Robert T. Lawrence

The Proteomic Landscape of Triple-Negative Breast Cancer

Triple-negative breast cancer is a heterogeneous disease characterized by poor clinical outcomes and a shortage of targeted treatment options. To discover molecular features of triple-negative breast cancer, we performed quantitative proteomics analysis of twenty human-derived breast cell lines and four primary breast tumors to a depth of more than 12,000 distinct proteins. We used this data to identify breast cancer subtypes at the protein level and demonstrate the precise quantification of biomarkers, signaling proteins, and biological pathways by mass spectrometry. We integrated proteomics data with exome sequence resources to identify genomic aberrations that affect protein expression. We performed a high-throughput drug screen to identify protein markers of drug sensitivity and understand the mechanisms of drug resistance. The genome and proteome provide complementary information that, when combined, yield a powerful engine for therapeutic discovery. This resource is available to the cancer research community to catalyze further analysis and investigation.

Genetic inhibition of hepatic acetyl-CoA carboxylase activity increases liver fat and alters global protein acetylation

Lipid deposition in the liver is associated with metabolic disorders including fatty liver disease, type II diabetes, and hepatocellular cancer. The enzymes acetyl-CoA carboxylase 1 (ACC1) and ACC2 are powerful regulators of hepatic fat storage; therefore, their inhibition is expected to prevent the development of fatty liver. In this study we generated liver-specific ACC1 and ACC2 double knockout (LDKO) mice to determine how the loss of ACC activity affects liver fat metabolism and whole-body physiology. Characterization of LDKO mice revealed unexpected phenotypes of increased hepatic triglyceride and decreased fat oxidation. We also observed that chronic ACC inhibition led to hyper-acetylation of proteins in the extra-mitochondrial space. In sum, these data reveal the existence of a compensatory pathway that protects hepatic fat stores when ACC enzymes are inhibited. Furthermore, we identified an important role for ACC enzymes in the regulation of protein acetylation in the extra-mitochondrial space.

Plug-and-play analysis of the human phosphoproteome by targeted high-resolution mass spectrometry

Systematic approaches to studying cellular signaling require phosphoproteomic techniques that reproducibly measure the same phosphopeptides across multiple replicates, conditions, and time points. Here we present a method to mine information from large-scale, heterogeneous phosphoproteomics data sets to rapidly generate robust targeted mass spectrometry (MS) assays. We demonstrate the performance of our method by interrogating the IGF-1/AKT signaling pathway, showing that even rarely observed phosphorylation events can be consistently detected and precisely quantified.

Quantitative proteomic analysis of the adipocyte plasma membrane

The adipocyte is a key regulator of mammalian metabolism. To advance our understanding of this important cell, we have used quantitative proteomics to define the protein composition of the adipocyte plasma membrane (PM) in the presence and absence of insulin. Using this approach, we have identified a high confidence list of 486 PM proteins, 52 of which potentially represent novel cell surface proteins, including a member of the adiponectin receptor family and an unusually high number of hydrolases with no known function. Several novel insulin-responsive proteins including the sodium/hydrogen exchanger, NHE6 and the collagens III and VI were also identified, and we provide evidence of PM-ER association suggestive of a unique functional association between these two organelles in the adipocyte. Together these studies provide a wealth of potential therapeutic targets for the manipulation of adipocyte function and a valuable resource for metabolic research and PM biology.

Not all fat is equal: differential gene expression and potential therapeutic targets in subcutaneous adipose, visceral adipose, and endometrium of obese women with and without endometrial cancer.

Objective To identify obesity-related cancer genes in endometrial and adipose tissue depots of body mass index–matched morbidly obese women with and without endometrial cancer. Methods Eight women undergoing hysterectomy (4 women with and 4 women without endometrial cancer) were matched by age (52.6 years) and body mass index (44.5 kg/m2). Endometrium, visceral adipose tissue, and subcutaneous adipose tissue were collected and subjected to microarray analysis using Affymetrix Human Genome U133 Plus 2.0 Arrays. Gene set enrichment analysis used to extract biological information from the gene expression data and t test metric ranked and compared genes in the expression data set. Protein expression was measured in the endometrial samples, and serum was collected for hormone/metabolite assays. Results No significant differences were detected in hormone/metabolite levels between groups. Gene set enrichment analysis comparisons demonstrated that endometrial, visceral adipose and subcutaneous adipose tissues displayed 40, 47, and 38 alternatively regulated gene set pathways when comparing patients with and without cancer. Nineteen gene sets were alternately regulated in both visceral and subcutaneous adipose tissues; however, eighteen of these were regulated in the opposite direction. Five pathways were significantly and alternately regulated in all 3 tissue types and included glycolysis/gluconeogenesis, ribosome, peroxisome proliferator activated receptor signaling, pathogenic Escherichia coli infection, and natural killer–mediated cytotoxicity. In the malignant endometrium, liver kinase B1 underexpression was observed in all patients with cancer. Liver kinase B1 underexpression decreased adenosine monophosphate–activated protein kinase activity toward acetyl-CoA carboxylase and implied enhanced lipid biosynthesis in obesity-induced endometrial cancer. Conclusions Subcutaneous and visceral adipose tissue depots have opposite patterns of gene expression in obese patients with and without endometrial cancer. The altered de novo lipogenesis and individual gene targets identified provide new potential targets for cancer treatment and prevention for at-risk obese women.

