Quantitative Molecular Phenotyping of Gill Remodeling in a Cichlid Fish Responding to Salinity Stress

A two-tiered label-free quantitative (LFQ) proteomics workflow was used to elucidate how salinity affects the molecular phenotype, i.e. proteome, of gills from a cichlid fish, the euryhaline tilapia (Oreochromis mossambicus). The workflow consists of initial global profiling of relative tryptic peptide abundances in treated versus control samples followed by targeted identification (by MS/MS) and quantitation (by chromatographic peak area integration) of validated peptides for each protein of interest. Fresh water acclimated tilapia were independently exposed in separate experiments to acute short-term (34 ppt) and gradual long-term (70 ppt, 90 ppt) salinity stress followed by molecular phenotyping of the gill proteome. The severity of salinity stress can be deduced with high technical reproducibility from the initial global label-free quantitative profiling step alone at both peptide and protein levels. However, an accurate regulation ratio can only be determined by targeted label-free quantitative profiling because not all peptides used for protein identification are also valid for quantitation. Of the three salinity challenges, gradual acclimation to 90 ppt has the most pronounced effect on gill molecular phenotype. Known salinity effects on tilapia gills, including an increase in the size and number of mitochondria-rich ionocytes, activities of specific ion transporters, and induction of specific molecular chaperones are reflected in the regulation of abundances of the corresponding proteins. Moreover, specific protein isoforms that are responsive to environmental salinity change are resolved and it is revealed that salinity effects on the mitochondrial proteome are nonuniform. Furthermore, protein NDRG1 has been identified as a novel key component of molecular phenotype restructuring during salinity-induced gill remodeling. In conclusion, besides confirming known effects of salinity on gills of euryhaline fish, molecular phenotyping reveals novel insight into proteome changes that underlie the remodeling of tilapia gill epithelium in response to environmental salinity change.Euryhaline fish are capable of living in fresh water (FW),¹ brackish water (BW), seawater (SW), and hypersaline water (>SW). They adjust transepithelial ion transport across gill epithelium when challenged by an environmental salinity change (1). Acclimation from hyposmotic (relative to plasma, e.g. FW) to hyperosmotic (relative to plasma, e.g. SW) environments is accompanied by extensive remodeling of gill epithelium, the most prominent feature of which is an increase in the number and size of salt-secretory, mitochondria-rich ionocytes (2). In addition, molecular chaperones and distinct sets of transport proteins are activated when euryhaline fish are challenged by increasing environmental salinity (3–5). A euryhaline fish species in which these physiological responses have been observed is the Mozambique tilapia, Oreochromis mossambicus (6–8). Tilapia have evolved in Africa but have spread to subtropical and tropical freshwater and marine habitats throughout the world as a result of escaping from aquaculture farms and their high environmental adaptability. These cichlids tolerate salinities ranging from fresh water to almost 4× seawater (120 ppt) and they inhabit freshwater and hypersaline desert lakes as well as coastal marine and brackish habitats (9). This high salinity tolerance may have been selected for during tilapia evolution by frequent seasonal droughts and intermittent flooding events in their native African habitat containing salt-rich bedrock and soil (10). Tilapia are highly abundant in the California Salton Sea, which is a large hypersaline desert lake with an average salinity of 50 ppt and seasonal salinity increases up to 100 ppt in some parts (11–13). Thus, studies investigating the mechanisms that enable tilapia to cope with extreme and diverse osmotic stress are of great interest from an ecophysiological perspective and for understanding the basis of their high invasiveness in novel habitats.Moreover, because of their outstanding osmotolerance tilapia are excellent models for studying the mechanisms of body water and electrolyte homeostasis in vertebrates. O. mossambicus is a very close relative of (and readily hybridizes with) the Nile tilapia, Oreochromis nilotics, for which a complete reference proteome is available in major databases, including UniProtKB (14, 15). Therefore, tilapia are well suited for proteomics studies directed at identifying, quantifying, and explaining molecular phenotypes (alterations in the proteome) induced by environmental stress. Because higher-order phenotypes (physiology, morphology, behavior) associated with salinity acclimation are well documented for tilapia, knowledge of the underlying molecular phenotypes will provide insight into the mechanisms that govern salinity acclimation of euryhaline fish (13, 16, 17). The main purpose of this study is to optimize and use a label-free quantitative proteomics (LFQ) workflow for molecular phenotyping of tilapia gill responses to salinity stress.The workflow consists of initial protein identification and global label-free quantitative (LFQ) profiling followed by subsequent targeted LFQ of particular proteins based on quantitatively diagnostic, validated peptide ions. High resolution and high retention-time reproducibility in nano-flow liquid chromatography in combination with fast, high mass accuracy and high resolution mass spectrometers have enabled large-scale LFQ of proteins (18). Both relative and absolute LFQ of proteins are possible (19, 20) and protein quantities can be inferred from either spectral counts or ion currents and chromatographic peak intensity (21, 22). Spectral counting procedures have been used to roughly approximate relative protein quantities in different samples (23). In the present study, the other approach for LFQ, quantitation of ion current intensity, is used for relative quantitation of protein abundances in gill tissue from salinity stressed fish compared with FW handling controls. The quantitative precision of carefully optimized ion current intensity-based LFQ approaches is comparable to that of isotopic label-based quantitation (24, 25). Ion current intensity can be measured as peak height (maximum ion current) or peak area (integral of extracted ion chromatogram) (20–22). Because peak area provides a more accurate measure of peptide (and correspondingly protein) quantity this approach is used in the present study (21, 22).The present study applies this LFQ workflow to identify the specific isoforms of (a) proteins involved in transepithelial ion transport and (b) molecular chaperones that are regulated by environmental salinity in tilapia gills. Such information is very difficult and often impossible to obtain with antibody-based approaches because isoform-specific antibodies for fish proteins are rare and none are available for the tilapia proteins of interest. Therefore, most quantitative analyses of fish proteins by Western blot use antibodies made against a different species (or even a mammalian or other more distantly evolutionarily related homolog) that are not suitable to distinguish individual isoforms (e.g. 3, 26, 27). The present study also investigates whether salinity-induced changes in ionocyte number and size are reflected in abundances of mitochondrial proteins, whether there is disparity in how different mitochondrial proteins are regulated in response to salinity stress, and which mitochondrial proteins are most affected by salinity stress. In addition, the initial global profiling step of the LFQ proteomics workflow described and the deposition of corresponding identification and quantitation data in the public PRIDE repository (28, 29) provides quantitative information on many proteins for which no prior information about effects of salinity on their abundance is available.     

