The microBEnet blog

Genomic Standards Consortium 19 in Australia May 2017 registration open (focus on viruses & microbial euks)

I thought this would be of interest – got it by email

We are happy to announce that registration for GSC19 is now open!

The meeting will take place at the Stamford Plaza, Brisbane, Australia between 15th-17th May, 2017.
The theme of the meeting will be Extending Standards to Viruses and Microbial Eukaryotes.

The agenda is packed with exciting sessions and topics:

  • Viral classification and genome standards
  • Microbial eukaryote classification and genome standards
  • Bioinformatic workflow standards, (large scale, reproducible, cost-effective)
  • Microbiomes of Australia
  • Modes and tempo of evolution
  • Genome taxonomy

We have an exciting line-up of speakers:

  • Aaron Darling, University of Technology, Sydney
  • Nikos Kyrpides, DOE, Joint Genome Institute
  • Tanja Woyke, DOE, Joint Genome Institute
  • Howard Ochman, University of Texas, Austin
  • Michael Crusoe, Common Workflow Language project, Lithuania
  • Donovan Parks, Consultant, University of Queensland
  • Jodie Van de Kamp, BASE-CSIRO Marine & Atmospheric Research
  • Jian Xu, Qingdao Inst of Bioenergy & Bioprocess Tech, China
  • Pelin Yilmaz, Max Planck Institute, Bremen
  • Folker Meyer, Argonne National Laboratory
  • Lynn Schriml, University of Maryland
  • Thomas Rattei, University of Vienna
  • Jan Meier-Kolthoff, Newcastle University, UK
  • Dave Wood, University of Queensland
  • Chris Rinke, University of Queensland
  • Maria Dzunkova, University of Queensland

The agenda is still taking shape, you can find specific session details and confirmed speakers in the GSC19 homepage:

Please note that we have a limited time special offer from the workshop hotels:

Stamford Plaza
Stamford Plaza and Hotel is the main Accommodation and meeting venue. They are holding 50 rooms for the period of Sunday 14th to Tuesday 16th (inclusive) at the rate of AUD$205/night (USD$154/Euro$145). Other nights are AUD$235/night (USD$176/Euro$166). Please follow this link to make a booking.

Oaks Felix
Oaks Felix have set up a group code ‘GSC19’. The code offers 12% off their best available rates at Oaks Felix, Oaks 212 Margaret and iStay River City. Please follow this link make a booking.

We are looking forward to seeing you all in Brisbane!

Pelin Yilmaz (on behalf of the GSC19 organising committee)

From @CNNAshley at @CNN: Why NASA is sending a superbug to the space station 

Just a quick post here.  There is a new CNN story that may be of interest.

An antibiotic-resistant superbug will launch from the same pad where the first manned mission to the moon lifted off to be studied on the International Space Station.

Source: Why NASA is sending a superbug to the space station –

I confess I am skeptical of some of the scientific claims being reportedly made by Dr. Anita Goel. For example  – see this:

I have this hypothesis that microgravity will accelerate the mutation patterns. If we can use microgravity as an accelerator to fast-forward and get a sneak preview of what these mutations will look like, then we can essentially build smarter drugs on Earth

We know lots of ways to accelerate mutation rates on earth – radiation, making mutations in DNA repair genes, other mutagens, and so on.  Why would using microgravity be worthwhile compared to those other methods?  I do not know.

Also – each agent that leads to an increase in mutation rate has it’s own spectrum of types of mutations that it accelerates.  Who is to say that microgravity will increase mutations in the same way that they would occur on earth with just an increase in speed?

And then there is this:

“If indeed we can use the ISS as an accelerator, an incubator, to know what future mutations of superbugs like MRSA will be, we use that info to develop better algorithms on Earth to inform drug discovery and faster ways to get to smarter drugs that are more personalized and more precisely targeted to a bug or strain at hand. We can have those drugs ready before the mutations even show up on Earth.”

Same issues I guess.  Even if microgravity led to an acceleration in the mutation rate, I just don’t see how that will help anticipate the mutations that will show up on Earth.

I am all for doing research on microbes in space, for many reasons (e.g., see  And certainly microgravity could be an interesting tool for studying some processes in microbes.  But I am skeptical of some of the claimed goals of this project.  Not that I object to this work – I think we can learn a lot from such experiments – just not what is being claimed here.  And to be honest – anything that gets the public to think more about microbes can potentially be a good thing, it just should be presented carefully.

