An Integrated Approach to Protein Discovery and Detection From Complex Biofluids.

Ovarian cancer, a leading cause of cancer-related deaths among women, has been notoriously difficult to screen for and diagnose early, as early detection significantly improves survival. Researchers and clinicians seek routinely usable and noninvasive screening methods; however, available methods (i.e., biomarker screening) lack desirable sensitivity/specificity. The most fatal form, high-grade serous ovarian cancer, often originate in the fallopian tube; therefore, sampling from the vaginal environment provides more proximal sources for tumor detection. To address these shortcomings and leverage proximal sampling, we developed an untargeted mass spectrometry microprotein profiling method and identified cystatin A, which was validated in an animal model. To overcome the limits of detection inherent to mass spectrometry, we demonstrated that cystatin A is present at 100 pM concentrations using a label-free microtoroid resonator and translated our workflow to patient-derived clinical samples, highlighting the potential utility of early stage detection where biomarker levels would be low.

A Label-Free Approach for Relative Spatial Quantitation of c-di-GMP in Microbial Biofilms.

Microbial biofilms represent an important lifestyle for bacteria and are dynamic three-dimensional structures. Cyclic dimeric guanosine monophosphate (c-di-GMP) is a ubiquitous signaling molecule that is known to be tightly regulated with biofilm processes. While measurements of global levels of c-di-GMP have proven valuable toward understanding the genetic control of c-di-GMP production, there is a need for tools to observe the local changes of c-di-GMP production in biofilm processes. We have developed a label-free method for the direct detection of c-di-GMP in microbial colony biofilms using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We applied this method to the enteric pathogen Vibrio cholerae, the marine symbiont V. fischeri, and the opportunistic pathogen Pseudomonas aeruginosa PA14 and detected spatial and temporal changes in c-di-GMP signal that accompanied genetic alterations in factors that synthesize and degrade the compound. We further demonstrated how this method can be simultaneously applied to detect additional metabolites of interest from a single sample.

Reducing Mass Confusion over the Microbiome.

As genetic tools continue to emerge and mature, more information is revealed about the identity and diversity of microbial community members. Genetic tools can also be used to make predictions about the chemistry that bacteria and fungi produce to function and communicate with one another and the host. Ongoing efforts to identify these products and link genetic information to microbiome chemistry rely on analytical tools. This tutorial highlights recent advancements in microbiome studies driven by techniques in mass spectrometry.

TIMSCONVERT: a workflow to convert trapped ion mobility data to open data formats.

MOTIVATION: Advances in mass spectrometry have led to the development of mass spectrometers with ion mobility spectrometry capabilities and dual-source instrumentation; however, the current software ecosystem lacks interoperability with downstream data analysis using open-source software and pipelines. RESULTS: Here, we present TIMSCONVERT, a data conversion high-throughput workflow from timsTOF Pro/fleX mass spectrometer raw data files to mzML and imzML formats that incorporates ion mobility data while maintaining compatibility with data analysis tools. We showcase several examples using data acquired across different experiments and acquisition modalities on the timsTOF fleX MS. AVAILABILITY AND IMPLEMENTATION: TIMSCONVERT and its documentation can be found at https://github.com/gtluu/timsconvert and is available as a standalone command-line interface tool for Windows and Linux, NextFlow workflow and online in the Global Natural Products Social (GNPS) platform. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The neurotransmitter receptor Gabbr1 regulates proliferation and function of hematopoietic stem and progenitor cells.

Hematopoietic and nervous systems are linked via innervation of bone marrow (BM) niche cells. Hematopoietic stem/progenitor cells (HSPCs) express neurotransmitter receptors, such as the γ-aminobutyric acid (GABA) type B receptor subunit 1 (GABBR1), suggesting that HSPCs could be directly regulated by neurotransmitters like GABA that directly bind to GABBR1. We performed imaging mass spectrometry and found that the endogenous GABA molecule is regionally localized and concentrated near the endosteum of the BM niche. To better understand the role of GABBR1 in regulating HSPCs, we generated a constitutive Gabbr1-knockout mouse model. Analysis revealed that HSPC numbers were significantly reduced in the BM compared with wild-type littermates. Moreover, Gabbr1-null hematopoietic stem cells had diminished capacity to reconstitute irradiated recipients in a competitive transplantation model. Gabbr1-null HSPCs were less proliferative under steady-state conditions and upon stress. Colony-forming unit assays demonstrated that almost all Gabbr1-null HSPCs were in a slow or noncycling state. In vitro differentiation of Gabbr1-null HSPCs in cocultures produced fewer overall cell numbers with significant defects in differentiation and expansion of the B-cell lineage. To determine whether a GABBR1 agonist could stimulate human umbilical cord blood (UCB) HSPCs, we performed brief ex vivo treatment prior to transplant into immunodeficient mice, with significant increases in long-term engraftment of HSPCs compared with GABBR1 antagonist or vehicle treatments. Our results indicate a direct role for GABBR1 in HSPC proliferation, and identify a potential target to improve HSPC engraftment in clinical transplantation.

