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Cold adaptation in proteins, at sequence & structural level

Cold adaptation in proteins, at sequence & structural level


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When looking for cold adaptation in unicellular eukaryotes there is not much work found. Most of the time general sequence comparative sequence analysis between marine mesophile & psychrophile also does not give clear results. If I am planning to study at structural level (homology modeling) will I get answers? What type of parameters can I look to study? Which proteins are expected to provide cold adaptation apart from ice binding or antifreeze proteins because IBP & AFP cant be found by sequence comparison. Is it possible to give some ideas regarding this?

Thanks


There are research groups working on this exact question; understanding cold adaptation in enzymes. You can read about this in several articles such as 'Computation of enzyme cold adaptation', or 'Molecular Structural Basis for the Cold Adaptedness of the Psychrophilic β-Glucosidase BglU in Micrococcus antarcticus', or 'Specific amino acids responsible for the cold adaptedness of Micrococcus antarcticus β-glucosidase BglU'

On a general level there are several sructural characteristics that are typically found. They are usually far more flexible (i.e. less salt-bridges and other such stabilising bonds). The flexibility come from having fewer strong bond between and within the polypeptide chain, and even containing disordered regions. The flexibility also means that they are usually far less stable, and more difficult to work with. They are industrially interesting, as developing enzymes that can work at low temperatures can reduce the cost of running reactions. This is essentially a step towards a greener-industry. There are also speculations about various ratios and abundance of the amino acid types, and where they are located. You would have to read articles on specific proteins to investigate this.

From a practical view-point, cold adapted enzymes are usually isolated from arctic microorganisms and characterised in the lab - in order to determine their temperature tolerance. The structure of such enzymes are then solved (after lots of work) and form the basis for understanding cold-adaptation.

To answer the question more specifically, no its not realistic to know if something is coldadapted directly by looking at the protein sequence (on its own), this has to be determined experimentally in the lab. However, if the protein is from a cold adapted organism (typically arctic bacteria) there is reasons to assume it is cold adapted before you test it in the lab. You can also apply som bioinformatics (e.g. blast search) to determine if its related to cold adapted proteins. Also, If that specific type of protein that you are looking at, is well studies, you could also try to make homology models and see if its structurally similar to cold-adapted relatives or if it is more structurally similar to its mesophilic or even thermophilic counterparts. This is however very speculative, and i would not put too much weight on theoretically assumed adaptations - you should at minimum know that the protein of interest is from a cold adapted organisms, to even begin to look (computationally) on why and how it could be cold adapted.


Molecular characterization of cold adaptation based on ortholog protein sequences from Vibrionaceae species

A set of 298 protein families from psychrophilic Vibrio salmonicida was compiled to identify genotypic characteristics that discern it from orthologous sequences from the mesophilic Vibrio/Photobacterium branch of the gamma-Proteobacteria (Vibrionaceae family). In our comparative exploration we employed alignment based bioinformatical and statistical methods. Interesting information was found in the substitution matrices, and the pattern of asymmetries in the amino acid substitution process. Together with the compositional difference, they identified the amino acids Ile, Asn, Ala and Gln as those having the most psycrophilic involvement. Ile and Asn are enhanced whereas Gln and Ala are suppressed. The inflexible Pro residue is also suppressed in loop regions, as expected in a flexible structure. The dataset were also classified and analysed according to the predicted subcellular location, and we made an additional study of 183 intracellular and 65 membrane proteins. Our results revealed that the psychrophilic proteins have similar hydrophobic and charge contributions in the core of the protein as mesophilic proteins, while the solvent-exposed surface area is significantly more hydrophobic. In addition, the psychrophilic intracellular (but not the membrane) proteins are significantly more negatively charged at the surface. Our analysis supports the hypothesis of preference for more flexible amino acids at the molecular surface. Life in cold climate seems to be obtained through many minor structural modifications rather than certain amino acids substitutions.

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Background

Microorganisms that live under forbidding conditions are called extremophiles, whose discovery points out the unique adaptability of primitive life-forms. These microorganisms are grouped according to their optimal growth conditions in which they exist such as acidophiles (exhibiting optimum growth in acidic pH conditions), alkaliphiles (thriving in alkaline pH conditions), barophiles (surviving under great pressures), endoliths (living in deep inside rocks), halophiles (thriving in high salt concentrations), psychrophiles (optimal temperature below 20°C), and the thermophiles (optimal temperature between 45–80°C), hyperthermophiles (optimal temperature above 80°C) [1]. The largest coverage of known extremophile conditions of the earth's biosphere is below 10°C. For example, three fourths of earth is covered by oceans, which maintain an average temperature of one to three degrees centigrade. Furthermore, the vast land areas of the Arctic and Antarctic are permanently frozen throughout the year [1]. Other few examples of cryo habitats include cold deserts, high alpine soils, sea ice, cold caves, marine sediments, permafrost soils, glacier, snow etc.

The majority of known psychrophiles belong to varieties of archaea and bacteria, and a few species of yeast, fungi and algae [2]. The ability to thrive at life-endangering effects of low temperatures, close to freezing point of water, requires a vast array of adaptations from all their cellular components, including their membranes, energy-generating systems, protein synthesis machinery, biodegradative enzymes and the components responsible for nutrient uptake etc., to maintain metabolism, sustain growth and reproduction compatible with life in these low temperature conditions [3, 4]. Having evolved with special mechanisms, the psychrophiles successfully colonized these niches [2, 5]. Psychrophilic proteins display sequences and structures comparable with those of their meso and (hyper) thermophilic homolog's, especially enzymes with their ability to work efficiently as catalysts at low temperatures [6]. The thermolability of these proteins at moderate temperatures warrant tremendous industrial applications in biotechnology, bioremediation, food, textiles, detergents bio-catalysis under low-water conditions and detergents etc [5–9].

Due to above facts, historically starting from mid-1970's, much attention was paid mainly to sequence and structural attributes contributing to adaptation of proteins (mainly enzymes) to high temperature conditions. Many investigators have compared sequence and structure-based parameters among thermophilic and mesophilic proteins [10]. With the advent of pioneering efforts in late 1990's in solving three dimensional structures of cryophilic enzymes such as alpha-amylase [11] alkaline protease [12] triose phosphate isomerase [13] malate dehydrogenase [14] from Antarctic microorganisms, and due to handful of available structures in the protein data bank (PDB), groups have focused to address the structural basis of proteins in cold adaptation [4, 15–20].

The steady increase in sequencing of proteomes of extremophiles has opened many new avenues in understanding adaptations to extreme conditions [16, 21–25]. A comprehensive comparison of global amino acid preferences and substitution patterns as deduced from proteomes of different organisms is now possible [26–28]. Using homologous sequences, clustering along with various statistical methods we conducted an extensive analysis of proteomes of psychrophilic, mesophilic, thermophilic and hyperthermophilic microorganisms to examine a possible correlation of amino acid substitution patterns with adaptation to their respective optimal growth conditions. In this manuscript we discuss the results from comparative analysis of fully sequenced proteomes of six members from each of psychrophilic and mesophilic organisms.


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Structural Adaptation of Cold-Active RTX Lipase from Pseudomonas sp. Strain AMS8 Revealed via Homology and Molecular Dynamics Simulation Approaches

The psychrophilic enzyme is an interesting subject to study due to its special ability to adapt to extreme temperatures, unlike typical enzymes. Utilizing computer-aided software, the predicted structure and function of the enzyme lipase AMS8 (LipAMS8) (isolated from the psychrophilic Pseudomonas sp., obtained from the Antarctic soil) are studied. The enzyme shows significant sequence similarities with lipases from Pseudomonas sp. MIS38 and Serratia marcescens. These similarities aid in the prediction of the 3D molecular structure of the enzyme. In this study, 12 ns MD simulation is performed at different temperatures for structural flexibility and stability analysis. The results show that the enzyme is most stable at 0°C and 5°C. In terms of stability and flexibility, the catalytic domain (N-terminus) maintained its stability more than the noncatalytic domain (C-terminus), but the non-catalytic domain showed higher flexibility than the catalytic domain. The analysis of the structure and function of LipAMS8 provides new insights into the structural adaptation of this protein at low temperatures. The information obtained could be a useful tool for low temperature industrial applications and molecular engineering purposes, in the near future.

