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Abstract Background The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. Results VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. Conclusions VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php.

Abstract Background Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. Results We experimentally annotated the bacterial pathogen Salmonella Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in Salmonella and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in Salmonella pathogenesis. We also characterized post-translational features in the Salmonella genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our in vivo proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function. Conclusion This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of Salmonella as a resource for systems analysis.

Background: Lipids are regulators of insulitis and β-cell death in type 1 diabetes development, but the underlying mechanisms are poorly understood. Here, we investigated how the islet lipid composition and downstream signaling regulate β-cell death., Methods: We performed lipidomics using three models of insulitis: human islets and EndoC-βH1 β cells treated with the pro-inflammatory cytokines interlukine-1β and interferon-γ, and islets from pre-diabetic non-obese mice. We also performed mass spectrometry and fluorescence imaging to determine the localization of lipids and enzyme in islets. RNAi, apoptotic assay, and qPCR were performed to determine the role of a specific factor in lipid-mediated cytokine signaling., Results: Across all three models, lipidomic analyses showed a consistent increase of lysophosphatidylcholine species and phosphatidylcholines with polyunsaturated fatty acids and a reduction of triacylglycerol species. Imaging assays showed that phosphatidylcholines with polyunsaturated fatty acids and their hydrolyzing enzyme phospholipase PLA2G6 are enriched in islets. In downstream signaling, omega-3 fatty acids reduce cytokine-induced β-cell death by improving the expression of ADP-ribosylhydrolase ARH3. The mechanism involves omega-3 fatty acid-mediated reduction of the histone methylation polycomb complex PRC2 component Suz12, upregulating the expression of Arh3, which in turn decreases cell apoptosis., Conclusions: Our data provide insights into the change of lipidomics landscape in β cells during insulitis and identify a protective mechanism by omega-3 fatty acids. Video Abstract., (© 2024. Battelle Memorial Institute.)

Type 1 diabetes (T1D) results from autoimmune destruction of β cells. Insufficient availability of biomarkers represents a significant gap in understanding the disease cause and progression. We conduct blinded, two-phase case-control plasma proteomics on the TEDDY study to identify biomarkers predictive of T1D development. Untargeted proteomics of 2,252 samples from 184 individuals identify 376 regulated proteins, showing alteration of complement, inflammatory signaling, and metabolic proteins even prior to autoimmunity onset. Extracellular matrix and antigen presentation proteins are differentially regulated in individuals who progress to T1D vs. those that remain in autoimmunity. Targeted proteomics measurements of 167 proteins in 6,426 samples from 990 individuals validate 83 biomarkers. A machine learning analysis predicts if individuals would remain in autoimmunity or develop T1D 6 months before autoantibody appearance, with areas under receiver operating characteristic curves of 0.871 and 0.918, respectively. Our study identifies and validates biomarkers, highlighting pathways affected during T1D development., Competing Interests: Declaration of interests The authors declare no competing interests., (Published by Elsevier Inc.)

Pulmonary alveolar microlithiasis is an autosomal recessive lung disease caused by a deficiency in the pulmonary epithelial Npt2b sodium-phosphate co-transporter that results in accumulation of phosphate and formation of hydroxyapatite microliths in the alveolar space. The single cell transcriptomic analysis of a pulmonary alveolar microlithiasis lung explant showing a robust osteoclast gene signature in alveolar monocytes and the finding that calcium phosphate microliths contain a rich protein and lipid matrix that includes bone resorbing osteoclast enzymes and other proteins suggested a role for osteoclast-like cells in the host response to microliths. While investigating the mechanisms of microlith clearance, we found that Npt2b modulates pulmonary phosphate homeostasis through effects on alternative phosphate transporter activity and alveolar osteoprotegerin, and that microliths induce osteoclast formation and activation in a receptor activator of nuclear factor-κB ligand and dietary phosphate dependent manner. This work reveals that Npt2b and pulmonary osteoclast-like cells play key roles in pulmonary homeostasis and suggest potential new therapeutic targets for the treatment of lung disease., (© 2023. The Author(s).)

