Glomerular filtrate proteins in acute cardiorenal syndrome

Acute cardiorenal syndrome (CRS-1) is a morbid complication of acute cardiovascular disease. Heart-to-kidney signals transmitted by "cardiorenal connectors" have been postulated, but investigation into CRS-1 has been limited by technical limitations and a paucity of models. To address these limitations, we developed a translational model of CRS-1, cardiac arrest and cardiopulmonary resuscitation (CA/CPR), and now report findings from nanoscale mass spectrometry proteomic exploration of glomerular filtrate 2 hours after CA/CPR or sham procedure. Filtrate acquisition was confirmed by imaging, molecular weight and charge distribution, and exclusion of protein specific to surrounding cells. Filtration of proteins specific to the heart was detected following CA/CPR and confirmed with mass spectrometry performed using urine collections from mice with deficient tubular endocytosis. Cardiac LIM protein was a CA/CPR-specific filtrate component. Cardiac arrest induced plasma release of cardiac LIM protein in mice and critically ill human cardiac arrest survivors, and administration of recombinant cardiac LIM protein to mice altered renal function. These findings demonstrate that glomerular filtrate is accessible to nanoscale proteomics and elucidate the population of proteins filtered 2 hours after CA/CPR. The identification of cardiac-specific proteins in renal filtrate suggests a novel signaling mechanism in CRS-1. We expect these findings to advance understanding of CRS-1.

Palm oil and dietary change: Application of an integrated macroeconomic, environmental, demographic, and health modelling framework for Thailand

Palm oil is a cooking oil and food ingredient in widespread use in the global food system. However, as a highly saturated fat, palm oil consumption has been associated with negative effects on cardiovascular health, while large scale oil palm production has been linked to deforestation. We construct an innovative fully integrated Macroeconomic-Environmental-Demographic-health (MED-health) model to undertake integrated health, environmental, and economic analyses of palm oil consumption and oil palm production in Thailand over the coming 20 years (2016-2035). In order to put a health and fiscal food policy perspective on policy priorities of future palm oil consumption growth, we model the implications of a 54% product-specific sales tax to achieve a halving of future energy intakes from palm cooking oil consumption. Total patient incidence and premature mortality from myocardial infarction and stroke decline by 0.03-0.16% and rural-urban equity in health and welfare improves in most regions. However, contrary to accepted wisdom, reduced oil palm production would not be environmentally beneficial in the Thailand case, since, once established, oil palms have favourable carbon sequestration characteristics compared to alternative uses of Thai cropland. The increased sales tax also provokes mixed economic impacts: While real GDP increases in a second-best Thai tax policy environment, relative consumption-to-investment price changes may reduce household welfare over extended periods unless accompanied by non-distortionary government compensation payments. Overall, our holistic approach demonstrates that product-specific fiscal food policy taxes may involve important trade-offs between nutrition, health, the economy, and the environment.

Inherent versus induced protein flexibility: Comparisons within and between apo and holo structures

Understanding how ligand binding influences protein flexibility is important, especially in rational drug design. Protein flexibility upon ligand binding is analyzed herein using 305 proteins with 2369 crystal structures with ligands (holo) and 1679 without (apo). Each protein has at least two apo and two holo structures for analysis. The inherent variation in structures with and without ligands is first established as a baseline. This baseline is then compared to the change in conformation in going from the apo to holo states to probe induced flexibility. The inherent backbone flexibility across the apo structures is roughly the same as the variation across holo structures. The induced backbone flexibility across apo-holo pairs is larger than that of the apo or holo states, but the increase in RMSD is less than 0.5 Å. Analysis of χ1 angles revealed a distinctly different pattern with significant influences seen for ligand binding on side-chain conformations in the binding site. Within the apo and holo states themselves, the variation of the χ1 angles is the same. However, the data combining both apo and holo states show significant displacements. Upon ligand binding, χ1 angles are frequently pushed to new orientations outside the range seen in the apo states. Influences on binding-site variation could not be easily attributed to features such as ligand size or x-ray structure resolution. By combining these findings, we find that most binding site flexibility is compatible with the common practice in flexible docking, where backbones are kept rigid and side chains are allowed some degree of flexibility.

Towards resolving the spatial metabolome with unambiguous molecular annotations in complex biological systems by coupling mass spectrometry imaging with structures for lossless ion manipulations

We demonstrate the coupling of liquid extraction surface analysis (LESA) to structures for lossless ion manipulations in conjunction with serpentine ultralong path with extending routing (SLIM SUPER) ion mobility-mass spectrometry (IM-MS) for the unambiguous annotation of important isomeric glycoforms in carbon-fixing communities.

