Premature skewing of T cell receptor clonality and delayed memory expansion in HIV-exposed infants

While preventing vertical HIV transmission has been very successful, HIV-exposed uninfected infants (iHEU) experience an elevated risk to infections compared to HIV-unexposed and uninfected infants (iHUU). Here we present a longitudinal multimodal analysis of infant immune ontogeny that highlights the impact of HIV/ARV exposure. Using mass cytometry, we show alterations in T cell memory differentiation between iHEU and iHUU being significant from week 15 of life. The altered memory T cell differentiation in iHEU was preceded by lower TCR Vβ clonotypic diversity and linked to TCR clonal depletion within the naïve T cell compartment. Compared to iHUU, iHEU had elevated CD56loCD16loPerforin+CD38+CD45RA+FcεRIγ+ NK cells at 1 month postpartum and whose abundance pre-vaccination were predictive of vaccine-induced pertussis and rotavirus antibody responses post 3 months of life. Collectively, HIV/ARV exposure disrupted the trajectory of innate and adaptive immunity from birth which may underlie relative vulnerability to infections in iHEU.

Longitudinal gut microbiota composition of South African and Nigerian infants in relation to tetanus vaccine responses

Infants who are exposed to HIV but uninfected (iHEU) have higher risk of infectious morbidity than infants who are HIV-unexposed and uninfected (iHUU), possibly due to altered immunity. As infant gut microbiota may influence immune development, we evaluated the effects of HIV exposure on infant gut microbiota and its association with tetanus toxoid vaccine responses. We evaluated the gut microbiota of 82 South African (61 iHEU and 21 iHUU) and 196 Nigerian (141 iHEU and 55 iHUU) infants at <1 and 15 weeks of life by 16S rRNA gene sequencing. Anti-tetanus antibodies were measured by enzyme-linked immunosorbent assay at matched time points. Gut microbiota in the 278 included infants and its succession were more strongly influenced by geographical location and age than by HIV exposure. Microbiota of Nigerian infants, who were exclusively breastfed, drastically changed over 15 weeks, becoming dominated by Bifidobacterium longum subspecies infantis. This change was not observed among South African infants, even when limiting the analysis to exclusively breastfed infants. The Least Absolute Shrinkage and Selection Operator regression suggested that HIV exposure and gut microbiota were independently associated with tetanus titers at week 15, and that high passively transferred antibody levels, as seen in the Nigerian cohort, may mitigate these effects. In conclusion, in two African cohorts, HIV exposure minimally altered the infant gut microbiota compared to age and setting, but both specific gut microbes and HIV exposure independently predicted humoral tetanus vaccine responses.IMPORTANCEGut microbiota plays an essential role in immune system development. Since infants HIV-exposed and uninfected (iHEU) are more vulnerable to infectious diseases than unexposed infants, we explored the impact of HIV exposure on gut microbiota and its association with vaccine responses. This study was conducted in two African countries with rapidly increasing numbers of iHEU. Infant HIV exposure did not substantially affect gut microbial succession, but geographic location had a strong effect. However, both the relative abundance of specific gut microbes and HIV exposure were independently associated with tetanus titers, which were also influenced by baseline tetanus titers (maternal transfer). Our findings provide insight into the effect of HIV exposure, passive maternal antibody, and gut microbiota on infant humoral vaccine responses.

Abrupt perturbation and delayed recovery of the vaginal ecosystem following childbirth

The vaginal ecosystem is closely tied to human health and reproductive outcomes, yet its dynamics in the wake of childbirth remain poorly characterized. Here, we profile the vaginal microbiota and cytokine milieu of participants sampled longitudinally throughout pregnancy and for at least one year postpartum. We show that delivery, regardless of mode, is associated with a vaginal pro-inflammatory cytokine response and the loss of Lactobacillus dominance. By contrast, neither the progression of gestation nor the approach of labor strongly altered the vaginal ecosystem. At 9.5-months postpartum-the latest timepoint at which cytokines were assessed-elevated inflammation coincided with vaginal bacterial communities that had remained perturbed (highly diverse) from the time of delivery. Time-to-event analysis indicated a one-year postpartum probability of transitioning to Lactobacillus dominance of 49.4%. As diversity and inflammation declined during the postpartum period, dominance by L. crispatus, the quintessential health-associated commensal, failed to return: its prevalence before, immediately after, and one year after delivery was 41%, 4%, and 9%, respectively. Revisiting our pre-delivery data, we found that a prior live birth was associated with a lower odds of L. crispatus dominance in pregnant participants-an outcome modestly tempered by a longer ( > 18-month) interpregnancy interval. Our results suggest that reproductive history and childbirth in particular remodel the vaginal ecosystem and that the timing and degree of recovery from delivery may help determine the subsequent health of the woman and of future pregnancies.

Longitudinal gut microbiota composition of South African and Nigerian infants in relation to tetanus vaccine responses

Introduction

Infants who are exposed to HIV but uninfected (iHEU) have higher risk of infectious morbidity than infants who are HIV-unexposed and uninfected (iHUU), possibly due to altered immunity. As infant gut microbiota may influence immune development, we evaluated the effects of HIV exposure on infant gut microbiota and its association with tetanus toxoid (TT) vaccine responses.

Methods

We evaluated gut microbiota by 16S rRNA gene sequencing in 278 South African and Nigerian infants during the first and at 15 weeks of life and measured antibodies against TT vaccine by enzyme-linked immunosorbent assay (ELISA) at matched time points.

Results

Infant gut microbiota and its succession were more strongly influenced by geographical location and age than by HIV exposure. Microbiota of Nigerian infants drastically changed over 15 weeks, becoming dominated by Bifidobacterium longum subspecies infantis. This change was not observed among EBF South African infants. Lasso regression suggested that HIV exposure and gut microbiota were independently associated with TT vaccine responses at week 15, and that high passive antibody levels may mitigate these effects.

Conclusion

In two African cohorts, HIV exposure minimally altered the infant gut microbiota compared to age and country, but both specific gut microbes and HIV exposure independently predicted humoral vaccine responses.

Profiling the human intestinal environment under physiological conditions

The spatiotemporal structure of the human microbiome1,2, proteome3 and metabolome4,5 reflects and determines regional intestinal physiology and may have implications for disease6. Yet, little is known about the distribution of microorganisms, their environment and their biochemical activity in the gut because of reliance on stool samples and limited access to only some regions of the gut using endoscopy in fasting or sedated individuals7. To address these deficiencies, we developed an ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. Collection of 240 intestinal samples from 15 healthy individuals using the device and subsequent multi-omics analyses identified significant differences between bacteria, phages, host proteins and metabolites in the intestines versus stool. Certain microbial taxa were differentially enriched and prophage induction was more prevalent in the intestines than in stool. The host proteome and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Furthermore, microbially conjugated bile acid concentrations exhibited amino acid-dependent trends that were not apparent in stool. Overall, non-invasive, longitudinal profiling of microorganisms, proteins and bile acids along the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease.

HIV-1 Group M Capsid Amino Acid Variability: Implications for Sequence Quality Control of Genotypic Resistance Testing

BACKGROUND

With the approval of the HIV-1 capsid inhibitor, lenacapavir, capsid sequencing will be required for managing lenacapavir-experienced individuals with detectable viremia. Successful sequence interpretation will require examining new capsid sequences in the context of previously published sequence data.

METHODS

We analyzed published HIV-1 group M capsid sequences from 21,012 capsid-inhibitor naïve individuals to characterize amino acid variability at each position and influence of subtype and cytotoxic T lymphocyte (CTL) selection pressure. We determined the distributions of usual mutations, defined as amino acid differences from the group M consensus, with a prevalence ≥ 0.1%. Co-evolving mutations were identified using a phylogenetically-informed Bayesian graphical model method.

