A lipidomics-based method to eliminate negative urine culture in general population.

Urinary tract infections (UTIs) pose a significant challenge to human health. Accurate and timely detection remains pivotal for effective intervention. Current urine culture techniques, while essential, often encounter challenges where urinalysis yields positive results, but subsequent culture testing produces a negative result. This highlights potential discrepancies between the two methods and emphasizes the need for improved correlation in urinary tract infection (UTI) detection. Employing advanced lipidomics techniques, we deployed the fast lipid analysis technique (FLAT) on a clinical cohort suspected of having UTIs. Lipid fingerprinting by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), directly from urine samples without ex vivo growth, correctly identified the common uropathogens within a 1 hour timeframe when compared to urine culture. FLAT analysis also identified urine samples without culturable pathogens (negative UTIs) with 99% microbial identification (ID) agreement, whereas urinalysis showed 37% ID agreement with the gold standard urine culture. In 402 urine samples suspected for UTI from outpatients, FLAT assay rapidly ruled out negative urines without the need for culture in 77% of all cases. The potential impact of this innovative lipidomic-based approach extends beyond conventional diagnostic limitations, offering new avenues for early detection and targeted management of urinary tract infections. This research marks a paradigm shift in urine culture methodology, paving the way for improved clinical outcomes and public health interventions. IMPORTANCE: This study employs a lipidomics-based method that promises to enhance the accuracy and reliability of urine culture diagnostics within 1 hour of sample collection. Our findings underscore the potential of lipidomics as a valuable tool in identifying and characterizing microbial populations present in urine samples and efficiently rule out negative urines, ultimately leading to improved patient care and management of urinary tract infections.

A Multimodal System for Lipid A Structural Analysis from a Single Colony.

Structural elucidation of Gram-negative bacterial lipid A traditionally requires chemical extraction followed by tandem MS data in the negative ion mode. Previously, we reported FLAT and FLATn as methods to rapidly determine the structure of lipid A without chromatographic techniques. In this work, we extend the capability and effectiveness of these techniques to elucidate the chemical structure in a de novo manner by including the use of positive ion mode (FLAT+ and FLATn+) spectral approaches. Advantages of positive mode analysis of lipid A include the generation of more interpretable and informative fragmentation patterns that include the identification of diagnostic fragments, including selective dissociation of a glycosidic bond between two glucosamine units and the selective dissociation at the secondary acyl chain in 2'-N, allowing for the determination of the composition of fatty acids. As a proof of principle, we present here two previously uncharacterized structures of lipid A from Roseomonas mucosa (R. mucosa) and Moraxella canis (M. canis). In R. mucosa, we determined the lipid A structure with a nonconventional backbone of-ß-1,6 linked 2,3-dideoxy-2,3-diamno-d-glucopyranose further modified with galacturonic acid in the place of typical 1-phosphate, and in M. canis, we assigned a single discrete structure using the specific fragmentation patterns of terminal phosphate groups present in lipid A. Therefore, FLATn+, in combination with FLAT and FLATn, provides a multimodal structural platform for rapid structure characterization of unusual and complex lipid A structures from a single colony.

Metaproteomic analysis from cervical biopsies and cytologies identifies proteinaceous biomarkers representing both human and microbial species.

The detection of HPV infection and microbial colonization in cervical lesions is currently done through PCR-based viral or bacterial DNA amplification. Our objective was to develop a methodology to expand the metaproteomic landscape of cervical disease and determine if protein biomarkers from both human and microbes could be detected in distinct cervical samples. This would lead to the development of multi-species proteomics, which includes protein-based lateral flow diagnostics that can define patterns of microbes and/or human proteins relevant to disease status. In this study, we collected both non-frozen tissue biopsy and exfoliative non-fixed cytology samples to assess the consistency of detecting human proteomic signatures between the cytology and biopsy samples. Our results show that proteomics using biopsies or cytologies can detect both human and microbial organisms. Across patients, Lumican and Galectin-1 were most highly expressed human proteins in the tissue biopsy, whilst IL-36 and IL-1RA were most highly expressed human proteins in the cytology. We also used mass spectrometry to assess microbial proteomes known to reside based on prior 16S rRNA gene signatures. Lactobacillus spp. was the most highly expressed proteome in patient samples and specific abundant Lactobacillus proteins were identified. These methodological approaches can be used in future metaproteomic clinical studies to interrogate the vaginal human and microbiome structure and metabolic diversity in cytologies or biopsies from the same patients who have pre-invasive cervical intraepithelial neoplasia, invasive cervical cancer, as well as in healthy controls to assess how human and pathogenic proteins may correlate with disease presence and severity.

