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DNA helps answer the origin of infectious diseases: are cases sporadic events or part of larger epidemic, such as the recent Salmonella Montevideo outbreak involving at least 245 persons in 44 states, traced to a single importer of crushed red pepper used in salami manufacturing. In a similar way, DNA helps answer the origin of apparently widespread species–are they part of single outbreak so to speak, or are they multiple independent populations or species. (This suggests useful connections between phylogeography, the genetic study of populations, and molecular epidemiology of disease.)  As with pathogen diagnostics, a minimalist DNA testing approach will help make feasible analyzing large numbers of specimens.

In February 2010 PLoS ONE, six researchers from University of North Carolina report on Odorous house ant Tapinoma sessile (smells like rotten coconuts when crushed), collected from 47 urban and rural localities across the US.  According to the authors, T. sessile is the most common and widely distributed ant in North America, found “from the West coast to the East coast and the deserts nearly all the way to the tundra.” The structure of the 18 colonies examined in detail ranged from a monogynous (single queen) colony in an acorn with 50 workers, to a polygynous colony with 2 queens and 250 workers, to a large, dispersed colony of “several million workers and thousands of queens in and around several buildings on a college campus.”  For DNA analysis, 68 individual were analyzed (1 from each of the 18 colonies, plus 23 collections in natural environments made by entomologists, 26 collections in urban environments mostly provided by pest control professionals, and 1 T. erraticum specimen). Menke and colleagues found 4 distinct genetic groups, corresponding to geographic areas, with 7.5 – 10% COI sequence differences among groups, and relatively small (0.2 – 2.3%) differences within groups, a pattern that “may represent multiple species.” Counter to initial expectations, urban ants were genetically similar or identical to non-urban ants within each region, and colony structure was not associated with urban vs natural environment, namely monogynous and polygynous colonies were found in both environments.

I conclude there is much we don’t know about the commonest, most everyday species, and that DNA barcodes are just the right size for many of the relevant scientific and practical questions. In closing, for a view of complexity of ant life, please see E.O. Wilson’s wonderful short story “Trailhead”, in March 6, 2010, New Yorker, an excerpt from his upcoming book Anthill.

Now that 3rd International Barcode of Life Conference (held in November 2009 in Mexico City with over 350 researchers from 54 countries) is behind us, where to turn for DNA barcode science and organizational news? A bright answer arrived in today’s email: the first issue of the International Barcode of Life (iBOL) Bulletin (download pdf or view online flash version). The 12-page illustrated quarterly iBOL newsletter has a promising diversity of news. To take one example, I learned that some members of the North American Moth Photographers Group (MPG) are submitting their hard-to-identify specimens to Biodiversity Institute of Ontario, thus building up the reference library, and in turn receiving DNA-based identifications! This sort of crowd-sourcing approach to specimen collection could be a big thing for barcoding in particular, and for biodiversity science in general. There are many dedicated, expert, non-professionals who are likely to contribute given the right framework.

In terms of citizen participation, the MPG story suggests expanding opportunities for biological research that harnesses the skill and energy of non-professionals, a step beyond the successful BioBlitz model, which still requires a lot of on-site organization. If North American birders can create a comprehensive, regularly-updated database documenting migration, i.e. eBird (1 1/2 to 2 million sightings submitted monthly), then there must be a large potential for crowd-sourcing specimen collection, at least for certain organisms. After all, the most expensive part of biodiversity science is often collecting and/or documenting specimens. How to encourage and streamline data collection is suggested by Cornell University’s recently-released iPhone app BirdsEye, which displays current local sightings based on eBird database and user’s GPS location, with planned update that will enable birders to instantly update eBird with their own sightings.

The Barcode Bulletin aims to “inform and entertain iBOL collaborators, the global DNA barcoding community and the wider world of biodiversity genomics”; this issue is a promising start.

Herbal products make a compelling case for DNA-based identification–how else to recognize dried bits of roots, leaves, stems, bark, and flowers from a multitude of species? In December 2009 J Nat Med, researchers from Ochanomizu University and Showa Pharmaceutical University, Japan, apply recently agreed-upon standards for DNA barcoding land plants, namely matK and rbcL, to distinguish among Dendrobium species. Dendrobium is a large (about 1200 species) genus of orchids widely distributed through east Asia to Philippines, Australia, and New Zealand.  Over 50 Dendrobium species are used in traditional medicines and are thought to have various pharmacologic activities, although the active ingredient(s) are not yet characterized.