I assume there is much more to the science here than is being reported in the news stories.  The basic science part of this sounds interesting.  I am just deeply skeptical of the claimed applied value (e.g., predicting future mutations of MRSA).

Investigating the antibiotic resistome of rural and peri-urban Latin America

For many years, efforts to profile the antibiotic resistome of the human gut focused exclusively on two extremes of human society: Western, industrialized cities and remote hunter-gatherers. While these studies were undoubtedly important, they overlooked the majority of the world’s population, which exists somewhere between the two extremes. Indeed, three-quarters of the world’s population lives in low- and middle-income countries [1-2], with almost a billion in slums (World Health Organization) [3]. In rural areas, though many have intermittent access to towns and cities, 16% of the population does not use improved drinking water sources, and 50% still lack access to improved sanitation facilities (United Nations Millennium Development Goals Report 2015) [4]. From an antibiotic resistance perspective, contact with both subsistence agriculture (including livestock and soil) and population centers (including processed foods and a dense, diverse population) could increase the diversity of bacteria and antibiotic resistance to which these populations are exposed. Furthermore, the high incidence of infectious disease and widespread availability of antibiotics without prescription, coupled with a lack of clean water, could contribute to the spread of bacteria and antibiotic resistance genes. In fact, industrializing countries were responsible for the majority of the worldwide 36% increase in antibiotic use between 2000 and 2010 [5]. To address this critical gap in our understanding of the human resistome, we recently published a large-scale study of the microbial communities and antibiotic resistance genes associated with the human gut, waste disposal systems, and the environment in a rural Salvadoran village and a Peruvian slum (“Interconnected microbiomes and resistomes in low-income human habitats”) [6]. I led this study along with Pablo Tsukayama as part of our respective PhD thesis projects in Gautam Dantas’s lab ( at Washington University in St Louis.

A prefabricated home in the rural village, El Salvador
(Photos courtesy of Giordano Sosa-Soto and Melissa Mejía-Bautista)

We began our study in 2011 with the help of Dr. Douglas Berg (Professor Emeritus, Washington University in St. Louis), who set up a collaboration with professors Maria Teresita Bertoli, William Hoyos-Arango, and Karla Navarrete at the Universidad Dr. José Matías Delgado (UJMD) in San Salvador to investigate the microbiota of rural Salvadorans. In parallel, we began a collaboration with the Universidad Peruana Cayetano Heredia (UPCH) in Lima, Peru, to study the microbiota of residents of urban slums. In retrospect, I had signed up for a uniquely challenging graduate experience. A mudslide destroyed the first village we had intended to study, and the village we finally selected was inaccessible during the rainy season when the mountainous dirt roads became impassable. There was exactly one manufacturer of dry ice in San Salvador, who was able to produce just enough dry ice in a single day for us to complete sample collection. Furthermore, though it may be difficult to believe, human feces was the easiest of the samples to import into the US: soil and animal feces, with their potential for the introduction of invasive species, are strictly regulated and required not only import permits but federal inspections of our laboratory space. To top it off, my Spanish was limited to one college semester and a year of frantic Rosetta Stone, and Gautam speaks no Spanish at all, which severely restricted our ability to communicate on the ground. Now in my postdoc, I am sometimes amazed that Gautam was willing, in his first five years as a PI, to invest serious resources in two such high-risk projects.

The insulated box that shipped samples between El Salvador and the US

Despite the challenges, we were able to successfully collect hundreds of samples from the village at multiple time points over two years, forming the basis for a longitudinal and cross-sectional profile of the microbiota of rural El Salvador. The lion’s share of the credit for this achievement goes to the Salvadoran team, whose creativity and dedication in solving the numerous obstacles that stood in the way of the project was outstanding. The primary responsibility of the faculty at UJMD is the teaching and practice of medicine. Unlike in the US, where we expect to be compensated for our research efforts, our collaborators advanced our research in their free time out of a passion for science and a desire to see the nascent Salvadoran research infrastructure grow. They used their experience treating people in rural locations to help decide which samples to collect, doggedly pursued regulatory officials to get the study protocol approved, and coordinated the sample collection with residents of the village. When a tree downed in a hurricane knocked out power for two weeks to the sole university laboratory where our samples were stored, they miraculously found alternate refrigeration sources. Two of the authors on the paper, medical students Melissa Mejía-Bautista and Giordano Sosa-Soto, even interrupted their medical education for a year to learn molecular biology in our lab, greatly contributing to the progress of the data production and introducing molecular biology techniques to their university.

