Zoltan Takats

Ambient Mass Spectrometry

A recent innovation in mass spectrometry is the ability to record mass spectra on ordinary samples, in their native environment, without sample preparation or preseparation by creating ions outside the instrument. In desorption electrospray ionization (DESI), the principal method described here, electrically charged droplets are directed at the ambient object of interest; they release ions from the surface, which are then vacuumed through the air into a conventional mass spectrometer. Extremely rapid analysis is coupled with high sensitivity and high chemical specificity. These characteristics are advantageously applied to high-throughput metabolomics, explosives detection, natural products discovery, and biological tissue imaging, among other applications. Future possible uses of DESI for in vivo clinical analysis and its adaptation to portable mass spectrometers are described.

Direct, trace level detection of explosives on ambient surfaces by desorption electrospray ionization mass spectrometry

Desorption electrospray ionization (DESI) mass spectrometry is used to detect trace amounts of explosives present on a variety of ambient surfaces in 5-second analysis times without any sample preparation.

Metabolic phenotyping in clinical and surgical environments

Metabolic phenotyping involves the comprehensive analysis of biological fluids or tissue samples. This analysis allows biochemical classification of a persons physiological or pathological states that relate to disease diagnosis or prognosis at the individual level and to disease risk factors at the population level. These approaches are currently being implemented in hospital environments and in regional phenotyping centres worldwide. The ultimate aim of such work is to generate information on patient biology using techniques such as patient stratification to better inform clinicians on factors that will enhance diagnosis or the choice of therapy. There have been many reports of direct applications of metabolic phenotyping in a clinical setting.

Intraoperative Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry

A mass spectrometric approach was developed for intraoperative identification of cancerous tissue, in near–real-time. Diagnosing the Masses One of the best options for curing cancer is surgery. Yet, surgeons can leave cancerous tissue behind by not seeing the “tumor margins”—or edges of the tumor—clearly. If a surgeon isn’t sure whether tissue is normal or cancerous, the tissue is sent to a pathologist for testing. During this time (20 to 30 min), the patient remains under anesthesia, and, quite often, additional samples are required. To ensure that all malignant tissue is removed in the operating room, Balog and colleagues developed a mass spectrometry–based approach that identifies cancer during surgery. After analyzing ex vivo samples of cancerous, healthy, and benign/inflammatory tissue with rapid evaporative ionization mass spectrometry (REIMS), the authors created a database of the nearly 3000 tissue-specific mass spectra. These spectra were unique for each cancer type, with lipids such as phosphatidylcholine and phosphotidylinositol showing different ratios. Using these ratios, Balog et al. were even able to identify the origin of metastatic tumors ex vivo. To adapt this technology for use in vivo, during surgery, the authors created the “intelligent knife” (iKnife), which samples surgical smoke for mass spectrometric analysis. More than 800 spectra were acquired with the iKnife from 81 patients. These spectra, when matched against the previously created database, confirmed the results of normal histology, with low rates of false-positive and false-negative readouts. This first-in-human demonstration shows that the iKnife technology is ready for widespread use in the operating room to improve the accuracy of surgical intervention in cancer. Rapid evaporative ionization mass spectrometry (REIMS) is an emerging technique that allows near–real-time characterization of human tissue in vivo by analysis of the aerosol (“smoke”) released during electrosurgical dissection. The coupling of REIMS technology with electrosurgery for tissue diagnostics is known as the intelligent knife (iKnife). This study aimed to validate the technique by applying it to the analysis of fresh human tissue samples ex vivo and to demonstrate the translation to real-time use in vivo in a surgical environment. A variety of tissue samples from 302 patients were analyzed in the laboratory, resulting in 1624 cancerous and 1309 noncancerous database entries. The technology was then transferred to the operating theater, where the device was coupled to existing electrosurgical equipment to collect data during a total of 81 resections. Mass spectrometric data were analyzed using multivariate statistical methods, including principal components analysis (PCA) and linear discriminant analysis (LDA), and a spectral identification algorithm using a similar approach was implemented. The REIMS approach differentiated accurately between distinct histological and histopathological tissue types, with malignant tissues yielding chemical characteristics specific to their histopathological subtypes. Tissue identification via intraoperative REIMS matched the postoperative histological diagnosis in 100% (all 81) of the cases studied. The mass spectra reflected lipidomic profiles that varied between distinct histological tumor types and also between primary and metastatic tumors. Thus, in addition to real-time diagnostic information, the spectra provided additional information on divergent tumor biochemistry that may have mechanistic importance in cancer.

Interaction of nilotinib, dasatinib and bosutinib with ABCB1 and ABCG2: implications for altered anti-cancer effects and pharmacological properties

Background and purpose:  ABC multidrug transporters (MDR‐ABC proteins) cause multiple drug resistance in cancer and may be involved in the decreased anti‐cancer efficiency and modified pharmacological properties of novel specifically targeted agents. It has been documented that ABCB1 and ABCG2 interact with several first‐generation, small‐molecule, tyrosine kinase inhibitors (TKIs), including the Bcr‐Abl fusion kinase inhibitor imatinib, used for the treatment of chronic myeloid leukaemia. Here, we have investigated the specific interaction of these transporters with nilotinib, dasatinib and bosutinib, three clinically used, second‐generation inhibitors of the Bcr‐Abl tyrosine kinase activity.

