Accurate Mass Tag Research Articles

Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering.

SUMMARYSingle-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low-abundance proteins. Herein, we describe an ion-mobility-enhanced mass spectrometry acquisition and peptide identification method, transferring identification based on FAIMS filtering (TIFF), to improve the sensitivity and accuracy of label-free scProteomics. TIFF extends the ion accumulation times for peptide ions by filtering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells, with >1,100 proteins consistently identified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identified time-dependent proteome changes. A record of this paper’s transparent peer review process is included in the supplemental information.

Proteomics analysis of the soil textile imprints from tomb M6043 of the Dahekou Cemetery site in Yicheng County, Shanxi Province, China

Proteomics has made important contributions to identify protein residues from ancient burials, especially for those archeological remains that have severely degraded. These analysis methods make it possible to identify the raw materials of textile imprints found in archeological sites and allow the imprints to be a new archeological material that can compensate for the lack of evidence of early silk artifacts. In this study, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in proteomics was used to analyze the textile imprints found in the tomb M6043 from the Dahekou Cemetery site (1046 BC–771 BC) in China. A combination of accurate mass and time (AMT) tags and peptide sequencing was used to identify the fiber type of the textile imprints. The AMT tag analysis results suggested that some organic residues from the archeological samples had a similar structure to the peptides in modern silk. Five different types of silk fibroin peptides determined that the archeological soil samples contained silk protein residues. Based on the proteomics analysis results, it can be determined that the raw material of the textile imprints from tomb M6043 of the Dahekou Cemetery site was silk fiber. Combining the location and the microtopography observation results of the textile imprints, it can be speculated that these imprints were probably residual traces of the pall, which were generally called “Huang Wei (荒帷)” in ancient China. This study shows that proteomics can play an important role in studying archeological protein residues, and textile soil imprints can be used as archeological materials for ancient textile research.

Proteomic profiling of exosomes leads to the identification of novel biomarkers for prostate cancer progression

Exosomes are vesicles which have garnered interest due to their diagnostic and therapeutic potential. Isolation of cancer‐derived exosomes is a prerequisite for their better understanding. We have investigated a new biomarker for prostate cancer progression via quantitative proteomics. Exosomes from androgen‐independent PC‐3 and the androgen‐dependent LNCaP prostate cancer cells were isolated by ultracentrifugation. After tryptic digestion, proteomic analyses utilized a nanoLC coupled with an LTQ‐Orbitrap operated in tandem MS (MS/MS) mode. Accurate Mass and Time (AMT) tag approach was employed for peptide identification and quantitation. Proteomic characterization showed that 105 proteins from PC‐3 exosomes were 10‐fold higher than those from LNCap. Validation by Western blotting and qRT‐PCR confirmed a higher abundance of PFKL, NRP1 and MCAM(CD146) in PC‐3 cell exosomes, too, indicating that aggressive prostate cancer exhibit higher levels of adhesion or cohesion proteins. We also show that MCAM (CD146) was strongly associated to PC‐3 mobility in vitro. These data provided that MCAM should be useful as a new candidate biomarker for prostate cancer progression.Support or Funding InformationThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) (OGM4391711)This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

High-resolution ultrahigh-pressure long column reversed-phase liquid chromatography for top-down proteomics

