Imaging mass spectrometry in microbiology

Imaging mass spectrometry tools allow the two-dimensional visualization of the distribution of trace metals, metabolites, surface lipids, peptides and proteins directly from biological samples without the need for chemical tagging or antibodies, and are becoming increasingly useful for microbiology applications. These tools, comprising different imaging mass spectrometry techniques, are ushering in an exciting new era of discovery by enabling the generation of chemical hypotheses based on the spatial mapping of atoms and molecules that can correlate to or transcend observed phenotypes. In this Innovation article, we explore the wide range of imaging mass spectrometry techniques that is available to microbiologists and describe the unique applications of these tools to microbiology with respect to the types of samples to be investigated.     

Imaging mass spectrometry for lipidomics

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a powerful tool that enables the simultaneous detection and identification of biomolecules in analytes. MALDI-imaging mass spectrometry (MALDI-IMS) is a two-dimensional MALDI-MS technique used to visualize the spatial distribution of biomolecules without extraction, purification, separation, or labeling of biological samples. This technique can reveal the distribution of hundreds of ion signals in a single measurement and also helps in understanding the cellular profile of the biological system. MALDI-IMS has already revealed the characteristic distribution of several kinds of lipids in various tissues. The versatility of MALDI-IMS has opened a new frontier in several fields, especially in lipidomics. In this review, we describe the methodology and applications of MALDI-IMS to biological samples.     

Imaging mass spectrometry statistical analysis

Imaging mass spectrometry is increasingly used to identify new candidate biomarkers. This clinical application of imaging mass spectrometry is highly multidisciplinary: expertise in mass spectrometry is necessary to acquire high quality data, histology is required to accurately label the origin of each pixel's mass spectrum, disease biology is necessary to understand the potential meaning of the imaging mass spectrometry results, and statistics to assess the confidence of any findings. Imaging mass spectrometry data analysis is further complicated because of the unique nature of the data (within the mass spectrometry field); several of the assumptions implicit in the analysis of LC-MS/profiling datasets are not applicable to imaging. The very large size of imaging datasets and the reporting of many data analysis routines, combined with inadequate training and accessible reviews, have exacerbated this problem. In this paper we provide an accessible review of the nature of imaging data and the different strategies by which the data may be analyzed. Particular attention is paid to the assumptions of the data analysis routines to ensure that the reader is apprised of their correct usage in imaging mass spectrometry research.     

Comparing cellular proteomes by mass spectrometry

Mass spectrometry and cryo-electron tomography together enable the determination of the absolute and relative abundances of proteins and their localization, laying the groundwork for comprehensive systems analyses of cells.     

Imaging mass spectrometry: principle and application

Imaging mass spectrometry (IMS) is two-dimensional mass spectrometry to visualize the spatial distribution of biomolecules, which does not need either separation or purification of target molecules, and enables us to monitor not only the identification of unknown molecules but also the localization of numerous molecules simultaneously. Among the ionization techniques, matrix assisted laser desorption/ionization (MALDI) is one of the most generally used for IMS, which allows the analysis of numerous biomolecules ranging over wide molecular weights. Proper selection and preparation of matrix is essential for successful imaging using IMS. Tandem mass spectrometry, which is referred to MSⁿ, enables the structural analysis of a molecule detected by the first step of IMS. Applications of IMS were initially developed for studying proteins or peptides. At present, however, targets of IMS research have expanded to the imaging of small endogenous metabolites such as lipids, exogenous drug pharmacokinetics, exploring new disease markers, and other new scientific fields. We hope that this new technology will open a new era for biophysics.     

Imaging lipids with secondary ion mass spectrometry

This review discusses the application of time-of-flight secondary ion mass spectrometry (TOF-SIMS) and magnetic sector SIMS with high lateral resolution performed on a Cameca NanoSIMS 50(L) to imaging lipids. The similarities between the two SIMS approaches and the differences that impart them with complementary strengths are described, and various strategies for sample preparation and to optimize the quality of the SIMS data are presented. Recent reports that demonstrate the new insight into lipid biochemistry that can be acquired with SIMS are also highlighted. This article is part of a Special Issue entitled Tools to study lipid functions.     

