Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus.

Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses.

Geospatially-resolved public-health surveillance via wastewater sequencing.

Wastewater, which contains everything from pathogens to pollutants, is a geospatially-and temporally-linked microbial fingerprint of a given population. As a result, it can be leveraged for monitoring multiple dimensions of public health across locales and time. Here, we integrate targeted and bulk RNA sequencing (n=1,419 samples) to track the viral, bacterial, and functional content over geospatially distinct areas within Miami Dade County from 2020-2022. First, we used targeted amplicon sequencing (n=966) to track diverse SARS-CoV-2 variants across space and time, and we found a tight correspondence with clinical caseloads from University students (N = 1,503) and Miami-Dade County hospital patients (N = 3,939 patients), as well as an 8-day earlier detection of the Delta variant in wastewater vs. in patients. Additionally, in 453 metatranscriptomic samples, we demonstrate that different wastewater sampling locations have clinically and public-health-relevant microbiota that vary as a function of the size of the human population they represent. Through assembly, alignment-based, and phylogenetic approaches, we also detect multiple clinically important viruses (e.g., norovirus ) and describe geospatial and temporal variation in microbial functional genes that indicate the presence of pollutants. Moreover, we found distinct profiles of antimicrobial resistance (AMR) genes and virulence factors across campus buildings, dorms, and hospitals, with hospital wastewater containing a significant increase in AMR abundance. Overall, this effort lays the groundwork for systematic characterization of wastewater to improve public health decision making and a broad platform to detect emerging pathogens.

Predicting COVID-19 cases using SARS-CoV-2 RNA in air, surface swab and wastewater samples.

Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples, which can serve as a noninvasive method of infectious disease surveillance. The research evaluates the efficacy of environmental monitoring of SARS-CoV-2 RNA in air, surface swabs and wastewater to predict COVID-19 cases. Using a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory housing roughly 500 students from March to May 2021 at the University of Miami, Coral Gables, FL. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 concentration in environmental samples was quantified using Volcano 2nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and COVID-19 cases. SARS-CoV-2 was detected in air, surface swab and wastewater samples on 52 (63.4 %), 40 (50.0 %) and 57 (68.6 %) days, respectively. On 19 (24 %) of 78 days SARS-CoV-2 was detected in all three sample types. COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100 %), 9 (81.8 %) and 8 (72.7 %) days in air, surface swab and wastewater samples, respectively. SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases and a 3-day lead indicator for a potential outbreak at the dormitory building scale. Proactive environmental surveillance of SARS-CoV-2 or other pathogens in multiple environmental media has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks within communities.

Expanding a Wastewater-Based Surveillance Methodology for DNA Isolation from a Workflow Optimized for SARS-CoV-2 RNA Quantification.

Wastewater-based surveillance (WBS) is a noninvasive, epidemiological strategy for assessing the spread of COVID-19 in communities. This strategy was based upon wastewater RNA measurements of the viral target, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The utility of WBS for assessing the spread of COVID-19 has motivated research to measure targets beyond SARS-CoV-2, including pathogens containing DNA. The objective of this study was to establish the necessary steps for isolating DNA from wastewater by modifying a long-standing RNA-specific extraction workflow optimized for SARS-CoV-2 detection. Modifications were made to the sample concentration process and included an evaluation of bead bashing prior to the extraction of either DNA or RNA. Results showed that bead bashing reduced detection of RNA from wastewater but improved recovery of DNA as assessed by quantitative polymerase chain reaction (qPCR). Bead bashing is therefore not recommended for the quantification of RNA viruses using qPCR. Whereas for Mycobacterium bacterial DNA isolation, bead bashing was necessary for improving qPCR quantification. Overall, we recommend 2 separate workflows, one for RNA viruses that does not include bead bashing and one for other microbes that use bead bashing for DNA isolation. The experimentation done here shows that current-standing WBS program methodologies optimized for SARS-CoV-2 need to be modified and reoptimized to allow for alternative pathogens to be readily detected and monitored, expanding its utility as a tool for public health assessment.