1. Introduction

A lipase (also known as triacylglycerol acylhydrolase (E.C 3.1.1.3)) is a serine hydrolase, which acts under aqueous conditions on the carboxyl ester bond of triacylglycerol to produce fatty acids and glycerol [1]. Lipases display common α/β-hydrolase folds that are also present in other hydrolases [2]. A typical lipase consists of an active site comprised of the catalytic triad of serine, glutamine/aspartate, and histidine [3].

Lipases are widely distributed among living organism, including bacteria, eukarya, and archaea as has been reported by Jaeger et al. [4]. Recently, lipases produced by psychrophilic bacteria have been studied because of their low optimum temperatures and high activities at very low temperatures. This is reportedly due to the inherent greater flexibility compared to mesophilic and thermophilic enzymes. These enzymes are severely impaired by an excess of rigidity. Additionally, peculiar properties of psychrophilic enzymes render them particularly useful as valuable tools for biotechnological purposes and for investigating the possible relationships between stability, flexibility, and specific activity [5, 6].

However, the adaptation of the enzyme at low temperatures is not fully understood because there has been little study on psychrophilic enzymes. Some features discovered by scientists include reduced numbers of salt bridges, slightly lower [Arg/(Arg + Lys)] ratios, reduced numbers of nonpolar residues, and higher numbers of exposed nonpolar residues [7]. In term of stability, psychrophilic enzymes are mostly unstable, as has been proven by various demonstrations, including fluorescence spectroscopy and other techniques. The enzyme tends to unfold at lower temperatures and calorimetric enthalpies [8]. Researchers suggest that one feature of these enzymes is higher numbers of nonpolar residues on their surfaces, which is responsible for the destabilization of the water structure surrounding the enzymes. There are also fewer arginine and proline residues this may increase the backbone flexibility. Note that research regarding the flexibility of the psychrophilic enzymes (using spectroscopic analysis, dynamic fluorescence quenching, and molecular dynamics simulations) has supported the idea that increased flexibility of psychrophilic enzymes contributed to the evolution of psychrophilic enzymes [9].

The importance of understanding the structural adaptations of extremozymes is underscored by their usefulness in various industrial applications. Until now, only a few extremophilic organisms, particularly psychrophiles, have been characterized and used as enzyme sources for industrial processes. Previously, a new strain of psychrophilic bacteria (designated strain AMS8) from Antarctic soil was screened for extracellular lipase activity and further analyzed using a molecular approach. Analysis of 16S rDNA showed that the strain AMS8 was similar to Pseudomonas sp. A lipase gene named LipAMS8 was successfully isolated from strain AMS8 with an open reading frame of 1,431 bp that encoded a polypeptide consisting of 476 amino acids. This crude lipase exhibited maximum activity at 20°C. Additional genetic studies revealed that LipAMS8 lacked an N-terminal signal peptide and contained a glycine- and aspartate-rich nonapeptide sequence at the C-terminus (experimental data).

In this study, the structure and function of lipase isolated from Pseudomonas sp. strain AMS8 are studied by using the structure predicted by using appropriate software. The structural adaptation of the enzyme at low temperatures is also studied using molecular dynamic simulation (MD simulation). Because it is a newly isolated enzyme, further study is needed to provide further understanding and reveal the potential of this psychrophilic enzyme, which may be used for the industrial, biotechnological, and fundamental purposes.

2. Materials and Methods

2.1. Software

The modeling and simulation of the enzyme’s predicted structure was run on a single PC (Intel (R) Core RM i5 CPU, 650 @ 3.2 GHz Co, 4.0 GB RAM) with the Windows 7 Ultimate operating system. The Yet Another Scientific Artificial Reality Application (YASARA) software [10] program was installed on the PC and was used for the molecular modeling and molecular dynamics (MD) simulation of the LipAMS8 predicted molecular structure.

2.2. Sequence Alignment of LipAMS8

The amino acid sequence of the LipAMS8 enzyme obtained from NCBI with Accession Number of ADM87309 consists of 476 amino acid residues a weight of 50 kDa is used for sequence analysis and modeling. The BLAST [11] program identified the homologous sequence that has high sequence identity with the LipAMS8 enzyme. The sequence with the highest score of sequence identity was chosen based on certain characteristics, including the type of origin and the availability of the solved 3D structures. Subsequently, multiple sequence alignment was carried out using the Biology Workbench [12] open software with the protein sequences of Serratia marcescens [13] and Pseudomonas sp. MIS38 [14] as both of these templates fulfilled the criteria needed as mentioned above.

2.3. Comparative Modeling and Validation

The templates used for the modeling were the crystal structures of the lipases obtained from Serratia marcescens [13] and Pseudomonas sp. MIS38 [14]. The atomic coordinates for the lipases Serratia marcescens (PDB ID: 2qua) and Pseudomonas sp. MIS38 (PDB ID: 2z8x) were obtained from the Protein Data Bank. The 3D model was generated using the YASARA [10]. The validation was performed with VERIFY3D [15] (to evaluate the fitness of the protein sequence in its current 3D structure) and Ramachandran plot [16] (to evaluate the geometrical aspects of the structure).

2.4. Molecular Dynamics (MD) Simulations at Various Temperatures

An MD simulation provided more information for detailed microscopic modeling on the molecular scale. The method follows the constructive approach by mimicking the behavior of molecules with the use of model systems. More powerful computers make it possible to study greater complexity with a realistic expectation of obtaining meaningful and useful information [17].

In this study, the MD simulation was performed in water. This involved the simulation of predicted model inside a trajectory box filled with 6940 molecules of solvent (including NaCl and water) and 467 LipAMS8 amino acid residues at the temperatures of 0°C, 5°C, 25°C, 37°C, 50°C, and 100°C. The density of water varies with temperature because the theoretical density of water depends on temperature.

The AMBER03 [18] force field parameter which implemented in the YASARA software was used for MD simulation. In each simulation, the initial model was minimized in order to reduce the contact area difference (CAD) between the protein model and the solvent molecule. During the minimization, conjugate-descent and steepest-descent algorithms were employed.

2.5. Simulation Analysis

The enzyme was studied using 240 saved steps for each simulation, which represents up to 6 nanoseconds of the production period. The analysis provides better understanding of the dynamic properties of the enzyme in water at different temperatures. The root mean square deviation (RMSd) was computed for the protein backbone and residues in order to check the stability of the trajectories. Additionally, the root mean square fluctuation (RMSf) was computed per residue in order to study the flexibility of the trajectories. Further analysis was performed by calculating the radius of gyration (Rgyration) and solvent accessible surface area (SASA) of the enzyme within the 6 nanoseconds (ns) of production time.

3. Results and Discussion

3.1. Comparative Modeling of LipAMS8
3.1.1. Modeling of LipAMS8

The sequence alignment searches for suitable templates to construct the 3D structure of the lipase AMS8 (LipAMS8), using comparative modeling. In this study, the crystal structures from Pseudomonas sp. MIS38 lipase and Serratia marcescens LipA (which score 80% and 69% for sequence identity) were chosen as the templates for modeling because both have highest scores of sequence identity when aligned with the LipAMS8 sequence. Both templates also have solved structures that can be obtained from the RSCB PDB Data Bank, which is important for predicting the 3D structure of the enzyme.

Two templates were used in the modeling of LipAMS8 in such a way that a model was formed from each template, as well as hybrid model which formed based on the best configuration of protein using the two templates chosen. However, the Z-score of each model is the most crucial parameter as the best Z-scores value obtained from each model obtained will denote for the accuracy and the quality of the model itself. Subsequently, the hybrid structure which is expected to be the best model for LipAMS8 is rejected due to poor Z-scores compared to the one obtained using only Pseudomonas sp. MIS38 as template.