RESULTS

162 (70.1%) positions had no usual mutations (45.9%) or only conservative usual mutations with a positive BLOSUM62 score (24.2%). Variability correlated independently with subtype-specific amino acid occurrence (Spearman rho = 0.83; p < 1 × 10-9) and the number of times positions were reported to contain an HLA-associated polymorphism, an indicator of CTL pressure (rho = 0.43; p = 0.0002).

CONCLUSIONS

Knowing the distribution of usual capsid mutations is essential for sequence quality control. Comparing capsid sequences from lenacapavir-treated and lenacapavir-naïve individuals will enable the identification of additional mutations potentially associated with lenacapavir therapy.

Highly Ambiguous HIV-1 Pol Positions Encoding Multiple Amino Acids Usually Result from Antiviral or Immune Selection Pressure

HIV-1 pol nucleotide ambiguities encoding amino acid mixtures occur commonly during population-based genotypic drug resistance testing. However, few studies have addressed the validity of sequences with fully ambiguous codons (FACs) containing codons translatable to more than four amino acids. We identified 839 published HIV-1 pol sequences with 846 FACs at 131 positions and determined their distribution relative to 215 HLA-associated pol positions (HAPs) and 84 drug-resistance positions. Among HIV-1 reverse transcriptase (RT) and protease sequences from antiretroviral therapy (ART)-naive and -experienced persons, there was a strong correlation between the likelihood a position was a FAC and that it was an HAP (Spearman's correlation coefficient rho >0.40; p < 1e-6). Among HIV-1 RT sequences from ART-experienced persons, there was a correlation between the likelihood that a position was a FAC and that it was a drug-resistance position (rho = 0.2; p = 8e-4). In the context of population-based genotypic resistance testing, FACs usually result from antiviral or immune selection pressure.

Stereotypic Expansion of T Regulatory and Th17 Cells during Infancy Is Disrupted by HIV Exposure and Gut Epithelial Damage

Few studies have investigated immune cell ontogeny throughout the neonatal and early pediatric period, when there is often increased vulnerability to infections. In this study, we evaluated the dynamics of two critical T cell populations, T regulatory (Treg) cells and Th17 cells, over the first 36 wk of human life. First, we observed distinct CD4⁺ T cells phenotypes between cord blood and peripheral blood, collected within 12 h of birth, showing that cord blood is not a surrogate for newborn blood. Second, both Treg and Th17 cells expanded in a synchronous fashion over 36 wk of life. However, comparing infants exposed to HIV in utero, but remaining uninfected, with HIV-unexposed uninfected control infants, there was a lower frequency of peripheral blood Treg cells at birth, resulting in a delayed expansion, and then declining again at 36 wk. Focusing on birth events, we found that Treg cells coexpressing CCR4 and α4β7 inversely correlated with plasma concentrations of CCL17 (the ligand for CCR4) and intestinal fatty acid binding protein, IL-7, and CCL20. This was in contrast with Th17 cells, which showed a positive association with these plasma analytes. Thus, despite the stereotypic expansion of both cell subsets over the first few months of life, there was a disruption in the balance of Th17 to Treg cells at birth likely being a result of gut damage and homing of newborn Treg cells from the blood circulation to the gut.

Expanded Spectrum of Antiretroviral-Selected Mutations in Human Immunodeficiency Virus Type 2

BACKGROUND

HIV-1 and HIV-2 differ in their antiretroviral (ARV) susceptibilities and drug resistance mutations (DRMs).

METHODS

We analyzed published HIV-2 pol sequences to identify HIV-2 treatment-selected mutations (TSMs). Mutation prevalences were determined by HIV-2 group and ARV status. Nonpolymorphic mutations were those in <1% of ARV-naive persons. TSMs were those associated with ARV therapy after multiple comparisons adjustment.

RESULTS

We analyzed protease (PR) sequences from 483 PR inhibitor (PI)-naive and 232 PI-treated persons; RT sequences from 333 nucleoside RT inhibitor (NRTI)-naive and 252 NRTI-treated persons; and integrase (IN) sequences from 236 IN inhibitor (INSTI)-naive and 60 INSTI-treated persons. In PR, 12 nonpolymorphic TSMs occurred in ≥11 persons: V33I, K45R, V47A, I50V, I54M, T56V, V62A, A73G, I82F, I84V, F85L, L90M. In RT, 9 nonpolymorphic TSMs occurred in ≥10 persons: K40R, A62V, K70R, Y115F, Q151M, M184VI, S215Y. In IN, 11 nonpolymorphic TSMs occurred in ≥4 persons: Q91R, E92AQ, T97A, G140S, Y143G, Q148R, A153G, N155H, H156R, R231 5-amino acid insertions. Nine of 32 nonpolymorphic TSMs were previously unreported.

CONCLUSIONS

This meta-analysis confirmed the ARV association of previously reported HIV-2 DRMs and identified novel TSMs. Genotypic and phenotypic studies of HIV-2 TSMs will improve approaches to predicting HIV-2 ARV susceptibility and treating HIV-2-infected persons.

Cytokine profile in plasma of severe COVID-19 does not differ from ARDS and sepsis

BACKGROUND

Elevated levels of inflammatory cytokines have been associated with poor outcomes among COVID-19 patients. It is unknown, however, how these levels compare with those observed in critically ill patients with acute respiratory distress syndrome (ARDS) or sepsis due to other causes.

METHODS

We used a Luminex assay to determine expression of 76 cytokines from plasma of hospitalized COVID-19 patients and banked plasma samples from ARDS and sepsis patients. Our analysis focused on detecting statistical differences in levels of 6 cytokines associated with cytokine storm (IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α) between patients with moderate COVID-19, severe COVID-19, and ARDS or sepsis.

RESULTS

Fifteen hospitalized COVID-19 patients, 9 of whom were critically ill, were compared with critically ill patients with ARDS (n = 12) or sepsis (n = 16). There were no statistically significant differences in baseline levels of IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α between patients with COVID-19 and critically ill controls with ARDS or sepsis.

CONCLUSION

Levels of inflammatory cytokines were not higher in severe COVID-19 patients than in moderate COVID-19 or critically ill patients with ARDS or sepsis in this small cohort. Broad use of immunosuppressive therapies in ARDS has failed in numerous Phase 3 studies; use of these therapies in unselected patients with COVID-19 may be unwarranted.

FUNDING

Funding was received from NHLBI K23 HL125663 (AJR); The Bill and Melinda Gates Foundation OPP1113682 (AJR and CAB); Burroughs Wellcome Fund Investigators in the Pathogenesis of Infectious Diseases #1016687 NIH/NIAID U19AI057229-16; Stanford Maternal Child Health Research Institute; and Chan Zuckerberg Biohub (CAB).

The levels of inflammatory cytokines in COVID-19 patients are compared to patients with other critical illness, such as sepsis or acute respiratory distress syndrome.

Effect of water, sanitation, handwashing and nutrition interventions on enteropathogens in children 14 months old: a cluster-randomized controlled trial in rural Bangladesh

BACKGROUND

We evaluated the impact of low-cost water, sanitation, handwashing (WSH) and child nutrition interventions on enteropathogen carriage in the WASH Benefits cluster-randomized controlled trial in rural Bangladesh.

METHODS

We analyzed 1411 routine fecal samples from children 14±2 months old in the WSH (n = 369), nutrition counseling plus lipid-based nutrient supplement (n = 353), nutrition plus WSH (n = 360), and control (n = 329) arms for 34 enteropathogens using quantitative PCR. Outcomes included the number of co-occurring pathogens; cumulative quantity of four stunting-associated pathogens; and prevalence and quantity of individual pathogens. Masked analysis was by intention-to-treat.

