Diversity, distribution and sources of bacteria in residential kitchens

Composition, Diversity and Abundance of Gut Microbiome in Prediabetes and Type 2 Diabetes

Association between type 2 diabetes (T2DM) and compositional changes in the gut micro biota is established, however little is known about the dysbiosis in early stages of Prediabetes (preDM). The purpose of this investigation is to elucidate the characteristics of the gut micro biome in preDM and T2DM, compared to Non-Diabetic (nonDM) subjects. Forty nine subjects were recruited for this study, 15 nonDM, 20 preDM and 14 T2DM. Bacterial community composition and diversity were investigated in fecal DNA samples using Illumina sequencing of the V4 region within the 16S rRNA gene. The five most abundant phyla identified were: Bacteroidetes, Firmicutes, Proteobacteria, Verrucomicrobia, and Actinobacteria. Class Chloracido bacteria was increased in preDM compared to T2DM (p = 0.04). An unknown genus from family Pseudonocardiaceae was significantly present in preDM group compared to the others (p = 0.04). Genus Collinsella, and an unknown genus belonging to family Enterobacteriaceae were both found to be significantly increased in T2DM compared to the other groups (Collinsella, and p = 0.03, Enterobacteriaceae genus p = 0.02). PERMANOVA and Mantel tests performed did not reveal a relationship between overall composition and diagnosis group or HbA1C level. This study identified dysbiosis associated with both preDM and T2DM, specifically at the class and genus levels suggesting that earlier treatment in preDM could possibly have an impact on the intestinal micro flora transitioning to T2DM.

Composition, Diversity and Abundance of Gut Microbiome in Prediabetes and Type 2 Diabetes

Association between type 2 diabetes (T2DM) and compositional changes in the gut micro biota is established, however little is known about the dysbiosis in early stages of Prediabetes (preDM). The purpose of this investigation is to elucidate the characteristics of the gut micro biome in preDM and T2DM, compared to Non-Diabetic (nonDM) subjects. Forty nine subjects were recruited for this study, 15 nonDM, 20 preDM and 14 T2DM. Bacterial community composition and diversity were investigated in fecal DNA samples using Illumina sequencing of the V4 region within the 16S rRNA gene. The five most abundant phyla identified were: Bacteroidetes, Firmicutes, Proteobacteria, Verrucomicrobia, and Actinobacteria. Class Chloracido bacteria was increased in preDM compared to T2DM (p = 0.04). An unknown genus from family Pseudonocardiaceae was significantly present in preDM group compared to the others (p = 0.04). Genus Collinsella, and an unknown genus belonging to family Enterobacteriaceae were both found to be significantly increased in T2DM compared to the other groups (Collinsella, and p = 0.03, Enterobacteriaceae genus p = 0.02). PERMANOVA and Mantel tests performed did not reveal a relationship between overall composition and diagnosis group or HbA1C level. This study identified dysbiosis associated with both preDM and T2DM, specifically at the class and genus levels suggesting that earlier treatment in preDM could possibly have an impact on the intestinal micro flora transitioning to T2DM.

The microbiome of the built environment and mental health

The microbiome of the built environment (MoBE) is a relatively new area of study. While some knowledge has been gained regarding impacts of the MoBE on the human microbiome and disease vulnerability, there is little knowledge of the impacts of the MoBE on mental health. Depending on the specific microbial species involved, the transfer of microorganisms from the built environment to occupant's cutaneous or mucosal membranes has the potential to increase or disrupt immunoregulation and/or exaggerate or suppress inflammation. Preclinical evidence highlighting the influence of the microbiota on systemic inflammation supports the assertion that microorganisms, including those originating from the built environment, have the potential to either increase or decrease the risk of inflammation-induced psychiatric conditions and their symptom severity. With advanced understanding of both the ecology of the built environment, and its influence on the human microbiome, it may be possible to develop bioinformed strategies for management of the built environment to promote mental health. Here we present a brief summary of microbiome research in both areas and highlight two interdependencies including the following: (1) effects of the MoBE on the human microbiome and (2) potential opportunities for manipulation of the MoBE in order to improve mental health. In addition, we propose future research directions including strategies for assessment of changes in the microbiome of common areas of built environments shared by multiple human occupants, and associated cohort-level changes in the mental health of those who spend time in the buildings. Overall, our understanding of the fields of both the MoBE and influence of host-associated microorganisms on mental health are advancing at a rapid pace and, if linked, could offer considerable benefit to health and wellness.

Relative and contextual contribution of different sources to the composition and abundance of indoor air bacteria in residences

BACKGROUND

The study of the microbial communities in the built environment is of critical importance as humans spend the majority of their time indoors. While the microorganisms in living spaces, especially those in the air, can impact health and well-being, little is known of their identity and the processes that determine their assembly. We investigated the source-sink relationships of airborne bacteria in 29 homes in the San Francisco Bay Area. Samples taken in the sites expected to be source habitats for indoor air microbes were analyzed by 16S rRNA-based pyrosequencing and quantitative PCR. The community composition was related to the characteristics of the household collected at the time of sampling, including the number of residents and pets, activity levels, frequency of cooking and vacuum cleaning, extent of natural ventilation, and abundance and type of vegetation surrounding the building.