The model was validated using the Ramachandran plot (Figure 2). The model had 89.5% of the residues residing in the most favored allowed region. Although the best scores are 90.0% and higher, the score obtained is considered to be acceptable because the model is a prediction model and not a crystal structure (i.e., the crystal structure is a fully solved structure compared to the predicted one). In a previous study, the serine of the catalytic triad, which resides in the negative/disallowed region of the Ramachandran plot, was proposed for the active conformation of the enzyme [19]. However, from this study, the Ser 207 of the catalytic triad of the LipAMS8 resides in the allowed region of the Ramachandran plot. This suggests that the enzyme is in the nonactive conformation, which is supported by the observable lid structure of the enzyme (closed conformation). Prediction of the active conformation of the enzyme also can be performed by observing the lid structure.

As compared to the template structure used to model LipAMS8 as shown in superimposed image in Figures 1(b) and 1(c), the predicted model of LipAMS8 also displays two main regions: the catalytic (green) and noncatalytic (blue) domains, as shown in Figure 1(a). The catalytic domain at the N-terminal is rich in α helices, while the noncatalytic domain at the C-terminal is dominated by β-strands. The catalytic domain also exhibits the presence of an α/β-hydrolase fold and catalytic triad, which includes Ser 207 , His 255 , and Asp 313 residues. The Ser 207 appears in the pentapeptide of G-X-S-X-G motifs (where X represents His 206 and Leu 208 ) and is located at the sharp turn between the β-strand and α-helix that resembles the nucleophilic elbow (normally present in the structural family of α/β-hydrolases) [20]. This suggests that the catalytic serine is aided by an oxyanion hole that stabilizes the negative charge generated during a nucleophilic attack by Ser Oγ [19].


(a)
(b)
(c)
(a)
(b)
(c) (a) LipAMS8 predicted 3D structure. The structure is composed of catalytic (green) and noncatalytic (blue) domains. The lid is colored in (red). (b) and (c) are superimposition of LipAMS8 structure (purple) with 2QUA (silver), and 2Z8X (yellow).


Ramachandran plot of the LipAMS8 3D structure. The structure scores 89.5%, meaning that 89.5% of the residues reside in the most favored region.

Generally, a lipase can exist in 2 conformational states: active and inactive. The lid conformation (open or closed) determines whether the enzyme is in the active or inactive conformation. The active conformation of the lipase is necessary for catalytic activity [19]. In this study, there is a lid-like structure that covers the catalytic site on the catalytic domain, which suggests the inactive conformation of the enzyme. Previous studies suggested that the active form of the enzyme has the lid open, allowing for the entrance of the substrate into the binding site for catalysis [21]. Thus, the closed conformation of the lid in this study meant that the nucleophilic Ser 207 could not attack the substrate. To open the lid, a water-oil interface is required so the lid can be modulated to uncover the catalytic site, providing access to the catalytic pocket for the substrates [19]. This enhances the activity of LipAMS8. Lid number 1 of LipAMS8 has high numbers of hydrophobic residues, including Ala 51 , Leu 53 , Val 54 , Val 57 , and Val 58 . This may allow efficient interaction between the hydrophobic lid residues with the lipid interface and contribute to easier lid opening.

From this study, the LipAMS8 consists of RTX motifs at the noncatalytic domain, suggesting the LipAMS8 is one of the RTX lipases that belong to the I.3 subfamily. This is further proven by the absence of cysteine residues [22]. Note that, the RTX motif is present in a variety of Gram-negative microorganisms [6]. This motif (comprised of glycine-rich nonapeptide sequences) is usually located at the carboxy-terminal portion of an enzyme [22]. In the 3D structure of LipAMS8, the sequence of RTX motifs constituted the parallel β-roll, which the first 6 residues of each motif form to attach calcium ions (Ca 2+ ). The remaining 3 residues build short β-strands, which result in the right-handed helix of the β-strand on the noncatalytic domain. The exact function of the RTX motifs remains obscure. However, they could be receptor binding domains, enhancers of secretion, and internal chaperones [6].

In the predicted model of LipAMS8, there are metal ions, including 6 atoms of Ca 2+ and 1 atom of Zn 2+ . Note that metal ions are required by a substantial fraction of enzymes to perform catalytic activity. Metal ions may also contribute to substrate activation and electrostatic stabilization of enzyme structure. In this study, Asp 128 , Asp 130 , and the ligand interact in the Zn 2+ binding sites. The Zn 2+ present in this LipAMS8 is not located in the catalytic site, so it may not contribute to the catalytic activity of the enzyme. Along with their contribution to catalytic activity, ions may ensure the local and overall structural stability, similar to the function of disulfides [23]. To conclude, there are metal ions in the predicted structure of LipAMS8, which may contribute to the overall structural stability. However, the enzyme is observed to have few or no arginines compared to lysines, low proline content, and a lack of a salt bridge, which reportedly contributes to the adaptation of psychrophilic enzymes at low temperatures. Additionally, the enzyme is predicted to have higher flexibility compared to mesophilic or thermophilic enzymes, allowing psychrophilic enzymes to be active at low energy costs [7].

3.1.2. Molecular Dynamic (MD) Simulations

MD simulation was performed to reveal changes in the structure, flexibility, and dynamics of LipAMS8 when simulated in elevated temperatures. The conformational sampling was limited to 12 ns. It has been suggested that LipAMS8 is a cold-active enzyme. Therefore, the structure should denature or unfold as the temperature increases from to 25°C to 100°C because of the disruption of the intermolecular forces, due to the increase in kinetic energy at elevated temperatures. However, in this study, there was no much unfolding of the secondary structure even when the enzyme is simulated at a higher temperature. This might be due to the limitation of conformational sampling, which is a maximum of 12 ns. The simulation time may need to be prolonged in order to see the structural changes.

3.1.3. Molecular Dynamics Simulation Data Analysis

The root mean square deviation (RMSd) values of the backbone atoms in the initial models assess the convergence of the protein system. In this study, the RMSd values from the minimized predicted model structure during MD simulation at 0°C, 5°C, 25°C, 37°C, 50°C, and 100°C are shown in Figure 3. At 5°C, the protein remains native-like and equilibrates with an average of 1.83 Å from the minimized structure. This indicates the stability of the enzyme at 5°C. Compared to 5°C, RMSd value at 0°C demonstrated that the 3D structure of the protein becomes unstable when it reaches 1000 ps. The RMSd value begins to fluctuate to values higher than 2 Å and even reached the value of 3.45 Å at 2525 ps. The value dropped to 1.807 Å at 3675 ps and rose to higher than 2 Å at 4000 ps. The unstable fluctuation of the RMSd is consistent with the difference in secondary structure elements observed during the simulation. However, the structural stability is observed after 5500 ps as the pattern of RMSd fluctuation is maintained and does not diverge more than 2 Å towards the end of simulation at 12 ns.


The fluctuation trend for the stability of the enzyme at 25°C, 37°C, 50°C, and 100°C increased in value throughout simulation with RMSd values remaining higher than 4.0 Å at 3000 ps for the rest of the simulation period. The unstable state of this enzyme is supported by experimental data, which found that the enzyme activity of LipAMS8 was reduced when the temperature was increased above 25°C. From the study, we deduce that at 25°C, 37°C, 50°C, and 100°C, the global 3D structure of the protein loses its native structure in order to adapt the molecule to changes in temperature and water density (the solvent). Thus, this result indicates that changes in the geometry coordinates and unfolding of the protein result from the reduced stability of the system.

We deduced that the most stable temperatures for LipAMS8 simulated in water are 0°C and 5°C as low temperature promotes less conformational movement maintaining structural integrity and stability. On the other hand, for temperatures between 25°C and 100°C, the enzyme structure is unstable and greatly deviates from its initial structure. The higher deviation of the enzyme structure when simulated in water at 25°C to 100°C may be related to the disruption of the molecular forces, which leads to higher kinetic activities of the molecules. However, the structural changes of the enzyme simulated in water are not that critical when compared to the structural changes that occur when the enzyme is simulated in an organic solvent [24].

