I recently bought these shoes online. I happily broke them in immediately upon receiving them, a bit hastily. If I had paid a little more attention to the various paper slips in the box, I would have noticed the excitedly-worded “ANTIMICROBIAL ODOR CONTROL” advertisement. Alas, I did not notice this. Nowhere on the site did it say anything about antimicrobials, and I had missed the tag amongst the billion tiny pieces of paper that came with the shoes (unnecessary paper use is a separate beef I have with this product though).
Why does every product seem to contain antimicrobials nowadays? I’ve come to take for granted the knowledge of antimicrobial resistance I have, but this company is either unaware of the issue or choosing to ignore it. Either way, I plan to write a letter to the appropriate representative (not that it’ll do much, in all likelihood, but you never know). Not only are antimicrobials prevalent in so many products we use, half the time the consumer doesn’t realize it. It’s not required by any law to advertise this. The only reason this shoe company did so is because they’re marketing it as a positive attribute of their product. Even if these shoes did successfully decrease foot/shoe odor, I personally wouldn’t have bought them. Not that there’s any (public) evidence indicating this antimicrobial will control my shoes’ odor…nor information about what antimicrobial was used at all.
It’s frustrating to see the gap between the information scientists and non-scientists have on topics like antimicrobial resistance. I may know how resistance affects humans and why it occurs and ways to prevent it, but many people I interact with on a daily basis are surprised when I happen to bring it up in conversation. There’s always been a lag in time between discovery of a topic and disseminating that knowledge. I don’t know the solution, and we are getting better at it with time, but it is frustrating for now nonetheless.
A short post, with only 2 papers. The first one is about microbes detected in the homes of a French cohort of children, and the second one looked at the bacteria growing on plastic garbage found on the bottom of the North Sea. Here is your song to go with it: Miranda Lambert – The House That Built Me.
Although exposure to indoor microorganisms in early life has already been associated with respiratory illness or allergy protection, only a few studies have performed standardized samplings and specific microbial analysis. Moreover, most do not target the different groups of microorganisms involved in respiratory diseases (fungi, bacteria, dust mites). In our study, ten specific qPCR targets (6 fungal species, 1 family and 2 genera of bacteria, 1 house dust mite) were used to analyze the microorganism composition of electrostatic dust fall collector (EDC) from 3193 dwellings of the Elfe French cohort study. Multivariate analyses allowed us to show that the microbial composition of dwellings, assessed with simultaneous analysis of 10 microorganisms, can be characterized by four entities: three bacteria, house dust mite Dermatophagoïdes pteronyssinus, fungi Alternaria alternata, and five other molds. Some dwellings’ intrinsic characteristics (occupational ratio, type of dwelling and presence of pets) clearly influence microorganism distribution, and six different profiles of dwellings, characterized by their composition in microorganisms, have been described across France. The use of these clusters seems promising in the evaluation of allergic risk. Allergic respiratory diseases will develop in the near future in some children of the Elfe cohort and will indicate to what extent our approach can be predictive of respiratory disease.
Bacterial colonization of marine plastic litter (MPL) is known for over four decades. Still, only a few studies on the plastic colonization process and its influencing factors are reported. In this study, seafloor MPL was sampled at different locations across the Belgian part of the North Sea to study bacterial community structure using 16S metabarcoding (note EB: I don’t like this term! And “16S”. Ugh). These marine plastic bacterial communities were compared with those of sediment and seawater, and resin pellets sampled on the beach, to investigate the origin and uniqueness of plastic bacterial communities. Plastics display great variation of bacterial community composition, while each showed significant differences from those of sediment and seawater, indicating that plastics represent a distinct environmental niche. Various environmental factors correlate with the diversity of MPL bacterial composition across plastics. In addition, intrinsic plastic-related factors such as pigment content may contribute to the differences in bacterial colonization. Furthermore, the differential abundance of known primary and secondary colonizers across the various plastics may indicate different stages of bacterial colonization, and may confound comparisons of free-floating plastics. Our studies provide insights in the factors that shape plastic bacterial colonization and shed light on the possible role of plastic as transport vehicle for bacteria through the aquatic environment.
