Integration of transcriptomic and proteomic data identifies biological functions in cell populations from human infant lung

Sorted-Cell Proteomics Reveals an AT1-Associated Epithelial Cornification Phenotype and Suggests Endothelial Redox Imbalance in Human Bronchopulmonary Dysplasia

Bronchopulmonary dysplasia (BPD) is a neonatal lung disease characterized by inflammation and scarring leading to long-term tissue damage. Previous whole tissue proteomics identified BPD-specific proteome changes and cell type shifts. Little is known about the proteome-level changes within specific cell populations in disease. Here, we sorted epithelial (EPI) and endothelial (ENDO) cell populations based on their differential surface markers from normal and BPD human lungs. Using a low-input compatible sample preparation method (MicroPOT), proteins were extracted and digested into peptides and subjected to Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) proteome analysis. Of the 4,970 proteins detected, 293 were modulated in abundance or detection in the EPI population and 422 were modulated in ENDO cells. Modulation of proteins associated with actin-cytoskeletal function such as SCEL, LMO7, and TBA1B were observed in the BPD EPIs. Using confocal imaging and analysis, we validated the presence of aberrant multilayer-like structures comprising SCEL and LMO7, known to be associated with epidermal cornification, in the human BPD lung. This is the first report of accumulation of cornification-associated proteins in BPD. Their localization in the alveolar parenchyma, primarily associated with alveolar type 1 (AT1) cells, suggests a role in the BPD post-injury response. In the ENDOs, redox balance and mitochondrial function pathways were modulated. Alternative mRNA splicing and cell proliferative functions were elevated in both populations suggesting potential dysregulation of cell progenitor fate. This study characterized the proteome of epithelial and endothelial cells from the BPD lung for the first time, identifying population-specific changes in BPD pathogenesis.

New & Noteworthy

The study is the first to perform proteomics on sorted pulmonary epithelial and endothelial populations from BPD and age-matched control human donors. We identified an increase in cornification-associated proteins in BPD (e.g., SCEL and LMO7), and evidenced the presence of multilayered structures unique to BPD alveolar regions, associated with alveolar type 1 (AT1) cells. By changing the nature and/or biomechanical properties of the epithelium, these structures may alter the behavior of other alveolar cell types potentially contributing to the arrested alveolarization observed in BPD. Lastly, our data suggest the modulation of cell proliferation and redox homeostasis in BPD providing potential mechanisms for the reduced vascular growth associated with BPD.

Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications

The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding of the brain, unlocking new possibilities in research, diagnosis, and therapy. This review explores how AI's cutting-edge algorithms-ranging from deep learning to neuromorphic computing-are revolutionizing neuroscience by enabling the analysis of complex neural datasets, from neuroimaging and electrophysiology to genomic profiling. These advancements are transforming the early detection of neurological disorders, enhancing brain-computer interfaces, and driving personalized medicine, paving the way for more precise and adaptive treatments. Beyond applications, neuroscience itself has inspired AI innovations, with neural architectures and brain-like processes shaping advances in learning algorithms and explainable models. This bidirectional exchange has fueled breakthroughs such as dynamic connectivity mapping, real-time neural decoding, and closed-loop brain-computer systems that adaptively respond to neural states. However, challenges persist, including issues of data integration, ethical considerations, and the "black-box" nature of many AI systems, underscoring the need for transparent, equitable, and interdisciplinary approaches. By synthesizing the latest breakthroughs and identifying future opportunities, this review charts a path forward for the integration of AI and neuroscience. From harnessing multimodal data to enabling cognitive augmentation, the fusion of these fields is not just transforming brain science, it is reimagining human potential. This partnership promises a future where the mysteries of the brain are unlocked, offering unprecedented advancements in healthcare, technology, and beyond.

Review on computer-assisted biosynthetic capacities elucidation to assess metabolic interactions and communication within microbial communities

Microbial communities thrive through interactions and communication, which are challenging to study as most microorganisms are not cultivable. To address this challenge, researchers focus on the extracellular space where communication events occur. Exometabolomics and interactome analysis provide insights into the molecules involved in communication and the dynamics of their interactions. Advances in sequencing technologies and computational methods enable the reconstruction of taxonomic and functional profiles of microbial communities using high-throughput multi-omics data. Network-based approaches, including community flux balance analysis, aim to model molecular interactions within and between communities. Despite these advances, challenges remain in computer-assisted biosynthetic capacities elucidation, requiring continued innovation and collaboration among diverse scientists. This review provides insights into the current state and future directions of computer-assisted biosynthetic capacities elucidation in studying microbial communities.

