Conventional and unconventional T-cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients.

Sepsis is characterized by a dysfunctional host response to infection culminating in life-threatening organ failure that requires complex patient management and rapid intervention. Timely diagnosis of the underlying cause of sepsis is crucial, and identifying those at risk of complications and death is imperative for triaging treatment and resource allocation. Here, we explored the potential of explainable machine learning models to predict mortality and causative pathogen in sepsis patients. By using a modelling pipeline employing multiple feature selection algorithms, we demonstrate the feasibility of identifying integrative patterns from clinical parameters, plasma biomarkers, and extensive phenotyping of blood immune cells. While no single variable had sufficient predictive power, models that combined five and more features showed a macro area under the curve (AUC) of 0.85 to predict 90-day mortality after sepsis diagnosis, and a macro AUC of 0.86 to discriminate between Gram-positive and Gram-negative bacterial infections. Parameters associated with the cellular immune response contributed the most to models predictive of 90-day mortality, most notably, the proportion of T cells among PBMCs, together with expression of CXCR3 by CD4+ T cells and CD25 by mucosal-associated invariant T (MAIT) cells. Frequencies of Vδ2+ γδ T cells had the most profound impact on the prediction of Gram-negative infections, alongside other T-cell-related variables and total neutrophil count. Overall, our findings highlight the added value of measuring the proportion and activation patterns of conventional and unconventional T cells in the blood of sepsis patients in combination with other immunological, biochemical, and clinical parameters.

GeoWaVe: geometric median clustering with weighted voting for ensemble clustering of cytometry data.

MOTIVATION: Clustering is an unsupervised method for identifying structure in unlabelled data. In the context of cytometry, it is typically used to categorize cells into subpopulations of similar phenotypes. However, clustering is greatly dependent on hyperparameters and the data to which it is applied as each algorithm makes different assumptions and generates a different 'view' of the dataset. As such, the choice of clustering algorithm can significantly influence results, and there is often not one preferred method but different insights to be obtained from different methods. To overcome these limitations, consensus approaches are needed that directly address the effect of competing algorithms. To the best of our knowledge, consensus clustering algorithms designed specifically for the analysis of cytometry data are lacking. RESULTS: We present a novel ensemble clustering methodology based on geometric median clustering with weighted voting (GeoWaVe). Compared to graph ensemble clustering methods that have gained popularity in single-cell RNA sequencing analysis, GeoWaVe performed favourably on different sets of high-dimensional mass and flow cytometry data. Our findings provide proof of concept for the power of consensus methods to make the analysis, visualization and interpretation of cytometry data more robust and reproducible. The wide availability of ensemble clustering methods is likely to have a profound impact on our understanding of cellular responses, clinical conditions and therapeutic and diagnostic options. AVAILABILITY AND IMPLEMENTATION: GeoWaVe is available as part of the CytoCluster package https://github.com/burtonrj/CytoCluster and published on the Python Package Index https://pypi.org/project/cytocluster. Benchmarking data described are available from https://doi.org/10.5281/zenodo.7134723. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

CytoPy: An autonomous cytometry analysis framework.

Cytometry analysis has seen a considerable expansion in recent years in the maximum number of parameters that can be acquired in a single experiment. In response to this technological advance there has been an increased effort to develop new computational methodologies for handling high-dimensional single cell data acquired by flow or mass cytometry. Despite the success of numerous algorithms and published packages to replicate and outperform traditional manual analysis, widespread adoption of these techniques has yet to be realised in the field of immunology. Here we present CytoPy, a Python framework for automated analysis of cytometry data that integrates a document-based database for a data-centric and iterative analytical environment. In addition, our algorithm-agnostic design provides a platform for open-source cytometry bioinformatics in the Python ecosystem. We demonstrate the ability of CytoPy to phenotype T cell subsets in whole blood samples even in the presence of significant batch effects due to technical and user variation. The complete analytical pipeline was then used to immunophenotype the local inflammatory infiltrate in individuals with and without acute bacterial infection. CytoPy is open-source and licensed under the MIT license. CytoPy is available at https://github.com/burtonrj/CytoPy, with notebooks accompanying this manuscript (https://github.com/burtonrj/CytoPyManuscript) and software documentation at https://cytopy.readthedocs.io/.

