Open Source Building Science Sensors

This is just a quick post to introduce some early work products resulting from a really exciting project my team has been working on: the Open Source Building Science Sensors (OSBSS) Project (funded by the Sloan Foundation). The goal of OSBSS is to to design and develop a network of inexpensive, open source devices based on the Arduino platform for measuring and recording long-term indoor environmental and building operational data, particularly those parameters that can influence microbial communities in buildings. The development, calibration, and performance of the sensor network is being documented in its entirety and made available freely online (www.osbss.com) along with detailed tutorials allowing others to incorporate in both ongoing and future projects.

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The motivation for this work is described in a recently published paper reviewing and prescribing tools to improve built environment data collection indoor microbial ecology investigations (blog coverage here), as well as a workshop report intended to better integrate building science with microbial ecology. We essentially make the case that most investigations into the microbiology of the built environment should also be include long-term measurements of a number of influential indoor environmental and building operational characteristics with high spatial and temporal resolution. Because the cost of building environmental sensors can escalate quickly depending on quantity and desired accuracy, we launched OSBSS to attempt to allow for more flexibility in synchronizing a large number of measurements with high spatial and temporal resolution in a more cost effective manner for use in future research projects.

It’s been an exciting project and I’m happy to report that our team — led by master’s student Akram Ali with lots of help from PhD student Torkan Fazli and undergraduate students Zack Zanzinger, Deion Debose, Boyang “Bobo” Dong, and Joseph Chee Poh Huan — has recently developed a really robust, low power draw, long battery life, easy to use, and accurate data logging platform assembled from a variety of off the shelf parts. The device can be built entirely from parts purchased online and with a little bit of soldering skills, you can make your own data logger with relative ease (even I’ve made one!).

So far we have an excellent temperature and relative humidity sensor tutorial fully developed and available online. You can also read about my own experience building my own sensor and testing against off the shelf equipment. Now that we have a great stable platform for data logging, we are rapidly producing prototypes and tutorials for several other sensors, including surface temperatures, equilibrium relative humidity of surfaces, a CO2 injection, decay and sensor system for ventilation rate measurements, human occupancy, and HVAC system flow and on/off sensors. Stay tuned in the next few months as we publish more of these tutorials!

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Comparing the new 16S rRNA V4 and ITS primers to the old primers-RESULTS!

The Knight lab has been working hard testing new primers for 16S rRNA amplicon production and its time to share our progress.

So far, the 16S rRNA V4 region forward primer (designated 515f) has been paired with five different reverse primers (806r, 926r, 967r, 1048r, and 1391r) to amplify ribosomal RNA from bacteria, Archaea, and Fungi.  Thanks to Jed Fuhrman and Amy Apprill, the 515f and 806r primers have also been modified, helping minimize the amplification bias against Crenarchaeota/Thaumarchaeota (515f) and SAR 11 (806r).  All primer pairs have successfully yielded PCR amplicons, and the amplicons from the 515f/806r and 515f/926r constructs sequenced.  The remaining primer pair constructs will be sequenced soon with an update to follow once we have the results.

The differences between the old and new 515f nd 806r constructs are described below:

Original 515f construct / modified construct (Jed Fuhrman, C to Y base change on the 5’ end)

5′-GTGCCAGCMGCCGCGGTAA-3′ / 5′-GTGYCAGCMGCCGCGGTAA-3′

Original 806r construct / modified construct (806rB, Amy Apprill, H to N base change mid-primer):

5′-GGACTACHVGGGTWTCTAAT-3′ / 5’-GGACTACNVGGGTWTCTAAT-3’

Why the new constructs, you ask?  And what does the added degeneracy mean?

  1. The barcodes, which were previously located on the reverse primer, are now located on the forward (515) primer.  This enables the user to pair the forward primer with various reverse primer constructs to enable longer amplicons.  We’ve tested the barcoded 515f primer with 806r and 926r.  Importantly, the barcoded constructs were screened in silico for secondary structure against a number of longer constructs (967r, 1048r, 1391r).  We have tested the performance of these constructs in PCR but have not validated the results on the MiSeq or HiSeq platforms.
  2. The degeneracy was added to the forward and reverse primers to minimize the bias against Crenarchaeota/Thaumarchaeota (515f modification) and the marine and freshwater alphaproteobacterial clade SAR11 (806r modification)

To compare the new primer constructs to the old ones and thus confirm the performance of the new constructs, we sequenced amplicons produced from both constructs applied to a number of studies.  Our intent was to sample a wide range of sample types to confirm that the new primer constructs produce data comparable to that obtained using the old constructs on a variety of sample types.  The studies/sample types that the constructs were tested on are:

