Reviewer Comments - EERE

2011 Algae Platform Review – Reviewer Comments
Reviewer Comments are direct transcripts of commentary and material provided by the Platform’s
Review Panel. They have not been edited or altered by the Biomass Program.
Reviewer: 6 Criteria Score: 5
It is relevent but does it duplicate ongoing work in other organizations and why is the DOE funding toxin
work?
Reviewer: 7 Criteria Score: 4
A conceptual risk survey is important, but trying to measure and mitigate risks does not appear to be
possible at the current state of technology development.
Presenter Response
The comments above do not apply to novel toxins or to “novel toxin generation’ by previously ‘benign’
species. I (Moeller) have worked in the HAB arena for over 20 years and I can assure you that there is
little to no literature out there on toxins people simply do not know about. To apply current understanding
of STX, PbTX, DA and/or microcystin to these systems is untenable. These projects require new
approaches, must develop new detection and monitoring tools and just as importantly, but be reassessed
routinely for even more “novel toxin generation”.
We are attempting to obtain algae samples from a cross-cutting representation of current growers, not just
DOE-funded projects.
All other DOE projects investigating “pathogens” are concerned with algal pathogens (i.e. algal viruses,
rotifers, etc.), not human pathogens. In light of the significant investments that DOE is making in algal
biofuels R&D and commercialization, it is imperative for DOE to take a proactive approach to understand
the risks. This includes the safety of products and co-products to consumers, as well as occupational
hazards. If no early action is performed, responses after the fact are likely to be expensive and reflect
negatively on the biofuel production community. We agree that risks associated with the application of
pesticides/herbicides to algal growth systems should be assessed, but are beyond the scope of this project.
We have spent considerable time determining which pathogens may be prevalent in different water
sources and in different areas. The list shown at the program review was simply a “working list”;
different species/genes will be targeted depending on the sample source. We are adapting pre-existing
PCR methods into a PCR array to enumerate pathogens and toxin genes in algae samples. We plan to
collaborate with Todd Lane, Sandia (also funded through this program) to perform deep sequence
analysis on select samples. Between the team’s collective experience and an exhaustive literature search
we have already conducted the “desk study”. The end result of that exercise convinced us that the
potential for a human health risk is present in algae ponds. The initial scoping study (Phase I) is designed
to provide the baseline data necessary to begin to carry out experiments (Phase II and Phase III) to
characterize those risks. This exploratory project aims to fill in some of the baseline information needed
to enable any level of risk assessment. It is our hope that the information gleaned from this project can be
used by professionals from other agencies (EPA, CDC, NOAA, etc.) to perform a proper risk assessment
(if warranted). Most of the toxin work will be performed at NOAA; however, this project does not an
overlap with existing HAB research. An algal production pond and natural waters are VERY different
systems. Nor does it overlap with work performed by the CDC. If we find strong evidence for the
sustained presence of a human pathogen in any of the production system samples, we plan to contact the
CDC and offer sample material for further analysis. One of the PIs (Zimba) has extensive experience
working with the aquaculture industry and views this project as extremely relevant and unique. During
the course of this project, we intend to collaborate closely with at least one algae production system using
wastewater (we are currently talking with Patrick Hatcher, also funded through this program, of Old
Dominion University). We can certainly learn much and apply existing data, techniques, etc. from the
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