Bottom-up ecology of the human microbiome: from metagenomes to metabolomes

Identification of Complex Multidimensional Patterns in Microbial Communities

10.1101/540815 ◽

2019 ◽

Author(s):

Golovko George ◽

Khanipov Kamil ◽

Albayrak Levent ◽

Fofanov Yuriy

Keyword(s):

Microbial Communities ◽

Statistical Significance ◽

Source Code ◽

Three Dimensional ◽

Human Microbiome ◽

Human Microbiome Project ◽

Site Specific ◽

Information Coefficient ◽

Complex Relationships ◽

Project Data

AbstractMotivationIdentification of complex relationships within members of microbial communities is key to understand and guide microbial transplantation and provide personalized anti-microbial and probiotic treatments. Since members of a given microbial community can be simultaneously involved in multiple relations that altogether will determine their abundance, not all significant relations between organisms are expected to be manifested as visually uninterrupted patterns and be detected using traditional correlation nor mutual information coefficient based approaches.ResultsThis manuscript proposes a pattern specific way to quantify the strength and estimate the statistical significance of two-dimensional co-presence, co-exclusion, and one-way relations patterns between abundance profiles of two organisms which can be extended to three or more dimensional patterns. Presented approach can also be extended by including a variety of physical (pH, temperature, oxygen concentration) and biochemical (antimicrobial susceptibility, nutrient and metabolite concentration) variables into the search for multidimensional patterns. The presented approach has been tested using 2,380 microbiome samples from the Human Microbiome Project resulting in body-site specific networks of statistically significant 2D patterns. We also were able to demonstrate the presence of several 3D patterns in the Human Microbiome Project data.AvailabilityC++ source code for two and three-dimensional patterns, as well as executable files for the Pickle pipeline, are in the attached supplementary [email protected]

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Comprehensive skin microbiome analysis reveals the uniqueness of human skin and evidence for phylosymbiosis within the class Mammalia

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1801302115 ◽

2018 ◽

Vol 115 (25) ◽

pp. E5786-E5795 ◽

Cited By ~ 59

Author(s):

Ashley A. Ross ◽

Kirsten M. Müller ◽

J. Scott Weese ◽

Josh D. Neufeld

Keyword(s):

Microbial Community ◽

Microbial Communities ◽

Human Skin ◽

Microbial Community Composition ◽

Geographic Location ◽

The Body ◽

16S Rrna Genes ◽

Rrna Genes ◽

Skin Microbiome ◽

Skin Microbiota

Skin is the largest organ of the body and represents the primary physical barrier between mammals and their external environment, yet the factors that govern skin microbial community composition among mammals are poorly understood. The objective of this research was to generate a skin microbiota baseline for members of the class Mammalia, testing the effects of host species, geographic location, body region, and biological sex. Skin from the back, torso, and inner thighs of 177 nonhuman mammals was sampled, representing individuals from 38 species and 10 mammalian orders. Animals were sampled from farms, zoos, households, and the wild. The DNA extracts from all skin swabs were amplified by PCR and sequenced, targeting the V3-V4 regions of bacterial and archaeal 16S rRNA genes. Previously published skin microbiome data from 20 human participants, sampled and sequenced using an identical protocol to the nonhuman mammals, were included to make this a comprehensive analysis. Human skin microbial communities were distinct and significantly less diverse than all other sampled mammalian orders. The factor most strongly associated with microbial community data for all samples was whether the host was a human. Within nonhuman samples, host taxonomic order was the most significant factor influencing skin microbiota, followed by the geographic location of the habitat. By comparing the congruence between host phylogeny and microbial community dendrograms, we observed that Artiodactyla (even-toed ungulates) and Perissodactyla (odd-toed ungulates) had significant congruence, providing evidence of phylosymbiosis between skin microbial communities and their hosts.

