Mass Spectrometric Methodologies for Investigating the Metabolic

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Mass Spectrometric Methodologies for Investigating the Metabolic Signatures of Parkinson’s disease: Current Progress and Future Perspectives Emily L Gill, Jeremy P Koelmel, Richard A Yost, Michael S Okun, Vinata Vedam-Mai, and Timothy J. Garrett Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b04084 • Publication Date (Web): 31 Jan 2018 Downloaded from http://pubs.acs.org on February 4, 2018

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Analytical Chemistry

Mass Spectrometric Methodologies for Investigating the Metabolic Signatures of Parkinson’s disease: Current Progress and Future Perspectives Emily L. Gill, ¶ Jeremy P. Koelmel, ¶ Richard A. Yost, ¶, § Michael S. Okun, # Vinata Vedam-Mai, ¥, ‡ and Timothy J. Garrett *, §, ‡ ¶

Department of Chemistry, University of Florida, Gainesville, Florida 32611, USA Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida 32610, USA # Department of Neurology, University of Florida, Gainesville, Florida 32610, USA ¥ Department of Neurosurgery, University of Florida, Gainesville, Florida 32610, USA §

Abstract Parkinson’s disease (PD) is a neurodegenerative disorder resulting from the loss of dopaminergic neurons of the substantia nigra as well as degeneration of motor and non-motor basal ganglia circuitries. Typically known for classical motor deficits (tremor, rigidity, bradykinesia), early stages of the disease are associated with a large non-motor component (depression, anxiety, apathy, etc.). Currently there are no definitive biomarkers of PD, and the measurement of dopamine metabolites does not allow for detection of prodromal PD, nor does it aid in long-term monitoring of disease progression. Given that PD is increasingly recognized as complex and heterogeneous, involving several neurotransmitters and proteins, it is of importance that we advance interdisciplinary studies to further our knowledge of the molecular and cellular pathways that are affected in PD. This approach will yield useful biomarkers for early diagnosis and will ultimately result in the development of disease-modifying therapies. Here, we discuss pre-analytical factors associated with metabolomics studies, summarize current mass spectrometric methodologies used to evaluate the metabolic signature of PD, and provide future perspectives of the rapidly developing field of MS in the context of PD. An Introduction to Parkinson’s disease Parkinson’s disease (PD) is the second most commonly diagnosed neurodegenerative disorder after Alzheimer’s disease (AD). The Parkinson’s Foundation estimates that over 10 million people are living with PD worldwide and several factors contribute to the disease progression (age, genetics, environment).1 PD is currently diagnosed based on history and clinical presentation, as well as by the initial response to dopaminergic drugs. Clinical manifestations may include slow movement, stiffness, resting tremor and postural instability. Non-motor features such as depression, anxiety and sleep issues may also be present. Unfortunately, at the time of manifestation, the patient has typically lost approximately 60% of dopaminergic neurons in the striatum.2 However, confirmation of PD diagnosis still depends ultimately on neuropathological examination of the brain for evidence of dopaminergic deterioration and Lewy body deposition. PD is a slow, progressive neurodegenerative disorder likely beginning years before diagnosis, involving multiple neuroanatomical areas, presenting with a variety of symptoms. Prodromal PD symptoms may include REM sleep behavior disorders (RBD), anosmia, gastrointestinal issues and depression. Due to the complex nature of PD, there are obvious clinical challenges. Specifically, there is no way to definitively diagnose the disease at its early stages, nor are there disease modifying therapies for PD, or neuroprotective agents capable of restoring lost neurons. Administered orally, L-DOPA, a precursor of dopamine, remains the gold standard treatment for PD and is the single most effective Food and Drug Administration (FDA) approved drug for managing PD symptoms.3 Long term treatment with L-DOPA along with disease progression may result in adverse manifestations such as motor fluctuations, dyskinesia and hallucinations.4