Printor, a Novel TorsinA-interacting Protein Implicated in Dystonia Pathogenesis

Early onset generalized dystonia (DYT1) is an autosomal dominant neurological disorder caused by deletion of a single glutamate residue (torsinA ΔE) in the C-terminal region of the AAA⁺ (ATPases associated with a variety of cellular activities) protein torsinA. The pathogenic mechanism by which torsinA ΔE mutation leads to dystonia remains unknown. Here we report the identification and characterization of a 628-amino acid novel protein, printor, that interacts with torsinA. Printor co-distributes with torsinA in multiple brain regions and co-localizes with torsinA in the endoplasmic reticulum. Interestingly, printor selectively binds to the ATP-free form but not to the ATP-bound form of torsinA, supporting a role for printor as a cofactor rather than a substrate of torsinA. The interaction of printor with torsinA is completely abolished by the dystonia-associated torsinA ΔE mutation. Our findings suggest that printor is a new component of the DYT1 pathogenic pathway and provide a potential molecular target for therapeutic intervention in dystonia.Early onset generalized torsion dystonia (DYT1) is the most common and severe form of hereditary dystonia, a movement disorder characterized by involuntary movements and sustained muscle spasms (1). This autosomal dominant disease has childhood onset and its dystonic symptoms are thought to result from neuronal dysfunction rather than neurodegeneration (2, 3). Most DYT1 cases are caused by deletion of a single glutamate residue at positions 302 or 303 (torsinA ΔE) of the 332-amino acid protein torsinA (4). In addition, a different torsinA mutation that deletes amino acids Phe³²³–Tyr³²⁸ (torsinA Δ323–328) was identified in a single family with dystonia (5), although the pathogenic significance of this torsinA mutation is unclear because these patients contain a concomitant mutation in another dystonia-related protein, ϵ-sarcoglycan (6). Recently, genetic association studies have implicated polymorphisms in the torsinA gene as a genetic risk factor in the development of adult-onset idiopathic dystonia (7, 8).TorsinA contains an N-terminal endoplasmic reticulum (ER)³ signal sequence and a 20-amino acid hydrophobic region followed by a conserved AAA⁺ (ATPases associated with a variety of cellular activities) domain (9, 10). Because members of the AAA⁺ family are known to facilitate conformational changes in target proteins (11, 12), it has been proposed that torsinA may function as a molecular chaperone (13, 14). TorsinA is widely expressed in brain and multiple other tissues (15) and is primarily associated with the ER and nuclear envelope (NE) compartments in cells (16–20). TorsinA is believed to mainly reside in the lumen of the ER and NE (17–19) and has been shown to bind lamina-associated polypeptide 1 (LAP1) (21), lumenal domain-like LAP1 (LULL1) (21), and nesprins (22). In addition, recent evidence indicates that a significant pool of torsinA exhibits a topology in which the AAA⁺ domain faces the cytoplasm (20). In support of this topology, torsinA is found in the cytoplasm, neuronal processes, and synaptic terminals (2, 3, 15, 23–26) and has been shown to bind cytosolic proteins snapin (27) and kinesin light chain 1 (20). TorsinA has been proposed to play a role in several cellular processes, including dopaminergic neurotransmission (28–31), NE organization and dynamics (17, 22, 32), and protein trafficking (27, 33). However, the precise biological function of torsinA and its regulation remain unknown.To gain insights into torsinA function, we performed yeast two-hybrid screens to search for torsinA-interacting proteins in the brain. We report here the isolation and characterization of a novel protein named printor (protein interactor of torsinA) that interacts selectively with wild-type (WT) torsinA but not the dystonia-associated torsinA ΔE mutant. Our data suggest that printor may serve as a cofactor of torsinA and provide a new molecular target for understanding and treating dystonia.     

Accurate Protein Complex Retrieval by Affinity Enrichment Mass Spectrometry (AE-MS) Rather than Affinity Purification Mass Spectrometry (AP-MS)