Integrating Molecular Perspectives: Strategies for Comprehensive Multi-Omics Integrative Data Analysis and Machine Learning Applications in Transcriptomics, Proteomics, and Metabolomics

With the advent of high-throughput technologies, the field of omics has made significant strides in characterizing biological systems at various levels of complexity. Transcriptomics, proteomics, and metabolomics are the three most widely used omics technologies, each providing unique insights into different layers of a biological system. However, analyzing each omics data set separately may not provide a comprehensive understanding of the subject under study. Therefore, integrating multi-omics data has become increasingly important in bioinformatics research. In this article, we review strategies for integrating transcriptomics, proteomics, and metabolomics data, including co-expression analysis, metabolite-gene networks, constraint-based models, pathway enrichment analysis, and interactome analysis. We discuss combined omics integration approaches, correlation-based strategies, and machine learning techniques that utilize one or more types of omics data. By presenting these methods, we aim to provide researchers with a better understanding of how to integrate omics data to gain a more comprehensive view of a biological system, facilitating the identification of complex patterns and interactions that might be missed by single-omics analyses.

Single-Cell Transcriptomic Profiling Identifies Molecular Phenotypes of Newborn Human Lung Cells

While animal model studies have extensively defined the mechanisms controlling cell diversity in the developing mammalian lung, there exists a significant knowledge gap with regards to late-stage human lung development. The NHLBI Molecular Atlas of Lung Development Program (LungMAP) seeks to fill this gap by creating a structural, cellular and molecular atlas of the human and mouse lung. Transcriptomic profiling at the single-cell level created a cellular atlas of newborn human lungs. Frozen single-cell isolates obtained from two newborn human lungs from the LungMAP Human Tissue Core Biorepository, were captured, and library preparation was completed on the Chromium 10X system. Data was analyzed in Seurat, and cellular annotation was performed using the ToppGene functional analysis tool. Transcriptional interrogation of 5500 newborn human lung cells identified distinct clusters representing multiple populations of epithelial, endothelial, fibroblasts, pericytes, smooth muscle, immune cells and their gene signatures. Computational integration of data from newborn human cells and with 32,000 cells from postnatal days 1 through 10 mouse lungs generated by the LungMAP Cincinnati Research Center facilitated the identification of distinct cellular lineages among all the major cell types. Integration of the newborn human and mouse cellular transcriptomes also demonstrated cell type-specific differences in maturation states of newborn human lung cells. Specifically, newborn human lung matrix fibroblasts could be separated into those representative of younger cells (n = 393), or older cells (n = 158). Cells with each molecular profile were spatially resolved within newborn human lung tissue. This is the first comprehensive molecular map of the cellular landscape of neonatal human lung, including biomarkers for cells at distinct states of maturity.

Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin's role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

LungMAP Portal Ecosystem: Systems-level Exploration of the Lung

An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular imaging, and pathological datasets. To centralize and standardize information across broad lung research efforts, we expanded the LungMAP.net website into a new gateway portal. This portal connects a broad spectrum of research networks, bulk and single-cell multiomics data, and a diverse collection of image data that span mammalian lung development and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances, including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, and mouse) to enable consistent queries across technologies, cohorts, age, disease, and drug treatment. These atlases are provided as independent and integrated queryable datasets, with an emphasis on dynamic visualization, figure generation, reanalysis, cell-type curation, and automated reference-based classification of user-provided single-cell genomics datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, supported data types, data portals and datasets from LungMAP, and external research efforts.

Systematic proteomics profiling of lysine crotonylation of the lung at Pseudoglandular and Canalicular phases in human fetus

Lung tissue is an important organ of the fetus, and genomic research on its development has improved our understanding of the biology of this tissue. However, the proteomic research of developing fetal lung tissue is still very scarce. We conducted comprehensive analysis of two developmental stages of fetal lung tissue of proteomics. It showed the developmental characteristics of lung tissue, such as the down-regulation of metabolism-related protein expression, the up-regulation of cell cycle-related proteins, and the regulation in proteins and pathways related to lung development. In addition, we also discovered some key core proteins related to lung development, and provided some key crotonylation modification sites that regulation during lung tissue development. Our comprehensive analysis of lung proteomics can provide a more comprehensive understanding of the developmental status of lung tissue, and provide a certain reference for future research and epigenetics of lung tissue.