RESULTS

326 (99.1%) control children had one or more enteropathogens detected (mean 3.8±1.8). Children receiving WSH interventions had lower prevalence and quantity of individual viruses than controls (prevalence difference for norovirus: -11% [95% confidence interval [CI], -5 to -17%]; sapovirus: -9% [95%CI, -3 to -15%]; and adenovirus 40/41: -9% [95%CI, -2 to - 15%]). There was no difference in bacteria, parasites, or cumulative quantity of stunting-associated pathogens between controls and any intervention arm.

CONCLUSIONS

WSH interventions were associated with fewer enteric viruses in children aged 14 months. Different strategies are needed to reduce enteric bacteria and parasites at this critical young age.

Microbiota assembly, structure, and dynamics among Tsimane horticulturalists of the Bolivian Amazon

Selective and neutral forces shape human microbiota assembly in early life. The Tsimane are an indigenous Bolivian population with infant care-associated behaviors predicted to increase mother-infant microbial dispersal. Here, we characterize microbial community assembly in 47 infant-mother pairs from six Tsimane villages, using 16S rRNA gene amplicon sequencing of longitudinal stool and tongue swab samples. We find that infant consumption of dairy products, vegetables, and chicha (a fermented drink inoculated with oral microbes) is associated with stool microbiota composition. In stool and tongue samples, microbes shared between mothers and infants are more abundant than non-shared microbes. Using a neutral model of community assembly, we find that neutral processes alone explain the prevalence of 79% of infant-colonizing microbes, but explain microbial prevalence less well in adults from river villages with more regular access to markets. Our results underscore the importance of neutral forces during microbiota assembly. Changing lifestyle factors may alter traditional modes of microbiota assembly by decreasing the role of neutral processes.

Selective and neutral forces shape human microbiota assembly in early life. Here, Sprockett et al. study microbial community assembly in 47 infant-mother pairs from the Tsimane, an indigenous Bolivian population, highlighting the importance of neutral forces during microbiota assembly.

Microbial biogeography and ecology of the mouth and implications for periodontal diseases

In humans, the composition of microbial communities differs among body sites and between habitats within a single site. Patterns of variation in the distribution of organisms across time and space are referred to as "biogeography." The human oral cavity is a critical observatory for exploring microbial biogeography because it is spatially structured, easily accessible, and its microbiota has been linked to the promotion of both health and disease. The biogeographic features of microbial communities residing in spatially distinct, but ecologically similar, environments on the human body, including the subgingival crevice, have not yet been adequately explored. The purpose of this paper is twofold. First, we seek to provide the dental community with a primer on biogeographic theory, highlighting its relevance to the study of the human oral cavity. We summarize what is known about the biogeographic variation of dental caries and periodontitis and postulate that disease occurrence reflects spatial patterning in the composition and structure of oral microbial communities. Second, we present a number of methods that investigators can use to test specific hypotheses using biogeographic theory. To anchor our discussion, we apply each method to a case study and examine the spatial variation of the human subgingival microbiota in 2 individuals. Our case study suggests that the composition of subgingival communities may conform to an anterior-to-posterior gradient within the oral cavity. The gradient appears to be structured by both deterministic and nondeterministic processes, although additional work is needed to confirm these findings. A better understanding of biogeographic patterns and processes will lead to improved efficacy of dental interventions targeting the oral microbiota.

Gut microbiota plasticity is correlated with sustained weight loss on a low-carb or low-fat dietary intervention

While low-carbohydrate and low-fat diets can both lead to weight-loss, a substantial variability in achieved long-term outcomes exists among obese but otherwise healthy adults. We examined the hypothesis that structural differences in the gut microbiota explain a portion of variability in weight-loss using two cohorts of obese adults enrolled in the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) study. A total of 161 pre-diet fecal samples were sequenced from a discovery cohort (n = 66) and 106 from a validation cohort (n = 56). An additional 157 fecal samples were sequenced from the discovery cohort after 10 weeks of dietary intervention. We found no specific bacterial signatures associated with weight loss that were consistent across both cohorts. However, the gut microbiota plasticity (i.e. variability), was correlated with long-term (12-month) weight loss in a diet-dependent manner; on the low-fat diet subjects with higher pre-diet daily plasticity had higher sustained weight loss, whereas on the low-carbohydrate diet those with higher plasticity over 10 weeks of dieting had higher 12-month weight loss. Our findings suggest the potential importance of gut microbiota plasticity for sustained weight-loss. We highlight the advantages of evaluating kinetic trends and assessing reproducibility in studies of the gut microbiota.

Latent variable modeling for the microbiome

The human microbiome is a complex ecological system, and describing its structure and function under different environmental conditions is important from both basic scientific and medical perspectives. Viewed through a biostatistical lens, many microbiome analysis goals can be formulated as latent variable modeling problems. However, although probabilistic latent variable models are a cornerstone of modern unsupervised learning, they are rarely applied in the context of microbiome data analysis, in spite of the evolutionary, temporal, and count structure that could be directly incorporated through such models. We explore the application of probabilistic latent variable models to microbiome data, with a focus on Latent Dirichlet allocation, Non-negative matrix factorization, and Dynamic Unigram models. To develop guidelines for when different methods are appropriate, we perform a simulation study. We further illustrate and compare these techniques using the data of Dethlefsen and Relman (2011, Incomplete recovery and individualized responses of the human distal gut microbiota to repeated antibiotic perturbation. Proceedings of the National Academy of Sciences108, 4554-4561), a study on the effects of antibiotics on bacterial community composition. Code and data for all simulations and case studies are available publicly.

Multitable Methods for Microbiome Data Integration

The simultaneous study of multiple measurement types is a frequently encountered problem in practical data analysis. It is especially common in microbiome research, where several sources of data-for example, 16s-rRNA, metagenomic, metabolomic, or transcriptomic data-can be collected on the same physical samples. There has been a proliferation of proposals for analyzing such multitable microbiome data, as is often the case when new data sources become more readily available, facilitating inquiry into new types of scientific questions. However, stepping back from the rush for new methods for multitable analysis in the microbiome literature, it is worthwhile to recognize the broader landscape of multitable methods, as they have been relevant in problem domains ranging across economics, robotics, genomics, chemometrics, and neuroscience. In different contexts, these techniques are called data integration, multi-omic, and multitask methods, for example. Of course, there is no unique optimal algorithm to use across domains-different instances of the multitable problem possess specific structure or variation that are worth incorporating in methodology. Our purpose here is not to develop new algorithms, but rather to 1) distill relevant themes across different analysis approaches and 2) provide concrete workflows for approaching analysis, as a function of ultimate analysis goals and data characteristics (heterogeneity, dimensionality, sparsity). Towards the second goal, we have made code for all analysis and figures available online at https://github.com/krisrs1128/multitable_review.

Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data

BACKGROUND

The accuracy of microbial community surveys based on marker-gene and metagenomic sequencing (MGS) suffers from the presence of contaminants-DNA sequences not truly present in the sample. Contaminants come from various sources, including reagents. Appropriate laboratory practices can reduce contamination, but do not eliminate it. Here we introduce decontam ( https://github.com/benjjneb/decontam ), an open-source R package that implements a statistical classification procedure that identifies contaminants in MGS data based on two widely reproduced patterns: contaminants appear at higher frequencies in low-concentration samples and are often found in negative controls.

RESULTS

Decontam classified amplicon sequence variants (ASVs) in a human oral dataset consistently with prior microscopic observations of the microbial taxa inhabiting that environment and previous reports of contaminant taxa. In metagenomics and marker-gene measurements of a dilution series, decontam substantially reduced technical variation arising from different sequencing protocols. The application of decontam to two recently published datasets corroborated and extended their conclusions that little evidence existed for an indigenous placenta microbiome and that some low-frequency taxa seemingly associated with preterm birth were contaminants.

