Allyson L. Byrd

Commensal–dendritic-cell interaction specifies a unique protective skin immune signature

The skin represents the primary interface between the host and the environment. This organ is also home to trillions of microorganisms that play an important role in tissue homeostasis and local immunity. Skin microbial communities are highly diverse and can be remodelled over time or in response to environmental challenges. How, in the context of this complexity, individual commensal microorganisms may differentially modulate skin immunity and the consequences of these responses for tissue physiology remains unclear. Here we show that defined commensals dominantly affect skin immunity and identify the cellular mediators involved in this specification. In particular, colonization with Staphylococcus epidermidis induces IL-17A+ CD8+ T cells that home to the epidermis, enhance innate barrier immunity and limit pathogen invasion. Commensal-specific T-cell responses result from the coordinated action of skin-resident dendritic cell subsets and are not associated with inflammation, revealing that tissue-resident cells are poised to sense and respond to alterations in microbial communities. This interaction may represent an evolutionary means by which the skin immune system uses fluctuating commensal signals to calibrate barrier immunity and provide heterologous protection against invasive pathogens. These findings reveal that the skin immune landscape is a highly dynamic environment that can be rapidly and specifically remodelled by encounters with defined commensals, findings that have profound implications for our understanding of tissue-specific immunity and pathologies.

Microbiota-Dependent Sequelae of Acute Infection Compromise Tissue-Specific Immunity

Infections have been proposed as initiating factors for inflammatory disorders; however, identifying associations between defined infectious agents and the initiation of chronic disease has remained elusive. Here, we report that a single acute infection can have dramatic and long-term consequences for tissue-specific immunity. Following clearance of Yersinia pseudotuberculosis, sustained inflammation and associated lymphatic leakage in the mesenteric adipose tissue deviates migratory dendritic cells to the adipose compartment, thereby preventing their accumulation in the mesenteric lymph node. As a consequence, canonical mucosal immune functions, including tolerance and protective immunity, are persistently compromised. Post-resolution of infection, signals derived from the microbiota maintain inflammatory mesentery remodeling and consequently, transient ablation of the microbiota restores mucosal immunity. Our results indicate that persistent disruption of communication between tissues and the immune system following clearance of an acute infection represents an inflection point beyond which tissue homeostasis and immunity is compromised for the long-term. VIDEO ABSTRACT.

Adapting Koch's postulates

Criteria for disease causation must take microbial interactions into account In the late 19th century, Robert Koch established his famous postulates as stringent guidelines to evaluate causation in infectious disease (1). These original postulates require isolation of the putative pathogen and reinfection of a healthy host to prove causation. Over the years, Kochs postulates have been continually restated to incorporate the latest scientific findings and technologies (2–5). Modern molecular techniques have demonstrated that current or previous members of a microbial community can affect disease outcome, providing a nuanced view of strict causation as originally proposed by Koch. There is thus a need to incorporate microbial communities into rigorous modern guidelines for evaluating disease causation.

PathoScope 2.0: a complete computational framework for strain identification in environmental or clinical sequencing samples

BackgroundRecent innovations in sequencing technologies have provided researchers with the ability to rapidly characterize the microbial content of an environmental or clinical sample with unprecedented resolution. These approaches are producing a wealth of information that is providing novel insights into the microbial ecology of the environment and human health. However, these sequencing-based approaches produce large and complex datasets that require efficient and sensitive computational analysis workflows. Many recent tools for analyzing metagenomic-sequencing data have emerged, however, these approaches often suffer from issues of specificity, efficiency, and typically do not include a complete metagenomic analysis framework.ResultsWe present PathoScope 2.0, a complete bioinformatics framework for rapidly and accurately quantifying the proportions of reads from individual microbial strains present in metagenomic sequencing data from environmental or clinical samples. The pipeline performs all necessary computational analysis steps; including reference genome library extraction and indexing, read quality control and alignment, strain identification, and summarization and annotation of results. We rigorously evaluated PathoScope 2.0 using simulated data and data from the 2011 outbreak of Shiga-toxigenic Escherichia coli O104:H4.ConclusionsThe results show that PathoScope 2.0 is a complete, highly sensitive, and efficient approach for metagenomic analysis that outperforms alternative approaches in scope, speed, and accuracy. The PathoScope 2.0 pipeline software is freely available for download at: http://sourceforge.net/projects/pathoscope/.

Staphylococcus aureus and Staphylococcus epidermidis strain diversity underlying pediatric atopic dermatitis.

