Protein interactions in human pathogens revealed through deep learning.

Identification of bacterial protein-protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lite, a rapid deep learning model that leverages residue-residue coevolution and protein structure prediction to systematically identify and structurally characterize protein-protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1,923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer-membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.

Computational design of serine hydrolases.

Enzymes that proceed through multistep reaction mechanisms often utilize complex, polar active sites positioned with sub-angstrom precision to mediate distinct chemical steps, which makes their de novo construction extremely challenging. We sought to overcome this challenge using the classic catalytic triad and oxyanion hole of serine hydrolases as a model system. We used RFdiffusion1 to generate proteins housing catalytic sites of increasing complexity and varying geometry, and a newly developed ensemble generation method called ChemNet to assess active site geometry and preorganization at each step of the reaction. Experimental characterization revealed novel serine hydrolases that catalyze ester hydrolysis with catalytic efficiencies (k cat /K m ) up to 3.8 x 103 M-1 s-1, closely match the design models (Cα RMSDs < 1 Å), and have folds distinct from natural serine hydrolases. In silico selection of designs based on active site preorganization across the reaction coordinate considerably increased success rates, enabling identification of new catalysts in screens of as few as 20 designs. Our de novo buildup approach provides insight into the geometric determinants of catalysis that complements what can be obtained from structural and mutational studies of native enzymes (in which catalytic group geometry and active site makeup cannot be so systematically varied), and provides a roadmap for the design of industrially relevant serine hydrolases and, more generally, for designing complex enzymes that catalyze multi-step transformations.

A pseudotyped adenovirus serotype 5 vector with serotype 49 fiber knob is an effective vector for vaccine and gene therapy applications.

Adenoviruses (Ads) have demonstrated significant success as replication-deficient (RD) viral vectored vaccines, as well as broad potential across gene therapy and cancer therapy. Ad vectors transduce human cells via direct interactions between the viral fiber knob and cell surface receptors, with secondary cellular integrin interactions. Ad receptor usage is diverse across the extensive phylogeny. Commonly studied human Ad serotype 5 (Ad5), and chimpanzee Ad-derived vector "ChAdOx1" in licensed ChAdOx1 nCoV-19 vaccine, both form primary interactions with the coxsackie and adenovirus receptor (CAR), which is expressed on human epithelial cells and erythrocytes. CAR usage is suboptimal for targeted gene delivery to cells with low/negative CAR expression, including human dendritic cells (DCs) and vascular smooth muscle cells (VSMCs). We evaluated the performance of an RD Ad5 vector pseudotyped with the fiber knob of human Ad serotype 49, termed Ad5/49K vector. Ad5/49K demonstrated superior transduction of murine and human DCs over Ad5, which translated into significantly increased T cell immunogenicity when evaluated in a mouse cancer vaccine model using 5T4 tumor-associated antigen. Additionally, Ad5/49K exhibited enhanced transduction of primary human VSMCs. These data highlight the potential of Ad5/49K vector for both vascular gene therapy applications and as a potent vaccine vector.

Cytomegalovirus-induced peroxynitrite promotes virus entry and contributes to pathogenesis in a murine model of infection.