CONCLUSIONS

Decontam improves the quality of metagenomic and marker-gene sequencing by identifying and removing contaminant DNA sequences. Decontam integrates easily with existing MGS workflows and allows researchers to generate more accurate profiles of microbial communities at little to no additional cost.

Metagenomic analysis with strain-level resolution reveals fine-scale variation in the human pregnancy microbiome

Recent studies suggest that the microbiome has an impact on gestational health and outcome. However, characterization of the pregnancy-associated microbiome has largely relied on 16S rRNA gene amplicon-based surveys. Here, we describe an assembly-driven, metagenomics-based, longitudinal study of the vaginal, gut, and oral microbiomes in 292 samples from 10 subjects sampled every three weeks throughout pregnancy. Nonhuman sequences in the amount of 1.53 Gb were assembled into scaffolds, and functional genes were predicted for gene- and pathway-based analyses. Vaginal assemblies were binned into 97 draft quality genomes. Redundancy analysis (RDA) of microbial community composition at all three body sites revealed gestational age to be a significant source of variation in patterns of gene abundance. In addition, health complications were associated with variation in community functional gene composition in the mouth and gut. The diversity of Lactobacillus iners-dominated communities in the vagina, unlike most other vaginal community types, significantly increased with gestational age. The genomes of co-occurring Gardnerella vaginalis strains with predicted distinct functions were recovered in samples from two subjects. In seven subjects, gut samples contained strains of the same Lactobacillus species that dominated the vaginal community of that same subject and not other Lactobacillus species; however, these within-host strains were divergent. CRISPR spacer analysis suggested shared phage and plasmid populations across body sites and individuals. This work underscores the dynamic behavior of the microbiome during pregnancy and suggests the potential importance of understanding the sources of this behavior for fetal development and gestational outcome.

Differential Induction of IFN-α and Modulation of CD112 and CD54 Expression Govern the Magnitude of NK Cell IFN-γ Response to Influenza A Viruses

In human and murine studies, IFN-γ is a critical mediator immunity to influenza. IFN-γ production is critical for viral clearance and the development of adaptive immune responses, yet excessive production of IFN-γ and other cytokines as part of a cytokine storm is associated with poor outcomes of influenza infection in humans. As NK cells are the main population of lung innate immune cells capable of producing IFN-γ early in infection, we set out to identify the drivers of the human NK cell IFN-γ response to influenza A viruses. We found that influenza triggers NK cells to secrete IFN-γ in the absence of T cells and in a manner dependent upon signaling from both cytokines and receptor-ligand interactions. Further, we discovered that the pandemic A/California/07/2009 (H1N1) strain elicits a seven-fold greater IFN-γ response than other strains tested, including a seasonal A/Victoria/361/2011 (H3N2) strain. These differential responses were independent of memory NK cells. Instead, we discovered that the A/Victoria/361/2011 influenza strain suppresses the NK cell IFN-γ response by downregulating NK-activating ligands CD112 and CD54 and by repressing the type I IFN response in a viral replication-dependent manner. In contrast, the A/California/07/2009 strain fails to repress the type I IFN response or to downregulate CD54 and CD112 to the same extent, which leads to the enhanced NK cell IFN-γ response. Our results indicate that influenza implements a strain-specific mechanism governing NK cell production of IFN-γ and identifies a previously unrecognized influenza innate immune evasion strategy.

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.

Integration of Next–Generation Sequencing, Viral Sequencing, and Host-Response Profiling for the Diagnosis of Acute Infections

Background

To guide treatment of infectious diseases, clinicians need sensitive, specific, and rapid diagnostics. We aim to incorporate complementary methods of microbial sequencing and host-response profiling to improve the diagnosis of patients at risk for acute infections.

Methods

We enrolled 200 adult patients with systemic inflammatory response syndrome (SIRS) at the Stanford Emergency Department. Physicians with specialty training in infectious diseases conducted retrospective two-physician chart review to establish likely admission diagnoses. Blood samples were tested with a previously described 18-gene host-response integrated antibiotics decision model (IADM) that distinguishes noninfectious SIRS, bacterial infections and viral infections. Plasma samples were tested with shotgun metagenomic next-generation sequencing (NGS) and viral sequencing with VirCapSeq. A novel statistical algorithm was developed to identify contaminant organism sequences in NGS data.

Results

The physician chart review classified 99 patients (49%) as infected, 69 (35%) possibly infected and 32 (16%) non-infected. Compared with chart review, the IADM distinguished bacterial from viral infections with an area under curve of 0.85 (95% confidence interval 0.77–0.93). NGS results to date confirmed positive blood cultures in seven of nine patients, with two of four blood culture-positive E. coli patients turning up negative on NGS due to E. coli contamination. NGS also confirmed positive cultures from other sites in two of six patients with negative blood cultures. Preliminary VirCapSeq data from 23 patients confirmed positive viral tests in five of six patients with Hepatitis C, BK Virus, Cytomegalovirus and Epstein–Barr Virus infections. VirCapSeq did not identify a causative agent in the plasma of 11 patients with confirmed respiratory viral infection and intestinal Norovirus infection, and six patients with idiopathic illness. Interestingly, VirCapSeq found viral reactivation in 8 of 12 immunocompromised patients.

Conclusion

The diagnosis of suspected infections may be enhanced by integrating host-response and microbial data alongside clinical judgment. Our results and large cohort lay the foundation to demonstrate the utility of this approach and in which patients these tools may be most useful.

Disclosures

T. E. Sweeney, Inflammatix, Inc: Employee and Shareholder, Salary; T. Briese, Roche: Columbia University has licensed VirCapSeq to Roche, Licensing agreement or royalty; W. I. Lipkin, Roche: Columbia University has licensed VirCapSeq to Roche., Licensing agreement or royalty; P. Khatri, Inflammatix, Inc.: Co-founder, Scientific Advisor and Shareholder, Licensing agreement or royalty and ownership stock; D. A. Relman, Karius: Consultant, Stock options; Arc Bio LLC: Consultant, Stock options

Prevalence of Drug-Resistant Minority Variants in Untreated HIV-1-Infected Individuals With and Those Without Transmitted Drug Resistance Detected by Sanger Sequencing

Minority variant human immunodeficiency virus type 1 (HIV-1) nonnucleoside reverse transcriptase inhibitor (NNRTI) resistance mutations are associated with an increased risk of virological failure during treatment with NNRTI-containing regimens. To determine whether individuals to whom variants with isolated NNRTI-associated drug resistance were transmitted are at increased risk of virological failure during treatment with a non-NNRTI-containing regimen, we identified minority variant resistance mutations in 33 individuals with isolated NNRTI-associated transmitted drug resistance and 49 matched controls. We found similar proportions of overall and nucleoside reverse transcriptase inhibitor-associated minority variant resistance mutations in both groups, suggesting that isolated NNRTI-associated transmitted drug resistance may not be a risk factor for virological failure during treatment with a non-NNRTI-containing regimen.

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.