Probing neuropeptide signaling at the organ and cellular domains via imaging mass spectrometry

Imaging mass spectrometry (IMS) has evolved to be a promising technology due to its ability to detect a broad mass range of molecular species and create density maps for selected compounds. It is currently one of the most useful techniques to determine the spatial distribution of neuropeptides in cells and tissues. Although IMS is conceptually simple, sample preparation steps, mass analyzers, and software suites are just a few of the factors that contribute to the successful design of a neuropeptide IMS experiment. This review provides a brief overview of IMS sampling protocols, instrumentation, data analysis tools, technological advancements and applications to neuropeptide localization in neurons and endocrine tissues. Future perspectives in this field are also provided, concluding that neuropeptide IMS would greatly facilitate studies of neuronal network and biomarker discovery.     

Imaging of metabolites using secondary ion mass spectrometry

This article provides an overview of the technique of secondary ion mass spectrometry imaging and highlights some current and future areas of application relevant to the field of metabolomics. The approach benefits from label-free analysis of molecular species up to ~1500 Da with minimal sample preparation. Offering the highest spatial resolution of current mass spectrometry imaging methodologies, the technique is well-suited to metabolite imaging in both biological tissue and cells, in both 2D and 3D.

     

Imaging of metabolites using secondary ion mass spectrometry

This article provides an overview of the technique of secondary ion mass spectrometry imaging and highlights some current and future areas of application relevant to the field of metabolomics. The approach benefits from label-free analysis of molecular species up to ~1500 Da with minimal sample preparation. Offering the highest spatial resolution of current mass spectrometry imaging methodologies, the technique is well-suited to metabolite imaging in both biological tissue and cells, in both 2D and 3D.     

Imaging mass spectrometry in biomarker discovery and validation

Biomarker discovery and validation involves the consideration of many issues and challenges in order to be effectively used for translation from bench to bedside. Imaging mass spectrometry (IMS) is a new technology to assess spatial molecular arrangements in tissue sections, going far beyond microscopy in providing hundreds of different molecular images from a single scan without the need of target-specific reagents. The possibility to correlate distribution maps of multiple analytes with histological and clinical features makes it an ideal tool to discover diagnostic and prognostic markers of diseases. Some recently published studies that show the usefulness and advantages of this technology in the field of cancer research are highlighted.     

Salamander retina phospholipids and their localization by MALDI imaging mass spectrometry at cellular size resolution

Salamander large cells facilitated identification and localization of lipids by MALDI imaging mass spectrometry. Salamander retina lipid extract showed similarity with rodent retina lipid extract in phospholipid content and composition. Like rodent retina section, distinct layer distributions of phospholipids were observed in the salamander retina section. Phosphatidylcholines (PCs) composing saturated and monounsaturated fatty acids (PC 32:0, PC 32:1, and PC 34:1) were detected mainly in the outer and inner plexiform layers (OPL and IPL), whereas PCs containing polyunsaturated fatty acids (PC 36:4, PC 38:6, and PC 40:6) composed the inner segment (IS) and outer segment (OS). The presence of PCs containing polyunsaturated fatty acids in the OS layer implied that these phospholipids form flexible lipid bilayers, which facilitate phototransduction process occurring in the rhodopsin rich OS layer. Distinct distributions and relative signal intensities of phospholipids also indicated their relative abundance in a particular cell or a cell part. Using salamander large cells, a single cell level localization and identification of biomolecules could be achieved by MALDI imaging mass spectrometry.     

Structure prediction of helical transmembrane proteins at two length scales

As the first step toward a multi-scale, hierarchical computational approach for membrane protein structure prediction, the packing of transmembrane helices was modeled at the residue and atom levels, respectively. For predictions at the residue level, the helix-helix and helix-membrane interactions were described by a set of knowledge-based energy functions. For predictions at the atom level, CHARMM19 force field was used. To facilitate the system to overcome energy barriers, the Wang-Landau method was employed, where a random walk is performed in the energy space with a uniform probability. Native-like structures were predicted at both levels for two model systems, each of which consists of two transmembrane helices. Interestingly, consistent results were obtained from simulations at the residue and atom levels for the same system, strongly suggesting the feasibility of a hierarchical approach for membrane protein structure predictions.     