Correlative analysis of wastewater trends with clinical cases and hospitalizations through five dominant variant waves of COVID-19.

Wastewater-based epidemiology (WBE) has been utilized to track community infections of Coronavirus Disease 2019 (COVID-19) by detecting RNA of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), within samples collected from wastewater. The correlations between community infections and wastewater measurements of the RNA can potentially change as SARS-CoV-2 evolves into new variations by mutating. This study analyzed SARS-CoV-2 RNA, and indicators of human waste in wastewater from two sewersheds of different scales (University of Miami (UM) campus and Miami-Dade County Central District wastewater treatment plant (CDWWTP)) during five internally defined COVID-19 variant dominant periods (Initial, Pre-Delta, Delta, Omicron and Post-Omicron wave). SARS-CoV-2 RNA quantities were compared against COVID-19 clinical cases and hospitalizations to evaluate correlations with wastewater SARS-CoV-2 RNA. Although correlations between documented clinical cases and hospitalizations were high, prevalence for a given wastewater SARS-CoV-2 level varied depending upon the variant analyzed. The correlative relationship was significantly steeper (more cases per level found in wastewater) for the Omicron-dominated period. For hospitalization, the relationships were steepest for the Initial wave, followed by the Delta wave with flatter slopes during all other waves. Overall results were interpreted in the context of SARS-CoV-2 virulence and vaccination rates among the community.

Relationships between SARS-CoV-2 in Wastewater and COVID-19 Clinical Cases and Hospitalizations, with and without Normalization against Indicators of Human Waste.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), ß-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant. Wastewater data were combined with complementary COVID-19 case tracking to evaluate the efficiency of wastewater surveillance for forecasting new COVID-19 cases and, for the larger scale, hospitalizations. Results show that the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in improved correlations with COVID-19 cases for campus data using volcano second generation (V2G)-qPCR chemistry (r s = 0.69 without normalization, r s = 0.73 with normalization). Mixed results were obtained for normalization by PMMoV for samples collected at the community scale. Overall benefits from normalizing with measures of human waste depend upon qPCR chemistry and improves with smaller sewershed scale. We recommend further studies that evaluate the efficacy of additional normalization targets.

A pilot study to troubleshoot quality control metrics when assessing circulating miRNA expression data reproducibility across study sites.

BACKGROUND: Given the growing interest in using microRNAs (miRNAs) as biomarkers of early disease, establishment of robust protocols and platforms for miRNA quantification in biological fluids is critical. OBJECTIVE: The goal of this multi-center pilot study was to evaluate the reproducibility of NanoString nCounter™ technology when analyzing the abundance of miRNAs in plasma and cystic fluid from patients with pancreatic lesions. METHODS: Using sample triplicates analyzed across three study sites, we assessed potential sources of variability (RNA isolation, sample processing/ligation, hybridization, and lot-to-lot variability) that may contribute to suboptimal reproducibility of miRNA abundance when using nCounter™, and evaluated expression of positive and negative controls, housekeeping genes, spike-in genes, and miRNAs. RESULTS: Positive controls showed a high correlation across samples from each site (median correlation coefficient, r> 0.9). Most negative control probes had expression levels below background. Housekeeping and spike-in genes each showed a similar distribution of expression and comparable pairwise correlation coefficients of replicate samples across sites. A total of 804 miRNAs showed a similar distribution of pairwise correlation coefficients between replicate samples (p= 0.93). After normalization and selecting miRNAs with expression levels above zero in 80% of samples, 55 miRNAs were identified; heatmap and principal component analysis revealed similar expression patterns and clustering in replicate samples. CONCLUSIONS: Findings from this pilot investigation suggest the nCounter platform can yield reproducible results across study sites. This study underscores the importance of implementing quality control procedures when designing multi-center evaluations of miRNA abundance.

COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples.

Importance: Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples. Analysis of these samples can be employed for noninvasive surveillance of infectious diseases. Objective: To evaluate the efficacy of environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for predicting COVID-19 cases in a college dormitory. Design: Using a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory from March to May 2021. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 in environmental samples was concentrated with electronegative filtration and quantified using Volcano 2 nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and clinically diagnosed COVID-19 cases. Setting: This study was conducted in a residential dormitory at the University of Miami, Coral Gables campus, FL, USA. The dormitory housed about 500 students. Participants: Students from the dormitory were randomly screened, for COVID-19 for 2-3 days / week while entering or exiting the dormitory. Main Outcome: Clinically diagnosed COVID-19 cases were of our main interest. We hypothesized that SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases in the dormitory, and SARS-CoV-2 can be detected in the environmental samples several days prior to the clinical diagnosis of COVID-19 cases. Results: SARS-CoV-2 genomic footprints were detected in air, surface swab and wastewater samples on 52 (63.4%), 40 (50.0%) and 57 (68.6%) days, respectively, during the study period. On 19 (24%) of 78 days SARS-CoV-2 was detected in all three sample types. Clinically diagnosed COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100%), 9 (81.8%) and 8 (72.7%) days in air, surface swab and wastewater samples, respectively. Conclusion: Proactive environmental surveillance of SARS-CoV-2 or other pathogens in a community/public setting has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks. Key Points: Question: How effective is environmental surveillance of SARS-CoV-2 in public places for early detection of COVID-19 cases in a community?Findings: All clinically confirmed COVID-19 cases were predicted with the aid of 2 day lagged SARS-CoV-2 in environmental samples in a college dormitory. However, the prediction efficiency varied by sample type: best prediction by air samples, followed by wastewater and surface swab samples. SARS-CoV-2 was also detected in these samples even on days without any reported cases of COVID-19, suggesting underreporting of COVID-19 cases.Meaning: SARS-CoV-2 can be detected in environmental samples several days prior to clinical reporting of COVID-19 cases. Thus, proactive environmental surveillance of microbiome in public places can serve as a mean for early detection of location-time specific outbreaks of infectious diseases. It can also be used for underreporting of infectious diseases.

Mitochondrial DNA sequence variation and risk of glioma.

BACKGROUND: Malignant gliomas are the most common primary adult brain tumors, with a poor prognosis and ill-defined etiology. Mitochondrial DNA (mtDNA) sequence variation has been linked with certain cancers; however, research on glioma is lacking. METHODS: We examined the association of common (minor allele frequency ≥ 5%) germline mtDNA variants and haplogroups with glioma risk in 1,566 glioma cases and 1,017 controls from a US case-control study, and 425 glioma cases and 1,534 matched controls from the UK Biobank cohort (UKB). DNA samples were genotyped using the UK Biobank array that included a set of common and rare mtDNA variants. Risk associations were examined separately for glioblastoma (GBM) and lower grade tumors (non-GBM). RESULTS: In the US study, haplogroup W was inversely associated with glioma when compared with haplogroup H (OR = 0.43, 95%CI: 0.23-0.79); this association was not demonstrated in the UKB (OR = 1.07, 95%CI: 0.47-2.43). In the UKB, the variant m.3010G > A was significantly associated with GBM (OR = 1.32; 95%CI: 1.01-1.73; p = 0.04), but not non-GBM (1.23; 95%CI: 0.78-1.95; p = 0.38); no similar association was observed in the US study. In the US study, the variant m.14798 T > C, was significantly associated with non-GBM (OR = 0.72; 95%CI: 0.53-0.99), but not GBM (OR = 0.86; 95%CI: 0.66-1.11), whereas in the UKB, a positive association was observed between this variant and GBM (OR = 1.46; 95%CI: 1.06-2.02) but not non-GBM (OR = 0.92; 95%CI: 0.52-1.63). None of these associations were significant after adjustment for multiple testing. CONCLUSION: The association of inherited mtDNA variation, including rare and singleton variants, with glioma risk merits further study.