Carrier-Assisted Single-Tube Processing Approach for Targeted Proteomics Analysis of Low Numbers of Mammalian Cells

Heterogeneity in composition is inherent in all cell populations, even those containing a single cell type. Single-cell proteomics characterization of cell heterogeneity is currently achieved by antibody-based technologies, which are limited by the availability of high-quality antibodies. Herein we report a simple, easily implemented, mass spectrometry (MS)-based targeted proteomics approach, termed cLC-SRM (carrier-assisted liquid chromatography coupled to selected reaction monitoring), for reliable multiplexed quantification of proteins in low numbers of mammalian cells. We combine a new single-tube digestion protocol to process low numbers of cells with minimal loss together with sensitive LC-SRM for protein quantification. This single-tube protocol builds upon trifluoroethanol digestion and further minimizes sample losses by tube pretreatment and the addition of carrier proteins. We also optimized the denaturing temperature and trypsin concentration to significantly improve digestion efficiency. cLC-SRM was demonstrated to have sufficient sensitivity for reproducible detection of most epidermal growth factor receptor (EGFR) pathway proteins expressed at levels ≥30 000 and ≥3000 copies per cell for 10 and 100 mammalian cells, respectively. Thus, cLC-SRM enables reliable quantification of low to moderately abundant proteins in less than 100 cells and could be broadly useful for multiplexed quantification of important proteins in small subpopulations of cells or in size-limited clinical samples. Further improvements of this method could eventually enable targeted single-cell proteomics when combined with either SRM or other emerging ultrasensitive MS detection.

Nanowell-mediated multidimensional separations combining nanoLC with SLIM IM-MS for rapid, high-peak-capacity proteomic analyses

Mass spectrometry (MS)-based analysis of complex biological samples is essential for biomedical research and clinical diagnostics. The separation prior to MS plays a key role in the overall analysis, with separations having larger peak capacities often leading to more identified species and improved confidence in those identifications. High-resolution ion mobility (IM) separations enabled by Structures for Lossless Ion Manipulation (SLIM) can provide extremely rapid, high-resolution separations and are well suited as a second dimension of separation following nanoscale liquid chromatography (nanoLC). However, existing sample handling approaches for offline coupling of separation modes require microliter-fraction volumes and are thus not well suited for analysis of trace biological samples. We have developed a novel nanowell-mediated fractionation system that enables nanoLC-separated samples to be efficiently preconcentrated and directly infused at nanoelectrospray flow rates for downstream analysis. When coupled with SLIM IM-MS, the platform enables rapid and high-peak-capacity multidimensional separations of small biological samples. In this study, peptides eluting from a 100 nL/min nanoLC separation were fractionated into ~ 60 nanowells on a microfluidic glass chip using an in-house-developed robotic system. The dried samples on the chip were individually reconstituted and ionized by nanoelectrospray for SLIM IM-MS analysis. Using model peptides for characterization of the nanowell platform, we found that at least 80% of the peptide components of the fractionated samples were recovered from the nanowells, providing up to ~tenfold preconcentration for SLIM IM-MS analysis. The combined LC-SLIM IM separation peak capacities exceeded 3600 with a measurement throughput that is similar to current one-dimensional (1D) LC-MS proteomic analyses. Graphical abstract A nanowell-mediated multidimensional separation platform that combines nanoLC with SLIM IM-MS enables rapid, high-peak-capacity proteomic analyses.

Using Skyline to Analyze Data-Containing Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Dimensions

Recent advances in ion mobility spectrometry (IMS) have illustrated its power in determining the structural characteristics of a molecule, especially when coupled with other separations dimensions such as liquid chromatography (LC) and mass spectrometry (MS). However, these three separation techniques together greatly complicate data analyses, making better informatics tools essential for assessing the resulting data. In this manuscript, Skyline was adapted to analyze LC-IMS-CID-MS data from numerous instrument vendor datasets and determine the effect of adding the IMS dimension into the normal LC-MS molecular pipeline. For the initial evaluation, a tryptic digest of bovine serum albumin (BSA) was spiked into a yeast protein digest at seven different concentrations, and Skyline was able to rapidly analyze the MS and CID-MS data for 38 of the BSA peptides. Calibration curves for the precursor and fragment ions were assessed with and without the IMS dimension. In all cases, addition of the IMS dimension removed noise from co-eluting peptides with close m/z values, resulting in calibration curves with greater linearity and lower detection limits. This study presents an important informatics development since to date LC-IMS-CID-MS data from the different instrument vendors is often assessed manually and cannot be analyzed quickly. Because these evaluations require days for the analysis of only a few target molecules in a limited number of samples, it is unfeasible to evaluate hundreds of targets in numerous samples. Thus, this study showcases Skyline's ability to work with the multidimensional LC-IMS-CID-MS data and provide biological and environmental insights rapidly. Graphical Abstract ᅟ.

