Not all transmembrane helices are born equal: Towards the extension of the sequence homology concept to membrane proteins

Background

Sequence homology considerations widely used to transfer functional annotation to uncharacterized protein sequences require special precautions in the case of non-globular sequence segments including membrane-spanning stretches composed of non-polar residues. Simple, quantitative criteria are desirable for identifying transmembrane helices (TMs) that must be included into or should be excluded from start sequence segments in similarity searches aimed at finding distant homologues.

Results

We found that there are two types of TMs in membrane-associated proteins. On the one hand, there are so-called simple TMs with elevated hydrophobicity, low sequence complexity and extraordinary enrichment in long aliphatic residues. They merely serve as membrane-anchoring device. In contrast, so-called complex TMs have lower hydrophobicity, higher sequence complexity and some functional residues. These TMs have additional roles besides membrane anchoring such as intra-membrane complex formation, ligand binding or a catalytic role. Simple and complex TMs can occur both in single- and multi-membrane-spanning proteins essentially in any type of topology. Whereas simple TMs have the potential to confuse searches for sequence homologues and to generate unrelated hits with seemingly convincing statistical significance, complex TMs contain essential evolutionary information.

Conclusion

For extending the homology concept onto membrane proteins, we provide a necessary quantitative criterion to distinguish simple TMs (and a sufficient criterion for complex TMs) in query sequences prior to their usage in homology searches based on assessment of hydrophobicity and sequence complexity of the TM sequence segments.

Reviewers

This article was reviewed by Shamil Sunyaev, L. Aravind and Arcady Mushegian.     

Orientational preferences of neighboring helices can drive ER insertion of a marginally hydrophobic transmembrane helix

α-helical integral membrane proteins critically depend on the correct insertion of their transmembrane α helices into the lipid bilayer for proper folding, yet a surprisingly large fraction of the transmembrane α helices in multispanning integral membrane proteins are not sufficiently hydrophobic to insert into the target membrane by themselves. How can such marginally hydrophobic segments nevertheless form transmembrane helices in the folded structure? Here, we show that a transmembrane helix with a strong orientational preference (N(cyt)-C(lum) or N(lum)-C(cyt)) can both increase and decrease the hydrophobicity threshold for membrane insertion of a neighboring, marginally hydrophobic helix. This effect helps explain the "missing hydrophobicity" in polytopic membrane proteins.     

Genetic affinities among the lower castes and tribal groups of India: inference from Y chromosome and mitochondrial DNA

Background

Past work on asthmatic African American families revealed a strong linkage peak with modest evidence of association on chromosome 11q. Here, we perform tests of association for asthma and a panel of 609 SNPs in African American subjects using a sliding window approach. While efficient in screening a region of dense genotyping, this approach does create some problems: high numbers of tests, assimilating thousands of results, and questions about setting priorities on regions with association signals.

Results

We present a newly developed tool, Graphical Assessment of Sliding P-values or GrASP, which uses color display to indicate the width of the sliding windows, significance of individual tests, density of SNP coverage and location of known genes that simplifies some of these issues, and use it to identify regions of interest in these data.

Conclusion

We demonstrate that GrASP makes it easier to visualize, summarize and prioritize regions of interest from sliding window haplotype analysis, based jointly on the p-value from all the tests from these windows and the building of haplotypes of significance in the region. Using this approach, five regions yielded strong evidence for linkage and association with asthma, including the prior peak linkage region.     