Protein–protein interactions are fundamental to the understanding of biological processes. Affinity purification coupled to mass spectrometry (AP-MS) is one of the most promising methods for their investigation. Previously, complexes were purified as much as possible, frequently followed by identification of individual gel bands. However, todays mass spectrometers are highly sensitive, and powerful quantitative proteomics strategies are available to distinguish true interactors from background binders. Here we describe a high performance affinity enrichment-mass spectrometry method for investigating protein–protein interactions, in which no attempt at purifying complexes to homogeneity is made. Instead, we developed analysis methods that take advantage of specific enrichment of interactors in the context of a large amount of unspecific background binders. We perform single-step affinity enrichment of endogenously expressed GFP-tagged proteins and their interactors in budding yeast, followed by single-run, intensity-based label-free quantitative LC-MS/MS analysis. Each pull-down contains around 2000 background binders, which are reinterpreted from troubling contaminants to crucial elements in a novel data analysis strategy. First the background serves for accurate normalization. Second, interacting proteins are not identified by comparison to a single untagged control strain, but instead to the other tagged strains. Third, potential interactors are further validated by their intensity profiles across all samples. We demonstrate the power of our AE-MS method using several well-known and challenging yeast complexes of various abundances. AE-MS is not only highly efficient and robust, but also cost effective, broadly applicable, and can be performed in any laboratory with access to high-resolution mass spectrometers.Protein–protein interactions are key to protein-mediated biological processes and influence all aspects of life. Therefore, considerable efforts have been dedicated to the mapping of protein–protein interactions. A classical experimental approach consists of co-immunoprecipitation of protein complexes combined with SDS-PAGE followed by Western blotting to identify complex members. More recently, high-throughput techniques have been introduced; among these affinity purification-mass spectrometry (AP-MS)¹ (1–3) and the yeast two-hybrid (Y2H) approach (4–6) are the most prominent. AP-MS, in particular, has great potential for detecting functional interactions under near-physiological conditions, and has already been employed for interactome mapping in several organisms (7–15). Various AP-MS approaches have evolved over time, that differ in expression, tagging, and affinity purification of the bait protein; fractionation, LC-MS measurement, and quantification of the sample; and in data analysis. Recent progress in the AP-MS field has been driven by two factors: A new generation of mass spectrometers (16) providing higher sequencing speed, sensitivity, and mass accuracy, and the development of quantitative MS strategies.In the early days of AP-MS, tagged bait proteins were mostly overexpressed, enhancing their recovery in the pull-down. However, overexpression comes at the cost of obscuring the true situation in the cell, potentially leading to the detection of false interactions (17). Today, increased MS instrument power helps in the detection of bait proteins and interactors expressed at endogenous levels, augmenting the chances to detect functional interactions. In some simple organisms like yeast, genes of interest can directly be tagged in their genetic loci and expressed under their native promoter. In higher organisms, tagging proteins in their endogenous locus is more challenging, but also for mammalian cells, methods for close to endogenous expression are available. For instance, in controlled inducible expression systems, the concentration of the tagged bait protein can be titrated to close to endogenous levels (18). A very powerful approach is BAC transgenomics (19), as used in our QUBIC protocol (20), where a bacterial artificial chromosome (BAC) containing a tagged version of the gene of interest including all regulatory sequences and the natural promoter is stably transfected into a host cell line.The affinity purification step has also been subject to substantial changes over time. Previously, AP has been combined with nonquantitative MS as the readout, meaning all proteins identified by MS were considered potential interactors. Therefore, to reduce co-purifying “contaminants,” stringent two-step AP protocols using dual affinity tags like the TAP-tag (21) had to be employed. However, such stringent and multistep protocols can result in the loss of weak or transient interactors (3), whereas laborious and partially subjective filtering still has to be applied to clean up the list of identified proteins. The introduction of quantitative mass spectrometry (22–25) to the interactomics field about ten years ago was a paradigm shift, as it offered a proper way of dealing with unspecific binding and true interactors could be directly distinguished from background binders (26, 27). Importantly, quantification enables the detection of true interactors even under low-stringent conditions (28). In turn, this allowed the return to single-step AP protocols, which are milder and faster, and hence more suitable for detecting weak and transient interactors.Despite these advances, nonquantitative methods—often in combination with the TAP-tagging approach—are still popular and widely used, presumably because of reagent expenses and labeling protocols used in label-based approaches. However, there are ways to determine relative protein abundances in a label-free format. A simple, semiquantitative label-free way to estimate protein abundance is spectral counting (29). Another relative label-free quantification strategy is based on peptide intensities (30). In recent years high resolution MS has become much more widely accessible and there has been great progress in intensity-based label-free quantification (LFQ) approaches. Together with development of sophisticated LFQ algorithms, this has boosted obtainable accuracy. Intensity-based LFQ now offers a viable and cost-effective alternative to label-based methods in most applications (31). The potential of intensity-based LFQ approaches as tools for investigating protein–protein interactions has already been demonstrated by us (20, 32, 33) and others (34, 35). We have further refined intensity-based LFQ in the context of the MaxQuant framework (36) using sophisticated normalization algorithms, achieving excellent accuracy and robustness of the measured “MaxLFQ” intensities (37).Another important advance in AP-MS, again enabled by increased MS instrument power, was the development of single-shot LC-MS methods with comprehensive coverage. Instead of extensive fractionation, which was previously needed to reduce sample complexity, nowadays even entire model proteomes can be measured in single LC-MS runs (38). The protein mixture resulting from pull-downs is naturally of lower complexity compared with the entire proteome. Therefore, modern MS obviates the need for gel-based (or other) fractionation and samples can be analyzed in single runs. Apart from avoiding selection of gel bands by visual examination, this has many advantages, including decreased sample preparation and measurement time, increased sensitivity, and higher quantitative accuracy in a label-free format.In this work, we build on many of the recent advances in the field to establish a state of the art LFQ AE-MS method. Based on our previous QUBIC pipeline (20), we developed an approach for investigating protein–protein interactions, which we exemplify in Saccharomyces cerevisiae. We extended the data analysis pipeline to extract the wealth of information contained in the LFQ data, by establishing a novel concept that specifically makes use of the signature of background binders instead of eliminating them from the data set. The large amount of unspecific binders detected in our experiments rendered the use of a classic untagged control strain unnecessary and enabled comparing to a control group consisting of many unrelated pull-downs instead. Our protocol is generic, practical, and fast, uses low input amounts, and identifies interactors with high confidence. We propose that single-step pull-down experiments, especially when coupled to high-sensitivity MS, should now be regarded as affinity enrichment rather than affinity purification methods.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Online Peptide Fractionation Using a Multiphasic Microfluidic Liquid Chromatography Chip Improves Reproducibility and Detection Limits for Quantitation in Discovery and Targeted Proteomics