Micropuncture of Bowman's Space in Mice Facilitated by 2 Photon Microscopy

Renal micropuncture and renal 2-photon imaging are seminal techniques in renal physiology. However, micropuncture is limited by dependence on conventional microscopy to surface nephron features, and 2-photon studies are limited in that interventions can only be assessed at the organ, rather than the nephron level. In particular, micropuncture studies of the glomeruli of mice have been challenged by the paucity of surface glomeruli in mice. To address this limitation in order to pursue studies of aspirate from Bowman's space in mouse physiologic models, we developed 2-photon glomerular micropuncture. We present a novel surgical preparation that allows lateral access to the kidney while preserving the required vertical imaging column for 2-photon microscopy. Administration of high molecular weight fluorescein isothiocyanate (FITC)-dextran is used to render the renal vasculature and therefore glomeruli visible for 2-photon imaging. A quantum dot-coated pipette is then introduced under stereotactic guidance to a glomerulus selected from the several to many which may be visualized within the imaging window. In this protocol, we provide details of the preparation, materials, and methods necessary to carry out the procedure. This technique facilitates previously-impossible physiologic study of the kidney, including recovery of filtrate from Bowman's space and all segments of the nephron within the imaging depth limit, about 100 µm below the renal capsule. Pressure, charge and flow may all be measured using the introduced pipette. Here, we provide representative data from liquid chromatography/mass spectrometry performed on aspirate from Bowman's space. We expect this technique to have wide applicability in renal physiologic investigation.

Unraveling the isomeric heterogeneity of glycans: ion mobility separations in structures for lossless ion manipulations

To address the challenges associated with glycan analyses, we have implemented a structures for lossless ion manipulations (SLIM) serpentine ultra-long path with extended routing (SUPER) ion mobility-mass spectrometry (i.e. SLIM SUPER IM-MS) platform to achieve much higher resolution of isomeric glycoforms. We have demonstrated the potential of this platform as a future component of the glycomics toolbox.

Improved Sensitivity and Separations for Phosphopeptides using Online Liquid Chromotography Coupled with Structures for Lossless Ion Manipulations Ion Mobility-Mass Spectrometry

Phosphoproteomics greatly augments proteomics and holds tremendous potential for insights into the modulation of biological systems for various disease states. However, numerous challenges hinder conventional methods in terms of measurement sensitivity, throughput, quantification, and capabilities for confident phosphopeptide and phosphosite identification. In this work, we report the first example of integrating structures for lossless ion manipulations ion mobility-mass spectrometry (SLIM IM-MS) with online reversed-phase liquid chromatography (LC) to evaluate its potential for addressing the aforementioned challenges. A mixture of 51 heavy-labeled phosphopeptides was analyzed with a SLIM IM module having integrated ion accumulation and long-path separation regions. The SLIM IM-MS provided limits of detection as low as 50-100 pM (50-100 amol/μL) for several phosphopeptides, with the potential for significant further improvements. In addition, conventionally problematic phosphopeptide isomers could be resolved following an 18 m SLIM IM separation. The 2-D LC-IM peak capacity was estimated as ∼9000 for a 90 min LC separation coupled to an 18 m SLIM IM separation, considerably higher than LC alone and providing a basis for both improved identification and quantification, with additional gains projected with the future use of longer path SLIM IM separations. Thus, LC-SLIM IM-MS offers great potential for improving the sensitivity, separation, and throughput of phosphoproteomics analyses.