Genomic and functional analyses of staphylococcal strain specificity reveal roles for microbes in human atopic dermatitis pathogenesis. Diving into the depths of atopic dermatitis The genus Staphylococcus is a known component of atopic dermatitis. In this issue, Byrd et al. used shotgun metagenomic sequencing to analyze the species and strains present at baseline and during flares in pediatric atopic dermatitis. They observed that patients with more mild disease had more Staphylococcus epidermidis detected in flares and that those with severe disease were colonized by dominant clonal Staphylococcus aureus strains. S. aureus strains from patients were applied to mouse skin, and strains from severe flares induced T cell expansion and epidermal thickening. These results highlight that not all Staphylococcus can be considered the same, even at the strain level, when it comes to atopic dermatitis pathogenesis. The heterogeneous course, severity, and treatment responses among patients with atopic dermatitis (AD; eczema) highlight the complexity of this multifactorial disease. Prior studies have used traditional typing methods on cultivated isolates or sequenced a bacterial marker gene to study the skin microbial communities of AD patients. Shotgun metagenomic sequence analysis provides much greater resolution, elucidating multiple levels of microbial community assembly ranging from kingdom to species and strain-level diversification. We analyzed microbial temporal dynamics from a cohort of pediatric AD patients sampled throughout the disease course. Species-level investigation of AD flares showed greater Staphylococcus aureus predominance in patients with more severe disease and Staphylococcus epidermidis predominance in patients with less severe disease. At the strain level, metagenomic sequencing analyses demonstrated clonal S. aureus strains in more severe patients and heterogeneous S. epidermidis strain communities in all patients. To investigate strain-level biological effects of S. aureus, we topically colonized mice with human strains isolated from AD patients and controls. This cutaneous colonization model demonstrated S. aureus strain–specific differences in eliciting skin inflammation and immune signatures characteristic of AD patients. Specifically, S. aureus isolates from AD patients with more severe flares induced epidermal thickening and expansion of cutaneous T helper 2 (TH2) and TH17 cells. Integrating high-resolution sequencing, culturing, and animal models demonstrated how functional differences of staphylococcal strains may contribute to the complexity of AD disease.

Clinical PathoScope: rapid alignment and filtration for accurate pathogen identification in clinical samples using unassembled sequencing data

BackgroundThe use of sequencing technologies to investigate the microbiome of a sample can positively impact patient healthcare by providing therapeutic targets for personalized disease treatment. However, these samples contain genomic sequences from various sources that complicate the identification of pathogens.ResultsHere we present Clinical PathoScope, a pipeline to rapidly and accurately remove host contamination, isolate microbial reads, and identify potential disease-causing pathogens. We have accomplished three essential tasks in the development of Clinical PathoScope. First, we developed an optimized framework for pathogen identification using a computational subtraction methodology in concordance with read trimming and ambiguous read reassignment. Second, we have demonstrated the ability of our approach to identify multiple pathogens in a single clinical sample, accurately identify pathogens at the subspecies level, and determine the nearest phylogenetic neighbor of novel or highly mutated pathogens using real clinical sequencing data. Finally, we have shown that Clinical PathoScope outperforms previously published pathogen identification methods with regard to computational speed, sensitivity, and specificity.ConclusionsClinical PathoScope is the only pathogen identification method currently available that can identify multiple pathogens from mixed samples and distinguish between very closely related species and strains in samples with very few reads per pathogen. Furthermore, Clinical PathoScope does not rely on genome assembly and thus can more rapidly complete the analysis of a clinical sample when compared with current assembly-based methods. Clinical PathoScope is freely available at: http://sourceforge.net/projects/pathoscope/.

Production of a reference transcriptome and transcriptomic database (EdwardsiellaBase) for the lined sea anemone, Edwardsiella lineata, a parasitic cnidarian

