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]     

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]     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[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]     

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]     

Question Processing and Clustering in INDOC: A Biomedical Question Answering System

The exponential growth in the volume of publications in the biomedical domain has made it impossible for an individual to keep pace with the advances. Even though evidence-based medicine has gained wide acceptance, the physicians are unable to access the relevant information in the required time, leaving most of the questions unanswered. This accentuates the need for fast and accurate biomedical question answering systems. In this paper we introduce INDOC—a biomedical question answering system based on novel ideas of indexing and extracting the answer to the questions posed. INDOC displays the results in clusters to help the user arrive the most relevant set of documents quickly. Evaluation was done against the standard OHSUMED test collection. Our system achieves high accuracy and minimizes user effort.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24]     

A Pipeline for Determining Protein–Protein Interactions and Proximities in the Cellular Milieu

It remains extraordinarily challenging to elucidate endogenous protein-protein interactions and proximities within the cellular milieu. The dynamic nature and the large range of affinities of these interactions augment the difficulty of this undertaking. Among the most useful tools for extracting such information are those based on affinity capture of target bait proteins in combination with mass spectrometric readout of the co-isolated species. Although highly enabling, the utility of affinity-based methods is generally limited by difficulties in distinguishing specific from nonspecific interactors, preserving and isolating all unique interactions including those that are weak, transient, or rapidly exchanging, and differentiating proximal interactions from those that are more distal. Here, we have devised and optimized a set of methods to address these challenges. The resulting pipeline involves flash-freezing cells in liquid nitrogen to preserve the cellular environment at the moment of freezing; cryomilling to fracture the frozen cells into intact micron chunks to allow for rapid access of a chemical reagent and to stabilize the intact endogenous subcellular assemblies and interactors upon thawing; and utilizing the high reactivity of glutaraldehyde to achieve sufficiently rapid stabilization at low temperatures to preserve native cellular interactions. In the course of this work, we determined that relatively low molar ratios of glutaraldehyde to reactive amines within the cellular milieu were sufficient to preserve even labile and transient interactions. This mild treatment enables efficient and rapid affinity capture of the protein assemblies of interest under nondenaturing conditions, followed by bottom-up MS to identify and quantify the protein constituents. For convenience, we have termed this approach Stabilized Affinity Capture Mass Spectrometry. Here, we demonstrate that Stabilized Affinity Capture Mass Spectrometry allows us to stabilize and elucidate local, distant, and transient protein interactions within complex cellular milieux, many of which are not observed in the absence of chemical stabilization.Insights into many cellular processes require detailed information about interactions between the participating proteins. However, the analysis of such interactions can be challenging because of the often-diverse physicochemical properties and the abundances of the constituent proteins, as well as the sometimes wide range of affinities and complex dynamics of the interactions. One of the key challenges has been acquiring information concerning transient, low affinity interactions in highly complex cellular milieux (3, 4).Methods that allow elucidation of such information include co-localization microscopy (5), fluorescence protein Förster resonance energy transfer (4), immunoelectron microscopy (5), yeast two-hybrid (6), and affinity capture (7, 8). Among these, affinity capture (AC)¹ has the unique potential to detect all specific in vivo interactions simultaneously, including those that interact both directly and indirectly. In recent times, the efficacy of such affinity isolation experiments has been greatly enhanced through the use of sensitive modern mass spectrometric protein identification techniques (9). Nevertheless, AC suffers from several shortcomings. These include the problem of 1) distinguishing specific from nonspecific interactors (10, 11); 2) preserving and isolating all unique interactions including those that are weak and/or transient, as well as those that exchange rapidly (10, 12, 13); and 3) differentiating proximal from more distant interactions (14).We describe here an approach to address these issues, which makes use of chemical stabilization of protein assemblies in the complex cellular milieu prior to AC. Chemical stabilization is an emerging technique for stabilizing and elucidating protein associations both in vitro (15–20) and in vivo (3, 12, 14, 21–29), with mass spectrometric (MS) readout of the AC proteins and their connectivities. Such chemical stabilization methods are indeed well-established and are often used in electron microscopy for preserving complexes and subcellular structures both in the cellular milieu (3) and in purified complexes (30, 31), wherein the most reliable, stable, and established stabilization reagents is glutaraldehyde. Recently, glutaraldehyde has been applied in the “GraFix” protocol in which purified protein complexes are subjected to centrifugation through a density gradient that also contains a gradient of glutaraldehyde (30, 31), allowing for optimal stabilization of authentic complexes and minimization of nonspecific associations and aggregation. GraFix has also been combined with mass spectrometry on purified complexes bound to EM grids to obtain a compositional analysis of the complexes (32), thereby raising the possibility that glutaraldehyde can be successfully utilized in conjunction with AC in complex cellular milieux directly.In this work, we present a robust pipeline for determining specific protein-protein interactions and proximities from cellular milieux. The first steps of the pipeline involve the well-established techniques of flash freezing the cells of interest in liquid nitrogen and cryomilling, which have been known for over a decade (33, 34) to preserve the cellular environment, as well as having shown outstanding performance when used in analysis of macromolecular interactions in yeast (35–39), bacterial (40, 41), trypanosome (42), mouse (43), and human (44–47) systems. The resulting frozen powder, composed of intact micron chunks of cells that have great surface area and outstanding solvent accessibility, is well suited for rapid low temperature chemical stabilization using glutaraldehyde. We selected glutaraldehyde for our procedure based on the fact that it is a very reactive stabilizing reagent, even at lower temperatures, and because it has already been shown to stabilize enzymes in their functional state (48–50). We employed highly efficient, rapid, single stage affinity capture (36, 51) for isolation and bottom-up MS for analysis of the macromolecular assemblies of interest (52–54). For convenience, we have termed this approach Stabilized Affinity-Capture Mass Spectrometry (SAC-MS).     

