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]     

Dbf4-Cdc7 Phosphorylation of Mcm2 Is Required for Cell Growth

The Dbf4-Cdc7 kinase (DDK) is required for the activation of the origins of replication, and DDK phosphorylates Mcm2 in vitro. We find that budding yeast Cdc7 alone exists in solution as a weakly active multimer. Dbf4 forms a likely heterodimer with Cdc7, and this species phosphorylates Mcm2 with substantially higher specific activity. Dbf4 alone binds tightly to Mcm2, whereas Cdc7 alone binds weakly to Mcm2, suggesting that Dbf4 recruits Cdc7 to phosphorylate Mcm2. DDK phosphorylates two serine residues of Mcm2 near the N terminus of the protein, Ser-164 and Ser-170. Expression of mcm2-S170A is lethal to yeast cells that lack endogenous MCM2 (mcm2Δ); however, this lethality is rescued in cells harboring the DDK bypass mutant mcm5-bob1. We conclude that DDK phosphorylation of Mcm2 is required for cell growth.The Cdc7 protein kinase is required throughout the yeast S phase to activate origins (1, 2). The S phase cyclin-dependent kinase also activates yeast origins of replication (3–5). It has been proposed that Dbf4 activates Cdc7 kinase in S phase, and that Dbf4 interaction with Cdc7 is essential for Cdc7 kinase activity (6). However, it is not known how Dbf4-Cdc7 (DDK)² acts during S phase to trigger the initiation of DNA replication. DDK has homologs in other eukaryotic species, and the role of Cdc7 in activation of replication origins during S phase may be conserved (7–10).The Mcm2-7 complex functions with Cdc45 and GINS to unwind DNA at a replication fork (11–15). A mutation of MCM5 (mcm5-bob1) bypasses the cellular requirements for DBF4 and CDC7 (16), suggesting a critical physiologic interaction between Dbf4-Cdc7 and Mcm proteins. DDK phosphorylates Mcm2 in vitro with proteins purified from budding yeast (17, 18) or human cells (19). Furthermore, there are mutants of MCM2 that show synthetic lethality with DBF4 mutants (6, 17), suggesting a biologically relevant interaction between DBF4 and MCM2. Nevertheless, the physiologic role of DDK phosphorylation of Mcm2 is a matter of dispute. In human cells, replacement of MCM2 DDK-phosphoacceptor residues with alanines inhibits DNA replication, suggesting that Dbf4-Cdc7 phosphorylation of Mcm2 in humans is important for DNA replication (20). In contrast, mutation of putative DDK phosphorylation sites at the N terminus of Schizosaccharomyces pombe Mcm2 results in viable cells, suggesting that phosphorylation of S. pombe Mcm2 by DDK is not critical for cell growth (10).In budding yeast, Cdc7 is present at high levels in G₁ and S phase, whereas Dbf4 levels peak in S phase (18, 21, 22). Furthermore, budding yeast DDK binds to chromatin during S phase (6), and it has been shown that Dbf4 is required for Cdc7 binding to chromatin in budding yeast (23, 24), fission yeast (25), and Xenopus (9). Human and fission yeast Cdc7 are inert on their own (7, 8), but Dbf4-Cdc7 is active in phosphorylating Mcm proteins in budding yeast (6, 26), fission yeast (7), and human (8, 10). Based on these data, it has been proposed that Dbf4 activates Cdc7 kinase in S phase and that Dbf4 interaction with Cdc7 is essential for Cdc7 kinase activity (6, 9, 18, 21–24). However, a mechanistic analysis of how Dbf4 activates Cdc7 has not yet been accomplished. For example, the multimeric state of the active Dbf4-Cdc7 complex is currently disputed. A heterodimer of fission yeast Cdc7 (Hsk1) in complex with fission yeast Dbf4 (Dfp1) can phosphorylate Mcm2 (7). However, in budding yeast, oligomers of Cdc7 exist in the cell (27), and Dbf4-Cdc7 exists as oligomers of 180 and 300 kDa (27).DDK phosphorylates the N termini of human Mcm2 (19, 20, 28), human Mcm4 (10), budding yeast Mcm4 (26), and fission yeast Mcm6 (10). Although the sequences of the Mcm N termini are poorly conserved, the DDK sites identified in each study have neighboring acidic residues. The residues of budding yeast Mcm2 that are phosphorylated by DDK have not yet been identified.In this study, we find that budding yeast Cdc7 is weakly active as a multimer in phosphorylating Mcm2. However, a low molecular weight form of Dbf4-Cdc7, likely a heterodimer, has a higher specific activity for phosphorylation of Mcm2. Dbf4 or DDK, but not Cdc7, binds tightly to Mcm2, suggesting that Dbf4 recruits Cdc7 to Mcm2. DDK phosphorylates two serine residues of Mcm2, Ser-164 and Ser-170, in an acidic region of the protein. Mutation of Ser-170 is lethal to yeast cells, but this phenotype is rescued by the DDK bypass mutant mcm5-bob1. We conclude that DDK phosphorylation of Ser-170 of Mcm2 is required for budding yeast growth.     