Comprehensive proteomic profiling of biological specimens usually requires multidimensional chromatographic peptide fractionation prior to mass spectrometry. However, this approach can suffer from poor reproducibility because of the lack of standardization and automation of the entire workflow, thus compromising performance of quantitative proteomic investigations. To address these variables we developed an online peptide fractionation system comprising a multiphasic liquid chromatography (LC) chip that integrates reversed phase and strong cation exchange chromatography upstream of the mass spectrometer (MS). We showed superiority of this system for standardizing discovery and targeted proteomic workflows using cancer cell lysates and nondepleted human plasma. Five-step multiphase chip LC MS/MS acquisition showed clear advantages over analyses of unfractionated samples by identifying more peptides, consuming less sample and often improving the lower limits of quantitation, all in highly reproducible, automated, online configuration. We further showed that multiphase chip LC fractionation provided a facile means to detect many N- and C-terminal peptides (including acetylated N terminus) that are challenging to identify in complex tryptic peptide matrices because of less favorable ionization characteristics. Given as much as 95% of peptides were detected in only a single salt fraction from cell lysates we exploited this high reproducibility and coupled it with multiple reaction monitoring on a high-resolution MS instrument (MRM-HR). This approach increased target analyte peak area and improved lower limits of quantitation without negatively influencing variance or bias. Further, we showed a strategy to use multiphase LC chip fractionation LC-MS/MS for ion library generation to integrate with SWATH^TM data-independent acquisition quantitative workflows. All MS data are available via ProteomeXchange with identifier PXD001464.Mass spectrometry based proteomic quantitation is an essential technique used for contemporary, integrative biological studies. Whether used in discovery experiments or for targeted biomarker applications, quantitative proteomic studies require high reproducibility at many levels. It requires reproducible run-to-run peptide detection, reproducible peptide quantitation, reproducible depth of proteome coverage, and ideally, a high degree of cross-laboratory analytical reproducibility. Mass spectrometry centered proteomics has evolved steadily over the past decade, now mature enough to derive extensive draft maps of the human proteome (1, 2). Nonetheless, a key requirement yet to be realized is to ensure that quantitative proteomics can be carried out in a timely manner while satisfying the aforementioned challenges associated with reproducibility. This is especially important for recent developments using data independent MS quantitation and multiple reaction monitoring on high-resolution MS (MRM-HR)¹ as they are both highly dependent on LC peptide retention time reproducibility and precursor detectability, while attempting to maximize proteome coverage (3). Strategies usually employed to increase the depth of proteome coverage utilize various sample fractionation methods including gel-based separation, affinity enrichment or depletion, protein or peptide chemical modification-based enrichment, and various peptide chromatography methods, particularly ion exchange chromatography (4–10). In comparison to an unfractionated “naive” sample, the trade-off in using these enrichments/fractionation approaches are higher risk of sample losses, introduction of undesired chemical modifications (e.g. oxidation, deamidation, N-terminal lactam formation), and the potential for result skewing and bias, as well as numerous time and human resources required to perform the sample preparation tasks. Online-coupled approaches aim to minimize those risks and address resource constraints. A widely practiced example of the benefits of online sample fractionation has been the decade long use of combining strong cation exchange chromatography (SCX) with C18 reversed-phase (RP) for peptide fractionation (known as MudPIT – multidimensional protein identification technology), where SCX and RP is performed under the same buffer conditions and the SCX elution performed with volatile organic cations compatible with reversed phase separation (11). This approach greatly increases analyte detection while avoiding sample handling losses. The MudPIT approach has been widely used for discovery proteomics (12–14), and we have previously shown that multiphasic separations also have utility for targeted proteomics when configured for selected reaction monitoring MS (SRM-MS). We showed substantial advantages of MudPIT-SRM-MS with reduced ion suppression, increased peak areas and lower limits of detection (LLOD) compared with conventional RP-SRM-MS (15).To improve the reproducibility of proteomic workflows, increase throughput and minimize sample loss, numerous microfluidic devices have been developed and integrated for proteomic applications (16, 17). These devices can broadly be classified into two groups: (1) microfluidic chips for peptide separation (18–25) and; (2) proteome reactors that combine enzymatic processing with peptide based fractionation (26–30). Because of the small dimension of these devices, they are readily able to integrate into nanoLC workflows. Various applications have been described including increasing proteome coverage (22, 27, 28) and targeting of phosphopeptides (24, 31, 32), glycopeptides and released glycans (29, 33, 34).In this work, we set out to take advantage of the benefits of multiphasic peptide separations and address the reproducibility needs required for high-throughput comparative proteomics using a variety of workflows. We integrated a multiphasic SCX and RP column in a “plug-and-play” microfluidic chip format for online fractionation, eliminating the need for users to make minimal dead volume connections between traps and columns. We show the flexibility of this format to provide robust peptide separation and reproducibility using conventional and topical mass spectrometry workflows. This was undertaken by coupling the multiphase liquid chromatography (LC) chip to a fast scanning Q-ToF mass spectrometer for data dependent MS/MS, data independent MS (SWATH) and for targeted proteomics using MRM-HR, showing clear advantages for repeatable analyses compared with conventional proteomic workflows.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

