Microproteomics: quantitative proteomic profiling of small numbers of laser-captured cells

Proteomic profiling of laser capture microdissection kidneys from diabetic nephropathy patients

Diabetic nephropathy (DN) remains the primary cause of end-stage renal disease (ESRD), warranting equal attention and separate analysis of glomerular, tubular, and interstitial lesions in its diagnosis and intervention. This study aims to identify the specific proteomics characteristics of DN, and assess changes in the biological processes associated with DN. 5 patients with DN and 5 healthy kidney transplant donor control individuals were selected for analysis. The proteomic characteristics of glomeruli, renal tubules, and renal interstitial tissue obtained through laser capture microscopy (LCM) were studied using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Significantly, the expression of multiple heat shock proteins (HSPs), tubulins, and heterogeneous nuclear ribonucleoproteins (hnRNPs) in glomeruli and tubules was significantly reduced. Differentially expressed proteins (DEPs) in the glomerulus showed significant enrichment in pathways related to cell junctions and cell movement, including the regulation of actin cytoskeleton and tight junction. DEPs in renal tubules were significantly enriched in glucose metabolism-related pathways, such as glucose metabolism, glycolysis/gluconeogenesis, and the citric acid cycle. Moreover, the glycolysis/gluconeogenesis pathway was a co-enrichment pathway in both DN glomeruli and tubules. Notably, ACTB emerged as the most crucial protein in the protein-protein interaction (PPI) analysis of DEPs in both glomeruli and renal tubules. In this study, we delve into the unique proteomic characteristics of each sub-region of renal tissue. This enhances our understanding of the potential pathophysiological changes in DN, particularly the potential involvement of glycolysis metabolic disorder, glomerular cytoskeleton and cell junctions. These insights are crucial for further research into the identification of disease biomarkers and the pathogenesis of DN.

STAT3/LKB1 controls metastatic prostate cancer by regulating mTORC1/CREB pathway

Prostate cancer (PCa) is a common and fatal type of cancer in men. Metastatic PCa (mPCa) is a major factor contributing to its lethality, although the mechanisms remain poorly understood. PTEN is one of the most frequently deleted genes in mPCa. Here we show a frequent genomic co-deletion of PTEN and STAT3 in liquid biopsies of patients with mPCa. Loss of Stat3 in a Pten-null mouse prostate model leads to a reduction of LKB1/pAMPK with simultaneous activation of mTOR/CREB, resulting in metastatic disease. However, constitutive activation of Stat3 led to high LKB1/pAMPK levels and suppressed mTORC1/CREB pathway, preventing mPCa development. Metformin, one of the most widely prescribed therapeutics against type 2 diabetes, inhibits mTORC1 in liver and requires LKB1 to mediate glucose homeostasis. We find that metformin treatment of STAT3/AR-expressing PCa xenografts resulted in significantly reduced tumor growth accompanied by diminished mTORC1/CREB, AR and PSA levels. PCa xenografts with deletion of STAT3/AR nearly completely abrogated mTORC1/CREB inhibition mediated by metformin. Moreover, metformin treatment of PCa patients with high Gleason grade and type 2 diabetes resulted in undetectable mTORC1 levels and upregulated STAT3 expression. Furthermore, PCa patients with high CREB expression have worse clinical outcomes and a significantly increased risk of PCa relapse and metastatic recurrence. In summary, we have shown that STAT3 controls mPCa via LKB1/pAMPK/mTORC1/CREB signaling, which we have identified as a promising novel downstream target for the treatment of lethal mPCa.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Infrared Laser Ablation Microsampling with a Reflective Objective

A Schwarzschild reflective objective with a numerical aperture of 0.3 and working distance of 10 cm was used for laser ablation sampling of tissue for off-line mass spectrometry. The objective focused the laser to a diameter of 5 μm and produced 10 μm ablation spots on thin ink films and tissue sections. Rat brain tissue sections 50 μm thick were ablated in transmission geometry, and the ablated material was captured in a microcentrifuge tube containing solvent. Proteins from ablated tissue sections were quantified with a Bradford assay, which indicated that approximately 300 ng of protein was captured from a 1 mm² area of ablated tissue. Areas of tissue ranging from 0.01 to 1 mm² were ablated and captured for bottom-up proteomics. Proteins were extracted from the captured tissue and digested for liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis for peptide and protein identification.

