Automated microbiology

I am not a molecular biologist… I see it all the time, it lives on the other side of the lab where DNA is extracted, amplified, and sequenced; often so that a particular microbe can be identified or detected. So my perception of it is that it is something that is generally done very carefully in a very clean environment. “I think this is contaminated” is something I have heard from that side of the lab. When trying to ID a cultured critter contamination from another coulter could give you a false ID. When trying to detect a critter from say, a water sample contamination from another water sample or a culture can give you a false positive.

These apparently persnickety techniques are extremely useful for doing things like detecting the presence of toxin producing algae. There are a bunch of algae species that produce a range of toxins that in turn have a range of effects on other organisms. Because these algae can have a significant economic and human health impact you really want to keep track of them; you want to know when and where they are most abundant, where they are going and how they got there.

Monitoring is a pain, it is long term and expensive. It often seems more rewarding to do (relatively) cheap experiments that yield lots of data quickly (I definitely take this way out). Using a persnickety technique to monitor toxin producing algae could be a double pain in the ass… if you are doing it all by hand. Bring on the automation.

Here is a project that used automated molecular biology labs to monitor coastal waters for toxic algae in Monterey Bay (Ryan et al 2011). On the same buoy that the molecular “lab” were also instruments for measuring a range of other chemical and physical parameters. They also deployed underwater autonomous vehicles, while the buoys are stationary these roam and gather data (mostly physical, some time chemical) on the water bweteen buoys. So, lots of instruments in the water collecting a ton of data. Oh, and don’t forget the satellites (I am not kidding).

What did they learn from all those measurements? They put it this way:

The molecular analytical and environmental observingnetwork revealed clear relationships between environmentalconditions and HAB species composition in MontereyBay.

So which harmful algal bloom (HAB) forming species was present relied heavily on environmental conditions. Some might of guessed that was the case but the interesting thing is the correlation between toxic diatoms and strong upwelling (surface water is pushed off shore and colder more nutrient rich deep water comes up to replace it) and dinoflagellates and weaker upwelling.

If you can correlate things like wind driven upwelling with toxin producing algal species then you can predict when a bloom might occur and plan appropriately.

The abstract

Using autonomous molecular analytical devices embedded within an ocean observatory, we studied harmful algal bloom (HAB) ecology in the dynamic coastal waters of Monterey Bay, California. During studies in 2007 and 2008, HAB species abundance and toxin concentrations were quantified periodically at two locations by Environmental Sample Processor (ESP) robotic biochemistry systems. Concurrently, environmental variability and processes were characterized by sensors co-located with ESP network nodes, regional ocean moorings, autonomous underwater vehicle surveys, and satellite remote sensing. The two locations differed in their longterm average physical and biological conditions and in their degree of exposure to episodic wind-forced variability. While anomalously weak upwelling and strong stratification during the 2007 study favored toxigenic dinoflagellates (Alexandrium catenella), anomalously strong upwelling during the 2008 study favored toxigenic diatoms (Pseudo-nitzschia spp.). During both studies, raphidophytes (Heterosigma akashiwo) were detected within a similar range of concentrations, and they reached higher abundances at the relatively sheltered, stratified site. During 2008, cellular domoic acid reached higher concentrations and was far more variable at the shallower ESP node, where phytoplankton populations were influenced by resuspended sediments. Episodic variability caused by wind forcing, lateral mixing, internal waves, and subsurface phytoplankton layers influenced ESP detection patterns. The results illustrate the importance of mobilizing HAB detection on autonomous platforms that can intelligently target sample acquisition as a function of environmental conditions and biological patch encounter.

The L&O link (I think this is free access)

The Ref

Ryan, J., D. Greenfield, R. Marin III, C. Preston, B. Roman, S. Jensen, D. Pargett, J. Birch, C. Mikulski, G. Doucette, and others. 2011. Harmful phytoplankton ecology studies using an autonomous molecular analytical and ocean observing network. Limnol. Oceanogr 56: 1255–1272.


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