Sterile containers lined up in preparation for fecal sample collection

In addition to our counterparts in El Salvador, I was shocked by the level of involvement and assistance we received from the village itself. Although most residents are subsistence farmers who are sometimes employed nearby, the village is extremely well-organized and headed by a mayor with a clear vision for their future. With the help of a local charitable organization, Epilogos Charities, Inc., the village had pursued a number of community improvement initiatives, including honey and fish farming co-operatives. The community also had prefabricated houses and composting latrines for each household, which use heat, dessication, and high pH to sterilize feces over the course of several months; the sterilized waste is then used as fertilizer for agricultural plots. The mayor was very proactive about checking in with us during each sample collection about any new information or benefits that had resulted from their participation in the study, and we sincerely hope that the information we gathered about the composition of their gut microbiota, as well as potential sources of antibiotic resistance genes, will lay the groundwork for future investigations and public health interventions.

Double-vault composting latrines

For example, studies such as ours may spur improvements in sanitation infrastructure in rural El Salvador, peri-urban Peru, and beyond. Given the enormous diversity of antibiotic resistance genes in the environment, the ready availability of antibiotics, and the rapid globalization and urbanization of our world, one of the best strategies for curbing the development of antibiotic resistance will be reducing the incidence of infectious disease before antibiotics become necessary. To do so, we will need creative sanitation solutions that can be deployed in places with limited income and limited water. Recently, a team of engineers at Washington University has begun work on improving the sterilization of human feces using composting latrines. Additionally, soon after our project began, El Salvador banned Intestinomicina, a cocktail of antibiotics available over-the-counter to treat gastrointestinal ailments. Although it was banned for unrelated health concerns, our research may draw attention to the ease of transfer of antibiotic resistance genes, leading to better stewardship of antibiotics.

A household agricultural plot


  1. The World Bank Group. Data: Countries: Middle Income. ( (2015)
  2. The World Bank Group. Data: Countries: Low Income. ( (2015)
  3. World Health Organization. Global Health Observatory (GHO) Data: Urban Health. ( (2015)
  4. United Nations. The Millennium Development Goals Report 2015. ( (2015)
  5. Van Boeckel, TP et al. Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data. Lancet Infect. Dis. 14, 742–750. (2014)
  6. Pehrsson EC, Tsukayama P, Patel S, Mejía-Bautista M, Sosa-Soto G, Navarrete KM, Calderon M, Cabrera L, Hoyos-Arango W, Bertoli MT, Berg DE, Gilman RH, Dantas G. Interconnected microbiomes and resistomes in low-income human habitats. Nature 533: 212-216. (2016) (

Of possible interest – DAS tool for metagenomic binning

Saw an interesting Tweet

And this tool may be of interest – it is from a new preprint in BioRXiv.  See abstract below:

Microbial communities are critical to ecosystem function. A key objective of metagenomic studies is to analyse organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of assembled genome fragments to genomes. Existing binning methods often fail to reconstruct a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotopes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tool applied to a constructed community generated more accurate bins than any automated method. Further, when applied to environmental and host-associated samples of different complexity, DAS Tool recovered substantially more near-complete genomes, including novel lineages, than any single binning method alone. The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.

Source: Recovery of genomes from metagenomes via a dereplication, aggregation, and scoring strategy | bioRxiv

Are these microbes the “same”?

There are a number of cases where determining the relationship between microbes is at the center of a research question. Are the microbes inhabiting a building the same as those inhabiting its tenants? Are the microbes in a hospital room the same as those that colonize newborn babies? Is the E. coli living on a wood surface the same as the E. coli living on a plastic surface?

The most common metric of comparing sequenced microbial genomes is average nucleotide identity (ANI)1. The basic idea is to align two genomes and count the number of mismatches in the alignment. Genomes with an ANI of 99% have 1 mismatch between them every hundred bases, whereas genomes with an ANI of 95% have five mismatches between them every one hundred bases, and so on. There are numerous methods to calculate average nucleotide identity, with the major difference being the algorithm used to align the genomes.2–4

Through calculating the ANI between genomes in a number of systems, some loose and general ANI breakpoints have been documented:

  • < 96% ANI   = Same 16S cluster (using standard 97% clustering)5
  • > 96% ANI   = Same bacterial species4
  • > 98% ANI   = Same E. coli clade6
  • > 98.8% ANI = Same Prochlorococcus clade7
  • > 99.9% ANI = Same K. pneumoniae outbreak strain8

