Hampton-Marcell Jarrad T.

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Hampton-Marcell
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Jarrad T.
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  • Article
    A simple novel device for air sampling by electrokinetic capture
    (BioMed Central, 2015-12-27) Gordon, Julian ; Gandhi, Prasanthi ; Shekhawat, Gajendra ; Frazier, Angel ; Hampton-Marcell, Jarrad T. ; Gilbert, Jack A.
    A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrode assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87 %, with the reference filter taken as “gold standard.” Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. The performance of the device is substantially equivalent to capture by pumping through a filter for microbiome analysis by quantitative PCR and amplicon sequencing.
  • Article
    Athletic equipment microbiota are shaped by interactions with human skin
    (BioMed Central, 2015-06-19) Wood, Mariah ; Gibbons, Sean M. ; Lax, Simon ; Eshoo-Anton, Tifani W. ; Owens, Sarah M. ; Kennedy, Suzanne ; Gilbert, Jack A. ; Hampton-Marcell, Jarrad T.
    Americans spend the vast majority of their lives in built environments. Even traditionally outdoor pursuits, such as exercising, are often now performed indoors. Bacteria that colonize these indoor ecosystems are primarily derived from the human microbiome. The modes of human interaction with indoor surfaces and the physical conditions associated with each surface type determine the steady-state ecology of the microbial community. Bacterial assemblages associated with different surfaces in three athletic facilities, including floors, mats, benches, free weights, and elliptical handles, were sampled every other hour (8 am to 6 pm) for 2 days. Surface and equipment type had a stronger influence on bacterial community composition than the facility in which they were housed. Surfaces that were primarily in contact with human skin exhibited highly dynamic bacterial community composition and non-random co-occurrence patterns, suggesting that different host microbiomes—shaped by selective forces—were being deposited on these surfaces through time. However, bacterial assemblages found on the floors and mats changed less over time, and species co-occurrence patterns appeared random, suggesting more neutral community assembly. These longitudinal patterns highlight the dramatic turnover of microbial communities on surfaces in regular contact with human skin. By uncovering these longitudinal patterns, this study promotes a better understanding of microbe-human interactions within the built environment.
  • Preprint
    Aquarium microbiome response to ninety-percent system water change : clues to microbiome management
    ( 2015-04) Van Bonn, William ; LaPointe, Allen ; Gibbons, Sean M. ; Frazier, Angel ; Hampton-Marcell, Jarrad T. ; Gilbert, Jack A.
    The bacterial community composition and structure of water from an established teleost fish system was examined before, during and after a major water change to explore the impact of such a water-change disturbance on the stability of the aquarium water microbiome. The diversity and evenness of the bacterial community significantly increased following the 90% water replacement. While the change in bacterial community structure was significant, it was slight, and was also weakly correlated with changes in physicochemical parameters. Interestingly there was a significant shift in the correlative network relationships between operational taxonomic units from before to after the water replacement. We suggest this shift in network structure is due to the turnover of many taxa during the course of water replacement. These observations will inform future studies into manipulation of the microbiome by changing system environmental parameter values to optimize resident animal health.
  • Article
    Forensic analysis of the microbiome of phones and shoes
    (BioMed Central, 2015-05-12) Lax, Simon ; Hampton-Marcell, Jarrad T. ; Gibbons, Sean M. ; Colares, Georgia Barguil ; Smith, Daniel ; Eisen, Jonathan A. ; Gilbert, Jack A.
    Microbial interaction between human-associated objects and the environments we inhabit may have forensic implications, and the extent to which microbes are shared between individuals inhabiting the same space may be relevant to human health and disease transmission. In this study, two participants sampled the front and back of their cell phones, four different locations on the soles of their shoes, and the floor beneath them every waking hour over a 2-day period. A further 89 participants took individual samples of their shoes and phones at three different scientific conferences. Samples taken from different surface types maintained significantly different microbial community structures. The impact of the floor microbial community on that of the shoe environments was strong and immediate, as evidenced by Procrustes analysis of shoe replicates and significant correlation between shoe and floor samples taken at the same time point. Supervised learning was highly effective at determining which participant had taken a given shoe or phone sample, and a Bayesian method was able to determine which participant had taken each shoe sample based entirely on its similarity to the floor samples. Both shoe and phone samples taken by conference participants clustered into distinct groups based on location, though much more so when an unweighted distance metric was used, suggesting sharing of low-abundance microbial taxa between individuals inhabiting the same space. Correlations between microbial community sources and sinks allow for inference of the interactions between humans and their environment.