Rapid in situ detection of alkaloids in plant tissue under ambient conditions using desorption electrospray ionization

Desorption electrospray ionization (DESI) mass spectrometry is applied to the in situ detection of alkaloids in the tissue of poison hemlock (Conium maculatum), jimsonweed (Datura stramonium) and deadly nightshade (Atropa belladonna). The experiment is carried out by electrospraying micro-droplets of solvent onto native or freshly-cut plant tissue surfaces. No sample preparation is required and the mass spectra are recorded under ambient conditions, in times of a few seconds. The impact of the sprayed droplets on the surface produces gaseous ions from organic compounds originally present in the plant tissue. The effects of operating parameters, including the electrospray high voltage, heated capillary temperature, the solvent infusion rate and the carrier gas pressure on analytical performance are evaluated and optimized. Different types of plant material are analyzed including seeds, stems, leaves, roots and flowers. All the previously reported alkaloids have been detected in C. maculatum, while fifteen out of nineteen known alkaloids for D. stramonium and the principal alkaloids of A. belladonna were also identified. All identifications were confirmed by tandem mass spectrometry. Results obtained show similar mass spectra, number of alkaloids, and signal intensities to those obtained when extraction and separation processes are performed prior to mass spectrometric analysis. Evidence is provided that DESI ionization occurs by both a gas-phase ionization process and by a droplet pick-up mechanism. Quantitative precision of DESI is compared with conventional electrospray ionization mass spectrometry (after sample workup) and the RSD values for the same set of 25 dicotyledonous C. maculatum seeds (one half of each seed analyzed by ESI and the other by DESI) are 9.8% and 5.2%, respectively.

Histology by mass spectrometry: label-free tissue characterization obtained from high-accuracy bioanalytical imaging.

Histological examination of biological and medical specimens has gained its universality and undisputed significance through distinct staining techniques and microscopical evaluation. Discrimination of tissue types after specific staining or labeling is an essential prerequisite for histopathological investigation, for example in accurate diagnosis of cancer. Histochemical staining techniques can only be used in a targeted manner for known compounds, and only a limited number of such targets can be visualized from a given sample at the same time. Another limitation of classical histology lies in the fact that a considerable amount of experience is required and that even well-trained pathologists often interpret histologically stained sections differently. Mass spectrometry (MS), on the other hand, offers complex but objective and reproducible information on biological material. Imaging of biological samples by MS gained interest after development of matrix-assisted laser desorption/ionization (MALDI) as a method to desorb and ionize biomolecules, such as peptides, proteins, glycans, or lipids, with a limit of detection in the attomole range. The first proof-of-principle of imaging by MALDI was presented in 1994, and was followed by numerous applications during the last decade. An extensive overview of instrumental developments and methodological approaches in MS imaging has been published recently. MS imaging allows the distribution of analytes to be investigated and displayed across a sample in a semi-quantitative manner and without the need to predefine or label selected substances prior to analysis. MALDI imaging is typically used with spatial resolutions of between 50 and 200 mm. Increasing the resolution into the lowmicrometer range has been demonstrated, but requires a very low limit of detection of the employed mass spectrometer, as the available amount of material per imaged spot is reduced quadratically with reduction of the spot diameter. Identification of molecules during MS imaging experiments is often limited if mass spectrometers with a rather low mass resolving power and accuracy are used. Additional offline bulk analyses of tissue material are typically used to back up imaging results. Imaging selectivity, that is, mass bin width for allocation to image signals, is typically set to onemass unit. Employing MS imaging for obtaining valid histological information requires a number of improvements: 1. The usable spatial resolution has to be high enough to resolve cellular features. 2. Analytical sensitivity has to be high enough to visualize the majority of interesting substances in high-lateralresolution experiments. 3. Mass resolving power and mass accuracy have to be as high as possible when complex biological samples are under investigation. To unequivocally assign a mass signal to an image and to identify substances by accurate mass, signals have to be stable and correct in detected mass values; that is, mass accuracy should be in the low-ppm range. 4. Image assignment to mass signals has to be both highly selective and flexible. To distinguish neighboring mass signals in biological tissue samples, the coding mass bin width must typically be smaller than 0.1 mass units. 5. To clearly identify imaged substances in complex samples, MS data from fragmentation of precursor ions has to be obtainable directly from individual imaged sample spots. 6. Ambient pressure conditions are often necessary, rather than high-vacuum conditions, for example when working under physiological conditions, imaging volatile substances such as drug metabolites, or using volatile matrices. 7. Sample handling and preparation have to be fast and robust. 8. Results have to be achievable in a reasonable timeframe.