RESULTS

Indoor air harbored a diverse bacterial community dominated by Diaphorobacter sp., Propionibacterium sp., Sphingomonas sp., and Alicyclobacillus sp. Source-sink analysis suggested that outdoor air was the primary source of indoor air microbes in most homes. Bacterial phylogenetic diversity and relative abundance in indoor air did not differ statistically from that in outdoor air. Moreover, the abundance of bacteria in outdoor air was positively correlated with that in indoor air, as would be expected if outdoor air was the main contributor to the bacterial community in indoor bioaerosols. The number of residents, presence of pets, and local tap water also influenced the diversity and size of indoor air microbes. The bacterial load in air increased with the number of residents, activity, and frequency of natural ventilation, and the proportion of bacteria putatively derived from skin increased with the number of residents. Vacuum cleaning increased the signature of pet- and floor-derived bacteria in indoor air, while the frequency of natural ventilation decreased the relative abundance of tap water-derived microorganisms in air.

CONCLUSIONS

Indoor air in residences harbors a diverse bacterial community originating from both outdoor and indoor sources and is strongly influenced by household characteristics.

Microbiota formed on attached stainless steel coupons correlates with the natural biofilm of the sink surface in domestic kitchens

Stainless steel coupons are frequently used in biofilm studies in the laboratory, as this material is commonly used in the food industry. The coupons are attached to different surfaces to create a "natural" biofilm to be studied further in laboratory trials. However, little has been done to investigate how well the microbiota on such coupons represents the surrounding environment. The microbiota on sink wall surfaces and on new stainless steel coupons attached to the sink wall for 3 months in 8 domestic kitchen sinks was investigated by next-generation sequencing (MiSeq) of the 16S rRNA gene derived from DNA and RNA (cDNA), and by plating and identification of colonies. The mean number of colony-forming units was about 10-fold higher for coupons than sink surfaces, and more variation in bacterial counts between kitchens was seen on sink surfaces than coupons. The microbiota in the majority of biofilms was dominated by Moraxellaceae (genus Moraxella/Enhydrobacter) and Micrococcaceae (genus Kocuria). The results demonstrated that the variation in the microbiota was mainly due to differences between kitchens (38.2%), followed by the different nucleic acid template (DNA vs RNA) (10.8%), and that only 5.1% of the variation was a result of differences between coupons and sink surfaces. The microbiota variation between sink surfaces and coupons was smaller for samples based on their RNA than on their DNA. Overall, our results suggest that new stainless steel coupons are suited to model the dominating part of the natural microbiota of the surrounding environment and, furthermore, are suitable for different downstream studies.

Microbiota of the indoor environment: a meta-analysis

BACKGROUND

As modern humans, we spend the majority of our time in indoor environments. Consequently, environmental exposure to microorganisms has important implications for human health, and a better understanding of the ecological drivers and processes that impact indoor microbial assemblages will be key for expanding our knowledge of the built environment. In the present investigation, we combined recent studies examining the microbiota of the built environment in order to identify unifying community patterns and the relative importance of indoor environmental factors. Ultimately, the present meta-analysis focused on studies of bacteria and archaea due to the limited number of high-throughput fungal studies from the indoor environment. We combined 16S ribosomal RNA (rRNA) gene datasets from 16 surveys of indoor environments conducted worldwide, additionally including 7 other studies representing putative environmental sources of microbial taxa (outdoor air, soil, and the human body).

RESULTS

Combined analysis of subsets of studies that shared specific experimental protocols or indoor habitats revealed community patterns indicative of consistent source environments and environmental filtering. Additionally, we were able to identify several consistent sources for indoor microorganisms, particularly outdoor air and skin, mirroring what has been shown in individual studies. Technical variation across studies had a strong effect on comparisons of microbial community assemblages, with differences in experimental protocols limiting our ability to extensively explore the importance of, for example, sampling locality, building function and use, or environmental substrate in structuring indoor microbial communities.

CONCLUSIONS

We present a snapshot of an important scientific field in its early stages, where studies have tended to focus on heavy sampling in a few geographic areas. From the practical perspective, this endeavor reinforces the importance of negative "kit" controls in microbiome studies. From the perspective of understanding mechanistic processes in the built environment, this meta-analysis confirms that broad factors, such as geography and building type, structure indoor microbes. However, this exercise suggests that individual studies with common sampling techniques may be more appropriate to explore the relative importance of subtle indoor environmental factors on the indoor microbiome.