Comparison of Electronegative Filtration to Magnetic Bead-Based Concentration and V2G-qPCR to RT-qPCR for Quantifying Viral SARS-CoV-2 RNA from Wastewater.

Methods of wastewater concentration (electronegative filtration (ENF) versus magnetic bead-based concentration (MBC)) were compared for the analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), beta-2 microglobulin, and human-coronavirus OC43. Using ENF as the concentration method, two quantitative Polymerase Chain Reaction (qPCR) analytical methods were also compared: Volcano 2nd Generation (V2G)-qPCR and reverse transcriptase (RT)-qPCR measuring three different targets of the virus responsible for the COVID-19 illness (N1, modified N3, and ORF1ab). Correlations between concentration methods were strong and statistically significant for SARS-CoV-2 (r=0.77, p<0.001) and B2M (r=0.77, p<0.001). Comparison of qPCR analytical methods indicate that, on average, each method provided equivalent results with average ratios of 0.96, 0.96 and 1.02 for N3 to N1, N3 to ORF1ab, and N1 to ORF1ab and were supported by significant (p<0.001) correlation coefficients (r =0.67 for V2G (N3) to RT (N1), r =0.74 for V2G (N3) to RT (ORF1ab), r = 0.81 for RT (N1) to RT (ORF1ab)). Overall results suggest that the two concentration methods and qPCR methods provide equivalent results, although variability is observed for individual measurements. Given the equivalency of results, additional advantages and disadvantages, as described in the discussion, are to be considered when choosing an appropriate method.

Mitochondrial DNA sequence variation and risk of meningioma.

BACKGROUND: Risk factors for meningioma include female gender, African American race, high body mass index (BMI), and exposure to ionizing radiation. Although genome-wide association studies (GWAS) have identified two nuclear genome risk loci for meningioma (rs12770228 and rs2686876), the relation between mitochondrial DNA (mtDNA) sequence variants and meningioma is unknown. METHODS: We examined the association of 42 common germline mtDNA variants (minor allele frequency ≥ 5%), haplogroups, and genes with meningioma in 1080 controls and 478 meningioma cases from a case-control study conducted at medical centers in the southeastern United States. Associations were examined separately for meningioma overall and by WHO grade (n = 409 grade I and n = 69 grade II/III). RESULTS: Overall, meningioma was significantly associated with being female (OR 2.85; 95% CI 2.21-3.69), self-reported African American race (OR 2.38, 95% CI 1.41-3.99), and being overweight (OR 1.48; 95% CI 1.11-1.97) or obese (OR 1.70; 95% CI 1.25-2.31). The variant m.16362T > C (rs62581341) in the mitochondrial control region was positively associated with grade II/III meningiomas (OR 2.33; 95% CI 1.14-4.77), but not grade I tumors (OR 0.99; 95% CI 0.64-1.53). Haplogroup L, a marker for African ancestry, was associated with meningioma overall (OR 2.92; 95% CI 1.01-8.44). However, after stratifying by self-reported race, this association was only apparent among the few self-reported Caucasians with this haplogroup (OR 6.35; 95% CI 1.56-25.9). No other mtDNA variant, haplogroup, or gene was associated with meningioma. CONCLUSION: Common mtDNA variants and major mtDNA haplogroups do not appear to have associations with the odds of developing meningioma.

The Effect of JAK1/2 Inhibitors on HIV Reservoir Using Primary Lymphoid Cell Model of HIV Latency.

