0.01). Participants who were severely immunocompromised had greater SARS-CoV-2 evolution and a higher risk of developing resistance against therapeutic monoclonal antibodies. Both S-HT and S-A participants had diminished SARS-CoV-2-specific humoral responses, whereas only the S-HT group had reduced T cell-mediated responses. This highlights the varied risk of persistent COVID-19 across distinct immunosuppressive conditions and suggests that suppression of both B and T cell responses results in the highest contributing risk of persistent infection.

Structure-based network analysis predicts mutations associated with inherited retinal disease.

With continued advances in gene sequencing technologies comes the need to develop better tools to understand which mutations cause disease. Here we validate structure-based network analysis (SBNA)1,2 in well-studied human proteins and report results of using SBNA to identify critical amino acids that may cause retinal disease if subject to missense mutation. We computed SBNA scores for genes with high-quality structural data, starting with validating the method using 4 well-studied human disease-associated proteins. We then analyzed 47 inherited retinal disease (IRD) genes. We compared SBNA scores to phenotype data from the ClinVar database and found a significant difference between benign and pathogenic mutations with respect to network score. Finally, we applied this approach to 65 patients at Massachusetts Eye and Ear (MEE) who were diagnosed with IRD but for whom no genetic cause was found. Multivariable logistic regression models built using SBNA scores for IRD-associated genes successfully predicted pathogenicity of novel mutations, allowing us to identify likely causative disease variants in 37 patients with IRD from our clinic. In conclusion, SBNA can be meaningfully applied to human proteins and may help predict mutations causative of IRD.

Identification of mouse CD4+ T cell epitopes in SARS-CoV-2 BA.1 spike and nucleocapsid for use in peptide:MHCII tetramers.

Understanding adaptive immunity against SARS-CoV-2 is a major requisite for the development of effective vaccines and treatments for COVID-19. CD4+ T cells play an integral role in this process primarily by generating antiviral cytokines and providing help to antibody-producing B cells. To empower detailed studies of SARS-CoV-2-specific CD4+ T cell responses in mouse models, we comprehensively mapped I-Ab-restricted epitopes for the spike and nucleocapsid proteins of the BA.1 variant of concern via IFNγ ELISpot assay. This was followed by the generation of corresponding peptide:MHCII tetramer reagents to directly stain epitope-specific T cells. Using this rigorous validation strategy, we identified 6 reliably immunogenic epitopes in spike and 3 in nucleocapsid, all of which are conserved in the ancestral Wuhan strain. We also validated a previously identified epitope from Wuhan that is absent in BA.1. These epitopes and tetramers will be invaluable tools for SARS-CoV-2 antigen-specific CD4+ T cell studies in mice.

T cell responses to SARS-CoV-2 infection and vaccination are elevated in B cell deficiency and reduce risk of severe COVID-19.

Individuals with primary and pharmacologic B cell deficiencies have high rates of severe disease and mortality from coronavirus disease 2019 (COVID-19), but the immune responses and clinical outcomes after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination have yet to be fully defined. Here, we evaluate the cellular immune responses after both SARS-CoV-2 infection and vaccination in patients receiving the anti-CD20 therapy rituximab (RTX) and those with low B cell counts due to common variable immune deficiency (CVID) disease. Assessment of effector and memory CD4+ and CD8+ T cell responses to SARS-CoV-2 revealed elevated reactivity and proliferative capacity after both infection and vaccination in B cell-deficient individuals, particularly within the CD8+ T cell compartment, in comparison with healthy controls. Evaluation of clinical outcomes demonstrates that vaccination of RTX-treated individuals was associated with about 4.8-fold reduced odds of moderate or severe COVID-19 in the absence of vaccine-induced antibodies. Analysis of T cell differentiation demonstrates that RTX administration increases the relative frequency of naïve CD8+ T cells, potentially by depletion of CD8+CD20dim T cells, which are primarily of an effector memory or terminal effector memory (TEMRA) phenotype. However, this also leads to a reduction in preexisting antiviral T cell immunity. Collectively, these data indicate that individuals with B cell deficiencies have enhanced T cell immunity after both SARS-CoV-2 infection and vaccination that potentially accounts for reduced hospitalization and severe disease from subsequent SARS-CoV-2 infection.

