Dataset Information

Fluorescence Imaging of Posterior Spiracles from Second and Third Instars of Forensically Important Chrysomya rufifacies (Diptera: Calliphoridae).

ABSTRACT: Entomological protocols for aging blowfly (Diptera: Calliphoridae) larvae to estimate the time of colonization (TOC) are commonly used to assist in death investigations. While the methodologies for analyzing fly larvae differ, most rely on light microscopy, genetic analysis, or, more rarely, electron microscopy. This pilot study sought to improve resolution of larval stage in the forensically important blowfly Chrysomya rufifacies using high-content fluorescence microscopy and biochemical measures of developmental marker proteins. We established fixation and mounting protocols, defined a set of measurable morphometric criteria and captured developmental transitions of 2nd instar to 3rd instar using both fluorescence microscopy and anti-ecdysone receptor Western blot analysis. The data show that these instars can be distinguished on the basis of robust, nonbleaching, autofluorescence of larval posterior spiracles. High-content imaging techniques using confocal microscopy, combined with morphometric and biochemical techniques, may therefore aid forensic entomologists in estimating TOC.

SUBMITTER: Flores D

PROVIDER: S-EPMC5118101 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Fluorescence Imaging of Posterior Spiracles from Second and Third Instars of Forensically Important Chrysomya rufifacies (Diptera: Calliphoridae).

Flores Danielle D Miller Amy L AL Showman Angelique A Tobita Caitlyn C Shimoda Lori M N LM Sung Carl C Stokes Alexander J AJ Tomberlin Jeffrey K JK Carter David O DO Turner Helen H

Journal of forensic sciences 20161005 6

Entomological protocols for aging blowfly (Diptera: Calliphoridae) larvae to estimate the time of colonization (TOC) are commonly used to assist in death investigations. While the methodologies for analyzing fly larvae differ, most rely on light microscopy, genetic analysis, or, more rarely, electron microscopy. This pilot study sought to improve resolution of larval stage in the forensically important blowfly Chrysomya rufifacies using high-content fluorescence microscopy and biochemical measur ...[more]

PMID: 27706817

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Project description:Correct identification of forensically important insects, such as flies in the family Calliphoridae, is a crucial step for them to be used as evidence in legal investigations. Traditional identification based on morphology has been effective, but has some limitations when it comes to identifying immature stages of certain species. DNA-barcoding, using COI, has demonstrated potential for rapid and accurate identification of Calliphoridae, however, this gene does not reliably distinguish among some recently diverged species, raising questions about its use for delimitation of species of forensic importance. To facilitate DNA based identification of Calliphoridae in the Caribbean we developed a vouchered reference collection from across the region, and a DNA sequence database, and further added the nuclear ITS2 as a second marker to increase accuracy of identification through barcoding. We morphologically identified freshly collected specimens, did phylogenetic analyses and employed several species delimitation methods for a total of 468 individuals representing 19 described species. Our results show that combination of COI + ITS2 genes yields more accurate identification and diagnoses, and better agreement with morphological data, than the mitochondrial barcodes alone. All of our results from independent and concatenated trees and most of the species delimitation methods yield considerably higher diversity estimates than the distance based approach and morphology. Molecular data support at least 24 distinct clades within Calliphoridae in this study, recovering substantial geographic variation for Lucilia eximia, Lucilia retroversa, Lucilia rica and Chloroprocta idioidea, probably indicating several cryptic species. In sum, our study demonstrates the importance of employing a second nuclear marker for barcoding analyses and species delimitation of calliphorids, and the power of molecular data in combination with a complete reference database to enable identification of taxonomically and geographically diverse insects of forensic importance.