At which ANI threshold it becomes appropriate to call genomes the “same” depends on the research question. If the question is whether the microbes in an office in Flagstaff are the same as those in an office in San Diego, two microbes of the same species should probably be considered the “same,” and thus an ANI of 95% (or 16S sequencing) would adequately address the question (and it did; Chase, 20169). If the question is whether microbes in two different body sites came from the same source, 95% ANI is too low. Just because E. coli is on two body sites doesn’t mean they came from the same place; one strain could have come from the soil and the other strain from the neighbor next door. An ANI above 95% is definitely needed to show both strains come from the same source, but how high of an ANI is needed is another question (99.9% ANI was used to address this in a recent publication; Olm, 201610).

When picking an ANI threshold for a specific question it is often helpful to visualize the relationship between the genomes. dRep, a python program recently published on bioRxiv11, was written to do just that. For example:


The figure above shows the ANI between strains of Streptomyces inhabiting different babies in the same NICU in Pittsburgh. From the figure, you can see that the ANI between conN3_174_037G1_concoct_13 and conN1_023_029G1_concoct_18 is about 99.25, the ANI between conN3_174_023G1_concoct_19 and conN3_174_021G1_concoct_4 is about 100, and so on. The figure also makes it clear that different ANI thresholds will result in different conclusions about which babies have the “same” strains. For example, calling genomes the “same” if their ANI is >= 98.5% (as shown at the dotted black line) will result in the conclusion that there is only one single strain of Streptomyces that all babies share. Calling genomes the “same” if their ANI is >= 99.5% (as shown at the dotted red line) will result in the conclusions that there are 5 different strains of Streptomyces, two of which (conN3_174_037G1_concoct_13 and conN1_023_029G1_concoct_18) are only in one infant. In this example changing the ANI threshold by a single percentage point completely altered the conclusions drawn from the data, highlighting the importance of selecting a threshold carefully.

dRep, the program used to compute the ANI and generate the above figure, was recently published on bioRxiv.11 Documentation is available on ReadTheDocs, and the source code is available on GitHub. dRep cannot tell you which ANI threshold is appropriate for your specific application, but it can produce figures like the one shown above to help guide the decision.


1. Konstantinidis, K. T., Ramette, A. & Tiedje, J. M. The bacterial species definition in the genomic era. Philos. Trans. R. Soc. B Biol. Sci. 361, 1929–1940 (2006).

2. Goris, J. et al. DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int. J. Syst. Evol. Microbiol. 57, 81–91 (2007).

3. Richter, M. & Rosselló-Móra, R. Shifting the genomic gold standard for the prokaryotic species definition. Proc. Natl. Acad. Sci. 106, 19126–19131 (2009).

4. Varghese, N. J. et al. Microbial species delineation using whole genome sequences. Nucleic Acids Res. 43, 6761–6771 (2015).

5. Kim, M., Oh, H.-S., Park, S.-C. & Chun, J. Towards a taxonomic coherence between average nucleotide identity and 16S rRNA gene sequence similarity for species demarcation of prokaryotes. Int. J. Syst. Evol. Microbiol. 64, 346–351 (2014).

6. Luo, C. et al. Genome sequencing of environmental Escherichia coli expands understanding of the ecology and speciation of the model bacterial species. Proc. Natl. Acad. Sci. 108, 7200–7205 (2011).

7. Kashtan, N. et al. Single-cell genomics reveals hundreds of coexisting subpopulations in wild Prochlorococcus. Science 344, 416–420 (2014).

8. Snitkin, E. S. et al. Tracking a hospital outbreak of carbapenem-resistant Klebsiella pneumoniae with whole-genome sequencing. Sci. Transl. Med. 4, 148ra116–148ra116 (2012).

9. Chase, J. et al. Geography and Location Are the Primary Drivers of Office Microbiome Composition. mSystems 1, (2016).

10. Olm, M. R. et al. Identical bacterial populations colonize premature infant gut, skin, and oral microbiomes and exhibit different in situ growth rates. Genome Res. gr-213256 (2017).