Tyrosine Phosphorylation of Growth Factor Receptor-bound Protein-7 by Focal Adhesion Kinase in the Regulation of Cell Migration, Proliferation, and Tumorigenesis

We have previously reported that growth factor receptor-bound protein-7 (Grb7), an Src-homology 2 (SH2)-containing adaptor protein, enables interaction with focal adhesion kinase (FAK) to regulate cell migration in response to integrin activation. To further elucidate the signaling events mediated by FAK·Grb7 complexes in promoting cell migration and other cellular functions, we firstly examined the phos pho ryl a ted tyrosine site(s) of Grb7 by FAK using an in vivo mutagenesis. We found that FAK was capable of phos pho rylating at least 2 of 12 tyrosine residues within Grb7, Tyr-188 and Tyr-338. Moreover, mutations converting the identified Tyr to Phe inhibited integrin-dependent cell migration as well as impaired cell proliferation but not survival compared with the wild-type control. Interestingly, the above inhibitory effects caused by the tyrosine phos pho ryl a tion-deficient mutants are probably attributed to their down-regulation of phospho-Tyr-397 of FAK, thereby implying a mechanism by competing with wild-type Grb7 for binding to FAK. Consequently, these tyrosine phos pho ryl a tion-deficient mutants evidently altered the phospho-Tyr-118 of paxillin and phos pho ryl a tion of ERK1/2 but less on phospho-Ser-473 of AKT, implying their involvement in the FAK·Grb7-mediated cellular functions. Additionally, we also illustrated that the formation of FAK·Grb7 complexes and Grb7 phos pho ryl a tion by FAK in an integrin-dependent manner were essential for cell migration, proliferation and anchorage-independent growth in A431 epidermal carcinoma cells, indicating the importance of FAK·Grb7 complexes in tumorigenesis. Our data provide a better understanding on the signal transduction event for FAK·Grb7-mediated cellular functions as well as to shed light on a potential therapeutic in cancers.Growth factor receptor bound protein-7 (Grb7)² is initially identified as a SH2 domain-containing adaptor protein bound to the activated EGF receptor (1). Grb7 is composed of an N-terminal proline-rich region, following a putative RA (Ras-associating) domain and a central PH (pleckstrin homology) domain and a BPS motif (between PH and SH2 domains), and a C-terminal SH2 domain (2–6). Despite the lack of enzymatic activity, the presence of multiple protein-protein interaction domains allows Grb7 family adaptor proteins to participate in versatile signal transduction pathways and, therefore, to regulate many cellular functions (4–6). A number of signaling molecules has been reported to interact with these featured domains, although most of the identified Grb7 binding partners are mediated through its SH2 domain. For example, the SH2 domain of Grb7 has been demonstrated to be capable of binding to the phospho-tyrosine sites of EGF receptor (1), ErbB2 (7), ErbB3 and ErbB4 (8), Ret (9), platelet-derived growth factor receptor (10), insulin receptor (11), SHPTP2 (12), Tek/Tie2 (13), caveolin (14), c-Kit (15), EphB1 (16), G6f immunoreceptor protein (17), Rnd1 (18), Shc (7), FAK (19), and so on. The proceeding α-helix of the PH domain of Grb7 is the calmodulin-binding domain responsible for recruiting