Metabolomics of bacterial-fungal pairwise interactions reveal conserved molecular mechanisms.

Bacterial-fungal interactions (BFIs) can shape the structure of microbial communities, but the small molecules mediating these BFIs are often understudied. We explored various optimization steps for our microbial culture and chemical extraction protocols for bacterial-fungal co-cultures, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) revealed that metabolomic profiles are mainly comprised of fungi derived features, indicating that fungi are the key contributors to small molecules in BFIs. LC-inductively coupled plasma MS (LC-ICP-MS) and MS/MS based dereplication using database searching revealed the presence of several known fungal specialized metabolites and structurally related analogues in these extracts, including siderophores such as desferrichrome, desferricoprogen, and palmitoylcoprogen. Among these analogues, a novel putative coprogen analogue possessing a terminal carboxylic acid motif was identified from Scopulariopsis sp. JB370, a common cheese rind fungus, and its structure was elucidated via MS/MS fragmentation. Based on these findings, filamentous fungal species appear to be capable of producing multiple siderophores with potentially different biological roles (i.e. various affinities for different forms of iron). These findings highlight that fungal species are important contributors to microbiomes via their production of abundant specialized metabolites and that elucidating their role in complex communities should continue to be a priority.

Automated Microbial Library Generation Using the Bioinformatics Platform IDBac.

Libraries of microorganisms have served as a cornerstone of therapeutic drug discovery, though the continued re-isolation of known natural product chemical entities has remained a significant obstacle to discovery efforts. A major contributing factor to this redundancy is the duplication of bacterial taxa in a library, which can be mitigated through the use of a variety of DNA sequencing strategies and/or mass spectrometry-informed bioinformatics platforms so that the library is created with minimal phylogenetic, and thus minimal natural product overlap. IDBac is a MALDI-TOF mass spectrometry-based bioinformatics platform used to assess overlap within collections of environmental bacterial isolates. It allows environmental isolate redundancy to be reduced while considering both phylogeny and natural product production. However, manually selecting isolates for addition to a library during this process was time intensive and left to the researcher's discretion. Here, we developed an algorithm that automates the prioritization of hundreds to thousands of environmental microorganisms in IDBac. The algorithm performs iterative reduction of natural product mass feature overlap within groups of isolates that share high homology of protein mass features. Employing this automation serves to minimize human bias and greatly increase efficiency in the microbial strain prioritization process.

Nitric oxide-targeted therapy inhibits stemness and increases the efficacy of tamoxifen in estrogen receptor-positive breast cancer cells.

Cancer stem cells (CSCs) are involved in the resistance of estrogen (ER)-positive breast tumors against endocrine therapy. On the other hand, nitric oxide (NO) plays a relevant role in CSC biology, although there are no studies addressing how this important signaling molecule may contribute to resistance to antihormonal therapy in ER+ breast cancer. Therefore, we explored whether targeting NO in ER+ breast cancer cells impacts CSC subpopulation and sensitivity to hormonal therapy with tamoxifen. NO was targeted in ER+ breast cancer cells by specific NO depletion and NOS2 silencing and mammosphere formation capacity, stem cell markers and tamoxifen sensitivity were analyzed. An orthotopic breast tumor model in mice was also performed to analyze the efficacy of NO-targeted therapy plus tamoxifen. Kaplan-Meier curves were made to analyze the association of NOS2 gene expression with survival of ER+ breast cancer patients treated with tamoxifen. Our results show that targeting NO inhibited mamosphere formation, CSC markers expression and increased the antitumoral efficacy of tamoxifen in ER+ breast cancer cells, whereas tamoxifen-resistant cells displayed higher expression levels of NOS2 and Notch-1 compared with parental cells. Notably, NO-targeted therapy plus tamoxifen was more effective than either treatment alone in an orthotopic breast tumor model in immunodeficient mice. Furthermore, low NOS2 expression was significantly associated with a higher metastasis-free survival in ER+ breast cancer patients treated with tamoxifen. In conclusion, our data support that NO-targeted therapy in ER+ breast cancer may contribute to increase the efficacy of antihormonal therapy avoiding the development of resistance to these treatments.

