One population, multiple lifestyles: Commensalism and pathogenesis in the human mycobiome.

Candida auris and Candida albicans can result in invasive fungal diseases. And yet, these species can stably and asymptomatically colonize human skin and gastrointestinal tracts. To consider these disparate microbial lifestyles, we first review factors shown to influence the underlying microbiome. Structured by the damage response framework, we then consider the molecular mechanisms deployed by C. albicans to switch between commensal and pathogenic lifestyles. Next, we explore this framework with C. auris to highlight how host physiology, immunity, and/or antibiotic receipt are associated with progression from colonization to infection. While treatment with antibiotics increases the risk that an individual will succumb to invasive candidiasis, the underlying mechanisms remain unclear. Here, we describe several hypotheses that may explain this phenomenon. We conclude by highlighting future directions integrating genomics with immunology to advance our understanding of invasive candidiasis and human fungal disease.

Predicting cancer immunotherapy response from gut microbiomes using machine learning models.

Cancer immunotherapy has significantly improved patient survival. Yet, half of patients do not respond to immunotherapy. Gut microbiomes have been linked to clinical responsiveness of melanoma patients on immunotherapies; however, different taxa have been associated with response status with implicated taxa inconsistent between studies. We used a tumor-agnostic approach to find common gut microbiome features of response among immunotherapy patients with different advanced stage cancers. A combined meta-analysis of 16S rRNA gene sequencing data from our mixed tumor cohort and three published immunotherapy gut microbiome datasets from different melanoma patient cohorts found certain gut bacterial taxa correlated with immunotherapy response status regardless of tumor type. Using multivariate selbal analysis, we identified two separate groups of bacterial genera associated with responders versus non-responders. Statistical models of gut microbiome community features showed robust prediction accuracy of immunotherapy response in amplicon sequencing datasets and in cross-sequencing platform validation with shotgun metagenomic datasets. Results suggest baseline gut microbiome features may be predictive of clinical outcomes in oncology patients on immunotherapies, and some of these features may be generalizable across different tumor types, patient cohorts, and sequencing platforms. Findings demonstrate how machine learning models can reveal microbiome-immunotherapy interactions that may ultimately improve cancer patient outcomes.

A mouse model of occult intestinal colonization demonstrating antibiotic-induced outgrowth of carbapenem-resistant Enterobacteriaceae.

BACKGROUND: The human intestinal microbiome is a complex community that contributes to host health and disease. In addition to normal microbiota, pathogens like carbapenem-resistant Enterobacteriaceae may be asymptomatically present. When these bacteria are present at very low levels, they are often undetectable in hospital surveillance cultures, known as occult or subclinical colonization. Through the receipt of antibiotics, these subclinical pathogens can increase to sufficiently high levels to become detectable, in a process called outgrowth. However, little is known about the interaction between gut microbiota and Enterobacteriaceae during occult colonization and outgrowth. RESULTS: We developed a clinically relevant mouse model for studying occult colonization. Conventional wild-type mice without antibiotic pre-treatment were exposed to Klebsiella pneumoniae but rapidly tested negative for colonization. This occult colonization was found to perturb the microbiome as detected by both 16S rRNA amplicon and shotgun metagenomic sequencing. Outgrowth of occult K. pneumoniae was induced either by a four-antibiotic cocktail or by individual receipt of ampicillin, vancomycin, or azithromycin, which all reduced overall microbial diversity. Notably, vancomycin was shown to trigger K. pneumoniae outgrowth in only a subset of exposed animals (outgrowth-susceptible). To identify factors that underlie outgrowth susceptibility, we analyzed microbiome-encoded gene functions and were able to classify outgrowth-susceptible microbiomes using pathways associated with mRNA stability. Lastly, an evolutionary approach illuminated the importance of xylose metabolism in K. pneumoniae colonization, supporting xylose abundance as a second susceptibility indicator. We showed that our model is generalizable to other pathogens, including carbapenem-resistant Escherichia coli and Enterobacter cloacae. CONCLUSIONS: Our modeling of occult colonization and outgrowth could help the development of strategies to mitigate the risk of subsequent infection and transmission in medical facilities and the wider community. This study suggests that microbiota mRNA and small-molecule metabolites may be used to predict outgrowth-susceptibility. Video Abstract.

Integrating cultivation and metagenomics for a multi-kingdom view of skin microbiome diversity and functions.

Human skin functions as a physical barrier to foreign pathogen invasion and houses numerous commensals. Shifts in the human skin microbiome have been associated with conditions ranging from acne to atopic dermatitis. Previous metagenomic investigations into the role of the skin microbiome in health or disease have found that much of the sequenced data do not match reference genomes, making it difficult to interpret metagenomic datasets. We combined bacterial cultivation and metagenomic sequencing to assemble the Skin Microbial Genome Collection (SMGC), which comprises 622 prokaryotic species derived from 7,535 metagenome-assembled genomes and 251 isolate genomes. The metagenomic datasets that we generated were combined with publicly available skin metagenomic datasets to identify members and functions of the human skin microbiome. The SMGC collection includes 174 newly identified bacterial species and 12 newly identified bacterial genera, including the abundant genus 'Candidatus Pellibacterium', which has been newly associated with the skin. The SMGC increases the characterized set of known skin bacteria by 26%. We validated the SMGC metagenome-assembled genomes by comparing them with sequenced isolates obtained from the same samples. We also recovered 12 eukaryotic species and assembled thousands of viral sequences, including newly identified clades of jumbo phages. The SMGC enables classification of a median of 85% of skin metagenomic sequences and provides a comprehensive view of skin microbiome diversity, derived primarily from samples obtained in North America.