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Although the underlying mechanisms of neuronal degeneration are currently unknown, oxidative stress, chronic neuroinflammation and mitochondrial dysfunction may play a role in both sporadic as well as genetic forms of PD.5,6 Reactive gliosis resulting from astrocytes and microglial activation are present in PD and are thought to contribute to the sustained inflammation leading to abnormal aggregation of alpha synuclein, a key player in PD pathogenesis.7 Spreading synucleinopathy has been suggested by Braak et al. as a unifying hypothesis for the underlying pathogenesis of the disease, however PD experts have yet to reach an agreement.8 Furthermore, over the past decade, several genetic mutations have been identified relating to PD.9 While a comprehensive discussion of the genetics of PD is beyond the scope of this article, certain key genes involved in mediating PD are described briefly below. Autosomal dominant forms of PD can be mediated by: SNCA (encodes alpha-synuclein, which is a major component of Lewy bodies and neurites), LRRK2 (encodes leucine-rich repeat kinase 2, which is involved in membrane trafficking, autophagy, and neurite outgrowth among others), VPS35 (encodes vacuolar protein sorting 35, which is involved in protein trafficking between Golgi and lysosomes), DNAJC13, and CHCHD2. Autosomal recessive forms of PD are mediated by: Parkin, PINK1 and DJ-1, all of which encode proteins involved in protecting and maintaining the health of mitochondria. Other genes known to be associated with PD-like symptoms include FBXO7, SCA2, SCA3, RAB39B, and POLG1. In cancer research, metabolic profiling has helped uncover pathways underlying the disease, contributing to better classification and therapeutic strategies. For example, elevated levels of branched chain acids (BCAAs) in plasma are now associated with an increased risk of developing pancreatic cancer.10 It is evident that PD also results in perturbations of the metabolome, which could be useful for the identification of a fingerprint for early diagnosis, monitoring disease progression and ultimately resulting in a therapeutic strategy. Mass spectrometry (MS) is a key analytical approach that directly measures small molecules, and therefore offers the most promising approach to elucidate key pathways and regulators by comprehensively measuring multiple metabolites and lipids either directly from tissue or following separation (‘omics’).11 An Overview of Metabolomics and Mass Spectrometry The ‘omics’ approach to investigating neurodegenerative disorders such as PD refers to the study of the genome (genomics), which specifies ‘what could happen’, the proteome (proteomics), which specifies ‘how it happens’, and the metabolome (metabolomics), which specifies ‘what does happen’ with regards to an organism (Figure 1).12,13 The metabolome is the entire set of small molecules in an organism, biological substrate, cell or organelle; measurement of these metabolites indicates a network of metabolic reactions and the products of these reactions represent the phenotype in an organism. Metabolomics is the comprehensive study of the numerous metabolites present in the metabolome at any given time. Metabolites arise from environmental and genetic interactions thus providing information regarding the biological response to a disease state. Metabolites are considered one of the best indicators of cell states, as their rapid fluxes are extremely sensitive to cellular changes.14 Therefore, metabolomic studies compliment genomics and proteomics by offering a platform for biomarker identification and a rapid phenotypic prospective of the disease state. Lipidomics is a specialized subarea of metabolomics that focuses on the study of polar and non-polar lipid species. Technological advances in MS have opened up new directions for investigating the metabolic signatures of PD and the hope is that these advances will improve our understanding of its etiology, and pathogenesis leading to new treatments and/or prevention.


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Figure 1. A schematic representation of the ‘omics’ approaches. Environmental factors may include, life-style, microbiome and xenobiotics. Reproduced from Frédérich, M.; Pirotte, B.; Fillet, M.; de Tullio, P. J. Med. Chem. 2016, 59, 8649–8666. Copyright 2016 American Chemical Society.13 Perhaps the most established platform for metabolomics studies is liquid chromatography-mass spectrometry (LC-MS) which dominates the field due to the high throughput nature, wide coverage of the metabolome enabling the characterization of polar and non-polar species in a single injection, wide dynamic range, and high mass accuracy when high resolution MS is employed (5 ppm or lower).15 It is considered the gold standard analytical tool for metabolic profiling offering an identification platform for small molecules and a semiquantitative measurement.16 Liquid chromatography-high resolution mass spectrometry (LCHRMS) provides a comprehensive view of the metabolic content of a variety of samples (i.e. tissue and bodily fluids) with archival quality data. Metabolomic studies using MS methodologies can be either targeted, in which case the metabolites of interest are known, or untargeted, in which case full metabolic profiling is performed.17 However, no individual method is capable of detecting all metabolites and therefore a variety of different sample preparation, separation approaches and instrument platforms are often necessary to fully characterize the metabolome (e.g. sugars are not separated via a reverse phase separation approach). In addition, methods for analysis are usually 20-30 minutes per injection providing a bottleneck of analysis with larger batches of samples. Furthermore, untargeted metabolomics is not a fully comprehensive approach, with thousands of features (i.e. relating to a specific m/z and retention time) detected per injection, including features related to sample degradation due and poor sample handling, contamination and artifacts. Investigations into PD have been conducted using MS coupled with separation techniques, but have also been conducted with direct analysis techniques such as MS imaging.18,19,20 MS imaging techniques complement LC-MS by providing a visualization platform for metabolic changes occurring within and beyond the etiological region. This approach also eliminates the extraction step because extraction is performed during ionization, thus minimizing tissue handling. Furthermore, gas chromatography-mass spectrometry (GC-MS) is preferred for certain classes of small molecules such as organic acids, steroids and eicosanoids. When combined, GC-MS provides an untargeted analysis of the volatile metabolites whilst LC-MS examines less volatile or nonvolatile metabolites, providing increased coverage of the


