The Bowman Lab

I’m continuing the theme of cost-saving lab tricks (see this post on the topic).  Over the summer my laptop died on me.  While putting everything back together I couldn’t find my key for the commercial synchronization software (Allway Sync) that I’d been using to backup my computer.  I could have migrated to the provided backup software in Windows 7 (or Timemachine, if I had a mac’nbook), but for some reason I have a strong mistrust of these programs.  It may be that I’m not an experienced enough user, but I want my backup files to be a human-navigable copy of my hard drive.  This way if my laptop is lost or suddenly fails I can plug the drive into any computer and instantly access what I need.  If my laptop fails as a result of a virus it also allows me to manually rebuild the system, hopefully avoiding a re-infection.

To avoid repurchasing third party synchronization software I decided to look for a solution that relies on windows commands.  After a little searching I discovered the windows command robocopy which, when the right options are selected, does the trick (the linux/unix/os command cp should work for those systems, though I haven’t dialed in the options yet).  My laptop has two hard drives, so I run robocopy for each as such:

ROBOCOPY C:\ F:\C_backup\ /zb /xo /E /Z /V /R:2 /W:0 /MIR /tee

ROBOCOPY E:\ F:\E_backup\ /zb /xo /E /Z /V /R:2 /W:0 /MIR /tee

The backup drive, one in my office and one at home, is always F.  The command is telling the system to write everything on C (and E) to a specified directory on F.  The zb option enables “backup mode” (if access is denied a read-only copy of the file is created), xo insures that only new or modified files are copied, E copies all subfolders, Z allows a restart if the connection is lost, V enables verbose mode (so you can see what is being copied), R:2 means that two attempts will be made to copy a file, if it cannot be accessed on the first attempt, w:0 indicates that the system should wait 0 seconds for the second try, MIR removes deleted files from the backup drive, and tee directs the log output to the screen.

To make the two commands easier to execute I wrote them into a batch file.  A batch file (analogous to a shell script in the unix family of operating systems) is a text file with the extension .bat.  You can create this in notepad or the text editor of your choice, and no header (such as the #!/bin/bash for bash shell scripts) is required.  Double clicking on the .bat file instantly executes the commands in it, in the order that they appear.

This worked well for a while.  Backup.bat lived on my desktop and I’d execute it whenever I felt the need to backup (typically daily, once at office and once at home).  Robocopy is fast and not very resource intensive allowing me to continue working while it ran.  However after a bit I decided I wanted to house the file in my Start menu for easier access.  I struggled with this before learning that the Start menu really doesn’t want to host a .bat file.  Fortunately there’s an easy solution – convert the .bat to a .exe.  There are a few free converters out there, I used this one.  My new backup.exe is recognized by the Start menu and allows me to quickly, freely, and transparently backup my system whenever I want.

NOTES ON TIME: When robocopy is run for the first time it takes a while, at least overnight for the average hard drive.  Subsequent backups on my system (two hard drives totally ~ 700 gb) takes ~2 hours, depending on the number of changes, the number of files in the source directory tree, and the size of the tree.  The process can be stopped just by closing the terminal window that pops up during execution, with no ill-effects.

Many thanks to Robert Krulwich, co host of NPR’s RadioLab, for a great article on frost flowers.  Reading through the comments I can see that there is a lot of public interest in this phenomenon.  I want to take the opportunity to clarify a couple of details that Robert didn’t have the time to go into in his article.

One comment to the article notes that frost flowers probably melt to 1-2 mililiters, not milimeters.  Mililiters is correct… the average frost flower is 2-4 cm tall and has a similar diameter.  They are mostly air however, and melt to a much smaller volume.  If you want to know more about the geometry of frost flowers check out these two papers:

Frost flower surface area and chemistry as a function of salinity and temperature

Specific surface area, density, and microstructure of frost flowers

There were a number of comments on the blog regarding how salt gets into frost flowers.  Frost flowers can be so salty that they are bitter to taste (like bitterns at a solar salt harvesting pond).  This seems counter-intuitive, frost flowers are derived from atmospheric moisture that has gone through a distillation process via evaporation at the ice surface (one comment noted that a small amount of salt can evaporate with the water vapor, this is true, but accounts only for a very small quantity).  The salt comes from the surface of newly formed sea ice, which is very salty due to the process of brine rejection during ice formation.

