Sensory Nerves Impede the Formation of Tertiary Lymphoid Structures and Development of Protective Antimelanoma Immune Responses.

Peripheral neurons comprise a critical component of the tumor microenvironment (TME). The role of the autonomic innervation in cancer has been firmly established. However, the effect of the afferent (sensory) neurons on tumor progression remains unclear. Utilizing surgical and chemical skin sensory denervation methods, we showed that afferent neurons supported the growth of melanoma tumors in vivo and demonstrated that sensory innervation limited the activation of effective antitumor immune responses. Specifically, sensory ablation led to improved leukocyte recruitment into tumors, with decreased presence of lymphoid and myeloid immunosuppressive cells and increased activation of T-effector cells within the TME. Cutaneous sensory nerves hindered the maturation of intratumoral high endothelial venules and limited the formation of mature tertiary lymphoid-like structures containing organized clusters of CD4+ T cells and B cells. Denervation further increased T-cell clonality and expanded the B-cell repertoire in the TME. Importantly, CD8a depletion prevented denervation-dependent antitumor effects. Finally, we observed that gene signatures of inflammation and the content of neuron-associated transcripts inversely correlated in human primary cutaneous melanomas, with the latter representing a negative prognostic marker of patient overall survival. Our results suggest that tumor-associated sensory neurons negatively regulate the development of protective antitumor immune responses within the TME, thereby defining a novel target for therapeutic intervention in the melanoma setting.

Technology dictates algorithms: recent developments in read alignment.

Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today's diverse array of alignment methods. We provide a systematic survey of algorithmic foundations and methodologies across 107 alignment methods, for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. We discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology.

Inference of mutability landscapes of tumors from single cell sequencing data.

One of the hallmarks of cancer is the extremely high mutability and genetic instability of tumor cells. Inherent heterogeneity of intra-tumor populations manifests itself in high variability of clone instability rates. Analogously to fitness landscapes, the instability rates of clonal populations form their mutability landscapes. Here, we present MULAN (MUtability LANdscape inference), a maximum-likelihood computational framework for inference of mutation rates of individual cancer subclones using single-cell sequencing data. It utilizes the partial information about the orders of mutation events provided by cancer mutation trees and extends it by inferring full evolutionary history and mutability landscape of a tumor. Evaluation of mutation rates on the level of subclones rather than individual genes allows to capture the effects of genomic interactions and epistasis. We estimate the accuracy of our approach and demonstrate that it can be used to study the evolution of genetic instability and infer tumor evolutionary history from experimental data. MULAN is available at https://github.com/compbel/MULAN.

Inference of clonal selection in cancer populations using single-cell sequencing data.

SUMMARY: Intra-tumor heterogeneity is one of the major factors influencing cancer progression and treatment outcome. However, evolutionary dynamics of cancer clone populations remain poorly understood. Quantification of clonal selection and inference of fitness landscapes of tumors is a key step to understanding evolutionary mechanisms driving cancer. These problems could be addressed using single-cell sequencing (scSeq), which provides an unprecedented insight into intra-tumor heterogeneity allowing to study and quantify selective advantages of individual clones. Here, we present Single Cell Inference of FItness Landscape (SCIFIL), a computational tool for inference of fitness landscapes of heterogeneous cancer clone populations from scSeq data. SCIFIL allows to estimate maximum likelihood fitnesses of clone variants, measure their selective advantages and order of appearance by fitting an evolutionary model into the tumor phylogeny. We demonstrate the accuracy our approach, and show how it could be applied to experimental tumor data to study clonal selection and infer evolutionary history. SCIFIL can be used to provide new insight into the evolutionary dynamics of cancer. AVAILABILITY AND IMPLEMENTATION: Its source code is available at https://github.com/compbel/SCIFIL.

GHOST: global hepatitis outbreak and surveillance technology.