Grb7 to plasma membrane in a Ca²⁺-dependent manner (20), and the association between the PH domain of Grb7 and phosphoinositides is required for the phosphorylation by FAK (21). Two additional proteins, NIK (nuclear factor κB-inducing kinase) and FHL2 (four and half lim domains isoform 2), in association with the GM region (Grb and Mig homology region) of Grb7 are also reported, although the physiological functions for these interactions remain unknown (22, 23). Recently, other novel roles in translational controls and stress responses through the N terminus of Grb7 are implicated for the findings of Grb7 interacting with the 5′-untranslated region of capped targeted KOR (kappa opioid receptor) mRNA and the Hu antigen R of stress granules in an FAK-mediated phosphorylation manner (24, 25).Unlike its member proteins Grb10 and Grb14, the role of Grb7 in cell migration is unambiguous and well documented. This is supported by a series of studies. Firstly, Grb7 family members share a significantly conserved molecular architecture with the Caenorhabditis elegans Mig-10 protein, which is involved in neuronal cell migration during embryonic development (4, 5, 26), suggesting that Grb7 may play a role in cell migration. Moreover, Grb7 is often co-amplified with Her2/ErbB2 in certain human cancers and tumor cell lines (7, 27, 28), and its overexpression resulted in invasive and metastatic consequences of various cancers and tumor cells (23, 29–33). On the contrary, knocking down Grb7 by RNA interference conferred to an inhibitory outcome of the breast cancer motility (34). Furthermore, interaction of Grb7 with autophosphorylated FAK at Tyr-397 could promote integrin-mediated cell migration in NIH 3T3 and CHO cells, whereas overexpression of its SH2 domain, an dominant negative mutant of Grb7, inhibited cell migration (19, 35). Recruitment and phosphorylation of Grb7 by EphB1 receptors enhanced cell migration in an ephrin-dependent manner (16). Recently, G7–18NATE, a selective Grb7-SH2 domain affinity cyclic peptide, was demonstrated to efficiently block cell migration of tumor cells (32, 36). In addition to cell migration, Grb7 has been shown to play a role in a variety of physiological and pathological events, for instance, kidney development (37), tumorigenesis (7, 14, 38–41), angiogenic activity (20), proliferation (34, 42, 43), anti-apoptosis (44), gene expression regulation (24), Silver-Russell syndrome (45), rheumatoid arthritis (46), atopic dermatitis (47), and T-cell activation (17, 48). Nevertheless, it remains largely unknown regarding the downstream signaling events of Grb7-mediated various functions. In particular, given the role of Grb7 as an adaptor molecule and its SH2 domain mainly interacting with upstream regulators, it will be interesting to identify potential downstream effectors through interacting with the functional GM region or N-terminal proline-rich region.In this report, we identified two tyrosine phosphorylated sites of Grb7 by FAK and deciphered the signaling targets downstream through these phosphorylated tyrosine sites to regulate various cellular functions such as cell migration, proliferation, and survival. In addition, our study sheds light on tyrosine phosphorylation of Grb7 by FAK involved in tumorigenesis.     