Eukaryotic cells transit through the cell cycle to produce two daughter cells. Dysregulation of the cell cycle leads to cell death or tumorigenesis. Herein, we found a subunit of the ER membrane complex, EMC3, as a key regulator of cell cycle. Conditional deletion of Emc3 in mouse embryonic mesoderm led to reduced size and patterning defects of multiple organs. Emc3 deficiency impaired cell proliferation, causing spindle assembly defects, chromosome mis-segregation, cell cycle arrest at G2/M, and apoptosis. Upon entry into mitosis, mesenchymal cells upregulate EMC3 protein levels and localize EMC3 to the mitotic centrosomes. Further analysis indicated that EMC3 works together with VCP to tightly regulate the levels and activity of Aurora A, an essential factor for centrosome function and mitotic spindle assembly: while overexpression of EMC3 or VCP degraded Aurora A, their loss led to increased Aurora A stability but reduced Aurora A phosphorylation in mitosis., Competing Interests: The authors declare no competing interests., (© 2022 The Author(s).)

Human disease states are biomolecularly multifaceted and can span across phenotypic states, therefore it is important to understand diseases on all levels, across cell types, and within and across microanatomical tissue compartments. To obtain an accurate and representative view of the molecular landscape within human lungs, this fragile tissue must be inflated and embedded to maintain spatial fidelity of the location of molecules and minimize molecular degradation for molecular imaging experiments. Here, we evaluated agarose inflation and carboxymethyl cellulose embedding media and determined effective tissue preparation protocols for performing bulk and spatial mass spectrometry-based omics measurements. Mass spectrometry imaging methods were optimized to boost the number of annotatable molecules in agarose inflated lung samples. This optimized protocol permitted the observation of unique lipid distributions within several airway regions in the lung tissue block. Laser capture microdissection of these airway regions followed by high-resolution proteomic analysis allowed us to begin linking the lipidome with the proteome in a spatially resolved manner, where we observed proteins with high abundance specifically localized to the airway regions. We also compared our mass spectrometry results to lung tissue samples preserved using two other inflation/embedding media, but we identified several pitfalls with the sample preparation steps using this preservation method. Overall, we demonstrated the versatility of the inflation method, and we can start to reveal how the metabolome, lipidome, and proteome are connected spatially in human lungs and across disease states through a variety of different experiments., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lukowski, Olson, Velickovic, Wang, Kyle, Kim, Williams, Zhu, Huyck, McGraw, Poole, Rogers, Misra, Alexandrov, Ansong, Pryhuber, Clair, Adkins, Carson and Anderton.)

Single-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low-abundance proteins. Herein, we describe an ion-mobility-enhanced mass spectrometry acquisition and peptide identification method, transferring identification based on FAIMS filtering (TIFF), to improve the sensitivity and accuracy of label-free scProteomics. TIFF extends the ion accumulation times for peptide ions by filtering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells, with >1,100 proteins consistently identified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identified time-dependent proteome changes. A record of this paper's transparent peer review process is included in the supplemental information., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Rationale: The current understanding of human lung development derives mostly from animal studies. Although transcript-level studies have analyzed human donor tissue to identify genes expressed during normal human lung development, protein-level analysis that would enable the generation of new hypotheses on the processes involved in pulmonary development are lacking. Objectives: To define the temporal dynamic of protein expression during human lung development. Methods: We performed proteomics analysis of human lungs at 10 distinct times from birth to 8 years to identify the molecular networks mediating postnatal lung maturation. Measurements and Main Results: We identified 8,938 proteins providing a comprehensive view of the developing human lung proteome. The analysis of the data supports the existence of distinct molecular substages of alveolar development and predicted the age of independent human lung samples, and extensive remodeling of the lung proteome occurred during postnatal development. Evidence of post-transcriptional control was identified in early postnatal development. An extensive extracellular matrix remodeling was supported by changes in the proteome during alveologenesis. The concept of maturation of the immune system as an inherent part of normal lung development was substantiated by flow cytometry and transcriptomics. Conclusions: This study provides the first in-depth characterization of the human lung proteome during development, providing a unique proteomic resource freely accessible at Lungmap.net. The data support the extensive remodeling of the lung proteome during development, the existence of molecular substages of alveologenesis, and evidence of post-transcriptional control in early postnatal development.

The human lung plays vital roles in respiration, host defense, and basic physiology. Recent technological advancements such as single-cell RNA sequencing and genetic lineage tracing have revealed novel cell types and enriched functional properties of existing cell types in lung. The time has come to take a new census. Initiated by members of the NHLBI-funded LungMAP Consortium and aided by experts in the lung biology community, we synthesized current data into a comprehensive and practical cellular census of the lung. Identities of cell types in the normal lung are captured in individual cell cards with delineation of function, markers, developmental lineages, heterogeneity, regenerative potential, disease links, and key experimental tools. This publication will serve as the starting point of a live, up-to-date guide for lung research at https://www.lungmap.net/cell-cards/. We hope that Lung CellCards will promote the community-wide effort to establish, maintain, and restore respiratory health., Competing Interests: Declaration of interests X.S. and E.E.M. are members of the advisory board for Developmental Cell., (Copyright © 2021 Elsevier Inc. All rights reserved.)

