Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform.

Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

Hanging drop sample preparation improves sensitivity of spatial proteomics.

Spatial proteomics holds great promise for revealing tissue heterogeneity in both physiological and pathological conditions. However, one significant limitation of most spatial proteomics workflows is the requirement of large sample amounts that blurs cell-type-specific or microstructure-specific information. In this study, we developed an improved sample preparation approach for spatial proteomics and integrated it with our previously-established laser capture microdissection (LCM) and microfluidics sample processing platform. Specifically, we developed a hanging drop (HD) method to improve the sample recovery by positioning a nanowell chip upside-down during protein extraction and tryptic digestion steps. Compared with the commonly-used sitting-drop method, the HD method keeps the tissue pixel away from the container surface, and thus improves the accessibility of the extraction/digestion buffer to the tissue sample. The HD method can increase the MS signal by 7 fold, leading to a 66% increase in the number of identified proteins. An average of 721, 1489, and 2521 proteins can be quantitatively profiled from laser-dissected 10 µm-thick mouse liver tissue pixels with areas of 0.0025, 0.01, and 0.04 mm2, respectively. The improved system was further validated in the study of cell-type-specific proteomes of mouse uterine tissues.

De novo sequencing and native mass spectrometry revealed hetero-association of dirigent protein homologs and potential interacting proteins in Forsythia × intermedia.

The discovery of dirigent proteins (DPs) and their functions in plant phenol biochemistry was made over two decades ago with Forsythia × intermedia. Stereo-selective, DP-guided, monolignol-derived radical coupling in vitro was then reported to afford the optically active lignan, (+)-pinoresinol from coniferyl alcohol, provided one-electron oxidase/oxidant capacity was present. It later became evident that DPs have several distinct sub-families, presumably with different functions. Some known DPs require other essential enzymes/proteins (e.g. oxidases) for their functions. However, the lack of a fully sequenced genome for Forsythia × intermedia made it difficult to profile other components co-purified with the (+)-pinoresinol forming DP. Herein, we used an integrated bottom-up, top-down, and native mass spectrometry (MS) approach to de novo sequence the extracted proteins via adaptation of our initial report of DP solubilization and purification. Using publicly available transcriptome and genomic data from closely related species, we identified 14 proteins that were putatively associated with either DP function or the cell wall. Although their co-occurrence after extraction and chromatographic separation is suggestive for potential protein-protein interactions, none were found to form stable protein complexes with DPs in native MS under the specific experimental conditions we have explored. Interestingly, two new DP homologs were found and they formed hetero-trimers. Molecular dynamics simulations suggested that similar hetero-trimers were possible between Arabidopsis DP homologs with comparable sequence similarities. Nevertheless, our integrated mass spectrometry method development helped prepare for future investigations directed to the discovery of novel proteins and protein-protein interactions. These advantages can be highly beneficial for plant and microbial research where fully sequenced genomes may not be readily available.

High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip.

Global quantification of protein abundances in single cells could provide direct information on cellular phenotypes and complement transcriptomics measurements. However, single-cell proteomics is still immature and confronts many technical challenges. Herein we describe a nested nanoPOTS (N2) chip to improve protein recovery, operation robustness, and processing throughput for isobaric-labeling-based scProteomics workflow. The N2 chip reduces reaction volume to <30 nL and increases capacity to >240 single cells on a single microchip. The tandem mass tag (TMT) pooling step is simplified by adding a microliter droplet on the nested nanowells to combine labeled single-cell samples. In the analysis of ~100 individual cells from three different cell lines, we demonstrate that the N2 chip-based scProteomics platform can robustly quantify ~1500 proteins and reveal membrane protein markers. Our analyses also reveal low protein abundance variations, suggesting the single-cell proteome profiles are highly stable for the cells cultured under identical conditions.

Facile One-Pot Nanoproteomics for Label-Free Proteome Profiling of 50-1000 Mammalian Cells.