BackgroundThe lined sea anemone Edwardsiella lineata is an informative model system for evolutionary-developmental studies of parasitism. In this species, it is possible to compare alternate developmental pathways leading from a larva to either a free-living polyp or a vermiform parasite that inhabits the mesoglea of a ctenophore host. Additionally, E. lineata is confamilial with the model cnidarian Nematostella vectensis, providing an opportunity for comparative genomic, molecular and organismal studies.DescriptionWe generated a reference transcriptome for E. lineata via high-throughput sequencing of RNA isolated from five developmental stages (parasite; parasite-to-larva transition; larva; larva-to-adult transition; adult). The transcriptome comprises 90,440 contigs assembled from >15 billion nucleotides of DNA sequence. Using a molecular clock approach, we estimated the divergence between E. lineata and N. vectensis at 215–364 million years ago. Based on gene ontology and metabolic pathway analyses and gene family surveys (bHLH-PAS, deiodinases, Fox genes, LIM homeodomains, minicollagens, nuclear receptors, Sox genes, and Wnts), the transcriptome of E. lineata is comparable in depth and completeness to N. vectensis. Analyses of protein motifs and revealed extensive conservation between the proteins of these two edwardsiid anemones, although we show the NF-κB protein of E. lineata reflects the ancestral structure, while the NF-κB protein of N. vectensis has undergone a split that separates the DNA-binding domain from the inhibitory domain. All contigs have been deposited in a public database (EdwardsiellaBase), where they may be searched according to contig ID, gene ontology, protein family motif (Pfam), enzyme commission number, and BLAST. The alignment of the raw reads to the contigs can also be visualized via JBrowse.ConclusionsThe transcriptomic data and database described here provide a platform for studying the evolutionary developmental genomics of a derived parasitic life cycle. In addition, these data from E. lineata will aid in the interpretation of evolutionary novelties in gene sequence or structure that have been reported for the model cnidarian N. vectensis (e.g., the split NF-κB locus). Finally, we include custom computational tools to facilitate the annotation of a transcriptome based on high-throughput sequencing data obtained from a “non-model system.”

The human skin microbiome

Functioning as the exterior interface of the human body with the environment, skin acts as a physical barrier to prevent the invasion of foreign pathogens while providing a home to the commensal microbiota. The harsh physical landscape of skin, particularly the desiccated, nutrient-poor, acidic environment, also contributes to the adversity that pathogens face when colonizing human skin. Despite this, the skin is colonized by a diverse microbiota. In this Review, we describe amplicon and shotgun metagenomic DNA sequencing studies that have been used to assess the taxonomic diversity of microorganisms that are associated with skin from the kingdom to the strain level. We discuss recent insights into skin microbial communities, including their composition in health and disease, the dynamics between species and interactions with the immune system, with a focus on Propionibacterium acnes, Staphylococcus epidermidis and Staphylococcus aureus.

White Adipose Tissue Is a Reservoir for Memory T Cells and Promotes Protective Memory Responses to Infection

Summary White adipose tissue bridges body organs and plays a fundamental role in host metabolism. To what extent adipose tissue also contributes to immune surveillance and long‐term protective defense remains largely unknown. Here, we have shown that at steady state, white adipose tissue contained abundant memory lymphocyte populations. After infection, white adipose tissue accumulated large numbers of pathogen‐specific memory T cells, including tissue‐resident cells. Memory T cells in white adipose tissue expressed a distinct metabolic profile, and white adipose tissue from previously infected mice was sufficient to protect uninfected mice from lethal pathogen challenge. Induction of recall responses within white adipose tissue was associated with the collapse of lipid metabolism in favor of antimicrobial responses. Our results suggest that white adipose tissue represents a memory T cell reservoir that provides potent and rapid effector memory responses, positioning this compartment as a potential major contributor to immunological memory. Graphical Abstract Figure. No caption available. HighlightsWhite adipose tissue serves as a reservoir for memory T cellsWhite adipose tissue memory T cells have a distinct functional and metabolic profileMemory T cells from white adipose tissue can protect against lethal infectious challengeReactivation of white adipose tissue memory T cells alters adipose tissue physiology &NA; The role of adipose tissue in protective immunity is largely unknown. Han et al. reveal that white adipose tissue is a reservoir for memory T cells endowed with a distinct functional and metabolic profile. These memory T cells are able to protect against infection while inducing physiological remodeling of adipose tissue.

Contextual control of skin immunity and inflammation by Corynebacterium

How defined microbes influence the skin immune system remains poorly understood. Here we demonstrate that Corynebacteria, dominant members of the skin microbiota, promote a dramatic increase in the number and activation of a defined subset of &ggr;&dgr; T cells. This effect is long-lasting, occurs independently of other microbes, and is, in part, mediated by interleukin (IL)-23. Under steady-state conditions, the impact of Corynebacterium is discrete and noninflammatory. However, when applied to the skin of a host fed a high-fat diet, Corynebacterium accolens alone promotes inflammation in an IL-23–dependent manner. Such effect is highly conserved among species of Corynebacterium and dependent on the expression of a dominant component of the cell envelope, mycolic acid. Our data uncover a mode of communication between the immune system and a dominant genus of the skin microbiota and reveal that the functional impact of canonical skin microbial determinants is contextually controlled by the inflammatory and metabolic state of the host.