An understanding of the immune mechanisms that lead to rejection versus tolerance of allogeneic pancreatic islet grafts is of paramount importance, as it facilitates the development of innovative methods to improve the transplant outcome. Here, we used our established intraocular islet transplant model to gain novel insight into changes in the local metabolome and proteome within the islet allograft's immediate microenvironment in association with immune-mediated rejection or tolerance. We performed integrated metabolomics and proteomics analyses in aqueous humor samples representative of the graft's microenvironment under each transplant outcome. The results showed that several free amino acids, small primary amines, and soluble proteins related to the Warburg effect were upregulated or downregulated in association with either outcome. In general, the observed shifts in the local metabolite and protein profiles in association with rejection were consistent with established pro-inflammatory metabolic pathways and those observed in association with tolerance were immune regulatory. Taken together, the current findings further support the potential of metabolic reprogramming of immune cells towards immune regulation through targeted pharmacological and dietary interventions against specific metabolic pathways that promote the Warburg effect to prevent the rejection of transplanted islets and promote their immune tolerance.

Mass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Bronchiolitis obliterans (BO) is a devastating lung disease seen commonly after lung transplant, following severe respiratory tract infection or chemical inhalation exposure. Diacetyl (DA; 2,3-butanedione) is a highly reactive alpha-diketone known to cause BO when inhaled, however, the mechanisms of how inhalation exposure leads to BO development remains poorly understood. In the current work, we combined two clinically relevant models for studying the pathogenesis of DA-induced BO: (1) an in vivo rat model of repetitive DA vapor exposures with recovery and (2) an in vitro model of primary human airway epithelial cells exposed to pure DA vapors. Rats exposed to 5 consecutive days 200 parts-per-million DA 6 h per day had worsening survival, persistent hypoxemia, poor weight gain, and histologic evidence of BO 14 days after DA exposure cessation. At the end of exposure, increased expression of the ubiquitin stress protein ubiquitin-C accumulated within DA-exposed rat lung homogenates and localized primarily to the airway epithelium, the primary site of BO development. Lung proteasome activity increased concurrently with ubiquitin-C expression after DA exposure, supportive of significant proteasome stress. In primary human airway cultures, global proteomics identified 519 significantly modified proteins in DA-exposed samples relative to controls with common pathways of the ubiquitin proteasome system, endosomal reticulum transport, and response to unfolded protein pathways being upregulated and cell-cell adhesion and oxidation-reduction pathways being downregulated. Collectively, these two models suggest that diacetyl inhalation exposure causes abundant protein damage and subsequent ubiquitin proteasome stress prior to the development of chemical-induced BO pathology.

Single-cell RNA-sequencing (scRNA-Seq) technologies have greatly enhanced our understanding of islet cell transcriptomes and have revealed the existence of β-cell heterogeneity. However, comparison of scRNA-Seq data sets from different groups have highlighted inconsistencies in gene expression patterns, primarily due to variable detection of lower abundance transcripts. Furthermore, such analyses are unable to uncover the spatial organization of heterogeneous gene expression. In this study, we used fluctuation localization imaging-based fluorescence in situ hybridization (fliFISH) to quantify transcripts in single cells in mouse pancreatic islet sections. We compared the expression patterns of Insulin 2 ( Ins2 ) with Mafa and Ucn3 , two genes expressed in β-cells as they mature, as well as Rgs4 , a factor with variably reported expression in the islet. This approach accurately quantified transcripts across a wide range of expression levels, from single copies to >100 copies/cell in one islet. Importantly, fliFISH allowed evaluation of transcript heterogeneity in the spatial context of an intact islet. These studies confirm the existence of a high degree of heterogeneous gene expression levels within the islet and highlight relative and radial expression patterns that likely reflect distinct β-cell maturation states along the radial axis of the islet., (© 2021 by the American Diabetes Association.)

Background: Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics., Methods: Blood from human subjects at high risk for T1D (and healthy controls; n = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to controls., Results: The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples without exception. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. IPA-predicted candidate biomarkers were used to construct a putative integrated signature containing several miRNAs and metabolite/lipid features in the at-risk subjects., Conclusions: Preliminary parallel quadra-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and highlighted the potential for identifying associated integrated biomarker signatures. With further development and validation in larger cohorts, parallel multi-omics could ultimately facilitate the classification of T1D progressors from non-progressors.