Microbiology of the Built Environment research these recent years have explored how humans are a source of microbes and microbial products indoors. To further study the effect of human occupancy on the biological aerosols of indoor space, our research group at Berkeley decided to move from observation studies to controlled experiments to isolate — and quantify — this human input. So, we utilized the Controlled Environmental Chamber (a conference-room like environment; see picture) within the Center For the Built Environment to do a particle- and biological-based assessment of the effect of occupancy on bioaerosols.
For our experiment, we varied the number and activity level of occupants in the chamber. We collected particles for genetic analysis, and we also monitored total and fluorescent biological aerosol particles, which are particles determined to be biological in original based on their intrinsic fluorescent properties. The particle and microbial papers are recently published (and open access).
As a short summary of our findings, the particle-based study showed a clear effect of occupancy level and activity on particle concentrations, and it was estimated that a person emits about 1 million fluorescent particles per hour. On the other hand, microbial composition indoors showed high affinity with a corresponding outdoor sample, and the effect of occupancy on these short 2-hour sampling periods was quite subtle. These paired results taken together are kind of puzzling – how can a person sitting at a desk be emitting about a million fluorescent biological particles per hour and yet that be practically unidentifiable in the airborne microbial composition?
In thinking about what factors influence the indoor airborne microbial composition, we came up with a schematic that breaks occupant emissions into three parts: direct shedding, transport vector, and resuspension of reservoir microbes. Direct shedding comes from shedding skin and spitting, for example. A peculiar pattern involving a puffball showed the potential for humans to act as transport vectors for particles we’ve picked up in the environment (details in the paper). As for the resuspension of reservoir microbes, the study chamber we used undergoes long periods of low occupancy, and it could be that an environmental, rather than human, signature has built up in the room. Perhaps it was this environmental reservoir that got resuspended when people occupied that indoor space during our experiment, leading to a large generation of biological particles but a microbial signature that compositionally resembled outdoor air. As I said, it’s our working hypothesis, and we are pursuing projects to explore further. Maybe Charles Schulz’s Pigpen – a sort of particle-laden wildebeest never quite getting free of a debris cloud – is a good model for how humans influence the indoor air environment.
I did not find a lot of recent papers on indoor microbiology, but quite a couple on the microbiology of drinking and wastewater, and some on ballast, pharmacy, and oil-platform water. Since this blog is all about water, I am playing The Waterboys – The Whole Of The Moon in the background.
The magnitude and spatial variability of acute gastrointestinal illness (AGI) cases attributable to microbial contamination of US community drinking water systems are not well characterized. We compared three approaches (drinking water attributable risk, quantitative microbial risk assessment, and population intervention model) to estimate the annual number of emergency department visits for AGI attributable to microorganisms in North Carolina (NC) community water systems. … The differences in results between the drinking water attributable risk method, which has been the main basis for previous national risk estimates, and the other two approaches highlights the need to improve methods for estimating endemic waterborne disease risks, in order to prioritize investments to improve community drinking water systems.
With wastewater treatment systems being increasingly recognized as resource (energy, nutrients and water) recovery facilities, the role of microbiome and resource management is crucial for sustainable process development. … This mini-review focuses on the use of meta-omic tools to understand wastewater microbiology and potential integrated approaches for simultaneous and simple yet reliable analysis of the microbial systems in anaerobic digestion and microbial fuel cell systems which share several common features including the ability to produce energy and other valuable chemical and energy products under anaerobic conditions with complex microbial ecology.
Detecting the presence of potential invasive species in ballast water is a priority for preventing their spread into new environments. … Here we apply high throughput sequencing from DNA extracted from ballast water (BW) samples employing two different platforms, Ion Torrent and 454, and compare the putative species catalogues from the resulting Operational Taxonomic Units (OTU). … Some putative species detected from the two platforms increased in frequency during the Polarstern travel, which suggests they were alive and therefore tolerant to adverse conditions. OTU assigned to the highly invasive red alga Polysiphoniahave been detected at low but increasing frequency from the two platforms. Although in this moment NGST could not replace current methods of sampling, sorting and individual taxonomic identification of BW biota, it has potential as an exploratory methodology especially for detecting scarce species.