Recent advances in sample preparation enable label-free mass spectrometry (MS)-based proteome profiling of small numbers of mammalian cells. However, specific devices are often required to downscale sample processing volume from the standard 50-200 µL to sub-µL for effective nanoproteomics, which greatly impedes the implementation of current nanoproteomics methods by the proteomics research community. Herein, we report a facile one-pot nanoproteomics method termed SOPs-MS (surfactant-assisted one-pot sample processing at the standard volume coupled with MS) for convenient robust proteome profiling of 50-1000 mammalian cells. Building upon our recent development of SOPs-MS for label-free single-cell proteomics at a low µL volume, we have systematically evaluated its processing volume at 10-200 µL using 100 human cells. The processing volume of 50 µL that is in the range of volume for standard proteomics sample preparation has been selected for easy sample handling with a benchtop micropipette. SOPs-MS allows for reliable label-free quantification of ∼1200-2700 protein groups from 50 to 1000 MCF10A cells. When applied to small subpopulations of mouse colon crypt cells, SOPs-MS has revealed protein signatures between distinct subpopulation cells with identification of ∼1500-2500 protein groups for each subpopulation. SOPs-MS may pave the way for routine deep proteome profiling of small numbers of cells and low-input samples.

MetFish: a Metabolomics Pipeline for Studying Microbial Communities in Chemically Extreme Environments.

Metabolites have essential roles in microbial communities, including as mediators of nutrient and energy exchange, cell-to-cell communication, and antibiosis. However, detecting and quantifying metabolites and other chemicals in samples having extremes in salt or mineral content using liquid chromatography-mass spectrometry (LC-MS)-based methods remains a significant challenge. Here, we report a facile method based on in situ chemical derivatization followed by extraction for analysis of metabolites and other chemicals in hypersaline samples, enabling for the first time direct LC-MS-based exometabolomics analysis in sample matrices containing up to 2 M total dissolved salts. The method, MetFish, is applicable to molecules containing amine, carboxylic acid, carbonyl, or hydroxyl functional groups, and it can be integrated into either targeted or untargeted analysis pipelines. In targeted analyses, MetFish provided limits of quantification as low as 1 nM, broad linear dynamic ranges (up to 5 to 6 orders of magnitude) with excellent linearity, and low median interday reproducibility (e.g., 2.6%). MetFish was successfully applied in targeted and untargeted exometabolomics analyses of microbial consortia, quantifying amino acid dynamics in the exometabolome during community succession; in situ in a native prairie soil, whose exometabolome was isolated using a hypersaline extraction; and in input and produced fluids from a hydraulically fractured well, identifying dramatic changes in the exometabolome over time in the well. IMPORTANCE The identification and accurate quantification of metabolites using electrospray ionization-mass spectrometry (ESI-MS) in hypersaline samples is a challenge due to matrix effects. Clean-up and desalting strategies that typically work well for samples with lower salt concentrations are often ineffective in hypersaline samples. To address this gap, we developed and demonstrated a simple yet sensitive and accurate method-MetFish-using chemical derivatization to enable mass spectrometry-based metabolomics in a variety of hypersaline samples from varied ecosystems and containing up to 2 M dissolved salts.

Physiologically Based Pharmacokinetic Modeling of Salivary Concentrations for Noninvasive Biomonitoring of 2,4-Dichlorophenoxyacetic Acid (2,4-D).

Saliva has become a favorable sample matrix for biomonitoring due to its noninvasive attributes and overall flexibility in collection. To ensure measured salivary concentrations reflect the exposure, a solid understanding of the salivary transport mechanism and relationships between salivary concentrations and other monitored matrices (ie, blood, urine) is needed. Salivary transport of a commonly applied herbicide, 2,4-dichlorophenoxyacetic acid (2,4-D), was observed in vitro and in vivo and a physiologically based pharmacokinetic (PBPK) model was developed to translate observations from the cell culture model to those in animal models and further evaluate 2,4-D kinetics in humans. Although apparent differences in experimental in vitro and in vivo saliva:plasma ratios (0.034 and 0.0079) were observed, simulations with the PBPK model demonstrated dynamic time and dose-dependent saliva:plasma ratios, elucidating key mechanisms affecting salivary transport. The model suggested that 2,4-D exhibited diffusion-limited transport to saliva and was additionally impacted by protein binding saturation and permeability across the salivary gland. Consideration of sampling times post-exposure and potential saturation of transport mechanisms are then critical aspects for interpreting salivary 2,4-D biomonitoring observations. This work utilized PBPK modeling in in vitro to in vivo translation to explore benefits and limitations of salivary analysis for occupational biomonitoring.