E-cigarette (e-cig) aerosols are complex mixtures of various chemicals including humectants (propylene glycol (PG) and vegetable glycerin (VG)), nicotine, and various flavoring additives. Emerging research is beginning to challenge the "relatively safe" perception of e-cigarettes. Recent studies suggest e-cig aerosols provoke oxidative stress; however, details of the underlying molecular mechanisms remain unclear. Here we used a redox proteomics assay of thiol total oxidation to identify signatures of site-specific protein thiol modifications in Sprague-Dawley rat lungs following in vivo e-cig aerosol exposures. Histologic evaluation of rat lungs exposed acutely to e-cig aerosols revealed mild perturbations in lung structure. Bronchoalveolar lavage (BAL) fluid analysis demonstrated no significant change in cell count or differential. Conversely, total lung glutathione decreased significantly in rats exposed to e-cig aerosol compared to air controls. Redox proteomics quantified the levels of total oxidation for 6682 cysteine sites representing 2865 proteins. Protein thiol oxidation and alterations by e-cig exposure induced perturbations of protein quality control, inflammatory responses and redox homeostasis. Perturbations of protein quality control were confirmed with semi-quantification of total lung polyubiquitination and 20S proteasome activity. Our study highlights the importance of redox control in the pulmonary response to e-cig exposure and the utility of thiol-based redox proteomics as a tool for elucidating the molecular mechanisms underlying this response., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

The applicability and benefits of pancreatic islet transplantation are limited due to various issues including the need to avoid immune-mediated rejection. Here, we used our experimental platform of allogeneic islet transplant in the anterior chamber of the eye (ACE-platform) to longitudinally monitor the progress of rejection in mice and obtain aqueous humor samples representative of the microenvironment of the graft for accurately-timed proteomic analyses. LC-MS/MS-based proteomics performed on such mass-limited samples (~5 μL) identified a total of 1296 proteins. Various analyses revealed distinct protein patterns associated with the mounting of the inflammatory and immune responses and their evolution with the progression of the rejection. Pathway analyses indicated predominant changes in cytotoxic functions, cell movement, and innate and adaptive immune responses. Network prediction analyses revealed transition from humoral to cellular immune response and exacerbation of pro-inflammatory signaling. One of the proteins identified by this localized proteomics as a candidate biomarker of islet rejection, Cystatin 3, was further validated by ELISA in the aqueous humor. This study provides (1) experimental evidence demonstrating the feasibility of longitudinal localized proteomics using small aqueous humor samples and (2) proof-of-concept for the discovery of biomarkers of impending immune attack from the immediate local microenvironment of ACE-transplanted islets. SIGNIFICANCE: The combination of the ACE-platform and longitudinal localized proteomics offers a powerful approach to biomarker discovery during the various stages of immune reactions mounted against transplanted tissues including pancreatic islets. It also supports proteomics-assisted drug discovery and development efforts aimed at preventing rejection through efficacy assessment of new agents by noninvasive and longitudinal graft monitoring., Competing Interests: Declaration of Competing Interest MHA is consultant for Biocrine, an unlisted biotech company that is using the anterior chamber of the eye technique as a research tool. All other authors declare no conflict of interest associated with their contribution to this manuscript. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Extracellular vesicles (EVs) have been growingly recognized as biomarkers and mediators of alcoholic liver disease (ALD) in human and mice. Here we characterized hepatocyte-derived EVs (HC-EVs) and their cargo for their biological functions in a novel murine model that closely resembles liver pathology observed in patients with alcoholic hepatitis (AH), the most severe spectrum of ALD. The numbers of circulating EVs and HC-EVs were significantly increased by 10-fold in AH mice compared with control mice. The miRNA (miR)-seq analysis detected 20 upregulated and 4 downregulated miRNAs (P < 0.001-0.05) in AH-HC-EVs. Treatment of murine primary hepatic stellate cells (HSCs) with AH-HC-EVs induced α-SMA (P < 0.05) and Col1a1 (P < 0.001). Smad7 and Nr1d2 genes, which were downregulated in HSCs from the AH mice, were predicted targets of 20 miRs upregulated in AH-HC-EVs. Among them were miR-27a and miR-181 which upon transfection in HSCs, indeed repressed Nr1d2, the quiescent HSC marker. AH-HC-EVs were also enriched with organelle proteins and mitochondrial DNA (10-fold, P < 0.05) and upregulated IL-1β and IL-17 production by hepatic macrophages (HMs) from AH mice in a TLR9-dependent manner. These results demonstrate HC-EV release is intensified in AH and suggest that AH-HC-EVs orchestrate liver fibrogenesis by directly targeting the quiescent HSC transcripts via a unique set of miRNAs and by amplifying HSC activation via DAMP-based induction of profibrogenic IL-1β and IL-17 by HMs. KEY MESSAGES: • Circulating EVs and HC-EVs were increased in AH mice compared with control mice • AH-HC-EVs were enriched in miRNAs, organelle proteins, and mitochondrial DNA • AH-HC-EVs increased cytokine production by AH-HMs in a TLR9-dependent manner.