This brine at the ice surface is wicked upwards into the frost flowers by capillary action, as one reader correctly guessed (or at least this is our best understanding at the moment).  This process stops when all the available brine has been used up, or the frost flower melts under its own over-accumulation of salt (often as the day warms slightly) destroying the capillary flow.  Here’s a very brief video created from a slide in a presentation I made a while back that illustrates this:

One reader of the blog raised a very important issue regarding all this salt.  Its presence in the frost flowers (as in all sea ice) means that these structure are not solid.  Unless it is extremely cold (-54 C for sea ice) all saline ice is a porous matrix containing liquid brine and interspaced among solid, almost entirely salt-free crystals.  The more salt, the larger the volume of brine in the matrix.  This is what makes sea ice so interesting as an ecosystem, all that liquid brine at even very cold temperatures offers a habitat for a diverse array of microscopic life.  The following images of Arctic winter time sea ice (from Krembs et al. 2002) illustrate this occupation of sea ice pore spaces by microbial life.

I have an experiment that I want to do that involves growing bacteria in relatively large volumes (around 10 L) in a cold room for several weeks.  Typically in this sort of experiment you stir the cultures with a magnetic stir bar.  This keeps the oxygen level up and prevents the bacteria from falling out on the bottom of the vessel or adhering to the sides.  Unfortunately this is an unfunded side project and it is prohibitively expensive to purchase the nine commercial stir plates I would need to do this (at $300 a piece).  I decided to try to  build a stir plate alternative.

Electric motors and magnets are cheap, so I thought that I could epoxy a couple of circular rare Earth magnets to an electric motor and be done with it.  This creates a spinning magnet well enough, but the speed of the motor is way too fast for a stir bar in a culture vessel to keep up.  The speed can be reduced by dropping the voltage, but there are practical limitations to this if you want the motor to spin at 60-100 rpm (something like 0.6 % of what the motor was designed for, which would necessitate a ridiculously small voltage).

It turns out that there is an easier way to control the speed of the motor, using something called pulse-width modulation.  A pulse-width modulator outputs “pulses” of the input voltage.  The longer the pulse, the higher the average voltage received by the motor, and the faster the motor spins.  Here’s an image from the robotics site micromouse that illustrates the process.

I searched high and low for an off-the-shelf pulse width modulator and couldn’t find one.  Fortunately there are two relatively straightforward ways to build one.  The elegant way uses a microcontroller and requires programming a simple piece of firmware (necessitating some knowledge of C).  This seemed a little advanced for a first attempt, but good instructions can be found here (I think the LED light example would transfer to this application without modification).  I opted for the uglier analogue circuit method using a kit made by Velleman (DC to Pulse Width Modulator K8004), available online from Radioshack (but not in stores).

I have very little experience with soldering, but after a couple of false starts and some guidance from YouTube things went pretty quick.  Total assembly time on the kit was around 4 hours.  I could probably do it again in less than half the time.  Here’s what the assembled board looks like wired into a power source (I used a 19V drill battery) and my electric motor with magnet  (I won’t show you the backside with my ugly soldering effort).  I had very little hope that it would actually work as described, but was pleasantly surprised!Here’s the whole prototype, spinning a beaker of water at low speed.  The speed controls are pretty twitchy, but manageable.  What I’ll try to do next is connect a series of nine electric motors (with magnets) to the single PWM, built into a wood frame sturdy enough to support the incubation vessels.  Should be pretty straightforward and I think the increased resistance on the circuit will make speed control even easier.