PTIP Regulates 53BP1 and SMC1 at the DNA Damage Sites

Although PTIP is implicated in the DNA damage response, through interactions with 53BP1, the function of PTIP in the DNA damage response remain elusive. Here, we show that RNF8 controls DNA damage-induced nuclear foci formation of PTIP, which in turn regulates 53BP1 localization to the DNA damage sites. In addition, SMC1, a substrate of ATM, could not be phosphorylated at the DNA damage sites in the absence of PTIP. The PTIP-dependent pathway is important for DNA double strand breaks repair and DNA damage-induced intra-S phase checkpoint activation. Taken together, these results suggest that the role of PTIP in the DNA damage response is downstream of RNF8 and upstream of 53BP1. Thus, PTIP regulates 53BP1-dependent signaling pathway following DNA damage.The DNA damage response pathways are signal transduction pathways with DNA damage sensors, mediators, and effectors, which are essential for maintaining genomic stability (1–3). Following DNA double strand breaks, histone H2AX at the DNA damage sites is rapidly phosphorylated by ATM/ATR/DNAPK (4–10), a family homologous to phosphoinositide 3-kinases (11, 12). Subsequently, phospho-H2AX (γH2AX) provides the platform for accumulation of a larger group of DNA damage response factors, such as MDC1, BRCA1, 53BP1, and the MRE11·RAD50·NBS1 complex (13, 14), at the DNA damage sites. Translocalization of these proteins to the DNA double strand breaks (DSBs)³ facilitates DNA damage checkpoint activation and enhances the efficiency of DNA damage repair (14, 15).Recently, PTIP (Pax2 transactivation domain-interacting protein, or Paxip) has been identified as a DNA damage response protein and is required for cell survival when exposed to ionizing radiation (IR) (1, 16–18). PTIP is a 1069-amino acid nuclear protein and has been originally identified in a yeast two-hybrid screening as a partner of Pax2 (19). Genetic deletion of the PTIP gene in mice leads to early embryonic lethality at embryonic day 8.5, suggesting that PTIP is essential for early embryonic development (20). Structurally, PTIP contains six tandem BRCT (BRCA1 carboxyl-terminal) domains (16–18, 21). The BRCT domain is a phospho-group binding domain that mediates protein-protein interactions (17, 22, 23). Interestingly, the BRCT domain has been found in a large number of proteins involved in the cellular response to DNA damages, such as BRCA1, MDC1, and 53BP1 (7, 24–29). Like other BRCT domain-containing proteins, upon exposure to IR, PTIP forms nuclear foci at the DSBs, which is dependent on its BRCT domains (16–18). By protein affinity purification, PTIP has been found in two large complexes. One includes the histone H3K4 methyltransferase ALR and its associated cofactors, the other contains DNA damage response proteins, including 53BP1 and SMC1 (30, 31). Further experiments have revealed that DNA damage enhances the interaction between PTIP and 53BP1 (18, 31).To elucidate the DNA damage response pathways, we have examined the upstream and downstream partners of PTIP. Here, we report that PTIP is downstream of RNF8 and upstream of 53BP1 in response to DNA damage. Moreover, PTIP and 53BP1 are required for the phospho-ATM association with the chromatin, which phosphorylates SMC1 at the DSBs. This PTIP-dependent pathway is involved in DSBs repair.     

Refined Preparation and Use of Anti-diglycine Remnant (K-ε-GG) Antibody Enables Routine Quantification of 10,000s of Ubiquitination Sites in Single Proteomics Experiments

Detection of endogenous ubiquitination sites by mass spectrometry has dramatically improved with the commercialization of anti-di-glycine remnant (K-ε-GG) antibodies. Here, we describe a number of improvements to the K-ε-GG enrichment workflow, including optimized antibody and peptide input requirements, antibody cross-linking, and improved off-line fractionation prior to enrichment. This refined and practical workflow enables routine identification and quantification of ∼20,000 distinct endogenous ubiquitination sites in a single SILAC experiment using moderate amounts of protein input.The commercialization of antibodies that recognize lysine residues modified with a di-glycine remnant (K-ε-GG)¹ has significantly transformed the detection of endogenous protein ubiquitination sites by mass spectrometry (1–5). Prior to the development of these highly specific reagents, proteomics experiments were limited to identification of up to only several hundred ubiquitination sites, which severely limited the scope of global ubiquitination studies (6). Recent proteomic studies employing anti-K-ε-GG antibodies have enhanced our understanding of ubiquitin biology through the identification of thousands of ubiquitination sites and the analysis of the change in relative abundance of these sites after chemical or biological perturbation (1–3, 5, 7). Use of stable isotope labeling by amino acids in cell culture (SILAC) for quantification has enabled researchers to better understand the extent of ubiquitin regulation upon proteasome inhibition and precisely identify those protein classes, such as newly synthesized proteins or chromatin-related proteins, that see overt changes in their ubiquitination levels upon drug treatment (2, 3, 5). Emanuel et al. (1) have combined genetic and proteomics assays implementing the anti-K-ε-GG antibody to identify hundreds of known and putative Cullin-RING ligase substrates, which has clearly demonstrated the extensive role of Cullin-RING ligase ubiquitination on cellular protein regulation.Despite the successes recently achieved with the use of the anti-K-ε-GG antibody, increased sample input (up to ∼35 mg) and/or the completion of numerous experimental replicates have been necessary to achieve large numbers of K-ε-GG sites (>5,000) in a single SILAC-based experiment (1–3, 5). For example, it has been recently shown that detection of more than 20,000 unique ubiquitination sites is possible from the analysis of five different murine tissues (8). However, as the authors indicate, only a few thousands sites are detected in any single analysis of an individual tissue sample (8). It is recognized that there is need for further improvements in global ubiquitin technology to increase the depth-of-coverage attainable in quantitative proteomic experiments using moderate amounts of protein input (9). Through systematic study and optimization of key pre-analytical variables in the preparation and use of the anti-K-ε-GG antibody as well as the proteomic workflow, we have now achieved, for the first time, routine quantification of ∼20,000 nonredundant K-ε-GG sites in a single SILAC triple encoded experiment starting with 5 mg of protein per SILAC channel. This represents a 10-fold improvement over our previously published method (3).     

