Untargeted Metabolomics Profiling for Determination of the Time since Deposition of Biofluids in a Forensic Context: A Proof-of-Concept for Urine, Saliva, and Semen in Addition to Blood.

In a criminal trial, the reconstruction of a crime is one of the fundamental steps of the prosecution process. Common questions, such as what happened, where and how it happened, and who made it happen, need to be solved. Biological evidence at crime scenes can be crucial in the determination of these fundamental questions. One of the more challenging riddles to solve is the when? A trace left at a crime scene can prove a person's presence at the crime scene. Knowledge about when it was deposited there, the time since deposition (TsD), would allow linking the person in space and time to the site. This could fortify allegations against a suspect or discharge accusations if proven to be outside of the temporal boundaries where a suspected crime had occurred. Determining the TsD has yet to become routine forensic casework, despite recent research efforts, especially for blood traces. However, next to blood, other biological traces are also commonly encountered in crime scenes. We here present a study to profile the metabolomes of artificially aged dried body fluid spots of blood, semen, saliva, and urine over 4 weeks by liquid chromatography high-resolution mass spectrometry and data-dependent acquisition. All four body fluids (BFs) exhibited diverse time-dependent changes, and a large number of molecular features (MF) were associated with TsD. Still, significant differences between the BFs were observed, limiting universal interpretability independent of the BF and facilitating a need to further study time-dependent changes of different BFs individually toward the goal of TsD estimation.

Determination of the Time since Deposition of Blood Traces Utilizing a Liquid Chromatography-Mass Spectrometry-Based Proteomics Approach.

Knowledge about when a bloodstain was deposited at a crime scene can be of critical value in forensic investigation. A donor of a genetically identified bloodstain could be linked to a suspected time frame and the crime scene itself. Determination of the time since deposition (TsD) has been extensively studied before but has yet to reach maturity. We therefore conducted a proof-of-principle study to study time- and storage-dependent changes of the proteomes of dried blood stains. A bottom-up proteomics approach was employed, and high-resolution liquid-chromatography-mass-spectrometry (HR-LC-MS) and data-independent acquisition (DIA) were used to analyze samples aged over a 2 month period and two different storage conditions. In multivariate analysis, samples showed distinct clustering according to their TsD in both principal component analysis (PCA) and in partial least square discriminant analysis (PLS DA). The storage condition alters sample aging and yields different separation-driving peptides in hierarchical clustering and in TsD marker peptide selection. Certain peptides and amino acid modifications were identified and further assessed for their applicability in assessing passed TsD. A prediction model based on data resampling (Jackknife) was applied, and prediction values for selected peptide ratios were created. Depending on storage conditions and actual sample age, mean prediction performances ranges in between 70 and 130% for the majority of peptides and time points. This places this study as a first in investigating LC-MS based bottom-up proteomics approaches for TsD determination.

A new metabolomics-based strategy for identification of endogenous markers of urine adulteration attempts exemplified for potassium nitrite.

Urine adulteration to circumvent positive drug testing represents a problem for toxicological laboratories. While creatinine is a suitable marker for dilution, detection of chemicals is often performed by dipstick tests associated with high rates of false positives. Several methods would be necessary to check for all possible adulterants. Untargeted mass spectrometry (MS) methods used in metabolomics should theoretically allow detecting concentration changes of any endogenous urinary metabolite or presence of new biomarkers produced by chemical adulteration. As a proof of concept study, urine samples from 10 volunteers were treated with KNO2 and analyzed by high-resolution MS. For statistical data evaluation, XCMSplus and MetaboAnalyst were used. Compound identification was performed by database searches using an in-house database, Chemspider, METLIN, HMDB, and NIST. Principle component analysis revealed clear separation between treated and untreated urine samples. In detail, 307 features showed significant concentration changes with fold changes greater than 2 (79 decreased; 228 increased). Mainly amino acids (e.g., histidine, methylhistidine, di- and trimethyllysine) and purines (uric acid) were detected in lower amounts. 5-HO-isourate was found to be formed as a new compound from uric acid and, e.g., imidazole lactate concentrations increased due to the breakdown of histidine. This metabolomics-based strategy allowed for a broad identification range of markers of urinary adulteration. More studies will be needed to investigate routine applicability of identified potential markers exploring urinary conditions of their formation and stability. Selected markers might then be integrated into routine MS screening procedures allowing for detection of adulteration within routine MS analysis. Graphical Abstract ᅟ.

Do dried blood spots have the potential to support result management processes in routine sports drug testing?-Part 3: LC-MS/MS-based peptide analysis for dried blood spot sampling time point estimation.

Along with the recent acknowledgement of the World Anti-Doping Agency to use dried blood spot (DBS) samples for routine doping control purposes, there have been propositions to use DBS as a matrix that allows regular proactive remotely supervised self-sampling, providing potential longitudinal monitoring of an athlete's exposure to doping agents. However, several organizational aspects have to be considered before implementation, such as the verification of the sample collections time point. Based on a previous untargeted proteomics workflow utilizing liquid chromatography-high-resolution mass spectrometry (LC-HRMS) to identify protein/peptide markers to define the time since deposition of a bloodstain, the aim of the current study was to develop a targeted LC-HRMS/MS analytical method for promising peptidic target analytes. A long-term DBS storage experiment was carried out over a 3-month period (sample collection time points: 0, 2, 4, 7, 14, 21, 28, 42, 56, 70, 84 and 91 days) with DBS samples of 10 volunteers for longitudinal investigation of signal abundance changes of targeted peptide sequences at different storage temperatures (room temperature [RT], 4°C and -20°C). Prior to experimental analysis, LC-HRMS/MS method characteristics were successfully assessed, including intraday precision, carryover and sample extract stability. For estimation of DBS sample collection time points, ratios of two peptides that originate from the same protein prior to tryptic digestion were created. Two targeted peptide area ratios were found to significantly increase after being stored at RT for 28 days, representing potential markers for future use in routine doping controls that contribute to advancing complementary avenues in anti-doping.

Analytical considerations for (un)-targeted metabolomic studies with special focus on forensic applications.

Over the past few years, the interest in metabolomics has increased in various fields including forensic toxicology. Forensic analysis typically requires a high degree of accuracy, which is often a problem in metabolomics applications. We aimed for a systematic evaluation of different analytical considerations of a metabolomics workflow allowing a targeted approach within an untargeted setup. Samples with 69 metabolites from different chemical classes were qualitatively and quantitatively analyzed on a high resolution quadrupole time of flight mass spectrometer coupled to liquid chromatography (UHPLC-QTOF). Three issues were addressed: (a) Two different approaches on "blind matrix" a simulated body fluid (SBF) and plasma-filtrate, were tested for calibration samples; (b) comparison of two different HPLC columns, reverse-phase (RP) and hydrophilic interaction chromatography (HILIC); and (c) comparison of three different acquisition modes (TOF-MS, information dependent data acquisition (IDA), and sequential window acquisition of all theoretical fragment-ion spectra (SWATH). Samples were measured repeatedly for method comparison based on sensitivity, accuracy, precision, and detection robustness. The blind matrices showed similar accuracy for most analytes, while SBF provided an easier preparation with satisfying results. To cover a wide part of the human metabolome, a combination of RP and HILIC showed the best results. The different scan modes performed equally regarding metabolite quantification while TOF-MS was more sensitive but lacked MS/MS spectra generation. IDA and SWATH files were aligned to various databases where IDA showed good MS/MS spectra matches. SWATH seemed to be beneficial in detection rate but was incompatible with many important software tools in metabolomics.