Final cost for the project?  Kit = $30 (x 1), Motor = $3 (x 9), Magnet = $3 (x 18), all together = $111.  That’s a significant savings over the $3K the commercial version would have cost…

Well, at least on another blog.  Thanks to Dr. Kim Martini, a physical oceanographer at the University of Alaska at Fairbanks, for including linked photos from this blog in an article on frost flowers for Deep Sea News.  Dr. Martini’s article can be viewed here:

http://deepseanews.com/2012/11/the-icy-plumage-of-the-arctic/?utm_source=dlvr.it&utm_medium=twitter

Dr. Martini’s article isn’t the only place where frost flowers have appeared in print recently.  Writing in the journal Polar Biology, Aslam and co-authors recently reported the results of what must have been a very challenging study of frost flowers grown in a laboratory tank – a much larger and more natural experimental setup than our early laboratory studies.  The Aslam study was particularly interesting in that natural seawater was used for the experiments, trucked to the lab in Germany in a food-grade commercial tanker from the North Sea.  The North Sea is far from being a polar sea, but the hope is that this water is similar enough to polar seawater to provide insight into how organic compounds in seawater are distributed in newly formed sea ice.

Frost flowers growing on the surface of laboratory sea ice, from Aslam et al. 2012.

In agreement with our findings for laboratory and natural frost flowers Aslam and colleagues found that organic material and bacterial cells are concentrated near the surface of newly formed sea ice, in liquid brines and in frost flowers.

What we still don’t know is what, if anything, all these bacteria and organic compounds at the ice surface are doing.  Microbial metabolism decreases with decreasing temperature, and it is very cold at the surface of young sea ice, but not cold enough to make microbial activity here impossible.  And all that organic material at the ice surface can actually help bacteria survive there, by protecting them from high salt and freezing conditions.

The high concentration of organics also help overcome the poor efficiency of bacterial enzymes at low temperature.  The more organic substrate an enzyme has to interact with the less it needs to function efficiently to still get the job done.  Imagine that you’ve spilled m&ms all over your kitchen table and are trying to eat them as quick as you can.  Your fingers are very cold (you are trying to save on your heating bill) and you don’t have your normal dexterity.  The more m&ms on the table the more likely it is you will find ones that you can actually pick up.  Now fill your kitchen with saltwater the salinity of the Dead Sea, add a UV lamp bright enough to give you a sunburn, and repeat the experiment.  You are now experiencing the life of a marine bacterium at the surface of newly formed sea ice.

***UPDATE***

I was recently introduced to a great tool for working with phylogenetic trees that can do something similar to what I describe below (and a whole lot more).  Check it out at http://itol.embl.de/.

******

It seemed like a simple enough task at the time.  I have several sets of classified 16S 454 reads from which I’ve tallied the number of members for some genera of interest.  Id like a heatmap showing the abundance of these genera, with a phylogram showing the relationship between genera (rows).  Since the heatmap and heatmap.2 (package gplots) commands in R both support row ordering by dendrograms I thought this would be easy.

The first step was to find a single representative sequence for each of 134 genera that I want in the heatmap.  I used sequences from the RDP for this.  I aligned and trimmed these sequences using standard methods in mothur (my favorite 16S analysis program) That’s the easy bit.

Attempt 1 – A dendrogram should never be confused with a phylogenetic tree.  Despite knowing this I thought I could approximate a phylogenetic tree by building a distance matrix outside of R (in clustalo) and performing the clustering inside R (using hclust).  The result was a nice looking dendrogram that had clear flaws in illustrating evolutionary relationships.  This basic method may actually work, but for reasons that will become clear it didn’t in this case.