Toward improvement of screening through mass spectrometry-based proteomics: ovarian cancer as a case study.

Ovarian cancer is one of the leading causes of cancer related deaths affecting United States women. Early-stage detection of ovarian cancer has been linked to increased survival, however, current screening methods, such as biomarker testing, have proven to be ineffective in doing so. Therefore, further developments are necessary to be able to achieve positive patient prognosis. Ongoing efforts are being made in biomarker discovery towards clinical applications in screening for early-stage ovarian cancer. In this perspective, we discuss and provide examples for several workflows employing mass spectrometry-based proteomics towards protein biomarker discovery and characterization in the context of ovarian cancer; workflows include protein identification and characterization as well as intact protein profiling. We also discuss the opportunities to merge these workflows for a multiplexed approach for biomarkers. Lastly, we provide our insight as to future developments that may serve to enhance biomarker discovery workflows while also considering translational potential.

Coupling MALDI-TOF mass spectrometry protein and specialized metabolite analyses to rapidly discriminate bacterial function.

For decades, researchers have lacked the ability to rapidly correlate microbial identity with bacterial metabolism. Since specialized metabolites are critical to bacterial function and survival in the environment, we designed a data acquisition and bioinformatics technique (IDBac) that utilizes in situ matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze protein and specialized metabolite spectra recorded from single bacterial colonies picked from agar plates. We demonstrated the power of our approach by discriminating between two Bacillus subtilis strains in <30 min solely on the basis of their differential ability to produce cyclic peptide antibiotics surfactin and plipastatin, caused by a single frameshift mutation. Next, we used IDBac to detect subtle intraspecies differences in the production of metal scavenging acyl-desferrioxamines in a group of eight freshwater Micromonospora isolates that share >99% sequence similarity in the 16S rRNA gene. Finally, we used IDBac to simultaneously extract protein and specialized metabolite MS profiles from unidentified Lake Michigan sponge-associated bacteria isolated from an agar plate. In just 3 h, we created hierarchical protein MS groupings of 11 environmental isolates (10 MS replicates each, for a total of 110 spectra) that accurately mirrored phylogenetic groupings. We further distinguished isolates within these groupings, which share nearly identical 16S rRNA gene sequence identity, based on interspecies and intraspecies differences in specialized metabolite production. IDBac is an attempt to couple in situ MS analyses of protein content and specialized metabolite production to allow for facile discrimination of closely related bacterial colonies.

A Family of Nonribosomal Peptides Modulate Collective Behavior in Pseudovibrio Bacteria Isolated from Marine Sponges*.

Although swarming motility and biofilms are opposed collective behaviors, both contribute to bacterial survival and host colonization. Pseudovibrio bacteria have attracted attention because they are part of the microbiome of healthy marine sponges. Two-thirds of Pseudovibrio genomes contain a member of a nonribosomal peptide synthetase-polyketide synthase gene cluster family, which is also found sporadically in Pseudomonas pathogens of insects and plants. After developing reverse genetics for Pseudovibrio, we isolated heptapeptides with an ureido linkage and related nonadepsipeptides we termed pseudovibriamides A and B, respectively. A combination of genetics and imaging mass spectrometry experiments showed heptapetides were excreted, promoting motility and reducing biofilm formation. In contrast to lipopeptides widely known to affect motility/biofilms, pseudovibriamides are not surfactants. Our results expand current knowledge on metabolites mediating bacterial collective behavior.

Detection of Ovarian Cancer Using Samples Sourced from the Vaginal Microenvironment.