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metabolome. It should be noted that GC-MS applications can measure non-volatile metabolites, but requires chemical derivatization to enhance the volatility. However, Other MS methodologies are emerging, such as ambient ionization approaches and ion mobility mass spectrometry (IMS) that may aid in further characterizing the metabolome by expanding the breadth of metabolites covered. Ambient methodologies allow for rapid sampling, little or no sample preparation and potential for real-time tissue manipulation during analysis, a feature not possible using traditional vacuum ionization as in matrix assisted laser desorption ionization (MALDI).21 Furthermore, IMS, which provides information regarding the collision cross-section or size-to-charge ratio (Ω/z) of a molecular species, is an emerging separation technique providing an orthogonal approach to liquid chromatography (LC). LC approaches may require lengthily run times or not achieve chromatographic separation, therefore adding a new dimension of separation such as IMS is attractive to the clinical laboratory, because it can separate metabolites that may not be separated by LC.22 For example, Vauts et al. report the use of IMS, with a real-time data display for breath analysis.23 Technology of this nature, which offers low-cost, rapid analysis, portability, ease of use and ultimately in-home diagnosis, could be considered the future of clinical diagnosis. We provide a perspective on the continuously developing field of MS approaches that could provide much needed insight into neurodegenerative disorders, such as PD. Applications in Parkinson’s disease Pre-Analytical Factors The heterogeneity of the symptoms of PD pose a challenge to scientists as it complicates understanding the etiology of the disease. Varying levels of cognitive impairments, ranging from no-impairments to severe impairments, have been observed in PD patients.24 These observations are thought to be related to the presence of other symptoms (such as tremors), as well as clinical characteristics such as, duration of the disease and age at disease onset; amongst others.24 Therefore, the search for definitive biomarkers and pathophysiological answers is a complex problem from the disease perspective compounded by the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors.25 These factors pose potential issues when recruiting human participants for research studies and when interpreting results from biomarker studies. Thus, animal models are commonly used for metabolomic studies before translation to humans.26 Yet, despite having several advantages, animal models can only mimic the course of human disease. However, since access to human brain tissue is limited due to the invasive nature of collection and validity of postmortem tissue, bodily fluids (urine, serum, saliva) are more widely studied in the hope of finding biomarkers relevant to the disease.27 Each sample type has its advantages and disadvantages; brain tissue analysis usually focuses on disease progression for etiopathological elucidation. Bodily fluids are distributed throughout the body and are therefore affected and diluted by changes relating to the physiology of many different organs. However, bodily fluids are of interest when searching for biomarkers, because they offer a less or non-invasive diagnostic approach that can be readily employed as part of normal clinical care. 27,28,29 The extent of sample preparation required for mass spectrometric methodologies can introduce variability and interference, for example homogenization and phase extraction is needed for LC-MS, while matrix coating is needed for MALDI. Sample preparation is perhaps the most important aspect of metabolomic studies and pre-analytical processes such as sample collection, transportation, storage, extraction time and human factors may affect the results of metabolomics studies.30,31 For example, metabolites can be significantly degraded, altering the molecular profile of samples, if the appropriate freezing procedures are not followed prior to analysis.32 Tissue based preparation approaches for LC-MS involve homogenization and then extraction tailored for metabolites or lipids. These steps eliminate any regional specific