Diagnosis of colorectal and emergency surgical site infections in the era of enhanced recovery: an all-Wales prospective study.

AIM: Surgical site infections (SSIs) are associated with increased morbidity, hospital stay and cost. The literature reports that 25% of patients who undergo colorectal surgical procedures develop a SSI. Due to the enhanced recovery programme, patients are being discharged earlier with some SSIs presenting in primary care, making accurate recording of SSIs difficult. The aim of this study was to accurately record the 30-day SSI rate after surgery performed by colorectal surgeons nationally within Wales. METHOD: During March 2019, a national prospective snapshot study of all patients undergoing elective or emergency colorectal and general surgical procedures under the care of a colorectal consultant at 12 Welsh hospitals was completed. There was a multimodal 30-day follow-up using electronic records, clinic visits and/or telephone calls. Diagnosis of SSI was based on Centers for Disease Control and Prevention diagnostic criteria. RESULTS: Within Wales, of the 545 patients included, 13% developed a SSI within 30 days, with SSI rates of 14.3% for elective surgery and 11.7% for emergency surgery. Of these SSIs, 49.3% were diagnosed in primary care, with 28.2% of patients being managed exclusively in the community. There were two peaks of diagnosis at days 5-7 and days 22-28. SSI rates between laparoscopic (8.6%) and open (16.2%) surgeries were significantly different (p = 0.028), and there was also a significantly different rate of SSI between procedure groups (p = 0.001), with high SSI rates for colon (22%) and rectal (18.9%) surgery compared with general surgical procedures. CONCLUSION: This first all-Wales prospective study demonstrated an overall SSI rate of 13%. By incorporating accurate primary care follow-up it was found that 49.3% of these SSIs were diagnosed in primary care.

Control of neutrophil influx during peritonitis by transcriptional cross-regulation of chemokine CXCL1 by IL-17 and IFN-γ.

Neutrophil infiltration is a hallmark of peritoneal inflammation, but mechanisms regulating neutrophil recruitment in patients with peritoneal dialysis (PD)-related peritonitis are not fully defined. We examined 104 samples of PD effluent collected during acute peritonitis for correspondence between a broad range of soluble parameters and neutrophil counts. We observed an association between peritoneal IL-17 and neutrophil levels. This relationship was evident in effluent samples with low but not high IFN-γ levels, suggesting a differential effect of IFN-γ concentration on neutrophil infiltration. Surprisingly, there was no association of neutrophil numbers with the level of CXCL1, a key IL-17-induced neutrophil chemoattractant. We investigated therefore the production of CXCL1 by human peritoneal mesothelial cells (HPMCs) under in vitro conditions mimicking clinical peritonitis. Stimulation of HPMCs with IL-17 increased CXCL1 production through induction of transcription factor SP1 and activation of the SP1-binding region of the CXCL1 promoter. These effects were amplified by TNFα. In contrast, IFN-γ dose-dependently suppressed IL-17-induced SP1 activation and CXCL1 production through a transcriptional mechanism involving STAT1. The SP1-mediated induction of CXCL1 was also observed in HPMCs exposed to PD effluent collected during peritonitis and containing IL-17 and TNFα, but not IFN-γ. Supplementation of the effluent with IFN-γ led to a dose-dependent activation of STAT1 and a resultant inhibition of SP1-induced CXCL1 expression. Transmesothelial migration of neutrophils in vitro increased upon stimulation of HPMCs with IL-17 and was reduced by IFN-γ. In addition, HPMCs were capable of binding CXCL1 at their apical cell surface. These observations indicate that changes in relative peritoneal concentrations of IL-17 and IFN-γ can differently engage SP1-STAT1, impacting on mesothelial cell transcription of CXCL1, whose release and binding to HPMC surface may determine optimal neutrophil recruitment and retention during peritonitis. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Toll-like receptor linked cytokine profiles in cerebrospinal fluid discriminate neurological infection from sterile inflammation.