High-definition De Novo Sequencing of Crustacean Hyperglycemic Hormone (CHH)-family Neuropeptides

A complete understanding of the biological functions of large signaling peptides (>4 kDa) requires comprehensive characterization of their amino acid sequences and post-translational modifications, which presents significant analytical challenges. In the past decade, there has been great success with mass spectrometry-based de novo sequencing of small neuropeptides. However, these approaches are less applicable to larger neuropeptides because of the inefficient fragmentation of peptides larger than 4 kDa and their lower endogenous abundance. The conventional proteomics approach focuses on large-scale determination of protein identities via database searching, lacking the ability for in-depth elucidation of individual amino acid residues. Here, we present a multifaceted MS approach for identification and characterization of large crustacean hyperglycemic hormone (CHH)-family neuropeptides, a class of peptide hormones that play central roles in the regulation of many important physiological processes of crustaceans. Six crustacean CHH-family neuropeptides (8–9.5 kDa), including two novel peptides with extensive disulfide linkages and PTMs, were fully sequenced without reference to genomic databases. High-definition de novo sequencing was achieved by a combination of bottom-up, off-line top-down, and on-line top-down tandem MS methods. Statistical evaluation indicated that these methods provided complementary information for sequence interpretation and increased the local identification confidence of each amino acid. Further investigations by MALDI imaging MS mapped the spatial distribution and colocalization patterns of various CHH-family neuropeptides in the neuroendocrine organs, revealing that two CHH-subfamilies are involved in distinct signaling pathways.Neuropeptides and hormones comprise a diverse class of signaling molecules involved in numerous essential physiological processes, including analgesia, reward, food intake, learning and memory (1). Disorders of the neurosecretory and neuroendocrine systems influence many pathological processes. For example, obesity results from failure of energy homeostasis in association with endocrine alterations (2, 3). Previous work from our lab used crustaceans as model organisms found that multiple neuropeptides were implicated in control of food intake, including RFamides, tachykinin related peptides, RYamides, and pyrokinins (4–6).Crustacean hyperglycemic hormone (CHH)¹ family neuropeptides play a central role in energy homeostasis of crustaceans (7–17). Hyperglycemic response of the CHHs was first reported after injection of crude eyestalk extract in crustaceans. Based on their preprohormone organization, the CHH family can be grouped into two sub-families: subfamily-I containing CHH, and subfamily-II containing molt-inhibiting hormone (MIH) and mandibular organ-inhibiting hormone (MOIH). The preprohormones of the subfamily-I have a CHH precursor related peptide (CPRP) that is cleaved off during processing; and preprohormones of the subfamily-II lack the CPRP (9). Uncovering their physiological functions will provide new insights into neuroendocrine regulation of energy homeostasis.Characterization of CHH-family neuropeptides is challenging. They are comprised of more than 70 amino acids and often contain multiple post-translational modifications (PTMs) and complex disulfide bridge connections (7). In addition, physiological concentrations of these peptide hormones are typically below picomolar level, and most crustacean species do not have available genome and proteome databases to assist MS-based sequencing.MS-based neuropeptidomics provides a powerful tool for rapid discovery and analysis of a large number of endogenous peptides from the brain and the central nervous system. Our group and others have greatly expanded the peptidomes of many model organisms (3, 18–33). For example, we have discovered more than 200 neuropeptides with several neuropeptide families consisting of as many as 20–40 members in a simple crustacean model system (5, 6, 25–31, 34). However, a majority of these neuropeptides are small peptides with 5–15 amino acid residues long, leaving a gap of identifying larger signaling peptides from organisms without sequenced genome. The observed lack of larger size peptide hormones can be attributed to the lack of effective de novo sequencing strategies for neuropeptides larger than 4 kDa, which are inherently more difficult to fragment using conventional techniques (34–37). Although classical proteomics studies examine larger proteins, these tools are limited to identification based on database searching with one or more peptides matching without complete amino acid sequence coverage (36, 38).Large populations of neuropeptides from 4–10 kDa exist in the nervous systems of both vertebrates and invertebrates (9, 39, 40). Understanding their functional roles requires sufficient molecular knowledge and a unique analytical approach. Therefore, developing effective and reliable methods for de novo sequencing of large neuropeptides at the individual amino acid residue level is an urgent gap to fill in neurobiology. In this study, we present a multifaceted MS strategy aimed at high-definition de novo sequencing and comprehensive characterization of the CHH-family neuropeptides in crustacean central nervous system. The high-definition de novo sequencing was achieved by a combination of three methods: (1) enzymatic digestion and LC-tandem mass spectrometry (MS/MS) bottom-up analysis to generate detailed sequences of proteolytic peptides; (2) off-line LC fractionation and subsequent top-down MS/MS to obtain high-quality fragmentation maps of intact peptides; and (3) on-line LC coupled to top-down MS/MS to allow rapid sequence analysis of low abundance peptides. Combining the three methods overcomes the limitations of each, and thus offers complementary and high-confidence determination of amino acid residues. We report the complete sequence analysis of six CHH-family neuropeptides including the discovery of two novel peptides. With the accurate molecular information, MALDI imaging and ion mobility MS were conducted for the first time to explore their anatomical distribution and biochemical properties.     