Humans differ in their personal microbial cloud

Dispersal of microbes between humans and the built environment can occur through direct contact with surfaces or through airborne release; the latter mechanism remains poorly understood. Humans emit upwards of 10⁶ biological particles per hour, and have long been known to transmit pathogens to other individuals and to indoor surfaces. However it has not previously been demonstrated that humans emit a detectible microbial cloud into surrounding indoor air, nor whether such clouds are sufficiently differentiated to allow the identification of individual occupants. We used high-throughput sequencing of 16S rRNA genes to characterize the airborne bacterial contribution of a single person sitting in a sanitized custom experimental climate chamber. We compared that to air sampled in an adjacent, identical, unoccupied chamber, as well as to supply and exhaust air sources. Additionally, we assessed microbial communities in settled particles surrounding each occupant, to investigate the potential long-term fate of airborne microbial emissions. Most occupants could be clearly detected by their airborne bacterial emissions, as well as their contribution to settled particles, within 1.5–4 h. Bacterial clouds from the occupants were statistically distinct, allowing the identification of some individual occupants. Our results confirm that an occupied space is microbially distinct from an unoccupied one, and demonstrate for the first time that individuals release their own personalized microbial cloud.

Cleanroom Maintenance Significantly Reduces Abundance but Not Diversity of Indoor Microbiomes

Cleanrooms have been considered microbially-reduced environments and are used to protect human health and industrial product assembly. However, recent analyses have deciphered a rather broad diversity of microbes in cleanrooms, whose origin as well as physiological status has not been fully understood. Here, we examined the input of intact microbial cells from a surrounding built environment into a spacecraft assembly cleanroom by applying a molecular viability assay based on propidium monoazide (PMA). The controlled cleanroom (CCR) was characterized by ~6.2*10³ 16S rRNA gene copies of intact bacterial cells per m² floor surface, which only represented 1% of the total community that could be captured via molecular assays without viability marker. This was in contrast to the uncontrolled adjoining facility (UAF) that had 12 times more living bacteria. Regarding diversity measures retrieved from 16S rRNA Illumina-tag analyzes, we observed, however, only a minor drop in the cleanroom facility allowing the conclusion that the number but not the diversity of microbes is strongly affected by cleaning procedures. Network analyses allowed tracking a substantial input of living microbes to the cleanroom and a potential enrichment of survival specialists like bacterial spore formers and archaeal halophiles and mesophiles. Moreover, the cleanroom harbored a unique community including 11 exclusive genera, e.g., Haloferax and Sporosarcina, which are herein suggested as indicators of cleanroom environments. In sum, our findings provide evidence that archaea are alive in cleanrooms and that cleaning efforts and cleanroom maintenance substantially decrease the number but not the diversity of indoor microbiomes.

Meat Processing Plant Microbiome and Contamination Patterns of Cold-Tolerant Bacteria Causing Food Safety and Spoilage Risks in the Manufacture of Vacuum-Packaged Cooked Sausages

Refrigerated food processing facilities are specific man-made niches likely to harbor cold-tolerant bacteria. To characterize this type of microbiota and study the link between processing plant and product microbiomes, we followed and compared microbiota associated with the raw materials and processing stages of a vacuum-packaged, cooked sausage product affected by a prolonged quality fluctuation with occasional spoilage manifestations during shelf life. A total of 195 samples were subjected to culturing and amplicon sequence analyses. Abundant mesophilic psychrotrophs were detected within the microbiomes throughout the different compartments of the production plant environment. However, each of the main genera of food safety and quality interest, e.g., Leuconostoc, Brochothrix, and Yersinia, had their own characteristic patterns of contamination. Bacteria from the genus Leuconostoc, commonly causing spoilage of cold-stored, modified-atmosphere-packaged foods, were detected in high abundance (up to >98%) in the sausages studied. The same operational taxonomic units (OTUs) were, however, detected in lower abundances in raw meat and emulsion (average relative abundance of 2%±5%), as well as on the processing plant surfaces (<4%). A completely different abundance profile was found for OTUs phylogenetically close to the species Yersinia pseudotuberculosis. These OTUs were detected in high abundance (up to 28%) on the processing plant surfaces but to a lesser extent (<1%) in raw meat, sausage emulsion, and sausages. The fact that Yersinia-like OTUs were found on the surfaces of a high-hygiene packaging compartment raises food safety concerns related to their resilient existence on surfaces.

DNA Persistence in a Sink Drain Environment

Biofilms are organized structures composed mainly of cells and extracellular polymeric substances produced by the constituent microorganisms. Ubiquitous in nature, biofilms have an innate ability to capture and retain passing material and may therefore act as natural collectors of contaminants or signatures of upstream activities. To determine the persistence and detectability of DNA passing through a sink drain environment, Bacillus anthracis strain Ames35 was cultured (6.35 x 10⁷ CFU/mL), sterilized, and disposed of by addition to a sink drain apparatus with an established biofilm. The sink drain apparatus was sampled before and for several days after the addition of the sterilized B. anthracis culture to detect the presence of B. anthracis DNA. Multiple PCR primer pairs were used to screen for chromosomal and plasmid DNA with primers targeting shorter sequences showing greater amplification efficiency and success. PCR amplification and detection of target sequences indicate persistence of chromosomal DNA and plasmid DNA in the biofilm for 5 or more and 14 or more days, respectively.