Interestingly, average RMSd scores for 0°C and 5°C was seen to be stable throughout simulation. However, the stability was only adapted to catalytic domain of enzyme which is believed to be promoted by the presence of metal ions such as Zn 2+ and Ca 2+ . In other hands, the unstable state of this enzyme which is contributed from high flexibility of the noncatalytic domain at low temperature such as 0°C and 5°C however is somehow predictable since the enzyme has to adjust itself towards the low temperature whereby the kinetic energy is slowly decrease. If the enzyme does not increase their flexibility at this point, the structure may become too rigid and could not compensate for the decrease in catalysis temperature.

Figure 4 shows the root mean square fluctuations (RMSf) per residue for LipAMS8 simulated in water at temperatures from 0°C to 100°C. The average RMSf scores per residue for all temperatures vary from 1.12 Å to 4.1 Å. The highest fluctuation score is at 100°C. This result is equivalent to the effect of higher temperature on the flexibility of the enzyme. However, when comparing the flexibility of the enzyme at 0°C and 5°C, the RMSf value decreased from 1.43 to 1.12 Å. The higher flexibility of the enzyme at the lower temperature may suggest an adaptation of the enzyme to counteract the “freezing effect” as the temperatures dropped.


At the catalytic site, the RMSf scores do not indicate higher flexibility of the residues simulated in water at different temperatures. The flexibility is maintained at a value below the average RMSf score at different temperatures. This suggests the stability of the catalytic triad is supported by the figure of RMSd per residue.

Overall, the pattern of fluctuation per residue was similar to the pattern shown in the figure of RMSd per residue. Both figures show that higher fluctuation occurs at the noncatalytic domain. The most consistent fluctuation across temperatures occurred at residues 393–476, which reside in the noncatalytic domain whereby the RTX repeats are present. The flexibility of the domain may occur because of the presence of high glycine residues, which are known to introduce flexibility in protein structure because they lack side chains [25]. The increased flexibility of LipAMS8 (which originated from the low stability of the noncatalytic domain) may imply that the noncatalytic domain is the crucial part of the LipAMS8 molecular structure. This domain may contribute to high enzyme activity at low temperature.

An examination of the structural flexibility of the lid structure reveals that lid number 1, comprised of residues 51–58, does not have a higher than average RMSf score at any temperature. However, lid number 2, which comprised of residues 148–167, does have fluctuation at residues 148–153 at most temperatures. This proves the flexibility of the lid residue when simulated in water at various temperatures. This result led to the hypothesis that lid number 2 of LipAMS8 may be able to undergo a conformational transition under the right conditions, such as the presence of substrates. The residues 148–153 on lid number 2, which is more flexible, may acts like a holder that opens up the lid structure to expose the binding site in interfacial activation. In contrast to lid number 1, lid number 2 is more flexible. Thus, lid number 2 may be the first lid to open when substrates are present. The water-oil interface around the opening of first lid is less flexible for binding the substrate to the catalytic site. Note that the lid opening is a crucial step in a lipase with lid-like structure. The flexibility of the residues that reside in the lid structure is important for determining the motion rate of the lid, which plays an important role in the adaptation of enzyme function at low temperatures [7].

The structural flexibility observed on the structure of LipAMS8, simulated in water at various temperatures, may lessen if simulated in organic solvent. A previous study suggests higher rigidity of the enzyme in organic solution [26]. However, there is no much information available at the molecular level to accept or reject the proposal. To check the structural flexibility of the enzyme in both aqueous and nonaqueous environments, further simulation is needed to compare the structural basis of the enzyme.

The root mean square fluctuation (RMSf) analysis per residue and root mean square deviation per residue (RMSd) of the backbone atoms are used to analyze the atomic fluctuations of the predicted model of LipAMS8. Figure 5 shows the RMSd per residue at 0°C, 5°C, 25°C, 37°C, 50°C, and 100°C. The average RMSd for all residues, including the terminal residue, qualitatively measures the protein flexibility for the relationship between protein conformational flexibility and dynamics.


From the data, the RMSd average values of residues are almost the same between 0°C and 5°C. However, at 25°C, 37°C, 50°C, and 100°C, the RMSd average values increase to 6.29 Å. The pattern of the RMSd average values of residues is similar to the average values of root mean square fluctuation (RMSf) at all temperatures.

The deviation of the structural geometry of the enzyme mainly occurred at the noncatalytic domain. The RMSd values per residue at residues 412–425 and 436–470 are higher than the average score of RMSd at each temperature. From this, the destabilization of the enzyme does not involve the whole protein as proposed by one study [19]. Instead, the destabilization of the enzyme may involve a portion of the enzyme (as observed in this study). Additionally, the data also rejected the postulate that the destabilization of the enzyme mostly occurs at the catalytic domain [8]. The destabilization of the enzyme mostly occurs on the noncatalytic domain this may be caused by the presence of residues that cause a loss in stability of the enzyme 3D structure. Interestingly,

-roll is proposed to maintain the stability of Pseudomonas sp. MIS38. Deletion, alteration, and mutation on this -roll which is formed by the presence of RTX motifs and Ca 2+ would cause the structural conformation changes and denaturation of the enzyme. However, we proposed that actually shorter/lesser number of RTX repeats, less number of metal ions in this counterpart of Pseudomonas sp. MIS38, may be the reason why LipAMS8 is able to adapt in extremely cold environment.

Study of the catalytic domain shows that Asp 128 and Asp 130 , which interact with the Zn 2+ , have RMSd per residue values higher than the average scores of RMSd at each temperature. Thus, Asp 128 and Asp 130 are among those residues that fluctuate and mobilize the adaptation to temperature. However, the ratios of fluctuation of Asp 128 and Asp 130 to the average scores of the RMSd at each temperature decrease as the temperature increases. This implies higher interaction between metals and Asp 128 and Asp 130 at higher temperatures. This result strongly agrees with a previous study, which suggested that Zn 2+ promotes structural stabilization in an active conformation of the enzyme at elevated temperatures [27]. This result suggests a higher probability of adaptation of the enzyme at higher temperatures, especially in the catalytic domain because Zn 2+ stabilizes the enzyme structure.

As depicted from Figure 4, the scores for those residues that interact with Ca 2+ in the catalytic domain are maintained. This indicated that the metal contributes to stabilizing the catalytic domain so that the structure does not deviate from its initial structure. This result agrees with the function of Ca 2+ in the structural stability of the lipase proposed in a previous study of the B. glumae lipase [28]. Experimental data, on the effect of calcium on LipAMS8 activity, also supported the idea that Ca 2+ may promote structural stability of the enzyme. Thus, the enzymatic properties are maintained and the catalytic activity is improved to provide a greater yield. In contrast to the residues that interact with Ca 2+ at the catalytic domain, Ca 2+ in the noncatalytic domain has higher values of RMSd and RMSf, which indicates destabilization and flexibility of the residue. The Ca 2+ contribution on the stability of the residue does not agree with the suggestion that it promotes stability. The scores of RMSd and RMSf of the residue that interacts with Ca 2+ in the noncatalytic domain may be due to the process of adaptation from Ca 2+ so that the catalytic domain remains stable. This prevents the catalytic domain, which is responsible for catalytic activity, from being unfolded and dysfunction due to changes in the structural stability and configuration.