Saprobic fungi, such as Aspergillus niger, grow as colonies consisting of a network of branching and fusing hyphae that are often considered to be relatively uniform entities in which nutrients can freely move through the hyphae. In nature, different parts of a colony are often exposed to different nutrients. We have investigated, using a multi-omics approach, adaptation of A. niger colonies to spatially separated and compositionally different plant biomass substrates. This demonstrated a high level of intra-colony differentiation, which closely matched the locally available substrate. The part of the colony exposed to pectin-rich sugar beet pulp and to xylan-rich wheat bran showed high pectinolytic and high xylanolytic transcript and protein levels respectively. This study therefore exemplifies the high ability of fungal colonies to differentiate and adapt to local conditions, ensuring efficient use of the available nutrients, rather than maintaining a uniform physiology throughout the colony., (© 2019 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.)

Many studies have highlighted the role of dysregulated glucagon secretion in the etiology of hyperglycemia and diabetes. Accordingly, understanding the mechanisms underlying pancreatic islet α cell development and function has important implications for the discovery of new therapies for diabetes. In this study, comparative transcriptome analyses between embryonic mouse pancreas and adult mouse islets identified several pancreatic lncRNAs that lie in close proximity to essential pancreatic transcription factors, including the Pax6-associated lncRNA Paupar. We demonstrate that Paupar is enriched in glucagon-producing α cells where it promotes the alternative splicing of Pax6 to an isoform required for activation of essential α cell genes. Consistently, deletion of Paupar in mice resulted in dysregulation of PAX6 α cell target genes and corresponding α cell dysfunction, including blunted glucagon secretion. These findings illustrate a distinct mechanism by which a pancreatic lncRNA can coordinate glucose homeostasis by cell-specific regulation of a broadly expressed transcription factor., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Summary: Here we introduce Lipid Mini-On, an open-source tool that performs lipid enrichment analyses and visualizations of lipidomics data. Lipid Mini-On uses a text-mining process to bin individual lipid names into multiple lipid ontology groups based on the classification (e.g. LipidMaps) and other characteristics, such as chain length. Lipid Mini-On provides users with the capability to conduct enrichment analysis of the lipid ontology terms using a Shiny app with options of five statistical approaches. Lipid classes can be added to customize the user's database and remain updated as new lipid classes are discovered. Visualization of results is available for all classification options (e.g. lipid subclass and individual fatty acid chains). Results are also visualized through an editable network of relationships between the individual lipids and their associated lipid ontology terms. The utility of the tool is demonstrated using biological (e.g. human lung endothelial cells) and environmental (e.g. peat soil) samples., Availability and Implementation: Rodin (R package: https://github.com/PNNL-Comp-Mass-Spec/Rodin), Lipid Mini-On Shiny app (https://github.com/PNNL-Comp-Mass-Spec/LipidMiniOn) and Lipid Mini-On online tool (https://omicstools.pnnl.gov/shiny/lipid-mini-on/)., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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.

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.

Systems biology uses computational approaches to integrate diverse data types to understand cell and organ behavior. Data derived from complementary technologies, for example transcriptomic and proteomic analyses, are providing new insights into development and disease. We compared mRNA and protein profiles from purified endothelial, epithelial, immune, and mesenchymal cells from normal human infant lung tissue. Signatures for each cell type were identified and compared at both mRNA and protein levels. Cell-specific biological processes and pathways were predicted by analysis of concordant and discordant RNA-protein pairs. Cell clustering and gene set enrichment comparisons identified shared versus unique processes associated with transcriptomic and/or proteomic data. Clear cell-cell correlations between mRNA and protein data were obtained from each cell type. Approximately 40% of RNA-protein pairs were coherently expressed. While the correlation between RNA and their protein products was relatively low (Spearman rank coefficient r s ~0.4), cell-specific signature genes involved in functional processes characteristic of each cell type were more highly correlated with their protein products. Consistency of cell-specific RNA-protein signatures indicated an essential framework for the function of each cell type. Visualization and reutilization of the protein and RNA profiles are supported by a new web application, "LungProteomics," which is freely accessible to the public.