Functional Pdgfra fibroblast heterogeneity in normal and fibrotic mouse lung

Aberrant fibroblast function plays a key role in the pathogenesis of idiopathic pulmonary fibrosis, a devastating disease of unrelenting extracellular matrix deposition in response to lung injury. Platelet-derived growth factor α-positive (Pdgfra+) lipofibroblasts (LipoFBs) are essential for lung injury response and maintenance of a functional alveolar stem cell niche. Little is known about the effects of lung injury on LipoFB function. Here, we used single-cell RNA-Seq (scRNA-Seq) technology and PdgfraGFP lineage tracing to generate a transcriptomic profile of Pdgfra+ fibroblasts in normal and injured mouse lungs 14 days after bleomycin exposure, generating 11 unique transcriptomic clusters that segregated according to treatment. While normal and injured LipoFBs shared a common gene signature, injured LipoFBs acquired fibrogenic pathway activity with an attenuation of lipogenic pathways. In a 3D organoid model, injured Pdgfra+ fibroblast-supported organoids were morphologically distinct from those cultured with normal fibroblasts, and scRNA-Seq analysis suggested distinct transcriptomic changes in alveolar epithelia supported by injured Pdgfra+ fibroblasts. In summary, while LipoFBs in injured lung have not migrated from their niche and retain their lipogenic identity, they acquire a potentially reversible fibrogenic profile, which may alter the kinetics of epithelial regeneration and potentially contribute to dysregulated repair, leading to fibrosis.

Regionally distinct progenitor cells in the lower airway give rise to neuroendocrine and multiciliated cells in the developing human lung

Using scRNA-seq and microscopy, we describe a cell that is enriched in the lower airways of the developing human lung and identified by the unique coexpression of SCGB3A2/SFTPB/CFTR. To functionally interrogate these cells, we apply a single-cell barcode-based lineage tracing method, called CellTagging, to track the fate of SCGB3A2/SFTPB/CFTR cells during airway organoid differentiation in vitro. Lineage tracing reveals that these cells have a distinct differentiation potential from basal cells, giving rise predominantly to pulmonary neuroendocrine cells and a subset of multiciliated cells distinguished by high C6 and low MUC16 expression. Lineage tracing results are supported by studies using organoids and isolated cells from the lower noncartilaginous airway. We conclude that SCGB3A2/SFTPB/CFTR cells are enriched in the lower airways of the developing human lung and contribute to the epithelial diversity and heterogeneity in this region.

Integrated transcriptome-proteome analyses of human stem cells reveal source-dependent differences in their regenerative signature

Mesenchymal stem cells (MSCs) are gaining increasing prominence as an effective regenerative cellular therapy. However, ensuring consistent and reliable effects across clinical populations has proved to be challenging. In part, this can be attributed to heterogeneity in the intrinsic molecular and regenerative signature of MSCs, which is dependent on their source of origin. The present work uses integrated omics-based profiling, at different functional levels, to compare the anti-inflammatory, immunomodulatory, and angiogenic properties between MSCs from neonatal (umbilical cord MSC [UC-MSC]) and adult (adipose tissue MSC [AD-MSC], and bone marrow MSC [BM-MSC]) sources. Using multi-parametric analyses, we identified that UC-MSCs promote a more robust host innate immune response; in contrast, adult-MSCs appear to facilitate remodeling of the extracellular matrix (ECM) with stronger activation of angiogenic cascades. These data should help facilitate the standardization of source-specific MSCs, such that their regenerative signatures can be confidently used to target specific disease processes.

R-SPONDIN2+ mesenchymal cells form the bud tip progenitor niche during human lung development

The human respiratory epithelium is derived from a progenitor cell in the distal buds of the developing lung. These "bud tip progenitors" are regulated by reciprocal signaling with surrounding mesenchyme; however, mesenchymal heterogeneity and function in the developing human lung are poorly understood. We interrogated single-cell RNA sequencing data from multiple human lung specimens and identified a mesenchymal cell population present during development that is highly enriched for expression of the WNT agonist RSPO2, and we found that the adjacent bud tip progenitors are enriched for the RSPO2 receptor LGR5. Functional experiments using organoid models, explant cultures, and FACS-isolated RSPO2+ mesenchyme show that RSPO2 is a critical niche cue that potentiates WNT signaling in bud tip progenitors to support their maintenance and multipotency.