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metabolites in favor of producing a more comprehensive analysis approach. They are time consuming and can result in loss of metabolites or degradation of metabolites if not performed quickly. In contrast, direct analysis approaches enable rapid analysis, involving minimum sample preparation and manipulation, while maintaining the tissue specific localization. Neurological disorders often reflect a specific region of the brain rather than the whole. Thus, direct analysis approaches are ideal because they allow the detection of metabolites that are concentrated in only a small region and that may fall into the noise following homogenization and extraction approaches. For example, in PD patient’s dopamine neurotransmitters are significantly reduced in the substantia nigra portion of the brain, due to dopaminergic neuronal death.33 Two emerging ambient ionization MS methodologies such as the liquid micro-junction surface sampling (LMJSS) and desorption electrospray ionization (DESI) enable the simple sectioning of a tissue with placement on a glass microscope slide for analysis. In the case of LMJ-SS, a small piece of tissue can be analyzed without sectioning, as the technique is compatible with very thick tissue pieces. Traditional Workflows The complexity of PD becomes even greater when the symptomatic progression and severity varies amongst patients, but metabolomic approaches offer an intriguing opportunity to understand this complexity. Roede et al. present an untargeted metabolomics study investigating the metabolic signatures of PD in human serum comparing slow verses rapid progression PD.25 Using LC-HRMS, they identified potential alterations in polyamine (i.e. spermidine, putrescine) metabolism. The changes were seen early on in the disease and may relate to the progressive motor symptoms of PD. In particular, an acetylation product of spermidine, N8-acetylspermidine, was found to be significantly elevated in the rapid progression compared to slow progression PD. Spermidine is thought to interact with α-syn, assisting in misfolding, and therefore the elevation of N8-acetylspermidine may present a response to neuroinflammation.34 Luan et al. also evaluated the progression of PD using LC-HRMS and GC-MS to search for biomarkers in human urine.27 In this case early-stage, mid-stage and late-stage PD were compared to control subjects with higher levels of BCAAs being correlating with PD progression. BCAAs such as leucine, isoleucine and valine take part in protein synthesis, and deficiencies may result in muscle wasting.35 Furthermore, BCAAs are thought to interfere with L-DOPA absorption. Administered orally, L-DOPA is a precursor of dopamine, and to this day remains the single most effective Food and Drug Administration (FDA) approved drug for managing PD symptoms.36,3 This combined metabolomics approach shows the possibility to understand metabolic changes in association with treatment and could be used in future studies to further evaluate patient response. Lewitt et al. also compared CSF from PD patients, and healthy controls using a combination of GC-MS and ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS).37 A decrease in glutathione and an increase in 3-hydroxykynurenine were observed in PD patients compared to controls. Glutathione is an antioxidant, whilst 3hydroxykynurenine is a known generator of highly reactive free radicals.38,39 Furthermore, GC-MS was used by Tisch et al. to analyze volatile compounds in alveoli breath of PD patients.40 Statistically significant differences in the average abundance of tentatively identified volatile organic compounds (VOC), including 2,3,6,7-tetramethyloctane and 5-ethyl-2-methyloctane were observed. These methylated alkanes along with environmental toxins such as styrene were elevated in the breath of PD patients. This observation may relate to oxidative stress, which may damage DNA, and other studies have shown similar outcomes using rat models (Figure 2).41,42 If biomarkers can be found in the breath such methodologies would be ideal as a rapid, cost effective and non-invasive diagnostic tool.43


