Environmental Science: Processes & Impacts blog

Algae are identified in variety of research fields and used as indicators of water quality.  Quantifying and identifying algae is often a laborious task and requires a high level of skill.  Although there are several automated techniques now available, commercial developments have been limited.  Several software techniques based on imaging have been previously presented, however they’re often limited to only a few algal types, so not applicable to field samples. 

This paper presents an innovative method which provides real time recognition of multiple algaes.  The software uses image segmentation, shape features i.e. contours, centroid spectrum calculations and pigmentation.  The set up uses relatively simple hardware and no sample processing or fixation.  Coltelli et al tested the method on both cultured strains and field samples with the method correctly identifing 96.6% of 24 different algal phyla from 3423 images.

This article would be of interest to anyone involved in algal identification, whether from lab based cultures or water samples from the field. 

Automatic and real time recognition of microalgae by means of pigment and shape
Primo Coltelli, Laura Barsanti, Evangelista, Anna Maria Frassanito, Vincenzo Passarelli and Paolo Gualtieri
DOI: 10.1039/C3EM00160A

Biovolatilisation: a poorly studied pathway of the arsenic biogeochemical cycle
Adrien Mestrot, Britta Planer-Friedrich and Jörg Feldmann
DOI: 10.1039/C3EM00105A

Is meconium useful to predict fetal exposure to organochlorines and hydroxylated PCBs?
Anna Sofía Veyhe, Therese Haugdahl Nøst, Torkjel M. Sandanger, Solrunn Hansen, Jon Øyvind Odland and Evert Nieboer
DOI: 10.1039/C3EM00132F

Using quantitative structural property relationships, chemical fate models, and the chemical partitioning space to investigate the potential for long range transport and bioaccumulation of complex halogenated chemical mixtures
Anya Gawor and Frank Wania
DOI: 10.1039/C3EM00098B

Continuous, short-interval redox data loggers: verification and setup considerations
C. Shoemaker, R. Kröger, B. Reese and S. C. Pierce
DOI: 10.1039/C3EM00036B

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Fungal antigens, e.g. from damp homes, have been linked to a variety of illnesses and allergies.  Traditional techniques of identifying them, such as culture based-methods or microscopy, have several drawbacks including not being able to identify fungal fragments and limitations in species classification.  Currently available commercial monoclonal antibody-based ELISAs are avilable, however they have not been as successful in fungal identification as they have been in other common indoor allergens.   

This paper describes the development and validation of an enzyme sandwich ELISA designed to quantify A. versicolor antigens using polyclonal antibodies.  Samples from infected homes were collected and tested using the newly developed assay and the results were compared to the commercially available ELISA, colony forming units and fungi cultivations.

Proteins from A. versicolor spores and myecelia were extracted and subcutaneously injected into a rabbit.  The antibodies produced were then isolated and coated on to the plates to produce the immunoassays.   Positive and negative controls were run as well as the environmental samples. 

In brief the assay proved to be very sensitive (range = 0.12–4.5 ng mL^-1) and precise with intra-assay coefficient of variation (CV) = 4% and inter-assay CV = 11%.  Cross reactivity with other moulds was observed, although at intensities significantly lower than A. versicolor.  The assay also appeared to be more successful in environmental analysis than the commercial assay, showing a positive result for 88% of dust and 89% of bulk samples, with the commercial AveX ELISA only indicating positive results for 27% and 24% respectively.  This may be partly attributed to all the A. versicolor samples cultured showing A. versicolor antigens, whereas only 12 contained identifiable AveX antigens.  A wide range of proteins were shown to be identifiable by the polycolonal A. versicolor antibodies, although not smaller proteins (20–6 KDa) from the myecelia.

This immunoassay has been demonstrated to be effective in environmental studies and could prove to be a significant technique for those identifying and quantifying fungal infestations.  

This HOT article would be of interest to anyone involved in fungal identification or the development of immunoassays.  You can access it from the website for free for the next couple of weeks*!