A new proof-of-concept study by researchers at the University at Albany in New York has developed a mass spectrometry-based technique for the rapid species prediction of blow fly larvae for use in forensic investigations.
Entomological evidence (evidence relating to insects) has proven invaluable to forensic investigations for decades, particularly in the estimation of time since death. Insects which feed on decomposing remains, known as necrophagous insects, will colonise a body in a reasonably predictable pattern, with different insects arriving at different stages throughout the decomposition process. Different species of flies, beetles and mites are commonly encountered. Blow flies in particular will often arrive at the scene within minutes of death to lay eggs on the body. As these eggs hatch, larvae (or maggots) emerge to feed on the decomposing remains. By studying the type and age of insects present at a scene, it may be possible to estimate the time since death, or postmortem interval.
The ability to achieve this hinges on the correct identification of insect species, which is unfortunately not always straightforward. The larvae of different species of blow fly are visually very similar, thus difficult to distinguish by eye. For this reason, maggots are often reared to maturity for species identification, with adult blow flies exhibiting more distinguishing physical differences. Inevitably the rearing of maggots to adulthood is a time-consuming process that requires the expertise of a forensic entomologist.
In recent years, researchers have tried to develop more rapid approaches to insect species identification, particularly using chemical analysis. Researchers at the University at Albany in New York have been applying direct analysis in real time mass spectrometry (DART-MS) to the analysis of insect evidence to provide a rapid species identification tool. In DART-MS, the sample is placed between the DART ion source and the inlet of the mass spectrometer, allowing chemical components in the sample to be ionised and drawn into the MS for direct analysis. DART-MS requires minimal or no sample preparation and results can be obtained almost instantly. Using this technique, Rabi Musah and her team have already demonstrated the ability to determine the species of larvae, pupae and adult flies, highlighting a promising new tool in rapid species identification in forensic entomology.
However, until now this research has focused on the analysis of individual species. In a real-world scenario, maggots present on the body may consist of multiple different species, therefore any techniques developed for rapid species identification of larvae must be able to work with mixed samples. In a recent study, the team have taken the method one step further by examining the potential to identify larvae from mixed species.
Blow flies of various species were collected from Manhattan, New York. Maggots were submerged in 70% ethanol and the solution exposed to the ion source of the DART-MS to produce chemical signatures of both individual species and combinations of species. Mixtures of two, three, four, fix and six different species were analysed. Using the chemical profiles produced, a predictive model was constructed for the subsequent identification of unknown insect samples. Using this model, maggot species could be established with an accuracy of up to 94% and a confidence interval of 80-95%. Individual insect species are readily differentiated, with different species producing distinct chemical profiles. Similarly, mixtures of two different species could also be differentiated. As might be expected, samples containing a higher number of species were more difficult to differentiate.
Although only a proof-of-concept study and further validation is required, the study demonstrates that DART-MS could offer a way of rapidly determining the species of blowfly larvae, thus allowing investigators to establish which insects are present at the scene of a death and work out postmortem interval faster.
Beyramysoltan, S. Ventura, M. I. Rosati, J. Y. Giffen, J. E. Musah, R. A. Identification of the Species Constituents of Maggot Populations Feeding on Decomposing Remains—Facilitation of the Determination of Post Mortem Interval and Time Since Tissue Infestation through Application of Machine Learning and Direct Analysis in Real Time-Mass Spectrometry. Analytical Chem, 2020, In Press.