In the present work, a microbiological and genetic analysis was performed for the biological pool of an industrial wastewater treatment plant located in Civita Castellana (Viterbo, Italy). … For this study, Biolog community level physiological profiling (CLPP) on EcoPlates and PCR-amplified 16S rRNA denaturing gradient gel electrophoresis (DGGE) were used in comparison and combined as ecological techniques to characterize an anthropic closed ecosystem. Biolog CLPP provides the potential metabolic pattern and DGGE analyses helps to explain the structure and complexity of the microbial community. The results suggest that these techniques could be predictive and more useful when used together than alone.
Here, amplicon sequencing of the 16S rRNA gene region was performed alongside traditional water quality measures to assess the health, quality, and efficiency of two distinct, full-scale DWDSs. …. In both DWDSs bacterial communities differed significantly after disinfection, demonstrating the effectiveness of both treatment regimes. However, bacterial repopulation occurred further along the DWDSs, and some end-user samples were more similar to the source water than the post-disinfection water. … From this study, we conclude that metagenomic amplicon sequencing is an informative method to support current compliance-based methods, and can be used to reveal bacterial community interactions with the chemical and physical properties of DWDSs.
Hibernia is Canada’s largest offshore oil platform. Produced water is the major waste byproduct discharged into the ocean. … The objectives were to characterize the microbial communities and the chemical composition in the produced water and to characterize changes in the seawater bacterial community around the platform. The results from chemical, physicochemical, and microbial analyses revealed that the discharge did not have a detectable effect on the surrounding seawater. … Unique microorganisms like Thermoanaerobacter were found in the produced water. Thermoanaerobacter-specific q-PCR and nested-PCR primers were designed, and both methods demonstrated that Thermoanaerobacter was present in seawater up to 1000 m from the platform. These methods could be used to track the dispersion of produced water into the surrounding ocean.
Biological treatment processes offer the ideal conditions in which a high diversity of microorganisms can grow and develop. The wastewater produced during these processes is contaminated with antibiotics and, as such, they provide the ideal setting for the acquisition and proliferation of antibiotic resistance genes (ARGs). This research investigated the occurrence and variation in the ARGs found during the one-year operation of the anaerobic sequencing batch reactors (SBRs) used to treat pharmaceutical wastewater that contained combinations of sulfamethoxazole-tetracycline-erythromycin (STE) and sulfamethoxazole-tetracycline (ST). … Due to the limited availability of primers to detect ARGs, Illumina sequencing was also performed on the sludge and effluent of the STE and ST reactors. … According to the expression of genes results, microorganisms achieve tetracycline and erythromycin resistance through a combination of three mechanisms: efflux pumping protein, modification of the antibiotic target and modifying enzymes.
Sadly I was unable to make the MoBE 2015 meeting… it’s the first one I’ve missed since they started in 2012. From following the tweets, it sounded like a great and productive meeting as usual! Here’s the Storify for anyone else who wants to see what happened… hopefully we’ll get out some blog posts from participants as well.
You can clearly see a steady rise of CO2 concentrations in the room once we all gathered for the 8:50 am start. For the duration of the morning, CO2 concentrations were pretty consistently hovering around 1200-1300 ppm. That’s not a terribly high level, but it is about 800-900 ppm above background (for some context on this value, you might be interested in reading this recent study on CO2 and decision making). You can also clearly see when we all left for lunch around 12:15 pm — CO2 concentrations decayed essentially down to the same levels as outdoor air, suggesting that there room was indeed left empty (or mostly empty). Then you again see a similar steady rise when we all return for the 2 pm session, followed by another break around 4 pm (notice how rapid the decay was during this period — remember when the hotel staff opened all of the exterior doors to help cool the space?). Finally, you see one last steady rise during the final session. These are pretty clear patterns.
We can also use these data to answer a question that I heard several people asking yesterday: when the AC failed and temperatures noticeably rose to some pretty uncomfortable levels, did the ventilation system also fail or did it keep operating?
I personally heard some fan noise continuing even during the AC failure, so I figured that the ventilation system was continuing to operate. Atila Novoselac figured the same in his presentation. And if you look at the afternoon data, CO2 concentrations largely stabilized around 1300 to 1400 ppm, which wasn’t much different from earlier in the morning. The ventilation system was most certainly still operating at approximately its same rate as in the morning even during the AC failure. That’s good to know.
We can also use these data to answer a couple more questions.
