The Structure of a Type 3 Secretion System (T3SS) Ruler Protein Suggests a Molecular Mechanism for Needle Length Sensing

The type 3 secretion system (T3SS) and the bacterial flagellum are related pathogenicity-associated appendages found at the surface of many disease-causing bacteria. These appendages consist of long tubular structures that protrude away from the bacterial surface to interact with the host cell and/or promote motility. A proposed “ruler” protein tightly regulates the length of both the T3SS and the flagellum, but the molecular basis for this length control has remained poorly characterized and controversial. Using the Pseudomonas aeruginosa T3SS as a model system, we report the first structure of a T3SS ruler protein, revealing a “ball-and-chain” architecture, with a globular C-terminal domain (the ball) preceded by a long intrinsically disordered N-terminal polypeptide chain. The dimensions and stability of the globular domain do not support its potential passage through the inner lumen of the T3SS needle. We further demonstrate that a conserved motif at the N terminus of the ruler protein interacts with the T3SS autoprotease in the cytosolic side. Collectively, these data suggest a potential mechanism for needle length sensing by ruler proteins, whereby upon T3SS needle assembly, the ruler protein''s N-terminal end is anchored on the cytosolic side, with the globular domain located on the extracellular end of the growing needle. Sequence analysis of T3SS and flagellar ruler proteins shows that this mechanism is probably conserved across systems.     

Mining Proteins with Non-Experimental Annotations Based on an Active Sample Selection Strategy for Predicting Protein Subcellular Localization

Subcellular localization of a protein is important to understand proteins’ functions and interactions. There are many techniques based on computational methods to predict protein subcellular locations, but it has been shown that many prediction tasks have a training data shortage problem. This paper introduces a new method to mine proteins with non-experimental annotations, which are labeled by non-experimental evidences of protein databases to overcome the training data shortage problem. A novel active sample selection strategy is designed, taking advantage of active learning technology, to actively find useful samples from the entire data pool of candidate proteins with non-experimental annotations. This approach can adequately estimate the “value” of each sample, automatically select the most valuable samples and add them into the original training set, to help to retrain the classifiers. Numerical experiments with for four popular multi-label classifiers on three benchmark datasets show that the proposed method can effectively select the valuable samples to supplement the original training set and significantly improve the performances of predicting classifiers.     

Sequential Formation of Vaccinia Virus Proteins and Viral Deoxyribonucleic Acid Replication

In vaccinia virus-infected cell cultures, cellular protein synthesis was inhibited 50% at 2 hr postinfection (PI) and 80 to 90% by 4 hr PI. Input virus was responsible for this inhibition. Five early proteins, coded for by the viral genome, could be detected at 2 to 3 hr PI. Normally, their synthesis did not continue beyond 6 hr PI, at which time synthesis of a different set of proteins began. When DNA replication was blocked, synthesis of these early proteins continued until 9 to 12 hr PI. The bulk of the proteins which were incorporated into mature virus were synthesized at 8 hr PI and thereafter. The time of their formation was close to the time at which virus maturation occurred. However, 15% of the protein found in mature virus was synthesized early in the infectious cycle. The quantity of “early viral protein” which was not incorporated into mature virus was almost as large as the quantity of viral protein which did appear in mature virus. The “early” and “late” proteins could be shown to have separate and distinct immunological properties. The role of this large quantity of “early” protein is discussed.     

The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics

It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks. However, most of the focus in network studies has been on highly connected proteins (“hubs”). As a complementary notion, it is possible to define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many “shortest paths” going through them, analogous to major bridges and tunnels on a highway map). Bottlenecks are, in fact, key connector proteins with surprising functional and dynamic properties. In particular, they are more likely to be essential proteins. In fact, in regulatory and other directed networks, betweenness (i.e., “bottleneck-ness”) is a much more significant indicator of essentiality than degree (i.e., “hub-ness”). Furthermore, bottlenecks correspond to the dynamic components of the interaction network—they are significantly less well coexpressed with their neighbors than nonbottlenecks, implying that expression dynamics is wired into the network topology.     

