Alicia L. Richards

The One Hour Yeast Proteome

We describe the comprehensive analysis of the yeast proteome in just over one hour of optimized analysis. We achieve this expedited proteome characterization with improved sample preparation, chromatographic separations, and by using a new Orbitrap hybrid mass spectrometer equipped with a mass filter, a collision cell, a high-field Orbitrap analyzer, and, finally, a dual cell linear ion trap analyzer (Q-OT-qIT, Orbitrap Fusion). This system offers high MS2 acquisition speed of 20 Hz and detects up to 19 peptide sequences within a single second of operation. Over a 1.3 h chromatographic method, the Q-OT-qIT hybrid collected an average of 13,447 MS1 and 80,460 MS2 scans (per run) to produce 43,400 (x̄) peptide spectral matches and 34,255 (x̄) peptides with unique amino acid sequences (1% false discovery rate (FDR)). On average, each one hour analysis achieved detection of 3,977 proteins (1% FDR). We conclude that further improvements in mass spectrometer scan rate could render comprehensive analysis of the human proteome within a few hours.

Proteome sequencing goes deep

Advances in mass spectrometry (MS) have transformed the scope and impact of protein characterization efforts. Identifying hundreds of proteins from rather simple biological matrices, such as yeast, was a daunting task just a few decades ago. Now, expression of more than half of the estimated ∼20,000 human protein coding genes can be confirmed in record time and from minute sample quantities. Access to proteomic information at such unprecedented depths has been fueled by strides in every stage of the shotgun proteomics workflow-from sample processing to data analysis-and promises to revolutionize our understanding of the causes and consequences of proteome variation.

One-hour proteome analysis in yeast

Recent advances in chromatography and mass spectrometry (MS) have made rapid and deep proteomic profiling possible. To maximize the performance of the recently produced Orbitrap hybrid mass spectrometer, we have developed a protocol that combines improved sample preparation (including optimized cellular lysis by extensive bead beating) and chromatographic conditions (specifically, 30-cm capillary columns packed with 1.7-μm bridged ethylene hybrid material) and the manufacture of a column heater (to accommodate flow rates of 350–375 nl/min) that increases the number of proteins identified across a single liquid chromatography–tandem MS (LC-MS/MS) separation, thereby reducing the need for extensive sample fractionation. This strategy allowed the identification of up to 4,002 proteins (at a 1% false discovery rate (FDR)) in yeast (Saccharomyces cerevisiae strain BY4741) over 70 min of LC-MS/MS analysis. Quintuplicate analysis of technical replicates reveals 83% overlap at the protein level, thus demonstrating the reproducibility of this procedure. This protocol, which includes cell lysis, overnight tryptic digestion, sample analysis and database searching, takes ∼24 h to complete. Aspects of this protocol, including chromatographic separation and instrument parameters, can be adapted for the optimal analysis of other organisms.

SIRT3 Mediates Multi-Tissue Coupling for Metabolic Fuel Switching

SIRT3 is a member of the Sirtuin family of NAD(+)-dependent deacylases and plays a critical role in metabolic regulation. Organism-wide SIRT3 loss manifests in metabolic alterations; however, the coordinating role of SIRT3 among metabolically distinct tissues is unknown. Using multi-tissue quantitative proteomics comparing fasted wild-type mice to mice lacking SIRT3, innovative bioinformatic analysis, and biochemical validation, we provide a comprehensive view of mitochondrial acetylation and SIRT3 function. We find SIRT3 regulates the acetyl-proteome in core mitochondrial processes common to brain, heart, kidney, liver, and skeletal muscle, but differentially regulates metabolic pathways in fuel-producing and fuel-utilizing tissues. We propose an additional maintenance function for SIRT3 in liver and kidney where SIRT3 expression is elevated to reduce the acetate load on mitochondrial proteins. We provide evidence that SIRT3 impacts ketone body utilization in the brain and reveal a pivotal role for SIRT3 in the coordination between tissues required for metabolic homeostasis.

Mitochondrial protein functions elucidated by multi-omic mass spectrometry profiling

Mitochondrial dysfunction is associated with many human diseases, including cancer and neurodegeneration, that are often linked to proteins and pathways that are not well-characterized. To begin defining the functions of such poorly characterized proteins, we used mass spectrometry to map the proteomes, lipidomes, and metabolomes of 174 yeast strains, each lacking a single gene related to mitochondrial biology. 144 of these genes have human homologs, 60 of which are associated with disease and 39 of which are uncharacterized. We present a multi-omic data analysis and visualization tool that we use to find covariance networks that can predict molecular functions, correlations between profiles of related gene deletions, gene-specific perturbations that reflect protein functions, and a global respiration deficiency response. Using this multi-omic approach, we link seven proteins including Hfd1p and its human homolog ALDH3A1 to mitochondrial coenzyme Q (CoQ) biosynthesis, an essential pathway disrupted in many human diseases. This Resource should provide molecular insights into mitochondrial protein functions.