Short Course in the Microbiome

Over the past decade, it has become evident that the microbiome is an important environmental factor that affects many physiological processes, such as cell proliferation and differentiation, behaviour, immune function and metabolism. More importantly, it may contribute to a wide variety of diseases, including cancer, inflammatory diseases, metabolic diseases and responses to pathogens. We expect that international, integrative and interdisciplinary translational research teams, along with the emergence of FDA-approved platforms, will set the framework for microbiome-based therapeutics and diagnostics. We recognize that the microbiome ecosystem offers new promise for personalized/precision medicine and targeted treatment for a variety of diseases. The short course was held as a four-session webinar series in April 2015, taught by pioneers and experts in the microbiome ecosystem, covering a broad range of topics from the healthy microbiome to the effects of an altered microbiome from neonates to adults and the long term effects as it is related to disease, from asthma to cancer. We have learned to appreciate how beneficial our microbes are in breaking down our food, fighting off infections and nurturing our immune system, and this information provides us with ideas as to how we can manipulate our microbiome to prevent certain diseases. However, given the variety of applications, there are scientific challenges, though there are very promising areas in reference to the clinical benefits of understanding more about our microbiome, whether in our gut or on our skin: the outlook is bright. A summary of the short course is presented as a meeting dispatch.

Hospital-associated microbiota and implications for nosocomial infections

The rise of high-throughput sequencing technologies and culture-independent microbial surveys has the potential to revolutionize our understanding of how microbes colonize, move about, and evolve in hospital environments. Genome analysis of individual organisms, characterization of population dynamics, and microbial community ecology are facilitating the identification of novel pathogens, the tracking of disease outbreaks, and the study of the evolution of antibiotic resistance. Here we review the recent applications of these methods to microbial ecology studies in hospitals and discuss their potential to influence hospital management policy and practice and to reduce nosocomial infections and the spread of antibiotic resistance.

Quo vadis? Microbial profiling revealed strong effects of cleanroom maintenance and routes of contamination in indoor environments

Space agencies maintain highly controlled cleanrooms to ensure the demands of planetary protection. To study potential effects of microbiome control, we analyzed microbial communities in two particulate-controlled cleanrooms (ISO 5 and ISO 8) and two vicinal uncontrolled areas (office, changing room) by cultivation and 16S rRNA gene amplicon analysis (cloning, pyrotagsequencing, and PhyloChip G3 analysis). Maintenance procedures affected the microbiome on total abundance and microbial community structure concerning richness, diversity and relative abundance of certain taxa. Cleanroom areas were found to be mainly predominated by potentially human-associated bacteria; archaeal signatures were detected in every area. Results indicate that microorganisms were mainly spread from the changing room (68%) into the cleanrooms, potentially carried along with human activity. The numbers of colony forming units were reduced by up to ~400 fold from the uncontrolled areas towards the ISO 5 cleanroom, accompanied with a reduction of the living portion of microorganisms from 45% (changing area) to 1% of total 16S rRNA gene signatures as revealed via propidium monoazide treatment of the samples. Our results demonstrate the strong effects of cleanroom maintenance on microbial communities in indoor environments and can be used to improve the design and operation of biologically controlled cleanrooms.

Diversity of bacterial communities of fitness center surfaces in a U.S. metropolitan area

Public fitness centers and exercise facilities have been implicated as possible sources for transmitting community-acquired bacterial infections. However, the overall diversity of the bacterial community residing on the surfaces in these indoor environments is still unknown. In this study, we investigated the overall bacterial ecology of selected fitness centers in a metropolitan area (Memphis, TN, USA) utilizing culture-independent pyrosequencing of the 16S rRNA genes. Samples were collected from the skin-contact surfaces (e.g., exercise instruments, floor mats, handrails, etc.) within fitness centers. Taxonomical composition revealed the abundance of Firmicutes phyla, followed by Proteobacter and Actinobacteria, with a total of 17 bacterial families and 25 bacterial genera. Most of these bacterial genera are of human and environmental origin (including, air, dust, soil, and water). Additionally, we found the presence of some pathogenic or potential pathogenic bacterial genera including Salmonella, Staphylococcus, Klebsiella, and Micrococcus. Staphylococcus was found to be the most prevalent genus. Presence of viable forms of these pathogens elevates risk of exposure of any susceptible individuals. Several factors (including personal hygiene, surface cleaning and disinfection schedules of the facilities) may be the reasons for the rich bacterial diversity found in this study. The current finding underscores the need to increase public awareness on the importance of personal hygiene and sanitation for public gym users.

Indoor-air microbiome in an urban subway network: diversity and dynamics

Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on α- and β-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe.

Environmental viral contamination in a pediatric hospital outpatient waiting area: implications for infection control

BACKGROUND

Nosocomial outbreaks of viral etiology are costly and can have a major impact on patient care. Many viruses are known to persist in the inanimate environment and may pose a risk to patients and health care workers. We investigate the frequency of environmental contamination with common health care-associated viruses and explore the use of torque-teno virus as a marker of environmental contamination.