Rosetta Broker for membrane protein structure prediction: concentrative nucleoside transporter 3 and corticotropin-releasing factor receptor 1 test cases

Background

Membrane proteins are difficult targets for structure prediction due to the limited structural data deposited in Protein Data Bank. Most computational methods for membrane protein structure prediction are based on the comparative modeling. There are only few de novo methods targeting that distinct protein family. In this work an example of such de novo method was used to structurally and functionally characterize two representatives of distinct membrane proteins families of solute carrier transporters and G protein-coupled receptors. The well-known Rosetta program and one of its protocols named Broker was used in two test cases. The first case was de novo structure prediction of three N-terminal transmembrane helices of the human concentrative nucleoside transporter 3 (hCNT3) homotrimer belonging to the solute carrier 28 family of transporters (SLC28). The second case concerned the large scale refinement of transmembrane helices of a homology model of the corticotropin-releasing factor receptor 1 (CRFR1) belonging to the G protein-coupled receptors family.

Results

The inward-facing model of the hCNT3 homotrimer was used to propose the functional impact of its single nucleotide polymorphisms. Additionally, the 100 ns molecular dynamics simulation of the unliganded hCNT3 model confirmed its validity and revealed mobility of the selected binding site and homotrimer interface residues. The large scale refinement of transmembrane helices of the CRFR1 homology model resulted in the significant improvement of its accuracy with respect to the crystal structure of CRFR1, especially in the binding site area. Consequently, the antagonist CP-376395 could be docked with Autodock VINA to the CRFR1 model without any steric clashes.

Conclusions

The presented work demonstrated that Rosetta Broker can be a versatile tool for solving various issues referring to protein biology. Two distinct examples of de novo membrane protein structure prediction presented here provided important insights into three major areas of protein biology. Namely, the dynamics of the inward-facing hCNT3 homotrimer system, the structural changes of the CRFR1 receptor upon the antagonist binding and finally, the role of single nucleotide polymorphisms in both, hCNT3 and CRFR1 proteins, were investigated.

     

Genomic analysis of membrane protein families: abundance and conserved motifs

Background

Polytopic membrane proteins can be related to each other on the basis of the number of transmembrane helices and sequence similarities. Building on the Pfam classification of protein domain families, and using transmembrane-helix prediction and sequence-similarity searching, we identified a total of 526 well-characterized membrane protein families in 26 recently sequenced genomes. To this we added a clustering of a number of predicted but unclassified membrane proteins, resulting in a total of 637 membrane protein families.

Results

Analysis of the occurrence and composition of these families revealed several interesting trends. The number of assigned membrane protein domains has an approximately linear relationship to the total number of open reading frames (ORFs) in 26 genomes studied. Caenorhabditis elegans is an apparent outlier, because of its high representation of seven-span transmembrane (7-TM) chemoreceptor families. In all genomes, including that of C. elegans, the number of distinct membrane protein families has a logarithmic relation to the number of ORFs. Glycine, proline, and tyrosine locations tend to be conserved in transmembrane regions within families, whereas isoleucine, valine, and methionine locations are relatively mutable. Analysis of motifs in putative transmembrane helices reveals that GxxxG and GxxxxxxG (which can be written GG4 and GG7, respectively; see Materials and methods) are among the most prevalent. This was noted in earlier studies; we now find these motifs are particularly well conserved in families, however, especially those corresponding to transporters, symporters, and channels.

Conclusions

We carried out a genome-wide analysis on patterns of the classified polytopic membrane protein families and analyzed the distribution of conserved amino acids and motifs in the transmembrane helix regions in these families.

     

A novel family of P-loop NTPases with an unusual phyletic distribution and transmembrane segments inserted within the NTPase domain

Background

Recent sequence-structure studies on P-loop-fold NTPases have substantially advanced the existing understanding of their evolution and functional diversity. These studies provide a framework for characterization of novel lineages within this fold and prediction of their functional properties.