F-Actin Dynamics in Neurospora crassa

This study demonstrates the utility of Lifeact for the investigation of actin dynamics in Neurospora crassa and also represents the first report of simultaneous live-cell imaging of the actin and microtubule cytoskeletons in filamentous fungi. Lifeact is a 17-amino-acid peptide derived from the nonessential Saccharomyces cerevisiae actin-binding protein Abp140p. Fused to green fluorescent protein (GFP) or red fluorescent protein (TagRFP), Lifeact allowed live-cell imaging of actin patches, cables, and rings in N. crassa without interfering with cellular functions. Actin cables and patches localized to sites of active growth during the establishment and maintenance of cell polarity in germ tubes and conidial anastomosis tubes (CATs). Recurrent phases of formation and retrograde movement of complex arrays of actin cables were observed at growing tips of germ tubes and CATs. Two populations of actin patches exhibiting slow and fast movement were distinguished, and rapid (1.2 μm/s) saltatory transport of patches along cables was observed. Actin cables accumulated and subsequently condensed into actin rings associated with septum formation. F-actin organization was markedly different in the tip regions of mature hyphae and in germ tubes. Only mature hyphae displayed a subapical collar of actin patches and a concentration of F-actin within the core of the Spitzenkörper. Coexpression of Lifeact-TagRFP and β-tubulin–GFP revealed distinct but interrelated localization patterns of F-actin and microtubules during the initiation and maintenance of tip growth.Actins are highly conserved proteins found in all eukaryotes and have an enormous variety of cellular roles. The monomeric form (globular actin, or G-actin) can self-assemble, with the aid of numerous actin-binding proteins (ABPs), into microfilaments (filamentous actin, or F-actin), which, together with microtubules, form the two major components of the fungal cytoskeleton. Numerous pharmacological and genetic studies of fungi have demonstrated crucial roles for F-actin in cell polarity, exocytosis, endocytosis, cytokinesis, and organelle movement (6, 7, 20, 34, 35, 51, 52, 59). Phalloidin staining, immunofluorescent labeling, and fluorescent-protein (FP)-based live-cell imaging have revealed three distinct subpopulations of F-actin-containing structures in fungi: patches, cables, and rings (1, 14, 28, 34, 60, 63, 64). Actin patches are associated with the plasma membrane and represent an accumulation of F-actin around endocytic vesicles (3, 26, 57). Actin cables are bundles of actin filaments stabilized with cross-linking proteins, such as tropomyosins and fimbrin, and are assembled by formins at sites of active growth, where they form tracks for myosin V-dependent polarized secretion and organelle transport (10, 16, 17, 27, 38, 47, 48). Cables, unlike patches, are absolutely required for polarized growth in the budding yeast Saccharomyces cerevisiae (34, 38). Contractile actomyosin rings are essential for cytokinesis in budding yeast, whereas in filamentous fungi, actin rings are less well studied but are known to be involved in septum formation (20, 28, 34, 39, 40).Actin cables and patches have been particularly well studied in budding yeast. However, there are likely to be important differences between F-actin architecture and dynamics in budding yeast and those in filamentous fungi, as budding yeasts display only a short period of polarized growth during bud formation, which is followed by isotropic growth over the bud surface (10). Sustained polarized growth during hyphal morphogenesis is a defining feature of filamentous fungi (21), making them attractive models for studying the roles of the actin cytoskeleton in cell polarization, tip growth, and organelle transport.In Neurospora crassa and other filamentous fungi, disruption of the actin cytoskeleton leads to rapid tip swelling, which indicates perturbation of polarized tip growth, demonstrating a critical role for F-actin in targeted secretion to particular sites on the plasma membrane (7, 22, 29, 56). Immunofluorescence studies of N. crassa have shown that F-actin localizes to hyphal tips as “clouds” and “plaques” (7, 54, 59). However, immunolabeling has failed to reveal actin cables in N. crassa and offers limited insights into F-actin dynamics. Live-cell imaging of F-actin architecture and dynamics has not been accomplished in N. crassa, yet it is expected to yield key insights into cell polarization, tip growth, and intracellular transport.We took advantage of a recently developed live-cell imaging probe for F-actin called Lifeact (43). Lifeact is a 17-amino-acid peptide derived from the N terminus of the budding yeast actin-binding protein Abp140 (5, 63) and has recently been demonstrated to be a universal live-cell imaging marker for F-actin in eukaryotes (43). Here, we report the successful application of fluorescent Lifeact fusion constructs for live-cell imaging of F-actin in N. crassa. We constructed two synthetic genes consisting of Lifeact fused to “synthetic” green fluorescent protein (sGFP) (S65T) (henceforth termed GFP) (12) or red fluorescent protein (TagRFP) (33) and expressed these constructs in various N. crassa strains. In all strain backgrounds, fluorescent Lifeact constructs clearly labeled actin patches, cables, and rings and revealed a direct association of F-actin structures with sites of cell polarization and active tip growth. Our results demonstrate the efficacy of Lifeact as a nontoxic live-cell imaging probe in N. crassa.     