Coomassie Blue as a Near-infrared Fluorescent Stain: A Systematic Comparison With Sypro Ruby for In-gel Protein Detection

Quantitative proteome analyses suggest that the well-established stain colloidal Coomassie Blue, when used as an infrared dye, may provide sensitive, post-electrophoretic in-gel protein detection that can rival even Sypro Ruby. Considering the central role of two-dimensional gel electrophoresis in top-down proteomic analyses, a more cost effective alternative such as Coomassie Blue could prove an important tool in ongoing refinements of this important analytical technique. To date, no systematic characterization of Coomassie Blue infrared fluorescence detection relative to detection with SR has been reported. Here, seven commercial Coomassie stain reagents and seven stain formulations described in the literature were systematically compared. The selectivity, threshold sensitivity, inter-protein variability, and linear-dynamic range of Coomassie Blue infrared fluorescence detection were assessed in parallel with Sypro Ruby. Notably, several of the Coomassie stain formulations provided infrared fluorescence detection sensitivity to <1 ng of protein in-gel, slightly exceeding the performance of Sypro Ruby. The linear dynamic range of Coomassie Blue infrared fluorescence detection was found to significantly exceed that of Sypro Ruby. However, in two-dimensional gel analyses, because of a blunted fluorescence response, Sypro Ruby was able to detect a few additional protein spots, amounting to 0.6% of the detected proteome. Thus, although both detection methods have their advantages and disadvantages, differences between the two appear to be small. Coomassie Blue infrared fluorescence detection is thus a viable alternative for gel-based proteomics, offering detection comparable to Sypro Ruby, and more reliable quantitative assessments, but at a fraction of the cost.Gel electrophoresis is an accessible, widely applicable and mature protein resolving technology. As the original top-down approach to proteomic analyses, among its many attributes the high resolution achievable by two dimensional gel-electrophoresis (2DE)¹ ensures that it remains an effective analytical technology despite the appearance of alternatives. However, in-gel detection remains a limiting factor for gel-based analyses; available technology generally permits the detection and quantification of only relatively abundant proteins (35). Many critical components in normal physiology and also disease may be several orders of magnitude less abundant and thus below the detection threshold of in-gel stains, or indeed most techniques. Pre- and post-fractionation technologies have been developed to address this central issue in proteomics but these are not without limitations (1–5). Thus improved detection methods for gel-based proteomics continue to be a high priority, and the literature is rich with different in-gel detection methods and innovative improvements (6–34). This history of iterative refinement presents a wealth of choices when selecting a detection strategy for a gel-based proteomic analysis (35).Perhaps the best known in-gel detection method is the ubiquitous Coomassie Blue (CB) stain; CB has served as a gel stain and protein quantification reagent for over 40 years. Though affordable, robust, easy to use, and compatible with mass spectrometry (MS), CB staining is relatively insensitive. In traditional organic solvent formulations, CB detects ∼ 10 ng of protein in-gel, and some reports suggest poorer sensitivity (27, 29, 36, 37). Sensitivity is hampered by relatively high background staining because of nonspecific retention of dye within the gel matrix (32, 36, 38, 39). The development of colloidal CB (CCB) formulations largely addressed these limitations (12); the concentration of soluble CB was carefully controlled by sequestering the majority of the dye into colloidal particles, mediated by pH, solvent, and the ionic strength of the solution. Minimizing soluble dye concentration and penetration of the gel matrix mitigated background staining, and the introduction of phosphoric acid into the staining reagent enhanced dye-protein interactions (8, 12, 40), contributing to an in-gel staining sensitivity of 5–10 ng protein, with some formulations reportedly yielding sensitivities of 0.1–1 ng (8, 12, 22, 39, 41, 42). Thus CCB achieved higher sensitivity than traditional CB staining, yet maintained all the advantages of the latter, including low cost and