Results

Using sequence profile searches and homology-based structure prediction, we have identified a previously uncharacterized family of P-loop NTPases, which includes the neuronal membrane protein and receptor tyrosine kinase substrate Kidins220/ARMS, which is conserved in animals, the F-plasmid PifA protein involved in phage T7 exclusion, and several uncharacterized bacterial proteins. We refer to these (predicted) NTPases as the KAP family, after Kidins220/ARMS and PifA. The KAP family NTPases are sporadically distributed across a wide phylogenetic range in bacteria but among the eukaryotes are represented only in animals. Many of the prokaryotic KAP NTPases are encoded in plasmids and tend to undergo disruption to form pseudogenes. A unique feature of all eukaryotic and certain bacterial KAP NTPases is the presence of two or four transmembrane helices inserted into the P-loop NTPase domain. These transmembrane helices anchor KAP NTPases in the membrane such that the P-loop domain is located on the intracellular side. We show that the KAP family belongs to the same major division of the P-loop NTPase fold with the AAA+, ABC, RecA-like, VirD4-like, PilT-like, and AP/NACHT-like NTPase classes. In addition to the KAP family, we identified another small family of predicted bacterial NTPases, with two transmembrane helices inserted into the P-loop domain. This family is not specifically related to the KAP NTPases, suggesting independent acquisition of the transmembrane helices.

Conclusions

We predict that KAP family NTPases function principally in the NTP-dependent dynamics of protein complexes, especially those associated with the intracellular surface of cell membranes. Animal KAP NTPases, including Kidins220/ARMS, are likely to function as NTP-dependent regulators of the assembly of membrane-associated signaling complexes involved in neurite growth and development. One possible function of the prokaryotic KAP NTPases might be in the exclusion of selfish replicons, such as viruses, from the host cells. Phylogenetic analysis and phyletic patterns suggest that the common ancestor of the animals acquired a KAP NTPase via lateral transfer from bacteria. However, an earlier transfer into eukaryotes followed by multiple losses in several eukaryotic lineages cannot be ruled out.     

Multi-way metamodelling facilitates insight into the complex input-output maps of nonlinear dynamic models

Background

The physical periphery of a biological cell is mainly described by signaling pathways which are triggered by transmembrane proteins and receptors that are sentinels to control the whole gene regulatory network of a cell. However, our current knowledge about the gene regulatory mechanisms that are governed by extracellular signals is severely limited.

Results

The purpose of this paper is three fold. First, we infer a gene regulatory network from a large-scale B-cell lymphoma expression data set using the C3NET algorithm. Second, we provide a functional and structural analysis of the largest connected component of this network, revealing that this network component corresponds to the peripheral region of a cell. Third, we analyze the hierarchical organization of network components of the whole inferred B-cell gene regulatory network by introducing a new approach which exploits the variability within the data as well as the inferential characteristics of C3NET. As a result, we find a functional bisection of the network corresponding to different cellular components.

Conclusions

Overall, our study allows to highlight the peripheral gene regulatory network of B-cells and shows that it is centered around hub transmembrane proteins located at the physical periphery of the cell. In addition, we identify a variety of novel pathological transmembrane proteins such as ion channel complexes and signaling receptors in B-cell lymphoma.     

Protein Functional Surfaces: Global Shape Matching and Local Spatial Alignments of Ligand Binding Sites

Background

Protein surfaces comprise only a fraction of the total residues but are the most conserved functional features of proteins. Surfaces performing identical functions are found in proteins absent of any sequence or fold similarity. While biochemical activity can be attributed to a few key residues, the broader surrounding environment plays an equally important role.

Results

We describe a methodology that attempts to optimize two components, global shape and local physicochemical texture, for evaluating the similarity between a pair of surfaces. Surface shape similarity is assessed using a three-dimensional object recognition algorithm and physicochemical texture similarity is assessed through a spatial alignment of conserved residues between the surfaces. The comparisons are used in tandem to efficiently search the Global Protein Surface Survey (GPSS), a library of annotated surfaces derived from structures in the PDB, for studying evolutionary relationships and uncovering novel similarities between proteins.

Conclusion

We provide an assessment of our method using library retrieval experiments for identifying functionally homologous surfaces binding different ligands, functionally diverse surfaces binding the same ligand, and binding surfaces of ubiquitous and conformationally flexible ligands. Results using surface similarity to predict function for proteins of unknown function are reported. Additionally, an automated analysis of the ATP binding surface landscape is presented to provide insight into the correlation between surface similarity and function for structures in the PDB and for the subset of protein kinases.     