Establishing Personalized Blood Protein Reference Ranges Using Noninvasive Microsampling and Targeted Proteomics: Implications for Antidoping Strategies.

To prevent doping practices in sports, the World Anti-Doping Agency implemented the Athlete Biological Passport (ABP) program, monitoring biological variables over time to indirectly reveal the effects of doping rather than detect the doping substance or the method itself. In the context of this program, a highly multiplexed mass spectrometry-based proteomics assay for 319 peptides corresponding to 250 proteins was developed, including proteins associated with blood-doping practices. "Baseline" expression profiles of these potential biomarkers in capillary blood (dried blood spots (DBS)) were established using multiple reaction monitoring (MRM). Combining DBS microsampling with highly multiplexed MRM assays is the best-suited technology to enhance the effectiveness of the ABP program, as it represents a cost-effective and robust alternative analytical method with high specificity and selectivity of targets in the attomole range. DBS data were collected from 10 healthy athlete volunteers over a period of 140 days (28 time points per participant). These comprehensive findings provide a personalized targeted blood proteome "fingerprint" showcasing that the targeted proteome is unique to an individual and likely comparable to a DNA fingerprint. The results can serve as a baseline for future studies investigating doping-related perturbations.

Mass spectrometry imaging methods for visualizing tumor heterogeneity.

Profiling spatial distributions of lipids, metabolites, and proteins in tumors can reveal unique cellular microenvironments and provide molecular evidence for cancer cell dysfunction and proliferation. Mass spectrometry imaging (MSI) is a label-free technique that can be used to map biomolecules in tumors in situ. Here, we discuss current progress in applying MSI to uncover molecular heterogeneity in tumors. First, the analytical strategies to profile small molecules and proteins are outlined, and current methods for multimodal imaging to maximize biological information are highlighted. Second, we present and summarize biological insights obtained by MSI of tumor tissue. Finally, we discuss important considerations for designing MSI experiments and several current analytical challenges.

Structural Basis for Multivalent MUC16 Recognition and Robust Anti-Pancreatic Cancer Activity of Humanized Antibody AR9.6.

Mucin-16 (MUC16) is a target for antibody-mediated immunotherapy in pancreatic ductal adenocarcinoma (PDAC) among other malignancies. The MUC16-specific monoclonal antibody AR9.6 has shown promise for PDAC immunotherapy and imaging. Here, we report the structural and biological characterization of the humanized AR9.6 antibody (huAR9.6). The structure of huAR9.6 was determined in complex with a MUC16 SEA (Sea urchin sperm, Enterokinase, Agrin) domain. Binding of huAR9.6 to recombinant, shed, and cell-surface MUC16 was characterized, and anti-PDAC activity was evaluated in vitro and in vivo. HuAR9.6 bound a discontinuous, SEA domain epitope with an overall affinity of 88 nmol/L. Binding affinity depended on the specific SEA domain(s) present, and glycosylation modestly enhanced affinity driven by favorable entropy and enthalpy and via distinct transition state thermodynamic pathways. Treatment with huAR9.6 reduced the in vitro growth, migration, invasion, and clonogenicity of MUC16-positive PDAC cells and patient-derived organoids (PDO). HuAR9.6 blocked MUC16-mediated ErbB and AKT activation in PDAC cells, PDOs, and patient-derived xenografts and induced antibody-dependent cellular cytotoxicity and complement-dependent cytotoxicity. More importantly, huAR9.6 treatment caused substantial PDAC regression in subcutaneous and orthotopic tumor models. The mechanism of action of huAR9.6 may depend on dense avid binding to homologous SEA domains on MUC16. The results of this study validate the translational therapeutic potential of huAR9.6 against MUC16-positive PDACs.