The radius of gyration (Rgyration) of the enzyme at different temperatures within the trajectories at 12 ns is shown in Figure 6. The parameter provides information on the tendency of the protein structures to expand during a dynamic simulation. At 5°C, the score of Rgyration is maintained throughout the simulation compared to the Rgyration score of the enzyme when simulated at higher and lower temperatures. The highest score of radius of gyration of LipAMS8 is at 25°C the score increased to 27.128 Å within the 12 ns of simulation. This is followed by other temperatures’ scores except for the score at 5°C. This indicates the adaptation of the enzyme structure to prevent loss of the native compactness of the structure at low temperature. In general, the result is proportional to the deviation of the enzyme structure, as indicated in Figure 3. While SASA indicates the transfer of free energy required to move a protein from aqueous to nonpolar solvent [29], as exhibited in Figure 7, the SASA scores at 5°C and 0°C show the fluctuation pattern, which is maintained throughout the 12 ns of simulation. Compared to 25°C, the figure increases, which indicates unfolding of enzyme within the simulation period. The unfolding of enzyme at this temperature is proportional to the structural changes of enzyme’s secondary structure. The increase in SASA score is also observed at the temperatures of 37°C, 50°C, and 100°C.


Materials and Methods

Protein overexpression and purification

The EaBglA-pET28a expression vector was transformed into Escherichia coli BL21(DE3) cells (Agilent Technologies, Santa Clara, USA). The cells were grown in 1L of LB medium at 37 °C and protein expression was induced with 0.4 mM isopropyl -D-thiogalactopyranoside (IPTG) at 37 °C for 3 h. The cells were harvested by centrifugation at 7,000 xg (20 min, 4 °C), resuspended in buffer A (20 mM sodium phosphate, 500 mM NaCl, 20 mM imidazole, pH 7.5), supplemented with 1 mM PMSF, and lysed by lysozyme treatment followed by sonication. The cell extract was clarified by centrifugation (20,000 xg, 30 min, 4 °C) and the supernatant was applied onto 5 mL Hi-Trap chelating HP column (GE Healthcare Biosciences, Pittsburgh, USA) coupled to an ÄKTA system (GE Healthcare Biosciences, Pittsburgh, USA) and pre-equilibrated with buffer A. The bound proteins were eluted with a nonlinear gradient of buffer B (20 mM sodium phosphate, 500 mM NaCl, 500 mM imidazole, pH 7.5). The fractions with β-glucosidase activity were pooled, concentrated to 5 mL using Amicon Ultra centrifugal units and submitted to size-exclusion chromatography using a Superdex 75 16/60 column (GE Healthcare Biosciences, Pittsburgh, USA) previously equilibrated with 20 mM sodium phosphate, 150 mM NaCl, pH 7.5, at a flow rate of 0.5 mL/min. The tetrameric and monomeric forms were successfully separated in two different peaks by this chromatographic step and showed high purity according to SDS-PAGE analysis. Protein concentration was estimated by A280nm using the extinction coefficient of the 110,030 M −1 cm −1 .

Biochemical enzyme assays

Enzyme activity was measured using the colorimetric substrate 4-nitrophenyl β-D-glucopyranoside (pNPG, Sigma-Aldrich Co, St. Louis, USA). Experiments were carried out in triplicate in 100 μL reactions at substrate saturating conditions (0.5 mM pNPG) in 40 mM sodium phosphate buffer pH 7.0. The final enzyme concentration was 20 nM. The reactions were incubated for 10 min at optimum conditions for catalytic activity (30 °C and pH 7.0) and stopped with 100 μL of 1 M sodium carbonate (Na2CO3). The enzyme activity was measured spectrophotometrically at 405 nm monitoring the release of p-initrophenol using an Infinite® 200 PRO microplate reader (TECAN Group Ltd., Männedorf, Switzerland). The measurements were expressed as relative activity (%) considering the maximum catalytic activity observed for the biological unit of the enzyme (tetramer).

Circular Dichroism

Circular Dichroism spectroscopy was employed to assess the global conformation of EaBglA in both tetrameric and monomeric conformations. CD measurements were acquired on a JASCO J-815 CD spectrometer controlled by a CDF-426S/15 Peltier temperature control system (Jasco Analytical Instruments, Oklahoma, EUA). A quartz cuvette with a 1-cm path length was used for all CD experiments and each spectrum was an average of at least three scans. Protein concentration was 5.8 μM (for tetramer and monomer) in 20 mM sodium phosphate, 150 mM NaCl, pH 7.5. All spectra were obtained at 20 °C in the range 200–260 nm with a bandwidth of 2 nm and a response time of 4 s/nm. CD data were buffer subtracted and normalized to molar residual ellipticity allowing the comparison between the forms.

Dynamic light scattering

Hydrodynamic radius (Rh) of the monomeric form of EaBglA was determined by Dynamic Light Scattering (DLS). Data were recorded at 20 °C on a Malvern Zetasizer Nano ZS 90 (Malvern Instruments, Worcestershire, UK) with a 633 nm laser, in a quartz cell with a scattering angle of 90°. The samples purified from the size-exclusion chromatography were analyzed in different concentrations (0.3 to 1.2 mg/mL) and the hydrodynamic radii were obtained after the average of 20 runs from the extrapolation of the translational diffusion coefficient (Dt) according to the Stokes–Einstein equation.

Analytical ultracentrifugation (AUC)

Sedimentation velocity (SV) experiments were conducted using a Beckman Optima XL-A analytical ultracentrifuge (Beckman Coulter Inc, Brea, EUA). Data were collected at 35,000 rpm and 20 °C using the absorbance optical system for both 220 and 280 nm detections. EaBglA was prepared in different concentrations (0.2, 0.4 and 1 mg/mL) in 20 mM sodium phosphate, 150 mM NaCl, pH 7.4. The SV scans were analyzed using the c(s) method in the SEDFIT program (v14.4d) 36 in order to determine the molecular mass of the protein. A conventional c(s) distribution was applied with a fixed regularization confidence level of 0.95 and the frictional ratio (ƒ/ƒ0) used as a regularization parameter. The standard sedimentation coefficients (s20,w) were determined by the maximum of the peaks of the continuous c(S) curves after corrections to eliminate the interferences caused by the buffer viscosity, density and temperature (ρ = 1.0039 g/mL and η = 0.0102643 Poise were obtained by the SEDNTERP program). The s°20,w value at infinite dilution was obtained by the linear regression of s20,w as a function of protein concentration 37 .

Small angle X-ray scattering

Small angle X-ray scattering (SAXS) measurements were performed using a monochromatic X-ray beam (λ = 1.488 Å) from the D01A-SAXS2 beamline at the Brazilian Synchrotron Light Laboratory (LNLS, Campinas, Brazil). EaBglA samples were prepared in 20 mM sodium phosphate, 150 mM NaCl, pH 7.4 at the concentrations of 1 and 2 mg/mL. The samples were centrifuged for 30 min at 23,000 xg and 4 °C to remove potential aggregates before all SAXS experiments. The sample-to-detector distance was set to 1000 mm to obtain the range of the scattering vector (q) from 0.013 to 0.33 Å −1 , where q means the magnitude of the q-vector defined by q = 4π sinθ/λ (2θ is the scattering angle). The samples were analyzed at 20 °C in 1-mm path-length mica cells and the scattering profiles were recorded in ten successive frames (each of 10 s duration) to monitor radiation damage and beam stability. The obtained SAXS curves were buffer subtracted and integrated using the FIT2D program 38 . The radius of gyration (Rg) was determined from the Guinier equation 39 and by indirect Fourier transform method using the GNOM package 40 . The GNOM program was also used to generate the particle distance distribution p(r) and the maximum diameter, Dmax. The DAMMIN program 41 was applied to obtain ab initio models for EaBglA (dummy atom model), by a simulated annealing optimization routine that best fit to the experimental scattering data. The protein shape was reconstructed by averaging 20 different ab initio models using the DAMAVER package 42 . The obtained low-resolution model and the crystal structure were superimposed using the SUPCOMB program 43 . The theoretical scattering curve was generated from crystallographic atomic coordinates using the CRYSOL program 44 and compared to the experimental scattering data.