Efficient unfolding pattern recognition in single molecule force spectroscopy data

Background

Single-molecule force spectroscopy (SMFS) is a technique that measures the force necessary to unfold a protein. SMFS experiments generate Force-Distance (F-D) curves. A statistical analysis of a set of F-D curves reveals different unfolding pathways. Information on protein structure, conformation, functional states, and inter- and intra-molecular interactions can be derived.

Results

In the present work, we propose a pattern recognition algorithm and apply our algorithm to datasets from SMFS experiments on the membrane protein bacterioRhodopsin (bR). We discuss the unfolding pathways found in bR, which are characterised by main peaks and side peaks. A main peak is the result of the pairwise unfolding of the transmembrane helices. In contrast, a side peak is an unfolding event in the alpha-helix or other secondary structural element. The algorithm is capable of detecting side peaks along with main peaks. Therefore, we can detect the individual unfolding pathway as the sequence of events labeled with their occurrences and co-occurrences special to bR's unfolding pathway. We find that side peaks do not co-occur with one another in curves as frequently as main peaks do, which may imply a synergistic effect occurring between helices. While main peaks co-occur as pairs in at least 50% of curves, the side peaks co-occur with one another in less than 10% of curves. Moreover, the algorithm runtime scales well as the dataset size increases.

Conclusions

Our algorithm satisfies the requirements of an automated methodology that combines high accuracy with efficiency in analyzing SMFS datasets. The algorithm tackles the force spectroscopy analysis bottleneck leading to more consistent and reproducible results.     

Molecular analysis of the phosphoenolpyruvate-dependent l-sorbose: phosphotransferase system from Klebsiella pneumoniae and of its multidomain structure

We have cloned a 3.4 kb DNA fragment from the chromosome of Klebsiella pneumoniae that codes for a phosphoenolpyruvate-dependent l-sorbose: phosphotransferase system (PTS). The cloned fragment was sequenced and four open reading frames coding for 135 (sorF), 164 (sorB), 266 (sorA) and 274 (sorM) amino acids, respectively, were found. The corresponding proteins could be detected in a T7 overexpression system, which yielded molecular masses of about 14000 for SorF, 19000 for SorB, 25000 for SorA and 27000 for SorM. SorF and SorB have all the characteristics of soluble and intracellular proteins in accordance with their functions as EIIA^Sor and EIIB^Sor domains of the l-sorbose PTS. SorA and SorM, by contrast, are strongly hydrophobic, membrane-bound proteins with two to five putative transmembrane helices that alternate with a series of hydrophilic loops. They correspond to domains EIIC^Sor and EIID^Sor. The four proteins of the l-sorbose PTS resemble closely (27%–60%) the four subunits of a d-fructose PTS (EIIA^Lev, EIIB^Lev, EIIC^Lev, and EIID^Lev) from Bacillus subtilis and the three subunits of the d-mannose PTS (EIIA,B^Man, EIIC^Man, and EIID^Man) from Escherichia coli K-12. The three systems constitute a new PTS family, and sequence comparisons revealed highly conserved structures for the membranebound proteins. A consensus sequence for the membrane proteins was used to postulate a model for their integration into the membrane.     

High-frequency irreversible electroporation (H-FIRE) for non-thermal ablation without muscle contraction

Background

Therapeutic irreversible electroporation (IRE) is an emerging technology for the non-thermal ablation of tumors. The technique involves delivering a series of unipolar electric pulses to permanently destabilize the plasma membrane of cancer cells through an increase in transmembrane potential, which leads to the development of a tissue lesion. Clinically, IRE requires the administration of paralytic agents to prevent muscle contractions during treatment that are associated with the delivery of electric pulses. This study shows that by applying high-frequency, bipolar bursts, muscle contractions can be eliminated during IRE without compromising the non-thermal mechanism of cell death.