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation.     

Structural Basis for Ligand Regulation of the Fatty Acid-binding Protein 5, Peroxisome Proliferator-activated Receptor β/δ (FABP5-PPARβ/δ) Signaling Pathway

Fatty acid-binding proteins (FABPs) are a widely expressed group of calycins that play a well established role in solubilizing cellular fatty acids. Recent studies, however, have recast FABPs as active participants in vital lipid-signaling pathways. FABP5, like its family members, displays a promiscuous ligand binding profile, capable of interacting with numerous long chain fatty acids of varying degrees of saturation. Certain “activating” fatty acids induce the protein''s cytoplasmic to nuclear translocation, stimulating PPARβ/δ transactivation; however, the rules that govern this process remain unknown. Using a range of structural and biochemical techniques, we show that both linoleic and arachidonic acid elicit FABP5''s translocation by permitting allosteric communication between the ligand-sensing β2 loop and a tertiary nuclear localization signal within the α-helical cap of the protein. Furthermore, we show that more saturated, nonactivating fatty acids inhibit nuclear localization signal formation by destabilizing this activation loop, thus implicating FABP5 specifically in cis-bonded, polyunsaturated fatty acid signaling.     

Pathological States and Criminal Responsibility

The doctor is embarrassed in court when asked to testify to the effects of illness on a defendant''s capability “of appreciating the nature and quality of an act or omission or of knowing that an act or omission is wrong”. The source of his difficulty is traced to the legal concepts of “guilt”, “crime” and “punishment” which imply a legal view of man at variance with our modern biological view. To abolish this discrepancy we need not accept a medical model for criminal law where “crime” is analogous to “disease”, and “punishment” to “treatment”. A pragmatic approach to the handling of the criminal could exclude the notions of “guilt” and “punishment” and yet fulfil the rational goals of protecting society from the criminal and of compensating his victims.     

Metformin and Resveratrol Inhibited High Glucose-Induced Metabolic Memory of Endothelial Senescence through SIRT1/p300/p53/p21 Pathway

Endothelial senescence plays crucial roles in diabetic vascular complication. Recent evidence indicated that transient hyperglycaemia could potentiate persistent diabetic vascular complications, a phenomenon known as “metabolic memory.” Although SIRT1 has been demonstrated to mediate high glucose-induced endothelial senescence, whether and how “metabolic memory” would affect endothelial senescence through SIRT1 signaling remains largely unknown. In this study, we investigated the involvement of SIRT1 axis as well as the protective effects of resveratrol (RSV) and metformin (MET), two potent SIRT1 activators, during the occurrence of “metabolic memory” of cellular senescence (senescent “memory”). Human umbilical vascular endothelial cells (HUVECs) were cultured in either normal glucose (NG)/high glucose (HG) media for 6 days, or 3 days of HG followed by 3 days of NG (HN), with or without RSV or MET treatment. It was shown that HN incubation triggered persistent downregulation of deacetylase SIRT1 and upregulation of acetyltransferase p300, leading to sustained hyperacetylation (at K382) and activation of p53, and subsequent p53/p21-mediated senescent “memory.” In contrast, senescent “memory” was abrogated by overexpression of SIRT1 or knockdown of p300. Interestingly, we found that SIRT1 and p300 could regulate each other in response to HN stimulation, suggesting that a delicate balance between acetyltransferases and deacetylases may be particularly important for sustained acetylation and activation of non-histone proteins (such as p53), and eventually the occurrence of “metabolic memory.” Furthermore, we found that RSV or MET treatment prevented senescent “memory” by modulating SIRT1/p300/p53/p21 pathway. Notably, early and continuous treatment of MET, but not RSV, was particularly important for preventing senescent “memory.” In conclusion, short-term high glucose stimulation could induce sustained endothelial senescence via SIRT1/p300/p53/p21 pathway. RVS or MET treatment could enhance SIRT1-mediated signaling and thus protect against senescent “memory” independent of their glucose lowering mechanisms. Therefore, they may serve as promising therapeutic drugs against the development of “metabolic memory.”     

