Metabolite profiling of human renal cell carcinoma reveals tissue-origin dominance in nutrient availability.

The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer-driven tissue factors in shaping nutrient availability in these tumors.

Cancer cells convert nutrients into energy differently compared to healthy cells. This difference in metabolism allows them to grow and divide more quickly and sometimes to migrate to different areas of the body. The environment around cancer cells ­ known as the tumor microenvironment ­ contains a variety of different cells and blood vessels, which are bathed in interstitial fluid. This microenvironment provides nutrients for the cancer cells to metabolize, and therefore influences how well a tumor grows and how it might respond to treatment. Recent advances with techniques such as mass spectrometry, which can measure the chemical composition of a substance, have allowed scientists to measure nutrient levels in the tumor microenvironments of mice. However, it has been more difficult to conduct such studies in humans, as well as to compare the tumor microenvironment to the healthy tissue the tumors arose from. Abbott, Ali, Reinfeld et al. aimed to fill this gap in knowledge by using mass spectrometry to measure the nutrient levels in the tumor microenvironment of 55 patients undergoing surgery to remove kidney tumors. Comparing the type and levels of nutrients in the tumor interstitial fluid, the neighboring healthy kidney and the blood showed that nutrients in the tumor and healthy kidney were more similar to each other than those in the blood. For example, both the tumor and healthy kidney interstitial fluids contained less glucose than the blood. However, the difference between nutrient composition in the tumor and healthy kidney interstitial fluids was insignificant, suggesting that the healthy kidney and its tumor share a similar environment. Taken together, the findings indicate that kidney cancer cells must adapt to the nutrients available in the kidney, rather than changing what nutrients are available in the tissue. Future studies will be required to investigate whether this finding also applies to other types of cancer. A better understanding of how cancer cells adapt to their environments may aid the development of drugs that aim to disrupt the metabolism of tumors.

Normalizing granuloma vasculature and matrix improves drug delivery and reduces bacterial burden in tuberculosis-infected rabbits.

Host-directed therapies (HDTs) represent an emerging approach for bacterial clearance during tuberculosis (TB) infection. While most HDTs are designed and implemented for immuno-modulation, other host targets-such as nonimmune stromal components found in pulmonary granulomas-may prove equally viable. Building on our previous work characterizing and normalizing the aberrant granuloma-associated vasculature, here we demonstrate that FDA-approved therapies (bevacizumab and losartan, respectively) can be repurposed as HDTs to normalize blood vessels and extracellular matrix (ECM), improve drug delivery, and reduce bacterial loads in TB granulomas. Granulomas feature an overabundance of ECM and compressed blood vessels, both of which are effectively reduced by losartan treatment in the rabbit model of TB. Combining both HDTs promotes secretion of proinflammatory cytokines and improves anti-TB drug delivery. Finally, alone and in combination with second-line antitubercular agents (moxifloxacin or bedaquiline), these HDTs significantly reduce bacterial burden. RNA sequencing analysis of HDT-treated lung and granuloma tissues implicates up-regulated antimicrobial peptide and proinflammatory gene expression by ciliated epithelial airway cells as a putative mechanism of the observed antitubercular benefits in the absence of chemotherapy. These findings demonstrate that bevacizumab and losartan are well-tolerated stroma-targeting HDTs, normalize the granuloma microenvironment, and improve TB outcomes, providing the rationale to clinically test this combination in TB patients.

Metabolite profiling of human renal cell carcinoma reveals tissue-origin dominance in nutrient availability.

The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer driven tissue factors in shaping nutrient availability in these tumors.

Single-cell RNA sequencing of liver fine-needle aspirates captures immune diversity in the blood and liver in chronic hepatitis B patients.

BACKGROUND AND AIMS: HBV infection is restricted to the liver, where it drives exhaustion of virus-specific T and B cells and pathogenesis through dysregulation of intrahepatic immunity. Our understanding of liver-specific events related to viral control and liver damage has relied almost solely on animal models, and we lack useable peripheral biomarkers to quantify intrahepatic immune activation beyond cytokine measurement. Our objective was to overcome the practical obstacles of liver sampling using fine-needle aspiration and develop an optimized workflow to comprehensively compare the blood and liver compartments within patients with chronic hepatitis B using single-cell RNA sequencing. APPROACH AND RESULTS: We developed a workflow that enabled multi-site international studies and centralized single-cell RNA sequencing. Blood and liver fine-needle aspirations were collected, and cellular and molecular captures were compared between the Seq-Well S 3 picowell-based and the 10× Chromium reverse-emulsion droplet-based single-cell RNA sequencing technologies. Both technologies captured the cellular diversity of the liver, but Seq-Well S 3 effectively captured neutrophils, which were absent in the 10× dataset. CD8 T cells and neutrophils displayed distinct transcriptional profiles between blood and liver. In addition, liver fine-needle aspirations captured a heterogeneous liver macrophage population. Comparison between untreated patients with chronic hepatitis B and patients treated with nucleoside analogs showed that myeloid cells were highly sensitive to environmental changes while lymphocytes displayed minimal differences. CONCLUSIONS: The ability to electively sample and intensively profile the immune landscape of the liver, and generate high-resolution data, will enable multi-site clinical studies to identify biomarkers for intrahepatic immune activity in HBV and beyond.