A proteomic atlas of the legume Medicago truncatula and its nitrogen-fixing endosymbiont Sinorhizobium meliloti

Legumes are essential components of agricultural systems because they enrich the soil in nitrogen and require little environmentally deleterious fertilizers. A complex symbiotic association between legumes and nitrogen-fixing soil bacteria called rhizobia culminates in the development of root nodules, where rhizobia fix atmospheric nitrogen and transfer it to their plant host. Here we describe a quantitative proteomic atlas of the model legume Medicago truncatula and its rhizobial symbiont Sinorhizobium meliloti, which includes more than 23,000 proteins, 20,000 phosphorylation sites, and 700 lysine acetylation sites. Our analysis provides insight into mechanisms regulating symbiosis. We identify a calmodulin-binding protein as a key regulator in the host and assign putative roles and targets to host factors (bioactive peptides) that control gene expression in the symbiont. Further mining of this proteomic resource may enable engineering of crops and their microbial partners to increase agricultural productivity and sustainability.

The Negative Mode Proteome with Activated Ion Negative Electron Transfer Dissociation (AI-NETD)

The field of proteomics almost uniformly relies on peptide cation analysis, leading to an underrepresentation of acidic portions of proteomes, including relevant acidic posttranslational modifications. Despite the many benefits negative mode proteomics can offer, peptide anion analysis remains in its infancy due mainly to challenges with high-pH reversed-phase separations and a lack of robust fragmentation methods suitable for peptide anion characterization. Here, we report the first implementation of activated ion negative electron transfer dissociation (AI-NETD) on the chromatographic timescale, generating 7,601 unique peptide identifications from Saccharomyces cerevisiae in single-shot nLC-MS/MS analyses of tryptic peptides—a greater than 5-fold increase over previous results with NETD alone. These improvements translate to identification of 1,106 proteins, making this work the first negative mode study to identify more than 1,000 proteins in any system. We then compare the performance of AI-NETD for analysis of peptides generated by five proteases (trypsin, LysC, GluC, chymotrypsin, and AspN) for negative mode analyses, identifying as many as 5,356 peptides (1,045 proteins) with LysC and 4,213 peptides (857 proteins) with GluC in yeast—characterizing 1,359 proteins in total. Finally, we present the first deep-sequencing approach for negative mode proteomics, leveraging offline low-pH reversed-phase fractionation prior to online high-pH separations and peptide fragmentation with AI-NETD. With this platform, we identified 3,467 proteins in yeast with trypsin alone and characterized a total of 3,730 proteins using multiple proteases, or nearly 83% of the expressed yeast proteome. This work represents the most extensive negative mode proteomics study to date, establishing AI-NETD as a robust tool for large-scale peptide anion characterization and making the negative mode approach a more viable platform for future proteomic studies.

Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra

We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, 13C615N2 and 2H8, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ∼50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo+ resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification.

ATM directs DNA damage responses and proteostasis via genetically separable pathways

Independent functions in the response to DNA damage and to oxidative stress broaden the biological roles of the kinase ATM. The many roles of ATM The kinase ATM is classically known for its role in coordinating the response to DNA damage. DNA damage is caused by various intracellular and extracellular stimuli, including oxidative stress and free radicals. Lee et al. found critical amino acid residues that enable ATM to coordinate a response to DNA damage that is independent of its response to oxidative stress. Activation of ATM by either pathway promoted mitochondrial function and autophagy, thus mediating cell survival through metabolic changes. ATM activation via oxidative stress additionally promoted the clearance of toxic protein aggregates. These findings expand the roles of ATM and suggest that the loss of ATM function, such as in the neurodegenerative disease ataxia telangiectasia (A-T), causes broader cellular stress than that limited to a defective DNA damage response. The protein kinase ATM is a master regulator of the DNA damage response but also responds directly to oxidative stress. Loss of ATM causes ataxia telangiectasia, a neurodegenerative disorder with pleiotropic symptoms that include cerebellar dysfunction, cancer, diabetes, and premature aging. We genetically separated the activation of ATM by DNA damage from that by oxidative stress using separation-of-function mutations. We found that deficient activation of ATM by the Mre11-Rad50-Nbs1 complex and DNA double-strand breaks resulted in loss of cell viability, checkpoint activation, and DNA end resection in response to DNA damage. In contrast, loss of oxidative activation of ATM had minimal effects on DNA damage–related outcomes but blocked ATM-mediated initiation of checkpoint responses after oxidative stress and resulted in deficiencies in mitochondrial function and autophagy. In addition, expression of a variant ATM incapable of activation by oxidative stress resulted in widespread protein aggregation. These results indicate a direct relationship between the mechanism of ATM activation and its effects on cellular metabolism and DNA damage responses in human cells and implicate ATM in the control of protein homeostasis.