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Figure 2. The abundance of six VOCs that were increased in exhaled breath from the PDlesioned rats, as compared to the control rats. Reproduced from Tisch, U.; Aluf, Y.; Ionescu, R.; Nakhleh, M.; Bassal, R.; Axelrod, N.; Robertman, D.; Tessler, Y.; Finberg, J. P. M.; Haick, H. ACS Chem. Neurosci. 2011, 3, 161–166. Copyright 2011 American Chemical Society.41 An issue associated with untargeted metabolomic studies is the ability to identify the species present, especially in untargeted metabolomics where over 3000 features are often detected. Koelmel et al. presented a data dependent iterative exclusion (ddMS2-IE) methodology known as IE-omics using high-resolution tandem mass spectrometry (HR-MS/MS) combined with UHPLC that resulted in increased coverage of lipid metabolites.44 IE-omics data acquisition involves creating an exclusion list between traditional data dependent (ddMS2) acquisitions such that lower abundance species are not neglected in subsequent runs. Applying IE-omics to mouse substantia nigra increased molecular identifications in positive mode by 40%. This in turn increases the potential for finding and identifying biomarkers for etiopathological elucidation. In negative mode, IE-omics identified cardiolipin (CL), a lipid species thought to be implicated in PD, which was not identified using traditional ddMS2. It has been suggested that there are interactions between the α-syn and oxidized lipid metabolites, which lead to mitochondria dysfunction. CL is thought to be responsible for assisting in the physical association of α-syn oligomers with the mitochondria membrane.45 Binding mediated by CL may represent an important pathophysicological mechanism, by disrupting the integrity of the mitochondria leading to PD. Given the importance of the lipid class in PD, other LC-MS studies have focused on this lipid species.46,47 Boutin et al. evaluated human brain tissue using select reaction monitoring (SRM) in a targeted metabolomics study in conjunction with UHPLC-MS.48 SRM is a scanning mode of the triple quadrupole mass spectrometer, in which the precursor ion of interest is selected in the first quadrupole, fragmented in a collision cell (i.e. collision induced dissociation (CID)), and one or more product ion(s) selected in the final quadrupole. The study investigated a potential relationship between PD and an accumulation of glucosylceramides (GluCer) in brain tissue. GCase is an enzyme involved in cleaving the beta-glycosidic linkage of GluCer and is known to be deficient in PD brain tissue; therefore, accumulation of GluCer species in PD would be


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anticipated. However, no statistical differences were observed between the control and PD groups and the authors concluded that a larger sample size would be required to determine if any statistical change in GluCer are evident. This is an important consideration in metabolomics (or any ‘omics’) studies as a sufficient sample size (i.e. biological replicates) per group is needed to ensure changes observed are not due to numerous sources of biological and methodical noise, but rather biologically driven processes. Non-traditional Workflows In addition to chromatography, ion mobility is a separation technique that can be coupled to MS. Ion mobility is orthogonal to LC enabling the separation of small molecules based on size and shape. The use of ion mobility uncovered the potential existence of a dopamine isomers in rat striatum, thought to be 2-(2,4-dihydroxylphenyl) ethylamine.49 Nevertheless, Zhang et al. observed a decrease in dopamine signal in PD rat models compared to controls, whilst the isomer was unchanged.49 Although the isomer is not known to be significant in PD, isomers are still of interest in MS, because LC-MS may be over quantifying dopamine due to its inability to chromatographically resolve this potential isomer. This identification was based on a higher mobility (or shorter drift time) and subsequent reduced collision cross-section compared to dopamine and would not be detected using a traditional LC-MS approach.49 For reference, protein studies using IMS have also identified oligomers in α-syn aggregation thought to be associated with mitochondria dysfunction due to metabolic interactions leading to the symptoms of PD.50,51 Due to the low concentration of oligomers, they are not readily detected by conventional MS techniques and had only previously been observed by gel electrophoresis, but not identified.50 Currently, there is limited use of IMS approaches in small molecule studies of PD. This is partly due to the need for a separate instrument and the recent commercial development, but also due to software limitations and signal losses when IMS is employed. In our opinion, an ideal approach to extractive based analysis would be LC-IMS-HRMS/MS since it combines orthogonal separation approaches, and high resolution for further metabolite identification, but this approach is currently limited by available software to align and mine 4-dimensional data sets and thus most studies have focused on looking at a few metabolites rather than untargeted profiling. Real-Time Metabolomics Real-time analysis aims to capture metabolic signatures that are either occurring too quickly or are only present under physiological conditions. Recent studies have demonstrated the usefulness of segmented flow electrospray ionization MS (ESI-MS) when coupled to in vivo microdialysis (Figure 3).52 Generally, mapping chemicals in the brain of live subjects is challenging, but in vivo sampling methodologies can provide a better understanding of temporal fluctuations in neurotransmitters.53 However, although such methodologies are suitable for a variety of compounds, applications are currently limited to chemicals that can be readily ionized from complex mixtures since the analysis is usually conducted without chromatographic separation and no current in vivo sampling techniques have added IMS approaches for expanded separation of complex mixtures. Mabrouk et al. also used similar methodologies to monitor dopamine and its interaction with other neurotransmitters in the globus pallidus of rats.54 Microdialysis probes were implanted bilaterally into the globus pallidus and flushed with a ringer solution (aCSF), before being collected and analyzed offline using capillary LC-MS.54 Methodologies of this nature are also of interest to the study of deep brain stimulation (DBS) a symptomatic surgical treatment of PD, currently of unknown mechanism.55