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]     

N-Terminal-oriented Proteogenomics of the Marine Bacterium Roseobacter Denitrificans Och114 using N-Succinimidyloxycarbonylmethyl)tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP) Labeling and Diagonal Chromatography

Given the ease of whole genome sequencing with next-generation sequencers, structural and functional gene annotation is now purely based on automated prediction. However, errors in gene structure are frequent, the correct determination of start codons being one of the main concerns. Here, we combine protein N termini derivatization using (N-Succinimidyloxycarbonylmethyl)tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP Ac-OSu) as a labeling reagent with the COmbined FRActional DIagonal Chromatography (COFRADIC) sorting method to enrich labeled N-terminal peptides for mass spectrometry detection. Protein digestion was performed in parallel with three proteases to obtain a reliable automatic validation of protein N termini. The analysis of these N-terminal enriched fractions by high-resolution tandem mass spectrometry allowed the annotation refinement of 534 proteins of the model marine bacterium Roseobacter denitrificans OCh114. This study is especially efficient regarding mass spectrometry analytical time. From the 534 validated N termini, 480 confirmed existing gene annotations, 41 highlighted erroneous start codon annotations, five revealed totally new mis-annotated genes; the mass spectrometry data also suggested the existence of multiple start sites for eight different genes, a result that challenges the current view of protein translation initiation. Finally, we identified several proteins for which classical genome homology-driven annotation was inconsistent, questioning the validity of automatic annotation pipelines and emphasizing the need for complementary proteomic data. All data have been deposited to the ProteomeXchange with identifier PXD000337.Recent developments in mass spectrometry and bioinformatics have established proteomics as a common and powerful technique for identifying and quantifying proteins at a very broad scale, but also for characterizing their post-translational modifications and interaction networks (1, 2). In addition to the avalanche of proteomic data currently being reported, many genome sequences are established using next-generation sequencing, fostering proteomic investigations of new cellular models. Proteogenomics is a relatively recent field in which high-throughput proteomic data is used to verify coding regions within model genomes to refine the annotation of their sequences (2–8). Because genome annotation is now fully automated, the need for accurate annotation for model organisms with experimental data is crucial. Many projects related to genome re-annotation of microorganisms with the help of proteomics have been recently reported, such as for Mycoplasma pneumoniae (9), Rhodopseudomonas palustris (10), Shewanella oneidensis (11), Thermococcus gammatolerans (12), Deinococcus deserti (13), Salmonella thyphimurium (14), Mycobacterium tuberculosis (15, 16), Shigella flexneri (17), Ruegeria pomeroyi (18), and Candida glabrata (19), as well as for higher organisms such as Anopheles gambiae (20) and Arabidopsis thaliana (4, 5).The most frequently reported problem in automatic annotation systems is the correct identification of the translational start codon (21–23). The error rate depends on the primary annotation system, but also on the organism, as reported for Halobacterium salinarum and Natromonas pharaonis (24), Deinococcus deserti (21), and Ruegeria pomeroyi (18), where the error rate is estimated above 10%. Identification of a correct translational start site is essential for the genetic and biochemical analysis of a protein because errors can seriously impact subsequent biological studies. If the N terminus is not correctly identified, the protein will be considered in either a truncated or extended form, leading to errors in bioinformatic analyses (e.g. during the prediction of its molecular weight, isoelectric point, cellular localization) and major difficulties during its experimental characterization. For example, a truncated protein may be heterologously produced as an unfolded polypeptide recalcitrant to structure determination (25). Moreover, N-terminal modifications, which are poorly documented in annotation databases, may occur (26, 27).Unfortunately, the poor polypeptide sequence coverage obtained for the numerous low abundance proteins in current shotgun MS/MS proteomic studies implies that the overall detection of N-terminal peptides obtained in proteogenomic studies is relatively low. Different methods for establishing the most extensive list of protein N termini, grouped under the so-called “N-terminomics” theme, have been proposed to selectively enrich or improve the detection of these peptides (2, 28, 29). Large N-terminome studies have recently been reported based on resin-assisted enrichment of N-terminal peptides (30) or terminal amine isotopic labeling of substrates (TAILS) coupled to depletion of internal peptides with a water-soluble aldehyde-functionalized polymer (31–35). Among the numerous N-terminal-oriented methods (2), specific labeling of the N terminus of intact proteins with N-tris(2,4,6-trimethoxyphenyl)phosphonium acetyl succinamide (TMPP-Ac-OSu)¹ has proven reliable (21, 36–39). TMPP-derivatized N-terminal peptides have interesting properties for further LC-MS/MS mass spectrometry: (1) an increase in hydrophobicity because of the trimethoxyphenyl moiety added to the peptides, increasing their retention times in reverse phase chromatography, (2) improvement of their ionization because of the introduction of a positively charged group, and (3) a much simpler fragmentation pattern in tandem mass spectrometry. Other reported approaches rely on acetylation, followed by trypsin digestion, and then biotinylation of free amino groups (40); guanidination of lysine lateral chains followed by N-biotinylation of the N termini and trypsin digestion (41); or reductive amination of all free amino groups with formaldehyde preceeding trypsin digestion (42). Recently, we applied the TMPP method to the proteome of the Deinococcus deserti bacterium isolated from upper sand layers of the Sahara desert (13). This method enabled the detection of N-terminal peptides allowing the confirmation of 278 translation initiation codons, the correction of 73 translation starts, and the identification of non-canonical translation initiation codons (21). However, most TMPP-labeled N-terminal peptides are hidden among the more abundant internal peptides generated after proteolysis of a complex proteome, precluding their detection. This results in disproportionately fewer N-terminal validations, that is, 5 and 8% of total polypeptides coded in the theoretical proteomes of Mycobacterium smegmatis (37) and Deinococcus deserti (21) with a total of 342 and 278 validations, respectively.An interesting chromatographic method to fractionate peptide mixtures for gel-free high-throughput proteome analysis has been developed over the last years and applied to various topics (43, 44). This technique, known as COmbined FRActional DIagonal Chromatography (COFRADIC), uses a double chromatographic separation with a chemical reaction in between to change the physico-chemical properties of the extraneous peptides to be resolved from the peptides of interest. Its previous applications include the separation of methionine-containing peptides (43), N-terminal peptide enrichment (45, 46), sulfur amino acid-containing peptides (47), and phosphorylated peptides (48). COFRADIC was identified as the best method for identification of N-terminal peptides of two archaea, resulting in the identification of 240 polypeptides (9% of the theoretical proteome) for Halobacterium salinarum and 220 (8%) for Natronomonas pharaonis (24).Taking advantage of both the specificity of TMPP labeling, the resolving power of COFRADIC for enrichment, and the increase in information through the use of multiple proteases, we performed the proteogenomic analysis of a marine bacterium from the Roseobacter clade, namely Roseobacter denitrificans OCh114. This novel approach allowed us to validate and correct 534 unique proteins (13% of the theoretical proteome) with TMPP-labeled N-terminal signatures obtained using high-resolution tandem mass spectrometry. We corrected 41 annotations and detected five new open reading frames in the R. denitrificans genome. We further identified eight distinct proteins showing direct evidence for multiple start sites.     