Effects of Biogents Sentinel Trap Field Placement on Capture Rates of Adult Asian Tiger Mosquitoes,Aedes albopictus

The Biogents® Sentinel (BGS) trap is the standard tool to monitor adult Aedes (Stegomyia) albopictus (Skuse) (Diptera: Culicidae), the Asian tiger mosquito. BGS traps are commonly placed in residential properties during surveillance operations, but locations within properties may have significant differences in ambient light, temperature, and humidity (e.g. between a sunlit lawn and shady underbrush). We examined the effect of BGS trap placement on Ae. albopictus capture rates in three residential properties in Monmouth County, New Jersey, USA. In each property we visually selected locations as shade, partial shade, and sun. Traps in “partial shade” locations were under vegetation and were exposed to filtered sunlight during some parts of the day while “shaded” locations were never exposed to direct sunlight. Locations defined as “sun” were exposed to direct sunlight for large parts of the day. We placed a BGS trap in each of the three location types and used small data loggers to measure temperature, relative humidity, and light exposure at each trap during a 24-hour deployment. To address temporal variability, we made seven separate measurements from 31 August to 22 September 2010. We found that “partial shade” and “full shade” locations did not differ but that “full sun” locations had significantly higher light exposure, higher temperature, and lower humidity. Importantly, Ae. albopictus catches (males, females, or both) were consistently and significantly over 3 times higher in traps located in shaded locations. To further investigate the effects of local temperature and humidity on surveillance we examined Ae. albopictus collections from 37 BGS traps fitted with data loggers and deployed weekly from August through mid October, during the 2009 season, in three urban sites in Mercer County, NJ. We confirmed that local climate influences capture rates and that Ae. albopictus surveillance projects need to monitor trap placement carefully for maximum efficiency.     

Rhomboids of Mycobacteria: Characterization Using an aarA Mutant of Providencia stuartii and Gene Deletion in Mycobacterium smegmatis

Background

Rhomboids are ubiquitous proteins with unknown roles in mycobacteria. However, bioinformatics suggested putative roles in DNA replication pathways and metabolite transport. Here, mycobacterial rhomboid-encoding genes were characterized; first, using the Providencia stuartii null-rhomboid mutant and then deleted from Mycobacterium smegmatis for additional insight in mycobacteria.

Methodology/Principal Findings

Using in silico analysis we identified in M. tuberculosis genome the genes encoding two putative rhomboid proteins; Rv0110 (referred to as “rhomboid protease 1”) and Rv1337 (“rhomboid protease 2”). Genes encoding orthologs of these proteins are widely represented in all mycobacterial species. When transformed into P. stuartii null-rhomboid mutant (ΔaarA), genes encoding mycobacterial orthologs of “rhomboid protease 2” fully restored AarA activity (AarA is the rhomboid protein of P. stuartii). However, most genes encoding mycobacterial “rhomboid protease 1” orthologs did not. Furthermore, upon gene deletion in M. smegmatis, the ΔMSMEG_4904 single mutant (which lost the gene encoding MSMEG_4904, orthologous to Rv1337, “rhomboid protease 2”) formed the least biofilms and was also more susceptible to ciprofloxacin and novobiocin, antimicrobials that inhibit DNA gyrase. However, the ΔMSMEG_5036 single mutant (which lost the gene encoding MSMEG_5036, orthologous to Rv0110, “rhomboid protease 1”) was not as susceptible. Surprisingly, the double rhomboid mutant ΔMSMEG_4904–ΔMSMEG_5036 (which lost genes encoding both homologs) was also not as susceptible suggesting compensatory effects following deletion of both rhomboid-encoding genes. Indeed, transforming the double mutant with a plasmid encoding MSMEG_5036 produced phenotypes of the ΔMSMEG_4904 single mutant (i.e. susceptibility to ciprofloxacin and novobiocin).