There are no licensed vaccines for human cytomegalovirus (HCMV), and current antiviral drugs that target viral proteins are toxic and prone to resistance. Targeting host pathways essential for virus replication provides an alternate strategy that may reduce opportunities for drug resistance to occur. Oxidative stress is triggered by numerous viruses including HCMV. Peroxynitrite is a reactive nitrogen species that is formed during oxidative stress. Herein, we identified that HCMV rapidly induces the generation of intracellular peroxynitrite upon infection in a manner partially dependent upon xanthine oxidase generation. Peroxynitrite promoted HCMV infection in both cell-free and cell-associated infection systems in multiple cell types. Inhibiting peroxynitrite within the first 24 hours of infection prevented HCMV replication and peroxynitrite promoted cell entry and pp65 translocation into the host cell nuclei. Furthermore, using the murine cytomegalovirus model, we demonstrated that antagonizing peroxynitrite significantly reduces cytomegalovirus replication and pathogenesis in vivo. Overall, our study highlights a proviral role for peroxynitrite in CMV infection and implies that RNS and/or the mechanisms that induce their production could be targeted as a novel strategy to inhibit HCMV infection. IMPORTANCE: Human cytomegalovirus (HCMV) causes significant disease in individuals with impaired or immature immune systems, such as transplant patients and after congenital infection. Antiviral drugs that target the virus directly are toxic and are susceptible to antiviral drug resistance due to virus mutations. An alternate strategy is to target processes within host cells that are required by the virus for replication. Herein, we show that HCMV infection triggers a highly reactive molecule, peroxynitrite, during the initial stages of infection. Peroxynitrite was required for the initial entry of the virus into the cell and promotes virus replication in multiple cell types, suggesting a broad pro-viral function. Importantly, targeting peroxynitrite dramatically inhibited cytomegalovirus replication in cells in the laboratory and in mice, suggesting that therapeutic targeting of this molecule and/or the cellular functions it regulates could represent a novel strategy to inhibit HCMV infection.

A targeted single mutation in influenza A virus universal epitope transforms immunogenicity and protective immunity via CD4+ T cell activation.

CD4+ T cells are central to adaptive immunity. Their role in cross-protection in viral infections such as influenza and severe acute respiratory syndrome (SARS) is well documented; however, molecular rules governing T cell receptor (TCR) engagement of peptide-human leukocyte antigen (pHLA) class II are less understood. Here, we exploit an aspect of HLA class II presentation, the peptide-flanking residues (PFRs), to "tune" CD4+ T cell responses within an in vivo model system of influenza. Using a recombinant virus containing targeted substitutions at immunodominant HLA-DR1 epitopes, we demonstrate limited weight loss and improved clinical scores after heterosubtypic re-challenge. We observe enhanced protection linked to lung-derived influenza-specific CD4+ and CD8+ T cells prior to re-infection. Structural analysis of the ternary TCR:pHLA complex identifies that flanking amino acids influence side chains in the core 9-mer peptide, increasing TCR affinity. Augmentation of CD4+ T cell immunity is achievable with a single mutation, representing a strategy to enhance adaptive immunity that is decoupled from vaccine modality.

Essential and virulence-related protein interactions of pathogens revealed through deep learning.

Identification of bacterial protein-protein interactions and predicting the structures of the complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here, we developed a deep learning-based pipeline that leverages residue-residue coevolution and protein structure prediction to systematically identify and structurally characterize protein-protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.

Generalized biomolecular modeling and design with RoseTTAFold All-Atom.

Deep-learning methods have revolutionized protein structure prediction and design but are presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies that contain proteins, nucleic acids, small molecules, metals, and covalent modifications, given their sequences and chemical structures. By fine-tuning on denoising tasks, we developed RFdiffusion All-Atom (RFdiffusionAA), which builds protein structures around small molecules. Starting from random distributions of amino acid residues surrounding target small molecules, we designed and experimentally validated, through crystallography and binding measurements, proteins that bind the cardiac disease therapeutic digoxigenin, the enzymatic cofactor heme, and the light-harvesting molecule bilin.

Mucosal T-cell responses to chronic viral infections: Implications for vaccine design.

Mucosal surfaces that line the respiratory, gastrointestinal and genitourinary tracts are the major interfaces between the immune system and the environment. Their unique immunological landscape is characterized by the necessity of balancing tolerance to commensal microorganisms and other innocuous exposures against protection from pathogenic threats such as viruses. Numerous pathogenic viruses, including herpesviruses and retroviruses, exploit this environment to establish chronic infection. Effector and regulatory T-cell populations, including effector and resident memory T cells, play instrumental roles in mediating the transition from acute to chronic infection, where a degree of viral replication is tolerated to minimize immunopathology. Persistent antigen exposure during chronic viral infection leads to the evolution and divergence of these responses. In this review, we discuss advances in the understanding of mucosal T-cell immunity during chronic viral infections and how features of T-cell responses develop in different chronic viral infections of the mucosa. We consider how insights into T-cell immunity at mucosal surfaces could inform vaccine strategies: not only to protect hosts from chronic viral infections but also to exploit viruses that can persist within mucosal surfaces as vaccine vectors.

