Pooled-Peptide Epitope Mapping Strategies Are Efficient and Highly Sensitive: An Evaluation of Methods for Identifying Human T Cell Epitope Specificities in Large-Scale HIV Vaccine Efficacy Trials

The interferon gamma, enzyme-linked immunospot (IFN-γ ELISpot) assay is widely used to identify viral antigen-specific T cells is frequently employed to quantify T cell responses in HIV vaccine studies. It can be used to define T cell epitope specificities using panels of peptide antigens, but with sample and cost constraints there is a critical need to improve the efficiency of epitope mapping for large and variable pathogens. We evaluated two epitope mapping strategies, based on group testing, for their ability to identify vaccine-induced T-cells from participants in the Step HIV-1 vaccine efficacy trial, and compared the findings to an approach of assaying each peptide individually. The group testing strategies reduced the number of assays required by >7-fold without significantly altering the accuracy of T-cell breadth estimates. Assays of small pools containing 7–30 peptides were highly sensitive and effective at detecting single positive peptides as well as summating responses to multiple peptides. Also, assays with a single 15-mer peptide, containing an identified epitope, did not always elicit a response providing validation that 15-mer peptides are not optimal antigens for detecting CD8+ T cells. Our findings further validate pooling-based epitope mapping strategies, which are critical for characterizing vaccine-induced T-cell responses and more broadly for informing iterative vaccine design. We also show ways to improve their application with computational peptide:MHC binding predictors that can accurately identify the optimal epitope within a 15-mer peptide and within a pool of 15-mer peptides.     

Hawksbill turtle terra incognita: conservation genetics of?eastern Pacific rookeries

Prior to 2008 and the discovery of several important hawksbill turtle (Eretmochelys imbricata) nesting colonies in the EP (Eastern Pacific), the species was considered virtually absent from the region. Research since that time has yielded new insights into EP hawksbills, salient among them being the use of mangrove estuaries for nesting. These recent revelations have raised interest in the genetic characterization of hawksbills in the EP, studies of which have remained lacking to date. Between 2008 and 2014, we collected tissue samples from 269 nesting hawksbills at nine rookeries across the EP and used mitochondrial DNA sequences (766 bp) to generate the first genetic characterization of rookeries in the region. Our results inform genetic diversity, population differentiation, and phylogeography of the species. Hawksbills in the EP demonstrate low genetic diversity: We identified a total of only seven haplotypes across the region, including five new and two previously identified nesting haplotypes (pooled frequencies of 58.4% and 41.6%, respectively), the former only evident in Central American rookeries. Despite low genetic diversity, we found strong stock structure between the four principal rookeries, suggesting the existence of multiple populations and warranting their recognition as distinct management units. Furthermore, haplotypes EiIP106 and EiIP108 are unique to hawksbills that nest in mangrove estuaries, a behavior found only in hawksbills along Pacific Central America. The detected genetic differentiation supports the existence of a novel mangrove estuary “reproductive ecotype” that may warrant additional conservation attention. From a phylogeographic perspective, our research indicates hawksbills colonized the EP via the Indo‐Pacific, and do not represent relict populations isolated from the Atlantic by the rising of the Panama Isthmus. Low overall genetic diversity in the EP is likely the combined result of few rookeries, extremely small reproductive populations and evolutionarily recent colonization events. Additional research with larger sample sizes and variable markers will help further genetic understanding of hawksbill turtles in the EP.     

What Is a “Community Perception” of REDD+? A Systematic Review of How Perceptions of REDD+ Have Been Elicited and Reported in the Literature

Reducing emissions from deforestation and forest degradation (REDD+) is expected to generate co-benefits and safeguard the interests of people who live in the forested regions where emissions are reduced. Participatory measurement, reporting and verification (PMRV) is one way to ensure that the interests of local people are represented in REDD+. In order to design and use PMRV systems to monitor co-benefits and safeguards, we need to obtain input on how local people perceive REDD+. In the literature, this is widely discussed as “community perceptions of REDD+.” We systematically reviewed this literature to understand how these perceptions have been assessed, focusing specifically on how individual perceptions have been sampled and aggregated into “community perceptions.” Using Google Scholar, we identified 19 publications that reported community perceptions of REDD+, including perceptions of its design, implementation, impacts, relationship with land tenure, and both interest and actual participation by local people. These perceptions were elicited through surveys of probability samples of the local population and interviews with purposively selected community representatives. Many authors did not provide sufficient information on their methods to interpret the reported community perceptions. For example, there was often insufficient detail on the selection of respondents or sampling methods. Authors also reported perceptions by unquantified magnitudes (e.g., “most people”, “the majority”) that were difficult to assess or compare across cases. Given this situation in the scholarly literature, we expect that there are even more severe problems in the voluminous gray literature on REDD+ not indexed by Google Scholar. We suggest that readers need to be cognizant of these issues and that publication outlets should establish guidelines for better reporting, requiring information on the reference population, sampling methods, and methods used to aggregate individual responses into “community perceptions.”     

Changes in Colonic Bile Acid Composition following Fecal Microbiota Transplantation Are Sufficient to Control Clostridium difficile Germination and Growth

Fecal microbiota transplantation (FMT) is a highly effective therapy for recurrent Clostridium difficile infection (R-CDI), but its mechanisms remain poorly understood. Emerging evidence suggests that gut bile acids have significant influence on the physiology of C. difficile, and therefore on patient susceptibility to recurrent infection. We analyzed spore germination of 10 clinical C. difficile isolates exposed to combinations of bile acids present in patient feces before and after FMT. Bile acids at concentrations found in patients’ feces prior to FMT induced germination of C. difficile, although with variable potency across different strains. However, bile acids at concentrations found in patients after FMT did not induce germination and inhibited vegetative growth of all C. difficile strains. Sequencing of the newly identified germinant receptor in C. difficile, CspC, revealed a possible correspondence of variation in germination responses across isolates with mutations in this receptor. This may be related to interstrain variability in spore germination and vegetative growth in response to bile acids seen in this and other studies. These results support the idea that intra-colonic bile acids play a key mechanistic role in the success of FMT, and suggests that novel therapeutic alternatives for treatment of R-CDI may be developed by targeted manipulation of bile acid composition in the colon.     

Using simulations to evaluate Mantel‐based methods for assessing landscape resistance to gene flow

Mantel‐based tests have been the primary analytical methods for understanding how landscape features influence observed spatial genetic structure. Simulation studies examining Mantel‐based approaches have highlighted major challenges associated with the use of such tests and fueled debate on when the Mantel test is appropriate for landscape genetics studies. We aim to provide some clarity in this debate using spatially explicit, individual‐based, genetic simulations to examine the effects of the following on the performance of Mantel‐based methods: (1) landscape configuration, (2) spatial genetic nonequilibrium, (3) nonlinear relationships between genetic and cost distances, and (4) correlation among cost distances derived from competing resistance models. Under most conditions, Mantel‐based methods performed poorly. Causal modeling identified the true model only 22% of the time. Using relative support and simple Mantel r values boosted performance to approximately 50%. Across all methods, performance increased when landscapes were more fragmented, spatial genetic equilibrium was reached, and the relationship between cost distance and genetic distance was linearized. Performance depended on cost distance correlations among resistance models rather than cell‐wise resistance correlations. Given these results, we suggest that the use of Mantel tests with linearized relationships is appropriate for discriminating among resistance models that have cost distance correlations <0.85 with each other for causal modeling, or <0.95 for relative support or simple Mantel r. Because most alternative parameterizations of resistance for the same landscape variable will result in highly correlated cost distances, the use of Mantel test‐based methods to fine‐tune resistance values will often not be effective.