Recurrent gene flow between Neanderthals and modern humans over the past 200,000 years.

Although it is well known that the ancestors of modern humans and Neanderthals admixed, the effects of gene flow on the Neanderthal genome are not well understood. We develop methods to estimate the amount of human-introgressed sequences in Neanderthals and apply it to whole-genome sequence data from 2000 modern humans and three Neanderthals. We estimate that Neanderthals have 2.5 to 3.7% human ancestry, and we leverage human-introgressed sequences in Neanderthals to revise estimates of Neanderthal ancestry in modern humans, show that Neanderthal population sizes were significantly smaller than previously estimated, and identify two distinct waves of modern human gene flow into Neanderthals. Our data provide insights into the genetic legacy of recurrent gene flow between modern humans and Neanderthals.

Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks.

Understanding the regulatory architecture of phenotypic variation is a fundamental goal in biology, but connections between gene regulatory network (GRN) activity and individual differences in behavior are poorly understood. We characterized the molecular basis of behavioral plasticity in queenless honey bee (Apis mellifera) colonies, where individuals engage in both reproductive and non-reproductive behaviors. Using high-throughput behavioral tracking, we discovered these colonies contain a continuum of phenotypes, with some individuals specialized for either egg-laying or foraging and 'generalists' that perform both. Brain gene expression and chromatin accessibility profiles were correlated with behavioral variation, with generalists intermediate in behavior and molecular profiles. Models of brain GRNs constructed for individuals revealed that transcription factor (TF) activity was highly predictive of behavior, and behavior-associated regulatory regions had more TF motifs. These results provide new insights into the important role played by brain GRN plasticity in the regulation of behavior, with implications for social evolution.

Identification of lipid biomarkers of metastatic potential and gene expression (HER2/p53) in human breast cancer cell cultures using ambient mass spectrometry.

In breast cancer, overexpression of human epidermal growth factor receptor 2 (HER2) correlates with overactivation of lipogenesis, mutation of tumor suppressor p53, and increased metastatic potential. The mechanisms through which lipids mediate p53, HER2, and metastatic potential are largely unknown. We have developed a desorption electrospray ionization mass spectrometry (DESI-MS) method to identify lipid biomarkers of HER2/p53 expression, metastatic potential, and disease state (viz. cancer vs. non-cancerous) in monolayer and suspension breast cancer cell cultures (metastatic potential: MCF-7, T-47D, MDA-MB-231; HER2/p53: HCC2218 (HER2+++/p53+), HCC1599 (HER2-/p53-), HCC202 (HER2++/p53-), HCC1419 (HER2+++/p53-) HCC70 (HER2-/p53+++); non-cancerous: MCF-10A). Unsupervised principal component analysis (PCA) of DESI-MS spectra enabled identification of twelve lipid biomarkers of metastatic potential and disease state, as well as ten lipids that distinguish cell lines based on HER2/p53 expression levels (> 200 lipids were identified per cell line). In addition, we developed a DESI-MS imaging (DESI-MSI) method for mapping the spatial distribution of lipids in metastatic spheroids (MDA-MB-231). Of the twelve lipids that correlate with changes in the metastatic potential of monolayer cell cultures, three were localized to the necrotic core of spheroids, indicating a potential role in promoting cancer cell survival in nutrient-deficient environments. One lipid species, which was not detected in monolayer MDA-MB-231 cultures, was spatially localized to the periphery of the spheroid, suggesting a potential role in invasion and/or proliferation. These results demonstrate that combining DESI-MS/PCA of monolayer and suspension cell cultures with DESI-MSI of spheroids is a promising approach for identifying lipid biomarkers of specific genotypes and phenotypes, as well as elucidating the potential function of these biomarkers in breast cancer. Graphical Absract.

Lipid Heterogeneity between Astrocytes and Neurons Revealed by Single-Cell MALDI-MS Combined with Immunocytochemical Classification.

Transcriptomics characterizes cells based on their potential molecular repertoire whereas direct mass spectrometry (MS) provides information on the actual compounds present within cells. Single-cell matrix-assisted laser desorption/ionization (MALDI) MS can measure the chemical contents of individual cells but spectra are difficult to correlate to conventional cell types, limiting the metabolic information obtained. We present a protocol that combines MALDI-MS with immunocytochemistry to assay over a thousand individual rat brain cells. The approach entwines the wealth of knowledge obtained by immunocytochemical profiling with mass spectral information on the predominant lipids within each cell. While many lipid species showed a high degree of similarity between neurons and astrocytes, seventeen significantly differed between the two cell types, including four phosphatidylethanolamines elevated in astrocytes and nine phosphatidylcholines in neurons.