Separation of proteoforms for global intact protein analysis (i.e. top-down proteomics) has lagged well behind what is achievable for peptides in traditional bottom-up proteomic approach and is becoming a true bottle neck for top-down proteomics. Herein, we report use of long (≥1M) columns containing short alkyl (C1-C4) bonded phases to achieve high-resolution RPLC for separation of proteoforms. At a specific operation pressure limit (i.e., 96.5MPa or 14Kpsi used in this work), column length was found to be the most important factor for achieving maximal resolution separation of proteins when 1.5–5μm particles were used as packings and long columns provided peak capacities greater than 400 for proteoforms derived from a global cell lysate with molecular weights below 50kDa. Larger proteoforms (50–110kDa) were chromatographed on long RPLC columns and detected by MS; however, they cannot be identified yet by tandem mass spectrometry. Our experimental data further demonstrated that long alkyl (e.g., C8 and C18) bonded particles provided high-resolution RPLC for <10kDa proteoforms, not efficient for separation of global proteoforms. Reversed-phase particles with porous, nonporous, and superficially porous surfaces were systematically investigated for high-resolution RPLC. Pore size (200–400Å) and the surface structure (porous and superficially porous) of particles was found to have minor influences on high-resolution RPLC of proteoforms. RPLC presented herein enabled confident identification of ∼900 proteoforms (1% FDR) for a low-microgram quantity of proteomic samples using a single RPLC–MS/MS analysis. The level of RPLC performance attained in this work is close to that typically realized in bottom-up proteomics, and broadly useful when applying e.g., the single-stage MS accurate mass tag approach, but less effective when combined with current tandem MS. Our initial data indicate that MS detection and fragmentation inefficiencies provided by current high-resolution mass spectrometers are key challenges for characterization of larger proteoforms.

An Optimized Informatics Pipeline for Mass Spectrometry-Based Peptidomics.

The comprehensive MS analysis of the peptidome, the intracellular and intercellular products of protein degradation, has the potential to provide novel insights on endogenous proteolytic processing and its utility in disease diagnosis and prognosis. Along with the advances in MS instrumentation and related platforms, a plethora of proteomics data analysis tools have been applied for direct use in peptidomics; however, an evaluation of the currently available informatics pipelines for peptidomics data analysis has yet to be reported. In this study, we began by evaluating the results of several popular MS/MS database search engines, including MS-GF+, SEQUEST, and MS-Align+, for peptidomics data analysis, followed by identification and label-free quantification using the well-established accurate mass and time (AMT) tag and newly developed informed quantification (IQ) approaches, both based on direct LC-MS analysis. Our results demonstrated that MS-GF+ outperformed both SEQUEST and MS-Align+ in identifying peptidome peptides. Using a database established from MS-GF+ peptide identifications, both the AMT tag and IQ approaches provided significantly deeper peptidome coverage and less missing data for each individual data set than the MS/MS methods, while achieving robust label-free quantification. Besides having an excellent correlation with the AMT tag quantification results, IQ also provided slightly higher peptidome coverage. Taken together, we propose an optimized informatics pipeline combining MS-GF+ for initial database searching with IQ (or AMT tag) approaches for identification and label-free quantification for high-throughput, comprehensive, and quantitative peptidomics analysis. Graphical Abstract ᅟ.

Protein and microRNA biomarkers from lavage, urine, and serum in military personnel evaluated for dyspnea

BackgroundWe have identified candidate protein and microRNA (miRNA) biomarkers for dyspnea by studying serum, lavage fluid, and urine from military personnel who reported serious respiratory symptoms after they were deployed to Iraq or Afghanistan.MethodsForty-seven soldiers with the complaint of dyspnea who enrolled in the STudy of Active Duty Military Personnel for Environmental Dust Exposure (STAMPEDE) underwent comprehensive pulmonary evaluations at the San Antonio Military Medical Center. The evaluation included fiber-optic bronchoscopy with bronchoalveolar lavage. The clinical findings from the STAMPEDE subjects pointed to seven general underlying diagnoses or findings including airway hyperreactivity, asthma, low diffusivity of carbon monoxide, and abnormal cell counts. The largest category was undiagnosed. As an exploratory study, not a classification study, we profiled proteins or miRNAs in lavage fluid, serum, or urine in this group to look for any underlying molecular patterns that might lead to biomarkers. Proteins in lavage fluid and urine were identified by accurate mass tag (database-driven) proteomics methods while miRNAs were profiled by a hybridization assay applied to serum, urine, and lavage fluid.ResultsOver seventy differentially expressed proteins were reliably identified both from lavage and from urine in forty-eight dyspnea subjects compared to fifteen controls with no known lung disorder. Six of these proteins were detected both in urine and lavage. One group of subjects was distinguished from controls by expressing a characteristic group of proteins. A related group of dyspnea subjects expressed a unique group of miRNAs that included one miRNA that was differentially overexpressed in all three fluids studied. The levels of several miRNAs also showed modest but direct associations with several standard clinical measures of lung health such as forced vital capacity or gas exchange efficiency.ConclusionsCandidate proteins and miRNAs associated with the general diagnosis of dyspnea have been identified in subjects with differing medical diagnoses. Since these markers can be measured in readily obtained clinical samples, further studies are possible that test the value of these findings in more formal classification or case–control studies in much larger cohorts of subjects with specific lung diseases such as asthma, emphysema, or some other well-defined lung disease.