Distinguishing enantiomeric amino acids with chiral cyclodextrin adducts and structures for lossless ion manipulations

Enantiomeric molecular evaluations remain an enormous challenge for current analytical techniques. To date, derivatization strategies and long separation times are generally required in these studies, and the development and implementation of new approaches are needed to increase speed and distinguish currently unresolvable compounds. Herein, we describe a method using chiral cyclodextrin adducts and structures for lossless ion manipulations (SLIM) and serpentine ultralong path with extended routing (SUPER) ion mobility (IM) to achieve rapid, high resolution separations of d and l enantiomeric amino acids. In the analyses, a chiral cyclodextrin is added to each sample. Two cyclodextrins were found to complex each amino acid molecule (i.e. potentially sandwiching the amino acid in their cavities) and forming host-guest noncovalent complexes that were distinct for each d and l amino acid pair studied and thus separable with IM in SLIM devices. The SLIM was also used to accumulate much larger ion populations than previously feasible for evaluation and therefore allow enantiomeric measurements of higher sensitivity, with gains in resolution from our ultralong path separation capabilities, than previously reported by any other IM-based approach.

Physiological and proteomic analyses of Fe(III)-reducing co-cultures of Desulfotomaculum reducens MI-1 and Geobacter sulfurreducens PCA

We established Fe(III)-reducing co-cultures of two species of metal-reducing bacteria, the Gram-positive Desulfotomaculum reducens MI-1 and the Gram-negative Geobacter sulfurreducens PCA. Co-cultures were given pyruvate, a substrate that D. reducens can ferment and use as electron donor for Fe(III) reduction. G. sulfurreducens relied upon products of pyruvate oxidation by D. reducens (acetate, hydrogen) for use as electron donor in the co-culture. Co-cultures reduced Fe(III) to Fe(II) robustly, and Fe(II) was consistently detected earlier in co-cultures than pure cultures. Notably, faster cell growth, and correspondingly faster pyruvate oxidation, was observed by D. reducens in co-cultures. Global comparative proteomic analysis was performed to observe differential protein abundance during co-culture vs. pure culture growth. Proteins previously associated with Fe(III) reduction in G. sulfurreducens, namely c-type cytochromes and type IV pili proteins, were significantly increased in abundance in co-cultures relative to pure cultures. D. reducens ribosomal proteins were significantly increased in co-cultures, likely a reflection of faster growth rates observed for D. reducens cells while in co-culture. Furthermore, we developed multiple reaction monitoring (MRM) assays to quantitate specific biomarker peptides. The assays were validated in pure and co-cultures, and protein abundance ratios from targeted MRM and global proteomic analysis correlate significantly.

The human brainome: network analysis identifies HSPA2 as a novel Alzheimer’s disease target

Our hypothesis is that changes in gene and protein expression are crucial to the development of late-onset Alzheimer’s disease. Previously we examined how DNA alleles control downstream expression of RNA transcripts and how those relationships are changed in late-onset Alzheimer’s disease. We have now examined how proteins are incorporated into networks in two separate series and evaluated our outputs in two different cell lines. Our pipeline included the following steps: (i) predicting expression quantitative trait loci; (ii) determining differential expression; (iii) analysing networks of transcript and peptide relationships; and (iv) validating effects in two separate cell lines. We performed all our analysis in two separate brain series to validate effects. Our two series included 345 samples in the first set (177 controls, 168 cases; age range 65–105; 58% female; KRONOSII cohort) and 409 samples in the replicate set (153 controls, 141 cases, 115 mild cognitive impairment; age range 66–107; 63% female; RUSH cohort). Our top target is heat shock protein family A member 2 (HSPA2), which was identified as a key driver in our two datasets. HSPA2 was validated in two cell lines, with overexpression driving further elevation of amyloid-β40 and amyloid-β42 levels in APP mutant cells, as well as significant elevation of microtubule associated protein tau and phosphorylated-tau in a modified neuroglioma line. This work further demonstrates that studying changes in gene and protein expression is crucial to understanding late onset disease and further nominates HSPA2 as a specific key regulator of late-onset Alzheimer’s disease processes.10.1093/brain/awy215_video1awy215media15824729224001.

Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those because of collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality because of the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality because of both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.

Rapid Ion Mobility Separations of Bile Acid Isomers Using Cyclodextrin Adducts and Structures for Lossless Ion Manipulations

Bile acids (BAs) constitute an important class of steroid metabolites often displaying changes associated with disease states and other health conditions. Current analyses for these structurally similar compounds are limited by a lack of sensitivity and long separation times with often poor isomeric resolution. To overcome these challenges and provide rapid analyses for the BA isomers, we utilized cyclodextrin adducts in conjunction with novel ion mobility (IM) separation capabilities provided by structures for lossless ion manipulations (SLIM). Cyclodextrin was found to interact with both the tauro- and glyco-conjugated BA isomers studied, forming rigid noncovalent host-guest inclusion complexes. Without the use of cyclodextrin adducts, the BA isomers were found to be nearly identical in their respective mobilities and thus unable to be baseline resolved. Each separation of the cyclodextrin-bile acid host-guest inclusion complex was performed in less than 1 s, providing a much more rapid alternative to current liquid chromatography-based separations. SLIM provided capabilities for the accumulation of larger ion populations and IM peak compression that resulted in much higher resolution separations and increased signal intensities for the BA isomers studied.