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Figure 3. A schematic representation of microdialysis coupled to segmented flow ESI-MS showing, (A) the droplet generation device, (B) droplet coalescence connection and, (C) liquid connection at the ESI probe. Reproduced from Song, P.; Hershey, N. D.; Mabrouk, O. S.; Slaney, T. R.; Kennedy, R. T. Anal. Chem. 2012, 84, 4659–4664. Copyright 2012 American Chemical Society.52 Imaging Metabolomics Using LC-MS methodologies that require tissue homogenization no localization information is possible. Spatial information may provide an insight into biologically changing pathways in the PD brain. Sample preparation in the field of MSI has been steadily improving yet there are few studies using MSI to investigate the metabolic signature of PD.56,57 This is possible because it is difficult to use MSI techniques to map neurotransmitters and other small molecules, especially in lipid-rich brain tissue. Nevertheless, lipidomic studies are also scarce with many studies opting for LC-MS methodologies. Furthermore, there are currently no studies using MSI reporting the use of human postmortem PD brain tissue.58 Shariatgorji et al. developed a derivatization method allowing the simultaneous imaging and quantitation of multiple neurotransmitters.59 They producde spatially resolved images of key neurotransmitters such as dopamine in the striatum portion of brain sections from PD rat models.59 The concentration of dopamine in this region was consistent with studies using LC-MS methodologies and enabled localization.60 Overall, PD studies using MSI have tended to focus on protein changes associated with PD.61,19 Hanrieder et al. showed an increase in dynorphins and alpha-neoendorphin in the dorsolateral, but not the dorsomedial striatum of rat models with severe dyskinesia.61 Currently, LC-MS based techniques are dominating the field of metabolomics owing to their efficient separation and enhanced detection of the varied metabolic species.62 However, this approach provides no information regarding the anatomical location of metabolites; therefore, MSI techniques could be complimentary to existing studies using animal models and help to elucidate localized changes.


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Ambient Ionization Metabolomics Ambient ionization MS is an emerging technique, which unlike LC-MS and traditional MSI methodologies, requires little or no sample preparation, along with an opportunity for rapid analysis. Furthermore, unlike conventional MSI methodologies such as MALDI-MSI no matrix coating is required. Examples of ambient ionization MS include desorption electrospray ionization (DESI), liquid microjunction surface sampling (LMJ-SS) and laser ablation electrospray ionization (LAESI); amongst others.63,21,64 Bergman et al. used nanospray desorption electrospray ionization (nano-DESI) to quantify neurotransmitters in rat brain tissue.65 Quantification of the neurotransmitters was achieved by incorporating a deuterated standard into the DESI solvent system. Other DESI studies used derivatization to increase sensitivity for the detection of low abundant neurotransmitters.66 Ambient MS also offers MSI capabilities; however, unlike MALDI its use is limited by poor spatial resolution. Nevertheless, ambient MS has been successful in mapping the spatial distribution of low molecular weight species. Xu et al. mapped the spatial distribution of rotigotine, a dopamine agonist, in rat brain tissue using liquid extraction surface analysis (LESA).67,68 Since these are direct analysis approaches, separation, using LC is not possible, but separation with IMS could be explored that may enable improved analysis. Future studies may utilize the ambient nature of the sampling chamber for ex vivo analysis and take advantage of ambient MS as a rapid screening tool. Future Perspective In past years, LC-MS methodologies have dominated the field of metabolomics in terms of PD related studies. However, future research should take advantage of emerging ambient ionization techniques. Ambient ionization methodologies remove the vacuum constraints placed on the size and types of samples that can be analyzed. As a newly emerging area of MS, ambient ionization is still open to new applications, including the potential analysis of biologically active tissue (ex vivo analysis), and other living organisms.69 Nano-DESI has been applied to the study of living microbial colonies.70 Furthermore, LMJ-SS was able to identify metabolites in living microorganisms using a simple surface extraction mechanism (Figure 4).71