Quantitative shotgun proteomics with data-independent acquisition and traveling wave ion mobility spectrometry: a versatile tool in the life sciences.

Data-independent acquisition (DIA) implemented in a method called MS(E) can be performed in a massively parallel, time-based schedule rather than by sampling masses sequentially in shotgun proteomics. In MS(E) alternating low and high energy spectra are collected across the full mass range. This approach has been very successful and stimulated the development of variants modeled after the MS(E) protocol, but over narrower mass ranges. The massively parallel MS(E) and other DIA methodologies have enabled effective label-free quantitation methods that have been applied to a wide variety of samples including affinity pulldowns and studies of cells, tissues, and clinical samples. Another complementary technology matches accurate mass and retention times of precursor ions across multiple chromatographic runs. This further enhances the impact of MS(E) in counteracting the stochastic nature of mass spectrometry as applied in proteomics. Otherwise significant amounts of data in typical large-scale protein profiling experiments are missing. A variety of software packages perform this function similar in concept to matching of accurate mass tags. Another enhancement of this method involves a variation of MS(E) coupled with traveling wave ion mobility spectrometry to provide separations of peptides based on cross-sectional area and shape in addition to mass/charge (m/z) ratio. Such a two-dimensional separation in the gas phase considerably increases protein coverage as well as typically a doubling of the number of proteins detected. These developments along with advances in ultrahigh pressure liquid chromatography have resulted in the evolution of a robust and versatile platform for label-free protein profiling.

Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer

BackgroundCurrent markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes, ∼100 nm, which contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific biomarker discovery.Materials and MethodsExosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. After tryptic digestion, proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode. Accurate Mass and Time (AMT) tag approach was employed for peptide identification and quantitation. Candidate biomarkers were validated by Western blotting and Immunohistochemistry.ResultsProteomic characterization resulted in the identification of 248, 233, 169, and 216 proteins by at least 2 peptides in exosomes from PNT2C2, RWPE-1, PC346C, and VCaP, respectively. Statistical analyses revealed 52 proteins differently abundant between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes.ConclusionsIdentification of exosomal proteins using high performance LC-FTMS resulted in the discovery of PDCD6IP, FASN, XPO1 and ENO1 as new candidate biomarkers for prostate cancer.

Reduced Insulin/Insulin-like Growth Factor-1 Signaling and Dietary Restriction Inhibit Translation but Preserve Muscle Mass in Caenorhabditis elegans

Reduced signaling through the C. elegans insulin/insulin-like growth factor-1-like tyrosine kinase receptor daf-2 and dietary restriction via bacterial dilution are two well-characterized lifespan-extending interventions that operate in parallel or through (partially) independent mechanisms. Using accurate mass and time tag LC-MS/MS quantitative proteomics, we detected that the abundance of a large number of ribosomal subunits is decreased in response to dietary restriction, as well as in the daf-2(e1370) insulin/insulin-like growth factor-1-receptor mutant. In addition, general protein synthesis levels in these long-lived worms are repressed. Surprisingly, ribosomal transcript levels were not correlated to actual protein abundance, suggesting that post-transcriptional regulation determines ribosome content. Proteomics also revealed the increased presence of many structural muscle cell components in long-lived worms, which appeared to result from the prioritized preservation of muscle cell volume in nutrient-poor conditions or low insulin-like signaling. Activation of DAF-16, but not diet restriction, stimulates mRNA expression of muscle-related genes to prevent muscle atrophy. Important daf-2-specific proteome changes include overexpression of aerobic metabolism enzymes and general activation of stress-responsive and immune defense systems, whereas the increased abundance of many protein subunits of the proteasome core complex is a dietary-restriction-specific characteristic.