compatibility with existing densitometric detection instruments and MS. Although surpassed by newer methods, the practical advantages of CCB ensure that it remains one of the most common gel stains in use.Fluorescent stains have become the routine and sensitive alternative to visible dyes. Among these, the ruthenium-organometallic family of dyes have been widely applied and the most commercially well-known is Sypro Ruby (SR), which is purported to interact noncovalently with primary amines in proteins (15, 18, 19, 43). Chief among the attributes of these dyes is their high sensitivity. In-gel detection limits of < 1 ng for some proteins have been reported for SR (6, 9, 14, 44, 45). Moreover, SR staining has been reported to yield a greater linear dynamic range (LDR), and reduced interprotein variability (IPV) compared with CCB and silver stains (15, 19, 46–49). SR is easy to use, fully MS compatible, and relatively forgiving of variations in initial conditions (6, 15). The chief consequence of these advances remains high cost; SR and related stains are notoriously expensive, and beyond the budget of many laboratories. Furthermore, despite some small cost advantage relative to SR, none of the available alternatives has been consistently and quantitatively demonstrated to substantially improve on the performance of SR under practical conditions (9, 50).Notably, there is evidence to suggest that CCB staining is not fundamentally insensitive, but rather that its sensitivity has been limited by traditional densitometric detection (50, 51). When excited in the near IR at ∼650 nm, protein-bound CB in-gel emits light in the range of 700–800 nm. Until recently, the lack of low-cost, widely available and sufficiently sensitive infrared (IR)-capable imaging instruments prevented mainstream adoption of in-gel CB infrared fluorescence detection (IRFD); advances in imaging technology are now making such instruments far more accessible. Initial reports suggested that IRFD of CB-stained gels provided greater sensitivity than traditional densitometric detection (50, 51). Using CB R250, in-gel IRFD was reported to detect as little as 2 ng of protein in-gel, with a LDR of about an order of magnitude (2 to 20 ng, or 10 to 100 ng in separate gels), beyond which the fluorescent response saturated into the μg range (51). Using the G250 dye variant, it was determined that CB-IRFD of 2D gels detected ∼3 times as many proteins as densitometric imaging, and a comparable number of proteins as seen by SR (50). This study also concluded that CB-IRFD yielded a significantly higher signal to background ratio (S/BG) than SR, providing initial evidence that CB-IRFD may be superior to SR in some aspects of stain performance (50).Despite this initial evidence of the viability of CB-IRF as an in-gel protein detection method, a detailed characterization of this technology has not yet been reported. Here a more thorough, quantitative characterization of CB-IRFD is described, establishing its lowest limit of detection (LLD), IPV, and LDR in comparison to SR. Finally a wealth of modifications and enhancements of CCB formulations have been reported (8, 12, 21, 24, 26, 29, 40, 41, 52–54), and likewise there are many commercially available CCB stain formulations. To date, none of these formulations have been compared quantitatively in terms of their relative performance when detected using IRF. As a general detection method for gel-based proteomics, CB-IRFD was found to provide comparable or even slightly superior performance to SR according to most criteria, including sensitivity and selectivity (50). Furthermore, in terms of LDR, CB-IRFD showed distinct advantages over SR. However, assessing proteomes resolved by 2DE revealed critical distinctions between CB-IRFD and SR in terms of protein quantification versus threshold detection: neither stain could be considered unequivocally superior to the other by all criteria. Nonetheless, IRFD proved the most sensitive method of detecting CB-stained protein in-gel, enabling high sensitivity detection without the need for expensive reagents or even commercial formulations. Overall, CB-IRFD is a viable alternative to SR and other mainstream fluorescent stains, mitigating the high cost of large-scale gel-based proteomic analyses, making high sensitivity gel-based proteomics accessible to all labs. With improvements to CB formulations and/or image acquisition instruments, the performance of this detection technology may be further enhanced.     