Methods

A combination of analytical, numerical, and experimental techniques were performed to investigate high-frequency irreversible electroporation (H-FIRE). A theoretical model for determining transmembrane potential in response to arbitrary electric fields was used to identify optimal burst frequencies and amplitudes for in vivo treatments. A finite element model for predicting thermal damage based on the electric field distribution was used to design non-thermal protocols for in vivo experiments. H-FIRE was applied to the brain of rats, and muscle contractions were quantified via accelerometers placed at the cervicothoracic junction. MRI and histological evaluation was performed post-operatively to assess ablation.

Results

No visual or tactile evidence of muscle contraction was seen during H-FIRE at 250 kHz or 500 kHz, while all IRE protocols resulted in detectable muscle contractions at the cervicothoracic junction. H-FIRE produced ablative lesions in brain tissue that were characteristic in cellular morphology of non-thermal IRE treatments. Specifically, there was complete uniformity of tissue death within targeted areas, and a sharp transition zone was present between lesioned and normal brain.

Conclusions

H-FIRE is a feasible technique for non-thermal tissue ablation that eliminates muscle contractions seen in IRE treatments performed with unipolar electric pulses. Therefore, it has the potential to be performed clinically without the administration of paralytic agents.     

Correlation between amino acid residues converted by RNA editing and functional residues in protein three-dimensional structures in plant organelles

Background

In plant organelles, specific messenger RNAs (mRNAs) are subjected to conversion editing, a process that often converts the first or second nucleotide of a codon and hence the encoded amino acid. No systematic patterns in converted sites were found on mRNAs, and the converted sites rarely encoded residues located at the active sites of proteins. The role and origin of RNA editing in plant organelles remain to be elucidated.

Results

Here we study the relationship between amino acid residues encoded by edited codons and the structural characteristics of these residues within proteins, e.g., in protein-protein interfaces, elements of secondary structure, or protein structural cores. We find that the residues encoded by edited codons are significantly biased toward involvement in helices and protein structural cores. RNA editing can convert codons for hydrophilic to hydrophobic amino acids. Hence, only the edited form of an mRNA can be translated into a polypeptide with helix-preferring and core-forming residues at the appropriate positions, which is often required for a protein to form a functional three-dimensional (3D) structure.

Conclusion

We have performed a novel analysis of the location of residues affected by RNA editing in proteins in plant organelles. This study documents that RNA editing sites are often found in positions important for 3D structure formation. Without RNA editing, protein folding will not occur properly, thus affecting gene expression. We suggest that RNA editing may have conferring evolutionary advantage by acting as a mechanism to reduce susceptibility to DNA damage by allowing the increase in GC content in DNA while maintaining RNA codons essential to encode residues required for protein folding and activity.     

Are membrane proteins "inside-out" proteins?

One of the central paradigms of structural biology is that membrane proteins are "inside-out" proteins, in that they have a core of polar residues surrounded by apolar residues. This is the reverse of the characteristics found in water-soluble proteins. We have decided to test this paradigm, now that sufficient numbers of transmembrane alpha-helical structures are accessible to statistical analysis. We have analyzed the correlation between accessibility and hydrophobicity of both individual residues and complete helices. Our analyses reveal that hydrophobicity of residues in a transmembrane helical bundle does not correlate with any preferred location and that the hydrophilic vector of a helix is a poor indicator of the solvent exposed face of a helix. Neither polar nor hydrophobic residues show any bias for the exterior or the interior of a transmembrane domain. As a control, analysis of water-soluble helical bundles performed in a similar manner has yielded clear correlations between hydrophobicity and accessibility. We therefore conclude that, based on the data set used, membrane proteins as "inside-out" proteins is an unfounded notion, suggesting that packing of alpha-helices in membranes is better understood by maximization of van der Waal's forces, rather than by a general segregation of hydrophobicities driven by lipid exclusion.     