Mutational Correlates of Virological Failure in Individuals Receiving a WHO-Recommended Tenofovir-Containing First-Line Regimen: An International Collaboration

Tenofovir disoproxil fumarate (TDF) genotypic resistance defined by K65R/N and/or K70E/Q/G occurs in 20% to 60% of individuals with virological failure (VF) on a WHO-recommended TDF-containing first-line regimen. However, the full spectrum of reverse transcriptase (RT) mutations selected in individuals with VF on such a regimen is not known. To identify TDF regimen-associated mutations (TRAMs), we compared the proportion of each RT mutation in 2873 individuals with VF on a WHO-recommended first-line TDF-containing regimen to its proportion in a cohort of 50,803 antiretroviral-naïve individuals. To identify TRAMs specifically associated with TDF-selection pressure, we compared the proportion of each TRAM to its proportion in a cohort of 5805 individuals with VF on a first-line thymidine analog-containing regimen. We identified 83 TRAMs including 33 NRTI-associated, 40 NNRTI-associated, and 10 uncommon mutations of uncertain provenance. Of the 33 NRTI-associated TRAMs, 12 - A62V, K65R/N, S68G/N/D, K70E/Q/T, L74I, V75L, and Y115F - were more common among individuals receiving a first-line TDF-containing compared to a first-line thymidine analog-containing regimen. These 12 TDF-selected TRAMs will be important for monitoring TDF-associated transmitted drug-resistance and for determining the extent of reduced TDF susceptibility in individuals with VF on a TDF-containing regimen.

Hydrocephalus secondary to obstruction of the lateral apertures in two dogs

BACKGROUND

Traditionally, hydrocephalus is divided into communicating or non-communicating (obstructive) based on the identification of a blockage of cerebrospinal fluid (CSF) flow through the ventricular system. Hydrocephalus ex vacuo refers to ventricular enlargement as a consequence of neuroparenchymal loss. Hydrocephalus related to obstruction of the lateral apertures of the fourth ventricles has rarely been described.

CASE REPORT

The clinicopathologic findings in two dogs with hydrocephalus secondary to obstruction of the lateral apertures of the fourth ventricle are reported. Signs were associated with a caudal cervical spinal cord lesion in one dog and a caudal brain stem lesion in the other dog. Magnetic resonance imaging (MRI) disclosed dilation of the ventricular system, including the lateral recesses of the fourth ventricle. In one dog, postmortem ventriculography confirmed obstruction of the lateral apertures. Microscopic changes were identified in the choroid plexus in both dogs, yet a definitive cause of the obstructions was not identified. The MRI findings in both dogs are similar to membranous occlusion of the lateral and median apertures in human patients.

CONCLUSION

MRI detection of dilation of the entire ventricular system in the absence of an identifiable cause should prompt consideration of an obstruction of the lateral apertures. In future cases, therapeutic interventions aimed at re-establishing CSF flow or ventriculoperitoneal catheterisation should be considered.

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.

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.

Interpreting Prevotella and Bacteroides as biomarkers of diet and lifestyle

BACKGROUND

In a series of studies of the gut microbiome, "enterotypes" have been used to classify gut microbiome samples that cluster together in ordination analyses. Initially, three distinct enterotypes were described, although later studies reduced this to two clusters, one dominated by Bacteroides or Clostridiales species found more commonly in Western (American and Western European) subjects and the other dominated by Prevotella more often associated with non-Western subjects. The two taxa, Bacteroides and Prevotella, have been presumed to represent consistent underlying microbial communities, but no one has demonstrated the presence of additional microbial taxa across studies that can define these communities.

RESULTS

We analyzed the combined microbiome data from five previous studies with samples across five continents. We clearly demonstrate that there are no consistent bacterial taxa associated with either Bacteroides- or Prevotella-dominated communities across the studies. By increasing the number and diversity of samples, we found gradients of both Bacteroides and Prevotella and a lack of the distinct clusters in the principal coordinate plots originally proposed in the "enterotypes" hypothesis. The apparent segregation of the samples seen in many ordination plots is due to the differences in the samples' Prevotella and Bacteroides abundances and does not represent consistent microbial communities within the "enterotypes" and is not associated with other taxa across studies. The projections we see are consistent with a continuum of values created from a simple mixture of Bacteroides and Prevotella; these two biomarkers are significantly correlated to the projection axes. We suggest that previous findings citing Bacteroides- and Prevotella-dominated clusters are the result of an artifact caused by the greater relative abundance of these two taxa over other taxa in the human gut and the sparsity of Prevotella abundant samples.

CONCLUSIONS

We believe that the term "enterotypes" is misleading because it implies both an underlying consistency of community taxa and a clear separation of sets of human gut samples, neither of which is supported by the broader data. We propose the use of "biomarker" as a more accurate description of these and other taxa that correlate with diet, lifestyle, and disease state.

More effective drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1

In the early days of HIV treatment, drug resistance occurred rapidly and predictably in all patients, but under modern treatments, resistance arises slowly, if at all. The probability of resistance should be controlled by the rate of generation of resistance mutations. If many adaptive mutations arise simultaneously, then adaptation proceeds by soft selective sweeps in which multiple adaptive mutations spread concomitantly, but if adaptive mutations occur rarely in the population, then a single adaptive mutation should spread alone in a hard selective sweep. Here, we use 6717 HIV-1 consensus sequences from patients treated with first-line therapies between 1989 and 2013 to confirm that the transition from fast to slow evolution of drug resistance was indeed accompanied with the expected transition from soft to hard selective sweeps. This suggests more generally that evolution proceeds via hard sweeps if resistance is unlikely and via soft sweeps if it is likely.

DOI:http://dx.doi.org/10.7554/eLife.10670.001

In the early days of HIV therapy, the strains of the virus that infected patients frequently evolved drug resistance and the therapies would often eventually fail. These treatments generally involved using a single anti-viral drug. Nowadays, better therapies involving combinations of several anti-viral drugs are available and drug resistance in HIV is a much rarer occurrence. This means that now a particular therapy may be an effective treatment for an HIV-infected individual over much longer periods of time.

A theory of population genetics predicts that when it is easy for a population to acquire a beneficial genetic mutation – like one that provides drug resistance – multiple versions of that mutation may spread in the population at the same time. This is called a soft selective sweep. However, when beneficial mutations occur only rarely, it is expected that only one version of that mutation will take over in a population, which is known as a hard selective sweep.

Here, Feder et al. test this theory using data from 6717 patients with HIV who were treated between 1989 and 2013 using a variety of different drug therapies. The experiments aimed to find out whether the transition from the older drug therapies –where the virus frequently acquired resistance – to the newer, more effective drugs was associated with a transition from soft to hard sweeps.

Feder et al. find that HIV more often evolved drug resistance via soft sweeps in patients treated with the less effective drug combinations (like those given in the early days of HIV treatment), while hard sweeps were more common with the more effective drug combinations. This suggests that good drug combinations may allow fewer drug resistance mutations to occur in the HIV population within a patient. This may be because there are fewer virus particles in these patients, or because the specific combinations of mutations that provide resistance occur less often. Feder et al.’s findings are a step towards understanding why modern HIV treatments work so well, which will ultimately help us find better treatments for other infectious diseases.

DOI:http://dx.doi.org/10.7554/eLife.10670.002

Marine mammals harbor unique microbiotas shaped by and yet distinct from the sea

Marine mammals play crucial ecological roles in the oceans, but little is known about their microbiotas. Here we study the bacterial communities in 337 samples from 5 body sites in 48 healthy dolphins and 18 healthy sea lions, as well as those of adjacent seawater and other hosts. The bacterial taxonomic compositions are distinct from those of other mammals, dietary fish and seawater, are highly diverse and vary according to body site and host species. Dolphins harbour 30 bacterial phyla, with 25 of them in the mouth, several abundant but poorly characterized Tenericutes species in gastric fluid and a surprisingly paucity of Bacteroidetes in distal gut. About 70% of near-full length bacterial 16S ribosomal RNA sequences from dolphins are unique. Host habitat, diet and phylogeny all contribute to variation in marine mammal distal gut microbiota composition. Our findings help elucidate the factors structuring marine mammal microbiotas and may enhance monitoring of marine mammal health.

