A convenient correspondence between k-mer-based metagenomic distances and phylogenetically-informed ß-diversity measures.

k-mer-based distances are often used to describe the differences between communities in metagenome sequencing studies because of their computational convenience and history of effectiveness. Although k-mer-based distances do not use information about taxon abundances, we show that one class of k-mer distances between metagenomes (the Euclidean distance between k-mer spectra, or EKS distances) are very closely related to a class of phylogenetically-informed ß-diversity measures that do explicitly use both the taxon abundances and information about the phylogenetic relationships among the taxa. Furthermore, we show that both of these distances can be interpreted as using certain features of the taxon abundances that are related to the phylogenetic tree. Our results allow practitioners to perform phylogenetically-informed analyses when they only have k-mer data available and provide a theoretical basis for using k-mer spectra with relatively small values of k (on the order of 4-5). They are also useful for analysts who wish to know more of the properties of any method based on k-mer spectra and provide insight into one class of phylogenetically-informed ß-diversity measures.

Multiscale analysis of count data through topic alignment.

Topic modeling is a popular method used to describe biological count data. With topic models, the user must specify the number of topics $K$. Since there is no definitive way to choose $K$ and since a true value might not exist, we develop a method, which we call topic alignment, to study the relationships across models with different $K$. In addition, we present three diagnostics based on the alignment. These techniques can show how many topics are consistently present across different models, if a topic is only transiently present, or if a topic splits into more topics when $K$ increases. This strategy gives more insight into the process of generating the data than choosing a single value of $K$ would. We design a visual representation of these cross-model relationships, show the effectiveness of these tools for interpreting the topics on simulated and real data, and release an accompanying R package, alto.

Lack of Evidence for a Substantial Rate of Templated Mutagenesis in B Cell Diversification.

BCR sequences diversify through mutations introduced by purpose-built cellular machinery. A recent paper has concluded that a "templated mutagenesis" process is a major contributor to somatic hypermutation and therefore Ig diversification in mice and humans. In this proposed process, mutations in the Ig locus are introduced by copying short segments from other Ig genes. If true, this would overturn decades of research on B cell diversification and would require a complete rewrite of computational methods to analyze B cell data for these species. In this paper, we re-evaluate the templated mutagenesis hypothesis. By applying the original inferential method using potential donor templates absent from B cell genomes, we obtain estimates of the methods' false positive rates. We find false positive rates of templated mutagenesis in murine and human Ig loci that are similar to or even higher than the original rate inferences, and by considering the bases used in substitution, we find evidence that if templated mutagenesis occurs, it is at a low rate. We also show that the statistically significant results in the original paper can easily result from a slight misspecification of the null model.

Emphasis on the deep or shallow parts of the tree provides a new characterization of phylogenetic distances.

BACKGROUND: Phylogenetically informed distances are commonly used in the analysis of microbiome data, and analysts have many options to choose from. Although all phylogenetic distances share the goal of incorporating the phylogenetic relationships among the bacteria, they do so in different ways and give different pictures of the relationships between the bacterial communities. RESULTS: We investigate the properties of two classes of phylogenetically informed distances: the Unifrac family, including weighted, unweighted, and generalized Unifrac, and the DPCoA family, which we introduce here. Through several lines of evidence, including a combination of mathematical, data analytic, and computational methods, we show that a major and heretofore unrecognized cleavage in the phylogenetically informed distances is the relative weights placed on the deep and shallow parts of the phylogeny. Specifically, weighted Unifrac and DPCoA place more emphasis on the deep parts of the phylogeny, while unweighted Unifrac places more emphasis on the shallow parts of the phylogeny. Both the Unifrac and the DPCoA families have tunable parameters that can be shown to control how much emphasis the distances place on the deep or shallow parts of the phylogeny. CONCLUSIONS: Our results allow for a more informed choice of distance and give practitioners more insight into the potential differences resulting from different choices of distance.

A spatial gradient of bacterial diversity in the human oral cavity shaped by salivary flow.

Spatial and temporal patterns in microbial communities provide insights into the forces that shape them, their functions and roles in health and disease. Here, we used spatial and ecological statistics to analyze the role that saliva plays in structuring bacterial communities of the human mouth using >9000 dental and mucosal samples. We show that regardless of tissue type (teeth, alveolar mucosa, keratinized gingiva, or buccal mucosa), surface-associated bacterial communities vary along an ecological gradient from the front to the back of the mouth, and that on exposed tooth surfaces, the gradient is pronounced on lingual compared to buccal surfaces. Furthermore, our data suggest that this gradient is attenuated in individuals with low salivary flow due to Sjögren's syndrome. Taken together, our findings imply that salivary flow influences the spatial organization of microbial communities and that biogeographical patterns may be useful for understanding host physiological processes and for predicting disease.

Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment.

Our work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers following this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods.

Mass Cytometry Analytical Approaches Reveal Cytokine-Induced Changes in Natural Killer Cells.