-5 American Gut fecal samples

-5 American Gut skin Samples

-5 Body farm control Soil samples

-6 Body farm paired skin/soil samples

-33 Sloan house samples (various sites)

-15 Mouse decomposition control soils

-9 Rice Rhizome samples

-12 Agricultural soil samples

Below is a procrustes plot (using the unweighted UniFrac distance matrix on the left and the weighted UniFrac distance matrix to take into account taxa abundances on the right) comparing samples amplified using the original primer construct and the new, modified primer construct.  The calculated M2 value for the unweighted UniFrac based plot is 0.111 and for the weighted UniFrac based plot is 0.196.  With the exception of a few mouse decomposition and built environment samples, each sample produces extremely comparable results between the old and new primer constructs.  Importantly, very commonly studied sample types (stool, soil, skin) perform very well under the new constructs.


 

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What exactly is that sequencing data?

The idea for GenomePeek began two years ago when I was working with Karl Klose, Liz Dinsdale, and Rob Edwards to assemble a P. salmonis genome that was being particularly difficult, even though we had 9 gigabases of sequencing.   To check whether it was a single isolated genome I pulled out all the 16S reads that hit to 16S and then assembled them. All of the assembled contigs hit to P. salmonis, it was only until later that I found that genome had been shredded by an overactive transposon. We still haven’t solved that problem ….

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Looks like someone did not do a complete bacterial isolation.

GenomePeek lay dormant for a year, until a student from SDSU’s bacterial sequencing class came looking for help. In the class the students were isolating a bacterium, sequencing, assembling, and then analyzing it.   The student wanted to create a recA phylogeny and was having trouble with taxonomic assignment.   Their question was: “which RecA gene do I use?”.   This set off a red flag immediately, since RecA is essentially a single copy housekeeping gene.   On inspection, their assembled genome did indeed have two full copies of RecA; one that hit to a Vibrio and one that hit to a Photobacterium.   At the time the two 16S rRNA genes hit to Vibrio, although they were clearly different from each other and hit to different species (since then a representative Photobacterium 16S sequence has been added to the NCBI 16S database that is now the top hit). It turned out that this bacterium also had two sets of other single copy housekeeping genes (I checked rpoB, groEL, nifD, gyrB, and fusA). One of each gene hit to a Vibrio species while the other was most similar to a Photobacterium species. Suffice to say the student was very disappointed after spending a few weeks analyzing and writing up a paper.   The idea occurred for a tool where one could submit sequencing data and then quickly get back a set of useful housekeeping genes for phylogenetic analysis. I thought this tool would save everyone’s time wasted on assembly, annotation, and analysis. By quickly checking sequences, we could easily detect whether the original sequencing data was contaminated. I wrote (more…)

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2014 Microbiology of the Built Environment Fellows

The Sloan Foundation has recently announced their 2014 Microbiology of the Built Environment Postdoctoral Fellows.   The awards, along with the titles of the projects are below.  Congrats all!   Look forward to detailed blog posts from all the awardees describing their upcoming projects.

 

Huan Gu at Syracuse, along with Dacheng Ran. “Understanding and controlling biofilms in the built environment

Sarah-Jane Haig at University of Michigan, along with Lutgarde Raskin and John LiPuma “Regulation of the microbial community structures in drinking water, from source to tap

Brian Klein at Forsyth Institute, along with Katherine Lemon “Microbiomes of indoor track facilities and runners who train indoors vs outdoors

Zachery Lewis at UC Davis along with David Mills and Katie Hinde (Harvard) “Role of the built environment as a venue for microbial cross inoculation between infants

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New Paper : On the intrinsic sterility of 3D printing

As a biologist with a 3D printer, one of the questions I get most often about 3D printed parts is, “Can you autoclave these things?” As it turns out, no, not really. There are only a handful of thermoplastics that can survive the autoclave process, and most of them are not very good for 3D printing. With few exceptions, only polypropylene and blends of polypropylene hold up to repeated autoclave cycles, and polypropylene is, unfortunately, very a difficult material to print. It shrinks a lot when it cools, which causes a lot of warping during printing, and it is very difficult to get molten polypropylene to bond strongly to cooler, solid polypropylene.

It turns out that this is all unnecessary. Fused deposition modeling (FDM) 3D printing involves shoving a rod of thermoplastic into a hot nozzle until it melts and squirts out the nozzle. For most popular 3D printing plastics like ABS and PLA, the nozzle temperature is somewhere between 180C and 260C, and the plastic stays at that temperature for around a minute, depending on what the toolpath looks like. It’s actually a lot like Pasteurization, except way overkill. Get it? Overkill?

Anyway, here’s how FDM 3D printing compares to various Pasteurization (in black) and autoclave (in red) protocols :

FDM 3D printing compared to pasteurization (black) and autoclave (red) protocols.

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