Acquisition of suppressive function by conventional T cells limits antitumor immunity upon Treg depletion.

Regulatory T (Treg) cells contribute to immune homeostasis but suppress immune responses to cancer. Strategies to disrupt Treg cell-mediated cancer immunosuppression have been met with limited clinical success, but the underlying mechanisms for treatment failure are poorly understood. By modeling Treg cell-targeted immunotherapy in mice, we find that CD4+ Foxp3- conventional T (Tconv) cells acquire suppressive function upon depletion of Foxp3+ Treg cells, limiting therapeutic efficacy. Foxp3- Tconv cells within tumors adopt a Treg cell-like transcriptional profile upon ablation of Treg cells and acquire the ability to suppress T cell activation and proliferation ex vivo. Suppressive activity is enriched among CD4+ Tconv cells marked by expression of C-C motif receptor 8 (CCR8), which are found in mouse and human tumors. Upon Treg cell depletion, CCR8+ Tconv cells undergo systemic and intratumoral activation and expansion, and mediate IL-10-dependent suppression of antitumor immunity. Consequently, conditional deletion of Il10 within T cells augments antitumor immunity upon Treg cell depletion in mice, and antibody blockade of IL-10 signaling synergizes with Treg cell depletion to overcome treatment resistance. These findings reveal a secondary layer of immunosuppression by Tconv cells released upon therapeutic Treg cell depletion and suggest that broader consideration of suppressive function within the T cell lineage is required for development of effective Treg cell-targeted therapies.

Genetic manipulation of Patescibacteria provides mechanistic insights into microbial dark matter and the epibiotic lifestyle.

Patescibacteria, also known as the candidate phyla radiation (CPR), are a diverse group of bacteria that constitute a disproportionately large fraction of microbial dark matter. Its few cultivated members, belonging mostly to Saccharibacteria, grow as epibionts on host Actinobacteria. Due to a lack of suitable tools, the genetic basis of this lifestyle and other unique features of Patescibacteira remain unexplored. Here, we show that Saccharibacteria exhibit natural competence, and we exploit this property for their genetic manipulation. Imaging of fluorescent protein-labeled Saccharibacteria provides high spatiotemporal resolution of phenomena accompanying epibiotic growth, and a transposon-insertion sequencing (Tn-seq) genome-wide screen reveals the contribution of enigmatic Saccharibacterial genes to growth on their hosts. Finally, we leverage metagenomic data to provide cutting-edge protein structure-based bioinformatic resources that support the strain Southlakia epibionticum and its corresponding host, Actinomyces israelii, as a model system for unlocking the molecular underpinnings of the epibiotic lifestyle.

Inhibitory IL-10-producing CD4+ T cells are T-bet-dependent and facilitate cytomegalovirus persistence via coexpression of arginase-1.

Inhibitory CD4+ T cells have been linked with suboptimal immune responses against cancer and pathogen chronicity. However, the mechanisms that underpin the development of these regulatory cells, especially in the context of ongoing antigen exposure, have remained obscure. To address this knowledge gap, we undertook a comprehensive functional, phenotypic, and transcriptomic analysis of interleukin (IL)-10-producing CD4+ T cells induced by chronic infection with murine cytomegalovirus (MCMV). We identified these cells as clonally expanded and highly differentiated TH1-like cells that developed in a T-bet-dependent manner and coexpressed arginase-1 (Arg1), which promotes the catalytic breakdown of L-arginine. Mice lacking Arg1-expressing CD4+ T cells exhibited more robust antiviral immunity and were better able to control MCMV. Conditional deletion of T-bet in the CD4+ lineage suppressed the development of these inhibitory cells and also enhanced immune control of MCMV. Collectively, these data elucidated the ontogeny of IL-10-producing CD4+ T cells and revealed a previously unappreciated mechanism of immune regulation, whereby viral persistence was facilitated by the site-specific delivery of Arg1.

Genetic manipulation of candidate phyla radiation bacteria provides functional insights into microbial dark matter.

The study of bacteria has yielded fundamental insights into cellular biology and physiology, biotechnological advances and many therapeutics. Yet due to a lack of suitable tools, the significant portion of bacterial diversity held within the candidate phyla radiation (CPR) remains inaccessible to such pursuits. Here we show that CPR bacteria belonging to the phylum Saccharibacteria exhibit natural competence. We exploit this property to develop methods for their genetic manipulation, including the insertion of heterologous sequences and the construction of targeted gene deletions. Imaging of fluorescent protein-labeled Saccharibacteria provides high spatiotemporal resolution of phenomena accompanying epibiotic growth and a transposon insertion sequencing genome-wide screen reveals the contribution of enigmatic Saccharibacterial genes to growth on their Actinobacteria hosts. Finally, we leverage metagenomic data to provide cutting-edge protein structure-based bioinformatic resources that support the strain Southlakia epibionticum and its corresponding host, Actinomyces israelii , as a model system for unlocking the molecular underpinnings of the epibiotic lifestyle.

Recent advances in predicting and modeling protein-protein interactions.

Protein-protein interactions (PPIs) drive biological processes, and disruption of PPIs can cause disease. With recent breakthroughs in structure prediction and a deluge of genomic sequence data, computational methods to predict PPIs and model spatial structures of protein complexes are now approaching the accuracy of experimental approaches for permanent interactions and show promise for elucidating transient interactions. As we describe here, the key to this success is rich evolutionary information deciphered from thousands of homologous sequences that coevolve in interacting partners. This covariation signal, revealed by sophisticated statistical and machine learning (ML) algorithms, predicts physiological interactions. Accurate artificial intelligence (AI)-based modeling of protein structures promises to provide accurate 3D models of PPIs at a proteome-wide scale.

Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations.

Extensive research in well-studied animal models underscores the importance of commensal gastrointestinal (gut) microbes to animal physiology. Gut microbes have been shown to impact dietary digestion, mediate infection, and even modify behavior and cognition. Given the large physiological and pathophysiological contribution microbes provide their host, it is reasonable to assume that the vertebrate gut microbiome may also impact the fitness, health and ecology of wildlife. In accordance with this expectation, an increasing number of investigations have considered the role of the gut microbiome in wildlife ecology, health, and conservation. To help promote the development of this nascent field, we need to dissolve the technical barriers prohibitive to performing wildlife microbiome research. The present review discusses the 16S rRNA gene microbiome research landscape, clarifying best practices in microbiome data generation and analysis, with particular emphasis on unique situations that arise during wildlife investigations. Special consideration is given to topics relevant for microbiome wildlife research from sample collection to molecular techniques for data generation, to data analysis strategies. Our hope is that this article not only calls for greater integration of microbiome analyses into wildlife ecology and health studies but provides researchers with the technical framework needed to successfully conduct such investigations.

The Marine-Derived Macrolactone Mandelalide A Is an Indirect Activator of AMPK.

The mandelalides are complex macrolactone natural products with distinct macrocycle motifs and a bioactivity profile that is heavily influenced by compound glycosylation. Mandelalides A and B are direct inhibitors of mitochondrial ATP synthase (complex V) and therefore more toxic to mammalian cells with an oxidative metabolic phenotype. To provide further insight into the pharmacology of the mandelalides, we studied the AMP-activated protein kinase (AMPK) energy stress pathway and report that mandelalide A is an indirect activator of AMPK. Wild-type mouse embryonic fibroblasts (MEFs) and representative human non-small cell lung cancer (NSCLC) cells showed statistically significant increases in phospho-AMPK (Thr172) and phospho-ACC (Ser79) in response to mandelalide A. Mandelalide L, which also harbors an A-type macrocycle, induced similar increases in phospho-AMPK (Thr172) and phospho-ACC (Ser79) in U87-MG glioblastoma cells. In contrast, MEFs co-treated with an AMPK inhibitor (dorsomorphin), AMPKα-null MEFs, or NSCLC cells lacking liver kinase B1 (LKB1) lacked this activity. Mandelalide A was significantly more cytotoxic to AMPKα-null MEFs than wild-type cells, suggesting that AMPK activation serves as a protective response to mandelalide-induced depletion of cellular ATP. However, LKB1 status alone was not predictive of the antiproliferative effects of mandelalide A against NSCLC cells. When EGFR status was considered, erlotinib and mandelalide A showed strong cytotoxic synergy in combination against erlotinib-resistant 11-18 NSCLC cells but not against erlotinib-sensitive PC-9 cells. Finally, prolonged exposures rendered mandelalide A, a potent and efficacious cytotoxin, against a panel of human glioblastoma cell types regardless of the underlying metabolic phenotype of the cell. These results add biological relevance to the mandelalide series and provide the basis for their further pre-clinical evaluation as ATP synthase inhibitors and secondary activators of AMPK.