HIV eradication is hindered by the existence of latent HIV reservoirs in CD4+ T cells. Therapeutic strategies targeting latent cells are required to achieve a functional cure, however the study of latently infected cells from HIV infected persons is extremely challenging due to the lack of biomarkers that uniquely characterize them. In this study, the dual reporter virus HIVGKO was used to investigate latency establishment and maintenance in lymphoid-derived CD4+ T cells. Single cell technologies to evaluate protein expression, host gene expression, and HIV transcript expression were integrated to identify and analyze latently infected cells. FDA-approved, JAK1/2 inhibitors were tested in this system as a potential therapeutic strategy to target the latent reservoir. Latent and productively infected tonsillar CD4+ T cells displayed similar activation profiles as measured by expression of CD69, CD25, and HLADR, however latent cells showed higher CXCR5 expression 3 days post-infection. Single cell analysis revealed a small set of genes, including HIST1-related genes and the inflammatory cytokine, IL32, that were upregulated in latent compared to uninfected and productively infected cells suggesting a role for these molecular pathways in persistent HIV infection. In vitro treatment of HIV-infected CD4+ T cells with physiological concentrations of JAK1/2 inhibitors, ruxolitinib and baricitinib, used in clinical settings to target inflammation, reduced latent and productive infection events when added 24 hr after infection and blocked HIV reactivation from latent cells. Our methods using an established model of HIV latency and lymphoid-derived cells shed light on the biology of latency in a crucial anatomical site for HIV persistence and provides key insights about repurposing baricitinib or ruxolitinib to target the HIV reservoir.

Lessons learned from SARS-CoV-2 measurements in wastewater.

Standardized protocols for wastewater-based surveillance (WBS) for the RNA of SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, are being developed and refined worldwide for early detection of disease outbreaks. We report here on lessons learned from establishing a WBS program for SARS-CoV-2 integrated with a human surveillance program for COVID-19. We have established WBS at three campuses of a university, including student residential dormitories and a hospital that treats COVID-19 patients. Lessons learned from this WBS program address the variability of water quality, new detection technologies, the range of detectable viral loads in wastewater, and the predictive value of integrating environmental and human surveillance data. Data from our WBS program indicated that water quality was statistically different between sewer sampling sites, with more variability observed in wastewater coming from individual buildings compared to clusters of buildings. A new detection technology was developed based upon the use of a novel polymerase called V2G. Detectable levels of SARS-CoV-2 in wastewater varied from 102 to 106 genomic copies (gc) per liter of raw wastewater (L). Integration of environmental and human surveillance data indicate that WBS detection of 100 gc/L of SARS-CoV-2 RNA in wastewater was associated with a positivity rate of 4% as detected by human surveillance in the wastewater catchment area, though confidence intervals were wide (ß ~ 8.99 ∗ ln(100); 95% CI = 0.90-17.08; p < 0.05). Our data also suggest that early detection of COVID-19 surges based on correlations between viral load in wastewater and human disease incidence could benefit by increasing the wastewater sample collection frequency from weekly to daily. Coupling simpler and faster detection technology with more frequent sampling has the potential to improve the predictive potential of using WBS of SARS-CoV-2 for early detection of the onset of COVID-19.

Early ART initiation during infancy preserves natural killer cells in young European adolescents living with HIV (CARMA cohort).