First, we can use data from the decay period during lunch when we all vacated the space and if we assume there were no significant sources of CO2 during that period (it doesn’t look like there were), we can calculate the ventilation rate during that period (and we can probably assume that the rate was constant throughout the day, although we can’t really confirm that as I’ll discuss more below). Below you’ll see a plot of the lunchtime decay period data, log-transformed to calculate a first-order exponential decay rate (this is a standard way to estimate ventilation rates). We get a pretty clean fit and an estimated air exchange of about 0.041 per minute or about 2.5 air changes per hour (2.5 ACH). That’s reasonably well ventilated (better than the portable classrooms we heard about yesterday), but lower than we’ve measured in other environments (such as in the Hospital Microbiome Project).
Finally, we can also attempt make a rough approximation of occupancy using the data we have at this point. We recently published a paper with Jeff Siegel at the University of Toronto detailing some ways to estimate occupancy, including using CO2 concentrations and knowledge of ventilation rates to back calculate the number of people in a room. It requires us to make some assumptions for per-person CO2 emission rates and to estimate the volume of the room. Estimates for CO2 emission rates vary depending on a number of factors, but a typical assumption is about 0.27 L/min. If we use this assumption, and if we estimate the volume of the room to be about 440 cubic meters (about 40 feet x 40 feet x 10 foot ceilings), and if we take 1300 ppm as the approximate steady state room CO2 concentration, and if we take 420 ppm as the approximate outdoor CO2 concentration (the minimum measured during the unoccupied lunchtime period), and finally, if we assume that the same ~2.5 ACH ventilation rate estimated during unoccupied periods applies for the occupied periods as well (a somewhat tenuous assumption), I estimate that there should have been about 60 people in the room throughout the morning sessions using these data. Unfortunately, that’s a pretty poor estimate. With a quick visual count today I estimate probably about 110 people are actually in the room (which is probably about the same as yesterday, give or take 10 people or so), so my estimate using CO2 concentrations alone is WAY off. My guess is that the ventilation rate may be controlled by an automation system based on occupancy rather than being constant throughout the day, but I’m really not sure at this point.
Regardless, hopefully these data help understanding a bit more about what’s going on in this very building!
UPDATE Jul 17, 3:45 pm
Jeff, Hal, and I just recalculated occupancy based on a different assumption for emission rates. If you use 21 g/hr per person (or ~10 L/hour or ~0.18 L/min) presented earlier by Allen Goldstein (and mentioned in the comment by Bill Nazaroff below) using recent measurements in a classroom (an environment probably quite similar to this conference room) instead of 0.27 L/min used previously, and you also keep all the other assumptions constant, you get an estimated occupancy of about 91 people. That’s a whole lot closer to the observational count from today. As Bill Bahnfleth mentioned below as well, other differences might be explained by non-uniform mixing issues among other things.
Greetings microBEnet readers! I’m a new member of microBEnet and also an Assistant Professor at Duke. I’d like to share a job opening in my lab as my inaugural post. I’d be grateful if you could share with colleagues who you think could be interested.
A post-doctoral position is available in the laboratory of Lawrence David at Duke University (www.ladlab.org).
About the lab: Our lab is interested in devising tools and techniques for controlling human-associated bacterial communities. We take an interdisciplinary approach towards this goal, developing both experimental systems and computational models for manipulating human microbiota. Lab members hail from a range of disciplines, including bioinformatics, genetics, ecology, engineering, medicine, and microbiology. Our lab is centrally located in Duke’s Center for Interdisciplinary Engineering, Medicine and Applied Sciences, a new building nearby to Duke’s Schools of Engineering, Medicine, and Arts & Science.
About the position: We are looking for a postdoctoral associate to help develop high-throughput microfluidic techniques for investigating bacterial interactions and ecology. The associate will use findings from these tools to design strategies for engineering bacterial communities within hosts. We encourage applications from candidates with enthusiasm and skill in any of the fields listed below: computer science/computational biology, ecology, engineering, math/physics, or micro/molecular/synthetic biology. Expertise in flow cytometry, microfluidics and/or culture of bacterial communities is particularly valued.
Timing: The start date is flexible, but we would like to fill the position as soon as possible. The position is expected to continue for multiple years contingent on satisfactory performance.
Applying: To apply, please send a brief letter of research interests, CV, contact information for three references, and a publication representative of your work to: email@example.com. Applications will be read until the position is filled. Informal inquiries are welcome.