Ultrasensitive and Fast Bottom‐up Analysis of Femtogram Amounts of Complex Proteome Digests

Femtogram proteomics: An ultrasensitive capillary zone electrophoresis-mass spectrometry system that is based on an improved nanospray interface has been developed. This system is used for the analysis of picogram to femtogram amounts of E. coli digests; for example, over 100 proteins were identified from 16 pg digests by tandem mass spectrometry. AMTs=accurate mass and time tags.

Increasing confidence of LC–MS identifications by utilizing ion mobility spectrometry

Ion mobility spectrometry in conjunction with liquid chromatography separations and mass spectrometry offers a range of new possibilities for analyzing complex biological samples. To fully utilize the information obtained from these three measurement dimensions, informatics tools based on the accurate mass and time tag methodology were modified to incorporate ion mobility spectrometry drift times for peptides observed in human serum. In this work a reference human serum database was created for 12,139 peptides and populated with the monoisotopic mass, liquid chromatography normalized elution time, and ion mobility spectrometry drift time(s) for each. We demonstrate that the use of three dimensions for peak matching during the peptide identification process resulted in an increased numbers of identifications and a lower false discovery rate relative to only using the mass and normalized elution time dimensions.

Inversion of chromatographic elution orders of peptides and its importance for proteomics

Inversion of the order of peptide elution in reversed-phase liquid chromatography under changing separation conditions, such as gradient slope has been considered. Using a six-protein proteolytic peptide standard and available literature data, the occurrence frequency and importance of this phenomenon in proteomic studies utilizing methods of shotgun proteomics and accurate mass and time tags have been evaluated. Feasibility of qualitative and quantitative description of peptide elution order inversion has been demonstrated using a model of critical liquid chromatography. Existing approaches to predict peptide separation and directions of the shifts of chromatographic peaks when the gradient profile changes have been compared.

Identification of soybean proteins from a single cell type: The root hair

Root hairs (RH) are a terminally differentiated single cell type, mainly involved in water and nutrient uptake from the soil. The soybean RH cell represents an excellent model for the study of single cell systems biology. In this study, we identified 5702 proteins, with at least two peptides, from soybean RH using an accurate mass and time tag approach, establishing a comprehensive proteome reference map of this single cell type. We also showed that trypsin is the most appropriate enzyme for soybean proteomic studies by performing an in silico digestion of the soybean proteome using different proteases. Although the majority of proteins identified in this study are involved in basal metabolism, the function of others are more related to RH formation/function and include proteins involved in nutrient uptake (transporters) or vesicular trafficking (cytoskeleton and ras-associated binding proteins). Interestingly, some of these proteins appear to be specifically detected in RH and constitute promising candidates for further studies to elucidate unique features of this single-cell model.

Coupling methanol denaturation, immobilized trypsin digestion, and accurate mass and time tagging for liquid-chromatography-based shotgun proteomics of low nanogram amounts of RAW 264.7 cell lysate.

We report the shotgun proteomic analysis of mammalian cell lysates that contain low nanogram amounts of protein. Proteins were denatured using methanol, digested using immobilized trypsin, and analyzed by UPLC-ESI-MS/MS. The approach generated more peptides and higher sequence coverage for a mixture of three standard proteins than the use of free trypsin solution digestion of heat- or urea-denatured proteins. We prepared triplicate RAW 264.7 cell lysates that contained 6, 30, 120, and 300 ng of protein. An average of 2 ± 1, 23 ± 2, 134 ± 11, and 218 ± 26 proteins were detected for each sample size, respectively. The numbers of both protein and peptide IDs scaled linearly with the amount of sample taken for analysis. Our approach also outperformed traditional methods (free trypsin digestion of heat- or urea-denatured proteins) for 6-300 ng RAW 264.7 cell protein analysis in terms of number of peptides and proteins identified. The use of accurate mass and time (AMT) tags resulted in the identification of an additional 16 proteins based on 20 peptides from the 6 ng cell lysate prepared with our approach. When AMT analysis was performed for the 6 ng cell lysate prepared with traditional methods, no reasonable peptide signal could be obtained. In all cases, roughly ∼30% of the digested sample was taken for analysis, corresponding to the analysis of a 2 ng aliquot of homogenate from the 6 ng cell lysate.