Enhanced Prediction of Src Homology 2 (SH2) Domain Binding Potentials Using a Fluorescence Polarization-derived c-Met,c-Kit,ErbB, and Androgen Receptor Interactome

Many human diseases are associated with aberrant regulation of phosphoprotein signaling networks. Src homology 2 (SH2) domains represent the major class of protein domains in metazoans that interact with proteins phosphorylated on the amino acid residue tyrosine. Although current SH2 domain prediction algorithms perform well at predicting the sequences of phosphorylated peptides that are likely to result in the highest possible interaction affinity in the context of random peptide library screens, these algorithms do poorly at predicting the interaction potential of SH2 domains with physiologically derived protein sequences. We employed a high throughput interaction assay system to empirically determine the affinity between 93 human SH2 domains and phosphopeptides abstracted from several receptor tyrosine kinases and signaling proteins. The resulting interaction experiments revealed over 1000 novel peptide-protein interactions and provided a glimpse into the common and specific interaction potentials of c-Met, c-Kit, GAB1, and the human androgen receptor. We used these data to build a permutation-based logistic regression classifier that performed considerably better than existing algorithms for predicting the interaction potential of several SH2 domains.Src homology 2 protein domains (SH2)¹ are modular self-folding entities of about 100 amino acids that bind to tyrosine-phosphorylated peptide sequences contained within target proteins. The SH2 domain (1–3) was originally described nearly 20 years ago as an N-terminal region of the FES protein kinase that was not required for kinase activity but was important for its regulation. More recent studies have demonstrated that SH2 domains exist in many signaling molecules, including PLCγ1, Ras GAP, c-Src, and PI3KR. SH2 domains have been shown to enable the interaction of these signaling proteins with growth factor receptors such as FGFR1, EGFR, c-Met, and PDGFR in a phosphospecific manner (4–9). Subsequently, random peptide library screening approaches were used to define sequence motifs that resulted in the highest affinity interactions within particular SH2 domain classes (10, 11). For example, peptide sequences containing the pYEEI, pYXN, and pYMXM motifs were described to result in the highest affinity interactions with the SH2 domains from c-Src, Grb2, and the PI3KR SH2 domains, respectively. Data from such experiments have been used to generate predictions regarding the likelihood that any particular peptide sequence will interact with any particular SH2 domain (12–14).Unfortunately, the predictive performance of these algorithms has not been thoroughly empirically tested or optimized for biologically derived peptide sequences. We and others reported the first comprehensive cloning, expression, and functional analysis of human genome-encoded SH2 domains using a protein microarray-based interaction analysis approach (15–17). Similarly, peptide arrays have been used to query the interaction potential of SH2 domains with biologically derived peptide sequences in a semi-quantitative manner (18). These studies demonstrated that most biologically derived peptide sequences contained within RTKs and signaling proteins do not represent best fit sequence motifs and interact at a much lower affinity than with the optimal sequence motifs identified previously from random peptide libraries. Studies with biologically derived peptides indicated that context nonpermissive amino acids often contribute as much predictive information regarding interaction selectivity as positively contributing amino acids (19). Taken together, these results suggest that the collection of large quantitative protein interaction datasets between SH2 domains and biologically derived peptide sequences might be informative for building better algorithms that predict bona fide SH2 domain interaction sites within human protein sequences.Although protein microarrays enabled the first systems-level glimpse at SH2 domain selectivity (15, 17), they had several limitations that resulted in reduced ability to identify low affinity interactions in comparison with solution phase methods (20). We therefore designed a high throughput fluorescence polarization approach that allowed for lower affinity interactions to be defined between SH2 domains and phosphopeptides of the ErbB family of receptor tyrosine kinases (RTKs) than was possible with protein microarrays (20).RTKs are vital mediators of signal transduction in multicellular organisms. RTKs typically function as transmembrane receptors that contain a tyrosine kinase and other motifs that enable interaction with other intracellular proteins. Human cells often express many different RTK proteins from the set of 57 RTK genes encoded by the human genome (21). These RTKs may be activated in different combinations to transduce common and specific downstream signals (22). For a recent review of the complexity of RTK signaling networks, see Ref. 23. Following activation, RTKs are phosphorylated on several intracellular tyrosine residues that serve as recruitment sites for SH2 domains (15–18, 20). Activation of RTK signaling networks may cause changes in cellular motility, proliferation, survival, and cytoskeletal arrangement. Definition of their signaling capacity represents an important and unsolved problem in cell biology. Although most studies to date have focused on the role of singular RTKs in cancer progression, co-activation of RTKs derived from several unique RTK genes has recently emerged as an important driver of cancer progression (24–27). Co-activation of modules of RTKs may provide robustness against therapies designed to inhibit a single RTK (25).Herein, we profiled the interaction potential of two RTKs and two signaling proteins and compared them with the recruitment potential of the ErbB family that we have previously profiled (28). The ErbB family, c-Met, and c-Kit RTKs have been shown to drive the progression of many cancer types, including breast, head and neck, lung (29), gastrointestinal, and stomach cancers (30). Downstream adaptor proteins often augment the signaling potential of RTKs by acting as scaffolds for recruitment of many additional proteins (31–33). Therefore, we also included peptides in our study derived from the Gab1 adaptor protein, which is critical for mediating signaling networks downstream of c-Met and potentially other RTKs (34).Finally, alternative oncogenic signaling networks may have points of cross-talk with tyrosine kinase signaling networks. Steroid hormone receptors such as the androgen receptor (AR) have been shown to associate with RTKs such as EGFR (35), to be substrates of tyrosine kinases (36, 37), and to drive the progression of prostate cancer (36). We therefore queried the interaction potential of phosphopeptides derived from AR with a set of 93 of the 120 SH2 domains encoded in the human genome. We subsequently used this interaction dataset to develop a permutation-based logistic regression classifier (PEBL) for predicting the interaction potential of SH2 domains and biologically derived phosphotyrosine-containing peptides.     