Hepcidin, a cysteine-rich peptide hormone, secreted mainly by the liver, plays a central role in iron metabolism regulation. Emerging evidence suggests that disordered iron metabolism is a risk factor for various types of diseases including cancers. However, it remains challenging to apply current mass spectrometry (MS)-based hepcidin assays for precise quantification due to the low fragmentation efficiency of intact hepcidin as well as synthesis difficulties for the intact hepcidin standard. To address these issues we recently developed a reliable sensitive targeted MS assay for hepcidin quantification from clinical samples that uses fully alkylated rather than intact hepcidin as the internal standard. Limits of detection and quantification were determined to be <0.5 ng/mL and 1 ng/mL, respectively. Application of the alkylated hepcidin assay to 70 clinical plasma samples (42 non-cancerous and 28 ovarian cancer patient samples) enabled reliable detection of endogenous hepcidin from the plasma samples, as well as conditioned culture media. The hepcidin concentrations ranged from 0.0 to 95.6 ng/mL across non-cancerous and cancer plasma specimens. Interestingly, cancer patients were found to have significantly higher hepcidin concentrations compared to non-cancerous patients (mean: 20.6 ng/ml for cancer; 5.94 ng/ml for non-cancerous) (p value < 0.001). Our results represent the first application of the alkylated hepcidin assay to clinical samples and demonstrate that the developed assay has better sensitivity and quantification accuracy than current MS-based hepcidin assays without the challenges in synthesis of intact hepcidin standard and accurately determining its absolute amount.

Mass-spectrometry based omics technologies - namely proteomics, metabolomics and lipidomics - have enabled the molecular level systems biology investigation of organisms in unprecedented detail. There has been increasing interest for gaining a thorough, functional understanding of the biological consequences associated with cellular heterogeneity in a wide variety of research areas such as developmental biology, precision medicine, cancer research and microbiome science. Recent advances in mass spectrometry (MS) instrumentation and sample handling strategies are quickly making comprehensive omics analyses of single cells feasible, but key breakthroughs are still required to push through remaining bottlenecks. In this review, we discuss the challenges faced by single cell MS-based omics analyses and highlight recent technological advances that collectively can contribute to comprehensive and high throughput omics analyses in single cells. We provide a vision of the potential of integrating pioneering technologies such as Structures for Lossless Ion Manipulations (SLIM) for improved sensitivity and resolution, novel peptide identification tactics and standards free metabolomics approaches for future applications in single cell analysis.

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.

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analyzed by ultrasensitive nanoLC-MS. An average of circa 670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single-cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells., (© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Cell type-resolved proteome analyses of the brain, heart and liver have been reported, however a similar effort on the lipidome is currently lacking. Here we applied liquid chromatography-tandem mass spectrometry to characterize the lipidome of major lung cell types isolated from human donors, representing the first lipidome map of any organ. We coupled this with cell type-resolved proteomics of the same samples (available at Lungmap.net). Complementary proteomics analyses substantiated the functional identity of the isolated cells. Lipidomics analyses showed significant variations in the lipidome across major human lung cell types, with differences most evident at the subclass and intra-subclass (i.e. total carbon length of the fatty acid chains) level. Further, lipidomic signatures revealed an overarching posture of high cellular cooperation within the human lung to support critical functions. Our complementary cell type-resolved lipid and protein datasets serve as a rich resource for analyses of human lung function.

Lung diseases and disorders are a leading cause of death among infants. Many of these diseases and disorders are caused by premature birth and underdeveloped lungs. In addition to developmentally related disorders, the lungs are exposed to a variety of environmental contaminants and xenobiotics upon birth that can cause breathing issues and are progenitors of cancer. In order to gain a deeper understanding of the developing lung, we applied an activity-based chemoproteomics approach for the functional characterization of the xenometabolizing cytochrome P450 enzymes, active ATP and nucleotide binding enzymes, and serine hydrolases using a suite of activity-based probes (ABPs). We detected P450 activity primarily in the postnatal lung; using our ATP-ABP, we characterized a wide range of ATPases and other active nucleotide- and nucleic acid-binding enzymes involved in multiple facets of cellular metabolism throughout development. ATP-ABP targets include kinases, phosphatases, NAD- and FAD-dependent enzymes, RNA/DNA helicases, and others. The serine hydrolase-targeting probe detected changes in the activities of several proteases during the course of lung development, yielding insights into protein turnover at different stages of development. Select activity-based probe targets were then correlated with RNA in situ hybridization analyses of lung tissue sections.