Label-Free Quantitative LC–MS Proteomics of Alzheimer’s Disease and Normally Aged Human Brains

Quantitative proteomics analysis of cortical samples of 10 Alzheimer's disease (AD) brains versus 10 normally aged brains was performed by following the accurate mass and time tag (AMT) approach with the high resolution LTQ Orbitrap mass spectrometer. More than 1400 proteins were identified and quantitated. A conservative approach of selecting only the consensus results of four normalization methods was suggested and used. A total of 197 proteins were shown to be significantly differentially abundant (p-values <0.05, corrected for multiplicity of testing) in AD versus control brain samples. Thirty-seven of these proteins were reported as differentially abundant or modified in AD in previous proteomics and transcriptomics publications. The rest to the best of our knowledge are new. Mapping of the discovered proteins with bioinformatic tools revealed significant enrichment with differentially abundant proteins of pathways and processes known to be important in AD, including signal transduction, regulation of protein phosphorylation, immune response, cytoskeleton organization, lipid metabolism, energy production, and cell death.

Reconstruction of associative protein networks connected with processes of sodium exchange regulation and sodium deposition in healthy volunteers based on urine proteome analysis

The study was conducted during the experiment with 105-day isolation in experimental complex. In the present investigation we collected urine samples from 6 healthy volunteers. The physical activity, diurnal rhythm, temperature parameters and level of oxygen and carbon dioxide were controlled during the experiment. According to the program, food intake (electrolytes, water, calories, fat, carbohydrates, protein, vitamins, etc.) on each stage of experiment was normalized. All samples were analyzed using mass spectrometer of an ionic cyclotron resonance with transformation of Fure LTQ FT MS (Thermo) on the basis of the AMT-tags (accurate mass and time tags) approach. Among more than 20 000 we found out 690 proteotypical proteins and we identified about 600 urine proteins. For physiological interpretation of the proteome data we used computer systems ANDCell and ANDVisio. Clustering of proteins and application of these systems revealed proteins that are most closely associated with the regime of sodium intake, as well as build the network of their interactions.

The cerebrospinal fluid proteome in HIV infection: change associated with disease severity

BackgroundCentral nervous system (CNS) infection is a nearly universal feature of untreated systemic HIV infection with a clinical spectrum that ranges from chronic asymptomatic infection to severe cognitive and motor dysfunction. Analysis of cerebrospinal fluid (CSF) has played an important part in defining the character of this evolving infection and response to treatment. To further characterize CNS HIV infection and its effects, we applied advanced high-throughput proteomic methods to CSF to identify novel proteins and their changes with disease progression and treatment.ResultsAfter establishing an accurate mass and time (AMT) tag database containing 23,141 AMT tags for CSF peptides, we analyzed 91 CSF samples by LC-MS from 12 HIV-uninfected and 14 HIV-infected subjects studied in the context of initiation of antiretroviral therapy and correlated abundances of identified proteins a) within and between subjects, b) with all other proteins across the entire sample set, and c) with "external" CSF biomarkers of infection (HIV RNA), immune activation (neopterin) and neural injury (neurofilament light chain protein, NFL). We identified a mean of 2,333 +/- 328 (SD) peptides covering 307 +/-16 proteins in the 91 CSF sample set. Protein abundances differed both between and within subjects sampled at different time points and readily separated those with and without HIV infection. Proteins also showed inter-correlations across the sample set that were associated with biologically relevant dynamic processes. One-hundred and fifty proteins showed correlations with the external biomarkers. For example, using a threshold of cross correlation coefficient (Pearson's) ≤ -0.3 and ≥0.3 for potentially meaningful relationships, a total of 99 proteins correlated with CSF neopterin (43 negative and 56 positive correlations) and related principally to neuronal plasticity and survival and to innate immunity. Pathway analysis defined several networks connecting the identified proteins, including one with amyloid precursor protein as a central node.ConclusionsAdvanced CSF proteomic analysis enabled the identification of an array of novel protein changes across the spectrum of CNS HIV infection and disease. This initial analysis clearly demonstrated the value of contemporary state-of-the-art proteomic CSF analysis as a discovery tool in HIV infection with likely similar application to other neurological inflammatory and degenerative diseases.