High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform.

Effective extension of mass spectrometry-based proteomics to single cells remains challenging. Herein we combined microfluidic nanodroplet technology with tandem mass tag (TMT) isobaric labeling to significantly improve analysis throughput and proteome coverage for single mammalian cells. Isobaric labeling facilitated multiplex analysis of single cell-sized protein quantities to a depth of ∼1 600 proteins with a median CV of 10.9% and correlation coefficient of 0.98. To demonstrate in-depth high throughput single cell analysis, the platform was applied to measure protein expression in 72 single cells from three murine cell populations (epithelial, immune, and endothelial cells) in <2 days instrument time with over 2 300 proteins identified. Principal component analysis grouped the single cells into three distinct populations based on protein expression with each population characterized by well-known cell-type specific markers. Our platform enables high throughput and unbiased characterization of single cell heterogeneity at the proteome level.

Lipid Coverage in Nanospray Desorption Electrospray Ionization Mass Spectrometry Imaging of Mouse Lung Tissues.

Lipids are a naturally occurring group of molecules that not only contribute to the structural integrity of the lung preventing alveolar collapse but also play important roles in the anti-inflammatory responses and antiviral protection. Alteration in the type and spatial localization of lipids in the lung plays a crucial role in various diseases, such as respiratory distress syndrome (RDS) in preterm infants and oxidative stress-influenced diseases, such as pneumonia, emphysema, and lung cancer following exposure to environmental stressors. The ability to accurately measure spatial distributions of lipids and metabolites in lung tissues provides important molecular insights related to lung function, development, and disease states. Nanospray desorption electrospray ionization (nano-DESI) and other ambient ionization mass spectrometry techniques enable label-free imaging of complex samples in their native state with minimal to absolutely no sample preparation. However, lipid coverage obtained in nano-DESI mass spectrometry imaging (MSI) experiments has not been previously characterized. In this work, the depth of lipid coverage in nano-DESI MSI of mouse lung tissues was compared to liquid chromatography tandem mass spectrometry (LC-MS/MS) lipidomics analysis of tissue extracts prepared using two different procedures: standard Folch extraction method of the whole lung samples and extraction into a 90% methanol/10% water mixture used in nano-DESI MSI experiments. A combination of positive and negative ionization mode nano-DESI MSI identified 265 unique lipids across 20 lipids subclasses and 19 metabolites (284 in total) in mouse lung tissues. Except for triacylglycerols (TG) species, nano-DESI MSI provided comparable coverage to LC-MS/MS experiments performed using methanol/water tissue extracts and up to 50% coverage in comparison with the Folch extraction-based whole lung lipidomics analysis. These results demonstrate the utility of nano-DESI MSI for comprehensive spatially resolved analysis of lipids in tissue sections. A combination of nano-DESI MSI and LC-MS/MS lipidomics is particularly useful for exploring changes in lipid distributions during lung development, as well as resulting from disease or exposure to environmental toxicants.

Spatial distribution of marker gene activity in the mouse lung during alveolarization.

This data is a curated collection of visual images of gene expression patterns from the pre- and post-natal mouse lung, accompanied by associated mRNA probe sequences and RNA-Seq expression profiles. Mammalian lungs undergo significant growth and cellular differentiation before and after the transition to breathing air. Documenting normal lung development is an important step in understanding abnormal lung development, as well as the challenges faced during a preterm birth. Images in this dataset indicate the spatial distribution of mRNA transcripts for over 500 different genes that are active during lung development, as initially determined via RNA-Seq. Images were systematically acquired using high-throughput in situ hybridization with non-radioactive digoxigenin-labeled mRNA probes across mouse lungs from developmental time points E16.5, E18.5, P7, and P28. The dataset was produced as part of The Molecular Atlas of Lung Development Program (LungMAP) and is hosted at https://lungmap.net. This manuscript describes the nature of the data and the protocols for generating the dataset.

Preconditioning in the Rhesus Macaque Induces a Proteomic Signature Following Cerebral Ischemia that Is Associated with Neuroprotection.