Exploring the Fundamental Structures of Life: Non-Targeted, Chemical Analysis of Single Cells and Subcellular Structures.

Cells are a basic functional and structural unit of living organisms. Both unicellular communities and multicellular species produce an astonishing chemical diversity, enabling a wide range of divergent functions, yet each cell shares numerous aspects that are common to all living organisms. While there are many approaches for studying this chemical diversity, only a few are non-targeted and capable of analyzing hundreds of different chemicals at cellular resolution. Here, we review the non-targeted approaches used to perform comprehensive chemical analyses, provide chemical imaging information, or obtain high-throughput single-cell profiling data. Single-cell measurement capabilities are rapidly increasing in terms of throughput, limits of detection, and completeness of the chemical analyses; these improvements enable their application to understand ever more complex physiological phenomena, such as learning, memory, and behavior.

Multimodal Chemical Analysis of the Brain by High Mass Resolution Mass Spectrometry and Infrared Spectroscopic Imaging.

The brain functions through chemical interactions between many different cell types, including neurons and glia. Acquiring comprehensive information on complex, heterogeneous systems requires multiple analytical tools, each of which have unique chemical specificity and spatial resolution. Multimodal imaging generates complementary chemical information via spatially localized molecular maps, ideally from the same sample, but requires method enhancements that span from data acquisition to interpretation. We devised a protocol for performing matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance-mass spectrometry imaging (MSI), followed by infrared (IR) spectroscopic imaging on the same specimen. Multimodal measurements from the same tissue provide precise spatial alignment between modalities, enabling more advanced image processing such as image fusion and sharpening. Performing MSI first produces higher quality data from each technique compared to performing IR imaging before MSI. The difference is likely due to fixing the tissue section during MALDI matrix removal, thereby preventing analyte degradation occurring during IR imaging from an unfixed specimen. Leveraging the unique capabilities of each modality, we utilized pan sharpening of MS (mass spectrometry) ion images with selected bands from IR spectroscopy and midlevel data fusion. In comparison to sharpening with histological images, pan sharpening can employ a plethora of IR bands, producing sharpened MS images while retaining the fidelity of the initial ion images. Using Laplacian pyramid sharpening, we determine the localization of several lipids present within the hippocampus with high mass accuracy at 5 µm pixel widths. Further, through midlevel data fusion of the imaging data sets combined with k-means clustering, the combined data set discriminates between additional anatomical structures unrecognized by the individual imaging approaches. Significant differences between molecular ion abundances are detected between relevant structures within the hippocampus, such as the CA1 and CA3 regions. Our methodology provides high quality multiplex and multimodal chemical imaging of the same tissue sample, enabling more advanced data processing and analysis routines.

Optically Guided Single Cell Mass Spectrometry of Rat Dorsal Root Ganglia to Profile Lipids, Peptides and Proteins.

The mammalian dorsal root ganglia (DRG) are located on the dorsal roots of the spinal nerves and contain cell bodies of primary sensory neurons. DRG cells have been classified into subpopulations based on their size, morphology, intracellular markers, response to stimuli, and neuropeptides. To understand the connections between DRG chemical heterogeneity and cellular function, we performed optically guided, high-throughput single cell profiling using sequential matrix-assisted laser desorption/ionization mass spectrometry (MS) to detect lipids, peptides, and several proteins in individual DRG cells. Statistical analysis of the resulting mass spectra allows stratification of the DRG population according to cellular morphology and, presumably, major cell types. A subpopulation of small cells contained myelin proteins, which are abundant in Schwann cells, and mass spectra of several larger cells contained peaks matching neurofilament, vimentin, myelin basic protein S, and thymosin beta proteins. Of the over 1000 cells analyzed, approximately 78 % produced putative peptide-rich spectra, allowing the population to be classified into three distinct cell types. Two signals with m/z 4404 and 5487 were exclusively observed in a cell type, but could not be matched to results of our previous liquid chromatography-MS analyses.

Profiling of Microbial Colonies for High-Throughput Engineering of Multistep Enzymatic Reactions via Optically Guided Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry.

