Toward Machine Learning-Driven Mass Spectrometric Identification of Trichothecenes in the Absence of Standard Reference Materials.

While a significant body of work exists on the detection of commonly known trichothecene toxins, biological, environmental, and other transformational processes can generate many under-characterized and unknown modified trichothecenes. Lacking both analytical reference standards and associated mass spectral databases, identification of these modified compounds reflects both a challenge and a critical gap from forensic and public health perspectives. We report here the application of machine learning (ML) techniques toward identification of discriminative fragment ions from mass spectrometric data that can be exploited to detect evidence of type A and B trichothecenes. The goal of this work is to establish a new method for the identification of unknown, though structurally similar trichothecenes, by leveraging objective ML techniques. Discriminative fragments derived from a series of gradient-boosted machine learners are then used to develop ML-driven precursor ion scan (PIS) methods on a triple quadrupole mass spectrometer (QQQ) for screening of "unknown unknown" trichothecenes. Specifically, we apply the PIS method to a laboratory-synthesized trichothecene, a first step in demonstrating the power of alternative, machine learning-driven mass spectrometric methods.

Evaluation of 6-OxP-CD, an Oxime-based cyclodextrin as a viable medical countermeasure against nerve agent poisoning: Experimental and molecular dynamic simulation studies on its inclusion complexes with cyclosarin, soman and VX.

The ability of the cyclodextrin-oxime construct 6-OxP-CD to bind and degrade the nerve agents Cyclosarin (GF), Soman (GD) and S-[2-[Di(propan-2-yl)amino]ethyl] O-ethyl methylphosphonothioate (VX) has been studied using 31P-nuclear magnetic resonance (NMR) under physiological conditions. While 6-OxP-CD was found to degrade GF instantaneously under these conditions, it was found to form an inclusion complex with GD and significantly improve its degradation (t1/2 ~ 2 hrs) relative over background (t1/2 ~ 22 hrs). Consequently, effective formation of the 6-OxP-CD:GD inclusion complex results in the immediate neutralization of GD and thus preventing it from inhibiting its biological target. In contrast, NMR experiments did not find evidence for an inclusion complex between 6-OxP-CD and VX, and the agent's degradation profile was identical to that of background degradation (t1/2 ~ 24 hrs). As a complement to this experimental work, molecular dynamics (MD) simulations coupled with Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) calculations have been applied to the study of inclusion complexes between 6-OxP-CD and the three nerve agents. These studies provide data that informs the understanding of the different degradative interactions exhibited by 6-OxP-CD with each nerve agent as it is introduced in the CD cavity in two different orientations (up and down). For its complex with GF, it was found that the oxime in 6-OxP-CD lies in very close proximity (PGF⋯OOxime ~ 4-5 Å) to the phosphorus center of GF in the 'downGF' orientation for most of the simulation accurately describing the ability of 6-OxP-CD to degrade this nerve agent rapidly and efficiently. Further computational studies involving the center of masses (COMs) for both components (GF and 6-OxP-CD) also provided some insight on the nature of this inclusion complex. Distances between the COMs (ΔCOM) lie closer in space in the 'downGF' orientation than in the 'upGF' orientation; a correlation that seems to hold true not only for GF but also for its congener, GD. In the case of GD, calculations for the 'downGD' orientation showed that the oxime functional group in 6-OxP-CD although lying in close proximity (PGD⋯OOxime ~ 4-5 Å) to the phosphorus center of the nerve agent for most of the simulation, adopts another stable conformation that increase this distance to ~ 12-14 Å, thus explaining the ability of 6-OxP-CD to bind and degrade GD but with less efficiency as observed experimentally (t1/2 ~ 4 hr. vs. immediate). Lastly, studies on the VX:6-OxP-CD system demonstrated that VX does not form a stable inclusion complex with the oxime-bearing cyclodextrin and as such does not interact in a way that is conducive to an accelerated degradation scenario. Collectively, these studies serve as a basic platform from which the development of new cyclodextrin scaffolds based on 6-OxP-CD can be designed in the development of medical countermeasures against these highly toxic chemical warfare agents.

