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.

A Systematic Review and Meta-Analysis of Inpatient Mortality Associated With Nosocomial and Community COVID-19 Exposes the Vulnerability of Immunosuppressed Adults.

Background: Little is known about the mortality of hospital-acquired (nosocomial) COVID-19 infection globally. We investigated the risk of mortality and critical care admission in hospitalised adults with nosocomial COVID-19, relative to adults requiring hospitalisation due to community-acquired infection. Methods: We systematically reviewed the peer-reviewed and pre-print literature from 1/1/2020 to 9/2/2021 without language restriction for studies reporting outcomes of nosocomial and community-acquired COVID-19. We performed a random effects meta-analysis (MA) to estimate the 1) relative risk of death and 2) critical care admission, stratifying studies by patient cohort characteristics and nosocomial case definition. Results: 21 studies were included in the primary MA, describing 8,251 admissions across 8 countries during the first wave, comprising 1513 probable or definite nosocomial COVID-19, and 6738 community-acquired cases. Across all studies, the risk of mortality was 1.3 times greater in patients with nosocomial infection, compared to community-acquired (95% CI: 1.005 to 1.683). Rates of critical care admission were similar between groups (Relative Risk, RR=0.74, 95% CI: 0.50 to 1.08). Immunosuppressed patients diagnosed with nosocomial COVID-19 were twice as likely to die in hospital as those admitted with community-acquired infection (RR=2.14, 95% CI: 1.76 to 2.61). Conclusions: Adults who acquire SARS-CoV-2 whilst already hospitalised are at greater risk of mortality compared to patients admitted following community-acquired infection; this finding is largely driven by a substantially increased risk of death in individuals with malignancy or who had undergone transplantation. These findings inform public health and infection control policy and argue for individualised clinical interventions to combat the threat of nosocomial COVID-19, particularly for immunosuppressed groups. Systematic Review Registration: PROSPERO CRD42021249023.

Protein oligomer modeling guided by predicted interchain contacts in CASP14.

For CASP14, we developed deep learning-based methods for predicting homo-oligomeric and hetero-oligomeric contacts and used them for oligomer modeling. To build structure models, we developed an oligomer structure generation method that utilizes predicted interchain contacts to guide iterative restrained minimization from random backbone structures. We supplemented this gradient-based fold-and-dock method with template-based and ab initio docking approaches using deep learning-based subunit predictions on 29 assembly targets. These methods produced oligomer models with summed Z-scores 5.5 units higher than the next best group, with the fold-and-dock method having the best relative performance. Over the eight targets for which this method was used, the best of the five submitted models had average oligomer TM-score of 0.71 (average oligomer TM-score of the next best group: 0.64), and explicit modeling of inter-subunit interactions improved modeling of six out of 40 individual domains (ΔGDT-TS > 2.0).

Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14.

The trRosetta structure prediction method employs deep learning to generate predicted residue-residue distance and orientation distributions from which 3D models are built. We sought to improve the method by incorporating as inputs (in addition to sequence information) both language model embeddings and template information weighted by sequence similarity to the target. We also developed a refinement pipeline that recombines models generated by template-free and template utilizing versions of trRosetta guided by the DeepAccNet accuracy predictor. Both benchmark tests and CASP results show that the new pipeline is a considerable improvement over the original trRosetta, and it is faster and requires less computing resources, completing the entire modeling process in a median < 3 h in CASP14. Our human group improved results with this pipeline primarily by identifying additional homologous sequences for input into the network. We also used the DeepAccNet accuracy predictor to guide Rosetta high-resolution refinement for submissions in the regular and refinement categories; although performance was quite good on a CASP relative scale, the overall improvements were rather modest in part due to missing inter-domain or inter-chain contacts.

Burden of nosocomial COVID-19 in Wales: results from a multicentre retrospective observational study of 2508 hospitalised adults.

The burden of nosocomial SARS-CoV-2 infection remains poorly defined. We report on the outcomes of 2508 adults with molecularly-confirmed SARS-CoV-2 admitted across 18 major hospitals, representing over 60% of those hospitalised across Wales between 1 March and 1 July 2020. Inpatient mortality for nosocomial infection ranged from 38% to 42%, consistently higher than participants with community-acquired infection (31%-35%) across a range of case definitions. Those with hospital-acquired infection were older and frailer than those infected within the community. Nosocomial diagnosis occurred a median of 30 days following admission (IQR 21-63), suggesting a window for prophylactic or postexposure interventions, alongside enhanced infection control measures.

Optimal CD8+ T-cell memory formation following subcutaneous cytomegalovirus infection requires virus replication but not early dendritic cell responses.

Cytomegalovirus (CMV) induction of large frequencies of highly functional memory T cells has attracted much interest in the utility of CMV-based vaccine vectors, with exciting preclinical data obtained in models of infectious diseases and cancer. However, pathogenesis of human CMV (HCMV) remains a concern. Attenuated CMV-based vectors, such as replication- or spread-deficient viruses, potentially offer an alternative to fully replicating vectors. However, it is not well understood how CMV attenuation impacts vector immunogenicity, particularly when administered via relevant routes of immunization such as the skin. Herein, we used the murine cytomegalovirus (MCMV) model to investigate the impact of vector attenuation on T-cell memory formation following subcutaneous administration. We found that the spread-deficient virus (ΔgL-MCMV) was impaired in its ability to induce memory CD8+ T cells reactive to some (M38, IE1) but not all (IE3) viral antigens. Impaired-memory T-cell development was associated with a preferential and pronounced loss of polyfunctional (IFN-γ+ TNF-α+ ) T cells and also reduced accumulation of TCF1+ T cells, and was not rescued by increasing the dose of replication-defective MCMV. Finally, whilst vector attenuation reduced dendritic cell (DC) recruitment to skin-draining lymph nodes, systematic depletion of multiple DC subsets during acute subcutaneous MCMV infection had a negligible impact on T-cell memory formation, implying that attenuated responses induced by replication-deficient vectors were likely not a consequence of impaired initial DC activation. Thus, overall, these data imply that the choice of antigen and/or cloning strategy of exogenous antigen in combination with the route of immunization may influence the ability of attenuated CMV vectors to induce robust functional T-cell memory.