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.

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis

Rationale:

The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment.

Objective:

We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy.

Methods:

Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points.

Results:

A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status.

Conclusion:

A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Abstract 284: Integrated proteogenomic analysis of laser microdissected primary breast tumors define proteome clusters

Introduction: Breast tumors have 4 well-established intrinsic subtypes based on transcriptome profiling. However, clusters defined by proteomics are often in disagreement with those defined by transcriptomics. Here, we report the findings of proteogenomic profiling of 118 laser microdissected (LMD) breast tumors using RNA-Seq and mass-spectrometry (MS)-based proteomic technologies.

Methods: Cases used in this study were drawn from the Clinical Breast Care Project, with patients consented using an IRB-approved protocol. A total of 118 primary breast tumors embedded in OCT were selected and processed by LMD. Total RNA and protein were extracted using the Illustra triplePrep kit. Paired-end RNA sequencing of 118 cases was performed using the Illumina HiSeq platform, and the reads were preprocessed using a PERL-based pipeline involving the preprocessing tool PRINSEQ, splice-aligner GSNAP and HTSeq for quantifying expression. Quantitative global proteomics analyses were performed on 113 cases using isobaric TMT 6-plex labeling with the “universal reference” strategy. MS data were acquired using a Q-Exactive instrument and analyzed using Proteome Discoverer with Byonic node. Sample-to-sample normalization was conducted to remove pipetting errors and ComBat was used to remove batch effect. K-means clustering was done using Bioconductor package Consensusclustering.

Results: The number of preprocessed RNA sequencing reads for the 118 cases ranged from over 43 to 295 million. An average of 83% of reads was mapped, and 24,518 genes with a mean expression of ≥ 10 counts across 118 tumor samples were identified. The PAM50 algorithm was used for intrinsic subtyping, yielding 37 Basal-like, 16 HER2-enriched, 39 Luminal A and 26 Luminal B calls. Unsupervised clustering of 3,000 highly varying genes reflected 4 intrinsic subtypes. In the global proteomics data, 840 proteins were identified across all 113 cases. Unsupervised K-means consensus clustering on all 840 or just using the top 210 highly varying proteins indicated the optimal number of clusters to be 3. These 3 clusters were identified as Basal-enriched, Luminal A-enriched and Luminal B-enriched. HER2-enriched cases were distributed among these clusters.

We did not observe a stromal-enriched cluster in this analysis of LMD-prepared samples that selected against stromal components of the tumor.

Conclusion: Analysis of LMD breast tumors using proteogenomic technologies resulted in 3 clusters for proteome data: basal-enriched, luminal A-enriched and luminal B-enriched. Unlike a recent report on proteomics clustering using bulk processing of tumors, a stromal-enriched cluster was not observed in this analysis which excluded stromal components of the samples.

The views expressed in this abstract are those of the author and do not reflect the official policy of the Department of Army/Navy/Air Force, Department of Defense, or U.S. Government.

Citation Format: Praveen-Kumar Raj-Kumar, Tao Liu, Lori A. Sturtz, Albert J. Kovatich, Marina A. Gritsenko, Vladislav A. Petyuk, Brenda Deyarmin, Viswanadham Sridhara, James Craig, Jason E. McDermott, Anil K. Shukla, Ronald J. Moore, Matthew E. Monroe, Bobbie-Jo M. Webb-Robertson, Jeffrey A. Hooke, J.Leigh Fantacone-Campbell, Leonid Kvecher, Jianfang Liu, Jennifer Kane, Jennifer Melley, Stella Somiari, Stephen C. Benz, Justin Golovato, Shahrooz Rabizadeh, Patrick Soon-Shiong, Richard D. Smith, Richard J. Mural, Karin D. Rodland, Craig D. Shriver, Hai Hu. Integrated proteogenomic analysis of laser microdissected primary breast tumors define proteome clusters [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 284.