Differential scanning calorimetry

Thermal stability of EaBglA was investigated by differential scanning calorimetry (DSC). EaBglA, at a concentration of 2 mg/mL in 20 mM sodium phosphate, 150 mM NaCl and pH 7.4, was scanned at a rate of 1 °C/min in a VP-DSC device (Microcal, GE Healthcare, Northampton, USA) over the range of 15–90 °C at 0.5 °C increments. The DSC profile was buffer subtracted, concentration normalized and the resultant endotherms integrated following assignment of pre- and post-transition baselines. As the thermal-induced unfolding of EaBglA was irreversible in the tested conditions, the analysis was focused on the values of transition temperatures (Tm).

Protein crystallization

Crystallization experiments were performed by the vapor diffusion method in 96-well plates using a Honeybee 963 automated system (Digilab, Marlborough, MA). EaBglA crystallized at 18 °C in sitting drops containing 0.5 μl of protein solution at 15 mg/mL and 0.5 μL of the crystallization condition. C2221 crystals were grown in a condition containing 0.1 M CAPS (pH 10.5), 0.2 M lithium sulfate and 2 M ammonium sulfate using in situ proteolysis (1:1000 (w/w) ratio of trypsin:EaBglA). P21 crystals were obtained in a medium containing 0.1 M TRIS (pH 8.5), 2% (v/v) PEG400 and 1.45 M lithium sulfate.

Data collection and structure determination

X-ray diffraction data of C2221 and P21 crystals (cryoprotected with 20% (v/v) glycerol) were collected at the MX2 beamline from LNLS (Campinas, Brazil) and at the I03 beamline from the Diamond Light Source (Oxfordshire, UK), equipped with PILATUS 2M and PILATUS3 6M detectors, respectively. Data were indexed, integrated and scaled using the XDS package 45 . The crystal structure was solved by molecular replacement methods using the PHASER program with the atomic coordinates of the β-glucosidase from H. orenii (PDB ID: 4PTV) as a search model. The structures were refined alternating cycles of TLS, twin refinement (P21 crystal) and restrained refinement (including local NCS restraints) using REFMAC5 46 and manual model building using COOT 47 . The two last residues were disordered in all chains from both crystals and were not modeled. The final structures were validated using MOLPROBITY 48 . Data collection and refinement statistics are summarized in Table 3. The structure factors and atomic coordinates of both crystalline forms, P21 and C2221, were deposited in the PDB under the accession codes 5DT5 and 5DT7, respectively.

Structural analyses

Structural superimpositions were performed using the protein structure comparison service PDBeFold (http://www.ebi.ac.uk/msd-srv/ssm) 49 . Intramolecular interactions and protein interfaces were analyzed using the servers PIC (http://pic.mbu.iisc.ernet.in/) 50 and EPPIC (http://www.eppic-web.org/ewui/) 51 , respectively. The volume of protein cavities were calculated using KVFinder 52 and CASTp 53 . Figures were prepared using PYMOL 54 .

Molecular dynamics simulations

Simulation systems using explicit solvation were created for the biological units of EaBglA and HoBglA (PDB ID: 4PTX). A molecular dynamics simulation of 100 nanoseconds was carried out using the YAMBER3 force field with timestep of 5 femtoseconds saving a snapshot every 250 picoseconds using YASARA 55 . Each of the systems were simulated in 10 and 30 °C using the Berendsen thermostat for temperature control. Pressure was monitored using the solvent density as a probe and maintained constant during simulation by isotropically resizing the simulation cell to match adequate values of solvent density, when required.

Molecular dynamics analyses

Root mean square fluctuation as well as hydrogen bonds, salt bridges and solvent accessible area were calculated using custom scripts and the coordinates of the last 80 nanoseconds of the 100 nanoseconds simulations. Hydrogen bonds were identified considering the bond energy of 6.25 kJ/mol as a threshold, given that the bond energy is a function of the hydrogen-acceptor distance. Electrostatic pairs were considered when their atoms (not hydrogen) were closer than 4 Å from each other. The solvent accessible surface was calculated using routines implemented in the YASARA software.

Phylogenetic analysis

The protein sequences of β-glucosidases from psychrotrophic bacteria were used as baits in BLASTp searches against the NCBI non-redundant database. A maximum of four protein hits with a sequence identity ranging from 60 to 95% to each query were selected. For comparison purposes, homolog proteins of HoBglA were also retrieved using the same criteria. All protein sequences were aligned using the MUSCLE 56 software. Positions containing gaps or missing data were partially excluded from the multiple sequence alignment using a site coverage cutoff of 80%. Based on the resulting data subset, an evolutionary tree was inferred using the Maximum Likelihood (ML) method and the best model of amino acid substitution indicated by the MEGA software (version 6.0) 57 , which was the LG matrix assuming that the rate varies among sites according to a Gamma distribution (+G) and allowing for the presence of invariant sites (+I). The confidence of tree topology was assessed using the Bootstrap analysis based on 1,000 bootstrap replications. The taxonomy of bacteria species was retrieved from the Uniprot Knowledgebase 58 . Bacteria were classified based on their optimal growth temperature, when available, or in the minimal temperature they are able to growth as psychrophilic/psychrotrophic (Topt < 20 °C Tmin < 5 °C), mesophilic (20 °C < Topt > 40 °C Tmin > 5 °C) and thermophilic (Topt > 40 °C Tmin > 40 °C) (Table S5).


Cold adaptation in proteins, at sequence & structural level - Biology

Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.09 Å
  • R-Value Free: 0.236 
  • R-Value Work: 0.184 
  • R-Value Observed: 0.184 

wwPDB Validation   3D Report Full Report

Structural adaptations of the cold-active citrate synthase from an Antarctic bacterium.

(1998) Structure 6: 351-361

  • PubMed: 9551556  Search on PubMed
  • DOI: 10.1016/s0969-2126(98)00037-9
  • Primary Citation of Related Structures:  
    1A59
  • PubMed Abstract: 

The structural basis of adaptation of enzymes to low temperature is poorly understood. Dimeric citrate synthase has been used as a model enzyme to study the structural basis of thermostability, the structure of the enzyme from organisms living in habitats at 55 degrees C and 100 degrees C having previously been determined .

The structural basis of adaptation of enzymes to low temperature is poorly understood. Dimeric citrate synthase has been used as a model enzyme to study the structural basis of thermostability, the structure of the enzyme from organisms living in habitats at 55 degrees C and 100 degrees C having previously been determined. Here the study is extended to include a citrate synthase from an Antarctic bacterium, allowing us to explore the structural basis of cold activity and thermostability across the whole temperature range over which life is known to exit.


BIOLOGY COMMON RECALL QUESTIONS

1.Helical/spiral shape so compact
2.Molecule is insoluble so osmotically inactive (does not affect water potential)
3.Branched so glucose is easily accessible by enzymes to break down for respiration
4.Large molecule so cannot leave cell/cross cell-surface
membrane

2. joined by condensation to form glycosidic bond

4. "flipping over" of alternate molecules

5. hydrogen bonds linking long straight chains

6. cellulose makes cell walls strong

7. can resist turgor pressure/osmotic pressure

8. bond difficult to break

2. Joined by peptide bonds

3. That are formed by condensation

4. Primary structure is the order of amino acids

5. Secondary structure is folding of polypeptide chain due to hydrogen bonding

6. Tertiary structure is 3-D folding due to hydrogen bonding and ionic / disulfide
bonds

2. Broken down in a one step reaction which makes sure energy is available rapidly

3. Phosphorylates substances to make them more reactive

NON-REDUCING SUGAR
1. Do Benedict's Test and stays blue/negative
2. Boil with acid then neutralises with alkali
3. Heat with Benedict's and becomes red/orange (precipitate)

2.(Causing) change in amino acid sequence

3.Mutations build up over time

4.More mutations / more differences (in amino acid/ base / nucleotide sequence / primary
structure) between distantly related species
OR
Few(er) mutations / differences (in amino acid / base / nucleotide sequence / primary structure) in
closely related species