Each year, thousands of patients are at risk of cerebral ischemic injury, due to iatrogenic responses to surgical procedures. Prophylactic treatment of these patients as standard care could minimize potential neurological complications. We have shown that protection of brain tissue, in a non-human primate model of cerebral ischemic injury, is possible through pharmacological preconditioning using the immune activator D192935. We postulate that preconditioning with D192935 results in neuroprotective reprogramming that is evident in the brain following experimentally induced cerebral ischemia. We performed quantitative proteomic analysis of cerebral spinal fluid (CSF) collected post-stroke from our previously published efficacy study to determine whether CSF protein profiles correlated with induced protection. Four groups of animals were examined: naïve animals (no treatment or stroke); animals treated with vehicle prior to stroke; D192935 treated and stroked animals, further delineated into two groups, ones that were protected (small infarcts) and those that were not protected (large infarcts). We found that distinct protein clusters defined the protected and non-protected animal groups, with a 16-member cluster of proteins induced exclusively in D192935 protected animals. Seventy percent of the proteins induced in the protected animals have functions that would enhance neuroprotection and tissue repair, including several members associated with M2 macrophages, a macrophage phenotype shown to contribute to neuroprotection and repair during ischemic injury. These studies highlight the translational importance of CSF biomarkers in defining mechanism and monitoring responses to treatment in development of stroke therapeutics.

Benchtop-compatible sample processing workflow for proteome profiling of < 100 mammalian cells.

Extending proteomics to smaller samples can enable the mapping of protein expression across tissues with high spatial resolution and can reveal sub-group heterogeneity. However, despite the continually improving sensitivity of LC-MS instrumentation, in-depth profiling of samples containing low-nanogram amounts of protein has remained challenging due to analyte losses incurred during preparation and analysis. To address this, we recently developed nanodroplet processing in one pot for trace samples (nanoPOTS), a robotic/microfluidic platform that generates ready-to-analyze peptides from cellular material in ~200 nL droplets with greatly reduced sample losses. In combination with ultrasensitive LC-MS, nanoPOTS has enabled >3000 proteins to be confidently identified from as few as 10 cultured human cells and ~700 proteins from single cells. However, the nanoPOTS platform requires a highly skilled operator and a costly in-house-built robotic nanopipetting instrument. In this work, we sought to evaluate the extent to which the benefits of nanodroplet processing could be preserved when upscaling reagent dispensing volumes by a factor of 10 to those addressable by commercial micropipette. We characterized the resulting platform, termed microdroplet processing in one pot for trace samples (µPOTS), for the analysis of as few as ~25 cultured HeLa cells (4 ng total protein) or 50 µm square mouse liver tissue thin sections and found that ~1800 and ~1200 unique proteins were respectively identified with high reproducibility. The reduced equipment requirements should facilitate broad dissemination of nanoproteomics workflows by obviating the need for a capital-intensive custom liquid handling system.

Protein structural biology using cell-free platform from wheat germ.

One of the biggest bottlenecks for structural analysis of proteins remains the creation of high-yield and high-purity samples of the target protein. Cell-free protein synthesis technologies are powerful and customizable platforms for obtaining functional proteins of interest in short timeframes, while avoiding potential toxicity issues and permitting high-throughput screening. These methods have benefited many areas of genomic and proteomics research, therapeutics, vaccine development and protein chip constructions. In this work, we demonstrate a versatile and multiscale eukaryotic wheat germ cell-free protein expression pipeline to generate functional proteins of different sizes from multiple host organism and DNA source origins. We also report on a robust purification procedure, which can produce highly pure (> 98%) proteins with no specialized equipment required and minimal time invested. This pipeline successfully produced and analyzed proteins in all three major geometry formats used for structural biology including single particle analysis with electron microscopy, and both two-dimensional and three-dimensional protein crystallography. The flexibility of the wheat germ system in combination with the multiscale pipeline described here provides a new workflow for rapid production and purification of samples that may not be amenable to other recombinant approaches for structural characterization.

Evaluation of non-invasive biomonitoring of 2,4-Dichlorophenoxyacetic acid (2,4-D) in saliva.