Mass spectrometry (MS) offers high levels of specificity and sensitivity in clinical applications, and we have previously been able to demonstrate that matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS is capable of distinguishing two-component cell mixtures at low limits of detection. Ovarian cancer is notoriously difficult to detect due to the lack of diagnostic techniques available to the medical community. By sampling a local microenvironment, such as the vaginal canal and cervix, a MS based method is presented for monitoring disease progression from proximal samples to the diseased tissue. A murine xenograft model of high grade serous ovarian carcinoma (HGSOC) was used for this study, and vaginal lavages were obtained from mice on a weekly basis throughout disease progression and subjected to our MALDI-TOF MS workflow followed by statistical analyses. Proteins in the 4-20 kDa region of the mass spectrum yielded a fingerprint that we could consistently measure over time that correlated with disease progression. These fingerprints were found to be largely stable across all mice, with the protein fingerprint converging toward the end point of the study. MALDI-TOF MS serves as a unique analytical technique for measuring a sampled vaginal microenvironment in a specific and sensitive manner for the detection of HGSOC in a murine model.

Imaging mass spectrometry for natural products discovery: a review of ionization methods.

Covering: 2009-2019 Over the last decade, methods in imaging mass spectrometry (IMS) have progressively improved and diversified toward a variety of applications in natural products research. Because IMS allows for the spatial mapping of the production and distribution of biologically active molecules in situ, it facilitates phenotype and organelle driven discovery efforts. As practitioners of IMS for natural products discovery, we find one of the most important aspects of these experiments is the sample preparation and compatibility with different ionization sources that are available to a given researcher. As such, we have focused this mini review to cover types of ionization sources that have been used in natural products discovery applications and provided concrete examples of use for natural products discovery while discussing the advantages and limitations of each method. We aim for this article to serve as a resource to guide the broader natural product community interested in IMS toward the application/method that would best serve their natural product discovery needs given the sample and analyte(s) of interest. This mini review has been limited to applications using natural products and thus is not exhaustive of all possible ionization methods which have only been applied to image other types of samples such as mammalian tissues. Additionally, we briefly review how IMS has been coupled with other imaging platforms, such as microscopy, to enhance information outputs as well as offer our future perspectives on the incorporation of IMS in natural products discovery.

SWATH-based proteomics reveals processes associated with immune evasion and metastasis in poor prognosis colorectal tumours.

Newly emerged proteomic methodologies, particularly data-independent acquisition (DIA) analysis-related approaches, would improve current gene expression-based classifications of colorectal cancer (CRC). Therefore, this study was aimed to identify protein expression signatures using SWATH-MS DIA and targeted data extraction, to aid in the classification of molecular subtypes of CRC and advance in the diagnosis and development of new drugs. For this purpose, 40 human CRC samples and 7 samples of healthy tissue were subjected to proteomic and bioinformatic analysis. The proteomic analysis identified three different molecular CRC subtypes: P1, P2 and P3. Significantly, P3 subtype showed high agreement with the mesenchymal/stem-like subtype defined by gene expression signatures and characterized by poor prognosis and survival. The P3 subtype was characterized by decreased expression of ribosomal proteins, the spliceosome, and histone deacetylase 2, as well as increased expression of osteopontin, SERPINA 1 and SERPINA 3, and proteins involved in wound healing, acute inflammation and complement pathway. This was also confirmed by immunodetection and gene expression analyses. Our results show that these tumours are characterized by altered expression of proteins involved in biological processes associated with immune evasion and metastasis, suggesting new therapeutic options in the treatment of this aggressive type of CRC.

Minimizing Taxonomic and Natural Product Redundancy in Microbial Libraries Using MALDI-TOF MS and the Bioinformatics Pipeline IDBac.

Libraries of microorganisms have been a cornerstone of drug discovery efforts since the mid-1950s, but strain duplication in some libraries has resulted in unwanted natural product redundancy. In the current study, we implemented a workflow that minimizes both the natural product overlap and the total number of bacterial isolates in a library. Using a collection expedition to Iceland as an example, we purified every distinct bacterial colony off isolation plates derived from 86 environmental samples. We employed our mass spectrometry (MS)-based IDBac workflow on these isolates to form groups of taxa based on protein MS fingerprints (3-15 kDa) and further distinguished taxa subgroups based on their degree of overlap within corresponding natural product spectra (0.2-2 kDa). This informed the decision to create a library of 301 isolates spanning 54 genera. This process required only 25 h of data acquisition and 2 h of analysis. In a separate experiment, we reduced the size of an existing library based on the degree of metabolic overlap observed in natural product MS spectra of bacterial colonies (from 833 to 233 isolates, a 72.0% size reduction). Overall, our pipeline allows for a significant reduction in costs associated with library generation and minimizes natural product redundancy entering into downstream biological screening efforts.