BACKGROUND: Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters. Global Hepatitis Outbreak and Surveillance Technology (GHOST) is a cloud-based system enabling users, regardless of computational expertise, to analyze and visualize transmission clusters in an independent, accurate and reproducible way. RESULTS: We present and explore performance of several GHOST implemented algorithms using next-generation sequencing data experimentally obtained from hypervariable region 1 of genetically related and unrelated HCV strains. GHOST processes data from an entire MiSeq run in approximately 3 h. A panel of seven specimens was used for preparation of six repeats of MiSeq libraries. Testing sequence data from these libraries by GHOST showed a consistent transmission linkage detection, testifying to high reproducibility of the system. Lack of linkage among genetically unrelated HCV strains and constant detection of genetic linkage between HCV strains from known transmission pairs and from follow-up specimens at different levels of MiSeq-read sampling indicate high specificity and sensitivity of GHOST in accurate detection of HCV transmission. CONCLUSIONS: GHOST enables automatic extraction of timely and relevant public health information suitable for guiding effective intervention measures. It is designed as a virtual diagnostic system intended for use in molecular surveillance and outbreak investigations rather than in research. The system produces accurate and reproducible information on HCV transmission clusters for all users, irrespective of their level of bioinformatics expertise. Improvement in molecular detection capacity will contribute to increasing the rate of transmission detection, thus providing opportunity for rapid, accurate and effective response to outbreaks of hepatitis C. Although GHOST was originally developed for hepatitis C surveillance, its modular structure is readily applicable to other infectious diseases. Worldwide availability of GHOST for the detection of HCV transmissions will foster deeper involvement of public health researchers and practitioners in hepatitis C outbreak investigation.

Increased Mitochondrial Genetic Diversity in Persons Infected With Hepatitis C Virus.

BACKGROUND & AIMS: The host genetic environment contributes significantly to the outcomes of hepatitis C virus (HCV) infection and therapy response, but little is known about any effects of HCV infection on the host beyond any changes related to adaptive immune responses. HCV persistence is associated strongly with mitochondrial dysfunction, with liver mitochondrial DNA (mtDNA) genetic diversity linked to disease progression. METHODS: We evaluated the genetic diversity of 2 mtDNA genomic regions (hypervariable segments 1 and 2) obtained from sera of 116 persons using next-generation sequencing. RESULTS: Results were as follows: (1) the average diversity among cases with seronegative acute HCV infection was 4.2 times higher than among uninfected controls; (2) the diversity level among cases with chronic HCV infection was 96.1 times higher than among uninfected controls; and (3) the diversity was 23.1 times higher among chronic than acute cases. In 2 patients who were followed up during combined interferon and ribavirin therapy, mtDNA nucleotide diversity decreased dramatically after the completion of therapy in both patients: by 100% in patient A after 54 days and by 70.51% in patient B after 76 days. CONCLUSIONS: HCV infection strongly affects mtDNA genetic diversity. A rapid decrease in mtDNA genetic diversity observed after therapy-induced HCV clearance suggests that the effect is reversible, emphasizing dynamic genetic relationships between HCV and mitochondria. The level of mtDNA nucleotide diversity can be used to discriminate recent from past infections, which should facilitate the detection of recent transmission events and thus help identify modes of transmission.

Next-Generation Sequencing Reveals Frequent Opportunities for Exposure to Hepatitis C Virus in Ghana.

Globally, hepatitis C Virus (HCV) infection is responsible for a large proportion of persons with liver disease, including cancer. The infection is highly prevalent in sub-Saharan Africa. West Africa was identified as a geographic origin of two HCV genotypes. However, little is known about the genetic composition of HCV populations in many countries of the region. Using conventional and next-generation sequencing (NGS), we identified and genetically characterized 65 HCV strains circulating among HCV-positive blood donors in Kumasi, Ghana. Phylogenetic analysis using consensus sequences derived from 3 genomic regions of the HCV genome, 5'-untranslated region, hypervariable region 1 (HVR1) and NS5B gene, consistently classified the HCV variants (n = 65) into genotypes 1 (HCV-1, 15%) and genotype 2 (HCV-2, 85%). The Ghanaian and West African HCV-2 NS5B sequences were found completely intermixed in the phylogenetic tree, indicating a substantial genetic heterogeneity of HCV-2 in Ghana. Analysis of HVR1 sequences from intra-host HCV variants obtained by NGS showed that three donors were infected with >1 HCV strain, including infections with 2 genotypes. Two other donors share an HCV strain, indicating HCV transmission between them. The HCV-2 strain sampled from one donor was replaced with another HCV-2 strain after only 2 months of observation, indicating rapid strain switching. Bayesian analysis estimated that the HCV-2 strains in Ghana were expanding since the 16th century. The blood donors in Kumasi, Ghana, are infected with a very heterogeneous HCV population of HCV-1 and HCV-2, with HCV-2 being prevalent. The detection of three cases of co- or super-infections and transmission linkage between 2 cases suggests frequent opportunities for HCV exposure among the blood donors and is consistent with the reported high HCV prevalence. The conditions for effective HCV-2 transmission existed for ~ 3-4 centuries, indicating a long epidemic history of HCV-2 in Ghana.