The objective of this study was to evaluate the potential for non-invasive biomonitoring of 2,4-Dichlorophenoxyacetic acid (2,4-D) in saliva. Using an in vitro rat salivary gland epithelial cell (SGEC) system, a collection of experiments investigating chemical protein binding, temporal and directional transport, as well as competitive transport with para-aminohippuric acid (PAH), a substrate for renal organic anion transporters, was conducted to identify cellular transport parameters required to computationally model salivary transport of 2,4-D. Additionally, a physiological protein gradient was implemented to mimic physiologically relevant concentrations of protein in rat plasma and saliva, and under these conditions the transfer of 2,4-D was markedly slower, driven by increased protein binding (i.e. reduced free 2,4-D species available to cross salivary barrier). The rate of transfer was directly proportional to the amount of unbound 2,4-D and demonstrated no indication of active transport. An in vivo assessment of 2,4-D exposure in rats revealed non-linear protein binding in plasma, indicating saturated protein binding and increased levels of unbound 2,4-D species at higher doses. A strong correlation between 2,4-D concentrations in saliva and unbound 2,4-D in plasma was observed (Pearson correlation coefficient = 0.95). Saliva:plasma 2,4-D ratios measured in vivo (0.0079) were consistent within the linear protein binding range and expected 2,4-D levels from occupational exposures but were significantly different than ratios measured in vitro (physiological conditions) (0.034), possibly due to 2,4-D concentrations in saliva not being at equilibrium with 2,4-D concentrations in blood, as well as physiological features absent in in vitro settings (e.g. blood flow). We demonstrated that 2,4-D is consistently transported into saliva using both in vitro and in vivo models, making 2,4-D a potential candidate for human non-invasive salivary biomonitoring. Further work is needed to understand whether current sensor limits of detection are sufficient to measure occupationally relevant exposures.

Residual tissue repositories as a resource for population-based cancer proteomic studies.

BACKGROUND: Mass spectrometry-based proteomics has become a powerful tool for the identification and quantification of proteins from a wide variety of biological specimens. To date, the majority of studies utilizing tissue samples have been carried out on prospectively collected fresh frozen or optimal cutting temperature (OCT) embedded specimens. However, such specimens are often difficult to obtain, in limited in supply, and clinical information and outcomes on patients are inherently delayed as compared to banked samples. Annotated formalin fixed, paraffin embedded (FFPE) tumor tissue specimens are available for research use from a variety of tissue banks, such as from the surveillance, epidemiology and end results (SEER) registries' residual tissue repositories. Given the wealth of outcomes information associated with such samples, the reuse of archived FFPE blocks for deep proteomic characterization with mass spectrometry technologies would provide a valuable resource for population-based cancer studies. Further, due to the widespread availability of FFPE specimens, validation of specimen integrity opens the possibility for thousands of studies that can be conducted worldwide. METHODS: To examine the suitability of the SEER repository tissues for proteomic and phosphoproteomic analysis, we analyzed 60 SEER patient samples, with time in storage ranging from 7 to 32 years; 60 samples with expression proteomics and 18 with phosphoproteomics, using isobaric labeling. Linear modeling and gene set enrichment analysis was used to evaluate the impacts of collection site and storage time. RESULTS: All samples, regardless of age, yielded suitable protein mass after extraction for expression analysis and 18 samples yielded sufficient mass for phosphopeptide analysis. Although peptide, protein, and phosphopeptide identifications were reduced by 50, 20 and 76% respectively, from comparable OCT specimens, we found no statistically significant differences in protein quantitation correlating with collection site or specimen age. GSEA analysis of GO-term level measurements of protein abundance differences between FFPE and OCT embedded specimens suggest that the formalin fixation process may alter representation of protein categories in the resulting dataset. CONCLUSIONS: These studies demonstrate that residual FFPE tissue specimens, of varying age and collection site, are a promising source of protein for proteomic investigations if paired with rigorously verified mass spectrometry workflows.

Targeted brain proteomics uncover multiple pathways to Alzheimer's dementia.