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]     

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.     

Human Disease-causing Mutations Disrupt an N-C-terminal Interaction and Channel Function of Bestrophin 1

Mutations in the human bestrophin 1 (hBest1) chloride channel cause Best vitelliform macular dystrophy. Although mutations in its transmembrane domains were found to alter biophysical properties of the channel, the mechanism for disease-causing mutations in its N and C termini remains elusive. We hypothesized that these mutations lead to channel dysfunction through disruption of an N-C-terminal interaction. Here, we present data demonstrating that hBest1 N and C termini indeed interact both in vivo and in vitro. In addition, using a spectrum-based fluorescence resonance energy transfer method, we showed that functional hBest1 channels in the plasma membrane were multimers. Disease-causing mutations in the N terminus (R19C, R25C, and K30C) and the C terminus (G299E, D301N, and D312N) caused channel dysfunction and disruption of the N-C interaction. Consistent with the functional and biochemical results, mutants D301N and D312N clearly reduced fluorescence resonance energy transfer signal, indicating that the N-C interaction was indeed perturbed. These results suggest that hBest1 functions as a multimer in the plasma membrane, and disruption of the N-C interaction by mutations leads to hBest1 channel dysfunction.Extensive evidence has shown that bestrophins are anion channels when expressed heterologously in cell lines (1–9) and represent a type of endogenous calcium-activated chlorine channel in several cell types (10–12). Mutations disrupting hBest1 channel function lead to Best vitelliform macular dystrophy (Best disease) (13). Bestrophin 1 channels have been reported to exist as oligomers (2, 14). Results from immunoprecipitation experiments suggested that hBest1 exists as tetramers or pentamers when expressed heterologously (2), whereas a hydrodynamic study based on the calculations of the molecular mass of the Best1-detergent complex concluded that native porcine Best1 channels are dimers (14). Besides the uncertainty about the subunit stoichiometry, it is still unclear how bestrophin subunits assemble and interact in functional channels.Understanding how disease-causing mutations might adversely affect the assembly and interaction of bestrophin subunits is important for elucidating the molecular mechanism underlying the Best disease. The hBest1 protein contains six transmembrane domains (TMD1–6) with intracellularly located N and C termini. There are three “hot spots” of disease-causing mutations in hBest1: the N-terminal region, TMD2, and the C terminus proximal to TMD6 (13, 15). Multiple lines of evidence support that mutations in TMD2 alter the biophysical properties of the channel (3, 4, 7). How mutations distributed around the N- and C-terminal regions cause Best disease is less clear, although strong evidence recently suggested that certain mutations in the C terminus disrupt hBest1 channel gating by Ca²⁺ (16). N-C-terminal interaction of multimeric channels has been demonstrated to be involved in the activation of many channel types including inward rectifier K⁺ channels (17) and cyclic nucleotide-gated channels (18–20). In the present study we tested the hypothesis that an interaction between the N and C termini plays an important role in normal hBest1 channel function, and weakening or disruption of this interaction by mutations leads to channel dysfunction.To test our hypothesis, we introduced disease-causing mutations into the N- or C-terminal regions of hBest1 expressed in HEK293 cells and tested the effects of mutations on subunit interaction and channel function with a combination of electrophysiological, biochemical, and optical methods. We found that these mutations not only disrupted channel function but also caused N- and C-terminal dissociation both in vitro and in vivo. The findings suggest a novel molecular mechanism for the mutations in hBest1 to cause human Best disease.