INTRODUCTION: HIV infection causes pathological changes in the natural killer (NK) cell compartment that can be only partially restored by antiretroviral therapy (ART). We investigated NK cells phenotype and function in children with perinatally acquired HIV (PHIV) and long-term viral control (five years) due to effective ART in a multicentre cross-sectional European study (CARMA, EPIICAL consortium). The impact of age at ART start and viral reservoir was also evaluated. METHODS: Peripheral blood mononuclear cells (PBMCs) from 40 PHIV who started ART within two years of life (early treated patients (ET), ≤6 months; late treated patients (LT), > 6 months), with at least five years of HIV-1 suppression (<40 HIV copies/mL), were collected between November 2017 and August 2018. NK phenotype and function were analysed by flow cytometry and transcriptional profile of PBMCs by RNA-Seq. HIV-1 DNA was measured by real-time polymerase chain reaction (Data were analysed by Spearman correlation plots and multivariable Poisson regression model (adjusted for baseline %CD4 and RNA HIV viral load and for age at ART start as an interaction term, either ET or LT) to explore the association between NK cell parameters and HIV reservoir modulated by age at ART start. RESULTS: A significantly higher frequency of CD56neg NK cells was found in LT compared with ET. We further found in LT a positive correlation of CD56neg NK cells with HIV-1 DNA. LT also displayed increased expression of the NKG2D and NKp46 activating receptors and perforin compared with ET. Moreover, CD107a+ and IFN-γ+ frequencies in non-stimulated NK were associated with HIV-1 DNA in LT patients. Finally, RNA-Seq analysis showed in LT an up-regulation of genes related to NK-activating pathways and susceptibility to apoptosis compared with ET. CONCLUSIONS: We show that early initiation of ART during infancy preserves the NK compartment and is associated with lower HIV-1 reservoir. Such condition persists over adolescence due to long-term viral control achieved through effective ART.

Impact of Early Antiretroviral Therapy Initiation on HIV-Specific CD4 and CD8 T Cell Function in Perinatally Infected Children.

Early initiation of antiretroviral therapy (ART) in vertically HIV-infected children limits the size of the virus reservoir, but whether the time of treatment initiation (TI) can durably impact host immune responses associated with HIV infection is still unknown. This study was conducted in PBMC of 20 HIV-infected virally suppressed children on ART (mean age 9.4 y), classified as early treated (ET; age at ART initiation ≤0.5 y, n = 14) or late treated (LT; age at ART initiation 1-10 y, n = 6). Frequencies and functions of Ag-specific CD4 (CD40L+) and CD8 (CD69+) T cells were evaluated by intracellular IL-2, IFN-γ, and TNF-α production with IL-21 in CD4 or CD107a, granzyme B and perforin in CD8 T cells following stimulation with HIV gp140 protein (ENV) or GAG peptides by multiparameter flow cytometry. ET showed a higher proportion of cytokine-producing ENV- and GAG-specific CD4 and CD8 T cells compared with LT. In particular, ET were enriched in polyfunctional T cells. RNA sequencing analysis showed upregulation of immune activation pathways in LT compared with ET. Our results suggest that timing of TI in HIV-infected children has a long-term and measurable impact on the quality of the HIV-specific T cell immune responses and transcriptional profiles of PBMC, reinforcing the importance of early TI.

Leveraging transcriptional dynamics to improve BRAF inhibitor responses in melanoma.

BACKGROUND: Melanoma is a heterogeneous tumour, but the impact of this heterogeneity upon therapeutic response is not well understood. METHODS: Single cell mRNA analysis was used to define the transcriptional heterogeneity of melanoma and its dynamic response to BRAF inhibitor therapy and treatment holidays. Discrete transcriptional states were defined in cell lines and melanoma patient specimens that predicted initial sensitivity to BRAF inhibition and the potential for effective re-challenge following resistance. A mathematical model was developed to maintain competition between the drug-sensitive and resistant states, which was validated in vivo. FINDINGS: Our analyses showed melanoma cell lines and patient specimens to be composed of >3 transcriptionally distinct states. The cell state composition was dynamically regulated in response to BRAF inhibitor therapy and drug holidays. Transcriptional state composition predicted for therapy response. The differences in fitness between the different transcriptional states were leveraged to develop a mathematical model that optimized therapy schedules to retain the drug sensitive population. In vivo validation demonstrated that the personalized adaptive dosing schedules outperformed continuous or fixed intermittent BRAF inhibitor schedules. INTERPRETATION: Our study provides the first evidence that transcriptional heterogeneity at the single cell level predicts for initial BRAF inhibitor sensitivity. We further demonstrate that manipulating transcriptional heterogeneity through personalized adaptive therapy schedules can delay the time to resistance. FUNDING: This work was funded by the National Institutes of Health. The funder played no role in assembly of the manuscript.