Variation in Taxonomic Composition of the Fecal Microbiota in an Inbred Mouse Strain across Individuals and Time

Genetics, diet, and other environmental exposures are thought to be major factors in the development and composition of the intestinal microbiota of animals. However, the relative contributions of these factors in adult animals, as well as variation with time in a variety of important settings, are still not fully understood. We studied a population of inbred, female mice fed the same diet and housed under the same conditions. We collected fecal samples from 46 individual mice over two weeks, sampling four of these mice for periods as long as 236 days for a total of 190 samples, and determined the phylogenetic composition of their microbial communities after analyzing 1,849,990 high-quality pyrosequencing reads of the 16S rRNA gene V3 region. Even under these controlled conditions, we found significant inter-individual variation in community composition, as well as variation within an individual over time, including increases in alpha diversity during the first 2 months of co-habitation. Some variation was explained by mouse membership in different cage and vendor shipment groups. The differences among individual mice from the same shipment group and cage were still significant. Overall, we found that 23% of the variation in intestinal microbiota composition was explained by changes within the fecal microbiota of a mouse over time, 12% was explained by persistent differences among individual mice, 14% by cage, and 18% by shipment group. Our findings suggest that the microbiota of controlled populations of inbred laboratory animals may not be as uniform as previously thought, that animal rearing and handling may account for some variation, and that as yet unidentified factors may explain additional components of variation in the composition of the microbiota within populations and individuals over time. These findings have implications for the design and interpretation of experiments involving laboratory animals.

Genetically dictated change in host mucus carbohydrate landscape exerts a diet-dependent effect on the gut microbiota

We investigate how host mucus glycan composition interacts with dietary carbohydrate content to influence the composition and expressed functions of a human gut community. The humanized gnotobiotic mice mimic humans with a nonsecretor phenotype due to knockout of their α1-2 fucosyltransferase (Fut2) gene. The fecal microbiota of Fut2(-) mice that lack fucosylated host glycans show decreased alpha diversity relative to Fut2(+) mice and exhibit significant differences in community composition. A glucose-rich plant polysaccharide-deficient (PD) diet exerted a strong effect on the microbiota membership but eliminated the effect of Fut2 genotype. Additionally fecal metabolites predicted host genotype in mice on a polysaccharide-rich standard diet but not on a PD diet. A more detailed mechanistic analysis of these interactions involved colonization of gnotobiotic Fut2(+) and Fut2(-) mice with Bacteroides thetaiotaomicron, a prominent member of the human gut microbiota known to adaptively forage host mucosal glycans when dietary polysaccharides are absent. Within Fut2(-) mice, the B. thetaiotaomicron fucose catabolic pathway was markedly down-regulated, whereas BT4241-4247, an operon responsive to terminal β-galactose, the precursor that accumulates in the Fut2(-) mice, was significantly up-regulated. These changes in B. thetaiotaomicron gene expression were only evident in mice fed a PD diet, wherein B. thetaiotaomicron relies on host mucus consumption. Furthermore, up-regulation of the BT4241-4247 operon was also seen in humanized Fut2(-) mice. Together, these data demonstrate that differences in host genotype that affect the carbohydrate landscape of the distal gut interact with diet to alter the composition and function of resident microbes in a diet-dependent manner.

PRC2/EED-EZH2 complex is up-regulated in breast cancer lymph node metastasis compared to primary tumor and correlates with tumor proliferation in situ

BACKGROUND

Lymph node metastasis is a key event in the progression of breast cancer. Therefore it is important to understand the underlying mechanisms which facilitate regional lymph node metastatic progression.

METHODOLOGY/PRINCIPAL FINDINGS

We performed gene expression profiling of purified tumor cells from human breast tumor and lymph node metastasis. By microarray network analysis, we found an increased expression of polycomb repression complex 2 (PRC2) core subunits EED and EZH2 in lymph node metastatic tumor cells over primary tumor cells which were validated through real-time PCR. Additionally, immunohistochemical (IHC) staining and quantitative image analysis of whole tissue sections showed a significant increase of EZH2 expressing tumor cells in lymph nodes over paired primary breast tumors, which strongly correlated with tumor cell proliferation in situ. We further explored the mechanisms of PRC2 gene up-regulation in metastatic tumor cells and found up-regulation of E2F genes, MYC targets and down-regulation of tumor suppressor gene E-cadherin targets in lymph node metastasis through GSEA analyses. Using IHC, the expression of potential EZH2 target, E-cadherin was examined in paired primary/lymph node samples and was found to be significantly decreased in lymph node metastases over paired primary tumors.

CONCLUSIONS/SIGNIFICANCE

This study identified an over expression of the epigenetic silencing complex PRC2/EED-EZH2 in breast cancer lymph node metastasis as compared to primary tumor and its positive association with tumor cell proliferation in situ. Concurrently, PRC2 target protein E-cadherin was significant decreased in lymph node metastases, suggesting PRC2 promotes epithelial mesenchymal transition (EMT) in lymph node metastatic process through repression of E-cadherin. These results indicate that epigenetic regulation mediated by PRC2 proteins may provide additional advantage for the outgrowth of metastatic tumor cells in lymph nodes. This opens up epigenetic drug development possibilities for the treatment and prevention of lymph node metastasis in breast cancer.

Denoising PCR-amplified metagenome data

Background

PCR amplification and high-throughput sequencing theoretically enable the characterization of the finest-scale diversity in natural microbial and viral populations, but each of these methods introduces random errors that are difficult to distinguish from genuine biological diversity. Several approaches have been proposed to denoise these data but lack either speed or accuracy.

Results

We introduce a new denoising algorithm that we call DADA (Divisive Amplicon Denoising Algorithm). Without training data, DADA infers both the sample genotypes and error parameters that produced a metagenome data set. We demonstrate performance on control data sequenced on Roche’s 454 platform, and compare the results to the most accurate denoising software currently available, AmpliconNoise.

Conclusions

DADA is more accurate and over an order of magnitude faster than AmpliconNoise. It eliminates the need for training data to establish error parameters, fully utilizes sequence-abundance information, and enables inclusion of context-dependent PCR error rates. It should be readily extensible to other sequencing platforms such as Illumina.

Magnetic resonance imaging for the differentiation of neoplastic, inflammatory, and cerebrovascular brain disease in dogs

BACKGROUND

The reliability and validity of magnetic resonance imaging (MRI) for detecting neoplastic, inflammatory, and cerebrovascular brain lesions in dogs are unknown.

OBJECTIVES

To estimate sensitivity, specificity, and inter-rater agreement of MRI for classifying histologically confirmed neoplastic, inflammatory, and cerebrovascular brain disease in dogs.

ANIMALS

One hundred and twenty-one client-owned dogs diagnosed with brain disease (n = 77) or idiopathic epilepsy (n = 44).

METHODS

Retrospective, multi-institutional case series; 3 investigators analyzed MR images for the presence of a brain lesion with and without knowledge of case clinical data. Investigators recorded most likely etiologic category (neoplastic, inflammatory, cerebrovascular) and most likely specific disease for all brain lesions. Sensitivity, specificity, and inter-rater agreement were calculated to estimate diagnostic performance.

RESULTS

MRI was 94.4% sensitive (95% confidence interval [CI] = 88.7, 97.4) and 95.5% specific (95% CI = 89.9, 98.1) for detecting a brain lesion with similarly high performance for classifying neoplastic and inflammatory disease, but was only 38.9% sensitive for classifying cerebrovascular disease (95% CI = 16.1, 67.0). In general, high specificity but not sensitivity was retained for MR diagnosis of specific brain diseases. Inter-rater agreement was very good for overall detection of structural brain lesions (κ = 0.895, 95% CI = 0.792, 0.998, P < .001) and neoplastic lesions, but was only fair for cerebrovascular lesions (κ = 0.299, 95% CI = 0, 0.761, P = .21).