11. Olm, M. R., Brown, C. T., Brooks, B. & Banfield, J. F. dRep: A tool for fast and accurate genome de-replication that enables tracking of microbial genotypes and improved genome recovery from metagenomes. bioRxiv (2017). doi:10.1101/108142



Ants as (Possible) Vectors of Bacteria in Hospital Environments

Not really sure what to think about this article:  Ants as Vectors of Bacteria in Hospital Environments. Published in the Journal of Microbiology Research and authored by Bruna Rafaela Machado Oliveira, Luciano Ferreira de Sousa, Raquel Chalá Soares, Thiago César Nascimento, Marcelo Silva Madureira, Jorge Luiz Fortuna.

In a quick scan the science seems reasonable.  They collected ants, cultured microbes from them, screened the microbes for various resistances, and then analyzed the data.  And some of bacteria were identified as closely related to known pathogens

So that is certainly something to be aware of.  I am just not sure what the implications of this finding are.  Fortunately, the authors are at least somewhat cautious in their conclusions

The results show that the ants captured are possibly working as carriers of pathogenic bacteria. Transmission may take place directly, when ants crawl up a patient’s skin, or indirectly, when they run on medical devices. Besides the fact that these ants carry a significant number of clinically important bacteria in hospital settings, another relevant finding was the resistance to selected antimicrobials, which increases the risk of HAIs, especially in ICU inpatients who, in most cases, are immunodepleted.

The great importance of bacteria carried by ants in hospital environments lies in the resistance to antimicrobials they develop, highlighting the need for increased awareness in healthcare organizations as to the adoption of strict prevention measures. Such initiatives may be as simple as washing hands properly and as complex as devising sensible courses of antimicrobials to inpatients or conceiving efficient pest control programmes.

Despite the confirmation that ants carry microorganisms, our results have not afforded to clarify the precise role these insects have in HAIs. Further studies should be conducted to assess the risk of infection in hospital settings potentially colonized by ants.

So – don’t go out to kill at the ants everywhere based on this article.  But certainly it is worth keeping in mind that organisms other than humans may be involved in spreading microbes around in a hospital environment.


Worth a look: Special issue of @NYASAnnals on “Antimicrobial Therapeutics Reviews” 

Figure 2 from Guthrie and Gardy 2016.


There is a whole issue of the Annals of the NY Academy of Sciences that may be of interest.  The focus of the issue is on Antimicrobial Therapeutics Reviews.

Some of the papers are freely available.  These are

Definitely worth taking a look.

Nice article by @ibikeforfood on Small Cheese Makers and their microbiology work 

Another quick post here.  There is a really nice article about small cheese makers and their microbiology work in the New York Times by Larissa Zimberoff.

The laboratory at Jasper Hill Farm in Vermont is part of a new effort by American producers to better understand the microbial players in their craft.

Source: Small Cheese Makers Invest in a Stinky Science – The New York Times

The article includes a discussion of work by Rachel Dutton (one of my favorite scientists and people on the planet) and others including Benjamin Wolfe, Panos Lekkas at Jasper Hill Farm, and the Kehler brothers. 

Genomes of eight bacteria from the built environment

We just published an extended genome report from eight bacteria that were sequenced as part of the “Built Environment Reference Genome” (BERG) project. BERG is a microBEnet run effort to increase the number of reference genomes in the Built Environment (BE) by offering free genome sequencing to a number of labs working in the field. The goal of BERG was two-fold; 1) to get more genomes publicly available, and 2) to teach people – as much or as little as they wanted – about the process, and the power and utility of sequencing genomes.

These particular bacteria were isolated during aerosol sampling of bathrooms of residences in the San Francisco Bay area. We paired traditional cultivation techniques with particle sampling for sequence-based community composition analysis.

Collection of airborne bacteria on petri dishes during aerosol sampling (top left), followed by their isolation (top right).

These specific eight isolates, spanning 5 genera, were sequenced because they are commonly identified in the built environment, originating from the dominant sources of indoor bacteria: the outdoor environment, human commensals, and premise plumbing. For instance, we included three species (four isolates) of staphylococci. Coagulase-negative staphylococci (CoNS) are typically benign inhabitants of the human skin and mucous membranes. Mycobacterium iranicum is a newly described species that has been isolated from all over the world and whose clinical significance is still under study. Pseudomonas oryzihabitans, despite its environmental origin, it has been recognized as a potential pathogen in recent years, especially in immunocompromised hosts. Other taxa include a Microbacterium and a Plantibacter.

Transmitted light microscope images of the eight isolates (bar is 5 μm). (A) Microbacterium sp. H83 (B) Mycobacterium iranicum H39 (C) Plantibacter sp. H53 (D) Pseudomonas oryzihabitans H72 (E) Staphylococcus capitis H36 (F) Staphylococcus capitis H65 (G) Staphylococcus cohnii H62 (H) Staphylococcus hominis H69.