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Body site-specific microbiota reflect sex and age-class among wild spotted hyenas

FEMS Microbiology Ecology ◽

10.1093/femsec/fiaa007 ◽

2020 ◽

Vol 96 (2) ◽

Cited By ~ 3

Author(s):

Connie A Rojas ◽

Kay E Holekamp ◽

Andrew D Winters ◽

Kevin R Theis

Keyword(s):

Microbial Communities ◽

Mammalian Species ◽

Social Rank ◽

Rrna Gene ◽

Body Site ◽

Scent Gland ◽

Site Specific ◽

Adult Females ◽

Host Sex ◽

Spotted Hyenas

ABSTRACT Host-associated microbial communities, henceforth ‘microbiota’, can affect the physiology and behavior of their hosts. In mammals, host ecological, social and environmental variables are associated with variation in microbial communities. Within individuals in a given mammalian species, the microbiota also partitions by body site. Here, we build on this work and sequence the bacterial 16S rRNA gene to profile the microbiota at six distinct body sites (ear, nasal and oral cavities, prepuce, rectum and anal scent gland) in a population of wild spotted hyenas (Crocuta crocuta), which are highly social, large African carnivores. We inquired whether microbiota at these body sites vary with host sex or social rank among juvenile hyenas, and whether they differ between juvenile females and adult females. We found that the scent gland microbiota differed between juvenile males and juvenile females, whereas the prepuce and rectal microbiota differed between adult females and juvenile females. Social rank, however, was not a significant predictor of microbiota profiles. Additionally, the microbiota varied considerably among the six sampled body sites and exhibited strong specificity among individual hyenas. Thus, our findings suggest that site-specific niche selection is a primary driver of microbiota structure in mammals, but endogenous host factors may also be influential.

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Antiseptic Agents Elicit Short-Term, Personalized and Body Site-Specific Shifts in Resident Skin Bacterial Communities

10.1101/230193 ◽

2017 ◽

Author(s):

Adam J. SanMiguel ◽

Jacquelyn S. Meisel ◽

Joseph Horwinski ◽

Qi Zheng ◽

Charles W. Bradley ◽

...

Keyword(s):

Community Dynamics ◽

Population Level ◽

Community Diversity ◽

Skin Microbiome ◽

Body Site ◽

Short Term ◽

Site Specific ◽

Antiseptic Treatment ◽

Antimicrobial Interventions ◽

The Impact

ABSTRACTDespite critical functions in cutaneous health and disease, it is unclear how resident skin microbial communities are altered by topical antimicrobial interventions commonly used in personal and clinical settings. Here we show that acute exposure to antiseptic treatments elicits rapid but short-term depletion of microbial community diversity and membership. Thirteen subjects were enrolled in a longitudinal treatment study to analyze the effects of topical treatments (ethanol, povidone-iodine, chlorhexidine, water) on the skin microbiome at two skin sites of disparate microenvironment: forearm and back. Treatment effects were highly dependent on personalized and body site-specific colonization signatures, which concealed community dynamics at the population level when not accounted for in this analysis. The magnitude of disruption was influenced by the identity and abundance of particular bacterial inhabitants. Lowly abundant members of the skin microbiota were more likely to be displaced, and subsequently replaced by the most abundant taxa prior to treatment. Members of the skin commensal family Propionibactericeae were particularly resilient to treatment, suggesting a distinct competitive advantage in the face of disturbance. These results provide insight into the stability and resilience of the skin microbiome, while establishing the impact of topical antiseptic treatment on skin bacterial dynamics and community ecology.

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Hand bacterial communities vary across two different human populations

Microbiology ◽

10.1099/mic.0.075390-0 ◽

2014 ◽

Vol 160 (6) ◽

pp. 1144-1152 ◽

Cited By ~ 29

Author(s):

Denina Hospodsky ◽

Amy J. Pickering ◽

Timothy R. Julian ◽

Dana Miller ◽

Sisira Gorthala ◽

...