Rapid determination of an infective aetiology causing neurological inflammation in the cerebrospinal fluid can be challenging in clinical practice. Post-surgical nosocomial infection is difficult to diagnose accurately, as it occurs on a background of altered cerebrospinal fluid composition due to the underlying pathologies and surgical procedures involved. There is additional diagnostic difficulty after external ventricular drain or ventriculoperitoneal shunt surgery, as infection is often caused by pathogens growing as biofilms, which may fail to elicit a significant inflammatory response and are challenging to identify by microbiological culture. Despite much research effort, a single sensitive and specific cerebrospinal fluid biomarker has yet to be defined which reliably distinguishes infective from non-infective inflammation. As a result, many patients with suspected infection are treated empirically with broad-spectrum antibiotics in the absence of definitive diagnostic criteria. To begin to address these issues, we examined cerebrospinal fluid taken at the point of clinical equipoise to diagnose cerebrospinal fluid infection in 14 consecutive neurosurgical patients showing signs of inflammatory complications. Using the guidelines of the Infectious Diseases Society of America, six cases were subsequently characterized as infected and eight as sterile inflammation. Twenty-four contemporaneous patients with idiopathic intracranial hypertension or normal pressure hydrocephalus were included as non-inflamed controls. We measured 182 immune and neurological biomarkers in each sample and used pathway analysis to elucidate the biological underpinnings of any biomarker changes. Increased levels of the inflammatory cytokine interleukin-6 and interleukin-6-related mediators such as oncostatin M were excellent indicators of inflammation. However, interleukin-6 levels alone could not distinguish between bacterially infected and uninfected patients. Within the patient cohort with neurological inflammation, a pattern of raised interleukin-17, interleukin-12p40/p70 and interleukin-23 levels delineated nosocomial bacteriological infection from background neuroinflammation. Pathway analysis showed that the observed immune signatures could be explained through a common generic inflammatory response marked by interleukin-6 in both nosocomial and non-infectious inflammation, overlaid with a toll-like receptor-associated and bacterial peptidoglycan-triggered interleukin-17 pathway response that occurred exclusively during infection. This is the first demonstration of a pathway dependent cerebrospinal fluid biomarker differentiation distinguishing nosocomial infection from background neuroinflammation. It is especially relevant to the commonly encountered pathologies in clinical practice, such as subarachnoid haemorrhage and post-cranial neurosurgery. While requiring confirmation in a larger cohort, the current data indicate the potential utility of cerebrospinal fluid biomarker strategies to identify differential initiation of a common downstream interleukin-6 pathway to diagnose nosocomial infection in this challenging clinical cohort.

Identification of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms.

Women with uncomplicated urinary tract infection (UTI) symptoms are commonly treated with empirical antibiotics, resulting in overuse of antibiotics, which promotes antimicrobial resistance. Available diagnostic tools are either not cost-effective or diagnostically sub-optimal. Here, we identified clinical and urinary immunological predictors for UTI diagnosis. We explored 17 clinical and 42 immunological potential predictors for bacterial culture among women with uncomplicated UTI symptoms using random forest or support vector machine coupled with recursive feature elimination. Urine cloudiness was the best performing clinical predictor to rule out (negative likelihood ratio [LR-] = 0.4) and rule in (LR+ = 2.6) UTI. Using a more discriminatory scale to assess cloudiness (turbidity) increased the accuracy of UTI prediction further (LR+ = 4.4). Urinary levels of MMP9, NGAL, CXCL8 and IL-1ß together had a higher LR+ (6.1) and similar LR- (0.4), compared to cloudiness. Varying the bacterial count thresholds for urine culture positivity did not alter best clinical predictor selection, but did affect the number of immunological predictors required for reaching an optimal prediction. We conclude that urine cloudiness is particularly helpful in ruling out negative UTI cases. The identified urinary biomarkers could be used to develop a point of care test for UTI but require further validation.

Using artificial intelligence to reduce diagnostic workload without compromising detection of urinary tract infections.