METHODS

Environmental screening for a variety of clinically relevant viruses was carried out over 3 months in a UK pediatric hospital using air sampling and surface swabbing. Swabs were tested for the presence of virus nucleic acid by quantitative polymerase chain reactions.

RESULTS

Viral nucleic acid was found on surfaces and in the air throughout the screening period, with adenovirus DNA being the most frequent. Door handles were frequently contaminated. Torque-teno virus was also found at numerous sites.

CONCLUSION

Evidence of environmental contamination with viral pathogens is present in health care environments and may be indicative of an infectious virus being present. Screening for viruses should be included in infection control strategies. Torque-teno virus may provide a better marker of contamination and reduce time and cost of screening for individual viruses.

Microbial sequencing analyses suggest the presence of a fecal veneer on indoor climbing wall holds

Artificial climbing walls represent a unique indoor environment in which humans interact closely with a variety of surface types. Climbing wall holds may mediate transmission of organisms between individuals, and yet there are no studies that identify microorganisms present on these surfaces. In the current study, the microorganisms found on climbing wall holds were characterized by analysis of amplified SSU rRNA gene sequences. In contrast to many other studies of built environments, the majority of microorganisms on holds were most closely related to microbes annotated as being recovered from environmental sources, such as soil, with human skin also representing an important source. Regional patterns were evident as rRNA gene sequences from the marine cyanobacterium Prochlorococcus were abundant in gyms found within 16 km of the ocean. Enterobacteriaceae were present on 100 % of holds surveyed, and the members detected are commonly associated with fecal matter.

Mobile phones carry the personal microbiome of their owners

Most people on the planet own mobile phones, and these devices are increasingly being utilized to gather data relevant to our personal health, behavior, and environment. During an educational workshop, we investigated the utility of mobile phones to gather data about the personal microbiome - the collection of microorganisms associated with the personal effects of an individual. We characterized microbial communities on smartphone touchscreens to determine whether there was significant overlap with the skin microbiome sampled directly from their owners. We found that about 22% of the bacterial taxa on participants' fingers were also present on their own phones, as compared to 17% they shared on average with other people's phones. When considered as a group, bacterial communities on men's phones were significantly different from those on their fingers, while women's were not. Yet when considered on an individual level, men and women both shared significantly more of their bacterial communities with their own phones than with anyone else's. In fact, 82% of the OTUs were shared between a person's index and phone when considering the dominant taxa (OTUs with more than 0.1% of the sequences in an individual's dataset). Our results suggest that mobile phones hold untapped potential as personal microbiome sensors.

Associations between bacterial communities of house dust and infant gut

The human gut is host to a diverse and abundant community of bacteria that influence health and disease susceptibility. This community develops in infancy, and its composition is strongly influenced by environmental factors, notably perinatal anthropogenic exposures such as delivery mode (Cesarean vs. vaginal) and feeding method (breast vs. formula); however, the built environment as a possible source of exposure has not been considered. Here we report on a preliminary investigation of the associations between bacteria in house dust and the nascent fecal microbiota from 20 subjects from the Canadian Healthy Infant Longitudinal Development (CHILD) Study using high-throughput sequence analysis of portions of the 16S rRNA gene. Despite significant differences between the dust and fecal microbiota revealed by Nonmetric Multidimensional Scaling (NMDS) analysis, permutation analysis confirmed that 14 bacterial OTUs representing the classes Actinobacteria (3), Bacilli (3), Clostridia (6) and Gammaproteobacteria (2) co-occurred at a significantly higher frequency in matched dust-stool pairs than in randomly permuted pairs, indicating an association between these dust and stool communities. These associations could indicate a role for the indoor environment in shaping the nascent gut microbiota, but future studies will be needed to confirm that our findings do not solely reflect a reverse pathway. Although pet ownership was strongly associated with the presence of certain genera in the dust for dogs (Agrococcus, Carnobacterium, Exiguobacterium, Herbaspirillum, Leifsonia and Neisseria) and cats (Escherichia), no clear patterns were observed in the NMDS-resolved stool community profiles as a function of pet ownership.

Waste not, want not: why rarefying microbiome data is inadmissible

Current practice in the normalization of microbiome count data is inefficient in the statistical sense. For apparently historical reasons, the common approach is either to use simple proportions (which does not address heteroscedasticity) or to use rarefying of counts, even though both of these approaches are inappropriate for detection of differentially abundant species. Well-established statistical theory is available that simultaneously accounts for library size differences and biological variability using an appropriate mixture model. Moreover, specific implementations for DNA sequencing read count data (based on a Negative Binomial model for instance) are already available in RNA-Seq focused R packages such as edgeR and DESeq. Here we summarize the supporting statistical theory and use simulations and empirical data to demonstrate substantial improvements provided by a relevant mixture model framework over simple proportions or rarefying. We show how both proportions and rarefied counts result in a high rate of false positives in tests for species that are differentially abundant across sample classes. Regarding microbiome sample-wise clustering, we also show that the rarefying procedure often discards samples that can be accurately clustered by alternative methods. We further compare different Negative Binomial methods with a recently-described zero-inflated Gaussian mixture, implemented in a package called metagenomeSeq. We find that metagenomeSeq performs well when there is an adequate number of biological replicates, but it nevertheless tends toward a higher false positive rate. Based on these results and well-established statistical theory, we advocate that investigators avoid rarefying altogether. We have provided microbiome-specific extensions to these tools in the R package, phyloseq.