Modulators of calcium signalling at fertilization.

Calcium (Ca2+) signals initiate egg activation across the animal kingdom and in at least some plants. These signals are crucial for the success of development and, in the case of mammals, health of the offspring. The mechanisms associated with fertilization that trigger these signals and the molecules that regulate their characteristic patterns vary widely. With few exceptions, a major contributor to fertilization-induced elevation in cytoplasmic Ca2+ is release from endoplasmic reticulum stores through the IP3 receptor. In some cases, Ca2+ influx from the extracellular space and/or release from alternative intracellular stores contribute to the rise in cytoplasmic Ca2+. Following the Ca2+ rise, the reuptake of Ca2+ into intracellular stores or efflux of Ca2+ out of the egg drive the return of cytoplasmic Ca2+ back to baseline levels. The molecular mediators of these Ca2+ fluxes in different organisms include Ca2+ release channels, uptake channels, exchangers and pumps. The functions of these mediators are regulated by their particular activating mechanisms but also by alterations in their expression and spatial organization. We discuss here the molecular basis for modulation of Ca2+ signalling at fertilization, highlighting differences across several animal phyla, and we mention key areas where questions remain.

The dPix-Git complex is essential to coordinate epithelial morphogenesis and regulate myosin during Drosophila egg chamber development.

How biochemical and mechanical information are integrated during tissue development is a central question in morphogenesis. In many biological systems, the PIX-GIT complex localises to focal adhesions and integrates both physical and chemical information. We used Drosophila melanogaster egg chamber formation to study the function of PIX and GIT orthologues (dPix and Git, respectively), and discovered a central role for this complex in controlling myosin activity and epithelial monolayering. We found that Git's focal adhesion targeting domain mediates basal localisation of this complex to filament structures and the leading edge of migrating cells. In the absence of dpix and git, tissue disruption is driven by contractile forces, as reduction of myosin activators restores egg production and morphology. Further, dpix and git mutant eggs closely phenocopy defects previously reported in pak mutant epithelia. Together, these results indicate that the dPix-Git complex controls egg chamber morphogenesis by controlling myosin contractility and Pak kinase downstream of focal adhesions.

Planar-Polarized Semaphorin-5c and Plexin A Promote the Collective Migration of Epithelial Cells in Drosophila.

Collective migration of epithelial cells is essential for morphogenesis, wound repair, and the spread of many cancers, yet how individual cells signal to one another to coordinate their movements is largely unknown. Here, we introduce a tissue-autonomous paradigm for semaphorin-based regulation of collective cell migration. Semaphorins typically regulate the motility of neuronal growth cones and other migrating cell types by acting as repulsive cues within the migratory environment. Studying the follicular epithelial cells of Drosophila, we discovered that the transmembrane semaphorin, Sema-5c, promotes collective cell migration by acting within the migrating cells themselves, not the surrounding environment. Sema-5c is planar polarized at the basal epithelial surface such that it is enriched at the leading edge of each cell. This location places it in a prime position to send a repulsive signal to the trailing edge of the cell ahead to communicate directional information between neighboring cells. Our data show that Sema-5c can signal across cell-cell boundaries to suppress protrusions in neighboring cells and that Plexin A is the receptor that transduces this signal. Finally, we present evidence that Sema-5c antagonizes the activity of Lar, another transmembrane guidance cue that operates along leading-trailing cell-cell interfaces in this tissue, via a mechanism that appears to be independent of Plexin A. Together, our results suggest that multiple transmembrane guidance cues can be deployed in a planar-polarized manner across an epithelium and work in concert to coordinate individual cell movements for collective migration.

Part 1: Tracing Russian VX to its synthetic routes by multivariate statistics of chemical attribution signatures.

