Evasion of NKG2D-mediated cytotoxic immunity by sarbecoviruses.

SARS-CoV-2 and other sarbecoviruses continue to threaten humanity, highlighting the need to characterize common mechanisms of viral immune evasion for pandemic preparedness. Cytotoxic lymphocytes are vital for antiviral immunity and express NKG2D, an activating receptor conserved among mammals that recognizes infection-induced stress ligands (e.g., MIC-A/B). We found that SARS-CoV-2 evades NKG2D recognition by surface downregulation of MIC-A/B via shedding, observed in human lung tissue and COVID-19 patient serum. Systematic testing of SARS-CoV-2 proteins revealed that ORF6, an accessory protein uniquely conserved among sarbecoviruses, was responsible for MIC-A/B downregulation via shedding. Further investigation demonstrated that natural killer (NK) cells efficiently killed SARS-CoV-2-infected cells and limited viral spread. However, inhibition of MIC-A/B shedding with a monoclonal antibody, 7C6, further enhanced NK-cell activity toward SARS-CoV-2-infected cells. Our findings unveil a strategy employed by SARS-CoV-2 to evade cytotoxic immunity, identify the culprit immunevasin shared among sarbecoviruses, and suggest a potential novel antiviral immunotherapy.

SnapShot: COVID-19.

Coronavirus disease 2019 (COVID-19) is a novel respiratory illness caused by SARS-CoV-2. Viral entry is mediated through viral spike protein and host ACE2 enzyme interaction. Most cases are mild; severe disease often involves cytokine storm and organ failure. Therapeutics including antivirals, immunomodulators, and vaccines are in development. To view this SnapShot, open or download the PDF.

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy.

Tuberculosis (TB) is the world's deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen's antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

Pathogenesis of Post-Tuberculosis Lung Disease: Defining Knowledge Gaps and Research Priorities at the 2nd International Post-Tuberculosis Symposium.

Post-tuberculosis (TB) lung disease (PTLD) is increasingly recognized as a major contributor to the global burden of chronic lung disease, with recent estimates indicating that over half of TB survivors have impaired lung function after successful completion of TB treatment. However, the pathologic mechanisms that contribute to PTLD are not well understood, thus limiting the development of therapeutic interventions to improve long-term outcomes after TB. This report summarizes the work of the "Pathogenesis and Risk Factors Committee" for the Second International Post-Tuberculosis Symposium, which took place in Stellenbosch, South Africa in April 2023. The committee first identified six areas with high translational potential: (1) tissue matrix destruction, including the role of matrix metalloproteinase dysregulation and neutrophil activity, (2) fibroblasts and profibrotic activity, (3) granuloma fate and cell death pathways, (4) mycobacterial factors including pathogen burden, (5) animal models, and (6) the impact of key clinical risk factors including HIV, diabetes, smoking, malnutrition, and alcohol. We share here the key findings from a literature review of those areas, highlighting knowledge gaps and areas where further research is needed.

SARS-CoV-2 Virologic Rebound With Nirmatrelvir-Ritonavir Therapy : An Observational Study.