Drug and disease signature integration identifies synergistic combinations in glioblastoma.

Glioblastoma (GBM) is the most common primary adult brain tumor. Despite extensive efforts, the median survival for GBM patients is approximately 14 months. GBM therapy could benefit greatly from patient-specific targeted therapies that maximize treatment efficacy. Here we report a platform termed SynergySeq to identify drug combinations for the treatment of GBM by integrating information from The Cancer Genome Atlas (TCGA) and the Library of Integrated Network-Based Cellular Signatures (LINCS). We identify differentially expressed genes in GBM samples and devise a consensus gene expression signature for each compound using LINCS L1000 transcriptional profiling data. The SynergySeq platform computes disease discordance and drug concordance to identify combinations of FDA-approved drugs that induce a synergistic response in GBM. Collectively, our studies demonstrate that combining disease-specific gene expression signatures with LINCS small molecule perturbagen-response signatures can identify preclinical combinations for GBM, which can potentially be tested in humans.

Author Correction: MitoTALEN reduces mutant mtDNA load and restores tRNAAla levels in a mouse model of heteroplasmic mtDNA mutation.

In the version of this article originally published, there was an error in Fig. 1a. The m.5024C>T mutation, shown as a green T, was displaced by one base. The error has been corrected in the print, HTML and PDF versions of this article.

MitoTALEN reduces mutant mtDNA load and restores tRNAAla levels in a mouse model of heteroplasmic mtDNA mutation.

Mutations in the mitochondrial DNA (mtDNA) are responsible for several metabolic disorders, commonly involving muscle and the central nervous system1. Because of the critical role of mtDNA in oxidative phosphorylation, the majority of pathogenic mtDNA mutations are heteroplasmic, co-existing with wild-type molecules1. Using a mouse model with a heteroplasmic mtDNA mutation2, we tested whether mitochondrial-targeted TALENs (mitoTALENs)3,4 could reduce the mutant mtDNA load in muscle and heart. AAV9-mitoTALEN was administered via intramuscular, intravenous, and intraperitoneal injections. Muscle and heart were efficiently transduced and showed a robust reduction in mutant mtDNA, which was stable over time. The molecular defect, namely a decrease in transfer RNAAla levels, was restored by the treatment. These results showed that mitoTALENs, when expressed in affected tissues, could revert disease-related phenotypes in mice.

mitoTev-TALE: a monomeric DNA editing enzyme to reduce mutant mitochondrial DNA levels.

Pathogenic mitochondrial DNA (mtDNA) mutations often co-exist with wild-type molecules (mtDNA heteroplasmy). Phenotypes manifest when the percentage of mutant mtDNA is high (70-90%). Previously, our laboratory showed that mitochondria-targeted transcription activator-like effector nucleases (mitoTALENs) can eliminate mutant mtDNA from heteroplasmic cells. However, mitoTALENs are dimeric and relatively large, making it difficult to package their coding genes into viral vectors, limiting their clinical application. The smaller monomeric GIY-YIG homing nuclease from T4 phage (I-TevI) provides a potential alternative. We tested whether molecular hybrids (mitoTev-TALEs) could specifically bind and cleave mtDNA of patient-derived cybrids harboring different levels of the m.8344A>G mtDNA point mutation, associated with myoclonic epilepsy with ragged-red fibers (MERRF). We tested two mitoTev-TALE designs, one of which robustly shifted the mtDNA ratio toward the wild type. When this mitoTev-TALE was tested in a clone with high levels of the MERRF mutation (91% mutant), the shift in heteroplasmy resulted in an improvement of oxidative phosphorylation function. mitoTev-TALE provides an effective architecture for mtDNA editing that could facilitate therapeutic delivery of mtDNA editing enzymes to affected tissues.