Chemical attribution signatures (CAS) associated with different synthetic routes used for the production of Russian VX (VR) were identified. The goal of the study was to retrospectively determine the production method employed for an unknown VR sample. Six different production methods were evaluated, carefully chosen to include established synthetic routes used in the past for large scale production of the agent, routes involving general phosphorus-sulfur chemistry pathways leading to the agent, and routes whose main characteristic is their innate simplicity in execution. Two laboratories worked in parallel and synthesized a total of 37 batches of VR via the six synthetic routes following predefined synthesis protocols. The chemical composition of impurities and byproducts in each route was analyzed by GC/MS-EI and 49 potential CAS were recognized as important markers in distinguishing these routes using Principal Component Analysis (PCA). The 49 potential CAS included expected species based on knowledge of reaction conditions and pathways but also several novel compounds that were fully identified and characterized by a combined analysis that included MS-CI, MS-EI and HR-MS. The CAS profiles of the calibration set were then analyzed using partial least squares discriminant analysis (PLS-DA) and a cross validated model was constructed. The model allowed the correct classification of an external test set without any misclassifications, demonstrating the utility of this methodology for attributing VR samples to a particular production method. This work is part one of a three-part series in this Forensic VSI issue of a Sweden-United States collaborative effort towards the understanding of the CAS of VR in diverse batches and matrices. This part focuses on the CAS in synthesized batches of crude VR and in the following two parts of the series the influence of food matrices on the CAS profiles are investigated.

Part 2: Forensic attribution profiling of Russian VX in food using liquid chromatography-mass spectrometry.

This work is part two of a three-part series in this issue of a Sweden-United States collaborative effort towards the understanding of the chemical attribution signatures of Russian VX (VR) in synthesized samples and complex food matrices. In this study, we describe the sourcing of VR present in food based on chemical analysis of attribution signatures by liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with multivariate data analysis. Analytical data was acquired from seven different foods spiked with VR batches that were synthesized via six different routes in two separate laboratories. The synthesis products were spiked at a lethal dose into seven food matrices: water, orange juice, apple purée, baby food, pea purée, liquid eggs and hot dog. After acetonitrile sample extraction, the samples were analyzed by LC-MS/MS operated in MRM mode. A multivariate statistical calibration model was built on the chemical attribution profiles from 118 VR spiked food samples. Using the model, an external test-set of the six synthesis routes employed for VR production was correctly identified with no observable major impact of the food matrices to the classification. The overall performance of the statistical models was found to be exceptional (94%) for the test set samples retrospectively classified to their synthesis routes.

Part 3: Solid phase extraction of Russian VX and its chemical attribution signatures in food matrices and their detection by GC-MS and LC-MS.

Chemical attribution signatures indicative of O-isobutyl S-(2-diethylaminoethyl) methylphosphonothioate (Russian VX) synthetic routes were investigated in spiked food samples. Attribution signatures were identified using a multifaceted approach: Russian VX was synthesized using six synthetic routes and the chemical attribution signatures identified by GC-MS and LC-MS. Three synthetic routes were then down selected and spiked into complex matrices: bottled water, baby food, milk, liquid eggs, and hot dogs. Sampling and extraction methodologies were developed for these materials and used to isolate the attribution signatures and Russian VX from each matrix. Recoveries greater than 60% were achieved for most signatures in all matrices; some signatures provided recoveries greater than 100%, indicating some degradation during sample preparation. A chemometric model was then developed and validated with the concatenated data from GC-MS and LC-MS analyses of the signatures; the classification results of the model were > 75% for all samples. This work is part three of a three-part series in this issue of the United States-Sweden collaborative efforts towards the understanding of the chemical attribution signatures of Russian VX in crude materials and in food matrices.

Synthesis route attribution of sulfur mustard by multivariate data analysis of chemical signatures.

A multivariate model was developed to attribute samples to a synthetic method used in the production of sulfur mustard (HD). Eleven synthetic methods were used to produce 66 samples for model construction. Three chemists working in both participating laboratories took part in the production, with the aim to introduce variability while reducing the influence of laboratory or chemist specific impurities in multivariate analysis. A gas chromatographic/mass spectrometric data set of peak areas for 103 compounds was subjected to orthogonal partial least squares - discriminant analysis to extract chemical attribution signature profiles and to construct multivariate models for classification of samples. For one- and two-step routes, model quality allowed the classification of an external test set (16/16 samples) according to synthesis conditions in the reaction yielding sulfur mustard. Classification of samples according to first-step methodology was considerably more difficult, given the high purity and uniform quality of the intermediate thiodiglycol produced in the study. Model performance in classification of aged samples was also investigated.