BACKGROUND: Data are conflicting regarding an association between treatment of acute COVID-19 with nirmatrelvir-ritonavir (N-R) and virologic rebound (VR). OBJECTIVE: To compare the frequency of VR in patients with and without N-R treatment for acute COVID-19. DESIGN: Observational cohort study. SETTING: Multicenter health care system in Boston, Massachusetts. PARTICIPANTS: Ambulatory adults with acute COVID-19 with and without use of N-R. INTERVENTION: Receipt of 5 days of N-R treatment versus no COVID-19 therapy. MEASUREMENTS: The primary outcome was VR, defined as either a positive SARS-CoV-2 viral culture result after a prior negative result or 2 consecutive viral loads above 4.0 log10 copies/mL that were also at least 1.0 log10 copies/mL higher than a prior viral load below 4.0 log10 copies/mL. RESULTS: Compared with untreated persons (n = 55), those taking N-R (n = 72) were older, received more COVID-19 vaccinations, and more commonly had immunosuppression. Fifteen participants (20.8%) taking N-R had VR versus 1 (1.8%) who was untreated (absolute difference, 19.0 percentage points [95% CI, 9.0 to 29.0 percentage points]; P = 0.001). All persons with VR had a positive viral culture result after a prior negative result. In multivariable models, only N-R use was associated with VR (adjusted odds ratio, 10.02 [CI, 1.13 to 88.74]; P = 0.038). Virologic rebound was more common among those who started therapy within 2 days of symptom onset (26.3%) than among those who started 2 or more days after symptom onset (0%) (P = 0.030). Among participants receiving N-R, those who had VR had prolonged shedding of replication-competent virus compared with those who did not have VR (median, 14 vs. 3 days). Eight of 16 participants (50% [CI, 25% to 75%]) with VR also reported symptom rebound; 2 were completely asymptomatic. No post-VR resistance mutations were detected. LIMITATIONS: Observational study design with differences between the treated and untreated groups; positive viral culture result was used as a surrogate marker for risk for ongoing viral transmission. CONCLUSION: Virologic rebound occurred in approximately 1 in 5 people taking N-R, often without symptom rebound, and was associated with shedding of replication-competent virus. PRIMARY FUNDING SOURCE: National Institutes of Health.

Characterization of Virologic Rebound Following Nirmatrelvir-Ritonavir Treatment for Coronavirus Disease 2019 (COVID-19).

We enrolled 7 individuals with recurrent symptoms or antigen test conversion following nirmatrelvir-ritonavir treatment. High viral loads (median 6.1 log10 copies/mL) were detected after rebound for a median of 17 days after initial diagnosis. Three had culturable virus for up to 16 days after initial diagnosis. No known resistance-associated mutations were identified.

Determining the Incidence of Asymptomatic SARS-CoV-2 Among Early Recipients of COVID-19 Vaccines (DISCOVER-COVID-19): A Prospective Cohort Study of Healthcare Workers Before, During and After Vaccination.

The impact of coronavirus disease 2019 vaccination on viral characteristics of breakthrough infections is unknown. In this prospective cohort study, incidence of severe acute respiratory syndrome coronavirus 2 infection decreased following vaccination. Although asymptomatic positive tests were observed following vaccination, the higher cycle thresholds, repeat negative tests, and inability to culture virus raise questions about their clinical significance.

Virologic Features of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children.

BACKGROUND: Data on pediatric coronavirus disease 2019 (COVID-19) has lagged behind adults throughout the pandemic. An understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral dynamics in children would enable data-driven public health guidance. METHODS: Respiratory swabs were collected from children with COVID-19. Viral load was quantified by reverse-transcription polymerase chain reaction (RT-PCR); viral culture was assessed by direct observation of cytopathic effects and semiquantitative viral titers. Correlations with age, symptom duration, and disease severity were analyzed. SARS-CoV-2 whole genome sequences were compared with contemporaneous sequences. RESULTS: One hundred ten children with COVID-19 (median age, 10 years [range, 2 weeks-21 years]) were included in this study. Age did not impact SARS-CoV-2 viral load. Children were most infectious within the first 5 days of illness, and severe disease did not correlate with increased viral loads. Pediatric SARS-CoV-2 sequences were representative of those in the community and novel variants were identified. CONCLUSIONS: Symptomatic and asymptomatic children can carry high quantities of live, replicating SARS-CoV-2, creating a potential reservoir for transmission and evolution of genetic variants. As guidance around social distancing and masking evolves following vaccine uptake in older populations, a clear understanding of SARS-CoV-2 infection dynamics in children is critical for rational development of public health policies and vaccination strategies to mitigate the impact of COVID-19.

Systematic, multiparametric analysis of Mycobacterium tuberculosis intracellular infection offers insight into coordinated virulence.