Co-Targeting IL-6 and EGFR signaling for the treatment of schwannomatosis and associated pain.

Patients with Schwannomatosis (SWN) overwhelmingly present with intractable, debilitating chronic pain. There are no effective therapies to treat SWN. The drivers of pain response and tumor progression in SWN are not clear. The pain is not proportionally linked to tumor size and is not always relieved by tumor resection, suggesting that mechanisms other than mechanical nerve compression exist to cause pain. SWN research is limited by the lack of clinically-relevant models. Here, we established novel patient-derived xenograft (PDX) models, dorsal root ganglia (DRG) imaging model, and combined with single-cell resolution intravital imaging and RNASeq, we discovered: i) schwannomas on the peripheral nerve cause macrophage influx into the DRG, via secreting HMGB1 to directly stimulate DRG neurons to express CCL2, the key macrophage chemokine, ii) once recruited, macrophages cause pain response via overproduction of IL-6, iii) IL-6 blockade in a therapeutic setting significantly reduces pain but has modest efficacy on tumor growth, iv) EGF signaling is a potential driver of schwannoma growth and escape mechanism from anti-IL6 treatment, and v) combined IL-6 and EGFR blockade simultaneously controlled pain and tumor growth in SWN models. Our findings prompted the initiation of phase II clinical trial ( NCT05684692 ) for pain relief in patients with SWN.

Addition of Losartan to FOLFIRINOX and Chemoradiation Reduces Immunosuppression-Associated Genes, Tregs, and FOXP3+ Cancer Cells in Locally Advanced Pancreatic Cancer.

PURPOSE: Adding losartan (LOS) to FOLFIRINOX (FFX) chemotherapy followed by chemoradiation (CRT) resulted in 61% R0 surgical resection in our phase II trial in patients with locally advanced pancreatic cancer (LAPC). Here we identify potential mechanisms of benefit by assessing the effects of neoadjuvant LOS on the tumor microenvironment. EXPERIMENTAL DESIGN: We performed a gene expression and immunofluorescence (IF) analysis using archived surgical samples from patients treated with LOS+FFX+CRT (NCT01821729), FFX+CRT (NCT01591733), or surgery upfront, without any neoadjuvant therapy. We also conducted a longitudinal analysis of multiple biomarkers in the plasma of treated patients. RESULTS: In comparison with FFX+CRT, LOS+FFX+CRT downregulated immunosuppression and pro-invasion genes. Overall survival (OS) was associated with dendritic cell (DC) and antigen presentation genes for patients treated with FFX+CRT, and with immunosuppression and invasion genes or DC- and blood vessel-related genes for those treated with LOS+FFX+CRT. Furthermore, LOS induced specific changes in circulating levels of IL-8, sTie2, and TGF-ß. IF revealed significantly less residual disease in lesions treated with LOS+FFX+CRT. Finally, patients with a complete/near complete pathologic response in the LOS+FFX+CRT-treated group had reduced CD4+FOXP3+ regulatory T cells (Tregs), fewer immunosuppressive FOXP3+ cancer cells (C-FOXP3), and increased CD8+ T cells in pancreatic ductal adenocarcinoma lesions. CONCLUSIONS: Adding LOS to FFX+CRT reduced pro-invasion and immunosuppression-related genes, which were associated with improved OS in patients with LAPC. Lesions from responders in the LOS+FFX+CRT-treated group had reduced Tregs, decreased C-FOXP3 and increased CD8+ T cells. These findings suggest that LOS may potentiate the benefit of FFX+CRT by reducing immunosuppression.

Wnt inhibition alleviates resistance to immune checkpoint blockade in glioblastoma.