The term microbiome refers to the ecosystem of microbes that live in a defined environment. The decreasing cost and increasing speed of DNA sequencing technology has recently provided scientists with affordable and timely access to the genes and genomes of microbiomes that inhabit our planet and even our own bodies. In these investigations many microbiome samples are sequenced at the same time on the same DNA sequencing machine, but often result in total numbers of sequences per sample that are vastly different. The common procedure for addressing this difference in sequencing effort across samples – different library sizes – is to either (1) base analyses on the proportional abundance of each species in a library, or (2) rarefy, throw away sequences from the larger libraries so that all have the same, smallest size. We show that both of these normalization methods can work when comparing obviously-different whole microbiomes, but that neither method works well when comparing the relative proportions of each bacterial species across microbiome samples. We show that alternative methods based on a statistical mixture model perform much better and can be easily adapted from a separate biological sub-discipline, called RNA-Seq analysis.

Bacterial communities on classroom surfaces vary with human contact

BACKGROUND

Humans can spend the majority of their time indoors, but little is known about the interactions between the human and built-environment microbiomes or the forces that drive microbial community assembly in the built environment. We sampled 16S rRNA genes from four different surface types throughout a university classroom to determine whether bacterial assemblages on each surface were best predicted by routine human interactions or by proximity to other surfaces within the classroom. We then analyzed our data with publicly-available datasets representing potential source environments.

RESULTS

Bacterial assemblages from the four surface types, as well as individual taxa, were indicative of different source pools related to the type of human contact each surface routinely encounters. Spatial proximity to other surfaces in the classroom did not predict community composition.

CONCLUSIONS

Our results indicate that human-associated microbial communities can be transferred to indoor surfaces following contact, and that such transmission is possible even when contact is indirect, but that proximity to other surfaces in the classroom does not influence community composition.

Airborne bacterial communities in residences: similarities and differences with fungi

Genetic analysis of indoor air has uncovered a rich microbial presence, but rarely have both the bacterial and fungal components been examined in the same samples. Here we present a study that examined the bacterial component of passively settled microbes from both indoor and outdoor air over a discrete time period and for which the fungal component has already been reported. Dust was allowed to passively settle in five common locations around a home − living room, bedroom, bathroom, kitchen, and balcony − at different dwellings within a university-housing complex for a one-month period at two time points, once in summer and again in winter. We amplified the bacterial 16S rRNA gene in these samples and analyzed them with high-throughput sequencing. Like fungal OTU-richness, bacterial OTU-richness was higher outdoors then indoors and was invariant across different indoor room types. While fungal composition was structured largely by season and residential unit, bacterial composition varied by residential unit and room type. Bacteria from putative outdoor sources, such as Sphingomonas and Deinococcus, comprised a large percentage of the balcony samples, while human-associated taxa comprised a large percentage of the indoor samples. Abundant outdoor bacterial taxa were also observed indoors, but the reverse was not true; this is unlike fungi, in which the taxa abundant indoors were also well-represented outdoors. Moreover, there was a partial association of bacterial composition and geographic distance, such that samples separated by even a few hundred meters tended have greater compositional differences than samples closer together in space, a pattern also observed for fungi. These data show that while the outdoor source for indoor bacteria and fungi varies in both space and time, humans provide a strong and homogenizing effect on indoor bacterial bioaerosols, a pattern not observed in fungi.

Architectural design drives the biogeography of indoor bacterial communities

BACKGROUND

Architectural design has the potential to influence the microbiology of the built environment, with implications for human health and well-being, but the impact of design on the microbial biogeography of buildings remains poorly understood. In this study we combined microbiological data with information on the function, form, and organization of spaces from a classroom and office building to understand how design choices influence the biogeography of the built environment microbiome.

RESULTS

Sequencing of the bacterial 16S gene from dust samples revealed that indoor bacterial communities were extremely diverse, containing more than 32,750 OTUs (operational taxonomic units, 97% sequence similarity cutoff), but most communities were dominated by Proteobacteria, Firmicutes, and Deinococci. Architectural design characteristics related to space type, building arrangement, human use and movement, and ventilation source had a large influence on the structure of bacterial communities. Restrooms contained bacterial communities that were highly distinct from all other rooms, and spaces with high human occupant diversity and a high degree of connectedness to other spaces via ventilation or human movement contained a distinct set of bacterial taxa when compared to spaces with low occupant diversity and low connectedness. Within offices, the source of ventilation air had the greatest effect on bacterial community structure.

CONCLUSIONS

Our study indicates that humans have a guiding impact on the microbial biodiversity in buildings, both indirectly through the effects of architectural design on microbial community structure, and more directly through the effects of human occupancy and use patterns on the microbes found in different spaces and space types. The impact of design decisions in structuring the indoor microbiome offers the possibility to use ecological knowledge to shape our buildings in a way that will select for an indoor microbiome that promotes our health and well-being.