Keyword(s):

Microbial Communities ◽

Bacterial Communities ◽

Bacterial Population ◽

Human Microbiome ◽

Distinct Group ◽

Human Populations ◽

Skin Microbiome ◽

Associated Bacteria ◽

European Populations

This study utilized pyrosequencing-based phylogenetic library results to assess bacterial communities on the hands of women in Tanzania and compared these communities with bacteria assemblages on the hands of US women. Bacterial population profiles and phylogenetically based ordinate analysis demonstrated that the bacterial communities on hands were more similar for selected populations within a country than between the two countries considered. Organisms that have commonly been identified in prior human skin microbiome studies, including members of the Propionibacteriaceae, Staphylococcaceae and Streptococceacea families, were highly abundant on US hands and drove the clustering of US hand microbial communities into a distinct group. The most abundant bacterial taxa on Tanzanian hands were the soil-associated Rhodobacteraceae and Nocardioidaceae. These results help to expand human microbiome results beyond US and European populations, and the identification and abundance of soil-associated bacteria on Tanzanian hands demonstrated the important role of the environment in shaping the microbial communities on human hands.

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Human microbiome: an academic update on human body site specific surveillance and its possible role

Archives of Microbiology ◽

10.1007/s00203-020-01931-x ◽

2020 ◽

Vol 202 (8) ◽

pp. 2147-2167

Author(s):

Elakshi Dekaboruah ◽

Mangesh Vasant Suryavanshi ◽

Dixita Chettri ◽

Anil Kumar Verma

Keyword(s):

Human Body ◽

Human Microbiome ◽

Body Site ◽

Site Specific

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The Skin Microbiome of Cohabiting Couples

mSystems ◽

10.1128/msystems.00043-17 ◽

2017 ◽

Vol 2 (4) ◽

Cited By ~ 34

Author(s):

Ashley A. Ross ◽

Andrew C. Doxey ◽

Josh D. Neufeld

Keyword(s):

Machine Learning ◽

Microbial Communities ◽

The Body ◽

Rrna Genes ◽

Skin Microbiome ◽

Learning Approaches ◽

Body Site ◽

Cohabiting Couples ◽

Follow Up Studies

ABSTRACT Our work characterizes the influence of cohabitation as a factor influencing the composition of the skin microbiome. Although the body site and sampled individual were stronger influences than other factors collected as metadata in this study, we show that modeling of detected microbial taxa can help with correct identifications of cohabiting partners based on skin microbiome profiles using machine learning approaches. These results show that a cohabiting partner can significantly influence our microbiota. Follow-up studies will be important for investigating the implications of shared microbiome on dermatological health and the shared contributions of cohabiting parents to the microbiome profiles of their infants. Distinct microbial communities inhabit individuals as part of the human skin microbiome and are continually shed to the surrounding environment. Microbial communities from 17 skin sites of 10 sexually active cohabiting couples (20 individuals) were sampled to test whether cohabitation impacts an individual’s skin microbiome, leading to shared skin microbiota among partner pairs. Amplified 16S rRNA genes of bacteria and archaea from a total of 340 skin swabs were analyzed by high-throughput sequencing, and the results demonstrated that cohabitation was significantly associated with microbial community composition, although this association was greatly exceeded by characteristics of body location and individuality. Random forest modeling demonstrated that the partners could be predicted 86% of the time (P < 0.001) based on their skin microbiome profiles, which was always greater than combinations of incorrectly matched partners. Cohabiting couples had the most similar overall microbial skin communities on their feet, according to Bray-Curtis distances. In contrast, thigh microbial communities were strongly associated with biological sex rather than cohabiting partner. Additional factors that were associated with the skin microbiome of specific body locations included the use of skin care products, pet ownership, allergies, and alcohol consumption. These baseline data identified links between the skin microbiome and daily interactions among cohabiting individuals, adding to known factors that shape the human microbiome and, by extension, its relation to human health. IMPORTANCE Our work characterizes the influence of cohabitation as a factor influencing the composition of the skin microbiome. Although the body site and sampled individual were stronger influences than other factors collected as metadata in this study, we show that modeling of detected microbial taxa can help with correct identifications of cohabiting partners based on skin microbiome profiles using machine learning approaches. These results show that a cohabiting partner can significantly influence our microbiota. Follow-up studies will be important for investigating the implications of shared microbiota on dermatological health and the contributions of cohabiting parents to the microbiome profiles of their infants.