Comparative Proteomic Profiling Identifies Reciprocal Expression of Mitochondrial Proteins Between White and Gray Matter Lesions From Multiple Sclerosis Brains

Multiple sclerosis (MS) is a chronic inflammatory and demyelinating disease of the central nervous system, where ongoing demyelination and remyelination failure are the major factors for progressive neurological disability. In this report, we employed a comprehensive proteomic approach and immunohistochemical validation to gain insight into the pathobiological mechanisms that may be associated with the progressive phase of MS. Isolated proteins from myelinated regions, demyelinated white-matter lesions (WMLs), and gray-matter lesions (GMLs) from well-characterized progressive MS brain tissues were subjected to label-free quantitative mass spectrometry. Using a system-biology approach, we detected increased expression of proteins belonging to mitochondrial electron transport complexes and oxidative phosphorylation pathway in WMLs. Intriguingly, many of these proteins and pathways had opposite expression patterns and were downregulated in GMLs of progressive MS brains. A comparison to the human MitoCarta database mapped the mitochondrial proteins to mitochondrial subunits in both WMLs and GMLs. Taken together, we provide evidence of opposite expression of mitochondrial proteins in response to demyelination of white- and gray-matter regions in progressive MS brain.

Proteomic Profiling of the Tumor Microenvironment

The tumor microenvironment forms a complex pro-tumorigenic milieu constituted by extracellular matrix, surrounding stroma, infiltrating cell populations, and signaling molecules. Proteomic studies have the potential to reveal how individual cell populations within the tumor tissue modulate the microenvironment through protein secretion and consequently alter their protein expression and localization to adapt to this milieu. As a result, proteomic approaches have uncovered how these dynamic components communicate and promote tumor development and progression. The characterization of these mechanisms is relevant for the identification of clinically targetable pathways and for the development of diagnostic tools. Here we describe a method based on the isolation of individual cell compartments and the chromatographic fractionation of intact proteins, followed by enzymatic digestion of individual fractions, and mass-spectrometry analysis, for the profiling of tumor microenvironment cell populations.

Deep-ultraviolet laser ablation sampling for proteomic analysis of tissue

Deep-ultraviolet laser ablation with a pulsed 193 nm ArF excimer laser was used to remove localized regions from tissue sections from which proteins were extracted for spatially resolved proteomic analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). The ability to capture intact proteins by ablation at 193 nm wavelength was verified by matrix-assisted laser desorption ionization (MALDI) of the protein standard bovine serum albumin (BSA), which showed that BSA was ablated and captured without fragmentation. A Bradford assay of the ablated and captured proteins indicated 90% efficiency for transfer of the intact protein at a laser fluence of 3 kJ/m². Rat brain tissue sections mounted on quartz microscope slides and ablated in transmission mode yielded 2 μg protein per mm² as quantified by the Bradford assay. Tissue areas ranging from 0.06 mm² to 1 mm² were ablated and the ejected material was collected for proteomic analysis. Extracted proteins were digested and the resulting peptides were analyzed by LC-MS/MS. The proteins extracted from the ablated areas were identified and the average number of identified proteins ranged from 85 in the 0.06 mm² area to 2400 in the 1 mm² area of a 50 μm thick tissue. In comparison to infrared laser ablation of equivalent sampled areas, both the protein mass and number of proteins identified using DUV laser ablation sampling were approximately four times larger.