SARS-CoV-2 host-shutoff impacts innate NK cell functions, but antibody-dependent NK activity is strongly activated through non-spike antibodies.

The outcome of infection is dependent on the ability of viruses to manipulate the infected cell to evade immunity, and the ability of the immune response to overcome this evasion. Understanding this process is key to understanding pathogenesis, genetic risk factors, and both natural and vaccine-induced immunity. SARS-CoV-2 antagonises the innate interferon response, but whether it manipulates innate cellular immunity is unclear. An unbiased proteomic analysis determined how cell surface protein expression is altered on SARS-CoV-2-infected lung epithelial cells, showing downregulation of activating NK ligands B7-H6, MICA, ULBP2, and Nectin1, with minimal effects on MHC-I. This occurred at the level of protein synthesis, could be mediated by Nsp1 and Nsp14, and correlated with a reduction in NK cell activation. This identifies a novel mechanism by which SARS-CoV-2 host-shutoff antagonises innate immunity. Later in the disease process, strong antibody-dependent NK cell activation (ADNKA) developed. These responses were sustained for at least 6 months in most patients, and led to high levels of pro-inflammatory cytokine production. Depletion of spike-specific antibodies confirmed their dominant role in neutralisation, but these antibodies played only a minor role in ADNKA compared to antibodies to other proteins, including ORF3a, Membrane, and Nucleocapsid. In contrast, ADNKA induced following vaccination was focussed solely on spike, was weaker than ADNKA following natural infection, and was not boosted by the second dose. These insights have important implications for understanding disease progression, vaccine efficacy, and vaccine design.

An Analysis of Serological Response and Infection Outcomes Following Oxford-AstraZeneca (AZD1222) and Pfizer-BioNTech (mRNA BNT162b2) SARS-CoV-2 Vaccines in Kidney and Kidney-pancreas Transplants.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 is associated with high mortality among transplant recipients. Comparative data that define humoral responses to the Oxford-AstraZeneca (AZ) and BNT162b2 (Pfizer-BioNTech) vaccines are limited. METHODS: We recruited 920 kidney transplant patients receiving at least 1 dose of severe acute respiratory syndrome coronavirus 2 vaccine, excluding patients with virus pre-exposure. Serological status was determined with the COVID-SeroKlir ELISA (Kantaro-EKF Diagnostics). Patients with a corrected antibody level of <0.7 AU/mL were considered seronegative. RESULTS: Four hundred ninety-five AZ and 141 Pfizer patients had a sample analyzed after first dose and 593 after second dose (346 AZ versus 247 Pfizer). After first dose, 25.7% of patients seroconverted (26.6% AZ, 22.8% Pfizer). After second dose, 148 (42.8%) of AZ seroconverted compared with 130 (52.6%) of Pfizer (P = 0.02; hazard ratio, 1.48; 95% confidence interval, 1.07-2.06). When negative responders were excluded, Pfizer patients were shown to have significantly higher response than AZ patients (median 2.6 versus 1.78 AU/mL, P = 0.005).Patients on mycophenolate had a reduced seroconversion rate (42.2% versus 61.4%; P < 0.001; hazard ratio, 2.17) and reduced antibody levels (0.47 versus 1.22 AU/mL, P = 0.001), and this effect was dose dependent (P = 0.05). Prednisolone reduced the seroconversion from 58.2% to 43.6% (P = 0.03) among Pfizer but not AZ recipients. Regression analysis showed that antibody levels were reduced by older age (P = 0.002), mycophenolate (P < 0.001), AZ vaccine (versus Pfizer, P = 0.001), and male gender (P = 0.02). Sixteen of 17 serious postvaccine infections occurred to patients who did not seroconvert. CONCLUSIONS: Both seroconversion and antibody levels are lower in AZ compared with Pfizer vaccinated recipients following 2 vaccine doses. Mycophenolate was associated with lower antibody responses in a dose-dependent manner. Serious postvaccine infections occurred among seronegative recipients.