* LA David, et al. Diet rapidly and reproducibly alters the gut microbiome. Nature, 2014.
* LA David, et al. Host lifestyle affects human microbiota on daily timescales. Genome Biology, 2014.
* LA David, et al. Gut microbial succession follows acute secretory diarrhea in humans. mBio, 2015.
Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual’s race, color, religion, age, gender, sexual orientation, national origin, genetic information
I just saw this paper, published a couple of days ago in Nature’s Scientific Reports. And yeah, it’s open access! While reading this post, I would suggest playing Dalai Lama by Rammstein, the in-flight version of Der Erlkönig.
Human populations worldwide are increasingly confronted with infectious diseases and antimicrobial resistance spreading faster and appearing more frequently. Knowledge regarding their occurrence and worldwide transmission is important to control outbreaks and prevent epidemics. Here, we performed shotgun sequencing of toilet waste from 18 international airplanes arriving in Copenhagen, Denmark, from nine cities in three world regions. An average of 18.6 Gb (14.8 to 25.7 Gb) of raw Illumina paired end sequence data was generated, cleaned, trimmed and mapped against reference sequence databases for bacteria and antimicrobial resistance genes. An average of 106,839 (0.06%) reads were assigned to resistance genes with genes encoding resistance to tetracycline, macrolide and beta-lactam resistance genes as the most abundant in all samples. We found significantly higher abundance and diversity of genes encoding antimicrobial resistance, including critical important resistance (e.g. blaCTX-M) carried on airplanes from South Asia compared to North America. Presence of Salmonella enterica and norovirus were also detected in higher amounts from South Asia, whereas Clostridium difficile was most abundant in samples from North America. Our study provides a first step towards a potential novel strategy for global surveillance enabling simultaneous detection of multiple human health threatening genetic elements, infectious agents and resistance genes.
Mmm, it sounds a bit like “Big Brother is watching you” to me. But the science is cool.
The articles detail some new information on the history of the US Military conducting large scale city wide experiments on people, without persmission, involving spraying “fogs” of bacteria into urban environments.
From Kreston’s article
This would not be the last time that such “simulation” experiments would be carried out on American citizens. From 1950 to 1966, the military performed open-air testing of potential terrorist weapons at least 239 times in at least eight American cities, including New York City, Key West, and Panama City, FL, exposing still unknown numbers of Americans to Serratia and other microbial organisms (4). In the majority of those cases, exposure to the microbe was nothing more catastrophic than exposure to other microbes in a dust cloud. For a minority, including the elderly, young children, and immunocompromised, such exposure posed serious health risks.
Pretty scary actually. Given the terrible track record of US Labs in keeping pathogenic microbes under wraps, I think I am just not going to trust people proposing large scale experiments with supposedly harmless microbes.
I’m really excited to have been recently awarded an Alfred P. Sloan Foundation Microbiology of the Built Environment postdoctoral fellowship. I was asked to explain a little about my plans for the project I’ll be working on for the next two years now that I officially have my PhD.
As a graduate student I investigated the factors that affect the microbial communities of breast-fed infants. Babies go from being near-sterile in the womb to all of a sudden encountering the full microbial diversity of their new ex-utero environment, yet retain a gut microbiota distinct from that of adults. Our microbiota likely coevolved with us, and influences our own physiology in a number of ways1. As a PhD student in the lab of David Mills at UC Davis, I studied the microbiota of several infant cohorts from different areas of the world. Out of curiosity, I compared the data I worked on (from infants in Bangladesh2, the USA3, and a few as-yet unpublished datasets) with several other published datasets. I noticed a trend showing differences between the gut microbiomes of infants in Western, Educated, Industrialized, Rich, and Democratic (“WEIRD”) nations and nations in the Global South4. Most notably, healthy breast-fed infants in WEIRD populations had higher amounts of Bifidobacterium than infants in the Global South – a phenomenon that had been noted before5.
Bifidobacteria are gram-positive anaerophilic bacteria, and are interesting for a number of reasons. First off, they are very common in infants, much more so than in adults. Studies using marker gene sequencing techniques show that the gut of a healthy breast-fed infant is often dominated by bifidobacteria 6–9. This is likely because bifidobacteria are one of the few types of bacteria that can fully consume complex human milk glycans (HMGs) found in breast milk which are indigestible to the infant10–15. The structural complexity of HMGs serves as a barrier for other microbes to compete with bifidobacteria for these sugars in the infant gut. Bifidobacteria benefit from colonizing infants by getting access to these sugars – their “favorite food.”