Wnt signaling plays a critical role in the progression and treatment outcome of glioblastoma (GBM). Here, we identified WNT7b as a heretofore unknown mechanism of resistance to immune checkpoint inhibition (αPD1) in GBM patients and murine models. Acquired resistance to αPD1 was found to be associated with the upregulation of Wnt7b and ß-catenin protein levels in GBM in patients and in a clinically relevant, stem-rich GBM model. Combining the porcupine inhibitor WNT974 with αPD1 prolonged the survival of GBM-bearing mice. However, this combination had a dichotomous response, with a subset of tumors showing refractoriness. WNT974 and αPD1 expanded a subset of DC3-like dendritic cells (DCs) and decreased the granulocytic myeloid-derived suppressor cells (gMDSCs) in the tumor microenvironment (TME). By contrast, monocytic MDSCs (mMDSCs) increased, while T-cell infiltration remained unchanged, suggesting potential TME-mediated resistance. Our preclinical findings warrant the testing of Wnt7b/ß-catenin combined with αPD1 in GBM patients with elevated Wnt7b/ß-catenin signaling.

Aldosterone in chronic kidney disease and renal outcomes.

AIMS: Randomized controlled trials have demonstrated the efficacy of mineralocorticoid receptor (MR) antagonism in delaying chronic kidney disease (CKD) progression in diabetes; however, they have not investigated the role of aldosterone or whether these beneficial effects could be achieved in individuals without diabetes. METHODS AND RESULTS: The association between serum aldosterone concentrations and kidney disease progression was investigated among 3680 participants in the Chronic Renal Insufficiency Cohort. The primary outcome was CKD progression [defined as the composite of 50% decline in estimated glomerular filtration rate (eGFR) or end-stage kidney disease, whichever occurred first]. The associations between serum aldosterone and kidney disease outcomes were assessed using Cox proportional hazard models. At baseline, higher aldosterone concentrations were associated with a lower eGFR, lower serum potassium, greater urinary potassium, and protein excretion. Over a median follow-up of 9.6 years, 1412 participants developed CKD progression. In adjusted models, each doubling of serum aldosterone was associated with a 11% increased risk of CKD progression [hazard ratio (HR) 1.11, 95% confidence interval (CI) 1.04-1.18]. Individuals with the highest quartile of serum aldosterone had a 45% increased risk of CKD progression (HR 1.45, 95% CI 1.22-1.73) compared with the lowest quartile. The risk for CKD progression was similar regardless of whether patients had concomitant diabetes (P-interaction = 0.10). CONCLUSION: Higher serum aldosterone levels among individuals with CKD are independently associated with an increased risk for kidney disease progression, irrespective of concomitant diabetes. These findings provide mechanistic support for MR antagonists in delaying CKD progression and suggest that they may also have a role in those without diabetes.

Expression of IGF-1 receptor and GH receptor in hepatic tissue of patients with nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.

OBJECTIVE: The GH and IGF-1 axis is a candidate disease-modifying target in nonalcoholic fatty liver disease (NAFLD) given its lipolytic, anti-inflammatory and anti-fibrotic properties. IGF-1 receptor (IGF-1R) and GH receptor (GHR) expression in adult, human hepatic tissue is not well understood across the spectrum of NAFLD severity. Therefore, we sought to investigate hepatic IGF-1R and GHR expression in subjects with NAFLD utilizing gene expression analysis (GEA) and immunohistochemistry (IHC). DESIGN: GEA (n = 318) and IHC (n = 30) cohorts were identified from the Massachusetts General Hospital NAFLD Tissue Repository. GEA subjects were categorized based on histopathology as normal liver histology (NLH), steatosis only (Steatosis), nonalcoholic steatohepatitis (NASH) without fibrosis (NASH F0), and NASH with fibrosis (NASH F1-4) with GEA by the Nanostring nCounter assay. IHC subjects were matched for age, body mass index (BMI), sex, and diabetic status across three groups (n = 10 each): NLH, Steatosis, and NASH with fibrosis (NASH F1-3). IHC for IGF-1R, IGF-1 and GHR was performed on formalin-fixed, paraffin-embedded hepatic tissue samples. RESULTS: IGF-1R gene expression did not differ across NAFLD severity while IGF-1 gene expression decreased with increasing NAFLD severity, including when controlled for BMI and age. GHR expression did not differ by severity of NAFLD based on GEA or IHC. CONCLUSIONS: IGF-1R and GHR expression levels were not significantly different across NAFLD disease severity. However, expression of IGF-1 was lower with increasing severity of NAFLD. Additional research is needed regarding the contribution of the GH/IGF-1 axis to the pathophysiology of NAFLD and NASH.