Broad Coverage Identification of Multiple Proteolytic Cleavage Site Sequences in Complex High Molecular Weight Proteins Using Quantitative Proteomics as a Complement to Edman Sequencing

Proteolytic processing modifies the pleiotropic functions of many large, complex, and modular proteins and can generate cleavage products with new biological activity. The identification of exact proteolytic cleavage sites in the extracellular matrix laminins, fibronectin, and other extracellular matrix proteins is not only important for understanding protein turnover but is needed for the identification of new bioactive cleavage products. Several such products have recently been recognized that are suggested to play important cellular regulatory roles in processes, including angiogenesis. However, identifying multiple cleavage sites in extracellular matrix proteins and other large proteins is challenging as N-terminal Edman sequencing of multiple and often closely spaced cleavage fragments on SDS-PAGE gels is difficult, thus limiting throughput and coverage. We developed a new liquid chromatography-mass spectrometry approach we call amino-terminal oriented mass spectrometry of substrates (ATOMS) for the N-terminal identification of protein cleavage fragments in solution. ATOMS utilizes efficient and low cost dimethylation isotopic labeling of original N-terminal and proteolytically generated N termini of protein cleavage fragments followed by quantitative tandem mass spectrometry analysis. Being a peptide-centric approach, ATOMS is not dependent on the SDS-PAGE resolution limits for protein fragments of similar mass. We demonstrate that ATOMS reliably identifies multiple proteolytic sites per reaction in complex proteins. Fifty-five neutrophil elastase cleavage sites were identified in laminin-1 and fibronectin-1 with 34 more identified by matrix metalloproteinase cleavage. Hence, our degradomics approach offers a complimentary alternative to Edman sequencing with broad applicability in identifying N termini such as cleavage sites in complex high molecular weight extracellular matrix proteins after in vitro cleavage assays. ATOMS can therefore be useful in identifying new cleavage products of extracellular matrix proteins cleaved by proteases in pathology for bioactivity screening.Recently, considerable efforts have been deployed to develop high throughput proteomic screens to identify protease substrates in complex biological samples (1–8). Validation of substrates identified by these approaches or identification of cleavage sites by in vitro incubation of candidate substrates with the protease of interest is generally performed by SDS-PAGE analysis and Edman degradation and sequencing. However, the complexity of large modular proteins renders Edman sequencing of proteolytic fragments difficult to apply because each of the numerous proteolytic fragments should be analyzed separately, and high coverage of cleavage sites is rarely attained (9). Cleavage site identification after protein degradation is also very difficult for small peptide products less than 4 kDa. Consequently, the precise cleavage sites in complex extracellular matrix proteins such as laminin and fibronectin by important tissue and inflammatory cell proteases such as the matrix metalloproteinases (MMPs)1 and neutrophil elastase are mostly unknown.These limitations of Edman sequencing are problematic in the study of tissue remodeling and proteolysis in pathology. Neutrophil elastase and several MMPs such as MMP2, MMP8, and MMP9 play key roles in inflammation (10, 11), tissue healing (12, 13), and carcinogenesis (14, 15) and are well known for degrading extracellular matrix proteins (16). More recently, signaling functions for MMPs are increasingly recognized as one of their most important roles by the precise processing of cytokines or their binding proteins (17). In addition, several important examples are now known of cryptic binding sites being exposed after precise protein cleavage or new proteins termed neoproteins (18) being released upon limited cleavage of extracellular matrix proteins and having completely different functions compared with their parent molecule, including several with importance in angiogenesis (19–25). Many such sites or neoproteins are generated by inflammatory proteases or proteases of the coagulation and fibrinolysis systems (24, 25), and this is a burgeoning field of discovery that is often hampered by difficulties in their N-terminal sequencing.In light of this limitation, we developed, validated, and used a new method for targeted and simultaneous N-terminal sequencing of one or a small number of protein N termini or cleavage products we call amino-terminal oriented mass spectrometry of substrates (ATOMS). We applied ATOMS for the analysis of cleavage sites generated in laminin-1 and fibronectin-1 by neutrophil elastase and neutrophil and tissue MMPs. Laminin-1 (LM-111), a trimeric glycoprotein composed of the α1, β1, and γ1 chains, is ubiquitously expressed in epithelium and endothelium. Proteolytic processing of laminins greatly affects cellular behavior and is also implicated in cancer cell migration (20, 26–29). Another important extracellular matrix protein is plasma fibronectin (also known as fibronectin isoform 1) and its cellular isoforms, which are homodimers linked by a disulfide bridge at the C terminus (30) that are important for cell adhesion and intracellular signaling (31–34). Fibronectin is susceptible to proteolysis (35, 36), which affects its biological functions (37–39). However, the cleavage sites within these two molecules by inflammatory MMPs and neutrophil elastase are largely unknown. Here we identified a total of 55 neutrophil elastase cleavage sites in LM-111 and fibronectin-1 and 34 MMP cleavage sites, demonstrating the capacity of ATOMS to identify multiple N-terminal sequences in solution. ATOMS also outperformed N-terminal Edman sequencing with 50% more cleavage sites identified by ATOMS, representing a significant advance in N-terminal sequencing technology. The utility of the method is broadly applicable for the analysis of multiple cleavages in other very large molecules and so offers great potential to accurately identify and rapidly sequence multiple cryptic bioactive protein fragments liberated following proteolytic processing.     