Examining the utility of extended laboratory panel testing in the emergency department for risk stratification of patients with COVID-19: a single-centre retrospective service evaluation.

BACKGROUND: The role of specific blood tests to predict poor prognosis in patients admitted with infection from SARS-CoV-2 remains uncertain. During the first wave of the global pandemic, an extended laboratory testing panel was integrated into the local pathway to guide triage and healthcare resource utilisation for emergency admissions. We conducted a retrospective service evaluation to determine the utility of extended tests (D-dimer, ferritin, high-sensitivity troponin I, lactate dehydrogenase and procalcitonin) compared with the core panel (full blood count, urea and electrolytes, liver function tests and C reactive protein). METHODS: Clinical outcomes for adult patients with laboratory-confirmed COVID-19 admitted between 17 March and 30 June 2020 were extracted, alongside costs estimates for individual tests. Prognostic performance was assessed using multivariable logistic regression analysis with 28-day mortality used as the primary endpoint and a composite of 28-day intensive care escalation or mortality for secondary analysis. RESULTS: From 13 500 emergency attendances, we identified 391 unique adults admitted with COVID-19. Of these, 113 died (29%) and 151 (39%) reached the composite endpoint. 'Core' test variables adjusted for age, gender and index of deprivation had a prognostic area under the curve of 0.79 (95% CI 0.67 to 0.91) for mortality and 0.70 (95% CI 0.56 to 0.84) for the composite endpoint. Addition of 'extended' test components did not improve on this. CONCLUSION: Our findings suggest use of the extended laboratory testing panel to risk stratify community-acquired COVID-19 positive patients on admission adds limited prognostic value. We suggest laboratory requesting should be targeted to patients with specific clinical indications.

Computed structures of core eukaryotic protein complexes.

Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coevolution analysis and deep-learning­based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes within the Saccharomyces cerevisiae proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of yeast proteins, identify 1505 likely to interact, and build structure models for 106 previously unidentified assemblies and 806 that have not been structurally characterized. These complexes, which have as many as five subunits, play roles in almost all key processes in eukaryotic cells and provide broad insights into biological function.

COVID-19 and X-linked agammaglobulinemia (XLA) - insights from a monogenic antibody deficiency.

PURPOSE OF REVIEW: The clinical outcomes from COVID-19 in monogenic causes of predominant antibody deficiency have pivotal implications for our understanding of the antiviral contribution of humoral immunity. This review summarizes the lessons learned from COVID-19 infection in X-linked agammaglobulinemia (XLA) due to genetic defects in Bruton's tyrosine kinase (BTK). RECENT FINDINGS: Key molecular pathways underlying the development of severe COVID-19 are emerging, highlighting the possible contribution of BTK to hyperinflammation. SARS-CoV-2 specific T-cell responses and complement activation appear insufficient to achieve viral clearance in some B-cell deficient individuals. Whilst appearing efficacious in this group, use of convalescent plasma has been recently associated with the evolution of viral escape variants. Early data suggests individuals with XLA can mount a viral-specific T-cell vaccine response, however, the clinical significance of this is still emerging. SUMMARY: In contrast to reports made early in the pandemic, we show XLA patients remain susceptible to severe disease. Persistent infection was common and is likely to carry a significant symptom burden and risk of novel variant evolution. COVID-19 infection in this vulnerable, antibody deficient group due to genetic, therapeutic or disease causes may require prompt and specific intervention for both patient and societal benefit.