OBJECTIVE: Previous gene expression analysis identified a network of coexpressed genes that is associated with ß-amyloid neuropathology and cognitive decline in older adults. The current work targeted influential genes in this network with quantitative proteomics to identify potential novel therapeutic targets. METHODS: Data came from 834 community-based older persons who were followed annually, died, and underwent brain autopsy. Uniform structured postmortem evaluations assessed the burden of ß-amyloid and other common age-related neuropathologies. Selected reaction monitoring quantified cortical protein abundance of 12 genes prioritized from a molecular network of aging human brain that is implicated in Alzheimer's dementia. Regression and linear mixed models examined the protein associations with ß-amyloid load and other neuropathological indices as well as cognitive decline over multiple years preceding death. RESULTS: Average age at death was 88.6 years. Overall, 349 participants (41.9%) had Alzheimer's dementia at death. A higher level of PLXNB1 abundance was associated with more ß-amyloid load (p = 1.0 × 10-7 ) and higher PHFtau tangle density (p = 2.3 × 10-7 ), and the association of PLXNB1 with cognitive decline is mediated by these known Alzheimer's disease pathologies. On the other hand, higher IGFBP5, HSPB2, and AK4 and lower ITPK1 levels were associated with faster cognitive decline, and, unlike PLXNB1, these associations were not fully explained by common neuropathological indices, suggesting novel mechanisms leading to cognitive decline. INTERPRETATION: Using targeted proteomics, this work identified cortical proteins involved in Alzheimer's dementia and begins to dissect two different molecular pathways: one affecting ß-amyloid deposition and another affecting resilience without a known pathological footprint. Ann Neurol 2018;83:78-88.

Towards High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry Coupled to Shear Force Microscopy.

Constant mode ambient mass spectrometry imaging (MSI) of tissue sections with high lateral resolution of better than 10 µm was performed by combining shear force microscopy with nanospray desorption electrospray ionization (nano-DESI). Shear force microscopy enabled precise control of the distance between the sample and nano-DESI probe during MSI experiments and provided information on sample topography. Proof-of-concept experiments were performed using lung and brain tissue sections representing spongy and dense tissues, respectively. Topography images obtained using shear force microscopy were comparable to the results obtained using contact profilometry over the same region of the tissue section. Variations in tissue height were found to be dependent on the tissue type and were in the range of 0-5 µm for lung tissue and 0-3 µm for brain tissue sections. Ion images of phospholipids obtained in this study are in good agreement with literature data. Normalization of nano-DESI MSI images to the signal of the internal standard added to the extraction solvent allowed us to construct high-resolution ion images free of matrix effects. Graphical Abstract ᅟ.

Lipidomics reveals dramatic lipid compositional changes in the maturing postnatal lung.

Lung immaturity is a major cause of morbidity and mortality in premature infants. Understanding the molecular mechanisms driving normal lung development could provide insights on how to ameliorate disrupted development. While transcriptomic and proteomic analyses of normal lung development have been previously reported, characterization of changes in the lipidome is lacking. Lipids play significant roles in the lung, such as dipalmitoylphosphatidylcholine in pulmonary surfactant; however, many of the roles of specific lipid species in normal lung development, as well as in disease states, are not well defined. In this study, we used liquid chromatography-mass spectrometry (LC-MS/MS) to investigate the murine lipidome during normal postnatal lung development. Lipidomics analysis of lungs from post-natal day 7, day 14 and 6-8 week mice (adult) identified 924 unique lipids across 21 lipid subclasses, with dramatic alterations in the lipidome across developmental stages. Our data confirmed previously recognized aspects of post-natal lung development and revealed several insights, including in sphingolipid-mediated apoptosis, inflammation and energy storage/usage. Complementary proteomics, metabolomics and chemical imaging corroborated these observations. This multi-omic view provides a unique resource and deeper insight into normal pulmonary development.

Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples.

Laser capture microdissection (LCM)-enabled region-specific tissue analyses are critical to better understand complex multicellular processes. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, impacting measurement robustness, quantification and throughput. Here, we coupled LCM with a proteomics workflow that provides fully automated analysis of proteomes from microdissected tissues. Benchmarking against the current state-of-the-art in ultrasensitive global proteomics (FASP workflow), our approach demonstrated significant improvements in quantification (~2-fold lower variance) and throughput (>5 times faster). Using our approach we for the first time characterized, to a depth of >3,400 proteins, the ontogeny of protein changes during normal lung development in microdissected alveolar tissue containing only 4,000 cells. Our analysis revealed seven defined modules of coordinated transcription factor-signaling molecule expression patterns, suggesting a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes.