Cameron P. Casey

SNaPP: Simplified Nanoproteomics Platform for Reproducible Global Proteomic Analysis of Nanogram Protein Quantities

Global proteomic analyses of complex protein samples in nanogram quantities require a fastidious approach to achieve in-depth protein coverage and quantitative reproducibility. Biological samples are often severely mass limited and can preclude the application of more robust bulk sample processing workflows. In this study, we present a system that minimizes sample handling by using online immobilized trypsin digestion and solid phase extraction to create a simple, sensitive, robust, and reproducible platform for the analysis of nanogram-size proteomic samples. To demonstrate the effectiveness of our simplified nanoproteomics platform, we used the system to analyze preimplantation blastocysts collected on day 4 of pregnancy by flushing the uterine horns with saline. For each of our three sample groups, blastocysts were pooled from three mice resulting in 22, 22, and 25 blastocysts, respectively. The resulting proteomic data provide novel insight into mouse blastocyst protein expression on day 4 of normal pregnancy because we characterized 348 proteins that were identified in at least two sample groups, including 59 enzymes and blastocyst specific proteins (eg, zona pellucida proteins). This technology represents an important advance in which future studies could perform global proteomic analyses of blastocysts obtained from an individual mouse, thereby enabling researchers to investigate interindividual variation as well as increase the statistical power without increasing animal numbers. This approach is also easily adaptable to other mass-limited sample types.

Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome

Although the gut microbiome plays important roles in host physiology, health and disease1, we lack understanding of the complex interplay between host genetics and early life environment on the microbial and metabolic composition of the gut. We used the genetically diverse Collaborative Cross mouse system2 to discover that early life history impacts the microbiome composition, whereas dietary changes have only a moderate effect. By contrast, the gut metabolome was shaped mostly by diet, with specific non-dietary metabolites explained by microbial metabolism. Quantitative trait analysis identified mouse genetic trait loci (QTL) that impact the abundances of specific microbes. Human orthologues of genes in the mouse QTL are implicated in gastrointestinal cancer. Additionally, genes located in mouse QTL for Lactobacillales abundance are implicated in arthritis, rheumatic disease and diabetes. Furthermore, Lactobacillales abundance was predictive of higher host T-helper cell counts, suggesting an important link between Lactobacillales and host adaptive immunity.

Sexual dimorphism in the fetal cardiac response to maternal nutrient restriction

Poor maternal nutrition causes intrauterine growth restriction (IUGR); however, its effects on fetal cardiac development are unclear. We have developed a baboon model of moderate maternal undernutrition, leading to IUGR. We hypothesized that the IUGR affects fetal cardiac structure and metabolism. Six control pregnant baboons ate ad-libitum (CTRL)) or 70% CTRL from 0.16 of gestation (G). Fetuses were euthanized at C-section at 0.9G under general anesthesia. Male but not female IUGR fetuses showed left ventricular fibrosis inversely correlated with birth weight. Expression of extracellular matrix protein TSP-1 was increased (p<0.05) in male IUGR. Expression of cardiac fibrotic markers TGFβ, SMAD3 and ALK-1 were downregulated in male IUGRs with no difference in females. Autophagy was present in male IUGR evidenced by upregulation of ATG7 expression and lipidation LC3B. Global miRNA expression profiling revealed 56 annotated and novel cardiac miRNAs exclusively dysregulated in female IUGR, and 38 cardiac miRNAs were exclusively dysregulated in males (p<0.05). Fifteen (CTRL) and 23 (IUGR) miRNAs, were differentially expressed between males and females (p<0.05) suggesting sexual dimorphism, which can be at least partially explained by differential expression of upstream transcription factors (e.g. HNF4α, and NFκB p50). Lipidomics analysis of fetal cardiac tissue exhibited a net increase in diacylglycerol and plasmalogens and a decrease in triglycerides and phosphatidylcholines. In summary, IUGR resulting from decreased maternal nutrition is associated with sex-dependent dysregulations in cardiac structure, miRNA expression, and lipid metabolism. If these changes persist postnatally, they may program offspring for higher later life cardiac risk.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry and Mass Spectrometry

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches.

Comparing identified and statistically significant lipids and polar metabolites in 15-year old serum and dried blood spot samples for longitudinal studies

RATIONALE The use of dried blood spots (DBS) has many advantages over traditional plasma and serum samples such as the smaller blood volume required, storage at room temperature, and ability to sample in remote locations. However, understanding the robustness of different analytes in DBS samples is essential, especially in older samples collected for longitudinal studies. METHODS Here we analyzed the stability of polar metabolites and lipids in DBS samples collected in 2000-2001 and stored at room temperature. The identified and statistically significant molecules were then compared to matched serum samples stored at -80°C to determine if the DBS samples could be effectively used in a longitudinal study following metabolic disease. RESULTS A total of 400 polar metabolites and lipids were identified in the serum and DBS samples using gas chromatograph/mass spectrometry (GC/MS), liquid chromatography (LC)/MS, and LC/ion mobility spectrometry-MS (LC/IMS-MS). The identified polar metabolites overlapped well between the sample types, though only one statistically significant metabolite was conserved in a case-control study of older diabetic males with low amounts of high-density lipoproteins and high body mass indices, triacylglycerides and glucose levels when compared to non-diabetic patients with normal levels, indicating that degradation in the DBS samples affects polar metabolite quantitation. Differences in the lipid identifications indicated that some oxidation occurs in the DBS samples. However, 36 statistically significant lipids correlated in both sample types. CONCLUSIONS The difference in the number of statistically significant polar metabolites and lipids indicated that the lipids did not degrade to as great of a degree as the polar metabolites in the DBS samples and lipid quantitation was still possible. Copyright

LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data

Summary: We introduce an open‐source software, LIQUID, for semi‐automated processing and visualization of LC‐MS/MS‐based lipidomics data. LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species. LIQUID was compared to other freely available software commonly used to identify lipids and other small molecules (e.g. CFM‐ID, MetFrag, GNPS, LipidBlast and MS‐DIAL), and was found to have a faster processing time to arrive at a higher number of validated lipid identifications. Availability and Implementation: LIQUID is available at http://github.com/PNNL‐Comp‐Mass‐Spec/LIQUID. Contact: jennifer.kyle@pnnl.gov or thomas.metz@pnnl.gov Supplementary information: Supplementary data are available at Bioinformatics online.

PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association

Motivation: Drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS‐MS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS at multiple electric fields and compute their associated collisional cross sections (CCS), we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of data that can then be used to create a reference library of experimental CCS values for use in high throughput omics analyses. Results: We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE‐generated CCS values were within error of those calculated using commercially available instrument vendor software. Availability and implementation: PIXiE is an open‐source tool, freely available on Github. The documentation, source code of the software, and a GUI can be found at https://github.com/PNNL‐Comp‐Mass‐Spec/PIXiE and the source code of the backend workflow library used by PIXiE can be found at https://github.com/PNNL‐Comp‐Mass‐Spec/IMS‐Informed‐Library. Contact: erin.baker@pnnl.gov or thomas.metz@pnnl.gov Supplementary information: Supplementary data are available at Bioinformatics online.

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

Mass spectrometry (MS)-based integrated metaproteomic, metabolomic, and lipidomic (multi-omic) studies are transforming our ability to understand and characterize microbial communities in environmental and biological systems. These measurements are even enabling enhanced analyses of complex soil microbial communities, which are the most complex microbial systems known to date. Multi-omic analyses, however, do have sample preparation challenges, since separate extractions are typically needed for each omic study, thereby greatly amplifying the preparation time and amount of sample required. To address this limitation, a 3-in-1 method for the simultaneous extraction of metabolites, proteins, and lipids (MPLEx) from the same soil sample was created by adapting a solvent-based approach. This MPLEx protocol has proven to be both simple and robust for many sample types, even when utilized for limited quantities of complex soil samples. The MPLEx method also greatly enabled the rapid multi-omic measurements needed to gain a better understanding of the members of each microbial community, while evaluating the changes taking place upon biological and environmental perturbations.

MERS-CoV and H5N1 influenza virus antagonize antigen presentation by altering the epigenetic landscape

Significance Both highly pathogenic avian influenza virus and Middle East respiratory syndrome coronavirus (MERS-CoV) infections are characterized by severe disease and high mortality. The continued threat of their emergence from zoonotic populations underscores an important need to understand the dynamics of their infection. By comparing the host responses across other related respiratory virus infections, these studies have identified a common avenue used by MERS-CoV and A/influenza/Vietnam/1203/2004 (H5N1-VN1203) influenza to antagonize antigen presentation through epigenetic modulation. Overall, the use of cross-comparisons provides an additional approach to leverage systems biology data to identify key pathways and strategies used by viruses to subvert host immune responses and may be critical in developing both vaccines and therapeutic treatment. Convergent evolution dictates that diverse groups of viruses will target both similar and distinct host pathways to manipulate the immune response and improve infection. In this study, we sought to leverage this uneven viral antagonism to identify critical host factors that govern disease outcome. Utilizing a systems-based approach, we examined differential regulation of IFN-γ–dependent genes following infection with robust respiratory viruses including influenza viruses [A/influenza/Vietnam/1203/2004 (H5N1-VN1203) and A/influenza/California/04/2009 (H1N1-CA04)] and coronaviruses [severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome CoV (MERS-CoV)]. Categorizing by function, we observed down-regulation of gene expression associated with antigen presentation following both H5N1-VN1203 and MERS-CoV infection. Further examination revealed global down-regulation of antigen-presentation gene expression, which was confirmed by proteomics for both H5N1-VN1203 and MERS-CoV infection. Importantly, epigenetic analysis suggested that DNA methylation, rather than histone modification, plays a crucial role in MERS-CoV–mediated antagonism of antigen-presentation gene expression; in contrast, H5N1-VN1203 likely utilizes a combination of epigenetic mechanisms to target antigen presentation. Together, the results indicate a common mechanism utilized by H5N1-VN1203 and MERS-CoV to modulate antigen presentation and the host adaptive immune response.