A role for endothelial nitric oxide synthase in intestinal stem cell proliferation and mesenchymal colorectal cancer.

BACKGROUND: Nitric oxide (NO) has been highlighted as an important agent in cancer-related events. Although the inducible nitric oxide synthase (iNOS) isoform has received most attention, recent studies in the literature indicate that the endothelial isoenzyme (eNOS) can also modulate different tumor processes including resistance, angiogenesis, invasion, and metastasis. However, the role of eNOS in cancer stem cell (CSC) biology and mesenchymal tumors is unknown. RESULTS: Here, we show that eNOS was significantly upregulated in VilCre ERT2 Apc fl/+ and VilCre ERT2 Apc fl/fl mouse intestinal tissue, with intense immunostaining in hyperproliferative crypts. Similarly, the more invasive VilCre ERT2 Apc fl/+ Pten fl/+ mouse model showed an overexpression of eNOS in intestinal tumors whereas this isoform was not expressed in normal tissue. However, none of the three models showed iNOS expression. Notably, when 40 human colorectal tumors were classified into different clinically relevant molecular subtypes, high eNOS expression was found in the poor relapse-free and overall survival mesenchymal subtype, whereas iNOS was absent. Furthermore, Apc fl/fl organoids overexpressed eNOS compared with wild-type organoids and NO depletion with the scavenger carboxy-PTIO (c-PTIO) decreased the proliferation and the expression of stem-cell markers, such as Lgr5, Troy, Vav3, and Slc14a1, in these intestinal organoids. Moreover, specific NO depletion also decreased the expression of CSC-related proteins in human colorectal cancer cells such as ß-catenin and Bmi1, impairing the CSC phenotype. To rule out the contribution of iNOS in this effect, we established an iNOS-knockdown colorectal cancer cell line. NO-depleted cells showed a decreased capacity to form tumors and c-PTIO treatment in vivo showed an antitumoral effect in a xenograft mouse model. CONCLUSION: Our data support that eNOS upregulation occurs after Apc loss, emerging as an unexpected potential new target in poor-prognosis mesenchymal colorectal tumors, where NO scavenging could represent an interesting therapeutic alternative to targeting the CSC subpopulation.

Pseudomonas aeruginosa PumA acts on an endogenous phenazine to promote self-resistance.

The activities of critical metabolic and regulatory proteins can be altered by exposure to natural or synthetic redox-cycling compounds. Many bacteria, therefore, possess mechanisms to transport or transform these small molecules. The opportunistic pathogen Pseudomonas aeruginosa PA14 synthesizes phenazines, redox-active antibiotics that are toxic to other organisms but have beneficial effects for their producer. Phenazines activate the redox-sensing transcription factor SoxR and thereby induce the transcription of a small regulon, including the operon mexGHI-opmD, which encodes an efflux pump that transports phenazines, and PA14_35160 (pumA), which encodes a putative monooxygenase. Here, we provide evidence that PumA contributes to phenazine resistance and normal biofilm development, particularly during exposure to or production of strongly oxidizing N-methylated phenazines. We show that phenazine resistance depends on the presence of residues that are conserved in the active sites of other putative and characterized monooxygenases found in the antibiotic producer Streptomyces coelicolor. We also show that during biofilm growth, PumA is required for the conversion of phenazine methosulfate to unique phenazine metabolites. Finally, we compare ∆mexGHI-opmD and ∆pumA strains in assays for colony biofilm morphogenesis and SoxR activation, and find that these deletions have opposing phenotypic effects. Our results suggest that, while MexGHI-OpmD-mediated efflux has the effect of making the cellular phenazine pool more reducing, PumA acts on cellular phenazines to make the pool more oxidizing. We present a model in which these two SoxR targets function simultaneously to control the biological activity of the P. aeruginosa phenazine pool.

Altered S-nitrosothiol homeostasis provides a survival advantage to breast cancer cells in HER2 tumors and reduces their sensitivity to trastuzumab.