But what is in it for the infants and mothers? Why bother to provide these sugars to the bacteria? There are some ideas as to why. Infants with bifidobacteria-dominated gastrointestinal tracts have a higher resistance to colonization by pathogens, improved responses to some vaccines, and better gut barrier function 2,15–17. Bifidobacteria aid the appropriate development of the infant’s innate and acquired immune systems, simultaneously enhancing surveillance yet reducing inflammation 17–20. Infant-type bifidobacteria present during weaning may guide the immune system towards tolerance during the introduction of new foods and their associated antigens 21–24. I think levels of bifidobacteria might be suitable as a biomarker for a desirable infant gut microbiome, even though the ecological dynamics at play within the infant microbiota and their relationship to health outcomes are complex and not fully understood. For that reason, the observed differences in bifidobacterial levels across the globe might have some important public health implications.
Additional studies are needed to confirm this trend of lower amounts of bifidobacteria in infants in the WEIRD world, but if it holds true, identifying the cause(s) will be important for understanding this phenomenon. I see two broad possibilities for what the cause(s) might be: either the gut environments of infants in the WEIRD nations are differentially selective (against bifidobacteria), or there are higher barriers to bifidobacteria getting into infants in the WEIRD world (bifidobacteria are in fact, not “everywhere25”). My project focuses on the second possibility. The initial source of microbes in infants is often thought to be a combination of the maternal vaginal microbiota 26,27, the mother’s intestinal microbiota 28, and other environmental factors including caretaker skin 29. Breast milk also contains microbes, but their origin and potential impact on colonization is unclear 30–32. However, I’d like to test an alternative hypothesis – that the most likely place from which an infant might acquire infant-adapted bifidobacteria is… another infant. Infants in WEIRD nations might have lower propinquity to other infants than babies in the Global South, and thus have challenges in acquiring bifidobacteria from them. This low infant/infant overlap lifestyle may differ from the conditions experienced over the course of evolutionary history, and it may be (in part) driving the lower levels of bifidobacterial colonization I’ve observed in WEIRD places.
But how can this hypothesis be tested? The potential of the built environment as venue for cross-inoculation between infants has not been studied, despite hints of shared microbes in the built environment and infant gut ecosystems33. Could infants be leaving a microbial trace of their presence on the environmental features with which they interact? Barring outside intervention, infants are indiscriminate in their spread of fecal microbes to individuals and objects with which they come into contact (as any parent that has experienced a major diaper blow-out can testify). My plan is to examine specific built environments to investigate potential microbial signatures left by infants. I will also test the microbiomes of infants in the U.S.A. and compare them to those of the Himba, a population of traditionally-living pastoralists. There are two main questions I am asking in this study:
Question 1: Do breast-fed infants leave viable bifidobacteria in their surrounding built environment which are not found in non-infant-associated built environments?
To investigate the nature of the infant-associated built environment microbiome, I will study the microbiota of daycare centers. I will swab select built environment features (play tables, toys, floors, etc.) and analyze the microbes captured through sequencing and culture-based methods (to test viability). I will collect metadata about potential microbiota-influencing building conditions at these locations (e.g. usage, cleaning procedures, relative humidity, and temperature) using building sensors developed at UC Davis (thanks to Nic Madrid and Prof. Andre Knoesen). As a positive control, I will also study diaper-changing tables (somewhere where the presence of infant fecal microbes might be expected) whose usage will also be monitored with sensors. As a negative control, I will also be studying a series of 40 dedicated lactation sites on UC Davis campus which are used by breastfeeding mothers to express breast milk. A special thanks to the UC Davis breastfeeding support program for giving me and my team of undergraduates permission to swab the rooms. As infants are not typically present in these rooms, these spaces serve as a negative control where direct deposition of microbes by infants is not a factor. However, as the rooms are used principally by mothers who come into frequent contact with their own breast-fed infants, studying the lactation sites would allow for detection of potential indirect transfer of microbes between infants via the mothers.
Question 2: Are levels of bifidobacteria in the infant gut be positively associated with exposure to multi-infant built environments?