Strategies to minimize heterogeneity and optimize clinical trials in Acute Respiratory Distress Syndrome (ARDS): Insights from mathematical modelling.

BACKGROUND: Mathematical modelling may aid in understanding the complex interactions between injury and immune response in critical illness. METHODS: We utilize a system biology model of COVID-19 to analyze the effect of altering baseline patient characteristics on the outcome of immunomodulatory therapies. We create example parameter sets meant to mimic diverse patient types. For each patient type, we define the optimal treatment, identify biologic programs responsible for clinical responses, and predict biomarkers of those programs. FINDINGS: Model states representing older and hyperinflamed patients respond better to immunomodulation than those representing obese and diabetic patients. The disparate clinical responses are driven by distinct biologic programs. Optimal treatment initiation time is determined by neutrophil recruitment, systemic cytokine expression, systemic microthrombosis and the renin-angiotensin system (RAS) in older patients, and by RAS, systemic microthrombosis and trans IL6 signalling for hyperinflamed patients. For older and hyperinflamed patients, IL6 modulating therapy is predicted to be optimal when initiated very early (<4th day of infection) and broad immunosuppression therapy (corticosteroids) is predicted to be optimally initiated later in the disease (7th - 9th day of infection). We show that markers of biologic programs identified by the model correspond to clinically identified markers of disease severity. INTERPRETATION: We demonstrate that modelling of COVID-19 pathobiology can suggest biomarkers that predict optimal response to a given immunomodulatory treatment. Mathematical modelling thus constitutes a novel adjunct to predictive enrichment and may aid in the reduction of heterogeneity in critical care trials. FUNDING: C.V. received a Marie Sklodowska Curie Actions Individual Fellowship (MSCA-IF-GF-2020-101028945). R.K.J.'s research is supported by R01-CA208205, and U01-CA 224348, R35-CA197743 and grants from the National Foundation for Cancer Research, Jane's Trust Foundation, Advanced Medical Research Foundation and Harvard Ludwig Cancer Center. No funder had a role in production or approval of this manuscript.

Distinct Hepatic Gene-Expression Patterns of NAFLD in Patients With Obesity.

Approaches to manage nonalcoholic fatty liver disease (NAFLD) are limited by an incomplete understanding of disease pathogenesis. The aim of this study was to identify hepatic gene-expression patterns associated with different patterns of liver injury in a high-risk cohort of adults with obesity. Using the NanoString Technologies (Seattle, WA) nCounter assay, we quantified expression of 795 genes, hypothesized to be involved in hepatic fibrosis, inflammation, and steatosis, in liver tissue from 318 adults with obesity. Liver specimens were categorized into four distinct NAFLD phenotypes: normal liver histology (NLH), steatosis only (steatosis), nonalcoholic steatohepatitis without fibrosis (NASH F0), and NASH with fibrosis stage 1-4 (NASH F1-F4). One hundred twenty-five genes were significantly increasing or decreasing as NAFLD pathology progressed. Compared with NLH, NASH F0 was characterized by increased inflammatory gene expression, such as gamma-interferon-inducible lysosomal thiol reductase (IFI30) and chemokine (C-X-C motif) ligand 9 (CXCL9), while complement and coagulation related genes, such as C9 and complement component 4 binding protein beta (C4BPB), were reduced. In the presence of NASH F1-F4, extracellular matrix degrading proteinases and profibrotic/scar deposition genes, such as collagens and transforming growth factor beta 1 (TGFB1), were simultaneously increased, suggesting a dynamic state of tissue remodeling. Conclusion: In adults with obesity, distinct states of NAFLD are associated with intrahepatic perturbations in genes related to inflammation, complement and coagulation pathways, and tissue remodeling. These data provide insights into the dynamic pathogenesis of NAFLD in high-risk individuals.

Differentiation of exhausted CD8+ T cells after termination of chronic antigen stimulation stops short of achieving functional T cell memory.

T cell exhaustion is associated with failure to clear chronic infections and malignant cells. Defining the molecular mechanisms of T cell exhaustion and reinvigoration is essential to improving immunotherapeutic modalities. Here we confirmed pervasive phenotypic, functional and transcriptional differences between memory and exhausted antigen-specific CD8+ T cells in human hepatitis C virus (HCV) infection before and after treatment. After viral cure, phenotypic changes in clonally stable exhausted T cell populations suggested differentiation toward a memory-like profile. However, functionally, the cells showed little improvement, and critical transcriptional regulators remained in the exhaustion state. Notably, T cells from chronic HCV infection that were exposed to antigen for less time because of viral escape mutations were functionally and transcriptionally more similar to memory T cells from spontaneously resolved HCV infection. Thus, the duration of T cell stimulation impacts exhaustion recovery, with antigen removal after long-term exhaustion being insufficient for the development of functional T cell memory.

Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19.

As predicting the trajectory of COVID-19 is challenging, machine learning models could assist physicians in identifying high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVID-19 patient data from the Mass General Brigham (MGB) Healthcare database, we developed and internally validated models using patients presenting to the Emergency Department (ED) between March-April 2020 (n = 3597) and further validated them using temporally distinct individuals who presented to the ED between May-August 2020 (n = 1711). We show that ensemble-based models perform better than other model types at predicting both 5-day ICU admission and 28-day mortality from COVID-19. CRP, LDH, and O2 saturation were important for ICU admission models whereas eGFR <60 ml/min/1.73 m2, and neutrophil and lymphocyte percentages were the most important variables for predicting mortality. Implementing such models could help in clinical decision-making for future infectious disease outbreaks including COVID-19.

Differentiation of exhausted CD8 T cells after termination of chronic antigen stimulation stops short of achieving functional T cell memory

T cell exhaustion is associated with failure to clear chronic infections and malignant cells. Defining the molecular mechanisms of T cell exhaustion and reinvigoration is essential to improving immunotherapeutic modalities. Analysis of antigen-specific CD8+ T cells before and after antigen removal in human hepatitis C virus (HCV) infection confirmed pervasive phenotypic, functional, and transcriptional differences between exhausted and memory CD8+ T cells. After viral cure, we observed broad phenotypic and transcriptional changes in clonally stable exhausted T-cell populations suggesting differentiation towards a memory-like profile. However, functionally, the cells showed little improvement and critical transcriptional regulators remained in the exhaustion state. Notably, T cells from chronic HCV infection that were exposed to antigen for shorter periods of time because of viral escape mutations were functionally and transcriptionally more similar to memory T cells from spontaneously resolved acute HCV infection. Thus, duration of T cell stimulation impacts the ability to recover from exhaustion, as antigen removal after long-term T cell exhaustion is insufficient for the development of key T cell memory characteristics.

Tissue-Resident Memory T Cells in the Liver-Unique Characteristics of Local Specialists.

T cells play an important role to build up an effective immune response and are essential in the eradication of pathogens. To establish a long-lasting protection even after a re-challenge with the same pathogen, some T cells differentiate into memory T cells. Recently, a certain subpopulation of memory T cells at different tissue-sites of infection was detected-tissue-resident memory T cells (TRM cells). These cells can patrol in the tissue in order to encounter their cognate antigen to establish an effective protection against secondary infection. The liver as an immunogenic organ is exposed to a variety of pathogens entering the liver through the systemic blood circulation or via the portal vein from the gut. It could be shown that intrahepatic TRM cells can reside within the liver tissue for several years. Interestingly, hepatic TRM cell differentiation requires a distinct cytokine milieu. In addition, TRM cells express specific surface markers and transcription factors, which allow their identification delimited from their circulating counterparts. It could be demonstrated that liver TRM cells play a particular role in many liver diseases such as hepatitis B and C infection, non-alcoholic fatty liver disease and even play a role in the development of hepatocellular carcinoma and in building long-lasting immune responses after vaccination. A better understanding of intrahepatic TRM cells is critical to understand the pathophysiology of many liver diseases and to identify new potential drug targets for the development of novel treatment strategies.

Predicting the recombination potential of severe acute respiratory syndrome coronavirus 2 and Middle East respiratory syndrome coronavirus.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) recently emerged to cause widespread infections in humans. SARS-CoV-2 infections have been reported in the Kingdom of Saudi Arabia, where Middle East respiratory syndrome coronavirus (MERS-CoV) causes seasonal outbreaks with a case fatality rate of ~37 %. Here we show that there exists a theoretical possibility of future recombination events between SARS-CoV-2 and MERS-CoV RNA. Through computational analyses, we have identified homologous genomic regions within the ORF1ab and S genes that could facilitate recombination, and have analysed co-expression patterns of the cellular receptors for SARS-CoV-2 and MERS-CoV, ACE2 and DPP4, respectively, to identify human anatomical sites that could facilitate co-infection. Furthermore, we have investigated the likely susceptibility of various animal species to MERS-CoV and SARS-CoV-2 infection by comparing known virus spike protein-receptor interacting residues. In conclusion, we suggest that a recombination between SARS-CoV-2 and MERS-CoV RNA is possible and urge public health laboratories in high-risk areas to develop diagnostic capability for the detection of recombined coronaviruses in patient samples.