Molecular Modelling Hurdle in the Next-Generation Sequencing Era

There are challenges in the genetic diagnosis of rare diseases, and pursuing an optimal strategy to identify the cause of the disease is one of the main objectives of any clinical genomics unit. A range of techniques are currently used to characterize the genomic variability within the human genome to detect causative variants of specific disorders. With the introduction of next-generation sequencing (NGS) in the clinical setting, geneticists can study single-nucleotide variants (SNVs) throughout the entire exome/genome. In turn, the number of variants to be evaluated per patient has increased significantly, and more information has to be processed and analyzed to determine a proper diagnosis. Roughly 50% of patients with a Mendelian genetic disorder are diagnosed using NGS, but a fair number of patients still suffer a diagnostic odyssey. Due to the inherent diversity of the human population, as more exomes or genomes are sequenced, variants of uncertain significance (VUSs) will increase exponentially. Thus, assigning relevance to a VUS (non-synonymous as well as synonymous) in an undiagnosed patient becomes crucial to assess the proper diagnosis. Multiple algorithms have been used to predict how a specific mutation might affect the protein's function, but they are far from accurate enough to be conclusive. In this work, we highlight the difficulties of genomic variability determined by NGS that have arisen in diagnosing rare genetic diseases, and how molecular modelling has to be a key component to elucidate the relevance of a specific mutation in the protein's loss of function or malfunction. We suggest that the creation of a multi-omics data model should improve the classification of pathogenicity for a significant amount of the detected genomic variability. Moreover, we argue how it should be incorporated systematically in the process of variant evaluation to be useful in the clinical setting and the diagnostic pipeline.

Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering

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.

A census of the lung: CellCards from LungMAP

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.

Advanced single-cell technologies to guide the development of bioengineered lungs

Lung transplantation remains the only viable option for individuals suffering from end-stage lung failure. However, a number of current limitations exist including a continuing shortage of suitable donor lungs and immune rejection following transplantation. To address these concerns, engineering a decellularized biocompatible lung scaffold from cadavers reseeded with autologous lung cells to promote tissue regeneration is being explored. Proof-of-concept transplantation of these bioengineered lungs into animal models has been accomplished. However, these lungs were incompletely recellularized with resulting epithelial and endothelial leakage and insufficient basement membrane integrity. Failure to repopulate lung scaffolds with all of the distinct cell populations necessary for proper function remains a significant hurdle for the progression of current engineering approaches and precludes clinical translation. Advancements in 3D bioprinting, lung organoid models, and microfluidic device and bioreactor development have enhanced our knowledge of pulmonary lung development, as well as important cell-cell and cell-matrix interactions, all of which will help in the path to a bioengineered transplantable lung. However, a significant gap in knowledge of the spatiotemporal interactions between cell populations as well as relative quantities and localization within each compartment of the lung necessary for its proper growth and function remains. This review will provide an update on cells currently used for reseeding decellularized scaffolds with outcomes of recent lung engineering attempts. Focus will then be on how data obtained from advanced single-cell analyses, coupled with multiomics approaches and high-resolution 3D imaging, can guide current lung bioengineering efforts for the development of fully functional, transplantable lungs.

Valproic acid treatment rescues injured tissues after traumatic brain injury

BACKGROUND

No agents that are specifically neuroprotective are currently approved to emergently treat patients with traumatic brain injury (TBI). The histone deacetylase inhibitor, high-dose valproic acid (VPA) has been shown to have cytoprotective potential in models of combined TBI and hemorrhagic shock, but it has not been tested in an isolated TBI model. We hypothesized that VPA, administered after isolated TBI, will penetrate the injured brain, attenuate the lesion size, and activate prosurvival pathways.

METHODS

Yorkshire swine were subjected to severe TBI by cortical impact. One hour later, animals were randomized to VPA treatment (150 mg/kg delivered intravenously for 1 hour; n = 4) or control (saline vehicle; n = 4) groups. Seven hours after injury, animals were sacrificed, and brain lesion size was measured. Mass spectrometry imaging was used to visualize and quantitate brain tissue distribution of VPA. Sequential serum samples were assayed for key biomarkers and subjected to proteomic and pathway analysis.

RESULTS

Brain lesion size was 50% smaller (p = 0.01) in the VPA-treated animals (3,837 ± 948 mm) compared with the controls (1,900 ± 614 mm). Endothelial regions had eightfold higher VPA concentrations than perivascular regions by mass spectrometry imaging, and it readily penetrated the injured brain tissues. Serum glial fibrillary acid protein was significantly lower in the VPA-treated compared with the control animals (p < 0.05). More than 500 proteins were differentially expressed in the brain, and pathway analysis revealed that VPA affected critical modulators of TBI response including calcium signaling pathways, mitochondria metabolism, and biosynthetic machinery.