Nosocomial hepatitis C virus transmission from tampering with injectable anesthetic opioids.

UNLABELLED: The extent of provider-to-patient hepatitis C virus (HCV) transmission from diversion, self-injection, and substitution ("tampering") of anesthetic opioids is unknown. To quantify the contribution of opioid tampering to nosocomial HCV outbreaks, data from health care-related HCV outbreaks occurring in developed countries from 1990 to 2012 were collated, grouped, and compared. Tampering was associated with 17% (8 of 46) of outbreaks, but 53% (438 of 833) of cases. Of the tampering outbreaks, six (75%) involved fentanyl, five (63%) occurred in the United States, and one each in Australia, Israel, and Spain. Case counts ranged from 5 to 275 in the tampering outbreaks (mean, 54.8; median, 25), and 1-99 in the nontampering outbreaks (mean, 10.4; median, 5); between them, the difference in mean ranks of counts was significant (P < 0.01). To estimate HCV transmission risks from tampering, risk-assessment models were constructed, and these risks compared with those from surgery. HCV transmission risk from exposure to an opioid preparation tampered by a provider of unknown HCV infection status who is a person who injects drugs (PWID; 0.62%; standard error [SE] = 0.38%) exceeds 16,757 times the risk from surgery by a surgeon of unknown HCV infection status (0.000037%; SE = 0.000029%) and 135 times by an HCV-infected surgeon (0.0046%; SE = 0.0033%). To pose a 50% patient transmission risk, an infected surgeon may take 30 years, compared to <1 year for a PWID tamperer, and weeks or days for a PWID tamperer who intensifies access to opioids. CONCLUSION: Disproportionately, many cases of HCV infection from nosocomial outbreaks were attributable to provider tampering of anesthetic opioids. Transmission risk from tampering is substantially higher than from surgery.

Network Analysis of the Chronic Hepatitis C Virome Defines Hypervariable Region 1 Evolutionary Phenotypes in the Context of Humoral Immune Responses.

UNLABELLED: Hypervariable region 1 (HVR1) of hepatitis C virus (HCV) comprises the first 27 N-terminal amino acid residues of E2. It is classically seen as the most heterogeneous region of the HCV genome. In this study, we assessed HVR1 evolution by using ultradeep pyrosequencing for a cohort of treatment-naive, chronically infected patients over a short, 16-week period. Organization of the sequence set into connected components that represented single nucleotide substitution events revealed a network dominated by highly connected, centrally positioned master sequences. HVR1 phenotypes were observed to be under strong purifying (stationary) and strong positive (antigenic drift) selection pressures, which were coincident with advancing patient age and cirrhosis of the liver. It followed that stationary viromes were dominated by a single HVR1 variant surrounded by minor variants comprised from conservative single amino acid substitution events. We present evidence to suggest that neutralization antibody efficacy was diminished for stationary-virome HVR1 variants. Our results identify the HVR1 network structure during chronic infection as the preferential dominance of a single variant within a narrow sequence space. IMPORTANCE: HCV infection is often asymptomatic, and chronic infection is generally well established in advance of initial diagnosis and subsequent treatment. HVR1 can undergo rapid sequence evolution during acute infection, and the variant pool is typically seen to diverge away from ancestral sequences as infection progresses from the acute to the chronic phase. In this report, we describe HVR1 viromes in chronically infected patients that are defined by a dominant epitope located centrally within a narrow variant pool. Our findings suggest that weakened humoral immune activity, as a consequence of persistent chronic infection, allows for the acquisition and maintenance of host-specific adaptive mutations at HVR1 that reflect virus fitness.