I plan to address this question in two ways. First, by comparing infants with different exposures within the USA. Approximately 80 infants are currently enrolled in the UC Davis Lactation Study. Fecal samples from the infants were collected over the first year of life, and intensive metadata was collected about breastfeeding, C-section births, antibiotic supplementation by the mother and infant, maternal use of personal products containing antimicrobial agents, maternal demographics, and numerous other factors. However, information about daycare enrollment, social interactions (e.g. “mommy-and-me” groups), shared nannies, and other social factors was not collected. Together with the leaders of the lactation study, I have sent out a survey to the mothers asking for this additional information so that I can compare it to data on the infants’ microbiomes.
The second way I want to ask this question is by comparing the US infants as a whole to infants in a very different setting, the Himba of Namibia. The Himba are traditionally-living pastoralists that live a very different lifestyle from people in WEIRD countries. I will explore the impact of various social factors on the infant microbiome through the sampling of infant feces and swabbing of built environment features among the Himba. Prof. Brooke Scelza (Anthropology, UCLA) has helmed a long-term demography and behavioral ecology research program among the community and recently launched a collaboration on breastmilk and breastfeeding among the Himba with Prof. Katie Hinde (Center for Evolution and Medicine, Arizona State University; Human Evolutionary Biology, Harvard), an anthropologist and co-advisor on my project. Thanks to these collaborators, I will be able to explore the importance of various environmental and cultural factors to rates of colonization by bifidobacteria
The past century has yielded unprecedented changes in both environmental and cultural factors that impact the human microbiota. It has become increasingly clear that these changes are often not without undesirable side effects. Lack of exposure to an inoculum of bifidobacteria suitable for the breast-fed infant gut was likely not an issue often faced by our ancestors. Our physiology, shaped by natural selection, may be adapted to “expect” exposure to bifidobacteria, whose presence provides crucial developmental cues and protections. The absence of these exposures is therefore of public health importance. Using populations in the Global South as a “more adaptive” point of reference, the available data suggest that the United States and other WEIRD populations may be facing widespread under-colonization by bifidobacteria. This project investigates the microbiology of the baby-associated built environment as a way to provide guidance on a potential mechanism that might be driving this phenomenon.
Hinde, K. & Lewis, Z. T. Mother’s littlest helpers. Science (80-. ).348, 1427–1428 (2015).
Huda, M. N. et al. Stool Microbiota and Vaccine Responses of Infants. Pediatrics134, e362–72 (2014).
Lewis, Z. T. et al. Maternal Fucosyltransferase 2 Status Affects the Gut Bifidobacterial Communities of Breastfed Infants. Microbiome3, 1–21 (2015).
Henrich, J., Heine, S. J. & Norenzayan, A. The weirdest people in the world? Behav. Brain Sci.33, 61–83; discussion 83–135 (2010).
Grześkowiak, Ł. et al. Distinct gut microbiota in southeastern African and northern European infants. J. Pediatr. Gastroenterol. Nutr.54, 812–6 (2012).
Abrahamsson, T. R. et al. Low diversity of the gut microbiota in infants with atopic eczema. J. Allergy Clin. Immunol.129, 434–40, 440.e1–2 (2012).
Roos, S. et al. 454 pyrosequencing analysis on faecal samples from a randomized DBPC trial of colicky infants treated with Lactobacillus reuteri DSM 17938. PLoS One8, e56710 (2013).
Fouhy, F. et al. High-Throughput Sequencing Reveals the Incomplete, Short-Term Recovery of Infant Gut Microbiota following Parenteral Antibiotic Treatment with Ampicillin and Gentamicin. Antimicrob. Agents Chemother.56, 5811–20 (2012).
Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature486, 222–227 (2012).
Marcobal, A. et al. Consumption of human milk oligosaccharides by gut-related microbes. J. Agric. Food Chem.58, 5334–40 (2010).
Yu, Z.-T., Chen, C. & Newburg, D. S. Utilization of major fucosylated and sialylated human milk oligosaccharides by isolated human gut microbes. Glycobiology0, 1–12 (2013).
Sela, D. A. et al. The genome sequence of Bifidobacterium longum subsp. infantis reveals adaptations for milk utilization within the infant microbiome. Proc. Natl. Acad. Sci. U. S. A.105, 18964–9 (2008).