Treatment of Relapsing HPV Diseases by Restored Function of Natural Killer Cells.

Human papillomavirus (HPV) infections underlie a wide spectrum of both benign and malignant epithelial diseases. In this report, we describe the case of a young man who had encephalitis caused by herpes simplex virus during adolescence and currently presented with multiple recurrent skin and mucosal lesions caused by HPV. The patient was found to have a pathogenic germline mutation in the X-linked interleukin-2 receptor subunit gamma gene (IL2RG), which was somatically reverted in T cells but not in natural killer (NK) cells. Allogeneic hematopoietic-cell transplantation led to restoration of NK cytotoxicity, with normalization of the skin microbiome and persistent remission of all HPV-related diseases. NK cytotoxicity appears to play a role in containing HPV colonization and the ensuing HPV-related hyperplastic or dysplastic lesions. (Funded by the National Institutes of Health and the Herbert Irving Comprehensive Cancer Center Flow Cytometry Shared Resources.).

Skin Metagenomic Sequence Analysis of Early Candida auris Outbreaks in U.S. Nursing Homes.

Candida auris is a human fungal pathogen classified as an urgent threat to the delivery of health care due to its extensive antimicrobial resistance and the high mortality rates associated with invasive infections. Global outbreaks have occurred in health care facilities, particularly, long-term care hospitals and nursing homes. Skin is the primary site of colonization for C. auris. To accelerate research studies, we developed microbiome sequencing protocols, including amplicon and metagenomic sequencing, directly from patient samples at health care facilities with ongoing C. auris outbreaks. We characterized the skin mycobiome with a database optimized to classify Candida species and C. auris to the clade level. While Malassezia species were the predominant skin-associated fungi, nursing home residents also harbored Candida species, including C. albicans, and C. parapsilosis. Amplicon sequencing was concordant with culturing studies to identify C. auris-colonized patients and provided further resolution that distinct clades of C. auris are colonizing facilities in New York and Illinois. Shotgun metagenomic sequencing from a clinical sample with a high fungal bioburden generated a skin-associated profile of the C. auris genome. Future larger scale clinical studies are warranted to more systematically investigate the effects of commensal microbes and patient risk factors on the colonization and transmission of C. auris. IMPORTANCE Candida auris is a human pathogen of high concern due to its extensive antifungal drug resistance and high mortality rates associated with invasive infections. Candida auris skin colonization and persistence on environmental surfaces make this pathogen difficult to control once it enters a health care facility. Residents in long-term care hospitals and nursing homes are especially vulnerable. In this study, we developed microbiome sequencing protocols directly from surveillance samples, including amplicon and metagenomic sequencing, demonstrating concordance between sequencing results and culturing.

Integrated genomic, epidemiologic investigation of Candida auris skin colonization in a skilled nursing facility.

Candida auris is a fungal pathogen of high concern due to its ability to cause healthcare-associated infections and outbreaks, its resistance to antimicrobials and disinfectants and its persistence on human skin and in the inanimate environment. To inform surveillance and future mitigation strategies, we defined the extent of skin colonization and explored the microbiome associated with C. auris colonization. We collected swab specimens and clinical data at three times points between January and April 2019 from 57 residents (up to ten body sites each) of a ventilator-capable skilled nursing facility with endemic C. auris and routine chlorhexidine gluconate (CHG) bathing. Integrating microbial-genomic and epidemiologic data revealed occult C. auris colonization of multiple body sites not targeted commonly for screening. High concentrations of CHG were associated with suppression of C. auris growth but not with deleterious perturbation of commensal microbes. Modeling human mycobiome dynamics provided insight into underlying alterations to the skin fungal community as a possible modifiable risk factor for acquisition and persistence of C. auris. Failure to detect the extensive, disparate niches of C. auris colonization may reduce the effectiveness of infection-prevention measures that target colonized residents, highlighting the importance of universal strategies to reduce C. auris transmission.

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.

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.

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.

The Landscape Ecology and Microbiota of the Human Nose, Mouth, and Throat.

Landscape ecology examines the relationships between the spatial arrangement of different landforms and the processes that give rise to spatial and temporal patterns in local community structure. The spatial ecology of the microbial communities that inhabit the human body-in particular, those of the nose, mouth, and throat-deserves greater attention. Important questions include what defines the size of a population (i.e., "patch") in a given body site, what defines the boundaries of distinct patches within a single body site, and where and over what spatial scales within a body site are gradients detected. This Review looks at the landscape ecology of the upper respiratory tract and mouth and seeks greater clarity about the physiological factors-whether immunological, chemical, or physical-that govern microbial community composition and function and the ecological traits that underlie health and disease.