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) mass spectrometry (MS) imaging has been used for rapid phenotyping of enzymatic activities, but is mainly limited to single-step conversions. Herein we report a label-free method for high-throughput engineering of multistep biochemical reactions based on optically guided MALDI-ToF MS analysis of bacterial colonies. The bacterial cells provide containment of multiple enzymes and access to substrates and cofactors via metabolism. Automated MALDI-ToF MS acquisition from randomly distributed colonies simplifies procedures to prepare strain libraries without liquid handling. MALDI-ToF MS profiling was utilized to screen both substrate and enzyme libraries for natural product biosynthesis. Computational algorithms were developed to process and visualize the resulting mass spectral data sets. For analogues of the peptidic antibiotic plantazolicin, multivariate analyses by t-distributed stochastic neighbor embedding were used to group similar spectra for rapid identification of nonisobaric variants. After MALDI-ToF MS screening, follow-up analyses using high-resolution MS and tandem MS were readily performed on the same sample target. Separately, relative ion intensities of rhamnolipid congeners with various lipid moieties were evaluated to engineer enzymatic specificity. The glycolipid profiles of each colony were overlaid with optical images to facilitate the recovery of desirable mutants. For both the antibiotic and rhamnolipid cases, large populations of colonies were rapidly surveyed at the molecular level, providing information-rich insights not easily obtained with traditional screening assays. Utilizing standard microbiological techniques with routine microscopy and MALDI-ToF MS instruments, this simple yet effective workflow is applicable for a wide range of screening campaigns targeting multistep enzymatic reactions.

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling.

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. Graphical Abstract ᅟ.

MALDI MS Guided Liquid Microjunction Extraction for Capillary Electrophoresis-Electrospray Ionization MS Analysis of Single Pancreatic Islet Cells.

The ability to characterize chemical heterogeneity in biological structures is essential to understanding cellular-level function in both healthy and diseased states, but these variations remain difficult to assess using a single analytical technique. While mass spectrometry (MS) provides sufficient sensitivity to measure many analytes from volume-limited samples, each type of mass spectrometric analysis uncovers only a portion of the complete chemical profile of a single cell. Matrix-assisted laser desorption/ionization (MALDI) MS and capillary electrophoresis electrospray ionization (CE-ESI)-MS are complementary analytical platforms frequently utilized for single-cell analysis. Optically guided MALDI MS provides a high-throughput assessment of lipid and peptide content for large populations of cells, but is typically nonquantitative and fails to detect many low-mass metabolites because of MALDI matrix interferences. CE-ESI-MS allows quantitative measurements of cellular metabolites and increased analyte coverage, but has lower throughput because the electrophoretic separation is relatively slow. In this work, the figures of merit for each technique are combined via an off-line method that interfaces the two MS systems with a custom liquid microjunction surface sampling probe. The probe is mounted on an xyz translational stage, providing 90.6 ± 0.6% analyte removal efficiency with a spatial targeting accuracy of 42.8 ± 2.3 µm. The analyte extraction footprint is an elliptical area with a major diameter of 422 ± 21 µm and minor diameter of 335 ± 27 µm. To validate the approach, single rat pancreatic islet cells were rapidly analyzed with optically guided MALDI MS to classify each cell into established cell types by their peptide content. After MALDI MS analysis, a majority of the analyte remains for follow-up measurements to extend the overall chemical coverage. Optically guided MALDI MS was used to identify individual pancreatic islet α and ß cells, which were then targeted for liquid microjunction extraction. Extracts from single α and ß cells were analyzed with CE-ESI-MS to obtain qualitative information on metabolites, including amino acids. Matching the molecular masses and relative migration times of the extracted analytes and related standards allowed identification of several amino acids. Interestingly, dopamine was consistently detected in both cell types. The results demonstrate the successful interface of optical microscopy-guided MALDI MS and CE-ESI-MS for sequential chemical profiling of individual, mammalian cells.

Single Cell Profiling Using Ionic Liquid Matrix-Enhanced Secondary Ion Mass Spectrometry for Neuronal Cell Type Differentiation.

