"Unveiling Forensic Signature: Leveraging Soil Microbiome and Enzymatic Response and Machine Learning Applications for Cyanide-Induced Death Detection"
Creators: name: P.S, Muhammad Safar
name: Manaf, Jannath
Publisher: name: Zenodo
Year: 2024
Subjects: subject: Forensic sciences
subject: forensic microbiome
subject: Microbiology
subject: FOS: Biological sciences

description: Research Proposal: Unveiling Forensic Signatures - Leveraging Soil Microbiome and Enzymatic Responses to Detect Cyanide-Induced Deaths.

Background and MotivationThe Jolly Serial Cyanide Killing case in Kerala, India, highlights the critical challenges faced by law enforcement in detecting cyanide from decomposed bodies. The rapid breakdown of cyanide and various environmental factors created difficulties for forensic analysis, leading to inaccurate conclusions about the timing and severity of exposure. This case underscores the urgent need for improved methods of cyanide detection, especially in forensic scenarios where only skeletal remains are present. Conventional toxicological analysis often falls short in cases involving extensive decomposition, as the evaporation properties of cyanide can make it challenging to detect during examinations after death. The redistribution of cyanide after death further complicates the interpretation of toxicological findings, potentially resulting in inaccurate conclusions about the cause of death.Research ObjectivesThe proposed research aims to advance the field of forensic science by investigating the soil microbiome and enzymatic responses to cyanide exposure from decomposing rodent remains. Specifically, the objectives of this study are:1.    To characterize the changes in soil microbial community composition and diversity in response to cyanide exposure from decomposing rodent carcasses.2.    To identify key cyanide-degrading microorganisms and their associated enzymatic pathways that can serve as potential forensic biomarkers for detecting cyanide-induced deaths.3.    To explore the integration of machine learning techniques for the classification of samples, estimation of postmortem interval, and recognition of patterns linked to cyanide exposure based on complex microbiome data.By addressing these objectives, the proposed research aims to develop a comprehensive understanding of the soil microbiome and enzymatic responses to cyanide exposure, ultimately contributing to more effective and reliable methods for detecting cyanide-induced deaths in forensic investigations.MethodologyThe proposed research will employ a multidisciplinary approach, combining microbial community analysis, enzymatic assays, and advanced analytical techniques to investigate the soil microbiome's response to cyanide exposure from decomposing rodent remains.1.    Soil Sample Collection and Preparation: Soil samples will be collected from controlled experimental settings where rodent carcasses are exposed to varying concentrations of cyanide. Samples will be collected at different time points during the decomposition process to capture the dynamic changes in the soil microbiome.2.    Microbial Community Analysis: The soil microbiome will be characterized using 16S rRNA gene sequencing, metagenomics, and metatranscriptomics. These techniques will provide a comprehensive understanding of the microbial community composition, diversity, and functional capabilities in response to cyanide exposure.3.    Enzymatic Activity Assays: Targeted enzymatic assays will be performed to identify and quantify the activity of key cyanide-degrading enzymes, such as rhodanese, cyanide hydratase, and cyanidase. This will help elucidate the biochemical pathways involved in the soil microbiome's response to cyanide.4.    Isolation and Characterization of Cyanide-Degrading Microorganisms: Selective cultivation techniques will be employed to isolate and characterize microorganisms with the ability to degrade cyanide. Their physiological and metabolic properties will be studied to assess their potential as forensic biomarkers.5.    Machine Learning Integration: Machine learning algorithms will be applied to the complex microbiome data to enable the classification of samples, estimation of postmortem interval, and recognition of patterns associated with cyanide exposure. This will help establish robust and reliable forensic tools for detecting cyanide-induced deaths.Expected Outcomes and ImpactThe proposed research is expected to yield the following key outcomes:1.    Comprehensive understanding of the soil microbiome's response to cyanide exposure, including changes in community composition, diversity, and enzymatic activity.2.    Identification of cyanide-degrading microorganisms and their associated enzymatic pathways that can serve as potential forensic biomarkers for detecting cyanide-induced deaths.3.    Development of machine learning-based models for the classification of samples, estimation of postmortem interval, and recognition of patterns linked to cyanide exposure, enhancing the reliability and precision of forensic investigations.4.    Establishment of a standardized protocol for the integration of soil microbiome analysis and enzymatic responses into forensic investigation practices, particularly in cases involving extensive decomposition or limited direct chemical detection of cyanide.The impact of this research will be significant in the field of forensic science. By leveraging the soil microbiome and enzymatic responses to cyanide exposure, this study will provide a novel and complementary approach to traditional toxicological analysis, addressing the limitations of conventional cyanide detection methods. The findings will contribute to more accurate and reliable forensic investigations, ultimately leading to improved justice and fairness in cases involving cyanide-induced deaths. Furthermore, the insights gained from this research will enhance our understanding of the environmental impact of cyanide and its effects on soil ecosystems. This knowledge can inform environmental remediation efforts and support the development of strategies for the safe disposal of cyanide-containing waste.ConclusionThe proposed research on unveiling forensic signatures through the study of soil microbiome and enzymatic responses to cyanide exposure from decomposing rodent remains holds immense potential for advancing the field of forensic science. By addressing the challenges faced in the Jolly Serial Cyanide Killing case and other similar scenarios, this research will contribute to the development of more effective and reliable methods for detecting cyanide-induced deaths, even in cases involving extensive decomposition.