Plasma Biomarkers for Detecting Hodgkin's Lymphoma in HIV Patients

The lifespan of people with human immunodeficiency virus (HIV) infection has increased as a result of effective antiretroviral therapy, and the incidences of the AIDS-defining cancers, non-Hodgkin's lymphoma and Kaposi sarcoma, have declined. Even so, HIV-infected individuals are now at greater risk of other cancers, including Hodgkin's lymphoma (HL). To identify candidate biomarkers for the early detection of HL, we undertook an accurate mass and elution time tag proteomics analysis of individual plasma samples from either HIV-infected patients without HL (controls; n = 14) and from HIV-infected patient samples with HL (n = 22). This analysis identified 60 proteins that were statistically (p<0.05) altered and at least 1.5-fold different between the two groups. At least three of these proteins have previously been reported to be altered in the blood of HL patients that were not known to be HIV positive, suggesting that these markers may be broadly useful for detecting HL. Ingenuity Pathway Analysis software identified “inflammatory response” and “cancer” as the top two biological functions associated with these proteins. Overall, this study validated three plasma proteins as candidate biomarkers for detecting HL, and identified 57 novel candidate biomarkers that remain to be validated. The relationship of these novel candidate biomarkers with cancer and inflammation suggests that they are truly associated with HL and therefore may be useful for the early detection of this cancer in susceptible populations.

A Statistical Method for Assessing Peptide Identification Confidence in Accurate Mass and Time Tag Proteomics

Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, because this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referenced as Statistical Tools for AMT Tag Confidence (STAC). STAC additionally provides a uniqueness probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download, as both a command line and a Windows graphical application.

Discovery of Mouse Spleen Signaling Responses to Anthrax using Label-Free Quantitative Phosphoproteomics via Mass Spectrometry

Inhalational anthrax is caused by spores of the bacterium Bacillus anthracis (B. anthracis), and is an extremely dangerous disease that can kill unvaccinated victims within 2 weeks. Modern antibiotic-based therapy can increase the survival rate to ∼50%, but only if administered presymptomatically (within 24-48 h of exposure). To discover host signaling responses to presymptomatic anthrax, label-free quantitative phosphoproteomics via liquid chromatography coupled to mass spectrometry was used to compare spleens from uninfected and spore-challenged mice over a 72 h time-course. Spleen proteins were denatured using urea, reduced using dithiothreitol, alkylated using iodoacetamide, and digested into peptides using trypsin, and the resulting phosphopeptides were enriched using titanium dioxide solid-phase extraction and analyzed by nano-liquid chromatography-Linear Trap Quadrupole-Orbitrap-MS(/MS). The fragment ion spectra were processed using DeconMSn and searched using both Mascot and SEQUEST resulting in 252,626 confident identifications of 6248 phosphopeptides (corresponding to 5782 phosphorylation sites). The precursor ion spectra were deisotoped using Decon2LS and aligned using MultiAlign resulting in the confident quantitation of 3265 of the identified phosphopeptides. ANOVAs were used to produce a q-value ranked list of host signaling responses. Late-stage (48-72 h postchallenge) Sterne strain (lethal) infections resulted in global alterations to the spleen phosphoproteome. In contrast, ΔSterne strain (asymptomatic; missing the anthrax toxin) infections resulted in 188 (5.8%) significantly altered (q<0.05) phosphopeptides. Twenty-six highly tentative phosphorylation responses to early-stage (24 h postchallenge) anthrax were discovered (q<0.5), and ten of these originated from eight proteins that have known roles in the host immune response. These tentative early-anthrax host response signaling events within mouse spleens may translate into presymptomatic diagnostic biomarkers of human anthrax detectable within circulating immune cells, and could aid in the identification of pathogenic mechanisms and therapeutic targets.