SODIUM IONS
1. Co-transport of glucose/amino acids (into cells)
2. (Because) sodium moved out by active transport/sodium potassium pump
3. Creates a sodium ion concentration/diffusion gradient
4. Affects osmosis/water potential

Active site is flexible & can mould around the substrate

2. Active site is only complementary to maltose

3. Description of induced fit

4. Enzyme is a catalyst which lowers the activation energy required for the reaction

(Competitive inhibition),
2. Inhibitor has a similar shape to substrate
3. It binds to the active site (of enzyme)
4. Inhibition can be overcome by adding more substrate

Maintaining low concentration of sodium in the epithelial cell compared to the
lumen

Glucose moves in to the epithelial cell with sodium
Via carrier/channel protein
Glucose moves into blood

2. Endopeptidases break polypeptides into smaller peptide chains

3. Exopeptidases remove terminal amino acids

2. Many mitochondria produce ATP for active transport
3. Carrier proteins present for active transport

4. Channel / carrier proteins for facilitated diffusion

5. Co-transport of sodium and glucose achieved through carrier protein for sodium (ions) and glucose

2. Phospholipid (bilayer) prevents movement/diffusion of polar/lipid-insoluble substances

3. Carrier proteins allow active transport

4. Channel/carrier proteins allow facilitated diffusion/co-transport

5. Shape/Charge of channel/carrier determines which substances move

6. Number of channels/carriers determines how much movement

7. Membrane surface area determines how much diffusion/movement

2. Long / large molecule so can store lots of information

3. Helix / coiled so compact

4. Base sequence allows information to be stored (protein formation)

5. Double stranded so replication can occur semi-conservatively as existing
strands can act as templates via complementary base pairing

2. base pairing held together by hydrogen bonds

3. hydrogen bonds weak so easily broken, which allows strands to separate

4. bases exposed and act as a template
5. A with T, C with G

2. Breaks hydrogen bonds between base pairs, exposing them

3. Only one DNA strand acts as a template

4. RNA nucleotides attracted to exposed bases

5. (Attraction) according to base pairing rule (A-U & C-G)

6. RNA polymerase joins the RNA nucleotides together, to form pre-mRNA

3. tRNA molecules bring amino acids to the ribosome

4. A specific tRNA molecule exists for a specific amino acid

5. Anticodon of tRNA complementary to codon on mRNA

6. Peptide bonds form between adjacent amino acids

7. tRNA detaches and leaves to collect another amino acid

2. Change in amino acid sequence

3. This alters position of hydrogen/ionic/disulfide bonds

2. chromosomes made from two identical chromatids, due to replication in interphase

3. chromosomes move to equator of the cell

4. Chromosomes attach to individual spindle fibres

5. Spindle fibres contract & the centromeres divide

6. Sister chromatids move to opposite poles

7. Each pole receives all the genetic information

2. Chromosomes associate into their homologous pairs

3. Crossing-over occurs between chromosomes, through the formation of a chiasma

4. Chromosomes join to spindle fibres, via there centromeres

6. Homologous chromosomes move to opposite poles

2. Independent assortment (segregation of homologous chromosomes) in meiosis I

3. Independent assortment (segregation of chromatids) in meiosis II

+ Any three from:
4. Causes individuals to have different adaptations making some better adapted

7. These pass on the gene / allele

2. Obtain thin section of plant tissue and place on slide

3. Stain with iodine in potassium iodide.

2. Filter to remove large debris / whole cells

3. Use isotonic solution to prevent damage to mitochondria/organelles

4. Keep cold to reduce damage by enzymes/ use buffer to prevent enzyme denaturation

5. Centrifuge at lower speed to separate nuclei / cell fragments / heavy organelles

2. Small / non-polar / lipid-soluble molecules pass via phospholipids / bilayer
OR
Large / polar / water-soluble molecules go through proteins

3. Water moves by osmosis from high water potential to low water potential

4. Active transport against concentration gradient

5. Active transport/facilitated diffusion involves proteins /carriers

6. Active transport requires energy / ATP

2. Cannot cross lipid bilayer

3. Chloride ions transported by facilitated diffusion using
channel/carrier protein

4. Oxygen not charged/non-polar

2. Many mitochondria produce ATP / release or provide energy for active
transport

3. Carrier proteins for active transport

4. Channel/carrier proteins for facilitated diffusion

5. Co-transport of sodium ions and glucose using a symport / carrier protein

2. Active involves production of antibody by plasma cells / memory cells

3. Passive involves antibody introduced into body from outside

4. Active long term, because antibody produced in response to antigen

5. Passive short term, because antibody given is broken down

2. Pathogen engulfed / ingested

3. Enclosed in vacuole, forming a phagosome

4. Vacuole fuses with lysosome

5. Lysosome contains enzymes that are emptied into the vacuole

Plasma cells make antibodies

2 antigen binds to complementary receptors on B lymphocyte

3 lymphocyte becomes activated

4 (B) lymphocytes reproduce by mitosis

2. Antigen is displayed on antigen-presenting cells (macrophages)

3. Helper T cell with complementary receptor protein binds to antigen

4. Helper T cell stimulates B cell

5. With the complementary antibody on its surface

6. B cell secretes large amounts of antibody

3. On second exposure memory cells produce become active and produce antibodies

4. Rapidly produce antibodies/ produces more antibodies

2. The shape of tertiary structure of the binding site

3. Complementary to the antigens

Enzyme uses HIV RNA to make DNA copy

DNA joined to host cell's DNA/chromosome

DNA used to make HIV RNA copies

And HIV capsid proteins/enzymes

Assembly of new virus particles

2. Ventricle now has higher pressure than atrium (due to filling / contraction).
This causes atrioventricular valves to close

3. Ventricle has higher pressure than aorta causing semilunar valve to open

4. This leads to a higher pressure in the aorta than the ventricle (as heart
relaxes) causing semilunar valve to close

2. Single cell thick walls - reduces diffusion distance

3. Flattened (endothelial) cells - reduces diffusion distance

4. Fenestrations - allows large molecules through

5. Small diameter/ narrow - gives a large surface area to volume / short
diffusion distance

6. Narrow lumen - reduces flow rate giving more time for diffusion

2. Fluid & soluble molecules pass out

3. Proteins & large molecules remain behind

4. This lowers the water potential

5. Water moves back into venous end of capillary
by osmosis

2. floor of mouth is lowered

3. water enters due to a decreased pressure & an
increased volume

4. mouth closes, operculum/opercular valve opens

5. floor raised results in an increased pressure & a decreased volume

gill plates or secondary lamellae

large number of capillaries --> to remove oxygen / to maintain a gradient

thin epithelium --> short diffusion pathway

pressure changes --> to bring in more water / to maintain gradient

2. Walls of alveoli thin to provide a short diffusion pathway

3. Walls of capillary are thin between the alveoli so provides a short diffusion pathway

4. Walls of capillaries/alveoli have flattened cells

5. Cell membrane permeable to gases

6. Many blood capillaries provide a large surface area

7. Intercostal muscles & diaphragm muscles used to ventilate lungs to maintain a diffusion
gradient

8. Wide trachea & branching of bronchi/bronchioles for efficient flow of air


MATERIALS AND METHODS

Sample collection

Pareledone sp., Robson 1932, was collected during January from below the ice in McMurdo station, Antarctica. The specimen collected was kindly provided by Dr Chris DeVries. Octopus bimaculatus, Verrill 1883, was collected by SCUBA diving from Wrigley Marine Lab, Two Harbors, Catalina Island, CA, USA. Octopus defilippi, Vérany 1851, was collected from Rio Grande, Puerto Rico. Octopus digueti, Perrier and Rochebrune 1894, was collected from San Lucas Cove, Santa Rosalia, Baja California Sur, Mexico. Bathypolypus arcticus (Prosch 1847) and Benthoctopus piscatorum (Verrill 1879) were collected off the north coast of the Svalbard archipelago, Norway. From all samples, the stellate ganglia were dissected, preserved in RNA later (Ambion, Austin, TX, USA) and frozen at –80°C.