Lipin 2 binds phosphatidic acid by the electrostatic hydrogen bond switch mechanism independent of phosphorylation

Background: Lipin 2 is a phosphatidic acid phosphatase (PAP) responsible for DAG formation at the ER membrane during lipogenesis. Results: A combination of biochemical approaches is used to characterize lipin 2 phosphatase activity and regulation. Conclusion: The electrostatic charge of PA regulates activity, but phosphorylation does not. Significance: These findings demonstrate differential regulation of PAP activity within the lipin family. Lipin 2 is a phosphatidic acid phosphatase (PAP) responsible for the penultimate step of triglyceride synthesis and dephosphorylation of phosphatidic acid (PA) to generate diacylglycerol. The lipin family of PA phosphatases is composed of lipins 1–3, which are members of the conserved haloacid dehalogenase superfamily. Although genetic alteration of LPIN2 in humans is known to cause Majeed syndrome, little is known about the biochemical regulation of its PAP activity. Here, in an attempt to gain a better general understanding of the biochemical nature of lipin 2, we have performed kinetic and phosphorylation analyses. We provide evidence that lipin 2, like lipin 1, binds PA via the electrostatic hydrogen bond switch mechanism but has a lower rate of catalysis. Like lipin 1, lipin 2 is highly phosphorylated, and we identified 15 phosphosites. However, unlike lipin 1, the phosphorylation of lipin 2 is not induced by insulin signaling nor is it sensitive to inhibition of the mammalian target of rapamycin. Importantly, phosphorylation of lipin 2 does not negatively regulate either membrane binding or PAP activity. This suggests that lipin 2 functions as a constitutively active PA phosphatase in stark contrast to the high degree of phosphorylation-mediated regulation of lipin 1. This knowledge of lipin 2 regulation is important for a deeper understanding of how the lipin family functions with respect to lipid synthesis and, more generally, as an example of how the membrane environment around PA can influence its effector proteins.

Drafts of the human proteome.