BACKGROUND: Natural killer (NK) cells have antiviral and antitumor activity that could be harnessed for the treatment of infections and malignancies. To maintain cell viability and enhance antiviral and antitumor effects, NK cells are frequently treated with cytokines. Here they performed an extensive assessment of the effects of cytokines on the phenotype and function of human NK cells. METHODS: They used cytometry by time-of-flight (CyTOF) to evaluate NK cell repertoire changes after stimulation with interleukin (IL)-2, IL-15 or a combination of IL-12/IL-15/IL-18. To analyze the high dimensional CyTOF data, they used several statistical and visualization tools, including viSNE (Visualization of t-Distributed Stochastic Neighbor Embedding), Citrus (Cluster identification, characterization, and regression), correspondence analysis, and the Friedman-Rafsky test. RESULTS: All three treatments (IL-2, IL-15, and IL-12/IL-15/IL-18) increase expression of CD56 and CD69. The effects of treatment with IL-2 and IL-15 are nearly indistinguishable and characterized principally by increased expression of surface markers including CD56, NKp30, NKp44, and increased expression of functional markers, such as perforin, granzyme B, and MIP-1ß. The combination of IL-12/IL-15/IL-18 induces a profound shift in the repertoire structure, decreasing expression of CD16, CD57, CD8, NKp30, NKp46, and NKG2D, and dramatically increasing expression of IFN-γ. CONCLUSIONS: CyTOF provides insights into the effects of cytokines on the phenotype and function of NK cells, which could inform future research efforts and approaches to NK cell immunotherapy. There are several analytical approaches to CyTOF data, and the appropriate method should be carefully selected based on which aspect of the dataset is being explored. © 2016 International Clinical Cytometry Society.

Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses.

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, whether parametric or nonparametric. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests and nonparametric testing using community networks and the ggnetwork package.

REPRODUCIBLE RESEARCH WORKFLOW IN R FOR THE ANALYSIS OF PERSONALIZED HUMAN MICROBIOME DATA.

This article presents a reproducible research workflow for amplicon-based microbiome studies in personalized medicine created using Bioconductor packages and the knitr markdown interface.We show that sometimes a multiplicity of choices and lack of consistent documentation at each stage of the sequential processing pipeline used for the analysis of microbiome data can lead to spurious results. We propose its replacement with reproducible and documented analysis using R packages dada2, knitr, and phyloseq. This workflow implements both key stages of amplicon analysis: the initial filtering and denoising steps needed to construct taxonomic feature tables from error-containing sequencing reads (dada2), and the exploratory and inferential analysis of those feature tables and associated sample metadata (phyloseq). This workow facilitates reproducible interrogation of the full set of choices required in microbiome studies. We present several examples in which we leverage existing packages for analysis in a way that allows easy sharing and modification by others, and give pointers to articles that depend on this reproducible workflow for the study of longitudinal and spatial series analyses of the vaginal microbiome in pregnancy and the oral microbiome in humans with healthy dentition and intra-oral tissues.

Human NK cell repertoire diversity reflects immune experience and correlates with viral susceptibility.

Innate natural killer (NK) cells are diverse at the single-cell level because of variegated expressions of activating and inhibitory receptors, yet the developmental roots and functional consequences of this diversity remain unknown. Because NK cells are critical for antiviral and antitumor responses, a better understanding of their diversity could lead to an improved ability to harness them therapeutically. We found that NK diversity is lower at birth than in adults. During an antiviral response to either HIV-1 or West Nile virus, NK diversity increases, resulting in terminal differentiation and cytokine production at the cost of cell division and degranulation. In African women matched for HIV-1 exposure risk, high NK diversity is associated with increased risk of HIV-1 acquisition. Existing diversity may therefore decrease the flexibility of the antiviral response. Collectively, the data reveal that human NK diversity is a previously undefined metric of immune history and function that may be clinically useful in forecasting the outcomes of infection and malignancy.

Pregnancy Does Not Attenuate the Antibody or Plasmablast Response to Inactivated Influenza Vaccine.

BACKGROUND: Inactivated influenza vaccine (IIV) is recommended during pregnancy to prevent influenza infection and its complications in pregnant women and their infants. However, the extent to which pregnancy modifies the antibody response to vaccination remains unclear, and prior studies have focused primarily on hemagglutinin inhibition (HI) titers. A more comprehensive understanding of how pregnancy modifies the humoral immune response to influenza vaccination will aid in maximizing vaccine efficacy. METHODS: Healthy pregnant women and control women were studied prior to, 7 days after, and 28 days after vaccination with IIV. HI titers, microneutralization (MN) titers, and the frequency of circulating plasmablasts were evaluated in pregnant versus control women. RESULTS: Pregnant women and control women mount similarly robust serologic immune responses to IIV, with no significant differences for any influenza strain in postvaccination geometric mean HI or MN titers. HI and MN titers correlate, though MN titers demonstrate more robust changes pre- versus postvaccination. The induction of circulating plasmablasts is increased in pregnant women versus controls (median fold-change 2.60 vs 1.49 [interquartile range, 0.94-7.53 vs 0.63-2.67]; P = .03). CONCLUSIONS: Pregnant women do not have impaired humoral immune responses to IIV and may have increased circulating plasmablast production compared to control women.