In vivo, in situ tissue analysis using rapid evaporative ionization mass spectrometry

The analysis of intact biological tissues by mass spectrometry (MS) has been pursued for more than three decades. However, mass spectrometric methods have always put strong constraints on the geometry and the preparation of these samples. Even with the recent advent of ambient ionization methods, not all of these restrictions have been lifted. MS analysis of biomolecules in tissue has traditionally been achieved by desorption ionization methods including secondary ion mass spectrometry (SIMS), matrix-assisted laser desorption (MALDI), 19, 20] and desorption electrospray ionization (DESI) 5,18] methods. While desorption ionization methods are not appropriate for the analysis of vital (living) tissues, rapid thermal evaporation has the potential to establish the in situ, in vivo ionization of tissue constituents. The possible formation of organic ions from condensed-phase samples in a purely thermal process was initially proposed by Holland et al., and it was successfully demonstrated later. The rationale of rapid heating was to achieve molecular evaporation rates comparable to the rate of decomposition, which results in the formation of a considerable quantity of gaseous molecules or molecular ions. The quest for efficient thermal evaporation methods has led to the development of various thermally assisted ionization methods, including thermospray ionization. Since collisional cooling of nascent ions at higher pressure is more effective, thermal evaporation at atmospheric pressure is expected to suppress thermal decomposition. Atmospheric pressure thermal desorption ionization was demonstrated recently by the desorption of organic cations with minimal thermal degradation. 27] The present study is based on the discovery that rapid thermal evaporation of biological tissues yields gaseous molecular ions of the major tissue components, for example, phospholipids. As thermal evaporation of tissues is widely used in surgery (i.e., electrosurgery and laser surgery), it was sensible to use dedicated surgical instruments for the experiments. Combination of surgical and MS techniques also offers a possibility for in situ chemical analysis of tissue during surgery. Since the key feature of the technique is the fast evaporation of a sample, it was termed “Rapid Evaporative Ionization Mass Spectrometry” (REIMS). The tentative mechanism of ion formation is described in the Supporting Information. Electrosurgical dissection is based on the Joule heating and evaporation of tissues by an electric current. The presence of ionized water molecules during electrosurgical dissection raises the possibility of an alternative ionization mechanism involving neutral desorption and chemical ionization in the gas phase. For more details, see the Supporting Information. An electrosurgical electrode was used as an ion source coupled to a distant mass spectrometer employing a Venturi gas jet pump and 1–2 m long polytetrafluoroethylene (PTFE) tubing (Figure 1).

Identification of Biological Tissues by Rapid Evaporative Ionization Mass Spectrometry

The newly developed rapid evaporative ionization mass spectrometry (REIMS) provides the possibility of in vivo, in situ mass spectrometric tissue analysis. The experimental setup for REIMS is characterized in detail for the first time, and the description and testing of an equipment capable of in vivo analysis is presented. The spectra obtained by various standard surgical equipments were compared and found highly specific to the histological type of the tissues. The tissue analysis is based on their different phospholipid distribution; the identification algorithm uses a combination of principal component analysis (PCA) and linear discriminant analysis (LDA). The characterized method was proven to be sensitive for any perturbation such as age or diet in rats, but it was still perfectly suitable for tissue identification. Tissue identification accuracy higher than 97% was achieved with the PCA/LDA algorithm using a spectral database collected from various tissue species. In vivo, ex vivo, and post mortem REIMS studies were performed, and the method was found to be applicable for histological tissue analysis during surgical interventions, endoscopy, or after surgery in pathology.

Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer

Significance Mass spectrometry imaging (MSI) technology represents a highly promising approach in cancer research. Here, we outline current roadblocks in translational MSI and introduce a comprehensive workflow designed to address current methodological limitations. An integrated bioinformatics platform is presented that allows intuitive histology-directed interrogation of MSI datasets. We show that this strategy permits the analysis of multivariate molecular signatures with direct correlation to morphological regions of interest, which can offer new insights into how different tumor microenvironmental populations interact with one another and generate novel region-of-interest specific biomarkers and therapeutic targets. Mass spectrometry imaging (MSI) provides the opportunity to investigate tumor biology from an entirely novel biochemical perspective and could lead to the identification of a new pool of cancer biomarkers. Effective clinical translation of histology-driven MSI in systems oncology requires precise colocalization of morphological and biochemical features as well as advanced methods for data treatment and interrogation. Currently proposed MSI workflows are subject to several limitations, including nonoptimized raw data preprocessing, imprecise image coregistration, and limited pattern recognition capabilities. Here we outline a comprehensive strategy for histology-driven MSI, using desorption electrospray ionization that covers (i) optimized data preprocessing for improved information recovery; (ii) precise image coregistration; and (iii) efficient extraction of tissue-specific molecular ion signatures for enhanced biochemical distinction of different tissue types. The proposed workflow has been used to investigate region-specific lipid signatures in colorectal cancer tissue. Unique lipid patterns were observed using this approach according to tissue type, and a tissue recognition system using multivariate molecular ion patterns allowed highly accurate (>98%) identification of pixels according to morphology (cancer, healthy mucosa, smooth muscle, and microvasculature). This strategy offers unique insights into tumor microenvironmental biochemistry and should facilitate compilation of a large-scale tissue morphology-specific MSI spectral database with which to pursue next-generation, fully automated histological approaches.