Proteomic Evolution from Acute to Post-COVID-19 Conditions.

Many COVID-19 survivors have post-COVID-19 conditions, and females are at a higher risk. We sought to determine (1) how protein levels change from acute to post-COVID-19 conditions, (2) whether females have a plasma protein signature different from that of males, and (3) which biological pathways are associated with COVID-19 when compared to restrictive lung disease. We measured protein levels in 74 patients on the day of admission and at 3 and 6 months after diagnosis. We determined protein concentrations by multiple reaction monitoring (MRM) using a panel of 269 heavy-labeled peptides. The predicted forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLCO) were measured by routine pulmonary function testing. Proteins associated with six key lipid-related pathways increased from admission to 3 and 6 months; conversely, proteins related to innate immune responses and vasoconstriction-related proteins decreased. Multiple biological functions were regulated differentially between females and males. Concentrations of eight proteins were associated with FVC, %, and they together had c-statistics of 0.751 (CI:0.732-0.779); similarly, concentrations of five proteins had c-statistics of 0.707 (CI:0.676-0.737) for DLCO, %. Lipid biology may drive evolution from acute to post-COVID-19 conditions, while activation of innate immunity and vascular regulation pathways decreased over that period. (ProteomeXchange identifiers: PXD041762, PXD029437).

Divergent Pseudomonas aeruginosa LpxO enzymes perform site-specific lipid A 2-hydroxylation.

Pseudomonas aeruginosa can survive in a myriad of environments, partially due to modifications of its lipid A, the membrane anchor of lipopolysaccharide. We previously demonstrated that divergent late acyltransferase paralogs, HtrB1 and HtrB2, add acyloxyacyl laurate to lipid A 2- and 2'-acyl chains, respectively. The genome of P. aeruginosa also has genes which encode two dioxygenase enzymes, LpxO1 and LpxO2, that individually hydroxylate a specific secondary laurate. LpxO1 acts on the 2'-acyloxyacyl laurate (added by HtrB2), whereas LpxO2 acts on the 2-acyloxyacyl laurate (added by HtrB1) in a site-specific manner. Furthermore, while both enzyme pairs are evolutionarily linked, phylogenomic analysis suggests the LpxO1/HtrB2 enzyme pair as being of ancestral origin, present throughout the Pseudomonas lineage, whereas the LpxO2/HtrB1 enzyme pair likely arose via horizontal gene transfer and has been retained in P. aeruginosa over time. Using a murine pulmonary infection model, we showed that both LpxO1 and LpxO2 enzymes are functional in vivo, as direct analysis of in vivo lipid A structure from bronchoalveolar lavage fluid revealed 2-hydroxylated lipid A. Gene expression analysis reveals increased lpxO2 but unchanged lpxO1 expression in vivo, suggesting differential regulation of these enzymes during infection. We also demonstrate that loss-of-function mutations arise in lpxO1 and lpxO2 during chronic lung infection in people with cystic fibrosis (CF), indicating a potential role for pathogenesis and airway adaptation. Collectively, our study characterizes lipid A 2-hydroxylation during P. aeruginosa airway infection that is regulated by two distinct lipid A dioxygenase enzymes.IMPORTANCEPseudomonas aeruginosa is an opportunistic pathogen that causes severe infection in hospitalized and chronically ill individuals. During infection, P. aeruginosa undergoes adaptive changes to evade host defenses and therapeutic interventions, increasing mortality and morbidity. Lipid A structural alteration is one such change that P. aeruginosa isolates undergo during chronic lung infection in CF. Investigating genetic drivers of this lipid A structural variation is crucial in understanding P. aeruginosa adaptation during infection. Here, we describe two lipid A dioxygenases with acyl-chain site specificity, each with different evolutionary origins. Further, we show that loss of function in these enzymes occurs in CF clinical isolates, suggesting a potential pathoadaptive phenotype. Studying these bacterial adaptations provides insight into selection pressures of the CF airway on P. aeruginosa phenotypes that persist during chronic infection. Understanding these adaptive changes may ultimately provide clinicians better control over bacterial populations during chronic infection.