A high-throughput single cell profiling method has been developed for matrix-enhanced-secondary ion mass spectrometry (ME-SIMS) to investigate the lipid profiles of neuronal cells. Populations of cells are dispersed onto the substrate, their locations determined using optical microscopy, and the cell locations used to guide the acquisition of SIMS spectra from the cells. Up to 2,000 cells can be assayed in one experiment at a rate of 6 s per cell. Multiple saturated and unsaturated phosphatidylcholines (PCs) and their fragments are detected and verified with tandem mass spectrometry from individual cells when ionic liquids are employed as a matrix. Optically guided single cell profiling with ME-SIMS is suitable for a range of cell sizes, from Aplysia californica neurons larger than 75 µm to 7-µm rat cerebellar neurons. ME-SIMS analysis followed by t-distributed stochastic neighbor embedding of peaks in the lipid molecular mass range (m/z 700-850) distinguishes several cell types from the rat central nervous system, largely based on the relative proportions of four dominant lipids, PC(32:0), PC(34:1), PC(36:1), and PC(38:5). Furthermore, subpopulations within each cell type are tentatively classified consistent with their endogenous lipid ratios. The results illustrate the efficacy of a new approach to classify single cell populations and subpopulations using SIMS profiling of lipid and metabolite contents. These methods are broadly applicable for high throughput single cell chemical analyses.

Categorizing Cells on the Basis of their Chemical Profiles: Progress in Single-Cell Mass Spectrometry.

The chemical differences between individual cells within large cellular populations provide unique information on organisms' homeostasis and the development of diseased states. Even genetically identical cell lineages diverge due to local microenvironments and stochastic processes. The minute sample volumes and low abundance of some constituents in cells hinder our understanding of cellular heterogeneity. Although amplification methods facilitate single-cell genomics and transcriptomics, the characterization of metabolites and proteins remains challenging both because of the lack of effective amplification approaches and the wide diversity in cellular constituents. Mass spectrometry has become an enabling technology for the investigation of individual cellular metabolite profiles with its exquisite sensitivity, large dynamic range, and ability to characterize hundreds to thousands of compounds. While advances in instrumentation have improved figures of merit, acquiring measurements at high throughput and sampling from large populations of cells are still not routine. In this Perspective, we highlight the current trends and progress in mass-spectrometry-based analysis of single cells, with a focus on the technologies that will enable the next generation of single-cell measurements.

Enhanced Temporal Resolution with Ion Channel-Functionalized Sensors Using a Conductance-Based Measurement Protocol.

The binding of a target analyte to an ion channel (IC), which is readily detected electrochemically in a label-free manner with single-molecule selectivity and specificity, has generated widespread interest in using natural and engineered ICs as transducers in biosensing platforms. To date, the majority of developments in IC-functionalized sensing have focused on IC selectivity or sensitivity or development of suitable membrane environments and aperture geometries. Comparatively little work has addressed analytical performance criteria, particularly criteria required for temporal measurements of dynamic processes. We report a measurement protocol suitable for rapid, time-resolved monitoring (≤30 ms) of IC-modulated membrane conductance. Key features of this protocol include the reduction of membrane area and the use of small voltage steps (10 mV) and short duration voltage pulses (10 ms), which have the net effect of reducing the capacitive charging and decreasing the time required to achieve steady state currents. Application of a conductance protocol employing three sequential, 10 ms voltage steps (-10 mV, -20 mV, -30 mV) in an alternating, pyramid-like arrangement enabled sampling of membrane conductance every 30 ms. Using this protocol, dynamic IC measurements on black lipid membranes (BLMs) functionalized with gramicidin A were conducted using a fast perfusion system. BLM conductance decreased by 76 ± 7.5% within 30 ms of switching from solutions containing 0 to 1 M Ca2+, which demonstrates the feasibility of using this approach to monitor rapid, dynamic chemical processes. Rapid conductance measurements will be broadly applicable to IC-based sensors that undergo analyte-specific gating.

A one-step matrix application method for MALDI mass spectrometry imaging of bacterial colony biofilms.

Matrix-assisted laser desorption/ionization imaging of biofilms cultured on agar plates is challenging because of problems related to matrix deposition onto agar. We describe a one-step, spray-based application of a 2,5-dihydroxybenzoic acid solution for direct matrix-assisted laser desorption/ionization imaging of hydrated Bacillus subtilis biofilms on agar. Using both an optimized airbrush and a home-built automatic sprayer, region-specific distributions of signaling metabolites and cannibalistic factors were visualized from B. subtilis cells cultivated on biofilm-promoting medium. The approach provides a homogeneous, relatively dry coating on hydrated samples, improving spot to spot signal repeatability compared with sieved matrix application, and is easily adapted for imaging a range of agar-based biofilms. Copyright © 2016 John Wiley & Sons, Ltd.