Biochemical networks mediating normal lung morphogenesis and function have important implications for ameliorating morbidity and mortality in premature infants. Although several transcript-level studies have examined normal lung development, corresponding protein-level analyses are lacking. Here we performed proteomics analysis of murine lungs from embryonic to early adult ages to identify the molecular networks mediating normal lung development. We identified 8,932 proteins, providing a deep and comprehensive view of the lung proteome. Analysis of the proteomics data revealed discrete modules and the underlying regulatory and signaling network modulating their expression during development. Our data support the cell proliferation that characterizes early lung development and highlight responses of the lung to exposure to a nonsterile oxygen-rich ambient environment and the important role of lipid (surfactant) metabolism in lung development. Comparison of dynamic regulation of proteomic and recent transcriptomic analyses identified biological processes under posttranscriptional control. Our study provides a unique proteomic resource for understanding normal lung formation and function and can be freely accessed at Lungmap.net.

Nanospray Desorption Electrospray Ionization mass spectrometry imaging (nano-DESI MSI) enables ambient imaging of biological samples with high sensitivity and minimal sample pretreatment. Recently, we developed an approach for constant-distance mode MSI using shear force microscopy to precisely control the distance between the sample and the nano-DESI probe. Herein, we demonstrate the power of this approach for robust imaging of pancreatic islets with high spatial resolution of ∼11 μm. Pancreatic islets are difficult to characterize using traditional mass spectrometry approaches due to their small size (∼100 μm) and molecular heterogeneity. Nano-DESI MSI was used to examine the spatial localization of several lipid classes including phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), phosphatidylinositol (PI), and phosphatidylserine (PS) along with fatty acids and their metabolites (e.g., prostaglandins) in the individual islets and surrounding tissue. Several lipids were found to be substantially enhanced in the islets indicating these lipids may be involved in insulin secretion. Remarkably different distributions were observed for several pairs of Lyso PC (LPC) and PC species differing only by one double bond, such as LPC 18:1 vs LPC 18:0, PC 32:1 vs PC 32:0, and PC 34:2 vs PC 34:1. These findings indicate that minor variations in the fatty acid chain length and saturation have a pronounced effect on the localization of PC and LPC species in pancreatic islets. Interestingly, oxidized PC species observed experimentally were found to be specifically localized to pancreatic islets. These PCs are potential biomarkers for reactive oxygen species in the islets, which could be harmful to pancreatic beta cells. The experimental approach presented in this study will provide valuable information on the heterogeneity of individual pancreatic islets, which is difficult to assess using bulk characterization techniques.

Phage-host interactions are critical to ecology, evolution, and biotechnology. Central to those is infection efficiency, which remains poorly understood, particularly in nature. Here we apply genome-wide transcriptomics and proteomics to investigate infection efficiency in nature's own experiment: two nearly identical (genetically and physiologically) Bacteroidetes bacterial strains (host18 and host38) that are genetically intractable, but environmentally important, where phage infection efficiency varies. On host18, specialist phage phi18:3 infects efficiently, whereas generalist phi38:1 infects inefficiently. On host38, only phi38:1 infects, and efficiently. Overall, phi18:3 globally repressed host18's transcriptome and proteome, expressed genes that likely evaded host restriction/modification (R/M) defenses and controlled its metabolism, and synchronized phage transcription with translation. In contrast, phi38:1 failed to repress host18's transcriptome and proteome, did not evade host R/M defenses or express genes for metabolism control, did not synchronize transcripts with proteins and its protein abundances were likely targeted by host proteases. However, on host38, phi38:1 globally repressed host transcriptome and proteome, synchronized phage transcription with translation, and infected host38 efficiently. Together these findings reveal multiple infection inefficiencies. While this contrasts the single mechanisms often revealed in laboratory mutant studies, it likely better reflects the phage-host interaction dynamics that occur in nature.