Attempt 2 – I decided to build a tree in fasttree (superb tree building program) and then, somehow, get the tree into R and trick R into thinking that it was a dendrogram.  Using package ape this is pretty easy.  Ape even has a method for converting the tree to a dendrogram.  The problem is that the tree must be rooted, bifurcating, and ultrametric (each tip equidistant from the root).  This took a substantial bit of tweaking but I was able to get it:

##### create tree as dendrogram for row order #####

library(ape)

rep_tree <- read.tree(‘../known_degrader_rep.tre’)

#For the root I selected the node between the two Archaea and Planctomyces

rep_tree_r <- root(rep_tree,
                   resolve.root = T,
                   interactive = T
                   )

#can’t have any branch lengths of zero or downstream commands will collapse those nodes…

rep_tree_r$edge.length[which(rep_tree_r$edge.length == 0)] <- 0.00001

rep_tree_um <- chronopl(rep_tree_r,
                        lambda = 0.1,
                        tol = 0)

rep_tree_d <- as.dendrogram(as.hclust.phylo(rep_tree_um))

plot(rep_tree_d)

Great!  When I created the heatmap however, I found that there is a major hitch in this method – and any other method that performs clustering separate from heatmap creation.  The heatmap and heatmap.2 commands don’t match up the rows and dendrogram tips by name (in my case by genera), but by the index of the the data as it was first imported into R.  Since I imported my tree and the abundance table separately each genus was assigned a different index.  Using the root() command prior to converting my tree to a dendrogram made it difficult to reconcile the two, because the index values of the dendrogram were no longer in order.  Reordering my abundance matrix so that it matched the index values, but not their current order, took a bit of thought.  Here’s the code I came up with, I’m sure there is a cleaner way…

#force row order so that it matches the order of leafs in rep_tree_d

clade_order <- order.dendrogram(rep_tree_d)

clade_name <- labels(rep_tree_d)

clade_position <- data.frame(clade_name,
                        clade_order
                        )

clade_position <- clade_position[order(clade_position$clade_order),]

new_order <- match(clade_position$clade_name,
                   row.names(combined_matrix)
                   )

combined_ordered_matrix <- combined_matrix[new_order,]

And that seems to work nicely – combined_ordered_matrix is in the same order as the dendrogram INDEX (not the dendrogram leaves).  When the heatmap is constructed the accompanying phylogeny looks fine.  Note that in the following code I’ve switched all zeros to NAs to differentiate between an abundance of 0 and a low abundance:

##### Generate heatmap #####

library(RColorBrewer)
library(colorRamps)

color <- colorRampPalette(c(‘white’,’blue’,’red’))(100)

row_col_table <- read.table(‘../genera_row_colors.txt’,
                            as.is = T)
row_col <- row_col_table$V1

combined_ordered_matrix[which(combined_ordered_matrix == 0)] <- NA

library(gplots)
heatmap.2(combined_ordered_matrix,  
          margins=c(7,10),
          sepcolor=”white”,
          sepwidth=c(0.01,0.01),
          Rowv = rep_tree_d,
          Colv = F,
          dendrogram=’row’,
          colsep=seq(1,10,1),
          rowsep=seq(1,134,1),
          key = TRUE,
          trace=’none’,
          col=color,
          lwid = c(2,5,5,10),
          lhei = c(1,50),
          cexCol = 0.7,
          cexRow = 0.7,
          RowSideColors = row_col,
          density.info=c(‘none’),
          scale = ‘none’,
          na.color = ‘yellow’
          )

If you run this code you’ll notice that the margins don’t allow the key to show.  Still have to fix that.  Here’s the resulting heatmap and phylogeny with 0 values as yellow and the remaining relative abundances on a white-blue-red scale.

This blog was originally intended to share the experiences of our group while we conducted field work in Antarctica during the Austral winter/spring of 2011.  The further I get into analysis however, the more I find myself needing a place to document progress and solutions to problems.  I’ve been using a more “raw” space accessed via the Research Wiki link in the header of this page for this, but will now start using this blog space for more polished ideas and solutions.

A major motivation for doing this is to make my solutions and ideas accessible to others who might be doing similar work.  Almost every day I rely on someone’s blog or forum post to overcome an analytical problem.

For those who followed the Antarctica Blog (thank you!) the format will be a little different.  I envision that the posts will be shorter and more technical, however I’ll try to keep it entertaining and informative.  Due to an excessive number of spam comment posts I’ve disabled new subscriptions, however I might change this in the future.