Prognostic machine learning models for COVID-19 to facilitate decision making.

An increasing number of COVID-19 cases worldwide has overwhelmed the healthcare system. Physicians are struggling to allocate resources and to focus their attention on high-risk patients, partly because early identification of high-risk individuals is difficult. This can be attributed to the fact that COVID-19 is a novel disease and its pathogenesis is still partially understood. However, machine learning algorithms have the capability to analyse a large number of parameters within a short period of time to identify the predictors of disease outcome. Implementing such an algorithm to predict high-risk individuals during the early stages of infection would be helpful in decision making for clinicians such that irreversible damage could be prevented. Here, we propose recommendations to develop prognostic machine learning models using electronic health records so that a real-time risk score can be developed for COVID-19.

Selection of viral variants during persistent infection of insectivorous bat cells with Middle East respiratory syndrome coronavirus.

Coronaviruses that cause severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) are speculated to have originated in bats. The mechanisms by which these viruses are maintained in individuals or populations of reservoir bats remain an enigma. Mathematical models have predicted long-term persistent infection with low levels of periodic shedding as a likely route for virus maintenance and spillover from bats. In this study, we tested the hypothesis that bat cells and MERS coronavirus (CoV) can co-exist in vitro. To test our hypothesis, we established a long-term coronavirus infection model of bat cells that are persistently infected with MERS-CoV. We infected cells from Eptesicus fuscus with MERS-CoV and maintained them in culture for at least 126 days. We characterized the persistently infected cells by detecting virus particles, protein and transcripts. Basal levels of type I interferon in the long-term infected bat cells were higher, relative to uninfected cells, and disrupting the interferon response in persistently infected bat cells increased virus replication. By sequencing the whole genome of MERS-CoV from persistently infected bat cells, we identified that bat cells repeatedly selected for viral variants that contained mutations in the viral open reading frame 5 (ORF5) protein. Furthermore, bat cells that were persistently infected with ΔORF5 MERS-CoV were resistant to superinfection by wildtype virus, likely due to reduced levels of the virus receptor, dipeptidyl peptidase 4 (DPP4) and higher basal levels of interferon in these cells. In summary, our study provides evidence for a model of coronavirus persistence in bats, along with the establishment of a unique persistently infected cell culture model to study MERS-CoV-bat interactions.

Hepatitis C virus-specific CD4+ T cell phenotype and function in different infection outcomes.

CD4+ T cell failure is a hallmark of chronic hepatitis C virus (HCV) infection. However, the mechanisms underlying the impairment and loss of virus-specific CD4+ T cells in persisting HCV infection remain unclear. Here we examined HCV-specific CD4+ T cells longitudinally during acute infection with different infection outcomes. We found that HCV-specific CD4+ T cells are characterized by expression of a narrower range of T cell inhibitory receptors compared with CD8+ T cells, with initially high expression levels of PD-1 and CTLA-4 that were associated with negative regulation of proliferation in all patients, irrespective of outcome. In addition, HCV-specific CD4+ T cells were phenotypically similar during early resolving and persistent infection and secreted similar levels of cytokines. However, upon viral control, CD4+ T cells quickly downregulated inhibitory receptors and differentiated into long-lived memory cells. In contrast, persisting viremia continued to drive T cell activation and PD-1 and CTLA-4 expression, and blocked T cell differentiation, until the cells quickly disappeared from the circulation. Our data support an important and physiological role for inhibitory receptor-mediated regulation of CD4+ T cells in early HCV infection, irrespective of outcome, with persistent HCV viremia leading to sustained upregulation of PD-1 and CTLA-4.

Immune System Modulation and Viral Persistence in Bats: Understanding Viral Spillover.

Bats harbor a myriad of viruses and some of these viruses may have spilled over to other species including humans. Spillover events are rare and several factors must align to create the "perfect storm" that would ultimately lead to a spillover. One of these factors is the increased shedding of virus by bats. Several studies have indicated that bats have unique defense mechanisms that allow them to be persistently or latently infected with viruses. Factors leading to an increase in the viral load of persistently infected bats would facilitate shedding of virus. This article reviews the unique nature of bat immune defenses that regulate virus replication and the various molecular mechanisms that play a role in altering the balanced bat⁻virus relationship.