Simple and Efficient Microsolid-Phase Extraction Tip-Based Sample Preparation Workflow to Enable Sensitive Proteomic Profiling of Limited Samples (200 to 10,000 Cells)

In-depth LC-MS-based proteomic profiling of limited biological and clinical samples, such as rare cells or tissue sections from laser capture microdissection or microneedle biopsies, has been problematic due, in large, to the inefficiency of sample preparation and attendant sample losses. To address this issue, we developed on-microsolid-phase extraction tip (OmSET)-based sample preparation for limited biological samples. OmSET is simple, efficient, reproducible, and scalable and is a widely accessible method for processing ∼200 to 10,000 cells. The developed method benefits from minimal sample processing volumes (1-3 μL) and conducting all sample processing steps on-membrane within a single microreactor. We first assessed the feasibility of using micro-SPE tips for nanogram-level amounts of tryptic peptides, minimized the number of required sample handling steps, and reduced the hands-on time. We then evaluated the capability of OmSET for quantitative analysis of low numbers of human monocytes. Reliable and reproducible label-free quantitation results were obtained with excellent correlations between protein abundances and the amounts of starting material (R2 = 0.93) and pairwise correlations between sample processing replicates (R2 = 0.95) along with the identification of approximately 300, 1800, and 2000 protein groups from injected ∼10, 100, and 500 cell equivalents, resulting from processing approximately 200, 2000, and 10,000 cells, respectively.

Microproteomic sample preparation

Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size-limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom-up approaches, and sample clean-up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean-up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs).

STAT3-dependent analysis reveals PDK4 as independent predictor of recurrence in prostate cancer

Prostate cancer (PCa) has a broad spectrum of clinical behavior; hence, biomarkers are urgently needed for risk stratification. Here, we aim to find potential biomarkers for risk stratification, by utilizing a gene co-expression network of transcriptomics data in addition to laser-microdissected proteomics from human and murine prostate FFPE samples. We show up-regulation of oxidative phosphorylation (OXPHOS) in PCa on the transcriptomic level and up-regulation of the TCA cycle/OXPHOS on the proteomic level, which is inversely correlated to STAT3 expression. We hereby identify gene expression of pyruvate dehydrogenase kinase 4 (PDK4), a key regulator of the TCA cycle, as a promising independent prognostic marker in PCa. PDK4 predicts disease recurrence independent of diagnostic risk factors such as grading, staging, and PSA level. Therefore, low PDK4 is a promising marker for PCa with dismal prognosis.

Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts

High-grade serous carcinoma has a poor prognosis, owing primarily to its early dissemination throughout the abdominal cavity. Genomic and proteomic approaches have provided snapshots of the proteogenomics of ovarian cancer1,2, but a systematic examination of both the tumour and stromal compartments is critical in understanding ovarian cancer metastasis. Here we develop a label-free proteomic workflow to analyse as few as 5,000 formalin-fixed, paraffin-embedded cells microdissected from each compartment. The tumour proteome was stable during progression from in situ lesions to metastatic disease; however, the metastasis-associated stroma was characterized by a highly conserved proteomic signature, prominently including the methyltransferase nicotinamide N-methyltransferase (NNMT) and several of the proteins that it regulates. Stromal NNMT expression was necessary and sufficient for functional aspects of the cancer-associated fibroblast (CAF) phenotype, including the expression of CAF markers and the secretion of cytokines and oncogenic extracellular matrix. Stromal NNMT expression supported ovarian cancer migration, proliferation and in vivo growth and metastasis. Expression of NNMT in CAFs led to depletion of S-adenosyl methionine and reduction in histone methylation associated with widespread gene expression changes in the tumour stroma. This work supports the use of ultra-low-input proteomics to identify candidate drivers of disease phenotypes. NNMT is a central, metabolic regulator of CAF differentiation and cancer progression in the stroma that may be therapeutically targeted.