BACKGROUND: A substantial proportion of microbiological screening in diagnostic laboratories is due to suspected urinary tract infections (UTIs), yet approximately two thirds of urine samples typically yield negative culture results. By reducing the number of query samples to be cultured and enabling diagnostic services to concentrate on those in which there are true microbial infections, a significant improvement in efficiency of the service is possible. METHODOLOGY: Screening process for urine samples prior to culture was modelled in a single clinical microbiology laboratory covering three hospitals and community services across Bristol and Bath, UK. Retrospective analysis of all urine microscopy, culture, and sensitivity reports over one year was used to compare two methods of classification: a heuristic model using a combination of white blood cell count and bacterial count, and a machine learning approach testing three algorithms (Random Forest, Neural Network, Extreme Gradient Boosting) whilst factoring in independent variables including demographics, historical urine culture results, and clinical details provided with the specimen. RESULTS: A total of 212,554 urine reports were analysed. Initial findings demonstrated the potential for using machine learning algorithms, which outperformed the heuristic model in terms of relative workload reduction achieved at a classification sensitivity > 95%. Upon further analysis of classification sensitivity of subpopulations, we concluded that samples from pregnant patients and children (age 11 or younger) require independent evaluation. First the removal of pregnant patients and children from the classification process was investigated but this diminished the workload reduction achieved. The optimal solution was found to be three Extreme Gradient Boosting algorithms, trained independently for the classification of pregnant patients, children, and then all other patients. When combined, this system granted a relative workload reduction of 41% and a sensitivity of 95% for each of the stratified patient groups. CONCLUSION: Based on the considerable time and cost savings achieved, without compromising the diagnostic performance, the heuristic model was successfully implemented in routine clinical practice in the diagnostic laboratory at Severn Pathology, Bristol. Our work shows the potential application of supervised machine learning models in improving service efficiency at a time when demand often surpasses resources of public healthcare providers.

Neutrophil-derived miR-223 as local biomarker of bacterial peritonitis.

Infection remains a major cause of morbidity, mortality and technique failure in patients with end stage kidney failure who receive peritoneal dialysis (PD). Recent research suggests that the early inflammatory response at the site of infection carries diagnostically relevant information, suggesting that organ and pathogen-specific "immune fingerprints" may guide targeted treatment decisions and allow patient stratification and risk prediction at the point of care. Here, we recorded microRNA profiles in the PD effluent of patients presenting with symptoms of acute peritonitis and show that elevated peritoneal miR-223 and reduced miR-31 levels were useful predictors of bacterial infection. Cell culture experiments indicated that miR-223 was predominantly produced by infiltrating immune cells (neutrophils, monocytes), while miR-31 was mainly derived from the local tissue (mesothelial cells, fibroblasts). miR-223 was found to be functionally stabilised in PD effluent from peritonitis patients, with a proportion likely to be incorporated into neutrophil-derived exosomes. Our study demonstrates that microRNAs are useful biomarkers of bacterial infection in PD-related peritonitis and have the potential to contribute to disease-specific immune fingerprints. Exosome-encapsulated microRNAs may have a functional role in intercellular communication between immune cells responding to the infection and the local tissue, to help clear the infection, resolve the inflammation and restore homeostasis.

Altered Gut Microbiota Activate and Expand Insulin B15-23-Reactive CD8+ T Cells.

Insulin is a major autoantigen in type 1 diabetes, targeted by both CD8 and CD4 T cells. We studied an insulin-reactive T-cell receptor (TCR) α-chain transgenic NOD mouse on a TCRCα and proinsulin 2 (PI2)-deficient background, designated as A22Cα-/-PI2-/- NOD mice. These mice develop a low incidence of autoimmune diabetes. To test the role of gut microbiota on diabetes development in this model system, we treated the A22Cα-/-PI2-/- NOD mice with enrofloxacin, a broad-spectrum antibiotic. The treatment led to male mice developing accelerated diabetes. We found that enrofloxacin increased the frequency of the insulin-reactive CD8+ T cells and activated the cells in the Peyer's patches and pancreatic lymph nodes, together with induction of immunological effects on the antigen-presenting cell populations. The composition of gut microbiota differed between the enrofloxacin-treated and untreated mice and also between the enrofloxacin-treated mice that developed diabetes compared with those that remained normoglycemic. Our results provide evidence that the composition of the gut microbiota is important for determining the expansion and activation of insulin-reactive CD8+ T cells.