Figure 4. A schematic of the liquid-microjunction surface sampling probe (LMJ-SSP) used for the analysis of living microorganisms on a petri dish. A liquid-junction with an optimized solvent system was maintained between the analyte surface and the probe, by matching the solvent flow


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rate and applied gas pressure. Depending on the solvent system, analytes are drawn in by the continuous flow of solvent in preparation for ionization using an ESI source. Reproduced from Hsu, C.-C.; ElNaggar, M. S.; Peng, Y.; Fang, J.; Sanchez, L. M.; Mascuch, S. J.; Møller, K. A.; Alazzeh, E. K.; Pikula, J.; Quinn, R. A.; Zeng, Y.; Wolfe, B. E.; Dutton, R. J.; Gerwick, L.; Zhang, L.; Liu, X.; Månsson, M.; Dorrestein, P. C. Anal. Chem. 2013, 85, 7014–7018. Copyright 2013 American Chemical Society.71 There are various pathways that researchers could take when applying ambient ionization MS to the study of PD. First, researchers may use ambient ionization MS as a screening platform, to generate a real-time understanding of the activation mechanism of microglia cells from a metabolic prospective. Microglia cells are located throughout the brain and spinal cord and are involved in active immune defense within the central nervous system (CNS). They become activated by various pro-inflammatory factors and may be involved in the initiation of neurodegenerative disorders, such as PD.72 Another pathway involves using MS to examine tissue ex vivo drawing from neuroscience perspectives. In the field of neuroscience, brain tissue viability is maintained ex vivo using artificial cerebrospinal fluid (aCSF) under near-physiological conditions. This is essential when investigating neural networks and neuronal activity for both neuroscientific and electrophysiology studies. Thomas et al. reported a chamber that allows tissue sections to be maintained under near-physiological conditions whilst preserving the ability to record from the tissue surface (i.e. electrophysiology). Similarly, the ambient nature of LMJ-SS provides potential for ex vivo surface sampling.73 Such advances pose new directions for the field of MS, and could provide an insight into PD from a complementary prospective. The separation capabilities of IMS has potentially revealed the presence of a dopamine isomers in rat striatum.49 Therefore, it is possible that LC-MS over quantifies certain metabolites due to its inability to chromatographically resolve isomeric species. Structurally similar compounds often require extended analysis time to achieve separation, whilst identification using MS/MS fails when dealing with similar fragmentation patterns. Therefore, studies targeting specific metabolites may take advantage of IMS in conjunction with traditional chromatographic separation. MS has a unique ability to sift out biomarkers in a wide variety of bio-fluids and tissue samples. Achieving the goal of finding a non-invasive biomarker for PD will benefit both patients and medical practitioners. Perhaps the least invasive samples currently analyzed by MS are urine and feces; however, analysis thereafter still requires extensive sample preparation and a lengthily chromatographic run-time. The potential for rapid screening is becoming increasingly possible using GC-MS (or possibly IMS), with promising results showing changes in VOC in the breath of PD patients, complimenting studies previously done in rats.40,41 The ability to detect biomarkers in breath could provide a low-cost, and rapid methodology for increased diagnosis speed, and advancements in remedial treatment protocols. Overall, exciting new directions in the field of MS are becoming possible and may ultimately provide researchers with new platforms for investigating neurodegenerative disorders such as PD, unraveling new pathways that lead to diagnosis and potentially a cure. Concluding Remarks The clinical challenges associated with PD are ongoing. Owing to an aging population, intervention is increasingly necessary and common. Knowledge of the etiopathogenesis of the disease is required to develop both symptomatic treatments and disease modifying therapies to provide a better quality of life to those living with PD. MS techniques are contributing to this goal, and emerging techniques may provide a means to build on what is already known about the disease state. Finally, although only PD is discussed in this article, such methodologies could be easily translated to other neurological disorders.


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Author Information *Corresponding Author Tel: (352) 273-5050, Email: [email protected] Author Contributions ‡These authors share senior authorship. Acknowledgments The authors would like to thank the Southeast Center for Integrated Metabolomics (SECIM) at the University of Florida (NIH Grant #U24 DK097209). References

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Mass Spectrometric Methodologies for Investigating the Metabolic

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