Garrido, D., Kim, J. H., German, J. B., Raybould, H. E. & Mills, D. a. Oligosaccharide binding proteins from Bifidobacterium longum subsp. infantis reveal a preference for host glycans. PLoS One6, e17315 (2011).
Garrido, D., Dallas, D. C. & Mills, D. a. Consumption of human milk glycoconjugates by infant-associated bifidobacteria: mechanisms and implications. Microbiology159, 649–64 (2013).
Fukuda, S. et al. Bifidobacteria can protect from enteropathogenic infection through production of acetate. Nature469, 543–7 (2011).
Romond, M.-B. et al. Does the intestinal bifidobacterial colonisation affect bacterial translocation? Anaerobe14, 43–8 (2008).
Chichlowski, M., De Lartigue, G., German, J. B., Raybould, H. E. & Mills, D. a. Bifidobacteria isolated from infants and cultured on human milk oligosaccharides affect intestinal epithelial function. J. Pediatr. Gastroenterol. Nutr.55, 321–7 (2012).
Sheil, B. et al. Role of interleukin (IL-10) in probiotic-mediated immune modulation: an assessment in wild-type and IL-10 knock-out mice. Clin. Exp. Immunol.144, 273–80 (2006).
Tanabe, S., Kinuta, Y. & Saito, Y. Bifidobacterium infantis suppresses proinflammatory interleukin-17 production in murine splenocytes and dextran sodium sulfate-induced intestinal inflammation. Int. J. Mol. Med.22, 181–185 (2008).
Preising, J. et al. Selection of bifidobacteria based on adhesion and anti-inflammatory capacity in vitro for amelioration of murine colitis. Appl. Environ. Microbiol.76, 3048–51 (2010).
Roger, L. C., Costabile, A., Holland, D. T., Hoyles, L. & McCartney, A. L. Examination of faecal Bifidobacterium populations in breast- and formula-fed infants during the first 18 months of life. Microbiology156, 3329–41 (2010).
Roger, L. C. & McCartney, A. L. Longitudinal investigation of the faecal microbiota of healthy full-term infants using fluorescence in situ hybridization and denaturing gradient gel electrophoresis. Microbiology156, 3317–28 (2010).
Martin, M. A. & Sela, D. A. in Building Babies: Primate Development in in Proximate and Ultimate Perspective, Developments in Primatology: Progress and Prospects 37 (eds. Clancy, K. B. H., Hinde, K. & Rutherford, J. N.) 233–256 (Springer New York, 2013). doi:10.1007/978-1-4614-4060-4
Young, S. L. et al. Bifidobacterial Species Differentially Affect Expression of Cell Surface Markers and Cytokines of Dendritic Cells Harvested from Cord Blood. Clin. Diagn. Lab. Immunol.11, 686–690 (2004).
De Wit, R. & Bouvier, T. ‘Everything is everywhere, but, the environment selects’; what did Baas Becking and Beijerinck really say? Environ. Microbiol.8, 755–8 (2006).
Dominguez-Bello, M. G. et al. Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns. Proc. Natl. Acad. Sci. U. S. A.107, 11971–5 (2010).
Chaban, B. & Seanhemmingsennrc-cnrcgcca, E. Characterization of the vaginal microbiota of healthy Canadian women through the menstrual cycle.
Fanaro, S., Chierici, R., Guerrini, P. & Vigi, V. Intestinal microflora in early infancy: composition and development. Acta Paediatr. Suppl.91, 48–55 (2003).
Adlerberth, I. & Wold, a E. Establishment of the gut microbiota in Western infants. Acta Paediatr.98, 229–38 (2009).
Perez, P. F. et al. Bacterial imprinting of the neonatal immune system: lessons from maternal cells? Pediatrics119, e724–32 (2007).
Fernández, L. et al. The human milk microbiota: Origin and potential roles in health and disease. Pharmacol. Res.69, 1–10 (2013).
Urbaniak, C., Burton, J. P. & Reid, G. Breast, milk and microbes: a complex relationship that does not end with lactation. Womens. Health (Lond. Engl).8, 385–98 (2012).
Konya, T. et al. Associations between bacterial communities of house dust and infant gut. Environ. Res.131, 25–30 (2014).