Molecular cloning

Total RNA was extracted from each stellate ganglion using the RNAqueous-Micro kit (Ambion) and used as a template for cDNA synthesis with the SuperScript III first-strand cDNA synthesis kit (Invitrogen, Carlsbad, CA, USA). Full-length Na + /K + -ATPase α-subunits were amplified by PCR using Taq polymerase (for O. bimaculatus and Pareledone sp.) or Phusion polymerase (O. defilippi, O. digueti, B. arcticus and B. piscatorum) and primers based on the UTRs of a Loligo opalescens Na + /K + -ATPase α-subunit clone [GenBank: EF467998 (Colina et al., 2007)]. To obtain a consensus sequence, multiple cDNA clones were sequenced to completion.

Functional expression in Xenopus oocytes

The coding region of the Na + /K + -ATPase α-subunit for each species was cloned into the Xenopus expression vector pBSTA (Liman et al., 1992) and used as a template for cRNA synthesis with T7 promotor-based kits (mMessage mMachine T7 Ultra, Ambion or mScript mRNA production system, Epicentre, Madison, WI, USA). cRNA was also made for the native β-subunit of the squid giant axon system [GenBank: EF467996 (Colina et al., 2007)]. Oocytes were injected with 80 ng of an equimolar mix of α- and β-subunit cRNAs. Experiments were performed 3–4 days after injection. Oocytes were surgically removed and de-folliculated by an enzymatic treatment with collagenase. Stage V and VI oocytes were selected for injection. After injection, oocytes were maintained for 3–4 days at 18°C in ND-96 solution (in mmol l –1 : 96 NaCl, 2 KCl, 1.8 CaCl2, 1 MgCl2 and 5 Hepes pH 7.6). Immediately prior to recording, oocytes were loaded with Na + for 45 min in a Na + -loading solution (in mmol l –1 : 100 Na-glutamate, 2.5 Na-citrate and 5 Hepes pH 7.5) (Rakowski et al., 1991).

Experimental solutions for electrophysiological measurements

The extracellular solutions employed to evaluate pump function throughout this study were 5 mmol l –1 K + solution (in mmol l –1 : 100 Na-glutamate, 5 K-glutamate, 5 BaCl2, 2 NiCl2, 5 Hepes, 2 MgCl2 and 0.3 niflumic acid) and K + -free solution (same as 5 mmol l –1 K + solution except that 5 mmol l –1 N-methyl d -glucamine was substituted for the 5 mmol l –1 K + ). Ouabain was used at a concentration of 100 μmol l –1 in both the 5 mmol l –1 K + or K + -free solutions. When using the ‘cut-open oocyte Vaseline-gap’ technique (see below), the internal solution contained (mmol l –1 ): 80 Na-glutamate, 20 TEA-glutamate, 10 MgSO4, 10 Hepes, 5 EGTA and 5 MgATP. To gain electrical access to the inside, oocytes were permeabilized with 0.2% (w/v) saponin in the internal solution. The pH of all experimental solutions was adjusted to 7.5 with N-methyl d -glucamine at room temperature and was determined to vary by 0.2 units between 30 and 5°C.

Na + /K + -ATPase expression levels

Expression levels were assessed as the total ouabain-sensitive current recorded from whole oocytes expressing either construct. Oocytes were clamped using a conventional two-microelectrode voltage clamp amplifier (GeneClamp 500B Axon Instruments, Foster City, CA, USA). Analog signals were filtered at 1 kHz and digitized using an Innovative Integrations SBC6711 A/D converter (Simi Valley, CA, USA). GPATCH software was kindly provided by Dr Francisco Bezanilla. Oocytes were held at 0 mV, and pumps were fully activated with the 5 mmol l –1 K + solution, followed by addition of ouabain. Endogenous pump expression was recorded from un-injected oocytes. All experiments to assess expression level were performed at room temperature (∼22°C).

Voltage dependence and turnover rate studies

Voltage dependence and turnover rate experiments were performed using the ‘cut-open oocyte Vaseline-gap’ technique (Taglialatela et al., 1992). Oocytes were clamped with a Dagan CA-1B high-performance oocyte clamp (Dagan Corporation, Minneapolis, MN, USA), sampling exclusively from the animal pole to minimize the signal from endogenous pumps (Holmgren and Rakowski, 1994). In these experiments, oocytes were held at 0 mV and stepped to various potentials ranging from –200 to +50 mV with 10 mV increments. The length of the pulses was either 35 or 60 ms. An Innovative Integrations SBC6711 A/D board with GPATCH software was used to control voltage protocols and digitize analog signals. Records on a slow time base (‘chart records’) were collected using a MiniDigi 1A board and AxoScope 9.0 software (Axon Instruments). Signals were acquired at 100 kHz and filtered at 10 kHz. Intracellular voltage was measured with a 0.2–0.3 MΩ pipette filled with 1 mol l –1 NaCl, and bridges filled with 3 mol l –1 Na-MES (4-morpholineethanesulfonic acid sodium salt) in 3% (w/v) agarose. In all experiments, the stability of the recordings was assessed by time controls, obtained from the difference between current–voltage (IV) relationships obtained under the same experimental conditions at equivalent time intervals. These experiments were performed at ∼22°C.

The voltage dependence of the Na + /K + -ATPase current was evaluated by performing the voltage protocol in 5 mmol l –1 K + solutions before and after the addition of 100 μmol l –1 ouabain. The difference between these recordings yielded the ouabain-sensitive pump current. Steady-state current produced at each voltage was measured and plotted. The potential for half-maximal current (mid-point mean ± s.e.m.) for each Na + /K + -ATPase construct was measured from the IV plot for each experiment and then averaged. The significance of the mid-point values was tested using a two-population t-test with α=0.05.

Temperature sensitivity of the Na + /K + -ATPase turnover rate

The temperature sensitivity of the pumps was studied in whole oocytes using two-microelectrode voltage clamp. Oocytes were held at 0 mV in a chamber where the temperature was controlled using Peltier devices. Pumps were activated with 5 mmol l –1 K + at 30°C. Once fully activated, the temperature was progressively reduced to ∼5°C and then returned to 30°C. This protocol was then repeated in the presence of ouabain to assess leak currents. During current recordings, temperature was recorded simultaneously by placing a thermocouple immediately adjacent to the oocyte. The output of the thermocouple was calibrated and collected at 1 kHz on-line. The temperature-dependent leak was negligible compared with the pump current. For each experiment, the amount of ouabain-sensitive current at each temperature was normalized to the value at 22°C. Normalized values obtained from individual experiments were then averaged for multiple oocytes. Estimates of the amount of endogenous pump current at each temperature were made using the magnitude of the endogenous current in un-injected oocytes at 22°C and the temperature sensitivity of the endogenous current (see supplementary material Fig. S1). The endogenous values were then subtracted from the data for the clone-injected oocytes. These values (means ± s.e.m.) were converted to turnover rates based on turnover rates determined at 22°C. In some cases data were normalized to the current value at 28°C.


Figure S1. ΔB'-values of psychrophilic serine protease (PDB:

Additional file 1: 1ELT) and mesophilic serine protease (PDB:1EAI) at each amino acid position in a pairwise alignment. Graphic of ΔB'-values from paired protein 1ELT and 1EAI. At the top is the secondary structure of the psychrophilic enzyme. One visible rigid region from (amino acids 1-110) and one flexible region (amino acids 111-235) are obtaining using the ΔB'-value methodology. Figure S2. Table of number of positions found at each secondary structure in psychro/mesophilic pair. Table of number of positions found at each secondary structure in the 20 psychro/mesophilic pairs. Figure S3. Graphic of buried, crystallographic waters of each psychro/mesophilic pair. Plot of buried crystallographic waters from the 20 psychro/mesophilic pairs. In cases where multiple chains were present in the crystal structure, the values were averaged. Note: 1a59 contains no reported crystallographic waters. (PDF 1 MB)


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