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Faculty Opinions recommendation of A site-specific, multiplexed kinase activity assay using stable-isotope dilution and high-resolution mass spectrometry.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1161908.623533 ◽

2009 ◽

Author(s):

Jonathan Chernoff

Keyword(s):

Mass Spectrometry ◽

High Resolution ◽

Kinase Activity ◽

High Resolution Mass Spectrometry ◽

Activity Assay ◽

Site Specific ◽

Stable Isotope Dilution ◽

A Site ◽

Kinase Activity Assay ◽

Resolution Mass

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High-Resolution Spatiotemporal Water Use Mapping of Surface and Direct-Root-Zone Drip-Irrigated Grapevines Using UAS-Based Thermal and Multispectral Remote Sensing

Remote Sensing ◽

10.3390/rs13050954 ◽

2021 ◽

Vol 13 (5) ◽

pp. 954

Author(s):

Abhilash K. Chandel ◽

Lav R. Khot ◽

Behnaz Molaei ◽

R. Troy Peters ◽

Claudio O. Stöckle ◽

...

Keyword(s):

High Resolution ◽

Water Use ◽

Root Zone ◽

Lateral Roots ◽

Irrigation Treatment ◽

Crop Coefficient ◽

Spatiotemporal Resolution ◽

Site Specific ◽

Canopy Transpiration ◽

Irrigation Treatments

Site-specific irrigation management for perennial crops such as grape requires water use assessments at high spatiotemporal resolution. In this study, small unmanned-aerial-system (UAS)-based imaging was used with a modified mapping evapotranspiration at high resolution with internalized calibration (METRIC) energy balance model to map water use (UASM-ET approach) of a commercial, surface, and direct-root-zone (DRZ) drip-irrigated vineyard. Four irrigation treatments, 100%, 80%, 60%, and 40%, of commercial rate (CR) were also applied, with the CR estimated using soil moisture data and a non-stressed average crop coefficient of 0.5. Fourteen campaigns were conducted in the 2018 and 2019 seasons to collect multispectral (ground sampling distance (GSD): 7 cm/pixel) and thermal imaging (GSD: 13 cm/pixel) data. Six of those campaigns were near Landsat 7/8 satellite overpass of the field site. Weather inputs were obtained from a nearby WSU-AgWeatherNet station (1 km). First, UASM-ET estimates were compared to those derived from soil water balance (SWB) and conventional Landsat-METRIC (LM) approaches. Overall, UASM-ET (2.70 ± 1.03 mm day−1 [mean ± std. dev.]) was higher than SWB-ET (1.80 ± 0.98 mm day−1). However, both estimates had a significant linear correlation (r = 0.64–0.81, p < 0.01). For the days of satellite overpass, UASM-ET was statistically similar to LM-ET, with mean absolute normalized ET departures (ETd,MAN) of 4.30% and a mean r of 0.83 (p < 0.01). The study also extracted spatial canopy transpiration (UASM-T) maps by segmenting the soil background from the UASM-ET, which had strong correlation with the estimates derived by the standard basal crop coefficient approach (Td,MAN = 14%, r = 0.95, p < 0.01). The UASM-T maps were then used to quantify water use differences in the DRZ-irrigated grapevines. Canopy transpiration (T) was statistically significant among the irrigation treatments and was highest for grapevines irrigated at 100% or 80% of the CR, followed by 60% and 40% of the CR (p < 0.01). Reference T fraction (TrF) curves established from the UASM-T maps showed a notable effect of irrigation treatment rates. The total water use of grapevines estimated using interpolated TrF curves was highest for treatments of 100% (425 and 320 mm for the 2018 and 2019 seasons, respectively), followed by 80% (420 and 317 mm), 60% (391 and 318 mm), and 40% (370 and 304 mm) of the CR. Such estimates were within 5% to 11% of the SWB-based water use calculations. The UASM-T-estimated water use was not the same as the actual amount of water applied in the two seasons, probably because DRZ-irrigated vines might have developed deeper or lateral roots to fulfill water requirements outside the irrigated soil volume. Overall, results highlight the usefulness of high-resolution imagery toward site-specific water use management of grapevines.

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