An improved cell-permeable fluorogenic substrate as the basis for a highly sensitive test for NAD(P)H quinone oxidoreductase 1 (NQO1) in living cells.

NAD(P)H:quinone oxidoreductase 1 (NQO1) is a flavoenzyme upregulated in response to oxidative stress and in some cancers. Its upregulation by compounds has been used as an indicator of their potential anti-cancer properties. In this study we have designed, produced and tested a fluorogenic coumarin conjugate which selectively releases highly fluorescent 4-methylumbelliferone (4-MU) in the presence of NQO1. It was found that measuring 4-MU release rapidly and specifically quantitated NQO1 levels in vitro and in live cells. Both the substrate and its products freely perfused through cell membranes and were non-toxic. The substrate was very specific with low background, and the assay itself could be done in less than 10minutes. This is the first assay to allow the quantitation of NQO1 in live cells which can then be retained for further experiments.

CD200 receptor restriction of myeloid cell responses antagonizes antiviral immunity and facilitates cytomegalovirus persistence within mucosal tissue.

CD200 receptor (CD200R) negatively regulates peripheral and mucosal innate immune responses. Viruses, including herpesviruses, have acquired functional CD200 orthologs, implying that viral exploitation of this pathway is evolutionary advantageous. However, the role that CD200R signaling plays during herpesvirus infection in vivo requires clarification. Utilizing the murine cytomegalovirus (MCMV) model, we demonstrate that CD200R facilitates virus persistence within mucosal tissue. Specifically, MCMV infection of CD200R-deficient mice (CD200R(-/-)) elicited heightened mucosal virus-specific CD4 T cell responses that restricted virus persistence in the salivary glands. CD200R did not directly inhibit lymphocyte effector function. Instead, CD200R(-/-) mice exhibited enhanced APC accumulation that in the mucosa was a consequence of elevated cellular proliferation. Although MCMV does not encode an obvious CD200 homolog, productive replication in macrophages induced expression of cellular CD200. CD200 from hematopoietic and non-hematopoietic cells contributed independently to suppression of antiviral control in vivo. These results highlight the CD200-CD200R pathway as an important regulator of antiviral immunity during cytomegalovirus infection that is exploited by MCMV to establish chronicity within mucosal tissue.

Oncogenic properties of apoptotic tumor cells in aggressive B cell lymphoma.

BACKGROUND: Cells undergoing apoptosis are known to modulate their tissue microenvironments. By acting on phagocytes, notably macrophages, apoptotic cells inhibit immunological and inflammatory responses and promote trophic signaling pathways. Paradoxically, because of their potential to cause death of tumor cells and thereby militate against malignant disease progression, both apoptosis and tumor-associated macrophages (TAMs) are often associated with poor prognosis in cancer. We hypothesized that, in progression of malignant disease, constitutive loss of a fraction of the tumor cell population through apoptosis could yield tumor-promoting effects. RESULTS: Here, we demonstrate that apoptotic tumor cells promote coordinated tumor growth, angiogenesis, and accumulation of TAMs in aggressive B cell lymphomas. Through unbiased "in situ transcriptomics" analysis-gene expression profiling of laser-captured TAMs to establish their activation signature in situ-we show that these cells are activated to signal via multiple tumor-promoting reparatory, trophic, angiogenic, tissue remodeling, and anti-inflammatory pathways. Our results also suggest that apoptotic lymphoma cells help drive this signature. Furthermore, we demonstrate that, upon induction of apoptosis, lymphoma cells not only activate expression of the tumor-promoting matrix metalloproteinases MMP2 and MMP12 in macrophages but also express and process these MMPs directly. Finally, using a model of malignant melanoma, we show that the oncogenic potential of apoptotic tumor cells extends beyond lymphoma. CONCLUSIONS: In addition to its profound tumor-suppressive role, apoptosis can potentiate cancer progression. These results have important implications for understanding the fundamental biology of cell death, its roles in malignant disease, and the broader consequences of apoptosis-inducing anti-cancer therapy.