Conclusions/Significance

Mycobacterial rhomboid-encoding genes exhibit differences in complementing aarA whereby it''s only genes encoding “rhomboid protease 2” orthologs that fully restore AarA activity. Additionally, gene deletion data suggests inhibition of DNA gyrase by MSMEG_4904; however, the ameliorated effect in the double mutant suggests occurrence of compensatory mechanisms following deletion of genes encoding both rhomboids.     

Assessing the accuracy of ancestral protein reconstruction methods

The phylogenetic inference of ancestral protein sequences is a powerful technique for the study of molecular evolution, but any conclusions drawn from such studies are only as good as the accuracy of the reconstruction method. Every inference method leads to errors in the ancestral protein sequence, resulting in potentially misleading estimates of the ancestral protein's properties. To assess the accuracy of ancestral protein reconstruction methods, we performed computational population evolution simulations featuring near-neutral evolution under purifying selection, speciation, and divergence using an off-lattice protein model where fitness depends on the ability to be stable in a specified target structure. We were thus able to compare the thermodynamic properties of the true ancestral sequences with the properties of “ancestral sequences” inferred by maximum parsimony, maximum likelihood, and Bayesian methods. Surprisingly, we found that methods such as maximum parsimony and maximum likelihood that reconstruct a “best guess” amino acid at each position overestimate thermostability, while a Bayesian method that sometimes chooses less-probable residues from the posterior probability distribution does not. Maximum likelihood and maximum parsimony apparently tend to eliminate variants at a position that are slightly detrimental to structural stability simply because such detrimental variants are less frequent. Other properties of ancestral proteins might be similarly overestimated. This suggests that ancestral reconstruction studies require greater care to come to credible conclusions regarding functional evolution. Inferred functional patterns that mimic reconstruction bias should be reevaluated.     

Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity

Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein–ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art “fixed backbone” design methods perform poorly on these tests, we develop a new “coupled moves” design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein – ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.     

Diffusion,Crowding & Protein Stability in a Dynamic Molecular Model of the Bacterial Cytoplasm

A longstanding question in molecular biology is the extent to which the behavior of macromolecules observed in vitro accurately reflects their behavior in vivo. A number of sophisticated experimental techniques now allow the behavior of individual types of macromolecule to be studied directly in vivo; none, however, allow a wide range of molecule types to be observed simultaneously. In order to tackle this issue we have adopted a computational perspective, and, having selected the model prokaryote Escherichia coli as a test system, have assembled an atomically detailed model of its cytoplasmic environment that includes 50 of the most abundant types of macromolecules at experimentally measured concentrations. Brownian dynamics (BD) simulations of the cytoplasm model have been calibrated to reproduce the translational diffusion coefficients of Green Fluorescent Protein (GFP) observed in vivo, and “snapshots” of the simulation trajectories have been used to compute the cytoplasm''s effects on the thermodynamics of protein folding, association and aggregation events. The simulation model successfully describes the relative thermodynamic stabilities of proteins measured in E. coli, and shows that effects additional to the commonly cited “crowding” effect must be included in attempts to understand macromolecular behavior in vivo.     