CONCLUSION

Valproic acid penetrates injured brain tissues and exerts neuroprotective and prosurvival effects that resulted in a significant reduction in brain lesion size after isolated TBI. Levels of serum biomarkers reflect these changes, which could be useful for monitoring the response of TBI patients during clinical studies.

Cestode strobilation: prediction of developmental genes and pathways

BACKGROUND

Cestoda is a class of endoparasitic worms in the flatworm phylum (Platyhelminthes). During the course of their evolution cestodes have evolved some interesting aspects, such as their increased reproductive capacity. In this sense, they have serial repetition of their reproductive organs in the adult stage, which is often associated with external segmentation in a developmental process called strobilation. However, the molecular basis of strobilation is poorly understood. To assess this issue, an evolutionary comparative study among strobilated and non-strobilated flatworm species was conducted to identify genes and proteins related to the strobilation process.

RESULTS

We compared the genomic content of 10 parasitic platyhelminth species; five from cestode species, representing strobilated parasitic platyhelminths, and five from trematode species, representing non-strobilated parasitic platyhelminths. This dataset was used to identify 1813 genes with orthologues that are present in all cestode (strobilated) species, but absent from at least one trematode (non-strobilated) species. Development-related genes, along with genes of unknown function (UF), were then selected based on their transcriptional profiles, resulting in a total of 34 genes that were differentially expressed between the larval (pre-strobilation) and adult (strobilated) stages in at least one cestode species. These 34 genes were then assumed to be strobilation related; they included 12 encoding proteins of known function, with 6 related to the Wnt, TGF-β/BMP, or G-protein coupled receptor signaling pathways; and 22 encoding UF proteins. In order to assign function to at least some of the UF genes/proteins, a global gene co-expression analysis was performed for the cestode species Echinococcus multilocularis. This resulted in eight UF genes/proteins being predicted as related to developmental, reproductive, vesicle transport, or signaling processes.

CONCLUSIONS

Overall, the described in silico data provided evidence of the involvement of 34 genes/proteins and at least 3 developmental pathways in the cestode strobilation process. These results highlight on the molecular mechanisms and evolution of the cestode strobilation process, and point to several interesting proteins as potential developmental markers and/or targets for the development of novel antihelminthic drugs.

The Importance of Vaccinating Children and Pregnant Women against Influenza Virus Infection

Influenza virus infection is responsible for significant morbidity and mortality in the pediatric and pregnant women populations, with deaths frequently caused by severe influenza-associated lower respiratory tract infection and acute respiratory distress syndrome (ARDS). An appropriate immune response requires controlling the viral infection through activation of antiviral defenses, which involves cells of the lung and immune system. High levels of viral infection or high levels of inflammation in the lower airways can contribute to ARDS. Pregnant women and young children, especially those born prematurely, may develop serious complications if infected with influenza virus. Vaccination against influenza will lead to lower infection rates and fewer complications, even if the vaccine is poorly matched to circulating viral strains, with maternal vaccination offering infants protection via antibody transmission through the placenta and breast milk. Despite the health benefits of the influenza vaccine, vaccination rates around the world remain well below targets. Trust in the use of vaccines among the public must be restored in order to increase vaccination rates and decrease the public health burden of influenza.

Recent advances in our understanding of the mechanisms of lung alveolarization and bronchopulmonary dysplasia

Bronchopulmonary dysplasia (BPD) is the most common cause of morbidity and mortality in preterm infants. A key histopathological feature of BPD is stunted late lung development, where the process of alveolarization-the generation of alveolar gas exchange units-is impeded, through mechanisms that remain largely unclear. As such, there is interest in the clarification both of the pathomechanisms at play in affected lungs, and the mechanisms of de novo alveoli generation in healthy, developing lungs. A better understanding of normal and pathological alveolarization might reveal opportunities for improved medical management of affected infants. Furthermore, disturbances to the alveolar architecture are a key histopathological feature of several adult chronic lung diseases, including emphysema and fibrosis, and it is envisaged that knowledge about the mechanisms of alveologenesis might facilitate regeneration of healthy lung parenchyma in affected patients. To this end, recent efforts have interrogated clinical data, developed new-and refined existing-in vivo and in vitro models of BPD, have applied new microscopic and radiographic approaches, and have developed advanced cell-culture approaches, including organoid generation. Advances have also been made in the development of other methodologies, including single-cell analysis, metabolomics, lipidomics, and proteomics, as well as the generation and use of complex mouse genetics tools. The objective of this review is to present advances made in our understanding of the mechanisms of lung alveolarization and BPD over the period 1 January 2017-30 June 2019, a period that spans the 50th anniversary of the original clinical description of BPD in preterm infants.

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.