Two novel human cytomegalovirus NK cell evasion functions target MICA for lysosomal degradation.

NKG2D plays a major role in controlling immune responses through the regulation of natural killer (NK) cells, αß and γδ T-cell function. This activating receptor recognizes eight distinct ligands (the MHC Class I polypeptide-related sequences (MIC) A andB, and UL16-binding proteins (ULBP)1-6) induced by cellular stress to promote recognition cells perturbed by malignant transformation or microbial infection. Studies into human cytomegalovirus (HCMV) have aided both the identification and characterization of NKG2D ligands (NKG2DLs). HCMV immediate early (IE) gene up regulates NKGDLs, and we now describe the differential activation of ULBP2 and MICA/B by IE1 and IE2 respectively. Despite activation by IE functions, HCMV effectively suppressed cell surface expression of NKGDLs through both the early and late phases of infection. The immune evasion functions UL16, UL142, and microRNA(miR)-UL112 are known to target NKG2DLs. While infection with a UL16 deletion mutant caused the expected increase in MICB and ULBP2 cell surface expression, deletion of UL142 did not have a similar impact on its target, MICA. We therefore performed a systematic screen of the viral genome to search of addition functions that targeted MICA. US18 and US20 were identified as novel NK cell evasion functions capable of acting independently to promote MICA degradation by lysosomal degradation. The most dramatic effect on MICA expression was achieved when US18 and US20 acted in concert. US18 and US20 are the first members of the US12 gene family to have been assigned a function. The US12 family has 10 members encoded sequentially through US12-US21; a genetic arrangement, which is suggestive of an 'accordion' expansion of an ancestral gene in response to a selective pressure. This expansion must have be an ancient event as the whole family is conserved across simian cytomegaloviruses from old world monkeys. The evolutionary benefit bestowed by the combinatorial effect of US18 and US20 on MICA may have contributed to sustaining the US12 gene family.

The death receptor 3/TL1A pathway is essential for efficient development of antiviral CD4⁺ and CD8⁺ T-cell immunity.

Death receptor 3 (DR3, TNFRSF25), the closest family relative to tumor necrosis factor receptor 1, promotes CD4(+) T-cell-driven inflammatory disease. We investigated the in vivo role of DR3 and its ligand TL1A in viral infection, by challenging DR3-deficient (DR3(KO)) mice and their DR3(WT) littermates with the ß-herpesvirus murine cytomegalovirus or the poxvirus vaccinia virus. The phenotype and function of splenic T-cells were analyzed using flow cytometry and molecular biological techniques. We report surface expression of DR3 by naive CD8(+) T cells, with TCR activation increasing its levels 4-fold and altering the ratio of DR3 splice variants. T-cell responses were reduced up to 90% in DR3(KO) mice during acute infection. Adoptive transfer experiments indicated this was dependent on T-cell-restricted expression of DR3. DR3-dependent CD8(+) T-cell expansion was NK and CD4 independent and due to proliferation, not decreased cell death. Notably, impaired immunity in DR3(KO) hosts on a C57BL/6 background was associated with 4- to 7-fold increases in viral loads during the acute phase of infection, and in mice with suboptimal NK responses was essential for survival (37.5%). This is the first description of DR3 regulating virus-specific T-cell function in vivo and uncovers a critical role for DR3 in mediating antiviral immunity.

Human cytomegalovirus UL40 signal peptide regulates cell surface expression of the NK cell ligands HLA-E and gpUL18.