SARS-CoV-2 Viral Clearance and Evolution Varies by Extent of Immunodeficiency.

Despite vaccination and antiviral therapies, immunocompromised individuals are at risk for prolonged SARS-CoV-2 infection, but the immune defects that predispose to persistent COVID-19 remain incompletely understood. In this study, we performed detailed viro-immunologic analyses of a prospective cohort of participants with COVID-19. The median time to nasal viral RNA and culture clearance in the severe hematologic malignancy/transplant group (S-HT) were 72 and 40 days, respectively, which were significantly longer than clearance rates in the severe autoimmune/B-cell deficient (S-A), non-severe, and non-immunocompromised groups (P<0.001). Participants who were severely immunocompromised had greater SARS-CoV-2 evolution and a higher risk of developing antiviral treatment resistance. Both S-HT and S-A participants had diminished SARS-CoV-2-specific humoral, while only the S-HT group had reduced T cell-mediated responses. This highlights the varied risk of persistent COVID-19 across immunosuppressive conditions and suggests that suppression of both B and T cell responses results in the highest contributing risk of persistent infection.

T cell reactivity to the SARS-CoV-2 Omicron variant is preserved in most but not all prior infected and vaccinated individuals.

The SARS-CoV-2 Omicron variant (B.1.1.529) contains mutations that mediate escape from infection and vaccine-induced antibody responses, although the extent to which these substitutions in spike and non-spike proteins affect T cell recognition is unknown. Here we show that T cell responses in individuals with prior infection, vaccination, both prior infection and vaccination, and boosted vaccination are largely preserved to Omicron spike and non-spike proteins. However, we also identify a subset of individuals (∻21%) with a >50% reduction in T cell reactivity to the Omicron spike. Evaluation of functional CD4 + and CD8 + memory T cell responses confirmed these findings and reveal that reduced recognition to Omicron spike is primarily observed within the CD8 + T cell compartment. Booster vaccination substantially enhanced T cell responses to Omicron spike. In contrast to neutralizing immunity, these findings suggest preservation of T cell responses to the Omicron variant, although with reduced reactivity in some individuals.

Dynamic Phenotypic Switching and Group Behavior Help Non-Small Cell Lung Cancer Cells Evade Chemotherapy.

Drug resistance, a major challenge in cancer therapy, is typically attributed to mutations and genetic heterogeneity. Emerging evidence suggests that dynamic cellular interactions and group behavior also contribute to drug resistance. However, the underlying mechanisms remain poorly understood. Here, we present a new mathematical approach with game theoretical underpinnings that we developed to model real-time growth data of non-small cell lung cancer (NSCLC) cells and discern patterns in response to treatment with cisplatin. We show that the cisplatin-sensitive and cisplatin-tolerant NSCLC cells, when co-cultured in the absence or presence of the drug, display dynamic group behavior strategies. Tolerant cells exhibit a 'persister-like' behavior and are attenuated by sensitive cells; they also appear to 'educate' sensitive cells to evade chemotherapy. Further, tolerant cells can switch phenotypes to become sensitive, especially at low cisplatin concentrations. Finally, switching treatment from continuous to an intermittent regimen can attenuate the emergence of tolerant cells, suggesting that intermittent chemotherapy may improve outcomes in lung cancer.

HLA class-I-peptide stability mediates CD8+ T cell immunodominance hierarchies and facilitates HLA-associated immune control of HIV.

Defining factors that govern CD8+ T cell immunodominance is critical for the rational design of vaccines for viral pathogens. Here, we assess the contribution of human leukocyte antigen (HLA) class-I-peptide stability for 186 optimal HIV epitopes across 18 HLA alleles using transporter associated with antigen processing (TAP)-deficient mono-allelic HLA-expressing cell lines. We find that immunodominant HIV epitopes increase surface stabilization of HLA class-I molecules in comparison to subdominant epitopes. HLA class-I-peptide stability is also strongly correlated with overall immunodominance hierarchies, particularly for epitopes from high-abundance proteins (e.g., Gag). Moreover, HLA alleles associated with HIV protection are preferentially stabilized by epitopes derived from topologically important viral regions at a greater frequency than neutral and risk alleles. These findings indicate that relative stabilization of HLA class-I is a key factor for CD8+ T cell epitope immunodominance hierarchies, with implications for HIV control and the design of T-cell-based vaccines.