We explored the presence of genes associated with factors we thought to be relevant from the BE perspective. For example, the genome annotation of the CoNS revealed several genes associated with the ability to attach to a surface (e.g., putative adhesins), biofilm accumulation, and pro-inflammatory molecules with cytolytic and antimicrobial properties, among others. Additionally, we specifically looked for genes related to triclosan (TCS) resistance, a synthetic antimicrobial agent that is commonly used in a variety of home and personal care products. Although susceptibility to TCS or other antibiotics was not experimentally tested for our isolates, we found many genes associated with efflux pumps predicted to confer resistance to more than one class of antimicrobials (e.g., fluoroquinolones) or to specific antimicrobials (e.g., chloramphenicol). Gene components related to non-specific multidrug efflux pumps as induced by triclosan were found in almost all isolates, while P. oryzihabitans was the only isolate to contain an efflux pump predicted to offer triclosan resistance.

The chemical ecology of microorganisms on indoor surfaces is a component of BIMERC’s ongoing research efforts in the BE. We are studying the chemistry of biological interactions among microorganisms on residential indoor surfaces. The genomes of these eight isolates of bacteria will be valuable tools in our efforts to interpret future metagenomic and transcriptomic datasets, but also to understand these chemical interactions in vitro and to explore the basic microbiology of indoor microbes.




2017 Innovation Lab on Quantitative Approaches to Biomedical Data Science Challenges in our Understanding of the Microbiome

Quick post here sharing an interesting sounding event “2017 Innovation Lab on Quantitative Approaches to Biomedical Data Science Challenges in our Understanding of the Microbiome“.   From the website:


The BD2K Training Coordinating Center is organizing an Innovation Lab to foster new interdisciplinary collaborations among quantitative and biomedical researchers to address data science challenges in our understanding of the microbiome. The scope of microbiome, as defined here, broadly describes the corresponding high-dimensional big data derived from microbiota associated with a health or biomedical research objective. A more detailed description of the Lab can be found in the document Detailed information on 2017 Innovation Lab. Some exemplar areas of quantitative interest are suggested in the document Quantitative Topics of Expertise Needed and biomedical interest are suggested in the document Biomedical Topics of Expertise Needed.

The Innovation Lab process entails participation in an intensive five-day residential workshop in order to facilitate the development of new teams of early-career biomedical and quantitative investigators who generate multidisciplinary cooperative research programs through a real-time and iterative mentoring process. The concept of the Innovation Lab program is to organize intensive multidisciplinary interactions involving around 30 participants, with the aim of developing new and bold approaches to address grand challenge questions for topics that could benefit from a fresh or divergent perspective. Prior knowledge of research at this interface is not required; rather, applicants with either quantitative or biomedical expertise who demonstrate their willingness to engage in collaborative multidisciplinary research are sought. Teams are highly encouraged to develop proposals for submission to the funding agencies after the conclusion of the workshop. Professional facilitators and senior scientists (mentors) with relevant expertise and exposure to the topic area assist the participants. The scientific experts serve as mentors and act as impartial referees during the process. Working under the guidance of the mentors, participants will form teams during the workshop to develop interdisciplinary projects to solve a data science challenge arising from a biomedical research question involving the microbiome.

The lab will include opportunities for learning about NIH and NSF funding through interaction with program officers.

Application Procedure:

Applications accepted Starting February 1, 2017
11:59PM, Eastern Time, Sunday, March 12, 2017

Applications will be considered from researchers in quantitative disciplines (mathematics, statistics, computer science, engineering, as well as other data-intensive areas including but not limited to finance, physics, climate modeling, and astronomy) and biomedical disciplines (including but not limited to biological, behavioral, social, environmental, and clinical domains). Researchers coming from a broad diversity of quantitative and biomedical backgrounds are encouraged to apply. Researchers in the biomedical domain must demonstrate their experience working with microbiome big data (e.g. data from sources including but not limited to whole or metagenomics analyses, transcriptomics, metabolomics, or other big data approaches involving microbial communities from human and/or other environmental niches with a health or biomedical research implication). A committee will select approximately 30 applicants to take part in the Lab. Selected participants will have their travel and hotel expenses fully covered by BD2K TCC. Applicants must be willing to commit to stay for the entire Innovation Lab.