The diversity and distribution of fungi on residential surfaces

The predominant hypothesis regarding the composition of microbial assemblages in indoor environments is that fungal assemblages are structured by outdoor air with a moderate contribution by surface growth, whereas indoor bacterial assemblages represent a mixture of bacteria entered from outdoor air, shed by building inhabitants, and grown on surfaces. To test the fungal aspect of this hypothesis, we sampled fungi from three surface types likely to support growth and therefore possible contributors of fungi to indoor air: drains in kitchens and bathrooms, sills beneath condensation-prone windows, and skin of human inhabitants. Sampling was done in replicated units of a university-housing complex without reported mold problems, and sequences were analyzed using both QIIME and the new UPARSE approach to OTU-binning, to the same result. Surfaces demonstrated a mycological profile similar to that of outdoor air from the same locality, and assemblages clustered by surface type. "Weedy" genera typical of indoor air, such as Cladosporium and Cryptococcus, were abundant on sills, as were a diverse set of fungi of likely outdoor origin. Drains supported more depauperate assemblages than the other surfaces and contained thermotolerant genera such as Exophiala, Candida, and Fusarium. Most surprising was the composition detected on residents' foreheads. In addition to harboring Malassezia, a known human commensal, skin also possessed a surprising richness of non-resident fungi, including plant pathogens such as ergot (Claviceps purperea). Overall, fungal richness across indoor surfaces was high, but based on known autecologies, most of these fungi were unlikely to be growing on surfaces. We conclude that while some endogenous fungal growth on typical household surfaces does occur, particularly on drains and skin, all residential surfaces appear - to varying degrees - to be passive collectors of airborne fungi of putative outdoor origin, a view of the origins of the indoor microbiome quite different from bacteria.

Identification of household bacterial community and analysis of species shared with human microbiome

Microbial populations in indoor environments, where we live and eat, are important for public health. Various bacterial species reside in the kitchen, and refrigerators, the major means of food storage within kitchens, can be a direct source of food borne illness. Therefore, the monitoring of microbiota in the refrigerator is important for food safety. We investigated and compared bacterial communities that reside in the vegetable compartment of the refrigerator and on the seat of the toilet, which is recognized as highly colonized by microorganisms, in ten houses using high-throughput sequencing. Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes were predominant in refrigerator and toilet samples. However, Proteobacteria was more abundant in the refrigerator, and Firmicutes was more abundant in the toilet. These household bacterial communities were compared with those of human skin and gut to identify potential sources of household bacteria. Bacterial communities from refrigerators and toilets shared more species in common with human skin than gut. Opportunistic pathogens, including Propionibacterium acnes, Bacteroides vulgatus, and Staphylococcus epidermidis, were identified as species shared with human skin and gut microbiota. This approach can provide a general background of the household microbiota and a potential method of source-tracking for public health purposes.

Facility-specific "house" microbiome drives microbial landscapes of artisan cheesemaking plants

Cheese fermentations involve the growth of complex microbial consortia, which often originate in the processing environment and drive the development of regional product qualities. However, the microbial milieus of cheesemaking facilities are largely unexplored and the true nature of the fermentation-facility relationship remains nebulous. Thus, a high-throughput sequencing approach was employed to investigate the microbial ecosystems of two artisanal cheesemaking plants, with the goal of elucidating how the processing environment influences microbial community assemblages. Results demonstrate that fermentation-associated microbes dominated most surfaces, primarily Debaryomyces and Lactococcus, indicating that establishment of these organisms on processing surfaces may play an important role in microbial transfer, beneficially directing the course of sequential fermentations. Environmental organisms detected in processing environments dominated the surface microbiota of washed-rind cheeses maturing in both facilities, demonstrating the importance of the processing environment for populating cheese microbial communities, even in inoculated cheeses. Spatial diversification within both facilities reflects the functional adaptations of microbial communities inhabiting different surfaces and the existence of facility-specific "house" microbiota, which may play a role in shaping site-specific product characteristics.

Monitoring Seasonal Changes in Winery-Resident Microbiota

During the transformation of grapes to wine, wine fermentations are exposed to a large area of specialized equipment surfaces within wineries, which may serve as important reservoirs for two-way transfer of microbes between fermentations. However, the role of winery environments in shaping the microbiota of wine fermentations and vectoring wine spoilage organisms is poorly understood at the systems level. Microbial communities inhabiting all major equipment and surfaces in a pilot-scale winery were surveyed over the course of a single harvest to track the appearance of equipment microbiota before, during, and after grape harvest. Results demonstrate that under normal cleaning conditions winery surfaces harbor seasonally fluctuating populations of bacteria and fungi. Surface microbial communities were dependent on the production context at each site, shaped by technological practices, processing stage, and season. During harvest, grape- and fermentation-associated organisms populated most winery surfaces, acting as potential reservoirs for microbial transfer between fermentations. These surfaces harbored large populations of Saccharomyces cerevisiae and other yeasts prior to harvest, potentially serving as an important vector of these yeasts in wine fermentations. However, the majority of the surface communities before and after harvest comprised organisms with no known link to wine fermentations and a near-absence of spoilage-related organisms, suggesting that winery surfaces do not overtly vector wine spoilage microbes under normal operating conditions.