CONCLUSIONS AND CLINICAL IMPORTANCE

MRI is sensitive and specific for identifying brain lesions and classifying disease as inflammatory or neoplastic in dogs. Cerebrovascular disease in general and specific inflammatory, neoplastic, and cerebrovascular brain diseases were frequently misclassified.

Magnetic resonance imaging enhancement of intervertebral disc disease in 30 dogs following chemical fat saturation

OBJECTIVE

To describe the patterns of enhancement of extradural intervertebral disc on chemically fat saturated gadolinium-enhanced magnetic resonance images and to investigate the clinical and pathological associations with enhancement.

METHODS

Medical records and magnetic resonance images were reviewed from 30 dogs with histopathologically confirmed disc disease and enhancement on a T1-weighted postcontrast fat saturated sequence.

RESULTS

Median duration of neurological signs was 4 days and the most common grade of severity was II, seen in 46·6% of dogs. Homogeneous, heterogeneous and peripheral patterns of disc enhancement were described, with peripheral enhancement most commonly identified (57% of dogs). There were no clinical or pathological differences between the dogs with each of the patterns. The mean signal intensity of a region of interest within the extruded disc material and contrast-to-noise ratio of the disc material were significantly higher on postcontrast T1-weighted fat saturated images (P=<0·0001 each).

CLINICAL SIGNIFICANCE

The use of fat saturated gadolinium-enhanced magnetic resonance imaging can detect enhancement of extradural disc material. Patterns of enhancement are not associated with the clinical presentation or pathological features.

A multifaceted analysis of HIV-1 protease multidrug resistance phenotypes

Background

Great strides have been made in the effective treatment of HIV-1 with the development of second-generation protease inhibitors (PIs) that are effective against historically multi-PI-resistant HIV-1 variants. Nevertheless, mutation patterns that confer decreasing susceptibility to available PIs continue to arise within the population. Understanding the phenotypic and genotypic patterns responsible for multi-PI resistance is necessary for developing PIs that are active against clinically-relevant PI-resistant HIV-1 variants.

Results

In this work, we use globally optimal integer programming-based clustering techniques to elucidate multi-PI phenotypic resistance patterns using a data set of 398 HIV-1 protease sequences that have each been phenotyped for susceptibility toward the nine clinically-approved HIV-1 PIs. We validate the information content of the clusters by evaluating their ability to predict the level of decreased susceptibility to each of the available PIs using a cross validation procedure. We demonstrate the finding that as a result of phenotypic cross resistance, the considered clinical HIV-1 protease isolates are confined to ~6% or less of the clinically-relevant phenotypic space. Clustering and feature selection methods are used to find representative sequences and mutations for major resistance phenotypes to elucidate their genotypic signatures. We show that phenotypic similarity does not imply genotypic similarity, that different PI-resistance mutation patterns can give rise to HIV-1 isolates with similar phenotypic profiles.

Conclusion

Rather than characterizing HIV-1 susceptibility toward each PI individually, our study offers a unique perspective on the phenomenon of PI class resistance by uncovering major multidrug-resistant phenotypic patterns and their often diverse genotypic determinants, providing a methodology that can be applied to understand clinically-relevant phenotypic patterns to aid in the design of novel inhibitors that target other rapidly evolving molecular targets as well.

Adaptive importance sampling for network growth models

Network Growth Models such as Preferential Attachment and Duplication/Divergence are popular generative models with which to study complex networks in biology, sociology, and computer science. However, analyzing them within the framework of model selection and statistical inference is often complicated and computationally difficult, particularly when comparing models that are not directly related or nested. In practice, ad hoc methods are often used with uncertain results. If possible, the use of standard likelihood-based statistical model selection techniques is desirable. With this in mind, we develop an Adaptive Importance Sampling algorithm for estimating likelihoods of Network Growth Models. We introduce the use of the classic Plackett-Luce model of rankings as a family of importance distributions. Updates to importance distributions are performed iteratively via the Cross-Entropy Method with an additional correction for degeneracy/over-fitting inspired by the Minimum Description Length principle. This correction can be applied to other estimation problems using the Cross-Entropy method for integration/approximate counting, and it provides an interpretation of Adaptive Importance Sampling as iterative model selection. Empirical results for the Preferential Attachment model are given, along with a comparison to an alternative established technique, Annealed Importance Sampling.

A classification model for G-to-A hypermutation in hepatitis B virus ultra-deep pyrosequencing reads

MOTIVATION

G → A hypermutation is an innate antiviral defense mechanism, mediated by host enzymes, which leads to the mutational impairment of viruses. Sensitive and specific identification of host-mediated G → A hypermutation is a novel sequence analysis challenge, particularly for viral deep sequencing studies. For example, two of the most common hepatitis B virus (HBV) reverse transcriptase (RT) drug-resistance mutations, A181T and M204I, arise from G → A changes and are routinely detected as low-abundance variants in nearly all HBV deep sequencing samples.

RESULTS

We developed a classification model using measures of G → A excess and predicted indicators of lethal mutation and applied this model to 325 920 unique deep sequencing reads from plasma virus samples from 45 drug treatment-naïve HBV-infected individuals. The 2.9% of sequence reads that were classified as hypermutated by our model included most of the reads with A181T and/or M204I, indicating the usefulness of this model for distinguishing viral adaptive changes from host-mediated viral editing.

AVAILABILITY

Source code and sequence data are available at http://hivdb.stanford.edu/pages/resources.html.

CONTACT

ereuman@stanfordalumni.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Constrained patterns of covariation and clustering of HIV-1 non-nucleoside reverse transcriptase inhibitor resistance mutations

Objectives

We characterized pairwise and higher order patterns of non-nucleoside reverse transcriptase inhibitor (NNRTI)-selected mutations because multiple mutations are usually required for clinically significant resistance to second-generation NNRTIs.

Patients and methods

We analysed viruses from 13 039 individuals with sequences containing at least one of 52 published NNRTI-selected mutations, including 1133 viruses from individuals who received efavirenz but no other NNRTI and 1510 viruses from individuals who received nevirapine but no other NNRTI. Of the 17 reported etravirine resistance-associated mutations (RAMs), Y181C/I/V, L100I, K101P and M230L were considered major based on published in vitro susceptibility data.

Results

Efavirenz preferentially selected for 16 mutations, including L100I (14% versus 0.1%, P < 0.001), K101P (3.3% versus 0.4%, P < 0.001) and M230L (2.8% versus 1.3%, P = 0.004), whereas nevirapine preferentially selected for 12 mutations, including Y181C/I/V (48% versus 6.9%, P < 0.001). Twenty-nine pairs of NNRTI-selected mutations covaried significantly, including Y181C with seven other mutations (A98G, K101E/H, V108I, G190A/S and H221Y), L100I with K103N, and K101P with K103S. Two pairs (Y181C + V179F and Y181C + G190S) were predicted to confer >10-fold decreased etravirine susceptibility. Seventeen percent of sequences had three or more NNRTI-selected mutations, mostly in clusters of covarying mutations. Many clusters had Y181C plus a non-major etravirine RAM; few had more than one major etravirine RAM.

Conclusions

Although major etravirine RAMs rarely occur in combination, 2 of 29 pairs of covarying mutations were associated with >10-fold decreased etravirine susceptibility. Viruses with three or more NNRTI-selected mutations often contained Y181C in combination with one or more minor etravirine RAMs; however, phenotypic and clinical correlates for most of these higher order combinations have not been published.