The impact of growth hormone on proteomic profiles: a review of mouse and adult human studies

Growth hormone (GH) is a protein that is known to stimulate postnatal growth, counter regulate insulin's action and induce expression of insulin-like growth factor-1. GH exerts anabolic or catabolic effects depending upon on the targeted tissue. For instance, GH increases skeletal muscle and decreases adipose tissue mass. Our laboratory has spent the past two decades studying these effects, including the effects of GH excess and depletion, on the proteome of several mouse and human tissues. This review first discusses proteomic techniques that are commonly used for these types of studies. We then examine the proteomic differences found in mice with excess circulating GH (bGH mice) or mice with disruption of the GH receptor gene (GHR^-/-). We also describe the effects of increased and decreased GH action on the proteome of adult patients with either acromegaly, GH deficiency or patients after short-term GH treatment. Finally, we explain how these proteomic studies resulted in the discovery of potential biomarkers for GH action, particularly those related with the effects of GH on aging, glucose metabolism and body composition.

Convergent transcriptional specializations in the brains of humans and song-learning birds

Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes of song-learning birds and humans relative to vocal nonlearners identified convergent gene expression specializations in specific song and speech brain regions of avian vocal learners and humans. The strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively, with human laryngeal motor cortex and parts of the striatum that control speech production and learning. Most of the associated genes function in motor control and brain connectivity. Thus, convergent behavior and neural connectivity for a complex trait are associated with convergent specialized expression of multiple genes.

Core and region-enriched networks of behaviorally regulated genes and the singing genome

Songbirds represent an important model organism for elucidating molecular mechanisms that link genes with complex behaviors, in part because they have discrete vocal learning circuits that have parallels with those that mediate human speech. We found that ~10% of the genes in the avian genome were regulated by singing, and we found a striking regional diversity of both basal and singing-induced programs in the four key song nuclei of the zebra finch, a vocal learning songbird. The region-enriched patterns were a result of distinct combinations of region-enriched transcription factors (TFs), their binding motifs, and presinging acetylation of histone 3 at lysine 27 (H3K27ac) enhancer activity in the regulatory regions of the associated genes. RNA interference manipulations validated the role of the calcium-response transcription factor (CaRF) in regulating genes preferentially expressed in specific song nuclei in response to singing. Thus, differential combinatorial binding of a small group of activity-regulated TFs and predefined epigenetic enhancer activity influences the anatomical diversity of behaviorally regulated gene networks.

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.

Cancer biomarker discovery: current status and future perspectives

PURPOSE

Cancer is a multigene disease which arises as a result of mutational and epigenetic changes coupled with activation of complex signaling networks. The use of biomarkers for early cancer detection, staging and individualization of therapy might improve patient care. A few fundamental issues such as tumor heterogeneity, a highly dynamic nature of the intrinsic and extrinsic determinants of radio- and chemoresistance, along with the plasticity and diversity of cancer stem cells (CSC) make biomarker development a challenging task. In this review we outline the preclinical strategies of cancer biomarker discovery including genomic, proteomic, metabolomic and microRNomic profiling, comparative genome hybridization (CGH), single nucleotide polymorphism (SNP) analysis, high throughput screening (HTS) and next generation sequencing (NGS). Other promising approaches such as assessment of circulating tumor cells (CTC), analysis of CSC-specific markers and cell-free circulating tumor DNA (ctDNA) are also discussed.

CONCLUSIONS

The emergence of powerful proteomic and genomic technologies in conjunction with advanced bioinformatic tools allows the simultaneous analysis of thousands of biological molecules. These techniques yield the discovery of new tumor signatures, which are sensitive and specific enough for early cancer detection, for monitoring disease progression and for proper treatment selection, paving the way to individualized cancer treatment.