Structural Elucidation of Intact Rough-type Lipopolysaccharides Using Field Asymmetric Ion Mobility Spectrometry and Kendrick Mass Defect Plots.

Lipopolysaccharides (LPSs) are a hallmark virulence factor of Gram-negative bacteria. They are complex, structurally heterogeneous mixtures due to variations in number, type, and position of their simplest units: fatty acids and monosaccharides. Thus, LPS structural characterization by traditional mass spectrometry (MS) methods is challenging. Here, we describe the benefits of field asymmetric ion mobility spectrometry (FAIMS) for analysis of an intact R-type lipopolysaccharide complex mixture (lipooligosaccharide; LOS). Structural characterization was performed using Escherichia coli J5 (Rc mutant) LOS, a TLR4 agonist widely used in glycoconjugate vaccine research. FAIMS gas-phase fractionation improved the (S/N) ratio and number of detected LOS species. Additionally, FAIMS allowed the separation of overlapping isobars facilitating their tandem MS characterization and unequivocal structural assignments. In addition to FAIMS gas-phase fractionation benefits, extra sorting of the structurally related LOS molecules was further accomplished using Kendrick mass defect (KMD) plots. Notably, a custom KMD base unit of [Na-H] created a highly organized KMD plot that allowed identification of interesting and novel structural differences across the different LOS ion families, i.e., ions with different acylation degrees, oligosaccharides composition, and chemical modifications. Defining the composition of a single LOS ion by tandem MS along with the organized KMD plot structural network was sufficient to deduce the composition of 181 LOS species out of 321 species present in the mixture. The combination of FAIMS and KMD plots allowed in-depth characterization of the complex LOS mixture and uncovered a wealth of novel information about its structural variations.

Deep proteome coverage advances knowledge of Treponema pallidum protein expression profiles during infection.

Comprehensive proteome-wide analysis of the syphilis spirochete, Treponema pallidum ssp. pallidum, is technically challenging due to high sample complexity, difficulties with obtaining sufficient quantities of bacteria for analysis, and the inherent fragility of the T. pallidum cell envelope which further complicates proteomic identification of rare T. pallidum outer membrane proteins (OMPs). The main aim of the present study was to gain a deeper understanding of the T. pallidum global proteome expression profile under infection conditions. This will corroborate and extend genome annotations, identify protein modifications that are unable to be predicted at the genomic or transcriptomic levels, and provide a foundational knowledge of the T. pallidum protein expression repertoire. Here we describe the optimization of a T. pallidum-specific sample preparation workflow and mass spectrometry-based proteomics pipeline which allowed for the detection of 77% of the T. pallidum protein repertoire under infection conditions. When combined with prior studies, this brings the overall coverage of the T. pallidum proteome to almost 90%. These investigations identified 27 known/predicted OMPs, including potential vaccine candidates, and detected expression of 11 potential OMPs under infection conditions for the first time. The optimized pipeline provides a robust and reproducible workflow for investigating T. pallidum protein expression during infection. Importantly, the combined results provide the deepest coverage of the T. pallidum proteome to date.

Investigating A Multi-Domain Polyketide Synthase in Amphidinium carterae.

Dinoflagellates are unicellular organisms that are implicated in harmful algal blooms (HABs) caused by potent toxins that are produced through polyketide synthase (PKS) pathways. However, the exact mechanisms of toxin synthesis are unknown due to a lack of genomic segregation of fat, toxins, and other PKS-based pathways. To better understand the underlying mechanisms, the actions and expression of the PKS proteins were investigated using the toxic dinoflagellate Amphidinium carterae as a model. Cerulenin, a known ketosynthase inhibitor, was shown to reduce acetate incorporation into all fat classes with the toxins amphidinol and sulpho-amphidinol. The mass spectrometry analysis of cerulenin-reacted synthetic peptides derived from ketosynthase domains of A. carterae multimodular PKS transcripts demonstrated a strong covalent bond that could be localized using collision-induced dissociation. One multi-modular PKS sequence present in all dinoflagellates surveyed to date was found to lack an AT domain in toxin-producing species, indicating trans-acting domains, and was shown by Western blotting to be post-transcriptionally processed. These results demonstrate how toxin synthesis in dinoflagellates can be differentiated from fat synthesis despite common underlying pathway.