Single Cell Peptide Heterogeneity of Rat Islets of Langerhans.

Measuring the chemical composition of individual cells in mammalian organs can provide critical insights toward understanding the mechanisms leading to their normal and pathological function. In this work, single cell heterogeneity of islets of Langerhans is characterized with high throughput by microscopy-guided single cell matrix-assisted laser desorption/ionization mass spectrometry. Two levels of chemical heterogeneity were observed from the analysis of more than 3000 individual cells. Within a single islet, cellular heterogeneity was evident from the exclusive expression of the canonical biomarkers glucagon, insulin, pancreatic polypeptide (PP), and somatostatin within α-, ß-, γ-, and δ-cells, respectively. We localized the neuropeptide WE-14, a known cell-to-cell signaling molecule, to individual δ-cells. Moreover, several unreported endogenous peptides generated by dibasic site cleavages of PP were detected within individual γ-cells. Of these, PP(27-36) was previously shown to activate the human Y4 receptor, suggesting it has a signaling role in vivo. Heterogeneity in cell composition was also observed between islets as evidenced by a 50-fold larger α-cell population in islets of the dorsal pancreas compared to the ventral-derived pancreatic islets. Finally, PP(27-36) was more abundant in γ-cells from the ventral region of the pancreas, indicating differences in the extent of PP-prohormone processing in the two regions of the pancreas.

On-Tissue Derivatization via Electrospray Deposition for Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging of Endogenous Fatty Acids in Rat Brain Tissues.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is used for the multiplex detection and characterization of diverse analytes over a wide mass range directly from tissues. However, analyte coverage with MALDI MSI is typically limited to the more abundant compounds, which have m/z values that are distinct from MALDI matrix-related ions. On-tissue analyte derivatization addresses these issues by selectively tagging functional groups specific to a class of analytes, while simultaneously changing their molecular masses and improving their desorption and ionization efficiency. We evaluated electrospray deposition of liquid-phase derivatization agents as a means of on-tissue analyte derivatization using 2-picolylamine; we were able to detect a range of endogenous fatty acids with MALDI MSI. When compared with airbrush application, electrospray led to a 3-fold improvement in detection limits and decreased analyte delocalization. Six fatty acids were detected and visualized from rat cerebrum tissue using a MALDI MSI instrument operating in positive mode. MALDI MSI of the hippocampal area allowed targeted fatty acid analysis of the dentate gyrus granule cell layer and the CA1 pyramidal layer with a 20-µm pixel width, without degrading the localization of other lipids during liquid-phase analyte derivatization.

Metal-assisted polyatomic SIMS and laser desorption/ionization for enhanced small molecule imaging of bacterial biofilms.

Mass spectrometry imaging (MSI) has become an important analytical tool for many sectors of science and medicine. As the application of MSI expands into new areas of inquiry, existing methodologies must be adapted and improved to meet emerging challenges. Particularly salient is the need for small molecule imaging methods that are compatible with complex multicomponent systems, a challenge that is amplified by the effects of analyte migration and matrix interference. With a focus on microbial biofilms from the opportunistic pathogen Pseudomonas aeruginosa, the relative advantages of two established microprobe-based MSI techniques-polyatomic secondary ion mass spectrometry (SIMS) and laser desorption/ionization-are compared, with emphasis on exploring the effect of surface metallization on small molecule imaging. A combination of qualitative image comparison and multivariate statistical analysis demonstrates that sputtering microbial biofilms with a 2.5 nm layer of gold selectively enhances C60-SIMS ionization for several molecular classes including rhamnolipids and 2-alkyl-quinolones. Metallization also leads to the reduction of in-source fragmentation and subsequent ionization of media-specific background polymers, which improves spectral purity and image quality. These findings show that the influence of metallization upon ionization is strongly dependent on both the surface architecture and the analyte class, and further demonstrate that metal-assisted C60-SIMS is a viable method for small molecule imaging of intact molecular ions in complex biological systems.

Photopolymerization of Dienoyl Lipids Creates Planar Supported Poly(lipid) Membranes with Retained Fluidity.