A hydrophobic spine stabilizes a surface-exposed α-helix according to analysis of the solvent-accessible surface area

Background

Most of hydrophilic and hydrophobic residues are thought to be exposed and buried in proteins, respectively. In contrast to the majority of the existing studies on protein folding characteristics using protein structures, in this study, our aim was to design predictors for estimating relative solvent accessibility (RSA) of amino acid residues to discover protein folding characteristics from sequences.

Methods

The proposed 20 real-value RSA predictors were designed on the basis of the support vector regression method with a set of informative physicochemical properties (PCPs) obtained by means of an optimal feature selection algorithm. Then, molecular dynamics simulations were performed for validating the knowledge discovered by analysis of the selected PCPs.

Results

The RSA predictors had the mean absolute error of 14.11% and a correlation coefficient of 0.69, better than the existing predictors. The hydrophilic-residue predictors preferred PCPs of buried amino acid residues to PCPs of exposed ones as prediction features. A hydrophobic spine composed of exposed hydrophobic residues of an α-helix was discovered by analyzing the PCPs of RSA predictors corresponding to hydrophobic residues. For example, the results of a molecular dynamics simulation of wild-type sequences and their mutants showed that proteins 1MOF and 2WRP_H16I (Protein Data Bank IDs), which have a perfectly hydrophobic spine, have more stable structures than 1MOF_I54D and 2WRP do (which do not have a perfectly hydrophobic spine).

Conclusions

We identified informative PCPs to design high-performance RSA predictors and to analyze these PCPs for identification of novel protein folding characteristics. A hydrophobic spine in a protein can help to stabilize exposed α-helices.

     

The pro-apoptotic Bcl-2 family member tBid localizes to mitochondrial contact sites

Background

Following cleavage by caspase 8, the C-terminus of Bid translocates from the cytosol to the mitochondria that is dependent upon structures formed by the mitochondrial-specific lipid cardiolipin. Once associated with mitochondria, truncated Bid (tBid) causes the potent release of cytochrome c, endonuclease G, and smac.

Results

We investigated whether tBid localizes specifically to the contact sites of mitochondria purported to be rich in cardiolipin. A point mutation changing the glycine at position 94 to glutamic acid in the BH3 domain of tBid (tBid_G94E) was principally used because mitochondria treated with this mutant tBid displayed better preservation of the outer membrane than those treated with wild type tBid. Additionally, tBid_G94E lowers the cytochrome c releasing activity of tBid without affecting its targeting to mitochondria. Electron microscope tomography coupled with immunogold labeling was used as a new hybrid technique to investigate the three-dimensional distributions of tBid and tBid_G94E around the mitochondrial periphery. The statistics of spatial point patterns was used to analyze the association of these proteins with contact sites.

Conclusions

Immunoelectron tomography with statistical analysis confirmed the preferential association of tBid with mitochondrial contact sites. These findings link these sites with cardiolipin in tBid targeting and suggest a role for Bcl-2 family members in regulating the activity of contact sites in relation to apoptosis. We propose a mechanism whereby Bcl-2 proteins alter mitochondrial function by disrupting cardiolipin containing contact site membranes.     

Combination of hydrogel nanoparticles and proteomics to reveal secreted proteins associated with decidualization of human uterine stromal cells

Background

Identification of secreted proteins of low abundance is often limited by abundant and high molecular weight (MW) proteins. We have optimised a procedure to overcome this limitation.

Results

Low MW proteins in the conditioned media of cultured cells were first captured using dual-size exclusion/affinity hydrogel nanoparticles and their identities were then revealed by proteomics.

Conclusions

This technique enables the analysis of secreted proteins of cultured cells low MW and low abundance.     

FPGA accelerator for protein secondary structure prediction based on the GOR algorithm

Background

Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases.

Results

The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes.

Conclusions

Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.