The monoclonal antibody trastuzumab against HER2/neu, which is overexpressed in 15-20% of breast cancers, has clinical efficacy but many patients do not respond to initial treatment or develop resistance during treatment. Nitric oxide (NO) regulates cell signaling by targeting specific cysteine residues in proteins, forming S-nitrosothiols (SNO) in a process known as S-nitrosylation. We previously reported that molecular characteristics in breast cancer may dictate the tumor response to impaired SNO homeostasis. In the present study, we explored the role of SNO homeostasis in HER2 breast tumors. The antiproliferative action of trastuzumab in HER2-overexpressing BT-474 and SKBR-3 cells was suppressed when S-nitrosoglutathione reductase (GSNOR/ADH5) activity, which plays a key role in SNO homeostasis, was specifically inhibited with the pyrrole derivative compound N6022. Moreover, GSNOR inhibition restored the activation of survival signaling pathways involved in the resistance to anti-HER2 therapies (AKT, Src and c-Abl kinases and TrkA/NRTK1, TrkB/NRTK2, EphA1 and EphA3 receptors) and reduced the apoptotic effect of trastuzumab. Accordingly, GSNOR inhibition augmented the S-nitrosylation of apoptosis-related proteins, including Apaf-1, pSer73/63 c-Jun, calcineurin subunit α and HSF1. In agreement with in vitro data, immunohistochemical analyses of 51 breast tumors showed that HER2 expression was associated with lower expression of GSNOR protein. Moreover, gene expression analysis confirmed that high ADH5/GSNOR gene expression was associated with high patient survival rates in HER2 tumors. In conclusion, our data provide evidence of molecular mechanisms contributing to the progression of HER2+ breast cancers and could facilitate the development of therapeutic options to counteract resistance to anti-HER2 therapies.

Exhaled breath condensate biomarkers for the early diagnosis of lung cancer using proteomics.

We explored whether the proteomic analysis of exhaled breath condensate (EBC) may provide biomarkers for noninvasive screening for the early detection of lung cancer (LC). EBC was collected from 192 individuals [49 control (C), 49 risk factor-smoking (S), 46 chronic obstructive pulmonary disease (COPD) and 48 LC]. With the use of liquid chromatography and tandem mass spectrometry, 348 different proteins with a different pattern among the four groups were identified in EBC samples. Significantly more proteins were identified in the EBC from LC compared with other groups (C: 12.4 ± 1.3; S: 15.3 ± 1; COPD: 14 ± 1.6; LC: 24.2 ± 3.6; P = 0.0001). Furthermore, the average number of proteins identified per sample was significantly higher in LC patients, and receiver operating characteristic curve (ROC) analysis showed an area under the curve of 0.8, indicating diagnostic value. Proteins frequently detected in EBC, such as dermcidin and hornerin, along with others much less frequently detected, such as hemoglobin and histones, were identified. Cytokeratins (KRTs) were the most abundant proteins in EBC samples, and levels of KRT6A, KRT6B, and KRT6C isoforms were significantly higher in samples from LC patients (P = 0.0031, 0.0011, and 0.0009, respectively). Moreover, the amount of most KRTs in EBC samples from LC patients showed a significant positive correlation with tumor size. Finally, we used a random forest algorithm to generate a robust model using EBC protein data for the diagnosis of patients with LC where the area under the ROC curve obtained indicated a good classification (82%). Thus this study demonstrates that the proteomic analysis of EBC samples is an appropriated approach to develop biomarkers for the diagnosis of lung cancer.

Proteomic approaches to evaluate protein S-nitrosylation in disease.

Many of nitric oxide (NO) actions are mediated through the coupling of a nitroso moiety to a reactive cysteine leading to the formation of a S-nitrosothiol (SNO), a process known as S-nitrosylation or S-nitrosation. In many cases this reversible post-translational modification is accompanied by altered protein function and aberrant S-nitrosylation of proteins, caused by altered production of NO and/or impaired SNO homeostasis, has been repeatedly reported in a variety of pathophysiological settings. A growing number of studies are directed to the identification and characterization of those proteins that undergo S-nitrosylation and the analysis of S-nitrosoproteomes under pathological conditions is beginning to be reported. The study of these S-nitrosoproteomes has been fueled by advances in proteomic technologies that are providing researchers with improved tools for exploring this post-translational modification. Here we review novel refinements and improvements to these methods, and some recent studies of the S-nitrosoproteome in disease.