Strategies for uncovering stable isotope tracing patterns between cell populations.

Despite practical complexities, isotope tracing studies in humans are becoming increasingly feasible. However, several technological challenges need to be addressed in order to take full advantage of human tracing studies. First, absolute metabolic flux measurements in mice are not so easily applied to human models, given that tissue resection is restricted to a single surgical time point. Second, isotope tracing has yet to be employed to detect metabolic differences between cells types in vivo. Here, we discuss the current models and propose an alternative, liquid tumor environment, that could overcome these limitations. Furthermore, we highlight current strategies used to maintain isotopolog enrichment following cell isolation techniques to facilitate cell-type-specific analysis.

Structural Elucidation of Intact Rough-Type Lipopolysaccharides using Field Asymmetric Ion Mobility Spectrometry and Kendrick Mass Defect Plots.

Lipopolysaccharide (LPS) is a hallmark virulence factor of Gram-negative bacteria. It is a complex, structurally heterogeneous mixture due to variations in number, type, and position of its simplest units: fatty acids and monosaccharides. Thus, LPS structural characterization by traditional mass spectrometry (MS) methods is challenging. Here, we describe the benefits of field asymmetric ion mobility spectrometry (FAIMS) for analysis of intact R-type lipopolysaccharide complex mixture (lipooligosaccharide; LOS). Structural characterization was performed using Escherichia coli J5 (Rc mutant) LOS, a TLR4 agonist widely used in glycoconjugate vaccine research. FAIMS gas phase fractionation improved the (S/N) ratio and number of detected LOS species. Additionally, FAIMS allowed the separation of overlapping isobars facilitating their tandem MS characterization and unequivocal structural assignments. In addition to FAIMS gas phase fractionation benefits, extra sorting of the structurally related LOS molecules was further accomplished using Kendrick mass defect (KMD) plots. Notably, a custom KMD base unit of [NaH] created a highly organized KMD plot that allowed identification of interesting and novel structural differences across the different LOS ion families; i.e., ions with different acylation degrees, oligosaccharides composition, and chemical modifications. Defining the composition of a single LOS ion by tandem MS along with the organized KMD plot structural network was sufficient to deduce the composition of 179 LOS species out of 321 species present in the mixture. The combination of FAIMS and KMD plots allowed in-depth characterization of the complex LOS mixture and uncovered a wealth of novel information about its structural variations.

Lipid A structural diversity among members of the genus Leptospira.

Lipid A is the hydrophobic component of bacterial lipopolysaccharide and an activator of the host immune system. Bacteria modify their lipid A structure to adapt to the surrounding environment and, in some cases, to evade recognition by host immune cells. In this study, lipid A structural diversity within the Leptospira genus was explored. The individual Leptospira species have dramatically different pathogenic potential that ranges from non-infectious to life-threatening disease (leptospirosis). Ten distinct lipid A profiles, denoted L1-L10, were discovered across 31 Leptospira reference species, laying a foundation for lipid A-based molecular typing. Tandem MS analysis revealed structural features of Leptospira membrane lipids that might alter recognition of its lipid A by the host innate immune receptors. Results of this study will aid development of strategies to improve diagnosis and surveillance of leptospirosis, as well as guide functional studies on Leptospira lipid A activity.

Structure Determination of Lipid A with Multiple Glycosylation Sites by Tandem MS of Lithium-Adducted Negative Ions.