Home life: factors structuring the bacterial diversity found within and between homes

Most of our time is spent indoors where we are exposed to a wide array of different microorganisms living on surfaces and in the air of our homes. Despite their ubiquity and abundance, we have a limited understanding of the microbial diversity found within homes and how the composition and diversity of microbial communities change across different locations within the home. Here we examined the diversity of bacterial communities found in nine distinct locations within each of forty homes in the Raleigh-Durham area of North Carolina, USA, using high-throughput sequencing of the bacterial 16S rRNA gene. We found that each of the sampled locations harbored bacterial communities that were distinct from one another with surfaces that are regularly cleaned typically harboring lower levels of diversity than surfaces that are cleaned infrequently. These location-specific differences in bacterial communities could be directly related to usage patterns and differences in the likely sources of bacteria dispersed onto these locations. Finally, we examined whether the variability across homes in bacterial diversity could be attributed to outdoor environmental factors, indoor habitat structure, or the occupants of the home. We found that the presence of dogs had a significant effect on bacterial community composition in multiple locations within homes as the homes occupied by dogs harbored more diverse communities and higher relative abundances of dog-associated bacterial taxa. Furthermore, we found a significant correlation between the types of bacteria deposited on surfaces outside the home and those found inside the home, highlighting that microbes from outside the home can have a direct effect on the microbial communities living on surfaces within our homes. Together this work provides the first comprehensive analysis of the microbial communities found in the home and the factors that shape the structure of these communities both within and between homes.

Bacterial communities associated with the surfaces of fresh fruits and vegetables

Fresh fruits and vegetables can harbor large and diverse populations of bacteria. However, most of the work on produce-associated bacteria has focused on a relatively small number of pathogenic bacteria and, as a result, we know far less about the overall diversity and composition of those bacterial communities found on produce and how the structure of these communities varies across produce types. Moreover, we lack a comprehensive view of the potential effects of differing farming practices on the bacterial communities to which consumers are exposed. We addressed these knowledge gaps by assessing bacterial community structure on conventional and organic analogs of eleven store-bought produce types using a culture-independent approach, 16 S rRNA gene pyrosequencing. Our results demonstrated that the fruits and vegetables harbored diverse bacterial communities, and the communities on each produce type were significantly distinct from one another. However, certain produce types (i.e., sprouts, spinach, lettuce, tomatoes, peppers, and strawberries) tended to share more similar communities as they all had high relative abundances of taxa belonging to the family Enterobacteriaceae when compared to the other produce types (i.e., apples, peaches, grapes, and mushrooms) which were dominated by taxa belonging to the Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria phyla. Although potentially driven by factors other than farming practice, we also observed significant differences in community composition between conventional and organic analogs within produce types. These differences were often attributable to distinctions in the relative abundances of Enterobacteriaceae taxa, which were generally less abundant in organically-grown produce. Taken together, our results suggest that humans are exposed to substantially different bacteria depending on the types of fresh produce they consume with differences between conventionally and organically farmed varieties contributing to this variation.

Studying the microbiology of the indoor environment

The majority of people in the developed world spend more than 90% of their lives indoors. Here, we examine our understanding of the bacteria that co-inhabit our artificial world and how they might influence human health.

Home life: factors structuring the bacterial diversity found within and between homes

Most of our time is spent indoors where we are exposed to a wide array of different microorganisms living on surfaces and in the air of our homes. Despite their ubiquity and abundance, we have a limited understanding of the microbial diversity found within homes and how the composition and diversity of microbial communities change across different locations within the home. Here we examined the diversity of bacterial communities found in nine distinct locations within each of forty homes in the Raleigh-Durham area of North Carolina, USA, using high-throughput sequencing of the bacterial 16S rRNA gene. We found that each of the sampled locations harbored bacterial communities that were distinct from one another with surfaces that are regularly cleaned typically harboring lower levels of diversity than surfaces that are cleaned infrequently. These location-specific differences in bacterial communities could be directly related to usage patterns and differences in the likely sources of bacteria dispersed onto these locations. Finally, we examined whether the variability across homes in bacterial diversity could be attributed to outdoor environmental factors, indoor habitat structure, or the occupants of the home. We found that the presence of dogs had a significant effect on bacterial community composition in multiple locations within homes as the homes occupied by dogs harbored more diverse communities and higher relative abundances of dog-associated bacterial taxa. Furthermore, we found a significant correlation between the types of bacteria deposited on surfaces outside the home and those found inside the home, highlighting that microbes from outside the home can have a direct effect on the microbial communities living on surfaces within our homes. Together this work provides the first comprehensive analysis of the microbial communities found in the home and the factors that shape the structure of these communities both within and between homes.