A key to the pathogenic success of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, is the capacity to survive within host macrophages. Although several factors required for this survival have been identified, a comprehensive knowledge of such factors and how they work together to manipulate the host environment to benefit bacterial survival are not well understood. To systematically identify Mtb factors required for intracellular growth, we screened an arrayed, non-redundant Mtb transposon mutant library by high-content imaging to characterize the mutant-macrophage interaction. Based on a combination of imaging features, we identified mutants impaired for intracellular survival. We then characterized the phenotype of infection with each mutant by profiling the induced macrophage cytokine response. Taking a systems-level approach to understanding the biology of identified mutants, we performed a multiparametric analysis combining pathogen and host phenotypes to predict functional relationships between mutants based on clustering. Strikingly, mutants defective in two well-known virulence factors, the ESX-1 protein secretion system and the virulence lipid phthiocerol dimycocerosate (PDIM), clustered together. Building upon the shared phenotype of loss of the macrophage type I interferon (IFN) response to infection, we found that PDIM production and export are required for coordinated secretion of ESX-1-substrates, for phagosomal permeabilization, and for downstream induction of the type I IFN response. Multiparametric clustering also identified two novel genes that are required for PDIM production and induction of the type I IFN response. Thus, multiparametric analysis combining host and pathogen infection phenotypes can be used to identify novel functional relationships between genes that play a role in infection.

Phosphorylation of the Peptidoglycan Synthase PonA1 Governs the Rate of Polar Elongation in Mycobacteria.

Cell growth and division are required for the progression of bacterial infections. Most rod-shaped bacteria grow by inserting new cell wall along their mid-section. However, mycobacteria, including the human pathogen Mycobacterium tuberculosis, produce new cell wall material at their poles. How mycobacteria control this different mode of growth is incompletely understood. Here we find that PonA1, a penicillin binding protein (PBP) capable of transglycosylation and transpeptidation of cell wall peptidoglycan (PG), is a major governor of polar growth in mycobacteria. PonA1 is required for growth of Mycobacterium smegmatis and is critical for M. tuberculosis during infection. In both cases, PonA1's catalytic activities are both required for normal cell length, though loss of transglycosylase activity has a more pronounced effect than transpeptidation. Mutations that alter the amount or the activity of PonA1 result in abnormal formation of cell poles and changes in cell length. Moreover, altered PonA1 activity results in dramatic differences in antibiotic susceptibility, suggesting that a balance between the two enzymatic activities of PonA1 is critical for survival. We also find that phosphorylation of a cytoplasmic region of PonA1 is required for normal activity. Mutations in a critical phosphorylated residue affect transglycosylase activity and result in abnormal rates of cell elongation. Together, our data indicate that PonA1 is a central determinant of polar growth in mycobacteria, and its governance of cell elongation is required for robust cell fitness during both host-induced and antibiotic stress.

Identification of host-targeted small molecules that restrict intracellular Mycobacterium tuberculosis growth.

Mycobacterium tuberculosis remains a significant threat to global health. Macrophages are the host cell for M. tuberculosis infection, and although bacteria are able to replicate intracellularly under certain conditions, it is also clear that macrophages are capable of killing M. tuberculosis if appropriately activated. The outcome of infection is determined at least in part by the host-pathogen interaction within the macrophage; however, we lack a complete understanding of which host pathways are critical for bacterial survival and replication. To add to our understanding of the molecular processes involved in intracellular infection, we performed a chemical screen using a high-content microscopic assay to identify small molecules that restrict mycobacterial growth in macrophages by targeting host functions and pathways. The identified host-targeted inhibitors restrict bacterial growth exclusively in the context of macrophage infection and predominantly fall into five categories: G-protein coupled receptor modulators, ion channel inhibitors, membrane transport proteins, anti-inflammatories, and kinase modulators. We found that fluoxetine, a selective serotonin reuptake inhibitor, enhances secretion of pro-inflammatory cytokine TNF-α and induces autophagy in infected macrophages, and gefitinib, an inhibitor of the Epidermal Growth Factor Receptor (EGFR), also activates autophagy and restricts growth. We demonstrate that during infection signaling through EGFR activates a p38 MAPK signaling pathway that prevents macrophages from effectively responding to infection. Inhibition of this pathway using gefitinib during in vivo infection reduces growth of M. tuberculosis in the lungs of infected mice. Our results support the concept that screening for inhibitors using intracellular models results in the identification of tool compounds for probing pathways during in vivo infection and may also result in the identification of new anti-tuberculosis agents that work by modulating host pathways. Given the existing experience with some of our identified compounds for other therapeutic indications, further clinically-directed study of these compounds is merited.