Erratum: A Non-genetic Mechanism Involving the Integrin ß4/Paxillin Axis Contributes to Chemoresistance in Lung Cancer.

[This corrects the article DOI: 10.1016/j.isci.2020.101496.].

A Non-genetic Mechanism Involving the Integrin ß4/Paxillin Axis Contributes to Chemoresistance in Lung Cancer.

Tumor heterogeneity and cisplatin resistance are major causes of tumor relapse and poor survival. Here, we show that in lung cancer, interaction between paxillin (PXN) and integrin ß4 (ITGB4), components of the focal adhesion (FA) complex, contributes to cisplatin resistance. Knocking down PXN and ITGB4 attenuated cell growth and improved cisplatin sensitivity, both in 2D and 3D cultures. PXN and ITGB4 independently regulated expression of several genes. In addition, they also regulated expression of common genes including USP1 and VDAC1, which are required for maintaining genomic stability and mitochondrial function, respectively. Mathematical modeling suggested that bistability could lead to stochastic phenotypic switching between cisplatin-sensitive and resistant states in these cells. Consistently, purified subpopulations of sensitive and resistant cells re-created the mixed parental population when cultured separately. Altogether, these data point to an unexpected role of the FA complex in cisplatin resistance and highlight a novel non-genetic mechanism.

Monitoring and Determining Mitochondrial Network Parameters in Live Lung Cancer Cells.

Mitochondria are dynamic organelles that constantly fuse and divide, forming dynamic tubular networks. Abnormalities in mitochondrial dynamics and morphology are linked to diverse pathological states, including cancer. Thus, alterations in mitochondrial parameters could indicate early events of disease manifestation or progression. However, finding reliable and quantitative tools for monitoring mitochondria and determining the network parameters, particularly in live cells, has proven challenging. Here, we present a 2D confocal imaging-based approach that combines automatic mitochondrial morphology and dynamics analysis with fractal analysis in live small cell lung cancer (SCLC) cells. We chose SCLC cells as a test case since they typically have very little cytoplasm, but an abundance of smaller mitochondria compared to many of the commonly used cell types. The 2D confocal images provide a robust approach to quantitatively measure mitochondrial dynamics and morphology in live cells. Furthermore, we performed 3D reconstruction of electron microscopic images and show that the 3D reconstruction of the electron microscopic images complements this approach to yield better resolution. The data also suggest that the parameters of mitochondrial dynamics and fractal dimensions are sensitive indicators of cellular response to subtle perturbations, and hence, may serve as potential markers of drug response in lung cancer.

Phenotypic Switching of Naïve T Cells to Immune-Suppressive Treg-Like Cells by Mutant KRAS.

Oncogenic (mutant) Ras protein Kirsten rat sarcoma viral oncogene homolog (KRAS) promotes uncontrolled proliferation, altered metabolism, and loss of genome integrity in a cell-intrinsic manner. Here, we demonstrate that CD4+ T cells when incubated with tumor-derived exosomes from mutant (MT) KRAS non-small-cell lung cancer (NSCLC) cells, patient sera, or a mouse xenograft model, induce phenotypic conversion to FOXP3+ Treg-like cells that are immune-suppressive. Furthermore, transfecting T cells with MT KRAS cDNA alone induced phenotypic switching and mathematical modeling supported this conclusion. Single-cell sequencing identified the interferon pathway as the mechanism underlying the phenotypic switch. These observations highlight a novel cytokine-independent, cell-extrinsic role for KRAS in T cell phenotypic switching. Thus, targeting this new class of Tregs represents a unique therapeutic approach for NSCLC. Since KRAS is the most frequently mutated oncogene in a wide variety of cancers, the findings of this investigation are likely to be of broad interest and have a large scientific impact.