Characterization of applied fields for ion mobility separations in traveling wave based structures for lossless ion manipulations (SLIM)

Ion mobility (IM) is rapidly gaining attention for the separation and analysis of biomolecules due to the ability to distinguish the shapes of ions. However, conventional constant electric field drift tube IM separations have limited resolving power, constrained by practical limitations on the path length and maximum applied voltage. The implementation of traveling waves (TW) in IM removes the latter limitation, allowing higher resolution to be achieved using extended path lengths. Both of these can be readily obtained in structures for lossless ion manipulations (SLIM), which are fabricated from arrays of electrodes patterned on two parallel surfaces where potentials are applied to generate appropriate electric fields between the surfaces. Here we have investigated the relationship between the primary SLIM variables, such as electrode dimensions, inter-surface gap, and the applied TW voltages, that directly impact the fields experienced by ions. Ion trajectory simulations and theoretical calculations have been utilized to understand the dependence of SLIM geometry and effective electric fields on IM resolution. The variables explored impact both ion confinement and the observed IM resolution using SLIM modules.

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 β-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 β-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 β-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 β-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 β-amyloid deposition and another affecting resilience without a known pathological footprint. Ann Neurol 2018;83:78-88.

Specialized proteomic responses and an ancient photoprotection mechanism sustain marine green algal growth during phosphate limitation

Marine algae perform approximately half of global carbon fixation, but their growth is often limited by the availability of phosphate or other nutrients^1,2. As oceans warm, the area of phosphate-limited surface waters is predicted to increase, resulting in ocean desertification^3,4. Understanding the responses of key eukaryotic phytoplankton to nutrient limitation is therefore critical^5,6. We used advanced photo-bioreactors to investigate how the widespread marine green alga Micromonas commoda grows under transitions from replete nutrients to chronic phosphate limitation and subsequent relief, analysing photosystem changes and broad cellular responses using proteomics, transcriptomics and biophysical measurements. We find that physiological and protein expression responses previously attributed to stress are critical to supporting stable exponential growth when phosphate is limiting. Unexpectedly, the abundance of most proteins involved in light harvesting does not change, but an ancient light-harvesting-related protein, LHCSR, is induced and dissipates damaging excess absorbed light as heat throughout phosphate limitation. Concurrently, a suite of uncharacterized proteins with narrow phylogenetic distributions increase multifold. Notably, of the proteins that exhibit significant changes, 70% are not differentially expressed at the mRNA transcript level, highlighting the importance of post-transcriptional processes in microbial eukaryotes. Nevertheless, transcript-protein pairs with concordant changes were identified that will enable more robust interpretation of eukaryotic phytoplankton responses in the field from metatranscriptomic studies. Our results show that P-limited Micromonas responds quickly to a fresh pulse of phosphate by rapidly increasing replication, and that the protein network associated with this ability is composed of both conserved and phylogenetically recent proteome systems that promote dynamic phosphate homeostasis. That an ancient mechanism for mitigating light stress is central to sustaining growth during extended phosphate limitation highlights the possibility of interactive effects arising from combined stressors under ocean change, which could reduce the efficacy of algal strategies for optimizing marine photosynthesis.

Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets

Current mass spectrometry (MS)-based proteomics approaches are ineffective for mapping protein expression in tissue sections with high spatial resolution because of the limited overall sensitivity of conventional workflows. Here we report an integrated and automated method to advance spatially resolved proteomics by seamlessly coupling laser capture microdissection (LCM) with a recently developed nanoliter-scale sample preparation system termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples). The workflow is enabled by prepopulating nanowells with DMSO, which serves as a sacrificial capture liquid for microdissected tissues. The DMSO droplets efficiently collect laser-pressure catapulted LCM tissues as small as 20 μm in diameter with success rates >87%. We also demonstrate that tissue treatment with DMSO can significantly improve proteome coverage, likely due to its ability to dissolve lipids from tissue and enhance protein extraction efficiency. The LCM-nanoPOTS platform was able to identify 180, 695, and 1827 protein groups on average from 12-μm-thick rat brain cortex tissue sections having diameters of 50, 100, and 200 μm, respectively. We also analyzed 100-μm-diameter sections corresponding to 10-18 cells from three different regions of rat brain and comparatively quantified ∼1000 proteins, demonstrating the potential utility for high-resolution spatially resolved mapping of protein expression in tissues.

Proteomic Analysis of Single Mammalian Cells Enabled by Microfluidic Nanodroplet Sample Preparation and Ultrasensitive NanoLC-MS

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.