Polymerization of substrate-supported bilayers composed of dienoylphosphatidylcholine (PC) lipids is known to greatly enhance their chemical and mechanical stability; however, the effects of polymerization on membrane fluidity have not been investigated. Here planar supported lipid bilayers (PSLBs) composed of dienoyl PCs on glass substrates were examined to assess the degree to which UV-initiated polymerization affects lateral lipid mobility. Fluorescence recovery after photobleaching (FRAP) was used to measure the diffusion coefficients (D) and mobile fractions of rhodamine-DOPE in unpolymerized and polymerized PSLBs composed of bis-sorbyl phosphatidylcholine (bis-SorbPC), mono-sorbyl-phosphatidylcholine (mono-SorbPC), bis-dienoyl-phosphatidylcholine (bis-DenPC), and mono-dienoyl phosphatidylcholine (mono-DenPC). Polymerization was performed in both the Lα and Lß phase for each lipid. In all cases, polymerization reduced membrane fluidity; however, measurable lateral diffusion was retained which is attributed to a low degree of polymerization. The D values for sorbyl lipids were less than those of the denoyl lipids; this may be a consequence of the distal location of polymerizable group in the sorbyl lipids which may facilitate interleaflet bonding. The D values measured after polymerization were 0.1-0.8 of those measured before polymerization, a range that corresponds to fluidity intermediate between that of a Lα phase and a Lß phase. This D range is comparable to ratios of D values reported for liquid-disordered (Ld) and liquid-ordered (Lo) lipid phases and indicates that the effect of UV polymerization on lateral diffusion in a dienoyl PSLB is similar to the transition from a Ld phase to a Lo phase. The partial retention of fluidity in UV-polymerized PSLBs, their enhanced stability, and the activity of incorporated transmembrane proteins and peptides is discussed.

Synchronized Desorption Electrospray Ionization Mass Spectrometry Imaging.

Desorption electrospray ionization (DESI) has emerged as a powerful technique for mass spectral analysis and imaging under ambient conditions. Synchronization of DESI (sDESI) with the ion injection period (IT)of low-duty cycle mass spectrometers has been previously shown to improve sensitivity and reduce the amount of sample depleted during the acquisition of each spectrum (viz. MS scan time). In this report, we describe the development and characterization of an sDESI mass spectrometry imaging source (sDESI-MSI). Our results show that synchronization of DESI with the IT of an LTQ Orbitrap-XL mass spectrometer improves spatial resolution by factors of ∼4-6. In addition, under certain experimental conditions, synchronization was essential to acquire distinct MS images of low-intensity endogenous FAs (< 5% relative intensity) in fingermarks at high sampling frequencies (step sizes ≤ 75 µm). The magnitudes of these improvements in performance depend on the properties of the microdroplet spray, sample, and surface. Simulations that model analyte movement during desorption and the "washing effect" replicate the experimental results with the washing parameter having the greatest impact on performance. Thus, synchronization improves spatial resolution and sensitivity by decreasing the percentage of the total MS scan time that analytes are influenced by the "washing effect". Generally, synchronization of DESI with IT improves performance and expands the range of analytes, surfaces, and experimental conditions amenable to DESI-MSI, especially for analytes that are weakly attached to a surface.

Classification of Large Cellular Populations and Discovery of Rare Cells Using Single Cell Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry.

Cell-to-cell variability and functional heterogeneity are integral features of multicellular organisms. Chemical classification of cells into cell type is important for understanding cellular specialization as well as organismal function and organization. Assays to elucidate these chemical variations are best performed with single cell samples because tissue homogenates average the biochemical composition of many different cells and oftentimes include extracellular components. Several single cell microanalysis techniques have been developed but tend to be low throughput or require preselection of molecular probes that limit the information obtained. Mass spectrometry (MS) is an untargeted, multiplexed, and sensitive analytical method that is well-suited for studying chemically complex individual cells that have low analyte content. In this work, populations of cells from the rat pituitary, the rat pancreatic islets of Langerhans, and from the Aplysia californica nervous system, are classified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI) MS by their peptide content. Cells were dispersed onto a microscope slide to generate a sample where hundreds to thousands of cells were separately located. Optical imaging was used to determine the cell coordinates on the slide, and these locations were used to automate the MS measurements to targeted cells. Principal component analysis was used to classify cellular subpopulations. The method was modified to focus on the signals described by the lower principal components to explore rare cells having a unique peptide content. This approach efficiently uncovers and classifies cellular subtypes as well as discovers rare cells from large cellular populations.