Project description:Background:The time-length between the first colonization of necrophagous insect on the corpse and the beginning of investigation represents the most important forensic concept of minimum post-mortem inference (PMImin). Before colonization, the time spent by an insect to detect and locate a corpse could significantly influence the PMImin estimation. The olfactory system plays an important role in insect food foraging behavior. Proteins like odorant binding proteins (OBPs), chemosensory proteins (CSPs), odorant receptors (ORs), ionotropic receptors (IRs) and sensory neuron membrane proteins (SNMPs) represent the most important parts of this system. Exploration of the above genes and their necrophagous products should facilitate not only the understanding of their roles in forging but also their influence on the period before PMImin. Transcriptome sequencing has been wildly utilized to reveal the expression of particular genes under different temporal and spatial condition in a high throughput way. In this study, transcriptomic study was implemented on antennae of adult Aldrichina grahami (Aldrich) (Diptera: Calliphoridae), a necrophagous insect with forensic significance, to reveal the composition and expression feature of OBPs, CSPs, ORs, IRs and SNMPs genes at transcriptome level. Method:Antennae transcriptome sequencing of A. grahami was performed using next-generation deep sequencing on the platform of BGISEQ-500. The raw data were deposited into NCBI (PRJNA513084). All the transcripts were functionally annotated using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Differentially expressed genes (DEGs) were analyzed between female and male antennae. The transcripts of OBPs, CSPs, ORs, IRs and SNMPs were identified based on sequence feature. Phylogenetic development of olfactory genes of A. grahami with other species was analyzed using MEGA 5.0. RT-qPCR was utilized to verify gene expression generated from the transcriptome sequencing. Results:In total, 14,193 genes were annotated in the antennae transcriptome based on the GO and the KEGG databases. We found that 740 DEGs were differently expressed between female and male antennae. Among those, 195 transcripts were annotated as candidate olfactory genes then checked by sequence feature. Of these, 27 OBPs, one CSPs, 49 ORs, six IRs and two SNMPs were finally identified in antennae of A. grahami. Phylogenetic development suggested that some olfactory genes may play a role in food forging, perception of pheromone and decomposing odors. Conclusion:Overall, our results suggest the existence of gender and spatial expression differences in olfactory genes from antennae of A. grahami. Such differences are likely to greatly influence insect behavior around a corpse. In addition, candidate olfactory genes with predicted function provide valuable information for further studies of the molecular mechanisms of olfactory detection of forensically important fly species and thus deepen our understanding of the period before PMImin.

Project description:Forensic entomology is the branch of forensic science that is related to using arthropod specimens found in legal issues. Fly maggots are one of crucial pieces of evidence that can be used for estimating post-mortem intervals worldwide. However, the species-level identification of fly maggots is difficult, time consuming, and requires specialized taxonomic training. In this work, a novel method for the identification of different forensically-important fly species is proposed using convolutional neural networks (CNNs). The data used for the experiment were obtained from a digital camera connected to a compound microscope. We compared the performance of four widely used models that vary in complexity of architecture to evaluate tradeoffs in accuracy and speed for species classification including ResNet-101, Densenet161, Vgg19_bn, and AlexNet. In the validation step, all of the studied models provided 100% accuracy for identifying maggots of 4 species including Chrysomya megacephala (Diptera: Calliphoridae), Chrysomya (Achoetandrus) rufifacies (Diptera: Calliphoridae), Lucilia cuprina (Diptera: Calliphoridae), and Musca domestica (Diptera: Muscidae) based on images of posterior spiracles. However, AlexNet showed the fastest speed to process the identification model and presented a good balance between performance and speed. Therefore, the AlexNet model was selected for the testing step. The results of the confusion matrix of AlexNet showed that misclassification was found between C. megacephala and C. (Achoetandrus) rufifacies as well as between C. megacephala and L. cuprina. No misclassification was found for M. domestica. In addition, we created a web-application platform called thefly.ai to help users identify species of fly maggots in their own images using our classification model. The results from this study can be applied to identify further species by using other types of images. This model can also be used in the development of identification features in mobile applications. This study is a crucial step for integrating information from biology and AI-technology to develop a novel platform for use in forensic investigation.

Dataset Information

Fluorescence Imaging of Posterior Spiracles from Second and Third Instars of Forensically Important Chrysomya rufifacies (Diptera: Calliphoridae).

Publications

Fluorescence Imaging of Posterior Spiracles from Second and Third Instars of Forensically Important Chrysomya rufifacies (Diptera: Calliphoridae).

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