Brian K. Erickson

The BioPlex Network: A Systematic Exploration of the Human Interactome

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors.

MultiNotch MS3 Enables Accurate, Sensitive, and Multiplexed Detection of Differential Expression across Cancer Cell Line Proteomes

Multiplexed quantitation via isobaric chemical tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantitation (iTRAQ)) has the potential to revolutionize quantitative proteomics. However, until recently the utility of these tags was questionable due to reporter ion ratio distortion resulting from fragmentation of coisolated interfering species. These interfering signals can be negated through additional gas-phase manipulations (e.g., MS/MS/MS (MS3) and proton-transfer reactions (PTR)). These methods, however, have a significant sensitivity penalty. Using isolation waveforms with multiple frequency notches (i.e., synchronous precursor selection, SPS), we coisolated and cofragmented multiple MS2 fragment ions, thereby increasing the number of reporter ions in the MS3 spectrum 10-fold over the standard MS3 method (i.e., MultiNotch MS3). By increasing the reporter ion signals, this method improves the dynamic range of reporter ion quantitation, reduces reporter ion signal variance, and ultimately produces more high-quality quantitative measurements. To demonstrate utility, we analyzed biological triplicates of eight colon cancer cell lines using the MultiNotch MS3 method. Across all the replicates we quantified 8 378 proteins in union and 6 168 proteins in common. Taking into account that each of these quantified proteins contains eight distinct cell-line measurements, this data set encompasses 174 704 quantitative ratios each measured in triplicate across the biological replicates. Herein, we demonstrate that the MultiNotch MS3 method uniquely combines multiplexing capacity with quantitative sensitivity and accuracy, drastically increasing the informational value obtainable from proteomic experiments.

Effects of diet on resource utilization by a model human gut microbiota containing Bacteroides cellulosilyticus WH2, a symbiont with an extensive glycobiome.

Artificial human gut microbial communities implanted into germ-free mice provide insights into how species-level responses to changes in diet give rise to community-level structural and functional reconfiguration and how types of bacteria prioritize use of available nutrients in vivo.

Architecture of the human interactome defines protein communities and disease networks

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein–protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification–mass spectrometry methodology to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.

Mitochondrial ROS regulate thermogenic energy expenditure and sulfenylation of UCP1

Brown and beige adipose tissues can dissipate chemical energy as heat through thermogenic respiration, which requires uncoupling protein 1 (UCP1). Thermogenesis from these adipocytes can combat obesity and diabetes, encouraging investigation of factors that control UCP1-dependent respiration in vivo. Here we show that acutely activated thermogenesis in brown adipose tissue is defined by a substantial increase in levels of mitochondrial reactive oxygen species (ROS). Remarkably, this process supports in vivo thermogenesis, as pharmacological depletion of mitochondrial ROS results in hypothermia upon cold exposure, and inhibits UCP1-dependent increases in whole-body energy expenditure. We further establish that thermogenic ROS alter the redox status of cysteine thiols in brown adipose tissue to drive increased respiration, and that Cys253 of UCP1 is a key target. UCP1 Cys253 is sulfenylated during thermogenesis, while mutation of this site desensitizes the purine-nucleotide-inhibited state of the carrier to adrenergic activation and uncoupling. These studies identify mitochondrial ROS induction in brown adipose tissue as a mechanism that supports UCP1-dependent thermogenesis and whole-body energy expenditure, which opens the way to improved therapeutic strategies for combating metabolic disorders.

Evaluating Multiplexed Quantitative Phosphopeptide Analysis on a Hybrid Quadrupole Mass Filter/Linear Ion Trap/Orbitrap Mass Spectrometer

As a driver for many biological processes, phosphorylation remains an area of intense research interest. Advances in multiplexed quantitation utilizing isobaric tags (e.g., TMT and iTRAQ) have the potential to create a new paradigm in quantitative proteomics. New instrumentation and software are propelling these multiplexed workflows forward, which results in more accurate, sensitive, and reproducible quantitation across tens of thousands of phosphopeptides. This study assesses the performance of multiplexed quantitative phosphoproteomics on the Orbitrap Fusion mass spectrometer. Utilizing a two-phosphoproteome model of precursor ion interference, we assessed the accuracy of phosphopeptide quantitation across a variety of experimental approaches. These methods included the use of synchronous precursor selection (SPS) to enhance TMT reporter ion intensity and accuracy. We found that (i) ratio distortion remained a problem for phosphopeptide analysis in multiplexed quantitative workflows, (ii) ratio distortion can be overcome by the use of an SPS-MS3 scan, (iii) interfering ions generally possessed a different charge state than the target precursor, and (iv) selecting only the phosphate neutral loss peak (single notch) for the MS3 scan still provided accurate ratio measurements. Remarkably, these data suggest that the underlying cause of interference may not be due to coeluting and cofragmented peptides but instead from consistent, low level background fragmentation. Finally, as a proof-of-concept 10-plex experiment, we compared phosphopeptide levels from five murine brains to five livers. In total, the SPS-MS3 method quantified 38 247 phosphopeptides, corresponding to 11 000 phosphorylation sites. With 10 measurements recorded for each phosphopeptide, this equates to more than 628 000 binary comparisons collected in less than 48 h.