Rapamycin Rescues TDP-43 Mislocalization and the Associated Low Molecular Mass Neurofilament Instability

TDP-43 is a nuclear protein involved in exon skipping and alternative splicing. Recently, TDP-43 has been identified as the pathological signature protein in frontotemporal lobar degeneration with ubiquitin-positive inclusions and in amyotrophic lateral sclerosis. In addition, TDP-43-positive inclusions are present in Parkinson disease, dementia with Lewy bodies, and 30% of Alzheimer disease cases. Pathological TDP-43 is redistributed from the nucleus to the cytoplasm, where it accumulates. An ∼25-kDa C-terminal fragment of TDP-43 accumulates in affected brain regions, suggesting that it may be involved in the disease pathogenesis. Here, we show that overexpression of the 25-kDa C-terminal fragment is sufficient to cause the mislocalization and cytoplasmic accumulation of endogenous full-length TDP-43 in two different cell lines, thus recapitulating a key biochemical characteristic of TDP-43 proteinopathies. We also found that TDP-43 mislocalization is associated with a reduction in the low molecular mass neurofilament mRNA levels. Notably, we show that the autophagic system plays a role in TDP-43 metabolism. Specifically, we found that autophagy inhibition increases the accumulation of the C-terminal fragments of TDP-43, whereas inhibition of mTOR, a key protein kinase involved in autophagy regulation, reduces the 25-kDa C-terminal fragment accumulation and restores TDP-43 localization. Our results suggest that autophagy induction may be a valid therapeutic target for TDP-43 proteinopathies.TDP-43 (transactive response DNA-binding protein 43) is a conserved and ubiquitously expressed nuclear protein with a theoretical molecular mass of ∼44 kDa. It is encoded by the TARDBP gene on chromosome 1, which is made of six exons that can be alternatively spliced to yield 11 different isoforms, with the mRNA encoding TDP-43 being the major species (1). Functionally, TDP-43 appears to be involved in exon skipping and alternative splicing (2, 3), and it has also been shown to link different types of nuclear bodies (4). Structural studies have confirmed the presence of two RNA recognition motifs (RRM1 and RRM2) and a glycine-rich C-terminal tail, which is thought to mediate protein-protein interaction (5).Recently, TDP-43 has been shown to be the major pathological protein in a wide range of disorders referred to as TDP-43 proteinopathies (6–8). These include frontotemporal lobar degeneration with ubiquitin-positive inclusions (FTLD-U),² motor neuron disease, and amyotrophic lateral sclerosis (ALS). These last two disorders have been directly linked to mutations in TDP-43 (9, 10). In addition, TDP-43-positive inclusions are present in Parkinson disease, dementia with Lewy bodies, and 30% of Alzheimer disease cases (11–14). Sporadic and familial forms of FTLD-U and ALS are characterized by cytoplasmic accumulation of insoluble, hyperphosphorylated, ubiquitinated, and proteolytically cleaved C-terminal fragments in affected brain and spinal cord regions. The cytoplasmic accumulation of TDP-43 is associated with a depletion of nuclear TDP-43 (8, 15–21). These data suggest that some of these TDP-43 proteinopathies may share common mechanisms of pathogenesis.FTLD-U is caused by loss-of-function mutations in the progranulin gene, which lead, by an unknown mechanism, to the accumulation of cytoplasmic TDP-43 inclusions (22, 23). Notably, the TDP-43 inclusions in the ALS and FTLD-U brains are enriched with TDP-43 C-terminal fragments (8, 19). It has been suggested that the C-terminal fragments can be obtained by caspase-dependent cleavage of the full-length protein (24). However, it remains to be established if these fragments play a role in the disease pathogenesis.TDP-43 proteinopathies are characterized by the accumulation of abnormally modified TDP-43, suggesting that dysfunction in the intracellular quality control systems (ubiquitin-proteasome system and the autophagy-lysosome system) may be involved in the disease pathogenesis. The autophagic system is a conserved intracellular system designed for the degradation of long-lived proteins and organelles in lysosomes (25, 26). Three types of autophagy have been described: macroautophagy, microautophagy, and chaperon-mediated autophagy. Whereas macroautophagy and microautophagy involve the “in bulk” degradation of regions of the cytosol (27, 28), chaperon-mediated autophagy is a more selective pathway, and only proteins with a lysosomal targeting sequence are degraded (29). Cumulative evidence has suggested that an age-dependent decrease in the autophagy-lysosome system may account for the accumulation of abnormal proteins during aging (30, 31).Macroautophagy is induced when an isolation membrane is formed surrounding cytosolic components, forming an autophagic vacuole, which will eventually fuse with lysosomes for protein/organelle degradation. Induction of the isolation membrane is negatively regulated by mTOR (mammalian target of rapamycin) (32). It has been shown that increasing autophagy activation by mTOR inhibitors has beneficial effects in neurodegeneration (33–35).     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.     

Multipattern Consensus Regions in Multiple Aligned Protein Sequences and Their Segmentation

Decomposing a biological sequence into its functional regions is an important prerequisite to understand the molecule. Using the multiple alignments of the sequences, we evaluate a segmentation based on the type of statistical variation pattern from each of the aligned sites. To describe such a more general pattern, we introduce multipattern consensus regions as segmented regions based on conserved as well as interdependent patterns. Thus the proposed consensus region considers patterns that are statistically significant and extends a local neighborhood. To show its relevance in protein sequence analysis, a cancer suppressor gene called p53 is examined. The results show significant associations between the detected regions and tendency of mutations, location on the 3D structure, and cancer hereditable factors that can be inferred from human twin studies.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]