Proteomic analysis of laser capture microscopy purified myotendinous junction regions from muscle sections

The myotendinous junction is a specialized structure of the muscle fibre enriched in mechanosensing complexes, including costameric proteins and core elements of the z-disc. Here, laser capture microdissection was applied to purify membrane regions from the myotendinous junctions of mouse skeletal muscles, which were then processed for proteomic analysis. Sarcolemma sections from the longitudinal axis of the muscle fibre were used as control for the specificity of the junctional preparation. Gene ontology term analysis of the combined lists indicated a statistically significant enrichment in membrane-associated proteins. The myotendinous junction preparation contained previously uncharacterized proteins, a number of z-disc costameric ligands (e.g., actinins, capZ, αB cristallin, filamin C, cypher, calsarcin, desmin, FHL1, telethonin, nebulin, titin and an enigma-like protein) and other proposed players of sarcomeric stretch sensing and signalling, such as myotilin and the three myomesin homologs. A subset were confirmed by immunofluorescence analysis as enriched at the myotendinous junction, suggesting that laser capture microdissection from muscle sections is a valid approach to identify novel myotendinous junction players potentially involved in mechanotransduction pathways.

Moving H5N1 studies into the era of systems biology

The dynamics of H5N1 influenza virus pathogenesis are multifaceted and can be seen as an emergent property that cannot be comprehended without looking at the system as a whole. In past years, most of the high-throughput studies on H5N1-host interactions have focused on the host transcriptomic response, at the cellular or the lung tissue level. These studies pointed out that the dynamics and magnitude of the innate immune response and immune cell infiltration is critical to H5N1 pathogenesis. However, viral-host interactions are multidimensional and advances in technologies are creating new possibilities to systematically measure additional levels of 'omic data (e.g. proteomic, metabolomic, and RNA profiling) at each temporal and spatial scale (from the single cell to the organism) of the host response. Natural host genetic variation represents another dimension of the host response that determines pathogenesis. Systems biology models of H5N1 disease aim at understanding and predicting pathogenesis through integration of these different dimensions by using intensive computational modeling. In this review, we describe the importance of 'omic studies for providing a more comprehensive view of infection and mathematical models that are being developed to integrate these data. This review provides a roadmap for what needs to be done in the future and what computational strategies should be used to build a global model of H5N1 pathogenesis. It is time for systems biology of H5N1 pathogenesis to take center stage as the field moves toward a more comprehensive view of virus-host interactions.

The Aryl-Hydrocarbon Receptor Protein Interaction Network (AHR-PIN) as Identified by Tandem Affinity Purification (TAP) and Mass Spectrometry

The aryl-hydrocarbon receptor (AHR), a ligand activated PAS superfamily transcription factor, mediates most, if not all, of the toxicity induced upon exposure to various dioxins, dibenzofurans, and planar polyhalogenated biphenyls. While AHR-mediated gene regulation plays a central role in the toxic response to dioxin exposure, a comprehensive understanding of AHR biology remains elusive. AHR-mediated signaling starts in the cytoplasm, where the receptor can be found in a complex with the heat shock protein of 90 kDa (Hsp90) and the immunophilin-like protein, aryl-hydrocarbon receptor-interacting protein (AIP). The role these chaperones and other putative interactors of the AHR play in the toxic response is not known. To more comprehensively define the AHR-protein interaction network (AHR-PIN) and identify other potential pathways involved in the toxic response, a proteomic approach was undertaken. Using tandem affinity purification (TAP) and mass spectrometry we have identified several novel protein interactions with the AHR. These interactions physically link the AHR to proteins involved in the immune and cellular stress responses, gene regulation not mediated directly via the traditional AHR:ARNT heterodimer, and mitochondrial function. This new insight into the AHR signaling network identifies possible secondary signaling pathways involved in xenobiotic-induced toxicity.