Strategies for Metagenomic-Guided Whole-Community Proteomics of Complex Microbial Environments

Accurate protein identification in large-scale proteomics experiments relies upon a detailed, accurate protein catalogue, which is derived from predictions of open reading frames based on genome sequence data. Integration of mass spectrometry-based proteomics data with computational proteome predictions from environmental metagenomic sequences has been challenging because of the variable overlap between proteomic datasets and corresponding short-read nucleotide sequence data. In this study, we have benchmarked several strategies for increasing microbial peptide spectral matching in metaproteomic datasets using protein predictions generated from matched metagenomic sequences from the same human fecal samples. Additionally, we investigated the impact of mass spectrometry-based filters (high mass accuracy, delta correlation), and de novo peptide sequencing on the number and robustness of peptide-spectrum assignments in these complex datasets. In summary, we find that high mass accuracy peptide measurements searched against non-assembled reads from DNA sequencing of the same samples significantly increased identifiable proteins without sacrificing accuracy.

The Nuclear Proteome of a Vertebrate

The composition of the nucleoplasm determines the behavior of key processes such as transcription, yet there is still no reliable and quantitative resource of nuclear proteins. Furthermore, it is still unclear how the distinct nuclear and cytoplasmic compositions are maintained. To describe the nuclear proteome quantitatively, we isolated the large nuclei of frog oocytes via microdissection and measured the nucleocytoplasmic partitioning of ∼9,000 proteins by mass spectrometry. Most proteins localize entirely to either nucleus or cytoplasm; only ∼17% partition equally. A proteins native size in a complex, but not polypeptide molecular weight, is predictive of localization: partitioned proteins exhibit native sizes larger than ∼100 kDa, whereas natively smaller proteins are equidistributed. To evaluate the role of nuclear export in maintaining localization, we inhibited Exportin 1. This resulted in the expected re-localization of proteins toward the nucleus, but only 3% of the proteome was affected. Thus, complex assembly and passive retention, rather than continuous active transport, is the dominant mechanism for the maintenance of nuclear and cytoplasmic proteomes.

Experimental Approach for Deep Proteome Measurements from Small-Scale Microbial Biomass Samples

Many methods of microbial proteome characterizations require large quantities of cellular biomass (>1-2 g) for sample preparation and protein identification. Our experimental approach differs from traditional techniques by providing the ability to identify the proteomic state of a microbe from a few milligrams of starting cellular material. The small-scale, guanidine lysis method minimizes sample loss by achieving cellular lysis and protein digestion in a single-tube experiment. For this experimental approach, the freshwater microbe Shewanella oneidensis MR-1 and the purple non-sulfur bacterium Rhodopseudomonas palustris CGA0010 were used as model organisms for technology development and evaluation. A 2-D LC-MS/MS comparison between a standard sonication lysis method and the small-scale guanidine lysis techniques demonstrates that the guanidine lysis method is more efficient with smaller sample amounts of cell pellet (i.e., down to 1 mg). The described methodology enables deeper proteome measurements from a few milliliters of confluent bacterial cultures. We also report a new protocol for efficient lysis from small amounts of natural biofilm samples for deep proteome measurements, which should greatly enhance the emerging field of environmental microbial community proteomics. This straightforward sample boiling protocol is complementary to the small-scale guanidine lysis technique, is amenable for small sample quantities, and requires no special reagents that might complicate the MS measurements.

Defining the Boundaries and Characterizing the Landscape of Functional Genome Expression in Vascular Tissues of Populus using Shotgun Proteomics

Current state-of-the-art experimental and computational proteomic approaches were integrated to obtain a comprehensive protein profile of Populus vascular tissue. This featured: (1) a large sample set consisting of two genotypes grown under normal and tension stress conditions, (2) bioinformatics clustering to effectively handle gene duplication, and (3) an informatics approach to track and identify single amino acid polymorphisms (SAAPs). By applying a clustering algorithm to the Populus database, the number of protein entries decreased from 64,689 proteins to a total of 43,069 protein groups, thereby reducing 7505 identified proteins to a total of 4226 protein groups, in which 2016 were singletons. This reduction implies that ∼50% of the measured proteins shared extensive sequence homology. Using conservative search criteria, we were able to identify 1354 peptides containing a SAAP and 201 peptides that become tryptic due to a K or R substitution. These newly identified peptides correspond to 502 proteins, including 97 previously unidentified proteins. In total, the integration of deep proteome measurements on an extensive sample set with protein clustering and peptide sequence variants provided an exceptional level of proteome characterization for Populus, allowing us to spatially resolve the vascular tissue proteome.