RNA signatures allow rapid identification of pathogens and antibiotic susceptibilities.

With rising rates of drug-resistant infections, there is a need for diagnostic methods that rapidly can detect the presence of pathogens and reveal their susceptibility to antibiotics. Here we propose an approach to diagnosing the presence and drug-susceptibility of infectious diseases based on direct detection of RNA from clinical samples. We demonstrate that species-specific RNA signatures can be used to identify a broad spectrum of infectious agents, including bacteria, viruses, yeast, and parasites. Moreover, we show that the behavior of a small set of bacterial transcripts after a brief antibiotic pulse can rapidly differentiate drug-susceptible and -resistant organisms and that these measurements can be made directly from clinical materials. Thus, transcriptional signatures could form the basis of a uniform diagnostic platform applicable across a broad range of infectious agents.

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy.

Tuberculosis (TB) is the world's deadliest infectious disease, with over 1.5 million deaths annually and 10 million new cases reported each year. The causative organism, Mycobacterium tuberculosis (Mtb) can take nearly 40 days to culture, a required step to determine the pathogen's antibiotic susceptibility. Both rapid identification of Mtb and rapid antibiotic susceptibility testing (AST) are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the MtB complex strain Bacillus Calmette Guerin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin and amikacin, as well as a pan susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and in patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all 5 BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5000. We show how this instrument and our machine learning model enables combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

A mouse model of TB-associated lung fibrosis reveals persistent inflammatory macrophage populations during treatment.

Post-TB lung disease (PTLD) causes a significant burden of global disease. Fibrosis is a central component of many clinical features of PTLD. To date, we have a limited understanding of the mechanisms of TB-associated fibrosis and how these mechanisms are similar to or dissimilar from other fibrotic lung pathologies. We have adapted a mouse model of TB infection to facilitate the mechanistic study of TB-associated lung fibrosis. We find that the morphologies of fibrosis that develop in the mouse model are similar to the morphologies of fibrosis observed in human tissue samples. Using Second Harmonic Generation (SHG) microscopy, we are able to quantify a major component of fibrosis, fibrillar collagen, over time and with treatment. Inflammatory macrophage subpopulations persist during treatment; matrix remodeling enzymes and inflammatory gene signatures remain elevated. Our mouse model suggests that there is a therapeutic window during which adjunctive therapies could change matrix remodeling or inflammatory drivers of tissue pathology to improve functional outcomes after treatment for TB infection.

Enhancing antibody responses by multivalent antigen display on thymus-independent DNA origami scaffolds.

Protein-based virus-like particles (P-VLPs) are commonly used to spatially organize antigens and enhance humoral immunity through multivalent antigen display. However, P-VLPs are thymus-dependent antigens that are themselves immunogenic and can induce B cell responses that may neutralize the platform. Here, we investigate thymus-independent DNA origami as an alternative material for multivalent antigen display using the receptor binding domain (RBD) of the SARS-CoV-2 spike protein, the primary target of neutralizing antibody responses. Sequential immunization of mice with DNA-based VLPs (DNA-VLPs) elicits protective neutralizing antibodies to SARS-CoV-2 in a manner that depends on the valency of the antigen displayed and on T cell help. Importantly, the immune sera do not contain boosted, class-switched antibodies against the DNA scaffold, in contrast to P-VLPs that elicit strong B cell memory against both the target antigen and the scaffold. Thus, DNA-VLPs enhance target antigen immunogenicity without generating scaffold-directed immunity and thereby offer an important alternative material for particulate vaccine design.

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.