Statistical analysis of the chemical attribution signatures of 3-methylfentanyl and its methods of production.

Chemical attribution of the origin of an illegal drug is a key component of forensic efforts aimed at combating illicit and clandestine manufacture of drugs and pharmaceuticals. The results of these studies yield detailed information on synthesis byproducts, reagents, and precursors that can be used to identify the method of manufacture. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic 3-methylfentanyl, N-(3-methyl-1-phenethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Eighteen crude samples from six synthesis methods were generated, the analysis of which was used to identify signatures (i.e. chemical compounds) that were important in the discrimination of synthetic route. These methods were carefully selected to minimize the use of scheduled precursors, complicated laboratory equipment, number of steps, and extreme reaction conditions. Using gas and liquid chromatographies combined with time-of-flight mass spectrometry (GC-QTOF and LC-QTOF) over 160 distinct species were monitored. Analysis of this combined data set was performed using modern machine learning techniques capable of reducing the size of the data set, prioritizing key chemical attribution signatures, and identifying the method of production for blindly synthesized 3-methylfentanyl materials.

Chemical Attribution of Fentanyl Using Multivariate Statistical Analysis of Orthogonal Mass Spectral Data.

Attribution of the origin of an illicit drug relies on identification of compounds indicative of its clandestine production and is a key component of many modern forensic investigations. The results of these studies can yield detailed information on method of manufacture, starting material source, and final product, all critical forensic evidence. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic fentanyl, N-(1-phenylethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Six synthesis methods, all previously published fentanyl synthetic routes or hybrid versions thereof, were studied in an effort to identify and classify route-specific signatures. A total of 160 distinct compounds and inorganic species were identified using gas and liquid chromatographies combined with mass spectrometric methods (gas chromatography/mass spectrometry (GC/MS) and liquid chromatography-tandem mass spectrometry-time of-flight (LC-MS/MS-TOF)) in conjunction with inductively coupled plasma mass spectrometry (ICPMS). The complexity of the resultant data matrix urged the use of multivariate statistical analysis. Using partial least-squares-discriminant analysis (PLS-DA), 87 route-specific CAS were classified and a statistical model capable of predicting the method of fentanyl synthesis was validated and tested against CAS profiles from crude fentanyl products deposited and later extracted from two operationally relevant surfaces: stainless steel and vinyl tile. This work provides the most detailed fentanyl CAS investigation to date by using orthogonal mass spectral data to identify CAS of forensic significance for illicit drug detection, profiling, and attribution.

Antagonism between Gdf6a and retinoic acid pathways controls timing of retinal neurogenesis and growth of the eye in zebrafish.

Maintaining neurogenesis in growing tissues requires a tight balance between progenitor cell proliferation and differentiation. In the zebrafish retina, neuronal differentiation proceeds in two stages with embryonic retinal progenitor cells (RPCs) of the central retina accounting for the first rounds of differentiation, and stem cells from the ciliary marginal zone (CMZ) being responsible for late neurogenesis and growth of the eye. In this study, we analyse two mutants with small eyes that display defects during both early and late phases of retinal neurogenesis. These mutants carry lesions in gdf6a, a gene encoding a BMP family member previously implicated in dorsoventral patterning of the eye. We show that gdf6a mutant eyes exhibit expanded retinoic acid (RA) signalling and demonstrate that exogenous activation of this pathway in wild-type eyes inhibits retinal growth, generating small eyes with a reduced CMZ and fewer proliferating progenitors, similar to gdf6a mutants. We provide evidence that RA regulates the timing of RPC differentiation by promoting cell cycle exit. Furthermore, reducing RA signalling in gdf6a mutants re-establishes appropriate timing of embryonic retinal neurogenesis and restores putative stem and progenitor cell populations in the CMZ. Together, our results support a model in which dorsally expressed gdf6a limits RA pathway activity to control the transition from proliferation to differentiation in the growing eye.