Asahina and colleagues analyzed rbcL and matK from 12 samples representing 5 Dendrobium sp. and 3 hybrid cultivars whose genetic histories are uncertain. Single primer sets successfully amplified matK and rbcL from all specimens. The researchers cloned PCR products (and then sequenced at least 3 clones per species), rather than directly sequencing amplified products (rationale for the cloning step is not given). They found that matK, but not rbcL, distinguished among the five species; this is consistent with general observation that rbcL varies less among closely-related species than does matK. Results were similar when 22 matK Dendrobium sp. sequences from GenBank were added to analysis (bringing species total to 6), with one exception; 1 of 11 D. officinale GenBank matK sequences was unique, and in NJ diagram appeared on branch distant from the other 10. In this modest sampling, there was no intra-specific variation in the original 12 samples; some intra-specific differences were noted in 2 species in comparison with GenBank sequences.

This study demonstrates advantages of DNA barcoding approach for plant identification. Of course, there is already a lot of interest in DNA identification of herbal plants in general and Dendrobium orchids in particular. For example, I found over a dozen articles describing DNA methods for distinguishing Dendrobium sp. However, the methods described are limited to identifying species in this one genus, which means one has to have a pretty good idea what the specimen is before applying DNA testing! This highlights the essential advantage of barcoding–a standardized approach can be applied to any unknown, and makes feasible creation of a comprehensive reference library.

Looking ahead, we want to know more about intra- and inter-specific variation in plants. In animals, the patterning of mitochondrial variation is quite uniform, with intra-specific << inter-specific variation, such that most species form relatively tight clusters distinct from those of other species in NJ diagrams. Results so far in plants generally show little intraspecific variation in chloroplast genes (including rbcL and matK), but a diversity of distances among closely-related species. Assuming these early results are borne out, we then want to know why plants and animals differ? For more genetic variation in plants and animals, see Rieseberg et al Nature 2006, Fazekas et al Mol Ecol Res 2009).

In forensic investigation, insect evidence helps date the time of death, as the various species that colonize corpses exhibit different stages of development according to time and temperature. Determining the post-mortem interval (PMI) rests on accurate species identification, including of immature forms. In Dec 2009 Int J Legal Med researchers from University of Wollongong, Australia, test DNA-based identification of Sarcophagidae flies, which lack distinguishing features as immature forms, and their adult identification requires “meticulous examination of subtle morphological differences, including regional hair presence and colour, body pigmentation and bristle length, placement and abundance”, and even then may need genitalic dissection for confirmation. As a result, sarcophagid flies are little used in forensic study, although being viviparous, they are “prospectively more reliable for PMI estimations compared with other initial dipteran colonisers” [the latter are mostly egg-laying species (e.g. callophorid blowflies), which hatch only if certain environmental conditions are met, adding uncertainty to PMI determinations].

The researchers successfully recovered COI barcodes, without evidence of pseudogenes, from 85 adult specimens representing 16 species, using a single primer pair with degenerate bases previously applied to forensic blowflies (Nelson et al 2007 Med Vet Entomol).  In NJ analysis, 14 of 16 species showed single clusters distinct from other species; the remaining 2 species showed deep divergences which the authors surmise may indicate cryptic species, perhaps more likely given that “taxonomic descriptions of the Australian Sarcophagidae have not been updated since the 1950s”.

Meikeljohn and colleagues demonstrate efficacy of COI barcodes as species-level identifiers for Australian sarcophagids. The tight intra-specific clustering in these flies appears identical to that seen in diverse animal groups including vertebrates, for example, yet flies are presumably several orders of magnitude more abundant. (As an aside, although the authors report their sequences and associated specimen data are deposited in BOLD, their data are not visible in “Public Projects”–I hope the authors will amend this.)  What then limits mitochondrial variation within species? Or in the language of population genetics, why are effective population sizes for animal species uniformly small, unrelated to census population sizes? Like the nature of dark matter, explanation(s) await.

Addendum 11 Feb 2010: Dr. Meikeljohn reports that the sequences and associated data are scheduled to appear in BOLD and NCBI GenBank as soon article appears in print edition.