Sgt1 Dimerization Is Negatively Regulated by Protein Kinase CK2-mediated Phosphorylation at Ser361

The kinetochore, which consists of centromere DNA and structural proteins, is essential for proper chromosome segregation in eukaryotes. In budding yeast, Sgt1 and Hsp90 are required for the binding of Skp1 to Ctf13 (a component of the core kinetochore complex CBF3) and therefore for the assembly of CBF3. We have previously shown that Sgt1 dimerization is important for this kinetochore assembly mechanism. In this study, we report that protein kinase CK2 phosphorylates Ser³⁶¹ on Sgt1, and this phosphorylation inhibits Sgt1 dimerization.The kinetochore is a structural protein complex located in the centromeric region of the chromosome coupled to spindle microtubules (1, 2). The kinetochore generates a signal to arrest cells during mitosis when it is not properly attached to microtubules, thereby preventing chromosome missegregation, which can lead to aneuploidy (3, 4). The molecular structure of the kinetochore complex of the budding yeast Saccharomyces cerevisiae has been well characterized; it is composed of more than 70 proteins, many of which are conserved in mammals (2).The centromere DNA in the budding yeast is a 125-bp region that contains three conserved regions, CDEI, CDEII, and CDEIII (5, 6). CDEIII (25 bp) is essential for centromere function (7) and is bound to a key component of the centromere, the CBF3 complex. The CBF3 complex contains four proteins, Ndc10, Cep3, Ctf13 (8–15), and Skp1 (14, 15), all essential for viability. Mutations in any of the CBF3 proteins abolish the ability of CDEIII to bind to CBF3 (16, 17). All of the kinetochore proteins, except the CDEI-binding Cbf1 (18–20), localize to the kinetochores in a CBF3-dependent manner (2). Thus, CBF3 is a fundamental kinetochore complex, and its mechanism of assembly is of great interest.We have previously found that Sgt1 and Skp1 activate Ctf13; thus, they are required for assembly of the CBF3 complex (21). The molecular chaperone Hsp90 is also required to form the active Ctf13-Skp1 complex (22). Sgt1 has two highly conserved motifs that are required for protein-protein interaction: the tetratricopeptide repeat (21) and the CHORD protein and Sgt1-specific motif. We and others have found that both domains are important for the interaction of Sgt1 with Hsp90 (23–26), which is required for assembly of the core kinetochore complex. This interaction is an initial step in kinetochore activation (24, 26, 27), which is conserved between yeast and humans (28, 29).We have recently shown that Sgt1 dimerization is important for Sgt1-Skp1 binding and therefore for kinetochore assembly (30). In this study, we have found that protein kinase CK2 phosphorylates Sgt1 at Ser³⁶¹, and this phosphorylation inhibits Sgt1 dimerization. Therefore, CK2 appears to regulate kinetochore assembly negatively in budding yeast.