Enhanced natural killer-cell and T-cell responses to influenza A virus during pregnancy.

Pregnant women experience increased morbidity and mortality after influenza infection, for reasons that are not understood. Although some data suggest that natural killer (NK)- and T-cell responses are suppressed during pregnancy, influenza-specific responses have not been previously evaluated. Thus, we analyzed the responses of women that were pregnant (n = 21) versus those that were not (n = 29) immediately before inactivated influenza vaccination (IIV), 7 d after vaccination, and 6 wk postpartum. Expression of CD107a (a marker of cytolysis) and production of IFN-γ and macrophage inflammatory protein (MIP) 1ß were assessed by flow cytometry. Pregnant women had a significantly increased percentage of NK cells producing a MIP-1ß response to pH1N1 virus compared with nonpregnant women pre-IIV [median, 6.66 vs. 0.90% (P = 0.0149)] and 7 d post-IIV [median, 11.23 vs. 2.81% (P = 0.004)], indicating a heightened chemokine response in pregnant women that was further enhanced by the vaccination. Pregnant women also exhibited significantly increased T-cell production of MIP-1ß and polyfunctionality in NK and T cells to pH1N1 virus pre- and post-IIV. NK- and T-cell polyfunctionality was also enhanced in pregnant women in response to the H3N2 viral strain. In contrast, pregnant women had significantly reduced NK- and T-cell responses to phorbol 12-myristate 13-acetate and ionomycin. This type of stimulation led to the conclusion that NK- and T-cell responses during pregnancy are suppressed, but clearly this conclusion is not correct relative to the more biologically relevant assays described here. Robust cellular immune responses to influenza during pregnancy could drive pulmonary inflammation, explaining increased morbidity and mortality.

Nasal microenvironments and interspecific interactions influence nasal microbiota complexity and S. aureus carriage.

The indigenous microbiota of the nasal cavity plays important roles in human health and disease. Patterns of spatial variation in microbiota composition may help explain Staphylococcus aureus colonization and reveal interspecies and species-host interactions. To assess the biogeography of the nasal microbiota, we sampled healthy subjects, representing both S. aureus carriers and noncarriers at three nasal sites (anterior naris, middle meatus, and sphenoethmoidal recess). Phylogenetic compositional and sparse linear discriminant analyses revealed communities that differed according to site epithelium type and S. aureus culture-based carriage status. Corynebacterium accolens and C. pseudodiphtheriticum were identified as the most important microbial community determinants of S. aureus carriage, and competitive interactions were only evident at sites with ciliated pseudostratified columnar epithelium. In vitro cocultivation experiments provided supporting evidence of interactions among these species. These results highlight spatial variation in nasal microbial communities and differences in community composition between S. aureus carriers and noncarriers.

Comparisons of distance methods for combining covariates and abundances in microbiome studies.

This article compares different methods for combining abundance data, phylogenetic trees and clinical covariates in a nonparametric setting. In particular we study the output from the principal coordinates analysis on UNIFRAC and WEIGHTED UNIFRAC distances and the output from a double principal coordinate analyses DPCOA using distances computed on the phylogenetic tree. We also present power comparisons for some of the standard tests of phylogenetic signal between different types of samples. These methods are compared both on simulated and real data sets. Our study shows that DPCoA is less robust to outliers, and more robust to small noisy fluctuations around zero.

Thrombospondin-1 inhibits nitric oxide signaling via CD36 by inhibiting myristic acid uptake.

Although CD36 is generally recognized to be an inhibitory signaling receptor for thrombospondin-1 (TSP1), the molecular mechanism for transduction of this signal remains unclear. Based on evidence that myristic acid and TSP1 each modulate endothelial cell nitric oxide signaling in a CD36-dependent manner, we examined the ability of TSP1 to modulate the fatty acid translocase activity of CD36. TSP1 and a CD36 antibody that mimics the activity of TSP1 inhibited myristate uptake. Recombinant TSP1 type 1 repeats were weakly inhibitory, but an anti-angiogenic peptide derived from this domain potently inhibited myristate uptake. This peptide also inhibited membrane translocation of the myristoylated CD36 signaling target Fyn and activation of Src family kinases. Myristate uptake stimulated cGMP synthesis via endothelial nitric-oxide synthase and soluble guanylyl cyclase. CD36 ligands blocked myristate-stimulated cGMP accumulation in proportion to their ability to inhibit myristate uptake. TSP1 also inhibited myristate-stimulated cGMP synthesis by engaging its receptor CD47. Myristate stimulated endothelial and vascular smooth muscle cell adhesion on type I collagen via the NO/cGMP pathway, and CD36 ligands that inhibit myristate uptake blocked this response. Therefore, the fatty acid translocase activity of CD36 elicits proangiogenic signaling in vascular cells, and TSP1 inhibits this response by simultaneously inhibiting fatty acid uptake via CD36 and downstream cGMP signaling via CD47.