Human CMV (HCMV)-encoded NK cell-evasion functions include an MHC class I homolog (UL18) with high affinity for the leukocyte inhibitory receptor-1 (CD85j, ILT2, or LILRB1) and a signal peptide (SP(UL40)) that acts by upregulating cell surface expression of HLA-E. Detailed characterization of SP(UL40) revealed that the N-terminal 14 aa residues bestowed TAP-independent upregulation of HLA-E, whereas C region sequences delayed processing of SP(UL40) by a signal peptide peptidase-type intramembrane protease. Most significantly, the consensus HLA-E-binding epitope within SP(UL40) was shown to promote cell surface expression of both HLA-E and gpUL18. UL40 was found to possess two transcription start sites, with utilization of the downstream site resulting in translation being initiated within the HLA-E-binding epitope (P2). Remarkably, this truncated SP(UL40) was functional and retained the capacity to upregulate gpUL18 but not HLA-E. Thus, our findings identify an elegant mechanism by which an HCMV signal peptide differentially regulates two distinct NK cell-evasion pathways. Moreover, we describe a natural SP(UL40) mutant that provides a clear example of an HCMV clinical virus with a defect in an NK cell-evasion function and exemplifies issues that confront the virus when adapting to immunogenetic diversity in the host.

The role of tumor necrosis factor receptor superfamily members in mammalian brain development, function and homeostasis.

Tumor necrosis factor receptor superfamily (TNFRSF) members were initially identified as immunological mediators, and are still commonly perceived as immunological molecules. However, our understanding of the diversity of TNFRSF members' roles in mammalian physiology has grown significantly since the first discovery of TNFRp55 (TNFRSF1) in 1975. In particular, the last decade has provided evidence for important roles in brain development, function and the emergent field of neuronal homeostasis. Recent evidence suggests that TNFRSF members are expressed in an overlapping regulated pattern during neuronal development, participating in the regulation of neuronal expansion, growth, differentiation and regional pattern development. This review examines evidence for non-immunological roles of TNFRSF members in brain development, function and maintenance under normal physiological conditions. In addition, several aspects of brain function during inflammation will also be described, when illuminating and relevant to the non-immunological role of TNFRSF members. Finally, key questions in the field will be outlined.

Age-dependent maintenance of motor control and corticostriatal innervation by death receptor 3.

Death receptor 3 is a proinflammatory member of the immunomodulatory tumor necrosis factor receptor superfamily, which has been implicated in several inflammatory diseases such as arthritis and inflammatory bowel disease. Intriguingly however, constitutive DR3 expression has been detected in the brains of mice, rats, and humans, although its neurological function remains unknown. By mapping the normal brain expression pattern of DR3, we found that DR3 is expressed specifically by cells of the neuron lineage in a developmentally regulated and region-specific pattern. Behavioral studies on DR3-deficient (DR3(ko)) mice showed that constitutive neuronal DR3 expression was required for stable motor control function in the aging adult. DR3(ko) mice progressively developed behavioral defects characterized by altered gait, dyskinesia, and hyperactivity, which were associated with elevated dopamine and lower serotonin levels in the striatum. Importantly, retrograde tracing showed that absence of DR3 expression led to the loss of corticostriatal innervation without significant neuronal loss in aged DR3(ko) mice. These studies indicate that DR3 plays a key nonredundant role in the retention of normal motor control function during aging in mice and implicate DR3 in progressive neurological disease.

Antigen specificity determines the pro- or antitumoral nature of CD8+ T cells.

Although CD8+ T cells are usually considered antitumoral, several recent studies report that the cells can also promote tumor progression. Using the melanoma cell line B16 as a murine model of pulmonary metastasis, we examined whether the pro- versus antitumoral effects of CD8+ T cells relate to their Ag specificity. Results of the study indicate that although CD8+ T cells specific for tumor Ags promote tumor rejection, CD8+ T cells specific for unrelated Ags promote tumor progression. We found the effect to be partly attributable to CD8+ T cells dampening effective antitumor NK cell responses. Notably, activation of CD8+ T cell responses by an unrelated stimulus, in this case infection with influenza virus, increased the number of pulmonary tumor nodules. These data provide a rationale for previously unexplained data identifying contrasting roles for CD8+ T cells in tumor progression.