FLATn is a tandem mass spectrometric technique that can be used to rapidly generate spectral information applicable for structural elucidation of lipids like lipid A from Gram-negative bacterial species from a single bacterial colony. In this study, we extend the scope and capability of FLATn by tandem MS fragmentation of lithium-adducted molecular lipid A anions and fragments (FLATn-Li) that provides additional structural and diagnostic data from FLATn samples allowing for the discrimination of terminal phosphate modifications in a variety of pathogenic and environmental species. Using FLATn-Li, we elucidated the lipid A structure from several bacterial species, including novel structures from arctic bacterioplankton of the Duganella and Massilia genera that favor 4-amino-4-deoxy-l-arabinopyranose (Ara4N) modification at the 1-phosphate position and that demonstrate double glycosylation with Ara4N at the 1 and 4' phosphate positions simultaneously. The structures characterized in this work demonstrate that some environmental psychrophilic species make extensive use of this structural lipid A modification previously characterized as a pathogenic adaptation and the structural basis of resistance to cationic antimicrobial peptides. This observation extends the role of phosphate modification(s) in environmental species adaptation and suggests that Ara4N modification can functionally replace the positive charge of the phosphoethanolamine modification that is more typically found attached to the 1-phosphate position of modified lipid A.

Sample Preparation Methods for Targeted Single-Cell Proteomics.

We compared three cell isolation and two proteomic sample preparation methods for single-cell and near-single-cell analysis. Whole blood was used to quantify hemoglobin (Hb) and glycated-Hb (gly-Hb) in erythrocytes using targeted mass spectrometry and stable isotope-labeled standard peptides. Each method differed in cell isolation and sample preparation as follows: 1) FACS and automated preparation in one-pot for trace samples (autoPOTS); 2) limited dilution via microscopy and a novel rapid one-pot sample preparation method that circumvented the need for the solid-phase extraction, low-volume liquid handling instrumentation and humidified incubation chamber; and 3) CellenONE-based cell isolation and the same one-pot sample preparation method used for limited dilution. Only the CellenONE device routinely isolated single-cells from which Hb was measured to be 540-660 amol per red blood cell (RBC), which was comparable to the calculated SI reference range for mean corpuscular hemoglobin (390-540 amol/RBC). FACSAria sorter and limited dilution could routinely isolate single-digit cell numbers, to reliably quantify CMV-Hb heterogeneity. Finally, we observed that repeated measures, using 5-25 RBCs obtained from N = 10 blood donors, could be used as an alternative and more efficient strategy than single RBC analysis to measure protein heterogeneity, which revealed multimodal distribution, unique for each individual.

The Immunopeptidome from a Genomic Perspective: Establishing the Noncanonical Landscape of MHC Class I-Associated Peptides.

Tumor antigens can emerge through multiple mechanisms, including translation of noncoding genomic regions. This noncanonical category of tumor antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry (MS) to enable the discovery of noncanonical MHC class I-associated peptides (ncMAP) from noncoding regions. Considering that the emergence of tumor antigens can also involve posttranslational modifications (PTM), we included an open search component in our pipeline. Leveraging the wealth of MS-based immunopeptidomics, we analyzed data from 26 MHC class I immunopeptidomic studies across 11 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant PTMs, using spectral matching and controlled their FDR to 1%. The noncanonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 55%. The data reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive therapeutic targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targets for T-cell therapies or vaccine development.

Absolute Quantitative Targeted Proteomics Assays for Plasma Proteins.

Preclinical and clinical trials require rapid, precise, and multiplexed analytical methods to characterize the complex samples and to allow high-throughput biomarker monitoring with low consumption of sample material. Targeted proteomics has been used to address these challenges when quantifying protein abundances in complex biological matrices. In many of these studies, blood plasma is collected either as the main research or diagnostic sample or in combination with other specimens. Mass spectrometry (MS)-based targeted proteomics using multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) with stable isotope-labeled internal standard (SIS) peptides allows robust characterization of blood plasma protein via absolute quantification. Compared to other commonly used technologies like enzyme-linked immunosorbent assay (ELISA), targeted proteomics is faster, more sensitive, and more cost-effective. Here we describe a protocol for the quantification of proteins in blood plasma using targeted MRM proteomics with heavy-labeled internal standards. The 270-protein panel allows rapid and robust absolute quantitative proteomic characterization of blood plasma in a 1 h gradient. The method we describe here works for non-depleted plasma, which makes it simple and easy to implement. Moreover, the protocol works with the two most commonly used blood plasma collection methods used in practice, namely, either K2EDTA or sodium citrate as anticoagulants.

Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics.

In targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8 k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.