volume 32 number 8 august 2014 nature biotechnology Robert T. Lawrence and Judit Villén are at the Department of Genome Sciences, University of Washington, Seattle, Washington, USA. e-mail: jvillen@u.washington.edu Kim et al.3 and Wilhelm et al.4 devoted considerable effort to developing potential applications of their datasets. To delimit a ‘core’ set of proteins expressed by all tissues and cells versus proteins that are more specifically expressed, Kim et al.3 identified 2,350 proteins that were found in every sample and accounted for the majority of bulk protein mass. Wilhelm et al.4 compared the five largest human proteomics datasets, including the 27 tissues profiled in-house for this study, to identify 10,000–12,000 ubiquitously expressed proteins that primarily function in cellular control and maintenance. To study differential expression patterns, they pooled the 100 most abundant proteins from each tissue and compared the expression of this set of proteins across the dataset. Surprisingly, although these proteins were identified in a majority of samples, their abundance varied by as much as five orders of magnitude. The two studies also investigated additional features of the proteome such as post-translational modifications, isoform-specific expression, protein complexes and translational control. are no longer expressed by human cells. Still others might only be expressed with extreme spatiotemporal specificity and represent gaps that might eventually be filled in by the proteomics community. Aggregating the results of diverse projects to generate ‘big data’ has been a considerable challenge in genome sciences, as exemplified by the Encyclopedia of DNA Elements (ENCODE)7. Aggregation of proteomics data introduces its own unique set of hurdles stemming from the volume of data that must be handled as well as the variability in data quality and sensitivity. Wilhelm et al.4 comment on issues related to data aggregation such as the scalability of the false discovery rate for protein identification. They suggest several reasons why current approaches to estimate false discovery rates do not scale well for big data projects and emphasize the importance of developing new statistical methods to cope with large datasets. They also systematically evaluated several quantification methods before deciding how to integrate data from different sources and concluded that it is feasible to compare disparate samples accurately. A little more than a decade since the initial sequencing of the human genome1,2, two independent research teams have now assembled mass spectrometry–based maps of protein expression throughout the human body3,4. These endeavors complement other ambitious proteomics projects, such as the Human Protein Atlas5, which relies on antibody staining to catalog the precise location of proteins within cells and tissues, and the Human Proteome Project6, a consortium effort that uses both mass spectrometry and antibody technologies to characterize the role of each protein in human biology and disease. The resources generated by the new studies—Human Proteome Map3 (http://www.humanproteomemap.org/) and ProteomicsDB4 (https:// www.proteomicsdb.org/)—should be useful to researchers across the biomedical sciences. Together, the two reports comprise >70 million confidently assigned mass spectra, each of which is like a fingerprint in that it uniquely matches a particular protein fragment. In each study, >17,000 proteins encoded by distinct genes were identified. Kim et al.3 systematically examined 30 different human tissues, including 7 fetal tissues and 6 hematopoietic cell types. Wilhelm et al.4 combined their own data from a similar number of tissues with > 10,000 publicly available raw data files to generate a database encompassing 60 human tissues, 147 cell lines and 13 body fluids. The analyzed specimens included some of the most widely studied tissues, such as liver, heart and kidney, as well as tissues that have received less attention, such as synovial fluid and gall bladder. The 18,097 proteins from Wilhelm et al.4 establish a new baseline for the number of proteins in the human proteome; they represent 92% of open reading frames included in the Swiss-Prot database. The remaining 8% of proteins are missing for various reasons. The authors suggest that several hundred of these proteins are not accessible to mass spectrometric analysis after digestion with commonly used proteases such as trypsin. Many others might be pseudogenes—by-products of evolution that Drafts of the human proteome

The phosphatidic acid–binding, polybasic domain is responsible for the differences in the phosphoregulation of lipins 1 and 3

Lipins 1, 2, and 3 are Mg2+-dependent phosphatidic acid phosphatases and catalyze the penultimate step of triacylglycerol synthesis. We have previously investigated the biochemistry of lipins 1 and 2 and shown that di-anionic phosphatidic acid (PA) augments their activity and lipid binding and that lipin 1 activity is negatively regulated by phosphorylation. In the present study, we show that phosphorylation does not affect the catalytic activity of lipin 3 or its ability to associate with PA in vitro. The lipin proteins each contain a conserved polybasic domain (PBD) composed of nine lysine and arginine residues located between the conserved N- and C-terminal domains. In lipin 1, the PBD is the site of PA binding and sensing of the PA electrostatic charge. The specific arrangement and number of the lysines and arginines of the PBD vary among the lipins. We show that the different PBDs of lipins 1 and 3 are responsible for the presence of phosphoregulation on the former but not the latter enzyme. To do so, we generated lipin 1 that contained the PBD of lipin 3 and vice versa. The lipin 1 enzyme with the lipin 3 PBD lost its ability to be regulated by phosphorylation but remained downstream of phosphorylation by mammalian target of rapamycin. Conversely, the presence of the lipin 1 PBD in lipin 3 subjected the enzyme to negative intramolecular control by phosphorylation. These results indicate a mechanism for the observed differences in lipin phosphoregulation in vitro.

Comprehensive peptide quantification for data independent acquisition mass spectrometry using chromatogram libraries

Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. We introduce a new experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in an experiment. These coordinates calibrate information in spectrum libraries or protein databases to a specific mass spectrometer and chromatography setup, and enable sensitive peptide detection in quantitative experiments. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect and quantify >50% more peptides from DIA experiments than with DDA-based spectrum libraries alone.

A practical recipe to survey phosphoproteomes.

The field of cellular signaling is fueled by the discovery of novel protein phosphorylation events. Phosphoproteomics focuses on the large-scale identification and characterization of serine, threonine, and tyrosine phosphorylation of proteins. Phosphopeptide enrichment followed by mass spectrometry has emerged as the most powerful technique for unbiased, discovery-driven analysis by offering high sensitivity, resolution, and speed. Methods for mass spectrometry-based phosphoproteomics analysis have improved substantially over the last decade, making the discipline more approachable to the broader scientific community. Herein we describe the status of the field of phosphoproteomics and provide a robust workflow covering the major aspects of large-scale phosphorylation analysis from phosphopeptide enrichment via IMAC to data analysis.