Alcoholic hepatitis (AH) continues to be a disease with high mortality and no efficacious medical treatment. Although severe AH is presented as acute on chronic liver failure, what underlies this transition from chronic alcoholic steatohepatitis (ASH) to AH is largely unknown. To address this question, unbiased RNA sequencing and proteomic analyses were performed on livers of the recently developed AH mouse model, which exhibits the shift to AH from chronic ASH upon weekly alcohol binge, and these results are compared to gene expression profiling data from AH patients. This cross-analysis has identified Casp11 (CASP4 in humans) as a commonly up-regulated gene known to be involved in the noncanonical inflammasome pathway. Immunoblotting confirms CASP11/4 activation in AH mice and patients, but not in chronic ASH mice and healthy human livers. Gasdermin-D (GSDMD), which induces pyroptosis (lytic cell death caused by bacterial infection) downstream of CASP11/4 activation, is also activated in AH livers in mice and patients. CASP11 deficiency reduces GSDMD activation, bacterial load in the liver, and severity of AH in the mouse model. Conversely, the deficiency of interleukin-18, the key antimicrobial cytokine, aggravates hepatic bacterial load, GSDMD activation, and AH. Furthermore, hepatocyte-specific expression of constitutively active GSDMD worsens hepatocellular lytic death and polymorphonuclear leukocyte inflammation., Conclusion: These results implicate pyroptosis induced by the CASP11/4-GSDMD pathway in the pathogenesis of AH. (Hepatology 2018;67:1737-1753)., (© 2017 by the American Association for the Study of Liver Diseases.)

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.

Quantitative gene expression analysis in intact single cells can be achieved using single molecule-based fluorescence in situ hybridization (smFISH). This approach relies on fluorescence intensity to distinguish between true signals, emitted from an RNA copy hybridized with multiple oligonucleotide probes, and background noise. Thus, the precision in smFISH is often compromised by partial or nonspecific probe binding and tissue autofluorescence, especially when only a small number of probes can be fitted to the target transcript. Here we provide an accurate approach for setting quantitative thresholds between true and false signals, which relies on on-off duty cycles of photoswitchable dyes. This fluctuation localization imaging-based FISH (fliFISH) uses on-time fractions (measured over a series of exposures) collected from transcripts bound to as low as 8 probes, which are distinct from on-time fractions collected from nonspecifically bound probes or autofluorescence. Using multicolor fliFISH, we identified radial gene expression patterns in mouse pancreatic islets for insulin, the transcription factor, NKX2-2 and their ratio (Nkx2-2/Ins2). These radial patterns, showing higher values in β cells at the islet core and lower values in peripheral cells, were lost in diabetic mouse islets. In summary, fliFISH provides an accurate, quantitative approach for detecting and counting true RNA copies and rejecting false signals by their distinct on-time fractions, laying the foundation for reliable single-cell transcriptomics., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Traditionally, proteomic studies have been carried out on whole tissues or organs enabling the profiling of thousands of proteins within a single LC-MS analysis. A disadvantage of this approach is that proteomes generated from whole tissues are an "average" that represents a blend of cell types and distinct anatomical regions which can obscure important biological phenomena. Laser capture microdissection (LCM) is an elegant method that allows tissue features of interest, as small as a single cell, to be identified and isolated for downstream analysis. Herein we describe an approach that utilizes an immobilized enzyme reactor (IMER) coupled directly to nanoLC-MS/MS for highly sensitive, automated, quantitative proteomic analysis of the microscopic tissue specimens generated by LCM.

Adaptation to air breathing after birth is dependent upon the synthesis and secretion of pulmonary surfactant by alveolar type 2 (AT2) cells. Surfactant, a complex mixture of phospholipids and proteins, is secreted into the alveolus, where it reduces collapsing forces at the air-liquid interface to maintain lung volumes during the ventilatory cycle. ABCA3, an ATP-dependent Walker domain containing transport protein, is required for surfactant synthesis and lung function at birth. Mutations in ABCA3 cause severe surfactant deficiency and respiratory failure in newborn infants. We conditionally deleted the Abca3 gene in AT2 cells in the mature mouse lung. Loss of ABCA3 caused alveolar cell injury and respiratory failure. ABCA3-related lung dysfunction was associated with surfactant deficiency, inflammation, and alveolar-capillary leak. Extensive but incomplete deletion of ABCA3 caused alveolar injury and inflammation, and it initiated proliferation of progenitor cells, restoring ABCA3 expression, lung structure, and function. M2-like macrophages were recruited to sites of AT2 cell proliferation during the regenerative process and were present in lung tissue from patients with severe lung disease caused by mutations in ABCA3. The remarkable and selective regeneration of ABCA3-sufficient AT2 progenitor cells provides plausible approaches for future correction of ABCA3 and other genetic disorders associated with surfactant deficiency and acute interstitial lung disease.