Identification of deacetylase substrates with the biotin switch approach

The identification of lysine-acetylated proteins and deacetylase substrates has primarily relied on protein immune-affinity techniques with antibodies that recognize acetylated lysine residues (Kac antibodies). While these antibody-based techniques are continuously improving, they can be limited by the narrow and many times unknown epitope specificity of Kac antibodies. An alternative approach is the biotin switch capture of deacetylated proteins. Similar in part to other biotin switch methodologies, this technique relies on the blocking of native lysine residues and removal of the modification of interest in vitro, after which the newly deacetylated proteins can be captured and identified by mass spectrometry (MS). In this chapter, we cover the essential steps of the procedure, highlight key points in the assay to reduce false positive protein identification, and discuss the quantitative MS methods useful for identifying the captured deacetylase substrates. We also discuss potential strategies and future improvements to overcome current limitations of the assay.

Neurogenetics of birdsong

Songbirds are a productive model organism to study the neural basis of auditory-guided vocal motor learning. Like human babies, juvenile songbirds learn many of their vocalizations by imitating an adult conspecific. This process is a product of genetic predispositions and the individual's life experience and has been investigated mainly by neuroanatomical, physiological and behavioral methods. Results have revealed general principles governing vertebrate motor behavior, sensitive periods, sexual dimorphism, social behavior regulation and adult neurogenesis. More recently, the emerging field of birdsong neurogenetics has advanced the way we think about genetic contributions to communication, mechanistically and conceptually.

Solid-phase capture for the detection and relative quantification of S-nitrosoproteins by mass spectrometry

The proteomic analysis of S-nitrosylated protein (SNO-proteins) has long depended on the biotin switch technique (BST), which requires blocking of free thiols, ascorbate-based denitrosylation of SNO-Cys, biotinylation of nascent thiol and avidin-based affinity isolation. A more recent development is resin assisted-capture of SNO-proteins (SNO-RAC), which substitutes thiopropyl Sepharose (TPS) for biotin-avidin, thus reducing the number of steps required for enrichment of S-nitrosylated proteins. In addition, SNO-RAC facilitates on-resin proteolytic digestion following SNO-protein capture, greatly simplifying the purification of peptides containing sites of S-nitrosylation ("SNO-sites"). This resin-based approach has also now been applied to detection of alternative Cys-based modifications, including S-palmitoylation (Acyl-RAC) and S-oxidation (Ox-RAC). Here, we review the important steps to minimize false-positive identification of SNO-proteins, give detailed methods for processing of protein-bound TPS for mass spectrometry (MS) based analysis, and discuss the various quantitative MS methods that are compatible with SNO-RAC. We also discuss strategies to overcome the current limitations surrounding MS-based SNO-site localization in peptides containing more than one potential target Cys residue. This article therefore serves as a starting point and guide for the MS-focused exploration of SNO-proteomes by SNO-RAC.

Convergent differential regulation of parvalbumin in the brains of vocal learners

Spoken language and learned song are complex communication behaviors found in only a few species, including humans and three groups of distantly related birds – songbirds, parrots, and hummingbirds. Despite their large phylogenetic distances, these vocal learners show convergent behaviors and associated brain pathways for vocal communication. However, it is not clear whether this behavioral and anatomical convergence is associated with molecular convergence. Here we used oligo microarrays to screen for genes differentially regulated in brain nuclei necessary for producing learned vocalizations relative to adjacent brain areas that control other behaviors in avian vocal learners versus vocal non-learners. A top candidate gene in our screen was a calcium-binding protein, parvalbumin (PV). In situ hybridization verification revealed that PV was expressed significantly higher throughout the song motor pathway, including brainstem vocal motor neurons relative to the surrounding brain regions of all distantly related avian vocal learners. This differential expression was specific to PV and vocal learners, as it was not found in avian vocal non-learners nor for control genes in learners and non-learners. Similar to the vocal learning birds, higher PV up-regulation was found in the brainstem tongue motor neurons used for speech production in humans relative to a non-human primate, macaques. These results suggest repeated convergent evolution of differential PV up-regulation in the brains of vocal learners separated by more than 65–300 million years from a common ancestor and that the specialized behaviors of learned song and speech may require extra calcium buffering and signaling.