Ultra-deep pyrosequencing of hepatitis B virus quasispecies from nucleoside and nucleotide reverse-transcriptase inhibitor (NRTI)-treated patients and NRTI-naive patients

The dynamics of emerging nucleoside and nucleotide reverse-transcriptase inhibitor (NRTI) resistance in hepatitis B virus (HBV) are not well understood because standard dideoxynucleotide direct polymerase chain reaction (PCR) sequencing assays detect drug-resistance mutations only after they have become dominant. To obtain insight into NRTI resistance, we used a new sequencing technology to characterize the spectrum of low-prevalence NRTI-resistance mutations in HBV obtained from 20 plasma samples from 11 NRTI-treated patients and 17 plasma samples from 17 NRTI-naive patients, by using standard direct PCR sequencing and ultra-deep pyrosequencing (UDPS). UDPS detected drug-resistance mutations that were not detected by PCR in 10 samples from 5 NRTI-treated patients, including the lamivudine-resistance mutation V173L (in 5 samples), the entecavir-resistance mutations T184S (in 2 samples) and S202G (in 1 sample), the adefovir-resistance mutation N236T (in 1 sample), and the lamivudine and adefovir-resistance mutations V173L, L180M, A181T, and M204V (in 1 sample). G-to-A hypermutation mediated by the apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like family of cytidine deaminases was estimated to be present in 0.6% of reverse-transcriptase genes. Genotype A coinfection was detected by UDPS in each of 3 patients in whom genotype G virus was detected by direct PCR sequencing. UDPS detected low-prevalence HBV variants with NRTI-resistance mutations, G-to-A hypermutation, and low-level dual genotype infection with a sensitivity not previously possible.

Natural variation of HIV-1 group M integrase: implications for a new class of antiretroviral inhibitors

HIV-1 integrase is the third enzymatic target of antiretroviral (ARV) therapy. However, few data have been published on the distribution of naturally occurring amino acid variation in this enzyme. We therefore characterized the distribution of integrase variants among more than 1,800 published group M HIV-1 isolates from more than 1,500 integrase inhibitor (INI)-naïve individuals. Polymorphism rates equal or above 0.5% were found for 34% of the central core domain positions, 42% of the C-terminal domain positions, and 50% of the N-terminal domain positions. Among 727 ARV-naïve individuals in whom the complete pol gene was sequenced, integrase displayed significantly decreased inter- and intra-subtype diversity and a lower Shannon's entropy than protease or RT. All primary INI-resistance mutations with the exception of E157Q--which was present in 1.1% of sequences--were nonpolymorphic. Several accessory INI-resistance mutations including L74M, T97A, V151I, G163R, and S230N were also polymorphic with polymorphism rates ranging between 0.5% to 2.0%.

HIV-1 subtype B protease and reverse transcriptase amino acid covariation

Despite the high degree of HIV-1 protease and reverse transcriptase (RT) mutation in the setting of antiretroviral therapy, the spectrum of possible virus variants appears to be limited by patterns of amino acid covariation. We analyzed patterns of amino acid covariation in protease and RT sequences from more than 7,000 persons infected with HIV-1 subtype B viruses obtained from the Stanford HIV Drug Resistance Database (http://hivdb.stanford.edu). In addition, we examined the relationship between conditional probabilities associated with a pair of mutations and the order in which those mutations developed in viruses for which longitudinal sequence data were available. Patterns of RT covariation were dominated by the distinct clustering of Type I and Type II thymidine analog mutations and the Q151M-associated mutations. Patterns of protease covariation were dominated by the clustering of nelfinavir-associated mutations (D30N and N88D), two main groups of protease inhibitor (PI)-resistance mutations associated either with V82A or L90M, and a tight cluster of mutations associated with decreased susceptibility to amprenavir and the most recently approved PI darunavir. Different patterns of covariation were frequently observed for different mutations at the same position including the RT mutations T69D versus T69N, L74V versus L74I, V75I versus V75M, T215F versus T215Y, and K219Q/E versus K219N/R, and the protease mutations M46I versus M46L, I54V versus I54M/L, and N88D versus N88S. Sequence data from persons with correlated mutations in whom earlier sequences were available confirmed that the conditional probabilities associated with correlated mutation pairs could be used to predict the order in which the mutations were likely to have developed. Whereas accessory nucleoside RT inhibitor-resistance mutations nearly always follow primary nucleoside RT inhibitor-resistance mutations, accessory PI-resistance mutations often preceded primary PI-resistance mutations.

Down-regulation of the interferon signaling pathway in T lymphocytes from patients with metastatic melanoma

BACKGROUND

Dysfunction of the immune system has been documented in many types of cancers. The precise nature and molecular basis of immune dysfunction in the cancer state are not well defined.

METHODS AND FINDINGS

To gain insights into the molecular mechanisms of immune dysfunction in cancer, gene expression profiles of pure sorted peripheral blood lymphocytes from 12 patients with melanoma were compared to 12 healthy controls. Of 25 significantly altered genes in T cells and B cells from melanoma patients, 17 are interferon (IFN)-stimulated genes. These microarray findings were further confirmed by quantitative PCR and functional responses to IFNs. The median percentage of lymphocytes that phosphorylate STAT1 in response to interferon-alpha was significantly reduced (Delta = 16.8%; 95% confidence interval, 0.98% to 33.35%) in melanoma patients (n = 9) compared to healthy controls (n = 9) in Phosflow analysis. The Phosflow results also identified two subgroups of patients with melanoma: IFN-responsive (33%) and low-IFN-response (66%). The defect in IFN signaling in the melanoma patient group as a whole was partially overcome at the level of expression of IFN-stimulated genes by prolonged stimulation with the high concentration of IFN-alpha that is achievable only in IFN therapy used in melanoma. The lowest responders to IFN-alpha in the Phosflow assay also showed the lowest gene expression in response to IFN-alpha. Finally, T cells from low-IFN-response patients exhibited functional abnormalities, including decreased expression of activation markers CD69, CD25, and CD71; TH1 cytokines interleukin-2, IFN-gamma, and tumor necrosis factor alpha, and reduced survival following stimulation with anti-CD3/CD28 antibodies compared to controls.

CONCLUSIONS

Defects in interferon signaling represent novel, dominant mechanisms of immune dysfunction in cancer. These findings may be used to design therapies to counteract immune dysfunction in melanoma and to improve cancer immunotherapy.

Rapid assessment of recognition efficiency and functional capacity of antigen-specific T-cell responses

It is increasingly recognized that cells within an antigen-specific CD8 T-cell population may be diverse in recognition efficiency for target, which may significantly affect the overall efficacy of the response in clinical settings such as viral infections and cancer. CD8 T cells with seemingly identical antigen specificity, particularly those elicited by cancer vaccines, may be heterogeneous for sensitivity and recognition efficiency for the cognate peptide and functional state in vivo. Analysis of individual T-cell clones derived from an antigen-specific T-cell population would provide an accurate assessment of the overall response; however, this is time- and labor-intensive, preventing rapid and routine assessment of patient samples from clinical trials. By stimulating antigen-specific T cells that otherwise appear homogeneous on tetramer staining with graded amounts of cognate peptides, the authors show that individual cells downmodulate surface T-cell receptors (TCR) and thus lose tetramer reactivity with variable dynamics within the T-cell population. The dynamics of TCR downregulation represent an accurate assessment of an individual cell's antigen sensitivity, recognition efficiency, and relative functional state within an antigen-specific population and have direct correlation to killing capacity by chromium release as well as degranulation by CD107 mobilization. Furthermore, despite correlation of average T-cell function by all three techniques, TCR downregulation uncovered heterogeneity in T-cell responses after vaccination among patient samples directly ex vivo. When examined using this novel technique, antigen-specific T cells elicited by vaccination with heteroclitic peptides exhibited significantly different recognition efficiencies for the heteroclitic versus native peptides, translating into differences in functional responses. With advancing cancer vaccine trials, the capacity to detect and functionally characterize antigen-specific T-cell responses in detail is critical. Techniques, as presented here, that rapidly assess the overall antigen sensitivity, recognition efficiency, and functional status of patients' T-cell responses will guide future vaccine trials and immunotherapies.