Imaging mass spectrometry of neuropeptides in decapod crustacean neuronal tissues

Imaging mass spectrometry (IMS) of neuropeptides in crustacean neuronal tissues was performed on a MALDI-TOF/TOF instrument. Sample preparation protocols were developed for the sensitive detection of these highly complex endogenous signaling molecules. The neuromodulatory complements of the pericardial organ (PO) and brain of the Jonah crab, Cancer borealis, were mapped. Distributions of peptide isoforms belonging to 10 neuropeptide families were investigated using the IMS technique. Often, neuropeptides of high sequence homology were similarly located. However, two RFamide-family peptides and a truncated orcokinin peptide were mapped to locations distinct from other members of their respective families. Over 30 previously sequenced neuropeptides were identified based on mass measurement. For increased confidence of identification, select peptides were fragmented by post-source decay (PSD) and collisional-induced dissociation (CID). Collectively, this organ-level IMS study elucidates the spatial relationships between multiple neuropeptide isoforms of the same family as well as the relative distributions of neuropeptide families.     

Biofilm engineering: linking biofilm development at different length and time scales

Biofilms are heterogeneous and dynamic systems. Evaluation of biofilm structure and function at the microscale has been greatly advanced through the application of multidimensional imaging, in-situ identification of the microbial community composition, function, and genetic regulation. Biofilm reactors are being applied for advanced biological treatment processes and their overall (macroscale) operation is well understood and controlled. What is missing is the link between micro and macroscale. In this horizon paper we suggest how understanding the overall biofilm ecosystem will require an integrated evaluation of the different length and time scales.     

Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales.     

Characterizing tumor response to chemotherapy at various length scales using temporal diffusion spectroscopy

Measurements of apparent diffusion coefficient (ADC) using magnetic resonance imaging (MRI) have been suggested as potential imaging biomarkers for monitoring tumor response to treatment. However, conventional pulsed-gradient spin echo (PGSE) methods incorporate relatively long diffusion times, and are usually sensitive to changes in cell density and necrosis. Diffusion temporal spectroscopy using the oscillating gradient spin echo (OGSE) sequence is capable of probing short length scales, and may detect significant intracellular microstructural changes independent of gross cell density changes following anti-cancer treatment. To test this hypothesis, SW620 xenografts were treated by barasertib (AZD1152), a selective inhibitor of Aurora B kinase which causes SW620 cancer cells to develop polyploidy and increase in size following treatment, ultimately leading to cell death through apoptosis. Following treatment, the ADC values obtained by both the PGSE and low frequency OGSE methods increased. However, the ADC values at high gradient frequency (i.e. short diffusion times) were significantly lower in treated tumors, consistent with increased intracellular restrictions/hindrances. This suggests that ADC values at long diffusion times are dominated by tumor microstructure at long length scales, and may not convey unambiguous information of subcellular space. While the diffusion temporal spectroscopy provides more comprehensive means to probe tumor microstructure at various length scales. This work is the first study to probe intracellular microstructural variations due to polyploidy following treatment using diffusion MRI in vivo. It is also the first observation of post-treatment ADC changes occurring in opposite directions at short and long diffusion times. The current study suggests that temporal diffusion spectroscopy potentially provides pharmacodynamic biomarkers of tumor early response which distinguish microstructural variations following treatment at both the subcellular and supracellular length scales.     

Imaging mass spectrometry of proteins and peptides: 3D volume reconstruction

As large genomic and proteomic datasets are generated from homogenates of various tissues, the need for information on the spatial localization of their encoded products has become more pressing. Matrix-assisted laser desorption-ionization (MALDI) imaging mass spectrometry (IMS) offers investigators the means with which to unambiguously study peptides and proteins with molecular specificity, and to determine their distribution in two and three dimensions. In the past few years, several parameters have been optimized for IMS, including sample preparation, matrix application and instrumental acquisition parameters (Box 1). These developments have resulted in a high degree of reproducibility in mass accuracy and peak intensities (Supplementary Fig. 1 online). Recently, we have optimized our protocol to be able to increase the number of molecular species analyzed by collecting two sets of sections, covering one set of sections with sinapinic acid for optimal detection of proteins and adjacent sections with 2,5-dihydroxybenzoic acid (DHB) matrix for the optimal detection of low-mass species, including peptides. Approximately 1,000 peaks can be observed in each dataset (Fig. 1). Furthermore, the sections are collected at an equal distance, 200 mum instead of 400-500 mum used previously, thus enabling the use of virtual z-stacks and three-dimensional (3D) volume renderings to investigate differential localization patterns in much smaller brain structures such as the substantia nigra and the interpeduncular nucleus. Here we present our optimized step-by-step procedure based on previous work in our laboratory, describing how to make 3D volume reconstructions of MALDI IMS data, as applied to the rat brain.