Ca2+ Binding Enhanced Mechanical Stability of an Archaeal Crystallin

Structural topology plays an important role in protein mechanical stability. Proteins with β-sandwich topology consisting of Greek key structural motifs, for example, I27 of muscle titin and ¹⁰FNIII of fibronectin, are mechanically resistant as shown by single-molecule force spectroscopy (SMFS). In proteins with β-sandwich topology, if the terminal strands are directly connected by backbone H-bonding then this geometry can serve as a “mechanical clamp”. Proteins with this geometry are shown to have very high unfolding forces. Here, we set out to explore the mechanical properties of a protein, M-crystallin, which belongs to β-sandwich topology consisting of Greek key motifs but its overall structure lacks the “mechanical clamp” geometry at the termini. M-crystallin is a Ca²⁺ binding protein from Methanosarcina acetivorans that is evolutionarily related to the vertebrate eye lens β and γ-crystallins. We constructed an octamer of crystallin, (M-crystallin)₈, and using SMFS, we show that M-crystallin unfolds in a two-state manner with an unfolding force ∼90 pN (at a pulling speed of 1000 nm/sec), which is much lower than that of I27. Our study highlights that the β-sandwich topology proteins with a different strand-connectivity than that of I27 and ¹⁰FNIII, as well as lacking “mechanical clamp” geometry, can be mechanically resistant. Furthermore, Ca²⁺ binding not only stabilizes M-crystallin by 11.4 kcal/mol but also increases its unfolding force by ∼35 pN at the same pulling speed. The differences in the mechanical properties of apo and holo M-crystallins are further characterized using pulling speed dependent measurements and they show that Ca²⁺ binding reduces the unfolding potential width from 0.55 nm to 0.38 nm. These results are explained using a simple two-state unfolding energy landscape.     

Design of multi-specificity in protein interfaces

Interactions in protein networks may place constraints on protein interface sequences to maintain correct and avoid unwanted interactions. Here we describe a “multi-constraint” protein design protocol to predict sequences optimized for multiple criteria, such as maintaining sets of interactions, and apply it to characterize the mechanism and extent to which 20 multi-specific proteins are constrained by binding to multiple partners. We find that multi-specific binding is accommodated by at least two distinct patterns. In the simplest case, all partners share key interactions, and sequences optimized for binding to either single or multiple partners recover only a subset of native amino acid residues as optimal. More interestingly, for signaling interfaces functioning as network “hubs,” we identify a different, “multi-faceted” mode, where each binding partner prefers its own subset of wild-type residues within the promiscuous binding site. Here, integration of preferences across all partners results in sequences much more “native-like” than seen in optimization for any single binding partner alone, suggesting these interfaces are substantially optimized for multi-specificity. The two strategies make distinct predictions for interface evolution and design. Shared interfaces may be better small molecule targets, whereas multi-faceted interactions may be more “designable” for altered specificity patterns. The computational methodology presented here is generalizable for examining how naturally occurring protein sequences have been selected to satisfy a variety of positive and negative constraints, as well as for rationally designing proteins to have desired patterns of altered specificity.     

Whole-Genome Survey of the Putative ATP-Binding Cassette Transporter Family Genes in Vitis vinifera

The ATP-binding cassette (ABC) protein superfamily constitutes one of the largest protein families known in plants. In this report, we performed a complete inventory of ABC protein genes in Vitis vinifera, the whole genome of which has been sequenced. By comparison with ABC protein members of Arabidopsis thaliana, we identified 135 putative ABC proteins with 1 or 2 NBDs in V. vinifera. Of these, 120 encode intrinsic membrane proteins, and 15 encode proteins missing TMDs. V. vinifera ABC proteins can be divided into 13 subfamilies with 79 “full-size,” 41 “half-size,” and 15 “soluble” putative ABC proteins. The main feature of the Vitis ABC superfamily is the presence of 2 large subfamilies, ABCG (pleiotropic drug resistance and white-brown complex homolog) and ABCC (multidrug resistance-associated protein). We identified orthologs of V. vinifera putative ABC transporters in different species. This work represents the first complete inventory of ABC transporters in V. vinifera. The identification of Vitis ABC transporters and their comparative analysis with the Arabidopsis counterparts revealed a strong conservation between the 2 species. This inventory could help elucidate the biological and physiological functions of these transporters in V. vinifera.